Exploring effects of DNA methylation and gene expression on pan-cancer drug response by mathematical models

Since genetic alteration only accounts for 20%–30% in the drug effect-related factors, the role of epigenetic regulation mechanisms in drug response is gradually being valued. However, how epigenetic changes and abnormal gene expression affect the chemotherapy response remains unclear. Therefore, we constructed a variety of mathematical models based on the integrated DNA methylation, gene expression, and anticancer drug response data of cancer cell lines from pan-cancer levels to identify genes whose DNA methylation is associated with drug response and then to assess the impact of epigenetic regulation of gene expression on the sensitivity of anticancer drugs. The innovation of the mathematical models lies in: Linear regression model is followed by logistic regression model, which greatly shortens the calculation time and ensures the reliability of results by considering the covariates. Second, reconstruction of prediction models based on multiple dataset partition methods not only evaluates the model stability but also optimizes the drug-gene pairs. For 368,520 drug-gene pairs with P < 0.05 in linear models, 999 candidate pairs with both AUC ≥ 0.8 and P < 0.05 were obtained by logistic regression models between drug response and DNA methylation. Then 931 drug-gene pairs with 45 drugs and 491 genes were optimized by model stability assessment. Integrating both DNA methylation and gene expression markedly increased predictive power for 732 drug-gene pairs where 598 drug-gene pairs including 44 drugs and 359 genes were prioritized. Several drug target genes were enriched in the modules of the drug-gene-weighted interaction network. Besides, for cancer driver genes such as EGFR, MET, and TET2, synergistic effects of DNA methylation and gene expression can predict certain anticancer drugs’ responses. In summary, we identified potential drug sensitivity-related markers from pan-cancer levels and concluded that synergistic regulation of DNA methylation and gene expression affect anticancer drug response.     

Differential expression analysis in ovarian cancer: A functional genomics and systems biology approach

BackgroundOvarian cancer is one of the rarest lethal oncologic diseases that have hardly any specific biomarkers. The availability of high-throughput genomic data and advancement in bioinformatics tools allow us to predict gene biomarkers and apply systems biology approaches to get better diagnosis, and prognosis of the disease with a tentative drug that may be repurposed.ObjectiveTo perform genome-wide association studies using microarray gene expression of ovarian cancer and identify gene biomarkers, construction and analyze networks, perform survival analysis, and drug interaction studies for better diagnosis, prognosis, and treatment of ovarian cancer.MethodThe gene expression profiles of both healthy and serous ovarian cancer epithelial samples were considered. We applied a series of bioinformatics methods and tools, including fold-change statistics for differential expression analysis, DisGeNET and NCBI-Gene databases for gene-disease association mapping, DAVID 6.8 for GO enrichment analysis, GeneMANIA for network construction, Cytoscape 3.8 with its plugins for network visualization, analysis, and module detection, the UALCAN for patient survival analysis, and PubChem, DrugBank and DGIdb for gene-drug interaction.ResultsWe identified 8 seed genes that were subjected for drug-gene interaction studies. Because of over-expression in all the four stages of ovarian cancer, we discern that genes HMGA1 and PSAT1 are potential therapeutic biomarkers for its diagnosis at an early stage (stage I). Our analysis suggests that there are 11 drugs common in the seed genes. However, hypermethylated seed genes HMGA1 and PSAT1 showcased a good interaction affinity with drugs cisplatin, cyclosporin, bisphenol A, progesterone, and sunitinib, and are crucial in the proliferation of ovarian cancer.ConclusionOur study reveals that HMGA1 and PSAT1 can be deployed for initial screening of ovarian cancer and drugs cisplatin, bisphenol A, cyclosporin, progesterone, and sunitinib are effective in curbing the epigenetic alteration.     

