Fundamental Biological Features of Spaceflight: Advancing the Field to Enable Deep-Space Exploration.

Research on astronaut health and model organisms have revealed six features of spaceflight biology that guide our current understanding of fundamental molecular changes that occur during space travel. The features include oxidative stress, DNA damage, mitochondrial dysregulation, epigenetic changes (including gene regulation), telomere length alterations, and microbiome shifts. Here we review the known hazards of human spaceflight, how spaceflight affects living systems through these six fundamental features, and the associated health risks of space exploration. We also discuss the essential issues related to the health and safety of astronauts involved in future missions, especially planned long-duration and Martian missions.

Comprehensive Multi-omics Analysis Reveals Mitochondrial Stress as a Central Biological Hub for Spaceflight Impact.

Spaceflight is known to impose changes on human physiology with unknown molecular etiologies. To reveal these causes, we used a multi-omics, systems biology analytical approach using biomedical profiles from fifty-nine astronauts and data from NASA's GeneLab derived from hundreds of samples flown in space to determine transcriptomic, proteomic, metabolomic, and epigenetic responses to spaceflight. Overall pathway analyses on the multi-omics datasets showed significant enrichment for mitochondrial processes, as well as innate immunity, chronic inflammation, cell cycle, circadian rhythm, and olfactory functions. Importantly, NASA's Twin Study provided a platform to confirm several of our principal findings. Evidence of altered mitochondrial function and DNA damage was also found in the urine and blood metabolic data compiled from the astronaut cohort and NASA Twin Study data, indicating mitochondrial stress as a consistent phenotype of spaceflight.

XACT-Seq Comprehensively Defines the Promoter-Position and Promoter-Sequence Determinants for Initial-Transcription Pausing.

Pausing by RNA polymerase (RNAP) during transcription elongation, in which a translocating RNAP uses a "stepping" mechanism, has been studied extensively, but pausing by RNAP during initial transcription, in which a promoter-anchored RNAP uses a "scrunching" mechanism, has not. We report a method that directly defines the RNAP-active-center position relative to DNA with single-nucleotide resolution (XACT-seq; "crosslink-between-active-center-and-template sequencing"). We apply this method to detect and quantify pausing in initial transcription at 411 (∼4,000,000) promoter sequences in vivo in Escherichia coli. The results show initial-transcription pausing can occur in each nucleotide addition during initial transcription, particularly the first 4 to 5 nucleotide additions. The results further show initial-transcription pausing occurs at sequences that resemble the consensus sequence element for transcription-elongation pausing. Our findings define the positional and sequence determinants for initial-transcription pausing and establish initial-transcription pausing is hard coded by sequence elements similar to those for transcription-elongation pausing.

A roadmap for the Human Developmental Cell Atlas.

The Human Developmental Cell Atlas (HDCA) initiative, which is part of the Human Cell Atlas, aims to create a comprehensive reference map of cells during development. This will be critical to understanding normal organogenesis, the effect of mutations, environmental factors and infectious agents on human development, congenital and childhood disorders, and the cellular basis of ageing, cancer and regenerative medicine. Here we outline the HDCA initiative and the challenges of mapping and modelling human development using state-of-the-art technologies to create a reference atlas across gestation. Similar to the Human Genome Project, the HDCA will integrate the output from a growing community of scientists who are mapping human development into a unified atlas. We describe the early milestones that have been achieved and the use of human stem-cell-derived cultures, organoids and animal models to inform the HDCA, especially for prenatal tissues that are hard to acquire. Finally, we provide a roadmap towards a complete atlas of human development.

CapZyme-Seq Comprehensively Defines Promoter-Sequence Determinants for RNA 5' Capping with NAD.

