flowCyBar

flowCyBar analyzes high-throughput flow cytometry (FCM) data using gate information to monitor population and community dynamics and to characterize optical properties of individual bacterial cells in natural communities.

Key Features:

• Gate-based monitoring: Uses gate information to track population and community dynamics in flow cytometry datasets.
• High-throughput FCM processing: Processes high-throughput flow cytometry (FCM) data to extract cytometric signals.
• Cytometric histograms: Visualizes FCM data as cytometric histograms that serve as fingerprints of microbial community structure across time points or microenvironments.
• Optical characterization of individual bacterial cells: Characterizes optical properties of individual bacterial cells within natural communities.
• Derivation of cytometric fingerprints: Derives cytometric fingerprints for correlation with experimental and functional parameters.
• Comparison with other methods: Has been systematically compared to Dalmatian Plot, Cytometric Histogram Image Comparison (CHIC), CyBar, and FlowFP.
• Operator experience: Evaluates the level of expertise required to handle cytometric datasets across methods.
• Change detection sensitivity: Assesses sensitivity in detecting changes within microbial communities.
• Time efficiency: Considers time demand for analysis across comparative methods.
• Software requirements: Reviews software prerequisites needed for each comparative method.

Scientific Applications:

• Biofilm community characterization: Applied to characterize community structures in electroactive microbial biofilms.
• Correlation with experimental and functional parameters: Correlates cytometric fingerprints with experimental and functional parameters, including measures of biofilm performance and productivity.
• Assessment of inoculum effects: Assesses influence of inoculum source, such as different wastewater samples, on microbial community structure and biofilm performance.
• Evaluation of substrate impact: Evaluates the impact of substrates (acetate or lactate) on community structure within the studied system.
• Monitoring structural changes: Monitors structural changes in natural microbial communities over time.

Methodology:

Processes high-throughput flow cytometry (FCM) data using gate information to generate cytometric histograms and cytometric fingerprints.