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Circular RNAs (circRNAs) are a group of non-coding RNAs with a unique circular structure generated by back-splicing. It is acknowledged that circRNAs play critical roles in cardiovascular diseases. However, functional studies of circRNAs were impeded due to lack of effective in vivo silencing approaches. Since most circRNAs are produced by protein-coding transcripts, gene editing typically affects the coding activity of the parental genes. In this study, we developed a circular antisense RNA (cA-circSlc8a1) that could silence the highly expressed circRNA circSlc8a1 in the mouse heart but not its parental Slc8a1 linear mRNA. Transgenic cA-circSlc8a1 mice developed congestive heart failure resulting in a significant increase in the body weight secondary to peripheral edema and congestive hepatopathy. To further test the role of circSlc8a1, we generated transgenic mice overexpressing circSlc8a1 and observed a protective effect of circSlc8a1 in a pressure overload model. Mechanistically, we found that circSlc8a1 translocated into mitochondria to drive ATP synthesis. While establishing a transgenic murine model for antisense-mediated circRNA silencing without interfering with the parental linear RNA, our finding revealed the essential role of circSlc8a1 in maintaining heart function and may lay the groundwork of using the circular antisense RNA as a potential gene therapy approach for cardiovascular diseases.

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.

Metastatic cancer cells invade surrounding tissues by forming dynamic actin-based invadopodia, which degrade the surrounding extracellular matrix and allow cancer cell invasion. Regulatory RNAs, including circular RNA, have been implicated in this process. By microarray, we found that the circular RNA circSKA3 was highly expressed in breast cancer cells and human breast cancer tissues. We further found that the invasive capacity of breast cancer cells was positively correlated with circSKA3 expression, through the formation of invadopodia. Mechanistically, we identified Tks5 and integrin β1 as circSKA3 binding partners in these tumor-derived invadopodia. Ectopic circSKA3 expression conferred increased tumor invasiveness in vitro and in vivo. We further identified the RNA-protein binding sites between circSKA3, Tks5 and integrin β1. In tumor formation assays, we found that circSKA3 expression promoted tumor progression and invadopodium formation. Mutation of the circSKA3 binding sites or transfection with blocking oligos abrogated the observed effects. Thus, we provide evidence that the circular RNA circSKA3 promotes tumor progression by complexing with Tks5 and integrin β1, inducing invadopodium formation.

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.

Circular RNAs represent a large class of non-coding RNAs that are extensively expressed in mammals. However, the functions of circular RNAs are largely unknown. We recently reported that the circular RNA circ-Ccnb1 could bind with H2AX in p53 mutant cells and suppressed mutant p53 in tumor progression. Here we found that circ-Ccnb1 could interact with both Ccnb1 and Cdk1 proteins. Normally, Ccnb1 and Cdk1 proteins form a complex, allowing Ccnb1 to function as an all-or-none switch for cell mitosis. The interaction of circ-Ccnb1 with Ccnb1 and Cdk1 proteins dissociated the formation of Ccnb1-Cdk1 complex, by forming a large complex containing circ-Ccnb1, Ccnb1 and Cdk1. Formation of this large complex may occur in cytosol and nuclei, and Ccnb1 loses its roles in enhancing cell migration, invasion, proliferation and survival. In vivo, ectopic delivery of circ-Ccnb1 inhibited tumor growth and extended mouse viability. These results have added another layer of mechanisms for circ-Ccnb1 to regulate tumor progression in vitro and in vivo.

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.

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.

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.

TP53 mutations occur in many different types of cancers that produce mutant p53 proteins. The mutant p53 proteins have lost wild-type p53 activity and gained new functions that contribute to malignant tumor progression. Different p53 mutations create distinct profiles in loss of wild-type p53 activity and gain of functions. Targeting the consequences generated by the great number of p53 mutations would be extremely complex. Therefore, in this study we used a workaround and took advantage of the fact that mutant p53 cannot bind H2AX. Using this, we developed a new approach to repress the acquisition of mutant p53 functions. We show here that the delivery of a circular RNA circ-Ccnb1 inhibited the function of three p53 mutations. By microarray analysis and real-time PCR, we detected decreased circ-Ccnb1 expression levels in patients bearing breast carcinoma. Ectopic delivery of circ-Ccnb1 inhibited tumor growth and extended mouse viability. Using proteomics, we found that circ-Ccnb1 precipitated p53 in p53 wild-type cells, but instead precipitated Bclaf1 in p53 mutant cells. Further experiments showed that H2AX serves as a bridge, linking the interaction of circ-Ccnb1 and wild-type p53, thus allowing Bclaf1 to bind Bcl2 resulting in cell survival. In the p53 mutant cells, circ-Ccnb1 formed a complex with H2AX and Bclaf1, resulting in the induction of cell death. We found that this occurred in three p53 mutations. These results shed light on the possible development of new approaches to inhibit the malignancy of p53 mutations.

