Density Distribution Maps: A Novel Tool for Subcellular Distribution Analysis and Quantitative Biomedical Imaging

Subcellular spatial location is an essential descriptor of molecules biological function. Presently, super-resolution microscopy techniques enable quantification of subcellular objects distribution in fluorescence images, but they rely on instrumentation, tools and expertise not constituting a default for most of laboratories. We propose a method that allows resolving subcellular structures location by reinforcing each single pixel position with the information from surroundings. Although designed for entry-level laboratory equipment with common resolution powers, our method is independent from imaging device resolution, and thus can benefit also super-resolution microscopy. The approach permits to generate density distribution maps (DDMs) informative of both objects’ absolute location and self-relative displacement, thus practically reducing location uncertainty and increasing the accuracy of signal mapping. This work proves the capability of the DDMs to: (a) improve the informativeness of spatial distributions; (b) empower subcellular molecules distributions analysis; (c) extend their applicability beyond mere spatial object mapping. Finally, the possibility of enhancing or even disclosing latent distributions can concretely speed-up routine, large-scale and follow-up experiments, besides representing a benefit for all spatial distribution studies, independently of the image acquisition resolution. DDMaker, a Software endowed with a user-friendly Graphical User Interface (GUI), is also provided to support users in DDMs creation.

[1]  M. Chorilli,et al.  Characteristics, Properties and Analytical Methods of Paclitaxel: A Review , 2018, Critical reviews in analytical chemistry.

[2]  Ian M. Dobbie,et al.  Imaging cellular structures in super-resolution with SIM, STED and Localisation Microscopy: A practical comparison , 2016, Scientific Reports.

[3]  Vyacheslav V. Lyashenko,et al.  The methodology of wavelet analysis as a tool for cytology preparations image processing , 2016 .

[4]  Yunpeng Li,et al.  CIDRE: an illumination-correction method for optical microscopy , 2015, Nature Methods.

[5]  Wolfgang Link,et al.  Protein localization in disease and therapy , 2011, Journal of Cell Science.

[6]  Hong-Bin Shen,et al.  Bioimage-based protein subcellular location prediction: a comprehensive review , 2018, Frontiers of Computer Science.

[7]  Conor L Evans,et al.  Biomedical Image Processing with Containers and Deep Learning: An Automated Analysis Pipeline , 2019, BioEssays : news and reviews in molecular, cellular and developmental biology.

[8]  Penghui Zhang,et al.  Recent advances in drug release monitoring , 2019, Nanophotonics.

[9]  Jean-Baptiste Sibarita,et al.  Single molecule localisation microscopy reveals how HIV-1 Gag proteins sense membrane virus assembly sites in living host CD4 T cells , 2018, Scientific Reports.

[10]  Domingos Vieira,et al.  Preclinical Imaging: an Essential Ally in Modern Biosciences , 2013, Molecular Diagnosis & Therapy.

[11]  Emma Lundberg,et al.  Immunofluorescence and fluorescent-protein tagging show high correlation for protein localization in mammalian cells , 2013, Nature Methods.

[12]  A. Tesei,et al.  In vitro irradiation system for radiobiological experiments , 2013, Radiation Oncology.

[13]  Hanbing Deng,et al.  Depth Density Achieves a Better Result for Semantic Segmentation with the Kinect System , 2020, Sensors.

[14]  B. Fu,et al.  Investigation of Endothelial Surface Glycocalyx Components and Ultrastructure by Single Molecule Localization Microscopy: Stochastic Optical Reconstruction Microscopy (STORM) , 2018, The Yale journal of biology and medicine.

[15]  Howard Y. Chang,et al.  Long noncoding RNAs and human disease. , 2011, Trends in cell biology.

[16]  Xijing Liang,et al.  Establishment of a Customizable Fluorescent Probe Platform for the Organelle-targeted Bioactive Species Detection. , 2020, ACS sensors.

