Biology subjects

Green, T.

Publications and source records attributed to Green, T..

17 recordsLinked to original sources

bioRxiv2026

Crossmodal plasticity effects of hearing loss and ageing in the human auditory cortex

Crossmodal plasticity refers to the phenomenon by which typical sensory areas respond to stimulation in other sensory modalities when their main input is absent or reduced. In this study, we examined the effect of age-related hearing loss (ARHL) on crossmodal plasticity in auditory brain regions. ARHL is prevalent in a large proportion of older adults, and it is associated with an increased risk of cognitive decline and dementia. Understanding how the brain adapts to ARHL is essential in aiding the development of adequate therapies and interventions for a phenomenon experienced by most adults aged 65 and over. Previous research in congenitally deaf adults has shown that crossmodal plasticity effects are stronger for conditions that require higher executive demands. We conducted an fMRI experiment in older adults to determine whether crossmodal recruitment of auditory cortical regions during higher executive demands also occurs following ARHL. In the MRI scanner, participants with and without ARHL completed a visual task-switching paradigm and a visual working memory task, each comprising high and low executive-demand conditions. Results from both groups of participants showed that the high-demand conditions reliably activated canonical frontoparietal regions involved in executive function and cognitive control. Crucially, we also observed significant recruitment of auditory regions during these visual tasks, particularly under the higher executive demands condition of the task-switching paradigm. Crossmodal activations in auditory areas occurred in both groups, with no significant effects of hearing level or age. These findings indicate that auditory regions are involved in high executive demand visual processing, and that crossmodal plasticity effects are not restricted to early sensitive periods. We propose that reduced auditory input and age-related changes in cortical processing jointly contribute to the reorganisation of the auditory cortex in later life. Understanding these mechanisms is critical for clarifying the neural consequences of ARHL and their impact on cognitive decline.

neuroscience↗

bioRxiv2025

PLD1-Dependent Regulation of Synaptic Integrity: Implications for Cognitive Resilience and Alzheimer's Disease Pathogenesis

Dysregulation of Phospholipase D1 (PLD1) has been implicated in the progression of neurodegenerative diseases, including Alzheimers Disease (AD). This study investigated PLD1 signaling in synaptic integrity and cognition during aging and in a late-onset AD mouse model, hypothesizing differential effects of PLD1 modulation on synaptic vulnerability. AAV2-mediated gene transfer was employed to overexpress (PLD1 OXP) or attenuate (PLD1 ATT) PLD1 in aged wild-type (WT) and 3xTg-AD mice. To validate these constructs, differentiated PC12 cells were utilized. Within these cells, a model of post-mitotic neurons, PLD1 OXP exhibited a notable reduction in both the average neurite length and the percentage of neurite-bearing cells. This suggests that elevated PLD1 activity exerts a significant influence on neurite outgrowth. Conversely, PLD1 ATT did not inhibit neurite formation, indicating it is not detrimental at the cellular level. These cellular findings paralleled in vivo observations - electrophysiological studies revealed PLD1 OXP impaired long-term potentiation (LTP) and synaptic transmission, particularly in aged WT mice, whereas PLD1 ATT improved synaptic function in 3xTg-AD mice. Behaviorally, PLD1 ATT enhanced spatial working memory and reduced anxiety-like behavior, notably in 3xTg-AD mice. These results highlight that tight PLD1 regulation is vital for maintaining synaptic integrity and cognitive resilience. Thus, PLD1 attenuation may serve as an important complement to immunotherapeutic approaches by strengthening synaptic resilience in neurodysfunctional states, including AD and related dementia (ADRD).

neuroscience↗

bioRxiv2025

Advancing Luciferase Activity and Stability beyond Directed Evolution and Rational Design through Expert Guided Deep Learning

