Collaboration and engagement with decision-makers are needed to reduce evidence complacency in wildlife management

There exists an extensive, diverse, and robust evidence base to support complex decisions that address the planetary biodiversity crisis. However, it is generally not sought or used by environmental decision-makers, who instead draw on intuition, experience, or opinion to inform important decisions. Thus, there is a need to examine evidence exchange processes in wildlife management to understand the multiple inputs to decisions. Here, we adopt a novel approach, fuzzy cognitive mapping (FCM), to examine perceptions of individuals from Indigenous and Western governments on the reliability of evidence which may influence freshwater fisheries management decisions in British Columbia, Canada. We facilitated four FCM workshops participants representing Indigenous or Western regulatory/governance groups of fisheries managers. Our results show that flows of evidence to decision-makers occur within a relatively closed governance network, constrained to the few well-connected decision-making organizations (i.e., wildlife management agencies) and their close partners. This implies that increased collaboration (i.e., knowledge co-production) and engagement (i.e., knowledge brokerage) with wildlife managers and decision-makers are needed to produce actionable evidence and increase evidence exchange.

A Canadian Simulation Model for Major Depressive Disorder: Study Protocol

BACKGROUND

Major depressive disorder (MDD) is a common, often recurrent condition and a significant driver of healthcare costs. People with MDD often receive pharmacological therapy as the first-line treatment, but the majority of people require more than one medication trial to find one that relieves symptoms without causing intolerable side effects. There is an acute need for more effective interventions to improve patients' remission and quality of life and reduce the condition's economic burden on the healthcare system. Pharmacogenomic (PGx) testing could deliver these objectives, using genomic information to guide prescribing decisions. With an already complex and multifaceted care pathway for MDD, future evaluations of new treatment options require a flexible analytic infrastructure encompassing the entire care pathway. Individual-level simulation models are ideally suited for this purpose. We sought to develop an economic simulation model to assess the effectiveness and cost effectiveness of PGx testing for individuals with major depression. Additionally, the model serves as an analytic infrastructure, simulating the entire patient pathway for those with MDD.

METHODS AND ANALYSIS

Key stakeholders, including patient partners, clinical experts, researchers, and modelers, designed and developed a discrete-time microsimulation model of the clinical pathways of adults with MDD in British Columbia (BC), including all publicly-funded treatment options and multiple treatment steps. The Simulation Model of Major Depression (SiMMDep) was coded with a modular approach to enhance flexibility. The model was populated using multiple original data analyses conducted with BC administrative data, a systematic review, and an expert panel. The model accommodates newly diagnosed and prevalent adult patients with MDD in BC, with and without PGx-guided treatment. SiMMDep comprises over 1500 parameters in eight modules: entry cohort, demographics, disease progression, treatment, adverse events, hospitalization, costs and quality-adjusted life-years (payoff), and mortality. The model predicts health outcomes and estimates costs from a health system perspective. In addition, the model can incorporate interactive decision nodes to address different implementation strategies for PGx testing (or other interventions) along the clinical pathway. We conducted various forms of model validation (face, internal, and cross-validity) to ensure the correct functioning and expected results of SiMMDep.

CONCLUSION

SiMMDep is Canada's first medication-specific, discrete-time microsimulation model for the treatment of MDD. With patient partner collaboration guiding its development, it incorporates realistic care journeys. SiMMDep synthesizes existing information and incorporates provincially-specific data to predict the benefits and costs associated with PGx testing. These predictions estimate the effectiveness, cost-effectiveness, resource utilization, and health gains of PGx testing compared with the current standard of care. However, the flexible analytic infrastructure can be adapted to support other policy questions and facilitate the rapid synthesis of new data for a broader search for efficiency improvements in the clinical field of depression.

High-density genetic linkage mapping in Sitka spruce advances the integration of genomic resources in conifers

In species with large and complex genomes such as conifers, dense linkage maps are a useful resource for supporting genome assembly and laying the genomic groundwork at the structural, populational, and functional levels. However, most of the 600+ extant conifer species still lack extensive genotyping resources, which hampers the development of high-density linkage maps. In this study, we developed a linkage map relying on 21,570 single nucleotide polymorphism (SNP) markers in Sitka spruce (Picea sitchensis [Bong.] Carr.), a long-lived conifer from western North America that is widely planted for productive forestry in the British Isles. We used a single-step mapping approach to efficiently combine RAD-seq and genotyping array SNP data for 528 individuals from 2 full-sib families. As expected for spruce taxa, the saturated map contained 12 linkages groups with a total length of 2,142 cM. The positioning of 5,414 unique gene coding sequences allowed us to compare our map with that of other Pinaceae species, which provided evidence for high levels of synteny and gene order conservation in this family. We then developed an integrated map for P. sitchensis and Picea glauca based on 27,052 markers and 11,609 gene sequences. Altogether, these 2 linkage maps, the accompanying catalog of 286,159 SNPs and the genotyping chip developed, herein, open new perspectives for a variety of fundamental and more applied research objectives, such as for the improvement of spruce genome assemblies, or for marker-assisted sustainable management of genetic resources in Sitka spruce and related species.

Exploration of Germline Correlates and Risk of Immune-Related Adverse Events in Advanced Cancer Patients Treated with Immune Checkpoint Inhibitors

Immune checkpoint inhibitors (ICIs) are increasingly used in the treatment of many tumor types, and durable responses can be observed in select populations. However, patients may exhibit significant immune-related adverse events (irAEs) that may lead to morbidity. There is limited information on whether the presence of specific germline mutations may highlight those at elevated risk of irAEs. We evaluated 117 patients with metastatic solid tumors or hematologic malignancies who underwent genomic analysis through the ongoing Personalized OncoGenomics (POG) program at BC Cancer and received an ICI during their treatment history. Charts were reviewed for irAEs. Whole genome sequencing of a fresh biopsy and matched normal specimens (blood) was performed at the time of POG enrollment. Notably, we found that MHC class I alleles in the HLA-B27 family, which have been previously associated with autoimmune conditions, were associated with grade 3 hepatitis and pneumonitis (q = 0.007) in patients treated with combination PD-1/PD-L1 and CTLA-4 inhibitors, and PD-1 inhibitors in combination with IDO-1 inhibitors. These data highlight that some patients may have a genetic predisposition to developing irAEs.

Nutrient scavenging-fueled growth in pancreatic cancer depends on caveolae-mediated endocytosis under nutrient-deprived conditions

Pancreatic ductal adenocarcinoma (PDAC) is characterized by its nutrient-scavenging ability, crucial for tumor progression. Here, we investigated the roles of caveolae-mediated endocytosis (CME) in PDAC progression. Analysis of patient data across diverse datasets revealed a strong association of high caveolin-1 (Cav-1) expression with higher histologic grade, the most aggressive PDAC molecular subtypes, and worse clinical outcomes. Cav-1 loss markedly promoted longer overall and tumor-free survival in a genetically engineered mouse model. Cav-1-deficient tumor cell lines exhibited significantly reduced proliferation, particularly under low nutrient conditions. Supplementing cells with albumin rescued the growth of Cav-1-proficient PDAC cells, but not in Cav-1-deficient PDAC cells under low glutamine conditions. In addition, Cav-1 depletion led to significant metabolic defects, including decreased glycolytic and mitochondrial metabolism, and downstream protein translation signaling pathways. These findings highlight the crucial role of Cav-1 and CME in fueling pancreatic tumorigenesis, sustaining tumor growth, and promoting survival through nutrient scavenging.

Weak local adaptation to drought in seedlings of a widespread conifer

Tree seedlings from populations native to drier regions are often assumed to be more drought tolerant than those from wetter provenances. However, intraspecific variation in drought tolerance has not been well-characterized despite being critical for developing climate change mitigation and adaptation strategies, and for predicting the effects of drought on forests. We used a large-scale common garden drought-to-death experiment to assess range-wide variation in drought tolerance, measured by decline of photosynthetic efficiency, growth, and plastic responses to extreme summer drought in seedlings of 73 natural populations of the two main varieties of Douglas-fir (Pseudotsuga menziesii var. menziesii and var. glauca). Local adaptation to drought was weak in var. glauca and nearly absent in menziesii. Var. glauca showed higher tolerance to drought but slower growth than var. menziesii. Clinal variation in drought tolerance and growth species-wide was mainly associated with temperature rather than precipitation. A higher degree of plasticity for growth was observed in var. menziesii in response to extreme drought. Genetic variation for drought tolerance in seedlings within varieties is maintained primarily within populations. Selective breeding within populations may facilitate adaptation to drought more than assisted gene flow.

