Connectivity mapping (ssCMap) to predict A20-inducing drugs and their antiinflammatory action in cystic fibrosis

Critical analysis of polycyclic tetramate macrolactam biosynthetic gene cluster phylogeny and functional diversity

Polycyclic tetramate macrolactams (PTMs) are bioactive natural products commonly associated with certain actinobacterial and proteobacterial lineages. These molecules have been the subject of numerous structure-activity investigations since the 1970s. New members continue to be pursued in wild and engineered bacterial strains, and advances in PTM biosynthesis suggest their outwardly simplistic biosynthetic gene clusters (BGCs) belie unexpected product complexity. To address the origins of this complexity and understand its influence on PTM discovery, we engaged in a combination of bioinformatics to systematically classify PTM BGCs and PTM-targeted metabolomics to compare the products of select BGC types. By comparing groups of producers and BGC mutants, we exposed knowledge gaps that complicate bioinformatics-driven product predictions. In sum, we provide new insights into the evolution of PTM BGCs while systematically accounting for the PTMs discovered thus far. The combined computational and metabologenomic findings presented here should prove useful for guiding future discovery.IMPORTANCEPolycyclic tetramate macrolactam (PTM) pathways are frequently found within the genomes of biotechnologically important bacteria, including Streptomyces and Lysobacter spp. Their molecular products are typically bioactive, having substantial agricultural and therapeutic interest. Leveraging bacterial genomics for the discovery of new related molecules is thus desirable, but drawing accurate structural predictions from bioinformatics alone remains challenging. This difficulty stems from a combination of previously underappreciated biosynthetic complexity and remaining knowledge gaps, compounded by a stream of yet-uncharacterized PTM biosynthetic loci gleaned from recently sequenced bacterial genomes. We engaged in the following study to create a useful framework for cataloging historic PTM clusters, identifying new cluster variations, and tracing evolutionary paths for these molecules. Our data suggest new PTM chemistry remains discoverable in nature. However, our metabolomic and mutational analyses emphasize the practical limitations of genomics-based discovery by exposing hidden complexity.

PharmGWAS: a GWAS-based knowledgebase for drug repurposing

Leveraging genetics insights to promote drug repurposing has become a promising and active strategy in pharmacology. Indeed, among the 50 drugs approved by FDA in 2021, two-thirds have genetically supported evidence. In this regard, the increasing amount of widely available genome-wide association studies (GWAS) datasets have provided substantial opportunities for drug repurposing based on genetics discoveries. Here, we developed PharmGWAS, a comprehensive knowledgebase designed to identify candidate drugs through the integration of GWAS data. PharmGWAS focuses on novel connections between diseases and small-molecule compounds derived using a reverse relationship between the genetically-regulated expression signature and the drug-induced signature. Specifically, we collected and processed 1929 GWAS datasets across a diverse spectrum of diseases and 724 485 perturbation signatures pertaining to a substantial 33609 molecular compounds. To obtain reliable and robust predictions for the reverse connections, we implemented six distinct connectivity methods. In the current version, PharmGWAS deposits a total of 740 227 genetically-informed disease-drug pairs derived from drug-perturbation signatures, presenting a valuable and comprehensive catalog. Further equipped with its user-friendly web design, PharmGWAS is expected to greatly aid the discovery of novel drugs, the exploration of drug combination therapies and the identification of drug resistance or side effects. PharmGWAS is available at https://ngdc.cncb.ac.cn/pharmgwas.

An AI Approach to Identifying Novel Therapeutics for Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a chronic autoimmune disorder that has a significant impact on quality of life and work capacity. Treatment of RA aims to control inflammation and alleviate pain; however, achieving remission with minimal toxicity is frequently not possible with the current suite of drugs. This review aims to summarise current treatment practices and highlight the urgent need for alternative pharmacogenomic approaches for novel drug discovery. These approaches can elucidate new relationships between drugs, genes, and diseases to identify additional effective and safe therapeutic options. This review discusses how computational approaches such as connectivity mapping offer the ability to repurpose FDA-approved drugs beyond their original treatment indication. This review also explores the concept of drug sensitisation to predict co-prescribed drugs with synergistic effects that produce enhanced anti-disease efficacy by involving multiple disease pathways. Challenges of this computational approach are discussed, including the availability of suitable high-quality datasets for comprehensive analysis and other data curation issues. The potential benefits include accelerated identification of novel drug combinations and the ability to trial and implement established treatments in a new index disease. This review underlines the huge opportunity to incorporate disease-related data and drug-related data to develop methods and algorithms that have strong potential to determine novel and effective treatment regimens.

Current research into A20 mediation of allergic respiratory diseases and its potential usefulness as a therapeutic target

Allergic airway diseases are characterized by excessive and prolonged type 2 immune responses to inhaled allergens. Nuclear factor κB (NF-κB) is a master regulator of the immune and inflammatory response, which has been implicated to play a prominent role in the pathogenesis of allergic airway diseases. The potent anti-inflammatory protein A20, termed tumor necrosis factor-α-inducible protein 3 (TNFAIP3), exerts its effects by inhibiting NF-κB signaling. The ubiquitin editing abilities of A20 have attracted much attention, resulting in its identification as a susceptibility gene in various autoimmune and inflammatory disorders. According to the results of genome-wide association studies, several TNFAIP3 gene locus nucleotide polymorphisms have been correlated to allergic airway diseases. In addition, A20 has been found to play a pivotal role in immune regulation in childhood asthma, particularly in the protection against environmentally mediated allergic diseases. The protective effects of A20 against allergy were observed in conditional A20-knockout mice in which A20 was depleted in the lung epithelial cells, dendritic cells, or mast cells. Furthermore, A20 administration significantly decreased inflammatory responses in mouse models of allergic airway diseases. Here, we review emerging findings elucidating the cellular and molecular mechanisms by which A20 regulates inflammatory signaling in allergic airway diseases, as well as discuss its potential as a therapeutic target.

