Image-based physical characterization of magnetotactic bacteria from an environmental sample

TL;DR

This paper introduces an integrated, open-source image-based approach combining sequencing, microscopy, and novel magnetic characterization techniques to analyze magnetotactic bacteria populations directly from environmental samples.

Contribution

It presents a new pipeline for physical characterization of MTB using automated image analysis and magnetic field-based cell classification, enabling rapid population analysis.

Findings

Successful identification of diverse MTB in Latvia's Ogre River

Development of a novel magnetic cell classification method

Demonstration of a fast, robust analysis pipeline for environmental samples

Abstract

Magnetotactic bacteria (MTB) are a diverse group of microorganisms that are able to biomineralize magnetic nanoparticles. Most MTB remain uncultured, making population-level characterization from natural environments difficult. We report the discovery of a new and diverse MTB-rich site in the Ogre River, Latvia, and present an integrated approach combining 16S rRNA sequencing, transmission electron microscopy, and novel open-source, automated image-based physical methods to characterize bacteria populations within environmental samples. We introduce a pipeline for cell velocimetry using a static magnetic field and a method to classify cell populations based on their magnetic moment using a modified U-turn method where cell behavior is studied in an alternating magnetic field. This study demonstrates that our physical analysis methods provide a powerful, fast, and robust toolset for MTB population analysis in complex environmental samples.