Anna Sintsova

Genome-scale metabolic models for a synthetic soil microbial community as a path for understanding community functioning

The paper develops genome-scale metabolic models for a synthetic soil microbial community to understand metabolic interactions and community function.

The Ocean Microbiomics Database reveals thermal niches and projected pressure on marine microbes in a warming ocean

The paper introduces the Ocean Microbiomics Database (OMDB) to analyze microbial thermal niches and predict their response to ocean warming, showing richness declines faster than abundance.

Nuclear stress bodies enable a germline-specific transcriptional stress response in Drosophila

This study identifies nuclear stress bodies in Drosophila germline that mediate a stress response by delaying Hsf-dependent transcription and enabling selective expression of molecular chaperones over transposable elements.

Biphasic bacterial community assembly predicted from generalized first principles of monoculture growth and inferred species interactions

The paper develops a mathematical framework to predict microbial community assembly using monoculture growth kinetics and inferred species interactions, revealing biphasic community development driven by competition and cross-feeding.

Competition against the intestinal microbiota selects for pathoadaptive traits in ESBL E. coli

This study identifies how the intestinal microbiota drives the evolution of pathoadaptive traits in ESBL E. coli through adhesion and biofilm formation.

Meiotic pairing through barcode-like satellite DNA repeats

The paper demonstrates that satellite DNA barcodes facilitate meiotic pairing in Drosophila by showing that repeat mismatches disrupt pairing and that pairing defects correlate with oocyte death.

Plasticity of genetic regulation during cellular learning

This study investigates the genetic basis of cellular learning in budding yeast, showing it arises from a dynamic, redundant network with variable gene contributions and broad functional integration.

Genome-resolved diversity and biosynthetic potential of the coral reef microbiome

This study assesses the microbial biosynthetic potential of reef-building corals using genome-resolved metagenomics, revealing host-specific microbiomes with high biotechnological value.

Salmonella multimutants enable efficient identification of SPI-2 effector protein function in gut inflammation and systemic colonization

The paper uses multimutant Salmonella strains to identify SPI-2 effector functions in gut inflammation and systemic colonization, finding SopD2 and GtgE critical for mucosal pathology.

The Gfr uptake system provides a context-dependent fitness advantage to Salmonella Typhimurium SL1344 during the initial gut colonization phase

The paper shows that the gfr operon in Salmonella Typhimurium provides a fitness advantage during gut colonization by utilizing dietary Amadori compounds like fructoselysine.

Transcriptomic profiles of single-copy marker genes enable predicting bacterial growth states in microbial communities

The paper introduces a transcriptomic marker gene-based classifier to predict bacterial growth states across species in microbial communities.

Nuclear mechanostability emerges from satellite DNA condensation into chromocenters

This study shows that nuclear mechanostability arises from satellite DNA condensation into chromocenters, which help dissipate mechanical stress and protect genome integrity.

Monosaccharides Drive Salmonella Gut Colonization in a Context-Dependent Manner

This study identifies context-dependent and -independent carbohydrates used by Salmonella Typhimurium for gut colonization in mice, highlighting D-glucose, D-fructose, and D-galactose as key substrates.

mBARq: a versatile and user-friendly framework for the analysis of DNA barcodes from transposon insertion libraries, knockout mutants and isogenic strain populations

mBARq simplifies the analysis of DNA barcode data from transposon libraries and isogenic strains through a user-friendly tool and web app integration.

Predicting base editing outcomes with an attention-based deep learning algorithm trained on high-throughput target library screens

This paper develops BE-DICT, a deep learning model trained on high-throughput screens to predict base editing outcomes with high accuracy.