Systematic assessment of long-read RNA-seq methods for transcript identification and quantification.

The Long-read RNA-Seq Genome Annotation Assessment Project Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. Using different protocols and sequencing platforms, the consortium generated over 427 million long-read sequences from complementary DNA and direct RNA datasets, encompassing human, mouse and manatee species. Developers utilized these data to address challenges in transcript isoform detection, quantification and de novo transcript detection. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. Incorporating additional orthogonal data and replicate samples is advised when aiming to detect rare and novel transcripts or using reference-free approaches. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.

Genotyping Plasmodium falciparum gametocytes using amplicon deep sequencing.

BACKGROUND: Understanding the dynamics of gametocyte production in polyclonal Plasmodium falciparum infections requires a genotyping method that detects distinct gametocyte clones and estimates their relative frequencies. Here, a marker was identified and evaluated to genotype P. falciparum mature gametocytes using amplicon deep sequencing. METHODS: A data set of polymorphic regions of the P. falciparum genome was mined to identify a gametocyte genotyping marker. To assess marker resolution, the number of unique haplotypes in the marker region was estimated from 95 Malawian P. falciparum whole genome sequences. Specificity of the marker for detection of mature gametocytes was evaluated using reverse transcription-polymerase chain reaction of RNA extracted from NF54 mature gametocytes and rings from a non-gametocyte-producing strain of P. falciparum. Amplicon deep sequencing was performed on experimental mixtures of mature gametocytes from two distinct parasite clones, as well as gametocyte-positive P. falciparum field isolates to evaluate the quantitative ability and determine the limit of detection of the genotyping approach. RESULTS: A 400 bp region of the pfs230 gene was identified as a gametocyte genotyping marker. A larger number of unique haplotypes was observed at the pfs230 marker (34) compared to the sera-2 (18) and ama-1 (14) markers in field isolates from Malawi. RNA and DNA genotyping accurately estimated gametocyte and total parasite clone frequencies when evaluating agreement between expected and observed haplotype frequencies in gametocyte mixtures, with concordance correlation coefficients of 0.97 [95% CI: 0.92-0.99] and 0.92 [95% CI: 0.83-0.97], respectively. The detection limit of the genotyping method for male gametocytes was 0.41 pfmget transcripts/µl [95% CI: 0.28-0.72] and for female gametocytes was 1.98 ccp4 transcripts/µl [95% CI: 1.35-3.68]. CONCLUSIONS: A region of the pfs230 gene was identified as a marker to genotype P. falciparum gametocytes. Amplicon deep sequencing of this marker can be used to estimate the number and relative frequency of parasite clones among mature gametocytes within P. falciparum infections. This gametocyte genotyping marker will be an important tool for studies aimed at understanding dynamics of gametocyte production in polyclonal P. falciparum infections.

Positive-unlabeled learning identifies vaccine candidate antigens in the malaria parasite Plasmodium falciparum.

Malaria vaccine development is hampered by extensive antigenic variation and complex life stages of Plasmodium species. Vaccine development has focused on a small number of antigens, many of which were identified without utilizing systematic genome-level approaches. In this study, we implement a machine learning-based reverse vaccinology approach to predict potential new malaria vaccine candidate antigens. We assemble and analyze P. falciparum proteomic, structural, functional, immunological, genomic, and transcriptomic data, and use positive-unlabeled learning to predict potential antigens based on the properties of known antigens and remaining proteins. We prioritize candidate antigens based on model performance on reference antigens with different genetic diversity and quantify the protein properties that contribute most to identifying top candidates. Candidate antigens are characterized by gene essentiality, gene ontology, and gene expression in different life stages to inform future vaccine development. This approach provides a framework for identifying and prioritizing candidate vaccine antigens for a broad range of pathogens.

A meta-analysis of the carcinogenic effects of particulate matter and polycyclic aromatic hydrocarbons.

