Methods for detecting a dormant infection

Abstract

Compositions, methods, and kits are provided for diagnosing bacterial infections that distinguish tissue infected with dormant bacteria from uninfected tissue. In particular, the subject methods can be used to detect dormant bacteria, including bacteria in biofilms on joint replacement implants by measuring biomarkers in synovial fluid or blood or analyzing specific immune cell types, including regulatory T-cells, natural killer cells, monocytes, plasmacytoid dendritic cells, or myeloid dendritic cells within a periarticular tissue sample in contact with the effective joint space of an implant.

Description

METHODS FOR DETECTING A DORMANT INFECTIONCROSS REFERENCE TO RELATED PPLICATION

[0001] This application claims benefit of U.S. Provisional Patent Application No. 63 / 677,070, filed July 30, 2024, which application is incorporated herein by reference in its entirety.BACKGROUND OF THE INVENTION

[0002] Detecting dormant bacteria in tissue is challenging because of the formation of bacterial biofilms, which contain sessile bacterial communities encased in a protective extracellular matrix. Biofilms are notoriously difficult to culture, remarkably tolerant to antibiotics, and able to evade phagocytosis. Phagocytized bacteria dramatically alter cytokine production and compromise antigen presentation, which makes them also difficult to detect. There remains a need for better methods of diagnosing bacterial infections that can detect both biofilms and phagocytized bacteria and better distinguish tissue infected with dormant bacteria from uninfected tissue.SUMMARY OF THE INVENTION

[0003] Compositions, methods, and kits are provided for diagnosing bacterial infections that distinguish tissue infected with dormant bacteria from uninfected tissue. In particular, the subject methods can be used to detect dormant bacteria, including bacteria in biofilms on joint replacement implants by measuring biomarkers in synovial fluid or blood or analyzing specific immune cell types, including regulatory T-cells, natural killer cells, monocytes, plasmacytoid dendritic cells, or myeloid dendritic cells within a periarticular tissue sample in contact with the effective joint space of an implant.

[0004] In one aspect, a method of diagnosing and treating a periprosthetic joint infection in a patient is provided, the method comprising: (a) obtaining a synovial fluid sample from the patient; (b) measuring levels of one or more biomarkers selected from C-X-C motif chemokine ligand 5 (CXCL5), platelet derived growth factor subunit B (PDGF-B), galectin-1 (Gal-1 ), C-X-C motif chemokine ligand 11 (CXCL11 ), angiopoietin 1 (ANGPT1 ), epidermal growth factor (EGF), TEK receptor tyrosine kinase (TIE2), monocyte chemoattractant protein 2 (MCP-2), CD244 molecule (CD244), and nitric oxide synthase 3 (NOS3), and one or more biomarkers selected from adenosine deaminase (ADA), C-X-C motif chemokine ligand 1 (CXCL1 ), C-C motif chemokine ligand 20 (CCL20), and tumor necrosis factor superfamily member 14 (TNFSF14) in the synovial fluid sample; (c) diagnosing the patient, wherein increased levels of the one or more biomarkers selected from CXCL5, PDGF-B, CXCL11 , ANGPT1 , EGF, TIE2, MCP-2, CD244, and NOS3, increased levels of the one or morebiomarkers selected from ADA, CXCL1 , CCL20, and TNFSF14, and decreased levels of the Gal-1 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from an uninfected control subject indicate that the patient has the periprosthetic joint infection; and (d) treating the patient diagnosed with the periprosthetic joint infection to eradicate the periprosthetic joint infection. In certain embodiments, treatment comprises removal of the implant, debridement of the joint, placement of an antibiotic spacer, oral or intravenous antibiotic therapy with an antibiotic such as, but not limited to, cefazolin, cefdinir, cefpodoxime, ceftriaxone, cefepime cefuroxime, clindamycin, cotrimoxazole, ciprofloxacin, levofloxacin, delafloxacin, gemifloxacin, moxifloxacin, ofloxacin cefadroxil, cephalexin, ceftriaxone, ceftaroline, doxycycline, amoxicillin- claulanate, penicillin, vancomycin, azithromycin, clarithromycin, linezolid, tedizolid, or rifampin, replacement of the infected implant with a new implant, or any combination thereof.

[0005] In certain embodiments, measuring the levels of the one or more biomarkers comprises measuring the levels of ADA, CXCL1 , CCL20, and TNFSF14 in the synovial fluid sample of the patient, wherein increased levels of the ADA, CXCL1 , CCL20, and TNFSF14 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from a subject with a dormant periprosthetic joint infection indicate that the patient has an active periprosthetic joint infection; and wherein decreased levels of the ADA, CXCL1 , CCL20, and TNFSF14 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from a subject with an active periprosthetic joint infection indicate that the patient has a dormant periprosthetic joint infection.

[0006] In certain embodiments, measuring the levels of the one or more biomarkers comprises measuring the levels of the CXCL5, PDGF-B, Gal-1 , CXCL11 , ANGPT1 , EGF, TIE2, MCP-2 (CCL8), CD244, and NOS3 in the synovial fluid sample of the patient, wherein decreased levels of the CXCL5, PDGF-B, CXCL11 , ANGPT1 , EGF, TIE2, MCP-2 (CCL8), CD244, and NOS3 and increased levels of the Gal-1 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from a subject with a dormant periprosthetic joint infection indicate that the patient does not have a periprosthetic joint infection; and wherein increased levels of the CXCL5, PDGF-B, CXCL1 1 , ANGPT1 , EGF, TIE2, MCP-2 (CCL8), CD244, and NOS3 and decreased levels of the Gal-1 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from the uninfected control subject indicate that the patient has a dormant periprosthetic joint infection.

[0007] In certain embodiments, measuring the levels of the one or more biomarkers comprises performing an enzyme-linked immunosorbent assay (ELISA), a radioimmunoassay (RIA), an immunofluorescent assay (I FA) , immunohistochemistry, fluorescence-activated cell sorting (FACS),a Western Blot, mass spectrometry, tandem mass spectrometry, an aptamer-based assay, an enzymatic or biochemical assay, liquid chromatography, or nuclear magnetic resonance (NMR). In some embodiments, the ELISA is performed using a multiplex ELISA array.

[0008] In certain embodiments, the patient has a joint replacement implant. In some embodiments, the joint replacement implant is in a hip, knee, shoulder, ankle, or other joint. In some embodiments, the joint replacement implant was treated for an infection previously.

[0009] In another aspect, a method of monitoring a patient with a joint implant for development of an active periprosthetic joint infection is provided, the method comprising: (a) obtaining a first synovial fluid sample from the patient at a first time point and a second synovial fluid sample from the patient later at a second time point; (b) measuring levels of one or more biomarkers selected from ADA, CXCL1 , CCL20, and TNFSF14 in the first synovial fluid sample and the second synovial fluid sample; and (c) analyzing the levels of the one or more biomarkers in conjunction with respective reference value ranges for said biomarkers, wherein detection of increased levels of the one or more biomarkers selected from selected from ADA, CXCL1 , CCL20, and TNFSF14 in the second synovial fluid sample compared to the first synovial fluid sample indicate that the patient is developing an active periprosthetic joint infection, and detection of decreased levels of expression of the one or more biomarkers selected from ADA, CXCL1 , CCL20, and TNFSF14 in the second synovial fluid sample compared to the first synovial fluid sample indicate that the patient is not developing an active periprosthetic joint infection. In certain embodiments, the method further comprises treating the patient developing an active periprosthetic joint infection to eradicate the periprosthetic joint infection. In some embodiments, the treatment comprises removal of an infected joint implant, debridement of the joint, placement of an antibiotic spacer, oral or intravenous antibiotic therapy with an antibiotic, replacement of the infected joint implant with a new joint implant, or any combination thereof.

[0010] In another aspect, a kit is provided, the kit comprising agents for detecting C-X-C motif chemokine ligand 5 (CXCL5), platelet derived growth factor subunit B (PDGF-B), galectin-1 (Gal-1 ), C-X-C motif chemokine ligand 11 (CXCL11 ), angiopoietin 1 (ANGPT1 ), epidermal growth factor (EGF), TEK receptor tyrosine kinase, also known as tyrosine kinase with Ig and EGF homology domains-2 (TIE2), C-C motif chemokine ligand 8 (CCL8) also known as monocyte chemoattractant protein 2 (MCP-2), CD244 molecule (CD244), nitric oxide synthase 3 (NOS3), adenosine deaminase (ADA), C-X-C motif chemokine ligand 1 (CXCL1 ), C-C motif chemokine ligand 20 (CCL20), and tumor necrosis factor superfamily member 14 (TNFSF14).

[0011] In certain embodiments, the kit further comprises reagents for performing an immunoassay.

[0012] In certain embodiments, the kit comprises an antibody or aptamer that specifically binds to CXCL5, an antibody or aptamer that specifically binds to PDGF-B, an antibody or aptamer that specifically binds to Gal-1 , an antibody or aptamer that specifically binds to CXCL1 1 , an antibody or aptamer that specifically binds to ANGPT1 , an antibody or aptamer that specifically binds to EGF, an antibody or aptamer that specifically binds to TIE2, an antibody or aptamer that specifically binds to MCP-2 (CCL8), an antibody or aptamer that specifically binds to CD244, an antibody or aptamer that specifically binds to NOS3, an antibody or aptamer that specifically binds to ADA, an antibody or aptamer that specifically binds to CXCL1 , an antibody or aptamer that specifically binds to CCL20, and an antibody or aptamer that specifically binds to TNFSF14.

[0013] In certain embodiments, the kit further comprises instructions for determining whether a patient has an active or dormant periprosthetic joint infection.

[0014] In another aspect, a protein selected from the group consisting of C-X-C motif chemokine ligand 5 (CXCL5), platelet derived growth factor subunit B (PDGF-B), galectin-1 (Gal-1 ), C-X-C motif chemokine ligand 11 (CXCL1 1 ), angiopoietin 1 (ANGPT1 ), epidermal growth factor (EGF), TEK receptor tyrosine kinase, also known as tyrosine kinase with Ig and EGF homology domains-2 (TIE2), C-C motif chemokine ligand 8 (CCL8) also known as monocyte chemoattractant protein 2 (MCP-2), CD244 molecule (CD244), nitric oxide synthase 3 (NOS3), adenosine deaminase (ADA), C-X-C motif chemokine ligand 1 (CXCL1 ), C-C motif chemokine ligand 20 (CCL20), and tumor necrosis factor superfamily member 14 (TNFSF14) for use as a biomarker in diagnosing a periprosthetic joint infection is provided.

[0015] In another aspect, a composition for use in diagnosing a periprosthetic joint infection is provided, the composition comprising one or more biomarkers selected from C-X-C motif chemokine ligand 5 (CXCL5), platelet derived growth factor subunit B (PDGF-B), galectin-1 (Gal-1 ), C-X-C motif chemokine ligand 11 (CXCL11 ), angiopoietin 1 (ANGPT1 ), epidermal growth factor (EGF), TEK receptor tyrosine kinase (TIE2), monocyte chemoattractant protein 2 (MCP-2), CD244 molecule (CD244), and nitric oxide synthase 3 (NOS3), and one or more biomarkers selected from adenosine deaminase (ADA), C-X-C motif chemokine ligand 1 (CXCL1 ), C-C motif chemokine ligand 20 (CCL20), and tumor necrosis factor superfamily member 14 (TNFSF14).

[0016] In another aspect, an in vitro method of diagnosing a periprosthetic joint infection is provided, the method comprising: (a) obtaining a synovial fluid sample from the patient; (b) measuring levels of one or more biomarkers selected from C-X-C motif chemokine ligand 5 (CXCL5), platelet derived growth factor subunit B (PDGF-B), galectin-1 (Gal-1 ), C-X-C motif chemokine ligand 11 (CXCL11 ), angiopoietin 1 (ANGPT1 ), epidermal growth factor (EGF), TEK receptor tyrosine kinase (TIE2), monocyte chemoattractant protein 2 (MCP-2), CD244 molecule (CD244), and nitric oxide synthase3 (N0S3), and one or more biomarkers selected from adenosine deaminase (ADA), C-X-C motif chemokine ligand 1 (CXCL1 ), C-C motif chemokine ligand 20 (CCL20), and tumor necrosis factor superfamily member 14 (TNFSF14) in the synovial fluid sample; and (c) diagnosing the patient, wherein increased levels of the one or more biomarkers selected from CXCL5, PDGF-B, CXCL11 , ANGPT1 , EGF, TIE2, MCP-2, CD244, and NOS3, increased levels of the one or more biomarkers selected from ADA, CXCL1 , CCL20, and TNFSF14, and decreased levels of the Gal-1 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from an uninfected control subject indicate that the patient has the periprosthetic joint infection.

[0017] In another aspect, a method of diagnosing a dormant bacterial infection in a patient is provided, the method comprising: obtaining a tissue sample from the patient; dissociating the tissue sample into a plurality of cells; separating activated M1 macrophages, activated M2 macrophages, and / or myeloid dendritic cells from other cells of the plurality; measuring levels of one or more messenger RNA (mRNA) transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , ITGAM, C1 QB, LIPA, CD9, DUSP1 , SLC7A7, IL3RA, LAMP1 , QPCT, CD52, PIK3IP1 , KCNE3, CD28, TLR8, PCNA, IGLC3, CXCL5, IFITM3, IGKC, C10orf54, SLC25A37, CLEC4E, MMP9, CXCL8, FOSB, CXCL2, DUSP4, CD48, IL1 RN, LAT2, IER3, CXCL3, PRDM1 , CCR7, LY86, ALAS2, IL1 B, CXCL1 , RNASE2, DPP4, IL15RA, CLEC10A, TBX21 , CCL4, TNF, IL12RB1 , LAT, IL1 R2, S100A12, STAT4, CCL20, ITGA4, KIAA0101 , CD72, FAS, IL7R, UBE2C, and CD209 in the activated M1 macrophages, wherein decreased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of VSIG4, FN1 , ITGAM, C1QB, LIPA, CD9, DUSP1 , SLC7A7, IL3RA, LAMP1 , QPCT, CD52, PIK3IP1 , KCNE3, CD28, TLR8, and PCNA, and increased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of IGLC3, CXCL5, IFITM3, IGKC, C10orf54, SLC25A37, CLEC4E, MMP9, CXCL8, FOSB, CXCL2, DUSP4, CD48, IL1 RN, LAT2, IER3, CXCL3, PRDM1 , CCR7, LY86, ALAS2, IL1 B, CXCL1 , RNASE2, DPP4, IL15RA, CLEC10A, TBX21 , CCL4, TNF, IL12RB1 , LAT, IL1 R2, S100A12, STAT4, CCL20, ITGA4, KIAA0101 , CD72, FAS, IL7R, UBE2C, and CD209 in the activated M1 macrophages from the patient compared to reference value ranges for the levels of the one or more mRNA transcripts in M1 macrophages from an uninfected tissue sample indicate that the patient has the dormant bacterial infection; measuring levels of one or more mRNA transcripts of one or more genes selected from the group consisting of C1 QB, LAMP1 , FN1 , TNFSF13, FCGR3A, ITGAE, SLC7A7, CD52, C1 QA, CD9, ITGAM, CTSD, CD14, LIPA, DOCK8, ITGB2, LILRB4, IRF8, IER3, IFITM3, FYN, JUN, SLC25A37, LAT2, FOSB, C10orf54, SELL, LY86, IFITM2, ADA, CXCL5, VPS28, VEGFA, CXCL2, THBD, and CXCL8 in the activated M2 macrophages, wherein decreased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of01 QB, LAMP1 , FN1 , TNFSF13, FCGR3A, ITGAE, SLC7A7, CD52, C1 QA, CD9, ITGAM, CTSD, CD14, LIPA, D0CK8, ITGB2, LILRB4, and IRF8, and increased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of IER3, IFITM3, FYN, JUN, SLC25A37, LAT2, FOSB, C10orf54, SELL, LY86, IFITM2, ADA, CXCL5, VPS28, VEGFA, CXCL2, THBD, and CXCL8 in the activated M2 macrophages from the patient compared to reference value ranges for the levels of the one or more mRNA transcripts in M2 macrophages from an uninfected tissue sample indicate that the patient has the dormant bacterial infection; and / or measuring levels of one or more mRNA transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , C1 QB, 01 QA, CD9, ITGAM, CST7, IFITM2, IFITM3, FCN1 , and THBS1 in the activated myeloid dendritic cells, wherein decreased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of VSIG4, FN1 , C1QB, C1QA, CD9, and ITGAM, and increased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of CST7, IFITM2, IFITM3, FCN1 , and THBS1 in the myeloid dendritic cells from the patient compared to reference value ranges for the levels of the one or more mRNA transcripts in myeloid dendritic cells from an uninfected tissue sample indicate that the patient has the dormant bacterial infection. In certain embodiments, the method further comprises treating the patient diagnosed with the dormant bacterial infection to eradicate the dormant bacterial infection. In some embodiments, the treatment comprises removal of an infected joint implant, debridement of the joint, placement of an antibiotic spacer, oral or intravenous antibiotic therapy with an antibiotic, replacement of the infected joint implant with a new joint implant, or any combination thereof.

[0018] In another aspect, a composition for use in diagnosing a dormant bacterial infection is provided, the composition comprising one or more messenger RNA (mRNA) transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , ITGAM, 01 QB, LIPA, CD9, DUSP1 , SLC7A7, IL3RA, LAMP1 , QPCT, CD52, PIK3IP1 , KCNE3, CD28, TLR8, PCNA, IGLC3, CXCL5, IFITM3, IGKC, C10orf54, SLC25A37, CLEC4E, MMP9, CXCL8, FOSB, CXCL2, DUSP4, CD48, IL1 RN, LAT2, IER3, CXCL3, PRDM1 , CCR7, LY86, ALAS2, IL1 B, CXCL1 , RNASE2, DPP4, IL15RA, CLEC1 OA, TBX21 , CCL4, TNF, IL12RB1 , LAT, IL1 R2, S100A12, STAT4, CCL20, ITGA4, KIAA0101 , CD72, FAS, IL7R, UBE2C, and CD209 in activated M1 macrophages; one or more mRNA transcripts of one or more genes selected from the group consisting of C1QB, LAMP1 , FN1 , TNFSF13, FCGR3A, ITGAE, SLC7A7, CD52, C1 QA, CD9, ITGAM, CTSD, CD14, LIPA, DOCK8, ITGB2, LILRB4, IRF8, IER3, IFITM3, FYN, JUN, SLC25A37, LAT2, FOSB, C10orf54, SELL, LY86, IFITM2, ADA, CXCL5, VPS28, VEGFA, CXCL2, THBD, and CXCL8 in activated M2 macrophages, and one or more mRNA transcripts of one or more genes selected from the group consisting of VSIG4, FN1 ,C1 QB, C1 QA, CD9, ITGAM, CST7, IFITM2, IFITM3, FCN1 , and THBS1 in the activated myeloid dendritic cells.

[0019] In another aspect, a method of diagnosing a dormant bacterial infection in a patient is provided, the method comprising: obtaining a tissue sample from the patient; measuring levels of one or more mRNA transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , C1 QB, IL3RA, ITGAM, DUSP1 , PIK3AP1 , SLC7A7, CD9, TNFSF13, LAMP1 , QPCT, TLR8, LIPA, CD163, CD52, ITGAE, PCNA, APOE, FCGR3A, PIK3IP1 , KCNE3, IRF8, TREM1 , DOCK8, CTSD, CD22, CD28, CHI3L1 , MITF, IFITM3, RNASE2, CD2, CST7, CXCL5, CD6, CCR7, SLC25A37, IGKC, CXCL1 , LAT2, CD48, DUSP4, S100A12, FYN, FCN1 , CXCR3, CXCL8, GNLY, CD7, FOSB, DUSP2, IL32, ITGA4, IL1 R2, CTSW, BIRC3, MMP9, TRAC, CLEC4E, IL1 B, IRF4, LAT, SELL, APOBEC3G, FAS, IER3, CCL5, IL15RA, CCL20, PRDM1 , CLEC10A, CCND2, TBX21 , PDCD1 , CD72, DPP4, THBS1 , IL6, IL1 RN, GIMAP5, STAT4, IL12RB1 , LEF1 , TNF, IL7R, LIF, ADGRE1 , F5, FCER1 A, CD34, and CD244 in the tissue sample; and diagnosing the patient wherein decreased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of VSIG4, FN1 , C1QB, IL3RA, ITGAM, DUSP1 , PIK3AP1 , SLC7A7, CD9, TNFSF13, LAMP1 , QPCT, TLR8, LIPA, CD163, CD52, ITGAE, PCNA, APOE, FCGR3A, PIK3IP1 , KCNE3, IRF8, TREM1 , DOCK8, CTSD, CD22, CD28, CHI3L1 , and MITF, and increased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of IFITM3, RNASE2, CD2, CST7, CXCL5, CD6, CCR7, SLC25A37, IGKC, CXCL1 , LAT2, CD48, DUSP4, S100A12, FYN, FCN1 , CXCR3, CXCL8, GNLY, CD7, FOSB, DUSP2, IL32, ITGA4, IL1 R2, CTSW, BIRC3, MMP9, TRAC, CLEC4E, IL1 B, IRF4, LAT, SELL, APOBEC3G, FAS, IER3, CCL5, IL15RA, CCL20, PRDM1 , CLEC10A, CCND2, TBX21 , PDCD1 , CD72, DPP4, THBS1 , IL6, IL1 RN, GIMAP5, STAT4, IL12RB1 , LEF1 , TNF, IL7R, LIF, ADGRE1 , F5, FCER1A, CD34, and CD244 in the tissue sample from the patient compared to reference value ranges for the levels of the one or more mRNA transcripts in an uninfected tissue sample indicate that the patient has the dormant bacterial infection. In certain embodiments, the one or more genes comprise CXCL1 , TNF, JUN, IRF8, CD22, QPCT, PIK3AP1 , VSIG4, CXCL2, HLA.DQB1 , TNFSF13, C1 QB, PCNA, and LAMP1. In certain embodiments, the method further comprises treating the patient diagnosed with the dormant bacterial infection to eradicate the dormant bacterial infection. In some embodiments, the treatment comprises removal of an infected joint implant, debridement of the joint, placement of an antibiotic spacer, oral or intravenous antibiotic therapy with an antibiotic, replacement of the infected joint implant with a new joint implant, or any combination thereof.

[0020] In another aspect, a composition for use in diagnosing a dormant bacterial infection is provided, the composition comprising one or more messenger RNA (mRNA) transcripts of one ormore genes selected from VSIG4, FN1 , C1 QB, IL3RA, ITGAM, DUSP1 , PIK3AP1 , SLC7A7, CD9, TNFSF13, LAMP1 , QPCT, TLR8, LIPA, CD163, CD52, ITGAE, PCNA, APOE, FCGR3A, PIK3IP1 , KCNE3, IRF8, TREM1 , DOCK8, CTSD, CD22, CD28, CHI3L1 , MITF, IFITM3, RNASE2, CD2, CST7, CXCL5, CD6, CCR7, SLC25A37, IGKC, CXCL1 , LAT2, CD48, DUSP4, S100A12, FYN, FCN1 , CXCR3, CXCL8, GNLY, CD7, FOSB, DUSP2, IL32, ITGA4, IL1 R2, CTSW, BIRC3, MMP9, TRAC, CLEC4E, IL1 B, IRF4, LAT, SELL, APOBEC3G, FAS, IER3, CCL5, IL15RA, CCL20, PRDM1 , CLEC1 OA, CCND2, TBX21 , PDCD1 , CD72, DPP4, THBS1 , IL6, IL1 RN, GIMAP5, STAT4, IL12RB1 , LEF1 , TNF, IL7R, LIF, ADGRE1 , F5, FCER1 A, CD34, and CD244.

[0021] In another aspect, a method of diagnosing a dormant bacterial infection in a patient is provided, the method comprising: obtaining a blood or plasma sample from the patient; measuring levels of one or more biomarker proteins selected from the group consisting of CD70, C-X-C motif chemokine ligand 5 (CXCL5), epidermal growth factor (EGF), granzyme H (GZMH), fibroblast growth factor 2 (FGF2), CD28, lysosomal associated membrane protein 3 (LAMP3), pleiotrophin (PTN), and matrix metallopeptidase 12 (MMP12) in the blood or plasma sample; and diagnosing the patient, wherein decreased levels of one or more biomarker proteins selected from the group consisting of CD70, CXCL5, EGF, GZMH, FGF2, CD28, and LAMP3, and increased levels of the one or more biomarker proteins selected from the group consisting of PTN and MMP12 in the blood or plasma sample from the patient compared to reference value ranges for the levels of the one or more biomarker proteins in a blood or plasma sample from an uninfected subject indicate that the patient has the dormant bacterial infection. In certain embodiments, the method further comprises treating the patient diagnosed with the dormant bacterial infection to eradicate the dormant bacterial infection. In some embodiments, the treatment comprises removal of an infected joint implant, debridement of the joint, placement of an antibiotic spacer, oral or intravenous antibiotic therapy with an antibiotic, replacement of the infected joint implant with a new joint implant, or any combination thereof.

[0022] In another aspect, a composition for use in diagnosing a dormant bacterial infection is provided, the composition comprising one or more biomarker proteins selected from CD70, C-X-C motif chemokine ligand 5 (CXCL5), epidermal growth factor (EGF), granzyme H (GZMH), fibroblast growth factor 2 (FGF2), CD28, lysosomal associated membrane protein 3 (LAMP3), pleiotrophin (PTN), and matrix metallopeptidase 12 (MMP12).

[0023] In another aspect, a method of diagnosing a dormant bacterial infection in a patient is provided, the method comprising: obtaining a tissue sample from the patient; counting one or more target immune cells selected from regulatory T cells, natural killer cells, plasmacytoid dendritic cells, classical monocytes, and myeloid dendritic cells in the tissue sample; and diagnosing the patient wherein increased numbers of the one or more target immune cells in the tissue sample from thepatient compared to reference value ranges for the target immune cells in an uninfected tissue sample indicate that the patient has the dormant bacterial infection. In certain embodiments, the method further comprises treating the patient diagnosed with the dormant bacterial infection to eradicate the dormant bacterial infection. In some embodiments, the treatment comprises removal of an infected joint implant, debridement of the joint, placement of an antibiotic spacer, oral or intravenous antibiotic therapy with an antibiotic, replacement of the infected joint implant with a new joint implant, or any combination thereof.

[0024] In certain embodiments, the presence of more than one regulatory T cell, more than one natural killer cell, more than one plasmacytoid dendritic cell, three classical monocytes, or more than eighteen myeloid dendritic cells in the tissue sample from the patient in combination with increased numbers of the one or more target immune cells in the tissue sample from the patient compared to reference value ranges for the target immune cells in an uninfected tissue sample indicate that the patient has the dormant bacterial infection.

[0025] In certain embodiments, the tissue sample is a periarticular tissue sample.

[0026] In certain embodiments, the tissue sample is in contact with joint space containing an implant. In some embodiments, the joint space is a suprapatellar pouch in a knee or a superior capsule in a hip.

[0027] In certain embodiments, the tissue sample is from a nidus of the infection.

[0028] In certain embodiments, the patient is treated for the dormant bacterial infection if the patient is determined to have the dormant bacterial infection based on any of the methods described herein.BRIEF DESCRIPTION OF THE DRAWINGS

[0029] FIGS. 1 A-1 B. Dormant Infection State is a Novel Paradigm of Infection Diagnostics. FIG. 1 A) Current diagnostic tests2635for infected joint replacement use the local and systemic neutrophil response to dived patients into uninfected and infection groups, but recently FIG. 1 B) the mononuclear phagocyte system has been used to find joint replacement with a dormant infection that were previously characterized as uninfected using current diagnostic tests.12’2635We hypothesize that joint replacements with a prior infection have a high prevalence of dormant infections that can be distinguished from uninfected joint replacements by the inflammatory response within synovial fluid and / or circulating plasma and that detecting a dormant infection increases the risk of recurrence.

[0030] FIGS. 2A-2B. Clinical Treatment Pathway as Determined by the Current Diagnostic Criteria. FIG. 2A) Synovial protein and blood samples were drawn in Musculoskeletal Infection Society (MSIS) infected cases (septic, n=9), cases of instability, loosening, wear, fracture (MSIS-cleared, aseptic, n=12), and Musculoskeletal Infection Society (MSIS)-cleared previously septic cases for proteomicanalysis of blood and synovial fluid then followed for a minimum 3 years to evaluate the rate of infection relapse after unsupervised clustering of the immune-oncology proteomic analytes. FIG. 2B) Comparison of MSIS diagnostic criteria and biomarkers for assessing infection status.

[0031] FIGS. 3A-3C. Synovial Inflammatory Protein Expression Differs by Infected State. Synovial protein expression as detected by proximity extension assay from joint replacements with an (FIG. 3A) active infection or (FIG. 3B) a prior infection in relationship to no infection as well as in relationship to each other (FIG. 3C).

[0032] FIGS. 4A-4B. Prior Infections Display Heterogeneity and CXCL5 Expression is a Hallmark of Dormant and Active Infection. FIG. 4A) Hieratical clustering synovial samples from joint replacements (left, y-axis) with an active infection (red), a prior infection (green), or no infection (blue) by synovial protein expression as detected by proximity extension assay and represented as a clustered heatmap (top, x-axis). FIG. 4B) Principal component analysis showing a lack of distinction between active infection (red), a prior infection (green), and no infection (blue) with CXCL5 expression driving the resolution of active infection seen by Euclidean distance-based clustering.

[0033] FIGS. 5A-5C. Candidate Biomarkers that Distinguish Dormant Infections from Uninfected Joint Replacements. FIG. 5A) Synovial inflammatory protein expression as detected by proximity extension assay from joint replacements with a dormant infection in relationship to joint replacements with no infection demonstrating the expression of 15 candidate biomarkers for dormant infection in the synovial fluid of joint replacement patients. FIG. 5B) Accuracy as measured by area under the curve (AUG) for all candidate biomarkers with a better accuracy than CXCL5, as identified by Euclidean distance-based clustering, for identifying a dormant infection. Embedded box and whisker plots showing the expression of each candidate biomarkers in normalized protein expression (NPX, logs) for patients with a dormant infection (green) and without an infection (blue). FIG. 5C) Importance of each candidate biomarker for dormant infection in percentage increase in mean squared error (%lncMSE).

[0034] FIGS. 6A-6C. Candidate Biomarkers that Distinguish Dormant Infections from Infected Joint Replacements. FIG. 6A) Synovial inflammatory protein expression as detected by proximity extension assay from joint replacements with a dormant infection in relationship to joint replacements with an infection demonstrating the expression of 4 candidate biomarkers for dormant infection in the synovial fluid of joint replacement patients. FIG. 6B) Accuracy as measured by area under the curve (AUC) for all candidate biomarkers. Embedded box and whisker plots showing the expression of each candidate biomarkers in normalized protein expression (NPX, Iog2) for patients with a dormant infection (green) and an infection (red). FIG. 6C) Importance of each candidate biomarker for detecting dormant infection in percentage increase in mean squared error (%lncMSE).

[0035] FIG. 7. Dormant Infections Display Signs of Peripheral Tolerance. Heatmap of gene set variation analysis (GSVA) using gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways comparing dormant infection to joint replacements without an infection based on log fold change (LogFC) as well as false discovery rate (FDR) suggesting the emergence of a distinct immune signature during a dormant infection that may involve local immune tolerance.DETAILED DESCRIPTION OF THE INVENTION

[0036] Compositions, methods, and kits are provided for diagnosing bacterial infections that distinguish tissue infected with dormant bacteria from uninfected tissue. In particular, the subject methods can be used to detect dormant bacteria, including bacteria in biofilms on joint replacement implants by measuring biomarkers in synovial fluid or blood or analyzing specific immune cell types, including regulatory T-cells, natural killer cells, monocytes, plasmacytoid dendritic cells, or myeloid dendritic cells within a periarticular tissue sample in contact with the effective joint space of an implant.

[0037] Before the present compositions, methods, and kits are described, it is to be understood that this invention is not limited to particular methods or compositions described, as such may, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the present invention will be limited only by the appended claims.

[0038] Where a range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit unless the context clearly dictates otherwise, between the upper and lower limits of that range is also specifically disclosed. Each smaller range between any stated value or intervening value in a stated range and any other stated or intervening value in that stated range is encompassed within the invention. The upper and lower limits of these smaller ranges may independently be included or excluded in the range, and each range where either, neither or both limits are included in the smaller ranges is also encompassed within the invention, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the invention.

