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Abstract Background The shotgun strategy (liquid chromatography coupled with tandem mass spectrometry) is widely applied for identification of proteins in complex mixtures. This method gives rise to thousands of spectra in a single run, which are interpreted by computational tools. Such tools normally use a protein database from which peptide sequences are extracted for matching with experimentally derived mass spectral data. After the database search, the correctness of obtained peptide-spectrum matches (PSMs) needs to be evaluated also by algorithms, as a manual curation of these huge datasets would be impractical. The target-decoy database strategy is largely used to perform spectrum evaluation. Nonetheless, this method has been applied without considering sensitivity, i.e., only error estimation is taken into account. A recently proposed method termed MUDE treats the target-decoy analysis as an optimization problem, where sensitivity is maximized. This method demonstrates a significant increase in the retrieved number of PSMs for a fixed error rate. However, the MUDE model is constructed in such a way that linear decision boundaries are established to separate correct from incorrect PSMs. Besides, the described heuristic for solving the optimization problem has to be executed many times to achieve a significant augmentation in sensitivity. Results Here, we propose a new method, termed MUMAL, for PSM assessment that is based on machine learning techniques. Our method can establish nonlinear decision boundaries, leading to a higher chance to retrieve more true positives. Furthermore, we need few iterations to achieve high sensitivities, strikingly shortening the running time of the whole process. Experiments show that our method achieves a considerably higher number of PSMs compared with standard tools such as MUDE, PeptideProphet, and typical target-decoy approaches. Conclusion Our approach not only enhances the computational performance, and thus the turn around time of MS-based experiments in proteomics, but also improves the information content with benefits of a higher proteome coverage. This improvement, for instance, increases the chance to identify important drug targets or biomarkers for drug development or molecular diagnostics.

Abstract Background In higher plants, the inhibition of photosynthetic capacity under drought is attributable to stomatal and non-stomatal (i.e., photochemical and biochemical) effects. In particular, a disruption of photosynthetic metabolism and Rubisco regulation can be observed. Several studies reported reduced expression of the RBCS genes, which encode the Rubisco small subunit, under water stress. Results Expression of the RBCS1 gene was analysed in the allopolyploid context of C. arabica, which originates from a natural cross between the C. canephora and C. eugenioides species. Our study revealed the existence of two homeologous RBCS1 genes in C. arabica: one carried by the C. canephora sub-genome (called CaCc) and the other carried by the C. eugenioides sub-genome (called CaCe). Using specific primer pairs for each homeolog, expression studies revealed that CaCe was expressed in C. eugenioides and C. arabica but was undetectable in C. canephora. On the other hand, CaCc was expressed in C. canephora but almost completely silenced in non-introgressed ("pure") genotypes of C. arabica. However, enhanced CaCc expression was observed in most C. arabica cultivars with introgressed C. canephora genome. In addition, total RBCS1 expression was higher for C. arabica cultivars that had recently introgressed C. canephora genome than for "pure" cultivars. For both species, water stress led to an important decrease in the abundance of RBCS1 transcripts. This was observed for plants grown in either greenhouse or field conditions under severe or moderate drought. However, this reduction of RBCS1 gene expression was not accompanied by a decrease in the corresponding protein in the leaves of C. canephora subjected to water withdrawal. In that case, the amount of RBCS1 was even higher under drought than under unstressed (irrigated) conditions, which suggests great stability of RBCS1 under adverse water conditions. On the other hand, for C. arabica, high nocturnal expression of RBCS1 could also explain the accumulation of the RBCS1 protein under water stress. Altogether, the results presented here suggest that the content of RBCS was not responsible for the loss of photosynthetic capacity that is commonly observed in water-stressed coffee plants. Conclusion We showed that the CaCe homeolog was expressed in C. eugenioides and non-introgressed ("pure") genotypes of C. arabica but that it was undetectable in C. canephora. On the other hand, the CaCc homeolog was expressed in C. canephora but highly repressed in C. arabica. Expression of the CaCc homeolog was enhanced in C. arabica cultivars that experienced recent introgression with C. canephora. For both C. canephora and C. arabica species, total RBCS1 gene expression was highly reduced with WS. Unexpectedly, the accumulation of RBCS1 protein was observed in the leaves of C. canephora under WS, possibly coming from nocturnal RBCS1 expression. These results suggest that the increase in the amount of RBCS1 protein could contribute to the antioxidative function of photorespiration in water-stressed coffee plants.

