Dataset Information

Extracting Subcellular Fibrillar Alignment with Error Estimation: Application to Microtubules.

ABSTRACT: The order and orientation of cortical microtubule (CMT) arrays and their dynamics play an essential role in plant morphogenesis. To extract detailed CMT alignment structures in an objective, local, and accurate way, we propose an error-based extraction method that applies to general fluorescence intensity data on three-dimensional cell surfaces. Building on previous techniques to quantify alignments, our method can determine the statistical error for specific local regions, or the minimal scales of local regions for a desired accuracy goal. After validating our method with synthetic images with known alignments, we demonstrate the ability of our method to quantify subcellular CMT alignments on images with microtubules marked with green fluorescent protein in various cell types. Our method could also be applied to detect alignment structures in other fibrillar elements, such as actin filaments, cellulose, and collagen.

SUBMITTER: Tsugawa S

PROVIDER: S-EPMC4850328 | biostudies-other | 2016 Apr

REPOSITORIES: biostudies-other

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Publications

Extracting Subcellular Fibrillar Alignment with Error Estimation: Application to Microtubules.

Tsugawa Satoru S Hervieux Nathan N Hamant Oliver O Boudaoud Arezki A Smith Richard S RS Li Chun-Biu CB Komatsuzaki Tamiki T

Biophysical journal 20160401 8

The order and orientation of cortical microtubule (CMT) arrays and their dynamics play an essential role in plant morphogenesis. To extract detailed CMT alignment structures in an objective, local, and accurate way, we propose an error-based extraction method that applies to general fluorescence intensity data on three-dimensional cell surfaces. Building on previous techniques to quantify alignments, our method can determine the statistical error for specific local regions, or the minimal scales ...[more]

PMID: 27119643

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Project description:Measuring the organisation of the cellular cytoskeleton and the surrounding extracellular matrix (ECM) is currently of wide interest as changes in both local and global alignment can highlight alterations in cellular functions and material properties of the extracellular environment. Different approaches have been developed to quantify these structures, typically based on fibre segmentation or on matrix representation and transformation of the image, each with its own advantages and disadvantages. Here we present AFT-Alignment by Fourier Transform, a workflow to quantify the alignment of fibrillar features in microscopy images exploiting 2D Fast Fourier Transforms (FFT). Using pre-existing datasets of cell and ECM images, we demonstrate our approach and compare and contrast this workflow with two other well-known ImageJ algorithms to quantify image feature alignment. These comparisons reveal that AFT has a number of advantages due to its grid-based FFT approach. 1) Flexibility in defining the window and neighbourhood sizes allows for performing a parameter search to determine an optimal length scale to carry out alignment metrics. This approach can thus easily accommodate different image resolutions and biological systems. 2) The length scale of decay in alignment can be extracted by comparing neighbourhood sizes, revealing the overall distance that features remain anisotropic. 3) The approach is ambivalent to the signal source, thus making it applicable for a wide range of imaging modalities and is dependent on fewer input parameters than segmentation methods. 4) Finally, compared to segmentation methods, this algorithm is computationally inexpensive, as high-resolution images can be evaluated in less than a second on a standard desktop computer. This makes it feasible to screen numerous experimental perturbations or examine large images over long length scales. Implementation is made available in both MATLAB and Python for wider accessibility, with example datasets for single images and batch processing. Additionally, we include an approach to automatically search parameters for optimum window and neighbourhood sizes, as well as to measure the decay in alignment over progressively increasing length scales.

Dataset Information

Extracting Subcellular Fibrillar Alignment with Error Estimation: Application to Microtubules.

Publications

Extracting Subcellular Fibrillar Alignment with Error Estimation: Application to Microtubules.

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