423 results about "Proteome" patented technology

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.

This invention discloses a milk protein containing composition comprising: at least one milk protein; at least a first protein; at least a second protein; and at least a linker comprising an amino acid sequence coded by nucleotide sequence which is at least 80% similar to sequences selected from the group consisting of SEQ ID NO: 14, SEQ ID NO: 15, SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 18, SEQ ID NO: 19, SEQ ID NO: 20, and SEQ ID NO: 21

The invention discloses a method for screening and identifying a cucumber aphid-resistant gene as well as a screened gene and application thereof, and provides a brand-new method for screening and identifying the cucumber aphid-resistant gene, which is used for screening the cucumber aphid-resistant gene based on four omics technologies. The four types of omics comprise transcriptome, proteome, methylation group and metabolome before and after inoculation of aphids on cucumbers, and the cucumber aphid resistance regulation gene is screened through combined analysis, so that a new gene resource is provided for improving the aphid resistance of the cucumbers, and a new method and a new idea are provided for designing molecular genetic breeding. The CsPGD2 gene obtained through screening is an aphid resistance gene, the dynamic change of a metabolic substance 5-ribulose phosphate in a metabolome is consistent with that of a transcriptome gene CsPGD2, the aphid resistance function of the gene CsPGD2 is verified through VIGS, and the result proves that the gene CsPGD2 is an important regulation factor for the aphid resistance of cucumbers. The invention provides a new gene resource for improving the aphid resistance of cucumbers, and has a good application prospect.

The invention provides a rapid quantitative analysis method for an outer vesicle proteome, and belongs to the technical field of quantitative analysis of the outer vesicle proteome. According to the rapid quantitative analysis method for the outer vesicle proteome, firstly, a high-quality outer vesicle sample is obtained through low-speed centrifugation, ultra-speed centrifugation and membrane filtration; and obtaining proteome data by utilizing two-dimensional electrophoresis and mass spectrometry. Then, a mathematical model equation set is constructed for preliminary analysis, a protein interaction network is optimized through an embedded game optimization index model, and feature extraction and quantitative analysis are conducted through a convolution parameter adaptive function and a residual network deep learning model; finally, a quantitative analysis result containing the protein expression level and the function importance is generated in combination with the multi-dimensional protein expression contribution index, and the technical problem that in the prior art, in the rapid quantitative analysis process of the outer vesicle proteome, the protein component complexity is high, and consequently the quantitative precision is low is solved.

The present invention addresses the problem of providing an improved RpBphP1 mutant and an improved RpPpsR2 mutant in such a manner that the binding and dissociation can be reliably controlled by light irradiation and shielding of near-infrared light. More specifically, the present invention is a proteome comprising two types of proteins that bind to each other under irradiation of near-infrared light, the proteome being a group of RpBphP1 mutants and wild-type RpPpsR2, a group of wild-type RpBphP1 mutants and RpPpsR2 mutants, or a group of RpBphP1 mutants and RpPpsR2 mutants, the binding of the proteome being greater than that of the wild-type RpBphP1 mutants and that of the wild-type RpPpsR2, and the binding of the proteome being less than that of the wild-type RpBphP1 mutants and that of the wild-type RpPpsR2. The binding in a dark place is weak and / or the binding under the irradiation of near-infrared light is strong.

The invention relates to the field of agricultural products, and particularly discloses a polypeptide for improving plant disease resistance, and the polypeptide is LAND2 small peptide and homologous peptide thereof. The LAND2 small peptide disclosed by the invention is screened and found from an arabidopsis thaliana proteome, and homologous peptides of the LAND2 small peptide are respectively derived from chilies and cucumbers. Tests prove that when the LAND2 small peptide is externally applied to arabidopsis thaliana, the local and systematic resistance of plants to botrytis cinerea can be enhanced, and the LAND2 small peptide has broad-spectrum immunocompetence in chilies and cucumbers. The polypeptide is practically applied to agricultural production, can enhance the disease resistance of plants and improve the yield and quality of the plants, and has practical popularization and application values.

