1
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Weimann A, Dinan AM, Ruis C, Bernut A, Pont S, Brown K, Ryan J, Santos L, Ellison L, Ukor E, Pandurangan AP, Krokowski S, Blundell TL, Welch M, Blane B, Judge K, Bousfield R, Brown N, Bryant JM, Kukavica-Ibrulj I, Rampioni G, Leoni L, Harrison PT, Peacock SJ, Thomson NR, Gauthier J, Fothergill JL, Levesque RC, Parkhill J, Floto RA. Evolution and host-specific adaptation of Pseudomonas aeruginosa. Science 2024; 385:eadi0908. [PMID: 38963857 DOI: 10.1126/science.adi0908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 05/02/2024] [Indexed: 07/06/2024]
Abstract
The major human bacterial pathogen Pseudomonas aeruginosa causes multidrug-resistant infections in people with underlying immunodeficiencies or structural lung diseases such as cystic fibrosis (CF). We show that a few environmental isolates, driven by horizontal gene acquisition, have become dominant epidemic clones that have sequentially emerged and spread through global transmission networks over the past 200 years. These clones demonstrate varying intrinsic propensities for infecting CF or non-CF individuals (linked to specific transcriptional changes enabling survival within macrophages); have undergone multiple rounds of convergent, host-specific adaptation; and have eventually lost their ability to transmit between different patient groups. Our findings thus explain the pathogenic evolution of P. aeruginosa and highlight the importance of global surveillance and cross-infection prevention in averting the emergence of future epidemic clones.
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Affiliation(s)
- Aaron Weimann
- Victor Phillip Dahdaleh Heart & Lung Research Institute, University of Cambridge, Cambridge, UK
- University of Cambridge Molecular Immunity Unit, MRC Laboratory of Molecular Biology, Cambridge, UK
- Cambridge Centre for AI in Medicine, University of Cambridge, Cambridge, UK
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Adam M Dinan
- Victor Phillip Dahdaleh Heart & Lung Research Institute, University of Cambridge, Cambridge, UK
- University of Cambridge Molecular Immunity Unit, MRC Laboratory of Molecular Biology, Cambridge, UK
- Cambridge Centre for AI in Medicine, University of Cambridge, Cambridge, UK
| | - Christopher Ruis
- Victor Phillip Dahdaleh Heart & Lung Research Institute, University of Cambridge, Cambridge, UK
- University of Cambridge Molecular Immunity Unit, MRC Laboratory of Molecular Biology, Cambridge, UK
- Cambridge Centre for AI in Medicine, University of Cambridge, Cambridge, UK
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Audrey Bernut
- Laboratory of Pathogens and Host Immunity (LPHI), UMR5235, CNRS/Université de Montpellier, Montpellier, France
| | - Stéphane Pont
- Laboratory of Pathogens and Host Immunity (LPHI), UMR5235, CNRS/Université de Montpellier, Montpellier, France
| | - Karen Brown
- Victor Phillip Dahdaleh Heart & Lung Research Institute, University of Cambridge, Cambridge, UK
- University of Cambridge Molecular Immunity Unit, MRC Laboratory of Molecular Biology, Cambridge, UK
- Cambridge Centre for Lung Infection, Royal Papworth Hospital, Cambridge, UK
| | - Judy Ryan
- Victor Phillip Dahdaleh Heart & Lung Research Institute, University of Cambridge, Cambridge, UK
- University of Cambridge Molecular Immunity Unit, MRC Laboratory of Molecular Biology, Cambridge, UK
| | - Lúcia Santos
- Department of Physiology, Bioscience Institute, University College Cork, Cork, Ireland
| | - Louise Ellison
- University of Cambridge Molecular Immunity Unit, MRC Laboratory of Molecular Biology, Cambridge, UK
| | - Emem Ukor
- University of Cambridge Molecular Immunity Unit, MRC Laboratory of Molecular Biology, Cambridge, UK
- Cambridge Centre for Lung Infection, Royal Papworth Hospital, Cambridge, UK
| | - Arun P Pandurangan
- Victor Phillip Dahdaleh Heart & Lung Research Institute, University of Cambridge, Cambridge, UK
- Department of Biochemistry, University of Cambridge, Cambridge, UK
- Department of Medicine, University of Cambridge, Cambridge, UK
| | - Sina Krokowski
- Victor Phillip Dahdaleh Heart & Lung Research Institute, University of Cambridge, Cambridge, UK