Network-assisted investigation of antipsychotic drugs and their targets

Antipsychotic drugs are tranquilizing psychiatric medications primarily used in the treatment of schizophrenia and similar severe mental disorders. So far, most of these drugs have been discovered without knowing much on the molecular mechanisms of their actions. The available large amount of pharmacogenetics, pharmacometabolomics, and pharmacoproteomics data for many drugs makes it possible to systematically explore the molecular mechanisms underlying drug actions. In this study, we applied a unique network-based approach to investigate antipsychotic drugs and their targets. We first retrieved 43 antipsychotic drugs, 42 unique target genes, and 46 adverse drug interactions from the DrugBank database and then generated a drug-gene network and a drug-drug interaction network. Through drug-gene network analysis, we found that seven atypical antipsychotic drugs tended to form two clusters that could be defined by drugs with different target receptor profiles. In the drug-drug interaction network, we found that three drugs (zuclopenthixol, ziprasidone, and thiothixene) tended to have more adverse drug interactions than others, while clozapine had fewer adverse drug interactions. This investigation indicated that these antipsychotics might have different molecular mechanisms underlying the drug actions. This pilot network-assisted investigation of antipsychotics demonstrates that network-based analysis is useful for uncovering the molecular actions of antipsychotics.     

In silico drug repositioning against human NRP1 to block SARS-CoV-2 host entry

Despite COVID-19 turned into a pandemic, no approved drug for the treatment or globally available vaccine is out yet. In such a global emergency, drug repurposing approach that bypasses a costly and long-time demanding drug discovery process is an effective way in search of finding drugs for the COVID-19 treatment. Recent studies showed that SARS-CoV-2 uses neuropilin-1 (NRP1) for host entry. Here we took advantage of structural information of the NRP1 in complex with C-terminal of spike (S) protein of SARS-CoV-2 to identify drugs that may inhibit NRP1 and S protein interaction. U.S. Food and Drug Administration (FDA) approved drugs were screened using docking simulations. Among top drugs, well-tolerated drugs were selected for further analysis. Molecular dynamics (MD) simulations of drugs-NRP1 complexes were run for 100 ns to assess the persistency of binding. MM/GBSA calculations from MD simulations showed that eltrombopag, glimepiride, sitagliptin, dutasteride, and ergotamine stably and strongly bind to NRP1. In silico Alanine scanning analysis revealed that Tyr²⁹⁷, Trp³⁰¹, and Tyr³⁵³ amino acids of NRP1 are critical for drug binding. Validating the effect of drugs analyzed in this paper by experimental studies and clinical trials will expedite the drug discovery process for COVID-19.     

Exploring the multi-drug resistance in Escherichia coli O157:H7 by gene interaction network: A systems biology approach

In the present study, we have constructed an interaction network of 29 antibiotic resistant genes along with 777 interactions in E. coli O157:H7. Gene ontology analysis reveals that 94, 89 and 67 genes have roles in the cellular process, biological process and molecular function respectively. Gene complexes related to tripartite efflux pumps mdtEF-tolC and ABC family efflux pump macAB-tolC play key roles in multidrug efflux systems. It is noteworthy to mention that, 19 genes are involved in multi-efflux pumps and they play a significant role in multidrug resistance (MDR); while 18 genes are vital for fatty acid synthesis. Interestingly, we found that the four genes arnABCD are involved in both MDR and in fatty acid synthesis. Hence these genes could be targeted for new drug discovery. On the whole, our results provide a detailed understanding of the mode of MDR mechanisms in E.coli O157:H7.     

SAveRUNNER: A network-based algorithm for drug repurposing and its application to COVID-19

The novelty of new human coronavirus COVID-19/SARS-CoV-2 and the lack of effective drugs and vaccines gave rise to a wide variety of strategies employed to fight this worldwide pandemic. Many of these strategies rely on the repositioning of existing drugs that could shorten the time and reduce the cost compared to de novo drug discovery. In this study, we presented a new network-based algorithm for drug repositioning, called SAveRUNNER (Searching off-lAbel dRUg aNd NEtwoRk), which predicts drug–disease associations by quantifying the interplay between the drug targets and the disease-specific proteins in the human interactome via a novel network-based similarity measure that prioritizes associations between drugs and diseases locating in the same network neighborhoods. Specifically, we applied SAveRUNNER on a panel of 14 selected diseases with a consolidated knowledge about their disease-causing genes and that have been found to be related to COVID-19 for genetic similarity (i.e., SARS), comorbidity (e.g., cardiovascular diseases), or for their association to drugs tentatively repurposed to treat COVID-19 (e.g., malaria, HIV, rheumatoid arthritis). Focusing specifically on SARS subnetwork, we identified 282 repurposable drugs, including some the most rumored off-label drugs for COVID-19 treatments (e.g., chloroquine, hydroxychloroquine, tocilizumab, heparin), as well as a new combination therapy of 5 drugs (hydroxychloroquine, chloroquine, lopinavir, ritonavir, remdesivir), actually used in clinical practice. Furthermore, to maximize the efficiency of putative downstream validation experiments, we prioritized 24 potential anti-SARS-CoV repurposable drugs based on their network-based similarity values. These top-ranked drugs include ACE-inhibitors, monoclonal antibodies (e.g., anti-IFNγ, anti-TNFα, anti-IL12, anti-IL1β, anti-IL6), and thrombin inhibitors. Finally, our findings were in-silico validated by performing a gene set enrichment analysis, which confirmed that most of the network-predicted repurposable drugs may have a potential treatment effect against human coronavirus infections.     

