Workshop 2: Math and the Microbiome

(October 10,2018 - October 12,2018 )

Organizers


Adriana Dawes
Department of Mathematics / Department of Molecular Genetics, The Ohio State University
Vanessa Hale
Department of Veterinary Preventive Medicine, The Ohio State University
Matthew Sullivan
Department of Microbiology, The Ohio State University

Goals of this workshop include:

  1. Identify the questions, challenges, tools, and needs for microbiome studies at Ohio State University (OSU) and in the greater Columbus area.
  2. Stimulate interdisciplinary collaborations at OSU and in the greater Columbus area (e.g. Nationwide Children’s Hospital, Battelle).

The intended workshop participants are faculty / PIs who are laboratory scientists, mathematicians, statisticians, or metabolic modelers working on or interested in questions that involve the microbiome.

As such, preference will be given to OSU or local faculty applicants for this workshop.


From the bacteria in our guts, to microbes involved in biodegradation and crop growth, to viruses in the ocean, some of Earth’s tiniest organisms play some of the most important roles in global health, food production, and climate change. Advances in metagenomic sequencing technology including 16S, viromics, and mycobiomics - along with metabolomics, transcriptomics, and proteomics allow us to characterize these complex microbial communities and begin to understand their functions. This Big Data creates opportunities for data driven discovery and new data analytics, but Big Data also comes with challenges: Meaningful integration of multi-omic data has become increasingly critical to microbiome studies as recent work highlights the importance of community dynamics, interactions, and microbial ecology over the roles of individual microbes. For example, microbial metabolisms are now recognized to often be ‘distributed’ across consortia; viruses manipulate microbial metabolisms and population dynamics, and co-occurring fungi in most ecosystems are virtually unstudied but likely play key roles as well. Data integration techniques range from correlations to network analyses to genome-scale microbial community metabolic models that assess metabolite flux to ecosystem models that provide predictive power of which organisms drive key features of the system. Some of these techniques, like correlations, accommodate many types of –omic data but cannot account for the complex biology or ecology of a system. Other techniques, like metabolic modeling, better account for this complexity, but do not yet integrate phenotypic –omic data (i.e. metabolomics, proteomics) well. Each of these techniques has advantages and limitations and new computational tools for data integration and modeling have rapidly developed over the last 2 years. Besides data integration, Whether studying environmental, gut, or industrial microbes, the ability to accurately identify and predict the structure and function of microbial communities has far-reaching potential and paves the way for microbial engineering in bioremediation, probiotic development, and sustainable agriculture.

In this 3 day workshop, we will take a genome to phonome approach with broad perspectives provided by mathematicians, biologists, and statisticians. We will also develop interdisciplinary working subgroups to consider the questions, challenges, tools, and needs of data integration and modeling in microbiome studies. Each participant will present a short talk (5 minutes, 3 slides) highlighting his or her research, perspectives, and challenges. The goal is to help develop a broadly collaborative community of math-enabled microbiome scientists with common research goals.

This workshop is co-sponsored by the Mathematical Biosciences Institute, the National Institute of Statistical Sciences, and the Infectious Diseases Institute at Ohio State University.







Accepted Speakers

Jason Papin
Department of Biomedical Engineering, University of Virginia
Katrine Whiteson
Molecular Bio and Biochem, UC Irvine
Wednesday, October 10, 2018
Time Session
08:00 AM
09:00 AM

Breakfast and Daily Introduction

09:00 AM
09:55 AM
Jason Papin - Metabolic Mechanisms of Interaction in Microbial Communities
Abstract not provided.
09:55 AM
10:50 AM
Katrine Whiteson - Metabolites, Germs and People: Eavesdropping on Human-Associated Microbial Communities
Persistent and unique microbial communities impart the majority of genetic and metabolic diversity in humans, and their composition and activity are important indicators of health and disease. The Whiteson lab uses culture-independent metagenomics, metabolomics, and ecological statistics along with hypothesis driven, reductionist microbiology to answer questions about how bacteria and viruses affect human health. We and others find that the most important source of variance in both microbiome and metabolome data is the individual the sample was taken from, making longitudinal samples where a person’s own sample can act as the baseline an important approach. Several recent research projects using metabolomics and sequencing will be presented from healthy humans and Cystic Fibrosis patients, with the hope of brainstorming analytical approaches to relate longitudinal microbiome and metabolomics data.
10:50 AM
11:05 AM

