Daniel Weinreich, PhD, Harvard University 1998Edit My Page
Professor Weinreich is interested in how genetic novelty fuels evolution by natural selection. Using tools from computer science and mathematics he models the evolutionary consequences of various patterns of interaction within the genome. This motivates complementary experimental work using techniques of molecular biology and microbiology to measure patterns of interaction within genes and genomes of bacteria and bacteriophage. This experimental work in turn drives novel theory.
Professor Weinreich received his bachelor's degree in computer science from the University of Michigan in 1983. Computer science has a long tradition of interest in the algorithmics of Darwin's paradigm and this provides the formal framework for Weinreich's research. After nine years as a software engineer, he began his graduate studies in evolutionary and population genetics at Harvard University. He received his PhD in 1998 and did postdoctoral work at Brown University (1998-2000), the University of California (2000-2001) and at Harvard University (2001-2006).
Professor Weinreich was appointed an Assistant Professor in the Department of Ecology and Evolutionary Biology at Brown in January 2007. He is also a member of the Center for Computational Molecular Biology at Brown.
I work on the evolutionary genetics of biological adaptation, in theory and in laboratory populations of microbes.
I am actively seeking new lab members at all levels from High School interns to postdocs. Please click the Teaching tab above and see the BIOL 1950/1960/2980 description for ongoing student projects. Click here to visit the lab web page. Or send me an email describing your background and interests if you would like to join us.
Some time ago I developed novel theory to describe the evolutionary constraints that that mutational interactions impose (Weinreich 2005, Weinreich et al. 2005, Weinreich and Chao 2005). Specifically I pointed out that if mutation X unconditionally improves an organism's fitness but Y improves it only in the presence of X, a population's evolutionary trajectory would be constrainted because mutations would only be favored in some temporal order (here, Y must follow X). We designated this form of mutational interaction sign epistasis (Weinreich et al. 2005).
Microbes offer several technical advantages that render them an excellent experimental complement to this theoretical framework. For example, the ease of reverse genetics in E. coli allowed us to construct all 32 combinations of five point mutations in a β-lactamase gene known to jointly increase antibiotic resistance ~100,000-fold. We showed that four of these five mutations exhibit sign epistasis and that as a result, only 18 of the 5! = 120 possible mutational trajectories to this high-resistance quintuple-mutant are selectively accessible (Weinreich et al. 2006).
This finding raises the question of mechanism: what are the functional interactions among these five mutations responsible for this sign epistasis? A simple biophysical model of protein evolution suggests that sign epistasis may occur if mutations pleiotropically perturb multiple phenotypes, each under stabilizing selection (DePristo, Weinreich and Hartl 2005) and we are testing this hypothesis using β-lactamase. We imagine that the drug resistance conferred by each β-lactamase sequence may be decomposed into it's expression level, it's protein product's folding stability, enzymatic properties, etc.
This and several other current projects are detailed under RESEARCH PROJECTS at the top of this page.
2011 -- Brown University Center for Computational Molecular Biology Sabbatical Travel Award.
2010 -- Brown University Center for Computational Molecular Biology Seed Award.
2009 -- Brown University Center for Computational Molecular Biology Travel Award.
2009 -- Brown University Center for Computational Molecular Biology Seed Award.
2008 -- Brown University Center for Computational Molecular Biology Teacher Award.
2008, 2009 -- Brown University NSF/EPSCoR Proteomics Instrumentation Use Award.
2008 -- Brown University Salomon Faculty Research Award.
2007 -- Brown University Center for Computational Molecular Biology Scholarship Innovator Award.
2000 -- NIH National Research Service Award.
Society for the Study of Evolution
Developing and Testing a Novel Geometric Model of Protein Evolution.
Daniel Weinreich, PI
Sept 1, 2011 Aug 31, 2016. $1,511,619.
NSF Emerging Frontiers Award DEB 1038657
Inferring Biological Mechanisms from Mutational Interactions.
Daniel Weinreich, PI
Sept 15, 2010 - Aug 31, 2013 $259,079.
Brown University Salomon Faculty Research Award
The genetic basis of adaptation to novel environments in laboratory microbial populations.
Feb 1, 2008 - June 30, 2009 $16,000.