Identification of phytochemicals as potential therapeutic agents that binds to Nsp15 protein target of coronavirus (SARS-CoV-2) that are capable of inhibiting virus replication

BackgroundCoronavirus disease 2019 (COVID-19) playing havoc across the globe caused 585,727 deaths and 13,616,593 confirmed cases so far as per World Health Organization data released till 17th July 2020. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV- 2) is responsible for causing this pandemic across different continents. It is not only impacting the world economy but also quarantined millions of people in their homes or hospitals.PurposeAt present, there is no Food and Drug Administration-approved drug or vaccine available to treat this disease. Still, people are trying various pre-existing medicines that are known to have anti-viral or anti-parasitic effects. In view of this, the present study aimed to study the binding potential of various phytochemicals present in multiple natural plant extract as a secondary metabolite to non-structural protein 15 (Nsp15) protein, a drug target known to play a crucial role in virulence of coronavirus.MethodNsp15 protein was selected because it shows 89% similarity to the other SARS-CoV, which caused the earlier outbreak. The assumption is that inhibition of Nsp15 slowdowns the viral replication. Phytochemicals are selected as these are present in various plant parts (seed, flower, roots, etc.), which are used in different food cuisines in different geographical regions across the globe. The molecular docking approach was performed using two different software, i.e., Autodock, and Swissdock, to study the interaction of various phytochemicals with Nsp15 protein. Hydroxychloroquine is used as a positive control as it is used by medical professionals showing some positive effects in dealing with coronavirus.ResultsThe present study demonstrated the binding potential of approximately 50 phytochemicals with Nsp15 and capable of inhibiting the viral replication, although in vitro and in vivo tests are required to confirm these findings.ConclusionsIn conclusion, the present study successfully demonstrated the binding of phytochemicals such as sarsasapogenin, ursonic acid, curcumin, ajmalicine, novobiocin, silymarin and aranotin, piperine, gingerol, rosmarinic acid, and alpha terpinyl acetate to Nsp15 viral protein and they might play a key role in inhibiting SARS-CoV-2 replication.     

Potential mechanisms underlying the promoting effects of 3D collagen scaffold culture on stemness and drug resistance of glioma cells

Background3D collagen scaffold culture is a good tool to study glioma metastasis and recurrence in vitro.MethodsThe effect of 3D collagen culture on the colony formation, the sphere formation, and drug sensitivity of glioma cells was observed by soft-agar colony formation assays, sphere formation assays, and CCK-8 assays, respectively. 3D-glioma-drug genes were identified by previous results and online databases. Gene enrichment and PPI analyses were performed by R software and Metacsape. Hub 3D-glioma-drug genes were screened by STRING and Cytoscape. TCGA and CGGA databases and R software were used to analyze the distribution of hub genes in glioma and their effects on the prognosis. Western Blot was used to verify the effect of 3D collagen culture on the expression of hub genes. miRNAs targeting hub genes were predicted by ENCORI.Results3D collagen scaffold culture promoted colony formation, sphere formation, and drug resistance of glioma cells. There were 77 3D-glioma-drug genes screened, and the pathways enriched in the protein interaction network mainly included responses to stressors, DNA damage and repair, and drug metabolism. Hub 3D-glioma-drug genes were AKT1, ATM, CASP3, CCND1, EGFR, PARP1, and TP53. These genes and predicted miRNAs were expressed differentially in glioma samples and partially affected the prognosis of patients with glioma. These findings suggested these hub genes and miRNAs may play a key role in the effects generated by the 3D culture model and become new markers for glioma diagnosis and treatment.     

