Biology subjects

Chen, K.

Publications and source records attributed to Chen, K..

At least 289 records · Page 16Linked to original sources

bioRxiv2022

In vivo spatiotemporal dynamics of astrocyte reactivity following neural electrode implantation

Brain computer interfaces (BCIs), including penetrating microelectrode arrays, enable both recording and stimulation of neuronal cells. However, device implantation inevitably causes injury to brain tissue and induces a foreign body response, leading to reduced recording performance and stimulation efficacy. Astrocytes in the healthy brain play multiple roles including regulating energy metabolism, homeostatic balance, transmission of neural signals, and neurovascular coupling. Following an insult to the brain, they are activated and observed to gather around the site of injury. These reactive astrocytes have been regarded as one of the main contributors to the formation of a glial scar which affects the performance of microelectrode arrays. This study investigates the dynamics of astrocytes within the first 2 weeks after implantation of an intracortical microelectrode into the mouse brain using two-photon microscopy. From our observation astrocytes are highly dynamic during this period, exhibiting patterns of process extension, soma migration, morphological activation, and device encapsulation that are spatiotemporally distinct from other glial cells, such as microglia or oligodendrocyte precursor cells. This detailed characterization of astrocyte reactivity will help to better understand the tissue response to intracortical devices and lead to the development of more effective intervention strategies to improve the functional performance neural interfacing technology.

bioengineering↗

bioRxiv2022

Disruptive selection via pollinators and seed predators on the height of flowers in a wind-dispersed alpine herb

Premise of the studyFloral stalk height is known to affect pollination and seed dispersal in wind-dispersed grassland species, but it may also affect the attractiveness of flowers and fruits in animal-pollinated and animal-dispersed plants. Stalk height may thus be responsive to selection via interactions with both mutualist pollinators and seed dispersers, but also antagonist florivors and seed predators. In this study, we aimed to determine the effect of pollinators and seed predators on selection on floral stalk height in the insect-pollinated and wind-dispersed alpine andromonoecious herb Pulsatilla alpina, whose flowers also vary in their sex allocation and thus in the resources available to both mutualists and antagonists. MethodsWe measured the resource status of individuals in terms of their size and the height of the vegetation surrounding plants of P. alpina at eleven sites. In one population, we recorded the dynamics of floral stalk height over the course of an entire growing season and its association with floral morphology and floral sex allocation (pistil and stamen number), and we used leaf-removal manipulations to assess the effect of herbivory on floral stalk height. Finally, in four populations we studied phenotypic selection on floral stalk height in four female components of reproductive success before seed dispersal. Key resultsStalk height was positively associated with female allocation of the respective flower, the resource status of the individual, and the height of the surrounding vegetation, and negatively affected by leaf removal. Our results point to disruptive selection on stalk height in terms of both selection differentials and selection gradients for fertilization, seed predation, and seed maturation rates, and to positive selection on stalk height in terms of a selection differential for mature seed number. ConclusionsStalk height in P. alpina is a costly trait that affects female reproductive success via interactions with both mutualists and antagonists. We discuss the interplay between the resource status and selection imposed on female reproductive success and its likely role in the evolution of sex-allocation strategies, especially andromonoecy.

evolutionary biology↗

bioRxiv2022

Inferring CTCF insulators and anchored loops across human tissues and cell types

CCCTC-binding factor (CTCF) is a transcription regulator which is involved in many cellular processes. How CTCF recognizes DNA sequence to exert chromosome barrier or enhancer blocking effects remains to be fully interrogated. Despite many computational tools were developed to predict CTCF-mediated loops qualitatively or quantitatively, few could specially evaluate the regulatory potential of DNA sequence at CTCF binding sites (CBSs) and how it affects chromatin loop formation. Here, we developed a deep learning model, DeepAnchor, to precisely characterize the binding patterns for different types of CBSs. By incorporating base-wise genomic/epigenomic features, we revealed distinct chromatin and sequence features for CTCF-mediated insulation and looping at a high resolution, such as two sequence motifs flanking the core CTCF motif at loop-associated CBSs. Besides, we leveraged the predicted anchor score to optimize the loop extrusion model and achieved the best performance in predicting CTCF-anchored loops. We established a compendium of context-specific CTCF-anchored loops across 52 human tissue/cell types and found that genomic disruption of CTCF-anchored loops may represent a general causal mechanism of disease pathogenesis. These computational models, together with the established resource, could facilitate the mechanistic research on how the CTCF-mediated cis-regulatory elements (CREs) shapes context-specific gene regulation in cell development and disease progression.