[0039] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, some potential and preferred methods and materials are now described. All publications mentioned herein are incorporated herein by reference to disclose and describe the methods and / or materials in connection with which the publications arecited. It is understood that the present disclosure supersedes any disclosure of an incorporated publication to the extent there is a contradiction.

[0040] As will be apparent to those of skill in the art upon reading this disclosure, each of the individual embodiments described and illustrated herein has discrete components and features which may be readily separated from or combined with the features of any of the other several embodiments without departing from the scope or spirit of the present invention. Any recited method can be carried out in the order of events recited or in any other order which is logically possible.

[0041] It must be noted that as used herein and in the appended claims, the singular forms "a", "an", and "the" include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to "a biomarker" includes a plurality of such biomarkers and reference to "the polypeptide" includes reference to one or more polypeptides and equivalents thereof, e.g. peptides or proteins known to those skilled in the art, and so forth.

[0042] The publications discussed herein are provided solely for their disclosure prior to the filing date of the present application. Nothing herein is to be construed as an admission that the present invention is not entitled to antedate such publication by virtue of prior invention. Further, the dates of publication provided may be different from the actual publication dates which may need to be independently confirmed.Definitions

[0043] Biomarkers. The term “biomarker” as used herein refers to a cell, which is present in different numbers, or a compound, such as a protein, a mRNA, a metabolite, or a metabolic byproduct which is differentially expressed or present at different concentrations, levels, or frequencies in one sample compared to another, such as a blood, synovial fluid, or tissue sample from patients who have a dormant bacterial infection compared to an uninfected blood, synovial fluid, or tissue sample from healthy control subjects (i.e., subjects not having an active or dormant bacterial infection or infectious condition). Biomarkers include, but are not limited to, a protein selected from the group consisting of C-X-C motif chemokine ligand 5 (CXCL5), platelet derived growth factor subunit B (PDGF-B), galectin-1 (Gal-1 ), C-X-C motif chemokine ligand 1 1 (CXCL11 ), angiopoietin 1 (ANGPT1 ), epidermal growth factor (EGF), TEK receptor tyrosine kinase, also known as tyrosine kinase with Ig and EGF homology domains-2 (TIE2), C-C motif chemokine ligand 8 (CCL8) also known as monocyte chemoattractant protein 2 (MCP-2), CD244 molecule (CD244), nitric oxide synthase 3 (NOS3), adenosine deaminase (ADA), C-X-C motif chemokine ligand 1 (CXCL1 ), C-C motif chemokine ligand 20 (CCL20), and tumor necrosis factor superfamily member 14 (TNFSF14) in a synovial fluid sample; a mRNA transcript of a gene selected from the group consisting of VSIG4, FN1 , ITGAM, C1 QB,LIPA, CD9, DUSP1 , SLC7A7, IL3RA, LAMP1 , QPCT, CD52, PIK3IP1 , KCNE3, CD28, TLR8, PCNA, IGLC3, CXCL5, IFITM3, IGKC, C10orf54, SLC25A37, CLEC4E, MMP9, CXCL8, FOSB, CXCL2, DUSP4, CD48, IL1 RN, LAT2, IER3, CXCL3, PRDM1 , CCR7, LY86, ALAS2, IL1 B, CXCL1 , RNASE2, DPP4, IL15RA, CLEC10A, TBX21 , CCL4, TNF, IL12RB1 , LAT, IL1 R2, S100A12, STAT4, CCL20, ITGA4, KIAA0101 , CD72, FAS, IL7R, UBE2C, and CD209 in an activated M1 macrophage; a mRNA transcript of a gene selected from the group consisting of C1QB, LAMP1 , FN1 , TNFSF13, FCGR3A, ITGAE, SLC7A7, CD52, C1 QA, CD9, ITGAM, CTSD, CD14, LIPA, DOCK8, ITGB2, LILRB4, IRF8, IER3, IFITM3, FYN, JUN, SLC25A37, LAT2, FOSB, C10orf54, SELL, LY86, IFITM2, ADA, CXCL5, VPS28, VEGFA, CXCL2, THBD, and CXCL8 in an activated M2 macrophage; a mRNA transcript of a gene selected from the group consisting of VSIG4, FN1 , C1 QB, C1 QA, CD9, ITGAM, CST7, IFITM2, IFITM3, FCN1 , and THBS1 in an activated myeloid dendritic cell; a mRNA transcript of a gene selected from the group consisting of VSIG4, FN1 , 01 QB, IL3RA, ITGAM, DUSP1 , PIK3AP1 , SLC7A7, CD9, TNFSF13, LAMP1 , QPCT, TLR8, LIPA, CD163, CD52, ITGAE, PCNA, APOE, FCGR3A, PIK3IP1 , KCNE3, IRF8, TREM1 , DOCK8, CTSD, CD22, CD28, CHI3L1 , MITF, IFITM3, RNASE2, CD2, CST7, CXCL5, CD6, CCR7, SLC25A37, IGKC, CXCL1 , LAT2, CD48, DUSP4, S100A12, FYN, FCN1 , CXCR3, CXCL8, GNLY, CD7, FOSB, DUSP2, IL32, ITGA4, IL1 R2, CTSW, BIRC3, MMP9, TRAC, CLEC4E, IL1 B, IRF4, LAT, SELL, APOBEC3G, FAS, IER3, CCL5, IL15RA, CCL20, PRDM1 , CLEC1 OA, CCND2, TBX21 , PDCD1 , CD72, DPP4, THBS1 , IL6, IL1 RN, GIMAP5, STAT4, IL12RB1 , LEF1 , TNF, IL7R, LIF, ADGRE1 , F5, FCER1A, CD34, and CD244 in bulk RNA of a tissue sample; a protein selected from the group consisting of CD70, C-X-C motif chemokine ligand 5 (CXCL5), epidermal growth factor (EGF), granzyme H (GZMH), fibroblast growth factor 2 (FGF2), CD28, lysosomal associated membrane protein 3 (LAMP3), pleiotrophin (PTN), and matrix metallopeptidase 12 (MMP12) in a blood or plasma sample; and immune cells such as T cells, natural killer cells, dendritic cells, monocytes, or dendritic cells in tissue (e.g., periarticular tissue or tissue in contact with a joint space containing an implant).

[0044] A "reference level" or "reference value" of a biomarker means a level of the biomarker that is indicative of a particular disease state, phenotype, or predisposition to developing a particular disease state or phenotype, or lack thereof, as well as combinations of disease states, phenotypes, or predisposition to developing a particular disease state or phenotype, or lack thereof. A "positive" reference level of a biomarker means a level that is indicative of a particular disease state or phenotype. A "negative" reference level of a biomarker means a level that is indicative of a lack of a particular disease state or phenotype. A "reference level" of a biomarker may be an absolute or relative amount or concentration of the biomarker, a presence or absence of the biomarker, a range of amount or concentration of the biomarker, a minimum and / or maximum amount or concentrationof the biomarker, a mean amount or concentration of the biomarker, and / or a median amount or concentration of the biomarker; and, in addition, "reference levels" of combinations of biomarkers may also be ratios of absolute or relative amounts or concentrations of two or more biomarkers with respect to each other. Appropriate positive and negative reference levels of biomarkers for a particular disease state, phenotype, or lack thereof may be determined by measuring levels of desired biomarkers in one or more appropriate subjects, and such reference levels may be tailored to specific populations of subjects (e.g., a reference level may be age-matched or gender-matched so that comparisons may be made between biomarker levels in samples from subjects of a certain age or gender and reference levels for a particular disease state, phenotype, or lack thereof in a certain age or gender group). Such reference levels may also be tailored to specific techniques that are used to measure levels of biomarkers in biological samples (e.g., flow cytometry, microscopy, immunoassays (e.g., ELISA, immunohistochemistry, immunofluorescence), mass spectrometry (e.g., LC-MS, GC-MS), tandem mass spectrometry, NMR, biochemical or enzymatic assays, PCR, microarray analysis, etc.), where the levels of biomarkers may differ based on the specific technique that is used.

[0045] A "similarity value" is a number that represents the degree of similarity between two things being compared. For example, a similarity value may be a number that indicates the overall similarity between a patient's biomarker profile using specific phenotype-related biomarkers and reference value ranges for the biomarkers in one or more control samples or a reference profile (e.g., similarity to "tissue with a dormant bacterial infection" biomarker expression profile, "tissue with an active bacterial infection" biomarker expression profile, or "non-infected tissue" biomarker expression profile). The similarity value may be expressed as a similarity metric, such as a correlation coefficient, or may simply be expressed as a difference in numbers of immune cells or expression levels, or the aggregate of the expression level differences, between levels of biomarkers in a patient sample and a control sample or reference expression profile.

[0046] The terms "quantity", "amount", and "level" are used interchangeably herein and may refer to an absolute quantification of the number of cells or molecules or analytes in a sample, or to a relative quantification of the number of cells, molecules, or analytes in a sample, i.e., relative to another value such as relative to a reference value as taught herein, or to a range of values for the biomarker. These values or ranges can be obtained from a single patient or from a group of patients.

[0047] The term “biological sample” encompasses samples of fluid, tissue, or cells isolated from a subject, including but not limited to, blood, plasma, serum, synovial fluid, fecal matter, urine, bone marrow, bile, cerebral spinal fluid, lymph fluid, fine needle aspirate, cystic aspirate, a paracentesis sample, a thoracentesis sample, samples of the skin, external secretions of the skin, respiratory,intestinal, and genitourinary tracts, tears, saliva, milk, blood cells, immune cells (e.g., T-cells, natural killer cells, dendritic cells, monocytes, or macrophages), organs, tissue obtained by surgical resection or biopsy, and also samples of in vitro cell culture constituents, including but not limited to, cells in culture, cell lysates, conditioned media resulting from the growth of cells and tissues in culture medium, recombinant cells, and cell components. The definition also includes samples that have been manipulated in any way after their procurement, such as by treatment with reagents, washed, or enriched for particular types of molecules (e.g., biomarker proteins, peptides, RNA transcripts) or cells (e.g., immune cells such as T-cells, natural killer cells, dendritic cells, monocytes, or macrophages), etc.

[0048] Obtaining and assaying a sample. The term “assaying” is used herein to include the physical steps of manipulating a biological sample to generate data related to the biological sample. As will be readily understood by one of ordinary skill in the art, a biological sample must be “obtained” prior to assaying the sample. Thus, the term “assaying” implies that the sample has been obtained. The terms “obtained” or “obtaining” as used herein encompass the act of receiving an extracted or isolated biological sample. For example, a testing facility can “obtain” a biological sample in the mail (or via delivery, etc.) prior to assaying the sample. In some such cases, the biological sample was “extracted” or “isolated” from an individual by another party prior to mailing (i.e., delivery, transfer, etc.), and then “obtained” by the testing facility upon arrival of the sample. Thus, a testing facility can obtain the sample and then assay the sample, thereby producing data related to the sample.

[0049] The terms “obtained” or “obtaining” as used herein can also include the physical extraction or isolation of a biological sample from a subject. Accordingly, a biological sample can be isolated from a subject (and thus “obtained”) by the same person or same entity that subsequently assays the sample. When a biological sample is “extracted” or “isolated” from a first party or entity and then transferred (e.g., delivered, mailed, etc.) to a second party, the sample was “obtained” by the first party (and also “isolated” by the first party), and then subsequently “obtained” (but not “isolated”) by the second party. Accordingly, in some embodiments, the step of obtaining does not comprise the step of isolating a biological sample.

[0050] In some embodiments, the step of obtaining comprises the step of isolating a biological sample (e.g., a pre-treatment biological sample, a post-treatment biological sample, etc.). Methods and protocols for isolating various biological samples will be known to one of ordinary skill in the art and any convenient method may be used to isolate a biological sample.

[0051] It will be understood by one of ordinary skill in the art that in some cases, it is convenient to wait until multiple samples have been obtained prior to assaying the samples. Accordingly, in somecases an isolated biological sample is stored until all appropriate samples have been obtained. One of ordinary skill in the art will understand how to appropriately store a variety of different types of biological samples and any convenient method of storage may be used (e.g., refrigeration) that is appropriate for the particular biological sample. In some embodiments, a pre-treatment biological sample is assayed prior to obtaining a post-treatment biological sample. In some cases, a pretreatment biological sample and a post-treatment biological sample are assayed in parallel. In some cases, multiple different post-treatment biological samples and / or a pre-treatment biological sample are assayed in parallel. In some cases, biological samples are processed immediately or as soon as possible after they are obtained.

[0052] In some embodiments, the concentration (i.e., “level”), or expression level of a gene product, which may be a protein, peptide, etc., (which will be referenced herein as a biomarker), in a biological sample is measured (i.e., “determined”). By “expression level” (or “level”) it is meant the level of a gene product (e.g., the absolute and / or normalized value determined for the RNA expression level of a biomarker or for the expression level of the encoded polypeptide, or the concentration of the protein in a biological sample). The term “gene product” or “expression product” are used herein to refer to the RNA transcription products (RNA transcripts, e.g., mRNA, an unspliced RNA, a splice variant mRNA, and / or a fragmented RNA) of the gene, including mRNA, and the polypeptide translation products of such RNA transcripts. A gene product can be, for example, an unspliced RNA, an mRNA, a splice variant mRNA, a microRNA, a fragmented RNA, a polypeptide, a post- translationally modified polypeptide, a splice variant polypeptide, etc.

[0053] The terms “determining”, “measuring”, “evaluating”, “assessing,” “assaying,” and “analyzing” are used interchangeably herein to refer to any form of measurement, and include determining if an element is present or not. These terms include both quantitative and / or qualitative determinations. Assaying may be relative or absolute. For example, “assaying” can be determining whether the expression level is less than or “greater than or equal to” a particular threshold, (the threshold can be pre-determined or can be determined by assaying a control sample). On the other hand, “assaying to determine the expression level” can mean determining a quantitative value (using any convenient metric) that represents the level of expression (i.e., expression level, e.g., the amount of protein and / or RNA, e.g., mRNA) of a particular biomarker. The level of expression can be expressed in arbitrary units associated with a particular assay (e.g., fluorescence units, e.g., mean fluorescence intensity (MFI)), or can be expressed as an absolute value with defined units (e.g., number of mRNA transcripts, number of protein molecules, concentration of protein, etc.). Additionally, the level of expression of a biomarker can be compared to the expression level of one or more additional genes (e.g., nucleic acids and / or their encoded proteins) to derive a normalized value that represents anormalized expression level. The specific metric (or units) chosen is not crucial as long as the same units are used (or conversion to the same units is performed) when evaluating multiple biological samples from the same individual (e.g., biological samples taken at different points in time from the same individual). This is because the units cancel when calculating a fold-change (i.e., determining a ratio) in the expression level from one biological sample to the next (e.g., biological samples taken at different points in time from the same individual).

[0054] For measuring RNA levels, the amount or level of an RNA in the sample is determined, e.g., the level of an mRNA. In some instances, the expression level of one or more additional RNAs may also be measured, and the level of biomarker expression compared to the level of the one or more additional RNAs to provide a normalized value for the biomarker expression level. Any convenient protocol for evaluating RNA levels may be employed wherein the level of one or more RNAs in the assayed sample is determined.

[0055] A number of exemplary methods for measuring RNA (e.g., nascent RNA or mRNA) levels in a sample are known by one of ordinary skill in the art, and any convenient method can be used. Exemplary methods include, but are not limited to: GRO-seq to measure levels of nascent RNA transcripts (see, e.g., Gardini et al. (2017) Methods Mol. Biol. 1468:1 11 -120, Tzerpos et al. (2021 ) Methods Mol. Biol. 2351 :25-39.Jordan-Pla et al. (2019) Methods 159-160:177-182, Cardiello et al. (2020) Transcription 1 1 (1 ):3-18; herein incorporated by reference in their entireties), RNA-seq to measure levels of RNA transcripts (see, e.g., Hrdlickova et al. (2017) Wiley Interdiscip Rev RNA 8(1 ):10.1002 / wrna.1364, Wang et al. (2009) Nat. Rev. Genet. 10(1 ):57-63; Withanage et al. (2022) Methods Mol. Biol. 2418:405-424; Owens et al. (2019) Cold Spring Harb Protoc. 2019(6); herein incorporated by reference in their entireties), hybridization-based methods such as Northern blotting, array hybridization (e.g., microarray); in situ hybridization; and in situ hybridization followed by FACS, and the like (see, e.g., Parker & Barnes (1999) Methods in Molecular Biology 106:247-283); RNAse protection assays (Hod (1992) Biotechniques 13:852-854); PCR-based methods such as reverse transcription PCR (RT-PCR), quantitative RT-PCR (qRT-PCR), real-time RT-PCR, and the like (see, e.g., Weis et al. (1992) Trends in Genetics 8:263-264); and the like. See also, Robert E. Farrell Jr, RNA Methodologies: A Laboratory Guide for Isolation and Characterization (6thEdition, Academic Press, November 22, 2022; herein incorporated by reference in its entirety.

[0056] In some embodiments, the biological sample can be assayed directly. In some embodiments, nucleic acids of the biological sample are amplified (e.g., by PCR) prior to assaying. For example, techniques such as PCR (Polymerase Chain Reaction), RT-PCR (reverse transcriptase PCR), qRT- PCR (quantitative RT-PCR, real time RT-PCR), etc. can be used prior to the hybridization methods and / or the sequencing methods discussed above.

[0057] For measuring protein levels, the amount or level of a protein in the biological sample is determined. In some cases, the protein comprises a post-translational modification (e.g., phosphorylation, glycosylation) associated with regulation of activity of the protein such as by a signaling cascade, wherein the modified protein is the biomarker, and the amount of the modified protein is therefore measured. In some embodiments, an extracellular protein level is measured. For example, in some cases, the protein (i.e., polypeptide) being measured is a secreted protein, and the concentration can be measured in aqueous humor. In some embodiments, concentration is a relative value measured by comparing the level of one protein relative to another protein. In other embodiments the concentration is an absolute measurement of weight / volume or weight / weight.

[0058] In some instances, the concentration of one or more additional proteins may also be measured, and biomarker concentration compared to the level of the one or more additional proteins to provide a normalized value for the biomarker concentration. Any convenient protocol for evaluating protein levels may be employed wherein the level of one or more proteins in the assayed sample is determined.

[0059] While a variety of different methods of assaying protein levels are known to one of ordinary skill in the art, and any convenient method may be used, two representative and convenient techniques for assaying protein levels include antibody-based methods such as the enzyme-linked immunosorbent assay (ELISA) and electrochemiluminescence-based immunoassays.

[0060] In ELISA and ELISA-based assays, one or more antibodies specific for the proteins of interest may be immobilized onto a selected solid surface, preferably a surface exhibiting a protein affinity such as the wells of a polystyrene microtiter plate. After washing to remove incompletely adsorbed material, the assay plate wells are coated with a non-specific “blocking” protein that is known to be antigenically neutral with regard to the test sample such as bovine serum albumin (BSA), casein or solutions of powdered milk. This allows for blocking of non-specific adsorption sites on the immobilizing surface, thereby reducing the background caused by non-specific binding of antigen onto the surface. After washing to remove unbound blocking protein, the immobilizing surface is contacted with the sample to be tested under conditions that are conducive to immune complex (antigen / antibody) formation. Following incubation, the antisera-contacted surface is washed so as to remove non-immunocomplexed material. The occurrence and amount of immunocomplex formation may then be determined by subjecting the bound immunocomplexes to a second antibody having specificity for the target that differs from the first antibody and detecting binding of the second antibody. In certain embodiments, the second antibody will have an associated enzyme, e.g. urease, peroxidase, or alkaline phosphatase, which will generate a color precipitate upon incubating with an appropriate chromogenic substrate. After such incubation with the second antibody and washing toremove unbound material, the amount of label is quantified, for example by incubation with a chromogenic substrate such as urea and bromocresol purple in the case of a urease label or 2,2'- azino-di-(3-ethyl-benzthiazoline)-6-sulfonic acid (ABTS) and H2O2, in the case of a peroxidase label. Quantitation is then achieved by measuring the degree of color generation, e.g., using a visible spectrum spectrophotometer.

[0061] The preceding format may be altered by first binding the sample to the assay plate. Then, primary antibody is incubated with the assay plate, followed by detecting of bound primary antibody using a labeled second antibody with specificity for the primary antibody. The solid substrate upon which the antibody or antibodies are immobilized can be made of a wide variety of materials and in a wide variety of shapes, e.g., microtiter plate, microbead, dipstick, resin particle, etc. The substrate may be chosen to maximize signal to noise ratios, to minimize background binding, as well as for ease of separation and cost. Washes may be effected in a manner most appropriate for the substrate being used, for example, by removing a bead or dipstick from a reservoir, emptying or diluting a reservoir such as a microtiter plate well, or rinsing a bead, particle, chromatographic column or filter with a wash solution or solvent.

[0062] Electrochemiluminescence-based immunoassays utilize a biomarker-specific antibody tagged with an electrochemiluminescent luminophore that generates a high-energy species in an electron transfer reaction at an electrode. The species generated at the electrode is in an electronically excited state, which emits light upon relaxation to a lower-energy state. Photons generated by the electrochemiluminescent luminophore may be detected, for example, with photomultiplier tubes or silicon photodiode or gold coated fiber-optic sensors. In some embodiments, the electrochemiluminescent luminophore comprises a ruthenium complex (e.g., Ru(bpy)s2+) or silicon nanoparticle. For a description of electrochemiluminescence-based immunoassays, see, e.g., Wang et al. (2023) Bioelectrochemistry 149:108281 , Muzyka et al. (2014) Biosens. Bioelectron. 54:393-407, Keustermans et al. (2013) Methods 61 (1 ):10-7, and Sornambigai et al. (2023) Anal. Bioanal. Chem. 415(24):5875-5898; herein incorporated by reference in their entireties.

[0063] Alternatively, other methods for measuring the levels of one or more proteins in a sample may be employed. Representative exemplary methods include but are not limited to antibody-based methods (e.g., immunofluorescence assay, radioimmunoassay, immunoprecipitation, Western blotting, proteomic arrays, xMAP microsphere technology (e.g., Luminex technology), immunohistochemistry, flow cytometry, and the like) as well as non-antibody-based methods (e.g., aptamer-based assays, nuclear magnetic resonance, mass spectrometry, liquid chromatographymass spectrometry, or tandem mass spectrometry).

[0064] "Diagnosis" as used herein generally includes determination as to whether a subject is likely affected by a given disease, disorder or dysfunction. The skilled artisan often makes a diagnosis on the basis of one or more diagnostic indicators, i.e., a biomarker, the presence, absence, or amount of which is indicative of the presence or absence of the disease, disorder or dysfunction.

[0065] "Prognosis" as used herein generally refers to a prediction of the probable course and outcome of a clinical condition or disease. A prognosis of a patient is usually made by evaluating factors or symptoms of a disease that are indicative of a favorable or unfavorable course or outcome of the disease. It is understood that the term "prognosis" does not necessarily refer to the ability to predict the course or outcome of a condition with 100% accuracy. Instead, the skilled artisan will understand that the term "prognosis" refers to an increased probability that a certain course or outcome will occur; that is, that a course or outcome is more likely to occur in a patient exhibiting a given condition, when compared to those individuals not exhibiting the condition.Additional terms.

[0066] The terms "treatment", "treating", "treat" and the like are used herein to generally refer to obtaining a desired pharmacologic and / or physiologic effect. The effect can be prophylactic in terms of completely or partially preventing a disease or symptom(s) thereof and / or may be therapeutic in terms of a partial or complete stabilization or cure for a disease and / or adverse effect attributable to the disease. The term “treatment" encompasses any treatment of a disease in a mammal, particularly a human, and includes: (a) preventing the disease and / or symptom(s) from occurring in a subject who may be predisposed to the disease or symptom but has not yet been diagnosed as having it; (b) inhibiting the disease and / or symptom(s), i.e., arresting their development; or (c) relieving the disease symptom(s), i.e., causing regression of the disease and / or symptom(s). Those in need of treatment include those already inflicted (e.g., those with a dormant or active infection) as well as those in which prevention is desired (e.g., those with diabetes (type I or type II), those with a genetic predisposition to developing a dormant or active infection, those with increased susceptibility to a dormant or active infection, those suspected of having a dormant or active infection, etc.).

[0067] A therapeutic treatment is one in which the subject is inflicted prior to administration and a prophylactic treatment is one in which the subject is not inflicted prior to administration. In some embodiments, the subject has an increased likelihood of becoming inflicted or is suspected of being inflicted prior to treatment. In some embodiments, the subject is suspected of having an increased likelihood of becoming inflicted.

[0068] A "therapeutically effective dose" or “therapeutic dose” is an amount sufficient to effect desired clinical results (i.e., achieve therapeutic efficacy). A therapeutically effective dose can be administered in one or more administrations.

[0069] "Dosage unit" refers to physically discrete units suited as unitary dosages for the particular individual to be treated. Each unit can contain a predetermined quantity of active compound(s) calculated to produce the desired therapeutic effect(s) in association with the required pharmaceutical carrier. The specification for the dosage unit forms can be dictated by (a) the unique characteristics of the active compound(s) and the particular therapeutic effect(s) to be achieved, and (b) the limitations inherent in the art of compounding such active compound(s).

[0070] The term "about," particularly in reference to a given quantity, is meant to encompass deviations of plus or minus five percent.

[0071] The terms “individual”, “subject”, and “patient”, are used interchangeably herein and refer to any mammalian subject for whom diagnosis, treatment, or therapy is desired, particularly humans. Mammals include human and non-human mammals such as non-human primates, including chimpanzees and other apes and monkey species; laboratory animals such as mice, rats, rabbits, hamsters, guinea pigs, and chinchillas; domestic animals such as dogs and cats; farm animals such as sheep, goats, pigs, horses and cows. In some cases, the methods of the invention find use in experimental animals, in veterinary application, and in the development of animal models for disease, including, but not limited to, rodents including mice, rats, and hamsters; primates, and transgenic animals.

[0072] “Isolated” refers to an entity of interest that is in an environment different from that in which it may naturally occur. “Isolated” is meant to include entities that are within samples that are substantially enriched for the entity of interest and / or in which the entity of interest is partially or substantially purified.

[0073] The terms "polypeptide," "peptide" and "protein" are used interchangeably herein to refer to a polymer of amino acid residues. The terms also apply to amino acid polymers in which one or more amino acid residue is an artificial chemical mimetic of a corresponding naturally occurring amino acid, as well as to naturally occurring amino acid polymers and non-naturally occurring amino acid polymer. Both full-length proteins and fragments thereof are encompassed by the definition. The terms also include postexpression modifications of the polypeptide, for example, phosphorylation, glycosylation, acetylation, hydroxylation, oxidation, and the like.

[0074] The terms "polynucleotide," "oligonucleotide," "nucleic acid" and "nucleic acid molecule" are used herein to include a polymeric form of nucleotides of any length, either ribonucleotides or deoxyribonucleotides. This term refers only to the primary structure of the molecule. Thus, the termincludes triple-, double- and single-stranded DNA, as well as triple-, double- and single-stranded RNA. It also includes modifications, such as by methylation and / or by capping, and unmodified forms of the polynucleotide. More particularly, the terms "polynucleotide," "oligonucleotide," "nucleic acid" and "nucleic acid molecule" include polydeoxyribonucleotides (containing 2-deoxy-D-ribose), polyribonucleotides (containing D-ribose), and any other type of polynucleotide which is an N- or C-glycoside of a purine or pyrimidine base. There is no intended distinction in length between the terms "polynucleotide," "oligonucleotide," "nucleic acid" and "nucleic acid molecule," and these terms are used interchangeably.

[0075] The term "antibody" encompasses monoclonal antibodies, polyclonal antibodies, as well as hybrid antibodies, altered antibodies, chimeric antibodies, and humanized antibodies. The term antibody includes: hybrid (chimeric) antibody molecules (see, for example, Winter et al. (1991 ) Nature 349:293-299; and U.S. Pat. No. 4,816,567); bispecific antibodies, bispecific T cell engager antibodies (BiTE), trispecific antibodies, and other multispecific antibodies (see, e.g., Fan et al. (2015) J. Hematol. Oncol. 8:130, Krishnamurthy et al. (2018) Pharmacol Ther. 185:122-134), F(ab')2 and F(ab) fragments; Fvmolecules (noncovalent heterodimers, see, for example, Inbar et al. (1972) Proc Natl Acad Sci USA 69:2659-2662; and Ehrlich et al. (1980) Biochem 19:4091 -4096); singlechain Fv molecules (scFv) (see, e.g., Huston et al. (1988) Proc Natl Acad Sci USA 85:5879-5883); nanobodies or single-domain antibodies (sdAb) (see, e.g., Wang et al. (2016) Int J Nanomedicine 11 :3287-3303, Vincke et al. (2012) Methods Mol Biol 911 :15-26; dimeric and trimeric antibody fragment constructs; minibodies (see, e.g., Pack et al. (1992) Biochem 31 :1579-1584; Cumber et al. (1992) J Immunology 149B:120-126); humanized antibody molecules (see, e.g., Riechmann et al. (1988) Nature 332:323-327; Verhoeyan et al. (1988) Science 239:1534-1536; and U.K. Patent Publication No. GB 2,276,169, published 21 Sep. 1994); and, any functional fragments obtained from such molecules, wherein such fragments retain specific-binding properties of the parent antibody molecule.

[0076] The phrase "specifically (or selectively) binds" with reference to binding of an antibody to an antigen (e.g., biomarker) refers to a binding reaction that is determinative of the presence of the antigen in a heterogeneous population of proteins and other biologies. Thus, under designated immunoassay conditions, the specified antibodies bind to a particular antigen at least two times over the background and do not substantially bind in a significant amount to other antigens present in the sample. Specific binding to an antigen under such conditions may require an antibody that is selected for its specificity for a particular antigen. For example, antibodies raised to an antigen from specific species such as rat, mouse, or human can be selected to obtain only those antibodies that are specifically immunoreactive with the antigen and not with other proteins, except for polymorphicvariants and alleles. This selection may be achieved by subtracting out antibodies that cross-react with molecules from other species. A variety of immunoassay formats may be used to select antibodies specifically immunoreactive with a particular antigen. For example, solid-phase ELISA immunoassays are routinely used to select antibodies specifically immunoreactive with a protein (see, e.g., Harlow & Lane. Antibodies, A Laboratory Manual (1988), for a description of immunoassay formats and conditions that can be used to determine specific immunoreactivity). Typically, a specific or selective reaction will be at least twice background signal or noise and more typically more than10 to 100 times background.

