Biology subjects

Wong, A.

Publications and source records attributed to Wong, A..

At least 55 records · Page 3Linked to original sources

bioRxiv2023

Early-life stress triggers long-lasting organismal resilience and longevity via tetraspanin

Early-life stress experiences can produce lasting impacts on organismal adaptation and fitness. How transient stress elicits memory-like physiological effects is largely unknown. Here we show that early-life thermal stress strongly up-regulates tsp-1, a gene encoding the conserved transmembrane tetraspanin in C. elegans. TSP-1 forms prominent multimers and stable web- like structures critical for membrane barrier functions in adults and during aging. The up- regulation of TSP-1 persists even after transient early-life stress. Such regulation requires CBP- 1, a histone acetyl-transferase that facilitates initial tsp-1 transcription. Tetraspanin webs form regular membrane structures and mediate resilience-promoting effects of early-life thermal stress. Gain-of-function TSP-1 confers marked C. elegans longevity extension and thermal resilience in human cells. Together, our results reveal a cellular mechanism by which early-life thermal stress produces long-lasting memory-like impact on organismal resilience and longevity. TeaserStudies reveal mechanisms of how early-life heat exposure produces long-lasting benefits on longevity in the nematode C. elegans.

physiology↗

bioRxiv2023

Combinatorial genetic strategy accelerates the discovery of cancer genotype-phenotype associations

Available genetically-defined cancer models are limited in genotypic and phenotypic complexity and underrepresent the heterogeneity of human cancer. Herein, we describe a combinatorial genetic strategy applied to an organoid transformation assay to rapidly generate diverse, clinically relevant bladder and prostate cancer models. Importantly, the clonal architecture of the resultant tumors can be resolved using single-cell or spatially resolved next-generation sequencing to uncover polygenic drivers of cancer phenotypes.

cancer biology↗

bioRxiv2023

Genetic impacts on DNA methylation help elucidate regulatory genomic processes

Pinpointing genetic impacts on DNA methylation can improve our understanding of pathways that underlie gene regulation and disease risk. We report heritability and methylation quantitative trait locus (meQTL) analysis at 724,499 CpGs profiled with the Illumina Infinium MethylationEPIC array in 2,358 blood samples from three UK cohorts, with replication. Methylation levels at 34.2% of CpGs were affected by SNPs, and 98% of effects were cis-acting or within 1 Mbp of the tested CpG. Our results are consistent with meQTL analyses based on the former Illumina Infinium HumanMethylation450 array. Both meQTL SNPs and CpGs with meQTLs were overrepresented in enhancers, which have improved coverage on this platform compared to previous approaches. Co-localisation analyses across genetic effects on DNA methylation and 56 human traits identified 1,520 co-localisations across 1,325 unique CpGs and 34 phenotypes, including in disease-relevant genes, such ICOSLG (inflammatory bowel disease), and USP1 and DOCK7 (total cholesterol levels). Enrichment analysis of meQTLs and integration with expression QTLs gave insights into mechanisms underlying cis-meQTLs, for example through disruption of transcription factor binding sites for CTCF and SMC3, and trans-meQTLs, for example through regulating the expression of ACD and SENP7 which can modulate DNA methylation at distal sites. Our findings improve the characterisation of the mechanisms underlying DNA methylation variability and are informative for prioritisation of GWAS variants for functional follow-ups. A results database and viewer are available online.

genomics↗

bioRxiv2023

Pathogenesis of Breakthrough Infections with SARS-CoV-2 Variants in Syrian Hamsters

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, has evolved into multiple variants. Animal models are important to understand variant pathogenesis, particularly for those with mutations that have significant phenotypic or epidemiological effects. Here, cohorts of naive or previously infected Syrian hamsters (Mesocricetus auratus) were infected with variants to investigate viral pathogenesis and disease protection. Naive hamsters infected with SARS-CoV-2 variants had consistent clinical outcomes, tissue viral titers, and pathology, while hamsters that recovered from initial infection and were reinfected demonstrated less severe clinical disease and lung pathology than their naive counterparts. Males had more frequent clinical signs than females in most variant groups, but few sex variations in tissue viral titers and lung pathology were observed. These findings support the use of Syrian hamsters as a SARS-CoV-2 model and highlight the importance of considering sex differences when using this species. ImportanceWith the continued circulation and emergence of new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, understanding differences between the initial and a subsequent reinfection on disease pathogenesis is critical and highly relevant. This study characterizes Syrian hamsters as an animal model to study reinfection with SARS-CoV-2. Previous infection reduced the disease severity of reinfection with different SARS-CoV-2 variants.

