Biology subjects

Harris, L.

Publications and source records attributed to Harris, L..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Spatial Transcriptomic Sequencing of a DIPG-infiltrated Brainstem reveals Key Invasion Markers and Novel Ligand-Receptor Pairs contributing to Tumour to TME Crosstalk

Emerging spatially-resolved sequencing technologies offer unprecedented possibilities to study cellular functionality and organisation, transforming our understanding of health and disease. The necessity to understand healthy and diseased tissues in its entirety becomes even more evident for the human brain, the most complex organ in the body. The brains cellular architecture and corresponding functions are tightly regulated. However, when intercellular communications are altered by pathologies, such as brain cancer, these microenvironmental interactions are disrupted. DIPG is a brainstem high-grade glioma arising in young children and is universally fatal. Major disease obstacles include intratumoural genetic and cellular heterogeneity as well as a highly invasive phenotype. Recent breakthrough studies have highlighted the vital oncogenic capacity of brain cancer cells to functionally interact with the central nervous system (CNS). This CNS-crosstalk crucially contributes to tumour cell invasion and disease progression. Ongoing worldwide efforts seek to better understand these cancer-promoting CNS interactions to develop more effective DIPG anti-cancer therapies. In this study, we performed spatial transcriptomic analysis of a complete tumour-infiltrated brainstem from a single DIPG patient. Gene signatures from ten sequential tumour regions were analysed to assess disease progression and to study DIPG cell interactions with the tumour microenvironment (TME). We leveraged this unique DIPG dataset to evaluate genes significantly correlated with invasive tumour distal regions versus the proximal tumour initiation site. Furthermore, we assessed novel ligand-receptor pairs that actively promote DIPG tumour progression via crosstalk with endothelial, neuronal and immune cell communities, which can be utilised to support future research efforts in this area of high unmet need.

cancer biology↗

bioRxiv2024

Reversal of Obesity by Enhancing Slow-wave Sleep via a Prokineticin Receptor Neural Circuit

Obese subjects often exhibit hypersomnia accompanied by severe sleep fragmentation, while emerging evidence suggests that poor sleep quality promotes overeating and exacerbates diet-induced obesity (DIO). However, the neural circuit and signaling mechanism underlying the reciprocal control of appetite and sleep is yet not elucidated. Here, we report a neural circuit where prokineticin receptor 2 (PROKR2)-expressing neurons within the parabrachial nucleus (PBN) of the brainstem received direct projections from neuropeptide Y receptor Y2 (NPY2R)-expressing neurons within the lateral preoptic area (LPO) of the hypothalamus. The RNA-Seq results revealed Prokr2 in the PBN is the most regulated GPCR signaling gene that is responsible for comorbidity of obesity and sleep dysfunction. Furthermore, those NPY2RLPO neurons are minimally active during NREM sleep and maximally active during wakefulness and REM sleep. Activation of the NPY2RLPO[->]PBN circuit or the postsynaptic PROKR2PBN neurons suppressed feeding of a high-fat diet and abrogated morbid sleep patterns in DIO mice. Further studies showed that genetic ablation of the PROKR2 signaling within PROKR2PBN neurons alleviated the hyperphagia and weight gain, and restored sleep dysfunction in DIO mice. We further discovered pterostilbene, a plant-derived stilbenoid, is a powerful anti-obesity and sleep-improving agent, robustly suppressed hyperphagia and promoted reconstruction of a healthier sleep architecture, thereby leading to significant weight loss. Collectively, our results unveil a neural mechanism for the reciprocal control of appetite and sleep, through which pterostilbene, along with a class of similarly structured compounds, may be developed as effective therapeutics for tackling obesity and sleep disorders.

neuroscience↗

bioRxiv2023

Polycomb Repressive Complex 2 is critical for mouse cortical glutamatergic neuron development