[0077] “Providing an analysis” is used herein to refer to the delivery of an oral or written analysis (i.e., a document, a report, etc.). A written analysis can be a printed or electronic document. A suitable analysis (e.g., an oral or written report) provides any or all of the following information: identifying information of the subject (name, age, etc.), a description of what type of biological sample(s) was used and / or how it was used, the technique used to assay the sample, the results of the assay (e.g., the level of the biomarker as measured, and / or the fold-change of a biomarker level over time, or in a post-treatment assay compared to a pre-treatment assay), the assessment as to whether the individual is determined to have a dormant bacterial infection, an active bacterial infection, or be uninfected, a recommendation for treatment, and / or to continue or alter therapy, a recommended strategy for additional therapy, etc. The report can be in any format including, but not limited to printed information on a suitable medium or substrate (e.g., paper); or electronic format. If in electronic format, the report can be in any computer readable medium, e.g., diskette, compact disk (CD), flash drive, and the like, on which the information has been recorded. In addition, the report may be present as a website address which may be used via the internet to access the information at a remote site.Biomarkers and Diagnostic Methods

[0078] Biomarkers that can be used in the practice of the subject methods include, without limitation, a protein selected from the group consisting of C-X-C motif chemokine ligand 5 (CXCL5), platelet derived growth factor subunit B (PDGF-B), galectin-1 (Gal-1 ), C-X-C motif chemokine ligand11 (CXCL11 ), angiopoietin 1 (ANGPT1 ), epidermal growth factor (EGF), TEK receptor tyrosine kinase, also known as tyrosine kinase with Ig and EGF homology domains-2 (TIE2), C-C motif chemokine ligand 8 (CCL8) also known as monocyte chemoattractant protein 2 (MCP-2), CD244 molecule (CD244), nitric oxide synthase 3 (NOS3), adenosine deaminase (ADA), C-X-C motif chemokine ligand 1 (CXCL1 ), C-C motif chemokine ligand 20 (CCL20), and tumor necrosis factor superfamily member 14 (TNFSF14) in a synovial fluid sample; a mRNA transcript of a geneselected from the group consisting of VSIG4, FN1 , ITGAM, C1 QB, LIPA, CD9, DUSP1 , SLC7A7, IL3RA, LAMP1 , QPCT, CD52, PIK3IP1 , KCNE3, CD28, TLR8, PCNA, IGLC3, CXCL5, IFITM3, IGKC, C10orf54, SLC25A37, CLEC4E, MMP9, CXCL8, FOSB, CXCL2, DUSP4, CD48, IL1 RN, LAT2, IER3, CXCL3, PRDM1 , CCR7, LY86, ALAS2, IL1 B, CXCL1 , RNASE2, DPP4, IL15RA, CLEC1 OA, TBX21 , CCL4, TNF, IL12RB1 , LAT, IL1 R2, S100A12, STAT4, CCL20, ITGA4, KIAA0101 , CD72, FAS, IL7R, UBE2C, and CD209 in an activated M1 macrophage; a mRNA transcript of a gene selected from the group consisting of C1 QB, LAMP1 , FN1 , TNFSF13, FCGR3A, ITGAE, SLC7A7, CD52, C1 QA, CD9, ITGAM, CTSD, CD14, LIPA, DOCK8, ITGB2, LILRB4, IRF8, IER3, IFITM3, FYN, JUN, SLC25A37, LAT2, FOSB, C10orf54, SELL, LY86, IFITM2, ADA, CXCL5, VPS28, VEGFA, CXCL2, THBD, and CXCL8 in an activated M2 macrophage; a mRNA transcript of a gene selected from the group consisting of VSIG4, FN1 , C1 QB, C1 QA, CD9, ITGAM, CST7, IFITM2, IFITM3, FCN1 , and THBS1 in an activated myeloid dendritic cell; a mRNA transcript of a gene selected from the group consisting of VSIG4, FN1 , C1 QB, IL3RA, ITGAM, DUSP1 , PIK3AP1 , SLC7A7, CD9, TNFSF13, LAMP1 , QPCT, TLR8, LIPA, CD163, CD52, ITGAE, PCNA, APOE, FCGR3A, PIK3IP1 , KCNE3, IRF8, TREM1 , DOCK8, CTSD, CD22, CD28, CHI3L1 , MITF, IFITM3, RNASE2, CD2, CST7, CXCL5, CD6, CCR7, SLC25A37, IGKC, CXCL1 , LAT2, CD48, DUSP4, S100A12, FYN, FCN1 , CXCR3, CXCL8, GNLY, CD7, FOSB, DUSP2, IL32, ITGA4, IL1 R2, CTSW, BIRC3, MMP9, TRAC, CLEC4E, IL1 B, IRF4, LAT, SELL, APOBEC3G, FAS, IER3, CCL5, IL15RA, CCL20, PRDM1 , CLEC1 OA, CCND2, TBX21 , PDCD1 , CD72, DPP4, THBS1 , IL6, IL1 RN, GIMAP5, STAT4, IL12RB1 , LEF1 , TNF, IL7R, LIF, ADGRE1 , F5, FCER1A, CD34, and CD244 in bulk RNA of a tissue sample; a protein selected from the group consisting of CD70, C-X-C motif chemokine ligand 5 (CXCL5), epidermal growth factor (EGF), granzyme H (GZMH), fibroblast growth factor 2 (FGF2), CD28, lysosomal associated membrane protein 3 (LAMP3), pleiotrophin (PTN), and matrix metallopeptidase 12 (MMP12) in a blood or plasma sample; and immune cells such as T cells, natural killer cells, dendritic cells, monocytes, or dendritic cells in tissue (e.g., periarticular tissue or tissue in contact with a joint space containing an implant). These biomarkers can be used for detecting a dormant or active bacterial infection, such as a dormant or active periprosthetic joint infection.

[0079] In certain embodiments, a panel of biomarkers is provided for detecting an active or dormant bacterial infection (e.g., a periprosthetic joint infection) in a patient. Biomarker panels of any size can be used in the practice of the subject methods. Biomarker typically comprise at least 3 biomarkers and up to 100 biomarkers, including any number of biomarkers in between, such as 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23, 24, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 100 biomarkers. In certain embodiments, a biomarker panel comprising at least 3, or at least 4, or at least 5, or at least 6, or at least 7, or at least 8, or at least 9, or at least 10, or atleast 1 1 , or at least 1 , or at least 13, or at least 14, or at least 5, or at least 16, or at least 17, or at least 18, or at least 19, or at least 20, or more biomarkers. Although smaller biomarker panels are usually more economical, larger biomarker panels (i.e., greater than 20 biomarkers) have the advantage of providing more detailed information and can also be used in the practice of the subject methods.

[0080] A biological sample comprising the biomarkers (e.g., proteins, mRNA, or immune cells) is obtained from the subject. The sample may be, for example, synovial fluid, blood or plasma, or tissue such as periarticular tissue or tissue in contact with a joint space containing an implant. In some embodiments, the joint space is a suprapatellar pouch in a knee or a superior capsule in a hip. In some embodiments, the tissue sample is from a nidus of infection.

[0081] . A "control" sample, as used herein, refers to a biological sample from a subject that is not infected. That is, a control sample is obtained from a normal or healthy subject (e.g., an individual known to not have a dormant or active bacterial infection or other infectious condition). A biological sample can be obtained from a subject by conventional techniques. For example, blood can be obtained by venipuncture, while plasma and serum can be obtained by fractionating whole blood according to known methods. Synovial fluid can be obtained by arthrocentesis or joint aspiration, which involves inserting a needle into a joint space to withdraw fluid according to methods well known in the art. Tissue samples can be obtained by surgical resection or by biopsy using fine needle aspiration (FNA), a core needle biopsy, or an excisional biopsy according to methods well known in the art.

[0082] When analyzing the levels of biomarkers in a biological sample from a subject, the reference value ranges used for comparison can represent the levels of one or more biomarkers in a biological sample from one or more subjects without a dormant or active bacterial infection (i.e., normal or healthy, uninfected control). Alternatively, the reference values can represent the levels of one or more biomarkers from one or more subjects with a dormant or active bacterial infection, wherein similarity to the reference value ranges indicates the subject has a dormant or active bacterial infection. More specifically, the reference value ranges can represent the levels of one or more biomarkers from one or more subjects with a dormant bacterial infection (a "dormant bacterial infection” biomarker expression profile, or the levels of one or more biomarkers from one or more subjects with an active bacterial infection (an “active bacterial infection" biomarker expression profile).

[0083] In certain embodiments, the diagnostic methods are used to determine if a patient has a periprosthetic joint infection. For example, the patient undergoing diagnostic testing may have a joint replacement implant for a hip, knee, shoulder, ankle, or other joint. In some embodiments, the patienthas had a previously infected joint replacement that was treated with antibiotic therapy and is undergoing diagnostic testing to determine if the joint replacement implant is now truly aseptic and safe to use after antibiotic therapy or if the joint replacement implant has a dormant infection and Is unsafe to use without further treatment to eradicate the bacteria.

[0084] Accordingly, in one aspect, a method of diagnosing a periprosthetic joint infection in a patient is provided, the method comprising: (a) obtaining a synovial fluid sample from the patient; (b) measuring levels of one or more biomarkers selected from C-X-C motif chemokine ligand 5 (CXCL5), platelet derived growth factor subunit B (PDGF-B), galectin-1 (Gal-1 ), C-X-C motif chemokine ligand 11 (CXCL11 ), angiopoietin 1 (ANGPT1 ), epidermal growth factor (EGF), TEK receptor tyrosine kinase (TIE2), monocyte chemoattractant protein 2 (MCP-2), CD244 molecule (CD244), and nitric oxide synthase 3 (NOS3), and one or more biomarkers selected from adenosine deaminase (ADA), C-X-C motif chemokine ligand 1 (CXCL1 ), C-C motif chemokine ligand 20 (CCL20), and tumor necrosis factor superfamily member 14 (TNFSF14) in the synovial fluid sample; and (c) diagnosing the patient, wherein increased levels of the one or more biomarkers selected from CXCL5, PDGF- B, CXCL1 1 , ANGPT 1 , EGF, TIE2, MCP-2, CD244, and NOS3, increased levels of the one or more biomarkers selected from ADA, CXCL1 , CCL20, and TNFSF14, and decreased levels of the Gal-1 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from an uninfected control subject indicate that the patient has the periprosthetic joint infection.

[0085] In certain embodiments, the levels of ADA, CXCL1 , CCL20, and TNFSF14 are measured in the synovial fluid sample of the patient, wherein increased levels of the ADA, CXCL1 , CCL20, and TNFSF14 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from a subject with a dormant periprosthetic joint infection indicate that the patient has an active periprosthetic joint infection; and wherein decreased levels of the ADA, CXCL1 , CCL20, and TNFSF14 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from a subject with an active periprosthetic joint infection indicate that the patient has a dormant periprosthetic joint infection.

[0086] In certain embodiments, the levels of CXCL5, PDGF-B, Gal-1 , CXCL11 , ANGPT1 , EGF, TIE2, MCP-2 (CCL8), CD244, and NOS3 are measured in the synovial fluid sample of the patient, wherein decreased levels of the CXCL5, PDGF-B, CXCL11 , ANGPT1 , EGF, TIE2, MCP-2 (CCL8), CD244, and NOS3 and increased levels of the Gal-1 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from a subject with a dormant periprosthetic joint infection indicate that the patient does not have a periprosthetic joint infection; and wherein increased levels of the CXCL5, PDGF-B, CXCL11 , ANGPT1 , EGF, TIE2, MCP-2(CCL8), CD244, and N0S3 and decreased levels of the Gal-1 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from an uninfected control subject indicate that the patient has a dormant periprosthetic joint infection.

[0087] In another aspect, a method of diagnosing a dormant bacterial infection in a patient is provided, the method comprising: obtaining a tissue sample from the patient; dissociating the tissue sample into a plurality of cells; separating activated M1 macrophages, activated M2 macrophages, and / or myeloid dendritic cells from other cells of the plurality; measuring levels of one or more mRNA transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , ITGAM, C1 QB, LIPA, CD9, DUSP1 , SLC7A7, IL3RA, LAMP1 , QPCT, CD52, PIK3IP1 , KCNE3, CD28, TLR8, PCNA, IGLC3, CXCL5, IFITM3, IGKC, C10orf54, SLC25A37, CLEC4E, MMP9, CXCL8, FOSB, CXCL2, DUSP4, CD48, IL1 RN, LAT2, IER3, CXCL3, PRDM1 , CCR7, LY86, ALAS2, IL1 B, CXCL1 , RNASE2, DPP4, IL15RA, CLEC10A, TBX21 , CCL4, TNF, IL12RB1 , LAT, IL1 R2, S100A12, STAT4, CCL20, ITGA4, KIAA0101 , CD72, FAS, IL7R, UBE2C, and CD209 in the activated M1 macrophages, wherein decreased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of VSIG4, FN1 , ITGAM, C1 QB, LIPA, CD9, DUSP1 , SLC7A7, IL3RA, LAMP1 , QPCT, CD52, PIK3IP1 , KCNE3, CD28, TLR8, and PCNA, and increased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of IGLC3, CXCL5, IFITM3, IGKC, C10orf54, SLC25A37, CLEC4E, MMP9, CXCL8, FOSB, CXCL2, DUSP4, CD48, IL1 RN, LAT2, IER3, CXCL3, PRDM1 , CCR7, LY86, ALAS2, IL1 B, CXCL1 , RNASE2, DPP4, IL15RA, CLEC10A, TBX21 , CCL4, TNF, IL12RB1 , LAT, IL1 R2, S100A12, STAT4, CCL20, ITGA4, KIAA0101 , CD72, FAS, IL7R, UBE2C, and CD209 in the activated M1 macrophages from the patient compared to reference value ranges for the levels of the one or more mRNA transcripts in M1 macrophages from an uninfected tissue sample indicate that the patient has the dormant bacterial infection; measuring levels of one or more mRNA transcripts of one or more genes selected from the group consisting of C1 QB, LAMP1 , FN1 , TNFSF13, FCGR3A, ITGAE, SLC7A7, CD52, C1 QA, CD9, ITGAM, CTSD, CD14, LIPA, DOCK8, ITGB2, LILRB4, IRF8, IER3, IFITM3, FYN, JUN, SLC25A37, LAT2, FOSB, C10orf54, SELL, LY86, IFITM2, ADA, CXCL5, VPS28, VEGFA, CXCL2, THBD, and CXCL8 in the activated M2 macrophages, wherein decreased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of C1 QB, LAMP1 , FN1 , TNFSF13, FCGR3A, ITGAE, SLC7A7, CD52, C1 QA, CD9, ITGAM, CTSD, CD14, LIPA, DOCK8, ITGB2, LILRB4, and IRF8, and increased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of IER3, IFITM3, FYN, JUN, SLC25A37, LAT2, FOSB, C10orf54, SELL, LY86, IFITM2, ADA, CXCL5, VPS28, VEGFA, CXCL2, THBD, and CXCL8 in the activated M2 macrophages from the patient compared to reference value ranges for the levelsof the one or more mRNA transcripts in M2 macrophages from an uninfected tissue sample indicate that the patient has the dormant bacterial infection; and / or measuring levels of one or more mRNA transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , C1 QB, C1 QA, CD9, ITGAM, CST7, IFITM2, IFITM3, FCN1 , and THBS1 in the activated myeloid dendritic cells, wherein decreased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of VSIG4, FN1 , C1QB, C1QA, CD9, and ITGAM, and increased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of CST7, IFITM2, IFITM3, FCN1 , and THBS1 in the myeloid dendritic cells from the patient compared to reference value ranges for the levels of the one or more mRNA transcripts in myeloid dendritic cells from an uninfected tissue sample indicate that the patient has the dormant bacterial infection.

[0088] In another aspect, a method of diagnosing a dormant bacterial infection in a patient is provided, the method comprising: obtaining a tissue sample from the patient; measuring levels of one or more mRNA transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , C1 QB, IL3RA, ITGAM, DUSP1 , PIK3AP1 , SLC7A7, CD9, TNFSF13, LAMP1 , QPCT, TLR8, LIPA, CD163, CD52, ITGAE, PCNA, APOE, FCGR3A, PIK3IP1 , KCNE3, IRF8, TREM1 , DOCK8, CTSD, CD22, CD28, CHI3L1 , MITF, IFITM3, RNASE2, CD2, CST7, CXCL5, CD6, CCR7, SLC25A37, IGKC, CXCL1 , LAT2, CD48, DUSP4, S100A12, FYN, FCN1 , CXCR3, CXCL8, GNLY, CD7, FOSB, DUSP2, IL32, ITGA4, IL1 R2, CTSW, BIRC3, MMP9, TRAC, CLEC4E, IL1 B, IRF4, LAT, SELL, APOBEC3G, FAS, IER3, CCL5, IL15RA, CCL20, PRDM1 , CLEC10A, CCND2, TBX21 , PDCD1 , CD72, DPP4, THBS1 , IL6, IL1 RN, GIMAP5, STAT4, IL12RB1 , LEF1 , TNF, IL7R, LIF, ADGRE1 , F5, FCER1 A, CD34, and CD244 in the tissue sample; and diagnosing the patient wherein decreased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of VSIG4, FN1 , C1QB, IL3RA, ITGAM, DUSP1 , PIK3AP1 , SLC7A7, CD9, TNFSF13, LAMP1 , QPCT, TLR8, LIPA, CD163, CD52, ITGAE, PCNA, APOE, FCGR3A, PIK3IP1 , KCNE3, IRF8, TREM1 , DOCK8, CTSD, CD22, CD28, CHI3L1 , and MITF, and increased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of IFITM3, RNASE2, CD2, CST7, CXCL5, CD6, CCR7, SLC25A37, IGKC, CXCL1 , LAT2, CD48, DUSP4, S100A12, FYN, FCN1 , CXCR3, CXCL8, GNLY, CD7, FOSB, DUSP2, IL32, ITGA4, IL1 R2, CTSW, BIRC3, MMP9, TRAC, CLEC4E, IL1 B, IRF4, LAT, SELL, APOBEC3G, FAS, IER3, CCL5, IL15RA, CCL20, PRDM1 , CLEC10A, CCND2, TBX21 , PDCD1 , CD72, DPP4, THBS1 , IL6, IL1 RN, GIMAP5, STAT4, IL12RB1 , LEF1 , TNF, IL7R, LIF, ADGRE1 , F5, FCER1A, CD34, and CD244 in the tissue sample from the patient compared to reference value ranges for the levels of the one or more mRNA transcripts in an uninfected tissue sample indicate that the patient has the dormant bacterialinfection. In certain embodiments, the one or more genes comprise CXCL1 , TNF, JUN, IRF8, CD22, QPCT, PIK3AP1 , VSIG4, CXCL2, HLA.DQB1 , TNFSF13, C1 QB, PCNA, and LAMP1.

[0089] In another aspect, a method of diagnosing a dormant bacterial infection in a patient is provided, the method comprising: obtaining a blood or plasma sample from the patient; measuring levels of one or more biomarker proteins selected from the group consisting of CD70, C-X-C motif chemokine ligand 5 (CXCL5), epidermal growth factor (EGF), GZMH, FGF2, CD28, LAMP3, PTN, and MMP12 in the blood or plasma sample; and diagnosing the patient, wherein decreased levels of one or more biomarker proteins selected from the group consisting of CD70, CXCL5, EGF, GZMH, FGF2, CD28, and LAMP3, and increased levels of the one or more biomarker proteins selected from the group consisting of PTN and MMP12 in the blood or plasma sample from the patient compared to reference value ranges for the levels of the one or more biomarker proteins in a blood or plasma sample from an uninfected subject indicate that the patient has the dormant bacterial infection.

[0090] In another aspect, a method of diagnosing a dormant bacterial infection in a patient is provided, the method comprising: obtaining a tissue sample from the patient; counting one or more target immune cells selected from regulatory T cells, natural killer cells, plasmacytoid dendritic cells, classical monocytes, and myeloid dendritic cells in the tissue sample; and diagnosing the patient wherein increased numbers of the one or more target immune cells in the tissue sample from the patient compared to reference value ranges for the target immune cells in an uninfected tissue sample indicate that the patient has the dormant bacterial infection. In certain embodiments, the presence of more than one regulatory T cell, more than one natural killer cell, more than one plasmacytoid dendritic cell, three classical monocytes, or more than eighteen myeloid dendritic cells in the tissue sample from the patient in combination with increased numbers of the one or more target immune cells in the tissue sample from the patient compared to reference value ranges for the target immune cells in an uninfected tissue sample indicate that the patient has the dormant bacterial infection.

[0091] The methods described herein may be used to determine an appropriate treatment regimen for a patient and, in particular, whether a patient should be treated for a dormant or active bacterial infection. For example, a patient is selected for treatment for dormant or active bacterial infection if the patient has a positive diagnosis for a dormant or active bacterial infection based on a biomarker expression profile, as described herein. The treatment for a dormant or active bacterial infection may comprise, for example, removal of the implant, debridement of the joint, placement of an antibiotic spacer, oral or intravenous antibiotic therapy with an antibiotic such as, but not limited to, cefazolin, cefdinir, cefpodoxime, ceftriaxone, cefepime cefuroxime, clindamycin, cotrimoxazole, ciprofloxacin, levofloxacin, delafloxacin, gemifloxacin, moxifloxacin, ofloxacin cefadroxil, cephalexin, ceftriaxone,ceftaroline, doxycycline, amoxicillin-claulanate, penicillin, vancomycin, azithromycin, clarithromycin, linezolid, tedizolid, or rifampin, replacement of the infected implant with a new implant, or any combination thereof.

[0092] In some embodiments, the methods described herein are used for monitoring a patient with a joint implant for development of an active periprosthetic joint infection. For example, a first synovial fluid sample can be obtained from the patient at a first time point and a second synovial fluid sample can be obtained from the subject at a second (later) time point. In some embodiments, the levels of one or more biomarkers selected from ADA, CXCL1 , CCL20, and TNFSF14 are measured in the first synovial fluid sample and the second synovial fluid sample; and the levels of the one or more biomarkers are analyzed in conjunction with respective reference value ranges for the biomarkers, wherein detection of increased levels of the one or more biomarkers selected from selected from ADA, CXCL1 , CCL20, and TNFSF14 in the second synovial fluid sample compared to the first synovial fluid sample indicate that the patient is developing an active periprosthetic joint infection, and detection of decreased levels of expression of the one or more biomarkers selected from ADA, CXCL1 , CCL20, and TNFSF14 in the second synovial fluid sample compared to the first synovial fluid sample indicate that the patient is not developing an active periprosthetic joint infection. In some embodiments, the method further comprises treating the patient that has developed an active periprosthetic joint infection to eradicate the periprosthetic joint infection.

[0093] The subject methods may also be used for assaying pre-treatment and post-treatment biological samples obtained from an individual to determine whether the individual is responsive or not responsive to a treatment for a dormant or active infection. For example, a first synovial fluid sample can be obtained from a subject before the subject undergoes the therapy, and a second synovial fluid sample can be obtained from the subject after the subject undergoes the therapy. In one embodiment, the efficacy of a treatment of a patient for a dormant or active bacterial infection is monitored by measuring levels of one or more biomarkers selected from C-X-C motif chemokine ligand 5 (CXCL5), platelet derived growth factor subunit B (PDGF-B), galectin-1 (Gal-1 ), C-X-C motif chemokine ligand 11 (CXCL11 ), angiopoietin 1 (ANGPT1 ), epidermal growth factor (EGF), TEK receptor tyrosine kinase (TIE2), monocyte chemoattractant protein 2 (MCP-2), CD244 molecule (CD244), and nitric oxide synthase 3 (NOS3), and one or more biomarkers selected from adenosine deaminase (ADA), C-X-C motif chemokine ligand 1 (CXCL1 ), C-C motif chemokine ligand 20 (CCL20), and tumor necrosis factor superfamily member 14 (TNFSF14) in the first synovial fluid sample and the second synovial fluid sample; and evaluating the efficacy of the treatment, wherein detection of increased levels of the one or more biomarkers selected from CXCL5, PDGF-B, CXCL11 , ANGPT1 , EGF, TIE2, MCP-2, CD244, and NOS3, increased levels of the one or morebiomarkers selected from ADA, CXCL1 , CCL20, and TNFSF14, and decreased levels of the Gal-1 in the second biological sample compared to the first biological sample indicate that the patient is worsening or not responding to the treatment, and detection of decreased levels of the one or more biomarkers selected from CXCL5, PDGF-B, CXCL11 , ANGPT1 , EGF, TIE2, MCP-2, CD244, and NOS3, decreased levels of the one or more biomarkers selected from ADA, CXCL1 , CCL20, and TNFSF14, and increased levels of the Gal-1 in the second synovial fluid sample compared to the first synovial fluid sample indicate that the patient is improving and responding to the therapy.

[0094] In some cases, combinations of biomarkers are used in the subject methods. In some such cases, the levels of all measured biomarkers must change (as described above) in order for the diagnosis to be made. In some embodiments, only some biomarkers are used in the methods described herein. For example, a single biomarker, 2 biomarkers, 3 biomarkers, 4 biomarkers, 5 biomarkers, 6 biomarkers, 7 biomarkers, 8 biomarkers, 9 biomarkers, 10 biomarkers, 1 1 biomarkers, 12 biomarkers, 13 biomarkers, 14 biomarkers, 15 biomarkers, 16 biomarkers, 17 biomarkers, 18 biomarkers, 19 biomarkers, or 20 biomarkers can be used in any combination. In other embodiments, all the biomarkers are used. The quantitative values may be combined in linear or non-linear fashion to calculate one or more risk scores for dormant or active bacterial infection for the individual.

[0095] The level of a biomarker in a pre-treatment biological sample can be referred to as a “pretreatment value” because the first biological sample is isolated from the individual prior to the administration of the therapy (i.e., “pre-treatment”). The level of a biomarker in the pre-treatment biological sample can also be referred to as a “baseline value” because this value is the value to which “post-treatment” values are compared. In some cases, the baseline value (i.e., “pre-treatment value”) is determined by determining the level of a biomarker in multiple (i.e., more than one, e.g., two or more, three or more, for or more, five or more, etc.) pre-treatment biological samples. In some cases, the multiple pre-treatment biological samples are isolated from an individual at different time points in order to assess natural fluctuations in biomarker levels prior to treatment. As such, in some cases, one or more (e.g., two or more, three or more, for or more, five or more, etc.) pre-treatment biological samples are isolated from the individual. In some embodiments, all of the pre-treatment biological samples will be the same type of biological sample (e.g., a biopsy sample). In some cases, two or more pre-treatment biological samples are pooled prior to determining the level of the biomarker in the biological samples. In some cases, the level of the biomarker is determined separately for two or more pre-treatment biological samples and a “pre-treatment value” is calculated by averaging the separate measurements.

[0096] A post-treatment biological sample is isolated from an individual after the administration of a therapy. Thus, the level of a biomarker in a post-treatment sample can be referred to as a “post-treatment value”. In some embodiments, the level of a biomarker is measured in additional posttreatment biological samples (e.g., a second, third, fourth, fifth, etc. post-treatment biological sample). Because additional post-treatment biological samples are isolated from the individual after the administration of a treatment, the levels of a biomarker in the additional biological samples can also be referred to as “post-treatment values.”

[0097] The term “responsive” as used herein means that the treatment is having the desired effect such as eradicating a dormant or active infection. When the individual does not improve in response to the treatment, it may be desirable to seek a different therapy or treatment regime for the individual.

[0098] The determination that an individual has a dormant or active bacterial infection by expression profiling or immune cell counting is an active clinical application of the correlation between levels of a biomarker and the disease. For example, “determining” requires the active step of reviewing the data, which is produced during the active assaying step(s), and resolving whether an individual does or does not have dormant or active bacterial infection. Additionally, in some cases, a decision is made to proceed with the current treatment (i.e., therapy), or instead to alter the treatment. In some cases, the subject methods include the step of continuing therapy or altering therapy.

[0099] The term “continue treatment” (i.e., continue therapy) is used herein to mean that the current course of treatment (e.g., continued administration of a therapy) is to continue. If the current course of treatment is not effective in treating the dormant or active bacterial infection, the treatment may be altered. “Altering therapy” is used herein to mean “discontinuing therapy” or “changing the therapy” (e.g., changing the type of treatment, changing the particular dose and / or frequency of administration of medication, e.g., increasing the dose and / or frequency). In some cases, therapy can be altered until the individual is deemed to be responsive. In some embodiments, altering therapy means changing which type of treatment is administered, discontinuing a particular treatment altogether, etc.

[0100] As a non-limiting illustrative example, a patient may be initially treated for a dormant or active bacterial infection by administering an antibiotic. Then to “continue treatment” would be to continue with this type of treatment. If the current course of treatment is not effective, the treatment may be altered, e.g., switching treatment to a different antibiotic or increasing the dose or frequency of administration of the antibiotic, or changing to a different type of treatment such as removal of an infected joint implant, debridement of the joint, placement of an antibiotic spacer, replacement of the infected joint implant with a new joint implant, or any combination thereof.

[0101] In other words, the level of one or more biomarkers may be monitored in order to determine when to continue therapy and / or when to alter therapy. As such, a post-treatment biological sample can be isolated after a treatment and the biological sample can be assayed to determine the level ofa biomarker. Accordingly, the subject methods can be used to determine whether an individual being treated for a dormant or active bacterial infection is responsive or is maintaining responsiveness to a treatment.

[0102] The therapy can be administered to an individual any time after a pre-treatment biological sample is isolated from the individual, but it is preferable for the therapy to be administered simultaneous with or as soon as possible (e.g., about 7 days or less, about 3 days or less, e.g., 2 days or less, 36 hours or less, 1 day or less, 20 hours or less, 18 hours or less, 12 hours or less, 9 hours or less, 6 hours or less, 3 hours or less, 2.5 hours or less, 2 hours or less, 1 .5 hours or less, 1 hour or less, 45 minutes or less, 30 minutes or less, 20 minutes or less, 15 minutes or less, 10 minutes or less, 5 minutes or less, 2 minutes or less, or 1 minute or less) after a pre-treatment biological sample is isolated (or, when multiple pre-treatment biological samples are isolated, after the final pre-treatment biological sample is isolated).

[0103] In some cases, more than one type of therapy may be administered to the individual. For example, a subject who has a dormant or active bacterial infection may be treated with intravenous or oral antibiotic therapy and debridement of the joint, placement of an antibiotic spacer, or replacement of the infected joint implant with a new joint implant, or any combination thereof.

[0104] In some embodiments, the subject methods include providing an analysis indicating whether an individual is determined to have a dormant bacterial infection, an active bacterial infection, or be uninfected. In some embodiments, the analysis indicates whether the individual is determined to have a dormant or active periprosthetic joint infection. The analysis may further provide an analysis of whether an individual is responsive or not responsive to a treatment, or whether the individual is determined to be maintaining responsiveness or not maintaining responsiveness to a treatment for a dormant or active bacterial infection. As described above, an analysis can be an oral or written report (e.g., written or electronic document). The analysis can be provided to the subject, to the subject's physician, to a testing facility, etc. The analysis can also be accessible as a website address via the internet. In some such cases, the analysis can be accessible by multiple different entities (e.g., the subject, the subject’s physician, a testing facility, etc.).Detecting and Measuring Biomarkers

[0105] It is understood that the biomarkers in a sample can be measured by any suitable method known in the art. Measurement of the level of a biomarker can be direct or indirect. For example, the abundance levels of RNAs, proteins, or immune cell types can be directly quantitated. Alternatively, the amount of a biomarker can be determined indirectly by measuring abundance levels of cDNAs, amplified RNAs or DNAs, or by measuring quantities or activities of RNAs, proteins,or other molecules (e.g., metabolites or metabolic byproducts) that are indicative of the expression level of the biomarker. The methods for measuring biomarkers in a sample have many applications. For example, one or more biomarkers can be measured to aid in diagnosing a patient with a dormant or active bacterial infection and determining the appropriate treatment for a subject, as well as monitoring responses of a subject to treatment.

[0106] In some embodiments, the amount or level in the sample (e.g., plasma or synovial fluid) of one or more proteins / polypeptides encoded by a gene of interest is determined. Any convenient protocol for evaluating protein levels may be employed where the level of one or more proteins in the assayed sample is determined. For antibody-based methods of protein level determination, any convenient antibody can be used that specifically binds to the intended biomarker such as C-X-C motif chemokine ligand 5 (CXCL5), platelet derived growth factor subunit B (PDGF-B), galectin-1 (Gal-1 ), C-X-C motif chemokine ligand 1 1 (CXCL11 ), angiopoietin 1 (ANGPT1), epidermal growth factor (EGF), TEK receptor tyrosine kinase (TIE2), monocyte chemoattractant protein 2 (MCP-2), CD244 molecule (CD244), nitric oxide synthase 3 (NOS3), adenosine deaminase (ADA), C-X-C motif chemokine ligand 1 (CXCL1 ), C-C motif chemokine ligand 20 (CCL20), tumor necrosis factor superfamily member 14 (TNFSF14), CD70, epidermal growth factor (EGF), granzyme H (GZMH), fibroblast growth factor 2 (FGF2), CD28, lysosomal associated membrane protein 3 (LAMP3), pleiotrophin (PTN), or matrix metallopeptidase 12 (MMP12). The terms "specifically binds" or "specific binding" as used herein refer to preferential binding to a molecule relative to other molecules or moieties in a solution or reaction mixture (e.g., an antibody specifically binds to a particular polypeptide or epitope relative to other available polypeptides or epitopes). In some embodiments, the affinity of one molecule for another molecule to which it specifically binds is characterized by a Kd (dissociation constant) of 10'5M or less (e.g., 10-6M or less, 10-7M or less, 10‘8M or less, 10'9M or less, 10'10M or less, 10'11M or less, 10'12M or less, 10'13M or less, 10'14M or less, 10'15M or less, or 10'16M or less). By "affinity" it is meant the strength of binding, increased binding affinity being correlated with a lower Kd.

