Biology subjects

Kerr, L.

Publications and source records attributed to Kerr, L..

9 recordsLinked to original sources

bioRxiv2025

Spatial density and habitat associations of Atlantic Cod on the Northeastern US Continental Shelf

The spatial distribution of the Atlantic cod (Gadus morhua) stock is shaped in part by several habitat and oceanographic variables. In this study, Vector Autoregressive Spatio-Temporal (VAST) models were used to combine data from multiple survey programs to hindcast seasonal spatial densities of three size classes of cod within the Northeast US Continental Shelf from 1982 to 2021. Bottom habitat characteristics, bottom water temperature, depth, and basin-averaged climate indices were included as density covariates. Depth, bottom temperature, and gravel sediments were strongly associated with spatial density. The relative abundance of all size classes generally decreased throughout the time series. Model outputs highlighted patches with persistently high spatial density despite range losses and declining abundance. This aligns with the basin model, a spatial dynamic frequently reported in collapsed fish stocks. The availability of habitat with suitable depth and temperature will likely be reduced under current projections of bottom water temperature, further endangering the recovery of the stock. Improving our understanding of cod habitat preferences and variation in spatial density will be important for future management efforts.

ecology↗

bioRxiv2024

Whole Virion Proteomics of HCMV Reveals that gpUL141 is a Virion Component that Regulates Envelope Glycoprotein Composition to Protect Against Humoral Immunity

Human cytomegalovirus (HCMV) is a clinically important herpesvirus that has co-evolved for millions of years with its human host, and establishes lifelong persistent infection. A substantial proportion of its 235kb genome is dedicated to manipulating host immunity through targeting antiviral host proteins for degradation or relocalisation. Quantitative proteomics of the infected cell has extensively characterised these processes, but the cell-free virion has been less well studied. We therefore carried out proteomic analysis of a clinical HCMV strain (Merlin) virion. This revealed 18 novel components, including the viral protein gpUL141, which is recognised as an NK immune-evasin that targets several host proteins (CD155, CD112, and TRAILR) when expressed within the cell. Co-Immunoprecipitation of gpUL141 from virions identified interactions with viral entry glycoproteins from the trimer (gH/gL/gO), pentamer (gH/gL/UL128/UL130/UL131A), and gH/gpUL116 complexes, as well as gB. Only interactions with gH/gB occurred in the absence of other viral proteins. Analysis supported a model in which gpUL141 homodimers independently interacted with separate gB/gH-containing complexes. gpUL141 encodes an ER retention domain that restricts trafficking through the ER/golgi, and limited the transport of glycoprotein complexes bound by gpUL141. As a result, gpUL141 reduced levels of multiple glycoprotein complexes on the infected cell surface as well as in the virion. This reduced syncytium formation, inhibited antibody-dependent cellular cytotoxicity (ADCC), and reduced susceptibility to neutralising antibodies. Thus, gpUL141 represents an immune-evasin that not only targets host proteins to limit NK-cell attack, but also alters the trafficking of multiple viral glycoprotein complexes in order to evade humoral immunity. SignificanceThe large number of immune-modulators encoded by HCMV has led to it becoming a paradigm for pathogen-mediated immune-modulation. These mechanisms have informed on virus pathogenesis, the evolution and function of host defences, and identified therapeutic targets. Previously discovered immune-evasins functioned by modifying host proteins. gpUL141 represents a novel strategy in which multiple immunological functions are targeted through manipulating eight different viral entry glycoproteins, via interactions with two proteins common to multiple complexes. Entry glycoproteins define virus tropism, mechanisms of infection and spread, and susceptibility to neutralising and non-neutralising antibody activities, yet UL141 is frequently mutated in passaged viruses. This demonstrates the need to work with virus strains encoding the complete repertoire of viral accessory proteins during preclinical therapeutic development.

