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[Methods for transcriptome and proteome research: applications for studying the biology of reproduction in cattle].

Improvements of animal health, welfare and product quality are major goals of modern animal breeding. Thus, in addition to the classical production traits, functional traits such as disease resistance, fertility and longevity moved into the center of animal breeder's interests. Due to their low heritability, the improvement of functional traits using conventional approaches of phenotypic testing and quantitative genetics is difficult. A number of studies have been conducted worldwide in various species to map quantitative trait loci (QTLs) and to identify genetic markers for health traits. This has revealed a plethora of chromosome regions which may harbor genes with relevance for animal health. Functional genome research integrates holistic investigations at the level of the genome, at the level of gene activity (transcriptome, proteome) and at various levels of phenotypic expression. The integration of all these levels of information provides the basis for the functional dissection of complex traits. This review provides an overview of the most important strategies for holistic transcriptome and proteome analyses. The successful application of these techniques is exemplified by our studies of bovine reproductive biology.

Animals↗
PubMed2005

Liquid Tissue: proteomic profiling of formalin-fixed tissues.

Identification and quantitation of candidate biomarker proteins in large numbers of individual tissues is required to validate specific proteins, or panels of proteins, for clinical use as diagnostic, prognostic, toxicological, or therapeutic markers. Mass spectrometry (MS) provides an exciting analytical methodology for this purpose. Liquid Tissue MS protein preparation allows researchers to utilize the vast, already existing, collections offormalin-fixed paraffin-embedded (FFPE) tissues for the procurement of peptides and the analysis across a variety of MS platforms.

Chromatography, Liquid↗
PubMed2004

Acute leukemia subclassification: a marker protein expression perspective.

Improved leukemia classification and tailoring of therapy have greatly improved patient outcome particularly for children with acute leukemia (AL). Using immunophenotyping, molecular genetics and cytogenetics the low hanging fruits of biomedical research have been successfully incorporated in routine diagnosis of leukemia subclasses. Future improvements in the classification and understanding of leukemia biology will very likely be more slow and laborious. Recently, gene expression profiling has provided a framework for the global molecular analysis of hematological cancers, and high throughput proteomic analysis of leukemia samples is on the way. Here we consider classification of acute leukemia samples by flow cytometry using the marker proteins of immunophenotyping as a component of the proteome. Marker protein expressions are converted into quantitative expression values and subjected to computational analysis. Quantitative multivariate analysis from panels of marker proteins has demonstrated that marker protein expression profiles can distinguish MLLre from non-MLLre ALL cases and also allow to specifically distinguish MLL/AF4 cases. Potentially, these quantitative expression analyses can be used in clinical diagnosis. Immunophenotypic data collection using flow cytometry is a fast and relatively easily accessible technology that has already been implemented in most centers for leukemia diagnosis and the translation into quantitative expression data sets is a matter of flow cytometer settings and output calibration. However, before application in clinical diagnostics can occur it is crucial that quantitative immunophenotypic data set analysis is validated in independent experiments and in large data sets.

Acute Disease↗
PubMed2005

Multidimensional fractionation of the bovine skeletal muscle proteome.

The ultimate goal of proteomics is to understand complex biological systems. The first step toward this end is the discovery of protein differences by profiling a given proteome. One approach to proteome profiling is to fractionate it into intact proteins, with subsequent identification and quantitation. In this work, lysates of bovine skeletal muscle were prepared. Reproducible proteome profiles were generated by an automatic two-dimensional protein fractionation system. Proteins were separated by isoelectric point and then by hydrophobicity. The data collected from both separations were used to generate proteome profiles. A high protein content fraction with pl above 8.5 was digested with trypsin, and its main protein component was identified as lysozyme C by matrix assisted laser desorption/ionization-time of flight mass spectrometry.

Animals↗
PubMed2004

Tracking cell signaling protein expression and phosphorylation by innovative proteomic solutions.