Engineered luciferases have transformed biological imaging and sensing, yet optimizing NanoLuc luciferase (NLuc) remains challenging due to the inherent stability-activity trade-off and its limited sequence homology with characterized proteins. We report a hybrid approach that synergistically integrates computational deep learning with structure-guided rational design to develop enhanced NLuc variants that improve thermostability and thereby activity at elevated temperatures. By systematically analyzing libraries of engineered variants, we established that modifications to termini and loops distal from the catalytic center, combined with preservation of allosterically coupled networks, effectively enhance thermal resilience while maintaining enzymatic function. Our optimized variants - notably B.07 and B.09 - exhibit substantial thermostability enhancements (increases of 4.2 {degrees}C and 5.2 {degrees}C at 50 % solubility), leading to increased activity at elevated temperatures (320 % and 370 % of wild-type at 55 {degrees}C). These variants maintain NLucs pH tolerance and retain improved activity with the alternative substrate coelenterazine. Molecular dynamics simulations and protein folding studies elucidate how these mutations favorably modulate conformational landscapes without perturbing substrate binding architecture. Beyond providing superior tools for bioluminescence applications, our integrated methodology establishes a broadly applicable framework for engineering enzymes where traditional homology-based approaches fail, and stability-activity constraints present formidable barriers to improvement.

biochemistry↗

bioRxiv2024

Pertpy: an end-to-end framework for perturbation analysis

Advances in single-cell technology have enabled the measurement of cell-resolved molecular states across a variety of cell lines and tissues under a plethora of genetic, chemical, environmental, or disease perturbations. Current methods focus on differential comparison or are specific to a particular task in a multi-condition setting with purely statistical perspectives. The quickly growing number, size, and complexity of such studies requires a scalable analysis framework that takes existing biological context into account. Here, we present pertpy, a Python-based modular framework for the analysis of large-scale perturbation single-cell experiments. Pertpy provides access to harmonized perturbation datasets and metadata databases along with numerous fast and user-friendly implementations of both established and novel methods such as automatic metadata annotation or perturbation distances to efficiently analyze perturbation data. As part of the scverse ecosystem, pertpy interoperates with existing libraries for the analysis of single-cell data and is designed to be easily extended.

bioinformatics↗

bioRxiv2024

A myelinic channel system for organelle transport to the glial-axonal junction

Myelin sheaths comprise compacted layers of oligodendroglial membrane wrapped spirally around axons. Each sheath, if imagined unwrapped, has a cytoplasm-filled space at its perimeter, linking it to the oligodendrocyte soma via a short process. By electron microscopy (EM), this space, which we term the myelinic channel system contains microtubules and membranous organelles, but whether these are remnants of development or serve a function is unknown. Performing live imaging of myelinating oligodendrocytes expressing fluorescent reporters, we found that the myelinic channel system serves microtubule-dependent organelle transport. Further, the intra-myelinic movement of peroxisomes was modulated by neuronal electrical activity in these mixed neural cell cultures. Loss of oligodendroglial Kif21b or CNP in vivo led to apparent stasis of myelin organelles and secondary axon pathology. This suggests that oligodendrocytes require motor transport in myelin to maintain axonal integrity.

neuroscience↗

bioRxiv2024

Impact of Pathogenic Variants of the Ras-MAPK Pathway on Major White Matter Tracts in the Human Brain

Noonan syndrome (NS) and Neurofibromatosis type-1 (NF1) are genetic conditions linked to pathogenic variants in genes of the Ras-MAPK signaling pathway. Both conditions hyperactivate signaling of the Ras pathway and exhibit a high prevalence of neuropsychiatric disorders. Further, animal models of NS and NF1 and human imaging studies show white-matter abnormalities in both conditions. While these findings suggest Ras pathway hyper-activation effects on white-matter, it is unknown whether these effects are syndrome-specific or pathway-specific. To characterize the effect of NS and NF1 on human white-matter microstructural integrity and discern potential syndrome-specific influences on microstructural integrity of individual tracts, we collected diffusion-weighted imaging data from children with NS (n=24), NF1 (n=28), and age and sex-matched controls (n=31). We contrasted the clinical groups (NS or NF1) and controls using voxel-wise, tract-based, and along-tract analyses. Outcomes included voxel-wise, tract-based and along-tract fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD). NS and NF1 showed similar patterns of reduced FA and increased AD, RD, and MD on white-matter relative to controls and different spatial patterns. NS presented a more extensive spatial effect than NF1 on white-matter integrity as measured by FA. Tract-based analysis also demonstrated differences in effect magnitude with overall lower FA in NS compared to NF1 (d=0.4). At the tract-level, NS specific-effects on FA were detected in association tracts (superior longitudinal, uncinate and arcuate fasciculi; ps <0.012) and NF1 specific-effects were detected in the corpus callosum (ps<0.037) compared to controls. Results from along-tract analyses aligned with results from tract-based analyses and indicated that effects are pervasive along the affected tracts. In conclusion, we find that pathogenic variants in the Ras-MAPK pathway are associated with white-matter abnormalities as measured by diffusion in the developing brain. Overall NS and NF1 show common effects on FA and diffusion scalars, as well as specific unique effects, namely on temporoparietal-frontal tracts (intra-hemispheric) in NS and on the corpus callosum (inter-hemispheric) in NF1. The observed specific effects not only confirm prior observations from independent cohorts of NS and NF1 but also inform on syndrome-specific susceptibility of individual tracts. Thus, these findings suggest potential targets for precise, brain-focused outcome measures for existing medications, such as MEK inhibitors, that act on the Ras pathway.

