{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T09:45:56Z","timestamp":1753868756703,"version":"3.41.2"},"reference-count":41,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T00:00:00Z","timestamp":1743033600000},"content-version":"vor","delay-in-days":26,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Current Protocols"],"published-print":{"date-parts":[[2025,3]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Antibiotics are frequently used in food production animals to control disease and improve productivity, but this promotes the development of antimicrobial resistance (AMR) and subsequent broader spread of AMR bacteria throughout food chain, endangering the well\u2010being and health of both animals and humans. In humans, the gut microbiome harbors a diverse range of AMR bacteria, known as the resistome. To effectively mitigate AMR in food animals requires first determining the expression and abundance of AMR\u2010related genes in the gut resistome. Currently, such knowledge in regard to food animals is largely lacking. Gut tissue RNA sequencing (GTRS) can capture metabolically active transcripts from both the host and the microbes attached to the gut epithelium. Ideally, AMR genes can be quantified using GTRS data, making it possible to study the relationship between host and microbe. For the majority of these GTRS studies, only host transcriptome changes have been reported, while the microbial AMR remains largely unexamined, mainly due to the lack of easily implementable bioinformatics tools. Here we present a straightforward workflow to accomplish that using common command\u2010line bioinformatics tools. With this pipeline, the host is considered noise, and host data are filtered out from the microbial reads. Transcript quantification of the AMR genes is then performed. The pipeline then continues through AMR transcript quantification, differential gene expression, and SNP analysis. Using open\u2010source tools, we made this analytical pipeline easy to implement and able to generate results ready to be incorporated into publishable reports. Published 2025. This article is a U.S. Government work and is in the public domain in the USA.<\/jats:p><jats:p><jats:bold>Basic Protocol<\/jats:bold>: Running the gene quantification pipeline<\/jats:p><jats:p><jats:bold>Support Protocol 1<\/jats:bold>: Downloading FASTQ files from the NCBI database<\/jats:p><jats:p><jats:bold>Support Protocol 2<\/jats:bold>: Building a genome reference index of the host<\/jats:p><jats:p><jats:bold>Support Protocol 3<\/jats:bold>: Differential gene expression analysis<\/jats:p><jats:p><jats:bold>Support Protocol 4<\/jats:bold>: Single\u2010nucleotide polymorphism (SNP) analysis<\/jats:p>","DOI":"10.1002\/cpz1.70116","type":"journal-article","created":{"date-parts":[[2025,3,30]],"date-time":"2025-03-30T03:15:41Z","timestamp":1743304541000},"source":"Crossref","is-referenced-by-count":0,"title":["Pipeline for Antimicrobial Resistance Gene Quantification from Host Tissue"],"prefix":"10.1002","volume":"5","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2016-9519","authenticated-orcid":false,"given":"Levi M.","family":"Svaren","sequence":"first","affiliation":[{"name":"USDA Agricultural Research Service  Madison Wisconsin"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenli","family":"Li","sequence":"additional","affiliation":[{"name":"USDA Agricultural Research Service  Madison Wisconsin"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,3,27]]},"reference":[{"volume-title":"The Java programming language","year":"2005","author":"Arnold K.","key":"e_1_2_10_2_1_1"},{"key":"e_1_2_10_2_2_1","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkac1047"},{"key":"e_1_2_10_2_3_1","doi-asserted-by":"publisher","DOI":"10.1093\/gigascience\/giab008"},{"key":"e_1_2_10_2_4_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bts635"},{"key":"e_1_2_10_2_5_1","doi-asserted-by":"publisher","DOI":"10.1002\/0471250953.bi1114s51"},{"key":"e_1_2_10_2_6_1","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.1923"},{"key":"e_1_2_10_2_7_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btr509"},{"key":"e_1_2_10_2_8_1","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1303.3997"},{"key":"e_1_2_10_2_9_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598\u2010018\u201037033\u20104"},{"key":"e_1_2_10_2_10_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13059\u2010014\u20100550\u20108"},{"key":"e_1_2_10_2_11_1","unstructured":"National Center for Biotechnology Information. (2023).SRA Toolkit. Retrieved fromhttps:\/\/trace.ncbi.nlm.nih.gov\/Traces\/sra\/sra.cgi?view=software"},{"key":"e_1_2_10_2_12_1","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.4197"},{"volume-title":"R: A language and environment for statistical computing","year":"2021","author":"R Core Team","key":"e_1_2_10_2_13_1"},{"key":"e_1_2_10_2_14_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12864\u2010017\u20103611\u20106"},{"key":"e_1_2_10_2_15_1","doi-asserted-by":"publisher","DOI":"10.1042\/BCJ20160510"},{"key":"e_1_2_10_2_16_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btp120"},{"key":"e_1_2_10_2_17_1","doi-asserted-by":"publisher","DOI":"10.1038\/nprot.2012.016"},{"key":"e_1_2_10_3_2_1","unstructured":"https:\/\/github.com\/lmsvaren\/AMR_pipeline_protocols"},{"key":"e_1_2_10_3_3_1","unstructured":"GitHub containing all files needed to run these protocols. You will need to maintain the folder structure of AMR_pipeline to ensure all scripts run."