Biology subjects

Wu, Y.

Publications and source records attributed to Wu, Y..

At least 829 records · Page 46Linked to original sources

bioRxiv2021

Mutations in PIKFYVE cause autosomal dominant congenital cataract

Congenital cataract, an ocular disease predominantly occurring within the first decade of life, is one of the leading causes of blindness in children. Through whole exome sequencing of a Chinese family with congenital cataract, we identified a disease-causing mutation (p.G1943E) in PIKFYVE, which affecting the PIP kinase domain of the PIKfyve protein. We demonstrated that heterozygous/homozygous disruption of PIKfyve kinase domain, instead of overexpression of PIKFYVEG1943E in zebrafish mimicked the cataract defect in human patients, suggesting that haploinsufficiency, rather than dominant-negative inhibition of PIKfyve activity caused the disease. Phenotypical analysis of pikfyve zebrafish mutants revealed that loss of Pikfyve caused aberrant vacuolation (accumulation of Rab7+Lc3+ amphisomes) in lens cells, which was significantly alleviated by treatment with the V-ATPase inhibitor bafilomycin A1 (Baf-A1). Collectively, we identified PIKFYVE as a novel causative gene for congenital cataract and demonstrated the potential application of Baf-A1 in treatment of congenital cataract.

genomics↗

bioRxiv2021

Reproducing Human Motor Adaptation in Spiking Neural Simulation and known Synaptic Learning Rules

Sensorimotor adaptation enables us to adjust our goal-oriented movements in response to external perturbations. These phenomena have been studied experimentally and computationally at the level of human and animals reaching movements, and have clear links to the cerebellum as evidenced by cerebellar lesions and neurodegeneration. Yet, despite our macroscopic understanding of the high-level computational mechanisms it is unclear how these are mapped and are implemented in the neural substrates of the cerebellum at a cellular-computational level. We present here a novel spiking neural circuit model of the sensorimotor system including a cerebellum which control physiological muscle models to reproduce behaviour experiments. Our cerebellar model is composed of spiking neuron populations reflecting cells in the cerebellar cortex and deep cerebellar nuclei, which generate motor correction to change behaviour in response to perturbations. The model proposes two learning mechanisms for adaptation: predictive learning and memory formation, which are implemented with synaptic updating rules. Our model is tested in a force-field sensorimotor adaptation task and successfully reproduce several phenomena arising from human adaptation, including well-known learning curves, aftereffects, savings and other multi-rate learning effects. This reveals the capability of our model to learn from perturbations and generate motor corrections while providing a bottom-up view for the neural basis of adaptation. Thus, it also shows the potential to predict how patients with specific types of cerebellar damage will perform in behavioural experiments. We explore this by in silico experiments where we selectively incapacitate selected cerebellar circuits of the model which generate and reproduce defined motor learning deficits. Author summaryA rich body of work in human motor neuroscience developed high-level computational theories of sensorimotor control, learning and adaptation. But there is a gap in understanding how this may be implemented and learn on the level of neurons, synapses and spikes. Conversely, studies of patients with cerebellar lesions or neurological disease highlight the essential role the cerebellum plays in our ability to perform motor learning. Yet, how these anatomical and molecular defects play out in terms of human movement have to date not been linked to a model that spans multiple level of biological organisation from neural circuits to reproducing human motor experiments. To address this gap, we present a spiking neuron of the sensorimotor system focused on the cerebellum, with which we can on the one side reproduce the high-level behaviour learning phenomena observed in healthy subjects, as well as quantitatively predicting the putative effects on human movement trajectories of cerebellar lesions implemented at the cellular level.

neuroscience↗

bioRxiv2021

CMTr cap-adjacent 2`-O-ribose mRNA methyltransferases are required for reward learning and mRNA localization to synapses

Cap-adjacent nucleotides of animal, protist and viral mRNAs can be dynamically O-methylated at the 2 position of the ribose (cOMe). The functions of cOMe in animals, however, remain unknown. Here we show that the two cap methyltransferases (CMTr1 and CMTr2) of Drosophila can methylate the ribose of the first nucleotide in mRNA. Double-mutant flies lack cOMe but are viable. Consistent with prominent neuronal expression, they have a reward learning defect that can be rescued by conditional expression in mushroom body neurons before training. Among CMTr targets are cell adhesion and signaling molecules relevant for learning and cOMe is required for local translation of mRNAs at synapses. Hence, our study reveals a mechanism to co-transcriptionally prime mRNAs by cOMe for localized protein synthesis at synapses.