neuroscience↗

bioRxiv2024

Pangenome reconstruction in rats enhances genotype-phenotype mapping and novel variant discovery

The HXB/BXH family of recombinant inbred rat strains is a unique genetic resource that has been extensively phenotyped over 25 years, resulting in a vast dataset of quantitative molecular and physiological phenotypes. We built a pangenome graph from 10x Genomics Linked-Read data for 31 recombinant inbred rats to study genetic variation and association mapping. The pangenome includes 0.2Gb of sequence that is not present the reference mRatBN7.2, confirming the capture of substantial additional variation. We validated variants in challenging regions, including complex structural variants resolving into multiple haplotypes. Phenome-wide association analysis of validated SNPs uncovered variants associated with glucose/insulin levels and hippocampal gene expression. We propose an interaction between Pirl1l1, chromogranin expression, TNF- levels, and insulin regulation. This study demonstrates the utility of linked-read pangenomes for comprehensive variant detection and mapping phenotypic diversity in a widely used rat genetic reference panel.

genomics↗

bioRxiv2023

Optimal distance metrics for single-cell RNA-seq populations

In single-cell data workflows and modeling, distance metrics are commonly used in loss functions, model evaluation, and subpopulation analysis. However, these metrics behave differently depending on the source of variation, conditions and subpopulations in single-cell expression profiles due to data sparsity and high dimensionality. Thus, the metrics used for downstream tasks in this domain should be carefully selected. We establish a set of benchmarks with three evaluation measures, capturing desirable facets of absolute and relative distance behavior. Based on seven datasets using perturbation as ground truth, we evaluated 16 distance metrics applied to scRNA-seq data and demonstrated their application to three use cases. We find that linear metrics such as mean squared error (MSE) performed best across our three evaluation criteria. Therefore, we recommend the use of MSE for comparing single-cell RNA-seq populations and evaluating gene expression prediction models.

bioinformatics↗

bioRxiv2022

Germline variation contributes to false negatives in CRISPR-based experiments with varying burden across ancestries

Reducing disparities is critical to promote equity of access to precision treatments for all patients with cancer. While socioenvironmental factors are a major driver behind such disparities, biological differences also are likely to contribute. The prioritization of cancer drug targets is foundational for drug discovery, yet whether ancestry-related signals in target discovery pipelines exist has not been systematically explored due to the absence of data at the appropriate scale. Here, we analyzed data from 611 genome-scale CRISPR/Cas9 viability experiments in human cell line models as part of the Cancer Dependency Map to identify ancestry-associated genetic dependencies. Surprisingly, we found that most putative associations between ancestry and dependency arose from artifacts related to germline variants that are present at different frequencies across ancestry groups. In 2-5% of genes profiled in each cellular model, germline variants in sgRNA targeting sequences likely reduced cutting by the CRISPR/Cas9 nuclease. Unfortunately, this bias disproportionately affected cell models derived from individuals of recent African descent because their genomes tended to diverge more from the consensus genome typically used for CRISPR/Cas9 guide design. To help the scientific community begin to resolve this source of bias, we report three complementary methods for ancestry-agnostic CRISPR experiments. This report adds to a growing body of literature describing ways in which ancestry bias impacts cancer research in underappreciated ways.

cancer biology↗

bioRxiv2022

Subjective assessment and taste strips testing of gustatory function, at home, and in the lab