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 performed a 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 6000 SARS-CoV-2 sequences and identified 92 mutations in S, 37 in RdRp, and 11 in 3CLpro regions. The impact of these mutations was also investigated using various in silico approaches. Among these, 32 mutations in S, 15 in RdRp, and 3 in 3CLpro proteins were found to be deleterious in nature and could alter the structural and functional behavior of the encoded proteins. The D614G mutation in spike and the P323Lmutation in RdRp are the globally dominant variants with a high frequency. Most of the identified mutations were also found in the binding moiety of the viral proteins which determine their critical involvement in host–pathogen interactions and may represent drug targets. Furthermore, potential CD4+ and CD8+ T cell epitopes were predicted, and their overlap with genetic variations was explored. This study also highlights several hot spots in which HLA and drug selective pressure overlap. The findings of the current study may allow a better understanding of COVID-19 diagnostics, vaccines, and therapeutics.

Delayed or impaired wound healing is a major health issue worldwide, especially in patients with diabetes and atherosclerosis. Here we show that expression of the circular RNA circ-Amotl1 accelerated healing process in a mouse excisional wound model. Further studies showed that ectopic circ-Amotl1 increased protein levels of Stat3 and Dnmt3a. The increased Dnmt3a then methylated the promoter of microRNA miR-17, decreasing miR-17-5p levels but increasing fibronectin expression. We found that Stat3, similar to Dnmt3a and fibronectin, was a target of miR-17-5p. Decreased miR-17-5p levels would increase expression of fibronectin, Dnmt3a, and Stat3. All of these led to increased cell adhesion, migration, proliferation, survival, and wound repair. Furthermore, we found that circ-Amotl1 not only increased Stat3 expression but also facilitated Stat3 nuclear translocation. Thus, the ectopic expressed circ-Amotl1 and Stat3 were mainly translocated to nucleus. In the presence of circ-Amotl1, Stat3 interacted with Dnmt3a promoter with increased affinity, facilitating Dnmt3a transcription. Ectopic application of circ-Amotl1 accelerating wound repair may shed light on skin wound healing clinically.

Circular RNAs (circRNAs) are a subclass of noncoding RNAs widely expressed in mammalian cells. We report here the tumorigenic capacity of a circRNA derived from angiomotin-like1 (circ-Amotl1). Circ-Amotl1 is highly expressed in patient tumor samples and cancer cell lines. Single-cell inoculations using circ-Amotl1-transfected tumor cells showed a 30-fold increase in proliferative capacity relative to control. Agarose colony-formation assays similarly revealed a 142-fold increase. Tumor-take rate in nude mouse xenografts using 6-day (219 cells) and 3-day (9 cells) colonies were 100%, suggesting tumor-forming potential of every cell. Subcutaneous single-cell injections led to the formation of palpable tumors in 41% of mice, with tumor sizes >1 cm3 in 1 month. We further found that this potent tumorigenicity was triggered through interactions between circ-Amotl1 and c-myc. A putative binding site was identified in silico and tested experimentally. Ectopic expression of circ-Amotl1 increased retention of nuclear c-myc, appearing to promote c-myc stability and upregulate c-myc targets. Expression of circ-Amotl1 also increased the affinity of c-myc binding to a number of promoters. Our study therefore reveals a novel function of circRNAs in tumorigenesis, and this subclass of noncoding RNAs may represent a potential target in cancer therapy.