microbiology↗

bioRxiv2022

Modelling the role of contour integration in visual inference

Under difficult viewing conditions, the brains visual system uses a variety of recurrent modulatory mechanisms to augment feed-forward processing. One resulting phenomenon is contour integration, which occurs in the primary visual (V1) cortex and strengthens neural responses to edges if they belong to a larger smooth contour. Computational models have contributed to an understanding of the circuit mechanisms of contour integration, but less is known about its role in visual perception. To address this gap, we embedded a biologically grounded model of contour integration in a task-driven artificial neural network, and trained it using a gradient-descent variant. We used this model to explore how brain-like contour integration may be optimized for high-level visual objectives as well as its potential roles in perception. When the model was trained to detect contours in a background of random edges, a task commonly used to examine contour integration in the brain, it closely mirrored the brain in terms of behavior, neural responses, and lateral connection patterns. When trained on natural images, the model enhanced weaker contours and distinguished whether two points lay on the same vs. different contours. The model learnt robust features that generalized well to out-of-training-distribution stimuli. Surprisingly, and in contrast with the synthetic task, a parameter-matched control network without recurrence performed the same or better than the model on the natural-image tasks. Thus a contour integration mechanism is not essential to perform these more naturalistic contour-related tasks. Finally, the best performance in all tasks was achieved by a modified contour integration model that did not distinguish between excitatory and inhibitory neurons. Author summaryDeep networks are machine-learning systems that consist of interconnected neuron-like elements. More than other kinds of artificial system, they rival human information processing in a variety of tasks. These structural and functional parallels have raised interest in using deep networks as simplified models of the brain, to better understand of brain function. For example, incorporating additional biological phenomena into deep networks may help to clarify how they affect brain function. In this direction, we adapted a deep network to incorporate a model of visual contour integration, a process in the brain that makes contours appear more visually prominent. We found that suitable training led this model to behave much like the corresponding brain circuits. We then investigated potential roles of the contour integration mechanism in processing of natural images, an important question that has been difficult to answer. The results were not straightforward. For example, the contour integration mechanism actually impaired the networks ability to tell whether two points lay on the same contour or not, but improved the networks ability to generalize this skill to a different group of images. Overall, this approach has raised more sophisticated questions about the role of contour integration in natural vision.

neuroscience↗

bioRxiv2022

Sensitivity of diffusion-tensor and correlated diffusion imaging to white-matter microstructural abnormalities: application in COVID-19

There has been growing attention on the effect of COVID-19 on white-matter microstructure, especially among those that self-isolated after being infected. There is also immense scientific interest and potential clinical utility to evaluate the sensitivity of single-shell diffusion MRI methods for detecting such effects. In this work, the sensitivities of three single-shell-compatible diffusion MRI modeling methods are compared for detecting the effect of COVID-19, including diffusion-tensor imaging, diffusion-tensor decomposition of orthogonal moments and correlated diffusion imaging. Imaging was performed on self-isolated patients at baseline and 3-month follow-up, along with age- and sex-matched controls. We demonstrate through simulations and experimental data that correlated diffusion imaging is associated with far greater sensitivity, being the only one of the three single-shell methods to demonstrate COVID-19-related brain effects. Results suggest less restricted diffusion in the frontal lobe in COVID-19 patients, but also more restricted diffusion in the cerebellar white matter, in agreement with several existing studies highlighting the vulnerability of the cerebellum to COVID-19 infection. These results, taken together with the simulation results, suggest that a significant proportion of COVID-19 related white-matter microstructural pathology manifests as a change in water diffusivity. Interestingly, different b-values also confer different sensitivities to the effects. No significant difference was observed in patients at the 3-month follow-up, likely due to the limited size of the follow-up cohort. To summarize, correlated diffusion imaging is shown to be a sensitive single-shell diffusion analysis approach that allows us to uncover opposing patterns of diffusion changes in the frontal and cerebellar regions of COVID-19 patients, suggesting the two regions react differently to viral infection.

