Ishi Keenum

1. Omic methods (e.g., metagenomics, metatranscriptomics, and metaproteomics) have emerged as a powerful tool for investigating biological systems. In human medicine, genomics has enabled precision...

Aquatic environments can maintain and express antibiotic resistance genes even without antibiotic pressure, but the conditions that govern their activity remain poorly understood. Redox oscillations are pervasive in natural and engineered waters and strongly alter microbial metabolism, yet whether their frequency shapes resistance expression is unknown. We reanalyzed paired metagenomes and metatranscriptomes from a published chemostat experiment in which a sulfidic stream community was cycled between oxic and anoxic conditions at high, medium and low frequency (HF, MF, LF), with strain-resolved population genomics of the dominant Pseudomonas lineage. Resistance genes were broadly distributed across treatments, whereas transcription concentrated under fast cycling, reaching a median 168 TPM under HF against 38 under LF although no antibiotic was present, so genetic potential and expression diverged. Fast cycling induced ROS-generating flavoproteins, antioxidant defenses and transcription-coupled DNA repair, and Pseudomonas supplied 99% of resistance-gene transcripts under HF, chiefly through its intrinsic efflux systems. Within the dominant Pseudomonas genome, however, the four resistance genes carried no sequence variants under HF, where coverage was deepest, and no fixed difference from the reference in any sample. Genome-wide selection remained purifying throughout (pooled pN/pS 0.72 under HF against 0.12 under LF, both below 1), and the relaxation trended toward redox and central metabolism. Redox frequency therefore raises resistance expression by selecting a metabolically versatile, high-efflux lineage, while the resistance sequences themselves stay conserved. Resistance activity in aquatic systems responds to an abiotic driver, which argues for weighing expression alongside gene presence in environmental surveillance. Abstract Figure: Highlights: Fast redox cycling raised ARG expression without any antibiotic added. High-frequency cycling induced ROS sources, antioxidant defense and DNA repair. Fast cycling swept one Pseudomonas lineage to community dominance. ARGs in the dominant Pseudomonas genome carried no variants under HF. Gene-based AMR surveillance would miss the rise in resistance expression.

Background: Metagenomic next-generation sequencing (mNGS) enables broad, untargeted detection of pathogens and microbial signals across complex sample types. However, the diversity of operational contexts, from regulatory enforcement to exploratory discovery, challenges the defining of analytical or interpretive standards appropriate across all applications. Variability in laboratory practices, bioinformatic methods, and reporting conventions continues to limit consistency and decision-maker confidence in mNGS results. Objectives: We introduce Structured Framework for Reporting, Assessment, and Translational Utility of Metagenomics (STRATUM), a use-case–stratified framework that aligns QA, metadata reporting, and interpretive standards with the consequence and intended use of metagenomic sequencing outputs. Methods: STRATUM is organized around five representative biosurveillance use cases spanning public health, food safety, environmental monitoring, synthetic biology detection, and national security. A three-tier interpretive model calibrates analytical rigor, validation expectations, and reporting requirements to decision consequence; from high-consequence regulatory and clinical determinations (Tier 1), through operational surveillance (Tier 2), to exploratory and hypothesis-generating contexts (Tier 3). Results: The framework provides graduated guidance across key domains including sample preparation, sequencing design, controls and contamination governance, reference database curation, bioinformatics reproducibility, and multi-factor signal validation. Cross-cutting principles include explicit documentation of evidentiary bases, transparency in database and pipeline provenance, and defined escalation pathways when results transition between interpretive tiers. Conclusion: Realizing the operational potential of mNGS requires evidentiary standards responsive to decision context rather than fixed across applications. STRATUM offers a consequence-tiered model for quality and reporting in applied metagenomics, supporting reproducible, transparent, and defensible sequencing-based surveillance across public health and biodefense domains. Highlights: Introduction of STRATUM, a consequence-tiered evidentiary framework for applied metagenomics. Structured calibration of analytical rigor and reporting standards to decision context. Cross-use-case guidance spanning surveillance, regulatory, and national security applications.

Wastewater surveillance is increasingly used for antimicrobial resistance (AMR) monitoring in urban environments, but low-resource settings often lack a piped sewerage system. Instead, coprophagous flies—flies that ingest feces—may serve as composite samplers for monitoring fecal wastes present in terrestrial environments. We evaluated whether the class 1 integron-integrase gene intI1 was associated with genetic markers of AMR and fecal source tracking markers (FST) in coprophagous flies collected from latrine entrances and food preparation areas in low-income urban Maputo, Mozambique. We quantified intI1 , an enteric 16S rRNA target (for normalization), three FST markers, and 30 ARG targets using qPCR. We normalized concentrations of intI1 and each target to enteric 16S rRNA. We fit linear mixed models with a random intercept for housing compound to estimate within-fly associations between log ₁₀ relative abundance of intI1 and log ₁₀ relative abundance of each target with and without adjustment for fly taxonomic group, capture location, and standardized fly mass. We also modeled per-fly unique ARG count (i.e., number of ARG targets detected) using Poisson regression. Of 188 flies assayed, 176 passed internal controls; intI1 and enteric 16S rRNA were detected in 95% and 96% of flies, respectively. Higher relative abundance of intI1 was positively associated with ARG and FST targets, with the strongest associations observed for sulfonamide-( sul1 : β = 0.87; 95% CI: 0.81, 0.94; sul2 : β = 0.81; 95% CI: 0.73, 0.89), tetracycline- ( tetA : β = 0.78; 95% CI: 0.70, 0.85; tetB : β = 0.69; 95% CI: 0.60, 0.79), and trimethoprim-related ( dfrA17 : β = 0.78; 95% CI: 0.70, 0.86) genes. Associations with FST markers were weaker (i.e., human mtDNA: β = 0.46; 95% CI: 0.37, 0.55; human-associated Bacteroides : β = 0.34; 95% CI: 0.25, 0.43). Higher relative abundance of intI1 was also associated with a greater number of ARGs detected: each 10-fold increase in intI1 was associated with an 8% higher expected unique ARG count (aRR=1.08, 95% CI: 1.04–1.12). These findings support the need for further research across different settings exploring intI1 carried by coprophagous flies as a potential standardized screening target for AMR surveillance in unsewered terrestrial environments.