A20 functions as a negative regulator of the lipopolysaccharide-induced inflammation in corneal epithelial cells

A20, also called TNFAIP3, is a crucial regulator of inflammation in various diseases but has not evidenced its function in the cornea. We aimed to evaluate the existence and the functions of A20 in human corneal epithelial (HCE-T) cells. After being treated with lipopolysaccharide (LPS) in different concentrations or at separate times, cells were collected to analyze A20 expressions. We then constructed the A20 knockdown system by siRNA and the A20 overexpressing system by lentivirus transduction. Systems were further exposed to medium with or without LPS for indicated times. Next, we evaluated the production of inflammatory cytokines (IL-6 and IL-8) by qRT-PCR and ELISA. Also, the translocation of P65 and the phosphorylation of P65, P38 and JNK were observed in two systems. In addition, we used the nuclear factor kappa-B (NF-κB) antagonist TPCA-1 for the pretreatment in cells and then detected the A20 expressions. We found a low basal expression of A20 in HCE-T cells, and the expressions could be dose-dependently induced by LPS, peaking at 4 h in protein level after stimulation. Both the A20 knockdown and A20 overexpressing systems were confirmed to be effective. After the LPS treatment, productions of IL-6 and IL-8 were enhanced in the A20 knockdown system and reduced in the A20 overexpressing system. A20 reduced the translocation of P65 into the nucleus and the phosphorylation of P65, P38 and JNK. Furthermore, TPCA-1 pretreatment reduced the expression of A20 in cells. We concluded that A20 is a potent regulator for corneal epithelium's reaction to inflammation, and it thus is expected to be a potential therapy target for ocular surface diseases.

Venetoclax Decreases the Expression of the Spike Protein through Amino Acids Q493 and S494 in SARS-CoV-2

The new coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus (SARS-CoV-2) has been reported and spread globally. There is an urgent need to take urgent measures to treat and prevent further infection of this virus. Here, we use virtual drug screening to establish pharmacophore groups and analyze the ACE2 binding site of the spike protein with the ZINC drug database and DrugBank database by molecular docking and molecular dynamics simulations. Screening results showed that Venetoclax, a treatment drug for chronic lymphocytic leukemia, has a potential ability to bind to the spike protein of SARS-CoV-2. In addition, our in vitro study found that Venetoclax degraded the expression of the spike protein of SARS-CoV-2 through amino acids Q493 and S494 and blocked the interaction with the ACE2 receptor. Our results suggest that Venetoclax is a candidate for clinical prevention and treatment and deserves further research.

Computational drug repurposing against SARS-CoV-2 reveals plasma membrane cholesterol depletion as key factor of antiviral drug activity

Comparing SARS-CoV-2 infection-induced gene expression signatures to drug treatment-induced gene expression signatures is a promising bioinformatic tool to repurpose existing drugs against SARS-CoV-2. The general hypothesis of signature-based drug repurposing is that drugs with inverse similarity to a disease signature can reverse disease phenotype and thus be effective against it. However, in the case of viral infection diseases, like SARS-CoV-2, infected cells also activate adaptive, antiviral pathways, so that the relationship between effective drug and disease signature can be more ambiguous. To address this question, we analysed gene expression data from in vitro SARS-CoV-2 infected cell lines, and gene expression signatures of drugs showing anti-SARS-CoV-2 activity. Our extensive functional genomic analysis showed that both infection and treatment with in vitro effective drugs leads to activation of antiviral pathways like NFkB and JAK-STAT. Based on the similarity-and not inverse similarity-between drug and infection-induced gene expression signatures, we were able to predict the in vitro antiviral activity of drugs. We also identified SREBF1/2, key regulators of lipid metabolising enzymes, as the most activated transcription factors by several in vitro effective antiviral drugs. Using a fluorescently labeled cholesterol sensor, we showed that these drugs decrease the cholesterol levels of plasma-membrane. Supplementing drug-treated cells with cholesterol reversed the in vitro antiviral effect, suggesting the depleting plasma-membrane cholesterol plays a key role in virus inhibitory mechanism. Our results can help to more effectively repurpose approved drugs against SARS-CoV-2, and also highlights key mechanisms behind their antiviral effect.

Overcoming Drug Resistance in Advanced Prostate Cancer by Drug Repurposing

Prostate cancer (PCa) is the second most common cancer in men. Common treatments include active surveillance, surgery, or radiation. Androgen deprivation therapy and chemotherapy are usually reserved for advanced disease or biochemical recurrence, such as castration-resistant prostate cancer (CRPC), but they are not considered curative because PCa cells eventually develop drug resistance. The latter is achieved through various cellular mechanisms that ultimately circumvent the pharmaceutical’s mode of action. The need for novel therapeutic approaches is necessary under these circumstances. An alternative way to treat PCa is by repurposing of existing drugs that were initially intended for other conditions. By extrapolating the effects of previously approved drugs to the intracellular processes of PCa, treatment options will expand. In addition, drug repurposing is cost-effective and efficient because it utilizes drugs that have already demonstrated safety and efficacy. This review catalogues the drugs that can be repurposed for PCa in preclinical studies as well as clinical trials.

Quercetin Preserves Oral Cavity Health by Mitigating Inflammation and Microbial Dysbiosis

Failure to attenuate inflammation coupled with consequent microbiota changes drives the development of bone-destructive periodontitis. Quercetin, a plant-derived polyphenolic flavonoid, has been linked with health benefits in both humans and animals. Using a systematic approach, we investigated the effect of orally delivered Quercetin on host inflammatory response, oral microbial composition and periodontal disease phenotype. In vivo, quercetin supplementation diminished gingival cytokine expression, inflammatory cell infiltrate and alveolar bone loss. Microbiome analyses revealed a healthier oral microbial composition in Quercetin-treated versus vehicle-treated group characterized by reduction in the number of pathogenic species including Enterococcus, Neisseria and Pseudomonas and increase in the number of non-pathogenic Streptococcus sp. and bacterial diversity. In vitro, Quercetin diminished inflammatory cytokine production through modulating NF-κB:A20 axis in human macrophages following challenge with oral bacteria and TLR agonists. Collectively, our findings reveal that Quercetin supplement instigates a balanced periodontal tissue homeostasis through limiting inflammation and fostering an oral cavity microenvironment conducive of symbiotic microbiota associated with health. This proof of concept study provides key evidence for translational studies to improve overall health.

