Fast, robust, and accurate determination of transmission electron microscopy contrast transfer function

Transmission electron microscopy, as most imaging devices, introduces optical aberrations that in the case of thin specimens are usually modeled in Fourier space by the so-called contrast transfer function (CTF). Accurate determination of the CTF is crucial for its posterior correction. Furthermore, the CTF estimation must be fast and robust if high-throughput three-dimensional electron microscopy (3DEM) studies are to be carried out. In this paper we present a robust algorithm that fits a theoretical CTF model to the power spectrum density (PSD) measured on a specific micrograph or micrograph area. Our algorithm is capable of estimating the envelope of the CTF which is absolutely needed for the correction of the CTF amplitude changes.     

FASTDEF: Fast defocus and astigmatism estimation for high-throughput transmission electron microscopy

In this work we present a fast and automated algorithm for estimating the contrast transfer function (CTF) of a transmission electron microscope. The approach is very suitable for High Throughput work because: (a) it does not require any initial defocus estimation, (b) it is almost an order of magnitude faster than existing approaches, (c) it opens the way to well-defined extensions to the estimation of higher order aberrations, at the same time that provides defocus and astigmatism estimations comparable in accuracy to well established methods, such as Xmipp and CTFFIND3 approaches. The new algorithm is based on obtaining the wrapped modulating phase of the power spectra density pattern by the use of a quadrature filter. This phase is further unwrapped in order to obtain the continuous and smooth absolute phase map; then a Zernike polynomial fitting is performed and the defocus and astigmatism parameters are determined. While the method does not require an initial estimation of the defocus parameters or any non-linear optimization procedure, these approaches can be used if further refinement is desired. Results of the CTF estimation method are presented for standard negative stained images, cryo-electron microscopy images in the absence of carbon support, as well as micrographs with only ice. Additionally, we have also tested the proposed method with micrographs acquired from tilted and untilted samples, obtaining good results. The algorithm is freely available as a part of the Xmipp package [http://xmipp.cnb.csic.es].     

Toward understanding the structure and interactions of microtubules and motor proteins

To obtain an overall three-dimensional picture of the interaction between microtubules and the motor proteins of the kinesin family it will be necessary to take account of both atomic resolution structures obtained by X-ray crystallography and medium resolution reconstructions obtained by electron cryomicroscopy. We examine the problems associated with obtaining the required structural information from electron micrographs of vitreous ice-embedded microtubules decorated with motor domains. We find that the minus-end directed motor, ncd, decorates microtubules with an 80 Å periodicity as for kinesin. Our theoretical analysis and experiments with ncd illustrate the difficulty in determining unambiguously the surface lattice organization by diffraction analysis of micrographs. 3D reconstructions of decorated microtubules are required to accurately locate the motor domains. Helical diffraction theory is not usually applicable because microtubules are cylindrical structures that rarely have complete helical symmetry. We propose using a back-projection method based on the long pitch helices formed by individual protofilaments. Model reconstructions show that this approach is feasible. © 1995 Wiley-Liss, Inc.     

Structural motifs recurring in different folds recognize the same ligand fragments

Background  

The structural analysis of protein ligand binding sites can provide information relevant for assigning functions to unknown proteins, to guide the drug discovery process and to infer relations among distant protein folds. Previous approaches to the comparative analysis of binding pockets have usually been focused either on the ligand or the protein component. Even though several useful observations have been made with these approaches they both have limitations. In the former case the analysis is restricted to binding pockets interacting with similar ligands, while in the latter it is difficult to systematically check whether the observed structural similarities have a functional significance.     

Bias in error estimation when using cross-validation for model selection

Background  

Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers by choosing classifier parameter values that minimize the CV error estimate. We have evaluated the validity of using the CV error estimate of the optimized classifier as an estimate of the true error expected on independent data.     

Prediction of calcium-binding sites by combining loop-modeling with machine learning

Background  

Protein ligand-binding sites in the apo state exhibit structural flexibility. This flexibility often frustrates methods for structure-based recognition of these sites because it leads to the absence of electron density for these critical regions, particularly when they are in surface loops. Methods for recognizing functional sites in these missing loops would be useful for recovering additional functional information.     

Orientation determination by wavelets matching for 3D reconstruction of very noisy electron microscopic virus images

Background  

In order to perform a 3D reconstruction of electron microscopic images of viruses, it is necessary to determine the orientation (Euler angels) of the 2D projections of the virus. The projections containing high resolution information are usually very noisy. This paper proposes a new method, based on weighted-projection matching in wavelet space for virus orientation determination. In order to speed the retrieval of the best match between projections from a model and real virus particle, a hierarchical correlation matching method is also proposed.     

