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Guliaev, A., Hjort, K., Rossi, M., Jonsson, S., Nicoloff, H., Guy, L. & Andersson, D. I. (2025). Machine learning detection of heteroresistance in Escherichia coli. EBioMedicine, 113, Article ID 105618.
Open this publication in new window or tab >>Machine learning detection of heteroresistance in Escherichia coli
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2025 (English)In: EBioMedicine, E-ISSN 2352-3964, Vol. 113, article id 105618Article in journal (Refereed) Published
Abstract [en]

Background

Heteroresistance (HR) is a significant type of antibiotic resistance observed for several bacterial species and antibiotic classes where a susceptible main population contains small subpopulations of resistant cells. Mathematical models, animal experiments and clinical studies associate HR with treatment failure. Currently used susceptibility tests do not detect heteroresistance reliably, which can result in misclassification of heteroresistant isolates as susceptible which might lead to treatment failure. Here we examined if whole genome sequence (WGS) data and machine learning (ML) can be used to detect bacterial HR.

Methods

We classified 467 Escherichia coli clinical isolates as HR or non-HR to the often used β-lactam/inhibitor combination piperacillin-tazobactam using pre-screening and Population Analysis Profiling tests. We sequenced the isolates, assembled the whole genomes and created a set of predictors based on current knowledge of HR mechanisms. Then we trained several machine learning models on 80% of this data set aiming to detect HR isolates. We compared performance of the best ML models on the remaining 20% of the data set with a baseline model based solely on the presence of β-lactamase genes. Furthermore, we sequenced the resistant sub-populations in order to analyse the genetic mechanisms underlying HR.

Findings

The best ML model achieved 100% sensitivity and 84.6% specificity, outperforming the baseline model. The strongest predictors of HR were the total number of β-lactamase genes, β-lactamase gene variants and presence of IS elements flanking them. Genetic analysis of HR strains confirmed that HR is caused by an increased copy number of resistance genes via gene amplification or plasmid copy number increase. This aligns with the ML model's findings, reinforcing the hypothesis that this mechanism underlies HR in Gram-negative bacteria.

Interpretation

We demonstrate that a combination of WGS and ML can identify HR in bacteria with perfect sensitivity and high specificity. This improved detection would allow for better-informed treatment decisions and potentially reduce the occurrence of treatment failures associated with HR.

Keywords
Antibiotic resistance, Antibiotic heteroresistance, E. coli, Machine learning, Piperacillin-tazobactam
National Category
Artificial Intelligence Bioinformatics and Computational Biology Microbiology Molecular Biology
Identifiers
urn:nbn:se:uu:diva-551626 (URN)10.1016/j.ebiom.2025.105618 (DOI)001432028800001 ()2-s2.0-85217905563 (Scopus ID)
Funder
Swedish Research Council, 2021-02091NIH (National Institutes of Health), U19AI158080-01
Available from: 2025-02-27 Created: 2025-02-27 Last updated: 2025-04-18Bibliographically approved
Heyman, G., Jonsson, S., Fatsis-Kavalopoulos, N., Hjort, K., Nicoloff, H., Furebring, M. & Andersson, D. I. (2025). Prevalence, misclassification, and clinical consequences of the heteroresistant phenotype in Escherichia coli bloodstream infections in patients in Uppsala, Sweden: a retrospective cohort study [Review]. Lancet Microbe, 6(4), Article ID 101010.
Open this publication in new window or tab >>Prevalence, misclassification, and clinical consequences of the heteroresistant phenotype in Escherichia coli bloodstream infections in patients in Uppsala, Sweden: a retrospective cohort study
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2025 (English)In: Lancet Microbe, E-ISSN 2666-5247, Vol. 6, no 4, article id 101010Article, book review (Refereed) Published
Abstract [en]

Background

Antibiotic heteroresistance is a common bacterial phenotype characterised by the presence of small resistant subpopulations within a susceptible population. During antibiotic exposure, these resistant subpopulations can be enriched and potentially lead to treatment failure. In this study, we examined the prevalence, misclassification, and clinical effect of heteroresistance in Escherichia coli bloodstream infections for the clinically important antibiotics cefotaxime, gentamicin, and piperacillin–tazobactam.