molecular biology↗

bioRxiv2021

Engineered small extracellular vesicles as a FGL1/PD-L1 dual-targeting delivery system for alleviating immune rejection

There is an urgent need for developing new immunosuppressive agents due to the toxicity of long-term use of broad immunosuppressive agents post organ transplantation. Comprehensive sample analysis revealed dysregulation of FGL1/LAG-3 and PD-L1/PD-1 immune checkpoints in allogeneic heart transplantation mice and clinical kidney transplant patients. In order to enhance these two immunosuppressive signal axes, we developed a bioengineering strategy to simultaneously display FGL1/PD-L1 (FP) on the surface of small extracellular vesicles (sEVs). Among various cell sources, FP sEVs derived from mesenchymal stem cells (MSCs) not only enriched FGL1/PD-L1 expression but also maintained the immunomodulatory properties of unmodified MSC sEVs. Next, we confirmed that FGL1 and PD-L1 on sEVs were specifically bound to their receptors LAG-3 and PD-1 on target cells. Importantly, FP sEVs significantly inhibited T cell activation and proliferation in vitro and a heart allograft model. Furthermore, FP sEVs encapsulated with low-dose FK506 (FP sEVs@FK506) exerted stronger effects on inhibiting T cell proliferation, reducing CD8+ T cell density and cytokine production in the spleens and heart grafts, inducing regulatory T cells in lymph nodes, and extending graft survival. Taken together, dual-targeting sEVs have the potential to boost the immune inhibitory signalings in synergy and slow down transplant rejection.

bioengineering↗

bioRxiv2021

NNAL, a major metabolite of tobacco-specific carcinogen NNK, promotes lung cancer progression through deactivating LKB1 in an isomer-dependent manner

Smoking is associated with worse clinical outcomes for lung cancer patients. Cell-based studies suggest that NNK (a tobacco specific carcinogen) promotes lung cancer progression. Given its short half-life, the physiological relevance of these in vitro results remains elusive. NNAL, a major metabolite of NNK with a similar structure, a chiral center, and a longer half-life, has never been evaluated in cancer cells. In this study, we characterized the effect of NNAL and its enantiomers on cancer progression among a panel of NSCLC cell lines and explored the associated mechanisms. We found that (R)-NNAL promotes cell proliferation, enhances migration, and induces drug resistance while (S)-NNAL has much weaker effects. Mechanistically, (R)-NNAL phosphorylates and deactivates LKB1 via the {beta}-AR signaling in the LKB1 wild type NSCLC cell lines, contributing to the enhanced proliferation, migration, and drug resistance. Of note, NNK exposure also increases the phosphorylation of LKB1 in A/J mice. More importantly, human lung cancer tissues appear to have elevated LKB1 phosphorylation. Our results reveal, for the first time, that NNAL may promote lung cancer progression through LKB1 deactivation in an isomer-dependent manner.

cancer biology↗

bioRxiv2021

Caveolae, CAVIN1, and lipid peroxidation mediate the oxidative stress response

Caveolae have been linked to many biological functions, but their precise roles are unclear. Using quantitative whole cell proteomics of genome-edited cells, we show that the oxidative stress response is the major pathway dysregulated in cells lacking the key caveola structural protein, CAVIN1. CAVIN1 deletion compromised sensitivity to oxidative stress in cultured cells and in animals. Wound-induced accumulation of reactive oxygen species and apoptosis were suppressed in Cavin1-null zebrafish, negatively affecting regeneration. Oxidative stress triggered lipid peroxidation and induced caveolar disassembly. The resulting release of CAVIN1 from caveolae allowed direct interaction between CAVIN1 and NRF2, a key regulator of the antioxidant response, facilitating NRF2 degradation. CAVIN1-null cells with impaired negative regulation of NRF2 showed resistance to lipid peroxidation-induced ferroptosis. Thus, caveolae, via lipid peroxidation and CAVIN1 release, maintain cellular susceptibility to oxidative stress-induced cell death demonstrating a crucial role for this enigmatic organelle in cellular homeostasis and wound response.

