Quantitative Proteomic Analysis Using Isobaric Protein Tags Enables Rapid Comparison of Changes in Transcript and Protein Levels in Transformed Cells

Proteomic Analysis Dissects Molecular Mechanisms Underlying Plant Responses to Phosphorus Deficiency

Phosphorus (P) is an essential nutrient for plant growth. In recent decades, the application of phosphate (Pi) fertilizers has contributed to significant increases in crop yields all over the world. However, low efficiency of P utilization in crops leads to intensive application of Pi fertilizers, which consequently stimulates environmental pollution and exhaustion of P mineral resources. Therefore, in order to strengthen the sustainable development of agriculture, understandings of molecular mechanisms underlying P efficiency in plants are required to develop cultivars with high P utilization efficiency. Recently, a plant Pi-signaling network was established through forward and reverse genetic analysis, with the aid of the application of genomics, transcriptomics, proteomics, metabolomics, and ionomics. Among these, proteomics provides a powerful tool to investigate mechanisms underlying plant responses to Pi availability at the protein level. In this review, we summarize the recent progress of proteomic analysis in the identification of differential proteins that play roles in Pi acquisition, translocation, assimilation, and reutilization in plants. These findings could provide insights into molecular mechanisms underlying Pi acquisition and utilization efficiency, and offer new strategies in genetically engineering cultivars with high P utilization efficiency.

Recent Developments in Clinical Plasma Proteomics—Applied to Cardiovascular Research

The human plasma proteome mirrors the physiological state of the cardiovascular system, a fact that has been used to analyze plasma biomarkers in routine analysis for the diagnosis and monitoring of cardiovascular diseases for decades. These biomarkers address, however, only a very limited subset of cardiovascular diseases, such as acute myocardial infarct or acute deep vein thrombosis, and clinical plasma biomarkers for the diagnosis and stratification cardiovascular diseases that are growing in incidence, such as heart failure and abdominal aortic aneurysm, do not exist and are urgently needed. The discovery of novel biomarkers in plasma has been hindered by the complexity of the human plasma proteome that again transforms into an extreme analytical complexity when it comes to the discovery of novel plasma biomarkers. This complexity is, however, addressed by recent achievements in technologies for analyzing the human plasma proteome, thereby facilitating the possibility for novel biomarker discoveries. The aims of this article is to provide an overview of the recent achievements in technologies for proteomic analysis of the human plasma proteome and their applications in cardiovascular medicine.

Narrow Precursor Mass Range for DIA-MS Enhances Protein Identification and Quantification in Arabidopsis

Data independent acquisition-mass spectrometry (DIA-MS) is becoming widely utilised for robust and accurate quantification of samples in quantitative proteomics. Here, we describe the systematic evaluation of the effects of DIA precursor mass range on total protein identification and quantification. We show that a narrow mass range of precursors (~250 m/z) for DIA-MS enables a higher number of protein identifications. Subsequent application of DIA with narrow precursor range (from 400 to 650 m/z) on an Arabidopsis sample with spike-in known proteins identified 34.7% more proteins than in conventional DIA (cDIA) with a wide precursor range of 400-1200 m/z. When combining several DIA-MS analyses with narrow precursor ranges (i.e., 400-650, 650-900 and 900-1200 m/z), we were able to quantify 10,099 protein groups with a median coefficient of variation of <6%. These findings represent a 54.7% increase in the number of proteins quantified than with cDIA analysis. This is particularly important for low abundance proteins, as exemplified by the six-protein mix spike-in. In cDIA only five out of the six-protein mix were quantified while our approach allowed accurate quantitation of all six proteins.

Combining Precursor and Fragment Information for Improved Detection of Differential Abundance in Data Independent Acquisition

In bottom-up, label-free discovery proteomics, biological samples are acquired in a data-dependent (DDA) or data-independent (DIA) manner, with peptide signals recorded in an intact (MS1) and fragmented (MS2) form. While DDA has only the MS1 space for quantification, DIA contains both MS1 and MS2 at high quantitative quality. DIA profiles of complex biological matrices such as tissues or cells can contain quantitative interferences, and the interferences at the MS1 and the MS2 signals are often independent. When comparing biological conditions, the interferences can compromise the detection of differential peptide or protein abundance and lead to false positive or false negative conclusions.We hypothesized that the combined use of MS1 and MS2 quantitative signals could improve our ability to detect differentially abundant proteins. Therefore, we developed a statistical procedure incorporating both MS1 and MS2 quantitative information of DIA. We benchmarked the performance of the MS1-MS2-combined method to the individual use of MS1 or MS2 in DIA using four previously published controlled mixtures, as well as in two previously unpublished controlled mixtures. In the majority of the comparisons, the combined method outperformed the individual use of MS1 or MS2. This was particularly true for comparisons with low fold changes, few replicates, and situations where MS1 and MS2 were of similar quality. When applied to a previously unpublished investigation of lung cancer, the MS1-MS2-combined method increased the coverage of known activated pathways.Since recent technological developments continue to increase the quality of MS1 signals (e.g. using the BoxCar scan mode for Orbitrap instruments), the combination of the MS1 and MS2 information has a high potential for future statistical analysis of DIA data.

Arabidopsis proteome and the mass spectral assay library

Arabidopsis is an important model organism and the first plant with its genome completely sequenced. Knowledge from studying this species has either direct or indirect applications for agriculture and human health. Quantitative proteomics by data-independent acquisition mass spectrometry (SWATH/DIA-MS) was recently developed and is considered as a high-throughput, massively parallel targeted approach for accurate proteome quantification. In this approach, a high-quality and comprehensive spectral library is a prerequisite. Here, we generated an expression atlas of 10 organs of Arabidopsis and created a library consisting of 15,514 protein groups, 187,265 unique peptide sequences, and 278,278 precursors. The identified protein groups correspond to ~56.5% of the predicted proteome. Further proteogenomics analysis identified 28 novel proteins. We applied DIA-MS using this library to quantify the effect of abscisic acid on Arabidopsis. We were able to recover 8,793 protein groups of which 1,787 were differentially expressed. MS data are available via ProteomeXchange with identifier PXD012708 and PXD012710 for data-dependent acquisition and PXD014032 for DIA analyses.