The Polycomb Repressive Complex 2 (PRC2) regulates corticogenesis, yet the consequences of mutations to this epigenetic modifier in the mature brain are poorly defined. Importantly, PRC2 core genes are haploinsufficient and causative for several human neurodevelopmental disorders. To address the role of PRC2 in mature cortical structure and function, we conditionally mutated the PRC2 gene Eed in the developing mouse telencephalon. Adult homozygotes displayed smaller forebrain structures. Single-nucleus transcriptomics revealed glutamatergic neurons were particularly affected, exhibiting dysregulation of cortical layer-specific profiles, accompanied by aberrations in neuronal morphology and connectivity. Incredibly, homozygous mice performed well on challenging cognitive tasks. In contrast, heterozygous mice did not exhibit anatomical or behavioral phenotypes but displayed dysregulation of neuronal genes and altered neuronal morphology that was strikingly different from homozygous phenotypes. Collectively, we demonstrate how alterations to PRC2 function shape the mature brain and reveal a dose-specific role for PRC2 in determining glutamatergic neuron identity.

developmental biology↗

bioRxiv2023

Small variant benchmark from a complete assembly of X and Y chromosomes

The sex chromosomes contain complex, important genes impacting medical phenotypes, but differ from the autosomes in their ploidy and large repetitive regions. To evaluate variant detection on chromosomes X and Y, we created an 111,725 variant benchmark for the Genome in a Bottle HG002 reference material. We show how complete assemblies can expand benchmarks to difficult regions, but highlight remaining challenges benchmarking complex gene conversions, copy number variable gene arrays, and human satellites.

genomics↗

bioRxiv2023

Evaluating proteomics imputation methods with improved criteria

Quantitative measurements produced by tandem mass spectrometry proteomics experiments typically contain a large proportion of missing values. This missingness hinders reproducibility, reduces statistical power, and makes it difficult to compare across samples or experiments. Although many methods exist for imputing missing values in proteomics data, in practice, the most commonly used methods are among the worst performing. Furthermore, previous benchmarking studies have focused on relatively simple measurements of error, such as the mean-squared error between the imputed and the held-out observed values. Here we evaluate the performance of a set of commonly used imputation methods using three practical, "downstream-centric" criteria, which measure the ability of imputation methods to reconstruct differentially expressed peptides, identify new quantitative peptides, and improve peptide lower limit of quantification. Our evaluation spans several experiment types and acquisition strategies, including datadependent and data-independent acquisition. We find that imputation does not necessarily improve the ability to identify differentially expressed peptides, but that it can identify new quantitative peptides and improve peptide lower limit of quantification. We find that MissForest is generally the best performing method per our downstream-centric criteria. We also argue that exisiting imputation methods do not properly account for the variance of peptide quantifications and highlight the need for methods that do.

bioinformatics↗

bioRxiv2022

A community driven GWAS summary statistics standard

Summary statistics from genome-wide association studies (GWAS) represent a huge potential for research. A challenge for researchers in this field is the access and sharing of summary statistics data due to a lack of standards for the data content and file format. For this reason, the GWAS Catalog hosted a series of meetings in 2021 with summary statistics stakeholders to guide the development of a standard format. The key requirements from the stakeholders were for a standard that contained key data elements to be able to support a wide range of data analyses, required low bioinformatics skills for file access and generation, to have easily accessible metadata, and unambiguous and interoperable data. Here, we define the specifications for the first version of the GWAS-SSF format, which was developed to meet the requirements discussed with the community. GWAS-SSF consists of a tab-separated data file with well-defined fields and an accompanying metadata file.

bioinformatics↗

bioRxiv2022

Reversal of obesogenic feeding and hypometabolism by a bifurcating GABAergic neural circuit

Diet-induced obesity is characterized by unsatiated consumption of energy-dense diets and impaired metabolism, whereby anti-obesity effect of the high-level of circulating leptin is unknowingly blunted. Emerging evidence suggests that the leptin receptor (LepR) signaling system, residing within the agouti-related protein (AgRP) neurons of the hypothalamus, critically contributes to obesogenic feeding, nutrient partitioning, and energy metabolism. However, the neural circuit mechanism underlying the leptin-dependent control of obesogenic feeding and energy balance remains largely elusive. Here, we show that two distinct subgroups of LepR-expressing AgRP neurons send non-collateral, GABAergic projections to the dorsomedial hypothalamic nucleus (DMH) and to the medial part of the medial preoptic nucleus (MPO) for the differential control of metabolic homeostasis and obesogenic feeding, respectively. We found that the AgRPLepR-DMH neural circuit plays a significant role in leptin-dependent control of metabolic homeostasis through the 3-containing GABAA receptor signaling on the melanocortin 4 receptor neurons within the DMH (MC4RDMH). In contrast, the AgRPLepR-MPO neural circuit elicits dominant effects on the appetitive response to high-fat diet through the 2-containing GABAA receptors on the MC4RMPO neurons. Consistent with these behavioral results, the post-synaptic GABAA neurons located within the DMH and MPO displayed differentiated firing responses under various feeding and nutrient conditions. Our results demonstrate that these novel GABAergic neural circuits exert differentiated control of metabolic hemostasis and obesogenic feeding via distinct post-synaptic targets of leptin-responsive AgRP neurons. The findings of two genetically and anatomically distinct GABAA receptor signaling pathways within the DMH and MPO would undoubtedly accelerate the development of targeted, individualized, anti-obesity therapy.