cell biology↗

bioRxiv2021

A multiple genome alignment workflow shows the impact of repeat masking and parameter tuning on alignment of functional regions in plants

Alignments of multiple genomes are a cornerstone of comparative genomics, but generating these alignments remains technically challenging and often impractical. We developed the msa_pipeline workflow (https://bitbucket.org/bucklerlab/msa_pipeline) based on the LAST aligner to allow practical and sensitive multiple alignment of diverged plant genomes with minimal user inputs. Our workflow only requires a set of genomes in FASTA format as input. The workflow outputs multiple alignments in MAF format, and includes utilities to help calculate genome-wide conservation scores. As high repeat content and genomic divergence are substantial challenges in plant genome alignment, we also explored the impact of different masking approaches and alignment parameters using genome assemblies of 33 grass species. Compared to conventional masking with RepeatMasker, a k-mer masking approach increased the alignment rate of CDS and non-coding functional regions by 25% and 14% respectively. We further found that default alignment parameters generally perform well, but parameter tuning can increase the alignment rate for non-coding functional regions by over 52% compared to default LAST settings. Finally, by increasing alignment sensitivity from the default baseline, parameter tuning can increase the number of non-coding sites that can be scored for conservation by over 76%.

genomics↗

bioRxiv2021

A connectomic study of a petascale fragment of human cerebral cortex

We acquired a rapidly preserved human surgical sample from the temporal lobe of the cerebral cortex. We stained a 1 mm3 volume with heavy metals, embedded it in resin, cut more than 5000 slices at [~]30 nm and imaged these sections using a high-speed multibeam scanning electron microscope. We used computational methods to render the three-dimensional structure containing 57,216 cells, hundreds of millions of neurites and 133.7 million synaptic connections. The 1.4 petabyte electron microscopy volume, the segmented cells, cell parts, blood vessels, myelin, inhibitory and excitatory synapses, and 104 manually proofread cells are available to peruse online. Many interesting and unusual features were evident in this dataset. Glia outnumbered neurons 2:1 and oligodendrocytes were the most common cell type in the volume. Excitatory spiny neurons comprised 69% of the neuronal population, and excitatory synapses also were in the majority (76%). The synaptic drive onto spiny neurons was biased more strongly toward excitation (70%) than was the case for inhibitory interneurons (48%). Despite incompleteness of the automated segmentation caused by split and merge errors, we could automatically generate (and then validate) connections between most of the excitatory and inhibitory neuron types both within and between layers. In studying these neurons we found that deep layer excitatory cell types can be classified into new subsets, based on structural and connectivity differences, and that chandelier interneurons not only innervate excitatory neuron initial segments as previously described, but also each others initial segments. Furthermore, among the thousands of weak connections established on each neuron, there exist rarer highly powerful axonal inputs that establish multi-synaptic contacts (up to [~]20 synapses) with target neurons. Our analysis indicates that these strong inputs are specific, and allow small numbers of axons to have an outsized role in the activity of some of their postsynaptic partners.

neuroscience↗

bioRxiv2021

Multiview super-resolution microscopy

We enhance the performance of confocal microscopy over imaging scales spanning tens of nanometers to millimeters in space and milliseconds to hours in time, improving volumetric resolution more than 10-fold while simultaneously reducing phototoxicity. We achieve these gains via an integrated, four-pronged approach: 1) developing compact line-scanners that enable sensitive, rapid, diffraction-limited imaging over large areas; 2) combining line-scanning with multiview imaging, developing reconstruction algorithms that improve resolution isotropy and recover signal otherwise lost to scattering; 3) adapting techniques from structured illumination microscopy, achieving super-resolution imaging in densely labeled, thick samples; 4) synergizing deep learning with these advances, further improving imaging speed, resolution and duration. We demonstrate these capabilities on more than twenty distinct fixed and live samples, including protein distributions in single cells; nuclei and developing neurons in Caenorhabditis elegans embryos, larvae, and adults; myoblasts in Drosophila wing imaginal disks; and mouse renal, esophageal, cardiac, and brain tissues.

