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Himes, B.

Publications and source records attributed to Himes, B..

2 recordsLinked to original sources

Nutrient availability shifts the biosynthetic potential of soil-derived microbial communities

Secondary metabolites produced by microorganisms are the main source of antimicrobials other pharmaceutical drugs. Soil microbes have been the primary discovery source for these secondary metabolites, often producing complex organic compounds with specific biological activities. Research suggests that secondary metabolism broadly shapes microbial ecological interactions, but little is known about the factors that shape the abundance, distribution, and diversity of biosynthetic gene clusters in the context of microbial communities. In this study, we investigate the role of nutrient availability on the abundance of biosynthetic gene clusters in soil-derived microbial consortia. We found that soil microbial consortia enriched in medium with 150 mg/L of glucose and 200 mg/L of trehalose (here defined as high sugar) had more biosynthetic gene cluster and higher inhibitory activity than soil microbial consortia enriched in medium with 15 mg/L of glucose + 20 mg/L of trehalose (here defined as low sugar). Our results demonstrate that laboratory microbial communities are a promising tool to study ecology of specialized metabolites.

microbiology↗

High resolution in situ structural determination of heterogeneous specimen

Macromolecular complexes are intrinsically flexible and often challenging to purify for structure determination by single particle cryoEM. Such complexes may be studied in situ using cryo-electron tomography combined with sub-tomogram alignment and classification, which in exceptional cases reaches sub-nanometer resolution, yielding insight into structure-function relationships. All maps currently deposited in the EMDB with resolution < 9 [A] are from macromolecules that form ordered structural arrays, like viral capsids, which greatly simplifies structural determination. Extending this approach to more common specimens that exhibit conformational or compositional heterogeneity, and may be available in limited numbers, remains challenging. We developed emClarity, a GPU-accelerated image processing package, specifically to address fundamental hurdles to this aim, and demonstrate significant improvements in the resolution of maps compared to those generated using current state-of-the-art software. Furthermore, we devise a novel approach to sub-tomogram classification that reveals functional states not previously observed with the same data.\n\nThe software is freely available from https://www.github.com/bHimes/emClarity\n\nTutorial documentation and videos at https://www.github.com/bHimes/emClarity/wiki

biophysics↗