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Hulme, C.

Publications and source records attributed to Hulme, C..

3 recordsLinked to original sources

Kinase-independent activity of DYRK1A promotes viral entry of highly pathogenic human coronaviruses

Identifying host genes essential for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has the potential to reveal novel drug targets and further our understanding of coronavirus disease 2019 (COVID-19). We previously performed a genome-wide CRISPR/Cas9 screen to identify pro-viral host factors for highly pathogenic human coronaviruses. Very few host factors were required by diverse coronaviruses across multiple cell types, but DYRK1A was one such exception. Although its role in coronavirus infection was completely unknown, DYRK1A encodes Dual Specificity Tyrosine Phosphorylation Regulated Kinase 1A and regulates cell proliferation, and neuronal development, among other cellular processes. Interestingly, individuals with Down syndrome overexpress DYRK1A 1.5-fold and exhibit 5-10x higher hospitalization and mortality rates from COVID-19 infection. Here, we demonstrate that DYRK1A regulates ACE2 and DPP4 transcription independent of its catalytic kinase function to support SARS-CoV, SARS-CoV-2, and MERS-CoV entry. We show that DYRK1A promotes DNA accessibility at the ACE2 promoter and a putative distal enhancer, facilitating transcription and gene expression. Finally, we validate that the pro-viral activity of DYRK1A is conserved across species using cells of monkey and human origin and an in vivo mouse model. In summary, we report that DYRK1A is a novel regulator of ACE2 and DPP4 expression that may dictate susceptibility to multiple highly pathogenic human coronaviruses. Whether DYRK1A overexpression contributes to heightened COVID-19 severity in individuals with Down syndrome through ACE2 regulation warrants further future investigation.

microbiology↗

A comprehensive proteomic and bioinformatics analysis of human spinal cord injury plasma identifies proteins associated with the complement cascade and liver function as potential prognostic indicators of neurological outcome

1.1.1. IntroductionSpinal Cord Injury (SCI) is a major cause of disability, with complications post-injury often leading to life-long health issues with need of extensive treatment. Neurological outcome post-SCI can be variable and difficult to predict, particularly in incomplete injured patients. The identification of specific SCI biomarkers in blood, may be able to improve prognostics in the field. This study has utilised proteomic and bioinformatics methodologies to investigate differentially expressed proteins in plasma samples across human SCI cohorts with the aim of identifying prognostic biomarkers and biological pathway alterations that relate to neurological outcome. 1.2. Methods and MaterialsBlood samples were taken, following informed consent, from ASIA impairment scale (AIS) grade C "Improvers" (those who experienced an AIS grade improvement) and "Non-Improvers" (No AIS change), and AIS grade A and D at <2 weeks ("Acute") and approx. 3 months ("Sub-acute") post-injury. The total protein concentration from each sample was extracted, with pooled samples being labelled and non-pooled samples treated with ProteoMiner beads. Samples were then analysed using two 4-plex isobaric tag for relative and absolute quantification (iTRAQ) analyses and a label-free experiment for comparison, before quantifying with mass spectrometry. Data are available via ProteomeXchange with identifiers PXD035025 and PXD035072 for the iTRAQ and label-free experiments respectively. Proteomic datasets were analysed using OpenMS (version 2.6.0). R (version 4.1.4) and in particular, the R packages MSstats (version 4.0.1) and pathview (version 1.32.0) were used for downstream analysis. Proteins of interest identified from this analysis were further validated by enzyme-linked immunosorbent assay (ELISA). 1.3. ResultsThe data demonstrated proteomic differences between the cohorts, with the results from the iTRAQ approach supporting those of the label-free analysis. A total of 79 and 87 differentially abundant proteins across AIS and longitudinal groups were identified from the iTRAQ and label-free analyses, respectively. Alpha-2-macroglobulin (A2M), retinol binding protein 4 (RBP4), serum amyloid A1 (SAA1), Peroxiredoxin 2, Apolipoprotein A1 (ApoA1) and several immunoglobulins were identified as bio-logically relevant and differentially abundant, with potential as individual prognostic biomarkers of neurological outcome. Bioinformatics analyses revealed that the majority of differentially abundant proteins were components of the complement cascade and most interacted directly with the liver. 1.4. ConclusionsMany of the proteins of interest identified using proteomics were detected only in a single group and therefore have potential as a binary (present or absent) biomarkers, RBP4 and PRX-2 in particular. Additional investigations into the chronology of these proteins, and their levels in other tissues (cerebrospinal fluid in particular) are needed to better understand the underlying pathophysiology, including any potentially modifiable targets. Pathway analysis highlighted the complement cascade as being significant across groups of differential functional recovery.

bioinformatics↗

Genome-wide association analyses of individual differences in quantitatively assessed reading- and language-related skills in up to 34,000 people

The use of spoken and written language is a capacity that is unique to humans. Individual differences in reading- and language-related skills are influenced by genetic variation, with twin-based heritability estimates of 30-80%, depending on the trait. The relevant genetic architecture is complex, heterogeneous, and multifactorial, and yet to be investigated with well-powered studies. Here, we present a multicohort genome-wide association study (GWAS) of five traits assessed individually using psychometric measures: word reading, nonword reading, spelling, phoneme awareness, and nonword repetition, with total sample sizes ranging from 13,633 to 33,959 participants aged 5-26 years (12,411 to 27,180 for those with European ancestry, defined by principal component analyses). We identified a genome-wide significant association with word reading (rs11208009, p=1.098 x 10-8) independent of known loci associated with intelligence or educational attainment. All five reading-/language-related traits had robust SNP-heritability estimates (0.13-0.26), and genetic correlations between them were modest to high. Using genomic structural equation modelling, we found evidence for a shared genetic factor explaining the majority of variation in word and nonword reading, spelling, and phoneme awareness, which only partially overlapped with genetic variation contributing to nonword repetition, intelligence and educational attainment. A multivariate GWAS was performed to jointly analyse word and nonword reading, spelling, and phoneme awareness, maximizing power for follow-up investigation. Genetic correlation analysis of multivariate GWAS results with neuroimaging traits identified association with cortical surface area of the banks of the left superior temporal sulcus, a brain region with known links to processing of spoken and written language. Analysis of evolutionary annotations on the lineage that led to modern humans showed enriched heritability in regions depleted of Neanderthal variants. Together, these results provide new avenues for deciphering the biological underpinnings of these uniquely human traits.

genomics↗