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.

Publications

(since 2016)

2022

  • ProteasomeID: quantitative mapping of proteasome interactomes and substrates for in vitro and in vivo studies
    Bartolome A, Heiby* JC, Dau* T, Di Fraia D, Heinze I, Kirkpatrick JM, Ori A
    bioRxiv 2022, https://doi.org/10.1101/2022.08. * equal contribution
  • p53-mediated AKT and mTOR inhibition requires RFX7 and DDIT4 and depends on nutrient abundance.
    Coronel* L, Häckes* D, Schwab* K, Riege K, Hoffmann** S, Fischer** M
    Oncogene 2022, 41(7), 1063-9 * equal contribution, ** co-corresponding authors
  • Conserved exchange of paralog proteins during neuronal differentiation.
    Di Fraia D, Anitei M, Mackmull MT, Parca L, Behrendt L, Andres-Pons A, Gilmour D, Helmer Citterich M, Kaether C, Beck M, Ori A
    Life Sci Alliance 2022, 5(6)
  • Metabolic determination of cell fate through selective inheritance of mitochondria.
    Döhla J, Kuuluvainen E, Gebert N, Amaral A, Englund JI, Gopalakrishnan S, Konovalova S, Nieminen AI, Salminen ES, Torregrosa Muñumer R, Ahlqvist K, Yang Y, Bui H, Otonkoski T, Käkelä R, Hietakangas V, Tyynismaa H, Ori A, Katajisto P
    Nat Cell Biol 2022, 24(2), 148-54
  • The natural compound atraric acid suppresses androgen-regulated neo-angiogenesis of castration-resistant prostate cancer through angiopoietin 2.
    Ehsani M, Bartsch S, Rasa SMM, Dittmann J, Pungsrinont T, Neubert L, Huettner SS, Kotolloshi R, Schindler K, Ahmad A, Mosig AS, Adam L, Ori A, Neri F, Berndt A, Grimm MO, Baniahmad A
    Oncogene 2022, 41(23), 3263-77
  • Synthesizing genome regulation data with vote-counting.
    Fischer M, Hoffmann S
    Trends Genet 2022 (epub ahead of print)
  • Coordinating gene expression during the cell cycle.
    Fischer M, Schade AE, Branigan TB, Müller GA, DeCaprio JA
    Trends Biochem Sci 2022 (epub ahead of print)
  • TargetGeneReg 2.0: a comprehensive web-atlas for p53, p63, and cell cycle-dependent gene regulation.
    Fischer* M, Schwarz R, Riege K, DeCaprio JA, Hoffmann S
    NAR Cancer 2022, 4(1), zcac009 * corresponding author
  • Glycation Alters the Fatty Acid Binding Capacity of Human Serum Albumin.
    Henning C, Stübner C, Arabi SH, Reichenwallner J, Hinderberger D, Fiedler R, Girndt M, Di Sanzo S, Ori A, Glomb MA
    J Agric Food Chem 2022, 70(9), 3033-46
  • LINC00892 Is an lncRNA Induced by T Cell Activation and Expressed by Follicular Lymphoma-Resident T Helper Cells.
    Iaccarino I, Mourtada F, Reinke S, Patil P, Doose G, Monaco G, Hoffmann S, Siebert R, Klapper W
    Noncoding RNA 2022, 8(3)