Sensing of pathogens by specialized receptors is the hallmark of the innate immunity. Innate immune response also mounts a defense response against various allergens and pollutants including particulate matter present in the atmosphere. Air pollution has been included as the top threat to global health declared by WHO which aims to cover more than three billion people against health emergencies from 2019 to 2023. Particulate matter (PM), one of the major components of air pollution, is a significant risk factor for many human diseases and its adverse effects include morbidity and premature deaths throughout the world. Several clinical and epidemiological studies have identified a key link between the PM existence and the prevalence of respiratory and inflammatory disorders. However, the underlying molecular mechanism is not well understood. Here, we investigated the influence of air pollutant, PM 10 (particles with aerodynamic diameter less than 10 μm) during RNA virus infections using Highly Pathogenic Avian Influenza (HPAI) – H5N1 virus. We thus characterized the transcriptomic profile of lung epithelial cell line, A549 treated with PM 10 prior to H5N1infection, which is known to cause severe lung damage and respiratory disease. We found that PM 10 enhances vulnerability (by cellular damage) and regulates virus infectivity to enhance overall pathogenic burden in the lung cells. Additionally, the transcriptomic profile highlights the connection of host factors related to various metabolic pathways and immune responses which were dysregulated during virus infection. Collectively, our findings suggest a strong link between the prevalence of respiratory illness and its association with the air quality.
Host innate immunity is the major player against continuous microbial infection. Various pathogenic bacteria adopt the strategies to evade the immunity and show resistance toward the various established therapies. Despite the advent of many antibiotics for bacterial infections, there is a substantial need for the host-directed therapies (HDTs) to combat the infection. HDTs are recently being adopted to be useful in eradicating intracellular bacterial infection. Changing the innate immune responses of the host cells alters pathogen’s ability to reside inside the cell. MicroRNAs are the small non-coding endogenous molecules and post-transcriptional regulators to target the 3’UTR of the messenger RNA. They are reported to modulate the host’s immune responses during bacterial infections. Exploiting microRNAs as a therapeutic candidate in HDTs upon bacterial infection is still in its infancy. Here, initially, we re-analyzed the publicly available transcriptomic dataset of macrophages, infected with different pathogenic bacteria and identified significant genes and microRNAs common to the differential infections. We thus identified and miR-30e-5p, to be upregulated in different bacterial infections which enhances innate immunity to combat bacterial replication by targeting key negative regulators such as SOCS1 and SOCS3 of innate immune signaling pathways. Therefore, we propose miR-30e-5p as one of the potential candidates to be considered for additional clinical validation toward HDTs.
Dengue virus (DENV) is a mosquito‐borne flavivirus that causes frequent outbreaks in tropical countries. Due to the four different serotypes and ever‐mutating RNA genome, it is challenging to develop efficient therapeutics. Early diagnosis is crucial to prevent the severe form of dengue, leading to mortality. In the past decade, rapid advancement in the high throughput sequencing technologies has shed light on the crucial regulating role of non‐coding RNAs (ncRNAs), also known as the “dark matter” of the genome, in various pathological processes. In addition to the human host ncRNAs like microRNAs and circular RNAs, DENV also produces ncRNAs such as subgenomic flaviviral RNAs that can modulate the virus life cycle and regulate disease outcomes. This review outlines the advances in understanding the interplay between the human host and DENV ncRNAs, their regulation of the innate immune system of the host, and the prospects of the ncRNAs in clinical applications such as dengue diagnosis and promising therapeutics.
The Coronavirus disease 2019 (COVID-19) pandemic, caused by rapidly evolving variants of severe acute respiratory syndrome coronavirus (SARS-CoV-2), continues to be a global health threat. SARS-CoV-2 infection symptoms often intersect with other nonsevere respiratory infections, making early diagnosis challenging. There is an urgent need for early diagnostic and prognostic biomarkers to predict severity and reduce mortality when a sudden outbreak occurs. This study implemented a novel approach of integrating bioinformatics and machine learning algorithms over publicly available clinical COVID-19 transcriptome data sets. The robust 7-gene biomarker identified through this analysis can not only discriminate SARS-CoV-2 associated acute respiratory illness (ARI) from other types of ARIs but also can discriminate severe COVID-19 patients from nonsevere COVID-19 patients. Validation of the 7-gene biomarker in an independent blood transcriptome data set of longitudinal analysis of COVID-19 patients across various stages of the disease showed that the dysregulation of the identified biomarkers during severe disease is restored during recovery, showing their prognostic potential. The blood biomarkers identified in this study can serve as potential diagnostic candidates and help reduce COVID-19-associated mortality.
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