Folker Meyer Lab

Folker Meyer

University of Chicago
Computation Institute
Research Institute Suite 405
5640 South Ellis Avenue
Chicago, IL 60637

Argonne National Laboratory
9700 South Cass Avenue
Building 240
Argonne, IL 60439

Phone: (630) 252-3261

About the Lab

Dr. Meyer builds research software to study microbial communities.

His research interests include microbial ecology, distributed high performance computing and big data. He leads the MG-RAST project, providing what is currently the most widely used metagenomics and metatranscriptomics analysis platform with. MG-RAST has analyzed over 100,000 data sets analyzed in early 2014.

Dr. Meyer is the area lead for microbial community sciences in the Department of Energy (DOE) Systems Biology Knowledgebase project KBase.

In the past he has worked on the GenDB and RAST projects. He is a board member of the Genomics Standards Consortium and a founding member of the Earth Microbiome Project (EMP).

ResearchGate: Folker Meyer
Google scholar: Folker Meyer

Selected Papers

Genomic encyclopedia of bacteria and archaea: sequencing a myriad of type strains
Kyrpides NC, Hugenholtz P, Eisen JA, Woyke T, Göker M, Parker CT, Amann R, Beck BJ, Chain PS, Chun J, Colwell RR, Danchin A, Dawyndt P, Dedeurwaerdere T, DeLong EF, Detter JC, De Vos P, Donohue TJ, Dong XZ, Ehrlich DS, Fraser C, Gibbs R, Gilbert J, Gilna P, Glöckner FO, Jansson JK, Keasling JD, Knight R, Labeda D, Lapidus A, Lee JS, Li WJ, Ma J, Markowitz V, Moore ER, Morrison M, Meyer F, Nelson KE, Ohkuma M, Ouzounis CA, Pace N, Parkhill J, Qin N, Rossello-Mora R, Sikorski J, Smith D, Sogin M, Stevens R, Stingl U, Suzuki K, Taylor D, Tiedje JM, Tindall B, Wagner M, Weinstock G, Weissenbach J, White O, Wang J, Zhang L, Zhou YG, Field D, Whitman WB, Garrity GM, Klenk HP.
PLoS Biol. 2014 Aug 5;12(8):e1001920. doi: 10.1371/journal.pbio.1001920. eCollection 2014 Aug.
PMID: 2509381

The complete genome sequence for putative H2 - and S-oxidizer Candidatus Sulfuricurvum sp., assembled de novo from an aquifer-derived metagenome
Handley KM, Bartels D, O'Loughlin EJ, Williams KH, Trimble WL, Skinner K, Gilbert JA, Desai N, Glass EM, Paczian T, Wilke A, Antonopoulos D, Kemner KM, Meyer F.
Environ Microbiol. 2014 Mar 14. doi: 10.1111/1462-2920.12453. [Epub ahead of print]
PMID: 24628880

Lab Members

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M
Folker Meyer

Folker Meyer

Argonne, Core Member, Sr. Fellow,
Computational Biologist, Mathematics and Computer Science Division, Argonne National Laboratories
Senior Fellow, Computation Institute, The University of Chicago
(630) 252-3261

Additional Lab Members

  • Jared Bischof, MSc
  • Dan Braithewaite, BSc
  • Mark D'Souza, PhD
  • Wolfgang Gerlach, PhD
  • Elizabeth Glass, PhD
  • Travis Harrison, MSc
  • Adina Chuang Howe, PhD
  • Kevin Keegan, PhD
  • Tobias Paczian, MSc
  • Will Trimble, PhD
  • Wei Tang, PhD
  • Andreas Wilke, MSc

Jack Gilbert Lab

Jack Gilbert

Argonne National Laboratory
9700 South Cass Avenue
Argonne, IL 60439

Phone: (630) 252-7489

About the Lab

My laboratory focuses on numerous key aspects of how bacteria assemble into distinct communities, the metabolic mechanisms that structure these assemblages, and whether these systems can be predictively modeled over time and space. We use next generation sequencing approaches to access phylogenetic and functional information embedded within the genes of bacteria that populate these communities.  Our goal is to use this information to reconstruct community interactions, and ultimately to build statistical models of the microbial ecosystem.  These models will help us visualize large-scale patterns, generate predictions of responses to changes in an environment, and to identify gaps in our sampling campaigns.

We are a very collaborative group.  Currently, we are involved in the (1) Earth Microbiome Project, which is a systematic characterization of microbial life across the biomes of planet earth; (2) Home Microbiome Project, an ongoing study to determine the rate and direction of microbial interaction between people, their pets and their homes; (3) Chicago Waterways Metagenomic Initiative, which aims to map and model the dynamics of microbial metabolism in the Chicago River and surrounding canals; (4) The Gulf of Mexico Microbial Metabolic Modeling Initiative that will map and model the microbial dynamics of the Gulf of Mexico; (5) American Gut, which aims to characterize the microbial diversity of 20,000 humans over the next 2 years; (6) The Autism Microbiome Consortium, which is providing a nexus for research into the influence of microbial metabolism on the symptoms of Autism; (7) Microbial Assemblage Prediction, which involves developing microbial modeling tools capable of allowing global forecasting of microbial community structure and metabolic potential across planet earth.

