Biology subjects

Hughes, M.

Publications and source records attributed to Hughes, M..

31 records · Page 2Linked to original sources

bioRxiv2021

Single-cell landscapes of primary glioblastomas and matched organoids and cell lines reveal variable retention of inter- and intra-tumor heterogeneity

Glioblastomas (GBMs) are aggressive primary malignant brain tumors characterized by extensive levels of inter- and intra-tumor genetic and phenotypic heterogeneity. Patient-derived organoids (PDOs) have recently emerged as useful models to study such heterogeneity. Here, we present bulk exome as well as single-cell genome and transcriptome profiles of primary IDH wild type GBMs from ten patients, including two recurrent tumors, as well as PDOs and brain tumor-initiating cell (BTIC) lines derived from these patients. We find that PDOs are genetically similar to and variably retain gene expression characteristics of their parent tumors. At the phenotypic level, PDOs appear to exhibit similar levels of transcriptional heterogeneity as their parent tumors, whereas BTIC lines tend to be enriched for cells in a more uniform transcriptional state. The datasets introduced here will provide a valuable resource to help guide experiments using GBM-derived organoids, especially in the context of studying cellular heterogeneity.

cancer biology↗

bioRxiv2021

IQCELL: A platform for predicting the effect of gene perturbations on developmental trajectories using single-cell RNA-seq data

The increasing availability of single-cell RNA-sequencing (scRNA-seq) data from various developmental systems provides the opportunity to infer gene regulatory networks (GRNs) directly from data. Herein we describe IQCELL, a platform to infer, simulate, and study executable logical GRNs directly from scRNA-seq data. Such executable GRNs provide an opportunity to inform fundamental hypotheses in developmental programs and help accelerate the design of stem cell-based technologies. We first describe the architecture of IQCELL. Next, we apply IQCELL to a scRNA-seq dataset of early mouse T-cell development and show that it can infer a priori over 75% of causal gene interactions previously reported via decades of research. We will also show that dynamic simulations of the derived GRN qualitatively recapitulate the effects of the known gene perturbations on the T-cell developmental trajectory. IQCELL is applicable to many developmental systems and offers a versatile tool to infer, simulate, and study GRNs in biological systems. (https://gitlab.com/stemcellbioengineering/iqcell)

systems biology↗

bioRxiv2020

Perceptual Degradation Affects Stop-Signal Performance in Normal Healthy Adults

During stop-signal task performance, little is known how the quality of visual information of the go stimuli may indirectly affect the interplay between the go and stop processes. In this study, we assessed how perceptual degradation of the visual go stimuli affect response inhibition. Twenty-six healthy individuals (mean age 33.34 {+/-} 9.61) completed a modified 12-minute stop-signal task, where V and Y letters were used as visual go stimuli. The stimuli were subjected to four levels of perceptual degradation using Gaussian smoothing, to parametrically manipulate stop difficulty across low, intermediate-1, intermediate-2 and high difficulty conditions. On 33% of trials, the stop-signal (50ms audio tone) followed a go stimulus after a stop-signal delay, which was individually adjusted for each participant. As predicted, we found that with increased level of stop difficulty (little perceptual degradation), reaction times on go trials and the proportion of successful behavioural inhibitions on stop trials (P(i)) decreased in normal healthy adults. Contrary to our predictions, there was no effect of increased stop difficulty on the number of correct responses on go trials and reaction times on stop trials. Overall, manipulation of the completion time of the go process via perceptual degradation has been partially successful, whereby increased stop difficulty differentially affected P(i) and SSRT. These findings have implications for the relationship between the go and stop processes and the horse-race model, which may be limited in explaining the role of various cortico-basal ganglia loops in modulation of response inhibition. HighlightsO_LIManipulation of the completion time of the go process is partially successful C_LIO_LIPerceptual degradation differentially affects stop-signal performance C_LIO_LIIncreased stop difficulty (easy go) results in lower P(i) C_LIO_LIIncreased stop difficulty (easy go) has no effect on SSRT C_LIO_LIHorse-race model does not fully explain basal ganglia involvement in inhibition C_LI

neuroscience↗

bioRxiv2020

Disparate Bone Anabolic Cues Activate Bone Formation by Regulating the Rapid Lysosomal Degradation of Sclerostin Protein

The down regulation of sclerostin mediates bone formation in response to mechanical cues and parathyroid hormone (PTH). To date, the regulation of sclerostin has been attributed exclusively to the transcriptional downregulation that occurs hours after stimulation. Here, we describe, for the first time, the rapid post-translational degradation of sclerostin protein by the lysosome following mechanical load or PTH. We present a unifying model, integrating both new and established mechanically- and hormonally-activated effectors into the regulated degradation of sclerostin by lysosomes. Using an in vivo mechanical loading model, we find transient inhibition of lysosomal degradation or the upstream mechano-signaling pathway controlling sclerostin abundance impairs subsequent load-induced bone formation. We also link dysfunctional lysosomes to aberrant sclerostin regulation using Gaucher disease iPSCs. These results inform a paradigm shift in how bone anabolic cues post-translationally regulate sclerostin and expands our understanding of how osteocytes regulate this fundamentally important protein to regulate bone formation.

