Model-driven discovery of synergistic inhibitors against E. coli and S. enterica serovar Typhimurium targeting a novel synthetic lethal pair, aldA and prpC

In Silico and In Vitro Investigation of the Distribution and Expression of Key Genes in the Fucose Operon of Escherichia coli

Many gut bacteria degrade polysaccharides, providing nutritional advantages to their hosts. Fucose, a mucin degradation product, was suggested as a communication molecule between the resident microbiota and external pathogens. However, the precise role and variants of the fucose utilization pathway remain to be elucidated. Here, we computationally and experimentally investigated the fucose utilization operon of E. coli. While the operon is conserved among E. coli genomes, a variant pathway, in which an ABC transporter system replaces the fucose permease gene (fucP), was computationally identified in 50 out of 1058 genomes. Comparative genomics and subsystems analysis results were confirmed by polymerase chain reaction-based screening of 40 human E. coli isolates, which indicated the conservation of fucP in 92.5% of the isolates (vs. 7.5% of its suggested alternative, yjfF). The in silico predictions were confirmed by in vitro experiments comparing the growth of E. coli strains K12, BL21, and isogenic fucose-utilization K12 mutants. Additionally, fucP and fucI transcripts were quantified in E. coli K12 and BL21, after in silico analysis of their expression in 483 public transcriptomes. In conclusion, E. coli utilizes fucose by two pathway variants, with measurable transcriptional differences. Future studies will explore this variation's impact on signaling and virulence.

Small-Molecule Antibiotics Inhibiting tRNA-Regulated Gene Expression Is a Viable Strategy for Targeting Gram-Positive Bacteria

Bacterial infections and the rise of antibiotic resistance, especially multidrug resistance, have generated a clear need for discovery of novel therapeutics. We demonstrated that a small-molecule drug, PKZ18, targets the T-box mechanism and inhibits bacterial growth. The T-box is a structurally conserved riboswitch-like gene regulator in the 5' untranslated region (UTR) of numerous essential genes of Gram-positive bacteria. T-boxes are stabilized by cognate, unacylated tRNA ligands, allowing the formation of an antiterminator hairpin in the mRNA that enables transcription of the gene. In the absence of an unacylated cognate tRNA, transcription is halted due to the formation of a thermodynamically more stable terminator hairpin. PKZ18 targets the site of the codon-anticodon interaction of the conserved stem I and reduces T-box-controlled gene expression. Here, we show that novel analogs of PKZ18 have improved MICs, bactericidal effects against methicillin-resistant Staphylococcus aureus (MRSA), and increased efficacy in nutrient-limiting conditions. The analogs have reduced cytotoxicity against eukaryotic cells compared to PKZ18. The PKZ18 analogs acted synergistically with aminoglycosides to significantly enhance the efficacy of the analogs and aminoglycosides, further increasing their therapeutic windows. RNA sequencing showed that the analog PKZ18-22 affects expression of 8 of 12 T-box controlled genes in a statistically significant manner, but not other 5'-UTR regulated genes in MRSA. Very low levels of resistance further support the existence of multiple T-box targets for PKZ18 analogs in the cell. Together, the multiple targets, low resistance, and synergy make PKZ18 analogs promising drugs for development and future clinical applications.

Genome-scale metabolic models as platforms for identification of novel genes as antimicrobial drug targets

The growing number of multidrug-resistant pathogenic bacteria is becoming a world leading challenge for the scientific community and for public health. However, advances in high-throughput technologies and whole-genome sequencing of bacterial pathogens make the construction of bacterial genome-scale metabolic models (GEMs) increasingly realistic. The use of GEMs as an alternative platforms will expedite identification of novel unconditionally essential genes and enzymes of target organisms with existing and forthcoming GEMs. This approach will follow the existing protocol for construction of high-quality GEMs, which could ultimately reduce the time, cost and labor-intensive processes involved in identification of novel antimicrobial drug targets in drug discovery pipelines. We discuss the current impact of existing GEMs of selected multidrug-resistant pathogenic bacteria for identification of novel antimicrobial drug targets and the challenges of closing the gap between genome-scale metabolic modeling and conventional experimental trial-and-error approaches in drug discovery pipelines.

MinGenome: An In Silico Top-Down Approach for the Synthesis of Minimized Genomes

Genome minimized strains offer advantages as production chassis by reducing transcriptional cost, eliminating competing functions and limiting unwanted regulatory interactions. Existing approaches for identifying stretches of DNA to remove are largely ad hoc based on information on presumably dispensable regions through experimentally determined nonessential genes and comparative genomics. Here we introduce a versatile genome reduction algorithm MinGenome that implements a mixed-integer linear programming (MILP) algorithm to identify in size descending order all dispensable contiguous sequences without affecting the organism's growth or other desirable traits. Known essential genes or genes that cause significant fitness or performance loss can be flagged and their deletion can be prohibited. MinGenome also preserves needed transcription factors and promoter regions ensuring that retained genes will be properly transcribed while also avoiding the simultaneous deletion of synthetic lethal pairs. The potential benefit of removing even larger contiguous stretches of DNA if only one or two essential genes (to be reinserted elsewhere) are within the deleted sequence is explored. We applied the algorithm to design a minimized E. coli strain and found that we were able to recapitulate the long deletions identified in previous experimental studies and discover alternative combinations of deletions that have not yet been explored in vivo.

Comparative genome-scale modelling of Staphylococcus aureus strains identifies strain-specific metabolic capabilities linked to pathogenicity

Staphylococcus aureus is a preeminent bacterial pathogen capable of colonizing diverse ecological niches within its human host. We describe here the pangenome of S. aureus based on analysis of genome sequences from 64 strains of S. aureus spanning a range of ecological niches, host types, and antibiotic resistance profiles. Based on this set, S. aureus is expected to have an open pangenome composed of 7,411 genes and a core genome composed of 1,441 genes. Metabolism was highly conserved in this core genome; however, differences were identified in amino acid and nucleotide biosynthesis pathways between the strains. Genome-scale models (GEMs) of metabolism were constructed for the 64 strains of S. aureus These GEMs enabled a systems approach to characterizing the core metabolic and panmetabolic capabilities of the S. aureus species. All models were predicted to be auxotrophic for the vitamins niacin (vitamin B3) and thiamin (vitamin B1), whereas strain-specific auxotrophies were predicted for riboflavin (vitamin B2), guanosine, leucine, methionine, and cysteine, among others. GEMs were used to systematically analyze growth capabilities in more than 300 different growth-supporting environments. The results identified metabolic capabilities linked to pathogenic traits and virulence acquisitions. Such traits can be used to differentiate strains responsible for mild vs. severe infections and preference for hosts (e.g., animals vs. humans). Genome-scale analysis of multiple strains of a species can thus be used to identify metabolic determinants of virulence and increase our understanding of why certain strains of this deadly pathogen have spread rapidly throughout the world.