Single-cell atlas of the human brain vasculature across development, adulthood and disease.

A broad range of brain pathologies critically relies on the vasculature, and cerebrovascular disease is a leading cause of death worldwide. However, the cellular and molecular architecture of the human brain vasculature remains incompletely understood1. Here we performed single-cell RNA sequencing analysis of 606,380 freshly isolated endothelial cells, perivascular cells and other tissue-derived cells from 117 samples, from 68 human fetuses and adult patients to construct a molecular atlas of the developing fetal, adult control and diseased human brain vasculature. We identify extensive molecular heterogeneity of the vasculature of healthy fetal and adult human brains and across five vascular-dependent central nervous system (CNS) pathologies, including brain tumours and brain vascular malformations. We identify alteration of arteriovenous differentiation and reactivated fetal as well as conserved dysregulated genes and pathways in the diseased vasculature. Pathological endothelial cells display a loss of CNS-specific properties and reveal an upregulation of MHC class II molecules, indicating atypical features of CNS endothelial cells. Cell-cell interaction analyses predict substantial endothelial-to-perivascular cell ligand-receptor cross-talk, including immune-related and angiogenic pathways, thereby revealing a central role for the endothelium within brain neurovascular unit signalling networks. Our single-cell brain atlas provides insights into the molecular architecture and heterogeneity of the developing, adult/control and diseased human brain vasculature and serves as a powerful reference for future studies.

Multiomic ALS signatures highlight subclusters and sex differences suggesting the MAPK pathway as therapeutic target.

Amyotrophic lateral sclerosis (ALS) is a debilitating motor neuron disease and lacks effective disease-modifying treatments. This study utilizes a comprehensive multiomic approach to investigate the early and sex-specific molecular mechanisms underlying ALS. By analyzing the prefrontal cortex of 51 patients with sporadic ALS and 50 control subjects, alongside four transgenic mouse models (C9orf72-, SOD1-, TDP-43-, and FUS-ALS), we have uncovered significant molecular alterations associated with the disease. Here, we show that males exhibit more pronounced changes in molecular pathways compared to females. Our integrated analysis of transcriptomes, (phospho)proteomes, and miRNAomes also identified distinct ALS subclusters in humans, characterized by variations in immune response, extracellular matrix composition, mitochondrial function, and RNA processing. The molecular signatures of human subclusters were reflected in specific mouse models. Our study highlighted the mitogen-activated protein kinase (MAPK) pathway as an early disease mechanism. We further demonstrate that trametinib, a MAPK inhibitor, has potential therapeutic benefits in vitro and in vivo, particularly in females, suggesting a direction for developing targeted ALS treatments.

m-nitrobenzyl alcohol supercharging reagent enhances the chromatographic separation and the charging of disulfide bond linked and His-tag peptides.

The linkages of disulfide bond (DSB) play important roles in protein stability and activity. Mass spectrometry-based (MS-based) techniques become accepted tools for DSB analysis in the recent decade. In the bottom-up approach, after enzyme digestion, the neighbouring amino acids of cysteines have great impacts on the physicochemical properties of resulting disulfide bond peptides, determining their retention behaviour on liquid chromatography (LC) and their MS ionization efficiency. In this study, the addition of supercharging reagent in LC mobile phase was used to examine the impact of supercharging reagent on the charge states of disulfide-bond peptides. The results showed that 0.1 % m-nitrobenzyl alcohol (m-NBA) in LC mobile phase increased the sensitivity and charge states of DSB peptides from our model protein, equine Interleukin-5 (eIL5), as well as the resolution of reversed-phase chromatography. Notably, also the sensitivity of C-terminal peptide with His-tag significantly improved. Our findings highlight the effectiveness of employing m-NBA as a supercharging reagent when investigating disulfide-linked peptides and the C-terminal peptide with a His-tag through nano-liquid chromatography mass spectrometry.

Nucleolin promotes angiogenesis and endothelial metabolism along the oncofetal axis in the human brain vasculature.

