Projects

We investigate how cell-cell interactions govern complex behavior in cell populations. We combine experimental and computational approaches and investigate three systems of biomedical relevance:

  • The opportunistic pathogen Pseudomonas aeruginosa
  • The gut microbiome
  • The tumor microenvironment

Social interaction and evolution in pathogenic bacteria

August 2013 cover

August 2013 cover

Pathogenic bacteria can be very social. Bacterial cells interact in many ways for example by signaling each other chemically, exchanging metabolites, building biofilms and moving in swarms. However, cooperation is vulnerable to cheating, which happens when individuals exploit the efforts of the collective without contributing. How do cooperative traits in bacteria evolve in spite of the evolutionary conflict between individual- and population-level interests? Can we exploit social conflicts to develop better therapies against bacterial pathogens?
We use swarming in Pseudomonas aeruginosa (an opportunistic human pathogen) as a model social behavior.

Read:
van Ditmarsch D, Boyle KE, Sakhtah H, Oyler JE, Nadell CD, Deziel E, Dietrich LEP, Xavier JB. Convergent evolution of hyperswarming leads to impaired biofilm formation in pathogenic bacteria.  Cell Reports, 2013 [open access]

de Vargas Roditi L, Boyle KE, Xavier JB. Multilevel selection analysis of a microbial social trait Molecular Systems Biology, 2013 [open Access]

Implications for antimicrobial therapies.
Drugs that target individual level traits of bacteria, such as antibiotics and other antimicrobials, create a strong selective pressure for resistance. Our growing understanding of social interaction opens the way to therapeutic strategies that do not select for resistance.

See:
Exploiting social evolution in biofilms. Boyle KE, Heilmann S, van Ditmarsch D, Xavier JB. Current Opinion in Microbiology, 2013  [PDF]

Species interaction in the gut microbiota

Text Box:  Our gut hosts bacteria in such high numbers that they outnumber our own cells by 10:1. The gut microbiota is a complex symbiotic microbial community that helps digest nutrients and fight off invasion by pathogens. Yet, in spite of its central role for human health, this complex microbial ecosystem remains largely unknown to us. Many of the bacterial species are unculturable which makes even a simple census difficult.

This is changing in recent years with the application of metagenomics and we can envision future diagnostics and therapeutics that restitute healthy balances in the microbiome. Before  clinical translation of microbiome biology is possible we must seek to understand the ecological processes governing its composition dynamics and function thoroughly. We develope mathematical modeling and analytical methods inspired by mathematical ecology.

This project was started in the Lucille Castori Center for Microbes, Inflammation and Cancer (established June 2010).

Read:
Bucci V, Bradde S, Biroli G, Xavier JB. Social Interaction, Noise and Antibiotic-Mediated Switches in the Intestinal Microbiota. PLoS Computational Biology, 2012 [open access]

Taur Y, Xavier JB, Lipuma L, Ubeda M, Goldberg J, Gobourne A, Joo Lee Y, Dubin KA, Socci ND, Viale A, Perales MA, Jenq RR, van den Brink M, Pamer EG. Intestinal Domination and the Risk of Bacteremia in Patients Undergoing Allogeneic Hematopoietic Stem Cell Transplantation. Clin Infect Dis. [PDF]

Buffie C, Jarchum I, Equinda M, Lipuma L, Gobourne A, Viale A, Ubeda-Morant C, Xavier JB, Pamer E. Profound alterations of intestinal microbiota following a single dose of Clindamycin results in sustained susceptibility to C. difficile-induced colitis.  Infection and Immunity, 2013 [PDF]

Cell-cell interactions in cancer

Text Box:  Tumors  cells have interactions with cells in its microenvironment that are essential to cancer progression and invasiveness. These interactions involve many molecular players and dependent on physical properties of the tumor microenvironment. Often, signaling and physical processes interact in complex ways. Mathematical formalism can bring this complexity to a tractable form.

We are adapting mathematical models developed for other systems to investigate cancer interactions in spatially structured environments. This can lead to novel predictive tools for tumor progression and eventual assist in the rational design of therapies.
This project is funded by the Integrative Cancer Biology Program of the NCI.

See:
Carlos Carmona-Fontaine, Vanni Bucci, Leila Akkari, Maxime Deforet, J. A. Joyce, and Joao B. Xavier.
Emergence of spatial structure in the tumor microenvironment due to the Warburg effect
PNAS, 2013 [PDF]

Chang WK, Carmona Fontaine C, Xavier JB. Tumour–stromal interactions generate emergent persistence in collective cancer cell migration Interface Focus, 2013 [PDF]

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