microbiology↗

bioRxiv2022

DNMT3B PWWP mutations cause hypermethylation of heterochromatin

The correct establishment of DNA methylation patterns is vital for mammalian development and is achieved largely by the de novo DNA methyltransferases DNMT3A and DNMT3B. Mutations in DNMT3B can cause immunodeficiency-centromeric instability-facial anomalies type 1 (ICF1) syndrome which is characterised by hypomethylated heterochromatin. However, in the genome, DNMT3B primarily localises to actively transcribing gene bodies through the interaction of its PWWP domain with the histone modification H3K36me3 and it is unclear how it is recruited to heterochromatin. Here we show that in DNMT3B knockout cells, loss of DNA methylation predominantly occurs in heterochromatic domains marked by H3K9me3. We also find that PWWP domain mutations which disrupt DNMT3Bs interaction with H3K36me3 result in striking increases of DNA methylation in H3K9me3-marked heterochromatin. Gains of methylation are also observed when the PWWP domain of DNMT3B is deleted. In contrast, we find that the ICF1 syndrome-causing PWWP mutation, S270P, does not result in hypermethylation of heterochromatin and destabilises the protein. We also show that removal of the N-terminus region of DNMT3B affects its recruitment to chromatin and ability to methylate H3K9me3 marked regions. Our results suggest that DNMT3B is recruited to H3K9me3 marked heterochromatin in a PWWP-independent manner and that this recruitment is facilitated by the proteins N-terminus. More generally, we suggest that DNMT3B plays a role in DNA methylation homeostasis at heterochromatin, a process which is disrupted in ICF syndrome, cancer and aging.

genetics↗

bioRxiv2022

Genome-wide single-molecule analysis of long-read DNA methylation reveals heterogeneous patterns at heterochromatin

High-throughput sequencing technology is central to our current understanding of the human methylome. The vast majority of studies use chemical conversion to analyse bulk-level patterns of DNA methylation across the genome from a population of cells. While this technology has been used to probe single-molecule methylation patterns, such analyses are limited to short reads of a few hundred basepairs. DNA methylation can also be directly detected using Nanopore sequencing which can generate reads measuring megabases in length. However, thus far these analyses have largely focused on bulk-level assessment of DNA methylation. Here, we analyse DNA methylation in single Nanopore reads with a mean length of 24.6kb, to show that bulk-level metrics underestimate large-scale heterogeneity in the methylome. We use the correlation in methylation state between neighbouring sites to quantify single-molecule heterogeneity and find that heterogeneity varies significantly across the human genome, with some regions having heterogeneous methylation patterns at the single-molecule level and others possessing more homogeneous methylation patterns. By comparing the genomic distribution of the correlation to epigenomic annotations, we find that the greatest heterogeneity in single-molecule patterns is observed within heterochromatic partially methylated domains (PMDs). In contrast, reads originating from euchromatic regions and gene bodies have more ordered DNA methylation patterns. By analysing the patterns of single molecules in more detail, we show the existence of a 185bp periodicity in DNA methylation that accounts for some of the heterogeneity we uncover in long single-molecule DNA methylation patterns. We find that this periodic structure is partially masked in bulk data in a manner that is consistent with imperfect phasing of nucleosomes between molecules. Our findings demonstrate the power of single-molecule analysis of long-read data to understand the structure of the human methylome.

bioinformatics↗

bioRxiv2021

Larval densities of the protected Striped lychnis moth Shargacucullia lychnis (Lepidoptera: Noctuidae) in Buckinghamshire

Natural history information is essential for ecologically-relevant inferences about (adaptive) responses in organismal biology. Yet, natural history data can be difficult to obtain, particularly for the developmental stages of holometabolous insects. This gap can compromise our ability to design controlled experiments that provide useful understanding of insect responses to changing environments and precludes our ability to understand how natural populations may respond to unpredictable climatic changes in their natural environment. In this study, we collated data from previous reports from the Butterfly Conservation Upper Thames Branch on the larval population density of Shargacucullia lychnis (Lepidoptera: Noctuidae) in Buckinghamshire. In the UK, S. lychnis is a protected species, for which natural history information can be invaluable for its effective conservation. We report here that the natural range of larval densities observed for S. lychnis across locations and years is 0.001 to 6.417 larvae per spike. More importantly, S. lychnis larval density has overall declined from 1996 to 2020, which could support previous reports of a contraction in population range for this species. Overall, this study provides invaluable information about larval population density for an important protected Lepidopteran species of the UK.

zoology↗

bioRxiv2021

Cluster mean-field theory accurately predicts statistical properties of large-scale DNA methylation patterns

The accurate establishment and maintenance of DNA methylation patterns is vital for mammalian development and disruption to these processes causes human disease. Our understanding of DNA methylation mechanisms has been facilitated by mathematical modelling, particularly stochastic simulations. Mega-base scale variation in DNA methylation patterns is observed in development, cancer and ageing and the mechanisms generating these patterns are little understood. However, the computational cost of stochastic simulations prevents them from modelling such large genomic regions. Here we test the utility of three different mean-field models to predict large-scale DNA methylation patterns. By comparison to stochastic simulations, we show that a cluster mean-field model accurately predicts the statistical properties of steady-state DNA methylation patterns, including the mean and variance of methylation levels calculated across a system of CpG sites, as well as the covariance and correlation of methylation levels between neighbouring sites. We also demonstrate that a cluster mean-field model can be used within an approximate Bayesian computation framework to accurately infer model parameters from data. As mean-field models can be solved numerically in a few seconds, our work demonstrates their utility for understanding the processes underpinning large-scale DNA methylation patterns.