Methods

We conducted a retrospective cohort analysis of patients (n=255) admitted to in-patient care and treated for E coli bloodstream infections within the Uppsala region in Sweden between Jan 1, 2014, and Dec 31, 2015. Patient inclusion criteria were admission to hospital on suspicion of infection, starting systemic antibiotics at the time of admission, positive blood cultures for the growth of E coli upon admission, and residency in the Uppsala health-care region at the time of admission. Exclusion criteria were growth of an additional pathogen than E coli in blood cultures taken at admission or previous inclusion of the patients in the study for another bloodstream infection. Antibiotic susceptibility of preserved blood culture isolates of E coli was assessed for cefotaxime, gentamicin, and piperacillin–tazobactam by disk diffusion and breakpoint crossing heteroresistance (BCHR) was identified using population analysis profiling. The clinical outcome parameters were obtained from patient records. The primary outcome variable was length of hospital stay due to the E coli bloodstream infection, defined as the time between admission and discharge from inpatient care as noted on the physician’s notes. Secondary outcomes were time to fever resolution, admission to intermediary care unit or intensive care unit during time in hospital, switching or adding another intravenous antibiotic treatment, re-admission to hospital within 30 days of original admission, recurrent E coli infection within 30 days of admission to hospital, and all-cause mortality within 90 days of admission.

Findings

A total of 255 participants with a corresponding E coli isolate (out of 500 screened for eligibility) met the inclusion criteria, with 135 female patients and 120 male patients. One (<1%) of 255 strains was BCHR for cefotaxime, 109 (43%) of 255 strains were BCHR for gentamicin, and 22 (9%) of 255 strains were BCHR for piperacillin–tazobactam. Clinical susceptibility testing misclassified 120 (96%) of 125 heteroresistant bacterial strains as susceptible. The BCHR phenotypes had no correlation to length of hospital stay due to the E coli bloodstream infection. However, patients with piperacillin–tazobactam BCHR strains who received piperacillin–tazobactam had 3·1 times higher odds for admittance to the intermediate care unit (95% CI 1·1–9·6, p=0·041) than the remainder of the cohort, excluding those treated with gentamicin. Similarly, those infected with gentamicin BCHR who received gentamicin showed higher odds for admittance to the intensive care unit (5·6 [1·1–42·0, p=0·043]) and mortality (7·1 [1·2–49·2, p=0·030]) than patients treated with gentamicin who were infected with non-gentamicin BCHR E coli.

Interpretation

In a cohort of patients with E coli bloodstream infections, heteroresistance is common and frequently misidentified in routine clinical testing. Several negative effects on patient outcomes are associated with heteroresistant strains.

Place, publisher, year, edition, pages
Elsevier, 2025
National Category
Infectious Medicine
Research subject
Microbiology
Identifiers
urn:nbn:se:uu:diva-554201 (URN)10.1016/j.lanmic.2024.101010 (DOI)001460868100001 ()39827894 (PubMedID)2-s2.0-85215365230 (Scopus ID)
Funder
Wallenberg Foundations, 2018.0168Swedish Research Council, 2021-02091
Available from: 2025-04-09 Created: 2025-04-09 Last updated: 2025-04-22Bibliographically approved
Jonsson, S., Guliaev, A., Berryhill, B. A., Andersson, D. I. & Nicoloff, H. (2025). The dynamic distribution of genetic tandem amplifications in a heteroresistant Escherichia coli population revealed by ultra-deep long read sequencing: Appendix files.
Open this publication in new window or tab >>The dynamic distribution of genetic tandem amplifications in a heteroresistant Escherichia coli population revealed by ultra-deep long read sequencing: Appendix files
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2025 (English)Other (Other academic)
National Category
Microbiology in the Medical Area
Identifiers
urn:nbn:se:uu:diva-555031 (URN)
Available from: 2025-04-22 Created: 2025-04-22 Last updated: 2025-04-23Bibliographically approved
Heidarian, S., Guliaev, A., Nicoloff, H., Hjort, K. & Andersson, D. I. (2024). High prevalence of heteroresistance in Staphylococcus aureus is caused by a multitude of mutations in core genes. PLoS biology, 22(1), Article ID e3002457.
Open this publication in new window or tab >>High prevalence of heteroresistance in Staphylococcus aureus is caused by a multitude of mutations in core genes
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2024 (English)In: PLoS biology, ISSN 1544-9173, E-ISSN 1545-7885, Vol. 22, no 1, article id e3002457Article in journal (Refereed) Published
Abstract [en]

