Biology subjects

Wen, H.

Publications and source records attributed to Wen, H..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

Single-cell analysis of Rohon-Beard neurons implicates Fgf signaling in axon maintenance and cell survival

Peripheral sensory neurons are a critical part of the nervous system that transmit a multitude of sensory stimuli to the central nervous system. During larval and juvenile stages in zebrafish, this function is mediated by Rohon-Beard somatosensory neurons (RBs). RBs are optically accessible and amenable to experimental manipulation, making them a powerful system for mechanistic investigation of sensory neurons. Previous studies provided evidence that RBs fall into multiple subclasses; however, the number and molecular make up of these potential RB subtypes have not been well defined. Using a single-cell RNA sequencing (scRNA-seq) approach, we demonstrate that larval RBs in zebrafish fall into three, largely non-overlapping classes of neurons. We also show that RBs are molecularly distinct from trigeminal neurons in zebrafish. Cross-species transcriptional analysis indicates that one RB subclass is similar to a mammalian group of A-fiber sensory neurons. Another RB subclass is predicted to sense multiple modalities, including mechanical stimulation and chemical irritants. We leveraged our scRNA-seq data to determine that the fibroblast growth factor (Fgf) pathway is active in RBs. Pharmacological and genetic inhibition of this pathway led to defects in axon maintenance and RB cell death. Moreover, this can be phenocopied by treatment with dovitinib, an FDA-approved Fgf inhibitor with a common side effect of peripheral neuropathy. Importantly, dovitinib-mediated axon loss can be suppressed by loss of Sarm1, a positive regulator of neuronal cell death and axonal injury. This offers a molecular target for future clinical intervention to fight neurotoxic effects of this drug.

neuroscience↗

bioRxiv2023

UNI-RNA: UNIVERSAL PRE-TRAINED MODELS REVOLUTIONIZE RNA RESEARCH

AO_SCPLOWBSTRACTC_SCPLOWRNA molecules play a crucial role as intermediaries in diverse biological processes. Attaining a profound understanding of their function can substantially enhance our comprehension of lifes activities and facilitate drug development for numerous diseases. The advent of high-throughput sequencing technologies makes vast amounts of RNA sequence data accessible, which contains invaluable information and knowledge. However, deriving insights for further application from such an immense volume of data poses a significant challenge. Fortunately, recent advancements in pre-trained models have surfaced as a revolutionary solution for addressing such challenges owing to their exceptional ability to automatically mine and extract hidden knowledge from massive datasets. Inspired by the past successes, we developed a novel context-aware deep learning model named Uni-RNA that performs pre-training on the largest dataset of RNA sequences at the unprecedented scale to date. During this process, our model autonomously unraveled the obscured evolutionary and structural information embedded within the RNA sequences. As a result, through fine-tuning, our model achieved the state-of-the-art (SOTA) performances in a spectrum of downstream tasks, including both structural and functional predictions. Overall, Uni-RNA established a new research paradigm empowered by the large pre-trained model in the field of RNA, enabling the community to unlock the power of AI at a whole new level to significantly expedite the pace of research and foster groundbreaking discoveries.

bioinformatics↗

bioRxiv2023

A generalized approach to genetic drift and its applications -- I. An example of the evolution of ribosomal RNA genes

Multi-copy gene systems that evolve within, as well as between, individuals are common. They include viruses, mitochondrial DNAs, multi-gene families etc. The paradox is that neutral evolution in two stages should be slower than single-copy systems but the opposite is often true. We now apply the Haldane model, recently generalized as the GH model (1), to quantify genetic drift in mammalian ribosomal RNA genes (rDNAs). On average, the copy number (C) is 150 - 300 per haploid. A neutral mutation in rDNA should take 4NC* generations to become fixed (N, the population size; C *, the effective copy number within individuals). While C > C* >> 1 is expected, the observed fixation time in mouse is < 4N, leading to the paradox of C* < 1. Genetic drift of rRNA genes thus appears 10-100 times stronger than in single-copy genes. The large increases are driven by a host of molecular mechanisms such as gene conversion and unequal crossover. Although each mechanism of drift is very difficult to quantify, the GH model permits the estimation of their total effects that constitute the aggregate "evolutionary noises". In humans, the fixation rate of rRNA genes is higher than the theoretical maximum of drift, hence, justifying the inference of adaptive evolution. In conclusion, the stochastic evolution in multi-copy gene systems, including viruses and others, can be effectively tracked by GH model.

