Experiences of cardiac care nurses related to the management and delayed removal of trans-radial band of patients at a private tertiary care hospital, Islamabad.

Objectives: To explore the experiences of cardiac care nurses in managing transradial band of patients in a tertiary care setting. METHODS: The exploratory, descriptive, qualitative study was conducted at a private-sector tertiary care hospital in Islamabad, Pakistan, from March to September 2021, and comprised registered cardiac care nurses with >6 months of relevant experience. Data was collected through face-to-face interviews using a semi-structured interview guide. Data was analysed qualitatively using the Creswell and Creswell framework. RESULTS: Of the 10 nurses, 5(50%) were males and 5(50%) were females. In terms of age, 5(50%) were aged <25 years. Cardiac specialisation had been done by 2(20%) nurses, and none of the subjects had formal training related to transradial band. The main theme that emerged from the data was nurses' management of patients with transradial band, and the three categories were nurses' knowledge and practices about transradial band, reasons for delayed transradial band removal, and strategies to minimise complications. CONCLUSIONS: To minimise transradial band-related complications, in-service training of nurses and ensuring a safe nursepatient ratio are necessary.

Prediction of virus-host interactions and identification of hot spot residues of DENV-2 and SH3 domain interactions.

Dengue virus, particularly serotype 2 (DENV-2), poses a significant global health threat, and understanding the molecular basis of its interactions with host cell proteins is imperative for developing targeted therapeutic strategies. This study elucidated the interactions between proline-enriched motifs and Src homology 3 (SH3) domain. The SH3 domain is pivotal in mediating protein-protein interactions, particularly by recognizing and binding to proline-rich regions in partner proteins. Through a computational pipeline, we analyzed the interactions and binding modes of proline-enriched motifs with SH3 domains, identified new potential DENV-2 interactions with the SH3 domain, and revealed potential hot spot residues, underscoring their significance in the viral life cycle. This comprehensive analysis provides crucial insights into the molecular basis of DENV-2 infection, highlighting conserved and serotype-specific interactions. The identified hot spot residues offer potential targets for therapeutic intervention, laying the foundation for developing antiviral strategies against Dengue virus infection. These findings contribute to the broader understanding of viral-host interactions and provide a roadmap for future research on Dengue virus pathogenesis and treatment.

Uncovering domain motif interactions using high-throughput protein-protein interaction detection methods.

Protein-protein interactions (PPIs) are often mediated by short linear motifs (SLiMs) in one protein and domain in another, known as domain-motif interactions (DMIs). During the past decade, SLiMs have been studied to find their role in cellular functions such as post-translational modifications, regulatory processes, protein scaffolding, cell cycle progression, cell adhesion, cell signalling and substrate selection for proteasomal degradation. This review provides a comprehensive overview of the current PPI detection techniques and resources, focusing on their relevance to capturing interactions mediated by SLiMs. We also address the challenges associated with capturing DMIs. Moreover, a case study analysing the BioGrid database as a source of DMI prediction revealed significant known DMI enrichment in different PPI detection methods. Overall, it can be said that current high-throughput PPI detection methods can be a reliable source for predicting DMIs.

Proteome-wide assessment of human interactome as a source of capturing domain-motif and domain-domain interactions.

Protein-protein interactions (PPIs) play a crucial role in various biological processes by establishing domain-motif (DMI) and domain-domain interactions (DDIs). While the existence of real DMIs/DDIs is generally assumed, it is rarely tested; therefore, this study extensively compared high-throughput methods and public PPI repositories as sources for DMI and DDI prediction based on the assumption that the human interactome provides sufficient data for the reliable identification of DMIs and DDIs. Different datasets from leading high-throughput methods (Yeast two-hybrid [Y2H], Affinity Purification coupled Mass Spectrometry [AP-MS], and Co-fractionation-coupled Mass Spectrometry) were assessed for their ability to capture DMIs and DDIs using known DMI/DDI information. High-throughput methods were not notably worse than PPI databases and, in some cases, appeared better. In conclusion, all PPI datasets demonstrated significant enrichment in DMIs and DDIs (p-value <0.001), establishing Y2H and AP-MS as reliable methods for predicting these interactions. This study provides valuable insights for biologists in selecting appropriate methods for predicting DMIs, ultimately aiding in SLiM discovery.

