Biology subjects

Cheng, Z.

Publications and source records attributed to Cheng, Z..

At least 73 records · Page 4Linked to original sources

bioRxiv2024

BMAP: a comprehensive and reproducible biomedical data analysis platform

In the realm of biomedical research, efficient data analysis and processing are crucial due to the escalating volume and complexity of data generated by research teams. Managing these vast arrays of localized data presents significant challenges, necessitating precise, efficient, and reproducible analysis methodologies to ensure the integrity and reliability of scientific outcomes. Traditional management of analysis codes, computing environments, and the inherent difficulties in result traceability due to team dynamics often lead to inefficiencies and potential risks in maintaining academic integrity. Furthermore, while online storage platforms such as Dryad, GitHub, and Docker facilitate data, code, and environment management, they do not inherently guarantee the reproducibility of results, with issues like data incompleteness, forgotten parameters, or software discrepancies posing additional challenges. To address these critical gaps, we developed a BioMedical data Analysis Platform (BMAP) to offer online and localized categorized management of research assets. BMAP enhances workflow efficiency by transforming complex pipelines into user-friendly web applications, promoting consistency and standardization across team analyses. Its comprehensive web analysis module and seamless integration with data and computing resources support automated result reproducibility and visualization. According to the assessment, 1,692 omics-related figures from 101 recent articles, across 45 visualization types, were tested with BMAP, which could cover 37.8% of the types and 64.3% of the figures. BMAP also enables the sharing and enhancement of research methods through its cloud platform, allowing researchers to utilize the previously developed and validated tools, thereby reducing redundant effort and minimizing analytical discrepancies due to methodological differences.

bioinformatics↗

bioRxiv2024

Decoding the Epigenetic Landscape: Insights into 5mC and 5hmC Patterns in Mouse Cortical Cell Types

The DNA modifications, 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC), represent powerful epigenetic regulators of temporal and spatial gene expression. Yet, how the cooperation of these genome-wide, epigenetic marks determine unique transcriptional signatures across different brain cell populations is unclear. Here we applied Nanopore sequencing of native DNA to obtain a complete, genome-wide, single-base resolution atlas of 5mC and 5hmC modifications in neurons, astrocytes and microglia in the mouse cortex (99% genome coverage, 40 million CpG sites). In tandem with RNA sequencing, analysis of 5mC and 5hmC patterns across cell types reveals astrocytes drive uniquely high brain 5hmC levels and support two decades of research regarding methylation patterns, gene expression and alternative splicing, benchmarking this resource. As such, we provide the most comprehensive DNA methylation data in mouse brain as an interactive, online tool (NAM-Me, https://olsenlab.shinyapps.io/NAMME/) to serve as a resource dataset for those interested in the methylome landscape.

neuroscience↗

bioRxiv2024

Genomic characterization of Escherichia coli harbor a polyketide synthase (pks) island associated with colorectal cancer (CRC) development

The E. coli strain harboring the polyketide synthase (Pks) island encodes the genotoxin colibactin, a secondary metabolite reported to have severe implications for human health and for the progression of colorectal cancer. The present study involved whole-genome-wide comparison and phylogenetic analysis of pks harboring E. coli isolates to gain insight into the distribution and evolution of these organism. Fifteen E. coli strains isolated from patients with ulcerative colitis were sequenced, 13 of which harbored pks islands. In addition, 2,654 genomes from the public database were also screened for pks harboring E. coli genomes, 158 of which were pks-positive isolates. Whole-genome-wide comparison and phylogenetic analysis revealed that 171 (158+13) pks-positive isolates belonged to phylogroup B2, and most of the isolates associated to sequence types ST73 and ST95. One isolate from an ulcerative colitis (UC) patient was of the sequence type ST8303. The maximum likelihood tree based on the core genome of pks-positive isolates revealed horizontal gene transfer across sequence types and serotypes. Virulome and resistome analyses revealed the preponderance of virulence genes and a reduced number of antimicrobial genes in Pks-positive isolates. This study strongly contributes to understanding the evolution of pks islands in E. coli.

immunology↗

bioRxiv2024

An Efficient and Principled Model to Jointly Learn the Agnostic and Multifactorial Effect in Large-Scale Biological Data

