Domain Organization of Long Signal Peptides of Single-Pass Integral Membrane Proteins Reveals Multiple Functional Capacity

Targeting signals direct proteins to their extra - or intracellular destination such as the plasma membrane or cellular organelles. Here we investigated the structure and function of exceptionally long signal peptides encompassing at least 40 amino acid residues. We discovered a two-domain organization (“NtraC model”) in many long signals from vertebrate precursor proteins. Accordingly, long signal peptides may contain an N-terminal domain (N-domain) and a C-terminal domain (C-domain) with different signal or targeting capabilities, separable by a presumably turn-rich transition area (tra). Individual domain functions were probed by cellular targeting experiments with fusion proteins containing parts of the long signal peptide of human membrane protein shrew-1 and secreted alkaline phosphatase as a reporter protein. As predicted, the N-domain of the fusion protein alone was shown to act as a mitochondrial targeting signal, whereas the C-domain alone functions as an export signal. Selective disruption of the transition area in the signal peptide impairs the export efficiency of the reporter protein. Altogether, the results of cellular targeting studies provide a proof-of-principle for our NtraC model and highlight the particular functional importance of the predicted transition area, which critically affects the rate of protein export. In conclusion, the NtraC approach enables the systematic detection and prediction of cryptic targeting signals present in one coherent sequence, and provides a structurally motivated basis for decoding the functional complexity of long protein targeting signals

Omics and multi-omics analysis for the early identification and improved outcome of patients with psoriatic arthritis

The definitive diagnosis and early treatment of many immune-mediated inflammatory diseases (IMIDs) is hindered by variable and overlapping clinical manifestations. Psoriatic arthritis (PsA), which develops in ~30% of people with psoriasis, is a key example. This mixed-pattern IMID is apparent in entheseal and synovial musculoskeletal structures, but a definitive diagnosis often can only be made by clinical experts or when an extensive progressive disease state is apparent. As with other IMIDs, the detection of multimodal molecular biomarkers offers some hope for the early diagnosis of PsA and the initiation of effective management and treatment strategies. However, specific biomarkers are not yet available for PsA. The assessment of new markers by genomic and epigenomic profiling, or the analysis of blood and synovial fluid/tissue samples using proteomics, metabolomics and lipidomics, provides hope that complex molecular biomarker profiles could be developed to diagnose PsA. Importantly, the integration of these markers with high-throughput histology, imaging and standardized clinical assessment data provides an important opportunity to develop molecular profiles that could improve the diagnosis of PsA, predict its occurrence in cohorts of individuals with psoriasis, differentiate PsA from other IMIDs, and improve therapeutic responses. In this review, we consider the technologies that are currently deployed in the EU IMI2 project HIPPOCRATES to define biomarker profiles specific for PsA and discuss the advantages of combining multi-omics data to improve the outcome of PsA patients

Machine-learned association of next-generation sequencing-derived variants in thermosensitive ion channels genes with human thermal pain sensitivity phenotypes

Genetic association studies have shown their usefulness in assessing the role of ion channels in human thermal pain perception. We used machine learning to construct a complex phenotype from pain thresholds to thermal stimuli and associate it with the genetic information derived from the next-generation sequencing (NGS) of 15 ion channel genes which are involved in thermal perception, including ASIC1, ASIC2, ASIC3, ASIC4, TRPA1, TRPC1, TRPM2, TRPM3, TRPM4, TRPM5, TRPM8, TRPV1, TRPV2, TRPV3, and TRPV4. Phenotypic information was complete in 82 subjects and NGS genotypes were available in 67 subjects. A network of artificial neurons, implemented as emergent self-organizing maps, discovered two clusters characterized by high or low pain thresholds for heat and cold pain. A total of 1071 variants were discovered in the 15 ion channel genes. After feature selection, 80 genetic variants were retained for an association analysis based on machine learning. The measured performance of machine learning-mediated phenotype assignment based on this genetic information resulted in an area under the receiver operating characteristic curve of 77.2%, justifying a phenotype classification based on the genetic information. A further item categorization finally resulted in 38 genetic variants that contributed most to the phenotype assignment. Most of them (10) belonged to the TRPV3 gene, followed by TRPM3 (6). Therefore, the analysis successfully identified the particular importance of TRPV3 and TRPM3 for an average pain phenotype defined by the sensitivity to moderate thermal stimuli

Disagreement between two common biomarkers of global DNA methylation

Background: The quantification of global DNA methylation has been established in epigenetic screening. As more practicable alternatives to the HPLC-based gold standard, the methylation analysis of CpG islands in repeatable elements (LINE-1) and the luminometric methylation assay (LUMA) of overall 5-methylcytosine content in “CCGG” recognition sites are most widely used. Both methods are applied as virtually equivalent, despite the hints that their results only partly agree. This triggered the present agreement assessments. Results: Three different human cell types (cultured MCF7 and SHSY5Y cell lines treated with different chemical modulators of DNA methylation and whole blood drawn from pain patients and healthy volunteers) were submitted to the global DNA methylation assays employing LINE-1 or LUMA-based pyrosequencing measurements. The agreement between the two bioassays was assessed using generally accepted approaches to the statistics for laboratory method comparison studies. Although global DNA methylation levels measured by the two methods correlated, five different lines of statistical evidence consistently rejected the assumption of complete agreement. Specifically, a bias was observed between the two methods. In addition, both the magnitude and direction of bias were tissue-dependent. Interassay differences could be grouped based on Bayesian statistics, and these groups allowed in turn to re-identify the originating tissue. Conclusions: Although providing partly correlated measurements of DNA methylation, interchangeability of the quantitative results obtained with LINE-1 and LUMA was jeopardized by a consistent bias between the results. Moreover, the present analyses strongly indicate a tissue specificity of the differences between the two methods