evolutionary biology↗

bioRxiv2023

Single cell RNA-seq analysis of spinal locomotor circuitry in larval zebrafish

Identification of the neuronal types that form the specialized circuits controlling distinct behaviors has benefited greatly from the simplicity offered by zebrafish. Electrophysiological studies have shown that additional to connectivity, understanding of circuitry requires identification of functional specializations among individual circuit components, such as those that regulate levels of transmitter release and neuronal excitability. In this study we use single cell RNA sequencing (scRNAseq) to identify the molecular bases for functional distinctions between motoneuron types that are causal to their differential roles in swimming. The primary motoneuron (PMn) in particular, expresses high levels of a unique combination of voltage-dependent ion channel types and synaptic proteins termed functional cassettes. The ion channel types are specialized for promoting high frequency firing of action potentials and augmented transmitter release at the neuromuscular junction, both contributing to greater power generation. Our transcriptional profiling of spinal neurons further assigns expression of this cassette to specific interneuron types also involved in the central circuitry controlling high speed swimming and escape behaviors. Our analysis highlights the utility of scRNAseq in functional characterization of neuronal circuitry, in addition to providing a gene expression resource for studying cell type diversity.

neuroscience↗

bioRxiv2023

Endodermal BRD4 mediates epithelial-mesenchymal crosstalk during lung development

Lung morphogenesis relies on diverse cell intrinsic and extrinsic mechanisms to ensure proper cellular differentiation and compartmentalization. Using genetic mouse models, tissue explants, and transcriptomic analysis, we demonstrate that the epigenetic reader Bromodomain Containing Protein 4 (BRD4) is required for lung morphogenesis and perinatal survival. Endodermal BRD4 deletion impairs epithelial-mesenchymal crosstalk, leading to disrupted proximal-distal patterning and branching morphogenesis. These early defects result in dilated airways and the formation of cystic distal airway structures, containing both airway and alveolar features. Moreover, BRD4 deficient lungs exhibit abnormal airway and alveolar epithelial cell lineage allocation and differentiation. Restoration of SHH signaling partially rescues defects due to loss of BRD4, suggesting a role for BRD4 in regulating the SHH-FGF signaling axis. Together, these data identify the essential role of Brd4 in lung development to ensure proper intercellular crosstalk to enable proper lineage specification, identity, and maturation.

developmental biology↗

bioRxiv2023

Photosynthetic living fibers fabrication from algal-bacterial consortia with controlled spatial distribution

Living materials that combine active cells and synthetic matrix materials have become a promising research field in recent years. While multicellular systems present exclusive benefits in developing living materials over single-cell systems, creating artificial multicellular systems can be challenging due to the difficulty in controlling the multicellular assemblies and the complexity of cell-to-cell interactions. Here, we propose a co-culture platform capable of isolating and controlling the spatial distribution of algal-bacterial consortia, which can be used to construct photosynthetic living fibers. Through coaxial extrusion-based 3D printing, hydrogel fibers containing bacteria or algae can be deposited into designated structures and further processed into materials with precise geometries. In addition, the photosynthetic living fibers demonstrate a significant synergistic catalytic effect resulting from the immobilization of both bacteria and algae, which effectively optimize sewage treatment for bioremediation purposes. The integration of microbial consortia and 3D printing gives functional living materials that have promising applications in biocatalysis, biosensing, and biomedicine. Our approach provides an optimized solution for constructing efficient multicellular systems and opens a new avenue for the development of advanced materials.

