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Purpose of Review Mounting evidence indicates that habitats such as wastewater and environmental waters are pathways for the spread of antibiotic-resistant bacteria (ARB) and mobile antibiotic resistance genes (ARGs). We identified antibiotic-resistant members of the genera Acinetobacter, Aeromonas, and Pseudomonas as key opportunistic pathogens that grow or persist in built (e.g., wastewater) or natural aquatic environments. Effective methods for monitoring these ARB in the environment are needed to understand their influence on dissemination of ARB and ARGs, but standard methods have not been developed. This systematic review considers peer-reviewed papers where the ARB above were cultured from wastewater or surface water, focusing on the accuracy of current methodologies. Recent Findings Recent studies suggest that many clinically important ARGs were originally acquired from environmental microorganisms. Acinetobacter, Aeromonas, and Pseudomonas species are of interest because their ability to persist and grow in the environment provides opportunities to engage in horizontal gene transfer with other environmental bacteria. Pathogenic strains of these organisms resistant to multiple, clinically relevant drug classes have been identified as an urgent threat. However, culture methods for these bacteria were generally developed for clinical samples and are not well-vetted for environmental samples. Summary The search criteria yielded 60 peer-reviewed articles over the past 20 years, which reported a wide variety of methods for isolation, confirmation, and antibiotic resistance assays. Based on a systematic comparison of the reported methods, we suggest a path forward for standardizing methodologies for monitoring antibiotic resistant strains of these bacteria in water environments.

Shotgun metagenomic sequencing of the collective genomic information carried across microbial communities is emerging as a powerful approach for monitoring antibiotic resistance in environmental matrices. Metagenomics is advantageous in that known and putative antibiotic resistance genes (ARGs) (i.e., the resistome) can be screened simultaneously without a priori selection of targets. Additionally, as new ARGs are discovered and catalogued, stored sequencing data can be reanalyzed to assess the prevalence of emerging genes or pathogens. However, best practices for metagenomic data generation and processing are needed to support comparability across space and time. To support reproducible downstream analysis, guidance is first needed with respect to sampling design, sample preservation and storage, DNA extraction, library preparation, sequencing depth, and experimental controls. Here we conducted a systematic review to assess current practices for the application of metagenomics for AR profiling of wastewater, recycled water, and surface water and to offer recommendations to support comparability in the collection, production, and analysis of resulting data. Based on integrated analysis of findings and data reported across 95 articles identified, a field to benchtop metagenomic workflow is discussed for optimizing the representativeness and comparability of generated data. Through the reanalysis of 1474 publicly-available metagenomes, appropriate sequencing depths per environment and uniform normalization strategies are provided. Further, there is opportunity to harness the quantitative capacity of metagenomics more overtly through inclusion of sequencing controls. The recommendations will amplify the overall value of the metagenomic data generated to support within and between study comparisons, now and in the future.

Water environments are increasingly recognized as a conduit for the spread of antibiotic resistance, but there is need to standardize antibiotic resistance monitoring protocols to ensure comparability across studies. Quantitative polymerase chain reaction (qPCR) is attractive as a sensitive means of quantifying antibiotic resistance genes (ARGs) and has been applied broadly over the past two decades to various water matrices. QPCR avoids challenges and biases associated with culture-based methods, providing a reproducible and highly sensitive measure of ARGs carried across a bacterial community. However, there are numerous quality assurance and other aspects of protocols that need to be addressed to ensure that measurements are representative and comparable across studies. Here we conducted a critical review to identify gene targets that are most commonly measured by qPCR to quantify antibiotic resistance in surface water, recycled water, and wastewater and to assess corresponding protocols. Identified targets monitored in water samples included sul1, tetA, and intI1, given their abundance and tendency to correlate with anthropogenic inputs, and vanA and blaCTX-M, as more rarely detected, but highly clinically-relevant targets. We identified 117 peer-reviewed studies meeting search criteria for application of these assays to water matrices of interest and systematically assessed the corresponding protocols, including sample collection and concentration, DNA extraction, primer/probe specificity, amplification conditions, amplicon length, PCR inhibition evaluation, and limit of detection/quantification. Gene copy numbers reported across studies were further compared by assay and water matrix. Based on this comprehensive evaluation, we recommend assays, standardized workflows, and reporting for the five target genes. This work was supported by the Water Research Foundation (WRF) Project 5052: Standardizing Methods with QA/QC Standards for Investigating the Occurrence and Removal of Antibiotic Resistant Bacteria/Antibiotic Resistance Genes (ARB/ARGs) in Surface Water, Wastewater, and Recycled Water. Support was also provided by National Science Foundation Awards OAC 2004751, OISE 1545756, NRT 2125798, and ECCS 2025151. Published version

