Biology subjects

McLean, C.

Publications and source records attributed to McLean, C..

At least 19 recordsLinked to original sources

bioRxiv2025

Transcriptomic analysis of repeat expansion-ataxias uncovers distinct non-neuronal cell type-specific signatures of disease across the human brain

Hereditary ataxias are a heterogeneous group of neurogenetic conditions characterised by the clinical syndrome of progressive loss of coordination from neurodegeneration of the cerebellum. A commonality across the most prevalent ataxias is the underlying disease mechanism secondary to expansions of short tandem DNA repeats. There is currently an incomplete understanding of the pathogenic mechanisms of these repeat expansion disorders, a core feature of which revolves around RNA-dysregulation. In this study, we used both bulk and single nuclear RNA-sequencing to study post-mortem brain tissue of human donors with a range of repeat-expansion ataxias to reveal further mechanistic insights. We compared post-mortem paired cerebellar and frontal cortex tissue bulk RNA-sequencing data from 23 ataxia patients and 22 sex-, age-matched controls from two brain banks (spinocerebellar ataxia (SCA)1, SCA2, SCA6, SCA7, SCA17, Friedreichs ataxia (FRDA), and 7 cases with unknown molecular diagnoses). We analysed bulk RNA-sequencing data for transcript usage, differential and cell-type-specific expression to transcriptomically profile these diseases. We also generated single nuclear RNA-sequencing data of the cerebellum from donors with SCA1, SCA2, SCA6 and FRDA to decipher changes in cell type proportions in the disease state. Using this approach, we found that: (i) despite the commonalities in the genetics of ataxia, there were components of their transcriptional signatures which were distinct; (ii) there were extensive transcriptional changes evident not only in the cerebellum but also the frontal cortex in ataxia cases; (iii) activation of immune and inflammatory pathways, as well as involvement of non-neuronal cell types was a feature of all ataxias to a lesser or greater extent. This study provides a novel resource to understand the mechanisms of disease in ataxia. Furthermore, taken together, these results highlight immune pathways and the role of non-neuronal cell types as early and potentially important therapeutic targets. These findings provide a map of transcriptomic changes in ataxia to further understanding of the underlying pathogenesis.

neuroscience↗

bioRxiv2024

Isoform-level profiling of m6A epitranscriptomic signatures in human brain

The RNA modification N6-methyladenosine (m6A) is highly abundant in the human brain and implicated in neuropsychiatric and neurodegenerative disorders. However, most techniques for studying m6A cannot resolve modifications within RNA isoforms and we lack an isoform-level map of m6A sites in the brain. Profiling m6A within isoforms is therefore a critical step towards understanding the complex mechanisms that underpin brain function and disease. Oxford Nanopore direct RNA sequencing (DRS) can quantify isoform expression, modifications and polyA tail lengths, enabling simultaneous investigation of the transcriptome and epitranscriptome. We applied DRS to three post-mortem human brain regions: prefrontal cortex, caudate nucleus and cerebellum. We identified 57,000 m6A sites within 15,000 isoforms and estimated that >27% of mRNA molecules contained an m6A modification. Our results revealed both isoform- and brain-region-specific patterning of m6A modifications and polyA tail lengths. The prefrontal cortex exhibited a distinctive profile of specifically modified isoforms enriched in excitatory neuron cell types and also had the highest proportion of previously unannotated m6A sites. A population of isoforms were hypermodified with m6A and were associated with excitatory neuron cell types in all three brain regions. We also discovered >15k differentially expressed isoforms, >2k differentially modified m6A sites and 566 isoforms with differential polyA lengths between brain regions. Our study demonstrates the utility of DRS for investigating multiple features of RNA isoforms in the brain and provides new insights into brain region specificity and functioning with implications for neurological development and disease.

genomics↗

bioRxiv2023

Trabid patient mutations impede the axonal trafficking of adenomatous polyposis coli to disrupt neurite growth

