Assessing protein immunogenicity with a dendritic cell line-derived endolysosomal degradome

Background

The growing number of novel candidate molecules for the treatment of allergic diseases imposed a dramatic increase in the demand for animal experiments to select immunogenic vaccines, a pre-requisite for efficacy. Because no in vitro methods to predict the immunogenicity of a protein are currently available, we developed an in vitro assay that exploits the link between a protein''s immunogenicity and its susceptibility to endolysosomal proteolysis.

Methodology

We compared protein composition and proteolytic activity of endolysosomal fractions isolated from murine bone marrow- and human blood- derived dendritic cells, and from the dendritic cell line JAWS II. Three groups of structurally related antigen variants differing in their ability to elicit immune responses in vivo (Bet v 1.0101 and Bet v 1.0401, RNases A and S, holo- and apo-HRP) were subjected to in vitro simulated endolysosomal degradation. Kinetics and patterns of generated proteolytic peptides were evaluated by gel electrophoresis and mass spectrometry.

Results

Antigens displaying weak capacity of T cell priming in vivo were highly susceptible to endolysosomal proteases in vitro. As proteolytic composition, activity, and specificity of endolysosomal fractions derived from human and murine dendritic cells were comparable, the JAWS II cell line could be used as a substitute for freshly isolated human or murine cells in in vitro degradation assays.

Conclusions

Endolysosomal fractions prepared from the JAWS II cell line provide a reliable tool for in vitro estimation of protein immunogenicity. The rapid and simple assay described here is very useful to study the immunogenic properties of a protein, and can help to replace, reduce, and refine animal experiments in allergy research and vaccine development in general.     

A Proteomic Approach for Comprehensively Screening Substrates of Protein Kinases Such as Rho-Kinase

Background

Protein kinases are major components of signal transduction pathways in multiple cellular processes. Kinases directly interact with and phosphorylate downstream substrates, thus modulating their functions. Despite the importance of identifying substrates in order to more fully understand the signaling network of respective kinases, efficient methods to search for substrates remain poorly explored.

Methodology/Principal Findings

We combined mass spectrometry and affinity column chromatography of the catalytic domain of protein kinases to screen potential substrates. Using the active catalytic fragment of Rho-kinase/ROCK/ROK as the model bait, we obtained about 300 interacting proteins from the rat brain cytosol fraction, which included the proteins previously reported as Rho-kinase substrates. Several novel interacting proteins, including doublecortin, were phosphorylated by Rho-kinase both in vitro and in vivo.

Conclusions/Significance

This method would enable identification of novel specific substrates for kinases such as Rho-kinase with high sensitivity.     

Run Charts Revisited: A Simulation Study of Run Chart Rules for Detection of Non-Random Variation in Health Care Processes

Background

A run chart is a line graph of a measure plotted over time with the median as a horizontal line. The main purpose of the run chart is to identify process improvement or degradation, which may be detected by statistical tests for non-random patterns in the data sequence.

Methods

We studied the sensitivity to shifts and linear drifts in simulated processes using the shift, crossings and trend rules for detecting non-random variation in run charts.

Results

The shift and crossings rules are effective in detecting shifts and drifts in process centre over time while keeping the false signal rate constant around 5% and independent of the number of data points in the chart. The trend rule is virtually useless for detection of linear drift over time, the purpose it was intended for.     

An Integrated Mass-Spectrometry Pipeline Identifies Novel Protein Coding-Regions in the Human Genome

Background

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

Results

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

Conclusions

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

Rapid MALDI-TOF Mass Spectrometry Strain Typing during a Large Outbreak of Shiga-Toxigenic Escherichia coli

Background

In 2011 northern Germany experienced a large outbreak of Shiga-Toxigenic Escherichia coli O104:H4. The large amount of samples sent to microbiology laboratories for epidemiological assessment highlighted the importance of fast and inexpensive typing procedures. We have therefore evaluated the applicability of a MALDI-TOF mass spectrometry based strategy for outbreak strain identification.

