Data for: Constitutive expression of the Type VI secretion system carries no measurable fitness cost in Vibrio cholerae

The Type VI Secretion System (T6SS) is a widespread and highly effective mechanism of microbial warfare; it confers the ability to efficiently kill susceptible cells within close proximity. Due to its large physical size, complexity, and ballistic basis for intoxication, it has widely been assumed to incur significant growth costs in the absence of improved competitive outcomes. In this study, we precisely examine the fitness costs of constitutive T6SS firing in the bacterium Vibrio cholerae. We find that, contrary to expectations, constitutive expression of the T6SS has a negligible impact on growth, reducing growth fitness by 0.025 ± 0.5% (95% CI) relative to a T6SS- control. Mathematical modeling of microbial populations demonstrates that, due to clonal interference, constitutive expression of the T6SS will often be neutral, with little impact on evolutionary outcomes. Our findings underscore the importance of precisely measuring the fitness costs of microbial social behaviors, and help explain the prevalence of the T6SS across Gram negative bacteria.

Methods
Bacterial strains and media: Bacterial strains were grown aerobically at 37°C overnight in lysogeny broth (LB) (1% w/v tryptone (Teknova, Hollister CA, USA), 0.5% w/v yeast extract (Hardy Diagnostics, Santa Maria CA, USA), 1% w/v NaCl (VWR Life Sciences, Radnor PA, USA)) with constant shaking or on LB agar (1.5% w/v agar; Genesee Scientific, San Diego CA, USA) standing at 37°C. LB-X-gal was made by mixing in 40 μg/mL of X-gal (GoldBio, St. Louis MO, USA) to LB agar while it is liquid.

Mutant Construction: All V. cholerae mutant strains were made using the pKAS allelic exchange system described by Skorupski et al using pKAS32 (Skorupski & Taylor, 1996). JT101 and SN598 [Supplemental Data File 1] were described in previous studies (Ng et al., 2022; Thomas et al., 2017). CZ005 and CZ006 were generated through an insertion of a spectinomycin resistance cassette into the lacZ gene of JT101 and SN598 respectively. All insertions and changes to phenotype were confirmed with PCR, antibiotic screening, and killing assays.

Liquid LB Competition Experiment: Overnight cultures of V. cholerae were normalized to an OD600 = 1 then mixed in a 1:1 ratio by volume. Each mixture was then serially diluted and 100 μL of the 10-3 dilution was mixed into 5mL of LB and incubated overnight shaking at 37°C. 100 μL of the 10-5 dilution was plated onto an LB X-gal plate for quantification with blue-white screening. For the subsequent 4 days, each overnight mixture was serially diluted and 100 μL of the 10-5 dilution was mixed into 5mL of LB and the 10-6 dilution was plated onto an LB X-gal plate for quantification. Fitness was calculated by finding the ratio of Malthusian parameters as described in Lenski et al (1991).

Solid Agar Competition Experiment: Overnight cultures of V. cholerae were normalized to an OD600 = 1 then mixed in a 1:1 ratio by volume. Each mixture was then serially diluted and 100 μL of the 10-5 dilution was plated onto LB X-gal as well as on LB. The X-gal plate was saved for quantification. The LB plate was incubated standing at 37°C. Every following 8 hours for 5 days, the LB plate was taken out of the standing incubator and all of the agar was scraped off of the plate and transferred into a 50 mL conical tube containing 10mL of LB. This conical tube was vortexed for 30 seconds and 300 μL of the supernatant was transferred into a 96 well plate and serially diluted. 100 μL that contained approximately 200-1000 CFU per 100uL was transferred onto an LB plate for the next time point. Every three time points were recorded via blue-white screening by plating 100uL of the serial dilution that contained between 30-300 CFU per 100uL onto X-gal for quantification. Fitness was calculated with the same calculation as the Liquid LB competition experiment.

Wright-Fisher Model: The Wright-Fisher model is a standard framework used in evolutionary biology to describe stochastic allelic evolutionary processes including genetic drift, and in our paper, clonal interference. In a Wright-Fisher simulation, discrete generations of bacteria are calculated by drawing from a weighted binomial distribution from the previous generation. To simulate the effects of clonal interference, each cell had a 10-5 chance of mutation every generation. When a cell was mutated, the overall fitness effect of the mutation was drawn from an exponential distribution with the parameter ꞵ derived from Good et al (2012). Each simulation was run 1000 times and 200 random runs were plotted for clarity.

Statistics: The 95% confidence interval for both competition assays was calculated with a two sample t-test for the difference in two means. See supplemental table for details. The p values in Figure 2 were calculated by counting the quantity of populations that reached fixation or extinction after 5000 simulated generations and using a ?2-test to test the null hypothesis that the T6SS+ strain will go to fixation 50% of the time.

Killing assay: Overnight cultures of V. cholerae and E. coli (resistant to chloramphenicol) were normalized to an OD600 = 1 then mixed in a 10:1 ratio of V. cholerae to E. coli by volume. 5 μL of this mixture was spotted onto an LB agarose plate and left to dry for 10 minutes. The plate was then incubated at 37°C for 3 hours. The spot on the plate was cut out and vortexed with 5 mL of LB broth for 30 seconds. The broth was then serially diluted and 5uL of each of the serial dilution mixtures were spotted onto an LB chloramphenicol plate.

RNA sequencing analysis: Overnight cultures of T6SS+, T6SS−, and WT Vibrio cholerae were grown at 37°C in lysogeny broth (LB) (n = 2 biological replicates). RNA was extracted from these cultures using an Qiagen RNeasy mini kit (Qiagen, Hilden, Germany). An RNA library was prepared using the NEB Ultra II directional RNA library prep kit (New England Biolabs, Ipswitch, MA, USA) and the QIASeq Fast select -RNA HMR kit (Qiagen, Hilden, Germany) was used for bacterial rRNA depletion. The completed bacterial RNA library was sequenced on the Illumina NovaSeq 6000 (Illumina, San Diego, CA, USA). To analyze the transcriptomic data, we first trimmed adapters and filtered low-quality reads using Trimmonatic (v0.39) (Bolger et al., 2014). We then perform alignment of paired reads to reference contigs of V. cholerae C6706 (NCBI RefSeq assembly GCF_009763945.1) using STAR (v 2.7.11a) (Dobin et al., 2013) to create binary alignment files (BAM) sorted by genomic coordinates. We counted aligned fragments to all annotated loci in NCBI Refseq annotation using featureCounts (v2.0.6) (Liao et al., 2014). Fragment counts were filtered for low expression and used for differential expression analysis using DESeq2 in R (Love et al., 2014).