Antibacterial Activity of Ikarugamycin against Intracellular Staphylococcus aureus in Bovine Mammary Epithelial Cells In Vitro Infection Model

Simple Summary

Antibiotics are widely used for the treatment and control of bovine mastitis. However, the treatment has only been partially effective, as the cure percentage only ranging from 10–30%. Infection by Staphylococcus aureus (S. aureus) is particularly difficult to treat due to the bacteria’s ability to enter and resides inside the host cells. Most antibiotics are ineffective against intracellular bacterial due to the poor penetration into host cells to achieve optimal intracellular bactericidal bioavailability levels. There is therefore, an increasing need to evaluate candidate active substances and develop novel antibiotics effective against intracellular persistence infection. In this study, we examine the potential antibacterial properties of ikarugamycin compound as an alternative drug candidate to be explored for treating persistent bovine mastitis caused by intracellular S. aureus using bovine mammary cell line as an in vitro infection model. We also assessed the potential cytotoxicity effect of ikarugamycin in the infection model. We found that, the ikarugamycin possessed intracellular killing activity against S. aureus within the mammary epithelial cell. This finding highlights the potential application of ikarugamycin as a novel antimicrobial for the treatment of S. aureus mastitis.

Abstract

Staphylococcus aureus is an ubiquitous and versatile pathogen associated with a wide range of diseases. In animals, this bacterium is one of the causative agents of bovine mastitis, responsible for huge economic losses in the dairy industry. Besides the development of antibiotic resistance, the intracellular survival of S. aureus within udder cells has rendered many antibiotics ineffective, leading to therapeutic failure. Our study therefore aims to investigate the in vitro bactericidal activity of ikarugamycin (IKA) against intracellular S. aureus using a bovine mammary epithelial cells (Mac-T cells) infection model and determine the cytotoxic effect. Minimum inhibitory concentration (MIC) was used to determine the antibacterial activity of IKA, and Mac-T cells were infected with S. aureus using gentamicin protection assay. IKA intracellular antibacterial activity assays were used to determine the bactericidal activity of IKA against intracellular S. aureus. The cytotoxicity of IKA against Mac-T cells was evaluated using the resazurin assay. We showed that, S. aureus is susceptible to IKA with a MIC value of 0.6 μg/mL. IKA at 4 × MIC and 8 × MIC have bactericidal activity by reducing 3 and 5 logs₁₀ CFU/mL of S. aureus in the first six-hour of treatment respectively. In addition, IKA demonstrated intracellular killing activity by killing 90% of intracellular S. aureus at 5 μg/mL. This level is comparatively lower than 9.2 μg/mL determined as the half-maximal inhibitory concentration (IC₅₀) of IKA required to kill 50% of Mac-T cells, highlighting a lower concentration required for bactericidal effect compared to the cytotoxic effect. The study highlighted that importance of IKA as a potential antibiotic candidate to be explored for the in vivo efficacy in treating S. aureus mastitis.

A potent endocytosis inhibitor Ikarugamycin up-regulates TNF production

Ikarugamycin (IK) is an antibiotic which has been reported to have a variety of functions, such as inhibition of clathrin-mediated endocytosis (CME), anti-tumor effects and regulation of the immune system. Whether IK influences cytokine production is poorly understood. We have investigated the relationship between IK and production of tumor necrosis factor-α (TNF). TNF plays a pivotal role in pathogenesis of many diseases. Although the dynamics of soluble TNF (sTNF) has been widely explored so far, the functions of the membrane form of TNF (mTNF) have not been fully elucidated. We demonstrated that IK increases the amount of mTNF and prolongs the duration of TNF expression. This effect is unrelated to the shedding activity of disintegrin and metalloproteinase domain-containing protein 17 (ADAM 17). Our results revealed that there is a mechanism to terminate inflammation at the cellular level which IK dysregulates. Furthermore, IK can be a tool to study TNF signaling due to its effect of increasing mTNF expression.

Host-targeted Interventions as an Exciting Opportunity to Combat Malaria

Terminal and benign diseases alike in adults, children, pregnant women, and others are successfully treated by pharmacological inhibitors that target human enzymes. Despite extensive global efforts to fight malaria, the disease continues to be a massive worldwide health burden, and new interventional strategies are needed. Current drugs and vector control strategies have contributed to the reduction in malaria deaths over the past 10 years, but progress toward eradication has waned in recent years. Resistance to antimalarial drugs is a substantial and growing problem. Moreover, targeting dormant forms of the malaria parasite Plasmodium vivax is only possible with two approved drugs, which are both contraindicated for individuals with glucose-6-phosphate dehydrogenase deficiency and in pregnant women. Plasmodium parasites are obligate intracellular parasites and thus have specific and absolute requirements of their hosts. Growing evidence has described these host necessities, paving the way for opportunities to pharmacologically target host factors to eliminate Plasmodium infection. Here, we describe progress in malaria research and adjacent fields and discuss key challenges that remain in implementing host-directed therapy against malaria.

Identification and validation of novel biomarkers and therapeutics for pulpitis using connectivity mapping

AIM

To create an irreversible pulpitis gene signature from microarray data of healthy and inflamed dental pulps, followed by a bioinformatics approach using connectivity mapping to identify therapeutic compounds that could potentially treat pulpitis.

METHODOLOGY

The Gene Expression Omnibus (GEO) database, an international public repository of genomics data sets, was searched for human microarray datasets assessing pulpitis. An irreversible pulpitis gene expression signature was generated by differential expression analysis. The statistically significant connectivity map (ssCMap) method was used to identify compounds with a highly correlating gene expression pattern. qPCR was used to validate novel pulpitis genes. An ex vivo pulpitis model was used to test the effects of the compounds identified, and the level of inflammatory cytokines was measured with qPCR, ELISA and multiplex array. Means were compared using the t-test or ANOVA with the level of significance set at p ≤ .05.