bioengineering↗

bioRxiv2021

Structure-Function Relationships of the Vertebral Endplate

BackgroundAlthough deformation and fracture of the vertebral endplate have been implicated in spinal conditions such as vertebral fracture and disc degeneration, few biomechanical studies of this structure are available. The goal of this study was to quantify the mechanical behavior of the vertebral endplate. MethodsEight-five rectangular specimens were dissected from the superior and/or inferior central endplates of human lumbar spine segments L1-L4. Micro-computed tomography (CT) imaging, four-point-bend testing, and ashing were performed to quantify the apparent elastic modulus and yield stress (modulus and yield stress, respectively, of the porous vertebral endplate), tissue yield stress (yield stress of the tissue of the vertebral endplate, excluding pores), ultimate strain, fracture strain, bone volume fraction (BV/TV), bone mineral density (BMD), and various measures of tissue density and composition (tissue mineral density, ash fraction, and ash density). Regression was used to assess the dependence of mechanical properties on density and composition. ResultsWide variations in elastic and failure properties, and in density and tissue composition, were observed. BMD and BV/TV were good predictors of many of the apparent-level mechanical properties, including modulus, yield stress, and in the case of the inferior vertebral endplate, failure strains. Similar values of the mechanical properties were noted between superior and inferior vertebral endplates. In contrast to the dependence of apparent stiffness and strength on BMD and BV/TV, none of the mechanical properties depended on any of the tissue-level density measurements. ConclusionThe dependence of many of the mechanical properties of the vertebral endplate on BV/TV and BMD suggests possibilities for non-invasive assessment of how this region of the spine behaves during habitual and injurious loading. Further study of the non-mineral components of the endplate tissue is required to understand how the composition of this tissue may influence the overall mechanical behavior of the vertebral endplate.

bioengineering↗

bioRxiv2021

The Taxus genome provides insights into paclitaxel biosynthesis

The ancient gymnosperm genus Taxus is the exclusive source of the anticancer drug paclitaxel, yet no reference genome sequences are available for comprehensively elucidating the paclitaxel biosynthesis pathway. We have completed a chromosome-level genome of Taxus chinensis var. mairei with a total length of 10.23 Gb. Taxus shared an ancestral whole-genome duplication with the coniferophyte lineage and underwent distinct transposon evolution. We discovered a unique physical and functional grouping of CYP725As (cytochrome P450) in the Taxus genome for paclitaxel biosynthesis. We also identified a gene cluster in the taxadiene biosynthesis, which was mainly formed by gene duplications. This study will facilitate the elucidation of paclitaxel biosynthesis and unleash the biotechnological potential of Taxus. One Sentence SummaryA chromosome-level genome assembly of Taxus chinensis var. mairei uncovers its unique genome evolution process and genetic architectures for the paclitaxel biosynthesis pathway.

genomics↗

bioRxiv2021

Nucleic acid delivery of immune-focused SARS-CoV-2 nanoparticles drive rapid and potent immunogenicity capable of single-dose protection

Antibodies from SARS-CoV-2 vaccines may target epitopes which reduce durability or increase the potential for escape from vaccine-induced immunity. Using a novel synthetic vaccinology pipeline, we developed rationally immune focused SARS-CoV-2 Spike-based vaccines. N-linked glycans can be employed to alter antibody responses to infection and vaccines. Utilizing computational modeling and comprehensive in vitro screening, we incorporated glycans into the Spike Receptor-Binding Domain (RBD) and assessed antigenic profiles. We developed glycan coated RBD immunogens and engineered seven multivalent configurations. Advanced DNA delivery of engineered nanoparticle vaccines rapidly elicited potent neutralizing antibodies in guinea pigs, hamsters and multiple mouse models, including human ACE2 and human B cell repertoire transgenics. RBD nanoparticles encoding wild-type and the P.1 SARS-CoV-2 variant induced high levels of cross-neutralizing antibodies. Single, low dose immunization protected against a lethal SARS-CoV-2 challenge. Single-dose coronavirus vaccines via DNA-launched nanoparticles provide a platform for rapid clinical translation of novel, potent coronavirus vaccines.

