Reframing gene essentiality in terms of adaptive flexibility

Gabriela I. Guzmán, Connor A. Olson, Ying Hefner, Patrick V. Phaneuf, Edward Catoiu, Lais B. Crepaldi, Lucas Goldschmidt Micas, Bernhard O. Palsson, Adam M. Feist*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

Background: Essentiality assays are important tools commonly utilized for the discovery of gene functions. Growth/no growth screens of single gene knockout strain collections are also often utilized to test the predictive power of genome-scale models. False positive predictions occur when computational analysis predicts a gene to be non-essential, however experimental screens deem the gene to be essential. One explanation for this inconsistency is that the model contains the wrong information, possibly an incorrectly annotated alternative pathway or isozyme reaction. Inconsistencies could also be attributed to experimental limitations, such as growth tests with arbitrary time cut-offs. The focus of this study was to resolve such inconsistencies to better understand isozyme activities and gene essentiality. Results: In this study, we explored the definition of conditional essentiality from a phenotypic and genomic perspective. Gene-deletion strains associated with false positive predictions of gene essentiality on defined minimal medium for Escherichia coli were targeted for extended growth tests followed by population sequencing and transcriptome analysis. Of the twenty false positive strains available and confirmed from the Keio single gene knock-out collection, 11 strains were shown to grow with longer incubation periods making these actual true positives. These strains grew reproducibly with a diverse range of growth phenotypes. The lag phase observed for these strains ranged from less than one day to more than 7 days. It was found that 9 out of 11 of the false positive strains that grew acquired mutations in at least one replicate experiment and the types of mutations ranged from SNPs and small indels associated with regulatory or metabolic elements to large regions of genome duplication. Comparison of the detected adaptive mutations, modeling predictions of alternate pathways and isozymes, and transcriptome analysis of KO strains suggested agreement for the observed growth phenotype for 6 out of the 9 cases where mutations were observed. Conclusions: Longer-term growth experiments followed by whole genome sequencing and transcriptome analysis can provide a better understanding of conditional gene essentiality and mechanisms of adaptation to such perturbations. Compensatory mutations are largely reproducible mechanisms and are in agreement with genome-scale modeling predictions to loss of function gene deletion events.

Original languageEnglish
Article number143
JournalBMC Systems Biology
Volume12
Issue number1
DOIs
Publication statusPublished - 17 Dec 2018

Bibliographical note

Funding Information:
Funding for this work was provided by The Novo Nordisk Foundation, Grant Number NNF10CC1016517 and from the National Institutes of Health/National Institute of Allergy and Infectious Diseases Grant 1-U01-AI124316.

Funding Information:
We would like to thank Richard Szubin and Julia Xu for assistance with strain resequencing. We would also like to thank Troy Sandberg, David Heckmann, Zachary King, and Amitesh Anand for their constructive feedback on the manuscript. LBC and LGM would also like to thank the Brazil Scientific Mobility Program - Science without Borders, and their scholarship sponsors CAPES (Comissão de Aperfeiçoamento de Pessoal do Nível Superior).

Publisher Copyright:
© 2018 The Author(s).

Other keywords

  • Adaptive evolution
  • Essentiality
  • Genome-scale model

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