Our group is also part of a recently launched Hospital Microbiome Project.  This new initiative will characterize the taxonomic composition of surface-, air-, water- and human associated microbial communities in two hospitals.  The aim is to determine the influence of bacterial population demographics on the directionality in which the community evolves and the rate of colonization by potential pathogens. The influence of space, and the building materials used to create the space, will be examined in parallel.  The overall goal of the project is make inroads into the management of healthcare associated infections, which affect more ~1.7M people in the US every year.  The first part of this 2-year study will be performed at the new Center for Care and Discovery at The University of Chicago, taking advantage of a unique opportunity to examine the rate and structure of succession of a hospital microbiome as a hospital starts accepting staff and patients.  The second part of the study will take place in a very different environment, a US Army medical center in Germany.

In addition to these core projects, we also have over 35 ongoing collaborations with researchers from around the world and right here in Chicago.

Selected publications

Gibbons SM, Caporaso JG, Pirrung M, Field D, Knight R, Gilbert JA. 2013. Evidence for a persistent microbial seed bank throughout the global ocean. Proc Natl Acad Sci USA. 110 (12); 4651-4655

Fierer N, Leff JW, Adams BJ, Nielsen UN, Bates ST, Lauber CL, Owens S, Gilbert JA, Wall DH, Caporaso JG. 2012. Cross-biome metagenomic analyses of soil microbial communities and their functional attributes. Proc Natl Acad Sci U S A. 2012 Dec 26;109(52):21390-5.

Knight R, Jansson J, Field D, Fierer N, Desai N, Fuhrman J, Hugenholtz P, Meyer F, Stevens R, Bailey M, Gordon JI, Kowalchuk G, Gilbert JA. 2012. Designing Better Metagenomic Surveys: The role of experimental design and metadata capture in making useful metagenomic datasets for ecology and biotechnology. Nature Biotechnology. 30 (6), 513–520

Gilbert JA, Steele J, Caporaso JG, Steinbruck L, Somerfield PJ, Reeder J, Temperton B, Huse S, Joint I, McHardy AC, Knight R, Fuhrman JA, Field D. 2012. Defining seasonal marine microbial community dynamics. ISME J. 6, 298-308.

Larsen PE, Field D, Gilbert JA. 2012. Predicting bacterial community assemblages using an artificial neural network approach. Nature Methods. 9 621-625

Lab Members

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M
Folker Meyer

Folker Meyer

Argonne, Core Member, Sr. Fellow,
Computational Biologist, Mathematics and Computer Science Division, Argonne National Laboratories
Senior Fellow, Computation Institute, The University of Chicago
(630) 252-3261

News

Research Papers

Barbara Stranger Lab

Barbara Stranger

Institute for Genomics and Systems Biology
The University of Chicago
KCBD 10134
900 E. 57th St.
Chicago, IL 60637

Phone: 773-702-4301

About the Lab

The overriding research interest of the lab is trying to disentangle the relationship between genotype and phenotype, and to understand the forces shaping functional genetic variation in humans. We use a combination of experimental and computational approaches: We employ high-throughput functional genomics and genome-wide association analysis (GWAS) to identify variable regions of the genome with functional effects on the transcriptome, and to investigate the context-specificity of these patterns. At the same time, we examine the levels and patterns of genetic variation within and between human populations, and between human and other species to identify regions of the genome with patterns of variation suggestive of natural selection.

Current projects in the lab investigate genetic and epigenetic effects on transcriptome regulation in disease contexts that include cancer, asthma and pre-eclampsia. In parallel, we are studying immune cells of healthy cohorts to obtain a baseline against which to compare disease regulatory networks in immune-mediated diseases. These approaches complement disease-mapping studies and provide hypotheses for the mechanism of action of specific variants in creating disease phenotypes.

We recently integrated GWAS results with protein-protein interaction networks and transcriptome data to examine the relationship between genome evolution and inflammatory disease (Raj et al, 2013).  We identified 21 genome regions with a ‘signature’ for both inflammatory disease susceptibility and natural selection. Our study suggests that genetic variants selected through human evolution based on their ability to function in pathogen-protection mechanisms can - in our modern, more pathogen-free, environment – predispose to autoimmune disease.

In Li et al (2013), we combined GWASs and data from The Cancer Genome Atlas (TCGA) to gain insight into the mechanisms by which breast cancer risk alleles predispose to disease.  Expression quantitative trait locus (eQTL) analyses of 15 breast cancer risk loci demonstrated that three risk variants regulate expression of the estrogen receptor (ESR1) and the oncogenes MYC and KLF4, and have downstream effects on transcript levels of many genes. The methods applied in this comprehensive study are being applied to additional cancer types.

The lab is also interested in projects that are less disease centric and would be categorized as basic genome science.  We are interested in investigating:  1) the evolution of paralogs in the human genome; 2) the influence of genetic variation, ancestry, age, sex, cell-type, epigenome, and tissue-type on transcriptional networks; 3) genetic and epigenetic roles in gene splicing and 4) population genomics of regulatory regions and variants. We are constantly re-tooling and developing new analytic methods and tools to most effectively and efficiently make use of large-scale genomics data.

