A critical appraisal of techniques, software packages, and standards for quantitative proteomic analysis

Abstract New methods for performing quantitative proteome analyses based on differential labeling protocols or label-free techniques are reported in the literature on an almost monthly basis. In parallel, a correspondingly vast number of software tools for the analysis of quantitative proteomics data has also been described in the literature and produced by private companies. In this article we focus on the review of some of the most popular techniques in the field and present a critical appraisal of several software packages available to process and analyze the data produced. We also describe the importance of community standards to support the wide range of software, which may assist researchers in the analysis of data using different platforms and protocols. It is intended that this review will serve bench scientists both as a useful reference and a guide to the selection and use of different pipelines to perform quantitative proteomics data analysis. We have produced a web-based tool ( http://www.proteosuite.org/?q=other_resources ) to help researchers find appropriate software for their local instrumentation, available file formats, and quantitative methodology.     

Use of diethyldithiocarbamate for quantitative determination of tellurite uptake by bacteria.

We have developed a simple method for the quantitative determination of tellurite in biological media. This assay is suitable for studying tellurite uptake in bacteria and overcomes the problems of older techniques which are time consuming and labor intensive. In earlier protocols diethyldithiocarbamate was reacted with tellurite and the resulting complex was extracted into organic solvents before spectrophotometric determination. In this study, diethyldithiocarbamate was incubated with tellurite at neutral pH to form a yellow colloidal solution. The absorbance of the aqueous yellow sol was used to determine tellurite concentrations in the range of 1 to 50 micrograms/ml (4 to 200 microM) without the need for solvent extraction.     

Detection and monitoring of virus infections by real-time PCR

The employment of polymerase chain reaction (PCR) techniques for virus detection and quantification offers the advantages of high sensitivity and reproducibility, combined with an extremely broad dynamic range. A number of qualitative and quantitative PCR virus assays have been described, but commercial PCR kits are available for quantitative analysis of a limited number of clinically important viruses only. In addition to permitting the assessment of viral load at a given time point, quantitative PCR tests offer the possibility of determining the dynamics of virus proliferation, monitoring of the response to treatment and, in viruses displaying persistence in defined cell types, distinction between latent and active infection. Moreover, from a technical point of view, the employment of sequential quantitative PCR assays in virus monitoring helps identifying false positive results caused by inadvertent contamination of samples with traces of viral nucleic acids or PCR products. In this review, we provide a survey of the current state-of-the-art in the application of the real-time PCR technology to virus analysis. Advantages and limitations of the RQ-PCR methodology, and quality control issues related to standardization and validation of diagnostic assays are discussed.     

Common practice in molecular biology may introduce statistical bias and misleading biological interpretation

In studies on enzyme activity or gene expression at the protein level, data are usually analyzed by using a standard curve after subtracting blank values. In most cases and for most techniques (spectrophotometric assays, ELISA), this approach satisfies the basic principles of linearity and specificity. In our experience, this might be also the case for Western-blot analysis. By contrast, mRNA data are usually presented as arbitrary units of the ratio of a target RNA over levels of a control RNA species. We here demonstrate by simple experiments and various examples that this data-normalization procedure may result in misleading conclusions. Common molecular biology techniques have never been carefully tested according to the basic principles of validation of quantitative techniques. We thus prefer a regression-based approach for quantifying mRNA levels relatively to a control RNA species by Northern-blot, semi-quantitative RT-PCR or similar techniques. This type of techniques is also characterized by a lower reproducibility for repeated assays when compared to biochemical analyses. Therefore, we also recommend to design experiments, which allow the detection of a similar range of variance by biochemical and molecular biology techniques. Otherwise, spurious conclusions may be provided regarding the control level of gene expression.     

Reference genes for measuring mRNA expression

The aim of this review is to find answers to some of the questions surrounding reference genes and their reliability for quantitative experiments. Reference genes are assumed to be at a constant expression level, over a range of conditions such as temperature. These genes, such as GADPH and beta-actin, are used extensively for gene expression studies using techniques like quantitative PCR. There have been several studies carried out on identifying reference genes. However, a lot of evidence indicates issues to the general suitability of these genes. Recent studies had shown that different factors, including the environment and methods, play an important role in changing the expression levels of the reference genes. Thus, we conclude that there is no reference gene that can deemed suitable for all the experimental conditions. In addition, we believe that every experiment will require the scientific evaluation and selection of the best candidate gene for use as a reference gene to obtain reliable scientific results.     

