22 results about "Microbial genome" patented technology

The invention discloses a small CRISPR (clustered regularly interspaced short palindromic repeats)-Cas gene editing system and application thereof. According to the invention, based on microbial genome and metagenome data, a class of CRISPR-Cas family protein is mined through a biological information method, and is named as Cas12r. A CRISPR-Cas12r editing tool constructed on the basis of the gene can realize gene editing in prokaryotic or eukaryotic cells. The CRISPR-Cas12r gene editing system obtained by the invention has the characteristics of miniaturization and various PAM types.

The invention belongs to the technical field of dynamic monitoring of oil production engineering, and particularly relates to a method for analyzing and identifying inter-well connectivity based on microbial genome DNA (Deoxyribose Nucleic Acid). Comprising the following steps: acquiring liquid samples of a producing well and a water injection well and rock debris samples of a new drilled well in the same area and the same stratum as the producing well; carrying out microbial genome DNA analysis on the obtained sample to obtain dominant strain compositions of the oil producing well, the water injection well and the newly-drilled well; comparing the number of the dominant strains shared by the producing well and the water injection well and the number of the dominant strains shared by the producing well and the new drilling well, and judging the connectivity of the producing well and the water injection well according to a comparison result. The invention provides a novel inter-well connectivity identification method, which can effectively solve the problems that the water breakthrough direction of an oil production well is complicated and is difficult to identify clearly due to the influence of dominant channels, natural fractures, water injection dynamic fractures and other factors on a water injection development oil reservoir.

The invention discloses a method and system for synchronously detecting host chromatin openness and in-vivo microbiome based on transposase, and belongs to the technical field of biological sequencing data analysis. According to the method, transposase is used for selectively fragmenting an open chromatin region of a host, and a microbial genome is almost randomly cut, so that synchronous enrichment of host and microbial DNA is realized; after high-throughput sequencing library construction and double-end sequencing, sequencing data is split into host source and non-host source reads through bioinformatics analysis, host chromatin state and microorganism composition are analyzed respectively, and a microorganism-host epigenetic regulation network is constructed; the invention further provides a matched DNA sequencing library and an analysis system, multi-scene research of infectious diseases, intestinal microecology, tumor microenvironment and the like is supported, a public database can be reanalyzed, and potential microbial interaction signals are mined. According to the method, the host-microorganism interaction research efficiency is remarkably improved, and a high-sensitivity and integrated technical scheme is provided for epigenetic regulation mechanism analysis.

The application discloses a gene editing system CRISPR-Cas12p and application thereof. Based on microbial genomes and metagenomic data, the CRISPR-Cas12p protein of the CRISPR-Cas protein family is obtained by preliminary screening by using a Prodigal gene prediction tool, a Pfam database and HMMER software, and a gene editing system CRISPR-Cas12p is constructed. PAM preference and interference function identification show that the editing system has a PAM preference of 5'-TTC-3', can effectively realize targeted cutting by using long transcripts and double RNA hybrid chain transcripts respectively, and can realize editing of a target gene in prokaryotic and eukaryotic cells. The CRISPR-Cas12p gene editing system obtained by the application has a small protein component, is beneficial to delivery, can realize gene editing in prokaryotic and eukaryotic cells, and has a wide application prospect.

The invention provides a method for batch detection of viruses in a single-cell microbial genome. According to the method, by constructing the comprehensive reference index and the independent reference index and combining the two-stage detection strategy, high-throughput, batch and automatic analysis is achieved, whether all viruses / plasmids in a database exist in a sample or not can be detected at the same time through one-time operation, correlation analysis with all strains is automatically completed, and the detection efficiency is greatly improved.

The application discloses a specific molecular marker screening method for microbial tracing, comprising the following steps: step one, microbial genome characteristic analysis; step two, specific candidate gene screening; step three, homologous arm design and target fragment amplification; step four, recombination plasmid construction; step five, positive control system establishment; step six, specificity verification; step seven, sensitivity detection; step eight, stability evaluation; step nine, marker practicability verification; and step ten, standardization and shaping; the unique gene fragment of the target microorganism is screened through whole genome alignment, and multiple verifications such as specificity, sensitivity, stability and practicability are combined, so that the screened molecular marker has high specificity, can effectively distinguish the target microorganism from the non-target microorganism close to the target microorganism, and cross reaction is avoided.