Exploring Viral-Host Protein Interactions as Antiviral Therapies: A Computational Perspective.

The interactions between human and viral proteins are pivotal in viral infection and host immune responses. These interactions traverse different stages of the viral life cycle, encompassing initial entry into host cells, replication, and the eventual deployment of immune evasion strategies. As viruses exploit host cellular machinery for their replication and survival, targeting key protein-protein interactions offer a strategic approach for developing antiviral drugs. This review discusses how viruses interact with host proteins to develop viral-host interactions. In addition, we also highlight valuable resources that aid in identifying new interactions, incorporating high-throughput methods, and computational approaches, ultimately helping to understand how these tools can be effectively utilized to study viral-host interactions.

Digital Knowledge Translation Tools for Disseminating Sexual and Reproductive Health Information to Adolescents: Protocol for an Evidence Gap Map Review.

BACKGROUND: Digital or eHealth knowledge translation (KT) interventions have been identified as useful public health tools, particularly to advance sexual and reproductive health (SRH) among adolescents. Existing literature reviews on digital health interventions for adolescents' SRH demonstrate limitations, including shortcomings in reporting and comprehensiveness that limit the utility and trustworthiness of findings. However, there is a lack of evidence synthesis on the effectiveness of available digital or mobile health KT tools to promote SRH interventions for adolescents. OBJECTIVE: We aim to identify, map, and describe existing empirical evidence on the digital KT tools developed to improve adolescent SRH outcomes globally. METHODS: This study will be conducted using an evidence gap map (EGM) approach to address the objectives, including reviewing relevant literature and a landscape analysis of the outcomes of interest. The following electronic databases will be searched for retrieval of literature: MEDLINE (1946-present), Embase (1974-present), and Global Health (1910-present) via OVID; CINAHL (1936-present) via EBSCOhost; Scopus (1976-present); and Cochrane Library (1993-present) via Wiley. We will include only those studies that focused on adolescents aged 10-19 years and addressed SRH outcomes. We will include experimental studies (randomized or cluster randomized and nonrandomized controlled trials, including quasi-randomized, controlled before-after, and interruptive time series) and observational studies, that is, including prospective cohort and case-control studies. The experimental and observational studies will only be included in the presence of control or comparison arms. Studies with a historical control arm will be excluded. The systematic review software, Covidence (Ventas Health Innovation), will be used to screen and select the studies. Further, 2 independent reviewers will complete the first and second levels of screening of studies and any conflicts arising will be resolved by consensus between the 2 reviewers or by involving the third reviewer. We will conduct the quality assessment of all included studies using the Risk of Bias tool for randomized controlled trials and nonrandomized controlled trials, and AMSTAR2 for systematic reviews. RESULTS: Papers screening, data extraction, and synthesis will be completed by March 2024. We will use EPPI-Mapper (The International Public Policy Observatory) software to generate an online evidence map and to produce the tables and figures for the descriptive report. This EGM review will identify areas with high-quality, evidence-based digital KT tools (for immediate scale and spread) and areas where few or no KT tools exist (for targeted KT tool development and research or policy prioritization). CONCLUSIONS: This protocol focused on mapping eHealth KT tools that have been used in the literature to address SRH among adolescents. This will be the first EGM exercise to map digital KT tools to promote adolescents' SRH and will incorporate a range of published sources. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/55081.

Faecal microbial transfer and complex carbohydrates mediate protection against COPD.