Nasopharyngeal angiotensin converting enzyme 2 (ACE2) expression as a risk-factor for SARS-CoV-2 transmission in concurrent hospital associated outbreaks

BACKGROUND

Widespread human-to-human transmission of the severe acute respiratory syndrome coronavirus two (SARS-CoV-2) stems from a strong affinity for the cellular receptor angiotensin converting enzyme two (ACE2). We investigate the relationship between a patient's nasopharyngeal ACE2 transcription and secondary transmission within a series of concurrent hospital associated SARS-CoV-2 outbreaks in British Columbia, Canada.

METHODS

Epidemiological case data from the outbreak investigations was merged with public health laboratory records and viral lineage calls, from whole genome sequencing, to reconstruct the concurrent outbreaks using infection tracing transmission network analysis. ACE2 transcription and RNA viral load were measured by quantitative real-time polymerase chain reaction. The transmission network was resolved to calculate the number of potential secondary cases. Bivariate and multivariable analyses using Poisson and Negative Binomial regression models was performed to estimate the association between ACE2 transcription the number of SARS-CoV-2 secondary cases.

RESULTS

The infection tracing transmission network provided n = 76 potential transmission events across n = 103 cases. Bivariate comparisons found that on average ACE2 transcription did not differ between patients and healthcare workers (P = 0.86). High ACE2 transcription was observed in 98.6% of transmission events, either the primary or secondary case had above average ACE2. Multivariable analysis found that the association between ACE2 transcription (log2 fold-change) and the number of secondary transmission events differs between patients and healthcare workers. In health care workers Negative Binomial regression estimated that a one-unit change in ACE2 transcription decreases the number of secondary cases (β = -0.132 (95%CI: -0.255 to -0.0181) adjusting for RNA viral load. Conversely, in patients a one-unit change in ACE2 transcription increases the number of secondary cases (β = 0.187 (95% CI: 0.0101 to 0.370) adjusting for RNA viral load. Sensitivity analysis found no significant relationship between ACE2 and secondary transmission in health care workers and confirmed the positive association among patients.

CONCLUSION

Our study suggests that ACE2 transcription has a positive association with SARS-CoV-2 secondary transmission in admitted inpatients, but not health care workers in concurrent hospital associated outbreaks, and it should be further investigated as a risk-factor for viral transmission.

HNF4A guides the MLL4 complex to establish and maintain H3K4me1 at gene regulatory elements

Hepatocyte nuclear factor 4A (HNF4A/NR2a1), a transcriptional regulator of hepatocyte identity, controls genes that are crucial for liver functions, primarily through binding to enhancers. In mammalian cells, active and primed enhancers are marked by monomethylation of histone 3 (H3) at lysine 4 (K4) (H3K4me1) in a cell type-specific manner. How this modification is established and maintained at enhancers in connection with transcription factors (TFs) remains unknown. Using analysis of genome-wide histone modifications, TF binding, chromatin accessibility and gene expression, we show that HNF4A is essential for an active chromatin state. Using HNF4A loss and gain of function experiments in vivo and in cell lines in vitro, we show that HNF4A affects H3K4me1, H3K27ac and chromatin accessibility, highlighting its contribution to the establishment and maintenance of a transcriptionally permissive epigenetic state. Mechanistically, HNF4A interacts with the mixed-lineage leukaemia 4 (MLL4) complex facilitating recruitment to HNF4A-bound regions. Our findings indicate that HNF4A enriches H3K4me1, H3K27ac and establishes chromatin opening at transcriptional regulatory regions.

Proteomic Evolution from Acute to Post-COVID-19 Conditions

Many COVID-19 survivors have post-COVID-19 conditions, and females are at a higher risk. We sought to determine (1) how protein levels change from acute to post-COVID-19 conditions, (2) whether females have a plasma protein signature different from that of males, and (3) which biological pathways are associated with COVID-19 when compared to restrictive lung disease. We measured protein levels in 74 patients on the day of admission and at 3 and 6 months after diagnosis. We determined protein concentrations by multiple reaction monitoring (MRM) using a panel of 269 heavy-labeled peptides. The predicted forced vital capacity (FVC) and diffusing capacity of the lungs for carbon monoxide (DLCO) were measured by routine pulmonary function testing. Proteins associated with six key lipid-related pathways increased from admission to 3 and 6 months; conversely, proteins related to innate immune responses and vasoconstriction-related proteins decreased. Multiple biological functions were regulated differentially between females and males. Concentrations of eight proteins were associated with FVC, %, and they together had c-statistics of 0.751 (CI:0.732-0.779); similarly, concentrations of five proteins had c-statistics of 0.707 (CI:0.676-0.737) for DLCO, %. Lipid biology may drive evolution from acute to post-COVID-19 conditions, while activation of innate immunity and vascular regulation pathways decreased over that period. (ProteomeXchange identifiers: PXD041762, PXD029437).

Costs of major depression covered / not covered in British Columbia, Canada

BACKGROUND

Major depressive disorder (MDD) is one of the world's leading causes of disability. Our purpose was to characterize the total costs of MDD and evaluate the degree to which the British Columbia provincial health system meets its objective to protect people from the financial impact of illness.

METHODS

We performed a population-based cohort study of adults newly diagnosed with MDD between 2015 and 2020 and followed their health system costs over two years. The expenditure proportion of MDD-related, patient paid costs relative to non-subsistence income was estimated, incidences of financial hardship were identified and the slope index of inequality (SII) between the highest and lowest income groups compared across regions.

RESULTS

There were 250,855 individuals diagnosed with MDD in British Columbia over the observation period. Costs to the health system totalled >$1.5 billion (2020 CDN), averaging $138/week for the first 12 weeks following a new diagnosis and $65/week to week 52 and $55/week for weeks 53-104 unless MDD was refractory to treatment ($125/week between week 12-52 and $101/week over weeks 53-104). The proportion of MDD-attributable costs not covered by the health system was 2-15x greater than costs covered by the health system, exceeding $700/week for patients with severe MDD or MDD that was refractory to treatment. Population members in lower-income groups and urban homeowners had disadvantages in the distribution of financial protection received by the health system (SII reached - 8.47 and 15.25, respectively); however, financial hardship and inequities were mitigated province-wide if MDD went into remission (SII - 0.07 to 0.6).

CONCLUSIONS

MDD-attributable costs to health systems and patients are highest in the first 12 weeks after a new diagnosis. During this time, lower income groups and homeowners in urban areas run the risk of financial hardship.

Deep Learning-Enabled MS/MS Spectrum Prediction Facilitates Automated Identification Of Novel Psychoactive Substances

The market for illicit drugs has been reshaped by the emergence of more than 1100 new psychoactive substances (NPS) over the past decade, posing a major challenge to the forensic and toxicological laboratories tasked with detecting and identifying them. Tandem mass spectrometry (MS/MS) is the primary method used to screen for NPS within seized materials or biological samples. The most contemporary workflows necessitate labor-intensive and expensive MS/MS reference standards, which may not be available for recently emerged NPS on the illicit market. Here, we present NPS-MS, a deep learning method capable of accurately predicting the MS/MS spectra of known and hypothesized NPS from their chemical structures alone. NPS-MS is trained by transfer learning from a generic MS/MS prediction model on a large data set of MS/MS spectra. We show that this approach enables a more accurate identification of NPS from experimentally acquired MS/MS spectra than any existing method. We demonstrate the application of NPS-MS to identify a novel derivative of phencyclidine (PCP) within an unknown powder seized in Denmark without the use of any reference standards. We anticipate that NPS-MS will allow forensic laboratories to identify more rapidly both known and newly emerging NPS. NPS-MS is available as a web server at https://nps-ms.ca/, which provides MS/MS spectra prediction capabilities for given NPS compounds. Additionally, it offers MS/MS spectra identification against a vast database comprising approximately 8.7 million predicted NPS compounds from DarkNPS and 24.5 million predicted ESI-QToF-MS/MS spectra for these compounds.

Repeatability of adaptation in sunflowers reveals that genomic regions harbouring inversions also drive adaptation in species lacking an inversion

Local adaptation commonly involves alleles of large effect, which experience fitness advantages when in positive linkage disequilibrium (LD). Because segregating inversions suppress recombination and facilitate the maintenance of LD between locally adapted loci, they are also commonly found to be associated with adaptive divergence. However, it is unclear what fraction of an adaptive response can be attributed to inversions and alleles of large effect, and whether the loci within an inversion could still drive adaptation in the absence of its recombination-suppressing effect. Here, we use genome-wide association studies to explore patterns of local adaptation in three species of sunflower: Helianthus annuus, Helianthus argophyllus, and Helianthus petiolaris, which each harbour a large number of species-specific inversions. We find evidence of significant genome-wide repeatability in signatures of association to phenotypes and environments, which are particularly enriched within regions of the genome harbouring an inversion in one species. This shows that while inversions may facilitate local adaptation, at least some of the loci can still harbour mutations that make substantial contributions without the benefit of recombination suppression in species lacking a segregating inversion. While a large number of genomic regions show evidence of repeated adaptation, most of the strongest signatures of association still tend to be species-specific, indicating substantial genotypic redundancy for local adaptation in these species.

