A High-Throughput Method for Screening for Genes Controlling Bacterial Conjugation of Antibiotic Resistance

Abstract

The rapid horizontal transmission of antibiotic resistance genes on conjugative plasmids between bacterial host cells is a major cause of the accelerating antibiotic resistance crisis. There are currently no experimental platforms for fast and cost-efficient screening of genetic effects on antibiotic resistance transmission by conjugation, which prevents understanding and targeting conjugation. We introduce a novel experimental framework to screen for conjugation-based horizontal transmission of antibiotic resistance between >60,000 pairs of cell populations in parallel. Plasmid-carrying donor strains are constructed in high-throughput. We then mix the resistance plasmid-carrying donors with recipients in a design where only transconjugants can reproduce, measure growth in dense intervals, and extract transmission times as the growth lag. As proof-of-principle, we exhaustively explore chromosomal genes controlling F-plasmid donation within Escherichia coli populations, by screening the Keio deletion collection in high replication. We recover all seven known chromosomal gene mutants affecting conjugation as donors and identify many novel mutants, all of which diminish antibiotic resistance transmission. We validate nine of the novel genes' effects in liquid mating assays and complement one of the novel genes' effect on conjugation (rseA). The new framework holds great potential for exhaustive disclosing of candidate targets for helper drugs that delay resistance development in patients and societies and improve the longevity of current and future antibiotics. Further, the platform can easily be adapted to explore interspecies conjugation, plasmid-borne factors, and experimental evolution and be used for rapid construction of strains.IMPORTANCE The rapid transmission of antibiotic resistance genes on conjugative plasmids between bacterial host cells is a major cause of the accelerating antibiotic resistance crisis. There are currently no experimental platforms for fast and cost-efficient screening of genetic effects on antibiotic resistance transmission by conjugation, which prevents understanding and targeting conjugation. We introduce a novel experimental framework to screen for conjugation-based horizontal transmission of antibiotic resistance between >60,000 pairs of cell populations in parallel. As proof-of-principle, we exhaustively explore chromosomal genes controlling F-plasmid donation within E. coli populations. We recover all previously known and many novel chromosomal gene mutants that affect conjugation efficiency. The new framework holds great potential for rapid screening of compounds that decrease transmission. Further, the platform can easily be adapted to explore interspecies conjugation, plasmid-borne factors, and experimental evolution and be used for rapid construction of strains.

Keywords: Escherichia coli; antibiotic resistance; conjugation; high-throughput screening; horizontal gene transfer; horizontal transmission; plasmid.

FIG 1

Experimental scheme for screening strains for conjugative efficiency. (A) Construction and screening of donor library. The donor library constructed by mating XL1-Blue (F′ Tet^r) with the Keio collection carrying a kanamycin resistance gene in place of almost 4,000 genes is shown at the top. Resulting donor (F′ Tet^r) and recipient (chromosomal Cam^r) strains were then grown separately on appropriate preculture plates and then pinned robotically in a 1536 format to a selective plate (Tet Chl) that allows only transconjugants to grow. Plates were placed in a flatbed scanner and scanned every 10 min for 24 h at 30°C. Data were then analyzed with Scan-o-Matic as described in the text. (B) Growth of transconjugants formed on selective plates. Blue denotes growth of spots pinned with HA4 (chromosomal Cam^r) and HA14 (F′ Tet^r) together, showing growth of the resulting transconjugants which occurs after a lag compared to HA5 (Cam^r Tet^r) (green), which grows with no detectable lag. Negative controls HA4 alone (red) and HA14 alone (black) are shown. Five representative graphs are shown for each taken from two technical replicates of 768 biological replicates (HA14 × HA4), 384 biological replicates (HA5), and 192 biological replicates (negative controls).

FIG 2

Conjugative efficiency of the Keio collection. (A) Growth lag time of the entire Keio collection in the conjugation assay. The growth lag of each curve is expressed relative to the nearby control and the log₂ value calculated. Shown is the frequency plot for the collection: a positive value indicates that the strain has a longer lag period and a negative number indicates it is shorter than the control mating. Data are derived from four biological replicates done with two technical replicates as described in the text. (B) Growth lag time of the top candidates. Conjugation efficiency screening was repeated with 96 strains at higher replication (18 replicates). Strains were chosen as described in the text. Plotted is the mean of the values with the standard error of the mean. Especially in the top candidates, many of the replicates had no detectable conjugation. For comparison, we have set values in this data set with no measurable growth lag to a value of 2, which corresponds to a mating lag time of four times the local control. Two strains had no measurable conjugation in any of the replicates (priA and rfaD). Two of the strains (aroD and crp) had fewer replicates (12). Previously known conjugation-deficient mutants are indicated with gray bars.

FIG 2

Conjugative efficiency of the Keio collection. (A) Growth lag time of the entire Keio collection in the conjugation assay. The growth lag of each curve is expressed relative to the nearby control and the log₂ value calculated. Shown is the frequency plot for the collection: a positive value indicates that the strain has a longer lag period and a negative number indicates it is shorter than the control mating. Data are derived from four biological replicates done with two technical replicates as described in the text. (B) Growth lag time of the top candidates. Conjugation efficiency screening was repeated with 96 strains at higher replication (18 replicates). Strains were chosen as described in the text. Plotted is the mean of the values with the standard error of the mean. Especially in the top candidates, many of the replicates had no detectable conjugation. For comparison, we have set values in this data set with no measurable growth lag to a value of 2, which corresponds to a mating lag time of four times the local control. Two strains had no measurable conjugation in any of the replicates (priA and rfaD). Two of the strains (aroD and crp) had fewer replicates (12). Previously known conjugation-deficient mutants are indicated with gray bars.

FIG 3

Conjugative efficiency from strains with detectable defects in mating. (A) Representative growth curves from 5 previously known (arcA, crp, dnaJ, dnaK, and hda) and four newly identified (dapF, dnaQ, fis, and fabF) conjugation-deficient mutants. The deleted gene in each strain is indicated. Three curves were taken from the plate screening experiments for each mutant as indicated (blue) and three nearby control mating results (green). The curves are representative of the 6 biological replicates each done with three technical replicates (n = 18). (B) Liquid mating assay results from 9 newly identified conjugation-deficient strains. The gene deleted in each mutant is indicated, and the average mating efficiency (number of transconjugants per number of donor cells divided by the corresponding value of a control mating done on the same day) in a 30-min liquid mating assay with 4 to 6 biological replicates (each with two technical replicates) over 2 to 3 different days is shown. Error bars indicate the standard error of the mean. P values were calculated using a one-sided Student t test: all results had a P value of <0.001.