Reframing gene essentiality in terms of adaptive flexibility

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.

Keywords: Adaptive evolution; Essentiality; Genome-scale model.

Fig. 1

Project workflow and growth characterizations of false positive strains. a A workflow summarizing the sequence of analyses followed and results from this study. A Keio gene KO collection strain was not available for approximately half of the corresponding false positive genes listed in [13], most likely due to essentiality on rich growth media [22]. Of those strains that were viable in rich media and thus available for a longer growth test, approximately half showed growth in minimal defined media. Those strains that grew were analyzed for mutations. Five false positive strains showed mutations in all replicate experiments sequenced. Four strains showed mixed results, meaning that only some populations accrued mutations. Two strains showed no mutations in any replicate samples. The nine strains that showed mutations in at least some populations were further analyzed in the context of model-predicted alternate pathways and historical data. Six of these cases showed agreement with model-predictions, two showed agreement with previous reports of multi-copy suppression [81], and mutation analysis for one case was not clearly linked to either. b Growth curves of eleven Keio collection strains associated with false positive predictions in defined minimal media. Growth data in terms of cellular density in grams of dry weight per Liter (gDW/L) is reported for the FP gene KO strains. Those strains that accrued mutations in all replicate populations during this growth test are noted with small dashed lines. Those strains that showed mixed results, showing mutations in only some populations, are noted with larger dashed lines. All Keio strains were grown in M9 minimal medium with glucose as the carbon source with the exception of ΔcysK and ΔcysP which utilized a glycerol carbon source. Growth of the wild type strain in glucose and glycerol is also provided as a point of reference (black and grey growth curves)

Fig. 2

Pathway maps related to ΔthrA, ΔptsI, and ΔserB false positive cases. Whole genome sequencing analysis revealed that for two out of three of these cases the model prediction was in agreement with the observed utilized pathway as inferred from mutation analysis. The associated gene-protein-reaction information for each case is highlighted. In a, the mutation results for ΔthrA imply that MetL (highlighted in orange) is the enzyme responsible for the isozyme activity as predicted. b Results for ΔptsI suggest that the predicted alternate pathway related to GalP is utilized in the absence of PtsI. c Results for ΔserB suggest that contrary to the predicted GlyA associated alternate pathway, HisB is responsible for rescuing growth in the absence of SerB

Fig. 3

RNA sequencing data for ΔthrA and ΔserB experiments support isozyme predictions and mutation analysis. Volcano plots display log₂(fold change) on the x-axis and -log₁₀(p-adjusted value) on the y-axis for RNA sequencing data acquired for ΔthrA and ΔserB experiments. The log₂(fold change) and p-adjusted value data was acquired comparing the experimental condition expression data (biological duplicate replicates) to wild type BW25113 expression data (biological duplicate replicates). Each dot in the plots corresponds to the differential expression data of a gene. Panels A. and B. correspond to the data for ΔthrA experiments and panels c and d correspond to the data for ΔserB experiments. The vertical dashed lines in each plot corresponds to the 2X fold change line in either direction (log₂(fold change) = 1, -1) and the horizontal dashed line corresponds to the 0.05 p-adjusted value line (-log₁₀(p-adjusted value) = 1.3). Highlighted in red in panels a and b are the metL and metB genes, which are expressed in the same operon. Of interest for the thrA experiments was the up-regulation of the predicted isozyme, metL. Highlighted in red in panels c and d are his operon genes that were up-regulated in both ΔserB experiments. Of particular interest was hisB expression, the predicted isozyme for serB

Fig. 4

Structural mutations observed in ΔproA and ΔproB experiments analyzed in relation to ArgE underground activity. a Metabolic pathway maps related to ΔproA and ΔproB false positive cases. Both are involved in L-proline synthesis. Model simulations predict using an alternate pathway related to arginine and ornithine synthesis to rescue a proA/proB deficient E. coli strain. Mutations were observed in the coding regions of the metabolic genes argD and glnA. It is suggested that reduced flux through these enzymes increases flux through the ArgE associated underground activity, thus increasing production of L-proline and allowing for cell growth. b Mutation analysis in relation to the glutamine synthetase (GlnA) protein structure. An I-Tasser-predicted protein structure is provided [55] and the amino acid residue associated with observed glnA mutations in the ΔproB populations are highlighted in red. Those residues associated with ligand binding based on the crystal structure of the Salmonella typhimurium GlnA enzyme [56] are highlighted in blue. The mutations appear to be in buried regions of the homo-dodecameric enzyme at the interface of chain-chain interactions