Arabidopsis proteome and the mass spectral assay library

Arabidopsis is an important model organism and the first plant with its genome completely sequenced. Knowledge from studying this species has either direct or indirect applications for agriculture and human health. Quantitative proteomics by data-independent acquisition mass spectrometry (SWATH/DIA-MS) was recently developed and is considered as a high-throughput, massively parallel targeted approach for accurate proteome quantification. In this approach, a high-quality and comprehensive spectral library is a prerequisite. Here, we generated an expression atlas of 10 organs of Arabidopsis and created a library consisting of 15,514 protein groups, 187,265 unique peptide sequences, and 278,278 precursors. The identified protein groups correspond to ~56.5% of the predicted proteome. Further proteogenomics analysis identified 28 novel proteins. We applied DIA-MS using this library to quantify the effect of abscisic acid on Arabidopsis. We were able to recover 8,793 protein groups of which 1,787 were differentially expressed. MS data are available via ProteomeXchange with identifier PXD012708 and PXD012710 for data-dependent acquisition and PXD014032 for DIA analyses.

Arabidopsis proteome and the mass spectral assay library

Arabidopsis is an important model organism and the first plant with its genome completely sequenced. Knowledge from studying this species has either direct or indirect applications for agriculture and human health. Quantitative proteomics by data-independent acquisition mass spectrometry (SWATH/DIA-MS) was recently developed and is considered as a high-throughput, massively parallel targeted approach for accurate proteome quantification. In this approach, a high-quality and comprehensive spectral library is a prerequisite. Here, we generated an expression atlas of 10 organs of Arabidopsis and created a library consisting of 15,514 protein groups, 187,265 unique peptide sequences, and 278,278 precursors. The identified protein groups correspond to ~56.5% of the predicted proteome. Further proteogenomics analysis identified 28 novel proteins. We applied DIA-MS using this library to quantify the effect of abscisic acid on Arabidopsis. We were able to recover 8,793 protein groups of which 1,787 were differentially expressed. MS data are available via ProteomeXchange with identifier PXD012708 and PXD012710 for data-dependent acquisition and PXD014032 for DIA analyses.

Measurement(s)	Proteome
Technology Type(s)	mass spectrometry assay • computational modeling technique
Sample Characteristic - Organism	Arabidopsis thaliana

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.9959036

Labeled quantitative mass spectrometry to study the host response during aspergillosis in the common bottlenose dolphin (Tursiops truncatus)

Aspergillosis is a fungal infection caused by Aspergillus molds that can affect both humans and animals. Despite advances in diagnostics and therapy, medical management of this disease remains difficult. Expansion of the basic knowledge regarding its pathophysiology in animals is critical to aid in the identification of new biomarkers of infection for diagnosis and therapeutic targets. For such a purpose, proteomics can be used by addressing protein changes during various disease processes. In the present study, a mass spectrometry analysis based on isobaric tagging for relative and absolute quantitation (iTRAQ^®) was applied for direct identification and relative quantitation of proteins in blood collected from 32 Aspergillus-diseased common bottlenose dolphins (Tursiops truncatus, 32 samples) in comparison with blood from 55 other dolphins (55 samples from 41 clinically-normal controls and from 14 cetaceans with miscellaneous non-Aspergillus inflammation diseases) and ten convalescent dolphins (28 samples). Sixty-six and 40 proteins were found to be ≥2.0-fold over- and underrepresented versus miscellaneous non-Aspergillus inflammatory dolphins, respectively, and most were confirmed vs. clinically-normal controls and convalescents. Many proteins which play a role in the adaptive immune response were identified, including MHC proteins and others involved in catalytic activity like the NADPH-ubiquinone oxido-reductases. Overall, iTRAQ^® appears to be a convenient proteomic tool greatly suited for exploratory ex vivo studies focusing on pathophysiology. This technique should be considered as a preliminary step before validation of new diagnostic markers.

Mass Spectrometry-Based Proteomics to Define Intracellular Collagen Interactomes

We present the development, optimization, and application of constructs, cell lines, covalent cross-linking methods, and immunoprecipitation strategies that enable robust and accurate determination of collagen interactomes via mass spectrometry-based proteomics. Using collagen type-I as an example, protocols for working with large, repetitive, and GC-rich collagen genes are described, followed by strategies for engineering cells that stably and inducibly express antibody epitope-tagged collagen-I. Detailed steps to optimize collagen interactome cross-linking and perform immunoprecipitations are then presented. We conclude with a discussion of methods to elute collagen interactomes and prepare samples for mass spectrometry-mediated identification of interactors. Throughout, caveats and potential problems researchers may encounter when working with collagen are discussed. We note that the protocols presented herein may be readily adapted to define interactomes of other collagen types, as well as to determine comparative interactomes of normal and disease-causing collagen variants using quantitative isotopic labeling (SILAC)- or isobaric mass tags (iTRAQ or TMT)-based mass spectrometry analysis.

Advances in Biomarker Studies in Autism Spectrum Disorders

Autism spectrum disorder (ASD) is a neurological and developmental condition that begins early in childhood and lasts throughout life. The epidemiology of ASD is continuously increasing all over the world with huge social and economical burdens. As the etiology of autism is not completely understood, there is still no medication available for the treatment of this disorder. However, some behavioral interventions are available to improve the core and associated symptoms of autism, particularly when initiated at an early stage. Thus, there is an increasing demand for finding biomarkers for ASD. Although diagnostic biomarkers have not yet been established, research efforts have been carried out in neuroimaging and biological analyses including genomics and gene testing, proteomics, metabolomics, transcriptomics, and studies of the immune system, inflammation, and microRNAs. Here, we will review the current progress in these fields and focus on new methods, developments, research strategies, and studies of blood-based biomarkers.