Urbanization has numerous benefits to human society, but some aspects of urban environments, such as air pollution, can negatively affect human health. Two major air pollutants, particulate matter (PM) and polycyclic aromatic hydrocarbons (PAH), have been classified as carcinogens by the International Agency for Research on Cancer. Here, we answer two questions: (1) What are the carcinogenic effects of PM and PAH exposure? (2) How does carcinogenic risk vary across geographical regions? We performed a comprehensive literature search of peer-reviewed published studies examining the link between air pollution and human cancer rates. Focusing on studies published since 2014 when the last IARC monograph on air pollution was published, we converted the extracted data into relative risks and performed subgroup analyses. Exposure to PM2.5 (per 10 µg/m3) resulted in an 8.5% increase in cancer incidence when all cancer types were combined, and risk for individual cancer types (i.e. lung cancer and adenocarcinoma) was also elevated. PM2.5 was also associated with 2.5% higher mortality due to cancer when all types of cancer were combined, and for individual cancer types (i.e., lung and breast cancer). Exposure to PM2.5 and PM10 posed the greatest risk to lung cancer incidence and mortality in Europe (PM2.5 RR 2.15; PM10 RR 1.26); the risk in Asia and the Americas was also elevated. Exposure to PAH and benzo[a]pyrene significantly increased the pooled risk of cancer incidence (10.8% and 8.0% respectively) at the highest percentile of exposure concentration. Our meta-analyses of studies over the past decade shows that urban air pollution in the form of PM2.5, PM10, and PAH all elevate the incidence and mortality of cancer. We discuss the possible mechanisms of carcinogenesis of PM and PAH. These results support World Health Organization's conclusion that air pollution poses among the greatest health risks to humans living in cities.

Cost-benefit analysis of ecosystem modeling to support fisheries management.

Mathematical and statistical models underlie many of the world's most important fisheries management decisions. Since the 19th century, difficulty calibrating and fitting such models has been used to justify the selection of simple, stationary, single-species models to aid tactical fisheries management decisions. Whereas these justifications are reasonable, it is imperative that we quantify the value of different levels of model complexity for supporting fisheries management, especially given a changing climate, where old methodologies may no longer perform as well as in the past. Here we argue that cost-benefit analysis is an ideal lens to assess the value of model complexity in fisheries management. While some studies have reported the benefits of model complexity in fisheries, modeling costs are rarely considered. In the absence of cost data in the literature, we report, as a starting point, relative costs of single-species stock assessment and marine ecosystem models from two Australian organizations. We found that costs varied by two orders of magnitude, and that ecosystem model costs increased with model complexity. Using these costs, we walk through a hypothetical example of cost-benefit analysis. The demonstration is intended to catalyze the reporting of modeling costs and benefits.

Landscapes of inequities, structural racism, and disease during the COVID-19 pandemic: Experiences of immigrant and racialized populations in Canada.

The COVID-19 pandemic has disproportionately affected immigrant and racialized communities globally and revealed another public health crisis - structural racism. While structural racism is known to foster discrimination via mutually reinforcing systems, the unevenness of COVID-19 infections, hospitalizations, and deaths across societies has precipitated attention to the impacts of structural racism. Research highlights the inequitable burden of COVID-19 among immigrant and racialized groups; however, little is known about the synergistic impacts of structural racism and COVID-19 on the health and wellbeing of these groups. Fewer studies examine how structural racism and COVID-19 intersect within neighbourhoods to co-produce landscapes of disease exposure and management. This article examines the pathways through which structural racism shapes access, use, and control of environmental resources among immigrant and racialized individuals in the neighbourhoods of the Peel Region and how they converged to shape health and disease dynamics during the height of Canada's COVID-19 pandemic. Findings from in-depth interviews reveal that mutually reinforcing inequitable systems created environments for COVID-19 to reinscribe disparities in access, use, and control of key resources needed to manage health and disease, and created new forms of disparities and landscapes of inequality for immigrants and racialized individuals. We close with a discussion on the impacts for policy and practice.

Heterogeneity in the prevalence of subclinical malaria, other co-infections and anemia among pregnant women in rural areas of Myanmar: a community-based longitudinal study.