As central nodes in cardiomyocyte signaling, nuclear AKT appears to play a cardio-protective role in cardiovascular disease. Here we describe a circular RNA, circ-Amotl1 that is highly expressed in neonatal human cardiac tissue, and potentiates AKT-enhanced cardiomyocyte survival. We hypothesize that circ-Amotl1 binds to PDK1 and AKT1, leading to AKT1 phosphorylation and nuclear translocation. In primary cardiomyocytes, epithelial cells, and endothelial cells, we found that forced circ-Amotl1 expression increased the nuclear fraction of pAKT. We further detected increased nuclear pAKT in circ-Amotl1-treated hearts. In vivo, circ-Amotl1 expression was also found to be protective against Doxorubicin (Dox)-induced cardiomyopathy. Putative PDK1- and AKT1-binding sites were then identified in silico. Blocking oligonucleotides could reverse the effects of exogenous circ-Amotl1. We conclude that circ-Amotl1 physically binds to both PDK1 and AKT1, facilitating the cardio-protective nuclear translocation of pAKT.

Circular RNAs have been identified as naturally occurring RNAs that are highly represented in the eukaryotic transcriptome. Although a large number of circRNAs have been reported, circRNA functions remain largely unknown. CircRNAs can function as miRNA sponges, thereby reducing their ability to target mRNAs. We hypothesize that circRNAs may bind, store, sort, and sequester proteins to particular subcellular locations, and act as dynamic scaffolding molecules that modulate protein-protein interactions. Here, we review the biological implication and function of circRNA-protein interaction, and reveal a dynamic model of the interaction in various tissues, development stages and physiological conditions. Improved techniques to identify and characterize the dynamic RNA-protein interactions may elucidate the molecular mechanisms associated with the expression and functional diversity of circRNAs.

Cell-to-cell variation in genotypic/phenotypic traits is a common phenomenon and universal feature of multicellular organisms. Even within any single tissue, phenotypically different population of cells exist, all of which signifies diverse manifestations of that tissue type. This cellular heterogeneity plays a vital role in cellular decision-making and may be well understood with single-cell analysis. Single-cell omics is an emerging frontier of the biological sciences that can help to differentiate clearly between the behaviors of cells and their subpopulations. The overall behavior of genomes, transcriptomes, and proteomes aid the exploration of diverse behavior of cells in different situations. Systems biology, on the other hand, seeks to quantitatively understand the dynamic interactions between various biological components by employing omics and single-cell biology. A systems-level understanding of single-cell has the ability to design, record, and model massive amounts of data at the omics level. Despite substantial advances, considerable challenges, including the features of biological systems, systematic noise, and the complexity and sparsity of the data remain in the scrutinization, integration, and interpretation of single-cell omics. Therefore, there is a need for a fundamental paradigm shift toward scrutinization of single cells both at computational and experimental levels. In this chapter, we will discuss techniques, methods, and applications of systems biology to unravel the biology of single cells via systems-level approaches to enhance our understanding of cell biology as a system. The current cutting-edge technologies with respect to computational techniques and algorithms that can aid the analysis will be discussed, along with their challenges and future prospects.

Circular RNAs are a class of non-coding RNAs that are receiving extensive attention. Despite reports showing circular RNAs acting as microRNA sponges, the biological functions of circular RNAs remain largely unknown. We show that in patient tumor samples and in a panel of cancer cells, circ-Foxo3 was minimally expressed. Interestingly, during cancer cell apoptosis, the expression of circ-Foxo3 was found to be significantly increased. We found that silencing endogenous circ-Foxo3 enhanced cell viability, whereas ectopic expression of circ-Foxo3 triggered stress-induced apoptosis and inhibited the growth of tumor xenografts. Also, expression of circ-Foxo3 increased Foxo3 protein levels but repressed p53 levels. By binding to both, circ-Foxo3 promoted MDM2-induced p53 ubiquitination and subsequent degradation, resulting in an overall decrease of p53. With low binding affinity to Foxo3 protein, circ-Foxo3 prevented MDM2 from inducing Foxo3 ubiquitination and degradation, resulting in increased levels of Foxo3 protein. As a result, cell apoptosis was induced by upregulation of the Foxo3 downstream target PUMA.