Selected Publications

Intersection of population variation and autoimmunity genetics in human T cell activation
Ye CJ, Feng T, Kwon HK, Raj T, Wilson MT, Asinovski N, McCabe C, Lee MH, Frohlich I, Paik HI, Zaitlen N, Hacohen N, Stranger B, De Jager P, Mathis D, Regev A, Benoist C.
Science. 2014 Sep 12;345(6202):1254665. doi: 10.1126/science.1254665.
PMID: 25214635

Regulation of gene expression in autoimmune disease loci and the genetic basis of proliferation in CD4+ effector memory T cells
Hu X, Kim H, Raj T, Brennan PJ, Trynka G, Teslovich N, Slowikowski K, Chen WM, Onengut S, Baecher-Allan C, De Jager PL, Rich SS, Stranger BE, Brenner MB, Raychaudhuri S.
PLoS Genet. 2014 Jun 26;10(6):e1004404. doi: 10.1371/journal.pgen.1004404. eCollection 2014 Jun.
PMID: 24968232

Expression QTL-based analyses reveal candidate causal genes and loci across five tumor types
Li Q, Stram A, Chen C, Kar S, Gayther S, Pharoah P, Haiman C, Stranger B, Kraft P, Freedman ML.
Hum Mol Genet. 2014 Oct 1;23(19):5294-302. doi: 10.1093/hmg/ddu228. Epub 2014 Jun 6.
PMID: 24907074

Genomics of alternative splicing: evolution, development and pathophysiology
Gamazon ER, Stranger BE.
Hum Genet. 2014 Jun;133(6):679-87. doi: 10.1007/s00439-013-1411-3. Epub 2014 Jan 1. Review.
PMID: 24378600

Lab Members

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M
Folker Meyer

Folker Meyer

Argonne, Core Member, Sr. Fellow,
Computational Biologist, Mathematics and Computer Science Division, Argonne National Laboratories
Senior Fellow, Computation Institute, The University of Chicago
(630) 252-3261

News

IGSB Core Member Co-Authors Paper

Barbara Stranger and her lab led analyses of data published in the journal, Science. The report, “Polarization of the Effects of Autoimmune and Neurodegenerative Risk Alleles in Leukocytes,” demonstrates how genetic variations among healthy, young individuals can influence immune cell function. Many of those variants are also genetic risk factors for Alzheimer’s disease, diabetes, and multiple sclerosis later in life, offering new insight into disease pathology.

Immunity, inflammation and natural selection

Barbara Stranger and colleagues take a systems approach, integrating GWAS, eQTL and protein interaction data, to demonstrate that loci associated with inflammatory disease susceptibility are enriched for genomic signatures of recent evolutionary selection.  Their analyses suggest that natural selection for pathogen-defense mechanisms through human evolution may underlie modern susceptibility to inflammatory diseases.

Research Papers

Robert Grossman Lab

Robert Grossman

Institute for Genomics and Systems Biology
The University of Chicago
900 East 57th Street KCBD 10146
Chicago, IL 60637

Phone: 773-834-4669

About the Lab

Professor Grossman’s research group focuses on bioinformatics, data mining, cloud computing, data intensive computing, and related areas.  Current research projects include: Bionimbus (http://www.bionimbus.org) a cloud-based system for managing, analyzing and sharing genomic data and the Open Science Data Cloud (OSDC), a large-scale distributed cloud-based infrastructure for managing, analyzing, integrating and sharing scientific data.  The OSDC is operated by the Open Cloud Consortium (OCC), which is a not-for-profit supporting the cloud community by operating cloud infrastructure.  Professor Grossman is also interested in developing new algorithms for the large-scale analysis projects of genomic and phenotypic data.

 

Selected Papers

Diverse patterns of genomic targeting by transcriptional regulators in Drosophila melanogaster
Slattery M, Ma L, Spokony RF, Arthur RK, Kheradpour P, Kundaje A, Nègre N, Crofts A, Ptashkin R, Zieba J, Ostapenko A, Suchy S, Victorsen A, Jameel N, Grundstad AJ, Gao W, Moran JR, Rehm EJ, Grossman RL, Kellis M, White KP.
Genome Res. 2014 Jul;24(7):1224-35. doi: 10.1101/gr.168807.113.
PMID: 24985916

Toward more transparent and reproducible omics studies through a common metadata checklist and data publications
Kolker E, Özdemir V, Martens L, Hancock W, Anderson G, Anderson N, Aynacioglu S, Baranova A, Campagna SR, Chen R, Choiniere J, Dearth SP, Feng WC, Ferguson L, Fox G, Frishman D, Grossman R, Heath A, Higdon R, Hutz MH, Janko I, Jiang L, Joshi S, Kel A, Kemnitz JW, Kohane IS, Kolker N, Lancet D, Lee E, Li W, Lisitsa A, Llerena A, Macnealy-Koch C, Marshall JC, Masuzzo P, May A, Mias G, Monroe M, Montague E, Mooney S, Nesvizhskii A, Noronha S, Omenn G, Rajasimha H, Ramamoorthy P, Sheehan J, Smarr L, Smith CV, Smith T, Snyder M, Rapole S, Srivastava S, Stanberry L, Stewart E, Toppo S, Uetz P, Verheggen K, Voy BH, Warnich L, Wilhelm SW, Yandl G.
OMICS. 2014 Jan;18(1):10-4. doi: 10.1089/omi.2013.0149.
PMID: 24456465

