2021 – Poster Session

Presenter Name	Poster Title
Emma Accorsi	Determinants of Staphylococcus aureus carriage in the developing infant nasal microbiomeEmma K. Accorsi, Eric A. Franzosa, Tiffany Hsu, Regina Joice Cordy, Ayala Maayan-Metzger, Hanaa Jaber, Aylana Reiss-Mandel, Casey DuLong, Marc Lipsitch, Gili Regev-Yochay, Curtis Huttenhower
Abigail Armstrong	Saliva microbiome collection and processing methodsAbigail JS Armstrong, Veenat Parmar, Martin J Blaser
Ye-Ji Bang	Microbiota-induced vitamin A mobilization by serum amyloid A and its role in intestinal immunityYe-Ji Bang, Zehan Hu, Yun Li, Sureka Gattu, Kelly A. Ruhn, Joachim Herz, and Lora V. Hooper
Amrisha Bhosle	Prioritization and Annotation of Novel Bioactive Small Molecules from the MicrobiomeAmrisha Bhosle, Sena Bae, Yancong Zhang, Eunyong Chun, Julian Avila-Pacheco, Ludwig Geistlinger, Levi Waldron, Clary Clish, Ramnik Xavier, Hera Vlamakis, Eric A. Franzosa, Wendy S. Garrett, Curtis Huttenhower
Marissa Bivins	Discovery of the Gut Microbial Enzymes that Drive the Dose-Limiting Toxicity of the Immunosuppressant Mycophenolate MofetilMarissa M. Bivins, Lindsay E. Bass, Amanda L. Graboski, Michelle E. Fiamingo, Rebecca L. Johnson, Joshua B. Simpson,William G. Walton, Nathan I. Nicely, John R. Lee, Matthew R. Redinbo
Asker Brejnrod	Discovering antibiotics by integrating microbiome and metabolome data via high dimensional mediation analysisBrejnrod A, Qing Fang, Manimozhiyan Arumugam, Pieter Dorrestein
Matthew Brock	16S sequencing on pediatric blood detects DNA signatures of commensals and pathogenic microbes that correlate with clinical featuresMatthew Brock, Bo Zhang, Patricia Pichilingue-Reto, Carlos Arana, Lora Hooper, Nicolai S.C. van Oers and Prithvi Raj
Andrew Brooks	Pre-symptomatic detection of COVID-19 from smartwatch dataTejaswini Mishra*, Meng Wang*, Ahmed A Metwally*, Gireesh K Bogu*, Andrew W Brooks*, Amir Bahmani*, Arash Alavi*, Alessandra Celli, Emily Higgs, Orit Dagan-Rosenfeld, Bethany Fay, Susan Kirkpatrick, Ryan Kellogg, Michelle Gibson, Tao Wang, Erika M Hunting, Petra Mamic, Ariel B Ganz, Benjamin Rolnik, Xiao Li**, Michael P Snyder**
Jennifer Dawkins	Gut metabolites predict Clostridioides difficile recurrenceJennifer J. Dawkins, Jessica R. Allegretti, Travis E. Gibson, Lynn Bry, Georg K. Gerber
Anders Dohlman	The Cancer Microbiome Atlas (TCMA): A Resource for Querying Host-Microbe InteractionsAnders B. Dohlman, Diana Arguijo, Shengli Ding, Michael Gao, Holly Dressman, Iliyan D. Iliev, Steven M. Lipkin, Xiling Shen
Eric Franzosa	Integrating taxonomic, functional, and strain profiling of microbial communities with bioBakery 3F. Beghini, L.J. McIver, A. Blanco-Míguez, L. Dubois, F. Asnicar, S. Maharjan, A. Mailyan, A.M. Thomas,P. Manghi, M. Valles-Colomer, G. Weingart, Y. Zhang, M. Zolfo, C. Huttenhower, E.A. Franzosa, N. Segata
Leah Froehle	CD8+ T Cells Mediate Colon Epithelial Cell Death in an Organoid Model of HIV PathogenesisUpasana Das Adhikari, Leah M. Froehle, Alice H. Linder, Muntsa Rocafort Junca, Mark S. Ladinsky, and Douglas S. Kwon
Andrew Ghazi	High-sensitivity pattern discovery in large, paired multi-omic datasets with HAllAAndrew R. Ghazi, Kathleen Sucipto, Gholamali Rahnavard, Eric A. Franzosa, Lauren J. McIver, Jason Lloyd- Price, Emma Schwager, George Weingart, Yo Sup Moon, Xochitl C. Morgan, Levi Waldron, Curtis Huttenhower
Isabella Goodchild-Michelman	Reconstruction of metagenome-scale models of the gut microbiota metabolism at species-level resolution in Inflammatory Bowel DiseaseIsabella M. Goodchild-Michelman, Analeigha V. Colarusso, Ali R. Zomorrodi
Danting Jiang	Uncovering the role of gut microbiota in HIV acquisition and vaccine response in infant monkeysDanting Jiang and Neil Surana
Shelley Kalaora	Identification of microbial-derived HLA-bound peptides in melanomaShelly Kalaora, Adi Nagler, Deborah Nejman, Michal Alon, Chaya Barbolin, Eilon Barnea, Steven L. C. Ketelaars, Kuoyuan Cheng, Kevin Vervier, Noam Shental, Yuval Bussi, Ron Rotkopf, Ronen Levy, Gil Benedek, Sophie Trabish, Tali Dadosh, Smadar Levin-Zaidman, Leore T. Geller, Kun Wang, Polina Greenberg, Gal Yagel, Aviyah Peri, Garold Fuks, Neerupma Bhardwaj, Alexandre Reuben, Leandro Hermida, Sarah B. Johnson, Jessica R. Galloway-Peña, William C. Shropshire, Chantale Bernatchez, Cara Haymaker, Reetakshi Arora, Lior Roitman, Raya Eilam, Adina Weinberger, Maya Lotan-Pompan, Michal Lotem, Arie Admon, Yishai Levin, Trevor D. Lawley, David J. Adams, Mitchell P. Levesque, Michal J. Besser, Jacob Schachter, Ofra Golani, Eran Segal, Naama Geva-Zatorsky, Eytan Ruppin, Pia Kvistborg, Scott N. Peterson, Jennifer A. Wargo, Ravid Straussman & Yardena Samuels
Maddy Kline	Characterization of a novel microbiome marker anti-correlated with Staphylococcus aureus carriage in the infant nasal microbiomeMadeleine C. Kline, Emma K. Accorsi, Eric A. Franzosa, Curtis Huttenhower
Peter Larson	Instability, Heterogeneity, and Pathogenicity Reservoirs in the Skin, Oral, and Gut Microbiota of Older AdultsPeter Larson, George Kuchel MD, James Grady PhD, Julie Robison PhD, Julia Oh PhD
Giovana Leite	Probiotic Supplementation and Marathon Runners: there are any effect up to Gut Microbiota and neutrophil function?Geovana S F Leite, Ayane S Resende, Edgar Tavares, Helena A P Batatinha, Ricardo A Fock, José C R Neto, Ronaldo V T dos Santos, Antonio H Lancha Junior
Chengchen Li	The Microbiome Collection Core at the Harvard T.H. Chan School of Public Health (HCMCC)Chengchen Li, Jeremy E. Wilkinson, Curtis Huttenhower
Venkata Suhas Maranganti	A Fast and Accurate Machine Learning of Human Interpretable Rules Predicting Host Status from Microbiome DynamicsVenkata Suhas Maringanti, Vanni Bucci, Georg K. Gerber
Yuka Moroishi	Infant Gut Microbiome and Infections and Symptoms: A Prospective Cohort StudyYuka Moroishi, Jiang Gui, Anne G. Hoen, Hilary G. Morrison, Emily R. Baker, Kari Nadeau,Hongzhe Li, Zhigang Li, Juliette Madan, Margaret R. Karagas
Quang Nguyen	cILR: Taxonomic Enrichment Analysis with Isometric Log RatiosQuang Nguyen, Anne G. Hoen, H. Robert Frost
Emese O’Donnell	Intestinal inflammation leads to changes in the blood PBMC and plasma microbiomeEmese Prandovszky O’Donnell, Hua Liu, Emily G. Severance, Faith Dickerson, Robert H. Yolken
Daniel Radford-Smith	Maternal probiotic intake during obesity ameliorates depressive-like behaviour and alters the gut-brain axis in adult offspringRadford-Smith DE., Probert F., Burnet PWJ. & Anthony DC.
Meghan Short	Power and sample size calculation for microbiome epidemiologyMeghan I. Short, Emma Schwager, Siyuan Ma, Lauren McIver, Jeremy E. Wilkinson, Eric A. Franzosa, Curtis Huttenhower
Apollo Stacy	Infection trains the host for microbiota-enhanced resistance to pathogensApollo Stacy, Vinicius Andrade-Oliveira, John A. McCulloch, Benedikt Hild, Ji Hoon Oh, P. Juliana Perez-Chaparro, Choon K. Sim, Ai Ing Lim, Verena M. Link, Michel Enamorado, Giorgio Trinchieri, Julia A. Segre, Barbara Rehermann, Yasmine Belkaid
Jotham Suez	Probiotics alter the antibiotic resistance gene reservoir along the human GI tractEmmanuel Montassier, Rafael Valdés-Mas, Eric Batard, Niv Zmora, Mally Dori-Bachash, Jotham Suez, Eran Elinav
Edgar Tavares-Silva	Probiotic Supplementation Increase Monocyte’s Function and Maintain Gut Microbiota Alpha Diversity of Marathon RunnersEdgar Tavares-Silva, Geovana S F Leite, Helena A P Batatinha, Ayane S Resende, Antônio H Lancha Junior, José C R Neto, Ronaldo V Thomatieli-Santos.
Kelsey Thompson	The gut microbiome in juvenile idiopathic arthritisKelsey N Thompson, Kevin S Bonham,Elizabeth C Rosser, Emma Robinson, Emma Jordan, Fatema Jeralii, Hannah Peckham, Nicholas E Ilott, Lilian H Lam, Paula Colmenero, Sam J Bullers, the Inflammatory Arthritis Microbiome Consortium, Coziana Ciurtin, Lucy R Wedderburn, Fiona Powrie, and Curtis Huttenhower
Liisa Veerus	Evolutionary Implications of Reproductive Tract Microbiota in the Polygynandrous Red Junglefowl (Gallus gallus)Liisa Veerus, Allison M. Roth, Yunke Wang, Shorok B. Mombrikotb, Emma Ransome, Rosie Eccleston, Thomas Bell, Tommaso Pizzari
Aaron Walsh	The role of host genetics in the development of the infant gut microbiomeAaron M. Walsh, Tommi Vatanen, George Weingart, Mondher Khidiri, Kendra Vehik, Eric A. Franzosa, and Curtis Huttenhower
Kai Wang	The modulating role of the gut microbiome in body weight responses to physical activityK. Wang, W. Ma, LH. Nguyen, D. Wang, RS. Mehta, D. Hang, L. Al-Shaar, CH. Pernar, CH. Lo, B. Fu, S. Ogino, EB. Rimm, FB. Hu, WS. Garrett, Q. Sun, AT. Chan, C. Huttenhower, M. Song
Ya Lea Wang	Characterizing microbial community viability with RNA-based high-throughput sequencingYa Wang,Yan Yan, Kelsey N. Thompson, Sena Bae, Jiaxian Shen,Hera Vlamakis, Erica M. Hartman, Curtis Huttenhower
Jeremy Wilkinson	The Harvard T.H. Chan School of Public Health Microbiome Analysis CoreJeremy E. Wilkinson, Lauren J. McIver, Chengchen Li, Thomas M. Kuntz, Curtis Huttenhower
Yan Yan	Identifying strain-specific functional genes in colorectal cancerYan Yan, Andrew M. Thomas, Kelsey N. Thompson, Paolo Manghi, Lauren J. Mciver, Eric A. Franzosa, Nicola Segata, Andrew T. Chan, Wendy S. Garrett, Curtis Huttenhower
Yue Sandra Yin	Deletion of innate effector serum amyloid A alters gut microbiome and drives metabolism in miceYue Sandra Yin, Laura J. den Hartigh, Xue-Song Zhang, Shari Wang, Zhan Gao, Abigail Armstrong, Jincheng Wang, Maria Gloria Dominguez-Bello, Martin J. Blaser
Caroline Young	The colorectal cancer-associated microbiome
Lufei Young	A cross-link between dietary sodium, gut microbiome, and heart failureYue Sandra Yin, Laura J. den Hartigh, Xue-Song Zhang, Shari Wang, Zhan Gao, Abigail Armstrong, Jincheng Wang, Maria Gloria Dominguez-Bello, Martin J. Blaser
Yancong Zhang	Identifying Novel Bioactive Microbial Gene Products in Inflammatory Bowel DiseaseYancong Zhang, Amrisha Bhosle, Sena Bae, Lauren J. Mclver, Emma Accorsi, Kelsey N. Thompson, Cesar Arze, Ya Wang, Ayshwarya Subramanian, Damian R. Plichita, Ali Rahnavard, Afrah Shafquat , Ramnik J. Xavier, Hera Vlamakis, Wendy S. Garrett, Andy Krueger , Curtis Huttenhower, Eric A. Franzosa

