Sander R. Piersma

PPIB Mutations Cause Severe Osteogenesis Imperfecta

Deficiency of cartilage-associated protein (CRTAP) or prolyl 3-hydroxylase 1(P3H1) has been reported in autosomal-recessive lethal or severe osteogenesis imperfecta (OI). CRTAP, P3H1, and cyclophilin B (CyPB) form an intracellular collagen-modifying complex that 3-hydroxylates proline at position 986 (P986) in the alpha1 chains of collagen type I. This 3-prolyl hydroxylation is decreased in patients with CRTAP and P3H1 deficiency. It was suspected that mutations in the PPIB gene encoding CyPB would also cause OI with decreased collagen 3-prolyl hydroxylation. To our knowledge we present the first two families with recessive OI caused by PPIB gene mutations. The clinical phenotype is compatible with OI Sillence type II-B/III as seen with COL1A1/2, CRTAP, and LEPRE1 mutations. The percentage of 3-hydroxylated P986 residues in patients with PPIB mutations is decreased in comparison to normal, but it is higher than in patients with CRTAP and LEPRE1 mutations. This result and the fact that CyPB is demonstrable independent of CRTAP and P3H1, along with reported decreased 3-prolyl hydroxylation due to deficiency of CRTAP lacking the catalytic hydroxylation domain and the known function of CyPB as a cis-trans isomerase, suggest that recessive OI is caused by a dysfunctional P3H1/CRTAP/CyPB complex rather than by the lack of 3-prolyl hydroxylation of a single proline residue in the alpha1 chains of collagen type I.

Direct Visualization by Cryo-EM of the Mycobacterial Capsular Layer: A Labile Structure Containing ESX-1-Secreted Proteins

The cell envelope of mycobacteria, a group of Gram positive bacteria, is composed of a plasma membrane and a Gram-negative-like outer membrane containing mycolic acids. In addition, the surface of the mycobacteria is coated with an ill-characterized layer of extractable, non-covalently linked glycans, lipids and proteins, collectively known as the capsule, whose occurrence is a matter of debate. By using plunge freezing cryo-electron microscopy technique, we were able to show that pathogenic mycobacteria produce a thick capsule, only present when the cells were grown under unperturbed conditions and easily removed by mild detergents. This detergent-labile capsule layer contains arabinomannan, α-glucan and oligomannosyl-capped glycolipids. Further immunogenic and proteomic analyses revealed that Mycobacterium marinum capsule contains high amounts of proteins that are secreted via the ESX-1 pathway. Finally, cell infection experiments demonstrated the importance of the capsule for binding to cells and dampening of pro-inflammatory cytokine response. Together, these results show a direct visualization of the mycobacterial capsular layer as a labile structure that contains ESX-1-secreted proteins.

On the beta-binomial model for analysis of spectral count data in label-free tandem mass spectrometry-based proteomics

MOTIVATION Spectral count data generated from label-free tandem mass spectrometry-based proteomic experiments can be used to quantify proteins abundances reliably. Comparing spectral count data from different sample groups such as control and disease is an essential step in statistical analysis for the determination of altered protein level and biomarker discovery. The Fishers exact test, the G-test, the t-test and the local-pooled-error technique (LPE) are commonly used for differential analysis of spectral count data. However, our initial experiments in two cancer studies show that the current methods are unable to declare at 95% confidence level a number of protein markers that have been judged to be differential on the basis of the biology of the disease and the spectral count numbers. A shortcoming of these tests is that they do not take into account within- and between-sample variations together. Hence, our aim is to improve upon existing techniques by incorporating both the within- and between-sample variations. RESULT We propose to use the beta-binomial distribution to test the significance of differential protein abundances expressed in spectral counts in label-free mass spectrometry-based proteomics. The beta-binomial test naturally normalizes for total sample count. Experimental results show that the beta-binomial test performs favorably in comparison with other methods on several datasets in terms of both true detection rate and false positive rate. In addition, it can be applied for experiments with one or more replicates, and for multiple condition comparisons. Finally, we have implemented a software package for parameter estimation of two beta-binomial models and the associated statistical tests. AVAILABILITY AND IMPLEMENTATION A software package implemented in R is freely available for download at http://www.oncoproteomics.nl/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Workflow comparison for label-free, quantitative secretome proteomics for cancer biomarker discovery: method evaluation, differential analysis, and verification in serum.