Proteins mediate all physiological changes. Seminal plasma (SP), the product of testes, epididymis, and accessory sex glands, is a fluid released during ejaculation and represents up to 98% of the voluminous stallion ejaculate. The SP plays an essential role in reproduction as a transit medium and a source of energy, antioxidants, enzymes, and minerals. This study aimed to investigate proteomic profile of the seminal plasma of stallions. Twenty-four Criollo stallions with a known reproductive history and per-cycle concept rate data calculated from at least 30 inseminations were used. One ejaculate was collected from each stallion during the breeding season. Pregnancy rates ranged at day 16 after artificial insemination from 20.2% to 95.6%. The animals were divided into two groups: High Pregnancy (HP), with a pregnancy rate per cycle ≥51%, and Low Pregnancy (LP), with a pregnancy rate of <50%. Sperm concentration, kinetics, morphology, and plasma membrane integrity and functionality were evaluated. The sample was centrifuged at 400xg for 10min. SP was then transferred to a 2 mL microcentrifuge tube and centrifuged again (10.000xg, 60min, 4°C). Proteins were separated using 2D SDS PAGE gel electrophoresis in duplicate. Spots in at least 80% of the gels in one of the groups, with significant abundance (P<0.05) and at least a 1.5-fold magnitude difference between groups, were selected. Thespectra were acquired in a nano LC-MS/MS spectrometer, and proteins were identified by the MASCOT application and validated by SCAFFOLD. From a total of 716 analyzed spots, four were selected. For non-parametric data the Kruskal Wallis and for parametric data Anova and t-test were used. The cysteine-rich secretory protein 3 (CRISP3) and SP protein HSP-1-like (HSP1) showed higher abundance in the SP in group LP than HP (P< 0.05). However, kallikrein-1E2 (KLK) and phospholipase A2 (PLA2) showed higher abundance in HP than LP (P<0.05). In the horse, CRISP-3 is synthesized in great amounts in the accessory sexual glands, ampulla and seminal vesicle. HSP1 has an essential role as a molecular chaperone for sperm motility and viability, in the formation of the oviductal sperm reservoir, in the regulation of cell volume, and possibly in the interaction between gametes. KLK is one of the major proteins found in seminal equine plasma. The kallikreins are serine proteases, and the glandular kallikrein is regulated by androgens and secreted by the prostate. The PLA2 plays an essential role in the late maturational events of spermatozoa, the acrosomal reaction, and sperm egg fusion. In conclusion, the proteins are essential to the biological processes related to stallion fertility, providing insight into SP proteins that could serve as biomarkers for fertility in stallions. [ABSTRACT FROM AUTHOR]

Background: Anticarsia gemmatalis larvae are key defoliating pests of soybean plants. Inorganic insecticides, harmful to the environment and human health, are the main molecules used in the control of this pest. To apply more sustainable management methods, organic molecules with high specificities, such as proteinaceous protease inhibitors, have been sought. Thus, molecular docking studies, kinetics assays, and biological tests were performed to evaluate the inhibitory activity of two peptides (GORE1 and GORE2) rationally designed to inhibit trypsin-like enzymes, which are the main proteases of A. gemmatalis midgut., Results: The molecular docking simulations revealed critical hydrogen bonding patterns of the peptides with key active site residues of trypsin-like proteases of A. gemmatalis and other Lepidopteran insects. The negative values of binding energy indicate that hydrogen bonds potentiate the tight binding of the peptides with trypsin-like proteases, predicting an effective inhibition. The inhibition's rate constants (Ki) were 0.49 and 0.10 mM for GORE1 and GORE2, resulting in effective inhibition of the activity trypsin on the L-BApNA substrate in the in vitro tests, indicating that the peptide GORE2 has higher inhibitory capacity on the A. gemmatalis trypsins. In addition, the two peptides were determined to be reversible competitive inhibitors. The in vivo test demonstrated that the peptides harm the survival and development of A. gemmatalis larvae., Conclusion: These results suggest that these peptides are potential candidates in the management of A. gemmatalis larvae and provide baseline information for the design of new trypsin-like inhibitors based on peptidomimetic tools. © 2020 Society of Chemical Industry., (© 2020 Society of Chemical Industry.)