Transcriptome of nasopharyngeal samples from COVID-19 patients and a comparative analysis with other SARS-CoV-2 infection models reveal disparate host responses against SARS-CoV-2

Upper Airway Epithelial Tissue Transcriptome Analysis Reveals Immune Signatures Associated with COVID-19 Severity in Ghanaians

The immunological signatures driving the severity of coronavirus disease 19 (COVID-19) in Ghanaians remain poorly understood. We performed bulk transcriptome sequencing of nasopharyngeal samples from severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-infected Ghanaians with mild and severe COVID-19, as well as healthy controls to characterize immune signatures at the primary SARS-CoV-2 infection site and identify drivers of disease severity. Generally, a heightened antiviral response was observed in SARS-CoV-2-infected Ghanaians compared with uninfected controls. COVID-19 severity was associated with immune suppression, overexpression of proinflammatory cytokines, including CRNN, IL1A, S100A7, and IL23A, and activation of pathways involved in keratinocyte proliferation. SAMD9L was among the differentially regulated interferon-stimulated genes in our mild and severe disease cohorts, suggesting that it may play a critical role in SARS-CoV-2 pathogenesis. By comparing our data with a publicly available dataset from a non-African (Indians) (GSE166530), an elevated expression of antiviral response-related genes was noted in COVID-19-infected Ghanaians. Overall, the study describes immune signatures driving COVID-19 severity in Ghanaians and identifies immune drivers that could serve as potential prognostic markers for future outbreaks or pandemics. It further provides important preliminary evidence suggesting differences in antiviral response at the upper respiratory interface in sub-Saharan Africans (Ghanaians) and non-Africans, which could be contributing to the differences in disease outcomes. Further studies using larger datasets from different populations will expand on these findings.

Hypoxia and Activation of Neutrophil Degranulation-Related Genes in the Peripheral Blood of COVID-19 Patients

Severe COVID-19 is characterized by systematic hyper-inflammation and subsequent damage to various organs. Therefore, it is critical to trace this cascade of hyper-inflammation. Blood transcriptome has been routinely utilized in the interrogation of host immune response in COVID-19 and other infectious conditions. In this study, consensus gene dysregulation in the blood was obtained from 13 independent transcriptome studies on COVID-19. Among the up-regulated genes, the most prominent functional categories were neutrophil degranulation and cell cycle, which is clearly different from the classical activation of interferon signaling pathway in seasonal flu. As for the potential upstream causal factors of the atypical gene dysregulation, systemic hypoxia was further examined because it is much more widely reported in COVID-19 than that in seasonal flu. It was found that both physiological and pathological hypoxia can induce activation of neutrophil degranulation-related genes in the blood. Furthermore, COVID-19 patients with different requirement for oxygen intervention showed distinctive levels of gene expression related to neutrophil degranulation in the whole blood, which was validated in isolated neutrophils. Thus, activation of neutrophil degranulation-related genes in the blood of COVID-19 could be partially attributed to hypoxia. Interestingly, similar pattern was also observed in H1N1 infection (the cause of Spanish flu) and several other severe respiratory viral infections. As for the molecular mechanism, both HIF-dependent and HIF-independent pathways have been examined. Since the activation of neutrophil degranulation-related genes is highly correlated with disease severity in COVID-19, early detection of hypoxia and active intervention may prevent further activation of neutrophil degranulation-related genes and other harmful downstream hyper-inflammation. This common mechanism is applicable to current and future pandemic as well as the severe form of common respiratory infection.

Lung transcriptomics of K18-hACE2 mice highlights mechanisms and genes involved in the MVA-S vaccine-mediated immune response and protection against SARS-CoV-2 infection

Unravelling the molecular mechanism of COVID-19 vaccines through transcriptomic pathways involved in the host response to SARS-CoV-2 infection is key to understand how vaccines work, and for the development of optimized COVID-19 vaccines that can prevent the emergence of SARS-CoV-2 variants of concern (VoCs) and future outbreaks. In this study, we investigated the effects of vaccination with a modified vaccinia virus Ankara (MVA)-based vector expressing the full-length SARS-CoV-2 spike protein (MVA-S) on the lung transcriptome from susceptible K18-hACE2 mice after SARS-CoV-2 infection. One dose of MVA-S regulated genes related to viral infection control, inflammation processes, T-cell response, cytokine production and IFN-γ signalling. Down-regulation of Rhcg and Tnfsf18 genes post-vaccination with one and two doses of MVA-S may represent a mechanism for controlling infection immunity and vaccine-induced protection. One dose of MVA-S provided partial protection with a distinct lung transcriptomic profile to healthy animals, while two doses of MVA-S fully protected against infection with a transcriptomic profile comparable to that of non-vaccinated healthy animals. This suggests that the MVA-S booster generates a robust and rapid antigen-specific immune response preventing virus infection. Notably, down-regulation of Atf3 and Zbtb16 genes in mice vaccinated with two doses of MVA-S may contribute to vaccine control of innate immune system and inflammation processes in the lungs during SARS-CoV-2 infection. This study shows host transcriptomic mechanisms likely involved in the MVA-S vaccine-mediated immune response against SARS-CoV-2 infection, which could help in improving vaccine dose assessment and developing novel, well-optimized SARS-CoV-2 vaccine candidates against prevalent or emerging VoCs.

Analysis of blood and nasal epithelial transcriptomes to identify mechanisms associated with control of SARS-CoV-2 viral load in the upper respiratory tract

OBJECTIVES

The amount of SARS-CoV-2 detected in the upper respiratory tract (URT viral load) is a key driver of transmission of infection. Current evidence suggests that mechanisms constraining URT viral load are different from those controlling lower respiratory tract viral load and disease severity. Understanding such mechanisms may help to develop treatments and vaccine strategies to reduce transmission. Combining mathematical modelling of URT viral load dynamics with transcriptome analyses we aimed to identify mechanisms controlling URT viral load.

METHODS

COVID-19 patients were recruited in Spain during the first wave of the pandemic. RNA sequencing of peripheral blood and targeted NanoString nCounter transcriptome analysis of nasal epithelium were performed and gene expression analysed in relation to paired URT viral load samples collected within 15 days of symptom onset. Proportions of major immune cells in blood were estimated from transcriptional data using computational differential estimation. Weighted correlation network analysis (adjusted for cell proportions) and fixed transcriptional repertoire analysis were used to identify associations with URT viral load, quantified as standard deviations (z-scores) from an expected trajectory over time.

RESULTS

Eighty-two subjects (50% female, median age 54 years (range 3-73)) with COVID-19 were recruited. Paired URT viral load samples were available for 16 blood transcriptome samples, and 17 respiratory epithelial transcriptome samples. Natural Killer (NK) cells were the only blood cell type significantly correlated with URT viral load z-scores (r = -0.62, P = 0.010). Twenty-four blood gene expression modules were significantly correlated with URT viral load z-score, the most significant being a module of genes connected around IFNA14 (Interferon Alpha-14) expression (r = -0.60, P = 1e-10). In fixed repertoire analysis, prostanoid-related gene expression was significantly associated with higher viral load. In nasal epithelium, only GNLY (granulysin) gene expression showed significant negative correlation with viral load.

CONCLUSIONS

Correlations between the transcriptional host response and inter-individual variations in SARS-CoV-2 URT viral load, revealed many molecular mechanisms plausibly favouring or constraining viral replication. Existing evidence corroborates many of these mechanisms, including likely roles for NK cells, granulysin, prostanoids and interferon alpha-14. Inhibition of prostanoid production and administration of interferon alpha-14 may be attractive transmission-blocking interventions.

