Metal organic framework suitable for enriching proteins, protein sample pretreatment method, and label-free proteome analysis method

Abstract

Disclosed in the present invention are a lanthanide metal organic framework which is rich in boric acid groups and used for enriching proteins, the preparation thereof, a protein sample pretreatment method, and a label-free proteome analysis method, which relate to the field of protein detection. The metal organic framework uses 3,5-dicarboxyphenylboronic acid as an organic ligand, and lanthanide elements dysprosium, europium, gadolinium and terbium as metal nodes. Also provided in the present invention are a preparation method for the metal organic framework, the protein sample pretreatment method using the metal organic framework, and the label-free proteome analysis method using the metal organic framework. The analysis method comprises a pretreatment step of a protein sample and a step of collecting and analyzing captured proteins, the pretreatment step comprising a step of capturing proteins in the protein sample by using the metal organic framework. The material and the methods in the present invention can perform strong, rapid, efficient, highly-sensitive and low-cost protein sample pretreatment and label-free proteome analysis.

Description

A metal-organic framework suitable for protein enrichment, protein sample pretreatment method, and label-free proteome analysis method Technical Field

[0001] The present invention relates to the field of protein detection, and in particular to a metal-organic framework suitable for enriching proteins, a protein sample pretreatment method, and a label-free proteome analysis method. Background Art

[0002] This section is intended to provide a background or context to the embodiments of the invention that are recited in the claims. No statement herein is admitted to be prior art by virtue of its inclusion in this section.

[0003] Proteins are the basic organic matter that constitutes cells and are the main bearers of life activities. They directly indicate functional states such as signaling and metabolic pathways under different physiological states. The large-scale application of proteomic information in science and medicine lags behind genomics to a large extent due to the complexity of protein molecules themselves and the lack of equivalent amplification mechanisms for low-abundance proteins. Complex workflows limit the scalability of proteomics, making comprehensive research on the proteome in clinical samples challenging. [1] .

[0004] Currently, protein identification primarily relies on targeted measurement using antibodies, such as flow cytometry by time-of-flight (CyTOF), imaging mass cytometry (IMC), and single cell western blot (sc-WB). However, the results of these identification methods are limited by the quality and availability of antibodies, which are also expensive. Label-free proteomics based on mass spectrometry (MS) has become an important technology for describing the spectrum of protein changes and discovering biomarkers, elucidating the dynamics of protein-protein interactions under different cellular states and improving the diagnosis and molecular understanding of disease mechanisms. Overall, mass spectrometry-based proteomics can reveal the quantitative state of the proteome, thereby gaining a deep understanding of the biochemical state of the relevant cells or tissues, and has revolutionized modern biological research.

[0005] A typical bottom-up proteomics workflow begins with trypsin digestion of a protein sample into short peptides, which are then separated by liquid chromatography. As the peptides elute from the column, they are ionized by electrospray and sprayed directly into a mass spectrometer for secondary mass spectrometry. In the first stage, the mass analyzer measures the mass-to-charge ratio (m / z) of the peptide molecular ion (MS1). In the second stage, the m / z values ​​of the fragment ions produced by the fragmentation of specific peptide ions are detected (MS2). The specific fragment ion pattern and its m / z value for each peptide ion enable reliable identification of the peptides present in the sample. The identified peptide sequences can then be mapped to proteins, and the signal intensity of the peptide or fragment ions can be used to estimate relative changes in sample abundance. [2] .

[0006] However, proteome coverage is limited due to the inevitable loss of significant amounts of protein due to nonspecific adsorption and contamination during the complex and laborious pretreatment process. [3] In reality, clinical patients only have access to limited and sometimes non-renewable sample resources for mass spectrometry analysis, such as rare cell subsets, microliter-scale blood, and cerebrospinal fluid. Proteomic detection of ultra-trace biological samples is a practical need, but it often encounters difficulties. The tiny protein input amount is a bottleneck for achieving high proteome coverage.

[0007] Exploring whole-protein functional materials for capturing trace amounts of proteins in cells, biofluids, and tissue samples is promising but remains an ongoing challenge.

[0008] Currently, researchers have developed a series of workflows and equipment to process samples with limited mass for downstream mass spectrometry analysis to improve protein coverage. Filter-aided sample preparation (FASP) is the most commonly used "gold standard" for proteomics pre-processing. It allows the removal of low molecular weight contaminants and retention of proteins through molecular weight cut-off ultrafiltration centrifugation, but can only recover 50% of peptides. [4] .

[0009] Another research direction focuses on enhancing proteomic sensitivity by miniaturizing sample preparation to limit protein contact with adhesion surfaces, thereby reducing protein loss. The introduction of microfluidic platforms to process trace cell samples significantly reduces the contact area between the sample and the surface by minimizing the size of the nanodroplets, thereby improving proteomic coverage. Nanodroplet Processing in One Pot for Trace Samples (nanoPOTS) [5]Nanoliter-scale oil-air-droplet (OAD) chip [6] Integrated proteome analysis device (iPAD-1) [7] All-in-One digital microfluidic pipeline (DMF) [8] and integrated proteomics chip (iProChip) [9] Devices such as these can reduce the processing volume for label-free proteomics to 2-200 nL, reducing sample adsorption losses that occur during large-scale sample processing prior to low-cell number or even single-cell level analysis, and achieving higher identification depth at the single-cell level. However, few of these methods can effectively process biofluid samples, and the high requirements for developing automated instrumentation and microfabrication, such as obtaining robotic nanoliter liquid handling or complex capillary and column connections, have made it difficult to widely apply even in well-equipped laboratories.

[0010] In the Single-Cell ProtEomics by Mass Spectrometry (SCoPE-MS) method, excess carrier peptides are mixed with the peptide sample labeled with tandem mass tags (TMT) to reduce the surface adsorption loss of labeled peptides. However, the exogenous protein carrier will greatly reduce the sequencing opportunity of low-abundance endogenous peptides, and the reproducibility is poor.

[0010] .