Multiparameter Optimization of Two Common Proteomics Quantification Methods for Quantifying Low-Abundance Proteins

Quantitative proteomics has been extensively applied in the screening of differentially regulated proteins in various research areas for decades, but its sensitivity and accuracy have been a bottleneck for many applications. Every step in the proteomics workflow can potentially affect the quantification of low-abundance proteins, but a systematic evaluation of their effects has not been done yet. In this work, to improve the sensitivity and accuracy of label-free quantification and tandem mass tags (TMT) labeling in quantifying low-abundance proteins, multiparameter optimization was carried out using a complex 2-proteome artificial sample mixture for a series of steps from sample preparation to data analysis, including the desalting of peptides, peptide injection amount for LC-MS/MS, MS1 resolution, the length of LC-MS/MS gradient, AGC targets, ion accumulation time, MS2 resolution, precursor coisolation threshold, data analysis software, statistical calculation methods, and protein fold changes, and the best settings for each parameter were defined. The suitable cutoffs for detecting low-abundance proteins with at least 1.5-fold and 2-fold changes were identified for label-free and TMT methods, respectively. The use of optimized parameters will significantly improve the overall performance of quantitative proteomics in quantifying low-abundance proteins and thus promote its application in other research areas.

Data-independent acquisition-based SWATH-MS for quantitative proteomics: a tutorial

Many research questions in fields such as personalized medicine, drug screens or systems biology depend on obtaining consistent and quantitatively accurate proteomics data from many samples. SWATH-MS is a specific variant of data-independent acquisition (DIA) methods and is emerging as a technology that combines deep proteome coverage capabilities with quantitative consistency and accuracy. In a SWATH-MS measurement, all ionized peptides of a given sample that fall within a specified mass range are fragmented in a systematic and unbiased fashion using rather large precursor isolation windows. To analyse SWATH-MS data, a strategy based on peptide-centric scoring has been established, which typically requires prior knowledge about the chromatographic and mass spectrometric behaviour of peptides of interest in the form of spectral libraries and peptide query parameters. This tutorial provides guidelines on how to set up and plan a SWATH-MS experiment, how to perform the mass spectrometric measurement and how to analyse SWATH-MS data using peptide-centric scoring. Furthermore, concepts on how to improve SWATH-MS data acquisition, potential trade-offs of parameter settings and alternative data analysis strategies are discussed.

Translational proteomic study to address host protein changes during aspergillosis

Aspergillosis is a fungal disease due to Aspergillus molds that can affect both humans and animals. As routine diagnosis remains difficult, improvement of basic knowledge with respect to its pathophysiology is critical to search for new biomarkers of infection and new therapeutic targets. Large-scale proteomics allows assessment of protein changes during various disease processes. In the present study, mass spectrometry iTRAQ® (isobaric tags for relative and absolute quantitation) protocol was used for direct identification and relative quantitation of host proteins in diseased fluids and tissues collected from an experimental rat model challenged with Aspergillus, as well as in blood obtained from naturally-infected penguins. In all, mass spectrometry analysis revealed that proteome during aspergillosis was mostly represented by proteins that usually express role in metabolic processes and biological process regulation. Ten and 17 proteins were significantly ≥4.0-fold overrepresented in blood of Aspergillus-diseased rats and penguins, respectively, while five and 39 were negatively ≥4.0-fold depleted within the same samples. In rat lungs, 33 proteins were identified with positive or negative relative changes versus controls and were quite different from those identified in the blood. Except for some zinc finger proteins, kinases, and histone transferases, and while three pathways were common (Wnt, cadherin and FGF), great inter-species variabilities were observed regarding the identity of the differentially-represented proteins. Thus, this finding confirmed how difficult it is to define a unique biomarker of infection. iTRAQ® protocol appears as a convenient proteomic tool that is greatly suited to ex vivo exploratory studies and should be considered as preliminary step before validation of new diagnostic markers and new therapeutic targets in humans.

New developments in transplant proteomics

PURPOSE OF REVIEW

Despite modern immunosuppression, renal allograft rejection remains a major contributor to graft loss. Novel biomarkers may help improve posttransplant outcomes through the early detection and treatment of rejection. Our objective is to provide an overview of proteomics, review recent discovery-based rejection studies, and explore innovative approaches in biomarker development.

RECENT FINDINGS

Urine MMP7 was identified as a biomarker of subclinical and clinical rejection using two-dimensional liquid chromatography tandem-mass spectrometry (LC-MS/MS) and improved the overall diagnostic discrimination of urine CXCL10 : Cr alone for renal allograft inflammation. A novel peptide signature to classify stable allografts from acute rejection, chronic allograft injury, and polyoma virus (BKV) nephropathy was identified using isobaric tag for relative and absolute quantitation (TRAQ) and label-free MS, with independent validation by selected reaction monitoring mass spectrometry (SRM-MS). Finally, an in-depth exploration of peripheral blood mononuclear cells identified differential proteoform expression in healthy transplants versus rejection.

SUMMARY

There is still much in the human proteome that remains to be explored, and further integration of renal, urinary, and exosomal data may offer deeper insight into the pathophysiology of rejection. Functional proteomics may be more biologically relevant than protein/peptide quantity alone, such as assessment of proteoforms or activity-based protein profiling. Discovery-based studies have identified potential biomarker candidates, but external validation studies are required.

Application of mass spectrometry to elucidate the pathophysiology of Encephalitozoon cuniculi infection in rabbits

Encephalitozoon cuniculi is a microsporidian species which can induce subclinical to serious disease in mammals including rabbits, a definitive natural host. The pathophysiology of infection has not been comprehensively elucidated. In this exploratory study, we utilized two mass spectrometry approaches: first, the analysis of the humoral response by profiling the microsporidian antigens as revealed by Western blot screening, and second, implementing the iTRAQ®-labeling protocol to focus on the changes within the host proteome during infection. Seven E. cuniculi proteins were identified at one-dimensional gel regions where specific seropositive reaction was observed by Western blot, including polar tube protein 3, polar tube protein 2, and for the first time reported: heat shock related 70kDa protein, polysaccharide deacetylase domain-containing protein, zinc finger protein, spore wall and anchoring disk complex protein EnP1, and translation elongation factor 1 alpha. In addition, there was a significant increase of nine host proteins in blood samples from E. cuniculi-diseased rabbits in comparison with non-diseased control subjects undergoing various inflammatory processes. This included serum paraoxonase, alpha-1-antiproteinase F precursor and alpha-1-antiproteinase S-1 which have presumptive catalytic activity likely related to infection control, and cystatin fetuin-B-type, an enzyme regulator that has been poorly studied to date. Notably, 11 proteins were found to be statistically increased in rabbits with neurological versus renal clinical presentation of E. cuniculi infection. Overall, this novel analysis based on mass spectrometry has provided new insights on the inflammatory and humoral responses during E. cuniculi infection in rabbits.