cell biology↗

bioRxiv2020

Optimising biomedical relationship extraction with BioBERT: Best practices for data creation

Text mining is widely used within the life sciences as an evidence stream for inferring relationships between biological entities. In most cases, conventional string matching is used to identify cooccurrences of given entities within sentences. This limits the utility of text mining results, as they tend to contain significant noise due to weak inclusion criteria. We show that, in the indicative case of protein-protein interactions (PPIs), the majority of sentences containing cooccurrences ({bsim}75%) do not describe any causal relationship. We further demonstrate the feasibility of fine tuning a strong domain-specific language model, BioBERT, to analyse sentences containing cooccurrences and accurately (F1 score: 88.95%) identify functional links between proteins. These strong results come in spite of the deep complexity of the language involved, which limits the accuracy even of expert curators. We establish guidelines for best practices in data creation to this end, including an examination of inter-annotator agreement, of semisupervision, and of rules based alternatives to manual curation, and explore the potential for downstream use of the model to accelerate curation of interactions in the SIGNOR database of causal protein interactions and the IntAct database of experimental evidence for physical protein interactions.

bioinformatics↗

bioRxiv2019

The genomic landscape of intrinsic and acquired resistance to cyclin-dependent kinase 4/6 inhibitors in patients with hormone receptor positive metastatic breast cancer

Clinical resistance mechanisms to CDK4/6 inhibitors in HR+ breast cancer have not been clearly defined. Whole exome sequencing of 59 tumors with CDK4/6i exposure revealed multiple candidate resistance mechanisms including RB1 loss, activating alterations in AKT1, RAS, AURKA, CCNE2, ERBB2, and FGFR2, and loss of ER expression. In vitro experiments confirmed that these alterations conferred CDK4/6i resistance. Cancer cells cultured to resistance with CDK4/6i also acquired RB1, KRAS, AURKA, or CCNE2 alterations, which conferred sensitivity to AURKA, ERK, or CHEK1 inhibition. Besides inactivation of RB1, which accounts for [~]5% of resistance, seven of these mechanisms have not been previously identified as clinical mediators of resistance to CDK4/6 inhibitors in patients. Three of these--RAS activation, AKT activation, and AURKA activation--have not to our knowledge been previously demonstrated preclinically. Together, these eight mechanisms were present in 80% of resistant tumors profiled and may define therapeutic opportunities in patients. SignificanceWe identified eight distinct mechanisms of resistance to CDK4/6 inhibitors present in 80% of resistant tumors profiled. Most of these have a therapeutic strategy to overcome or prevent resistance in these tumors. Taken together, these findings have critical implications related to the potential utility of precision-based approaches to overcome resistance in many patients with HR+ MBC.

cancer biology↗

bioRxiv2019

Observations on the interactions of mammals and birds with badger (Meles meles) dung pits at a site used by a single social group in an urban area

During a monitoring study of a single social group of badger (Meles meles) at an urban site, incidental observations were noted of mammalian and avian species feeding within and removing material from M. meles dung pits. In response to these observations, infra-red cameras were deployed at dung pits for a 10-week period to document the nature, timing and frequency of these behaviours. Cameras were triggered a total of 954 times by a total of nine mammal and 12 bird species. Harvesting of material accounted for 28 % of latrine-associated behaviours. Results may have implications for disease transmission and the efficacy of badger surveys, particularly in areas where brown rats are prevalent.

animal behavior and cognition↗

bioRxiv2019

Host density dependence and environmental factors affecting laurel wilt invasion

Host size, density and distribution, in addition to climate, can affect the likelihood a pathogen will invade and saturate landscapes. Laurel wilt, caused by the vector-borne forest pathogen Raffaelea lauricola, has devastated populations of native Lauraceae in the Southeastern US, and continues to spread. We surveyed 87 plots in six coastal islands in South Carolina, Georgia and North Florida, and one inland site (Archbold Biological Station) in South Florida for laurel wilt-affected and non-affected individual plants belonging to the genus Persea. The coastal island sites were surveyed once in 2008 or 2009, and the inland site was surveyed eight times from 2011 to 2013. Disease incidence per plot ranged from 0% to 96%, with mean disease incidence 45% across all sites. Disease incidence was positively correlated with trunk diameter and density of hosts with trunk diameter > 5 cm, but negatively with the degree of clustering, which was highest for small trees. A recursive partitioning model indicated that higher disease incidence was associated with moderate temperatures, wider trunk diameter, lower relative humidity, and lower wind speeds. Disease progress over time at Archbold followed a Gompertz curve, plateauing at 3% in two years. The dispersal kernel for disease incidence from a focus followed a negative exponential distribution. The number of plots with diseased trees at Archbold was similar for redbay (P. borbonia) and swampbay (P. palustris), but was lower for silkbay (P. humilis). Understanding how host density, size, and diversity interact with environmental effects will help guide future risk prediction efforts.

