Reconstruction of Single-Cell Innate Fluorescence Signatures by Confocal Microscopy

Tomohiro Hirayama; Kyosuke Takabe; Tatsunori Kiyokawa; Nobuhiko Nomura; Yutaka Yawata

doi:10.3791/61120

JoVE Journal
Biology

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JoVE Journal Biology

Reconstruction of Single-Cell Innate Fluorescence Signatures by Confocal Microscopy

共焦点顕微鏡による単細胞自然蛍光シグネチャの再構築

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07:29 min

May 27, 2020

DOI: 10.3791/61120-v

Tomohiro Hirayama*¹, Kyosuke Takabe*², Tatsunori Kiyokawa¹, Nobuhiko Nomura^2,3, Yutaka Yawata*^2,3

¹Graduate School of Life and Environmental Sciences,University of Tsukuba, ²Faculty of Life and Environmental Sciences,University of Tsukuba, ³Microbiology Research Center for Sustainability,University of Tsukuba

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Overview

This study presents a protocol for optically extracting and cataloging innate cellular fluorescence signatures from individual live cells. It emphasizes a non-invasive method suitable for analyzing various biological systems at single-cell resolution, including bacterial, fungal, yeast, plant, and animal cells.

Key Study Components

Research Area

Cellular fluorescence analysis
Single-cell resolution techniques
Phenotypic characterization of microorganisms

Background

Importance of non-invasive tagging methods
Challenges in analyzing cellular heterogeneity
Potential applications in microbiology

Methods Used

Confocal reflection microscopy
Multichannel confocal microspectroscopy
Image analysis for cell segmentation and dimensional reduction

Main Results

Successful extraction of innate cellular fluorescence signatures
Identification of phenotype variability among microbial populations
Demonstration of the impact of accurate cell segmentation on analysis

Conclusions

This study highlights a technique for high-resolution fluorescence signature analysis.
It opens avenues for understanding microbial phenotypic diversity in healthcare and ecological studies.

Frequently Asked Questions

What is the purpose of the presented protocol?

The protocol is designed to extract and analyze innate fluorescence signatures from live cells, enabling non-invasive identification.

What types of cells can this technique be applied to?

The technique is applicable to bacteria, fungi, yeasts, plants, and animal cells.

How does this method differ from traditional tagging methods?

This method does not require invasive tagging, allowing for more natural cellular states during analysis.

What technologies are necessary to implement this protocol?

The protocol requires a confocal microscope equipped for reflection microscopy and multichannel spectral imaging.

How does accurate cell segmentation affect results?

Accurate segmentation reduces variability in fluorescence signatures, leading to more reliable data interpretation.

What insights does this study contribute to microbial research?

It contributes to understanding phenotypic heterogeneity and physiological status within microbial populations.

Can machine learning be applied in this context?

Yes, machine learning models can be trained using the dataset for classification and prediction tasks based on fluorescence signatures.

ここでは、3次元空間に分布する全ての個々の生細胞から自然な細胞蛍光シグネチャ(すなわち細胞自家蛍光)を光学的に抽出およびカタログするためのプロトコルが提示される。この方法は、細菌、真菌、酵母、植物、および動物からの細胞を含む単一細胞分解能で、多様な生物学的系の自然蛍光シグネチャを研究するのに適しています。

この技術は、侵襲的なタグ付けを必要とせずに、単一細胞レベルで細胞の同一性または生理学的特性を証明するための独自の研究を提供します。この手法の主な利点は、解析のシングルセルレベルの空間分解能を容易にすることと、バックグラウンドプロセスと区別できることです。したがって、この技術は、病原性微生物の同定と表現型解析に貢献できる可能性があります。

この手法は、表現型の不均一性の研究、または関心のある微生物集団の生理学的状態のモニタリングにも適用できます。その手順を実演していただくのは、私の研究室の高部恭介助教です。共焦点反射顕微鏡とマルチチャンネル共焦点顕微分光法のセットアップ。

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