Dynamics of protein secretion during adipocyte differentiation

The major functions of adipocytes include both lipid storage and the production of secretory factors. However, the type of proteins released from mouse 3T3-L1 cells during adipocyte differentiation remains poorly understood. We examined the dynamics of secreted proteins during adipocyte differentiation using mass spectrometry (MS) combined with an iTRAQ (®) labeling method that enables the simultaneous analysis of relative protein expression levels. A total of 215 proteins were identified and quantified from approximately 10 000 MS/MS spectra. Of these, approximately 38% were categorized as secreted proteins based on gene ontology classification. Adipokine secretion levels were increased with the progression of differentiation. By contrast, levels of fibril collagen components, such as subunits of type I and III collagens, were decreased during differentiation. Basement membrane components attained their peak levels at day 4 when small lipid droplets accumulated in differentiated 3T3-L1 cells. Simultaneously, peak levels of collagen microfibril components that comprise type V and VI collagen subunits were also observed. Our data demonstrated that extracellular matrix components were predominantly released during the early and middle stages of adipocyte differentiation, with a subsequent increase in the secretion of adipokines. This suggests that 3T3-L1 cells secrete adipokines after their ECM is constructed during adipocyte differentiation.

Quantitative proteomic analysis reveals maturation as a mechanism underlying glucocorticoid resistance in B lineage ALL and re-sensitization by JNK inhibition

Glucocorticoid (GC) resistance is a continuing clinical problem in childhood acute lymphoblastic leukaemia (ALL) but the underlying mechanisms remain unclear. A proteomic approach was used to compare profiles of the B-lineage ALL GC-sensitive cell line, PreB 697, and its GC-resistant sub-line, R3F9, pre- and post-dexamethasone exposure. PAX5, a transcription factor critical to B-cell development was differentially regulated in the PreB 697 compared to the R3F9 cell line in response to GC. PAX5 basal protein expression was less in R3F9 compared to its GC-sensitive parent and confirmed to be lower in other GC-resistant sub-lines of Pre B 697 and was associated with a decreased expression of the PAX5 transcriptional target, CD19. Gene set enrichment analysis showed that increasing GC-resistance was associated with differentiation from preB-II to an immature B-lymphocyte stage. GC-resistant sub-lines were shown to have higher levels of phosphorylated JNK compared to the parent line and JNK inhibition caused re-sensitization to GC. Exploiting this maturation may be key to overcoming GC resistance and targeting signalling pathways linked to the maturation state, such as JNK, may be a novel approach.

Exploiting the multiplexing capabilities of tandem mass tags for high-throughput estimation of cellular protein abundances by mass spectrometry

The generation of dynamic models of biological processes critically depends on the determination of precise cellular concentrations of biomolecules. Measurements of system-wide absolute protein levels are particularly valuable information in systems biology. Recently, mass spectrometry based proteomics approaches have been developed to estimate protein concentrations on a proteome-wide scale. However, for very complex proteomes, fractionation steps are required, increasing samples number and instrument analysis time. As a result, the number of full proteomes that can be routinely analyzed is limited. Here we combined absolute quantification strategies with the multiplexing capabilities of isobaric tandem mass tags to determine cellular protein abundances in a high throughput and proteome-wide scale even for highly complex biological systems, such as a whole human cell line. We generated two independent data sets to demonstrate the power of the approach regarding sample throughput, dynamic range, quantitative precision and accuracy as well as proteome coverage in comparison to existing mass spectrometry based strategies.

Quantitative phosphoproteome analysis of embryonic stem cell differentiation toward blood

Murine embryonic stem (ES) cells can differentiate in vitro into three germ layers (endodermic, mesodermic, ectodermic). Studies on the differentiation of these cells to specific early differentiation stages has been aided by an ES cell line carrying the Green Fluorescent Protein (GFP) targeted to the Brachyury (Bry) locus which marks mesoderm commitment. Furthermore, expression of the Vascular Endothelial Growth Factor receptor 2 (Flk1) along with Bry defines hemangioblast commitment. Isobaric-tag for relative and absolute quantification (iTRAQ(TM)) and phosphopeptide enrichment coupled to liquid chromatography separation and mass spectrometry allow the study of phosphorylation changes occurring at different stages of ES cell development using Bry and Flk1 expression respectively. We identified and relatively quantified 37 phosphoentities which are modulated during mesoderm-induced ES cells differentiation, comparing epiblast-like, early mesoderm and hemangioblast-enriched cells. Among the proteins differentially phosphorylated toward mesoderm differentiation were: the epigenetic regulator Dnmt3b, the protein kinase GSK3b, the chromatin remodeling factor Smarcc1, the transcription factor Utf1; as well as protein specifically related to stem cell differentiation, as Eomes, Hmga2, Ints1 and Rif1. As most key factors regulating early hematopoietic development have also been implicated in various types of leukemia, understanding the post-translational modifications driving their regulation during normal development could result in a better comprehension of their roles during abnormal hematopoiesis in leukemia.

Temporal lobe proteins implicated in synaptic failure exhibit differential expression and deamidation in vascular dementia

Progressive synaptic failure precedes the loss of neurons and decline in cognitive function in neurodegenerative disorders, but the specific proteins and posttranslational modifications that promote synaptic failure in vascular dementia (VaD) remain largely unknown. We therefore used an isobaric tag for relative and absolute proteomic quantitation (iTRAQ) to profile the synapse-associated proteome of post-mortem human cortex from vascular dementia patients and age-matched controls. Brain tissue from VaD patients exhibited significant down-regulation of critical synaptic proteins including clathrin (0.29; p < 1.0⋅10(-3)) and GDI1 (0.51; p = 3.0⋅10(-3)), whereas SNAP25 (1.6; p = 5.5⋅10(-3)), bassoon (1.4; p = 1.3⋅10(-3)), excitatory amino acid transporter 2 (2.6; p = 9.2⋅10(-3)) and Ca(2+)/calmodulin dependent kinase II (1.6; p = 3.0⋅10(-2)) were substantially up-regulated. Our analyses further revealed divergent patterns of protein modification in the dementia patient samples, including a specific deamidation of synapsin1 predicted to compromise protein structure. Our results reveal potential molecular targets for intervention in synaptic failure and prevention of cognitive decline in VaD.

