M. Tikhonov

Linear-regression-based algorithms can succeed at identifying microbial functional groups despite the nonlinearity of ecological function

The paper evaluates regression-based methods for identifying microbial functional groups using synthetic data, finding that simpler linear methods can outperform complex ones.

Improving the accuracy of bulk fitness assays by correcting barcode processing biases

The paper develops a computational method to correct barcode processing biases in bulk fitness assays, improving fitness estimates in yeast variant libraries.

Metabolomic rearrangement controls the intrinsic microbial response to temperature changes

The paper shows that metabolomic rearrangements, not stress responses, control bacterial temperature adaptation, with a model explaining growth dynamics under temperature shifts.

Global patterns in gene content of soil microbiomes emerge from microbial interactions

The paper shows that environmental filtering alone cannot explain global patterns in soil microbiome gene content, as ecological interactions between genotypes drive observed associations with pH.

Learning the functional landscape of microbial communities

The paper introduces community-function landscapes to predict microbial community functions from strain presence/absence, showing they can be accurately trained with limited data and are broadly applicable.

Defining coarse-grainability in a model of structured microbial ecosystems

The paper defines coarse-grainability in microbial ecosystems by showing that simplified models can accurately represent complex systems under specific conditions.

Photo sensing and quorum sensing are integrated to control bacterial collective behaviors.

This study shows that light sensing via BphP regulates the KinB-AlgB two-component system, which controls biofilm formation and virulence in Pseudomonas aeruginosa.

Modeling the interplay between plastic tradeoffs and evolution in changing environments

The paper presents a model showing how evolutionary history influences tradeoff strength and future evolution in changing environments.

Emergent Simplicity in Microbial Community Assembly

The paper shows that microbial communities re-assemble into predictable, stable communities through non-specific metabolic cross-feeding, even when grown in minimal environments.