{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T08:42:45Z","timestamp":1772268165214,"version":"3.50.1"},"reference-count":43,"publisher":"PeerJ","license":[{"start":{"date-parts":[[2021,9,2]],"date-time":"2021-09-02T00:00:00Z","timestamp":1630540800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/publicdomain\/zero\/1.0\/"}],"funder":[{"name":"Armed Forces Health Surveillance Division, Global Emerging Infections Surveillance (GEIS) Branch","award":["ProMIS ID 17_KY_1.3.8 (2017\/2019)"],"award-info":[{"award-number":["ProMIS ID 17_KY_1.3.8 (2017\/2019)"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"\n Background<\/jats:title>\n There is a global increase in reports of emerging diseases, some of which have emerged as spillover events from wild animals. The spleen is a major phagocytic organ and can therefore be probed for systemic microbiome. This study assessed bacterial diversity in the spleen of wild caught small mammals so as to evaluate their utility as surveillance tools for monitoring bacteria in an ecosystem shared with humans.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n \n Fifty-four small mammals (rodents and shrews) were trapped from different sites in Marigat, Baringo County, Kenya. To characterize their bacteriome, DNA was extracted from their spleens and the V3\u2013V4 regions of the 16S rRNA amplified and then sequenced on Illumina MiSeq. A non-target control sample was used to track laboratory contaminants. Sequence data was analyzed with Mothur v1.35, and taxomy determined using the SILVA database. The Shannon diversity index was used to estimate bacterial diversity in each animal and then aggregated to genus level before computing the means. Animal species within the rodents and shrews were identified by amplification of mitochondrial cytochrome b (\n cytb<\/jats:italic>\n ) gene followed by Sanger sequencing. CLC workbench was used to assemble the\n cytb<\/jats:italic>\n gene sequences, after which their phylogenetic placements were determined by querying them against the GenBank nucleotide database.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n cytb<\/jats:italic>\n gene sequences were generated for 49\/54 mammalian samples: 38 rodents (\n Rodentia)<\/jats:italic>\n and 11 shrews (Eulipotyphyla). Within the order Rodentia, 21 Acomys, eight Mastomys, six Arvicanthis and three Rattus were identified. In the order Eulipotyphyla, 11 Crucidura were identified. Bacteria characterization revealed 17 phyla that grouped into 182 genera. Of the phyla, Proteobacteria was the most abundant (67.9%). Other phyla included Actinobacteria (16.5%), Firmicutes (5.5%), Chlamydiae (3.8%), Chloroflexi (2.6%) and Bacteroidetes (1.3%) among others. Of the potentially pathogenic bacteria,\n Bartonella<\/jats:italic>\n was the most abundant (45.6%), followed by\n Anaplasma<\/jats:italic>\n (8.0%),\n Methylobacterium<\/jats:italic>\n (3.5%),\n Delftia<\/jats:italic>\n (3.8%),\n Coxiella<\/jats:italic>\n (2.6%),\n Bradyrhizobium<\/jats:italic>\n (1.6%) and\n Acinetobacter<\/jats:italic>\n (1.1%). Other less abundant (<1%) and potentially pathogenic included\n Ehrlichia<\/jats:italic>\n ,\n Rickettsia<\/jats:italic>\n ,\n Leptospira<\/jats:italic>\n ,\n Borrelia<\/jats:italic>\n ,\n Brucella<\/jats:italic>\n ,\n Chlamydia<\/jats:italic>\n and\n Streptococcus<\/jats:italic>\n . By Shannon diversity index,\n Acomys<\/jats:italic>\n spleens carried more diverse bacteria (mean Shannon diversity index of 2.86,\n p<\/jats:italic>\n \u00a0=\u00a00.008) compared to 1.77 for\n Crocidura<\/jats:italic>\n , 1.44 for\n Rattus<\/jats:italic>\n , 1.40 for\n Arvicathis<\/jats:italic>\n and 0.60 for\n Mastomys<\/jats:italic>\n .\n <\/jats:p>\n <\/jats:sec>\n \n Conclusion<\/jats:title>\n This study examined systemic bacteria that are filtered by the spleen and the findings underscore the utility of 16S rRNA deep sequencing in characterizing complex microbiota that are potentially relevant to one health issues. An inherent problem with the V3-V4 region of 16S rRNA is the inability to classify bacteria reliably beyond the genera. Future studies should utilize the newer long read methods of 16S rRNA analysis that can delimit the species composition.<\/jats:p>\n <\/jats:sec>","DOI":"10.7717\/peerj.12067","type":"journal-article","created":{"date-parts":[[2021,9,2]],"date-time":"2021-09-02T05:24:25Z","timestamp":1630560265000},"page":"e12067","source":"Crossref","is-referenced-by-count":4,"title":["The spleen bacteriome of wild rodents and shrews from Marigat, Baringo County, Kenya"],"prefix":"10.7717","volume":"9","author":[{"given":"Rehema","family":"Liyai","sequence":"first","affiliation":[{"name":"Department of Zoology, Maseno University College, Kisumu, Kenya"},{"name":"Basic Science Laboratory, United States Army Medical Research Directorate-Africa, Kisumu, Kenya"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gathii","family":"Kimita","sequence":"additional","affiliation":[{"name":"Basic Science Laboratory, United States Army Medical Research Directorate-Africa, Kisumu, Kenya"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Clement","family":"Masakhwe","sequence":"additional","affiliation":[{"name":"Basic Science Laboratory, United States Army Medical Research Directorate-Africa, Kisumu, Kenya"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Abuom","sequence":"additional","affiliation":[{"name":"Entomology Section, United States Medical Research Directorate-Africa, Kisumu, Kenya"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Beth","family":"Mutai","sequence":"additional","affiliation":[{"name":"Basic Science Laboratory, United States Army Medical Research Directorate-Africa, Kisumu, Kenya"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David Miruka","family":"Onyango","sequence":"additional","affiliation":[{"name":"Department of Zoology, Maseno University College, Kisumu, 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