Developmental Differentiations of Major Maize Stemborers Due to Global Warming in Temperate and Tropical Climates.

While many insects are in decline due to global warming, the effect of rising temperatures on crop insect pests is uncertain. A capacity to understand future changes in crop pest populations remains critical to ensure food security. Using temperature-dependent mathematical models of the development of four maize stemborers in temperate and tropical regions, we evaluated the potential impacts of different climate change scenarios on development time. While recognizing the limitations of the temperature-dependent development rate approach, we found that global warming could either be beneficial or detrimental to pest development, depending on the optimal temperature for the development of the species and scenarios of climate change. Expected responses range from null development to 1.5 times faster development than expected today. These results suggest that in the medium term, the studied species could benefit from global warming with an accelerated development, while in the long term, their development could either be delayed or accelerated, which may impact their dynamics with implications on maize cultivation.

Microbial community dispersal from wheat grains to sourdoughs: A contribution of participatory research.

Understanding microbial dispersal is critical to understand the dynamics and evolution of microbial communities. However, microbial dispersal is difficult to study because of uncertainty about their vectors of migration. This applies to both microbial communities in natural and human-associated environments. Here, we studied microbial dispersal along the sourdoughs bread-making chain using a participatory research approach. Sourdough is a naturally fermented mixture of flour and water. It hosts a community of bacteria and yeasts whose origins are only partially known. We analysed the potential of wheat grains and flour to serve as an inoculum for sourdough microbial communities using 16S rDNA and ITS1 metabarcoding. First, in an experiment involving farmers, a miller and bakers, we followed the microbiota from grains to newly initiated and propagated sourdoughs. Second, we compared the microbiota of 46 sourdough samples collected everywhere in France, and of the flour used for their back-slopping. The core microbiota detected on the seeds, in the flour and in the sourdough was composed mainly of microbes known to be associated with plants and not living in sourdoughs. No sourdough yeast species were detected on grains and flours. Sourdough lactic acid bacteria were rarely found in flour. When they were, they did not have the same amplicon sequence variant (ASV) as found in the corresponding sourdough. However, the low sequencing depth for bacteria in flour did not allow us to draw definitive conclusion. Thus, our results showed that sourdough yeasts did not come from flour, and suggest that neither do sourdough LAB.

Modeling Temperature-Dependent Development Rate in Insects and Implications of Experimental Design.

Characterizing the temperature-dependent development rate requires empirical data acquired by rearing individuals at different temperatures. Many mathematical models can be fitted to empirical data, making model comparison a mandatory step, yet model selection practices widely vary. We present guidelines for model selection using statistical criteria and the assessment of biological relevance of fits, exemplified throughout a Lepidoptera pest dataset. We also used in silico experiments to explore how experimental design and species attributes impact estimation accuracy of biological traits. Our results suggested that the uncertainty in model predictions was mostly determined by the rearing effort and the variance in development times of individuals. We found that a higher number of tested temperatures instead of a higher sample size per temperature may lead to more accurate estimations of model parameters. Our simulations suggested that an inappropriate model choice can lead to biased estimated values of biological traits (defined as attributes of temperature dependent development rate, i.e., optimal temperature for development and critical thresholds), highlighting the need for standardized model selection methods. Therefore, our results have direct implications for future studies on the temperature-dependent development rate of insects.

High-Throughput Feeding Bioassay for Lepidoptera Larvae.

Finding plant cultivars that are resistant or tolerant against lepidopteran pests, takes time, effort and is costly. We present here a high throughput leaf-disk consumption assay system, to screen plants for resistance or chemicals for their deterrence. A webcam capturing images at regular intervals can follow the feeding activities of 150 larvae placed into individual cages. We developed a computer program running under an open source image analysis program to analyze and measure the surface of each leaf disk over time. We further developed new statistical procedures to analyze the time course of the feeding activities of the larvae and to compare them between treatments. As a test case, we compared how European corn borer larvae respond to a commercial antifeedant containing azadirachtin, and to quinine, which is a bitter alkaloid for many organisms. As expected, increasing doses of azadirachtin reduced and delayed feeding. However, quinine was poorly effective at the range of concentrations tested (10-5 M to 10-2 M). The model cage, the camera holder, the plugins, and the R scripts are freely available, and can be modified according to the users' needs.