Gustatory ability is an important marker of health status, including COVID-19 disease. We compare self-reporting with home and lab psychophysical "taste strips" tests in healthy subjects. The taste test consisted of paper strips impregnated with sweet, bitter, salty, or sour tastants, and with the trigeminal stimulus capsaicin, each in high and in low concentration. The test was carried out either in a controlled lab environment (74 participants, 47 women) with the strips being administered by the experimenter or self-administered by the participants at home (77 participants, 59 women). After self-reporting their subjective assessment of chemosensory ability, the participant identified the taste of each strip and rated intensity and pleasantness. Identification score, intensity, and pleasantness averaged over the 8 taste strips were similar between the lab and the home-administered tests. Self-rated taste ability did not correlate with any of these scores, but strongly correlated with self-rated smell ability in the lab group (r=0.73), and moderately correlated in the home group (r=0.51). Taste identification correlated with intensity ratings (r=0.63 lab, r=0.36 home) but not with the pleasantness ratings (r=-0.14 lab, r=0.1 home). The results of the taste strips test were similar in the lab and at home for healthy young participants and provide a baseline against which taste tests can be compared in future applications.

physiology↗

bioRxiv2022

3D-Beacons: Decreasing the gap between protein sequences and structures through a federated network of protein structure data resources

While scientists can often infer the biological function of proteins from their 3-dimensional quaternary structures, the gap between the number of known protein sequences and their experimentally determined structures keeps increasing. A potential solution to this problem is presented by ever more sophisticated computational protein modelling approaches. While often powerful on their own, most methods have strengths and weaknesses. Therefore, it benefits researchers to examine models from various model providers and perform comparative analysis to identify what models can best address their specific use cases. To make data from a large array of model providers more easily accessible to the broader scientific community, we established 3D-Beacons, a collaborative initiative to create a federated network with unified data access mechanisms. The 3D-Beacons Network allows researchers to collate coordinate files and metadata for experimentally determined and theoretical protein models from state-of-the-art and specialist model providers and also from the Protein Data Bank.

bioinformatics↗

bioRxiv2021

Protein complex prediction with AlphaFold-Multimer

While the vast majority of well-structured single protein chains can now be predicted to high accuracy due to the recent AlphaFold [1] model, the prediction of multi-chain protein complexes remains a challenge in many cases. In this work, we demonstrate that an AlphaFold model trained specifically for multimeric inputs of known stoichiometry, which we call AlphaFold-Multimer, significantly increases accuracy of predicted multimeric interfaces over input-adapted single-chain AlphaFold while maintaining high intra-chain accuracy. On a benchmark dataset of 17 heterodimer proteins without templates (introduced in [2]) we achieve at least medium accuracy (DockQ [3] [≥] 0.49) on 13 targets and high accuracy (DockQ [≥] 0.8) on 7 targets, compared to 9 targets of at least medium accuracy and 4 of high accuracy for the previous state of the art system (an AlphaFold-based system from [2]). We also predict structures for a large dataset of 4,446 recent protein complexes, from which we score all non-redundant interfaces with low template identity. For heteromeric interfaces we successfully predict the interface (DockQ [≥] 0.23) in 70% of cases, and produce high accuracy predictions (DockQ [≥] 0.8) in 26% of cases, an improvement of +27 and +14 percentage points over the flexible linker modification of AlphaFold [4] respectively. For homomeric inter-faces we successfully predict the interface in 72% of cases, and produce high accuracy predictions in 36% of cases, an improvement of +8 and +7 percentage points respectively.

bioinformatics↗

bioRxiv2021

Define protein variant functions with high-complexity mutagenesis libraries and enhanced mutation detection software

Pooled variant expression libraries can test the phenotypes of thousands of variants of a gene in a single multiplexed experiment. In a library encoding all single-amino-acid substitutions of a protein, each variant differs from its reference only at a single codon-position located anywhere along the coding sequence. Consequently, accurately identifying these variants by sequencing is a major technical challenge. A popular but expensive brute-force approach is to divide the pool of variants into multiple smaller sub-libraries that each contains variants of a small region and that must each be constructed and screened individually, but that can then be PCR-amplified and fully sequenced with a single read to allow direct readout of variant abundance. Here we present an approach to screen very large variant libraries with mutations spanning a wide region in a single pool, including library design criteria and mutant-detection algorithms that permit reliable calling and counting of variants from large-scale sequencing data.

systems biology↗

bioRxiv2020

Single-dose intranasal administration of AdCOVID elicits systemic and mucosal immunity against SARS-CoV-2 in mice