RESULTS

Pulpitis gene signatures were created using differential gene expression analysis at cutoff points p = .0001 and .000018. Top upregulated genes were selected as potential pulpitis biomarkers. Among these, IL8, IL6 and MMP9 were previously identified as pulpitis biomarkers. Novel upregulated genes, chemokine (C-C motif) ligand 21 (CCL21), metallothionein 1H (MT1H) and aquaporin 9 (AQP9) were validated in the pulp tissue of teeth clinically diagnosed with irreversible pulpitis using qPCR. ssCMap analysis identified fluvastatin (Statin) and dequalinium chloride (Quaternary ammonium) as compounds with the strongest correlation to the gene signatures (p = .0001). Fluvastatin reduced IL8, IL6, CCL21, AQP9 (p < .001) and MMP9 (p < .05) in the ex vivo pulpitis model, while dequalinium chloride reduced AQP9 (p < .001) but had no significant effect on the other biomarkers.

CONCLUSIONS

AQP9, MT1H and CCL21 were identified and validated as novel biomarkers for pulpitis. Fluvastatin and dequalinium chloride identified by the ssCMap as potential therapeutics for pulpitis reduced selected pulpitis biomarkers in an ex vivo pulpitis model. In vivo testing of these licenced drugs is warranted.

Integrative chemogenomic analysis identifies small molecules that partially rescue ΔF508-CFTR for cystic fibrosis

Rare diseases affect 10% of the first-world population, yet over 95% lack even a single pharmaceutical treatment. In the present age of information, we need ways to leverage our vast data and knowledge to streamline therapeutic development and lessen this gap. Here, we develop and implement an innovative informatic approach to identify therapeutic molecules, using the Connectivity Map and LINCS L1000 databases and disease-associated transcriptional signatures and pathways. We apply this to cystic fibrosis (CF), the most common genetic disease in people of northern European ancestry leading to chronic lung disease and reduced lifespan. We selected and tested 120 small molecules in a CF cell line, finding 8 with activity, and confirmed 3 in primary CF airway epithelia. Although chemically diverse, the transcriptional profiles of the hits suggest a common mechanism associated with the unfolded protein response and/or TNFα signaling. This study highlights the power of informatics to help identify new therapies and reveal mechanistic insights while moving beyond target-centric drug discovery.

The Advantages of Connectivity Map Applied in Traditional Chinese Medicine

Amid the establishment and optimization of Connectivity Map (CMAP), the functional relationships among drugs, genes, and diseases are further explored. This biological database has been widely used to identify drugs with common mechanisms, repurpose existing drugs, discover the molecular mechanisms of unknown drugs, and find potential drugs for some diseases. Research on traditional Chinese medicine (TCM) has entered a new era in the wake of the development of bioinformatics and other subjects including network pharmacology, proteomics, metabolomics, herbgenomics, and so on. TCM gradually conforms to modern science, but there is still a torrent of limitations. In recent years, CMAP has shown its distinct advantages in the study of the components of TCM and the synergetic mechanism of TCM formulas; hence, the combination of them is inevitable.

Identification of 37 Heterogeneous Drug Candidates for Treatment of COVID-19 via a Rational Transcriptomics-Based Drug Repurposing Approach

A year after the initial outbreak, the COVID-19 pandemic caused by SARS-CoV-2 virus remains a serious threat to global health, while current treatment options are insufficient to bring major improvements. The aim of this study is to identify repurposable drug candidates with a potential to reverse transcriptomic alterations in the host cells infected by SARS-CoV-2. We have developed a rational computational pipeline to filter publicly available transcriptomic datasets of SARS-CoV-2-infected biosamples based on their responsiveness to the virus, to generate a list of relevant differentially expressed genes, and to identify drug candidates for repurposing using LINCS connectivity map. Pathway enrichment analysis was performed to place the results into biological context. We identified 37 structurally heterogeneous drug candidates and revealed several biological processes as druggable pathways. These pathways include metabolic and biosynthetic processes, cellular developmental processes, immune response and signaling pathways, with steroid metabolic process being targeted by half of the drug candidates. The pipeline developed in this study integrates biological knowledge with rational study design and can be adapted for future more comprehensive studies. Our findings support further investigations of some drugs currently in clinical trials, such as itraconazole and imatinib, and suggest 31 previously unexplored drugs as treatment options for COVID-19.

Bioactive natural products from the genus Salinospora: a review

Actinomycetes are an important source for bioactive secondary metabolites. Among them, the genus Salinispora is one of the first salt obligatory marine species worldwide and is typically found in various types of substrates in tropical and subtropical marine environments including sediments and marine organisms. This genus produces a wide range of chemical scaffolds and bioactive compounds such as lomaiviticins, cyclomarins, rifamycins, salinaphthoquinones, and salinosporamides. This review arranged Salinispora derived secondary metabolites according to the three species that comprise the genus. Moreover, muta- and semi-synthesis analogs derived from salinosporamide were also described in this review.

Sesamin attenuates carrageenan-induced lung inflammation through upregulation of A20 and TAX1BP1 in rats

Sesamin is a major component in lignans of sesame seeds, has been described to possess a lot of biological activity. The main objective of our study was to investigate the inhibitory effect and novel molecular mechanisms of sesamin on carrageenan-induced lung inflammation in rats. Here we showed that sesamin can obviously reduce polymorphonuclear neutrophils infiltration and exudate volume. Further studies exhibited sesamin can inhibit cytokines release, polymorphonuclear neutrophils markers production and the degree of lung tissues injury. Western blot analysis revealed that sesamin can inhibit the TRAF6 expression and NF-κB pathway activation in lung tissue. We found that sesamin can increase the expression of A20 and TAX1BP1 in lung tissues, and the interaction between the two molecules. In conclusion, all these results demonstrated that sesamin can attenuate carrageenan-induced lung inflammation, the mechanisms that may be related to upregulation of the novel target A20 and TAX1BP1 which can negative regulation for NF-κB pathway. Importantly, this is the first evidence showing that TAX1BP1 can be as a novel regulatory target to attenuate the lung inflammation.

