Science in neo-Victorian poetry

This article considers the work of three contemporary poets and their engagement, in verse, with Victorian science. Beginning with the outlandish ‘theories’ of Mick Imlah’s ‘The Zoologist’s Bath’ (1983), it moves on to two works of biografiction – Anthony Thwaite’s poem ‘At Marychurch’ (1980), which outlines Philip Henry Gosse’s doomed attempts to unite evolution and Christianity, and Ruth Padel’s Darwin: A Life in Poems (2009). Starting off with John Glendening’s idea that science in neo-Victorian fiction, if fully embraced, provides an opportunity for self-revelation to characters, this article explores the rather less happy resolutions of each of these poems, while in addition discussing the ways in which these poems perform the formal changes and mutability discussed within them

Differential Proteomic Analysis of Mammalian Tissues Using SILAM

Differential expression of proteins between tissues underlies organ-specific functions. Under certain pathological conditions, this may also lead to tissue vulnerability. Furthermore, post-translational modifications exist between different cell types and pathological conditions. We employed SILAM (Stable Isotope Labeling in Mammals) combined with mass spectrometry to quantify the proteome between mammalian tissues. Using 15N labeled rat tissue, we quantified 3742 phosphorylated peptides in nuclear extracts from liver and brain tissue. Analysis of the phosphorylation sites revealed tissue specific kinase motifs. Although these tissues are quite different in their composition and function, more than 500 protein identifications were common to both tissues. Specifically, we identified an up-regulation in the brain of the phosphoprotein, ZFHX1B, in which a genetic deletion causes the neurological disorder Mowat–Wilson syndrome. Finally, pathway analysis revealed distinct nuclear pathways enriched in each tissue. Our findings provide a valuable resource as a starting point for further understanding of tissue specific gene regulation and demonstrate SILAM as a useful strategy for the differential proteomic analysis of mammalian tissues

From Synapse to Function: A Perspective on the Role of Neuroproteomics in Elucidating Mechanisms of Drug Addiction

Drug addiction is a complex disorder driven by dysregulation in molecular signaling across several different brain regions. Limited therapeutic options currently exist for treating drug addiction and related psychiatric disorders in clinical populations, largely due to our incomplete understanding of the molecular pathways that influence addiction pathology. Recent work provides strong evidence that addiction-related behaviors emerge from the convergence of many subtle changes in molecular signaling networks that include neuropeptides (neuropeptidome), protein-protein interactions (interactome) and post-translational modifications such as protein phosphorylation (phosphoproteome). Advancements in mass spectrometry methodology are well positioned to identify these novel molecular underpinnings of addiction and further translate these findings into druggable targets for therapeutic development. In this review, we provide a general perspective of the utility of novel mass spectrometry-based approaches for addressing critical questions in addiction neuroscience, highlighting recent innovative studies that exemplify how functional assessments of the neuroproteome can provide insight into the mechanisms of drug addiction

Comparison of Protein Expression Ratios Observed by Sixplex and Duplex TMT Labeling Method

Stable isotope labeling via isobaric derivatization of peptides is a universally applicable approach that enables concurrent identification and quantification of proteins in different samples using tandem mass spectrometry. In this study, we evaluated the performance of amine-reactive isobaric tandem mass tag (TMT), available as duplex and sixplex sets, with regard to their ability to elucidate protein expression changes. Using rat brain tissue from two different developmental time points, postnatal day 1 (p1) and 45 (p45), as a model system, we compared the protein expression ratios (p45/p1) observed using duplex TMT tags in triplicate measurements versus sixplex tag in a single LC–MS/MS analysis. A correlation of 0.79 in relative protein abundance was observed in the proteins quantified by these two sets of reagents. However, more proteins passed the criteria for significant fold change (−1.0 ≤ log₂ ratio (p45/p1) ≥ +1.0 and <i>p</i> < 0.05) in the sixplex analysis. Nevertheless, in both methods most proteins showing significant fold change were identified by multiple spectra, increasing their quantification precision. Additionally, the fold change in p45 rats against p1, observed in TMT experiments, was corroborated by a metabolic labeling strategy where relative quantification of differentially expressed proteins was obtained using ¹⁵N-labeled p45 rats as an internal standard

PSEA-Quant: A Protein Set Enrichment Analysis on Label-Free and Label-Based Protein Quantification Data

The majority of large-scale proteomics quantification methods yield long lists of quantified proteins that are often difficult to interpret and poorly reproduced. Computational approaches are required to analyze such intricate quantitative proteomics data sets. We propose a statistical approach to computationally identify protein sets (e.g., Gene Ontology (GO) terms) that are significantly enriched with abundant proteins with reproducible quantification measurements across a set of replicates. To this end, we developed PSEA-Quant, a protein set enrichment analysis algorithm for label-free and label-based protein quantification data sets. It offers an alternative approach to classic GO analyses, models protein annotation biases, and allows the analysis of samples originating from a single condition, unlike analogous approaches such as GSEA and PSEA. We demonstrate that PSEA-Quant produces results complementary to GO analyses. We also show that PSEA-Quant provides valuable information about the biological processes involved in cystic fibrosis using label-free protein quantification of a cell line expressing a CFTR mutant. Finally, PSEA-Quant highlights the differences in the mechanisms taking place in the human, rat, and mouse brain frontal cortices based on tandem mass tag quantification. Our approach, which is available online, will thus improve the analysis of proteomics quantification data sets by providing meaningful biological insights

Dynamics of Subcellular Proteomes During Brain Development

Many neurological disorders are caused by perturbations during brain development, but these perturbations cannot be readily identified until there is comprehensive description of the development process. In this study, we performed mass spectrometry analysis of the synaptosomal and mitochondrial fractions from three rat brain regions at four postnatal time points. To quantitate our analysis, we employed ¹⁵N labeled rat brains using a technique called SILAM (stable isotope labeling in mammals). We quantified 167429 peptides and identified over 5000 statistically significant changes during development including known disease-associated proteins. Global analysis revealed distinct trends between the synaptic and nonsynaptic mitochondrial proteomes and common protein networks between regions each consisting of a unique array of expression patterns. Finally, we identified novel regulators of neurodevelopment that possess the identical temporal pattern of known regulators of neurodevelopment. Overall, this study is the most comprehensive quantitative analysis of the developing brain proteome to date, providing an important resource for neurobiologists

Dynamics of Subcellular Proteomes During Brain Development

Many neurological disorders are caused by perturbations during brain development, but these perturbations cannot be readily identified until there is comprehensive description of the development process. In this study, we performed mass spectrometry analysis of the synaptosomal and mitochondrial fractions from three rat brain regions at four postnatal time points. To quantitate our analysis, we employed ¹⁵N labeled rat brains using a technique called SILAM (stable isotope labeling in mammals). We quantified 167429 peptides and identified over 5000 statistically significant changes during development including known disease-associated proteins. Global analysis revealed distinct trends between the synaptic and nonsynaptic mitochondrial proteomes and common protein networks between regions each consisting of a unique array of expression patterns. Finally, we identified novel regulators of neurodevelopment that possess the identical temporal pattern of known regulators of neurodevelopment. Overall, this study is the most comprehensive quantitative analysis of the developing brain proteome to date, providing an important resource for neurobiologists