Associations of an HDL apolipoproteomic index with cardiometabolic risk factors before and after exercise training in the HERITAGE Family Study.

BACKGROUND AND AIMS: Previous studies have derived and validated an HDL apolipoproteomic score (pCAD) that predicts coronary artery disease (CAD) risk. However, the associations between pCAD and markers of cardiometabolic health in healthy adults are not known, nor are the effects of regular exercise on pCAD. METHODS: A total of 641 physically inactive adults free of cardiovascular disease from the HERITAGE Family Study completed 20 weeks of exercise training. The pCAD index (range 0-100) was calculated using measurements of apolipoproteins A-I, C-I, C-II, C-III, and C-IV from ApoA-I-tagged serum (higher index = higher CAD risk). The associations between pCAD index and cardiometabolic traits at baseline and their training responses were assessed with Spearman correlation and general linear models. A Bonferroni correction of p < 8.9 × 10-04 was used to determine statistical significance. RESULTS: The mean ± SD baseline pCAD index was 29 ± 32, with 106 (16.5 %) participants classified as high CAD risk. At baseline, pCAD index was positively associated with blood pressure, systemic inflammation, and body composition. HDL size, VO2max, and HDL-C were negatively associated with pCAD index at baseline. Of those classified as high CAD risk at baseline, 52 (49 %) were reclassified as normal risk after training. Following training, pCAD index changes were inversely correlated (p < 1.4 × 10-04) with changes in HDL-C, HDL size, and LDL size. CONCLUSIONS: A higher pCAD index was associated with a worse cardiometabolic profile at baseline but improved with regular exercise. The results from this study highlight the potential role of HDL apolipoproteins as therapeutic targets for lifestyle interventions, particularly in high-risk individuals.

Proteomic Determinants of Variation in Cholesterol Efflux: Observations from the Dallas Heart Study.

High-density lipoproteins (HDLs) are promising targets for predicting and treating atherosclerotic cardiovascular disease (ASCVD), as they mediate removal of excess cholesterol from lipid-laden macrophages that accumulate in the vasculature. This functional property of HDLs, termed cholesterol efflux capacity (CEC), is inversely associated with ASCVD. HDLs are compositionally diverse, associating with >250 different proteins, but their relative contribution to CEC remains poorly understood. Our goal was to identify and define key HDL-associated proteins that modulate CEC in humans. The proteomic signature of plasma HDL was quantified in 36 individuals in the multi-ethnic population-based Dallas Heart Study (DHS) cohort that exhibited persistent extremely high (>=90th%) or extremely low CEC (<=10th%) over 15 years. Levels of apolipoprotein (Apo)A-I associated ApoC-II, ApoC-III, and ApoA-IV were differentially correlated with CEC in high (r = 0.49, 0.41, and -0.21 respectively) and low (r = -0.46, -0.41, and 0.66 respectively) CEC groups (p for heterogeneity (pHet) = 0.03, 0.04, and 0.003 respectively). Further, we observed that levels of ApoA-I with ApoC-III, complement C3 (CO3), ApoE, and plasminogen (PLMG) were inversely associated with CEC in individuals within the low CEC group (r = -0.11 to -0.25 for subspecies with these proteins vs. r = 0.58 to 0.65 for subspecies lacking these proteins; p < 0.05 for heterogeneity). These findings suggest that enrichment of specific proteins on HDLs and, thus, different subspecies of HDLs, differentially modulate the removal of cholesterol from the vasculature.

The small HDL particle hypothesis of Alzheimer's disease.

We propose the hypothesis that small high-density lipoprotein (HDL) particles reduce the risk of Alzheimer's disease (AD) by virtue of their capacity to exchange lipids, affecting neuronal membrane composition and vascular and synaptic functions. Concentrations of small HDLs in cerebrospinal fluid (CSF) and plasma were measured in 180 individuals ≥60 years of age using ion mobility methodology. Small HDL concentrations in CSF were positively associated with performance in three domains of cognitive function independent of apolipoprotein E (APOE) ε4 status, age, sex, and years of education. Moreover, there was a significant correlation between levels of small HDLs in CSF and plasma. Further studies will be aimed at determining whether specific components of small HDL exchange across the blood, brain, and CSF barriers, and developing approaches to exploit small HDLs for therapeutic purposes.

Differences in HDL-Bound Apolipoproteins in Patients With Advanced Liver Fibrosis Due to Nonalcoholic Fatty Liver Disease.