bioinformatics↗

bioRxiv2022

Spatiotemporal dynamics of zygotic genome activation in basal chordates revealed by interspecific hybrids

Zygotic genome activation (ZGA), a universal process in early embryogenesis that occurs during the maternal-to-zygotic transition, involves reprogramming in the zygotic nucleus that initiates global transcription. In recent decades, knowledge of this process has been acquired from research on various model organisms; however, a consensus explanation of the mechanism underlying the process, especially in relation to housekeeping gene reactivation, is lacking. Here, we used hybrids derived from two ascidian species (Ciona robusta and C. savignyi), which diverged >120 Mya with significant divergence among most orthologous genes, to symmetrically document the unique dynamics of ZGA in urochordates. We found two co-ordinated waves of ZGA, representing early developmental and housekeeping gene reactivation, during the 8-cell to 110-cell stage. Comparative analysis revealed the regulatory connection between maternal and zygotic genes as well as allelic-specific expression in a species-rather than parental-related manner, which was attributed to the divergence of cis-regulatory elements. Single-cell RNA sequencing revealed that spatial differential reactivation of paternal housekeeping genes was significantly correlated with the mechanical property of each cell type. These findings potentially provide a new system for understanding the evolution and adaptation of strategies regulating ZGA in basal chordates.

developmental biology↗

bioRxiv2022

MEBOCOST: Metabolic Cell-Cell Communication Modeling by Single Cell Transcriptome

We developed MEBOCOST, a computational algorithm for quantitatively inferring metabolite-mediated intercellular communications using single cell RNA-seq data. The algorithm identifies cell-cell communications in which metabolites, such as lipids, are secreted by sender cells and traveled to interact with sensor proteins of receiver cells. The sensor proteins on receiver cell might be cell surface receptors, transporters across the cell membrane, or nuclear receptors. MEBOCOST relies on a comprehensive database of metabolite-sensor partners, which we manually curated from the literatures and other public sources. MEBOCOST defines sender and receiver cells for an extracellular metabolite based on the expression levels of the enzymes and sensors, respectively, thus identifies metabolite-sensor communications between the cells. Applying MEBOCOST to mouse brown adipose tissue (BAT) successfully recaptured known metabolite-mediated cell communications and further identified new communications. Additionally, MEBOCOST identified a set of BAT intercellular metabolite-sensor communications that was regulated by cold exposure of the mice. MEBOCOST will be useful to numerous researchers to investigate metabolite-mediated cell-cell communications in many biological and disease models. The MEBOCOST software is freely available at https://github.com/zhengrongbin/MEBOCOST.

bioinformatics↗

bioRxiv2022

Characterizing transition cells in developmental processes from scRNA-seq data

Multi-cellular organism development involves orchestrated gene regulations of different cell types and cell states. Single-cell RNA-Seq, enable simultaneous observation of cells in various states, making it possible to study the underlying molecular mechanisms. However, most of the analytical methods do not make full use of the dynamics captured. Here, we model single-cell RNA-seq data obtained from a developmental process as a function of gene regulatory network using stochastic differential equations (SDEs). Based on dynamical systems theory, we showed that pair-wise gene expression correlation coefficients can accurately infer cell state transitions and validated it using mouse muscle cell regeneration scRNA-seq data. We then applied our analytical framework to the PDAC (Pancreatic ductal adenocarcinoma) mouse model scRNA-seq data. Through transition cells found in the pancreatic preinvasive lesions scRNA-seq data, we can better explain the heterogeneity and predict distinct cell fate even at early tumorigenesis stage. This suggests that the biomarkers identified by transition cells can be potentially used for diagnosis, prognosis and therapeutics of diseases.

