Biology subjects

Cai, J.

Publications and source records attributed to Cai, J..

At least 145 records · Page 8Linked to original sources

bioRxiv2019

Polarized Lung Inflammation and Tie2/Angiopoietin-Mediated Endothelial Dysfunction during Severe Orientia tsutsugamushi Infection

Orientia tsutsugamushi infection can cause acute lung injury and high mortality in humans; however, the underlying mechanisms are unclear. Here, we tested a hypothesis that dysregulated pulmonary inflammation and Tie2-mediated endothelial malfunction contribute to lung damage. Using a murine model of lethal O. tsutsugamushi infection, we demonstrated pathological characteristics of vascular activation and tissue damage: 1) a significant increase of ICAM-1, VEGFR2, and angiopoietin-2 (Ang2) proteins in inflamed tissues and lung-derived endothelial cells (EC), 2) a progressive loss of endothelial quiescent and junction proteins (Ang1, VE-cadherin/CD144, occuludin), and 3) a profound impairment of Tie2 receptor at the transcriptional and functional levels. In vitro infection of primary human EC cultures and serum Ang2 proteins in scrub typhus patients support our animal studies, implying endothelial dysfunction in severe scrub typhus. Flow cytometric analyses of lung-recovered cells further revealed that pulmonary macrophages (M{Phi}) were polarized toward an M1-like phenotype (CD80+CD64+CD11b+Ly6G-) during the onset of disease and prior to host death, which correlated with the significant loss of CD31+CD45- ECs and M2-like (CD206+CD64+CD11b+Ly6G-) cells. In vitro studies indicated extensive bacterial replication in M2-type, but not M1-type, M{Phi}s, implying the protective and pathogenic roles of M1-skewed responses. This is the first detailed investigation of lung cellular immune responses during acute O. tsutsugamushi infection. It uncovers specific biomarkers for vascular dysfunction and M1-skewed inflammatory responses, highlighting future therapeutic research for the control of this neglected tropical disease.\n\nAuthor SummaryScrub typhus is a life-threatening disease, infecting an estimated one million people yearly. Acute lung injury is the most common clinical observation; however, its pathogenic biomarkers and mechanisms of progression remain unknown. Here, we used a lethal infection mouse model that parallels certain aspects of severe scrub typhus, primary human endothelial cell cultures, and patient sera to define pathogenic biomarkers following Orientia tsutsugamushi infections. We found a significant increase in the levels of endothelial activation/stress markers (angiopoietins and ICAM-1) in infected mouse lungs and in patient sera, but a progressive loss of endothelium-specific Tie2 receptor and junction proteins (VE-cadherin), at severe stages of disease. These signs of vasculature disruption positively correlated with the timing and magnitude of recruitment/activation of proinflammatory M{Phi} subsets in infected lungs. Bacterial growth in vitro was favored in M2-like, but not in M1-like, M{Phi}s. This study, for the first time, reveals endothelial malfunction and dysregulated inflammatory responses, suggesting potential therapeutic targets to ameliorate tissue damage and pathogenesis.

microbiology↗

bioRxiv2019

Secondary bile acid ursodeoxycholic acid (UDCA) alters weight, the gut microbiota, and the bile acid pool in conventional mice

