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Novel biomarkers of CNS pericytes
Abstracts
Introduction: Mitochondrial genome is constituted by a single, maternally inherited, circular chromosome of 16,569 base pairs, present in a variable number of copies inside each cell. Mutation accumulation determines a decrease in energy production that has been associated with neurodegenerative diseases like Alzheimer, Parkinson and Huntington syndrome but also with sarcopenia, AIDS progression and aging. Due to the lack of recombination, mutations initially characterizing ancestral sequences are inherited by their descendants, with the possible addition of personal variances. Clusters of samples sharing common mutations are defined as haplogroups. This inheritance pattern can be described using phylogenetic trees that, rooted to an ideal common ancestral sequence (mtMRCA), are able to detail all the occurred mutations as time went by. The most comprehensive and updated tree available in literature is PhyloTree. Haplogroup classification can be employed in many different contexts, from sample quality control to population and clinical genetics. Their role as disease-linked markers is under investigation and the number of sequences to be classified will increase in the near future, searching for subtle associations and retaining a sufficient statistical power in the meantime. Manual classification will not be sufficient, due to its long and error-prone nature. To address this problem we developed HaploFind, a Web Application able to efficiently classify mtDNA complete samples. Methods: HaploFind classifies mitochondrial sequences according to PhyloTree nomenclature, since it represent the de-facto standard in human phylogenetic studies. Mutations which define haplogroups have been weighted reflecting their conservation in annotated quality-checked mtDNA sequences, obtained from GenBank. To address the problem of stored sample quality we used sequences reported from PhyloTree and the ones referred in the database manually curated by Ian Logan (http://www.ianlogan.co.uk/). Each sequence in our dataset has been aligned against rCRS to identify its mutations and compare them, using PhyloTree as a guideline, to the variants characterizing the annotated haplogroups, obtaining a score proportional to their conservation. An additional parameter, the assignment threshold, is computed for each haplogroup, taking into consideration the entire pattern conservation. HaploFind algorithm has been integrated in a Web Application powered by Python Django Framework and MySQL database. Client–server architecture brings two benefits: users always work with the updated HaploFind version, and all the CPU-intensive work is performed on server side, allowing researchers with poor computational resources to access the service. Results: HaploFind algorithm relies on a weighted phylogenetic tree based on the statistical analysis of ~7800 mtDNA samples. A 1000 iteration cross validation has been used to check the algorithm performance, randomly subdividing the k available sequences in a training (k − 100 sequences) and testing (100 sequences) set at each iteration. The dataset composed only of complete sequences showed an error rate around 0.03%, while the vast majority of sequences were correctly (79.8%) or better (20%) determined. The dataset comprising also incomplete samples scored similarly, with a slightly lower percentage of correct assignments (79.1%). All tests were performed on a 2.3 GHz quad-core Intel Core i7 with 8 Gb of RAM. Using this machine, we were able to analyze 7803 samples in 730 s, a mean of 0.09 s/sequence (~40,000 sequence/h). Conclusions: HaploFind is an easy-to-update high-throughput pipeline for complete mtDNA sequences and haplogroup classification. Thanks to its ability to cope even with huge datasets, HaploFind will be helpful in the framework of small projects in need of rapidly and easily characterize new samples and even in more complex ones, where a fast classification method is required.