bioinformatics↗

bioRxiv2022

Characterizing metabolism from bulk and single-cell RNA-seq data using METAFlux

Cells often alter metabolic strategies under nutrient-deprived conditions to support their survival and growth. Characterizing metabolic reprogramming in the TME (Tumor Microenvironment) is of emerging importance in ongoing cancer research and therapy development. Recent developments in mass spectrometry (MS)-based technologies allow simultaneous characterization of metabolic features of tumor, stroma, and immune cells in the TME. However, they only measure a subset of metabolites and cannot provide in situ measurements. Computational methods such as flux balance analysis (FBA) have been developed to estimate metabolic flux from bulk RNA-seq data and have recently been extended to single-cell RNA-seq (scRNA-seq) data. However, it is unclear how reliable the results are, particularly in the context of tissue TME characterization. To investigate this question and fill the analytical gaps, we developed a computational program METAFlux (METAbolic Flux balance analysis), which extends the FBA framework to infer metabolic fluxes from either bulk or single-cell transcriptomic TME data. We benchmarked the prediction accuracy of METAFlux using the exometabolomics data generated on the NCI-60 cell lines and observed significant improvement over existing approaches. We tested METAFlux in bulk RNA-seq data obtained from various tumor types including those in the TCGA. We validated previous knowledge, e.g., lung squamous cell carcinoma (LUSC) has higher glucose uptake than lung adenocarcinoma (LUAD). We also found a novel subset of LUAD samples with unique metabolic profiles and distinct survival outcome. We further examined METAFlux on scRNA-seq data obtained from coculturing tumor cells with CAR-NK cells and observed high consistency between the predicted and the experimental (i.e., Seahorse extracellular) flux measurements. Throughout our investigation, we discovered various modes of metabolic cooperation and competition between various cell-types in TMEs, which could lead to further target discovery and development.

bioinformatics↗

bioRxiv2022

Highly dense and scalable protein arrays for single-molecule studies

Single-molecule proteomic studies are critically important for understanding the molecular origins of cellular phenotypes. However, no currently available technology can achieve both the single-molecule sensitivity and high dynamic range required to comprehensively analyze the complex mixtures of proteins in biological samples. One approach to achieve high sensitivity across a wide dynamic range would be to create a protein array that arranges billions of single molecules with regular spacing on a patterned surface. However, creating such a protein array has remained an unsolved challenge for the field. Here, we present a highly scalable method for fabricating dense single-molecule protein arrays using a specially designed DNA origami structure, protein click-conjugation, photolithography and surface functionalization. The origami-structure is enhanced via terminal deoxynucleotidyl transferase-extension, which generates brush-like projections, increasing the effective size of the origami from 88 nm to greater than 200 nm. These particles are large enough to enable super-Poisson deposition of individual protein molecules on a nano-patterned chip (>98% occupancy with only 1% of sites occupied with multiple protein molecules). This approach allowed for single-molecule protein display of 600 million protein molecules per microscope slide-sized chip with the potential to scale further with denser feature spacing. We hypothesize that this technology will ultimately enable the development of highly scalable proteomic analysis platforms that address the currently unmet need for protein measurements at single-molecule sensitivity across an exceptionally wide dynamic range of protein concentrations.

bioengineering↗

bioRxiv2022

Sugar transporter Slc37a2 regulates bone metabolism via a dynamic tubular lysosomal network in osteoclasts

