Current Proteomics - Volume 18, Issue 1, 2021

Aim: The purpose of this study was to screen the bacteria producing cellulase enzymes and their bioinformatics studies. Background: Cellulose is a long-chain polymer of glucose that hydrolyzes by cellulases to glucose molecules. In order to design the new biotechnological applications, some strategies have been used as increasing the efficiency of enzyme production, generating cost-effective enzymes, producing stable enzymes and identification of new strains. Objective: On the other hand, some bacteria special features have made them suitable candidates for the identification of the new source of enzymes. In this regard, some native strains of bacteria were screened. Methods: These bacteria were grown on a culture containing the liquid M9 media containing CMC to ensure the synthesis of cellulase. The formation of a clear area in the culture medium indicated decomposition of cellulose. In the following, the DNA of these bacteria were extracted and their 16S rDNA genes were amplified. Result: The results show that nine samples were able to synthesize cellulase. In following, these strains were identified using 16S rDNA. The results show that these screened bacteria belonged to the Bacillus sp., Alcaligenes sp., Alcaligenes sp., and Enterobacter sp. Conclusion: The enzyme activity analysis shows that the Bacillus toyonensis, Bacillus sp. strain XA15-411 Bacillus cereus have produced the maximum yield of cellulases. However, these amounts of enzyme production in these samples are not proportional to their growth rate. As the bacterial growth chart within 4 consecutive days shows that the Alcaligenes sp. Bacillus cereus, Bacillus toyonensis, Bacillus sp. strain XA15-411 have a maximum growth rate. The study of the phylogenetic tree also shows that Bacillus species are more abundant in the production of cellulase enzyme. These bioinformatics analyses show that the Bacillus species have different evolutionary relationships and evolved in different evolutionary time. However, for maximum cellulase production by this bacteria, some information as optimum temperature, optimum pH, carbon and nitrogen sources are needed for the ideal formulation of media composition. The cellulase production is closely controlled in microorganisms and the cellulase yields appear to depend on a variety of factors. However, the further studies are needed for cloning, purification and application of these new microbial cellulases in the different commercial fields as in food, detergent, and pharmaceutical, paper, textile industries and also various chemical industries. However, these novel enzymes can be further engineered through rational design or using random mutagenesis techniques.

Background: Mycobacterium tuberculosis (MTB) and Mycobacterium avium (MA) are intracellular parasitic bacteria. The biological characteristics of MA and MTB are very similar and need to be identified. Objective: The study aims to better understand how MTB survives in macrophages and the different pathogenic mechanisms of MTB and MA. Methods: The Tandem Mass Tag (TMT) and liquid chromatography-tandem mass spectrometry (LCMS/ MS) were used for analysis of the differentially expressed proteins in MTB-infected macrophages and MA-infected macrophages. Results: A total of 682 proteins were found to be differentially expressed in MTB-infected cells in comparison with MA-infected cells. Among these, 10 proteins (O60812, P06576, O43660-2, E9PL10, O00442, M0R050, Q9H8H0, Q9BSJ8, P41240 and Q8TD57-3) were down-regulated in MTB-infected cells, and M0R050, O00442, Q9H8H0, O60812 and O43660 are interactive proteins which participate in a multitude of cellular RNA processing. Conclusion: The five down-regulated proteins (M0R050, O00442, Q9H8H0, O60812 and O43660) might repress the synthesis of some resistant proteins in MTB-infected cells to promote MTB survival in macrophages.

Background: Glycation is a nonenzymatic post-translational modification process by attaching a sugar molecule to a protein or lipid molecule. It may impair the function and change the characteristic of the proteins which may lead to some metabolic diseases. In order to understand the underlying molecular mechanisms of glycation, computational prediction methods have been developed because of their convenience and high speed. However, a more effective computational tool is still a challenging task in computational biology. Methods: In this study, we showed an accurate identification tool named ABC-Gly for predicting lysine glycation sites. At first, we utilized three informative features, including position-specific amino acid propensity, secondary structure and the composition of k-spaced amino acid pairs to encode the peptides. Moreover, to sufficiently exploit discriminative features thus can improve the prediction and generalization ability of the model, we developed a two-step feature selection, which combined the Fisher score and an improved binary artificial bee colony algorithm based on the support vector machine. Finally, based on the optimal feature subset, we constructed an effective model by using the Support Vector Machine on the training dataset. Results: The performance of the proposed predictor ABC-Gly was measured with the sensitivity of 76.43%, the specificity of 91.10%, the balanced accuracy of 83.76%, the Area Under the receiveroperating characteristic Curve (AUC) of 0.9313, a Matthew’s Correlation Coefficient (MCC) of 0.6861 by 10-fold cross-validation on training dataset, and a balanced accuracy of 59.05% on independent dataset. Compared to the state-of-the-art predictors on the training dataset, the proposed predictor achieved significant improvement in the AUC of 0.156 and MCC of 0.336. Conclusion: The detailed analysis results indicated that our predictor may serve as a powerful complementary tool to other existing methods for predicting protein lysine glycation. The source code and datasets of the ABC-Gly were provided in the Supplementary File 1.

