Post COVID-19 complications and follow up biomarkers.

Millions of people were infected by the coronavirus disease (COVID-19) epidemic, which left a huge burden on the care of post COVID-19 survivors around the globe. The self-reported COVID-19 symptoms were experienced by an estimated 1.3 million people in the United Kingdom (2% of the population), and these symptoms persisted for about 4 weeks from the beginning of the infection. The symptoms most frequently reported were exhaustion, shortness of breath, muscular discomfort, joint pain, headache, cough, chest pain, cognitive impairment, memory loss, anxiety, sleep difficulties, diarrhea, and a decreased sense of smell and taste in post-COVID-19 affected people. The post COVID-19 complications were frequently related to the respiratory, cardiac, nervous, psychological and musculoskeletal systems. The lungs, liver, kidneys, heart, brain and other organs had been impaired by hypoxia and inflammation in post COVID-19 individuals. The upregulation of substance "P" (SP) and various cytokines such as tumor necrosis factor-alpha (TNF-α), interleukin 6 (IL-6), interleukin 10 (IL-10), interleukin 1 beta (IL-1ß), angiotensin-converting enzyme 2 (ACE2) and chemokine C-C motif ligand 3 (CCL3) has muddled respiratory, cardiac, neuropsychiatric, dermatological, endocrine, musculoskeletal, gastrointestinal, renal and genitourinary complications in post COVID-19 people. To prevent these complications from worsening, it was therefore important to study how these biomarkers were upregulated and block their receptors.

Immunoinformatic and reverse vaccinology-based designing of potent multi-epitope vaccine against Marburgvirus targeting the glycoprotein.

Marburg virus (MARV) has been a major concern since its first outbreak in 1967. Although the deadly BSL-4 pathogen has been reported in few individuals with sporadic outbreaks following 1967, its rarity commensurate the degree of disease severity. The virus has been known to cause extreme hemorrhagic fever presenting flu-like symptoms (as implicated in COVID-19) with a 90% case fatality rate (CFR). After a number of plausible evidences, it has been observed that the virus usually originates from African fruit bat, Rousettus aegyptiacus, who themselves do not indicate any signs of illness. Thus, efforts have been made in the recent years for a universal treatment of the infection, but till date, no such vaccine or therapeutics could circumvent the viral pathogenicity. In an attempt to formulate a vaccine design computationally, we have explored the entire proteome of the virus and found a strong correlation of its glycoprotein (GP) in receptor binding and subsequent role in infection progression. The present study, explores the MARV glycoprotein GP1 and GP2 domains for quality epitopes to elicit an extended immune response design potential vaccine construct using appropriate linkers and adjuvants. Finally, the chimeric vaccine wass evaluated for its binding affinity towards the receptors via molecular docking and molecular dynamics simulation studies. The rare, yet deadly zoonotic infection with mild outbreaks in recent years has flustered an alarming future with various challenges in terms of viral diseases. Thus, our study has aimed to provide novel insights to design potential vaccines by using the predictive framework.

Mapping CircRNA-miRNA-mRNA regulatory axis identifies hsa_circ_0080942 and hsa_circ_0080135 as a potential theranostic agents for SARS-CoV-2 infection.

Non-coding RNAs (ncRNAs) can control the flux of genetic information; affect RNA stability and play crucial roles in mediating epigenetic modifications. A number of studies have highlighted the potential roles of both virus-encoded and host-encoded ncRNAs in viral infections, transmission and therapeutics. However, the role of an emerging type of non-coding transcript, circular RNA (circRNA) in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has not been fully elucidated so far. Moreover, the potential pathogenic role of circRNA-miRNA-mRNA regulatory axis has not been fully explored as yet. The current study aimed to holistically map the regulatory networks driven by SARS-CoV-2 related circRNAs, miRNAs and mRNAs to uncover plausible interactions and interplay amongst them in order to explore possible therapeutic options in SARS-CoV-2 infection. Patient datasets were analyzed systematically in a unified approach to explore circRNA, miRNA, and mRNA expression profiles. CircRNA-miRNA-mRNA network was constructed based on cytokine storm related circRNAs forming a total of 165 circRNA-miRNA-mRNA pairs. This study implies the potential regulatory role of the obtained circRNA-miRNA-mRNA network and proposes that two differentially expressed circRNAs hsa_circ_0080942 and hsa_circ_0080135 might serve as a potential theranostic agents for SARS-CoV-2 infection. Collectively, the results shed light on the functional role of circRNAs as ceRNAs to sponge miRNA and regulate mRNA expression during SARS-CoV-2 infection.