Methods

Specific peaks in the outbreak strain’s spectrum were identified by comparative analysis of archived pre-outbreak spectra that had been acquired for routine species-level identification. Proteins underlying these discriminatory peaks were identified by liquid chromatography tandem mass spectrometry and validated against publicly available databases. The resulting typing scheme was evaluated against PCR genotyping with 294 E. coli isolates from clinical samples collected during the outbreak.

Results

Comparative spectrum analysis revealed two characteristic peaks at m/z 6711 and m/z 10883. The underlying proteins were found to be of low prevalence among genome sequenced E. coli strains. Marker peak detection correctly classified 292 of 293 study isolates, including all 104 outbreak isolates.

Conclusions

MALDI-TOF mass spectrometry allowed for reliable outbreak strain identification during a large outbreak of Shiga-Toxigenic E. coli. The applied typing strategy could probably be adapted to other typing tasks and might facilitate epidemiological surveys as part of the routine pathogen identification workflow.     

An approach to multiscale modelling with graph grammars

Background and Aims

Functional–structural plant models (FSPMs) simulate biological processes at different spatial scales. Methods exist for multiscale data representation and modification, but the advantages of using multiple scales in the dynamic aspects of FSPMs remain unclear. Results from multiscale models in various other areas of science that share fundamental modelling issues with FSPMs suggest that potential advantages do exist, and this study therefore aims to introduce an approach to multiscale modelling in FSPMs.

Methods

A three-part graph data structure and grammar is revisited, and presented with a conceptual framework for multiscale modelling. The framework is used for identifying roles, categorizing and describing scale-to-scale interactions, thus allowing alternative approaches to model development as opposed to correlation-based modelling at a single scale. Reverse information flow (from macro- to micro-scale) is catered for in the framework. The methods are implemented within the programming language XL.

Key Results

Three example models are implemented using the proposed multiscale graph model and framework. The first illustrates the fundamental usage of the graph data structure and grammar, the second uses probabilistic modelling for organs at the fine scale in order to derive crown growth, and the third combines multiscale plant topology with ozone trends and metabolic network simulations in order to model juvenile beech stands under exposure to a toxic trace gas.

Conclusions

The graph data structure supports data representation and grammar operations at multiple scales. The results demonstrate that multiscale modelling is a viable method in FSPM and an alternative to correlation-based modelling. Advantages and disadvantages of multiscale modelling are illustrated by comparisons with single-scale implementations, leading to motivations for further research in sensitivity analysis and run-time efficiency for these models.     

Blood peptidome-degradome profile of breast cancer

Background

Cancer invasion and metastasis are closely associated with activities within the degradome; however, little is known about whether these activities can be detected in the blood of cancer patients.

Methodology and Principal Findings

The peptidome-degradome profiles of pooled blood plasma sampled from 15 breast cancer patients (BCP) and age, race, and menopausal status matched control healthy persons (HP) were globally characterized using advanced comprehensive separations combined with tandem Fourier transform mass spectrometry and new data analysis approaches that facilitated top-down peptidomic analysis. The BCP pool displayed 71 degradome protein substrates that encompassed 839 distinct peptidome peptides. In contrast, the HP 50 degradome substrates found encompassed 425 peptides. We find that the ratios of the peptidome peptide relative abundances can vary as much as >4000 fold between BCP and HP. The experimental results also show differential degradation of substrates in the BCP sample in their functional domains, including the proteolytic and inhibitory sites of the plasmin-antiplasmin and thrombin-antithrombin systems, the main chains of the extracellular matrix protection proteins, the excessive degradation of innate immune system key convertases and membrane attack complex components, as well as several other cancer suppressor proteins.

Conclusions

Degradomics-peptidomics profiling of blood plasma is highly sensitive to changes not evidenced by conventional bottom-up proteomics and potentially provides unique signatures of possible diagnostic utility.     