immunology↗

bioRxiv2021

Image-based Motion Artifact Reduction on Liver Dynamic Contrast Enhanced MRI

Liver MRI images often suffer degraded quality from ghosting or blurring artifact caused by patient respiratory or bulk motion. In this study, we developed a two-stage deep learning model to reduce motion artifact on dynamic contrast enhanced (DCE) liver MRIs. The stage-I network utilized a deep residual network with a densely connected multi-resolution block (DRN-DCMB) network to remove the majority of motion artifacts. The stage-II network applied the perceptual loss to preserve image structural features by updating the parameters of the stage-I network via backpropagation. The stage-I network was trained using small image patches simulated with five types of motion, i.e., rotational, sinusoidal, random, elastic deformation and through-plane, to mimic actual liver motion patterns. The stage-II network training used full-size images with the same types of motion as the stage-I network. The motion reduction deep learning model was testing using simulated motion images and images with real motion artifacts. The resulted images after two-stage processing demonstrated substantially reduced motion artifacts while preserved anatomic details without image blurriness. This model outperformed existing methods of motion reduction artifact on liver DCE-MRI.

bioinformatics↗

bioRxiv2021

Evidence for continent-wide convergent evolution and stasis throughout 150 years of a biological invasion

The extent to which evolution can rescue a species from extinction, or facilitate range expansion, depends critically on the rate, duration, and geographical extent of the evolutionary response to natural selection. Adaptive evolution can occur quickly, but the duration and geographical extent of contemporary evolution in natural systems remains poorly studied. This is particularly true for species with large geographical ranges and for timescales that lie between long-term field experiments and the fossil record. Here, we introduce the Virtual Common Garden (VCG) to investigate phenotypic evolution in natural history collections while controlling for phenotypic plasticity in response to local growing conditions. Reconstructing 150 years of evolution in Lythrum salicaria (purple loosestrife) as it invaded North America, we analyze phenology measurements of 3,429 herbarium records, reconstruct growing conditions from more than 12 million local temperature records, and validate predictions across three common gardens spanning 10 degrees of latitude. We find that phenology clines have evolved along parallel climatic gradients, repeatedly throughout the range, during the first century of evolution. Thereafter, the rate of microevolution stalls, recapitulating macroevolutionary stasis observed in the fossil record. Our study demonstrates that preserved specimens are a critical resource for investigating limits to evolution in natural populations. Our results show how natural selection and trade-offs measured in field studies predict adaptive divergence observable in herbarium specimens over 15 decades at a continental scale.

evolutionary biology↗

bioRxiv2021

Ultrapotent SARS-CoV-2 neutralizing antibodies with protective efficacy against newly emerged mutational variants

Accumulating mutations in the SARS-CoV-2 Spike (S) protein can increase the possibility of immune escape, challenging the present COVID-19 prophylaxis and clinical interventions. Here, 3 receptor binding domain (RBD) specific monoclonal antibodies (mAbs), 58G6, 510A5 and 13G9, with high neutralizing potency blocking authentic SARS-CoV-2 virus displayed remarkable efficacy against authentic B.1.351 virus. Each of these 3 mAbs in combination with one neutralizing Ab recognizing non-competing epitope exhibited synergistic effect against authentic SARS-CoV-2 virus. Surprisingly, structural analysis revealed that 58G6 and 13G9, encoded by the IGHV1-58 and the IGKV3-20 germline genes, both recognized the steric region S470-495 on the RBD, overlapping the E484K mutation presented in B.1.351. Also, 58G6 directly bound to another region S450-458 in the RBD. Significantly, 58G6 and 510A5 both demonstrated prophylactic efficacy against authentic SARS-CoV-2 and B.1.351 viruses in the transgenic mice expressing human ACE2 (hACE2), protecting weight loss and reducing virus loads. These 2 ultrapotent neutralizing Abs can be promising candidates to fulfill the urgent needs for the prolonged COVID-19 pandemic.

immunology↗

bioRxiv2021

Assessing the origins of the European Plagues following the Black Death: a synthesis of genomic, historical and ecological information