The invention provides a method for screening high-activity endogenous antibacterial peptides, which comprises the following steps: (1) collecting antibacterial peptide sequences in an antibacterial peptide database, and constructing an antibacterial peptide prediction model; (2) acquiring pig source proteome data; (3) screening out sequences with the length of 8-50 residues from pig-source proteome data to construct a candidate data set; (4) screening out non-redundant sequences from the candidate data set to construct a prediction data set; (5) predicting endogenous antibacterial peptides in the prediction data set by using the antibacterial peptide prediction model to obtain candidate antibacterial peptides; and (6) carrying out bioinformatics analysis on the candidate antibacterial peptide, comparing the candidate antibacterial peptide with an antibacterial peptide database, and screening out the antibacterial peptide with the similarity of less than 100% and secretory protein characteristics or exosome protein characteristics to obtain the high-activity endogenous antibacterial peptide. The method provided by the invention can be used for efficiently and quickly screening the high-activity endogenous antibacterial peptide, provides a new way for developing novel antibacterial peptide, and has a wide application prospect.

Provided herein are novel stabiligases for use in cell membrane proteome analysis. The subject stabiligases are capable of attaching to glycans found on the surface of cell membranes to form glycan-tethered (GT) stabiligases. Such glycan-tethered stabiligases are capable of robustly and selectively attaching label probes to cell surface proteins of intact cells. The subject novel stabiligases described herein advantageously allow for the identification and profiling of cell membrane proteins that have undergone an extracellular N-terminal proteolytic event.

The invention discloses a biological age assessment method, which comprises the following steps: acquiring a key protein index of a to-be-assessed person, and inputting an improved biological age assessment model I to obtain the biological age of the to-be-assessed person; the improved biological age assessment model I is constructed and obtained based on an elastic network regression algorithm by taking proteome data and body composition age of an individual as training data. The invention also discloses a construction method of the model, namely a two-step method. According to the method, the user is allowed to calculate the biological age according to the proteome data of the user, personalized monitoring of the muscle aging state is achieved, and the method has great guiding significance in the aspects of identifying individuals with premature aging of muscle functions and formulating personalized precise anti-aging schemes.

The invention provides a single-cell drug sensitivity prediction algorithm based on multi-modal reinforcement learning, and aims to solve the problem that the accuracy of a traditional drug sensitivity prediction method is limited. According to the system, multi-modal bioinformatics data including cell line gene expression data, proteome data, metabolome data, drug reaction data and single-cell RNA sequencing data are integrated, and feature extraction, fusion and selection are performed by using a deep reinforcement learning technology, so that high-precision prediction of single-cell drug sensitivity is realized. The algorithm mainly comprises five core modules: a multi-modal data integration and preprocessing module, a deep reinforcement learning feature extraction and fusion module, a dynamic feature selection and importance evaluation module, a cross-domain migration and adaptive learning module and a deep reinforcement learning prediction model and performance optimization module. The modules work cooperatively, potential features can be learned automatically from multi-modal data, a feature fusion strategy can be optimized, a key feature subset can be selected dynamically, and a model structure and parameters can be adjusted adaptively according to features of target domain data, so that prediction accuracy and stability are improved remarkably. Experimental results show that the algorithm shows significant advantages in multiple evaluation indexes, and compared with a traditional prediction method, the algorithm has higher prediction accuracy and wider applicability. Therefore, the invention provides a novel and efficient drug sensitivity prediction tool for the fields of personalized medical treatment and drug research and development, and has important practical application value.

The present disclosure provides compositions and methods for targeting neoantigens, for example, to treat or prevent cancer. The disclosed embodiments include binding proteins, such as T cell receptors, that bind to the neoantigen: HLA complex. The binding protein further comprises a construct comprising a fusion protein of the CD95 extracellular domain and the CD137 intracellular signaling domain (Fas-41BB), and a CDS coreceptor alpha or beta chain. The disclosed binding proteins are highly sensitive to antigens and are capable of inducing activation of host T cells at low concentrations of peptide antigens. In certain embodiments, binding proteins of the present disclosure (i) have no alloreactivity, substantially no alloreactivity, and / or low risk of alloreactivity, to amino acid sequences from human proteomes and / or (ii) to human HLA alleles. Polynucleotides encoding such binding proteins can be introduced into host cells, such as T cells, and the cells can be used in immunotherapy for the treatment of various cancers.

Kits and methods of analyzing macromolecules, including peptides, polypeptides, and proteins, using nucleic acid coding are disclosed. Sample analysis kits employ nucleic acid coding and / or nucleic acid recording of molecular interactions and / or reactions, such as recognition events (e.g., between antigens and antibodies, between modified terminal amino acid residues, or between small molecules or peptide therapeutic agents and targets, etc. Additional barcoding reagents, such as reagents for cycle-specific barcoding (e.g., "timing"), compartment barcoding reagents, combined barcoding reagents, spatial barcoding reagents, or any combination thereof, may be included in the kit. The sample may comprise macromolecules, including peptides, polypeptides, and proteins, and the recording may produce molecular interaction and / or reaction information, and / or polypeptide sequence information. The kits can be used for high throughput, multiplexing and / or automated analysis, and are suitable for the analysis of proteomes or subsets thereof.

