Understanding the adaptations of microorganisms to their environment is key to predicting the stability and dynamics of microbial communities. To uncover molecular mechanisms of environmental response, we extracted genomic features from 13,554 prokaryotic isolates, and trained machine learning models to identify which...
M. B. Walter Costa, R. Brouns, Maria Schreiber et al.· bioRxiv· 0 citations
Urinary tract infections (UTIs), particularly cystitis, are among the most common bacterial infections worldwide, with a disproportionate burden on adult female individuals, who often have recurrence. The discovery of the urobiome, a low microbial biomass community in the urinary tract, has transformed our understandin...
Marleen D. Hekker, Adam J. Bindas, Freya Darling Eriksen et al.· The Lancet Microbe· 0 citations
Bacteriophages can only be understood through their interactions with bacterial hosts. As environmental sequencing efforts expanded, the number of available phage genome sequences has exploded, yet the vast majority of these sequences lack host information. Predicting the host of a newly observed phage is therefore a k...
Malte Siemers, J. L. López, B. Dutilh· bioRxiv· 0 citations
A micro-biome cloud model is proposed, re-ecting the temporal and spatial uncertainty of deflecting an individual’s microbiome composition, with examples of how intra-individual variations (such as age and mode of delivery) shape the microbiome structure.
M. ElRakaiby, Dutilh, E. Baş et al.· 0 citations
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