Poster Session 2024

Presenter Name	Poster Title
Mirae Baichoo	Understanding role of diet on microbiome injury and patient outcome for hospitalized Allo-HCT patients.Anqi Dai, Mirae Baichoo, William Jogia, Teng Fei, Nicholas Waters, Madhumitha Rangesa, Anna Ballweg, Sukanya Sahu, Jonas Schluter, Marcel RM van den Brink, Jonathan U Peled
Amrisha Bhosle	Response of the gut microbiome and metabolome to dietary fiber in healthy dogsAmrisha Bhosle, Matthew I. Jackson, Aaron Walsh, Eric A. Franzosa, Curtis Huttenhower, Dayakar V. Badri
Marina Chen	Host-Childcare Microbiome Interactions Highlighted by Using Long Read SequencingMarina Chen, Ya Wang, Kelsey N. Thompson, Jeremy E. Wilkinson, Jacob Nearing, David C. Christiani, Eric A. Franzosa, John D. Spengler, Curtis Huttenhower
Slater L. Clay	Acetoacetate alters the colonic microbiota, expands intra-tumoral MAIT cells and inhibits colorectal cancerSlater L. Clay, Sena Bae, Geicho Nakatsu1,2, Diogo Fonseca-Pereira1,2, Monia Michaud1,2, Meghan MacDonald1,2, Jonathan N. Glickman3, and Wendy S. Garrett1,2
Teng Fei	FLORAL: Scalable Log-ratio Lasso Regression Enhances Microbial Feature SelectionTeng Fei, Tyler Funnel, Nicholas Waters, Sandeep Raj, Marcel van den Brink,
Adele Gabba	Development of a structurally-defined polymer platform to boost humoral immunity against non-peptidic antigens by T cell primingAdele Gabba, Valerie Lensch, Chae Rin Kim, Laura L. Kiessling
Amit K. Gandhi	Structural biology-based approaches in understanding CEACAM1 oligomerization and binding with microbial ligands Amit K. Gandhi, Zhen-Yu J. Sun, Yu-Hwa Huang, Richard S. Blumberg.
Isabella M. Goodchild-Michelman	Probiotic-induced functional alterations in the gut microbiome of preterm infantsIsabella M. Goodchild-Michelman, Shirin Moossavi, Emily Mercer, Belal Alshaikh, Luis Murguia Favela, James Kellner, Thierry Lacaze-Masmonteil, Laura Sycuro, Hussein Zein, Leonora Hendson, Thomas A. Tompkins, Marie-Claire Arrieta, Ali R. Zomorrodi
Yordan Hodzhev	Terpenoid Synthesis and Antigen Initiation: Microbial Contributions to Inflammatory and Oncogenic Processes in the LungsYordan Hodzhev, Borislava Tsafarova, Vladimir Tolchkov, Vania Youroukova, Silvia Ivanova, Dimitar Kostadinov, Nikolay Yanev, Mariya Nacheva-Sokolova, Stefan Tsonev, Maya Zhelyazkova, Stefan Panaiotov
Michael James	The Analytical Chemistry Core at Harvard Medical SchoolMichael James
Jordan Jensen	Integrating reference- and assembly-based methods for improved viral identification from metagenomes, metatranscriptomes, and viromesJordan Jensen, Ya Wang, Moreno Zolfo, Philipp C. Münch, Nicola Segata, Eric A. Franzosa, Curtis Huttenhower
Taylor Lander	Comparative Analysis of Skin Microbiome in Pancreatic Cancer Patients, Individuals with Other Cancers, and Cancer-Free Controls: A Pilot StudyTaylor Davis, Katherine Decker, Dana Hosseini, Gayle Jameson, Erkut Borazanci
Steven Medina	The Harvard T.H. Chan School of Public Health Microbiome Collection CoreSteven Medina, Curtis Huttenhower
Zhendong Mei	A Cross-Cohort Multi-Omics Study of Diet, Gut Microbiome, and Metabolomics in Type 2 DiabetesZhendong Mei, Amrisha Bhosle, Fenglei Wang, Danyue Dong, Jacob T. Nearing, Qibin Qi, Robert D. Burk, Robert C. Kaplan, Curtis Huttenhower, Dong D Wang
Xochitl C. Morgan	The Harvard T.H. Chan School of Public Health Microbiome Analysis Core Xochitl C. Morgan, Lauren J. McIver, Thomas Kuntz, Curtis Huttenhower
Jacob T. Nearing	Capturing Primer-Specific Ambiguity in Taxonomic Classification for Amplicon SequencingJacob T. Nearing, Kelsey N. Thompson, Artemis S. Louyakis, Amrisha Bhosle, Tobyn Branck, Dayakar V. Badri, Eric A. Franzosa, Christoph Brockel, Curtis Huttenhower, Meghan I. Short
William Nickols	Refining and extending generalized multivariate linear models for meta-omic discovery with MaAsLin 3William A. Nickols, Jacob T. Nearing, Kelsey N. Thompson, Curtis Huttenhower
Ana Nogal	Mapping the Gut Microbiome signature along the colorectal adenoma-carcinoma continuumAna Nogal, Kelsey N Thompson, Kai Wang, Mengxi Du, Yujia Lu, Eric B. Rimm, Wendy S. Garrett, Andrew T. Chan, Curtis Huttenhower, Mingyang Song
Alican Özkan	Modulation of Acute Radiation Syndrome in Human Intestine by Gut Microbiome and a Probiotic Revealed using Organ ChipsAlican Özkan, Arash Naziripour, Thomas Mathiassen, Nina LoGrande, Viktor Horvath, David Breault, Girija Goyal, and Donald E. Ingber
Yabdiel A. Ramos-Valerio	The Effect of Sodium Butyrate on the Cell Viability of Triple-Negative Inflammatory Breast CancerYabdiel A. Ramos-Valerio, Mikaela A. Ríos-Colón, Josue Pérez-Santiago, and Esther A. Peterson-Peguero
Rezaul Karim Ripon	Seafood intake and Community Drinking water supply is related to PFAS Exposure and its Reproductive Cancer outcomes: Epidemiological perspective from NHNAES 2010-2018Rezaul Karim Ripon
Utkarsh Sharma	New ultrasensitive assay to measure host immune profile from fecesUtkarsh Sharma, Stephanie J Zhang, David R Walt, Travis E Gibson
Jiaxian Shen	Concurrent and habitual diet differentially associate with microbial Multi-omic Profiles in Inflammatory Bowel Disease(IBD)Jiaxian Shen, Etienne Nzabarushimana, Hanseul Kim, Hannah VanEvery, Yiqing Wang, Kelsey N. Thompson, Andrew T. Chan, Curtis Huttenhower, Long H. Nguyen
Ya Wang	Using housekeeping gene cpn60 as a marker for microbial community profiling and viability assessmentYa Wang, Kelsey N. Thompson, Sagun Maharjan, Marina Chen,  Meghan I. Short, Yancong Zhang, Jacob Nearing, Eric A. Franzosa, Curtis Huttenhower
Yin Yuan	Gut-derived lipopolysaccharide: Tthe initiator of the Cytokine storms in acture-on-chronic liver failureYin Yuan, Xiaolin Li and Shuo Ni
Yancong Zhang	Response of the gut microbiome to acute enteric pathogen infection and antibiotic treatment Yancong Zhang, Sagun Maharjan, Jane M. Michalski, Taylor K.S. Richter, Wilbur H. Chen, Anup Mahurkar, Eric A. Franzosa, Curtis Huttenhower, David A. Rasko