biophysics↗

bioRxiv2022

Mortality without springing a leak: Locust gut epithelia do not become more permeable to fluorescent dextran and bacteria in the cold

The insect gut, which plays a role in ion and water balance, has been shown to leak solutes in the cold. Cold stress can also activate insect immune systems, but it is unknown if the leak of the gut microbiome is a possible immune trigger in the cold. We developed a novel feeding protocol to load the gut of locusts (Locusta migratoria) with fluorescent bacteria before exposing them to -2{degrees}C for up to 48 h. No bacteria were recovered from the hemolymph of cold-exposed locusts, regardless of exposure duration. To examine this further, we used an ex vivo gut sac preparation to re-test cold-induced fluorescent FITC-dextran leak across the gut and found no increased rate of leak. These results question not only the validity of FITC-dextran as a marker of paracellular barrier permeability in the gut, but also to what extent the insect gut becomes leaky in the cold.

physiology↗

bioRxiv2022

Near infrared spectroscopy detection of hemispheric cerebral ischemia following middle cerebral artery occlusion in rats

Timely and sensitive in vivo estimation of ischemic stroke-induced brain infarction are necessary to guide diagnosis and evaluation of treatments efficacy. The gold standard for estimation of the cerebral infarction volume is magnetic resonance imaging (MRI), which is expensive and not readily accessible. Measuring regional cerebral blood flow (rCBF) with Laser Doppler flowmetry (LDF) is the status quo for confirming reduced blood flow in experimental ischemic stroke models. However, rCBF reduction following cerebral artery occlusion often does not correlate with subsequent infarct volume. In the present study, we employed the continuous-wave near infrared spectroscopy (NIRS) technique to monitor cerebral oxygenation during 90 min of the intraluminal middle cerebral artery occlusion (MCAO) in Sprague-Dawley rats (n=8, male). The NIRS device consisted of a controller module and an optical sensor with two LED light sources and two photodiodes making up two parallel channels for monitoring left and right cerebral hemispheres. Optical intensity measurements were converted to deoxyhemoglobin (Hb) and oxyhemoglobin (HbO2) changes relative to a 2-min window prior to MCAO. Area under the curve (auc) for Hb and HbO2 was calculated for the 90-min occlusion period for each hemisphere (ipsilateral and contralateral). To obtain a measure of total ischemia, auc of the contralateral side was subtracted from the ipsilateral side resulting in {Delta}Hb and {Delta}HbO2 parameters. Infarct volume (IV) was calculated by triphenyl tetrazolium chloride (TTC) staining at 24h reperfusion. Results showed a significant negative correlation (r = -0.81, p = 0.03) between {Delta}Hb and infarct volume. In conclusion, our results show feasibility of using a noninvasive optical imaging instrument, namely NIRS, in monitoring cerebral ischemia in a rodent stroke model. This cost-effective, non-invasive technique may improve the rigor of experimental models of ischemic stroke by enabling in vivo longitudinal assessment of cerebral oxygenation and ischemic injury.

neuroscience↗

bioRxiv2022

Targeted curation of the gut microbial gene content modulating human cardiovascular disease

Despite the promise of the gut microbiome to forecast human health, few studies expose the microbial functions underpinning such predictions. To comprehensively inventory gut microorganisms and their gene content that control trimethylamine induced cardiovascular disease, we mined over 200,000 gut-derived genomes from cultivated and uncultivated microbial lineages. Creating MAGICdb (Methylated Amine Gene Inventory of Catabolism database), we designated an atherosclerotic profile for 6,341 microbial genomes that encoded metabolisms associated with heart disease. We used MAGICdb to evaluate diverse human fecal metatranscriptome and metaproteome datasets, demonstrating how this resource eases the recovery of methylated amine gene content previously obscured in microbiome datasets. From the feces of healthy and diseased subjects, we show MAGICdb gene markers predicted cardiovascular disease as effectively as traditional blood diagnostics. This functional microbiome catalog is a public, exploitable resource, enabling a new era of microbiota-based therapeutics.

genomics↗

bioRxiv2022

Tbx3 is required for mammalian retinal angiogenesis.