Bioinformatics and system biology analysis revealed the crosstalk between COVID-19 and osteoarthritis

BACKGROUND

The global coronavirus disease 2019 (COVID-19) outbreak has significantly impacted public health. Moreover, there has been an association between the incidence and severity of osteoarthritis (OA) and the onset of COVID-19. However, the optimal diagnosis and treatment strategies for patients with both diseases remain uncertain. Bioinformatics is a novel approach that may help find the common pathology between COVID-19 and OA.

METHODS

Differentially expressed genes (DEGs) were screened by R package "limma." Functional enrichment analyses were performed to find key biological functions. Protein-protein interaction (PPI) network was constructed by STRING database and then Cytoscape was used to select hub genes. External data sets and OA mouse model validated and identified the hub genes in both mRNA and protein levels. Related transcriptional factors (TF) and microRNAs (miRNAs) were predicted with miRTarBase and JASPR database. Candidate drugs were obtained from Drug Signatures database. The immune infiltration levels of COVID-19 and OA were evaluated by CIBERSORT and scRNA-seq.

RESULTS

A total of 74 common DEGs were identified between COVID-19 and OA. Receiver operating characteristic curves validated the effective diagnostic values (area under curve > 0.7) of four hub genes (matrix metalloproteinases 9, ATF3, CCL4, and RELA) in both the training and validation data sets of COVID-19 and OA. Quantitative polymerase chain reaction and Western Blot showed significantly higher hub gene expression in OA mice than in healthy controls. A total of 84 miRNAs and 28 TFs were identified to regulate the process of hub gene expression. The top 10 potential drugs were screened including "Simvastatin," "Hydrocortisone," and "Troglitazone" which have been proven by Food and Drug Administration. Correlated with hub gene expression, Macrophage M0 was highly expressed while Natural killer cells and Mast cells were low in both COVID-19 and OA.

CONCLUSION

Four hub genes, disease-related miRNAs, TFs, drugs, and immune infiltration help to understand the pathogenesis and perform further studies, providing a potential therapy target for COVID-19 and OA.

Exploring dysregulated immune response genes and endothelial dysfunction biomarkers as predictors of severe COVID-19

Identifying individuals and factors associated with severe cases of COVID-19 is crucial as the pandemic continues to spread globally. Effective biomarkers for predicting severe cases are essential for optimizing clinical management, therapy, and preventing unfavorable outcomes. This exploratory observational study aimed to investigate the expression of dysregulated immune response genes (ARG1, NOS2, ITGA4, and SELPLG) in total leukocytes, plasmatic levels of P-selectin and PSGL-1, and their clinical associations in patients with mild and severe COVID-19. Data from 117 confirmed COVID-19 patients (severe = 58, mild = 59) were collected upon admission. Gene expression was measured using RT-qPCR, and plasma protein levels assessed with ELISA assay. The severe COVID-19 patient group had a higher median age of 62.0 (p = 0.0001), a higher proportion of black individuals (86.2%, p < 0.0001), and more males (65.5%, p = 0.007). The neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) were significantly higher in the severe COVID-19 patient group (p < 0.0001), indicating ongoing systemic inflammation. Severe COVID-19 patients also exhibited increased expression of ARG1 (p < 0.05) and SELPLG (p < 0.0001) genes, as well as higher concentrations of soluble P-selectin (p < 0.005) and PSGL-1 (p < 0.05) proteins. Multivariate analysis revealed that NLR, PLR, the expression of SELPLG and sPSGL-1 were independent predictors of COVID-19 severity. In conclusion, this study suggests that biomarkers of endothelial dysfunction and dysregulated leukocyte responses are associated with COVID-19 severity, serving as promising predictive tools for optimizing clinical management and patient monitoring.

SARS-CoV-2 infection severity and mortality is modulated by repeat-mediated regulation of alternative splicing

Like single-stranded RNA viruses, SARS-CoV-2 hijacks the host transcriptional machinery for its own replication. Numerous traditional differential gene expression-based investigations have examined the diverse clinical symptoms caused by SARS-CoV-2 infection. The virus, on the other hand, also affects the host splicing machinery, causing host transcriptional dysregulation, which can lead to diverse clinical outcomes. Hence, in this study, we performed host transcriptome sequencing of 125 hospital-admitted COVID-19 patients to understand the transcriptomic differences between the severity sub-phenotypes of mild, moderate, severe, and mortality. We performed transcript-level differential expression analysis, investigated differential isoform usage, looked at the splicing patterns within the differentially expressed transcripts (DET), and elucidated the possible genome regulatory features. Our DTE analysis showed evidence of diminished transcript length and diversity as well as altered promoter site usage in the differentially expressed protein-coding transcripts in the COVID-19 mortality patients. We also investigated the potential mechanisms driving the alternate splicing and discovered a compelling differential enrichment of repeats in the promoter region and a specific enrichment of SINE (Alu) near the splicing sites of differentially expressed transcripts. These findings suggested a repeat-mediated plausible regulation of alternative splicing as a potential modulator of COVID-19 disease severity. In this work, we emphasize the role of scarcely elucidated functional role of alternative splicing in influencing COVID-19 disease severity sub-phenotypes, clinical outcomes, and its putative mechanism. IMPORTANCE The wide range of clinical symptoms reported during the COVID-19 pandemic inherently highlights the numerous factors that influence the progression and prognosis of SARS-CoV-2 infection. While several studies have investigated the host response and discovered immunological dysregulation during severe infection, most of them have the common theme of focusing only up to the gene level. Viruses, especially RNA viruses, are renowned for hijacking the host splicing machinery for their own proliferation, which inadvertently puts pressure on the host transcriptome, exposing another side of the host response to the pathogen challenge. Therefore, in this study, we examine host response at the transcript-level to discover a transcriptional difference that culminates in differential gene-level expression. Importantly, this study highlights diminished transcript diversity and possible regulation of transcription by differentially abundant repeat elements near the promoter region and splicing sites in COVID-19 mortality patients, which together with differentially expressed isoforms hold the potential to elaborate disease severity and outcome.

Systems-level profiling of early peripheral host-response landscape variations across COVID-19 severity states in an Indian cohort

Host immune response to COVID-19 plays a significant role in regulating disease severity. Although big data analysis has provided significant insights into the host biology of COVID-19 across the world, very few such studies have been performed in the Indian population. This study utilizes a transcriptome-integrated network analysis approach to compare the immune responses between asymptomatic or mild and moderate-severe COVID-19 patients in an Indian cohort. An immune suppression phenotype is observed in the early stages of moderate-severe COVID-19 manifestation. A number of pathways are identified that play crucial roles in the host control of the disease such as the type I interferon response and classical complement pathway which show different activity levels across the severity spectrum. This study also identifies two transcription factors, IRF7 and ESR1, to be important in regulating the severity of COVID-19. Overall this study provides a deep understanding of the peripheral immune landscape in the COVID-19 severity spectrum in the Indian genetic background and opens up future research avenues to compare immune responses across global populations.

Host Expression Profiling From Diagnostic Coronavirus Disease 2019 Swabs Associates Upper Respiratory Tract Immune Responses With Radiologic Lung Pathology and Clinical Severity

Background

COVID-19 presents with a breadth of symptomatology including a spectrum of clinical severity requiring intensive care unit (ICU) admission. We investigated the mucosal host gene response at the time of gold standard COVID-19 diagnosis using clinical surplus RNA from upper respiratory tract swabs.

Methods

Host response was evaluated by RNA-sequencing, and transcriptomic profiles of 44 unvaccinated patients including outpatients and in-patients with varying levels of oxygen supplementation were included. Additionally, chest X-rays were reviewed and scored for patients in each group.

