Developing the Arsenal Against Pest and Vector Dipterans: Inputs of Transgenic and Paratransgenic Biotechnologies

Insects are the most numerous of all animals and are found in almost every inhabitable place on earth. The order Diptera (true flies) contains many members that are notorious agricultural pests, nuisance or vectors of diseases. The list is long: mosquitoes, tsetse flies, screw worms, fruit flies, sand flies, blow flies, house flies, gall and biting midges, black flies, leaf miners, horse flies, and so on. Efforts to combat some of these pests and vectors have resulted in control measures such as the chemical, physical, and cultural control methods. These methods, though largely beneficial, have disadvantages and limitations, which sometimes seem to outweigh the problems initially sought to be controlled. The chemical method, for example, is not environment-friendly since it negatively affects many nontarget organisms and disrupts ecosystem balance. Development of insecticide resistance by pests/vectors is another concern. Molecular biotechnology has introduced vast arrays of novel ways to tackle pests and disease vectors, as well as improve the potency of existing control methods. This chapter looks at transgenic and paratransgenic biotechnologies and how they have been applied so far to develop and expand the arsenal against dipteran pests and disease vectors. Further, we discuss the advantages, disadvantages, and limitations of these technologies

Modeling horizontal gene transfer (HGT) in the gut of the Chagas disease vector Rhodnius prolixus

<p>Abstract</p> <p>Background</p> <p>Paratransgenesis is an approach to reducing arthropod vector competence using genetically modified symbionts. When applied to control of Chagas disease, the symbiont bacterium <it>Rhodococcus rhodnii</it>, resident in the gut lumen of the triatomine vector <it>Rhodnius prolixus </it>(Hemiptera: Reduviidae), is transformed to export cecropin A, an insect immune peptide. Cecropin A is active against <it>Trypanosoma cruzi</it>, the causative agent of Chagas disease. While proof of concept has been achieved in laboratory studies, a rigorous and comprehensive risk assessment is required prior to consideration of field release. An important part of this assessment involves estimating probability of transgene horizontal transfer to environmental organisms (HGT). This article presents a two-part risk assessment methodology: a theoretical model predicting HGT in the gut of <it>R. prolixus </it>from the genetically transformed symbiont <it>R. rhodnii </it>to a closely related non-target bacterium, <it>Gordona rubropertinctus</it>, in the absence of selection pressure, and a series of laboratory trials designed to test the model.</p> <p>Results</p> <p>The model predicted an HGT frequency of less than 1.14 × 10^-16per 100,000 generations at the 99% certainty level. The model was iterated twenty times, with the mean of the ten highest outputs evaluated at the 99% certainty level. Laboratory trials indicated no horizontal gene transfer, supporting the conclusions of the model.</p> <p>Conclusions</p> <p>The model treats HGT as a composite event, the probability of which is determined by the joint probability of three independent events: gene transfer through the modalities of transformation, transduction, and conjugation. Genes are represented in matrices and Monte Carlo method and Markov chain analysis are used to simulate and evaluate environmental conditions. The model is intended as a risk assessment instrument and predicts HGT frequency of less than 1.14 × 10^-16per 100,000 generations. With laboratory studies that support the predictions of this model, it may be possible to argue that HGT is a negligible consideration in risk assessment of genetically modified <it>R. rhodnii </it>released for control of Chagas disease.</p

Paratransgenic Control of Vector Borne Diseases

Conventional methodologies to control vector borne diseases with chemical pesticides are often associated with environmental toxicity, adverse effects on human health and the emergence of insect resistance. In the paratransgenic strategy, symbiotic or commensal microbes of host insects are transformed to express gene products that interfere with pathogen transmission. These genetically altered microbes are re-introduced back to the insect where expression of the engineered molecules decreases the host's ability to transmit the pathogen. We have successfully utilized this strategy to reduce carriage rates of Trypanosoma cruzi, the causative agent of Chagas disease, in the triatomine bug, Rhodnius prolixus, and are currently developing this methodology to control the transmission of Leishmania donovani by the sand fly Phlebotomus argentipes. Several effector molecules, including antimicrobial peptides and highly specific single chain antibodies, are currently being explored for their anti-parasite activities in these two systems. In preparation for eventual field use, we are actively engaged in risk assessment studies addressing the issue of horizontal gene transfer from the modified bacteria to environmental microbes

