Highly Multiplexed Reverse-Transcription Loop-Mediated Isothermal Amplification and Nanopore Sequencing (LAMPore) for Wastewater-Based Surveillance.

Wastewater-based surveillance (WBS) has gained attention as a strategy to monitor and provide an early warning for disease outbreaks. Here, we applied an isothermal gene amplification technique, reverse-transcription loop-mediated isothermal amplification (RT-LAMP), coupled with nanopore sequencing (LAMPore) as a means to detect SARS-CoV-2. Specifically, we combined barcoding using both an RT-LAMP primer and the nanopore rapid barcoding kit to achieve highly multiplexed detection of SARS-CoV-2 in wastewater. RT-LAMP targeting the SARS-CoV-2 N region was conducted on 96 reactions including wastewater RNA extracts and positive and no-target controls. The resulting amplicons were pooled and subjected to nanopore sequencing, followed by demultiplexing based on barcodes that differentiate the source of each SARS-CoV-2 N amplicon derived from the 96 RT-LAMP products. The criteria developed and applied to establish whether SARS-CoV-2 was detected by the LAMPore assay indicated high consistency with polymerase chain reaction-based detection of the SARS-CoV-2 N gene, with a sensitivity of 89% and a specificity of 83%. We further profiled sequence variations on the SARS-CoV-2 N amplicons, revealing a number of mutations on a sample collected after viral variants had emerged. The results demonstrate the potential of the LAMPore assay to facilitate WBS for SARS-CoV-2 and the emergence of viral variants in wastewater.

Making waves: Uses of real-time, hyperlocal flood sensor data for emergency management, resiliency planning, and flood impact mitigation.

Flooding is expected to increase due to intensification of extreme precipitation events, sea-level rise, and urbanization. Low-cost water level sensors have the ability to fill a critical data gap on the presence, depth, and duration of street-level floods by measuring flood profiles (i.e., flood stage hydrographs) in real-time with a time interval on the order of minutes. Hyperlocal flood data collected by low-cost sensors have many use cases for a variety of stakeholders including municipal agencies, community members, and researchers. Here we outline examples of potential uses of flood sensor data before, during, and after flood events, based on dialog with stakeholders in New York City. These uses include inputs to predictive flood models, generation of real-time flood alerts for community members and emergency response teams, storm recovery assistance and cataloging of storm impacts, and informing infrastructure design and investment for long-term flood resilience project planning.