Set-base dynamical parameter estimation and model invalidation for biochemical reaction networks

Background  

Mathematical modeling and analysis have become, for the study of biological and cellular processes, an important complement to experimental research. However, the structural and quantitative knowledge available for such processes is frequently limited, and measurements are often subject to inherent and possibly large uncertainties. This results in competing model hypotheses, whose kinetic parameters may not be experimentally determinable. Discriminating among these alternatives and estimating their kinetic parameters is crucial to improve the understanding of the considered process, and to benefit from the analytical tools at hand.     

An integrated analysis of molecular aberrations in NCI-60 cell lines

Background  

Cancer is a complex disease where various types of molecular aberrations drive the development and progression of malignancies. Large-scale screenings of multiple types of molecular aberrations (e.g., mutations, copy number variations, DNA methylations, gene expressions) become increasingly important in the prognosis and study of cancer. Consequently, a computational model integrating multiple types of information is essential for the analysis of the comprehensive data.     

Island method for estimating the statistical significance of profile-profile alignment scores

Background  

In the last decade, a significant improvement in detecting remote similarity between protein sequences has been made by utilizing alignment profiles in place of amino-acid strings. Unfortunately, no analytical theory is available for estimating the significance of a gapped alignment of two profiles. Many experiments suggest that the distribution of local profile-profile alignment scores is of the Gumbel form. However, estimating distribution parameters by random simulations turns out to be computationally very expensive.     

Common Genetic Variation in the Human CTF1 Locus,Encoding Cardiotrophin-1, Determines Insulin Sensitivity

Aims/Hypothesis

Recently, cardiotrophin-1, a member of the interleukin-6 family of cytokines was described to protect beta-cells from apoptosis, to improve glucose-stimulated insulin secretion and insulin resistance, and to prevent streptozotocin-induced diabetes in mice. Here, we studied whether common single nucleotide polymorphisms (SNPs) in the CTF1 locus, encoding cardiotrophin-1, influence insulin secretion and insulin sensitivity in humans.

Methods

We genotyped 1,771 German subjects for three CTF1 tagging SNPs (rs1046276, rs1458201, and rs8046707). The subjects were metabolically characterized by an oral glucose tolerance test. Subgroups underwent magnetic resonance (MR) imaging/spectroscopy and hyperinsulinaemic-euglycaemic clamps.

Results

After appropriate adjustment, the minor allele of CTF1 SNP rs8046707 was significantly associated with decreased in vivo measures of insulin sensitivity. The other tested SNPs were not associated with OGTT-derived sensitivity parameters, nor did the three tested SNPs show any association with OGTT-derived parameters of insulin release. In the MR subgroup, SNP rs8046707 was nominally associated with lower visceral adipose tissue. Furthermore, the SNP rs1458201 showed a nominal association with increased VLDL levels.

Conclusions

In conclusion, this study, even though preliminary and awaiting further confirmation by independent replication, provides first evidence that common genetic variation in CTF1 could contribute to insulin sensitivity in humans. Our SNP data indicate an insulin-desensitizing effect of cardiotrophin-1 and underline that cardiotrophin-1 represents an interesting target to influence insulin sensitivity.     

GeneBrowser 2: an application to explore and identify common biological traits in a set of genes

Background  

The development of high-throughput laboratory techniques created a demand for computer-assisted result analysis tools. Many of these techniques return lists of genes whose interpretation requires finding relevant biological roles for the problem at hand. The required information is typically available in public databases, and usually, this information must be manually retrieved to complement the analysis. This process is a very time-consuming task that should be automated as much as possible.     

Improving the accuracy of a solid spherical source radius and depth estimation using the diffusion equation in fluorescence reflectance mode

Background  

Non-invasive planar fluorescence reflectance imaging (FRI) is used for accessing physiological and molecular processes in biological tissue. This method is efficiently used to detect superficial fluorescent inclusions. FRI is based on recording the spatial radiance distribution (SRD) at the surface of a sample. SRD provides information for measuring structural parameters of a fluorescent source (such as radius and depth). The aim of this article is to estimate the depth and radius of the source distribution from SRD, measured at the sample surface. For this reason, a theoretical expression for the SRD at the surface of a turbid sample arising from a spherical light source embedded in the sample, was derived using a steady-state solution of the diffusion equation with an appropriate boundary condition.     