The rich information contained in biological data is often distorted by multiple interacting intrinsic or extrinsic factors. Modeling the effects of these factors is necessary to uncover the underlying true signals. However, this is challenging in real applications, because biological data usually consist of tens of thousands or millions of factors, and no reliable prior knowledge is available on how these factors exert the effect, to what degree the effect is, as well as how they interact with each other. Thus, the existing approaches rely on excessive simplification or unrealistic assumptions such as the probabilistic independence among factors. In this paper, we report the finding that after reformulating the data as a contingency tensor the problem can be well addressed by a fundamental machine learning principle, Maximum Entropy, with an extra effort of designing an efficient algorithm to solve the large-scale optimization problem. Based on the principle of maximum entropy, and by constraining the marginals of the contingency tensor using the observed values, our Conditional Multifactorial Contingency (CMC) model imposes minimum but essential assumptions about the multifactorial joint effects and leads to a conceptually simple distribution, which informs how these factors exert the effects and interact with each other. By replacing hard constraints with expected values, CMC avoids the NP-hard problem and results in a theoretically solvable convex problem. However, due to the large scale of variables and constraints, the standard convex solvers do not work. Exploring the special properties of the CMC model we developed an efficient iterative optimizer, which reduces the running time from infeasible to minutes or from days to seconds. We applied CMC to quite a few cutting-edge biological applications, including the detection of driving transcription factor, scRNA-seq normalization, cancer-associated gene identification, GO-term activity transformation, and quantification of single-cell-level similarity. CMC gained much better performance than other methods with respect to various evaluation criteria. Our source code of CMC as well as its example applications can be found at https://github.com/yu-lab-vt/CMC. One-Sentence SummaryCMC jointly learns intertwined effects of numerous factors in biologival data and outperform existing methods in multiple cutting-edge biological applications.

bioinformatics↗

bioRxiv2024

RT-Sort: an action potential propagation-based algorithm for real time spike detection and sorting with millisecond latencies

With the use of high density multi electrode recording devices, electrophysiological signals resulting from action potentials of individual neurons can now be reliably detected on multiple adjacent recording electrodes both in vivo and in vitro. Spike sorting assigns these signals to putative neural sources. However, until now, spike sorting can only be performed after completion of the recording, preventing true real time usage of spike sorting algorithms. Utilizing the unique propagation patterns of action potentials along axons detected as high fidelity sequential activations on adjacent electrodes, together with a convolutional neural network based spike detection algorithm, we introduce RT-Sort (Real Time Sorting), a spike sorting algorithm that enables the sorted detection of action potentials within 7.5ms{+/-}1.5ms (mean{+/-}STD) after the waveform trough while the recording remains ongoing. RT-Sorts true real-time spike sorting capabilities enable closed loop experiments with latencies comparable to synaptic delay times. We show RT-Sorts performance on both Multi-Electrode Arrays as well as Neuropixels probes to exemplify RT-Sorts functionality on different types of recording hardware and electrode configurations.

neuroscience↗

bioRxiv2024

The genomic trajectory of ovarian high grade serous carcinoma is determined in STIC lesions

Ovarian high-grade serous carcinoma (HGSC) originates in the fallopian tube, with secretory cells carrying a TP53 mutation, known as p53 signatures, identified as potential precursors. p53 signatures evolve into serous tubal intraepithelial carcinomas (STIC) lesions, which, in turn, progress into invasive HGSC that readily spread to the ovary and disseminate around the peritoneal cavity. We recently investigated the genomic landscape of early- and late-stage HGSC and found higher ploidy in late-stage (median 3.1) than early-stage (median 2.0) samples. Here, to explore whether the high ploidy and possible whole genome duplication observed in late-stage disease are determined early in the evolution of HGSC, we analysed archival formalin-fixed paraffin-embedded samples (FFPE) from five HGSC patients. p53 signatures and STIC lesions were laser-capture microdissected and sequenced using shallow whole genome sequencing (sWGS), while invasive ovarian/fallopian tube and metastatic carcinoma samples underwent macrodissection and were profiled using both sWGS and targeted next generation sequencing. Results showed highly similar patterns of global copy number change between STIC lesions and invasive carcinoma samples within each patient. Ploidy changes were evident in STIC lesions, but not p53 signatures, and there was strong correlation between ploidy in STIC lesions and invasive ovarian/fallopian tube and metastatic samples in each patient. The reconstruction of sample phylogeny for each patient from relative copy number indicated that high ploidy, when present, occurred early in the evolution of HGSC, which was further validated by copy number signatures in ovarian and metastatic tumours. These findings suggest that aberrant ploidy, suggestive of whole genome duplication, arises early in HGSC, and is detected in STIC lesions, implying that the trajectory of HGSC may be determined at the earliest stages of tumour development.