Glioblastomas are among the deadliest human cancers and are highly vascularized. Angiogenesis is dynamic during brain development, almost quiescent in the adult brain but reactivated in vascular-dependent CNS pathologies, including brain tumors. The oncofetal axis describes the reactivation of fetal programs in tumors, but its relevance in endothelial and perivascular cells of the human brain vasculature in glial brain tumors is unexplored. Nucleolin is a regulator of cell proliferation and angiogenesis, but its roles in the brain vasculature remain unknown. Here, we studied the expression of Nucleolin in the neurovascular unit in human fetal brains, adult brains, and human gliomas in vivo as well as its effects on sprouting angiogenesis and endothelial metabolism in vitro. Nucleolin is highly expressed in endothelial and perivascular cells during brain development, downregulated in the adult brain, and upregulated in glioma. Moreover, Nucleolin expression correlated with glioma malignancy in vivo. In culture, siRNA-mediated Nucleolin knockdown reduced human brain endothelial cell (HCMEC) and HUVEC sprouting angiogenesis, proliferation, filopodia extension, and glucose metabolism. Furthermore, inhibition of Nucleolin with the aptamer AS1411 decreased brain endothelial cell proliferation in vitro. Mechanistically, Nucleolin knockdown in HCMECs and HUVECs uncovered regulation of angiogenesis involving VEGFR2 and of endothelial glycolysis. These findings identify Nucleolin as a neurodevelopmental factor reactivated in glioma that promotes sprouting angiogenesis and endothelial metabolism, characterizing Nucleolin as an oncofetal protein. Our findings have potential implications in the therapeutic targeting of glioma.

Translational Proteomics Analysis of Anthracycline-Induced Cardiotoxicity From Cardiac Microtissues to Human Heart Biopsies.

Anthracyclines, including doxorubicin, idarubicin, and epirubicin, are common antitumor drugs as well as well-known cardiotoxic agents. This study analyzed the proteomics alteration in cardiac tissues caused by these 3 anthracyclines analogs. The in vitro human cardiac microtissues were exposed to drugs in 2 weeks; the proteomic data were measured at 7 time points. The heart biopsy data were collected from heart failure patients, in which some patients underwent anthracycline treatment. The anthracyclines-affected proteins were separately identified in the in vitro and in vivo dataset using the WGCNA method. These proteins engage in different cellular pathways including translation, metabolism, mitochondrial function, muscle contraction, and signaling pathways. From proteins detected in 2 datasets, a protein-protein network was established with 4 hub proteins, and 7 weighted proteins from both cardiac microtissue and human biopsies data. These 11 proteins, which involve in mitochondrial functions and the NF-κB signaling pathway, could provide insights into the anthracycline toxic mechanism. Some of them, such as HSPA5, BAG3, and SH3BGRL, are cardiac therapy targets or cardiotoxicity biomarkers. Other proteins, such as ATP5F1B and EEF1D, showed similar responses in both the in vitro and in vivo data. This suggests that the in vitro outcomes could link to clinical phenomena in proteomic analysis.

Mapping Spatial Genetic Landscapes in Tissue Sections through Microscale Integration of Sampling Methodology into Genomic Workflows.

In cancer research, genomic profiles are often extracted from homogenized macrodissections of tissues, with the histological context lost and a large fraction of material underutilized. Pertinently, the spatial genomic landscape provides critical complementary information in deciphering disease heterogeneity and progression. Microscale sampling methods such as microdissection to obtain such information are often destructive to a sizeable fraction of the biopsy sample, thus showing limited multiplexability and adaptability to different assays. A modular microfluidic technology is here implemented to recover cells at the microscale from tumor tissue sections, with minimal disruption of unsampled areas and tailored to interface with genome profiling workflows, which is directed here toward evaluating intratumoral genomic heterogeneity. The integrated workflow-GeneScape-is used to evaluate heterogeneity in a metastatic mammary carcinoma, showing distinct single nucleotide variants and copy number variations in different tumor tissue regions, suggesting the polyclonal origin of the metastasis as well as development driven by multiple location-specific drivers.

A Natural Low Phytic Acid Finger Millet Accession Significantly Improves Iron Bioavailability in Indian Women.

