Biology subjects

Zhang, S.

Publications and source records attributed to Zhang, S..

At least 739 records · Page 41Linked to original sources

bioRxiv2022

STAMarker: Determining spatial domain-specific variable genes with saliency maps in deep learning

Spatial transcriptomics characterizes gene expression profiles while retaining the information of the spatial context, providing an unprecedented opportunity to understand cellular systems. One of the essential tasks in such data analysis is to determine spatially variable genes (SVGs), which demonstrate spatial expression patterns. Existing methods only consider genes individually and fail to model the inter-dependence of genes. To this end, we present an analytic tool STAMarker for robustly determining spatial domain-specific SVGs with saliency maps in deep learning. STAMarker is a three-stage ensemble framework consisting of graphattention autoencoders, multilayer perceptron (MLP) classifiers, and saliency map computation by the backpropagated gradient. We illustrate the effectiveness of STAMarker and compare it with three competing methods on four spatial transcriptomic data generated by various platforms. STAMarker considers all genes at once and is more robust when the dataset is very sparse. STAMarker could identify spatial domain-specific SVGs for characterizing spatial domains and enable in-depth analysis of the region of interest in the tissue section.

bioinformatics↗

bioRxiv2022

Sequencing by avidity enables high accuracy with low reagent consumption

We present avidity sequencing - a novel sequencing chemistry that separately optimizes the process of stepping along a DNA template and the process of identifying each nucleotide within the template. Nucleotide identification uses multivalent nucleotide ligands on dye-labeled cores to form polymerase-polymer nucleotide complexes bound to clonal copies of DNA targets. These polymer-nucleotide substrates, termed avidites, decrease the required concentration of reporting nucleotides from micromolar to nanomolar, and yield negligible dissociation rates. We demonstrate the use of avidites as a key component of a sequencing technology that surpasses Q40 accuracy and enables a diversity of applications that include single cell RNA-seq and whole human genome sequencing. We also show the advantages of this technology in sequencing through long homopolymers.

genomics↗

bioRxiv2022

Development of a novel oral treatment that rescues gait ataxia and retinal degeneration in a phenotypic mouse model of familial dysautonomia.

Familial Dysautonomia (FD) is a rare neurodegenerative disease caused by a splicing mutation in the Elongator complex protein 1 gene (ELP1). This mutation leads to the skipping of exon 20 and a tissue-specific reduction of ELP1 protein, mainly in the central and peripheral nervous systems. FD is a complex neurological disorder accompanied by severe gait ataxia and retinal degeneration. There is currently no effective treatment to restore ELP1 protein expression in individuals with FD, and the disease is ultimately fatal. After identifying kinetin as a small molecule able to correct the ELP1 splicing defect, we worked on its optimization to generate novel splicing modulator compounds (SMCs) that can be used in patients. Here, we optimize the potency, efficacy, and bio-distribution of second-generation kinetin derivatives to develop an oral treatment for FD that can efficiently pass the blood-brain barrier and correct the ELP1 splicing defect in the nervous system. We demonstrate that the novel compound, PTC258, efficiently restores correct ELP1 splicing in mouse tissues, including brain, and most importantly, prevents the progressive neuronal degeneration that is characteristic of FD. Postnatal oral administration of PTC258 to the phenotypic mouse model TgFD9;Elp1{Delta}20/flox increases full-length ELP1 transcript in a dose-dependent manner and leads to a two-fold increase in functional ELP1 protein in the brain. Remarkably, PTC258 treatment improves survival, gait ataxia, and retinal degeneration in the phenotypic FD mice. Our findings highlight the great therapeutic potential of this novel class of small molecules as an oral treatment for FD.

genetics↗

bioRxiv2022

CRISPR/FnCas12a-mediated efficient multiplex and iterative genome editing in bacterial plant pathogens without donor DNA templates