systems biology↗

bioRxiv2021

Novel antibiotic mode of action by repression of promoter isomerisation

Rising levels of antibiotic resistance dictate that new antibiotics with novel modes of action must be found. Here, we investigated the mode of action of a novel antibiotic that is a member of a family of synthetic DNA minor groove binding (MGB) molecules. MGB-BP-3 has successfully completed a Phase II clinical trial in humans as an orally administered drug for the treatment of chronic Clostridioides (Clostridium) difficile infections, where it outperformed the existing benchmark (vancomycin). MGB-BP-3 is active against a variety of Gram-positive pathogens including Staphylococcus aureus, which was used as the model for this study. The transcriptomic response of S. aureus to MGB-BP-3 identified downregulated promoters. DNase I and permanganate footprinting demonstrated binding to essential SigA promoters and the inhibition of promoter isomerisation by RNA polymerase holoenzyme. Promoters controlling DNA replication and peptidoglycan biosynthesis are amongst those affected by MGB-BP-3. Thus, MGB-BP-3 binds to and inhibits multiple essential promoters on the S. aureus chromosome, suggesting that evolution of resistance by drug target mutation should be unlikely. In confirmation, laboratory-directed evolution against sub-inhibitory concentrations of MGB-BP-3 resulted in no resistance whereas resistance to the single target RNA-polymerase inhibitor rifampicin arose rapidly.

molecular biology↗

bioRxiv2020

Deficiency of the splicing factor RBM10 limits EGFR inhibitor response in EGFR mutant lung cancer

Molecularly targeted cancer therapy has improved outcomes for cancer patients with targetable oncoproteins, such as mutant epidermal growth factor receptor (EGFR) in lung cancer. Yet, long-term patient survival remains limited because treatment responses are typically incomplete. One potential explanation for the lack of complete and durable responses is that oncogene-driven cancers with activating mutations in the EGFR often harbor additional co-occurring genetic alterations. This hypothesis remains untested for most genetic alterations that co-occur with mutant EGFR. Here, we report the functional impact of inactivating genetic alteration of the mRNA splicing factor RBM10 that co-occur with mutant EGFR. RBM10 deficiency decreased EGFR inhibitor efficacy in patient-derived EGFR mutant tumor models. RBM10 modulated mRNA alternative splicing of the mitochondrial apoptotic regulator Bcl-x to regulate tumor cell apoptosis during treatment. Genetic inactivation of RBM10 diminished EGFR inhibitor-mediated apoptosis by decreasing the ratio of Bcl-xS-(pro-apoptotic)-to-Bcl-xL(anti-apoptotic) Bcl-x isoforms. RBM10 deficiency was a biomarker of poor response to EGFR inhibitor treatment in clinical samples. Co-inhibition of Bcl-xL and mutant EGFR overcame resistance induced by RBM10 deficiency. This study sheds light on the role of co-occurring genetic alterations, and on the impact of splicing factor deficiency in the modulation of sensitivity to targeted kinase inhibitor cancer therapy.

cancer biology↗

bioRxiv2019

Differential transcription of expanded gene families in central carbon metabolism of Streptomyces coelicolor A3(2)

BackgroundStreptomycete bacteria are prolific producers of specialised metabolites, many of which have clinically relevant bioactivity. A striking feature of their genomes is the expansion of gene families that encode the same enzymatic function. Genes that undergo expansion events, either by horizontal gene transfer or duplication, can have a range of fates: genes can be lost, or they can undergo neo-functionalisation or sub-functionalisation. To test whether expanded gene families in Streptomyces exhibit differential expression, an RNA-Seq approach was used to examine cultures of wild-type Streptomyces coelicolor grown with either glucose or tween as the sole carbon source. ResultsRNA-Seq analysis showed that two-thirds of genes within expanded gene families show transcriptional differences when strains were grown on tween compared to glucose. In addition, expression of specialised metabolite gene clusters (actinorhodin, isorenieratane, coelichelin and a cryptic NRPS) was also influenced by carbon source. ConclusionsExpression of genes encoding the same enzymatic function had transcriptional differences when grown on different carbon sources. This transcriptional divergence enables partitioning to function under different physiological conditions. These approaches can inform metabolic engineering of industrial Streptomyces strains and may help develop cultivation conditions to activate the so-called silent biosynthetic gene clusters.

microbiology↗