Developing lineage tracing tools to study single-cell heterogeneity  and stress response in 3D biofilms

ORAL

Abstract

Biofilms consist of surface-associated bacteria embedded in a protective extracellular matrix. Recently, we found heterogeneous expression of multiple genes and secondary messenger molecules in developing clonal biofilms, coupled to the cells’ mechanical environment and spatial organization. However, how these heterogeneities emerge, and their effect on the biofilm’s lifecycle remains largely unknown. Beyond this, it is widely believed that a differential stress response underlies the elevated antibiotic resistance of cells in biofilm, but very little is known about how this heterogeneous response occurs.  Here, we use the model organism Vibrio cholerae to study the emergence of spatiotemporal patterning and heterogeneity within biofilms at the single-cell level. We developed a methodology to trace full lineages (family trees) in 3D biofilms grown from a single cell, using a combination of confocal microscopy, fluorescent reporters and custom computer vision algorithms. In this approach, we use bright fluorescent markers to track the 3D position of all the cells in the developing biofilm without requiring cell segmentation.  With this novel technique, we are studying the emergence of non-genetic inheritance in biofilms, allowing us to determine if heterogeneity emerges stochastically or from a deterministic developmental program.  We also seek to understand the consequences of this heterogeneity on biofilm development and stress response.

*This work was supported by the National Institute of General Medical Sciences of the National Institutes of Health under Award Number DP2GM146253 (J.Y.) and by a Burroughs Wellcome Fund Postdoctoral Diversity Enrichment Program (BWF PDEP) award sponsored by the Revson Foundation (D.V-M). 

Presenters

  • Diana S Valverde Mendez

    • Yale University

Authors

  • Diana S Valverde Mendez

    • Yale University
  • Jung-Shen Benny Tai

    • Yale University
  • Jing Yan

    • Yale University