Ursodeoxycholic acid (commercially available as Ursodiol) is a naturally occurring bile acid that is used to treat a variety of hepatic and gastrointestinal diseases. Ursodiol can modulate bile acid pools, which have the potential to alter the gut microbiota community structure. In turn, the gut microbial community can modulate bile acid pools, thus highlighting the interconnectedness of the gut microbiota-bile acid-host axis. Despite these interactions, it remains unclear if and how exogenously administered ursodiol shapes the gut microbial community structure and bile acid pool. This study aims to characterize how ursodiol alters the gastrointestinal ecosystem in conventional mice. C57BL/6J wildtype mice were given one of three doses of ursodiol (50, 150, or 450 mg/kg/day) by oral gavage for 21 days. Alterations in the gut microbiota and bile acids were examined including stool, ileal, and cecal content. Bile acids were also measured in serum. Significant weight loss was seen in mice treated with the low and high dose of ursodiol. Alterations in the microbial community structure and bile acid pool were seen in ileal and cecal content compared to pretreatment, and longitudinally in feces following the 21-day ursodiol treatment. In both ileal and cecal content, members of the Lachnospiraceae family significantly contributed to the changes observed. This study is the first to provide a comprehensive view of how exogenously administered ursodiol shapes the gastrointestinal ecosystem. Further studies to investigate how these changes in turn modify the host physiologic response are important.\n\nImportanceUrsodeoxycholic acid (commercially available as ursodiol) is used to treat a variety of hepatic and gastrointestinal diseases. Despite its widespread use, how ursodiol impacts the gut microbial community structure and bile acid pool remains unknown. This study is the first to provide a comprehensive view of how exogenously administered ursodiol shapes the gastrointestinal ecosystem. Ursodiol administration in conventional mice resulted in significant alterations in the gut microbial community structure and bile acid pool, indicating that ursodiol has direct impacts on the gut microbiota-bile acid-host axis which should be considered when this medication is administered.\n\nBile Acid AbbreviationsMCA - -Muricholic acid; {beta}MCA -{beta}-Muricholic acid; {omega}MCA -{omega}-Muricholic acid; CA - Cholic acid; CDCA - Chenodeoxycholic acid; DCA - Deoxycholic acid; GCDCA - Glycochenodeoxycholic acid; GDCA - Glycodeoxycholic acid; GLCA - Glycolithocholic acid; GUDCA - Glycoursodeoxycholic acid; HCA - Hyodeoxycholic acid; iDCA - Isodeoxycholic acid; iLCA - Isolithocholic acid; LCA - Lithocholic acid; TCA - Taurocholic acid; TCDCA - Taurochenodeoxycholic acid; TDCA - Taurodeoxycholic acid; THCA - Taurohyodeoxycholic acid; TUDCA - Tauroursodeoxycholic acid; T{beta}MCA - Tauro-{beta}-muricholic acid; T{omega}MCA -Tauro {omega}-muricholic acid; UDCA - Ursodeoxycholic acid.

microbiology↗

bioRxiv2019

Lanthanide transport, storage, and beyond: genes and processes contributing to XoxF function in Methylorubrum extorquens AM1

Lanthanide elements have been recently recognized as "new life metals" for diverse environmental microorganisms including Gram-negative methylotrophic bacteria and strains of Pseudomonas and Bradyrhizobium. Yet much remains unknown regarding lanthanide acquisition and homeostasis. In Methylorubrum extorquens AM1, the periplasmic lanthanide-dependent methanol dehydrogenase XoxF1 produces formaldehyde, which is lethal if allowed to accumulate. This property enabled a transposon mutagenesis study to expand knowledge of the metabolic network required for methanol oxidation when lanthanides are available. Growth studies were conducted to detail the involvement of novel gene products that impact the ability of XoxF-type enzymes to oxidize methanol to formaldehyde. The identified genes encode an MxaD homolog, an ABC-type transporter, an aminopeptidase, a putative homospermidine synthase, and two genes of unknown function annotated as orf6 and orf7. Lanthanide transport and trafficking genes were also identified. Growth and lanthanide uptake were measured using strains lacking individual lanthanide transport cluster genes and transmission electron microscopy was used to visualize lanthanide localization. We corroborated previous reports that a TonB-ABC transport system is required for lanthanide incorporation to the cytoplasm. However, cells are able to acclimate overtime and bypass the requirement for the TonB outer membrane transporter to allow expression of xoxF1 and growth. Transcriptional reporter fusions show that excess lanthanides repress the gene encoding the TonB-receptor. Using growth studies along with energy dispersive X-ray spectroscopy and transmission electron microscopy, we demonstrate that lanthanides are stored as cytoplasmic inclusions that resemble polyphosphate granules. IMPORTANCEThe increasing genetic and biochemical evidence that lanthanide-dependent enzymes are widespread among numerous environmental microbes leads to the parallel questions of how these insoluble metals are scavenged, transported, and used by bacteria. Results herein describe the contribution of the different gene products that constitute the lanthanide utilization and transport machinery in the methylotroph M. extorquens AM1 and highlight possible redundancies by periplasmic components. The discovery and characterization of intracellular lanthanide storage in mineral form by these microbes opens the possibility of using methylotrophic platforms for concentration and recovery of these critical energy metals from diverse sources. In addition, methylotrophs are effective biotechnological platforms for the production of biofuels and bioplastics from pollutants such as methane, and inexpensive carbon feedstocks like methanol. Defining the lanthanide acquisition, transport, and storage machinery is a step forward in designing a sustainable platform to recover lanthanides efficiently.

