Review. Reflections on amyloidosis in Papua New Guinea

The amyloidoses comprise a heterogeneous group of diseases in which 1 out of more than 25 human proteins aggregates into characteristic beta-sheet fibrils with some unique properties. Aggregation is nucleation dependent. Among the known amyloid-forming constituents is the prion protein, well known for its ability to transmit misfolding and disease from one individual to another. There is increasing evidence that other amyloid forms also may be transmissible but only if certain prerequisites are fulfilled. One of these forms is systemic AA-amyloidosis in which an acute-phase reactant, serum AA, is over-expressed and, possibly after cleavage, aggregates into amyloid fibrils, causing disease. In a mouse model, this disorder can easily be transmitted from one animal to another both by intravenous and oral routes. Also, synthetic amyloid-like fibrils made from defined small peptides have this property, indicating a prion-like transmission mechanism. Even some fibrils occurring in the environment can transmit AA-amyloidosis in the murine model. AA-amyloidosis is particularly common in certain areas of Papua New Guinea, probably due to the endemicity of malaria and perhaps genetic predisposition. Now, when kuru is disappearing, more interest should be focused on the potentially lethal systemic AA-amyloidosis.     

Mass spectrometric identification of human prostate cancer-derived proteins in serum of xenograft-bearing mice

Lack of sensitivity and specificity of current tumor markers has intensified research efforts to find new biomarkers. The identification of potential tumor markers in human body fluids is hampered by large variability and complexity of both control and patient samples, laborious biochemical analyses, and the fact that the identified proteins are unlikely produced by the diseased cells but are due to secondary body defense mechanisms. In a new approach presented here, we eliminate these problems by performing proteomic analysis in a prostate cancer xenograft model in which human prostate cancer cells form a tumor in an immune-incompetent nude mouse. Using this concept, proteins present in mouse serum that can be identified as human will, by definition, originate from the human prostate cancer xenograft and might have potential diagnostic and prognostic value. Using one-dimensional gel electrophoresis, liquid chromatography, and mass spectrometry, we identified tumor-derived human nm23/nucleoside-diphosphate kinase (NME) in the serum of a nude mouse bearing the androgen-independent human prostate cancer xenograft PC339. NME is known to be involved in the metastatic potential of several tumor cells, including prostate cancer cells. Furthermore we identified six human enzymes involved in glycolysis (fructose-bisphosphate aldolase A, triose-phosphate isomerase, glyceraldehyde-3-phosphate dehydrogenase, alpha enolase, and lactate dehydrogenases A and B) in the serum of the tumor-bearing mice. The presence of human NME and glyceraldehyde-3-phosphate dehydrogenase in the serum of PC339-bearing mice was confirmed by Western blotting. Although the putative usefulness of these proteins in predicting prognosis of prostate cancer remains to be determined, the present data illustrate that our approach is a promising tool for the focused discovery of new prostate cancer biomarkers.     

The human serum proteome: display of nearly 3700 chromatographically separated protein spots on two-dimensional electrophoresis gels and identification of 325 distinct proteins

Plasma, the soluble component of the human blood, is believed to harbor thousands of distinct proteins, which originate from a variety of cells and tissues through either active secretion or leakage from blood cells or tissues. The dynamic range of plasma protein concentrations comprises at least nine orders of magnitude. Proteins involved in coagulation, immune defense, small molecule transport, and protease inhibition, many of them present in high abundance in this body fluid, have been functionally characterized and associated with disease processes. For example, protein sequence mutations in coagulation factors cause various serious disease states. Diagnosing and monitoring such diseases in blood plasma of affected individuals has typically been conducted by use of enzyme-linked immunosorbent assays, which using a specific antibody quantitatively measure only the affected protein in the tested plasma samples. The discovery of protein biomarkers in plasma for diseases with no known correlations to genetic mutations is challenging. It requires a highly parallel display and quantitation strategy for proteins. We fractionated blood serum proteins prior to display on two-dimensional electrophoresis (2-DE) gels using immunoaffinity chromatography to remove the most abundant serum proteins, followed by sequential anion-exchange and size-exclusion chromatography. Serum proteins from 74 fractions were displayed on 2-DE gels. This approach succeeded in resolving approximately 3700 distinct protein spots, many of them post-translationally modified variants of plasma proteins. About 1800 distinct serum protein spots were identified by mass spectrometry. They collapsed into 325 distinct proteins, after sequence homology and similarity searches were carried out to eliminate redundant protein annotations. Although a relatively insensitive dye, Coomassie Brilliant Blue G-250, was used to visualize protein spots, several proteins known to be present in serum in < 10 ng/mL concentrations were identified such as interleukin-6, cathepsins, and peptide hormones. Considering that our strategy allows highly parallel protein quantitation on 2-DE gels, it holds promise to accelerate the discovery of novel serum protein biomarkers.     

