Subcellular Euclidean distance measurements with multicolor fluorescence localization imaging in cultured cells

Germanova, Tsvetelina E.; Roscioli, Emanuele; Harrison, Jonathan U.; McAinsh, Andrew D.; Burroughs, Nigel John

doi:10.1016/j.xpro.2021.100774

Cited by 2 publications

(14 citation statements)

References 8 publications

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“…For pair-wise inferences the likelihood with isotropic measurement errors is analytically tractable (Eq (6) in [6]); we can thus determine the posterior (assuming the same flat priors we use for the pair-wise method) and therefore calculate the posterior mean ("means" in Table 1). This estimate, and the pair-wise based Bayesian inference method [9] give near identical results (as expected as they share the same assumptions apart from the extra degree of freedom of [9] for anisotropic measurement errors). For the small length jX 3 − X 2 j, the pair-wise based posterior has a long thick tail towards zero, see Fig 3a and 3c, indicating large uncertainty.…”

Section: Algorithm Performance On Simulated Datasupporting

confidence: 64%

“…Correction of chromatic aberration within the Bayesian inference model would also be possible and allow the variance PLOS COMPUTATIONAL BIOLOGY associated with this effect to be estimated. This flexible approach does however come with longer run-times compared to the pair-wise methods ( [6,9]). The run-time of the single-state simulated Example 1.1 (N = 400 measurements and 100, 000 Markov chain iterations) was about 2 days on a standard desktop computer (with enough threads to run five independent chains in parallel).…”

Section: Discussionmentioning

confidence: 99%

“…comparing consistency for the posterior length that is common to different triplets (specifically Ndc80C-Ndc80N), iii. comparing with the pair-wise method of [9], see Table 3 In fact, even the pair-wise posterior means violate the triangle inequality in this case, indicating it is not possible to construct a joint triangle distribution that preserves the pair-wise length marginals (see Triangle length means never violate the triangle inequality in S1 Text for why no triangle distribution exists that has (marginals with) means violating the triangle inequality). This improvement for smaller lengths is also seen for Ndc80N-Ndc80C in nocodazole, the posterior under the triangle correction has a substantial peak whilst the pair-wise correction has a thick tail towards zero, Fig 7. This is analogous to the thick tails seen in simulated data for small length inference.…”

Section: Analysis Of the Human Kinetochore: A Structured Macro-molecu...mentioning

confidence: 97%

“…. ., J}; previous pair-wise methods also assume Gaussian errors, [6] (isotropic) and [9] (anisotropic). Note, that only the shape of the measurement error is assumed; σ j;xy , σ j;z are to be inferred.…”

Section: Model Assumptionsmentioning

confidence: 99%

“…Examples 1.2-1.6 in Table 1 are for anisotropic measurement errors. There are only two methods available for anisotropic errors: our triangle correction and the pair-wise Bayesian method [9]. These two methods give consistent results, but the triangle method typically has PLOS COMPUTATIONAL BIOLOGY lower posterior variance, particularly for the short lengths.…”

Section: Algorithm Performance On Simulated Datamentioning

confidence: 99%

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Bayesian inference of multi-point macromolecular architecture mixtures at nanometre resolution

et al. 2022

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Gaussian spot fitting methods have significantly extended the spatial range where fluorescent microscopy can be used, with recent techniques approaching nanometre (nm) resolutions. However, small inter-fluorophore distances are systematically over-estimated for typical molecular scales. This bias can be corrected computationally, but current algorithms are limited to correcting distances between pairs of fluorophores. Here we present a flexible Bayesian computational approach that infers the distances and angles between multiple fluorophores and has several advantages over these previous methods. Specifically it improves confidence intervals for small lengths, estimates measurement errors of each fluorophore individually and infers the correlations between polygon lengths. The latter is essential for determining the full multi-fluorophore 3D architecture. We further developed the algorithm to infer the mixture composition of a heterogeneous population of multiple polygon states. We use our algorithm to analyse the 3D architecture of the human kinetochore, a macro-molecular complex that is essential for high fidelity chromosome segregation during cell division. Using triple fluorophore image data we unravel the mixture of kinetochore states during human mitosis, inferring the conformation of microtubule attached and unattached kinetochores and their proportions across mitosis. We demonstrate that the attachment conformation correlates with intersister tension and sister alignment to the metaphase plate.

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Section: Algorithm Performance On Simulated Datasupporting

confidence: 64%

Section: Discussionmentioning

confidence: 99%

Section: Analysis Of the Human Kinetochore: A Structured Macro-molecu...mentioning

confidence: 97%

Section: Model Assumptionsmentioning

confidence: 99%

Section: Algorithm Performance On Simulated Datamentioning

confidence: 99%

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Bayesian inference of multi-point macromolecular architecture mixtures at nanometre resolution

et al. 2022

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Bayesian inference of multi-point macromolecular architecture mixtures at nanometre resolution

Embacher

Germanova

Roscioli

et al. 2021

Preprint

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Gaussian spot fitting methods have significantly extended the spatial range where fluorescent microscopy can be used, with recent techniques approaching nanometre (nm) resolutions. However, small inter-fluorophore distances are systematically over-estimated for typical molecular scales (≲ 50nm). This bias can be corrected computationally, but current algorithms are limited to correcting distances between pairs of fluorophores. Here we present a flexible Bayesian computational approach that infers the distances and angles between multiple markers and has several advantages over these previous methods. Specifically it improves confidence intervals for small lengths, estimates measurement errors of each fluorescent marker individually and infers the correlations between polygon lengths. The latter is essential for determining the full multi-fluorophore 3D architecture. We further developed the algorithm to infer the mixture composition of a heterogeneous population of multiple polygon states. We use our algorithm to analyse the 3D architecture of the human kinetochore, a macro-molecular complex that is essential for high fidelity cell division. We examine the conformational change induced by microtubule attachment using triple fluorophore marked data and demonstrate for the first time that in metaphase kinetochore conformation is heterogeneous.

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Subcellular Euclidean distance measurements with multicolor fluorescence localization imaging in cultured cells

Cited by 2 publications

References 8 publications

Bayesian inference of multi-point macromolecular architecture mixtures at nanometre resolution

Bayesian inference of multi-point macromolecular architecture mixtures at nanometre resolution

Bayesian inference of multi-point macromolecular architecture mixtures at nanometre resolution

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