Quantitative single-molecule microscopy reveals that CENP-A(Cnp1) deposition occurs during G2 in fission yeast

The inheritance of the histone H3 variant CENP-A in nucleosomes at centromeres following DNA replication is mediated by an epigenetic mechanism. To understand the process of epigenetic inheritance, or propagation of histones and histone variants, as nucleosomes are disassembled and reassembled in living eukaryotic cells, we have explored the feasibility of exploiting photo-activated localization microscopy (PALM). PALM of single molecules in living cells has the potential to reveal new concepts in cell biology, providing insights into stochastic variation in cellular states. However, thus far, its use has been limited to studies in bacteria or to processes occurring near the surface of eukaryotic cells. With PALM, one literally observes and 'counts' individual molecules in cells one-by-one and this allows the recording of images with a resolution higher than that determined by the diffraction of light (the so-called super-resolution microscopy). Here, we investigate the use of different fluorophores and develop procedures to count the centromere-specific histone H3 variant CENP-A(Cnp1) with single-molecule sensitivity in fission yeast (Schizosaccharomyces pombe). The results obtained are validated by and compared with ChIP-seq analyses. Using this approach, CENP-A(Cnp1) levels at fission yeast (S. pombe) centromeres were followed as they change during the cell cycle. Our measurements show that CENP-A(Cnp1) is deposited solely during the G2 phase of the cell cycle

A Breast Cancer Meta-Analysis of Two Expression Measures of Chromosomal Instability Reveals a Relationship with Younger Age at Diagnosis and High Risk Histopathological Variables

Breast cancer in younger patients often presents with adverse histopathological features, including increased frequency of estrogen receptor negative and lymph node positive disease status. Chromosomal instability (CIN) is increasingly recognised as an important prognostic variable in solid tumours. In a breast cancer meta-analysis of 2423 patients we examine the relationship between clinicopathological parameters and two distinct chromosomal instability gene expression signatures in order to address whether younger age at diagnosis is associated with increased tumour genome instability. We find that CIN, assessed by the two independently derived CIN expression signatures, is significantly associated with increased tumour size, ER negative or HER2 positive disease, higher tumour grade and younger age at diagnosis in ER negative breast cancer. These data support the hypothesis that chromosomal instability may be a defining feature of breast cancer biology and clinical outcome

A breast cancer meta-analysis of two expression measures of chromosomal instability reveals a relationship with younger age at diagnosis and high risk histopathological variables

Breast cancer in younger patients often presents with adverse histopathological features, including increased frequency of estrogen receptor negative and lymph node positive disease status. Chromosomal instability (CIN) is increasingly recognised as an important prognostic variable in solid tumours. In a breast cancer meta-analysis of 2423 patients we examine the relationship between clinicopathological parameters and two distinct chromosomal instability gene expression signatures in order to address whether younger age at diagnosis is associated with increased tumour genome instability. We find that CIN, assessed by the two independently derived CIN expression signatures, is significantly associated with increased tumour size, ER negative or HER2 positive disease, higher tumour grade and younger age at diagnosis in ER negative breast cancer. These data support the hypothesis that chromosomal instability may be a defining feature of breast cancer biology and clinical outcome

Virtual-'light-sheet' single-molecule localisation microscopy enables quantitative optical sectioning for super-resolution imaging.

Single-molecule super-resolution microscopy allows imaging of fluorescently-tagged proteins in live cells with a precision well below that of the diffraction limit. Here, we demonstrate 3D sectioning with single-molecule super-resolution microscopy by making use of the fitting information that is usually discarded to reject fluorophores that emit from above or below a virtual-'light-sheet', a thin volume centred on the focal plane of the microscope. We describe an easy-to-use routine (implemented as an open-source ImageJ plug-in) to quickly analyse a calibration sample to define and use such a virtual light-sheet. In addition, the plug-in is easily usable on almost any existing 2D super-resolution instrumentation. This optical sectioning of super-resolution images is achieved by applying well-characterised width and amplitude thresholds to diffraction-limited spots that can be used to tune the thickness of the virtual light-sheet. This allows qualitative and quantitative imaging improvements: by rejecting out-of-focus fluorophores, the super-resolution image gains contrast and local features may be revealed; by retaining only fluorophores close to the focal plane, virtual-'light-sheet' single-molecule localisation microscopy improves the probability that all emitting fluorophores will be detected, fitted and quantitatively evaluated.We thank the Wellcome Trust for the PhD studentship of MP (093756/B/10/Z), and the Royal Society for the University Research Fellowship of SFL (UF120277). The work by SB and DL was also funded by the Wellcome Trust (082010/Z/07/Z). UE and MH acknowledge funding by the German Science Foundation (grants EXC 115 and SFB 902). SB is funded by a BBSRC grant (BB/K013726/1). AMC acknowledges ERC Award 268788-SMI-DDR. We also thank the European Commision for support through the 4DCellFate project (EC FP7 CP 277899).This is the final version of the article. It first appeared from PLOS via http://dx.doi.org/10.1371/journal.pone.012543

Studying Large Multi-Protein Complexes Using Single Molecule Localization Microscopy