Repurposing Lansoprazole and Posaconazole to treat Leishmaniasis: Integration of in vitro Testing, Pharmacological Corroboration, and Mechanisms of Action

Leishmaniasis remains a serious public health problem in many tropical regions of the world. Among neglected tropical diseases, the mortality rate of leishmaniasis is second only to malaria. All currently approved therapeutics have toxic side effects and face rapidly increasing resistance. To identify existing drugs with antileishmanial activity and predict the mechanism of action, we designed a drug-discovery pipeline utilizing both in-silico and in-vitro methods. First, we screened compounds from the Selleckchem Bio-Active Compound Library containing ~1622 FDA-approved drugs and narrowed these down to 96 candidates based on data mining for possible anti-parasitic properties. Next, we completed preliminary in-vitro testing of compounds against Leishmania amastigotes and selected the most promising active compounds, Lansoprazole and Posaconazole. We identified possible Leishmania drug targets of Lansoprazole and Posaconazole using several available servers. Our in-silico screen identified likely Lansoprazole targets as the closely related calcium-transporting ATPases (LdBPK_352080.1, LdBPK_040010.1, and LdBPK_170660.1), and the Posaconazole target as lanosterol 14-alpha-demethylase (LdBPK_111100.1). Further validation showed LdBPK_352080.1 to be the most plausible target based on induced-fit docking followed by long (100ns) MD simulations to confirm the stability of the docked complexes. We present a likely ion channel-based mechanism of action of Lansoprazole against Leishmania calcium-transporting ATPases, which are essential for parasite metabolism and infectivity. The LdBPK_111100.1 interaction with Posaconazole is very similar to the known fungal orthologue. Herein, we present two novel anti-leishmanial agents, Posaconazole and Lansoprazole, already approved by the FDA for different indications and propose plausible mechanisms of action for their antileishmanial activity

In Silico Binding of 2-Aminocyclobutanones to SARS-CoV-2 Nsp13 Helicase and Demonstration of Antiviral Activity

The landscape of viral strains and lineages of SARS-CoV-2 keeps changing and is currently dominated by Delta and Omicron variants. Members of the latest Omicron variants, including BA.1, are showing a high level of immune evasion, and Omicron has become a prominent variant circulating globally. In our search for versatile medicinal chemistry scaffolds, we prepared a library of substituted α-aminocyclobutanones from an α-aminocyclobutanone synthon (11). We performed an in silico screen of this actual chemical library as well as other virtual 2-aminocyclobutanone analogs against seven SARS-CoV-2 nonstructural proteins to identify potential drug leads against SARS-CoV-2, and more broadly against coronavirus antiviral targets. Several of these analogs were initially identified as in silico hits against SARS-CoV-2 nonstructural protein 13 (Nsp13) helicase through molecular docking and dynamics simulations. Antiviral activity of the original hits as well as α-aminocyclobutanone analogs that were predicted to bind more tightly to SARS-CoV-2 Nsp13 helicase are reported. We now report cyclobutanone derivatives that exhibit anti-SARS-CoV-2 activity. Furthermore, the Nsp13 helicase enzyme has been the target of relatively few target-based drug discovery efforts, in part due to a very late release of a high-resolution structure accompanied by a limited understanding of its protein biochemistry. In general, antiviral agents initially efficacious against wild-type SARS-CoV-2 strains have lower activities against variants due to heavy viral loads and greater turnover rates, but the inhibitors we are reporting have higher activities against the later variants than the wild-type (10–20X). We speculate this could be due to Nsp13 helicase being a critical bottleneck in faster replication rates of the new variants, so targeting this enzyme affects these variants to an even greater extent. This work calls attention to cyclobutanones as a useful medicinal chemistry scaffold, and the need for additional focus on the discovery of Nsp13 helicase inhibitors to combat the aggressive and immune-evading variants of concern (VOCs)

A Review of the Preclinical and Clinical Efficacy of Remdesivir, Hydroxychloroquine, and Lopinavir-Ritonavir Treatments against COVID-19

