Inflammatory mediators play havoc in several diseases including the novel Coronavirus disease 2019 (COVID-19) and generally correlate with the severity of the disease. Interleukin-13 (IL-13), is a ...pleiotropic cytokine that is known to be associated with airway inflammation in asthma and reactive airway diseases, in neoplastic and autoimmune diseases. Interestingly, the recent association of IL-13 with COVID-19 severity has sparked interest in this cytokine. Therefore characterization of new molecules which can regulate IL-13 induction might lead to novel therapeutics.
Here, we present an improved prediction of IL-13-inducing peptides. The positive and negative datasets were obtained from a recent study (IL13Pred) and the Pfeature algorithm was used to compute features for the peptides. As compared to the state-of-the-art which used the regularization based feature selection technique (linear support vector classifier with the L1 penalty), we used a multivariate feature selection technique (minimum redundancy maximum relevance) to obtain non-redundant and highly relevant features. In the proposed study (improved IL-13 prediction (iIL13Pred)), the use of the mRMR feature selection method is instrumental in choosing the most discriminatory features of IL-13-inducing peptides with improved performance. We investigated seven common machine learning classifiers including Decision Tree, Gaussian Naïve Bayes, k-Nearest Neighbour, Logistic Regression, Support Vector Machine, Random Forest, and extreme gradient boosting to efficiently classify IL-13-inducing peptides. We report improved AUC, and MCC scores of 0.83 and 0.33 on validation data as compared to the current method.
Extensive benchmarking experiments suggest that the proposed method (iIL13Pred) could provide improved performance metrics in terms of sensitivity, specificity, accuracy, the area under the curve - receiver operating characteristics (AUCROC) and Matthews correlation coefficient (MCC) than the existing state-of-the-art approach (IL13Pred) on the validation dataset and an external dataset comprising of experimentally validated IL-13-inducing peptides. Additionally, the experiments were performed with an increased number of experimentally validated training datasets to obtain a more robust model. A user-friendly web server ( www.soodlab.com/iil13pred ) is also designed to facilitate rapid screening of IL-13-inducing peptides.
The COVID-19 pandemic has caused huge socio-economic losses and continues to threat humans worldwide. With more than 4.5 million deaths and more than 221 million confirmed COVID-19 cases, the impact ...on physical, mental, social and economic resources is immeasurable. During any novel disease outbreak, one of the primary requirements for effective mitigation is the knowledge of clinical manifestations of the disease. However, in absence of any unique identifying characteristics, diagnosis/prognosis becomes difficult. It intensifies misperception and leads to delay in containment of disease spread. Numerous clinical research studies, systematic reviews and meta-analyses have generated considerable data on the same. However, identification of some of the distinct clinical signs and symptoms, disease progression biomarkers and the risk factors leading to adverse COVID-19 outcomes warrant in-depth understanding. In view of this, we assessed 20 systematic reviews and meta-analyses with an intent to understand some of the potential independent predictors/biomarkers/risk factors of COVID-19 severity and mortality.
G-quadruplexes (G4s) are secondary structures in DNA that have been shown to be involved in gene regulation. They play a vital role in the cellular processes and several pathogens including bacteria, ...fungi, and viruses have also been shown to possess G4s that help them in their pathogenesis. Additionally, cross-talk among the CpG islands and G4s has been shown to influence biological processes. The virus-encoded G4s are affected by the mutational landscape leading to the formation/deletion of these G4s. Therefore, understanding and predicting these multivariate effects on traditional and non-traditional quadruplexes forms an important area of research, that is, yet to be investigated. We have designed a user-friendly webserver QUFIND (
http://soodlab.com/qufinder/
) that can predict traditional as well as non-traditional quadruplexes in a given sequence. QUFIND is connected with ENSEMBL and NCBI so that the sequences can be fetched in a real-time manner. The algorithm is designed in such a way that the user is provided with multiple options to customize the base (A, T, G, or C), size of the stem (2–5), loop length (1–30), number of bulges (1–5) as well as the number of mismatches (0–2) enabling the identification of any of the secondary structure as per their interest. QUFIND is designed to predict both CpG islands as well as G4s in a given sequence. Since G4s are very short as compared to the CpG islands, hence, QUFIND can also predict the overlapping G4s within CpG islands. Therefore, the user has the flexibility to identify either overlapping or non-overlapping G4s along with the CpG islands. Additionally, one section of QUFIND is dedicated to comparing the G4s in two viral sequences. The visualization is designed in such a manner that the user is able to see the unique quadruplexes in both the input sequences. The efficiency of QUFIND is calculated on G4s obtained from G4 high throughput sequencing data (
n
= 1000) or experimentally validated G4s (
n
= 329). Our results revealed that QUFIND is able to predict G4-quadruplexes obtained from G4-sequencing data with 90.06% prediction accuracy whereas experimentally validated quadruplexes were predicted with 97.26% prediction accuracy.
Human immunodeficiency virus type 1 (HIV-1) has RNA genome and depends on host cellular machinery for most of its activities. Host cellular proteins modulate the expression and activity of viral ...proteins to combat the virus. HIV-1 proteins are known to regulate each other for the benefit of virus by exploiting these modulations. Here, we report that HIV-1 Vif increases the levels of Tat
AKT signaling pathway. We show that HIV-1 Vif activates AKT signaling pathway by inducing phosphorylation of AKT. Mdm2, downstream target of AKT signaling, increases the levels of Tat protein in ubiquitin-dependent manner by inducing Ubiquitin Specific Protease 17 (USP17), which is a deubiquitinase and stabilizes Tat protein. Thus, HIV-1 proteins exploit AKT signaling pathway to promote viral replication.
