Characterization of global yeast quantitative proteome data generated from the wild-type and glucose repression saccharomyces cerevisiae strains: the comparison of two quantitative methods

The quantitative proteomic analysis of complex protein mixtures is emerging as a technically challenging but viable systems-level approach for studying cellular function. This study presents a large-scale comparative analysis of protein abundances from yeast protein lysates derived from both wild-type yeast and yeast strains lacking key components of the Snf1 kinase complex. Four different strains were grown under well-controlled chemostat conditions. Multidimensional protein identification technology followed by quantitation using either spectral counting or stable isotope labeling approaches was used to identify relative changes in the protein expression levels between the strains. A total of 2388 proteins were relatively quantified, and more than 350 proteins were found to have significantly different expression levels between the two strains of comparison when using the stable isotope labeling strategy. The stable isotope labeling based quantitative approach was found to be highly reproducible among biological replicates when complex protein mixtures containing small expression changes were analyzed. Where poor correlation between stable isotope labeling and spectral counting was found, the major reason behind the discrepancy was the lack of reproducible sampling for proteins with low spectral counts. The functional categorization of the relative protein expression differences that occur in Snf1-deficient strains uncovers a wide range of biological processes regulated by this important cellular kinase.     

Inverse labeling-mass spectrometry for the rapid identification of differentially expressed protein markers/targets

Comparative proteomic studies can lead to the identification of protein markers for disease diagnostics and protein targets for potential disease interventions. An inverse labeling strategy based on the principle of protein stable isotope labeling and mass spectrometric detection has been successfully applied to three general protein labeling methods. In contrast to the conventional single experiment approach, two labeling experiments are performed in which the initial labeling is reversed in the second experiment. Signals from differentially expressed proteins will distinguish themselves by exhibiting a characteristic pattern of isotope intensity profile reversal that will lead to the rapid identification of these proteins. Application of the inverse labeling method is demonstrated using model systems for protein chemical labeling, protein proteolytic labeling, and protein metabolic labeling. The methodology has clear advantages which are illustrated in the various studies. The inverse labeling strategy permits quick focus on signals from differentially expressed proteins (markers/targets) and eliminates ambiguities caused by the dynamic range of detection. In addition, the inverse labeling approach enables the unambiguous detection of covalent changes of proteins responding to a perturbation.     

同位素标记相对和绝对定量蛋白组技术研究进展

近年来定量蛋白组学技术迅速发展,目前常用的有双向荧光差异凝胶电泳、同位素亲和标记、15N同位素标记、同位素标记相对和绝对定量和细胞培养条件下稳定同位素标记技术等。同位素标记相对和绝对定量技术以其高通量、高灵敏度、高重复性、高动态检测限和能对各种复杂样品进行相对和绝对定量研究等优势而备受研究者青睐,目前已发展到在同一实验中分析8组样品,增加了实验设计的灵活性。我们就同位素标记相对和绝对定量技术在定量蛋白组史中的地位作用、研究策略,以及在病毒致病机制研究和医药临床相关问题中的应用做简要综述。     

A review of quantitative methods for proteomic studies

An overview is provided of six strategies for relative or absolute quantitation of protein abundances that are widely used in proteomic studies. Strengths and limitations are discussed. Four of these involve stable isotope labeling and isotope ratio measurements by mass spectrometry. In another, mass spectra are used to deconvolute overlapping peptide HPLC peaks to provide relative quantitation based on peak areas. The sixth provides relative abundances of proteins based on 2-D gel arrays. It should be noted that these strategies measure peptide and protein abundances, and cannot directly assess changes in regulation or expression.     