[0011] One-pot preparation integrates cell sorting, lysis, protein reduction alkylation, and digestion into a single tube, avoiding sample transfer. It has now developed to the single-cell stage, but it cannot effectively process clinical liquid samples, and unpurified peptides are harmful to chromatographic columns and electrospray emitters.

[0011] .

[0012] Using a miniaturized, packaged proteomic sample processing (in-stagetip, iST) device combined with pipette-based sample separation, approximately 7,000 proteins were identified across 12 immune cell types with mass-restricted immune cell accessibility.

[0012] , but it is expensive to counterfeit and has poor reproducibility.

[0013] Prior to MS acquisition for whole-proteome proteomics, various nanoparticles have been developed to capture proteins via nanobiointeractions in clinical samples. The use of surface-functionalized magnetic nanoparticles coupled with robotic nanoliter liquid handlers has enabled rapid, scalable, and high-throughput proteomic studies of biofluids and tissue samples.

[0014] Single-pot, solid-phase-enhanced sample-preparation technology (SP3) uses carboxylic acid-coated magnetic beads to absorb proteins through hydrophilic interactions. It is suitable for efficient processing of small samples and can quantify proteins in as few as 100 HeLa cells.

[0013] However, nucleic acids will also be captured, making the beads sticky and difficult to handle. John et al. used magnetic nanoparticles with different charges to form different protein coronas to separate proteins from plasma, achieving deep proteomics mining in plasma.

[0014] Despite numerous published studies, reproducible and high-yield peptide generation under sample-limited conditions remains challenging due to the difficulty in fabricating compatible automated instruments and the lack of universally effective sampling and processing techniques.

[0015] Exploring functional materials for capturing intact proteins at trace levels in cells, biofluids, and tissue samples is promising but remains an ongoing challenge. [9] .

[0016] Protein surfaces are typically occupied by cationic groups such as amines, imidazoles, and guanidines, as well as anionic carboxylic acid groups. Therefore, developing functional materials that can bind to anionic and cationic groups on protein surfaces could effectively capture proteins in ultratrace clinical samples. Phenylboronic acid (PBA) is an electron-deficient group that can coordinate with cationic amine and imidazole groups on histidine and lysine / proteins via nitrogen borate complexation. The aromatic ring in PBA allows for interaction with guanidine or ammonium groups on proteins via cation-π interactions. Furthermore, anionic carboxylates on proteins can effectively bind to cationic species through enhanced ionic interactions and coordination.

[0017] Metal-organic frameworks (MOFs) are porous crystalline materials formed by the self-assembly of organic ligands and inorganic metal-doped nodes, typically carrying a positive charge. MOFs with high surface areas have also been developed as novel matrices for the analysis of small molecules in matrix-assisted laser desorption / time-of-flight mass spectrometry (MALDI-TOF MS). Surface-modified MOFs are often used as affinity materials to selectively capture modified peptides, such as glycopeptides and phosphopeptides, for the detection of post-translational modifications in proteomics.

[0018] Therefore, those skilled in the art are committed to developing a powerful, rapid, efficient, low-cost protein sample processing material and method that improves detection sensitivity.

[0019] References

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[0032]

[0013] S. Ferdosi, A. Stukalov, M. Hasan, B. Tangeysh, T. R. Brown, T. Wang, E. M. Elgierari, X. Zhao, Y. Huang, A. Alavi, B. Lee-McMullen, J. Chu, M. Figa, W. Tao, J. Wang, M. Goldberg, E. S. O'Brien, H. Xia, C. Stolarczyk, R. Weissleder, V. Farias, S. Batzoglou, A. Siddiqui, O. C. Farokhzad, D. Hornburg, Adv Mater 2022, 34, e2206008.

[0033]

[0014] S. Ferdosi, A. Stukalov, M. Hasan, B. Tangeysh, T. R. Brown, T. Wang, E. M. Elgierari, X. Zhao, Y. Huang, A. Alavi, B. Lee-McMullen, J. Chu, M. Figa, W. Tao, J. Wang, M. Goldberg, E. S. O'Brien, H. Xia, C. Stolarczyk, R. Weissleder, V. Farias, S. Batzoglou, A. Siddiqui, O. C. Farokhzad, D. Hornburg, Adv Mater 2022, 34, e2206008. Summary of the Invention

[0034] In view of the above-mentioned defects of the prior art, the technical problem to be solved by the present invention is to provide a strong, rapid, efficient, low-cost protein sample pretreatment material and method with improved detection sensitivity, as well as a label-free proteome analysis method.

[0035] To achieve the above-mentioned object, the present invention provides a first aspect of a label-free proteome analysis method, which includes a protein sample pre-treatment step, and a step of collecting and analyzing the captured proteins;

[0036] The pre-treatment step includes a step of capturing proteins in the protein sample using a metal organic framework, wherein the metal organic framework uses 3,5-dicarboxyphenylboronic acid as an organic ligand and a lanthanide element as a metal node.

[0037] In some embodiments of the present invention, the lanthanide elements include one, two, three, or four of dysprosium, europium, gadolinium, and terbium. Furthermore, the lanthanide elements include two or more of dysprosium, europium, gadolinium, and terbium. Furthermore, the lanthanide elements include four of dysprosium, europium, gadolinium, and terbium.

[0038] In some embodiments of the present invention, the organic ligand further comprises isophthalic acid.

[0039] Furthermore, the molar ratio of the 3,5-dicarboxyphenylboronic acid to the isophthalic acid is 0.8 to 1.2, such as 0.8, 0.9, 1, 1.1 or 1.2. Furthermore, the molar ratio of the 3,5-dicarboxyphenylboronic acid to the isophthalic acid is 1.