CONTEXT: The mechanisms leading to increased cardiovascular disease in patients with nonalcoholic fatty liver disease (NAFLD) and advanced liver fibrosis remain incompletely understood. OBJECTIVE: This study assessed HDL-bound proteins in patients with NAFLD with or without advanced fibrosis. METHODS: This cross-sectional study at a university hospital included 185 patients with or without type 2 diabetes (T2D). Patients underwent liver proton magnetic resonance spectroscopy to measure intrahepatic triglyceride accumulation and those with NAFLD underwent a percutaneous liver biopsy. Advanced lipid testing with lipoprotein subfraction measurements and targeted proteomics of HDL-bound proteins was performed. RESULTS: Patients with and without advanced fibrosis had similar clinical characteristics, except for lower HDL-C (34 ± 8 vs 38 ± 9 mg/dL, P = 0.024) and higher prevalence of T2D in advanced fibrosis. Patients with advanced fibrosis had lower HDL particle number. A panel of 28 HDL-bound proteins were targeted and quantified by multiple reaction monitoring liquid chromatography-tandem mass spectrometry. Five proteins were found to be decreased in patients with advanced fibrosis (ApoC-I [P < 0.001], ApoC-IV [P = 0.012], ApoM [P = 0.008], LCAT [P = 0.014], and SAA4 [P = 0.016]). No differences were observed in these proteins in patients with vs without NAFLD or steatohepatitis. The pCAD index, associated with coronary artery disease and cardiovascular mortality, was significantly higher in patients with advanced fibrosis (97 ± 5 vs 86 ± 25, P = 0.04). CONCLUSION: Patients with NAFLD with advanced fibrosis showed significant differences in HDL-bound protein levels; this translated into increased cardiovascular risk based on pCAD index. Different lipoprotein composition and function may explain the link between liver disease and increased cardiovascular mortality in these patients.

Development and Validation of Apolipoprotein AI-Associated Lipoprotein Proteome Panel for the Prediction of Cholesterol Efflux Capacity and Coronary Artery Disease.

BACKGROUND: Cholesterol efflux capacity (CEC) is a measure of HDL function that, in cell-based studies, has demonstrated an inverse association with cardiovascular disease. The cell-based measure of CEC is complex and low-throughput. We hypothesized that assessment of the lipoprotein proteome would allow for precise, high-throughput CEC prediction. METHODS: After isolating lipoprotein particles from serum, we used LC-MS/MS to quantify 21 lipoprotein-associated proteins. A bioinformatic pipeline was used to identify proteins with univariate correlation to cell-based CEC measurements and generate a multivariate algorithm for CEC prediction (pCE). Using logistic regression, protein coefficients in the pCE model were reweighted to yield a new algorithm predicting coronary artery disease (pCAD). RESULTS: Discovery using targeted LC-MS/MS analysis of 105 training and test samples yielded a pCE model comprising 5 proteins (Spearman r = 0.86). Evaluation of pCE in a case-control study of 231 specimens from healthy individuals and patients with coronary artery disease revealed lower pCE in cases (P = 0.03). Derived within this same study, the pCAD model significantly improved classification (P < 0.0001). Following analytical validation of the multiplexed proteomic method, we conducted a case-control study of myocardial infarction in 137 postmenopausal women that confirmed significant separation of specimen cohorts in both the pCE (P = 0.015) and pCAD (P = 0.001) models. CONCLUSIONS: Development of a proteomic pCE provides a reproducible high-throughput alternative to traditional cell-based CEC assays. The pCAD model improves stratification of case and control cohorts and, with further studies to establish clinical validity, presents a new opportunity for the assessment of cardiovascular health.

Rapid Affinity Enrichment of Human Apolipoprotein A-I Associated Lipoproteins for Proteome Analysis.

Isolation of high density lipoproteins (HDL) for structural and functional studies typically relies on ultracentrifugation techniques, which are time-consuming and difficult to scale. With emerging interest in the clinical relevance of HDL structure and function to cardiovascular disease, a significant gap exists between current and desirable sample preparation throughput. To enable proteomic studies of HDL with large clinical cohorts, we have developed an affinity enrichment approach that relies on the association of histidine-tagged, lipid free ApoA-I with HDL followed by standard metal chelate chromatography. Characterization of the resulting affinity-enriched ApoA-I associated lipoprotein (AALP) pool using biochemical, electrophoretic, and proteomic analysis demonstrates that the isolated material is closely related in structural features, lipid content, protein complement, and relative protein distribution to HDL isolated by ultracentrifugation using sequential density adjustment. The simplicity of the method provides avenues for high-throughput analysis of HDL associated proteins.