Trabid/ZRANB1 missense mutations have been identified in children diagnosed with a range of congenital disorders including reduced brain size, but how Trabid regulates neurodevelopment is not understood. We have characterised these patient mutations in cells and mice to identify a key role for Trabid in the regulation of neurite growth. One of the patient mutations flanked the catalytic cysteine of Trabid and its deubiquitylating (DUB) activity was abrogated. The second variant retained DUB activity, but failed to bind STRIPAK, a large multiprotein assembly implicated in cytoskeleton organisation and neural development. Trabid/ZRANB1 knock-in mice harbouring either of these patient mutations exhibited reduced neuronal and glial cell densities in the brain and a motor deficit consistent with fewer dopaminergic neurons and projections. Mechanistically, both DUB-impaired and STRIPAK-binding-deficient Trabid variants impeded the trafficking of adenomatous polyposis coli (APC) to microtubule plus-ends. Consequently, the formation of neuronal growth cones and the trajectory of neurite outgrowth from mutant midbrain progenitors were severely compromised. We propose that STRIPAK recruits Trabid to deubiquitylate APC, and that in cells with mutant Trabid, APC becomes hyperubiquitylated and mislocalised causing impaired organisation of the cytoskeleton that underlie the neuronal and developmental phenotypes.

cell biology↗

bioRxiv2023

Distribution of ubiquilin 2 and TDP-43 aggregates throughout the CNS in UBQLN2 p.T487I-linked amyotrophic lateral sclerosis and frontotemporal dementia

Mutations in the UBQLN2 gene cause amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). The neuropathology of such UBQLN2-linked cases of ALS/FTD is characterised by aggregates of the ubiquilin 2 protein in addition to aggregates of the transactive response DNA-binding protein of 43 kDa (TDP-43). ALS and FTD without UBQLN2 mutations are also characterised by TDP-43 aggregates, that may or may not colocalise with wildtype ubiquilin 2. Despite this, the relative contributions of TDP-43 and ubiquilin 2 to disease pathogenesis remain largely under-characterised, as does their relative deposition as aggregates across the central nervous system (CNS). Here we conducted multiplex immunohistochemistry of three UBQLN2 p.T487I-linked ALS/FTD cases, three non-UBQLN2-linked (sporadic) ALS cases, and eight non-neurodegenerative disease controls, covering 40 CNS regions. We then quantified ubiquilin 2 aggregates, TDP-43 aggregates, and aggregates containing both proteins in regions of interest to determine how UBQLN2-linked and non-UBQLN2-linked proteinopathy differ. We find that ubiquilin 2 aggregates that are negative for TDP-43 are predominantly small and punctate, and are abundant in the hippocampal formation, spinal cord, all tested regions of neocortex, medulla, and substantia nigra in UBQLN2-linked ALS/FTD but not sporadic ALS. Curiously, the striatum harboured small punctate ubiquilin 2 aggregates in all cases examined, while large diffuse striatal ubiquilin 2 aggregates were specific to UBQLN2-linked ALS/FTD. Overall, ubiquilin 2 is mainly deposited in clinically unaffected regions throughout the CNS such that symptomology in UBQLN2-linked cases maps best to the aggregation of TDP-43.

neuroscience↗

bioRxiv2022

An Empirical Study of ML-based Phenotyping and Denoising for Improved Genomic Discovery

Genome-wide association studies (GWAS) are used to identify genetic variants significantly correlated with a target disease or phenotype as a first step to detect potentially causal genes. The availability of high-dimensional biomedical data in population-scale biobanks has enabled novel machine-learning-based phenotyping approaches in which machine learning (ML) algorithms rapidly and accurately phenotype large cohorts with both genomic and clinical data, increasing the statistical power to detect variants associated with a given phenotype. While recent work has demonstrated that these methods can be extended to diseases for which only low quality medical-record-based labels are available, it is not possible to quantify changes in statistical power since the underlying ground-truth liability scores for the complex, polygenic diseases represented by these medical-record-based phenotypes is unknown. In this work, we aim to empirically study the robustness of ML-based phenotyping procedures to label noise by applying varying levels of random noise to vertical cup-to-disc ratio (VCDR), a quantitative feature of the optic nerve that is predictable from color fundus imagery and strongly influences glaucoma referral risk. We show that the ML-based phenotyping procedure recovers the underlying liability score across noise levels, significantly improving genetic discovery and PRS predictive power relative to noisy equivalents. Furthermore, initial denoising experiments show promising preliminary results, suggesting that improving such methods will yield additional gains.

genetics↗

bioRxiv2022

An untargeted metabolomics approach to characterize dissolved organic matter in groundwater of the Samail Ophiolite