Understanding role of diet on microbiome injury and patient outcome for hospitalized Allo-HCT patients

Presented by: Mirae Baichoo

View Abstract
Nutrition is a key determinant of microbiome composition, but this relationship is poorly understood in humans under perturbations such as antibiotics, intestinal inflammation, anorexia, or hospitalization. There exists profound intestinal-microbiota disruption that accompanies hematopoietic cell transplantation (HCT) and its related treatments, including antibiotics and chemotherapy. Using paired nutrition data and sequenced stool samples from 173 hospitalized HCT patients we have uncovered a link between increased sucrose intake and a reduction in microbiota ɑ-diversity in patients receiving antibiotic treatment. Furthermore we observed these patients have an increased likelihood of Enterococcus domination events, an observation we previously reported as a predictor of mortality in this population. We have experimentally recapitulated this antibiotic-induced Enterococcus domination and loss of diversity in mice, and are exploring the metagenomic and metatranscriptomic profiles of the cecal-microbiome before and after injury. Initial data suggest that the antibiotic treatment appears to drive the early transcriptional response regardless of dietary intervention, however a distinct sucrose-dependent transcriptomic profile emerges on day 3 after antibiotic exposure. This suggests that diet, and thus nutritional intervention, may play a role in determining community recovery following disruption by antibiotics. Further explorations can help us identify specific mechanisms and suggest strategies for promoting healthy microbiota recovery after dysbiotic incidents and improving clinical outcomes following hematopoietic cell transplantation.

Response of the gut microbiome and metabolome to dietary fiber in healthy dogs

Presented by: Amrisha Bhosle

Dietary fiber has been shown to expand beneficial microbial activity in the gut and is being explored to maximize health-related benefits from the microbiome in both humans and companion animals. However, a clear understanding of the precise interactions among fiber-containing diets, specific fibers, and microbiome composition and function is lacking. To fill this knowledge gap, we analyzed fecal metagenomic and metabolomic profiles from 18 healthy dogs at 13 time points each (totaling 226 samples) that were fed 12 test foods containing different fiber sources and quantities (5-13% fiber on an as-fed basis) belonging to three food groups (high starch/low fiber, medium starch/medium fiber, and low starch/high fiber). Taxonomic and functional profiling identified taxa and functions whose abundances were associated either with overall fiber intake or specific fiber compositions. Short-chain fatty acids (SCFAs), acylglycerols, and intermediate products of fiber degradation including sugars (arabinose, xylulose, fucose) and intercalating polyphenols (genistein, hesperidin, limonin, naringenin, and secoisolariciresinol) were enriched in response to intake of insoluble fiber. Some of these were also associated with affected microbes in particular food groups. Eleven species were significantly enriched in response to only one food group. Accordingly, enrichment of beneficial metabolites such as SCFAs was more pronounced in response to these fiber sources, highlighting the importance of interactions between specific dietary components and individual microbes. That is, the production of beneficial metabolites was dependent on both the presence of the appropriate pre-existing microbiota, and the introduction of an appropriate dietary substrate. Correspondingly, the response of microbes to dietary macronutrients varied across subjects, as did the metabolomic consequences of the foods and their overall influence on the microbiome. These data are useful for directing population-wide dietary modifications and for personalized health targeting, with implications for other animals and humans.

Host-Childcare Microbiome Interactions Highlighted by Using Long Read Sequencing

Presented by: Marina Chen

Early-life exposure to microorganisms plays a crucial role in shaping children’s health by instructing immune maturation and modulating the risk of disease development. Most preschool-aged children spend seven to ten hours a day in childcare centers, yet the microbial communities in childcare settings and how they interact with human and human-associated microbiomes have yet to be fully elucidated. A limited number of previous studies have primarily focused on bacterial communities, using amplicon-based profiling methods, largely due to the low biomass of these communities in this built-environment setting. These studies thus omit functional or genetic information and non-bacterial community members. Additionally, none of the prior research has incorporated host-associated phenotypes and microbial profiles to investigate transmission. Expanding upon these efforts, we collected a variety of indoor and outdoor environmental samples from two childcare centers, as well as nasal and oral swabs from 34 participating children aged two to four. We profiled all samples using PacBio full-length 16S rRNA gene and internal transcribed spacer (ITS) sequencing, respectively, for bacterial and fungal community members, and a subset of pooled samples using shotgun metagenomic sequencing including both short- and long-read metagenomics. This approach not only offered enhanced resolution to identify previously unknown aspects of the microbial communities in childcare environments, but also provided additional insight regarding the functional potential in the ecosystem. Current results revealed distinct microbial profiles associated with different host-associated and environmental communities. Most of shared species between host and environmental communities were identified to be specific host-associated ones, including those associated with host food consumption, such as Lactococcus lactis and Streptococcus thermophilus. These results suggest potential microbial transmission and interactions via host shedding. Our work thus expands the understanding of microbial ecology in childcare environments and these communities’ relevance to childhood health. The knowledge gained from this study can allow us to identify potential environmental reservoirs of pathogens, track microbial transmission routes, and develop targeted interventions to benefit early-life human health.