Integrated analysis to study the interplay between post-translational modifications (PTM) in hepatitis C virus proteins and hepatocellular carcinoma (HCC) development.

Many PTMs dysregulation is known to be the major cause of many cancers including HCV induced HCC. PTMs of hepatitis C virus (HCV) regions NS3/4A, NS5A and NS5B are crucial for proper protein functions and replication that directly affect the generation of infectious virus particles and completion of its life cycle. In this study, we have performed comprehensive analysis of PTMs within HCV non-structural proteins (NS3/4A, NS5A and NS5B) through bioinformatics analysis to examine post-translational crosstalk between phosphorylation, palmitoylation, methylation, acetylation and ubiquitination sites in selected viral proteins. Our analysis has revealed many highly putative PTMs sites that are also conserved among major genotypes conferring the importance of these sites. We have also analysed viral 3D structures in their modified and unmodified forms to address extent and signatures of structural changes upon PTM. This study provides evidence that PTMs induce significant conformational changes and make viral proteins more stable. To find the potential role of PTMs in HCV induced HCC, docking analysis between selected viral proteins and p38-MAPK has been performed which also confirms their strong association with HCV induced HCC. The major findings proposed that PTMs at specific sites of HCV viral proteins could dysregulate specific pathways that cause the development of HCC.

Human Coronavirus Spike Protein Based Multi-Epitope Vaccine against COVID-19 and Potential Future Zoonotic Coronaviruses by Using Immunoinformatic Approaches.

Zoonotic coronaviruses (CoV) have emerged twice and have caused severe respiratory diseases in humans. Due to the frequent outbreaks of different human coronaviruses (HCoVs), the development of a pan-HCoV vaccine is of great importance. Various conserved epitopes shared by HCoVs are reported to induce cross-reactive T-cell responses. Therefore, this study aimed to design a multi-epitope vaccine, targeting the HCoV spike protein. Genetic analysis revealed that the spike region is highly conserved among SARS-CoV-2, bat SL-CoV, and SARS-CoV. By employing the immunoinformatic approach, we prioritized 20 MHC I and 10 MHCII conserved epitopes to design a multi-epitope vaccine. This vaccine candidate is anticipated to strongly elicit both humoral and cell-mediated immune responses. These results warrant further development of this vaccine into real-world application.

Comparative in silico characterization of Klebsiella pneumoniae hypervirulent plasmids and their antimicrobial resistance genes.

BACKGROUND: The hypervirulent pathotype of Klebsiella pneumoniae (hvKp) is mainly mediated by large virulent plasmids. It seems that these hypervirulent plasmids (HVPs) are accumulating antimicrobial resistance genes (ARGs) and are turning quickly into drug-resistant hypervirulent hybrids. Therefore, molecular mechanisms involved in this convergence needs to be investigated to control their global spread. METHODS: In this study, the complete sequence of 79 non-redundant hypervirulent plasmids were retrieved from GenBank and their genetic features, hypervirulence and antimicrobial resistance patterns (AMR) as well as their putative transmission capability were compared using bioinformatics tools. RESULTS: The majority of HVPs belonged to clonal complex (CC)23, and sequence type (ST)11. IncFIB and IncHI1B were the most prevalent plasmid replicon types. Out of 79 plasmids, 78 were positive for iutA and iucA. The iucC, iucB and iucD genes were found in 77 plasmids. Almost 26% of the HVPs were potentially conjugative of which 71% carried AGRs. ARGs against beta-lactams, carbapenems, quinolones, aminoglycosides, chloramphenicols, tetracyclines and macrolides were detected in 30% of HVPs. Class 1 integron and prophage structures harboring multiple ARGs were found in eight plasmids. Insertion sequences (IS)6, IS110 and IS1380 appeared to be important genetic elements in transmission of ARGs. CONCLUSIONS: The high prevalence of iucA and iutA suggests their strong capability for rapid and accurate genetic markers for discrimination of hvKp in the laboratory. This study indicated the important role of mobile genetic elements (MGEs) in the emergence of drug-resistance in hypervirulent strains. The high prevalence of putative conjugative hybrids implies higher incidence of multidrug-resistant (MDR)-hvKp strains in near future.