Nucleoside-containing metabolites such as NAD+ can be incorporated as 5' caps on RNA by serving as non-canonical initiating nucleotides (NCINs) for transcription initiation by RNA polymerase (RNAP). Here, we report CapZyme-seq, a high-throughput-sequencing method that employs NCIN-decapping enzymes NudC and Rai1 to detect and quantify NCIN-capped RNA. By combining CapZyme-seq with multiplexed transcriptomics, we determine efficiencies of NAD+ capping by Escherichia coli RNAP for ∼16,000 promoter sequences. The results define preferred transcription start site (TSS) positions for NAD+ capping and define a consensus promoter sequence for NAD+ capping: HRRASWW (TSS underlined). By applying CapZyme-seq to E. coli total cellular RNA, we establish that sequence determinants for NCIN capping in vivo match the NAD+-capping consensus defined in vitro, and we identify and quantify NCIN-capped small RNAs (sRNAs). Our findings define the promoter-sequence determinants for NCIN capping with NAD+ and provide a general method for analysis of NCIN capping in vitro and in vivo.

Stratification of neurogenic bladder risk in spina bifida using the urinary peptidome.

Neurogenic bladder poses a major morbidity in children with spina bifida (SB), and videourodynamic studies (VUDS) are used to stratify this risk. This small-scale pilot study utilized current mass-spectrometry-based proteomic approaches to identify peptides or proteins in urine that may differentiate children at high risk of developing renal complications from a neurogenic bladder. Twenty-two urine samples of which nine had high bladder pressure storage that put the upper urinary tract at risk, while 13 with a lower risk for renal compromise were analyzed. More than 1,900 peptides across all 22 samples were quantified, and 115 peptides differed significantly (P < 0.05) between the two groups. Using machine learning approaches five peptides that showed the greatest differences between these two clinical categories were used to build a classifier. We tested this classifier by blind analysis of an additional six urine samples and showed that it correctly assigned the unknown samples in their proper risk category. These promising results indicate that a urinary screening test based on peptides could be performed on a regular basis to stratify the neurogenic bladder into low or high-risk categories. Expanding this work to larger cohorts as well as across a broad spectrum of urodynamics outcomes may provide a useful diagnostic test for neurogenic bladder.NEW & NOTEWORTHY This approach could help risk stratify the neurogenic bladder in patients with spina bifida and could allow us to safely defer on up to 1/3 of urodynamic studies. These pilot data justify a larger trial before this approach becomes a clinical tool.

Promoter-sequence determinants and structural basis of primer-dependent transcription initiation in Escherichia coli.

Chemical modifications of RNA 5'-ends enable "epitranscriptomic" regulation, influencing multiple aspects of RNA fate. In transcription initiation, a large inventory of substrates compete with nucleoside triphosphates for use as initiating entities, providing an ab initio mechanism for altering the RNA 5'-end. In Escherichia coli cells, RNAs with a 5'-end hydroxyl are generated by use of dinucleotide RNAs as primers for transcription initiation, "primer-dependent initiation." Here, we use massively systematic transcript end readout (MASTER) to detect and quantify RNA 5'-ends generated by primer-dependent initiation for ∼410 (∼1,000,000) promoter sequences in E. coli The results show primer-dependent initiation in E. coli involves any of the 16 possible dinucleotide primers and depends on promoter sequences in, upstream, and downstream of the primer binding site. The results yield a consensus sequence for primer-dependent initiation, YTSS-2NTSS-1NTSSWTSS+1, where TSS is the transcription start site, NTSS-1NTSS is the primer binding site, Y is pyrimidine, and W is A or T. Biochemical and structure-determination studies show that the base pair (nontemplate-strand base:template-strand base) immediately upstream of the primer binding site (Y:RTSS-2, where R is purine) exerts its effect through the base on the DNA template strand (RTSS-2) through interchain base stacking with the RNA primer. Results from analysis of a large set of natural, chromosomally encoded Ecoli promoters support the conclusions from MASTER. Our findings provide a mechanistic and structural description of how TSS-region sequence hard-codes not only the TSS position but also the potential for epitranscriptomic regulation through primer-dependent transcription initiation.