microbiology↗

bioRxiv2019

Bridging traditional evolutionary game theory and metabolic models for predicting Nash equilibrium of microbial metabolic interactions

Microbial metabolic interactions impact ecosystems, human health and biotechnological processes profoundly. However, their determination remains elusive, invoking an urgent need for predictive models that seamlessly integrate metabolic details with ecological and evolutionary principles which shape the interactions within microbial communities. Inspired by the evolutionary game theory, we formulated a bi-level optimization framework termed NECom for the prediction of Nash equilibria of microbial community metabolic models with significantly enhanced accuracy. NECom is free of a long hidden forced altruism setup in previous static algorithm while allowing for sensing and responding between microbial members that is missing in dynamic methods. We successfully predicted several classical games in the context of metabolic interactions that were falsely or incompletely predicted by existing methods, including prisoners dilemma, snowdrift game and mutualism. The results provided insights into why mutualism is favorable despite seemingly costly cross-feeding metabolites, and demonstrated the potential to predict heterogeneous phenotypes among the same species. NECom was then applied to a reported algae-yeast co-culture system that shares typical cross-feeding features of lichen, a model system of mutualism. More than 1200 growth conditions were simulated, of which 488 conditions correspond to 3221 experimental data points. Without fitting any ad-hoc parameters, an overall 63.5% and 81.7% reduction in root-mean-square error in predicted growth rates for the two species respectively was achieved when compared with the standard flux balance analysis. The simulation results further show that growth-limiting crossfeeding metabolites can be pinpointed by shadow price analysis to explain the predicted frequency-dependent growth pattern, offering insights into how stabilizing microbial interactions control microbial populations.

systems biology↗

bioRxiv2019

Landscape and regulation of m6A and m6Am methylome across human and mouse tissues

N6-methyladenosine (m6A), the most abundant internal mRNA modification, and N6,2-O-dimethyladenosine (m6Am), found at the first-transcribed nucleotide, are two examples of dynamic and reversible epitranscriptomic marks. However, the profiles and distribution patterns of m6A and m6Am across different human and mouse tissues are poorly characterized. Here we report the m6A and m6Am methylome through an extensive profiling of 42 human tissues and 16 mouse tissue samples. Globally, the m6A and m6Am peaks in non-brain tissues demonstrates mild tissue-specificity but are correlated in general, whereas the m6A and m6Am methylomes of brain tissues are clearly resolved from the non-brain tissues. Nevertheless, we identified a small subset of tissue-specific m6A peaks that can readily classify the tissue types. The number of m6A and m6Am peaks are partially correlated with the expression levels of their writers and erasers. In addition, the m6A- and m6Am-containing regions are enriched for single nucleotide polymorphisms. Furthermore, cross-species analysis of m6A and m6Am methylomes revealed that species, rather than tissue types, is the primary determinant of methylation. Collectively, our study provides an in-depth resource for dissecting the landscape and regulation of the m6A and m6Am epitranscriptomic marks across mammalian tissues.