- University of Cambridge Molecular Immunity Unit, MRC Laboratory of Molecular Biology, Cambridge, UK
| | - Tom L Blundell
- Victor Phillip Dahdaleh Heart & Lung Research Institute, University of Cambridge, Cambridge, UK
- Department of Biochemistry, University of Cambridge, Cambridge, UK
- Department of Medicine, University of Cambridge, Cambridge, UK
| | - Martin Welch
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Beth Blane
- Department of Medicine, University of Cambridge, Cambridge, UK
| | - Kim Judge
- Wellcome Sanger Institute, Hinxton, UK
| | - Rachel Bousfield
- Department of Medicine, University of Cambridge, Cambridge, UK
- Cambridge University Hospitals Trust, Cambridge, UK
| | | | | | - Irena Kukavica-Ibrulj
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec City, Québec, Canada
| | - Giordano Rampioni
- Department of Science, University Roma Tre, Rome, Italy
- IRCCS Fondazione Santa Lucia, Rome, Italy
| | - Livia Leoni
- Department of Science, University Roma Tre, Rome, Italy
| | - Patrick T Harrison
- Department of Physiology, Bioscience Institute, University College Cork, Cork, Ireland
| | - Sharon J Peacock
- Department of Medicine, University of Cambridge, Cambridge, UK
- Cambridge University Hospitals Trust, Cambridge, UK
| | - Nicholas R Thomson
- Wellcome Sanger Institute, Hinxton, UK
- London School of Hygiene and Tropical Medicine, London, UK
| | - Jeff Gauthier
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec City, Québec, Canada
| | - Jo L Fothergill
- Department of Clinical Infection, Microbiology and Immunology, University of Liverpool, Liverpool, UK
| | - Roger C Levesque
- Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Québec City, Québec, Canada
| | - Julian Parkhill
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - R Andres Floto
- Victor Phillip Dahdaleh Heart & Lung Research Institute, University of Cambridge, Cambridge, UK
- University of Cambridge Molecular Immunity Unit, MRC Laboratory of Molecular Biology, Cambridge, UK
- Cambridge Centre for AI in Medicine, University of Cambridge, Cambridge, UK
- Cambridge Centre for Lung Infection, Royal Papworth Hospital, Cambridge, UK
- Department of Medicine, University of Cambridge, Cambridge, UK
- Cambridge University Hospitals Trust, Cambridge, UK
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2
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Khawaja T, Mäklin T, Kallonen T, Gladstone RA, Pöntinen AK, Mero S, Thorpe HA, Samuelsen Ø, Parkhill J, Izhar M, Akhtar MW, Corander J, Kantele A. Deep sequencing of Escherichia coli exposes colonisation diversity and impact of antibiotics in Punjab, Pakistan. Nat Commun 2024; 15:5196. [PMID: 38890378 PMCID: PMC11189469 DOI: 10.1038/s41467-024-49591-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Accepted: 06/10/2024] [Indexed: 06/20/2024] Open
Abstract
Multi-drug resistant (MDR) E. coli constitute a major public health burden globally, reaching the highest prevalence in the global south yet frequently flowing with travellers to other regions. However, our comprehension of the entire genetic diversity of E. coli colonising local populations remains limited. We quantified this diversity, its associated antimicrobial resistance (AMR), and assessed the impact of antibiotic use by recruiting 494 outpatients and 423 community dwellers in the Punjab province, Pakistan. Rectal swab and stool samples were cultured on CLED agar and DNA extracted from plate sweeps was sequenced en masse to capture both the genetic and AMR diversity of E. coli. We assembled 5,247 E. coli genomes from 1,411 samples, displaying marked genetic diversity in gut colonisation. Compared with high income countries, the Punjabi population generally showed a markedly different distribution of genetic lineages and AMR determinants, while use of antibiotics elevated the prevalence of well-known globally circulating MDR clinical strains. These findings implicate that longitudinal multi-regional genomics-based surveillance of both colonisation and infections is a prerequisite for developing mechanistic understanding of the interplay between ecology and evolution in the maintenance and dissemination of (MDR) E. coli.
