Current Proteomics - Volume 15, Issue 3, 2018

Background: Protein Data Bank is a world-wide repository that collects and provides macromolecular data of protein structures and other molecules for Life sciences community. Manipulation of vast amount of 3D protein structures and exploration of their properties require parsing thousands of flat files that are used to describe these macromolecular structures every time we perform calculations. Objective: Expecting more protein structures to appear in the future in open access repositories, like the Protein Data Bank, and meeting the expectations of the era of fast data analytics, we propose inmemory management system for protein structures that predominantly uses main memory of the host server to store, manage and manipulate data. This allows to eliminate the overhead related to loading data from hard drives and storing them in a buffer cache. Method: In this paper, we show in-memory protein structure management system (IMPSMS), which allows performing various operations, including basic functions like: selection, inserting, updating and searching of protein structures, and execution of more sophisticated functions, like batch calculation of root mean square deviation between proteins stored in the database, batch calculation of torsion angles, structure comparison, structural alignment and superposition of the given molecule to molecules stored in the in-memory database. Results: In the experimental part, we show that with dedicated in-memory data structures particular operations on proteins can be performed even a hundred times faster than analogous operations preceded by traditional loading and parsing macromolecular data from standard PDB flat files. Conclusion: Our work proves that designing dedicated data structures and management systems for frequent protein data manipulations brings significant time savings and increases capabilities of running fast data analytics in bioinformatics.

Background: An epitope is a specific portion of a macromolecular antigen that can determine antigen specificity, and has great significance in studying adaptive immune responses. It can be a linear fragment in the antigen structure (also called a linear B-cell epitope) or an area of conformational structure in space (also known as a conformational B-cell epitope). However, the methods of empirical testing used to identify epitopes are costly and time consuming. Objective: The objective of this study is to provide an efficient predictor for distinguishing linear B-cell epitopes. Method: In this study, we present a predictor model based on the incorporation of information on the position- specific amino acid propensity, composition of amino acids, composition of pairs of amino acids and position-specific pair of amino acids propensity. And F-Score was used to select valid features. Results: In jackknife cross-validation, our model achieved an overall sensitivity of 92.59%, specificity of 95.47%, accuracy of 94.36% and Matthews correlation coefficient of 0.8729 on a non-redundant dataset. Conclusion: The results confirm the constructed model is superior to other existing methods.

Background: Cancerlectins play an important role in various cancer metastasis and tumor cell differentiation. Therefore, comprehensively understanding the functions of cancerlectins could reveal the future direction of cancer treatment. Although cancerlectin protein sequences can be distinguished by various computational methods, which have been proposed as auxiliary tools, these methods sometimes fail because of the large sequence diversity among cancerlectins. Objective: The objective of this study is to provide an efficient predictor for identifying cancerlectins. Method: Herein, we build a prediction model based on a support vector machine, which improves the sensitivity and accuracy of cancerlectin protein identification. Feature extraction and selection are performed by our proposed Split Bi-Profile Bayes (SBPB) scheme and a lasso algorithm, respectively. Results: In jackknife cross-validation, our model (called iCanLec-SBPB) achieved a sensitivity of 81.36% and an accuracy of 83.25%. Conclusion: The results confirm the higher sensitivity and accuracy of iCanLec-SBPB than other existing methods.

Space travelling has emerged as a hot issue in the world for various purposes. The man has been trying to establish space stations and these efforts have turned into a reality. Longtime stay in space is very much challenging due to various limiting environmental problems and health issues. Among many, one is microgravity that generates uneven flow of fluids in the body which results in oxidative stress. This stress markedly interrupts cerebral activity of astronauts both structurally and functionally. This oxidative stress produced by microgravity distort many essential protein signaling pathways that intricate various homeostatic behaviors within the body. The current knowledge of microgravity effects on human brain especially the hypothalamus is expanding; whereas the comprehension of the basic components of this phenomenon is restricted. Various literature reports already outlined many key phenomena distorted by earth-based simulated microgravity. Therefore, an effort is being made to summarize this bulk of knowledge in a simple way for the convenience of space research community. This review will elucidate the effect of microgravity on the expression of key proteins involved in structural, morphological, functional and molecular functions.

Premature Ovarian Insufficiency (POI) is a fertility-related disorder affecting 1% of women. It is defined as the development of hypergonadotropic hypogonadism before the typical natural age of the menopause. The diagnosis of POI, previously described as premature ovarian failure, is one of unexpected, bad news for generally young, healthy and well-being women less than 40 years old. Despite iatrogenic and genetic pathogenesis approximately 90% of cases are diagnosed accidentally with unknown etiology. Sirtuins (SIRTs) are a class of nicotine adenine dinucleotide (NAD+)-dependent proteins which regulate various biochemical pathways and participate in a wide range of major cellular processes, such as aging, apoptosis, inflammation, stress resistance, genomic stability and energy metabolism. Some findings also suggest that sirtuins family proteins may be potential markers of ovarian aging. The present review evaluates some activities of sirtuins, especially sirtuin1 and its possible association with woman's metabolism, ovarian aging and premature ovarian insufficiency. This discussion gives the novel insight into the etiology of idiopathic premature ovarian insufficiency and offers new research directions in the field (Fig. 1).