定量蛋白质组学中的同位素标记技术

定量蛋白质组学的目的是对复杂的混合体系中所有的蛋白质进行鉴定,并对蛋白质的量及量的变化进行准确的测定,是当前系统生物科学研究的重要内容。近年来,由于质谱技术和生物信息学的进步,定量蛋白质组学在分析蛋白质组或亚蛋白质组方面已取得了令人瞩目的成就,但其最显著的成就应该归功于稳定同位素标记技术的应用。该技术使用针对某一类蛋白具有特异性的化学探针来标记目的蛋白质或肽段,同时化学探针要求含有用以精确定量的稳定同位素信号。在此基础上,实现了对表达的蛋白质差异和翻译后修饰的蛋白质差异进行精确定量分析。综述了在定量蛋白质组学中使用的各种同位素标记技术及其应用。     

Double standards in quantitative proteomics: direct comparative assessment of difference in gel electrophoresis and metabolic stable isotope labeling

Quantitative protein expression profiling is a crucial part of proteomics and requires methods that are able to efficiently provide accurate and reproducible differential expression values for proteins in two or more biological samples. In this report we evaluate in a direct comparative assessment two state-of-the-art quantitative proteomic approaches, namely difference in gel electrophoresis (DiGE) and metabolic stable isotope labeling. Therefore, Saccharomyces cerevisiae was grown under well defined experimental conditions in chemostats under two single nutrient-limited growth conditions using (14)N- or (15)N-labeled ammonium sulfate as the single nitrogen source. Following lysis and protein extraction from the two yeast samples, the proteins were fluorescently labeled using different fluorescent CyDyes. Subsequently, the yeast samples were mixed, and the proteins were separated by two-dimensional gel electrophoresis. Following in-gel digestion, the resulting peptides were analyzed by mass spectrometry using a MALDI-TOF mass spectrometer. Relative ratios in protein expression between these two yeast samples were determined using both DiGE and metabolic stable isotope labeling. Focusing on a small, albeit representative, set of proteins covering the whole gel range, including some protein isoforms and ranging from low to high abundance, we observe that the correlation between these two methods of quantification is good with the differential ratios determined following the equation R(Met.Lab.) = 0.98R(DiGE) with r(2) = 0.89. Although the correlation between DiGE and metabolic stable isotope labeling is exceptionally good, we do observe and discuss (dis)advantages of both methods as well as in relation to other (quantitative) approaches.     

Trypsin is the primary mechanism by which the (18)O isotopic label is lost in quantitative proteomic studies

Labeling with (18)O is currently one of the most commonly used methods for incorporating a stable isotopic label into samples for comparative proteomic studies. In this approach, isotopic labeling involves the enzymatic digestion, typically performed with trypsin, of a protein population in (18)O-water, which incorporates the stable isotope into the C termini of the newly formed peptides. Although trypsin is often used to facilitate isotopic incorporation after digestion, it is typically overlooked that this same mechanism can lead to isotopic loss even under conditions such as low pH where it is assumed that trypsin is inactive. To examine the role that trypsin plays in isotopic loss, several experiments were performed on the rate of delabeling under conditions relevant to multidimensional proteomic experiments. Results from these studies demonstrate that enzyme-facilitated exchange of (18)O in the peptide with (16)O in the aqueous solvent was the major process by which the label is removed from the peptides, even under conditions of low pH and temperature where trypsin is thought to be inactive. This study brings the rapid, tryptic-facilitated exchange to the attention of laboratories using this scheme to prevent inaccuracies in quantitative labeling due to loss of the isotopic label.     

The 15N isotope effect in Escherichia coli: A neutron can make the difference

Several techniques based on stable isotope labeling are used for quantitative MS. These include stable isotope metabolic labeling methods for cells in culture as well as live organisms with the assumption that the stable isotope has no effect on the proteome. Here, we investigate the ¹⁵N isotope effect on Escherichia coli cultures that were grown in either unlabeled (¹⁴N) or ¹⁵N‐labeled media by LC‐ESI‐MS/MS‐based relative protein quantification. Consistent protein expression level differences and altered growth rates were observed between ¹⁴N and ¹⁵N‐labeled cultures. Furthermore, targeted metabolite analyses revealed altered metabolite levels between ¹⁴N and ¹⁵N‐labeled bacteria. Our data demonstrate for the first time that the introduction of the ¹⁵N isotope affects protein and metabolite levels in E. coli and underline the importance of implementing controls for unbiased protein quantification using stable isotope labeling techniques.     