Antimicrobial resistance (AMR) is a grand societal challenge with important dimensions in the water environment that contribute to its evolution and spread. Environmental monitoring could provide vital information for mitigating the spread of AMR; this includes assessing antibiotic resistance genes (ARGs) circulating among human populations, identifying key hotspots for evolution and dissemination of resistance, informing epidemiological and human health risk assessment models, and quantifying removal efficiencies by domestic wastewater infrastructure. However, standardized methods for monitoring AMR in the water environment will be vital to producing the comparable data sets needed to address such questions. Here we sought to establish scientific consensus on a framework for such standardization, evaluating the state of the science and practice of AMR monitoring of wastewater, recycled water, and surface water, through a literature review, survey, and workshop leveraging the expertise of academic, governmental, consulting, and water utility professionals. Water Research Foundation [5052]; U.S. National Science Foundation [OIE 1545756, OAC 2004751, CBET 1936319, NRT 2125798] Published version We thank the participants in our expert survey and workshop. Workshop participants included the following: Alison Franklin, Amy Kirby, Andrea Ottesen, Anthea Lee, Ayella Maile-Moskowitz, Bina Nayak, Connor Brown, Daniel Quintanar, Daniel Gerrity, Ed Topp, Emily Garner, Erin Swanson, Gaya Ram Mohan, Jade Mitchell, Jay Garland, Jean McLain, Jeff Soller, Jennifer Jay, Johan Bengtsson-Palme, John Griffith, Jorge Matheu Alvarez, Kara Nelson, Kati Bell, Kerry Hamilton, Kim Cook, Lauren Stadler, Lenwood Heath, Liqing Zhang, Lisa Durso, Mark Borchardt, Mark Ibekwe, Mark LeChevallier, Mark Sobsey, Gertjan Medema, Nicholas Ashbolt, Peter Vikesland, Raul Gonzalez, Satoshi Ishii, Scott Keely, Sharon Nappier, Sunny Jiang, Suraj Gupta, Tanja Rauch-Williams, Thomas Berendonk, Walter Jakubowksi, and Zia Bukhari. Thanks also go to Anna Kurowski for assisting with workshop video transcripts. This contribution was funded by the Water Research Foundation Project 5052. Additional funding was provided by U.S. National Science Foundation Award Nos. OIE 1545756, OAC 2004751, CBET 1936319, and NRT 2125798.

Wastewater treatment plants (WWTPs) receive a confluence of sewage containing antimicrobials, antibiotic resistant bacteria, antibiotic resistance genes (ARGs), and pathogens and thus are a key point of interest for antibiotic resistance surveillance. WWTP monitoring has the potential to inform with respect to the antibiotic resistance status of the community served as well as the potential for ARGs to escape treatment. However, there is lack of agreement regarding suitable sampling frequencies and monitoring targets to facilitate comparison within and among individual WWTPs. The objective of this study was to comprehensively evaluate patterns in metagenomic-derived indicators of antibiotic resistance through various stages of treatment at a conventional WWTP for the purpose of informing local monitoring approaches that are also informative for global comparison. Relative abundance of total ARGs decreased by ∼50% from the influent to the effluent, with each sampling location defined by a unique resistome (i.e., total ARG) composition. However, 90% of the ARGs found in the effluent were also detected in the influent, while the effluent ARG-pathogen taxonomic linkage patterns identified in assembled metagenomes were more similar to patterns in regional clinical surveillance data than the patterns identified in the influent. Analysis of core and discriminatory resistomes and general ARG trends across the eight sampling events (i.e., tendency to be removed, increase, decrease, or be found in the effluent only), along with quantification of ARGs of clinical concern, aided in identifying candidate ARGs for surveillance. Relative resistome risk characterization further provided a comprehensive metric for predicting the relative mobility of ARGs and likelihood of being carried in pathogens and can help to prioritize where to focus future monitoring and mitigation. Most antibiotics that were subject to regional resistance testing were also found in the WWTP, with the total antibiotic load decreasing by ∼40–50%, but no strong correlations were found between antibiotics and corresponding ARGs. Overall, this study provides insight into how metagenomic data can be collected and analyzed for surveillance of antibiotic resistance at WWTPs, suggesting that effluent is a beneficial monitoring point with relevance both to the local clinical condition and for assessing efficacy of wastewater treatment in reducing risk of disseminating antibiotic resistance. Published version

Use-dependent plasticity, thought to contribute to functional recovery after brain injury, is elicited by motor training. The purpose of this study was to determine if administration of d-amphetamine facilitates the effects of motor training on use-dependent plasticity. Healthy human volunteers underwent a training period of voluntary thumb movements under the effects of placebo or d-amphetamine in different sessions in a randomized double-blind, counterbalanced design. Previous work in a drug-naive condition showed that such training causes changes in the direction of thumb movements evoked by transcranial magnetic stimulation and in transcranial magnetic stimulation-evoked electromyographic responses. The endpoint measure of the study was the magnitude of training-induced changes in transcranial magnetic stimulation-evoked kinematic and electromyographic responses in the d-amphetamine and in the placebo conditions. Motor training resulted in increased magnitude, faster development and longer lasting duration of use-dependent plasticity under d-amphetamine compared to the placebo session. These results document a facilitatory effect of d-amphetamine on use-dependent plasticity, a possible mechanism mediating the beneficial effect of this drug on functional recovery after cortical lesions.

