A Review of Cyanophage-Host Relationships: Highlighting Cyanophages as a Potential Cyanobacteria Control Strategy.

Harmful algal blooms (HABs) are naturally occurring phenomena, and cyanobacteria are the most commonly occurring HABs in freshwater systems. Cyanobacteria HABs (cyanoHABs) negatively affect ecosystems and drinking water resources through the production of potent toxins. Furthermore, the frequency, duration, and distribution of cyanoHABs are increasing, and conditions that favor cyanobacteria growth are predicted to increase in the coming years. Current methods for mitigating cyanoHABs are generally short-lived and resource-intensive, and have negative impacts on non-target species. Cyanophages (viruses that specifically target cyanobacteria) have the potential to provide a highly specific control strategy with minimal impacts on non-target species and propagation in the environment. A detailed review (primarily up to 2020) of cyanophage lifecycle, diversity, and factors influencing infectivity is provided in this paper, along with a discussion of cyanophage and host cyanobacteria relationships for seven prominent cyanoHAB-forming genera in North America, including: Synechococcus, Microcystis, Dolichospermum, Aphanizomenon, Cylindrospermopsis, Planktothrix, and Lyngbya. Lastly, factors affecting the potential application of cyanophages as a cyanoHAB control strategy are discussed, including efficacy considerations, optimization, and scalability for large-scale applications.

Prevention through design: insights from computational fluid dynamics modeling to predict exposure to ultrafine particles from 3D printing.

Fused filament fabrication (FFF) 3D printers are increasingly used in industrial, academic, military, and residential sectors, yet their emissions and associated user exposure scenarios are not fully described. Characterization of potential user exposure and environmental releases requires robust investigation. During operation, common FFF 3D printers emit varying amounts of ultrafine particles (UFPs) depending upon feedstock material and operation procedures. Volatile organic compounds associated with these emissions exhibit distinct odors; however, the UFP portion is largely imperceptible by humans. This investigation presents straightforward computational modeling as well as experimental validation to provide actionable insights for the proactive design of lower exposure spaces where 3D printers may be used. Specifically, data suggest that forced clean airflows may create lower exposure spaces, and that computational modeling might be employed to predict these spaces with reasonable accuracy to assist with room design. The configuration and positioning of room air ventilation diffusers may be a key factor in identifying lower exposure spaces. A workflow of measuring emissions during a printing process in an ANSI/CAN/UL 2904 environmental chamber was used to provide data for computational fluid dynamics (CFD) modeling of a 6 m2 room. Measurements of the particle concentrations in a Class 1000 clean room of identical geometry were found to pass the Hanna test for agreement between model and experimental data, validating the findings.

AOPERA: A proposed methodology and inventory of effective tools to link chemicals to adverse outcome pathways.

New approaches, like the Adverse Outcome Pathway (AOP) framework, have been developed to describe how chemicals cause toxicity by linking in vitro assays to adverse health outcomes. However, approaches, tools and resources for development of AOPs have not been well described. Here we review information resources for AOP development and define a streamlined process for linking a chemical to an existing AOP. We propose a four step process to facilitate AOP development: link the uncharacterized chemical directly to Molecular Initiating Events, Key Events, or Adverse Outcomes; identify analogs with toxicological information for the uncharacterized chemical; link the characterized chemical (initial chemical if characterized, a characterized analog if initial chemical is not) to Molecular Initiating Events, Key Events, or Adverse Outcomes; and identify AOPs that contain the Molecular Initiating Events, Key Events, or Adverse Outcomes that were found in Steps 1 and 3. The process and library of informational resources proposed and tested here served as the foundation for an informational online tool (AOPERA) that helps practitioners identify their current-state knowledge gaps, navigate the four-step process, and connect to relevant resources. AOPERA can be found at https://igbb.github.io/AOPERA_HTML. Additionally, we anticipate that by simplifying and standardizing the process of linking a chemical to a known AOP, we will lower the barrier to entry for this objective and increase its accessibility to new practitioners. In turn, this may increase the demand for new or improved AOPs to which practitioners can link chemicals, thereby contributing to the expansion of the library of known AOPs.

A quantitative risk assessment method for synthetic biology products in the environment.

