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Scanning flow cytometry (SFCM) is characterized by the measurement of time-resolved pulses of fluorescence and scattering, enabling the high-throughput quantification of phytoplankton morphology and pigmentation. Quantifying variation at the single cell and colony level improves our ability to understand dynamics in natural communities. Automated high-frequency monitoring of these communities is presently limited by the absence of repeatable, rapid protocols to analyse SFCM datasets, where images of individual particles are not available. Here we demonstrate a repeatable, semi-automated method to (1) rapidly clean SFCM data from a phytoplankton community by removing signals that do not belong to live phytoplankton cells, (2) classify individual cells into trait clusters that correspond to functional groups, and (3) quantify the biovolumes of individual cells, the total biovolume of the whole community and the total biovolumes of the major functional groups. Our method involves the development of training datasets using lab cultures, the use of an unsupervised clustering algorithm to identify trait clusters, and machine learning tools (random forests) to (1) evaluate variable importance, (2) classify data points, and (3) estimate biovolumes of individual cells. We provide example datasets and R code for our analytical approach that can be adapted for analysis of datasets from other flow cytometers or scanning flow cytometers.

Chemical micropollutants occur worldwide in the environment at low concentrations and in complex mixtures, and how they affect the ecology of natural systems is still uncertain. Dynamics of natural communities are driven by the interaction between individual organisms and their growth environment, which is mediated by the organisms' expressed phenotypic traits. We tested whether exposure to a mixture of 12 pharmaceuticals and personal care products (PPCP) influences phenotypic trait diversity in lake phytoplankton communities and their ability to regulate biomass production to fit environmental changes (response capacity). We exposed natural phytoplankton assemblages to three mixture levels in permeable microcosms maintained at three depths in a eutrophic lake for one week, during which the environmental conditions were fluctuating. We studied individual-level traits, phenotypic diversity and community biomass. PPCP reduced individual-level trait variance and overall community phenotypic diversity, but maintained higher standing phytoplankton biomass compared to untreated controls. Estimated effect sizes of PPCP on traits and community properties were very large (partial Eta-squared > 0.15). The PPCP mixture antagonistically interacted with the natural environmental gradient in habitats offered by different depths and, at concentrations comparable to those in waste-water effluents, prevented communities from converging to the same phenotypic structure and total biomass of unexposed controls. We show that micropollutants can alter individual-level trait diversity of lake phytoplankton communities and therefore their capacity to respond to natural environmental gradients, potentially affecting aquatic ecosystem processes.

Animal contact is a potential transmission route for campylobacteriosis, and both domestic household pet and petting zoo exposures have been identified as potential sources of exposure. Research has typically focussed on the prevalence, concentration, and transmission of zoonoses from farm animals to humans, yet there are gaps in our understanding of these factors among animals in contact with the public who don't live on or visit farms. This study aims to quantify, through a systematic review and meta-analysis, the prevalence and concentration of Campylobacter carriage in household pets and petting zoo animals. Four databases were accessed for the systematic review (PubMed, CAB direct, ProQuest, and Web of Science) for papers published in English from 1992-2012, and studies were included if they examined the animal population of interest, assessed prevalence or concentration with fecal, hair coat, oral, or urine exposure routes (although only articles that examined fecal routes were found), and if the research was based in Canada, USA, Europe, Australia, and New Zealand. Studies were reviewed for qualitative synthesis and meta-analysis by two reviewers, compiled into a database, and relevant studies were used to create a weighted mean prevalence value. There were insufficient data to run a meta-analysis of concentration values, a noted study limitation. The mean prevalence of Campylobacter in petting zoo animals is 6.5% based on 7 studies, and in household pets the mean is 24.7% based on 34 studies. Our estimated concentration values were: 7.65x103cfu/g for petting zoo animals, and 2.9x105cfu/g for household pets. These results indicate that Campylobacter prevalence and concentration are lower in petting zoo animals compared with household pets and that both of these animal sources have a lower prevalence compared with farm animals that do not come into contact with the public. There is a lack of studies on Campylobacter in petting zoos and/or fair animals in Canada and abroad. Within this literature, knowledge gaps were identified, and include: a lack of concentration data reported in the literature for Campylobacter spp. in animal feces, a distinction between ill and diarrheic pets in the reported studies, noted differences in shedding and concentrations for various subtypes of Campylobacter, and consistent reporting between studies.

Background: The Foodborne Disease Burden Epidemiology Reference Group (FERG) was established in 2007 by the World Health Organization to estimate the global burden of foodborne diseases (FBDs). This paper describes the methodological framework developed by FERG's Computational Task Force to transform epidemiological information into FBD burden estimates., Methods and Findings: The global and regional burden of 31 FBDs was quantified, along with limited estimates for 5 other FBDs, using Disability-Adjusted Life Years in a hazard- and incidence-based approach. To accomplish this task, the following workflow was defined: outline of disease models and collection of epidemiological data; design and completion of a database template; development of an imputation model; identification of disability weights; probabilistic burden assessment; and estimating the proportion of the disease burden by each hazard that is attributable to exposure by food (i.e., source attribution). All computations were performed in R and the different functions were compiled in the R package 'FERG'. Traceability and transparency were ensured by sharing results and methods in an interactive way with all FERG members throughout the process., Conclusions: We developed a comprehensive framework for estimating the global burden of FBDs, in which methodological simplicity and transparency were key elements. All the tools developed have been made available and can be translated into a user-friendly national toolkit for studying and monitoring food safety at the local level.