bioengineering↗

bioRxiv2023

SpatialCTD: a large-scale TME spatial transcriptomic dataset to evaluate cell type deconvolution for immuno-oncology

Recent technological advancements have enabled spatially resolved transcriptomic profiling but at multi-cellular resolution. The task of cell type deconvolution has been introduced to disentangle discrete cell types from such multi-cellular spots. However, existing datasets for cell type deconvolution are limited in scale, predominantly encompassing data on mice, and are not designed for human immuno-oncology. In order to overcome these limitations and promote comprehensive investigation of cell type deconvolution for human immuno-oncology, we introduce a large-scale spatial transcriptomic dataset named SO_SCPLOWPATIALC_SCPLOWCTD, encompassing 1.8 million cells from the human tumor microenvironment across the lung, kidney, and liver. Distinct from existing approaches that primarily depend on single-cell RNA sequencing data as a reference without incorporating spatial information, we introduce Graph Neural Network-based method (i.e., GNNDO_SCPLOWECONVOLVERC_SCPLOW) that effectively utilize the spatial information from reference samples, and extensive experiments show that GNNDO_SCPLOWECONVOLVERC_SCPLOW often outperforms existing state-of-the-art methods by a substantial margin, without requiring single-cell RNA-seq data. To enable comprehensive evaluations on spatial transcriptomics data from flexible protocols, we provide an online tool capable of converting spatial transcriptomic data from other platforms (e.g., 10x Visium, MERFISH and sci-Space) into pseudo spots, featuring adjustable spot size. The SO_SCPLOWPATIALC_SCPLOWCTD dataset and GNNDO_SCPLOWECONVOLVERC_SCPLOW implementation are available at https://github.com/OmicsML/SpatialCTD, and the online converter tool can be accessed at https://omicsml.github.io/SpatialCTD/.

bioinformatics↗

bioRxiv2023

Tubular Mitochondrial Pyruvate Carrier Disruption Elicits Redox Adaptations that Protect from Acute Kidney Injury

Energy-intensive kidney reabsorption processes essential for normal whole-body function are maintained by tubular epithelial cell metabolism. Tubular metabolism changes markedly following acute kidney injury (AKI), but which changes are adaptive versus maladaptive remain poorly understood. In publicly available data sets, we noticed a consistent downregulation of the mitochondrial pyruvate carrier (MPC) after AKI, which we experimentally confirmed. To test the functional consequences of MPC downregulation, we generated novel tubular epithelial cell-specific Mpc1 knockout (MPC TubKO) mice. 13C-glucose tracing, steady-state metabolomic profiling, and enzymatic activity assays revealed that MPC TubKO coordinately increased activities of the pentose phosphate pathway and the glutathione and thioredoxin oxidant defense systems. Following rhabdomyolysis-induced AKI, MPC TubKO decreased markers of kidney injury and oxidative damage and strikingly increased survival. Our findings suggest that decreased mitochondrial pyruvate uptake is a central adaptive response following AKI and raise the possibility of therapeutically modulating the MPC to attenuate AKI severity.

biochemistry↗

bioRxiv2022

Investigation of a mathematical model describing global cancer growth and treatment: An inhomogeneous model based on the generalized logistic equation

Tumor growth is manifestation of the evolution of a complex system. Researchers have limited scope of modelling studies on specific aspects or stages of the process. It has led to unsatisfactory explanation of clinical observations. We hereby demonstrated that an inhomogeneous model built on the generalized logistic equation could serve better. It was developed to describe the whole process of tumor progression, clinically observed independence of index tumor growth from spread of the disease and growth deceleration during early stage of solid tumors. It was validated by simulating the coexistence of exponential and sigmoidal growth in chronic lymphocytic leukaemia, theories of tumor heterogeneity, as well as by accommodating notions pertaining to tumor treatment and prognosis. We thought therefore it was an interesting and not unjustifiable description of actual tumor growth in human body and hoped it might encourage more researchers to look at tumor modelling from a clinical perspective.