The Second Plague Pandemic started in Europe with the Black Death in 1346 and lasted until the 19th century. Based on ancient DNA studies, there is a scientific disagreement over whether the bacterium, Yersinia pestis, came into Europe once (Hypothesis 1), or repeatedly over the following four centuries (Hypothesis 2). Here we synthesize the most updated phylogeny together with historical, archeological, evolutionary and ecological information. On the basis of this holistic view, we conclude that Hypothesis 2 is the most plausible. We also suggest that Y. pestis lineages might have developed attenuated virulence during transmission, which can explain the convergent evolutionary signals, including pla-decay, that appeared at the end of the pandemics. Significance StatementOver the last few years there has been a great deal of scientific debate regarding whether the plague bacterium, Yersinia pestis, spread from a Western European reservoir during the Second Plague Pandemic, or if it repeatedly came to Europe from Asia. Here we make a synthesis of the available evidence, including genomes of ancient DNA, historical, archeological and ecological information. We conclude that the bacterium most likely came to Europe from Asia several times during the Second Plague Pandemic.

evolutionary biology↗

bioRxiv2021

Analyzing Brain Morphology in Alzheimer's Disease Using Discriminative and Generative Spiral Networks

Several patterns of atrophy have been identified and strongly related to Alzheimers disease (AD) pathology and its progression. Morphological changes in brain shape have been identified up to ten years before clinical diagnoses of AD, making its early detection more relevant. We propose novel geometric deep learning frameworks for the analysis of brain shape in the context of neurodegeneration caused by AD. Our deep neural networks learn low-dimensional shape descriptors of multiple neuroanatomical structures, instead of handcrafted features for each structure. A discriminative network using spiral convolution on 3D meshes is constructed for the in-vivo binary classification of AD from healthy controls (HCs) using a fast and efficient "spiral" convolution operator on 3D triangular mesh surfaces of human brain subcortical structures extracted from T1-weighted magnetic resonance imaging (MRI). Our network architecture consists of modular learning blocks using residual connections to improve overall classifier performance. In this work: (1) a discriminative network is used to analyze the efficacy of disease classification using input data from multiple brain structures and compared to using a single hemisphere or a single structure. It also outperforms prior work using spectral graph convolution on the same the same tasks, as well as alternative methods that operate on intermediate point cloud representations of 3D shapes. (2) Additionally, visual interpretations for regions on the surface of brain structures that are associated to true positive AD predictions are generated and fall in accordance with the current reports on the structural localization of pathological changes associated to AD. (3) A conditional generative network is also implemented to analyze the effects of phenotypic priors given to the model (i.e. AD diagnosis) in generating subcortical structures. The generated surface meshes by our model indicate learned morphological differences in the presence of AD that agrees with the current literature on patterns of atrophy associated to the disease. In particular, our inference results demonstrate an overall reduction in subcortical mesh volume and surface area in the presence of AD, especially in the hippocampus. The low-dimensional shape descriptors obtained by our generative model are also evaluated in our discriminative baseline comparisons versus our discriminative network and the alternative shape-based approaches.

neuroscience↗

bioRxiv2021

A quantile integral linear model to quantify genetic effects on phenotypic variability

Detecting genetic variants associated with the variance of complex traits, i.e. variance quantitative trait loci (vQTL), can provide crucial insights into the interplay between genes and environments and how they jointly shape human phenotypes in the population. We propose a quantile integral linear model (QUAIL) to estimate genetic effects on trait variability. Through extensive simulations and analyses of real data, we demonstrate that QUAIL provides computationally efficient and statistically powerful vQTL mapping that is robust to non-Gaussian phenotypes and confounding effects on phenotypic variability. Applied to UK Biobank (N=375,791), QUAIL identified 11 novel vQTL for body mass index (BMI). Top vQTL findings showed substantial enrichment for interactions with physical activities and sedentary behavior. Further, variance polygenic scores (vPGS) based on QUAIL effect estimates showed superior predictive performance on both population-level and within-individual BMI variability compared to existing approaches. Overall, QUAIL is a unified framework to quantify genetic effects on the phenotypic variability at both single-variant and vPGS levels. It addresses critical limitations in existing approaches and may have broad applications in future gene-environment interaction studies.

genetics↗