Entropy-Driven, Integrative Bioinformatics Approaches Reveal the Recent Transmission of the Monkeypox Virus from Nigeria to Multiple Non-African Countries.

Monkeypox virus (mpox) has currently affected multiple countries around the globe. This study aims to analyze how the virus spread globally. The study uses entropy-driven bioinformatics in five directions to analyze the 60 full-length complete genomes of mpox. We analyzed the topological entropy distribution of the genomes, principal component analysis (PCA), the dissimilarity matrix, entropy-driven phylogenetics, and genome clustering. The topological entropy distribution showed genome positional entropy. We found five clusters of the mpox genomes through the two PCA, while the three PCA elucidated the clustering events in 3D space. The clustering of genomes was further confirmed through the dissimilarity matrix and phylogenetic analysis which showed the bigger size of Cluster 1 and size similarity between Clusters 2 and 4 as well as Clusters 3 and 5. It corroborated with the phylogenetics of the genomes, where Cluster 1 showed clear segregation from the other four clusters. Finally, the study concluded that the spreading of the mpox is likely to have originated from African countries to the rest of the non-African countries. Overall, the spreading and distribution of the mpox will shed light on its evolution and pathogenicity of the mpox and help to adopt preventive measures to stop the spreading of the virus.

Determination of k-mer density in a DNA sequence and subsequent cluster formation algorithm based on the application of electronic filter.

We describe a novel algorithm for information recovery from DNA sequences by using a digital filter. This work proposes a three-part algorithm to decide the k-mer or q-gram word density. Employing a finite impulse response digital filter, one can calculate the sequence's k-mer or q-gram word density. Further principal component analysis is used on word density distribution to analyze the dissimilarity between sequences. A dissimilarity matrix is thus formed and shows the appearance of cluster formation. This cluster formation is constructed based on the alignment-free sequence method. Furthermore, the clusters are used to build phylogenetic relations. The cluster algorithm is in good agreement with alignment-based algorithms. The present algorithm is simple and requires less time for computation than other currently available algorithms. We tested the algorithm using beta hemoglobin coding sequences (HBB) of 10 different species and 18 primate mitochondria genome (mtDNA) sequences.

Understanding the molecular evolution of tiger diversity through DNA barcoding marker ND4 and NADH dehydrogenase complex using computational biology.

BACKGROUND: Currently, Tigers (the top predator of an ecosystem) are on the list of endangered species. Thus the need is to understand the tiger's population genomics to design their conservation strategies. OBJECTIVE: We analyzed the molecular evolution of tiger diversity using NADH dehydrogenase subunit 4 (ND4), a significant electron transport chain component. METHODS: We have analyzed nucleotide composition and distribution pattern of ND genes, molecular evolution, evolutionary conservation pattern and conserved blocks of NADH, phylogenomics of ND4, and estimating species divergence, etc., using different bioinformatics tools and software, and MATLAB programming and computing environment. RESULTS: The nucleotide composition and distribution pattern of ND genes in the tiger genome demonstrated an increase in the number of adenine (A) and a lower trend of A+T content in some place of the distribution analysis. However, the observed distributions were not significant (P > 0.05). Evolutionary conservation analysis showed three highly align blocks (186 to 198, 406 to 416, and 527 to 545). On mapping the molecular evolution of ND4 among model species (n = 30), we observed its presence in a broader range of species. ND4 based molecular evolution of tiger diversity and time divergence for a tiger (20 different other species) shows that genus Panthera originated more or less at a similar time. CONCLUSIONS: The nucleotide composition and nucleotide distribution pattern of tiger ND genes showed the evolutionary pattern and origin of tiger and Panthera lineage concerning the molecular clock, which will help to understand their adaptive evolution.

The novel strategies for next-generation cancer treatment: miRNA combined with chemotherapeutic agents for the treatment of cancer.

Medical practitioners are recommending combination therapy in cancer for its various advantages. Combination therapy increases the efficacy of treatment due to its synergistic effects in cancer treatment. In this post-genomic era, microRNAs (miRNAs) are receiving attention for their role in human disease and disease therapy. In this review, we discuss the combination of miRNAs and chemotherapeutic agents for cancer treatment. Moreover, we attempted to portray the role of miRNAs in cancer therapy; outline combination therapy, especially chemo-combination therapy, and discuss the basis for miRNA-based chemo-combination therapies and chemo-combination therapy with miRNA for cancer treatment.