[0107] While a variety of different manners of assaying for protein levels are known in the art, one representative and convenient type of protocol for assaying protein levels is the enzyme-linked immunosorbent assay (ELISA). In ELISA and ELISA-based assays, one or more antibodies specific for the proteins of interest may be immobilized onto a selected solid surface, preferably a surface exhibiting a protein affinity such as the wells of a polystyrene microtiter plate. After washing to remove incompletely adsorbed material, the assay plate wells are coated with a non-specific "blocking" protein that is known to be antigenically neutral with regard to the test sample such as bovine serum albumin (BSA), casein or solutions of powdered milk. This allows for blocking of non-specific adsorption sites on the immobilizing surface, thereby reducing the background caused by non-specific binding of antigen onto the surface. After washing to remove unbound blocking protein, the immobilizing surface is contacted with the sample to be tested under conditions that are conducive to immune complex (antigen / antibody) formation. Such conditions include diluting the sample with diluents such as BSA or bovine gamma globulin (BGG) in phosphate buffered saline (PBS)ZTween or PBS / Triton-X 100, which also tend to assist in the reduction of nonspecific background, and allowing the sample to incubate for about 2-4 hours at temperatures on the order of about 25°-27° C. (although other temperatures may be used). Following incubation, the antisera- contacted surface is washed so as to remove non-immunocomplexed material. An exemplary washing procedure includes washing with a solution such as PBS / Tween, PBS / Triton-X 100, or borate buffer. The occurrence and amount of immunocomplex formation may then be determined by subjecting the bound immunocomplexes to a second antibody having specificity for the target that differs from the first antibody and detecting binding of the second antibody. In certain embodiments, the second antibody will have an associated enzyme, e.g., urease, peroxidase, or alkaline phosphatase, which will generate a color precipitate upon incubating with an appropriate chromogenic substrate. For example, a urease or peroxidase-conjugated anti-human IgG may be employed, for a period of time and under conditions which favor the development of immunocomplex formation (e.g., incubation for 2 hours at room temperature in a PBS-containing solution such as PBS / Tween). After such incubation with the second antibody and washing to remove unbound material, the amount of label is quantified, for example by incubation with a chromogenic substrate such as urea and bromocresol purple in the case of a urease label or 2,2'-azino-di-(3-ethyl- benzthiazoline)-6-sulfonic acid (ABTS) and H2O2, in the case of a peroxidase label. Quantitation is then achieved by measuring the degree of color generation, e.g., using a visible spectrum spectrophotometer. The preceding format may be altered by first binding the sample to the assay plate. Then, primary antibody is incubated with the assay plate, followed by detecting of bound primary antibody using a labeled second antibody with specificity for the primary antibody.

[0108] The solid substrate upon which the antibody or antibodies are immobilized can be made of a wide variety of materials and in a wide variety of shapes, e.g., microtiter plate, microbead, dipstick, resin particle, etc. The substrate may be chosen to maximize signal to noise ratios, to minimize background binding, as well as for ease of separation and cost. Washes may be effected in a manner most appropriate for the substrate being used, for example, by removing a bead or dipstick from a reservoir, emptying or diluting a reservoir such as a microtiter plate well, or rinsing a bead, particle, chromatographic column or filter with a wash solution or solvent.

[0109] Alternatively, non-ELISA based-methods for measuring the levels of one or more proteins in a sample may be employed and any convenient method may be used. Representative examples known to one of ordinary skill in the art include but are not limited to other immunoassay techniques such as radioimmunoassays (RIA), sandwich immunoassays, fluorescent immunoassays, enzyme multiplied immunoassay technique (EMIT), capillary electrophoresis immunoassays (CEIA), and immunoprecipitation assays; mass spectrometry, or tandem mass spectrometry, proteomic arrays, xMAP microsphere technology, western blotting, immunohistochemistry, flow cytometry, cytometry by time-of-flight (CyTOF), multiplexed ion beam imaging (MIBI), and detection in body fluid by electrochemical sensor. In, for example, flow cytometry methods, the quantitative level of gene products of the one or more genes of interest are detected on cells in a cell suspension by lasers. As with ELISAs and immunohistochemistry, antibodies (e.g., monoclonal antibodies) that specifically bind the polypeptides encoded by the genes of interest are used in such methods.

[0110] Aptamer-based assays use aptamers comprising single-stranded oligonucleotides that bind specifically to biomarker proteins of interest. Either high affinity RNA or DNA aptamers with specificity for a protein of interest may be used. Functional groups that mimic amino acid side-chains may be added to aptamers to confer protein-like properties to improve binding affinity to a protein of interest. Aptamers that bind specifically and with high affinity to a protein of interest can be selected from large libraries of aptamers having randomized sequences using Systematic Evolution of Ligands by Exponential enrichment (SELEX). The aptamers may be designed with unique nucleotide sequences recognizable by specific hybridization probes for capture on a hybridization array for multiplexed detection of biomarkers (see, e.g., Gold et al. (2010) Aptamer-Based Multiplexed Proteomic Technology for Biomarker Discovery. PLoS ONE 5(12):e15004; herein incorporated by reference in its entirety.

[0111] As another example, electrochemical sensors may be employed. In such methods, a capture aptamer or an antibody that is specific for a target protein (the "analyte") is immobilized on an electrode. A second aptamer or antibody, also specific for the target protein, is labeled with, for example, pyrroquinoline quinone glucose dehydrogenase ((PQQ)GDH). The sample of body fluid is introduced to the sensor either by submerging the electrodes in body fluid or by adding the sample fluid to a sample chamber, and the analyte allowed to interact with the labeled aptamer / antibody and the immobilized capture aptamer / antibody. Glucose is then provided to the sample, and the electric current generated by (PQQ)GDH is observed, where the amount of electric current passing through the electrochemical cell is directly related to the amount of analyte captured at the electrode.

[0112] In some embodiments, the amount or level of one or more RNA transcripts of interest in a sample (e.g., tissue or immune cells such as M1 macrophages, activated M2 macrophages, myeloiddendritic cells, plasmacytoid dendritic cells, regulatory T cells, natural killer cells, or classical monocytes) is determined. Any convenient protocol for evaluating RNA transcript levels may be employed wherein the level of one or more RNA transcripts in the assayed sample is determined. Measurement of levels of transcription of an RNA transcript biomarker can be direct or indirect. In some embodiments, the amount or level in the sample of nascent RNA or RNA transcripts encoded by a gene of interest is determined. A number of exemplary methods for measuring RNA (e.g., nascent RNA or mRNA) levels in a sample are known by one of ordinary skill in the art, and any convenient method can be used.

[0113] For example, RNA-seq can be used to measure levels of RNA transcripts in a sample. In an exemplary embodiment, RNA-seq involves lysis of cells, RNA capture, reverse transcription (conversion of RNA into cDNA), cDNA amplification, and sequencing of cDNA amplicons. For a further description of RNA-seq techniques, see, e.g., Hrdlickova et al. (2017) Wiley Interdiscip Rev RNA 8(1 ):10.1002 / wrna.1364, Wang et al. (2009) Nat. Rev. Genet. 10(1 ):57-63; Withanage et al. (2022) Methods Mol. Biol. 2418:405-424; Owens et al. (2019) Cold Spring Harb Protoc. 2019(6); herein incorporated by reference in their entireties.

[0114] Single-cell RNA sequencing (scRNA-seq) additionally involves the step of isolating single cells, followed by lysis of cells, RNA capture, reverse transcription (conversion of RNA into cDNA), cDNA amplification, and sequencing of cDNA amplicons. For a description of scRNA-seq techniques, see, e.g., Jovic et al. (2022) Clin. Transl. Med. 12(3):e694, Papalexi et al. (2018) Nat. Rev. Immunol. 18(1 ):35-45 Li et al. (2021 ) Int. J. Oral Sci. 13(1 ):36, Yamada et al. (2020) Int. J. Mol. Sci. 21 (21):8345, Eberwine et al. (2014). Nature Methods. 11 (1 ):25-27, Saliba et al. (2014) Nucleic Acids Research 42(14):8845-8860, Shintaku et al. (2014) Analytical Chemistry 86 (4):1953-1957, Nawy et al. (2014). "Single-cell sequencing". Nature Methods. 11 (1 ):18; herein incorporated by reference in their entireties).

[0115] GRO-seq can be used to measure levels of nascent RNA transcripts. In an exemplary embodiment, GRO-seq involves lysis of cells to release nuclei, isolation of nuclei, incorporation of Br-UTP into nascent RNA molecules by RNA polymerases, affinity purification of RNA molecules using antibodies against bromodeoxyuridine, reverse transcription (conversion of RNA into cDNA), cDNA amplification, and sequencing of cDNA amplicons. For a further description of GRO-seq techniques, see, e.g., Gardini et al. (2017) Methods Mol. Biol. 1468:1 11-120, Tzerpos et al. (2021 ) Methods Mol. Biol. 2351 :25-39.Jordan-Pla et al. (2019) Methods 159-160:177-182, Cardiello et al. (2020) Transcription 11 (1 ) :3-18; herein incorporated by reference in their entireties.

[0116] Cellular indexing of transcriptomes and epitopes sequencing (CITE-seq) can be used to measure levels of both RNA transcripts and proteins of single cells. CITE-seq utilizes antibody-oligonucleotide conjugates, known as antibody-derived tags (ADTs), in combination with scRNA- seq. Each ADT comprises an antibody specific for a cell surface protein of interest and an oligonucleotide for barcoding the antibody, which can be amplified by PCR and sequenced to identify the antibody. The oligonucleotide is typically linked to the antibody non-covalently by conjugating the antibody with streptavidin and the oligonucleotide with biotin. A plurality of ADTs are used for immunostaining cells, which in combination with scRNA-seq allows multiplex protein and transcriptome co-profiling. For a further description of CITE-seq, see, e.g., Mercatelli et al. (2021 ) Methods and Protocols 4 (2):28, Stoeckius et al. (2017) Nature Methods. 14 (9):865-868, Scheyltjens et al. (2022) Nat. Protoc. 17(10):2354-2388, Xu et al. (2021 ) Methods 189:65-73, Liu et al. (2023) Nat. Biotechnol. 41 (10):1405-1409; herein incorporated by reference in their entireties.

[0117] RNA expression and protein sequencing (REAP-seq) is very similar to CITE-seq except for using antibody-oligonucleotide conjugates in which the antibody is covalently linked to an aminated DNA barcode. For a further description of REAP-seq, see, e.g., Peterson, et al. (2017) Nature Biotechnology 35 (10): 936-939; herein incorporated by reference in its entirety.

[0118] Any high-throughput technique for sequencing can be used to sequence RNA transcripts isolated from cells. DNA sequencing techniques include dideoxy sequencing reactions (Sanger method) using labeled terminators or primers and gel separation in slab or capillary, sequencing by synthesis using reversibly terminated labeled nucleotides, pyrosequencing, 454 sequencing, sequencing by synthesis using allele specific hybridization to a library of labeled clones followed by ligation, real time monitoring of the incorporation of labeled nucleotides during a polymerization step, polony sequencing, SOLID sequencing, and the like.

[0119] Certain high-throughput methods of sequencing comprise a step in which individual molecules are spatially isolated on a solid surface where they are sequenced in parallel. Such solid surfaces may include nonporous surfaces (such as in Solexa sequencing, e.g. Bentley et al, Nature, 456: 53-59 (2008) or Complete Genomics sequencing, e.g. Drmanac et al, Science, 327: 78-81 (2010)), arrays of wells, which may include bead- or particle-bound templates (such as with 454, e.g. Margulies et al, Nature, 437: 376-380 (2005) or Ion Torrent sequencing, e.g., U.S. patent publication 2010 / 0137143 or 2010 / 0304982), micromachined membranes (such as with SMRT sequencing, e.g. Eid et al, Science, 323: 133-138 (2009)), or bead arrays (as with SOLiD sequencing or polony sequencing, e.g. Kim et al, Science, 316: 1481 -1414 (2007)). Such methods may comprise amplifying the isolated molecules either before or after they are spatially isolated on a solid surface. Prior amplification may comprise emulsion-based amplification, such as emulsion PCR or rolling circle amplification.

[0120] Of particular interest is sequencing on the Illumina MiSeq, NextSeq, and HiSeq platforms, which use reversible-terminator sequencing by synthesis technology (see, e.g., Shen et al. (2012) BMC Bioinformatics 13:160; Junemann et al. (2013) Nat. Biotechnol. 31 (4):294-296; Glenn (2011 ) Mol. Ecol. Resour. 11 (5):759-769; Thudi et al. (2012) Brief Funct. Genomics 11 (1 ):3-11 ; herein incorporated by reference); the Oxford Nanopore Technologies Inc. MinlON, GridlON, and PromethlON nanopore sequencing platforms, which can be used to determine the sequences of DNA or RNA by monitoring changes in electrical current as nucleic acids are passed through a protein nanopore (see, e.g., Lu et al. (2016) Genomics Proteomics Bioinformatics 14(5):265-279, Petersen et al. (2019) J. Clin. Microbiol. 58(1 ):e01315-19, Kono et al. (2019) Dev Growth Differ. 61 (5):316-326, Deamer et al. (2016) Nat. Biotechnol. 34(5):518-24, Madoui et al. (2015) BMC Genomics 16:327, Szalay et al. (2015) Nat. Biotechnol 33, 1087-1091 ; herein incorporated by reference); the PacBIO Single Molecule, Real-Time (SMRT) sequencing platforms, including the Sequel, HiFi, and RS II sequencing platforms (see, e.g., Ardui et al. (2018) Nucleic Acids Res. 46(5):2159-2168, An et al. (2018) Genes (Basel) 9(1 ):43), Nakano et al. (2017) Hum Cell. 30(3):149- 161 ; herein incorporated by reference), the Omniome sequencing by binding (SBB®) short-read sequencing platform using high fidelity plasmonic nanohole arrays (see, e.g., Cetin et al. (2018) ACS Sens. 3(3):561 -568; herein incorporated by reference), the Gynapsys compact DNA sequencer, which uses metal oxide semiconductor (CMOS) sequencing chips for electronic data detection and sequencing by synthesis (SBS) chemistry, the Singular Genomics G4 benchtop sequencing platform, which uses SBS chemistry, and the Element Biosciences AVITI™ benchtop sequencer, which uses a modified form of SBS chemistry that reduces reagent usage.

[0121] Other methods of detecting levels of RNA transcripts include hybridization-based methods such as Northern blotting, array hybridization (e.g., microarray); in situ hybridization; and in situ hybridization followed by FACS, and the like (see, e.g., Parker & Barnes (1999) Methods in Molecular Biology 106:247-283); RNAse protection assays (Hod (1992) Biotechniques 13:852-854); PCR- based methods such as reverse transcription PCR (RT-PCR), quantitative RT-PCR (qRT-PCR), realtime RT-PCR, and the like (see, e.g., Weis et al. (1992) Trends in Genetics 8:263-264); and the like. See also, Robert E. Farrell Jr, RNA Methodologies: A Laboratory Guide for Isolation and Characterization (6thEdition, Academic Press, November 22, 2022; herein incorporated by reference in its entirety.

[0122] For measuring mRNA levels, the starting material is typically total RNA or poly A+ RNA isolated from a biological sample (e.g., cancerous cells from a tumor biopsy or surgical specimen, or from a homogenized tissue, e.g. a homogenized biopsy sample, an aspirate, a homogenized paraffin- or OCT-embedded sample, etc.). General methods for mRNA extraction are well known inthe art and are disclosed in standard textbooks of molecular biology, including Ausubel et al., Current Protocols of Molecular Biology, John Wiley and Sons (1997). RNA isolation can also be performed using a purification kit, buffer set and protease from commercial manufacturers, according to the manufacturer’s instructions. For example, RNA from cell suspensions can be isolated using Qiagen RNeasy mini-columns, and RNA from cell suspensions or homogenized tissue samples can be isolated using the TRIzol reagent-based kits (Invitrogen), MasterPure™ Complete DNA and RNA Purification Kit (Epicentre, Madison, Wl), Paraffin Block RNA Isolation Kit (Ambion, Inc.) or RNA Stat- 60 kit (Tel-Test).

[0123] A variety of different manners of measuring mRNA levels are known in the art, e.g., as employed in the field of differential gene expression analysis. One representative and convenient type of protocol for measuring mRNA levels is array-based gene expression profiling. Such protocols are hybridization assays in which a nucleic acid that displays “probe” nucleic acids for each of the genes to be assayed / profiled is employed. In these assays, a sample of target nucleic acids is first prepared from the initial nucleic acid sample being assayed, where preparation may include labeling of the target nucleic acids with a label (e.g., member of signal producing system such as a fluorophore that allows detection by measuring fluorescence). Following target nucleic acid sample preparation, the sample is contacted with the array under hybridization conditions, whereby complexes are formed between target nucleic acids that are complementary to probe sequences attached to the array surface. The presence of hybridized complexes is then detected, either qualitatively or quantitatively.

[0124] Specific hybridization technology which may be practiced to generate the expression profiles employed in the subject methods includes the technology described in U.S. Patent Nos.: 5,143,854; 5,288,644; 5,324,633; 5,432,049; 5,470,710; 5,492,806; 5,503,980; 5,510,270; 5,525,464; 5,547,839; 5,580,732; 5,661 ,028; 5,800,992; the disclosures of which are herein incorporated by reference; as well as WO 95 / 21265; WO 96 / 31622; WO 97 / 10365; WO 97 / 27317; EP 373 203; and EP 785 280. In these methods, an array of “probe” nucleic acids that includes a probe for each of the phenotype determinative genes whose expression is being assayed is contacted with target nucleic acids as described above. Contact is carried out under hybridization conditions, e.g., stringent hybridization conditions, and unbound nucleic acid is then removed. The term “stringent assay conditions” as used herein refers to conditions that are compatible to produce binding pairs of nucleic acids, e.g., surface bound and solution phase nucleic acids, of sufficient complementarity to provide for the desired level of specificity in the assay while being less compatible to the formation of binding pairs between binding members of insufficient complementarity to provide for the desiredspecificity. Stringent assay conditions are the summation or combination (totality) of both hybridization and wash conditions.

[0125] The resultant pattern of hybridized nucleic acid provides information regarding expression for each of the genes that have been probed, where the expression information is in terms of whether or not the gene is expressed and, typically, at what level, where the expression data, i.e., expression profile (e.g., in the form of a transcriptosome), may be both qualitative and quantitative.

[0126] In some embodiments, a microarray is used comprising a plurality of probes that specifically hybridize to mRNA transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , ITGAM, C1QB, LIPA, CD9, DUSP1 , SLC7A7, IL3RA, LAMP1 , QPCT, CD52, PIK3IP1 , KCNE3, CD28, TLR8, PCNA, IGLC3, CXCL5, IFITM3, IGKC, C10orf54, SLC25A37, CLEC4E, MMP9, CXCL8, FOSB, CXCL2, DUSP4, CD48, IL1 RN, LAT2, IER3, CXCL3, PRDM1 , CCR7, LY86, ALAS2, IL1 B, CXCL1 , RNASE2, DPP4, IL15RA, CLEC10A, TBX21 , CCL4, TNF, IL12RB1 , LAT, IL1 R2, S100A12, STAT4, CCL20, ITGA4, KIAA0101 , CD72, FAS, IL7R, UBE2C, and CD209.

[0127] In some embodiments, a microarray is used comprising a plurality of probes that specifically hybridize to mRNA transcripts of one or more genes selected from the group consisting of C1 QB, LAMP1 , FN1 , TNFSF13, FCGR3A, ITGAE, SLC7A7, CD52, C1QA, CD9, ITGAM, CTSD, CD14, LIPA, DOCK8, ITGB2, LILRB4, IRF8, IER3, IFITM3, FYN, JUN, SLC25A37, LAT2, FOSB, C10orf54, SELL, LY86, IFITM2, ADA, CXCL5, VPS28, VEGFA, CXCL2, THBD, and CXCL8.

[0128] In some embodiments, a microarray is used comprising a plurality of probes that specifically hybridize to mRNA transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , C1 QB, C1 QA, CD9, ITGAM, CST7, IFITM2, IFITM3, FCN1 , and THBS1.

[0129] Alternatively, non-array based methods for quantitating the level of one or more nucleic acids in a sample may be employed. These include those based on amplification protocols, e.g., Polymerase Chain Reaction (PCR)-based assays, including quantitative PCR, reverse-transcription PCR (RT-PCR), real-time PCR, and the like, e.g. TaqMan® RT-PCR, MassARRAY® System, Bead Array® technology, and Luminex technology; and those that rely upon hybridization of probes to filters, e.g. Northern blotting and in situ hybridization.

[0130] The resultant data provides information regarding expression, amount, and / or activity for each of the biomarkers that have been measured, wherein the information is in terms of whether or not the biomarker is present (e.g., expressed) and at what level, and wherein the data may be both qualitative and quantitative.

[0131] In some embodiments, the number of immune cells of a particular cell type (e.g., M1 macrophages, activated M2 macrophages, myeloid dendritic cells, plasmacytoid dendritic cells, regulatory T cells, natural killer cells, or classical monocytes) is measured in a sample (e.g.,periarticular tissue). Any convenient protocol for counting cells may be employed wherein the numbers of immune cells of particular cell types in the assayed sample is determined. For example, immune cells can be detected and quantified using flow cytometry, a Coulter counter, manual or automated analysis of microscopy images, a cell counter (e.g., hemocytometer, Sedgewick Rafter counting chamber, or Neubauer counting chamber), stereologic cell counting, or automated cellcounting with microfluidic devices.

[0132] In some embodiments, the cells are counted using flow cytometry or a cell counter equipped to differentiate cells by size and scatter characteristics. For example, flow cytometry can be used to identify and quantify specific cell types based on their size, as determined by forward scatter, and granularity, as determined by side scatter. In some embodiments, cells are counted using a Coulter counter or other device that measure changes in electrical impedance caused by cells passing through an aperture. In yet other embodiments, microscopy is used to identify and count cells, which can be performed manually or automated with image analysis software.

[0133] Immune cells of a particular cell type may be separated from other cells to allow counting using any suitable cell separation technique such as, but not limited to, centrifugation-based cell separation, positive or negative selection against surface markers on cells (e.g., with antibody- coated beads), affinity chromatography, panning and immunopanning techniques, fluorescence activated cell sorting (FACS), or magnetic-activated cell sorting (MACS). Affinity reagents may be employed comprising specific receptors or ligands specific for cell surface molecules. For specific cell type identification, immunohistochemical staining may be used with antibodies against cell typespecific cellular markers, including, for example, without limitation, CD4 and FOXP3 for regulatory T-cells, CD56 for natural killer cells, CD303 for plasmacytoid dendritic cells, CD14 and CD16 for monocytes, and CD11 c and HLA-DR for myeloid dendritic cells. Immune cells may be separated from dead cells by employing viability dyes (e.g., propidium iodide). Any technique may be employed which is not unduly detrimental to the viability of the immune cells. For a further description of cell separation and counting techniques, see, e.g., Manohar et al. (2021 ) Bioanalysis. 13(3):181 -198, McKinnon (2018) Curr Protoc Immunol. 120:5.1.1 -5.1.11 , Phelan et al. (2001 ) Curr. Protoc. Cytom. Appendix 3:Appendix 3A, Grishagin et al. (2015) Anal. Biochem. 473:63-65, Avci et al. (2023) Anal. Methods 15(18):2244-2252, Zhang et al. (2020) J. Clin. Lab. Anal. 34(1):e23024, Wang et al. (2022) Biosensors (Basel12(7):443, Luo et al. (2020) Electrophoresis 41 (16-17):1450-1468, Lin-Gibson et al. (2018) Cytotherapy 20(6):785-795, Nasiri et al. (2020) Small 16(29):e2000171 , Paz et al. (2025) Lab Chip. 25(1 1):2521 -2565, Zhang et al. (2024) Biotechnol Adv. 71 :108317, Tang et al. (2019) Electrophoresis. 40(6):930-954, Xu et al. (2016) Biosens Bioelectron. 77:824-36, Zhou et al. (2021 )Analyst. 146(20) :6064-6083, Houston et al. (2018) Methods Mol Biol. 1678:421-446, and Bene (2017) Int J Lab HematoL 39 Suppl 1 :93-97; herein incorporated by reference in their entireties.Data Analysis

[0134] In some embodiments, one or more pattern recognition methods can be used in analyzing the data for biomarker levels. The quantitative values may be combined in linear or non-linear fashion to calculate one or more risk scores for dormant or active bacterial infection for an individual. In some embodiments, measurements for a biomarker or combinations of biomarkers are formulated into linear or non-linear models or algorithms (e.g., a 'biomarker signature') and converted into a likelihood score. This likelihood score indicates the probability that a biological sample is from a patient who is uninfected, who has a dormant bacterial infection, or who has an active bacterial infection. The models and / or algorithms can be provided in machine readable format, and may be used to correlate biomarker levels or a biomarker profile with an infected or uninfected state, and / or to designate a treatment modality for a patient or class of patients.

[0135] Analyzing the levels of a plurality of biomarkers may comprise the use of an algorithm or classifier. In some embodiments, a machine learning algorithm is used to classify a patient as uninfected or having a dormant or active bacterial infection. The machine learning algorithm may comprise a supervised learning algorithm. Examples of supervised learning algorithms may include Average One-Dependence Estimators (AODE), Artificial neural network (e.g., Backpropagation), Bayesian statistics (e.g., Naive Bayes classifier, Bayesian network, Bayesian knowledge base), Case-based reasoning, Decision trees, Inductive logic programming, Gaussian process regression, Group method of data handling (GMDH), Learning Automata, Learning Vector Quantization, Minimum message length (decision trees, decision graphs, etc.), Lazy learning, Instance-based learning Nearest Neighbor Algorithm, Analogical modeling, Probably approximately correct learning (PAC) learning, Ripple down rules, a knowledge acquisition methodology, Symbolic machine learning algorithms, Subsymbolic machine learning algorithms, Support vector machines, Random Forests, Ensembles of classifiers, Bootstrap aggregating (bagging), and Boosting. Supervised learning may comprise ordinal classification such as regression analysis and Information fuzzy networks (IFN). Alternatively, supervised learning methods may comprise statistical classification, such as AODE, Linear classifiers (e.g., Fisher's linear discriminant, Logistic regression, Naive Bayes classifier, Perceptron, and Support vector machine), quadratic classifiers, k-nearest neighbor, Boosting, Decision trees (e.g., C4.5, Random forests), Bayesian networks, and Hidden Markov models.

[0136] The machine learning algorithms may also comprise an unsupervised learning algorithm. Examples of unsupervised learning algorithms may include artificial neural network, Data clustering, Expectation-maximization algorithm, Self-organizing map, Radial basis function network, Vector Quantization, Generative topographic map, Information bottleneck method, and IBSEAD. Unsupervised learning may also comprise association rule learning algorithms such as Apriori algorithm, Eclat algorithm and FP-growth algorithm. Hierarchical clustering, such as Single-linkage clustering and Conceptual clustering, may also be used. Alternatively, unsupervised learning may comprise partitional clustering such as K-means algorithm and Fuzzy clustering.

[0137] In some instances, the machine learning algorithms comprise a reinforcement learning algorithm. Examples of reinforcement learning algorithms include, but are not limited to, temporal difference learning, Q-learning and Learning Automata. Alternatively, the machine learning algorithm may comprise Data Pre-processing.

[0138] Preferably, the machine learning algorithms may include, but are not limited to, Average One-Dependence Estimators (AODE), Fisher's linear discriminant, Logistic regression, Perceptron, Multilayer Perceptron, Artificial Neural Networks, Support vector machines, Quadratic classifiers, Boosting, Decision trees, C4.5, Bayesian networks, Hidden Markov models, High-Dimensional Discriminant Analysis, and Gaussian Mixture Models. The machine learning algorithm may comprise support vector machines, Naive Bayes classifier, k-nearest neighbor, high-dimensional discriminant analysis, or Gaussian mixture models. In some instances, the machine learning algorithm comprises Random Forests.Kits

[0139] Also provided are kits for use in the methods, disclosed herein, for diagnosing a dormant or active infection, particularly a periprosthetic joint infection. The subject kits include agents (e.g., an antibody or aptamer that specifically binds to a biomarker and / or other reagents, and the like) for determining the level of at least one biomarker.

[0140] In some embodiments, a kit comprises agents for determining the levels of one or more biomarkers selected from C-X-C motif chemokine ligand 5 (CXCL5), platelet derived growth factor subunit B (PDGF-B), galectin- 1 (Gal-1), C-X-C motif chemokine ligand 11 (CXCL1 1), angiopoietin 1 (ANGPT1 ), epidermal growth factor (EGF), TEK receptor tyrosine kinase (TIE2), monocyte chemoattractant protein 2 (MCP-2), CD244 molecule (CD244), and nitric oxide synthase 3 (NOS3), and one or more biomarkers selected from adenosine deaminase (ADA), C-X-C motif chemokine ligand 1 (CXCL1 ), C-C motif chemokine ligand 20 (CCL20), and tumor necrosis factor superfamily member 14 (TNFSF14).

[0141] In some embodiments, a kit comprises agents for determining the levels of one or more biomarkers selected from CD70, C-X-C motif chemokine ligand 5 (CXCL5), epidermal growth factor (EGF), granzyme H (GZMH), fibroblast growth factor 2 (FGF2), CD28, lysosomal associated membrane protein 3 (LAMP3), pleiotrophin (PTN), or matrix metallopeptidase 12 (MMP12).

[0142] In some embodiments, a kit comprises agents for determining the levels of one or more mRNA transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , ITGAM, C1 QB, LIPA, CD9, DUSP1 , SLC7A7, IL3RA, LAMP1 , QPCT, CD52, PIK3IP1 , KCNE3, CD28, TLR8, PCNA, IGLC3, CXCL5, IFITM3, IGKC, C10orf54, SLC25A37, CLEC4E, MMP9, CXCL8, FOSB, CXCL2, DUSP4, CD48, IL1 RN, LAT2, IER3, CXCL3, PRDM1 , CCR7, LY86, ALAS2, IL1 B, CXCL1 , RNASE2, DPP4, IL15RA, CLEC10A, TBX21 , CCL4, TNF, IL12RB1 , LAT, IL1 R2, S100A12, STAT4, CCL20, ITGA4, KIAA0101 , CD72, FAS, IL7R, UBE2C, and CD209 in activated M1 macrophages; one or more mRNA transcripts of one or more genes selected from the group consisting of C1 QB, LAMP1 , FN1 , TNFSF13, FCGR3A, ITGAE, SLC7A7, CD52, C1QA, CD9, ITGAM, CTSD, CD14, LIPA, DOCK8, ITGB2, LILRB4, IRF8, IER3, IFITM3, FYN, JUN, SLC25A37, LAT2, FOSB, C10orf54, SELL, LY86, IFITM2, ADA, CXCL5, VPS28, VEGFA, CXCL2, THBD, and CXCL8 in activated M2 macrophages; and one or more mRNA transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , C1 QB, C1 QA, CD9, ITGAM, CST7, IFITM2, IFITM3, FCN1 , and THBS1 in activated myeloid dendritic cells.

[0143] In addition to the above components, the subject kits may further include (in certain embodiments) instructions for practicing the subject methods. These instructions may be present in the subject kits in a variety of forms, one or more of which may be present in the kit. One form in which these instructions may be present is as printed information on a suitable medium or substrate, e.g., a piece or pieces of paper on which the information is printed, in the packaging of the kit, in a package insert, and the like. Yet another form of these instructions is a computer readable medium, e.g., diskette, compact disk (CD), DVD, flash drive, and the like, on which the information has been recorded. Yet another form of these instructions that may be present is a website address which may be used via the internet to access the information at a removed site.

[0144] In certain embodiments, the kit further comprises reagents for performing an immunoassay or aptamer-based assay. In some embodiments, the kit comprises an antibody or aptamer that specifically binds to CXCL5, an antibody or aptamer that specifically binds to PDGF-B, an antibody or aptamer that specifically binds to Gal-1 , an antibody or aptamer that specifically binds to CXCL11 , an antibody or aptamer that specifically binds to ANGPT 1 , an antibody or aptamer that specifically binds to EGF, an antibody or aptamer that specifically binds to TIE2, an antibody or aptamer that specifically binds to MCP-2 (CCL8), an antibody or aptamer that specifically binds to CD244, anantibody or aptamer that specifically binds to NOS3, an antibody or aptamer that specifically binds to ADA, an antibody or aptamer that specifically binds to CXCL1 , an antibody or aptamer that specifically binds to CCL20, and an antibody or aptamer that specifically binds to TNFSF14.

[0145] In some embodiments, the kit comprises an antibody or aptamer that specifically binds to CD70, an antibody or aptamer that specifically binds to C-X-C motif chemokine ligand 5 (CXCL5), an antibody or aptamer that specifically binds to epidermal growth factor (EGF), an antibody or aptamer that specifically binds to granzyme H (GZMH), an antibody or aptamer that specifically binds to fibroblast growth factor 2 (FGF2), an antibody or aptamer that specifically binds to CD28, an antibody or aptamer that specifically binds to lysosomal associated membrane protein 3 (LAMP3), an antibody or aptamer that specifically binds to pleiotrophin (PTN), and an antibody or aptamer that specifically binds to matrix metallopeptidase 12 (MMP12).