neuroscience↗

bioRxiv2021

Towards a Comprehensive Variation Benchmark for Challenging Medically-Relevant Autosomal Genes

The repetitive nature and complexity of multiple medically important genes make them intractable to accurate analysis, despite the maturity of short-read sequencing, resulting in a gap in clinical applications of genome sequencing. The Genome in a Bottle Consortium has provided benchmark variant sets, but these excluded some medically relevant genes due to their repetitiveness or polymorphic complexity. In this study, we characterize 273 of these 395 challenging autosomal genes that have multiple implications for medical sequencing. This extended, curated benchmark reports over 17,000 SNVs, 3,600 INDELs, and 200 SVs each for GRCh37 and GRCh38 across HG002. We show that false duplications in either GRCh37 or GRCh38 result in reference-specific, missed variants for short- and long-read technologies in medically important genes including CBS, CRYAA, and KCNE1. Our proposed solution improves variant recall in these genes from 8% to 100%. This benchmark will significantly improve the comprehensive characterization of these medically relevant genes and guide new method development.

genomics↗

bioRxiv2021

Neural stem cells alter nucleocytoplasmic partitioning and accumulate nuclear polyadenylated transcripts during quiescence

Quiescence is a cellular state characterised by reversible cell-cycle arrest and diminished biosynthetic activity that protects against environmental insults, replicative exhaustion and proliferation-induced mutations1. Entry into and exit from this state controls development, maintenance and repair of tissues plus, in the adult central nervous system, generation of new neurons and thus cognition and mood2-4. Cancer stem cells too can undergo quiescence, which confers them resistance to current therapies5, 6. Despite clinical relevance, quiescence is poorly understood and is defined functionally given lack of molecular markers. Decrease of the most resource-intensive cellular process of protein synthesis is a feature of quiescence, controlled across species and cell types by inhibition of the Target of Rapamycin (TOR) pathway1, 7. Here, we combine Drosophila genetics and a mammalian model to show that altered nucleocytoplasmic partitioning and nuclear accumulation of polyadenylated RNAs are novel evolutionarily conserved hallmarks of quiescence regulation. Furthermore, nuclear accumulation of messenger RNA (mRNA) in quiescent NSCs (qNSCs) largely predicts protein downregulation, accounting for uncoupling between transcriptome and proteome in quiescence. These mechanisms provide a previously unappreciated regulatory layer to reducing protein synthesis in quiescent cells, whilst priming them for reactivation in response to appropriate cues.

developmental biology↗

bioRxiv2020

Wnt/beta-catenin signalling is dispensable for adult neural stem cell homeostasis and activation.

Adult mouse hippocampal neural stem cells (NSCs) generate new neurons that integrate into existing hippocampal networks and modulate mood and memory. These NSCs are largely quiescent and are stimulated by niche signals to activate and produce neurons. Wnt/{beta}-catenin signalling acts at different steps along the hippocampal neurogenic lineage and has been shown to promote the proliferation of intermediate progenitor cells. However, whether it has a direct role in the regulation of NSCs still remains unclear. Here we used Wnt/{beta}-catenin reporters and transcriptomic data from in vivo and in vitro models to show that both active and quiescent adult NSCs respond to Wnt/{beta}-catenin signalling. Wnt/{beta}-catenin stimulation instructed neuronal differentiation of active NSCs and promoted the activation or differentiation of quiescent NSCs in a dose-dependent manner. However, we found that inhibiting NSCs response to Wnt, by conditionally deleting {beta}-catenin, did not affect their activation or maintenance of their stem cell characteristics. Together, our results indicate that whilst NSCs do respond to Wnt/{beta}-catenin stimulation in a dose-dependent and state-specific manner, Wnt/{beta}-catenin signalling is not cell-autonomously required to maintain NSC homeostasis, which could reconcile some of the contradictions in the literature as to the role of Wnt/{beta}-catenin signalling in adult hippocampal NSCs.