Acetoacetate alters the colonic microbiota, expands intra-tumoral MAIT cells and inhibits colorectal cancer

Presented by: Slater L. Clay

The ketones beta-hydroxybutyrate (BHB) and acetoacetate (AcAc) have wide ranging effects on host and microbial physiology. Ketogenic diets and exogenous BHB can be pro- or anti-tumorigenic, but the potential for acetoacetate to alter anti-cancer immunity is unclear. AcAc can function as a signaling molecule and an energy source for host, microbial and tumor cells. We hypothesized that in vivo administration of AcAc will have both systemic and site-specific effects, impacting the stool microbiota, immune function, and tumor development.
Oral administration of an esterized form of AcAc (EAA) increased serum, fecal and tumor AcAc concentrations, and reduced tumor burden in two genetic models of colorectal cancer. In host cells, scRNA-Seq and flow cytometry identified changes in immune, tumor, epithelial, and stromal cells within the tumor microenvironment (TME). Mucosal associated invariant T (MAIT) cells were increased in treated tumors, and MAIT cell expression of IFNg, granzymes and perforins was higher than vehicle-treated controls. AcAc treatment also altered the microbiota. 16S rRNA gene amplicon analysis revealed enrichment of fecal Bifidobacteria following treatment. In vitro cultures supplemented with AcAc increased Bifidobacteria growth in a dose-dependent manner, while other taxa were not affected by supplementation. This suggests AcAc alters microbial composition by providing a growth advantage to specific taxa. Subsequently, metabolomics studies identified altered abundance of Bifidobacteria metabolites in multiple sites. In vivo stable isotope tracing of orally administered 13C EAA revealed 13C incorporation into a range of tumor metabolites including TCA cycle intermediates and amino acids.
Together, these results support that exogenous AcAc reduces neoplastic progression, alters colonic microbial composition, and promotes MAIT cell cytotoxicity. This reveals a connection between ketones, the microbiota and unconventional T cells. Metabolomics data, including results from in vivo 13C EAA stable isotope tracing, provided further insights about AcAc metabolism, and have informed mechanistic studies. The aims of ongoing work include determining how ketones regulate microbial metabolism and enhance anti-tumor MAIT functions. These studies will reveal metabolic processes that could inform ketone treatment or identify downstream immunometabolic pathways as novel therapeutic targets.

FLORAL: Scalable Log-ratio Lasso Regression Enhances Microbial Feature Selection

Presented by: Teng Fei

Identifying predictive microbial biomarkers of patient outcomes from high-throughput microbiome data is of high interest in contemporary cancer research. We present FLORAL, an open-source computational tool to perform scalable log-ratio lasso regression and microbial feature selection for continuous, binary, time-to-event, and competing risk outcomes. The proposed method adapts the augmented Lagrangian algorithm for a zero-sum constraint optimization problem while enabling a two-stage screening process for extended false-positive control. In extensive simulation and real data analyses, FLORAL achieved consistently better false-positive control compared to other lasso-based approaches, and better sensitivity over popular differential abundance approaches for datasets with smaller sample size. We also demonstrate the practical utility of FLORAL in handling longitudinal microbiome data in a survival analysis of MSKCC allogeneic hematopoietic-cell transplant (allo-HCT) cohort. The R package is available on CRAN and at https://vdblab.github.io/FLORAL/.

Development of a structurally-defined polymer platform to boost humoral immunity against non-peptidic antigens by T cell priming

Presented by: Adele Gabba

Conjugated vaccines sidestep the challenges of handling live pathogens, offering a safer and highly targeted approach to disease prevention. They represented a major breakthrough in achieving IgG antibody production against non-peptide epitopes, haptens, by invoking T cell help. Haptens random conjugation to carrier proteins can induce a T cell mediated humoral response by generating peptide-specific and hapten-specific T cells. While numerous efforts have been focused towards increasing immunogenicity of haptens, studies involving random functionalization of proteins do not tease out molecular level understanding of the criteria for hapten-specific T cell priming and impact of T cell specificity in humoral immunity. To overcome this limitation, we designed a structurally-defined polymer platform displaying position-specific haptenization of the MHCII epitope ova323-339 to study hapten-specific T cell induction and the corresponding impact on antibody production. This platform enabled a systematic study of B and T cell recognition and immune outcome and lead to the identification of the polymer pDNP-OVA2. pDNP-OVA2 outperformed a classical protein carrier platform in generating IgG titers by simultaneously priming B and T cells against a small molecule. Furthermore, it induced a signature signaling cascade that generated high titer of IgG3, an antibody subclass with superior effector function indispensable for neutralization of encapsulated bacteria like Streptococcus pneumoniae (SPn) and Haemophilus influenzae type b (Hib). This polymer vaccine platform can be leveraged to efficiently present a wide range of non-classical antigens to T cells and achieve better humoral immunity.

Structural biology-based approaches in understanding CEACAM1 oligomerization and binding with microbial ligands

Presented by: Amit K. Gandhi

Human (h) carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) mediates homophilic and heterophilic interactions with various microbial and host ligands and is a very important immunoreceptor important in mediating immune T cell tolerance. To understand hCEACAM1 mediated interactions, we decipher hCEACAM1 structural approached to predict how GFCC’ face regulates homodimerization and heterophilic associations. In addition, associations through’ face enables highly flexible ABED face interactions to arise. Structural modeling and predict that such oligomerization and microbial binds are not impeded by the presence of carbohydrate side- chain modifications. In addition, using UV spectroscopy and NMR studies, we show that oligomerization is further facilitated by the presence of a conserved metal ion (Zn++ or Ni++) binding site on the G strand of the FG loop. Together these studies provide therapeutical insights on how GFCC’ and ABED face interactions together with metal ion binding may facilitate hCEACAM1 oligomerization beyond dimerization and facilitate microbial and host ligands binding.

