CoDIAC: A comprehensive approach for interaction analysis reveals novel insights into SH2 domain function and regulation.

Protein domains are conserved structural and functional units and are the functional building blocks of proteins. Evolutionary expansion means that domain families are often represented by many members in a species, which are found in various configurations with other domains, which have evolved new specificity for interacting partners. Here, we develop a structure-based interface analysis to comprehensively map domain interfaces from available experimental and predicted structures, including interfaces with other macromolecules and intraprotein interfaces (such as might exist between domains in a protein). We hypothesized that a comprehensive approach to contact mapping of domains could yield new insights. Specifically, we use it to gain information about how domains selectivity interact with ligands, whether domain-domain interfaces of repeated domain partnerships are conserved across diverse proteins, and identify regions of conserved post-translational modifications, using relationship to interaction interfaces as a method to hypothesize the effect of post-translational modifications (and mutations). We applied this approach to the human SH2 domain family, an extensive modular unit that is the foundation of phosphotyrosine-mediated signaling, where we identified a novel approach to understanding the binding selectivity of SH2 domains and evidence that there is coordinated and conserved regulation of multiple SH2 domain binding interfaces by tyrosine and serine/threonine phosphorylation and acetylation, suggesting that multiple signaling systems can regulate protein activity and SH2 domain interactions in a regulated manner. We provide the extensive features of the human SH2 domain family and this modular approach, as an open source Python package for COmprehensive Domain Interface Analysis of Contacts (CoDIAC).

Using the Culex pipiens sperm proteome to identify elements essential for mosquito reproduction.

Mature sperm from Culex pipiens were isolated and analyzed by mass spectrometry to generate a mature sperm proteome dataset. In this study, we highlight subsets of proteins related to flagellar structure and sperm motility and compare the identified protein components to previous studies examining essential functions of sperm. The proteome includes 1700 unique protein IDs, including a number of uncharacterized proteins. Here we discuss those proteins that may contribute to the unusual structure of the Culex sperm flagellum, as well as potential regulators of calcium mobilization and phosphorylation pathways that regulate motility. This database will prove useful for understanding the mechanisms that activate and maintain sperm motility as well as identify potential molecular targets for mosquito population control.

Spectral characteristics of urine from patients with end-stage kidney disease analyzed using Raman Chemometric Urinalysis (Rametrix).

Raman Chemometric Urinalysis (RametrixTM) was used to discern differences in Raman spectra from (i) 362 urine specimens from patients receiving peritoneal dialysis (PD) therapy for end-stage kidney disease (ESKD), (ii) 395 spent dialysate specimens from those PD therapies, and (iii) 235 urine specimens from healthy human volunteers. RametrixTM analysis includes spectral processing (e.g., truncation, baselining, and vector normalization); principal component analysis (PCA); statistical analyses (ANOVA and pairwise comparisons); discriminant analysis of principal components (DAPC); and testing DAPC models using a leave-one-out build/test validation procedure. Results showed distinct and statistically significant differences between the three types of specimens mentioned above. Further, when introducing "unknown" specimens, RametrixTM was able to identify the type of specimen (as PD patient urine or spent dialysate) with better than 98% accuracy, sensitivity, and specificity. RametrixTM was able to identify "unknown" urine specimens as from PD patients or healthy human volunteers with better than 96% accuracy (with better than 97% sensitivity and 94% specificity). This demonstrates that an entire Raman spectrum of a urine or spent dialysate specimen can be used to determine its identity or the presence of ESKD by the donor.

Spectral characteristics of urine specimens from healthy human volunteers analyzed using Raman chemometric urinalysis (Rametrix).

Raman chemometric urinalysis (Rametrix™) was used to analyze 235 urine specimens from healthy individuals. The purpose of this study was to establish the "range of normal" for Raman spectra of urine specimens from healthy individuals. Ultimately, spectra falling outside of this range will be correlated with kidney and urinary tract disease. Rametrix™ analysis includes direct comparisons of Raman spectra but also principal component analysis (PCA), discriminant analysis of principal components (DAPC) models, multivariate statistics, and it is available through GitHub as the Rametrix™ LITE Toolbox for MATLAB®. Results showed consistently overlapping Raman spectra of urine specimens with significantly larger variances in Raman shifts, found by PCA, corresponding to urea, creatinine, and glucose concentrations. A 2-way ANOVA test found that age of the urine specimen donor was statistically significant (p < 0.001) and donor sex (female or male identification) was less so (p = 0.0526). With DAPC models and blind leave-one-out build/test routines using the Rametrix™ PRO Toolbox (also available through GitHub), an accuracy of 71% (sensitivity = 72%; specificity = 70%) was obtained when predicting whether a urine specimen from a healthy unknown individual was from a female or male donor. Finally, from female and male donors (n = 4) who contributed first morning void urine specimens each day for 30 days, the co-occurrence of menstruation was found statistically insignificant to Rametrix™ results (p = 0.695). In addition, Rametrix™ PRO was able to link urine specimens with the individual donor with an average of 78% accuracy. Taken together, this study established the range of Raman spectra that could be expected when obtaining urine specimens from healthy individuals and analyzed by Rametrix™ and provides the methodology for linking results with donor characteristics.