Methods for identifying Meox1 modulators and inhibitors

Abstract

Described herein are methods for treating cardiac conditions that involve modulating Meox1 enhancer activity, Meox1 transcription, Meox1 translation, MEOX1 protein function, or a combination thereof. Also described herein are methods for identifying agents that can modulate Meox1 enhancer activity.

Description

[Background technology]

[0001] Government support This invention was made in part with funding from R01HL1 awarded by the National Institutes of Health. 2 This invention was made with Government support under US Provisional Patent Application No. 7240. The Government has certain rights in this invention.

[0002] background Heart failure (HF) is a leading cause of mortality and a significant unmet need with current treatments having limited efficacy. Stress-activated signaling cascades can converge on chromatin regulatory mechanisms that exacerbate or induce HF, inducing widespread shifts in transcription and cellular state, triggering events that drive the cycle of pathological cardiac remodeling. Summary of the Invention

[0003] Described herein is a method for improving cardiac function, comprising, for example, inhibiting Meox1 transcription, Meox1 translation, or the function of MEOX1 protein.As shown herein, Meox1 regulator is activated in fibroblasts during stressful cardiac events, leading to increased levels of Meox1 and a cascade of profibrotic events that worsen cardiac conditions.Such inhibition of Meox1 regulator can improve cardiac function.

[0004] The method described herein includes contacting a cell population with at least one test agent to provide a test evaluation mixture, and identifying one or more Meox1 regulators by measuring Meox1 levels. For example, the cell population can include fibroblasts, activated fibroblasts, resting fibroblasts, myofibroblasts, activated myofibroblasts, or combinations thereof. The cell population can be derived from various tissues, such as heart, lung, liver, kidney, or combinations thereof. The cell population evaluated with the test agent can be derived from a patient seeking to treat a cardiac condition or disease. The patient providing the cell population to be tested can have increased Meox1 levels in cardiac fibroblasts, increased nascent Meox1 levels in cardiac fibroblasts, increased chromatin accessibility at Meox1 enhancers in cardiac fibroblasts, or combinations thereof.

[0005] In some cases, measuring Meox1 levels includes measuring chromatin accessibility of Meox1 enhancer, measuring Meox1 transcript levels, measuring nascent Meox1 transcript levels, or a combination thereof. Meox1 levels can include measuring the absolute number of observed Meox1 transcripts or Meox1 nascent transcripts per gene per cell. Meox1 enhancer can be located at about position 43,589,381 to 43,595,263 of human chromosome 17. Various test agents can be tested. For example, at least one of the test agents can be an antisense oligonucleotide, a small interfering RNA (siRNA), a small hairpin RNA (shRNA), a CRISPR guide RNA, a CRISPR ribonucleoprotein including guide RNA and cas nuclease, or a combination thereof. One or more of the Meox1 regulators that can regulate Meox1 levels can reduce Meox1 levels, reduce Meox1 enhancer activity, or a combination thereof. For example, one or more of the Meox1 regulating agents can reduce chromatin accessibility of the Meox1 enhancer, reduce the transcription level of Meox1, reduce nascent Meox1 transcription level, or a combination thereof. Such methods can further include identifying therapeutic agents by administering one or more of the Meox1 regulating agents to an animal model of a condition or disease and determining whether one or more of the Meox1 regulating agents reduces the symptoms or severity of the condition or disease.

[0006] Furthermore, the method may also include administering one or more of the test agents or therapeutic agents to the subject. Such a subject may have or be suspected of having cardiac fibrosis, pulmonary fibrosis, liver fibrosis, renal fibrosis, heart failure, congestive heart failure, myocardial infarction, cardiac ischemia, myocarditis, arrhythmic cardiomyopathy, dilated cardiomyopathy, coronary artery disease, hypertension, valvular heart disease, hypertrophic cardiomyopathy (HCM), familial dilated cardiomyopathy (FDCM), restrictive cardiomyopathy (RCM), arrhythmogenic cardiomyopathy (AVC), unclassified cardiomyopathy, or a combination thereof.

[0007] Further described herein is a method comprising contacting a cell with an agent that inhibits Meox1 RNA transcription, Meox1 chromatin accessibility, Meox1 RNA processing, or Meox1 translation. The cell can comprise a fibroblast, a myofibroblast, an activated fibroblast, an activated myofibroblast, or a combination thereof. The population of cells can be derived from various tissues, such as heart, lung, liver, kidney, or a combination thereof.

[0008] The agent can knock down or knock out the transcription of Meox1, knock down or knock out the enhancer activity of Meox1, or a combination thereof. For example, the agent can include one or more inhibitory nucleic acids, one or more guide RNAs, one or more cas nuclease:guide RNA ribonucleoprotein complexes, or a combination thereof. Such contacting of cells can occur in vitro. In some cases, the modified cells can be administered to a subject with a condition or heart disease. The cells contacted in vitro can be allogeneic or autologous to the patent or subject to which the modified cells are subsequently administered.

[0009] The contacting of the cell with the test agent or regulator can occur in vivo by administering the agent to a subject. Such a subject can have or be suspected to have cardiac fibrosis, pulmonary fibrosis, liver fibrosis, renal fibrosis, heart failure, congestive heart failure, myocardial infarction, cardiac ischemia, myocarditis, arrhythmic cardiomyopathy, dilated cardiomyopathy, coronary artery disease, hypertension, valvular heart disease, hypertrophic cardiomyopathy (HCM), familial dilated cardiomyopathy (FDCM), restrictive cardiomyopathy (RCM), arrhythmogenic cardiomyopathy (AVC), unclassified cardiomyopathy, or a combination thereof. [Brief description of the drawings]

[0010] [Figure 1] FIG. 1 shows a map of the Meox1 chromosomal locus. [Figure 2A]Figures 2A-2J show that dynamic reversibility of heart failure following bromodomain and extra-terminal domain (BET) inhibitor exposure correlates with myofibroblast status. Figure 2A graphically depicts left ventricular (LV) ejection fraction (EF) quantified by echocardiography in sham-treated mice (Sham), vehicle-treated mice with induced myocardial infarction (MI-Veh), and CPI456-treated mice with induced myocardial infarction (MI-CPI456) (n=17, 21, and 21 for Sham, MI-Veh, and MI-CPI456). The myocardial infarction (MI) model involved heart failure induced by permanent anterior wall myocardial infarction. The BET inhibitor CPI456 (10 mgk) is a JQ1 derivative that was administered intermittently as indicated in the timeline above the graph. Statistical significance is shown between MI-Veh and MI-CPI456. [Figure 2B] FIG. 2B shows left ventricular (LV) ejection fraction (EF) quantified by echocardiography in sham-treated mice (Sham), vehicle-treated Transverse Constriction Model (TAC) mice (TAC-Veh) and Transverse Constriction Model (TAC) mice treated with the small molecule BET inhibitor JQ1 (TAC JQ1) (n=4, 6, 6 and 6 for Sham, TAC-Veh, TAC JQ1 and TAC JQ1 withdrawal) with intermittent administration of the BET inhibitor JQ1 (50 mgk) (without JQ1 withdrawal vs. with JQ1 withdrawal). Statistical significance is shown between TAC JQ1 and TAC JQ1 withdrawal. [Figure 2C]Figure 2C shows a schematic of the experimental workflow for the generation of single-cell RNA sequencing and Transposase-Accessible Chromatin (ATAC) sequencing samples from cardiac samples. Figure 2D shows a uniform manifold approximation and projection (UMAP, Stratton et al. Circ. Res. 125, 662-677 (2019)) plot of all captured cells in the adult mouse population colored by cluster identity. Total cells n=35,551. As shown, single-cell RNA sequencing identifies major non-cardiomyocyte populations in the adult heart. Figure 2E shows a uniform manifold approximation and projection (UMAP, Stratton et al. Circ. Res. 125, 662-677 (2019)) plot of all captured cells in the adult mouse population colored by sample identity. Total cells n=35,551. Global transcriptional changes in hearts subjected to BET inhibition are shown. [Figure 2F] FIG. 2F is a dot plot showing the expression (average expression scale) and percentage of cells of the top differentially expressed (DE) marker genes between samples. [Figure 2G] Figure 2G shows a UMAP plot of fibroblast (FB) subclusters colored by sample identity, total cells n=13,937. [Figure 2H] FIG. 2H shows periostin (Postn) expression in fibroblasts (FBs) within the sample illustrated as a UMAP feature plot and a violin plot (y-axis is normalized UMI level). [Figure 2I] Figure 2I shows a UMAP plot of FB subclusters colored by cluster identity along with a dendrogram showing cluster relationships. Representative top Gene Ontology (GO) terms for clusters 0, 1, 4; 2, 3; and 5 are shown on the right. In Figures 2A and 2B, *P<0.05 and ****P<0.0001 for the indicated comparisons. Data are presented as mean ± SEM. [Figure 2J]Figure 2J shows a schematic highlighting our approach for integrating scRNAseq with scATACseq. For details, see Extended Methods. [Figure 3A] Figures 3A-3J illustrate that reversibility of chromatin states in fibroblasts reveals novel dynamically accessible DNA elements associated with cardiac function. Figure 3A graphically depicts chromatin accessibility of distal elements in fibroblasts derived from scATACseq samples. A 10% crop of the most extreme points was performed for better visualization. [Figure 3B] Figure 3B shows the dynamic accessibility of distal elements in fibroblasts clustered by trend across samples (left), along with the top three GO terms of the genes closest to the distal elements in each cluster (right). [Figure 3C] FIG. 3C shows enrichment scores of TF motif accessibility in distal elements across samples for the 10 most expressed transcription factors (TFs) observed during TAC in fibroblasts. [Figure 3D] Figure 3D shows a heatmap of PROSeq coverage of differentially transcribed distal regions between unstimulated and TGFβ-treated fibroblasts. Top GO terms are shown on the right, along with the average signal of two replicates for each condition. [Figure 3E] Figure 3E graphically depicts PROseq coverage measured in Unstim- and TGFβ-treated fibroblasts in vitro for scATAC peaks that were open (n=8964) or closed (n=1628) between Sham and TAC in vivo. [Figure 3F] Figure 3F shows the effect of CRISPRi targeting of the Peak 11 region on Postn expression when fibroblasts are stimulated with or without TGFβ (Unstim). Postn expression was measured by qPCR in control and Peak 11-CRISPRi-targeted lines in Unstim and TGFβ-treated fibroblasts (each panel was normalized to its Unstim condition). [Figure 3G] Figure 3G shows a schematic representation of the correlation analysis between LV ejection fraction and chromatin accessibility, highlighting negative or positive correlations. [Figure 3H] Figure 3H is a volcano plot showing the correlation coefficients (see analysis shown in Figure 3G) and corresponding p-values ​​of 470 super-enhancers in fibroblasts. The region distal to the Meox1 gene has one of the largest negative correlation coefficients. In Figure 3F, **P<0.01 and ****P<0.0001 for the indicated comparisons. Data are presented as mean ± SEM. [Figure 3I] FIG. 3I graphically depicts chromatin accessibility at distal elements in myeloid cells. [Figure 3J] Figure 3J graphically depicts chromatin accessibility at distal elements in endothelial cells. In Figures 3I-3J, 10% extreme points were cropped for better visualization. [Figure 4A] Figures 4A-4K show chromatin accessibility and nascent transcription of cis-regulatory elements regulating the expression of Meox1. Figure 4A shows a UMAP plot of fibroblasts colored and subclustered by sample identity (same as Figure 3G) and shows Meox1 expression in fibroblasts in the samples as UMAP feature plots and violin plots (y-axis is normalized to UMI levels). [Figure 4B] Figure 4B shows the Meox1 locus (gene and enhancer), from top to bottom: coverage of scATAC samples in fibroblasts; ChIPseq of BRD4 (GSE46668), H3K27ac and CTCF (ENCSR000CDF and ENCSR000CBI) in adult heart; coverage of PROseq in Unstim and TGFβ treated fibroblasts; and measurement of co-accessibility between the Meox1 promoter and Peak 9 / 10 region in fibroblasts using scATAC. Highly transcribed regions (Peak 9 / 10) are highlighted in red within the large Meox1 enhancer. [Figure 4C1]Figure 4C shows the coverage of chromosome conformation capture (4C) in Unstim and TGFβ treated fibroblasts between the peak 9 region (anchor point) and the Meox1 promoter. Genomic regions of 922 kb (top) and 328 kb (bottom) are shown. The last track represents the called TGFβ induced loop with peak 9 (colored purple in the original text). [Figure 4C2] Same as above. [Figure 4D] Figure 4D shows schematic CRISPRi targeting of three regions (peaks 5, 9 and 13) within the Meox1 enhancer at the top. Meox1 expression by qPCR between Unstim and TGFβ treated fibroblasts in three CRISPRi fibroblast cell lines targeting peaks 5, 9 or 13 (each panel is normalized to its Unstim condition). In Figure 4D, **P<0.01 and ***P<0.001 for the indicated comparisons. Data are shown as mean ± SEM. [Figure 4E] Figure 4E shows chromatin accessibility of the Meox1 super-enhancer (SE) in fibroblasts, myeloid cells, and endothelial cells that were mock treated (leftmost bar), received TAC (middle left bar), received TAC and JQ1 treated (middle right bar), or received TAC and transiently treated with JQ1 followed by withdrawal of JQ1 (rightmost bar). [Figure 4F] FIG. 4F shows scATAC coverage across samples at the Meox1 super-enhancer in fibroblasts where multiple dynamic peaks were identified during heart failure with pulsatile BET inhibition. [Figure 4G] FIG. 4G graphically depicts Meox1 expression measured by qPCR in Unstim- and TGFβ-treated fibroblast FBs with or without JQ1 treatment. [Figure 4H]Figure 4H graphically illustrates that Peak9 / 10 is an essential regulatory element regulating Meox1 expression, as demonstrated by the deletion of Peak9 / 10 in cardiac fibroblasts. Meox1 expression was measured by qPCR in unstimulated and TGFβ-stimulated CRISPR Cas9-treated WT (isogenic line) and Peak9 / 10-deleted cells. [Figure 4I] FIG. 4I graphically depicts Brd2, Brd3, or Brd4 expression measured by qPCR of individual BET genes in Unstim- or TGFβ-treated fibroblasts with siRNA targeting either Ctrl, Brd2, Brd3, or Brd4. [Figure 4J] Figure 4J graphically depicts Meox1 expression measured by qPCR in Unstim or TGFβ-treated fibroblasts with siRNA targeting either Ctrl, Brd2, Brd3 or Brd4. In 4I-4J, *P<0.05, ***P<0.001 and ****P<0.0001 for the indicated comparisons. Data are presented as mean ± SEM. Data are presented as mean ± SEM. [Figure 4K] FIG. 4K shows that deletion of Brd4 improves cardiac function during heart disease. [Figure 5A] Figures 5A-5J show that MEOX1 is a novel regulator of fibroblast plasticity and profibrotic function. Figure 5A shows representative images of fibroblasts seeded onto a compressible collagen gel matrix and assessed for gel contraction after treatment with siRNA targeting TGFβ and Meox1 for 72 hours. For comparison, the effect of control siRNA on collagen gel contraction is also shown. [Figure 5B] Figure 5B graphically depicts quantification of gel shrinkage images reported as percent shrinkage (n=4 plates per condition). Data are presented as mean±SEM. [Figure 5C]Figure 5C graphically depicts quantification of Edu uptake in fibroblasts after 72 hours of treatment with TGFβ and Ctrl siRNA or Meox1-targeting siRNA. Data are presented as mean ± SEM. In Figures 5B and 5C, **P<0.01 and ****P<0.0001 for the indicated comparisons. [Figure 5D] Figure 5D shows a heatmap of MEOX1-HA ChIPseq occupancy at protein-coding genes (−2 kb from transcription start, +2 kb from transcription end) sorted by intensity of ChIPseq signal (8366 regions are shown). [Figure 5E] (E) Heatmap of PROseq coverage of differentially transcribed protein-coding genes between fibroblasts treated with TGFβ with Ctrl or Meox1 siRNA. The average signal of two replicates for each condition is shown. Top associated GO terms and exemplary genes are shown on the right. [Figure 5F] FIG. 5F shows MEOX1 ChIP and PROseq (Unstim and TGFβ-treated fibroblasts with Ctrl or Meox1 siRNA) coverage at the Ctgf or Postn locus (including the Postn peak 11 regulatory element). [Figure 5G] Figure 5G graphically depicts Meox1 expression in human cardiac diseases, such as hypertrophic cardiomyopathy (HCM) and dilated cardiomyopathy (DCM). Bulk RNAseq data shows human MEOX1 expression (-GSE141910) among controls and individuals with HCM / DCM assessed in cardiac tissue. [Figure 5H] Figure 5H graphically depicts expression of Meox1 in idiopathic pulmonary fibrosis (IPF). Bulk RNAseq data shows human MEOX1 expression (-GSE134692) between controls and individuals with idiopathic pulmonary fibrosis assessed in lung tissue. For Figures 5G-5H, p-values ​​are indicated in the panels. [Figure 5I]Figure 5I graphically depicts the expression of Meox1 in human fibroblasts derived from lung, liver and kidney. MEOX1 expression was measured by qPCR in unstimulated fibroblasts (Unstim, left bar), as well as in human fibroblasts derived from lung, liver and kidney treated with TGFβ (middle bar) or TGFβ+JQ1 (right bar). Data are shown as mean ± SEM. [Figure 5J] Figure 5J shows a schematic of the transcriptional switches that activate fibroblasts in correlation with cardiac disease states. Combining single-cell transcriptomic and epigenomic investigations, we discovered key enhancers and protein-coding genes that dynamically regulate fibroblast plasticity and profibrotic functions, including the transcription factor MEOX1. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] As shown herein, Meox1 enhancer element is a fibroblast-specific transcription switch that reversibly mediates stress-induced fibroblast activation.The experiments described herein show that inhibiting Meox1 expression and function and / or inhibiting Meox1 enhancer can improve cardiac function, pulmonary function, renal function, liver function, or a combination thereof.Therefore, the present application relates to a method of inhibiting Meox1 transcription, inhibiting Meox1 enhancer activity, or a combination thereof.Also described is a method of screening useful for identifying agents that can regulate Meox1 transcription and / or Meox1 enhancer activity.