Osteoclasts are giant bone-digesting cells that harbour specialized lysosome-related organelles termed secretory lysosomes (SLs). SLs store cathepsin K and serve as a membrane precursor to the ruffled border, the osteoclasts resorptive apparatus. Yet, the molecular composition and spatiotemporal organization of SLs remains incompletely understood. Here, using organelle-resolution proteomics, we identify member a2 of the solute carrier 37 family (Slc37a2) as a SL sugar transporter. We demonstrate that Slc37a2 localizes to the SL limiting membrane and that these organelles adopt a hitherto unnoticed but dynamic tubular network in living osteoclasts that is required for bone digestion. Accordingly, mice lacking Slc37a2 accrue high bone mass owing to uncoupled bone metabolism and disturbances in SL export of monosaccharide sugars, a prerequisite for SL delivery to the ruffled border. Thus, Slc37a2 is a physiological component of the osteoclasts unique secretory organelle and a potential therapeutic target for metabolic bone diseases.

cell biology↗

bioRxiv2022

BIN2 phosphorylates the Thr280 of CO to restrict its function in promoting Arabidopsis flowering

CONSTANS (CO) is a central regulator of floral initiation in response to photoperiod. In this study, we show that the GSK3 kinase BIN2 physically interacts with CO and the gain-of-function mutant bin2-1 displays late flowering phenotype through down-regulation of FT transcription. Genetic analyses show that BIN2 genetically acts upstream of CO in regulating flowering time. Further, we illustrate that BIN2 phosphorylates the Thr280 residue of CO. Importantly, the BIN2 phosphorylation of Thr280 residue restricts the function of CO in promoting flowering. Moreover, we reveal that the N-terminal part of CO harboring the B-Box domain mediates the interaction of both CO-CO and BIN2-CO. We find that BIN2 inhibits the formation of CO dimer/oligomer. Taken together, this study reveals that BIN2 regulates flowering time through phosphorylating the Thr280 of CO and inhibiting the CO-CO interaction in Arabidopsis. HighlightBIN2 regulates flowering time through phosphorylating the Thr280 of CO in Arabidopsis.

molecular biology↗

bioRxiv2022

Laboratory evolution of synthetic electron transport system variants reveals a larger metabolic respiratory system and its plasticity

Respiration requires organisms to have an electron transport system (ETS) for the generation of proton motive force across the membrane that drives ATP synthase. Although the molecular details of the ETS are well studied and constitute textbook material, few studies have appeared to elucidate its systems biology. The most thermodynamically efficient ETS consists of two enzymes, an NADH: quinone oxidoreductase (NqRED) and a dioxygen reductase (O2RED), which facilitate the shuttling of electrons from NADH to oxygen. However, evolution has produced variations within ETS which modulate the overall energy efficiency of the system even within the same organism 1-3. The system-level impact of these variations and their individual physiological optimality remain poorly determined. To mimic varying ETS efficiency we generated four Escherichia coli deletion strains (named ETS-1H, 2H, 3H, and 4H) harboring unbranched ETS variants that pump 1, 2, 3, or 4 proton(s) per electron respectively. We then used a combination of synergistic methods (laboratory evolution, multi-omic analyses, and computation of proteome allocation) to characterize these ETS variants. We found that: (a) all four ETS variants evolved to a similar optimized growth rate, (b) the evolution of ETS variants was enabled by specific rewiring of major energy-generating pathways that couple to the ETS to optimize their ATP production capability, (c) proteome allocation per ATP generated was the same for all the variants, (d) the aero-type, that designates the overall ATP generation strategy 4 of a variant, remained conserved during its laboratory evolution, with the exception of the ETS-4H variant, and (e) integrated computational analysis of then data supported a proton-to-ATP ratio of 10 protons per 3 ATP for ATP synthase for all four ETS variants. We thus have defined the Aero-Type System (ATS) as a generalization of the aerobic bioenergetics, which is descriptive of the metabolic systems biology of respiration and demonstrates its plasticity.

systems biology↗

bioRxiv2022

The Modular μSiM: a Mass Produced, Rapidly Assembled, and Reconfigurable Platform for the Study of Barrier Tissue Models In Vitro