[0040] In some embodiments of the present invention, the metal-organic framework is one, two, three or four of a dysprosium metal-organic framework, a europium metal-organic framework, a gadolinium metal-organic framework and a terbium metal-organic framework; the dysprosium metal-organic framework has 3,5-dicarboxyphenylboronic acid and isophthalic acid as organic ligands and dysprosium as metal nodes; the europium metal-organic framework has 3,5-dicarboxyphenylboronic acid and isophthalic acid as organic ligands and europium as metal nodes; the gadolinium metal-organic framework has 3,5-dicarboxyphenylboronic acid and isophthalic acid as organic ligands and gadolinium as metal nodes; the terbium metal-organic framework has 3,5-dicarboxyphenylboronic acid and isophthalic acid as organic ligands and terbium as metal nodes.

[0041] Furthermore, the metal-organic framework is a mixture of two or more of a dysprosium metal-organic framework, a europium metal-organic framework, a gadolinium metal-organic framework and a terbium metal-organic framework.

[0042] Furthermore, the metal organic framework is a mixture of a dysprosium metal organic framework, a europium metal organic framework, a gadolinium metal organic framework and a terbium metal organic framework.

[0043] Furthermore, the molar ratio of the dysprosium metal organic framework, the europium metal organic framework, the gadolinium metal organic framework and the terbium metal organic framework is 1:0.8~1.2:0.8~1.2:0.8~1.2, for example, 1:0.8:0.8:0.8, 1:0.8:0.8:0.9, 1:0.8:0.8:1, 1:0.8:0.8:1.1, 1:0.8:0.8:1.2, 1:0.8: 0.9:0.8, 1:0.8:1:0.8, 1:0.8:1.1:0.8, 1:0.8:1.2:0.8, 1:0.9:0.8:0.8, 1:1:0.8:0.8, 1:1.1:0.8:0.8, 1:1.2:0.8:0.8, 1:0.9:0.9:0.9, 1:1:1:1, 1:1.1:1.1:1.1, 1:1.2:1.2:1.2, etc.

[0044] Furthermore, the metal-organic framework is a mixture of equal amounts of a dysprosium metal-organic framework, a europium metal-organic framework, a gadolinium metal-organic framework and a terbium metal-organic framework.

[0045] In some embodiments of the present invention, the metal-organic framework is a freeze-dried body.

[0046] In some embodiments of the present invention, the metal-organic framework is spherical.

[0047] In some embodiments of the present invention, the pre-treatment step further comprises the steps of washing the metal organic framework with captured proteins, digesting the proteins, and eluting and desalting the digested proteins.

[0048] Furthermore, the washing and digestion are performed in the same tube.

[0049] Furthermore, the pre-treatment step further includes a step of cracking the protein sample before the metal-organic framework captures the protein.

[0050] Furthermore, the lysis, washing and digestion are performed in the same tube.

[0051] Furthermore, the tube is a centrifuge tube.

[0052] In some embodiments of the present invention, the specific method of the pretreatment step is: loading the metal organic framework into the protein sample and capturing the protein, then discarding the supernatant containing impurities by centrifugation, then washing the protein on the surface of the metal organic framework, and using an enzyme to digest the protein into peptides, and then eluting and desalting the protein.

[0053] In some embodiments of the present invention, the acquisition and analysis step uses mass spectrometry to acquire data and then performs data processing.

[0054] In some embodiments of the present invention, the protein sample comprises a lysed cell sample, a lysed tissue sample, or a biological fluid sample.

[0055] Furthermore, the number of cells in the lysed cell sample is 10 to 5000.

[0056] Furthermore, the mass of the tissue in the lysed tissue sample is 50 micrograms to 1000 micrograms.

[0057] Furthermore, the volume of the biological fluid sample is 1 microliter to 1000 microliters.

[0058] In some embodiments of the present invention, the metal-organic framework captures trace amounts of protein in the protein sample.

[0059] The present invention also provides a protein-enriched boric acid-rich lanthanide metal-organic framework, wherein the metal-organic framework uses 3,5-dicarboxyphenylboronic acid as an organic ligand and a lanthanide element as a metal node.

[0060] In a preferred embodiment of the present invention, the lanthanide elements are dysprosium, europium, gadolinium and terbium.

[0061] The present invention also provides a method for preparing the above-mentioned protein-enriched boric acid-rich lanthanide metal organic framework, which uses isophthalic acid (1,3-BDC) and 3,5-dicarboxyphenylboronic acid as mixed ligands to prepare spherical lanthanide metal organic frameworks (Ln-MOFs) by a solvothermal method.

[0062] In some embodiments of the present invention, the method specifically includes: adding lanthanide metal ions, isophthalic acid and 3,5-dicarboxyphenylboronic acid to a mixed solution of N,N-dimethylformamide and H2O, stirring and dissolving at room temperature, then heating the mixture at 100°C to 140°C for 4 to 36 hours, cooling to room temperature, concentrating and collecting fine powder, and then washing with DMF, ethanol and deionized water respectively, dialyzing the formed metal organic framework in deionized water, freeze-drying the product, and mixing dysprosium metal organic framework, europium metal organic framework, gadolinium metal organic framework and terbium metal organic framework to prepare the metal organic framework.

[0063] In a preferred embodiment of the present invention, lanthanide metal ions, isophthalic acid, i.e., 1,3-BDC, and 3,5-dicarboxyphenylboronic acid are added to a mixed solution of N,N-dimethylformamide, i.e., DMF / H2O, and stirred vigorously. Ultrasonic stirring is performed at room temperature for 1 hour to fully dissolve the mixture. After that, the mixture is transferred to a polytetrafluoroethylene-lined stainless steel autoclave and heated at 120°C for 6 hours. After cooling to room temperature, i.e., 25°C, it is concentrated at 20,000g for 10 minutes. Fine powder is collected from the emulsion solution and then washed three times with DMF, ethanol, and deionized water, respectively. The formed metal-organic framework, i.e., MOFs, is dialyzed in deionized water for 1 day, with the water changed every two hours. The product is freeze-dried and stored in a drying jar for further use. Equal amounts of dysprosium metal-organic framework, europium metal-organic framework, gadolinium metal-organic framework, and terbium metal-organic framework are mixed to prepare mixed Ln-MOFs.