Hepatitis C virus (HCV) vaccines, designed to augment specific T-cell responses, have been designated as an important aspect of effective antiviral treatment. However, despite the current satisfactory progress of these vaccines, extensive past efforts largely remained unsuccessful in mediating clinically relevant anti-HCV activity in humans. In this study, we used a series of immunoinformatics approaches to propose a multiepitope vaccine against HCV by prioritizing 16 conserved epitopes from three viral proteins (i.e., NS34A, NS5A, and NS5B). The prioritised epitopes were tested for their possible antigenic combinations with each other along with linker AAY using structural modelling and epitope–epitope interactions analysis. An adjuvant (β-defensin) at the N-terminal of the construct was added to enhance the immunogenicity of the vaccine construct. Molecular dynamics (MD) simulation revealed the most stable structure of the proposed vaccine. The designed vaccine is potentially antigenic in nature and can form stable and significant interactions with Toll-like receptor 3 and Toll-like receptor 8. The proposed vaccine was also subjected to an in silico cloning approach, which confirmed its expression efficiency. These analyses suggest that the proposed vaccine can elicit specific immune responses against HCV; however, experimental validation is required to confirm the safety and immunogenicity profile of the proposed vaccine construct.

Polio viral proteinase 2A performs several essential functions in genome replication. Its inhibition prevents viral replication, thus making it an excellent substrate for drug development. In this study, the three-dimensional structure of 2A protease was determined and optimized by homology modelling. To predict the molecular basis of the interaction of small molecular agonists, docking simulations were performed on a structurally diverse dataset of poliovirus 2A protease (PV2Apr°) inhibitors. Docking results were employed to identify high risk missense mutations that are highly damaging to the structure, as well as the function, of the protease. Intrinsic disorder regions (IDRs), drug binding sites (DBS), and protein stability changes upon mutations were also identified among them. Our results demonstrated dominant roles for Lys 15, His 20, Cys 55, Cys 57, Cys 64, Asp 108, Cys 109 and Gly 110, indicating the presence of various important drug binding sites of the protein. Upon subjecting these sites to single-nucleotide polymorphism (SNP) analysis, we observed that out of 155 high risk SNPs, 139 residues decrease the protein stability. We conclude that these missense mutations can affect the functionality of the 2A protease, and that identified protein binding sites can be directed for the attachment and inhibition of the target proteins.

Circular RNAs are a large group of noncoding RNAs that are widely expressed in mammalian cells. Genome-wide analyses have revealed abundant and evolutionarily conserved circular RNAs across species, which suggest specific physiological roles of these species. Using a microarray approach, we detected increased expression of a circular RNA circ-Dnmt1 in eight breast cancer cell lines and in patients with breast carcinoma. Silencing circ-Dnmt1 inhibited cell proliferation and survival. Ectopic circ-Dnmt1 increased the proliferative and survival capacities of breast cancer cells by stimulating cellular autophagy. We found that circ-Dnmt1-mediated autophagy was essential in inhibiting cellular senescence and increasing tumor xenograft growth. We further found that ectopically expressed circ-Dnmt1 could interact with both p53 and AUF1, promoting the nuclear translocation of both proteins. Nuclear translocation of p53 induced cellular autophagy while AUF1 nuclear translocation reduced Dnmt1 mRNA instability, resulting in increased Dnmt1 translation. From here, functional Dnmt1 could then translocate into the nucleus, inhibiting p53 transcription. Computational algorithms revealed that both p53 and AUF1 could bind to different regions of circ-Dnmt1 RNA. Our results showed that the highly expressed circular RNA circ-Dnmt1 could bind to and regulate oncogenic proteins in breast cancer cells. Thus circ-Dnmt1 appears to be an oncogenic circular RNA with potential for further preclinical research.

HCV is a major causative agent of liver infection and is the leading cause of Hepatocellular carcinoma (HCC). To understand the complexity in interactions within the HCV induced immune signaling networks, a logic-based diagram is generated based on multiple reported interactions. A simple conceptual framework is presented to explore the key determinants of the immune system and their functions during HCV infection. Furthermore, an abstracted sub-network is modeled qualitatively which consists of both the key cellular and cytokine components of the HCV induced immune system. In the presence of NS5A protein of HCV, the behaviors and the interplay amongst the natural killer (NK) and T regulatory (Tregs) cells along with cytokines such as IFN-γ, IL-10, IL-12 are predicted. The overall modelling approach followed in this study comprises of prior knowledge-based logical interaction network, network abstraction, parameter estimation, regulatory network construction and analysis through state graph, enabling the prediction of paths leading to both, disease state and a homeostatic path/cycle predicted based on maximum betweenness centrality. To study the continuous dynamics of the network, Petri net (PN) model was generated. The analysis implicates the critical role of IFN-γ producing NK cells in recovery while, the role of IL-10 and IL-12 in pathogenesis. The predictive ability of the model implicates that IL-12 has a dual role under varying circumstances and leads to varying disease outcomes. This model attempts to reduce the noisy biological data and captures a holistic view of the key determinants of the HCV induced immune response.

