Imaging Minimal Bacteria at the Nanoscale: a Reliable and Versatile Process to Perform Single-Molecule Localization Microscopy in Mycoplasmas

Rideau, Fabien; Villa, Audrey; Belzanne, Pauline; Verdier, Emeline; Hosy, Eric; Arfi, Yonathan

doi:10.1128/spectrum.00645-22

Cited by 12 publications

(7 citation statements)

References 100 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It supports phase contrast and fluorescence images, and has been tested with different species (bacteria E. coli and B. subtilis , yeast S. pombe ), mother machine designs, and optical configurations. The modular pipeline architecture allows flexible use of mid-stream outputs and straightforward troubleshooting (for instance, while M. mycoides is too small to segment with traditional microscopy methods ( Rideau et al, 2022 ), we were able to obtain growth rate measurements by running the first half of the pipeline).…”

Section: Resultsmentioning

confidence: 99%

Tools and methods for high-throughput single-cell imaging with the mother machine

Thiermann

Sandler

Ahir

et al. 2024

eLife

View full text Add to dashboard Cite

Despite much progress, image processing remains a significant bottleneck for high-throughput analysis of microscopy data. One popular platform for single-cell time-lapse imaging is the mother machine, which enables long-term tracking of microbial cells under precisely controlled growth conditions. While several mother machine image analysis pipelines have been developed in the past several years, adoption by a non-expert audience remains a challenge. To fill this gap, we implemented our own software, MM3, as a plugin for the multidimensional image viewer napari. napari-MM3 is a complete and modular image analysis pipeline for mother machine data, which takes advantage of the high-level interactivity of napari. Here, we give an overview of napari-MM3 and test it against several well-designed and widely-used image analysis pipelines, including BACMMAN and DeLTA. In addition, the rapid adoption and widespread popularity of deep-learning methods by the scientific community raises an important question: to what extent can users trust the results generated by such “black box” methods? We explicitly demonstrate “What You Put Is What You Get” (WYPIWYG); i.e., the image analysis results can reflect the user bias encoded in the training dataset. Finally, while the primary purpose of this work is to introduce the image analysis software that we have developed over a decade in our lab, we also provide useful information for those who want to implement mother-machine-based high-throughput imaging and image analysis methods in their research. This includes our guiding principles and best practices to ensure transparency and reproducible results.

show abstract

Section: Resultsmentioning

confidence: 99%

Tools and methods for high-throughput single-cell imaging with the mother machine

Thiermann

Sandler

Ahir

et al. 2024

eLife

View full text Add to dashboard Cite

show abstract

“…Alternatively, the lack of transformants with the first set of plasmids may have resulted from poor expression of the antibiotic resistance marker with the p438 promoter. However, given that the p438 promoter is functional in Mgal, 42 this second hypothesis appears to be less plausible. Finally, five transformants were randomly selected for each plasmid and further characterized by single-primer PCR and sequencing to determine the insertion sites of the transposon (Figure S3, Table S3).…”

Section: ■ Results and Discussionmentioning

confidence: 99%

Genome Engineering in Mycoplasma gallisepticum Using Exogenous Recombination Systems

et al. 2022

View full text Add to dashboard Cite

Mycoplasma gallisepticum (Mgal) is a common pathogen of poultry worldwide that has recently spread to North American house finches after a single host shift in 1994. The molecular determinants of Mgal virulence and host specificity are still largely unknown, mostly due to the absence of efficient methods for functional genomics. After evaluating two exogenous recombination systems derived from phages found in the phylogenetically related Spiroplasma phoeniceum and the more distant Bacillus subtilis, the RecET-like system from B. subtilis was successfully used for gene inactivation and targeted replacement in Mgal. In a second step, the Cre-lox recombination system was used for the removal of the antibiotic resistance marker in recombinant mutants. This study therefore describes the first genetic tool for targeted genome engineering of Mgal and demonstrates the efficiency of heterologous recombination systems in minimal bacteria.

show abstract

“…It supports phase contrast and fluorescence images, and has been tested with different species (bacteria E. coli and B. subtilis , yeast S. pombe ), mother machine designs, and optical configurations. The modular pipeline architecture allows flexible use of mid-stream outputs and straightforward troubleshooting (for instance, while M. mycoides is too small to segment with traditional microscopy methods [31] , we were able to obtain growth rate measurements by running the first half of the pipeline).…”

Section: Mother Machine Image Analysis With Napari-mm3mentioning

confidence: 99%

Tools and methods for high-throughput single-cell imaging with the mother machine

Thiermann

Sandler

Ahir

et al. 2023

Preprint

View full text Add to dashboard Cite

Despite much progress, image processing remains a significant bottleneck for high-throughput analysis of microscopy data. One popular platform for single-cell time-lapse imaging is the mother machine, which enables long-term tracking of microbial cells under precisely controlled growth conditions. While several mother machine image analysis pipelines have been developed, adoption by a non-expert audience remains a challenge. To fill this gap, we implemented our own software, MM3, as a plugin for the multidimensional image viewer napari. napari-MM3 is a complete and modular image analysis pipeline for mother machine data, which also benefits from the high level interactivity and rapidly growing user base of napari. Here we give an overview of napari-MM3 and test it against existing mother machine analysis software. By analyzing one dataset separately via multiple methods, we find that the distributions and correlations in several key physiological parameters are robust to the choice of analysis tool, though care must be taken when interpreting absolute spatial measurements such as cell size. By lowering the barrier to entry in image analysis - a key bottleneck in mother machine adoption - we aim to expand the user base of this powerful tool.

show abstract

Imaging Minimal Bacteria at the Nanoscale: a Reliable and Versatile Process to Perform Single-Molecule Localization Microscopy in Mycoplasmas

Cited by 12 publications

References 100 publications

Tools and methods for high-throughput single-cell imaging with the mother machine

Tools and methods for high-throughput single-cell imaging with the mother machine

Genome Engineering in Mycoplasma gallisepticum Using Exogenous Recombination Systems

Tools and methods for high-throughput single-cell imaging with the mother machine

Contact Info

Product

Resources

About