106 results about "Proteomics" patented technology

The invention relates to the technical field of biomedicine, in particular to a method for constructing a plasma ctDNA organ distribution characteristic spectrum of advanced colorectal cancer. The method comprises the following steps: collecting a peripheral blood sample at multiple time points, separating plasma by adopting a double-centrifugal method, and extracting circulating tumor DNA (Deoxyribose Nucleic Acid); carrying out whole exome sequencing based on ctDNA to obtain genome variation information and calculating variation allele frequency, and synchronously detecting the expression quantity of immune-related proteins by adopting an Olink proteomics technology; integrating the genome data, the protein expression data and the clinical pathological features, and constructing a multi-dimensional feature data matrix; and taking the organ metastasis condition confirmed by iconography as a supervision label, training a model by applying a machine learning algorithm, screening key prediction factors, constructing a quantitative prediction model, and finally generating a visual organ metastasis tendency prediction map. According to the method, early and accurate prediction of the advanced colorectal cancer organ metastasis tendency is realized through multi-omics data collaborative analysis and machine learning modeling.

The invention belongs to the technical field of biological materials and biological information, and provides a space phosphorylation modification omics detection method. According to the detection method disclosed by the invention, proteomics analysis can be carried out on trace sample phosphorylation, 4259 phosphorylation sites can be identified by 5 micrograms of peptide fragments, and the credibility of 3506 sites is greater than 0.75.

The invention discloses a multi-layer heterogeneous network unicellular organism network inference method based on meta-path enhancement, which mainly comprises a gene regulation knowledge base enhanced multi-layer heterogeneous network construction module for integrating an external gene interaction network and multiple omics data such as scRNA-seq, scATAC-seq, ST and the like; constructing a single-cell multi-omics multilayer heterogeneous network containing cell-cell, cell-gene and gene-gene relationships, and fusing spatial constraints to consider cell positions and tissue structures; and the feature enhancement module based on the meta-path explores complex semantics of the network by designing a multi-hop meta-path mode, designs an adaptive multi-view learning framework and a multi-round enhancement mechanism, and optimizes feature representation by using cell-gene interaction and cross-modal attention fusion. The unicellular biological network can be effectively deduced, the deduction accuracy and biological interpretation are remarkably improved, the method plays an important role in understanding the cell biological process, developing and treating diseases and the like, has good expandability, and can further integrate multi-modal omics data such as proteomics and metabonomics.

The invention discloses a breast milk fat globule membrane protein simulation degree evaluation method based on multi-dimensional similarity weighted fusion, and the method comprises the steps: constructing a breast milk MFGM proteomics database, and obtaining the proteomics data of a to-be-evaluated sample; the method comprises the following steps: obtaining a reference matrix through row screening and column screening based on a breast milk MFGM proteomics database, performing logarithmic transformation on the reference matrix, calculating a mean value and a standard deviation of each feature in the reference matrix, and constructing a Z-score matrix and a missing mask matrix corresponding to the reference matrix; calculating abundance distribution similarity and missing mode similarity of the to-be-evaluated sample; setting a shrinkage coefficient based on the actual overlapping feature number, screening a core protein set according to a set threshold value, and comparing to obtain the missing MFGM protein type of the to-be-detected sample; and constructing a Top-K neighbor center, calculating the feature deviation contribution and abundance difference of the to-be-evaluated sample, and outputting key defect proteins and formula optimization suggestions according to preset feature importance indexes. And the similarity simulation accuracy is improved.