Alternative exon usage creates novel transcript variants of tumor suppressor SHREW-1 gene with differential tissue expression profile

Shrew-1, also called AJAP1, is a transmembrane protein associated with E-cadherin-mediated adherence junctions and a putative tumor suppressor. Apart from its interaction with β-catenin and involvement in E-cadherin internalization, little structure or function information exists. Here we explored shrew-1 expression during postnatal differentiation of mammary gland as a model system. Immunohistological analyses with antibodies against either the extracellular or the cytoplasmic domains of shrew-1 consistently revealed the expression of full-length shrew-1 in myoepithelial cells, but only part of it in luminal cells. While shrew-1 localization remained unaltered in myoepithelial cells, nuclear localization occurred in luminal cells during lactation. Based on these observations, we identified two unknown shrew-1 transcript variants encoding N-terminally truncated proteins. The smallest shrew-1 protein lacks the extracellular domain and is most likely the only variant present in luminal cells. RNA analyses of human tissues confirmed that the novel transcript variants of shrew-1 exist in vivo and exhibit a differential tissue expression profile. We conclude that our findings are essential for the understanding and interpretation of future functional and interactome analyses of shrew-1 variants

High-Throughput Analysis of Global DNA Methylation Using Methyl-Sensitive Digestion.

DNA methylation is a major regulatory process of gene transcription, and aberrant DNA methylation is associated with various diseases including cancer. Many compounds have been reported to modify DNA methylation states. Despite increasing interest in the clinical application of drugs with epigenetic effects, and the use of diagnostic markers for genome-wide hypomethylation in cancer, large-scale screening systems to measure the effects of drugs on DNA methylation are limited. In this study, we improved the previously established fluorescence polarization-based global DNA methylation assay so that it is more suitable for application to human genomic DNA. Our methyl-sensitive fluorescence polarization (MSFP) assay was highly repeatable (inter-assay coefficient of variation = 1.5%) and accurate (r2 = 0.99). According to signal linearity, only 50-80 ng human genomic DNA per reaction was necessary for the 384-well format. MSFP is a simple, rapid approach as all biochemical reactions and final detection can be performed in one well in a 384-well plate without purification steps in less than 3.5 hours. Furthermore, we demonstrated a significant correlation between MSFP and the LINE-1 pyrosequencing assay, a widely used global DNA methylation assay. MSFP can be applied for the pre-screening of compounds that influence global DNA methylation states and also for the diagnosis of certain types of cancer

Emergent biomarker derived from next-generation sequencing to identify pain patients requiring uncommonly high opioid doses

Next-generation sequencing (NGS) provides unrestricted access to the genome, but it produces ‘big data’ exceeding in amount and complexity the classical analytical approaches. We introduce a bioinformatics-based classifying biomarker that uses emergent properties in genetics to separate pain patients requiring extremely high opioid doses from controls. Following precisely calculated selection of the 34 most informative markers in the OPRM1, OPRK1, OPRD1 and SIGMAR1 genes, pattern of genotypes belonging to either patient group could be derived using a k-nearest neighbor (kNN) classifier that provided a diagnostic accuracy of 80.6±4%. This outperformed alternative classifiers such as reportedly functional opioid receptor gene variants or complex biomarkers obtained via multiple regression or decision tree analysis. The accumulation of several genetic variants with only minor functional influences may result in a qualitative consequence affecting complex phenotypes, pointing at emergent properties in genetics

The workflow of the methyl-sensitive fluorescence polarization (MSFP) assay.

<p>Lambda (λ) and human genomic DNA are restricted by MspI (white) or by HpaII each alone or by a combination of HpaII and HpyCH4IV (grey) (Step 1). Subsequently, digested DNA with CpG overhangs at the 5' termini are terminally extended with fluorescence-labelled TAMRA-dCTP (C*, *C) (Step 2). TAMRA-dCTP incorporated into DNA is quantified by fluorescence polarization directly on the plate without additional purification procedures.</p

Comparison of the MSFP and LINE-1 assays.

<p>(A) Detection of DNA hypomethylation induced by Aza and DAC using the LINE-1 pyrosequencing assay. Three independent experiments were carried out and each data value (circle, triangle) and its median (bar) are shown in a Box-Whisker-Plot. (B) The MSFP assay data present different DNA methylation states as the ratio of the FP_HH values to the FP_M values. In contrast to the LINE-1 data, a decrease in global DNA methylation (here due to Aza or DAC), results in a higher FP_HH value and therefore, in a higher FP_HH/FP_M ratio. The DNA samples used for the MSFP assay were identical to those used for the LINE-1 assay. The data represent three independent experiments with technical triplicates and each data value (circle, triangle) and its median (bar) presented as a Box-Whisker-Plot. The statistical differences between untreated and treated groups (Aza or DAC) were determined using a Kruskall-Wallis test with Dunn’s multiple comparison test (*p<0.05, **p<0.01) for both assays. (C) Correlation between the MSFP and LINE-1 assays. Global DNA methylation level in THP-1 cells treated with DNMT inhibitors (n = 18) was determined using the MSFP and LINE-1 assays, and the reciprocal correlation between the methods determined by two-tailed Spearman’s rank correlation test (ρ = –0.80).</p