Comparative plasma proteome analysis of lymphoma-bearing SJL mice

In SJL mice, growth of RcsX lymphoma cells induces an inflammatory response by stimulating V(beta)16+ T cells. During inflammation, various serum protein levels can increase (e.g., acute phase reactants) or decrease (e.g., albumin), and most of these altered proteins are thus potential biomarkers. Although blood plasma is a valuable and promising sample for biomarker discovery for diseases or for novel drug targets, its proteome is complex. To address this, we have focused on a comprehensive comparison of the plasma proteomes from normal and RcsX-tumor-bearing SJL mice using the 1D-Gel-LC-MS/MS method after removing albumin and immunoglobulins. This analysis resulted in the identification of a total of 1079 nonredundant mouse plasma proteins; more than 480 in normal and 790 in RcsX-tumor-bearing SJL mouse plasma. Of these, only 191 proteins were found in common. The molecular weights ranged from 2 to 876 kDa, covering the pI values between 4.22 and 12.09, and included proteins with predicted transmembrane domains. By comparing the plasma proteomic profile of normal and RcsX-tumor-bearing SJL mice, we found significant changes in the levels of many proteins in RcsX-tumor-bearing mouse plasma. Most of the up-regulated proteins were identified as acute-phase proteins (APPs). Also, several unique proteins i.e., haptoglobin, proteosome subunits, fetuin-B, 14-3-3 zeta, MAGE-B4 antigen, etc, were found only in the tumor-bearing mouse plasma; either secreted, shed by membrane vesicles, or externalized due to cell death. These results affirm the effectiveness of this approach for protein identification from small samples, and for comparative proteomics in potential animal models of human disorders.     

Proteomic characteristics of the liver and skeletal muscle in the Chinese tree shrew (Tupaia belangeri chinensis)

Valid animal models are useful for studying the pathophysiology of specific disorders, such as neural disease, diabetes and cancer. Previous molecular phylogeny studies indicate that the tree shrew is in the same order as (or a close sister to) primates, and thus may be an ideal model in which to study human disease. In this study, the proteome of liver and muscle tissue in tree the shrew was identified by combining peptide fractionation and LC-MS/MS identification. In total, 2146 proteins were detected, including 1759 proteins in liver samples and 885 proteins in skeletal muscle samples from the tree shrew. Further sub-source analysis revealed that nearly half of the identified proteins (846 proteins and 418 proteins) were derived from human database. In this study, we are the first to describe the characteristics of the proteome from the liver and skeletal muscle of the tree shrew. Phylogenetic tree analysis based on these proteomic data showed that the tree shrew is closer to primates (human) than to glires (the mouse and rat).     

TIP,a T-cell factor identified using high-throughput screening increases survival in a graft-versus-host disease model

A coordinated effort combining bioinformatic tools with high-throughput cell-based screening assays was implemented to identify novel factors involved in T-cell biology. We generated a unique library of cDNAs encoding predicted secreted and transmembrane domain-containing proteins generated by analyzing the Human Genome Sciences cDNA database with a combination of two algorithms that predict signal peptides. Supernatants from mammalian cells transiently transfected with this library were incubated with primary T cells and T-cell lines in several high-throughput assays. Here we describe the discovery of a T cell factor, TIP (T cell immunomodulatory protein), which does not show any homology to proteins with known function. Treatment of primary human and murine T cells with TIP in vitro resulted in the secretion of IFN-gamma, TNF-alpha, and IL-10, whereas in vivo TIP had a protective effect in a mouse acute graft-versus-host disease (GVHD) model. Therefore, combining functional genomics with high-throughput cell-based screening is a valuable and efficient approach to identifying immunomodulatory activities for novel proteins.     

