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Plasmodium infection is a health challenge. Although, antiplasmodial drugs kill the parasites, information on the effects of infection and drugs on the expression of some genes is limited.Malaria was induced in two different studies using NK65 (chloroquine-susceptible, study 1), and ANKA (chloroquine-resistant, study 2) strains of Plasmodium berghei in 30 male Swiss mice (n = 5) in each study. Mice orally received 10 mL/kg distilled water, (infected control), Mefloquine (MF) (10 mg/kg), MF and Curcumin (CM) (25 mg/kg), MF and CM (50 mg/kg), CM (25 mg/kg) and CM (50 mg/kg). Five mice (un-infected) were used as the control. After treatment, total Ribonucleic acid (RNA) was isolated from liver and erythrocytes while Deoxyribonucleic acid (DNA)-free RNA were converted to cDNA. Polymerase Chain Reaction (PCR) amplification was performed and relative expressions of FIKK12, AQP3, P38 MAPK, NADH oxidoreductase, and cytochrome oxidase expressions were determined. Markers of glycolysis, toxicity and antioxidants were determined using ELISA assays. While the expression of FIKK12 was blunted by MF in the susceptible study, co-treatment with curcumin (25 mg/kg) yielded the same results in the chloroquine-resistant study. Similar results were obtained on AQP3 in both studies. Curcumin decreased P38 MAPK in both studies. Plasmodium infection decreased NADH oxidoreductase and cytochrome oxidase but mefloquine-curcumin restored the expression of these genes. While glycolysis and toxicity were inhibited, antioxidant systems improved in the treated groups. Curcumin is needed for effective therapeutic efficacy and prevention of toxicity. Plasmodium infection and treatment modulate the expressions of some genes in the host. Curcumin combination with mefloquine modulates the expression of some genes in the host.

Abstract Background An efficient supply of reducing equivalent is essential for chemicals production by engineered microbes. In phototrophic microbes, the NADPH generated from photosynthesis is the dominant form of reducing equivalent. However, most dehydrogenases prefer to utilize NADH as a cofactor. Thus, sufficient NADH supply is crucial to produce dehydrogenase-derived chemicals in cyanobacteria. Photosynthetic electron is the sole energy source and excess electrons are wasted in the light reactions of photosynthesis. Results Here we propose a novel strategy to direct the electrons to generate more ATP from light reactions to provide sufficient NADH for lactate production. To this end, we introduced an electron transport protein-encoding gene omcS into cyanobacterium Synechococcus elongatus UTEX 2973 and demonstrated that the introduced OmcS directs excess electrons from plastoquinone (PQ) to photosystem I (PSI) to stimulate cyclic electron transfer (CET). As a result, an approximately 30% increased intracellular ATP, 60% increased intracellular NADH concentrations and up to 60% increased biomass production with fourfold increased d-lactate production were achieved. Comparative transcriptome analysis showed upregulation of proteins involved in linear electron transfer (LET), CET, and downregulation of proteins involved in respiratory electron transfer (RET), giving hints to understand the increased levels of ATP and NADH. Conclusions This strategy provides a novel orthologous way to improve photosynthesis via enhancing CET and supply sufficient NADH for the photosynthetic production of chemicals.

Living organisms receive necessary energy substances directly from cellular respiration. The completion of electron storage and transportation requires the process of cellular respiration with the aid of electron transport chains. Therefore, the work of deciphering electron transport proteins is inevitably needed. The identification of these proteins with high performance has a prompt dependence on the choice of methods for feature extraction and machine learning algorithm. In this study, protein sequences served as natural language sentences comprising words. The nominated word embedding-based feature sets, hinged on the word embedding modulation and protein motif frequencies, were useful for feature choosing. Five word embedding types and a variety of conjoint features were examined for such feature selection. The support vector machine algorithm consequentially was employed to perform classification. The performance statistics within the 5-fold cross-validation including average accuracy, specificity, sensitivity, as well as MCC rates surpass 0.95. Such metrics in the independent test are 96.82, 97.16, 95.76 percent, and 0.9, respectively. Compared to state-of-the-art predictors, the proposed method can generate more preferable performance above all metrics indicating the effectiveness of the proposed method in determining electron transport proteins. Furthermore, this study reveals insights about the applicability of various word embeddings for understanding surveyed sequences. [ABSTRACT FROM AUTHOR]

