Subarea 5: Computational and Systems Biology of Aging
Subarea 5 focuses on the development of methods to analyse and understand complex biological systems. This work includes the design of computer algorithms and biostatistical approaches as well as the development of novel Omic strategies (i.e. genomics/epigenomics, transcriptomics, proteomics, and metabolomics) to study aging and aging-related diseases. According to the FLI, due to the Subarea's expertise in computational data analysis, it is deeply interconnected with all other Subareas. The Subarea hosts two critical core facilities (Life Science Computing, Proteomics) and provides consulting services in statistics. Furthermore, it organizes courses on data analysis and statistics.
The research is defined by five focus areas:
- Mapping extrinsic and intrinsic factors influencing stem cells during aging,
- Integration of spatiotemporal proteomics and transcriptomics data,
- Comprehensive evaluation of qualitative and quantitative expression changes,
- Identification and analysis of epigenomic alterations during aging and age-related diseases, and
- Network analysis of genomic, transcriptomic and epigenomic alterations during aging.
Research focus of Subarea 5.
The biology of aging can be viewed as a multilayered array of networks at the level of organs, cells, molecules, and genes. The FLI wants to meet this complexity by establishing the new Subarea on “Computational and Systems Biology of Aging”. The overall goal is to interconnect research at different scales, taking place in Subareas 1-4 of the Institute’s research program. The new group on Systems Biology will integrate data from networks at multiple scales and will thus point to mechanisms and interactions that would not be seen in unilayer approaches.
- Quantitation of Reactive Acyl-CoA Species Mediated Protein Acylation by HPLC-MS/MS.
Baldensperger T, Simone DS, Ori A, Glomb MA
Anal Chem 2019 (epub ahead of print)
- Cohesin-mediated NF-κB signaling limits hematopoietic stem cell self-renewal in aging and inflammation.
Chen Z, Amro EM, Becker F, Hölzer M, Rasa SMM, Njeru SN, Han B, Di Sanzo S, Chen Y, Tang D, Tao S, Haenold R, Groth M, Romanov VS, Kirkpatrick JM, Kraus JM, Kestler HA, Marz M, Ori A, Neri F, Morita** Y, Rudolph** KL
J Exp Med 2019, 216(1), 152-75 ** co-corresponding authors
- Comment on 'Naked mole-rat mortality rates defy Gompertzian laws by not increasing with age'.
Dammann* P, Scherag* A, Zak N, Szafranski K, Holtze S, Begall S, Burda H, Kestler HA, Hildebrandt T, Platzer M
Elife 2019, 8 * corresponding author
- Conservation and divergence of the p53 gene regulatory network between mice and humans.
Oncogene 2019, 38(21), 4095-109
- Profiling of gallbladder carcinoma reveals distinct miRNA profiles and activation of STAT1 by the tumor suppressive miRNA-145-5p.
Goeppert B, Truckenmueller F, Ori A, Fritz V, Albrecht T, Fraas A, Scherer D, Silos RG, Sticht C, Gretz N, Mehrabi A, Bewerunge-Hudler M, Pusch S, Bermejo JL, Dietrich P, Schirmacher P, Renner M, Roessler S
Sci Rep 2019, 9(1), 4796
- Nucleoporin Nup155 is part of the p53 network in liver cancer.
Holzer K, Ori A, Cooke A, Dauch D, Drucker E, Riemenschneider P, Andres-Pons A, DiGuilio AL, Mackmull MT, Baßler J, Roessler S, Breuhahn K, Zender L, Glavy JS, Dombrowski F, Hurt E, Schirmacher P, Beck M, Singer S
Nat Commun 2019, 10(1), 2147
- Reduced proteasome activity in the aging brain results in ribosome stoichiometry loss and aggregation.
Kelmer Sacramento* E, Kirkpatrick* JM, Mazzetto* M, Di Sanzo S, Caterino C, Sanguanini M, Papaevgeniou N, Lefaki M, Childs D, Bagnoli S, Terzibasi Tozzini E, Bartolome A, Romanov N, Baumgart M, Huber W, Chondrogianni N, Vendruscolo M, Cellerino** A, Ori** A
bioRxiv 2019, https://doi.org/10.1101/577478 * equal contribution, ** co-corresponding authors
- Genomic and transcriptomic changes complement each other in the pathogenesis of sporadic Burkitt lymphoma.
López C, Kleinheinz K, Aukema SM, Rohde M, Bernhart SH, Hübschmann D, Wagener R, Toprak UH, Raimondi F, Kreuz M, Waszak SM, Huang Z, Sieverling L, Paramasivam N, Seufert J, Sungalee S, Russell RB, Bausinger J, Kretzmer H, Ammerpohl O, Bergmann AK, Binder H, Borkhardt A, Brors B, Claviez A, Doose G, Feuerbach L, Haake A, Hansmann ML, Hoell J, Hummel M, Korbel JO, Lawerenz C, Lenze D, Radlwimmer B, Richter J, Rosenstiel P, Rosenwald A, Schilhabel MB, Stein H, Stilgenbauer S, Stadler PF, Szczepanowski M, Weniger MA, Zapatka M, Eils R, Lichter P, Loeffler M, Möller P, Trümper L, Klapper W, ICGC MMML-Seq Consortium, Hoffmann S, Küppers R, Burkhardt B, Schlesner M, Siebert R
Nat Commun 2019, 10(1), 1459
- Comparison of protein quantification in a complex background by DIA and TMT workflows with fixed instrument time.
Muntel* J, Kirkpatrick* J, Bruderer R, Huang T, Vitek O, Ori** A, Reiter** L
J Proteome Res 2019, 18(3), 1340-51 * equal contribution, ** co-senior authors
- Metastatic-niche labelling reveals parenchymal cells with stem features.
Ombrato L, Nolan E, Kurelac I, Mavousian A, Bridgeman VL, Heinze I, Chakravarty P, Horswell S, Gonzalez-Gualda E, Matacchione G, Weston A, Kirkpatrick J, Husain E, Speirs V, Collinson L, Ori A, Lee JH, Malanchi I
Nature 2019, 572(7771), 603-8