Coffee Break with Snacks

11:05 AM
12:00 PM
Matthew Sullivan - Math and the Virosphere: Needs and Opportunities
Microbes are recently recognized as driving the energy and nutrient transformations that fuel Earth’s ecosystems in soils, oceans and humans. Where studied, viruses appear to modulate these microbial impacts in ways ranging from mortality and nutrient recycling to complete metabolic reprogramming during infection. As environmental virology strives to get a handle on the global virosphere (the diversity of viruses in nature) clear challenges are emerging where collaboration with mathematicians will be powerfully enabling. I will present a few ripe research avenues where we (environmental virologists) could use some help from mathematicians, statisticians, theorists and modelers to better understand the nanoscale (viruses) and microscale (microbes) entities that drive Earth’s ecosystems, and human health and disease.
12:00 PM
02:00 PM

Lunch and Participant Collaboration

02:00 PM
03:00 PM

Flash Talks

03:00 PM
03:30 PM

Math/Microbiome Opportunities and Big Questions

03:30 PM
05:00 PM

Group Discussions on Big Questions and Opportunities

06:00 PM
09:00 PM

Dinner and Continued Discussion at El Vaquero

Thursday, October 11, 2018
Time Session
08:00 AM
09:00 AM

Breakfast and Daily Introduction

09:00 AM
10:00 AM

Report Out (1 Slide) on Big Question Discussions

10:00 AM
10:30 AM

Coffee Break with Snacks

10:30 AM
11:30 AM

Continued Group Discussions on Big Questions

11:30 AM
12:00 PM

Report Out (1 Slide) Summarizing Each Group's Discussion

12:00 PM
01:30 PM

Lunch and Participant Collaboration

01:30 PM
02:00 PM

Provide Guidelines for Project Design Competition

02:00 PM
04:00 PM

Competitive Project Design in Small Groups

04:00 PM
05:00 PM

Group Project Reports

05:30 PM
07:30 PM

Happy Hour and Continued Discussion at Arch City Tavern

Friday, October 12, 2018
Time Session
08:00 AM
09:00 AM

Working Breakfast / Preparation for Final Pitches

09:00 AM
11:00 AM

Competitive Project Pitches

11:00 AM
12:00 PM

Moderated Group Deliberations on Projects

12:00 PM
01:45 PM

Farewell Lunch and Participant Collaboration

01:45 PM
02:00 PM

Awards Ceremony to Announce Seed Grant Project Winners

Name Email Affiliation
Abbaoui, Besma abbaoui.1@osu.edu Food Science & Technology, The Ohio State University
Altabtbaei, Khaled altabtbaei.1@osu.edu Biosciences, The Ohio State University
Alzalg, Baha baha2math@gmail.com Mathematics, The University of Jordan
Anderson, Matt anderson.3196@osu.edu Microbiology Admin, The Ohio State University
Bailey, Mike michael.bailey2@nationwidechildrens.org Pediatrics, The Ohio State University
Ballweg, Rick ballwera@mail.uc.edu Systems Biology and Physiology Graduate Program, University of Cincinnati
Beall, Clifford beallc@ccri.net Center for Gene Therapy, The Ohio State University
Bjrk, Johannes bjork.johannes@gmail.com Department of Biological Sciences, University of Notre Dame
Bolduc, Ben bolduc.10@osu.edu Microbiology, The Ohio State University
Chukwu, Angela unnachuks2002@yahoo.co.uk Department of Statistics, University of Ibadan
Cui, Jing Jing.Cui@agri.ohio.gov Animal Disease Diagnostic Laboratory, Ohio Department of Agriculture
Dannemiller, Karen dannemiller.70@osu.edu Civil, Envir & Geod Eng, The Ohio State University
Das, Jayajit jayajit.das@nationwidechildrens.org Battelle Ctr. for Mathematical Medicine/ Dept. of Pediatrics, The Ohio State University
Dawes, Adriana dawes.33@osu.edu Department of Mathematics / Department of Molecular Genetics, The Ohio State University
Garabed, Rebecca garabed.1@osu.edu Veterinary Preventive Medicine, The Ohio State University
Ghanem, Mostafa ghanem.9@osu.edu Veterinary Preventive Medicine, The Ohio State University
Gong, Ming gongm1@udayton.edu Electrical Engineering, University of Dayton
