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.
Abstract An in-depth analysis of first wave SARS-CoV-2 genome is required to identify various mutations that significantly affect viral fitness. In the present study, we have performed comprehensive in-silico mutational analysis of 3C-like protease (3CLpro), RNA dependent RNA polymerase (RdRp), and spike (S) proteins with the aim of gaining important insights into first wave virus mutations and their functional and structural impact on SARS-CoV-2 proteins. Our integrated analysis gathered 3465 SARS-CoV-2 sequences and identified 92 mutations in S, 37 in RdRp, and 11 in 3CLpro regions. The impact of those mutations was also investigated using various in silico approaches. Among these 32 mutations in S, 15 in RdRp, and 3 in 3CLpro proteins are found to be deleterious in nature and could alter the structural and functional behavior of the encoded proteins. D614G mutation in spike and P323L in RdRp are the globally dominant variants with a high frequency. Most of them have also been found in the binding moiety of the viral proteins which determine their critical involvement in the host-pathogen interactions and drug targets. The findings of the current study may facilitate better understanding of COVID-19 diagnostics, vaccines, and therapeutics.
Transforming growth factor beta1 (TGF-β1) 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 TGF-β1 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 NFNJB, 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 TGF-β1 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 TGF-β and MMP-9.
A computational and in silico system level framework was developed to identify and prioritize the antibacterial drug targets in Clostridium botulinum (Clb), the causative agent of flaccid paralysis in humans that can be fatal in 5 to 10% of cases. This disease is difficult to control due to the emergence of drug-resistant pathogenic strains and the only available treatment antitoxin which can target the neurotoxin at the extracellular level and cannot reverse the paralysis. This study framework is based on comprehensive systems-scale analysis of genomic sequence homology and phylogenetic relationships among Clostridium, other infectious bacteria, host and human gut flora. First, the entire 2628-annotated genes of this bacterial genome were categorized into essential, non-essential and virulence genes. The results obtained showed that 39% of essential proteins that functionally interact with virulence proteins were identified, which could be a key to new interventions that may kill the bacteria and minimize the host damage caused by the virulence factors. Second, a comprehensive comparative COGs and blast sequence analysis of these proteins and host proteins to minimize the risks of side effects was carried out. This revealed that 47% of a set of C. botulinum proteins were evolutionary related with Homo sapiens proteins to sort out the non-human homologs. Third, orthology analysis with other infectious bacteria to assess broad-spectrum effects was executed and COGs were mostly found in Clostridia, Bacilli (Firmicutes), and in alpha and beta Proteobacteria. Fourth, a comparative phylogenetic analysis was performed with human microbiota to filter out drug targets that may also affect human gut flora. This reduced the list of candidate proteins down to 131. Finally, the role of these putative drug targets in clostridial biological pathways was studied while subcellular localization of these candidate proteins in bacterial cellular system exhibited that 68% of the proteins were located in the cytoplasm, out of which 6% was virulent. Finally, this framework may serve as a general computational strategy for future drug target identification in infectious diseases.
Background. Hepatitis C Virus (HCV) is a major causative agent of liver infection leading to critical liver damage. In response to HCV, the improper regulation of host immune system leads to chronic infection. The host immune system employs multiple cell types, diverse variety of cytokine mediators and interacting signaling networks to neutralize the HCV infection. To understand the complexity of the interactions within the immune signaling networks, systems biology provides an efficient alternative approach. Integrating such approaches with immunology and virology helps to study highly complex immune regulatory networks within the host and presents a concise view of the whole system. Methods . Initially, a logic-based diagram is generated based on multiple reported interactions between immune cells and cytokines during host immune response to HCV. Furthermore, an abstracted sub-network is modeled qualitatively which consists of both the key cellular and cytokine components of the HCV induced immune system. Rene’ Thomas formalism is applied in the study to generate a qualitative model which requires only the qualitative thresholds and associated logical parameters generated via SMBioNet software in accordance with biological observations. Furthermore, the continuous dynamics of the model have been studied via Petri nets based analysis. Results. In the presence of NS5A protein of HCV, the behaviors of the Natural Killer (NK) and T regulatory (Tregs) cells along with cytokines such as IFN-γ, IL-10, IL-12 are predicted. The model also attempts to consider the viral strategies to circumvent immune response mediated by viral proteins. The state graph analysis enabled the prediction of paths leading to disease state. The most probable cycle is predicted based on maximum betweenness centrality. Furthermore, to study the continuous dynamics of the modeled network, a Petri net (PN) model was generated. The predictive ability of the model implicates the critical role of IL-12 over-expression in pathogenesis. This observation speculates that IL-12 has a dual role under varying circumstances and leads to varying disease outcomes. Conclusion. This model attempts to reduce the noisy biological data and captures a holistic view of the regulations amongst the key determinants of HCV induced adaptive immune responses. The observations warrant for further studies to elucidate the role of IL-12 under varying external and internal stimuli. Also, introducing diversion by therapeutic perturbation may divert the system from diseased paths to recovery by stabilizing the activation of IFN-γ producing NK cells. The modeling approach employed in this study can be extended to include real-time experimental data to propose new therapeutic interventions.