Diverse electron carriers drive syntrophic interactions in an enriched anaerobic acetate-oxidizing consortium

In many anoxic environments, syntrophic acetate oxidation (SAO) is a key pathway mediating the conversion of acetate into methane through obligate cross-feeding interactions between SAO bacteria (SAOB) and methanogenic archaea. The SAO pathway is particularly important in engineered environments such as anaerobic digestion (AD) systems operating at thermophilic temperatures and/or with high ammonia. Despite the widespread importance of SAOB to the stability of the AD process, little is known about their in situ physiologies due to typically low biomass yields and resistance to isolation. Here, we performed a long-term (300-day) continuous enrichment of a thermophilic (55 °C) SAO community from a municipal AD system using acetate as the sole carbon source. Over 80% of the enriched bioreactor metagenome belonged to a three-member consortium, including an acetate-oxidizing bacterium affiliated with DTU068 encoding for carbon dioxide, hydrogen, and formate production, along with two methanogenic archaea affiliated with Methanothermobacter_A. Stable isotope probing was coupled with metaproteogenomics to quantify carbon flux into each community member during acetate conversion and inform metabolic reconstruction and genome-scale modeling. This effort revealed that the two Methanothermobacter_A species differed in their preferred electron donors, with one possessing the ability to grow on formate and the other only consuming hydrogen. A thermodynamic analysis suggested that the presence of the formate-consuming methanogen broadened the environmental conditions where ATP production from SAO was favorable. Collectively, these results highlight how flexibility in electron partitioning during SAO likely governs community structure and fitness through thermodynamic-driven mutualism, shedding valuable insights into the metabolic underpinnings of this key functional group within methanogenic ecosystems.

Complex Autism Spectrum Disorder in a Patient with a Novel De Novo Heterozygous MYT1L Variant

Autism spectrum disorder (ASD) comprises a group of complex neurodevelopmental features seen in many different forms due to variable causes. Highly impactful ASD-susceptibility genes are involved in pathways associated with brain development, chromatin remodeling, and transcription regulation. In this study, we investigate a proband with complex ASD. Whole genome sequencing revealed a novel de novo missense mutation of a highly conserved amino acid residue (NP_001289981.1:p.His516Gln; chr2:1917275; hg38) in the MYT1L neural transcription factor gene. In combination with in silico analysis on gene effect and pathogenicity, we described the proband's phenotype and made comparisons with previously reported cases to explore the spectrum of clinical features in MYT1L single nucleotide variant (SNV) cases. The phenotype-genotype correlation showed a high degree of clinical similarity with previously reported cases of missense variants in MYT1L, indicating MYT1L as the causal gene for the observed phenotype in our proband. The variant was also predicted to be damaging according to multiple in silico pathogenicity predicting tools. This study expands the clinical description of SNVs on the MYT1L gene and provides insight into its contribution to ASD.

Structural Elucidation of Intact Rough-type Lipopolysaccharides Using Field Asymmetric Ion Mobility Spectrometry and Kendrick Mass Defect Plots

Lipopolysaccharides (LPSs) are a hallmark virulence factor of Gram-negative bacteria. They are complex, structurally heterogeneous mixtures due to variations in number, type, and position of their simplest units: fatty acids and monosaccharides. Thus, LPS structural characterization by traditional mass spectrometry (MS) methods is challenging. Here, we describe the benefits of field asymmetric ion mobility spectrometry (FAIMS) for analysis of an intact R-type lipopolysaccharide complex mixture (lipooligosaccharide; LOS). Structural characterization was performed using Escherichia coli J5 (Rc mutant) LOS, a TLR4 agonist widely used in glycoconjugate vaccine research. FAIMS gas-phase fractionation improved the (S/N) ratio and number of detected LOS species. Additionally, FAIMS allowed the separation of overlapping isobars facilitating their tandem MS characterization and unequivocal structural assignments. In addition to FAIMS gas-phase fractionation benefits, extra sorting of the structurally related LOS molecules was further accomplished using Kendrick mass defect (KMD) plots. Notably, a custom KMD base unit of [Na-H] created a highly organized KMD plot that allowed identification of interesting and novel structural differences across the different LOS ion families, i.e., ions with different acylation degrees, oligosaccharides composition, and chemical modifications. Defining the composition of a single LOS ion by tandem MS along with the organized KMD plot structural network was sufficient to deduce the composition of 181 LOS species out of 321 species present in the mixture. The combination of FAIMS and KMD plots allowed in-depth characterization of the complex LOS mixture and uncovered a wealth of novel information about its structural variations.

Integration of data-independent acquisition (DIA) with co-fractionation mass spectrometry (CF-MS) to enhance interactome mapping capabilities

Proteomics technologies are continually advancing, providing opportunities to develop stronger and more robust protein interaction networks (PINs). In part, this is due to the ever-growing number of high-throughput proteomics methods that are available. This review discusses how data-independent acquisition (DIA) and co-fractionation mass spectrometry (CF-MS) can be integrated to enhance interactome mapping abilities. Furthermore, integrating these two techniques can improve data quality and network generation through extended protein coverage, less missing data, and reduced noise. CF-DIA-MS shows promise in expanding our knowledge of interactomes, notably for non-model organisms (NMOs). CF-MS is a valuable technique on its own, but upon the integration of DIA, the potential to develop robust PINs increases, offering a unique approach for researchers to gain an in-depth understanding into the dynamics of numerous biological processes.

Uncovering the history of recombination and population structure in western Canadian stripe rust populations through mating type alleles

BACKGROUND

The population structure of crop pathogens such as Puccinia striiformis f. sp. tritici (Pst), the cause of wheat stripe rust, is of interest to researchers looking to understand these pathogens on a molecular level as well as those with an applied focus such as disease epidemiology. Cereal rusts can reproduce sexually or asexually, and the emergence of novel lineages has the potential to cause serious epidemics such as the one caused by the 'Warrior' lineage in Europe. In a global context, Pst lineages in Canada were not well-characterized and the origin of foreign incursions was not known. Additionally, while some Pst mating type genes have been identified in published genomes, there has been no rigorous assessment of mating type diversity and distribution across the species.

RESULTS

We used a whole-genome/transcriptome sequencing approach for the Canadian Pst population to identify lineages in their global context and evidence tracing foreign incursions. More importantly: for the first time ever, we identified nine alleles of the homeodomain mating type locus in the worldwide Pst population and show that previously identified lineages exhibit a single pair of these alleles. Consistently with the literature, we find only two pheromone receptor mating type alleles. We show that the recent population shift from the 'PstS1' lineage to the 'PstS1-related' lineage is also associated with the introduction of a novel mating type allele (Pst-b3-HD) to the Canadian population. We also show evidence for high levels of mating type diversity in samples associated with the Himalayan center of diversity for Pst, including a single Canadian race previously identified as 'PstPr' (probable recombinant) which we identify as a foreign incursion, most closely related to isolates sampled from China circa 2015.

CONCLUSIONS

These data describe a recent shift in the population of Canadian Pst field isolates and characterize homeodomain-locus mating type alleles in the global Pst population which can now be utilized in testing several research questions and hypotheses around sexuality and hybridization in rust fungi.

Macrocephaly and developmental delay caused by missense variants in RAB5C

Rab GTPases are important regulators of intracellular vesicular trafficking. RAB5C is a member of the Rab GTPase family that plays an important role in the endocytic pathway, membrane protein recycling and signaling. Here we report on 12 individuals with nine different heterozygous de novo variants in RAB5C. All but one patient with missense variants (n = 9) exhibited macrocephaly, combined with mild-to-moderate developmental delay. Patients with loss of function variants (n = 2) had an apparently more severe clinical phenotype with refractory epilepsy and intellectual disability but a normal head circumference. Four missense variants were investigated experimentally. In vitro biochemical studies revealed that all four variants were damaging, resulting in increased nucleotide exchange rate, attenuated responsivity to guanine exchange factors and heterogeneous effects on interactions with effector proteins. Studies in C. elegans confirmed that all four variants were damaging in vivo and showed defects in endocytic pathway function. The variant heterozygotes displayed phenotypes that were not observed in null heterozygotes, with two shown to be through a dominant negative mechanism. Expression of the human RAB5C variants in zebrafish embryos resulted in defective development, further underscoring the damaging effects of the RAB5C variants. Our combined bioinformatic, in vitro and in vivo experimental studies and clinical data support the association of RAB5C missense variants with a neurodevelopmental disorder characterized by macrocephaly and mild-to-moderate developmental delay through disruption of the endocytic pathway.

