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As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing and/or sequencing capacity, which can also introduce biases1–3. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing4,5. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We developed and deployed improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detected emerging variants of concern up to 14 days earlier in wastewater samples, and identified multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.

Beech leaf disease (BLD), an emerging threat to American beech (Fagus grandifolia) in the northern U.S. and Canada, was recently confirmed to be caused by the nematode, Litylenchus crenatae subsp. mccannii (hereafter L. crenatae). Consequently, there is a need for a rapid, sensitive, and accurate method for detecting L. crenatae for both diagnostic as well as control purposes. This research developed a new set of DNA primers that specifically amplify L. crenatae and allow for accurate detection of the nematode in plant tissue. These primers have also been used in quantitative PCR (qPCR) to determine relative differences in gene copy number between samples. This primer set provides an improved, effective tool for monitoring and detection of L. crenatae in temperate tree leaf tissue which is necessary to understand the spread of this emerging forest pest and to develop management strategies.

SummaryAs SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing/sequencing capacity, which can also introduce biases. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here, we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We develop and deploy improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detect emerging variants of concern up to 14 days earlier in wastewater samples, and identify multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.

Mycobacterium avium subsp. avium and Mycobacterium intracellulare are primary causes of mycobacteriosis in captive birds throughout the world, but little is known about how they are transmitted. To define the local epidemiology of infection, we strain-typed 70 M. avium subsp. avium and 15 M. intracellulare culture isolates obtained over a 4-year period from captive birds. Typing was performed using randomly amplified polymorphic DNA (RAPD) PCR, amplified fragment length polymorphic (AFLP) fragment analyses, and for a subset of isolates, DNA sequencing of a segment of the 16S-23S rRNA internal transcribed spacer region. Six strain clusters comprising 43 M. avium subsp. avium, isolates were identified; 42 isolates had unique typing patterns, including all M. intracellulare isolates. Phylo-geographical analyses using RAPD and AFLP fingerprints and animal confinement histories showed no correlation between housing of infected birds and mycobacterial strain-type, except for two animals. The diversity of M. avium subsp. avium and M. intracellulare isolates and minimal evidence for bird-to-bird transmission suggest that environmental reservoirs may be important sources of infection in captivity.