Science

Colorectal cancer

There are 1.4 million people in the US with a history of colorectal cancer (CRC). Although the mortality rate has declined in recent decades, incidence rates are expected to rise due to the aging population and increasing occurrence of CRC in younger individuals. Cancerous or precancerous cells in the colon form lesions which are typically detected via colonoscopy, but the technique is invasive, expensive, and only 39% of patients return for subsequent screening. There is a need for improved non-invasive screening methods. We are using an innovative source to detect CRC: the human microbiome. Human microbiome can directly contribute to the development of CRC. We try to identify microbial biomarkers associated with CRC and to develop computational models that improve the non-invasive detection of CRC.

  1. Armour CR, Topcuoglu BD, Garretto A, Schloss PD. 2022. A Goldilocks Principle for the Gut Microbiome: Taxonomic Resolution Matters for Microbiome-Based Classification of Colorectal Cancer. mBio. 13: e03161-21. DOI: 10.1128/mbio.03161-21.
  2. Topçuoğlu BD, Lesniak NA, Ruffin MT IV, Wiens J, Schloss PD. 2020. Effective application of machine learning to microbiome-based classification problems. mBio. 11: 1-13. DOI: 10.1128/mBio.00434-20.
  3. Yu AI, Zhao L, Eaton KA, Ho S, Chen J, Poe S, Becker J, Gonzalez A, McKinstry D, Hasso M, Mendoza-Castrejon J, Whitfield J, Koumpouras C, Schloss PD, Martens EC, and Chen GY. 2020. Gut microbiota modulate CD8 T cell responses to influence colitis-associated tumorigenesis. Cell Reports. 31: 107471. DOI: 10.1016/j.celrep.2020.03.035.
  4. Sze MA, Topçuoğlu BD, Lesniak NA, IV Ruffin MT, Schloss PD. 2019. Fecal short-chain fatty acids are not predictive of colonic tumor status and cannot be predicted based on bacterial community structure. mBio. 10: e01454-19. DOI: 10.1128/mBio.01454-19.
  5. Flynn KJ, Ruffin MT IV, Turgeon DK, Schloss PD. 2018. Spatial variation of the native colon microbiota in healthy adults. Cancer Prev Res (Phila). 11: 393-401. DOI: 10.1158/1940-6207.CAPR-17-0370.

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Clostridium difficile Infection

Clostridium difficile infection (CDI) following therapeutic antibiotic treatment represents a considerable threat to human health, each year causing as many as half a million infections, 29,000 deaths, and a healthcare burden of $4.8 million. CDI can cause severe abdominal pain and diarrhea, and can develop the life-threatening conditions, which it accomplishes through secretion of protein toxins. Infections in healthy individuals are uncommon, as the combination of the innate immune system and gut microbiome prevent colonization under ordinary circumstances. However, disruption of the native gut bacterial communities during antibiotic therapy, often for unrelated illness, provides opportunity for C. difficile to establish infection. Subsequent treatment of CDI with antibiotics is typically effective, but recurrence of disease is common and may be increasing in prevalence. This, in combination with increased prevalence of infection, the emergence of more virulent forms of the pathogen, and the ever-present threat of antibiotic resistance highlight the need to better understand the mechanisms by which the gut immune system and the resident microbiota prevent initial colonization and subsequent recurrence by C. difficile. We use a combination of 16S rRNA gene sequencing, metagenomics, metatranscriptomics, and metabolomics in a mouse model for CDI and in infected patients to identify microbial functions that are important for colonization resistance and clearance of C. difficile.

  1. Leslie JL, Jenior ML, Vendrov KC, Standke AK, Barron MR, O’Brien TJ, Unverdorben L, Thaprawat P, Bergin IL, Schloss PD, Young VB. 2021. Protection from lethal Clostridioides difficile infection via intraspecies competition for co-germinant. mBio. 12: e00522-21. DOI: 10.1128/mBio.00522-21.
  2. Lesniak NA, Schubert AM, Sinani H, Schloss PD. 2021. Clearance of Clostridioides difficile colonization is associated with antibiotic-specific bacterial changes. mSphere. 6: e01238-20. DOI: 10.1128/mSphere.01238-20.
  3. Tomkovich S, Taylor A, King J, Colovas J, Bishop L, McBride K, Royzenblat S, Lesniak NA, Bergin IL, Schloss PD. 2021. An osmotic laxative renders mice susceptible to prolonged Clostridioides difficile colonization and hinders clearance. mSphere. 6: e00629-21. DOI: 10.1128/mSphere.00629-21.
  4. Stough JMA, Beaudoin AJ, Schloss PD. 2020. Coding-complete RNA virus genomes assembled from murine cecal metatranscriptomes. Microbiology Resource Announcements. 9: e00018-20. DOI: 10.1128/MRA.00018-20.
  5. Tomkovich S, Stough JMA, Bishop L, Schloss PD. 2020. The initial gut microbiota and response to antibiotic perturbation influence Clostridioides difficile colonization in mice. mSphere. 5: e00869-20. DOI: 10.1128/mSphere.00869-20.