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. 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. 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/ .
Introduction Breast Cancer is the number one cause of cancer related deaths in Pakistani women with an incidence of 1 in 9. This abstract is a part of a larger study that we conducted to identify the variants in 27 possible genes known for breast and ovarian cancer along with several oxidative stress markers. The current objective is to report a predictive novel variant of diagnostic importance in local females with breast cancer. Furthermore, to study the epidemiological and clinical presentation that may be predictive of this variable. Methods After ethical approval and informed consent, we extracted DNA from peripheral blood and conducted next generation sequencing followed by Sanger confirmation. Bioinformatic analysis was performed on ANNOVAR and SNP-Nexus softwares. Results Our results on both softwares indicate that an identical novel Phosphatase and Tension Homolog (PTEN) variant is present in 69% patients. It is a homozygous frameshift substitution (GCGCCG > CCGCCGC) at amino acid position C65S on exon 2 of chromosome 10 from 89623901 to 89623906. It acts at Micro-RNA and Cellular Senescence level of cancer pathways. All PTEN cases showed significant triple negative behavior at estrogen, progesterone and HER2 receptors, associated with adverse outcome. A total of 85% were premenopausal with mean age of 35 years +/- SD 5.611; SE 1.255; range 27-46 years). Their mean age at menarche was 13.25 years +/- SD 0.716; SE 0.160. The mean BMI showed overweight status. Family history was positive and known in only 35% but they were mainly (60%) the outcome of related parents. In majority (75%) of them history of breast feeding was positive and had no difficulty in breast feeding (70%). Around 80% were non-smokers and 100% were non-alcoholics. Most of them (85%) presented with Invasive Ductal Carcinoma and 55% with grade III. They all were homemakers, most (85%) being married and majority (75%) did not receive education above grade 10. Nearly 70% used tap / filtered-tap-water for drinking. They all had unilateral breast cancer of right side mainly (60%). Almost all (95%) detected it by feeling the lump. Mastectomy was performed only in 30% and all of them underwent chemotherapy. Radiotherapy was offered to only 10%. A total of 35% among them had only 1 year post-diagnosis survival. Conclusion This novel variant may be useful for researcher and clinician to expect similar outcome in unaffected carriers. It can be offered as a screening tool to achieve pre-diagnosis around 13 years of age to predict similar clinical manifestation using affordable Sanger technique, even before the breast development. The early diagnosis may improve the outcome.
Objective: To compared the functional gait among left and right hemisphere lesion patients of stroke.
Methods: This cross sectional comparative study included 126 patients with right and left sided hemispheric lesion. The study was conducted from December 2019 to March 2020. Patients were selected consecutively from different hospitals and rehabilitation centers of Lahore, Pakistan on the basis of inclusion & exclusion criteria. Functional gait assessment (FGA) scale was used to measure functional gait performance and disturbance related to balance in stroke patients. Independent sample t-test was used for comparison of functional gait between left and right hemispheric lesions. A p-value ≤ .05 was taken statistically significant.
Results: A total of 126 patients of stroke with right and left sided hemisphere lesion were assessed for functional gait assessment. The mean age of patients in group A and B was 54.19±8.54 years and 51.46±8.57 years, respectively. The mean weight of patients in group A and B was 61.95±8.82 kg and 58.67±5.83 kg, respectively. Functional gait assessment mean score in group A was 12.56±2.60 and in group B was 15.59±4.17 points with p-value of 0.001. There was a significant difference of FGA scores present between the two groups.
Conclusions: The study concluded that ambulatory functions differ with respect to site of hemisphere lesion. The site of hemisphere lesion impact on patient's functional gait has statistically significant.
A recent pandemic caused by a single stranded RNA virus, COVID-19 initially affecting Chinese population, is now spreading globally. This poses a serious threat which 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. 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 spike protein of SARS-CoV-2 was explored for potential immunogenic epitopes to design multi-epitope vaccine constructs. 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 protein 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.
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