Using Metagenomics to Measure In-Situ Microbial Growth Rates

Growth rates are central to understanding microbial interactions and community dynamics. The Fuhrman Lab, which uses ‘omics data to seek a better understanding of microbial growth, interactions, and biogeographies has been evaluating a promising new approach to simultaneously determine the growth rates of many different kinds of microbes from the within-genome distributions of DNA extracted from in-situ (mixed) ocean populations. Continue reading “Using Metagenomics to Measure In-Situ Microbial Growth Rates”

Towards a Better Model for the Microbe Membrane (Revisited)

Postdoc John Casey continues to work closely with MIT-CBIOMES Group PI Mick Follows on research combining quantitative proteomics, flux balance analysis, and molecular modeling of membrane transports to develop a steady-state model of microbial acclimation to substrate limitation. A paper by the same name was recently published in PLOS Computational Biology. Continue reading “Towards a Better Model for the Microbe Membrane (Revisited)”

Turning to Traits to Understand Phytoplankton Biomass Patterns

The Irwin Group uses statistical modeling techniques to understand niches, traits, and interactions within marine microbial communities. A new paper confirms the value of trait-based approaches in investigating the mechanisms underlying phytoplankton biomass dynamics, and in predicting the community response to environmental changes. Continue reading “Turning to Traits to Understand Phytoplankton Biomass Patterns”