Correction: Investigations of the mechanisms of interactions between four non-conventional species with Saccharomyces cerevisiae in oenological conditions.

[This corrects the article DOI: 10.1371/journal.pone.0233285.].

Investigations of the mechanisms of interactions between four non-conventional species with Saccharomyces cerevisiae in oenological conditions.

Fermentation by microorganisms is a key step in the production of traditional food products such as bread, cheese, beer and wine. In these fermentative ecosystems, microorganisms interact in various ways, namely competition, predation, commensalism and mutualism. Traditional wine fermentation is a complex microbial process performed by Saccharomyces and non-Saccharomyces (NS) yeast species. To better understand the different interactions occurring within wine fermentation, isolated yeast cultures were compared with mixed co-cultures of one reference strain of S. cerevisiae with one strain of four NS yeast species (Metschnikowia pulcherrima, M. fructicola, Hanseniaspora opuntiae and H. uvarum). In each case, we studied population dynamics, resource consumed and metabolites produced from central carbon metabolism. This phenotyping of competition kinetics allowed us to confirm the main mechanisms of interaction between strains of four NS species. S. cerevisiae competed with H. uvarum and H. opuntiae for resources although both Hanseniaspora species were characterized by a strong mortality either in mono or mixed fermentations. M. pulcherrima and M. fructicola displayed a negative interaction with the S. cerevisiae strain tested, with a decrease in viability in co-culture. Overall, this work highlights the importance of measuring specific cell populations in mixed cultures and their metabolite kinetics to understand yeast-yeast interactions. These results are a first step towards ecological engineering and the rational design of optimal multi-species starter consortia using modeling tools. In particular the originality of this paper is for the first times to highlight the joint-effect of different species population dynamics on glycerol production and also to discuss on the putative role of lipid uptake on the limitation of some non-conventional species growth although interaction processes.

Fungal Species Diversity in French Bread Sourdoughs Made of Organic Wheat Flour.

Microbial communities are essential for the maintenance and functioning of ecosystems, including fermented food ecosystems. The analysis of food microbial communities is mainly focused on lactic acid bacteria (LAB), while yeast diversity is less understood. Here, we describe the fungal diversity of a typical food fermented product, sourdough bread. The species diversity of 14 sourdoughs collected from bakeries located all over France was analyzed. Bakeries were chosen to represent diverse bakery practices and included bakers and farmer-bakers. Both non-culture-based (pyrosequencing of Internal Transcribed Spacer 1 amplicons) and culture-based methods were used. While both identification methods were in agreement regarding the dominant yeast species of each sourdough, the ITS1 metabarcoding analysis identified an increased number of fungal species in sourdough communities. Two third of the identified sequences obtained from sourdoughs were Saccharomycetales, mostly in the Kazachstania genus. No Saccharomycetales species was shared by all the sourdoughs, whereas five other fungal species, mainly known plant pathogens, were found in all sourdoughs. Interestingly, Saccharomyces cerevisiae, known as "baker's yeast," was identified as the dominant species in only one sourdough. By contrast, five Kazachstania species were identified as the dominant sourdough species, including one recently described Kazachstania species, Kazachstania saulgeensis and an undescribed Kazachstania sp. Sourdoughs from farmer-bakers harbored Kazachstania bulderi, Kazachstania unispora and two newly described Kazachstania species, while sourdough from bakers mostly carried Kazachstania humilis as the dominant species. Such yeast diversity has not been found in sourdoughs before, highlighting the need to maintain different traditional food practices to conserve microbial diversity.

Bakery yeasts, a new model for studies in ecology and evolution.