The process of serpentinization supports life on Earth and gives rise to the habitability of other worlds in our Solar System. While numerous studies have provided clues to the survival strategies of microbial communities in serpentinizing environments on the modern Earth, characterizing microbial activity in such environments remains challenging due to low biomass and extreme conditions. Here, we use an untargeted metabolomics approach to characterize dissolved organic matter in groundwater in the Samail Ophiolite, the largest and best characterized example of actively serpentinizing uplifted ocean crust and mantle. We found that dissolved organic matter composition is strongly correlated with both fluid type and microbial community composition, and that the fluids that were most influenced by serpentinization contained the greatest number of unique compounds, none of which could be identified using the current metabolite databases. Using metabolomics in conjunction with metagenomic data, we detected numerous products and intermediates of microbial metabolic processes and identified potential biosignatures of microbial activity, including pigments, porphyrins, quinones, fatty acids, and metabolites involved in methanogenesis. Metabolomics techniques like the ones used in this study may be used to further our understanding of life in serpentinizing environments, and aid in the identification of biosignatures that can be used to search for life in serpentinizing systems on other worlds.

microbiology↗

bioRxiv2022

The mutational landscape of single neurons and oligodendrocytes reveals evidence of inflammation-associated DNA damage in multiple sclerosis

Neuroinflammation has been linked to DNA damage in multiple sclerosis (MS), but its impact on neural cell genomes at nucleotide resolution is unknown. To address this question, we performed single nucleus whole genome sequencing to determine the landscape of somatic mutation in 172 neurons and oligodendrocytes (OLs) extracted from post-mortem brain tissue from 5 MS cases and three controls. We identified two cases with a significant excess of somatic single nucleotide variants (sSNV) in neurons and OLs from MS inflammatory demyelinated lesions. For a case with primary progressive MS, this translated to a 68% increase in sSNV frequency and 32-year equivalent increase in biological age of lesion-resident cells. Mutational signature analysis conducted on all cells revealed that defective DNA repair and transcription-associated DNA damage are important mutagenic mechanism in both neurons and OLs in MS. Our findings provide the first evidence that inflammation in the brains of people with MS is associated with DNA damage, which may have implications for other neurodegenerative diseases and future drug development.

genomics↗

bioRxiv2021

Prefrontal cortex neural compensation during an operant devaluation task

Deficits in goal-directed action are reported in multiple neuropsychiatric conditions, including schizophrenia. However, dysfunction is not always apparent in early stages of schizophrenia, possibly due to neural compensation. We designed a novel devaluation task in which goal-directed action could be guided by stimulus-outcome (S-O) [presumably orbitofrontal cortex (OFC)-mediated] or response-outcome (R-O) associations [presumably prelimbic cortex (PL)-mediated]. We previously found suggestive evidence that OFC and PL could compensate for each other in this task, and we more directly assessed this potential compensation here. In Experiment 1, rats received OFC, PL, combined OFC+PL, or sham lesions and then completed our devaluation task. The OFC+PL lesion group exhibited impaired devaluation. In Experiment 2, rats received cholera-toxin-b (CTb) into OFC and either neurotoxic or sham PL lesions. Rats were then sacrificed on the last training day to double-label for Arc and CTb. We found increased Arc+CTb in mediodorsal thalamus (MD) and increased Arc+ neurons in OFC when PL was lesioned, suggesting that PL lesions lead to a compensatory increased activation of the MD[->]OFC circuit. Our results suggest that our devaluation task can model neural compensation between OFC and PL and this compensation may be regulated by MD. Significance StatementTo detect compensatory responses, behavioral models that use different strategies must be developed to determine if the strategies shift when a brain area or circuit is incapacitated. Neural compensation is commonly observed in human research but only a few models of neural compensation exist, and few identify compensation within the prefrontal cortex. This research is among the first to show neural compensation between prefrontal cortex regions and implicate a thalamocortical circuit in modulating this compensation. Not only will this model provide a way to behaviorally identify subtle neurological shifts, it can also elucidate basic neurological mechanisms that mediate how circuits interact with each other and how dysfunction in one circuit can affect connectivity in other brain areas.

neuroscience↗

bioRxiv2021

Cortical hyperexcitability drives dying forward ALS symptoms and pathology in mice

Amyotrophic lateral sclerosis (ALS) is a progressive fatal disorder caused by degeneration of motor neurons in the cortex and spinal cord. The origin of ALS in the central nervous system is unclear, however cortical hyperexcitability appears as an early and intrinsic feature of ALS and has been linked to degeneration of spinal motor neurons via a dying-forward mechanism. Here, we implement chemogenetics to validate the dying forward hypothesis of ALS in mice. We show that chronic hyperexcitability of corticomotoneurons induced by excitatory chemogenetics results in motor symptoms and core neuropathological hallmarks of ALS, including corticomotoneuron loss, corticospinal tract degeneration and reactive gliosis. Importantly, corticomotoneuron loss was sufficient to drive degeneration of spinal motor neurons and neuromuscular junctions (NMJs), associated with cytoplasmic TAR DNA binding protein 43 (TDP-43) pathology. These findings establish a cortical origin of ALS mediated by neuronal hyperexcitability, consistent with a dying forward mechanism of neurodegeneration.