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Affiliation(s)
- Tamim Khawaja
- Meilahti Infectious Diseases and Vaccine Research Center (MeiVac), Helsinki University Hospital and University of Helsinki, Helsinki, Finland
- Human Microbiome Research Program, University of Helsinki, Helsinki, Finland
- Multidiciplinary Center of Excellence in Antimicrobial Resistance Research, FIMAR, Medical Faculty, University of Helsinki, Helsinki, Finland
| | - Tommi Mäklin
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - Teemu Kallonen
- Department of Clinical Microbiology, Turku University Hospital, Turku, Finland
| | | | - Anna K Pöntinen
- Department of Biostatistics, University of Oslo, Oslo, Norway
- Norwegian National Advisory Unit on Detection of Antimicrobial Resistance, Department of Microbiology and Infection Control, University Hospital of North Norway, Tromsø, Norway
| | - Sointu Mero
- Human Microbiome Research Program, University of Helsinki, Helsinki, Finland
- Multidiciplinary Center of Excellence in Antimicrobial Resistance Research, FIMAR, Medical Faculty, University of Helsinki, Helsinki, Finland
| | - Harry A Thorpe
- Department of Biostatistics, University of Oslo, Oslo, Norway
| | - Ørjan Samuelsen
- Norwegian National Advisory Unit on Detection of Antimicrobial Resistance, Department of Microbiology and Infection Control, University Hospital of North Norway, Tromsø, Norway
- Department of Pharmacy, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
| | - Julian Parkhill
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
| | - Mateen Izhar
- Department of Microbiology, Shaikh Zayed Post-Graduate Medical Institute, Lahore, Pakistan
| | - M Waheed Akhtar
- School of Biological Science, University of the Punjab, Lahore, Pakistan
| | - Jukka Corander
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland.
- Department of Biostatistics, University of Oslo, Oslo, Norway.
- Parasites and Microbes, Wellcome Sanger Institute, Hinxton, UK.
| | - Anu Kantele
- Meilahti Infectious Diseases and Vaccine Research Center (MeiVac), Helsinki University Hospital and University of Helsinki, Helsinki, Finland.
- Human Microbiome Research Program, University of Helsinki, Helsinki, Finland.
- Multidiciplinary Center of Excellence in Antimicrobial Resistance Research, FIMAR, Medical Faculty, University of Helsinki, Helsinki, Finland.
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3
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Liao H, Ji Y, Sun Y. High-resolution strain-level microbiome composition analysis from short reads. MICROBIOME 2023; 11:183. [PMID: 37587527 PMCID: PMC10433603 DOI: 10.1186/s40168-023-01615-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 07/07/2023] [Indexed: 08/18/2023]
Abstract
BACKGROUND Bacterial strains under the same species can exhibit different biological properties, making strain-level composition analysis an important step in understanding the dynamics of microbial communities. Metagenomic sequencing has become the major means for probing the microbial composition in host-associated or environmental samples. Although there are a plethora of composition analysis tools, they are not optimized to address the challenges in strain-level analysis: highly similar strain genomes and the presence of multiple strains under one species in a sample. Thus, this work aims to provide a high-resolution and more accurate strain-level analysis tool for short reads. RESULTS In this work, we present a new strain-level composition analysis tool named StrainScan that employs a novel tree-based k-mers indexing structure to strike a balance between the strain identification accuracy and the computational complexity. We tested StrainScan extensively on a large number of simulated and real sequencing data and benchmarked StrainScan with popular strain-level analysis tools including Krakenuniq, StrainSeeker, Pathoscope2, Sigma, StrainGE, and StrainEst. The results show that StrainScan has higher accuracy and resolution than the state-of-the-art tools on strain-level composition analysis. It improves the F1 score by 20% in identifying multiple strains at the strain level. CONCLUSIONS By using a novel k-mer indexing structure, StrainScan is able to provide strain-level analysis with higher resolution than existing tools, enabling it to return more informative strain composition analysis in one sample or across multiple samples. StrainScan takes short reads and a set of reference strains as input and its source codes are freely available at https://github.com/liaoherui/StrainScan . Video Abstract.