An in-depth understanding of complex systems such as hepatitis C virus (HCV) infection and host immunomodulatory response is an open challenge for biologists. In order to understand the mechanisms involved in immune evasion by HCV, we present a simplified formalization of the highly dynamic system consisting of HCV, its replication cycle and host immune responses at the cellular level using Hybrid Petri Net (HPN). The approach followed in this study comprises of step wise simulation, model validation and analysis of host immune response. This study was performed with an objective of making correlations among viral RNA levels, interferon (IFN) production and interferon stimulated genes (ISGs) induction. The results correlate with the biological data verifying that the model is very useful in predicting the dynamic behavior of the signaling proteins in response to a stimulus. This study implicates that the HCV infection is dependent upon several key factors of the host immune response. The effect of host proteins on limiting viral infection is effectively overruled by the viral pathogen. This study also analyzes activity levels of RNase L, miR-122, IFN, ISGs and PKR induction and inhibition of TLR3/RIG1 mediated pathways in response to targeted manipulation in the presence of HCV. The results are in complete agreement at the time of writing with the published expression studies and western blot experiments. Our model also provides some biological insights regarding the role of PKR in the acute infection of HCV. It might help to explain why many patients fail to clear acute HCV infection while others, with low ISGs basal levels, clear HCV spontaneously. The described methodology can easily be reproduced, which suitably supports the study of other viral infections in a formal, automated and expressive manner. The Petri Net-based modeling approach applied here may provide valuable insights for study design and analyses to evaluate other disease associated integrated pathways in biological systems.

A regulated immune system employs multiple cell types, diverse variety of cytokines and interacting signalling networks against infections. Systems biology offers a promising solution to model and simulate such large populations of interacting components of immune systems holistically. This study focuses on the distinct components of the adaptive immune system and analysis, both individually and in association with HCV infection. The effective and failed adaptive immune response models have been developed followed by interventions/perturbations of various treatment strategies to get better assessment of the treatment responses under varying stimuli. Based on the model predictions, the NK cells, T regulatory cells, IL-10, IL-21, IL-12, IL-2 entities are found to be the most critical determinants of treatment response. The proposed potential immunomodulatory therapeutic interventions include IL-21 treatment, blocking of inhibitory receptors on T-cells and exogenous anti-IL-10 antibody treatment. The relative results showed that these interventions have differential effect on the expression levels of cellular and cytokines entities of the immune response. Notably, IL-21 enhances the expression of NK cells, Cytotoxic T lymphocytes and CD4+ T cells and hence restore the host immune potential. The models presented here provide a starting point for cost-effective analysis and more comprehensive modeling of biological phenomenon.

Among solid tumors, hepatocellular carcinoma (HCC) emerges as a prototypical therapy-resistant tumor. Considering the emerging sorafenib resistance crisis in HCC, future studies are urgently required to overcome resistance. Recently noncoding RNAs (ncRNAs) have emerged as significant regulators in signalling pathways involved in cancer drug resistance and pharmacologically targeting these ncRNAs might be a novel stratagem to reverse drug resistance. In the current study, using a hybrid Petri net based computational model, we have investigated the harmonious effect of miR-17-92 cluster inhibitors/mimics and circular RNAs on sorafenib resistant HCC cells in order to explore potential resistance mechanisms and to identify putative targets for sorafenib-resistant HCC cells. An integrated model was developed that incorporates seven miRNAs belonging to miR-17-92 cluster (hsa-miR-17-5p, hsa-miR-17-3p, hsa-miR-19a, hsa-miR-19b, hsa-miR-18a, hsa-miR-20a and hsa-miR-92) and crosstalk of two signaling pathways (EGFR and IL-6) that are differentially regulated by these miRNAs. The mechanistic connection was proposed by the correlation between members belonging to miR-17-92 cluster and corresponding changes in the protein levels of their targets in HCC, specifically those targets that have verified importance in sorafenib resistance. Current findings uncovered potential pathway features, underlining the significance of developing modulators of this cluster to combat drug resistance in HCC.