cancer biology↗

bioRxiv2024

High-accuracy crRNA array assembly strategy for multiplex CRISPR

Simultaneous targeting of multiple loci with CRISPR system, a tool known as multiplex CRISPR, offers us more feasibility to manipulate and elucidate the intricate and redundant endogenous networks underlying complex cellular functions. Owing to the versatility of the continuously emerging Cas nucleases and the utilization of CRISPR arrays, multiplex CRISPR has been implemented by numerous in vitro and in vivo studies. However, a streamlined practical strategy for CRISPR array assembly with both convenience and accuracy is still lacking. Here, we present a novel high-accuracy, cost- and time-saving strategy for CRISPR array assembly. Using this strategy, we efficiently accomplished the assembly of up to twelve crRNAs (for AsCas12a) or fifteen crRNAs (for RfxCas13d) in a single reaction. Moreover, we reveal that CRISPR arrays driven by Pol II promoters exhibit a distinct targeting pattern compared to Pol III promoters, which could be exploited for specific distributions of CRISPR intensity. For long CRISPR arrays, we designed a better approach than simply selecting one from U6 or EF1a. Collectively, our study provides a flexible and powerful tool for the convenient implementation of multiplex CRISPR across DNA to RNA, facilitating the dissection of sophisticated cellular networks and the future realization of multi-target gene therapy.

synthetic biology↗

bioRxiv2024

Gene Therapy Mediates Therapeutic Improvement in Cardiac Hypertrophy and Survival in a Murine Model of MYBPC3-Associated Cardiomyopathy

BackgroundHypertrophic cardiomyopathy (HCM) affects an estimated 600,000 people in the U.S. and is the leading cause of sudden cardiac arrest in those under 18. Loss-of-function mutations in Myosin Binding Protein C3, MYBPC3, are the most common genetic cause of HCM. The majority of MYBPC3 mutations causative for HCM result in truncations. The sarcomeric pathophysiology of the majority of HCM patients with MYBPC3 mutations appears to be due to haploinsufficiency, as the total amount of MYBPC3 protein incorporated into sarcomeres falls significantly below normal. MethodsA clear path for the treatment of haploinsufficiency is the restoration of the insufficient gene product; in this case wild-type MYBPC3. To achieve this, we engineered an AAV vector (TN-201) with superior properties for mediating cardiomyocyte-selective expression of MYBPC3 after systemic delivery. ResultsWe have demonstrated for the first time with AAV gene therapy the ability of both a mouse surrogate and TN-201, which encodes human MYBPC3 to reverse cardiac hypertrophy and systolic dysfunction and to improve diastolic dysfunction and survival in a symptomatic MYBPC3-deficient murine model of disease. Dose-ranging efficacy studies exhibited restoration of wild-type MYBPC3 protein levels and saturation of cardiac improvement at the clinically relevant dose of 3E13 vg/kg, outperforming a previously published construct. Further, we have established stable cardiac benefit for greater than one year post-injection, as well as reversal of cardiac dysfunction even in late-stage models of disease. ConclusionsOur data suggest that by restoring MYBPC3 to the sarcomere, TN-201 has the potential to slow and even reverse the course of the disease in patients with MYBPC3-associated HCM.

genetics↗

bioRxiv2023

Structure-based discovery of positive allosteric modulators for the calcium sensing receptor