The present invention relates to nucleic acids coding for a protein said protein comprising a truncated glial fibrillary acidic protein (GFAP), proteins comprising a truncated GFAP, expression constructs comprising a nucleic acid coding for a protein which comprises a truncated GFAP, vectors comprising the nucleic acids or expression constructs disclosed herein and eukaryotic cells comprising a nucleic acid, proteins, expression construct or vector disclosed herein. The present invention furthermore relates to compositions comprising the herein disclosed proteins and kits comprising the herein disclosed proteins and / or compositions. Furthermore, the present invention relates to the use of the herein disclosed proteins, compositions and / or kits for calibrating a measurement system for the in vitro quantification of GFAP or a variant thereof in a sample.

The invention belongs to the technical field of breast cancer treatment, and particularly relates to a patient layering method based on a breast cancer single cell space proteome multicellular enrichment mode, which comprises the following steps: S1, breast cancer single cell space proteome image data cell segmentation and cell type identification; s2, constructing a cell network diagram, and simulating a tumor microenvironment; s3, detecting closely connected cell communities, and extracting cell community characteristics; s4, carrying out cell community feature clustering, and representing a tumor microenvironment distribution mode of the patient; and S5, calculating the similarity of the tumor microenvironment distribution modes of the patients, and layering the patients. By means of the method, the patients can be layered, and prognosis of the patient groups has significant difference.

According to the screening method for the potential protein biomarkers and the drug targets of the gastric cancer, Mendel randomization analysis in a proteome range is adopted, the genetic causal relationship between circulating plasma protein and the risk of the gastric cancer is evaluated, and finally the remarkably related protein is identified. According to the screening method of the potential protein biomarker and the drug target of the gastric cancer, provided by the invention, the potential association between circulating plasma protein and the gastric cancer is systematically revealed by integrating Mendel randomization, single-cell RNA sequencing analysis, space transcriptome analysis, virtual drug screening, molecular docking, molecular dynamics simulation and other methods.

This disclosure pertains to compositions comprising an anti-FcRn antibody, M281. The compositions include the full, intact antibody and size variants thereof that not include two antibody heavy chains and to antibody light chains. Thus, a M281 pharmaceutical composition can include: an antibody comprising a heavy chain comprising the amino acid sequence of SEQ ID NO:2 and a light chain comprising the amino acid sequence of SEQ ID NO:1, wherein the composition comprises a major protein component having a molecular weight of 140,000-145,000 Da and a minor protein component of molecular weight 118,000-120,000 Da.

The presently described and claimed disclosure relates to capillary electrophoresis methods for quantifying an intact AAV genome and protein components in an AAV using the same capillary electrophoresis system. The claimed and described approach offers an automated analysis of AAV samples and provides information to determine the AAV empty / full ratio.

The invention belongs to the technical field of biological analysis, and particularly relates to a co-extraction method for mRNA and protein in a trace sample and application. The co-extraction method mainly comprises the following steps: capturing messenger RNA by adopting Oligo dT magnetic beads so as to separate the messenger RNA from protein, and then selecting a proteome pretreatment working process based on SP3 magnetic beads. According to the technology, Oligo dT magnetic beads are innovatively selected to separate messenger RNA. The surface of the Oligo dT magnetic bead is modified with an Oligo dT sequence, so that the Oligo dT magnetic bead can selectively capture mRNA. The mRNA separation and purification technology has the characteristics of high efficiency, high purity and simplicity and convenience in operation. The problems that mRNA and protein in a trace sample are difficult to separate, the RNA amount is small, follow-up analysis cannot be met, and the proteomics pretreatment process is low in efficiency can be solved.