Hydroxymethylation at gene regulatory regions directs stem/early progenitor cell commitment during erythropoiesis
Madzo J, Liu H, Rodriguez A, Vasanthakumar A, Sundaravel S, Caces DB, Looney TJ, Zhang L, Lepore JB, Macrae T, Duszynski R, Shih AH, Song CX, Yu M, Yu Y, Grossman R, Raumann B, Verma A, He C, Levine RL, Lavelle D, Lahn BT, Wickrema A, Godley LA.
Cell Rep. 2014 Jan 16;6(1):231-44. doi: 10.1016/j.celrep.2013.11.044. Epub 2013 Dec 27.
PMID: 24373966

Bionimbus: a cloud for managing, analyzing and sharing large genomics datasets
Heath AP, Greenway M, Powell R, Spring J, Suarez R, Hanley D, Bandlamudi C, McNerney ME, White KP, Grossman RL.
J Am Med Inform Assoc. 2014 Jan 24. doi: 10.1136/amiajnl-2013-002155. [Epub ahead of print]
PMID: 24464852

Lab Members

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M
Folker Meyer

Folker Meyer

Argonne, Core Member, Sr. Fellow,
Computational Biologist, Mathematics and Computer Science Division, Argonne National Laboratories
Senior Fellow, Computation Institute, The University of Chicago
(630) 252-3261

News

Big Data Versus the Big C

IGSB investigators Bob Grossman and Megan McNerney
are highlighted in an Outlook Cancer: Bioinformatics profile in the May 29, 2014 issue of Nature.

Open Science Data Cloud – Partnerships for International Research & Education

TRAVEL ABROAD WHILE RESEARCHING THE LATEST TECHNOLOGIES IN CLOUD COMPUTING WITH NSF FUNDED OSDC-PIRE FELLOWSHIP                                                             DEADLINE: April 30, 2014

The Open Science Data Cloud PIRE project provides international research and education experiences through training and study at universities and research institutes around the world with leading scientists in computing. Increase your expertise in managing and analyzing data.

Robert Grossman named a Federal 100 Award winner

The annual list, published by Federal Computer Week, recognizes government, industry and academic leaders who have played pivotal roles in the federal government IT community.

IGSB Core Faculty Robert Grossman appointed Chief Research Informatics Officer

Robert Grossman, PhD, assumed the role of chief research informatics officer and is currently overseeing a research group focused on bioinformatics, data mining, data intensive computing and related areas. Press Release

Research Papers

Michael Rust Lab

Michael Rust

Institute for Genomics and Systems Biology
The University of Chicago
900 East 57th Street
KCBD 10124
Chicago, IL 60637

Phone: (773)-834-1463

About the Lab

My lab is interested in understanding how the properties of living cells emerge from the stochastic reactions of molecular components. We use a mixture of biophysical, biochemical, genomic, mathematical modeling, and single-cell microscopy approaches to link the properties of molecules to the systems-level behavior of cells. Most of our attention is currently focused on an oscillatory protein network found in the cyanobacterium Synechococcus elongates that the organism uses to predict the time of day. Remarkably, the biological rhythms generated by this circadian clock can be reconstituted in a test tube using three purified protein components - KaiA, KaiB, KaiC - making this the best-defined biological oscillator currently known. It is possible to reconstitute metabolic input signaling to this minimal clock by varying ATP and ADP concentrations (Rust et al, 2011).  We are actively pursuing a quantitative understanding of the reactions that generate oscillations and the robustness properties of this minimal circadian clock. We are also working outward to expand the functions that can be studied in a purified context and include additional components from the in vivo clock system. We seek to tie the biochemical and biophysical properties of these components back to physiologically relevant conclusions for the organism by making quantitative measurements of growth rate and single-cell behavior, including experiments that are uniquely possible in microbial model systems.


We have recently shown that both robustness and adaptability of the clock are determined by the two enzymatic domains of KaiC (Phong et al, 2013).  One of the domains, CII, phosphorylates itself in response to input signals.  CI, a domain of previously unknown function, is insulated from input signals and sets a slow, constant timescale for the interaction between KaiC and the negative regulator KaiB. By building mathematical models of this system, we showed that this two-domain architecture is needed to get the combination of robust period and tunable phase in the circadian clock.  These models will help to illuminate the structures of the clock networks in humans and other organisms where input-sensitive and input-insensitive feedback loops may also be required for proper function.

