Comparative evaluation of two two-dimensional gel electrophoresis image analysis software applications using synovial fluids from patients with joint disease

Seminal Plasma Proteins Associated with The Fertility of Brahman Bulls in The Colombian Low Tropics

The sperm interacts with seminal plasma proteins during its transport through the female reproductive tract to reach the oocyte. Seminal plasma proteins have been associated as biomarkers of fertility in bovine males, while two-dimensional electrophoresis in polyacrylamide gels under denaturing conditions (2D-PAGE) is a useful technique for their separation, allowing their subsequent analysis with the aid of specialised software. Brahman bulls are known for their tolerance to tropical conditions such as low-quality pastures, high temperatures, and relative humidity as well as moderate resistance to infestations by parasites and insects. The present study describes the two-dimensional electrophoretic profiles of the seminal plasma proteins in the rainy and dry seasons, associating them with the fertility of Brahman bulls in the Colombian Orinoquía in a 90-days breeding season and a single-sire mating system (1 bull per 50 Brahman cows) with 60 consecutive days of rest. The fertility-related seminal plasma protein spots increased in the dry season. Likewise, a meaningful relationship was found between the protein spots that possibly coincide with the Binder of Sperm Proteins. It was also found that bulls with the highest percentages of pregnancy also had similarities in their 2D seminal plasma maps. We conclude that the seminal plasma protein profile of Brahman bulls raised in the Colombian low tropic changes between rainy and dry seasons, and such changes may influence the reproductive performance of those animals.

Comparative Evaluation of Software Features and Performances

Analysis of two-dimensional gel images is a crucial step for the determination of changes in the protein expression, but at present, it still represents one of the bottlenecks in 2-DE studies. Over the years, different commercial and academic software packages have been developed for the analysis of 2-DE images. Each of these shows different advantageous characteristics in terms of quality of analysis. In this chapter, the characteristics of the different commercial software packages are compared in order to evaluate their main features and performances.

Inoculation with endophytic Bacillus megaterium 1Y31 increases Mn accumulation and induces the growth and energy metabolism-related differentially-expressed proteome in Mn hyperaccumulator hybrid pennisetum

In this study, a hydroponic culture experiment was conducted in a greenhouse to investigate the molecular and microbial mechanisms involved in the endophytic Bacillus megaterium 1Y31-enhanced Mn tolerance and accumulation in Mn hyperaccumulator hybrid pennisetum. Strain 1Y31 significantly increased the dry weights (ranging from 28% to 94%) and total Mn uptake (ranging from 23% to 112%) of hybrid pennisetum treated with 0, 2, and 10mM Mn compared to the control. Total 98 leaf differentially expressed proteins were identified between the live and dead bacterial inoculated hybrid pennisetum. The major leaf differentially expressed proteins were involved in energy generation, photosynthesis, response to stimulus, metabolisms, and unknown function. Furthermore, most of the energy generation and photosynthesis-related proteins were up-regulated, whereas most of the response to stimulus and metabolism-related proteins were down-regulated under Mn stress. Notably, the proportion of indole-3-acetic acid (IAA)-producing endophytic bacteria was significantly higher in the bacterial inoculated plants under Mn stress. The results suggested that strain 1Y31 increased the growth and Mn uptake of hybrid pennisetum through increasing the efficiency of photosynthesis and energy metabolism as well as the proportion of plant growth-promoting endophytic bacteria in the plants.

