[Patterns in the immunoenzyme analysis of bacterial cells]

Area of Science:

• Microbiology
• Biotechnology
• Immunochemistry

Background:

• Contaminant microflora poses a significant risk to the microbiological production of enzymes like alpha-amylase and alkaline protease.
• Early and accurate detection of contaminant microorganisms is crucial for maintaining the quality and yield of biotechnological products.
• Existing detection methods may lack the speed and sensitivity required for real-time process monitoring.

Purpose of the Study:

• To investigate the regularities of enzyme immunoassay (EIA) for whole bacterial cells of a specific contaminant bacillary species.
• To develop and optimize rapid EIA methods for the early detection of contaminant microflora in microbiological production.
• To define kinetic and equilibrant parameters for antibody-cell interactions in EIA.

Main Methods:

• Studied enzyme immunoassay (EIA) of whole bacterial cells, focusing on peroxidase-labeled antibodies.
• Optimized cell separation techniques, including filtration using filter plates and centrifugation.
• Developed and validated four distinct EIA methods for contaminant microflora quantification.

Main Results:

• Defined effective kinetic and equilibrant parameters for peroxidase-labeled antibody-cell interactions in solution and on plate surfaces.
• Proposed an effective method for immobilizing bacterial cells via centrifugation in assay plates.
• Achieved detection limits of 5 X 10^5 to 5 X 10^4 cells/ml within 1-3.5 minutes, depending on the assay scheme.

Conclusions:

• Optimized EIA methods provide a rapid and sensitive tool for detecting specific contaminant microflora in industrial settings.
• The developed methods are suitable for early warning systems, preventing contamination issues in enzyme production.
• This approach significantly reduces detection time compared to traditional microbiological methods.