Hale, Vanessa hale.502@osu.edu Department of Veterinary Preventive Medicine, The Ohio State University
Kang, Jia (John) jia.kang@merck.com Biostatistics, Merck Research Laboratories
Kigerl, Kristina kristina.kigerl@osumc.edu Neuroscience, The Ohio State University
Lauber, Chris Christian.Lauber@nationwidechildrens.org Institute for Genomic Medicine, Nationwide Children's Hospital
Mackos, Amy mackos.3@osu.edu College of Nursing, The Ohio State University
Mifflin, Katherine katherine.mifflin@gmail.com Neuroscience, The Ohio State University
Mukherjee, Chiranjit mukherjee.55@osu.edu Biomedical Sciences, The Ohio State University
Oyamakin, Samuel fm_oyamakin@yahoo.com Statistics, Centre for Environment, Renewable Natural Resources Management, Research and Development, (CENRAD)
Papin, Jason papin@virginia.edu Department of Biomedical Engineering, University of Virginia
Roth, Kimberly roth@juniata.edu Mathematics, Juniata College
Russi Rodrigues, Denise russirodrigues.1@osu.edu OARDC Animal Sciences, The Ohio State University
Sabree, Zakee sabree.8@osu.edu EEOB, The Ohio State University
Short, Sarah short.343@osu.edu Entomology, The Ohio State University
Siddiqui, Jalal Khalid siddiqui.13@osu.edu SBS-Biomedical Informatics, The Ohio State University
Song, Chi song.1188@osu.edu COPH-Division of Biostatistics, The Ohio State University
Sudakov, Ivan isudakov1@udayton.edu Physics, University of Dayton
Sullivan, Matthew sullivan.948@osu.edu Department of Microbiology, The Ohio State University
Sun, Christine sun.2508@osu.edu Microbiology Admin, The Ohio State University
Tokarev, Vasily tokarev@juniata.edu Biomedical Sciences, Juniata College
Whiteson, Katrine katrine@uci.edu Molecular Bio and Biochem, UC Irvine
Winston, Jenessa jeandrze@ncsu.edu PHP, North Carolina State University - College of Veterinary Medicine
Zhang, Yan yan.zhang@agri.ohio.gov Animal Disease Diagnostic Laboratory, Ohio Department of Agriculture
Metabolic Mechanisms of Interaction in Microbial Communities
Abstract not provided.
Math and the Virosphere: Needs and Opportunities
Microbes are recently recognized as driving the energy and nutrient transformations that fuel Earth’s ecosystems in soils, oceans and humans. Where studied, viruses appear to modulate these microbial impacts in ways ranging from mortality and nutrient recycling to complete metabolic reprogramming during infection. As environmental virology strives to get a handle on the global virosphere (the diversity of viruses in nature) clear challenges are emerging where collaboration with mathematicians will be powerfully enabling. I will present a few ripe research avenues where we (environmental virologists) could use some help from mathematicians, statisticians, theorists and modelers to better understand the nanoscale (viruses) and microscale (microbes) entities that drive Earth’s ecosystems, and human health and disease.
Metabolites, Germs and People: Eavesdropping on Human-Associated Microbial Communities
Persistent and unique microbial communities impart the majority of genetic and metabolic diversity in humans, and their composition and activity are important indicators of health and disease. The Whiteson lab uses culture-independent metagenomics, metabolomics, and ecological statistics along with hypothesis driven, reductionist microbiology to answer questions about how bacteria and viruses affect human health. We and others find that the most important source of variance in both microbiome and metabolome data is the individual the sample was taken from, making longitudinal samples where a person’s own sample can act as the baseline an important approach. Several recent research projects using metabolomics and sequencing will be presented from healthy humans and Cystic Fibrosis patients, with the hope of brainstorming analytical approaches to relate longitudinal microbiome and metabolomics data.