Selected publications

Mixtures of opposing phosphorylations within hexamers precisely time feedback in the cyanobacterial circadian clock
Lin J, Chew J, Chockanathan U, Rust MJ.
Proc Natl Acad Sci U S A. 2014 Sep 16;111(37):E3937-45. doi:10.1073/pnas.1408692111. Epub 2014 Sep 2.
PMID: 25197081

Rhythms in energy storage control the ability of the cyanobacterial circadian clock to reset
Pattanayak GK, Phong C, Rust MJ.
Curr Biol. 2014 Aug 18;24(16):1934-8. doi: 10.1016/j.cub.2014.07.022. Epub 2014 Aug 7.
PMID: 25127221

The cyanobacterial clock and metabolism
Pattanayak G, Rust MJ.
Curr Opin Microbiol. 2014 Apr;18:90-5. doi: 10.1016/j.mib.2014.02.010. Epub 2014 Mar 22.
PMID: 24667330

Ant control efficacy of pyrethroids and fipronil on outdoor concrete surfaces
Jiang W, Soeprono A, Rust MK, Gan J.
Pest Manag Sci. 2014 Feb;70(2):271-7. doi: 10.1002/ps.3555. Epub 2013 Jun 27.
PMID: 23576335

Lab Members

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M
Folker Meyer

Folker Meyer

Argonne, Core Member, Sr. Fellow,
Computational Biologist, Mathematics and Computer Science Division, Argonne National Laboratories
Senior Fellow, Computation Institute, The University of Chicago
(630) 252-3261

News

IGSB Students Participate in iGEM Competition

IGSB students in Mike Rust's lab are collaborating on an International Genetically Engineered Machines (iGEM) project about synthetic biology. IGSB team members are using standardized biological parts provided by iGEM and molecular components they have devised to engineer E.coli mutator strains that can optimize the production of a desired metabolite using a novel technique in directed evolution. The team will go to the 2014 iGEM jamboree at MIT to present their research. Participating iGEM teams from around the world will also attend and demonstrate synthetic living systems with innovative functions and capabilities.

Mike Rust Honored by Being Named a Pew Scholar

IGSB Core Member, Mike Rust, was
honored today by being named a Pew
Scholar in the Biomedical Sciences by the
Pew Charitable Trusts. Pew Scholars are
selected by a national advisory committee.
They receive flexible funding over four
years to seed innovation at the start of
independent research careers.

The inner workings of the circadian clock

Michael Rust and colleagues reveal the biochemical mechanisms that allow the oscillations of the cyanobacterial biological clock to be tuned to changes in the environment while simultaneously maintaining a robust 24-hour period.

Research Papers

Dionysios Antonopoulos Lab

Dionysios Antonopoulos

Argonne National Laboratory
9700 S. Cass Avenue
Bldg 202, Room A-249
Argonne, IL 60439

Phone: (630) 252 3935

About the Lab

My laboratory specializes in microbial ecology and using metagenomic-enabled approaches to study communities of microorganisms in a variety of environments. We apply next -generation DNA sequencing technologies towards describing both the structure and function of microbial communities in these systems, taking advantage of the computational resources available at Argonne for handling the scale of data afforded by these technologies. I started my career as a microbiologist studying the cellulose-degrading capabilities of bacteria from production livestock, making extensive use of anaerobic cultivation buoyed by the then emerging area of comparative microbial genomics.  My interest in understanding mammalian gastrointestinal function has expanded to research in environmental systems (subsurface and topsoil systems) using metagenomics. Although the scales are vastly different between the two, similar approaches based in classical ecological theory can be used for both gastrointestinal and field research to circumnavigate the complex microbial communities underlying system function.

In collaboration with colleagues at the University of Chicago these approaches were used to understand the role that diet plays in promoting complex immune disorders such as inflammatory bowel disease (IBD). This study, which appeared in the journal Nature, provides new insights into why some people are more likely than others to develop IBD (Devkota et al, 2012). Working with a mouse model, we traced both the shift in the microbial community structure and the corresponding host immune response to a diet high in saturated (milk-derived) fats. To dissolve such fats, the liver produces a form of bile rich in sulfur. When the bile reaches the intestines, a microbe called Bilophila wadsworthia – the name means “bile loving” – blooms. Such blooms can trigger the immune system in people with a genetic predisposition. Moreover, the byproducts of this microbe’s interaction with bile can amplify the effect, making the bowel more permeable and unleashing an unregulated immune response in individuals at high risk for diseases such as IBD.

Presently, as part of the Human Microbiome Project, my laboratory is focused on understanding how microbial communities re-establish themselves in the GI tract following resectioning of the lower GI tract (creation of an ileal pouch-anal anastomosis [IPAA]) used to treat ulcerative colitis, a form of inflammatory bowel disease (IBD). As the microbial community restablishes itself following this surgical procedure we want to understand what aspects of the community lead to a healthy state versus reversion to the disease state (pouchitis). In collaboration with the University of Michigan, Michigan State University, and the Marine Biological Laboratory we are using a multi-pronged approach to studying this phenomenon by way of both cultivation and non-cultivation based approaches (Young et al, 2013)(Vital et al, 2013).

Selected publications

Young VB, Raffals LH, Huse SM, Vital M, Dai D, Schloss PD, Brulc JM, Antonopoulos DA, Arrieta RL, Kwon JH, Reddy KG, Hubert NA, Grimm SL, Vineis JH, Dalal SM, Morrison HG, Eren AM, Meyer F, Schmidt TM, Tiedje JM, Chang EB, ML Sogin. Multiphasic analysis of the temporal development of the distal gut microbiota in patients following ileal pouch anastomosis.  BMC Microbiome. 2013 1:9. doi:10.1186/2049-2618-1-9.

