Biology subjects

Zheng, G.

Publications and source records attributed to Zheng, G..

66 records · Page 4Linked to original sources

bioRxiv2021

High-throughput functional characterization of visceral afferents by optical recordings from thoracolumbar and lumbosacral dorsal root ganglions

Functional understanding of visceral afferents is important for developing new treatment to visceral hypersensitivity and pain. The sparse distribution of visceral afferents in dorsal root ganglions (DRGs) has challenged conventional electrophysiological recordings. Alternatively, Ca2+ indicators like GCaMP6f allow functional characterization by optical recordings. Here we report a turnkey microscopy system that enables simultaneous Ca2+ imaging at two parallel focal planes from intact DRG. By using consumer-grade optical components, the microscopy system is cost effective and can be made broadly available without loss of capacity. It records low-intensity fluorescent signals at a wide field of view (1.9 x 1.3 mm) to cover a whole mouse DRG, with a high pixel resolution of 0.7 micron/pixel, a fast frame rate of 50 frames/sec, and the capability of remote focusing without perturbing the sample. The wide scanning range (100 mm) of the motorized sample stage allows convenient recordings of multiple DRGs in thoracic, lumbar, and sacral vertebrae. As a demonstration, we characterized mechanical neural encoding of visceral afferents innervating distal colon and rectum (colorectum) in GCaMP6f mice driven by VGLUT2 promotor. A post-processing routine is developed for conducting unsupervised detection of visceral afferent responses from GCaMP6f recordings, which also compensates the motion artefacts caused by mechanical stimulation of the colorectum. The reported system offers a cost-effective solution for high-throughput recordings of visceral afferent activities from a large volume of DRG tissues. We anticipate a wide application of this microscopy system to expedite our functional understanding of visceral innervations in both health and diseases.

bioengineering↗

bioRxiv2020

An interactive viral genome evolution network analysis system enabling rapid large-scale molecular tracing of SARS-CoV-2

Comprehensive analyses of viral genomes can provide a global picture on SARS-CoV-2 transmission and help to predict the oncoming trends of pandemic. This molecular tracing is mainly conducted through extensive phylogenetic network analyses. However, the rapid accumulation of SARS-CoV-2 genomes presents an unprecedented data size and complexity that has exceeded the capacity of existing methods in constructing evolution network through virus genotyping. Here we report a Viral genome Evolution Network Analysis System (VENAS), which uses Hamming distances adjusted by the minor allele frequency to construct viral genome evolution network. The resulting network was topologically clustered and divided using community detection algorithm, and potential evolution paths were further inferred with a network disassortativity trimming algorithm. We also employed parallel computing technology to achieve rapid processing and interactive visualization of >10,000 viral genomes, enabling accurate detection and subtyping of the viral mutations through different stages of Covid-19 pandemic. In particular, several core viral mutations can be independently identified and linked to early transmission events in Covid-19 pandemic. As a general platform for comprehensive viral genome analysis, VENAS serves as a useful computational tool in the current and future pandemics.

evolutionary biology↗

bioRxiv2020

Towards Building a Smart Kidney Atlas: Network-based integration of multimodal transcriptomic, proteomic, metabolomic and imaging data in the Kidney Precision Medicine Project

AO_SCPLOWBSTRACTC_SCPLOWKidney Precision Medicine Project (KPMP) is building a spatially-specified human tissue atlas at the single-cell resolution with molecular details of the kidney in health and disease. Here, we describe the construction of an integrated reference tissue map of cells, pathways and genes using unaffected regions of nephrectomy tissues and undiseased human biopsies from 55 subjects. We use single-cell and -nucleus transcriptomics, subsegmental laser microdissection bulk transcriptomics and proteomics, near-single-cell proteomics, 3-D nondestructive and CODEX imaging, and spatial metabolomics data to hierarchically identify genes, pathways and cells. Integrated data from these different technologies coherently describe cell types/subtypes within different nephron segments and interstitium. These spatial profiles identify cell-level functional organization of the kidney tissue as indicative of their physiological functions and map different cell subtypes to genes, proteins, metabolites and pathways. Comparison of transcellular sodium reabsorption along the nephron to levels of mRNAs encoding the different sodium transporter genes indicate that mRNA levels are largely congruent with physiological activity.This reference atlas provides an initial framework for molecular classification of kidney disease when multiple molecular mechanisms underlie convergent clinical phenotypes.