Determinants of Staphylococcus aureus carriage in the developing infant nasal microbiome

Presented by: Emma Accorsi

Staphylococcus aureus is a leading cause of healthcare- and community-associated infections and can be difficult to treat due to antimicrobial resistance. About 30% of individuals carry S. aureus asymptomatically in their nares, a risk factor for later infection, and interactions with other species in the nasal microbiome likely modulate its carriage. It is thus important to identify ecological or functional genetic elements within the maternal or infant nasal microbiomes that influence S. aureus acquisition and retention in early life. We recruited 36 mother-infant pairs and profiled a subset of monthly longitudinal nasal samples from the first year after birth using shotgun metagenomic sequencing. The infant nasal microbiome is highly variable, weakly influenced by maternal nasal microbiome composition, and primarily shaped by developmental and external factors, such as daycare. Infants display distinctive patterns of S. aureus carriage, positively associated with Acinetobacter species, Streptococcus parasanguinis, Streptococcus salivarius, and Veillonella species and inversely associated with maternal Dolosigranulum pigrum. In gene-content based strain profiling, infant S. aureus strains are more similar to maternal strains. Mothers may represent a sporadic early source for S. aureus transmission to the naïve infant microbiome, but microbiome determinants become more important later in the first year. Furthermore, we identified a specific protein family that is highly predictive of infant S. aureus status, significantly anticorrelated with S. aureus positivity in both infants and mothers, sufficiently prevalent to drive widespread patterns of S. aureus carriage, and which ecologically interacts with the commensal species D. pigrum. In subsequent companion work, we determined that this (misannotated) protein family was a non-protein-coding sequence acting as a phylogenetic marker of a likely novel bacterial clade. Our study provides an improved understanding of how the infant nasal microbiome develops in early life, and how it can act to promote or exclude S. aureus colonization.

Saliva microbiome collection and processing methods

Presented by: Abigail Armstrong

The oral microbiome has been connected with lung health and may be of significance in the progression of SARS-CoV2 infection. Saliva-based SARS-CoV2 tests provide the opportunity to leverage stored samples for measuring the oral microbiome. However, these collection kits have not been tested for accuracy of measuring the oral microbiome. Saliva is highly enriched with human DNA and reducing it prior to shotgun sequencing may increase the depth of bacterial reads. We examined both the effect of saliva collection method and sequence processing on measurement of microbiome depth and diversity by 16S and shotgun metagenomics. We collected 56 samples from 22 subjects. Each subject provided two saliva samples with and without preservative; 6 subjects provided a second set of samples the following day. 16S rRNA gene (V4) sequencing was performed on all of the samples, and shotgun metagenomics was performed on 8 of the samples collected with preservative with and without human DNA depletion before sequencing. We observed beta diversity distance within subjects over time was smaller than between unrelated subjects, and distances within subjects were smaller in samples collected with preservative. Samples collected with preservative had higher alpha diversity measuring both richness and evenness. Human DNA depletion before extraction and shotgun sequencing yielded higher total and relative reads mapping to bacterial sequencing. We conclude that collecting saliva with preservative may give more consistent measures of the oral microbiome and depleting human DNA increases yield.

Microbiota-induced vitamin A mobilization by serum amyloid A and its role in intestinal immunity

Presented by: Ye-Ji Bang

Vitamin A and its derivative retinol are essential for the development of intestinal adaptive immunity. Retinoic acid (RA)-producing myeloid cells are central to this process, but how myeloid cells acquire retinol for enzymatic conversion to RA is unknown. Here, we show that serum amyloid A (SAA) proteins, retinol binding proteins induced in intestinal epithelial cells by the microbiota, deliver retinol to myeloid cells. We identify LDL receptor-related protein 1 (LRP1) as an SAA receptor that facilitates endocytosis of SAA-retinol complexes and promotes retinol acquisition by RA-producing intestinal myeloid cells. Consequently, SAA and LRP1 are essential for the development of vitamin A-dependent adaptive immunity, including B and T cell homing to the intestine and IgA production, and promote protection against enteric infection after immunization. Our findings identify a key mechanism underpinning vitamin A’s effects on the immune system and provide insight into how the microbiota promotes intestinal immunity.

Prioritization and Annotation of Novel Bioactive Small Molecules from the Microbiome

Presented by: Amrisha Bhosle

Microbial communities – particularly the human gut microbiome – are a rich source of novel bioactive small molecule metabolites. Tens of thousands of metabolites have been assayed from stool, in association with millions of microbial enzymes, but as yet with minimal biochemical characterization or knowledge of their therapeutic potential. This is especially true for microbially-derived or -associated small molecule immunomodulators in conditions such as the inflammatory bowel diseases (IBD), in which gut microbial alterations have been implicated in induction of or protection from inflammation. Here, we have developed and validated a new approach for identifying and prioritizing potentially bioactive novel metabolites from the gut microbiome, which we initially applied to ~82k compounds spanning 546 metabolomes from 106 IBD patients and controls in the Integrative Human Microbiome Project (HMP2). We assigned putative biochemical annotations, and prioritization of potential bioactivity was done by integrating epidemiological properties (e.g. IBD pathogenesis) with ecological ones (e.g. covariation and prevalence). Top-ranked features were enriched for bile acid derivatives and short-chain fatty acid precursors, among other classes of chemical compounds that have been previously implicated in IBD-related dysbiosis, as well as modestly explored classes such as medium-chain fatty acids, putrescine metabolites, and B vitamins. These results point to new, potentially microbially-derived and -associated compounds for immunomodulation in inflammatory conditions. The general method can be applied to integrate knowledge of chemical profiles from any microbial community metabolomics with phenotypic or environmental indicators of bioactivity. We provide an open source implementation as MACARRoN (Metabolome Analysis and Combined Annotation Ranks for pRediction of Novel bioactives). The metabolites prioritized in this study of IBD expand our understanding of interactions between the microbiota and host during gut inflammation and offer new candidate small molecules with therapeutic potential.

