Dataset Information

SVD-clustering, a general image-analyzing method explained and demonstrated on model and Raman micro-spectroscopic maps.

ABSTRACT: An image analyzing method (SVD-clustering) is presented. Amplitude vectors of SVD factorization (V1…Vi) were introduced into the imaging of the distribution of the corresponding Ui basis-spectra. Since each Vi vector contains each point of the map, plotting them along the X, Y, Z dimensions of the map reconstructs the spatial distribution of the corresponding Ui basis-spectrum. This gives valuable information about the first, second, etc. higher-order deviations present in the map. We extended SVD with a clustering method, using the significant Vi vectors from the VT matrix as coordinates of image points in a ne-dimensional space (ne is the effective rank of the data matrix). This way every image point had a corresponding coordinate in the ne-dimensional space and formed a point set. Clustering was applied to this point set. SVD-clustering is universal; it is applicable to any measurement where data are recorded as a function of an external parameter (time, space, temperature, concentration, species, etc.). Consequently, our method is not restricted to spectral imaging, it can find application in many different 2D and 3D image analyses. Using SVD-clustering, we have shown on models the theoretical possibilities and limitations of the method, especially in the context of creating, meaning/interpreting of cluster spectra. Then for real-world samples, two examples are presented, where we were able to reveal minute alterations in the samples (changing cation ratios in minerals, differently structured cellulose domains in plant root) with spatial resolution.

SUBMITTER: Szalontai B

PROVIDER: S-EPMC7060257 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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SVD-clustering, a general image-analyzing method explained and demonstrated on model and Raman micro-spectroscopic maps.

Szalontai B B Debreczeny M M Fintor K K Bagyinka Cs C

Scientific reports 20200306 1

An image analyzing method (SVD-clustering) is presented. Amplitude vectors of SVD factorization (V1…Vi) were introduced into the imaging of the distribution of the corresponding Ui basis-spectra. Since each Vi vector contains each point of the map, plotting them along the X, Y, Z dimensions of the map reconstructs the spatial distribution of the corresponding Ui basis-spectrum. This gives valuable information about the first, second, etc. hi ...[more]

PMID: 32144407

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Project description:In recent decades, Raman spectroscopy has entered the biological and medical fields. It enables nondestructive analysis of structural details at the molecular level and has been used to study viruses and their constituents. Here, we used Raman spectroscopy to study echovirus 1 (EV1), a small, nonenveloped human pathogen, in two different uncoating states induced by heat treatments. Raman signals of capsid proteins and RNA genome were observed from the intact virus, the uncoating intermediate, and disrupted virions. Transmission electron microscopy data revealed general structural changes between the studied particles. Compared to spectral characteristics of proteins in the intact virion, those of the proteins of the heat-treated particles indicated reduced ?-helix content with respect to ?-sheets and coil structures. Changes observed in tryptophan and tyrosine signals suggest an increasingly hydrophilic environment around these residues. RNA signals revealed a change in the environment of the genome and in its conformation. The ionized-carbonyl vibrations showed small changes between the intact virion and the uncoating intermediate, which points to cleavage of salt bridges in the protein structure during the uncoating process. In conclusion, our data reveal distinguishable Raman signatures of the intact, intermediate, and disrupted EV1 particles. These changes indicate structural, chemical, and solute-solvent alterations in the genome and in the capsid proteins and lay the essential groundwork for investigating the uncoating of EV1 and related viruses in real time.In order to combat virus infection, we need to know the details of virus uncoating. We present here the novel Raman signatures for opened and intact echovirus 1. This gives hope that the signatures may be used in the near future to evaluate the ambient conditions in endosomes leading to virus uncoating using, e.g., coherent anti-Stokes Raman spectroscopy (CARS) imaging. These studies will complement structural studies on virus uncoating. In addition, Raman/CARS imaging offers the possibility of making dynamic live measurements in vitro and in cells which are impossible to measure by, for example, cryo-electron tomography. Furthermore, as viral Raman spectra can be overwhelmed with various contaminants, our study is highly relevant in demonstrating the importance of sample preparation for Raman spectroscopy in the field of virology.

Dataset Information

SVD-clustering, a general image-analyzing method explained and demonstrated on model and Raman micro-spectroscopic maps.

Publications

SVD-clustering, a general image-analyzing method explained and demonstrated on model and Raman micro-spectroscopic maps.

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