Biology subjects

Xie, G.

Publications and source records attributed to Xie, G..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Noncaloric monosaccharides induce excessive sprouting angiogenesis in zebrafish via foxo1a-marcksl1a signal

Artificially sweetened beverages containing noncaloric monosaccharides were suggested as healthier alternatives to sugar-sweetened beverages. Nevertheless, the potential detrimental effects of these noncaloric monosaccharides on blood vessel function remain inadequately understood. We have established a zebrafish model that exhibits significant excessive angiogenesis induced by high glucose, resembling the hyperangiogenic characteristics observed in proliferative diabetic retinopathy (PDR). Utilizing this model, we observed that glucose and noncaloric monosaccharides could induce excessive formation of blood vessels, especially intersegmental vessels (ISVs). The excessively branched vessels were observed to be formed by ectopic activation of quiescent endothelial cells (ECs) into tip cells. Single-cell transcriptomic sequencing analysis of the endothelial cells in the embryos exposed to high glucose revealed an augmented ratio of capillary ECs, proliferating ECs, and a series of upregulated proangiogenic genes. Further analysis and experiments validated that reduced foxo1a mediated the excessive angiogenesis induced by monosaccharides via up-regulating the expression of marcksl1a. This study has provided new evidence showing the negative effects of noncaloric monosaccharides on the vascular system and the underlying mechanisms.

pharmacology and toxicology↗

bioRxiv2024

Tractography-based automated identification of the retinogeniculate visual pathway with novel microstructure-informed supervised contrastive learning

The retinogeniculate visual pathway (RGVP) is responsible for carrying visual information from the retina to the lateral geniculate nucleus. Identification and visualization of the RGVP are important in studying the anatomy of the visual system and can inform the treatment of related brain diseases. Diffusion MRI (dMRI) tractography is an advanced imaging method that uniquely enables in vivo mapping of the 3D trajectory of the RGVP. Currently, identification of the RGVP from tractography data relies on expert (manual) selection of tractography streamlines, which is time-consuming, has high clinical and expert labor costs, and is affected by inter-observer variability. In this paper, we present a novel deep learning framework, DeepRGVP, to enable fast and accurate identification of the RGVP from dMRI tractography data. We design a novel microstructure-informed supervised contrastive learning method that leverages both streamline label and tissue microstructure information to determine positive and negative pairs. We propose a simple and successful streamline-level data augmentation method to address highly imbalanced training data, where the number of RGVP streamlines is much lower than that of non-RGVP streamlines. We perform comparisons with several state-of-the-art deep learning methods that were designed for tractography parcellation, and we show superior RGVP identification results using DeepRGVP. In addition, we demonstrate a good generalizability of DeepRGVP to dMRI tractography data from neurosurgical patients with pituitary tumors and we show DeepRGVP can successfully identify RGVPs despite the effect of lesions affecting the RGVPs. Overall, our study shows the high potential of using deep learning to automatically identify the RGVP.

neuroscience↗

bioRxiv2023

A molecularly distinct accumbal-to-lateral hypothalamic circuit modulates food seeking and consumption

Orchestrating complex behavioral states, such as approach and consumption of food, is critical for survival. In addition to hypothalamus neuronal circuits, the nucleus accumbens (NAc) also plays an important role in controlling appetite and satiety in responses to changing external stimuli. However, the specific neuronal subtypes of NAc involved as well as how the humoral and neuronal signals coordinate to regulate feeding remain incompletely understood. Here, we deciphered the spatial diversity of neuron subtypes of the NAc shell (NAcSh) and defined a dopamine receptor D1(Drd1)- and Serpinb2-expressing subtype located in NAcSh encoding food consumption. Chemogenetics- and optogenetics-mediated regulation of Serpinb2+ neurons bidirectionally regulates food seeking and consumption specifically. Circuitry stimulation revealed the NAcShSerpinb2[->]LHLepR projection controls refeeding and can overcome leptin-mediated feeding suppression. Furthermore, NAcSh Serpinb2+ neuron ablation reduces food intake and upregulates energy expenditure resulting in body weight loss. Together, our study reveals a neural circuit consisted of molecularly distinct neuronal subtype that bidirectionally regulates energy homeostasis, which can serve as a potential therapeutic target for eating disorders.

