Background: Sub-cellular structures interact in numerous direct and indirect ways in order to fulfill cellular functions. While direct molecular interactions crucially depend on spatial proximity, other interactions typically result in spatial correlations between the interacting structures. Such correlations are the target of microscopy-based co-localization analysis, which can provide hints of potential interactions. Two complementary approaches to co-localization analysis can be distinguished: intensity correlation methods capitalize on pattern discovery, whereas object-based methods emphasize detection power.
Results: We first reinvestigate the classical co-localization measure in the context of spatial point pattern analysis. This allows us to unravel the set of implicit assumptions inherent to this measure and to identify potential confounding factors commonly ignored. We generalize object-based co-localization analysis to a statistical framework involving spatial point processes. In this framework, interactions are understood as position co-dependencies in the observed localization patterns. The framework is based on a model of effective pairwise interaction potentials and the specification of a null hypothesis for the expected pattern in the absence of interaction. Inferred interaction potentials thus reflect all significant effects that are not explained by the null hypothesis. Our model enables the use of a wealth of well-known statistical methods for analyzing experimental data, as demonstrated on synthetic data and in a case study considering virus entry into live cells. We show that the classical co-localization measure typically under-exploits the information contained in our data.
Conclusions: We establish a connection between co-localization and spatial interaction of sub-cellular structures by formulating the object-based interaction analysis problem in a spatial statistics framework based on nearest-neighbor distance distributions. We provide generic procedures for inferring interaction strengths and quantifying their relative statistical significance from sets of discrete objects as provided by image analysis methods. Within our framework, an interaction potential can either refer to a phenomenological or a mechanistic model of a physico-chemical interaction process. This increased flexibility in designing and testing different hypothetical interaction models can be used to quantify the parameters of a specific interaction model or may catalyze the discovery of functional relations.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2919515 | PMC |
http://dx.doi.org/10.1186/1471-2105-11-372 | DOI Listing |
J Biol Chem
December 2024
Department of Molecular Biology and Biophysics, UCONN Health, Farmington, CT 06032, USA. Electronic address:
Nucleic Acids Res
December 2024
School of Physics and Astronomy, University of Edinburgh, Peter Guthrie Tait Road, Edinburgh EH9 3FD, UK.
All life forms are miraculous, but some are more inexplicable than others. Trypanosomes are by far one of the most puzzling organisms on Earth: their mitochondrial genome, also called kinetoplast DNA (kDNA) forms an Olympic-ring-like network of interlinked DNA circles, challenging conventional paradigms in both biology and physics. In this review, I will discuss kDNA from the astonished perspective of a polymer physicist and tell a story of how a single sub-cellular structure from a blood-dwelling parasite is inspiring generations of polymer chemists and physicists to create new catenated materials.
View Article and Find Full Text PDFAging Cell
December 2024
Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, USA.
Senescent osteocytes are key contributors to age-related bone loss and fragility; however, the impact of mechanobiological changes in these cells remains poorly understood. This study provides a novel analysis of these changes in primary osteocytes following irradiation-induced senescence. By integrating subcellular mechanical measurements with gene expression analyses, we identified significant, time-dependent alterations in the mechanical properties of senescent bone cells.
View Article and Find Full Text PDFimaging of dynamic sub-cellular brain structures in is key to understanding several phenomena in neuroscience. However, a trade-off between spatial resolution, speed, photodamage, and setup complexity limits its implementation. Here, we designed and built a single objective light sheet microscope, customized for imaging of adult flies and optimized for maximum resolution.
View Article and Find Full Text PDFActa Neuropathol
November 2024
Department of Translational Neuroscience, University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, 3584 CG, Utrecht, The Netherlands.
Mesial temporal lobe epilepsy (mTLE) is a debilitating disease characterized by recurrent seizures originating from temporal lobe structures such as the hippocampus. The pathogenic mechanisms underlying mTLE are incompletely understood but include changes in the expression of non-coding RNAs in affected brain regions. Previous work indicates that some of these changes may be selective to specific sub-cellular compartments, but the full extent of these changes and how these sub-cellular compartments themselves are affected remains largely unknown.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!