Towards stable diagnostic setups in clinical proteomics: Absolute quantitation of peptide biomarkers using MALDI‐TOF‐MS

In routine clinical diagnostics, peptide biomarkers are most commonly quantified using immunological techniques but these methods often lack sensitivity and/or specificity. Hence, quantitative mass spectrometry detection is desirable as an alternative diagnostic tool. To date, quantitative mass spectrometry is mostly based on ESI‐MS coupled to LC, requiring highly sophisticated instrumentation and knowledge and is time consuming and expensive. In contrast, MALDI‐TOF‐MS is a very simple, sensitive and rapid method for the detection of peptide biomarkers. However, the infeasibility of absolute quantification has been a tremendous handicap to the use of MS in stable clinical diagnostics. Here, we describe the development of a technical platform based on ClinProt particles and heavy‐isotope internal peptide standards for the fast and reliable preparation of samples. This combines the advantages of MALDI‐TOF as a read‐out system with absolute quantitation of peptide biomarkers. As a proof‐of‐concept, this platform was successfully employed for the absolute determination of the concentration of the highly abundant serum peptide des‐Ala‐Fibrinopeptide A in 45 serum samples from healthy donors. Such technology essentially contributes to the development of a stable MALDI‐TOF‐MS‐based clinical assay.     

Hemoglobin depletion from red blood cell cytosol reveals new proteins in 2-D gel-based proteomics study

Proteomics studies to identify proteins in the erythrocyte cytosol have been largely affected by the huge abundance of hemoglobin (Hb), which masks the detection of other proteins in the 2-D gel-based separation. We have depleted Hb effectively from erythrocyte cytosol using cation exchange chromatography and have detected more than 600 protein spots in the Hb depleted hemolysate using 2-DE. We have so far identified 59 proteins in the Hb-depleted cytosol of normal erythrocytes, including 10 proteins not identified before.     

Unraveling the complexity of neurodegeneration in brains of subjects with Down syndrome: Insights from proteomics

Down syndrome (DS) is one of the most common genetic causes of intellectual disability characterized by multiple pathological phenotypes, among which neurodegeneration is a key feature. The neuropathology of DS is complex and likely results from impaired mitochondrial function, increased oxidative stress, and altered proteostasis. After the age of 40 years, many (most) DS individuals develop a type of dementia that closely resembles that of Alzheimer's disease with deposition of senile plaques and neurofibrillary tangles. A number of studies demonstrated that increased oxidative damage, accumulation of damaged/misfolded protein aggregates, and dysfunction of intracellular degradative systems are critical events in the neurodegenerative processes. This review summarizes the current knowledge that demonstrates a “chronic” condition of oxidative stress in DS pointing to the putative molecular pathways that could contribute to accelerate cognition and memory decline. Proteomics and redox proteomics studies are powerful tools to unravel the complexity of DS phenotypes, by allowing to identifying protein expression changes and oxidative PTMs that are proved to be detrimental for protein function. It is reasonable to suggest that changes in the cellular redox status in DS neurons, early from the fetal period, could provide a fertile environment upon which increased aging favors neurodegeneration. Thus, after a critical age, DS neuropathology can be considered a human model of early Alzheimer's disease and could contribute to understanding the overlapping mechanisms that lead from normal aging to development of dementia.     

Proteomic analysis of pericardial effusion: Characteristics of tuberculosis-related proteins

The aim of this study has been designed to identify the tuberculosis (TB)-related proteins in pericardial effusion by proteomic approaches. TB is one of the major infectious diseases causing pericardial effusion. This study details protein profiles in pericardial effusion from three TB patients and three heart failure patients. Pericardial effusions were analyzed using 2-DE combined with the nano-HPLC-ESI-MS/MS. Eleven protein spots with differential expression in pericardial effusion were identified between the two groups of TB and heart failure patients (the control group). Seven protein spots were upregulated and four were downregulated. The composition of the pericardial effusion proteome may reflect the pathophysiological conditions affecting the progression of tuberculous pericarditis. The proteins in the tuberculous pericardial effusion with differential expression may serve as new and direct indicators of drug treatment. A possible conclusion is indicated that fibrinogen may play an important role for fibrin assembly in tuberculous pericardial effusion.     