The invention discloses a plasma proteome-based colorectal cancer precancerous lesion diagnosis model construction method, and aims to solve the problem that a current colorectal cancer diagnosis kit is insufficient in sensitivity and specificity when detecting an early stage (precancerous lesion / early cancer) through a proximity extension technology (PEA) and selecting a specific detection panel. Protein biomarkers in plasma samples of 80 patients with precancerous lesion (progression stage adenoma) and early cancer (Tis / T1 stage) in a discovery queue are identified. By adjusting potential clinical confounding factors, 15 key protein biomarkers are identified. In the discovery queue, four machine learning algorithms (Lasso regression, random forest, SVM and XGBoost) are adopted to diagnose early colorectal cancer lesions, and high diagnosis efficiency is realized through multiple machine learning algorithms. In a verification queue sample, the diagnosis model also shows an important diagnosis capability for patients with progression-stage adenoma or early-stage colorectal cancer, and has a potential clinical application value.

The present disclosure provides methods of identifying a disease-specific immunogenic peptide through a series of selection steps. Immunogenic epitopes identified by methods of the present disclosure are applicable for use in peptide-based immunotherapy, preferably cancer therapy. Furthermore, the methods of the present disclosure may be performed in a high-throughput manner and serve as a means of personalized vaccine development and therapy. Also provided are compositions of immunogenic peptides as well as methods of treatment comprising said compositions.

The present description provides methods, assays and reagents useful for sequencing proteins. Sequencing proteins in a broad sense involves observing the plausible identity and order of amino acids, which is useful for sequencing single polypeptide molecules or multiple molecules of a single polypeptide. In one aspect, the methods are useful for sequencing multiple polypeptides. The methods and reagents described herein can be useful for high resolution interrogation of the proteome and enabling ultrasensitive diagnostics critical for early detection of diseases.

The invention relates to the technical field of optics, and discloses a visualization method of a biological tissue three-dimensional full-information atlas, which comprises the following steps of: acquiring image data, electron microscope data, mechanical data, protein distribution, omics information and histological staining images of biological tissues by using various biological visualization technologies, and correspondingly processing the acquired data to obtain a three-dimensional full-information atlas of the biological tissues; finally, organization information fusion and digital display are achieved. According to the method, a cross-scale feature correlation algorithm framework is innovatively established, and multi-source heterogeneous data fusion is performed on medical image topological data (CT / MRI), ultrastructure scanning data (SEM / TEM), molecular positioning information (immunofluorescence, immunohistochemistry and enzyme immunoassay), omics maps (space transcriptome / proteome) and high-resolution tissue staining data. The data island dilemma caused by traditional single-mode analysis is broken through, and full-scale visualization from nanoscale molecular distribution to centimeter-level organ tissue structure-function relationship is realized for the first time.

A direct-read precision de novo sequencing method for amino acid sequences of proteins and proteome, the method involving determining the type of product ions on the basis of lysine (K) and arginine (R) dual mass-defect amino acid encoding (NeuCode) labeling, and performing paired mirror digestion to achieve the direct-read precision de novo sequencing of animo acid sequences of proteins with full product-ion coverage. A protein is labeled with K / R NeuCode amino acids, mirror peptide fragments are obtained by means of paired mirror digestion, and the mirror peptide fragments are subjected to tandem mass spectrometry analysis to obtain a mirror spectrum with full product-ion coverage and product ion type identification. Consequently, the amino acid sequence information in a secondary spectrum can be directly read on the basis of the mass difference of two adjacent product ions of the same type, thereby realizing direct reading and precision sequencing of the amino acid sequence of the protein.

Provided herein are compositions, systems, and methods for delivering an effector protein into a cell. The present disclosure, in some aspects, provide novel proteins delivering an effector protein into a cell. The novel proteins are supernegatively charged proteins derived from highly anionic proteins identified from the proteome (e.g., human proteome). The novel protein tags can be associated (e.g., covalently or nocovalently) with the protein to be delivered to facilitate delivery of the effector protein into a cell.

The present disclosure provides a single mouse exhaled breath collection device and proof- of-concept analyses utlizing an ultra- sensitive and customizable EV purification assay, EV- CATCHER® (Extracellular Vesicle Capture by AnTibody of CHoice and Enzymatic Release) assay. Preliminary studies show that this assay work well for the isolation of exhaled extracellular vesicles (exh-EVs) from exhaled breath condensates (EBC) to capture and characterize miRNAs contained in exh-EVs. Because assembling a large enough cohort of asymptomatic subjects requires time, a complementary approach of using humanized animal models has been chosen to comprehensively assess the robustness and sensitivity of transcriptomic (miRNA and mRNA) and proteomic biomarkers contained in tumor exh-EVs and to enable sensitive detection of human primary and secondary lung cancers during their early development. The results of preliminary analyses demonstrate that the purification of exh-EVs with EV-CATCHER® offers specificity and sensitivity, which will be critical for the targeted purification of tumor exh-EVs from the EBC of transgenic, orthotopic, and Patient-Derived Xenograft (PDX) animal models of human lung cancers.

