Abstract

The nonessential regions in bacterial chromosomes are ill-defined due to incomplete functional information. Here, we establish a comprehensive repertoire of the genome regions that are dispensable for growth of Bacillus subtilis in a variety of media conditions. In complex medium, we attempted deletion of 157 individual regions ranging in size from 2 to 159 kb. A total of 146 deletions were successful in complex medium, whereas the remaining regions were subdivided to identify new essential genes (4) and coessential gene sets (7). Overall, our repertoire covers ∼76% of the genome. We screened for viability of mutant strains in rich defined medium and glucose minimal media. Experimental observations were compared with predictions by the iBsu1103 model, revealing discrepancies that led to numerous model changes, including the large-scale application of model reconciliation techniques. We ultimately produced the iBsu1103V2 model and generated predictions of metabolites that could restore the growth of unviable strains. These predictions were experimentally tested and demonstrated to be correct for 27 strains, validating the refinements made to the model. The iBsu1103V2 model has improved considerably at predicting loss of viability, and many insights gained from the model revisions have been integrated into the Model SEED to improve reconstruction of other microbial models.

Highlights

  • Biological systems often maintain phenotypic stability when exposed to diverse perturbations arising from environmental changes, intracellular stochastic events and genetic variation

  • The chromosome regions targeted for deletion were defined relative to the 271 genes reported to be individually essential for B. subtilis survival in LB medium at 37C [23]

  • 254 genes involved in cellular processes essential for the experimental procedures, such as DNA recombination and repair, SOS response, competence development and transformation, and pyrimidine salvage pathway were preserved

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Summary

Introduction

Biological systems often maintain phenotypic stability when exposed to diverse perturbations arising from environmental changes, intracellular stochastic events (or noise) and genetic variation. This robustness is an inherent property of all biological systems and is strongly favored by evolution [1]. Functional robustness arises from many redundancies, interlocking pathways and feedback mechanisms inherent to the complexity of biological networks [4]. This complexity enables the biological systems to dynamically adapt or compensate for losses or environmental changes.

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