The need to prevent possible adverse environmental health impacts resulting from synthetic biology (SynBio) products is widely acknowledged in both the SynBio risk literature and the global regulatory community. To-date, however, discussions of potential risks of SynBio products have been largely speculative, and the limited attempts to characterize the risks of SynBio products have been non-uniform and entirely qualitative. As the SynBio discipline continues to accelerate and bring forth novel, highly-engineered life forms, a standardized risk assessment framework will become critical for ensuring that the environmental risks of these products are characterized in a consistent, reliable, and objective manner that incorporates all SynBio-unique risk factors. In their current forms, established risk assessment frameworks - including those that address traditional genetically modified organisms - fall short of the features required of this standard framework. To address this gap, we propose the Quantitative Risk Assessment Method for Synthetic Biology Products (QRA-SynBio) - an incremental build on established risk assessment methodologies that supplements traditional paradigms with the SynBio risk factors that are currently absent, and necessitates quantitative analysis for more transparent and objective risk characterizations. We demonstrate through a hypothetical case study that the proposed framework facilitates defensible quantification of the environmental risks of SynBio products in both foreseeable and hypothetical use scenarios. Additionally, we show how the quantitative nature of the proposed method can promote increased experimental investigation into the true likelihood of hazard and exposure parameters and highlight the most sensitive parameters where uncertainty should be reduced, ultimately leading to more targeted SynBio risk research and yielding more precise characterizations of risk.

Assessing the sustainability of advanced materials using multicriteria decision analysis and the triple bottom line.

Although advanced materials (AdMs) are beneficial in many applications, questions remain as to whether they are more or less sustainable than the conventional materials that they may replace. Currently, there is no available tool to provide clarity to these questions. Traditional approaches for evaluating the sustainability of a chemical or material are usually not standardized, and as a result, the metrics used in sustainability measurements are subjective and often vary from assessor to assessor. Additionally, sustainability characterizations resulting from these approaches are typically presented qualitatively and are often vaguely drawn, making it difficult to confidently and transparently conclude that 1 material is more sustainable than another. This paper aims to address these gaps by enabling stakeholders involved in the production, use, or governance of AdMs to assess the sustainability of AdMs in a consistent, objective, and quantitative way using a multicriteria decision analysis (MCDA)-based model. The model proposed herein adapts a triple-bottom-line (TBL) framework from the Institution of Chemical Engineers (IChemE) and incorporates criteria weights identified through a stakeholder values assessment conducted by surveying AdM practitioners. Results from the stakeholder values assessment show that the perceived importance of the economic component of the TBL varies the most across stakeholders, and that practitioners providing responses from the perspective of a nongovernmental environmental advocacy group or a regulator of AdMs such as the United States Environmental Protection Agency were more likely to score and weigh economic indicators lower and environmental indicators higher compared to when responding from a business owner perspective. The resulting MCDA-based model allows stakeholders to assess the sustainability of an AdM or AdM-enabled product and compare it to product alternatives, predict how other stakeholders might score a product by identifying the extent to which components of the TBL are valued by other stakeholders, and identify which subcriteria contribute most to an improvement in a product's sustainability score. Integr Environ Assess Manag 2019;00:1-8. © 2019 SETAC.

A Definition and Categorization System for Advanced Materials: The Foundation for Risk-Informed Environmental Health and Safety Testing.

Novel materials with unique or enhanced properties relative to conventional materials are being developed at an increasing rate. These materials are often referred to as advanced materials (AdMs) and they enable technological innovations that can benefit society. Despite their benefits, however, the unique characteristics of many AdMs, including many nanomaterials, are poorly understood and may pose environmental safety and occupational health (ESOH) risks that are not readily determined by traditional risk assessment methods. To assess these risks while keeping up with the pace of development, technology developers and risk assessors frequently employ risk-screening methods that depend on a clear definition for the materials that are to be assessed (e.g., engineered nanomaterial) as well as a method for binning materials into categories for ESOH risk prioritization. The term advanced material lacks a consensus definition and associated categorization or grouping system for risk screening. In this study, we aim to establish a practitioner-driven definition for AdMs and a practitioner-validated framework for categorizing AdMs into conceptual groupings based on material characteristics. Results from multiple workshops and interviews with practitioners provide consistent differentiation between AdMs and conventional materials, offer functional nomenclature for application science, and provide utility for future ESOH risk assessment prioritization. The definition and categorization framework established here serve as a first step in determining if and when there is a need for specific ESOH and regulatory screening for an AdM as well as the type and extent of risk-related information that should be collected or generated for AdMs and AdM-enabled technologies.

