Current Genomics - Volume 22, Issue 8, 2021

SARS-CoV-2 pathogenesis has been recently extended to human central nervous system (CNS), in addition to nasopharyngeal truck, eye, lung and gut. The recent literature highlights that some SARS-CoV-2 spike glycoprotein regions homologous to neurotoxin-like peptides might bind to human nicotinic Acetyl-Choline Receptors (nAChRs). Spike-nAChR interaction can probably cause dysregulation of CNS and cholinergic anti-inflammatory pathways and uncontrolled immune-response, both associated to a severe COVID-19 pathophysiology. Herein, we hypothesize that inside the Open Reading Frame (ORF) region of spike glycoprotein, the RNA polymerase can translate small neurotoxic peptides by means of a “jumping mechanism” already demonstrated in other coronaviruses. These small peptides can bind the snAChRs instead of Spike glycoproteins. A striking homology occurred between these small peptides observed by sequence retrieval and proteins alignment. Acting as nAChRs antagonists, these small peptides (conotoxins) could be the explanation for the extrapulmonary clinical manifestations (neurological, hemorrhagic and thrombotic expressions, the prolonged apnea, the cardiocirculatory collapse, the heart arrhythmias, the ventricular tachycardia, the body temperature alteration, the electrolyte K+ imbalance and finally the significant reduction of butyryl cholinesterase (BuChE) plasma levels, as observed in COVID-19 patients. Several factors might induce the expression of these small peptides, including microbiota. The main hypothesis regarding the presence of these small peptides opens a new scenario on the etiology of COVID-19 clinical symptoms observed so far, including the neurological manifestations.

Background: Recent development in neuroimaging and genetic testing technologies have made it possible to measure pathological features associated with Alzheimer's disease (AD) in vivo. Mining potential molecular markers of AD from high-dimensional, multi-modal neuroimaging and omics data will provide a new basis for early diagnosis and intervention in AD. In order to discover the real pathogenic mutation and even understand the pathogenic mechanism of AD, lots of machine learning methods have been designed and successfully applied to the analysis and processing of large-scale AD biomedical data. Objective: To introduce and summarize the applications and challenges of machine learning methods in Alzheimer's disease multi-source data analysis. Methods: The literature selected in the review is obtained from Google Scholar, PubMed, and Web of Science. The keywords of literature retrieval include Alzheimer's disease, bioinformatics, image genetics, genome-wide association research, molecular interaction network, multi-omics data integration, and so on. Conclusion: This study comprehensively introduces machine learning-based processing techniques for AD neuroimaging data and then shows the progress of computational analysis methods in omics data, such as the genome, proteome, and so on. Subsequently, machine learning methods for AD imaging analysis are also summarized. Finally, we elaborate on the current emerging technology of multi-modal neuroimaging, multi-omics data joint analysis, and present some outstanding issues and future research directions.

Background: A newly emerging novel coronavirus appeared and rapidly spread worldwide and World Health Organization declared a pandemic on March 11, 2020. The roles and characteristics of coronavirus have captured much attention due to its power of causing a wide variety of infectious diseases, from mild to severe, on humans. The detection of the lethality of human coronavirus is key to estimate the viral toxicity and provide perspectives for treatment. Methods: We developed an alignment-free framework that utilizes machine learning approaches for an ultra-fast and highly accurate prediction of the lethality of human-adapted coronavirus using genomic sequences. We performed extensive experiments through six different feature transformation and machine learning algorithms combining digital signal processing to identify the lethality of possible future novel coronaviruses using existing strains. Results: The results tested on SARS-CoV, MERS-CoV and SARS-CoV-2 datasets show an average 96.7% prediction accuracy. We also provide preliminary analysis validating the effectiveness of our models through other human coronaviruses. Our framework achieves high levels of prediction performance that is alignment-free and based on RNA sequences alone without genome annotations and specialized biological knowledge. Conclusion: The results demonstrate that, for any novel human coronavirus strains, this study can offer a reliable real-time estimation for its viral lethality.