本发明实施例公开了一种基于蛋白质组学的脓毒症休克患者液体管理策略预测方法。所述方法包括：收集脓毒症休克患者的血浆样本，检测蛋白质标志物的表达水平，所述蛋白质标志物为GAL、NFASC、MICB_MICA、MAP2K6、JCHAIN和CSF3的组合；基于亚组识别模型计算效益得分，获得脓毒症休克患者的液体管理策略结果。本发明通过收集脓毒症休克患者的临床数据和蛋白质表达数据，采用LASSO回归分析，构建基于上述蛋白质标志物的亚组识别模型，进而获得效益评分，基于效益评分能预测患者液体管理策略方案的适用性，为脓毒症休克患者的液体治疗提供了可靠的方案，实现个体化和精准的液体治疗，在临床具有较好的应用前景。

The application discloses a marker for determining the severity of IgAN kidney tissue lesions and application thereof, and inventors find that ACTN4, ACADS and COL1A1 are significantly differentially expressed proteins in kidney tissues. The significant down-regulation of ACTN4 may cause the change of actin cytoskeleton of IgAN glomerular podocytes; the significant down-regulation of ACAD may indirectly participate in the occurrence process of abnormal structure and function of IgAN renal tubular epithelial cells by affecting fatty acid metabolism in the cells; and the significant up-regulation of COL1A1 may participate in the accumulation of extracellular matrix in the renal interstitium of IgAN, and play a certain role in promoting the renal interstitial fibrosis. The combination of ACTN4, ACADS and COL1A1 has good prediction efficiency for the diagnosis of the severity of IgAN kidney tissue lesions, and the area under the ROC curve is 0.815, P 0.043. In addition, the immunohistochemical results also confirm the expression trend of the three proteins ACTN4, ACADS and COL1A1 in the corresponding kidney tissue substructures in proteomics.

The present invention relates to the field of biochemistry, more particularly to proteomics, more particularly to protein sequencing, even more particularly to single molecule peptide sequencing. The invention discloses means and methods for single molecule protein sequencing and / or amino acid identification using cleavage inducing agent. Said cleavage inducing agents which are not specific for one particular amino acid, cleave polypeptides step by step from the N-terminus onwards and provide information on the identity of the cleaved amino acids based on the kinetics of said reaction.

The present invention provides a multiomics approach, which integrate single-cell RNA-sequencing (scRNA-seq) and spatiotemporal transcriptomics (ST) offering potential for dissecting transcriptional networks and revealing cell-cell interactions involved in biomolecular pathomechanisms. The present invention also provides a multimodal approach combining high-throughput scRNA-seq and ST to elucidate XLRS-specific transcriptomic signatures in two XLRS-like models with retinal splitting phenotypes, including genetically engineered (Rs1emR209C) mice and patient-derived retinal organoids harboring the same patient-specific p.R209C mutation. Through multiomics transcriptomic analysis, the endoplasmic reticulum (ER) stress / eIF2 signaling, mTOR pathway, and the regulation of eIF4 and p70S6K pathways as chronically enriched and highly conserved disease pathways between two XLRS-like models are identified. Western blots and proteomics analysis validated the occurrence of unfolded protein responses, chronic eIF2α signaling activation, and chronic ER stress-induced apoptosis. Furthermore, therapeutic targeting of the chronic ER stress / eIF2α pathway activation synergistically enhanced the efficacy of AAV mediated RS1 gene delivery, ultimately improving bipolar cell integrity, postsynaptic transmission, disorganized retinal architecture and electrophysiological responses. Collectively, the complex transcriptomic signatures obtained from Rs1emR209C mice and patient-derived retinal organoids using the multiomics approach provide opportunities to unravel potential therapeutic targets for incurable retinal diseases, such as XLRS.

A method for predicting one or more sample metric values by machine learning is provided. The method comprises determining a plurality of characteristics from raw data obtained by analysing a proteomics sample in a liquid chromatography mass spectrometer, LC-MS. The method further comprises predicting one or more sample metric values by processing the plurality of characteristics using one or more trained machine learning models.

This invention relates to the construction and application of an exosome purification device. The purification device utilizes the differences in size and charge between exosomes and other substances, combining the tangential flow of the sample within the device with the dual effects of membrane sieving and an electric field to remove contaminants and achieve high-purity exosome enrichment. The device includes a pre-filtration section and an exosome purification section. This device is simple to operate, can handle large sample volumes, has a short processing time, is less prone to membrane clogging by contaminants, and achieves high purity exosome separation with minimal structural damage. It can meet the separation and purification needs of exosomes from different sources and can be further applied to research on exosome proteomics, drug loading, activity, and biological functions.