Drugs acting as positive allosteric modulators (PAMs) to enhance the activation of the calcium sensing receptor (CaSR) and to suppress parathyroid hormone (PTH) secretion can treat hyperparathyroidism but suffer from side effects including hypocalcemia and arrhythmias. Seeking new CaSR modulators, we docked libraries of 2.7 million and 1.2 billion molecules against transforming pockets in the active-state receptor dimer structure. Consistent with simulations suggesting that docking improves with library size, billion-molecule docking found new PAMs with a hit rate that was 2.7-fold higher than the million-molecule library and with hits up to 37-fold more potent. Structure-based optimization of ligands from both campaigns led to nanomolar leads, one of which was advanced to animal testing. This PAM displays 100-fold the potency of the standard of care, cinacalcet, in ex vivo organ assays, and reduces serum PTH levels in mice by up to 80% without the hypocalcemia typical of CaSR drugs. Cryo-EM structures with the new PAMs show that they induce residue rearrangements in the binding pockets and promote CaSR dimer conformations that are closer to the G-protein coupled state compared to established drugs. These findings highlight the promise of large library docking for therapeutic leads, especially when combined with experimental structure determination and mechanism. One sentence summaryStructure-based virtual screening uncovers novel CaSR allosteric modulators with enhanced efficacy and less side effects.

biophysics↗

bioRxiv2023

Battery-Free Optoelectronic Patch for Photodynamic and Light Therapies in Treating Bacteria-Infected Wounds

Light therapy is an effective approach for the treatment of a variety of challenging dermatological conditions. In contrast to existing methods involving high doses and large areas of illumination, alternative strategies based on wearable designs that utilize a low light dose over an extended period provide a precise and convenient treatment. In this study, we present a battery-free, skin-integrated optoelectronic patch that incorporates a coil-powered circuit, an array of microscale violet and red light emitting diodes (LEDs), and polymer microneedles (MNs) loaded with 5-aminolevulinic acid (5-ALA). This polymer MNs, based on the biodegradable composite materials of polyvinyl alcohol (PVA) and hyaluronic acid (HA), serves as light waveguides for optical access and a medium for drug release into deeper skin layers. Unlike conventional clinical photomedical appliances with a rigid and fixed light source, this flexible design allows for a conformable light source that can be applied directly to the skin. In animal models with bacterial-infected wounds, the experimental group with the combination treatment of metronomic photodynamic and light therapies reduced 2.48 log10 CFU mL-1 in bactericidal level compared to the control group, indicating an effective anti-infective response. Furthermore, post-treatment analysis revealed the activation of proregenerative genes in monocyte and macrophage cell populations, suggesting enhanced tissue regeneration, neovascularization, and dermal recovery. Overall, this optoelectronic patch design broadens the scope for targeting deep skin lesions, and provides an alternative with the functionality of standard clinical light therapy methods.

bioengineering↗

bioRxiv2023

An inducible genetic tool for tracking and manipulating specific microglial states in development and disease

Recent single-cell RNA sequencing studies have revealed distinct microglial states in development and disease. These include proliferative region-associated microglia (PAM) in developing white matter and disease-associated microglia (DAM) prevalent in various neurodegenerative conditions. PAM and DAM share a similar core gene signature and other functional properties. However, the extent of the dynamism and plasticity of these microglial states, as well as their functional significance, remains elusive, partly due to the lack of specific tools. Here, we report the generation of an inducible Cre driver line, Clec7a-CreERT2, designed to target PAM and DAM in the brain parenchyma. Utilizing this tool, we profile labeled cells during development and in several disease models, uncovering convergence and context-dependent differences in PAM/DAM gene expression. Through long-term tracking, we demonstrate surprising levels of plasticity in these microglial states. Lastly, we specifically depleted DAM in cuprizone-induced demyelination, revealing their roles in disease progression and recovery.

neuroscience↗

bioRxiv2023

SCC3 acts as the cohesin and inhibits inter-sister chromatids repair during rice meiosis