The most challenging and fruitful biomedical research endeavor of this decade will be the mapping of cell signaling systems and establishing their linkages to normal and disease-related processes. Amongst other things, the Human Genome Sequencing Project has greatly facilitated MALDI-TOF mass spectrometry identification of proteins that have been resolved by standard 2D gel electrophoresis. However, the low abundance of protein kinases and other signal transduction proteins has rendered their analyses particularly problematic without some means of purification and enrichment from cell and tissue lysates. Antibodies have been the most specific affinity probes for tracking target proteins, but their variable quality and high cost preclude their deployment in most discovery-based proteomics studies. Current multi-immunoblotting techniques can permit the probing of a single mini-SDS-PAGE gel with 50 or more antibodies at a time to monitor large changes in the expression and phosphorylation states of signaling proteins. The development of new affinity probes to replace antibodies is necessary to drive large scale proteomics studies. Such affinity probes could include short peptide antibody mimetics (PAM's) and oligonucleotide aptamers that when spotted in 2D array formats (e.g. membrane macroarrays, glass microarrays) or presented on specific beads (e.g. Luminex beads) can capture target proteins for their specific enrichment. The bound target proteins can then be detected using reporter antibodies or other specific probes for their quantitation by high throughput systems. These new proteomics methodologies will accelerate assessment of specific protein expression, post-translational modification, protein-protein interactions and protein-drug interactions to provide a more holistic view of cellular operations and how they might be manipulated under pathological circumstances.

Animals↗
PubMed2000

A quantitative, high-throughput screen for protein stability.

In proteomic research, it is often necessary to screen a large number of polypeptides for the presence of stable structure. Described here is a technique (referred to as SUPREX, stability of unpurified proteins from rates of H/D exchange) for measuring the stability of proteins in a rapid, high-throughput fashion. The method uses hydrogen exchange to estimate the stability of microgram quantities of unpurified protein extracts by using matrix-assisted laser desorption/ionization MS. The stabilities of maltose binding protein and monomeric lambda repressor variants determined by SUPREX agree well with stability data obtained from conventional CD denaturation of purified protein. The method also can detect the change in stability caused by the binding of maltose to maltose binding protein. The results demonstrate the precision of the method over a wide range of stabilities.

Bacterial Proteins↗
PubMed2026

Enzyme kinetics shapes the growth response of metabolic networks.

Microbes adjust their metabolism to environmental challenges by changing protein expression levels, metabolite concentrations, and reaction rates. Average expression levels in large proteome sectors change coherently, while individual proteins show divergent shifts even within the same pathway. Here, we establish a metabolic model that integrates local enzyme kinetics and global network architecture to predict the joint growth response of proteins and metabolites. Under nutrient limitation, we predict a remarkably simple pattern of proteome reallocation with growth rate: protein expression levels change linearly but heterogeneously. For a given enzyme, the direction of change is determined by its local kinetic constants - catalytic rate and substrate affinity - and by the degree of nutrient restriction affecting its embedding pathway. This double-graded growth response of the proteome is mediated by restriction-dependent metabolite levels, which are predicted to decrease with growth rate in a nonlinear way. The model establishes three specific growth laws: protein expression changes of individual enzymes are negatively correlated with their expression and with their substrate saturation at high growth; average changes of pathways and larger functional sectors are correlated with their internal variance. These predictions are in quantitative agreement with measured system-wide proteomics and metabolomics data of E. coli. Enzyme-specific response patterns are a starting point for model-guided interventions into bacterial metabolism.

Kinetics↗
PubMed2006

Engineering challenges of BioNEMS: the integration of microfluidics, micro- and nanodevices, models and external control for systems biology.

