dagLogo: An R/Bioconductor package for identifying and visualizing differential amino acid group usage in proteomics data

Sequence logos have been widely used as graphical representations of conserved nucleic acid and protein motifs. Due to the complexity of the amino acid (AA) alphabet, rich post-translational modification, and diverse subcellular localization of proteins, few versatile tools are available for effective identification and visualization of protein motifs. In addition, various reduced AA alphabets based on physicochemical, structural, or functional properties have been valuable in the study of protein alignment, folding, structure prediction, and evolution. However, there is lack of tools for applying reduced AA alphabets to the identification and visualization of statistically significant motifs. To fill this gap, we developed an R/Bioconductor package dagLogo, which has several advantages over existing tools. First, dagLogo allows various formats for input sets and provides comprehensive options to build optimal background models. It implements different reduced AA alphabets to group AAs of similar properties. Furthermore, dagLogo provides statistical and visual solutions for differential AA (or AA group) usage analysis of both large and small data sets. Case studies showed that dagLogo can better identify and visualize conserved protein sequence patterns from different types of inputs and can potentially reveal the biological patterns that could be missed by other logo generators

An Orthogonal Proteomic Screen of Zika virus Reveals Specific Targeting of Neuronal Differentiation Factors

Zika virus (ZIKV) has recently emerged as a global health concern owing to its widespread diffusion and its association with severe neurological symptoms and microcephaly in newborns1. However, the molecular mechanisms that are responsible for the pathogenicity of ZIKV remain largely unknown. Here we use human neural progenitor cells and the neuronal cell line SK-N-BE2 in an integrated proteomics approach to characterize the cellular responses to viral infection at the proteome and phosphoproteome level, and use affinity proteomics to identify cellular targets of ZIKV proteins. Using this approach, we identify 386 ZIKV-interacting proteins, ZIKV-specific and pan-flaviviral activities as well as host factors with known functions in neuronal development, retinal defects and infertility. Moreover, our analysis identified 1,216 phosphorylation sites that are specifically up- or downregulated after ZIKV infection, indicating profound modulation of fundamental signalling pathways such as AKT, MAPK-ERK and ATM-ATR and thereby providing mechanistic insights into the proliferation arrest elicited by ZIKV infection. Functionally, our integrative study identifies ZIKV host-dependency factors and provides a comprehensive framework for a system-level understanding of ZIKV-induced perturbations at the levels of proteins and cellular pathways

Characterization of host proteins interacting with the lymphocytic choriomeningitis virus L protein

RNA-dependent RNA polymerases (RdRps) play a key role in the life cycle of RNA viruses and impact their immunobiology. The arenavirus lymphocytic choriomeningitis virus (LCMV) strain Clone 13 provides a benchmark model for studying chronic infection. A major genetic determinant for its ability to persist maps to a single amino acid exchange in the viral L protein, which exhibits RdRp activity, yet its functional consequences remain elusive. To unravel the L protein interactions with the host proteome, we engineered infectious L protein-tagged LCMV virions by reverse genetics. A subsequent mass-spectrometric analysis of L protein pulldowns from infected human cells revealed a comprehensive network of interacting host proteins. The obtained LCMV L protein interactome was bioinformatically integrated with known host protein interactors of RdRps from other RNA viruses, emphasizing interconnected modules of human proteins. Functional characterization of selected interactors highlighted proviral (DDX3X) as well as antiviral (NKRF, TRIM21) host factors. To corroborate these findings, we infected Trim21-/-mice with LCMV and found impaired virus control in chronic infection. These results provide insights into the complex interactions of the arenavirus LCMV and other viral RdRps with the host proteome and contribute to a better molecular understanding of how chronic viruses interact with their host

Bitter taste signaling in tracheal epithelial brush cells elicits innate immune responses to bacterial infection