Cohesin is a multi-subunit protein that plays a pivotal role in holding sister chromatids together during cell division. Sister chromatid cohesion 3 (SCC3), constituents of cohesin complex, is highly conserved from yeast to mammals. Since the deletion of individual cohesin subunit always causes lethality, it is difficult to dissect its biological function in both mitosis and meiosis. Here, we obtained scc3 weak mutants using CRISPR-Cas9 system to explore its function during rice mitosis and meiosis. The scc3 weak mutants displayed obvious vegetative defects and complete sterility, underscoring the essential roles of SCC3 in both mitosis and meiosis. SCC3 is localized on chromatin from interphase to prometaphase in mitosis. However, in meiosis, SCC3 acts as an axial element during early prophase I and subsequently situates onto centromeric regions following the disassembly of the synaptonemal complex. The loading of SCC3 onto meiotic chromosomes depends on REC8. scc3 shows severe defects in homologous pairing and synapsis. Consequently, SCC3 functions as an axial element that is essential for maintaining homologous chromosome pairing and synapsis during meiosis.

genetics↗

bioRxiv2023

Genetic Discovery Enabled by A Large Language Model

Artificial intelligence (AI) has been used in many areas of medicine, and recently large language models (LLMs) have shown potential utility for clinical applications. However, since we do not know if the use of LLMs can accelerate the pace of genetic discovery, we used data generated from mouse genetic models to investigate this possibility. We examined whether a recently developed specialized LLM (Med-PaLM 2) could analyze sets of candidate genes generated from analysis of murine models of biomedical traits. In response to free-text input, Med-PaLM 2 correctly identified the murine genes that contained experimentally verified causative genetic factors for six biomedical traits, which included susceptibility to diabetes and cataracts. Med-PaLM 2 was also able to analyze a list of genes with high impact alleles, which were identified by comparative analysis of murine genomic sequence data, and it identified a causative murine genetic factor for spontaneous hearing loss. Based upon this Med-PaLM 2 finding, a novel bigenic model for susceptibility to spontaneous hearing loss was developed. These results demonstrate Med-PaLM 2 can analyze gene-phenotype relationships and generate novel hypotheses, which can facilitate genetic discovery.

genetics↗

bioRxiv2023

Stereo-anomaly is found more frequently in tasks that require discrimination between depths

AO_SCPLOWBSTRACTC_SCPLOWWithin the population of humans with otherwise normal vision, there exists some proportion whose ability to perceive depth from binocular disparity is poor or absent. The prevalence of this "stereoanomaly" has been investigated in previous studies, some finding the proportion to be as small as 2%, others finding it to be as great as 30%. In this study, we set out to investigate the possible reason for the wide range of results found in these studies. We used a digital stereoacuity measurement tool that could measure performance in tasks requiring either the detection of disparity or the discrimination of the sign of disparity. The stimulus design was otherwise similar between the two tasks. In a cohort of 228 participants, we found that 98% were able to consistently perform the detection task. In contrast, only 69% consistently performed the discrimination task. The 31% of participants who had difficulty with the discrimination task could further be divided into 17% who were consistently unable to perform the task (seeming to behave at chance), and 14% who showed some ability to perform the task. We propose that the greater prevalence of stereo-anomaly is revealed when tasks require the judgement of the direction of disparity.

neuroscience↗

bioRxiv2023

Biosynthesis- and Metabolomics-guided discovery of antimicrobial cyclopeptides against drug-resistant clinical isolates

Antimicrobial resistance remains a significant global threat, contributing significantly to mortality rates worldwide. Ribosomally synthesized and post-translationally modified peptides (RiPPs) have emerged as a promising source of novel peptide antibiotics due to their diverse chemical structures. Here, we reported the discovery of new Avi(Me)Cys-containing cyclopeptide antibiotics through a synergistic approach that combines rule-based genome mining, automated metabolomic analysis, and heterologous expression. We first bioinformatically identified 1,172 RiPP biosynthetic gene clusters (BGCs) responsible for Avi(Me)Cys-containing cyclopeptides from a vast pool of over 50,000 bacterial genomes. Subsequently, we successfully established the connection between three newly identified BGCs and the synthesis of five new peptide antibiotics. Notably, massatide A displayed excellent activity against a spectrum of gram-positive pathogens, including drug-resistant clinical isolates like linezolid-resistant S. aureus and methicillin-resistant S. aureus, with a minimum inhibitory concentration (MIC) of 0.25 g/mL. The remarkable performance of massatide A in an animal infection model, coupled with a low risk of resistance and favorable safety profile, positions it as a promising candidate for antibiotic development. Our study highlights the potential of Avi(Me)Cys-containing cyclopeptides in expanding the arsenal of antibiotics against multi-drug-resistant bacteria, offering promising drug leads in the ongoing battle against infectious diseases.

