Biology subjects

Wu, A. R.

Publications and source records attributed to Wu, A. R..

12 recordsLinked to original sources

bioRxiv2023

Reversibly-bonded Microfluidic Devices for Stable Cell Culture and Rapid, Gentle Cell Extraction

Microfluidics chips have emerged as significant tools in cell culture due to their capacity for supporting cells to adopt more physiologically relevant morphology in 3D compared with traditional cell culture in 2D. Currently, irreversible bonding methods commonly used in chip fabrication mean that chips cannot be detached from their substrate without destroying the chip structure, which makes it challenging to do further analysis on cells that have been cultured on-chip. Some reversible bonding techniques exist but are restricted to certain materials, or require complex processing procedures. Here, we demonstrate a simple and reversible polydimethylsiloxane (PDMS)-polystyrene (PS) bonding technique that allows devices to withstand extended operation while pressurized, and supports long-term stable cell cultures. Importantly, it allows rapid and gentle live cell extraction for further downstream manipulation and characterization after long-term on-chip culturing, or even further subculturing. Our new approach could greatly facilitate microfluidic chip-based tissue and cell cultures, overcoming current analytical limitations and opening up new avenues for downstream uses of on-chip cultures, including 3D-engineered tissue structures for biomedical applications.

bioengineering↗

bioRxiv2023

Changes in Seasonal Footwear Elicited Alterations in Gait Kinematics but Not Stability

During daily walking, humans might contend with various perturbations from slippery surfaces in the winter to uneven sidewalks in the summer. Inertial sensors enable investigations of how humans maintain balance under these natural conditions, but conducting these outdoor studies has practical considerations that might influence study results, such as the selection of footwear under different weather conditions. Our study investigates the effects of winter and summer shoe types on gait patterns, specifically whether different shoe types induce changes in gait stability measures under the same walking environment. Twelve healthy adult participants walked indoors with winter and summer shoes while their gait kinematics were recorded using an inertial sensor-based motion capture system. Spatiotemporal measures, body kinematics, stability measures (minimum margin of stability and local divergence exponent), and stepping regressions were calculated to evaluate differences between walking in summer and winter shoes. Statistical significance was determined by paired t-tests. Varying shoe types altered spatiotemporal and kinematic measures, such as increased stride time and stance time while wearing winter shoes, but increased step width and reliance on stepping were the only stability-related changes found. Our study provides insights into the influence of footwear for inertial sensor-based gait studies in real environments, aiding the analysis and interpretation of those studies to augment our understanding of natural stability behavior.

bioengineering↗

bioRxiv2023

Construction of a 3D whole organism spatial atlas by joint modeling of multiple slices

Spatial transcriptomics (ST) technologies are revolutionizing the way that researchers explore the spatial architecture of tissues. Currently, ST data analysis is often restricted to 2D space within a single tissue slice, limiting our capacity to understand biological processes that take place in 3D space. Here, we present STitch3D, a unified computational framework that integrates multiple 2D tissue slices to reconstruct 3D cellular structures from the tissue level to the whole organism level. By jointly modeling multiple 2D tissue slices and integrating them with cell-type-specific expression profiles derived from single-cell RNA-sequencing data, STitch3D simultaneously identifies 3D spatial regions with coherent gene expression levels and reveals 3D distributions of cell types. STitch3D distinguishes biological variation among slices from batch effects, and effectively borrows shared information across slices to assemble powerful 3D models of tissues. Through comprehensive experiments using diverse datasets, we demonstrate the performance of STitch3D in building comprehensive 3D tissue architectures of the mouse brain, the human heart, and the Drosophila embryo, which allow 3D analysis in the entire tissue region or even the whole organism. To gain deeper biological insights, the outputs of STitch3D can be used for downstream tasks, such as inference of spatial trajectories, identification of spatially variable genes enriched in tissue regions or subregions, denoising or imputation of spatial gene expressions, as well as generation of virtual tissue slices.

bioinformatics↗

bioRxiv2022

Organoid-based single-cell spatiotemporal gene expression landscape of human embryonic development and hematopoiesis