Advanced in vitro tissue chip models can reduce and replace animal experimentation and may eventually support on-chip clinical trials. To realize this potential, however, tissue chip platforms must be both mass-produced and reconfigurable to allow for customized design. To address these unmet needs, we introduce an extension of our {micro}SiM (microdevice featuring a silicon-nitride membrane) platform. The modular {micro}SiM (m-{micro}SiM) uses mass-produced components to enable rapid assembly and reconfiguration by laboratories without knowledge of microfabrication. We demonstrate the utility of the m-{micro}SiM by establishing an hiPSC-derived blood-brain barrier (BBB) in bioengineering and non-engineering, brain barriers focused laboratories. We develop and validate in situ and sampling-based assays of small molecule diffusion as a measure of barrier function. BBB properties show excellent interlaboratory agreement and match expectations from literature, validating the m-{micro}SiM as a platform for barrier models and demonstrating successful dissemination of components and protocols. We then demonstrate the ability to quickly reconfigure the m-{micro}SiM for co-culture and immune cell transmigration studies through addition of accessories and/or quick exchange of components. Because the development of modified components and accessories is easily achieved, custom designs of the m-{micro}SiM should be accessible to any laboratory desiring a barrier-style tissue chip platform.

bioengineering↗

bioRxiv2022

Simultaneously spatiotemporal gene expression and chromatin accessibility for mouse brain development

Brain are complex biological tissues which function relies on coordinated anatomical and molecular structure comprised by a large number of specialized cells. The spatial architecture of brain which is key to the understanding of its physiological and pathological significance is formed during embryo development. However, the molecular basis for discrete neuroanatomical domains particularly in the context of spatial organization of the brain is inadequate. Here, we introduced microfluidic indexing based spatial ATAC and RNA sequencing (MISAR-seq), a method for joint profiling of chromatin accessibility and gene expression with spatial information retained in the developing mouse brain. Our study has established a direct means to spatially determine the coordination between chromatin accessibility and transcriptome, identified the chromatin potential to define cell fate determination of brain organization, and uncovered spatiotemporal regulatory principles during mammalian brain development.

developmental biology↗

bioRxiv2022

Cas9-Mediated Knockout of Ndrg2 Enhances the Regenerative Potential of Dendritic Cells for Wound Healing

Chronic wounds impose a significant healthcare burden to a broad patient population. Cell based therapies, while having shown benefits for the treatment of chronic wounds, have not achieved widespread adoption into clinical practice. Here, we developed a novel CRISPR/Cas9 approach to precisely edit dendritic cells (DCs) to enhance their therapeutic potential for healing chronic wounds. Using single-cell RNA sequencing (scRNA-seq) of tolerogenic DCs, we discover N-myc downregulated gene 2 (Ndrg2), which marks a specific population of DC progenitors, as a promising target for CRISPR knockout (KO). Ndrg2-KO alters the transcriptomic profile of DCs and preserves an immature cell state with a strong, pro-angiogenic and regenerative capacity. We then incorporated our CRISPR-based cell engineering within a hydrogel technology for in vivo cell delivery and developed a highly effective translational approach for DC based immunotherapy that accelerated healing of full-thickness wounds in both non-diabetic and diabetic mouse models. These findings could open the door to future clinical trials using safe gene editing in DCs for treating various types of chronic wounds.

cell biology↗

bioRxiv2022

Exploring the Neoantigen burden in Breast Carcinoma Patients

In this study we performed a multi-omics analysis comprising whole-exome sequencing (WES) and RNA sequencing (RNA-Seq) on seven breast cancer patients, consisting of three Estrogen receptor (ER) positive and four Triple negative breast cancer (TNBC) subtypes to understand the neoantigen burden in breast cancer tumor samples. We predicted both class-I and class-II human leukocyte antigen (HLA) bound neoantigens by analyzing matched tumor-normal pair of exomes. Across all the patients, we predicted 434 unique neoantigens (NeoFil) in total, affecting 237 different genes and 87% of them (n = 378) are expressed at RNA level (Neoexp). The missense mutations (87%) are the major contributor in neoantigen (Neoexp) generation, followed by frameshift (11%) and indels (2%). The neoantigens (NeoFil) were found to be positively correlated with the somatic mutations (R2 = 0.89). We also noted that the vast majority (99.98%) of the predicted neoantigens are patient specific. Overall, the current study offers significant insight into the neoantigen profile in tumor types with intermediate/low mutation burdens like breast cancer.

