An Evolutionary Conserved Role for Anaplastic Lymphoma Kinase in Behavioral Responses to Ethanol

Anaplastic lymphoma kinase (Alk) is a gene expressed in the nervous system that encodes a receptor tyrosine kinase commonly known for its oncogenic function in various human cancers. We have determined that Alk is associated with altered behavioral responses to ethanol in the fruit fly Drosophila melanogaster, in mice, and in humans. Mutant flies containing transposon insertions in dAlk demonstrate increased resistance to the sedating effect of ethanol. Database analyses revealed that Alk expression levels in the brains of recombinant inbred mice are negatively correlated with ethanol-induced ataxia and ethanol consumption. We therefore tested Alk gene knockout mice and found that they sedate longer in response to high doses of ethanol and consume more ethanol than wild-type mice. Finally, sequencing of human ALK led to the discovery of four polymorphisms associated with a low level of response to ethanol, an intermediate phenotype that is predictive of future alcohol use disorders (AUDs). These results suggest that Alk plays an evolutionary conserved role in ethanol-related behaviors. Moreover, ALK may be a novel candidate gene conferring risk for AUDs as well as a potential target for pharmacological intervention

Silencing of Renal DNaseI in Murine Lupus Nephritis Imposes Exposure of Large Chromatin Fragments and Activation of Toll Like Receptors and the Clec4e

Recent studies demonstrate that transformation of mild lupus nephritis into end-stage disease is imposed by silencing of renal DNaseI gene expression in (NZBxNZW)F1 mice. Down-regulation of DNaseI results in reduced chromatin fragmentation, and in deposition of extracellular chromatin-IgG complexes in glomerular basement membranes in individuals that produce IgG anti-chromatin antibodies. The main focus of the present study is to describe the biological consequences of renal DNaseI shut-down and reduced chromatin fragmentation with a particular focus on whether exposed large chromatin fragments activate Toll like receptors and the necrosis-related Clec4e receptor in murine and human lupus nephritis. Furthermore, analyses where performed to determine if matrix metalloproteases are up-regulated as a consequence of chromatin-mediated Toll like receptors/Clec4e stimulation. Mouse and human mRNA expression levels of DNaseI, Toll like receptors 7–9, Clec4e, pro-inflammatory cytokines and MMP2/MMP9 were determined and compared with in situ protein expression profiles and clinical data. We demonstrate that exposure of chromatin significantly up-regulate Toll like receptors and Clec4e in mice, and also but less pronounced in patients with lupus nephritis treated with immunosuppresants. In conclusion, silencing of renal DNaseI gene expression initiates a cascade of inflammatory signals leading to progression of both murine and human lupus nephritis. Principal component analyses biplot of data from murine and human lupus nephrits demonstrate the importance of DNaseI gene shut down for progression of the organ disease

Role of Matrix Metalloproteinases and Therapeutic Benefits of Their Inhibition in Spinal Cord Injury

This review will focus on matrix metalloproteinases (MMPs) and their inhibitors in the context of spinal cord injury (SCI). MMPs have a specific cellular and temporal pattern of expression in the injured spinal cord. Here we consider their diverse functions in the acutely injured cord and during wound healing. Excessive activity of MMPs, and in particular gelatinase B (MMP-9), in the acutely injured cord contributes to disruption of the blood-spinal cord barrier, and the influx of leukocytes into the injured cord, as well as apoptosis. MMP-9 and MMP-2 regulate inflammation and neuropathic pain after peripheral nerve injury and may contribute to SCI-induced pain. Early pharmacologic inhibition of MMPs or the gelatinases (MMP-2 and MMP-9) results in an improvement in long-term neurological recovery and is associated with reduced glial scarring and neuropathic pain. During wound healing, gelatinase A (MMP-2) plays a critical role in limiting the formation of an inhibitory glial scar, and mice that are genetically deficient in this protease showed impaired recovery. Together, these findings illustrate complex, temporally distinct roles of MMPs in SCIs. As early gelatinase activity is detrimental, there is an emerging interest in developing gelatinase-targeted therapeutics that would be specifically tailored to the acute injured spinal cord. Thus, we focus this review on the development of selective gelatinase inhibitors