Systems biology, i.e. quantitative, postgenomic, postproteomic, dynamic, multiscale physiology, addresses in an integrative, quantitative manner the shockwave of genetic and proteomic information using computer models that may eventually have 10(6) dynamic variables with non-linear interactions. Historically, single biological measurements are made over minutes, suggesting the challenge of specifying 10(6) model parameters. Except for fluorescence and micro-electrode recordings, most cellular measurements have inadequate bandwidth to discern the time course of critical intracellular biochemical events. Micro-array expression profiles of thousands of genes cannot determine quantitative dynamic cellular signalling and metabolic variables. Major gaps must be bridged between the computational vision and experimental reality. The analysis of cellular signalling dynamics and control requires, first, micro- and nano-instruments that measure simultaneously multiple extracellular and intracellular variables with sufficient bandwidth; secondly, the ability to open existing internal control and signalling loops; thirdly, external BioMEMS micro-actuators that provide high bandwidth feedback and externally addressable intracellular nano-actuators; and, fourthly, real-time, closed-loop, single-cell control algorithms. The unravelling of the nested and coupled nature of cellular control loops requires simultaneous recording of multiple single-cell signatures. Externally controlled nano-actuators, needed to effect changes in the biochemical, mechanical and electrical environment both outside and inside the cell, will provide a major impetus for nanoscience.

Animals↗
PubMed2006

Comparative proteomics of glycosomes from bloodstream form and procyclic culture form Trypanosoma brucei brucei.

Peroxisomes are present in nearly every eukaryotic cell and compartmentalize a wide range of important metabolic processes. Glycosomes of Kinetoplastid parasites are peroxisome-like organelles, characterized by the presence of the glycolytic pathway. The two replicating stages of Trypanosoma brucei brucei, the mammalian bloodstream form (BSF) and the insect (procyclic) form (PCF), undergo considerable adaptations in metabolism when switching between the two different hosts. These adaptations involve also substantial changes in the proteome of the glycosome. Comparative (non-quantitative) analysis of BSF and PCF glycosomes by nano LC-ESI-Q-TOF-MS resulted in the validation of known functional aspects of glycosomes and the identification of novel glycosomal constituents.

Animals↗
PubMed2026

Moving Beyond Morphology to Multiplexed Molecular Imaging as the Next Frontier in Diagnostic Pathology.

Diagnostic pathology has long relied on the morphologic interpretation of hematoxylin and eosin-stained tissues to guide diagnosis and assess prognostic features. Although pathologists intuitively recognize spatial patterns and architectural organization, these assessments remain largely qualitative and difficult to quantify systematically. Immunohistochemistry and immunofluorescence have introduced molecular specificity but are limited in multiplexing capacity, whereas bulk genomic and transcriptomic assays provide high molecular depth but lose spatial context by averaging signals across heterogeneous cell populations. Recent advances in spatial proteomics-including mass spectrometry-based imaging and cyclic immunofluorescence-now enable multiplexed, single-cell protein analysis within intact tissue architecture. These technologies have revealed complex immune and stromal microenvironments, spatially organized biomarkers predictive of therapeutic response, and molecular gradients underlying disease progression. By integrating histologic and molecular information, spatial proteomics bridges traditional microscopy with high-dimensional omics, allowing quantitative, spatially resolved insights into tissue organization and disease mechanisms. This review summarizes recent developments in multiplexed spatial proteomics from both scientific and pathologic perspectives, highlighting how these technologies extend beyond morphology to quantify histologic patterns, refine biomarker discovery, and facilitate clinical translation. The review also examines translational challenges and barriers to clinical implementation, including costs, standardization requirements, and workflow integration.

Humans↗
PubMed2006

Proteomic profiling of differentiating osteoblasts.

