Genome sequencing has been widely deployed to study the evolution of SARS-CoV-2 with more than 90,000 genome sequences uploaded to the GISAID database. We published a method for SARS-CoV-2 genome sequencing ( https://www.protocols.io/view/ncov-2019-sequencing-protocol-bbmuik6w ) online on January 22, 2020. This approach has rapidly become the most popular method for sequencing SARS-CoV-2 due to its simplicity and cost-effectiveness. Here we present improvements to the original protocol: i) an updated primer scheme with 22 additional primers to improve genome coverage, ii) a streamlined library preparation workflow which improves demultiplexing rate for up to 96 samples and reduces hands-on time by several hours and iii) cost savings which bring the reagent cost down to £10 per sample making it practical for individual labs to sequence thousands of SARS-CoV-2 genomes to support national and international genomic epidemiology efforts.

Studies of environmental microbiota typically target only specific groups of microorganisms, with most focusing on bacteria through taxonomic classification of 16S rRNA gene sequences. For a more holistic understanding of a microbiome, a strategy to characterize the viral, bacterial, and eukaryotic components is necessary. We developed a method for metagenomic and amplicon-based analysis of freshwater samples involving the concentration and size-based separation of eukaryotic, bacterial, and viral fractions. Next-generation sequencing and culture-independent approaches were used to describe and quantify microbial communities in watersheds with different land use in British Columbia. Deep amplicon sequencing was used to investigate the distribution of certain viruses (g23 and RdRp), bacteria (16S rRNA and cpn60), and eukaryotes (18S rRNA and ITS). Metagenomic sequencing was used to further characterize the gene content of the bacterial and viral fractions at both taxonomic and functional levels. This study provides a systematic approach to separate and characterize eukaryotic-, bacterial-, and viral-sized particles. Methodologies described in this research have been applied in temporal and spatial studies to study the impact of land use on watershed microbiomes in British Columbia.

Giardia duodenalis causes large numbers of gastrointestinal illness in humans. Its transmission through the contaminated surface water/wildlife intersect is significant, and the water-dwelling rodents beavers have been implicated as one important reservoir. To trace human infections to their source, we used genome techniques to characterize genetic relationships among 89 Giardia isolates from surface water, humans, and animals. Our study showed the presence of two previously described genetic assemblages, A and B, with mixed infections detected from isolates collected during outbreaks. Study findings also showed that while assemblage A could be divided into A1 and A2, A1 showed little genetic variation among animal and human hosts in isolates collected from across the globe. Assemblage B, the most common type found in the study surface water samples, was shown to be highly variable. Our study demonstrates that the beaver is a possible source of human infections from contaminated surface water, while acknowledging that theirs is only one role in the complex cycle of zoonotic spread. Mixes of parasite groups have been detected in waterborne outbreaks. More information on Giardia diversity and its evolution using genomics will further the understanding of the epidemiology of spread of this disease-causing protozoan.

Knowledge of host specificity, combined with genomic sequencing of Giardia and Cryptosporidium spp., has demonstrated a microbial source tracking (MST) utility for these common waterborne microbes. To explore the source attribution potential of these pathogens, water samples were collected in a mixed rural-urban watershed in the Township of Langley, in southwestern British Columbia (BC), Canada, over a 2-year period. Cryptosporidium was detected in 63% of surface water samples at concentrations ranging from no positive detection (NPD) to 20,600 oocysts per 100 liters. Giardia was detected in 86% of surface water samples at concentrations ranging from NPD to 3,800 cysts per 100 liters of water. Sequencing at the 18S rRNA locus revealed that 50% of Cryptosporidium samples and 98% of Giardia samples contained species/genotypes ( Cryptosporidium ) or assemblages ( Giardia ) that are capable of infecting humans, based on current knowledge of host specificity and taxonomy. Cryptosporidium genotyping data were more promising for source tracking potential, due to the greater number of host-adapted (i.e., narrow-host-range) species/genotypes compared to Giardia , since 98% of Giardia isolates were zoonotic and the potential host could not be predicted. This report highlights the benefits of parasite genomic sequencing to complement Method 1623 (U.S. Environmental Protection Agency) and shows that Cryptosporidium subtyping for MST purposes is superior to the use of Giardia subtyping, based on better detection limits for Cryptosporidium -positive samples than for Giardia -positive samples and on greater host specificity among Cryptosporidium species. These additional tools could be used for risk assessment in public health and watershed management decisions.