neuroscience↗

bioRxiv2021

DeepNull: Modeling non-linear covariate effects improves phenotype prediction and association power

Genome-wide association studies (GWAS) examine the association between genotype and phenotype while adjusting for a set of covariates. Although the covariates may have non-linear or interactive effects, due to the challenge of specifying the model, GWAS often neglect such terms. Here we introduce DeepNull, a method that identifies and adjusts for non-linear and interactive covariate effects using a deep neural network. In analyses of simulated and real data, we demonstrate that DeepNull maintains tight control of the type I error while increasing statistical power by up to 20% in the presence of non-linear and interactive effects. Moreover, in the absence of such effects, DeepNull incurs no loss of power. When applied to 10 phenotypes from the UK Biobank (n=370K), DeepNull discovered more hits (+6%) and loci (+7%), on average, than conventional association analyses, many of which are biologically plausible or have previously been reported. Finally, DeepNull improves upon linear modeling for phenotypic prediction (+23% on average).

genetics↗

bioRxiv2021

DeepTrio: Variant Calling in Families Using Deep Learning

Every human inherits one copy of the genome from their mother and another from their father. Parental inheritance helps us understand the transmission of traits and genetic diseases, which often involve de novo variants and rare recessive alleles. Here we present DeepTrio, which learns to analyze child-mother-father trios from the joint sequence information, without explicit encoding of inheritance priors. DeepTrio learns how to weigh sequencing error, mapping error, and de novo rates and genome context directly from the sequence data. DeepTrio has higher accuracy on both Illumina and PacBio HiFi data when compared to DeepVariant. Improvements are especially pronounced at lower coverages (with 20x DeepTrio roughly equivalent to 30x DeepVariant). DeepTrio includes pre-trained models for Illumina WGS, Illumina exome, and PacBio HiFi.

bioinformatics↗

bioRxiv2021

Harmful Algal Bloom-Forming Organism Responds to Nutrient Stress Distinctly From Model Phytoplankton

O_LIResources such as nitrogen (N) and phosphorus (P) play an important role in primary production and constraining phytoplankton bloom dynamics. Models to predict bloom dynamics require mechanistic knowledge of algal metabolic shifts in response to resource limitation. For well-studied model phytoplankton like diatoms, this information is plentiful. However, for less-studied groups such as the raphidophytes, there remain significant gaps in understanding metabolic changes associated with nutrient limitation. C_LIO_LIUsing a novel combination of metabolomics and transcriptomics, we examined how the harmful algal bloom-forming raphidophyte Heterosigma akashiwo shifts its metabolism under N- and P-stress. We chose H. akashiwo because of its ubiquity within estuarine environments worldwide, where bloom dynamics are influenced by N and P availability. C_LIO_LIOur results show that each stress phenotype is distinct in both the allocation of carbon and the recycling of macromolecules. Further, we identified biomarkers of N- and P-stress that may be applied in situ to help modelers and stakeholders manage, predict, and prevent future blooms. C_LIO_LIThese findings provide a mechanistic foundation to model the metabolic traits and trade-offs associated with N- and P-stress in H. akashiwo, and evaluate the extent to which these metabolic responses can be inferred in other phytoplankton groups. C_LI

ecology↗

bioRxiv2021

Matrix-Bound Growth Factors are Released upon Cartilage Compression by an Aggrecan-Dependent Sodium Flux that is Lost in Osteoarthritis