Vaccinomics to Design a Multi-Epitopes Vaccine for Acinetobacter baumannii.

Antibiotic resistance (AR) is the result of microbes' natural evolution to withstand the action of antibiotics used against them. AR is rising to a high level across the globe, and novel resistant strains are emerging and spreading very fast. Acinetobacter baumannii is a multidrug resistant Gram-negative bacteria, responsible for causing severe nosocomial infections that are treated with several broad spectrum antibiotics: carbapenems, ß-lactam, aminoglycosides, tetracycline, gentamicin, impanel, piperacillin, and amikacin. The A. baumannii genome is superplastic to acquire new resistant mechanisms and, as there is no vaccine in the development process for this pathogen, the situation is more worrisome. This study was conducted to identify protective antigens from the core genome of the pathogen. Genomic data of fully sequenced strains of A. baumannii were retrieved from the national center for biotechnological information (NCBI) database and subjected to various genomics, immunoinformatics, proteomics, and biophysical analyses to identify potential vaccine antigens against A. baumannii. By doing so, four outer membrane proteins were prioritized: TonB-dependent siderphore receptor, OmpA family protein, type IV pilus biogenesis stability protein, and OprD family outer membrane porin. Immuoinformatics predicted B-cell and T-cell epitopes from all four proteins. The antigenic epitopes were linked to design a multi-epitopes vaccine construct using GPGPG linkers and adjuvant cholera toxin B subunit to boost the immune responses. A 3D model of the vaccine construct was built, loop refined, and considered for extensive error examination. Disulfide engineering was performed for the stability of the vaccine construct. Blind docking of the vaccine was conducted with host MHC-I, MHC-II, and toll-like receptors 4 (TLR-4) molecules. Molecular dynamic simulation was carried out to understand the vaccine-receptors dynamics and binding stability, as well as to evaluate the presentation of epitopes to the host immune system. Binding energies estimation was achieved to understand intermolecular interaction energies and validate docking and simulation studies. The results suggested that the designed vaccine construct has high potential to induce protective host immune responses and can be a good vaccine candidate for experimental in vivo and in vitro studies.

Innovations in Genomics and Big Data Analytics for Personalized Medicine and Health Care: A Review.

Big data in health care is a fast-growing field and a new paradigm that is transforming case-based studies to large-scale, data-driven research. As big data is dependent on the advancement of new data standards, technology, and relevant research, the future development of big data applications holds foreseeable promise in the modern day health care revolution. Enormously large, rapidly growing collections of biomedical omics-data (genomics, proteomics, transcriptomics, metabolomics, glycomics, etc.) and clinical data create major challenges and opportunities for their analysis and interpretation and open new computational gateways to address these issues. The design of new robust algorithms that are most suitable to properly analyze this big data by taking into account individual variability in genes has enabled the creation of precision (personalized) medicine. We reviewed and highlighted the significance of big data analytics for personalized medicine and health care by focusing mostly on machine learning perspectives on personalized medicine, genomic data models with respect to personalized medicine, the application of data mining algorithms for personalized medicine as well as the challenges we are facing right now in big data analytics.

Brain-protective mechanisms of autophagy associated circRNAs: Kick starting self-cleaning mode in brain cells via circRNAs as a potential therapeutic approach for neurodegenerative diseases.