Discovery of the Gut Microbial Enzymes that Drive the Dose-Limiting Toxicity of the Immunosuppressant Mycophenolate Mofetil

Presented by: Marissa Bivins

Mycophenolate mofetil (MMF) is an immunosuppressant used chronically by organ transplant and autoimmune patients. Unfortunately, MMF causes dose-limiting, gastrointestinal side effects, including ulcers, weight loss, vomiting, and diarrhea. The active form of MMF, mycophenolic acid (MPA), is inactivated to mycophenolate-glucuronide (MPA-G) via human drug metabolism and sent to the gut for elimination. Bacteria residing within the gut express β-glucuronidase enzymes (GUSs) that convert drug-glucuronides into their active forms and have been subjected to targeted inhibition. Reactivation of MPA-G within the gut is predicted to cause this drug’s intestinal toxicity and drive difficulties in dosing due to enterohepatic recirculation. Here, we show that complex enzyme slurries from MMF-treated patient fecal samples have variable MPA-G processing activities that are not inhibited by previously validated GUS inhibitors. To identify the GUS enzymes that process MPA-G, we kinetically evaluated a panel of GUSs in vitro and discovered two highly efficient isoforms from Bacteroides uniformis and Roseburia hominis. Structural analyses pinpointed specific motifs that enable MPA-G reactivation by these enzymes. Defining the structural basis of efficient MPA-G processing by microbial GUS proteins will facilitate the development of novel inhibitors to prevent MMF-induced gut toxicity.

Discovering antibiotics by integrating microbiome and metabolome data via high dimensional mediation analysis

Presented by: Asker Brejnrod

Antibiotics resistance is a problem of growing importance. Discovery of new candidate compounds that are tolerable for humans is an important path to alleviate this problem as most screened compounds are toxic to humans. In this work we leverage publicly available data of paired microbiome and metabolome samples from human gut to discover compounds that has antibiotic activity at physiologically relevant concentrations to identify non-toxic candidates.

We built on the ecological theory that some bacteria produce compounds to inhibit competing bacteria, by constructing correlation networks and selecting negatively correlating taxa. To select metabolite features that might mediate this killing we fit high dimensional mediation models while controlling false discovery rates.

We test this proposition by selecting candidate compounds against Vancomycin Resistant Enterococcus (VRE). We selected 5 candidates of which 1 had previously been reported in the literature. We determined Minimum Inhibitory Concentrations and saw that 3 including the previously reported compound had inhibitory effects.

In conclusion, integration of parallel metabolome and microbiome observations can be used to discover compounds with antibiotic activity.

16S sequencing on pediatric blood detects DNA signatures of commensals and pathogenic microbes that correlate with clinical features

Presented by: Matthew Brock

The presence of bacterial DNA in the blood of pediatric patients is largely unstudied frontier. We performed 16S rRNA sequencing on 147 apparently healthy 1- and 2-year-old children to explore potential microbial communities in the blood. Interestingly, 16S data detected some common pediatric pathogens in 6 out of 147 children. These were Staphylococcus, Streptococcus, Haemophilus and Deinococcus. Four of these 6 children also had a recorded history of some kind of infection, supporting the 16S data. More than 20K sequencing reads supported these pathogen signatures, which is similar to the counts observed in active infections. Beside these, the assay also picked up DNA signatures of several commensals such as Firmicutes, Bacteroides and Proteobacteria. Although the read count supporting these OTUs were hundreds of folds lower than their typical abundance in gut or stool samples, 16S data stratified samples into four major clusters differing in microbial composition. Cluster 1 was dominated by Proteobacteria. Cluster 2 was present in almost 50% of the samples, comprised of 60-70% Firmicutes. Cluster 3 was mix in composition and present in 18% of the samples. Cluster 4 was dominated by Actinobacteria and represented by 4% of the samples. Interestingly, Cluster 1 was found significantly (p=0.002) associated with higher BMI in children. To investigate the potential source of blood microbial signatures we studied microbiota in stool, skin and blood of germ-free and conventional mice. So, while more work remains to be done to establish if an active microbial community exist in pediatric blood, the our data suggest that 16S sequencing assay can rapidly detect microbial DNA signatures of commensals and pathogens in blood to assist with infectious disease diagnosis.

Pre-symptomatic detection of COVID-19 from smartwatch data

Presented by: Andrew Brooks

The COVID-19 pandemic has disrupted societies and scientific research around the globe, and necessitates rapid innovation among the microbiology community to address the unprecedented viral crisis. Critical to combatting spread of the SARS-CoV-2 virus is understanding the factors that predict infection and hospitalization in personalized ways to allow unique responses. Leveraging individual level data generated from wearable technology, we have been developing predictive systems for COVID-19 using physiological measures from smartwatches and other wearable devices to enable a real-time pre-symptomatic COVID-19 alarm system through our phone application (https://innovations.stanford.edu/wearables).

Tens of millions of Americans actively use wearable devices digitally measuring vital signs on a daily basis, and these have proven useful for monitoring health and illness onset with potential for real-time monitoring and disease detection. Using smartwatch data from infected individuals in a cohort of over 6,000 participants, we investigated the use of wearables for early, pre-symptomatic detection of COVID-19. In phase 1, we demonstrated that COVID-19 infections are associated with alterations in heart rate, steps and sleep in 80% of COVID-19 infection cases, with detection before or at symptom onset in 85% of the positive cases. We developed a method detecting 67% of infection cases at or before symptom onset in real-time, which has been implemented in phase 2 with currently over 3,000 participants receiving alerts from our custom phone application to warn of potential COVID-19 infection signs. Results are being validated in the second phase through FDA certified nasal swabs, as well as blood and stool microsampling kits mailed to study participants. Stool samples will be used for microbiome analyses and compared to extensive survey data, wearable data, and predictive algorithm accuracy.

Gut metabolites predict Clostridioides difficile recurrence

Presented by: Jennifer Dawkins

Clostridioides difficile infection (CDI) is the most common hospital acquired infection in the U.S., causing ~450,000 cases and 29,000 deaths annually. CDI recurrence in patients is high: ~25% for the first recurrence and increasing with each episode. The initial development of CDI and CDI recurrence are mechanistically tied to disruption of the normal gut microbiota. Metabolites reflect functional activities of the microbiome and pathways common to multiple bacterial species, and thus may provide a clearer picture of the gut microbiota than microbial compositional data alone.  We aim to predict CDI recurrence and better understand its pathogenesis by analyzing the gut microbiota and gut metabolites present in participants recently diagnosed with initial CDI.

We used 16S rRNA amplicon sequencing and liquid-chromatography/mass-spectrometry (LC/MS) untargeted metabolomics to analyze stool samples from 53 participants at diagnosis of CDI, directly after cessation of treatment, and weekly or bi-weekly for 4-6 weeks or until recurrence occurred. Using lasso-penalized logistic regression on these data, we developed predictors of CDI recurrence.

Our predictor achieved a median cross-validated area-under-the-curve (AUC) of 0.788 (0.733, 0.788) when using only metabolome data, compared to a median 0.645 (0.623, 0.695) AUC when using only microbial composition data. The combined data achieved an AUC of 0.781 (0.780, 0.781) and moreover selected only metabolite covariates, suggesting no gain in predictive capability from the microbial composition data. We found several metabolites that predict recurrence, including a host inflammatory biomarker, a metabolite reported to affect permeability of the intestinal lumen, and a metabolite highly associated with microbial-host co-metabolism. We also found a metabolite that predicts protection against CDI recurrence; this metabolite has been implicated in antimicrobial activity and cell cycle regulation.

These results suggest that gut-metabolites may provide mechanistic insights into CDI and moreover can accurately predict recurrence, a challenging clinical problem that if solved could enable prompt, targeted treatments to short-circuit the vicious cycle of recurrence. Because CDI is so prevalent in hospitals, preventing CDI recurrence would make hospital stays safer and shorter for those admitted for any condition.

The Cancer Microbiome Atlas (TCMA): A Resource for Querying Host-Microbe Interactions

Presented by: Anders Dohlman

Despite the rapid expansion of microbiome research, studying the microbial composition of internal human organs and their association with disease states remains challenging due to the difficulty of acquiring clinical biopsies for microbial profiling. Next-generation sequencing data contain reads that map to both human and microbial genomes, but analyses of these datasets are plagued by contamination, which is relatively abundant in low-biomass tissue samples. We designed a statistical comparative model to analyze the prevalence of microbial species across sample types and sequencing centers from The Cancer Genome Atlas (TCGA). This revealed that species detected at equal rates across tissue and blood samples are predominantly contaminants, bearing unique signatures from each TCGA-designated sequencing center. Removal of such equiprevalent species from the dataset mitigated center-related batch effects and allowed isolation of the tissue-resident microbiome. The analytical results were further validated by metagenomic sequencing of original matched TCGA colorectal tumor and blood samples that were sequenced independently at each designated center. We thus present The Cancer Microbiome Atlas (TCMA), a collection of curated, decontaminated microbial compositions for TCGA sequencing data on oropharyngeal, esophageal, gastrointestinal, and colorectal cancer tissues with tissue-resident populations. The creation of TCMA led to several findings, including prognostic species, tumor-associated coabundance groups, and blood signatures of mucosal barrier injuries. Finally, we demonstrate that TCMA enables systematic matched microbe-host omics (epigenetic, transcriptomic, and proteomic) analyses, which will help guide future studies of the microbiome’s role in human health and disease.