Results

Host transcriptomics revealed significant changes in the immune and inflammatory response. Patients destined for the ICU were distinguished by the significant upregulation of immune response pathways and inflammatory chemokines, including cxcl2 which has been linked to monocyte subsets associated with COVID-19 related lung damage. In order to temporally associate gene expression profiles in the upper respiratory tract at diagnosis of COVID-19 with lower respiratory tract sequalae, we correlated our findings with chest radiography scoring, showing nasopharygeal or mid-turbinate sampling can be a relevant surrogate for downstream COVID-19 pneumonia/ICU severity.

Conclusions

This study demonstrates the potential and relevance for ongoing study of the mucosal site of infection of SARS-CoV-2 using a single sampling that remains standard of care in hospital settings. We highlight also the archival value of high quality clinical surplus specimens, especially with rapidly evolving COVID-19 variants and changing public health/vaccination measures.

High-throughput sequencing approaches applied to SARS-CoV-2

High-throughput sequencing is crucial for surveillance and control of viral outbreaks. During the ongoing coronavirus disease 2019 (COVID-19) pandemic, advances in the high-throughput sequencing technology resources have enhanced diagnosis, surveillance, and vaccine discovery. From the onset of the pandemic in December 2019, several genome-sequencing approaches have been developed and supported across the major sequencing platforms such as Illumina, Oxford Nanopore, PacBio, MGI DNBSEQTM and Ion Torrent. Here, we share insights from the sequencing approaches developed for sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) between December 2019 and October 2022.

Role of different types of RNA molecules in the severity prediction of SARS-CoV-2 patients

SARS-CoV-2 pandemic is the current threat of the world with enormous number of deceases. As most of the countries have constraints on resources, particularly for intensive care and oxygen, severity prediction with high accuracy is crucial. This prediction will help the medical society in the selection of patients with the need for these constrained resources. Literature shows that using clinical data in this study is the common trend and molecular data is rarely utilized in this prediction. As molecular data carry more disease related information, in this study, three different types of RNA molecules ( lncRNA, miRNA and mRNA) of SARS-COV-2 patients are used to predict the severity stage and treatment stage of those patients. Using seven different machine learning algorithms along with several feature selection techniques shows that in both phenotypes, feature importance selected features provides the best accuracy along with random forest classifier. Further to this, it shows that in the severity stage prediction miRNA and lncRNA give the best performance, and lncRNA data gives the best in treatment stage prediction. As most of the studies related to molecular data uses mRNA data, this is an interesting finding.

Selection of Ideal Reference Genes for Gene Expression Analysis in COVID-19 and Mucormycosis

Selection of reference genes during real-time quantitative PCR (qRT-PCR) is critical to determine accurate and reliable mRNA expression. Nonetheless, not a single study has investigated the expression stability of candidate reference genes to determine their suitability as internal controls in SARS-CoV-2 infection or COVID-19-associated mucormycosis (CAM). Using qRT-PCR, we determined expression stability of the nine most commonly used housekeeping genes, namely, TATA-box binding protein (TBP), cyclophilin (CypA), β-2-microglobulin (B2M), 18S rRNA (18S), peroxisome proliferator-activated receptor gamma (PPARG) coactivator 1 alpha (PGC-1α), glucuronidase beta (GUSB), hypoxanthine phosphoribosyltransferase 1 (HPRT-1), β-ACTIN, and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) in patients with COVID-19 of various severities (asymptomatic, mild, moderate, and severe) and those with CAM. We used statistical algorithms (delta-CT [threshold cycle], NormFinder, BestKeeper, GeNorm, and RefFinder) to select the most appropriate reference gene and observed that clinical severity profoundly influences expression stability of reference genes. CypA demonstrated the most consistent expression irrespective of disease severity and emerged as the most suitable reference gene in COVID-19 and CAM. Incidentally, GAPDH, the most commonly used reference gene, showed the maximum variations in expression and emerged as the least suitable. Next, we determined expression of nuclear factor erythroid 2-related factor 2 (NRF2), interleukin-6 (IL-6), and IL-15 using CypA and GAPDH as internal controls and show that CypA-normalized expression matches well with the RNA sequencing-based expression of these genes. Further, IL-6 expression correlated well with the plasma levels of IL-6 and C-reactive protein, a marker of inflammation. In conclusion, GAPDH emerged as the least suitable and CypA as the most suitable reference gene in COVID-19 and CAM. The results highlight the expression variability of housekeeping genes due to disease severity and provide a strong rationale for identification of appropriate reference genes in other chronic conditions as well. IMPORTANCE Gene expression studies are critical to develop new diagnostics, therapeutics, and prognostic modalities. However, accurate determination of expression requires data normalization with a reference gene, whose expression does not vary across different disease stages. Misidentification of a reference gene can produce inaccurate results. Unfortunately, despite the global impact of COVID-19 and an urgent unmet need for better treatment, not a single study has investigated the expression stability of housekeeping genes across the disease spectrum to determine their suitability as internal controls. Our study identifies CypA and then TBP as the two most suitable reference genes for COVID-19 and CAM. Further, GAPDH, the most commonly used reference gene in COVID-19 studies, turned out to be the least suitable. This work fills an important gap in the field and promises to facilitate determination of an accurate expression of genes to catalyze development of novel molecular diagnostics and therapeutics for improved patient care.

Quantitative Reverse Transcription PCR Surveillance of SARS-CoV-2 Variants of Concern in Wastewater of Two Counties in Texas, United States

After its emergence in late November/December 2019, the severe acute respiratory syndrome coronavirus 2 virus (SARS-CoV-2) rapidly spread globally. Recognizing that this virus is shed in feces of individuals and that viral RNA is detectable in wastewater, testing for SARS-CoV-2 in sewage collections systems has allowed for the monitoring of a community's viral burden. Over a 9 month period, the influents of two regional wastewater treatment facilities were concurrently examined for wild-type SARS-CoV-2 along with variants B.1.1.7 and B.1.617.2 incorporated as they emerged. Epidemiological data including new confirmed COVID-19 cases and associated hospitalizations and fatalities were tabulated within each location. RNA from SARS-CoV-2 was detectable in 100% of the wastewater samples, while variant detection was more variable. Quantitative reverse transcription PCR (RT-qPCR) results align with clinical trends for COVID-19 cases, and increases in COVID-19 cases were positively related with increases in SARS-CoV-2 RNA load in wastewater, although the strength of this relationship was location specific. Our observations demonstrate that clinical and wastewater surveillance of SARS-CoV-2 wild type and constantly emerging variants of concern can be combined using RT-qPCR to characterize population infection dynamics. This may provide an early warning for at-risk communities and increases in COVID-19 related hospitalizations.

Predicting COVID-19 disease severity from SARS-CoV-2 spike protein sequence by mixed effects machine learning

Epidemiological studies show that COVID-19 variants-of-concern, like Delta and Omicron, pose different risks for severe disease, but they typically lack sequence-level information for the virus. Studies which do obtain viral genome sequences are generally limited in time, location, and population scope. Retrospective meta-analyses require time-consuming data extraction from heterogeneous formats and are limited to publicly available reports. Fortuitously, a subset of GISAID, the global SARS-CoV-2 sequence repository, includes "patient status" metadata that can indicate whether a sequence record is associated with mild or severe disease. While GISAID lacks data on comorbidities relevant to severity, such as obesity and chronic disease, it does include metadata for age and sex to use as additional attributes in modeling. With these caveats, previous efforts have demonstrated that genotype-patient status models can be fit to GISAID data, particularly when country-of-origin is used as an additional feature. But are these models robust and biologically meaningful? This paper shows that, in fact, temporal and geographic biases in sequences submitted to GISAID, as well as the evolving pandemic response, particularly reduction in severe disease due to vaccination, create complex issues for model development and interpretation. This paper poses a potential solution: efficient mixed effects machine learning using GPBoost, treating country as a random effect group. Training and validation using temporally split GISAID data and emerging Omicron variants demonstrates that GPBoost models are more predictive of the impact of spike protein mutations on patient outcomes than fixed effect XGBoost, LightGBM, random forests, and elastic net logistic regression models.

