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Temperature is a key determinant of microbial behaviour and survival in the environment and within hosts. At intermediate temperatures, growth rate varies according to the Arrhenius law of thermodynamics, which describes the effect of temperature on the rate of a chemical reaction. However, the mechanistic basis for this behaviour remains unclear. Here we use single-cell microscopy to show that Escherichia coli exhibits a gradual response to temperature upshifts with a timescale of ~1.5 doublings at the higher temperature. The response was largely independent of initial or final temperature and nutrient source. Proteomic and genomic approaches demonstrated that adaptation to temperature is independent of transcriptional, translational or membrane fluidity changes. Instead, an autocatalytic enzyme network model incorporating temperature-sensitive Michaelis–Menten kinetics recapitulates all temperature-shift dynamics through metabolome rearrangement, resulting in a transient temperature memory. The model successfully predicts alterations in the temperature response across nutrient conditions, diverse E. coli strains from hosts with different body temperatures, soil-dwelling Bacillus subtilis and fission yeast. In sum, our model provides a mechanistic framework for Arrhenius-dependent growth. 

Engineering microfluidic devices relies on the ability to manufacture sub-100 micrometer fluidic channels. Conventional lithographic methods provide high resolution but require costly exposure tools and outsourcing of masks, which extends the turnaround time to several days. The desire to accelerate design/test cycles has motivated the rapid prototyping of microfluidic channels; however, many of these methods (e.g., laser cutters, craft cutters, fused deposition modeling) have feature sizes of several hundred microns or more. In this paper, we describe a 1-day process for fabricating sub-100 µm channels, leveraging a low-cost (USD 600) 8K digital light projection (DLP) 3D resin printer. The soft lithography process includes mold printing, post-treatment, and casting polydimethylsiloxane (PDMS) elastomer. The process can produce microchannels with 44 µm lateral resolution and 25 µm height, posts as small as 400 µm, aspect ratio up to 7, structures with varying z-height, integrated reservoirs for fluidic connections, and a built-in tray for casting. We discuss strategies to obtain reliable structures, prevent mold warpage, facilitate curing and removal of PDMS during molding, and recycle the solvents used in the process. To our knowledge, this is the first low-cost 3D printer that prints extruded structures that can mold sub-100 µm channels, providing a balance between resolution, turnaround time, and cost (~USD 5 for a 2 × 5 × 0.5 cm^3 chip) that will be attractive for many microfluidics labs. 

Early detection of the COVID-19 virus, SARS-CoV-2, is key to mitigating the spread of new outbreaks. Data from individual testing is increasingly difficult to obtain as people conduct non-reported home tests, defer tests due to logistics or attitudes, or ignore testing altogether. Wastewater based epidemiology is an alternative method for surveilling a community while maintaining individual anonymity; however, a problem is that SARS-CoV-2 markers in wastewater vary throughout the day. Collecting grab samples at a single time may miss marker presence, while autosampling throughout a day is technically challenging and expensive. This study investigates a passive sampling method that would be expected to accumulate greater amounts of viral material from sewers over a period of time. Tampons were tested as passive swab sampling devices from which viral markers could be eluted with a Tween-20 surfactant wash. Six sewersheds in Detroit were sampled 16–22 times by paired swab (4 h immersion before retrieval) and grab methods over a five-month period and enumerated for N1 and N2 SARS-CoV-2 markers using ddPCR. Swabs detected SARS-CoV-2 markers significantly more frequently (P < 0.001) than grab samples, averaging two to three-fold more copies of SARS-CoV-2 markers than their paired grab samples (p < 0.0001) in the assayed volume (10 mL) of wastewater or swab eluate. No significant difference was observed in the recovery of a spiked-in control (Phi6), indicating that the improved sensitivity is not due to improvements in nucleic acid recovery or reduction of PCR inhibition. The outcomes of swab-based sampling varied significantly between sites, with swab samples providing the greatest improvements in counts for smaller sewersheds that otherwise tend to have greater variation in grab sample counts. Swab-sampling with tampons provides significant advantages in detection of SARS-CoV-2 wastewater markers and are expected to provide earlier detection of new outbreaks than grab samples, with consequent public health benefits. 

ABSTRACT Wastewater-based epidemiology (WBE) expanded rapidly in response to the COVID-19 pandemic. As the public health emergency has ended, researchers and practitioners are looking to shift the focus of existing wastewater surveillance programs to other targets, including bacteria. Bacterial targets may pose some unique challenges for WBE applications. To explore the current state of the field, the National Science Foundation-funded Research Coordination Network (RCN) on Wastewater Based Epidemiology for SARS-CoV-2 and Emerging Public Health Threats held a workshop in April 2023 to discuss the challenges and needs for wastewater bacterial surveillance. The targets and methods used in existing programs were diverse, with twelve different targets and nine different methods listed. Discussions during the workshop highlighted the challenges in adapting existing programs and identified research gaps in four key areas: choosing new targets, relating bacterial wastewater data to human disease incidence and prevalence, developing methods, and normalizing results. To help with these challenges and research gaps, the authors identified steps the larger community can take to improve bacteria wastewater surveillance. This includes developing data reporting standards and method optimization and validation for bacterial programs. Additionally, more work is needed to understand shedding patterns for potential bacterial targets to better relate wastewater data to human infections. Wastewater surveillance for bacteria can help provide insight into the underlying prevalence in communities, but much work is needed to establish these methods. IMPORTANCEWastewater surveillance was a useful tool to elucidate the burden and spread of SARS-CoV-2 during the pandemic. Public health officials and researchers are interested in expanding these surveillance programs to include bacterial targets, but many questions remain. The NSF-funded Research Coordination Network for Wastewater Surveillance of SARS-CoV-2 and Emerging Public Health Threats held a workshop to identify barriers and research gaps to implementing bacterial wastewater surveillance programs. 

Wastewater surveillance for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an emerging approach to help identify the risk of a coronavirus disease (COVID-19) outbreak. This tool can contribute to public health surveillance at both community (wastewater treatment system) and institutional (e.g., colleges, prisons, and nursing homes) scales. This paper explores the successes, challenges, and lessons learned from initial wastewater surveillance efforts at colleges and university systems to inform future research, development and implementation. We present the experiences of 25 college and university systems in the United States that monitored campus wastewater for SARS-CoV-2 during the fall 2020 academic period. We describe the broad range of approaches, findings, resources, and impacts from these initial efforts. These institutions range in size, social and political geographies, and include both public and private institutions. Our analysis suggests that wastewater monitoring at colleges requires consideration of local information needs, sewage infrastructure, resources for sampling and analysis, college and community dynamics, approaches to interpretation and communication of results, and follow-up actions. Most colleges reported that a learning process of experimentation, evaluation, and adaptation was key to progress. This process requires ongoing collaboration among diverse stakeholders including decision-makers, researchers, faculty, facilities staff, students, and community members.