Abstract

Multidimensional gradients of inorganic compounds influence microbial activity in diverse pristine and anthropogenically perturbed environments. Here, we suggest that high-throughput cultivation and genetics can be systematically applied to generate quantitative models linking gene function, microbial community activity, and geochemical parameters. Metal resistance determinants represent a uniquely universal set of parameters around which to study and evaluate microbial fitness because they represent a record of the environment in which all microbial life evolved. By cultivating microbial isolates and enrichments in laboratory gradients of inorganic ions, we can generate quantitative predictions of limits on microbial range in the environment, obtain more accurate gene annotations, and identify useful strategies for predicting and engineering the trajectory of natural ecosystems.

Highlights

  • Multidimensional gradients of inorganic compounds influence microbial activity in diverse pristine and anthropogenically perturbed environments

  • It is possible to fill microplates with arrays of compounds or serially diluted solutions to simultaneously evaluate the influence of hundreds to tens of thousands of parameters on microbial growth kinetics and metabolism[7]

  • Microbial niche space is often viewed as an n-dimensional matrix in which antimetabolites, carbon sources, and essential nutrients influence the ability of a microorganism or microbial community to grow and survive[13,14]

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Summary

Adams D: The More Than Complete Hitchhiker’s Guide

2. Smith DB, Cannon WF, Woodruff LG, et al.: Geochemical and Mineralogical Data for Soils of the Conterminous United States. 3. Ellefsen KJ, Smith DB, Horton JD: A modified procedure for mixture-model clustering of regional geochemical data. Int J Mol Sci. 2016; 17(8): pii: E1275. Tietjen K, Drewes M, Stenzel K: High throughput screening in agrochemical research. 9. Wetmore KM, Price MN, Waters RJ, et al.: Rapid quantification of mutant fitness in diverse bacteria by sequencing randomly bar-coded transposons. Deutschbauer A, Price MN, Wetmore KM, et al.: Evidence-based annotation of gene function in Shewanella oneidensis MR-1 using genome-wide fitness profiling across 121 conditions.

14. Wimpenny JW
Findings
16. Crichton R
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