Probiotic-induced functional alterations in the gut microbiome of preterm infants

Presented by: Isabella M. Goodchild-Michelman

Preterm infants exhibit a distinct gut microbiomes characterized by a low microbial load and reduced microbial diversity. While probiotics have shown promise in transforming preterm infants’ microbiomes to resemble those of full-term infants, their influence on microbiome functionality remains underexplored. This study aimed to investigate the impact of probiotics on the functional development of the gut microbiota in pre-term infants. Our population study includes 105 preterm infants (gestational age 23-36 weeks) from the observation longitudinal BLOOM study, 68 of whom received a multi-strain probiotic treatment for the first eight weeks post-birth. We developed GEnome-scale Models (GEMs) of metabolism for each probiotic strain and species-resolved GEMs for the infants’ microbiota from 762 stool samples, incorporating known Human Milk Oligosaccharides (HMOs) degradation pathways. We simulated each GEM under a breastmilk diet. Species abundance analysis revealed that probiotics accelerated gut microbiota maturation in preterm infants. Metabolite profiling in feces using GEMs highlighted functional differences between control and probiotic groups, with notable increases in several metabolites in the latter. GEMs additionally pinpointed key microbial species and probiotic strains crucial for producing modulatory metabolites like short-chain fatty acids (SCFAs) and HMO degradants. Distinct microbial contributions to metabolite production were observed between the groups. Finally, shadow price analysis in GEMs indicated that the probiotic-treated microbiomes had enhanced capabilities for producing SCFAs and degrading HMOs, suggesting a more adaptable metabolic environment. Our study offers novel insights into how probiotics fundamentally shape the functional landscape and dynamics of pre-term infants’ gut microbiota development.

Terpenoid Synthesis and Antigen Initiation: Microbial Contributions to Inflammatory and Oncogenic Processes in the Lungs

Presented by: Yordan Hodzhev

Several bacterial genera, such as Veillonella, Prevotella, Cutibacterium, Streptococcus, etc. are often associated with atypical inflammation and carcinogenesis. Studies on microbiomes from blood and bronchoalveolar lavage fluid (BAL) in patients with sarcoidosis or lung cancer suggest that these microbes contribute to granulomatous inflammation. The terpenoid pathway, which is a critical metabolic route involved in energy storage, was identified as a common factor among these organisms.
The aim of this study was to assess the potential impact of microbiome dysbiosis, specifically through the terpenoid synthesis pathway, on pulmonary carcinogenesis.
To examine gene interactions and the metabolic capabilities of microbes, we applied flux balance analysis (FBA) models under normal and stress conditions.
Comparative analysis showed significant differences in the metabolic potentials of microbiomes from patients with pulmonary diseases compared to healthy controls. The study highlighted modifications in the terpenoid pathway as potential links between microbiome dysbiosis and lung cancer development.
These findings emphasize the influence of microbial metabolic pathways, specifically terpenoid synthesis, on pulmonary carcinogenesis. This study highlights the important role of microbiome dysbiosis in the development of lung cancer and suggests potential avenues for future therapeutic interventions.
Keywords: terpenoid synthesis, pulmonary carcinogenesis, microbiome dysbiosis, Flux balance analysis (FBA)
Acknowledgements: This work was supported by the Bulgarian National Science Fund: grant numbers KP-06-DV/10-21.12.2019 and KP-06-Н73/5 5.12.2023

The Analytical Chemistry Core at Harvard Medical School

Presented by: Michael James

The Analytical Chemistry Core (ACC) in the department of Biological Chemistry and Molecular Pharmacology at Harvard Medical School focuses on serving the needs of investigators at HMS and all the Harvard affiliated Institutions by providing consultation, training, and access to instrumentation for the identification, quantitation and screening of small molecules using mass spectrometry techniques.

Integrating reference- and assembly-based methods for improved viral identification from metagenomes, metatranscriptomes, and viromes

Presented by: Jordan Jensen

Capturing an accurate representation of the viral members of a microbial community presents significant experimental and computational challenges. Sample preparation approaches for virus-like particle (VLP) enrichment vary greatly in their efficiency among protocols and environments, and sequences from any technology (metagenomic, metatranscriptomic, or VLP enrichments) can be difficult to identify computationally. Limitations include small viral genome size, and subsequently a small proportion of genetic content in samples; lack of universal marker genes; multiple nucleic acid backbone types; rapid evolution, recombination, and sequence divergence; and most prominently, a lack of well-characterized viral reference databases.
To address these limitations, we developed BAQLaVa (Bioinformatic Application for Quantification and Labeling of Viral taxonomy), which integrates tired reference-based profiling to provide viral profiles from shotgun DNA or RNA sequencing (with or without enrichment). Reads are compared with both nucleotide and protein (translated) databases that are pre-screened for viral identification using a modification of the MetaPhlAn algorithm and reconciled with the most recent International Committee on Taxonomy of Viruses (ICTV) taxonomic rankings. We hope these methods will unlock as-yet-unaccessed information on viral community members from thousands of existing metagenomes and metatranscriptomes, as well as enabling more accurate characterization of future VLPs from a variety of microbial environments.

Comparative Analysis of Skin Microbiome in Pancreatic Cancer Patients, Individuals with Other Cancers, and Cancer-Free Controls: A Pilot Study

Presented by: Taylor Lander

Background: Several studies have reported the importance of the human microbiome in the overall health of its host. While recent studies have explored the microbiome’s role in various types of cancer compared to healthy patients, this study narrows the focus to pancreatic cancer. This study aims to characterize the skin microbiomes on the forehead and cheek of individuals from three groups: 1) patients with pancreatic cancer, 2) patients with other forms of cancer, and 3) patients without any form of cancer. The goal is to determine if the results from this trial could provide insight on associations of microbial flora with the state or severity of cancer, status of host immune system, or progress of an ongoing therapy, which could have therapeutic applications.