RNA sequence analysis of nasopharyngeal swabs from asymptomatic and mildly symptomatic patients with COVID-19

OBJECTIVES

The characterization of asymptomatic and mildly symptomatic patients with COVID-19 by observing changes in gene expression profile and possible bacterial coinfection is relevant to be investigated. We aimed to identify transcriptomic and coinfection profiles in both groups of patients.

METHODS

A ribonucleic acid (RNA) sequence analysis on nasopharyngeal swabs were performed using a shotgun sequencing pipeline. Differential gene analysis, viral genome assembly, and metagenomics analysis were further performed using the retrieved data.

RESULTS

Both groups of patients underwent a cilia modification and mRNA splicing. Modulations in macroautophagy, epigenetics, and cell cycle processes were observed specifically in the asymptomatic group. Modulation in the RNA transport was found specifically in the mildly symptomatic group. The mildly symptomatic group showed modulation in the RNA transport and upregulation of autophagy regulator genes and genes in the complement system. No link between viral variants and disease severity was found. Microbiome analysis revealed the elevation of Streptococcus pneumoniae and Veillonella parvula proportion in symptomatic patients.

CONCLUSION

A reduction in the autophagy influx and modification in the epigenetic profile might be involved in halting the disease progression. A global dysregulation of RNA processing and translation might cause more severe outcomes in symptomatic individuals. Coinfection by opportunistic microflora should be taken into account when assessing the possible outcome of SARS-CoV-2 infection.

The Chemokines CXC, CC and C in the Pathogenesis of COVID-19 Disease and as Surrogates of Vaccine-Induced Innate and Adaptive Protective Responses

COVID-19 is one of the progressive viral pandemics that originated from East Asia. COVID-19 or SARS-CoV-2 has been shown to be associated with a chain of physio-pathological mechanisms that are basically immunological in nature. In addition, chemokines have been proposed as a subgroup of chemotactic cytokines with different activities ranging from leukocyte recruitment to injury sites, irritation, and inflammation to angiostasis and angiogenesis. Therefore, researchers have categorized the chemotactic elements into four classes, including CX3C, CXC, CC, and C, based on the location of the cysteine motifs in their structures. Considering the severe cases of COVID-19, the hyperproduction of particular chemokines occurring in lung tissue as well as pro-inflammatory cytokines significantly worsen the disease prognosis. According to the studies conducted in the field documenting the changing expression of CXC and CC chemokines in COVID-19 cases, the CC and CXC chemokines contribute to this pandemic, and their impact could reflect the development of reasonable strategies for COVID-19 management. The CC and the CXC families of chemokines are important in host immunity to viral infections and along with other biomarkers can serve as the surrogates of vaccine-induced innate and adaptive protective responses, facilitating the improvement of vaccine efficacy. Furthermore, the immunogenicity elicited by the chemokine response to adenovirus vector vaccines may constitute the basis of vaccine-induced immune thrombotic thrombocytopaenia.

Identification of Novel Therapeutic Candidates Against SARS-CoV-2 Infections: An Application of RNA Sequencing Toward mRNA Based Nanotherapeutics

Due to fast transmission and various circulating SARS-CoV-2 variants, a significant increase of coronavirus 2019 infection cases with acute respiratory symptoms has prompted worries about the efficiency of current vaccines. The possible evasion from vaccine immunity urged scientists to identify novel therapeutic targets for developing improved vaccines to manage worldwide COVID-19 infections. Our study sequenced pooled peripheral blood mononuclear cells transcriptomes of SARS-CoV-2 patients with moderate and critical clinical outcomes to identify novel potential host receptors and biomarkers that can assist in developing new translational nanomedicines and vaccine therapies. The dysregulated signatures were associated with humoral immune responses in moderate and critical patients, including B-cell activation, cell cycle perturbations, plasmablast antibody processing, adaptive immune responses, cytokinesis, and interleukin signaling pathway. The comparative and longitudinal analysis of moderate and critically infected groups elucidated diversity in regulatory pathways and biological processes. Several immunoglobin genes (IGLV9-49, IGHV7-4, IGHV3-64, IGHV1-24, IGKV1D-12, and IGKV2-29), ribosomal proteins (RPL29, RPL4P2, RPL5, and RPL14), inflammatory response related cytokines including Tumor Necrosis Factor (TNF, TNFRSF17, and TNFRSF13B), C-C motif chemokine ligands (CCL3, CCL25, CCL4L2, CCL22, and CCL4), C-X-C motif chemokine ligands (CXCL2, CXCL10, and CXCL11) and genes related to cell cycle process and DNA proliferation (MYBL2, CDC20, KIFC1, and UHCL1) were significantly upregulated among SARS-CoV-2 infected patients. 60S Ribosomal protein L29 (RPL29) was a highly expressed gene among all COVID-19 infected groups. Our study suggested that identifying differentially expressed genes (DEGs) based on disease severity and onset can be a powerful approach for identifying potential therapeutic targets to develop effective drug delivery systems against SARS-CoV-2 infections. As a result, potential therapeutic targets, such as the RPL29 protein, can be tested in vivo and in vitro to develop future mRNA-based translational nanomedicines and therapies to combat SARS-CoV-2 infections.

Identification of COVID-19-Specific Immune Markers Using a Machine Learning Method

Notably, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a tight relationship with the immune system. Human resistance to COVID-19 infection comprises two stages. The first stage is immune defense, while the second stage is extensive inflammation. This process is further divided into innate and adaptive immunity during the immune defense phase. These two stages involve various immune cells, including CD4⁺ T cells, CD8⁺ T cells, monocytes, dendritic cells, B cells, and natural killer cells. Various immune cells are involved and make up the complex and unique immune system response to COVID-19, providing characteristics that set it apart from other respiratory infectious diseases. In the present study, we identified cell markers for differentiating COVID-19 from common inflammatory responses, non-COVID-19 severe respiratory diseases, and healthy populations based on single-cell profiling of the gene expression of six immune cell types by using Boruta and mRMR feature selection methods. Some features such as IFI44L in B cells, S100A8 in monocytes, and NCR2 in natural killer cells are involved in the innate immune response of COVID-19. Other features such as ZFP36L2 in CD4⁺ T cells can regulate the inflammatory process of COVID-19. Subsequently, the IFS method was used to determine the best feature subsets and classifiers in the six immune cell types for two classification algorithms. Furthermore, we established the quantitative rules used to distinguish the disease status. The results of this study can provide theoretical support for a more in-depth investigation of COVID-19 pathogenesis and intervention strategies.