Iron deficiency and anemia are common in low- and middle-income countries. This is due to a poor dietary iron density and low iron absorption resulting from the high inhibitory phytic acid content in cereal and millet-based diets. Here, we report that a naturally occurring low phytic acid finger millet accession (571 mg 100 g-1), stable across three growing seasons with normal iron content (3.6 mg 100 g-1), increases iron absorption by 3-folds in normal Indian women. The accessions differing in grain phytic acid content, GE 2358 (low), and GE1004 (high) were selected from a core collection of 623 accessions. Whole genome re-sequencing of the accessions revealed significant single nucleotide variations segregating them into distinct clades. A non-synonymous mutation in the EcABCC phytic acid transporter gene between high and low accessions could affect gene function and result in phytic acid differences. The highly sensitive dual stable-isotope erythrocyte incorporation method was adopted to assess the fractional iron absorption. The low phytic acid accession resulted in a significantly higher iron absorption compared with the high phytic acid accession (3.7 vs. 1.3%, p < 0.05). The low phytic acid accession could be effective in preventing iron deficiency in regions where finger millet is habitually eaten. With its low water requirement, finger millet leaves low environmental footprints and hence would be an excellent sustainable strategy to mitigate iron deficiency.

Gas-Phase Fragmentation of ADP-Ribosylated Peptides: Arginine-Specific Side-Chain Losses and Their Implication in Database Searches.

ADP-ribosylation is a reversible post-translational modification of proteins that has been linked to many biological processes. The identification of ADP-ribosylated proteins and particularly of their acceptor amino acids remains a major challenge. The attachment sites of the modification are difficult to localize by mass spectrometry (MS) because of the labile nature of the linkage and the complex fragmentation pattern of the ADP-ribose in MS/MS experiments. In this study we performed a comprehensive analysis of higher-energy collisional dissociation (HCD) spectra acquired from ADP-ribosylated peptides which were modified on arginine, serine, glutamic acid, aspartic acid, tyrosine, or lysine residues. In addition to the fragmentation of the peptide backbone, various cleavages of the ADP-ribosylated amino acid side chains were investigated. We focused on gas-phase fragmentations that were specific either to ADP-ribosylated arginine or to ADP-ribosylated serine and other O-linked ADP-ribosylations. The O-glycosidic linkage between ADP-ribose and serine, glutamic acid, or aspartic acid was the major cleavage site, making localization of these modification sites difficult. In contrast, the bond between ADP-ribose and arginine was relatively stable. The main cleavage site was the inner bond of the guanidine group, which resulted in the formation of ADP-ribosylated carbodiimide and of ornithine in place of modified arginine. Taking peptide fragment ions resulting from this specific cleavage into account, a considerably larger number of peptides containing ADP-ribosylated arginine were identified in database searches. Furthermore, the presence of diagnostic ions and of losses of fragments from peptide ions allowed us, in most cases, to distinguish between ADP-ribosylated arginine and serine residues.

Targeted Proteomics Guided by Label-free Quantitative Proteome Analysis in Saliva Reveal Transition Signatures from Health to Periodontal Disease.

Periodontal diseases are among the most prevalent worldwide, but largely silent, chronic diseases. They affect the tooth-supporting tissues with multiple ramifications on life quality. Their early diagnosis is still challenging, due to lack of appropriate molecular diagnostic methods. Saliva offers a non-invasively collectable reservoir of clinically relevant biomarkers, which, if utilized efficiently, could facilitate early diagnosis and monitoring of ongoing disease. Despite several novel protein markers being recently enlisted by discovery proteomics, their routine diagnostic application is hampered by the lack of validation platforms that allow for rapid, accurate and simultaneous quantification of multiple proteins in large cohorts. Here we carried out a pipeline of two proteomic platforms; firstly, we applied open ended label-free quantitative (LFQ) proteomics for discovery in saliva (n = 67, including individuals with health, gingivitis, and periodontitis), followed by selected-reaction monitoring (SRM)-targeted proteomics for validation in an independent cohort (n = 82). The LFQ platform led to the discovery of 119 proteins with at least 2-fold significant difference between health and disease. The 65 proteins chosen for the subsequent SRM platform included 50 functionally related proteins derived from the significantly enriched processes of the LFQ data, 11 from literature-mining, and four house-keeping ones. Among those, 60 were reproducibly quantifiable proteins (92% success rate), represented by a total of 143 peptides. Machine-learning modeling led to a narrowed-down panel of five proteins of high predictive value for periodontal diseases with maximum area under the receiver operating curve >0.97 (higher in disease: Matrix metalloproteinase-9, Ras-related protein-1, Actin-related protein 2/3 complex subunit 5; lower in disease: Clusterin, Deleted in Malignant Brain Tumors 1). This panel enriches the pool of credible clinical biomarker candidates for diagnostic assay development. Yet, the quantum leap brought into the field of periodontal diagnostics by this study is the application of the biomarker discovery-through-verification pipeline, which can be used for validation in further cohorts.

