Skip to main content

Microbiology

Automated Methods

This section explores the theory, interpretation, and application of automated methods for bacterial identification. Automated systems have revolutionized clinical microbiology, offering speed, efficiency, and increased throughput

Theory: The Science Behind the Automated Revolution

  • What are Automated Identification Systems?
    • Automated identification systems are computer-controlled instruments that perform multiple biochemical tests and/or utilize advanced techniques to identify bacteria
    • They automate the entire process from inoculation to result reporting
    • They use various detection methods to measure biochemical reactions, including turbidimetry, colorimetry, fluorometry, and impedance
  • Why Use Automated Identification Systems?
    • High Throughput: Process large volumes of samples quickly
    • Speed: Results are generated much faster than manual methods
    • Efficiency: Reduced labor costs and hands-on time
    • Standardization: Standardized protocols minimize variability and improve reproducibility
    • Objective Results: Instruments provide objective and accurate results
    • Database Support: Integrated databases facilitate identification and provide comprehensive information
    • Data Management: Integrated software provides data storage, analysis, and reporting capabilities
  • Key Technologies Used in Automated Systems
    • Spectrophotometry: Measures changes in light absorbance or transmission to detect bacterial growth or metabolic activity
    • Nephelometry: Measures light scattering caused by bacterial growth
    • Colorimetry: Detects color changes resulting from biochemical reactions (e.g., pH changes, substrate utilization)
    • Fluorometry: Measures fluorescence emitted by a reaction
    • Impedance: Measures changes in electrical resistance as bacteria grow and metabolize nutrients
    • Mass Spectrometry (MALDI-TOF): Provides a protein “fingerprint” for rapid identification (covered in a separate section)
  • General Principles of Operation
    1. Sample Preparation: Inoculum is prepared from a pure culture
    2. Inoculation: The sample is introduced into the test system (e.g., a cuvette, well, or card)
    3. Incubation: The test system is incubated at the appropriate temperature and atmosphere
    4. Detection: The instrument monitors the reactions using the appropriate detection method
    5. Data Analysis: The instrument analyzes the data and compares it to a database of known organisms
    6. Identification: The instrument provides an identification with a probability and/or confidence level
    7. Reporting: Results are reported to the LIS (Laboratory Information System)

Interpretation: Deciphering the Automated Output

  • Result Formats
    • Species Identification: The instrument provides the most probable species identification
    • Probability Percentage: A percentage indicating the likelihood of the identification
    • Confidence Level: A qualitative assessment of the certainty of the identification (e.g., excellent, good, acceptable)
    • Biochemical Profile: The results of individual tests may be displayed
    • Antibiotic Susceptibility Results: Some systems offer antimicrobial susceptibility testing (AST) capabilities
  • Understanding the Results
    • High Probability/Confidence: The identification is likely correct
    • Low Probability/Confidence: The identification may require further testing
    • Multiple Potential Identifications: The instrument may provide a list of possible identifications, requiring additional tests or clinical information to differentiate
    • Unidentifiable Organism: The instrument may be unable to identify the organism, requiring manual testing or referral to a reference laboratory
  • Factors Affecting Accuracy
    • Database Accuracy: The accuracy of the identification is dependent on the accuracy and completeness of the instrument’s database
    • Sample Quality: The purity and viability of the inoculum are critical
    • Instrument Performance: Proper instrument maintenance and calibration are essential
    • User Technique: Adherence to the manufacturer’s instructions is important
    • Organism Characteristics: Some organisms may be difficult to identify, even with automated systems
  • Troubleshooting Interpretation
    • Review the Gram stain and colony morphology: Correlate the automated results with the preliminary findings
    • Check for contamination: If the identification is unexpected, consider the possibility of contamination
    • Consult the database: Review the biochemical profile of the identified organism to confirm its plausibility
    • Perform additional tests: If the identification is questionable, perform additional tests or consult a reference laboratory