Users can explore the TCMA database here: https://tcma.pratt.duke.edu

Integrating taxonomic, functional, and strain profiling of microbial communities with bioBakery 3

Presented by: Eric Franzosa

Culture-independent analyses of microbial communities have improved dramatically in the last decade, particularly due to advances in methods for biological profiling via shotgun metagenomics. Opportunities for improvement continue to accelerate given greater access to multi-omics, microbial reference genomes, and strain-level diversity. To leverage these resources, we present bioBakery 3: a set of integrated and improved methods for taxonomic, strain-level, functional, and phylogenetic profiling of metagenomes and metatranscriptomes developed using the largest set of reference sequences now available. Compared to current alternatives, MetaPhlAn 3 increases the accuracy of taxonomic profiling, and HUMAnN 3 improves that of functional potential and activity. These methods detected novel disease-microbiome associations in applications to CRC (1,262 metagenomes) and IBD (1,635 metagenomes and 817 metatranscriptomes). Strain-level profiling of an additional 4,077 metagenomes with StrainPhlAn 3 and PanPhlAn 3 unraveled the phylogenetic and functional structure of the common gut microbe Ruminococcus bromii, previously described by only 15 isolate genomes. Phylogenetic analysis with PhyloPhlAn 3 supports both genomic and metagenomic data, by assigning genomes from isolate sequencing or metagenomic assemblies to species-level genome bins defined on >230,000 publically available sequences. It accurately reconstructs phylogenies at different resolutions (from strain-level to microbial tree-of-life) using maximally informative markers and, optionally, metagenomic assemblies and novel organisms. The bioBakery 3 implementation includes open-source software, documentation, training data, and cloud-deployable reproducible workflows to help researchers deepen the resolution, scale, and accuracy of multi-omic profiling for microbial communities.

CD8+ T Cells Mediate Colon Epithelial Cell Death in an Organoid Model of HIV Pathogenesis

Presented by: Leah Froehle

There are 37.9 million people worldwide living with HIV [1] and although advances in antiretroviral treatment (ART) have significantly extended life expectancy, the burden of HIV-associated comorbidities remains high [2,3,4,5]. Gut epithelial barrier disruption is a hallmark of HIV infection and even after decades of ART, markers of intestinal barrier disruption remain persistently elevated in some individuals [6,7]. Gut barrier disruption can result in the translocation of luminal bacteria and bacterial products, leading to systemic inflammation [8,9]. The specific mechanisms of this HIV-associated gut epithelial barrier disruption remain incompletely understood, but it is believed to be a critical driver of the increased prevalence of inflammation-associated comorbidities observed in those with ART-treated HIV [10]. We demonstrated that intestinal epithelial cells from HIV-infected individuals undergo increased apoptosis in comparison to those from HIV-uninfected individuals. Employing an ex vivo 3D mini-colon organoid model cocultured with autologous colon mucosal lymphocytes, we showed that this epithelial cell death can also be seen ex vivo in HIV-infected lymphocyte-organoid co-cultures derived from HIV-uninfected individuals. Moreover, colon epithelial cell death is dependent upon tissue resident CD8+ T cells, excluding HIV-specific CD8+ T cells. We also show that CD8+ T cell derived TNF and IFN are dispensable for mediating the epithelial cell death. Since the molecular characteristics of colon tissue resident CD8+ T cells in the context of chronic viral infection are largely unknown, our current work seeks to elucidate the inherent metabolic programming of these colon tissue resident CD8+ T cells. The metabolic profile of colon tissue resident CD8+ T cells may contribute to the observed epithelial cell death in the context of HIV pathogenesis. These findings may help identify novel methods to better treat those living with HIV.

High-sensitivity pattern discovery in large, paired multi-omic datasets with HAllA

Presented by: Andrew Ghazi

Modern biological screens yield enormous numbers of measurements and finding statistically significant associations among features with ease of interpretation is essential. Here, we present a novel hierarchical framework, HAllA (Hierarchical All-against-All association testing), for well-structured association discovery between paired high-dimensional datasets. HAllA efficiently integrates hierarchical nonparametric hypothesis testing with false discovery rate correction to reveal significant linear and non-linear block-wise relationships among continuous and/or categorical. We optimized and evaluated HAllA using heterogeneous synthetic datasets of known association structure, where HAllA outperformed all-against-all and other block testing approaches across a range of common similarity measures. We then applied HAllA to a series of real-world multi-omics datasets, revealing new associations between gene expression and host immune activity, the microbiome and host transcriptome, metabolomic profiling, and human health phenotypes. An open-source (Python) implementation of HAllA is freely available at http://huttenhower.sph.harvard.edu/halla along with documentation, demo datasets, and a user group.

Reconstruction of metagenome-scale models of the gut microbiota metabolism at species-level resolution in Inflammatory Bowel Disease

Presented by: Isabella Goodchild-Michelman

Inflammatory bowel Disease (IBD) is a chronic inflammatory condition of the intestinal tract that affects over three million Americans each year. Numerous studies have associated microbial species and microbially-derived metabolites in the gut and IBD. Nevertheless, as association studies do not necessarily point to underlying causal mechanisms, the exact microbial mechanisms of IBD pathogenesis are still unknown. To better understand the functional role of microbial species in IBD pathogenesis, we aimed to reconstruct genome-scale models (GEMs) of metabolism for bacterial species in the gut microbiota of IBD and non-IBD subjects. To this end, we are using taxonomic profiling data from fecal samples of IBD and non-IBD subjects in the Human Microbiome Project to reconstruct GEMs for all microbial species. We then integrate GEMs of species present in each sample into a community model representative of the fecal microbiota in that sample. These community GEMs are being used to computationally simulate the metabolic activity of individual microbial species and inter-species metabolic interactions in IBD and non-IBD subjects. By comparing the predicted species-level metabolite secretion and uptake fluxes, we determined how microbiota-derived metabolites and the metabolic activity of individual microbial species differs between the IBD and non-IBD models. Our analyses revealed significant fold changes in the production levels of several metabolites a number of which were previously implicated in IBD. For example, we observed higher levels of lactate linked to Enterococcus faecium and Klebsiella pneumoniae and lower levels of butyrate linked to Finegoldia magna and to Peptostreptococcus anerobius in IBD cases compared to non-IBD controls. They also enabled us to trace back microbial species that are responsible for the production of metabolites linked to IBD pathogenesis. Overall, our study is expected to provide unprecedented insight into the link between species and metabolite-level biomarkers of IBD.

Uncovering the role of gut microbiota in HIV acquisition and vaccine response in infant monkeys

Presented by: Danting Jiang

The HIV/AIDS epidemic remains one of the world’s most critical public health problems. Following decades of research on HIV pathogenesis, there is a growing wealth of studies that have characterized the dysbiosis of gut microbiota caused by HIV in infected patients. Inversely, however, it is still unclear whether these diverse communities of microorganisms, which play a fundamental role in host physiology, affect susceptibility to HIV infection. Here, we analyzed 16S rRNA gene sequencing data from fecal samples of infant rhesus macaques in a pediatric HIV vaccine study, which includes HIV and control vaccine groups (immunized at 0, 6, and 12 weeks of age; n=12/group). Starting at 15 weeks of age, all monkeys were orally challenged with SHIV every week until they became infected. Although the HIV vaccine did not confer protection, the animals exhibited variable time to acquisition of SHIV. We compared the overall microbial profile of animals from the two groups and found that the HIV vaccine caused changes in the gut microbiota despite its failure to provide protection. Additionally, we identified 7 bacterial taxa that were bioinformatically associated with increased susceptibility of HIV, and 2 taxa that were associated with decreased susceptibility. Importantly, one of the protective taxa, Lactobacillus gasseri, has previously been experimentally confirmed as inhibiting HIV infection of human tissue in vitro, which helps validate our overall findings. Taken together, our results support the idea that the gut microbiota impacts acquisition of HIV and provides new insights on its prevention.

Identification of microbial-derived HLA-bound peptides in melanoma

Presented by: Shelley Kalaora

Bacteria were first detected in human tumors more than 100 years ago, but the complex interplay between the microbiome and cancer initiation, progression, and response to therapies is only starting to unravel. While different mechanisms by which bacteria can affect the immune response were reported, the role of bacterial antigen presentation as the mediator of immune recognition and response has remained unclear. Recent investigations, of stool samples collected from cancer patients treated with immune-checkpoint-inhibitors, allowed the identification of bacteria subsets that were more abundant in responding versus nonresponding patients. Fecal microbiota transplantation of feces from patients who showed clinical response to immune-checkpoint-inhibitors, induced similar improved immune response in the recipients, both in pre-clinical mouse models and human patients. These results highlight the fact that immune responses observed in the patients were derived from their microbiome composition, and strengthens the importance of identifying the mechanisms by which specific bacteria influence an anti-tumor response.

In this study, combination of human leucocyte antigen (HLA) peptidomics with 16S rRNA sequencing of 19 melanoma metastasis derived from 9 different patients, lead us to the unbiased identification of hundreds of HLA-I- and tens of HLA-II-bacterial peptides. We were able to validate these results by controlled cell culture work, from the step of bacteria invasion, by co-culturing the bacterial species identified by 16S sequencing with the patient derived melanoma cells, throughout validating the peptide’s presentation by preforming HLA peptidomics on the infected cells. Importantly, we were able to identify common bacterial peptides from different metastases of the same patient as well as from different patients. Some of the common bacterial peptides, as well as others, were able to elicit an immune response by the autologous tumor infiltrating lymphocytes.

By identifying immunogenic microbial-derived antigens presented on tumor HLA molecules, we demonstrate that tumor bacteria may not only shape the immune tumor microenvironment but also directly affect T cell immune-reactivity. Antigen presentation of bacterial antigens provides insights into a new mechanism by which bacteria influence immune system activation and response to immunotherapy. Introducing bacterial derived antigens to the repertoire of tumor associated antigens, potentially extends the variety of targets for cancer immunotherapies.