Identification of Epigenetic Factor Proteins Expressed in Human Embryonic Stem Cell-Derived Trophoblasts and in Human Placental Trophoblasts.

Human embryonic stem cells (hESCs) have been used to derive trophoblasts through differentiation in vitro. Intriguingly, mouse ESCs are prevented from differentiation to trophoblasts by certain epigenetic factor proteins such as Dnmt1, thus necessitating the study of epigenetic factor proteins during hESC differentiation to trophoblasts. We used stable isotope labeling by amino acids in cell culture and quantitative proteomics to study changes in the nuclear proteome during hESC differentiation to trophoblasts and identified changes in the expression of 30 epigenetic factor proteins. Importantly, the DNA methyltransferases DNMT1, DNMT3A, and DNMT3B were downregulated. Additionally, we hypothesized that nuclear proteomics of hESC-derived trophoblasts may be used for screening epigenetic factor proteins expressed by primary trophoblasts in human placental tissue. Accordingly, we conducted immunohistochemistry analysis of six epigenetic factor proteins identified from hESC-derived trophoblasts-DNMT1, DNMT3B, BAF155, BAF60A, BAF57, and ING5-in 6-9 week human placentas. Indeed, expression of these proteins was largely, though not fully, consistent with that observed in 6-9 week placental trophoblasts. Our results support the use of hESC-derived trophoblasts as a model for placental trophoblasts, which will enable further investigation of epigenetic factors involved in human trophoblast development.

Analysis of the Role of the C-Terminal Tail in the Regulation of the Epidermal Growth Factor Receptor.

The ∼230-residue C-terminal tail of the epidermal growth factor receptor (EGFR) is phosphorylated upon activation. We examined whether this phosphorylation is affected by deletions within the tail and whether the two tails in the asymmetric active EGFR dimer are phosphorylated differently. We monitored autophosphorylation in cells using flow cytometry and found that the first ∼80 residues of the tail are inhibitory, as demonstrated previously. The entire ∼80-residue span is important for autoinhibition and needs to be released from both kinases that form the dimer. These results are interpreted in terms of crystal structures of the inactive kinase domain, including two new ones presented here. Deletions in the remaining portion of the tail do not affect autophosphorylation, except for a six-residue segment spanning Tyr 1086 that is critical for activation loop phosphorylation. Phosphorylation of the two tails in the dimer is asymmetric, with the activator tail being phosphorylated somewhat more strongly. Unexpectedly, we found that reconstitution of the transmembrane and cytoplasmic domains of EGFR in vesicles leads to a peculiar phenomenon in which kinase domains appear to be trapped between stacks of lipid bilayers. This artifactual trapping of kinases between membranes enhances an intrinsic functional asymmetry in the two tails in a dimer.

Activin/nodal signaling switches the terminal fate of human embryonic stem cell-derived trophoblasts.

Human embryonic stem cells (hESCs) have been routinely treated with bone morphogenetic protein and/or inhibitors of activin/nodal signaling to obtain cells that express trophoblast markers. Trophoblasts can terminally differentiate to either extravillous trophoblasts or syncytiotrophoblasts. The signaling pathways that govern the terminal fate of these trophoblasts are not understood. We show that activin/nodal signaling switches the terminal fate of these hESC-derived trophoblasts. Inhibition of activin/nodal signaling leads to formation of extravillous trophoblast, whereas loss of activin/nodal inhibition leads to the formation of syncytiotrophoblasts. Also, the ability of hESCs to form bona fide trophoblasts has been intensely debated. We have examined hESC-derived trophoblasts in the light of stringent criteria that were proposed recently, such as hypomethylation of the ELF5-2b promoter region and down-regulation of HLA class I antigens. We report that trophoblasts that possess these properties can indeed be obtained from hESCs.

Tissue phosphoproteomics with PolyMAC identifies potential therapeutic targets in a transgenic mouse model of HER2 positive breast cancer.

