Imaging Flow Cytometry to Study Microbial Autoaggregation

Ronit Suissa; Uzi Hadad; Michael Meijler; Ilana Kolodkin-Gal

doi:10.3791/65788

JoVE Journal
Biology

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JoVE Journal Biology

Imaging Flow Cytometry to Study Microbial Autoaggregation

成像流式细胞术研究微生物自聚集

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05:19 min

September 29, 2023

DOI: 10.3791/65788-v

Ronit Suissa¹, Uzi Hadad², Michael Meijler¹, Ilana Kolodkin-Gal^3,4

¹Department of Chemistry,Ben-Gurion University of the Negev, ²Ilse Kats Institute for Nanoscale Science & Technology,Ben-Gurion University of the Negev, ³Department of Plant Pathology and Microbiology, Faculty of Agriculture, Food and Environment,The Hebrew University of Jerusalem, ⁴The Scojen institute for synthetic biology,Reichman university

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Overview

This study investigates microbial autoaggregation using Lactobacillaceae as a model system, highlighting the effectiveness of imaging flow cytometry for analysis. The research focuses on the response of Lactobacillaceae species to dietary carbohydrates and employs high-throughput imaging methods.

Key Study Components

Research Area

Microbial autoaggregation
Effects of dietary carbohydrates
Imaging flow cytometry analysis

Background

Traditional methods for measuring autoaggregation include spectrophotometry and microscopy.
Challenges in single event segmentation in high-throughput imaging.
Importance of analyzing microbial behaviors in relation to nutrition.

Methods Used

Imaging flow cytometry for studying microbial autoaggregation
Lactobacillaceae species as the organism model
Calibration and data acquisition protocols for flow cytometry

Main Results

Variations in aggregation characteristics of different LAB strains in response to sugars.
Observation of single cells, small aggregates, larger aggregates, and chains in tested strains.
Data analysis revealed significant results concerning the impact of fermentable and non-fermentable sugars.

Conclusions

The study demonstrates the potential of imaging flow cytometry in understanding microbial autoaggregation.
Findings offer insights into how dietary components influence microbial behaviors.

Frequently Asked Questions

What is microbial autoaggregation?

Microbial autoaggregation refers to the ability of microorganisms to clump together, which can impact their behavior and function in various environments.

Why use imaging flow cytometry for this study?

Imaging flow cytometry allows for high-throughput analysis and better visualization of individual microbial aggregates, overcoming traditional measurement limitations.

What organisms were studied?

Lactobacillaceae species were used as the model organisms in this research.

What dietary factors were investigated?

The study focused on the response of microbial autoaggregation to various simple carbohydrates from the diet.

What were the key findings?

Significant variations in aggregation behaviors were observed based on the type of sugar consumed.

How does this research contribute to the field of biology?

This research enhances understanding of microbial dynamics in response to nutrition, relevant for applications in food science and health.

What challenges does high-throughput imaging present?

Single event segmentation is a major challenge in high-throughput imaging, which this study addresses through imaging flow cytometry.

该协议描述了一种使用成像流式细胞术测量微生物自聚集的定量方法。

本研究以乳酸菌属为模型，证明了成像流式细胞术分析在研究微生物自聚集方面的有效性。重点是分析乳酸菌物种的自聚集对饮食中简单碳水化合物的反应。测量自聚集最常用的方法是光谱光度法（测量微生物悬浮液、浊度或光密度）和传统显微镜技术（如明场、相衬和荧光显微镜）。