Detection of Mycobacterium tuberculosis Peptides in the Exosomes of Patients with Active and Latent M. tuberculosis Infection Using MRM-MS

The identification of easily measured, accurate diagnostic biomarkers for active tuberculosis (TB) will have a significant impact on global TB control efforts. Because of the host and pathogen complexities involved in TB pathogenesis, identifying a single biomarker that is adequately sensitive and specific continues to be a major hurdle. Our previous studies in models of TB demonstrated that exosomes, such as those released from infected macrophages, contain mycobacterial products, including many Mtb proteins. In this report, we describe the development of targeted proteomics assays employing multiplexed multiple reaction monitoring mass spectrometry (MRM-MS) in order to allow us to follow those proteins previously identified by western blot or shotgun mass spectrometry, and enhance biomarker discovery to include detection of Mtb proteins in human serum exosomes. Targeted MRM-MS assays were applied to exosomes isolated from human serum samples obtained from culture-confirmed active TB patients to detect 76 peptides representing 33 unique Mtb proteins. Our studies revealed the first identification of bacteria-derived biomarker candidates of active TB in exosomes from human serum. Twenty of the 33 proteins targeted for detection were found in the exosomes of TB patients, and included multiple peptides from 8 proteins (Antigen 85B, Antigen 85C, Apa, BfrB, GlcB, HspX, KatG, and Mpt64). Interestingly, all of these proteins are known mycobacterial adhesins and/or proteins that contribute to the intracellular survival of Mtb. These proteins will be included as target analytes in future validation studies as they may serve as markers for persistent active and latent Mtb infection. In summary, this work is the first step in identifying a unique and specific panel of Mtb peptide biomarkers encapsulated in exosomes and reveals complex biomarker patterns across a spectrum of TB disease states.     

A proteomic study of the HUPO Plasma Proteome Project's pilot samples using an accurate mass and time tag strategy

Characterization of the human blood plasma proteome is critical to the discovery of routinely useful clinical biomarkers. We used an accurate mass and time (AMT) tag strategy with high-resolution mass accuracy cLC-FT-ICR MS to perform a global proteomic analysis of pilot study samples as part of the HUPO Plasma Proteome Project. HUPO reference serum and citrated plasma samples from African Americans, Asian Americans, and Caucasian Americans were analyzed, in addition to a Pacific Northwest National Laboratory reference serum and plasma. The AMT tag strategy allowed us to leverage two previously published "shotgun" proteomics experiments to perform global analyses on these samples in triplicate in less than 4 days total analysis time. A total of 722 (22% with multiple peptide identifications) International Protein Index redundant proteins, or 377 protein families by ProteinProphet, were identified over the six individual HUPO serum and plasma samples. The samples yielded a similar number of identified redundant proteins in the plasma samples (average 446 +/- 23) as found in the serum samples (average 440 +/- 20). These proteins were identified by an average of 956 +/- 35 unique peptides in plasma and 930 +/- 11 unique peptides in serum. In addition to this high-throughput analysis, the AMT tag approach was used with a Z-score normalization to compare relative protein abundances. This analysis highlighted both known differences in serum and citrated plasma such as fibrinogens, and reproducible differences in peptide abundances from proteins such as soluble activin receptor-like kinase 7b and glycoprotein m6b. The AMT tag strategy not only improved our sample throughput but also provided a basis for estimated quantitation.     

A mouse model repository for cancer biomarker discovery

Early detection of cancer using biomarkers obtained from blood or other easily accessible tissues would have a significant impact on reducing cancer mortality. However, identifying new blood-based biomarkers has been hindered by the dynamic complexity of the human plasma proteome, confounded by genetic and environmental variability, and the scarcity of high quality controlled samples. In this report, we discuss a new paradigm for biomarker discovery through the use of mouse models. Inbred mouse models of cancer recapitulate many critical features of human cancer, while eliminating sources of environmental and genetic variability. The ability to collect samples from highly matched cases and controls under identical conditions further reduces variability which is critical for successful biomarker discovery. We describe the establishment of a repository containing tumor, plasma, urine, and other tissues from 10 different mouse models of human cancer, including two breast, two lung, two prostate, two gastrointestinal, one ovarian, and one skin tumor model. We present the overall design of this resource and its potential use by the research community for biomarker discovery.     

