In silico immune infiltration profiling combined with functional enrichment analysis reveals a potential role for naïve B cells as a trigger for severe immune responses in the lungs of COVID-19 patients

Sarcoidosis-related autoimmune inflammation in COVID-19 convalescent patients

Currently, there are a large number of reports about the development of autoimmune conditions after COVID-19. Also, there have been cases of sarcoid-like granulomas in convalescents as a part of the post-COVID-19 syndrome. Since one of the etiological theories of sarcoidosis considers it to be an autoimmune disease, we decided to study changes in the adaptive humoral immune response in sarcoidosis and SARS-CoV-2 infection and to find out whether COVID-19 can provoke the development of sarcoidosis. This review discusses histological changes in lymphoid organs in sarcoidosis and COVID-19, changes in B cell subpopulations, T-follicular helper cells (Tfh), and T-follicular regulatory cells (Tfr), and analyzes various autoantibodies detected in these pathologies. Based on the data studied, we concluded that SARS-CoV-2 infection may cause the development of autoimmune pathologies, in particular contributing to the onset of sarcoidosis in convalescents.

Stem cell-based therapy for COVID-19

While The World Health Organization (WHO) has announced that COVID-19 is no longer a public health emergency of international concern(PHEIC), the risk of reinfection and new emerging variants still makes it crucial to study and work towards the prevention of COVID-19. Stem cell and stem cell-like derivatives have shown some promising results in clinical trials and preclinical studies as an alternative treatment option for the pulmonary illnesses caused by the COVID-19 and can be used as a potential vaccine. In this review, we will systematically summarize the pathophysiological process and potential mechanisms underlying stem cell-based therapy in COVID-19, and the registered COVID-19 clinical trials, and engineered extracellular vesicle as a potential vaccine for preventing COVID-19.

Regulation of the immune system by the insulin receptor in health and disease

The signaling pathways downstream of the insulin receptor (InsR) are some of the most evolutionarily conserved pathways that regulate organism longevity and metabolism. InsR signaling is well characterized in metabolic tissues, such as liver, muscle, and fat, actively orchestrating cellular processes, including growth, survival, and nutrient metabolism. However, cells of the immune system also express the InsR and downstream signaling machinery, and there is increasing appreciation for the involvement of InsR signaling in shaping the immune response. Here, we summarize current understanding of InsR signaling pathways in different immune cell subsets and their impact on cellular metabolism, differentiation, and effector versus regulatory function. We also discuss mechanistic links between altered InsR signaling and immune dysfunction in various disease settings and conditions, with a focus on age related conditions, such as type 2 diabetes, cancer and infection vulnerability.

Antifungal Effect of Nanoparticles against COVID-19 Linked Black Fungus: A Perspective on Biomedical Applications

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible and pathogenic coronavirus that has caused a 'coronavirus disease 2019' (COVID-19) pandemic in multiple waves, which threatens human health and public safety. During this pandemic, some patients with COVID-19 acquired secondary infections, such as mucormycosis, also known as black fungus disease. Mucormycosis is a serious, acute, and deadly fungal infection caused by Mucorales-related fungal species, and it spreads rapidly. Hence, prompt diagnosis and treatment are necessary to avoid high mortality and morbidity rates. Major risk factors for this disease include uncontrolled diabetes mellitus and immunosuppression that can also facilitate increases in mucormycosis infections. The extensive use of steroids to prevent the worsening of COVID-19 can lead to black fungus infection. Generally, antifungal agents dedicated to medical applications must be biocompatible, non-toxic, easily soluble, efficient, and hypoallergenic. They should also provide long-term protection against fungal growth. COVID-19-related black fungus infection causes a severe increase in fatalities. Therefore, there is a strong need for the development of novel and efficient antimicrobial agents. Recently, nanoparticle-containing products available in the market have been used as antimicrobial agents to prevent bacterial growth, but little is known about their efficacy with respect to preventing fungal growth, especially black fungus. The present review focuses on the effect of various types of metal nanoparticles, specifically those containing silver, zinc oxide, gold, copper, titanium, magnetic, iron, and carbon, on the growth of various types of fungi. We particularly focused on how these nanoparticles can impact the growth of black fungus. We also discussed black fungus co-infection in the context of the global COVID-19 outbreak, and management and guidelines to help control COVID-19-associated black fungus infection. Finally, this review aimed to elucidate the relationship between COVID-19 and mucormycosis.

Identifying novel host-based diagnostic biomarker panels for COVID-19: a whole-blood/nasopharyngeal transcriptome meta-analysis

BACKGROUND

Regardless of improvements in controlling the COVID-19 pandemic, the lack of comprehensive insight into SARS-COV-2 pathogenesis is still a sophisticated challenge. In order to deal with this challenge, we utilized advanced bioinformatics and machine learning algorithms to reveal more characteristics of SARS-COV-2 pathogenesis and introduce novel host response-based diagnostic biomarker panels.

