In silico design and performance of peptide microarrays for breast cancer tumour-auto-antibody testing

The simplicity and potential of minimally invasive testing using sera from patients makes auto-antibody based biomarkers a very promising tool for use in cancer diagnostics. Protein microarrays have been used for the identification of such auto-antibody signatures. Because high throughput protein expression and purification is laborious, synthetic peptides might be a good alternative for microarray generation and multiplexed analyses. In this study, we designed 1185 antigenic peptides, deduced from proteins expressed by 642 cDNA expression clones found to be sero-reactive in both breast tumour patients and controls. The sero-reactive proteins and the corresponding peptides were used for the production of protein and peptide microarrays. Serum samples from females with benign and malignant breast tumours and healthy control sera (n=16 per group) were then analysed. Correct classification of the serum samples on peptide microarrays were 78% for discrimination of ‘malignant versus healthy controls’, 72% for ‘benign versus malignant’ and 94% for ‘benign versus controls’. On protein arrays, correct classification for these contrasts was 69%, 59% and 59%, respectively. The over-representation analysis of the classifiers derived from class prediction showed enrichment of genes associated with ribosomes, spliceosomes, endocytosis and the pentose phosphate pathway. Sequence analyses of the peptides with the highest sero-reactivity demonstrated enrichment of the zinc-finger domain. Peptides’ sero-reactivities were found negatively correlated with hydrophobicity and positively correlated with positive charge, high inter-residue protein contact energies and a secondary structure propensity bias. This study hints at the possibility of using in silico designed antigenic peptide microarrays as an alternative to protein microarrays for the improvement of tumour auto-antibody based diagnostics

Molecular mechanism of synergy between the antimicrobial peptides PGLa and magainin 2

PGLa and magainin 2 (MAG2) are amphiphilic α-helical membranolytic peptides from frog skin with known synergistic antimicrobial activity. By systematically mutating residues in the two peptides it was possible to identify the ones crucial for the synergy, as monitored by biological assays, fluorescence vesicle leakage, and solid-state 15N-NMR. Electrostatic interactions between anionic groups in MAG2 and cationic residues in PGLa enhance synergy but are not necessary for the synergistic effect. Instead, two Gly residues (7 and 11) in a so-called GxxxG motif in PGLa are necessary for synergy. Replacing either of them with Ala or another hydrophobic residue completely abolishes synergy according to all three methods used. The designer-made peptide MSI-103, which has a similar sequence as PGLa, shows no synergy with MAG2, but by introducing two Gly mutations it was possible to make it synergistic. A molecular model is proposed for the functionally active PGLa-MAG2 complex, consisting of a membrane-spanning antiparallel PGLa dimer that is stabilized by intimate Gly-Gly contacts, and where each PGLa monomer is in contact with one MAG2 molecule at its C-terminus

Pattern Recognition in Pulmonary Tuberculosis Defined by High Content Peptide Microarray Chip Analysis Representing 61 Proteins from M. tuberculosis

Background: Serum antibody-based target identification has been used to identify tumor-associated antigens (TAAs) for development of anti-cancer vaccines. A similar approach can be helpful to identify biologically relevant and clinically meaningful targets in M.tuberculosis (MTB) infection for diagnosis or TB vaccine development in clinically well defined populations. Method: We constructed a high-content peptide microarray with 61 M.tuberculosis proteins as linear 15 aa peptide stretches with 12 aa overlaps resulting in 7446 individual peptide epitopes. Antibody profiling was carried with serum from 34 individuals with active pulmonary TB and 35 healthy individuals in order to obtain an unbiased view of the MTB epitope pattern recognition pattern. Quality data extraction was performed, data sets were analyzed for significant differences and patterns predictive of TB+/2. Findings: Three distinct patterns of IgG reactivity were identified: 89/7446 peptides were differentially recognized (in 34/34 TB+ patients and in 35/35 healthy individuals) and are highly predictive of the division into TB+ and TB2, other targets were exclusively recognized in all patients with TB (e.g. sigmaF) but not in any of the healthy individuals, and a third peptide set was recognized exclusively in healthy individuals (35/35) but no in TB+ patients. The segregation between TB+ and TB2 does no

Building ProteomeTools based on a complete synthetic human proteome.