BACKGROUND: Due to the low prevalence of clinically suspected malaria among pregnant women in Myanmar, little is known about its impact on mothers and newborns. Helminth and Human Immuno-deficiency Virus (HIV) co-infections cause anemia in pregnant women. This study assessed the prevalence of subclinical malaria and co-infections among pregnant women, and its association with adverse outcomes of pregnancy in the presence of infection. METHODS: A prospective longitudinal study was conducted in 12 villages in two townships in Myanmar between 2013 to 2015. A total of 752 pregnant women, with a mean age of 27 years, were enrolled and followed up once a month until six weeks after childbirth. Prevalence ratio was calculated in the multivariable analysis. RESULTS: The prevalence of subclinical malaria as measured by nested PCR was 5.7% for either P. falciparum or P. vivax, 2.7% prevalence of P. falciparum and 2.8% prevalence of P. vivax. Helminth infections were prevalent in 17% of women, and one woman with an HIV infection was found in our study. The burden of anemia was high, with an overall prevalence of 37% with or without helminth infection, 42% of the women were malaria positive and 43% had dual infections (both malaria and helminth). Only 11 abnormal pregnancy outcomes (7 stillbirths, 2 premature, 2 twins) were identified. Poisson regression showed that women in their first trimester had a 2.9 times higher rate of subclinical malaria compared to women in the third trimester (PR:2.9, 95%CI 1.19, 7.31, p = 0.019), women who were enrolled during the wet season were 2.5 times more likely to be malaria positive than the women enrolled in the dry season (PR: 2.5, 95%CI 1.27, 4.88, p = 0.008), and the malaria positivity rate decreased by 5% when increased in one year of woman's age (PR:0.95, 95%CI 0.91, 0.99, p = 0.02). In the multivariable regression, the age of respondents was the only significant factor associated with subclinical malaria in pregnancy. CONCLUSIONS: A comprehensive approach of integrating interventions for malaria, anemia, and helminths should be delivered during antenatal care services for pregnant women in rural areas of Myanmar.

Unlocking ensemble ecosystem modelling for large and complex networks.

The potential effects of conservation actions on threatened species can be predicted using ensemble ecosystem models by forecasting populations with and without intervention. These model ensembles commonly assume stable coexistence of species in the absence of available data. However, existing ensemble-generation methods become computationally inefficient as the size of the ecosystem network increases, preventing larger networks from being studied. We present a novel sequential Monte Carlo sampling approach for ensemble generation that is orders of magnitude faster than existing approaches. We demonstrate that the methods produce equivalent parameter inferences, model predictions, and tightly constrained parameter combinations using a novel sensitivity analysis method. For one case study, we demonstrate a speed-up from 108 days to 6 hours, while maintaining equivalent ensembles. Additionally, we demonstrate how to identify the parameter combinations that strongly drive feasibility and stability, drawing ecological insight from the ensembles. Now, for the first time, larger and more realistic networks can be practically simulated and analysed.

Generation and analysis of a mouse multi-tissue genome annotation atlas.

Generating an accurate and complete genome annotation for an organism is complex because the cells within each tissue can express a unique set of transcript isoforms from a unique set of genes. A comprehensive genome annotation should contain information on what tissues express what transcript isoforms at what level. This tissue-level isoform information can then inform a wide range of research questions as well as experiment designs. Long-read sequencing technology combined with advanced full-length cDNA library preparation methods has now achieved throughput and accuracy where generating these types of annotations is achievable. Here, we show this by generating a genome annotation of the mouse (Mus musculus). We used the nanopore-based R2C2 long-read sequencing method to generate 64 million highly accurate full length cDNA consensus reads - averaging 5.4 million reads per tissue for a dozen tissues. Using the Mandalorion tool we processed these reads to generate the Tissue-level Atlas of Mouse Isoforms (TAMI - available at https://genome.ucsc.edu/s/vollmers/TAMI) which we believe will be a valuable complement to conventional, manually curated reference genome annotations.

Natural immunity to malaria preferentially targets the endothelial protein C receptor-binding regions of PfEMP1s.