Role of Cystic Fibrosis Bronchial Epithelium in Neutrophil Chemotaxis

A hallmark of cystic fibrosis (CF) chronic respiratory disease is an extensive neutrophil infiltrate in the mucosa filling the bronchial lumen, starting early in life for CF infants. The genetic defect of the CF Transmembrane conductance Regulator (CFTR) ion channel promotes dehydration of the airway surface liquid, alters mucus properties, and decreases mucociliary clearance, favoring the onset of recurrent and, ultimately, chronic bacterial infection. Neutrophil infiltrates are unable to clear bacterial infection and, as an adverse effect, contribute to mucosal tissue damage by releasing proteases and reactive oxygen species. Moreover, the rapid cellular turnover of lumenal neutrophils releases nucleic acids that further alter the mucus viscosity. A prominent role in the recruitment of neutrophil in bronchial mucosa is played by CF bronchial epithelial cells carrying the defective CFTR protein and are exposed to whole bacteria and bacterial products, making pharmacological approaches to regulate the exaggerated neutrophil chemotaxis in CF a relevant therapeutic target. Here we revise: (a) the major receptors, kinases, and transcription factors leading to the expression, and release of neutrophil chemokines in bronchial epithelial cells; (b) the role of intracellular calcium homeostasis and, in particular, the calcium crosstalk between endoplasmic reticulum and mitochondria; (c) the epigenetic regulation of the key chemokines; (d) the role of mutant CFTR protein as a co-regulator of chemokines together with the host-pathogen interactions; and (e) different pharmacological strategies to regulate the expression of chemokines in CF bronchial epithelial cells through novel drug discovery and drug repurposing.

Modulation of allergic inflammation in the lung by a peptide derived from Mycobacteria tuberculosis chaperonin 60.1

BACKGROUND

We have previously demonstrated that Mycobacteria tuberculosis chaperonin 60.1 inhibits leucocyte diapedesis and bronchial hyperresponsiveness in a murine model of allergic lung inflammation.

METHODS

In the present study, we have investigated the effect of a shorter peptide sequence derived from Cpn 60.1, named IRL201104, on allergic lung inflammation induced by ovalbumin (OVA) in mice and by house dust mite (HDM) in guinea pigs, as well as investigating the action of IRL201104 on human cells in vitro.

RESULTS

Pre-treatment of mice or guinea pigs with IRL201104 inhibits the infiltration of eosinophils to the lung, cytokine release, and in guinea pig skin, inhibits allergen-induced vascular permeability. The protective effect of intranasal IRL201104 against OVA-induced eosinophilia persisted for up to 20 days post-treatment. Moreover, OVA-sensitized mice treated intranasally with 20 ng/kg of IRL201104 show a significant increase in the expression of the anti-inflammatory molecule ubiquitin A20 and significant inhibition of the activation of NF-κB in lung tissue. Our results also show that A20 expression was significantly reduced in blood leucocytes and ASM obtained from patients with asthma compared to cells obtained from healthy subjects which were restored after incubation with IRL201104 in vitro, when added alone, or in combination with LPS or TNF-α in ASM.

CONCLUSIONS

Our results suggest that a peptide derived from mycobacterial Cpn60.1 has a long-lasting anti-inflammatory and immunomodulatory activity which may help explain some of the protective effects of TB against allergic diseases.

Targeting Degradation of the Transcription Factor C/EBPβ Reduces Lung Fibrosis by Restoring Activity of the Ubiquitin-Editing Enzyme A20 in Macrophages

Although recent progress provides mechanistic insights into the pathogenesis of pulmonary fibrosis (PF), rare anti-PF therapeutics show definitive promise for treating this disease. Repeated lung epithelial injury results in injury-repairing response and inflammation, which drive the development of PF. Here, we report that chronic lung injury inactivated the ubiquitin-editing enzyme A20, causing progressive accumulation of the transcription factor C/EBPβ in alveolar macrophages (AMs) from PF patients and mice, which upregulated a number of immunosuppressive and profibrotic factors promoting PF development. In response to chronic lung injury, elevated glycogen synthase kinase-3β (GSK-3β) interacted with and phosphorylated A20 to suppress C/EBPβ degradation. Ectopic expression of A20 or pharmacological restoration of A20 activity by disturbing the A20-GSK-3β interaction accelerated C/EBPβ degradation and showed potent therapeutic efficacy against experimental PF. Our study indicates that a regulatory mechanism of the GSK-3β-A20-C/EBPβ axis in AMs may be a potential target for treating PF and fibroproliferative lung diseases.

A20 as a novel target for the anti-neuroinflammatory effect of chrysin via inhibition of NF-κB signaling pathway

Neuroinflammation is now recognized to be a feature of many neurological disorders. More accumulated evidences suggested chrysin which was contained in honey, propolis, vegetables, fruits and plants can exert biological activities including anti-neuroinflammatory effects. However, the precise molecular mechanisms of anti-neuroinflammatory effects remain unclear. In the present study, we explored a novel molecular mechanism involved in the anti-neuroinflammatory effect of chrysin. Firstly, we investigated the anti-neuroinflammatory effects of chrysin in LPS-induced BV2, primary microglial cells and mice. Next, we found chrysin can inhibit NF-κB pathway and TRAF6 expression, but upregulate the expression of zinc-finger protein A20. Further studies have revealed upregulation of A20 can regulate the inhibitory effects of chrysin on NF-κB pathways via regulation of TRAF6 polyubiquitination. This present study demonstrates that chrysin exerts an anti-neuroinflammatory effect via a novel mechanism, the upregulation of A20 expression, also validates A20 is a novel effective pharmacological target for developing agents in the treatment of neuroinflammation-related diseases.