Characterization of a novel microbiome marker anti-correlated with Staphylococcus aureus carriage in the infant nasal microbiome

Presented by: Maddy Kline

Staphylococcus aureus carriage in the nasal microbiome is an important determinant of subsequent S. aureus soft tissue infection. Identifying elements of the nasal microbiome that influence carriage provides insight on how to modulate these factors to prevent progression to infection. Prior work by Accorsi et al. 20201 discovered an uncharacterized, taxonomically unassigned ORF that was the major predictor of whether infant microbiome samples evaluated with shotgun metagenomic sequencing contained S. aureus. Subsequent investigation indicated that this ORF was actually a segment of 16S rRNA gene sequence incorrectly annotated by UniProt as a protein-coding gene. In order to determine its true provenance and possible roles in preventing S. aureus carriage, we performed updated taxonomic and functional profiling of 284 shotgun metagenomes from nasal swabs spanning 36 mother-infant pairs monthly for the first year of life. We then analyzed which known gene families were correlated with the marker by 1) performing covariation-based genome reconstruction and 2) traditional metagenomic assembly. Our analyses found that this marker was weakly positively correlated with gene families classified to Streptococcus species and Dolosigranulum pigrum. Our assembly showed larger genomic fragments with portions that annotated as 16S rRNA gene fragments from similar species. We confirmed these findings by using parallel analyses on 267 nares metagenomes from the Expanded Human Microbiome Project. Our analyses thus provide substantial initial support for the hypothesis that this sequence represents a phylogenetic marker for a novel clade with genomic similarity to Streptococcus species and D. pigrum, which could antagonize S. aureus during colonization of the infant nasal microbiome.

Instability, Heterogeneity, and Pathogenicity Reservoirs in the Skin, Oral, and Gut Microbiota of Older Adults

Presented by: Peter Larson

Background: The microbiota – communities of bacteria, viruses, fungi, archaea, and protozoa that inhabit nearly every surface of the human body – are an emerging risk factor for aging-related diseases. Microbiota influence local and systemic health through metabolic and immunomodulatory processes, and can harbor, or protect against, pathogens. Despite this, older adults have often been excluded from systematic metagenome studies. We investigated the skin, oral, and gut microbiota of older adults living in both community and skilled nursing facility (SNF) settings, focusing on potential relationships with frailty and place of residence.

Methods: We conducted a longitudinal microbiome survey of 47 subjects age 65+ years of age; 22 SNF dwelling (SNFD) and 25 community dwelling (CD). We performed metagenomic whole genome shotgun sequencing on stool, oral, and skin samples from 8 sites, 1360 total. To correlate clinical and behavioral variables, we measured frailty, collected medical records, and interviewed subjects on diet and lifestyle. We also drew comparisons with our and others’ previous younger cohorts.

Results: We observed prominent differences between the microbiomes of younger and older adults, particularly for SNFDs, at all body sites. Subject frailty was negatively correlated with the relative abundance of Cutibacterium acnes in skin communities, which itself was highly correlated with microbial community stability, diversity, heterogeneity, and biogeography, factors that may modulate pathogen colonization and disease risk. The skin was the primary reservoir for plasmid-borne antimicrobial resistance and clinically important pathobionts. Strain composition of important commensals such as C. acnes and Staphylococcus epidermidis in SNFDs further indicated a shift from healthy to pro-inflammatory or nosocomial pathogen strains.

Conclusions: Our results constitute the first holistic assessment of the older adult microbiome, raising new hypotheses about the relationship between the microbiota and aging, as well as how they could be leveraged to improve the health of older adults. These findings suggest skin aging may predispose resident microflora to perturbation and highlight the skin as a perhaps the major reservoir for pathogens and antibiotic resistance in older adults.

Probiotic Supplementation and Marathon Runners: there are any effect up to Gut Microbiota and neutrophil function?

Presented by: Giovana Leite

Probiotic supplementation can induce positive alterations in intestinal environment, however the effect of a month period short of probiotic supplementation on gut microbiota and neutrophil function of endurance athletes is not known. PURPOSE: Investigate the effect of thirty days of probiotic supplementation up on gut microbiota composition and neutrophil function in marathon athletes. METHODS: Twenty-seven marathon runners were double-blind randomly assigned to either a Probiotic (PR) (35,96 ± 5,81 years,79,30 ±10,99Kg) or Placebo (PL) group (PL= 40,46 ± 7,79 years, 72,67 ±10,20Kg). PR consumed Lactobacillus Acidophilus and Bifidobacterium Lactis (10x109UFC + maltodextrin) during 30 days in a sachet form, while PL received a sachet with maltodextrin (5g/day). The gut microbiota composition was evaluated before (BASELINE) and after the supplementation period (POS-SUP). Fiber consumption was evaluated using one-day diet record at the baseline and Pos-sup. Blood collection was realized (BASELINE and POS-SUP) to verify neutrophil function, after blood cell neutrophil isolation peroxide and cytokine production (IL-1- β; TNF-α; IL-6; IL-8) was analyzed. The Bacterial DNA were extracted using QIAamp Fast DNA Stool Mini Kit® and faecal microbiota composition was assessed by 16S rRNA sequencing, V3-V4 regions, with Illumina® MiiSeq plataform. Operational taxonomic units (OTUs) and diversity indices were obtained after bioinformatic treatment on Qiime2® software. β-diversity was computed considering the sampling of 1,800 sequences per sample, which was based on the rarefaction curve. To test differences among groups and time, it was performed a pairwise PERMANOVA for beta-diversity and ANCOM for OTUs relative abundance. Data analyses were conducted using SAS Statistical Software version 9.3® (p< 0.05 and multiple tests corrected when necessary). For neutrophil function was used the of repeated measures statistical test mixed Model (with ‘group’ and ‘time’ as factors) being used with Tukey’s post hoc – GraphPad Prim8 ®. RESULTS: Fiber consumption was similar between groups with no statistical difference [BASELINE: 23,65 ± 10,53 (PL); 24,92± 19,15 (PR); POS-SUP= 25,63± 15,61 (PL); 15,61±15,25(PR)]. The peroxide and cytokines production by neutrophils were no different between groups. From the gut microbiota analyses, it was identified 2.634 OTUs based on 173.096 final sequences. Regarding beta- diversity, UniFrac weighted index was different between groups (p=0,04; PERMANOVA) and the relative abundance of Lactobacillus ruminis was significant different between groups, in which PR exhibited significant high levels after supplementation period. DISCUSSION: Probiotic induced changes in the intestinal environment or increased interaction among specific bacterial species leading to an increase in the relative abundance of lactic acid bacteria, such as Lactobacillus ruminis. This effect seems to be a positive change from the supplementation toward athletes’ health, since this specie is a probiotic bacteria known for its immunomodulatory activity. CONCLUSION: Without fiber consumption influence, 30 days of Lactobacillus Acidophilus plus Bifidobacterium Lactis (10x109UFC/day) supplementation not modify neutrophil peroxide and cytokine (IL-1-β; TNF-α; IL-6; IL-8) production however cause specific modification in gut microbiota composition increasing relative abundance of Lactobacillus ruminis. Financial Support: CNPq, CAPES/PROEX. We declare that there is no conflict of interest in research.

The Microbiome Collection Core at the Harvard T.H. Chan School of Public Health (HCMCC)

Presented by: Chengchen Li

The Microbiome Collection Core at the Harvard T.H. Chan School of Public Health (HCMCC) aims to support population-scale microbiome studies with reliable, scalable, and flexible in-home fecal and oral specimen collections. Leveraging the intellectual and infrastructure foundation laid by the HMP2 (the 2nd phase of the NIH Human Microbiome Project) and the MLSC (Massachusetts Life Sciences Center)-funded MICRO-N (MICRObiome Among Nurses) collection, the HCMCC provides customizable fee-for-service implementations and processes of sample collection kits. Preservatives included in the kit stabilize major microbial communities at ambient temperature and various shipment options, and provide capabilities for amplicon, shotgun metagenomic and metatranscriptomic sequencing, stool metabolomic profiling, in addition to future culture and gnotobiotic animal model studies. Standardized questionnaires are included to capture proximal exposure, outcome, covariate, biometric, and technical information accompanying each sample collection, along with participant-friendly kit instructions. Together, the HCMCC’s generalized fecal and oral microbiome sample collection protocol enables researchers to conduct cost-effective microbiome study ranging from population-scale cohorts to pilot trials, ultimately, to expand our understanding of the microbiome to improve population health.

A Fast and Accurate Machine Learning of Human Interpretable Rules Predicting Host Status from Microbiome Dynamics

Presented by: Venkata Suhas Maranganti

Introduction

Understanding the relationship between microbiome dynamics and host outcomes is critical for defining predictive models and ultimately understanding the mechanisms through which the microbiome causes disease. Although off-the-shelf “black box” machine learning methods are widely deployed in the field, many methods do not consider biologically relevant structure in the data and are not interpretable.

Methods

We developed a new model, MDITRE: Microbial Differentiable and Interpretable Temporal Rule Engine that accelerates our earlier fully-Bayesian method, for learning human-interpretable rules to predict host outcomes from longitudinal microbial data. MDITRE uses continuous relaxations of discrete variables that capture relevant phylogenetic and temporal features, using novel domain-specific attention mechanisms, which enables highly efficient gradient-based optimization inference algorithms on GPUs.

Results

MDITRE achieves similar predictive performance as our original method on a suite of longitudinal microbiome datasets, while running 30X-70X faster. Moreover our model learns biologically meaningful relationships that our prior model did not.

Conclusion

We developed MDITRE, a highly scalable and accurate supervised machine learning model that learns human interpretable rules from longitudinal microbiome data. We demonstrate that our model can provide new insights into the complex and dynamic host-microbial ecosystems.

Infant Gut Microbiome and Infections and Symptoms: A Prospective Cohort Study

Presented by: Yuka Moroishi

Background: Emerging evidence points to a critical role of developing gut microbiome on immune maturation and infant health; however as yet, epidemiologic studies are limited to experimental studies, high risk cohorts and cross-sectional analyses. We examined whether infant gut microbiota related to the occurrence of health outcomes such as infections, eczema, and allergy during the first year of life.

Methods: Infants from the prospective New Hampshire Birth Cohort Study were studied. We applied generalized estimating equations to 16S rRNA V4-V5 gene sequencing data from stool samples of 465 infants and shotgun metagenomics sequencing data from185 infants at approximately 6 weeks of age.