Massively Systematic Transcript End Readout, "MASTER": Transcription Start Site Selection, Transcriptional Slippage, and Transcript Yields.

We report the development of a next-generation sequencing-based technology that entails construction of a DNA library comprising up to at least 4(7) (∼ 16,000) barcoded sequences, production of RNA transcripts, and analysis of transcript ends and transcript yields (massively systematic transcript end readout, "MASTER"). Using MASTER, we define full inventories of transcription start sites ("TSSomes") of Escherichia coli RNA polymerase for initiation at a consensus core promoter in vitro and in vivo; we define the TSS-region DNA sequence determinants for TSS selection, reiterative initiation ("slippage synthesis"), and transcript yield; and we define effects of DNA topology and NTP concentration. The results reveal that slippage synthesis occurs from the majority of TSS-region DNA sequences and that TSS-region DNA sequences have profound, up to 100-fold, effects on transcript yield. The results further reveal that TSSomes depend on DNA topology, consistent with the proposal that TSS selection involves transcription-bubble expansion ("scrunching") and transcription-bubble contraction ("anti-scrunching").

Provincial policies affecting resident quality of life in Canadian residential long-term care.

BACKGROUND: The precautions and restrictions imposed by the recent Covid-19 pandemic drew attention to the criticality of quality of care in long-term care facilities internationally, and in Canada. They also underscored the importance of residents' quality of life. In deference to the risk mitigation measures in Canadian long-term care settings during Covid-19, some person-centred, quality of life policies were paused, unused, or under-utilised. This study aimed to interrogate these existing but latent policies, to capture their potentiality in terms of positively influencing the quality of life of residents in long-term care in Canada. METHODS: The study analysed policies related to quality of life of long-term care residents in four Canadian provinces (British Columbia, Alberta, Ontario, and Nova Scotia). Three policy orientations were framed utilising a comparative approach: situational (environmental conditions), structural (organisational content), and temporal (developmental trajectories). 84 long term care policies were reviewed, relating to different policy jurisdictions, policy types, and quality of life domains. RESULTS: Overall, the intersection of jurisdiction, policy types, and quality of life domains confirms that some policies, particularly safety, security and order, may be prioritised in different types of policy documents, and over other quality of life domains. Alternatively, the presence of a resident focused quality of life in many policies affirms the cultural shift towards greater person-centredness. These findings are both explicit and implicit, and mediated through the expression of individual policy excerpts. CONCLUSION: The analysis provides substantive evidence of three key policy levers: situations-providing specific examples of resident focused quality of life policy overshadowing in each jurisdiction; structures-identifying which types of policy and quality of life expressions are more vulnerable to dominance by others; and trajectories-confirming the cultural shift towards more person-centredness in Canadian long-term care related policies over time. It also demonstrates and contextualises examples of policy slippage, differential policy weights, and cultural shifts across existing policies. When applied within a resident focused, quality of life lens, these policies can be leveraged to improve extant resource utilisation. Consequently, the study provides a timely, positive, forward-facing roadmap upon which to enhance and build policies that capitalise and enable person-centredness in the provision of long-term care in Canada.

Betacoronavirus-specific alternate splicing.