Co-evolution of physical and social sciences in synthetic biology.

Emerging technologies research often covers various perspectives in disciplines and research areas ranging from hard sciences, engineering, policymaking, and sociology. However, the interrelationship between these different disciplinary domains, particularly the physical and social sciences, often occurs many years after a technology has matured and moved towards commercialization. Synthetic biology may serve an exception to this idea, where, since 2000, the physical and the social sciences communities have increasingly framed their research in response to various perspectives in biological engineering, risk assessment needs, governance challenges, and the social implications that the technology may incur. This paper reviews a broad collection of synthetic biology literature from 2000-2016, and demonstrates how the co-development of physical and social science communities has grown throughout synthetic biology's earliest stages of development. Further, this paper indicates that future co-development of synthetic biology scholarship will assist with significant challenges of the technology's risk assessment, governance, and public engagement needs, where an interdisciplinary approach is necessary to foster sustainable, risk-informed, and societally beneficial technological advances moving forward.

A modular approach for assembly of quantitative adverse outcome pathways.

The adverse outcome pathway (AOP) framework is a conceptual construct that mechanistically links molecular initiating events to adverse biological outcomes through a series of causal key events (KEs) that represent the perturbation of the biological system. Quantitative, predictive AOPs are necessary for screening emerging contaminants and potential substitutes to inform their prioritization for testing. In practice, they are not widely used because they can be costly to develop and validate. A modular approach for assembly of quantitative AOPs, based on existing knowledge, would allow for rapid development of biological pathway models to screen contaminants for potential hazards and prioritize them for subsequent testing and modeling. For each pair of KEs, a quantitative KE relationship (KER) can be derived as a response-response function or a conditional probability matrix describing the anticipated change in a KE based on the response of the prior KE. This transfer of response across KERs can be used to assemble a quantitative AOP. Here we demonstrate the use of proposed approach in two cases: inhibition of cytochrome P450 aromatase leading to reduced fecundity in fathead minnows and ionic glutamate receptor mediated excitotoxicity leading to memory impairment in rodents. The model created from these chains have value in characterizing the pathway and the potential or relative level of toxicological effect anticipated. This approach to simplistic, modular AOP models has wide applicability for rapid development of biological pathway models.

Risks from Ebolavirus Discharge from Hospitals to Sewer Workers.

Current World Health Organization and Centers for Disease Control and Prevention guidance for the disposal of liquid waste from patients undergoing treatment for Ebola virus disease at hospitals in the U.S. is to manage patient excreta as ordinary wastewater without pretreatment. The potential for Ebolavirus transmission via liquid waste discharged into the wastewater environment is currently unknown, however. Possible worker inhalation exposure to Ebolavirus-contaminated aerosols in the sewer continues to be a concern within the wastewater treatment community. In this study, a quantitative microbial risk assessment was carried out to assess a sewer worker's potential risk of developing Ebola virus disease from inhalation exposure when performing standard occupational activities in a sewer line serving a hospital receiving Ebola patients where there is no pretreatment of the waste prior to discharge. Risk projections were estimated for four scenarios that considered the infectivity of viral particles and the degree of worker compliance with personal protective equipment guidelines. Under the least-favorable scenario, the median potential risk of developing Ebola virus disease from inhalation exposure to Ebolavirus-contaminated aerosols in the sewer is approximately 10-5.77 (with a first to third quartile range of 10-7.06 to 10-4.65), a value higher than many risk managers may be willing to accept. Although further data gathering efforts are necessary to improve the precision of the risk projections presented here, the results suggest that the potential risk that sewer workers face when operating in a wastewater collection system downstream from a hospital receiving Ebola patients warrants further attention, and that current authoritative guidance for Ebolavirus liquid waste disposal-to dispose in the sanitary sewer without further treatment-may be insufficiently protective of sewer worker safety.