Results: Higher alpha diversity associated with increased risk of infection or respiratory symptoms (RR: 1.39; 95% CI: 1.10-1.77) and specifically upper respiratory tract infections (RR: 1.40; 95% CI: 1.12-1.76). After stratifying by delivery mode, we observed increased relative risk of number of infections and symptoms, upper RTI, wheeze, and diarrhea in vaginally delivered infants in relation to increased microbial alpha diversity at 6 weeks of life. Metagenomics analyses identified several microbial species, including Veillonella, Streptococcus, and Clostridium species, as associated with immune-related outcomes.

Conclusion: Our findings in a large prospective birth cohort in the US suggest that early intestinal microbial diversity and abundance of specific key species of the gut microbiome may influence infants’ risks of infection and symptoms such as wheeze and diarrhea. Clarifying patterns in the early life microbiome that may predict adverse immune mediated health outcomes provide opportunities for microbial focused interventions to improve lifelong health.

cILR: Taxonomic Enrichment Analysis with Isometric Log Ratios

Presented by: Quang Nguyen

Background: High-dimensionality and sparsity are challenging problems in statistical analysis of microbiome relative abundance data. One approach is to aggregate taxa to sets, most commonly to Linnean taxonomic categories identified through classification of representative sequences. However, most researchers perform aggregation through the pairwise summation of counts, preventing comparison across sets of different sizes.

Methods: We developed a taxa set enrichment method based on the isometric log-ratio transformation (cILR) for microbiome relative abundance data. Our method generates sample-specific taxa set enrichment scores with a well-defined null hypothesis corresponding to the Q2 competitive null hypothesis in the gene set testing literature. Significance testing was performed by estimating the empirical null distribution accounting for variance inflation due to inter-taxa correlation.

Results: Here we demonstrated the performance of our method using both real data and parametric simulations for multiple microbiome analysis tasks, which are: single sample enrichment testing, differential abundance testing, and disease prediction.

Conclusions: The cILR method provides a flexible way to aggregate taxonomic variables to pre-defined sets, allowing for a comparison of enrichment across sets of different sizes. The statistic corresponds to a well-defined null hypothesis and is designed to address the compositional nature of microbiome data.

Intestinal inflammation leads to changes in the blood PBMC and plasma microbiome

Presented by: Emese O’Donnell

Despite several studies having confirmed the presence of bacteria in the blood of humans, very little is known about the distribution of microbial DNA among leukocytes in the systemic circulation. In this preliminary study, we aimed 1) to evaluate the peripheral blood mononuclear cells (PBMC) and plasma bacterial microbiome in humans, and 2) to investigate potential bacterial translocation into systemic circulation. To address these questions, two groups of individuals were selected for the microbiome analyses of both plasma and PBMC samples: one group with acute intestinal inflammation and the other without it. Along with several blanks and microbial community standards, the DNA was extracted from the plasma and PBMC samples using the Ultra-Deep Microbiome Prep Kit from Molzym. Then, 16S v3v4 amplicon libraries were made using the standard NexteraXT Illumina library prep protocol and sequenced on a MiSeq v3 platform. After careful contaminant removal, sequences were analyzed using the Qiime2 pipeline. We found that patients with intestinal inflammation are more likely to have detectable bacterial microflora than those without it, moreover, the bacterial composition of the two groups was significantly different from each other. Enterococcus faecalis and Escherichia-Shigella genus, bacteria more likely to originate from the intestine, were enriched in the group with intestinal inflammation in both plasma and PBMC. The result was confirmed by PCR. Due to the preliminary feature of the study, the main limitations are the small sample size and lack of correction for potential cofounders. The measurement of the microbiome from plasma and PBMC may provide a new method for the characterization of intestinal inflammation and offer a new diagnostic and therapeutic target.

Maternal probiotic intake during obesity ameliorates depressive-like behaviour and alters the gut-brain axis in adult offspring

Presented by: Daniel Radford-Smith

Depression is a common disorder which continues to increase in prevalence. Epidemiological evidence demonstrates a role for gestational obesity in offspring behavioural disorders, alongside perturbations to the microbiota-gut-brain axis. Prebiotic administration reduces offspring depressive-like behaviour in naïve, normal weight dams, but the action of probiotics in obese dams is unknown. Moreover, the mechanisms by which perinatal probiotic exposure exerts beneficial effects remains elusive. We aimed to determine whether maternal probiotic supplementation protected adult offspring against the adverse behavioural and metabolic effects of maternal obesity. CD-1 female mice were randomly assigned to receive either a high-fat diet or a carbohydrate-matched control diet prior to and throughout gestation and nursing. Adult offspring behaviour was tested at 16 weeks of age. We then used nuclear magnetic resonance spectroscopy to investigate the functional changes of maternal diet-induced obesity and maternal probiotic intake in offspring, across the gut-brain axis. Progeny of obese dams exhibited increased depressive-like behaviour, while maternal probiotic intake mitigated the pro-depressant effects of maternal obesity. Faecal short-chain fatty acids were increased in probiotic offspring in adulthood, while acetate and lactate were increased in the adult brain. We provide novel evidence for the therapeutic effects of perinatal probiotic supplementation on offspring depressive-like behaviour, induced by maternal obesity, and associate these effects with a longstanding increase in microbial short-chain fatty acid production.

Power and sample size calculation for microbiome epidemiology

Presented by: Meghan Short

Accurately assessing statistical power as a function of sample size and effect size is critical for good study design, particularly with respect to complex human populations and high-dimensional molecular epidemiology. Microbiome data especially pose unique challenges, considering the many biological factors that can influence the microbiome, the multiple types of molecular measurements possible, and their technical and biological variability including compositionality, zero-inflation, and measurement error. Standard methods for calculating power may thus be inadequate for measuring associations between microbial features and biological variables of interest. We demonstrate this using simulated and synthetically spiked microbial profiles containing known relationships of varying types. Standard parametric or rank-based tests consistently mis-estimated power, suggesting that richer hierarchical models or simulation frameworks for study design will be more appropriate. We are currently testing such models using this benchmarking approach to provide a suite of methods for accurate feature-wise and omnibus test power calculations in human microbiome population studies.

Infection trains the host for microbiota-enhanced resistance to pathogens

Presented by: Apollo Stacy

The microbiota shields the host against infections in a process known as colonization resistance. How infections themselves shape this fundamental process remains largely unknown. Here, we show that gut microbiota from previously infected hosts display enhanced resistance to infection. This long-term functional remodeling is associated with altered bile acid metabolism leading to the expansion of taxa that utilize the sulfonic acid taurine. Notably, supplying exogenous taurine alone is sufficient to induce this alteration in microbiota function and enhance resistance. Mechanistically, taurine potentiates the microbiota’s production of sulfide, an inhibitor of cellular respiration, which is key to host invasion by numerous pathogens. As such, pharmaceutical sequestration of sulfide perturbs the microbiota’s composition and promotes pathogen invasion. Together, this work reveals a process by which the host, triggered by infection, can deploy taurine as a nutrient to nourish and train the microbiota, promoting its resistance to subsequent infection.

Probiotics alter the antibiotic resistance gene reservoir along the human GI tract

Presented by: Jotham Suez

Antimicrobial resistance poses a substantial threat to human health. The gut microbiome is considered a reservoir (the gut “resistome”) for potential spread of resistance genes from commensals to pathogens. The impact of probiotics, commonly consumed by many in health or in conjunction to antibiotics administration, on the gut resistome remains elusive. Direct assessment of the gut resistome in situ along the gastrointestinal tract in healthy antibiotics-naïve humans supplemented with an 11-probiotic-strain preparation demonstrated that probiotics reduce the number of antibiotic resistance genes exclusively in the gut of colonization-permissive individuals. In mice and in a separate cohort of humans, a course of antibiotics resulted in expansion of the lower gastrointestinal (GI) tract resistome, which was mitigated by autologous fecal microbiome transplantation or during spontaneous recovery. In contrast, probiotics further exacerbated resistome expansion in the GI mucosa, by supporting the bloom of strains carrying vancomycin resistance genes, but not resistance genes encoded by the probiotic strains. Importantly, the aforementioned effects were not reflected in stool samples, highlighting the importance of direct sampling for analyzing the effect of probiotics and antibiotics on the gut resistome. Analyzing antibiotic resistance genes content in additional published clinical trials with probiotics further highlighted the importance of per-person metagenomics-based profiling of the gut resistome using direct sampling. Collectively, these findings suggest opposing person-specific and antibiotics-dependent effects of probiotics on the resistome, whose contribution to the spread of antimicrobial resistance genes along the human gastrointestinal tract merit further studies.

Probiotic Supplementation Increase Monocyte’s Function and Maintain Gut Microbiota Alpha Diversity of Marathon Runners

Presented by: Edgar Tavares-Silva

After prolonged physical exercise, the immunological response of athletes could be impaired. Recently, the relationship between the intestinal microbiota and the immunological response has been postulated. Thus, we investigated whether probiotic supplementation modulates athlete’s intestinal microbiota and the immune response before and after a marathon race.

Materials and Methods
Marathon athletes (n=30) were allocated into placebo (maltodextrin 5g) or probiotic (10×109 CFU of Lactobacillus acidophilus LA-G80 and 10×109 CFU of Bifidobacterium animalis subsp. lactis BL-G101) and received a double-blind supplementation for thirty days. Before the supplementation period (Baseline) and 24 hours before the race (24h-Pre), faeces were collected to analyze microbiota Alpha diversity. Blood was collected at four different times (Baseline, 24h-Pre, 1h-Post and five days after the race) to analyze monocyte’s function and plasma cytokine. For ten days after the marathon race, athletes answered a checklist about symptoms of URTI. Bacterial genetic sequencing was based on the V3-V4 regions of rRNA 16S following Illumina’s MiSeq platform system and visualization by Quantitative Insights Into Microbial Ecology – QIIME. The data normality was verified using the Shapiro-Wilk test, and the Anova Two-Way applied with a significance level of p ≤ 5% for immune response.