Southern Indiana has intensive livestock production, yet species-resolved fecal pathogen and pathogen associated gene profiles are limited. At 10 sites in southern Indiana (April–June 2024), we collected 128 fecal specimens from 10 hosts: pigs (n = 12), horses (12), cats (12), chickens (12), dogs (22), white-tailed deer (12), sheep (12), goats (12), cows (12), and humans (10). We extracted and assayed total nucleic acids using a custom 43-target TaqMan Array Card (RT-qPCR). Flotation microscopy was performed on pig and dog stools for helminth ova. In-silico specificity checks were conducted for selected targets due to potential for cross reactivity between pathogen species. Most samples (60%, 75/126) were positive for ≥1 target, including enteropathogenic Escherichia coli ( eae ) 16% and shiga toxin genes ( stx1 10%, stx2 6.3%). Higher prevalence of genes associated with specific pathogens and gut microbes in specific animals was common, including E. coli O157:H7 in pigs (42%) and sheep (8.3%); Campylobacter coli in chickens (36%) and Klebsiella pneumoniae in humans (60%) and dogs (9.1%). We found the protozoa Giardia in 15% of samples (notably dogs 32%, cows 33%) and Cryptosporidium in 14% (cats 55%, cows 25%, chickens 27%). Most (55%) chicken samples were positive for Plasmodium , which aligned with evidence of locally circulating avian haemosporidians. The Ascaris lumbricoides assay was positive only in pigs (17%), and we identified Ascaris type eggs in 92% of pig samples via microscopy, suggesting our Ascaris lumbricoides assay cross reacted with Ascaris suum supporting detection of the swine lineage ( A. suum ). We detected the class 1 integron-integrase gene ( intI1 ) in 43% of stools, concentrated in chickens, pigs, and horses. These findings suggest animal feces poses a public health hazard in Southern Indiana and indicate the need for targeted One Health studies to better understand the public health risks of specific exposures and animal feces management practices (e.g., farm storage capacity, land application timing, soil incorporation/injection, tile-drain proximity).

Southern Indiana has intensive livestock production, yet species-resolved fecal pathogen profiles are limited. At 10 sites in southern Indiana (April–June 2024), we collected 128 fecal specimens from 10 hosts: pigs (n=12), horses (12), cats (12), chickens (12), dogs (22), white-tailed deer (12), sheep (12), goats (12), cows (12), and humans (10). We extracted and assayed total nucleic acids using a custom 43-target TaqMan Array Card (RT-qPCR). Flotation microscopy was performed on pig and dog stools for helminth ova. In-silico specificity checks were conducted for selected targets due to potential for cross reactivity between pathogen species. Most samples (59.5%, 75/126) were positive for ≥1 target, including enteropathogenic Escherichia coli ( eae ) 15.9% and shiga toxin genes ( stx1 10.3%, stx2 6.3%). Higher prevalence of specific pathogens in specific animals was common, including E. coli O157:H7 in pigs (41.7%) and sheep (8.3%); Campylobacter coli in chickens (36.4%) and Klebsiella pneumoniae in humans (60%) and dogs (9.1%). We found the protozoa Giardia in 15.1% of samples (notably dogs 31.8%, cows 33.3%) and Cryptosporidium in 13.5% (cats 54.5%, cattle 25.0%, chickens 27.3%). Most (54.5%) chicken samples were positive for Plasmodium , which aligned with evidence of locally circulating avian haemosporidians. The Ascaris lumbricoides assay was positive only in pigs (16.7%), and we identified Ascaris eggs in 91.7% of pig samples via microscopy, suggesting our Ascaris lumbricoides assay cross reacted with Ascaris suum supporting detection of the swine lineage ( A. suum ). We detected integrase gene class 1 ( intI1 ) in 42.9% of stools, concentrated in chickens, pigs, and horses. These findings suggest animal feces poses a public health hazard in Southern Indiana and indicate the need for targeted One Health studies to better understand the public health risks of specific exposures and animal feces management practices (e.g., farm storage capacity, land application timing, soil incorporation/injection, tile-drain proximity).

As exemplified during the COVID-19 pandemic, wastewater-based surveillance (WBS) can deliver near real-time, population-level pathogen data to guide public health action. Its impact, however, hinges on timely, transparent, and context-specific communication to stakeholders, including health authorities, policymakers, scientists, clinicians, and the public. This review examines current WBS communication practices, identifies persistent challenges, and proposes strategies to enhance relevance. Key challenges include data complexity, lack of standardised communication frameworks, ethical and privacy concerns, and variable stakeholder capabilities. The strategic use of digital platforms, such as dashboards, reports, press releases, and social media, alongside traditional media, can broaden reach and aid interpretation. Rapid, accurate, and empathetic communication is essential during health crises to maintain trust and counter misinformation. Standardised messaging, simplified data visualisations, and integration with clinical surveillance systems enhance credibility and usability. Strengthening cross-sector collaboration, improving data interpretation, and translating findings into actionable insights are essential to maximising the public health benefits of WBS. Immediate efforts should prioritise building globally coordinated, adaptive communication networks that can evolve alongside surveillance technologies and emerging health threats. Overall, the review underscores the key role of strategic communication in advancing WBS for global health preparedness and optimising public health actions.