AbSciCon day 1

Jennifer Pentz, Dinah Davison, and Cristian Solari enjoying a glass of wine.

Jennifer Pentz, Dinah Davison, and Cristian Solari enjoying a glass of wine.

I’m in Chicago for the biennial Astrobiology Science Conference (AbSciCon). This is always (well, it’s my second time) a fun one, with topics ranging from origins of life to proposed interplanetary missions. I took the train from Whitefish, Montana, which is a bit of an adventure in itself.

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Pierrick Bourrat responds

[I invited Pierrick Bourrat to respond to my two posts about his new paper and to comments to those posts. He kindly agreed, and he provided the following guest post, which I have edited only for formatting.]

First of all, I would like to thank Matthew Herron for his interest in my work and his invitation to respond to his posts. Also, I would like to thank Rick Michod and Deborah Shelton for their comments.

I will respond to several issues pointed out both in the posts and the comments.

About the usefulness of the export of fitness view of ETI: I agree that it is a useful way of thinking about it, as long as it is used as a heuristic. This means that I am not inclined to think that building models with the assumption that the fitness of a cell would have been 0 had it been in an environment with not social partners will be able to explain in some deep sense ETIs (and even more so the origin of fitness at some level). In his comment to Matthew’s first post, Rick Michod claims that I somehow confuse realized fitness from a more counterfactual notion of fitness.  Well, to be honest, I do not see how one could simulate (I do not mean ‘explain’) the evolution of a process if the variables in the model do not correspond to realized properties of the system. If I want to model a particular phenomenon, I ought to use variables and parameters that represent the target system and clearly, at least for me, this counterfactual notion of fitness does not represent any properties the cells have because they always have social partners. It is common to use expected rather than realized fitness in models, but this assumption is justified when we can assume that population are large and the environment is overall not fluctuating too much. With the counterfactual notion of fitness, aside from being useful for explaining the ETIs, I fail to see how it could be successfully integrated in models (by successfully, I mean how it could represent meaningfully the target system).

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Expression and form: Arash Kianianmomeni on gene regulation

Kianianmomeni Figure 1

Figure 1 from Kianianmomeni 2015. Gene regulatory mechanisms behind the evolution of multicellularity. Model illustrating the role of gene regulatory mechanisms in the evolution of multicellular Volvox from a Chlamydomonas-like ancestor.

Arash Kianianmomeni’s latest paper in Communicative & Integrative Biology addresses the possible roles of gene regulation and alternative splicing in the evolution of multicellularity and cellular differentiation (Kianianmomeni, A. 2015. Potential impact of gene regulatory mechanisms on the evolution of multicellularity in the volvocine algae. Commun. Integr. Biol., 37–41. doi 10.1080/19420889.2015.1017175). The article is an ‘Addendum’ to a 2014 study by Kianianmomeni and colleagues in BMC Genomics. Communicative & Integrative Biology often invites authors to write these addenda after they have published a (usually high impact) paper elsewhere, providing authors the opportunity to publish material that was not included in the original paper due to space limitations or because it was opinionated or speculative. I may address the BMC Genomics article in a future post, but right now there is more new volvocine research than I have time to write about (it should be an exciting Volvox meeting this summer!).

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Pierrick Bourrat on levels, time, and fitness, part 2: collective fitness

Last week, I posted some thoughts on Pierrick Bourrat’s new paper in Philosophy and Theory in Biology, focusing on his criticism of Rick Michod’s ‘export of fitness’ framework. This week, I’ll take a look at the second of Bourrat’s criticisms, regarding the transition from MLS1 to MLS2, as first defined by Damuth & Heisler, during a transition in individuality.
MLS1 and MLS2 refer to two different versions of MultiLevel Selection. As Bourrat describes it (and this is pretty much in line with other authors), fitness in MLS1 is defined in terms of the number of particles (or lower-level units, or cells) produced, while in MLS2 the fitnesses of the particles and collectives (or cells and multicellular organisms) are measured in different units. Cell-level fitness (for example) is defined in terms of the number of daughter cells, organism-level fitness is based on the number of daughter organisms. (As with last week’s post, I’ll generally stick to cells and organisms, though the principles apply equally to any two adjacent levels.

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Pierrick Bourrat on levels, time, and fitness, part 1: zero fitness?

Pierrick Bourrat’s new paper in Philosophy and Theory in Biology criticizes aspects of the influential ‘export of fitness’ framework developed by Rick Michod and colleagues and extended by Samir Okasha (Bourrat, P. 2015. Levels, time and fitness in evolutionary transitions in individuality. Philos. Theory Biol., 7: e601. doi: 10.3998/ptb.6959004.0007.001). According to this view, an evolutionary transition in individuality, for example from unicellular to multicellular life, involves a transfer of fitness from the lower level units (e.g. cells) to the higher level unit (e.g. nascent multicellular organism). Fitness is defined as the product of viability and fecundity, and the emergence of a division of labor between reproductive (germ) and non-reproductive (somatic) units at the lower level exports fitness to the higher level. Full disclosure: Rick Michod was my Ph.D. co-advisor, and he has had a huge influence on my thinking about this topic.

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Pleodorina study featured on NAI website

My new paper in Evolutionary Ecology Research is currently featured on the NASA Astrobiology Institute website (“Algae Fitness and Multicellular Life“). This was the final chapter of my Ph.D. dissertation, and it describes an artificial selection experiment using Pleodorina starrii. The paper is co-authored by my Ph.D. advisor, Rick Michod, and two (then) undergraduates, Susma Ghimire and Conner Vinikoor.
Pleodorina starrii

A 32-celled colony of Pleodorina starrii with 12 somatic cells.

Pleodorina is considered “partially differentiated,” meaning that some of its cells are of the ancestral, undifferentiated type (like those of Eudorina) and some are differentiated as somatic cells. These somatic cells never grow much, and they never divide to form daughter colonies.

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