Antibody responses to variant surface antigens (VSAs) produced by the malaria parasite Plasmodium falciparum may contribute to age-related natural immunity to severe malaria. One VSA family, P. falciparum erythrocyte membrane protein-1 (PfEMP1), includes a subset of proteins that binds endothelial protein C receptor (EPCR) in human hosts and potentially disrupts the regulation of inflammatory responses, which may lead to the development of severe malaria. We probed peptide microarrays containing segments spanning five PfEMP1 EPCR-binding domain variants with sera from 10 Malian adults and 10 children to determine the differences between adult and pediatric immune responses. We defined serorecognized peptides and amino acid residues as those that elicited a significantly higher antibody response than malaria-naïve controls. We aimed to identify regions consistently serorecognized among adults but not among children across PfEMP1 variants, potentially indicating regions that drive the development of immunity to severe malaria. Adult sera consistently demonstrated broader and more intense serologic responses to constitutive PfEMP1 peptides than pediatric sera, including peptides in EPCR-binding domains. Both adults and children serorecognized a significantly higher proportion of EPCR-binding peptides than peptides that do not directly participate in receptor binding, indicating a preferential development of serologic responses at functional residues. Over the course of a single malaria transmission season, pediatric serological responses increased between the start and the peak of the season, but waned as the transmission season ended. IMPORTANCE Severe malaria and death related to malaria disproportionately affect sub-Saharan children under 5 years of age, commonly manifesting as cerebral malaria and/or severe malarial anemia. In contrast, adults in malaria-endemic regions tend to experience asymptomatic or mild disease. Our findings indicate that natural immunity to malaria targets specific regions within the EPCR-binding domain, particularly peptides containing EPCR-binding residues. Epitopes containing these residues may be promising targets for vaccines or therapeutics directed against severe malaria. Our approach provides insight into the development of natural immunity to a binding target linked to severe malaria by characterizing an "adult-like" response as recognizing a proportion of epitopes within the PfEMP1 protein, particularly regions that mediate EPCR binding. This "adult-like" response likely requires multiple years of malaria exposure, as increases in pediatric serologic response over a single malaria transmission season do not appear significant.

Quantifying the role of photoacclimation and self-facilitation for seagrass resilience to light deprivation.

Introduction: Light gradients are ubiquitous in marine systems as light reduces exponentially with depth. Seagrasses have a set of mechanisms that help them to cope with light stress gradients. Physiological photoacclimation and clonal integration help to maximize light capture and minimize carbon losses. These mechanisms can shape plants minimum light requirements (MLR), which establish critical thresholds for seagrass survival and help us predict ecosystem responses to the alarming reduction in light availability. Methods: Using the seagrass Cymodocea nodosa as a case study, we compare the MLR under different carbon model scenarios, which include photoacclimation and/or self-facilitation (based on clonal integration) and that where parameterized with values from field experiments. Results: Physiological photoacclimation conferred plants with increased tolerance to reducing light, approximately halving their MLR from 5-6% surface irradiance (SI) to ≈ 3% SI. In oligotrophic waters, this change in MLR could translate to an increase of several meters in their depth colonization limit. In addition, we show that reduced mortality rates derived from self-facilitation mechanisms (promoted by high biomass) induce bistability of seagrass meadows along the light stress gradient, leading to abrupt shifts and hysteretic behaviors at their deep limit. Discussion: The results from our models point to (i) the critical role of physiological photoacclimation in conferring greater resistance and ability to recover (i.e., resilience), to seagrasses facing light deprivation and (ii) the importance of self-facilitating reinforcing mechanisms in driving the resilience and recovery of seagrass systems exposed to severe light reduction events.

Systematic assessment of long-read RNA-seq methods for transcript identification and quantification.

