7 results on '"Sridhar, Sushmita"'
Search Results
2. Inhibitory concentrations of ciprofloxacin induce an adaptive response promoting the intracellular survival of Salmonella Typhimurium
- Author
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Sridhar, Sushmita
- Subjects
Microbial Physiology ,FOS: Biological sciences ,Pathogenic Microbiology ,Life Sciences ,Bacteriology ,biochemical phenomena, metabolism, and nutrition ,bacterial infections and mycoses ,Microbiology - Abstract
Antimicrobial resistance (AMR) is a pressing global health crisis, which has been fuelled 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 S. Typhimurium to differing concentrations of ciprofloxacin, dependent on their minimum inhibitory concentrations (MIC), 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 are 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 have increased capacity for intracellular replication in comparison to 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.
- Published
- 2022
- Full Text
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3. High-content imaging to phenotype antimicrobial effects on individual bacteria at scale
- Author
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Sridhar, Sushmita
- Subjects
Microbial Physiology ,FOS: Biological sciences ,Pathogenic Microbiology ,Medicine and Health Sciences ,Life Sciences ,Microbiology - Abstract
High-content imaging (HCI) is a technique for screening multiple cells in high resolution to detect subtle morphological and phenotypic variation. The method has been commonly deployed on model eukaryotic cellular systems, often for screening new drugs and targets. HCI is not commonly utilized for studying bacterial populations but may be a powerful tool in understanding and combatting antimicrobial resistance. Consequently, we developed a high-throughput method for phenotyping bacteria under antimicrobial exposure at the scale of individual bacterial cells. Imaging conditions were optimized on an Opera Phenix confocal microscope (Perkin Elmer), and novel analysis pipelines were established for both Gram-negative bacilli and Gram-positive cocci. The potential of this approach was illustrated using isolates of Klebsiella pneumoniae, Salmonella enterica serovar Typhimurium, and Staphylococcus aureus. HCI enabled the detection and assessment of subtle morphological characteristics, undetectable through conventional phenotypical methods, that could reproducibly distinguish between bacteria exposed to different classes of antimicrobials with distinct modes of action (MOAs). In addition, distinctive responses were observed between susceptible and resistant isolates. By phenotyping single bacterial cells, we observed intrapopulation differences, which may be critical in identifying persistence or emerging resistance during antimicrobial treatment. The work presented here outlines a comprehensive method for investigating morphological changes at scale in bacterial populations under specific perturbation. https://doi.org/10.1128/mSystems.00028-21.
- Published
- 2022
- Full Text
- View/download PDF
4. Inherent Variability of Growth Media Impacts the Ability of Salmonella Typhimurium to Interact with Host Cells.
- Author
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Sridhar, Sushmita and Steele-Mortimer, Olivia
- Subjects
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SALMONELLA typhimurium , *PHAGOCYTES , *MICROBIAL virulence , *PHENOTYPES , *HOSTS (Biology) - Abstract
Efficient invasion of non-phagocytic cells, such as intestinal epithelial cells, by Salmonella Typhimurium is dependent on the Salmonella Pathogenicity Island 1 (SPI-1)-encoded Type Three Secretion System. The environmental cues involved in SPI-1 induction are not well understood. In vitro, various conditions are used to induce SPI-1 and the invasive phenotype. Although lysogeny broth (LB) is widely used, multiple formulations exist, and variation can arise due to intrinsic differences in complex components. Minimal media are also susceptible to variation. Still, the impact of these inconsistencies on Salmonella virulence gene expression has not been well studied. The goal of this project is to identify growth conditions in LB and minimal medium that affect SPI-1 induction in vitro using both whole population and single cell analysis. Here we show, using a fluorescent reporter of the SPI-1 gene prgH, that growth of Salmonella in LB yields variable induction. Deliberate modification of media components can influence the invasive profile. Finally, we demonstrate that changes in SPI-1 inducing conditions can affect the ability of Salmonella to replicate intracellularly. These data indicate that the specific media growth conditions impact how the bacteria interact with host cells. [ABSTRACT FROM AUTHOR]