Heteroresistance (HR) is an enigmatic phenotype where, in a main population of susceptible cells, small subpopulations of resistant cells exist. This is a cause for concern, as this small subpopulation is difficult to detect by standard antibiotic susceptibility tests, and upon antibiotic exposure the resistant subpopulation may increase in frequency and potentially lead to treatment complications or failure. Here, we determined the prevalence and mechanisms of HR for 40 clinical Staphylococcus aureus isolates, against 6 clinically important antibiotics: daptomycin, gentamicin, linezolid, oxacillin, teicoplanin, and vancomycin. High frequencies of HR were observed for gentamicin (69.2%), oxacillin (27%), daptomycin (25.6%), and teicoplanin (15.4%) while none of the isolates showed HR toward linezolid or vancomycin. Point mutations in various chromosomal core genes, including those involved in membrane and peptidoglycan/teichoic acid biosynthesis and transport, tRNA charging, menaquinone and chorismite biosynthesis and cyclic-di-AMP biosynthesis, were the mechanisms responsible for generating the resistant subpopulations. This finding is in contrast to gram-negative bacteria, where increased copy number of bona fide resistance genes via tandem gene amplification is the most prevalent mechanism. This difference can be explained by the observation that S. aureus has a low content of resistance genes and absence of the repeat sequences that allow tandem gene amplification of these genes as compared to gram-negative species.

Place, publisher, year, edition, pages
Public Library of Science (PLoS), 2024
National Category
Microbiology in the medical area Biochemistry Molecular Biology
Identifiers
urn:nbn:se:uu:diva-521793 (URN)10.1371/journal.pbio.3002457 (DOI)001142608300001 ()38175839 (PubMedID)
Funder
Swedish Research Council, 2021-02091Knut and Alice Wallenberg Foundation, 2018-0168
Available from: 2024-02-05 Created: 2024-02-05 Last updated: 2025-02-20Bibliographically approved
Nicoloff, H., Hjort, K., Andersson, D. I. & Wang, H. (2024). Three concurrent mechanisms generate gene copy number variation and transient antibiotic heteroresistance. Nature Communications, 15(1), Article ID 3981.
Open this publication in new window or tab >>Three concurrent mechanisms generate gene copy number variation and transient antibiotic heteroresistance
2024 (English)In: Nature Communications, E-ISSN 2041-1723, Vol. 15, no 1, article id 3981Article in journal (Refereed) Published
Abstract [en]

Heteroresistance is a medically relevant phenotype where small antibiotic-resistant subpopulations coexist within predominantly susceptible bacterial populations. Heteroresistance reduces treatment efficacy across diverse bacterial species and antibiotic classes, yet its genetic and physiological mechanisms remain poorly understood. Here, we investigated a multi-resistant Klebsiella pneumoniae isolate and identified three primary drivers of gene dosage-dependent heteroresistance for several antibiotic classes: tandem amplification, increased plasmid copy number, and transposition of resistance genes onto cryptic plasmids. All three mechanisms imposed fitness costs and were genetically unstable, leading to fast reversion to susceptibility in the absence of antibiotics. We used a mouse gut colonization model to show that heteroresistance due to elevated resistance-gene dosage can result in antibiotic treatment failures. Importantly, we observed that the three mechanisms are prevalent among Escherichia coli bloodstream isolates. Our findings underscore the necessity for treatment strategies that address the complex interplay between plasmids, resistance cassettes, and transposons in bacterial populations.