[0146] In some embodiments, the kit comprises a microarray comprising a plurality of probes that specifically hybridize to mRNA transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , ITGAM, C1 QB, LIPA, CD9, DUSP1 , SLC7A7, IL3RA, LAMP1 , QPCT, CD52, PIK3IP1 , KCNE3, CD28, TLR8, PCNA, IGLC3, CXCL5, IFITM3, IGKC, C10orf54, SLC25A37, CLEC4E, MMP9, CXCL8, FOSB, CXCL2, DUSP4, CD48, IL1 RN, LAT2, IER3, CXCL3, PRDM1 , CCR7, LY86, ALAS2, IL1 B, CXCL1 , RNASE2, DPP4, IL15RA, CLEC10A, TBX21 , CCL4, TNF, IL12RB1 , LAT, IL1 R2, S100A12, STAT4, CCL20, ITGA4, KIAA0101 , CD72, FAS, IL7R, UBE2C, and CD209.

[0147] In some embodiments, the kit comprises a microarray comprising a plurality of probes that specifically hybridize to mRNA transcripts of one or more genes selected from the group consisting of C1QB, LAMP1 , FN1 , TNFSF13, FCGR3A, ITGAE, SLC7A7, CD52, C1 QA, CD9, ITGAM, CTSD, CD14, LIPA, DOCK8, ITGB2, LILRB4, IRF8, IER3, IFITM3, FYN, JUN, SLC25A37, LAT2, FOSB, C10orf54, SELL, LY86, IFITM2, ADA, CXCL5, VPS28, VEGFA, CXCL2, THBD, and CXCL8.

[0148] In some embodiments, the kit comprises a microarray comprising a plurality of probes that specifically hybridize to mRNA transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , C1 QB, C1 QA, CD9, ITGAM, CST7, IFITM2, IFITM3, FCN1 , and THBS1 .Examples of Non-Limiting Aspects of the Disclosure

[0149] Aspects, including embodiments, of the present subject matter described above may be beneficial alone or in combination, with one or more other aspects or embodiments. Without limiting the foregoing description, certain non-limiting aspects of the disclosure numbered 1-79 are provided below. As will be apparent to those of skill in the art upon reading this disclosure, each of the individually numbered aspects may be used or combined with any of the preceding or followingindividually numbered aspects. This is intended to provide support for all such combinations of aspects and is not limited to combinations of aspects explicitly provided below.1 . A method of diagnosing and treating a periprosthetic joint infection in a patient, the method comprising:(a) obtaining a synovial fluid sample from the patient;(b) measuring levels of one or more biomarkers selected from C-X-C motif chemokine ligand 5 (CXCL5), platelet derived growth factor subunit B (PDGF-B), galectin-1 (Gal-1 ), C-X-C motif chemokine ligand 11 (CXCL11 ), angiopoietin 1 (ANGPT1 ), epidermal growth factor (EGF), TEK receptor tyrosine kinase (TIE2), monocyte chemoattractant protein 2 (MCP-2), CD244 molecule (CD244), and nitric oxide synthase 3 (NOS3), and one or more biomarkers selected from adenosine deaminase (ADA), C-X-C motif chemokine ligand 1 (CXCL1 ), C-C motif chemokine ligand 20 (CCL20), and tumor necrosis factor superfamily member 14 (TNFSF14) in the synovial fluid sample;(c) diagnosing the patient, wherein increased levels of the one or more biomarkers selected from CXCL5, PDGF-B, CXCL11 , ANGPT1 , EGF, TIE2, MCP-2, CD244, and NOS3, increased levels of the one or more biomarkers selected from ADA, CXCL1 , CCL20, and TNFSF14, and decreased levels of the Gal-1 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from an uninfected control subject indicate that the patient has the periprosthetic joint infection; and(d) treating the patient diagnosed with the periprosthetic joint infection to eradicate the periprosthetic joint infection.2. The method of aspect 1 , wherein said treating comprises removal of an infected joint implant, debridement of the joint, placement of an antibiotic spacer, oral or intravenous antibiotic therapy with an antibiotic, replacement of the infected joint implant with a new joint implant, or any combination thereof.3. The method of aspect 1 or 2, wherein said measuring the levels of the one or more biomarkers comprises measuring the levels of ADA, CXCL1 , CCL20, and TNFSF14 in the synovial fluid sample of the patient, wherein increased levels of the ADA, CXCL1 , CCL20, and TNFSF14 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from a subject with a dormant periprosthetic joint infection indicate that the patient has an active periprosthetic joint infection; and wherein decreased levels of the ADA, CXCL1 , CCL20, and TNFSF14 in the synovial fluid sample of the patient compared to reference value ranges for asynovial fluid sample from a subject with an active periprosthetic joint infection indicate that the patient has a dormant periprosthetic joint infection.4. The method of any one of aspects 1 -3, wherein said measuring the levels of the one or more biomarkers comprises measuring the levels of the CXCL5, PDGF-B, Gal-1 , CXCL11 , ANGPT 1 , EGF, TIE2, MCP-2 (CCL8), CD244, and NOS3 in the synovial fluid sample of the patient, wherein decreased levels of the CXCL5, PDGF-B, CXCL11 , ANGPT1 , EGF, TIE2, MCP-2 (CCL8), CD244, and NOS3 and increased levels of the Gal-1 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from a subject with a dormant periprosthetic joint infection indicate that the patient does not have a periprosthetic joint infection; and wherein increased levels of the CXCL5, PDGF-B, CXCL11 , ANGPT1 , EGF, TIE2, MCP-2 (CCL8), CD244, and NOS3 and decreased levels of the Gal-1 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from the uninfected control subject indicate that the patient has a dormant periprosthetic joint infection.5. The method of any one of aspects 1 -4, wherein said measuring the levels of the one or more biomarkers comprises performing an enzyme-linked immunosorbent assay (ELISA), a radioimmunoassay (RIA), an immunofluorescent assay (IFA), immunohistochemistry, fluorescence- activated cell sorting (FACS), a Western Blot, mass spectrometry, tandem mass spectrometry, an aptamer-based assay, an enzymatic or biochemical assay, liquid chromatography, or nuclear magnetic resonance (NMR).6. The method of aspect 5, wherein the ELISA is performed using a multiplex ELISA array.7. The method of any one of aspects 1 -6, wherein the patient has a joint replacement implant, optionally wherein the joint replacement implant was treated for an infection previously.8. The method of aspect 7, wherein the joint replacement implant is in a hip, knee, shoulder, ankle, or other joint.9. A method of monitoring a patient with a joint implant for development of an active periprosthetic joint infection, the method comprising:(a) obtaining a first synovial fluid sample from the patient at a first time point and a second synovial fluid sample from the patient later at a second time point;(b) measuring levels of one or more biomarkers selected from ADA, CXCL1 , CCL20, and TNFSF14 in the first synovial fluid sample and the second synovial fluid sample; and(c) analyzing the levels of the one or more biomarkers in conjunction with respective reference value ranges for said biomarkers, wherein detection of increased levels of the one or more biomarkers selected from selected from ADA, CXCL1 , CCL20, and TNFSF14 in the second synovial fluid sample compared to the first synovial fluid sample indicate that the patient is developing an active periprosthetic joint infection, and detection of decreased levels of expression of the one or more biomarkers selected from ADA, CXCL1 , CCL20, and TNFSF14 in the second synovial fluid sample compared to the first synovial fluid sample indicate that the patient is not developing an active periprosthetic joint infection.10. The method of aspect 9, further comprising treating the patient developing an active periprosthetic joint infection to eradicate the periprosthetic joint infection.1 1. The method of aspect 10, wherein said treating comprises removal of the infected joint implant, debridement of the joint, placement of an antibiotic spacer, oral or intravenous antibiotic therapy with an antibiotic, replacement of the infected joint implant with a new joint implant, or any combination thereof.12. A kit comprising agents for detecting C-X-C motif chemokine ligand 5 (CXCL5), platelet derived growth factor subunit B (PDGF-B), galectin-1 (Gal-1 ), C-X-C motif chemokine ligand 11 (CXCL11 ), angiopoietin 1 (ANGPT1 ), epidermal growth factor (EGF), TEK receptor tyrosine kinase, also known as tyrosine kinase with Ig and EGF homology domains-2 (TIE2), C-C motif chemokine ligand 8 (CCL8) also known as monocyte chemoattractant protein 2 (MCP-2), CD244 molecule (CD244), nitric oxide synthase 3 (NOS3), adenosine deaminase (ADA), C-X-C motif chemokine ligand 1 (CXCL1 ), C-C motif chemokine ligand 20 (CCL20), and tumor necrosis factor superfamily member 14 (TNFSF14).13. The kit of aspect 12, further comprising reagents for performing an immunoassay.14. The kit of aspect 12 or 13, wherein the kit comprises an antibody or aptamer that specifically binds to CXCL5, an antibody or aptamer that specifically binds to PDGF-B, an antibodyor aptamer that specifically binds to Gal-1 , an antibody or aptamer that specifically binds to CXCL11 , an antibody or aptamer that specifically binds to ANGPT 1 , an antibody or aptamer that specifically binds to EGF, an antibody or aptamer that specifically binds to TIE2, an antibody or aptamer that specifically binds to MCP-2 (CCL8), an antibody or aptamer that specifically binds to CD244, an antibody or aptamer that specifically binds to NOS3, an antibody or aptamer that specifically binds to ADA, an antibody or aptamer that specifically binds to CXCL1 , an antibody or aptamer that specifically binds to CCL20, and an antibody or aptamer that specifically binds to TNFSF14.15. The kit of any one of aspects 12-14, further comprising instructions for determining whether a patient has an active or dormant periprosthetic joint infection.16. A protein selected from the group consisting of C-X-C motif chemokine ligand 5 (CXCL5), platelet derived growth factor subunit B (PDGF-B), galectin-1 (Gal-1 ), C-X-C motif chemokine ligand 11 (CXCL1 1 ), angiopoietin 1 (ANGPT1 ), epidermal growth factor (EGF), TEK receptor tyrosine kinase, also known as tyrosine kinase with Ig and EGF homology domains-2 (TIE2), C-C motif chemokine ligand 8 (CCL8) also known as monocyte chemoattractant protein 2 (MCP-2), CD244 molecule (CD244), nitric oxide synthase 3 (NOS3), adenosine deaminase (ADA), C-X-C motif chemokine ligand 1 (CXCL1 ), C-C motif chemokine ligand 20 (CCL20), and tumor necrosis factor superfamily member 14 (TNFSF14) for use as a biomarker in diagnosing a periprosthetic joint infection.17. A composition comprising one or more biomarkers selected from C-X-C motif chemokine ligand 5 (CXCL5), platelet derived growth factor subunit B (PDGF-B), galectin-1 (Gal-1 ), C-X-C motif chemokine ligand 11 (CXCL11 ), angiopoietin 1 (ANGPT1 ), epidermal growth factor (EGF), TEK receptor tyrosine kinase (TIE2), monocyte chemoattractant protein 2 (MCP-2), CD244 molecule (CD244), and nitric oxide synthase 3 (NOS3), and one or more biomarkers selected from adenosine deaminase (ADA), C-X-C motif chemokine ligand 1 (CXCL1 ), C-C motif chemokine ligand 20 (CCL20), and tumor necrosis factor superfamily member 14 (TNFSF14) for use in diagnosing a periprosthetic joint infection.18. An in vitro method of diagnosing a periprosthetic joint infection, the method comprising:(a) obtaining a synovial fluid sample from the patient;(b) measuring levels of one or more biomarkers selected from C-X-C motif chemokine ligand 5 (CXCL5), platelet derived growth factor subunit B (PDGF-B), galectin-1 (Gal-1 ), C-X-C motif chemokine ligand 11 (CXCL11 ), angiopoietin 1 (ANGPT1 ), epidermal growth factor (EGF), TEK receptor tyrosine kinase (TIE2), monocyte chemoattractant protein 2 (MCP-2), CD244 molecule (CD244), and nitric oxide synthase 3 (NOS3), and one or more biomarkers selected from adenosine deaminase (ADA), C-X-C motif chemokine ligand 1 (CXCL1 ), C-C motif chemokine ligand 20 (CCL20), and tumor necrosis factor superfamily member 14 (TNFSF14) in the synovial fluid sample; and(c) diagnosing the patient, wherein increased levels of the one or more biomarkers selected from CXCL5, PDGF-B, CXCL11 , ANGPT1 , EGF, TIE2, MCP-2, CD244, and NOS3, increased levels of the one or more biomarkers selected from ADA, CXCL1 , CCL20, and TNFSF14, and decreased levels of the Gal-1 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from an uninfected control subject indicate that the patient has the periprosthetic joint infection.19. The method of aspect 18, wherein said measuring the levels of the one or more biomarkers comprises measuring the levels of ADA, CXCL1 , CCL20, and TNFSF14 in the synovial fluid sample of the patient, wherein increased levels of the ADA, CXCL1 , CCL20, and TNFSF14 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from a subject with a dormant periprosthetic joint infection indicate that the patient has an active periprosthetic joint infection; and wherein decreased levels of the ADA, CXCL1 , CCL20, and TNFSF14 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from a subject with an active periprosthetic joint infection indicate that the patient has a dormant periprosthetic joint infection.20. The method of aspect 18 or 19, wherein said measuring the levels of the one or more biomarkers comprises measuring the levels of the CXCL5, PDGF-B, Gal-1 , CXCL11 , ANGPT 1 , EGF, TIE2, MCP-2 (CCL8), CD244, and NOS3 in the synovial fluid sample of the patient, wherein decreased levels of the CXCL5, PDGF-B, CXCL11 , ANGPT1 , EGF, TIE2, MCP-2 (CCL8), CD244, and NOS3 and increased levels of the Gal-1 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from a subject with a dormant periprosthetic joint infection indicate that the patient does not have a periprosthetic joint infection; andwherein increased levels of the CXCL5, PDGF-B, CXCL11 , ANGPT1 , EGF, TIE2, MCP-2 (CCL8), CD244, and N0S3 and decreased levels of the Gal-1 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from an uninfected control subject indicate that the patient has a dormant periprosthetic joint infection.21 . The method of any one of aspects 18-20, wherein said measuring the levels of the one or more biomarkers comprises performing an enzyme-linked immunosorbent assay (ELISA), a radioimmunoassay (RIA), an immunofluorescent assay (IFA), immunohistochemistry, fluorescence- activated cell sorting (FACS), a Western Blot, mass spectrometry, tandem mass spectrometry, an aptamer-based assay, an enzymatic or biochemical assay, liquid chromatography, or nuclear magnetic resonance (NMR).22. The method of aspect 21 , wherein the ELISA is performed using a multiplex ELISA array.23. The method of any one of aspects 18-22, wherein the patient has a joint replacement implant, optionally wherein the joint replacement implant was treated for an infection previously.24. The method of aspect 23, wherein the joint replacement implant is in a hip, knee, shoulder, ankle, or other joint.25. A method of diagnosing a dormant bacterial infection in a patient, the method comprising: obtaining a tissue sample from the patient; dissociating the tissue sample into a plurality of cells; separating activated M1 macrophages, activated M2 macrophages, and / or myeloid dendritic cells from other cells of the plurality; measuring levels of one or more messenger RNA (mRNA) transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , ITGAM, C1 QB, LIPA, CD9, DUSP1 , SLC7A7, IL3RA, LAMP1 , QPCT, CD52, PIK3IP1 , KCNE3, CD28, TLR8, PCNA, IGLC3, CXCL5, IFITM3, IGKC, C10orf54, SLC25A37, CLEC4E, MMP9, CXCL8, FOSB, CXCL2, DUSP4, CD48, IL1 RN, LAT2, IER3, CXCL3, PRDM1 , CCR7, LY86, ALAS2, IL1 B, CXCL1 , RNASE2, DPP4, IL15RA, CLEC10A, TBX21 , CCL4, TNF, IL12RB1 , LAT, IL1 R2, S100A12, STAT4, CCL20, ITGA4, KIAA0101 , CD72, FAS, IL7R, UBE2C, and CD209 in the activated M1 macrophages, wherein decreased levelsof the one or more mRNA transcripts of the one or more genes selected from the group consisting of VSIG4, FN1 , ITGAM, C1 QB, LIPA, CD9, DUSP1 , SLC7A7, IL3RA, LAMP1 , QPCT, CD52, PIK3IP1 , KCNE3, CD28, TLR8, and PCNA, and increased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of IGLC3, CXCL5, IFITM3, IGKC, C10orf54, SLC25A37, CLEC4E, MMP9, CXCL8, FOSB, CXCL2, DUSP4, CD48, IL1 RN, LAT2, IER3, CXCL3, PRDM1 , CCR7, LY86, ALAS2, IL1 B, CXCL1 , RNASE2, DPP4, IL15RA, CLEC1 OA, TBX21 , CCL4, TNF, IL12RB1 , LAT, IL1 R2, S100A12, STAT4, CCL20, ITGA4, KIAA0101 , CD72, FAS, IL7R, UBE2C, and CD209 in the activated M1 macrophages from the patient compared to reference value ranges for the levels of the one or more mRNA transcripts in M1 macrophages from an uninfected tissue sample indicate that the patient has the dormant bacterial infection; measuring levels of one or more mRNA transcripts of one or more genes selected from the group consisting of 01 QB, LAMP1 , FN1 , TNFSF13, FCGR3A, ITGAE, SLC7A7, CD52, C1 QA, CD9, ITGAM, CTSD, CD14, LIPA, DOCK8, ITGB2, LILRB4, IRF8, IER3, IFITM3, FYN, JUN, SLC25A37, LAT2, FOSB, C10orf54, SELL, LY86, IFITM2, ADA, CXCL5, VPS28, VEGFA, CXCL2, THBD, and CXCL8 in the activated M2 macrophages, wherein decreased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of C1 QB, LAMP1 , FN1 , TNFSF13, FCGR3A, ITGAE, SLC7A7, CD52, C1 QA, CD9, ITGAM, CTSD, CD14, LIPA, DOCK8, ITGB2, LILRB4, and IRF8, and increased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of IER3, IFITM3, FYN, JUN, SLC25A37, LAT2, FOSB, C10orf54, SELL, LY86, IFITM2, ADA, CXCL5, VPS28, VEGFA, CXCL2, THBD, and CXCL8 in the activated M2 macrophages from the patient compared to reference value ranges for the levels of the one or more mRNA transcripts in M2 macrophages from an uninfected tissue sample indicate that the patient has the dormant bacterial infection; and / or measuring levels of one or more mRNA transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , C1 QB, C1 QA, CD9, ITGAM, CST7, IFITM2, IFITM3, FCN1 , and THBS1 in the activated myeloid dendritic cells, wherein decreased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of VSIG4, FN1 , C1 QB, 01 QA, CD9, and ITGAM, and increased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of CST7, IFITM2, IFITM3, FCN1 , and THBS1 in the myeloid dendritic cells from the patient compared to reference value ranges for the levels of the one or more mRNA transcripts in the myeloid dendritic cells from an uninfected tissue sample indicate that the patient has the dormant bacterial infection.26. The method of aspect 25, further comprising treating the patient diagnosed with the dormant bacterial infection to eradicate the dormant bacterial infection.27. The method of aspect 26, wherein said treating comprises removal of an infected joint implant, debridement of the joint, placement of an antibiotic spacer, oral or intravenous antibiotic therapy with an antibiotic, replacement of the infected joint implant with a new joint implant, or any combination thereof.28. A composition comprising one or more messenger RNA (mRNA) transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , ITGAM, C1 QB, LIPA, CD9, DUSP1 , SLC7A7, IL3RA, LAMP1 , QPCT, CD52, PIK3IP1 , KCNE3, CD28, TLR8, PCNA, IGLC3, CXCL5, IFITM3, IGKC, C10orf54, SLC25A37, CLEC4E, MMP9, CXCL8, FOSB, CXCL2, DUSP4, CD48, IL1 RN, LAT2, IER3, CXCL3, PRDM1 , CCR7, LY86, ALAS2, IL1 B, CXCL1 , RNASE2, DPP4, IL15RA, CLEC1 OA, TBX21 , CCL4, TNF, IL12RB1 , LAT, IL1 R2, S100A12, STAT4, CCL20, ITGA4, KIAA0101 , CD72, FAS, IL7R, UBE2C, and CD209 in activated M1 macrophages; one or more mRNA transcripts of one or more genes selected from the group consisting of C1QB, LAMP1 , FN1 , TNFSF13, FCGR3A, ITGAE, SLC7A7, CD52, C1 QA, CD9, ITGAM, CTSD, CD14, LIPA, DOCK8, ITGB2, LILRB4, IRF8, IER3, IFITM3, FYN, JUN, SLC25A37, LAT2, FOSB, C10orf54, SELL, LY86, IFITM2, ADA, CXCL5, VPS28, VEGFA, CXCL2, THBD, and CXCL8 in activated M2 macrophages, and one or more mRNA transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , 01 QB, C1 QA, CD9, ITGAM, CST7, IFITM2, IFITM3, FCN1 , and THBS1 in the activated myeloid dendritic cells for use in diagnosing a dormant bacterial infection.29. A method of diagnosing a dormant bacterial infection in a patient, the method comprising: obtaining a tissue sample from the patient; measuring levels of one or more messenger RNA (mRNA) transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , C1QB, IL3RA, ITGAM, DUSP1 , PIK3AP1 , SLC7A7, CD9, TNFSF13, LAMP1 , QPCT, TLR8, LIPA, CD163, CD52, ITGAE, PCNA, APOE, FCGR3A, PIK3IP1 , KCNE3, IRF8, TREM1 , DOCK8, CTSD, CD22, CD28, CHI3L1 , MITF, IFITM3, RNASE2, CD2, CST7, CXCL5, CD6, CCR7, SLC25A37, IGKC, CXCL1 , LAT2, CD48, DUSP4, S100A12, FYN, FCN1 , CXCR3, CXCL8, GNLY, CD7, FOSB, DUSP2, IL32, ITGA4, IL1 R2, CTSW, BIRC3, MMP9, TRAC, CLEC4E, IL1 B, IRF4, LAT, SELL, APOBEC3G, FAS, IER3, CCL5, IL15RA, CCL20, PRDM1 , CLEC1 OA, CCND2, TBX21 , PDCD1 , CD72, DPP4, THBS1 , IL6, IL1 RN, GIMAP5,STAT4, IL12RB1 , LEF1 , TNF, IL7R, LIF, ADGRE1 , F5, FCER1A, CD34, and CD244 in the tissue sample; and diagnosing the patient, wherein decreased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of VSIG4, FN1 , C1 QB, IL3RA, ITGAM, DUSP1 , PIK3AP1 , SLC7A7, CD9, TNFSF13, LAMP1 , QPCT, TLR8, LIPA, CD163, CD52, ITGAE, PCNA, APOE, FCGR3A, PIK3IP1 , KCNE3, IRF8, TREM1 , D0CK8, CTSD, CD22, CD28, CHI3L1 , and MITF, and increased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of IFITM3, RNASE2, CD2, CST7, CXCL5, CD6, CCR7, SLC25A37, IGKC, CXCL1 , LAT2, CD48, DUSP4, S100A12, FYN, FCN1 , CXCR3, CXCL8, GNLY, CD7, FOSB, DUSP2, IL32, ITGA4, IL1 R2, CTSW, BIRC3, MMP9, TRAC, CLEC4E, IL1 B, IRF4, LAT, SELL, AP0BEC3G, FAS, IER3, CCL5, IL15RA, CCL20, PRDM1 , CLEC10A, CCND2, TBX21 , PDCD1 , CD72, DPP4, THBS1 , IL6, IL1 RN, GIMAP5, STAT4, IL12RB1 , LEF1 , TNF, IL7R, LIF, ADGRE1 , F5, FCER1A, CD34, and CD244 in the tissue sample from the patient compared to reference value ranges for the levels of the one or more mRNA transcripts in an uninfected tissue sample indicate that the patient has the dormant bacterial infection.30. The method of aspect 29, further comprising treating the patient diagnosed with the dormant bacterial infection to eradicate the dormant bacterial infection.31 . The method of aspect 30, wherein said treating comprises removal of an infected joint implant, debridement of the joint, placement of an antibiotic spacer, oral or intravenous antibiotic therapy with an antibiotic, replacement of the infected joint implant with a new joint implant, or any combination thereof.32. The method of any one of aspects 29-31 , wherein the one or more genes comprise CXCL1 , TNF, JUN, IRF8, CD22, QPCT, PIK3AP1 , VSIG4, CXCL2, HLA.DQB1 , TNFSF13, C1 QB, PCNA, and LAMP1.33. The method of any one of aspects 29-32, wherein the tissue sample is a periarticular tissue sample.34. The method of any one of aspects 29-33, wherein the tissue sample is in contact with a joint space containing an implant.35. The method of aspect 34, wherein the joint space is a suprapatellar pouch in a knee or a superior capsule in a hip.36. The method of any one of aspects 29-35, wherein the tissue sample is from a nidus of the dormant bacterial infection.37. The method of any one of aspects 29-36, where said dissociating the tissue comprises digesting the tissue sample with a collagenase.38. A composition comprising one or more messenger RNA (mRNA) transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , C1 QB, IL3RA, ITGAM, DUSP1 , PIK3AP1 , SLC7A7, CD9, TNFSF13, LAMP1 , QPCT, TLR8, LIPA, CD163, CD52, ITGAE, PCNA, APOE, FCGR3A, PIK3IP1 , KCNE3, IRF8, TREM1 , DOCK8, CTSD, CD22, CD28, CHI3L1 , MITF, IFITM3, RNASE2, CD2, CST7, CXCL5, CD6, CCR7, SLC25A37, IGKC, CXCL1 , LAT2, CD48, DUSP4, S100A12, FYN, FCN1 , CXCR3, CXCL8, GNLY, CD7, FOSB, DUSP2, IL32, ITGA4, IL1 R2, CTSW, BIRC3, MMP9, TRAC, CLEC4E, IL1 B, IRF4, LAT, SELL, APOBEC3G, FAS, IER3, CCL5, IL15RA, CCL20, PRDM1 , CLEC10A, CCND2, TBX21 , PDCD1 , CD72, DPP4, THBS1 , IL6, IL1 RN, GIMAP5, STAT4, IL12RB1 , LEF1 , TNF, IL7R, LIF, ADGRE1 , F5, FCER1A, CD34, and CD244 for use in diagnosing a dormant bacterial infection.39. A method of diagnosing a dormant bacterial infection in a patient, the method comprising: obtaining a blood or plasma sample from the patient; measuring levels of one or more biomarker proteins selected from the group consisting of CD70, C-X-C motif chemokine ligand 5 (CXCL5), epidermal growth factor (EGF), GZMH, FGF2, CD28, LAMP3, PTN, and MMP12 in the blood or plasma sample; and diagnosing the patient, wherein decreased levels of one or more biomarker proteins selected from the group consisting of CD70, CXCL5, EGF, GZMH, FGF2, CD28, and LAMP3, and increased levels of the one or more biomarker proteins selected from the group consisting of PTN and MMP12 in the blood or plasma sample from the patient compared to reference value ranges for the levels of the one or more biomarker proteins in a blood or plasma sample from an uninfected subject indicate that the patient has the dormant bacterial infection.40. The method of aspect 39, further comprising treating the patient diagnosed with the dormant bacterial infection.41 . The method of aspect 40, wherein said treating comprises removal of an infected joint implant, debridement of the joint, placement of an antibiotic spacer, oral or intravenous antibiotic therapy with an antibiotic, replacement of the infected joint implant with a new joint implant, or any combination thereof.42. A composition comprising one or more biomarker proteins selected from the group consisting of CD70, C-X-C motif chemokine ligand 5 (CXCL5), epidermal growth factor (EGF), GZMH, FGF2, CD28, LAMP3, PTN, and MMP12 for use in diagnosing a dormant bacterial infection.43. A method of diagnosing a dormant bacterial infection in a patient, the method comprising: obtaining a tissue sample from the patient; counting one or more target immune cells selected from regulatory T cells, natural killer cells, plasmacytoid dendritic cells, classical monocytes, and myeloid dendritic cells in the tissue sample; and diagnosing the patient, wherein increased numbers of the one or more target immune cells in the tissue sample from the patient compared to reference value ranges for the target immune cells in an uninfected tissue sample indicate that the patient has the dormant bacterial infection.44. The method of aspect 43, further comprising treating the patient diagnosed with the dormant bacterial infection.45. The method of aspect 44, wherein said treating comprises administering an antibiotic to the patient, removing an infected prosthesis from the patient, or a combination thereof, wherein said treating comprises removal of an infected joint implant, debridement of the joint, placement of an antibiotic spacer, oral or intravenous antibiotic therapy with an antibiotic, replacement of the infected joint implant with a new joint implant, or any combination thereof.46. The method of any one of aspects 43-45, wherein presence of more than one regulatory T cell, more than one natural killer cell, more than one plasmacytoid dendritic cell, three classical monocytes, or more than eighteen myeloid dendritic cells in the tissue sample from thepatient in combination with increased numbers of the one or more target immune cells in the tissue sample from the patient compared to reference value ranges for the target immune cells in an uninfected tissue sample indicate that the patient has the dormant bacterial infection.47. The method of any one of aspects 43-46, further comprising fixing the tissue sample.48. The method of any one of aspects 43-47, further comprising sectioning the tissue sample.49. The method of any one of aspects 43-48, further comprising dividing the tissue sample into fragments.50. The method of any one of aspects 43-49, further comprising dissociating the tissue into plurality of cells.51 . The method of aspect 50, where said dissociating the tissue comprises digesting the tissue sample with a collagenase.52. The method of any one of aspects 43-51 , wherein the tissue sample is a periarticular tissue sample.53. The method of any one of aspects 43-52, wherein the tissue sample is in contact with joint space containing an implant.54. The method of aspect 53, wherein the joint space is a suprapatellar pouch in a knee or a superior capsule in a hip.55. The method of any one of aspects 43-54, wherein the tissue sample is from a nidus of the infection.56. The method of any one of aspects 43-55, further comprising: adding a cryoprotectant to the tissue sample; and freezing the tissue sample prior to said counting the one or more target immune cells.57. The method of aspect 56, wherein the cryoprotectant comprises an optimal cutting temperature (OCT) compound.58. The method of aspect 56 or 57, wherein said freezing comprises freezing the biological sample in liquid nitrogen.59. The method of any one of aspects 43-58, further comprising storing the biological sample at -80°C prior to said counting the one or more target immune cells.60. The method of any one of aspects 43-59, wherein the one or more target immune cells are selected from regulatory T-cells, natural killer cells, and plasmacytoid dendritic cells.61 . The method of any one of aspects 43-60, wherein said counting comprises performing flow cytometry, immunohistochemistry, or microscopy.62. The method of any one of aspects 43-61 , wherein said counting comprises using a cell counter.63. The method of any one of aspects 43-62, wherein the different target immune cell subtypes are distinguished from one another by cell size, morphology, surface markers, granularity, or light scattering, or a combination thereof.64. The method of any one of aspects 43-63, further comprising staining one or more surface markers on the target immune cells in the sample to identify the target immune cells.65. The method of aspect 64, wherein the one or more surface markers are selected from CD4, FOXP3, CD56, CD303, CD14, CD16, CD11c, and HLA-DR.66. The method of aspect 64 or 65, wherein said staining the one or more surface markers comprises performing chromogenic staining or immunofluorescent staining of the one or more surface markers on the target immune cells.67. The method of aspect 66, wherein said immunofluorescent staining comprises contacting the immune cells with one or more primary antibodies that specifically bind to the one or more surface markers.68. The method of aspect 67, wherein the one or more primary antibodies are fluorescently labeled.69. The method of aspect 67, wherein said immunofluorescent staining further comprises contacting the target immune cells with fluorescently labeled secondary antibodies that bind to the one or more primary antibodies bound to the one or more surface markers.70. The method of any one of aspects 43-69, wherein the regulatory T-cells are identified by their cell size, light scattering properties, and the staining of the CD4 and the FOXP3.71 . The method of any one of aspects 43-70, wherein the natural killer cells are identified by their cell size, granularity, and the staining of the CD56.12.. The method of any one of aspects 43-71 , wherein the plasmacytoid dendritic cells are identified by their cell size, light scattering, and the staining of the CD303.73. The method of any one of aspects 43-72, wherein the classical monocytes are identified by their cell size, light scattering, and the staining of the CD14 and the CD16.74. The method of any one of aspects 43-73, wherein the myeloid dendritic cells are identified by their cell size, light scattering, and the staining of the CD11c and the HLA-DR.75. The method of any one of aspects 43-74, further comprising staining nuclei of the one or more immune cells.76. A kit comprising agents for detecting messenger RNA (mRNA) transcripts of two, three, four, or five or more genes selected from VSIG4, FN1 , ITGAM, C1QB, LIPA, CD9, DUSP1 , SLC7A7, IL3RA, LAMP1 , QPCT, CD52, PIK3IP1 , KCNE3, CD28, TLR8, PCNA, IGLC3, CXCL5, IFITM3, IGKC, C10orf54, SLC25A37, CLEC4E, MMP9, CXCL8, FOSB, CXCL2, DUSP4, CD48, IL1 RN, LAT2, IER3, CXCL3, PRDM1 , CCR7, LY86, ALAS2, IL1 B, CXCL1 , RNASE2, DPP4, IL15RA,CLEC1 OA, TBX21 , CCL4, TNF, IL12RB1 , LAT, IL1 R2, S100A12, STAT4, CCL20, ITGA4, KIAA0101 , CD72, FAS, IL7R, UBE2C, and CD209.77. The kit of aspect 76, wherein the kit comprises a microarray comprising a plurality of probes that specifically hybridize to mRNA transcripts of VSIG4, FN1 , ITGAM, C1 QB, LIPA, CD9, DUSP1 , SLC7A7, IL3RA, LAMP1 , QPCT, CD52, PIK3IP1 , KCNE3, CD28, TLR8, PCNA, IGLC3, CXCL5, IFITM3, IGKC, C10orf54, SLC25A37, CLEC4E, MMP9, CXCL8, FOSB, CXCL2, DUSP4, CD48, IL1 RN, LAT2, IER3, CXCL3, PRDM1 , CCR7, LY86, ALAS2, IL1 B, CXCL1 , RNASE2, DPP4, IL15RA, CLEC10A, TBX21 , CCL4, TNF, IL12RB1 , LAT, IL1 R2, S100A12, STAT4, CCL20, ITGA4, KIAA0101 , CD72, FAS, IL7R, UBE2C, and CD209.78. The kit of aspect 76 or 77, wherein the kit comprises a microarray comprising a plurality of probes that specifically hybridize to mRNA transcripts of C1 QB, LAMP1 , FN1 , TNFSF13, FCGR3A, ITGAE, SLC7A7, CD52, C1 QA, CD9, ITGAM, CTSD, CD14, LIPA, DOCK8, ITGB2, LILRB4, IRF8, IER3, IFITM3, FYN, JUN, SLC25A37, LAT2, FOSB, C10orf54, SELL, LY86, IFITM2, ADA, CXCL5, VPS28, VEGFA, CXCL2, THBD, and CXCL8.79. The kit of any one of aspects 76-78, wherein the kit comprises a microarray comprising a plurality of probes that specifically hybridize to mRNA transcripts of VSIG4, FN1 , C1 QB, 01 QA, CD9, ITGAM, CST7, IFITM2, IFITM3, FCN1 , and THBS1.