- Published
- 2016
- Full Text
- View/download PDF
5. Superspreaders drive the largest outbreaks of hospital onset COVID-19 infections
- Author
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Illingworth, Christopher, Hamilton, William L, Warne, Ben, Routledge, Matthew, Popay, Ashley, Jackson, Chris, Fieldman, Tom, Meredith, Luke W, Houldcroft, Charlotte J, Hosmillo, Myra, Jahun, Aminu S, Caller, Laura G, Caddy, Sarah L, Yakovleva, Anna, Hall, Grant, Khokhar, Fahad A, Feltwell, Theresa, Pinckert, Malte L, Georgana, Iliana, Chaudhry, Yasmin, Curran, Martin D, Parmar, Surendra, Sparkes, Dominic, Rivett, Lucy, Jones, Nick K, Sridhar, Sushmita, Forrest, Sally, Dymond, Tom, Grainger, Kayleigh, Workman, Chris, Ferris, Mark, Gkrania-Klotsas, Effrossyni, Brown, Nicholas M, Weekes, Michael P, Baker, Stephen, Peacock, Sharon J, Goodfellow, Ian G, Gouliouris, Theodore, De Angelis, Daniela, and Török, M Estée
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Male ,Infectious disease ,Evolutionary Biology ,Superspreader ,1. No poverty ,Sars-cov-2 ,COVID-19 ,Middle Aged ,Microbiology ,Hospitals ,3. Good health ,Virus ,Nosocomial Transmission ,Disease Outbreaks ,Hospital ,FOS: Biological sciences ,Humans ,Female ,Retrospective Studies - Abstract
SARS-CoV-2 is notable both for its rapid spread, and for the heterogeneity of its patterns of transmission, with multiple published incidences of superspreading behaviour. Here, we applied a novel network reconstruction algorithm to infer patterns of viral transmission occurring between patients and health care workers (HCWs) in the largest clusters of COVID-19 infection identified during the first wave of the epidemic at Cambridge University Hospitals NHS Foundation Trust, UK. Based upon dates of individuals reporting symptoms, recorded individual locations, and viral genome sequence data, we show an uneven pattern of transmission between individuals, with patients being much more likely to be infected by other patients than by HCWs. Further, the data were consistent with a pattern of superspreading, whereby 21% of individuals caused 80% of transmission events. Our study provides a detailed retrospective analysis of nosocomial SARS-CoV-2 transmission, and sheds light on the need for intensive and pervasive infection control procedures.
6. Superspreaders drive the largest outbreaks of hospital onset COVID-19 infections
- Author
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Illingworth, Christopher, Hamilton, William L, Warne, Ben, Routledge, Matthew, Popay, Ashley, Jackson, Chris, Fieldman, Tom, Meredith, Luke W, Houldcroft, Charlotte J, Hosmillo, Myra, Jahun, Aminu S, Caller, Laura G, Caddy, Sarah L, Yakovleva, Anna, Hall, Grant, Khokhar, Fahad A, Feltwell, Theresa, Pinckert, Malte L, Georgana, Iliana, Chaudhry, Yasmin, Curran, Martin D, Parmar, Surendra, Sparkes, Dominic, Rivett, Lucy, Jones, Nick K, Sridhar, Sushmita, Forrest, Sally, Dymond, Tom, Grainger, Kayleigh, Workman, Chris, Ferris, Mark, Gkrania-Klotsas, Effrossyni, Brown, Nicholas M, Weekes, Michael P, Baker, Stephen, Peacock, Sharon J, Goodfellow, Ian G, Gouliouris, Theodore, De Angelis, Daniela, and Török, M Estée
- Subjects
superspreader ,Male ,SARS-CoV-2 ,infectious disease ,evolutionary biology ,microbiology ,1. No poverty ,nosocomial transmission ,COVID-19 ,virus ,Middle Aged ,Hospitals ,3. Good health ,Disease Outbreaks ,Humans ,Female ,hospital ,Retrospective Studies - Abstract
SARS-CoV-2 is notable both for its rapid spread, and for the heterogeneity of its patterns of transmission, with multiple published incidences of superspreading behaviour. Here, we applied a novel network reconstruction algorithm to infer patterns of viral transmission occurring between patients and health care workers (HCWs) in the largest clusters of COVID-19 infection identified during the first wave of the epidemic at Cambridge University Hospitals NHS Foundation Trust, UK. Based upon dates of individuals reporting symptoms, recorded individual locations, and viral genome sequence data, we show an uneven pattern of transmission between individuals, with patients being much more likely to be infected by other patients than by HCWs. Further, the data were consistent with a pattern of superspreading, whereby 21% of individuals caused 80% of transmission events. Our study provides a detailed retrospective analysis of nosocomial SARS-CoV-2 transmission, and sheds light on the need for intensive and pervasive infection control procedures.
