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Mol Microbiol. 2016 Feb;99(4):767-77. doi: 10.1111/mmi.13264. Epub 2015 Dec 18.

Oufti: an integrated software package for high-accuracy, high-throughput quantitative microscopy analysis.

Paintdakhi A1,2, Parry B1,2,3, Campos M1,2,3, Irnov I1,2,3, Elf J4, Surovtsev I1,2,3, Jacobs-Wagner C1,2,3,5.

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Microbial Sciences Institute, Yale University, West Haven, CT, 06516, USA.
Howard Hughes Medical Institute, Yale University, New Haven, CT, 06520, USA.
Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, 06520, USA.
Department of Cell and Molecular Biology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
Department of Microbial Pathogenesis, Yale School of Medicine, New Haven, CT, 06510, USA.


With the realization that bacteria display phenotypic variability among cells and exhibit complex subcellular organization critical for cellular function and behavior, microscopy has re-emerged as a primary tool in bacterial research during the last decade. However, the bottleneck in today's single-cell studies is quantitative image analysis of cells and fluorescent signals. Here, we address current limitations through the development of Oufti, a stand-alone, open-source software package for automated measurements of microbial cells and fluorescence signals from microscopy images. Oufti provides computational solutions for tracking touching cells in confluent samples, handles various cell morphologies, offers algorithms for quantitative analysis of both diffraction and non-diffraction-limited fluorescence signals and is scalable for high-throughput analysis of massive datasets, all with subpixel precision. All functionalities are integrated in a single package. The graphical user interface, which includes interactive modules for segmentation, image analysis and post-processing analysis, makes the software broadly accessible to users irrespective of their computational skills.

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