Screening and Evaluation of Chassis Cells for Heterologous Biosynthesis of Gas Vesicles as Ultrasound Contrast Agents

TL;DR

This paper explores using different bacteria to produce gas vesicles for ultrasound imaging, aiming to find the best strain for high yield and performance.

Contribution

The study provides experimental evidence on how different bacterial chassis cells affect gas vesicle production and function.

Findings

Five bacterial strains were tested for gas vesicle production, with varying yields and imaging performance.

The intracellular environment of chassis cells significantly influences gas vesicle morphology and function.

Abstract

Gas vesicles (GVs) are hollow protein nanostructures derived from microorganisms and show significant potential for ultrasound imaging applications. However, the direct production of gas vesicles (GVs) from their native hosts faces several limitations: poor contrast imaging performance, insufficient yield, and high costs associated with extraction and purification. These challenges heavily hinder their clinical translation and application. The heterologous expression of GV genes varies significantly among different chassis strains due to their distinct intracellular environments, which ultimately affects GV performance and yield. Therefore, it is crucial to select an appropriate chassis cell that can produce GVs with excellent imaging performance. In this study, the GV gene cluster from Serratia sp. ATCC 39006 was heterologously expressed in five different bacterial chassis strains: Escherichia coli BL21 (AI), Escherichia coli K-12 MG1655, Escherichia coli Nissle 1917, Salmonella YB1, and Vibrio natriegens. By systematically comparing the yield, particle morphology, and ultrasound imaging performance of GVs produced by these strains, we elucidated the impact of chassis cells on GV synthesis and function. This work provides experimental evidence and theoretical support for screening robust GV-producing strains and facilitates future biomedical applications of GVs.

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