BMAC Weekly — 2026-W31

8 papers selected for 2026-W31.

← Weekly papers

2026-07-21–2026-07-27 · 8 papers

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

Isaline Guex, Melanie L. Stäubli, Anna Sintsova, Vladimir Sentchilo, Senka Čaušević, Adline Vouillamoz, Clara A. Bailey, Hans‐Joachim Ruscheweyh, Shinichi Sunagawa, Christian Mazza, Jan Roelof van der Meer

2026-07-10 · bioRxiv (Cold Spring Harbor Laboratory)

TL;DR. A mathematical framework integrating monoculture growth kinetics and inferred species interactions predicts biphasic community assembly in soil microcosms, with an initial competition phase followed by cross-feeding-driven growth.

Key signal. Community biomass is largely driven by cross-feeding interactions; models without species interactions reproduced only 20% of observed biomass.

Why it matters here. This work directly connects monoculture growth parameters to community dynamics, aligning with Fangzhou's interest in microbial population dynamics and community ecology.

Microbial populations & communities PDF

Eco-evolutionary dynamics lead to functionally robust and redundant communities

Lorenzo Fant, Iuri Macocco, Jacopo Grilli

2026-07-21 · PLoS Computational Biology

TL;DR. Eco-evolutionary simulations show that microbial communities converge to a functional attractor determined by environment, explaining functional redundancy despite taxonomic variability.

Key signal. Functional composition is robustly determined by environment, while taxonomic composition is non-reproducible yet constrained by functional conservation.

Why it matters here. This provides a theoretical foundation for functional redundancy in microbial communities, relevant to Fangzhou's interest in community ecology and population dynamics.

Microbial populations & communities PDF

Drift-driven microbiome simplification generates reconstructable and ecologically cohesive microbial communities

Rubén Chaboy‐Cansado, Paula Cobeta, Ramón Gallego, Alberto Rastrojo, Daniel Aguirre de Cárcer

2026-07-16 · bioRxiv

TL;DR. Drift-driven simplification via dilution and serial propagation generates reduced, reconstructable microbial communities that resist invasion by the original complex community.

Key signal. Simplified communities maintained system-level properties and were at least as resistant to invasion as a rationally designed synthetic community.

Why it matters here. Offers a strategy for generating simplified microbial consortia, relevant to Fangzhou's interest in microbial community ecology and synthetic communities.

Microbial populations & communities PDF

Effects of antibiotic pollution on the composition and antibiotic resistance of freshwater sediment bacterial communities

Joana Q. Mends

2026-07-21 · ERA

TL;DR. Low antibiotic concentrations (0.1–10 µg/L) enriched resistance determinants without community shifts, while higher concentrations disrupted community composition and promoted persistence of resistant bacteria.

Key signal. Even low antibiotic concentrations selectively increased sul1 and intI1 abundance, indicating subtle resistance expansion without community-level changes.

Why it matters here. Directly addresses antibiotic resistance dynamics in microbial communities, a core interest tied to Fangzhou's work on antibiotic resistance and microbial ecology.

Microbial populations & communitiesMicrobial physiology, growth & division

A single DNA methylation site regulates cell fate during Clostridioides difficile sporulation

Pola Kuhn, John W. Ribis, Mi Ni, Gang Fang, Aimee Shen

2026-07-23 · PLoS Pathogens

TL;DR. A single CamA DNA methylation site in the spoIIE promoter regulates sporulation cell fate in Clostridioides difficile, with premature σF activation leading to abortive sporulation and resumption of vegetative growth.

Key signal. Methylation of a single motif increases spoIIE transcription and σF activation, and premature activation does not cause lysis but allows developmental plasticity.

Why it matters here. Ties directly to Fangzhou's interest in microbial physiology, growth, and cell-fate regulation, specifically through a DNA methylation mechanism controlling sporulation.

Microbial physiology, growth & division PDF

Using BONCAT-FACS to probe the active soil microbial community during nitrous oxide production

Jonah Gray, Jennifer E. Harris, Jason P. Kaye, Estelle Couradeau

2026-07-13 · bioRxiv (Cold Spring Harbor Laboratory)

TL;DR. BONCAT-FACS-Seq reveals that less than 1% of the soil microbial community drives N2O production, with flux correlated to an ensemble of eight active taxa rather than a single species.

Key signal. N2O flux rates correlate with the combined abundance of multiple active taxa, not a dominant single species.

Why it matters here. Demonstrates ensemble-based activity in a key biogeochemical process, relevant to Fangzhou's interest in microbial community function and dynamics.

Microbial populations & communities PDF

Assessing the restoration of a seasonally flooded riparian forest through soil carbon and nitrogen cycling indicators and soil microbial communities

HV Santos, MR Scotti

2026-07-21 · iForest - Biogeosciences and Forestry

TL;DR. Soil carbon and nitrogen cycling indicators and microbial community profiles show that a six-year restored riparian forest is approaching preserved forest conditions, but ammonium accumulation from impaired nitrification hinders recovery.

Key signal. Ammonium accumulation due to periodic flooding is the main environmental impact hindering restoration progress.

Why it matters here. Provides a case study of microbial community responses to environmental factors, relevant to Fangzhou's interest in microbial ecology and ecosystem function.

Microbial populations & communities PDF

Statistical learning of bacterial growth in combinatorially constructed environments

Andrea Arrabal, Magdalena San Román, Juan Díaz‐Colunga, Alvaro Sanchez

2026-06-30 · bioRxiv (Cold Spring Harbor Laboratory)

TL;DR. Full factorial experiments on seven bacterial species across 8 carbon sources reveal that pairwise interactions dominate growth variation, enabling accurate prediction of growth in novel environments via sparse data.

Key signal. Additive and pairwise interactions explain most growth variance, allowing simple regression models to predict growth in untested nutrient combinations.

Why it matters here. Directly addresses bacterial growth laws and resource epistasis, core to Fangzhou's interest in microbial physiology, growth, and metabolic allocation.

Microbial physiology, growth & division PDF