Novel biomarker for prostate cancer diagnosis by MRS.

Magnetic resonance spectroscopy (MRS) is a prospective tool for characterization of the chemical composition of tissues. In vivo MRS can be used for metabolite profiling in the prostate tissue to discriminate non-invasively carcinomas and healthy prostate. In this article different prostate metabolites have been discussed and how to exploit the MRS technique for the estimation of metabolites in prostate tissue quantitatively is elucidated. Choline, citrate, creatine, myo-inositol metabolites can be considered as biomarker for localization of malignancy in the prostate and their ratio can be used for the determination of cancer tissue in the prostate gland.

Mapping the structural topology of IRS family cascades through computational biology.

Structural topologies of proteins play significant roles in analyzing their biological functions. Converting the amino acid data in a protein sequence into structural information to outline the function of a protein is a major challenge in post-genome research which can add an extra room in understanding the protein sequence-structure-function relationships. In this study, we performed a comprehensive bioinformatics analysis of structural topology of the IRS family members such as IRS-1, IRS-2, IRS-3, IRS-4, IRS-5 and IRS-6. Based on this assessment, we found that IRS-2 encloses the highest number of α helices, ß sheets and ß turns in the secondary structure topology compared to IRS-1 and IRS-6. IRS family members are rich in serine or leucine residues. Among the IRS family members, the highest percentage of serine and leucine was observed in IRS-1 (15%) and IRS-5 (10%), respectively. Notably, the highest number of disulphide bonds was observed in IRS-1 (10) which is responsible for structural stability of the protein. Hydrogen bond pattern in α helices and ß sheet was recorded in IRS-1, IRS-2 and IRS-6. By conservation analysis, the longest protein IRS-3 was found to be highly conserved among the IRS family members. The cluster of sequence logo present in the N terminus of these cascades was noted, and highly conserved residues in N-terminal region help in the formation of the two highly conserved domains such as PH domain and PTB domain. Results generated from this analysis will be more beneficial to researchers in understanding more about insulin signalling mechanism(s) as well as insulin resistance pathway. We discuss here that bioinformatics tools utilized in this study can play a vital role in addressing the complexity of structural topology to understand structure-function relationships in insulin signalling cascades.

Information processing in network architecture of genome controlled signal transduction circuit. A proposed theoretical explanation.

In this paper, Shannon information theory has been applied to elaborate cell signaling. It is proposed that in the cellular network architecture, four components viz. source (DNA), transmitter (mRNA), receiver (protein) and destination (another protein) are involved. The message transmits from source (DNA) to transmitter (mRNA) and then passes through a noisy channel reaching finally the receiver (protein). The protein synthesis process is here considered as the noisy channel. Ultimately, signal is transmitted from receiver to destination (another protein). The genome network architecture elements were compared with genetic alphabet L = {A, C, G, T} with a biophysical model based on the popular Shannon information theory. This study found the channel capacity as maximum for zero error (sigma = 0) and at this condition, transition matrix becomes a unit matrix with rank 4. The transition matrix will be erroneous and finally at sigma = 1 channel capacity will be localized maxima with a value of 0.415 due to the increased value at sigma. On the other hand, minima exists at sigma = 0.75, where all transition probabilities become 0.25 and uncertainty will be maximum resulting in channel capacity with the minima value of zero.

Variations of water uptake, lipid consumption, and dynamics during the germination of Sesamum indicum seed: a nuclear magnetic resonance spectroscopic investigation.

Germination in sesame seeds (Sesamum indicum L.) in water and in indole-3-acetic acid (IAA) solution is investigated with magic-angle-spinning (MAS) solid state nuclear magnetic resonance (NMR) spectroscopy, supplemented by liquid state NMR spectroscopy. The spectra show good resolution and can be assigned with sufficient confidence. The characteristic spectral peaks and relaxation rates were monitored during the entire course of germination for better understanding of the biophysical and biochemical mechanisms involved in the triphasic water uptake of the seed. A highly positive correlation is found between water uptake and lipid consumption during germination. No significant variation is observed in the relaxation times for the lipid protons during the first two stages of triphasic water uptake, while evident differences are observed for water proton relaxation rates in all stages. Although the total amount of water uptake is largely not changed as a result of IAA, the addition of IAA in seed-germination medium has shown some prominent effects on the germination process, e.g, it suppresses lipid consumption and water mobility, and it reduces the longitudinal and transverse relaxation times of lipid protons and causes a more scattered range for these parameters.