DBLiPro: A Database for Lipids and Proteins in Human Lipid Metabolism.

To help researchers in the field of biology, medicine, chemistry, and materials science to use lipidomic data conveniently, there is an urgent need to develop a platform that provides a systematic knowledgebase of human lipid metabolism and lipidome-centric omics analysis tools. DBLiPro is a user-friendly webserver allowing for access to human metabolism-related lipids and proteins knowledge database and an interactive bioinformatics integrative analysis workflow for lipidomics, transcriptomics, and proteomics data. In DBLiPro, there are 3109 lipid-associated proteins (LAPs) and 2098 lipid metabolites in the knowledge base section, which were obtained from Uniprot, Kyoto Encyclopedia of Genes and Genomes (KEGG) and were further annotated by information from other public resources in the knowledge base section, such as RaftProt and PubChem. DBLiPro offers a step-by-step interactive analysis workflow for lipidomics, transcriptomics, proteomics, and their integrating multi-omics analysis focusing on the human lipid metabolism. In summary, DBLiPro is capable of helping users discover key molecules (lipids and proteins) in human lipid metabolism and investigate lipid-protein functions underlying mechanisms based on their own omics data. The DBLiPro is freely available at http://lipid.cloudna.cn/home.

Quantitative proteomics reveals ER-α involvement in CD146-induced epithelial-mesenchymal transition in breast cancer cells.

The cell adhesion molecule CD146 is a novel inducer of epithelial-mesenchymal transition (EMT), which was associated with triple-negative breast cancer (TNBC). To gain insights into the complex networks that mediate CD146-induced EMT in breast cancers, we conducted a triple Stable Isotope Labeling with Amino Acids in Cell Culture (SILAC), to analyze whole cell protein profiles of MCF-7 cells that had undergone gradual EMT upon CD146 expression from moderate to high levels. In this study, we identified 2293 proteins in total, of which 103 exhibited changes in protein abundance that correlated with CD146 expression levels, revealing extensive morphological and biochemical changes associated with EMT. Ingenuity Pathway Analysis (IPA) showed that estrogen receptor (ER) was the most significantly inhibited transcription regulator during CD146-induced EMT. Functional assays further revealed that ER-α expression was repressed in cells undergoing CD146-induced EMT, whereas re-expression of ER-α abolished their migratory and invasive behavior. Lastly, we found that ER-α mediated its effects on CD146-induced EMT via repression of the key EMT transcriptional factor Slug. Our study revealed the molecular details of the complex signaling networks during CD146-induced EMT, and provided important clues for future exploration of the mechanisms underlying the association between CD146 and TNBC as observed in the clinic. BIOLOGICAL SIGNIFICANCE: This study used a proteomics screen to reveal molecular changes mediated by CD146-induced epithelial-mesenchymal transition (EMT) in breast cancer cells. Estrogen receptor (ER) was found to be the most significantly inhibited transcription regulator, which mediated its effects on CD146-induced EMT via repression of the transcriptional factor Slug. Elucidation of protein interaction networks and signal networks generated from 103 significantly changed proteins would facilitate future investigation into the mechanisms underlying CD146 induced-EMT in breast cancers.

CAPER 2.0: an interactive, configurable, and extensible workflow-based platform to analyze data sets from the Chromosome-centric Human Proteome Project.

The Chromosome-centric Human Proteome Project (C-HPP) aims to map and annotate the entire human proteome by the "chromosome-by-chromosome" strategy. As the C-HPP proceeds, the increasing volume of proteomic data sets presents a challenge for customized and reproducible bioinformatics data analyses for mining biological knowledge. To address this challenge, we updated the previous static proteome browser CAPER into a higher version, CAPER 2.0 - an interactive, configurable and extensible workflow-based platform for C-HPP data analyses. In addition to the previous visualization functions of track-view and heatmap-view, CAPER 2.0 presents a powerful toolbox for C-HPP data analyses and also integrates a configurable workflow system that supports the view, construction, edit, run, and share of workflows. These features allow users to easily conduct their own C-HPP proteomic data analyses and visualization by CAPER 2.0. We illustrate the usage of CAPER 2.0 with four specific workflows for finding missing proteins, mapping peptides to chromosomes for genome annotation, integrating peptides with transcription factor binding sites from ENCODE data sets, and functionally annotating proteins. The updated CAPER is available at http://www.bprc.ac.cn/CAPE.