Results
The probiotic group significantly increased the phagocytosis rate after thirty days of probiotic supplementation. The production of hydrogen peroxide and cytokines by monocytes did not differ between the groups. After the marathon race, plasma IL-10 increase and five days after, plasma IL-15 increase and plasma IL-8 decrease in both groups. The microbiota Alpha diversity does not differ between groups by the rarefaction curves measured by the Shannon Index and Observed OTUS Enrichment with the saturation of 1.860 16S rRNA sequences in each sample. The uniformity between the groups and moments verified through the Pielou Evenness index did not differ between the placebo and probiotic groups. The symptoms and severity of URTI were not different between groups.

Conclusions
Supplementation of 10×109 CFU of Lactobacillus acidophilus LA-G80 and 10×109 CFU of Bifidobacterium animalis subsp. lactis BL-G101 for thirty days was not sufficient to modify the microbiota Alpha diversity of marathon athletes and did not modify symptom parameters of opportunistic infections in the upper respiratory tract. However, probiotic supplementation was able to modulate the cellular response of monocytes, with a significant increase in phagocytosis rate after the supplementation period. Different studies have demonstrated the efficiency of probiotic supplementation on the immunological response and intestinal microbiota modulation in recent years. We believe it is necessary to investigate different doses and supplementation time for this specific population of marathon runners.

The gut microbiome in juvenile idiopathic arthritis

Presented by: Kelsey Thompson

One in every thousand children in the United Kingdom is diagnosed with juvenile idiopathic arthritis (JIA), a persistent, early-onset inflammatory joint disease that both parallels and differs from its adult analogs (e.g. rheumatoid arthritis, spondyloarthritis). JIA is among the many chronic systemic inflammatory diseases in which the gut microbiome has been implicated, but careful multi’omic studies of this complex condition have not previously been carried out. The Inflammatory Arthritis Microbiome Consortium (IAMC) characterized JIA gut microbial ecology, metabolism, and interactions with the hosts’ immune system through shotgun metagenomic and immunotype profiles. Samples were collected from children with juvenile enthesitis-related arthritis, oligoarticular JIA, polyarticular JIA, and psoriatic arthritis for a total of 113 JIA samples, plus 38 samples collected from age matched controls. We found that JIA subtype, current arthritis modifying drugs, and HLA-B27 status all explained a significant amount of taxonomic and functional variability within the gut ecosystem (PERMANOVA R² 2-3%, q<0.25). Current C-reactive protein levels and limited joint count, which are used to determine clinical inflammation status, also explained nominal amounts of variation. Age of the patient, as expected, explained the largest portion of the taxonomic (but not functional) variation. While the spread in age across such an important and rapidly changing gut microbiome landscape made it more difficult to interpret key ecological shifts, we were able to quantify several clades that mimic the results of adults with severe arthritis. These included a loss of key gut commensals (e.g. Faecalibacterium prausnitzii) associated with inflammatory markers (e.g. limited joint counts) and increased prevalence and abundance of proinflammatory taxa such as Esherichia coli. Additionally, sub-species phylogenetic associations were found with age, current drug, and JIA subtype. Functionally, several alterations to fatty acid metabolism were identified, along with modifications across sulfur related cycling and metabolism. Untargeted metabolomic profiles have also been generated in order to link potentially causal microbial changes to mediating small molecules. Taken together, our efforts represent the first comprehensive investigation of the gut microbial landscape’s interaction with systemic inflammation during juvenile idiopathic arthritis.

Evolutionary Implications of Reproductive Tract Microbiota in the Polygynandrous Red Junglefowl (Gallus gallus)

Presented by: Liisa Veerus

Host-associated microbiota are temporally unstable—novel bacteria are acquired from the environment and exchanged between hosts. In the current literature, hypotheses have emerged about the potential for host social behaviour to influence its gut microbiota, while the gut bacteria may affect host social decision making. A similar, yet under-explored evolutionary interdependence may also occur between host mating behaviour and its reproductive microbiota. For example, reproductive bacteria may partake in host reproductive decisions, play a role in sexual selection and conflict, and determine host socio- sexual network structure. How bacterial communities in the reproductive tract relate to host evolution may be more evident in non-human hosts. We therefore investigated this association by characterising the microbiota in the reproductive tracts of both female and male red junglefowl (Gallus gallus)—the main wild ancestor of the domestic chicken (G. domesticus)—that mates frequently and with multiple partners (polygynandry) over the breeding season. By carrying out 16S rRNA gene sequencing on functionally-distinct reproductive tract samples from both sexes, ejaculates from males, and cloacal wipes from sexually-interacting social groups, we show that both females and males harbour bacteria across the continuum of their internal reproductive tracts, and that these assemblages are distinct from the gut microbiota. We find evidence for spatial structure in female reproductive tract microbiota, while male reproductive tract and ejaculate microbiota are more homogenous, suggesting a potential for sexual conflict between females and males. We also report that reproductive tract bacteria are sexually transmitted in social groups of red junglefowl, and that individuals that fail to secure a partner diverge in their cloacal microbiota from the rest of the mating population. Combined, our findings highlight the importance of exploring bacterial communities in the context of host evolution, and spark hypotheses about the sex-specific costs and benefits of exchanging bacteria during mating.

The role of host genetics in the development of the infant gut microbiome

Presented by: Aaron Walsh

The infant gut microbiome is crucial for the maturation of the host immune system, and dysbiosis of the infant gut microbiome has been linked to autoimmunity later in life. The infant gut microbiome, itself, is shaped by a number of factors, including the mode of delivery, breastfeeding, and antibiotics. However, it is unclear if host genetics plays a role in shaping the infant gut microbiome, although studies in adults have reported that a handful of taxa are associated with mutations in genes which are involved in immunity. The aim of our study is to determine if host genetics interacts with the infant gut microbiome. We genotyped 902 infants using an Immunochip, and we tracked changes in their gut microbiomes over the first 3 years of life using shotgun metagenomics. Subsequently, we employed linear mixed-effect models to identify microbiome-genotype associations. We show that microbiome-genotype associations were strongest during the first 18 months of life, and we report that the rates at which a subset of species changed over time varied as a function of host genotype. Our results support a role for host genetics in the development of the infant gut microbiome.

The modulating role of the gut microbiome in body weight responses to physical activity

Presented by: Kai Wang

stipes putredinis. Individuals with a higher abundance of A. putredinis showed a more pronounced response to PA level in lowering BMI, fat mass percentage, short- and long-term body weight change, and plasma HbA1c level. A. putredinis was found to contribute in 75%-50% of the microbial enzymes within the five Glycolysis pathways.

Conclusions: Our findings suggest that individuals with a higher A. putredinis abundance may have a better body weight response to PA; the modulating role of A. putredinis may be partly attributed to its roles in Glycolysis. More studies are needed to elucidate the potential of A. putredinis as a probiotic in improving body weight response to PA.

Figure 1. Alistipes putredinis abundance modulates the associations of physical activity (PA) with body weight measures and plasma biomarkers. The interactions between PA and A. putredinis abundance (with median level as cutoff for low and high abundance) are significant in relation to all of body mass index (BMI), fat mass percentage, short-term and long-term body weight changes, and plasma hemoglobin A1c (HbA1c) level. a, The interaction between recent total PA and A. putredinis abundance in relation to BMI. b, Recent total PA levels in relation to BMI among participants with low and high A. putredinis abundance separately. Box plot centers show medians of the PA measures with boxes indicating their inter-quartile ranges (IQRs), upper and lower whiskers indicating 1.5 times the IQR from above the upper quartile and below the lower quartile, respectively. c, Association between recent total PA and BMI according to A. putredinis abundance. The dots in the plot indicate beta coefficients in the multivariable-adjusted generalized linear mixed-effects regression models, with error bars indicating upper and lower limits of their 95% confidence intervals. Beta coefficients and P_interaction were calculated from multivariable-adjusted generalized linear mixed-effects regression models while adjusting for age, smoking, total energy intake, probiotic use, antibiotic use, and Bristol stool scale. d, Associations between PA levels with other body weight measures, including fat mass percentage, short-term body weight change (6-month weight change), long-term body weight change (weight change between age 21 and stool collection), plasma HbA1c and high-sensitivity C-reactive protein (CRP) levels.

Characterizing microbial community viability with RNA-based high-throughput sequencing

Presented by: Ya Lea Wang

Characterization of microbial community viability is of great importance: essentially all sequence-based technologies do not differentiate living from dead microbes, whereas the functions and phenotypes of microbial communities (including the human microbiome) are defined by biochemically active (“viable”) organisms. As a result, our understanding of microbial community structures and their potential mechanisms of transmission between humans and our surrounding environments remains incomplete. As a potential solution to this issue, 16S RNA-based amplicon sequencing (not rRNA gene, i.e. 16S-associated DNA) has been proposed as a method to quantify the viable fraction of a microbial community, but its reliability has not been evaluated systematically.

Here, we present our work to benchmark 16S-RNA-seq (targeting 16S rRNA transcripts and genes for parallel RNA and DNA sequencing) for viability assessment in synthetic and realistic microbial communities. In synthetic communities, we found that 16S-RNA-seq successfully reconstructed the mixtures of heat-killed Escherichia coli and Streptococcus sanguinis. We further applied this technique to swabbings of natural microbial communities (computer screens and mice, soil, and saliva) spiked with known concentrations of living and heat-killed E. coli to evaluate its performance under variable biomass, chemical background and diversity conditions. No significant compositional differences were explained by the 16S-RNA assessment, suggesting that 16S-RNA-seq is not appropriate for viability assessment in complex communities. Results were slightly different in our validation using environmental samples of similar origins (i.e. from Boston subway systems), samples were differentiated both by environment type as well as by library type, though compositional dissimilarities between DNA and RNA samples remained low. Overall, these results show that 16S-RNA-seq has promise, but that previous literature assuming that 16S-rRNA amplicons are directly, quantitatively enriched for viable microbes is likely incorrect. Potentially due to the stability of this uniquely non-protein-coding RNA or its abundance being highly non-correlated with underlying microbial cell count, 16S rRNA amplicons do not reflect microbial viability outside of very simple, synthetic “communities.”