developmental biology↗

bioRxiv2020

Gene Expression Meta-Analysis Identifies Molecular Changes Associated with SARS-CoV Infection in Lungs

BackgroundSevere Acute Respiratory Syndrome (SARS) corona virus (CoV) infections are a serious public health threat because of their pandemic-causing potential. This work analyzes mRNA expression data from SARS infections through meta-analysis of gene signatures, possibly identifying therapeutic targets associated with major SARS infections. MethodsThis work defines 37 gene signatures representing SARS-CoV, Middle East Respiratory Syndrome (MERS)-CoV, and SARS-CoV2 infections in human lung cultures and/or mouse lung cultures or samples and compares them through Gene Set Enrichment Analysis (GSEA). To do this, positive and negative infectious clone SARS (icSARS) gene panels are defined from GSEA-identified leading-edge genes between two icSARS-CoV derived signatures, both from human cultures. GSEA then is used to assess enrichment and identify leading-edge icSARS panel genes between icSARS gene panels and 27 other SARS-CoV gene signatures. The meta-analysis is expanded to include five MERS-CoV and three SARS-CoV2 gene signatures. Genes associated with SARS infection are predicted by examining the intersecting membership of GSEA-identified leading-edges across gene signatures. ResultsSignificant enrichment (GSEA p<0.001) is observed between two icSARS-CoV derived signatures, and those leading-edge genes defined the positive (233 genes) and negative (114 genes) icSARS panels. Non-random significant enrichment (null distribution p<0.001) is observed between icSARS panels and all verification icSARSvsmock signatures derived from human cultures, from which 51 over- and 22 under-expressed genes are shared across leading-edges with 10 over-expressed genes already associated with icSARS infection. For the icSARSvsmock mouse signature, significant, non-random significant enrichment held for only the positive icSARS panel, from which nine genes are shared with icSARS infection in human cultures. Considering other SARS strains, significant, non-random enrichment (p<0.05) is observed across signatures derived from other SARS strains for the positive icSARS panel. Five positive icSARS panel genes, CXCL10, OAS3, OASL, IFIT3, and XAF1, are found across mice and human signatures regardless of SARS strains. ConclusionThe GSEA-based meta-analysis approach used here identifies genes with and without reported associations with SARS-CoV infections, highlighting this approachs predictability and usefulness in identifying genes that have potential as therapeutic targets to preclude or overcome SARS infections.

microbiology↗

bioRxiv2020

IGF targeting perturbs global replication through ribonucleotide reductase dysfunction

IGF receptor (IGF-1R) inhibition delays repair of radiation-induced DNA double-strand breaks (DSBs), prompting us to investigate whether IGF-1R influences endogenous DNA damage. We demonstrate that IGF-1R inhibition generates endogenous DNA lesions protected by 53BP1 bodies, indicating under-replicated DNA. We detect delayed replication fork progression in IGF-inhibited or IGF-1R depleted cancer cells, with activation of ATR-CHK1 signaling and the intra-S-phase checkpoint. This phenotype reflects unanticipated regulation of global replication by IGF-1, mediated via AKT, MEK/ERK and JUN to influence expression of ribonucleotide reductase (RNR) subunit RRM2. IGF-1R inhibition or depletion downregulate RRM2, compromising RNR function and dNTP supply. The resulting delay in fork progression and hallmarks of replication stress are rescued by RRM2 overexpression, confirming RRM2 as the critical factor through which IGF-1 regulates replication. Following targeted compound screens, we identify synergy between IGF inhibition and ATM loss, with evidence that IGF inhibition compromises growth of ATM null cells and xenografts. This synthetic lethal effect reflects conversion of single-stranded lesions in IGF-inhibited cells into toxic DSBs upon ATM inhibition. These data implicate IGF-1R in alleviating replication stress, and the identified reciprocal IGF:ATM co-dependence provides an approach to exploit this effect in ATM-deficient cancers.