neuroscience↗

bioRxiv2022

Differential roles of extracellular matrix proteins on primary and metastatic pancreatic cancer cells

Pancreatic cancer adenocarcinoma (PDAC) is reported to be the third highest cause of cancer-related deaths in the United States. PDAC is known for its high proportion of stroma, which accounts for 90% of the tumor mass. The stroma is made up of extracellular matrix (ECM) and non-malignant cells such as inflammatory cells, cancer-associated fibroblasts, and lymphatic and blood vessels. Here, we decoupled the effects of the ECM on PDAC cell lines by culturing cells on surfaces coated with different ECM proteins. Our data show that the primary tumor-derived cell lines have different morphology depending on the ECM proteins on which they are cultured, while metastatic lesion-derived PDAC lines morphology does not change with respect to the different ECM proteins. Similarly, ECM proteins modulate the proliferation rate and the gemcitabine sensitivity of the primary tumor PDAC cell lines, but not the metastatic PDAC lines. Lastly, transcriptomics analysis of the primary tumor PDAC cells cultured on different ECM proteins reveals the regulation of various pathways, such as cell cycle, cell adhesion molecules, and focal adhesion, including the regulation of several integrin genes that are essential for ECM recognition.

cancer biology↗

bioRxiv2022

Genomic variations drive phenotypic heterogeneity in pancreatic cancer cells

ObjectivesTo evaluate the suitability of the MIA PaCa-2 cell line for studying pancreatic cancer intratumor heterogeneity, we aim to further characterize the nature of MIA PaCa-2 cells phenotypic, genomic, and transcriptomic heterogeneity. MethodsMIA PaCa-2 single-cell clones were established through flow cytometry. For the phenotypic study, we quantified the cellular morphology, proliferation rate, migration potential, and drug sensitivity of the clones. The chromosome copy number and transcriptomic profiles were quantified using SNPa and RNA-seq, respectively. ResultsFour MIA PaCa-2 clones showed distinctive phenotypes, with differences in cellular morphology, proliferation rate, migration potential, and drug sensitivity. We also observed a degree of genomic variations between these clones in form of chromosome copy number alterations and single nucleotide variations, suggesting the genomic heterogeneity of the population, and the intrinsic genomic instability of MIA PaCa-2 cells. Lastly, transcriptomic analysis of the clones also revealed gene expression profile differences between the clones, including the uniquely regulated ITGAV, which dictates the morphology of MIA PaCa-2 clones. ConclusionsMIA PaCa-2 is comprised of cells with distinctive phenotypes, heterogeneous genomes, and differential transcriptomic profiles, suggesting its suitability as a model to study the underlying mechanisms behind pancreatic cancer heterogeneity.

cancer biology↗

bioRxiv2022

Tumor subclones, where are you?

IntroductionTumor clonal structure is closely related to future progression, which has been mainly investigated via mutation abundance clustering in bulk sample. With limited studies at single-cell resolution, a systematic comparison of the two approaches is still lacking. MethodsHere, using bulk and single-cell mutational data from liver and colorectal cancers, we would like to check the possibility of obtaining accurate tumor clonal structures from bulk-level analysis. We checked whether co-mutations determined by single-cell analysis had corresponding bulk variant allele frequency (VAF) peaks. We examined VAF ranges for different groups of co-mutations, and also the possibility of discriminating them. ResultsWhile bulk analysis suggested absence of subclonal peaks and possibly neutral evolution in some cases, single-cell analysis identified co-existing subclones. The overlaps of bulk VAF ranges for co-mutations from different subclones made it difficult to separate them, even with other parameter introduced. The difference between mutation cluster and tumor subclone is accountable for the challenge in bulk clonal deconvolution, especially in case of branched evolution as shown in colorectal cancer. ConclusionComplex subclonal structures and dynamic evolution are hidden under the seemingly clonal neutral pattern at bulk level, suggesting single-cell analysis will be needed to avoid under-estimation of tumor heterogeneity. Research HighlightsO_LIBulk-level mutation abundance clusters are not equal to tumor subclones. C_LIO_LIDifferent groups of co-mutations could not be discriminated at bulk-level. C_LIO_LISingle-cell mutational analysis can identify rather than infer tumor subclones. C_LIO_LICo-existing tumor subclones may have clonal neutral appearance at bulk-level. C_LI Lay summarySystematic comparison of tumor clonal structure differences between bulk and single-cell mutational analysis is lacking. Here we performed such as study and found that complex subclonal structures and dynamic evolution are hidden under clonal neutral appearance at bulk level in liver and colorectal cancers, suggesting single-cell analysis will be needed to avoid under-estimation of tumor heterogeneity.