The pattern of gene expression in mouse Gr-1(+) myeloid progenitor cells

To understand the pattern of gene expression in mouse myeloid progenitor cells, we carried out a genome-wide analysis of gene expression in mouse bone marrow Gr-1(+) cells using SAGE and GLGI techniques. We identified 22,033 unique SAGE tags with quantitative information from 73,869 collected SAGE tags. Among these unique tags, 64% match known sequences, including many genes important for myeloid differentiation, and 36% have no matches to known sequences and are likely to represent novel genes. We compared the expression of mouse Gr-1(+) and human CD15(+) myeloid progenitor cells and showed that the pattern of gene expression of these two cell populations had some similarities. We also compared the expression of mouse Gr-1(+) myeloid progenitor cells with that of mouse brain tissue and found a highly tissue-specific manner of gene expression in these two samples. Our data provide a basis for studying altered gene expression in myeloid disorders using mouse models.     

Mapping of the serum proteome of hepatocellular carcinoma induced by targeted overexpression of epidermal growth factor to liver cells of transgenic mice

Epidermal growth factor (EGF) is an important mitogen for hepatocytes. Its targeted overexpression induced hepatocellular carcinomas (HCC), as recently reported by us (Borlak et al. 2005). Early detection of disease is essential for successful therapy and overall survival. Here we describe our efforts in identifying serum biomarkers of liver cancer in a transgenic disease model that mimics effectively the consequence of exaggerated EGF signaling. We report a reference 2-DE map of mouse serum proteins. About 180 proteins were detected per gel and 130 proteins were identified by 2-DE-MALDI-MS analysis. We compared serum proteins of healthy nontransgenic and HCC tumor-bearing mice and identified 25 regulated proteins, of which n = 7 reached statistical significance ( p < 0.05). Furthermore, we identified several fragments of fibrinogens and of the alpha-2-macroglobulin to be disease-associated. We also found immunoglobulins to be repressed or absent in serum samples of tumor-bearing mice, and this included, among others, the Ig K and L class. In contrast, amyloid component P and apolipoprotein M were highly significantly increased by 10- and 8-fold, respectively, in serum samples of HCC mice. Overall, our findings provide a rationale for further clinical evaluation of the herein identified biomarker candidates.     

Clinical-scale high-throughput human plasma proteome analysis: lung adenocarcinoma

Clinical proteomics requires the stable and reproducible analysis of a large number of human samples. We report a high-throughput comprehensive protein profiling system comprising a fully automated, on-line, two-dimensional microflow liquid chromatography/tandem mass spectrometry (2-D microLC-MS/MS) system for use in clinical proteomics. A linear ion-trap mass spectrometer (ITMS) also known as a 2-D ITMS instrument, which is characterized by high scan speed, was incorporated into the microLC-MS/MS system in order to obtain highly improved sensitivity and resolution in MS/MS acquisition. This system was used to evaluate bovine serum albumin and human 26S proteasome. Application of these high-throughput microLC conditions and the 2-D ITMS resulted in a 10-fold increase in sensitivity in protein identification. Additionally, peptide fragments from the 26S proteasome were identified three-fold more efficiently than by the conventional 3-D ITMS instrument. In this study, the 2-D microLC-MS/MS system that uses linear 2-D ITMS has been applied for the plasma proteome analysis of a few samples from healthy individuals and lung adenocarcinoma patients. Using the 2-D and 1-D microLC-MS/MS analyses, approximately 250 and 100 different proteins were detected, respectively, in each HSA- and IgG-depleted sample, which corresponds to only 0.4 microL of blood plasma. Automatic operation enabled the completion of a single run of the entire 1-D and 2-D microLC-MS/MS analyses within 11 h. Investigation of the data extracted from the protein identification datasets of both healthy and adenocarcinoma groups revealed that several of the group-specific proteins could be candidate protein disease markers expressed in the human blood plasma. Consequently, it was demonstrated that this high-throughput microLC-MS/MS protein profiling system would be practically applicable to the discovery of protein disease markers, which is the primary objective in clinical plasma proteome projects.     

A xenograft mouse model coupled with in-depth plasma proteome analysis facilitates identification of novel serum biomarkers for human ovarian cancer

Proteomics discovery of novel cancer serum biomarkers is hindered by the great complexity of serum, patient-to-patient variability, and triggering by the tumor of an acute-phase inflammatory reaction. This host response alters many serum protein levels in cancer patients, but these changes have low specificity as they can be triggered by diverse causes. We addressed these hurdles by utilizing a xenograft mouse model coupled with an in-depth 4-D protein profiling method to identify human proteins in the mouse serum. This strategy ensures that identified putative biomarkers are shed by the tumor, and detection of low-abundance proteins shed by the tumor is enhanced because the mouse blood volume is more than a thousand times smaller than that of a human. Using TOV-112D ovarian tumors, more than 200 human proteins were identified in the mouse serum, including novel candidate biomarkers and proteins previously reported to be elevated in either ovarian tumors or the blood of ovarian cancer patients. Subsequent quantitation of selected putative biomarkers in human sera using label-free multiple reaction monitoring (MRM) mass spectrometry (MS) showed that chloride intracellular channel 1, the mature form of cathepsin D, and peroxiredoxin 6 were elevated significantly in sera from ovarian carcinoma patients.     