Corilagin prevents SARS-CoV-2 infection by targeting RBD-ACE2 binding

BackgroundThe outbreak of coronavirus (SARS-CoV-2) disease caused more than 100,000,000 people get infected and over 2,200,000 people being killed worldwide. However, the current developed vaccines or drugs may be not effective in preventing the pandemic of COVID-19 due to the mutations of coronavirus and the severe side effects of the newly developed vaccines. Chinese herbal medicines and their active components play important antiviral activities. Corilagin exhibited antiviral effect on human immunodeficiency virus (HIV), hepatitis C virus (HCV) and Epstein-Barr virus (EBV). However, whether it blocks the interaction between SARS-CoV-2 RBD and hACE2 has not been elucidated.PurposeTo characterize an active compound, corilagin derived from Phyllanthus urinaria as potential SARS-CoV-2 entry inhibitors for its possible preventive application in daily anti-virus hygienic products.MethodsComputational docking coupled with bio-layer interferometry, BLI were adopted to screen more than 1800 natural compounds for the identification of SARS-CoV-2 spike-RBD inhibitors. Corilagin was confirmed to have a strong binding affinity with SARS-CoV-2-RBD or human ACE2 (hACE2) protein by the BLI, ELISA and immunocytochemistry (ICC) assay. Furthermore, the inhibitory effect of viral infection of corilagin was assessed by in vitro pseudovirus system. Finally, the toxicity of corilagin was examined by using MTT assay and maximal tolerated dose (MTD) studies in C57BL/6 mice.ResultsCorilagin preferentially binds to a pocket that contains residues Cys 336 to Phe 374 of spike-RBD with a relatively low binding energy of -9.4 kcal/mol. BLI assay further confirmed that corilagin exhibits a relatively strong binding affinity to SARS-CoV-2-RBD and hACE2 protein. In addition, corilagin dose-dependently blocks SARS-CoV-2-RBD binding and abolishes the infectious property of RBD-pseudotyped lentivirus in hACE2 overexpressing HEK293 cells, which mimicked the entry of SARS-CoV-2 virus in human host cells. Finally, in vivo studies revealed that up to 300 mg/kg/day of corilagin was safe in C57BL/6 mice. Our findings suggest that corilagin could be a safe and potential antiviral agent against the COVID-19 acting through the blockade of the fusion of SARS-CoV-2 spike-RBD to hACE2 receptors.ConclusionCorilagin could be considered as a safe and environmental friendly anti-SARS-CoV-2 agent for its potential preventive application in daily anti-virus hygienic products.     

HMG-CoA reductase inhibitors and COVID-19 mortality in Stockholm,Sweden: A registry-based cohort study

BackgroundThe relationship between statin treatment and Coronavirus Disease 2019 (COVID-19) mortality has been discussed due to the pleiotropic effects of statins on coagulation and immune mechanisms. However, available observational studies are hampered by study design flaws, resulting in substantial heterogeneity and ambiguities. Here, we aim to determine the relationship between statin treatment and COVID-19 mortality.Methods and findingsThis cohort study included all Stockholm residents aged 45 or older (N = 963,876), followed up from 1 March 2020 until 11 November 2020. The exposure was statin treatment initiated before the COVID-19-pandemic, defined as recorded statin dispensation in the Swedish Prescribed Drug Register between 1 March 2019 and 29 February 2020. COVID-19-specific mortality was ascertained from the Swedish Cause of Death Registry. Hazard ratios (HRs) were calculated using multivariable Cox regression models. We further performed a target trial emulation restricted to initiators of statins.In the cohort (51.6% female), 169,642 individuals (17.6%) were statin users. Statin users were older (71.0 versus 58.0 years), more likely to be male (53.3% versus 46.7%), more often diagnosed with comorbidities (for example, ischemic heart disease 23.3% versus 1.6%), more frequently on anticoagulant and antihypertensive treatments, less likely to have a university-level education (34.5% versus 45.4%), and more likely to have a low disposable income (20.6% versus 25.2%), but less likely to reside in crowded housing (6.1% versus 10.3%).A total of 2,545 individuals died from COVID-19 during follow-up, including 765 (0.5%) of the statin users and 1,780 (0.2%) of the nonusers. Statin treatment was associated with a lowered COVID-19 mortality (adjusted HR, 0.88; 95% CI, 0.79 to 0.97, P = 0.01), and this association did not vary appreciably across age groups, sexes, or COVID-19 risk groups. The confounder adjusted HR for statin treatment initiators was 0.78 (95% CI, 0.59 to 1.05, P = 0.10) in the emulated target trial. Limitations of this study include the observational design, reliance on dispensation data, and the inability to study specific drug regimens.ConclusionsStatin treatment had a modest negative association with COVID-19 mortality. While this finding needs confirmation from randomized clinical trials, it supports the continued use of statin treatment for medical prevention according to current recommendations also during the COVID-19 pandemic.