OBJECTIVE: Chronic obstructive pulmonary disease (COPD) is a major cause of global illness and death, most commonly caused by cigarette smoke. The mechanisms of pathogenesis remain poorly understood, limiting the development of effective therapies. The gastrointestinal microbiome has been implicated in chronic lung diseases via the gut-lung axis, but its role is unclear. DESIGN: Using an in vivo mouse model of cigarette smoke (CS)-induced COPD and faecal microbial transfer (FMT), we characterised the faecal microbiota using metagenomics, proteomics and metabolomics. Findings were correlated with airway and systemic inflammation, lung and gut histopathology and lung function. Complex carbohydrates were assessed in mice using a high resistant starch diet, and in 16 patients with COPD using a randomised, double-blind, placebo-controlled pilot study of inulin supplementation. RESULTS: FMT alleviated hallmark features of COPD (inflammation, alveolar destruction, impaired lung function), gastrointestinal pathology and systemic immune changes. Protective effects were additive to smoking cessation, and transfer of CS-associated microbiota after antibiotic-induced microbiome depletion was sufficient to increase lung inflammation while suppressing colonic immunity in the absence of CS exposure. Disease features correlated with the relative abundance of Muribaculaceae, Desulfovibrionaceae and Lachnospiraceae family members. Proteomics and metabolomics identified downregulation of glucose and starch metabolism in CS-associated microbiota, and supplementation of mice or human patients with complex carbohydrates improved disease outcomes. CONCLUSION: The gut microbiome contributes to COPD pathogenesis and can be targeted therapeutically.

Prediction of motif-mediated viral mimicry through the integration of host-pathogen interactions.

One of the mechanisms viruses use in hijacking host cellular machinery is mimicking Short Linear Motifs (SLiMs) in host proteins to maintain their life cycle inside host cells. In the face of the escalating volume of virus-host protein-protein interactions (vhPPIs) documented in databases; the accurate prediction of molecular mimicry remains a formidable challenge due to the inherent degeneracy of SLiMs. Consequently, there is a pressing need for computational methodologies to predict new instances of viral mimicry. Our present study introduces a DMI-de-novo pipeline, revealing that vhPPIs catalogued in the VirHostNet3.0 database effectively capture domain-motif interactions (DMIs). Notably, both affinity purification coupled mass spectrometry and yeast two-hybrid assays emerged as good approaches for delineating DMIs. Furthermore, we have identified new vhPPIs mediated by SLiMs across different viruses. Importantly, the de-novo prediction strategy facilitated the recognition of several potential mimicry candidates implicated in the subversion of host cellular proteins. The insights gleaned from this research not only enhance our comprehension of the mechanisms by which viruses co-opt host cellular machinery but also pave the way for the development of novel therapeutic interventions.

How different viruses perturb host cellular machinery via short linear motifs.

The virus interacts with its hosts by developing protein-protein interactions. Most viruses employ protein interactions to imitate the host protein: A viral protein with the same amino acid sequence or structure as the host protein attaches to the host protein's binding partner and interferes with the host protein's pathways. Being opportunistic, viruses have evolved to manipulate host cellular mechanisms by mimicking short linear motifs. In this review, we shed light on the current understanding of mimicry via short linear motifs and focus on viral mimicry by genetically different viral subtypes by providing recent examples of mimicry evidence and how high-throughput methods can be a reliable source to study SLiM-mediated viral mimicry.

Bioinformatics prediction and screening of viral mimicry candidates through integrating known and predicted DMI data.

Domain-motif interactions (DMIs) represent transient bonds formed when a Short Linear Motif (SLiM) engages a globular domain via a compact contact interface. Understanding the mechanics of DMIs is critical for maintaining diverse regulatory processes and deciphering how various viruses hijack host cellular machinery. However, identifying DMIs through traditional in vitro and in vivo experiments is challenging due to their degenerate nature and small contact areas. Predictions often carry a high rate of false positives, necessitating rigorous in-silico validation before embarking on experimental work. This study assessed the binding energy changes in predicted SLiM instances through in-silico peptide exchange experiment, elucidating how they interact with known 3D DMI complexes. We identified a subset of potential mimicry candidates that exhibited effective binding affinities with native DMI structures, suggesting their potential to be true mimicry candidates. The identified viral SLiMs can be potential targets in developing therapeutics, opening new opportunities for innovative treatments that can be finely tuned to address the complex molecular underpinnings of various diseases. To gain a comprehensive understanding of identified DMIs, it is imperative to conduct further validation through experimental approaches.