The secretome of the working human skeletal muscle--a promising opportunity to combat the metabolic disaster?

Recent years have provided clear evidence for the skeletal muscle as an endocrine organ. Muscle contraction during physical activity has emerged as an important activator of the release of the proteins and peptides called "myokines." Diverse proteomic profiling approaches were applied to rodent and human skeletal muscle cells to characterize the complete secretome, to study the regulation of the secretome during cell differentiation or the release of myokines upon contractile activity of myotubes. Several of the exercise-regulated factors have the potency to mediate an interorgan crosstalk. The paracrine function of the secreted peptides and proteins to regulate muscle regeneration, tissue remodeling, and trainability can have direct effects on whole-body glucose disposal and oxygen consumption. The overall composition and dynamic of the myokinome are still incompletely characterized. Recent advantages in metabolomics and lipidomics will add metabolites and lipids with autocrine, paracrine, or endocrine function to the contraction-induced secretome of the skeletal muscle. The identification of these metabolites will lead to a more comprehensive view described by a new myo(metabo)kinome consisting of peptides, proteins, and metabolites.

General statistical framework for quantitative proteomics by stable isotope labeling

The combination of stable isotope labeling (SIL) with mass spectrometry (MS) allows comparison of the abundance of thousands of proteins in complex mixtures. However, interpretation of the large data sets generated by these techniques remains a challenge because appropriate statistical standards are lacking. Here, we present a generally applicable model that accurately explains the behavior of data obtained using current SIL approaches, including (18)O, iTRAQ, and SILAC labeling, and different MS instruments. The model decomposes the total technical variance into the spectral, peptide, and protein variance components, and its general validity was demonstrated by confronting 48 experimental distributions against 18 different null hypotheses. In addition to its general applicability, the performance of the algorithm was at least similar than that of other existing methods. The model also provides a general framework to integrate quantitative and error information fully, allowing a comparative analysis of the results obtained from different SIL experiments. The model was applied to the global analysis of protein alterations induced by low H₂O₂ concentrations in yeast, demonstrating the increased statistical power that may be achieved by rigorous data integration. Our results highlight the importance of establishing an adequate and validated statistical framework for the analysis of high-throughput data.

Proteomic approaches in biomarker discovery: new perspectives in cancer diagnostics

Despite remarkable progress in proteomic methods, including improved detection limits and sensitivity, these methods have not yet been established in routine clinical practice. The main limitations, which prevent their integration into clinics, are high cost of equipment, the need for highly trained personnel, and last, but not least, the establishment of reliable and accurate protein biomarkers or panels of protein biomarkers for detection of neoplasms. Furthermore, the complexity and heterogeneity of most solid tumours present obstacles in the discovery of specific protein signatures, which could be used for early detection of cancers, for prediction of disease outcome, and for determining the response to specific therapies. However, cancer proteome, as the end-point of pathological processes that underlie cancer development and progression, could represent an important source for the discovery of new biomarkers and molecular targets for tailored therapies.

Delineating the effect of host environmental signals on a fully virulent strain of Bacillus anthracis using an integrated transcriptomics and proteomics approach

Pathogenic bacteria sense the host environment and regulate expression of virulence-related genes. Environmental signals like temperature, bicarbonate/CO2 and glucose induce toxin production in Bacillus anthracis, but the mechanisms by which these signals contribute to virulence and overall physiological adaptation remains elusive. An integrated, systems level investigation using transcriptomics and iTRAQ-based proteomics was done to assess the effect of temperature, bicarbonate/CO2 and glucose on B. anthracis. Significant changes observed in amino acid, carbohydrate, energy and nucleotide metabolism indicates events of metabolic readjustments by environmental factors. Directed induction of genes involved in polyamine biosynthesis and iron metabolism revealed the redirection of cellular metabolite pool towards iron uptake. Protein levels of glycolytic enzymes, ptsH and Ldh along with transcripts involved in immune evasion (mprF, bNOS, Phospholipases and asnA), cell surface remodeling (rfbABCD, antABCD, and cls) and utilization of lactate (lutABC) and inositol showed constant repression under environmental perturbations. Discrepancies observed in mRNA/protein level of genes involved in glycolysis, protein synthesis, stress response and nucleotide metabolism hinted at the existence of additional regulatory layers and illustrated the utility of an integrated approach. The above findings might assist in the identification of novel adaptive strategies of B. anthracis during host associated survival and pathogenesis.

BIOLOGICAL SIGNIFICANCE

In this study, the changes observed at both transcript and protein level were quantified and integrated to understand the effect of host environmental factors (host temperature, bicarbonate and glucose) in shaping the physiology and adaptive strategies of a fully virulent strain of B. anthracis for efficient survival and virulence in its host. Perturbations affecting toxin production were found to concordantly affect vital metabolic pathways and several known as well as novel virulence factors. These changes act as a valuable asset for generating testable hypotheses that can be further verified by detailed molecular and mutant studies to identify novel adaptive strategies of B. anthracis during infection. Adaptation of an integrated transcriptomics and proteomics approach also led to the identification of discrepancies between mRNA/protein levels among genes across major functional categories. Few of these discrepancies have been previously reported in literature for model organisms. However their existence in B. anthracis and that too as a result of growth perturbations have not been reported till date. These findings demonstrate a substantial role of regulatory processes post mRNA synthesis via post transcriptional, translational or protein degradation mechanisms. This article is part of a Special Issue entitled: Proteomics of non-model organisms.