Single-cell level characterization of embryonic development is a major benchmark of human developmental biology. Spatiotemporal analysis of stem-cell-derived embryos offers conceptual and technical advances in the field. Here, we defined the single-cell spatiotemporal gene expression landscape of human embryonic development with stem-cell-derived organoids. We established the human embryonic organoid (HEMO) from expanded potential stem cells and achieved both embryonic and extraembryonic tissues in the same organoid. Time-series single-cell RNA sequencing paired with single-cell resolution spatial revealed human embryonic development signatures such as extraembryonic placenta, yolk sac hematopoiesis neural crest, blood vessels, and cardiac mesoderm. Hematopoietic tissues eventually predominated HEMO with erythropoiesis, mekagaryopiesis, and myelopoiesis. Cell-cell communication network analysis demonstrated that trophoblast-like tissues supplied WNT signaling in neural crest cells to facilitate maturation and migration. Single-cell resolution spatial transcriptomics defined the yolk sac erythro-megakaryopoietic niche. Vitronectin-integrin signaling, a major contributor to megakaryocyte maturation, was predominant in the yolk sac niche in HEMO and to human fetal samples. Overall, our study advances the spatiotemporal analysis of human embryonic development in stem-cell-derived organoids. HighlightsO_LIModeling human embryonic development from stem cells C_LIO_LIUsed of both 10X Chromium and 10X Visium to define the gene expression landscape of embryonic development and hematopoiesis C_LIO_LIWNT signaling as a regulator of neural crest maturation and EMT C_LIO_LIVTN-ITGA2B as the main contributor to Mk maturation within the yolk sac erythro-megakaryopoietic niche C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=158 HEIGHT=200 SRC="FIGDIR/small/505700v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@1710d00org.highwire.dtl.DTLVardef@10ca8e0org.highwire.dtl.DTLVardef@2310d1org.highwire.dtl.DTLVardef@252728_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

bioRxiv2021

Transcriptomic Analysis of 3D Vasculature-On-A-Chip Reveals Paracrine Factors Affecting Vasculature Growth and Maturation

In vitro models of vasculature are of great importance for modelling vascular physiology and pathology. However, there is usually a lack of proper spatial patterning of interacting heterotypic cells in conventional vasculature dish models, which might confound results between contact and non-contact interactions. We use a microfluidic platform with structurally defined separation between human microvasculature and fibroblasts to probe their dynamic, paracrine interactions. We also develop a novel, versatile technique to retrieve cells embedded in extracellular matrix from the microfluidic device for downstream transcriptomic analysis, and uncover growth factor and cytokine expression profiles associated with improved vasculature growth. Paired receptor-ligand analysis further reveals paracrine signaling molecules that could be supplemented into the medium for vasculatures models where fibroblast co-culture is undesirable or infeasible. These findings also provide deeper insights into the molecular cues for more physiologically relevant vascular mimicry and vascularized organoid model for clinical applications such as drug screening and disease modeling.

bioengineering↗

bioRxiv2021

Adversarial domain translation networks enable fast and accurate large-scale atlas-level single-cell data integration

The rapid emergence of large-scale atlas-level single-cell RNA-seq datasets presents remarkable opportunities for broad and deep biological investigations through integrative analyses. However, harmonizing such datasets requires integration approaches to be not only computationally scalable, but also capable of preserving a wide range of fine-grained cell populations. We created Portal, a unified framework of adversarial domain translation to learn harmonized representations of datasets. With innovation in model and algorithm designs, Portal achieves superior performance in preserving biological variation during integration, while achieving integration of millions of cells in minutes with low memory consumption. We show that Portal is widely applicable to integrating datasets across samples, platforms and data types (including scRNA-seq, snRNA-seq and scATAC-seq). Finally, we demonstrate the power of Portal by applying it to the integration of cross-species datasets with limited shared information among them, elucidating biological insights into the similarities and divergences in the spermatogenesis process among mouse, macaque and human.

bioinformatics↗

bioRxiv2021

RNA splicing programs define tissue compartments and cell types at single cell resolution