Common and metal-specific proteomic responses to cadmium and zinc in the metal tolerant ericoid mycorrhizal fungus Oidiodendron maius Zn

Although adaptive metal tolerance may arise in fungal populations in polluted soils, the mechanisms underlying metal-specific tolerance are poorly understood. Comparative proteomics is a powerful tool to identify variation in protein profiles caused by changing environmental conditions, and was used to investigate protein accumulation in a metal tolerant isolate of the ericoid mycorrhizal fungus Oidiodendron maius exposed to zinc and cadmium. Two-dimensional gel electrophoresis and shotgun proteomics followed by mass spectrometry lead to the identification of common and metal-specific proteins and pathways. Proteins selectively induced by cadmium exposure were molecular chaperons of the Hsp90 family, cytoskeletal proteins and components of the translation machinery. Zinc significantly up-regulated metabolic pathways related to energy production and carbohydrates metabolism, likely mirroring zinc adaptation of this fungal isolate. Common proteins induced by the two metal ions were the antioxidant enzyme Cu/Zn superoxide dismutase and ubiquitin. In mycelia exposed to zinc and cadmium, both proteomic techniques also identified agmatinase, an enzyme involved in polyamine biosynthesis. This novel finding suggests that, like plants, polyamines may have important functions in response to abiotic environmental stress in fungi. Genetic evidence also suggests that the biosynthesis of polyamines via an alternative metabolic pathway may be widespread in fungi.

A systems biology approach to synovial joint lubrication in health, injury, and disease

The synovial joint contains synovial fluid (SF) within a cavity bounded by articular cartilage and synovium. SF is a viscous fluid that has lubrication, metabolic, and regulatory functions within synovial joints. SF contains lubricant molecules, including proteoglycan-4 and hyaluronan. SF is an ultrafiltrate of plasma with secreted contributions from cell populations lining and within the synovial joint space, including chondrocytes and synoviocytes. Maintenance of normal SF lubricant composition and function are important for joint homeostasis. In osteoarthritis, rheumatoid arthritis, and joint injury, changes in lubricant composition and function accompany alterations in the cytokine and growth factor environment and increased fluid and molecular transport through joint tissues. Thus, understanding the synovial joint lubrication system requires a multifaceted study of the various parts of the synovial joint and their interactions. Systems biology approaches at multiple scales are being used to describe the molecular, cellular, and tissue components and their interactions that comprise the functioning synovial joint. Analyses of the transcriptome and proteome of SF, cartilage, and synovium suggest that particular molecules and pathways play important roles in joint homeostasis and disease. Such information may be integrated with physicochemical tissue descriptions to construct integrative models of the synovial joint that ultimately may explain maintenance of health, recovery from injury, or development and progression of arthritis.

Interaction between selected bacterial strains and Arabidopsis halleri modulates shoot proteome and cadmium and zinc accumulation

The effects of plant-microbe interactions between the hyperaccumulator Arabidopsis halleri and eight bacterial strains, isolated from the rhizosphere of A. halleri plants grown in a cadmium- and zinc-contaminated site, were analysed for shoot metal accumulation, shoot proteome, and the transcription of genes involved in plant metal homeostasis and hyperaccumulation. Cadmium and zinc concentrations were lower in the shoots of plants cultivated in the presence of these metals plus the selected bacterial strains compared with plants grown solely with these metals or, as previously reported, with plants grown with these metals plus the autochthonous rhizosphere-derived microorganisms. The shoot proteome of plants cultivated in the presence of these selected bacterial strains plus metals, showed an increased abundance of photosynthesis- and abiotic stress-related proteins (e.g. subunits of the photosynthetic complexes, Rubisco, superoxide dismutase, and malate dehydrogenase) counteracted by a decreased amount of plant defence-related proteins (e.g. endochitinases, vegetative storage proteins, and β-glucosidase). The transcription of several homeostasis genes was modulated by the microbial communities and by Cd and Zn content in the shoot. Altogether these results highlight the importance of plant-microbe interactions in plant protein expression and metal accumulation and emphasize the possibility of exploiting microbial consortia for increasing or decreasing shoot metal content.

