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Metabolomics is a mainstream approach for investigating the metabolic underpinnings of complex biological phenomena and is increasingly being applied to large-scale studies involving hundreds or thousands of samples. Although metabolomics methods are robust in smaller-scale studies, they can be challenging to apply to larger cohorts due to the inherent variability of liquid chromatography mass spectrometry (LC-MS). Much of this difficulty results from the time-dependent changes in the LC-MS system, which affects both the qualitative and quantitative performances of the instrument. Herein, we introduce an analytical strategy for addressing this problem in large-scale microbial studies. Our approach quantifies microbial boundary fluxes using two zwitterionic hydrophilic interaction liquid chromatography (ZIC-HILIC) columns that are plumbed to enable offline column equilibration. Using this strategy, we show that over 397 common metabolites can be resolved in 4.5 min per sample and that metabolites can be quantified with a median coefficient of variation of 0.127 across 1100 technical replicates. We illustrate the utility of this strategy via an analysis of 960 strains of

Liquid chromatography mass spectrometry (LC–MS) has emerged as a mainstream strategy for metabolomics analyses. One advantage of LC–MS is that it can serve both as a biomarker discovery tool and as a platform for clinical diagnostics. Consequently, it offers an exciting opportunity to potentially transition research studies into real-world clinical tools. One important distinction between research versus diagnostics-based applications of LC–MS is throughput. Clinical LC–MS must enable quantitative analyses of target molecules in hundreds or thousands of samples each day. Currently, the throughput of these clinical applications is limited by the chromatographic gradient lengths, which—when analyzing complex metabolomics samples—are difficult to conduct in under ~ 3 min per sample without introducing serious quantitative analysis problems. To address this shortcoming, we developed sequential quantification using isotope dilution (SQUID), an analytical strategy that combines serial sample injections into a continuous isocratic mobile phase to maximize throughput. SQUID uses internal isotope-labelled standards to correct for changes in LC–MS response factors over time. We show that SQUID can detect microbial polyamines in human urine specimens (lower limit of quantification; LLOQ = 106 nM) with less than 0.019 normalized root mean square error. Moreover, we show that samples can be analyzed in as little as 57 s. We propose SQUID as a new, high-throughput LC–MS tool for quantifying small sets of target biomarkers across large cohorts. Graphical Abstract

To determine if the Study To Optimize Peritoneal Infection Therapy (STOP-IT) randomized controlled trial (RCT) changed antibiotic prescribing in patients with Complicated Intra-Abdominal Infection (CIAI).CIAI is common and causes significant morbidity. In May 2015, the STOP-IT RCT showed equivalent outcomes between four-day and clinically determined antibiotic duration.This was a population-based retrospective cohort study using interrupted time series methods. The STOP-IT publication date was the exposure. Median duration of inpatient antibiotic prescription was the outcome. All adult patients admitted to four hospitals in Calgary, Canada between July 2012 and December 2018 with CIAI who survived at least four days following source control were included. Analysis was stratified by infectious source as appendix or biliary tract (group A) versus other (group B).Among 4384 included patients, clinical and demographic attributes were similar before vs after publication. In Group A, median inpatient antibiotic duration was 3 days and unchanged from the beginning to the end of the study period (adjusted median difference -0.00 days, 95% confidence interval [CI] -0.37 - 0.37 days). In Group B, antibiotic duration was shorter at the end of the study period (7.87 vs 6.73 days; -1.14 days, CI -2.37 - 0.09 days), however there was no change in trend following publication (-0.03 days, CI -0.16 - 0.09).For appendiceal or biliary sources of CIAI, antibiotic duration was commensurate with the experimental arm of STOP-IT. For other sources, antibiotic duration was long and did not change in response to trial publication. Additional implementation science is needed to improve antibiotic stewardship.