Methods: A total of 58 participants were enrolled in the study. Participants were given a questionnaire that prompted them to provide information including age, gender, ethnicity, race, weight, height, and status of skin health. An additional 60 control samples were drawn from an existing broader database of healthy skin samples at ProdermIQ to supplement the analysis. The participants were enrolled from three groups: cancer patients with pancreatic cancer, cancer patients with other types of cancer, and individuals without cancer. Skin microbiome samples from the forehead and cheek collection sites were processed and then analyzed by incorporating both statistical methods and machine learning techniques.

Results: A total of 150 samples were analyzed, including 79 samples from subjects with cancer and 71 samples from control subjects. The mean age of the control group was 60 years, and the mean age of the cancer group was 63 years. Characterization of the two analysis groups was further refined using observed features and alpha diversity metrics. The cancer group displayed a significantly higher mean alpha diversity compared to the control group. Our analysis showed that the following organisms were the most abundant across all samples: Cutibacterium acnes PMH5, Streptococcus sanguinis SK353, Staphylococcus aureus subsp. aureus NN50, Streptococcus mitis SK642, Snograssella alvi wkB12, Staphylococcus epidermidis NW32, Streptococcus anginosus ChDC B695, Streptococcus gordonii Challis CH1, Kingella oralis UB-38, Streptococcus porci DSM 23759, Cutibacterium acnes HL411PA1, Corynebacterium kroppenstedtii DSM 44385, Corynebacterium diphtheriae sv. mitis B-D-16-78, Gardnerella vaginalis 315-A, and Cutibacterium acnes HL053PA1. Organisms such as Streptococcus

mitis SK642, Snograssella alvi wkB12, and Streptococcus gordonii Challis CH1 were seen in abundance within the pancreatic and other cancer groups but not within the no cancer group. Streptococcus porci DSM 23759 and Kingella oralis UB-38 were seen significantly within the pancreatic and no cancer group but not within the other cancer group. Additionally, a machine learning classification model built on the microbiome data demonstrated a median F1 Score of 0.761 for accurately classifying the cancer (all types) versus control samples. Given that F1 scores above 0.70 are generally regarded as satisfactory, this result indicates the skin microbiome can be predictive of cancer status.

Conclusion: This analysis showed that there were significant differences in the skin microbiome of cancer patients versus patients without cancer. The cancer groups showed an increase in alpha diversity versus the no cancer group, and the machine learning model achieved a satisfactory F1 Score for differentiating the control and cancer samples . This could indicate the presence of dysbiosis in cancer subjects’ skin microbiomes due to their clear differentiation from the healthy skin microbiomes. Additional research could provide potential opportunities to develop biomarkers that can identify pancreatic and other types of cancer.

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

Presented by: Steven Medina

The Microbiome Collection Core at the Harvard T.H. Chan School of Public Health (HCMCC) was established in response to a strong demand among the research community for validated microbiome collection kit configurations and easy usability for in-home sampling. Under the umbrella of the Harvard Chan Microbiome in Public Health Center (HCMPH), HCMCC aims to support population-scale microbiome sample collection and expand our understanding of the microbiome to improve population health. The HCMCC has developed a multi carrier-compatible home stool and oral sample collection kit that permits cost-effect multi’omic microbiome studies, 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. By providing this customizable microbiome collection kit, we enable researchers to perform multiple different molecular assays and tailor collection plan to study-specific needs.

A Cross-Cohort Multi-Omics Study of Diet, Gut Microbiome, and Metabolomics in Type 2 Diabetes

Presented by: Zhendong Mei

The gut microbiome, interacting with dietary intake, modulates host metabolism and contributes to the pathogenesis of type 2 diabetes (T2D). Yet, large-scale multi-omics studies to examine these complex interactions are limited. Applying a validated data harmonization pipeline, we conducted a comprehensive study that integrates data on long-term habitual diet, gut microbiome, and circulating metabolomes from six studies of 4,929 participants with T2D, prediabetes, and normoglycemic status in the US, Europe, and Israel. Our analysis identified diet- and host-derived metabolites (e.g., quinate) and microbial-host co-metabolites (e.g., cinnamoylglycine and indole propionate) associated with T2D, independent of major risk factors. We also identified interactions between microbe and metabolite implicated in T2D risk. In addition, the inter-individual difference in the association of species (such as Roseburia inulinivorans) with T2D risk could potentially be explained by the strain-specific processing of metabolite implicated in the pathogenesis of T2D. Our study offers robust insights into the intricate interplay of diet, gut microbes, and their metabolites underlying the development of T2D in diverse populations. 

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

Presented by: Xochitl C. Morgan

The Microbiome Analysis Core at the Harvard T.H. Chan 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, and selection of data generation options, as well as analysis of data from amplicon (16S/18S/ITS), shotgun metagenomic sequencing, metatranscriptomics, metabolomics, and other molecular assays. The Microbiome Analysis Core has extensive experience with microbiome profiles in diverse populations, including taxonomic and functional profiles from large cohorts, qualitative 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.

Capturing Primer-Specific Ambiguity in Taxonomic Classification for Amplicon Sequencing

Presented by: Jacob T. Nearing

Amplicon sequencing, a common strategy to taxonomically profile microbial communities, is relatively low cost and high throughput, but it can present various biases, including primer incompatibility within specific taxonomic groups and the inability to differentiate between certain microbes due to low sequence variability. The identifiable taxa are often specific to given variable regions, resulting in differential, and often challenging, downstream taxonomic assignments. To help address these issues, we developed Parathaa (Preserving and Assimilating Region-specific Ambiguities in Taxonomic Hierarchical Assignments for Amplicons), which directly models the sequence ambiguities (similarities) associated with specific amplicon regions and allows for assignment to multiple ambiguous taxonomic labels. Parathaa accomplishes this by leveraging full-length amplicon sequence databases to build primer-specific phylogenies. Then, using those phylogenies, it identifies optimal taxonomic distance thresholds and assigns taxonomy to new representative sequences by placing them into the tree using pplacer. Thus, Parathaa captures biological ambiguities specific to the sequenced variable region of interest. Parathaa had greater performance than DADA2’s taxonomic classifier when applied to a synthetic dataset from across the bacterial kingdom, and it identified a higher proportion of species when analyzing a mock community dataset. Overall, Parathaa’s approach allows users to retain more information and understand potential sources of bias (i.e., sequence ambiguity) when classifying amplicon reads.