PurposeIn Retinopathy of Prematurity (ROP), infants often have incomplete vascularization, affecting the temporal region. A factor expressed in this region during retinal development is the T-box factor, Tbx3, which has not been studied in the mammalian eye. The purpose of this study was to determine if Tbx3 is required during eye formation for retinal angiogenesis. MethodsConditional removal of Tbx3 from both retinal progenitors and astrocytes was done using the optic cup-Cre recombinase driver, BAC-Dkk3-CRE and analyzed using standard immunohistochemical techniques. ResultsWith Tbx3 loss, the retinas were hypovascular, as seen in patients with ROP and Familial Exudative Vitreoretinopathy (FEVR). Retinal vasculature failed to form the stereotypic tri-layered plexus in the dorsal-temporal region. Astrocyte precursors were reduced in number and failed to form a lattice at the dorsal-temporal edge. We next examined retinal ganglion cells, as they have been shown to play a critical role in retinal angiogenesis. We found that melanopsin expression and Islet1/2-positive retinal ganglion cells were reduced in the dorsal half of the retina. In previous studies, loss of melanopsin has been linked to hyaloid artery persistence, which we also observed in the Tbx3 cKO retina, as well as in infants with ROP or FEVR. ConclusionsTogether, these results show that TBX3 is required for normal mammalian eye formation for the first time. This potentially provides a new genetic model for retinal hypovascular diseases.

neuroscience↗

bioRxiv2022

Microbial Energy Metabolism Fuels a CSF2-dependent Intestinal Macrophage Niche within Tertiary Lymphoid Organs

Maintaining intestinal macrophage (MP) heterogeneity is critical to ensure tissue homeostasis and host defense. The gut microbiota and host factors are thought to synergistically shape colonic MP development, although there remains a fundamental gap in our understanding of the details of such collaboration. Here, we report tertiary lymphoid organs (TLOs), enriched in group 3 innate lymphoid cells (ILC3s), as a microbiota-operated intestinal niche for the development of monocyte-derived MPs. ILC3-derived colony stimulating factor 2 (CSF2) serves as a developmental and functional determinant for MPs and required microbe-derived extracellular adenosine 5-triphosphate (ATP) as a trigger. Microbial communities rich in extracellular ATP promoted MP turnover via ILC3 activity in an NLRP3-dependent fashion. Single cell RNA-sequencing of MPs revealed unique TLO-associated, CSF2-dependent MP populations critical for anti-microbial defense against enteric infection. Collectively, these findings describe a fundamental framework that constitutes an intestinal MP niche fueled by microbial energy metabolism.

immunology↗

bioRxiv2022

Selective inhibitors of JAK1 targeting a subtype-restricted allosteric cysteine

The JAK family of non-receptor tyrosine kinases includes four subtypes (JAK1, JAK2, JAK3, and TYK2) and is responsible for signal transduction downstream of diverse cytokine receptors. JAK inhibitors have emerged as important therapies for immuno(onc)ological disorders, but their use is limited by undesirable side effects presumed to arise from poor subtype selectivity, a common challenge for inhibitors targeting the ATP-binding pocket of kinases. Here, we describe the chemical proteomic discovery of a druggable allosteric cysteine present in the non-catalytic pseudokinase domain of JAK1 (C817) and TYK2 (C838), but absent from JAK2 or JAK3. Electrophilic compounds selectively engaging this site block JAK1-dependent transphosphorylation and cytokine signaling, while appearing to act largely as "silent" ligands for TYK2. Importantly, the allosteric JAK1 inhibitors do not impair JAK2-dependent cytokine signaling and are inactive in cells expressing a C817A JAK1 mutant. Our findings thus reveal an allosteric approach for inhibiting JAK1 with unprecedented subtype selectivity.