Viruses can subvert a number of cellular processes including splicing in order to block innate antiviral responses, and many viruses interact with cellular splicing machinery. SARS-CoV-2 infection was shown to suppress global mRNA splicing, and at least 10 SARS-CoV-2 proteins bind specifically to one or more human RNAs. Here, we investigate 17 published experimental and clinical datasets related to SARS-CoV-2 infection, datasets from the betacoronaviruses SARS-CoV and MERS, as well as Streptococcus pneumonia, HCV, Zika virus, Dengue virus, influenza H3N2, and RSV. We show that genes showing differential alternative splicing in SARS-CoV-2 have a similar functional profile to those of SARS-CoV and MERS and affect a diverse set of genes and biological functions, including many closely related to virus biology. Additionally, the differentially spliced transcripts of cells infected by coronaviruses were more likely to undergo intron-retention, contain a pseudouridine modification, and have a smaller number of exons as compared with differentially spliced transcripts in the control groups. Viral load in clinical COVID-19 samples was correlated with isoform distribution of differentially spliced genes. A significantly higher number of ribosomal genes are affected by differential alternative splicing and gene expression in betacoronavirus samples, and the betacoronavirus differentially spliced genes are depleted for binding sites of RNA-binding proteins. Our results demonstrate characteristic patterns of differential splicing in cells infected by SARS-CoV-2, SARS-CoV, and MERS. The alternative splicing changes observed in betacoronaviruses infection potentially modify a broad range of cellular functions, via changes in the functions of the products of a diverse set of genes involved in different biological processes.

An interdomain helix in IRE1α mediates the conformational change required for the sensor's activation.

The unfolded protein response plays an evolutionarily conserved role in homeostasis, and its dysregulation often leads to human disease, including diabetes and cancer. IRE1α is a major transducer that conveys endoplasmic reticulum stress via biochemical signals, yet major gaps persist in our understanding of how the detection of stress is converted to one of several molecular outcomes. It is known that, upon sensing unfolded proteins via its endoplasmic reticulum luminal domain, IRE1α dimerizes and then oligomerizes (often visualized as clustering). Once assembled, the kinase domain trans-autophosphorylates a neighboring IRE1α, inducing a conformational change that activates the RNase effector domain. However, the full details of how the signal is transmitted are not known. Here, we describe a previously unrecognized role for helix αK, located between the kinase and RNase domains of IRE1α, in conveying this critical conformational change. Using constructs containing mutations within this interdomain helix, we show that distinct substitutions affect oligomerization, kinase activity, and the RNase activity of IRE1α differentially. Furthermore, using both biochemical and computational methods, we found that different residues at position 827 specify distinct conformations at distal sites of the protein, such as in the RNase domain. Of importance, an RNase-inactive mutant, L827P, can still dimerize with wildtype monomers, but this mutation inactivates the wildtype molecule and renders leukemic cells more susceptible to stress. We surmise that helix αK is a conduit for the activation of IRE1α in response to stress.

Differentiating children with sepsis with and without acute respiratory distress syndrome using proteomics.

Both sepsis and acute respiratory distress syndrome (ARDS) rely on imprecise clinical definitions leading to heterogeneity, which has contributed to negative trials. Because circulating protein/DNA complexes have been implicated in sepsis and ARDS, we aimed to develop a proteomic signature of DNA-bound proteins to discriminate between children with sepsis with and without ARDS. We performed a prospective case-control study in 12 children with sepsis with ARDS matched to 12 children with sepsis without ARDS on age, severity of illness score, and source of infection. We performed co-immunoprecipitation and downstream proteomics in plasma collected ≤ 24 h of intensive care unit admission. Expression profiles were generated, and a random forest classifier was used on differentially expressed proteins to develop a signature which discriminated ARDS. The classifier was tested in six independent blinded samples. Neutrophil and nucleosome proteins were over-represented in ARDS, including two S100A proteins, superoxide dismutase (SOD), and three histones. Random forest produced a 10-protein signature that accurately discriminated between children with sepsis with and without ARDS. This classifier perfectly assigned six independent blinded samples as having ARDS or not. We validated higher expression of the most informative discriminating protein, galectin-3-binding protein, in children with ARDS. Our methodology has applicability to isolation of DNA-bound proteins from plasma. Our results support the premise of a molecular definition of ARDS, and give preliminary insight into why some children with sepsis, but not others, develop ARDS.

Leaders supporting leaders: Leaders' role in building resilience and psychologically healthy workplaces during the pandemic and beyond.

