TermineR: Extracting information on endogenous proteolytic processing from shotgun proteomics data.

State-of-the-art mass spectrometers combined with modern bioinformatics algorithms for peptide-to-spectrum matching (PSM) with robust statistical scoring allow for more variable features (i.e., post-translational modifications) being reliably identified from (tandem-) mass spectrometry data, often without the need for biochemical enrichment. Semi-specific proteome searches, that enforce a theoretical enzymatic digestion to solely the N- or C-terminal end, allow to identify of native protein termini or those arising from endogenous proteolytic activity (also referred to as "neo-N-termini" analysis or "N-terminomics"). Nevertheless, deriving biological meaning from these search outputs can be challenging in terms of data mining and analysis. Thus, we introduce TermineR, a data analysis approach for the (1) annotation of peptides according to their enzymatic cleavage specificity and known protein processing features, (2) differential abundance and enrichment analysis of N-terminal sequence patterns, and (3) visualization of neo-N-termini location. We illustrate the use of TermineR by applying it to tandem mass tag (TMT)-based proteomics data of a mouse model of polycystic kidney disease, and assess the semi-specific searches for biological interpretation of cleavage events and the variable contribution of proteolytic products to general protein abundance. The TermineR approach and example data are available as an R package at https://github.com/MiguelCos/TermineR.

Data-Independent Acquisition: A Milestone and Prospect in Clinical Mass Spectrometry-Based Proteomics.

Data-independent acquisition (DIA) has revolutionized the field of mass spectrometry (MS)-based proteomics over the past few years. DIA stands out for its ability to systematically sample all peptides in a given m/z range, allowing an unbiased acquisition of proteomics data. This greatly mitigates the issue of missing values and significantly enhances quantitative accuracy, precision, and reproducibility compared to many traditional methods. This review focuses on the critical role of DIA analysis software tools, primarily focusing on their capabilities and the challenges they address in proteomic research. Advances in MS technology, such as trapped ion mobility spectrometry, or high field asymmetric waveform ion mobility spectrometry require sophisticated analysis software capable of handling the increased data complexity and exploiting the full potential of DIA. We identify and critically evaluate leading software tools in the DIA landscape, discussing their unique features, and the reliability of their quantitative and qualitative outputs. We present the biological and clinical relevance of DIA-MS and discuss crucial publications that paved the way for in-depth proteomic characterization in patient-derived specimens. Furthermore, we provide a perspective on emerging trends in clinical applications and present upcoming challenges including standardization and certification of MS-based acquisition strategies in molecular diagnostics. While we emphasize the need for continuous development of software tools to keep pace with evolving technologies, we advise researchers against uncritically accepting the results from DIA software tools. Each tool may have its own biases, and some may not be as sensitive or reliable as others. Our overarching recommendation for both researchers and clinicians is to employ multiple DIA analysis tools, utilizing orthogonal analysis approaches to enhance the robustness and reliability of their findings.

Neoadjuvant chemo- or chemo-radiation-therapy of pancreatic ductal adenocarcinoma differentially shift ECM composition, complement activation, energy metabolism and ribosomal proteins of the residual tumor mass.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer, often diagnosed at stages that dis-qualify for surgical resection. Neoadjuvant therapies offer potential tumor regression and improved resectability. Although features of the tumor biology (e.g., molecular markers) may guide adjuvant therapy, biological alterations after neoadjuvant therapy remain largely unexplored. We performed mass spectrometry to characterize the proteomes of 67 PDAC resection specimens of patients who received either neoadjuvant chemo (NCT) or chemo-radiation (NCRT) therapy. We employed data-independent acquisition (DIA), yielding a proteome coverage in excess of 3500 proteins. Moreover, we successfully integrated two publicly available proteome datasets of treatment-naïve PDAC to unravel proteome alterations in response to neoadjuvant therapy, highlighting the feasibility of this approach. We found highly distinguishable proteome profiles. Treatment-naïve PDAC was characterized by enrichment of immunoglobulins, complement and extracellular matrix (ECM) proteins. Post-NCT and post-NCRT PDAC presented high abundance of ribosomal and metabolic proteins as compared to treatment-naïve PDAC. Further analyses on patient survival and protein expression identified treatment-specific prognostic candidates. We present the first proteomic characterization of the residual PDAC mass after NCT and NCRT, and potential protein candidate markers associated with overall survival. We conclude that residual PDAC exhibits fundamentally different proteome profiles as compared to treatment-naïve PDAC, influenced by the type of neoadjuvant treatment. These findings may impact adjuvant or targeted therapy options.

A 14-Day Double-Blind, Randomized, Controlled Crossover Intervention Study with Anti-Bacterial Benzyl Isothiocyanate from Nasturtium (Tropaeolum majus) on Human Gut Microbiome and Host Defense.

Despite substantial heterogeneity of studies, there is evidence that antibiotics commonly used in primary care influence the composition of the gastrointestinal microbiota in terms of changing their composition and/or diversity. Benzyl isothiocyanate (BITC) from the food and medicinal plant nasturtium (Tropaeolum majus) is known for its antimicrobial activity and is used for the treatment of infections of the draining urinary tract and upper respiratory tract. Against this background, we raised the question of whether a 14 d nasturtium intervention (3 g daily, N = 30 healthy females) could also impact the normal gut microbiota composition. Spot urinary BITC excretion highly correlated with a weak but significant antibacterial effect against Escherichia coli. A significant increase in human beta defensin 1 as a parameter for host defense was seen in urine and exhaled breath condensate (EBC) upon verum intervention. Pre-to-post analysis revealed that mean gut microbiome composition did not significantly differ between groups, nor did the circulating serum metabolome. On an individual level, some large changes were observed between sampling points, however. Explorative Spearman rank correlation analysis in subgroups revealed associations between gut microbiota and the circulating metabolome, as well as between changes in blood markers and bacterial gut species.