Thanks to Chunxu Song and the CAU for great partnership and collaboration, and Jos Raaijmakers (NIOO-KNAW) and Liesje Mommer (WUR) for their crucial roles in advising the work.

Also, catabolic gene cluster absence/presence profiles were shown to be strongly predictive of rhizosphere competence, even more so than a dataset of experimental assays of catabolic potential. 4/4

Running rhizoSMASH on a large collection of plant- and soil-associated genomes enabled charting the first map of root-associated catabolic functions across key plant-associated microbial taxa. 3/4

Similar as for antiSMASH and later gutSMASH, Yuze curated a set of profile HMMs and detection rules to reliably identify these gene clusters, guided by sequence similarity network analysis to distinguish true positives from false positives accurately. 2/4

Thanks to @jjjvanderhooft.bsky.social for co-supervision and @wildtypemc.bsky.social @johandelsman.bsky.social @zachreitz.bsky.social #ClaraBelzer @YijunZhu for great contributions & collaborations!

We think this type of analysis can be used to predict/reveal functions of unknown biosynthetic gene clusters in the future, and understand interactions that mediate microbiome-associated phenotypes.

... and expression (anti-)correlations of biosynthetic gene clusters highlight positive and negative responses to antibiotic production (related to stress response, siderophores, redox balance).

Coexpression networks of primary metabolic modules highlight both competition and cross-feeding...