Group selection as a basis for screening mutagenized libraries of public goods (bacillus thuringiensis cry toxins)

The pesticidal toxins of Bacillus thuringiensis (Bt) supply the active proteins for genetically modified insect-resistant crops. There is therefore keen interest in finding new toxins, or improving known toxins, in order to increase the mortality of various targets. The production and screening of large libraries of mutagenized toxins are among the means of identifying improved toxins. Since Cry toxins are public goods, and do not confer advantages to producers in competition, conventional directed evolution approaches cannot be used here. Instead, thousands of individual mutants have to be sequenced and assayed individually, a costly and time-consuming process. In this study, we tested a group selection-based approach that could be used to screen an uncharacterized pool of Cry toxin mutants. This involved selecting for infectivity between subpopulations of Bt clones within metapopulations of infected insects in three rounds of passage. We also tested whether additional mutagenesis from exposure to ethyl methanesulfonate could increase infectivity or supply additional Cry toxin diversity during passage. Sequencing of pools of mutants at the end of selection showed that we could effectively screen out Cry toxin variants that had reduced toxicity with our group selection approach. The addition of extra mutagenesis during passage decreased the efficiency of selection for infectivity and did not produce any additional novel toxin diversity. Toxins with loss-of-function mutations tend to dominate mutagenized libraries, and so a process for screening out these mutants without time-consuming sequencing and characterization steps could be beneficial when applied to larger libraries. IMPORTANCE Insecticidal toxins from the bacterium Bacillus thuringiensis are widely exploited in genetically modified plants. This application creates a demand for novel insecticidal toxins that can be used to better manage resistant pests or control new or recalcitrant target species. An important means of producing novel toxins is via high-throughput mutagenesis and screening of existing toxins, a lengthy and resource-intensive process. This study describes the development and testing of an efficient means of screening a test library of mutagenized insecticidal toxins. Here, we showed that it is possible to screen out loss-of-function mutations with low infectivity within a pool without the need to characterize and sequence each mutant individually. This has the potential to improve the efficiency of processes used to identify novel proteins

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

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

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

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