[0150] It will be apparent to one of ordinary skill in the art that various changes and modifications can be made without departing from the spirit or scope of the invention.EXPERIMENTAL

[0151] The following examples are put forth so as to provide those of ordinary skill in the art with a complete disclosure and description of how to make and use the present invention, and are not intended to limit the scope of what the inventors regard as their invention nor are they intended to represent that the experiments below are all or the only experiments performed. Efforts have been made to ensure accuracy with respect to numbers used (e.g. amounts, temperature, etc.) but some experimental errors and deviations should be accounted for. Unless indicated otherwise, parts are parts by weight, molecular weight is weight average molecular weight, temperature is in degrees Centigrade, and pressure is at or near atmospheric.

[0152] All publications and patent applications cited in this specification are herein incorporated by reference as if each individual publication or patent application were specifically and individually indicated to be incorporated by reference.

[0153] The present invention has been described in terms of particular embodiments found or proposed by the present inventor to comprise preferred modes for the practice of the invention. It will be appreciated by those of skill in the art that, in light of the present disclosure, numerous modifications and changes can be made in the particular embodiments exemplified without departing from the intended scope of the invention. For example, due to codon redundancy, changes can be made in the underlying DNA sequence without affecting the protein sequence. Moreover, due to biological functional equivalency considerations, changes can be made in protein structure without affecting the biological action in kind or amount. All such modifications are intended to be included within the scope of the appended claims.Example 1The Presence of Persistent Synovial Inflammation after “Eradication” Unmasks the “Unseen” Dormant State of Infection Allowing the Prediction of Infection Free Survival in Total Joint ReplacementsINTRODUCTION

[0154] Bacteria form biofilms on orthopaedic implants (e.g., plates, screws, joint replacements), non- orthopaedic implants (e.g., pacemakers, abdominal mesh, breast implants, catheters), and biologic tissues that act as “implants” (e.g., endocarditis, osteomyelitis, cellulitis, sinusitis, chronic wounds).1-5The annual healthcare cost attributed to biofilm exceeds $386 billion globally and biofilm accounts for 80% of microbial infections, many of which end up requiring surgical treament.1'67Biofilm is composed of bacterial communities encased in a protective extracellular matrix. Biofilm-resident bacteria (e.g., small colony variants, sessile cells, and / or persister cells) are notoriously difficult to culture, remarkably tolerant to antibiotics, and capable of evading phagocytosis.8 11When phagocytized, biofilm-resident bacteria dramatically alter cytokine production, modify macrophage polarization, compromise antigen presentation, and inhibit neutrophil function.9’12-17

[0155] The ability of biofilm-resident bacteria to regulate the immune response, coupled with the overreliance of current diagnostic criteria for infected joint replacements on the local and systemic neutrophil response, means that biofilm-resident bacteria can establish a dormant infection that may be misclassified as uninfected.12 18Next-generation sequencing of fluid from antibiotic-laden spacesfrom joint replacements with a prior infection show the continued presence of biofilm-resident bacteria (indicative of a dormant infection) that are next to impossible to culture and thus may be misclassified as uninfected.18-21The high infection relapse rate after a revision joint replacement with a prior infection is consistent with the hypothesis that patients may harbor dormant infections that emerge into acute infections after subsequent surgery.21Given the surgical etiology, access to synovial samples, and staged spacer-related treatment, revision joint replacements with a prior infection are the ideal population to detect implant-associated dormant infection.22

[0156] The accurate identification of dormant infection is of critical importance for cost-effective management of implant-associated infection. The inability to effectively diagnose a dormant infection relegates most clinical work on infection to the diagnosis of only the most advanced disease state - systemic sepsis and actively infected joints.23The inability to effectively diagnose a pre-disease state, like dormant infection, prevents the prediction of future active infections that currently appear to emerge sporadically. The sporadic presentation may be due to the emergence of active inflammatory signals that trigger conventional clinical diagnostic criteria for a periprosthetic joint infection (PJI) that develop from a more dormant inflammatory state (i.e., conversion of the predisease state to the advanced disease state).2425We hypothesize that revision joint replacements with a prior infection have a high prevalence of dormant infections that can be distinguished from uninfected joint replacements by the inflammatory response in synovial fluid and / or circulating plasma and that detection of a dormant infection reveals an increased risk of infection relapse.

[0157] This hypothesis builds on our previous work using single-cell transcriptomics to reveal the cellular signature and gene expression characteristics of dormant infection. The cellular signature of dormant infection has many hallmarks of active infection, including a reduction in both classically activated M1 and alternatively activated M2 macrophages coupled with an increase in classical monocytes, myeloid and plasmacytoid dendritic cells, natural killer cells, and regulatory T-cells, but lacked the systemic or local neutrophil recruitment commonly seen in active infections.12The characteristic gene expression of dormant infection suggested the activation of interleukin (IL)-17 and tumor necrosis factor (TNF) pathways that drive synovial CXCL5 expression, which should stimulate neutrophil recruitment. However, dormant infections also downregulated neutrophil extracellular trap (NET) formation as well as immune checkpoint regulation, classically activated M1 macrophage polarization, and T-cell response.12To remain unbiased for the purpose of this work, we defined a dormant infection as a joint replacement with a prior infection as diagnosed by the 2018 Musculoskeletal Infection Society (MSIS) criteria that underwent implant resection and completion of 6 weeks of microbe-specific intravenous antibiotic therapy and were subsequently reimplanted after being deemed “infection free” using the same 2018 MSIS criteria at the end of a more than 6week antibiotic holiday, and at reimplantation had a synovial inflammatory response that mimicked an active infection as determined by unsupervised clustering of the synovial proteome.2627METHODSPatient Samples

[0158] After institutional review board approval at Stanford University (Biosafety #4328, Clinical Safety #54462 and #72855), we collected matched whole blood and aspirated synovial fluid in separate purple top tubes from 32 patients. We excluded one patient with a quality control warning in the synovial fluid sample and another patient as a potential outlier based on the interquartile range of synovial fluid sample medians. The remaining 30 paired patient samples (94%, Table 1 , FIG. 1 ) comprised 14 (47%) total hip and 16 (53%) total knee replacements. Seven joint replacements had an active infection with Staphylococcus aureus, S. lugdunesis, S. epidermidis, Escherichia coli, or Proteus mirabilis (23% septic revisions, follow-up: 2.6 ± 1.1 years after resection and retention of a durable 1.5 stage antibiotic-laden spacer), 12 joint replacements without an infection (39% aseptic revisions for instability, loosening, wear, or fracture, follow-up: 3.2 ± 0.3 years after aseptic revision surgery, p=0.200, t-test v. infections), and 11 joint replacements with a prior S. aureus, S. lugdunesis, S. epidermidis, or Salmonella enterica infection deemed “infection-free” after spacer placement by the 2018 MSIS criteria after completion of >6 weeks of oral or intravenous antibiotics and a >6 week antibiotic free holiday (37% MSIS-cleared, follow-up of 3.0 ± 0.2 years after definitive reimplantation, p=0.170, t-test v. infections, FIG. 1).26Continuous demographic and clinical variables are reported as mean and standard deviation (SD) unless otherwise noted and compared via independent t-tests with the two-sided level of significance set to a < 0.05. Categorical demographic and clinical variables are reported as numerical count and percentages and compared via a chi-square or Fisher’s exact tests with the level of significance set to a < 0.05.Proximity Extension Assay (PEA)

[0159] The expression of 96 plasma proteomic analytes was determined using a highly multiplexed platform (Immuno-Oncology Panel, Olink Proteomics, Uppsala, Sweden) from intra-operative synovial fluid and pre-operative plasma samples matched to the tissue samples from each patient via proximity extension.28This proximity extension assay (PEA) allows high-throughput, multiplexed protein quantification with high specificity and sensitivity. Normalized protein expression (NPX, logs) data were exported from Olink Software and loaded into R (version 4.3.2) using the read_NPX function from the OlinkAnalyze R package (version 4.0.1 ). Quality control was performed andexcluded one sample with a quality control warning and another as a potential outlier based on the interquartile range of sample medians. Statistical testing for differential protein expression was performed using olink ttest in the OlinkAnalyze R package. Statistically significant expressions with an adjusted p-value < 0.05 after Welch two-sample t-test were labeled in each of the volcano plots.Unsupervised Clustering to Identify Dormant Infection

[0160] There are three reasons we intentionally utilized unsupervised clustering to create a novel immunologic definition of a dormant infection based on a persistent synovial inflammation after a prior culture-positive implant-associated infection.27First, biofilm and bacterial persistence often obscure bacterial culture results, making them a highly unreliable diagnostic tool.8,29'30Second, advanced sequencing techniques are subject to surgical sampling bias and the detection of contaminating bacterial DNA.31 32Third, our goal was not to define a new test to replace synovial or tissue culture, but to instead define the persistent inflammatory signature required to influence the immunologic definition of infection itself. This is particularly important, because the MSIS,2633European Bone and Joint Infection Society (EBJIS),3435Infectious Disease Society of America (IDSA),36and International Consensus Meeting (ICM)3738criteria are essentially immunologic criteria that represent the local and systemic neutrophil response.39To identify a persistent inflammatory signature indicative of dormant infections, we utilized Euclidean distance-based clustering and principal component analysis (PCA).2740Clustering was visualized with the heatmap function from the ComplexHeatmap R package (version 2.18.0), and PCA was performed using the prcomp function from the stats R package (version 4.3.2).41Gene Set Variation Analysis (GSVA)

[0161] Gene set scores for Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were computed using the gsva function from the GSVA R package (version 1 .50.5).42Differential expression analysis was performed using empirical Bayesian statistics with the eBayes function in the limma R package (version 3.58.1 ).43Adjustments for multiple comparisons were applied using the Benjamin-Hochberg method to control the False Discovery Rate (FDR).Identification of Biomarkers of Dormant Infection

[0162] To identify the most informative proteins that distinguish the dormant infection state from the active and no infection states, we used the area under the receiver operating characteristic curve (AUG) and the random forest algorithm. AUG values were computed using the roc and auc functionsin the pROC R package (version 1.18.5).44Random Forest modeling was performed using the random Forest function in the randomForest R package (version 4.7.1.2), and the importance of each protein was assessed based on the percentage increase in mean squared error (%lncMSE). Proteins were then ranked based on AUG and %lncMSE values, and those with the highest scores were selected as the most informative proteins for the accurate detection of a dormant infection.RESULTSSynovial Inflammation Persists after Infection Clearance

[0163] Clinically infected synovial-fluid proteomes segregated sharply from samples that showed no signs of prior infection. As expected, culture-positive joint replacements with an active infection displayed a broad inflammatory signature (FIG. 2A). Strikingly, MSIS-cleared joint replacements undergoing re-implantation showed an inflammatory profile almost indistinguishable from actively infected joint replacements (FIG. 2B, Supplementary Table 1). Only six mediators, ADA, CXCL1 , CCL20, MCP-3, PD-L2, and TNFSF14, differed between the “infection-free” and actively infected groups (FIG. 2C). The near-identity of the synovial proteomic fingerprints of the “MSIS-cleared” and septic joint replacements, despite normal systemic acute-phase reactants and minimal synovial neutrophil recruitment (Table 2), suggests that many re-implantations of prior infections may be mislabeled as “infection-free” and still harbor a biologically active, yet clinically “dormant,” infection. Plasma proteomics did not discriminate among the three groups (data not shown), underscoring the peri-implant space as the critical compartment for detecting implant-associated dormant infection as a unique pathologic entity.Persistent Synovial Inflammation Unmasks Dormant Infection

[0164] Unsupervised clustering of the synovial proteome stratified the 11 MSIS-cleared reimplantations into 3 molecular subgroups (FIG. 3A). Eight cases (73%) grouped tightly with culturepositive joint replacements with an active infection, despite normal ESR / CRP and scant synovial neutrophils, and are hereafter designated as “dormant infections.” Two cases (18%) clustered with aseptic joint replacements, whereas one sample (9%) lay equidistant from both poles and was excluded from downstream analyses. CXCL5, a neutrophil-attracting chemokine, was similarly elevated in active (12.8 ± 0.7 MPX) and dormant infection samples (12.9 ± 1.1 MPX, p=0.780) when compared to the aseptic joint replacements and the MSIS-cleared samples that clustered with them (10.5 ± 1.6 MPX, p<0.001 versus dormant, p=0.002 versus active). Hence, CXCL5 expression can discriminate the dormant and active states from the uninfected state (FIG. 3B).

[0165] Comparing dormant infections with aseptic joint replacements identified 15 candidate biomarkers that can discriminate the dormant from the uninfected state (FIG. 4A). Random-forest modelling ranked 7 of these, PDGF-B, Gal-1 , CXCL1 1 , ANGPT1 , EGF, TIE2, and MCP-2 (CCL8), as the most informative with individual accuracies exceeding 90%, each surpassing CXCL5 (AUC = 0.897; %lncMSE = 1 .7) for diagnostic power (FIGS. 4B-4C, Supplementary Table 2). Both CD244 and NOS3 matched CXCL5 in accuracy, with NOS3 showing greater model importance (%lncMSE=4.5, FIGS. 4B-4C, Supplementary Table 2). None of the discriminatory proteins was detectably altered in plasma (data not shown), again underscoring the value of local sampling.

[0166] A complementary analysis contrasting dormant with acute infection revealed a minimal four- protein signature, including ADA, CXCL1 , CCL20, and TNFSF14, each exceeding 90% accuracy and ranking among the most informative features for separating the dormant from the active state (FIG. 5, Supplemental Table 2). Again, plasma proteomes were nondiscriminatory (data not shown). Taken together, FIGS. 3-5 delineate the synovial states of infection that ranges from sterile to dormant colonization to frank intra-articular sepsis - an immunologic terrain that conventional acute phase reactant- and neutrophil-centric diagnostic criteria fail to fully detect and differentiate.Dormant Infections Reprogram the Inflammatory Response Toward Immune Tolerance

[0167] Pathway analysis highlighted a defense-silencing paradox within joint replacements with a dormant infection. Compared with aseptic revisions, dormant infection was characterized by robust suppression of granulocyte activation as well as T-cell selection and proliferation (FDR< 0.001 for both comparisons, FIG. 6). Concomitantly, programs linked to receptor-mediated endocytosis and to coagulation, including platelet activation and hemostasis, were selectively up-regulated during dormant infection (FDR<0.001 for each comparison, FIG. 6). The net effect is an immune landscape that detects bacterial presence yet downshifts the cellular machinery needed for eradication, mirroring immune tolerance circuits described in chronic viral infections and solid tumor microenvironments.The Absence of a Dormant Infection Forecasts Durable Cure

[0168] One re-implantation originally labeled indeterminate by clustering was reevaluated against the nine-marker panel and expressed eight of nine dormant-infection proteins (89%, PDGF-B, Gal- 1 , CXCL11 , ANGPT1 , EGF, TIE2, MCP-2, and NOS3) prompting its reassignment as a dormant infection. Long-term follow-up confirmed the panel’s prognostic value over 3.0 ± 0.2 years, as two of the eleven biomarker-positive joint replacements (18%) developed culture-confirmed recurrence, whereas none of the thirteen biomarker-negative or aseptic revisions relapsed over 3.2 ± 0.3 years.The panel thus delivered 100% specificity and 100% positive predictive value for future infection with a good negative predictive value (74%) and overall accuracy (64%) but lacked sensitivity (18%). Although the cohort was underpowered to identify which individual protein best predicts infection relapse, the data establish the synovial signature of dormant infection creating a panel of proteins that are sufficient and reliable at ruling-out the presence of biofilm-embedded bacteria and are strong predictors of sustained infection-free implant survival.DISCUSSION

[0169] Our findings have broad implications for infection biology in general and the care of patients with implants in particular. They reveal the protein-based inflammatory signature of dormant infection in joint replacements, a state in which bacteria persist without causing overt clinical or laboratory signs of active infection (a.k.a., periprosthetic joint infection, PJI). Currently, conventional diagnostic criteria for a PJI rely heavily on acute inflammatory markers (e.g., synovial neutrophils, C-reactive protein, erythrocyte sedimentation rate) and culture-based tests detecting only the most advanced active infections that are accompanied by robust immune activation.26In contrast, we demonstrate that even implants deemed “infection-free” after treatment of prior infection can harbor low-grade inflammation with the distinct immunological “footprint” of lingering biofilm-resident bacteria.12’26Our proteomic analysis shows that multiple inflammatory proteins remained elevated in the synovial fluid of joint replacements with a prior infection, even after treatment and MSIS screening, when compared to truly uninfected joint replacements (i.e., joint replacements with no prior incidence of infection, FIG. 3B), despite the absence of the systemic and local signs traditionally associated with an active PJI (Table 2).2633 39The synovial profiles of the majority of joint replacements with a prior infection were largely indistinguishable from joint replacements with active infections, differing significantly in only six known inflammatory mediators. This raised the concern that many “infection- free” cases were not truly sterile, prompting us to search for the definitive inflammatory signature of dormant infection. Unsupervised hierarchical clustering confirmed the presence of a persistent inflammatory signature in 73% of “infection-free” cases that clustered with overtly infected cases (FIG. 4A), despite normal acute phase reactants (ESR, OPR) and minimal recruitment of intraarticular neutrophils, thereby defining these cases as dormant infections (Table 2).12These findings are in line with our prior work using single-cell synovial transcriptomics, which suggested that 50% of joint replacements with a prior infection have dormant infections characterized by synovial CXCL5 expression mediated through activation of the IL-17 and TNF pathways.12In practical terms, the absence of clinical inflammation according to conventional diagnostic criteria26,33-39does not guarantee the absence of infection. It may instead signal a pathogen’s success at evading, or evenactively suppressing, the immune response, facilitating its survival within the host.12 19This shifts the paradigm of PJI and all implant-associated infection diagnostics away from a reliance on neutrophil- driven diagnostic criteria and demonstrates that the current clinical paradigms are inadequate to describe the relevant clinical complexity of implant-associated infections (FIG. 7).12Notably, none of the dormant infections identified in our cohort would have been flagged by conventional diagnostic criteria,26'33-39yet the identified cases carried significant clinical risk of infection relapse, highlighting an urgent need for a more comprehensive and sensitive panel of immunological markers that can account for the full breadth of clinically-relevant implant-associated infections.

[0170] The distinct biomarker panel that characterizes the dormant infection state is a key finding of this work. We identified a set of nine synovial fluid proteins that robustly distinguishes joint replacements with a dormant infection from truly uninfected joint replacements that carry significantly less risk of recurrent infection. CXCL5 (ENA-78), a chemoattractant for neutrophils and several other types of immune cells, emerged as a hallmark of dormant infection. Immune (monocytes, macrophages, eosinophils, and neutrophils) and non-immune (endothelial, epithelial, fibroblasts, and smooth muscle) cells can all produce CXCL5. CXCL5 was similarly elevated 5-fold in active and dormant infections (12.8 ± 1 .0 MPX) relative to its expression in uninfected joint replacements (10.5 ± 1 .6 MPX, p<0.001 ). The persistent overexpression of CXCL5 in the dormant state is striking, given the lack of neutrophil recruitment in joint replacements with a dormant infection, suggesting a disconnect between chemokine signaling and effector cell response. Beyond CXCL5, our machinelearning approach highlighted several other novel candidates: PDGF-B, Galectin-1 , CXCL11 , ANGPT 1 , EGF, TIE2, MCP-2, and NOS3 that each outperformed CXCL5 in discriminating a dormant infection from uninfected joint replacements (FIG. 5). Notably, two of these proteins, MCP-2 (CCL8) and CXCL11 (l-TAC), are also immune chemokines, are expressed by monocytes, T-cells, and fibroblasts, and recruit monocytes and T-cells to orchestrate tissue injury repair and modulate inflammation.45-47

[0171] In deciphering, “why dormant infections remain clinically silent,” our data point to mechanisms of peripheral immune tolerance. Joint replacements with a dormant infection showed a downregulation of pathways related to neutrophil activation and T-cell proliferation compared to uninfected joint replacements. One might expect an infection to provoke inflammation; instead, dormant infection exhibited a subdued immune transcriptomic profile, as if the immune system had been actively dampened.12Gene set analysis confirmed a distinct immunologic signature consistent with peripheral immune tolerance in the local environment (FIG. 6). Notably, Galectin-1 (Gal-1 ) normally promotes immune tolerance and limits inflammation, so the downregulation of Gal-1 in joint replacements with a dormant infection suggests an ongoing antibacterial response.48Hence, in thecontext of dormant infection, a chemokine-driven feedback loop sustains a chronic inflammatory state that neither eradicates the bacteria nor allows full inflammatory resolution. This equilibrium, an immune “truce” between host and microbe, mirrors phenomena observed in chronic viral infections, cancer, and commensal colonization where the host and pathogen coexist in a state of muted inflammatory conflict. Notably, the concept of a dormant infection has parallels beyond orthopaedic surgery and PJI. Diseases like tuberculosis feature latent infections where pathogens persist in a granuloma with the host immune system in an immunologic stalemate. Likewise, staphylococcal infections in other implanted devices may have analogous dormant phases. Thus, our findings are broadly relevant to infection biology and immunology, illustrating how a pathogen can persist as an indolent reservoir for acute infection relapse and how immune profiling unmasks this silent presence.

[0172] We speculate that biofilm-resident bacteria in a persistent state actively modulate the synovial immune milieu to avoid terminal clearance, much as cancer stem cells create an immunosuppressive microenvironment to evade immune clearance. The parallel between dormant infection persistence and cancer stem cell immunity is compelling. For example, increased expression of CXCL5 in the tumor microenvironment has been linked to activation of the CXCR2 pathway and recruitment of protumor immune cells, thereby promoting tumorigenesis and angiogenesis, demonstrating that CXCL5 expression drives glioblastoma progression.49Elevated CXCL5 is associated with poor patient survival, underscoring how a sustained chemokine signal can facilitate pathological persistence.5051In our study, the chronic presence of CXCL5 (and related angiogenic / immunoregulatory factors) in synovial fluid may similarly help bacteria persist and shape the tissue microenvironment into one more permissive to bacterial survival and devoid of aggressive inflammatory destruction. The expression of platelet-derived growth factor (PDGF-B), angiopoietin-1 (ANGPT1), TIE2 (ANGPT1 receptor, tyrosine kinase with immunoglobulin and EGF homology domain 2, endothelial tyrosine kinase, TEK), endothelial growth factor (EGF), and nitric oxide synthase 3 (NOS3) from endothelial cells and fibroblasts can be triggered as secondary responses to bacterial damage,52'56but also serve to stabilize the vascular endothelium and prevent cellular migration from the bloodstream to the synovial space over time. Vascular sequestration during a time of local neutrophil depletion helps explain the increased CXCL5, CXCL11 , and MCP-2 levels, lack of systemic acute phase reactant expression, and continued monocyte and T-cell activity previously shown to be indicative of dormant infection (FIG. 8).12

[0173] When combined as a panel, these 9 biomarkers provide high sensitivity and carry a high negative predictive value for forecasting infection relapse within three years. In practical terms, if none of these markers were elevated in a patient's synovial fluid, we observed no infection recurrence within 3 years. Conversely, elevation of the dormant infection markers, alongsidereduction of Galectin-1 , carried an increased risk of infection recurrence (17%) within 3 years. Because not every biomarker-positive case progressed to clinical infection in the observed timeframe, the panel’s sensitivity and negative predictive value were moderate, indicating the potential for some false negatives, or possibly indicating that many more cases remain dormant with quiescent microbes that continue to remain immunologically contained until future relapse beyond the observed timeframe. Nonetheless, the high specificity of this panel makes it a powerful rule-out test that can, with high confidence, identify patients truly free of infection, which is crucial for safe reimplantation surgery. Equally important, it provides a novel, culture-independent means of detecting an occult infection that traditional microbiological methods or inflammatory markers would miss.26’33' 39,57,58

[0174] These insights carry four critical clinical implications. First, diagnosing a dormant infection could become a reality using this biomarker approach.12Second, a biomarker-positive result would alert clinicians to residual infection risk even if traditional markers are negative (e.g., synovial neutrophils, C-reactive protein, erythrocyte sedimentation rate) and result in more prompt and more aggressive management, for example by extending the course of antibiotics, revising surgical strategy to ensure more complete biofilm removal, or delaying re-implantation to give additional time for more durable infection control.59’60Third, a biomarker-negative result provides strong confidence that the joint is truly infection-free, supporting safe definitive re-implantation.24Indeed, in our cohort, patients without the synovial immune signature of dormant infection had 0% infection relapse within the observed 3-year timespan. Fourth, in terms of prognosis, identifying a dormant infection might warrant closer postoperative surveillance, or even prophylactic monitoring, to catch relapse early, as is the case with current cancer management strategies. The ability to predict which patients are at high risk of relapse moves us closer to precision medicine for implant-associated infections.

[0175] Beyond diagnostics, recognizing the roles of peripheral immune tolerance and vascular sequestration in establishing implant-associated dormant infection suggests multiple novel therapeutic avenues. If bacteria can persist by inducing local immune suppression, then intentionally modulating the immune response could help eradicate them as well. This concept is analogous to cancer immunotherapy, where the goal is to break the immune evasion in the tumor microenvironment. One could imagine adjunct treatments that disrupt the tolerant niche or boost local immunity. For example, therapies that disrupt the CXCL5-CXCR2 (SB225002, AZD-8309)61’62or ANGPT1 / TIE2 (BowANGI , AKB-9778)6364axes are already under exploration and might be repurposed to prevent bacteria from exploiting the dormant state. Alternatively, localized immune stimulation at the affected joint could be considered. There is also interest in whether immune checkpoint pathways, such as the programmed death-ligand 1 (PD-L1 ) pathway, may play a role inbacterial persistence; if so, checkpoint inhibitors or other immunomodulators could theoretically be employed to tip the balance in favor of the host immune system.

[0176] This study has limitations that should be considered when interpreting the results. First, we conducted this pilot study under the presumption that biofilm that may not easily found by clinically available culture methods due to the slow growth rate and auxotrophic culture conditions of biofilmresident bacteria and the possibility of sampling bias at the time of surgery, so we did not seek to provide direct evidence of local biofilm per se, such as microscopic analysis of spacers, and instead chose to create a novel set of immunologic biomarkers that would bypass these microbiologic deficiencies and increase the clinical utility of our new paradigm. Second, this is a pilot study, and the corresponding sample size is relatively small, with only 30 analyzed patients. This limited sample size can introduce sampling bias, affecting the generalizability of the findings. Larger, more diverse cohorts are needed to validate the results and ensure they are representative of the broader population after multivariate control. Third, while the molecular methods presented here offer a culture-independent approach to detecting infections, they are not capable of identifying which bacterial species are present. Due to the slow-growing and difficult-to-culture nature of biofilmresident bacteria, culture-based methods of identification are also problematic, and as such bacterial DNA / RNA sequencing of the synovial fluid would be better suited to characterize the microbial landscape. This limitation underscores the need for complementary methods to provide a comprehensive understanding of infection dynamics. Fourth, we did not account for variations in pre- and postoperative prophylactic treatments and other medical interventions, which could modulate the inflammatory response and influence the study outcomes. Standardizing these factors or adjusting for them in the analysis is crucial for more accurate interpretations. Fifth, we identified associations between the proteomic profile and dormant infection, but these associations do not establish causality. Future studies should focus on validating our findings with a larger cohort and longitudinal study to assess the prevalence, characteristics, and progression of dormant infections in joint replacements, as well as the possibility of temporal resolution of dormant infections. Multicenter studies involving diverse patient populations will help establish the sensitivity and specificity of the proposed biomarkers with respect to more traditional diagnostic tests.

