Wastewater surveillance for pathogens using reverse transcription-polymerase chain reaction (RT-PCR) is an effective and resource-efficient tool for gathering additional community-level public health information, including the incidence of coronavirus disease-19 (COVID-19). Surveillance of SARS-CoV-2 in wastewater can provide an early warning signal of COVID-19 infections in a community. The capacity of the world's environmental microbiology and virology laboratories for SARS-CoV-2 RNA characterization in wastewater is increasing rapidly. However, there are no standardized protocols or harmonized quality assurance and quality control (QA/QC) procedures for SARS-CoV-2 wastewater surveillance. This paper is a technical review of factors that can cause false-positive and false-negative errors in the surveillance of SARS-CoV-2, culminating in recommended strategies that can be implemented to identify and mitigate these errors. Recommendations include stringent QA/QC measures, representative sampling approaches, effective virus concentration and efficient RNA extraction, amplification inhibition assessment, inclusion of sample processing controls, and considerations for RT-PCR assay selection and data interpretation. Clear data interpretation guidelines (e.g., determination of positive and negative samples) are critical, particularly when the incidence of SARS-CoV-2 in wastewater is low. Corrective and confirmatory actions must be in place for inconclusive results or results diverging from current trends (e.g., initial onset or reemergence of COVID-19 in a community). It is also prudent to perform interlaboratory comparisons to ensure results' reliability and interpretability for prospective and retrospective analyses. The strategies that are recommended in this review aim to improve SARS-CoV-2 characterization and detection for wastewater surveillance applications. A silver lining of the COVID-19 pandemic is that the efficacy of wastewater surveillance continues to be demonstrated during this global crisis. In the future, wastewater should also play an important role in the surveillance of a range of other communicable diseases.

We have developed a program that can accurately analyze the dynamic properties of tethered bacterial cells. The program works especially well with cells that tend to give rise to unstable rotations, such as polar-flagellated bacteria. The program has two novel components. The first dynamically adjusts the center of the cell's rotational trajectories. The second applies piecewise linear approximation to the accumulated rotation curve to reduce noise and separate the motion of bacteria into phases. Thus, it can separate counterclockwise (CCW) and clockwise (CW) rotations distinctly and measure rotational speed accurately. Using this program, we analyzed the properties of tethered Pseudomonas aeruginosa and Pseudomonas putida cells for the first time. We found that the Pseudomonas flagellar motor spends equal time in both CCW and CW phases and that it rotates with the same speed in both phases. In addition, we discovered that the cell body can remain stationary for short periods of time, leading to the existence of a third phase of the flagellar motor which we call "pause." In addition, P. aeruginosa cells adopt longer run lengths, fewer pause frequencies, and shorter pause durations as part of their chemotactic response. We propose that one purpose of the pause phase is to allow the cells to turn at a large angle, where we show that pause durations in free-swimming cells positively correlate with turn angle sizes. Taken together, our results suggest a new "run-reverse-turn" paradigm for polar-flagellated Pseudomonas motility that is different from the "run-and-tumble" paradigm established for peritrichous Escherichia coli.

Wastewater-based surveillance for SARS-CoV-2 has been used for the early warning of transmission or objective trending of the population-level disease prevalence. Here, we describe a new use-case of conducting targeted wastewater surveillance to complement clinical testing for case identification in a small community at risk of COVID-19 transmission. On 2 July 2020, a cluster of COVID-19 cases in two unrelated households residing on different floors in the same stack of an apartment building was reported in Singapore. After cases were conveyed to healthcare facilities and six healthy household contacts were quarantined in their respective apartments, wastewater surveillance was implemented for the entire residential block. SARS-CoV-2 was subsequently detected in wastewaters in an increasing frequency and concentration, despite the absence of confirmed COVID-19 cases, suggesting the presence of fresh case/s in the building. Phone interviews of six residents in quarantine revealed that no one was symptomatic (fever/ respiratory illness). However, when nasopharyngeal swabs from six quarantined residents were tested by PCR tests, one was positive for SARS-CoV-2. The positive case reported episodes of diarrhea and the case's stool sample was also positive for SARS-CoV-2, explaining the SARS-CoV-2 spikes observed in wastewaters. After the case was conveyed to a healthcare facility, wastewaters continued to yield positive signals for five days, though with a decreasing intensity. This was attributed to the return of recovered cases, who had continued to shed the virus. Our findings demonstrate the utility of wastewater surveillance as a non-intrusive tool to monitor high-risk COVID-19 premises, which is able to trigger individual tests for case detection, highlighting a new use-case for wastewater testing.

We propose a minimum set of meta-information to accompany the reporting of SARS-CoV-2 occurrence in wastewater for improved data interpretation.

Tracking fast-swimming bacteria in three dimensions can be extremely challenging with current optical techniques and a microscopic approach that can rapidly acquire volumetric information is required. Here, we introduce phase-contrast holographic video microscopy as a solution for the simultaneous tracking of multiple fast moving cells in three dimensions. This technique uses interference patterns formed between the scattered and the incident field to infer the three-dimensional (3D) position and size of bacteria. Using this optical approach, motility dynamics of multiple bacteria in three dimensions, such as speed and turn angles, can be obtained within minutes. We demonstrated the feasibility of this method by effectively tracking multiple bacteria species, including Escherichia coli, Agrobacterium tumefaciens, and Pseudomonas aeruginosa. In addition, we combined our fast 3D imaging technique with a microfluidic device to present an example of a drug/chemical assay to study effects on bacterial motility.