plant biology↗

bioRxiv2019

Toward A Reproducible, Scalable Framework for Processing Large Neuroimaging Datasets

Emerging neuroimaging datasets (collected through modalities such as Electron Microscopy, Calcium Imaging, or X-ray Microtomography) describe the location and properties of neurons and their connections at unprecedented scale, promising new ways of understanding the brain. These modern imaging techniques used to interrogate the brain can quickly accumulate gigabytes to petabytes of structural brain imaging data. Unfortunately, many neuroscience laboratories lack the computational expertise or resources to work with datasets of this size: computer vision tools are often not portable or scalable, and there is considerable difficulty in reproducing results or extending methods. We developed an ecosystem of neuroimaging data analysis pipelines that utilize open source algorithms to create standardized modules and end-to-end optimized approaches. As exemplars we apply our tools to estimate synapse-level connectomes from electron microscopy data and cell distributions from X-ray microtomography data. To facilitate scientific discovery, we propose a generalized processing framework, that connects and extends existing open-source projects to provide large-scale data storage, reproducible algorithms, and workflow execution engines. Our accessible methods and pipelines demonstrate that approaches across multiple neuroimaging experiments can be standardized and applied to diverse datasets. The techniques developed are demonstrated on neuroimaging datasets, but may be applied to similar problems in other domains.

neuroscience↗

bioRxiv2018

Compensation Related Utilization of Neural Circuits Hypothesis Model in Response Inhibition in Premanifest Huntington’s Disease

During premanifest stages of Huntingtons disease (pre-HD), individuals typically show increased functional brain activity thought to compensate for widespread brain anomalies. What remains unknown, is to disentangle whether increased functional brain activity reflects compensation or whether it is more of a product of HD-related pathological processes. We used a quantitative model of compensation, known as the CRUNCH (Compensation-Related Utilization of Neural Circuits Hypothesis) to characterise compensatory function in pre-HD using functional magnetic resonance imaging (fMRI). To test CRUNCH predictions, pre-HD individuals (n = 15) and age- and gender-matched controls (n = 15) performed a modified stop-signal task that incremented in four levels of stop difficulty (low, intermediate-1, intermediate-2, and high). Our results did not support the critical assumption of the CRUNCH model - controls did not show increased fMRI activity with increased level of stop difficulty. By contrast, controls showed decreased fMRI activity with increased stop difficulty in right inferior frontal gyrus pars triangularis and right caudate nucleus. Relative to controls, pre-HD individuals showed increased fMRI activity in right inferior frontal gyrus pars triangularis at intermediate-2 and high level of stop difficulty, which is the opposite effect to that predicted by the CRUNCH model. Contrary to the CRUNCH prediction, the pre-HD group showed decreased fMRI activity in right caudate nucleus at low level of stop difficulty, compared with controls. Further to this, fMRI activity patterns in right inferior frontal gyrus pars triangularis and right caudate nucleus were not accompanied by a decline in the number of successful behavioural stops in pre-HD. We therefore suggest that the CRUNCH model does not apply to characterise compensatory processes associated with response inhibition in pre-HD.\n\nHighlightsO_LICRUNCH does not apply to characterise compensation during stop-signal in pre-HD\nC_LIO_LIDeficits in inhibitory control in pre-HD occur 25 years prior to clinical diagnosis\nC_LIO_LICRUNCH may show signs of selective reporting\nC_LI

neuroscience↗

bioRxiv2018

Gene therapy in argininosuccinic aciduria

Argininosuccinate lyase (ASL) belongs to the liver-based urea cycle detoxifying ammonia, and the citrulline-nitric oxide cycle synthesising nitric oxide (NO). ASL-deficient patients present argininosuccinic aciduria characterised by hyperammonaemia and a multi-organ disease with neurocognitive impairment. Current therapeutic guidelines aim to control ammonaemia without considering the systemic NO imbalance. Here, we observed a neuronal disease with oxidative/nitrosative stress in ASL-deficient mouse brains. A single systemic injection of gene therapy mediated by an adeno-associated viral vector serotype 8 (AAV8) in adult or neonatal mice demonstrated the long-term correction of the urea cycle and the citrulline-NO cycle in the brain, respectively. The neuronal disease persisted if ammonaemia only was normalised but was dramatically reduced after correction of both ammonaemia and neuronal ASL activity. This was correlated with behavioural improvement and a decrease of the cortical cell death rate. Thus, the cerebral disease in argininosuccinic aciduria involves neuronal oxidative/nitrosative stress not mediated by hyperammonaemia, which is reversed by AAV gene transfer targeting the brain and the liver, acting on two different metabolic pathways via a single vector delivered systemically. This approach provides new hope for hepatocerebral metabolic diseases.