METHODS

In the present study, eight published RNA-Seq datasets related to whole-blood (WB) and nasopharyngeal (NP) swab samples of patients with COVID-19, other viral and non-viral acute respiratory illnesses (ARIs), and healthy controls (HCs) were integrated. To define COVID-19 meta-signatures, Gene Ontology and pathway enrichment analyses were applied to compare COVID-19 with other similar diseases. Additionally, CIBERSORTx was executed in WB samples to detect the immune cell landscape. Furthermore, the optimum WB- and NP-based diagnostic biomarkers were identified via all the combinations of 3 to 9 selected features and the 2-phases machine learning (ML) method which implemented k-fold cross validation and independent test set validation.

RESULTS

The host gene meta-signatures obtained for SARS-COV-2 infection were different in the WB and NP samples. The gene ontology and enrichment results of the WB dataset represented the enhancement in inflammatory host response, cell cycle, and interferon signature in COVID-19 patients. Furthermore, NP samples of COVID-19 in comparison with HC and non-viral ARIs showed the significant upregulation of genes associated with cytokine production and defense response to the virus. In contrast, these pathways in COVID-19 compared to other viral ARIs were strikingly attenuated. Notably, immune cell proportions of WB samples altered in COVID-19 versus HC. Moreover, the optimum WB- and NP-based diagnostic panels after two phases of ML-based validation included 6 and 8 markers with an accuracy of 97% and 88%, respectively.

CONCLUSIONS

Based on the distinct gene expression profiles of WB and NP, our results indicated that SARS-COV-2 function is body-site-specific, although according to the common signature in WB and NP COVID-19 samples versus controls, this virus also induces a global and systematic host response to some extent. We also introduced and validated WB- and NP-based diagnostic biomarkers using ML methods which can be applied as a complementary tool to diagnose the COVID-19 infection from non-COVID cases.

Immune Cells in Subretinal Wound Healing and Fibrosis

The subretinal space is devoid of any immune cells under normal conditions and is an immune privileged site. When photoreceptors and/or retinal pigment epithelial cells suffer from an injury, a wound healing process will be initiated. Retinal microglia and the complement system, as the first line of retinal defense, are activated to participate in the wound healing process. If the injury is severe or persists for a prolonged period, they may fail to heal the damage and circulating immune cells will be summoned leading to chronic inflammation and abnormal wound healing, i.e., subretinal or intraretinal fibrosis, a sight-threatening condition frequently observed in rhematogenous retinal detachment, age-related macular degeneration and recurrent uveoretinitis. Here, we discussed the principles of subretinal wound healing with a strong focus on the conditions whereby the damage is beyond the healing capacity of the retinal defense system and highlighted the roles of circulating immune cells in subretinal wound healing and fibrosis.

Effects of theaflavin-gallate in-silico binding with different proteins of SARS-CoV-2 and host inflammation and vasoregulations referring an experimental rat-lung injury

Background SARS-CoV-2 claimed 5,209,104 lives, infected 260,997,910 individuals, globally. Infection is caused due to exposure or susceptibility; deaths occur due to age,comorbidity,higher-viral-load, immuno-suppression, inflammation, and multi-organ failure. Theaflavin-gallate, the major black tea component, showed previous evidence to inhibit HIV-1. Purpose As theaflavin-gallate prevents experimental rat-lung injury, the study of inhibitory effects of theaflavin-gallate was done, on SARS-CoV-2proteins and various host proteins related to some adverse effects in COVID-19 patients. Study Design Currently, some prospective phytochemical, black-tea (Camellia-sinensis) extract (BTE) was initially tested in vivo in strong oxidant-mutagen arsenic-induced model rat lung injury similar to that of COVID-19 manifestations like severe inflammation, oxidative stress, lung tissue degenerations, and apoptotic death. In silico, extensive bioinformatics and molecular docking experiments were performed on all catechin or theaflavin derivatives of C. sinensis, and finally theaflavin-3'-O-gallate (TFMG) were screened for blocking or inactivation of several proteins of SARS CoV-2 and host adversely-acting proteins or factors. Methods In vivo experiments in DNA stability (ladder, comet assay), free radicals attack (malondialdehyde; MDA, superoxide dismutase SOD, catalase gel-zymogram assay), extra cellular matrix damage (matrix metalloprotease; MMP2and9 zymogram assay) and inflammation (TNF-α, ELISA). In silico experiments- molecular docking by AutoDock-Patchdock analysis, Surface Topology Calculation by CASTp, Grid-value calculation, and Ramachandran Plot study. Results The BTE showed strong protection of lung DNA and cell-matrix by decreasing MMPs, TNF-α, and free radicals, the same factors affecting COVID-19 patients. In silico data suggest that TFMG significantly blocked the entry, exit, and amino acids at catalytic active-site of more than thirty proteins including viral (nsp1,nsp2,Mainpro,∼-9.0 kcal/mol) and host inflammatory, oxidants, apoptotic, vaso-destabilizer molecules (FAS, CD40R, BCL2, TLR2, ∼ -10 and ACE1or2 ∼ -9.0 and AT1or2∼ -7.5 kcal/mol and more). When the binding energy of TFMG ranged from -7 to -11.7 kcal/mol(average -9.0) the same for hydroxy‑Chloroquine ranged (-2.5 to -7 average -4.5) and dexamethasone (-3.0 to -6.0, average -4.0 kcal/mol). Conclusions TFMG has some novel physicochemical or structural properties like (ACE values of binding to all tested proteins, -300 to -625), (for TFMG H-bond acceptor or donor: 15/10, for TFDG 20/13). Their topological-polar-surface-area (264Ų and 351Ų) and travel depth/height; 17.0/9.6 Å and 15.4/11.3 Å, respectively) were more potent than other compounds. Conclusively, the efficacy of TFMG may be further verified.