[17]  Juliette Griffié,et al.  Quantitative fibre analysis of single-molecule localization microscopy data , 2018, Scientific Reports.

[18]  C. Mony,et al.  Additive effects of connectivity provided by different habitat types drive plant assembly , 2019, Scientific Reports.

[19]  A. Shiras,et al.  Effective Visualization and Easy Tracking of Extracellular Vesicles in Glioma Cells , 2019, Biological Procedures Online.

[20]  Seong Ho Kang,et al.  Toward Sub-Diffraction Imaging of Single-DNA Molecule Sensors Based on Stochastic Switching Localization Microscopy , 2020, Sensors.

[21]  Xiangyong Li,et al.  Dynamics of Ras Complexes Observed in Living Cells , 2012, Sensors.

[22]  V. Rotter,et al.  Conditional RNA interference in vivo to study mutant p53 oncogenic gain of function on tumor malignancy , 2008, Cell cycle.

[23]  Talley J. Lambert,et al.  Navigating challenges in the application of superresolution microscopy , 2017, The Journal of cell biology.

[24]  Caroline Laplante,et al.  Building the contractile ring from the ground up: a lesson in perseverance and scientific creativity , 2018, Biophysical Reviews.

[25]  A. Iacoangeli,et al.  BC RNA Mislocalization in the Fragile X Premutation , 2018, eNeuro.

[26]  Muhammad Attique,et al.  Analytical Study of Hybrid Techniques for Image Encryption and Decryption , 2020, Sensors.

[27]  Christopher M. Warner,et al.  Interplay between Convective and Viscoelastic Forces Controls the Morphology of In Vitro Paclitaxel-Stabilized Microtubules , 2020, Crystals.

[28]  Jack Hu,et al.  Diverse and pervasive subcellular distributions for both coding and long noncoding RNAs , 2016, Genes & development.

[29]  N. Carragher,et al.  Developments in preclinical cancer imaging: innovating the discovery of therapeutics , 2014, Nature Reviews Cancer.

[30]  P. Rigby,et al.  Visualisation of Multiple Tight Junctional Complexes in Human Airway Epithelial Cells , 2018, Biological Procedures Online.

[31]  G. Lukács,et al.  Quality control for unfolded proteins at the plasma membrane , 2010, The Journal of cell biology.

[32]  Tao Chen,et al.  Characterization of the subcellular localization of Epstein-Barr virus encoded proteins in live cells , 2017, Oncotarget.

[33]  G. Sotgiu,et al.  Functionalized Keratin as Nanotechnology-Based Drug Delivery System for the Pharmacological Treatment of Osteosarcoma , 2018, International journal of molecular sciences.

[34]  Hossein Azizpour,et al.  Phenotypic Image Analysis Software Tools for Exploring and Understanding Big Image Data from Cell-Based Assays. , 2018, Cell systems.

[35]  Christophe Zimmer,et al.  A computational framework to study sub-cellular RNA localization , 2018, Nature Communications.

[36]  Wei Li,et al.  Automated defect analysis in electron microscopic images , 2018, npj Computational Materials.

[37]  Akos Vertes,et al.  Subcellular Peptide Localization in Single Identified Neurons by Capillary Microsampling Mass Spectrometry , 2018, Scientific Reports.

[38]  A. Bevilacqua,et al.  Reliable measurement of E. coli single cell fluorescence distribution using a standard microscope set-up , 2017, Journal of biological engineering.

[39]  James M. Hogan,et al.  Visualization of Biomedical Data , 2018, Annual Review of Biomedical Data Science.

[40]  Maximilian T. Strauss,et al.  Molecular mechanism to recruit galectin-3 into multivesicular bodies for polarized exosomal secretion , 2018, Proceedings of the National Academy of Sciences.

[41]  J. Bewersdorf,et al.  Biological Insight from Super-Resolution Microscopy: What We Can Learn from Localization-Based Images. , 2018, Annual review of biochemistry.