[0012] For example, using a combination of mouse models of heart failure, small molecule BET bromodomain inhibitors, and single-cell omics, we show that cardiac myofibroblasts respond highly to inhibition of transcription. For example, myofibroblasts show robust reversibility of their cellular condition, switching between basal and activated myofibroblasts in a manner that is directly related to BET inhibitor exposure. In addition, data provided herein also show elevated Meox1 expression in activated fibroblasts from human lung, kidney, and liver. Utilizing an integrated epigenomic approach, we discovered and dissected the function of a super-enhancer that regulates the expression of the transcription factor Meox1. Modulating this super-enhancer may regulate Meox1 expression and reduce the deleterious effects of fibroblast activation.

[0013] Meox1 is specifically expressed in fibroblasts and regulates their proliferation and contractile activity by directly binding to the promoters of fibroblast genes. As described herein, transcriptional regulation during disease development, combined with single-cell investigations, reveals cellular conditions and molecular mechanisms involved in chronic disease progression and resolution, and offers novel therapeutic approaches.

[0014] The human Meox1 gene is located on chromosome 17, mapping to NC_000017.11 (43640389..43661977, complement). A map of the Meox1 chromosomal locus is shown in FIG. 1.

[0015] An example of a MEOX1 amino acid sequence is available from the NCBI database under accession number NP_004518.1 and is set forth below as SEQ ID NO:1.

[0016] [ka]

[0017] The nucleotide sequence of the human MEOX1 protein is shown below as SEQ ID NO:2.

[0018] [ka]

[0019] [ka]

[0020] Other human Meox1 sequences are available under accession numbers NM_013999.3 (GI:84105330); NM_001040002.2 (GI:1675087437); and XM_011524818.2 (GI:1370470996).

[0021] An enhancer controlling expression of the Meox1 transcription factor is located at about positions 43,589,381 to 43,595,263 on human chromosome 17. The sequence of the peak 9 / 10 region of this enhancer is shown below as SEQ ID NO:3.

[0022] [ka]

[0023] [ka]

[0024] [ka]

[0025] [ka]

[0026] Meox1 sequences may vary among human populations. Many such variants may include codon mutations and / or conservative amino acid changes. However, Meox1 sequences may also include non-conservative mutations. For example, Meox1 nucleic acids or Meox1 proteins may have at least 85% sequence identity and / or complementarity, or at least 90% sequence identity and / or complementarity, or at least 95% sequence identity and / or complementarity, or at least 96% sequence identity and / or complementarity, or at least 97% sequence identity and / or complementarity, or at least 98% sequence identity and / or complementarity, or at least 99% sequence identity and / or complementarity to any of the Meox1 nucleic acid sequences or Meox1 protein sequences described herein.

[0027] The Meox1 enhancer described herein can be detected in nascent Meox1 transcripts. Therefore, it can be said that the enhancer is transcribed. Therefore, Meox1 can be regulated by using methods that regulate both the Meox1 chromosomal site and the Meox1 RNA transcript.

[0028] Inhibition of Meox1 transcription, Meox1 translation, or Meox1 protein function can be used to treat cardiac diseases and conditions. Examples of diseases and conditions that can be treated include heart failure, cardiac fibrosis, pulmonary fibrosis, renal fibrosis, hepatic fibrosis, congestive heart failure, myocardial infarction, cardiac ischemia, myocarditis, arrhythmia, or a combination thereof.

[0029] The function of the epigenetic acetyl-lysine reader protein BET (Bromodomain and Extra Terminal) may be a chromatin coactivator in the pathogenesis of heart failure, which can be pharmacologic targeted in vivo. Administration of the small molecule BET inhibitor JQ1 can prevent or treat HF ​​in multiple rodent models. However, the intrinsic cellular conditions and epigenetic mechanisms mediating these beneficial effects, and the extent of their reversibility, are unclear. In the experiments described herein, we utilize small molecule BET bromodomain inhibition to transiently block enhancer-to-promoter signaling in a mouse heart failure model, and combine it with single-cell RNA-Seq and single-cell ATAC-Seq of cardiac tissue to discover dynamic cellular conditions and activated chromatin elements underlying therapeutic response.

[0030] JQ1 is a thienotriazolodiazepine with the structure shown below. It is a potent inhibitor of the BET family of bromodomain proteins, which includes mammalian BRD2, BRD3, BRD4, and the testis-specific protein BRDT.

[0031] [ka]

[0032] BET inhibitors structurally similar to JQ1 are being tested by various investigators in clinical trials for various cancers, including NUT midline carcinoma. screening Agents that modulate Meox1, thereby reducing the symptoms, severity and / or progression of a cardiac disease / condition, can be identified by using the methods described herein.

[0033] Such a method may, for example, comprise contacting a cell population with one or more test agents to form an assay mixture, and then measuring Meox1 levels, thereby identifying one or more Meox1 regulators. The cell population may comprise cardiac cells, fibroblasts, resting fibroblasts, myofibroblasts, or combinations thereof. In some cases, the cell population comprises activated fibroblasts. For example, the fibroblasts may be activated by TGFβ.

[0034] Measuring the level of Meox1 can include measuring the chromatin accessibility of a Meox1 regulatory element, such as an enhancer. For example, the Meox1 regulatory element can be a peak 9 / 10 enhancer, such as an enhancer between about positions 43,589,381 and 43,595,263 of human chromosome 17.

[0035] In some cases, the screening method may include measuring Meox1 transcript or protein levels. For example, measuring Meox1 levels may include measuring the absolute number of observed Meox1 transcripts (UMI counts) per gene per cell.

[0036] Test agents may be selected as modulators of Meox1 that increase Meox1 levels. However, the test agent can be selected as a Meox1 regulator that preferably reduces Meox1 level.For example, one or more of the Meox1 regulators can reduce the enhancer activity of Meox1.Reducing the enhancer activity of Meox1 can include, for example, reducing the chromosomal accessibility of Meox1 enhancer.Meox1 enhancer can be located between about position 43,589,381 and 43,595,263 on human chromosome 17.

[0037] In some cases, the cell population in the test assay is derived from a patient who is seeking treatment or prevention of a cardiac condition or disease. Such a patient may exhibit elevated Meox1 levels in the cardiac fibroblasts of the patient, increased chromosomal accessibility of one or more Meox1 regulatory elements in the cardiac fibroblasts, or a combination thereof.

[0038] The screening methods described herein may also include identifying therapeutic agents by administering one or more of the Meox1 regulating agents to an animal model of a cardiac condition or disease and determining whether one or more of the Meox1 regulating agents reduces the symptoms or severity of the cardiac condition or disease. In addition, the methods may include administering one or more of the test agents or therapeutic agents to a patient.

[0039] Regulation of Meox1 Meox1 can be modulated by various agents and methods. For example, Meox1 can be modulated by any of the test agents, therapeutic agents, inhibitory nucleic acids, guide RNAs, nucleases, ribonucleoprotein complexes including cas nucleases, inhibitory nucleic acids, chromatin stabilizers, or combinations thereof described herein.

[0040] For example, a test agent, a therapeutic agent, an inhibitory nucleic acid, a guide RNA, a nuclease, a ribonucleoprotein complex comprising a cas nuclease, an inhibitory nucleic acid, a ribonucleoprotein complex comprising a chromatin stabilizer, or a combination thereof may be administered to a subject, such as a patient or an animal. The patient or animal receiving the test agent or therapeutic agent may be one in need of one or more of the test agent, the therapeutic agent, the inhibitory nucleic acid, a guide RNA, a nuclease, a ribonucleoprotein complex comprising a cas nuclease, an inhibitory nucleic acid, a ribonucleoprotein complex comprising a chromatin stabilizer, or a combination thereof. In some cases, the subject receiving the test agent, the therapeutic agent, the inhibitory nucleic acid, a guide RNA, a nuclease, a ribonucleoprotein complex comprising a cas nuclease, an inhibitory nucleic acid, a ribonucleoprotein complex comprising a chromatin stabilizer, or a combination thereof is an animal model of a cardiac condition or disease.

[0041] The subject may have fibroblasts that exhibit increased chromosomal accessibility at a Meox1 regulatory element, such as an enhancer. For example, the Meox1 regulatory element may be a peak 9 / 10 enhancer, such as the Meox1 enhancer between about positions 43,589,381 and 43,595,263 on human chromosome 17.

[0042] The subject (e.g., patient, animal, and / or animal model) may have a cardiac disease or condition. Such cardiac condition or disease may include cardiac fibrosis, pulmonary fibrosis, renal fibrosis, liver fibrosis, heart failure, congestive heart failure, myocardial infarction, cardiac ischemia, myocarditis, arrhythmic cardiomyopathy, dilated cardiomyopathy, cardiac artery disease, hypertension, valvular heart disease, hypertrophic cardiomyopathy (HCM), familial dilated cardiomyopathy (FDCM), restrictive cardiomyopathy (RCM), arrhythmogenic cardiomyopathy (AVC), unclassifiable cardiomyopathy, or combinations thereof. In some cases, the subject may not show any symptoms of cardiac disease or condition, in which case the test agent or therapeutic agent can be administered to suppress the development of cardiac disease or condition.

[0043] In some cases, the knockout or knockdown of Meox1 regulatory element can be used to regulate fibroblasts, myofibroblasts, or combinations thereof of a subject.Such knockout or knockdown of Meox1 regulatory element can be carried out in vivo or in vitro in cells or subjects.For example, the knockout or knockdown of Meox1 regulatory element can include the CRISPR modification of Meox1 regulatory element or use the Meox1 inhibitory nucleic acid that targets Meox1 regulatory element.

[0044] In vitro knockout or knockdown of Meox1 regulatory elements in a population of cells of a subject can be used to evaluate the response of a patient or to select a therapeutic agent for the treatment of a subject. However, in some cases, in vitro knockout or knockdown of Meox1 regulatory elements in a population of cells of a subject can be used to generate modified cells, and then the modified fibroblasts can be reintroduced into a patient. Such modified fibroblasts may not respond to stress stimuli that cause a cascade of problematic physiological responses that can result in fibrotic tissue. For this reason, cardiac fibrosis, pulmonary fibrosis, kidney fibrosis, liver fibrosis, and related organ failure can be avoided by reducing Meox1 expression.

[0045] The modified cells can be, for example, modified fibroblasts, modified lung fibroblasts, modified myofibroblasts, modified cardiac fibroblasts, modified lung fibroblasts, modified liver fibroblasts, modified kidney fibroblasts, modified cardiac cells, or combinations thereof.

[0046] Gene Regulation Described herein are guide RNAs capable of regulating, knocking down or knocking out Meox1 regulatory elements, including Meox1 peak 9 / 10 enhancer elements. Using the CRISPR-Cas9 genome editing system, Meox1 regulatory elements that are activated during cardiac conditions and diseases can be deleted or modified. Single guide RNAs (sgRNAs) are used to recognize one or more target sequences in the genome of a subject, and nucleases can act as scissors to cut single-stranded or double-stranded genomic DNA. Mutations in the genome near the cut site can be introduced by endogenous non-homologous end joining (NHEJ) or homology-dependent repair (HDR) pathways. Thus, the guide RNA guides the nucleases to cut the target Meox1 genomic site for deletion and / or modification by endogenous mechanisms.

[0047] Meox1-specific guide RNAs can modify Meox1 regulatory elements to make them less responsive to stress activation, which can trigger signaling cascades that cause broad shifts in transcription and cellular states that exacerbate disease conditions.

[0048] The Cas system can recognize any sequence in the genome that matches the 20-base gRNA. However, because the "protospacer adjacent motif" (PAM) directly binds to the Cas protein, each gRNA must also be adjacent to a PAM that is invariant to each type of Cas protein. See Doudna et al., Science 346(6213):1077, 1258096 (2014) and Jinek et al., Science 337:816-21 (2012). Thus, the guide RNA can have a PAM site sequence that can be bound by the Cas protein.

[0049] When the Cas system was first described with Cas9 having a "NGG" PAM site, this PAM was somewhat restrictive in that it required the GG to be oriented correctly relative to the target site. Different Cas9 species are now described with different PAM sites. See Jinek et al., Science 337:816-21 (2012), Ran et al., Nature 520:186-91 (2015), and Zetsche et al., Cell 163:759-71 (2015). In addition, mutations in the PAM recognition domain (Table 1) increased the diversity of PAM sites for SpCas9 and SaCas9. See Kleinstiver et al., Nat Biotechnol 33:1293-1298 (2015), and Kleinstiver et al., Nature 523:481-5 (2015).

[0050] Table 1 summarizes information about the PAM site.

[0051] [Table 1]

[0052] Note that the guide RNAs for SpCas9 and SaCas9 cover 20 bases 5' to the PAM site, whereas for FnCas2 (Cpf1) the guide RNA covers 20 bases 3' to the PAM.

[0053] There are many different types of nucleases and systems that can be used for gene editing. The nuclease employed can be any DNA-binding protein, possibly with nuclease activity. Examples of nucleases include Streptococcus pyogenes Cas (SpCas9) nuclease, Staphylococcus aureus Cas9 (SpCas9) nuclease, Francisella novicida Cas2 (FnCas2, also called dFnCpf1) nuclease, zinc finger nucleases (ZFNs), meganucleases, TAL effector nucleases (TALENs), Fok-I nucleases, any DNA-binding protein with nuclease activity, any DNA-binding protein that binds to a nuclease, or a combination thereof. However, the CRISPR-Cas system is usually the most widely used. In some cases, the nuclease is therefore a Cas nuclease.

[0054] CRISPR-Cas systems are usually divided into two classes: class 1 systems include types I, III, and IV, and class 2 systems include types II, V, and VI. Class 1 CRISPR-Cas systems use complexes of multiple Cas proteins, whereas class 2 systems use only a single Cas protein with multiple domains. Class 2 CRISPR-Cas systems are usually preferred for genetic engineering applications due to their simplicity and ease of use.

[0055] Various Cas nucleases can be employed in the methods described herein. The three best characterized are provided as examples. The most commonly used Cas nuclease is Streptococcus pyogenes Cas9 (SpCas9). More recently described forms of Cas are Staphylococcus aureus Cas9 (SaCas9) and Francisella novicida Cas2 (FnCas2, also called FnCpf1). See Jinek et al., Science 337:816-21 (2012); Qi et al., Cell 152:1173-83 (2013); Ran et al., Nature 520:186-91 (2015); Zetsche et al., Cell 163:759-71 (2015).

[0056] An example of the amino acid sequence of a Streptococcus pyogenes Cas9 (SpCas9) nuclease is provided below (SEQ ID NO:4).

[0057] [ka]

[0058] The cDNA encoding Streptococcus pyogenes Cas9 (SpCas9) is provided below (SEQ ID NO: 15).

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[0062] The amino acid sequence of Francisella novicida Cas2 (FnCas2, also known as FnCpf1) is shown below (SEQ ID NO: 16).

[0063] [ka]

[0064] The cDNA encoding the above-mentioned Francisella novicida Cas2 (FnCas2, also known as dFnCpf1) polypeptide is shown below (SEQ ID NO: 17).

[0065] [ka]

[0066] [ka]

[0067] [ka]

[0068] Nucleic acids that inhibit Meox1 As described herein, reducing the expression of Meox1 can improve cardiac function. Furthermore, the data provided herein show that the peak 9 / 10 enhancer is transcribed in Meox1 nascent transcripts.

[0069] Inhibitory nucleic acids can be used to reduce the expression and / or translation of Meox1. Such inhibitory nucleic acids can specifically bind to Meox1 nucleic acids, including nascent RNAs encoding Meox1 and / or Meox1 enhancers (e.g., peak 9 / 10 Meox1 enhancer elements). Antisense oligonucleotides have been used to suppress other enhancers, including enhancers that can control cardiac fibroblast proliferation, migration, and survival (see, e.g., Micheletti et al. Sci. Transl. Med. 9(395)eaai9118(2017)). Thus, even if the enhancer is distant from the amino acid coding region, the enhancer can still be suppressed by the inhibitory nucleic acid.

[0070] The inhibitory nucleic acid may have at least one segment that hybridizes to the nucleic acid of Meox1 in cells or under stringent conditions. The inhibitory nucleic acid may reduce the processing, expression, and / or translation of the nucleic acid encoding Meox1. The inhibitory nucleic acid may hybridize to genomic DNA, messenger RNA, nascent RNA, or a combination thereof. The inhibitory nucleic acid may be incorporated into a plasmid vector or viral DNA. It may be single-stranded or double-stranded, circular, linear.

[0071] Inhibitory nucleic acids can be polymers of ribose nucleotides (RNAi) or deoxyribose nucleotides having a length of 13 or more bases. Inhibitory nucleic acids can be naturally occurring nucleotides; synthetic, modified, or pseudonucleotides, such as phosphorothiolates; and P 32The inhibitory nucleic acid may comprise a nucleotide having a detectable label, such as, for example, biotin, digoxigenin, etc. The inhibitory nucleic acid may reduce the expression, processing, and / or translation of the Meox1 nucleic acid. Such an inhibitory nucleic acid may be perfectly complementary to a segment of the Meox1 nucleic acid (e.g., Meox1 mRNA or Meox1 nascent transcript containing at least one Meox1 enhancer element, such as the peak 9 / 10 enhancer).