Altered autophagy is a hallmark of neurodegeneration but how autophagy is regulated in the brain and dysfunctional autophagy leads to neuronal death has remained cryptic. Being a key cellular waste-recycling and housekeeping system, autophagy is implicated in a range of brain disorders and altering autophagy flux could be an effective therapeutic strategy and has the potential for clinical applications down the road. Tight regulation of proteins and organelles in order to meet the needs of complex neuronal physiology suggests that there is distinct regulatory pattern of neuronal autophagy as compared to non-neuronal cells and nervous system might have its own separate regulator of autophagy. Evidence has shown that circRNAs participates in the biological processes of autophagosome assembly. The regulatory networks between circRNAs, autophagy, and neurodegeneration remains unknown and warrants further investigation. Understanding the interplay between autophagy, circRNAs and neurodegeneration requires a knowledge of the multiple steps and regulatory interactions involved in the autophagy pathway which might provide a valuable resource for the diagnosis and therapy of neurodegenerative diseases. In this review, we aimed to summarize the latest studies on the role of brain-protective mechanisms of autophagy associated circRNAs in neurodegenerative diseases (including Alzheimer's disease, Parkinson's disease, Huntington's disease, Spinal Muscular Atrophy, Amyotrophic Lateral Sclerosis, and Friedreich's ataxia) and how this knowledge can be leveraged for the development of novel therapeutics against them. Autophagy stimulation might be potential one-size-fits-all therapy for neurodegenerative disease as per considerable body of evidence, therefore future research on brain-protective mechanisms of autophagy associated circRNAs will illuminate an important feature of nervous system biology and will open the door to new approaches for treating neurodegenerative diseases.

Discovery of Novel Inhibitors From Medicinal Plants for V-Domain Ig Suppressor of T-Cell Activation.

V-domain Ig suppressor of T cell activation (VISTA) is an immune checkpoint and is a type I transmembrane protein. VISTA is linked to immunotherapy resistance, and it is a potential immune therapeutic target, especially for triple-negative breast cancer. It expresses at a high concentration in regulatory T cells and myeloid-derived suppressor cells, and its functional blockade is found to delay tumor growth. A useful medicinal plant database for drug designing (MPD3), which is a collection of phytochemicals from diverse plant families, was employed in virtual screening against VISTA to prioritize natural inhibitors against VISTA. Three compounds, Paratocarpin K (PubChem ID: 14187087), 3-(1H-Indol-3-yl)-2-(trimethylazaniumyl)propanoate (PubChem ID: 3861164), and 2-[(5-Benzyl-4-ethyl-1,2,4-triazol-3-yl)sulfanylmethyl]-5-methyl-1,3,4-oxadiazole (PubChem ID: 6494266), having binding energies stronger than -6 kcal/mol were found to have two common hydrogen bond interactions with VISTA active site residues: Arg54 and Arg127. The dynamics of the compound-VISTA complexes were further explored to infer binding stability of the systems. Results revealed that the compound 14187087 and 6494266 systems are highly stable with an average RMSD of 1.31 Å. Further affirmation on the results was achieved by running MM-GBSA on the MD simulation trajectories, which re-ranked 14187087 as the top-binder with a net binding energy value of -33.33 kcal/mol. In conclusion, the present study successfully predicted natural compounds that have the potential to block the function of VISTA and therefore can be utilized further in experimental studies to validate their real anti-VISTA activity.

Pan-vaccinomics approach towards a universal vaccine candidate against WHO priority pathogens to address growing global antibiotic resistance.