More than 95% of human genes are alternatively spliced. Yet, the extent splicing is regulated at single-cell resolution has remained controversial due to both available data and methods to interpret it. We apply the SpliZ, a new statistical approach that is agnostic to transcript annotation, to detect cell-type-specific regulated splicing in > 110K carefully annotated single cells from 12 human tissues. Using 10x data for discovery, 9.1% of genes with computable SpliZ scores are cell-type specifically spliced. These results are validated with RNA FISH, single cell PCR, and in high throughput with Smart-seq2. Regulated splicing is found in ubiquitously expressed genes such as actin light chain subunit MYL6 and ribosomal protein RPS24, which has an epithelial-specific microexon. 13% of the statistically most variable splice sites in cell-type specifically regulated genes are also most variable in mouse lemur or mouse. SpliZ analysis further reveals 170 genes with regulated splicing during sperm development using, 10 of which are conserved in mouse and mouse lemur. The statistical properties of the SpliZ allow model-based identification of subpopulations within otherwise indistinguishable cells based on gene expression, illustrated by subpopulations of classical monocytes with stereotyped splicing, including an un-annotated exon, in SAT1, a Diamine acetyltransferase. Together, this unsupervised and annotation-free analysis of differential splicing in ultra high throughput droplet-based sequencing of human cells across multiple organs establishes splicing is regulated cell-type-specifically independent of gene expression.

bioinformatics↗

bioRxiv2020

Upper body and ankle strategies compensate for reduced lateral stability at very slow walking speeds

AO_SCPLOWBSTRACTC_SCPLOWAt the typical walking speeds of healthy humans, step placement seems to be the primary strategy to maintain gait stability, with ankle torques and upper body momentum providing additional compensation. The average walking speeds of populations with an increased risk of falling, however, are much slower and may require differing control strategies. The purpose of this study was to analyze mediolateral gait stability and the contributions of the different control strategies at very slow walking speeds. We analyzed an open dataset including kinematics and kinetics from eight healthy subjects walking at speeds from 0.1 to 0.6 m/s as well as a self-selected speed. As gait speed slowed, we found that the margin of stability decreased linearly. Increased lateral excursions of the extrapolated centre of mass, caused by increased lateral excursions of the trunk, were not compensated for by an equivalent increase in the lateral centre of pressure, leading to decreased margin of stability. Additionally, both the ankle eversion torque and hip abduction torque at the minimum margin of stability event increased at the same rate as gait speed slowed. These results suggest that the contributions of both the ankle and the upper body to stability are more crucial than stepping at slow speeds, which have important implications for populations with slow gait and limited motor function.

bioengineering↗

bioRxiv2020

FIRM: Fast Integration of single-cell RNA-sequencing data across Multiple platforms

Single-cell RNA-sequencing (scRNA-seq) is being used extensively to measure the mRNA expression of individual cells from deconstructed tissues, organs, and even entire organisms to generate cell atlas references, leading to discoveries of novel cell types and deeper insight into biological trajectories. These massive datasets are usually collected from many samples using different scRNA-seq technology platforms, including the popular SMART-Seq2 (SS2) and 10X platforms. Inherent heterogeneities between platforms, tissues, and other batch effects makes scRNA-seq data difficult to compare and integrate, especially in large-scale cell atlas efforts; yet, accurate integration is essential for gaining deeper insights into cell biology. Through comprehensive data exploration, we found that accurate integration is often hampered by differences in cell-type compositions. Herein we describe FIRM, an algorithm that addresses this problem and achieves efficient and accurate integration of heterogeneous scRNA-seq datasets across multiple tissue types, platforms, and experimental batches. We applied FIRM to numerous large-scale scRNA-seq datasets from mouse, mouse lemur, and human, comparing its performance in dataset integration with other state-of-the-art methods. FIRM-integrated datasets show accurate mixing of shared cell type identities and superior preservation of original structure without overcorrection, generating robust integrated datasets for downstream exploration and analysis. It is also a facile way to transfer cell type labels and annotations from one dataset to another, making it a reliable and versatile tool for scRNA-seq analysis, especially for cell atlas data integration.