Multiple hybrid de novo genome assembly of finger millet, an orphan allotetraploid crop.

Finger millet (Eleusine coracana (L.) Gaertn) is an important crop for food security because of its tolerance to drought, which is expected to be exacerbated by global climate changes. Nevertheless, it is often classified as an orphan/underutilized crop because of the paucity of scientific attention. Among several small millets, finger millet is considered as an excellent source of essential nutrient elements, such as iron and zinc; hence, it has potential as an alternate coarse cereal. However, high-quality genome sequence data of finger millet are currently not available. One of the major problems encountered in the genome assembly of this species was its polyploidy, which hampers genome assembly compared with a diploid genome. To overcome this problem, we sequenced its genome using diverse technologies with sufficient coverage and assembled it via a novel multiple hybrid assembly workflow that combines next-generation with single-molecule sequencing, followed by whole-genome optical mapping using the Bionano Irys® system. The total number of scaffolds was 1,897 with an N50 length >2.6 Mb and detection of 96% of the universal single-copy orthologs. The majority of the homeologs were assembled separately. This indicates that the proposed workflow is applicable to the assembly of other allotetraploid genomes.

Prognostic value of cross-omics screening for kidney clear cell renal cancer survival.

BACKGROUND: Kidney renal clear cell carcinoma (KIRC) is a type of cancer that is resistant to chemotherapy and radiotherapy and has limited treatment possibilities. Large-scale molecular profiling of KIRC tumors offers a great potential to uncover the genetic and epigenetic changes underlying this disease and to improve the clinical management of KIRC patients. However, in practice the clinicians and researchers typically focus on single-platform molecular data or on a small set of genes. Using molecular and clinical data of over 500 patients, we have systematically studied which type of molecular data is the most informative in predicting the clinical outcome of KIRC patients, as a standalone platform and integrated with clinical data. RESULTS: We applied different computational approaches to preselect on survival-predictive genomic markers and evaluated the usability of mRNA/miRNA/protein expression data, copy number variation (CNV) data and DNA methylation data in predicting survival of KIRC patients. Our analyses show that expression and methylation data have statistically significant predictive powers compared to a random guess, but do not perform better than predictions on clinical data alone. However, the integration of molecular data with clinical variables resulted in improved predictions. We present a set of survival associated genomic loci that could potentially be employed as clinically useful biomarkers. CONCLUSIONS: Our study evaluates the survival prediction of different large-scale molecular data of KIRC patients and describes the prognostic relevance of such data over clinical-variable-only models. It also demonstrates the survival prognostic importance of methylation alterations in KIRC tumors and points to the potential of epigenetic modulators in KIRC treatment. REVIEWERS: An extended abstract of this research paper was selected for the CAMDA Satellite Meeting to ISMB 2015 by the CAMDA Programme Committee. The full research paper then underwent one round of Open Peer Review under a responsible CAMDA Programme Committee member, Djork-Arné Clevert, PhD (Bayer AG, Germany). Open Peer Review was provided by Martin Otava, PhD (Janssen Pharmaceutica, Belgium) and Hendrik Luuk, PhD (The Centre for Disease Models and Biomedical Imaging, University of Tartu, Estonia). The Reviewer comments section shows the full reviews and author responses.

Host-Associated Genomic Features of the Novel Uncultured Intracellular Pathogen Ca. Ichthyocystis Revealed by Direct Sequencing of Epitheliocysts.