Systems biology models to identify the influence of SARS-CoV-2 infections to the progression of human autoimmune diseases

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been circulating since 2019, and its global dominance is rising. Evidences suggest the respiratory illness SARS-CoV-2 has a sensitive affect on causing organ damage and other complications to the patients with autoimmune diseases (AD), posing a significant risk factor. The genetic interrelationships and molecular appearances between SARS-CoV-2 and AD are yet unknown. We carried out the transcriptomic analytical framework to delve into the SARS-CoV-2 impacts on AD progression. We analyzed both gene expression microarray and RNA-Seq datasets from SARS-CoV-2 and AD affected tissues. With neighborhood-based benchmarks and multilevel network topology, we obtained dysfunctional signaling and ontological pathways, gene disease (diseasesome) association network and protein-protein interaction network (PPIN), uncovered essential shared infection recurrence connectivities with biological insights underlying between SARS-CoV-2 and AD. We found a total of 77, 21, 9, 54 common DEGs for SARS-CoV-2 and inflammatory bowel disorder (IBD), SARS-CoV-2 and rheumatoid arthritis (RA), SARS-CoV-2 and systemic lupus erythematosus (SLE) and SARS-CoV-2 and type 1 diabetes (T1D). The enclosure of these common DEGs with bimolecular networks revealed 10 hub proteins (FYN, VEGFA, CTNNB1, KDR, STAT1, B2M, CD3G, ITGAV, TGFB3). Drugs such as amlodipine besylate, vorinostat, methylprednisolone, and disulfiram have been identified as a common ground between SARS-CoV-2 and AD from drug repurposing investigation which will stimulate the optimal selection of medications in the battle against this ongoing pandemic triggered by COVID-19.

Factors associated with weak positive SARS-CoV-2 diagnosis by reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR)

During the COVID-19 pandemic, the reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) assay has been the primary method of diagnosis of SARS-CoV-2 infection. However, RT-qPCR assay interpretation can be ambiguous with no universal absolute cut-off value to determine sample positivity, which particularly complicates the analysis of samples with high Ct values, or weak positives. Therefore, we sought to analyse factors associated with weak positive SARS-CoV-2 diagnosis.

We analysed sample data associated with all positive SARS-CoV-2 RT-qPCR diagnostic tests performed by the Victorian Infectious Diseases Reference Laboratory (VIDRL) in Melbourne, Australia, during the Victorian first wave (22 January 2020–30 May 2020). A subset of samples was screened for the presence of host DNA and RNA using qPCR assays for CCR5 and 18S, respectively.

Assays targeting the viral RNA-dependent RNA polymerase (RdRp) had higher Ct values than assays targeting the viral N and E genes. Weak positives were not associated with the age or sex of individuals’ samples nor with reduced levels of host DNA and RNA. We observed a relationship between Ct value and time post-SARS-CoV-2 diagnosis.

High Ct value or weak positive SARS-CoV-2 was not associated with any particular bias including poor biological sampling.

Effect of cannabidiol on apoptosis and cellular interferon and interferon-stimulated gene responses to the SARS-CoV-2 genes ORF8, ORF10 and M protein

AIMS

To study effects on cellular innate immune responses to ORF8, ORF10, and Membrane protein (M protein) from the Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes COVID-19, in combination with cannabidiol (CBD).

MAIN METHODS

HEK293 cells transfected with plasmids expressing control vector, ORF8, ORF10, or M protein were assayed for cell number and markers of apoptosis at 24 h, and interferon and interferon-stimulated gene expression at 14 h, with or without CBD. Cells transfected with polyinosinic:polycytidylic acid (Poly (I:C)) were also studied as a general model of RNA-type viral infection.

KEY FINDINGS

Reduced cell number and increased early and late apoptosis were found when expression of viral genes was combined with 1-2 μM CBD treatment, but not in control-transfected cells treated with CBD, or in cells expressing viral genes but treated only with vehicle. In cells expressing viral genes, CBD augmented expression of IFNγ, IFNλ1 and IFNλ2/3, as well as the 2'-5'-oligoadenylate synthetase (OAS) family members OAS1, OAS2, OAS3, and OASL. CBD also augmented expression of these genes in control cells not expressing viral genes, but without enhancing apoptosis. CBD similarly enhanced the cellular anti-viral response to Poly (I:C).

SIGNIFICANCE

Our results demonstrate a poor ability of HEK293 cells to respond to SARS-CoV-2 genes alone, but an augmented innate anti-viral response to these genes in the presence of CBD. Thus, CBD may prime components of the innate immune system, increasing readiness to respond to RNA-type viral infection without activating apoptosis, and could be studied for potential in prophylaxis.

Long-Read RNA Sequencing Identifies Polyadenylation Elongation and Differential Transcript Usage of Host Transcripts During SARS-CoV-2 In Vitro Infection

Better methods to interrogate host-pathogen interactions during Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infections are imperative to help understand and prevent this disease. Here we implemented RNA-sequencing (RNA-seq) using Oxford Nanopore Technologies (ONT) long-reads to measure differential host gene expression, transcript polyadenylation and isoform usage within various epithelial cell lines permissive and non-permissive for SARS-CoV-2 infection. SARS-CoV-2-infected and mock-infected Vero (African green monkey kidney epithelial cells), Calu-3 (human lung adenocarcinoma epithelial cells), Caco-2 (human colorectal adenocarcinoma epithelial cells) and A549 (human lung carcinoma epithelial cells) were analyzed over time (0, 2, 24, 48 hours). Differential polyadenylation was found to occur in both infected Calu-3 and Vero cells during a late time point (48 hpi), with Gene Ontology (GO) terms such as viral transcription and translation shown to be significantly enriched in Calu-3 data. Poly(A) tails showed increased lengths in the majority of the differentially polyadenylated transcripts in Calu-3 and Vero cell lines (up to ~101 nt in mean poly(A) length, padj = 0.029). Of these genes, ribosomal protein genes such as RPS4X and RPS6 also showed downregulation in expression levels, suggesting the importance of ribosomal protein genes during infection. Furthermore, differential transcript usage was identified in Caco-2, Calu-3 and Vero cells, including transcripts of genes such as GSDMB and KPNA2, which have previously been implicated in SARS-CoV-2 infections. Overall, these results highlight the potential role of differential polyadenylation and transcript usage in host immune response or viral manipulation of host mechanisms during infection, and therefore, showcase the value of long-read sequencing in identifying less-explored host responses to disease.

Genome-wide CRISPR screens identify GATA6 as a proviral host factor for SARS-CoV-2 via modulation of ACE2

The global spread of SARS-CoV-2 led to major economic and health challenges worldwide. Revealing host genes essential for infection by multiple variants of SARS-CoV-2 can provide insights into the virus pathogenesis, and facilitate the development of novel therapeutics. Here, employing a genome-scale CRISPR screen, we provide a comprehensive data-set of cellular factors that are exploited by wild type SARS-CoV-2 as well as two additional recently emerged variants of concerns (VOCs), Alpha and Beta. We identified several host factors critical for SARS-CoV-2 infection, including various components belonging to the Clathrin-dependent transport pathway, ubiquitination, Heparan sulfate biogenesis and host phosphatidylglycerol biosynthesis. Comparative analysis of the different VOCs revealed the host factors KREMEN2 and SETDB1 as potential unique candidates required only to the Alpha variant. Furthermore, the analysis identified GATA6, a zinc finger transcription factor, as an essential proviral gene for all variants inspected. We show that GATA6 directly regulates ACE2 transcription and accordingly, is critical for SARS-CoV-2 cell entry. Analysis of clinical samples collected from SARS-CoV-2 infected individuals shows elevated levels of GATA6, suggesting a role in COVID-19 pathogenesis. Finally, pharmacological inhibition of GATA6 resulted in down-modulation of ACE2 and inhibition of viral infectivity. Overall, we show GATA6 may represent a target for the development of anti-SARS-CoV-2 therapeutic strategies and reaffirm the value of the CRISPR loss-of-function screens in providing a list of potential new targets for therapeutic interventions.