CRISPR-based genome editing technology is revolutionizing prokaryotic research, but it has been rarely studied in bacterial plant pathogens. Here, we have developed a targeted genome editing method with no requirement of donor templates for convenient and efficient gene knockout in Xanthomonas oryzae pv. oryzae (Xoo), one of the most important bacterial pathogens on rice, by employing the heterogenous CRISPR/Cas12a from Francisella novicida and NHEJ proteins from Mycobacterium tuberculosis. FnCas12a nuclease generated both small and large DNA deletions at the target sites as well as it enabled multiplex genome editing, gene cluster deletion and plasmid cure in the Xoo PXO99A strain. Accordingly, a non-TAL effector-free polymutant strain PXO99AD25E, which lacks all 25 Xop genes involved in Xoo pathogenesis, has been engineered through iterative genome editing. Whole-genome sequencing analysis indicated that FnCas12a did not have a noticeable off-target effect. In addition, we revealed that these strategies are also suitable for targeted genome editing in another bacterial plant pathogen Pseudomonas syringae pv. tomato (Pst). We believe that our bacterial genome editing method will greatly expand the CRISPR study on microorganisms and advance our understanding of the physiology and pathogenesis of Xoo.

microbiology↗

bioRxiv2022

A single-nucleus and spatial transcriptomic atlas of the COVID-19 liver reveals topological, functional, and regenerative organ disruption in patients

The molecular underpinnings of organ dysfunction in acute COVID-19 and its potential long-term sequelae are under intense investigation. To shed light on these in the context of liver function, we performed single-nucleus RNA-seq and spatial transcriptomic profiling of livers from 17 COVID-19 decedents. We identified hepatocytes positive for SARS-CoV-2 RNA with an expression phenotype resembling infected lung epithelial cells. Integrated analysis and comparisons with healthy controls revealed extensive changes in the cellular composition and expression states in COVID-19 liver, reflecting hepatocellular injury, ductular reaction, pathologic vascular expansion, and fibrogenesis. We also observed Kupffer cell proliferation and erythrocyte progenitors for the first time in a human liver single-cell atlas, resembling similar responses in liver injury in mice and in sepsis, respectively. Despite the absence of a clinical acute liver injury phenotype, endothelial cell composition was dramatically impacted in COVID-19, concomitantly with extensive alterations and profibrogenic activation of reactive cholangiocytes and mesenchymal cells. Our atlas provides novel insights into liver physiology and pathology in COVID-19 and forms a foundational resource for its investigation and understanding.

genomics↗

bioRxiv2022

A non-human primate model with Alzheimer's disease-like pathology induced by hippocampal overexpression of human tau

Alzheimers disease (AD) is one of the most burdening diseases of the century with no disease-modifying treatment yet. Non-human primates (NHPs) share genetic, anatomical and physiological similarities with humans, making them an ideal model for investigating the pathogenesis and therapeutics of AD. However, the applications of NHPs in AD research have been hindered by the paucity of spontaneous or induced monkey models for AD due to their long generation time, ethical considerations and technical challenges in making genetically modified monkeys. Here we developed an AD-like NHP model by overexpressing human tau in bilateral hippocampi of adult rhesus macaque monkeys. We evaluated the pathological features of these monkeys with immunostaining, cerebrospinal fluid (CSF) analysis, magnetic resonance imaging (MRI), positron emission tomography (PET) scan, and behavioral tests. We demonstrated that after hippocampal overexpression of human tau, the rhesus macaque monkeys displayed multiple pathological features of AD, including neurofibrillary tangle formation, neuronal loss, hippocampal atrophy, neuroinflammation, A{beta} clearance deficit, blood vessel damage and cognitive decline. This work establishes a human tau-induced AD-like NHP model that may facilitate mechanistic studies and therapeutic treatments for AD.

neuroscience↗

bioRxiv2022

Spatial organization of the 3D genome encodes gene co-expression programs in single cells

Deconstructing the mechanism by which the 3D genome encodes genetic information to generate diverse cell types during animal development is a major challenge in biology. The contrast between the elimination of chromatin loops and domains upon Cohesin loss and the lack of downstream gene expression changes at the cell population level instigates intense debates regarding the structure-function relationship between genome organization and gene regulation. Here, by analyzing single cells after acute Cohesin removal with sequencing and spatial genome imaging techniques, we discover that, instead of dictating population-wide gene expression levels, 3D genome topology mediated by Cohesin safeguards long-range gene co-expression correlations in single cells. Notably, Cohesin loss induces gene co-activation and chromatin co-opening between active domains in cis up to tens of megabase apart, far beyond the typical length scale of enhancer-promoter communication. In addition, Cohesin separates Mediator protein hubs, prevents active genes in cis from localizing into shared hubs and blocks intersegment transfer of diverse transcriptional regulators. Together, these results support that spatial organization of the 3D genome orchestrates dynamic long-range gene and chromatin co-regulation in single living cells.