Advances in single-cell and mini-metagenome sequencing have enabled important investigations into uncultured bacteria. In this study, we applied the mini-metagenome sequencing method to assemble genome drafts of the uncultured causative agents of epitheliocystis, an emerging infectious disease in the Mediterranean aquaculture species gilthead seabream. We sequenced multiple cyst samples and constructed 11 genome drafts from a novel beta-proteobacterial lineage, Candidatus Ichthyocystis. The draft genomes demonstrate features typical of pathogenic bacteria with an obligate intracellular lifestyle: a reduced genome of up to 2.6 Mb, reduced G + C content, and reduced metabolic capacity. Reconstruction of metabolic pathways reveals that Ca Ichthyocystis genomes lack all amino acid synthesis pathways, compelling them to scavenge from the fish host. All genomes encode type II, III, and IV secretion systems, a large repertoire of predicted effectors, and a type IV pilus. These are all considered to be virulence factors, required for adherence, invasion, and host manipulation. However, no evidence of lipopolysaccharide synthesis could be found. Beyond the core functions shared within the genus, alignments showed distinction into different species, characterized by alternative large gene families. These comprise up to a third of each genome, appear to have arisen through duplication and diversification, encode many effector proteins, and are seemingly critical for virulence. Thus, Ca Ichthyocystis represents a novel obligatory intracellular pathogenic beta-proteobacterial lineage. The methods used: mini-metagenome analysis and manual annotation, have generated important insights into the lifestyle and evolution of the novel, uncultured pathogens, elucidating many putative virulence factors including an unprecedented array of novel gene families.

Highly sensitive, non-invasive detection of colorectal cancer mutations using single molecule, third generation sequencing.

Colorectal cancer (CRC) represents one of the most prevalent and lethal malignant neoplasms and every individual of age 50 and above should undergo regular CRC screening. Currently, the most effective preventive screening procedure to detect adenomatous polyps, the precursors to CRC, is colonoscopy. Since every colorectal cancer starts as a polyp, detecting all polyps and removing them is crucial. By exactly doing that, colonoscopy reduces CRC incidence by 80%, however it is an invasive procedure that might have unpleasant and, in rare occasions, dangerous side effects. Despite numerous efforts over the past two decades, a non-invasive screening method for the general population with detection rates for adenomas and CRC similar to that of colonoscopy has not yet been established. Recent advances in next generation sequencing technologies have yet to be successfully applied to this problem, because the detection of rare mutations has been hindered by the systematic biases due to sequencing context and the base calling quality of NGS. We present the first study that applies the high read accuracy and depth of single molecule, real time, circular consensus sequencing (SMRT-CCS) to the detection of mutations in stool DNA in order to provide a non-invasive, sensitive and accurate test for CRC. In stool DNA isolated from patients diagnosed with adenocarcinoma, we are able to detect mutations at frequencies below 0.5% with no false positives. This approach establishes a foundation for a non-invasive, highly sensitive assay to screen the population for CRC and the early stage adenomas that lead to CRC.

iTRAQ-Based and Label-Free Proteomics Approaches for Studies of Human Adenovirus Infections.

Both isobaric tags for relative and absolute quantitation (iTRAQ) and label-free methods are widely used for quantitative proteomics. Here, we provide a detailed evaluation of these proteomics approaches based on large datasets from biological samples. iTRAQ-label-based and label-free quantitations were compared using protein lysate samples from noninfected human lung epithelial A549 cells and from cells infected for 24 h with human adenovirus type 3 or type 5. Either iTRAQ-label-based or label-free methods were used, and the resulting samples were analyzed by liquid chromatography (LC) and tandem mass spectrometry (MS/MS). To reduce a possible bias from quantitation software, we applied several software packages for each procedure. ProteinPilot and Scaffold Q+ software were used for iTRAQ-labeled samples, while Progenesis LC-MS and ProgenesisF-T2PQ/T3PQ were employed for label-free analyses. R (2) correlation coefficients correlated well between two software packages applied to the same datasets with values between 0.48 and 0.78 for iTRAQ-label-based quantitations and 0.5 and 0.86 for label-free quantitations. Analyses of label-free samples showed higher levels of protein up- or downregulation in comparison to iTRAQ-labeled samples. The concentration differences were further evaluated by Western blotting for four downregulated proteins. These data suggested that the label-free method was more accurate than the iTRAQ method.