Indirect exposure to insect growth disruptors affects honey bee (Apis mellifera) reproductive behaviors and ovarian protein expression

Pesticide exposure and queen loss are considered to be major causes of honey bee colony mortality, yet little is known regarding the effects of regularly encountered agrochemicals on honey bee reproduction. Here, we present the results of a two-generational study using specialized cages to expose queens to commonly used insect growth disrupting pesticides (IGDs) via their retinue of worker bees. Under IGD exposure, we tracked queen performance and worker responses to queens, then the performance of the exposed queens' offspring was assessed to identify patterns that may contribute to the long-term health and stability of a social insect colony. The positive control, novaluron, resulted in deformed larvae hatching from eggs laid by exposed queens, and methoxyfenozide, diflubenzuron, and novaluron caused a slight decrease in daily egg laying rates, but this was not reflected in the total egg production over the course of the experiment. Curiously, eggs laid by queens exposed to pyriproxyfen exhibited increased hatching rates, and those larvae developed into worker progeny with increased responsiveness to their queens. Additionally, pyriproxyfen and novaluron exposure affected the queen ovarian protein expression, with the overwhelming majority of differentially expressed proteins coming from the pyriproxyfen exposure. We discuss these results and the potential implications for honey bee reproduction and colony health.

Comparing methods to classify admitted patients with SARS-CoV-2 as admitted for COVID-19 versus with incidental SARS-CoV-2: A cohort study

INTRODUCTION

Not all patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection develop symptomatic coronavirus disease 2019 (COVID-19), making it challenging to assess the burden of COVID-19-related hospitalizations and mortality. We aimed to determine the proportion, resource utilization, and outcomes of SARS-CoV-2 positive patients admitted for COVID-19, and assess the impact of using the Center for Disease Control's (CDC) discharge diagnosis-based algorithm and the Massachusetts state department's drug administration-based classification system on identifying admissions for COVID-19.

METHODS

In this retrospective cohort study, we enrolled consecutive SARS-CoV-2 positive patients admitted to one of five hospitals in British Columbia between December 19, 2021 and May 31,2022. We completed medical record reviews, and classified hospitalizations as being primarily for COVID-19 or with incidental SARS-CoV-2 infection. We applied the CDC algorithm and the Massachusetts classification to estimate the difference in hospital days, intensive care unit (ICU) days and in-hospital mortality and calculated sensitivity and specificity.

RESULTS

Of 42,505 Emergency Department patients, 1,651 were admitted and tested positive for SARS-CoV-2, with 858 (52.0%, 95% CI 49.6-54.4) admitted for COVID-19. Patients hospitalized for COVID-19 required ICU admission (14.0% versus 8.2%, p<0.001) and died (12.6% versus 6.4%, p<0.001) more frequently compared with patients with incidental SARS-CoV-2. Compared to case classification by clinicians, the CDC algorithm had a sensitivity of 82.9% (711/858, 95% CI 80.3%, 85.4%) and specificity of 98.1% (778/793, 95% CI 97.2%, 99.1%) for COVID-19-related admissions and underestimated COVID-19 attributable hospital days. The Massachusetts classification had a sensitivity of 60.5% (519/858, 95% CI 57.2%, 63.8%) and specificity of 78.6% (623/793, 95% CI 75.7%, 81.4%) for COVID-19-related admissions, underestimating total number of hospital and ICU bed days while overestimating COVID-19-related intubations, ICU admissions, and deaths.

CONCLUSION

Half of SARS-CoV-2 hospitalizations were for COVID-19 during the Omicron wave. The CDC algorithm was more specific and sensitive than the Massachusetts classification, but underestimated the burden of COVID-19 admissions.

TRIAL REGISTRATION

Clinicaltrials.gov, NCT04702945.

Functional characterization of fungal lytic polysaccharide monooxygenases for cellulose surface oxidation

BACKGROUND

Microbial lytic polysaccharide monooxygenases (LPMOs) cleave diverse biomass polysaccharides, including cellulose and hemicelluloses, by initial oxidation at C1 or C4 of glycan chains. Within the Carbohydrate-Active Enzymes (CAZy) classification, Auxiliary Activity Family 9 (AA9) comprises the first and largest group of fungal LPMOs, which are often also found in tandem with non-catalytic carbohydrate-binding modules (CBMs). LPMOs originally attracted attention for their ability to potentiate complete biomass deconstruction to monosaccharides. More recently, LPMOs have been applied for selective surface modification of insoluble cellulose and chitin.

RESULTS

To further explore the catalytic diversity of AA9 LPMOs, over 17,000 sequences were extracted from public databases, filtered, and used to construct a sequence similarity network (SSN) comprising 33 phylogenetically supported clusters. From these, 32 targets were produced successfully in the industrial filamentous fungus Aspergillus niger, 25 of which produced detectable LPMO activity. Detailed biochemical characterization of the eight most highly produced targets revealed individual C1, C4, and mixed C1/C4 regiospecificities of cellulose surface oxidation, different redox co-substrate preferences, and CBM targeting effects. Specifically, the presence of a CBM correlated with increased formation of soluble oxidized products and a more localized pattern of surface oxidation, as indicated by carbonyl-specific fluorescent labeling. On the other hand, LPMOs without native CBMs were associated with minimal release of soluble products and comparatively dispersed oxidation pattern.

CONCLUSIONS

This work provides insight into the structural and functional diversity of LPMOs, and highlights the need for further detailed characterization of individual enzymes to identify those best suited for cellulose saccharification versus surface functionalization toward biomaterials applications.

A comparison of sampling and testing approaches for the surveillance of SARS-CoV-2 in farmed American mink

Surveillance for SARS-CoV-2 in American mink (Neovison vison) is a global priority because outbreaks on mink farms have potential consequences for animal and public health. Surveillance programs often focus on screening natural mortalities; however, significant knowledge gaps remain regarding sampling and testing approaches. Using 76 mink from 3 naturally infected farms in British Columbia, Canada, we compared the performance of 2 reverse-transcription real-time PCR (RT-rtPCR) targets (the envelope [E] and RNA-dependent RNA polymerase [RdRp] genes) as well as serology. We also compared RT-rtPCR and sequencing results from nasopharyngeal, oropharyngeal, skin, and rectal swabs, as well as nasopharyngeal samples collected using swabs and interdental brushes. We found that infected mink were generally RT-rtPCR-positive on all samples; however, Ct values differed significantly among sample types (nasopharyngeal < oropharyngeal < skin < rectal). There was no difference in the results of nasopharyngeal samples collected using swabs or interdental brushes. For most mink (89.4%), qualitative (i.e., positive vs. negative) serology and RT-rtPCR results were concordant. However, mink were positive on RT-rtPCR and negative on serology and vice versa, and there was no significant correlation between Ct values on RT-rtPCR and percent inhibition on serology. Both the E and RdRp targets were detectable in all sample types, albeit with a small difference in Ct values. Although SARS-CoV-2 RNA can be detected in multiple sample types, passive surveillance programs in mink should focus on multiple target RT-rtPCR testing of nasopharyngeal samples in combination with serology.

Genetic counselors' research dissemination practices and attitudes

Benefits have been demonstrated to disseminating aggregate research results to all relevant audiences, including study participants. Despite this, many health researchers face barriers in dissemination to broad audiences and returning aggregate results to participants is not commonly practiced. Due to their research presence and training in communication, genetic counselors can lead in implementing best practices in this area. We explored genetic counselors' current practices and opinions regarding educating study participants and wider audiences of research findings. We distributed a survey of 32 multiple-choice and open-ended questions to National Society of Genetics Counselors (NSGC) and Canadian Association of Genetic Counsellors (CAGC) members. Most respondents (90.1%, n = 128/142) identified with a responsibility to disseminate their research findings to a broad audience and identified several associated benefits. All respondents saw value in communicating aggregate results to study participants, although over half (53.2%, n = 66/124) had never done so. Genetic counselors reported resource and knowledge barriers to research dissemination. Despite expertise in education and communication, genetic counselors face similar barriers as other researchers toward broad dissemination of research. Formal training and professional guidelines specific to research dissemination practices will equip genetic counselors to reach broader audiences and maximize the impact of research findings.

