Chemical biology-whole genome engineering datasets predict new antibacterial combinations

Abstract

Trimethoprim and sulfamethoxazole are used commonly together as cotrimoxazole for the treatment of urinary tract and other infections. The evolution of resistance to these and other antibacterials threatens therapeutic options for clinicians. We generated and analysed a chemical-biology-whole-genome data set to predict new targets for antibacterial combinations with trimethoprim and sulfamethoxazole. For this we used a large transposon mutant library in Escherichia coli BW25113 where an outward-transcribing inducible promoter was engineered into one end of the transposon. This approach allows regulated expression of adjacent genes in addition to gene inactivation at transposon insertion sites, a methodology that has been called TraDIS-Xpress. These chemical genomic data sets identified mechanisms for both reduced and increased susceptibility to trimethoprim and sulfamethoxazole. The data identified that over-expression of FolA reduced trimethoprim susceptibility, a known mechanism for reduced susceptibility. In addition, transposon insertions into the genes tdk, deoR, ybbC, hha, ldcA, wbbK and waaS increased susceptibility to trimethoprim and likewise for rsmH, fadR, ddlB, nlpI and prc with sulfamethoxazole, while insertions in ispD, uspC, minC, minD, yebK, truD and umpG increased susceptibility to both these antibiotics. Two of these genes' products, Tdk and IspD, are inhibited by AZT and fosmidomycin respectively, antibiotics that are known to synergise with trimethoprim. Thus, the data identified two known targets and several new target candidates for the development of co-drugs that synergise with trimethoprim, sulfamethoxazole or cotrimoxazole. We demonstrate that the TraDIS-Xpress technology can be used to generate information-rich chemical-genomic data sets that can be used for antibacterial development.

Keywords: TIS; TraDIS; antibiotics; chemical; combinations; genomics.

Fig. 1.

(a) Steps in the generation of data using TraDIS-Xpress. Following introduction of the transposon into the bacteria, transposon mutant colonies are grown on nutrient agar medium with selection for the transposon-encoded resistance determinant (1). Colonies are harvested from agar surfaces by suspending in nutrient broth and scraping the mutants into a large pool (2). The mutant pool is then subjected to a growth condition of interest and an appropriate control condition (3), then genomic DNA is extracted (4). Using a customised nucleotide sequencing protocol, sequence reads are then generated from the known sequences within the end of the transposon into the nucleotides surrounding the transposon insertion site (5). Where the sequence reads match the sequence of a reference genome sequence locates the transposon insertion sites (6), and the number of reads at any site reflects the number of mutants. Comparison of data sets for different growth conditions indicates those mutations which confer a competitive change, thereby identifying genes relevant to the growth condition of interest (7). (b) Likely consequences following insertion into the bacterial genome of a transposon incorporating an outward transcribing promoter. The transposon (blue) used for TraDIS-Xpress encodes an antibacterial resistance determinant (AbR) to enable selection of transposon mutants and incorporates an outward transcribing promoter (black arrowhead). If the transposon inserts within a gene (red) the result is likely to be insertional inactivation of the gene. Insertion 5’ to a gene can result in altered transcription, and insertion 3’ to a gene can result in altered expression due to RNA interference (RNAi) of reverse complimentary RNA (rcRNA) with the native mRNA.

Fig. 2.

Network analysis of genes involved in susceptibility to trimethoprim and sulfamethoxazole based on insertional inactivation. Genes for which q<0.001 and log₂CPM>5 are included. TMP, Trimethoprim, SUL, sulfamethoxazole. 2_, 1_, 0.5_ and 0.25_ indicates 2, 1, 0.5 and 0.25× MIC respectively. Genes on a green or grey background gave the most statistically significant result (q<0.0001, log₂CPM>6) and are also listed in Table 1, grey being involved in both trimethoprim and sulfamethoxazole susceptibility and green being involved in susceptibility to only one of these. Genes on a blue background were less statistically significant (q<0.001, log₂CPM>5) and are not listed in Table 1. Red connectors indicate an increase in mutants, and blue a decrease, with the width proportional to the fold change.

Fig. 3.

Visualisation of TraDIS-Xpress data for folA, dksA, dnaKJ, tdk, wzxE, degP and their adjacent genes. Along the bottom of each panel the relative location of each gene is indicated. Above this are five horizontal frames, one control (ctrl) and 2 x MIC and 1× MIC each for trimethoprim and sulfamethoxazole (2TMP, 1TMP, 2SUL and 1SUL respectively). Vertical lines within these frames indicate transposon insertion sites, and the height of these reflects the number of reads that located to each site which is an indicator of the number of insertion mutants. Vertical lines above the axis indicate reads that located to the forward strand such that the outward-transcribing promoter in the transposon end transcribes in the left to right direction, and those below the axis indicate transposon insertions in the opposite orientation. Only one of the duplicate data sets for each condition is shown. (a) folA shows transposon insertions upstream and transcribing into folA following growth with trimethoprim but no significant changes across this entire region with sulfamethoxazole compared to growth without antibiotic. Note that there are no sequence reads locating within folA, indicating that this is an essential gene and would not have been assayed without the transposon outward-transcribing promoter. (b) dksA shows an increase in mutants following growth in 2TMP and 1TMP only. (c) dnaKJ shows increased mutants following growth in 2TMP and 1TMP only, with insertions into the 3’-quarter of dnaK only and predominantly in one orientation. (d) tdk shows fewer mutants following growth in 2TMP and 1TMP only. (e) and (f) wzxE and degP show fewer mutants following growth in 2SUL.

Fig. 4.

Results of growth competition between mutants and parent strain in the presence or absence of trimethoprim. Shown are colonies that grew following growth of mutants from the Keio collection [20] in competition with the parent strain BW25113 without trimethoprim (TMP, upper panel) and with 0.25 mg l⁻¹ trimethoprim (lower panel). Approximately equal numbers of the parent strain and mutant to be tested were inoculated into LB broth and grown at 37 °C for 20 h. Then, each culture was serially diluted and 5 µl spotted onto LB-agar to allow growth of both parent strain and mutant, and onto LB-agar supplemented with kanamycin (Km) to allow growth of the mutant only. Following growth without trimethoprim, all mutants persisted in the cultures (upper panel). With 0.25 mg l⁻¹ trimethoprim, the tdk mutant was lost from the culture, whilst the dksA and truA mutants dominated the culture (lower panel). As predicted from the TraDIS-Xpress data, trimethoprim made less, if any, obvious difference to growth of the acrR and ompF mutants. BW indicates a control culture with BW25113 alone. Mutants of the Keio collection come as independent pairs for each gene, and both mutants of the pairs were tested. The results were the same for each, so only one is presented.