The hidden enzymology of bacterial natural product biosynthesis

Bacterial natural products display astounding structural diversity, which, in turn, endows them with a remarkable range of biological activities that are of significant value to modern society. Such structural features are generated by biosynthetic enzymes that construct core scaffolds or perform peripheral modifications, and can thus define natural product families, introduce pharmacophores and permit metabolic diversification. Modern genomics approaches have greatly enhanced our ability to access and characterize natural product pathways via sequence-similarity-based bioinformatics discovery strategies. However, many biosynthetic enzymes catalyse exceptional, unprecedented transformations that continue to defy functional prediction and remain hidden from us in bacterial (meta)genomic sequence data. In this Review, we highlight exciting examples of unusual enzymology that have been uncovered recently in the context of natural product biosynthesis. These suggest that much of the natural product diversity, including entire substance classes, awaits discovery. New approaches to lift the veil on the cryptic chemistries of the natural product universe are also discussed.

Use of big data in drug development for precision medicine: an update

INTRODUCTION

Big-data-driven drug development resources and methodologies have been evolving with ever-expanding data from large-scale biological experiments, clinical trials, and medical records from participants in data collection initiatives. The enrichment of biological- and clinical-context-specific large-scale data has enabled computational inference more relevant to real-world biomedical research, particularly identification of therapeutic targets and drugs for specific diseases and clinical scenarios.

AREAS COVERED

Here we overview recent progresses made in the fields: new big-data-driven approach to therapeutic target discovery, candidate drug prioritization, inference of clinical toxicity, and machine-learning methods in drug discovery.

EXPERT OPINION

In the near future, much larger volumes and complex datasets for precision medicine will be generated, e.g., individual and longitudinal multi-omic, and direct-to-consumer datasets. Closer collaborations between experts with different backgrounds would also be required to better translate analytic results into prognosis and treatment in the clinical practice. Meanwhile, cloud computing with protected patient privacy would become more routine analytic practice to fill the gaps within data integration along with the advent of big-data. To conclude, integration of multitudes of data generated for each individual along with techniques tailored for big-data analytics may eventually enable us to achieve precision medicine.

gene2drug: a computational tool for pathway-based rational drug repositioning

Motivation

Drug repositioning has been proposed as an effective shortcut to drug discovery. The availability of large collections of transcriptional responses to drugs enables computational approaches to drug repositioning directly based on measured molecular effects.

Results

We introduce a novel computational methodology for rational drug repositioning, which exploits the transcriptional responses following treatment with small molecule. Specifically, given a therapeutic target gene, a prioritization of potential effective drugs is obtained by assessing their impact on the transcription of genes in the pathway(s) including the target. We performed in silico validation and comparison with a state-of-art technique based on similar principles. We next performed experimental validation in two different real-case drug repositioning scenarios: (i) upregulation of the glutamate-pyruvate transaminase (GPT), which has been shown to induce reduction of oxalate levels in a mouse model of primary hyperoxaluria, and (ii) activation of the transcription factor TFEB, a master regulator of lysosomal biogenesis and autophagy, whose modulation may be beneficial in neurodegenerative disorders.

Availability and implementation

A web tool for Gene2drug is freely available at http://gene2drug.tigem.it. An R package is under development and can be obtained from https://github.com/franapoli/gep2pep.

Contact

dibernardo@tigem.it.

Supplementary information

Supplementary data are available at Bioinformatics online.

Synergy from gene expression and network mining (SynGeNet) method predicts synergistic drug combinations for diverse melanoma genomic subtypes

Systems biology perspectives are crucial for understanding the pathophysiology of complex diseases, and therefore hold great promise for the discovery of novel treatment strategies. Drug combinations have been shown to improve durability and reduce resistance to available first-line therapies in a variety of cancers; however, traditional drug discovery approaches are prohibitively cost and labor-intensive to evaluate large-scale matrices of potential drug combinations. Computational methods are needed to efficiently model complex interactions of drug target pathways and identify mechanisms underlying drug combination synergy. In this study, we employ a computational approach, SynGeNet (Synergy from Gene expression and Network mining), which integrates transcriptomics-based connectivity mapping and network centrality analysis to analyze disease networks and predict drug combinations. As an exemplar of a disease in which combination therapies demonstrate efficacy in genomic-specific contexts, we investigate malignant melanoma. We employed SynGeNet to generate drug combination predictions for each of the four major genomic subtypes of melanoma (BRAF, NRAS, NF1, and triple wild type) using publicly available gene expression and mutation data. We validated synergistic drug combinations predicted by our method across all genomic subtypes using results from a high-throughput drug screening study across. Finally, we prospectively validated the drug combination for BRAF-mutant melanoma that was top ranked by our approach, vemurafenib (BRAF inhibitor) + tretinoin (retinoic acid receptor agonist), using both in vitro and in vivo models of BRAF-mutant melanoma and RNA-sequencing analysis of drug-treated melanoma cells to validate the predicted mechanisms. Our approach is applicable to a wide range of disease domains, and, importantly, can model disease-relevant protein subnetworks in precision medicine contexts.

Regulators of A20 (TNFAIP3): new drug-able targets in inflammation

Persistent activation of the transcription factor Nuclear factor-κB (NF-κB) is central to the pathogenesis of many inflammatory disorders, including those of the lung such as cystic fibrosis (CF), asthma, and chronic obstructive pulmonary disease (COPD). Despite recent advances in treatment, management of the inflammatory component of these diseases still remains suboptimal. A20 is an endogenous negative regulator of NF-κB signaling, which has been widely described in several autoimmune and inflammatory disorders and more recently in terms of chronic lung disorders. However, the underlying mechanism for the apparent lack of A20 in CF, COPD, and asthma has not been investigated. Transcriptional regulation of A20 is complex and requires coordination of different transcription factors. In this review we examine the existing body of research evidence on the regulation of A20, concentrating on pulmonary inflammation. Special focus is given to the repressor downstream regulatory element antagonist modulator (DREAM) and its nuclear and cytosolic action to regulate inflammation. We provide evidence that would suggest the A20-DREAM axis to be an important player in (airway) inflammatory responses and point to DREAM as a potential future therapeutic target for the modification of phenotypic changes in airway inflammatory disorders. A schematic summary describing the role of DREAM in inflammation with a focus on chronic lung diseases as well as the possible consequences of altered DREAM expression on immune responses is provided.