TLR7 promotes smoke-induced experimental lung damage through the activity of mast cell tryptase.

Toll-like receptor 7 (TLR7) is known for eliciting immunity against single-stranded RNA viruses, and is increased in both human and cigarette smoke (CS)-induced, experimental chronic obstructive pulmonary disease (COPD). Here we show that the severity of CS-induced emphysema and COPD is reduced in TLR7-deficient mice, while inhalation of imiquimod, a TLR7-agonist, induces emphysema without CS exposure. This imiquimod-induced emphysema is reduced in mice deficient in mast cell protease-6, or when wild-type mice are treated with the mast cell stabilizer, cromolyn. Furthermore, therapeutic treatment with anti-TLR7 monoclonal antibody suppresses CS-induced emphysema, experimental COPD and accumulation of pulmonary mast cells in mice. Lastly, TLR7 mRNA is increased in pre-existing datasets from patients with COPD, while TLR7+ mast cells are increased in COPD lungs and associated with severity of COPD. Our results thus support roles for TLR7 in mediating emphysema and COPD through mast cell activity, and may implicate TLR7 as a potential therapeutic target.

Expression of targets of the RNA-binding protein AUF-1 in human airway epithelium indicates its role in cellular senescence and inflammation.

Introduction: The RNA-binding protein AU-rich-element factor-1 (AUF-1) participates to posttranscriptional regulation of genes involved in inflammation and cellular senescence, two pathogenic mechanisms of chronic obstructive pulmonary disease (COPD). Decreased AUF-1 expression was described in bronchiolar epithelium of COPD patients versus controls and in vitro cytokine- and cigarette smoke-challenged human airway epithelial cells, prompting the identification of epithelial AUF-1-targeted transcripts and function, and investigation on the mechanism of its loss. Results: RNA immunoprecipitation-sequencing (RIP-Seq) identified, in the human airway epithelial cell line BEAS-2B, 494 AUF-1-bound mRNAs enriched in their 3'-untranslated regions for a Guanine-Cytosine (GC)-rich binding motif. AUF-1 association with selected transcripts and with a synthetic GC-rich motif were validated by biotin pulldown. AUF-1-targets' steady-state levels were equally affected by partial or near-total AUF-1 loss induced by cytomix (TNFα/IL1ß/IFNγ/10 nM each) and siRNA, respectively, with differential transcript decay rates. Cytomix-mediated decrease in AUF-1 levels in BEAS-2B and primary human small-airways epithelium (HSAEC) was replicated by treatment with the senescence- inducer compound etoposide and associated with readouts of cell-cycle arrest, increase in lysosomal damage and senescence-associated secretory phenotype (SASP) factors, and with AUF-1 transfer in extracellular vesicles, detected by transmission electron microscopy and immunoblotting. Extensive in-silico and genome ontology analysis found, consistent with AUF-1 functions, enriched RIP-Seq-derived AUF-1-targets in COPD-related pathways involved in inflammation, senescence, gene regulation and also in the public SASP proteome atlas; AUF-1 target signature was also significantly represented in multiple transcriptomic COPD databases generated from primary HSAEC, from lung tissue and from single-cell RNA-sequencing, displaying a predominant downregulation of expression. Discussion: Loss of intracellular AUF-1 may alter posttranscriptional regulation of targets particularly relevant for protection of genomic integrity and gene regulation, thus concurring to airway epithelial inflammatory responses related to oxidative stress and accelerated aging. Exosomal-associated AUF-1 may in turn preserve bound RNA targets and sustain their function, participating to spreading of inflammation and senescence to neighbouring cells.

CRISPR single base-editing: in silico predictions to variant clonal cell lines.