Practicing movements results in improvement in performance and in plasticity of the motor cortex. To identify the underlying mechanisms, we studied use-dependent plasticity in human subjects premedicated with drugs that influence synaptic plasticity. Use-dependent plasticity was reduced substantially by dextromethorphan (an N- methyl- d -aspartate receptor blocker) and by lorazepam [a γ-aminobutyric acid (GABA) type A receptor-positive allosteric modulator]. These results identify N -methyl- d -aspartate receptor activation and GABAergic inhibition as mechanisms operating in use-dependent plasticity in intact human motor cortex and point to similarities in the mechanisms underlying this form of plasticity and long-term potentiation.

System integration and validation of embedded technologies has always been a challenge, particularly in the case of autonomous underwater vehicles (AUVs). The inaccessibility of the remote environment combined with the cost of field operations have been the main obstacles to the maturity and evolution of underwater technologies. Additionally, the analysis of embedded technologies is hampered by data processing and analysis time lags, due to low bandwidth data communications with the underwater platform. This makes realworld monitoring and testing challenging for the developer/operator as they are unable to react quickly or in real-time to the remote platform stimuli. This chapter discusses the different testing techniques useful for unmanned underwater vehicle (UUVs) and gives example applications where necessary. Later sections digress into more detail about a new novel framework called the Augmented Reality Framework (ARF) and its applications on improving pre-real-world testing facilities for UUVs. To begin with more background is given on current testing techniques and their uses. To begin with some background is given about Autonomous Underwater Vehicles (AUVs). An AUV (Healey et al., 1995) is a type of UUV. The difference between AUVs and Remotely operated vehicles (ROVs) is that AUVs employ intelligence, such as sensing and automatic decision making, allowing them to perform tasks autonomously, whilst ROVs are controlled remotely by a human with communications running down a tether. AUVs can operate for long periods of time without communication with an operator as they run a predefined mission plan. An operator can design missions for multiple AUVs and monitor their progress in parallel. ROVs require at least one pilot per ROV controlling them continuously. The cost of using AUVs should be drastically reduced compared with ROVs providing the AUV technology is mature enough to execute the task as well as an ROV. AUVs have no tether, or physical connection with surface vessels, and therefore are free to move without restriction around or inside complex structures. AUVs can be smaller and have lower powered thrusters than ROVs because they do not have to drag a tether behind them. Tethers can be thousands of metres in length for deep sea missions and consequently very heavy. In general, AUVs require less infrastructure than ROVs i.e. ROVs usually require a large ship and crew to operate which is not required with an AUV due to being easier to deploy and recover. In general, autonomous vehicles (Zyda et al., 1990) can go where humans cannot, do not want to, or in more relaxed terms they are suited to doing the “the dull, the dirty, and the O pe n A cc es s D at ab as e w w w .in te ch w eb .o rg

In healthy individuals, motor training can elicit use-dependent plasticity. Here the authors studied six subjects in whom training alone failed to elicit this effect. Administration of a single dose of 10 mg of D-amphetamine preceding training led to use-dependent plasticity in a subgroup of these subjects. Using pharmacologic interventions to enhance the effects of motor training might help rehabilitative efforts in patients in whom training alone fails.

Motor practice elicits use-dependent plasticity in humans as well as in animals. Given the influence of cholinergic neurotransmission on learning and memory processes, we evaluated the effects of scopolamine (a muscarinic receptor antagonist) on use-dependent plasticity and corticomotor excitability in a double-blind placebo-controlled randomized design study. Use-dependent plasticity was substantially attenuated by scopolamine in the absence of global changes in corticomotor excitability. These results identify a facilitatory role for cholinergic influences in use-dependent plasticity in the human motor system.

Use-dependent plasticity, thought to contribute to functional recovery after brain injury, is elicited by motor training. The purpose of this study was to determine if administration of d-amphetamine facilitates the effects of motor training on use-dependent plasticity. Healthy human volunteers underwent a training period of voluntary thumb movements under the effects of placebo or d-amphetamine in different sessions in a randomized double-blind, counterbalanced design. Previous work in a drug-naive condition showed that such training causes changes in the direction of thumb movements evoked by transcranial magnetic stimulation and in transcranial magnetic stimulation-evoked electromyographic responses. The endpoint measure of the study was the magnitude of training-induced changes in transcranial magnetic stimulation-evoked kinematic and electromyographic responses in the d-amphetamine and in the placebo conditions. Motor training resulted in increased magnitude, faster development and longer lasting duration of use-dependent plasticity under d-amphetamine compared to the placebo session. These results document a facilitatory effect of d-amphetamine on use-dependent plasticity, a possible mechanism mediating the beneficial effect of this drug on functional recovery after cortical lesions.