We are currently continuing this work to develop new RNA amplicon-seq markers based on protein-encoding genes such as rpoB and cpn60, as well as to improve viability assessment with multi-omic integration, e.g. combining amplicon-seq with functional indicators such as metatranscriptomic and metaproteomic profiles. These can circumvent some of the current limitations of 16S-RNA-seq, providing a complementary definition of viability, and directly observing activities such as virulence, pathogenicity, or antimicrobial resistance that are not captured by amplicon sequencing.

The Harvard T.H. Chan School of Public Health Microbiome Analysis Core

Presented by: Jeremy Wilkinson

The Microbiome Analysis Core at the Harvard T.H. School of Public Health was established in response to the rapidly emerging field of microbiome research and its potential to affect studies across the biomedical sciences. The Core’s goal is to aid researchers with microbiome study design and interpretation, reducing the gap between primary data and translatable biology. The Microbiome Analysis Core provides end-to-end support for microbial community and human microbiome research, from experimental design through data generation, bioinformatics, and statistics. This includes general consulting, power calculations, selection of data generation options, and analysis of data from amplicon (16S/18S/ITS), shotgun metagenomic sequencing, metatranscriptomics, metabolomics, and other molecular assays. The Core has extensive experience with microbiome profiles in diverse populations, including taxonomic and functional profiles from large cohorts, quantitative ecology, multi’omics and meta-analysis, and microbial systems and human epidemiological analysis. By integrating microbial community profiles with host clinical and environmental information, we enable researchers to interpret molecular activities of the microbiota and assess its impact on human health.

Identifying strain-specific functional genes in colorectal cancer

Presented by: Yan Yan

Changes in the gut microbiota have been associated with colorectal cancer (CRC), but neither the causal mechanisms nor corresponding microbial strains and small molecule products have been elucidated for CRC. We have developed a new strain-level meta-analysis using stool metagenomic profiles of 600 CRC patients, 143 with precancerous adenomas, and 662 healthy controls from nine recently published CRC microbiome studies. We created the MMUPHin framework to jointly normalise these datasets and identify potential consistently significant links between CRC neoplasia, severity, and microbial species and strains. We identified several species as novel CRC biomarkers including several typical oral species. We observed that CRC cases were depleted in geographically-specific Prevotella copri subtype carriers. A group of functional genes unique to subsets of Escherichia coli strains was associated with CRC phenotypes, comprising annotations to transporters, type II secretion systems, flagellar and sulfur metabolism. This study adds further evidence to the hypothesis that strain-level genomic variation in gut microbes may be a major driver in the initiation or development of CRC.

Deletion of innate effector serum amyloid A alters gut microbiome and drives metabolism in mice

Presented by: Yue Sandra Yin

Background: The serum amyloid A (SAA) proteins, mostly produced in the liver, are acute-phase reactants. SAA also is expressed in the intestinal epithelium, which is an interface between gut microbes and host immunity. SAA stimulates T_H17 cells and functions as an inflammatory marker in infectious disease and metabolic disorders. Here, using two murine models, we investigated the role of SAA in mediating host responses and metabolism and the intestinal microbiota.

Methods: In germ-free (GF) and conventional (CONV) C57BL/6 mice, we assessed ileal and colonic SAA expression over time. Then we examined microbiota perturbation and microbiota-mediated phenotypes comparing wildtype (WT) and SAA1/2^-/- (KO) mice derived from Het/Het crosses to ensure common ancestry. WT and KO mice were either reared separately or co-housed post-weaning. Dextran sodium sulfate (DSS) colitis was induced in a separate cohort of WT and KO mice. We monitored body weight and colitis development, characterized the fecal microbiome, and measured lipid levels and expression of inflammatory marker genes.

Results: GF and CONV mice expressed differential microbiota-dependent regulation of SAA subtypes in the ileum and colon. SAA expression was depressed in the absence of microbes in the ileum but increased in the colon. SAA KO led to significantly higher post-weaning weight gain (with effects in females>males), and cohousing diminished this effect, suggesting a critical role of gut microbes. Microbial community structure differed in the WT and KO mice, with specific taxonomic differences. In the KO mice, expression of genes indicative of adipocyte differentiation and inflammation was increased in white adipose tissues. DSS treatment led to increased colonic shortening and slower recovery in the KO mice.

Conclusion: Our results suggest that intestinal SAAs have major effects on local inflammation and microbiome characteristics, and mediate microbiota-dependent effects on host metabolism through alterations of inflammatory cytokines, adipogenesis, and lipid cycling.

The colorectal cancer-associated microbiome

Presented by: Young Caroline

In this talk, Caroline will introduce the CRUK Grand Challenge team “OPTIMISTICC” which is investigating over the next 5 years the mechanisms and therapeutic potential of the CRC-associated microbiome.

She will then discuss the results from two recently published studies, one showing the CRC screening potential of the faecal microbiome, and the other investigating the CRC-associated microbiome of non-Western countries.

References

https://cancergrandchallenges.org

https://optimisticc.org

Young et al Clinical Cancer Research 2021 PMID: 33658300

Young et al Genome Medicine 2021 PMID: 33593386

A cross-link between dietary sodium, gut microbiome, and heart failure

Presented by: Lufei Young

Background: Inflammation plays a central role in the development of heart failure (HF). Inflammation can also directly and indirectly modulate the bacterial composition of the human microbiome. Evidence shows high sodium intake contributes to progression of HF through inflammation.  However, the mechanism through which high salt diet influences vascular inflammation in HF has not been fully understood. The purpose to of the study is to examine the relationships between salt intakes and gut bacterial composition in HF patients.

Methods: This is a retrospective study using data collected from 90 HF patients participating cardiac rehabilitation. The daily sodium intake was assessed by 24-hour urine excretion. Fecal samples were collected and gut microbiota was assessed through 16sRNA sequencing. Gut microbiota data and 24-hour urinary sodium excretion were log-transformed and gut microbiota data were further standardized before statistical analysis. Mixed-effects models were used to assess the association of 24-hour urinary sodium excretion with gut microbiota with adjustment of age, race, sex, body mass index, group assignment, visit, and diet.

Results: Gut microbiota were measured in a total of 119 samples from 80 HF patients, who were aged 64.2 ± 10.4 years old, 56% male, and 58% Caucasian. The average ejection fraction (EF) was 46.7 ± 15.4 %. We found a significant correlation between sodium intake and the composition of gut proteobacteria (β = 0.57; P = 0.026) among HF patients.  HF patients who had higher daily sodium intake had increased proportions of proteobacteria in their gastrointestinal (GI) system.

Discussion:

The significant correlation between sodium intake and the increased proportion of proteobacteria may be explained by the direct impact of high sodium intake on the growth of proteobacteria and/or indirect effect through the inflammation process. The inflammatory cells release reactive nitrogen species which are used by proteobacteria for anaerobic respiration and growth. As a result, the growth of proteobacteria is a biomarker of vascular inflammation caused by high sodium intake in HF patients.

Conclusion: The role of gut microbiota in heart failure prognosis may help explain the link between dietary sodium intake and heart failure prognosis. Increased proportions of proteobacteria may be a sensitive indicator of worsening HF caused by high sodium intake. Additional research is needed to support our finding.

Identifying Novel Bioactive Microbial Gene Products in Inflammatory Bowel Disease

Presented by: Yancong Zhang

Microbial communities and their associated bioactive compounds are often disrupted in conditions such as inflammatory bowel diseases (IBD). However, even in well-characterized environments (e.g. the human gastrointestinal tract), more than one-third of microbial proteins are uncharacterized and often expected to be bioactive. Here, we introduce a method to identify putative bioactive gene products in any microbial community and use it to prioritize potentially bioactive novel proteins from the human gut during IBD, beginning with a catalog of 1,665,223 protein families assembled from 1,595 metagenomes in the Integrative Human Microbiome Project (HMP2). Remarkably, 1,157,695 (~70%) of these proteins were uncharacterized, including those with strong homology to known functionally uncharacterized proteins (24%), potentially novel proteins with weak homology (33%), and completely novel proteins without significant homology (12%). We assigned putative annotations to these uncharacterized families using a combination of guilt-by-association, taxonomic binning, secondary structure analysis, and environmental parameters or phenotypes, ultimately leaving only 30,567 protein families (2.6%) still functionally and taxonomically unannotated. >340,000 protein families were prioritized as potentially bioactive with respect to gut inflammation during IBD by integrating evidence from ecological properties and environmental or phenotypic properties. ~39% of the prioritized novel proteins expanded the pangenomes of common gut taxa, and >90% of the remainder with unclear taxonomy were assigned at least one putative biochemical annotation. To validate our prioritized microbial gene products, we used a combination of metagenomics, metatranscriptomics and protein structure analysis to provide evidence of bioactivity for a subset of proteins involved in the crosstalk processes between host and microbial communication, such as adherence/invasion processes and secreted proteins. This methodology is fully generalizable to other environmental microbial communities and human disease phenotypes, and we provide an open source implementation as MetaWIBELE (Workflow to Identify novel Bioactive Elements in the microbiome). Prioritized results here provide thousands of new candidate microbial proteins likely to interact with the host immune system in IBD, expanding our understanding of potentially bioactive gene products in chronic disease states and offering a rational and targeted compendium of potential therapeutic compounds.