Aging in Single-celled Organisms: from Bacteria to the Whole Tree of Life/UliSteiner
Notes by user Uli Steiner (University of Southern Denmark) for Aging in Single-celled Organisms: from Bacteria to the Whole Tree of Life
1+ paragraphs on any combination of the following:
- Presentation highlights
- Open questions that came up
- How your perspective changed
- Impact on your own work
- e.g. the discussion on [A] that we are having reminds me of [B] conference/[C] initiative/[D] funding call-for-proposal/[E] research group
The discrepancies what aging entails seems to be related to the difference of fields and questions tackled. To me as an evolutionary biologist aging is simply the process of senescence, where senescence is the deterioration of function, or more precisely the change of function with age. This change does not need to be a directional decline. Function should be somewhat related to fitness, which explains that survival and reproduction are first targets to quantify aging, though all functional traits could be and should be considered for understanding senescence. However if fitness is the parameter that integrates the processes, it is evident that a cell within a multi-cellular organism has a different definition of fitness than a whole organism in itself, be it unicellular or multi-cellular.
The generalities as described by Chris are highly interesting and inspirational. I gained much inspiration on how senescence is unified across cells of different level of biological organization, but where, how, and why these universal patterns fall apart is something I would love to deepen discussing.
The differences in heterogeneity and homeostasis among cells that has been shown by Sri, where I was really puzzled how similar cells are and how such similarity could be maintained, and Bree's system where the heterogeneity is large, though spatially still well structured.
What are the most prominent markers that we should focus on? How can we measure these?
Reference material notes
- Here is [A] database on [B] that I pull data from to do [C] analysis that might be of interest to this group (insert link).
- Here is a free tool for calculating [ABC] (insert link)
- This painting/sculpture/forms of artwork is emblematic to our discussion on [X]!
- Schwartz et al. 2017 offers a review on [ABC] migration as relate to climatic factors (add the reference as well).
Here are some references that explain how mortality plateaus arise.
Steinsaltz and Evans shows how mortality plateaus arise through convergence to a quasi-stationary distribution.
Steinsaltz, D., and S. N. Evans. 2004. Markov mortality models: implications of quasistationarity and varying initial distributions. Theor. Popul. Biol. 65:319–337.
Weitz and Fraser illustrate how such mortality plateaus arise from damage accumulation and purging of damage at the population level through a random walk with drift model.
Weitz, J., and H. Fraser. 2001. Explaining mortality rate plateaus. Proc. Natl. Acad. Sci. USA 98:15383–15386.
Mathematical similarities among Gamma Gompertz models and damage accumulation models (LeBras type models). We used this mathematical similarity in our Evolution paper for parameter estimation of the model.
Yashin, A. I., J. W. Vaupel, and I. A. Iachine. 1994. A duality in aging: the equivalence of mortality models based on radically different concepts. Mech. Ageing Dev. 74:1–14.
The Evolution paper that has most of the data that I presented including data on growth, division rates, cell elongation, size at division etc.
Ulrich K Steiner, Adam Lenart, Ming Ni, Peipei Chen, Xiaohu Song, François Taddei, James W Vaupel, Ariel B Lindner. 2019.Two stochastic processes shape diverse senescence patterns in a single‐cell organismhttps://doi.org/10.1111/evo.13708
Here an asymmetric division model that has been inspired by the early e. coli aging work:
Evans, S. N., and D. Steinsaltz. 2007. Damage segregation at fissioning may increase growth rates: a superprocessmodel. Theor. Popul.Biol. 71:473–490
Quantifying mutation in singe e. coli cells by the mismatch repair system.
Lydia Robert, Jean Ollion, Jerome Robert, Xiaohu Song, Ivan Matic, Marina Elez. Mutation dynamics and fitness effects followed in single cells.
Vol. 359, Issue 6381, pp. 1283-1286