pharmacology and toxicology↗

bioRxiv2021

Environment Classification for Robotic Leg Prostheses and Exoskeletons using Deep Convolutional Neural Networks

Robotic leg prostheses and exoskeletons can provide powered locomotor assistance to older adults and/or persons with physical disabilities. However, the current locomotion mode recognition systems being developed for intelligent high-level control and decision-making use mechanical, inertial, and/or neuromuscular data, which inherently have limited prediction horizons (i.e., analogous to walking blindfolded). Inspired by the human vision-locomotor control system, we designed and evaluated an advanced environment classification system that uses computer vision and deep learning to forward predict the oncoming walking environments prior to physical interaction, therein allowing for more accurate and robust locomotion mode transitions. In this study, we first reviewed the development of the ExoNet database - the largest and most diverse open-source dataset of wearable camera images of indoor and outdoor real-world walking environments, which were annotated using a hierarchical labelling architecture. We then trained and tested over a dozen state-of-the-art deep convolutional neural networks (CNNs) on the ExoNet database for large-scale image classification of the walking environments, including: EfficientNetB0, InceptionV3, MobileNet, MobileNetV2, VGG16, VGG19, Xception, ResNet50, ResNet101, ResNet152, DenseNet121, DenseNet169, and DenseNet201. Lastly, we quantitatively compared the benchmarked CNN architectures and their environment classification predictions using an operational metric called NetScore, which balances the image classification accuracy with the computational and memory storage requirements (i.e., important for onboard real-time inference). Although we designed this environment classification system to support the development of next-generation environment-adaptive locomotor control systems for robotic prostheses and exoskeletons, applications could extend to humanoids, autonomous legged robots, powered wheelchairs, and assistive devices for persons with visual impairments.

bioengineering↗

bioRxiv2021

Non-destructive Chemical Imaging of Bone Tissue for Intraoperative and Diagnostic Applications

Bone is difficult to image using traditional histopathological methods, leading to challenges in intraoperative consultations needed in orthopedic oncology. However, intraoperative pathological evaluation is critical in guiding surgical treatment. In this study, we demonstrate that a multimodal imaging approach that combines stimulated Raman scattering (SRS) microscopy, two-photon fluorescence (TPF) microscopy, and second harmonic generation (SHG) microscopy can provide useful diagnostic information regarding intact bone tissue fragments from surgical excision or biopsy specimens. We imaged bone samples from 14 patient cases and performed comprehensive chemical and morphological analyses of both mineral and organic components of bone. Our main findings show that carbonate content combined with morphometric analysis of bone organic matrix can separate several major classes of bone cancer associated diagnostic categories with an average accuracy of >90%. This proof-of-principle study demonstrate that multimodal imaging and machine learning-based analysis of bony tissue can provide crucial diagnostic information for guiding clinical decisions in orthopedic oncology.

pathology↗

bioRxiv2021

Longitudinal changes in diet cause repeatable and largely reversible shifts in gut microbial communities of laboratory mice and are observed across segments of the entire intestinal tract

Dietary changes are known to alter the composition of the gut microbiome. However, it is less understood how repeatable and reversible these changes are and how diet-switches affect the microbiota in the various segments of the gastrointestinal tract. Here, a treatment group of conventionally raised laboratory mice is subjected to two periods of western diet (WD) interrupted by a period of standard diet (SD) of the same duration. Beta-diversity analyses show that diet-induced microbiota changes are largely reversible (q = 0.1501; PERMANOVA, weighted-UniFrac comparison of the treatment-SD group to the control-SD group) and repeatable (q = 0.032; PERMANOVA, weighted-UniFrac comparison of both WD treatments). Furthermore, we report that diet switches alter the gut microbiota composition along the length of the intestinal tract in a segment-specific manner, leading to gut segment-specific Firmicutes/Bacteroidota ratios. We identified prevalent and distinct Amplicon Sequencing Variants (ASVs), particularly in genera of the recently described Muribaculaceae, along the gut as well as ASVs that are differentially abundant between segments of treatment and control groups. Overall, this study provides insights into the reversibility of diet-induced microbiota changes and highlights the importance to expand sampling efforts beyond the collections of fecal samples to characterize diet-dependent and segment-specific microbiome differences.