bioinformatics↗

bioRxiv2020

Behavioral and neural decomposition of skull-induced death awareness

Death awareness influences multiple aspects of human lives, but its psychological constructs and underlying brain mechanisms remain unclear. We address these by measuring behavioral and brain responses to images of human skulls. We show that skulls relative to control stimuli delay responses to life-related words but speed responses to death-related words. Skulls compared to the control stimuli induce early deactivations in the posterior ventral temporal cortex followed by activations in the posterior and anterior ventral temporal cortices. The early and late neural modulations by perceived skulls respectively predict skull-induced changes of behavioral responses to life- and death-related words and the early neural modulation further predicts death anxiety. Our findings decompose skull-induced death awareness into two-stage neural processes of a lifeless state of a former life. One sentence summaryBehavioral and brain imaging findings decompose skull-induced death awareness into two-stage neural processes of a lifeless state of a former life.

neuroscience↗

bioRxiv2020

Role of RgsA in oxidative stress resistance in Pseudomonas aeruginosa

Pseudomonas aeruginosa is an extremely common opportunistic pathogen in clinical practice. Patients with metabolic disorders, hematologic diseases, malignancies, who have undergone surgery or who have received certain treatments are susceptible to this bacterium. In addition, P. aeruginosa is a multidrug-resistant that tends to form biofilms and is refractory to treatment. Small regulatory RNAs are RNA molecules that are 40-500 nucleotides long, possess regulatory function, are ubiquitous in bacteria, and are also known as small RNA (sRNA). sRNAs play important regulatory roles in various vital life processes in diverse bacteria and their quantity and diversity of regulatory functions exceeds that of proteins. In this study, we showed that deletion of the sRNA RgsA decreases the growth rate and ability to resist different concentrations and durations of peroxide in P. aeruginosa. These decreases occur not only in the planktonic state, but also in the biofilm state. Finally, protein mass spectrometry was employed to understand changes in the entire protein spectrum. The results presented herein provide a description of the role of RgsA in the life activities of P. aeruginosa at the molecular, phenotypic, and protein levels.

microbiology↗

bioRxiv2019

RNA Sequencing by Direct Tagmentation of RNA/DNA Hybrids

Transcriptome profiling by RNA sequencing (RNA-seq) has been widely used to characterize cellular status but it relies on second strand cDNA synthesis to generate initial material for library preparation. Here we use bacterial transposase Tn5, which has been increasingly used in various high-throughput DNA analyses, to construct RNA-seq libraries without second strand synthesis. We show that Tn5 transposome can randomly bind RNA/DNA heteroduplexes and add sequencing adapters onto RNA directly after reverse transcription. This method, Sequencing HEteRo RNA-DNA-hYbrid (SHERRY), is versatile and scalable. SHERRY accepts a wide range of starting materials, from bulk RNA to single cells. SHERRY offers a greatly simplified protocol, and produces results with higher reproducibility and GC uniformity compared with prevailing RNA-seq methods. Significance StatementRNA sequencing is widely used to measure gene expression in biomedical research; therefore, improvements in the simplicity and accuracy of the technology are desirable. All existing RNA sequencing methods rely on the conversion of RNA into double-stranded DNA through reverse transcription followed by second strand synthesis. The latter step requires additional enzymes and purification, and introduces sequence-dependent bias. Here, we show that Tn5 transposase, which randomly binds and cuts double-stranded DNA, can directly fragment and prime the RNA/DNA heteroduplexes generated by reverse transcription. The primed fragments are then subject to PCR amplification. This provides a new approach for simple and accurate RNA characterization and quantification.