Tight junctions help prevent the passage of digestive enzymes and microorganisms through the space between adjacent epithelial cells lining. However, Helicobacter pylori encoded virulence factors negatively regulate these tight junctions and contribute to dysfunction of gastric mucosa. Here, we have predicted the regulation of important tight junction proteins, such as Zonula occludens-1, Claudin-2 and Connexin32 in the presence of pathogenic proteins. Molecular events such as post translational modifications and crosstalk between phosphorylation, O-glycosylation, palmitoylation and methylation are explored which may compromise the integrity of these tight junction proteins. Furthermore, the signaling pathways disrupted by dysregulated kinases, proteins and post-translational modifications are reviewed to design an abstracted computational model showing the situation-dependent dynamic behaviors of these biological processes and entities. A qualitative hybrid Petri Net model is therefore constructed showing the altered host pathways in the presence of virulence factor cytotoxin-associated gene A, leading to the disruption of tight junction proteins. The model is qualitative logic-based, which does not depend on any kinetic parameter and quantitative data and depends on knowledge derived from experiments. The designed model provides insights into the tight junction disruption and disease progression. Model is then verified by the available experimental data, nevertheless formal in vitro experimentation is a promising way to ensure its validation. The major findings propose that H. pylori activated kinases are responsible to trigger specific post translational modifications within tight junction proteins, at specific sites. These modifications may favor alterations in gastric barrier and provide a route to bacterial invasion into host cells.

The blood-brain barrier (BBB) poses a huge challenge and is a serious issue in deciphering the pathophysiology of central nervous system disorders. Endothelial tight junctions play an essential role in maintaining the integrity of the BBB. Post-translational modifications (PTMs) in endothelial tight junction proteins are known to cause deleterious functional impairment and possible disruptions in BBB integrity. PTMs in tight junction proteins play an important role in human immunodeficiency virus type 1 (HIV-1) entry through the BBB. Human claudin-5 is one of the highly expressed brain endothelial tight junction protein and various PTMs in claudin-5 are expected to aid HIV-1 in crossing the BBB. A precise characterization of PTMs in claudin-5 is important for understanding its role in HIV-1 brain infiltration. In this study, we have examined post-translational crosstalk between phosphorylation, O-glycosylation, palmitoylation and methylation sites in claudin-5, which could alter claudin-5's ability to maintain BBB integrity. To the best of our knowledge, this is the first report on claudin-5 protein that suggests a novel interplay between potential PTM sites. PTMs of predicted residues in claudin-5, suggested in this study, can serve as compelling targets for potential therapeutic agents against HIV-1 induced neuropathogenesis. Further site-specific experimental studies in this aspect are highly recommended.

Background Acinetobacter baumannii has emerged as a significant nosocomial pathogen during the last few years, exhibiting resistance to almost all major classes of antibiotics. Alternative treatment options such as vaccines tend to be most promising and cost effective approaches against this resistant pathogen. In the current study, we have explored the pan-genome of A. baumannii followed by immune-proteomics and reverse vaccinology approaches to identify potential core vaccine targets. Results The pan-genome of all available A. baumannii strains (30 complete genomes) is estimated to contain 7,606 gene families and the core genome consists of 2,445 gene families (~32 % of the pan-genome). Phylogenetic tree, comparative genomic and proteomic analysis revealed both intra- and inter genomic similarities and evolutionary relationships. Among the conserved core genome, thirteen proteins, including P pilus assembly protein, pili assembly chaperone, AdeK, PonA, OmpA, general secretion pathway protein D, FhuE receptor, Type VI secretion system OmpA/MotB, TonB dependent siderophore receptor, general secretion pathway protein D, outer membrane protein, peptidoglycan associated lipoprotein and peptidyl-prolyl cis-trans isomerase are identified as highly antigenic. Epitope mapping of the target proteins revealed the presence of antigenic surface exposed 9-mer T-cell epitopes. Protein-protein interaction and functional annotation have shown their involvement in significant biological and molecular processes. The pipeline is validated by predicting already known immunogenic targets against Gram negative pathogen Helicobacter pylori as a positive control. Conclusion The study, based upon combinatorial approach of pan-genomics, core genomics, proteomics and reverse vaccinology led us to find out potential vaccine candidates against A. baumannii. The comprehensive analysis of all the completely sequenced genomes revealed thirteen putative antigens which could elicit substantial immune response. The integration of computational vaccinology strategies would facilitate in tackling the rapid dissemination of resistant A.baumannii strains. The scarcity of effective antibiotics and the global expansion of sequencing data making this approach desirable in the development of effective vaccines against A. baumannii and other bacterial pathogens. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2951-4) contains supplementary material, which is available to authorized users.

