Protein-protein cross-linking and human health: the challenge of elucidating with mass spectrometry

Characterizing lysinoalanine crosslinks in food systems: Discovery of a diagnostic ion in model peptides using MALDI mass spectrometry

Formation of lysinoalanine protein-protein crosslinks during food processing adversely impacts nutritional value. However, mapping lysinoalanine directly in food is challenging. We characterized the fragmentation pattern of lysinoalanine crosslinks in synthetic peptide models over a range of pH and time treatments using mass spectrometry. A putative diagnostic ion resulting from the cleavage of the α-carbon and β-carbon of lysinoalanine is identified in MALDI MS/MS spectra. This represents the first step in mapping lysinoalanine in real food samples with higher precision than currently identifiable through standard or customized software. We then determined a correlated trend in the reduction of disulfide bonds and formation of lysinoalanine with increasing pH and time. Mapping lysinoalanine formation is critical to enhance our understanding of molecular processes impacting the nutritional value of foods, including notably in the development of protein alternatives that use alkaline treatment to extract protein isolates.

Mass Spectrometry-Based Untargeted Approaches to Reveal Diagnostic Signatures of Male Infertility in Seminal Plasma: A New Laboratory Perspective for the Clinical Management of Infertility?

Male infertility has been recognized as a global health problem. Semen analysis, although considered the golden standard, may not provide a confident male infertility diagnosis alone. Hence, there is the urgent request for an innovative and reliable platform to detect biomarkers of infertility. The rapid expansion of mass spectrometry (MS) technology in the field of the 'omics' disciplines, has incredibly proved the great potential of MS-based diagnostic tests to revolutionize the future of pathology, microbiology and laboratory medicine. Despite the increasing success in the microbiology area, MS-biomarkers of male infertility currently remain a proteomic challenge. In order to address this issue, this review encompasses proteomics investigations by untargeted approaches with a special focus on experimental designs and strategies (bottom-up and top-down) for seminal fluid proteome profiling. The studies reported here witness the efforts of the scientific community to address these investigations aimed at the discovery of MS-biomarkers of male infertility. Proteomics untargeted approaches, depending on the study design, might provide a great plethora of biomarkers not only for a male infertility diagnosis, but also to address a new MS-biomarkers classification of infertility subtypes. From the early detection to the evaluation of infertility grade, new MS-derived biomarkers might also predict long-term outcomes and clinical management of infertility.

Accurate and Automated High-Coverage Identification of Chemically Cross-Linked Peptides with MaxLynx

Cross-linking combined with mass spectrometry (XL-MS) provides a wealth of information about the three-dimensional (3D) structure of proteins and their interactions. We introduce MaxLynx, a novel computational proteomics workflow for XL-MS integrated into the MaxQuant environment. It is applicable to noncleavable and MS-cleavable cross-linkers. For both, we have generalized the Andromeda peptide database search engine to efficiently identify cross-linked peptides. For noncleavable peptides, we implemented a novel dipeptide Andromeda score, which is the basis for a computationally efficient N-squared search engine. Additionally, partial scores summarize the evidence for the two constituents of the dipeptide individually. A posterior error probability (PEP) based on total and partial scores is used to control false discovery rates (FDRs). For MS-cleavable cross-linkers, a score of signature peaks is combined with the conventional Andromeda score on the cleavage products. The MaxQuant 3D peak detection was improved to ensure more accurate determination of the monoisotopic peak of isotope patterns for heavy molecules, which cross-linked peptides typically are. A wide selection of filtering parameters can replace the manual filtering of identifications, which is often necessary when using other pipelines. On benchmark data sets of synthetic peptides, MaxLynx outperforms all other tested software on data for both types of cross-linkers and on a proteome-wide data set of cross-linked Drosophila melanogaster cell lysate. The workflow also supports ion mobility-enhanced MS data. MaxLynx runs on Windows and Linux, contains an interactive viewer for displaying annotated cross-linked spectra, and is freely available at https://www.maxquant.org/.

Gingival Crevicular Fluid Peptidome Profiling in Healthy and in Periodontal Diseases

Given its intrinsic nature, gingival crevicular fluid (GCF) is an attractive source for the discovery of novel biomarkers of periodontal diseases. GCF contains antimicrobial peptides and small proteins which could play a role in specific immune-inflammatory responses to guarantee healthy gingival status and to prevent periodontal diseases. Presently, several proteomics studies have been performed leading to increased coverage of the GCF proteome, however fewer efforts have been done to explore its natural peptides. To fill such gap, this review provides an overview of the mass spectrometric platforms and experimental designs aimed at GCF peptidome profiling, including our own data and experiences gathered from over several years of matrix-assisted laser desorption ionization/time of flight mass spectrometry (MALDI-TOF MS) based approach in this field. These tools might be useful for capturing snapshots containing diagnostic clinical information on an individual and population scale, which may be used as a specific code not only for the diagnosis of the nature or the stage of the inflammatory process in periodontal disease, but more importantly, for its prognosis, which is still an unmet medical need. As a matter of fact, current peptidomics investigations suffer from a lack of standardized procedures, posing a serious problem for data interpretation. Descriptions of the efforts to address such concerns will be highlighted.

The Apoptosis Regulator 14-3-3η and Its Potential as a Therapeutic Target in Pituitary Oncocytoma

The 14-3-3 protein family has attracted much attention in research into the pathogenesis of human tumors because of its involvement in tumorigenesis. In previous studies, we found that 14-3-3η was highly expressed in pituitary oncocytoma. However, the mechanism by which 14-3-3η regulates tumorigenesis in pituitary oncocytoma is unclear. 14-3-3η-binding proteins were investigated in pituitary oncocytoma by immunoprecipitation and proteomic analysis. A total of 443 proteins were identified as 14-3-3η binding proteins. The interactions of 14-3-3η and its binding partners were identified by a network analysis using the STRING database. The network included 433 nodes and 564 edges. PRAS40 (AKT1S1) was a binding protein of 14-3-3η and showed experimental interactions with 14-3-3η in the STRING database. The combined score was 0.407, which suggested a functional link. The 443 binding proteins of 14-3-3η showed enriched molecular signatures in GSEA and GO analysis. PRAS40 (AKT1S1) was enriched in the mTOR signaling pathway. Western blot analysis showed that the relative expression of p-PRAS40 (T246)/PRAS40 was significantly higher in pituitary oncocytoma than in normal pituitary tissues (p < 0.05). R18, a 14-3-3 protein inhibitor, inhibited MMQ cell proliferation after treatment with 8 μM R18 for 48 h compared to the control group (p < 0.01). These results suggest that 14-3-3η may be involved in promoting tumorigenesis in pituitary oncocytoma by interacting with PRAS40 (T246) via the mTOR signaling pathway.