Winter mortality, diversification, and self-sufficiency affect honey bee (Hymenoptera: Apidae) colony profit in Canada: a model of commercial Alberta beekeepers

Canadian beekeepers faced widespread levels of high honey bee colony mortality over the winter of 2021/2022, with an average winter loss of 45%. To understand the economic impact of winter colony mortality in Canada and the beekeeping management strategies used to mitigate these losses, we develop a profit model of commercial beekeeping operations in Alberta, Canada. Our model shows that for operations engaging in commercial pollination as well as honey production (compared to honey production alone), per colony profit is higher and operations are better able to withstand fluctuations in exogenous variables such as prices and environmental factors affecting productivity including winter mortality rates. The results also suggest that beekeeping operations that replace winter colony losses with splits instead of package bees accrue higher per colony profit than those importing packages to replace losses. Further, operations that produce their own queens to use in their replacement splits, accrue even higher profit. Our results demonstrate that the profitability of beekeeping operations is dependent on several factors including winter mortality rates, colony replacement strategies, and the diversification of revenue sources. Beekeepers who are not as susceptible to price and risk fluctuations in international markets and imported bee risks accrue more consistently positive profits.

Adding epitope compatibility to deceased donor kidney allocation criteria: recommendations from a pan-Canadian online public deliberation

BACKGROUND

The widening supply-demand imbalance for kidneys necessitates finding ways to reduce rejection and improve transplant outcomes. Human leukocyte antigen (HLA) epitope compatibility between donor and recipient may minimize premature graft loss and prolong survival, but incorporating this strategy to deceased donor allocation criteria prioritizes transplant outcomes over wait times. An online public deliberation was held to identify acceptable trade-offs when implementing epitope compatibility to guide Canadian policymakers and health professionals in deciding how best to allocate kidneys fairly.

METHODS

Invitations were mailed to 35,000 randomly-selected Canadian households, with over-sampling of rural/remote locations. Participants were selected for socio-demographic diversity and geographic representation. Five two-hour online sessions were held from November-December 2021. Participants received an information booklet and heard from expert speakers prior to deliberating on how to fairly implement epitope compatibility for transplant candidates and governance issues. Participants collectively generated and voted on recommendations. In the final session, kidney donation and allocation policymakers engaged with participants. Sessions were recorded and transcribed.

RESULTS

Thirty-two individuals participated and generated nine recommendations. There was consensus on adding epitope compatibility to the existing deceased donor kidney allocation criteria. However, participants recommended including safeguards/flexibility around this (e.g., mitigating declining health). They called for a transition period to epitope compatibility, including an ongoing comprehensive public education program. Participants unanimously recommended regular monitoring and public sharing of epitope-based transplant outcomes.

CONCLUSIONS

Participants supported adding epitope compatibility to kidney allocation criteria, but advised safeguards and flexibility around implementation. These recommendations provide guidance to policymakers about incorporating epitope-based deceased donor allocation criteria.

Reference-free assembly of long-read transcriptome sequencing data with RNA-Bloom2

Long-read sequencing technologies have improved significantly since their emergence. Their read lengths, potentially spanning entire transcripts, is advantageous for reconstructing transcriptomes. Existing long-read transcriptome assembly methods are primarily reference-based and to date, there is little focus on reference-free transcriptome assembly. We introduce "RNA-Bloom2 [ https://github.com/bcgsc/RNA-Bloom ]", a reference-free assembly method for long-read transcriptome sequencing data. Using simulated datasets and spike-in control data, we show that the transcriptome assembly quality of RNA-Bloom2 is competitive to those of reference-based methods. Furthermore, we find that RNA-Bloom2 requires 27.0 to 80.6% of the peak memory and 3.6 to 10.8% of the total wall-clock runtime of a competing reference-free method. Finally, we showcase RNA-Bloom2 in assembling a transcriptome sample of Picea sitchensis (Sitka spruce). Since our method does not rely on a reference, it further sets the groundwork for large-scale comparative transcriptomics where high-quality draft genome assemblies are not readily available.

Human germline heterozygous gain-of-function STAT6 variants cause severe allergic disease

STAT6 (signal transducer and activator of transcription 6) is a transcription factor that plays a central role in the pathophysiology of allergic inflammation. We have identified 16 patients from 10 families spanning three continents with a profound phenotype of early-life onset allergic immune dysregulation, widespread treatment-resistant atopic dermatitis, hypereosinophilia with esosinophilic gastrointestinal disease, asthma, elevated serum IgE, IgE-mediated food allergies, and anaphylaxis. The cases were either sporadic (seven kindreds) or followed an autosomal dominant inheritance pattern (three kindreds). All patients carried monoallelic rare variants in STAT6 and functional studies established their gain-of-function (GOF) phenotype with sustained STAT6 phosphorylation, increased STAT6 target gene expression, and TH2 skewing. Precision treatment with the anti-IL-4Rα antibody, dupilumab, was highly effective improving both clinical manifestations and immunological biomarkers. This study identifies heterozygous GOF variants in STAT6 as a novel autosomal dominant allergic disorder. We anticipate that our discovery of multiple kindreds with germline STAT6 GOF variants will facilitate the recognition of more affected individuals and the full definition of this new primary atopic disorder.

Co-learning commentary: a patient partner perspective in mental health care research

BACKGROUND

Although including patients as full, active members of research teams is becoming more common, there are few accounts about how to do so successfully, and almost none of these are written by patient partners themselves. Three patient partners contributed their lived experience to a three-year, multi-component mental health research project in British Columbia, Canada. As patient partners, we contributed to innovative co-learning in this project, resulting in mutual respect and wide-ranging benefits. To guide future patient partners and researchers seeking patient engagement, we outline the processes that helped our research team 'get it right'.

MAIN BODY

From the outset, we were integrated into components of the project that we chose: thematically coding a rapid review, developing questions and engagement processes for focus groups, and shaping an economic model. Our level of engagement in each component was determined by us. Additionally, we catalyzed the use of surveys to evaluate our engagement and the perceptions of patient engagement from the wider team. At our request, we had a standing place on each monthly meeting agenda. Importantly, we broke new ground when we moved the team from using previously accepted psychiatric terminology that no longer fit the reality of patients' experiences. We worked diligently with the team to represent the reality that was appropriate for all parties. The approach taken in this project led to meaningful and successfully integrated patient experiences, fostered a shared understanding, which positively impacted team development and cohesion. The resulting 'lessons learned' included engaging early, often, and with respect; carving out and creating a safe place, free from stigma; building trust within the research team; drawing on lived experience; co-creating acceptable terminology; and cultivating inclusivity throughout the entire study.

CONCLUSION

We believe that lived experience can and should go hand-in-hand with research, to ensure study outcomes reflect the knowledge of patients themselves. We were willing to share the truth of our lived experience. We were treated as co-researchers. Successful engagement came from the 'lessons learned' that can be used by other teams who wish to engage patient partners in health research.

Intubation practices and outcomes for patients with suspected or confirmed COVID-19: a national observational study by the Canadian COVID-19 Emergency Department Rapid Response Network (CCEDRRN)

OBJECTIVE

Intubation practices changed during the COVID-19 pandemic to protect healthcare workers from transmission of disease. Our objectives were to describe intubation characteristics and outcomes for patients tested for SARS CoV-2 infection. We compared outcomes between patients testing SARS COV-2 positive with those testing negative.

METHODS

We conducted a health records review using the Canadian COVID-19 Emergency Department Rapid Response Network (CCEDRRN) registry. We included consecutive eligible patients who presented to one of 47 EDs across Canada between March 1, 2020 and June 20, 2021, were tested for SARS-CoV-2 and intubated in the ED. The primary outcome was the proportion of patients experiencing a post-intubation adverse event during the ED stay. Secondary outcomes included first-pass success, intubation practices, and hospital mortality. We used descriptive statistics to summarize variables with subgroup differences examined using t tests, z tests, or chi-squared tests where appropriate with 95% CIs.

RESULTS

Of 1720 patients with suspected COVID-19 who were intubated in the ED during the study period, 337 (19.6%) tested SARS-CoV-2 positive and 1383 (80.4%) SARS-CoV-2 negative. SARS-CoV-2 positive patients presented to hospital with lower oxygen levels than SARS-CoV-2 negative patients (mean pulse oximeter SaO2 86 vs 94%, p < 0.001). In total, 8.5% of patients experienced an adverse event post-intubation. More patients in the SARS-CoV-2 positive subgroup experienced post-intubation hypoxemia (4.5 vs 2.2%, p = 0.019). In-hospital mortality was greater for patients who experienced intubation-related adverse events (43.2 vs 33.2%, p = 0.018). There was no significant difference in adverse event-associated mortality by SARS-CoV-2 status. First-pass success was achieved in 92.4% of all intubations, with no difference by SARS-CoV-2 status.

CONCLUSIONS

During the COVID-19 pandemic, we observed a low risk of adverse events associated with intubation, even though hypoxemia was common in patients with confirmed SARS-CoV-2. We observed high rates of first-pass success and low rates of inability to intubate. The limited number of adverse events precluded multivariate adjustments. Study findings should reassure emergency medicine practitioners that system modifications made to intubation processes in response to the COVID-19 pandemic do not appear to be associated with worse outcomes compared to pre-COVID-19 practices.