The major event that triggers osteogenesis is the transition of mesenchymal stem cells into bone-forming, differentiating osteoblast cells. Osteoblast differentiation is the primary event of bone formation, exemplified by the synthesis, deposition and mineralization of extracellular matrix. Osteoblast differentiation is controlled tightly by sequential activation of diverse transcription factors that regulate the expression of specific genes. The spatial and temporal regulation of the differentiation process is not completely understood at the cellular or molecular level. Recent advances in mass spectrometry-based proteomics have allowed for the systematic qualitative and quantitative profiling of differentiating osteoblasts, enabling a better understanding of the multiple factors and signaling events that control the differentiation process at a molecular level. This review focuses on recent developments in the proteomic analysis of differentiating osteoblasts, including advances, challenges and future prospects of using mass spectrometry to investigate the local and systemic factors regulating bone formation and its homeostasis.

Animals↗
PubMed2002

Proteomic analysis of striated muscle.

The techniques collectively known as proteomics are useful for characterizing the protein phenotype of a particular tissue or cell as well as quantitatively identifying differences in the levels of individual proteins following modulation of a tissue or cell. In the area of striated muscle research, proteomics has been a useful tool for identifying qualitative and quantitative changes in the striated muscle protein phenotype resulting from either disease or physiological modulation. Proteomics is useful for these investigations because many of the changes in the striated muscle phenotype resulting from either disease or changes in physiological state are qualitative and not quantitative changes. For example, modification of striated muscle proteins by phosphorylation and proteolytic cleavage are readily observed using proteomic technologies while these changes would not be identified using genomic technology. In this review, I will discuss the application of proteomic technology to striated muscle research, research designed to identify key protein changes that are either causal for or markers of a striated muscle disease or physiological condition.

Animals↗
PubMed2026

Integrative proteogenomic and observational analysis identifies potential biomarkers for latent autoimmune diabetes in adults.

BACKGROUND: Latent autoimmune diabetes in adults (LADA) shares core genetic and immunological features with type 1 diabetes (T1D) but is frequently misdiagnosed as type 2 diabetes (T2D). With few biomarkers for its timely diagnosis and management, this study integrated proteome-wide Mendelian randomisation (MR) and observational clinical analysis to identify potential LADA biomarkers. METHODS: We performed proteome-wide MR using cis-protein quantitative trait loci (cis-pQTLs) for 1,389 plasma proteins from the deCODE study (n = 35,559) and genome-wide association study (GWAS) data for LADA (2,634 cases and 5,947 controls, European ancestry). Robustness was enhanced via multiple sensitivity analyses. Pathway enrichment analysis, druggability evaluation, phenome-wide MR, and interaction analyses were performed to investigate the clinical relevance and biological context of candidate proteins. Candidate proteins were further evaluated using enzyme-linked immunosorbent assays in a matched Chinese clinical study (n = 241) to assess their discriminative ability for LADA. RESULTS: Proteome-wide MR and colocalisation analyses indicated associations between genetically predicted plasma levels of C-X-C motif chemokine ligand 10 (CXCL10; OR [95% CI] per 1-SD increase in protein levels: 5.49 [1.74,17.32]), serum amyloid A1 (SAA1; 1.28 [1.14,1.45]), and SAA2 (1.22 [1.11,1.34]) with LADA risk. Replication, multi-tissue eQTL, and multivariable MR supported CXCL10's association. Druggability evaluation suggested CXCL10 as a drug target under investigation, and phenome-wide MR of 1,006 diseases and traits indicated no major safety concerns for CXCL10 as a potential biomarker. In the observational clinical study, CXCL10 differentiated LADA from healthy controls (area under the receiver operating characteristic curve [ROC-AUC]: 0.889; precision-recall area under the curve [PR-AUC]: 0.919) and T2D (ROC-AUC: 0.838; PR-AUC: 0.921), with both models showing adequate calibration. CONCLUSIONS: This study suggests that CXCL10 is a putative biomarker associated with LADA, demonstrating discriminative ability to distinguish LADA from T2D in an observational clinical cohort. These findings contribute to understanding the autoimmune molecular aetiology of LADA and support its diagnostic potential in resolving the clinical ambiguity between LADA and T2D.

Humans↗
PubMed2005

Weighing in on ubiquitin: the expanding role of mass-spectrometry-based proteomics.