Improving network inference algorithms using resampling methods

Abstract Background Relatively small changes to gene expression data dramatically affect co-expression networks inferred from that data which, in turn, can significantly alter the subsequent biological interpretation. This error propagation is an underappreciated problem that, while hinted at in the literature, has not yet been thoroughly explored. Resampling methods (e.g. bootstrap aggregation, random subspace method) are hypothesized to alleviate variability in network inference methods by minimizing outlier effects and distilling persistent associations in the data. But the efficacy of the approach assumes the generalization from statistical theory holds true in biological network inference applications. Results We evaluated the effect of bootstrap aggregation on inferred networks using commonly applied network inference methods in terms of stability, or resilience to perturbations in the underlying expression data, a metric for accuracy, and functional enrichment of edge interactions. Conclusion Bootstrap aggregation results in improved stability and, depending on the size of the input dataset, a marginal improvement to accuracy assessed by each method’s ability to link genes in the same functional pathway

Metrics for the Human Proteome Project 2016: Progress on Identifying and Characterizing the Human Proteome, Including Post-Translational Modifications

The HUPO Human Proteome Project (HPP) has two overall goals: (1) stepwise completion of the protein parts list, the draft human proteome, confidently identifying and characterizing at least one protein product from each protein-coding gene, with increasing emphasis on the sequence variants, post-translational modifications, and splice isoforms of those proteins, and (2) making proteomics an integrated counterpart to genomics throughout the biomedical and life sciences community. PeptideAtlas and GPMDB reanalyze all major mass spectrometry datasets available through ProteomeXchange with standardized protocols and stringent quality filters; neXtProt curates and integrates mass spectrometry and other findings. The HPP Guidelines for Mass Spectrometry Data Interpretation version 2.0 were applied to manuscripts submitted for this 2016 C-HPP-led special issue [www.thehpp.org/guidelines]. The Human Proteome presented as neXtProt version 2016-02 has 16,518 confident protein identifications (Protein Existence [PE] Level 1), up from 13,664 at 2012-12, 15,646 at 2013-09, and 16,491 at 2014-10. There are 485 proteins that would have been PE1 under the Guidelines v1.0 from 2012, but now have insufficient evidence due to the agreed-upon more stringent Guidelines v2.0 to reduce false-positives. neXtProt and PeptideAtlas now both require two non-nested, uniquely-mapping (proteotypic) peptides of at least 9 aa in length. There are 2949 missing proteins (PE2+3+4) as the baseline for submissions for the 4th annual C-HPP special issue of Journal of Proteome Research. PeptideAtlas has 14,629 canonical (plus 1187 uncertain and 1755 redundant) entries. GPMdb has 16,190 EC4 entries, and the Human Protein Atlas has 10,475 entries with supportive evidence. neXtProt, PeptideAtlas, and GPMDB are rich resources of information about PTMs, SAAVs, and splice isoforms. Meanwhile, the Biology and Disease-driven B/D-HPP has created comprehensive SRM resources, generated popular-protein lists to guide targeted proteomics assays for specific diseases, and launched an Early Career Researchers initiative

Bayesian Model Averaging for Ensemble-Based Estimates of Solvation-Free Energies.