Altered protein phosphorylation is a feature of many human cancers that can be targeted therapeutically. Phosphopeptide enrichment is a critical step for maximizing the depth of phosphoproteome coverage by MS, but remains challenging for tissue specimens because of their high complexity. We describe the first analysis of a tissue phosphoproteome using polymer-based metal ion affinity capture (PolyMAC), a nanopolymer that has excellent yield and specificity for phosphopeptide enrichment, on a transgenic mouse model of HER2-driven breast cancer. By combining phosphotyrosine immunoprecipitation with PolyMAC, 411 unique peptides with 139 phosphotyrosine, 45 phosphoserine, and 29 phosphothreonine sites were identified from five LC-MS/MS runs. Combining reverse phase liquid chromatography fractionation at pH 8.0 with PolyMAC identified 1571 unique peptides with 1279 phosphoserine, 213 phosphothreonine, and 21 phosphotyrosine sites from eight LC-MS/MS runs. Linear motif analysis indicated that many of the phosphosites correspond to well-known phosphorylation motifs. Analysis of the tyrosine phosphoproteome with the Drug Gene Interaction database uncovered a network of potential therapeutic targets centered on Src family kinases with inhibitors that are either FDA-approved or in clinical development. These results demonstrate that PolyMAC is well suited for phosphoproteomic analysis of tissue specimens.

Carboxyl group footprinting mass spectrometry and molecular dynamics identify key interactions in the HER2-HER3 receptor tyrosine kinase interface.

The HER2 receptor tyrosine kinase is a driver oncogene in many human cancers, including breast and gastric cancer. Under physiologic levels of expression, HER2 heterodimerizes with other members of the EGF receptor/HER/ErbB family, and the HER2-HER3 dimer forms one of the most potent oncogenic receptor pairs. Previous structural biology studies have individually crystallized the kinase domains of HER2 and HER3, but the HER2-HER3 kinase domain heterodimer structure has yet to be solved. Using a reconstituted membrane system to form HER2-HER3 kinase domain heterodimers and carboxyl group footprinting mass spectrometry, we observed that HER2 and HER3 kinase domains preferentially form asymmetric heterodimers with HER3 and HER2 monomers occupying the donor and acceptor kinase positions, respectively. Conformational changes in the HER2 activation loop, as measured by changes in carboxyl group labeling, required both dimerization and nucleotide binding but did not require activation loop phosphorylation at Tyr-877. Molecular dynamics simulations on HER2-HER3 kinase dimers identify specific inter- and intramolecular interactions and were in good agreement with MS measurements. Specifically, several intermolecular ionic interactions between HER2 Lys-716-HER3 Glu-909, HER2 Glu-717-HER3 Lys-907, and HER2 Asp-871-HER3 Arg-948 were identified by molecular dynamics. We also evaluated the effect of the cancer-associated mutations HER2 D769H/D769Y, HER3 E909G, and HER3 R948K (also numbered HER3 E928G and R967K) on kinase activity in the context of this new structural model. This study provides valuable insights into the EGF receptor/HER/ErbB kinase structure and interactions, which can guide the design of future therapies.

Quantitative proteomics with siRNA screening identifies novel mechanisms of trastuzumab resistance in HER2 amplified breast cancers.

HER2 is a receptor tyrosine kinase that is overexpressed in 20% to 30% of human breast cancers and which affects patient prognosis and survival. Treatment of HER2-positive breast cancer with the monoclonal antibody trastuzumab (Herceptin) has improved patient survival, but the development of trastuzumab resistance is a major medical problem. Many of the known mechanisms of trastuzumab resistance cause changes in protein phosphorylation patterns, and therefore quantitative proteomics was used to examine phosphotyrosine signaling networks in trastuzumab-resistant cells. The model system used in this study was two pairs of trastuzumab-sensitive and -resistant breast cancer cell lines. Using stable isotope labeling, phosphotyrosine immunoprecipitations, and online TiO(2) chromatography utilizing a dual trap configuration, ~1700 proteins were quantified. Comparing quantified proteins between the two cell line pairs showed only a small number of common protein ratio changes, demonstrating heterogeneity in phosphotyrosine signaling networks across different trastuzumab-resistant cancers. Proteins showing significant increases in resistant versus sensitive cells were subjected to a focused siRNA screen to evaluate their functional relevance to trastuzumab resistance. The screen revealed proteins related to the Src kinase pathway, such as CDCP1/Trask, embryonal Fyn substrate, and Paxillin. We also identify several novel proteins that increased trastuzumab sensitivity in resistant cells when targeted by siRNAs, including FAM83A and MAPK1. These proteins may present targets for the development of clinical diagnostics or therapeutic strategies to guide the treatment of HER2+ breast cancer patients who develop trastuzumab resistance.

Analytical strategies for the global quantification of intact proteins.