Constant exposure of the airways to inhaled pathogens requires efficient early immune responses protecting against infections. How bacteria on the epithelial surface are detected and first-line protective mechanisms are initiated are not well understood. We have recently shown that tracheal brush cells (BCs) express functional taste receptors. Here we report that bitter taste signaling in murine BCs induces neurogenic inflammation. We demonstrate that BC signaling stimulates adjacent sensory nerve endings in the trachea to release the neuropeptides CGRP and substance P that mediate plasma extravasation, neutrophil recruitment, and diapedesis. Moreover, we show that bitter tasting quorum-sensing molecules from Pseudomonas aeruginosa activate tracheal BCs. BC signaling depends on the key taste transduction gene Trpm5, triggers secretion of immune mediators, among them the most abundant member of the complement system, and is needed to combat P. aeruginosa infections. Our data provide functional insight into firstline defense mechanisms against bacterial infections of the lung

Bitter taste signaling in tracheal epithelial brush cells elicits innate immune responses to bacterial infection.

peer reviewedConstant exposure of the airways to inhaled pathogens requires efficient early immune responses protecting against infections. How bacteria on the epithelial surface are detected and first-line protective mechanisms are initiated are not well understood. We have recently shown that tracheal brush cells (BCs) express functional taste receptors. Here we report that bitter taste signaling in murine BCs induces neurogenic inflammation. We demonstrate that BC signaling stimulates adjacent sensory nerve endings in the trachea to release the neuropeptides CGRP and substance P that mediate plasma extravasation, neutrophil recruitment, and diapedesis. Moreover, we show that bitter tasting quorum-sensing molecules from Pseudomonas aeruginosa activate tracheal BCs. BC signaling depends on the key taste transduction gene Trpm5, triggers secretion of immune mediators, among them the most abundant member of the complement system, and is needed to combat P. aeruginosa infections. Our data provide functional insight into first-line defense mechanisms against bacterial infections of the lung

Deconvolution of Targeted Protein–Protein Interaction Maps

Current proteomic techniques allow researchers to analyze chosen biological pathways or an ensemble of related protein complexes at a global level via the measure of physical protein–protein interactions by affinity purification mass spectrometry (AP-MS). Such experiments yield information-rich but complex interaction maps whose unbiased interpretation is challenging. Guided by current knowledge on the modular structure of protein complexes, we propose a novel statistical approach, named BI-MAP, complemented by software tools and a visual grammar to present the inferred modules. We show that the BI-MAP tools can be applied from small and very detailed maps to large, sparse, and much noisier data sets. The BI-MAP tool implementation and test data are made freely available

Deconvolution of Targeted Protein–Protein Interaction Maps

Current proteomic techniques allow researchers to analyze chosen biological pathways or an ensemble of related protein complexes at a global level via the measure of physical protein–protein interactions by affinity purification mass spectrometry (AP-MS). Such experiments yield information-rich but complex interaction maps whose unbiased interpretation is challenging. Guided by current knowledge on the modular structure of protein complexes, we propose a novel statistical approach, named BI-MAP, complemented by software tools and a visual grammar to present the inferred modules. We show that the BI-MAP tools can be applied from small and very detailed maps to large, sparse, and much noisier data sets. The BI-MAP tool implementation and test data are made freely available

Deconvolution of Targeted Protein–Protein Interaction Maps

Current proteomic techniques allow researchers to analyze chosen biological pathways or an ensemble of related protein complexes at a global level via the measure of physical protein–protein interactions by affinity purification mass spectrometry (AP-MS). Such experiments yield information-rich but complex interaction maps whose unbiased interpretation is challenging. Guided by current knowledge on the modular structure of protein complexes, we propose a novel statistical approach, named BI-MAP, complemented by software tools and a visual grammar to present the inferred modules. We show that the BI-MAP tools can be applied from small and very detailed maps to large, sparse, and much noisier data sets. The BI-MAP tool implementation and test data are made freely available

Enhancing cognate target elution efficiency in gel-free chemical proteomics

Gel-free liquid chromatography mass spectrometry coupled to chemical proteomics is a powerful approach for characterizing cellular target profiles of small molecules. We have previously described a fast and efficient elution protocol; however, altered target profiles were observed. We hypothesised that elution conditions critically impact the effectiveness of disrupting drug-protein interactions. Thus, a number of elution conditions were systematically assessed with the aim of improving the recovery of all classes of proteins whilst maintaining compatibility with immunoblotting procedures. A double elution with formic acid combined with urea emerged as the most efficient and generically applicable elution method for chemical proteomics Keywords: Chemical proteomics, Mass spectrometry gel-free, Double elution, Dasatinib, Sunitini