A Network Pharmacology-Based Analysis of Multi-Target, Multi-Pathway, Multi-Compound Treatment for Ovarian Serous Cystadenocarcinoma

BACKGROUND AND OBJECTIVES

Pharmacological control against ovarian serous cystadenocarcinoma has received increasing attention. The purpose of this study was to investigate multi-drug treatments as synergetic therapy for ovarian serous cystadenocarcinoma and to explore their mechanisms of action by the network pharmacology method.

METHODS

Genes acting on ovarian serous cystadenocarcinoma were first collected from GEPIA and DisGeNET. Gene Ontology annotation, Kyoto Encyclopedia of Genes and Genomes pathway, Reactome pathway, and Disease Ontology analyses were then conducted. A connectivity map analysis was employed to identify compounds as treatment options for ovarian serous cystadenocarcinoma. Targets of these compounds were obtained from the Search Tool for Interacting Chemicals (STITCH). The intersections between the ovarian serous cystadenocarcinoma-related genes and the compound targets were identified. Finally, the Kyoto Encyclopedia of Genes and Genomes and Reactome pathways in which the overlapped genes participated were selected, and a correspondence compound-target pathway network was constructed.

RESULTS

A total of 541 ovarian serous cystadenocarcinoma-related genes were identified. The functional enrichment and pathway analyses indicated that these genes were associated with critical tumor-related pathways. Based on the connectivity map analysis, five compounds (resveratrol, MG-132, puromycin, 15-delta prostaglandin J2, and valproic acid) were determined as treatment agents for ovarian serous cystadenocarcinoma. Next, 48 targets of the five compounds were collected. Following mapping of the 48 targets to the 541 ovarian serous cystadenocarcinoma-related genes, we identified six targets (PTGS1, FOS, HMOX1, CASP9, PPARG, and ABCB1) as therapeutic targets for ovarian serous cystadenocarcinoma by the five compounds. By analysis of the compound-target pathway network, we found the synergistic anti-ovarian serous cystadenocarcinoma potential and the underlying mechanisms of action of the five compounds.

CONCLUSION

In summary, latent drugs against ovarian serous cystadenocarcinoma were acquired and their target actions and pathways were determined by the network pharmacology strategy, which provides a new prospect for medicamentous therapy for ovarian serous cystadenocarcinoma. However, further in-depth studies are indispensable to increase the validity of this study.

A20, an essential component of the ubiquitin-editing protein complex, is a negative regulator of inflammation in human myometrium and foetal membranes

STUDY QUESTION

Does A20 regulate mediators involved in the terminal processes of human labour in primary myometrial and amnion cells?

SUMMARY ANSWER

A20 is a nuclear factor-kappa B (NF-κB) responsive gene that acts as a negative regulator of NF-κB-induced expression of pro-labour mediators.

WHAT IS KNOWN ALREADY

Inflammation is commonly implicated in spontaneous preterm birth and the processes involved in rupture of foetal membranes and uterine contractions. In myometrium and foetal membranes, the pro-inflammatory transcription factor NF-κB regulates the transcription of pro-labour mediators in response to inflammatory stimuli. In non-gestational tissues, A20 is widely recognised as an anti-inflammatory protein that inhibits inflammation-induced NF-κB signalling.

STUDY DESIGN, SIZE, DURATION

Primary human amnion and myometrial cells were used to determine the effect of pro-inflammatory mediators on A20 expression and the effect of A20 siRNA on the expression and secretion of pro-labour mediators. The expression of A20 was assessed in myometrium and foetal membranes from non-labouring and labouring women at preterm and or term (n = 8 or nine samples per group).

PARTICIPANTS/MATERIALS, SETTING, METHODS

The effects of pro-inflammatory mediators and of A20 siRNA in cell cultures were determined by quantitative RT-PCR (qRT-PCR), western blots, immunoassays, gelatin zymography and luciferase assays. A20 expression in tissue samples was assessed by qRT-PCR. Statistical significance was ascribed to a P value < 0.05.

MAIN RESULTS AND THE ROLE OF CHANCE

In primary cells isolated from myometrium and or amnion, the pro-inflammatory cytokines IL1B and TNF, the bacterial products flagellin and fsl-1, and the viral double stranded RNA analogue poly(I:C) significantly increased A20 mRNA expression via NF-κB. A20 siRNA studies in primary myometrial and amnion cells demonstrated an augmentation of inflammation-induced expression and or secretion of pro-inflammatory cytokines (IL1A, IL6), chemokines (CXCL1, CXCL8, CCL2), adhesion molecules (ICAM1, VCAM1), contraction-associated proteins (PTGS2, PTGFR, PGF2α) and the extracellular matrix degrading enzyme MMP9, as well as NF-κB activation. Inhibition of NF-κB activity significant attenuated inflammation-induced expression of pro-labour mediators in A20 siRNA transfected cells. Finally, A20 mRNA expression was decreased in myometrium and foetal membranes with labour, and in foetal membranes with chorioamnionitis.

LARGE SCALE DATA

Not applicable.

LIMITATIONS, REASONS FOR CAUTION

The conclusions of this study are solely reliant on the data from in vitro experiments using cells isolated from myometrium and amnion.

WIDER IMPLICATIONS OF THE FINDINGS

The results of this study raise the possibility that targeting A20 may be a therapeutic approach to reduce inflammation associated with spontaneous preterm birth.

STUDY FUNDING AND COMPETING INTEREST(S)

Associate Professor Martha Lappas is supported by a Career Development Fellowship from the National Health and Medical Research Council (NHMRC; grant no. 1047025). Funding for this study was provided by the NHMRC (grant no. 1058786), Norman Beischer Medical Research Foundation and the Mercy Research Foundation. There are no competing interests.

A review of connectivity map and computational approaches in pharmacogenomics

Large-scale perturbation databases, such as Connectivity Map (CMap) or Library of Integrated Network-based Cellular Signatures (LINCS), provide enormous opportunities for computational pharmacogenomics and drug design. A reason for this is that in contrast to classical pharmacology focusing at one target at a time, the transcriptomics profiles provided by CMap and LINCS open the door for systems biology approaches on the pathway and network level. In this article, we provide a review of recent developments in computational pharmacogenomics with respect to CMap and LINCS and related applications.