SILAC compatible strain of Pichia pastoris for expression of isotopically labeled protein standards and quantitative proteomics

The methylotrophic yeast Pichia pastoris is a powerful eukaryotic platform for the production of heterologous protein. Recent publication of the P. pastoris genome has facilitated strain development toward biopharmaceutical and environmental science applications and has advanced the organism as a model system for the study of peroxisome biogenesis and methanol metabolism. Here we report the development of a P. pastoris arg-/lys- auxotrophic strain compatible with SILAC (stable isotope labeling by amino acids in cell culture) proteomic studies, which is capable of generating large quantities of isotopically labeled protein for mass spectrometry-based biomarker measurements. We demonstrate the utility of this strain to produce high purity human serum albumin uniformly labeled with isotopically heavy arginine and lysine. In addition, we demonstrate the first quantitative proteomic analysis of methanol metabolism in P. pastoris, reporting new evidence for a malate-aspartate NADH shuttle mechanism in the organism. This strain will be a useful model organism for the study of metabolism and peroxisome generation.     

15N-metabolic labeling for comparative plasma membrane proteomics in Arabidopsis cells

An important goal for proteomic studies is the global comparison of proteomes from different genotypes, tissues, or physiological conditions. This has so far been mostly achieved by densitometric comparison of spot intensities after protein separation by 2-DE. However, the physicochemical properties of membrane proteins preclude the use of 2-DE. Here, we describe the use of in vivo labeling by the stable isotope 15N as an alternative approach for comparative membrane proteomic studies in plant cells. We confirm that 15N-metabolic labeling of proteins is possible and efficient in Arabidopsis suspension cells. Quantification of 14N versus 15N MS signals reflects the relative abundance of 14N and 15N proteins in the sample analyzed. We describe the use of 15N-metabolic labeling to perform a partial comparative analysis of Arabidopsis cells following cadmium exposure. By focusing our attention on plasma membrane proteins, we were able to confidently identify proteins showing up to 5-fold regulation compared to unexposed cells. This study provides a proof of principle that 15N-metabolic labeling is a useful technique for comparative membrane proteome studies.     

Proteomic profiling of metformin effects in 3T3-L1 adipocytes by SILAC-based quantification

Metformin is a common and generally the first medication prescribed for treatment of type 2 diabetes. Its mechanism involves affecting pathways that regulate glucose and lipid metabolism in metabolic cells such as that of muscle and liver cells. In spite of various studies exploring its effects, the proteome changes in adipocytes in response to metformin remains poorly understood. In this study, we performed stable isotope labeling by amino acids in cell culture (SILAC)-based quantitative proteomic profiling to study the effects of metformin specifically on 3T3-L1 adipocytes. We define proteins that exhibited altered levels with metformin treatment, 400 of them showing statistically significant changes in our study. Our results suggest that metformin affects not only the PPAR signaling pathway, as well as glucose and lipid metabolism, but also protein folding, endoplasmic reticulum stress, negative regulation of appetite, and one-carbon folate metabolism in adipocytes. This proteomic investigation provides important insight into effects of metformin in adipocytes.     

UNiquant, a program for quantitative proteomics analysis using stable isotope labeling

Stable isotope labeling (SIL) methods coupled with nanoscale liquid chromatography and high resolution tandem mass spectrometry are increasingly useful for elucidation of the proteome-wide differences between multiple biological samples. Development of more effective programs for the sensitive identification of peptide pairs and accurate measurement of the relative peptide/protein abundance are essential for quantitative proteomic analysis. We developed and evaluated the performance of a new program, termed UNiquant, for analyzing quantitative proteomics data using stable isotope labeling. UNiquant was compared with two other programs, MaxQuant and Mascot Distiller, using SILAC-labeled complex proteome mixtures having either known or unknown heavy/light ratios. For the SILAC-labeled Jeko-1 cell proteome digests with known heavy/light ratios (H/L = 1:1, 1:5, and 1:10), UNiquant quantified a similar number of peptide pairs as MaxQuant for the H/L = 1:1 and 1:5 mixtures. In addition, UNiquant quantified significantly more peptides than MaxQuant and Mascot Distiller in the H/L = 1:10 mixtures. UNiquant accurately measured relative peptide/protein abundance without the need for postmeasurement normalization of peptide ratios, which is required by the other programs.     