molecular biology↗

bioRxiv2019

Inhibiting TG2 sensitize lung cancer to radiotherapy through interfering TOPOIIα-mediated DNA repair

Radiotherapy is an indispensable strategy for lung cancer, however, treatment failure or reoccurrence is often found in patients due to the developing radioresistance. Novel approaches are required for radiosensitizing to improve the therapeutic efficacy. In present study, we found that transglutaminase 2 (TG2) confers radioresistance in non-small cell lung cancer (NSCLC) cells through regulating TOPOII and promoting DNA repair. Our data showed that TG2 inhibitor or knockdown increased NSCLC radiosensitivity in vivo and in vitro. We found that TG2 translocated into nucleus and located to DSB sites, surprisingly, knockdown TG2 or glucosamine inhibited the phosphorylation of ATM, ATR and DNA-Pkcs. Through IP-MS assay and functional experiments, we identified that TOPOII as an downstream factor of TG2. Moreover, we found that TGase domain account for the interaction with TOPOII. Finally, we found that TG2 expression was correlated with poor survival in lung adenocarcinoma instead of squamous cell carcinoma. In conclusion, we demonstrated that inhibiting TG2 sensitize NSCLC to IR through interfere TOPOII mediated DNA repair, suggesting TG2 as a potential radiosensitizing target in NSCLC.

cancer biology↗

bioRxiv2019

MultiCapsNet: a interpretable deep learning classifier integrate data from multiple sources

Recent advances in experimental biology have generated huge amount of data. Due to differences present in detection targets and detection mechanisms, the produced data comes with different formats and lengths. There is an urgent call for computational methods to integrate these diverse data. Deep learning model is an ideal tool to cope with complex datasets, but its inherent black box nature needs more interpretability. Here, we present MultiCapsNet, a deep learning model built on CapsNet and scCapsNet. The MultiCapsNet model possesses the merits of both easier data integration and higher model interpretability. In the first example, we use the labeled variant call dataset, which is originally used to test the models for automating somatic variant refinement. We divide the 71 features listed in the dataset into eight groups according to data source and data property. Then, the data from those eight groups with different formats and lengths are integrated by our MultiCapsNet to predict the labels associated with each variant call. The performance of our MultiCapsNet matches the previous deep learning model well, given much less parameters than those needed by the previous model. After training, the MultiCapsNet model provides importance scores for each data source directly, while the previous deep learning model needs an extra importance determination step to do so. Despite that our MultiCapsNet model is substantially different from the previous deep learning model and the source importance measuring methods are also different, the importance score correlation between these two models is very high. In the second example, the prior knowledge, including information for protein-protein interactions and protein-DNA interactions, is used to determine the structure of MultiCapsNet model. The single cell RNA sequence data are decoupled into multiple parts according to the structure of MultiCapsNet model that has been integrated with prior knowledge, with each part represents genes influenced by a transcription factor or involved in a protein-protein interaction network and then could be viewed as a data source. The MultiCapsNet model could classify cells with high accuracy as well as reveal the contribution of each data source for cell type recognition. The high ranked contributors are often relevant to the contributed cell type.

bioinformatics↗

bioRxiv2019

Differential in vivo biodistribution of 131I-labeled exosomes from diverse cellular origins and its implication in the theranostic application.

Exosomes are critical mediators of intercellular crosstalk and regulator of cellular/tumor microenvironment. Exosomes have great prospects for clinical application as theranostic and prognostic probe. Nevertheless, the advancement of the exosomes research has been thwarted by limited knowledge elucidating the most efficient isolation method and their in vivo trafficking. Here we have showed that combination of two size-based methods using 0.20 {micro}m syringe filter and 100k centrifuge membrane filter followed by ultracentrifugation method yields a greater number of uniform exosomes. We also demonstrated the visual representation and quantification of differential in vivo distribution of radioisotope 131I-labelled exosomes from diverse cellular origins, e.g., tumor cells with or without treatments (HET0016 and GW2580), myeloid-derived suppressor cells and endothelial progenitor cells. We also determined that the distribution was dependent on the protein/cytokine contents of the exosomes. The applied in vivo imaging modalities can be utilized to monitor disease progression, metastasis, and exosome-based targeted therapy. Abbreviations