Background: Immune and skeletal systems physiologically and pathologically interact with each other. Immune and skeletal diseases may share potential pleiotropic genetics factors, but the shared specific genes are largely unknown. Objective: This study aimed to investigate the overlapping genetic factors between multiple diseases (including rheumatoid arthritis (RA), psoriasis, osteoporosis, osteoarthritis, sarcopenia, and fracture). Methods: The canonical correlation analysis (metaCCA) approach was used to identify the shared genes for six diseases by integrating genome-wide association study (GWAS)-derived summary statistics. The versatile Gene-based Association Study (VEGAS2) method was further applied to refine and validate the putative pleiotropic genes identified by metaCCA. Results: About 157 (p<8.19E-6), 319 (p<3.90E-6), and 77 (p<9.72E-6) potential pleiotropic genes were identified shared by two immune diseases, four skeletal diseases, and all of the six diseases, respectively. The top three significant putative pleiotropic genes shared by both immune and skeletal diseases, including HLA-B, TSBP1, and TSBP1-AS1 (p

Background: Abiotic stresses affect plants in several ways and as such, phytohormones such as abscisic acid (ABA) play an important role in conferring tolerance towards these stresses. Hence, to comprehend the role of ABA and its interaction with receptors of the plants, a thorough investigation is essential. Aim: The current study aimed to identify the ABA receptors in Oryza sativa, to find the receptor that binds best with ABA and to examine the mutations present to help predict better binding of the receptors with ABA. Methods: Protein sequences of twelve PYL (Pyrabactin resistance 1) and seven PP2C (type 2C protein phosphatase) receptors were retrieved from the Rice Annotation Project database and their 3D structures were predicted using RaptorX. Protein-ligand molecular docking studies between PYL and ABA were performed using AutoDock 1.5.6, followed by 100ns molecular dynamic simulation studies using Desmond to determine the acceptable conformational changes after docking via root mean square deviation RMSD plot analysis. Protein-protein docking was then carried out in three sets: PYL-PP2Cs, PYL-ABA-PP2C and PYL(mut)-ABA-PP2C to scrutinize changes in structural conformations and binding energies between complexes. The amino acids of interest were mapped at their respective genomic coordinates using SNP-seek database to ascertain if there were any naturally occurring single nucleotide polymorphisms (SNPs) responsible for triggering rice PYLs mutations. Results: Initial protein-ligand docking studies revealed good binding between the complexes, wherein PYL6-ABA complex showed the best energy of -8.15 kcal/mol. The 100ns simulation studies revealed changes in the RMSD values after docking, indicating acceptable conformational changes. Furthermore, mutagenesis study performed at specific PYL-ABA interacting residues followed by downstream PYL(mut)-ABA-PP2C protein-protein docking results after induction of mutations demonstrated binding energy of -8.17 kcal/mol for PP2C79-PYL11-ABA complex. No naturally occurring SNPs that were responsible for triggering rice PYL mutations were identified when specific amino acid coordinates were mapped at respective genomic coordinates. Conclusion: Thus, the present study provides valuable insights on the interactions of ABA receptors in rice and induced mutations in PYL11 that can enhance the downstream interaction with PP2C.

Background and objective: Intraoperative hypotension is a common complication in general anesthesia that could result in different serious complications particularly in elderly patients. This Randomized Clinical Trial (RCT) aims to determine effective continuous infusion rate of norepinephrine to prevent intraoperative hypotension during spinal surgery under general anesthesia in elderly patients. Methods: This RCT was conducted on elderly patients (n= 108) undergoing general anesthesia for posterior lumbar spinal fusion. The patients were randomly divided into 0.030, 0.060, and 0.090 μg.kg-1.min-1 groups of norepinephrine infusion rates. The outcomes were assessed at entrance to operation room (T0), 15 mins after anesthesia induction (T1), 60 mins following surgery (T2), and immediately after surgery (T3). The intraoperative and postoperative complications and rehabilitation outcomes were comparatively assessed. Results: All three groups significantly reduced the incidence of delayed wound healing (0.030 vs. 0.060 vs. 0.090 μg.kg-1.min-1; 33.3% vs. 10% vs. 10%, P=0.024) and wound infection (26.7% vs. 6.7% vs. 6.7%, P=0.031). Intraoperative total fluid volume and colloids volume in the 0.030 group were significantly higher than 0.060 and 0.090 groups (P=0.005, P=0.003, and P=0.01, respectively). The 0.060 and 0.090 groups significantly increased mean-arterial-pressure than the 0.030 group at T2 and T3. Both 0.060 and 0.090 infusion rates significantly reduced intraoperative hypotension than 0.030 dosage (P=0.01 and P=0.003, respectively). The bradycardia incidence in the 0.090 group was significantly higher than the 0.030 (P=0.026) and 0.060 groups (P=0.038). The 0.060 group decreased the first intake by 1.4 hours (P=0.008) and first flatus by 1.1 hours (P=0.004) and postoperative hospital stay by 1 day (P=0.066). Conclusion: The 0.060 µg·kg-1·min-1 norepinephrine infusion combined with goal-directed fluid therapy exhibited adequate intraoperative management and postoperative outcomes.