Editing Antimicrobial resistance (section)

=== Computational community surveillance ===
One of the key tools identified by the WHO and others for the fight against rising antimicrobial resistance is improved surveillance of the spread and movement of AMR genes through different communities and regions. Recent advances in high-throughput [[DNA sequencing]] as a result of the [[Human Genome Project]] have resulted in the ability to determine the individual microbial genes in a sample.<ref name="Kim_2021">{{cite journal | vauthors = Kim DW, Cha CJ | title = Antibiotic resistome from the One-Health perspective: understanding and controlling antimicrobial resistance transmission | journal = Experimental & Molecular Medicine | volume = 53 | issue = 3 | pages = 301–309 | date = March 2021 | pmid = 33642573 | pmc = 8080597 | doi = 10.1038/s12276-021-00569-z }}</ref> Along with the availability of databases of known antimicrobial resistance genes, such as the Comprehensive Antimicrobial Resistance Database (CARD)<ref>{{cite journal | vauthors = Alcock BP, Huynh W, Chalil R, Smith KW, Raphenya AR, Wlodarski MA, Edalatmand A, Petkau A, Syed SA, Tsang KK, Baker SJ, Dave M, McCarthy MC, Mukiri KM, Nasir JA, Golbon B, Imtiaz H, Jiang X, Kaur K, Kwong M, Liang ZC, Niu KC, Shan P, Yang JY, Gray KL, Hoad GR, Jia B, Bhando T, Carfrae LA, Farha MA, French S, Gordzevich R, Rachwalski K, Tu MM, Bordeleau E, Dooley D, Griffiths E, Zubyk HL, Brown ED, Maguire F, Beiko RG, Hsiao WW, Brinkman FS, Van Domselaar G, McArthur AG | title = CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database | journal = Nucleic Acids Research | volume = 51 | issue = D1 | pages = D690–D699 | date = January 2023 | pmid = 36263822 | pmc = 9825576 | doi = 10.1093/nar/gkac920 }}</ref><ref>{{cite web |title=The Comprehensive Antibiotic Resistance Database |url=https://card.mcmaster.ca/ |access-date=2023-03-28 |website=card.mcmaster.ca |archive-date=28 March 2023 |archive-url=https://web.archive.org/web/20230328115250/https://card.mcmaster.ca/ |url-status=live }}</ref> and [[ResFinder]],<ref>{{cite journal | vauthors = Florensa AF, Kaas RS, Clausen PT, Aytan-Aktug D, Aarestrup FM | title = ResFinder – an open online resource for identification of antimicrobial resistance genes in next-generation sequencing data and prediction of phenotypes from genotypes | journal = Microbial Genomics | volume = 8 | issue = 1 | date = January 2022 | pmid = 35072601 | pmc = 8914360 | doi = 10.1099/mgen.0.000748 | doi-access = free }}</ref><ref>{{cite web |title=ResFinder 4.1 |url=https://cge.food.dtu.dk/services/ResFinder/ |access-date=2023-03-28 |website=cge.food.dtu.dk |archive-date=28 March 2023 |archive-url=https://web.archive.org/web/20230328115302/https://cge.food.dtu.dk/services/ResFinder/ |url-status=live }}</ref> this allows the identification of all the antimicrobial resistance genes within the sample – the so-called "[[resistome]]". In doing so, a profile of these genes within a community or environment can be determined, providing insights into how antimicrobial resistance is spreading through a population and allowing for the identification of resistance that is of concern.<ref name="Kim_2021" />