A call for public archives for biological image data

Ellenberg, Jan; Swedlow, Jason R.; Barlow, Mary; Cook, Charles E.; Sarkans, Ugis; Patwardhan, Ardan; Brāzma, Alvis; Birney, Ewan

doi:10.1038/s41592-018-0195-8

Cited by 107 publications

(109 citation statements)

References 32 publications

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“…At least 10 3D dSTORM images were acquired in each imaging medium for both dyes (AF647 and AF(+)647), and for all targets, tubulin β3, NfL and βII spectrin. Raw image data used for dSTORM quantification are available in the BioImage Archive 26,27 (http://www.ebi.ac.uk/bioimage-archive) under accession number S-BIAD16.…”

Section: Scientific Reports |mentioning

confidence: 99%

Effect of Vectashield-induced fluorescence quenching on conventional and super-resolution microscopy

Arsić

Stajković

Spiegel

2020

Sci Rep

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Finding the right combination of a fluorescent dye and a mounting medium is crucial for optimal microscopy of fixed samples. It was recently shown that Vectashield, one of the most commonly used mounting media for conventional microscopy, can also be applied to super-resolution direct stochastic optical reconstruction microscopy (dSTORM). dSTORM utilizes conventional dyes and starts with samples in a fluorescent "ON" state. This helps in identifying structures of interest. Subsequently, labelled samples are induced into blinking, which is necessary for determining the position of single molecules and reconstruction of super-resolution images. This is only possible with certain fluorescent dyes and imaging buffers. One of the most widely used dyes for dSTORM, Alexa Fluor 647 (AF647), blinks in Vectashield. However, after preparing immunocytochemical samples in Vectashield, we noticed that the fluorescence intensity of AF647 is quenched. This is particularly evident for dimmer immunostainings, such as stainings of some components of neuronal cytoskeleton and axonal initial segment. Because structures of interest cannot be identified in quenched samples, loss of fluorescence intensity hinders imaging of AF647 in Vectashield. This has consequences for both conventional and dSTORM imaging. To overcome this, we provide: 1) a quantitative analysis of AF647 intensity in different imaging media, 2) a quantitative analysis of the suitability of Vectashield for dSTORM imaging of high and low-abundance AF647-labelled targets. Furthermore, for the first time, we quantitatively analyse the performance of Alexa Fluor Plus 647, a new variant of AF647-conjugated antibody, in dSTORM imaging.Super-resolution microscopy (SRM) provides unique insights into the subcellular organisation of cells and tissues. Several techniques have been developed to make nanoscale imaging possible 1-4 . Single-molecule localisation techniques, such as photoactivated localisation microscopy (PALM) 5 , fluorescence photoactivation localisation microscopy (FPALM) 6 , stochastic optical reconstruction microscopy (STORM) 7 and direct stochastic optical reconstruction microscopy (dSTORM) 8 rely on temporal separation of fluorescence emission. Temporal separation is achieved by blinking, which separates individual fluorescent molecules not only in time, but also in space. The resulting spatiotemporal separation of fluorescence emission enables precise determination of the location of fluorescent molecules, which is necessary to reconstruct SRM images 7,9 . Whereas PALM and FPALM utilize genetically engineered fluorescent proteins, dSTORM relies on synthetic fluorophores (dyes). To achieve blinking in dSTORM, dye molecules are switched to a dark "OFF" state from which they stochastically and spontaneously recover to a fluorescent "ON" state, multiple times before bleaching. Blinking can be induced in certain dyes by using strong lasers and particular imaging buffers, such as thiol-containing reducing agents (e.g. β-mercaptoethanol) with or without enzymatic ox...

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Section: Scientific Reports |mentioning

confidence: 99%

Effect of Vectashield-induced fluorescence quenching on conventional and super-resolution microscopy

Arsić

Stajković

Spiegel

2020

Sci Rep

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“…The user selects a workflow (3) to process the images, and sets its parameters (4) before running it. Finally the results can be visualized overlaid on the original images (5), and benchmark metrics are reported as overall statistics for all the images or per image (6).…”

Section: Resultsmentioning

confidence: 99%

“…Overall, this does not only impair the reusability of the methods and impede reproducing published results [5], but it also makes it difficult to adapt these methods to process similar image datasets. To improve this situation, scientific datasets are now increasingly made publicly available through web-based software [6][7] [8] and open data initiatives [9], but existing web platforms do not systematically offer advanced features such as the ability to remotely view multidimensional microscopy images, process the images online by remotely launching image analysis workflows, and compare the results of the methods against a ground-truth reference (a.k.a. benchmarking).…”

Section: Introductionmentioning

confidence: 99%

BIAFLOWS: A collaborative framework to reproducibly deploy and benchmark bioimage analysis workflows

Rubens

Mormont

Baecker

et al. 2019

Preprint

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Automated image analysis has become key to extract quantitative information from biological microscopy images, however the methods involved are now often so complex that they can no longer be unambiguously described using written protocols. We introduce BIAFLOWS, a web based framework to encapsulate, deploy, and benchmark automated bioimage analysis workflows (the software implementation of an image analysis method). BIAFLOWS helps fairly comparing image analysis workflows and reproducibly disseminating them, hence safeguarding research based on their results and promoting the highest quality standards in bioimage analysis.

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“…In particular, this effort will be important for imaging modalities for which this standard is not in use now and information is not automatically filled in, or for thirdparty software or home-made methods to compute the spatial transformation that link two images or volumes. For this reason, there is ongoing effort associated with the deployment of public image archive [139][140][141] to define some minimal metadata requirement, and the one associated with CMI have still to be defined by the community.…”

Section: Correlation Softwarementioning

confidence: 99%

Correlated Multimodal Imaging in Life Sciences: Expanding the Biomedical Horizon

et al. 2020

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A call for public archives for biological image data

Cited by 107 publications

References 32 publications

Effect of Vectashield-induced fluorescence quenching on conventional and super-resolution microscopy

Effect of Vectashield-induced fluorescence quenching on conventional and super-resolution microscopy

BIAFLOWS: A collaborative framework to reproducibly deploy and benchmark bioimage analysis workflows

Correlated Multimodal Imaging in Life Sciences: Expanding the Biomedical Horizon

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