FTICR mass spectrometry for qualitative and quantitative bioanalyses

Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) is playing an increasing role in the characterization of cellular systems owing to its capabilities for providing higher confidence of identification, increased dynamic range and sensitivity unmatched by other MS platforms. Particularly in proteomics, where global and quantitative approaches are essential, the attributes of FTICR-MS are poised to make significant contributions. Recent advances in the field that have particular importance for proteomic applications include the use of high-performance micro-capillary column separation techniques coupled to FTICR, as well as methods that improve protein identification, sensitivity, dynamic range and throughput.     

Real-time quantitative PCR in parasitology

Standard techniques for counting parasites are often time-consuming, difficult and inaccurate, and occasionally unpleasant. Real-time quantitative polymerase chain reaction has recently been applied to parasitology, specifically Plasmodium, Toxoplasma, Leishmania and Neospora. These techniques are truly quantitative, give results over a range of 6-7 orders of magnitude, are quick to perform and require no manipulations post-amplification. They can be used to count genome numbers and to study levels of gene expression. The advantages and limitations of existing thermocyclers and applicable detection systems are discussed here, and promising new developments are highlighted.     

Low-light imaging technology in the life sciences

Photon imaging is an increasingly important technique for the measurement and analysis of chemiluminescence and bioluminescence. New high-performance low-light level imaging systems have recently become available for the life science. These systems use advances in camera design and digital image processing and are now being used for a wide range of luminescence applications. They offer good sensitivity for photon detection and large dynamic range, and are suitable for quantitative analysis. This is achieved using a range of software techniques including image arithmetic, histogramming or summing regions of interest, feature extraction and multiple image processing for kinetics or assay screening. Improvements in imageprocessing hardware and software have increased the usefulness of these systems in the biosciences. Low-light imaging is a rapid and non-invasive method for the sensitive detection and analysis of luminescent assays. As such it offers a powerful and sensitive tool for investigating processes, both at the cellular level (luc and lux reporter genes, intracellular signalling) and for measurement of macro samples (immunoassays, gels and blots, tissue sections).     

The mechanical power requirements of avian flight

A major goal of flight research has been to establish the relationship between the mechanical power requirements of flight and flight speed. This relationship is central to our understanding of the ecology and evolution of bird flight behaviour. Current approaches to determining flight power have relied on a variety of indirect measurements and led to a controversy over the shape of the power-speed relationship and a lack of quantitative agreement between the different techniques. We have used a new approach to determine flight power at a range of speeds based on the performance of the pectoralis muscles. As such, our measurements provide a unique dataset for comparison with other methods. Here we show that in budgerigars (Melopsittacus undulatus) and zebra finches (Taenopygia guttata) power is modulated with flight speed, resulting in U-shaped power-speed relationship. Our measured muscle powers agreed well with a range of powers predicted using an aerodynamic model. Assessing the accuracy of mechanical power calculated using such models is essential as they are the basis for determining flight efficiency when compared to measurements of flight metabolic rate and for predicting minimum power and maximum range speeds, key determinants of optimal flight behaviour in the field.     

Estimation of environmental and genetic components of quantitative traits with application to serum cholesterol levels.

A mixed model of environmental, polygenic, and major locus effects is developed, allowing for environmental correlations between first-degree relatives and spouses. Maximum-likelihood techniques are used to determine the relative contributions of each of these effects to a quantitative trait. Inclusion of a nuclear family in the sample is assumed to depend on the value of the quantitative trait of one member of the family, so conditional distributions are used. Application of the method to serum cholesterol data from the general population shows that the addition of a polygenic effect to a model that assumes only an environmental effect makes a significant improvement. A completely dominant single gene is also found to be influencing serum cholesterol levels. Although cholesterol levels have been adjusted for a range of factors, such as age, sex, weight/height, and marital status, environmental factors still account for about half the variability in the residual values.     

