Organ-specific or personalized treatment for COVID-19: rationale, evidence, and potential candidates

Novel Advancements in COVID-19 and Neuroscience

From an initial cluster of cases reported in Wuhan, the SARS-Cov-2 infection has since spread globally, causing a pandemic that began on 11 March 2020 [...].

Ultrasensitive and fast detection of SARS-CoV-2 using RT-LAMP without pH-dependent dye

This study investigates the performance of reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay for the colorimetric detection of SARS-CoV-2 using fluorometric dye, namely, calcein. The detection limit (LoD) with the N-ID1 primer set resulted in superior performance, corresponding to ~ 2 copies/reaction or ~ 0.1 copies/μL of the RNA sample. The color development can be observed by the naked eye, using an ultraviolet (UV) transilluminator or a hand-UV light without the requirement of expensive devices. The average time-to-reaction (TTR) value was 26.2 min in high-copy number samples, while it was about 50 min in rRT-PCR. A mobile application was proposed to quantify the positive and negative results based on the three-color spaces (RGB, Lab, and HSB). Compared to rRT-PCR (n = 67), this assay allows fast and sensitive visual detection of SARS-CoV-2, with high sensitivity (90.9%), selectivity (100%), and accuracy (94.03%). Besides, the assay was sensitive regardless of variants. Since this assay uses a fluorescent dye for visual observation, it can be easily adapted in RT-LAMP assays with high sensitivity. Thus, it can be utilized in low-source centers and field testing such as conferences, sports meetings, refugee camps, companies, and schools.

Identification of six genes associated with COVID-19-related circadian rhythm dysfunction by integrated bioinformatic analysis

Patients with coronavirus disease 2019 (COVID-19) might cause long-term burden of insomnia, while the common pathogenic mechanisms are not elucidated. The gene expression profiles of COVID-19 patients and healthy controls were retrieved from the GEO database, while gene set related with circadian rhythm was obtained from GeneCards database. Seventy-six shared genes were screened and mainly enriched in cell cycle, cell division, and cell proliferation, and 6 hub genes were found out including CCNA2, CCNB1, CDK1, CHEK1, MKI67, and TOP2A, with positive correlation to plasma cells. In the TF-gene regulatory network, NFYA, NFIC, MEF2A, and FOXC1 showed high connectivity with hub genes. This study identified six hub genes and might provide new insights into pathogenic mechanisms and novel clinical management strategies.

RNA-seq analysis reveals an immunomodulatory peptide from highland barley activating RAW264.7 macrophages via TNF/NF-κB signaling pathway

Highland barley (HB) is an important cereal crop distributed in the plateau region. Bioactive peptides (BAPs) derived from cereal proteins have shown biological functions. However, the knowledge of highland barley peptide (HBP) is limited. This study aims to explore the immunomodulatory activity of HBP and the relationship between immunomodulatory activity and related gene expression through RNA-seq. Firstly, HBP is isolated from protease hydrolysates of HB protein, yielding 12.04% of crude HB protein. The molecular weight of HBP is about 1702 Da analyzed by gel filtration chromatography, and HBP has a specific amino acid sequence as Gln-Pro-Gln-Gln-Pro-Phe-Pro-Gln (QPQPFPQ) analyzed by LC-MS. Besides, HBP contains 42.20% hydrophobic amino acids and 10.86% basic amino acids. Next, the immunomodulatory activity of HBP in vitro shows that HBP enhances the phagocytosis of RAW264.7 macrophages, promotes nitric oxide (NO) production and the mRNA expression of pro-inflammatory genes including tumor necrosis factor α (TNF-α), interleukin 1β (IL-1β), and inducible nitric oxide synthase (iNOS), and decreases the mRNA expression of anti-inflammatory gene, transforming growth factor β1 (TGF-β1). RNA-seq analysis reveals TNF and nuclear factor kappa B (NF-κB) pathways are upregulated, and RT-qPCR is performed to verify RNA-seq analysis. In conclusion, HBP activates RAW264.7 macrophages via TNF/NF-κB signaling pathway. HBP, as a significant immunomodulatory peptide, might be a promising resource for future functional foods.

