Biology subjects

Chen, D.

Publications and source records attributed to Chen, D..

421 records · Page 24Linked to original sources

bioRxiv2018

The landscape and diagnostic potential of T and B cell repertoire in Immunoglobulin A Nephropathy

Immunoglobulin A Nephropathy (IgAN) is the most common glomerulonephritis worldwide. In IgAN, immune complex deposite in glomerular mesangium, which induce inflammation and affect the kidneys normal functions. However, the exact pathogenesis of IgAN is still incompletely understood. Further, in current practice the clinical diagnosis relies on needle biopsy on renal tissue. Therefore, a non-invasive method for clinical diagnosis and prognosis surveillance of the disease is in high demand. In this paper, we investigated both the T cell receptor bata chain (TCRB) and immunoglobulin heavy chain (IGH) repertoire of kidney infiltrating and circulating lymphocytes of IgAN patients by immune repertoire high throughput sequencing. We found that the features of TCRB and IGH in the renal tissues were remarkably different from that in blood, including a decreased repertoire diversity and increased IgA and IgG frequency, and more activated B cells. The CDR3 length of PBMC TCRB and IGH in patients is significantly shorter than that in healthy controls, which is the result of both VDJ rearrangement and clone selection. We also found that the IgA1 frequency in the PBMC of IgAN is significant higher than that in other Nephropathy (NIgAN) and healthy control, which is consistent with the previous reports on the level of IgA1 producing B cells and serum IgA1. Significantly, we identified a set of IgAN disease related TCRB and IGH CDR3s, which can be used to distinguish IgAN from NIgAN and healthy controls from the blood with high accuracy. These results indicated that TCRB and IGH repertoire can potentially serve as non-invasive biomarkers for IgAN diagnosis. The characteristics of kidney infiltrating and circulating lymphocytes repertoire shed light on IgAN detection, treatment and surveillance.

immunology↗

bioRxiv2018

RaftProt V2: understanding membrane microdomain function through lipid raft proteomes

Cellular membranes feature dynamic submicrometer-scale lateral membrane domainsvariously referred to as lipid rafts, membrane rafts or glycosphingolipid-enriched microdomains (GEM). In order to understand the molecular functions of lipid rafts, numerous studies have utilized various biochemical methods to isolate and examine the protein composition of membrane rafts. However, interpretation of individual raft proteomics studies are confounded by the limitations of isolation methods and the dynamic nature of rafts. Knowledge-based approaches can facilitate biological data interpretation by integrating experimental evidence from existing studies. To this end, we previously developed RaftProt (http://lipid-raft-database.di.uq.edu.au/), a searchable database of mammalian lipid raft-associated proteins. Despite being a valuable and highly used resource, improvements in search capabilities and visualisation were still needed. Here, we present RaftProt V2 (http://raftprot.org), an improved update of RaftProt, enabling interrogation and integration of datasets at the cell/tissue type and UniRef/Gene level. Besides the addition of new datasets and re-mapping of all entries to both UniProt and UniRef IDs, we have annotated the level of experimental evidence for each protein entry. The search engine now allows for multiple protein or experiment searches where correlations, interactions or overlaps can be investigated. The web-interface has been completely re-designed and offers new interactive tools for data and subset selection, correlation analysis and network visualization. Overall, RaftProt aims to advance our understanding of lipid raft function by revealing the proteomes and pathways that are associated with membrane microdomains in diverse tissue and conditions.\n\nDatabase URL: http://raftprot.org

bioinformatics↗

bioRxiv2017

Differentiation of primate primordial germ cell-like cells following transplantation into the adult gonadal niche

A major challenge in stem cell differentiation validation is the availability of bioassays to prove cell types generated in vitro are equivalent to cells in vivo. In the mouse model, differentiation of primordial germ cell-like cells (PGCLCs) from pluripotent cells was validated by transplantation, leading to the generation of spermatogenesis and to the birth of offspring. Here we report the use of xenotransplantation (monkey to mouse) and homologous transplantation (monkey to monkey) to validate our in vitro protocol for differentiating male rhesus macaque PGCLCs (rPGCLCs) from rhesus macaque induced pluripotent stem cells (riPSCs). Specifically, transplantation of aggregates containing rPGCLCs into mouse and nonhuman primate testicles overcomes a major bottleneck in rPGCLC differentiation with the expression of VASA and MAGEA4, but not ENO2. These findings suggest that immature rPGCLCs once transplanted into an adult gonadal niche commit to differentiate towards late PGCs and spermatogonia-like cells but do not complete the conversion into ENO2-positive spermatogonia.