Yeasts have been involved in bread making since ancient times and have thus played an important role in the history and nutrition of humans. Bakery-associated yeasts have only recently attracted the attention of researchers outside of the bread industry. More than 30 yeast species are involved in bread making, and significant progress has been achieved in describing these species. Here, we present a review of bread-making processes and history, and we describe the diversity of yeast species and the genetic diversity of Saccharomyces cerevisiae isolated from bakeries. We then describe the metabolic functioning and diversity of these yeasts and their relevance to improvements in bread quality. Finally, we examine yeast and bacterial interactions in sourdoughs. The purpose of this review is to show that bakery yeast species are interesting models for studying domestication and other evolutionary and ecological processes. Studying these yeasts can contribute much to our fundamental understanding of speciation, evolutionary dynamics, and community assembly, and this knowledge could ultimately be used to adjust, modify, and improve the production of bread and the conservation of microbial diversity.

Feedback between environment and traits under selection in a seasonal environment: consequences for experimental evolution.

Batch cultures are frequently used in experimental evolution to study the dynamics of adaptation. Although they are generally considered to simply drive a growth rate increase, other fitness components can also be selected for. Indeed, recurrent batches form a seasonal environment where different phases repeat periodically and different traits can be under selection in the different seasons. Moreover, the system being closed, organisms may have a strong impact on the environment. Thus, the study of adaptation should take into account the environment and eco-evolutionary feedbacks. Using data from an experimental evolution on yeast Saccharomyces cerevisiae, we developed a mathematical model to understand which traits are under selection, and what is the impact of the environment for selection in a batch culture. We showed that two kinds of traits are under selection in seasonal environments: life-history traits, related to growth and mortality, but also transition traits, related to the ability to react to environmental changes. The impact of environmental conditions can be summarized by the length of the different seasons which weight selection on each trait: the longer a season is, the higher the selection on associated traits. Since phenotypes drive season length, eco-evolutionary feedbacks emerge. Our results show how evolution in successive batches can affect season lengths and strength of selection on different traits.

Sourdough microbial community dynamics: An analysis during French organic bread-making processes.

Natural sourdoughs are commonly used in bread-making processes, especially for organic bread. Despite its role in bread flavor and dough rise, the stability of the sourdough microbial community during and between bread-making processes is debated. We investigated the dynamics of lactic acid bacteria (LAB) and yeast communities in traditional organic sourdoughs of five French bakeries during the bread-making process and several months apart using classical and molecular microbiology techniques. Sourdoughs were sampled at four steps of the bread-making process with repetition. The analysis of microbial density over 68 sourdough/dough samples revealed that both LAB and yeast counts changed along the bread-making process and between bread-making runs. The species composition was less variable. A total of six LAB and nine yeast species was identified from 520 and 1675 isolates, respectively. The dominant LAB species was Lactobacillus sanfranciscensis, found for all bakeries and each bread-making run. The dominant yeast species changed only once between bread-making processes but differed between bakeries. They mostly belonged to the Kazachstania clade. Overall, this study highlights the change of population density within the bread-making process and between bread-making runs and the relative stability of the sourdough species community during bread-making process.

Life-history strategies and carbon metabolism gene dosage in the Nakaseomyces yeasts.

The Nakaseomyces clade consists of a group of six hemiascomyceteous yeasts (Candida glabrata, Nakaseomyces delphensis, C. nivarensis, C. bracarensis, C. castelli, N. bacillisporus), phylogenetically close to the yeast Saccharomyces cerevisiae, their representative being the well-known pathogenic yeast C. glabrata. Four species had been previously examined for their carbon assimilation properties and found to have similar properties to S. cerevisiae (repression of respiration in high glucose-i.e. Crabtree positivity-and being a facultative anaerobe). We examined here the complete set of the six species for their carbon metabolic gene content. We also measured different metabolic and life-history traits (glucose consumption rate, population growth rate, carrying capacity, cell size, cell and biomass yield). We observed deviations from the glycolytic gene redundancy observed in S. cerevisiae presumed to be an important property for the Crabtree positivity, especially for the two species C. castelli and N. bacillisporus which frequently have only one gene copy, but different life strategies. Therefore, we show that the decrease in carbon metabolic gene copy cannot be simply associated with a reduction of glucose consumption rate and can be counterbalanced by other beneficial genetic variations.

Detailed contact data and the dissemination of Staphylococcus aureus in hospitals.