Background: Moyamoya Disease (MMD) is a rare cerebrovascular disease with a high rate of disability and mortality. Immune reactions have been implicated in the pathogenesis of MMD, however, the underlying mechanism is still unclear. Objective: To identify proteins related to MMD specially involved in the immunogenesis, we performed a proteomic study. Methods: In this work, dural tissues or plasma from 98 patients with MMD, 17 disease controls without MMD, and 12 healthy donors were included. Proteomic profiles of dural tissues from 4 MMD and 4 disease controls were analyzed by an isobaric tag for relative and absolute quantitation (iTRAQ)- based proteomics. The immune-related proteins were explored by bioinformatics and the key MMDrelated proteins were verified by western blot, multiple reaction monitoring methods, enzyme-linked immunosorbent assay, and tissue microarray. Results: 1,120 proteins were identified, and 82 MMD-related proteins were found with more than 1.5 fold difference compared with those in the control samples. Gene Ontology analysis showed that 29 proteins were immune-related. In particular, Haptoglobin (HP) was up-regulated in dural tissue and plasma of MMD samples compared to the controls, and its up-regulation was found to be sex- and MMD Suzuki grade dependent. Through Receiver Operating Characteristic (ROC) analysis, HP can well discriminate MMD and healthy donors with the Area Under the Curve (AUC) of 0.953. Conclusion: We identified the biggest protein database of the dura mater. 29 out of 82 differentially expressed proteins in MMD are involved in the immune process. Of which, HP was up-regulated in dural tissue and plasma of MMD, with sex- and MMD Suzuki grade-dependence. HP might be a potential biomarker of MMD.

Background: The cellular antiviral responses induced by interferons require some cellular protein kinase for its activation. Evidence indicated that a number of Hepatitis C Virus (HCV) proteins can repress double-stranded (ds) RNA-dependent Protein Kinase (PKR) function and help HCV to escape. However, the reports are controversial, some researchers have suggested that a region in Nonstructural 5A (NS5A) gene called Protein Kinase R-Binding Domain (PKR-BD) is associated with HCV sensitivity to the antiviral effects of Interferon (IFN). In addition, the other factor that might be associated with response to PEGylated-IFNα (Peg-IFNα) and Ribavirin (RBV) combination therapy, is IFNL4 genotypes. Objective: The aim of this study was to investigate the association between amino acid (aa) substitutions in the NS5A region and the IFNL4 genotypes in two Single Nucleotide Polymorphism (SNP) (rs8099917. rs12979860) in patients with HCV genotypes 1a and 3a. We also examined their response to combination therapy and the effect of these mutations on the function and structure of PKR-BD. Methods: Eighty-six patients with hepatitis C were recruited and follow-up for 6 months. Several tests, including alanine aminotransferase (ALT), aspartate aminotransferase (AST), viral load, IFNL4 genotyping, and PKR-BD sequencing were performed. Using several well-known and trustworthy bioinformatics tools, sequences were analyzed to define physio-chemical properties, structural features, immune epitopes and protein-protein interaction. Results: Of the 86 patients, 65.1% had high viral load at baseline, 64% had CT genotype for rs12979860 and 57% had GT genotype for rs8099917. Several aa residues changes were found in the PKR-BD region. We could not find any link between mutations in the PKR-BD region and different genotypes of IFNL4 in response to antiviral therapy. Regardless of pI, PKR-BD 1a and 3a showed similar physio-chemical properties, and 2 phosphorylation sites and one glycosylation site were estimated for both PKR-BD 1a and 3a. Trustworthy software were employed in order to predict B-cell epitopes, 3 regions (6-17, 26-32, 34-41) were found for both proteins, indicating a huge potential of PKR-BD protein to induce humoral immune system. Docking analysis determined non-responder sequences in both 1a and 3a genotypes to have higher energy value and are more compatible with PKR. Conclusion: To sum up, our results could not determine any significant relationship between mutations of PKR-BD and genotypes of IFNL4 with other factors; ALT, AST, viral load. However, docking results showed strengthened interaction between PKR-BD and PKR in non-responders that could have a momentous impact on the illness severity.

Aim: We aimed to identify new plasma biomarkers for the diagnosis of Pulmonary Tuberculosis (PTB). Background: Tuberculosis is an ancient infectious disease that remains one of the major global health problems. Until now, effective, convenient, and affordable methods for diagnosis of PTB were still lacking. Objective: This study focused on constructing a label-free LC-MS/MS-based comparative proteomics between six tuberculosis patients and six healthy controls to identify Differentially Expressed Proteins (DEPs) in plasma. Methods: To reduce the influences of high-abundant proteins, albumin and globulin were removed from plasma samples using affinity gels. Then DEPs from the plasma samples were identified using a label-free Quadrupole-Orbitrap LC-MS/MS system. The results were analyzed by the protein database search algorithm SEQUEST-HT to identify mass spectra to peptides. The predictive abilities of combinations of host markers were investigated by General Discriminant Analysis (GDA), with Leave-One-Out Cross- Validation (LOOCV). Results: A total of 572 proteins were identified and 549 proteins were quantified. The threshold for DEPs was set as adjusted p-value< 0.05 and fold change ≥1.5 or ≤0.6667, 32 DEPs were found. ClusterVis, TBtools, and STRING were used to find new potential biomarkers of PTB. Six proteins, LY6D, DSC3, CDSN, FABP5, SERPINB12, and SLURP1, which performed well in the LOOCV method validation, were termed as potential biomarkers. The percentage of cross-validated grouped cases correctly classified and original grouped cases correctly classified is greater than or equal to 91.7%. Conclusion: We successfully identified five candidate biomarkers for immunodiagnosis of PTB in plasma, LY6D, DSC3, CDSN, SERPINB12, and SLURP1. Our work supported this group of proteins as potential biomarkers for PTB, and be worthy of further validation.