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Affiliation(s)
- Herui Liao
- Department of Electrical Engineering, City University of Hong Kong, Kowloon, China
| | - Yongxin Ji
- Department of Electrical Engineering, City University of Hong Kong, Kowloon, China
| | - Yanni Sun
- Department of Electrical Engineering, City University of Hong Kong, Kowloon, China.
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4
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Alanko JN, Vuohtoniemi J, Mäklin T, Puglisi SJ. Themisto: a scalable colored k-mer index for sensitive pseudoalignment against hundreds of thousands of bacterial genomes. Bioinformatics 2023; 39:i260-i269. [PMID: 37387143 DOI: 10.1093/bioinformatics/btad233] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/01/2023] Open
Abstract
MOTIVATION Huge datasets containing whole-genome sequences of bacterial strains are now commonplace and represent a rich and important resource for modern genomic epidemiology and metagenomics. In order to efficiently make use of these datasets, efficient indexing data structures-that are both scalable and provide rapid query throughput-are paramount. RESULTS Here, we present Themisto, a scalable colored k-mer index designed for large collections of microbial reference genomes, that works for both short and long read data. Themisto indexes 179 thousand Salmonella enterica genomes in 9 h. The resulting index takes 142 gigabytes. In comparison, the best competing tools Metagraph and Bifrost were only able to index 11 000 genomes in the same time. In pseudoalignment, these other tools were either an order of magnitude slower than Themisto, or used an order of magnitude more memory. Themisto also offers superior pseudoalignment quality, achieving a higher recall than previous methods on Nanopore read sets. AVAILABILITY AND IMPLEMENTATION Themisto is available and documented as a C++ package at https://github.com/algbio/themisto available under the GPLv2 license.
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Affiliation(s)
- Jarno N Alanko
- Department of Computer Science, University of Helsinki, Helsinki 00014, Finland
| | - Jaakko Vuohtoniemi
- Department of Computer Science, University of Helsinki, Helsinki 00014, Finland
| | - Tommi Mäklin
- Department of Mathematics and Statistics, University of Helsinki, Helsinki 00014, Finland
| | - Simon J Puglisi
- Department of Computer Science, University of Helsinki, Helsinki 00014, Finland
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5
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Lindstedt K, Buczek D, Pedersen T, Hjerde E, Raffelsberger N, Suzuki Y, Brisse S, Holt K, Samuelsen Ø, Sundsfjord A. Detection of Klebsiella pneumoniae human gut carriage: a comparison of culture, qPCR, and whole metagenomic sequencing methods. Gut Microbes 2022; 14:2118500. [PMID: 36045603 PMCID: PMC9450895 DOI: 10.1080/19490976.2022.2118500] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
Klebsiella pneumoniae is an important opportunistic healthcare-associated pathogen and major contributor to the global spread of antimicrobial resistance. Gastrointestinal colonization with K. pneumoniae is a major predisposing risk factor for infection and forms an important hub for the dispersal of resistance. Current culture-based detection methods are time consuming, give limited intra-sample abundance and strain diversity information, and have uncertain sensitivity. Here we investigated the presence and abundance of K. pneumoniae at the species and strain level within fecal samples from 103 community-based adults by qPCR and whole metagenomic sequencing (WMS) compared to culture-based detection. qPCR demonstrated the highest sensitivity, detecting K. pneumoniae in 61.2% and 75.8% of direct-fecal and culture-enriched sweep samples, respectively, including 52/52 culture-positive samples. WMS displayed lower sensitivity, detecting K. pneumoniae in 71.2% of culture-positive fecal samples at a 0.01% abundance cutoff, and was inclined to false positives in proportion to the relative abundance of other Enterobacterales present. qPCR accurately quantified K. pneumoniae to 16 genome copies/reaction while WMS could estimate relative abundance to at least 0.01%. Quantification by both methods correlated strongly with each other (Spearman's rho = 0.91). WMS also supported accurate intra-sample K. pneumoniae sequence type (ST)-level diversity detection from fecal microbiomes to 0.1% relative abundance, agreeing with the culture-based detected ST in 16/19 samples. Our results show that qPCR and WMS are sensitive and reliable tools for detection, quantification, and strain analysis of K. pneumoniae from fecal samples with potential to support infection control and enhance insights in K. pneumoniae gastrointestinal ecology.