A universal sequencing read interpreter

Massively parallel DNA sequencing has led to the rapid growth of highly multiplexed experiments in biology. These experiments produce unique sequencing results that require specific analysis pipelines to decode highly structured reads. However, no versatile framework that interprets sequencing reads to extract their encoded information for downstream biological analysis has been developed. Here, we report INTERSTELLAR (interpretation, scalable transformation, and emulation of large-scale sequencing reads) that decodes data values encoded in theoretically any type of sequencing read and translates them into sequencing reads of another structure of choice. We demonstrated that INTERSTELLAR successfully extracted information from a range of short- and long-read sequencing reads and translated those of single-cell (sc)RNA-seq, scATAC-seq, and spatial transcriptomics to be analyzed by different software tools that have been developed for conceptually the same types of experiments. INTERSTELLAR will greatly facilitate the development of sequencing-based experiments and sharing of data analysis pipelines.

Lessons from Canada's notice of compliance with conditions policy for the life-cycle regulation of drugs

Innovative health technologies are not well regulated under current pathways, leading regulators to adopt contextual, life-cycle regulatory models, which authorize drugs based on earlier clinical evidence subject to the conduct of post-market trials that confirm clinical benefit and safety. In this paper, we evaluate all drugs authorized in Canada under the Notice of Compliance with conditions (NOC/c) policy from 1998 to 2021 to analyze its function, identify challenges and areas for improvement, and make recommendations to inform Health Canada's regulatory reforms. We analyzed a sample of 148 drugs authorized between 1998 and 2021, including characteristics about the pre- and post-market clinical trials, finding that most NOC/c authorizations are based on one, single-arm clinical trial using a surrogate endpoint. Post-market trials are more likely to be randomized, Phase III trials but mostly use surrogate endpoints. Based on our findings, we recommend increasing decision-making transparency throughout the regulatory process, developing comprehensive eligibility criteria for selecting appropriate health technologies, modernizing pre-market evidence requirements, adopting a more active role in designing post-market trials, and utilizing automatic expiry, stronger penalties, and ongoing disclosure of the status of post-market trials to promote compliance.

Should Canada adopt managed access agreements in Canada for expensive drugs?

Drugs are increasingly authorized based on less mature evidence, leaving payors faced with significant clinical and cost-effectiveness uncertainties. As a result, payors must often choose between reimbursing a drug that may not turn out to be cost-effective (or may even be unsafe) or delaying the reimbursement of a drug that is cost-effective and offers clinical benefit to patients. Novel reimbursement decision models and frameworks, such as managed access agreements (MAAs), may address this decision challenge. Here, we provide a comprehensive overview of the legal limitations, considerations, and implications for adopting MAAs in Canadian jurisdictions. We begin with an overview of current drug reimbursement processes in Canada, terminology and definitions of the different types of MAAs, and select international experiences with MAAs. We discuss the legal barriers to MAA governance frameworks, design and implementation considerations, and legal and policy implications of MAAs. Finally, we provide recommendations to guide policy development for implementing MAAs in Canada, based on existing literature, international experience, and our legal analysis. We conclude that legal and policy barriers likely prevent the adoption of a pan-Canadian MAA governance framework. More feasible is a quasi-federal or provincial approach, building on existing infrastructure.

Positioning whole exome sequencing in the diagnostic pathway for rare disease to optimise utility: a protocol for an observational cohort study and an economic evaluation

INTRODUCTION

Despite the superior diagnostic performance of exome and genome sequencing compared with conventional genetic tests, evidence gaps related to clinical utility and cost effectiveness have limited their availability in routine clinical practice in many jurisdictions. To inform adoption and reimbursement policy, this protocol provides a chain of evidence approach to determining the diagnostic utility, clinical utility and cost-effectiveness of whole exome sequencing (WES) from seven medical genetic centres in two Canadian provinces.

METHODS AND ANALYSIS

Using a multicentre observational cohort design, we will extract data specific to the pre-WES diagnostic pathway and 1-year post-WES medical management from electronic medical records for 650 patients with rare disease of suspected genetic aetiology who receive WES. The date from the clinical record will be linked to provincial administrative health database to capture healthcare resource use and estimate costs. Our analysis will: (1) define and describe diagnostic testing pathways that occur prior to WES among patients with rare disease, (2) determine the diagnostic utility of WES, characterised as the proportion of patients for whom causative DNA variants are identified, (3) determine the clinical utility of WES, characterised as a change in medical management triggered by WES results, (4) determine the pattern and cost of health service utilisation prior and 1 year following WES among patients who receive a diagnosis, do not receive a diagnosis, or receive an uncertain diagnosis and (5) estimate the cost-effectiveness of WES compared with conventional diagnostic testing pathways, measured by the incremental cost per additional patient diagnosed by WES using simulation modelling.

ETHICS AND DISSEMINATION

This protocol was approved by Clinical Trials Ontario (CTO-1577) and research ethics boards at the University of Calgary (REB18-0744 and REB20-1449) and University of Alberta (Pro0009156). Findings will be disseminated through academic publications and policy reports.

Collaborating with Patient Partners to Model Clinical Care Pathways in Major Depressive Disorder: The Benefits of Mixing Evidence and Lived Experience

BACKGROUND

Partnering with patients can enrich the design and development of models of clinical care pathways, yet the practice is not commonplace. Guidelines or "best practices" for patient involvement in modeling are scarce.

OBJECTIVES

In this paper, we outline the steps we took to form an effective partnership with patients to design a robust microsimulation Markov model of major depressive disorder care pathways in British Columbia, Canada, with the aim of encouraging other teams to partner with patients in healthcare modeling endeavors.

METHODS

We describe three unique phases of our collaborative process: uncertainty, mapping, and structured collaboration. We then explore the unique contributions the patient partners made, not only to the model itself, but to our process. Key perspectives are shared from both the modeler and the patient partners in their own words.

RESULTS

The patient partners made distinct contributions by challenging and verifying modeling assumptions, noting limitations of the model, and suggesting areas for future research. Both the patient partners and the modelers saw great value in the partnership and agreed that the model was strengthened by the diversity of the team.

CONCLUSIONS

We present our learning and key recommendations for future modeling teams in the absence of tested frameworks. We encourage more widespread adoption of patient involvement in modeling and the development of guidelines for such work to increase the democracy of scientific decision making.

Characterizing, mapping and valuing the demand for forest recreation using crowdsourced social media data

Mapping and valuing of forest recreation is time-consuming and complex, hampering its inclusion in forest management plans and hence the achievement of a fully sustainable forest management. In this study, we explore the potential of crowdsourced social media data in tackling the mapping and valuing of forest recreation demand. To do so, we assess the relationships between crowdsourced social media data, acquired from over 350,000 Flickr geotagged pictures, and demand for forest recreation in British Columbia (BC) forests. We first identify temporal and spatial trends of forest recreation demand, as well as the countries of origin of BC forests visitors. Second, we estimate the average number of annual recreational visits with a linear regression model calibrated with empirically collected secondary data. Lastly, we estimate recreational values by deriving the average consumer surpluses for the visitors of BC forested provincial parks. We find that annually, on average, over 44 million recreational experiences are completed in BC forests, with peaks during the summer months and during the weekends. Moreover, a crowdsourced travel cost approach allowed us to value the recreational ecosystem service in five forested provincial parks ranging from ~2.9 to ~35.0 million CAN$/year. Our findings demonstrate that social media data can be used to characterize, quantify and map the demand for forest recreation (especially in peri-urban forests), representing a useful tool for the inclusion of recreational values in forest management. Finally, we address the limitations of crowdsourced social media data in the study of forest recreation and the future perspectives of this rapidly growing research field.

Spike Mutation Profiles Associated With SARS-CoV-2 Breakthrough Infections in Delta Emerging and Predominant Time Periods in British Columbia, Canada

Background

COVID-19 vaccination is a key public health measure in the pandemic response. The rapid evolution of SARS-CoV-2 variants introduce new groups of spike protein mutations. These new mutations are thought to aid in the evasion of vaccine-induced immunity and render vaccines less effective. However, not all spike mutations contribute equally to vaccine escape. Previous studies associate mutations with vaccine breakthrough infections (BTI), but information at the population level remains scarce. We aimed to identify spike mutations associated with SARS-CoV-2 vaccine BTI in a community setting during the emergence and predominance of the Delta-variant.