Objective: Genome-wide association studies have uncovered a large number of genetic variants associated with type 2 diabetes or related phenotypes. In many cases the causal gene or polymorphism has not been identified, and its impact on response to anti-hyperglycemic medications is unknown. The Study to Understand the Genetics of the Acute Response to Metformin and Glipizide in Humans (SUGAR-MGH, NCT01762046) is a novel resource of genetic and biochemical data following glipizide and metformin administration. We describe recruitment, enrollment, and phenotyping procedures and preliminary results for the first 668 of our planned 1,000 participants enriched for individuals at risk of requiring anti-diabetic therapy in the future., Methods: All individuals are challenged with 5 mg glipizide × 1; twice daily 500 mg metformin × 2 days; and 75-g oral glucose tolerance test following metformin. Genetic variants associated with glycemic traits and blood glucose, insulin, and other hormones at baseline and following each intervention are measured., Results: Approximately 50% of the cohort is female and 30% belong to an ethnic minority group. Following glipizide administration, peak insulin occurred at 60 minutes and trough glucose at 120 minutes. Thirty percent of participants experienced non-severe symptomatic hypoglycemia and required rescue with oral glucose. Following metformin administration, fasting glucose and insulin were reduced. Common genetic variants were associated with fasting glucose levels., Conclusions: SUGAR-MGH represents a viable pharmacogenetic resource which, when completed, will serve to characterize genetic influences on pharmacological perturbations, and help establish the functional relevance of newly discovered genetic loci to therapy of type 2 diabetes., Trial Registration: ClinicalTrials.gov NCT01762046.

Background: Up to 150 million North Americans currently use a groundwater system as their principal drinking water source. These systems are a potential source of exposure to enteric pathogens, contributing to the burden of waterborne disease. Waterborne disease outbreaks have been associated with US and Canadian groundwater systems over the past two decades. However, to date, this literature has not been reviewed in a comprehensive manner., Methods and Principal Findings: A combined review and pooled-analysis approach was used to investigate groundwater contamination in Canada and the US from 1990 to 2013; fifty-five studies met eligibility criteria. Four study types were identified. It was found that study location affects study design, sample rate and studied pathogen category. Approximately 15% (316/2210) of samples from Canadian and US groundwater sources were positive for enteric pathogens, with no difference observed based on system type. Knowledge gaps exist, particularly in exposure assessment for attributing disease to groundwater supplies. Furthermore, there is a lack of consistency in risk factor reporting (local hydrogeology, well type, well use, etc). The widespread use of fecal indicator organisms in reported studies does not inform the assessment of human health risks associated with groundwater supplies., Conclusions: This review illustrates how groundwater study design and location are critical for subsequent data interpretation and use. Knowledge gaps exist related to data on bacterial, viral and protozoan pathogen prevalence in Canadian and US groundwater systems, as well as a need for standardized approaches for reporting study design and results. Fecal indicators are examined as a surrogate for health risk assessments; caution is advised in their widespread use. Study findings may be useful during suspected waterborne outbreaks linked with a groundwater supply to identify the likely etiological agent and potential transport pathway.

"It takes a village to finish (marine) science these days" Paraphrased from Curtis Huttenhower (the Human Microbiome project) The rapidity and complexity of climate change and its potential effects on ocean biota are challenging how ocean scientists conduct research. One way in which we can begin to better tackle these challenges is to conduct community-wide scientific studies. This study provides physiological datasets fundamental to understanding functional responses of phytoplankton growth rates to temperature. While physiological experiments are not new, our experiments were conducted in many laboratories using agreed upon protocols and 25 strains of eukaryotic and prokaryotic phytoplankton isolated across a wide range of marine environments from polar to tropical, and from nearshore waters to the open ocean. This community-wide approach provides both comprehensive and internally consistent datasets produced over considerably shorter time scales than conventional individual and often uncoordinated lab efforts. Such datasets can be used to parameterise global ocean model projections of environmental change and to provide initial insights into the magnitude of regional biogeographic change in ocean biota in the coming decades. Here, we compare our datasets with a compilation of literature data on phytoplankton growth responses to temperature. A comparison with prior published data suggests that the optimal temperatures of individual species and, to a lesser degree, thermal niches were similar across studies. However, a comparison of the maximum growth rate across studies revealed significant departures between this and previously collected datasets, which may be due to differences in the cultured isolates, temporal changes in the clonal isolates in cultures, and/or differences in culture conditions. Such methodological differences mean that using particular trait measurements from the prior literature might introduce unknown errors and bias into modelling projections. Using our community-wide approach we can reduce such protocol-driven variability in culture studies, and can begin to address more complex issues such as the effect of multiple environmental drivers on ocean biota.