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Affiliation(s)
- Kenneth Lindstedt
- Department of Medical Biology, Faculty of Health Sciences, UiT the Arctic University of Norway, Tromsø, Norway,CONTACT Kenneth Lindstedt
| | - Dorota Buczek
- Department of Medical Biology, Faculty of Health Sciences, UiT the Arctic University of Norway, Tromsø, Norway
| | - Torunn Pedersen
- Norwegian National Advisory Unit on Detection of Antimicrobial Resistance, Department of Microbiology and Infection Control, University Hospital of North Norway, Tromsø, Norway
| | - Erik Hjerde
- Department of Chemistry, UiT the Arctic University of Norway, Tromsø, Norway
| | - Niclas Raffelsberger
- Department of Medical Biology, Faculty of Health Sciences, UiT the Arctic University of Norway, Tromsø, Norway,Department of Microbiology and Infection Control, University Hospital of North Norway, Tromsø, Norway
| | - Yutaka Suzuki
- Department of Computational Biology and Medical Sciences, The University of Tokyo, Tokyo, Japan
| | - Sylvain Brisse
- Biodiversity and Epidemiology of Bacterial Pathogens Unit, Institut Pasteur, Université Paris Cité, Paris, France
| | - Kathryn Holt
- Department of Infectious Diseases, Central Clinical School, Monash University, Melbourne, Australia,Department of Infection Biology, London School of Hygiene and Tropical Medicine, London, UK
| | - Ørjan Samuelsen
- Norwegian National Advisory Unit on Detection of Antimicrobial Resistance, Department of Microbiology and Infection Control, University Hospital of North Norway, Tromsø, Norway,Department of Pharmacy, Faculty of Health Sciences, UiT the Arctic University of Norway, Tromsø, Norway
| | - Arnfinn Sundsfjord
- Department of Medical Biology, Faculty of Health Sciences, UiT the Arctic University of Norway, Tromsø, Norway,Norwegian National Advisory Unit on Detection of Antimicrobial Resistance, Department of Microbiology and Infection Control, University Hospital of North Norway, Tromsø, Norway,Arnfinn Sundsfjord Department of Medical Biology, Faculty of Health Sciences, UiT the Arctic University of Norway, Tromsø, 9038, Norway
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6
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Mäklin T, Kallonen T, Alanko J, Samuelsen Ø, Hegstad K, Mäkinen V, Corander J, Heinz E, Honkela A. Bacterial genomic epidemiology with mixed samples. Microb Genom 2021; 7:000691. [PMID: 34779765 PMCID: PMC8743562 DOI: 10.1099/mgen.0.000691] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 09/13/2021] [Indexed: 11/18/2022] Open
Abstract
Genomic epidemiology is a tool for tracing transmission of pathogens based on whole-genome sequencing. We introduce the mGEMS pipeline for genomic epidemiology with plate sweeps representing mixed samples of a target pathogen, opening the possibility to sequence all colonies on selective plates with a single DNA extraction and sequencing step. The pipeline includes the novel mGEMS read binner for probabilistic assignments of sequencing reads, and the scalable pseudoaligner Themisto. We demonstrate the effectiveness of our approach using closely related samples in a nosocomial setting, obtaining results that are comparable to those based on single-colony picks. Our results lend firm support to more widespread consideration of genomic epidemiology with mixed infection samples.