Giardiais the most common parasitic cause of gastrointestinal infections worldwide, with transmission through surface water playing an important role in various parts of the world.Giardia duodenalis(synonyms:G. intestinalisandG. lamblia), a multispecies complex, has two zoonotic subtypes, assemblages A and B. When British Columbia (BC), a western Canadian province, experienced several waterborne giardiasis outbreaks due to unfiltered surface drinking water in the late 1980s, collection of isolates from surface water, as well as from humans and beavers (Castor canadensis), throughout the province was carried out. To better understandGiardiain surface water, 71 isolates, including 29 from raw surface water samples, 29 from human giardiasis cases, and 13 from beavers in watersheds from this historical library were characterized by PCR. Study isolates also included isolates from waterborne giardiasis outbreaks. Both assemblages A and B were identified in surface water, human, and beavers samples, including a mixture of both assemblages A and B in waterborne outbreaks. PCR results were confirmed by whole-genome sequencing (WGS) for one waterborne outbreak and supported the clustering of human, water, and beaver isolates within both assemblages. We concluded that contamination of surface water byGiardiais complex, that the majority of our surface water isolates were assemblage B, and that both assemblages A and B may cause waterborne outbreaks. The higher-resolution data provided by WGS warrants further study to better understand the spread ofGiardia.

This study identified factors associated with hospital admission among people with laboratory-diagnosed COVID-19 cases in British Columbia. The study used data from the BC COVID-19 Cohort, which integrates data on all COVID-19 cases with data on hospitalizations, medical visits, emergency room visits, prescription drugs, chronic conditions and deaths. The analysis included all laboratory-diagnosed COVID-19 cases in British Columbia to 15 January 2021. We evaluated factors associated with hospital admission using multivariable Poisson regression analysis with robust error variance. Of the 56,874 COVID-19 cases included in the analysis, 2298 were hospitalized. Factors associated with increased hospitalization risk were as follows: male sex (adjusted risk ratio (aRR) = 1.27; 95% CI = 1.17–1.37), older age (p-trend < 0.0001 across age groups increasing hospitalization risk with increasing age [aRR 30–39 years = 3.06; 95% CI = 2.32–4.03, to aRR 80+ years = 43.68; 95% CI = 33.41–57.10 compared to 20–29 years-old]), asthma (aRR = 1.15; 95% CI = 1.04–1.26), cancer (aRR = 1.19; 95% CI = 1.09–1.29), chronic kidney disease (aRR = 1.32; 95% CI = 1.19–1.47), diabetes (treated without insulin aRR = 1.13; 95% CI = 1.03–1.25, requiring insulin aRR = 5.05; 95% CI = 4.43–5.76), hypertension (aRR = 1.19; 95% CI = 1.08–1.31), injection drug use (aRR = 2.51; 95% CI = 2.14–2.95), intellectual and developmental disabilities (aRR = 1.67; 95% CI = 1.05–2.66), problematic alcohol use (aRR = 1.63; 95% CI = 1.43–1.85), immunosuppression (aRR = 1.29; 95% CI = 1.09–1.53), and schizophrenia and psychotic disorders (aRR = 1.49; 95% CI = 1.23–1.82). In an analysis restricted to women of reproductive age, pregnancy (aRR = 2.69; 95% CI = 1.42–5.07) was associated with increased risk of hospital admission. Older age, male sex, substance use, intellectual and developmental disability, chronic comorbidities, and pregnancy increase the risk of COVID-19-related hospitalization.