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Bioinformatic tool development

The ability to generate data that describes the microbial world continues to grow rapidly. This requires that we develop and assess computational tools that allow us to synthesize these data to tell robust and compelling stories that solve important problems. We have been at the fore front of efforts to develop tools that are widely used by microbial ecologists for the past 15 years. Our tools have facilitated the analysis of 16S rRNA gene, metagenomic, and metatranscriptomic sequence data, metabolomics data, and clinical data.

Take a look at our software for links to documentation and other information, and check out our papers below:

  1. Lapp Z, Sovacool KL, Lesniak N, King D, Barnier C, Flickinger M, Krüger J, Armour CR, Lapp MM, Tallant J, Diao R, Oneka M, Tomkovich S, Moltzau Anderson J, Lucas SK, Schloss PD. 2022. Developing and deploying an integrated workshop curriculum teaching computational skills for reproducible research. The Journal of Open Science Education. DOI: 10.21105/jose.00144.
  2. Schloss PD. 2021. Preprint: Removal of rare amplicon sequence variants from 16S rRNA gene sequence surveys biases the interpretation of community structure data. DOI: 10.1101/2020.12.11.422279.
  3. Schloss PD. 2021. Amplicon sequence variants artificially split bacterial genomes into separate clusters. mSphere. 6: e0019121. DOI: 10.1128/mSphere.00191-21.
  4. Sovacool KL, Westcott SL, Mumphrey MB, Dotson GA, Schloss PD. 2021. Preprint: OptiFit: an improved method for fitting amplicon sequences to existing OTUs. DOI: 10.1101/2021.11.09.468000.
  5. Topçuoğlu BD, Lapp Z, Sovacool KL, Snitkin E, Wiens J, Schloss PD. 2021. mikropml: User-Friendly R Package for Supervised Machine Learning Pipelines. Journal of Open Source Software. 6: 3073. DOI: 10.21105/joss.03073.

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General microbiome research

We take an expansive approach to defining microbiomes. If it’s a community of microorganisms - bacteria, archaea, microeukaryotes, viruses - and it interacts with a biotic or abiotic environment, then it’s a microbiome. Although most of our ongoing work focuses on microbiomes associated with human or murine hosts, we have also studied microbiomes in hydrothermal vents, insects, sand dunes, soil, and more! We have also developed laboratory approaches to improve our ability to study these microbiomes.

  1. Mirzayi C, Renson A, Furlanello C, Sansone S, Zohra F, Elsafoury S, Geistlinger L, Kasselman LJ, Eckenrode K, van de Wijgert J, Loughman A, Marques FZ, MacIntyre DA, Arumugam M, Azhar R, Beghini F, Bergstrom K, Bhatt A, Bisanz JE, Braun J, Bravo H, Buck GA, Bushman F, Casero D, Clarke G, Collado M, Cotter PD, Cryan JF, Demmer RT, Devkota S, Elinav E, Escobar JS, Fettweis J, Finn RD, Fodor AA, Forslund S, Franke A, Furlanello C, Gilbert J, Grice E, Haibe-Kains B, Handley S, Herd P, Holmes S, Jacobs JP, Karstens L, Knight R, Knights D, Koren O, Kwon DS, Langille M, Lindsay B, McGovern D, McHardy AC, McWeeney S, Mueller NT, Nezi L, Olm M, Palm N, Pasolli E, Raes J, Redinbo MR, Rühlemann M, Sartor BR, Schloss PD, Schriml L, Segal E, Shardell M, Sharpton T, Smirnova E, Sokol H, Sonnenburg JL, Srinivasan S, Thingholm LB, Turnbaugh PJ, Upadhyay V, Walls RL, Wilmes P, Yamada T, Zeller G, Zhang M, Zhao N, Zhao L, Bao W, Culhane A, Devanarayan V, Dopazo J, Fan X, Fischer M, Jones W, Kusko R, Mason CE, Mercer TR, Sansone S, Scherer A, Shi L, Thakkar S, Tong W, Wolfinger R, Hunter C, Segata N, Huttenhower C, Dowd JB, Jones HE, Waldron L, Genomic Standards Consortium, Massive Analysis and Quality Control Society. 2021. Reporting guidelines for human microbiome research: the STORMS checklist. Nature Medicine. DOI: 10.1038/s41591-021-01552-x.
  2. Widder S, Zhao J, Carmody LA, Zhang Q, Kalikin LM, Schloss PD, LiPuma JJ. 2021. Association of bacterial community types, functional microbial processes and lung disease in cystic fibrosis airways. The ISME Journal. DOI: 10.1038/s41396-021-01129-z.
  3. Baxter NT, Lesniak NA, Sinani H, Schloss PD, Koropatkin NM. 2019. The glucoamylase inhibitor acarbose has a diet-dependent and reversible effect on the murine gut microbiome. mSphere. 4: e00528-18. DOI: 10.1128/mSphere.00528-18.
  4. Sze MA, Schloss PD. 2019. The impact of DNA polymerase and number of rounds of amplification in PCR on 16S rRNA gene sequence data. mSphere. 4: e00163-19. DOI: 10.1128/mSphere.00163-19.
  5. Doherty MD, Ding T, Koumpouras C, Telesco SE, Monast C, Das A, Brodmerkel C, Schloss PD. 2018. Fecal microbiota signatures are associated with response to Ustekinumab therapy among Crohn’s Disease patients. mBio. 9: e02120-17. DOI: 10.1128/mBio.02120-17.