The quantification of intact proteins is a relatively recent development in proteomics. In eukaryotic organisms, proteins are present as multiple isoforms as the result of variations in genetic code, alternative splicing, post-translational modification and other processing events. Understanding the identities and biological functions of these isoforms and how their concentrations vary across different states is the central goal of proteomics. To date, the bulk of proteomics research utilizes a "bottom-up" approach, digesting proteins into their more manageable constitutive peptides, but sacrificing information about the specific isoform and combinations of post-translational modifications present on the protein. Very specific strategies for protein quantification such as the enzyme-linked immunosorbent assay and Western blot are commonplace in laboratories and clinics, but impractical for the study of global biological changes. Herein, we describe strategies for the quantification of intact proteins, their distinct advantages, and challenges to their employment. Techniques contained in this review include the more traditional and widely employed methodology of differential gel electrophoresis and more recently developed mass spectrometry-based techniques including metabolic labeling, chemical labeling, and label-free methodologies.

The subcellular proteome of undifferentiated human embryonic stem cells.

We have characterized the subcellular proteome of human embryonic stem cells (hESCs) through MS analysis of the membrane, cytosolic, and nuclear fractions, isolated from the same sample of undifferentiated hESCs. Strikingly, 74% of all proteins identified were detected in a single subcellular fraction; we also carried out immunofluorescence studies to validate the subcellular localization suggested by proteomic analysis, for a subset of proteins. Our approach resulted in deeper proteome coverage - peptides mapping to 893, 2475, and 1185 proteins were identified in the nuclear, cytosolic, and membrane fractions, respectively. Additionally, we used spectral counting to estimate the relative abundance of all cytosolic proteins. A large number of proteins relevant to hESC biology, including growth factor receptors, cell junction proteins, transcription factors, chromatin remodeling proteins, and histone modifying enzymes were identified. Our analysis shows that components of a large number of interacting signaling pathways are expressed in hESCs. Finally, we show that proteomic analysis of the endoplasmic reticulum (ER) and Golgi compartments is a powerful alternative approach to identify secreted proteins since these are synthesized in the ER and transit through the Golgi. Taken together, our results show that systematic subcellular proteomic analysis is a valuable tool for studying hESC biology.

Comparison of stable-isotope labeling with amino acids in cell culture and spectral counting for relative quantification of protein expression.

Protein quantification is one of the principal goals of mass spectrometry (MS)-based proteomics, and many strategies exist to achieve it. Several approaches involve the incorporation of a stable-isotope label using either chemical derivatization, enzymatically catalyzed incorporation of (18)O, or metabolic labeling in a cell or tissue culture. These techniques can be cost or time prohibitive or not amenable to the biological system of interest. Label-free techniques including those utilizing integrated ion abundance and spectral counting offer an alternative to stable-isotope-based methodologies. Herein, we present the comparison of stable-isotope labeling of amino acids in cell culture (SILAC) with spectral counting for the quantification of human embryonic stem cells as they differentiate toward the trophectoderm at three time points. Our spectral counting experimental strategy resulted in the identification of 2641 protein groups across three time points with an average sequence coverage of 30.3%, of which 1837 could be quantified with more than five spectral counts. SILAC quantification was able to identify 1369 protein groups with an average coverage of 24.7%, of which 1027 could be quantified across all time points. Within this context we further explore the capacity of each strategy for proteome coverage, variation in quantification, and the relative sensitivity of each technique to the detection of change in relative protein expression.

Direct comparison of stable isotope labeling by amino acids in cell culture and spectral counting for quantitative proteomics.

Numerous experimental strategies exist for relative protein quantification, one of the primary objectives of mass spectrometry based proteomics analysis. These strategies mostly involve the incorporation of a stable isotope label via either metabolic incorporation in cell or tissue culture (¹5N/¹4N metabolic labeling, stable isotope labeling by amino acids in cell culture (SILAC)), chemical derivatization (ICAT, iTRAQ, TMT), or enzymatically catalyzed incorporation (¹8O labeling). Also, these techniques can be cost or time prohibitive or not amenable to the biological system of interest (i.e., metabolic labeling of clinical samples, most animals, or fungi). This is the case with the quantification of fungal proteomes, which often require auxotroph mutants to fully metabolically label. Alternatively, label-free strategies for protein quantification such as using integrated ion abundance and spectral counting have been demonstrated for quantification affording over 2 orders of magnitude of dynamic range which is comparable to metabolic labeling strategies. Direct comparisons of these quantitative techniques are largely lacking in the literature but are highly warranted in order to evaluate the capabilities, limitations, and analytical variability of available quantitative strategies. Here, we present the direct comparison of SILAC to label-free quantification by spectral counting of an identical set of data from the bottom-up proteomic analysis of human embryonic stem cells, which are readily able to be quantified using both strategies, finding that both strategies result in a similar number of protein identifications. We also discuss necessary constraints for accurate quantification using spectral counting and assess the potential of this label-free strategy as a viable alternative for quantitative proteomics.