HIV-1 Envelope Resistance to Proteasomal Cleavage: Implications for Vaccine Induced Immune Responses

Background

Antigen processing involves many proteolytic enzymes such as proteasomes and cathepsins. The processed antigen is then presented on the cell surface bound to either MHC class I or class II molecules and induces/interacts with antigen-specific CD8+ and CD4+ T-cells, respectively. Preliminary immunological data from the RV144 phase III trial indicated that the immune responses were biased towards the Env antigen with a dominant CD4+ T-cell response.

Methods

In this study, we examined the susceptibility of HIV-1 Env-A244 gp120 protein, one of the protein boost subunits of the RV144 Phase III vaccine trial, to proteasomes and cathepsins and identified the generated peptide epitope repertoire by mass spectrometry. The peptide fragments were tested for cytokine production in CD4⁺ T-cell lines derived from RV144 volunteers.

Results

Env-A244 was resistant to proteasomes, thus diminishing the possibility of the generation of class I epitopes by the classical MHC class I pathway. However, Env-A244 was efficiently cleaved by cathepsins generating peptide arrays identified by mass spectrometry that contained both MHC class I and class II epitopes as reported in the Los Alamos database. Each of the cathepsins generated distinct degradation patterns containing regions of light and dense epitope clusters. The sequence DKKQKVHALF that is part of the V2 loop of gp120 produced by cathepsins induced a polyfunctional cytokine response including the generation of IFN-γ from CD4⁺ T-cell lines-derived from RV144 vaccinees. This sequence is significant since antibodies to the V1/V2-loop region correlated inversely with HIV-1 infection in the RV144 trial.

Conclusions

Based on our results, the susceptibility of Env-A244 to cathepsins and not to proteasomes suggests a possible mechanism for the generation of Env-specific CD4⁺T cell and antibody responses in the RV144 vaccinees.     

Serum Stabilities of Short Tryptophan- and Arginine-Rich Antimicrobial Peptide Analogs

Background

Several short antimicrobial peptides that are rich in tryptophan and arginine residues were designed with a series of simple modifications such as end capping and cyclization. The two sets of hexapeptides are based on the Trp- and Arg-rich primary sequences from the “antimicrobial centre” of bovine lactoferricin as well as an antimicrobial sequence obtained through the screening of a hexapeptide combinatorial library.

Methodology/Principal Findings

HPLC, mass spectrometry and antimicrobial assays were carried out to explore the consequences of the modifications on the serum stability and microbicidal activity of the peptides. The results show that C-terminal amidation increases the antimicrobial activity but that it makes little difference to its proteolytic degradation in human serum. On the other hand, N-terminal acetylation decreases the peptide activities but significantly increases their protease resistance. Peptide cyclization of the hexameric peptides was found to be highly effective for both serum stability and antimicrobial activity. However the two cyclization strategies employed have different effects, with disulfide cyclization resulting in more active peptides while backbone cyclization results in more proteolytically stable peptides. However, the benefit of backbone cyclization did not extend to longer 11-mer peptides derived from the same region of lactoferricin. Mass spectrometry data support the serum stability assay results and allowed us to determine preferred proteolysis sites in the peptides. Furthermore, isothermal titration calorimetry experiments showed that the peptides all had weak interactions with albumin, the most abundant protein in human serum.

Conclusions/Significance

Taken together, the results provide insight into the behavior of the peptides in human serum and will therefore aid in advancing antimicrobial peptide design towards systemic applications.     

Detection of Pseudomonas aeruginosa in sputum headspace through volatile organic compound analysis

Introduction

Chronic pulmonary infection is the hallmark of Cystic Fibrosis lung disease. Searching for faster and easier screening may lead to faster diagnosis and treatment of Pseudomonas aeruginosa (P. aeruginosa). Our aim was to analyze and build a model to predict the presence of P. aeruginosa in sputa.

Methods

Sputa from 28 bronchiectatic patients were used for bacterial culturing and analysis of volatile compounds by gas chromatography–mass spectrometry. Data analysis and model building were done by Partial Least Squares Regression Discriminant analysis (PLS-DA). Two analysis were performed: one comparing P. aeruginosa positive with negative cultures at study visit (PA model) and one comparing chronic colonization according to the Leeds criteria with P. aeruginosa negative patients (PACC model).