cancer biology↗

bioRxiv2022

Genomic heterogeneity in pancreatic cancer organoids and its stability with culture

The establishment of patient-derived pancreatic cancer organoid culture in recent years creates an exciting opportunity for researchers to perform a wide range of in vitro studies on a model that closely recapitulates the tumor. Among the outstanding questions in pancreatic cancer biology are the causes and consequences of genomic heterogeneity observed in the disease. However, to use pancreatic cancer organoids as a model to study genomic variations, we need to first understand the degree of genomic heterogeneity and its stability within organoids. Here, we used single-cell whole-genome sequencing to investigate the genomic heterogeneity of two independent pancreatic cancer organoids, as well as their genomic stability with extended culture. Clonal populations with similar copy number profiles were observed within the organoids, and the proportion of these clones was shifted with extended culture, suggesting the growth advantage of some clones. However, sub-clonal genomic heterogeneity was also observed within each clonal population, indicating the genomic instability of the pancreatic cancer cells themselves. Furthermore, our transcriptomic analysis also revealed a positive correlation between copy number alterations and gene expression regulation, suggesting the functionality of these copy number alterations.

cancer biology↗

bioRxiv2022

Detection of latent Epstein-Barr virus gene expression in single-cell sequencing of peripheral blood mononuclear cells

Epstein-Barr virus (EBV) DNA is regularly found in the blood of patients with EBV associated diseases and occasionally in healthy individuals. However, EBV infected primary B-lymphocytes have not yet been detected using scRNA seq. Here, we screened the viral transcriptome in single cell RNA sequencing datasets from peripheral blood to identify virus infected cells. Whereas EBV RNA was detected in an immunocompromised patient, EBV associated nasopharyngeal carcinoma and multiple sclerosis samples did not display any levels of circulating EBV RNA. We further screened whole-blood samples from a cohort of immunosuppressed patients for viral transcripts using a custom enhanced RT-qPCR panel and detected latency programs dominated by noncoding RNAs (EBERs and RPMS1). To explore the interplay between the EBV and the host-cell transcriptome profile, we used enriched B-lymphocytes from a splenectomy patient with 30% EBER positivity estimated by in situ hybridization and performed 5 single-cell RNA sequencing with paired VDJ profiling. The EBV expression pattern of the patients B-lymphocytes confirmed the RT-qPCR assay with RPMS1 and LMP-1/BNLF2a/b significantly dominating the sequenced EBV polyadenylated RNA. A comparison between the expression profile of EBV positive B-lymphocytes and healthy controls B-lymphocytes revealed the upregulation in genes involved in cell population proliferation when infected with EBV. This is further supported by a measurable polyclonal expansion in the patient, as compared to a control, emphasizing EBVs role in a host-cells tendency for cellular expansion. However, when contrasting to cells that have undergone malignant transformation, the primary EBV infected cells display a rather dissimilar expression profile, even to cells that are supposed to simulate primary EBV infection (I.e. Lymphoblastoid Cell Lines). This implies that during primary infection of EBV, the host-cell enters a state of premalignancy rather than a complete oncogenic transformation at the initial time of infection

microbiology↗

bioRxiv2022

A computational toolbox to investigate the metabolic potential and resource allocation in fission yeast