Image analysis tools and emerging algorithms for expression proteomics

Since their origins in academic endeavours in the 1970s, computational analysis tools have matured into a number of established commercial packages that underpin research in expression proteomics. In this paper we describe the image analysis pipeline for the established 2-DE technique of protein separation, and by first covering signal analysis for MS, we also explain the current image analysis workflow for the emerging high-throughput 'shotgun' proteomics platform of LC coupled to MS (LC/MS). The bioinformatics challenges for both methods are illustrated and compared, whereas existing commercial and academic packages and their workflows are described from both a user's and a technical perspective. Attention is given to the importance of sound statistical treatment of the resultant quantifications in the search for differential expression. Despite wide availability of proteomics software, a number of challenges have yet to be overcome regarding algorithm accuracy, objectivity and automation, generally due to deterministic spot-centric approaches that discard information early in the pipeline, propagating errors. We review recent advances in signal and image analysis algorithms in 2-DE, MS, LC/MS and Imaging MS. Particular attention is given to wavelet techniques, automated image-based alignment and differential analysis in 2-DE, Bayesian peak mixture models, and functional mixed modelling in MS, and group-wise consensus alignment methods for LC/MS.

The inter- and intra-operator variability in manual spot segmentation and its effect on spot quantitation in two-dimensional electrophoresis analysis

Separation of complex mixtures of proteins by 2-DE is a fundamental component of current proteomic technology. Quantitative analysis of the images generated by digitization of such gels is critical for identifying alterations in protein expression within a given biological system. Software packages are designed for this purpose. The accurate definition of protein spot boundaries, using a suitable method of image segmentation, is a key requirement for image analysis. It is often necessary for operators to intervene manually to correct mistakes in spot segmentation; therefore operator subjectivity and differences in ability can weaken the analysis. We estimated the error in spot quantification after manual spot segmentation, which was performed by different operators, using two different software packages. Our results clearly show that this operation was associated with significant inter- and intra-variability and an overestimation of subsequent spot intensity, especially when spots were weak. For comparative studies, we suggest separately analysing spots which have been manually segmented by imposing a requirement for at least a threefold difference in spot intensity in addition to use of statistical tests.

Analytical strategies for detecting nanoparticle-protein interactions

A significant increase in biomedical applications of nanomaterials and their potential toxicity demands versatile analytical techniques to determine protein-nanoparticle (NP) interactions. These diverse analytical techniques are reviewed. Spectroscopic methods play a significant role in studying binding affinity, binding ratio, and binding mechanisms. To elucidate NP-proteome interactions, chromatography and electrophoresis techniques are applied to separate NP-bound proteins and matrix assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) to identify these proteins. Since NP-protein binding is a dynamic event, surface plasmon resonance (SPR) and quartz crystal microbalance (QCM) are methods of choice to study the kinetics of NP-protein binding.

Ocular proteomics with emphasis on two-dimensional gel electrophoresis and mass spectrometry

The intention of this review is to provide an overview of current methodologies employed in the rapidly developing field of ocular proteomics with emphasis on sample preparation, two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) and mass spectrometry (MS). Appropriate sample preparation for the diverse range of cells and tissues of the eye is essential to ensure reliable results. Current methods of protein staining for 2D-PAGE, protein labelling for two-dimensional difference gel electrophoresis, gel-based expression analysis and protein identification by MS are summarised. The uses of gel-free MS-based strategies (MuDPIT, iTRAQ, ICAT and SILAC) are also discussed. Proteomic technologies promise to shed new light onto ocular disease processes that could lead to the discovery of strong novel biomarkers and therapeutic targets useful in many ophthalmic conditions.

Proteomic analysis of Arabidopsis halleri shoots in response to the heavy metals cadmium and zinc and rhizosphere microorganisms

Arabidopsis halleri has the rare ability to colonize heavy metal-polluted sites and is an emerging model for research on adaptation and metal hyperaccumulation. The aim of this study was to analyze the effect of plant-microbe interaction on the accumulation of cadmium (Cd) and zinc (Zn) in shoots of an ecotype of A. halleri grown in heavy metal-contaminated soil and to compare the shoot proteome of plants grown solely in the presence of Cd and Zn or in the presence of these two metals and the autochthonous soil rhizosphere-derived microorganisms. The results of this analysis emphasized the role of plant-microbe interaction in shoot metal accumulation. Differences in protein expression pattern, identified by a proteomic approach involving 2-DE and MS, indicated a general upregulation of photosynthesis-related proteins in plants exposed to metals and to metals plus microorganisms, suggesting that metal accumulation in shoots is an energy-demanding process. The analysis also showed that proteins involved in plant defense mechanisms were downregulated indicating that heavy metals accumulation in leaves supplies a protection system and highlights a cross-talk between heavy metal signaling and defense signaling.

