{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T12:24:22Z","timestamp":1791980662066,"version":"4.4.0"},"reference-count":80,"publisher":"National Academy of Sciences","issue":"13","license":[{"start":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T00:00:00Z","timestamp":1774396800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["www.pnas.org"],"crossmark-restriction":true},"short-container-title":["Proc. Natl. Acad. Sci. U.S.A."],"published-print":{"date-parts":[[2026,3,31]]},"abstract":"<jats:p>\n                    The US broiler production system processes over 9.3 billion chickens annually through a highly integrated pyramid structure where two primary breeding companies supply genetic stock to approximately 40 major integrators operating nationwide. To provide a quantitative, system-wide estimate of contamination origins, I analyzed whole-genome sequences from\n                    <jats:italic toggle=\"yes\">\n                      <jats:italic toggle=\"yes\">Salmonella<\/jats:italic>\n                    <\/jats:italic>\n                    and\n                    <jats:italic toggle=\"yes\">\n                      <jats:italic toggle=\"yes\">Campylobacter<\/jats:italic>\n                    <\/jats:italic>\n                    isolates collected from over 800 processing facilities as part of the United States Department of Agriculture\u2019s Food Safety Inspection Service verification sampling (2019-2025). Single-linkage clustering identified isolates sharing common origins (\u22642, 4, or 8 SNPs genome-wide), which were categorized by processing complex, company, and geographical distributions to infer contamination sources. Among the isolates analyzed, 78% of\n                    <jats:italic toggle=\"yes\">\n                      <jats:italic toggle=\"yes\">Campylobacter<\/jats:italic>\n                    <\/jats:italic>\n                    , 77% of non-Enteritidis\n                    <jats:italic toggle=\"yes\">\n                      <jats:italic toggle=\"yes\">Salmonella<\/jats:italic>\n                    <\/jats:italic>\n                    , and 96% of\n                    <jats:italic toggle=\"yes\">\n                      <jats:italic toggle=\"yes\">Salmonella<\/jats:italic>\n                    <\/jats:italic>\n                    Enteritidis belonged to clusters spanning multiple companies and geographic regions\u2014a pattern consistent with primary breeder origin. The geographic spread of Enteritidis isolates within clusters matched a random model, and cluster populations showed temporal turnover yet spatial synchrony\u2014patterns explicable only by contamination from the apex of the breeding pyramid.\n                    <jats:italic toggle=\"yes\">\n                      <jats:italic toggle=\"yes\">Campylobacter<\/jats:italic>\n                    <\/jats:italic>\n                    showed regional clustering implying sources at lower levels of the breeding pyramid. Cluster persistence exceeded multiple production cycles (median &gt;4 y for\n                    <jats:italic toggle=\"yes\">\n                      <jats:italic toggle=\"yes\">Campylobacter<\/jats:italic>\n                    <\/jats:italic>\n                    , &gt;4.5 y for 75% of Enteritidis isolates), indicating stable contamination reservoirs upstream of processing. These results demonstrate that the primary breeders are a major source of broiler contamination and suggest that upstream interventions targeting breeding stock, in particular for Enteritidis, may represent an efficient strategy for further reducing clinical cases of foodborne illness.\n                  <\/jats:p>","DOI":"10.1073\/pnas.2536554123","type":"journal-article","created":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T18:07:16Z","timestamp":1774462036000},"update-policy":"https:\/\/doi.org\/10.1073\/pnas.cm10313","source":"Crossref","is-referenced-by-count":2,"title":["Genomic epidemiology of\n                    <i>Salmonella<\/i>\n                    and\n                    <i>Campylobacter<\/i>\n                    in poultry production: Quantifying the contribution of primary breeders"],"prefix":"10.1073","volume":"123","author":[{"given":"David J.","family":"Lipman","sequence":"first","affiliation":[{"name":"Department of Pathology, Stanford University School of Medicine","place":["Stanford"]},{"name":"Department of Biomedical Engineering, Johns Hopkins University","place":["Baltimore"]},{"name":"Department of Computer Science, Center for Computational Biology, Johns Hopkins University","place":["Baltimore"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"341","published-online":{"date-parts":[[2026,3,25]]},"reference":[{"key":"e_1_3_4_1_2","unstructured":"CDC Foodborne illness source attribution estimates\u2013United States 2022 [Internet]. 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