Characterization of the human ventricular cerebrospinal fluid proteome obtained from hydrocephalic patients

The continuing expansion of proteomic technology has been fueled by the potential for discovering novel biomarkers that may be used for the early detection of disease. It has been proposed that human cerebrospinal fluid (CSF), which surrounds and protects the brain and spinal cord from traumatic injury, may be a valuable target for the diagnosis of a variety of conditions such as Alzheimer's disease, traumatic brain injury, amyotrophic lateral sclerosis and Parkinson's disease. The immense complexity of biofluids, however, still requires that considerable development be made in the analytical techniques used so that comprehensive coverage of the proteins present in such samples is achieved. Using a simple separation strategy the protein complement of human ventricular cerebrospinal fluid obtained from patients with hydrocephalus was evaluated. The study resulted in the identification of over 1500 unique proteins that were found within all nine CSF samples that were analyzed. Comparison with the HUPO serum proteome database demonstrated that human ventricular CSF contains a large array of proteins that may be unique to CSF. This analysis greatly increases our knowledge of the protein content of this clinically important biofluid.     

A serum glycomics approach to breast cancer biomarkers

Because the glycosylation of proteins is known to change in tumor cells during the development of breast cancer, a glycomics approach is used here to find relevant biomarkers of breast cancer. These glycosylation changes are known to correlate with increasing tumor burden and poor prognosis. Current antibody-based immunochemical tests for cancer biomarkers of ovarian (CA125), breast (CA27.29 or CA15-3), pancreatic, gastric, colonic, and carcinoma (CA19-9) target highly glycosylated mucin proteins. However, these tests lack the specificity and sensitivity for use in early detection. This glycomics approach to find glycan biomarkers of breast cancer involves chemically cleaving oligosaccharides (glycans) from glycosylated proteins that are shed or secreted by breast cancer tumor cell lines. The resulting free glycan species are analyzed by MALDI-FT-ICR MS. Further structural analysis of the glycans can be performed in FTMS through the use of tandem mass spectrometry with infrared multiphoton dissociation. Glycan profiles were generated for each cell line and compared. These methods were then used to analyze sera obtained from a mouse model of breast cancer and a small number of serum samples obtained from human patients diagnosed with breast cancer or patients with no known history of breast cancer. In addition to the glycosylation changes detected in mice as mouse mammary tumors developed, glycosylation profiles were found to be sufficiently different to distinguish patients with cancer from those without. Although the small number of patient samples analyzed so far is inadequate to make any legitimate claims at this time, these promising but very preliminary results suggest that glycan profiles may contain distinct glycan biomarkers that may correspond to glycan "signatures of cancer."     

S100A6, a calcium- and zinc-binding protein, is overexpressed in SOD1 mutant mice, a model for amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterised by selective degeneration of motoneurones. Familial ALS is an age-dependent autosomal dominant disorder in which mutations in the homodimeric enzyme Cu/Zn superoxide dismutase 1 (SOD1) is linked to the disease. An animal model for this disease is a transgenic mouse expressing the mutated human SOD1(G93A) gene. Recent electrophysiological data emphasised that the striking selective vulnerability of motoneurones might be due to their differential calcium buffering capacities. Therefore we have investigated, using immunohistochemistry, the expression of different calcium binding proteins in brainstem and spinal cord from normal and SOD1 mutated mice. Among the 13 calcium-binding proteins screened, only one, S100A6, a homodimeric calcium-binding protein able to bind four Zn(2+), appeared to be highly expressed in the SOD1 mutated mice. In brainstem, reactive astrocytes, but not motoneurones, from several regions, including nerve 12 root, were highly S100A6-positive. Hypoglossal nucleus was negative for S100A6. In dorsal root, reactive astrocytes from both white matter and anterior horn were highly reactive. If overexpression of S100A6 is specific for ALS, it will be a valuable diagnostic marker for this disease.