Engineering single base edits using CRISPR technology including specific deaminases and single-guide RNA (sgRNA) is a rapidly evolving field. Different types of base edits can be constructed, with cytidine base editors (CBEs) facilitating transition of C-to-T variants, adenine base editors (ABEs) enabling transition of A-to-G variants, C-to-G transversion base editors (CGBEs) and recently adenine transversion editors (AYBE) that create A-to-C and A-to-T variants. The base-editing machine learning algorithm BE-Hive predicts which sgRNA and base editor combinations have the strongest likelihood of achieving desired base edits. We have used BE-Hive and TP53 mutation data from The Cancer Genome Atlas (TCGA) ovarian cancer cohort to predict which mutations can be engineered, or reverted to wild-type (WT) sequence, using CBEs, ABEs or CGBEs. We have developed and automated a ranking system to assist in selecting optimally designed sgRNA that considers the presence of a suitable protospacer adjacent motif (PAM), the frequency of predicted bystander edits, editing efficiency and target base change. We have generated single constructs containing ABE or CBE editing machinery, an sgRNA cloning backbone and an enhanced green fluorescent protein tag (EGFP), removing the need for co-transfection of multiple plasmids. We have tested our ranking system and new plasmid constructs to engineer the p53 mutants Y220C, R282W and R248Q into WT p53 cells and shown that these mutants cannot activate four p53 target genes, mimicking the behaviour of endogenous p53 mutations. This field will continue to rapidly progress, requiring new strategies such as we propose to ensure desired base-editing outcomes.

Digital health education and training for undergraduate and graduate nursing students: a scoping review protocol.

OBJECTIVE: The objective of this review is to collate and analyze literature reporting on digital health education and training courses, or other pedagogical interventions, for nursing students at the undergraduate and graduate level to identify gaps and inform the development of future educational interventions. INTRODUCTION: In this era of technology-driven health care, upskilling and/or reskilling the nursing workforce is urgently needed for nurses to lead the digital health future and improve patient care. While informatics competency frameworks serve to inform nursing education and practice, they do not address the entire digital health spectrum. INCLUSION CRITERIA: This review will include research studies, theoretical/discussion papers, and reports, as well as gray literature from relevant sources published in the last 10 years. Opinion pieces, editorials, conference proceedings, and papers published in languages other than English will be excluded. METHODS: The JBI methodology for scoping reviews will be followed. Searches will be conducted in Embase, CINAHL, ERIC, MEDLINE, Scopus, and Education Research Complete to retrieve potentially relevant studies. Hand searches of reference lists of included studies will be conducted. Two reviewers will independently screen records against predefined eligibility criteria and consult a third reviewer if conflicts arise. Decisions will be documented using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram. Quantitative data will be analyzed using descriptive statistics. Content analysis will be applied to qualitative data to identify categories and themes. Findings will be synthesized and reported in tables and narrative format. REVIEW REGISTRATION NUMBER: Open Science Framework osf.io/42eug.

RIPK1 kinase-dependent inflammation and cell death contribute to the pathogenesis of COPD.

BACKGROUND: Receptor-interacting protein kinase 1 (RIPK1) is a key mediator of regulated cell death (including apoptosis and necroptosis) and inflammation, both drivers of COPD pathogenesis. We aimed to define the contribution of RIPK1 kinase-dependent cell death and inflammation in the pathogenesis of COPD. METHODS: We assessed RIPK1 expression in single-cell RNA sequencing (RNA-seq) data from human and mouse lungs, and validated RIPK1 levels in lung tissue of COPD patients via immunohistochemistry. Next, we assessed the consequences of genetic and pharmacological inhibition of RIPK1 kinase activity in experimental COPD, using Ripk1 S25D/S25D kinase-deficient mice and the RIPK1 kinase inhibitor GSK'547. RESULTS: RIPK1 expression increased in alveolar type 1 (AT1), AT2, ciliated and neuroendocrine cells in human COPD. RIPK1 protein levels were significantly increased in airway epithelium of COPD patients compared with never-smokers and smokers without airflow limitation. In mice, exposure to cigarette smoke (CS) increased Ripk1 expression similarly in AT2 cells, and further in alveolar macrophages and T-cells. Genetic and/or pharmacological inhibition of RIPK1 kinase activity significantly attenuated airway inflammation upon acute and subacute CS exposure, as well as airway remodelling, emphysema, and apoptotic and necroptotic cell death upon chronic CS exposure. Similarly, pharmacological RIPK1 kinase inhibition significantly attenuated elastase-induced emphysema and lung function decline. Finally, RNA-seq on lung tissue of CS-exposed mice revealed downregulation of cell death and inflammatory pathways upon pharmacological RIPK1 kinase inhibition. CONCLUSIONS: RIPK1 kinase inhibition is protective in experimental models of COPD and may represent a novel promising therapeutic approach.

