Visualizing chemical structure-subcellular localization relationships using fluorescent small molecules as probes of cellular transport

Abstract

BackgroundTo study the chemical determinants of small molecule transport inside cells, it is crucial to visualize relationships between the chemical structure of small molecules and their associated subcellular distribution patterns. For this purpose, we experimented with cells incubated with a synthetic combinatorial library of fluorescent, membrane-permeant small molecule chemical agents. With an automated high content screening instrument, the intracellular distribution patterns of these chemical agents were microscopically captured in image data sets, and analyzed off-line with machine vision and cheminformatics algorithms. Nevertheless, it remained challenging to interpret correlations linking the structure and properties of chemical agents to their subcellular localization patterns in large numbers of cells, captured across large number of images.ResultsTo address this challenge, we constructed a Multidimensional Online Virtual Image Display (MOVID) visualization platform using off-the-shelf hardware and software components. For analysis, the image data set acquired from cells incubated with a combinatorial library of fluorescent molecular probes was sorted based on quantitative relationships between the chemical structures, physicochemical properties or predicted subcellular distribution patterns. MOVID enabled visual inspection of the sorted, multidimensional image arrays: Using a multipanel desktop liquid crystal display (LCD) and an avatar as a graphical user interface, the resolution of the images was automatically adjusted to the avatar’s distance, allowing the viewer to rapidly navigate through high resolution image arrays, zooming in and out of the images to inspect and annotate individual cells exhibiting interesting staining patterns. In this manner, MOVID facilitated visualization and interpretation of quantitative structure-localization relationship studies. MOVID also facilitated direct, intuitive exploration of the relationship between the chemical structures of the probes and their microscopic, subcellular staining patterns.ConclusionMOVID can provide a practical, graphical user interface and computer-assisted image data visualization platform to facilitate bioimage data mining and cheminformatics analysis of high content, phenotypic screening experiments.

Construction of an orthogonal ZnSalen/Salophen library as a colour palette for one- and two-photon live cell imaging

“…[1][2][3][4][5][6][7] In addition to the optical properties, subcellular organelle-specicity is another critical issue, which provides local information within intracellular regions of interest. 8,9 Thus, constructing a colour palette based on modular "core" dyes with tuneable emission and specic intracellular localizations is of importance to expand the repertoire of small molecular uorophores, and also to visualize and distinguish different organelles and even their intracellular cross-talking. [10][11][12][13] However, due to lack of structural information linking photophysical properties and the specicity of subcellular localizations, the modication of photophysical properties cannot always enable tailor-made specicity.…”

Designer nanoparticle: nanobiotechnology tool for cell biology

“…Similarly by isolating plasma membrane or endosomes, it is possible to generate proteomics, glycomics and lipidomics for these organelles [ 22 ]. By compiling obtained omics (proteomics, glycomics, and lipidomics), for different organelles, comprehensive whole cell omics can be generated both under native and altered conditions [ 23 – 26 ]. The key factor for generating comprehensive omics datasets s is to isolate subcellular compartments with high purity and yield.…”

Cellular localisation of structurally diverse diphenylacetylene fluorophores

“…11 Automated computational methods for analysing fluorescence images are also extremely beneficial for high-throughput work, for example in proteomics 12 or for analysis of combinatorial libraries of fluorescent compounds. 13 Predictive models for subcellular localisation are becoming increasingly beneficial for the design of new fluorophores, 14 and there is a great need for informative accounts of subcellular behaviour; the more structure-based imaging case-studies there are, the better informed we can be in making molecular design choices. 15 We recently reported a new class of diphenylacetylene that elicits cytotoxic activity when activated by UV, violet and corresponding two-photon near-IR irradiation.…”

“…H NMR (400 MHz, CDCl3) δ 1.53 (s, 9H), 3.22-3.28 (m, 4H), 3.38-3.45 (m, 4H), 6.37 (d, J = 15.9 Hz, 1H), 6.77 -6.95 (m, 2H), 7.33 -7.53 (m, 6H), 7.56 (d, J = 15.9 Hz, 1H);13 C NMR (176 MHz, CDCl3) δ 28.2, 80.6, 87.8, 92.2, 113.1, 115.2, 120.5, 125.5, 127.8, 127.8, 131.7, 132.8, 133.9, 142.7, 166.2; IR (ATR) vmax/cm -1 2967w, 2916w, 2830w, 2212w, 1687s, 1629m, 1595m, 1518m, 1326m, 1241m, 1159m, 1128m, 986m, 831s, 819s; MS(ASAP): m/z = 389.2 [M+H] + ; HRMS (ASAP) calcd. for C25H29N2O2 [M+H] + : 389.2229, found 389.2231. mL) was degassed by sparging with Ar for 1 h. Compound 10 (4.50 g, 15.6 mmol), compound 7a(3.05 g, 16.4 mmol), Pd(PPh3)2Cl2 (550 mg, 0.78 mmol) and CuI (150 mg, 0.78 mmol) were then added under Ar and the resultant suspension was stirred at 60 o C for 24 h. The solvent was then evaporated to give a crude solid which was purified by SiO2 chromatography (9:1, DCM/MeOH, 1% Et3N) and then recrystallisation from MeOH to give compound 3b as a yellow solid (2.74 g, 51%): 1 H NMR (600 MHz, DMSO-d6) δ 2.82-2.94 (m, 4H), 3.14-3.24 (m, 4H), 3.73 (s, 3H), 6.67 (d, J = 16.0 Hz, 1H), 6.94 (d, J = 8.4 Hz, 2H), 7.39 (d, J = 8.4 Hz, 2H), 7.52 (d, J = 8.0 Hz, 2H), 7.67 (d, J = 16.0 Hz, 1H), 7.74 (d, J = 8.0 Hz, 2H); 13 C NMR (151 MHz, DMSO-d6) δ 44.9, 47.5, 51.5, 87.6, 92.7, 110.7, 114.5, 118.3, 124.9, 128.6, 131.3, 132.5, 133.5, 143.6, 151.2, 166.6; IR (ATR) vmax/cm -1 3039w, 2952w, 2909w, 2830w, 2204w, 2173w, 1698s, 1630s, 1593m, 1518m, 1312m, 1243s, 1168s, 987m, 831s, 817s; MS(ASAP): m/z = 347.2 [M+H] + ; HRMS (ASAP) calcd.…”