The fission yeast Schizosaccharomyces pombe is a popular eukaryal model organism for cell division and cell cycle studies. With this extensive knowledge of its cell and molecular biology, S. pombe also holds promise for use in metabolism research and industrial applications. However, unlike the bakers yeast Saccharomyces cerevisiae, a major workhorse in these areas, cell physiology and metabolism of S. pombe remain less explored. One way to advance understanding of organism-specific metabolism is construction of computational models and their use for hypothesis testing. To this end, we leverage existing knowledge of S. cerevisiae to generate a manually-curated high-quality reconstruction of S. pombes metabolic network, including a proteome-constrained version of the model. Using these models, we gain insights into the energy demands for growth, as well as ribosome kinetics in S. pombe. Furthermore, we predict proteome composition and identify growth-limiting constraints that determine optimal metabolic strategies under different glucose availability regimes, and reproduce experimentally determined metabolic profiles. Notably, we find similarities in metabolic and proteome predictions of S. pombe with S. cerevisiae, which indicate that similar cellular resource constraints operate to dictate metabolic organization. With these use cases, we show, on the one hand, how these models provide an efficient means to transfer metabolic knowledge from a well-studied to a lesser-studied organism, and on the other, how they can successfully be used to explore the metabolic behaviour and the role of resource allocation in driving different strategies in fission yeast.

systems biology↗

bioRxiv2022

CyTOF-Lec: Single-cell glycomics analysis reveals glycan features defining cells differentially susceptible to HIV

High-parameter single-cell phenotyping has enabled in-depth classification and interrogation of immune cells, but to date has not allowed for glycan characterization. Here, we develop CyTOF-Lec as an approach to simultaneously characterize many protein and glycan features of human immune cells at the single-cell level. We implemented CyTOF-Lec to compare glycan features between different immune subsets from blood and multiple tissue compartments, and to characterize HIV-infected cell cultures. Using bioinformatics approaches to distinguish preferential infection of cellular subsets from viral-induced remodeling, we demonstrate that HIV upregulates the levels of cell surface fucose and sialic acid in a cell- intrinsic manner, and that memory CD4+ T cells co-expressing high levels of fucose and sialic acid are highly susceptible to HIV infection. Sialic acid levels were found to distinguish memory CD4+ T cell subsets expressing different amounts of viral entry receptors, pro-survival factors, homing receptors, and activation markers, and to play a direct role in memory CD4+ T cells susceptibility to HIV infection. The ability of sialic acid to distinguish memory CD4+ T cells with different susceptibilities to HIV infection was experimentally validated through sorting experiments. Together, these results suggest that HIV remodels not only cellular proteins but also glycans, and that glycan expression can differentiate memory CD4+ T cells with vastly different susceptibility to HIV infection.

immunology↗

bioRxiv2021

Generative Adversarial Network augmented the gut microbiome-based health index by profoundly improved discrimination power

Gut microbiome-based health index (GMHI) has been applied with success, while the discrimination powers of GMHI varied for different diseases, limiting its utility on a broad-spectrum of diseases. In this work, a generative adversarial network (GAN) model is proposed to improve the discrimination power of GMHI. Built based on the batch corrected data through GAN, GAN-GMHI has largely reduced the batch effects, and profoundly improved the performance for distinguishing healthy individuals and different diseases. GAN-GMHI has provided a solution to unravel the strong association of gut microbiome and diseases, and indicated a more accurate venue toward microbiome-based disease monitoring. The code for GAN-GMHI is available at https://github.com/HUST-NingKang-Lab/GAN-GMHI. ImportanceThe association of gut microbiome and diseases has been proven for many diseases, while the transformation of such association to a robust and universal disease prediction model has remained illusive, largely due to the batch effects presents in multiple microbiome cohorts. Our analyses have indicated a plausible venue, which is based on GAN technique, towards batch effect removal for microbiome datasets. GAN-GMHI is a novel method built based on the batch corrected data through GAN, as well as GMHI for prediction of a broad-spectrum of diseases.

bioinformatics↗

bioRxiv2021

mRNA vaccine-induced SARS-CoV-2-specific T cells recognize B.1.1.7 and B.1.351 variants but differ in longevity and homing properties depending on prior infection status