biochemistry↗

bioRxiv2023

Modeling Cystic Fibrosis Chronic Infection Using Engineered Mucus-like Hydrogels

The airway mucus of patients with cystic fibrosis has altered properties which create a microenvironment primed for chronic infections that are difficult to treat. These complex polymicrobial airway infections and corresponding mammalian-microbe interactions are challenging to model in vitro. Here, we report the development of mucus-like hydrogels with varied compositions and viscoelastic properties reflecting differences between healthy and cystic fibrosis airway mucus. Models of cystic fibrosis and healthy airway microenvironments were created by combining the hydrogels with relevant pathogens, human bronchial epithelial cells, and an antibiotic. Notably, pathogen antibiotic resistance was not solely dependent on the altered properties of the mucus-like hydrogels but was also influenced by culture conditions including microbe species, monomicrobial or polymicrobial culture, and the presence of epithelial cells. Additionally, the cystic fibrosis airway model showed the ability to mimic features characteristic of chronic cystic fibrosis airway infections including sustained polymicrobial growth and increased antibiotic tolerance.

bioengineering↗

bioRxiv2023

Cystic fibrosis transmembrane conductance regulator (CFTR) downregulates the excitability of deep pyramidal neurons in the rodent cortex

The cystic fibrosis transmembrane conductance regulator (CFTR) is an ATP-binding chloride channel that is regulated by intracellular cAMP/PKA phosphorylation. CFTR is widely expressed in peripheral tissues and organs of mammals and plays a vital role in maintaining chloride balance and cellular homeostasis. While preliminary studies have identified CFTR expression in the central nervous system (CNS), it is not clear whether this channel also modulates the neural network of the cerebral cortex by regulating the intracellular chloride level of neurons. In this study, we employed immunohistochemical staining, patch-clamp recording, and two-photon imaging techniques to comprehensively analyze the functions of the CFTR channel in the rodent cortex. Our results indicate that CFTR is primarily distributed in the deep pyramidal somata and superficial axons of the cerebral cortex. Regulation of CFTR has the potential to alter the resting membrane potential and evoke action potentials of layer V pyramidal neurons, which produces significant changes in inhibitory synaptic transmission. Furthermore, we found that inhibiting CFTR channels increased the calcium activity of axon boutons and somata of the primary motor cortex in vivo, promoting motor learning. Overall, these findings implicate a crucial role of CFTR in modulating Cl-homeostasis and neuronal excitability in the cerebral cortex, furthering our understanding of the functions of the chloride channel in the central nervous system.

neuroscience↗

bioRxiv2023

ABDS: tool suite for analyzing biologically diverse samples

MotivationAnalytics tools are essential to identify informative molecular features about different phenotypic groups. Among the most fundamental tasks are missing value imputation, signature gene detection, and expression pattern visualization. However, most commonly used analytics tools may be problematic for characterizing biologically diverse samples when either signature genes possess uneven missing rates across different groups yet involving complex missing mechanisms, or multiple biological groups are simultaneously compared and visualized. ResultsWe develop ABDS tool suite tailored specifically to analyzing biologically diverse samples. Mechanism-integrated group-wise imputation is developed to recruit signature genes involving informative missingness, cosine-based one-sample test is extended to detect enumerated signature genes, and unified heatmap is designed to comparably display complex expression patterns. We discuss the methodological principles and demonstrate the conceptual advantages of the three software tools. We also showcase the biomedical applications of these individual tools. Implemented in open-source R scripts, ABDS tool suite complements rather than replaces the existing tools and will allow biologists to more accurately detect interpretable molecular signals among diverse phenotypic samples. Availability and implementationThe R Scripts of ABDS tool suite is freely available at https://github.com/niccolodpdu/ABDS. Contactyuewang@vt.edu Supplementary informationSupplementary materials are available at Bioinformatics Advances online.

bioinformatics↗