Results

The PA model prediction of P. aeruginosa presence was rather poor, with a high number of false positives and false negatives. On the other hand, the PACC model was stable and explained chronic P. aeruginosa presence for 95% with 4 PLS-DA factors, with a sensitivity of 100%, a positive predictive value of 86% and a negative predictive value of 100%.

Conclusion

Our study shows the potential for building a prediction model for the presence of chronic P. aeruginosa based on volatiles from sputum.     

High levels of N-palmitoylethanolamide and N-stearoylethanolamide in microdialysate samples from myalgic trapezius muscle in women

Background

N-acylethanolamines (NAEs) are endogenous compounds that regulate inflammation and pain. These include the cannabinoid ligand anandamide (AEA) and the peroxisome proliferator-activated receptor-α ligand palmitoylethanolamide (PEA). Little is known as to the levels of NAEs in pain states in human, particularly in the skeletal muscle. The aim of this study was to investigate the levels of these lipid mediators in muscle dialysate from women with chronic neck-/shoulder pain compared to healthy controls.

Methods

Eleven women with chronic neck-/shoulder pain and eleven healthy women participated in this study. All participants went through microdialysis procedures in the trapezius muscle. Muscle dialysate samples were collected during four hours and analysed by nano liquid chromatography tandem mass spectrometry (nLC-MS/MS).

Results

We were able to detect AEA, PEA, N-stearoylethanolamine (SEA) and 2-arachidonoylglycerol (2-AG) in a single chromatographic run. Of the NAEs studied, PEA and SEA were clearly detectable in the muscle microdialysate samples. The muscle dialysate levels of PEA and SEA were significantly higher in myalgic subjects compared to healthy controls.

Conclusion

This study demonstrates that microdialysis in combination with mass spectrometry can be used for analysing NAE''s in human muscle tissue regularly over time. Furthermore the significant group differences in the concentration of PEA and SEA in this study might fill an important gap in our knowledge of mechanisms in chronic myalgia in humans. In the long run this expanded understanding of nociceptive and anitinociceptive processes in the muscle may provide a base for ameliorating treatment and rehabilitation of pain.     

Change in Body Fat Mass Is Independently Associated with Executive Functions in Older Women: A Secondary Analysis of a 12-Month Randomized Controlled Trial

Objectives

To investigate the independent contribution of change in sub-total body fat and lean mass to cognitive performance, specifically the executive processes of selective attention and conflict resolution, in community-dwelling older women.

Methods

This secondary analysis included 114 women aged 65 to 75 years old. Participants were randomly allocated to once-weekly resistance training, twice-weekly resistance training, or twice-weekly balance and tone training. The primary outcome measure was the executive processes of selective attention and conflict resolution as assessed by the Stroop Test. Sub-total body fat and lean mass were measured by dual-energy x-ray absorptiometry (DXA) to determine the independent association of change in both sub-total body fat and sub-total body lean mass with Stroop Test performance at trial completion.

Results

A multiple linear regression model showed reductions in sub-total body fat mass to be independently associated with better performance on the Stroop Test at trial completion after accounting for baseline Stroop performance, age, baseline global cognitive state, baseline number of comorbidities, baseline depression, and experimental group. The total variance explained was 39.5%; change in sub-total body fat mass explained 3.9% of the variance. Change in sub-total body lean mass was not independently associated with Stroop Test performance (P>0.05).

Conclusion

Our findings suggest that reductions in sub-total body fat mass – not sub-total lean mass – is associated with better performance of selective attention and conflict resolution.     

Fungal artificial chromosomes for mining of the fungal secondary metabolome

Background

With thousands of fungal genomes being sequenced, each genome containing up to 70 secondary metabolite (SM) clusters 30–80 kb in size, breakthrough techniques are needed to characterize this SM wealth.