Articular cartilage is a dense extracellular matrix-rich tissue that degrades following chronic mechanical stress, resulting in osteoarthritis (OA). The tissue has low intrinsic repair especially in aged and osteoarthritic joints. Here we describe three pro-regenerative factors; fibroblast growth factor 2 (FGF2), connective tissue growth factor, bound to transforming growth factor-beta (CTGF-TGF{beta}), and hepatoma-derived growth factor (HDGF), that are rapidly released from the pericellular matrix (PCM) of articular cartilage upon mechanical injury. All three growth factors bound heparan sulfate, and were displaced by exogenous NaCl. We hypothesised that sodium, sequestered within the aggrecan-rich matrix, was freed by injurious compression, thereby enhancing the bioavailability of pericellular growth factors. Indeed, growth factor release was abrogated when cartilage aggrecan was depleted by IL-1 treatment, and in severely damaged human osteoarthritic cartilage. A flux in free matrix sodium upon mechanical compression of cartilage was visualised by 23Na magnetic resonance imaging (MRI) just below the articular surface. This corresponded to a region of reduced tissue stiffness, measured by scanning acoustic microscopy and second harmonic generation microscopy, and where Smad2/3 was phosphorylated upon cyclic compression. Our results describe a novel intrinsic repair mechanism, controlled by matrix stiffness and mediated by the free sodium concentration, in which heparan sulfate-bound growth factors are released from cartilage upon injurious load. They identify aggrecan as a depot for sequestered sodium, explaining why osteoarthritic tissue loses its ability to repair. Treatments that restore matrix sodium to allow appropriate release of growth factors upon load are predicted to enable intrinsic cartilage repair in osteoarthritis. Significance StatementOsteoarthritis is the most prevalent musculoskeletal disease, affecting 250 million people worldwide 1. We identify a novel intrinsic repair response in cartilage, mediated by aggrecan-dependent sodium flux, and dependent upon matrix stiffness, which results in the release of a cocktail of pro-regenerative growth factors after injury. Loss of aggrecan in late-stage osteoarthritis prevents growth factor release and likely contributes to disease progression. Treatments that restore matrix sodium in osteoarthritis may recover the intrinsic repair response to improve disease outcome.

cell biology↗

bioRxiv2021

A workflow for simultaneous detection of coding and non-coding transcripts by ribosomal RNA-depleted RNA-Seq.

RNA sequencing offers unprecedented access to the transcriptome. Key to this is the identification and quantification of many different species of RNA from the same sample at the same time. In this study we describe a novel protocol for simultaneous detection of coding and non-coding transcripts using modifications to the Ion Total RNA-Seq kit v2 protocol, with integration of QIASeq FastSelect rRNA removal kit. We report highly consistent sequencing libraries can be produced from both frozen high integrity mouse hippocampal tissue and the more challenging post-mortem human tissue. Removal of rRNA using FastSelect was highly efficient, resulting in less than 1.5% rRNA content in the final library, significantly better than other reported rRNA removal techniques. We identified >30,000 unique transcripts from all samples, including protein-coding genes and many unique species of non-coding RNA, in biologically-relevant proportions. Furthermore, normalized sequencing read count for select genes significantly negatively correlated with Ct values from RT-qPCR analysis from the same samples. These results indicate that this protocol accurately and consistently identifies and quantifies a wide variety of transcripts simultaneously. The highly efficient rRNA depletion, coupled with minimized sample handling and without complicated and high-loss size selection protocols, makes this protocol useful to researchers wishing to investigate whole transcriptomes.

molecular biology↗

bioRxiv2020

A configurable model of the synaptic proteome reveals the molecular mechanisms of disease co-morbidity.

Synapses contain highly complex proteomes which control synaptic transmission, cognition and behaviour. Genes encoding synaptic proteins are associated with neuronal disorders many of which show clinical co-morbidity. Our hypothesis is that there is mechanistic overlap that is emergent from the network properties of the molecular complex. To test this requires a detailed and comprehensive molecular network model. We integrated 57 published synaptic proteomic datasets obtained between 2000 and 2019 that describe over 7000 proteins. The complexity of the postsynaptic proteome is reaching an asymptote with a core set of ~3000 proteins, with less data on the presynaptic terminal, where each new study reveals new components in its landscape. To complete the network, we added direct protein-protein interaction data and functional metadata including disease association. The resulting amalgamated molecular interaction network model is embedded into a SQLite database. The database is highly flexible allowing the widest range of queries to derive custom network models based on meta-data including species, disease association, synaptic compartment, brain region, and method of extraction. This network model enables us to perform in-depth analyses that dissect molecular pathways of multiple diseases revealing shared and unique protein components. We can clearly identify common and unique molecular profiles for co-morbid neurological disorders such as Schizophrenia and Bipolar Disorder and even disease comorbidities which span biological systems such as the intersection of Alzheimers Disease with Hypertension.

systems biology↗

bioRxiv2020

Characterization of Brain-Derived Extracellular Vesicle Lipids in Alzheimer's Disease