genomics↗

bioRxiv2022

MdrDB: Mutation-induced drug resistance DataBase

AO_SCPLOWBSTRACTC_SCPLOWMutation-induced drug resistance - where the efficacy of drugs is diminished by structural changes in proteins - presents a significant challenge to drug development and the clinical treatment of disease. Understanding the effects of mutation on protein-ligand binding affinities is a key step in developing more effective drugs and therapies, but as a research community we are currently hindered by the lack of a comprehensive database of relevant information. To address this issue, we have developed MdrDB, a database of information related to changes in protein-ligand affinity caused by mutations in protein structure. MdrDB combines data from seven publicly available datasets with calculated biochemical features, as well as 3D structures computed with PyMOL and AlphaFold 2.0, to form the largest database of its kind. With 3D structural information provided for all samples, MdrDB was specifically created to have the size, breadth, and complexity to be useful for practical protein mutation studies and drug resistance modeling. The database brings together wild type and mutant protein-ligand complexes, binding affinity changes upon mutation ({Delta}{Delta}G), and biochemical features calculated from complexes to advance our understanding of mutation-induced drug resistance, the development of combination therapies, and the discovery of novel chemicals. In total, MdrDB contains 100,537 samples generated from 240 proteins (5,119 total PDB structures), 2,503 mutations, and 440 drugs. Of the total samples, 95,971 are based on available PDB structures, with the remaining 4,566 based on AlphaFold 2.0 predicted structures.

bioinformatics↗

bioRxiv2022

Key Genetic Determinants Driving Esophageal Squamous Cell Carcinoma Initiation and Immune Evasion

Background and aimsDespite recent progress in identifying aberrant genetic and epigenetic alterations in esophageal squamous cell carcinoma (ESCC), the mechanism of ESCC initiation remains unknown. MethodsUsing CRISPR/Cas 9-based genetic ablation, we targeted 9 genes (TP53, CDKN2A, NOTCH1, NOTCH3, KMT2D, KMT2C, FAT1, FAT4, and AJUBA) in murine esophageal organoids (EOs). Transcriptomic phenotypes of organoids and chemokine released by organoids were analyzed by single-cell RNA sequencing (scRNA-seq). Tumorigenicity and immune evasion of organoids were monitored by allograft transplantation. Human ESCC scRNA-seq datasets were analyzed to classify patients and find subsets relevant to organoid models and immune evasion. ResultsWe established 32 genetically engineered EOs and identified key genetic determinants that drive ESCC initiation. A single-cell transcriptomic analysis uncovered that Trp53, Cdkn2a, and Notch1 (PCN) triple-knockout (KO) induces neoplastic features of ESCC by generating cell lineage heterogeneity and high cell plasticity. PCN KO also generates an immunosuppressive niche enriched with exhausted T cells and M2 macrophages via the CCL2-CCR2 axis. Mechanistically, CDKN2A inactivation transactivates CCL2 via NF-{kappa}B. Moreover, comparative single-cell transcriptomic analyses stratified ESCC patients and identified a specific subtype recapitulating the PCN-type ESCC signatures, including the high expression of CCL2 and CD274/PD-L1. ConclusionsOur study unveils that loss of TP53, CDKN2A, and NOTCH1 induces esophageal neoplasia and immune evasion for ESCC initiation and proposes the CCL2 blockade as a viable option for targeting PCN-type ESCC.