The application discloses a method for collecting and purifying mouthpart secretion of a predatory natural enemy Orius minor, and belongs to the technical field of biology. The method comprises the following steps: constructing a double-layer membrane sandwich artificial feeding device, encapsulating a nutrient solution in a sandwich space between a first membrane layer and a second membrane layer, and using the feeding drive of the Orius minor to make the Orius minor actively pierce the membrane layer and feed the nutrient solution, so that the mouthpart secretion is released into the nutrient solution in the natural feeding process; after the nutrient solution containing the secretion is collected, ultrafiltration centrifugation technology is used for concentration and purification, and a high-purity mouthpart secretion protein sample is obtained. The natural feeding state of the Orius minor is simulated, the collected secretion can more truly reflect the functional protein released by the Orius minor in the predation process, meanwhile, the integrated design of collection and purification effectively removes small molecular impurities in the sample, and the sample can be directly used for high-precision analysis such as proteomics.

The invention relates to a novel chemical cross-linking agent with mass spectrum fragmentable trehalose disaccharide as a skeleton structure and a preparation method thereof. The cross-linking agent disclosed by the invention has the following characteristics: 1) trehalose disaccharide is used as a skeleton structure, so that the cross-linking agent has excellent biocompatibility; 2) the trehalose skeleton has a pair of symmetrical mass spectrum fragmentable glucosidic bonds, so that a cross-linked peptide fragment can be simplified into a conventional peptide fragment modified by a cross-linking agent fragment; 3) the enrichment of the cross-linked peptide fragment can be realized by the trehalose skeleton under the condition of not adding an enrichment handle; and 4) active groups of the cross-linking agent comprise but not limited to a plurality of reactive groups such as succinamide ester, diaziridine, phenylsulfonyl fluoride, hydrazide group, amino group, hydroxylamine group and the like, and chemical cross-linking of a plurality of amino acids except lysine is realized. The trehalose cross-linking agent disclosed by the invention is applied to the field of proteomics, and provides technical support for realizing large-scale analysis of a protein complex in a complex sample, spatial structure analysis of protein and a protein-protein interaction network.

The invention provides a construction method for a tissue paraffin section space proteomics sequencing library. The method comprises the following steps: providing a solid phase carrier and an antibody-nucleic acid conjugate; attaching a tissue paraffin section sample to the solid-phase carrier, and carrying out section baking, dewaxing, hydration, decrosslinking and sealing treatment to obtain a sealed solid-phase carrier; incubating the antibody-nucleic acid conjugate and the closed solid-phase carrier to obtain a protein capture solid-phase carrier; carrying out permeabilization treatment and DNA synthesis on the protein capture solid phase carrier to obtain cDNA; releasing the cDNA from the solid-phase carrier, collecting the cDNA, and amplifying to obtain the sequencing library.

The invention relates to the technical field of biological detection, and provides an integrated gradient spinning fiber membrane for multi-omics analysis and a preparation method of the integrated gradient spinning fiber membrane. According to the fiber membrane, a coaxial electrostatic spinning technology is adopted, and functional zones are continuously formed on a single membrane by controlling the flow velocity of a shell layer (PLGA / chitosan solution) and a core layer (PEO / GPC3 aptamer solution): a nucleic acid enrichment end adsorbs and captures nucleic acid through positive electricity of chitosan, and a protein capture end recognizes a liver cancer marker GPC3 protein through a fixed GPC3 specific nucleic acid aptamer G625. According to the design, the capture environment of nucleic acid and protein is physically isolated, the problems of mutual interference and cross contamination of functional sites in a traditional method are fundamentally solved, and parallel and in-situ capture and enrichment of genomics, transcriptomics and proteomics information in the same trace biological sample are realized. The method is easy and convenient to operate, GPC3 protein is specifically captured and recognized, the nucleic acid enrichment capacity and the cross contamination resistance capacity are high, and a new strategy is provided for early diagnosis and precise typing of liver cancer.

