Pre-Disposition and Epigenetics Govern Variation in Bacterial Survival upon Stress

<div><p>Bacteria suffer various stresses in their unpredictable environment. In response, clonal populations may exhibit cell-to-cell variation, hypothetically to maximize their survival. The origins, propagation, and consequences of this variability remain poorly understood. Variability persists through cell division events, yet detailed lineage information for individual stress-response phenotypes is scarce. This work combines time-lapse microscopy and microfluidics to uniformly manipulate the environmental changes experienced by clonal bacteria. We quantify the growth rates and RpoH-driven heat-shock responses of individual <em>Escherichia coli</em> within their lineage context, stressed by low streptomycin concentrations. We observe an increased variation in phenotypes, as different as survival from death, that can be traced to asymmetric division events occurring prior to stress induction. Epigenetic inheritance contributes to the propagation of the observed phenotypic variation, resulting in three-fold increase of the RpoH-driven expression autocorrelation time following stress induction. We propose that the increased permeability of streptomycin-stressed cells serves as a positive feedback loop underlying this epigenetic effect. Our results suggest that stochasticity, pre-disposition, and epigenetic effects are at the source of stress-induced variability. Unlike in a bet-hedging strategy, we observe that cells with a higher investment in maintenance, measured as the basal RpoH transcriptional activity prior to antibiotic treatment, are more likely to give rise to stressed, frail progeny.</p> </div

Indirect Fitness Benefits Enable the Spread of Host Genes Promoting Costly Transfer of Beneficial Plasmids

<div><p>Bacterial genes that confer crucial phenotypes, such as antibiotic resistance, can spread horizontally by residing on mobile genetic elements (MGEs). Although many mobile genes provide strong benefits to their hosts, the fitness consequences of the process of transfer itself are less clear. In previous studies, transfer has been interpreted as a parasitic trait of the MGEs because of its costs to the host but also as a trait benefiting host populations through the sharing of a common gene pool. Here, we show that costly donation is an altruistic act when it spreads beneficial MGEs favoured when it increases the inclusive fitness of donor ability alleles. We show mathematically that donor ability can be selected when relatedness at the locus modulating transfer is sufficiently high between donor and recipients, ensuring high frequency of transfer between cells sharing donor alleles. We further experimentally demonstrate that either population structure or discrimination in transfer can increase relatedness to a level selecting for chromosomal transfer alleles. Both mechanisms are likely to occur in natural environments. The simple process of strong dilution can create sufficient population structure to select for donor ability. Another mechanism observed in natural isolates, discrimination in transfer, can emerge through coselection of transfer and discrimination alleles. Our work shows that horizontal gene transfer in bacteria can be promoted by bacterial hosts themselves and not only by MGEs. In the longer term, the success of cells bearing beneficial MGEs combined with biased transfer leads to an association between high donor ability, discrimination, and mobile beneficial genes. However, in conditions that do not select for altruism, host bacteria promoting transfer are outcompeted by hosts with lower transfer rate, an aspect that could be relevant in the fight against the spread of antibiotic resistance.</p></div

Growth inhibition and clonal cell death correlate with a high stress response.

<p>(A) Correlation between reporter intensity and growth rate in response to stress. The growth rate and fluorescence intensity of single cells are measured 130 minutes after Streptomycin treatment. Red indicates dead cells; blue, live cells. (B) Histogram of the growth rate distribution from the same data set as (A). The dashed line indicates the threshold we chose to distinguish alive from dead cells. (C) Life history of a sub-lineage from the micro-colony (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003148#pgen-1003148-g003" target="_blank">Figure 3</a> for the full lineage tree and the legend therein). The colour code represents the fluorescence intensity. Dead cells are indicated by a red dot at the end of the lineage tree. In addition, the cellular growth rate is represented inversely by line width (e.g., bold line the slow growers). The dashed line indicates the time of induction by streptomycin. Data correspond to <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003148#pgen.1003148.s022" target="_blank">Video S2</a>.</p

Selection of donor ability in structured populations.

<p><b>A: Experimental setup.</b> D⁺ (good donor, red) and D⁻ (nondonor, blue) strains are competed. 2.5% of D⁺ and D⁻ cells initially carry C plasmids (bright colours), while 97.5% do not (pale colours). The population <i>m</i> is a single well-mixed population; metapopulation <i>s</i> consists of two subpopulations, <i>s</i>_<i>1</i> and <i>s</i>_<i>2</i>, with initial D⁺/D⁻ ratios of 1/9 and 9/1. After growth and transfer (t₀ to t₁), subpopulations from <i>s</i> are pooled and cells are grown to saturation with or without antibiotic (Cm) selection (t₁ to t₂). The proportions of different cell types are represented schematically and do not correspond to actual numbers. <b>B: Selection of D</b>^<b>+</b> <b>strain.</b> The frequency of the good donor D⁺ is shown for <i>s</i> (black) and <i>m</i> (green) populations, with (plain lines) or without (dashed lines) Cm antibiotic during the selection phase. Good donors are only selected for in the <i>s</i> metapopulation, in the presence of antibiotic. <b>C: Plasmid dynamics.</b> Plasmid frequency in each population is shown for the transfer phase (from t₀ to t₁)_, in each of <i>m</i>, <i>s</i>_<i>1</i>, and <i>s</i>_<i>2</i> populations. Plasmids spread mostly in the s₂ subpopulation, enriched in the better donor, D⁺. <b>D: Transfer bias.</b> The proportion of C plasmids present in D⁺ strain, is shown as a function of time for <i>s</i> and <i>m</i> populations (same colour scheme as in B panel). C plasmids get enriched in the better donor D⁺ strain during the transfer phase, for the structured population <i>s</i>. All results are shown as means ± SEM. (<i>N</i> ≥ 6). Data are available from FigShare at <a href="http://dx.doi.org/10.6084/m9.figshare.3199252" target="_blank">http://dx.doi.org/10.6084/m9.figshare.3199252</a>.</p

Increased cellular membrane permeability following stress induction.