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Affiliation(s)
- Tommi Mäklin
- Helsinki Institute for Information Technology HIIT, Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - Teemu Kallonen
- Department of Biostatistics, University of Oslo, Oslo, Norway
- Wellcome Sanger Institute, Hinxton, Cambridgeshire, UK
| | - Jarno Alanko
- Helsinki Institute for Information Technology HIIT, Department of Computer Science, University of Helsinki, Helsinki, Finland
| | - Ørjan Samuelsen
- Norwegian National Advisory Unit on Detection of Antimicrobial Resistance, Department of Microbiology and Infection Control, University Hospital of North Norway, Tromsø, Norway
- Department of Pharmacy, UT The Arctic University of Norway, Tromsø, Norway
| | - Kristin Hegstad
- Norwegian National Advisory Unit on Detection of Antimicrobial Resistance, Department of Microbiology and Infection Control, University Hospital of North Norway, Tromsø, Norway
- Research group for Host-Microbe Interactions, Department of Medical Biology, Faculty of Health Sciences, UT The Arctic University of Norway, Tromsø, Norway
| | - Veli Mäkinen
- Helsinki Institute for Information Technology HIIT, Department of Computer Science, University of Helsinki, Helsinki, Finland
| | - Jukka Corander
- Helsinki Institute for Information Technology HIIT, Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
- Department of Biostatistics, University of Oslo, Oslo, Norway
- Wellcome Sanger Institute, Hinxton, Cambridgeshire, UK
| | - Eva Heinz
- Department of Biostatistics, University of Oslo, Oslo, Norway
- Liverpool School of Tropical Medicine, Liverpool, UK
| | - Antti Honkela
- Helsinki Institute for Information Technology HIIT, Department of Computer Science, University of Helsinki, Helsinki, Finland
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7
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Sridhar S, Forrest S, Pickard D, Cormie C, Lees EA, Thomson NR, Dougan G, Baker S. Inhibitory Concentrations of Ciprofloxacin Induce an Adaptive Response Promoting the Intracellular Survival of Salmonella enterica Serovar Typhimurium. mBio 2021; 12:e0109321. [PMID: 34154399 PMCID: PMC8262899 DOI: 10.1128/mbio.01093-21] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 05/19/2021] [Indexed: 12/02/2022] Open
Abstract
Antimicrobial resistance (AMR) is a pressing global health crisis, which has been fueled by the sustained use of certain classes of antimicrobials, including fluoroquinolones. While the genetic mutations responsible for decreased fluoroquinolone (ciprofloxacin) susceptibility are known, the implications of ciprofloxacin exposure on bacterial growth, survival, and interactions with host cells are not well described. Aiming to understand the influence of inhibitory concentrations of ciprofloxacin in vitro, we subjected three clinical isolates of Salmonella enterica serovar Typhimurium to differing concentrations of ciprofloxacin, dependent on their MICs, and assessed the impact on bacterial growth, morphology, and transcription. We further investigated the differential morphology and transcription that occurred following ciprofloxacin exposure and measured the ability of ciprofloxacin-treated bacteria to invade and replicate in host cells. We found that ciprofloxacin-exposed S. Typhimurium is able to recover from inhibitory concentrations of ciprofloxacin and that the drug induces specific morphological and transcriptional signatures associated with the bacterial SOS response, DNA repair, and intracellular survival. In addition, ciprofloxacin-treated S. Typhimurium has increased capacity for intracellular replication in comparison to that of untreated organisms. These data suggest that S. Typhimurium undergoes an adaptive response under ciprofloxacin perturbation that promotes cellular survival, a consequence that may justify more measured use of ciprofloxacin for Salmonella infections. The combination of multiple experimental approaches provides new insights into the collateral effects that ciprofloxacin and other antimicrobials have on invasive bacterial pathogens. IMPORTANCE Antimicrobial resistance is a critical concern in global health. In particular, there is rising resistance to fluoroquinolones, such as ciprofloxacin, a first-line antimicrobial for many Gram-negative pathogens. We investigated the adaptive response of clinical isolates of Salmonella enterica serovar Typhimurium to ciprofloxacin, finding that the bacteria adapt in short timespans to high concentrations of ciprofloxacin in a way that promotes intracellular survival during early infection. Importantly, by studying three clinically relevant isolates, we were able to show that individual isolates respond differently to ciprofloxacin and that for each isolate, there was a heterogeneous response under ciprofloxacin treatment. The heterogeneity that arises from ciprofloxacin exposure may drive survival and proliferation of Salmonella during treatment and lead to drug resistance.
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Affiliation(s)
- Sushmita Sridhar
- Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
- Wellcome Sanger Institute, Hinxton, United Kingdom
| | - Sally Forrest
- Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Derek Pickard
- Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Claire Cormie
- Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Emily A. Lees
- Department of Paediatrics, University of Oxford, Oxford, United Kingdom
| | - Nicholas R. Thomson
- Wellcome Sanger Institute, Hinxton, United Kingdom
- Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Gordon Dougan
- Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Stephen Baker
- Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
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