GreenLight Biosciences (United States)

Double-stranded RNA (dsRNA)-based biopesticides are a promising new method of pest management. These biopesticides leverage the endogenous RNA interference pathway to selectively regulate expression of key genes involved in growth and development in pests, providing the potential to minimize harmful environmental effects by highly specific targeting. As dsRNA-based biopesticides are presented for regulatory review, evaluating potential off-target effects on nontarget organisms (NTOs) in a manner that may be unique to this novel sequence-specific mode of action is crucial. To address this, we propose here a bioinformatics framework for consideration of sequence-specific off-target effects in NTOs. This framework includes careful consideration of NTOs based on potential exposure and susceptibility and recommends standardizing analyses to search for 21-nucleotide stretches of perfect identity and 80% overall identity between the dsRNA and off-target transcripts. We recommend a three-pronged approach to ensure a comprehensive risk assessment: (a) phylogenetic analysis of gene orthologs that defines the taxonomic scope of sequence similarity, (b) broad searches of large databases to identify potential unexpected similarity in distantly related species, and (c) full transcriptome analyses in NTO species of particular concern for a thorough understanding of all potential hazards. Finally, we recommend considering the results of bioinformatic analyses in the context of risk characterization, which means considering likely exposure to the dsRNA-based pesticide and potential susceptibility or barriers to dsRNA uptake. This approach enables a robust ecological risk assessment for dsRNA-based biopesticides and a regulatory path forward for this promising new pest management tool.

mRNA technology has widely incorporated modified nucleotides to temper innate immune activation by foreign RNA and achieve high levels of heterologous protein expression. However, the incorporation of modified nucleotides has had limited application to self-amplifying (sa) RNAs, as it impeded heterologous protein expression. Here, we used a reporter replicon of the attenuated TC-83 strain of Venezuelan equine encephalitis virus (VEEV) to investigate the impact of modified nucleotide incorporation on the replication capacity of the saRNA in transfected cells. ψ and m1ψ-modified molecules exhibited a profound defect in RNA synthesis compared to unmodified saRNA. Interestingly, the RNA synthesis levels of m5C-modified RNAs were similar to unmodified molecules, positioning m5C as a promising candidate for saRNA modification. Moreover, we found that saRNAs carrying mutations associated with resistance to nucleotide analog polymerase inhibitors partially overcame the negative impact of m1ψ-modified nucleotide incorporation on RNA synthesis. Overall, we uncovered a previously unappreciated link between polymerase fidelity and saRNA amplification.

The University of Oklahoma, Oklahoma State University, the US National Severe Storms Lab, and various US National Weather Service Forecast Offices have been actively engaged in enhancing the capabilities and applications of a 3D Mesonet system. This presentation will overview the extensive activities and advancements in Mesonet operations, focusing on the integration of uncrewed aircraft systems (UAS) for atmospheric profiling. The Oklahoma Mesonet system, comprised of 120 surface stations across the state, plays a crucial foundational role in real-time weather monitoring and data collection.Through numerous experiments and field campaigns since 2014, we have deployed UAS for high-resolution vertical measurements of atmospheric parameters such as pressure, temperature, humidity, wind speed, and direction. These measurements are key for understanding the atmospheric boundary layer (ABL) and improving weather forecasting, agricultural decision-making, wildland fire management, wind energy optimization, and climate monitoring. Additionally, 3D Mesonet data have shown great promise in nowcasting, particularly in identifying low-level inversions that impact pesticide application and predicting fire behavior and smoke dispersal.The integration of UAS with Mesonet infrastructure will allow for simultaneous data collection at multiple sites, providing new insights into the spatial heterogeneity of the ABL. This presentation will also discusses ongoing projects, including an initiative with WeatherHive and collaborations with the US National Weather Service (NWS) to enhance severe weather forecasting through real-time data ingest and analysis.Furthermore, this presentation will highlight the need to develop robust and reliable UAV systems equipped with precision landing, automatic charging, and risk mitigation measures for unattended operations. A prototype built by the Advanced Radar Research Center at the University of Oklahoma demonstrated the capability to detect aircraft within a geofenced area, ensuring safe and efficient data collection.Overall, the advancements in 3D Mesonet technology and its applications underscore the importance of continuous innovation in atmospheric research and its practical implications for various sectors.