Methods

This case-control study used both genomic, and epidemiological data from a provincial COVID-19 surveillance program. Analyses were stratified into two periods approximating the emergence and predominance of the Delta-variant, and restricted to primary SARS-CoV-2 infections from either unvaccinated individuals, or those infected ≥14 days after their second vaccination dose in a community setting. Each sample's spike mutations were concatenated into a unique spike mutation profile (SMP). Penalized logistic regression was used to identify spike mutations and SMPs associated with SARS-CoV-2 vaccine BTI in both time periods.

Results and Discussion

This study reports population level relative risk estimates, between 2 and 4-folds, of spike mutation profiles associated with BTI during the emergence and predominance of the Delta-variant, which comprised 19,624 and 17,331 observations, respectively. The identified mutations cover multiple spike domains including the N-terminal domain (NTD), receptor binding domain (RBD), S1/S2 cleavage region, fusion peptide and heptad regions. Mutations in these different regions imply various mechanisms contribute to vaccine escape. Our profiling method identifies naturally occurring spike mutations associated with BTI, and can be applied to emerging SARS-CoV-2 variants with novel groups of spike mutations.

Longitudinal Plasma Proteomics Analysis Reveals Novel Candidate Biomarkers in Acute COVID-19

The host response to COVID-19 pathophysiology over the first few days of infection remains largely unclear, especially the mechanisms in the blood compartment. We report on a longitudinal proteomic analysis of acute-phase COVID-19 patients, for which we used blood plasma, multiple reaction monitoring with internal standards, and data-independent acquisition. We measured samples on admission for 49 patients, of which 21 had additional samples on days 2, 4, 7, and 14 after admission. We also measured 30 externally obtained samples from healthy individuals for comparison at baseline. The 31 proteins differentiated in abundance between acute COVID-19 patients and healthy controls belonged to acute inflammatory response, complement activation, regulation of inflammatory response, and regulation of protein activation cascade. The longitudinal analysis showed distinct profiles revealing increased levels of multiple lipid-associated functions, a rapid decrease followed by recovery for complement activation, humoral immune response, and acute inflammatory response-related proteins, and level fluctuation in the regulation of smooth muscle cell proliferation, secretory mechanisms, and platelet degranulation. Three proteins were differentiated between survivors and nonsurvivors. Finally, increased levels of fructose-bisphosphate aldolase B were determined in patients with exposure to angiotensin receptor blockers versus decreased levels in those exposed to angiotensin-converting enzyme inhibitors. Data are available via ProteomeXchange PXD029437.

Integrating genomic information and productivity and climate-adaptability traits into a regional white spruce breeding program

Tree improvement programs often focus on improving productivity-related traits; however, under present climate change scenarios, climate change-related (adaptive) traits should also be incorporated into such programs. Therefore, quantifying the genetic variation and correlations among productivity and adaptability traits, and the importance of genotype by environment interactions, including defense compounds involved in biotic and abiotic resistance, is essential for selecting parents for the production of resilient and sustainable forests. Here, we estimated quantitative genetic parameters for 15 growth, wood quality, drought resilience, and monoterpene traits for Picea glauca (Moench) Voss (white spruce). We sampled 1,540 trees from three open-pollinated progeny trials, genotyped with 467,224 SNP markers using genotyping-by-sequencing (GBS). We used the pedigree and SNP information to calculate, respectively, the average numerator and genomic relationship matrices, and univariate and multivariate individual-tree models to obtain estimates of (co)variance components. With few site-specific exceptions, all traits examined were under genetic control. Overall, higher heritability estimates were derived from the genomic- than their counterpart pedigree-based relationship matrix. Selection for height, generally, improved diameter and water use efficiency, but decreased wood density, microfibril angle, and drought resistance. Genome-based correlations between traits reaffirmed the pedigree-based correlations for most trait pairs. High and positive genetic correlations between sites were observed (average 0.68), except for those pairs involving the highest elevation, warmer, and moister site, specifically for growth and microfibril angle. These results illustrate the advantage of using genomic information jointly with productivity and adaptability traits, and defense compounds to enhance tree breeding selection for changing climate.

Conditional Drug Approval as a Path to Market for Oncology Drugs in Canada: Challenges and Recommendations for Assessing Eligibility and Regulatory Responsiveness

International drug regulators use conditional drug approval mechanisms to facilitate faster patient access to drugs based on a lower evidentiary standard typically required of drug approvals. Faster and earlier access is justified by limiting eligibility to drugs intended for serious and life-threatening diseases and by requiring post-market evidence collection to confirm clinical benefit. One such mechanism in Canada, the Notice of Compliance with Conditions (NOC/c) policy, was introduced in 1998. Today, most of the drugs approved under the NOC/c policy are for oncology indications. We analyze oncology drugs approvals under the NOC/c policy to inform discussions of two tradeoffs applied to conditional drug approvals, eligibility criteria and post-market evidence. Our analysis informs recommendations for Canada's proposed regulatory reforms approach to conditional approvals pathways. Our analysis demonstrates that under the current policy, eligibility criteria are insufficiently defined, resulting in their inconsistent application by Health Canada. Regulatory responsiveness to post-market evidence from post-market clinical trial and foreign jurisdiction regulatory decisions is slow and insufficient. In the absence of sufficient regulatory responsiveness, physicians and patients must make clinical decisions without the benefit of the best available evidence. Together, our analysis of the two core tradeoffs in Canada's conditional drug approval provides insight to inform the further development of Canada's proposed agile regulatory approach to drugs and devices that will expand the use of terms and conditions.

Phenomic analysis of the honey bee pathogen-web and its dynamics on colony productivity, health and social immunity behaviors

Many pathogens and parasites have evolved to overwhelm and suppress their host's immune system. Nevertheless, the interactive effects of these agents on colony productivity and wintering success have been relatively unexplored, particularly in large-scale phenomic studies. As a defense mechanism, honey bees have evolved remarkable social behaviors to defend against pathogen and parasite challenges, which reduce the impact of disease and improve colony health. To investigate the complex role of pathogens, parasites and social immunity behaviors in relation to colony productivity and outcomes, we extensively studied colonies at several locations across Canada for two years. In 2016 and 2017, colonies founded with 1-year-old queens of diverse genetic origin were evaluated, which represented a generalized subset of the Canadian bee population. During each experimental year (May through April), we collected phenotypic data and sampled colonies for pathogen analysis in a standardized manner. Measures included: colony size and productivity (colony weight, cluster size, honey production, and sealed brood population), social immunity traits (hygienic behavior, instantaneous mite population growth rate, and grooming behavior), as well as quantification of gut parasites (Nosema spp., and Lotmaria passim), viruses (DWV-A, DWV-B, BQCV and SBV) and external parasites (Varroa destructor). Our goal was to examine: 1) correlations between pathogens and colony phenotypes; 2) the dynamics of pathogens and parasites on colony phenotypes and productivity traits; and 3) the effects of social immunity behaviors on colony pathogen load. Our results show that colonies expressing high levels of some social immunity behaviors were associated with low levels of pathogens/parasites, including viruses, Nosema spp., and V. destructor. In addition, we determined that elevated viral and Nosema spp. levels were associated with low levels of colony productivity, and that five out of six pathogenic factors measured were negatively associated with colony size and weight in both fall and spring periods. Finally, this study also provides information about the incidence and abundance of pathogens, colony phenotypes, and further disentangles their inter-correlation, so as to better understand drivers of honey bee colony health and productivity.

AMPlify: attentive deep learning model for discovery of novel antimicrobial peptides effective against WHO priority pathogens

BACKGROUND

Antibiotic resistance is a growing global health concern prompting researchers to seek alternatives to conventional antibiotics. Antimicrobial peptides (AMPs) are attracting attention again as therapeutic agents with promising utility in this domain, and using in silico methods to discover novel AMPs is a strategy that is gaining interest. Such methods can sift through large volumes of candidate sequences and reduce lab screening costs.

RESULTS

Here we introduce AMPlify, an attentive deep learning model for AMP prediction, and demonstrate its utility in prioritizing peptide sequences derived from the Rana [Lithobates] catesbeiana (bullfrog) genome. We tested the bioactivity of our predicted peptides against a panel of bacterial species, including representatives from the World Health Organization's priority pathogens list. Four of our novel AMPs were active against multiple species of bacteria, including a multi-drug resistant isolate of carbapenemase-producing Escherichia coli.

CONCLUSIONS

We demonstrate the utility of deep learning based tools like AMPlify in our fight against antibiotic resistance. We expect such tools to play a significant role in discovering novel candidates of peptide-based alternatives to classical antibiotics.