cancer biology↗

bioRxiv2022

PCLAF-DREAM Drives Alveolar Cell Plasticity for Lung Regeneration

Spatiotemporal control of stem and progenitor cells is essential for lung regeneration, the failure of which leads to lung disease. However, the mechanism of alveolar cell plasticity during regeneration remains elusive. We previously found that PCLAF remodels the DREAM complex for cell cycle re-entry. PCLAF expression is specifically enriched in proliferating lung progenitor cells, along with the DREAM target genes by lung damage. Genetic ablation of Pclaf inhibited alveolar type I (AT1) cell regeneration from alveolar type II (AT2) cells, inducing lung fibrosis. Mechanistically, the PCLAF-DREAM complex directly transactivates CLIC4, promoting TGF-{beta} signaling that regulates the balance between AT1 and AT2 cells. Furthermore, a drug candidate that mimics the PCLAF-DREAM transcriptional signatures for lung regeneration was identified and validated in organoids and mice. Our study unveils an unexpected role of the PCLAF-DREAM axis in controlling alveolar cell plasticity for lung regeneration and proposes a viable option for lung fibrosis prevention. One Sentence SummaryPCLAF-DREAM-driven alveolar cell plasticity is crucial for lung regeneration and can be pharmacologically targeted as a therapeutic strategy for lung fibrosis.

cell biology↗

bioRxiv2022

Domain Adaptive Neural Inference for Neurons, Microcircuits and Networks

Accurately inferring neural circuit connectivity from in vivo recordings is essential for understanding the computations that support behavior and cognition. However, current deep learning approaches are limited by incomplete observability and the lack of ground-truth labels in real experiments. Consequently, models are often trained on synthetic data, which leads to the well-known "model mismatch" problem when simulated dynamics diverge from true neural activity. To overcome these challenges, we present Deep Domain-Adaptive Matching (DeepDAM), a training framework that adaptively matches synthetic and in vivo data domains for neural connectivity inference. Specifically, DeepDAM fine-tunes deep neural networks on a combined dataset of synthetic simulations and unlabeled in vivo recordings, aligning the models feature representations with real neural dynamics to mitigate model mismatch. We demonstrate this approach in rodent hippocampal CA1 circuits as a proof-of-concept, achieving near-perfect connectivity inference performance (Matthews correlation coefficient [~]0.97-1.0) and substantially surpassing classical methods ([~]0.6-0.7). We further demonstrate robustness across multiple recording conditions within this hippocampal dataset. Additionally, to illustrate its broader applicability, we extend the framework to two distinct systems without altering the core methodology: a stomatogastric microcircuit in Cancer borealis (ex vivo) and single-neuron intracellular recordings in mouse, where DeepDAM significantly improves efficiency and accuracy over standard approaches. By effectively leveraging synthetic data for in vivo and ex vivo analysis, DeepDAM offers a generalizable strategy for overcoming model mismatch and represents a critical step towards data-driven reconstruction of functional neural circuits.

neuroscience↗

bioRxiv2022

A Suite of Advanced Tutorials for the WESTPA 2.0 Rare-Events Sampling Software

We present six advanced tutorials instructing users in the best practices of using key new features and plugins/extensions of the WESTPA 2.0 software package, which consists of major upgrades for enabling applications of the weighted ensemble (WE) path sampling strategy to even larger systems and/or slower processes. The tutorials demonstrate the use of the following key features: (i) a generalized resampler module for the creation of "binless" schemes, (ii) a minimal adaptive binning scheme for more efficient surmounting of free energy barriers, (iii) streamlined handling of large simulation datasets using an HDF5 framework, (iv) two different schemes for more efficient rate-constant estimation, (v) a Python API for simplified analysis of WE simulations, and (vi) plugins/extensions for Markovian Weighted Ensemble Milestoning and WE rule-based modeling at the system biology level. Applications of the tutorials range from atomistic to residue-level to non-spatial models, and include complex processes such as protein folding and the membrane permeability of a drug-like molecule. Users are expected to already have significant experience with running conventional molecular dynamics simulations and completed the previous suite of WESTPA tutorials.

biophysics↗

bioRxiv2022

Efficient Multi-Label Attribute Classification and Recognition of Microbiological Bacteria Based on Deep Learning and model fine-tuning

Bacterial vaginosis (BV) is the most common gynecological complaint affecting health of a large percentage of women worldwide. Traditional manual microscopy methods are expensive and time-consuming, to improve accuracy and efficiency, automated bacterial identification devices with detection intelligence algorithms are urgently needed. We propose a Fine-tuned SmallerVGG (FTS-VGG) deep convolutional network model based multi-label classification method for bacteria. Comparison experiments were deployed on several advanced backbone networks, including transfer learning on pre-trained VGG19, demonstrating that the proposed method achieves the advantages of being lighter, faster, more accurate and more efficient. Due to the high cost of time and expertise of experienced clinicians, we use random erasing for data augmentation to address the challenge of dataset collection and annotation, experiments demonstrate its robustness to occlusion. The proposed method has theoretical and practical implications, as well as the potential to be widely extended to other microscopic imaging applications.

