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Tami Lieberman, Ph.D.

Department of Civil and Environmental Engineering
Assistant Professor

E25, 5th floor


PhD, Systems Biology, Harvard University, 2014

Research Summary

Rational microbiome-based therapies have the potential to treat a wide range of diseases and promote wellness. However, we remain severely limited in our ability to employ such therapies. In particular, we cannot predict which bacterial strains have the potential to stably colonize a person. The Lieberman Lab seeks to close this knowledge gap, developing an understanding of how individual species and strains behave in the human microbiome–including the selective pressures they face, niche ranges, survival strategies, and the degree to which they adapt to individual people. The majority of our current research is focused on microbes colonizing human skin or human guts.

Within-person evolution of the microbiome, its specificity, and connection to disease
We have recently discovered that commensal bacteria in the human gut are continually evolving within individual people under the pressure of adaptive evolution–with mutations emerging and being fixed in the population within months (Zhao & Lieberman et al, in preparation). This evolution reveals genes and pathways critical to bacterial colonization in vivo, which may aid in the design of rational probiotic therapy.

My lab seeks to address the many questions brought on by this discovery. Can we use the mutations occurring in vivo to better design personalized probiotics? How specific is within-person evolution to an individual's genetics, diet, and microbial community? What are the impacts of within-person evolution on community structure and host function? Crucially, studies of within–person evolution can be performed without longitudinal studies, because bacterial strains diversify within hosts to form co-existing lineages that preserve a record of their natural history within the host (Lieberman et al, Nature Genetics, 2014).

Transmission of commensals within and between people
We are interested in how and when bacteria colonize our microbiomes, how they move around between body sites, and how within-host transmission impacts community structure. Recently, we have used fine-grained sampling, whole–genome sequencing of cultured isolates, and evolutionary inference to infer that the Propionibacterium acnes population within each pore on the human face is dominated by single lineage —resulting in pore–specific mutations (Lieberman et al, in preparation). This structure suggests pores are distinct ecological units.

Strain-level identification for disease association and epidemiology
We are developing novel methods for strain–level identification in metagenomic data, leveraging the growing number of microbial genomes and human metagenomes publicly available.

Niche characterization in the microbiome

We employ novel sampling strategies, experimental approaches, and whole–genome evolutionary inference to address questions related to niche range in the human microbiome. Can the same bacterial strain the lives on your cheek also live on your back? How many niches exist in your microbiome? What determines if a particular bacterial strain can colonize a particular microbiome?

Selected Publications

  • Lieberman TD, Wilson D, Misra R, Xiong LL, Moodley P, Cohen T, Kishony R. (2016). "Genomic diversity in autopsy samples reveals within-host dissemination of HIV– associated Mycobacterium tuberculosis." Nature Medicine, doi: 10.1038/nm.4205.
  • Baym M, Lieberman TD, Kelsic ED, Chait R, Gross M, Yelin I, Kishony R. (2016). "Spatiotemporal microbial evolution on antibiotic landscapes." Science, doi: 10.1126/science.aag0822.
  • Baym M*, Kryazhimskiy S*, Lieberman TD*, Chung H*, Desai MM, Kishony R. (2015). "Inexpensive Multiplexed Library Preparation for Megabase-Sized Genomes." PLOS ONE, doi: 10.1371/journal.pone.0128036
  • Lieberman TD, Flett KB, Yelin I, Martin TR, McAdam AJ, Priebe GP, Kishony R. (2014). "Genetic variation of a bacterial pathogen within individuals with cystic fibrosis provides a record of selective pressures." Nature Genetics, doi: 10.1038/ng.2848.
  • Lieberman TD*, Michel JB*, Aingaran M, Potter-Bynoe G, Roux D, Davis MR, Skurnik D, Lieby N, LiPuma JJ, Goldberg JB, McAdam AJ, Priebe GP, Kishony R. (2011). "Parallel bacterial evolution within multiple patients identifies candidate pathogenicity genes." Nature Genetics, doi: 10.1038/ng.997.

Last Updated: July 15, 2017