7. Superspreaders drive the largest outbreaks of hospital onset COVID-19 infections
- Author
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Stephen Baker, Grant Hall, Nicholas M. Brown, Aminu S Jahun, Lucy Rivett, Luke W. Meredith, Charlotte J. Houldcroft, Sally Forrest, William L Hamilton, Iliana Georgana, Daniela de Angelis, Malte L Pinckert, Michael P. Weekes, Yasmin Chaudhry, Nick K Jones, M. Estée Török, Anna Yakovleva, Sarah L Caddy, Laura G Caller, Mark Ferris, Ashley Popay, Theresa Feltwell, Tom Fieldman, Matthew Routledge, Tom Dymond, Martin D. Curran, Christopher Jackson, Myra Hosmillo, Sharon J. Peacock, Chris Workman, Christopher J. R. Illingworth, Sushmita Sridhar, Theodore Gouliouris, Effrossyni Gkrania-Klotsas, Dominic Sparkes, Fahad A Khokhar, Ben Warne, Ian Goodfellow, Kayleigh Grainger, Surendra Parmar, Illingworth, Christopher JR [0000-0002-0030-2784], Hamilton, William L [0000-0002-3330-353X], Houldcroft, Charlotte J [0000-0002-1833-5285], Hosmillo, Myra [0000-0002-3514-7681], Jahun, Aminu S [0000-0002-4585-1701], Caddy, Sarah L [0000-0002-9790-7420], Hall, Grant [0000-0003-3928-3979], Georgana, Iliana [0000-0002-8976-1177], Rivett, Lucy [0000-0002-2781-9345], Jones, Nick K [0000-0003-4475-7761], Sridhar, Sushmita [0000-0001-7453-7482], Ferris, Mark [0000-0001-5040-4263], Gkrania-Klotsas, Effrossyni [0000-0002-0930-8330], Brown, Nicholas M [0000-0002-6657-300X], Weekes, Michael P [0000-0003-3196-5545], Baker, Stephen [0000-0003-1308-5755], Peacock, Sharon J [0000-0002-1718-2782], Goodfellow, Ian G [0000-0002-9483-510X], Török, M Estée [0000-0001-9098-8590], Apollo - University of Cambridge Repository, and Illingworth, Christopher Jr [0000-0002-0030-2784]
- Subjects
superspreader ,Male ,Coronavirus disease 2019 (COVID-19) ,QH301-705.5 ,Science ,Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ,Microbiology ,General Biochemistry, Genetics and Molecular Biology ,law.invention ,Disease Outbreaks ,03 medical and health sciences ,0302 clinical medicine ,law ,Health care ,Medicine ,Humans ,030212 general & internal medicine ,Biology (General) ,hospital ,030304 developmental biology ,Retrospective Studies ,0303 health sciences ,Infectious disease ,Evolutionary Biology ,Microbiology and Infectious Disease ,General Immunology and Microbiology ,business.industry ,SARS-CoV-2 ,General Neuroscience ,nosocomial transmission ,Outbreak ,COVID-19 ,Retrospective cohort study ,General Medicine ,Middle Aged ,University hospital ,Hospitals ,3. Good health ,Virus ,Transmission (mechanics) ,Infectious disease (medical specialty) ,Female ,business ,Demography ,Research Article - Abstract
SARS-CoV-2 is notable both for its rapid spread, and for the heterogeneity of its patterns of transmission, with multiple published incidences of superspreading behaviour. Here, we applied a novel network reconstruction algorithm to infer patterns of viral transmission occurring between patients and health care workers (HCWs) in the largest clusters of COVID-19 infection identified during the first wave of the epidemic at Cambridge University Hospitals NHS Foundation Trust, UK. Based upon dates of individuals reporting symptoms, recorded individual locations, and viral genome sequence data, we show an uneven pattern of transmission between individuals, with patients being much more likely to be infected by other patients than by HCWs. Further, the data were consistent with a pattern of superspreading, whereby 21% of individuals caused 80% of transmission events. Our study provides a detailed retrospective analysis of nosocomial SARS-CoV-2 transmission, and sheds light on the need for intensive and pervasive infection control procedures., eLife digest The COVID-19 pandemic, caused by the SARS-CoV-2 virus, presents a global public health challenge. Hospitals have been at the forefront of this battle, treating large numbers of sick patients over several waves of infection. Finding ways to manage the spread of the virus in hospitals is key to protecting vulnerable patients and workers, while keeping hospitals running, but to generate effective infection control, researchers must understand how SARS-CoV-2 spreads. A range of factors make studying the transmission of SARS-CoV-2 in hospitals tricky. For instance, some people do not present any symptoms, and, amongst those who do, it can be difficult to determine whether they caught the virus in the hospital or somewhere else. However, comparing the genetic information of the SARS-CoV-2 virus from different people in a hospital could allow scientists to understand how it spreads. Samples of the genetic material of SARS-CoV-2 can be obtained by swabbing infected individuals. If the genetic sequences of two samples are very different, it is unlikely that the individuals who provided the samples transmitted the virus to one another. Illingworth, Hamilton et al. used this information, along with other data about how SARS-CoV-2 is transmitted, to develop an algorithm that can determine how the virus spreads from person to person in different hospital wards. To build their algorithm, Illingworth, Hamilton et al. collected SARS-CoV-2 genetic data from patients and staff in a hospital, and combined it with information about how SARS-CoV-2 spreads and how these people moved in the hospital . The algorithm showed that, for the most part, patients were infected by other patients (20 out of 22 cases), while staff were infected equally by patients and staff. By further probing these data, Illingworth, Hamilton et al. revealed that 80% of hospital-acquired infections were caused by a group of just 21% of individuals in the study, identifying a ‘superspreader’ pattern. These findings may help to inform SARS-CoV-2 infection control measures to reduce spread within hospitals, and could potentially be used to improve infection control in other contexts.
- Published
- 2021
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