A method for quantitatively analyzing polypeptides by integrating multiple liquid chromatography-mass spectrometry maps, and an application thereof, which belong to the cross technical field of analytical chemistry and computer science. The method comprises: using a liquid chromatography-mass spectrometry technique to analyze samples, so as to obtain multiple extracted ion flow chromatograms of secondary fragment ions; performing integration processing on multiple liquid chromatography-mass spectrometry maps, such that the original means of sequentially processing individual maps and then combining results is changed; by means of the consistency between multiple instances of analysis using the liquid chromatography-mass spectrometry technique in terms of the retention time, ion mass-to-charge ratio and relative strength of the same component, excluding inconsistent chromatographic peaks and secondary fragment ions among the multiple instances of analysis, such that the accuracy of quantitative chromatographic peaks and quantitative ions obtained by means of screening is improved; and using the quantitative chromatographic peaks and the quantitative ions obtained by means of screening to calculate the relative content of polypeptides between the samples, such that the quantitative accuracy of polypeptides and proteins is improved. The method can be applied to non-targeted proteome analysis of clinical samples and biological samples.

The invention relates to the field of gene engineering, in particular to a proximity marker enzyme mutant and application thereof. The proximity marker enzyme mutant takes ProtA-Turbo as a starting sequence, and one or more sites in K71, K240, K335, K345 and K351 are mutated into non-polar hydrophobic amino acid, polar neutral amino acid, acidic amino acid, basic amino acid or non-natural amino acid. The proximity marker enzyme mutant overcomes the influence of self biotinylation on the proximity marker activity, can continuously and stably mark the proximity proteome of the target protein on the immobilized cell, and obviously improves the sensitivity of identifying the proximity interacting protein of the target protein.

The present invention relates to the preparation and application of a micro-cell in-situ microreactor. By subjecting the inner wall of a capillary to silanization treatment and modifying epoxy groups on its surface through free radical polymerization reaction, an open-tubular capillary column is prepared. Then, polyethyleneimine and iodoacetic acid-N-succinimidyl ester are successively modified by covalent bonding to prepare a solid-phase alkylated capillary microreactor. The advantages of the present invention are that proteomic sample processing is carried out in-situ, which is conducive to reducing sample loss caused by multiple transfers during traditional sample processing. Therefore, this solid-phase alkylated open-tubular column is suitable for proteomic pretreatment of trace samples. In addition, this method is tolerant to various surfactants and strong lysis reagents and has good sample compatibility.

Kits and methods of using the kits for analyzing macromolecules, including peptides, polypeptides, and proteins, employing nucleic acid encoding are disclosed. The sample analysis kits employ nucleic acid encoding and / or nucleic acid recording of a molecular interaction and / or reaction, such as recognition events (e.g., between an antigen and an antibody, between a modified terminal amino acid residue, or between a small molecule or peptide therapeutic and a target, etc.). Additional barcoding reagents, such as those for cycle-specific barcoding (e.g., “clocking”), compartment barcoding, combinatorial barcoding, spatial barcoding, or any combination thereof, may be included in the kits. The sample may comprise macromolecules, including peptides, polypeptides, and proteins, and the recording may generate molecular interaction and / or reaction information, and / or polypeptide sequence information. The kits may be used in high-throughput, multiplexed, and / or automated analysis, and are suitable for analysis of a proteome or subset thereof.

The invention discloses a membrane-rupturing antibacterial peptide and application thereof. On the basis of an artificial intelligence screening method, a membrane-rupturing antibacterial peptide KLAKLLKLLLWAQNELDQKK is identified from a proteome of toads, the membrane-rupturing antibacterial peptide has three positive charges, and 50% of amino acid is hydrophobic amino acid. Through experimental tests, the antibacterial peptide can inhibit the growth of 10 different strains including gram negative strains and gram positive strains; meanwhile, the semi-maximum hemolysis concentration and the semi-maximum cytotoxicity concentration of the antibacterial peptide are both greater than 128 mu g / mL, and the antibacterial peptide has good biological safety. The antibacterial peptide plays an antibacterial role by destroying cell membranes, has the characteristic that the drug resistance of bacteria is not easily caused, and is an ideal development object of antibacterial drugs and antibacterial products such as disinfectants, detergents and feed additives.