Application: Putting Knowledge into Practice

  • Quality Control (QC)
    • Control Strains: Use known positive and negative control organisms for each instrument and test panel
    • Frequency: Perform QC according to the manufacturer’s recommendations (e.g., daily, weekly, with each new lot of reagents)
    • Documentation: Record QC results in a logbook or LIS
    • QC Failure: If QC fails, investigate the cause (e.g., reagent issues, instrument malfunction) and repeat the test with new reagents and/or a new control strain
  • Procedure
    1. Specimen Processing: Follow laboratory protocols for specimen collection, transport, and processing
    2. Gram Stain and Colony Morphology: Perform a Gram stain and observe colony morphology
    3. Inoculum Preparation: Prepare a pure culture of the organism according to the instrument’s instructions. Ensure the inoculum is of the correct density
    4. Instrument Setup: Follow the manufacturer’s instructions for setting up the instrument and preparing the test system (e.g., cuvettes, wells, or panels)
    5. Inoculation: Inoculate the test system with the prepared inoculum
    6. Incubation: The instrument automatically incubates the test system
    7. Reading and Analysis: The instrument automatically reads the results and analyzes the data
    8. Result Interpretation: Review the results (species identification, probability/confidence level, biochemical profile)
    9. Documentation: Record the results in the LIS
    10. Correlation: Correlate the results with the Gram stain, colony morphology, and other clinical information
    11. Reporting: Report the identification to the clinician
  • Examples of Automated Identification Systems
    • Vitek 2 (bioMérieux): Uses a miniaturized system with colorimetric and turbidimetric detection. Offers a wide range of identification and AST capabilities
    • MicroScan (Beckman Coulter): Uses a microdilution format with colorimetric detection. Offers a wide range of identification and AST capabilities
    • Phoenix (Becton Dickinson): Uses a combination of oxidation-reduction and colorimetric reactions. Offers identification and AST capabilities
  • Troubleshooting
    • Instrument Errors
      • Instrument Malfunction: Contact the manufacturer’s technical support
      • Maintenance Issues: Follow the manufacturer’s maintenance schedule
      • Calibration: Ensure the instrument is properly calibrated
    • Incorrect Results
      • Inoculum Issues: Verify inoculum purity and density
      • Reagent Problems: Check for expired reagents or improper storage
      • Database Limitations: Be aware of the limitations of the instrument’s database
    • Unidentifiable Organisms
      • Consult the database: The system may provide a limited number of possible identifications. If the organism is not in the database, manual testing or referral to a reference laboratory may be necessary
      • Consider atypical organisms: If the organism is unusual, it may not be identified by the instrument
      • Perform additional tests: If the identification is questionable, perform additional tests or consult a reference laboratory

Key Terms

  • Automated Identification Systems: Computer-controlled instruments that perform multiple biochemical tests and/or utilize advanced techniques to identify bacteria
  • High Throughput: The ability to process a large number of samples quickly
  • Spectrophotometry: The measurement of light absorbance or transmission
  • Nephelometry: The measurement of light scattering
  • Colorimetry: The detection of color changes
  • Fluorometry: The measurement of fluorescence
  • Impedance: The measurement of electrical resistance
  • Mass Spectrometry (MALDI-TOF): A technique used to identify bacteria based on their protein profiles
  • Inoculum: The material used to inoculate a culture medium or test system
  • Incubation: The process of maintaining a culture at a specific temperature and atmosphere to promote growth
  • Probability Percentage: A percentage indicating the likelihood of a correct identification
  • Confidence Level: A qualitative assessment of the certainty of the identification
  • Biochemical Profile: The results of individual biochemical tests
  • Antibiotic Susceptibility Testing (AST): Laboratory tests to determine the effectiveness of antibiotics against a bacterial isolate
  • Database: A collection of data used for identification
  • Quality Control (QC): Procedures used to monitor and ensure the reliability of laboratory testing
  • Control Strains: Known organisms used as positive and negative controls
  • Gram Stain: A differential staining technique used to classify bacteria based on their cell wall structure
  • Colony Morphology: The visual characteristics of bacterial colonies on solid media
  • LIS (Laboratory Information System): A computer system used to manage laboratory data
  • Aseptic Technique: Procedures used to prevent contamination
  • Turbidity: The cloudiness or haziness of a liquid, often indicating bacterial growth
  • Calibration: The process of adjusting an instrument to ensure accurate measurements
  • Maintenance: The routine care and upkeep of an instrument
  • Reagent: A substance used in a chemical reaction to detect or identify another substance
  • Atypical Organism: An organism that does not fit the typical characteristics of its species