Resolving distance variations by single-molecule FRET and EPR spectroscopy using rotamer libraries

Förster resonance energy transfer (FRET) and electron paramagnetic resonance (EPR) spectroscopy are complementary techniques for quantifying distances in the nanometer range. Both approaches are commonly employed for probing the conformations and conformational changes of biological macromolecules based on site-directed fluorescent or paramagnetic labeling. FRET can be applied in solution at ambient temperature and thus provides direct access to dynamics, especially if used at the single-molecule level, whereas EPR requires immobilization or work at cryogenic temperatures but provides data that can be more reliably used to extract distance distributions. However, a combined analysis of the complementary data from the two techniques has been complicated by the lack of a common modeling framework. Here, we demonstrate a systematic analysis approach based on rotamer libraries for both FRET and EPR labels to predict distance distributions between two labels from a structural model. Dynamics of the fluorophores within these distance distributions are taken into account by diffusional averaging, which improves the agreement with experiment. Benchmarking this methodology with a series of surface-exposed pairs of sites in a structured protein domain reveals that the lowest resolved distance differences can be as small as ∼0.25 nm for both techniques, with quantitative agreement between experimental and simulated transfer efficiencies within a range of ±0.045. Rotamer library analysis thus establishes a coherent way of treating experimental data from EPR and FRET and provides a basis for integrative structural modeling, including studies of conformational distributions and dynamics of biological macromolecules using both techniques.     

Isolation of human platelet and red blood cell plasma membrane proteins by preparative detergent electrophoresis

High resolution polyacrylamide gel electrophoretic techniques have been applied to the preparative isolation and analysis of plasma membrane proteins and glycoproteins from human platelets and red blood cells. The techniques presented allow relatively simple, direct, rapid and quantitative purification of a broad molecular weight range of membrane proteins, by means of continuous elution preparative gel electrophoresis of proteins solubilized with sodium dodecyl sulfate. Spectrophotometric and fluorophotometric (fluorescamine) profiling, and high resolution gel electrophoretic analysis (SDS-acrylamide gradient slab gels, and gel electrofocusing) of eluted protein species indicate that purified membrane proteins of a broad molecular weight range may be obtained in a one step procedure, and in quantities and concentrations sufficient for further analytical or experimental procedures.     

Isolation of human platelet and red blood cell plasma membrane proteins by preparative detergent electrophoresis.

High resolution polyacrylamide gel electrophoretic techniques have been applied to the preparative isolation and analysis of plasma membrane proteins and glycoproteins from human platelets and red blood cells. The techniques presented allow relatively simple, direct, rapid and quantitative purification of a broad molecular weight range of membrane proteins, by means of continuous elution preparative gel electrophoresis of protein solubilized with sodium dodecyl sulfate. Spectrophotometric and fluorophotometric (fluorescamine) profiling, and high resolution gel electrophoretic analysis (SDS-acrylamide gradient slab gels, and gel electrofocusing) of eluted protein species indicate that purified membrane proteins of a broad molecular weight range may be obtained in a one step procedure, and in quantities and concentrations sufficient for further analytical or experimental procedures.     

A computational method for quantifying morphological variation in scleractinian corals

Morphological variation in marine sessile organisms is frequently related to environmental factors. Quantifying such variation is relevant in a range of ecological studies. For example, analyzing the growth form of fossil organisms may indicate the state of the physical environment in which the organism lived. A quantitative morphological comparison is important in studies where marine sessile organisms are transplanted from one environment to another. This study presents a method for the quantitative analysis of three-dimensional (3D) images of scleractinian corals obtained with X-ray Computed Tomography scanning techniques. The advantage of Computed Tomography scanning is that a full 3D image of a complex branching object, including internal structures, can be obtained with a very high precision. There are several complications in the analysis of this data set. In the analysis of a complex branching object, landmark-based methods usually do not work and different approaches are required where various artifacts (for example cavities, holes in the skeleton, scanning artifacts, etc.) in the data set have to be removed before the analysis. A method is presented, which is based on the construction of a medial axis and a combination of image-processing techniques for the analysis of a 3D image of a complex branching object where the complications mentioned above can be overcome. The method is tested on a range of 3D images of samples of the branching scleractinian coral Madracis mirabilis collected at different depths. It is demonstrated that the morphological variation of these samples can be quantified, and that biologically relevant morphological characteristics, like branch-spacing and surface/volume ratios, can be computed. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Calcified tissue histochemistry: from microstructures to nanoparticles

