Related Experiment Video

Updated: Aug 29, 2026

Screening Foodstuffs for Class 1 Integrons and Gene Cassettes
09:37

Screening Foodstuffs for Class 1 Integrons and Gene Cassettes

Published on: June 19, 2015

Integrons as tools for epidemiological studies

P Severino1, V D Magalhães

  • 1Center for Experimental Research, Education and Research Institute, Hospital Albert Einstein, São Paulo, Brazil. psever@einstein.br

Clinical Microbiology and Infection : the Official Publication of the European Society of Clinical Microbiology and Infectious Diseases
|February 5, 2004
PubMed

Insights

Integron detection aids in identifying hospital cross-infections, particularly in intensive care units (ICUs). This molecular epidemiology tool complements ribotyping for accurate strain identification, enhancing patient safety.

Area of Science:

  • Medical Microbiology
  • Molecular Epidemiology
  • Infectious Disease Control

Background:

  • Hospital-acquired infections pose a significant threat to patient safety, especially in critical care settings.
  • Accurate identification of causative agents and transmission routes is crucial for effective infection control.
  • Molecular typing methods are essential tools for investigating outbreaks and understanding pathogen dissemination.

Purpose of the Study:

  • To investigate the utility of integron content analysis in detecting cross-infections among Gram-negative bacterial strains.
  • To compare the effectiveness of integron detection with ribotyping in molecular epidemiology studies within a hospital setting.
  • To assess the role of integron analysis in identifying epidemiologically related strains during suspected cross-infection episodes.

Main Methods:

  • Analysis of integron content in Gram-negative bacterial isolates from three distinct hospital cross-infection episodes.
  • Comparison of integron profiling results with conventional ribotyping techniques.
  • Epidemiological data collection from intensive care units (ICUs) and bronchoscopy patients.

Main Results:

  • Integron analysis and ribotyping showed agreement in identifying epidemiologically linked strains in two of the three investigated episodes (Acinetobacter and co-infections of Pseudomonas aeruginosa and Serratia marcescens).
  • In the third episode involving Enterobacter cloacae, integron analysis provided additional discriminatory power beyond ribotyping, highlighting its ability to refine epidemiological conclusions.
  • The study demonstrated the potential of integron detection as a valuable tool for rapid identification of cross-infection cases in critical hospital wards.

Conclusions:

  • Integron detection is a valuable adjunct to traditional methods like ribotyping for molecular epidemiology in hospital environments.
  • This method facilitates the prompt identification of potential cross-infection events, particularly in high-risk areas such as ICUs.
  • Utilizing integron analysis can significantly enhance the speed and accuracy of outbreak investigations and infection control strategies.

More Related Videos

Bidirectional Retroviral Integration Site PCR Methodology and Quantitative Data Analysis Workflow12:53

Bidirectional Retroviral Integration Site PCR Methodology and Quantitative Data Analysis Workflow

Published on: June 14, 2017

Amplification, Next-generation Sequencing, and Genomic DNA Mapping of Retroviral Integration Sites09:31

Amplification, Next-generation Sequencing, and Genomic DNA Mapping of Retroviral Integration Sites

Published on: March 22, 2016

Related Concept Videos

Non-LTR Retrotransposons03:18

Non-LTR Retrotransposons

As the name suggests, non-LTR retrotransposons lack the long terminal repeats characteristic of the LTR retrotransposons. Additionally, both LTR and non-LTR retrotransposons use distinct mechanisms of mobilization. Non-LTR retrotransposons are further divided into two classes - Long interspersed nuclear elements (LINEs) and short interspersed nuclear elements (SINEs), both of which occur abundantly in most mammals, including humans. Some of the active non-LTR retrotransposons in humans are L1...
Introduction to Epidemiology01:26

Introduction to Epidemiology

Epidemiology, known as the cornerstone of public health, involves studying the distribution and determinants of health-related events in defined populations and applying these insights to control health issues. This is essential for understanding how diseases spread, identifying populations at greater risk, and implementing measures to control or prevent outbreaks. Epidemiology addresses not only infectious diseases but also non-communicable conditions like cancer and cardiovascular disease,...
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
Investigation of Disease Outbreaks01:23

Investigation of Disease Outbreaks

Multistate foodborne outbreaks pose significant public health risks and require meticulous investigation to identify sources and implement control measures. The Centers for Disease Control and Prevention (CDC) utilizes a dynamic seven-step process for these investigations, integrating data from laboratories, interviews, and environmental assessments to protect public health.Outbreak Detection: The detection of multistate outbreaks typically begins with PulseNet, the CDC's national laboratory...
Confounding in Epidemiological Studies01:27

Confounding in Epidemiological Studies

Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This phenomenon...
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods: