Zhong Wei

Bacterial endosymbionts enhance fungal virulence by disrupting the disease-suppressive rhizobiome

This study shows bacterial endosymbionts in fungal pathogens enhance virulence by altering the rhizosphere microbiome and reducing disease-suppressive bacteria.

KuafuPrimer: Machine learning empowers the design of 16S amplicon sequencing primers toward minimal bias for bacterial communities

KuafuPrimer uses machine learning to design 16S rRNA gene primers with minimal bias, improving taxonomic accuracy and detecting rare taxa missed by universal primers.

eBiota: Designing microbial communities from large seed pools with desired function using rapid optimization and deep learning

eBiota designs microbial communities from large strain pools to generate target products using optimization and deep learning, showing accurate predictions and experimental validation.

Probiotic phage steering of disease suppressive rhizosphere microbiome

The paper shows that phage targeting a probiotic bacterium can enhance disease suppressiveness in the rhizosphere by altering bacterial interactions and diversity.

LorMe: a streamlined and interoperable R framework for end-to-end microbiome analysis

LorMe provides a unified R framework for microbiome analysis, offering an end-to-end pipeline with reproducibility and interoperability across tools.

Substrate utilization and cross-feeding synergistically determine microbiome resistance to pathogen invasion

This study uses genome-scale models and synthetic communities to show that substrate utilization and cross-feeding synergistically determine microbiome resistance to pathogen invasion.

Tracing Siderophore Precursors to Primary Metabolism for Ecological Applications

The paper develops a framework to trace siderophore biosynthesis to primary metabolism and applies it to identify metabolic differences between beneficial and pathogenic bacteria.

Spatiotemporal changes in soil properties predict plant health at continental scale

The paper predicts plant health using spatiotemporal changes in soil properties with 84% accuracy across multiple climates and cropping systems.

From sequence to molecules: Feature sequence-based genome mining uncovers the hidden diversity of bacterial siderophore pathways

The paper develops a bioinformatic pipeline to predict bacterial siderophore structures and receptors from genome sequences, revealing significant diversity in pyoverdines and their receptors.