While mRNA vaccines are proving highly efficacious against SARS-CoV-2, it is important to determine how booster doses and prior infection influence the immune defense they elicit, and whether they protect against variants. Focusing on the T cell response, we conducted a longitudinal study of infection-naive and COVID-19 convalescent donors before vaccination and after their first and second vaccine doses, using a high-parameter CyTOF analysis to phenotype their SARS-CoV-2-specific T cells. Vaccine-elicited spike-specific T cells responded similarly to stimulation by spike epitopes from the ancestral, B.1.1.7 and B.1.351 variant strains, both in terms of cell numbers and phenotypes. In infection-naive individuals, the second dose boosted the quantity and altered the phenotypic properties of SARS-CoV-2-specific T cells, while in convalescents the second dose changed neither. Spike-specific T cells from convalescent vaccinees differed strikingly from those of infection-naive vaccinees, with phenotypic features suggesting superior long-term persistence and ability to home to the respiratory tract including the nasopharynx. These results provide reassurance that vaccine-elicited T cells respond robustly to emerging viral variants, confirm that convalescents may not need a second vaccine dose, and suggest that vaccinated convalescents may have more persistent nasopharynx-homing SARS-CoV-2-specific T cells compared to their infection-naive counterparts.

immunology↗

bioRxiv2021

Protracted yet coordinated differentiation of long-lived SARS-CoV-2-specific CD8+ T cells during COVID-19 convalescence

CD8+ T cells are important antiviral effectors that can potentiate long-lived immunity against COVID-19, but a detailed characterization of these cells has been hampered by technical challenges. We screened 21 well-characterized, longitudinally-sampled convalescent donors that recovered from mild COVID-19 against a collection of SARS-CoV-2 tetramers, and identified one participant with an immunodominant response against Nuc322-331, a peptide that is conserved in all the SARS-CoV-2 variants-of-concern reported to date. We conducted 38- parameter CyTOF phenotyping on tetramer-identified Nuc322-331-specific CD8+ T cells, and on CD4+ and CD8+ T cells recognizing the entire nucleocapsid and spike proteins from SARS- CoV-2, and took 32 serological measurements on longitudinal specimens from this participant. We discovered a coordination of the Nuc322-331-specific CD8+ T response with both the CD4+ T cell and antibody pillars of adaptive immunity. Nuc322-331-specific CD8+ T cells were predominantly central memory T cells, but continually evolved over a [~]6-month period of convalescence. We observed a slow and progressive decrease in the activation state and polyfunctionality of the Nuc322-331-specific CD8+ T cells, accompanied by an increase in their lymph-node homing and homeostatic proliferation potential. These results suggest that following a typical case of mild COVID-19, SARS-CoV-2-specific CD8+ T cells not only persist but continuously differentiate in a coordinated fashion well into convalescence, into a state characteristic of long-lived, self-renewing memory.

immunology↗

bioRxiv2021

Single-cell RNA-seq revealed the role of Alkbh5 in reproduction

This manuscript has been withdrawn by the authors as it was submitted and made public without the full consent of all the authors. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author

bioinformatics↗

bioRxiv2021

Epstein-Barr virus long non-coding RNA RPMS1 full-length spliceome in transformed epithelial tissue

Epstein-Barr virus is associated with two types of epithelial neoplasms, nasopharyngeal carcinoma and gastric adenocarcinoma. The viral long non-coding RNA RPMS1 is the most abundantly expressed poly-adenylated viral RNA in these malignant tissues. The RPMS1 gene is known to contain two cassette exons, exon Ia and Ib, and several alternative splicing variants have been described in low-throughput studies. To characterize the entire RPMS1 spliceome we combined long-read sequencing data from the nasopharyngeal cell line C666-1 and a primary gastric adenocarcinoma, with complementary short-read sequencing datasets. We developed FLAME, a Python-based bioinformatics package that can generate complete high resolution characterization of RNA splicing at full-length. Using FLAME, we identified 32 novel exons in the RPMS1 gene, primarily within the large constitutive exons III, V and VII. Two of the novel exons contained retention of the intron between exon III and exon IV, and a novel cassette exon was identified between VI and exon VII. All previously described transcript variants of RPMS1 containing putative ORFs were identified at various levels. Similarly, native transcripts with the potential to form previously reported circular RNA elements were detected. Our work illuminates the multifaceted nature of viral transcriptional repertoires. FLAME provides a comprehensive overview of the relative abundance of alternative splice variants and allows for a wealth of previously unknown splicing events to be unveiled.

