Animal models are essential in understanding of the mechanisms of sepsis moreover the development and the assessment of emerging therapies. In clinically relevant porcine model, however, a significant variability in the host response has been observed among animals. Thus, there is a strong demand to better understand the potential sources of this heterogeneity. In this study, we compared faecal microbiome composition of 12 animals. Three samples were collected at different time points from each animal. Bacteriome was subjected to 16S rDNA profiling. A significant difference in bacterial composition was associated with the season (p < 0.001) but not with the sex of the pig (p = 0.28), the timing of sample collection (p = 0.59), or interactions thereof (all p > 0.3). The season batch explained 55% of the total variance in the bacteriome diversity. The season term was highly significant from the high-resolution level of the bacterial amplicon sequencing variants up to the level of phylum. The diversity of the microbiome composition could significantly influence experimental model of sepsis, and studies are warranted to demonstrate the effects of gut microbiome diversity on the host-response. If confirmed, control of the gut microbiome should become a standard part of the pre-clinical sepsis experiments.

Biomedical Center Faculty Medicine in Pilsen Charles University alej Svobody 76 323 00 Pilsen Czech Republic

Department of Internal Medicine Faculty Medicine in Pilsen Charles University Pilsen Czech Republic

Department of Microbiology Faculty Medicine in Pilsen Charles University Pilsen Czech Republic

Department of Paediatrics 2nd Faculty of Medicine Charles University and University Hospital Motol Prague Czech Republic

Department of Physiology Faculty Medicine in Pilsen Charles University Pilsen Czech Republic

Department of Stomatology Faculty Medicine in Pilsen Charles University Pilsen Czech Republic

Zobrazit více v PubMed

Singer M. The new sepsis consensus definitions (Sepsis-3): The good, the not-so-bad, and the actually-quite-pretty. Intensive Care Med. 2016;42:2027–2029. doi: 10.1007/s00134-016-4600-4. PubMed DOI

Fleischmann C, Thomas-Rueddel DO, Hartmann M, Hartog CS, Welte T, Heublein S, Dennler U, Reinhart K. Hospital incidence and mortality rates of sepsis. Dtsch. Arztebl. Int. 2016;113:159–166. PubMed PMC

Iba T, Connors JM, Nagaoka I, Levy JH. Recent advances in the research and management of sepsis-associated DIC. Int. J. Hematol. 2021;2:1–10. PubMed PMC

Lonsdale DO, Shah RV, Lipman J. Infection, sepsis and the inflammatory response: Mechanisms and therapy. Front. Med. 2020;7:588863. doi: 10.3389/fmed.2020.588863. PubMed DOI PMC

Patel A, Nunnally ME. The septic patient. Anesthesiol. Clin. 2020;38:889–899. doi: 10.1016/j.anclin.2020.08.004. PubMed DOI

Cavaillon JM, Singer M, Skirecki T. Sepsis therapies: Learning from 30 years of failure of translational research to propose new leads. EMBO Mol. Med. 2020;12:e10128. doi: 10.15252/emmm.201810128. PubMed DOI PMC

Goldfarb RD, Dellinger RP, Parrillo JE. Porcine models of severe sepsis: Emphasis on porcine peritonitis. Shock. 2005;24:75–81. doi: 10.1097/01.shk.0000191337.01036.b7. PubMed DOI

Sartelli M, Catena F, Di Saverio S, Ansaloni L, Malangoni M, Moore EE, Moore FA, Ivatury R, Coimbra R, Leppaniemi A, Biffl W, Kluger Y, Fraga GP, Ordonez CA, Marwah A, Gerych I, Lee JG, Tranà C, Coccolini F, Corradetti F, Kirkby-Bott J. Current concept of abdominal sepsis: WSES position paper. World J. Emerg. Surg. 2014;9:22. doi: 10.1186/1749-7922-9-22. PubMed DOI PMC

Kazarian KK, Perdue PW, Lynch W, Dziki A, Nevola J, Lee CH, Hayward I, Williams T, Law WR. Porcine peritoneal sepsis: Modeling for clinical relevance. Shock. 1994;1:201–212. doi: 10.1097/00024382-199403000-00008. PubMed DOI

Deusch S, Tilocca B, Camarinha-Silva A, Seifert J. News in livestock research—Use of Omics-technologies to study the microbiota in gastrointestinal tract of farm animals. Comput. Struct. Biotechnol. J. 2014;13:55–63. doi: 10.1016/j.csbj.2014.12.005. PubMed DOI PMC

Jeon J, Lourenco J, Kaiser EE, Waters ES, Scheulin KM, Fang X, Kinder HA, Platt SR, Rothrock MJ, Jr, Callaway TR, West FD, Park HJ. Dynamic changes in the gut microbiome at the acute stage of ischemic stroke in a pig model. Front. Neurosci. 2020;14:587986. doi: 10.3389/fnins.2020.587986. PubMed DOI PMC