cancer biology↗

bioRxiv2022

Distinct structure and gating mechanism in diverse NMDA receptors with GluN2C and GluN2D subunits

N-Methyl-D-Aspartate (NMDA) receptors are essential for many brain functions. These receptors are heterotetramers typically comprising two GluN1 subunits and two GluN2 subunits. The latter could alternate among four subtypes (N2A-N2D) and determine the functional diversity of NMDA receptors1, 2. For example, receptors containing N2C or N2D exhibit 50-fold lower channel open probability (Po) than those containing N2A (ref.3-5). Structures of N2A- and N2B-containing receptors have been extensively characterized, providing molecular basis for understanding NMDA receptor function6-14. Here we report the cryo-EM structures of N1-N2D and N1-N2C di-heterotetramers (di-receptors), and N1-N2A-N2C tri-heterotetramer (tri-receptor) at a resolution up to 3.0 [A]. Structural analysis showed that the bilobate N-terminal domain (NTD) in N2D adopted an intrinsic closed conformation, leading to a compact NTD tetramer in N1-N2D receptor. Functional studies further demonstrated that, in di-receptors containing N2D but not N2A or N2B, crosslinking NTD at the tetrameric interface had no effect on channel activity, while crosslinking ligand-binding domain (LBD) of two N1 protomers significantly elevated Po. Surprisingly, we found that the N1-N2C di-receptors spontaneously oscillated between symmetric and asymmetric conformation. The later one occupied a predominant population, whereby two N2C protomers exhibited distinct conformation. This asymmetry, which was also found to a lesser extent in N1-N2A di-receptor10, was further locked by the binding of an N2C-specific allosteric potentiator PYD-106 to a unique binding pocket between NTD and LBD in only one N2C protomer. Finally, N2A and N2C in the N1-N2A-N2C tri-receptor displayed the conformation close to that found in one protomer of N1-N2A and N1-N2C di-receptors, respectively. These findings provide a comprehensive structural understanding of diverse functional properties of major NMDA receptor subtypes.

neuroscience↗

bioRxiv2022

DANCE: A Deep Learning Library and Benchmark for Single-Cell Analysis

In the realm of single-cell analysis, computational approaches have brought an increasing number of fantastic prospects for innovation and invention. Meanwhile, it also presents enormous hurdles to reproducing the results of these models due to their diversity and complexity. In addition, the lack of gold-standard benchmark datasets, metrics, and implementations prevents systematic evaluations and fair comparisons of available methods. Thus, we introduce the DANCE platform, the first standard, generic, and extensible benchmark platform for accessing and evaluating computational methods across the spectrum of benchmark datasets for numerous single-cell analysis tasks. Currently, DANCE supports 3 modules and 8 popular tasks with 32 state-of-art methods on 21 benchmark datasets. People can easily reproduce the results of supported algorithms across major benchmark datasets via minimal efforts (e.g., only one command line). In addition, DANCE provides an ecosystem of deep learning architectures and tools for researchers to develop their own models conveniently. The goal of DANCE is to accelerate the development of deep learning models with complete validation and facilitate the overall advancement of single-cell analysis research. DANCE is an open-source python package that welcomes all kinds of contributions. All resources are integrated and available at https://omicsml.ai/.

bioinformatics↗

bioRxiv2022

Uni-Fold Symmetry: Harnessing Symmetry in Folding Large Protein Complexes

Deep folding models have revolutionized the conventional methods of protein complex prediction. However, applying them to large protein oligomers is not easy. These models generally require copying the sequences of identical subunits to capture the in-between relationships. Accordingly, the scales of target protein complexes are strictly limited due to the cubic complexity of these models. To address this issue, we propose UF-Symmetry (Uni-Fold Symmetry), which is extricated from the need of sequence copying via harnessing the intrinsic symmetry of large protein oligomers. Taking the sequences of the asymmetric unit (AU) and a pre-specified symmetry group, UF-Symmetry learns to fold the AU and to assemble the complex structure in an end-to-end manner. By reducing the input scales from entire assemblies to AUs, UF-Symmetry allows to predict much larger assemblies with significant acceleration: for a complex of 4-fold cyclic symmetry (C4) and AU size of 512, UF-Symmetry achieves approximately 20 times acceleration to current methods. On a benchmark of recently released PDB multimers, UF-Symmetry approximately halves the failure rate of current methods and achieves approaching accuracy on commonly successful cases.

