# US 10,762,982 B1 · System and method for nucleotide analysis > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,762,982 B1 - Document ID: US10762982B1 - Status: Granted - Kind: B1 - Application number: 15/288,731 - Filed: 2016-10-07 - Granted: 2020-09-01 - Earliest claimed: 2015-10-07 - Assignees: Trace Genomics, Inc. - Applicants: Trace Genomics, Inc. - Inventors: Diane Wu; Poornima Parameswaran - Web page: https://patentgrep.com/patent/US10762982B1 ## CPC - G16B 40/00: ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding - G16B 40/20: Supervised data analysis - G06N 3/08: Learning methods - G06N 3/09: Supervised learning - G06N 20/00: Machine learning - G16B 25/00: ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression - G16B 30/00: ICT specially adapted for sequence analysis involving nucleotides or amino acids - G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems - Y02A 90/10: Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation - G16B: BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA - Y02A: TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE ## Abstract A system and method for the detection of pathogens and other microbes using nucleotide analysis is described. Aligned and unaligned nucleotide sequences are utilized to predict the presence or absence of pathogens and other microbes. ## Claims ### Claim 1 A nucleotide sampling system comprising: a non-transitory computer-readable storage medium storing instructions, the instructions when executed by one or more processors cause the one or more processors to: receive a digitized sample based on soil of a farm, the digitized sample including a plurality of sequences of nucleic acids of a plurality of microbes present in the soil, wherein an identity of each of the plurality of microbes is not yet known; determine that a subset of the plurality of sequences includes sequences of nucleotides that align at least in part to nucleotides of one or more known nucleic acid sequences of known microbes; determine that a remaining subset of the plurality of sequences includes unaligned sequences, the unaligned sequences aligning to less than a threshold number of nucleotides of known nucleic acid sequences; determine a likelihood that at least one of the plurality of microbes is present in the soil based at least in part on the unaligned sequences; and determine a crop stress indicative of a pathogenic state of the soil according to the at least one of the plurality of microbes. ### Claim 2 (depends on 1) The nucleotide sampling system of claim 1, wherein determining the likelihood that at least one of the plurality of microbes is present is further based on one or more aligned sequences of nucleotides in the digitized sample. ### Claim 3 (depends on 1) The nucleotide sampling system of claim 1, wherein determining the likelihood that at least one of the plurality of microbes is present is further based on metadata associated with the digitized sample. ### Claim 4 (depends on 1) The nucleotide sampling system of claim 1, wherein the non-transitory computer-readable storage medium stores additional instructions that when executed by the one or more processors cause the one or more processors to determine a predicted risk of microbe presence based on the likelihood that at least one of the plurality of microbes is present. ### Claim 5 (depends on 1) The nucleotide sampling system of claim 1, wherein the at least one of the plurality of microbes is an indicator of a disease. ### Claim 6 (depends on 1) The nucleotide sampling system of claim 1, wherein the non-transitory computer-readable storage medium stores additional instructions that when executed by the one or more processors cause the one or more processors to receive metadata associated with the farm, the metadata including one or more of operation data about the farm, location data, and use data. ### Claim 7 (depends on 6) The nucleotide sampling system of claim 6, wherein the metadata associated with the farm includes one or more of: a length of time in operation, source of seeds for the farm, other farms utilizing the seeds, latitude and longitude, climate, weather patterns, sources of water, fertilizer use, and pesticide use. ### Claim 8 (depends on 1) The nucleotide sampling system of claim 1, wherein the non-transitory computer-readable storage medium stores additional instructions that when executed by the one or more processors cause the one or more processors to provide information about planting and timing data associated with the soil of the farm. ### Claim 9 A method comprising: receiving a digitized sample based on soil of a farm, the digitized sample including a plurality of sequences of nucleic acids of a plurality of microbes present in the soil, wherein an identity of each of the plurality of microbes is not yet known; determining that a subset of the plurality of sequences includes sequences of nucleotides that align at least in part to nucleotides of one or more known nucleic acid sequences of known microbes; determining that a remaining subset of the plurality of sequences includes unaligned sequences, the unaligned sequences aligning to less than a threshold number of nucleotides of known nucleic acid sequences; determining a likelihood that at least one of the plurality of microbes is present in the soil based at least in part on the unaligned sequences; and determining a crop stress indicative of a pathogenic state of the soil according to the at least one of the plurality of microbes. ### Claim 10 (depends on 9) The method of claim 9, further comprising: predicting one or more traits of the digitized sample based at least in part on the unaligned sequences nucleotides; and determining, based on the one or more traits of the digitized sample, nucleic acids that are causal markers for a disease, modulators of the disease, or beneficial nucleic acids that are suppressors of the disease. ### Claim 11 (depends on 9) The method of claim 9, further comprising: receiving metadata about a location associated with the digitized sample, wherein determining the likelihood is further based on the metadata. ### Claim 12 (depends on 9) The method of claim 9, further comprising: providing a predicted risk for one or more pathogens in the soil, the predicted risk determined based on the likelihood. ### Claim 13 (depends on 9) The method of claim 9, further comprising: treating the soil of the farm with fertilizer, pesticide, or water based on the likelihood that the at least one of the plurality of microbes is present in the soil. ### Claim 14 (depends on 9) The method of claim 9, further comprising: receiving a sample of the soil of the farm; and generating the digitized sample by sequencing the sample. ### Claim 15 (depends on 14) The method of claim 14, further comprising: extracting deoxyribonucleic acid from the sample of the soil; and performing PCR to amplify the deoxyribonucleic acid, wherein the amplified deoxyribonucleic acid is sequenced to generate the digitized sample. ### Claim 16 (depends on 9) The method of claim 9, further comprising: providing, for display on a user interface of a client device, a report based on the likelihood that the at least one of the plurality of microbes is present in the soil.