[0072] An inhibitory nucleic acid is sufficient to hybridize to a Meox1 nucleic acid under intracellular or stringent hybridization conditions and inhibit expression of the Meox1 nucleic acid. Intracellular conditions refer to conditions such as temperature, pH and salt concentration typically found within a cell, e.g., a target cell as described herein.

[0073] Typically, stringent hybridization conditions are those that meet the thermal melting point (T m ) is selected to be about 5°C lower than the thermal melting point of the selected sequence. However, stringent conditions, unless otherwise limited herein, encompass temperatures ranging from about 1°C to about 20°C lower than the thermal melting point of the selected sequence, depending on the degree of stringency desired. For example, inhibitory oligonucleotides containing 2, 3, 4, or 5 or more stretches of contiguous nucleotides that are exactly complementary to the Meox1 coding or flanking sequence can each be separated by a stretch of contiguous nucleotides that are not complementary to the flanking coding sequence, and such inhibitory nucleic acids can still inhibit the function of the Meox1 nucleic acid. Usually, each stretch of contiguous nucleotides is at least 4, 5, 6, 7, or 8 or more nucleotides in length. Non-complementary intervening sequences can be 1, 2, 3, or 4 nucleotides in length.

[0074] One skilled in the art can easily estimate the degree of mismatch that can be tolerated to inhibit the expression of a particular target nucleic acid by using the calculated thermal melting temperature of the inhibitory nucleic acid hybridized to the sense nucleic acid. The inhibitory nucleic acid of the present invention can be, for example, a short hairpin RNA, a small interfering RNA, a ribozyme, or an antisense nucleic acid molecule.

[0075] Inhibitory nucleic acid molecules can be single-stranded (e.g., antisense oligonucleotides) or double-stranded (e.g., siRNAs) and can function enzymatically or by steric blocking. Enzyme-dependent inhibitory nucleic acid molecules include those that are dependent on RNaseH activity to degrade target mRNA. These include single-stranded DNA, RNA, and phosphorothioate molecules, as well as double-stranded RNAi / siRNA systems that involve recognition of target mRNA via sense-antisense strand pairing and subsequent degradation of the target mRNA by an RNA-induced silencing complex. RNaseH-independent steric blocking inhibitory nucleic acids interfere with gene expression or other mRNA-dependent intracellular processes by binding to target mRNA and interfering with other processes. Steric blocking inhibitory nucleic acids include 2'-O alkyl (usually in chimeras with RNaseH-dependent antisense), peptide nucleic acid (PNA), locked nucleic acid (LNA), and morpholino antisense.

[0076] Small interfering RNA (siRNA) can be used to specifically reduce Meox1 processing or translation, for example, so that production of the encoded polypeptide is reduced. siRNA mediates post-transcriptional gene silencing in a sequence-specific manner. See, for example, the website at invitrogen.com / site / us / en / home / Products-and-Services / Applications / rnai.html. Once incorporated into the RNA-induced silencing complex, the siRNA mediates the cleavage of homologous endogenous mRNA transcripts by directing the complex to the homologous mRNA transcript, which is then cleaved by the complex. The siRNA can be homologous to any region of the Meox1 mRNA transcript. The homologous region can be 50 nucleotides or less, 30 nucleotides or less in length, 25 nucleotides or less, etc., or, for example, about 21 to 23 nucleotides in length. The siRNA is typically double-stranded and can have a 2-nucleotide 3' overhang, for example, a 3' overhang UU dinucleotide. Methods for designing siRNAs are available, see, e.g., Elbashir et al. Nature 411:494-498 (2001); Harborth et al. Antisense Nucleic Acid Drug Dev. 13:83-106 (2003).

[0077] A pSuppressorNeo vector expressing hairpin siRNA is commercially available from IMGENEX (San Diego, CA) and can be used to generate siRNA or shRNA to inhibit Meox1 expression. Construction of an expression plasmid for siRNA or shRNA involves the selection of a target region of mRNA, which can be a trial-and-error process. However, Elbashir et al. provide guidelines that appear to have about an 80% success rate. Elbashir, SM, et al., Analysis of gene function in somatic mammalian cells using small interfering RNAs. Methods, 2002.26(2):p.199-213. Thus, for the synthesis of synthetic siRNA or shRNA, the target region can be selected preferably 50 to 100 nucleotides downstream of the start codon. The 5' and 3' untranslated regions and the region near the start codon should be avoided, as these may be rich in regulatory protein binding sites. siRNA can start with AA, have 3'UU overhangs for both sense and antisense siRNA strands, and have about 50% G / C content. One example of a synthetic siRNA or shRNA sequence is 5'-AA(N19)UU, where N is any nucleotide in the mRNA sequence, and should have about 50% GC content. The selected sequence can be compared with others in the human genome database to minimize homology to other known coding sequences (e.g., by Blast search through the NCBI website).

[0078] Inhibitory nucleic acids (e.g., siRNAs, and / or antisense oligonucleotides) may be chemically synthesized, produced by in vitro transcription, or expressed from an expression vector or PCR expression cassette. See, for example, the website at invitrogen.com / site / us / en / home / Products-and-Services / Applications / rnai.html.

[0079] When siRNA is expressed from an expression vector or PCR expression cassette, the insert encoding the siRNA can be expressed as an RNA transcript that folds into an siRNA hairpin or shRNA. Thus, the RNA transcript can include a sense siRNA sequence linked to a reverse-complementary antisense siRNA sequence by a spacer sequence that forms a hairpin loop, and a series of U at the 3' end. The hairpin loop can be any suitable length, for example, 3 to 30 nucleotides long, or about 3 to 23 nucleotides long, and can include various nucleotide sequences, including, for example, AUG, CCC, UUCG, CCACC, CTCGAG, AAGCUU and CCACACC. siRNA can also be generated in vivo by cleavage of double-stranded RNA that is introduced directly or via a transgene or virus. In some organisms, amplification can occur by RNA-dependent RNA polymerase.

[0080] Inhibitory nucleic acids such as short hairpin RNA, siRNA, or antisense oligonucleotides can be prepared using methods such as by expression from an expression vector or expression cassette containing the sequence of the inhibitory nucleic acid. Alternatively, it may be prepared by chemical synthesis using naturally occurring nucleotides, modified nucleotides, or any combination thereof. In some embodiments, the inhibitory nucleic acid is made from modified nucleotides or non-phosphodiester bonds designed, for example, to increase the biological stability of the inhibitory nucleic acid or to increase the intracellular stability of the duplex formed between the inhibitory nucleic acid and the target Meox1 nucleic acid.

[0081] delivery There are various methods for delivering inhibitory nucleic acid, guide RNA, nuclease, or combinations thereof.In some cases, inhibitory nucleic acid, guide RNA, nuclease, or combinations thereof are directly administered to the subject.In other cases, inhibitory nucleic acid, guide RNA, nuclease, or combinations thereof can be encoded in one or more expression cassettes or expression vectors, and the expression cassettes / vectors can be administered to the subject.Therefore, inhibitory nucleic acid, guide RNA, nuclease, or combinations thereof can be expressed in vivo from expression cassettes / expression vectors.

[0082] The first and perhaps the easiest approach is to use a vector-based CRISPR-Cas9 system that encodes the nuclease and guide RNA (e.g., sgRNA) from the same vector, thus avoiding multiple transfections of the different components. The second approach is to deliver a mixture of Cas9 mRNA and sgRNA, and the third strategy is to deliver a mixture of Cas9 protein and sgRNA.

[0083] In some cases, guide RNA can be delivered to cells or administered to subjects in the form of expression cassette or vector that can express one or more of guide RNA. Nuclease can also be delivered to cells or administered to subjects in the form of expression cassette or vector that can express one or more nuclease. Nuclease can also be combined with their respective gRNA and delivered as RNA-protein complex (RNP). Thus, RNP can be pre-assembled outside cells and introduced into cells.

[0084] Inhibitory nucleic acid, guide RNA can be expressed from expression cassette or vector. Nuclease can also be expressed in the same cell with one or more gRNA. Inhibitory nucleic acid, guide RNA and nuclease can be introduced in the form of the nucleic acid molecule that codes for inhibitory nucleic acid, guide RNA and / or nuclease. Such nucleic acid molecule can be provided in expression cassette or expression vector.

[0085] The expression cassette may be present in a vector. The vector may be, for example, an expression vector, such as a virus or other vector that is easily taken up by cells. Examples of vectors that may be used include, for example, adeno-associated virus (AAV) gene transfer vectors, lentivirus vectors, retrovirus vectors, herpes virus vectors, such as cytomegalovirus vectors, herpes simplex virus vectors, varicella zoster virus vectors, adenovirus vectors, such as helper-dependent adenovirus vectors, adenovirus-AAV hybrids, rabies virus vectors, vesicular stomatitis virus (VSV) vectors, coronavirus vectors, poxvirus vectors, and the like. Non-viral vectors, such as liposomes, nanoparticles, microparticles, lipoplexes, polyplexes, nanotubes, and the like, may be employed for delivery of the expression vector. In one embodiment, two or more expression vectors are administered, each encoding, for example, a different inhibitory nucleic acid, a guide RNA, a different nuclease, or a combination thereof.

[0086] The expression cassette or expression vector comprises a promoter sequence operably linked to a nucleic acid segment encoding an inhibitory nucleic acid, a guide RNA, a nuclease, or a combination thereof. Methods for ensuring the expression of a functional inhibitory nucleic acid, a guide RNA, a nuclease, or a combination thereof may include expression from a transgene, an expression cassette, or an expression vector. For example, the nucleic acid segment encoding the selected inhibitory nucleic acid, a guide RNA, a nuclease, or a combination thereof may be present in a vector, such as a plasmid, a cosmid, a virus, a bacteriophage, or other vector available for genetic engineering. The coding sequence inserted into the vector may be synthesized by standard methods or isolated from a natural source. The coding sequence may further be linked to transcriptional regulatory elements, a termination sequence, and / or other amino acid-encoding sequences. Such regulatory sequences can provide for transcription initiation, an internal ribosome entry site (IRES) (Owens, Proc. Natl. Acad. Sci. USA 98:1471-1476 (2001)), and optionally, regulatory elements ensuring transcription termination and transcript stabilization.

[0087] Non-limiting examples of regulatory elements that ensure the initiation of transcription include a translation initiation codon, a transcription enhancer, such as the SV40 enhancer, an insulator and / or a promoter. The promoter can be a constitutive promoter, an inducible promoter, or a tissue-specific promoter. Examples of promoters that can be used include the cytomegalovirus (CMV) promoter, the SV40 promoter, the RSV promoter (Rous sarcoma virus), the lacZ promoter, the chicken beta actin promoter, the CAG promoter (the combination of the chicken beta actin promoter and the cytomegalovirus immediate early enhancer), the gai10 promoter, the human elongation factor 1 alpha promoter, the AOX1 promoter, the GAL1 promoter CaM kinase promoter, the lac, trp or tac promoter, the lacUV5 promoter, the Autographa californica nuclear polyhedrosis virus (AcMNPV) polyhedron promoter, or the globin intron in mammalian and other animal cells. Non-limiting examples of regulatory elements that ensure transcription termination include V40-polyA site, tk-polyA site, or SV40, lacZ or AcMNPV polyhedron polyadenylation signals, which will be included downstream of the nucleic acid sequence of the present invention. Additional regulatory elements may include translation enhancers, Kozak sequences, and intervening sequences adjacent to donor and acceptor sites for RNA splicing. In addition, origins of replication, drug resistance genes, or regulatory elements (as part of an inducible promoter) may also be included.

[0088] The expression cassette and / or expression vector can be introduced into a cell. The cell can be any mammalian or avian cell. For example, the cell can be a human cell, or a cell from a domesticated animal, a zoo animal, or a laboratory animal.

[0089] The cells may be obtained from a subject in need of treatment. The cells may be autologous or allogeneic to the subject. In some cases, the cells may be fibroblasts, myofibroblasts, cardiac fibroblasts, induced pluripotent stem cells, cardiac progenitor cells, cardiomyocytes and / or cardiac cells. The allogeneic cells may be classified to match those of the subject.

[0090] Guide RNA can also be introduced into cells or administered to a subject in the form of an RNA-protein complex (RNP). Nucleases can be pre-bound to one or more gRNAs before introduction into cells. The advantage of RNP delivery of Cas-gRNA complexes is the easily controllable complex formation ex vivo, and the structure and composition of the desired complex can be known with certainty, since the selected Cas polypeptide can be independently complexed with the selected guide RNA. RNPs are highly stable and there is no obvious exchange of gRNA. Thus, nuclease-gRNA RNPs can carry the selected gRNA to the site of genome editing.

[0091] For example, CasRNPs can be prepared by incubating Cas proteins with selected gRNAs using a molar excess of gRNA over protein (e.g., using a molar ratio of protein to gRNA of about 1:1.1 to 1:1.4). The buffer used during such incubation can include 20 mM HEPES (pH 7.5), 150 mM KCl, 1 mM MgCl2, 10% glycerol, and 1 mM TCEP. Incubation can be performed at 37°C for about 5 minutes to about 30 minutes (10 minutes is usually sufficient). When using a reference DNA or HDR template, it can be added to the CasRNP.

[0092] Nucleofection can be employed to introduce CasRNPs into cells. See, Lin et al., Enhanced homology-directed human genome engineering by controlled timing of CRISPR / Cas9 delivery. Elife 3:e04766. For example, a nucleofection reaction can be performed with approximately 1×10 RNPs in about 10 μl to 40 μl of nucleofection reagent. 4 1×10 7 This may include mixing 2×10 cells with about 5 μl to 30 μl of RNP:DNA. 5 The cells were mixed with approximately 20 μl of nucleofection reagent and approximately 10 μl of RNP:DNA. After electroporation, growth medium is added and the cells are transferred to tissue culture plates for growth and evaluation. Nucleofection reagents and equipment are available from Lonza (Allendale, NJ).

[0093] Thus, the present invention provides agents for use in medical therapy, such as gene therapy vectors, to treat, inhibit or prevent cardiac conditions and diseases. Administration Guide RNA or expression cassette / expression vector capable of expressing guide RNA can be administered to a subject. Modified cells (e.g., fibroblasts) can also be administered to a subject, reducing Meox1 transcription and / or Meox1 enhancer activity. Such guide RNA, expression cassette, expression vector and cells produced as described herein can be employed for the treatment or prevention of cardiac conditions and / or diseases in human patients or other subjects. The patient or subject may be in need of such treatment. In some cases, the patient or subject may not yet exhibit any symptoms of cardiac conditions / diseases or other medical conditions.

[0094] Guide RNA, expression cassette, expression vector, and cells are administered in a manner that allows them to be incorporated, transplanted, or migrate to a specific tissue site, such as cardiac tissue. Such guide RNA, expression cassette, expression vector, and cells can reconstitute or regenerate functionally deficient regions of tissue, including cardiac tissue. For example, devices are available that can be adapted to administer cells to cardiac tissue.

[0095] For treatment, the guide RNA, expression cassette, expression vector, and / or cells (e.g., fibroblasts, myofibroblasts, cardiac cells, etc.) may be administered locally or systemically. Administration may be by injection, catheter, implantable device, etc. The guide RNA, expression cassette, expression vector, and cells may be administered in any physiologically acceptable excipient or carrier that does not adversely affect the subject. For example, the guide RNA, expression cassette, expression vector, and cells may be administered intravenously or via an intracardiac route (e.g., epicardially or intramyocardially). Methods of administering the guide RNA, expression cassette, expression vector, and / or cells to a subject, particularly a human subject, include injection or implantation of the guide RNA, expression cassette, expression vector, and cells into a target site, or they may be inserted into a delivery device that facilitates the introduction, uptake, incorporation, or implantation of the expression cassette, expression vector, and cells. Such delivery devices include tubes, such as catheters, for introducing cells, expression vectors, and fluids into the body of a recipient subject. The tube may further include a needle, such as a syringe, through which the cells of the invention may be introduced into the subject at a desired location. Multiple injections may be performed using this method.

[0096] The term "solution" as used herein includes carriers or diluents in which the guide RNA, expression cassette, expression vector and cells of the present invention maintain viability and / or functionality. Carriers and diluents that can be used can include saline, aqueous buffer, solvent and / or dispersion medium. The use of such carriers and diluents is available in the art. The solution is preferably sterile and fluid to the extent that easy injection is present.

[0097] The guide RNA, the expression cassette, the expression vector, and the cells can also be embedded in a support matrix. Suitable components include matrix proteins that support or promote the incorporation of the guide RNA, the expression cassette, the expression vector, and the adhesion of the modified cells. In another embodiment, the composition can include a physiologically acceptable matrix scaffold. Such a physiologically acceptable matrix scaffold can be resorbable and / or biodegradable.

[0098] In some cases, cardiac cells can be modified to express guide RNAs and optionally nucleases. In addition, cardiac cells can be modified with guide RNAs and nucleases to generate a population of modified cells with reduced Meox1 expression and / or reduced activity of at least one Meox1 regulatory element.