Place, publisher, year, edition, pages
Springer Nature, 2024
National Category
Microbiology Genetics and Genomics Biochemistry Molecular Biology
Research subject
Microbiology
Identifiers
urn:nbn:se:uu:diva-528112 (URN)10.1038/s41467-024-48233-0 (DOI)001221549300044 ()38730266 (PubMedID)
Funder
Swedish Research Council, 2018-02376Swedish Research Council, 2022-0074Swedish Research Council, 2021-02091Swedish Society for Medical Research (SSMF), S18-0174Knut and Alice Wallenberg Foundation, 2018.0168
Available from: 2024-05-15 Created: 2024-05-15 Last updated: 2025-02-20Bibliographically approved
Jagdmann, J., Nicoloff, H. & Andersson, D. I. (2022). Clonal spread and antibiotic selection of a mutation preventing the evolution of high-level resistance: Supporting information: S1 Data.
Open this publication in new window or tab >>Clonal spread and antibiotic selection of a mutation preventing the evolution of high-level resistance: Supporting information: S1 Data
2022 (English)Data set, Primary data
National Category
Microbiology
Identifiers
urn:nbn:se:uu:diva-481966 (URN)
Available from: 2022-08-17 Created: 2022-08-17 Last updated: 2022-08-18Bibliographically approved
Jagdmann, J., Nicoloff, H. & Andersson, D. I. (2022). Clonal spread and antibiotic selection of a mutation preventing the evolution of high-level resistance: Supporting information: S10 Table.
Open this publication in new window or tab >>Clonal spread and antibiotic selection of a mutation preventing the evolution of high-level resistance: Supporting information: S10 Table
2022 (English)Data set, Aggregated data
National Category
Microbiology
Identifiers
urn:nbn:se:uu:diva-481970 (URN)
Available from: 2022-08-17 Created: 2022-08-17 Last updated: 2022-08-18Bibliographically approved
Jagdmann, J., Nicoloff, H. & Andersson, D. I. (2022). Clonal spread and antibiotic selection of a mutation preventing the evolution of high-level resistance: Supporting information: S11 Table.
Open this publication in new window or tab >>Clonal spread and antibiotic selection of a mutation preventing the evolution of high-level resistance: Supporting information: S11 Table
2022 (English)Data set, Aggregated data
National Category
Microbiology
Identifiers
urn:nbn:se:uu:diva-481971 (URN)
Available from: 2022-08-17 Created: 2022-08-17 Last updated: 2022-08-18Bibliographically approved
Jagdmann, J., Nicoloff, H. & Andersson, D. I. (2022). Clonal spread and antibiotic selection of a mutation preventing the evolution of high-level resistance: Supporting information: S2 Table.
Open this publication in new window or tab >>Clonal spread and antibiotic selection of a mutation preventing the evolution of high-level resistance: Supporting information: S2 Table
2022 (English)Data set, Aggregated data
National Category
Microbiology
Identifiers
urn:nbn:se:uu:diva-481967 (URN)
Available from: 2022-08-17 Created: 2022-08-17 Last updated: 2022-08-18Bibliographically approved
Jagdmann, J., Nicoloff, H. & Andersson, D. I. (2022). Clonal spread and antibiotic selection of a mutation preventing the evolution of high-level resistance: Supporting information: S4 Table.
Open this publication in new window or tab >>Clonal spread and antibiotic selection of a mutation preventing the evolution of high-level resistance: Supporting information: S4 Table
2022 (English)Data set, Aggregated data
National Category
Microbiology
Identifiers
urn:nbn:se:uu:diva-481968 (URN)
Available from: 2022-08-17 Created: 2022-08-17 Last updated: 2022-08-18Bibliographically approved
Projects
Plasmid copy number control in bacterial pathogenesis and antibiotic resistance [2022-00741_VR]; Uppsala University; Publications
Schubert, K., Zhang, J., Muscolo, M. E., Braly, M., McCausland, J. W., Lam, H. N., . . . Auerbuch, V. (2025). The polyadenylase PAPI is required for virulence plasmid maintenance in pathogenic bacteria. PLoS Pathogens, 21(5), Article ID e1012655.
Hidden Threats: How Small Cryptic Plasmids Drive Antibiotic Resistance Evolution ? [2024-06136_VR]; Uppsala University
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-4848-1371

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