microbiology↗

bioRxiv2021

Computer Vision and Deep Learning for Environment-Adaptive Control of Robotic Lower-Limb Exoskeletons

Robotic exoskeletons require human control and decision making to switch between different locomotion modes, which can be inconvenient and cognitively demanding. To support the development of automated locomotion mode recognition systems (i.e., high-level controllers), we designed an environment recognition system using computer vision and deep learning. We collected over 5.6 million images of indoor and outdoor real-world walking environments using a wearable camera system, of which ~923,000 images were annotated using a 12-class hierarchical labelling architecture (called the ExoNet database). We then trained and tested the EfficientNetB0 convolutional neural network, designed for efficiency using neural architecture search, to predict the different walking environments. Our environment recognition system achieved ~73% image classification accuracy. While these preliminary results benchmark Efficient-NetB0 on the ExoNet database, further research is needed to compare different image classification algorithms to develop an accurate and real-time environment-adaptive locomotion mode recognition system for robotic exoskeleton control.

bioengineering↗

bioRxiv2021

Moonlighting adenylyl cyclases in plants: an Arabidopsis thaliana 9-cis-epoxycarotenoid dioxygenase as point in case

Adenylyl cyclases (ACs) and their catalytic product cAMP are regulatory components of plant responses. AC domains are intrinsic components of complex molecules with multiple functions, some of which are co-regulated by cAMP. Here we used an amino acid search motif based on annotated ACs in organisms across species to identify 12 unique Arabidopsis thaliana candidate ACs, four of which have a role in the biosynthesis of the stress hormone abscisic acid (ABA). One of these, the 9-cis-epoxycarotenoid dioxygenase (NCED3, At3g14440), was identified by sequence and structural analysis as a putative AC and then tested experimentally for activity. We show that an NCED3 AC fragment can complement an AC deficient E. coli mutant and this rescue is nullified when key amino acids in the AC motif are mutated. AC activity was also confirmed by tandem liquid chromatography mass spectrometry (LC-MS/MS). Our results are consistent with a moonlighting role for mononucleotide cyclases in multi-domain proteins that have at least one other distinct molecular function such as catalysis or ion channel activation and promise to yield new insights into tuning mechanisms of ABA dependent plant responses. Finally, our search method can also be applied to discover ACs in other species including Homo sapiens. HighlightsO_LIAn adenylyl cyclase (AC) catalytic center motif identifies novel ACs in plants C_LIO_LIACs can moonlight in complex proteins with other enzymatic domains C_LIO_LIA 9-cis-epoxycarotenoid dioxygenase essential for abscisic acid synthesis contains an AC C_LIO_LIThis finding implicates cAMP in abscisic acid synthesis and signaling C_LI

plant biology↗

bioRxiv2020

Validation of lipid-related therapeutic targets for coronary heart disease prevention using human genetics

Drug target Mendelian randomization (MR) studies use DNA sequence variants in or near a gene encoding a drug target, that alter its expression or function, as a tool to anticipate the effect of drug action on the same target. Here, we applied MR to prioritize drug targets for their causal relevance for coronary heart disease (CHD). The targets were further prioritized using genetic co-localization, protein expression profiles from the Human Protein Atlas and, for targets with a licensed drug or an agent in clinical development, by sourcing data from the British National Formulary and clinicaltrials.gov. Out of the 341 drug targets identified through their association with circulating blood lipids (HDL-C, LDL-C and triglycerides), we were able to robustly prioritize 30 targets that might elicit beneficial treatment effects in the prevention or treatment of CHD. The prioritized list included NPC1L1 and PCSK9, the targets of licensed drugs whose efficacy has been already proven in clinical trials. To conclude, we discuss how this approach can be generalized to other targets, disease biomarkers and clinical end-points to help prioritize and validate targets during the drug development process. One Sentence SummaryWe provide genetic support for lipid-modifying drug targets for coronary heart disease prevention using drug target Mendelian randomization and further prioritization based on clinical and biological evidence.

genetics↗