The present disclosure is directed to methods for measuring proteomes of single cells. In one aspect, methods comprise disposing cells on a surface, synthesizing hydrogel chambers around each of the cells, lysing the cells to release intracellular proteins for adsorption onto the surface bounded by the hydrogel chambers, depolymerizing the hydrogel chambers, and quantifying the adsorbed proteins with detection antibodies to determine the single cell proteomes.

The invention provides a proteome-based malt yeast advanced flocculation performance prediction method and application, and belongs to the technical field of malt characteristic detection. The method can solve the problems that the detection result is easily interfered by external factors, the consumed time is long, and the pre-flocculation value of the malt yeast cannot be directly detected in the existing method for detecting the pre-flocculation performance of the malt yeast. According to the method for predicting the advanced flocculation performance of the malt yeast based on the proteome, the advanced flocculation performance of the malt yeast to be detected is predicted by performing peptide spectrum matching value analysis on specific protein obtained by analyzing the proteome of the malt to be detected. According to the method, the advanced flocculation performance of the yeast is predicted by detecting the difference between the expression quantity of related protein and the expression quantity of standard malt, the detection time is shortened to 1 day, the detection efficiency is improved, the influences of external factors such as yeast activity and oxygenation are effectively avoided, the advanced flocculation performance of the yeast in the malt can be rapidly and accurately evaluated in the malting stage, and the method is suitable for large-scale popularization and application. Problems encountered in production can be fed back in time to make process adjustment.

A method for predicting one or more sample metric values ​​using machine learning is provided. The method involves determining a variety of properties from raw data obtained by analyzing a proteomics sample in a liquid chromatography-mass spectrometer (LC-MS). The method further includes predicting one or more sample metric values ​​by processing these properties using one or more trained machine learning models.

A method processes an experiment design definition and resulting omics data containing measurements for multiple analytes. For each analyte, the method fits a model to estimate a first variability and computes a first quality metric per measurement. The method aggregates per-analyte measurements into a composite quality metric, fits a function relating the composite quality metric to the first variability, and uses the function to transform both variables. The method fits a model to the transformed data to obtain a second estimated variability for each analyte and computes residuals from the first and second estimates, followed by variance moderation of the residuals. The method then reads a second dataset with samples for multiple analytes, computes a second quality metric for each analyte, transforms the second quality metric using the function, and applies the fitted model to output a variance metric for each analyte in the second dataset.

The application discloses a research method of a potential protein target point of Guangxi Yaoshan sweet tea against diabetic nephropathy based on proteomics, relates to the technical field of biological medicine, and solves the problem of lacking research on the target point of the action of Yaoshan sweet tea on the prevention and treatment of diabetic nephropathy from the perspective of proteomics. The method comprises the following steps: determining a characteristic active ingredient, namely myricetin, of Yaoshan sweet tea for intervention on diabetic nephropathy, obtaining a PPI network of network pharmacology of the intersection target point of the characteristic active ingredient of Yaoshan sweet tea and diabetic nephropathy; preparing a myricetin solution, preparing a cell disease model and grouping intervention, collecting and pre-treating a cell protein sample, performing mass spectrometry, pre-processing proteomic mass spectrometry data, screening a potential protein target point, identifying and analyzing an expression change trend of the potential protein target point, and analyzing a core protein target point and a key signal path. The application directly locates the key protein target point of Guangxi Yaoshan sweet tea on diabetic nephropathy from a protein expression level, which is more intuitive and more accurate.

The invention discloses a herbicide-resistant gene StGSTF8 in sagittaria trifolia and application of the herbicide-resistant gene StGSTF8, and belongs to the technical field of genetic engineering. The bensulfuron methyl resistance gene StGSTF8 (glutathione-S-transferase F8) is identified from sagittaria trifolia for the first time by means of proteomics, molecular biology, transgenic function verification and the like, the nucleotide sequence is as shown in SEQ ID NO: 1, the coded amino acid sequence is as shown in SEQ ID NO: 2, and the nucleotide sequence is as shown in SEQ ID NO: 1. It is proved that the strain endows plants with resistance through mediating herbicide detoxification metabolism and oxidative stress resistance, and reference is provided for improvement of the resistance of plants to sulfonylurea herbicides and research and development of novel herbicides.

