From genetic footprinting to antimicrobial drug targets: examples in cofactor biosynthetic pathways

Abstract

Novel drug targets are required in order to design new defenses against antibiotic-resistant pathogens. Comparative genomics provides new opportunities for finding optimal targets among previously unexplored cellular functions, based on an understanding of related biological processes in bacterial pathogens and their hosts. We describe an integrated approach to identification and prioritization of broad-spectrum drug targets. Our strategy is based on genetic footprinting in Escherichia coli followed by metabolic context analysis of essential gene orthologs in various species. Genes required for viability of E. coli in rich medium were identified on a whole-genome scale using the genetic footprinting technique. Potential target pathways were deduced from these data and compared with a panel of representative bacterial pathogens by using metabolic reconstructions from genomic data. Conserved and indispensable functions revealed by this analysis potentially represent broad-spectrum antibacterial targets. Further target prioritization involves comparison of the corresponding pathways and individual functions between pathogens and the human host. The most promising targets are validated by direct knockouts in model pathogens. The efficacy of this approach is illustrated using examples from metabolism of adenylate cofactors NAD(P), coenzyme A, and flavin adenine dinucleotide. Several drug targets within these pathways, including three distantly related adenylyltransferases (orthologs of the E. coli genes nadD, coaD, and ribF), are discussed in detail.

FIG. 1.

General scheme for E. coli genetic footprinting procedure.

FIG. 2.

Detection and mapping of transposon insertions. (A) Primer strategy for nested PCR. Transposon-specific primers are shown in gray; chromosome-specific landmark primers are shown in black. (B) The gel image shows analysis of the three chromosomal loci: aspC (nonessential) and lpdA and ftsJ (essential) at time zero (lanes 1, 3, and 5) and after outgrowth (lanes 2, 4, and 6). ORF locations are marked relative to each pair of lanes. Several inserts are visible in lpdA and ftsJ at time zero, while none can be detected after outgrowth. The nonessential aspC contains insertions at both time points. (C to E) Examples of genetic footprints. Note that the scale is different in each panel. The length and direction of each gene are indicated by the large horizontal gray arrows. Black diamonds represent transposon inserts. The width of each diamond corresponds to the mapping error introduced by gel electrophoresis. The positions of the landmark PCR primers are shown by bows crossing the genes, as well as by arrows above the genes. (C) Genetic footprinting of the ftsK locus in MG1655. Only the 3′ half of this essential gene contains inserts. (D) Genetic footprinting of the coaD locus in MG1655. A transposon insertion immediately upstream of this essential gene apparently does not interfere with its expression. (E) Mapping of the Δ(ara-leu)7697 deletion in DH10B. The genetic footprint of the corresponding region in MG1655 is shown for comparison.

FIG. 3.

Simplified diagrams, illustrating the biochemical transformations directly involved in the biosynthesis of NAD(P) (A), CoA (B), and FMN/FAD (C). Most of the pathways and genes shown are those present in E. coli, with the few exceptions marked by dashed lines. Recycling pathways and other transformations related to genes that remain unknown (such as NMN deamidase) are not included.

FIG. 4.

Selection of antibacterial drug targets by a combination of genetic footprinting in E. coli and comparative analysis of reconstructed metabolic subsystems, pathways, and individual genes in pathogens and humans.

FIG. 5.

Prioritization of potential broad-spectrum antibacterial drug targets in biosynthetic pathways of NAD(P), CoA, and FAD. Three criteria are shown for each target enzyme (marked by abbreviations along the x axis). (A) Range of pathogens. A number of pathogens (from the representative set) containing the given target enzyme (and included in building of the corresponding HMM) are represented by filled bars. Organisms not containing this target enzyme and therefore excluded from the spectrum are indicated inside open bars (by two-letter abbreviations). (B) Compact pathogen subsets and outliers. Negative logarithms of the E values indicate how closely each bacterial sequence is related to the probabilistic consensus of the corresponding profile HMM (larger values indicate higher similarity). Subsets of pathogens with target orthologs most closely related to the consensus are shown inside dotted boxes. Outliers are indicated by two-letter organism abbreviations. Organisms shown are P. aeruginosa (○) (PA), B. anthracis (▾) (BA), M. tuberculosis (▿) (MT), H. pylori (▪) (HP), S. pneumoniae (□) (PN), S. aureus (♦) (SA), M. genitalium (⋄) (MG), H. influenzae (▴) (HI), C. trachomatis (▵) (CT), and E. coli (•). The E. coli proteins are very similar to those of Yersinia pestis and Salmonella enterica serovar Typhi. (C) Human counterparts: distance from bacterial families. The negative logarithms of the E values of human counterpart sequences compared to the corresponding bacterial HMMs (smaller values indicate higher divergence of the human enzyme from the corresponding bacterial family). ∗∗, HMM E values for these human proteins are higher than the threshold (>10,000).

FIG. 6.

General scheme of chemical transformations catalyzed by the three adenylyltransferases (ATse) in the biosynthesis of NAD(P), CoA, and FAD. These enzymes—NaMNAT (encoded in E. coli by nadD), PPAT (gene coaD), and FADS (ribF)—were selected as the most promising antibacterial drug targets within these pathways.