Comparison of protein expression ratios observed by sixplex and duplex TMT labeling method

Stable isotope labeling via isobaric derivatization of peptides is a universally applicable approach that enables concurrent identification and quantification of proteins in different samples using tandem mass spectrometry. In this study, we evaluated the performance of amine-reactive isobaric tandem mass tag (TMT), available as duplex and sixplex sets, with regard to their ability to elucidate protein expression changes. Using rat brain tissue from two different developmental time points, postnatal day 1 (p1) and 45 (p45), as a model system, we compared the protein expression ratios (p45/p1) observed using duplex TMT tags in triplicate measurements versus sixplex tag in a single LC-MS/MS analysis. A correlation of 0.79 in relative protein abundance was observed in the proteins quantified by these two sets of reagents. However, more proteins passed the criteria for significant fold change (-1.0 ≤ log(2) ratio (p45/p1) ≥ +1.0 and p < 0.05) in the sixplex analysis. Nevertheless, in both methods most proteins showing significant fold change were identified by multiple spectra, increasing their quantification precision. Additionally, the fold change in p45 rats against p1, observed in TMT experiments, was corroborated by a metabolic labeling strategy where relative quantification of differentially expressed proteins was obtained using (15)N-labeled p45 rats as an internal standard.

CD34⁺/CD38⁻ acute myelogenous leukemia cells aberrantly express CD82 which regulates adhesion and survival of leukemia stem cells

To identify molecular targets in leukemia stem cells (LSCs), this study compared the protein expression profile of freshly isolated CD34(+) /CD38(-) cells with that of CD34(+) /CD38(+) counterparts from individuals with acute myelogenous leukemia (n = 2, AML) using isobaric tags for relative and absolute quantitation (iTRAQ). A total of 98 proteins were overexpressed, while six proteins were underexpressed in CD34(+) /CD38(-) AML cells compared with their CD34(+) /CD38(+) counterparts. Proteins overexpressed in CD34(+) /CD38(-) AML cells included a number of proteins involved in DNA repair, cell cycle arrest, gland differentiation, antiapoptosis, adhesion, and drug resistance. Aberrant expression of CD82, a family of adhesion molecules, in CD34(+) /CD38(-) AML cells was noted in additional clinical samples (n = 12) by flow cytometry. Importantly, down-regulation of CD82 in CD34(+) /CD38(-) AML cells by a short hairpin RNA (shRNA) inhibited adhesion to fibronectin via up-regulation of matrix metalloproteinases 9 (MMP9) and colony forming ability of these cells as assessed by transwell assay, real-time RT-PCR, and colony forming assay, respectively. Moreover, we found that down-regulation of CD82 in CD34(+) /CD38(-) AML cells by an shRNA significantly impaired engraftment of these cells in severely immunocompromised mice. Taken together, aberrant expression of CD82 might play a role in adhesion of LSCs to bone marrow microenvironment and survival of LSCs. CD82 could be an attractive molecular target to eradicate LSCs.

Quantitative proteomic (iTRAQ) analysis of 1st trimester maternal plasma samples in pregnancies at risk for preeclampsia

A current major obstacle is that no reliable screening markers exist to detect pregnancies at risk for preeclampsia. Quantitative proteomic analysis employing isobaric labelling (iTRAQ) has been suggested to be suitable for the detection of potential plasma biomarkers, a feature we recently verified in analysis of pregnancies with Down syndrome foetuses. We have now examined whether this approach could yield biomarkers to screen pregnancies at risk for preeclampsia. In our study, we used maternal plasma samples obtained at 12 weeks of gestation, six from women who subsequently developed preeclampsia and six with uncomplicated deliveries. In our analysis, we observed elevations in 10 proteins out of 64 proteins in the preeclampsia study group when compared to the healthy control group. These proteins included clusterin, fibrinogen, fibronectin, and angiotensinogen, increased levels of which are known to be associated with preeclampsia. An elevation in the immune-modulatory molecule, galectin 3 binding protein, was also noted. Our pilot study, therefore, indicates that quantitative proteomic iTRAQ analysis could be a useful tool for the detection of new preeclampsia screening markers.

Identification of a panel of novel serum osteoarthritis biomarkers

Osteoarthritis (OA) is the most common rheumatic pathology. Because currently available diagnostic methods are limited and lack sensitivity, the identification of new specific biological markers for OA has become a focus. The purpose of this study was to identify novel protein biomarkers for moderate and severe OA in serum. Sera were obtained from 50 moderate OA patients, 50 severe OA patients, and 50 nonsymptomatic controls. Serum protein levels were analyzed using isobaric tags for relative and absolute quantitation (iTRAQ) and matrix-assisted laser desorption/ionization (MALDI)-TOF/TOF mass spectrometry. We identified 349 different proteins in the sera, 262 of which could be quantified by calculation of their iTRAQ ratios. Three sets of proteins were significantly (p < 0.05) changed in OA samples compared to controls. Of these, 6 were modulated only in moderate OA, 13 only in severe OA and 7 in both degrees. Although some of these proteins, such as cartilage oligomeric matrix protein, have a previously reported putative biomarker value for OA, most are novel biomarker candidates for the disease. These include some complement components, lipoproteins, von Willebrand factor, tetranectin, and lumican. The specificity and selectivity of these candidates need to be validated before new molecular diagnostic or prognostic tests for OA can be developed.

Quantitative proteomic analysis of the heat stress response in Clostridium difficile strain 630

Clostridium difficile is a serious nosocomial pathogen whose prevalence worldwide is increasing. Postgenomic technologies can now be deployed to develop understanding of the evolution and diversity of this important human pathogen, yet little is known about the adaptive ability of C. difficile. We used iTRAQ labeling and 2D-LC-MS/MS driven proteomics to investigate the response of C. difficile 630 to a mild, but clinically relevant, heat stress. A statistically validated list of 447 proteins to which functional roles were assigned was generated, allowing reconstruction of central metabolic pathways including glycolysis, γ-aminobutyrate metabolism, and peptidoglycan biosynthesis. Some 49 proteins were significantly modulated under heat stress: classical heat shock proteins including GroEL, GroES, DnaK, Clp proteases, and HtpG were up-regulated in addition to several stress inducible rubrerythrins and proteins associated with protein modification, such as prolyl isomerases and proline racemase. The flagellar filament protein, FliC, was down-regulated, possibly as an energy conservation measure, as was the SecA1 preprotein translocase. The up-regulation of hydrogenases and various oxidoreductases suggests that electron flux across these pools of enzymes changes under heat stress. This work represents the first comparative proteomic analysis of the heat stress response in C. difficile strain 630, complementing the existing proteomics data sets and the single microarray comparative analysis of stress response. Thus we have a benchmark proteome for this pathogen, leading to a deeper understanding of its physiology and metabolism informed by the unique functional and adaptive processes used during a temperature upshift mimicking host pyrexia.