The coronavirus disease 2019 (COVID-19) pandemic has highlighted the urgent need for effective preventive vaccination to reduce burden and spread of severe acute respiratory syndrome (SARS) coronavirus 2 (SARS-CoV-2) in humans. Intranasal vaccination is an attractive strategy to prevent COVID-19 as the nasal mucosa represents the first-line barrier to SARS-CoV-2 entry before viral spread to the lung. Although SARS-CoV-2 vaccine development is rapidly progressing, the current intramuscular vaccines are designed to elicit systemic immunity without conferring mucosal immunity. Here, we show that AdCOVID, an intranasal adenovirus type 5 (Ad5)-vectored vaccine encoding the receptor binding domain (RBD) of the SARS-CoV-2 spike protein, elicits a strong and focused immune response against RBD through the induction of mucosal IgA, serum neutralizing antibodies and CD4+ and CD8+ T cells with a Th1-like cytokine expression profile. Therefore, AdCOVID, which promotes concomitant systemic and local mucosal immunity, represents a promising COVID-19 vaccine candidate.

immunology↗

bioRxiv2020

Evaluation of Field Sampling Techniques for Environmental Microbial Exposure: Assessing Efficacy and Feasibility

Environmental exposures in schools, including microbial exposures, can lead to detrimental childhood health outcomes. We evaluated two sampling techniques - standard flocked swabs versus sterile electrostatic cloths - to quantify Staphylococcus bacterial burden from school surfaces. Electrostatic cloths demonstrated higher test sensitivity and yielded higher surface area-standardized colony forming units compared to swabs. Despite protocol standardization, consistently larger surface areas were sampled with electrostatic cloths. This suggest that electrostatic cloths were more effective and practical for fieldwork.

microbiology↗

bioRxiv2020

Non-canonical open reading frames encode functional proteins essential for cancer cell survival

A key question in genome research is whether biologically active proteins are restricted to the [~]20,000 canonical, well-annotated genes, or rather extend to the many non-canonical open reading frames (ORFs) predicted by genomic analyses. To address this, we experimentally interrogated 553 ORFs nominated in ribosome profiling datasets. Of these 553 ORFs, 57 (10%) induced a viability defect when the endogenous ORF was knocked out using CRISPR/Cas9 in 8 human cancer cell lines, 257 (46%) showed evidence of protein translation when ectopically expressed in HEK293T cells, and 401 (73%) induced gene expression changes measured by transcriptional profiling following ectopic expression across 4 cell types. CRISPR tiling and start codon mutagenesis indicated that the biological effects of these non-canonical ORFs required their translation as opposed to RNA-mediated effects. We selected one of these ORFs, G029442--renamed GREP1 (Glycine-Rich Extracellular Protein-1)--for further characterization. We found that GREP1 encodes a secreted protein highly expressed in breast cancer, and its knock-out in 263 cancer cell lines showed preferential essentiality in breast cancer derived lines. Analysis of the secretome of GREP1-expressing cells showed increased abundance of the oncogenic cytokine GDF15, and GDF15 supplementation mitigated the growth inhibitory effect of GREP1 knock-out. Taken together, these experiments suggest that the non-canonical ORFeome is surprisingly rich in biologically active proteins and potential cancer therapeutic targets deserving of further study.

cancer biology↗

bioRxiv2019

Agreement between two large pan-cancer CRISPR-Cas9 gene dependency datasets

Genome-scale CRISPR-Cas9 viability screens performed in cancer cell lines provide a systematic approach to identify cancer dependencies and new therapeutic targets. As multiple large-scale screens become available, a formal assessment of the reproducibility of these experiments becomes necessary. We analyzed data from recently published pan-cancer CRISPR-Cas9 screens performed at the Broad and Sanger institutes. Despite significant differences in experimental protocols and reagents, we found that the screen results are highly concordant across multiple metrics with both common and specific dependencies jointly identified across the two studies. Furthermore, robust biomarkers of gene dependency found in one dataset are recovered in the other. Through further analysis and replication experiments at each institute, we found that batch effects are driven principally by two key experimental parameters: the reagent library and the assay length. These results indicate that the Broad and Sanger CRISPR-Cas9 viability screens yield robust and reproducible findings.

cancer biology↗