This paper applies the Bayesian Model Averaging statistical ensemble technique to estimate small molecule solvation free energies. There is a wide range of methods available for predicting solvation free energies, ranging from empirical statistical models to ab initio quantum mechanical approaches. Each of these methods is based on a set of conceptual assumptions that can affect predictive accuracy and transferability. Using an iterative statistical process, we have selected and combined solvation energy estimates using an ensemble of 17 diverse methods from the fourth Statistical Assessment of Modeling of Proteins and Ligands (SAMPL) blind prediction study to form a single, aggregated solvation energy estimate. Methods that possess minimal or redundant information are pruned from the ensemble and the evaluation process repeats until aggregate predictive performance can no longer be improved. We show that this process results in a final aggregate estimate that outperforms all individual methods by reducing estimate errors by as much as 91% to 1.2 kcal mol-1 accuracy. This work provides a new approach for accurate solvation free energy prediction and lays the foundation for future work on aggregate models that can balance computational cost with prediction accuracy

Discovery of a proteolytic flagellin family in diverse bacterial phyla that assembles enzymatically active flagella

Bacterial flagella are cell locomotion and occasional adhesion organelles composed primarily of the polymeric protein flagellin, but to date have not been associated with any enzymatic function. Here, we report the bioinformatics-driven discovery of a class of enzymatic flagellins that assemble to form proteolytically active flagella. Originating by a metallopeptidase insertion into the central flagellin hypervariable region, this flagellin family has expanded to at least 74 bacterial species. In the pathogen, Clostridium haemolyticum, metallopeptidase-containing flagellin (which we termed flagellinolysin) is the second most abundant protein in the flagella and is localized to the extracellular flagellar surface. Purified flagellar filaments and recombinant flagellin exhibit proteolytic activity, cleaving nearly 1000 different peptides. With similar to 20,000 flagellin copies per similar to 10-mu m flagella this assembles the largest proteolytic complex known. Flagellum-mediated extracellular proteolysis expands our understanding of the functional plasticity of bacterial flagella, revealing this family as enzymatic biopolymers that mediate interactions with diverse peptide substrates

Metrics for the Human Proteome Project 2016: Progress on Identifying and Characterizing the Human Proteome, Including Post-Translational Modifications

The HUPO Human Proteome Project (HPP) has two overall goals: (1) stepwise completion of the protein parts listthe draft human proteome including confidently identifying and characterizing at least one protein product from each protein-coding gene, with increasing emphasis on sequence variants, post-translational modifications (PTMs), and splice isoforms of those proteins; and (2) making proteomics an integrated counterpart to genomics throughout the biomedical and life sciences community. PeptideAtlas and GPMDB reanalyze all major human mass spectrometry data sets available through ProteomeXchange with standardized protocols and stringent quality filters; neXtProt curates and integrates mass spectrometry and other findings to present the most up to date authorative compendium of the human proteome. The HPP Guidelines for Mass Spectrometry Data Interpretation version 2.1 were applied to manuscripts submitted for this 2016 C-HPP-led special issue [www.thehpp.org/guidelines]. The Human Proteome presented as neXtProt version 2016-02 has 16,518 confident protein identifications (Protein Existence [PE] Level 1), up from 13,664 at 2012-12, 15,646 at 2013-09, and 16,491 at 2014-10. There are 485 proteins that would have been PE1 under the Guidelines v1.0 from 2012 but now have insufficient evidence due to the agreed-upon more stringent Guidelines v2.0 to reduce false positives. neXtProt and PeptideAtlas now both require two non-nested, uniquely mapping (proteotypic) peptides of at least 9 aa in length. There are 2,949 missing proteins (PE2+3+4) as the baseline for submissions for this fourth annual C-HPP special issue of Journal of Proteome Research. PeptideAtlas has 14,629 canonical (plus 1187 uncertain and 1755 redundant) entries. GPMDB has 16,190 EC4 entries, and the Human Protein Atlas has 10,475 entries with supportive evidence. neXtProt, PeptideAtlas, and GPMDB are rich resources of information about post-translational modifications (PTMs), single amino acid variants (SAAVSs), and splice isoforms. Meanwhile, the Biology- and Disease-driven (B/D)-HPP has created comprehensive SRM resources, generated popular protein lists to guide targeted proteomics assays for specific diseases, and launched an Early Career Researchers initiative