Cryptosporidium spp. are parasites that cause severe illness in vulnerable human populations. Obtaining pure and sufficient Cryptosporidium DNA from clinical and environmental samples is a challenging task. Oocysts shed in available fecal samples can be limited in quantity, require purification (biased towards dominant strains), and yield limited DNA (<40 fg/oocyst). Here, we use updated genomic sequences from a broad diversity of Cryptosporidium species that have been found to infect humans ( C. cuniculus , C. hominis , C. meleagridis , C. parvum , C. tyzzeri , and C. viatorum ) to develop and validate a set of 100,000 RNA baits (CryptoCap_100k) with the aim of enriching Cryptosporidium DNA from varied samples. Compared to unenriched libraries, CryptoCap_100k increases the percentage of reads mapping to target genome sequences, increases the depth and breadth of genome coverage, and facilitates analyses of genetic variants in many samples, while decreasing overall costs.

During the COVID-19 pandemic, the detection and sequencing of SARS-CoV-2 from wastewater proved to be a valuable tool in assessing trends at the community level. Several whole genome enrichment methods have been proposed for sequencing SARS-CoV-2 from the mixed wastewater community, but there is little consensus on the most appropriate sequencing methods for variant detection or abundance estimations. Few studies have elucidated the errors associated with these methods or have established minimum sequencing requirements for correct interpretation of the results. To address these needs, we systematically assessed the efficacy of three tiled amplicon enrichment methods (Freed/Midnight, ARTIC V4, NEB VarSkip) for whole genome sequencing of SARS-CoV-2 variants using mock wastewater communities with variants at known proportions. We found the ARTIC V4 approach yielded the most accurate results for variant identification and variant abundance estimation, followed by the NEB VarSkip approach. Conversely, the NEB VarSkip method obtained the highest genomic coverage, with the ARTIC V4 method achieving the second highest coverage. Finally, we determined that the Freed/Midnight library preparation methods are not well-suited for use with short read sequencing. Based on the present results, the ARTIC V4 workflow appears to be the most robust and cost-effective approach for monitoring circulating SARS-CoV-2 variants with wastewater surveillance. IMPORTANCE This work is informative for practitioners of wastewater-based epidemiology. Here, we detail a systematic comparison of three tiled amplicon sequencing approaches for enrichment of SARS-CoV-2 variants from wastewater. Using mock communities of known variant composition, we validate the analysis methods previously published by Baaijens et al. in Genome Biology (2022) for estimating variant abundance from wastewater using an RNAseq pipeline, kallisto. We provide recommendations for minimum sequencing requirements for accurate abundance estimates of SARS-CoV-2 variants in wastewater. The sequences generated from the mock communities have been uploaded to NCBI’s Sequence Read Archive and will be useful to other practitioners seeking to validate their sequencing methods or bioinformatic pipelines.

The first influenza A(H5N1) human case associated with the A(H5N1) dairy cattle outbreak in the United States was identified in April 2024. The U.S. CDC response to this outbreak was activated days later and remained active until July 2025. During this time, 70 human cases of influenza A(H5N1) were detected with a range of epidemiological links to sources of exposure. Next-generation sequencing (NGS) of human samples was an effectual mechanism for tracking and analyzing the outbreak evolution throughout the response. Due to the specimens’ importance and their variable physical quality, an assortment of laboratory methods was utilized including influenza segment-specific amplification, enrichment capture, short-read, and long-read sequencing. Combining these methods allowed for high-quality genomic data production with rapid turnaround times—typically 2 days from sample receipt to public database submission. By leveraging replicate sequencing, enrichment capture, and sequencing of diagnostic amplicons, valuable genomic data could be produced directly from human clinical specimens that would have normally been considered too weak for routine virologic surveillance sequencing. The resulting assemblies were characterized and analyzed by CDC and shared with local and state public health authorities to facilitate case investigations and risk assessment. These data were further used for phylogenetic analyses of viruses from human cases to investigate likely animal-to-human transmission events and identify clusters within the outbreak that might indicate trends in the types of exposures. Through the adaptable laboratory workflow and the rapid release of viral genomic data, the public health risk mitigation strategies could be evaluated and adjusted in real time.

Wastewater-based epidemiology addresses key biases and limitations in clinical surveillance by providing population-level coverage, capturing subclinical infections, and mitigating limited clinical testing. Despite its demonstrated value during the COVID-19 pandemic, few phylogenetic studies of wastewater sequences have been conducted, with inferences limited to descriptive genomic diversity. Phylogenetic methods offer deeper insights into viral ancestry, transmission, and epidemic dynamics, yet their application to wastewater data remains unexplored. Here, we present the first study to apply Bayesian phylodynamic approaches to characterize SARS-CoV-2 variant dynamics using wastewater sequences. We conducted a 2.5-year long longitudinal study (June 2020 – December 2022) using wastewater samples collected from catchment sites in Clarke County, Georgia. Leveraging an optimized enrichment and sequencing strategy, we generated 80 whole genome sequences from 41 wastewater samples. As proof of concept for combining wastewater and clinical sequences, we reconstructed epidemic waves in Clarke County in the context of national and international transmission. Phylogenetic analyses showed that wastewater sequences captured all clinically observed variants, inferred variant emergence times consistent with or earlier than clinical genomes, and revealed cryptic Beta transmission. We further identified associations between student movement events and clade expansion, increased transmission, and subsequent case surges. Together, these results demonstrate the power of wastewater genomics to reconstruct viral emergence and spread. Integrating wastewater and clinical sequences provides a robust phylogenetic framework for identifying cryptic transmission, inferring epidemic history, and contextualizing local viral circulation within broader transmission patterns. These findings underscore the importance of wastewater surveillance for pandemic preparedness and public health response.