[0064] In another preferred embodiment of the present invention, when preparing Dy-MOFs, i.e., dysprosium organic frameworks, 0.072 mmol (27.13 mg) of DyCl3·6H2O, 0.036 mmol (7.56 mg) of isophthalic acid, and 0.036 mmol (6.12 mg) of 3,5-dicarboxyphenylboronic acid were added to 36 mL of a DMF / H2O mixed solution with a volume ratio of 7:3 and stirred.

[0065] In another preferred embodiment of the present invention, when preparing Eu-MOFs, i.e., europium organic frameworks, 0.072 mmol (26.81 mg) of EuCl3·6H2O, 0.036 mmol (7.56 mg) of isophthalic acid, and 0.036 mmol (6.12 mg) of 3,5-dicarboxyphenylboronic acid were added to 36 mL of a DMF / H2O mixed solution with a volume ratio of 7:3 and stirred.

[0066] In another preferred embodiment of the present invention, when preparing Gd-MOFs, i.e., gadolinium organic frameworks, 0.072 mmol (27.40 mg) of GdCl3·6H2O, 0.036 mmol (7.56 mg) of isophthalic acid, and 0.036 mmol (6.12 mg) of 3,5-dicarboxyphenylboronic acid were added to 36 mL of a DMF / H2O mixed solution with a volume ratio of 7:3 and stirred.

[0067] In another preferred embodiment of the present invention, when preparing Tb-MOFs, i.e., terbium organic frameworks, 0.072 mmol (26.88 mg) of TbCl3·6H2O, 0.036 mmol (7.56 mg) of isophthalic acid, and 0.036 mmol (6.12 mg) of 3,5-dicarboxyphenylboronic acid were added to 36 mL of a DMF / H2O mixed solution with a volume ratio of 7:3 and stirred.

[0068] The present invention also provides a protein sample pretreatment method using the above-mentioned protein-enriched borate-rich lanthanide metal-organic framework, characterized in that the metal-organic framework is loaded into the lysed sample and the protein is captured, and then the supernatant containing impurities is discarded by centrifugation. Subsequently, the protein on the surface of the metal-organic framework is washed, and the protein is digested into peptides using an enzyme, and the protein is eluted and desalted before mass spectrometry acquisition.

[0069] In a preferred embodiment of the present invention, the lysis, washing and digestion steps of the method are integrated into one centrifuge tube.

[0070] Technical Effects

[0071] 1. The present invention synthesized four metal-organic framework materials rich in boronic acid groups and with different metal nodes. These materials can target and bind to proteins in the sample in a directional and non-selective manner, eliminating the precipitation and ultrafiltration steps, improving protein recovery. The materials are powerful and efficient, with high protein capture efficiency, significantly improving detection sensitivity. 1,885 proteins were identified in 10 HEK 293T cells, far exceeding the detection limit of the traditional method FASP. After protein binding, this material can be separated from the protein in the sample by centrifugation for only 5 minutes, eliminating the time-consuming precipitation and centrifugation steps. The separation speed is fast and efficient.

[0072] 2. The present invention concentrates the entire protein pretreatment process in one centrifuge tube. The single-tube sample pretreatment process reduces the number of sample transfers and reduces sample loss caused by nonspecific adsorption due to contact.

[0073] 3. The raw materials of this technology are low-priced and do not use expensive consumables, which reduces the cost of sample pre-processing and is green and environmentally friendly.

[0074] The concept, specific structure and technical effects of the present invention will be further described below in conjunction with the accompanying drawings to fully understand the purpose, characteristics and effects of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] FIG1 is a schematic diagram of a borate-rich lanthanide metal-organic framework for protein enrichment and a protein sample pretreatment method thereof according to a preferred embodiment of the present invention;

[0076] FIG2 is a graph showing the interaction between the SS ligand and the ST ligand shown in Example 1 and four model proteins;

[0077] FIG3 is a graph showing the properties of four metal organic frameworks prepared in Example 2 and the ability of their mixture to capture model proteins;

[0078] FIG4 is a graph showing the surface element characterization results of four metal organic frameworks prepared in Example 2;

[0079] FIG5 is a graph showing the results of proteomic analysis of trace HEK 293T cells enhanced by MASP used in Example 3;

[0080] FIG6 is a schematic diagram of protein types identified in human embryonic kidney cells using MASP according to a preferred embodiment of the present invention;

[0081] FIG7 is a schematic diagram of the proteomic performance of the identification of three cell lines using MASP according to a preferred embodiment of the present invention;

[0082] FIG8 is a schematic diagram of using MASP to identify different cerebrospinal fluid proteins according to a preferred embodiment of the present invention;

[0083] FIG9 is a schematic diagram showing proteomic changes in CS and BR patients identified using MASP according to a preferred embodiment of the present invention;

[0084] FIG10 is a schematic diagram of proteins in mouse brain tissue identified using MASP according to a preferred embodiment of the present invention;

[0085] FIG11 is a comparative diagram of protein enrichment results using metal-organic frameworks of different morphologies. DETAILED DESCRIPTION

[0086] The following describes several preferred embodiments of the present invention with reference to the accompanying drawings to make its technical content clearer and easier to understand. The present invention can be embodied in many different forms of embodiments, and the scope of protection of the present invention is not limited to the embodiments mentioned herein.

[0087] In this study, novel borate-rich lanthanide metal-organic frameworks (MOFs) were synthesized using 3,5-dicarboxyphenylboronic acid and isophthalic acid as organic ligands and four lanthanide elements—dysprosium (Dy), europium (Eu), gadolinium (Gd), and terbium (Tb)—as metal nodes as functional materials for protein enrichment and separation (Figure 1B). These four MOFs, with high borate grafting rates, exhibit high binding affinity to different protein types through nitrogen-borate complexation and cation-π and ion interactions (Figure 1A). When exposed to protein-containing biofluids during sample pretreatment, the borate-rich lanthanide MOFs rapidly adsorb proteins in complex cell lysates and body fluids without the need for any inducers, helping to minimize protein loss and improve peptide recovery.

