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Preeclampsia is a pregnancy-specific multisystem disorder and a leading cause of maternal and perinatal morbidity and mortality. The exact pathogenesis of this multifactorial disease remains poorly defined. We applied proteomics analysis on maternal blood samples collected from 14 singleton pregnancies with early-onset severe preeclampsia and 6 uncomplicated pregnancies to investigate the pathophysiological pathways involved in this specific subgroup of preeclampsia. Maternal blood was drawn at diagnosis for cases and at matched gestational age for controls. LC-MS/MS proteomics analysis was conducted, and data were analyzed by multivariate and univariate statistical approaches with the identification of differential pathways by exploring the global human protein-protein interaction network. The unsupervised multivariate analysis (the principal component analysis) showed a clear difference between preeclamptic and uncomplicated pregnancies. The supervised multivariate analysis using orthogonal partial least square discriminant analysis resulted in a model with goodness of fit (R 2 X = 0.99, p < 0.001) and a strong predictive ability (Q 2 Y = 0.8, p < 0.001). By univariate analysis, we found 17 proteins statistically different after 5% FDR correction (q-value < 0.05). Pathway enrichment analysis revealed 5 significantly enriched pathways whereby the activation of the complement and coagulation cascades was on top (p = 3.17e-07). To validate these results, we assessed the deposits of C5b-9 complement complex and on endothelial cells that were exposed to activated plasma from an independent set of 4 cases of early-onset severe preeclampsia and 4 uncomplicated pregnancies. C5b-9 and Von Willbrand factor deposits were significantly higher in early-onset severe preeclampsia. Future studies are warranted to investigate potential therapeutic targets for early-onset severe preeclampsia within the complement and coagulation pathway.

Metaproteomics has emerged as a new, revolutionary approach to study gut microbiota functionality, but the lack of consistent studies in this field due to the great complexity of samples has prompted to search new strategies to achieve better metaproteome characterization. Some steps in sample preparation and data analysis procedures are critical for obtaining accurate results, therefore protein extraction buffers, digestion procedures and fractionation steps were tested here. Initially, two lysis buffers were used to improve protein extraction, two common digestion protocols were compared, and fractionation processes were employed at both the peptide and protein levels. The combination of these procedures resulted in five different methodologies; SDS buffer, in-gel digestion and fractionation at the peptide level provided the best results. Finally, the metaproteomics workflow was tested in a real case study with obese rats, in which a metagenomics study was previously performed. Important differences in protein levels were observed between groups that were potentially related to the taxonomical family, indicating that functional processes are modulated by the microbiota. Therefore, in addition to the necessity of combining different metaomics approaches, an optimized metaproteomics workflow such as the presented in this study is required to obtain a better understanding of the microbiota function. SIGNIFICANCE: Gut microbiota has emerged as an important factor with affects the health balance in host. To study its function new methodologies are necessary and the most appropriate one seems to be metaproteomics. The lack of studies in this field requires a deeply research in the most accurate workflow to better comprehend such complex samples. In this paper, five different methodologies have been compared, mainly in the most critical steps in classical proteomics and the methodology chosen was validated in a real case study in obese animals., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Over the last few years, the application of high-throughput meta-omics methods has provided great progress in improving the knowledge of the gut ecosystem and linking its biodiversity to host health conditions, offering complementary support to classical microbiology. Gut microbiota plays a crucial role in relevant diseases such as obesity or cardiovascular disease (CVD), and its regulation is closely influenced by several factors, such as dietary composition. In fact, polyphenol-rich diets are the most palatable treatment to prevent hypertension associated with CVD, although the polyphenol-microbiota interactions have not been completely elucidated. For this reason, the aim of this study was to evaluate microbiota effect in obese rats supplemented by hesperidin, after being fed with cafeteria or standard diet, using a multi meta-omics approaches combining strategy of metagenomics and metaproteomics analysis. We reported that cafeteria diet induces obesity, resulting in changes in the microbiota composition, which are related to functional alterations at proteome level. In addition, hesperidin supplementation alters microbiota diversity and also proteins involved in important metabolic pathways. Overall, going deeper into strategies to integrate omics sciences is necessary to understand the complex relationships between the host, gut microbiota, and diet., (© 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

The p16(ink4a) tumor suppressor protein plays a critical role in cell cycle control, tumorogenesis and senescence. The best known activity for p16(ink4a) is the inhibition of the activity of CDK4 and CDK6 kinases, both playing a key role in cell cycle progression. With the aim to study new p16(ink4a) functions we used affinity chromatography and MS techniques to identify new p16(ink4a)-interacting proteins. We generated p16(ink4a) columns by coupling the protein to activated Sepharose 4B. The proteins from MOLT-4 cell line that bind to p16(ink4a) affinity columns were resolved by SDS-PAGE and identified by MS using a MALDI-TOF. Thirty-one p16(ink4a) -interacting proteins were identified and grouped in functional clusters. The identification of two of them, proliferating cell nuclear antigen (PCNA) and minichromosome maintenance protein 6 (MCM6), was confirmed by Western blotting and their in vivo interactions with p16(ink4a) were demonstrated by immunoprecipitation and immunofluorescence studies. Results also revealed that p16(ink4a) interacts directly with the DNA polymerase delta accessory protein PCNA and thereby inhibits the polymerase activity.