[0099] The population of modified cells produced by the methods described herein may contain a low percentage of non-fibroblasts (e.g., other cardiac cells and / or endothelial cells). For example, a population of modified cells for use in compositions and administration to a subject may contain less than about 90% non-fibroblasts, less than about 85% non-fibroblasts, less than about 80% non-fibroblasts, less than about 75% non-fibroblasts, less than about 70% non-fibroblasts, less than about 65% non-fibroblasts, less than about 60% non-fibroblasts, less than about 55% non-fibroblasts, less than about 50% non-fibroblasts, less than about 45% non-fibroblasts, less than about 40% non-fibroblasts, less than about 35% non-fibroblasts, less than about 50 ... The cell population may have fibroblasts, less than about 30% non-fibroblasts, less than about 25% non-fibroblasts, less than about 20% non-fibroblasts, less than about 15% non-fibroblasts, less than about 12% non-fibroblasts, less than about 10% non-fibroblasts, less than about 8% non-fibroblasts, less than about 6% non-fibroblasts, less than about 5% non-fibroblasts, less than about 4% non-fibroblasts, less than about 3% non-fibroblasts, less than about 2% non-fibroblasts, less than about 1% non-fibroblasts, relative to total cells in the cell population.

[0100] Many cell types are capable of migrating to appropriate sites for regeneration and differentiation within a subject. To determine the suitability of various therapeutic administration regimens and doses of cell compositions, fibroblasts or other types of cells can first be tested in appropriate animal models. At one stage, the cells are evaluated for their ability to survive and maintain their phenotype in vivo. The cells can also be evaluated to see if they migrate to diseased or damaged sites in vivo, or to determine the appropriate number or dose of cells to be administered. The cell compositions can be administered to immunodeficient animals (e.g., nude mice, or animals rendered immunodeficient chemically or by irradiation). Tissues can be harvested after a period of repopulation and evaluated for whether the administered cells or their progeny are still present, alive, and / or have migrated to desired or undesired locations.

[0101] Injected fibroblasts or other cell types can be tracked by a variety of methods. For example, cells that contain or express a detectable label (e.g., green fluorescent protein or beta-galactosidase) can be easily detected. Cells can be tracked by BrdU or 3 The modified cells can be pre-labeled by the introduction of an expression cassette capable of expressing [H]-thymidine, or green fluorescent protein, or beta-galactosidase. Alternatively, the modified cells can be detected by the expression of a cell marker not expressed by the animal used in the test (e.g., a human-specific antigen when the cells are injected into an experimental animal). The presence and phenotype of the administered modified cell population can be assessed by fluorescence microscopy (e.g., for green fluorescent protein or beta-galactosidase), by immunohistochemistry (e.g., using antibodies against human antigens), by ELISA (using antibodies against human antigens), or by RT-PCR analysis using primers and hybridization conditions that cause specific amplification of RNA that exhibits a cardiac phenotype.

[0102] The modified cells may be included in the composition in various amounts depending on the severity of the disease or condition of the subject. For example, the composition may be about 10 3 ~about 10 12 modified cells, or about 10 4 ~about 10 10 modified cells, or about 10 5 ~10 8 The modified cells may be prepared in a liquid form for local or systemic administration.

[0103] An expression vector capable of expressing an RNP containing one or more guide RNAs or one or more guide RNAs, a nuclease, or a combination thereof, can also be administered with or without cells.

[0104] The guide RNA, nuclease, and / or RNP, with or without additional cells, may be administered in the composition as a single dose, in multiple doses, in a continuous or intermittent manner, for example, depending on the physiological state of the recipient, whether the purpose of administration is to respond to a stressful event or for a more sustained therapeutic purpose, and other factors known to those skilled in the art. The administration of the composition of the present invention may be as a single dose, or essentially continuous over a preselected period of time, or in a series of doses spaced apart. Both local and systemic administration are contemplated.

[0105] It will be understood that the amount of guide RNA, nuclease, RNP, and / or cells used in treatment may vary depending on the specific carrier selected, as well as the route of administration, the nature of the condition being treated, and the age and condition of the patient. Ultimately, the attending medical care provider may determine the appropriate dosage.

[0106] The following examples provide some of the work relevant to the development of the present invention. The following publications by the inventors provide further details: Alexian et al. (A Transcriptional Switch Governing Fibroblast Plasticity Underlies Reversibility of Chronic Heart Disease, bioRxiv (July 2020) doi.org / 10.1101 / 2020.07.21.214874, incorporated herein by reference in its entirety).

[0107] Example 1: Materials and Methods This example describes some of the materials and methods used in the development of the present invention.

[0108] Animal models All animal use protocols were approved by the University of California, San Francisco Institutional Animal Care and Use Committees and were performed in strict accordance with the National Institutes of Health Guide for Care and Use of Laboratory Animals. Studies were performed using age-matched male C57B1 / 6J mice. Mice were housed in a temperature- and humidity-controlled pathogen-free facility on a 12-h light / dark cycle.

[0109] Preparation of JQ1 JQ1 was synthesized and purified in Jun Qi's laboratory (Dana-Farber Cancer Institute) as described by Filippakopoulos et al. (Nature 468, 1067-1073 (2010)). For in vivo experiments, a stock solution [50 mg / ml JQ1 in dimethyl sulfoxide (DMSO)] was diluted to a working concentration of 5 mg / ml in an aqueous carrier (10% hydroxypropyl b-cyclodextrin; Sigma C0926) using vigorous vortexing. Mice were injected intraperitoneally once daily at a dose of 50 mg / kg. The vehicle control was an equal volume of DMSO dissolved in a 10% hydroxypropyl b-cyclodextrin carrier solution. All solutions were prepared and administered using sterile technique. For in vitro experiments, JQ1 was dissolved in DMSO and administered to cells at a final concentration of 500 nM, and an equal volume of DMSO was used as a control.

[0110] A mouse model of transverse aortic constriction, echocardiography and quantification of fibrosis All mice were 8-10 week old male C57Bl / 6J mice from The Jackson Laboratory (Stock Number: 000664). Mice were placed on a temperature-controlled small animal operating table to help maintain body temperature (37°C) during surgery. Mice were anesthetized with isoflurane, placed on a ventilator (Harvard Apparatus), and a thoracotomy was performed. For transverse aortic constriction (TAC) surgery, the aortic arch was constricted between the left common carotid artery and the brachiocephalic artery using 7-0 silk suture and a 25-gauge needle as described by Anand (Cell 154:569-582 (2013)). Intraperitoneal infusion of JQ1 (50 mg / kg / day) or vehicle was administered 18 days after TAC surgery and continued as described in Figure 2B. For sham surgery, a thoracotomy was performed as above and the aorta was surgically exposed without further intervention. For echocardiography, mice were anesthetized with 1% inhaled isoflurane and imaged using a Vevo 3100 High Resolution Imaging System (FujiFilm VisualSonics) and an MX550S probe. Measurements were obtained from M-mode sampling and integrated electrocardiogram-gated kilohertz visualization (EKV) images acquired in the ventricular (LV) short axis at the mid-papillary level as described in Anand (2013). Left ventricular area and ejection fraction were obtained from high-resolution two-dimensional measurements at end diastole and end systole as described in Anand (2013). For quantification of fibrosis in TAC JQ1 and TAC JQ1-withdrawn animals, mice were euthanized 62 days after TAC. Hearts were explanted after perfusion with 10 ml of PBS via introduction of a 22.5 G needle into the left ventricular apex and dissection of the right atrium. Hearts were washed in PBS and fixed overnight in 2% PFA, followed by graded dehydration to 100% ethanol. For paraffin embedding, hearts were processed in an automated system through a series of PBS washes, ascending alcohol (Aga), Clear Rite 3™ (Richard-Allan Scientific), and Shandon Histoplast (Thermo Scientific) at 56° C. Hearts were embedded in paraffin and cut transversely (3 μm sections).Sections representing different Z positions of the ventricle from the base to the apex of the atrium were dewaxed, rehydrated, and stained with picrosirius red (ab150681) according to the manufacturer's protocol. Sections were diaphanized in xylene and mounted in DPX Mountant (06522, Sigma-Aldrich) for histological examination. Images were acquired on a Leica DMi8 Widefield with a 4x objective and analyzed using FIJI software. In Fiji, images were separated into red, green, and blue channels, and fibrosis and total tissue section area were measured using the threshold tool for the green and blue channels, respectively. Percentage of fibrosis was normalized to total tissue section area, and a total of 24 sections were analyzed per animal. Statistical analysis of data was performed using Prism8, and statistical significance was determined at p<0.05. Tukey's multiple comparison test was applied. Normality was not established by the D'Agostino-Pearson omnibus normality test, so the Independent Samples Mann-Whitney U test was used. A blinded method (labeling of samples by alphanumeric codes) was performed for fibrosis analysis.

[0111] Langendorff perfusion and subsequent cell and nuclei isolation for single-cell RNA and ATACseq Cell isolation from mouse hearts was performed as described by Li et al. (J. Vis. Exp. (2014)) with modifications. Briefly, after reaching an appropriate level of anesthesia, a thoracotomy was performed and the mouse heart was isolated. The isolated heart was cannulated and perfused with perfusion buffer (120.4 mM NaCl, 14.7 mM KCl, 0.6 mM KH2PO4, 0.6 mM Na2HPO4, 1.2 mM MgSO4, 10 mM Na-HEPES, 4.6 mM NaHCO3, 30 mM taurine, 10 mM 2,3-butanedione monoxime, and 5.5 mM glucose, pH 7.0) in a Langendorff perfusion system (Radnoti 120108EZ) for 5–10 min at 37 °C. The cannulated hearts were then digested with digestion buffer (perfusion buffer containing 300 units / mL collagenase II (Worthington Biochemical) and 50 μM CaCl2) for approximately 10 min at 37 °C. At the end of digestion, the atria and great vessels were removed and the ventricular tissue was transferred into stop buffer (perfusion buffer containing 10% fetal bovine serum) at 37 °C and gently torn into small pieces. After gentle pipetting, the cell suspension was passed through a 250 μM strainer in a Falcon tube and then at room temperature (RT) for 3 min at 30 × g. The supernatant (containing most non-cardiomyocytes (CM)) was then separated from the pellet (containing the CM fraction). The non-CM fraction was centrifuged again at 30 × g for 3 min at room temperature and the supernatant was saved. The supernatant was then filtered using a cell strainer (70 μm) and finally centrifuged at 400 × g for 3 min at room temperature to remove debris. The non-CM pellet was finally resuspended in 1 mL of cold PBS 0.5% BSA. 30,000 cells were counted with trypan blue using a hemocytometer and then used for subsequent 10X Genomics Chromium® single-cell RNAseq preparation. For single-cell ATAC, 500,000 isolated and purified non-CM were resuspended in 100 μL of lysis buffer (Tris-HCl 10 mM pH 7.4, NaCl 10 mM, MgCl2 3 mM, Tween®-20 0.1%, P40 0.1%, digitonin 0.01%, BSA 1% in nuclease-free water), pipetted 10 times, and placed on ice for 5 min.Nuclei were then washed with 1 mL of 1x PBS containing 1% BSA, followed by centrifugation at 4°C for 5 min. The nuclear pellet was resuspended in 1 mL of 1x PBS containing 1% BSA and filtered using a 10 μM filter (pluriSelect #43-50010-00). Nuclei were then counted with DAPI using a hemocytometer, and finally 30,000 non-CM nuclei were used for the subsequent 10X Genomics Chromium® single-cell ATACseq preparation. After the first centrifugation, the CM fraction was centrifuged again in stop buffer at 30×g for 3 min at room temperature, and the supernatant was discarded. The CM pellet was finally centrifuged in stop buffer at 400×g for 3 min at room temperature, followed by discarding the supernatant, and the cell pellet was dissolved in Qiazol® (miRNeasy kit - Qiagen) for subsequent RNA extraction.

[0112] Bulk RNA sequencing in purified cardiomyocytes Total RNA from CM was extracted using miRNeasy kit (Qiagen) according to the manufacturer's instructions and quantified using Nanodrop® (Thermo scientific). After RNA quality control using Bioanalyzer Agilent 2100 (Agilent Technologies), paired-end poly(A) enriched RNA libraries were prepared for 9 samples: Sham (x3), TAC-Veh (x3) and TAC-JQ1 (x3) using ovation RNA-seq universal kit (NuGEN; strand-specific) from Gladstone Genomic core. High-throughput sequencing was performed on a NextSeq® 500 instrument (Illumina) using PE75 runs. Read results were mapped against the mm10 reference mouse genome using STAR (v2.7.3a) and assigned to Ensembl genes. We quantified gene expression using raw counts and retained protein-coding genes that showed average FPKM values ​​>0.5 FPKM across samples. where FPKM is the Fragments Per Kilobase of transcript per Million mapped reads. We then performed differential gene expression testing using default settings in DESeq2 (v.1.24.0 R package, see Love et al. (Genome Biol. 15, 550 (2014)). Statistical significance was set at 5% false positive rate (FDR; Benjamini-Hochberg).

[0113] Single-cell transcriptome library preparation, sequencing, and processing Single-cell droplet libraries (Figure 2C) derived from non-CM cell suspensions (2x Sham, 2x TAC-Veh, 2x TAC-JQ1 and 2x TAC-JQ1 withdrawal) were generated on a 10X Genomics Chromium® Controller following the manufacturer's instructions within the Chromium® Single Cell 3' Reagent Kit v.2 User Guide. Additional components used in library preparation include the Chromium® Single Cell 3' Library and Gel Beads Kit v.2 (PN-120237) and the Chromium® Single Cell 3' Chip Kit v.2 (PN-120236). Libraries were prepared using the Chromium® Single Cell 3' Library and Gel Beads Kit v.2 (PN-120237) and the Chromium® i7 Multiplex Kit (PN-120262) following the manufacturer's instructions. The final libraries were sequenced on a NextSeq® 500 (Illumina) for quality control runs, followed by NovaSeq® (Illumina) for deeper sequencing. All 8 samples were pooled and sequenced in a single lane. Sequencing parameters were selected according to the Chromium® Single Cell v.2 specifications. All libraries were sequenced to an average read depth of at least 50,000 total aligned reads per cell. Raw sequencing reads were processed using the Cell Ranger v.2.2.0 pipeline from 10X Genomics. Briefly, reads were demultiplexed, aligned to the mouse mm10 genome, and the absolute number of observed transcripts (UMI counts) were quantified per gene per cell to generate a gene-barcode matrix. Data from the 8 samples were aggregated and normalized to the same sequencing depth, resulting in a combined gene-barcode matrix for all samples.

[0114] Cell filtering and cell type clustering for transcriptome analysis Transcriptomes were sequenced from 35,551 cells from our eight samples (Figure 2C). Filtering and clustering analysis of these cells was performed using the Seurat v.2.2R package. Cells were normalized for expressed genes per cell and per total expression, then multiplied by a scale factor of 10,000 and log-transformed. Low-quality cells were excluded from our analysis. This was achieved by excluding cells with more than 4,000 and less than 1,000 genes, and cells with a high proportion of mitochondrial genes (>0.2%). Following the filtering step, we normalized the data (NormalizeData function, default scale factor of 10,000) and performed a linear regression on all genes (ScaleData function). We then performed a linear dimensionality reduction (RunPCA function). Significant principal components were used for downstream graph-based semi-supervised clustering into distinct populations (FindClusters function), and uniform manifold approximation and projection (UMAP) (Becht et al. Nat. Biotechnol. 37:38-44 (2018)) dimensionality reduction was used to project the cell populations into two dimensions. For clustering, a resolution parameter was approximated based on cell number according to the guidelines of Seurat; a vector of resolution parameters was passed through the FindClusters function to select the optimal resolution that established distinguishable clusters with distinct marker gene expression. We obtained a total of nine clusters representing the main adult cardiac non-CM cell populations. To identify the marker genes driving each cluster, clusters were compared pairwise for differential gene expression using a likelihood ratio test assuming an underlying negative binomial distribution (negbinom) (FindAllMarkers function). We then isolated specific clusters (WhichCells function) for subsequent analysis of fibroblast (cluster 0), myeloid (cluster 1) and endothelial (clusters 2 and 3) populations. Differential gene analysis between samples in the three major cell populations was performed using the function diffExp=FindMarkers.For visualization of gene expression data across different samples, several Seurat functions were used: FeaturePlot, VlnPlot, and DotPlot. To calculate normalized expression scores, a specific gene set was passed to the Seurat object to generate a score. To analyze gene feature scores across all fibroblasts, we aggregated the mean scaled and Z-score normalized gene expression for a given gene in each cell (Hu et al. Nat. Methods 17:833-843 (2020)). The resulting scores were then plotted in a violin plot.

[0115] Single-cell ATAC library preparation, sequencing, and processing After successful nuclei isolation, the nuclei were then processed according to the 10X Genomics Single Cell ATAC Kit v1.0 (PN-1000110) by first incubating with Tn5 transposase for 1 hour, followed by GEM generation and barcode amplification using the 10X Genomics Chromium® Controller according to the manufacturer's instructions. Additional components used in library preparation included the Chromium® Chip E Single Cell ATAC Kit (PN-1000082) and the Chromium® i7 Multiplex Kit N, Set A primers (PN-1000084). The final libraries were sequenced on a NextSeq® 500 (Illumina) for quality control runs, followed by NovaSeq® (Illumina) for deeper sequencing. All eight aforementioned samples (2xSham, 2xTAC-Veh, 2xTAC-JQ1 and 2xTAC-JQ1 withdrawal) (Figure 2C) were pooled and sequenced in a single lane on a NovaSeq®. Sequencing parameters were selected according to the Chromium® Single Cell ATAC v1.0 specifications. All libraries were sequenced to a median read depth of at least 2,500 fragments / nucleus. Raw sequencing reads were processed using the Cell Ranger ATAC v1.0 pipeline from 10X Genomics. Briefly, reads were demultiplexed and aligned to the mouse mm10 genome. As a test of sample quality, a minimum of 70% of fragments overlapped with the target region as measured by CellRanger. Peaks were then called on the aggregated fragments, and barcodes with fewer fragments within these peaks than an automatically determined threshold (usually around 200) were then discarded. The number of remaining fragments was counted to generate a peak-by-barcode matrix.