The COVID-19 pandemic is now endemic and has taken a terrible toll on the health workforce and its leaders. Stress and burnout are rampant, and health workers are leaving in record numbers. Using data collected during the first four waves of the pandemic, and a longitudinal analysis of these data, the authors identify ongoing challenges to health leadership related to building resilience and psychologically healthy workplaces. The article is organized around three questions: What happened during Waves 1 to 4? What did we learn? And what should be done differently? Eight actions emerged around the theme of "leaders supporting leaders": build personal resilience; practice compassionate leadership; model effective interpersonal leadership behaviour; ensure frequent and authentic communication; participate in networks and communities of practice; balance short- and long-term commitments; apply systems thinking; and contribute to a collaborative, national strategy.

Do Residential Long-Term Care Policies Support Family Involvement in Residents' Quality of Life in Four Canadian Provinces?

Family members are essential contributors to the quality of life (QoL) of persons living in residential long-term care (RLTC). This paper analyzes how the system enables or inhibits family involvement with residents in RLTC. Our analysis of 21 policies that regulate long-term care in four Canadian Provinces reveal differences in their portrayal of residents' families. Family roles are characterized procedurally (task-oriented) or relationally (interactive). Operational standards linked to licensing of RLTC homes employ more formal terminology, while RLTC program guidelines, use facilitative language to engage families and build relationships. Examples of orientation procedures, care protocols, living at risk, and end-of-life care reveal inter-provincial variations. We argue that there are opportunities to further engage families within the current regulatory framework and improve their continued contributions in the post-pandemic era.

Computational analysis of 10,860 phenotypic annotations in individuals with SCN2A-related disorders.

PURPOSE: Pathogenic variants in SCN2A cause a wide range of neurodevelopmental phenotypes. Reports of genotype-phenotype correlations are often anecdotal, and the available phenotypic data have not been systematically analyzed. METHODS: We extracted phenotypic information from primary descriptions of SCN2A-related disorders in the literature between 2001 and 2019, which we coded in Human Phenotype Ontology (HPO) terms. With higher-level phenotype terms inferred by the HPO structure, we assessed the frequencies of clinical features and investigated the association of these features with variant classes and locations within the NaV1.2 protein. RESULTS: We identified 413 unrelated individuals and derived a total of 10,860 HPO terms with 562 unique terms. Protein-truncating variants were associated with autism and behavioral abnormalities. Missense variants were associated with neonatal onset, epileptic spasms, and seizures, regardless of type. Phenotypic similarity was identified in 8/62 recurrent SCN2A variants. Three independent principal components accounted for 33% of the phenotypic variance, allowing for separation of gain-of-function versus loss-of-function variants with good performance. CONCLUSION: Our work shows that translating clinical features into a computable format using a standardized language allows for quantitative phenotype analysis, mapping the phenotypic landscape of SCN2A-related disorders in unprecedented detail and revealing genotype-phenotype correlations along a multidimensional spectrum.

Moving beyond 'don't ask, don't tell': Mental health needs of adults with type 1 diabetes in rural and remote regions of British Columbia.

AIMS: To investigate the mental health needs of adults with type 1 diabetes living in rural and remote regions of Interior, British Columbia (BC) and identify factors associated with accessing support. We also explored perspectives around using peer support and digital health strategies for delivering mental health support. METHODS: This study recruited 38 adults with type 1 diabetes to complete a self-report survey and participate in focus groups. We conducted six 90-min focus groups that addressed the following: current and past mental health needs, social media use for type 1 diabetes support, peer supporter recruitment and training, and support delivery features for virtual care platforms. Focus groups were recorded, transcribed, quality checked, coded and analysed to develop themes and subthemes. RESULTS: Four core themes emerged: (1) emotional challenges linked to type 1 diabetes management, (2) unique type 1 diabetes-related concerns in rural and remote communities, (3) previous support experiences and future support needs and (4) diabetes-related mental health support interventions involving peer support and digital health strategies. Existing support services are inadequate in meeting the needs of type 1 diabetes adults in Interior BC. Some have turned towards social media as a way to connect with the type 1 diabetes community for support. CONCLUSIONS: Though type 1 diabetes adults living in rural and remote settings experience distress associated with the ongoing burdens, frustrations and fears of managing a complex chronic condition, many have not been offered support and do not know how to seek services in the present/future. Peer support and digital health strategies are two potential solutions to address this care gap.