[0088] Among them, biological fluids include blood, cerebrospinal fluid, saliva, urine, gastric juice, pancreatic juice, lymph, milk, etc.

[0089] Example 1: Selection of organic ligands

[0090] 2-Boronic acid-1,4-benzenedicarboxylic acid (SS ligand) and 5-boronic acid-1,3-benzenedicarboxylic acid (3,5-dicarboxyphenylboronic acid, ST ligand) are two isomers that serve as candidate ligands for constructing MOFs and show high affinity with proteins through complex chemical and physical interactions.

[0091] Molecular docking simulations were performed using BSA, Hb, Cyt C, and Lys as four model proteins with different isoelectric points to elucidate the binding locations of SS and ST and their orientation within the binding sites of the model proteins and to examine the driving forces of the binding sites (Figure 2A). Molecular docking results showed that SS and ST occupy the same position on the model proteins. Non-covalent forces drive the interactions between SS and ST and the model proteins. Electrostatic interactions are the primary driving force governing the interaction between BSA and SS, while the interaction between BSA and ST is driven by hydrogen bonds and van der Waals forces. For Hb, Cyt C, and Lys, hydrophobic interactions were observed to be the primary driving force for their interactions with SS and ST. Notably, in addition to the interaction between BSA and ST, the binding sites of the model proteins interacting with SS and ST also involve secondary forces.

[0092] Furthermore, molecular docking results revealed that the boron atom in ST is oriented directly toward the secondary structural components of the binding site, particularly the α-helix, while the boron atom in SS is oriented in the opposite direction (Figures 2B-E). In the case of SS interactions with Cyt C and Lys, the boron atom faces the exterior of the protein. In contrast, in the interactions with Hb and BSA, the boron atom is oriented toward the space between the secondary structural components. Thus, the orientation of the boron atom in ST closely corresponds to the secondary structural components of the model protein, maintaining an appropriate distance. This orientation has positive implications for ST's ability to bind to proteins.

[0093] Fluorescence spectroscopy was used to evaluate the affinity of SS and ST for the model protein. Regular quenching curves were observed in the intrinsic emission spectra of the model protein with increasing concentrations of SS and ST, and the Gibbs free energy (ΔG) was calculated accordingly. 0 ) and the association constant (K a ). and ΔG 0 Lower, K a ST has a higher affinity for the model protein than SS. Molecular docking simulation and thermodynamic analysis consistently show that ST is superior to SS in protein affinity as a ligand.

[0094] Example 2: Synthesis of Metal-Organic Framework Materials

[0095] As previously reported, 5-boronbenzene-1,3-dicarboxylic acid (ST ligand) and Ln 3+ (Including Dy 3+ 、Eu 3+ 、Gd 3+ and Tb 3+ ) Ln-MOFs prepared using a solvothermal method exhibit irregular shapes. Therefore, in this example, isophthalic acid and 3,5-dicarboxyphenylboronic acid were used as mixed ligands to prepare spherical lanthanide metal-organic frameworks, or Ln-MOFs. 0.072 mmol DyCl₃·6H₂O (27.13 mg), 0.036 mmol isophthalic acid (7.56 mg), and 0.036 mmol 3,5-dicarboxyphenylboronic acid (6.12 mg) were added to 36 mL of a DMF / H₂O (7:3) mixture and stirred vigorously. Ultrasonic stirring was performed at room temperature for 1 hour to ensure complete dissolution. The mixture was then transferred to a 50 mL Teflon-lined stainless steel autoclave and heated at 120°C for 6 hours. After cooling to room temperature (25°C), the mixture was concentrated at 20,000 g for 10 minutes. A fine powder was collected from the emulsion and then washed with DMF (three times), ethanol (three times), and deionized water (three times). The prepared Dy-MOFs were dialyzed in deionized water for one day, changing the water every two hours.

[0096] The synthesis procedures for Eu-MOFs, Gd-MOFs, and Tb-MOFs were similar to those for Dy-MOFs, except that EuCl₃·6H₂O (26.81 mg, 0.072 mmol), GdCl₃·6H₂O (27.40 mg, 0.072 mmol), and TbCl₃·6H₂O (26.88 mg, 0.072 mmol), respectively, were used as metal sources. A mixed lanthanide metal-organic framework (Ln-NMOF) was prepared by mixing equal amounts of a dysprosium metal-organic framework, a europium metal-organic framework, a gadolinium metal-organic framework, and a terbium metal-organic framework. The product was freeze-dried and stored in a desiccator for further use.

[0097] SEM and TEM images revealed spherical shapes for Eu-MOFs, Gd-MOFs, Tb-MOFs, and Dy-MOFs (Figures 3A-D, i, ii, and iii). DLS measurements revealed hydrodynamic sizes of 845 nm, 817 nm, 769 nm, and 803 nm for Eu-MOFs, Gd-MOFs, Tb-MOFs, and Dy-MOFs, respectively (Figures 3A-D, iv). XPS was performed to characterize the elemental composition of the MOF surfaces (Figures 3A-D, v). The presence of B1 indicates the presence of the target BO groups within the MOFs, and the corresponding lanthanide elements were observed in each MOF, further confirming the successful preparation of borate-enriched lanthanide MOFs. UV-visible absorption spectroscopy was further employed to investigate the four MOFs. The absorption spectra of all four MOFs exhibited distinct absorption bands between 260 and 300 nm, which are attributed to the π-π* transitions of the ST ligands (Figure 3E). In addition, the spectral characteristics of the four MOFs remained unchanged, with characteristic absorption peaks appearing at 285 and 293 nm, which is consistent with the ST ligand. Fourier transform infrared spectroscopy (FT-IR) of the ST ligand and the four MOFs was performed to confirm the synthetic route (Figure 3F). C=O was observed in the ligand at 1679 cm -1 The stretching vibration peak at 100 nm was observed in the MOF, but disappeared in the MOF, which confirmed that the carboxylate group was bound to Ln 3+ The 1310 cm-1 peak was observed in both the ST ligand and the MOF. -1 The absorption peak at 0.05 is from BO, indicating that the preparation of MOF is successful and the boron group does not react with Ln 3+Coordination. Powder X-ray diffraction (PXRD) results of the MOFs showed that the four MOFs were isomorphous and phase pure with high crystallinity. The broad peaks observed were attributed to the nanoscale size of the MOFs (Figure 3G). The zeta potentials of Eu-MOFs, Gd-MOFs, Tb-MOFs, and Dy-MOFs were 26.8 mV, 19.7 mV, 13.0 mV, and 7.5 mV, respectively, indicating that they have different surface physicochemical properties (Figure 3H). Overall, in-depth characterization including TEM, XPS, DLS, and zeta potential measurements jointly confirmed the unique characteristics of the four MOFs synthesized in this application.