Vital M, Penton CR, Wang Q, Young VB, Antonopoulos DA, Sogin M, Morrison HG, Raffals L, Chang EB, Huffnagle GB, Schmidt TM, Cole JR, Tiedje JM. A gene-targeted approach to investigate the intestinal butyrate-producing bacterial community. BMC Microbiome. 2013 1:8. doi:10.1186/2049-2618-1-8.

Devkota S, Wang Y, Musch MW, Leone V, Fehlner-Peach H, Nadimpalli A, Antonopoulos DA, Jabri B, Chang EB.Dietary-fat-induced taurocholic acid promotes pathobiont expansion and colitis in Il10-/- mice. Nature. 2012 Jul 5;487(7405):104-8. doi: 10.1038/nature11225.

Desai N, Antonopoulos D, Gilbert JA, Glass EM, Meyer F. From genomics to metagenomics. Curr Opin Biotechnol. 2012 Feb;23(1):72-6. doi: 10.1016/j.copbio.2011.12.017.

Harrell L, Wang Y, Antonopoulos D, Young V, Lichtenstein L, Huang Y, Hanauer S, Chang E. Standard colonic lavage alters the natural state of mucosal-associated microbiota in the human colon. PLoS One. 2012;7(2):e32545. doi: 10.1371/journal.pone.0032545.

Lab Members

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M
Folker Meyer

Folker Meyer

Argonne, Core Member, Sr. Fellow,
Computational Biologist, Mathematics and Computer Science Division, Argonne National Laboratories
Senior Fellow, Computation Institute, The University of Chicago
(630) 252-3261

Andrey Rzhetsky Lab

Andrey Rzhetsky

Institute for Genomics and Systems Biology
The University of Chicago
900 East 57th Street
KCBD
Chicago, IL

Phone: (773) 834-7367 Fax: (773) 834-2877

About the Lab

Our group is engaged in a series of computational projects that involve mathematical modeling and analysis of disparate data sets, such as electronic medical records, scientific texts, and high-throughput experimental data.  The overarching goal of such analyses is formulating and testing hypotheses regarding interplay of genetic and environmental mechanisms of human disease.  Formulation and testing of models requires dynamic collaboration with a range of experts in disease phenotype, genetics, statistical modeling, epidemiology, and sociology of science.  We also closely collaborate with groups producing high-throughput data on data interrogation and experimental validation of computational predictions.

We are currently developing approaches for large-scale modeling and analyses of a time-series of phenotypic and environmental records, as represented in patient record databases.  In parallel, we are developing models to analyze gene association and genetic linkage data in a molecular network context, explicitly allowing for multigenic models.  We will implement joint probabilistic models of groups of disease phenotypes, accounting for their dependence on genetic variation, the proximity of genes in molecular networks, and environmental events.  Our aim is to integrate these multi-level models to jointly analyze genomic, clinical and textual data, so as to obtain insights into genetic and environmental factors that, in combination, determine disease phenotypes.

Selected publications

Evans J, A. Rzhetsky A, Philosophy of Science. Machine Science. Science 329, 399 (Jul 23, 2010).

Iossifov I, Rodriguez-Esteban R, Mayzus KJ, Millen J, Rzhetsky A. Looking at cerebellar malformations through text-mined interactomes of mice and humans. PLoS Comput Biol 5, e1000559 (Nov, 2009)

Feldman I, Rzhetsky A, Vitkup D. Network properties of genes harboring inherited disease mutations. Proc Natl Acad Sci USA 105, 4323 (Mar 18, 2008)

Rzhetsky A, Wajngurt D, Park N, Zheng T. Probing genetic overlap among complex human phenotypes. Proc Natl Acad Sci USA 104, 11694 (Jul 10, 2007)

Lab Members

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M
Folker Meyer

Folker Meyer

Argonne, Core Member, Sr. Fellow,
Computational Biologist, Mathematics and Computer Science Division, Argonne National Laboratories
Senior Fellow, Computation Institute, The University of Chicago
(630) 252-3261

News

New data-mining effort launched to study mental disorders

The Sylvio O. Conte Center, a multi-institutional effort based at the University of Chicago, will combine the statistical power of pre-existing genetics, pharmacogenomics, text-mining and clinical record databases to confront diseases that have so far frustrated researchers.Press Release

Research Papers

Kevin White Lab

Kevin White

James and Karen Frank Professor
Department of Human Genetics
Director, Institute for Genomics and Systems Biology
The University of Chicago

The Institute for Genomics and Systems Biology
The University of Chicago
900 East 57th Street
KCBD 10100A
Chicago, IL 60637