Considerations for powering a clinical proteomics study: Normal variability in the human plasma proteome

Proteomics is increasingly being applied to the human plasma proteome to identify biomarkers of disease for use in non‐invasive assays. 2‐D DIGE, simultaneously analysing thousands of protein spots quantitatively and maintaining protein isoform information, is one technique adopted. Sufficient numbers of samples must be analysed to achieve statistical power; however, few reported studies have analysed inherent variability in the plasma proteome by 2‐D DIGE to allow power calculations. This study analysed plasma from 60 healthy volunteers by 2‐D DIGE. Two samples were taken, 7 days apart, allowing estimation of sensitivity of detection of differences in spot intensity between two groups using either a longitudinal (paired) or non‐paired design. Parameters for differences were: two‐fold normalised volume change, α of 0.05 and power of 0.8. Using groups of 20 samples, alterations in 1742 spots could be detected with longitudinal sampling, and in 1206 between non‐paired groups. Interbatch gel variability was small relative to the detection parameters, indicating robustness and reproducibility of 2‐D DIGE for analysing large sample sets. In summary, 20 samples can allow detection of a large number of proteomic alterations by 2‐D DIGE in human plasma, the sensitivity of detecting differences was greatly improved by longitudinal sampling and the technology was robust across batches.     

Thymosin β4 is differentially expressed in the cerebrospinal fluid of Creutzfeldt‐Jakob disease patients: a MALDI‐TOF MS protein profiling study

MALDI‐TOF protein profiling analysis permits the detection of peptides and small proteins in complex protein mixtures with great accuracy. We applied this analysis to cerebrospinal fluid (CSF) from 15 patients affected by Creutzfeldt‐Jakob disease (CJD). We compared the levels of the normalized ion signals of 11 sporadic and 4 genetic CJD forms with those from ten healthy control subjects and eight non‐CJD relapsing‐remitting multiple sclerosis patients. In so doing, we detected 61 differentially expressed ion signals in CJD samples compared to controls. Among the 61 signals, 3 signals had significantly increased levels with high statistical significance (p <0.0001) and were located at 3238.3 m/z, 4963.7 m/z, and 8565.3 m/z. We characterized the 5.0 and 8.6 kDa proteins as thymosin β4 N‐acetylated and free ubiquitin, respectively, while the 3.2‐kDa peptide remained uncharacterized. Although elevated ubiquitin levels have previously been described in CJD, we have demonstrated for the first time the involvement of thymosin β4 in a neurodegenerative disease. To support the validity of thymosin β4 levels obtained by MALDI‐TOF analysis, an independent enzyme immunoassay analysis was performed. Moreover, a validation cohort consisting of CSF from three CJD patients, five healthy subjects, and six non‐CJD relapsing‐remitting multiple sclerosis patients was analyzed in a similar way, yielding superimposable results. We propose that thymosin β4 is a potential new candidate marker for the ante mortem diagnosis of CJD disease.     

ArchiDNA: An interactive system for creating 2D and 3D conceptual drawings in architectural design

We present an interactive system called ArchiDNA for creating 2D and 3D conceptual drawings in architectural design. We developed a novel principle of shape generation called match-and-attach by analyzing drawing styles of a contemporary architect, Peter Eisenman. The process consists of user interaction techniques and a set of rules that decide how one or more shapes attach to another shape. One key ingredient of our process is a unique concept for the interactive semi-automatic shape generation that uses the combination of algorithmic rules of a computer and designers’ manual inputs. These techniques enable designers to use CAD software in the early stages of architectural designs to explore conceptual building forms. ArchiDNA dynamically responds to drawing inputs, configures 2D shapes, and converts them to 3D shapes in a similar style. We intend to complement existing CAD software and computational drawing pipelines for intuitive 2D and 3D conceptual drawing creation.     

Collaborative simulation and scientific big data analysis: Illustration for sustainability in natural hazards management and chemical process engineering

Classical approaches for remote visualization and collaboration used in Computer-Aided Design and Engineering (CAD/E) applications are no longer appropriate due to the increasing amount of data generated, especially using standard networks. We introduce a lightweight and computing platform for scientific simulation, collaboration in engineering, 3D visualization and big data management. This ICT based platform provides scientists an “easy-to-integrate” generic tool, thus enabling worldwide collaboration and remote processing for any kind of data. The service-oriented architecture is based on the cloud computing paradigm and relies on standard internet technologies to be efficient on a large panel of networks and clients. In this paper, we discuss the need of innovations in (i) pre and post processing visualization services, (ii) 3D large scientific data set scalable compression and transmission methods, (iii) collaborative virtual environments, and (iv) collaboration in multi-domains of CAD/E. We propose our open platform for collaborative simulation and scientific big data analysis. This platform is now available as an open project with all core components licensed under LGPL V2.1. We provide two examples of usage of the platform in CAD/E for sustainability engineering from one academic application and one industrial case study. Firstly, we consider chemical process engineering showing the development of a domain specific service. With the rise of global warming issues and with growing importance granted to sustainable development, chemical process engineering has turned to think more and more environmentally. Indeed, the chemical engineer has now taken into account not only the engineering and economic criteria of the process, but also its environmental and social performances. Secondly, an example of natural hazards management illustrates the efficiency of our approach for remote collaboration that involves big data exchange and analysis between distant locations. Finally we underline the platform benefits and we open our platform through next activities in innovation techniques and inventive design.