[0116] Identification of cell types within single-cell ATAC samples based on scRNA-seq We identified a list of marker genes for each cluster in the scRNAseq data. Then, for each cell in each scATACseq sample, we calculated the percentage of accessible peaks of the cell that reside within the promoters of the marker genes of each cluster. We calculated a complete cell-cell similarity matrix for each sample using Jaccard similarity of the binarized peak-by-cell matrix generated by CellRanger. Figure 2J shows an example of mapping cluster 1 from the scRNA-seq data to the scATAC-seq sample. For example, the cells marked with darker dots in the rightmost panel of Figure 2J have accessible promoters of myeloid marker genes. The shading of each cell in Figure 2J reflects how similar they are to a single selected cell. We then calculated an overall impact score for each marker using the method described in Przytycki & Polland (BioRxiv(2019).doi:10.1101 / 847657). For each sample, we selected the parameter s that maximized the median influence of the labels corresponding to the three cell types of interest (fibroblast, myeloid, endothelial) in cells with accessible promoters for the three selected marker genes (Dcn, Lyz2, Fabp4, respectively). We assigned a type to each cell based on the label that had the greatest influence on that cell. Figure 2J shows that when cells are reprojected into tSNE space using the influence score, cells with the same label cluster together (this projection is used for illustrative purposes only). Using this method, we identified 5,215 as fibroblasts, 4,278 as endothelial, and 3,444 as myeloid cells across eight samples.

[0117] Determination of cell type enriched peaks in single-cell ATAC To avoid bias, we calculated cell type enriched peaks for each sample separately by comparing the accessibility of each type of cell to that of the other types of cells. To determine which peaks were enriched in a cell type for each cell type, we repeatedly sampled (10 times each) an equal number of sets of cells with a similar number of accessible peaks that were not of that type, and calculated a one-sided Wilcoxon test to determine whether each peak was more accessible in the examined cell type. We then combined the p-values ​​collected using Fisher's method and adjusted for multiple hypothesis correction using the Benjamini-Hochberg procedure. We considered a peak to be enriched in a cell type if it was significant at FDR<0.1. For each cell type, we discarded any peaks that were not replicated in at least one other sample. This identified 22,467 fibroblast-enriched peaks, 12,602 endothelial-enriched peaks, and 11,156 myeloid-enriched peaks. Note that a peak may be enriched in more than one cell type.

[0118] Calculation of single-cell ATAC-normalized accessibility scores For each peak, we calculated a normalized accessibility score for each cell as 1 over the total number of accessible peaks in that cell. To calculate the overall accessibility trend in cell types and conditions, we calculated the fraction of all cell type enriched peaks in cells that are accessible in that condition. For genome-wide normalized accessibility (e.g., for browser tracks), we instead normalized by the number of fragments. To do this, we first found all fragments that correspond to the barcodes of the cells for which we wanted to calculate genome-wide accessibility. We created a bedgraph by merging the bed files of those cells using the unionBedGraphs function in bedtools2. We assigned an accessibility score to each region of the combined bedgraph as the sum of the number of fragments in each cell in that region over the number of cells used in the combination, over the total number of fragments in that cell. To calculate the coaccessibility between peaks and promoters, we counted the number of cells in which both the promoter and the peak were accessible, and normalized by the promoter accessibility.

[0119] Calculation of TF enrichment scores from single-cell ATAC data To assess the significance of changes in transcription factor binding between conditions for each cell type, we associated transcription factor binding locations with gene expression changes by training a supervised learning model. We used transcription factors (TFs) with known vertebrate motifs included in HOMER and selected the top 10 with the most expressed TFs in TACs in fibroblasts, bone marrow and endothelial cells. First, all accessible binding sites for each transcription factor were determined in each condition using the “findMotifsGenome.pl” command in HOMER with the “-find” option using the set of distal cell type enriched peaks for that condition. We then constructed a g-by-m matrix M for each condition c by calculating the distance from each binding site to the transcription start site of each gene. cwhere g is the number of genes and m is the number of transcription factors. For each gene i and each binding position k of motif j, the corresponding entry in the matrix was defined as follows:

[0120]

number

[0121] Next, the difference in motif binding strength between the two conditions c1 and c2 is

[0122]

number

[0123] Then, given a vector Y of length g of the log fold change in gene expression between two conditions, we calculated the importance of each transcription factor as the difference in expression change of genes associated with that transcription factor minus genes not associated with that transcription factor, taking into account the effects of other transcription factors using a targeted maximum likelihood estimation (tMLE) approach described in Stone et al. (Cell Stem Cell 25:87-102.e9 (2019)).

[0124] Construction of an atlas of super-enhancers and correlation between chromatin accessibility and ejection fraction To find super-enhancers, we first used single-cell ATAC data from TAC Veh samples to stitch together all cell type enriched peaks within 12.5 kb of each other that were not separated by genes. We then calculated the normalized accessibility for each potential super-enhancer and determined the threshold at which a region could be called a super-enhancer using the ROSE algorithm (Whyte et al. Cell 153:307-319 (2013)). Using this method, we constructed a super-enhancer catalog for fibroblasts, bone marrow and endothelial cells in diseased hearts (TAC Veh). We then calculated how well the accessibility of each super-enhancer correlated with left ventricular ejection fraction (EF). For each super-enhancer, we fitted a linear model using the vector of EF observations across the four conditions as the response variable and the average accessibility across the given cell type and across other cells as types as a binomial vector. The fit coefficient of the model for a given cell type is the amount of change in EF explained by changes in accessibility in that cell type when controlling for changes in accessibility in other cell types. We call this value the correlation coefficient for each super-enhancer in each cell type, and the significance of each coefficient is determined by the p-value of that term in the linear model. For comparison, super-enhancers were generated using the same method using H3K27Ac peaks from in vitro unstimulated and TGF-β cell lines (see below).

[0125] Generation of cardiac fibroblast immortalized cell lines, culture conditions and TGFβ stimulation Tcf21MCM mice (Acharya et al., Genesis 49, 870-877 (2011)) were crossed with Rosa26-Ai6 mice (Jackson Laboratory stock #007906) to express Tcf21 MCM / + ;Rosa26 Ai6 / +Mice were generated. At 10 weeks of age, they were injected intraperitoneally with tamoxifen (75 mg tamoxifen / kg) for 5 days (once a day). Tamoxifen was prepared according to the Jackson Laboratory guidelines (see website jax.org / research-and-faculty / resources / cre-repository / tamoxifen#). Five days after injection, mice were sacrificed and non-cardiomyocytes were isolated via Langendorff perfusion (see Methods section "Langendorff perfusion and subsequent cell and nuclei isolation for single-cell RNA and ATACseq" for details). One hundred thousand ZsGreen positive cells were sorted using a BD AriaII sorter and cultured for 3 days at 37 °C in a humidified incubator with 5% CO2 and maintained in fibroblast medium: high glucose DMEM (Life Technologies) supplemented with 10% fetal bovine serum (FBS) (Hyclone, GE Healthcare), 1x non-essential amino acids (NEAA), 10 U / ml penicillin / streptomycin and 1 mM sodium pyruvate (all from Life Technologies). Because primary cells undergo only a finite, predefined number of cell divisions in culture before entering a state of replicative senescence, we employed a widely used method to immortalize mammalian cells in culture based on the expression of Simian Virus 40 (SV40) T antigen. For fibroblast immortalization, 3 days after selection, fibroblasts were trypsinized and plated at 5 × 10 per 100 mm plate in the afternoon. 5The cells were replated. The following morning, fresh medium was added to the plates, and 2 hours later, fibroblasts were infected with 5 μl of SV40 T antigen-expressing VSV-G pseudotyped lentiviral particles (Alstem, #CILV01) per 100 mm plate in the presence of polybrene (added to a final concentration of 5 μg / ml) according to the manufacturer's instructions. The following day, medium containing viral supernatant was removed and fibroblasts were returned to high glucose DMEM (Life Technologies) supplemented with 10% fetal bovine serum (FBS) (Hyclone, GE Healthcare), 1× non-essential amino acids (NEAA), 10 U / ml penicillin / streptomycin and 1 mM sodium pyruvate (all from Life Technologies). After 72 hours, cells were trypsinized and split 1:2 into two 100 mm plates. Infected cells were then positively selected for stable cell line generation by adding puromycin (final concentration 1 μg / ml) to the medium. After 10 days of puromycin selection, multiple clones were picked for expansion. For routine cell line maintenance, fibroblasts were split every 2–3 days and medium was changed every other day. The same medium was used for HEK-293T cell culture for lentivirus production (see next section). For TGF-β stimulation, 1 × 10 cells were cultured in a 6-well plate on day 1. 5 Fibroblasts were seeded at 100 / well. On day 2, the medium was changed to the same basal medium with 0.5% FBS. On day 3, TGF-β1 (Peprotech #100-21C) was added to the medium at a concentration of 10 ng / ml. Cells were harvested on day 5 for downstream analysis.

[0126] RNA extraction, RT-PCR, and real-time PCR analysis Quantitative RT-PCR. Cells were harvested in TRIzol™ LS Reagent (Invitrogen) and total RNA was extracted using the Direct-Zol RNA kit (Zymo Research) according to the manufacturer's instructions. 500ng of RNA was converted to cDNA using SuperScript® III First-strand Synthesis SuperMix for qRT-PCR (Invitrogen). For Taqman® real-time PCR, 1 / 50 of the cDNA was applied to a quantitative PCR reaction using Taqman® Universal PCR Master Mix (Life technologies). PCR was performed on a 7900HT Fast Real-Time System (Applied Biosystem). Taqman® probes are listed in the "Taqman Probe Table". For eRNA expression analysis, 1 / 30 of the cDNA was applied to a quantitative PCR reaction using SsoAdvanced Universal SYBR green supermix (Bio-Rad). Primer sequences are listed in the "Table of Syber Primers for Enhancer RNA (eRNA)". All gene expressions were normalized to the Actb gene.

[0127] Precision Nuclear Run-On Sequencing (PROseq) PRO-seq experiments were performed as reported by Kwak et al. (Science 339:950-953 (2013)) with some modifications. Briefly, 3 million cardiac fibroblasts were cultured as previously described in this method. After 48 hours of TGFβ treatment, cells were washed three times with cold PBS, then sequentially swollen in swelling buffer (10 mM Tris-HCl pH 7.5, 2 mM MgCl2, 3 mM CaCl2) for 10 minutes on ice, harvested, and lysed in lysis buffer (swelling buffer plus 0.5% NP-40, 20 units of SUPERase-In, and 10% glycerol). The resulting nuclei were washed two more times with 5 ml of lysis buffer, resuspended in 200 μl of freezing buffer (50 mM Tris-HCl pH 8.3, 40% glycerol, 5 mM MgCl2, 0.1 mM EDTA) and divided into two equal aliquots (aliquot A: no cap removal; aliquot B: cap removal). For run-on assays, the resuspended nuclei were mixed with an equal volume of reaction buffer (10 mM Tris-HCl pH 8.0, 5 mM MgCl2, 1 mM DTT, 300 mM KCl, 20 units of SUPERase-In, 1% Sarkosyl, 100 M A / GTP, 100 μM Biotin-11-C / UTP (Perkin-Elmer)) and incubated for 5 min at 30°C. The resulting nuclear-run-on RNA (NRO-RNA) was then extracted using TRIzol™ LS reagent (Life Technologies, Cat#10296-028) according to the manufacturer's instructions. NRO-RNA was fragmented to 200-500 nt by alkaline base hydrolysis for 30 min on ice, neutralized by adding 1× volume of 1 M Tris-HCl pH 6.8, and excess salts and residual NTPs were removed using a P-30 column (Bio-Rad, Cat#732-6250). Biotin-labeled RNA was enriched by precipitating the fragmented nascent RNA twice with 10 μl of MyOne Streptavidin C1 Dynabeads (Invitrogen, Cat#65001) according to the manufacturer's instructions.The beads were washed twice with high salt (2M NaCl, 50mM Tris-HCl pH 7.5, 0.5% Triton® X-100, 0.5mM EDTA), once with medium salt (1M NaCl, 5mM Tris-HCl pH 7.5, 0.1% Triton® X-100, 0.5mM EDTA), and once with low salt (5mM Tris-HCl pH 7.5, 0.1% Triton® X-100). Bound RNA was extracted from the beads using Trizol (Invitrogen, Cat#15596-018) in two successive extractions and the RNA fractions were pooled followed by ethanol precipitation.

[0128] In this step, the 5' cap was removed from the nascent RNA by incubating only aliquot B with RNA 5' pyrophosphohydrolase in decapping mix (1x Thermopol buffer NEB (B9004S), 20 units SUPERase-In) for 1 hour at 37°C. The decapping reaction was stopped by heating the samples for 5 minutes at 65°C and the RNA was extracted with Trizol (Invitrogen, Cat#15596-018) followed by ethanol precipitation. Both aliquots were then 5' phosphorylated by incubation in T4 reaction mix (T4 polynucleotide kinase (NEB #M0201L), 1x PNK buffer (NEB #B201S), 10 mM ATP (NEB #B0706A)) for 1 hour at 37°C. The RNA was extracted with Trizol (Invitrogen, Cat#15596-018) followed by ethanol precipitation. Libraries were generated using the NEBNext® Multiplex Small RNA Library Prep Set (NEB, Cat#E7300S) according to the manufacturer's instructions. cDNA products were separated on a 10% polyacrylamide TBE-urea gel and only fragments migrating between 200-500 bp were excised and recovered by gel extraction. Finally, libraries were quantified using Qubit® and sent to sequence SR75bp on a HiSeq® 4000 platform (Illumina).

[0129] PROseq analysis FastQ files obtained from deep sequencing were used to remove low-quality reads using Trimmomatic (Bolger et al. Bioinformatics 30:2114-2120(2014)). Trimmed FastQ files from aliquot A (no cap removal) and aliquot B (cap removal) were aligned together against the reference genome (mm10) using Bowtie2 (see website bowtie-bio.sourceforge.net / bowtie2 / ). The resulting alignment files were used to generate a Tag Directory for downstream analysis using homer (see website homer.ucsd.edu / homer / ). Differential expression of coding genes and distal elements was performed using the homer commands analyzeRepeats.pl and getDiffExpression.pl (see homer.ucsd.edu / homer / ngs / diffExpression.html). A minimum transcription threshold was used to select differentially transcribed genes (average number of lines x>20 across all samples for distal elements, average number of lines x>40 across all samples for protein-coding genes). Histogram plots were generated using the histogram mode of the command annotatePeaks (see homer.ucsd.edu / homer / ngs / annotation.html). We used a tool called makeMetaGeneProfile.pl to generate metagene histograms (see homer.ucsd.edu / homer / ngs / quantification.html). Finally, enhancers were called based on the density of PROseq tags using the homer commands findPeaks and getDistalPeaks.pl (see homer.ucsd.edu / homer / ngs / groseq / groseq.html).

[0130] CRISPR interference (CRISPRi) for sequence-specific suppression CRISPRi was used to suppress enhancer activity. The lentiviral plasmid pHR-SFFV-KRAB-dCas9-mcherry (gift from Dr. Jonathan Weissmen, Addgene: 60954) was used. To construct the gRNA lentiviral vector, pU6-sgRNAEF1Alpha-puroT2A-BFP (gift from Dr. Jonathan Weissmen, Addgene: 60955) was modified by replacing the puromycin gene with a hygromycin gene to generate pU6-sgRNAEF1Alpha-HygT2A-BFP. A pair of synthetic gRNA oligos with 5' and 3' overhangs (Table of CRISPRi guide RNAs targeting enhancers) were annealed and subcloned into BstXI and BlpI double-digested pU6-sgRNAEF1Alpha-HygT2A-BFP by ligation with T4 ligase. The constructs were verified by sequencing (Quintara Bio, Berkeley, CA). gRNAs for suppressing enhancer peaks were selected by the program Chopchop (see chopchop.cbu.uib.no). To generate lentiviral particles, 2 × 10 6HEK-293T cells were seeded in 100 mm plates one day prior to transfection and cultured in 10 ml of fibroblast medium. On the day of transfection, the old medium was supplemented with 8 ml of fresh medium, and then 5 μg of the desired lentiviral vector was co-transfected with 2.5 μg of the envelope protein vector pMD2.G (Addgene: 12258), and 2.5 μg of the packaging vector psPAX2 (Addgene: 12260) into HEK 293T cells using 59 μl of FUGENE® HD Transfection Reagent (Promega, San Luis Obispo, CA) according to the manufacturer's instructions. 48 hours after transfection, the supernatant was harvested and 12 ml of fresh medium was added to the plate, which was then cultured for an additional 24 hours before a second supernatant harvest. All supernatants were filtered through a 45 μm PVDF syringe filter (Thermo Fisher Scientific) to remove cell debris contamination. The resulting supernatant was then used to perform transduction in cardiac fibroblasts. First, we generated a fibroblast CRISPRi control line. We transduced fibroblasts with a lentiviral vector expressing KRAB-dCas9-mcherry. Then, we harvested the fibroblasts and selected single cells into 96-well plates by flow cytometry (BD Arial II) to generate clonal fibroblast lines expressing the CRISPRi machinery. The expression of dCas9 was confirmed by Western blot (data not shown), and the fibroblast line with the highest expression of dCas9 (referred to as clone C1) was used for subsequent experiments. For the generation of fibroblast lines with targeted suppression of enhancer regions in this study, the aforementioned C1 clone was transduced with three gRNA viral vectors targeting the desired regions (one gRNA targeting the center of the enhancer peak, the other gRNAs targeting both ends of the peak). A pure polyclonal population of targeting gRNA was selected by hygromycin selection at 200 μg / ml for 7 days. These gRNA-C1 cell lines, along with the C1 control line, were then used for TGF-β stimulation (see other sections herein).