cancer biology↗

bioRxiv2019

Genomic analysis reveals a functional role for myocardial trabeculae in adults

Since being first described by Leonardo da Vinci in 1513 it has remained an enigma why the endocardial surfaces of the adult heart retain a complex network of muscular trabeculae - with their persistence thought to be a vestige of embryonic development. For causative physiological inference we harness population genomics, image-based intermediate phenotyping and in silico modelling to determine the effect of this complex cardiovascular trait on function. Using deep learning-based image analysis we identified genetic associations with trabecular complexity in 18,097 UK Biobank participants which were replicated in an independently measured cohort of 1,129 healthy adults. Genes in these associated regions are enriched for expression in the fetal heart or vasculature and implicate loci associated with haemodynamic phenotypes and developmental pathways. A causal relationship between increasing trabecular complexity and both ventricular performance and electrical activity are supported by complementary biomechanical simulations and Mendelian randomisation studies. These findings show that myocardial trabeculae are a previously-unrecognised determinant of cardiovascular physiology in adult humans.

genomics↗

bioRxiv2019

Geographic Patterns of Bacterioplankton among Lakes of the Middle and Lower Reaches of the Yangtze River Basin, China

In aquatic ecosystems, microbial biogeography research is critical for unveiling the mechanisms of microbial community succession. However, little is known about the microbial biogeography among interconnected lakes. To address this deficit, we used high-throughput sequencing to explore geographic patterns and the relative importance of ecological processes that shape these patterns in abundant and rare bacterial subcommunities from 25 lakes across the middle and lower reaches of Yangtze River basin (MLYB, located in southeast China), where most of the lakes are interconnected by river networks. We found that there were significant differences in both abundant and rare bacterial subcommunities between the two lake groups that were far from each other, while were no difference among the nearby lakes in each group. Both abundant and rare bacteria followed a strong distance-decay relationship, especially for rare bacteria. These findings suggest that although the interconnectivity between lakes breaks the geographical isolation of bacteria, the dispersal capability of bacterial taxa was still limited by geographic distance. We also found that although deterministic processes and stochastic processes together drive the bacterial subcommunities assembly, the stochastic processes (based on adjusted R2 in redundancy analysis) exhibited a greater influence on bacterial subcommunities. Our results implied that bacterial dispersal among interconnected lakes was more stochastically. ImportanceUnraveling the relative importance of ecological processes regulating microbial community structure is a central goal in microbial ecology. In aquatic ecosystems, microbial communities often occur in spatially structured habitats, where connectivity directly affects dispersal and metacommunity processes. Recent theoretical work suggests that directional dispersal among connected habitats leads to higher variability in local diversity and among-community composition. However, the study of microbial biogeography among natural interconnected habitats is still lacking. The findings of this study revealed interesting phenomena of microbial biogeography among natural interconnected habitats, suggested that the high interconnectivity reduced the spatial heterogeneity of bacteria, and caused the dispersal of bacteria to be more stochastically. This study has provided a deeper understanding of the biogeographic patterns of rare and abundant bacterial taxa and their determined processes among interconnected aquatic habitats.

microbiology↗

bioRxiv2018

scCapsNet: a deep learning classifier with the capability of interpretable feature extraction, applicable for single cell RNA data analysis