The Long-read RNA-Seq Genome Annotation Assessment Project (LRGASP) Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. The consortium generated over 427 million long-read sequences from cDNA and direct RNA datasets, encompassing human, mouse, and manatee species, using different protocols and sequencing platforms. These data were utilized by developers to address challenges in transcript isoform detection and quantification, as well as de novo transcript isoform identification. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. When aiming to detect rare and novel transcripts or when using reference-free approaches, incorporating additional orthogonal data and replicate samples are advised. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.

Identifying and quantifying isoforms from accurate full-length transcriptome sequencing reads with Mandalorion.

In this manuscript, we introduce and benchmark Mandalorion v4.1 for the identification and quantification of full-length transcriptome sequencing reads. It further improves upon the already strong performance of Mandalorion v3.6 used in the LRGASP consortium challenge. By processing real and simulated data, we show three main features of Mandalorion: first, Mandalorion-based isoform identification has very high precision and maintains high recall even in the absence of any genome annotation. Second, isoform read counts as quantified by Mandalorion show a high correlation with simulated read counts. Third, isoforms identified by Mandalorion closely reflect the full-length transcriptome sequencing data sets they are based on.

Follow the Wax: The Natural Protection of the Ear Canal and Its Biome.

The external canal is a unique environment that has an elaborate mechanism for self-cleaning and protection. The fundamental basis of this is the epithelial migration of the desquamating layers of the keratinizing epithelium that lines the entire canal and ear drum. This migratory movement results in a "conveyor belt" effect where the dead skin is moved out of the bony ear canal to the cartilaginous portion, where it is lifted off with the help of glandular skin secretions and the hairs of the canal to form what we call "ear wax." The ear wax has numerous protective properties and is essential to the health of the external ear. The protective properties are due to chemical properties of the wax, in addition to intrinsic chemical secretions by the sebaceous and cerumen apocrine glands. The protection also comes from a diverse population of organisms that exist in the external ear that are usually saprophytic, commensal, and symbiotic, but in some cases, they can become parasitic and pathologic. Detection and quantification of the members of this biome has been difficult, and their overall role in the normal biome of the ear and their transition into pathogens remain an area of active research and investigation.

Are at-risk sociodemographic attributes stable across COVID-19 transmission waves?

COVID-19 health impacts and risks have been disproportionate across social, economic, and racial gradients (Chen et al., 2021; Thompson et al., 2021; Mamuji et al., 2021; COVID-19 and Ethnicity, 2020). By examining the first five waves of the pandemic in Ontario, we identify if Forward Sortation Area (FSAs)based measures of sociodemographic status and their relationship to COVID-19 cases are stable or vary by time. COVID-19 waves were defined using a time-series graph of COVID-19 case counts by epi-week. Percent Black visible minority, percent Southeast Asian visible minority and percent Chinese visible minority at the FSA level were then integrated into spatial error models with other established vulnerability characteristics. The models indicate that area-based sociodemographic patterns associated with COVID-19 infection change over time. If sociodemographic characteristics are identified as high risk (increased COVID-19 case rates) increased testing, public health messaging, and other preventative care may be implemented to protect populations from the inequitable burden of disease.

Validating the Perceived Active School Travel Enablers and Barriers-Parent (PASTEB-P) Questionnaire to Support Intervention Programming and Research.

A child's ability to participate in active school travel (AST) is complicated by several factors. Of particular note are parental controls, which are informed by their perceptions of the local built and social environments, assessments of their child's skills, and convenience preferences, among other considerations. However, there is currently a lack of AST-specific scales that include validated parental perception measures related to such notable barriers and enablers, or those that tend to frame their AST decision-making processes. Framed within the social-ecological model of health behaviour, the aims of the present paper were thus threefold, specifically to (1) outline and test the construct validity of measures delineating parental perceptions of barriers and enablers to AST, (2) evaluate the reliability and consistency of the developed measures, and (3) connect these measures to develop broader constructs for use in the Perceived Active School Travel Enablers and Barriers-Parent (PASTEB-P) questionnaire. To achieve these aims, a mixed-methods approach featuring cognitive interviews and surveys, along with qualitative (thematic analysis) and quantitative (Cohen's Kappa, McDonald's Omega, and confirmatory factor analysis) analyses, was applied across two studies. The validation processes of the two studies resulted in the development of fifteen items comprising seven distinct constructs (barriers: AST Skills, Convenience, Road Safety, Social Safety, and Equipment Storage; enablers: Supportive Environment and Safe Environment) related to parental perceptions of AST. The developed PASTEB-P questionnaire can be used to inform and evaluate AST intervention programming and can be applied for AST research purposes.