Photodynamic and Contact Killing Polymeric Fabric Coating for Bacteria and SARS-CoV-2

The development of low-cost, non-toxic, scalable antimicrobial textiles is needed to address the spread of deadly pathogens. Here, we report a polysiloxane textile coating that possesses two modes of antimicrobial inactivation, passive contact inactivation through amine/imine functionalities and active photodynamic inactivation through the generation of reactive oxygen species (ROS). This material can be coated and cross-linked onto natural and synthetic textiles through a simple soak procedure, followed by UV cure to afford materials exhibiting no aqueous leaching and only minimal leaching in organic solvents. This coating minimally impacts the mechanical properties of the fabric while also imparting hydrophobicity. Passive inactivation of Escherichia coli (E. coli) and methicillin-resistant Staphylococcus aureus (MRSA) is achieved with >98% inactivation after 24 h, with a 23× and 3× inactivation rate increase against E. coli and MRSA, respectively, when green light is used to generate ROS. Up to 90% decrease in the infectivity of SARS-CoV-2 after 2 h of irradiated incubation with the material is demonstrated. These results show that modifying textiles with dual-functional polymers results in robust and highly antimicrobial materials that are expected to find widespread use in combating the spread of deadly pathogens.

Clinical response to nivolumab in an INI1-deficient pediatric chordoma correlates with immunogenic recognition of brachyury

Poorly differentiated chordoma (PDC) is a recently recognized subtype of chordoma characterized by expression of the embryonic transcription factor, brachyury, and loss of INI1. PDC primarily affects children and is associated with a poor prognosis and limited treatment options. Here we describe the molecular and immune tumour microenvironment profiles of two paediatric PDCs produced using whole-genome, transcriptome and whole-genome bisulfite sequencing (WGBS) and multiplex immunohistochemistry. Our analyses revealed the presence of tumour-associated immune cells, including CD8+ T cells, and expression of the immune checkpoint protein, PD-L1, in both patient samples. Molecular profiling provided the rationale for immune checkpoint inhibitor (ICI) therapy, which resulted in a clinical and radiographic response. A dominant T cell receptor (TCR) clone specific for a brachyury peptide-MHC complex was identified from bulk RNA sequencing, suggesting that targeting of the brachyury tumour antigen by tumour-associated T cells may underlie this clinical response to ICI. Correlative analysis with rhabdoid tumours, another INI1-deficient paediatric malignancy, suggests that a subset of tumours may share common immune phenotypes, indicating the potential for a therapeutically targetable subgroup of challenging paediatric cancers.

Thrice out of Asia and the adaptive radiation of the western honey bee

The origin of the western honey bee Apis mellifera has been intensely debated. Addressing this knowledge gap is essential for understanding the evolution and genetics of one of the world’s most important pollinators. By analyzing 251 genomes from 18 native subspecies, we found support for an Asian origin of honey bees with at least three expansions leading to African and European lineages. The adaptive radiation of honey bees involved selection on a few genomic “hotspots.” We found 145 genes with independent signatures of selection across all bee lineages, and these genes were highly associated with worker traits. Our results indicate that a core set of genes associated with worker and colony traits facilitated the adaptive radiation of honey bees across their vast distribution.

RNA-Scoop: interactive visualization of transcripts in single-cell transcriptomes

Recent advances in single-cell RNA sequencing technologies have made detection of transcripts in single cells possible. The level of resolution provided by these technologies can be used to study changes in transcript usage across cell populations and help investigate new biology. Here, we introduce RNA-Scoop, an interactive cell cluster and transcriptome visualization tool to analyze transcript usage across cell categories and clusters. The tool allows users to examine differential transcript expression across clusters and investigate how usage of specific transcript expression mechanisms varies across cell groups.

Early-stage economic analysis of research-based comprehensive genomic sequencing for advanced cancer care

Genomic research is driving discovery for future population benefit. Limited evidence exists on immediate patient and health system impacts of research participation. This study uses real-world data and quasi-experimental matching to examine early-stage cost and health impacts of research-based genomic sequencing. British Columbia’s Personalized OncoGenomics (POG) single-arm program applies whole genome and transcriptome analysis (WGTA) to characterize genomic landscapes in advanced cancers. Our cohort includes POG patients enrolled between 2014 and 2015 and 1:1 genetic algorithm–matched usual care controls. We undertake a cost consequence analysis and estimate 1-year effects of WGTA on patient management, patient survival, and health system costs reported in 2015 Canadian dollars. WGTA costs are imputed and forecast using system of equations modeling. We use Kaplan-Meier survival analysis to explore survival differences and inverse probability of censoring weighted linear regression to estimate mean 1-year survival times and costs. Non-parametric bootstrapping simulates sampling distributions and enables scenario analysis, revealing drivers of incremental costs, survival, and net monetary benefit for assumed willingness to pay thresholds. We identified 230 POG patients and 230 matched controls for cohort inclusion. The mean period cost of research-funded WGTA was $26,211 (SD: $14,191). Sequencing costs declined rapidly, with WGTA forecasts hitting $13,741 in 2021. The incremental healthcare system effect (non-research expenditures) was $5203 (95% CI: 75, 10,424) compared to usual care. No overall survival differences were observed, but outcome heterogeneity was present. POG patients receiving WGTA-informed treatment experienced incremental survival gains of 2.49 months (95% CI: 1.32, 3.64). Future cost consequences became favorable as WGTA cost drivers declined and WGTA-informed treatment rates improved to 60%. Our study demonstrates the ability of real-world data to support evaluations of only-in-research health technologies. We identify situations where precision oncology research initiatives may produce survival benefit at a cost that is within healthcare systems’ willingness to pay. This economic evidence informs the early-stage healthcare impacts of precision oncology research.

The parasite Schistocephalus solidus secretes proteins with putative host manipulation functions

BACKGROUND

Manipulative parasites are thought to liberate molecules in their external environment, acting as manipulation factors with biological functions implicated in their host's physiological and behavioural alterations. These manipulation factors are part of a complex mixture called the secretome. While the secretomes of various parasites have been described, there is very little data for a putative manipulative parasite. It is necessary to study the molecular interaction between a manipulative parasite and its host to better understand how such alterations evolve.

METHODS

Here, we used proteomics to characterize the secretome of a model cestode with a complex life cycle based on trophic transmission. We studied Schistocephalus solidus during the life stage in which behavioural changes take place in its obligatory intermediate fish host, the threespine stickleback (Gasterosteus aculeatus). We produced a novel genome sequence and assembly of S. solidus to improve protein coding gene prediction and annotation for this parasite. We then described the whole worm's proteome and its secretome during fish host infection using LC-MS/MS.

RESULTS

A total of 2290 proteins were detected in the proteome of S. solidus, and 30 additional proteins were detected specifically in the secretome. We found that the secretome contains proteases, proteins with neural and immune functions, as well as proteins involved in cell communication. We detected receptor-type tyrosine-protein phosphatases, which were reported in other parasitic systems to be manipulation factors. We also detected 12 S. solidus-specific proteins in the secretome that may play important roles in host-parasite interactions.

CONCLUSIONS

Our results suggest that S. solidus liberates molecules with putative host manipulation functions in the host and that many of them are species-specific.

Straglr: discovering and genotyping tandem repeat expansions using whole genome long-read sequences

Tandem repeat (TR) expansion is the underlying cause of over 40 neurological disorders. Long-read sequencing offers an exciting avenue over conventional technologies for detecting TR expansions. Here, we present Straglr, a robust software tool for both targeted genotyping and novel expansion detection from long-read alignments. We benchmark Straglr using various simulations, targeted genotyping data of cell lines carrying expansions of known diseases, and whole genome sequencing data with chromosome-scale assembly. Our results suggest that Straglr may be useful for investigating disease-associated TR expansions using long-read sequencing.

Queen honey bees exhibit variable resilience to temperature stress

Extreme temperature exposure can reduce stored sperm viability within queen honey bees; however, little is known about how thermal stress may directly impact queen performance or other maternal quality metrics. Here, in a blind field trial, we recorded laying pattern, queen mass, and average callow worker mass before and after exposing queens to a cold temperature (4°C, 2 h), hot temperature (42°C, 2 h), and hive temperature (33°C, control). We measured sperm viability at experiment termination, and investigated potential vertical effects of maternal temperature stress on embryos using proteomics. We found that cold stress, but not heat stress, reduced stored sperm viability; however, we found no significant effect of temperature stress on any other recorded metrics (queen mass, average callow worker mass, laying patterns, the egg proteome, and queen spermathecal fluid proteome). Previously determined candidate heat and cold stress biomarkers were not differentially expressed in stressed queens, indicating that these markers only have short-term post-stress diagnostic utility. Combined with variable sperm viability responses to temperature stress reported in different studies, these data also suggest that there is substantial variation in temperature tolerance, with respect to impacts on fertility, amongst queens. Future research should aim to quantify the variation and heritability of temperature tolerance, particularly heat, in different populations of queens in an effort to promote queen resilience.