Antimicrobial resistance (AMR) in bacterial pathogens is a major global distress. Due to the slow progress of antibiotics development and the fast pace of resistance acquisition, there is an urgent need for effective vaccines against such bacterial pathogens. In-silico approaches including pan-genomics, subtractive proteomics, reverse vaccinology, immunoinformatics, molecular docking, and dynamics simulation studies were applied in the current study to identify a universal potential vaccine candidate against the 18 multi-drug resistance (MDRs) bacterial pathogenic species from a WHO priority list. Ten non-redundant, non-homologous, virulent, and antigenic vaccine candidates were filtered against all targeted species. Nine B-cell-derived T-cell antigen epitopes which show a great affinity to the dominant HLA allele (DRB1*0101) in the human population were screened from selected vaccine candidates using immunoinformatics approaches. Screened epitopes were then used to design a multi-epitope peptide vaccine construct (MEPVC) along with ß-defensin adjuvant to improve the immunogenic properties of the proposed vaccine construct. Molecular docking and MD simulation were carried out to study the binding affinity and molecular interaction of MEPVC with human immune receptors (TLR2, TLR3, TLR4, and TLR6). The final MEPVC construct was reverse translated and in-silico cloned in the pET28a(+) vector to ensure its effectiveness. This in silico construct is expected to be helpful for vaccinologists to assess its immune protection effectiveness in vivo and in vitro to counter rising antibiotic resistance worldwide.

Clinical outcomes of maitland mobilization in patients with Myofascial Chronic Neck Pain: A randomized controlled trial.

BACKGROUND AND OBJECTIVE: Myofascial neck pain is a common musculoskeletal problem caused by presence of trigger points and local and referred pain patterns. Chronic neck pain is responsible for the involvement of joints, ligaments, fascia and connective tissue as well. The objective of this study was to assess the effect of Maitland mobilization in patients with myofascial chronic neck pain. METHODS: In this randomized, placebo treatment-controlled trial, 30 patients consecutively aged 25-45 years meeting inclusion criteria were isolated into two groups. The study group was treated with Maitland mobilization consistently for eight weeks while the control group got placebo treatment for a similar timeframe. Visual analog Scale (VAS), Neck disability index (NDI) and cervical range of motion (ROM) questionnaire was filled by patients before, intermediate and after the intervention to evaluate the severity of pain, functional ability and range of motion. RESULTS: Following eight weeks of treatment, when compared the post treatment effects of both groups, the significance value for VAS was 0.008, for NDI p=0.030, for Flexion p=0.573, for extension p=0.001, for right rotation p<0.001, for left rotation p=0.002, for right and left side bending p<0.001. CONCLUSION: The study concluded that Maitland mobilization grades (I-IV) are effective in reducing pain and improving functional level of NDI scale and the ranges of cervical spine in patients with myofascial chronic neck pain.

Inhibitory Potential of Phytochemicals on Interleukin-6-Mediated T-Cell Reduction in COVID-19 Patients: A Computational Approach.

BACKGROUND: A recent COVID-19 pandemic has resulted in a large death toll rate globally and even no cure or vaccine has been successfully employed to combat this disease. Patients have been reported with multi-organ dysfunction along with acute respiratory distress syndrome which implies a critical situation for patients and made them difficult to breathe and survive. Moreover, pathology of COVID-19 is also related to cytokine storm which indicates the elevated levels of interleukin (IL)-1, IL-6, IL-12, and IL-18 along with tumor necrosis factor (TNF)-α. Among them, the proinflammatory cytokine IL-6 has been reported to be induced via binding of severe acute respiratory syndrome coronavirus 2 (SARS)-CoV-2 to the host receptors. METHODOLOGY: Interleukin-6 blockade has been proposed to constitute novel therapeutics against COVID-19. Thus, in this study, 15 phytocompounds with known antiviral activity have been subjected to test for their inhibitory effect on IL-6. Based on the affinity prediction, top 3 compounds (isoorientin, lupeol, and andrographolide) with best scores were selected for 50 ns molecular dynamics simulation and MMGB/PBSA binding free energy analysis. RESULTS: Three phytocompounds including isoorientin, lupeol, and andrographolide have shown strong interactions with the targeted protein IL-6 with least binding energies (-7.1 to -7.7 kcal/mol). Drug-likeness and ADMET profiles of prioritized phytocompounds are also very prominsing and can be further tested to be potential IL-6 blockers and thus benficial for COVID-19 treatment. The moelcular dynamics simulation couple with MMGB/PBSA binding free energy estimation validated conformational stability of the ligands and stronger intermolecular binding. The mean RMSD of the complexes is as: IL6-isoorientin complex (3.97 Å ± 0.77), IL6-lupeol (3.97 Å ± 0.76), and IL6-andrographolide complex (3.96 Å ± 0.77). In addition, the stability observation was affirmed by compounds mean RMSD: isoorientin (0.72 Å ± 0.32), lupeol (mean 0.38 Å ± 0.08), and andrographolide (1.09 Å ± 0.49). A similar strong agreement on systems stability was unraveled by MMGB/PBSA that found net binding net ~ -20 kcal/mol for the complexes dominated by van der Waal interaction energy. CONCLUSION: It has been predicted that proposing potential IL-6 inhibitors with less side effects can help critical COVID-19 patients because it may control the cytokine storm, a major responsible factor of its pathogenesis. In this study, 3 potential phytocompounds have been proposed to have inhibitory effect on IL-6 that can be tested as potential therapeutic options against SARS-CoV-2.