bioinformatics↗

bioRxiv2022

Complex functional phenotypes of NMDA receptor disease variants

NMDA receptors have essential roles in the physiology of central excitatory synapses and their dysfunction causes severe neuropsychiatric symptoms. Recently, a series of genetic variants have been identified in patients, however, functional information about these variants is sparse and their role in pathogenesis insufficiently known. Here we investigate the mechanism by which two GluN2A variants may be pathogenic. We use molecular dynamics simulation and single-molecule electrophysiology to examine the contribution of GluN2A subunit-residues, P552 and F652, and their pathogenic substitutions, P552R and F652V, affect receptor functions. We found that P552 and F652 interact during the receptors normal activity cycle; the interaction stabilizes receptors in open conformations and is required for a normal electrical response. Engineering shorter side-chains at these positions (P552A and/or F652V) caused a loss of interaction energy and produced receptors with severe gating, conductance, and permeability deficits. In contrast, the P552R sidechain resulted in stronger interaction and produced a distinct, yet still drastically abnormal electrical response. These results identify the dynamic contact between P552 and F652 as a critical step in the NMDA receptor activation, and show that both increased and reduced communication through this interaction cause dysfunction. Results show that subtle differences in NMDA receptor primary structure can generate complex phenotypic alterations whose binary classification is too simplistic to serve as a therapeutic guide. Main findingsO_LITwo NMDA receptor residues whose substitution results in encephalopathies, were found to form new interactions during activation, and the energy provided by this interaction is required for normal receptor gating. C_LIO_LIExperimental substitutions of these residues that change the strength of their interaction reduce the receptor open probability, unitary conductance, and calcium permeability. C_LIO_LIReceptors with variations at these positions identified in patients display a broad range of both gain- and loss-of-function changes depending on the stimulation protocol. C_LI

biophysics↗

bioRxiv2022

A common mechanism of temperature-sensing in thermoTRP channels

Detecting temperature is crucial for the survival of living organisms. Though the thermo transient receptor potential (thermoTRP) channels, such as TRPV1 or TRPM8, have been identified as prototypic heat or cold sensors, respectively, how they detect temperature remains elusive. Here we first identified groups of clustered residues in these channels that undergo burial/exposure conformational rearrangements during temperature activation by analyzing available protein structures or hydroxyl radical footprinting-mass spectroscopy (HRF-MS). By systematically perturbing water-protein interactions at these residues, we found that the temperature sensitivity in these channels were modulated in accordance with the sidechain hydrophobicity. The changes in energy associated with changes in water-protein interactions were sufficient for thermo activation. Therefore, our study has established that the water-protein interactions as a common mechanism underlying temperature sensing in TRPM8 and TRPV1.

biophysics↗

bioRxiv2022

A CXCL12 morphogen gradient uncovers lung endothelial heterogeneity and promotes distal vascular growth