Blue native/SDS-PAGE combined with iTRAQ analysis reveals advanced glycation end-product-induced changes of synaptosome proteins in C57 BL/6 mice

Evidence shows that administration of high-level D-galactose induces the production of advanced glycation end-products (AGEs) that have been implicated in the development of diabetic complications such as neuropathy. The deterioration of learning and memory during neuropathy might be associated with the altered expression of proteins in synapse. To evaluate AGE-induced protein network alterations in synapse, blue native/SDS-PAGE and iTRAQ proteomic methods were used to screen for differentially expressed synaptic proteins of cerebral cortex in D-galactose-induced C57 BL/6 mice. In total, the expression level of 84 proteins is changed during AGE accumulation. The significantly differentially expressed proteins mainly participate in neurotransmission, energy metabolism and signal transduction pathway, suggesting that energy metabolism is damaged and neurotransmission is attenuated in synapse. The results of in vivo activities of malondialdehyde and superoxide dismutase suggested that AGE accumulation in the brain leads to the generation of reactive oxygen species. Therefore, elucidating the differentially expressed proteins underlying the AGE accumulation will open a new window to the mechanism of learning and memory impairments in neuropathy.

Exoproteome of Staphylococcus aureus reveals putative determinants of nasal carriage

Due to the increasing prevalence of nosocomial and community-acquired antibiotic resistant Staphylococcus aureus (SA), understanding the determinants of SA nasal carriage has become a major imperative. Previous research has revealed many host and bacterial factors that contribute to SA nasal carriage. To assess bacterial factors that facilitate nasal carriage, we compared the exoproteome of a nasal carrier strain of SA to a genetically similar noncarrier strain. Additionally, the carrier strain biofilm exoproteome was also compared against its planktonic counterpart. Using high throughput proteomics, it was observed that the carrier strain of SA secretes a greater number of proteins that may promote successful colonization of the human nose, including cell attachment and immunoevasive proteins, than the noncarrier strain. Similarly, SA carrier strain biofilm exoproteome contains a greater number of immunoevasive proteins than its planktonic counterpart. Analysis of the most abundant immunoevasive proteins revealed that Staphylococcal protein A was present at significantly higher levels in carrier than in noncarrier strains of SA, suggesting an association with nasal carriage. While further analyses of specific differences between carrier and noncarrier strains of SA are required, many of the differentially expressed proteins identified can be considered to be putative determinants of nasal carriage.

The evolving field of imaging mass spectrometry and its impact on future biological research

Within the past decade, imaging mass spectrometry (IMS) has been increasingly recognized as an indispensable technique for studying biological systems. Its rapid evolution has resulted in an impressive array of instrument variations and sample applications, yet the tools and data are largely confined to specialists. It is therefore important that at this junction the IMS community begin to establish IMS as a permanent fixture in life science research thereby making the technology and/or the data approachable by non-mass spectrometrists, leading to further integration into biological and clinical research. In this perspective article, we provide insight into the evolution and current state of IMS and propose some of the directions that IMS could develop in order to stay on course to become one of the most promising new tools in life science research.

Differential Hox expression in murine embryonic stem cell models of normal and malignant hematopoiesis

The Hox family are master transcriptional regulators of developmental processes, including hematopoiesis. The Hox regulators, caudal homeobox factors (Cdx1-4), and Meis1, along with several individual Hox proteins, are implicated in stem cell expansion during embryonic development, with gene dosage playing a significant role in the overall function of the integrated Hox network. To investigate the role of this network in normal and aberrant, early hematopoiesis, we employed an in vitro embryonic stem cell differentiation system, which recapitulates mouse developmental hematopoiesis. Expression profiles of Hox, Pbx1, and Meis1 genes were quantified at distinct stages during the hematopoietic differentiation process and compared with the effects of expressing the leukemic oncogene Tel/PDGFRβ. During normal differentiation the Hoxa cluster, Pbx1 and Meis1 predominated, with a marked reduction in the majority of Hox genes (27/39) and Meis1 occurring during hematopoietic commitment. Only the posterior Hoxa cluster genes (a9, a10, a11, and a13) maintained or increased expression at the hematopoietic colony stage. Cdx4, Meis1, and a subset of Hox genes, including a7 and a9, were differentially expressed after short-term oncogenic (Tel/PDGFRβ) induction. Whereas Hoxa4-10, b1, b2, b4, and b9 were upregulated during oncogenic driven myelomonocytic differentiation. Heterodimers between Hoxa7/Hoxa9, Meis1, and Pbx have previously been implicated in regulating target genes involved in hematopoietic stem cell (HSC) expansion and leukemic progression. These results provide direct evidence that transcriptional flux through the Hox network occurs at very early stages during hematopoietic differentiation and validates embryonic stem cell models for gaining insights into the genetic regulation of normal and malignant hematopoiesis.

Proteomic analysis reveals a novel mechanism induced by the leukemic oncogene Tel/PDGFRβ in stem cells: activation of the interferon response pathways

Objective proteomic analysis offers opportunities for hypothesis generation on molecular events associated with pathogenesis in stem cells. Relative quantification mass spectrometry was employed to identify pathways affected by Tel/PDGFRβ, an oncogene associated with myeloproliferative neoplasia (MPN). Its effects on over 1800 proteins were quantified with high confidence. Of those up-regulated by Tel/PDGFRβ several were involved in the interferon gamma (IFNγ) response. To validate these observations we employed embryonic and myeloid stem cells models which revealed Tel/PDGFRβ-induced STAT1 up-regulation and activation was responsible for modulating the interferon response. A STAT1 target highly up-regulated was ICSBP, a transcriptional regulator of myeloid and eosinophilic differentiation. ICSBP interacts with CBP/p300 and Ets transcription factors, to promote transcription of additional genes, including the Egr family, key regulators of myelopoiesis. These interferon responses were recapitulated using IFNγ stimulation of stem cells. Thus Tel/PDGFRβ induces aberrant IFN signaling and downstream targets, which may ultimately impact the hematopoietic transcriptional factor network to bias myelomonocytic differentiation in this MPN.