Chimeric vaccine designs against Acinetobacter baumannii using pan genome and reverse vaccinology approaches.

Acinetobacter baumannii (A. baumannii), an opportunistic, gram-negative pathogen, has evoked the interest of the medical community throughout the world because of its ability to cause nosocomial infections, majorly infecting those in intensive care units. It has also drawn the attention of researchers due to its evolving immune evasion strategies and increased drug resistance. The emergence of multi-drug-resistant-strains has urged the need to explore novel therapeutic options as an alternative to antibiotics. Due to the upsurge in antibiotic resistance mechanisms exhibited by A. baumannii, the current therapeutic strategies are rendered less effective. The aim of this study is to explore novel therapeutic alternatives against A. baumannii to control the ailed infection. In this study, a computational framework is employed involving, pan genomics, subtractive proteomics and reverse vaccinology strategies to identify core promiscuous vaccine candidates. Two chimeric vaccine constructs having B-cell derived T-cell epitopes from prioritized vaccine candidates; APN, AdeK and AdeI have been designed and checked for their possible interactions with host BCR, TLRs and HLA Class I and II Superfamily alleles. These vaccine candidates can be experimentally validated and thus contribute to vaccine development against A. baumannii infections.

Designing multi-epitope vaccine against Staphylococcus aureus by employing subtractive proteomics, reverse vaccinology and immuno-informatics approaches.

Staphylococcus aureus is a deadly human bacterial pathogen that causes a wide variety of clinical manifestations. Invasive S. aureus infections in hospitals and the community are one of the main causes of mortality and morbidity, as virulent and multi-drug-resistant strains have evolved. There is an unmet and urgent clinical need for immune-based non-antibiotic approaches to treat these infections as the growing antibiotic resistance poses a significant public health danger. Subtractive proteomics assisted reverse vaccinology-based immunoinformatics pipeline was used in this study to target the suitable antigenic proteins for the development of multi-epitope vaccine (MEV). Three essential virulent and antigenic proteins were identified including Glycosyltransferase, Elastin Binding Protein, and Staphylococcal secretory antigen. A variety of immunoinformatics tools have been used to forecast T-cell and B-cell epitopes from target proteins. Seven CTL, five HTL, and eight LBL epitopes, connected through suitable linkers and adjuvant, were employed to design 444 amino acids long MEV construct. The vaccine was paired with the TLR4 agonist 50S ribosomal protein L7/L12 adjuvant to enhance the immune response towards the vaccine. The predicted MEV structure was assessed to be highly antigenic, non-toxic, non-allergenic, flexible, stable, and soluble. Molecular docking simulation of the MEV with the human TLR4 (toll-like receptor 4) and major histocompatibility complex molecules (MHCI and MHCII) was performed to validate the interactions with the receptors. Molecular dynamics (MD) simulation and MMGBSA binding free energy analyses were carried out for the stability evaluation and binding of the MEV docked complexes with TLR4, MHCI and MHCII. To achieve maximal vaccine protein expression with optimal post-translational modifications, MEV was reverse translated, its mRNA structure was analyzed, and finally in silico cloning was performed into E. coli expression host. These rigorous computational analyses supported the effectivity of proposed MEV in protection against infections associated with S. aureus. However, further experimental validations are required to fully evaluate the potential of proposed vaccine candidate.