Systemic corticosteroids for orbital complications of pediatric rhinosinusitis: A systematic review.

OBJECTIVES: Determine if systemic corticosteroids administration is associated with reduced length of stay, surgical intervention, and abscess formation in pediatric patients with orbital complications of rhinosinusitis. METHODS: Systematic review and meta-analysis were performed utilizing the PubMed and MEDLINE databases to identify articles published between January 1990 and April 2020. Retrospective cohort study of the same patient population over the same time period at our institution. RESULTS: Eight studies, 477 individuals, met criteria for inclusion in the systematic review. 144 patients (30.2%) received systemic corticosteroids, while 333 patients (69.8%) did not. Meta-analyses of frequency of surgical intervention and subperiosteal abscess showed no difference between those who did and did not receive systemic steroids ([OR = 1.06; 95% CI: 0.46 to 2.48] and [OR = 1.08; 95% CI: 0.43 to 2.76], respectively). 6 articles evaluated hospital length of stay (LOS). 3 of these reported enough data to perform meta-analysis, which showed patients with orbital complications who received systemic corticosteroids had shorter mean hospital LOS when compared with those who did not receive systemic steroids (SMD = -2.92, 95% CI: 5.65 to -0.19). CONCLUSION: While available literature was limited, systematic review and meta-analysis suggests systemic corticosteroids decrease length of stay for hospitalized pediatric patients with orbital complications of sinusitis. Further research is needed to more clearly define the role of systemic corticosteroids as an adjunctive treatment.

A New CSRML Structure-Based Fingerprint Method for Profiling and Categorizing Per- and Polyfluoroalkyl Substances (PFAS).

The term PFAS encompasses diverse per- and polyfluorinated alkyl (and increasingly aromatic) chemicals spanning industrial processes, commercial uses, environmental occurrence, and potential concerns. With increased chemical curation, currently exceeding 14,000 structures in the PFASSTRUCTV5 inventory on EPA's CompTox Chemicals Dashboard, has come increased motivation to profile, categorize, and analyze the PFAS structure space using modern cheminformatics approaches. Making use of the publicly available ToxPrint chemotypes and ChemoTyper application, we have developed a new PFAS-specific fingerprint set consisting of 129 TxP_PFAS chemotypes coded in CSRML, a chemical-based XML-query language. These are split into two groups, the first containing 56 mostly bond-type ToxPrints modified to incorporate attachment to either a CF group or F atom to enforce proximity to the fluorinated portion of the chemical. This focus resulted in a dramatic reduction in TxP_PFAS chemotype counts relative to the corresponding ToxPrint counts (averaging 54%). The remaining TxP_PFAS chemotypes consist of various lengths and types of fluorinated chains, rings, and bonding patterns covering indications of branching, alternate halogenation, and fluorotelomers. Both groups of chemotypes are well represented across the PFASSTRUCT inventory. Using the ChemoTyper application, we show how the TxP_PFAS chemotypes can be visualized, filtered, and used to profile the PFASSTRUCT inventory, as well as to construct chemically intuitive, structure-based PFAS categories. Lastly, we used a selection of expert-based PFAS categories from the OECD Global PFAS list to evaluate a small set of analogous structure-based TxP_PFAS categories. TxP_PFAS chemotypes were able to recapitulate the expert-based PFAS category concepts based on clearly defined structure rules that can be computationally implemented and reproducibly applied to process large PFAS inventories without need to consult an expert. The TxP_PFAS chemotypes have the potential to support computational modeling, harmonize PFAS structure-based categories, facilitate communication, and allow for more efficient and chemically informed exploration of PFAS chemicals moving forward.