Lipid dyshomeostasis is associated with the most common form of dementia, Alzheimers disease (AD). Substantial progress has been made in identifying positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarkers for AD, but they have limited use as front-line, non-invasive diagnostic tools. Small extracellular vesicles (EVs) are released by all cell types and contain an enriched subset of their parental cell molecular composition, including lipids. EVs are released from the brain into the periphery, providing a potential source of tissue and disease specific lipid biomarkers. However, the EV lipidome of the central nervous system (CNS) is currently unknown and the potential of brain-derived EVs (BDEVs) to inform on lipid dyshomeostasis in AD remains unclear. The aim of this study was to reveal the lipid composition of BDEVs in human frontal cortex tissue, and to determine whether BDEVs in AD have altered lipid profiles compared to age-matched neurological controls (NC). Here, using semi-quantitative mass spectrometry, we describe the BDEV lipidome, covering 4 lipid categories, 17 lipid classes and 692 lipid molecules. Frontal cortex-derived BDEVs were enriched in glycerophosphoserine (PS) lipids, a characteristic of small EVs. Here we report that BDEVs are enriched in ether-containing PS lipids. A novel finding that further establishes ether lipids as a feature of EVs. While no significant changes were detected in the frontal cortex in AD, the lipid profile of the BDEVs from this tissue exhibited disease related differences. AD BDEVs had altered glycerophospholipid (GP) and sphingolipid (SP) levels, specifically increased plasmalogen glycerophosphoethanolamine (PE-P) and decreased polyunsaturated fatty acyl containing lipids (PUFAs), and altered amide-linked acyl chain content in sphingomyelin (SM) and ceramide (Cer) lipids relative to vesicles from neurological control subjects. The most prominent alteration being a two-fold decrease in lipid species containing docosahexaenoic acid (DHA). The in-depth lipidome analysis provided in this study highlights the advantage of EVs over more complex tissues for improved detection of dysregulated lipids that may serve as potential biomarkers in the periphery.

molecular biology↗

bioRxiv2019

The Hippo pathway oncoprotein YAP promotes melanoma cell invasion and spontaneous metastasis

Melanoma is a deadly form of skin cancer that accounts for a disproportionally large proportion of cancer-related deaths in younger people. Compared to most other skin cancers, a feature of melanoma is its high metastatic capacity, although molecular mechanisms that confer this are not well understood. The Hippo pathway is a key regulator of organ growth and cell fate that is deregulated in many cancers. To analyse the Hippo pathway in cutaneous melanoma, we generated a transcriptional signature of pathway activity in melanoma cells. Hippo-mediated transcriptional activity varied in melanoma cell lines but failed to cluster with known genetic drivers of melanomagenesis such as BRAF and NRAS mutation status. Instead, it correlated strongly with published gene expression profiles linked to melanoma cell invasiveness. Consistent with this, the central Hippo oncogene, YAP, was both necessary and sufficient for melanoma cell invasion in vitro. In in vivo murine studies, YAP promoted spontaneous melanoma metastasis, whilst the growth of YAP-expressing primary tumours was impeded. Finally, we identified the YAP target genes AXL, THBS1 and CYR61 as key mediators of YAP-induced melanoma cell invasion. These data suggest that the Hippo pathway is a critical regulator of melanoma metastasis.

cancer biology↗

bioRxiv2019

The histone methyltransferase DOT1L prevents antigen-independent differentiation and safeguards epigenetic identity of CD8+ T cells

Cytotoxic T-cell differentiation is guided by epigenome adaptations but how epigenetic mechanisms control lymphocyte development has not been well defined. Here we show that the histone methyltransferase DOT1L, which marks the nucleosome core on active genes, safeguards normal differentiation of CD8+ T cells. T-cell specific ablation of Dot1L resulted in loss of naive CD8+ T cells and premature differentiation towards a memory-like state, independent of antigen exposure and in a cell-intrinsic manner. Without DOT1L, the memory-like CD8+ cells fail to acquire full effector functions in vitro and in vivo. Mechanistically, DOT1L controlled T-cell differentiation and function by ensuring normal T-cell receptor density and signaling, and by maintaining epigenetic identity, in part by indirectly supporting the repression of developmentally-regulated genes. Through our study DOT1L is emerging as a central player in physiology of CD8+ T cells, acting as a barrier to prevent premature differentiation and supporting the licensing of the full effector potential of cytotoxic T cells.

immunology↗