Recently deep learning methods have been applied to process biological data and greatly pushed the development of the biological research forward. However, the interpretability of the deep learning methods still needs to improve. Here for the first time, we present scCapsNet, a totally interpretable deep learning model adapted from CapsNet. The scCapsNet model retains the capsule parts of CapsNet but replaces the part of convolutional neural networks with several parallel fully connected neural networks. We apply scCapsNet to scRNA-seq data. The results show that scCapsNet performs well as a classifier and also that the parallel fully connected neural networks function like feature extractors as we supposed. The scCapsNet model provides contribution of each extracted feature to the cell type recognition. Evidences show that some extracted features are nearly orthogonal to each other. After training, through analysis of the internal weights of each neural network connected inputs and primary capsule, and with the information about the contribution of each extracted feature to the cell type recognition, the scCapsNet model could relate gene sets from inputs to cell types. The specific gene set is responsible for the identification of its corresponding cell types but does not affect the recognition of other cell types by the model. Many well-studied cell type markers are in the gene set with corresponding cell type. The internal weights of neural network for those well-studied cell type markers are different for different primary capsules. The internal weights of neural network connected to a primary capsule could be viewed as an embedding for genes, convert genes to real value low dimensional vectors. Furthermore, we mix the RNA expression data of two cells with different cell types and then use the scCapsNet model trained with non-mixed data to predict the cell types in the mixed data. Our scCapsNet model could predict cell types in a cell mixture with high accuracy.

bioinformatics↗

bioRxiv2018

Overdispersed gene expression characterizes schizophrenic brains

Schizophrenia (SCZ) is a severe, highly heterogeneous psychiatric disorder with varied clinical presentations. The polygenic genetic architecture of SCZ makes identification of causal variants daunting. Gene expression analyses have shown that SCZ may result in part from transcriptional dysregulation of a number of genes. However, most of these studies took the commonly used approach--differential gene expression analysis, assuming people with SCZ are a homogenous group, all with similar expression levels for any given gene. Here we show that the overall gene expression variability in SCZ is higher than that in an unaffected control (CTL) group. Specifically, we applied the test for equality of variances to the normalized expression data generated by the CommonMind Consortium (CMC) and identified 87 genes with significantly higher expression variances in the SCZ group than the CTL group. One of the genes with differential variability, VEGFA, encodes a vascular endothelial growth factor, supporting a vascular-ischemic etiology of SCZ. We also applied a Mahalanobis distance-based test for multivariate homogeneity of group dispersions to gene sets and identified 19 functional gene sets with higher expression variability in the SCZ group than the CTL group. Several of these gene sets are involved in brain development (e.g., development of cerebellar cortex, cerebellar Purkinje cell layer and neuromuscular junction), supporting that structural and functional changes in the cortex cause SCZ. Finally, using expression variability QTL (evQTL) analysis, we show that common genetic variants contribute to the increased expression variability in SCZ. Our results reveal that SCZ brains are characterized by overdispersed gene expression, resulting from dysregulated expression of functional gene sets pertaining to brain development, necrotic cell death, folic acid metabolism, and several other biological processes. Using SCZ as a model of complex genetic disorders with a heterogeneous etiology, our study provides a new conceptual framework for variability-centric analyses. Such a framework is likely to be important in the era of personalized medicine. (313 words)

genetics↗

bioRxiv2018

5-Hydroxymethylcytosines from Circulating Cell-free DNA as Diagnostic and Prognostic Markers for Hepatocellular Carcinoma