A BioID-Derived Proximity Interactome for SARS-CoV-2 Proteins

The novel coronavirus SARS-CoV-2 is responsible for the ongoing COVID-19 pandemic and has caused a major health and economic burden worldwide. Understanding how SARS-CoV-2 viral proteins behave in host cells can reveal underlying mechanisms of pathogenesis and assist in development of antiviral therapies. Here, the cellular impact of expressing SARS-CoV-2 viral proteins was studied by global proteomic analysis, and proximity biotinylation (BioID) was used to map the SARS-CoV-2 virus–host interactome in human lung cancer-derived cells. Functional enrichment analyses revealed previously reported and unreported cellular pathways that are associated with SARS-CoV-2 proteins. We have established a website to host the proteomic data to allow for public access and continued analysis of host–viral protein associations and whole-cell proteomes of cells expressing the viral–BioID fusion proteins. Furthermore, we identified 66 high-confidence interactions by comparing this study with previous reports, providing a strong foundation for future follow-up studies. Finally, we cross-referenced candidate interactors with the CLUE drug library to identify potential therapeutics for drug-repurposing efforts. Collectively, these studies provide a valuable resource to uncover novel SARS-CoV-2 biology and inform development of antivirals.

Transcriptional landscape of circulating platelets from patients with COVID-19 reveals key subnetworks and regulators underlying SARS-CoV-2 infection: implications for immunothrombosis

Background

Thrombosis and coagulopathy are pervasive pathological features of coronavirus disease 2019 (COVID-19), and thrombotic complications are a sign of severe COVID-19 disease and are associated with multiple organ failure and increased mortality. Platelets are essential cells that regulate hemostasis, thrombus formation and inflammation; however, the mechanism underlying the interaction between platelets and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains unclear.

Results

The present study performed RNA sequencing on the RNA isolated from platelets obtained from 10 COVID-19 patients and eight healthy donors, and discovered that SARS-CoV-2 not only significantly altered the coding and non-coding transcriptional landscape, but also altered the function of the platelets, promoted thrombus formation and affected energy metabolism of platelets. Integrative network biology analysis identified four key subnetworks and 16 risk regulators underlying SARS-CoV-2 infection, involved in coronavirus disease-COVID-19, platelet activation and immune response pathways. Furthermore, four risk genes (upstream binding transcription factor, RNA polymerase II, I and III subunit L, Y-box binding protein 1 and yippee like 2) were found to be associated with COVID-19 severity. Finally, a significant alteration in the von Willebrand factor/glycoprotein Ib-IX-V axis was revealed to be strongly associated with platelet aggregation and immunothrombosis.

Conclusions

The transcriptional landscape and the identification of critical subnetworks and risk genes of platelets provided novel insights into the molecular mechanisms of immunothrombosis in COVID-19 progression, which may pave the way for the development of novel therapeutic strategies for preventing COVID-19-associated thrombosis and improving the clinical outcome of COVID-19 patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13578-022-00750-5.

Thrombocytopenia in COVID‑19 and vaccine‑induced thrombotic thrombocytopenia

The highly heterogeneous symptomatology and unpredictable progress of COVID-19 triggered unprecedented intensive biomedical research and a number of clinical research projects. Although the pathophysiology of the disease is being progressively clarified, its complexity remains vast. Moreover, some extremely infrequent cases of thrombotic thrombocytopenia following vaccination against SARS-CoV-2 infection have been observed. The present study aimed to map the signaling pathways of thrombocytopenia implicated in COVID-19, as well as in vaccine-induced thrombotic thrombocytopenia (VITT). The biomedical literature database, MEDLINE/PubMed, was thoroughly searched using artificial intelligence techniques for the semantic relations among the top 50 similar words (>0.9) implicated in COVID-19-mediated human infection or VITT. Additionally, STRING, a database of primary and predicted associations among genes and proteins (collected from diverse resources, such as documented pathway knowledge, high-throughput experimental studies, cross-species extrapolated information, automated text mining results, computationally predicted interactions, etc.), was employed, with the confidence threshold set at 0.7. In addition, two interactomes were constructed: i) A network including 119 and 56 nodes relevant to COVID-19 and thrombocytopenia, respectively; and ii) a second network containing 60 nodes relevant to VITT. Although thrombocytopenia is a dominant morbidity in both entities, three nodes were observed that corresponded to genes (AURKA, CD46 and CD19) expressed only in VITT, whilst ADAM10, CDC20, SHC1 and STXBP2 are silenced in VITT, but are commonly expressed in both COVID-19 and thrombocytopenia. The calculated average node degree was immense (11.9 in COVID-19 and 6.43 in VITT), illustrating the complexity of COVID-19 and VITT pathologies and confirming the importance of cytokines, as well as of pathways activated following hypoxic events. In addition, PYCARD, NLP3 and P2RX7 are key potential therapeutic targets for all three morbid entities, meriting further research. This interactome was based on wild-type genes, revealing the predisposition of the body to hypoxia-induced thrombosis, leading to the acute COVID-19 phenotype, the 'long-COVID syndrome', and/or VITT. Thus, common nodes appear to be key players in illness prevention, progression and treatment.

Differential Co-Expression Network Analysis Reveals Key Hub-High Traffic Genes as Potential Therapeutic Targets for COVID-19 Pandemic

Background

The recent emergence of COVID-19, rapid worldwide spread, and incomplete knowledge of molecular mechanisms underlying SARS-CoV-2 infection have limited development of therapeutic strategies. Our objective was to systematically investigate molecular regulatory mechanisms of COVID-19, using a combination of high throughput RNA-sequencing-based transcriptomics and systems biology approaches.

Methods

RNA-Seq data from peripheral blood mononuclear cells (PBMCs) of healthy persons, mild and severe 17 COVID-19 patients were analyzed to generate a gene expression matrix. Weighted gene co-expression network analysis (WGCNA) was used to identify co-expression modules in healthy samples as a reference set. For differential co-expression network analysis, module preservation and module-trait relationships approaches were used to identify key modules. Then, protein-protein interaction (PPI) networks, based on co-expressed hub genes, were constructed to identify hub genes/TFs with the highest information transfer (hub-high traffic genes) within candidate modules.

Results

Based on differential co-expression network analysis, connectivity patterns and network density, 72% (15 of 21) of modules identified in healthy samples were altered by SARS-CoV-2 infection. Therefore, SARS-CoV-2 caused systemic perturbations in host biological gene networks. In functional enrichment analysis, among 15 non-preserved modules and two significant highly-correlated modules (identified by MTRs), 9 modules were directly related to the host immune response and COVID-19 immunopathogenesis. Intriguingly, systemic investigation of SARS-CoV-2 infection identified signaling pathways and key genes/proteins associated with COVID-19's main hallmarks, e.g., cytokine storm, respiratory distress syndrome (ARDS), acute lung injury (ALI), lymphopenia, coagulation disorders, thrombosis, and pregnancy complications, as well as comorbidities associated with COVID-19, e.g., asthma, diabetic complications, cardiovascular diseases (CVDs), liver disorders and acute kidney injury (AKI). Topological analysis with betweenness centrality (BC) identified 290 hub-high traffic genes, central in both co-expression and PPI networks. We also identified several transcriptional regulatory factors, including NFKB1, HIF1A, AHR, and TP53, with important immunoregulatory roles in SARS-CoV-2 infection. Moreover, several hub-high traffic genes, including IL6, IL1B, IL10, TNF, SOCS1, SOCS3, ICAM1, PTEN, RHOA, GDI2, SUMO1, CASP1, IRAK3, HSPA5, ADRB2, PRF1, GZMB, OASL, CCL5, HSP90AA1, HSPD1, IFNG, MAPK1, RAB5A, and TNFRSF1A had the highest rates of information transfer in 9 candidate modules and central roles in COVID-19 immunopathogenesis.

Conclusion

This study provides comprehensive information on molecular mechanisms of SARS-CoV-2-host interactions and identifies several hub-high traffic genes as promising therapeutic targets for the COVID-19 pandemic.