Autophagy, an evolutionary conserved multifaceted lysosome-mediated bulk degradation system, plays a vital role in liver pathologies including hepatocellular carcinoma (HCC). Post-translational modifications (PTMs) and genetic variations in autophagy components have emerged as significant determinants of autophagy related proteins. Identification of a comprehensive spectrum of genetic variations and PTMs of autophagy related proteins and their impact at molecular level will greatly expand our understanding of autophagy based regulation. In this study, we attempted to identify high risk missense mutations that are highly damaging to the structure as well as function of autophagy related proteins including LC3A, LC3B, BECN1 and SCD1. Number of putative structural and functional residues, including several sites that undergo PTMs were also identified. In total, 16 high-risk SNPs in LC3A, 18 in LC3B, 40 in BECN1 and 43 in SCD1 were prioritized. Out of these, 2 in LC3A (K49A, K51A), 1 in LC3B (S92C), 6 in BECN1 (S113R, R292C, R292H, Y338C, S346Y, Y352H) and 6 in SCD1 (Y41C, Y55D, R131W, R135Q, R135W, Y151C) coincide with potential PTM sites. Our integrated analysis found LC3B Y113C, BECN1 I403T, SCD1 R126S and SCD1 Y218C as highly deleterious HCC-associated mutations. This study is the first extensive in silico mutational analysis of the LC3A, LC3B, BECN1 and SCD1 proteins. We hope that the observed results will be a valuable resource for in-depth mechanistic insight into future investigations of pathological missense SNPs using an integrated computational platform.

Cellular immune responses (T cell responses) during hepatitis C virus (HCV) infection are significant factors for determining the outcome of infection. HCV adapts to host immune responses by inducing mutations in its genome at specific sites that are important for HLA processing/presentation. Moreover, HCV also adapts to resist potential drugs that are used to restrict its replication, such as direct-acting antivirals (DAAs). Although DAAs have significantly reduced disease burden, resistance to these drugs is still a challenge for the treatment of HCV infection. Recently, drug resistance mutations (DRMs) observed in HCV proteins (NS3/4A, NS5A and NS5B) have heightened concern that the emergence of drug resistance may compromise the effectiveness of DAAs. Therefore, the NS3/4A, NS5A and NS5B drug resistance variations were investigated in this study, and their prevalence was examined in a large number of protein sequences from all HCV genotypes. Furthermore, potential CD4+ and CD8+ T cell epitopes were predicted and their overlap with genetic variations was explored. The findings revealed that many reported DRMs within NS3/4A, NS5A and NS5B are not drug-induced; rather, they are already present in HCV strains, as they were also detected in HCV-naive patients. This study highlights several hot spots in which HLA and drug selective pressure overlap. Interestingly, these overlapping mutations were frequently observed among many HCV genotypes. This study implicates that knowledge of the host HLA type and HCV subtype/genotype can provide important information in defining personalized therapy.

Helicobacter pylori (H. pylori) is an important pathogen associated with diverse gastric disorders ranging from peptic ulcer to malignancy. It has also been recognized by the World Health Organization (WHO) as class I carcinogen. Conventional treatment regimens for H. pylori seem to be ineffective, possibly due to antibiotic resistance mechanisms acquired by the pathogen. In this study we have successfully employed a reverse vaccinology approach to predict the potential vaccine candidates against H. pylori. The predicted potential vaccine candidates include vacA, babA, sabA, fecA and omp16. Host–pathogen interactions analysis elaborated their direct or indirect role in the specific signaling pathways including epithelial cell polarity, metabolism, secretion system and transport. Furthermore, surface-exposed antigenic epitopes were predicted and analyzed for conservation among 39 complete genomes of H. pylori (Genbank) for all the candidate proteins. These epitopes may serve as a base for the development of broad spectrum peptide or multi-component vaccines against H. pylori. We also believe that the proposed pipeline can be extended to other pathogens and for the identification of novel candidates for the development of effective vaccines.