Phone: (773) 834-0074

About the Lab

The White lab studies the coordinated action of networks of genes that control developmental, disease and evolutionary processes. We have particular focus on discovery of genetic factors that contribute to cancer development and progression, and on building genome-wide models of transcriptional networks. We use an integrated approach that makes use of genome and transcriptome sequencing, large-scale protein-protein and protein-DNA interaction analyses, measurement of chromatin state, systematic RNAi and CRISPR mutational analysis, and high throughput functional analyses of genomic regulatory elements. By applying our methods to both closely and distantly related species, we are investigating how conserved molecular networks control basic developmental processes and how variation in molecular networks translates into variation in organismal phenotypes. We are also particularly interested in the transcriptional networks controlled by nuclear receptor proteins in development and disease. For example, we have produced genome-wide maps of the entire repertoire of nuclear receptors expressed in breast cancer cells, and this has led to the discovery of previously untargeted nuclear receptors that are promising drug candidates. We then test such candidates in mouse models, and we are attempting to ‘reverse engineer’ the nuclear receptor regulatory networks in breast cancer using a combination of genome-scale data generation, computational techniques and genomic engineering of cell lines and mice. We also have recently built novel algorithms for discovering tumor drivers and tumor risk factors from large-scale sequencing data, such as those available from The Cancer Genome Atlas. In those projects we have identified significantly co-occurring mutations and tested for genetic interactions in cell lines and in patient survival data, we have identified dozens of novel fusion genes and then synthesized them for testing in cell and mouse models, and we have systematically identified germline variants that may contribute to cancer risk and tested their functional roles using CRISPR engineered cell models.  Another focus of the lab is studying genetic regulatory programs that are highly conserved between fly and human. This has led to discoveries such as a role for the protein SPOP in both Drosophila embryogenesis and human kidney cancer, and to the identification of conserved targets of natural selection during adaptation to hypoxia (low oxygen) in both flies and humans. Related to this comparative work is our lab’s contributions to the ENCODE and modENCODE projects, where we have been systematically comparing the binding patterns of transcription factors genome-wide in flies, worms and humans. Our lab also contributes to the NIH GTEx and psychENCODE projects through our investigations of the relationship between genomic variation and variation in transcript and protein expression. Finally, we have recently embarked on an ambitious project in pancreatic cancer to co-analyze large numbers of tumor genomes, tens of thousands of electronic medical records, and literature databases to build predictive models of which patients might respond to which treatments. This work is facilitated by the use of patient-derived xenograft models, as well as mouse models developed using the CRISPR Cas9 system. Our goal is to develop algorithmic approaches to rapidly assess a tumor’s genomic and physiological state, then test drugs in mouse models that ultimately can be moved into patients.

Ci, W., et al., SPOP promotes tumorigenesis by acting as a key regulatory hub in kidney cancer. submitted.

TCGA, T.C.G.A.N., Comprehensive Molecular Portraits of Human Breast Tumors. Nature, in press.

Kittler, R., et al., A Comprehensive Map of Nuclear Receptor Networks in Breast Cancer Cells. Cell Rep. 2013 Feb 21;3(2):538-51. doi: 10.1016/j.celrep.2013.01.004. Epub 2013 Jan 31.

Ni X, Zhang YE, Nègre N, Chen S, Long M, White KP. Adaptive evolution and the birth of CTCF binding sites in the Drosophila genome. 2012 Nov;10(11):e1001420. doi: 10.1371/journal.pbio.1001420. Epub 2012 Nov 6.

ENCODE Project Consortium, et al. An integrated encyclopedia of DNA elements in the human genome.Nature. 2012. Sep 6;489(7414):57-74. doi: 10.1038/nature11247.

Dore, L.C., et al., Chromatin occupancy analysis reveals genome-wide GATA factor switching during hematopoiesis. Blood, 2012. 119(16): p. 3724-33.

Cancer Genome Atlas Research, N., Integrated genomic analyses of ovarian carcinoma. Nature, 2011. 474(7353): p. 609-15.

Negre, N., et al., A cis-regulatory map of the Drosophila genome. Nature, 2011. 471(7339): p. 527-31.

Al-Dhaheri, M., et al., CARM1 is an important determinant of ERalpha-dependent breast cancer cell differentiation and proliferation in breast cancer cells. Cancer Res, 2011. 71(6): p. 2118-28.

Godley, L.A., et al., An integrated genomic approach to the assessment and treatment of acute myeloid leukemia. Semin Oncol, 2011. 38(2): p. 215-24.

Consortium, E.P., A user’s guide to the encyclopedia of DNA elements (ENCODE). PLoS Biol, 2011. 9(4): p. e1001046.

Hah, N., et al., A rapid, extensive, and transient transcriptional response to estrogen signaling in breast cancer cells. Cell, 2011. 145(4): p. 622-34.

Negre, N., et al., A comprehensive map of insulator elements for the Drosophila genome. PLoS Genet, 2010. 6(1): p. e1000814.

modEncode, et al., Identification of functional elements and regulatory circuits by Drosophila modENCODE. Science, 2010. 330(6012): p. 1787-97.

Hua, S., R. Kittler, and K.P. White, Genomic antagonism between retinoic acid and estrogen signaling in breast cancer. Cell, 2009. 137(7): p. 1259-71.

Liu, J., et al., Analysis of Drosophila segmentation network identifies a JNK pathway factor overexpressed in kidney cancer. Science, 2009. 323(5918): p. 1218-22.

Celniker, S.E., et al., Unlocking the secrets of the genome. Nature, 2009. 459(7249): p. 927-30.