[0098] We then incubated hybrid lanthanide metal-organic frameworks (Ln-NMOFs, also known as qMOFs) with three colored model proteins: cytochrome C (CytC, red), human hemoglobin (Hb, brown), and fluorescein isothiocyanate-lysozyme (FTIC-Lys, yellow). Protein-enriched qMOFs exhibited distinct corresponding color changes, indicating protein adsorption onto the qMOFs (Figure 3J). Confocal images revealed colocalization of fluorescein isothiocyanate-bovine serum albumin (FTIC-BSA) and the qMOFs, further demonstrating the ideal capture of proteins on the MOF surface (Figure 3I). We measured the protein capacity of the qMOFs by loading increasing concentrations of qMOFs with the same amount of protein until fluorescence disappeared. Adsorption rate curves were plotted accordingly, with the saturation line (98% absorption) indicating that 50 μg of qMOFs can accommodate approximately 10 μg of FTIC-BSA (Figure 3K).

[0099] Figure 4 shows the surface elemental characterization results of four lanthanide MOFs using a combination of scanning electron microscopy and energy dispersive spectroscopy (SEM-EDS). EDS detects X-rays generated by the interaction of an electron beam with the sample, and based on the energy distribution differences, the relative content of each element in the four MOFs is verified. The spectra show that the elemental compositions of the four MOFs are consistent with expectations.

[0100] Example 3: Metal-Organic Framework (MOF) Aided Sample Preparation (MASP) Workflow

[0101] Prior to mass spectrometry analysis, we evaluated the utility of the MOF-assisted sample preparation (MASP) workflow for proteomic analysis by treating 100 HEK 293T cells with a mixture of four single MOFs and qMOFs. Single-shot DDA-MS acquisition parameters, including resolution and LC-MS / MS gradients, were optimized and tuned to achieve adequate proteomic coverage. Identification and quantification were performed at both the peptide-matched profile (PSM) and protein levels with a statistically stringent criterion of 1% FDR.

[0102] This method is used for deep proteomics with extensive proteome coverage and precise quantification (Figure 1C). Following sample lysis, proteins are loaded onto four single MOFs or qMOFs and captured, and the supernatant, containing impurities, is discarded by centrifugation. Proteins on the MOF surface are then washed and enzymatically digested into peptides. 1% FA is then added to disrupt the MOFs, and the peptides are eluted and desalted prior to mass spectrometry acquisition. MASP minimizes sample volume and simplifies processing steps, integrating lysis, washing, and digestion in a single centrifuge tube. This reduces protein loss due to surface contact and helps improve proteomic sensitivity in samples with limited sample quantities.

[0103] qMOFs quantified 4,506 proteins and 28,723 peptides, demonstrating deeper proteomic coverage and superior peptide identification compared to single MOFs (Figures 5A, 5B). In particular, while the four MOFs share the same organic ligands, the distinct metal nodes endow them with distinct physicochemical properties. Consequently, distinct protein coronas form on the surfaces of the four different MOFs, effectively contributing to the enhanced proteomic coverage of qMOFs, as they possess all the protein coronas formed by the four individual MOFs. Furthermore, substantial overlap in the quantified proteins between MOFs was observed in a Venn diagram (Figure 5C), indicating that the proteins identified in qMOFs are primarily a collection of proteins identified by the four individual MOFs.

[0104] Furthermore, we tested the MASP workflow in 100 HEK 293T cells using commonly used sample preparation methods, including SP3 (Single-pot solid-phase-enhanced sample preparation), SOP (Surfactant-assisted One-Pot processing), and FASP (Filter-Aided Sample Preparation) as a comparison method. Compared to SP3, MASP demonstrated superior performance in terms of proteome coverage and peptide identification. MASP quantified nearly twice the number of proteins compared to SOP (Figures 5D, 5E). Consistent proteome coverage was observed in MASP-100 cells and FASP-25 ng of peptide (equivalent to 100 cellular proteins), indicating that MASP is a competitive alternative to FASP. We further assessed the quantitative reproducibility of MASP by analyzing the intraclass correlation coefficient (R²) across three runs. The correlation coefficient for MASP was 0.99, comparable to that of FASP (Figure 5F). We calculated the coefficient of variation (CV) and assessed the dynamic range based on protein abundance for SP3, SOP, MASP, and FASP. We found that MASP had a lower median CV and a wider dynamic range than SP3 and SOP, which facilitated quantitative accuracy and biomarker discovery in ultrasensitive proteomic analysis (Figures 5G, 5H).

[0105] No significant discrepancies were observed in the physicochemical properties of proteins and peptides quantified using MASP and FASP in HEK 293T cells. Calculated isoelectric points of proteins (Figure 5K), molecular weights (Figure 5L), peptide retention times (Figure 5M), and peptide cleavage deletions (Figure 5N) displayed compatible distributions, demonstrating the consistency of proteins and peptides identified by MSAP and FASP. The high cross-talk and large overlap of proteomes and peptides using MASP and FASP further confirmed the confidence in the quantified protein and peptide properties (Figures 5I, 5J).