Chemical probes and tandem mass spectrometry: a strategy for the quantitative analysis of proteomes and subproteomes

Quantitative proteome profiling using mass spectrometry and stable isotope dilution is being widely applied for the functional analysis of biological systems and for the detection of clinical, diagnostic or prognostic marker proteins. Because of the enormous complexity of proteomes, their comprehensive analysis is unlikely to be routinely achieved in the near future. However, in recent years, significant progress has been achieved focusing quantitative proteomic analyses on specific protein classes or subproteomes that are rich in biologically or clinically important information. Such projects typically combine the use of chemical probes that are specific for a targeted group of proteins and may contain stable isotope signatures for accurate quantification with automated tandem mass spectrometry and bioinformatics tools for data analysis. In this review, we summarize technical and conceptual advances in quantitative subproteome profiling based on tandem mass spectrometry and chemical probes.     

Quantitative phosphoproteomics

Cells are highly responsive to their environment. One of the main strategies used by cells in signal transduction is protein phosphorylation, a reversible modification that regulates numerous biological processes. Misregulation of phosphorylation-mediated processes is often implicated in many human diseases and cancers. A global and quantitative analysis of protein phosphorylation provides a powerful new approach and has the potential to reveal new insights in signaling pathways. Recent technological advances in high resolution mass spectrometers and multidimensional liquid chromatography, combined with the use of stable isotope labeling of proteins, have led to the application of quantitative phosphoproteomics to study in vivo signal transduction events on a proteome-wide scale. Here we review recent advancements in quantitative phosphoproteomic technologies, discuss their potentials, and identify areas for future development. A key objective of proteomic technology is its application to addressing biological questions. We will therefore describe how current quantitative phosphoproteomic technology can be used to study the molecular basis of phosphorylation events in the DNA damage response.     

Downregulated expression of HSP27 in human low-grade glioma tissues discovered by a quantitative proteomic analysis

Background  

Heat shock proteins (HSPs), including mainly HSP110, HSP90, HSP70, HSP60 and small HSP families, are evolutionary conserved proteins involved in various cellular processes. Abnormal expression of HSPs has been detected in several tumor types, which indicates that specific HSPs have different prognostic significance for different tumors. In the current studies, the expression profiling of HSPs in human low-grade glioma tissues (HGTs) were investigated using a sensitive, accurate SILAC (stable isotope labeling with amino acids in cell culture)-based quantitative proteomic strategy.     

Use of stable isotope labeling by amino acids in cell culture as a spike-in standard in quantitative proteomics

Mass spectrometry (MS)-based proteomics is increasingly applied in a quantitative format, often based on labeling of samples with stable isotopes that are introduced chemically or metabolically. In the stable isotope labeling by amino acids in cell culture (SILAC) method, two cell populations are cultured in the presence of heavy or light amino acids (typically lysine and/or arginine), one of them is subjected to a perturbation, and then both are combined and processed together. In this study, we describe a different approach--the use of SILAC as an internal or 'spike-in' standard--wherein SILAC is only used to produce heavy labeled reference proteins or proteomes. These are added to the proteomes under investigation after cell lysis and before protein digestion. The actual experiment is therefore completely decoupled from the labeling procedure. Spike-in SILAC is very economical, robust and in principle applicable to all cell- or tissue-based proteomic analyses. Applications range from absolute quantification of single proteins to the quantification of whole proteomes. Spike-in SILAC is especially advantageous when analyzing the proteomes of whole tissues or organisms. The protocol describes the quantitative analysis of a tissue sample relative to super-SILAC spike-in, a mixture of five SILAC-labeled cell lines that accurately represents the tissue. It includes the selection and preparation of the spike-in SILAC standard, the sample preparation procedure, and analysis and evaluation of the results.     