The lack of highly sensitive and specific diagnostic biomarkers is a major contributor to the poor outcomes of patients with hepatocellular carcinoma (HCC), the second-most common cause of cancer deaths worldwide. We sought to develop a clinically convenient and minimally-invasive approach that can be deployed at scale for the sensitive, specific, and highly reliable diagnosis of HCC, and to evaluate the potential prognostic value of this approach. The study cohort comprised of 2,728 subjects, including HCC patients (n = 1,208), controls (n = 965) (572 healthy individuals and 393 patients with benign lesions), as well as patients with chronic hepatitis B infection (CHB) (n =291), liver cirrhosis (LC) (n = 110), and cholangiocarcinoma (CCC) (n = 154), was recruited from three major liver cancer hospitals in Shanghai, China, from July 2016 to November 2017. Circulating cell-free DNA (cfDNA) were collected from plasma samples from these individuals before surgery or any radical treatment. Applying our 5hmC-Seal technique, the summarized 5-hydroxymethylcytosine (5hmC) profiles in cfDNA were obtained. Molecular annotation analysis suggested that the profiled 5hmC loci in cfDNA were enriched with liver tissue-derived regulatory markers (e.g., H3K4me1). We showed that a weighted diagnostic score (wd-score) based on 117 genes detected using the summarized 5hmC profiles in cfDNA accurately distinguished HCC patients from controls (AUC = 95.1%; 95% CI, 93.6-96.5%) in the validation set, markedly outperformed -fetoprotein (AFP) with superior sensitivity. The wd-scores, which not only detected early BCLC stages (e.g., Stage 0: AUC = 96.2%; 95% CI,94.1-98.4%) and small tumors (e.g., < 2 cm: AUC = 95.7%; 95% CI: 93.6-97.7%), also showed high capacity for distinguishing HCC from non-cancer patients with CHB/LC (AUC = 80.2%; 95% CI, 75.8-84.6%). Moreover, the prognostic value of 5hmC markers in cfDNA was evaluated for HCC recurrence, showing that a weighted prognostic score (wp-score) based on 16 marker genes predicted the recurrence risk (HR = 6.67; 95% CI, 2.81-15.82, p < 0.0001) in 555 patients who have been followed up after surgery. In conclusion, we have developed and validated a robust 5hmC-based diagnostic model that can be applied routinely with clinically feasible amount of cfDNA (e.g., from ~2-5 mL of plasma). Applying this new approach in the clinic could significantly improve the clinical outcomes of HCC patients, for example by early detection of those patients with surgically resectable tumors or as a convenient disease surveillance tool for recurrence.

cancer biology↗

bioRxiv2018

Genome-wide Expression Profiling and Pathway Analysis in Cyclic Stretched Human Trabecular Meshwork Cells

PurposeRegulation of intraocular pressure is dependent upon homeostatic responses of trabecular meshwork (TM) cells to mechanical stretch. Despite the important roles of miRNAs in regulating TM function and aqueous outflow, it remains unclear how miRNA and their target genes interact in response to physiological cyclic mechanical stretch. We aimed to identify differentially expressed miRNAs and their potential targets in human TM cells in response to cyclic mechanical stress.\n\nMethodsMonolayers of TM cells from non-glaucomatous donors (n=3-6) were cultured in the presence or absence of 15% mechanical stretch, 1 cycle/s, for 6 or 24-hours using computer-controlled Flexcell Unit. We profiled the expression of 800 miRNAs using NanoString Human miRNA assays and identified differentially expressed miRNAs using the Bioconductor Limma package. We identified differentially expressed genes using Operon Human Oligo Arrays with GeneSpring software. Pathway analysis with WebGestalt identified stretch-related pathways. We used Integrative miRNA Target Finder from Ingenuity Pathway Analysis to identify potential miRNA-mRNA regulations.\n\nResultsWe identified 540 unique genes and 74 miRNAs with differential expression in TM cells upon cyclic mechanical stretch. Pathway analysis indicated the significant enrichment of genes involved in Wnt-signaling, receptor protein serine/threonine kinase signaling, TGF-{beta} pathway, and response to unfolded protein. We also identified several miRNA master regulators, including miR-19b-3p and miR-93-5p, which may act as switches to control several mechano-responsive genes.\n\nConclusionsThis study suggests that cyclic mechanical stress of TM cells triggers alterations in the expression of both mRNAs and miRNAs implicated in glaucoma-associated pathways.

genomics↗

bioRxiv2018

Sequencing of Panax notoginseng genome reveals genes involved in disease resistance and ginsenoside biosynthesis