Transcriptome-Based Molecular Networks Uncovered Interplay Between Druggable Genes of CD8+ T Cells and Changes in Immune Cell Landscape in Patients With Pulmonary Tuberculosis

BACKGROUND

Tuberculosis (TB) is a major infectious disease, where incomplete information about host genetics and immune responses is hindering the development of transformative therapies. This study characterized the immune cell landscape and blood transcriptomic profile of patients with pulmonary TB (PTB) to identify the potential therapeutic biomarkers.

METHODS

The blood transcriptome profile of patients with PTB and controls were used for fractionating immune cell populations with the CIBERSORT algorithm and then to identify differentially expressed genes (DEGs) with R/Bioconductor packages. Later, systems biology investigations (such as semantic similarity, gene correlation, and graph theory parameters) were implemented to prioritize druggable genes contributing to the immune cell alterations in patients with TB. Finally, real time-PCR (RT-PCR) was used to confirm gene expression levels.

RESULTS

Patients with PTB had higher levels of four immune subpopulations like CD8⁺ T cells (P = 1.9 × 10^-8), natural killer (NK) cells resting (P = 6.3 × 10^-5), monocytes (P = 6.4 × 10^-6), and neutrophils (P = 1.6 × 10^-7). The functional enrichment of 624 DEGs identified in the blood transcriptome of patients with PTB revealed major dysregulation of T cell-related ontologies and pathways (q ≤ 0.05). Of the 96 DEGs shared between transcriptome and immune cell types, 39 overlapped with TB meta-profiling genetic signatures, and their semantic similarity analysis with the remaining 57 genes, yielded 45 new candidate TB markers. This study identified 9 CD8⁺ T cell-associated genes (ITK, CD2, CD6, CD247, ZAP70, CD3D, SH2D1A, CD3E, and IL7R) as potential therapeutic targets of PTB by combining computational druggability and co-expression (r² ≥ |0.7|) approaches.

CONCLUSION

The changes in immune cell proportion and the downregulation of T cell-related genes may provide new insights in developing therapeutic compounds against chronic TB.

Inflammatory activation and immune cell infiltration are main biological characteristics of SARS-CoV-2 infected myocardium

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) can target cardiomyocytes (CMs) to directly invade the heart resulting in high mortality. This study aims to explore the biological characteristics of SARS-CoV-2 infected myocardium based on omics by collecting transcriptome data and analyzing them with a series of bioinformatics tools. Totally, 86 differentially expressed genes (DEGs) were discovered in SARS-CoV-2 infected CMs, and 15 miRNAs were discovered to target 60 genes. Functional enrichment analysis indicated that these DEGs were mainly enriched in the inflammatory signaling pathway. After the protein-protein interaction (PPI) network was constructed, several genes including CCL2 and CXCL8 were regarded as the hub genes. SRC inhibitor saracatinib was predicted to potentially act against the cardiac dysfunction induced by SARS-CoV-2. Among the 86 DEGs, 28 were validated to be dysregulated in SARS-CoV-2 infected hearts. Gene Set Enrichment Analysis (GSEA) analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG) showed that malaria, IL-17 signaling pathway, and complement and coagulation cascades were significantly enriched. Immune infiltration analysis indicated that ‘naive B cells’ was significantly increased in the SARS-CoV-2 infected heart. The above results may help to improve the prognosis of patients with COVID-19.