Refining and extending generalized multivariate linear models for meta-omic discovery with MaAsLin 3

Presented by: William A. Nickols

A common and important step in analyzing microbiome data is differential abundance testing, determining how the abundances of taxa change with respect to a community phenotype or environment. Differential abundance testing is complicated by the fact that microbiome data are usually compositional, sparse, right-skewed, and high-dimensional. Existing methods for differential abundance testing fail to model all of these properties of the data, including how both the abundance of a taxon and its prevalence—its probability of being present or absent in a sample—change in response to sample parameters. To bridge this gap, we have developed MaAsLin 3 (Microbiome Multivariable Associations with Linear Models) to simultaneously identify both prevalence and abundance associations in a biologically motivated and statistically principled manner. In addition to detecting prevalence differences, MaAsLin 3 enables more robust inference for abundance associations by accounting for compositionality with reference spike-ins or an iterative renormalization procedure. MaAsLin 3 also expands inferential abilities beyond traditional linear models by allowing users to test for microbial differences associated with ordered monotonic predictors and differences among more than two categorical groups. Across a variety of simulations, MaAsLin 3’s set of methods is more robust to the statistical properties of microbiome data than current state-of-the-art differential abundance methods. Additionally, when applied to a large dataset of stool samples from an inflammatory bowel disease cohort, MaAsLin 3 indicates that the vast majority of previous abundance associations are actually prevalence associations. In summary, MaAsLin 3 enables researchers to identify more specific and more accurate microbiome associations, especially in large and complex datasets.

MAPPING THE GUT MICROBIOME SIGNATURE ALONG THE COLORECTAL ADENOMA-CARCINOMA CONTINUUM

Presented by: Ana Nogal

Introduction: Adenomas are major precursors of colorectal cancers (CRC). Individuals after adenoma resection remain at a higher CRC risk than those with no adenomas. The gut microbiome is associated with CRC, but its dynamics over time following adenoma resection remain unknown. We aimed to characterize the patterns of species-level genome bins (SGBs) in patients with adenoma removal or CRC compared to healthy subjects.

Methods: We analyzed gut metagenomes of 354 patients after adenoma resection (mean years between resection and stool collection=12) and 354 matched polyp-free individuals from the Micro-N, a microbiome cohort within Nurses’ Health Study II (adenoma dataset). We also included publicly available metagenomes from 882 CRC cases and 929 healthy individuals from 11 external datasets. We calculated the standardized mean difference (SMD) between cases and controls for each SGB within each dataset and aggregated the effect sizes from the CRC datasets using a random-effects meta-analysis. To identify microbes with similar trends in CRC and adenoma cases, we employed a genetic algorithm to solve an optimization problem designed to reduce the SGB number while increasing the accuracy for distinguishing adenoma cases from controls based on the CRC case-control comparison. We assessed the associations between diet/lifestyle and the identified SGBs in the adenoma dataset using Spearman’s correlations.

Results: The microbiome profile of adenoma and CRC cases compared to their corresponding controls was correlated (rho=0.29, p<0.0001). We identified 41 SGBs with similar SMD trends in CRC and adenoma, including Blautia spp. and R. torques. A classifier based on the abundances and SMD values of these 41 SGBs in the CRC datasets showed moderate internal discrimination using leave-one-out cross-validation (area under the curve (AUC)=0.64) and similar discrimination in the adenoma dataset (AUC=0.67). Similar accuracy was noted when adenoma dataset-derived classifier was applied to distinguish CRC (AUC=0.61) and adenoma (AUC=0.61) from controls. For adenomas, the discriminatory accuracy was similar regardless of the time interval between resection and stool collection. However, CRC biomarkers specific to late-stage CRC and enriched in mucosa (e.g., F. nucleatum and P. micra) were not detectable in adenoma cases. SGBs’ enrichment in adenoma cases was inversely correlated with healthy diet/lifestyle factors and positively with unhealthy factors, with stronger correlations in adenoma cases than controls.

Conclusions: Individuals after adenoma resection showed similar microbial changes as observed in CRC, which persisted years after resection, potentially reflecting their increased CRC risk. These microbial changes might reflect the influence of persistent unhealthy dietary and lifestyle behaviors, underscoring the importance of lifestyle modification after adenoma resection for CRC prevention.

Modulation of Acute Radiation Syndrome in Human Intestine by Gut Microbiome and a Probiotic Revealed using Organ Chips