The emerging role and significance of circular RNAs in viral infections and antiviral immune responses: possible implication as theranostic agents.

Circular RNAs (circRNAs) are ubiquitously expressed, covalently closed rings, produced by pre-mRNA splicing in a reversed order during post-transcriptional processing. Circularity endows 3'-5'-linked circRNAs with stability and resistance to exonucleolytic degradation which raises the question whether circRNAs may be relevant as potential therapeutic targets or agents. High stability in biological systems is the most remarkable property and a major criterion for why circRNAs could be exploited for a range of RNA-centred medical applications. Even though various biological roles and regulatory functions of circRNAs have been reported, their in-depth study is challenging because of their circular structure and sequence-overlap with linear mRNA counterparts. Moreover, little is known about their role in viral infections and in antiviral immune responses. We believe that an in-depth and detailed understanding of circRNA mediated viral protein regulations will increase our knowledge of the biology of these novel molecules. In this review, we aimed to provide a comprehensive basis and overview on the biogenesis, significance and regulatory roles of circRNAs in the context of antiviral immune responses and viral infections including hepatitis C virus infection, hepatitis B virus infection, hepatitis delta virus infection, influenza A virus infection, Epstein-Barr virus infection, kaposi's sarcoma herpesvirus infection, human cytomegalovirus infection, herpes simplex virus infection, human immunodeficiency virus infection, porcine epidemic diarrhoea virus infection, ORF virus infection, avian leukosis virus infection, simian vacuolating virus 40 infection, transmissible gastroenteritis coronavirus infection, and bovine viral diarrhoea virus infection. We have also discussed the critical regulatory role of circRNAs in provoking antiviral immunity, providing evidence for implications as therapeutic agents and as diagnostic markers.

Designing Multi-Epitope Vaccines to Combat Emerging Coronavirus Disease 2019 (COVID-19) by Employing Immuno-Informatics Approach.

A recent pandemic caused by a single-stranded RNA virus, COVID-19, initially discovered in China, is now spreading globally. This poses a serious threat that needs to be addressed immediately. Genome analysis of SARS-CoV-2 has revealed its close relation to SARS-coronavirus along with few changes in its spike protein. The spike protein aids in receptor binding and viral entry within the host and therefore represents a potential target for vaccine and therapeutic development. In the current study, the spike protein of SARS-CoV-2 was explored for potential immunogenic epitopes to design multi-epitope vaccine constructs. The S1 and S2 domains of spike proteins were analyzed, and two vaccine constructs were prioritized with T-cell and B-cell epitopes. We adapted a comprehensive predictive framework to provide novel insights into immunogenic epitopes of spike proteins, which can further be evaluated as potential vaccine candidates against COVID-19. Prioritized epitopes were then modeled using linkers and adjuvants, and respective 3D models were constructed to evaluate their physiochemical properties and their possible interactions with ACE2, HLA Superfamily alleles, TLR2, and TLR4.

Formal model of the interplay between TGFß1 and MMP-9 and their dynamics in hepatocellular carcinoma.

Transforming growth factor beta1 (TGFß1) and matrix metalloproteinase-9 (MMP-9) have been associated with migration and invasion in hepatocellular carcinoma (HCC). Recent studies have suggested a positive feedback loop between TGFß1 and MMP-9 mediated by the PI3K signaling pathway that confers acquired invasion and metastasis in HCC via induction of the epithelial-mesenchymal transition (EMT), which grows into invasive carcinoma. But the potential molecular mechanism of this loop on HCC has not been clarified yet. Therefore, this study is designed to explore the association between the two entities and their key determinants such as NFκB, TIMP-1, and hepatic stellate cells (HSCs). Hence, a qualitative modeling framework is implemented that predict the role of biological regulatory network (BRN) during recovery and HCC metastasis. Qualitative modeling predicts discrete trajectories, stable states, and cycles that highlight the paths leading to disease recovery and homeostasis, respectively. The deadlock stable state (1, 1, 1, 1, 1) predicts high expression of all the entities in the BRN, resulting in the progression of HCC. The qualitative model predicts 30 cycles representing significant paths leading to recovery and homeostasis and amongst these the most significant discrete cycle was selected based on the highest betweenness centralities of the discrete states. We further verified our model with network modeling and simulation analysis based on petri net modeling approach. The BRN dynamics were analyzed over time. The results implied that over the course of disease condition or homeostasis, the biological entities are activated in a variable manner. Taken together, our findings suggest that the TGFß1 and the MMP-9 feedback loop is critical in tumor progression, as it may aid in the development of treatment strategies that are designed to target both TGFß and MMP-9.