Exploring COVID-19 pathogenesis on command-line: A bioinformatics pipeline for handling and integrating omics data

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first identified in late 2019 in Wuhan, China, and has proven to be highly pathogenic, making it a global public health threat. The immediate need to understand the mechanisms and impact of the virus made omics techniques stand out, as they can offer a holistic and comprehensive view of thousands of molecules in a single experiment. Mastering bioinformatics tools to process, analyze, integrate, and interpret omics data is a powerful knowledge to enrich results. We present a robust and open access computational pipeline for extracting information from quantitative proteomics and transcriptomics public data. We present the entire pipeline from raw data to differentially expressed genes. We explore processes and pathways related to mapped transcripts and proteins. A pipeline is presented to integrate and compare proteomics and transcriptomics data using also packages available in the Bioconductor and providing the codes used. Cholesterol metabolism, immune system activity, ECM, and proteasomal degradation pathways increased in infected patients. Leukocyte activation profile was overrepresented in both proteomics and transcriptomics data. Finally, we found a panel of proteins and transcripts regulated in the same direction in the lung transcriptome and plasma proteome that distinguish healthy and infected individuals. This panel of markers was confirmed in another cohort of patients, thus validating the robustness and functionality of the tools presented.

Bioinformatics and in-silico findings reveal medical features and pharmacological targets of biochanin A against colorectal cancer and COVID-19

Severe mortality due to the COVID-19 pandemic resulted from the lack of effective treatment. Although COVID-19 vaccines are available, their side effects have become a challenge for clinical use in patients with chronic diseases, especially cancer patients. In the current report, we applied network pharmacology and systematic bioinformatics to explore the use of biochanin A in patients with colorectal cancer (CRC) and COVID-19 infection. Using the network pharmacology approach, we identified two clusters of genes involved in immune response (IL1A, IL2, and IL6R) and cell proliferation (CCND1, PPARG, and EGFR) mediated by biochanin A in CRC/COVID-19 condition. The functional analysis of these two gene clusters further illustrated the effects of biochanin A on interleukin-6 production and cytokine-cytokine receptor interaction in CRC/COVID-19 pathology. In addition, pathway analysis demonstrated the control of PI3K-Akt and JAK-STAT signaling pathways by biochanin A in the treatment of CRC/COVID-19. The findings of this study provide a therapeutic option for combination therapy against COVID-19 infection in CRC patients.

Genome-wide expression of the residual lung reacting to experimental Pneumonectomy

Background

Acute or chronic irreversible respiratory failure may occur in patients undergoing pneumonectomy. Aim of this study was to determine transcriptome expression changes after experimental pneumonectomy in swine model. Experimental left pneumonectomy was performed in five pigs under general anaesthesia. Both the resected and the remaining lung, after 60 post-operative completely uneventful days, underwent genome-wide bulk RNA-Sequencing (RNA-Seq).

Results

Histological analysis showed dilation of air spaces and rupture of interalveolar septa. In addition, mild inflammation, no fibrosis, radial stretch of the bronchus, strong enlargement of airspaces and thinning of the blood supply were observed. Bioinformatic analyses of bulk RNA-Seq data identified 553 Differentially Expressed Genes (DEGs) at adjusted P-value below 0.001, between pre- and post-pneumonectomy. The top 10 up-regulated DEGs were Edn1, Areg, Havcr2, Gadd45g, Depp1, Cldn4, Atf3, Myc, Gadd45b, Socs3; the top 10 down-regulated DEGs were Obscn, Cdkn2b, ENSSSCG00000015738, Prrt2, Amer1, Flrt3, Efnb2, Tox3, Znf793, Znf365. Leveraging digital cytometry tools, no difference in cellular abundance was found between the two experimental groups, while the analysis of cell type-specific gene expression patterns highlighted a striking predominance of macrophage-specific genes among the DEGs. DAVID-based gene ontology analysis showed a significant enrichment of “Extrinsic apoptotic signaling pathway” (FDR q = 7.60 × 10^− 3) and “Response to insulin” (FDR q = 7.60 × 10^− 3) genes, along with an enrichment of genes involved as “Negative regulators of DDX58/IFIH1 signaling” (FDR q = 7.50 × 10^− 4) found by querying the REACTOME pathway database. Gene network analyses indicated a general dysregulation of gene inter-connections.

Conclusion

This translational genomics study highlighted the existence both of individual genes, mostly dysregulated in certain cellular populations (e.g., macrophages), and gene-networks involved in pulmonary reaction after left pneumonectomy. Their involvement in lung homeostasis is largely supported by previous studies, carried out both in humans and in other animal models (under homeostatic or disease-related conditions), that adopted candidate-gene approaches. Overall, the present findings represent a preliminary assessment for future, more focused, studies on compensatory lung adaptation, pulmonary regeneration and functional reload.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08171-3.

Multiomics integration-based molecular characterizations of COVID-19

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), rapidly became a global health challenge, leading to unprecedented social and economic consequences. The mechanisms behind the pathogenesis of SARS-CoV-2 are both unique and complex. Omics-scale studies are emerging rapidly and offer a tremendous potential to unravel the puzzle of SARS-CoV-2 pathobiology, as well as moving forward with diagnostics, potential drug targets, risk stratification, therapeutic responses, vaccine development and therapeutic innovation. This review summarizes various aspects of understanding multiomics integration-based molecular characterizations of COVID-19, which to date include the integration of transcriptomics, proteomics, genomics, lipidomics, immunomics and metabolomics to explore virus targets and developing suitable therapeutic solutions through systems biology tools. Furthermore, this review also covers an abridgment of omics investigations related to disease pathogenesis and virulence, the role of host genetic variation and a broad array of immune and inflammatory phenotypes contributing to understanding COVID-19 traits. Insights into this review, which combines existing strategies and multiomics integration profiling, may help further advance our knowledge of COVID-19.

Tetraspanins: Host Factors in Viral Infections

Tetraspanins are transmembrane glycoproteins that have been shown increasing interest as host factors in infectious diseases. In particular, they were implicated in the pathogenesis of both non-enveloped (human papillomavirus (HPV)) and enveloped (human immunodeficiency virus (HIV), Zika, influenza A virus, (IAV), and coronavirus) viruses through multiple stages of infection, from the initial cell membrane attachment to the syncytium formation and viral particle release. However, the mechanisms by which different tetraspanins mediate their effects vary. This review aimed to compare and contrast the role of tetraspanins in the life cycles of HPV, HIV, Zika, IAV, and coronavirus viruses, which cause the most significant health and economic burdens to society. In doing so, a better understanding of the relative contribution of tetraspanins in virus infection will allow for a more targeted approach in the treatment of these diseases.

Host transcriptional signatures as predictive markers of infection in children

PURPOSE OF REVIEW

Analyses of the host transcriptional response to infection has proved to be an alternative diagnostic strategy to standard direct pathogen detection. This review summarizes the value of applying blood and mucosal transcriptome analyses for the diagnosis and management of children with viral and bacterial infections.

RECENT FINDINGS

Over the years, studies have validated the concept that RNA transcriptional profiles derived from children with infectious diseases carry a pathogen-specific biosignature that can be qualitatively and quantitively measured. These biosignatures can be translated into a biologically meaningful context to improve patient diagnosis, as seen in children with tuberculosis, rhinovirus infections, febrile infants and children with pneumonia; understand disease pathogenesis (i.e. congenital CMV) and objectively classify patients according to clinical severity (i.e. respiratory syncytial virus).

SUMMARY

The global assessment of host RNA transcriptional immune responses has improved our understanding of the host-pathogen interactions in the clinical setting. It has shown the potential to be used in clinical situations wherein our current diagnostic tools are inadequate, guiding the diagnosis and classification of children with infectious diseases.