Presented by: Alican Özkan

Acute radiation syndrome (ARS) caused by exposure to high levels of g-radiation is associated with injury to the gastrointestinal system, which can be life-threatening [1]. Due to the lack of preclinical models that are representative of human pathophysiology, a limited number of drugs have been approved as radiation medical countermeasures (MCMs), and almost all of these are aimed at treating neutropenia. Therefore, there is still a great need for therapies that address the gastrointestinal manifestations of ARS. To meet this challenge, we modeled acute radiation injury using human intestine using organ-on-a-chip (Organ Chip) microfluidic culture technology that can recapitulate organ-level physiology and pathophysiology with high fidelity.  Human Intestine Chips were created by lining two-channel microfluidic chips with ileum organoid-derived epithelial cells isolated from healthy patients in one channel and interfacing them with small intestine-derived microvascular endothelial cells across a porous membrane in the second parallel channel. A hypoxia gradient was also generated on-chip to enable co-culture of the human cells with patient-derived complex microbiome (i.e., that contain anaerobes and aerobes) in the presence or absence of a commercially available probiotic consortium (VSL#3) for extended times [2]. Exposure of the Intestine Chips to g radiation (8 Gy) induced villus blunting, expression of DNA damage marker, H2AX, and production of pro-inflammatory cytokines (NGAL, MCP-1, IL-8) in both the epithelium and endothelium.  Inclusion of a complex gut microbiome in the chip prior to radiation exposure further increased villus blunting and H2AX expression in both the epithelium and endothelium, while also suppressing expression of the DNA damage repair protein, 53bp1, in the endothelium.  Importantly, administration of the VSL#3 probiotic formulation to the epithelial lumen of the Intestine Chip containing complex gut microbiome prior to radiation exposure significantly suppress radiation injury as measured by decreased villus blunting, lower H2AX expression, and suppressed pro-inflammatory cytokine production.  Interestingly, however, while the probiotic treatment decreased production of NGAL and MCP-1 by both the epithelium and endothelium, IL-8 production was only reduced in the epithelium. This work suggests that host-microbiome interactions may influence radiation-induced damage in the human intestine and that an existing low-cost, commercially available probiotic could potentially be repurposed as a radiation MCM therapeutic. 
References:
[1] Hauer-Jensen, et al. (2014). Nature Rev. Gas. & Hep., 11(8), 470-479.
[2] Jalili-Firoozinezhad, S., et al. (2019). Nature biomedical engineering, 3(7), 520-531.

The Effect of Sodium Butyrate on the Cell Viability of Triple-Negative Inflammatory Breast Cancer

Presented by: Yabdiel A. Ramos-Valerio

Inflammatory breast cancer (IBC) is the most aggressive form of breast cancer, accounting for 2-4% of cases but contributing to approximately 10% of annual breast cancer mortality in the USA. Studies have shown that the molecular profile of IBC differs significantly from other subtypes, however, these changes do not fully account for its aggressive and rapid metastasis. The microbiome, consisting of a diverse community of microorganisms living in the human body, has emerged as an influential player in cancer development and progression of different cancers, including breast cancer. There is evidence suggesting that microbial metabolites, such as short-chain fatty acids (SCFA), contribute to immune response, tumor growth, and the efficacy of chemotherapeutic drugs and immune checkpoint inhibitors. Additionally, the therapeutic potential of butyrate, an SCFA, in treating different cancers through the activation of MAPK pathways and apoptosis is well characterized, but its use in the treatment of IBC has not been assessed. In this study, we treated SUM149 ((Triple Negative IBC)  cells with multiple concentrations of butyrate at different time points and evaluated them in the context of MAPK activation, proliferation, and apoptosis. SUM149 cells were treated with 0, 3.12, 6.25, 12.50, 25, and 50mM concentrations of Sodium Butyrate for 1, 3, 6, and 24h. MAPK activation was assessed through western blot using specific antibodies including anti- p-JNK, p-p38, p38, P-ERK1/2, and ERK1/2 and normalized with anti-GAPDH as a loading control. Proliferating and apoptotic cells were detected by fluorescence microscopy of KI67-FITC and Annexin V-Cy3 respectively. We observed a dose-dependent increase in activation of p-JNK at 1h, while no difference was observed at longer time points. We saw a decrease in cell proliferation and an increase in cell apoptosis in SUM149 cells treated with 6.25mM of butyrate after 24h. Additionally, while we didn’t see a significant decrease in cell proliferation we did see a significant increase in apoptosis in cells treated with 50mM of butyrate after 24h. We are currently examining the molecular mechanisms involved in the effects of butyrate on cell viability in TNIBC-SUM149. Butyrate’s regulation of the JNK MAPK pathway may play an important role in the viability of TN-IBC cells treated with butyrate. These findings could establish a mechanistic link between the MAPK pathway and the effects of butyrate on TN-IBC cell viability.

Seafood intake and Community Drinking water supply is related to PFAS Exposure and its Reproductive Cancer outcomes: Epidemiological perspective from NHNAES 2010-2018

Presented by: Rezaul Karim Ripon

Background: Widespread environmental contaminants known as perfluoroalkyl substances (PFAS) are associated with various harmful health effects, including cancer. For public health interventions, it is essential to understand the relationship between sources of PFAS exposure and reproductive cancer outcomes.

Objective: Using data from the 2010-2018 National Health and Nutrition Examination Survey (NHANES), investigate how PFAS exposure, which comes from sea food intake and community drinking water, is related to reproductive cancer outcomes in the US population

Methods: The study examined PFAS exposure levels among 15,015,140 participants from NHANES data from 2017 – 2018 to investigate the relationship between exposure to PFAS and cancer outcome. Demographic variables were adjusted, and regression analysis was used to evaluate the relationship.

Results: The study found that over 50% of participants were above the detection limit for PFAS which comes from seafood intake and community drinking water.  AA significant association was found between exposure to PFAS in community drinking water supply sources and the incidence of prostate cancer (aOR = 1.53; 95% CI: 1.25-1.89; p < 0.001) and ovarian cancer. (aOR = 1.47; 95% CI: 1.19-1.82; p <0.001). These results highlight the increased reproductive cancer risk associated with routes of exposure to PFAS.

Conclusions: Addressing PFAS contamination in community water supplies and seafood intake as a public health priority is crucial. The strong correlation between PFAS exposure and reproductive cancer outcomes demonstrates the need for targeted interventions to reduce PFAS exposure in the population, thereby reducing the risk of cancer-related to these environmental contaminants.