[0131] Creation of the Meox1 enhancer peak 9 / 10 deletion in cardiac fibroblasts To create deletions in immortalized cardiac fibroblasts, we used CRISPR / Cas9 ribonucleoprotein complex (RNP)-mediated genome editing. Two crRNA oligos (upper-crRNA: AGGCTTCACTTACCCTAGAC (SEQ ID NO: 18); Down-crRNA: CAATAATGGGCTCTGTAAGG (SEQ ID NO: 19)) flanking the desired deletion region (Mm Chr17: chr17: 43,591,446-43,592,491) were synthesized along with TracRNA oligos and obtained from Integrated DNA Technologies (IDT). Prior to transfection, 240 pmol of each crRNA oligo was annealed with an equal amount of TracRNA to form guide RNA complexes. This was done by heating the mixture to 95°C for 5 min and cooling at room temperature for 30 min. The guide RNA mixture was then mixed with 40 pmol of spCas9 protein (Macro Lab, UCB) and incubated for 15 min at room temperature with 20 μl of transfection solution of P2 primary cells 4D Nucleofector x Kit (Lonza).

[0132] The final Cas9:gRNA RNP complex was diluted to 1 × 10 using Prog EN-150 in a Lonza 4D nucleofector (Lonza). 5The cells were nucleofected into cardiac fibroblasts. After transfection, the cells were seeded into one well of a 96-well plate and cultured for 2 days. On the third day, the cells were detached by trypsin and resuspended in 1 ml of fibroblast culture medium. The number of cells was counted and 300 cells were seeded into three 96-well plates to obtain one cell per well. After seeding, only wells with a single cell were marked. After two weeks, when the clones became confluent, one quarter of the cells were transferred to further culture and the remaining three quarters were harvested for genomic DNA extraction. Detection of the deletion was performed by PCR analysis using PrimSTAR® polymerase (TAKARA Bio) with a pair of primers selected from the upstream and downstream of the deletion region (Table: Primers for detection of Meox1 enhancer peak 9 / 10 deletion). The presence or absence of the deletion was confirmed by sequencing the PCR products by Sanger sequencing. The clones were further analyzed using digital PCR to identify biallelic peak 9 / 10 deletion clones. Digital PCR (ddPCR) assay mixtures were prepared in a final volume of 22 μl containing 50–100 ng of genomic DNA, 1× ddPCR Supermix (BioRad Laboratories), and WT and Del primers at final concentrations of 900 and 220 nM, along with FAM- or HEX-labeled probes. 20 μl of assay mixture and 70 μl of ddPCR droplet oil (BioRad Laboratories) were transferred onto a QX100 / 200 DG cartridge (BioRad Laboratories) and then added to a QX100 droplet generator (BioRad Laboratories), which pulls individual samples and oil through a flow-converging junction to generate water in oil droplets. Then, 40 μl of the oil and sample droplet emulsion was transferred to a 96-well plate and PCR reactions were performed in a T100 Thermo Cycler (BioRad Laboratories) at 95°C for 10 minutes, 94°C for 1 minute, and 60°C for 1 minute (repeated 40 cycles), followed by 98°C for 10 minutes.After PCR was completed, plates were then transferred to a QX200 droplet reader (BioRad Laboratories) and analyzed using QX software (BioRad Laboratories). Clones with and without the deletion were used for TGF-β1 stimulation studies.

[0133] Generation of MEOX1-HA cardiac fibroblast cell line The pHR-HAtag-mMeox1 vector was constructed by PCR amplification of the HAtag-mMeox1 fragment from the vector HA-tag-MEOX1 mouse (Twist Biosciences). To generate the pHR-HAtag-mMEOX1 construct, the KRAB and dCas9 cassettes from the pHR-SFFV-KRAB-dCas9-mCherry vector were replaced with the HA-tag-MEOX1 cassette using the Cold-fusion cloning kit from SBI System BioSciences (Palo Alto, CA) according to the instructions provided by the manufacturer. The construct was verified by sequencing. To generate lentiviral particles, the same procedure was used as described in the section "CRISPR interference (CRISPRi) for sequence-specific inhibition". The resulting supernatant was then used to transduce immortalized cardiac fibroblasts with lentiviral vectors expressing HA-tag-MEOX1 and mCherry. A pure polyclonal population of HA-tagged MEOX1 fibroblasts was sorted using flow cytometry (BD Arial II) for stable mCherry expression and was used for subsequent chromatin immunoprecipitation followed by sequencing (ChIPseq).

[0134] ChIP assays, library preparation for sequencing and analysis For ChIP experiments, 10 × 10 cells were cultured in unstimulated and TGFβ-treated conditions. 6Immortalized cardiac fibroblasts (HA-tagged-MEOX1 fibroblasts for MEOX1 ChIPseq) were pelleted, suspended in 10 ml of DMEM, and crosslinked in 1% formalin solution (Thermo Fisher Scientific) by rocking for 10 min at room temperature. Crosslinking was then quenched by adding glycine (final concentration 0.125 M) for 5 min. Samples were centrifuged at 1000 rcf for 5 min at 4°C. Cells were washed with 10 ml of cold 1x PBS supplemented with protease and phosphatase inhibitors (Roche #4693132001) and the pellets were flash frozen in liquid nitrogen. All samples were stored at -80°C until use. When ready, cell pellets were incubated in cell lysis buffer (20 mM Tris-HCl, pH 8, 85 mM KCl, 0.5% NP-40, protease inhibitors) for 10 min on a rotator at 4°C. Nuclei were isolated by centrifugation (2,500 × g, 5 min, 4 °C), resuspended in nuclear lysis buffer (50 mM Tris-HCl, pH 8, 10 mM EDTA, pH 8, 1% SDS, protease inhibitors) and incubated for 30 min on a rotator at 4 °C. Chromatin was sheared using a Covaris® S2 sonicator (Covaris Inc) for 20 min (60 s cycles, 20% duty cycles, 200 cycles / burst, intensity = 5) until DNA was in the range of 200-700 base pairs. Chromatin was diluted 3-fold in ChIP dilution buffer (0.01% SDS, 1.1% Triton® X-100, 1.2 mM EDTA, 16.7 mM Tris-HCl, pH 8, 167 mM NaCl, protease inhibitors) and incubated with 3 μl anti-HA antibody (Abcam #9110) or 2 μl anti-H3K27ac (Abcam #4729) or 2 μl anti-H3K9m3 (Abcam #8898) overnight with rotation at 4° C. Antibody-protein complexes were immunoprecipitated with Pierce Protein A / G magnetic beads for 2 hours at 4° C. with rotation.Beads were washed five times (2 min / wash with rotation) with cold RIPA buffer (50 mM HEPES-KOH, pH 7.5, 500 mM LiCl, 1 mM EDTA, 1% NP-40, 0.7% sodium deoxycholate) and then once with cold final wash buffer (1x TE, 50 mM NaCl). Immunoprecipitated chromatin was eluted in elution buffer (50 mM Tris-HCl pH 8.0, 10 mM EDTA, 1% SDS) at 65°C for 30 min with agitation. High salt buffer (250 mM Tris-HCl, pH 7.5, 32.5 mM EDTA, pH 8, 1.25 M NaCl) and proteinase K (New England Biolabs Inc (NEB)) were added and cross-links were reversed overnight at 65°C. Samples were treated with RNaseA and DNA was purified with AMPure XP beads (Beckman Coulter cat#A63881). For subsequent ChIPseq, fragmented ChIP and input DNA were end-repaired, 5'-phosphorylated, and dA-tailed using the NEBNext® Ultra II DNA Library Prep Kit for Illumina (NEB, E7645). Samples were ligated to adapter oligos for multiplex sequencing (NEB, E7335), PCR amplified, and sequenced on an Illumina NextSeq® 500 at Gladstone Institutes. For ChIP qPCR, primers spanning defined regions in the Postn and Meox1 loci (see table for primer sequences) were used to amplify ChIPed and input DNA, and RT-qPCR was performed.

[0135] Trimming of known adaptors and low quality regions of reads for ChIP analysis was performed using Fastq-mcf. Sequence quality control was assessed using FastQC (see www.bioinformatics.babraham.ac.uk / projects / fastqc / ). Alignment to the mm10 reference genome was performed using Bowtie 2.2.4 (Langmead et al., Nat. Methods 9, 357-359 (2012)). Correlation between replicates was tested using multiBamSummary in deeptools 3.5.0 (Ramirez et al. Nucleic Acids Res. 44, W160-5 (2016)). Peaks were called using GEM (Guo et al. PLoS Comput. Biol. 8, e1002638 (2012)). Read counts per peak were generated using featureCounts (Liao et al. Bioinformatics 30, 923-930 (2014)) and normalized to account for differences in sequencing depth between samples using upper quartile normalization separately for ChIP and input samples. For MEOX1 anti-HA and H3K27ac ChIPseq, regions enriched with MEOX1 or H3K27ac were determined using empirical Bayesian F-tests on pseudo-likelihood negative binomial generalized log-linear models of count data, as implemented in edgeR. Specifically, we tested for significant (i.e., non-zero at FDR<5%) log2-fold increases in ChIP normalized peak signal relative to the corresponding input sample. Region intersections were found using BEDTools (Quinlan & Hall, Bioinformatics 26, 841-842 (2010)). MEOX1 coverage distribution was first calculated as the read-normalized average across all three replicates per condition (unstimulated and TGFβ) using bamCompare in deeptools 3.5.0 (which also outputs a bigwig file used for the plot track), and then scored using computeMatrix in deeptools 3.5.0 with the scale-regions option.Coverage of H3K27Ac regions was calculated similarly, except that bed files were first created centered on each peak in the H3K27Ac data, with 1 kb extension upstream and downstream; computeMatrix was run on these bed files without the scale-regions option. To calculate how many protein-coding loci overlapped with MEOX1 peaks, we retained peaks that were present in at least two of the three replicates of MEOX1 ChIP with TGFβ treatment.

[0136] Circularized chromosome conformation capture (4C) 4C-seq experiments were performed on a large scale as reported by Stadhouders et al. (Nat. Protocol. 8:509-524 (2013)) with some modifications. Briefly, 10 million cardiac fibroblasts were cultured as described above in this method. After 48 h of TGF-β treatment, cells were washed three times with cold PBS and then sequentially crosslinked with 1% formaldehyde for 10 min. The reaction was quenched by adding glycine to a final concentration of 0.125 M. Cells were washed once more with cold PBS and nuclei were extracted by incubation on ice for 10 min in 5 ml of ice-cold lysis buffer (10 mM Tris-HCl, pH 8.0, 10 mM NaCl, 0.2% NP-40 + protease inhibitors). Nuclei were resuspended in restriction enzyme buffer (NEB Cat#B7006S) and incubated with 0.3% SDS for 1 hour at 37°C, followed by 2% Triton® X-100 for 1 hour. 400U DpnII restriction enzyme (NEB Cat#R0543S) was added and incubated overnight. The restriction enzyme was heat inactivated at 65°C for 20 minutes. Ligation of physically adjacent DNA regions was performed overnight with 1000U T4 DNA ligase (NEB M0202M). The next day, 300μg proteinase K was added and recrosslinking was performed overnight at 65°C. After recrosslinking, DNA was purified using phenol / chloroform precipitation and a second digestion was performed by adding 400U NlaIII restriction enzyme (NEB Cat#R0125S) followed by incubation at 65°C for 4 hours. After the second digestion, DNA ligation was performed again with T4 DNA ligase as described above. Primers containing partial Illumina sequence adapters (first primer: gttcagagttctacagtccgacgatc (SEQ ID NO: 20); second primer: agacgtgtgctcttccgatct (SEQ ID NO: 21)) were used in PCR to amplify the 4C-seq library. The first primer was designed on each viewpoint and the second primer was designed next to the NlaIII cleavage site closest to the viewpoint. The primer sequences used are listed in the "4C Primer Table".

[0137] Full-length Illumina sequence adapters and barcodes were added in a second PCR. Finally, libraries were quantified with Qubit® and library quality was checked with a bioanalyzer Agilent 2100 (Agilent Technologies). High-throughput sequencing was performed using an SE75 run on a NextSeq® 500 instrument (Illumina). Sequencing results were analyzed as described by Krijger et al. (Methods 170, 17-32 (2020)). Peak calling on background was performed using the de function "doPeakC" directly on the rds files generated by the pipeline as described by Krijger (2020).

[0138] siRNA transfection into cardiac fibroblasts 1×10 5 Immortalized fibroblasts or primary adult cardiac fibroblasts were seeded in 6-well plates the day before transfection. On the day of transfection, wells for subsequent TGFβ treatment were switched to fibroblast medium containing 0.5% FBS, and unstimulated wells were switched to regular fibroblast medium containing 10% FBS. Cells were transfected with 15 nM mouse Meox1, siBrd2, siBrd3, siBrd4, siSmad2 or siSmad3 siRNA or 15 nM siRNA control (all siRNAs were obtained from Sigma, reference numbers are shown in the table below) using 7 μl Lipofectamine® RNAiMAX transfection reagent (Thermo Fisher) per well according to the manufacturer's instructions. 24 hours after transfection, wells with 0.5% FBS medium were treated with TGF-β1 (detailed procedures are described in other sections).

[0139] Smooth muscle actin protein immunostaining Unstimulated and TGFβ-treated fibroblasts (with siRNA control or Meox1) were stimulated as described above (see the section "Generation of cardiac fibroblast immortalized cell lines, culture conditions and TGFβ stimulation" for details). For alpha smooth muscle actin staining, cells were fixed with 4% PFA for 15 min, washed and permeabilized in 0.2% Triton® X-100 (Sigma) for 5 min. After blocking with MOM blocking solution (VECTOR Laboratories), cells were then incubated with primary antibody against alpha smooth muscle actin (aSMA; DAKO, M0851; 1:100) for 30 min, followed by incubation with donkey anti-mouse IgG555 antibody (Invitrogen; 1:400) diluted in MOM diluent (VECTOR Laboratories) and Hoechst (Thermo Scientific, 62246; 1:10000) dye. Imaging was performed on a Zeiss Axio Observer Z1 using the same acquisition settings between samples and fold changes in aSMA expression were quantified using FIJI. Mean fluorescence intensity of aSMA was quantified using the Measure tool (Set Measurements "mean grey value") and normalized to total cell number. Total cell number was quantified by analyzing all nuclei per field using threshold, watershed and analyze particles tools. A total of 10 regions of interest were analyzed per well. Statistical analysis of data was performed using Prism8 with a determination of statistical significance set at p<0.05. Tukey's multiple comparison test was applied. Normality was not established by the D'Agostino-Pearson omnibus normality test, therefore the Independent Samples Mann-Whitney U test was utilized. A blinded method (labeling of samples by alphanumeric code) was implemented to analyze fibroblast aSMA expression.

[0140] Isolation and culture of primary adult cardiac fibroblasts Primary adult mouse ventricular fibroblasts (AMVFs) were prepared according to a previously described protocol (Travers et al. J. Am. Coll. Cardiol. 70, 958-971 (2017)) with minor modifications. Briefly, mice were anesthetized with isoflurane and administered 100 μL of heparin (100 U / mL) via intraperitoneal injection. Hearts were excised and immediately suspended in a Langendorff apparatus by the cannulation of the aortic root, and perfusion was initiated with perfusion buffer (113 mM NaCl, 4.7 mM KCl, 0.6 mM KH2PO4, 0.6 mM Na2HPO4, 1.2 mM MgSO4, 10 mM HEPES, 12 mM NaHCO3, 10 mM KHCO3, 30 mM taurine, 10 mM 2,3-butanedione monoxime, 5.5 mM D-(+)-glucose, pH 7.4) for the first 4 min at a constant perfusion rate of 4 mL / min at 37°C. Enzymatic digestion was then achieved by perfusion with calcium-free digestion buffer (400 units / mL collagenase II in perfusion buffer; Worthington LS004177) for 3 min followed by perfusion with digestion buffer containing 50 μM CaCl2 for 12 min. The heart was removed from the perfusion apparatus, the atria were removed, and the ventricles were placed in stop buffer (10% FBS and 12.5 μM CaCl2 in perfusion buffer). The ventricles were gently mechanically disrupted using a transfer pipette until the tissue was sufficiently digested. The cell suspension was filtered through a 250 μm mesh and the CM was allowed to settle by gravity for 10 min; the supernatant containing the first non-CM fraction was collected. The CM was resuspended in an additional 10 mL of stop buffer and then allowed to settle for 10 min. The supernatant was collected and both non-CM fractions were centrifuged at 500×g for 5 min. The CM was discarded. Non-CMs were resuspended, mixed and plated in growth medium consisting of DMEM / F12 medium (Corning 10-092-CV) supplemented with 10% BenchMark™ FBS (Gemini Bio-Products 100-106), 1% penicillin streptomycin L-glutamine (Corning 30-009-Cl) and 1 μmol / L ascorbic acid.Upon reaching 80% confluence, AMVFs were passaged once to P1 in an attempt to suppress spontaneous activation and appropriately plated for downstream assays.

[0141] Collagen gel contraction assay Compressible collagen was prepared in 24-well plates using PureCol EZ gel solution (Advanced BioMatrix 5074) by incubating at 37C for 1.5 hours. Passage 1 AMVF suspended in serum-supplemented growth medium were seeded onto the collagen gels (150,000 cells / gel) 24 hours prior to equilibration by overnight serum starvation (0.1% FBS), and 24 hours later equilibration by overnight serum starvation (0.1% FBS). During serum starvation, cells were transfected with siRNA against mouse Meox1 (or negative control siRNA) using Lipofectamine® RNAiMAX transfection reagent (ThermoFisher Scientific 13778030) according to the manufacturer's instructions. At the onset of contraction, the gels were detached from the walls of the wells, the transfection reagent was removed, and the cells were treated with 10 ng / mL TGF-β1 (Fisher Scientific 50725143) for 72 hours. Images of the wells were captured every 24 h; the gel area of ​​each well was determined using ImageJ software and the data is recorded as percent contraction.