biochemistry↗

bioRxiv2022

Perturbation of mitochondrial Ca2+ homeostasis activates cross-compartmental proteostatic response in Arabidopsis

Mitochondrial Ca2+ (mtCa2+) homeostasis is essential to mitochondrial functions. However, how mtCa2+ homeostasis is achieved and the consequences of impaired mtCa2+ homeostasis in plants is poorly understood. Here, we demonstrate a critical role for mitochondrial Ca2+ uniporter (MCU) in the control of mtCa2+ uptake for mtCa2+ homeostasis in planta by characterizing MCU mutants and overexpressed plants. Impaired MCU-controlled mtCa2+ homeostasis (iMUCH) in gain-of-function and loss-of-function MCU plants causes the misregulation of mitochondrial gene expression that triggers mitonuclear protein imbalance. Transcriptome integrated with proteomics analysis reveal activation of multiple compartmental UPR gene expression and decrease of cytosolic translation with selective repression of ribosome and RNA modification protein synthesis upon iMUCH. Intriguingly, TOR signalling is not involved in cytosolic translational response to iMUCH, but the reduction of eIF phosphorylation is evident under iMUCH induced mitochondrial stress. Thus, our study unveils the essential functions of MCU proteins for mtCa2+ homeostasis, and the involvement of MCU-controlled mtCa2+ homeostasis in mitochondrial stress dependent regulation of protein synthesis for cellular proteostasis that is connected to plant growth and stress resistance.

plant biology↗

bioRxiv2022

Nature of epigenetic aging from a single-cell perspective

Age-related changes in DNA methylation (DNAm) form the basis for the development of most robust predictors of age, epigenetic clocks, but a clear mechanistic basis for exactly what part of the aging process they quantify is lacking. Here, to clarify the nature of epigenetic aging, we juxtapose the aging dynamics of tissue and single-cell DNAm (scDNAm) with scDNAm changes during early development, and corroborate our analyses with a single-cell RNAseq analysis within the same multi-omics dataset. We show that epigenetic aging involves co-regulated changes, but it is dominated by the stochastic component, and this agrees with transcriptional coordination patterns. We further support the finding of stochastic epigenetic aging by direct tissue and single-cell DNAm analyses and modeling of aging DNAm trajectories with a stochastic process akin to radiocarbon decay. Finally, we describe a single-cell algorithm for the identification of co-regulated and stochastic CpG clusters showing consistent transcriptomic coordination patterns, providing new opportunities for targeting aging and evaluating longevity interventions.

systems biology↗

bioRxiv2022

SmartGate is a spatial metabolomics tool for resolving tissue structures

Imaging mass spectrometry (IMS) is one of the powerful tools in spatial metabolomics for obtaining metabolite data and probing the internal microenvironment of organisms. It has dramatically advanced the understanding of the structure of biological tissues and the drug treatment of diseases. However, the complexity of IMS data hinders the further acquisition of biomarkers and the study of certain specific activities of organisms. To this end, we introduce an artificial intelligence tool SmartGate to enable automatic peak picking and spatial structure identification in an iterative manner. SmartGate selects discriminative m/z features from the previous iteration by differential analysis and employs a graph attention auto-encoder model to perform spatial clustering for tissue segmentation using the selected features. We applied SmartGate to diverse IMS data at multicellular or subcellular spatial resolutions and compared it with four competing methods to demonstrate its effectiveness. SmartGate can significantly improve the accuracy of spatial segmentation and identify biomarker metabolites based on tissue structure-guided differential analysis. For multiple consecutive IMS data, SmartGate can effectively identify structures with spatial heterogeneity by introducing three-dimensional spatial neighbor information.