The invention provides a formula flora construction method and device, electronic equipment and a storage medium, and belongs to the field of bioinformatics, and the formula flora construction method comprises the following steps: converting a phylogenetic tree constructed by a microbial genome sequence into a weight matrix; performing center logarithm ratio transformation on the original abundance matrix and then inputting the original abundance matrix into an iterative random forest model; correcting the original feature importance into smooth feature importance by using the weight matrix so as to update the feature sampling weight of the next round; and when the model converges, extracting a high-order ecological interaction rule based on a decision path to output a candidate core flora, and further determining a target formula flora. The characteristics are smoothly corrected by introducing the phylogenetic relationship, so that the independence hypothesis of traditional abundance data is broken, the sparsity and false positive interference of high-dimensional sequencing data are effectively overcome, the evolution-driven real inter-species collaborative relationship is accurately captured and reserved, and the accuracy of the method is improved. Therefore, efficient steady-state colonization and precise targeted metabolic regulation of the formula flora in the host microenvironment are guaranteed.

This application provides a method and kit for detecting pathogenic microorganisms based on the properties of tetrastranded DNA oxidoreductase. The method utilizes isothermal amplification technology to amplify genomic fragments containing tetrastranded DNA / RNA sequences in the pathogenic microorganism genome, and then performs a colorimetric reaction by adding heme and oxidoreductase substrates, achieving rapid and visual detection of pathogenic microorganisms.

This application relates to a DNA construct for overexpressing a target gene in *Schizochytrium* microorganisms, and a method for expressing the target gene in *Schizochytrium* microorganisms using the construct. The DNA construct includes a 5' homologous arm and a 3' homologous arm capable of hybridizing to a high-expression site in the *Schizochytrium* microorganism genome.

The invention discloses endonuclease spCaslambda-2 with a wide target recognition range and application of the endonuclease spCaslambda-2. On the basis of metagenome data, through a bioinformatics method, endonuclease spCaslambda-2 is explored from an unknown microbial genome, and a crRNA sequence corresponding to the endonuclease spCaslambda-2 is identified. Compared with the known Caslambda enzyme, the spCaslambda-2 shows excellent cis and trans cleavage activity. The PAM sequence recognized by the enzyme is 5 '-YYR-3' (Y represents C or T, and R represents A or G), and can cover wider genome sites, so that the application potential of the Caslambda family in gene editing and detection is remarkably expanded.

This invention relates to a reagent combination, extraction kit, and extraction method for extracting microbial genomic DNA from soil, belonging to the field of biotechnology. The reagent combination for extracting microbial genomic DNA from soil of this invention includes individually packaged grinding beads I, grinding beads II, lysis buffer, inhibitor removal, binding buffer, magnetic beads, rinsing solution I, rinsing solution II, and elution buffer. In this invention, soil samples are ground and heated after adding grinding beads of two particle sizes and lysis buffer, which effectively lyses and releases nucleic acids from soil microorganisms. The inhibitor removal agent in this invention reduces the interaction between impurities in the sample and nucleic acids, and the flocculant in the inhibitor removal agent effectively settles impurities such as humic acid in the soil. The binding buffer in this invention promotes the binding of nucleic acid molecules to magnetic beads. The two rinsing solutions in this invention effectively remove impurities such as proteins and some small molecule compounds during the extraction process.

This application provides a method and system for constructing a metagenomic database of clinical pathogenic microorganisms. The method includes: collecting and correcting species information of pathogenic microorganisms; performing searches based on the corrected pathogenic microorganism genome results; filtering and counting bacterial genomes; screening and filtering reference genomes of viral pathogenic microorganisms; downloading the screened pathogenic microorganism genomes; breaking the genomes obtained from the above screening results into fixed-length fragments; classifying reads with overlapping regions to obtain contaminated regions in the genome; labeling contaminated sequences in all genomes; removing contaminated sequences from the genome; constructing an alignment database for the obtained genomes based on the k-mer algorithm and the lowest common ancestor algorithm; managing the database, regularly updating and maintaining the database; optimizing data storage by partitioning the database into different databases according to species boundaries and different setting criteria.