cancer biology↗

bioRxiv2020

Benchmarking challenging small variants with linked and long reads

Genome in a Bottle (GIAB) benchmarks have been widely used to help validate clinical sequencing pipelines and develop new variant calling and sequencing methods. Here, we use accurate linked reads and long reads to expand the prior benchmarks in 7 samples to include difficult-to-map regions and segmental duplications that are not readily accessible to short reads. Our new benchmark adds more than 300,000 SNVs, 50,000 indels, and 16 % new exonic variants, many in challenging, clinically relevant genes not previously covered (e.g., PMS2). For HG002, we include 92% of the autosomal GRCh38 assembly, while excluding problematic regions for benchmarking small variants (e.g., copy number variants and reference errors) that should not have been in the previous version, which included 85% of GRCh38. By including difficult-to-map regions, this benchmark identifies eight times more false negatives in a short read variant call set relative to our previous benchmark.We have demonstrated the utility of this benchmark to reliably identify false positives and false negatives across technologies in more challenging regions, which enables continued technology and bioinformatics development.

genomics↗

bioRxiv2020

Replication-transcription conflicts promote adaptive evolution

Cells may be able to promote adaptive evolution in a gene-specific and temporally-controlled manner. Genes encoded on the lagging strand have a higher mutation rate and evolve faster than genes on the leading strand. This effect is likely driven by head-on replication-transcription conflicts, which occur when lagging strand genes are transcribed during DNA replication. We previously suggested that the ability to selectively increase mutagenesis in a subset of genes may provide an adaptive advantage for cells. However, it is also possible that this effect could be neutral or even highly deleterious. Distinguishing between these models is important because, if the adaptive model is correct, it would indicate that 1) head-on conflicts, which are generally deleterious, can also provide a benefit to cells, and 2) cells possess the remarkable ability to fine-tune adaptive evolution. Furthermore, investigating these models may address the long-standing debate regarding whether accelerated evolution through conflicts can be adaptive. To distinguish between the adaptive and neutral models, we conducted single nucleotide polymorphism (SNP) analyses on wild strains of bacteria, from divergent phyla. To test the adaptive hypothesis, we analyzed convergent mutation patterns. As a simple test of the neutral hypothesis, we performed in silico modeling. Our results show that convergent mutations are enriched in lagging strand genes and that these mutations are unlikely to have arisen by chance. Additionally, we observe that convergent mutation frequency has a stronger positive correlation with gene-length in lagging strand genes. This effect strongly suggests that head-on conflicts between the DNA replication and transcription machineries are a key mechanism driving the formation of convergent mutations. Together, our data indicate that head-on replication-transcription conflicts can promote adaptive evolution in a variety of bacterial species, and potentially other organisms.

evolutionary biology↗

bioRxiv2020

A unifying framework disentangles genetic, epigenetic, and stochastic sources of drug-response variability in an in vitro model of tumor heterogeneity

Tumor heterogeneity is a primary cause of treatment failure and acquired resistance in cancer patients. Even in cancers driven by a single mutated oncogene, variability of targeted therapy response is observed. Additional genetic mutations can only partially explain this variability, leading to consideration of non-genetic factors, such as "stem-like" and "mesenchymal" phenotypic states, as critical contributors to tumor relapse and resistance. Here, we show that both genetic and non-genetic factors contribute to targeted drug-response variability in an experimental tumor heterogeneity model based on multiple versions and clonal sublines of PC9, the archetypal EGFR-mutant non-small cell lung cancer cell line. We observe significant drug-response variability across PC9 cell line versions, among sublines, and within sublines. To disentangle genetic, epigenetic, and stochastic components underlying this variability, we adopt a theoretical framework whereby distinct genetic states give rise to multiple epigenetic "basins of attraction", across which cells can transition driven by stochastic factors such as gene expression noise and asymmetric cell division. Using mutational impact analysis, single-cell differential gene expression, and semantic similarity of gene ontology terms to connect genomics and transcriptomics, we establish a baseline of genetic differences explaining drug-response variability across PC9 cell line versions. In contrast, with the same approach, we conclude that in all but one of the clonal sublines, drug-response variability is due to epigenetic rather than genetic differences. Finally, using a clonal drug-response assay and stochastic simulations, we attribute drug-response variability within sublines to intracellular stochastic fluctuations and confirm that one subline likely contains a genetic resistance mutation that emerged in the absence of selective pressures. We propose that a theoretical framework deconvolving the complex interplay among genetic, epigenetic, and stochastic sources of intratumoral heterogeneity will lead to novel therapeutic strategies to combat tumor relapse and resistance.

