Biology subjects

Gat, D.

Publications and source records attributed to Gat, D..

3 recordsLinked to original sources

bioRxiv2026

Rainfall legacy effects on the rhizosphere bacterial diversity of Brachypodium ecotypes across an aridity gradient

Plants exhibit clinal trait variation along aridity gradients driven by strong selective pressures, yet whether plant-microbiome associations follow similar patterns remains unclear. Brachypodium spp., a model for temperate cereals spanning environments from hyper-arid to humid, provides an ideal system to test this hypothesis. Here, we compare rhizosphere bacterial communities of Brachypodium growing across arid, semi-arid, and dry sub-humid zones in Israel with those of ecotypes collected along the same precipitation gradient and grown under common-garden conditions. Rhizosphere bacterial diversity was highest in plants from mid-precipitation sites within the Mediterranean semi-arid transition zone, where annual precipitation decreases from 600 to 400 mm. Together with higher stochasticity and fewer significantly associated taxa in rhizosphere microbiomes from mid-precipitation plants suggest weaker plant-driven microbiome selection in this transition zone, a pattern that persisted under common-garden conditions. The results may represent a promising avenue to develop microbiome-based strategies for drought resilience by advancing our understanding of host filtering across aridity gradients.

ecology↗

bioRxiv2021

Airborne bacteria over oceans shed light on global biogeodiversity patterns

Microbes are ubiquitous in the oceans and the atmosphere, playing essential roles in biogeochemical processes. The bio-exchanges between the two environments can provide important insights into microbial distribution and diversity but are still not well understood. We simultaneously surveyed the genomic diversity of airborne and marine bacterial communities across 15 000 kilometers in the Atlantic and Pacific oceans. Higher variability of microbial community composition was observed in the atmosphere than in the ocean surface waters. In addition, a greater similarity was observed between oceans than their overlaying atmosphere, and between atmospheric samples than with the ocean beneath. We additionally detected a higher coverage rate and relative abundance of marine bacteria in the Pacific atmosphere as compared to the Atlantic, while the dominant fraction in the Atlantic atmosphere was annotated as soil-associated bacteria. This study advances our understanding of microbial dispersion in the ocean, the atmosphere, and the exchange between them, as well as their potential impact on microbial composition, ecology, and biogeochemistry.

ecology↗

bioRxiv2019

Genome-Scale reconstruction of Paenarthrobacter aurescens TC1 metabolic model towards the study of atrazine bioremediation

Atrazine is an herbicide and pollutant of great environmental concern that is naturally biodegraded by microbial communities. The efficiency of biodegradation can be improved through the stimulating addition of fertilizers, electron acceptors, etc. In recent years, metabolic modelling approaches have become widely used as an in silico tool for organism-level phenotyping and the subsequent development of metabolic engineering strategies including biodegradation improvement. Here, we constructed a genome scale metabolic model, iRZ960, for Paenarthrobacter aurescens TC1 - a widely studied atrazine degrader - aiming at simulating its degradation activity. A mathematical stoichiometric metabolic model was constructed based on a published genome sequence of P. aurescens TC1. An Initial draft model was automatically constructed using the RAST and KBase servers. The draft was developed into a predictive model through semi-automatic gap-filling procedures including manual curation. In addition to growth predictions under different conditions, model simulations were used to identify optimized media for enhancing the natural degradation of atrazine without a need in strain design via genetic modifications. Model predictions for growth and atrazine degradation efficiency were tested in myriad of media supplemented with different combinations of carbon and nitrogen sources that were verified in vitro. Experimental validations support the reliability of the models predictions for both bacterial growth (biomass accumulation) and atrazine degradation. Predictive tools, such as the presented model, can be applied for achieving optimal biodegradation efficiencies and for the development of ecologically friendly solutions for pollutant degradation in changing environments.

bioinformatics↗