Biology subjects

Xiao, Z.

Publications and source records attributed to Xiao, Z..

100 records · Page 6Linked to original sources

bioRxiv2020

Single-cell Analysis of ACE2 Expression in Human Kidneys and Bladders Reveals a Potential Route of 2019-nCoV Infection

Since December 2019, a novel coronavirus named 2019 coronavirus (2019-nCoV) has emerged in Wuhan of China and spread to several countries worldwide within just one month. Apart from fever and respiratory complications, acute kidney injury has been observed in some patients with 2019-nCoV. In a short period of time, angiotensin converting enzyme II (ACE2), have been proposed to serve as the receptor for the entry of 2019-nCoV, which is the same for severe acute respiratory syndrome coronavirus (SARS). To investigate the possible cause of kidney damage in 2019-nCoV patients, we used both published kidney and bladder cell atlas data and an independent unpublished kidney single cell RNA-Seq data generated in-house to evaluate ACE2 gene expressions in all cell types in healthy kidneys and bladders. Our results showed the enriched expression of all subtypes of proximal tubule cells of kidney and low but detectable levels of expression in bladder epithelial cells. These results indicated the urinary system is a potential route for 2019-nCoV infection, along with the respiratory system and digestion system. Our findings suggested the kidney abnormalities of SARS and 2019-nCoV patients may be due to proximal tubule cells damage and subsequent systematic inflammatory response induced kidney injury. Beyond that, laboratory tests of viruses and related indicators in urine may be needed in some special patients of 2019-nCoV.

genomics↗

bioRxiv2019

Predictive Coding Models for Pain Perception

Pain is a complex, multidimensional experience that involves dynamic interactions between sensory-discriminative and affective-emotional processes. Pain experiences have a high degree of variability depending on their context and prior anticipation. Viewing pain perception as a perceptual inference problem, we propose a predictive coding paradigm to characterize evoked and non-evoked pain. We record the local field potentials (LFPs) from the primary somatosensory cortex (S1) and the anterior cingulate cortex (ACC) of freely behaving rats--two regions known to encode the sensory-discriminative and affective-emotional aspects of pain, respectively. We further use predictive coding to investigate the temporal coordination of oscillatory activity between the S1 and ACC. Specifically, we develop a phenomenological predictive coding model to describe the macroscopic dynamics of bottom-up and top-down activity. Supported by recent experimental data, we also develop a biophysical neural mass model to describe the mesoscopic neural dynamics in the S1 and ACC populations, in both naive and chronic pain-treated animals. Our proposed predictive coding models not only replicate important experimental findings, but also provide new prediction about the impact of the model parameters on the physiological or behavioral read-out--thereby yielding mechanistic insight into the uncertainty of expectation, placebo or nocebo effect, and chronic pain.

neuroscience↗

bioRxiv2019

Comparison of Non-linear and Linear Models of Single Channel EEG in patients and normal subjects

This article examines the possibility of using non-linear models(Support Vector Regression) to model the single channel EEG signals from psychiatric patients and a group of normal participants, to predict psychology trait ratings, like attention, anxiety, alertness, fatigue, sleepiness and depression. It used linear models as benchmarks, and the results showed non-linear models outperformed the benchmarks, as well as more advanced linear methods, like principle component regression. It is thus concluded that using single channel in practical situations to monitor these traits would be possible.

neuroscience↗

bioRxiv2019

Quantitative evaluation of a high resolution lipidomics platform

Given the general importance of lipids in health and disease, there is a need for efficient technology that broadly profiles and quantitates the lipid composition of complex mixtures. In this study, we developed and quantitatively evaluated a platform that simultaneously profiles both lipids and polar metabolites from the same sample. This method was achieved by using a methyl tert-butyl ether (MTBE) extraction and employing two liquid chromatography methods coupled with high resolution mass spectrometry (LC-HRMS). This workflow enabled detection and semi-quantitation of over 300 polar metabolites as well as over 300 lipids with comprehensive coverage of diverse chemical classes. Using cultured mammalian cells as an example, we report the quantitative properties of the platform including the sensitivity and linear range. The lipidomics strategy was further applied to characterize changes to lipid metabolism upon treatment with metformin to human ovarian cancer cells. Of the 256 detected lipids, 99 lipids (39%) significantly increased, 11 lipids (4%) were significantly reduced and 146 lipids (57%) remain unchanged in metformin-treated cells. Stable isotope tracing of carbon into lipids using [13C6]-glucose further measured the contribution of de novo fatty acid synthesis to the total fatty acid pool. In summary, the platform enabled the semi-quantitative assessment of hundreds of lipid species and associated carbon incorporation from glucose in a high throughput manner.