Results

Here we describe a novel system-level methodology for unbiased cloning of intact large SM clusters from a single fungal genome for one-step transformation and expression in a model host. All 56 intact SM clusters from Aspergillus terreus were individually captured in self-replicating fungal artificial chromosomes (FACs) containing both the E. coli F replicon and an Aspergillus autonomously replicating sequence (AMA1). Candidate FACs were successfully shuttled between E. coli and the heterologous expression host A. nidulans. As proof-of-concept, an A. nidulans FAC strain was characterized in a novel liquid chromatography-high resolution mass spectrometry (LC-HRMS) and data analysis pipeline, leading to the discovery of the A. terreus astechrome biosynthetic machinery.

Conclusion

The method we present can be used to capture the entire set of intact SM gene clusters and/or pathways from fungal species for heterologous expression in A. nidulans and natural product discovery.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1561-x) contains supplementary material, which is available to authorized users.     

Parkin mediates apparent E2-independent monoubiquitination in vitro and contains an intrinsic activity that catalyzes polyubiquitination

Background

Mutations in the parkin gene, which encodes a ubiquitin ligase (E3), are a major cause of autosomal recessive parkinsonism. Although parkin-mediated ubiquitination was initially linked to protein degradation, accumulating evidence suggests that the enzyme is capable of catalyzing multiple forms of ubiquitin modifications including monoubiquitination, K48- and K63-linked polyubiquitination. In this study, we sought to understand how a single enzyme could exhibit such multifunctional catalytic properties.

Methods and Findings

By means of in vitro ubiquitination assays coupled with mass spectrometry analysis, we were surprised to find that parkin is apparently capable of mediating E2-independent protein ubiquitination in vitro, an unprecedented activity exhibited by an E3 member. Interestingly, whereas full length parkin catalyzes solely monoubiquitination regardless of the presence or absence of E2, a truncated parkin mutant containing only the catalytic moiety supports both E2-independent and E2-dependent assembly of ubiquitin chains.

Conclusions

Our results here suggest a complex regulation of parkin''s activity and may help to explain how a single enzyme like parkin could mediate diverse forms of ubiquitination.     

Accelerated identification of proteins by mass spectrometry by employing covalent pre-gel staining with Uniblue A

Background

The identification of proteins by mass spectrometry is a standard method in biopharmaceutical quality control and biochemical research. Prior to identification by mass spectrometry, proteins are usually pre-separated by electrophoresis. However, current protein staining and de-staining protocols are tedious and time consuming, and therefore prolong the sample preparation time for mass spectrometry.

Methodology and Principal Findings

We developed a 1-minute covalent pre-gel staining protocol for proteins, which does not require de-staining before the mass spectrometry analysis. We investigated the electrophoretic properties of derivatized proteins and peptides and studied their behavior in mass spectrometry. Further, we elucidated the preferred reaction of proteins with Uniblue A and demonstrate the integration of the peptide derivatization into typical informatics tools.

Conclusions and Significance

The Uniblue A staining method drastically speeds up the sample preparation for the mass spectrometry based identification of proteins. The application of this chemo-proteomic strategy will be advantageous for routine quality control of proteins and for time-critical tasks in protein analysis.     

Classification and identification of bacteria by mass spectrometry and computational analysis

Background

In general, the definite determination of bacterial species is a tedious process and requires extensive manual labour. Novel technologies for bacterial detection and analysis can therefore help microbiologists in minimising their efforts in developing a number of microbiological applications.

Methodology

We present a robust, standardized procedure for automated bacterial analysis that is based on the detection of patterns of protein masses by MALDI mass spectrometry. We particularly applied the approach for classifying and identifying strains in species of the genus Erwinia. Many species of this genus are associated with disastrous plant diseases such as fire blight. Using our experimental procedure, we created a general bacterial mass spectra database that currently contains 2800 entries of bacteria of different genera. This database will be steadily expanded. To support users with a feasible analytical method, we developed and tested comprehensive software tools that are demonstrated herein. Furthermore, to gain additional analytical accuracy and reliability in the analysis we used genotyping of single nucleotide polymorphisms by mass spectrometry to unambiguously determine closely related strains that are difficult to distinguish by only relying on protein mass pattern detection.

