Raymond Shapiro raw bioassay and other data

This is an excel file with data on baseline bioassays, passage 6 and 12 bioassays, reproductive rate assays, and number of founders per host in the different treatments

Raw bacteria plasmid association data

Excel sheet containing data on bacterial abundance, genotype, replicon profiles associated with pat and site

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

Proportional outcomes from 10³ simulations for the spatial WAP model under a scenario of increased regional warming and an increase in the krill fishery.

<p>Blue represents a negative change, grey is no change, and orange is a positive change. Results indicate a higher propensity for negative change in the northern subregion (N) as compared to middle (M) and southern (S) subregions across a range of taxa.</p

Testing Paradigms of Ecosystem Change under Climate Warming in Antarctica

<div><p>Antarctic marine ecosystems have undergone significant changes as a result of human activities in the past and are now responding in varied and often complicated ways to climate change impacts. Recent years have seen the emergence of large-scale mechanistic explanations–or “paradigms of change”–that attempt to synthesize our understanding of past and current changes. In many cases, these paradigms are based on observations that are spatially and temporally patchy. The West Antarctic Peninsula (WAP), one of Earth’s most rapidly changing regions, has been an area of particular research focus. A recently proposed mechanistic explanation for observed changes in the WAP region relates changes in penguin populations to variability in krill biomass and regional warming. While this scheme is attractive for its simplicity and chronology, it may not account for complex spatio-temporal processes that drive ecosystem dynamics in the region. It might also be difficult to apply to other Antarctic regions that are experiencing some, though not all, of the changes documented for the WAP. We use qualitative network models of differing levels of complexity to test paradigms of change for the WAP ecosystem. Importantly, our approach captures the emergent effects of feedback processes in complex ecological networks and provides a means to identify and incorporate uncertain linkages between network elements. Our findings highlight key areas of uncertainty in the drivers of documented trends, and suggest that a greater level of model complexity is needed in devising explanations for ecosystem change in the Southern Ocean. We suggest that our network approach to evaluating a recent and widely cited paradigm of change for the Antarctic region could be broadly applied in hypothesis testing for other regions and research fields.</p> </div

Fixed spores dose-response

The dose-response for 900 Bacillus thuringiensis spores supplemented with varying quantities of toxins in two experiments. (Corresponding to Fig. 1B)

WT dose-response

The dose-response for wild type Bacillus thuringiensis in two experiments, presented in Fig. 2 of the main text. Shown are the dead and live insect counts for a range of inoculum sizes in each of the experiments

Fixed toxins dose-response

The dose-responses for varying quantities of spores of Bacillus thuringiensis a Cry null strain supplemented with 60 pg of toxin 180 pg of toxin (corresponding to Fig. 1A)

Principal components ordination of model predictions (proportion of simulations indicating a negative change for each variable in the spatial model) from sensitivity analyses.

<p>Eigenvectors (with magnitudes >0.2) are represented as a bioplot. 96% of the total variance is captured by PC1 (88%) and PC2 (8%). Results from varying the number of simulations used in qualitative network analyses (case (i) scenarios) are shown in black and grey; the filled grey circle represents the main perturbation scenario examined (concurrent increases in the krill fishery and warming) and default number of simulations (10⁴). Pink squares represent scenarios where the krill fishery and warming were perturbed separately (case (ii) scenarios), while blue squares represent scenarios where models were constrained to meet specific criteria (case (iii) scenarios, as described in the main text).</p

Spatial implementation of the extended network model for the WAP ecosystem (Fig. 1B).

<p>Northern (N), middle (M) and southern (S) subregions correspond approximately with the South Shetland Islands, the Palmer Long-Term Ecological Research Program area and Marguerite Bay, respectively. The model includes south to north transport of larval krill <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055093#pone.0055093-Thorpe1" target="_blank">[14]</a>, and pelagic foragers as trophic competitors with Adélie and chinstrap penguins. Chinstrap penguins are restricted to the northern subregion <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055093#pone.0055093-Fraser1" target="_blank">[30]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0055093#pone.0055093-Lynch1" target="_blank">[31]</a>. All model components have a limiting (negative) self-interaction, but for clarity these are not shown.</p