Annually, seasonal influenza is responsible for millions of infections and hundreds of thousands of deaths. The current method for managing influenza is vaccination using a standardized amount of the influenza virus’ primary surface antigen, hemagglutinin (HA), as the intended target of the immune response. This vaccination strategy results in vaccines with variable efficacy year to year due to antigenic drift of HA, which can be further exacerbated by manufacturing processes optimizing growth of vaccine virus in eggs. Due to these limitations, alternative vaccine platforms are actively being explored to improve influenza vaccine efficacy, including cell-based, recombinant protein, and mRNA vaccines. mRNA’s rapid, in vitro production makes it an appealing platform for influenza vaccination, and the success of SARS-CoV-2 mRNA vaccines in the clinic has encouraged the development of mRNA vaccines for other pathogens. Here, the immunogenicity and protective efficacy of a quadrivalent mRNA vaccine encoding HA from four seasonal influenza viruses, A/California/07/2009 (H1N1), A/Hong Kong/4801/2014 (H3N2), B/Brisbane/60/2008 (B-Victoria lineage), and B/Phuket/3073/2013 (B-Yamagata lineage), was evaluated. In mice, a 120 μg total dose of this quadrivalent mRNA vaccine induced robust antibody titers against each subtype that were commensurate with titers when each antigen was administered alone. Following A/California/04/2009 challenge, mice were fully protected from morbidity and mortality, even at doses as low as 1 μg of each antigen. Additionally, a single administration of 10 μg of quadrivalent mRNA was sufficient to prevent weight loss caused by A/California/04/2009. These results support the promise of this mRNA vaccine for prevention and mitigation of influenza vaccine.

SummaryCombination monoclonal broadly neutralizing antibody (bnAb) regimens are in clinical development for HIV prevention, necessitating additional knowledge of bnAb neutralization potency/breadth against circulating viruses. Williamson et al. (2021) described a software tool, Super LeArner Prediction of NAb Panels (SLAPNAP), with application to any HIV bnAb regimen with sufficient neutralization data against a set of viruses in the Los Alamos National Laboratory’s Compile, Neutralize, and Tally Nab Panels repository. SLAPNAP produces a proteomic antibody resistance (PAR) score for Env sequences based on predicted neutralization resistance and estimates variable importance of Env amino acid features. We apply SLAPNAP to compare HIV bnAb regimens undergoing clinical testing, finding improved power for downstream sieve analyses and increased precision for comparing neutralization potency/breadth of bnAb regimens due to the inclusion of PAR scores of Env sequences with much larger sample sizes available than for neutralization outcomes. SLAPNAP substantially improves bnAb regimen characterization, ranking, and down-selection.

EDITORIAL article Front. Agron., 27 May 2022Sec. Pest Management https://doi.org/10.3389/fagro.2022.903841

Simple SummaryThe western corn rootworm (WCR), Diabrotica virgifera virgifera LeConte, is an annual pest of maize in the United States Corn Belt. Larval feeding on the root system can promote significant yield loss through reduced water and nutrient uptake and decreased plant stability. Various management tactics, including crop rotation, insecticides, and transgenic crops expressing Bacillus thuringiensis Berliner proteins, have been used to manage WCR densities. However, resistance has evolved to each of these tactics in local areas, highlighting the need for new management strategies. The use of RNA interference (RNAi) technology for WCR management represents the next phase of species-specific pest management. This paper reviews the current knowledge of RNAi for WCR management. We present an overview of traits that have been explored and the accumulated knowledge acquired on mode of action, resistance, ecological risk assessment, and mammalian safety. We conclude by highlighting the challenges and future directions of this technology for WCR management.The western corn rootworm (WCR), Diabrotica virgifera virgifera LeConte, is considered one of the most economically important pests of maize (Zea mays L.) in the United States (U.S.) Corn Belt with costs of management and yield losses exceeding USD ~1–2 billion annually. WCR management has proven challenging given the ability of this insect to evolve resistance to multiple management strategies including synthetic insecticides, cultural practices, and plant-incorporated protectants, generating a constant need to develop new management tools. One of the most recent developments is maize expressing double-stranded hairpin RNA structures targeting housekeeping genes, which triggers an RNA interference (RNAi) response and eventually leads to insect death. Following the first description of in planta RNAi in 2007, traits targeting multiple genes have been explored. In June 2017, the U.S. Environmental Protection Agency approved the first in planta RNAi product against insects for commercial use. This product expresses a dsRNA targeting the WCR snf7 gene in combination with Bt proteins (Cry3Bb1 and Cry34Ab1/Cry35Ab1) to improve trait durability and will be introduced for commercial use in 2022.

Historically, genetically engineered (GE) plants that have incorporated genes conferring insect protection have primarily used Cry proteins derived from Bacillus thuringiensis (Bt) to achieve their insecticidal phenotype. As a result, regulators have developed a level of familiarity and confidence in reviewing plants incorporating these insecticidal proteins. However, new technologies have been developed that produce GE plants that incorporate pest protection by triggering an RNA interference (RNAi) response or proteins other than Bt Cry proteins. These technologies have new modes of action. Although the overall assessment paradigm for GE plants is robust, there are ongoing discussions about the appropriate tests and measurement endpoints needed to inform non-target arthropod assessment for technologies that have a different mode of action than the Bt Cry proteins. As a result, increasing attention is being paid to the use of sublethal endpoints and their value for environmental risk assessment (ERA). This review focuses on the current status and history of sublethal endpoint use in insect-active GE crops, and evaluates the future use of sublethal endpoints for new and emerging technologies. It builds upon presentations made at the Workshop on Sublethal Endpoints for Non-target Organism Testing for Non-Bt GE Crops (Washington DC, USA, 4–5 March 2019), and the discussions of government, academic and industry scientists convened for the purpose of reviewing the progress and status of sublethal endpoint testing in non-target organisms.