PPINGUIN: Peptide Profiling Guided Identification of Proteins improves quantitation of iTRAQ ratios.

BACKGROUND: Recent development of novel technologies paved the way for quantitative proteomics. One of the most important among them is iTRAQ, employing isobaric tags for relative or absolute quantitation. Despite large progress in technology development, still many challenges remain for derivation and interpretation of quantitative results. One of these challenges is the consistent assignment of peptides to proteins. RESULTS: We have developed Peptide Profiling Guided Identification of Proteins (PPINGUIN), a statistical analysis workflow for iTRAQ data addressing the problem of ambiguous peptide quantitations. Motivated by the assumption that peptides uniquely derived from the same protein are correlated, our method employs clustering as a very early step in data processing prior to protein inference. Our method increases experimental reproducibility and decreases variability of quantitations of peptides assigned to the same protein. Giving further support to our method, application to a type 2 diabetes dataset identifies a list of protein candidates that is in very good agreement with previously performed transcriptomics meta analysis. Making use of quantitative properties of signal patterns identified, PPINGUIN can reveal new isoform candidates. CONCLUSIONS: Regarding the increasing importance of quantitative proteomics we think that this method will be useful in practical applications like model fitting or functional enrichment analysis. We recommend to use this method if quantitation is a major objective of research.

Myc-mediated repression of microRNA-34a promotes high-grade transformation of B-cell lymphoma by dysregulation of FoxP1.

Gastric marginal zone B-cell lymphoma of MALT type (MALT lymphoma) arises in the context of chronic inflammation induced by the bacterial pathogen Helicobacter pylori. Although generally considered an indolent disease, MALT lymphoma may transform to gastric diffuse large B-cell lymphoma (gDLBCL) through mechanisms that remain poorly understood. By comparing microRNA expression profiles of gastric MALT lymphoma and gDLBCL, we have identified a signature of 27 deregulated microRNAs(miRNAs) that share the characteristic of being transcriptionally repressed by Myc. Myc overexpression was consequently detected in 80% of gDLBCL but only 20% of MALT lymphomas spotted on a tissue microarray. A highly similar signature of Myc-repressed miRNAs was further detected in nodal DLBCL. Small interfering RNA-mediated knock-down of Myc blocked proliferation of DLBCL cell lines. Of the Myc-repressed miRNAs down-regulated in malignant lymphoma, miR-34a showed the strongest antiproliferative properties when overexpressed in DLBCL cells. We could further attribute miR-34a's tumor-suppressive effects to deregulation of its target FoxP1. FoxP1 overexpression was detected in gDLBCL but not in gastric MALT lymphoma; FoxP1 knock-down efficiently blocked DLBCL proliferation. In conclusion, our results elucidate a novel Myc- and FoxP1-dependent pathway of malignant transformation and suggest miR-34a replacement therapy as a promising strategy in lymphoma treatment.

Phosphoproteomic analysis reveals interconnected system-wide responses to perturbations of kinases and phosphatases in yeast.

The phosphorylation and dephosphorylation of proteins by kinases and phosphatases constitute an essential regulatory network in eukaryotic cells. This network supports the flow of information from sensors through signaling systems to effector molecules and ultimately drives the phenotype and function of cells, tissues, and organisms. Dysregulation of this process has severe consequences and is one of the main factors in the emergence and progression of diseases, including cancer. Thus, major efforts have been invested in developing specific inhibitors that modulate the activity of individual kinases or phosphatases; however, it has been difficult to assess how such pharmacological interventions would affect the cellular signaling network as a whole. Here, we used label-free, quantitative phosphoproteomics in a systematically perturbed model organism (Saccharomyces cerevisiae) to determine the relationships between 97 kinases, 27 phosphatases, and more than 1000 phosphoproteins. We identified 8814 regulated phosphorylation events, describing the first system-wide protein phosphorylation network in vivo. Our results show that, at steady state, inactivation of most kinases and phosphatases affected large parts of the phosphorylation-modulated signal transduction machinery-and not only the immediate downstream targets. The observed cellular growth phenotype was often well maintained despite the perturbations, arguing for considerable robustness in the system. Our results serve to constrain future models of cellular signaling and reinforce the idea that simple linear representations of signaling pathways might be insufficient for drug development and for describing organismal homeostasis.