In December of 2019, an outbreak of a novel coronavirus flared in Wuhan, the capital city of the Hubei Province, China. The pathogen has been identified as a novel enveloped RNA beta-coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The virus SARS-CoV-2 is associated with a disease characterized by severe atypical pneumonia known as coronavirus 2019 (COVID-19). Typical symptoms of this disease include cough, fever, malaise, shortness of breath, gastrointestinal symptoms, anosmia, and, in severe cases, pneumonia.1 The high-risk group of COVID-19 patients includes people over the age of 60 years as well as people with existing cardiovascular disease and/or diabetes mellitus. Epidemiological investigations have suggested that the outbreak was associated with a live animal market in Wuhan. Within the first few months of the outbreak, cases were growing exponentially all over the world. The unabated spread of this deadly and highly infectious virus is a health emergency for all nations in the world and has led to the World Health Organization (WHO) declaring a pandemic on March 11, 2020. In this report, we consolidate and review the available clinically and preclinically relevant results emanating from in vitro animal models and clinical studies of drugs approved for emergency use as a treatment for COVID-19, including remdesivir, hydroxychloroquine, and lopinavir-ritonavir combinations. These compounds have been frequently touted as top candidates to treat COVID-19, but recent clinical reports suggest mixed outcomes on their efficacies within the current clinical protocol frameworks

Bisindolylmaleimide IX: a Novel Anti-SARS-CoV2 Agent Targeting Viral Main Protease 3CLpro Demonstrated by Virtual Screening Pipeline and In-Vitro Validation Assays

SARS-CoV-2, the virus that causes COVID-19 consists of several enzymes with essential functions within its proteome. Here, we focused on repurposing approved and investigational drugs/compounds. We targeted seven proteins with enzymatic activities known to be essential at different stages of the viral cycle including PLpro, 3CLpro, RdRP, Helicase, ExoN, NendoU, and 2′-O-MT. For virtual screening, energy minimization of a crystal structure of the modeled protein was carried out using the Protein Preparation Wizard (Schrodinger LLC 2020-1). Following active site selection based on data mining and COACH predictions, we performed a high-throughput virtual screen of drugs and investigational molecules (n = 5903). The screening was performed against viral targets using three sequential docking modes (i.e., HTVS, SP, and XP). Virtual screening identified ∼290 potential inhibitors based on the criteria of energy, docking parameters, ligand, and binding site strain and score. Drugs specific to each target protein were further analyzed for binding free energy perturbation by molecular mechanics (prime MM-GBSA) and pruning the hits to the top 32 candidates. The top lead from each target pool was further subjected to molecular dynamics simulation using the Desmond module. The resulting top eight hits were tested for their SARS-CoV-2 anti-viral activity in-vitro. Among these, a known inhibitor of protein kinase C isoforms, Bisindolylmaleimide IX (BIM IX), was found to be a potent inhibitor of SARS-CoV-2. Further, target validation through enzymatic assays confirmed 3CLpro to be the target. This is the first study that has showcased BIM IX as a COVID-19 inhibitor thereby validating our pipeline

Assessing the dynamics and complexity of disease pathogenicity using 4-dimensional immunological data

Investigating disease pathogenesis and personalized prognostics are major biomedical needs. Because patients sharing the same diagnosis can experience different outcomes, such as survival or death, physicians need new personalized tools, including those that rapidly differentiate several inflammatory phases. To address these topics, a pattern recognition-based method (PRM) that follows an inverse problem approach was designed to assess, in <10min, eight concepts: synergy, pleiotropy, complexity, dynamics, ambiguity, circularity, personalized outcomes, and explanatory prognostics (pathogenesis). By creating thousands of secondary combinations derived from blood leukocyte data, the PRM measures synergic, pleiotropic, complex and dynamic data interactions, which provide personalized prognostics while some undesirable features—such as false results and the ambiguity associated with data circularity-are prevented. Here, this method is compared to Principal Component Analysis (PCA) and evaluated with data collected from hantavirus-infected humans and birds that appeared to be healthy. When human data were examined, the PRM predicted 96.9 % of all surviving patients while PCA did not distinguish outcomes. Demonstrating applications in personalized prognosis, eight PRM data structures sufficed to identify all but one of the survivors. Dynamic data patterns also distinguished survivors from non-survivors, as well as one subset of non-survivors, which exhibited chronic inflammation. When the PRM explored avian data, it differentiated immune profiles consistent with no, early, or late inflammation. Yet, PCA did not recognize patterns in avian data. Findings support the notion that immune responses, while variable, are rather deterministic: a low number of complex and dynamic data combinations may be enough to, rapidly, unmask conditions that are neither directly observable nor reliably forecasted.Conacyt of Mexico (Consejo Nacional de Ciencia y Tecnologíahttp://www.frontiersin.org/Immunologyam2020Veterinary Tropical Disease