In this cohort study, Rita Bergqvist and colleagues investigate the relationship between statin treatment and COVID-19 mortality.     

Resistome analysis of Mycobacterium tuberculosis: Identification of aminoglycoside 2'-Nacetyltransferase (AAC) as co-target for drug desigining

The emergence of multidrug resistant tuberculosis (MDRTB) highlights the urgent need to understand the mechanisms of resistance to the drugs and to develop a new arena of therapeutics to treat the disease. Ethambutol, isonazid, pyrazinamide, rifampicin are first line of drugs against TB, whereas aminoglycoside, polypeptides, fluoroquinolone, ethionamide are important second line of bactericidal drugs used to treat MDRTB, and resistance to one or both of these drugs are defining characteristic of extensively drug resistant TB. We retrieved 1,221 resistant genes from Antibiotic Resistance Gene Database (ARDB), which are responsible for resistance against first and second line antibiotics used in treatment of Mycobacterium tuberculosis infection. From network analysis of these resistance genes, 53 genes were found to be common. Phylogenetic analysis shows that more than 60% of these genes code for acetyltransferase. Acetyltransferases detoxify antibiotics by acetylation, this mechanism plays central role in antibiotic resistance. Seven acetyltransferase (AT-1 to AT-7) were selected from phylogenetic analysis. Structural alignment shows that these acetyltransferases share common ancestral core, which can be used as a template for structure based drug designing. From STRING analysis it is found that acetyltransferase interact with 10 different proteins and it shows that, all these interaction were specific to M. tuberculosis. These results have important implications in designing new therapeutic strategies with acetyltransferase as lead co-target to combat against MDR as well as Extreme drug resistant (XDR) tuberculosis.

Abbreviations

AA - amino acid, AT - Acetyltransferase, AAC - Aminoglycoside 2''-N-acetyltransferase, XDR - Extreme drug-resistant, MDR - Multidrug-resistant, Mtb - Mycobacterium tuberculosis, TB - Tuberculosis.     

Network pharmacology and molecular docking analyses on Lianhua Qingwen capsule indicate Akt1 is a potential target to treat and prevent COVID‐19

ObjectivesCoronavirus disease 2019 (COVID‐19) is rapidly spreading worldwide. Lianhua Qingwen capsule (LQC) has shown therapeutic effects in patients with COVID‐19. This study is aimed to discover its molecular mechanism and provide potential drug targets.Materials and MethodsAn LQC target and COVID‐19–related gene set was established using the Traditional Chinese Medicine Systems Pharmacology database and seven disease‐gene databases. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and protein‐protein interaction (PPI) network were performed to discover the potential mechanism. Molecular docking was performed to visualize the patterns of interactions between the effective molecule and targeted protein.ResultsA gene set of 65 genes was generated. We then constructed a compound‐target network that contained 234 nodes of active compounds and 916 edges of compound‐target pairs. The GO and KEGG indicated that LQC can act by regulating immune response, apoptosis and virus infection. PPI network and subnetworks identified nine hub genes. The molecular docking was conducted on the most significant gene Akt1, which is involved in lung injury, lung fibrogenesis and virus infection. Six active compounds of LQC can enter the active pocket of Akt1, namely beta‐carotene, kaempferol, luteolin, naringenin, quercetin and wogonin, thereby exerting potential therapeutic effects in COVID‐19.ConclusionsThe network pharmacological strategy integrates molecular docking to unravel the molecular mechanism of LQC. Akt1 is a promising drug target to reduce tissue damage and help eliminate virus infection.     