Understanding Gene Expression and Transcriptome Profiling of COVID-19: An Initiative Towards the Mapping of Protective Immunity Genes Against SARS-CoV-2 Infection

The COVID-19 pandemic has created an urgent situation throughout the globe. Therefore, it is necessary to identify the differentially expressed genes (DEGs) in COVID-19 patients to understand disease pathogenesis and the genetic factor(s) responsible for inter-individual variability. The DEGs will help understand the disease's potential underlying molecular mechanisms and genetic characteristics, including the regulatory genes associated with immune response elements and protective immunity. This study aimed to determine the DEGs in mild and severe COVID-19 patients versus healthy controls. The Agilent-085982 Arraystar human lncRNA V5 microarray GEO dataset (GSE164805 dataset) was used for this study. We used statistical tools to identify the DEGs. Our 15 human samples dataset was divided into three groups: mild, severe COVID-19 patients and healthy control volunteers. We compared our result with three other published gene expression studies of COVID-19 patients. Along with significant DEGs, we developed an interactome map, a protein-protein interaction (PPI) pattern, a cluster analysis of the PPI network, and pathway enrichment analysis. We also performed the same analyses with the top-ranked genes from the three other COVID-19 gene expression studies. We also identified differentially expressed lncRNA genes and constructed protein-coding DEG-lncRNA co-expression networks. We attempted to identify the regulatory genes related to immune response elements and protective immunity. We prioritized the most significant 29 protein-coding DEGs. Our analyses showed that several DEGs were involved in forming interactome maps, PPI networks, and cluster formation, similar to the results obtained using data from the protein-coding genes from other investigations. Interestingly we found six lncRNAs (TALAM1, DLEU2, and UICLM CASC18, SNHG20, and GNAS) involved in the protein-coding DEG-lncRNA network; which might be served as potential biomarkers for COVID-19 patients. We also identified three regulatory genes from our study and 44 regulatory genes from the other investigations related to immune response elements and protective immunity. We were able to map the regulatory genes associated with immune elements and identify the virogenomic responses involved in protective immunity against SARS-CoV-2 infection during COVID-19 development.

Targeting S1PR1 May Result in Enhanced Migration of Cancer Cells in Bladder Carcinoma

Clinical bladder tumor histological analysis shows that high expression of S1PR1 is associated with poor patient prognosis. However, there are no studies that describe the underlying mechanism. To investigate the relative distribution and actual function of S1PR1 in bladder tumors, we analyzed multiple clinical databases in combination with tumor purity and immune cell infiltration simulations, as well as databases of well-defined histological phenotypes of bladder cancer, and single-cell sequencing of adjacent normal tissues and bladder tumors, and further compared them with bladder cancer cell lines. The results showed that S1PR1 expression was generally higher in normal tissues than in bladder cancer tissues, and its distribution was mainly in endothelial cells or immune cells. The association between high S1PR1 expression and poor prognosis may be due to tumor invasion of adjacent normal tissues, where highly expressed S1PR1 may affect prognostic interpretation. The effect of S1PR1 itself on cancer cells was associated with cell adhesion, and in bladder cancer cells, S1PR1 expression was negatively correlated with cell motility. Moreover, the use of FTY-720 will cause an increased metastatic ability of bladder cancer cells. In conclusion, we suggest that the use of S1PR1-specific inhibition as a synergistic treatment requires more observation and consideration.

CytokineLink: A Cytokine Communication Map to Analyse Immune Responses-Case Studies in Inflammatory Bowel Disease and COVID-19

Intercellular communication mediated by cytokines is critical to the development of immune responses, particularly in the context of infectious and inflammatory diseases. By releasing these small molecular weight peptides, the source cells can influence numerous intracellular processes in the target cells, including the secretion of other cytokines downstream. However, there are no readily available bioinformatic resources that can model cytokine-cytokine interactions. In this effort, we built a communication map between major tissues and blood cells that reveals how cytokine-mediated intercellular networks form during homeostatic conditions. We collated the most prevalent cytokines from the literature and assigned the proteins and their corresponding receptors to source tissue and blood cell types based on enriched consensus RNA-Seq data from the Human Protein Atlas database. To assign more confidence to the interactions, we integrated the literature information on cell-cytokine interactions from two systems of immunology databases, immuneXpresso and ImmunoGlobe. From the collated information, we defined two metanetworks: a cell-cell communication network connected by cytokines; and a cytokine-cytokine interaction network depicting the potential ways in which cytokines can affect the activity of each other. Using expression data from disease states, we then applied this resource to reveal perturbations in cytokine-mediated intercellular signalling in inflammatory and infectious diseases (ulcerative colitis and COVID-19, respectively). For ulcerative colitis, with CytokineLink, we demonstrated a significant rewiring of cytokine-mediated intercellular communication between non-inflamed and inflamed colonic tissues. For COVID-19, we were able to identify cell types and cytokine interactions following SARS-CoV-2 infection, highlighting important cytokine interactions that might contribute to severe illness in a subgroup of patients. Such findings have the potential to inform the development of novel, cytokine-targeted therapeutic strategies. CytokineLink is freely available for the scientific community through the NDEx platform and the project github repository.