bioinformatics↗

bioRxiv2020

Effect of methanol fixation on single-cell RNA sequencing data

Single-cell RNA sequencing (scRNA-seq) has led to remarkable progress in our understanding of tissue heterogeneity in health and disease. Recently, the need for scRNA-seq sample fixation has emerged in many scenarios, such as when samples need long-term transportation, or when experiments need to be temporally synchronized. Methanol fixation is a simple and gentle method that has been routinely applied in scRNA-seq. Yet, concerns remain that fixation may result in biases which may change the RNA-seq outcome. We adapted an existing methanol fixation protocol and performed scRNA-seq on both live and methanol fixed cells. Analyses of the results show methanol fixation can faithfully preserve biological related signals, while the discrepancy caused by fixation is subtle and relevant to library construction methods. By grouping transcripts based on their lengths and GC content, we find that transcripts with different features are affected by fixation to different degrees in full-length sequencing data, while the effect is alleviated in Drop-seq result. Our deep analysis reveals the effects of methanol fixation on sample RNA integrity and elucidates the potential consequences of using fixation in various scRNA-seq experiment designs.

genetics↗

bioRxiv2020

MINERVA: A facile strategy for SARS-CoV-2 whole genome deep sequencing of clinical samples

The novel coronavirus disease 2019 (COVID-19) pandemic poses a serious public health risk. Analyzing the genome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from clinical samples is crucial for the understanding of viral spread and viral evolution, as well as for vaccine development. Existing sample preparation methods for viral genome sequencing are demanding on user technique and time, and thus not ideal for time-sensitive clinical samples; these methods are also not optimized for high performance on viral genomes. We have developed MetagenomIc RNA EnRichment VirAl sequencing (MINERVA), a facile, practical, and robust approach for metagenomic and deep viral sequencing from clinical samples. This approach uses direct tagmentation of RNA/DNA hybrids using Tn5 transposase to greatly simplify the sequencing library construction process, while subsequent targeted enrichment can generate viral genomes with high sensitivity, coverage, and depth. We demonstrate the utility of MINERVA on pharyngeal, sputum and stool samples collected from COVID-19 patients, successfully obtaining both whole metatranscriptomes and complete high-depth high-coverage SARS-CoV-2 genomes from these clinical samples, with high yield and robustness. MINERVA is compatible with clinical nucleic extracts containing carrier RNA. With a shortened hands-on time from sample to virus-enriched sequencing-ready library, this rapid, versatile, and clinic-friendly approach will facilitate monitoring of viral genetic variations during outbreaks, both current and future.

molecular biology↗

bioRxiv2019

Cell Fate Determining Molecular Switches and Signaling Pathway in Pax7-expressing Somitic Mesoderm

Pax7-expressing progenitor cells in the somitic mesoderm differentiate into multiple lineages, such as brown adipose tissue, dorsal dermis, as well as muscle in the dorsal trunk and the diaphragm; however, the key molecular switches that determine and control the process of lineage commitment and cell fate are unknown. To probe the mechanisms behind mesoderm development, Pax7creER/R26-stop-EYFP embryos were tamoxifen-induced at E9.5 to label Pax7+ cells for lineage tracing and collected at later time points for analysis. The YFP-labelled cells which belonged to the Pax7 lineage were enriched by fluorescence-activated cell sorting (FACS) and subject to single-cell RNA profiling. We observed that a subpopulation of cells differentiated into the myogenic lineage, showing Myf5 expression as early as E12.5, whereas the rest of the population was fibroblast-like and appeared to be the early stage of the adipogenic and dermal lineages. Cells at E14.5 had distinct myogenic populations that expressed Myod1 and Myog; we also identified other populations with Ebf2 or Twist2 expression, which could belong to adipogenic or dermal lineages, respectively. Cell surface markers were also found for each specific lineage, providing insights in sorting strategy for lineage-of-interest for further functional evaluation. Adipogenic lineage was successfully sorted with a combination of Pdgfra and Thy1 antibodies. In addition, we found that upregulation of Wnt signaling pathway activity is dynamically regulated in dermal lineage. Finally, transcription factors that could potentially drive, or reprogram cell fate, were identified at different developmental time points.\n\nSummary statementInvestigation of Pax7 lineage transcriptomic profile at single-cell level identified multiple cell types, fate commitment time point, surface markers, transcription factors and signaling pathways that determine cell fate.

developmental biology↗