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TruaceTracing the truth around AIWednesday, August 5, 2026
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TRV-2026-0584Certified recordPeer-reviewed

Global genomic surveillance of β-lactam resistance in Escherichia coli across human, animal, and environmental reservoirs

Background Escherichia coli poses a global health threat from increasing β-lactam resistance. This study uses genomic and One-Health data to map resistance patterns and enhance antimicrobial resistance (AMR) prediction and management. Methods This study performed a One-Health whole-genome analysis of 30,554 E. coli isolates from human, animal, and environmental sources, spanning from 2000 to 2025. Publicly available genomic data were retrieved from NCBI, encompassing β-lactam resistance genes, including extended…

Climate · The Trace — both readings · certified 2026-07-29 · v1 · article view · machine-readable

Current reading — gain

Gradient-boosted machine learning predicted carbapenem MICs from resistance gene profiles with strong performance for imipenem and ertapenem, supporting AMR surveillance.

Current reading — problem

The same gradient-boosted models showed poor agreement with observed MICs for ampicillin and piperacillin-tazobactam and struggled with beta-lactamase inhibitor combinations.

What this doesn’t fix

Model accuracy was uneven across drug classes, with strong results for carbapenems but poor agreement for ampicillin and beta-lactamase inhibitor combinations, limiting broad clinical use.

Evidence

Reader signal

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Truvace Impact Record TRV-2026-0584, v1: “Global genomic surveillance of β-lactam resistance in Escherichia coli across human, animal, and environmental reservoirs.” Truvace, 2026-07-29. /record/TRV-2026-0584 (accessed at citation time). sha256 7ef54e5d5a94d4d9…

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