[0177] In summary, this study unmasks a highly prevalent, yet previously invisible immunologic footprint of dormant infection, providing proof-of-concept that the host immune response can be leveraged to detect and predict the presence of an occult persistent dormant infection.12 19'22These results pave the way for improved diagnostic accuracy, prognostic insight, and potentially innovative immunotherapeutic strategies for implant-associated infections. We envision five future directions to build on this work. First, retrospective larger series are needed to validate the performance of thebiomarker panel and determine its positive predictive value in a broader population of implant- associated infections. Second, refining the panel to a single practical test will be important for widespread clinical adoption. Third, mechanistic studies are warranted to understand how these proteins contribute to immune evasion. Fourth, time-course studies should examine how dormant infections evolve over time to inform optimal timing for intervention. Fifth, immunomodulatory therapies should be explored in randomized controlled trials to determine safety and efficacy in this patient population. Ultimately, diagnosing and clinically addressing dormant infection before relapse would significantly improve the success of long-term implant retention and infection-free patient outcomes, turning what was once an unseen threat into the next target for precision infection management.REFERENCES

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Ophthalmology 122, 545-554 (2015).Table 1 : Demographic and physiologic characterization joint replacement populations distributed by infection status.Infection StatusASA Classification, units (mean ± SD) 2.6 ± 0.5 2.7 ± 0.5 2.6 ± 0.6 2.5 ± 0.5 Body Mass Index, kg / m2(mean ± SD) 31.0 ± 8.6 30.9 ± 13.4 31 .5 ± 6.8 27.4 ± 5.5 Smokers, active, number (%) 5 (16.7) 2 (28.6) 2 (18.2) 1 (8.3)Co-MorbiditiesAnxiety / Depression, number (%) 8 (26.7) 2 (28.6) 3 (27.3) 3 (25.0) Abuse Disorder, number (%) 5 (16.7) 2 (28.6) 1 (9-1 ) 2 (16.7) Diabetes, number (%) 8 (26.7) 3 (42.9) 4 (36.4) 1 (8-3) Hypertension, number (%) 18 (60.0) 5 (71 .4) 7 (63.6) 6 (50.0) Hyperlipidemia, number (%) 4 (13.3) 2 (28.6) 2 (18.2) 0 (0.0)Coronary Artery Disease, number (%) 3 (10.0) 1 (14.3) 0 (0.0) 2 (16.7) Arrythmia, number (%) 4 (13.3) 1 (14.3) 1 (9-1 ) 2 (16.7)Congestive Heart Failure, number (%) 1 (3.3) 0 (0.0) 1 (9-1 ) 0 (0.0) Pulmonary Disease, number (%) 3 (10.0) 1 (14.3) 2 (18.2) 0 (0.0) Obstructive Sleep Apnea, number (%) 7 (23.3) 1 (14.3) 5 (45.5) 1 (8.3) Cerebral Vascular Accident, number (%) 1 (3.3) 0 (0.0) 0 (0.0) 1 (8.3) Anemia, number (%) 1 (3.3) 0 (0.0) 0 (0.0) 1 (8.3)Osteoporosis, number (%) 1 (3.3) 0 (0.0) 1 (9.1 ) 0 (0.0) Hypothyroidism, number (%) 3 (10.0) 0 (0.0) 1 (9.1 ) 2 (16.7) Prior Thrombosis or Embolism, number (%) 7 (23.3) 3 (42.9) 3 (27.3) 0 (0.0) Hepatitis, number (%) 2 (6.7) 0 (0.0) 1 (9-1 ) 1 (8.3)Renal Failure, number (%) 1 (3.3) 0 (0.0) 1 (9-1 ) 0 (0.0) Cancer, number (%) 1 (3.3) 0 (0.0) 0 (0.0) 1 (8.3)ASA: American Society of Anesthesiologists, SD: Standard Deviation, p<0.05 denoted as * for t-test active to prior, * for t-test prior to none, * for active to none, or#for Chi-square.Table 2: Serum scute phase reactants and synovial neutrophil-based markers of infected joint replacement populations distributed by infection status.Infection StatusMarker of Active InfectionErythrocyte Sedimentation Rate, mm / h (mean ± SD)**C-reactive Protein, mg / dL (mean ± SD)*’*Synovial White Blood Cell Count, Kcells / mL (mean ± SD)* *Percent Polymorphonuclear Neutrophils (mean ± SD)**Culture Positive, number (%)#SD: Standard Deviation, p<0.05 denoted as ' for t-test active to prior,ffor t-test prior to none, * for active to none, or#for Chi-square.Supplementary Table 1AdjustedAssay OlinkID UniProt Estimate Active None Method p-value DifferenceWelch Two SampleMCP-3 OID00755 P80098 2.6 10.5 8.0 t-test 8.3E-05 UPWelch Two SampleCCL17 OID00821 Q92583 2.7 10.8 8.1 t-test 1.4E-04 UPWelch Two SampleADA GID00775 P00813 2.7 10.3 7.6 t-test 3.5E-04 UPWelch Two SampleCCL20 OID00837 P78556 5.1 12.7 7.6 t-test 3.5E-04 UPWelch Two SampleIL6 OID00763 P05231 2.5 13.2 10.7 t-test 3.5E-04 UPWelch Two SampleCXCL1 GID00786 P09341 2.0t-test 7.7E-04 UPWelch Two SampleTNFSF14 OID00787 043557 4.3t-test 1.8E-03 UPWelch Two SampleCXCL5 OID00801 P42830 2.3t-test 2.0E-03 UPWelch Two SampleIL18 OID00782 Q14116 1.6 10.5 8.9 t-test 4.2E-03 UPWelch Two SampleTRAIL OID00769 P50591 2.3 8.7 6.4 t-test 6.8E-03 UPWelch Two SampleTIE2 OID00754 Q02763 1.1 8.7 7.6 t-test 6.8E-03 UPWelch Two SampleARG1 GID00815 P05089 1.9 7.9 5.9 t-test 7.0E-03 UPPDGF Welch Two Sample subunit t-testB GID00790 P01127 3.0 8.9 5.9 7.0E-03 UPWelch Two SampleHGF GID00803 P14210 1.4 13.3 11.9 t-test 7.0E-03 UPWelch Two SampleFGF2 OID00770 P09038 1.8 3.1 1.3 t-test 7.3E-03 UPIL-1 Welch Two Sample alpha OID00757 P01583 6.5 5.5 -1.0 t-test 1.2E-02 UPWelch Two SamplePD-L2 GID00831 Q9BQ51 1.6t-test 1.2E-02 UPWelch Two SampleCXCL11 OID00767 014625 3.1t-test 1.3E-02 UPWelch Two SampleEGF OID00759 P01133 4.1 5.5 1.4 t-test 1.3E-02 UPWelch Two SampleANGPT1 GID00760 Q15389 2.4 6.8 4.4 t-test 1.5E-02 UPWelch Two SampleIL13 OID00836 P35225 1.0 2.0 1.0 t-test 1.5E-02 UPWelch Two SampleVEGFR-2 OID00780 P35968 0.7 8.0 7.3 t-test 1.6E-02 UPWelch Two SampleMCP-2 OID00795 P80075 3.0 10.9 7.8 t-test 1.6E-02 UPWelch Two SampleIL10 OID00809 P22301 2.6 7.5 5.0 t-test 1.9E-02 UPWelch Two SampleNCR1 OID00816 076036 1.0 5.1 4.1 t-test 2.7E-02 UPWelch Two SampleCXCL13 OID00830 043927 1.2 11.3 10.2 t-test 2.9E-02 UPWelch Two SampleTN F OID05554 P01375 2.0 7.1 5.1 t-test 3.3E-02 UPWelch Two SampleMCP-4 OID00768 Q99616 1.5 12.4 10.9 t-test 4.3E-02 UPWelch Two SamplePD-L1 OID00799 Q9NZQ7 1.1 8.2 7.1 t-test 4.5E-02 UPWelch Two SampleCD28 OID00793 P 10747 -1.5 1.8 3.3 t-test 2.0E-03 DOWNMethod AdjustedAssay OlinkID UniProt Estimate Prior None p-value DifferenceWelch Two SampleANGPT1 OID00760 Q15389 3.2 7.5 4.4 t-test 0.001 UPWelch Two SampleVEGFR-2 OID00780 P35968 0.9 8.3 7.3 t-test 0.001 UPWelch Two SampleTRAIL OID00769 P50591 1.6 8.0 6.4 t-test 0.001 UPWelch Two SampleTIE2 OID00754 Q02763 0.7 8.3 7.6 t-test 0.002 UPWelch Two SampleCX3CL1 OID00806 P78423 0.8 4.1 3.2 t-test 0.002 UPWelch Two SampleCXCL11 OID00767 014625 2.0 7.6 5.5 t-test 0.008 UPWelch Two SampleN0S3 OID00777 P29474 1.8 4.3 2.5 t-test 0.008 UPWelch Two SampleEGF OID00759 P01133 4.0 5.3 1.4 t-test 0.017 UPWelch Two SampleMCP-2 OID00795 P80075 1.8 9.6 7.8 t-test 0.025 UPWelch Two SampleCXCL5 OID00801 P42830 2.1 12.6 10.4 t-test 0.025 UPPDGF Welch Two Sample subunit t-testB OID00790 P01127 2.3 8.2 5.9 0.029 UPWelch Two SampleCCL17 OID00821 Q92583 1.6 9.7 8.1 t-test 0.046 UPWelch Two SampleGal-1 OID00798 P09382 -0.4 7.3 7.7 t-test 0.008 DOWNWelch Two SampleIL15 OID05551 P40933 -1.1 8.1 9.2 t-test 0.038 DOWNMethod AdjustedAssay OlinkID UniProt Estimate Active Prior p-value DifferenceWelch Two SampleCXCL1 OID00786 P09341 2.2 12.8 10.6 t-test 0.002 UPWelch Two SampleCCL20 OID00837 P78556 4.1 12.7 8.6 t-test 0.002 UPWelch Two SampleTNFSF14 OID00787 043557 4.1 10.2 6.1 t-test 0.006 UPWelch Two SampleADA OID00775 P00813 2.1 10.3 8.3 t-test 0.006 UPWelch Two SamplePD-L2 OID00831 Q9BQ51 1.7 5.8 4.2 t-test 0.039 UPWelch Two SampleMCP-3 OID00755 P80098 2.8 10.5 7.8 t-test 0.039 UPSupplementary Table 2AdjustedOlinkID UniProt Estimate Dormant None Method p-value DifferenceWelch TwoCXCL11 OID00767 014625 2.4 8.0 5.6 Sample t-test 0.003 UPWelch TwoANGPT1 OID00760 Q15389 3.2 7.8 4.6 Sample t-test 0.003 UPWelch TwoTIE2 OID00754 Q02763 0.7 8.3 7.7 Sample t-test 0.007 UPWelch TwoCXCL5 OID00801 P42830 2.4 12.9 10.5 Sample t-test 0.008 UPWelch TwoCD244 OID00758 Q9BZW8 0.5 6.8 6.3 Sample t-test 0.008 UPWelch TwoVEGFR-2 OID00780 P35968 0.8 8.3 7.5 Sample t-test 0.008 UPWelch TwoTRAIL OID00769 P50591 1.5 8.0 6.6 Sample t-test 0.010 UPWelch TwoNOS3 GID00777 P29474 2.0 4.6 2.6 Sample t-test 0.012 UPPDGF Welch Two subunit B GID00790 P01127 2.9 8.7 5.8 Sample t-test 0.012 UPWelch TwoEGF OID00759 P01133 4.5 6.0 1.5 Sample t-test 0.014 UPWelch TwoCX3CL1 GID00806 P78423 0.8 4.1 3.3 Sample t-test 0.016 UPWelch TwoCCL17 GID00821 Q92583 1.7 9.9 8.2 Sample t-test 0.020 UPWelch TwoIL4 OID00833 P05112 0.5 0.8 0.3 Sample t-test 0.023 UPWelch TwoMCP-2 OID00795 P80075 1.9 9.8 8.0 Sample t-test 0.027 UPWelch TwoGal-1 GID00798 P09382 -0.4 7.2 in Sample t-test 0.012 DOWNMethod AdjustedAssay OlinkID UniProt Estimate Active Dormant p-value DifferenceWelch TwoCCL20 OID00837 P78556 4.0 12.7 8.6 Sample t-test 0.006 UPWelch TwoCXCL1 OID00786 P09341 2.2 12.8 10.6 Sample t-test 0.006 UPWelch TwoTNFSF14 OID00787 043557 3.6 10.2 6.6 Sample t-test 0.020 UPWelch TwoADA OID00775 P00813 1.9 10.3 8.4 Sample t-test 0.020 UPExample 2Methods for Identifying a Dormant Nidus-Associated Infection1. Tissue Level Method for Differentiating Dormant Infection from Uninfected Tissue

[0242] The present method provides a robust and precise approach for distinguishing dormant infections from uninfected tissue by analyzing specific cell types. This method is particularly effective for identifying regulatory T-cells, natural killer cells, plasmacytoid dendritic cells, classical monocytes, and / or myeloid dendritic cells within a periarticular tissue sample in contact with the effective joint space of an implant in question (examples include the suprapatellar pouch in the knee and superior capsule in the hip). a. Harvest Tissue

[0243] Step 1 : Obtain tissue samples from the subject using aseptic techniques. Preferred tissue samples include periarticular tissue sample in contact with the effective joint space of the implant in question (examples include the suprapatellar pouch in the knee and superior capsule in the hip).

[0244] Step 2: For frozen tissue procedures, immediately place the harvested tissue in a cryoprotectant solution (e.g., optimal cutting temperature (OCT) compound) and snap-freeze in liquid nitrogen. Store at -80°C until further processing. b. Process TissueFor Formalin-Fixed Paraffin-Embedded (FFPE) Tissue:

[0245] Step 1 : Remove tissue from preservation solution and proceed with standard paraffin embedding protocols. Dehydrate the tissue through a graded series of alcohols, clear with xylene, and embed in paraffin wax.

[0246] Step 2: Section the tissue using a microtome to obtain thin sections (approximately 5 micrometers thick) for further analysis.For Frozen Tissue:

[0247] Step 1 : Remove the tissue from -80°C storage and allow it to equilibrate to the cryostat temperature (-20°C).

[0248] Step 2: Embed the tissue in optimal cutting temperature (OCT) compound, if not already done.

[0249] Step 3: Section the frozen tissue using a cryostat to obtain thin sections (5-10 micrometers thick). Mount the sections onto pre-cooled microscope slides. c. Section TissueFor FFPE Tissue:

[0250] Step 1 : Mount the paraffin-embedded tissue sections on microscope slides. Ensure that the sections are evenly cut and properly affixed to the slides to avoid detachment during staining procedures.

[0251] Step 2: Dry the slides at 37°C overnight or at 60°C for one hour to ensure adherence.For Frozen Tissue:

[0252] Step 1 : Immediately fix the frozen tissue sections by immersing the slides in cold acetone or 4% paraformaldehyde for 10 minutes.

[0253] Step 2: Air dry the slides for a few minutes at room temperature. d. Stain Tissue SectionsFor FFPE Tissue:

[0254] Step 1 : Perform deparaffinization by immersing the slides in xylene for three consecutive baths (5 minutes each).

[0255] Step 2: Rehydrate the tissue sections through a graded series of ethanol (100%, 95%, 70%, and distilled water).

[0256] Step 3: Apply specific stains to identify the cell types of interest. Use hematoxylin and eosin (H&E) for general tissue morphology.

[0257] Step 4: For specific cell type identification, perform immunohistochemical staining. Use antibodies against markers such as FOXP3 for regulatory T-cells, CD56 for natural killer cells, and CD303 for plasmacytoid dendritic cells.

[0258] Step 5: Develop the stained slides using appropriate secondary antibodies and chromogenic substrates. Counterstain with hematoxylin, if necessary.For Frozen Tissue:

[0259] Step 1 : Perform immunofluorescent staining directly on the fixed frozen sections. Block nonspecific binding sites with a blocking solution (e.g., 5% BSA or normal serum) for 30 minutes at room temperature.

[0260] Step 2: Incubate the sections with primary antibodies specific to the markers of interest (e.g., FOXP3, CD56, CD303) for 1 hour at room temperature or overnight at 4°C.

[0261] Step 3: Wash the sections three times with PBS.

[0262] Step 4: Incubate the sections with appropriate fluorescent-labeled secondary antibodies for 1 hour at room temperature in the dark.

[0263] Step 5: Wash the sections three times with PBS. Counterstain with DAPI to visualize nuclei, if desired. e. Visually Assess for Cell Types

[0264] Step 1 : Examine the stained tissue sections under a light microscope (for chromogenic stains) or a fluorescence microscope (for immunofluorescent stains). Use appropriate magnification (typically 20x to 40x objective) to identify and count the target cells.

[0265] Step 2: For regulatory T-cells, look for FOXP3 positive cells typically found in the tissue periphery or within lymphoid aggregates.

[0266] Step 3: For natural killer cells, identify CD56 positive cells, characterized by their distinctive large granular lymphocyte morphology.

[0267] Step 4: For plasmacytoid dendritic cells, locate CD303 positive cells, generally small and plasmacytoid in appearance.

[0268] Step 5: Record the presence and abundance of these cell types, comparing them between samples from dormant infection and uninfected tissue. Significant differences in cell type distribution and frequency can help distinguish between dormant infections and uninfected tissue.2. Cellular Level Method for Differentiating Dormant Infection from Uninfected Tissue

[0269] The following method provides a detailed approach for distinguishing dormant infections from uninfected tissue at the cellular level by analyzing specific cell types. This method focuses on identifying and quantifying >1 regulatory T-cell, >1 natural killer cell, >1 plasmacytoid dendritic cell,>3 classical monocytes, and / or >18 myeloid dendritic cells based on their size or non-stain parameters. a. Harvest Tissue

[0270] Step 1 : Obtain tissue samples from the subject using aseptic techniques. Preferred tissue samples include periarticular tissue from joint replacements.

[0271] Step 2: Place the harvested tissue in a sterile container with an appropriate preservation solution, such as RPMI-1640 medium supplemented with antibiotics and antifungals, to prevent contamination. b. Digest Tissue

[0272] Step 1 : Mince the tissue into small fragments using sterile scissors or a scalpel.

[0273] Step 2: Transfer the tissue fragments into a digestion buffer containing enzymes such as collagenase D (1 -2 mg / mL) and DNase I (0.1 mg / mL) in RPMI-1640 medium.

[0274] Step 3: Incubate the tissue-digestion mixture at 37°C for 30-60 minutes with gentle agitation to ensure complete dissociation of cells.

[0275] Step 4: Filter the digested tissue through a 70-micrometer cell strainer to remove undigested debris and obtain a single-cell suspension.

[0276] Step 5: Wash the cells with cold PBS containing 2% fetal bovine serum (FBS) to stop the enzymatic digestion. Centrifuge at 300 x g for 5 minutes and discard the supernatant.

[0277] Step 6: Resuspend the cell pellet in an appropriate buffer (e.g., PBS with 2% FBS) for further analysis. c. Count Specific Cell Types

[0278] Step 1 : Prepare the single-cell suspension for flow cytometric analysis or cell sorting.

[0279] Step 2: Use flow cytometry to identify and quantify specific cell types based on their size(forward scatter, FSC) and granularity (side scatter, SSC) or other non-stain parameters.

[0280] Regulatory T-cells (Tregs): Identify Tregs by their characteristic size and scatter properties. Optionally, additional markers such as CD4 and FOXP3 can be used to improve specificity.

[0281] Natural Killer (NK) Cells: Identify NK cells by their size and granularity. Optionally, use additional markers such as CD56.

[0282] Plasmacytoid Dendritic Cells (pDCs): Identify pDCs by their smaller size and specific scatter profile. Optionally, use additional markers such as CD303.

[0283] Classical Monocytes: Identify classical monocytes by their size and scatter properties. Optionally, use additional markers such as CD14 and CD16.

[0284] Myeloid Dendritic Cells (mDCs): Identify mDCs by their size and scatter profile. Optionally, use additional markers such as CD11c and HLA-DR.

[0285] Step 3: Count the cells using flow cytometry or a cell counter equipped to differentiate cells by size and scatter characteristics.

[0286] Criteria:Regulatory T-cells (Tregs): Presence of more than one Treg.Natural Killer (NK) Cells: Presence of more than one NK cell.Plasmacytoid Dendritic Cells (pDCs): Presence of more than one pDC. Classical Monocytes: Presence of more than three classical monocytes. Myeloid Dendritic Cells (mDCs): Presence of more than eighteen mDCs.

[0287] Step 4: Record the presence and abundance of these cell types. Compare the counts between samples from dormant infection and uninfected tissue to identify significant differences that can help distinguish between dormant infections and uninfected tissue.3) Cellular RNA Level (mRNA expression of certain cell types is unique to dormant infection)

[0288] The following method provides a detailed approach for distinguishing dormant infections from uninfected tissue at the gene expression level by analyzing cellular mRNA. This method focuses on identifying cellular gene expression in M1 macrophages (M1 Table), M2 macrophages (M2 Table), and myeloid dendritic cells (MDC Table): a. Harvest Tissue

[0289] Obtain tissue samples from the subject using aseptic techniques. Preferred tissue samples include periarticular tissue from joint replacements or other relevant sources. b. Digest Tissue

[0290] Digest the harvested tissue to dissociate cells into a single-cell suspension. This is achieved using enzymatic digestion buffers containing enzymes such as collagenase and DNase. Optimize the conditions (e.g., temperature, time, and enzyme concentration) to maximize cell yield and viability while preserving cell surface markers.

[0291] Post-digestion, neutralize the enzymes and wash the cells to remove any remnants of the digestion enzymes. c. FACS Sort Cells

[0292] Use Fluorescence-Activated Cell Sorting (FACS) to sort the dissociated cells into specific cell types. Target classically activated M1 macrophages, alternatively activated M2 macrophages, and myeloid dendritic cells for sorting.

[0293] Employ specific surface markers and antibodies to identify and separate the desired cell populations. Ensure the FACS process maintains cell viability and integrity. d. Assess Gene Expression

[0294] Extract RNA from the sorted cell populations and assess gene expression. Use quantitative PCR (qPCR), ddPCR, RNA sequencing, or other suitable methods to measure mRNA levels.

[0295] Focus on genes whose expression patterns are indicative of dormant infection. Analyze the data to identify unique mRNA expression profiles associated with the different cell types.

[0296] This method enables the precise analysis of gene expression in specific immune cell populations, which is crucial for understanding dormant infections. Each step is performed under sterile conditions to prevent contamination and ensure the integrity of the samples and data.4) Bulk RNA Level (mRNA expression from tissue that distinguish dormant infection from uninfected as well as establish dormant infection from both infected and uninfected samples)

[0297] The following method provides a detailed approach for distinguishing dormant infections from uninfected tissue at the gene expression level by analyzing total tissue mRNA. This method focuses on identifying bulk gene expression (Bulk Table) in dormant infection from uninfected as well as distinguishing dormant infection from both from uninfected and infected samples (Both Table). a. Harvest Tissue

[0298] Obtain tissue samples from the subject using aseptic techniques. Preferred tissue samples include periarticular tissue from joint replacements or other relevant sources. b. Digest Tissue

[0299] Digest the harvested tissue to dissociate cells into a single-cell suspension. This is achieved using enzymatic digestion buffers containing enzymes such as collagenase and DNase. Optimizethe conditions (e.g., temperature, time, and enzyme concentration) to maximize cell yield and viability while preserving cell surface markers.

[0300] Post-digestion, neutralize the enzymes and wash the cells to remove any remnants of the digestion enzymes. c. Isolate mRNA

[0301] Isolate mRNA from the digested tissue using an appropriate RNA extraction method, such as column-based purification or magnetic bead separation. Ensure the procedure maintains the integrity and purity of the mRNA.

[0302] Quantify the isolated mRNA and assess its quality using spectrophotometric analysis or an RNA integrity number (RIN) score. d. Assess for 13 Genes Unique to Dormant Infection

[0303] Use quantitative PCR (qPCR), RNA sequencing, or another suitable method to assess the expression of 13 genes unique to dormant infection.

[0304] Analyze the expression levels of these genes in the bulk mRNA to identify patterns indicative of dormant infection.

[0305] Use appropriate controls and normalization techniques to ensure accurate and reliable gene expression measurements.

[0306] This method allows for the comprehensive analysis of mRNA expression in tissue samples, which is crucial for identifying markers of dormant infection. Each step is performed under sterile conditions to prevent contamination and ensure the integrity of the samples and data.5) Synovial Protein Level (3 synovial proteins are unique to dormant infection)

[0307] The following method provides a detailed approach for distinguishing dormant infections from uninfected tissue by analyzing synovial protein levels. This method focuses on identifying normalized protein expression in synovial fluid (Synovial Table). a. Harvest Synovial Fluid

[0308] Obtain synovial fluid samples from the subject using aseptic techniques. Preferred collection sites include joints with suspected infection or inflammation.

[0309] Collect the synovial fluid using a sterile syringe and transfer it into a suitable collection tube. Immediately place the samples on ice and process them as soon as possible to preserve protein integrity. b. Assess for CXCL13 and / or CXCL5 Expression Along with IL-7 Depletion

[0310] Use enzyme-linked immunosorbent assay (ELISA), Luminex multiplex assay, or another suitable protein detection method to assess the expression levels of CXCL13 and / or CXCL5 in the synovial fluid samples.

[0311] Simultaneously, measure the depletion levels of IL-7 in the same samples. Ensure that appropriate standards and controls are included to validate the assay results. Quantify the protein levels and compare them to known benchmarks or control samples to identify patterns indicative of dormant infection.

[0312] This method allows for the precise measurement of synovial proteins, which is crucial for diagnosing dormant infections based on protein expression profiles. Each step is performed under sterile conditions to prevent contamination and ensure the integrity of the samples and data.6) Plasma Protein Level (9 plasma proteins are unique to dormant infection)

[0313] The following method provides a detailed approach for distinguishing dormant infections from uninfected tissue by analyzing plasma protein levels. This method focuses on identifying normalized protein expression in plasma (Plasma Table). a. Harvest Whole Blood

[0314] Obtain whole blood samples from the subject using aseptic techniques. Preferred collection sites include veins with adequate blood flow.

[0315] Collect the blood using a sterile syringe and transfer it into EDTA-coated or heparin-coated tubes to prevent clotting. Immediately place the samples on ice and process them as soon as possible to preserve plasma integrity. b. Isolate Plasma

[0316] Centrifuge the collected blood samples at 1 ,500-2,000 x g for 10-15 minutes at 4°C to separate the plasma from the cellular components.

[0317] Carefully transfer the plasma layer to a new tube without disturbing the buffy coat. Store the isolated plasma at -80°C until further analysis.c. Assess for EGF, GZMN, FGF2, PTN, MMP12 Expression Along with CXCL5, CD70, CD28, LAMP3 Depletion

[0318] Use enzyme-linked immunosorbent assay (ELISA) or the Luminex multiplex assay to assess EGF, GZMN, FGF2, PTN, and MMP12 expression levels in the plasma samples.

[0319] Simultaneously, measure the depletion levels of CXCL5, CD70, CD28, and LAMP3 in the same samples. Ensure that appropriate standards and controls are included to validate the assay results.

[0320] Quantify the protein levels and compare them to known benchmarks or control samples to identify patterns indicative of dormant infection.

[0321] This method allows for the precise measurement of plasma proteins, which is crucial for diagnosing dormant infections based on protein expression profiles. Each step is performed under sterile conditions to prevent contamination and ensure the integrity of the samples and data.Table 1 : Differentially Expressed mRNA transcripts that Distinguish Dormant Infection from Both Uninfected Tissue and Non-Dormant Infected TissueGene TranscriptsCXCL1 3176TNF 692JUN 8334IRF8 11165CD22 770QPCT 6029PIK3AP1 14609VSIG4 65595CXCL2 49314HLA.DQB1 253212TNFSF13 21477C1QB 388202PCNA 4035LAM Pl 132989Table 2: Differentially Expressed Transcripts in Bulk mRNA Associated with DormantInfectionGene TranscriptsVSIG4 < 76829FN1 < 886896C1QB < 409741IFITM3 > 26543IL3RA < 14325ITGAM < 42456RNASE2 > 673DUSP1 < 108643PIK3AP1 < 15327CD2 > 1204SLC7A7 < 10078CD9 < 64870CST7 > 4029CXCL5 > 16808TNFSF13 < 21220LAMP1 < 146617CD6 > 1005QPCT < 6729CCR7 > 2683TLR8 < 2270SLC25A37 > 2144LIPA < 100850CD163 < 160317IGKC > 1945CD52 < 58436CXCL1 > 2939LAT2 > 3102CD48 > 3441ITGAE < 9395DUSP4 > 2731PCNA < 4258S100A12 > 1268FYN > 6025FCN1 > 10619CXCR3 > 906APOE < 1422CXCL8 > 59301GNLY > 1343CD7 > 478FCGR3A < 132738FOSB > 12255PIK3IP1 < 7189DUSP2 > 4292IL32 > 4423KCNE3 < 2712IRF8 < 10353ITGA4 > 795IL1R2 > 1107CTSW > 270TREM1 < 14348BIRC3 > 2069DOCK8 < 2887MMP9 > 12239CTSD < 191347TRAC > 505CLEC4E > 3167IL1B > 4001IRF4 > 542LAT > 984SELL > 1355APOBEC3G > 1387FAS > 1145IER3 > 18281CCL5 > 3428IL15RA > 793CCL20 > 7652PRDM1 > 1557CLEC10A > 3833CCND2 > 394CD22 < 724TBX21 > 366PDCD1 > 58CD72 > 1815DPP4 > 1901THBS1 > 7921IL6 > 2270IL1RN > 4329CD28 < 517GIMAP5 > 493STAT4 > 778IL12RB1 > 517CHI3L1 < 33071LEF1 > 195TNF > 757IL7R > 6749LIF > 755ADGRE1 > 332F5 > 319MITF < 2227FCER1A > 2410CD34 > 888CD244 > 270Table 3: Differentially Expressed mRNA in M1 macrophages Associated with DormantInfectionGene TranscriptsVSIG4 < 55908 FN1 < 572640 IGLC3 > 935 ITGAM < 30597 DUSP1 < 72496 CXCL5 > 16564 C1QB < 316093 LIPA < 63260 CD9 < 41719 IFITM3 > 17489 SLC7A7 < 6962 IL3RA < 10138 IGKC > 724 LAMP1 < 103017C10orf54 > 6538 CD52 < 36913 SLC25A37 > 1634 CLEC4E > 2471 MMP9 > 9200QPCT < 4219CXCL8 47869FOSB > 8275CXCL2 > 40092DUSP4 > 1421CD48 > 2256IL1RN > 3280LAT2 > 2370IER3 > 15107PIK3IP1 < 4364CXCL3 > 32379KCNE3 < 1834PRDM1 > 1154CCR7 > 800LY86 > 2936ALAS2 > 1761IL1B > 2452TLR8 < 1621CXCL1 > 2264RNASE2 > 420DPP4 > 1621IL15RA > 606CLEC10A > 1360TBX21 > 266CCL4 > 6028TNF > 657CD28 < 408IL12RB1 > 390LAT > 609IL1R2 > 264PCNA < 2567S100A12 > 421STAT4 > 299CCL20 > 6886ITGA4 > 395KIAA0101 > 625CD72 > 1254FAS > 717IL7R > 4527UBE2C > 583CD209 > 457Table 4: Differentially Expressed mRNA in M2 macrophages Associated with DormantInfectionGene TranscriptsC1QB < 23270 IER3 > 744 LAMP1 < 12391 IFITM3 > 3705 FN1 < 78622 FYN > 805 TNFSF13 < 1556 JUN > 2015 ITGAM < 3537 SLC25A37 > 269 LAT2 > 332 FCGR3A < 7128 ITGAE < 865 FOSB > 2138 C10orf54 > 865 SELL > 181 LY86 > 323 SLC7A7 < 720 CD52 < 4911 IFITM2 > 648 C1QA < 10856 CD9 < 6271 ADA > 560 CXCL5 > 420 VPS28 > 875 CTSD < 13258 CD14 < 5394 LIPA < 8042 VEGFA > 1382 DOCK8 < 274 ITGB2 < 16687 CXCL2 > 1299 THBD > 799 CXCL8 > 1361 LILRB4 < 2283 IRF8 < 835Table 5: Differentially Expressed mRNA in Myeloid Dendritic Cells (MDC) Associated with Dormant InfectionGene TranscriptsCST7 > 1145VSIG4 < 1305IFITM2 > 633IFITM3 > 1815FN1 < 9827C1QB < 9925C1QA < 6429FCN1 > 1164THBS1 > 1084CD9 < 1238ITGAM < 1232Table 5: Differentially Expressed Synovial Proteins Associated with Dormant InfectionAssay Normalized ExpressionCXCL13 > 9.73IL7 < 5.69CXCL5 > 10.97Table 6: Differentially Expressed Plasma Proteins Associated with Dormant InfectionProtein Normalized ExpressionCD70 < 4.00CXCL5 < 11.28PTN > 1.98EGF < 7.03GZMH < 4.09FGF2 < 1.96MMP12 > 7.73CD28 < 0.56LAMP3 < 5.99

Claims

What is claimed is:1 . A method of diagnosing and treating a periprosthetic joint infection in a patient, the method comprising:(a) obtaining a synovial fluid sample from the patient;(b) measuring levels of one or more biomarkers selected from C-X-C motif chemokine ligand 5 (CXCL5), platelet derived growth factor subunit B (PDGF-B), galectin-1 (Gal-1 ), C-X-C motif chemokine ligand 11 (CXCL11 ), angiopoietin 1 (ANGPT1 ), epidermal growth factor (EGF), TEK receptor tyrosine kinase (TIE2), monocyte chemoattractant protein 2 (MCP-2), CD244 molecule (CD244), and nitric oxide synthase 3 (NOS3), and one or more biomarkers selected from adenosine deaminase (ADA), C-X-C motif chemokine ligand 1 (CXCL1 ), C-C motif chemokine ligand 20 (CCL20), and tumor necrosis factor superfamily member 14 (TNFSF14) in the synovial fluid sample;(c) diagnosing the patient, wherein increased levels of the one or more biomarkers selected from CXCL5, PDGF-B, CXCL11 , ANGPT1 , EGF, TIE2, MCP-2, CD244, and NOS3, increased levels of the one or more biomarkers selected from ADA, CXCL1 , CCL20, and TNFSF14, and decreased levels of the Gal-1 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from an uninfected control subject indicate that the patient has the periprosthetic joint infection; and(d) treating the patient diagnosed with the periprosthetic joint infection to eradicate the periprosthetic joint infection.