We describe ProteomeTools, a project building molecular and digital tools from the human proteome to facilitate biomedical research. Here we report the generation and multimodal liquid chromatography-tandem mass spectrometry analysis of \u3e330,000 synthetic tryptic peptides representing essentially all canonical human gene products, and we exemplify the utility of these data in several applications. The resource (available at http://www.proteometools.org) will be extended to \u3e1 million peptides, and all data will be shared with the community via ProteomicsDB and ProteomeXchange

Analysis of Clonal Type-Specific Antibody Reactions in Toxoplasma gondii Seropositive Humans from Germany by Peptide-Microarray

BACKGROUND: Different clonal types of Toxoplasma gondii are thought to be associated with distinct clinical manifestations of infections. Serotyping is a novel technique which may allow to determine the clonal type of T. gondii humans are infected with and to extend typing studies to larger populations which include infected but non-diseased individuals. METHODOLOGY: A peptide-microarray test for T. gondii serotyping was established with 54 previously published synthetic peptides, which mimic clonal type-specific epitopes. The test was applied to human sera (n = 174) collected from individuals with an acute T. gondii infection (n = 21), a latent T. gondii infection (n = 53) and from T. gondii-seropositive forest workers (n = 100). FINDINGS: The majority (n = 124; 71%) of all T. gondii seropositive human sera showed reactions against synthetic peptides with sequences specific for clonal type II (type II peptides). Type I and type III peptides were recognized by 42% (n = 73) or 16% (n = 28) of the human sera, respectively, while type II-III, type I-III or type I-II peptides were recognized by 49% (n = 85), 36% (n = 62) or 14% (n = 25) of the sera, respectively. Highest reaction intensities were observed with synthetic peptides mimicking type II-specific epitopes. A proportion of the sera (n = 22; 13%) showed no reaction with type-specific peptides. Individuals with acute toxoplasmosis reacted with a statistically significantly higher number of peptides as compared to individuals with latent T. gondii infection or seropositive forest workers. CONCLUSIONS: Type II-specific reactions were overrepresented and higher in intensity in the study population, which was in accord with genotyping studies on T. gondii oocysts previously conducted in the same area. There were also individuals with type I- or type III-specific reactions. Well-characterized reference sera and further specific peptide markers are needed to establish and to perform future serotyping approaches with higher resolution

Validation of peptide epitope microarray experiments and extraction of quality data

Abstract. Within the last decade, the development of antigen microarray slides has enabled the simultaneous measurement of serum reactivity to hundreds of peptides in a single biological sample. Despite this considerable scientific progress, many issues remain regarding the quality, analysis and interpretation of the data these slides produce. There is currently no accepted approach to guide data analysis, and researchers use a wide variety of statistical methods and software tools. We designed and implemented a laboratory experiment to assess the reliability and range of measurement of peptide microarray data, and present graphical and statistical procedures for pre-processing so that quality data can be extracted for addressing biological hypotheses

PKC-theta is a novel SC35 splicing factor regulator in response to T cell activation

Alternative splicing of nuclear pre-mRNA is essential for generating protein diversity and regulating gene expression. Whilst many immunologically relevant genes undergo alternative splicing, the role of regulated splicing in T cell immune responses is largely unexplored, and the signaling pathways and splicing factors that regulate alternative splicing in T cells are poorly defined. Here we show using a combination of Jurkat T cells, human primary T cells, and ex vivo naïve and effector virus-specific T cells isolated after influenza A virus infection that SC35 phosphorylation is induced in response to stimulatory signals. We show that SC35 co-localizes with RNA polymerase II in activated T cells and spatially overlaps with H3K27ac and H3K4me3, which mark transcriptionally active genes. Interestingly, SC35 remains coupled to the active histone marks in the absence of continuing stimulatory signals. We show for the first time that nuclear PKC-θ co-exists with SC35 in the context of the chromatin template and is a key regulator of SC35 in T cells, directly phosphorylating SC35 peptide residues at RRM and RS domains. Collectively, our findings suggest that nuclear PKC-θ is a novel regulator of the key splicing factor SC35 in T cells