http://dx.doi.org/10.1016/j.exger.2013.05.018
687
Novel biomarkers of CNS pericytes J. Justa,b, K.R. Drasbeka, J. Randel Nyengaardc, L. Østergaarda, P. Kristensenb a Center of Functionally Integrative Neuroscience (CFIN), Aarhus University Hospital, Denmark b Department of Molecular Biology and Genetics (MBG), Aarhus University, Denmark c Stereology and EM Laboratory, MIND Centre, Aarhus University, Denmark Roguet, first described pericytes in 1873, as a population of cells surrounding the capillaries. They are found on almost all capillaries, with the retina and brain being the regions with the largest population of these cells. Pericytes play a key role in the development and maintenance of the cerebral microcirculation. However, the exact roles of pericytes in the neurovascular unit in the adult brain are elusive because of the lack of specific biomarkers. In spite of this elusiveness, more and more results indicate that pericyte malfunction or loss is involved in the vascular-mediated neuronal degenerative damage seen in e.g. ageing and Alzheimer's disease in consequence of a malfunctioning cerebral microcirculation. The aim of this project is centred on the in vitro development of recombinant antibodies against CNS pericytes using novel methods of selection and screening. This will provide novel biomarkers of CNS pericytes, which will be applied in imaging studies, where recombinant antibodies will be developed into imaging probes to study localization and functionality of the CNS pericyte. Keywords: CNS pericyte, The vascular system, Blood flow, Neurodegenerative diseases, Ageing, Phage display. http://dx.doi.org/10.1016/j.exger.2013.05.019
Optimization of a proteomic approach for evidencing and identifying oxidized proteins during human skeletal muscle aging S. Santosa, M. Baraibara, M. Le Boulcha, L. Larssonb, B. Frigueta a Université Pierre et Marie Curie-Paris 6, UR4, IFR83, Laboratoire de Biologie Cellulaire du Vieillissement, Paris, France b Uppsala University, Department of Clinical Neurophysiology, Uppsala, Sweden Sarcopenia is associated with skeletal muscle atrophy (loss in muscle mass) and weakness (loss in muscle force) during aging, leading to a progressive loss of mobility and quality of life. However, the cellular and molecular mechanisms involved are not well understood. In different tissues and organ systems, aging is characterized by the accumulation of oxidatively modified proteins. Although increased oxidative stress has been reported in skeletal muscle aging, the proteins targeted by oxidation have not been characterized. The identification of these proteins would shed light into the possible molecular pathways involved in sarcopenia. Immunodetection of carbonylated proteins after two dimensional electrophoresis separation (2D Oxyblot) has proved to be an efficient proteomic approach for evidencing oxidized proteins. In addition, this approach is compatible with mass spectrometry allowing the identification of the selected protein spots. In order to provide new insights into the molecular mechanisms implicated in human skeletal muscle aging, we optimized a high resolution 2D Oxyblot to evidence the oxidative status of proteins in biopsies from young and old healthy donors. Protein extraction was optimized by varying chaotropic agents as well as detergents in the lysis buffer. We found increased yields of extracted proteins when incorporating urea and thiourea along with the detergent chaps. Importantly, the protein recovery index was close to 10% (w/w) in relation with the biopsies wet weight. In order to improve the resolution of the protein spots during 2D electrophoresis, two different strategies were assayed: i)
Introduction: Mitochondrial genome is constituted by a single, maternally inherited, circular chromosome of 16,569 base pairs, present in a variable number of copies inside each cell. Mutation accumulation determines a decrease in energy production that has been associated with neurodegenerative diseases like Alzheimer, Parkinson and Huntington syndrome but also with sarcopenia, AIDS progression and aging. Due to the lack of recombination, mutations initially characterizing ancestral sequences are inherited by their descendants, with the possible addition of personal variances. Clusters of samples sharing common mutations are defined as haplogroups. This inheritance pattern can be described using phylogenetic trees that, rooted to an ideal common ancestral sequence (mtMRCA), are able to detail all the occurred mutations as time went by. The most comprehensive and updated tree available in literature is PhyloTree. Haplogroup classification can be employed in many different contexts, from sample quality control to population and clinical genetics. Their role as disease-linked markers is under investigation and the number of sequences to be classified will increase in the near future, searching for subtle associations and retaining a sufficient statistical power in the meantime. Manual classification will not be sufficient, due to its long and error-prone nature. To address this problem we developed HaploFind, a Web Application able to efficiently classify mtDNA complete samples. Methods: HaploFind classifies mitochondrial sequences according to PhyloTree nomenclature, since it represent the de-facto standard in human phylogenetic studies. Mutations which define haplogroups have been weighted reflecting their conservation in annotated quality-checked mtDNA sequences, obtained from GenBank. To address the problem of stored sample quality we used sequences reported from PhyloTree and the ones referred in the database manually curated by Ian Logan (http://www.ianlogan.co.uk/). Each sequence in our dataset has been aligned against rCRS to identify its mutations and compare them, using PhyloTree as a guideline, to the variants characterizing the annotated haplogroups, obtaining a score proportional to their conservation. An additional parameter, the assignment threshold, is computed for each haplogroup, taking into consideration the entire pattern conservation. HaploFind algorithm has been integrated in a Web Application powered by Python Django Framework and MySQL database. Client–server architecture brings two benefits: users always work with the updated HaploFind version, and all the CPU-intensive work is performed on server side, allowing researchers with poor computational resources to access the service. Results: HaploFind algorithm relies on a weighted phylogenetic tree based on the statistical analysis of ~7800 mtDNA samples. A 1000 iteration cross validation has been used to check the algorithm performance, randomly subdividing the k available sequences in a training (k − 100 sequences) and testing (100 sequences) set at each iteration. The dataset composed only of complete sequences showed an error rate around 0.03%, while the vast majority of sequences were correctly (79.8%) or better (20%) determined. The dataset comprising also incomplete samples scored similarly, with a slightly lower percentage of correct assignments (79.1%). All tests were performed on a 2.3 GHz quad-core Intel Core i7 with 8 Gb of RAM. Using this machine, we were able to analyze 7803 samples in 730 s, a mean of 0.09 s/sequence (~40,000 sequence/h). Conclusions: HaploFind is an easy-to-update high-throughput pipeline for complete mtDNA sequences and haplogroup classification. Thanks to its ability to cope even with huge datasets, HaploFind will be helpful in the framework of small projects in need of rapidly and easily characterize new samples and even in more complex ones, where a fast classification method is required.