cancer biology↗

bioRxiv2022

Social deficits induced by pervasive environmental stressors are prevented by microbial or dopaminergic modulation

Environmental toxicant exposure, including air pollution, is increasing worldwide. However, toxicant exposures are not equitably distributed. Rather, low-income and minority communities bear the greatest burden, along with higher levels of psychosocial stress. Both air pollution and maternal stress during pregnancy have been linked to neurodevelopmental disorders such as autism, but biological mechanisms and targets for therapeutic intervention remain poorly understood. We demonstrate that combined prenatal exposure to air pollution (diesel exhaust particles, DEP) and maternal stress (MS) in mice induces social behavior deficits only in male offspring, in line with the male bias in autism. These behavioral deficits are accompanied by changes in microglia and dopaminergic circuits in the brain, along with changes in the structure of the gut epithelium and microbiome. Importantly, DEP/MS-induced social deficits in males are prevented by shifting the gut microbiome by cross-fostering at birth and reversed by chemogenetic activation of the dopamine system.

neuroscience↗

bioRxiv2022

Single cell atlas of the neonatal small intestine with necrotizing enterocolitis

Necrotizing enterocolitis (NEC) is a gastrointestinal complication of premature infants with high rates of morbidity and mortality. A comprehensive view of the cellular changes and aberrant interactions that underlie this disease is lacking. Here, we combine single cell RNA sequencing, T Cell Receptor beta (TCR{beta}) analysis, bulk transcriptomics, and imaging to characterize cell identities, interactions and zonal changes in NEC. We find that inflammatory macrophages are abundant in NEC and that T cells exhibit increased expression of inflammatory genes and cytokines accompanied by an increase in TCR{beta} clonal expansion. Fibroblasts and endothelial cells increase in proportion and exhibit a switch to an activated pro-inflammatory state. Villus tip epithelial cell identity is substantially reduced in NEC and the remaining epithelial cells up-regulate pro-inflammatory genes. We establish a detailed map of aberrant epithelial-mesenchymal-immune interactions that may be driving inflammation in NEC mucosa. Our analyses highlight the cellular changes underlying NEC disease pathogenesis and identify potential targets for biomarker discovery and therapeutics.

immunology↗

bioRxiv2022

Reduced antigenicity of Omicron lowers host serologic response

SARS-CoV-2 Omicron variant of concern (VOC) contains fifteen mutations on the receptor binding domain (RBD), evading most neutralizing antibodies from vaccinated sera. Emerging evidence suggests that Omicron breakthrough cases are associated with substantially lower antibody titers than other VOC cases. However, the mechanism remains unclear. Here, using a novel geometric deep-learning model, we discovered that the antigenic profile of Omicron RBD is distinct from the prior VOCs, featuring reduced antigenicity in its remodeled receptor binding sites (RBS). To substantiate our deep-learning prediction, we immunized mice with different recombinant RBD variants and found that the Omicrons extensive mutations can lead to a drastically attenuated serologic response with limited neutralizing activity in vivo, while the T cell response remains potent. Analyses of serum cross-reactivity and competitive ELISA with epitope-specific nanobodies revealed that the antibody response to Omicron was reduced across RBD epitopes, including both the variable RBS and epitopes without any known VOC mutations. Moreover, computational modeling confirmed that the RBS is highly versatile with a capacity to further decrease antigenicity while retaining efficient receptor binding. Longitudinal analysis showed that this evolutionary trend of decrease in antigenicity was also found in hCoV229E, a common cold coronavirus that has been circulating in humans for decades. Thus, our study provided unprecedented insights into the reduced antibody titers associated with Omicron infection, revealed a possible trajectory of future viral evolution and may inform the vaccine development against future outbreaks.

immunology↗