This invention discloses a probiotic screening method based on neural networks and metagenomic data, relating to the field of probiotic screening. It involves obtaining metagenomic sequencing data from NCBI, preprocessing the data, and dividing the processed sequence data into training, validation, and test sets. A deep learning model is constructed based on a Transformer architecture combined with a HyenaOperator hybrid mechanism to capture the internal dependencies of sequence fragments at different distances, performing pooling to obtain better sequence features. These features are then input into a multilayer perceptron (MLP) base model for dimensionality reduction, and the predicted probabilities are output using a softmax function. A voting mechanism is used to summarize and determine the predicted results of the sequence fragments. This invention employs the aforementioned probiotic screening method based on neural networks and metagenomic data, enabling efficient and accurate screening of potential probiotics in large-scale microbial genome data.

The invention discloses a multi-province high-temperature yeast traceability identification method by combining microbial community characteristics with a machine learning algorithm. The method comprises the following steps: S1, sample collection and pretreatment: collecting high-temperature yeast samples from white spirit production areas with different flavors for low-temperature storage; s2, microbial information acquisition: extracting microbial genome DNA in the sample, performing amplicon sequencing, acquiring gene sequence information of a microbial community, and analyzing community composition and relative abundance of bacteria and fungi to acquire a microbial characteristic value; s3, feature screening: sorting the microbial feature values by adopting a feature sorting algorithm, and screening out microbial markers with producing area specificity in combination with an interpretable machine learning technology; s4, construction of a discrimination model: constructing a production area discrimination model by adopting a neural network algorithm based on the microbial marker; and S5, producing area discrimination: inputting the microbial information of a high-temperature yeast sample to be discriminated into the producing area discrimination model, and outputting a producing area result corresponding to the sample. According to the method, the high-temperature yeast for making hard liquor in different producing areas can be accurately distinguished by screening out the microbial marker with producing area specificity.

The invention belongs to the technical field of biological medicines, and particularly relates to an oral microorganism model for predicting whether an esophageal cancer patient progresses six months after radiotherapy and application of the oral microorganism model. The invention provides an oral cavity microbial model for predicting whether an esophageal cancer patient progresses six months after radiotherapy, the oral cavity microbial model is composed of 13 microbial genes shown as SEQ ID NO: 1-13, and the microbial genes are enriched in the oral cavity of a human body. The microbial gene model disclosed by the invention realizes good distinguishing ability on whether the esophageal cancer patient develops six months after radiotherapy, and the feasibility, applicability and universality of the microbial gene distinguishing model in the esophageal cancer patient are proved.

The invention relates to direct cloning of a biosynthetic gene cluster, in particular to a direct cloning method and application of an ultra-large biosynthetic gene cluster, a microbial genome is extracted from a low-melting-point agarose gel block through combination, and the ultra-large gene cluster can be rapidly cloned in a targeted manner by utilizing the specific cutting characteristic of CRISPR / Cas and a saccharomyces cerevisiae TAR technology. According to the method, mechanical shearing can be avoided by extracting and treating the genome in the thallus embedding block, and the operation is simple, so that the integrity of an ultra-large target gene cluster can be maintained to the maximum extent, and particularly, the probability that rearrangement is extremely easy to occur in a yeast body due to excessive overlapped fragments can be reduced for (ultra)-large PKS / NRPS gene clusters. CRISPR / Cas mediated cleavage can occur at any DNA site, and a target gene cluster can be released in a most accurate and fastest manner, so that targeted cloning is not limited by restriction enzyme cleavage sites any more. The high efficiency of the TAR technology enables the target cloning of (ultra) large gene clusters to be simple and feasible.

The invention discloses an information encryption method and system based on strain genome coding and identification. The method comprises the following steps: extracting target gene sequence features from a strain genome database, including conservative marker gene sequences, necessary functional gene sequences and genome variation site distribution, and generating a strain specific key matrix; after to-be-encrypted information is converted into binary codes, a dynamic mapping rule is established according to the strain specificity key matrix, the binary codes are converted into quaternary pseudo-gene sequences, and strain identity identification codes are embedded into the quaternary pseudo-gene sequences; a hierarchical coding mechanism is adopted to allocate different security levels according to strain system development levels, and multi-level key management and authority control are achieved; inserting a strain specific marker sequence and an integrity check code into the pseudo-gene sequence to generate a final biological ciphertext; according to the method, high-security quantum resistant encryption is realized by utilizing natural diversity and randomness of microbial genomes.