Jarkovska D, Markova M, Horak J, Nalos L, Benes J, Al-Obeidallah M, Tuma Z, Sviglerova J, Kuncova J, Matejovic M, Stengl M. Cellular mechanisms of myocardial depression in porcine septic shock. Front. Physiol. 2018;12:726. doi: 10.3389/fphys.2018.00726. PubMed DOI PMC

Kozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl. Environ. Microbiol. 2013;79:5112–5120. doi: 10.1128/AEM.01043-13. PubMed DOI PMC

Pal N, Bender JS, Opriessnig T. Rapid detection and differentiation of Erysipelothrix spp. By a novel multiplex real-time PCR assay. J. Appl. Microbiol. 2010;108:1083–1093. doi: 10.1111/j.1365-2672.2009.04560.x. PubMed DOI

De Puysseleyr K, De Puysseleyr L, Geldhof J, Cox E, Vanrompay D. Development and validation of a real-time PCR for Chlamydia suis diagnosis in swine and humans. PLoS ONE. 2014;9:e96704. doi: 10.1371/journal.pone.0096704. PubMed DOI PMC

Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJ, Holmes SP. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods. 2016;13:581–583. doi: 10.1038/nmeth.3869. PubMed DOI PMC

Callahan BJ, Sankaran K, Fukuyama JA, McMurdie PJ, Holmes SP. Bioconductor Workflow for Microbiome Data Analysis: From raw reads to community analyses. F1000Research. 2016;5:1492. doi: 10.12688/f1000research.8986.2. PubMed DOI PMC

Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 2013;41:D590–596. doi: 10.1093/nar/gks1219. PubMed DOI PMC

Dhariwal A, Chong J, Habib S, King I, Agellon LB, Xia J. MicrobiomeAnalyst—A web-based tool for comprehensive statistical, visual and meta-analysis of microbiome data. Nucleic Acids Res. 2017;45:W180–188. doi: 10.1093/nar/gkx295. PubMed DOI PMC

Oksanen, J., Blanchet F.G., Kindt R., Legendre P., Minchin P.R., O’Hara R.B., Simpson G.L., Solymos P., Stevens M.H.H., Szoecs E., Wagner H. Package ‘Vegan’ Community ecology package, version (2020), p. 2. (2020).

McMurdie PJ, Holmes S. phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE. 2013;8:e61217. doi: 10.1371/journal.pone.0061217. PubMed DOI PMC

Looft T, Allen HK, Cantarel BL, Levine UY, Bayles DO, Alt DP, Henrissat B, Stanton TB. Bacteria, phages and pigs: The effects of in-feed antibiotics on the microbiome at different gut locations. ISME J. 2014;8:1566–1576. doi: 10.1038/ismej.2014.12. PubMed DOI PMC

Xiang Z, Zhu H, Yang B, Fan H, Guo J, Liu J, Kong Q, Teng Q, Shang H, Su L, Qin C. A glance at the gut microbiota of five experimental animal species through fecal samples. Sci. Rep. 2020;10:16628. doi: 10.1038/s41598-020-73985-2. PubMed DOI PMC

Park I, Lee JH, Jang D-H, Kim D, Chang H, Kwon H, Kim S, Kim TS, Jo YH. Characterization of fecal peritonitis-induced sepsis in a porcine model. J. Surg. Res. 2019;244:492–501. doi: 10.1016/j.jss.2019.06.094. PubMed DOI

Horak J, Nalos L, Martinkova V, Tegl V, Vistejnova L, Kuncova J, Kohoutova M, Jarkovska D, Dolejsova M, Benes J, Stengl M, Matejovic M. Evaluation of mesenchymal stem cell therapy for sepsis: A randomized controlled porcine study. Front. Immunol. 2020;11:126. doi: 10.3389/fimmu.2020.00126. PubMed DOI PMC

Kohoutova M, Horak J, Jarkovska D, Martinkova V, Tegl V, Nalos L, Vistejnova L, Benes J, Sviglerova J, Kuncova J, Matejovic M, Stengl M. Vagus nerve stimulation attenuates multiple organ dysfunction in resuscitated porcine progressive sepsis. Crit. Care Med. 2019;47:e461–e469. doi: 10.1097/CCM.0000000000003714. PubMed DOI

Koulaouzidis A, Bhat S, Saeed AA. Spontaneous bacterial peritonitis. World J. Gastroenterol. 2009;15:1042–1049. doi: 10.3748/wjg.15.1042. PubMed DOI PMC

Modeling sepsis, with a special focus on large animal models of porcine peritonitis and bacteremia