Comparative genomics and integrated system biology approach unveiled undirected phylogeny patterns, mutational hotspots, functional patterns, and molecule repurposing for monkeypox virus

Monkeypox is a viral zoonosis with symptoms that are reminiscent of those experienced in previous smallpox cases. The GSAID database (Global Initiative on Sharing Avian Influenza Data) was used to assess 630 genomes of MPXV. The phylogenetic study revealed six primary clades, as well as a smaller percentage in radiating clades. Individual clades that make up various nationalities may have formed as a result of a particular SNP hotspot type that mutated in a specific population. The most significant mutation based on a mutational hotspot analysis was found at G3729A and G5143A. The gene ORF138, which encodes the Ankyrin repeat (ANK) protein, was found to have the most mutations. This protein mediates molecular recognition via protein-protein interactions. It was shown that 243 host proteins interacted with 10 monkeypox proteins identified as the hub proteins E3, SPI2, C5, K7, E8, G6, N2, B14, CRMB, and A41 through 262 direct connections. The interaction with chemokine system-related proteins provides further evidence that the monkeypox virus suppresses human proteins to facilitate its survival against innate immunity. Several FDA-approved molecules were evaluated as possible inhibitors of F13, a significant envelope protein on the membrane of extracellular versions of the virus. A total of 2500 putative ligands were individually docked with the F13 protein. The interaction between the F13 protein and these molecules may help prevent the monkeypox virus from spreading. After being confirmed by experiments, these putative inhibitors could have an impact on the activity of these proteins and be used in monkeypox treatments.

Using system biology and bioinformatics to identify the influences of COVID-19 co-infection with influenza virus on COPD

Coronavirus disease 2019 (COVID-19) has speedily increased mortality globally. Although they are risk factors for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), less is known about the common molecular mechanisms behind COVID-19, influenza virus A (IAV), and chronic obstructive pulmonary disease (COPD). This research used bioinformatics and systems biology to find possible medications for treating COVID-19, IAV, and COPD via identifying differentially expressed genes (DEGs) from gene expression datasets (GSE171110, GSE76925, GSE106986, and GSE185576). A total of 78 DEGs were subjected to functional enrichment, pathway analysis, protein-protein interaction (PPI) network construct, hub gene extraction, and other potentially relevant disorders. Then, DEGs were discovered in networks including transcription factor (TF)-gene connections, protein-drug interactions, and DEG-microRNA (miRNA) coregulatory networks by using NetworkAnalyst. The top 12 hub genes were MPO, MMP9, CD8A, HP, ELANE, CD5, CR2, PLA2G7, PIK3R1, SLAMF1, PEX3, and TNFRSF17. We found that 44 TFs-genes, as well as 118 miRNAs, are directly linked to hub genes. Additionally, we searched the Drug Signatures Database (DSigDB) and identified 10 drugs that could potentially treat COVID-19, IAV, and COPD. Therefore, we evaluated the top 12 hub genes that could be promising DEGs for targeted therapy for SARS-CoV-2 and identified several prospective medications that may benefit COPD patients with COVID-19 and IAV co-infection.

Bioinformatics analysis based on high-throughput sequencing data to identify hub genes related to different clinical types of COVID-19

This article aims to explore hub genes related to different clinical types of cases with COVID-19 and predict the therapeutic drugs related to severe cases. The expression profile of GSE166424 was divided into four data sets according to different clinical types of COVID-19 and then calculated the differential expression genes (DEGs). The specific genes of four clinical types of COVID-19 were obtained by Venn diagram and conducted enrichment analysis, protein-protein interaction (PPI) networks analysis, screening hub genes, and ROC curve analysis. The hub genes related to severe cases were verified in GSE171110, their RNA-specific expression tissues were obtained from the HPA database, and potential therapeutic drugs were predicted through the DGIdb database. There were 536, 266, 944, and 506 specific genes related to asymptomatic infections, mild, moderate, and severe cases, respectively. The hub genes of severe specific genes were AURKB, BRCA1, BUB1, CCNB1, CCNB2, CDC20, CDC6, KIF11, TOP2A, UBE2C, and RPL11, and also differentially expressed in GSE171110 (P < 0.05), and their AUC values were greater than 0.955. The RNA tissue specificity of AURKB, CDC6, KIF11, UBE2C, CCNB2, CDC20, TOP2A, BUB1, and CCNB1 specifically enhanced on lymphoid tissue; CCNB2, CDC20, TOP2A, and BUB1 specifically expressed on the testis. Finally, 55 drugs related to severe COVID-19 were obtained from the DGIdb database. Summary, AURKB, BRCA1, BUB1, CCNB1, CCNB2, CDC20, CDC6, KIF11, TOP2A, UBE2C, and RPL11 may be potential diagnostic biomarkers for severe COVID-19, which may affect immune and male reproductive systems. 55 drugs may be potential therapeutic drugs for severe COVID-19.