Panax notoginseng is a traditional Chinese herb with high medicinal and economic value. There has been considerable research on the pharmacological activities of ginsenosides contained in Panax spp.; however, very little is known about the ginsenoside biosynthetic pathway. We reported the first de novo genome of 2.36 Gb of sequences from P. notoginseng with 35,451 protein-encoding genes. Compared to other plants, we found notable gene family contraction of disease-resistance genes in P. notoginseng, but notable expansion for several ATP-binding cassette (ABC) transporter subfamilies, such as the Gpdr subfamily, indicating that ABCs might be an additional mechanism for the plant to cope with biotic stress. Combining eight transcriptomes of roots and aerial parts, we identified several key genes, their transcription factor binding sites and all their family members involved in the synthesis pathway of ginsenosides in P. notoginseng, including dammarenediol synthase, CYP716 and UGT71. The complete genome analysis of P. notoginseng, the first in genus Panax, will serve as an important reference sequence for improving breeding and cultivation of this important nutraceutical and medicinal but vulnerable plant species.

genomics↗

bioRxiv2017

Single Molecule Sequencing of Cell-free DNA from Maternal Plasma for Noninvasive Trisomy Detection

The demand of non-invasive prenatal testing for autosomal aneuploidy using cell-free fetal DNA (cffDNA) in maternal plasma is a highly sought-after diagnostic, with a rapidly growing market. Current approaches developed by next generation sequencing (NGS) need PCR amplifcation during sample preparation, which results in amplification bias in GC-rich areas of the human genome. With these approaches, the minimum fetal fraction in maternal plasma is 4% for the small differences in circulating cfDNA between trisomic and disomic pregnancies to be detectable. In this paper, we performed single molecule sequencing of cell-free DNA from maternal plasma for noninvasive trisomy 13, 18 and 21 detections using the GenoCare platform. We found that single molecule sequencing is sensitive enough to detect these chromosome abnormalities when the fetal DNA fraction is as low as 2%. Compared to the Hiseq2500 platform, no significant GC bias was observed. The improved sensitivity and unbiased GC readout make GenoCare a promising platform for autosomal aneuploidy detections, even in the very early stage of pregnancy.

genomics↗

bioRxiv2017

Genetic load and mutational meltdown in cancer cell populations

ABSRACTLarge and non-recombining genomes are prone to accumulating deleterious mutations faster than natural selection can purge (Mullers ratchet). A possible consequence would then be the extinction of small populations. Relative to most single-cell organisms, cancer cells, with large and non-recombining genomes, could be particularly susceptible to such \"mutational meltdown\". Curiously, deleterious mutations in cancer cells are rarely noticed despite the strong signals in cancer genome sequences. Here, by monitoring single-cell clones from HeLa cell lines, we characterize deleterious mutations that retard cell proliferation. The main mutational events are copy number variations (CNVs), which happen at an extraordinarily high rate of 0.29 events per cell division. The average fitness reduction, estimated to be 18% per mutation, is also very high. HeLa cell populations therefore have very substantial genetic load and, at this level, natural population would likely experience mutational meltdown. We suspect that HeLa cell populations may avoid extinction only after the population size becomes large. Because CNVs are common in most cell lines and cancer tissues, the observations hint at cancer cells vulnerability, which could be exploited by therapeutic strategies.

evolutionary biology↗

bioRxiv2017

Resequencing the Escherichia coli genome by GenoCare single molecule sequencing platform

Next generation sequencing (NGS) has revolutionized life sciences research. Recently, a new class of third-generation sequencing platforms has arrived to meet increasing demands in the clinic, capable of directly measuring DNA and RNA sequences at the single-molecule level without amplification. Here, we use the new GenoCare single molecule sequencing platform from Direct Genomics to resequence the E. coli genome and show comparable performance to the Illumina MiSeq system. Our platform detects single-molecule fluorescence by total internal reflection microscopy, with sequencing-by-synthesis chemistry. With a consensus sequence of 99.71% nucleotide identity to that of the Illumina MiSeq systems, GenoCare was determined to be a reliable platform for single-molecule sequencing, with strong potential for clinical applications.

genomics↗