Qing‐Yu He

Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.

UNLABELLED: ChIPseeker is an R package for annotating ChIP-seq data analysis. It supports annotating ChIP peaks and provides functions to visualize ChIP peaks coverage over chromosomes and profiles of peaks binding to TSS regions. Comparison of ChIP peak profiles and annotation are also supported. Moreover, it supports evaluating significant overlap among ChIP-seq datasets. Currently, ChIPseeker contains 15 000 bed file information from GEO database. These datasets can be downloaded and compare with user's own data to explore significant overlap datasets for inferring co-regulation or transcription factor complex for further investigation. AVAILABILITY AND IMPLEMENTATION: ChIPseeker is released under Artistic-2.0 License. The source code and documents are freely available through Bioconductor (http://www.bioconductor.org/packages/release/bioc/html/ChIPseeker.html).

Reactome is a manually curated pathway annotation database for unveiling high-order biological pathways from high-throughput data. ReactomePA is an R/Bioconductor package providing enrichment analyses, including hypergeometric test and gene set enrichment analyses. A functional analysis can be applied to the genomic coordination obtained from a sequencing experiment to analyze the functional significance of genomic loci including cis-regulatory elements and non-coding regions. Comparison among different experiments is also supported. Moreover, ReactomePA provides several visualization functions to produce highly customizable, publication-quality figures. The source code and documents of ReactomePA are freely available through Bioconductor (http://www.bioconductor.org/packages/ReactomePA).

Silver nanoparticles (nano-Ag) are potent and broad-spectrum antimicrobial agents. In this study, spherical nano-Ag (average diameter = 9.3 nm) particles were synthesized using a borohydride reduction method and the mode of their antibacterial action against E. coli was investigated by proteomic approaches (2-DE and MS identification), conducted in parallel to analyses involving solutions of Ag(+) ions. The proteomic data revealed that a short exposure of E. coli cells to antibacterial concentrations of nano-Ag resulted in an accumulation of envelope protein precursors, indicative of the dissipation of proton motive force. Consistent with these proteomic findings, nano-Ag were shown to destabilize the outer membrane, collapse the plasma membrane potential and deplete the levels of intracellular ATP. The mode of action of nano-Ag was also found to be similar to that of Ag(+) ions (e.g., Dibrov, P. et al, Antimicrob. Agents Chemother. 2002, 46, 2668-2670); however, the effective concentrations of nano-Ag and Ag(+) ions were at nanomolar and micromolar levels, respectively. Nano-Ag appear to be an efficient physicochemical system conferring antimicrobial silver activities.