Background: Early detection of breast cancer is a key to the success of breast cancer management. Serum proteome analysis using Surface-Enhanced Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry (SELDI-TOF-MS) generates useful information that can be utilized to describe exclusive prognostic and diagnostic biomarkers. Objective: This study aimed to use proteomics and bioinformatics to identify new biomarkers during the metastatic process of breast cancers that were classified as invasive lobular cancer or invasive ductal cancer. Method: Blood samples from 64 breast cancer patients [36 with invasive ductal cancer (14 of whom were lymph node positive); 28 with invasive lobular cancer (8 of whom were lymph node positive] were analyzed using IMAC 30 protein chips. The data acquired from the spectra were processed with univariate statistical analysis (Protein Chip Data Manager Software). Results: One-hundred-eighteen clusters were generated from the individual serum samples. Thirty-six proteins of the metastatic phenotype were found to be diagnostically accurate in cluster analysis. In the breast cancer group, a single candidate peak (m/z 1090.8) that was able to discriminate the metastatic progression was identified as a metastatic phenotype marker. Fifteen protein peaks were identified as markers to separate the histopathological subtypes as either invasive ductal cancer or invasive lobular cancer. Conclusion: In recent years, proteomic methods have rapidly become widespread in breast cancer research. This study revealed the pattern of a group of proteins that were not previously identified and are recommended as candidate markers to diagnose metastatic progression.

Background: HeLa cell line is a reference in vitro model widely used to study processes associated with protein interactions, such as cell signaling, cell cycle progress and apoptosis, among others. However, there are limited publications that include HeLa protein profile characterization through 2D-PAGE. Objective: The aim of the present report was to describe the differences between total protein profile of HeLa cell line and subcellular fractions obtained from cytoplasm and nucleus. Methods: Total and subcellular protein fractions were obtained through liquid nitrogen lysis and commercial kit, respectively. Extracted protein was analyzed by 2D-PAGE using the ZOOM IPGRunner system (Invitrogen®) and Image Master Platinum 7.0 (GE®) analysis software for proteome analysis. Identity prediction of spots was performed using Molecular weight (Mw) and Isoelectric point (pI) data from significant spots through Hela 2DE database comparison. Results: When the integrity of proteins was assessed by SDS-PAGE running, degradation of protein bands was not observed in the gels. In cytoplasmic and Nuclear fractions 324 and 284 spots were detected, versus 202 spots detected in total protein. Subcellular protein profiles also had differences in expression levels, improving the sensitivity of 2D-PAGE. Particularly, in gels of subcellular fractions was found a higher abundance of low molecular weight spots (below 35 kDa) compared to total protein profile. Conclusion: This report is the first description of HeLa cytoplasmic protein profile characterized by 2D-PAGE approach. Furthermore, the present results will be useful for further research involving protein analysis in this cellular model.

Background: Formosan Subterranean termites, Coptotermes formosanus Shiraki are sustaining in microbe-rich environment of the nest. The successful foraging and survival of termites within the nest revealed the adaptation of exceptional host-defence mechanism. There is an inherent need to unravel termites immune defence mechanism for knowledgeable host-pathogen understanding. Objective: Comparative protein expression pattern among uninfected and immunized Coptotermes formosanus Shiraki workers was explored for the first time to gain better understanding of host immune response to entomopathogenic fungi including Metarhizium anisopliae and Beauveria bassiana. Method: In this study, we analyzed the immune-related proteomic profile of C. formosanus Shiraki workers infected with entomopathogenic fungi including M. anisopliae and B. bassiana. After immunization confirmation by antifungal activity bioassays, homogenates were fractionated by cation exchange chromatography. Antifungal fractions were further analyzed by two-dimensional gel electrophoresis. Results: We obtained approximately 846 protein spots from uninfected, 709 from workers infected with M. anisopliae and 776 from B. bassiana. A total of 170 peptide fragments from 44 spots were identified to be immune-related by MALDI/TOF/MS. Among them, 20 proteins matched with sequences of C. formosanus. Identified immune related proteins trigger Toll and JAK-STAT pathways and were categorized into six types: five of them were pattern recognition receptors, five proteins were signal modulators, five of them involved in signal transduction, two effectors, four antioxidants and eleven other immune related proteins. Conclusion: Identified immune-related proteins indicate the existence of sophisticated immune mechanism against each pathogen and provide more information for further comprehension on the molecular mechanism of disease resistance among termites.

Background: Metastasis often happened in colorectal cancer patients. It is still unclear on the metastatic mechanism on colorectal cancer. Hence, we used a proteomic method to find the multiplex markers associated with metastasis. The colorectal cancer cell lines RKO and HT29 had been identified as the hepatic metastasis model in vitro. Method: Here, we compared the two cell proteome profiles and found some new molecular events of CRC metastasis. Using iTRAQ based proteomics method, we identified 1985 specific proteins, out of which 212 were found to be significantly changed in two cell lines. 28 candidate genes were confirmed by Q-PCR and 9 candidate proteins were further validated by western blot. Results: Bioinformatics analysis revealed the altered proteins played roles in actin cytoskeleton, focal adhesion and so on. KEGG analysis of the altered proteins indicated several signal pathways related to tumor invasion and metastasis. The expression of some genes was related to epigenetic changes. These results may supply an perspicacity with some new molecular biomarkers development in colorectal cancer metastasis. Conclusion: In a word, this study had identify several novel moleculars for CRC metastasis and development.