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Scientific culture

How we do science and who does it is as important as what we are sciencing. Our research group has been very interested in reproducibility, publishing, and open access. We try to lead by example without drawing much attention to how we are doing it. Sometimes, it’s important to be more vocal about what we think is important.

  1. Hagan AK, Lesniak NA, Balunas MJ, Bishop L, Close WL, Doherty MD, Elmore AG, Flynn KJ, Hannigan GK, Koumpouras CC, Jenior ML, Kozik AJ, McBride K, Rifkin SB, Stough JMA, Sovacool KL, Sze MA, Tomkovich S, Topçuoğlu BD, Schloss PD. 2020. Ten simple rules to increase computational skills among biologists with Code Clubs. PLOS Computational Biology. 16: e1008119. DOI: 10.1371/journal.pcbi.1008119.
  2. Hagan AK, Topçuoğlu BD, Gregory ME, Barton HA, Schloss PD. 2020. Women Are Underrepresented and Receive Differential Outcomes at ASM Journals: a Six-Year Retrospective Analysis. mBio. 11: e01680-20. DOI: 10.1128/mBio.01680-20.
  3. Heise M, Dermody TS, Casadevall A, Sandri-Goldin RM, Schloss PD. 2020. The Decision to Publish Gutierrez-Alvarez et al., "Middle East Respiratory Syndrome Coronavirus Gene 5 Modulates Pathogenesis in Mice". Journal of Virology. DOI: 10.1128/JVI.02118-20.
  4. Schloss PD, Junior M, Alvania R, Arias CA, Baumler A, Casadevall A, Detweiler C, Drake H, Gilbert J, Imperiale MJ, Lovett S, Maloy S, McAdam AJ, Newton ILG, Sadowsky MJ, Sandri-Goldin RM, Silhavy TJ, Tontonoz P, Young J-AH, Cameron CE, Cann I, Fuller AO, Kozik AJ. 2020. The ASM Journals Committee values the contributions of Black microbiologists. mBio. 11: e01998-20 (simultaneously published in all ASM journals). DOI: 10.1128/mBio.01998-20.
  5. Amann RI, Baichoo S, Blencowe BJ, Bork P, Borodovsky M, Brooksbank C, Chain PSG, Colwell RR, Daffonchio DG, Danchin A, de Lorenzo V, Dorrestein PC, Finn RD, Fraser CM, Gilbert JA, Hallam SJ, Hugenholtz P, Ioannidis JPA, Jansson JK, Kim JF, Klenk HP, Klotz MG, Knight R, Konstantinidis KT, Kyrpides NC, Mason CE, McHardy AC, Meyer F, Ouzounis CA, Patrinos AAN, Podar M, Pollard KS, Ravel J, Muñoz AR, Roberts RJ, Rosselló-Móra R, Sansone SA, Schloss PD, Schriml LM, Setubal JC, Sorek R, Stevens RL, Tiedje JM, Turjanski A, Tyson GW, Ussery DW, Weinstock GM, White O, Whitman WB, Xenarios I. 2019. Toward unrestricted use of public genomic data. Science. 363: 350-352. DOI: 10.1126/science.aaw1280.

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