Background: Mechanisms underlying yak adaptation to high-altitude environments have been investigated at the levels of morphology, anatomy, physiology, genome and transcriptome, but have not been explored at the proteome level. Objective: The protein profiles were compared between yak and cattle to explore molecular mechanisms underlying yak adaptation to high altitude conditions. Methods: In the present study, an antibody microarray chip was developed, which included 6,500 mouse monoclonal antibodies. Immunoprecipitation and mass spectrometry were performed on 12 selected antibodies which showed that the chip was highly specific. Using this chip, muscle tissue proteome was compared between yak and cattle, and 12 significantly Differentially Expressed Proteins (DEPs) between yak and cattle were identified. Their expression levels were validated using Western blot. Results: Compared with cattle, higher levels of Rieske Iron-Sulfur Protein (RISP), Cytochrome C oxidase subunit 4 isoform 1, mitochondrial (COX4I1), ATP synthase F1 subunit beta (ATP5F1B), Sarcoplasmic/ Endoplasmic Reticulum Calcium ATPase1 (SERCA1) and Adenosine Monophosphate Deaminase1 (AMPD1) in yak might improve oxygen utilization and energy metabolism. Pyruvate Dehydrogenase protein X component (PDHX) and Acetyltransferase component of pyruvate dehydrogenase complex (DLAT) showed higher expression levels and L-lactate dehydrogenase A chain (LDHA) showed lower expression level in yak, which might help yak reduce the accumulation of lactic acid. In addition, higher expression levels of Filamin C (FLNC) and low levels of AHNAK and Four and a half LIM domains 1 (FHL1) in yak might reduce the risks of pulmonary arteries vasoconstriction, remodeling and hypertension. Conclusion: Overall, the present study reported the differences in protein profile between yak and cattle, which might be helpful to further understand molecular mechanisms underlying yak adaptation to high altitude environments.

Background: The soybean seed’s physiological maturity (R7) period is an extraordinary period for the formation of seed vigor. However, how proteins and their related metabolic pathways in seed and leaf change during seed physiological maturity is still not fully understood. Methods: In the present study, using a pair of pre-harvest seed deterioration-sensitive and -resistant soybean cultivars Ningzhen No. 1 and Xiangdou No. 3, the changes were investigated through analyzing leaf, cotyledon and embryo at the levels of protein, ultrastructure, and physiology and biochemistry. Results: Soybean cultivars with stronger photosynthetic capacity in leaf, higher nutrients accumulation and protein biosynthesis in cotyledon, as well as stronger resistant-pathogen ability and cell stability in embryo during seed physiological maturity, would produce higher vitality seeds. Conclusion: Such a study allows us to further understand the changes at protein, ultrastructure, and physiology and biochemistry levels in developing seeds during the physiological maturity and provide a theoretical basis for cultivating soybean cultivars with higher seed vigor.

Background: The female Aedes aegypti mosquito is a vector of several arthropod-borne viruses, such as Mayaro, Dengue, Chikungunya, Yellow Fever, and Zika. These viruses cause the death of at least 600000 people a year and temporarily disable several million more around the world. Up to date, there are no effective prophylactic measures that would prevent the contact and bite of this arthropod and, therefore, its consequential contagion. Objective: The objective of the present study was to search for the regularities of the proteins expressed by these five viruses, at residues level, and obtain a “bioinformatic fingerprint” to select them. Methods: We used two bioinformatic systems, our in-house bioinformatic system named Polarity Index Method^® (PIM^®) supported at residues level, and the commonly used algorithm for the prediction of intrinsic disorder predisposition, PONDR^® FIT. We applied both programs to the 29 proteins that express the five groups of arboviruses studied, and we calculated for each of them their Polarity Index Method^® profile and their intrinsic disorder predisposition. This information was then compared with analogous information for other protein groups, such as proteins from bacteria, fungi, viruses, and cell-penetrating peptides from the UniProt database, and a set of intrinsically disordered proteins. Once the “fingerprint” of each group of arboviruses was obtained, these “fingerprints” were searched among the 559228 “reviewed” proteins from the UniProt database. Results: In total, 1736 proteins were identified from the 559228 “reviewed” proteins from the UniProt database, with similar “PIM^® profile” to the 29 mutated proteins that express the five groups of arboviruses. Conclusion: We propose that the “PIM^® profile” of characterization of proteins might be useful for the identification of proteins expressed by arthropod-borne viruses transmitted by Aedes aegypti mosquito.