A MS data search method for improved 15N‐labeled protein identification

Quantitative proteomics using stable isotope labeling strategies combined with MS is an important tool for biomarker discovery. Methods involving stable isotope metabolic labeling result in optimal quantitative accuracy, since they allow the immediate combination of two or more samples. Unfortunately, stable isotope incorporation rates in metabolic labeling experiments using mammalian organisms usually do not reach 100%. As a consequence, protein identifications in ¹⁵N database searches have poor success rates. We report on a strategy that significantly improves the number of ¹⁵N‐labeled protein identifications and results in a more comprehensive and accurate relative peptide quantification workflow.     

Systematic identification of the HSP90 candidate regulated proteome

HSP90 is a central player in the folding and maturation of many proteins. More than two hundred HSP90 clients have been identified by classical biochemical techniques including important signaling proteins with high relevance to human cancer pathways. HSP90 inhibition has thus become an attractive therapeutic concept and multiple molecules are currently in clinical trials. It is therefore of fundamental biological and medical importance to identify, ideally, all HSP90 clients and HSP90 regulated proteins. To this end, we have taken a global and a chemical proteomic approach in geldanamycin treated cancer cell lines using stable isotope labeling with amino acids in cell culture and quantitative mass spectrometry. We identified >6200 proteins in four different human cell lines and ~1600 proteins showed significant regulation upon drug treatment. Gene ontology and pathway/network analysis revealed common and cell-type specific regulatory effects with strong connections to unfolded protein binding and protein kinase activity. Of the 288 identified protein kinases, 98 were geldanamycin treatment including >50 kinases not formerly known to be regulated by HSP90. Protein turn-over measurements using pulsed stable isotope labeling with amino acids in cell culture showed that protein down-regulation by HSP90 inhibition correlates with protein half-life in many cases. Protein kinases show significantly shorter half lives than other proteins highlighting both challenges and opportunities for HSP90 inhibition in cancer therapy. The proteomic responses of the HSP90 drugs geldanamycin and PU-H71 were highly similar suggesting that both drugs work by similar molecular mechanisms. Using HSP90 immunoprecipitation, we validated several kinases (AXL, DDR1, TRIO) and other signaling proteins (BIRC6, ISG15, FLII), as novel clients of HSP90. Taken together, our study broadly defines the cellular proteome response to HSP90 inhibition and provides a rich resource for further investigation relevant for the treatment of cancer.     

Accumulation of “Old Proteins” and the Critical Need for MS‐based Protein Turnover Measurements in Aging and Longevity

Aging and age‐related diseases are accompanied by proteome remodeling and progressive declines in cellular machinery required to maintain protein homeostasis (proteostasis), such as autophagy, ubiquitin‐mediated degradation, and protein synthesis. While many studies have focused on capturing changes in proteostasis, the identification of proteins that evade these cellular processes has recently emerged as an approach to studying the aging proteome. With advances in proteomic technology, it is possible to monitor protein half‐lives and protein turnover at the level of individual proteins in vivo. For large‐scale studies, these technologies typically include the use of stable isotope labeling coupled with MS and comprehensive assessment of protein turnover rates. Protein turnover studies have revealed groups of highly relevant long‐lived proteins (LLPs), such as the nuclear pore complexes, extracellular matrix proteins, and protein aggregates. Here, the role of LLPs during aging and age‐related diseases and the methods used to identify and quantify their changes are reviewed. The methods available to conduct studies of protein turnover, used in combination with traditional proteomic methods, will enable the field to perform studies in a systems biology context, as changes in proteostasis may not be revealed in studies that solely measure differential protein abundances.