A review of connectivity map and computational approaches in pharmacogenomics

Large-scale perturbation databases, such as Connectivity Map (CMap) or Library of Integrated Network-based Cellular Signatures (LINCS), provide enormous opportunities for computational pharmacogenomics and drug design. A reason for this is that in contrast to classical pharmacology focusing at one target at a time, the transcriptomics profiles provided by CMap and LINCS open the door for systems biology approaches on the pathway and network level. In this article, we provide a review of recent developments in computational pharmacogenomics with respect to CMap and LINCS and related applications.

A combined connectivity mapping and pharmacoepidemiology approach to identify existing medications with breast cancer causing or preventing properties

PURPOSE

We applied a novel combined connectivity mapping and pharmacoepidemiological approach to identify medications that alter breast cancer risk.

METHODS

The connectivity mapping process identified 6 potentially cancer-causing (meloxicam, azithromycin, rizatriptan, citalopram, rosiglitazone, and verapamil) and 4 potentially cancer-preventing (bendroflumethiazide, sertraline, fluvastatin, and budesonide) medications that were suitable for pharmacoepidemiological investigation. Within the UK Clinical Practice Research Datalink, we matched 45,147 breast cancer cases to 45,147 controls based on age, year, and general practice. Medication use was determined from electronic prescribing records. We used conditional logistic regression to calculate odds ratios (ORs) for the association between medication use and cancer risk after adjustment for comorbidities, lifestyle factors, deprivation, and other medication use.

RESULTS

Bendroflumethiazide was associated with increased breast cancer risk (OR: 1.11; 95% CI: 1.06, 1.15); however the connectivity mapping exercise predicted that this medication would reduce risk. There were no statistically significant associations for any of the other candidate medications, with ever use ORs ranging from 0.93 (95% CI: 0.78, 1.11) for azithromycin to 1.16 (95% CI: 0.99, 1.37) for verapamil.

CONCLUSIONS

In this instance, our combined connectivity mapping and pharmacoepidemiological approach did not identify any additional medications that were substantially associated with breast cancer risk. This could be due to limitations in the connectivity mapping, such as implausible dosage requirements, or the pharmacoepidemiology, such as residual confounding.

Toll-Like Receptor-4 Signaling Drives Persistent Fibroblast Activation and Prevents Fibrosis Resolution in Scleroderma

Significance: This review provides current overview of the emerging role of innate immunity in driving fibrosis, and preventing its resolution, in scleroderma (systemic sclerosis, SSc). Understanding the mechanisms of dysregulated innate immunity in fibrosis and SSc will provide opportunities for therapeutic interventions using novel agents and repurposed existing drugs. Recent Advances: New insights from genomic and genetic studies implicate components of innate immune signaling such as pattern recognition receptors (PRRs), downstream signaling intermediates, and endogenous inhibitors, in fibrosis in SSc. Recent studies distinguish innate immune signaling in tissue-resident myofibroblasts and bone marrow-derived immune cells and define their roles in the development and persistence of tissue fibrosis. Critical Issues: Activation of toll-like receptors (TLRs) and other PRR mechanisms occurs in resident nonimmune cells within injured tissue microenvironments. These cells respond to damage-associated molecular patterns (DAMPs), such as tenascin-C that are recognized as danger signals, and elicit matrix production, cytokine secretion, and myofibroblast transformation and survival. When these responses persist due to constitutive TLR activation or impaired termination by endogenous inhibitors, they interfere with fibrosis resolution. The genetic basis and molecular mechanisms of these phenomena in the context of fibrosis are under current investigation. Future Directions: Precise delineation of the pathogenic DAMPs, their interaction with TLRs and other PRRs, the downstream signaling pathways and transcriptional events, and the fibroblast-specific regulation and function of endogenous inhibitors of innate immunity, will form the foundation for innovative targeted therapies to block fibrosis by reestablishing balanced innate immune signaling in fibroblasts.

Limiting inflammation-the negative regulation of NF-κB and the NLRP3 inflammasome

A properly mounted immune response is indispensable for recognizing and eliminating danger arising from foreign invaders and tissue trauma. However, the 'inflammatory fire' kindled by the host response must be tightly controlled to prevent it from spreading and causing irreparable damage. Accordingly, acute inflammation is self-limiting and is normally attenuated after elimination of noxious stimuli, restoration of homeostasis and initiation of tissue repair. However, unresolved inflammation may lead to the development of chronic autoimmune and degenerative diseases and cancer. Here, we discuss the key molecular mechanisms that contribute to the self-limiting nature of inflammatory signaling, with emphasis on the negative regulation of the NF-κB pathway and the NLRP3 inflammasome. Understanding these negative regulatory mechanisms should facilitate the development of much-needed therapeutic strategies for treatment of inflammatory and autoimmune pathologies.

Radiation protective effects of baclofen predicted by a computational drug repurposing strategy

Exposure to ionizing radiation causes damage to living tissues; however, only a small number of agents have been approved for use in radiation injuries. Radioprotector is the primary countermeasure to radiation injury and none radioprotector has indeed reached the drug development stage. Repurposing the long list of approved, non-radioprotective drugs is an attractive strategy to find new radioprotective agents. Here, we applied a computational approach to discover new radioprotectors in silico by comparing publicly available gene expression data of ionizing radiation-treated samples from the Gene Expression Omnibus (GEO) database with gene expression signatures of more than 1309 small-molecule compounds from the Connectivity Map (cmap) dataset. Among the best compounds predicted to be therapeutic for ionizing radiation damage by this approach were some previously reported radioprotectors and baclofen (P<0.01), a chemical that was not previously used as radioprotector. Validation using a cell-based model and a rodent in vivo model demonstrated that treatment with baclofen reduced radiation-induced cytotoxicity in vitro (P<0.01), attenuated bone marrow damage and increased survival in vivo (P<0.05). These findings suggest that baclofen might serve as a radioprotector. The drug repurposing strategy by connecting the GEO data and cmap can be used to identify known drugs as potential radioprotective agents.