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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”

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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)”

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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”