ArticleBiochemical and biophysical research communications2012
Analysis of gene expression levels in individual bacterial cells without image segmentation.
Article in Biochemical and biophysical research communications, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Environmental Triggers ofFrontiers in microbiology · 2020Article
- Carbohydrate and PepO control bimodality in competence development by Streptococcus mutans.Molecular microbiology · 2019Article
- Fluorescence Tools Adapted for Real-Time Monitoring of the Behaviors ofApplied and environmental microbiology · 2019Article
- Threshold regulation and stochasticity from the MecA/ClpCP proteolytic system in Streptococcus mutans competence.Molecular microbiology · 2018Article
- Intracellular Signaling by themSphere · 2018Article
- Oxidative Stressors Modify the Response of Streptococcus mutans to Its Competence Signal Peptides.Applied and environmental microbiology · 2017Article
- Intercellular Communication via theJournal of bacteriology · 2017Article
- Effects of Carbohydrate Source on Genetic Competence in Streptococcus mutans.Applied and environmental microbiology · 2016Article
- Bidirectional signaling in the competence regulatory pathway of Streptococcus mutans.FEMS microbiology letters · 2015Article
- Sharply Tuned pH Response of Genetic Competence Regulation in Streptococcus mutans: a Microfluidic Study of the Environmental Sensitivity of comX.Applied and environmental microbiology · 2015Article
- Microfluidic study of competence regulation in Streptococcus mutans: environmental inputs modulate bimodal and unimodal expression of comX.Molecular microbiology · 2012Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Studies of stochasticity in gene expression typically make use of fluorescent protein reporters, which permit the measurement of expression levels within individual cells by fluorescence microscopy. Analysis of such microscopy images is almost invariably based on a segmentation algorithm, where the image of a cell or cluster is analyzed mathematically to delineate individual cell boundaries. However segmentation can be ineffective for studying bacterial cells or clusters, especially at lower magnification, where outlines of individual cells are poorly resolved. Here we demonstrate an alternative method for analyzing such images without segmentation. The method employs a comparison between the pixel brightness in phase contrast vs fluorescence microscopy images. By fitting the correlation between phase contrast and fluorescence intensity to a physical model, we obtain well-defined estimates for the different levels of gene expression that are present in the cell or cluster. The method reveals the boundaries of the individual cells, even if the source images lack the resolution to show these boundaries clearly.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.