MS-BID: a Java package for label-free LC-MS-based comparative proteomic analysis

Summary: MS-BID (MS Biomarker Discovery Platform) is an integrative computational pipeline for biomarker discovery using LC-MS-based comparative proteomic analysis. This platform consists of several computational tools for: (i) detecting peptides in the collected patterns; (ii) matching detected peptides across a number of LC-MS datasets and (iii) selecting discriminatory peptides between classes of samples. Availability: MS-BID source codes, binaries and documentations are freely available under LGPL from http://tools.proteomecenter.org/msBID.php. Contact: [email protected]

Prequips—an extensible software platform for integration, visualization and analysis of LC-MS/MS proteomics data

Summary: We describe an integrative software platform, Prequips, for comparative proteomics-based systems biology analysis that: (i) integrates all information generated from mass spectrometry (MS)-based proteomics as well as from basic proteomics data analysis tools, (ii) visualizes such information for various proteomic analyses via graphical interfaces and (iii) links peptide and protein abundances to external tools often used in systems biology studies. Availability: http://prequips.sourceforge.net Contact: [email protected]

A systems approach to prion disease

Prions cause transmissible neurodegenerative diseases and replicate by conformational conversion of normal benign forms of prion protein (PrPC) to disease-causing PrPSc isoforms. A systems approach to disease postulates that disease arises from perturbation of biological networks in the relevant organ. We tracked global gene expression in the brains of eight distinct mouse strain–prion strain combinations throughout the progression of the disease to capture the effects of prion strain, host genetics, and PrP concentration on disease incubation time. Subtractive analyses exploiting various aspects of prion biology and infection identified a core of 333 differentially expressed genes (DEGs) that appeared central to prion disease. DEGs were mapped into functional pathways and networks reflecting defined neuropathological events and PrPSc replication and accumulation, enabling the identification of novel modules and modules that may be involved in genetic effects on incubation time and in prion strain specificity. Our systems analysis provides a comprehensive basis for developing models for prion replication and disease, and suggests some possible therapeutic approaches

Genomic Analysis of the Olfactory Receptor Region of the Mouse and Human T-Cell Receptor α/δ Loci

We have conducted a comparative genomic analysis of several olfactory receptor (OR) genes that lie immediately 5′ to the V-α gene segments at the mouse and human T-cell receptor (TCR) α/δ loci. Five OR genes are identified in the human cluster. The murine cluster has at least six OR genes; the first five are orthologous to the human genes. The sixth mouse gene has arisen since mouse-human divergence by a duplication of a ∼10-kb block. One pair of OR paralogs found at the mouse and human loci are more similar to each other than to their corresponding orthologs. This paralogous “twinning” appears to be under selection, perhaps to increase sensitivity to particular odorants or to resolve structurally-similar odorants. The promoter regions of the mouse OR genes were identified by RACE-PCR. Orthologs share extensive 5′ UTR homology, but we find no significant similarity among paralogs. These findings extend previous observations that suggest that OR genes do not share local significant regulatory homology despite having a common regulatory agenda. We also identified a diverged TCR-α gene segment that uses a divergent recombination signal sequence (RSS) to initiate recombination in T-cells from within the OR region. We explored the hypothesis that OR genes may use DNA recombination in expressing neurons, e.g., to recombine ORs into a transcriptionally active locus. We searched the mouse sequence for OR-flanking RSS motifs, but did not find evidence to suggest that these OR genes use TCR-like recombination target sequences

Engineering a tunable micropattern‐array assay to sort single extracellular vesicles and particles to detect RNA and protein in situ

Abstract The molecular heterogeneity of extracellular vesicles (EVs) and the co‐isolation of physically similar particles, such as lipoproteins (LPs), confounds and limits the sensitivity of EV bulk biomarker characterization. Herein, we present a single‐EV and particle (siEVP) protein and RNA assay (siEVPPRA) to simultaneously detect mRNAs, miRNAs, and proteins in subpopulations of EVs and LPs. The siEVPPRA immobilizes and sorts particles via positive immunoselection onto micropatterns and focuses biomolecular signals in situ. By detecting EVPs at a single‐particle resolution, the siEVPPRA outperformed the sensitivities of bulk‐analysis benchmark assays for RNA and protein. To assess the specificity of RNA detection in complex biofluids, EVs from various glioma cell lines were processed with small RNA sequencing, whereby two mRNAs and two miRNAs associated with glioblastoma multiforme (GBM) were chosen for cross‐validation. Despite the presence of single‐EV‐LP co‐isolates in serum, the siEVPPRA detected GBM‐associated vesicular RNA profiles in GBM patient siEVPs. The siEVPPRA effectively examines intravesicular, intervesicular, and interparticle heterogeneity with diagnostic promise

Serum brain-derived neurotrophic factor remains elevated after long term follow-up of combat veterans with chronic post-traumatic stress disorder.

Attempts to correlate blood levels of brain-derived neurotrophic factor (BDNF) with post-traumatic stress disorder (PTSD) have provided conflicting results. Some studies found a positive association between BDNF and PTSD diagnosis and symptom severity, while others found the association to be negative. The present study investigated whether serum levels of BDNF are different cross-sectionally between combat trauma-exposed veterans with and without PTSD, as well as whether longitudinal changes in serum BDNF differ as a function of PTSD diagnosis over time. We analyzed data of 270 combat trauma-exposed veterans (230 males, 40 females, average age: 33.29 ± 8.28 years) and found that, at the initial cross-sectional assessment (T0), which averaged 6 years after the initial exposure to combat trauma (SD=2.83 years), the PTSD positive group had significantly higher serum BDNF levels than the PTSD negative controls [31.03 vs. 26.95 ng/mL, t(268) = 3.921, p \u3c 0.001]. This difference remained significant after excluding individuals with comorbid major depressive disorder, antidepressant users and controlling for age, gender, race, BMI, and time since trauma. Fifty-nine of the male veterans who participated at the first timepoint (T0) were re-assessed at follow-up evaluation (T1), approximately 3 years (SD=0.88 years) after T0. A one-way ANOVA comparing PTSD positive, subthreshold PTSD and control groups revealed that serum BDNF remained significantly higher in the PTSD positive group than the control group at T1 [30.05 vs 24.66 ng/mL, F(2, 56)= 3.420, p = 0.040]. Serum BDNF levels did not correlate with PTSD symptom severity at either time point within the PTSD group [r(128) = 0.062, p = 0.481 and r(28) = 0.157, p = 0.407]. Serum BDNF did not significantly change over time within subjects [t(56) = 1.269, p = 0.210] nor did the change of serum BDNF from T0 to T1 correlate with change in PTSD symptom severity within those who were diagnosed with PTSD at T0 [r(27) = -0.250, p = 0.192]. Our longitudinal data are the first to be reported in combat PTSD and suggest that higher serum BDNF levels may be a stable biological characteristic of chronic combat PTSD independent of symptom severity