PanRV: Pangenome-reverse vaccinology approach for identifications of potential vaccine candidates in microbial pangenome.

BACKGROUND: A revolutionary diversion from classical vaccinology to reverse vaccinology approach has been observed in the last decade. The ever-increasing genomic and proteomic data has greatly facilitated the vaccine designing and development process. Reverse vaccinology is considered as a cost-effective and proficient approach to screen the entire pathogen genome. To look for broad-spectrum immunogenic targets and analysis of closely-related bacterial species, the assimilation of pangenome concept into reverse vaccinology approach is essential. The categories of species pangenome such as core, accessory, and unique genes sets can be analyzed for the identification of vaccine candidates through reverse vaccinology. RESULTS: We have designed an integrative computational pipeline term as "PanRV" that employs both the pangenome and reverse vaccinology approaches. PanRV comprises of four functional modules including i) Pangenome Estimation Module (PGM) ii) Reverse Vaccinology Module (RVM) iii) Functional Annotation Module (FAM) and iv) Antibiotic Resistance Association Module (ARM). The pipeline is tested by using genomic data from 301 genomes of Staphylococcus aureus and the results are verified by experimentally known antigenic data. CONCLUSION: The proposed pipeline has proved to be the first comprehensive automated pipeline that can precisely identify putative vaccine candidates exploiting the microbial pangenome. PanRV is a Linux based package developed in JAVA language. An executable installer is provided for ease of installation along with a user manual at https://sourceforge.net/projects/panrv2/ .

Model-based in silico analysis of the PI3K/Akt pathway: the elucidation of cross-talk between diabetes and breast cancer.

BACKGROUND: A positive association between diabetes and breast cancer has been identified by various epidemiological and clinical studies. However, the possible molecular interactions between the two heterogeneous diseases have not been fully determined yet. There are several underlying mechanisms which may increase the risk of breast cancer in diabetic patients. INTRODUCTION: In this study, we focused on the role of O-GlcNAc transferase (OGT) enzyme in the regulation of phosphatidylinositol-3 kinase (PI3K) pathway through activation/deactivation of Akt protein. The efficiency of insulin signaling in adipocytes is reduced as a result of OGT overexpression which further attenuates Akt signaling; as a result, the efficiency of insulin signaling is reduced by downregulation of insulin-responsive genes. On the other hand, increased expression of OGT results in Akt activation in breast cancer cells, leading to enhanced cell proliferation and inhibition of the apoptosis. However, the interplay amongst these signaling pathways is still under investigation. METHODS: In this study, we used Petri nets (PNs) to model and investigate the role of PI3K and OGT pathways, acting as key players in crosstalk between diabetes and breast cancer, resulting in progression of these chronic diseases. Moreover, in silico perturbation experiments were applied on the model to analyze the effects of anti-cancer agents (shRNA and BZX) and anti-diabetic drug (Metformin) on the system. RESULTS: Our PN model reflects the alterations in protein expression and behavior and the correlation between breast cancer and diabetes. The analysis proposed two combination therapies to combat breast cancer progression in diabetic patients including combination of OGTmRNA silencing and OGT inhibitor (BZX) as first combination and BZX and Metformin as the second. CONCLUSION: The PN model verified that alterations in O-GlcNAc signaling affect both insulin resistance and breast cancer. Moreover, the combination therapy for breast cancer patients consisting of anti-diabetic drugs such as Metformin along with OGT inhibitors, for example BZX, can produce better treatment regimens.