Gauhar, Z., et al., Genomic mapping of binding regions for the Ecdysone receptor protein complex. Genome Res, 2009. 19(6): p. 1006-13.

Tian, F., et al., Flynet: a genomic resource for Drosophila melanogaster transcriptional regulatory networks. Bioinformatics, 2009. 25(22): p. 3001-4.

Hua, S., et al., Genomic analysis of estrogen cascade reveals histone variant H2A.Z associated with breast cancer progression. Mol Syst Biol, 2008. 4: p. 188.

Cancer Genome Atlas Research, N., Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature, 2008. 455(7216): p. 1061-8.

Hooper, S.D., et al., Identification of tightly regulated groups of genes during Drosophila melanogaster embryogenesis. Mol Syst Biol, 2007. 3: p. 72.

Negre, N., et al., Chromosomal distribution of PcG proteins during Drosophila development. PLoS Biol, 2006. 4(6): p. e170.

Moorman, C., et al., Hotspots of transcription factor colocalization in the genome of Drosophila melanogaster. Proc Natl Acad Sci U S A, 2006. 103(32): p. 12027-32.

Rifkin, S.A., et al., A mutation accumulation assay reveals a broad capacity for rapid evolution of gene expression. Nature, 2005. 438(7065): p. 220-3.

Stolc, V., et al., A gene expression map for the euchromatic genome of Drosophila melanogaster. Science, 2004. 306(5696): p. 655-60.

Li, T.R. and K.P. White, Tissue-specific gene expression and ecdysone-regulated genomic networks in Drosophila. Dev Cell, 2003. 5(1): p. 59-72.

Michaut, L., et al., Analysis of the eye developmental pathway in Drosophila using DNA microarrays. Proc Natl Acad Sci U S A, 2003. 100(7): p. 4024-9.

Rifkin, S.A., J. Kim, and K.P. White, Evolution of gene expression in the Drosophila melanogaster subgroup. Nat Genet, 2003. 33(2): p. 138-44.

Sun, L.V., et al., Protein-DNA interaction mapping using genomic tiling path microarrays in Drosophila. Proc Natl Acad Sci U S A, 2003. 100(16): p. 9428-33.

Arbeitman, M.N., et al., Gene expression during the life cycle of Drosophila melanogaster. Science, 2002. 297(5590): p. 2270-5.

Lab Members

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Folker Meyer

Folker Meyer

Argonne, Core Member, Sr. Fellow,
Computational Biologist, Mathematics and Computer Science Division, Argonne National Laboratories
Senior Fellow, Computation Institute, The University of Chicago
(630) 252-3261

News

Audrey Fu Awarded K99 NIH Grant

IGSB Research Professional, Dr. Audrey Fu, was awarded a K99 NIH grant to support a research project entitled: Causal Inference of Gene Regulatory Networks with Application to Breast Cancer. The aim is to develop statistical models and computational methods for the inference of causal gene regulatory networks. The project will investigate how genetic variation acting on biological networks influences development and progression of diseases, using subtypes of breast cancer as a disease model.

IGSB Summer High School Student Accepted to Attend UChicago

Madison Olmsted, from Rio Americano High School in Sacramento, California, participated in a Research in Biological Sciences, Part 2 (RIBS-2) program in Kevin White’s lab last summer. 

Hormones and Microbes Interact to Modify Autoimmune Disease Progression

IGSB/CBC Postdoctoral Fellow Aly Khan co-authored a study on a previously unknown interaction between gut bacteria and gender bias in autoimmune diseases. The study proposes a novel two-signal model, in which hormones and microbes together influence the incidence and severity of autoimmune diseases. The results were published in Cell Immunity and are highlighted in a featured article in the issue.

Bionimbus Protected Data Cloud eliminates need for massive storage infrastructure

Bionimbus, an advanced cloud-based computing environment, helped Megan McNerney discover tumor suppressor gene, CUX1, is frequently inactivated in acute myeloid leukemia. The principal investigator for Bionimbus is Robert Grossman.

Gifts to boost University of Chicago as hub for biomedical ‘big data’

Two major gifts will build momentum behind the University of Chicago’s leadership in biomedical computation by assembling experts in the field and furnishing them with the tools to use “big data” to understand and treat disease.  Kevin White and Robert Grossman will lead the Pancreatic Cancer Genomic Medicine Initiative, which aims to improve care for patients with this disease using genomic and physiological data.

Tracing adaptive evolution of regulatory elements in the fly genome

Kevin White and colleagues determine the binding sites of the insulator protein CTCF in four Drosophila species whose divergence spans 25 million years in evolutionary time.  Their findings provide evidence for positive selection shaping the evolution of these regulatory sites and through them, the genes they control.

Aashish Jha was recently selected to receive a predoctoral fellowship from the University of Chicago

IGSB graduate student, Aashish Jha, in Kevin White?s lab, was recently selected to receive a predoctoral fellowship from the University of Chicago?s Center for Systems Biology of Oxygen Sensing.  An Institutional Training Grant, “Training in O2 Biology in Health & Disease,” will support his research training. This award is based on Aashish Jha?s academic record, scienti?c performance in the lab, and relevance of his thesis project to the ?eld of oxygen biology.

Research Papers