Conclusions

With the method for bacterial analysis, we could identify fire blight pathogens from a variety of biological sources. The method can be used for a number of additional bacterial genera. Moreover, the mass spectrometry approach presented allows the integration of data from different biological levels such as the genome and the proteome.     

Cross-platform microarray data normalisation for regulatory network inference

Background

Inferring Gene Regulatory Networks (GRNs) from time course microarray data suffers from the dimensionality problem created by the short length of available time series compared to the large number of genes in the network. To overcome this, data integration from diverse sources is mandatory. Microarray data from different sources and platforms are publicly available, but integration is not straightforward, due to platform and experimental differences.

Methods

We analyse here different normalisation approaches for microarray data integration, in the context of reverse engineering of GRN quantitative models. We introduce two preprocessing approaches based on existing normalisation techniques and provide a comprehensive comparison of normalised datasets.

Conclusions

Results identify a method based on a combination of Loess normalisation and iterative K-means as best for time series normalisation for this problem.     

CIG-P: Circular Interaction Graph for Proteomics

Background

A typical affinity purification coupled to mass spectrometry (AP-MS) experiment includes the purification of a target protein (bait) using an antibody and subsequent mass spectrometry analysis of all proteins co-purifying with the bait (aka prey proteins). Like any other systems biology approach, AP-MS experiments generate a lot of data and visualization has been challenging, especially when integrating AP-MS experiments with orthogonal datasets.

Results

We present Circular Interaction Graph for Proteomics (CIG-P), which generates circular diagrams for visually appealing final representation of AP-MS data. Through a Java based GUI, the user inputs experimental and reference data as file in csv format. The resulting circular representation can be manipulated live within the GUI before exporting the diagram as vector graphic in pdf format. The strength of CIG-P is the ability to integrate orthogonal datasets with each other, e.g. affinity purification data of kinase PRPF4B in relation to the functional components of the spliceosome. Further, various AP-MS experiments can be compared to each other.

Conclusions

CIG-P aids to present AP-MS data to a wider audience and we envision that the tool finds other applications too, e.g. kinase – substrate relationships as a function of perturbation. CIG-P is available under: http://sourceforge.net/projects/cig-p/

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-344) contains supplementary material, which is available to authorized users.     

Identification of Rothia bacteria as gluten-degrading natural colonizers of the upper gastro-intestinal tract

Background

Gluten proteins, prominent constituents of barley, wheat and rye, cause celiac disease in genetically predisposed subjects. Gluten is notoriously difficult to digest by mammalian proteolytic enzymes and the protease-resistant domains contain multiple immunogenic epitopes. The aim of this study was to identify novel sources of gluten-digesting microbial enzymes from the upper gastro-intestinal tract with the potential to neutralize gluten epitopes.

Methodology/Principal Findings

Oral microorganisms with gluten-degrading capacity were obtained by a selective plating strategy using gluten agar. Microbial speciations were carried out by 16S rDNA gene sequencing. Enzyme activities were assessed using gliadin-derived enzymatic substrates, gliadins in solution, gliadin zymography, and 33-mer α-gliadin and 26-mer γ-gliadin immunogenic peptides. Fragments of the gliadin peptides were separated by RP-HPLC and structurally characterized by mass spectrometry. Strains with high activity towards gluten were typed as Rothia mucilaginosa and Rothia aeria. Gliadins (250 µg/ml) added to Rothia cell suspensions (OD₆₂₀ 1.2) were degraded by 50% after ∼30 min of incubation. Importantly, the 33-mer and 26-mer immunogenic peptides were also cleaved, primarily C-terminal to Xaa-Pro-Gln (XPQ) and Xaa-Pro-Tyr (XPY). The major gliadin-degrading enzymes produced by the Rothia strains were ∼70–75 kDa in size, and the enzyme expressed by Rothia aeria was active over a wide pH range (pH 3–10).

Conclusion/Significance

While the human digestive enzyme system lacks the capacity to cleave immunogenic gluten, such activities are naturally present in the oral microbial enzyme repertoire. The identified bacteria may be exploited for physiologic degradation of harmful gluten peptides.