An integrated proteomics approach for studying the molecular pathogenesis of Dupuytren's disease.

Dupuytren's disease (DD) is a fibromatosis characterized by non-malignant transformation of palmar fascia leading to permanent contraction of one or more fingers. Despite the extensive knowledge of its clinical pathogenesis, the aetiology of this disease remains obscure. In the present paper, we report for the first time on the proteomic profiling of diseased versus unaffected patient-matched palmar fasciae tissues from DD patients using two-dimensional gel electrophoresis coupled with mass spectrometry analysis. The herein identified proteins were then used to create the protein-protein interaction network (interactome). Such an integrated approach revealed the involvement of several different molecular processes related to DD progression, including extra- and intra-cellular signalling, oxidative stress, cytoskeletal changes, and alterations in cellular metabolism. In particular, autocrine regulation through ERBB-2 and IGF-1R receptors and the Akt signalling pathway have emerged as novel components of pro-survival signalling in Dupuytren's fibroblasts and thus might provide a basis for a new therapeutic strategy in Dupuytren's disease.

Differential antiproliferative mechanisms of novel derivative of benzimidazo[1,2-alpha]quinoline in colon cancer cells depending on their p53 status.

In the present article, we describe a mechanistic study of a novel derivative of N-amidino-substituted benzimidazo[1,2-alpha]quinoline in two human colorectal cancer cell lines differing in p53 gene status. We used a proteomic approach based on two-dimensional gel electrophoresis coupled with mass spectrometry to complement the results obtained by common molecular biology methods for analyzing cell proliferation, cell cycle, and apoptosis. Tested quinoline derivative inhibited colon cancer cell growth, whereby p53 gene status seemed to be critical for its differential response patterns. DNA damage and oxidative stress are likely to be the common triggers of molecular events underlying its antiproliferative effects. In HCT 116 (wild-type p53), this compound induced a p53-dependent response resulting in accumulation of the G(1)- and S-phase cells and induction of apoptosis via both caspase-3-dependent and caspase-independent pathways. Quinoline derivative triggered transient, p53-independent G(2)-M arrest in mutant p53 cells (SW620) and succeeding mitotic transition, whereby these cells underwent cell death probably due to aberrant mitosis (mitotic catastrophe). Proteomic approach used in this study proved to be a valuable tool for investigating cancer cell response to newly synthesized compound, as it specifically unraveled some molecular changes that would not have been otherwise detected (e.g., up-regulation of the p53-dependent chemotherapeutic response marker maspin in HCT 116 and impairment in ribosome biogenesis in SW620). Finally, antiproliferative effects of tested quinoline derivative on SW620 cells strongly support its possible role as an antimetastatic agent and encourage further in vivo studies on the chemotherapeutic potential of this compound against colorectal carcinoma.

The Mass Distance Fingerprint: a statistical framework for de novo detection of predominant modifications using high-accuracy mass spectrometry.

We describe a statistical measure, Mass Distance Fingerprint, for automatic de novo detection of predominant peptide mass distances, i.e., putative protein modifications. The method's focus is to globally detect mass differences, not to assign peptide sequences or modifications to individual spectra. The Mass Distance Fingerprint is calculated from high accuracy measured peptide masses. For the data sets used in this study, known mass differences are detected at electron mass accuracy or better. The proposed method is novel because it works independently of protein sequence databases and without any prior knowledge about modifications. Both modified and unmodified peptides have to be present in the sample to be detected. The method can be used for automated detection of chemical/post-translational modifications, quality control of experiments and labeling approaches, and to control the modification settings of protein identification tools. The algorithm is implemented as a web application and is distributed as open source software.