[0106] We replicated MASP processing of 100 HEK 293T cells in ddaPASEF mode on a timsTOF fleX instrument. qMOFs quantified 4,820 proteins, a higher number than a single MOF. Consistent with previous findings using orbitrap, Venn diagrams showed a similar overlap of quantified proteins across all MOFs, further confirming that qMOFs surpassed single MOFs in proteomic identification depth. We mapped functional annotations, including GOCC, GOBP, KEGG, UniProt keywords, and Pfam, to UniProt IDs and compared enriched and depleted annotations in qMOFs to identify existing functional categories covered in HEK 293T cells (Figure 5O). Significant enrichment of various functional annotations, such as vesicle, proteasome, and RNA binding, was observed in proteins covered by qMOFs, while depleted annotations were concentrated in protein kinases and zinc fingers.

[0107] We analyzed the unique enrichment annotations for each MOF to further investigate the ability of individual MOFs to interrogate proteins from diverse functional classes. Protein locations were characterized using GOCC annotations (Figure 5Q). Tb-MOF showed enrichment of cytoplasmic and nucleoplasmic proteins, Dy-MOF showed depletion of nucleolar, membrane, and nucleoplasmic-associated proteins, and Gd-MOF enriched proteins in intracellular regions. Uniport keywords revealed that each MOF exhibited specific functional class enrichment and depletion annotations (Figure 5P). Furthermore, the ability to detect proteins from diverse functional classes demonstrates the broad and dynamic sampling capabilities of qMOFs, confirming their potential to improve sample recovery, proteomics sensitivity, and coverage.

[0108] The protein identification capabilities of MASP in cells were further characterized using qMOFs. The results demonstrated that MASP can perform label-free proteomic analysis in as few as 10 human embryonic kidney (HEK-293T) cells, making in-depth proteomics more feasible in real-world clinical scenarios, as shown in Figure 6.

[0109] Example 4: Verification of protein sample processing and detection effect

[0110] The proteomic performance of MASP using qMOFs was extensively analyzed in three cell lines: MBA-MB-231, HEK-293T, and MCF-7. As shown in Figure 7, an average of 7,130, 6,206, and 5,471 proteins were quantified in 100 MBA-MB-231, HEK-293T, and MCF-7 cells, respectively. Dynamic range was assessed based on protein abundance, as the wide dynamic range across various proteins hinders in-depth proteomic analysis, particularly for low-abundance proteins. The abundance of quantified proteins in the three cell populations spanned approximately five orders of magnitude, confirming the reliable identification of low-abundance proteins by MASP. In reproducible quantification with a CV of ≤ 20%, MBA-MB-231 cells demonstrated higher coverage of 4,696 quantifiable proteins, compared to the 3,829 and 3,422 proteins quantified in HEK-293T and MCF-7 cells, respectively. The low variation with a median CV <15.4% indicated stable protein expression in cells cultured under the same conditions.

[0111] Example 5: Verification of the effect of protein sample processing on auxiliary diagnosis

[0112] Stroke is a common acute cerebrovascular disease, with a significantly increased incidence with age. The sequelae of brain damage caused by head trauma in accidents severely impact patients' quality of life. Cerebrospinal fluid (CSF) from three small, independent cohorts was analyzed using the MASP workflow using qMOFs, including samples from six healthy controls (HC), 10 stroke (CS), and 12 brain damage (BD). As shown in Figure 8, an average of 2769, 3155, and 2863 proteins were quantified per 1 μL CSF sample for the HC, CS, and BD groups, respectively. 80.7% of the proteins were consistently detected across the three cohorts.

[0113] Hypothesis testing was performed in the CS and BR groups, using HC as a control, to investigate proteomic changes in CS and BR patients. A volcano plot, shown in Figure 9, was constructed to compare the CSF proteomes of CS and BD with those of HC. Eighteen upregulated proteins (FC > 1.5) and six downregulated proteins (FC < 0.67) were identified in CS patients. Enrichment analysis of the upregulated proteins was performed to identify potential biomarkers and therapeutic targets. Proteins upregulated in CS were categorized into angiogenesis and immune response. Increased expression of fibrinogen, a marker of thrombotic disease and involved in coagulation and hemostasis, was found. Based on UniProt annotation, proteins associated with thrombolysis and wound healing, such as SERPINE1, TIMP1, and ADAMTS13, were significantly increased, elucidating the molecular signature of post-stroke bioregulation in CS patients. In addition, 92 upregulated and five downregulated proteins were identified in BD patients. Enrichment analysis revealed that upregulated proteins were enriched in pathways involved in innate immune response, platelet degranulation, collagen catabolic processes, blood coagulation, and response to hypoxia, consistent with the body's response to severe bleeding caused by head injury. Further protein-protein interaction (PPI) network analysis revealed that SERPINA1 was a prominent factor in BD patients. The comprehensive protein expression levels associated with these five categories were profiled for potential future therapeutic exploration.

[0114] We extended the MASP workflow using qMOFs to process small amounts of tissue to characterize the mouse brain proteome. We extracted 50 μg of tissue from five random regions of the mouse brain and analyzed it using MASP (Figure 10). Across three individual mice, we identified an average of 9486 ± 79, 9598 ± 46, and 9526 ± 54 proteomes. MASP achieved promising quantitative reproducibility between replicate samples of biological tissue, with median correlation coefficients of 0.976, 0.977, and 0.949, respectively. The corresponding inter-sample coefficients of variation (CV) were 17.2%, 13.3%, and 17.8%, respectively, demonstrating low proteomic variability in small tissue samples and acceptable quantitative precision. Our results demonstrate that MASP is a promising tool for ultrasensitive and unbiased proteomic studies of small amounts of biological tissue.

[0115] Example 6: Comparison of the effects of different morphologies of metal-organic frameworks

[0116] To understand whether there are any differences between pre-treatment of MOF materials by directly dissolving them in a material storage solution for protein enrichment and freeze-drying them in freeze-dried tubes and then directly adding the protein sample to be enriched, this experiment used 50 293T cell samples for comparative testing. The experimental results are shown in Figure 11. The results show that freeze-drying the MOF materials does not significantly reduce their protein enrichment effect.