bioinformatics↗

bioRxiv2021

The repertoire of testicular extracellular vesicles cargoes and their involvement in inter-compartmental communication required for spermatogenesis

Extracellular vesicles (EVs) secreted by the epididymis and prostate are involved in sperm functions and epigenetic inheritance. However, the EVs in the testis remains unexplored. Here, we have established a testis dissociation protocol that allows the isolation of testicular EVs by minimizing the disruption of fragile sperm cells. We showed that testicular EVs were specifically and efficiently uptaken by somatic cells and germ cells in both interstitial space and seminiferous tubules compartments, including the spermatozoa. We profiled the proteome of testicular EVs and probed the cell types that release them. Moreover, we sequenced the small RNAs cargos of testicular EVs and identified sets of small non-coding RNAs that were overlooked in the testis transcriptome. Selected miRNA candidates in testicular EVs were found in sperm RNA payload and demonstrated specific resistance towards ribonuclease A independent of the vesicle membrane. Small molecule inhibition of EVs secretion increased the apoptosis of germ cells via inter-compartmental communication. Together, our study has provided valuable resources on the cargoes of testicular EVs and revealed the inter-compartmental communication that regulates spermatogenesis and may implicate in paternal inheritance.

cell biology↗

bioRxiv2020

First demonstration of the FLASH effect with ultrahigh dose-rate high energy X-rays

Ultrahigh dose-rate (FLASH) radiotherapy has attracted immense attention because of its tumor control efficiency and healthy tissue protection during preclinical experiments with electrons, kilo-voltage X-rays, and protons. Using high-energy X-rays (HEXs) in FLASH is advantageous owing to its deep penetration, small divergence, and cost-effectiveness. This is the first report on the implementation of HEXs with FLASH (HEX-FLASH) and its corresponding application in vivo. With a high-current and high-energy superconducting linear accelerator, FLASH with a good dose rate and high penetration was achieved. Breast cancers artificially induced in BAL b/c mice were efficiently controlled, and normal tissues surrounding the thorax/abdomen in C57BL/6 mice were protected from radiation with HEX-FLASH. Theoretical analyses of cellular responses following HEX-FLASH irradiation were performed to interpret the experimental results and design further experiments. Thus, this study highlights the generation of HEX-FLASH for the first time and its potential in future clinical applications.

cancer biology↗

bioRxiv2020

Comparison of multiple tractography methods for reconstruction of the retinogeniculate visual pathway using diffusion MRI

The retinogeniculate visual pathway (RGVP) conveys visual information from the retina to the lateral geniculate nucleus. The RGVP has four subdivisions, including two decussating and two non-decussating pathways that cannot be identified on conventional structural magnetic resonance imaging (MRI). Diffusion MRI tractography has the potential to trace these subdivisions and is increasingly used to study the RGVP. However, it is not yet known which fiber tracking strategy is most suitable for RGVP reconstruction. In this study, four tractography methods are compared, including constrained spherical deconvolution (CSD) based probabilistic (iFOD1) and deterministic (SD-Stream) methods, and multi-fiber (UKF-2T) and single-fiber (UKF-1T) unscented Kalman filter (UKF) methods. Experiments use diffusion MRI data from 57 subjects in the Human Connectome Project. The RGVP is identified using regions of interest created by two clinical experts. Quantitative anatomical measurements and expert anatomical judgment are used to assess the advantages and limitations of the four tractography methods. Overall, we conclude that UKF-2T and iFOD1 produce the best RGVP reconstruction results. The iFOD1 method can better quantitatively estimate the percentage of decussating fibers, while the UKF-2T method produces reconstructed RGVPs that are judged to better correspond to the known anatomy and have the highest spatial overlap across subjects. Overall, we find that it is challenging for current tractography methods to both accurately track RGVP fibers that correspond to known anatomy and produce an approximately correct percentage of decussating fibers. We suggest that future algorithm development for RGVP tractography should take consideration of both of these two points.

neuroscience↗