developmental biology↗

bioRxiv2017

Predicting Transcription Factor Binding Sites with Convolutional Kernel Networks

The growing number of annotated biological sequences available makes it possible to learn genotype-phenotype relationships from data with increasingly high accuracy. When large quantities of labeled samples are available for training a model, convolutional neural networks can be used to predict the phenotype of unannotated sequences with good accuracy. Unfortunately, their performance with medium- or small-scale datasets is mitigated, which requires inventing new data-efficient approaches. In this paper, we introduce a hybrid approach between convolutional neural networks and kernel methods to model biological sequences. Our method enjoys the ability of convolutional neural networks to learn data representations that are adapted to a specific task, while the kernel point of view yields algorithms that perform significantly better when the amount of training data is small. We illustrate these advantages for transcription factor binding prediction and protein homology detection, and we demonstrate that our model is also simple to interpret, which is crucial for discovering predictive motifs in sequences. The source code is freely available at https://gitlab.inria.fr/dchen/CKN-seq.

bioinformatics↗

bioRxiv2017

Down-regulation of LRIG1 by miR-20a modulates gastric cancer multidrug resistance

Multidrug resistance (MDR) significantly restricts the clinical efficacy of gastric cancer (GC) chemotherapy, and it is critical to search novel targets to predict and overcome MDR. Leucine-rich repeats and immunoglobulin-like domains 1 (LRIG1) has been proved to be correlated with drug resistance in several cancers. The present study revealed that LRIG1 was overexpressed in chemo-sensitive GC tissues and decreased expression of LRIG1 predicted poor survival in GC patients. We observed that up-regulation of LRIG1 enhanced chemo-sensitivity in GC cells. Interestingly, miR-20a, which was overexpressed in GC MDR cell lines and tissues, was identified to regulate LRIG1 expression by directly targeting its 3'untranslated region. We also found that inhibition of miR-20a suppressed GC MDR, and up-regulation showed opposite effects. Moreover, we demonstrated that the miR-20a/LRIG1 axis regulated GC cell MDR through EGFR mediated PI3K/AKT and MAPK/ERK signaling pathways. Finally, LRIG1 expression in human GC tissues is inversely correlated with miR-20a and EGFR. Taken together, the newly identified miR-20a/LRIG1/EGFR link provides insight into the MDR process of GC, and targeting this axis represents a novel potential therapeutic strategy to block GC chemo-resistance.

cancer biology↗

bioRxiv2017

N6-Methyladenine DNA Modification in Human Genome

DNA N6-methyladenine (6mA) modification is the most prevalent DNA modification in prokaryotes, but whether it exists in human cells and whether it plays a role in human diseases remain enigmatic. Here, we showed that 6mA is extensively present in human genome, and we cataloged 881,240 6mA sites accounting for [~]0.051% of the total adenines. [G/C]AGG[C/T] was the most significantly associated motif with 6mA modification. 6mA sites were enriched in the coding regions and mark actively transcribed genes in human cells. We further found that DNA N6-methyladenine and N6-demethyladenine modification in human genome were mediated by methyltransferase N6AMT1 and demethylase ALKBH1, respectively. The abundance of 6mA was significantly lower in cancers, accompaning with decreased N6AMT1 and increased ALKBH1 levels, and down-regulation of 6mA modification levels promoted tumorigenesis. Collectively, our results demonstrate that DNA 6mA modification is extensively present in human cells and the decrease of genomic DNA 6mA promotes human tumorigenesis.

genomics↗

bioRxiv2017

Endogenous synthesis of pyrethrins by cannabis

Pyrethrins are a class of natural terpenoid pesticides produced by Tanacetum cinerariifolium, commonly known as chrysanthemum. Here we present evidence that cannabis may be able to produce pyrethrins endogenously. Flower from a cannabis plant grown in a closed hydroponic environment contained 2.48 parts per million pyrethrin I by weight. A comparison of the genetics of T. cinerariifolium and Cannabis demonstrates Cannabis homologues of the genes that contribute to pyrethrins production in T. cinerariifolium. This provides a plausible pathway for the biosynthesis of pyrethrins in cannabis. Although preliminary, these data indicate a potentially significant confounding variable in both cannabis research and regulations on allowable pyrethrins residues in cannabis products.

plant biology↗