The application discloses a kind of bifunctional magnetic nano material and its preparation method and application.The nano material described in the application is Fe3O4@ZrO2@TiO2@mSiO2-L-Cys, with spherical structure;The material includes successively from inside to outside: the inner core is the magnetic nanoparticle of ferriferrous oxide;Intermediate layer is zirconium dioxide and titanium dioxide composite metal oxide layer;Sub-outer layer is mesoporous silica layer;The outermost layer is the L-cysteine molecular layer grafted by zirconium-sulfur chemical bond;The preparation method described in the application adopts solvothermal method to synthesize magnetic core, functional layer is coated by hydrothermal reaction, co-condensation method constructs mesoporous shell, and hydrophilic group is introduced by chemical grafting.The bifunctional magnetic mesoporous nano material prepared in the application is applied to the effective enrichment of glycopeptide and phosphopeptide in standard protease solution mixture, and the detection sensitivity of phosphopeptide and glycopeptide reaches 1 fmol / μL, which has wide prospect in glycopeptide and phosphopeptide proteomics analysis research.

The application relates to a screening and determining method of an ischemic cerebral stroke animal model biomarker of qi deficiency and blood stasis syndrome, which integrates proteomics and transcriptomics technologies, systematically screens differentially expressed proteins and genes related to the syndrome, and on the basis, constructs various disease animal models, verifies candidate targets by adopting ELISA, simultaneously combines qPCR technology, multi-dimensionally confirms expression changes in the models, further draws ROC curves, calculates AUC values, sensitivity and specificity and other diagnostic performance indexes, evaluates diagnostic potential, and further knocks down and overexpresses differentially expressed genes, deeply excavates potential biomarkers with diagnostic values, and provides scientific bases for objective diagnosis of ischemic cerebral stroke qi deficiency and blood stasis syndrome and exploration of molecular mechanisms.

The utility model provides a perforated plate system for single cell proteomics mass spectrometry, which relates to the field of detection supplies and comprises a perforated plate body and a buffer solution arranged in reaction holes of the perforated plate body, and the buffer solution is used for single cell lysis and enzymolysis and has liquid phase mass spectrum sample introduction compatibility. The porous plate system (such as a 96-pore plate, a 384-pore plate and the like) is integrated with ultramicro reaction liquid (namely a buffer solution which is used for single cell lysis and enzymolysis and has liquid phase mass spectrum sample introduction compatibility), has the liquid phase mass spectrum sample introduction compatibility, does not need any sample transfer step, can directly carry out liquid phase mass spectrum instrument analysis, and has the advantages of simple structure, convenience in operation and high efficiency. The method has the advantage of zero sample loss, realizes one-step completion of single-cell proteomic sample preparation, and realizes high throughput of single-cell proteomic sample preparation.

The invention belongs to the field of molecular biology, particularly relates to a three-function probe and application thereof, and more particularly relates to a three-function probe with marking, enriching and imaging functions and application thereof. The probe provided by the invention integrates marking, enriching and imaging, can simultaneously perform cell type imaging and in-situ proteomics analysis on the same tissue slice, reduces potential deviation, and enables an analysis result to be more accurate.

The present application relates to the technical field of protein genomics analysis, and particularly relates to a protein gene multiomics analysis method, which comprises: S1. sample collection and pretreatment: tumor tissue and paired normal adjacent tissue are selected as samples, and the samples are frozen and crushed; S2. sample multiomics detection: the frozen and crushed samples are subjected to genomics detection and proteomics detection; S3. sample multiomics data processing and analysis: the genomics detection result and the proteomics detection result of the samples are obtained, and tumor molecular characteristics are identified through multiomics data integration analysis.The present application carries out systematic protein genomics analysis on LCNEC tumor tissue and NATs. The research not only reveals the genomic abnormality characteristics of LCNE and disease-related molecular phenotypes, but also deepens the scientific cognition of patient stratification logic in targeted therapy strategies. Further research finds that IL33, as a new key therapeutic biomarker, is related to T cell infiltration and has anti-tumor activity.