Mass-spectrometry-based proteomics has become an essential tool for the qualitative and quantitative analysis of cellular systems. The biochemical complexity and functional diversity of the ubiquitin system are well suited to proteomic studies. This review summarizes advances involving the identification of ubiquitinated proteins, the elucidation of ubiquitin-modification sites and the determination of polyubiquitin chain linkages, as well as offering a perspective on the application of emerging technologies for mechanistic and functional studies of protein ubiquitination.

Animals↗
PubMed2006

CyDye immunoblotting for proteomics: co-detection of specific immunoreactive and total protein profiles.

The development of ECL-Plex CyDye-conjugated secondary antibodies allows the advancement of conventional Western blotting, opening up possibilities for highly sensitive and quantitative protein confirmation and identification. We report a novel proteomic method to simultaneously visualise the total protein profile as well as the specific immunodetection of an individual protein species by combining cyanine CyDye pre-labelled proteins and antibody immunoblotting. This technique proposes to revolutionise both 2-D immunoprobing and protein confirmation following MS analysis.

Amino Acid Sequence↗
PubMed2002

Proteomics based on high-efficiency capillary separations.

Identifying and quantifying in a high throughput manner the proteins expressed by cells, tissues or an organism provides the basis for understanding the functions of its constituents at a "systems" level. As a result, proteome analysis has increasingly become the focus of significant interest and research over the past decade. This is especially true following the recent stunning achievements in genomics analyses. However, unlike the static genome, the complexities and dynamism of the proteome present significant analytical challenges and demand highly efficient separations and detection technologies. A number of recent technological advancements have been in direct response to these challenges. Currently, strategically mated combinations of sophisticated separations techniques and advanced mass spectrometric detection represent the best approach to addressing the intricacies of the proteome. Liquid-phase separations, often within capillaries, are increasingly recognized as the best separations technique for this approach. In combination on-line with mass spectrometry, liquid-phase separations provide the improved analytical sensitivity, sample throughput, and quantitation capabilities necessitated by the multifaceted problems within proteomics analyses. This review focuses primarily on current high-efficiency capillary separations techniques, including both capillary liquid chromatography and capillary electrophoresis, applied to the analysis of complex proteomic samples. We emphasize developments at our laboratory and illustrate technical advances that attempt to review the role of separations within the broader context of a state-of-the-art integrated proteomics effort.

Chromatography, Liquid↗
PubMed2003

Stable isotope-coded proteomic mass spectrometry.

Developing the ability to quantify changes in protein abundance between cells subjected to a variety of physiological and environmental conditions is an extremely active area of proteome research. Although advances in chromatography, mass spectrometry instrumentation, and bioinformatics have contributed to producing a viable method for comparative proteome-wide analyses, the highest precision of quantitation is based, in part, upon improved methods for chemical and metabolic stable isotope labeling of proteins and peptides. The ability to quantify differences in protein expression and post-translational modifications using stable isotope labeling has been achieved, but insights into the biochemical mechanisms that will contribute to the development of new biotechnologies have yet to be realized.

Affinity Labels↗
PubMed2006

Microplate-based, label-free detection of biomolecular interactions: applications in proteomics.

This review describes a new type of label-free optical biosensor that is inexpensively manufactured from continuous sheets of plastic film and incorporated into standard format microplates to enable highly sensitive, high-throughput detection of small molecules, proteins and cells. The biosensor and associated detection instrumentation are applied to review two fundamental limiting issues for assays in proteomics research and drug discovery: requirement for quantitative measurement of protein concentration and specific activity, and measurements made with complex systems in highly parallel measurements. SRU BIosystems, Inc.'s BIND label-free detection will address these issues using data examples for hybridoma screening, epitope binning and mapping, small-molecule screening, and cell-based functional assays. The review describes several additional applications that are under development for the system, and the key issues that will drive adoption of the technology over the next 5 years.

Biosensing Techniques↗