Biology would not be where it is today without fluorescence microscopy. It is arguably one of the most commonly used tools in the biologists toolbox and it has helped scientists study the localization of cellular proteins and other small things for decades, but it is not without its limitations. Due to the diffraction limit, conventional fluorescence microscopy is limited to micrometer-range structures. Science has long relied upon electron microscopy and X-ray crystallography to study phenomena that occur below this limit. However, many of lifes processes occur between these two spatial domains. Super-resolution microscopy, the next stage of evolution of fluorescence microscopy, has the potential to bridge this gap between micro and nano. It combines superior resolutions of down to a few nanometers with the ability to view objects in their natural environments. It is the ideal tool for studying the large, multi-protein complexes that carry out most of lifes functions, but are too complex and fragile to put on an electron microscope or into a synchrotron. A form of super-resolution microscopy called SMLM Microscopy shows especially high promise in this regard. With its ability to detect individual molecules, it combines the high resolution needed for structural studies with the quantitative readout required for obtaining data on the stoichiometry of multi-protein complexes. This thesis describes new tools which expand the toolbox of SMLM with the specific aim of studying multi-protein complexes. First, the development of a novel fluorescent tagging system that is a mix of genetic tagging and immuno-staining. The system, termed BC2, consists of a short, genetically encodable peptide that is targeted by a nanobody (BC2 nanobody). The system brings several advantages. The small tag is not disruptive to the protein it is attached to and the small nanobody can get into tight spaces, making it an excellent tag for dense multi-protein structures. Next, several new variants of some commonly used green-to-red fluorescent proteins. The novel variants, which can be converted with a combination of blue and infrared light are especially useful for live-cell imaging. The developed fluorescent proteins can also be combined with photo-activatable fluorescent proteins to enable imaging of several targets with the same color protein. Finally, an application of the latter technique to study the multi-protein kinetochore complex and gain first glimpses into its spatial organization and the stoichiometry of its subunits

Unraveling the kinetochore nanostructure in Schizosaccharomyces pombe using multi-color SMLM imaging.

Funder: Boehringer Ingelheim FondsFunder: Bonn UniversityFunder: Max Planck SocietyFunder: Carnegie Mellon UniversityThe key to ensuring proper chromosome segregation during mitosis is the kinetochore (KT), a tightly regulated multiprotein complex that links the centromeric chromatin to the spindle microtubules and as such leads the segregation process. Understanding its architecture, function, and regulation is therefore essential. However, due to its complexity and dynamics, only its individual subcomplexes could be studied in structural detail so far. In this study, we construct a nanometer-precise in situ map of the human-like regional KT of Schizosaccharomyces pombe using multi-color single-molecule localization microscopy. We measure each protein of interest (POI) in conjunction with two references, cnp1CENP-A at the centromere and sad1 at the spindle pole. This allows us to determine cell cycle and mitotic plane, and to visualize individual centromere regions separately. We determine protein distances within the complex using Bayesian inference, establish the stoichiometry of each POI and, consequently, build an in situ KT model with unprecedented precision, providing new insights into the architecture

Improving the accuracy of dose estimates from automatically scored dicentric chromosomes by accounting for chromosome number

Purpose: The traditional workflow for biological dosimetry based on manual scoring of dicentric chromosomes is very time consuming. Especially for large-scale scenarios or for low-dose exposures, high cell numbers have to be analysed, requiring alternative scoring strategies. Semi-automatic scoring of dicentric chromosomes provides an opportunity to speed up the standard workflow of biological dosimetry. Due to automatic metaphase and chromosome detection, the number of counted chromosomes per metaphase is variable. This can potentially introduce overdispersion and statistical methods for conventional, manual scoring might not be applicable to data obtained by automatic scoring of dicentric chromosomes, potentially resulting in biased dose estimates and underestimated uncertainties. The identification of sources for overdispersion enables the development of methods appropriately accounting for increased dispersion levels. Materials and methods: Calibration curves based on in-vitro irradiated (137-Cs; 0.44 Gy/min) blood from three healthy donors were analysed for systematic overdispersion, especially at higher doses (> 2 Gy) of low LET radiation. For each donor, 12 doses in the range of 0-6 Gy were scored semi-automatically. The effect of chromosome number as a potential cause for the observed overdispersion was assessed. Statistical methods based on interaction models accounting for the number of detected chromosomes were developed for the estimation of calibration curves, dose and corresponding uncertainties. The dose estimation was performed based on a Bayesian Markov-Chain-Monte-Carlo method, providing high flexibility regarding the implementation of priors, likelihood and the functional form of the association between predictors and dicentric counts. The proposed methods were validated by simulations based on cross-validation. Results: Increasing dose dependent overdispersion was observed for all three donors as well as considerable differences in dicentric counts between donors. Variations in the number of detected chromosomes between metaphases were identified as a major source for the observed overdispersion and the differences between donors. Persisting overdispersion beyond the contribution of chromosome number was modelled by a Negative Binomial distribution. Results from cross-validation suggested that the proposed statistical methods for dose estimation reduced bias in dose estimates, variability between dose estimates and improved the coverage of the estimated confidence intervals. However, the 95% confidence intervals were still slightly too permissive, suggesting additional unknown sources of apparent overdispersion. Conclusions: A major source for the observed overdispersion could be identified, and statistical methods accounting for overdispersion introduced by variations in the number of detected chromosomes were developed, enabling more robust dose estimation and quantification of uncertainties or semi-automatic counting of dicentric chromosomes