The invention relates to the field of biological detection, in particular to a multi-omics combined screening cell senescence marker detection method and application thereof. According to the method, data of genomics, transcriptomics, proteomics and metabonomics are combined, and multi-dimensional data in the cell senescence process are subjected to high-throughput screening and integration by means of whole genome sequencing, RNA-Seq, a liquid chromatography-mass spectrometry technology and a gas chromatography-mass spectrometry technology. And adopting machine learning algorithms such as random forest, a support vector machine and deep learning to screen out key markers related to aging. The markers comprise genes, proteins and metabolites, and have relatively high sensitivity and specificity. Verification of different aging models proves that the screened markers change significantly in the aging process and can effectively reflect the biological characteristics of cell aging. The method provides new technical support and theoretical basis for research of an aging mechanism, early diagnosis of aging-related diseases and anti-aging treatment.

The invention relates to a polar aprotic organic solvent for dissociating a streptavidin-biotin conjugate as well as a screening method and application of the polar aprotic organic solvent. Aiming at the problems that a streptavidin-biotin conjugate system is difficult to elute quickly under a mild condition and a carrier is difficult to regenerate, a solvent molecule descriptor database is constructed; a polar aprotic organic solvent which meets specific molar refractive index and polarity parameters and is a non-hydrogen bond donor is screened from a large number of candidate solvents by utilizing a machine learning model. The solvent can realize rapid reversible dissociation of biotin conjugates from streptavidin at room temperature, and the carrier still keeps high activity after multiple rounds of binding-elution cycles. The solvent is further used for purification of biotinylated small molecules in a crude reaction solution, enrichment and elution of mitochondria and cell surface samples and the like, topological resolution proteomics analysis is achieved, a high-purity product can be obtained in a high-flux mode, and site level topological analysis can be completed.

Aptamer detection techniques with chemistry attachment with proximity hybridization and extension are described in an aptamer-based assay. In an embodiment, capture oligonucleotides can be used such that the capture oligonucleotides attach to spatially-fixed analytes in a fixed tissue sample. Aptamers that hybridize to the capture oligonucleotides are tagged with an extension sequence that can then be used for subsequent capture and spatial tagging steps.

This invention relates to the field of tissue processing technology and discloses an improved method for cryoembedding hollow organ tissues. The method includes the following steps: pretreatment of the ex vivo tissue; after ex vivo, the tissue is soaked in a buffer solution and gently shaken to clean off any adhering dirt, mucus, secretions, or necrotic material; then, the cleaned tissue is placed on multiple layers of absorbent paper to fully absorb excess water. Through a rapid gradient cooling process, combined with the low-temperature coagulation effect of water-soluble mixtures such as polyethylene glycol and polyvinyl alcohol, the tissue can be rapidly fixed, minimizing the formation of ice crystals and preventing tissue rupture. This also helps preserve the most accurate and detailed morphological structure of hollow organs rich in connective tissue, improving the accuracy of subsequent pathological diagnosis and research. Furthermore, for basic research, it is suitable for experiments such as immunofluorescence, spatial proteomics, and spatial transcriptomics.

The invention provides a COPD (chronic obstructive pulmonary disease) target protein based on plasma proteomics. The target protein comprises one or more of the following four proteins: HLA-DRA (human leukocyte antigen-DRA), CXCL9, TNFRSF8 and RNASET2. The invention not only highlights the important value of longitudinal proteomics analysis in revealing the early biological change of COPD, but also opens up a new path for the development of personalized treatment schemes. In view of the complex function of protein in the biological regulation and control process, the research result of the invention provides an important framework for understanding the pathological mechanism of COPD, and lays a foundation for developing a treatment strategy based on proteomics in the future. The invention also provides an application based on the COPD target protein and a medicine for treating COPD.