genetics↗

bioRxiv2018

Generation of light-producing somatic-transgenic mice using adeno-associated virus vectors

We have previously designed a library of lentiviral vectors to generate somatic-transgenic rodents to monitor signalling pathways in diseased organs using whole-body bioluminescence imaging, in conscious, freely moving rodents. We have now expanded this technology to adeno-associated viral vectors. We first explored bio-distribution by assessing GFP expression after neonatal intravenous delivery of AAV8. We observed widespread gene expression in, central and peripheral nervous system, liver, kidney and skeletal muscle. Next, we selected a constitutive SFFV promoter and NF{kappa}B binding sequence for bioluminescence and biosensor evaluation.\n\nAn intravenous injection of AAV8 containing firefly luciferase and eGFP under transcriptional control of either element resulted in strong and persistent widespread luciferase expression. A single dose of LPS-induced a 10-fold increase in luciferase expression in AAV8-NF{kappa}B mice and immunohistochemistry revealed GFP expression in cells of astrocytic and neuronal morphology. Importantly, whole-body bioluminescence persisted up to 240 days.\n\nTo further restrict biosensor activity to the CNS, we performed intracerebroventricular injection of each vector. We observed greater restriction of bioluminescence to the head and spine with both vectors. Immunohistochemistry revealed strongest expression in cells of neuronal morphology. LPS administration stimulated a 4-fold increase over baseline bioluminescence.\n\nWe have validated a novel biosensor technology in an AAV system by using an NF{kappa}B response element and revealed its potential to monitor signalling pathway in a non-invasive manner using a model of LPS-induced inflammation. This technology employs the 3Rs of biomedical animal research, complements existing germline-transgenic models and may be applicable to other rodent disease models with the use of different response elements.

genomics↗

bioRxiv2017

Large scale and significant expression from pseudogenes in Sodalis glossinidius - a facultative bacterial endosymbiont

The majority of bacterial genomes have high coding efficiencies, but there are some genomes of intracellular bacteria that have low gene density. The genome of the endosymbiont Sodalis glossinidius contains almost 50% pseudogenes containing mutations that putatively silence them at the genomic level. We have applied multiple omic strategies, combining: Illumina and Pacific Biosciences Single-Molecule Real Time DNA-sequencing and annotation; stranded RNA-sequencing; and proteome analysis to better understand the transcriptional and translational landscape of Sodalis pseudogenes, and potential mechanisms for their control. Between 53% and 74% of the Sodalis transcriptome remains active in cell-free culture. Mean sense transcription from Coding Domain Sequences (CDS) is four-times greater than that from pseudogenes. Comparative genomic analysis of six Illumina-sequenced Sodalis isolates from different host Glossina species shows pseudogenes make up ~40% of the 2,729 genes in the core genome, suggesting that they are stable and/or Sodalis is a recent introduction across the Glossina genus as a facultative symbiont. These data further shed light on the importance of transcriptional and translational control in deciphering host-microbe interactions, and demonstrate that pseudogenes are more complex than a simple degrading DNA sequence. The combination of genomics, transcriptomics and proteomics give a multidimensional perspective for studying prokaryotic genomes with a view to elucidating evolutionary adaptation to novel environmental niches.\n\nImportanceBacterial genomes are generally 1Kb in length, organized efficiently (i.e. with few gaps between genes or operons), and few open reading frames (ORFs) lack any predicted function. Intracellular bacteria have been removed from extracellular selection pressures acting on pathways of declining importance to fitness and thus, these bacteria tend to delete redundant genes in favour of smaller functional repertoires - maintaining genome efficiency. In the genomes of endosymbionts with a recent evolutionary relationship with their host, however, this process of genome reduction is not complete; Genes and pathways may be at an intermediate stage, undergoing mutation linked to reduced selection and small population numbers being vertically transmitted from mother to offspring in their hosts, resulting in an increase in abundance of pseudogenes and reduced coding capacities. A greater knowledge of the genomic architecture of persistent pseudogenes, with respect to their DNA structure, mRNA transcription and even putative translation to protein products, will lead to a better understanding of the evolutionary trajectory of endosymbiont genomes, many of which have important roles in arthropod ecology.

genomics↗