The recent pandemic caused by Severe Acute Respiratory Syndrome Coronavirus-2 has resulted in enormous deaths around the world. Clues from genomic sequences of parent and their mutants can be ...obtained to understand the evolving pathogenesis of this virus. Apart from the viral proteins, virus-encoded microRNAs (miRNAs) have been shown to play a vital role in regulating viral pathogenesis. Thus we sought to investigate the miRNAs encoded by SARS-CoV-2, its mutants, and the host. Here, we present the results obtained using a dual approach i.e (i) identifying host-encoded miRNAs that might regulate viral pathogenesis and (ii) identifying viral-encoded miRNAs that might regulate host cell signaling pathways and aid in viral pathogenesis. Analysis utilizing the first approach resulted in the identification of ten host-encoded miRNAs that could target the SARS, SARS-CoV-2, and its mutants. Interestingly our analysis revealed that there is a significantly higher number of host miRNAs that could target the SARS-CoV-2 genome as compared to the SARS reference genome. Results from the second approach resulted in the identification of a set of virus-encoded miRNAs which might regulate host signaling pathways. Our analysis further identified a similar "GA" rich motif in the SARS-CoV-2 and its mutant genomes that was shown to play a vital role in lung pathogenesis during severe SARS infections. In summary, we have identified human and virus-encoded miRNAs that might regulate the pathogenesis of SARS coronaviruses and describe similar non-coding RNA sequences in SARS-CoV-2 that were shown to regulate SARS-induced lung pathology in mice.
•Temporal analysis of the daily viral load and cytokine levels in hospitalized dengue patients identified the pattern of cytokine dynamics.•Elevated IL-8, IL-10, IL-6, GM-CSF, MCP-1, IL-13, and IL-4 ...and decreased IL-12, MIP-1β on the third day after symptom onset is predictive of severe dengue.•The imbalanced cytokine signature may inform clinical decision-making in treating severe dengue infections.
The immunopathogenesis of dengue severity is convoluted. The primary objective of the research was to examine the dynamics of cytokine storm and its correlation with disease development in individuals affected by DENV infection. Additionally, the study aimed to discover potential biomarkers that could indicate severe dengue infection and determine the most suitable timeframe for predicting the severity of these biomarkers during the acute stage of dengue infections. We conducted a temporal analysis of the daily viral load and cytokine levels in 60 hospitalized dengue patients until discharge. Our findings reveal a distinct cytokine profile (elevated IL-8, IL-10, IL-6, GM-CSF, MCP-1, IL-13, and IL-4 and decreased IL-12, MIP-1β) on the third day after symptom onset is predictive of severe dengue in secondary dengue infection. The imbalanced cytokine signature may inform clinical decision-making in treating severe dengue infections.
Autophagy is a lysosomal degradative pathway that has diverse physiological functions and plays crucial roles in several viral infections. Here we examine the role of autophagy in the life cycle of ...JEV, a neurotropic flavivirus. JEV infection leads to induction of autophagy in several cell types. JEV replication was significantly enhanced in neuronal cells where autophagy was rendered dysfunctional by ATG7 depletion, and in Atg5-deficient mouse embryonic fibroblasts (MEFs), resulting in higher viral titers. Autophagy was functional during early stages of infection however it becomes dysfunctional as infection progressed resulting in accumulation of misfolded proteins. Autophagy-deficient cells were highly susceptible to virus-induced cell death. We also observed JEV replication complexes that are marked by nonstructural protein 1 (NS1) and dsRNA colocalized with endogenous LC3 but not with GFP-LC3. Colocalization of NS1 and LC3 was also observed in Atg5 deficient MEFs, which contain only the nonlipidated form of LC3. Viral replication complexes furthermore show association with a marker of the ER-associated degradation (ERAD) pathway, EDEM1 (ER degradation enhancer, mannosidase α-like 1). Our data suggest that virus replication occurs on ERAD-derived EDEM1 and LC3-I-positive structures referred to as EDEMosomes. While silencing of ERAD regulators EDEM1 and SEL1L suppressed JEV replication, LC3 depletion exerted a profound inhibition with significantly reduced RNA levels and virus titers. Our study suggests that while autophagy is primarily antiviral for JEV and might have implications for disease progression and pathogenesis of JEV, nonlipidated LC3 plays an important autophagy independent function in the virus life cycle.
Picornaviruses are a leading cause of central nervous system (CNS) infections. While genotypes such as parechovirus A3 (PeV-A3) and echovirus 11 (E11) can elicit severe neurological disease, the ...highly prevalent PeV-A1 is not associated with CNS disease. Here, we expand our current understanding of these differences in PeV-A CNS disease using human brain organoids and clinical isolates of the two PeV-A genotypes. Our data indicate that PeV-A1 and A3 specific differences in neurological disease are not due to infectivity of CNS cells as both viruses productively infect brain organoids with a similar cell tropism. Proteomic analysis shows that PeV-A infection significantly alters the host cell metabolism. The inflammatory response following PeV-A3 (and E11 infection) is significantly more potent than that upon PeV-A1 infection. Collectively, our findings align with clinical observations and suggest a role for neuroinflammation, rather than viral replication, in PeV-A3 (and E11) infection.
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