The invention provides a pathogenic microorganism genome reference database and a construction method thereof, and particularly, the database construction method provided by the invention comprises the following steps: acquiring multi-source pathogen sequence data from a plurality of public databases and autonomous clinical data; performing cleaning and quality control on the data; based on the cleaned data, performing function-oriented redundancy elimination processing and standardized naming to obtain a standardized sequence data set; based on the standardized sequence data set, constructing a generic genome model, and establishing a hierarchical database according to the generic genome model; based on the hierarchical database, constructing a clinical priority-oriented query system; and automatically and dynamically updating the database. The pathogenic microorganism database provided by the invention is comprehensive in coverage, layered in structure and controllable in quality, and has good pathogen detection, classification, comparison, tracking and risk monitoring capabilities.

The invention belongs to the technical field of biological information, and particularly relates to a compost N2O emission path identification and environmental risk quantification method based on multiple omics. The method comprises the following steps: extracting and sequencing total DNA (Deoxyribonucleic Acid) and total RNA (Ribonucleic Acid) of a collected compost sample; by analyzing metagenome data, reconstructing an N2O-generated microbial genome and performing function annotation on the N2O-generated microbial genome; according to a functional gene set annotated by a genome, dividing four generation ways of nitrification, nitrifying bacteria denitrification, heterotrophic denitrification and reduction of dissimilatory nitrate into ammonium; and analyzing gene expression dynamics in the genome by combining with a metatranscriptome and carrying out risk quantification. Compared with targeted gene detection technologies such as PCR (polymerase chain reaction) and the like, the method has the advantages that the generation way and the emission potential of N2O in a composting system are accurately recognized by fusing the metagenome and the metatranscriptome, the limitation of a traditional method on the gene coverage degree is broken through, and the method has important application value on accurate management and control of organic solid waste engineering greenhouse gases.

The application provides a formula flora construction method and device, electronic equipment and storage medium, and belongs to the field of bioinformatics, and comprises the following steps: converting a phylogenetic tree constructed by a microbial genome sequence into a weight matrix; inputting a central logarithmic ratio transformed original abundance matrix into an iterative random forest model; correcting the original feature importance to smooth feature importance by using the weight matrix to update the feature sampling weight in the next round; and extracting high-order ecological interaction rules based on the decision path when the model converges to output a candidate core flora, and then determining a target formula flora. The application breaks the independence assumption of traditional abundance data by introducing phylogenetic relationships to smooth correct features, effectively overcomes the sparsity of high-dimensional sequencing data and false positive interference, accurately captures and retains the real interspecies synergistic relationship driven by evolution, and thus guarantees the efficient and stable colonization and precise targeted metabolic regulation of the formula flora in the host microenvironment.

The application provides a method for batch detection of viruses in single-cell microbial genomes. The method realizes high-throughput, batch and automatic analysis by constructing a comprehensive reference index, an independent reference index and combining a two-stage detection strategy, can simultaneously detect whether all viruses / plasmids in the database exist in the sample in one run, and automatically completes the correlation analysis with all strains, greatly improving the detection efficiency.

A method for determining a level of one or more live microbes in a sample of a Cannabis plant includes (a) introducing a DNase enzyme into a sample including (i) Cannabis plant matrix derived from lysed cells of a Cannabis plant and (ii) live microbial cells including microbial genomic DNA, (b) introducing an anionic detergent into the sample, where the anionic detergent is in an amount effective to inactivate the DNase enzyme in the sample and lyse the live microbial cells in the sample, (c) introducing a known quantity of control DNA into the sample, (d) contacting the sample with a plurality of polynucleotide capture agents, (e) isolating the plurality of polynucleotide capture agents, thereby isolating polynucleotides from the microbial genomic DNA and / or control DNA in the sample, and (f) amplifying at least a portion of polynucleotides from the microbial genomic DNA isolated in step (e).