systems biology↗

bioRxiv2020

Progressive changes in hippocampal stem cell properties ensure lifelong neurogenesis

Neural stem cell numbers fall rapidly in the hippocampus of juvenile mice but stabilise during adulthood, ensuring lifelong hippocampal neurogenesis. We show that this reduction in stem cell depletion rate is the result of multiple coordinated changes in stem cell behaviour. In particular, while active neural stem cells divide only once or twice before differentiating rapidly in juveniles, they increasingly return to a resting state of shallow quiescence and progress through additional self-renewing divisions in adulthood. Single-cell transcriptomic, mathematical modelling and label-retention analyses indicate that resting cells have a higher activation rate and greater contribution to neurogenesis than dormant cells, which have not left quiescence. These progressive changes in stem cell behaviour result from reduced expression of the pro-activation protein ASCL1 due to increased post-translational degradation. These mechanisms help reconcile current contradictory models of hippocampal NSC dynamics and may contribute to the different rates of decline of hippocampal neurogenesis in mammalian species including humans.

developmental biology↗

bioRxiv2019

Heterogeneity and targeted therapy-induced adaptations in lung cancer revealed by longitudinal single-cell RNA sequencing

Lung cancer, the leading cause of cancer mortality, exhibits heterogeneity that enables adaptability, limits therapeutic success, and remains incompletely understood. Single-cell RNA sequencing (scRNAseq) of metastatic lung cancer was performed using 44 tumor biopsies obtained longitudinally from 27 patients before and during targeted therapy. Over 20,000 cancer and tumor microenvironment (TME) single-cell profiles exposed a rich and dynamic tumor ecosystem. scRNAseq of cancer cells illuminated targetable oncogenes beyond those detected clinically. Cancer cells surviving therapy as residual disease (RD) expressed an alveolar-regenerative cell signature suggesting a therapy-induced primitive cell state transition, whereas those present at on-therapy progressive disease (PD) upregulated kynurenine, plasminogen, and gap junction pathways. Active T-lymphocytes and decreased macrophages were present at RD and immunosuppressive cell states characterized PD. Biological features revealed by scRNAseq were biomarkers of clinical outcomes in independent cohorts. This study highlights how therapy-induced adaptation of the multi-cellular ecosystem of metastatic cancer shapes clinical outcomes.

cancer biology↗

bioRxiv2019

Trophic variation within a piscivorous lake trout morph from Great Bear Lake, Canada: The initial step toward ecological specialization?

In a polymorphic species, stable differences in resource use are expected among ecotypes, and homogeneity in resource use is predicted within an ecotype. Yet, using a broad resource spectrum has been identified as a strategy for fishes living in unproductive northern environments, where food is patchily distributed and ephemeral. We investigated whether individual specialization of trophic resources occurred within the generalist piscivore ecotype of lake trout from Great Bear Lake, Canada, reflective of a form of diversity. Four distinct dietary patterns of resource use within the lake trout ecotype were detected from fatty acid composition, with some variation linked to spatial patterns within Great Bear Lake. Feeding habits of different groups within the ecotype were not associated with detectable morphological or genetic differentiation, suggesting that behavioral plasticity caused the trophic differences. A low level of genetic differentiation was detected between exceptionally large-sized individuals and other individuals. Investigating a geologically young system that displays high levels of intraspecific diversity and focusing on individual variation in diet suggested that individual trophic specialization can occur within an ecotype. The characterization of niche use among individuals, as done in this study, is necessary to understand the role that individual variation can play at the beginning of differentiation processes.

ecology↗