<p>Exponential phase cells of a strain carrying both p<i>^terR</i> - and p<i>^ibpAB</i> -driven fluorescence reporters are plated on LB-agar pads with or without streptomycin (3 µg/ml) and ATC (25 ng/ml). After 2–3 hours of colony growth, the reporter intensity is quantified by fluorescence microscopy. The intensity is normalized to that of the non-induced state ([streptomycin] = [ATC] = 0). The black dot in the middle of each data cloud shows the mean value of both fluorescence channels. R² and k are the coefficient of determination and slope for linear fitting. For each condition, at least 5 micro-colonies are quantified.</p

Default parameter values used in simulations.

<p>Parameters were generally based on our experimental measurements (see <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002478#sec015" target="_blank">Materials and Methods</a> for details and exceptions).</p

Increased auto-correlation of the stress response within micro-colonies after induction.

<p>The mathematical derivation of the auto-correlation function (AF) can be found in the <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003148#pgen.1003148.s020" target="_blank">Text S1</a>. The black curve shows the AF of non-induced micro-colonies (average of 4). The yellow area indicates the standard deviation. The blue, cyan, green and red curves are the AFs calculated with starting points that are 70 minutes, 90 minutes, 110 minutes, and 140 minutes after induction respectively. The induced AF data is from the micro-colony shown in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003148#pgen.1003148.s022" target="_blank">Video S2</a>. The generation is determined by the number of cells in the micro-colony. All the curves are truncated at the 8–16 cell stage due to increased fluctuations for small sample sizes.</p

Graphical representation of different scenarios for the selection of transfer as an altruistic trait.

<p>In this simplified diagram, we follow a strain with high donor ability (red) in competition with another strain with no donor ability (white). Some cells of both strains bear an antibiotic resistance plasmid (black dots) that donors can transfer (red arrows) to a cell of either type, as long as it is plasmid-free. Our model predicts that donors are selected for when the red-framed equation is true (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002478#pbio.1002478.e003" target="_blank">Eq 3</a>, see main text). For clarity, we assume three sequential steps: (1) transfer, whose recipients depend on relatedness at the donor ability locus (<i>R</i>_<i>q</i>) and whose efficiency depends on plasmid frequency within patches <i>p</i>_<i>j</i>; (2) antibiotic selection, where only plasmid-bearing cells survive (<i>e</i>_<i>p</i> > 0); and finally, (3) cell growth after selection, where donor cells experience a cost <i>c</i>_<i>q</i> and grow more slowly. We describe three possible scenarios, depending on the properties of transfer and its effects on relatedness at the donation locus. <b>A:</b> In the absence of discrimination in transfer or population structure, relatedness among donors and recipients is null, and transfer occurs with the same efficiency towards all cells. <b>B:</b> In the presence of discrimination in transfer, good donors transfer plasmids specifically to their kind. <b>C:</b> In structured populations, good donors are surrounded by their kind, to which they preferentially transfer plasmids even in the absence of discrimination. In all scenarios, donor cells experience the cost of expressing the transfer machinery during growth. However, only in <b>B</b> and <b>C</b> does transfer bias lead to an enrichment of plasmids in the donor strain after transfer, which can compensate for donor ability cost when plasmids are selected for.</p

Emergence of linkage between donation and discrimination loci.

<p><b>A: Selection of discrimination and donor ability.</b> The change in frequency of D⁺ (red) and M⁻ (blue) alleles after antibiotic selection is computed from simulations. The populations are analogous to structured populations <i>s</i> (<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1002478#pbio.1002478.g003" target="_blank">Fig 3</a>), but here we vary the strength of population structure (<i>x</i>-axis), expressed as the initial difference in D⁺ cell frequency between the two subpopulations. Initially, 2.5% of cells bear the antibiotic plasmid conferring antibiotic resistance. <b>B: Linkage between donation and discrimination alleles.</b> The linkage between D⁺ and M^- alleles is shown at the end of competition as a function of D⁺ population structure, calculated as before, in the absence (dashed line) and presence (bold line) of antibiotic selection that allows only plasmid-bearing cells to grow. <b>C: Plasmid transfer bias.</b> The proportion of each genotype among plasmid-bearing cells, at the end of competition is shown as a function of D⁺ population structure. With increasing population structuring, plasmids are progressively enriched in D⁺ M⁻ cells (red line). Data are available from FigShare at <a href="http://dx.doi.org/10.6084/m9.figshare.3199252" target="_blank">http://dx.doi.org/10.6084/m9.figshare.3199252</a>.</p

Selection of donor ability in a population structured by strong initial dilution.

<p>The simulated metapopulation consists of 192 subpopulations initiated from a strongly diluted mix of equal proportions of D⁺ and D⁻ cells, giving rise to a Poisson distribution of cell number across subpopulations for each cell type. The colour scale represents the change in D⁺ frequency from t₀ to t₂ averaged over 1,000 simulations, shown as a function of the initial proportion of plasmid-bearing cells and mean founding cell number per subpopulation after dilution. Data are available from FigShare at <a href="http://dx.doi.org/10.6084/m9.figshare.3199252" target="_blank">http://dx.doi.org/10.6084/m9.figshare.3199252</a>.</p