High-resolution cryo-EM performance comparison of two latest-generation cryo electron microscopes on the human ribosome

Recent technological advances in cryo electron microscopy (cryo-EM) have led to new opportunities in the structural biology field. Here we benchmark the performance of two 300 kV latest-generation cryo electron microscopes, Titan Krios G4 from Thermofisher Scientific and CRYO ARM 300 from Jeol, with regards to achieving high resolution single particle reconstructions on a real case sample. We compare potentially limiting factors such as drift rates, astigmatism & coma aberrations and performance during image processing and show that both microscopes, while comprising rather different technical setups & parameter settings and equipped with different types of energy filters & cameras, achieve a resolution of around 2 Å on the human ribosome, a non-symmetric object which constitutes a key drug target. Astigmatism correction, CTF refinement and correction of higher order aberrations through refinement in separate optics groups helped to account for astigmatism/coma caused by beam tilting during multi-spot and multi-hole acquisition in neighbouring holes without stage movement. The obtained maps resolve Mg²⁺ ions, water molecules, inhibitors and side-chains including chemical modifications. The fact that both instruments can resolve such detailed features will greatly facilitate understanding molecular mechanisms of various targets and helps in cryo-EM structure based drug design. The methods and analysis tools used here will be useful also to characterize existing instruments and optimize data acquisition settings and are applicable broadly to other drug targets in structural biology.     

Quantitative polymerase chain reaction analysis by deconvolution of internal standard

Background  

Quantitative Polymerase Chain Reaction (qPCR) is a collection of methods for estimating the number of copies of a specific DNA template in a sample, but one that is not universally accepted because it can lead to highly inaccurate (albeit precise) results. The fundamental problem is that qPCR methods use mathematical models that explicitly or implicitly apply an estimate of amplification efficiency, the error of which is compounded in the analysis to unacceptable levels.     

Short-Term Stability in Refractive Status Despite Large Fluctuations in Glucose Levels in Diabetes Mellitus Type 1 and 2

Purpose

This work investigates how short-term changes in blood glucose concentration affect the refractive components of the diabetic eye in patients with long-term Type 1 and Type 2 diabetes.

Methods

Blood glucose concentration, refractive error components (mean spherical equivalent MSE, J0, J45), central corneal thickness (CCT), anterior chamber depth (ACD), crystalline lens thickness (LT), axial length (AL) and ocular aberrations were monitored at two-hourly intervals over a 12-hour period in: 20 T1DM patients (mean age ± SD) 38±14 years, baseline HbA1c 8.6±1.9%; 21 T2DM patients (mean age ± SD) 56±11 years, HbA1c 7.5±1.8%; and in 20 control subjects (mean age ± SD) 49±23 years, HbA1c 5.5±0.5%. The refractive and biometric results were compared with the corresponding changes in blood glucose concentration.

Results

Blood glucose concentration at different times was found to vary significantly within (p<0.0005) and between groups (p<0.0005). However, the refractive error components and ocular aberrations were not found to alter significantly over the day in either the diabetic patients or the control subjects (p>0.05). Minor changes of marginal statistical or optical significance were observed in some biometric parameters. Similarly there were some marginally significant differences between the baseline biometric parameters of well-controlled and poorly-controlled diabetic subjects.

Conclusion

This work suggests that normal, short-term fluctuations (of up to about 6 mM/l on a timescale of a few hours) in the blood glucose levels of diabetics are not usually associated with acute changes in refractive error or ocular wavefront aberrations. It is therefore possible that factors other than refractive error fluctuations are sometimes responsible for the transient visual problems often reported by diabetic patients.     

Microarray image analysis: background estimation using quantile and morphological filters

Background  

In a microarray experiment the difference in expression between genes on the same slide is up to 10³ fold or more. At low expression, even a small error in the estimate will have great influence on the final test and reference ratios. In addition to the true spot intensity the scanned signal consists of different kinds of noise referred to as background. In order to assess the true spot intensity background must be subtracted. The standard approach to estimate background intensities is to assume they are equal to the intensity levels between spots. In the literature, morphological opening is suggested to be one of the best methods for estimating background this way.     

qPIPSA: Relating enzymatic kinetic parameters and interaction fields

Background  

The simulation of metabolic networks in quantitative systems biology requires the assignment of enzymatic kinetic parameters. Experimentally determined values are often not available and therefore computational methods to estimate these parameters are needed. It is possible to use the three-dimensional structure of an enzyme to perform simulations of a reaction and derive kinetic parameters. However, this is computationally demanding and requires detailed knowledge of the enzyme mechanism. We have therefore sought to develop a general, simple and computationally efficient procedure to relate protein structural information to enzymatic kinetic parameters that allows consistency between the kinetic and structural information to be checked and estimation of kinetic constants for structurally and mechanistically similar enzymes.