Public health genomics capacity assessment: readiness for large-scale pathogen genomic surveillance in Canada's public health laboratories.

BACKGROUND: Along with rapid diagnostic testing, contact tracing, and public health measures, an effective pandemic response incorporates genomics-based surveillance. Large-scale SARS-CoV-2 genome sequencing is a crucial component of the global response to COVID-19. Characterizing the state of genomics readiness among Canada's public health laboratories was necessary to inform strategic planning and deployment of capacity-building resources in the early stages of the pandemic. METHODS: We used a qualitative study design and focus group discussions, encompassing both technical and leadership perspectives, to perform an in-depth evaluation of the state of pathogen genomics readiness in Canada. RESULTS: We found substantial diversity in the state of readiness for SARS-CoV-2 genomic surveillance across Canada. Despite this variability, we identified common barriers and needs in the areas of specimen access, data flow and sharing, computing infrastructure, and access to highly qualified bioinformatics personnel. CONCLUSIONS: These findings enable the strategic prioritization and deployment of resources to increase Canada's ability to perform effective public health genomic surveillance for COVID-19 and prepare for future emerging infectious diseases. They also provide a unique qualitative research model for use in capacity building.

Unusual Legionnaires' outbreak in cool, dry Western Canada: an investigation using genomic epidemiology.

An outbreak of Legionnaires' disease occurred in an inner city district in Calgary, Canada. This outbreak spanned a 3-week period in November-December 2012, and a total of eight cases were identified. Four of these cases were critically ill requiring intensive care admission but there was no associated mortality. All cases tested positive for Legionella pneumophila serogroup 1 (LP1) by urinary antigen testing. Five of the eight patients were culture positive for LP1 from respiratory specimens. These isolates were further identified as Knoxville monoclonal subtype and sequence subtype ST222. Whole-genome sequencing revealed that the isolates differed by no more than a single vertically acquired single nucleotide variant, supporting a single point-source outbreak. Hypothesis-based environmental investigation and sampling was conducted; however, a definitive source was not identified. Geomapping of case movements within the affected urban sector revealed a 1·0 km common area of potential exposure, which coincided with multiple active construction sites that used water spray to minimize transient dust. This community point-source Legionnaires' disease outbreak is unique due to its ST222 subtype and occurrence in a relatively dry and cold weather setting in Western Canada. This report suggests community outbreaks of Legionella should not be overlooked as a possibility during late autumn and winter months in the Northern Hemisphere.

Targeted 16S rRNA high-throughput sequencing to characterize microbial communities during composting of livestock mortalities.

AIM: A comprehensive understanding of the microbial community is necessary to ensure a significant reduction in pathogens during the composting process. METHODS AND RESULTS: Two biosecure, static composting systems containing cattle mortalities were constructed at subzero temperatures. Temperature at each sampling site was measured continuously and samples were grouped as either ≤50 or ≥55°C, based on temperature exposure required for effective pathogen inactivation during composting. High-throughput 454 sequencing was used to characterize the bacterial communities within each sample. Clustering of bacterial communities was observed according to temperature. However, neither richness nor diversity differed between temperature groups. Firmicutes was the most abundant phylum within both temperature groups but was more pronounced (63·6%) in samples ≥55°C (P < 0·05). Similarly, members of Clostridia, Clostridium sensu stricto (3·64%), Clostridium XI (0·59%), UF (Clostridiaceae 1) (5·29%) and UF (Clostridiales Incertae Sedis XI) (6·20%), were prominent at ≥55°C (P < 0·05), likely a reflection of spore survival and/or anaerobic microenvironments within passively aerated compost piles. Members of Thermobifida (3·54%), UO (Actinomycetales) (12·29%) and UO (Bacillales) (19·49%) were also prominent at ≥55°C (P < 0·05). CONCLUSION: Substantial spatial diversity exists within bacterial communities in field-scale compost piles. Localized temperature at the site of sampling may be one of the factors contributing to this phenomenon. SIGNIFICANCE AND IMPACT OF THE STUDY: This is the first study to describe the microbial community profile with the use of targeted 16S rRNA high-throughput sequencing in passively aerated composted livestock mortalities.

Spatial autocorrelation and the scaling of species-environment relationships.

Issues of residual spatial autocorrelation (RSA) and spatial scale are critical to the study of species-environment relationships, because RSA invalidates many statistical procedures, while the scale of analysis affects the quantification of these relationships. Although these issues independently are widely covered in the literature, only sparse attention is given to their integration. This paper focuses on the interplay between RSA and the spatial scaling of species-environment relationships. Using a hypothetical species in an artificial landscape, we show that a mismatch between the scale of analysis and the scale of a species' response to its environment leads to a decrease in the portion of variation explained by environmental predictors. Moreover, it results in RSA and biased regression coefficients. This bias stems from error-predictor dependencies due to the scale mismatch, the magnitude of which depends on the interaction between the scale of landscape heterogeneity and the scale of a species' response to this heterogeneity. We show that explicitly considering scale effects on RSA can reveal the characteristic scale of a species' response to its environment. This is important, because the estimation of species-environment relationships using spatial regression methods proves to be erroneous in case of a scale mismatch, leading to spurious conclusions when scaling issues are not explicitly considered. The findings presented here highlight the importance of examining the appropriateness of the spatial scales used in analyses, since scale mismatches affect the rigor of statistical analyses and thereby the ability to understand the processes underlying spatial patterning in ecological phenomena.