2. The method of claim 1 , wherein said treating comprises removal of an infected joint implant, debridement of the joint, placement of an antibiotic spacer, oral or intravenous antibiotic therapy with an antibiotic, replacement of the infected joint implant with a new joint implant, or any combination thereof.

3. The method of claim 1 or 2, wherein said measuring the levels of the one or more biomarkers comprises measuring the levels of ADA, CXCL1 , CCL20, and TNFSF14 in the synovial fluid sample of the patient, wherein increased levels of the ADA, CXCL1 , CCL20, and TNFSF14 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from a subject with a dormant periprosthetic joint infection indicate that the patient has an active periprosthetic joint infection; and wherein decreased levels of the ADA, CXCL1 , CCL20, and TNFSF14 in the synovial fluid sample of the patient compared to reference value ranges for asynovial fluid sample from a subject with an active periprosthetic joint infection indicate that the patient has a dormant periprosthetic joint infection.

4. The method of any one of claims 1 -3, wherein said measuring the levels of the one or more biomarkers comprises measuring the levels of the CXCL5, PDGF-B, Gal-1 , CXCL11 , ANGPT 1 , EGF, TIE2, MCP-2 (CCL8), CD244, and NOS3 in the synovial fluid sample of the patient, wherein decreased levels of the CXCL5, PDGF-B, CXCL11 , ANGPT1 , EGF, TIE2, MCP-2 (CCL8), CD244, and NOS3 and increased levels of the Gal-1 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from a subject with a dormant periprosthetic joint infection indicate that the patient does not have a periprosthetic joint infection; and wherein increased levels of the CXCL5, PDGF-B, CXCL11 , ANGPT1 , EGF, TIE2, MCP-2 (CCL8), CD244, and NOS3 and decreased levels of the Gal-1 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from the uninfected control subject indicate that the patient has a dormant periprosthetic joint infection.

5. The method of any one of claims 1 -4, wherein said measuring the levels of the one or more biomarkers comprises performing an enzyme-linked immunosorbent assay (ELISA), a radioimmunoassay (RIA), an immunofluorescent assay (IFA), immunohistochemistry, fluorescence- activated cell sorting (FACS), a Western Blot, mass spectrometry, tandem mass spectrometry, an aptamer-based assay, an enzymatic or biochemical assay, liquid chromatography, or nuclear magnetic resonance (NMR).

6. The method of claim 5, wherein the ELISA is performed using a multiplex ELISA array.

7. The method of any one of claims 1 -6, wherein the patient has a joint replacement implant, optionally wherein the joint replacement implant was treated for an infection previously.

8. The method of claim 7, wherein the joint replacement implant is in a hip, knee, shoulder, ankle, or other joint.

9. A method of monitoring a patient with a joint implant for development of an active periprosthetic joint infection, the method comprising:(a) obtaining a first synovial fluid sample from the patient at a first time point and a second synovial fluid sample from the patient later at a second time point;(b) measuring levels of one or more biomarkers selected from ADA, CXCL1 , CCL20, and TNFSF14 in the first synovial fluid sample and the second synovial fluid sample; and(c) analyzing the levels of the one or more biomarkers in conjunction with respective reference value ranges for said biomarkers, wherein detection of increased levels of the one or more biomarkers selected from selected from ADA, CXCL1 , CCL20, and TNFSF14 in the second synovial fluid sample compared to the first synovial fluid sample indicate that the patient is developing an active periprosthetic joint infection, and detection of decreased levels of expression of the one or more biomarkers selected from ADA, CXCL1 , CCL20, and TNFSF14 in the second synovial fluid sample compared to the first synovial fluid sample indicate that the patient is not developing an active periprosthetic joint infection.

10. The method of claim 9, further comprising treating the patient developing an active periprosthetic joint infection to eradicate the periprosthetic joint infection.1 1 . The method of claim 10, wherein said treating comprises removal of the infected joint implant, debridement of the joint, placement of an antibiotic spacer, oral or intravenous antibiotic therapy with an antibiotic, replacement of the infected joint implant with a new joint implant, or any combination thereof.

12. A kit comprising agents for detecting C-X-C motif chemokine ligand 5 (CXCL5), platelet derived growth factor subunit B (PDGF-B), galectin-1 (Gal-1 ), C-X-C motif chemokine ligand 11 (CXCL11 ), angiopoietin 1 (ANGPT1 ), epidermal growth factor (EGF), TEK receptor tyrosine kinase, also known as tyrosine kinase with Ig and EGF homology domains-2 (TIE2), C-C motif chemokine ligand 8 (CCL8) also known as monocyte chemoattractant protein 2 (MCP-2), CD244 molecule (CD244), nitric oxide synthase 3 (NOS3), adenosine deaminase (ADA), C-X-C motif chemokine ligand 1 (CXCL1 ), C-C motif chemokine ligand 20 (CCL20), and tumor necrosis factor superfamily member 14 (TNFSF14).

13. The kit of claim 12, further comprising reagents for performing an immunoassay.

14. The kit of claim 12 or 13, wherein the kit comprises an antibody or aptamer that specifically binds to CXCL5, an antibody or aptamer that specifically binds to PDGF-B, an antibodyor aptamer that specifically binds to Gal-1 , an antibody or aptamer that specifically binds to CXCL11 , an antibody or aptamer that specifically binds to ANGPT 1 , an antibody or aptamer that specifically binds to EGF, an antibody or aptamer that specifically binds to TIE2, an antibody or aptamer that specifically binds to MCP-2 (CCL8), an antibody or aptamer that specifically binds to CD244, an antibody or aptamer that specifically binds to NOS3, an antibody or aptamer that specifically binds to ADA, an antibody or aptamer that specifically binds to CXCL1 , an antibody or aptamer that specifically binds to CCL20, and an antibody or aptamer that specifically binds to TNFSF14.

15. The kit of any one of claims 12-14, further comprising instructions for determining whether a patient has an active or dormant periprosthetic joint infection.

16. A protein selected from the group consisting of C-X-C motif chemokine ligand 5 (CXCL5), platelet derived growth factor subunit B (PDGF-B), galectin-1 (Gal-1 ), C-X-C motif chemokine ligand 11 (CXCL1 1 ), angiopoietin 1 (ANGPT1 ), epidermal growth factor (EGF), TEK receptor tyrosine kinase, also known as tyrosine kinase with Ig and EGF homology domains-2 (TIE2), C-C motif chemokine ligand 8 (CCL8) also known as monocyte chemoattractant protein 2 (MCP-2), CD244 molecule (CD244), nitric oxide synthase 3 (NOS3), adenosine deaminase (ADA), C-X-C motif chemokine ligand 1 (CXCL1 ), C-C motif chemokine ligand 20 (CCL20), and tumor necrosis factor superfamily member 14 (TNFSF14) for use as a biomarker in diagnosing a periprosthetic joint infection.

17. A composition comprising one or more biomarkers selected from C-X-C motif chemokine ligand 5 (CXCL5), platelet derived growth factor subunit B (PDGF-B), galectin-1 (Gal-1 ), C-X-C motif chemokine ligand 11 (CXCL11 ), angiopoietin 1 (ANGPT1 ), epidermal growth factor (EGF), TEK receptor tyrosine kinase (TIE2), monocyte chemoattractant protein 2 (MCP-2), CD244 molecule (CD244), and nitric oxide synthase 3 (NOS3), and one or more biomarkers selected from adenosine deaminase (ADA), C-X-C motif chemokine ligand 1 (CXCL1 ), C-C motif chemokine ligand 20 (CCL20), and tumor necrosis factor superfamily member 14 (TNFSF14) for use in diagnosing a periprosthetic joint infection.

18. An in vitro method of diagnosing a periprosthetic joint infection, the method comprising:(a) obtaining a synovial fluid sample from the patient;(b) measuring levels of one or more biomarkers selected from C-X-C motif chemokine ligand 5 (CXCL5), platelet derived growth factor subunit B (PDGF-B), galectin-1 (Gal-1 ), C-X-C motif chemokine ligand 11 (CXCL11 ), angiopoietin 1 (ANGPT1 ), epidermal growth factor (EGF), TEK receptor tyrosine kinase (TIE2), monocyte chemoattractant protein 2 (MCP-2), CD244 molecule (CD244), and nitric oxide synthase 3 (NOS3), and one or more biomarkers selected from adenosine deaminase (ADA), C-X-C motif chemokine ligand 1 (CXCL1 ), C-C motif chemokine ligand 20 (CCL20), and tumor necrosis factor superfamily member 14 (TNFSF14) in the synovial fluid sample; and(c) diagnosing the patient, wherein increased levels of the one or more biomarkers selected from CXCL5, PDGF-B, CXCL11 , ANGPT1 , EGF, TIE2, MCP-2, CD244, and NOS3, increased levels of the one or more biomarkers selected from ADA, CXCL1 , CCL20, and TNFSF14, and decreased levels of the Gal-1 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from an uninfected control subject indicate that the patient has the periprosthetic joint infection.

19. The method of claim 18, wherein said measuring the levels of the one or more biomarkers comprises measuring the levels of ADA, CXCL1 , CCL20, and TNFSF14 in the synovial fluid sample of the patient, wherein increased levels of the ADA, CXCL1 , CCL20, and TNFSF14 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from a subject with a dormant periprosthetic joint infection indicate that the patient has an active periprosthetic joint infection; and wherein decreased levels of the ADA, CXCL1 , CCL20, and TNFSF14 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from a subject with an active periprosthetic joint infection indicate that the patient has a dormant periprosthetic joint infection.

20. The method of claim 18 or 19, wherein said measuring the levels of the one or more biomarkers comprises measuring the levels of the CXCL5, PDGF-B, Gal-1 , CXCL11 , ANGPT 1 , EGF, TIE2, MCP-2 (CCL8), CD244, and NOS3 in the synovial fluid sample of the patient, wherein decreased levels of the CXCL5, PDGF-B, CXCL11 , ANGPT1 , EGF, TIE2, MCP-2 (CCL8), CD244, and NOS3 and increased levels of the Gal-1 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from a subject with a dormant periprosthetic joint infection indicate that the patient does not have a periprosthetic joint infection; andwherein increased levels of the CXCL5, PDGF-B, CXCL1 1 , ANGPT1 , EGF, TIE2, MCP-2 (CCL8), CD244, and NOS3 and decreased levels of the Gal-1 in the synovial fluid sample of the patient compared to reference value ranges for a synovial fluid sample from an uninfected control subject indicate that the patient has a dormant periprosthetic joint infection.21 . The method of any one of claims 18-20, wherein said measuring the levels of the one or more biomarkers comprises performing an enzyme-linked immunosorbent assay (ELISA), a radioimmunoassay (RIA), an immunofluorescent assay (IFA), immunohistochemistry, fluorescence- activated cell sorting (FACS), a Western Blot, mass spectrometry, tandem mass spectrometry, an aptamer-based assay, an enzymatic or biochemical assay, liquid chromatography, or nuclear magnetic resonance (NMR).

22. The method of claim 21 , wherein the ELISA is performed using a multiplex ELISA array.

23. The method of any one of claims 18-22, wherein the patient has a joint replacement implant, optionally wherein the joint replacement implant was treated for an infection previously.

24. The method of claim 23, wherein the joint replacement implant is in a hip, knee, shoulder, ankle, or other joint.

25. A method of diagnosing a dormant bacterial infection in a patient, the method comprising: obtaining a tissue sample from the patient; dissociating the tissue sample into a plurality of cells; separating activated M1 macrophages, activated M2 macrophages, and / or myeloid dendritic cells from other cells of the plurality; measuring levels of one or more messenger RNA (mRNA) transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , ITGAM, C1 QB, LIPA, CD9, DUSP1 , SLC7A7, IL3RA, LAMP1 , QPCT, CD52, PIK3IP1 , KCNE3, CD28, TLR8, PCNA, IGLC3, CXCL5, IFITM3, IGKC, C10orf54, SLC25A37, CLEC4E, MMP9, CXCL8, FOSB, CXCL2, DUSP4, CD48, IL1 RN, LAT2, IER3, CXCL3, PRDM1 , CCR7, LY86, ALAS2, IL1 B, CXCL1 , RNASE2, DPP4, IL15RA, CLEC10A, TBX21 , CCL4, TNF, IL12RB1 , LAT, IL1 R2, S100A12, STAT4, CCL20, ITGA4, KIAA0101 , CD72, FAS, IL7R, UBE2C, and CD209 in the activated M1 macrophages, wherein decreased levelsof the one or more mRNA transcripts of the one or more genes selected from the group consisting of VSIG4, FN1 , ITGAM, C1 QB, LIPA, CD9, DUSP1 , SLC7A7, IL3RA, LAMP1 , QPCT, CD52, PIK3IP1 , KCNE3, CD28, TLR8, and PCNA, and increased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of IGLC3, CXCL5, IFITM3, IGKC, C10orf54, SLC25A37, CLEC4E, MMP9, CXCL8, FOSB, CXCL2, DUSP4, CD48, IL1 RN, LAT2, IER3, CXCL3, PRDM1 , CCR7, LY86, ALAS2, IL1 B, CXCL1 , RNASE2, DPP4, IL15RA, CLEC10A, TBX21 , CCL4, TNF, IL12RB1 , LAT, IL1 R2, S100A12, STAT4, CCL20, ITGA4, KIAA0101 , CD72, FAS, IL7R, UBE2C, and CD209 in the activated M1 macrophages from the patient compared to reference value ranges for the levels of the one or more mRNA transcripts in M1 macrophages from an uninfected tissue sample indicate that the patient has the dormant bacterial infection; measuring levels of one or more mRNA transcripts of one or more genes selected from the group consisting of 01 QB, LAMP1 , FN1 , TNFSF13, FCGR3A, ITGAE, SLC7A7, CD52, C1 QA, CD9, ITGAM, CTSD, CD14, LIPA, DOCK8, ITGB2, LILRB4, IRF8, IER3, IFITM3, FYN, JUN, SLC25A37, LAT2, FOSB, C10orf54, SELL, LY86, IFITM2, ADA, CXCL5, VPS28, VEGFA, CXCL2, THBD, and CXCL8 in the activated M2 macrophages, wherein decreased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of C1 QB, LAMP1 , FN1 , TNFSF13, FCGR3A, ITGAE, SLC7A7, CD52, C1 QA, CD9, ITGAM, CTSD, CD14, LIPA, DOCK8, ITGB2, LILRB4, and IRF8, and increased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of IER3, IFITM3, FYN, JUN, SLC25A37, LAT2, FOSB, C10orf54, SELL, LY86, IFITM2, ADA, CXCL5, VPS28, VEGFA, CXCL2, THBD, and CXCL8 in the activated M2 macrophages from the patient compared to reference value ranges for the levels of the one or more mRNA transcripts in M2 macrophages from an uninfected tissue sample indicate that the patient has the dormant bacterial infection; and / or measuring levels of one or more mRNA transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , C1 QB, C1 QA, CD9, ITGAM, CST7, IFITM2, IFITM3, FCN1 , and THBS1 in the activated myeloid dendritic cells, wherein decreased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of VSIG4, FN1 , C1 QB, 01 QA, CD9, and ITGAM, and increased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of CST7, IFITM2, IFITM3, FCN1 , and THBS1 in the myeloid dendritic cells from the patient compared to reference value ranges for the levels of the one or more mRNA transcripts in the myeloid dendritic cells from an uninfected tissue sample indicate that the patient has the dormant bacterial infection.

26. The method of claim 25, further comprising treating the patient diagnosed with the dormant bacterial infection to eradicate the dormant bacterial infection.

27. The method of claim 26, wherein said treating comprises removal of an infected joint implant, debridement of the joint, placement of an antibiotic spacer, oral or intravenous antibiotic therapy with an antibiotic, replacement of the infected joint implant with a new joint implant, or any combination thereof.

28. A composition comprising one or more messenger RNA (mRNA) transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , ITGAM, C1 QB, LIPA, CD9, DUSP1 , SLC7A7, IL3RA, LAMP1 , QPCT, CD52, PIK3IP1 , KCNE3, CD28, TLR8, PCNA, IGLC3, CXCL5, IFITM3, IGKC, C10orf54, SLC25A37, CLEC4E, MMP9, CXCL8, FOSB, CXCL2, DUSP4, CD48, IL1 RN, LAT2, IER3, CXCL3, PRDM1 , CCR7, LY86, ALAS2, IL1 B, CXCL1 , RNASE2, DPP4, IL15RA, CLEC1 OA, TBX21 , CCL4, TNF, IL12RB1 , LAT, IL1 R2, S100A12, STAT4, CCL20, ITGA4, KIAA0101 , CD72, FAS, IL7R, UBE2C, and CD209 in activated M1 macrophages; one or more mRNA transcripts of one or more genes selected from the group consisting of C1QB, LAMP1 , FN1 , TNFSF13, FCGR3A, ITGAE, SLC7A7, CD52, C1 QA, CD9, ITGAM, CTSD, CD14, LIPA, DOCK8, ITGB2, LILRB4, IRF8, IER3, IFITM3, FYN, JUN, SLC25A37, LAT2, FOSB, C10orf54, SELL, LY86, IFITM2, ADA, CXCL5, VPS28, VEGFA, CXCL2, THBD, and CXCL8 in activated M2 macrophages, and one or more mRNA transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , 01 QB, C1 QA, CD9, ITGAM, CST7, IFITM2, IFITM3, FCN1 , and THBS1 in the activated myeloid dendritic cells for use in diagnosing a dormant bacterial infection.

29. A method of diagnosing a dormant bacterial infection in a patient, the method comprising: obtaining a tissue sample from the patient; measuring levels of one or more messenger RNA (mRNA) transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , C1QB, IL3RA, ITGAM, DUSP1 , PIK3AP1 , SLC7A7, CD9, TNFSF13, LAMP1 , QPCT, TLR8, LIPA, CD163, CD52, ITGAE, PCNA, APOE, FCGR3A, PIK3IP1 , KCNE3, IRF8, TREM1 , DOCK8, CTSD, CD22, CD28, CHI3L1 , MITF, IFITM3, RNASE2, CD2, CST7, CXCL5, CD6, CCR7, SLC25A37, IGKC, CXCL1 , LAT2, CD48, DUSP4, S100A12, FYN, FCN1 , CXCR3, CXCL8, GNLY, CD7, FOSB, DUSP2, IL32, ITGA4, IL1 R2, CTSW, BIRC3, MMP9, TRAC, CLEC4E, IL1 B, IRF4, LAT, SELL, APOBEC3G, FAS, IER3, CCL5, IL15RA, CCL20, PRDM1 , CLEC1 OA, CCND2, TBX21 , PDCD1 , CD72, DPP4, THBS1 , IL6, IL1 RN, GIMAP5,STAT4, IL12RB1 , LEF1 , TNF, IL7R, LIF, ADGRE1 , F5, FCER1A, CD34, and CD244 in the tissue sample; and diagnosing the patient, wherein decreased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of VSIG4, FN1 , C1 QB, IL3RA, ITGAM, DUSP1 , PIK3AP1 , SLC7A7, CD9, TNFSF13, LAMP1 , QPCT, TLR8, LIPA, CD163, CD52, ITGAE, PCNA, APOE, FCGR3A, PIK3IP1 , KCNE3, IRF8, TREM1 , DOCK8, CTSD, CD22, CD28, CHI3L1 , and MITF, and increased levels of the one or more mRNA transcripts of the one or more genes selected from the group consisting of IFITM3, RNASE2, CD2, CST7, CXCL5, CD6, CCR7, SLC25A37, IGKC, CXCL1 , LAT2, CD48, DUSP4, S100A12, FYN, FCN1 , CXCR3, CXCL8, GNLY, CD7, FOSB, DUSP2, IL32, ITGA4, IL1 R2, CTSW, BIRC3, MMP9, TRAC, CLEC4E, IL1 B, IRF4, LAT, SELL, APOBEC3G, FAS, IER3, CCL5, IL15RA, CCL20, PRDM1 , CLEC10A, CCND2, TBX21 , PDCD1 , CD72, DPP4, THBS1 , IL6, IL1 RN, GIMAP5, STAT4, IL12RB1 , LEF1 , TNF, IL7R, LIF, ADGRE1 , F5, FCER1A, CD34, and CD244 in the tissue sample from the patient compared to reference value ranges for the levels of the one or more mRNA transcripts in an uninfected tissue sample indicate that the patient has the dormant bacterial infection.

30. The method of claim 29, further comprising treating the patient diagnosed with the dormant bacterial infection to eradicate the dormant bacterial infection.31 . The method of claim 30, wherein said treating comprises removal of an infected joint implant, debridement of the joint, placement of an antibiotic spacer, oral or intravenous antibiotic therapy with an antibiotic, replacement of the infected joint implant with a new joint implant, or any combination thereof.

32. The method of any one of claims 29-31 , wherein the one or more genes comprise CXCL1 , TNF, JUN, IRF8, CD22, QPCT, PIK3AP1 , VSIG4, CXCL2, HLA.DQB1 , TNFSF13, C1 QB, PCNA, and LAMP1.

33. The method of any one of claims 29-32, wherein the tissue sample is a periarticular tissue sample.

34. The method of any one of claims 29-33, wherein the tissue sample is in contact with a joint space containing an implant.

35. The method of claim 34, wherein the joint space is a suprapatellar pouch in a knee or a superior capsule in a hip.

36. The method of any one of claims 29-35, wherein the tissue sample is from a nidus of the dormant bacterial infection.

37. The method of any one of claims 29-36, where said dissociating the tissue comprises digesting the tissue sample with a collagenase.

38. A composition comprising one or more messenger RNA (mRNA) transcripts of one or more genes selected from the group consisting of VSIG4, FN1 , C1 QB, IL3RA, ITGAM, DUSP1 , PIK3AP1 , SLC7A7, CD9, TNFSF13, LAMP1 , QPCT, TLR8, LIPA, CD163, CD52, ITGAE, PCNA, APOE, FCGR3A, PIK3IP1 , KCNE3, IRF8, TREM1 , DOCK8, CTSD, CD22, CD28, CHI3L1 , MITF, IFITM3, RNASE2, CD2, CST7, CXCL5, CD6, CCR7, SLC25A37, IGKC, CXCL1 , LAT2, CD48, DUSP4, S100A12, FYN, FCN1 , CXCR3, CXCL8, GNLY, CD7, FOSB, DUSP2, IL32, ITGA4, IL1 R2, CTSW, BIRC3, MMP9, TRAC, CLEC4E, IL1 B, IRF4, LAT, SELL, APOBEC3G, FAS, IER3, CCL5, IL15RA, CCL20, PRDM1 , CLEC10A, CCND2, TBX21 , PDCD1 , CD72, DPP4, THBS1 , IL6, IL1 RN, GIMAP5, STAT4, IL12RB1 , LEF1 , TNF, IL7R, LIF, ADGRE1 , F5, FCER1A, CD34, and CD244 for use in diagnosing a dormant bacterial infection.

39. A method of diagnosing a dormant bacterial infection in a patient, the method comprising: obtaining a blood or plasma sample from the patient; measuring levels of one or more biomarker proteins selected from the group consisting of CD70, C-X-C motif chemokine ligand 5 (CXCL5), epidermal growth factor (EGF), granzyme H (GZMH), fibroblast growth factor 2 (FGF2), CD28, lysosomal associated membrane protein 3 (LAMP3), pleiotrophin (PTN), and matrix metallopeptidase 12 (MMP12) in the blood or plasma sample; and diagnosing the patient, wherein decreased levels of one or more biomarker proteins selected from the group consisting of CD70, CXCL5, EGF, GZMH, FGF2, CD28, and LAMP3, and increased levels of the one or more biomarker proteins selected from the group consisting of PTN and MMP12 in the blood or plasma sample from the patient compared to reference value ranges for the levels of the one or more biomarker proteins in a blood or plasma sample from an uninfected subject indicate that the patient has the dormant bacterial infection.

40. The method of claim 39, further comprising treating the patient diagnosed with the dormant bacterial infection.41 . The method of claim 40, wherein said treating comprises removal of an infected joint implant, debridement of the joint, placement of an antibiotic spacer, oral or intravenous antibiotic therapy with an antibiotic, replacement of the infected joint implant with a new joint implant, or any combination thereof.

42. A composition comprising one or more biomarker proteins selected from the group consisting of CD70, C-X-C motif chemokine ligand 5 (CXCL5), epidermal growth factor (EGF), granzyme H (GZMH), fibroblast growth factor 2 (FGF2), CD28, lysosomal associated membrane protein 3 (LAMP3), pleiotrophin (PTN), and matrix metallopeptidase 12 (MMP12)for use in diagnosing a dormant bacterial infection.

43. A method of diagnosing a dormant bacterial infection in a patient, the method comprising: obtaining a tissue sample from the patient; counting one or more target immune cells selected from regulatory T cells, natural killer cells, plasmacytoid dendritic cells, classical monocytes, and myeloid dendritic cells in the tissue sample; and diagnosing the patient, wherein increased numbers of the one or more target immune cells in the tissue sample from the patient compared to reference value ranges for the target immune cells in an uninfected tissue sample indicate that the patient has the dormant bacterial infection.

44. The method of claim 43, further comprising treating the patient diagnosed with the dormant bacterial infection.

45. The method of claim 44, wherein said treating comprises administering an antibiotic to the patient, removing an infected prosthesis from the patient, or a combination thereof, wherein said treating comprises removal of an infected joint implant, debridement of the joint, placement of an antibiotic spacer, oral or intravenous antibiotic therapy with an antibiotic, replacement of the infected joint implant with a new joint implant, or any combination thereof.

46. The method of any one of claims 43-45, wherein presence of more than one regulatory T cell, more than one natural killer cell, more than one plasmacytoid dendritic cell, three classical monocytes, or more than eighteen myeloid dendritic cells in the tissue sample from the patient in combination with increased numbers of the one or more target immune cells in the tissue sample from the patient compared to reference value ranges for the target immune cells in an uninfected tissue sample indicate that the patient has the dormant bacterial infection.

47. The method of any one of claims 43-46, further comprising fixing the tissue sample.

48. The method of any one of claims 43-47, further comprising sectioning the tissue sample.

49. The method of any one of claims 43-48, further comprising dividing the tissue sample into fragments.

50. The method of any one of claims 43-49, further comprising dissociating the tissue into plurality of cells.51 . The method of claim 50, where said dissociating the tissue comprises digesting the tissue sample with a collagenase.

52. The method of any one of claims 43-51 , wherein the tissue sample is a periarticular tissue sample.

53. The method of any one of claims 43-52, wherein the tissue sample is in contact with joint space containing an implant.

54. The method of claim 53, wherein the joint space is a suprapatellar pouch in a knee or a superior capsule in a hip.

55. The method of any one of claims 43-54, wherein the tissue sample is from a nidus of the infection.

56. The method of any one of claims 43-55, further comprising:adding a cryoprotectant to the tissue sample; and freezing the tissue sample prior to said counting the one or more target immune cells.

57. The method of claim 56, wherein the cryoprotectant comprises an optimal cutting temperature (OCT) compound.

58. The method of claim 56 or 57, wherein said freezing comprises freezing the biological sample in liquid nitrogen.

59. The method of any one of claims 43-58, further comprising storing the biological sample at -80°C prior to said counting the one or more target immune cells.

60. The method of any one of claims 43-59, wherein the one or more target immune cells are selected from regulatory T-cells, natural killer cells, and plasmacytoid dendritic cells.61 . The method of any one of claims 43-60, wherein said counting comprises performing flow cytometry, immunohistochemistry, or microscopy.

62. The method of any one of claims 43-61 , wherein said counting comprises using a cell counter.

63. The method of any one of claims 43-62, wherein the different target immune cell subtypes are distinguished from one another by cell size, morphology, surface markers, granularity, or light scattering, or a combination thereof.

64. The method of any one of claims 43-63, further comprising staining one or more surface markers on the target immune cells in the sample to identify the target immune cells.

65. The method of claim 64, wherein the one or more surface markers are selected from CD4, FOXP3, CD56, CD303, CD14, CD16, CD11c, and HLA-DR.

66. The method of claim 64 or 65, wherein said staining the one or more surface markers comprises performing chromogenic staining or immunofluorescent staining of the one or more surface markers on the target immune cells.

67. The method of claim 66, wherein said immunofluorescent staining comprises contacting the immune cells with one or more primary antibodies that specifically bind to the one or more surface markers.

68. The method of claim 67, wherein the one or more primary antibodies are fluorescently labeled.

69. The method of claim 67, wherein said immunofluorescent staining further comprises contacting the target immune cells with fluorescently labeled secondary antibodies that bind to the one or more primary antibodies bound to the one or more surface markers.

70. The method of any one of claims 43-69, wherein the regulatory T-cells are identified by their cell size, light scattering properties, and the staining of the CD4 and the FOXP3.71 . The method of any one of claims 43-70, wherein the natural killer cells are identified by their cell size, granularity, and the staining of the CD56.

72. The method of any one of claims 43-71 , wherein the plasmacytoid dendritic cells are identified by their cell size, light scattering, and the staining of the CD303.

73. The method of any one of claims 43-72, wherein the classical monocytes are identified by their cell size, light scattering, and the staining of the CD14 and the CD16.

74. The method of any one of claims 43-73, wherein the myeloid dendritic cells are identified by their cell size, light scattering, and the staining of the CD11c and the HLA-DR.

75. The method of any one of claims 43-74, further comprising staining nuclei of the one or more immune cells.

76. A kit comprising agents for detecting messenger RNA (mRNA) transcripts of two, three, four, or five or more genes selected from VSIG4, FN1 , ITGAM, C1QB, LIPA, CD9, DUSP1 , SLC7A7, IL3RA, LAMP1 , QPCT, CD52, PIK3IP1 , KCNE3, CD28, TLR8, PCNA, IGLC3, CXCL5, IFITM3, IGKC, C10orf54, SLC25A37, CLEC4E, MMP9, CXCL8, FOSB, CXCL2, DUSP4, CD48,IL1 RN, LAT2, IER3, CXCL3, PRDM1 , CCR7, LY86, ALAS2, IL1 B, CXCL1 , RNASE2, DPP4, IL15RA, CLEC1 OA, TBX21 , CCL4, TNF, IL12RB1 , LAT, IL1 R2, S100A12, STAT4, CCL20, ITGA4, KIAA0101 , CD72, FAS, IL7R, UBE2C, and CD209.

77. The kit of claim 76, wherein the kit comprises a microarray comprising a plurality of probes that specifically hybridize to mRNA transcripts of VSIG4, FN1 , ITGAM, C1 QB, LIPA, CD9, DUSP1 , SLC7A7, IL3RA, LAMP1 , QPCT, CD52, PIK3IP1 , KCNE3, CD28, TLR8, PCNA, IGLC3, CXCL5, IFITM3, IGKC, C10orf54, SLC25A37, CLEC4E, MMP9, CXCL8, FOSB, CXCL2, DUSP4, CD48, IL1 RN, LAT2, IER3, CXCL3, PRDM1 , CCR7, LY86, ALAS2, IL1 B, CXCL1 , RNASE2, DPP4, IL15RA, CLEC10A, TBX21 , CCL4, TNF, IL12RB1 , LAT, IL1 R2, S100A12, STAT4, CCL20, ITGA4, KIAA0101 , CD72, FAS, IL7R, UBE2C, and CD209.

78. The kit of claim 76 or 77, wherein the kit comprises a microarray comprising a plurality of probes that specifically hybridize to mRNA transcripts of C1 QB, LAMP1 , FN1 , TNFSF13, FCGR3A, ITGAE, SLC7A7, CD52, C1 QA, CD9, ITGAM, CTSD, CD14, LIPA, DOCK8, ITGB2, LILRB4, IRF8, IER3, IFITM3, FYN, JUN, SLC25A37, LAT2, FOSB, C10orf54, SELL, LY86, IFITM2, ADA, CXCL5, VPS28, VEGFA, CXCL2, THBD, and CXCL8.

79. The kit of any one of claims 76-78, wherein the kit comprises a microarray comprising a plurality of probes that specifically hybridize to mRNA transcripts of VSIG4, FN1 , C1 QB, C1 QA, CD9, ITGAM, CST7, IFITM2, IFITM3, FCN1 , and THBS1.

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