Scedar: A scalable Python package for single-cell RNA-seq exploratory data analysis.

In single-cell RNA-seq (scRNA-seq) experiments, the number of individual cells has increased exponentially, and the sequencing depth of each cell has decreased significantly. As a result, analyzing scRNA-seq data requires extensive considerations of program efficiency and method selection. In order to reduce the complexity of scRNA-seq data analysis, we present scedar, a scalable Python package for scRNA-seq exploratory data analysis. The package provides a convenient and reliable interface for performing visualization, imputation of gene dropouts, detection of rare transcriptomic profiles, and clustering on large-scale scRNA-seq datasets. The analytical methods are efficient, and they also do not assume that the data follow certain statistical distributions. The package is extensible and modular, which would facilitate the further development of functionalities for future requirements with the open-source development community. The scedar package is distributed under the terms of the MIT license at https://pypi.org/project/scedar.

A transcriptome-based classifier to determine molecular subtypes in medulloblastoma.

Medulloblastoma is a highly heterogeneous pediatric brain tumor with five molecular subtypes, Sonic Hedgehog TP53-mutant, Sonic Hedgehog TP53-wildtype, WNT, Group 3, and Group 4, defined by the World Health Organization. The current mechanism for classification into these molecular subtypes is through the use of immunostaining, methylation, and/or genetics. We surveyed the literature and identified a number of RNA-Seq and microarray datasets in order to develop, train, test, and validate a robust classifier to identify medulloblastoma molecular subtypes through the use of transcriptomic profiling data. We have developed a GPL-3 licensed R package and a Shiny Application to enable users to quickly and robustly classify medulloblastoma samples using transcriptomic data. The classifier utilizes a large composite microarray dataset (15 individual datasets), an individual microarray study, and an RNA-Seq dataset, using gene ratios instead of gene expression measures as features for the model. Discriminating features were identified using the limma R package and samples were classified using an unweighted mean of normalized scores. We utilized two training datasets and applied the classifier in 15 separate datasets. We observed a minimum accuracy of 85.71% in the smallest dataset and a maximum of 100% accuracy in four datasets with an overall median accuracy of 97.8% across the 15 datasets, with the majority of misclassification occurring between the heterogeneous Group 3 and Group 4 subtypes. We anticipate this medulloblastoma transcriptomic subtype classifier will be broadly applicable to the cancer research and clinical communities.

Ten simple rules for providing effective bioinformatics research support.

Life scientists are increasingly turning to high-throughput sequencing technologies in their research programs, owing to the enormous potential of these methods. In a parallel manner, the number of core facilities that provide bioinformatics support are also increasing. Notably, the generation of complex large datasets has necessitated the development of bioinformatics support core facilities that aid laboratory scientists with cost-effective and efficient data management, analysis, and interpretation. In this article, we address the challenges-related to communication, good laboratory practice, and data handling-that may be encountered in core support facilities when providing bioinformatics support, drawing on our own experiences working as support bioinformaticians on multidisciplinary research projects. Most importantly, the article proposes a list of guidelines that outline how these challenges can be preemptively avoided and effectively managed to increase the value of outputs to the end user, covering the entire research project lifecycle, including experimental design, data analysis, and management (i.e., sharing and storage). In addition, we highlight the importance of clear and transparent communication, comprehensive preparation, appropriate handling of samples and data using monitoring systems, and the employment of appropriate tools and standard operating procedures to provide effective bioinformatics support.