[0142] EdU (5-ethyl-2'-deoxyuridine) incorporation assay Passage 1 AMVFs were seeded at a density of 20,000 cells / well into 12-well plates containing glass coverslips for 24 hours, followed by equilibration overnight in serum starvation medium (0.1% FBS). During serum starvation, cells were also transfected with siRNA against mouse Meox1 (or negative control siRNA) using Lipofectamine® RNAiMAX transfection reagent (ThermoFisher Scientific 13778030) according to the manufacturer's instructions. The medium was replaced and cells were stimulated with 10 ng / mL TGF-β1 (Fisher Scientific 50725143) for 48 hours; proliferative cells were labeled over the 48 hours of stimulation by simultaneously incubating AMVFs with 10 μM 5-ethyl-2′-deoxyuridine (EdU). AMVF were fixed with 3.7% formaldehyde and EdU-positive cells were detected using the Click-iT™ EdU Imaging Kit for Imaging (ThermoFisher Scientific C10337) according to the manufacturer's protocol. Coverslips were mounted with ProLong™ Diamond Antifade Mountant (Invitrogen P36961) and allowed to cure overnight before imaging on a Keyence BZ-X710 fluorescent microscope. The percentage of EdU incorporation was determined by quantifying the percentage of EdU-positive cells relative to the number of nuclei detected per field.

[0143] Human fibroblasts from lung, liver, and kidney Human fibroblasts from lung (ATCC, #CRL-4058), liver (CELL APPLICATIONS INC, #712-05f) and kidney (Cell Biologics, #H-6016) were passaged and expanded like mouse cardiac fibroblasts (see section "Generation of Immortalized Cardiac Fibroblast Cell Lines, Culture Conditions and TGFβ Stimulation" for details). Briefly, on day 1, 1 × 10 5Human fibroblasts were seeded at 10 cells / well. On day 2, the medium was replaced with the same basal medium containing 0.5% FBS. On day 3, TGF-β1 (Peprotech #100-21C) was added to the medium at a concentration of 10 ng / ml. JQ1 was added to a final concentration of 0.5 μM. On day 5, cells were harvested for RT-qPCR and gene expression analysis.

[0144] Gene Ontology (GO) analysis GO analysis of distal elements was performed using GREAT (see great.stanford.edu / public / html / ). GO analysis of protein-coding genes was performed using Enrichr (Chen et al. BMC Bioinformatics 14, 128 (2013)).

[0145] Statistics and reproducibility Standard statistical analysis was performed using GraphPad Prism8. When comparing multiple conditions, one-way ANOVA followed by Tukey's range test was performed to assess significance between pairs of conditions. When only two conditions were tested, we performed a Student's t-test. All p-values ​​associated with figures showing chromatin accessibility were obtained using a two-tailed Wilcoxon test. For all quantifications of cardiac function, gene expression by RT-qPCR, collagen contraction, and EdU incorporation, mean ± SEM was reported in the figures. For gene expression data by RT-qPCR analysis or RNAseq FPKM, the number of replicates is indicated as a data point in the graph. The levels of significance in all graphs are indicated as follows: *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001.

[0146] [Table 2]

[0147] [Table 3]

[0148] [Table 4]

[0149] [Table 5]

[0150] [Table 6]

[0151] [Table 7]

[0152] [Table 8]

[0153] Example 2: Tracking the dynamic reversibility of heart failure and myofibroblast status with BET inhibition This example describes the investigation of the therapeutic effect of small molecule BET bromodomain inhibition in a mouse model of heart failure and whether such heart failure is reversible by initiating, withdrawing, and resuming administration of CPI-456.

[0154] The first study evaluated the compound CPI-456 in a mouse model of heart failure induced by permanent anterior myocardial infarction (MI). CPI-456 is an orally bioavailable BET bromodomain inhibitor with subnanomolar potency and drug-like pharmacokinetic properties, which was initially developed as a clinical candidate for the treatment of cancer.

[0155] One month of CPI-456 treatment, initiated 5 days after MI, significantly improved left ventricular (LV) systolic function (Figure 2A). Discontinuation of CPI-456 for the following 3 weeks resulted in a decline in LV systolic function (Figure 2A). Readministration for the following 2 weeks improved LV systolic function to a similar extent as in the first treatment phase, and again, subsequent discontinuation of CPI-456 during the final week of the study reversed the decline in LV function to that of untreated controls.

[0156] Similar reversibility was observed when using the small molecule BET inhibitor JQ1 in a well-established mouse model of LV pressure overload-induced heart failure achieved via transverse aortic constriction (TAC) (Figure 2B). The structure of JQ1 is shown below.

[0157] [ka]

[0158] Taken together, by using chemically diverse BET bromodomain inhibitors in different mouse heart failure models, these studies demonstrate significant therapeutic reversibility in LV function.

[0159] Because BET bromodomain inhibition reversibly blocks enhancer-to-promoter signaling, we hypothesized that exposure to BET inhibitors could induce reversible changes in the state of cardiac cells in vivo in a manner that correlates with their observed therapeutic effects.

[0160] Given the remarkable protective effect of BET inhibition on LV contractile function, initial experiments focused on profiling cardiomyocytes (CMs). All subsequent in vivo transcriptomic and epigenomic analyses were performed in a mouse TAC model that uniformly and highly reproducibly stresses all regions of the LV. Because most adult CMs are too large to be adequately stored in a typical single-cell microfluidic workflow, we isolated adult CMs and analyzed them by bulk RNA-Seq.

[0161] Surprisingly, the effect of JQ1 on the transcriptome of isolated adult CMs was modest (<3% overlap) compared to previously published whole LV tissue transcriptome signatures, strongly indicating that the most robust effects on gene expression changes occurred in the non-CM population.We therefore performed single-cell RNA sequencing (scRNAseq) in the non-CM section of mouse hearts using the 10X Genomics platform.

[0162] We sequenced over 35,000 individual cells collected from four experimental groups: Sham, TAC vehicle treatment (TAC), TAC JQ1 treatment (TAC-JQ1) and TAC JQ1 treatment followed by JQ1 withdrawal (TAC JQ1 withdrawal) (Figure 2C). Unsupervised clustering of scRNAseq successfully identified diverse cardiac cell subpopulations including fibroblasts (FBs), endothelial cells, bone marrow cells and epicardial cells (Figure 2D). The most striking finding in this clustering was evident in the fibroblast population, where TAC triggered a major transition in cell state, and JQ1 treatment led to a dramatic recovery of this cell state, resembling it closer to the Sham state (Figure 2E). JQ1 withdrawal was associated with a transition of the FB population back to a TAC-like stress state, highlighting the reversible sensitivity of this cell compartment to JQ1 exposure (Figure 2E). Interestingly, JQ1 exposure also triggered dynamic transcriptomic transitions in endothelial and myeloid compartments (Figure 2E). However, in contrast to the reversible transitions of FBs between Sham- and TAC-like states, the sharp reversibility of JQ1-mediated transitions of cell states was less evident in endothelial and myeloid cells.

[0163] Given the near-complete bidirectional reversibility of fibroblast states in response to JQ1 exposure / withdrawal, we focused on analyzing the transcriptional reversibility of fibroblast compartments. Differential expression analysis of the transcriptomes of 13,937 individual fibroblasts pointed to strong similarities between the Sham and TAC JQ1 groups and highlighted a core signature of profibrotic genes that were significantly attenuated by BET inhibition (Figure 2F). Fibroblast subsetting and reclustering further demonstrated robust reversibility of fibroblasts between Sham and TAC states in response to JQ1 exposure (Figure 2G).

[0164] Cardiac stress can trigger the transition of resident fibroblasts into a contractile and synthetic state called myofibroblasts (myoFBs). Overlay of the myoFB marker gene Postn showed that TAC led to activation of myoFBs. However, administration of JQ1 reverted the state of myoFB cells to a Sham-like state, and withdrawal of JQ1 reverted these cells back to myoFBs (Figure 2H). Subclustering of fibroblasts showed the presence of 10 clusters showing a division of basal FB state (including Sham and TAC JQ1 cells; clusters 0, 1, and 4) versus myoFB state (including TAC and TAC JQ1 withdrawal cells; clusters 2, 3, and 5) (Figure 2I).

[0165] Gene Ontology (GO) analysis highlighted how gene programs associated with basal fibroblast homeostasis were enriched in Sham and TAC JQ1 cells, and furthermore, TAC and TAC JQ1-quit populations were enriched in profibrotic, secretory, proliferative, and migratory gene programs (Figure 2I). Taken together, these data show that a reversible transition between a basal fibroblast state and an activated myoFB state can be robustly switched using transcriptional inhibition, indicating that BET protein function in myoFBs influences the trajectory of heart failure development. Given the dynamic regulation of profibrotic and secretory proteins in fibroblasts, the effects of BET inhibition may be cell-autonomous and non-cell-autonomous.

[0166] Example 3: Chromatin accessibility and enhancer activation in heart failure We hypothesized that the transcriptional reversibility observed as a result of JQ1 exposure would be supported by corresponding changes in chromatin accessibility and enhancer activation in cardiac fibroblasts and other endogenous cardiac cell types during the development of heart failure. To test this, we integrated single-cell transcriptome analysis with single-cell assay for transposase-accessible chromatin sequencing (scATACseq) from the same hearts used for scRNAseq (Figure 2C).

[0167] We identified 490,020 accessible sites distributed in 31,766 individual cells and assigned cell identity based on chromatin features. The focus of this study was to analyze distal regulatory elements. Therefore, we excluded accessible sites in promoters and gene bodies and defined a catalog of distal elements enriched in fibroblasts, bone marrow, and endothelium that was used for all subsequent analyses.

[0168] Interestingly, fibroblasts showed a significantly greater increase in chromatin accessibility after TAC, which was reversibly attenuated using JQ1 treatment (Figure 3A), a feature that was less evident in bone marrow and endothelial cells (Figure 3I-3J). This highlights that fibroblast populations preferentially undergo chromatin activation during chronic heart failure that is partially dependent on BET proteins. To analyze dynamic and reversible changes in chromatin activation, we defined distal elements that were open and closed across the four samples and excluded regions that were constitutively open across all conditions. As shown in Figure 3B, robust reversibility of chromatin states occurred in response to stress and BET inhibition, especially in fibroblasts.

[0169] We identified a cluster of highly sensitive and dynamic fibroblast distal elements that were closed in Sham, opened in TAC, closed in JQ1, and robustly reaccessible after JQ1 withdrawal (cluster 2, Fig. 3B). GO analysis showed that these regions were in the vicinity of genes regulating cardiac hypertrophy and extracellular matrix (ECM) organization, two hallmarks of adverse cardiac remodeling and fibrosis. Interestingly, we also identified a large cluster of fibroblast regions that opened from Sham to TAC and were insensitive to JQ1, highlighting a signature of stress-responsive chromatin activation that was BET-independent (cluster 9, Fig. 3B).

[0170] Next, we explored how the accessibility of transcription factor (TF) binding motifs changed in dynamically regulated regions during the three phenotypic transitions described above that result in significant changes in cardiac function: Sham to TAC, TAC to TAC-JQ1, and TAC-JQ1 to TAC-JQ1 withdrawal. In fibroblasts, TF binding motifs for CEBPB, JUN, and MEOX1 showed enrichment in accessible regions during the Sham to TAC transition. Subsequent BET inhibition showed loss of enrichment, followed by regain of enrichment upon JQ1 withdrawal. These data indicate that chromatin dynamics occurs in regions enriched with functionally relevant motifs for stress-activated TFs (Figure 3C).

[0171] Next, we sought to identify functionally relevant enhancers in fibroblasts and activated myoFBs discovered during scATACseq. Studies have shown that enhancers can be pervasively transcribed, and that this nascent transcription activity is robust and an independent indicator of enhancer activity. Thus, we performed precision nuclear run-on transcript sequencing (PROseq; Mahat et al., Nat. Protoc. 11:1455-1476 (2016)) on in vitro cultured fibroblasts to map genome-wide RNA polymerase II nascent transcription and identify putative activated enhancers. Because PROseq requires large numbers of cells, we generated immortalized lines from primary adult mouse cardiac fibroblasts and treated the immortalized cell lines with TGF-β, a classical stimulant for inducing myoFB cell state transitions in vitro (Dobaczewski et al. J. Mol. Cell Cardiol. 51, 600-606 (2011)). We identified a set of distal elements that were significantly more highly transcribed after TGF-β stimulation and located in the vicinity of profibrotic and prosynthetic genes (Figure 3D). Using scATACseq data, we identified distal elements that were either open or closed between Sham and TAC in vivo, and then assessed PROseq signal in cultured FBs in these same regions. As shown in Figure 3E, in vitro TGF-β stimulation of cultured fibroblasts induces global transcriptional changes similar to those occurring in endogenous fibroblasts in vivo during the development of heart failure. Visualization of the Postn locus demonstrated the presence of chromatin openings that occurred in vivo after TAC, which correlated with dynamic sensitivity to JQ1 exposure. Within this large enhancer, PROseq revealed peak 11 as a specific region (peak 11) that was abundantly transcribed after TGF-β treatment. scATACseq coaccessibility analysis between the Postn promoter and the peak 11 region showed low coaccessibility in the sham condition, a robust increase in coaccessibility in response to TAC, and modulation of coaccessibility in response to JQ1 exposure.

[0172] CRISPR interference (CRISPRi) (Gilbert et al. Cell 154, 442-451 (2013)), which deploys a catalytically inactive Cas9 protein (dCas9) fused to the KRAB repressor protein, was used with guide RNAs specific for the Peak 11 region to drive sequence-specific repression of this particular regulatory element in fibroblasts. We found that this Peak 11 region is essential for Postn induction following TGF-β stimulation (Figure 3F).

[0173] Given the dynamic transcriptional regulation of Postn, a marker of myoFBs, we hypothesized that the integrated single-cell transcriptome and epigenomic approach described herein could be leveraged to discover novel mechanisms controlling intracellular stress responses during disease onset. Thus, we constructed an unbiased enhancer discovery pipeline to uncover distal elements that may play a role in heart failure progression and recovery. Using our scATACseq data in diseased hearts (TAC), we constructed a catalog of large enhancers (also known as stretch or super-enhancers) enriched in cell populations for fibroblasts, myeloid cells, and endothelial cells. Because BET inhibition robustly improved cardiac function in the TAC model, we correlated the degree of accessibility of these enhancers in fibroblasts, myeloid cells, and endothelial cells with LV ejection fraction. The correlation analysis between enhancer chromatin accessibility and physiological properties (in this case, LV ejection fraction) is summarized in Figure 3G. Enhancer elements were defined as negatively correlated if their accessibility was anti-correlated with cardiac function (i.e., these enhancers were open in the Sham-to-TAC setting, a setting where cardiac function is compromised). In contrast, positively correlated enhancers were closed in the Sham-to-TAC setting. Volcano plots of correlation coefficients were generated for each cell type (Figure 3H). Of the 470 large enhancers identified in fibroblasts, 48 ​​showed strong negative correlations, while 22 showed strong positive correlations (Figure 3H).

[0174] Example 4: Meox1 is a myofibroblast-specific transcription factor This example demonstrates that Meox1 is a myofibroblast-specific transcription factor. One of the most negatively correlated elements in fibroblasts was a large enhancer downstream of Meox1, a homeodomain-containing transcription factor expressed in the paraxial mesoderm and required for sclerotome development (Figure 3H). This is particularly interesting because Meox1 was minimally expressed in healthy mouse hearts but highly upregulated in MyoFBs following TAC (Figure 4A). BET inhibition abolished Meox1 expression, whereas JQ1 withdrawal was associated with robust re-induction of Meox1 expression (Figure 4A). Combined with the enrichment of MEOX1 DNA-binding motifs associated with dynamically accessible regions of chromatin in endogenous cardiac fibroblasts (Figure 3C), this indicated dynamic upregulation and functional engagement of MEOX1 with key fibroblast regulatory elements under stress conditions.

[0175] The Meox1 downstream enhancer was extremely sensitive to stress and JQ1 exposure in fibroblasts, but not in bone marrow and endothelial cells (Figures 4B and 4E). This enhancer had 10 peaks that significantly opened upon the transition from Sham to TAC conditions in fibroblasts, which were accessible upon this transition, closed back to Sham levels upon JQ1 treatment, and reopened when JQ1 was withdrawn (Figures 4B, 4E-4F). Analysis of chromatin accessibility at all individual peaks of the Meox1 enhancer indicated that certain elements were dynamically regulated.

[0176] The sequence of mouse Meox1 peak 9 / 10 region on mouse chromosome 11 at positions 101,828,401 to 101,833,068 is shown below (SEQ ID NO: 74).

[0177] [ka]

[0178] [ka]

[0179] [ka]

[0180] Publicly available BRD4 and H3K27ac ChIP-Seq data from adult mouse LV tissue supported active enhancer marks at the Meox1 locus, and CTCF ChIP-Seq consistently demonstrated the absence of contact isolation between the Meox1 gene and the enhancer, raising the possibility that this enhancer regulates Meox1 (Figure 4B). Importantly, Meox1 mRNA expression was induced in cultured fibroblasts treated with TGF-β (Figure 4G).