Therapeutic options of TCM for organ injuries associated with COVID-19 and the underlying mechanism

BackgroundCoronavirus disease-2019 (COVID-19) caused by infection with severe acute respiratory coronavirus-2 (SARS-CoV-2) has been spreading rapidly throughout China and in other countries since the end of 2019. The World Health Organization (WHO) has declared that the epidemic is a public health emergency of international concerns. The timely and appropriate measures for treating COVID-19 in China, which are inseparable from the contribution of traditional Chinese medicine (TCM), have won much praise of the world.PurposeThis review aimed to summarize and discuss the essential role of TCM in protecting tissues from injuries associated with COVID-19, and accordingly to clarify the possible action mechanisms of TCM from the perspectives of anti-inflammatory, antioxidant and anti-apoptotic effects.MethodsElectronic databases such as Pubmed, ResearchGate, Science Direct, Web of Science, medRixv and Wiley were used to search scientific literatures.ResultsThe present review found that traditional Chinese herbs commonly used for the clinical treatment of organ damages caused by COVID-19, such as Scutellaria baicalensis, Salvia miltiorrhizaSalvia miltiorrhiza, and ginseng, could act on multiple signaling pathways involved in inflammation, oxidative stress and apoptosis.ConclusionTCM could protect COVID-19 patients from tissue injuries, a protection that might be, at least partially, attributed to the anti-inflammatory, antioxidant and anti-apoptotic effects of the TCM under investigation. This review provides evidence and support for clinical treatment and novel drug research using TCM.     

The use of genomic variants to drive drug repurposing for chronic hepatitis B

BackgroundOne of the main challenges in personalized medicine is to establish and apply a large number of variants from genomic databases into clinical diagnostics and further facilitate genome-driven drug repurposing. By utilizing biological chronic hepatitis B infection (CHB) risk genes, our study proposed a systematic approach to use genomic variants to drive drug repurposing for CHB.MethodThe genomic variants were retrieved from the Genome-Wide Association Study (GWAS) and Phenome-Wide Association Study (PheWAS) databases. Then, the biological CHB risk genes crucial for CHB progression were prioritized based on the scoring system devised with five strict functional annotation criteria. A score of ≥ 2 were categorized as the biological CHB risk genes and further shed light on drug target genes for CHB treatments. Overlapping druggable targets were identified using two drug databases (DrugBank and Drug-Gene Interaction Database (DGIdb)).ResultsA total of 44 biological CHB risk genes were screened based on the scoring system from five functional annotation criteria. Interestingly, we found 6 druggable targets that overlapped with 18 drugs with status of undergoing clinical trials for CHB, and 9 druggable targets that overlapped with 20 drugs undergoing preclinical investigations for CHB. Eight druggable targets were identified, overlapping with 25 drugs that can potentially be repurposed for CHB. Notably, CD40 and HLA-DPB1 were identified as promising targets for CHB drug repurposing based on the target scores.ConclusionThrough the integration of genomic variants and a bioinformatic approach, our findings suggested the plausibility of CHB genomic variant-driven drug repurposing for CHB.     

Toxicity as prime selection criterion among SARS-active herbal medications

We present here a new selection criterion for prioritizing research on efficacious drugs for the fight against COVID-19: the relative toxicity versus safety of herbal medications, which were effective against SARS in the 2002/2003 epidemic. We rank these medicines according to their toxicity versus safety as basis for preferential rapid research on their potential in the treatment of COVID-19. The data demonstrate that from toxicological information nothing speaks against immediate investigation on, followed by rapid implementation of Lonicera japonica, Morus alba, Forsythia suspensa, and Codonopsis spec. for treatment of COVID-19 patients. Glycyrrhiza spec. and Panax ginseng are ranked in second priority and ephedrine-free Herba Ephedrae extract in third priority (followed by several drugs in lower preferences). Rapid research on their efficacy in the therapy - as well as safety under the specific circumstances of COVID-19 - followed by equally rapid implementation will provide substantial advantages to Public Health including immediate availability, enlargement of medicinal possibilities, in cases where other means are not successful (non-responders), not tolerated (sensitive individuals) or just not available (as is presently the case) and thus minimize sufferings and save lives. Moreover, their moderate costs and convenient oral application are especially advantageous for underprivileged populations in developing countries.     