Background: An efficient supply of reducing equivalent is essential for chemicals production by engineered microbes. In phototrophic microbes, the NADPH generated from photosynthesis is the dominant form of reducing equivalent. However, most dehydrogenases prefer to utilize NADH as a cofactor. Thus, sufficient NADH supply is crucial to produce dehydrogenase-derived chemicals in cyanobacteria. Photosynthetic electron is the sole energy source and excess electrons are wasted in the light reactions of photosynthesis. Results: Here we propose a novel strategy to direct the electrons to generate more ATP from light reactions to provide sufficient NADH for lactate production. To this end, we introduced an electron transport protein-encoding gene omcS into cyanobacterium Synechococcus elongatus UTEX 2973 and demonstrated that the introduced OmcS directs excess electrons from plastoquinone (PQ) to photosystem I (PSI) to stimulate cyclic electron transfer (CET). As a result, an approximately 30% increased intracellular ATP, 60% increased intracellular NADH concentrations and up to 60% increased biomass production with fourfold increased d-lactate production were achieved. Comparative transcriptome analysis showed upregulation of proteins involved in linear electron transfer (LET), CET, and downregulation of proteins involved in respiratory electron transfer (RET), giving hints to understand the increased levels of ATP and NADH. Conclusions: This strategy provides a novel orthologous way to improve photosynthesis via enhancing CET and supply sufficient NADH for the photosynthetic production of chemicals. [ABSTRACT FROM AUTHOR]

In several years, deep learning is a modern machine learning technique using in a variety of fields with state-of-the-art performance. Therefore, utilization of deep learning to enhance performance is also an important solution for current bioinformatics field. In this study, we try to use deep learning via convolutional neural networks and position specific scoring matrices to identify electron transport proteins, which is an important molecular function in transmembrane proteins. Our deep learning method can approach a precise model for identifying of electron transport proteins with achieved sensitivity of 80.3%, specificity of 94.4%, and accuracy of 92.3%, with MCC of 0.71 for independent dataset. The proposed technique can serve as a powerful tool for identifying electron transport proteins and can help biologists understand the function of the electron transport proteins. Moreover, this study provides a basis for further research that can enrich a field of applying deep learning in bioinformatics. © 2017 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Background: Cellular respiration is a catabolic pathway for producing adenosine triphosphate (ATP) and is the most efficient process through which cells harvest energy from consumed food. When cells undergo cellular respiration, they require a pathway to keep and transfer electrons (i.e., the electron transport chain). Due to oxidation-reduction reactions, the electron transport chain produces a transmembrane proton electrochemical gradient. In case protons flow back through this membrane, this mechanical energy is converted into chemical energy by ATP synthase. The convert process is involved in producing ATP which provides energy in a lot of cellular processes. In the electron transport chain process, flavin adenine dinucleotide (FAD) is one of the most vital molecules for carrying and transferring electrons. Therefore, predicting FAD binding sites in the electron transport chain is vital for helping biologists understand the electron transport chain process and energy production in cells. Results: We used an independent data set to evaluate the performance of the proposed method, which had an accuracy of 69.84 %. We compared the performance of the proposed method in analyzing two newly discovered electron transport protein sequences with that of the general FAD binding predictor presented by Mishra and Raghava and determined that the accuracy of the proposed method improved by 9–45 % and its Matthew's correlation coefficient was 0.14–0.5. Furthermore, the proposed method enabled reducing the number of false positives significantly and can provide useful information for biologists. Conclusions: We developed a method that is based on PSSM profiles and SAAPs for identifying FAD binding sites in newly discovered electron transport protein sequences. This approach achieved a significant improvement after we added SAAPs to PSSM features to analyze FAD binding proteins in the electron transport chain. The proposed method can serve as an effective tool for predicting FAD binding sites in electron transport proteins and can help biologists understand the functions of the electron transport chain, particularly those of FAD binding sites. We also developed a web server which identifies FAD binding sites in electron transporters available for academics. [ABSTRACT FROM AUTHOR]

In order to construct a supramolecular architecture composed of an electron transport protein and oligonucleotide, two complementary oligonucleotides were appended to cytochrome b562 (b562) and its cofactor heme as ‘tab for sticking’. His 63 of b562, located at the opposite side of the heme crevice was replaced with Cys to generate b562-SH. A 24-mer linker oligonucleotide (LO) was successfully linked through the Cys 63 residue to produce b562-LO. Moreover, the complementary oligonucleotide to LO (cLO) was appended to the heme propionate to create heme-cLO. The apoprotein of b562-SH was immobilized on the sensor surface by disulfide exchange reaction. The heme-cLO was incorporated into the immobilized apo b562-SH by the heme reconstitution, and then b562-LO was integrated on that surface by hybridization. All the self-assembly processes of these molecules by non-covalent bonding interactions were confirmed with the surface plasmon resonance biosensor. The utilization of DNA hybridization and/or apoprotein–cofactor interaction may allow a new strategy to construct a molecular electronic device. [Copyright &y& Elsevier]