Quantitative top-down proteomics of SILAC labeled human embryonic stem cells.

Human embryonic stem cells (hESCs) are self-renewing pluripotent cells with relevance to treatment of numerous medical conditions. However, a global understanding of the role of the hESC proteome in maintaining pluripotency or triggering differentiation is still largely lacking. The emergence of top-down proteomics has facilitated the identification and characterization of intact protein forms that are not readily apparent in bottom-up studies. Combined with metabolic labeling techniques such as stable isotope labeling by amino acids in cell culture (SILAC), quantitative comparison of intact protein expression under differing experimental conditions is possible. Herein, quantitative top-down proteomics of hESCs is demonstrated using the SILAC method and nano-flow reverse phase chromatography directly coupled to a linear-ion-trap Fourier transform ion cyclotron resonance mass spectrometer (nLC-LTQ-FT-ICR-MS). In this study, which to the best of our knowledge represents the first top-down analysis of hESCs, we have confidently identified 11 proteins by accurate intact mass, MS/MS, and amino acid counting facilitated by SILAC labeling. Although quantification is challenging due to the incorporation of multiple labeled amino acids (i.e., lysine and arginine) and arginine to proline conversion, we are able to quantitatively account for these phenomena using a mathematical model.

Proteomics characterization of cell membrane blebs in human retinal pigment epithelium cells.

Age-related macular degeneration (AMD) is the leading cause of legal blindness among the elderly population in the industrialized world, affecting about 14 million people in the United States alone. Smoking is a major environmental risk factor for AMD, and hydroquinone is a major component in cigarette smoke. Hydroquinone induces the formation of cell membrane blebs in human retinal pigment epithelium (RPE). Blebs may accumulate and eventually contribute first to sub-RPE deposits and then drusen formation, which is a prominent histopathologic feature in eyes with AMD. As an attempt to better understand the mechanisms involved in early AMD, we sought to investigate the proteomic profile of RPE blebs. Isolated blebs were subjected to SDS-PAGE fractionation, and in-gel trypsin-digested peptides were analyzed by LC-MS/MS that lead to the identification of a total of 314 proteins. Identified proteins were predominantly involved in oxidative phosphorylation, cell junction, focal adhesion, cytoskeleton regulation, and immunogenic processes. Importantly basigin and matrix metalloproteinase-14, key proteins involved in extracellular matrix remodeling, were identified in RPE blebs and shown to be more prevalent in AMD patients. Altogether our findings suggest, for the first time, the potential involvement of RPE blebs in eye disease and shed light on the implication of cell-derived microvesicles in human pathology.

Top-down identification and quantification of stable isotope labeled proteins from Aspergillus flavus using online nano-flow reversed-phase liquid chromatography coupled to a LTQ-FTICR mass spectrometer.

Online liquid chromatography-mass spectrometric (LC-MS) analysis of intact proteins (i.e., top-down proteomics) is a growing area of research in the mass spectrometry community. A major advantage of top-down MS characterization of proteins is that the information of the intact protein is retained over the vastly more common bottom-up approach that uses protease-generated peptides to search genomic databases for protein identification. Concurrent to the emergence of top-down MS characterization of proteins has been the development and implementation of the stable isotope labeling of amino acids in cell culture (SILAC) method for relative quantification of proteins by LC-MS. Herein we describe the qualitative and quantitative top-down characterization of proteins derived from SILAC-labeled Aspergillus flavus using nanoflow reversed-phase liquid chromatography directly coupled to a linear ion trap Fourier transform ion cyclotron resonance mass spectrometer (nLC-LTQ-FTICR-MS). A. flavus is a toxic filamentous fungus that significantly impacts the agricultural economy and human health. SILAC labeling improved the confidence of protein identification, and we observed 1318 unique protein masses corresponding to 659 SILAC pairs, of which 22 were confidently identified. However, we have observed some limiting issues with regard to protein quantification using top-down MS/MS analyses of SILAC-labeled proteins. The role of SILAC labeling in the presence of competing endogenously produced amino acid residues and its impact on quantification of intact species are discussed in detail.