Close proximity interactions (CPIs) measured by wireless electronic devices are increasingly used in epidemiological models. However, no evidence supports that electronically collected CPIs inform on the contacts leading to transmission. Here, we analyzed Staphylococcus aureus carriage and CPIs recorded simultaneously in a long-term care facility for 4 months in 329 patients and 261 healthcare workers to test this hypothesis. In the broad diversity of isolated S. aureus strains, 173 transmission events were observed between participants. The joint analysis of carriage and CPIs showed that CPI paths linking incident cases to other individuals carrying the same strain (i.e. possible infectors) had fewer intermediaries than predicted by chance (P < 0.001), a feature that simulations showed to be the signature of transmission along CPIs. Additional analyses revealed a higher dissemination risk between patients via healthcare workers than via other patients. In conclusion, S. aureus transmission was consistent with contacts defined by electronically collected CPIs, illustrating their potential as a tool to control hospital-acquired infections and help direct surveillance.

Phenotypic and genotypic convergences are influenced by historical contingency and environment in yeast.

Different organisms have independently and recurrently evolved similar phenotypic traits at different points throughout history. This phenotypic convergence may be caused by genotypic convergence and in addition, constrained by historical contingency. To investigate how convergence may be driven by selection in a particular environment and constrained by history, we analyzed nine life-history traits and four metabolic traits during an experimental evolution of six yeast strains in four different environments. In each of the environments, the population converged toward a different multivariate phenotype. However, the evolution of most traits, including fitness components, was constrained by history. Phenotypic convergence was partly associated with the selection of mutations in genes involved in the same pathway. By further investigating the convergence in one gene, BMH1, mutated in 20% of the evolved populations, we show that both the history and the environment influenced the types of mutations (missense/nonsense), their location within the gene itself, as well as their effects on multiple traits. However, these effects could not be easily predicted from ancestors' phylogeny or past selection. Combined, our data highlight the role of pleiotropy and epistasis in shaping a rugged fitness landscape.

Re-assessment of mitigation strategies for deliberate releases of anthrax using a real-time outbreak characterization tool.

Responding rapidly and appropriately to a covert anthrax release is an important public health challenge. A methodology to assist the geographical targeting of such a response has recently been published; as have a number of independent studies that investigate mitigation strategies. Here, we review and combine some of these published techniques to more realistically assess how key aspects of the public health response might impact on the outcomes of a bioterrorist attack. We combine a within-host mathematical model with our spatial back-calculation method to investigate the effects of a number of important response variables. These include how previously reported levels of adherence with taking antibiotics might affect the total outbreak size compared to assuming full adherence. Post-exposure vaccination is also considered, both with and without the use of antibiotics. Further, we investigate a range of delays (2, 4 and 8 days) before interventions are implemented, following the last day of symptomatic onset of some number of observed initial cases (5, 10 and 15). Our analysis confirms that outbreak size is minimised by implementing prophylactic treatment after having estimated the exposed area based on 5 observed cases; however, imperfect (rather than full) adherence with antibiotics results in approximately 15% additional cases. Moreover, of those infected individuals who only partially adhere with a prophylactic course of antibiotics, 86% remain disease free; a result that holds for scenarios in which infected individuals inhale much higher doses than considered here. Increasing logistical delays have a particularly detrimental effect on lives saved with an optimal strategy of early identification and analysis. Our analysis shows that it is critical to have systems and processes in place to rapidly identify, geospatially analyse and then swiftly respond to a deliberate anthrax release.

Estimating the location and spatial extent of a covert anthrax release.

Rapidly identifying the features of a covert release of an agent such as anthrax could help to inform the planning of public health mitigation strategies. Previous studies have sought to estimate the time and size of a bioterror attack based on the symptomatic onset dates of early cases. We extend the scope of these methods by proposing a method for characterizing the time, strength, and also the location of an aerosolized pathogen release. A back-calculation method is developed allowing the characterization of the release based on the data on the first few observed cases of the subsequent outbreak, meteorological data, population densities, and data on population travel patterns. We evaluate this method on small simulated anthrax outbreaks (about 25-35 cases) and show that it could date and localize a release after a few cases have been observed, although misspecifications of the spore dispersion model, or the within-host dynamics model, on which the method relies can bias the estimates. Our method could also provide an estimate of the outbreak's geographical extent and, as a consequence, could help to identify populations at risk and, therefore, requiring prophylactic treatment. Our analysis demonstrates that while estimates based on the first ten or 15 observed cases were more accurate and less sensitive to model misspecifications than those based on five cases, overall mortality is minimized by targeting prophylactic treatment early on the basis of estimates made using data on the first five cases. The method we propose could provide early estimates of the time, strength, and location of an aerosolized anthrax release and the geographical extent of the subsequent outbreak. In addition, estimates of release features could be used to parameterize more detailed models allowing the simulation of control strategies and intervention logistics.