NSF Population Biology DEB 0343598
Molecular evolvability in theory and in a bacterial drug-resistance gene
Dr. Daniel M. Weinreich, Author, Co-Investigator; Dr. Daniel L. Hartl, PI
Feb 1, 2004 - Jan 31, 2007 $236,000
NIH National Research Service Award F32 GM20736
Molecular evolution in the bacteriophage φ6
Aug 1, 2000 - Jul 31, 2003 $109,164
NSF Population Biology DEB-9981497
Recombination, dominance, and selection on amino acid mutations
Dr. Daniel M. Weinreich, Co-Investigator; Dr. David Rand, PI
Mar 1, 2000 - Feb 28, 2002 $172,367
NIH National Research Service Award
Animal mtDNA and a novel model of molecular evolution
Awarded Jul 1998; declined. $79,312
NSF Doctoral Dissertation Improvement Grant DEB-97000982
June 1 1997 - May 31, 1998 $7,940
Harvard University Department of Organismic and Evolutionary Biology
Student Research Grant
Jan 1, 1997 $3,500
NIH Genetics Training Grant GM07620
Nancy Kleckner, PI
Sept 1, 1992 - Aug 31, 1997
BIOL 0380 -- Ecology and Evolution of Infectious Disease (Fall term each year). In this course we will (1) survey the diverse biology of microbes responsible for human infectious disease, (2) develop and apply ecological and evolutionary theory to infectious microbes, (3) provide practical experience interpreting and synthesizing the peer-reviewed scientific literature, and (4) provide exposure to recent biotechnological advances. Weekly student presentations of published papers from a reading list will be complemented with lectures covering the discovery of infectious microbes, the role of genetic novelty, population structure and transmission mode, and the influence of clinical therapies and host immune response. Expected: BIOL 0200 or equivalent.
BIOL 1430 -- Computational Theory of Molecular Evolution (Fall term in odd-numbered years). This course employs intellectual traditions from computer science and biology to investigate the properties and principles of DNA sequence evolution. The roles of mutation, natural selection, population size and subdivision, and genetic recombination are explored. Lectures complemented by web-based computer exercises. Expected: either an introduction to evolution (BIOL 0200, 0480) or to computer science (CSCI 0150, 0160, 0170).
BIOL 1950/1960/2980 -- Directed Research/Independent Study/Graduate Independent Study. I am actively seeking highly motivated undergraduate and fifth-year masters students with interests in theoretical or experimental evolutionary genetics. Click on the RESEARCH tab above to learn more about ongoing work in the lab. Current student-led projects include:
Characterization of 'persister' dynamics (genetically drug-sensitive bacteria with drug-resistant phenotype) in Escherichia coli.
Characterizing life history traits in bacteriophage φX174.
Characterizing the phenotypic space of antibiotic resistance.
Characterizing caterpillars for parasitoid wasp infection.
Previous undergraduate projects:
Characterization of the role of standing genetic variation in novel environments using lab populations of Escherichia coli.
Characterization of epistatic interactions among compensatory mutations in the bacteriophage φX174.
Characterization of natural diversity among bacteriophage of archaea in Rhode Island.
Bioinformatic analysis of CRISPR spacer sequences.
The importance of codon and codon-pair bias in the bacteriophage φX174.
Please email if you are a Brown student interested in exploring the possibility of developing an independent research project with me.
- Computational Theory of Molecular Evolution (BIOL 1430)
- Directed Research/Independent Study (Biol 1950/1960)
- Ecology and Evolution of Infectious Disease (BIOL 0380)
- Graduate Independent Study (BIOL 2980)
- Weinreich, Daniel M. (2011) High-throughput identification of genetic interactions in HIV-1. Nature Genetics 43: 398-400. [pdf](2011)
- Watson, Richard A., Daniel M. Weinreich and John Wakeley (2010). Genome Structure and the Benefit of Sex. Evolution 65:523 536. [pdf](2010)
- Lozovsky, Elena, Thanat Chookajorn, Kyle Brown, Daniel M. Weinreich and Daniel Hartl (2009). Stepwise acquisition of pyrimethamine resistance in the malaria parasite. PNAS 106:12015 12030. [pdf](2009)
- Poelwijk, Frank J., Daniel J. Kivet, Daniel M. Weinreich and Sander J. Tans (2007) Empirical fitness landscapes reveal accessible paths. Nature 445:383-386. doi:10.1038/nature05451 [pdf](2007)
- Weinreich, Daniel M., Nigel Delaney, Mark A. DePristo and Daniel L. Hartl (2006). Darwinian evolution can follow only very few mutational paths to fitter proteins. Science 312:111-114. doi:10.1126/science.1123539 [pdf] [Supporting Online Material] [Research Highlight in Nature Reviews Genetics](2006)
- Weinreich, Daniel M., Richard A. Watson and Lin Chao (2005). Perspectives: Sign epistasis and constraint on evolutionary trajectories. (Cover article) Evolution 59:1165-1174. doi:10.1111/j.0014-3820.2005.tb01768.x [pdf](2005)
- DePristo, Mark A, Daniel M. Weinreich and Daniel L. Hartl (2005). Missense meanderings through sequence space: a biophysical perspective on protein evolution. Nature Reviews Genetics 6:678-687. doi:10.1038/nrg1672 [pdf](2005)