In adults, there is a growing amount of data uncovering the cellular diversity of the pulmonary circulation and mechanisms governing vascular repair after injury, however, molecular and cellular mechanisms contributing to the morphogenesis and growth of the pulmonary vasculature during embryonic development are less clear. Importantly, deficits in vascular development lead to a large number of lung diseases in children, indicating a need to uncover fetal programs that promote pulmonary vascular growth. To address this, we used a transgenic mouse reporter for expression of Cxcl12, an arterial hallmark gene, and performed single-cell RNA sequencing on isolated Cxcl12-DsRed+ endothelium to assess cellular heterogeneity within pulmonary endothelium. Combining cell annotation, gene ontology analysis, and spatial transcriptomics allowed us to segregate the developing artery into spatially and functionally distinct novel subpopulations. In addition, expression of Cxcl12 suggests a morphogen gradient from arteries to capillaries, suggesting directed cell migration for pulmonary vascular development. Disruption of this gradient led to abnormal branching and pulmonary vascular hypoplasia. These data provide evidence for arterial endothelial functional heterogeneity and reveal conserved signaling mechanisms essential for pulmonary vascular development.

developmental biology↗

bioRxiv2022

Mitochondrial Network Configuration Influences Sarcomere and Myosin Filament Structure in Striated Muscles

Sustained muscle contraction occurs through interactions between actin and myosin filaments within sarcomeres and requires a constant supply of adenosine triphosphate (ATP) from nearby mitochondria. However, it remains unclear how different physical configurations between sarcomeres and mitochondria alter the energetic support for contractile function. Here, we show that sarcomere cross-sectional area (CSA) varies along its length in a cell type-dependent manner where the reduction in Z-disk CSA relative to the sarcomere center is closely coordinated with mitochondrial network configuration in flies, mice, and humans. Further, we find myosin filaments near the sarcomere periphery are curved relative to interior filaments with greater curvature for filaments near mitochondria compared to sarcoplasmic reticulum. Finally, we demonstrate smaller myosin filament lattice spacing at filament ends than filament centers in a cell type-dependent manner. These data suggest both sarcomere structure and myofilament interactions are influenced by the location and orientation of mitochondria within muscle cells.

cell biology↗

bioRxiv2022

The runaway evolution of SARS-CoV-2 leading to the highly evolved Delta strain

In new epidemics after the host shift, the pathogens may experience accelerated evolution driven by novel selective pressures. When the accelerated evolution enters a positive feedback loop with the expanding epidemics, the pathogens runaway evolution may be triggered. To test this possibility in COVID-19, we analyze the extensive databases and identify 5 major waves of strains, one replacing the previous one in 2020 - 2021. The mutations differ entirely between waves and the number of mutations continues to increase, from 3-4 to 21-31. The latest wave is the Delta strain which accrues 31 new mutations to become highly prevalent. Interestingly, these new mutations in Delta strain emerge in multiple stages with each stage driven by 6 - 12 coding mutations that form a fitness group. In short, the evolution of SARS-CoV-2 from the oldest to the youngest wave, and from the earlier to the later stages of the Delta wave, is a process of acceleration with more and more mutations. The global increase in the viral population size (M(t), at time t) and the mutation accumulation (R(t)) may have indeed triggered the runaway evolution in late 2020, leading to the highly evolved Alpha and then Delta strain. To suppress the pandemic, it is crucial to break the positive feedback loop between M(t) and R(t), neither of which has yet to be effectively dampened by late 2021. New waves beyond Delta, hence, should not be surprising.

evolutionary biology↗

bioRxiv2021

Brain intrinsic connection patterns underlying tool processing in human adults are present in neonates and not in macaques

Tool understanding and use are supported by a dedicated left-lateralized, intrinsically connected network in the human adult brain. To examine this networks phylogenic and ontogenetic origins, we compared resting-state functional connectivity (rsFC) among regions subserving tool processing in human adults to rsFC among homologous regions in human neonates and macaque monkeys (adolescent and mature). These homologous regions formed an intrinsic network in human neonates, but not in macaques. Network topological patterns were highly similar between human adults and neonates, and significantly less so between humans and macaques. The premotor-parietal rsFC had most significant contribution to the formation of the neonate tool network. These results suggest that an intrinsic brain network potentially supporting tool processing exists in the human brain prior to individual tool use experiences, and that the premotor-parietal functional connection in particular offers a brain basis for complex tool behaviors specific to humans.

neuroscience↗