},{"key":"e_1_2_10_3_4_1","unstructured":"https:\/\/slurm.schedmd.com\/pdfs\/summary.pdf"},{"key":"e_1_2_10_3_5_1","unstructured":"SchedMD Slurm summary which provides descriptions for basic Slurm flags and commands."},{"key":"e_1_2_10_3_6_1","unstructured":"https:\/\/mally.stanford.edu\/~sr\/computing\/basic\u2010unix.html"},{"key":"e_1_2_10_3_7_1","unstructured":"Web page provided by Stanford with detailed explanations for basic UNIX commands."},{"key":"e_1_2_10_3_8_1","unstructured":"https:\/\/www.geeksforgeeks.org\/linux\u2010commands\u2010cheat\u2010sheet\/"},{"key":"e_1_2_10_3_9_1","unstructured":"Article providing an in\u2010depth list of UNIX commands sorted by function with command options and examples."},{"key":"e_1_2_10_3_10_1","unstructured":"https:\/\/web.stanford.edu\/class\/cs107\/resources\/vim"},{"key":"e_1_2_10_3_11_1","unstructured":"Page providing quick Vim editor commands and explanations covering the common navigation and editing commands."},{"key":"e_1_2_10_3_12_1","unstructured":"https:\/\/www.cs.cmu.edu\/~15131\/f17\/topics\/vim\/vim\u2010cheatsheet.pdf"},{"key":"e_1_2_10_3_13_1","unstructured":"Vim cheat sheet providing a more extensive list of commands available in Vim."},{"key":"e_1_2_10_3_14_1","unstructured":"https:\/\/www.ncbi.xyz\/Traces\/study\/"},{"key":"e_1_2_10_3_15_1","unstructured":"The SRA Run Selector provided by NCBI. Support Protocol1outlines the process of downloading file samples from here using the SRA Toolkit. Published data can be found using project or sample accession codes."},{"key":"e_1_2_10_3_16_1","unstructured":"https:\/\/www.ncbi.nlm.nih.gov\/datasets\/genome\/"},{"key":"e_1_2_10_3_17_1","unstructured":"The genome look\u2010up page on NCBI. Genomes can be found using assembly name accession code or taxonomic name. The Basic Protocol here describes how to use this search to find the correct reference genome. Reference genomes are marked by a white checkmark in a green shape."},{"key":"e_1_2_10_3_18_1","unstructured":"https:\/\/www.htslib.org\/doc\/samtools.html"},{"key":"e_1_2_10_3_19_1","unstructured":"User manual for SAMtools; can be used to look up all samtools commands and see examples of how to use them."},{"key":"e_1_2_10_3_20_1","unstructured":"https:\/\/samtools.github.io\/bcftools\/bcftools.html"},{"key":"e_1_2_10_3_21_1","unstructured":"User manual for BCFtools providing details about the available commands and flag options."},{"key":"e_1_2_10_3_22_1","unstructured":"https:\/\/salmon.readthedocs.io\/en\/latest\/salmon.html#using\u2010salmon"},{"key":"e_1_2_10_3_23_1","unstructured":"Different use cases for salmon are provided here. This protocol specifically uses salmon quant. This command and others are explained in detail in the documentation."},{"key":"e_1_2_10_3_24_1","unstructured":"https:\/\/physiology.med.cornell.edu\/faculty\/skrabanek\/lab\/angsd\/lecture_notes\/STARmanual.pdf"},{"key":"e_1_2_10_3_25_1","unstructured":"The STAR manual for v2.7.0a. Although the protocols presented here use v2.7.10b there is very little difference between those two versions and this manual remains current as of the time of publication. Chapters 1 and 2 cover what was used in this protocol and provide details on the parameters used."}],"container-title":["Current Protocols"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/currentprotocols.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/cpz1.70116","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,2]],"date-time":"2025-05-02T13:10:17Z","timestamp":1746191417000},"score":1,"resource":{"primary":{"URL":"https:\/\/currentprotocols.onlinelibrary.wiley.com\/doi\/10.1002\/cpz1.70116"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3]]},"references-count":41,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,3]]}},"alternative-id":["10.1002\/cpz1.70116"],"URL":"https:\/\/doi.org\/10.1002\/cpz1.70116","archive":["Portico"],"relation":{},"ISSN":["2691-1299","2691-1299"],"issn-type":[{"type":"print","value":"2691-1299"},{"type":"electronic","value":"2691-1299"}],"subject":[],"published":{"date-parts":[[2025,3]]},"article-number":"e70116"}}