Dataset Information

Phasor Analysis of Local ICS Detects Heterogeneity in Size and Number of Intracellular Vesicles.

ABSTRACT: Organelles represent the scale of organization immediately below that of the cell itself, and their composition, size, and number are tailored to their function. Monitoring the size and number of organelles in live cells is relevant for many applications but can be challenging due to their highly heterogeneous properties. Image correlation spectroscopy is a well-established analysis method capable of extracting the average size and number of particles in images. However, when image correlation spectroscopy is applied to a highly heterogeneous system, it can fail to retrieve, from a single correlation function, the characteristic size and the relative amount associated to each subspecies. Here, we describe a fast, unbiased, and fit-free algorithm based on the phasor analysis of multiple local image correlation functions, capable of mapping the sizes of elements contained in a heterogeneous system. The method correctly provides the size and number of separate subspecies, which otherwise would be hidden in the average properties of a single correlation function. We apply the method to quantify the spatial and temporal heterogeneity in the size and number of intracellular vesicles formed after endocytosis in live cells.

SUBMITTER: Scipioni L

PROVIDER: S-EPMC4982927 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Phasor Analysis of Local ICS Detects Heterogeneity in Size and Number of Intracellular Vesicles.

Scipioni Lorenzo L Gratton Enrico E Diaspro Alberto A Lanzanò Luca L

Biophysical journal 20160801 3

Organelles represent the scale of organization immediately below that of the cell itself, and their composition, size, and number are tailored to their function. Monitoring the size and number of organelles in live cells is relevant for many applications but can be challenging due to their highly heterogeneous properties. Image correlation spectroscopy is a well-established analysis method capable of extracting the average size and number of particles in images. However, when image correlation s ...[more]

PMID: 27508445

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Project description:BackgroundIt has been an abiding belief among geneticists that multicellular organisms' genomes can be analyzed under the assumption that a single individual has a uniform genome in all its cells. Despite some evidence to the contrary, this belief has been used as an axiomatic assumption in most genome analysis software packages. In this paper we present observations in human whole genome data, human whole exome data and in mouse whole genome data to challenge this assumption. We show that heterogeneity is in fact ubiquitous and readily observable in ordinary Next Generation Sequencing (NGS) data.ResultsStarting with the assumption that a single NGS read (or read pair) must come from one haplotype, we built a procedure for directly observing haplotypes at a local level by examining 2 or 3 adjacent single nucleotide polymorphisms (SNPs) which are close enough on the genome to be spanned by individual reads. We applied this procedure to NGS data from three different sources: whole genome of a Central European trio from the 1000 genomes project, whole genome data from laboratory-bred strains of mouse, and whole exome data from a set of patients of head and neck tumors. Thousands of loci were found in each genome where reads spanning 2 or 3 SNPs displayed more than two haplotypes, indicating that the locus is heterogeneous. We show that such loci are ubiquitous in the genome and cannot be explained by segmental duplications. We explain them on the basis of cellular heterogeneity at the genomic level. Such heterogeneous loci were found in all normal and tumor genomes examined.ConclusionsOur results highlight the need for new methods to analyze genomic variation because existing ones do not systematically consider local haplotypes. Identification of cancer somatic mutations is complicated because of tumor heterogeneity. It is further complicated if, as we show, normal tissues are also heterogeneous. Methods for biomarker discovery must consider contextual haplotype information rather than just whether a variant "is present".

Dataset Information

Phasor Analysis of Local ICS Detects Heterogeneity in Size and Number of Intracellular Vesicles.

Publications

Phasor Analysis of Local ICS Detects Heterogeneity in Size and Number of Intracellular Vesicles.

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