It has long been recognized that histochemistry and cytochemistry offer the only ways of gathering information about the biochemical composition of tissues and cells without disrupting their microscopic architecture. A variety of methods have been put forward for studying nuclei acids, proteins, carbohydrates, lipids, enzymes and other components of intact tissues and cells. By now, many of these have only a historical interest. Some do, however, survive in microscopic and ultramicroscopic applications, and have become incorporated in the most refined and precise techniques that are currently available. Histochemical reactions range from the classic procedures carried out on histological sections to yield final stained products recognizable under the light microscope, to those which are applied on ultrathin sections, using heavy metals or other electron-dense compounds to reveal specific components under the electron microscope; others range from procedures based on the antigen-antibody reaction that are capable of revealing the presence of specific biological molecules, to the biophysical techniques which permit the qualitative and quantitative analysis of elements; lastly, there are the recently proposed ultra-high resolution methods that allow nanoparticles to be recognized. This brief review, which is based on personal experience and on the data in the literature, will discuss the most important methods now being used.     

Assessment of Lignocellulosic Biomass Using Analytical Spectroscopy: an Evolution to High-Throughput Techniques

Lignocellulosic biomass has been proposed as an option for reducing global dependence on nonrenewable energy sources, such as oil. Selection and development of biomass feedstocks that efficiently yield the maximum fuel or biomaterial requires the availability of reliable methods for compositional and structural characterization of plant material. Many standard methods for biomass analysis are laborious and slow, and employ a variety of harsh reagents requiring some degree of remediation. The use of simpler and more rapid spectroscopic methods has proved invaluable in analyzing biomass. In the twenty-first century, researchers have employed techniques such as Raman, mid-infrared, and near-infrared spectroscopy for a wide range of applications in endeavors to further understand biofuel feedstocks. While many methods remain time consuming and expensive, a growing interest in high-throughput spectroscopic techniques has provided faster and larger scale feedstock screening for desirable traits. This review seeks to provide an overview of both high-throughput techniques and those requiring longer analysis times but still providing abundant qualitative and quantitative data. While applications of these instrumental methods have been researched for decades, more recent developments will be discussed here.     

Subpopulation range estimation for conservation planning: a case study of the critically endangered Cross River gorilla

Measuring and characterizing the area utilized by a population or species is essential for assessment of conservation status and for effective allocation of habitat to ensure population persistence. Yet population-level range delineation is complicated by the variety of available techniques coupled with a lack of empirical methods to compare the relative value of these techniques. This study assesses the effect of model choice on resulting subpopulation range estimation for the critically endangered and patchily distributed Cross River gorilla, and evaluates the conservation conclusions that can be drawn from each model. Models considered range from basic traditional approaches (e.g. minimum convex polygon) to newer home range techniques such as local convex hull (LoCoH). Overlap analysis comparing sub-sampled to complete data sets are used to evaluate the robustness of various modeling techniques to data limitations. Likelihood cross validation criterion is employed to compare core range model performance. Results suggest that differing LoCoH models produce similar range estimates, are robust to data requirements, provide a good fit for core habitat estimation, and are best able to detect unused habitat within the subpopulation range. LoCoH methods may thus be useful for studies into habitat selection and factors limiting endangered species distributions. However, LoCoH models tend to over-fit data, and kernel methods may provide similar information about animal space use while supporting protection of larger swaths of critical habitat. Subpopulation range analyses for conservation/management planning should therefore explore multiple modeling techniques, and employ both qualitative and quantitative assessments to select the best models to inform decision making for species of conservation concern.     

Laser capture sampling and analytical issues in proteomics

Proteomics holds the promise of evaluating global changes in protein expression and post-translational modification in response to environmental stimuli. However, difficulties in achieving cellular anatomic resolution and extracting specific types of proteins from cells have limited the efficacy of these techniques. Laser capture microdissection has provided a solution to the problem of anatomical resolution in tissues. New extraction methodologies have expanded the range of proteins identified in subsequent analyses. This review will examine the application of laser capture microdissection to proteomic tissue sampling, and subsequent extraction of these samples for differential expression analysis. Statistical and other quantitative issues important for the analysis of the highly complex datasets generated are also reviewed.