http://dx.doi.org/10.1016/j.exger.2013.05.018
687
Novel biomarkers of CNS pericytes J. Justa,b, K.R. Drasbeka, J. Randel Nyengaardc, L. Østergaarda, P. Kristensenb a Center of Functionally Integrative Neuroscience (CFIN), Aarhus University Hospital, Denmark b Department of Molecular Biology and Genetics (MBG), Aarhus University, Denmark c Stereology and EM Laboratory, MIND Centre, Aarhus University, Denmark Roguet, first described pericytes in 1873, as a population of cells surrounding the capillaries. They are found on almost all capillaries, with the retina and brain being the regions with the largest population of these cells. Pericytes play a key role in the development and maintenance of the cerebral microcirculation. However, the exact roles of pericytes in the neurovascular unit in the adult brain are elusive because of the lack of specific biomarkers. In spite of this elusiveness, more and more results indicate that pericyte malfunction or loss is involved in the vascular-mediated neuronal degenerative damage seen in e.g. ageing and Alzheimer's disease in consequence of a malfunctioning cerebral microcirculation. The aim of this project is centred on the in vitro development of recombinant antibodies against CNS pericytes using novel methods of selection and screening. This will provide novel biomarkers of CNS pericytes, which will be applied in imaging studies, where recombinant antibodies will be developed into imaging probes to study localization and functionality of the CNS pericyte. Keywords: CNS pericyte, The vascular system, Blood flow, Neurodegenerative diseases, Ageing, Phage display. http://dx.doi.org/10.1016/j.exger.2013.05.019
Optimization of a proteomic approach for evidencing and identifying oxidized proteins during human skeletal muscle aging S. Santosa, M. Baraibara, M. Le Boulcha, L. Larssonb, B. Frigueta a Université Pierre et Marie Curie-Paris 6, UR4, IFR83, Laboratoire de Biologie Cellulaire du Vieillissement, Paris, France b Uppsala University, Department of Clinical Neurophysiology, Uppsala, Sweden Sarcopenia is associated with skeletal muscle atrophy (loss in muscle mass) and weakness (loss in muscle force) during aging, leading to a progressive loss of mobility and quality of life. However, the cellular and molecular mechanisms involved are not well understood. In different tissues and organ systems, aging is characterized by the accumulation of oxidatively modified proteins. Although increased oxidative stress has been reported in skeletal muscle aging, the proteins targeted by oxidation have not been characterized. The identification of these proteins would shed light into the possible molecular pathways involved in sarcopenia. Immunodetection of carbonylated proteins after two dimensional electrophoresis separation (2D Oxyblot) has proved to be an efficient proteomic approach for evidencing oxidized proteins. In addition, this approach is compatible with mass spectrometry allowing the identification of the selected protein spots. In order to provide new insights into the molecular mechanisms implicated in human skeletal muscle aging, we optimized a high resolution 2D Oxyblot to evidence the oxidative status of proteins in biopsies from young and old healthy donors. Protein extraction was optimized by varying chaotropic agents as well as detergents in the lysis buffer. We found increased yields of extracted proteins when incorporating urea and thiourea along with the detergent chaps. Importantly, the protein recovery index was close to 10% (w/w) in relation with the biopsies wet weight. In order to improve the resolution of the protein spots during 2D electrophoresis, two different strategies were assayed: i)