Addressing accuracy and precision issues in iTRAQ quantitation

iTRAQ (isobaric tags for relative or absolute quantitation) is a mass spectrometry technology that allows quantitative comparison of protein abundance by measuring peak intensities of reporter ions released from iTRAQ-tagged peptides by fragmentation during MS/MS. However, current data analysis techniques for iTRAQ struggle to report reliable relative protein abundance estimates and suffer with problems of precision and accuracy. The precision of the data is affected by variance heterogeneity: low signal data have higher relative variability; however, low abundance peptides dominate data sets. Accuracy is compromised as ratios are compressed toward 1, leading to underestimation of the ratio. This study investigated both issues and proposed a methodology that combines the peptide measurements to give a robust protein estimate even when the data for the protein are sparse or at low intensity. Our data indicated that ratio compression arises from contamination during precursor ion selection, which occurs at a consistent proportion within an experiment and thus results in a linear relationship between expected and observed ratios. We proposed that a correction factor can be calculated from spiked proteins at known ratios. Then we demonstrated that variance heterogeneity is present in iTRAQ data sets irrespective of the analytical packages, LC-MS/MS instrumentation, and iTRAQ labeling kit (4-plex or 8-plex) used. We proposed using an additive-multiplicative error model for peak intensities in MS/MS quantitation and demonstrated that a variance-stabilizing normalization is able to address the error structure and stabilize the variance across the entire intensity range. The resulting uniform variance structure simplifies the downstream analysis. Heterogeneity of variance consistent with an additive-multiplicative model has been reported in other MS-based quantitation including fields outside of proteomics; consequently the variance-stabilizing normalization methodology has the potential to increase the capabilities of MS in quantitation across diverse areas of biology and chemistry.

A dynamic wavelet-based algorithm for pre-processing tandem mass spectrometry data

MOTIVATION

Mass spectrometry (MS)-based proteomics is one of the most commonly used research techniques for identifying and characterizing proteins in biological and medical research. The identification of a protein is the critical first step in elucidating its biological function. Successful protein identification depends on various interrelated factors, including effective analysis of MS data generated in a proteomic experiment. This analysis comprises several stages, often combined in a pipeline or workflow. The first component of the analysis is known as spectra pre-processing. In this component, the raw data generated by the mass spectrometer is processed to eliminate noise and identify the mass-to-charge ratio (m/z) and intensity for the peaks in the spectrum corresponding to the presence of certain peptides or peptide fragments. Since all downstream analyses depend on the pre-processed data, effective pre-processing is critical to protein identification and characterization. There is a critical need for more robust pre-processing algorithms that perform well on tandem mass spectra under a variety of different conditions and can be easily integrated into sophisticated data analysis pipelines for practical wet-lab applications.

RESULT

We have developed a new pre-processing algorithm. Based on wavelet theory, our method uses a dynamic peak model to identify peaks. It is designed to be easily integrated into a complete proteomic analysis workflow. We compared the method with other available algorithms using a reference library of raw MS and tandem MS spectra with known protein composition information. Our pre-processing algorithm results in the identification of significantly more peptides and proteins in the downstream analysis for a given false discovery rate.

AVAILABILITY

Software available at: http://www.maths.usyd.edu.au/u/penghao/index.html.

In vivo assessment and potential diagnosis of xenobiotics that perturb the thyroid pathway: Proteomic analysis of Xenopus laevis brain tissue following exposure to model T4 inhibitors

As part of a multi-endpoint systems approach to develop comprehensive methods for assessing endocrine stressors in vertebrates, differential protein profiling was used to investigate expression patterns in the brain of the amphibian model (Xenopus laevis) following in vivo exposure to a suite of T4 synthesis inhibitors. We specifically address the application of Two Dimensional Polyacrylamide Gel Electrophoresis (2D PAGE), Isobaric Tags for Relative and Absolute Quantitation (iTRAQ) and LC-MS/MS to assess changes in relative protein expression levels. 2D PAGE and iTRAQ proved to be effective complementary techniques for distinguishing protein changes in the developing amphibian brain in response to T4 synthesis inhibition. This information served to evaluate the use of distinctive protein profiles as a potential mechanism to screen chemicals for endocrine activity in anurans. Regulatory pathways associated with proteins expressed as a result of chemical effect are reported. To our knowledge, this is also the first account of the anuran larvae brain proteome characterization using proteomic technologies. Correlation of protein changes to other cellular and organism-level responses will aid in the development of a more rapid and cost-effective, non-mammalian screening assay for thyroid axis-disrupting chemicals.

An integrated mass-spectrometry pipeline identifies novel protein coding-regions in the human genome

Background

Most protein mass spectrometry (MS) experiments rely on searches against a database of known or predicted proteins, limiting their ability as a gene discovery tool.

Results

Using a search against an in silico translation of the entire human genome, combined with a series of annotation filters, we identified 346 putative novel peptides [False Discovery Rate (FDR)<5%] in a MS dataset derived from two human breast epithelial cell lines. A subset of these were then successfully validated by a different MS technique. Two of these correspond to novel isoforms of Heterogeneous Ribonuclear Proteins, while the rest correspond to novel loci.

Conclusions

MS technology can be used for ab initio gene discovery in human data, which, since it is based on different underlying assumptions, identifies protein-coding genes not found by other techniques. As MS technology continues to evolve, such approaches will become increasingly powerful.

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.

Mass spectrometry-based proteomics and its potential use in haematological research

In the last decade proteomics has made great progress reaching throughput and comprehensiveness comparable to genomics technologies. Mass spectrometry plays a key role in proteomics and has become an indispensable method for molecular and cellular biology because many cellular changes in response to internal or external stimuli can only be detected at the proteome level. Furthermore, different from genomics which depends on the availability of DNA or RNA, proteomics is not restricted to cellular samples, but also allows the analysis of biological fluids like serum, plasma or urine. This article provides an overview of the recent developments in proteomics techniques useful for haematological research.