The myth of automated, high-throughput two-dimensional gel analysis

Many software packages have been developed to process and analyze 2-D gel images. Some programs have been touted as automated, high-throughput solutions. We tested five commercially available programs using 18 replicate gels of a rat brain protein extract. We determined computer processing time, approximate spot editing time, time required to correct spot mismatches, as well as total processing time. We also determined the number of spots automatically detected, number of spots kept after manual editing, and the percentage of automatically generated correct matches. We also determined the effect of increasing the number of replicate gels on spot matching efficiency for two of the programs. We found that for all programs tested, less than 3% of the total processing time was automated. The remainder of the time was spent in manual, subjective editing of detected spots and computer generated matches. Total processing time for 18 gels varied from 22 to 84 h. The percentage of correct matches generated automatically varied from 1 to 62%. Increasing the number of gels in an experiment dramatically reduced the percentage of automatically generated correct matches. Our results demonstrate that these 2-D gel analysis programs are not automatic or rapid, and also suggest that matching accuracy decreases as experiment size increases.

Methods for samples preparation in proteomic research

Sample preparation is one of the most crucial processes in proteomics research. The results of the experiment depend on the condition of the starting material. Therefore, the proper experimental model and careful sample preparation is vital to obtain significant and trustworthy results, particularly in comparative proteomics, where we are usually looking for minor differences between experimental-, and control samples. In this review we discuss problems associated with general strategies of samples preparation, and experimental demands for these processes.

Human body fluid proteome analysis

The focus of this article is to review the recent advances in proteome analysis of human body fluids, including plasma/serum, urine, cerebrospinal fluid, saliva, bronchoalveolar lavage fluid, synovial fluid, nipple aspirate fluid, tear fluid, and amniotic fluid, as well as its applications to human disease biomarker discovery. We aim to summarize the proteomics technologies currently used for global identification and quantification of body fluid proteins, and elaborate the putative biomarkers discovered for a variety of human diseases through human body fluid proteome (HBFP) analysis. Some critical concerns and perspectives in this emerging field are also discussed. With the advances made in proteomics technologies, the impact of HBFP analysis in the search for clinically relevant disease biomarkers would be realized in the future.

Methods for proteomics in neuroscience

Proteomics reveals complex protein expression, function, interactions and localization in different phenotypes of neuron. As proteomics, regarded as a highly complex screening technology, moves from a theoretical approach to practical reality, neuroscientists have to determine the most-appropriate applications for this technology. Even though proteomics compliments genomics, it is in sheer contrast to the basically constant genome due to its dynamic nature. Neuroscientists have to surmount difficulties particular to the research in neuroscience; such as limited sample amounts, heterogeneous cellular compositions in samples and the fact that many proteins of interest are hydrophobic proteins. The necessity of exclusive technology, sophisticated software and skilled manpower tops the challenge. This review examines subcellular organelle isolation, protein fractionation and separation using two-dimensional gel electrophoresis (2-DGE) as well as multi-dimensional liquid chromatography (LC) followed by mass spectrometry (MS). The methods for quantifying relative gene product expression between samples (e.g., two-dimensional difference in gel electrophoresis (2D-DIGE), isotope-coded affinity tag (ICAT) and iTRAQ) are elaborated. An overview of the techniques used currently to assign post-translational modification status on a proteomics scale is also evaluated. The feasible coverage of the proteome, ability to detect unique cell components such as post-synaptic densities and membrane proteins, resource requirements and quantitative as well as qualitative reliability of different approaches is also discussed. While there are many challenges in neuroproteomics, this field promises many returns in the future.