The cancer cell secretome has emerged as an attractive subproteome for discovery of candidate blood-based biomarkers. To choose the best performing workflow, we assessed the performance of three first-dimension separation strategies prior to nanoLC-MS/MS analysis: (1) 1D gel electrophoresis (1DGE), (2) peptide SCX chromatography, and (3) tC2 protein reversed phase chromatography. 1DGE using 4-12% gradient gels outperformed the SCX and tC2 methods with respect to number of identified proteins (1092 vs 979 and 580, respectively), reproducibility of protein identification (80% vs 70% and 72%, respectively, assessed in biological N = 3). Reproducibility of protein quantitation based on spectral counting was similar for all 3 methods (CV: 26% vs 24% and 24%, respectively). As a proof-of-concept of secretome proteomics for blood-based biomarker discovery, the gradient 1DGE workflow was subsequently applied to identify IGF1R-signaling related proteins in the secretome of mouse embryonic fibroblasts transformed with human IGF1R (MEF/Toff/IGF1R). VEGF and osteopontin were differentially detected by LC-MS/MS and verified in secretomes by ELISA. Follow-up in serum of mice bearing MEF/Toff/IGF1R-induced tumors showed an increase of osteopontin levels paralleling tumor growth, and reduction in the serum of mice in which IGF1R expression was shut off and tumor regressed.

Proteomics of the TRAP-induced platelet releasate.

Upon stimulation, platelets release the soluble content of their cytoplasmic granules along with microparticles. This sub-proteome is of interest since many of its constituents are associated with coagulation, (tumor) angiogenesis, cell growth and adhesion. Previously, differential - antibody-based - serum analysis has yielded information on the proteins released from platelets upon stimulation. A promising alternative strategy is formed by identifying the proteins released by freshly isolated platelets from blood using proteomics. Here we report on the analysis of the thrombin receptor activating peptide (TRAP)-induced releasate from 3 different volunteers using high resolution, high mass accuracy hybrid LTQ-FT mass spectrometry in a GeLC-MS/MS workflow. We obtained an activated platelet releasate proteome comprising a total of 716 identified proteins with 225 proteins present in the releasate of 3/3 volunteers. This core dataset is characterized by gene ontology mining and signal peptide analysis. Meta-analysis of our dataset and two published datasets of platelet a-granules and microparticles reveals that 55% of our platelet releasate proteins can be annotated using these previous platelet subproteome data, of the remaining releasate proteome 5% overlaps with a published platelet secretome while 40% of our data consists of novel releasate proteins. This high-accuracy activated platelet releasate proteome represents the largest and most comprehensive analysis to date. This approach offers unique possibilities to analyse the role of platelet-secreted proteins in physiology and in diseases such as atherosclerosis and cancer.

Comparative Proteomics of Colon Cancer Stem Cells and Differentiated Tumor Cells Identifies BIRC6 as a Potential Therapeutic Target

Patients with liver metastases from colon carcinoma show highly variable responses to chemotherapy and tumor recurrence is frequently observed. Therapy-resistant cancer stem cells have been implicated in drug resistance and tumor recurrence. However, the factors determining therapy resistance and tumor recurrence are poorly understood. The aim of this study was to gain insight into these mechanisms by comparing the proteomes of patient-derived cancer stem cell cultures and their differentiated isogenic offspring. We established colonosphere cultures derived from resection specimens of liver metastases in patients with colon cancer. These colonospheres, enriched for colon cancer stem cells, were used to establish isogenic cultures of stably differentiated nontumorigenic progeny. Proteomics based on one-dimensional gel electrophoresis coupled to nano liquid chromatography tandem MS was used to identify proteome differences between three of these paired cultures. The resulting data were analyzed using Ingenuity Pathway Software. Out of a total data set of 3048 identified proteins, 32 proteins were at least twofold up-regulated in the colon cancer stem cells when compared with the differentiated cells. Pathway analysis showed that “cell death ” regulation is strikingly different between the two cell types. Interestingly, one of the top-up-regulated proteins was BIRC6, which belongs to the class of Inhibitor of Apoptosis Proteins. Knockdown of BIRC6 sensitized colon cancer stem cells against the chemotherapeutic drugs oxaliplatin and cisplatin. This study reveals that differentiation of colon cancer stem cells is accompanied by altered regulation of cell death pathways. We identified BIRC6 as an important mediator of cancer stem cell resistance against cisplatin and oxaliplatin. Targeting BIRC6, or other Inhibitors of Apoptosis Proteins, may help eradicating colon cancer stem cells.

Composition of the type VII secretion system membrane complex

Pathogenic mycobacteria require type VII secretion (T7S) systems to transport virulence factors across their complex cell envelope. These bacteria have up to five of these systems, termed ESX‐1 to ESX‐5. Here, we show that ESX‐5 of Mycobacterium tuberculosis mediates the secretion of EsxN, PPE and PE_PGRS proteins, indicating that ESX‐5 is a major secretion pathway in this important pathogen. Using the ESX‐5 system of Mycobacterium marinum and Mycobacterium bovis BCG as a model, we have purified and analysed the T7S membrane complex under native conditions. blue native‐PAGE and immunoprecipitation experiments showed that the ESX‐5 membrane complex of both species has a size of ∼ 1500 kDa and is composed of four conserved membrane proteins, i.e. EccB5, EccC5, EccD5 and EccE5. Subsequent limited proteolysis suggests that EccC5 and EccE5 mostly reside on the periphery of the complex. We also observed that EccC5 and EccD5 expression is essential for the formation of a stable membrane complex. These are the first data on a T7S membrane complex and, given the high conservation of its components, our data can likely be generalized to most mycobacterial T7S systems.