[0181] TGF-β-induced upregulation of Meox1 was suppressed by JQ1, and knockdown of each of the three BETs (Brd2, Brd3 or Brd4) individually with siRNA demonstrated that Meox1 induction was BRD4-dependent, but not BRD2- or BRD3-dependent (Figure 4I-4J). Among the individual scATAC-seq peaks at this locus showing increased accessibility by TAC in vivo, PROseq in cultured fibroblasts allowed us to identify a specific region (peak 9 / 10) located 62 kilobases (kb) downstream of the Meox1 promoter that was characterized by a marked increase in nascent transcription following TGF-β stimulation (Figure 4B). Notably, this 780 base pair (bp) element showed stronger TGF-β-stimulated transcription than the Meox1 gene body itself, and was also one of the most differentially transcribed regions across the genome in response to TGF-β stimulation (Figure 4B). The Meox1 promoter and Peak 9 / 10 regions showed low coaccessibility in the sham condition, strongly increased coaccessibility in response to TAC, and modulated coaccessibility in response to BET inhibition (Figure 4B). Chromosome conformation capture analysis of this locus in cultured fibroblasts revealed a robust increase in contacts between the Peak 9 / 10 enhancer region and the Meox1 promoter in response to TGF-β stimulation, consistent with dynamic contacts between these elements. Compared with other regions within the large Meox1 regulatory element, Peak 9 / 10 was characterized by two features that are strong predictors of functionally relevant enhancers: strong chromatin accessibility and nascent transcription. To definitively examine the endogenous function of Peak9 / 10, we performed a series of CRISPRi experiments at the Meox1 locus with guide strands specifically targeted to individual sites and found that the Peak9 / 10 element is required for Meox1 transactivation upon TGF-β stimulation (Fig. 4H ), whereas other accessible regions identified in vivo were not (data not shown).

[0182] Next, we investigated the function of MEOX1 and hypothesized that this poorly characterized homeobox transcription factor may directly regulate gene programs involved in fibrotic diseases. Knockdown of Meox1 by siRNA resulted in a significant reduction in TGF-β-stimulated collagen gel contraction and EdU incorporation, confirming that MEOX1 is required for the phenotypic transition between contraction and proliferation, two functional hallmarks of MyoFBs in disease pathogenesis (Figure 5A-5C). ChIPseq showed that MEOX1 binds to genes involved in fibroblast homeostasis and stress response (Figure 5D). GO analysis of highly MEOX1-bound genes showed enrichment for terms related to apoptosis, ECM / collagen organization and cell adhesion.

[0183] To understand whether MEOX1 controls the transcription of stress-responsive profibrotic genes, we performed PROseq in TGF-β-treated fibroblasts in the presence of either control or Meox1-targeting siRNA. When Meox1 was depleted, 509 genes were significantly less transcribed, while 819 genes were more transcribed (Figure 5E). Notably, GO analysis of Meox1-dependent genes revealed enrichment for profibrotic processes such as regulation of cell motility, proliferation, and migration. Among these genes were classical markers of cardiac MyoFB activation, including Ctgf and Postn. Their promoters and proximal regulatory elements (including the Postn peak 11 enhancer described in Figure 3F) showed MEOX1 enrichment, regions characterized by a large decrease in transcription following Meox1 deficiency (Figure 5F). These findings indicate that MEOX1 functions as an essential transcriptional mediator during the fibroblast-to-myoFB switch involved in fibrotic diseases. Using recent publicly available single-cell data from the adult human heart (see heartcellatlas.org), we found that MEOX1 is specifically expressed in the same subset of activated fibroblasts as POSTN.

[0184] Next, we explored whether MEOX1 activation in fibrotic diseases is conserved from rodents to humans. Single-cell data from human adult heart showed that MEOX1 is expressed in activated fibroblasts and is one of the top genes that, together with POSTN, determine the clustering of activated fibroblasts. A recent atlas of chromatin accessibility from human fetal heart showed that the peak 9 / 10 syntenic region was characterized by the strongest signal of accessible chromatin among MEOX1 distal elements in fibroblasts. Similar to heart failure, many critical human diseases are characterized by maladaptive fibroblast activation.

[0185] Because fibroblasts can have tissue-specific behavior, we investigated whether MEOX1 was also induced in fibroblasts derived from human lung, liver, and kidney, three organs that often develop substantial fibrosis in the setting of chronic organ failure. Similar to our findings in the heart, MEOX1 expression was induced by TGFβ and suppressed by JQ1 in fibroblasts derived from human lung, liver, and kidney (Figure 5I). Furthermore, MEOX1 expression was significantly upregulated in cardiac tissue from patients with cardiomyopathy (n=193) and lung tissue from patients with idiopathic pulmonary fibrosis (n=36), two human diseases that feature pathological fibrosis as a prominent feature (Figures 5G-5H).

[0186] Notably, MEOX1 expression was significantly upregulated in human diseases that prominently feature fibrosis, such as cardiac tissue from patients with cardiomyopathy and lung tissue from patients with idiopathic pulmonary fibrosis (Figures 5G-5J).

[0187] References

[0188] [Table 9-1]

[0189] [Table 9-2]

[0190] [Table 9-3]

[0191] [Table 9-4]

[0192] [Table 9-5]

[0193] [Table 9-6]

[0194] All patents and publications referenced or mentioned in this specification are indicative of the level of skill of those skilled in the art to which this invention pertains, and each patent or publication so referenced is hereby expressly incorporated by reference to the same extent as if it were individually incorporated by reference in its entirety or as if set forth in its entirety herein. Applicants reserve the right to physically incorporate into this specification any and all materials and information from any such cited patent or publication.

[0195] The following notes are intended to describe and summarize various embodiments of the present invention in accordance with the foregoing description herein. Additional Notes 1. A method comprising: providing a test assay mixture by contacting at least one test agent with a population of cells; and identifying one or more Meox1 modulating agents by measuring Meox1 levels.

[0196] 2. The method of claim 1, wherein the cell population comprises fibroblasts, quiescent fibroblasts, myofibroblasts, or a combination thereof. 3. The method of claim 1 or 2, wherein the cell population comprises activated fibroblasts.

[0197] 4. The method according to any one of appendices 1 to 3, wherein the fibroblasts are activated by TGFβ. 5. The method of any one of claims 1 to 4, wherein measuring the Meox1 level comprises measuring chromatin accessibility of a Meox1 regulatory element.

[0198] 6. The method of claim 5, wherein the Meox1 regulatory element is an enhancer. 7. The method of claim 5 or 6, wherein the Meox1 regulatory element is a peak 9 / 10 enhancer.

[0199] 8. The method of claim 5, 6 or 7, wherein the Meox1 regulatory element is located between about positions 43,589,381 and 43,595,263 of human chromosome 17. 9. The method of any one of claims 1 to 8, wherein the cell population comprises fibroblasts derived from cardiac tissue, lung tissue, liver tissue, kidney tissue, or a combination thereof.

[0200] 10. The method of any one of claims 1 to 9, wherein measuring Meox1 levels comprises measuring Meox1 transcript or protein levels, or wherein measuring Meox1 levels comprises measuring the absolute number of Meox1 transcripts observed per gene per cell (UMI count).

[0201] 11. The method of any one of claims 1 to 10, wherein one or more of the Meox1 modulating agents increases Meox1 levels. 12. The method of any one of claims 1 to 10, wherein one or more of the Meox1 regulating agents reduces Meox1 levels.

[0202] 13. The method of any one of claims 1 to 12, wherein one or more of the Meox1 modulating agents reduces Meox1 enhancer activity. 14. The method of any one of claims 1 to 13, wherein one or more of the Meox1 modulating agents reduces chromosomal accessibility of the Meox1 enhancer.

[0203] 15. The method according to claim 14, wherein the Meox1 enhancer is located between approximately positions 43,589,381 and 43,595,263 of human chromosome 17. 16. The method of any one of claims 1-15, further comprising identifying a therapeutic agent by administering one or more of the Meox1 regulating agents to an animal model of a cardiac condition or disease, and determining whether the one or more of the Meox1 regulating agents reduces a symptom or severity of the cardiac condition or disease.

[0204] 17. The method of claim 16, further comprising administering to the patient one or more of the therapeutic agents. 18. The method of claim 17, wherein the patient is in need of one or more of the therapeutic agents.

[0205] 19. The method of claim 16, 17, or 18, wherein the animal model or the patient has cardiac fibrosis, pulmonary fibrosis, renal fibrosis, hepatic fibrosis, heart failure, congestive heart failure, myocardial infarction, cardiac ischemia, myocarditis, arrhythmic cardiomyopathy, dilated cardiomyopathy, coronary artery disease, hypertension, valvular heart disease, hypertrophic cardiomyopathy (HCM), familial dilated cardiomyopathy (FDCM), restrictive cardiomyopathy (RCM), arrhythmogenic cardiomyopathy (AVC), unclassified cardiomyopathy, or a combination thereof.

[0206] 20. The method of any one of appendices 1-19, wherein the cell population is derived from a patient or subject seeking treatment for a cardiac condition or disease. 21. The method of claim 20, wherein the patient or subject exhibits increased Meox1 levels in cardiac fibroblasts, increased Meox1 nascent transcription, increased chromatin accessibility at Meox1 regulatory elements in cardiac fibroblasts, or a combination thereof.

[0207] 22. The method of claim 20 or 21, comprising knocking out or knocking down the Meox1 regulatory element in fibroblasts, myofibroblasts, or a combination thereof of the patient or subject.

[0208] 23. The method of claim 20, 21, or 22, comprising an in vivo knockout or knockdown of the Meox1 regulatory element in fibroblasts of the patient or subject.

[0209] 24. The method of claim 23, wherein knocking out or knocking down the Meox1 regulatory element comprises CRISPR modification of the Meox1 regulatory element, contacting the Meox1 regulatory element with a Meox1 inhibitory nucleic acid, or a combination thereof.

[0210] 25. The method of claim 24, wherein the Meox1 inhibitory nucleic acid is an antisense oligonucleotide, a small interfering RNA (siRNA), a small hairpin RNA (shRNA), a CRISPR guide RNA, a CRISPR ribonucleoprotein comprising a guide RNA and a cas nuclease, or a combination thereof.

[0211] 26. The method of any one of claims 22 to 24 or 25, comprising knocking out or knocking down the Meox1 regulatory element in vitro in a fibroblast population of the patient to generate modified fibroblasts, and reintroducing the modified fibroblasts into the patient.

[0212] 27. The method of any one of claims 20 to 25, wherein the fibroblasts are cardiac fibroblasts, myofibroblasts, or a combination thereof. 28. A method comprising administering a therapeutic agent to a subject comprising fibroblasts exhibiting increased chromatin accessibility at Meox1 regulatory elements, increased Meox1 expression, increased Meox1 nascent transcript levels, or a combination thereof.

[0213] 29. The method of claim 28, wherein the Meox1 regulatory element is an enhancer. 30. The method of claim 28 or 29, wherein the Meox1 regulatory element is a peak 9 / 10 enhancer.

[0214] 31. The method of any one of appendices 28 to 30, wherein the Meox1 regulatory element is located between approximately positions 43,589,381 and 43,595,263 of human chromosome 17.

[0215] 32. The method of any one of appendices 28 to 31, wherein the therapeutic agent is a guide RNA, a ribonucleoprotein complex containing a cas nuclease, an inhibitory nucleic acid, a chromatin stabilizer, or a combination thereof.

[0216] 33. A method comprising administering to a subject an agent that modulates Meox1 transcription, Meox1 translation, or MEOX1 protein function to treat a cardiac disease or condition. 34. The method of claim 33, wherein the agent inhibits one or more combinations of Meox1 transcription, Meox1 translation, or MEOX1 protein function.

[0217] 35. The method of claim 33 or 34, wherein the agent inhibits Meox1 transcription, Meox1 translation, or MEOX1 protein function. 36. The method of claim 33, 34, or 35, wherein the agent directly or indirectly regulates an enhancer operably linked to the Meox1 gene.

[0218] 37. The method of any one of claims 33 to 35 or 36, wherein the agent binds to an enhancer operably linked to the Meox1 gene or the MEOX1 coding region. 38. The method of any one of claims 33 to 36 and 37, wherein the agent is an RNA interference (RNAi) nucleic acid that reduces Meox1 translation.

[0219] 39. The method of any one of claims 33 to 37 or 38, wherein the Meox1 inhibitory nucleic acid is an antisense oligonucleotide, a small interfering RNA (siRNA), a small hairpin RNA (shRNA), or a combination thereof.

[0220] The specific methods and compositions described herein are representative of preferred embodiments and are exemplary and are not intended as limitations on the scope of the invention. Other objects, aspects, and embodiments will occur to those skilled in the art upon consideration of this specification, and are encompassed within the spirit of the invention as defined by the scope of the claims. It will be readily apparent to those skilled in the art that various substitutions and modifications can be made to the invention disclosed herein without departing from the scope and spirit of the invention.

[0221] The invention illustratively described herein may suitably be practiced in the absence of any element or any limitation not specifically disclosed herein as necessary. The methods and processes illustratively described herein may suitably be practiced with different sequences of steps, and the methods and processes are not necessarily limited to the sequences of steps set forth in this specification or the claims.

[0222] As used herein and in the appended claims, the singular forms "a," "an," "the," and "the" include plural references unless the context clearly dictates otherwise. Thus, for example, a reference to "a nucleic acid" or "a protein" or "a cell" includes a plurality of such nucleic acids, proteins, cells, etc. (e.g., a solution or dried preparation of a nucleic acid or expression cassette, a solution of a protein, or a population of cells). As used herein, the term "or" is used to refer to a non-exclusive or / or, and unless otherwise specified, "A or B" includes "A but not B," "B but not A," and "A and B."

[0223] Under no circumstances shall a patent be construed as limited to any particular examples or embodiments or methods specifically disclosed in the specification. Under no circumstances shall a patent be construed as limited by any statement made by an examiner or other officer or employee of the Patent and Trademark Office unless that statement is expressly adopted in the applicant's responsive filing and is free of qualifications or reservations.

[0224] The terms and expressions employed are used as terms of description and not of limitation, and there is no intention to exclude any equivalents of the illustrated and described or portions thereof using such terms and expressions, but it is recognized that various modifications are possible within the scope of the invention claimed.Thus, although the invention has been specifically disclosed by preferred embodiments and optional features, it will be understood that modifications and variations of the concepts disclosed herein may be employed by those skilled in the art, and such modifications and variations are considered to be within the scope of the invention as defined by the appended claims and appendices of the invention.

[0225] The invention has been described broadly and generically herein. Each of the narrower species and subgeneric groupings falling within the generic disclosure also form part of the invention. This includes the general description of the invention with a provisos or negative limitation removing any subject matter from the genus, regardless of whether the excised material is specifically described herein. In addition, features or aspects of the invention are described in terms of Markush groups, and one of skill in the art will recognize that the invention is also described thereby in terms of any individual members or subgroups of members of the Markush group.

Claims

1. A method for identifying one or more Meox1 modulating agents, the method comprising contacting at least one test agent with a population of fibroblast cells to provide a test assay mixture, and measuring chromatin accessibility of a Meox1 enhancer, the Meox1 enhancer being located between approximately positions 43,589,381 and 43,595,263 of human chromosome 17.

2. 2. The method of claim 1, wherein the fibroblast population comprises activated fibroblasts, quiescent fibroblasts, myofibroblasts, activated myofibroblasts, or a combination thereof.

3. 2. The method of claim 1, wherein at least one of the test agents is an antisense oligonucleotide, a small interfering RNA (siRNA), a small hairpin RNA (shRNA), a CRISPR guide RNA, a CRISPR ribonucleoprotein comprising a guide RNA and a cas nuclease, or a combination thereof.

4. 2. The method of claim 1, wherein one or more of the Meox1 modulating agents reduces Meox1 levels, reduces Meox1 enhancer activity, or a combination thereof.

5. The method of claim 1 , wherein one or more of the Meox1 modulating agents reduces chromatin accessibility of a Meox1 enhancer.

6. The method of claim 1, further comprising identifying a therapeutic agent by administering one or more of the Meox1 regulating agents to an animal model of a cardiac condition or disease and determining whether the one or more of the Meox1 regulating agents reduces a symptom or severity of the cardiac condition or disease.

7. The method of claim 1 , wherein the population of fibroblasts is derived from a patient seeking treatment for a condition or disease.

8. The method of claim 7, wherein the patient having the fibroblast population exhibits increased Meox1 levels in fibroblasts, increased nascent Meox1 levels in fibroblasts, increased chromatin accessibility at Meox1 enhancers in fibroblasts, or a combination thereof.

9. 9. The method of claim 8, wherein the fibroblasts are cardiac fibroblasts, lung fibroblasts, liver fibroblasts, kidney fibroblasts, or a combination thereof.

10. A method for identifying one or more inhibitors of Meox1, the method comprising contacting a fibroblast cell in vitro with a test agent and measuring chromatin accessibility of a Meox1 enhancer, wherein the test agent reduces chromatin accessibility of the Meox1 enhancer, thereby identifying one or more inhibitors of Meox1, the Meox1 enhancer being located between approximately positions 43,589,381 and 43,595,263 of human chromosome 17.

11. The method of claim 10, wherein the fibroblasts comprise myofibroblasts, activated fibroblasts, activated myofibroblasts, or a combination thereof.

12. 11. The method of claim 10, wherein the fibroblasts are cardiac fibroblasts, lung fibroblasts, liver fibroblasts, kidney fibroblasts, or a combination thereof.

13. 11. The method of claim 10, wherein the test agent comprises one or more inhibitory nucleic acids, guide RNAs, cas nucleases, cas nuclease:guide RNA ribonucleoprotein complexes, or combinations thereof.

14. The method of claim 10, wherein the fibroblasts contacted in vitro are derived from a subject who will subsequently be administered the modified cells.

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