Modeling the impact of tuberculosis control strategies in highly endemic overcrowded prisons.

BACKGROUND: Tuberculosis (TB) in prisons is a major health problem in countries of high and intermediate TB endemicity such as Brazil. For operational reasons, TB control strategies in prisons cannot be compared through population based intervention studies. METHODOLOGY/PRINCIPAL FINDINGS: A mathematical model is proposed to simulate the TB dynamics in prison and evaluate the potential impact on active TB prevalence of several intervention strategies. The TB dynamics with the ongoing program was simulated over a 10 year period in a Rio de Janeiro prison (TB prevalence 4.6 %). Then, a simulation of the DOTS strategy reaching the objective of 70 % of bacteriologically-positive cases detected and 85 % of detected cases cured was performed; this strategy reduced only to 2.8% the average predicted TB prevalence after 5 years. Adding TB detection at entry point to DOTS strategy had no major effect on the predicted active TB prevalence. But, adding further a yearly X-ray mass screening of inmates reduced the predicted active TB prevalence below 1%. Furthermore, according to this model, after applying this strategy during 2 years (three annual screenings), the TB burden would be reduced and the active TB prevalence could be kept at a low level by associating X-ray screening at entry point and DOTS. CONCLUSIONS/SIGNIFICANCE: We have shown that X-ray mass screenings should be considered to control TB in highly endemic prison. Prisons with different levels of TB prevalence could be examined thanks to this model which provides a rational tool for public health deciders.

Real-time monitoring of the influenza vaccine field effectiveness.

Twice a year, the World Health Organization recommends the composition of the influenza vaccine depending on the strains which circulate several months before the beginning of the epidemic. Therefore, it is important to assess the field vaccine effectiveness (FVE) yearly. Thanks to data on vaccine coverage and data on influenza like illness cases collected by the French Sentinel Network, we are able to estimate the FVE few weeks after the beginning of the yearly influenza epidemic. In this paper, we have analysed the estimates obtained for the last 10 epidemic seasons for people over and under 65. Making the assumption that the vaccine coverage is stable from 1 year to another, we are able to assess the level of the FVE few weeks after the beginning of the epidemic and we should detect a lack of effectiveness of the vaccine.

Modeling spatial and temporal transmission of foot-and-mouth disease in France: identification of high-risk areas.

Foot-and-mouth disease is one of the most contagious diseases of animal livestock. We used statistical tools to explore the dynamics of epidemics and to evaluate the consequences of virus reintroduction in France. We developed a stochastic farm-based model adapted to the French farm structure from previous modeling works following the 2001 epidemic in the United Kingdom. This model depends upon the distance between the 280,000 French farms and on species type (e.g. cows and sheep) and it tracks each animal's farm status at any given day. Since data were only available at the town scale, the farm location and the number of animals in each farm were simulated over the surface area of each French town, as well as the number of mixed farms. Based on 200 simulations of the model, our results allowed for the study of local disease transmission, since it begins simulations once limitation of movement is put into place. On average, the same 50 randomly chosen initially infected farms would lead to 1,110 infected farms (610; 1,590) when two control strategies (culling within 0.5 km from an infected farm and vaccination within 3 km) are put into place. Regions with high densities of cows and sheep (e.g. Pays-de-la-Loire) are high-risk zones, confirming that the epidemic process depends upon the location and the type of initially infected farms (size, species type). The results of this model highlight the importance of Geographical Information Systems (GIS) to obtain more precise data concerning herds.