Imaging mass spectrometry at cellular length scales

Imaging mass spectrometry (IMS) allows the direct investigation of both the identity and the spatial distribution of the molecular content directly in tissue sections, single cells and many other biological surfaces. In this protocol, we present the steps required to retrieve the molecular information from tissue sections using matrix-enhanced (ME) and metal-assisted (MetA) secondary ion mass spectrometry (SIMS) as well as matrix-assisted laser desorption/ionization (MALDI) IMS. These techniques require specific sample preparation steps directed at optimal signal intensity with minimal redistribution or modification of the sample analytes. After careful sample preparation, different IMS methods offer a unique discovery tool in, for example, the investigation of (i) drug transport and uptake, (ii) biological processing steps and (iii) biomarker distributions. To extract the relevant information from the huge datasets produced by IMS, new bioinformatics approaches have been developed. The duration of the protocol is highly dependent on sample size and technique used, but on average takes approximately 5 h.

Proteomic Profiling of Mycobacterium tuberculosis Identifies Nutrient-starvation-responsive Toxin–antitoxin Systems

In order to successfully enter the latent stage, Mycobacterium tuberculosis must adapt to conditions such as nutrient limitation and hypoxia. In vitro models that mimic latent infection are valuable tools for describing the changes in metabolism that occur when the bacterium exists in a non-growing form. We used two complementary proteomic approaches, label-free LC-MS/MS analysis and two-dimensional difference gel electrophoresis, to determine the proteome profile of extracellular proteins from M. tuberculosis cultured under nutrient starvation. Through the label-free LC-MS/MS analysis of fractionated samples, 1176 proteins were identified from culture filtrates of log phase and nutrient-starved cultures, and the protein levels of 230 proteins were increased in nutrient-starved culture filtrates, whereas those of 208 proteins were decreased. By means of Gene Ontology clustering analysis, significant differences in the overall metabolism during nutrient starvation were detected. Notably, members of the toxin–antitoxin systems were present in larger quantities in nutrient-starved cultures, supporting a role for these global modules as M. tuberculosis switches its metabolism into dormancy. Decreased abundance of proteins involved in amino acid and protein synthesis was apparent, as well as changes in the lipid metabolism. Further analysis of the dataset identified increased abundance of lipoproteins and decreased abundance of ESAT-6 family proteins. Results from the two-dimensional difference gel electrophoresis proteomics demonstrated overall agreement with the LC-MS/MS data and added complementary insights about protein degradation and modification.

Subnuclear Proteomics in Colorectal Cancer IDENTIFICATION OF PROTEINS ENRICHED IN THE NUCLEAR MATRIX FRACTION AND REGULATION IN ADENOMA TO CARCINOMA PROGRESSION

Abnormalities in nuclear phenotype and chromosome structure are key features of cancer cells. Investigation of the protein determinants of nuclear subfractions in cancer may yield molecular insights into aberrant chromosome function and chromatin organization and in addition may yield biomarkers for early cancer detection. Here we evaluate a proteomics work flow for profiling protein constituents in subnuclear domains in colorectal cancer tissues and apply this work flow to a comparative analysis of the nuclear matrix fraction in colorectal adenoma and carcinoma tissue samples. First, we established the reproducibility of the entire work flow. In a reproducibility analysis of three nuclear matrix fractions independently isolated from the same colon tumor homogenate, 889 of 1,047 proteins (85%) were reproducibly identified at high confidence (minimally two peptides per protein at 99% confidence interval at the protein level) with an average coefficient of variance for the number of normalized spectral counts per protein of 30%. This indicates a good reproducibility of the entire work flow from biochemical isolation to nano-LC-MS/MS analysis. Second, using spectral counting combined with statistics, we identified proteins that are significantly enriched in the nuclear matrix fraction relative to two earlier fractions (the chromatin-binding and intermediate filament fractions) isolated from six colorectal tissue samples. The total data set contained 2,059 non-redundant proteins. Gene ontology mining and protein network analysis of nuclear matrix-enriched proteins revealed enrichment for proteins implicated in “RNA processing” and “mRNA metabolic process.” Finally, an explorative comparison of the nuclear matrix proteome in colorectal adenoma and carcinoma tissues revealed many proteins previously implicated in oncogenesis as well as new candidates. A subset of these differentially expressed proteins also exhibited a corresponding change at the mRNA level. Together, the results show that subnuclear proteomics of tumor tissue is feasible and a promising avenue for exploring oncogenesis.