Hypoxia influences polysome distribution of human ribosomal protein S12 and alternative splicing of ribosomal protein mRNAs.

Ribosomes were once considered static in their composition because of their essential role in protein synthesis and kingdom-wide conservation. The existence of tolerated mutations in select ribosomal proteins (RPs), such as in Diamond-Blackfan anemia, is evidence that not all ribosome components are essential. Heterogeneity in the protein composition of eukaryotic ribosomes is an emerging concept with evidence that different pools of ribosomes exist with transcript-specificity. Here, we show that the polysome association of ribosomal proteins is altered by low oxygen (hypoxia), a feature of the tumor microenvironment, in human cells. We quantified ribosomal protein abundance in actively translating polysomes of normoxic and hypoxic HEK293 cells by tandem mass tags mass spectrometry. Our data suggest that RPS12 (eS12) is enriched in hypoxic monosomes, which increases the heavy polysome association of structured transcripts APAF-1 and XIAP. Furthermore, hypoxia induced five alternative splicing events within a subset of RP mRNAs in cell lines. One of these events in RPS24 (eS24 protein) alters the coding sequence to produce two protein isoforms that can incorporate into ribosomes. This splicing event is greatly induced in spheroids and correlates with tumor hypoxia in human prostate cancer. Our data suggest that hypoxia may influence the composition of the human ribosome through changes in RP incorporation and the production of hypoxia-specific RP isoforms.

Estimating the test-adjusted incidence of Chlamydia trachomatis infections identified through Public Health Ontario Laboratories in Peel region, Ontario, 2010-2018: a population-based study.

BACKGROUND: Public health guidelines for chlamydia testing are not sex specific, but young females test at a disproportionally higher rate than males and other age groups. This study aims to describe testing trends across age and sex subgroups, then estimate a test-adjusted incidence of chlamydia in these subgroups to identify gaps in current testing practices. METHODS: We used a population-based study to examine observed chlamydia rates by age and sex subgroups: 15-19 years, 20-29 years, 30-39 years and older than 40 years. The study included diagnostic test results recorded by Public Health Ontario Laboratories between Jan. 1, 2010, and Dec. 31, 2018, for individuals living in Peel region, Ontario. We then employed meta-regression models as a method of standardization to estimate the effect of sex and age on standardized morbidity ratio, testing ratio and test positivity, then calculate a test-adjusted incidence of chlamydia for each subgroup. RESULTS: Over the study period, infection, testing and test positivity varied across age and sex subgroups. Observed incidence and testing were highest in females aged 20-29 years, whereas males had the highest standardized test positivity across all age groups. After estimating test-adjusted incidence for each age-sex subgroup, males in the 15-19-year and 30-39-year age groups had an increase in incidence of 60.2% and 9.7%, respectively, compared with the observed incidence. INTERPRETATION: We found that estimated test-adjusted incidence was higher than observed incidence in males aged 15-19 years and 30-39 years. This suggests that infections in males are likely being missed owing to differential testing, and this may be contributing to the persistent increase in reported cases in Canada. Public health programming that targets males, especially in high-risk settings and communities, and use of innovative partner notification methods could be critical to curbing overall rates of chlamydia.

Sporadic SARS-CoV-2 cases at the neighbourhood level in Toronto, Ontario, 2020: a spatial analysis of the early pandemic period.

BACKGROUND: As the largest city in Canada, Toronto has played an important role in the dynamics of SARS-CoV-2 transmission in Ontario, and the burden of disease across Toronto neighbourhoods has shown considerable heterogeneity. The purpose of this study was to investigate the spatial variation of sporadic SARS-CoV-2 cases in Toronto neighbourhoods by detecting clusters of increased risk and investigating effects of neighbourhood-level risk factors on rates. METHODS: Data on sporadic SARS-CoV-2 cases, at the neighbourhood level, for Jan. 25 to Nov. 26, 2020, were obtained from the City of Toronto COVID-19 dashboard. We used a flexibly shaped spatial scan to detect clusters of increased risk of sporadic COVID-19. We then used a generalized linear geostatistical model to investigate whether average household size, population density, dependency ratio and prevalence of low-income households were associated with sporadic SARS-CoV-2 rates. RESULTS: We identified 3 clusters of elevated risk of SARS-CoV-2 infection, with standardized morbidity ratios ranging from 1.59 to 2.43. The generalized linear geostatistical model found that average household size (relative risk [RR] 2.17, 95% confidence interval [CI] 1.80-2.61) and percentage of low-income households (RR 1.03, 95% CI 1.02-1.04) were significant predictors of sporadic SARS-CoV-2 cases at the neighbourhood level. INTERPRETATION: During the study period, 3 clusters of increased risk of sporadic SARS-CoV-2 infection were identified, and average household size and percentage of low-income households were found to be associated with sporadic SARS-CoV-2 rates at the neighbourhood level. The findings of this study can be used to target resources and create policy to address inequities that are shown through heterogeneity of SARS-CoV-2 cases at the neighbourhood level in Toronto, Ontario.

A sub-national real-time epidemiological and vaccination database for the COVID-19 pandemic in Canada.

The COVID-19 pandemic has demonstrated the need for real-time, open-access epidemiological information to inform public health decision-making and outbreak control efforts. In Canada, authority for healthcare delivery primarily lies at the provincial and territorial level; however, at the outset of the pandemic no definitive pan-Canadian COVID-19 datasets were available. The COVID-19 Canada Open Data Working Group was created to fill this crucial data gap. As a team of volunteer contributors, we collect daily COVID-19 data from a variety of governmental and non-governmental sources and curate a line-list of cases and mortality for all provinces and territories of Canada, including information on location, age, sex, travel history, and exposure, where available. We also curate time series of COVID-19 recoveries, testing, and vaccine doses administered and distributed. Data are recorded systematically at a fine sub-national scale, which can be used to support robust understanding of COVID-19 hotspots. We continue to maintain this dataset, and an accompanying online dashboard, to provide a reliable pan-Canadian COVID-19 resource to researchers, journalists, and the general public.