bioinformatics↗

bioRxiv2022

Olfactory neuronal cells: biopsied surrogates for neurons in the brain

Biopsy is crucial in clinical medicine to obtain tissues and cells that directly reflect the pathological changes of each disease. However, the brain is an exception due to ethical and practical challenges. Nasal biopsy, which captures the olfactory neuronal epithelium, has been considered as an alternative method of obtaining neuronal cells from living patients. Multiple groups have enriched olfactory neuronal cells (ONCs) from biopsied nasal tissue. ONCs can be obtained from repeated biopsies in a longitudinal study, providing mechanistic insight associated with dynamic changes along the disease trajectory and treatment response. Nevertheless, molecular characterization of biopsied nasal cells/tissue has been insufficient. Taking advantage of recent advances in next-generation sequencing technologies at the single-cell resolution and related rich public databases, we aimed to define the neuronal characteristics, homogeneity, and utility of ONCs. We applied single-cell and bulk RNA sequencing for ONCs, analyzing and comparing the data with multiple public datasets. We observed that the molecular signatures of ONCs are similar to those of neurons, distinct from major glial cells. The signatures of ONCs resemble those of developing neurons and share features of excitatory neurons in the prefrontal and cingulate cortex. The high homogeneity of ONCs is advantageous in pharmacological, functional, and protein studies. Accordingly, we provide two proof-of-concept examples for functional and protein studies, solidifying the utility of ONCs in studying objective biomarkers and molecular mechanisms for brain disorders. The ONCs may also be useful in the studies for the olfactory epithelium impairment and the resultant mental dysfunction elicited by SARS-CoV-2. SIGNIFICANCE STATEMENTTo study dynamic changes and underlying mechanisms along disease trajectory and treatment response in neuropsychiatric disorders, olfactory neuronal cells (ONCs) enriched from biopsied nasal tissue may provide a crucial tool. Because ONCs can be obtained from repeated biopsies in a longitudinal study, this tool has been believed to be useful and complementary to postmortem brains and induced pluripotent stem cell-derived neurons. Nevertheless, molecular characterization of biopsied nasal cells/tissue has been insufficient, which hampers a broader use of this resource. Taking advantage of recent advances in next-generation sequencing technologies at the single-cell resolution and related rich public databases, the present study defines ONCs neuronal characteristics, homogeneity, and unique utility for the first time.

molecular biology↗

bioRxiv2022

Multi-lingual multi-platform investigations of online trade in jaguar parts

We conducted research to understand online trade in jaguar parts and develop tools of utility for jaguars and other species. Our research took place to identify potential trade across 31 online platforms in Spanish, Portuguese, English, Dutch, French, Chinese, and Vietnamese. We identified 230 posts from between 2009 and 2019. We screened the images of animal parts shown in search results to verify if from jaguar; 71 posts on 12 different platforms in four languages were accompanied by images identified as definitely jaguar, including a total of 125 jaguar parts (50.7% posts in Spanish, 25.4% Portuguese, 22.5% Chinese and 1.4% French). Search effort varied among languages due to staff availability. Standardizing for effort across languages by dividing number of posts advertising jaguars by search time and number individual searches completed via term/platform combinations, the adjusted rankings of posts were: Portuguese #1, Chinese 2 (time) & 3 (searches), Spanish 3 & 4; French 5 & 4; English 5 & 2, and Dutch 6. Teeth were most common; 156 posts offered at least 367 apparent teeth. From these, 95 teeth were assessed as definitely jaguar; 71 jaguar teeth could be linked to a location, with the majority of the 71 offered for sale from Mexico, China, Bolivia, and Brazil (26.8, 25.4, 16.9, and 12.7% respectively). Ranking of number of teeth was Mexico (19), China (18), Bolivia (12), Brazil (9), Peru/Ecuador (most accurate probable location) (8), Venezuela (3), Guadeloupe (1), and Uruguay (1). The second most traded item, skins and derivative items were only identified from Latin America: Brazil (7), was followed by Peru (6), Bolivia (3), Mexico (2 and 1 skin piece), and Nicaragua and Venezuela (1 each). Whether by number of posts or pieces, the ranking of parts was teeth, skins/pieces of skins, heads, and bodies. Our research presents a snapshot of online jaguar trade and methods that may have utility for many species now traded online. Our research took place within a longer-term project to assist law enforcement in host countries to better identify potential illegal trade online, with research findings informing hubs in Latin America for building such capacity.

ecology↗