[0117] The preferred embodiments of the present invention have been described in detail above. It should be understood that numerous modifications and variations based on the concepts of the present invention are possible without inventive effort by those skilled in the art. Therefore, any technical solution that can be derived by one skilled in the art through logical analysis, reasoning, or limited experimentation based on the concepts of the present invention and the prior art should be within the scope of protection defined by the claims.

Claims

1. A label-free proteome analysis method, characterized in that: The method includes a protein sample pre-treatment step and a step of collecting and analyzing the captured protein; The pre-treatment step includes a step of capturing proteins in the protein sample using a metal organic framework, wherein the metal organic framework uses 3,5-dicarboxyphenylboronic acid as an organic ligand and a lanthanide element as a metal node.

2. The label-free proteome analysis method according to claim 1, wherein: The lanthanide elements include one, two, three or four of dysprosium, europium, gadolinium and terbium.

3. The label-free proteome analysis method according to claim 1, wherein The organic ligand also includes isophthalic acid.

4. The label-free proteome analysis method according to claim 1, wherein The metal organic framework is one, two, three or four of a dysprosium metal organic framework, a europium metal organic framework, a gadolinium metal organic framework and a terbium metal organic framework; the dysprosium metal organic framework uses 3,5-dicarboxyphenylboronic acid and isophthalic acid as organic ligands and dysprosium as metal nodes; the europium metal organic framework uses 3,5-dicarboxyphenylboronic acid and isophthalic acid as organic ligands and europium as metal nodes; the gadolinium metal organic framework uses 3,5-dicarboxyphenylboronic acid and isophthalic acid as organic ligands and gadolinium as metal nodes; and the terbium metal organic framework uses 3,5-dicarboxyphenylboronic acid and isophthalic acid as organic ligands and terbium as metal nodes.

5. The label-free proteome analysis method according to claim 4, wherein: The metal organic framework is a mixture of four types of metal organic frameworks: dysprosium metal organic framework, europium metal organic framework, gadolinium metal organic framework and terbium metal organic framework.

6. The label-free proteome analysis method according to claim 5, wherein: The molar ratio of the dysprosium metal organic framework, the europium metal organic framework, the gadolinium metal organic framework and the terbium metal organic framework is 1:0.8-1.2:0.8-1.2:0.8-1.2; and / or, The molar ratio of the organic ligand to the metal node is 0.8 to 1.

2.

7. The label-free proteome analysis method according to claim 3, wherein: The molar ratio of the 3,5-dicarboxyphenylboronic acid to the isophthalic acid is 0.8-1.

2.

8. The label-free proteome analysis method according to claim 1, wherein The metal organic framework is a freeze-dried body; and / or, The metal organic framework is spherical.

9. The label-free proteome analysis method according to claim 1, wherein: The pre-treatment step also includes the steps of washing the metal organic framework with captured proteins, digesting the proteins, and eluting and desalting the digested proteins.

10. The label-free proteome analysis method according to claim 9, wherein: The washing and digestion were performed in the same tube.

11. The label-free proteome analysis method according to claim 9, wherein: The pre-treatment step further includes a step of cracking the protein sample before the metal organic framework captures the protein.

12. The label-free proteome analysis method according to claim 11, wherein: The lysis, washing and digestion were performed in the same tube.

13. The label-free proteome analysis method according to claim 1, wherein The specific method of the pretreatment step is: loading the metal organic framework into the protein sample and capturing the protein, then discarding the supernatant containing impurities by centrifugation, then washing the protein on the surface of the metal organic framework, and using enzymes to digest the protein into peptides, and then eluting and desalting the protein.

14. The label-free proteome analysis method according to claim 1, wherein: The acquisition and analysis steps use mass spectrometry to acquire data and then perform data processing.

15. The label-free proteome analysis method according to claim 1, wherein The protein sample includes a lysed cell sample, a lysed tissue sample or a biological fluid sample.

16. The label-free proteome analysis method according to claim 15, wherein: The number of cells in the lysed cell sample is 10 to 5000; The mass of the tissue in the lysed tissue sample is 50 μg to 1000 μg; The volume of the biological fluid sample is 1 μL to 1000 μL.

17. The label-free proteome analysis method according to claim 1, wherein: The metal-organic framework captures trace amounts of proteins in the protein sample.

18. A metal organic framework suitable for enriching proteins, characterized in that: The metal organic framework uses 3,5-dicarboxyphenylboronic acid as an organic ligand and lanthanide elements as metal nodes.

19. The metal organic framework according to claim 18, wherein The lanthanide elements include dysprosium, europium, gadolinium and terbium.

20. A method of a metal organic framework according to any one of claims 18 to 19, characterized in that The method uses isophthalic acid (1,3-BDC) and 3,5-dicarboxyphenylboronic acid as mixed ligands to prepare spherical lanthanide metal-organic frameworks (Ln-MOFs) through a solvothermal method.

21. The method according to claim 20, wherein The method specifically includes: adding lanthanide metal ions, isophthalic acid and 3,5-dicarboxyphenylboronic acid to a mixed solution of N,N-dimethylformamide and H2O, stirring and dissolving at room temperature, then heating the mixture at 100°C to 140°C for 4 to 36 hours, cooling to room temperature, concentrating and collecting fine powder, and then washing with DMF, ethanol and deionized water respectively, dialyzing the formed metal-organic framework in deionized water, freeze-drying the product, and mixing a dysprosium metal-organic framework, a europium metal-organic framework, a gadolinium metal-organic framework and a terbium metal-organic framework to prepare the metal-organic framework.

22. A protein sample pretreatment method using the metal organic framework according to any one of claims 18 to 19, characterized in that: The metal-organic framework is loaded into the sample and captures proteins, and the supernatant containing impurities is discarded by centrifugation. Subsequently, the proteins on the metal-organic framework surface are washed and enzymatically digested into peptides. The proteins are eluted and desalted before mass spectrometry acquisition.

23. The protein sample pretreatment method according to claim 22, wherein: The described method integrates lysis, washing, and digestion in one centrifuge tube.

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