Concurrent and habitual diet differentially associate with microbial Multi-omic Profiles in Inflammatory Bowel Disease(IBD)

Presented by: Jiaxian Shen

Background: Studies have linked diet to the risk and severity of inflammatory bowel disease (IBD) and its subtypes, Crohn’s disease (CD) and ulcerative colitis (UC). Similarly robust evidence has associated disease activity to characteristic alterations in gut microbial taxonomy (metagenomics, MGX), community functions (metatranscriptomics, MTX), and microbial metabolites (metabolomics, MBX). However, in IBD, explorations into how these multi-omic readouts are affected by concurrent/short-term vs. habitual/long-term diets are limited. Methods: Using the Integrative Human Microbiome Project in which 105 densely-phenotyped participants with IBD (n=38 with UC, 67 with CD) and 27 non-IBD controls collectively provided 1,638 stool metagenomes, 835 metatranscriptomes, and 546 metabolomes over one year, we conducted a longitudinal survey to compare the relative importance of concurrent and habitual diet in relation to MGX, MTX, MBX profiles using an abbreviated food frequency questionnaire with each stool sample. Concurrent diet was assessed by reported intake from the one-week preceding sample collection, while habitual diet was modeled using a decaying average of concurrent food records. We explored several different decaying formulas; for example, one formula assigned a weight of 2-n for the nth prior week. With these integrated time-series profiles, we linked diet and microbiome matrices via intra-individual mantel tests, quantifying associations within subjects only. We assessed differences in correlation coefficients using 4,999 permutations and evaluated robustness with 4,999 bootstraps.

Results: Diet-microbiome associations showed stronger correlations when accounting for within-person correlation compared with a subject-unaware omnibus association, supporting a personalized link between diet and multi-omic profiles. Compared to concurrent, habitual diets had a significantly stronger correlation with MGX taxonomy and MGX functional potential. Correlation increased as the decay became more gradual, and plateaued at weight=1/sqrt(time+1). We further explored the impact of diet on MTX functional activities (normalized by DNA gene copy number) and observed community-level patterns consistent with MGX. However, when functions were stratified by contributing microorganisms, no differences emerged between concurrent and habitual diets. This suggests that although habitual diet more significantly shapes community-level functions than concurrent diet, it does not predict which species contribute to specific functions. In contrast, neither habitual nor concurrent diets had additive effects on shaping MBX, which could be attributed to an actual biological pattern or potentially to the technical noise in MBX data, as the association tests showed less stability during bootstrapping.

Conclusion: This work offers a glimpse at how diet is differentially coupled to alterations in longer-term microbial growth, functional potential (MGX), and community functional activities (MTX) for which additional data on habitual diet is informative vs. comparatively transient multi-omics (MBX). However, the magnitude of the association is modest. Next, we will interrogate the bidirectional relationship between disease and dietary stability and whether these linkages differ among microbes or biochemical pathways canonically linked to IBD.

Using housekeeping gene cpn60 as a marker for microbial community profiling and viability assessment

Presented by: Ya Wang

While high-throughput metagenomic sequencing has revolutionized the study of microbial communities, it remains surprisingly difficult to determine which microbes in a community are “alive” versus “dead” using current techniques. Microbial viability is fundamental to an understanding of the biology of the microbiome, as the functions of a microbial community are defined by its viable members. This limits our understanding of microbiome structures and their transmission between humans and our surroundings. Currently, several sequencing-based methods have been attempted to address this issue, yet these methods struggle with accuracy and scalability in complex communities.
In this study, we introduced a novel protein-coding marker gene approach using the cpn60 gene for comprehensive microbial community profiling and functional activity assessment through metagenomic and metatranscriptomic sequencing. We first constructed an extensive database integrating cpn60 protein and enriched cpn60 nucleotide sequences, expanding on the existing cpnDB nucleotide database. We used cpn60 protein IDs for protein-based taxonomy inference in the Human Microbiome Project II dataset and found strong agreement between cpn60-protein-based taxonomy and shotgun metagenomic results. This would suggest cpn60 being a discriminative marker for taxonomy profiling. Furthermore, we explored the potential of cpn60 protein expression in metatranscriptomic data as an indicator of bacterial species’ transcriptional activity. The cpn60-protein-based analysis correlated positively with growth rates estimated using the bPTR method, suggesting cpn60 proteins as robust markers for microbial community viability characterization. These insights underscore the feasibility of cpn60 in crafting taxonomic profiles from shotgun metagenomics data and in representing species activities within microbial communities through the integration of metatranscriptomic data. Employing marker genes emerges as a promising strategy to forge efficient and cost-effective viability assessments for microbial community samples.
This study contributes a promising new approach enhancing our ability to assess the functional activity of microbial communities through advanced metagenomic profiling and providing insights into the dynamics of microbial life in various ecosystems.

Response of the gut microbiome to acute enteric pathogen infection and antibiotic treatment

Presented by: Yancong Zhang

Enterotoxigenic Escherichia coli (ETEC) is among the most significant enteric pathogens worldwide, as it ranks among the primary causes of diarrheal illnesses in low and middle income countries. However, our understanding of how the broader gut ecosystem can mitigate virulence or respond to acute infection (and recovery) remains limited. Here, we present a comprehensive exploration of functional dysbiosis in the gut microbiome in response to ETEC infection and antibiotic treatment in a laboratory environment. We conducted a longitudinal analysis on six adult participants, tracking their microbial community and activity profiles before, during, and after controlled exposure to ETEC and antibiotic-mediated recovery. This analysis profiled 106 shotgun metagenomic samples and 102 paired metatranscriptomes. Notably, the gut microbiome’s response to both ETEC and antibiotic treatment varied dramatically among individuals, consistent with the high variation of their clinical diarrheal outputs (from 0 mL to 3923 mL). Taxonomic profiles varied from 0.32 to 0.75 (i.e. Bray-Curtis dissimilarities within subject), for example, with around 36% of differentially abundant species more abundant in cases of severe disease. These included Ruminococcus bromii, Lachnospira eligens, and unclassified Eggerthellaceae species, likely a result of gut microbial growth dysfunction during diarrhea. Additionally, transcriptional changes shed light on how the gut microbiome responds to the pathogenic challenge and antibiotic treatment. Differentially expressed genes within the same species often participated in similar metabolic processes, such as glutamine metabolism in Bacteroides massiliensis, phage integration in Bifidobacterium adolescentis, and sporulation-related processes in Blautia wexlerae. This study offers valuable insights into how the gut microbiome reacts to pathogenic challenges and antibiotic exposure, deepening our understanding of ecological protective factors and responses during acute infection, diarrhea, and recovery. These findings have implications for mitigating the effects of enteric pathogens via the microbiome in both adults and vulnerable infant populations.