Rapid separation of bacteria from primary nasal samples using inertial microfluidics.

Microbial populations play a crucial role in human health and the development of many diseases. These diseases often arise from the explosive proliferation of opportunistic bacteria, such as those in the nasal cavity. Recently, there have been increases in the prevalence of these opportunistic pathogens displaying antibiotic resistance. Thus, the study of the nasal microbiota and its bacterial diversity is critical in understanding pathogenesis and developing microbial-based therapies for well-known and emerging diseases. However, the isolation and analysis of these populations for clinical study complicates the already challenging task of identifying and profiling potentially harmful bacteria. Existing methods are limited by low sample throughput, expensive labeling, and low recovery of bacteria with ineffective removal of cells and debris. In this study, we propose a novel microfluidic channel with a zigzag configuration for enhanced isolation and detection of bacteria from human clinical nasal swabs. This microfluidic zigzag channel separates the bacteria from epithelial cells and debris by size differential focusing. As such, pure bacterial cell fractions devoid of large contaminating debris or epithelial cells are obtained. DNA sequencing performed on the separated bacteria defines the diversity and species present. This novel method of bacterial separation is simple, robust, rapid, and cost-effective and has the potential to be used for the rapid identification of bacterial cell populations from clinical samples.

Understanding the sexual and reproductive health needs of immigrant adolescents in Canada: A qualitative study.

Background: Literature suggests that immigrant adolescents receive limited sexual and reproductive health (SRH) education and rarely utilize SRH services in Canada. This study sought to explore the SRH information needs of immigrant adolescents in the province of Alberta. Methods: A qualitative descriptive methodology was undertaken to conduct 21 individual interviews with immigrant adolescents in Alberta. Results: A total of four themes emerged from the interviews: (1) Barriers to SRH; (2) needs of adolescents regarding SRH; (3) sources of knowledge; and (4) strategies to improve SRH. Our findings document the conflicting needs and preferences between adolescents and their parents regarding access to SRH resources and services. Discussion: Adolescents often felt unprepared to deal with their SRH issues due to socio-cultural barriers and conflicts with their parents' conservative attitude toward SRH concerns. Structural barriers to accessing SRH resources and services were also reported, including the location and cost of services. As a result, the majority of adolescents relied on digital methods to receive SRH information. Conclusion: This study highlights that future research and SRH service provider efforts need to remain cognizant of the positionality of immigrant adolescents and explore innovative ways to deliver SRH resources and services that meet their unique needs.

Racism and the mental health of East Asian diasporas in North America: a scoping review.

BACKGROUND: The COVID-19 pandemic heightened anti-Asian racism towards East Asian diasporas in North America. Experiences of racism encountered by East Asian communities have been documented to negatively impact their mental health. METHODS: A scoping review was undertaken following Arksey and O'Malley's (2005) methodology to (a) map the foci of literature on racism and the mental health of East Asian diasporas in North America and (b) identify gaps in the current literature. RESULTS: A total of 1309 articles were identified in May 2021. Based on the inclusion criteria, 35 records were included. Two distinct mental health foci were found: mental health outcomes and mental healthcare access and utilization. The majority (n = 22) of the articles focused on racism at the interpersonal level. Six articles provided anti-racism solutions at the individual level, such as overcoming biases. Five articles targeted anti-racism solutions from both the individual and institutional levels, while 1 article addressed barriers at the institutional level, such as dismantling sanctioned power hierarchies. CONCLUSION: The expanding knowledge base on COVID-19-related racial discrimination is reminiscent of previous literature examining the history of anti-Asian racism in North America. Greater attention is needed to navigate impactful anti-racism solutions for East Asian populations' mental health in North America.