A BioID-derived proximity interactome for SARS-CoV-2 proteins

The novel coronavirus SARS-CoV-2 is responsible for the ongoing COVID-19 pandemic and has caused a major health and economic burden worldwide. Understanding how SARS-CoV-2 viral proteins behave in host cells can reveal underlying mechanisms of pathogenesis and assist in development of antiviral therapies. Here we use BioID to map the SARS-CoV-2 virus-host interactome using human lung cancer derived A549 cells expressing individual SARS-CoV-2 viral proteins. Functional enrichment analyses revealed previously reported and unreported cellular pathways that are in association with SARS-CoV-2 proteins. We have also established a website to host the proteomic data to allow for public access and continued analysis of host-viral protein associations and whole-cell proteomes of cells expressing the viral-BioID fusion proteins. Collectively, these studies provide a valuable resource to potentially uncover novel SARS-CoV-2 biology and inform development of antivirals.

Acute SARS-CoV-2 infection is associated with an increased abundance of bacterial pathogens, including Pseudomonas aeruginosa in the nose

Research conducted on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pathogenesis and coronavirus disease 2019 (COVID-19) generally focuses on the systemic host response, especially that generated by severely ill patients, with few studies investigating the impact of acute SARS-CoV-2 at the site of infection. We show that the nasal microbiome of SARS-CoV-2-positive patients (CoV⁺, n = 68) at the time of diagnosis is unique when compared to CoV⁻ healthcare workers (n = 45) and CoV⁻ outpatients (n = 21). This shift is marked by an increased abundance of bacterial pathogens, including Pseudomonas aeruginosa, which is also positively associated with viral RNA load. Additionally, we observe a robust host transcriptional response in the nasal epithelia of CoV⁺ patients, indicative of an antiviral innate immune response and neuronal damage. These data suggest that the inflammatory response caused by SARS-CoV-2 infection is associated with an increased abundance of bacterial pathogens in the nasal cavity that could contribute to increased incidence of secondary bacterial infections.

Updated pharmacological effects of Lonicerae japonicae flos, with a focus on its potential efficacy on coronavirus disease-2019 (COVID-19)

Lonicerae japonicae flos (LJF), known as Jin Yin Hua in Chinese, is one of the most commonly used traditional Chinese herbs and nutraceuticals. Nowadays, LJF is broadly applied in an array of afflictions, such as fever, sore throat, flu infection, cough, and arthritis, with the action mechanism to be elucidated. Here, we strove to summarize the main phytochemical components of LJF and review its updated pharmacological effects, including inhibition of inflammation, pyrexia, viruses, and bacteria, immunoregulation, and protection of the liver, nervous system, and heart, with a focus on the potential efficacy of LJF on coronavirus disease–2019 based on network pharmacology so as to fully underpin the utilization of LJF as a medicinal herb and a favorable nutraceutical in daily life.

Clinical characterization and therapeutic targets of vitamin A in patients with hepatocholangiocarcinoma and coronavirus disease

Recent reports indicate that patients with hepatocholangiocarcinoma (CHOL) have a higher morbidity and mortality rate for coronavirus disease (COVID-19). Anti-CHOL/COVID-19 medicines are inexistent. Vitamin A (VA) refers to a potent nutrient with anti-cytotoxic and anti-inflammatory actions. Therefore, this study aimed to determine the potential functions and molecular mechanisms of VA as a potential treatment for patients with both CHOL and COVID-19 (CHOL/COVID-19). The transcriptome data of CHOL patients were obtained from the Cancer Genome Analysis database. Furthermore, the network pharmacology approach and bioinformatics analysis were used to identify and reveal the molecular functions, therapeutic biotargets, and signaling of VA against CHOL/COVID-19. First, clinical findings identified the medical characteristics of CHOL patients with COVID-19, such as susceptibility gene, prognosis, recurrence, and survival rate. Anti-viral and anti-inflammatory pathways, and immunopotentiation were found as potential targets of VA against CHOL/COVID-19. These findings illustrated that VA may contribute to the clinical management of CHOL/COVID-19 achieved by induction of cell repair, suppression of oxidative stress and inflammatory reaction, and amelioration of immunity. Nine vital therapeutic targets (BRD2, NOS2, GPT, MAPK1, CXCR3, ICAM1, CDK4, CAT, and TMPRSS13) of VA against CHOL/COVID-19 were identified. For the first time, the potential pharmacological biotargets, function, and mechanism of action of VA in CHOL/COVID-19 were elucidated.

Acute SARS-CoV-2 infection is associated with an expansion of bacteria pathogens in the nose including Pseudomonas Aeruginosa

Much of the research conducted on SARS-CoV-2 and COVID-19 has focused on the systemic host response, especially that generated by severely ill patients. Very few studies have investigated the impact of acute SARS-CoV-2 within the nasopharynx, the site of initial infection and viral replication. In this study we profiled changes in the nasal microbial communities as well as in host transcriptional profile during acute SARS-CoV-2 infection using 16S amplicon sequencing and RNA sequencing. These analyses were coupled to viral genome sequencing. Our microbiome analysis revealed that the nasal microbiome of COVID patients was unique and was marked by an expansion of bacterial pathogens. Some of these microbes (i.e. Acinetobacter ) were shared with COVID negative health care providers from the same medical center but absent in COVID negative outpatients seeking care at the same institutions suggesting acquisition of nosocomial respiratory pathogens. Specifically, we report a distinct increase in the prevalence and abundance of the pathogen Pseudomonas aeruginosa in COVID patients that correlated with viral RNA load. These data suggest that the inflammatory environment caused by SARS-CoV-2 infection and potentially exposure to the hospital environment leads to an expansion of bacterial pathogens in the nasal cavity that could contribute to increased incidence of secondary bacterial infections. Additionally, we observed a robust host transcriptional response in the nasal epithelia of COVID patients, indicative of an antiviral innate immune repones and neuronal damage. Finally, analysis of viral genomes did not reveal an association between viral loads and viral sequences.

Coronavirus Disease 19 and Future Ecological Crises: Hopes from Epigenomics and Unraveling Genome Regulation in Humans and Infectious Agents

With coronavirus disease 19 (COVID-19), we have witnessed a shift from public health to planetary health and a growing recognition of the importance of systems science in developing effective solutions against pandemics in the 21st century. COVID-19 and the history of frequent infectious outbreaks in the last two decades suggest that COVID-19 is likely a dry run for future ecological crises. Now is the right time to plan ahead and deploy the armamentarium of systems science scholarship for planetary health. The science of epigenomics, which investigates both genetic and nongenetic traits regarding heritable phenotypic alterations, and new approaches to understanding genome regulation in humans and pathogens offer veritable prospects to boost the global scientific capacities to innovate therapeutics and diagnostics against novel and existing infectious agents. Several reversible epigenetic alterations, such as chromatin remodeling and histone methylation, control and influence gene expression. COVID-19 lethality is linked, in part, to the cytokine storm, age, and status of the immune system in a given person. Additionally, due to reduced human mobility and daily activities, effects of the pandemic on the environment have been both positive and negative. For example, reduction in environmental pollution and lesser extraction from nature have potential positive corollaries on water and air quality. Negative effects include pollution as plastics and other materials were disposed in unconventional places and spaces in the course of the pandemic. I discuss the opportunities and challenges associated with the science of epigenomics, specifically with an eye to inform and prevent future ecological crises and pandemics that are looming on the horizon in the 21st century. In particular, this article underscores that epigenetics of both viruses and the host may influence virus infectivity and severity of attendant disease.