molecular biology↗

bioRxiv2019

Computational comparison of developmental cell lineage trees by alignments

The developmental cell lineage tree, which records every cell division event and the terminal developmental state of each single cell, is one of the most important traits of multicellular organisms, as well as key to many significant unresolved questions in biology. Recent technological breakthroughs are paving the way for direct determination of cell lineage trees, yet a general framework for the computational analysis of lineage trees, in particular an algorithm to compare two lineage trees, is still lacking. Based on previous findings that the same developmental program can be invoked by different cells on the lineage tree to produce highly similar subtrees, we designed Developmental Cell Lineage Tree Alignment (DELTA), an algorithm that exhaustively searches for lineage trees with phenotypic resemblance in lineal organization of terminal cells, meanwhile resolving detailed correspondence between individual cells. Using simulated and nematode lineage trees, we demonstrated DELTAs capability of revealing similarities of developmental programs by lineal resemblances. Moreover, DELTA successfully identifies gene deletion-triggered homeotic cell fate transformations, reveals functional relationship between mutants by quantifying their lineal similarities, and finds the evolutionary correspondence between cell types defined non-uniformly for different species. DELTA establishes novel foundation for comparative study of lineage trees, much like sequence alignment algorithm for biological sequences, and along with the increase of lineage tree data, will likely bring unique insights for the myriads of important questions surrounding cell lineage trees.

bioinformatics↗

bioRxiv2019

Direct control of shell regeneration by the mantle tissue in the pearl oyster Pinctada fucata via accelerating CaCO3 nucleation

Molluscan bivalves rapidly repair the damaged shells to prevent further injury. However, it remains unclear how this process is precisely controlled. In this study, we applied scanning electronic microscopy, transmission electronic microscopy and histochemical analysis to examine the detailed shell regeneration process of the pearl oyster Pinctada fucata. It was found that the shell damage caused the mantle tissue to retract, which resulted in dislocation of the mantle zones to their correspondingly secreted shell layers. However, the secretory repertoires of the different mantle zones remained unchanged. As a result, the dislocation of the mantle tissue dramatically affected the shell morphology, and the unusual presence of the submarginal zone on the nacreous layers caused de novo precipitation of prismatic layers on the nacreous layers. Real-time PCR revealed that the expression of the shell matrix proteins (SMPs) were significantly upregulated, which was confirmed by the thermal gravimetric analysis (TGA) of the newly formed shell. The increased matrix secretion accelerated CaCO3 nucleation thus promoting shell deposition. Taken together, our study revealed the close relationship between the physiological activities of the mantle tissue and the morphological change of the regenerated shells.

zoology↗

bioRxiv2018

Transcription-factor centric genome mining strategy for discovery of diverse unprecedented RiPP gene clusters

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a rapidly emerging group of natural products with diverse biological activity. Most of their biosynthetic mechanisms are well studied and the \"genome mining\" strategy based on homology has led to the unearthing of many new ribosomal natural products, including lantipeptides, lasso peptides, cyanobactins. These precursor-centric or biosynthetic protein-centric genome mining strategies have encouraged the discovery of RiPPs natural products. However, a limitation of these strategies is that the newly identified natural products are similar to the known products and novel families of RiPP pathways were overlooked by these strategies. In this work, we applied a transcription-factor centric genome mining strategy and diverse unique crosslinked RiPP gene clusters were predicted in several sequenced microorganisms. Our research could significantly expand the category of biosynthetic pathways of RiPP natural products and predict new resources for novel RiPPs.