Increased SARS-CoV-2 Infection, Protease, and Inflammatory Responses in Chronic Obstructive Pulmonary Disease Primary Bronchial Epithelial Cells Defined with Single-Cell RNA Sequencing.

Rationale: Patients with chronic obstructive pulmonary disease (COPD) develop more severe coronavirus disease (COVID-19); however, it is unclear whether they are more susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and what mechanisms are responsible for severe disease. Objectives: To determine whether SARS-CoV-2 inoculated primary bronchial epithelial cells (pBECs) from patients with COPD support greater infection and elucidate the effects and mechanisms involved. Methods: We performed single-cell RNA sequencing analysis on differentiated pBECs from healthy subjects and patients with COPD 7 days after SARS-CoV-2 inoculation. We correlated changes with viral titers, proinflammatory responses, and IFN production. Measurements and Main Results: Single-cell RNA sequencing revealed that COPD pBECs had 24-fold greater infection than healthy cells, which was supported by plaque assays. Club/goblet and basal cells were the predominant populations infected and expressed mRNAs involved in viral replication. Proteases involved in SARS-CoV-2 entry/infection (TMPRSS2 and CTSB) were increased, and protease inhibitors (serpins) were downregulated more so in COPD. Inflammatory cytokines linked to COPD exacerbations and severe COVID-19 were increased, whereas IFN responses were blunted. Coexpression analysis revealed a prominent population of club/goblet cells with high type 1/2 IFN responses that were important drivers of immune responses to infection in both healthy and COPD pBECs. Therapeutic inhibition of proteases and inflammatory imbalances reduced viral titers and cytokine responses, particularly in COPD pBECs. Conclusions: COPD pBECs are more susceptible to SARS-CoV-2 infection because of increases in coreceptor expression and protease imbalances and have greater inflammatory responses. A prominent cluster of IFN-responsive club/goblet cells emerges during infection, which may be important drivers of immunity. Therapeutic interventions suppress SARS-CoV-2 replication and consequent inflammation.

SLiM-Enrich: computational assessment of protein-protein interaction data as a source of domain-motif interactions.

Many important cellular processes involve protein-protein interactions (PPIs) mediated by a Short Linear Motif (SLiM) in one protein interacting with a globular domain in another. Despite their significance, these domain-motif interactions (DMIs) are typically low affinity, which makes them challenging to identify by classical experimental approaches, such as affinity pulldown mass spectrometry (AP-MS) and yeast two-hybrid (Y2H). DMIs are generally underrepresented in PPI networks as a result. A number of computational methods now exist to predict SLiMs and/or DMIs from experimental interaction data but it is yet to be established how effective different PPI detection methods are for capturing these low affinity SLiM-mediated interactions. Here, we introduce a new computational pipeline (SLiM-Enrich) to assess how well a given source of PPI data captures DMIs and thus, by inference, how useful that data should be for SLiM discovery. SLiM-Enrich interrogates a PPI network for pairs of interacting proteins in which the first protein is known or predicted to interact with the second protein via a DMI. Permutation tests compare the number of known/predicted DMIs to the expected distribution if the two sets of proteins are randomly associated. This provides an estimate of DMI enrichment within the data and the false positive rate for individual DMIs. As a case study, we detect significant DMI enrichment in a high-throughput Y2H human PPI study. SLiM-Enrich analysis supports Y2H data as a source of DMIs and highlights the high false positive rates associated with naïve DMI prediction. SLiM-Enrich is available as an R Shiny app. The code is open source and available via a GNU GPL v3 license at: https://github.com/slimsuite/SLiMEnrich. A web server is available at: http://shiny.slimsuite.unsw.edu.au/SLiMEnrich/.