The potential use of Drosophila as an in vivo model organism for COVID-19-related research: a review

The world urgently needs effective antiviral approaches against emerging viruses, as shown by the coronavirus disease 2019 (COVID-19) pandemic, which has become an exponentially growing health crisis. Scientists from diverse backgrounds have directed their efforts towards identifying key features of SARS-CoV-2 and clinical manifestations of COVID-19 infection. Reports of more transmissible variants of SARS-CoV-2 also raise concerns over the possibility of an explosive trajectory of the pandemic, so scientific attention should focus on developing new weapons to help win the fight against coronaviruses that may undergo further mutations in the future. Drosophila melanogaster offers a powerful and potential in vivo model that can significantly increase the efficiency of drug screening for viral and bacterial infections. Thanks to its genes with functional human homologs, Drosophila could play a significant role in such gene-editing studies geared towards designing vaccines and antiviral drugs for COVID-19. It can also help rectify current drawbacks of CRISPR-based therapeutics like off-target effects and delivery issues, representing another momentous step forward in healthcare. Here I present an overview of recent literature and the current state of knowledge, explaining how it can open up new avenues for Drosophila in our battle against infectious diseases.     

Sulforaphane inhibits the expression of interleukin-6 and interleukin-8 induced in bronchial epithelial IB3-1 cells by exposure to the SARS-CoV-2 Spike protein

BackgroundA key clinical feature of COVID-19 is a deep inflammatory state known as “cytokine storm” and characterized by high expression of several cytokines, chemokines and growth factors, including IL-6 and IL-8. A direct consequence of this inflammatory state in the lungs is the Acute Respiratory Distress Syndrome (ARDS), frequently observed in severe COVID-19 patients. The "cytokine storm" is associated with severe forms of COVID-19 and poor prognosis for COVID-19 patients. Sulforaphane (SFN), one of the main components of Brassica oleraceae L. (Brassicaceae or Cruciferae), is known to possess anti-inflammatory effects in tissues from several organs, among which joints, kidneys and lungs.PurposeThe objective of the present study was to determine whether SFN is able to inhibit IL-6 and IL-8, two key molecules involved in the COVID-19 "cytokine storm".MethodsThe effects of SFN were studied in vitro on bronchial epithelial IB3-1 cells exposed to the SARS-CoV-2 Spike protein (S-protein). The anti-inflammatory activity of SFN on IL-6 and IL-8 expression has been evaluated by RT-qPCR and Bio-Plex analysis.ResultsIn our study SFN inhibits, in cultured IB3-1 bronchial cells, the gene expression of IL-6 and IL-8 induced by the S-protein of SARS-CoV-2. This represents the proof-of-principle that SFN may modulate the release of some key proteins of the COVID-19 "cytokine storm".ConclusionThe control of the cytokine storm is one of the major issues in the management of COVID-19 patients. Our study suggests that SFN can be employed in protocols useful to control hyperinflammatory state associated with SARS-CoV-2 infection.     

Possible Trichosporon asahii urinary tract infection in a critically ill COVID-19 patient

BackgroundTrichosporon asahii, an emerging fungal pathogen, has been frequently associated with invasive infections in critically ill patients.Case reportA 74-year-old male patient diagnosed with COVID-19 was admitted to an Intensive Care Unit (ICU). During hospitalization, the patient displayed episodes of bacteremia by Staphylococcus haemolyticus and a possible urinary tract infection by T. asahii. While the bacterial infection was successfully treated using broad-spectrum antibiotics, the fungal infection in the urinary tract was unsuccessfully treated with anidulafungin and persisted until the patient died.ConclusionsWith the evolving COVID-19 pandemic, invasive fungal infections have been increasingly reported, mainly after taking immunosuppressant drugs associated with long-term broad-spectrum antibiotic therapy. Although Candida and Aspergillus are still the most prevalent invasive fungi, T. asahii and other agents have emerged in critically ill patients. Therefore, a proper surveillance and diagnosing any fungal infection are paramount, particularly in COVID-19 immunocompromised populations.