genomics↗

bioRxiv2018

3D Shape Modeling for Cell Nuclear Morphological Analysis and Classification

Quantitative analysis of morphological changes in a cell nucleus is important for the understanding of nuclear architecture and its relationship with pathological conditions such as cancer. However, dimensionality of imaging data, together with a great variability of nuclear shapes, presents challenges for 3D morphological analysis. Thus, there is a compelling need for robust 3D nuclear morphometric techniques to carry out population-wide analysis. We propose a new approach that combines modeling, analysis, and interpretation of morphometric characteristics of cell nuclei and nucleoli in 3D. We used robust surface reconstruction that allows accurate approximation of 3D object boundary. Then, we computed geometric morphological measures characterizing the form of cell nuclei and nucleoli. Using these features, we compared over 450 nuclei with about 1,000 nucleoli of epithelial and mesenchymal prostate cancer cells, as well as 1,000 nuclei with over 2,000 nucleoli from serum-starved and proliferating fibroblast cells. Classification of sets of 9 and 15 cells achieved accuracy of 95.4% and 98%, respectively, for prostate cancer cells, and 95% and 98% for fibroblast cells. To our knowledge, this is the first attempt to combine these methods for 3D nuclear shape modeling and morphometry into a highly parallel pipeline workflow for morphometric analysis of thousands of nuclei and nucleoli in 3D.

bioinformatics↗

bioRxiv2018

Rotational 3D mechanogenomic Turing patterns of human colon Caco-2 cells during differentiation

Recent reports suggest that actomyosin meshwork act in a mechanobiological manner alter cell/nucleus/tissue morphology, including human colon epithelial Caco-2 cancer cells that form polarized 2D epithelium or 3D sphere/tube when placed in different culture conditions. We observed the rotational motion of the nucleus in Caco-2 cells in vitro that appears to be driven by actomyosin network prior to the formation of a differentiated confluent epithelium. Caco-2 cell monolayer preparations demonstrated 2D patterns consistent with Allan Turings \"gene morphogen\" hypothesis based on live cell imaging analysis of apical tight junctions indicating the actomyosin meshwork. Caco-2 cells in 3D culture are frequently used as a model to study 3D epithelial morphogenesis involving symmetric and asymmetric cell divisions. Differentiation of Caco-2 cells in vitro demonstrated similarity to intestinal enterocyte differentiation along the human colon crypt axis. We observed rotational 3D patterns consistent with gene morphogens during Caco-2 cell differentiation. Single- to multi-cell ring/torus-shaped genomes were observed that were similar to complex fractal Turing patterns extending from a rotating torus centre in a spiral pattern consistent with gene morphogen motif. Rotational features of the epithelial cells may contribute to well-described differentiation from stem cells to the luminal colon epithelium along the crypt axis. This dataset may be useful to study the role of mechanobiological processes and the underlying molecular mechanisms as determinants of cellular and tissue architecture in space and time, which is the focal point of the 4D nucleome initiative.

bioinformatics↗

bioRxiv2017

3D cell nuclear morphology: microscopy imaging dataset and voxel-based morphometry classification results

Cell deformation is regulated by complex underlying biological mechanisms associated with spatial and temporal morphological changes in the nucleus that are related to cell differentiation, development, proliferation, and disease. Thus, quantitative analysis of changes in size and shape of nuclear structures in 3D microscopic images is important not only for investigating nuclear organization, but also for detecting and treating pathological conditions such as cancer. While many efforts have been made to develop cell and nuclear shape characteristics in 2D or pseudo-3D, several studies have suggested that 3D morphometric measures provide better results for nuclear shape description and discrimination. A few methods have been proposed to classify cell and nuclear morphological phenotypes in 3D, however, there is a lack of publicly available 3D data for the evaluation and comparison of such algorithms. This limitation becomes of great importance when the ability to evaluate different approaches on benchmark data is needed for better dissemination of the current state of the art methods for bioimage analysis. To address this problem, we present a dataset containing two different cell collections, including original 3D microscopic images of cell nuclei and nucleoli. In addition, we perform a baseline evaluation of a number of popular classification algorithms using 2D and 3D voxel-based morphometric measures. To account for batch effects, while enabling calculations of AUROC and AUPR performance metrics, we propose a specific cross-validation scheme that we compare with commonly used k-fold cross-validation. Original and derived imaging data are made publicly available on the project web-page: http://www.socr.umich.edu/projects/3d-cell-morphometry/data.html.

bioinformatics↗