biochemistry↗

bioRxiv2019

Quantitative proteomic profiling of tumor-associated vascular endothelial cells in colorectal cancer

SummeryTo investigate the global proteomic profiles of vascular endothelial cells (VECs) in the tumor microenvironment and antiangiogenic therapy for colorectal cancer (CRC), matched pairs of normal (NVECs) and tumor-associated VECs (TVECs) were purified from CRC tissues by laser capture microdissection and subjected to iTRAQ based quantitative proteomics analysis. Here, 216 differentially expressed proteins (DEPs) were identified and performed bioinformatics analysis. Interestingly, these proteins were implicated in epithelial mesenchymal transition (EMT), ECM-receptor interaction, focal adhesion, PI3K-Akt signaling pathway, angiogenesis and HIF-1 signaling pathway, which may play important roles in CRC angiogenesis. Among these DEPs, Tenascin-C (TNC) was found to upregulated in the TVECs of CRC and be correlate with CRC multistage carcinogenesis and metastasis. Furthermore, the reduction of tumor-derived TNC could attenuate human umbilical vein endothelial cell (HUVEC) proliferation, migration and tube formation through ITGB3/FAK/Akt signaling pathway. Based on the present work, we provided a large-scale proteomic profiling of VECs in CRC with quantitative information, a certain number of potential antiangiogenic targets and a novel vision in the angiogenesis bio-mechanism of CRC. Summery statementWe provided large-scale proteomic profiling of vascular endothelial cells in colorectal cancer with quantitative information, a number of potential antiangiogenic targets and a novel vision in the angiogenesis bio-mechanism of CRC.

cancer biology↗

bioRxiv2019

Metabolic landscape of the tumor microenvironment

The tumor milieu consists of numerous cell types with each cell existing in a different nutritional environment. However, a characterization of intratumoral metabolic heterogeneity at the single-cell level in human cancer is not established. Here, we develop a computational pipeline to analyze metabolic gene expression programs of single cells within human tumors. In two representative cancer types, melanoma and head and neck, we apply this algorithm to define the single-cell metabolic landscape of human tumors. We find that malignant cells in general have higher metabolic activity and higher metabolic variation than previously observed from studies of bulk tumor comparisons. Indeed, most of the observed metabolic variation of single tumor and normal cells were found to be inconsistent with comparisons with bulk tumor samples. Variation in the expression of mitochondrial programs is the major contributor to intratumoral metabolic heterogeneity. Surprisingly, the expression of both glycolytic and mitochondrial programs strongly correlates with hypoxia in almost all cell types. Immune and stromal cells could also be distinguished by their metabolic features. Taken together this analysis establishes a computational framework for characterizing metabolism using single cell expression data and defines principles of intratumoral metabolic heterogeneity.

systems biology↗

bioRxiv2019

Genetic dissection of femoral and tibial microarchitecture

Our understanding of the genetic control of bone has relied almost exclusively on estimates of bone mineral density. In contrast, here we have used high-resolution x-ray tomography (8 m isotropic voxels) to measure femoral and tibial components across a set of ~600 mice belonging to 60 diverse BXD strains of mice. We computed heritabilities of 25 cortical and trabecular compartments. Males and females have well matched trait heritabilities, ranging from 0.25 to 0.75. We mapped 16 QTLs that collectively cover ~8% of all protein-coding genes in mouse. A majority of loci are detected only in females, and there is also a bias in favor of QTLs for cortical traits. To efficiently evaluate candidate genes we developed a method that couples gene ontologies with expression data to compute bone-enrichment scores for almost all protein-coding genes. We carefully collated and aligned murine candidates with recent human BMD genome-wide association results. We highlight a subset of 50 strong candidates that fall into three categories: 1. those linked to bone function that have already been experimentally validated (Adamts4, Ddr2, Darc, Adam12, Fkbp10, E2f6, Adam17, Grem2, Ifi204); 2. candidates with putative bone function but not yet tested (e.g., Greb1, Ifi202b) but several of which have been linked to phenotypes in humans; and 3. candidates that have high bone-enrichment scores but for which there is not yet any specific link to bone biology or skeletal disease, including Ifi202b, Ly9, Ifi205, Mgmt, F2rl1, Iqgap2. Our results highlight contrasting genetic architecture between the sexes and among major bone compartments. The joint use and alignment of murine and human data should greatly facilitate function analysis and preclinical testing.\n\nDisclosureThe authors declare that no competing interests exist.

