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An improved procedure for subcellular spatial alignment during live-cell CLEM.

ABSTRACT: Live-cell correlative light and electron microscopy (CLEM) offers unique insights into the ultrastructure of dynamic cellular processes. A critical and technically challenging part of CLEM is the 3-dimensional relocation of the intracellular region of interest during sample processing. We have developed a simple CLEM procedure that uses toner particles from a laser printer as orientation marks. This facilitates easy tracking of a region of interest even by eye throughout the whole procedure. Combined with subcellular fluorescence markers for the plasma membrane and nucleus, the toner particles allow for precise subcellular spatial alignment of the optical and electron microscopy data sets. The toner-based reference grid is printed and transferred onto a polymer film using a standard office printer and laminator. We have also designed a polymer film holder that is compatible with most inverted microscopes, and have validated our strategy by following the ultrastructure of mitochondria that were selectively photo-irradiated during live-cell microscopy. In summary, our inexpensive and robust CLEM procedure simplifies optical imaging, without limiting the choice of optical microscope.

SUBMITTER: Padman BS

PROVIDER: S-EPMC3995996 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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An improved procedure for subcellular spatial alignment during live-cell CLEM.

Padman Benjamin S BS Bach Markus M Ramm Georg G

PloS one 20140422 4

Live-cell correlative light and electron microscopy (CLEM) offers unique insights into the ultrastructure of dynamic cellular processes. A critical and technically challenging part of CLEM is the 3-dimensional relocation of the intracellular region of interest during sample processing. We have developed a simple CLEM procedure that uses toner particles from a laser printer as orientation marks. This facilitates easy tracking of a region of interest even by eye throughout the whole procedure. Com ...[more]

PMID: 24755651

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Project description:BackgroundBinding of peptides to Major Histocompatibility class II (MHC-II) molecules play a central role in governing responses of the adaptive immune system. MHC-II molecules sample peptides from the extracellular space allowing the immune system to detect the presence of foreign microbes from this compartment. Predicting which peptides bind to an MHC-II molecule is therefore of pivotal importance for understanding the immune response and its effect on host-pathogen interactions. The experimental cost associated with characterizing the binding motif of an MHC-II molecule is significant and large efforts have therefore been placed in developing accurate computer methods capable of predicting this binding event. Prediction of peptide binding to MHC-II is complicated by the open binding cleft of the MHC-II molecule, allowing binding of peptides extending out of the binding groove. Moreover, the genes encoding the MHC molecules are immensely diverse leading to a large set of different MHC molecules each potentially binding a unique set of peptides. Characterizing each MHC-II molecule using peptide-screening binding assays is hence not a viable option.ResultsHere, we present an MHC-II binding prediction algorithm aiming at dealing with these challenges. The method is a pan-specific version of the earlier published allele-specific NN-align algorithm and does not require any pre-alignment of the input data. This allows the method to benefit also from information from alleles covered by limited binding data. The method is evaluated on a large and diverse set of benchmark data, and is shown to significantly out-perform state-of-the-art MHC-II prediction methods. In particular, the method is found to boost the performance for alleles characterized by limited binding data where conventional allele-specific methods tend to achieve poor prediction accuracy.ConclusionsThe method thus shows great potential for efficient boosting the accuracy of MHC-II binding prediction, as accurate predictions can be obtained for novel alleles at highly reduced experimental costs. Pan-specific binding predictions can be obtained for all alleles with know protein sequence and the method can benefit by including data in the training from alleles even where only few binders are known. The method and benchmark data are available at http://www.cbs.dtu.dk/services/NetMHCIIpan-2.0.

Dataset Information

An improved procedure for subcellular spatial alignment during live-cell CLEM.

Publications

An improved procedure for subcellular spatial alignment during live-cell CLEM.

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