genetics↗

bioRxiv2018

Pleistocene Mammal Population Fluctuation Patterns Inferred by Their Genomes

Paleoclimate fluctuations critically affect paleoecological systems and influence mammal populations, even resulting in population differentiation [1]. Historical effective population size (Ne) can reflect these influences [2, 3]. Dozens of recent studies have investigated the relationship between variations in Ne values of one or a small number of mammalian species, inferred from genomic data, and fluctuations in paleoclimate [4-7]. However, there lacks an integrated and comprehensive study on the relationship between the fluctuations in paleoclimate and variations in Ne values inferred from genome sequencing data of a wide range of mammals. To investigate patterns in mammalian Ne values during the the Pleistocene, we gathered whole genome sequencing data of 60 mammals from 35 species distributed across Afro-Eurasia and the Americas, then inferred their Ne curves using the Pairwise Sequentially Markovian Coalescent (PSMC) method; 30 mammalian Ne curves almost simultaneously started to contract at the turning point of the Middle Pleistocene Transition (MPT); then the population of seven mammals started to expand at the turning point of the Middle Brunhes Event (MBE), while the contraction of other mammals populations was prolonged to the later different time periods. Eight mammals experienced a severe population contraction around the Last Glaciation Maximum, as some aves did [8], while four potential ruminant beneficiaries showed an expanding population. Sus scrofa and Bos taurus experienced an internal population differentiation in the MPT. To conclude, the phenomenon that critical paleoclimate events facilitated contemporaneous animal population fluctuations in the paleoecological system is showed by our Ne curve analysis.

bioinformatics↗

bioRxiv2017

Hypoxia in the grape berry linked to mesocarp cell death: the role of seed respiration and lenticels on the berry pedicel

Mesocarp cell death (CD) during ripening is common in berries of seeded Vitis vinifera L wine cultivars. We examined if hypoxia within berries is linked to CD. Internal oxygen concentration ([O2]) across the mesocarp was measured in berries from Chardonnay and Shiraz, both seeded, and Ruby Seedless, using an oxygen micro-sensor. Steep [O2] gradients were observed across the skin and [O2] decreased toward the middle of the mesocarp. As ripening progressed the minimum [O2] approached zero in the seeded cultivars and correlated to CD. Seed respiration was a large proportion of total berry respiration early in ripening but did not account for O2 deficiency late in ripening. [O2] increased towards the central axis corresponding to the presence of air spaces visualised using x-ray microCT. These connect to lenticels on the pedicel that were critical for berry O2 uptake as a function of temperature, and when blocked caused anoxia in the berry, ethanol accumulation and CD. Lenticel area on Chardonnay pedicels was higher than that for Shiraz probably accounting for the lower sensitivity of Chardonnay berry CD to high temperatures. The implications of hypoxia in grape berries are discussed in terms of its role in ripening and berry water relations.\n\nHighlightGrape berry internal oxygen concentration is dependent upon lenticels on the pedicel and cultivar differences in lenticels may account for temperature sensitivity of cell death in the mesocarp.

plant biology↗

bioRxiv2017

De Novo Annotation And Characterization Of The Translatome With Ribosome Profiling Data

By capturing and sequencing the RNA fragments protected by translating ribosomes, ribosome profiling sketches the landscape of translation at subcodon resolution. We developed a new method, RiboCode, which uses ribosome profiling data to assess the translation of each RNA transcript genome-wide. As shown by multiple tests with simulated data and cell type-specific QTI-seq and mass spectrometry data, RiboCode exhibits superior efficiency, sensitivity, and accuracy for de novo annotation of the translatome, which covers various types of novel ORFs in the previously annotated coding and non-coding regions and overlapping ORFs. Finally, to showcase its application, we applied RiboCode on a published ribosome profiling dataset and assembled the context-dependent translatomes of yeast under normal condition, heat shock, and oxidative stress. Comparisons among these translatomes revealed stress-activated novel upstream and downstream ORFs, some of which are associated with potential translational dysregulations of the main protein coding ORFs in response to the stress signals.

bioinformatics↗