Thread by @AlexBlokhuis

A question that is undoubtedly even more interesting than abiogenesis itself: how can we come up with a scientific methodology to actually figure the whole thing out? In @CyrJeancolas work, a case is made for thresholds. Let me mention some qualities there that set a standard :

https://twitter.com/CyrJeancolas/status/1329837931100561409

The work is not confined to one of the origins of life clusters (link.springer.com/article/10.100…). Rather, it fills its toolbox with thresholds from different scenarios. Practical, as many seem relevant for all past, present and future scenarios.

But it goes one step further. We want all the thresholds we can get, even if we need to find them elsewhere. For example, the stochastic yield catastrophe by @PhysOfLifeLMU is relatively unknown in the origins community, but seems more general than some canonical thresholds.

If you want to read more about that one the paper is here: elifesciences.org/articles/51020. It's interesting how a lot of extra thresholds are hidden in a more rigorous mathematical description.

E.g. if you look at the microscopic description of many of the situations where one typically uses a deterministic replicator equation, you'll often find that it's not quite applicable and plagued by new catastrophes and thresholds.

I really hope this part gets picked up: "From
this point, thorough theoretical investigations of the
parameter space and regimes help elaborating hypotheses
testable with synthetic experiments in chemistry, systems
chemistry, physical-chemistry, soft matter physics, etc."

An illustrative tale that is mentioned concerns notions of an error catastrophe. The stochastic corrector model (roughly: cell division) suggested that compartments subject to group selection could render such a phenomenon somewhat less catastrophic.

In a related experiment, compartments were used that were transient (science.sciencemag.org/content/354/63…), and their contents mixed in a pool after selection. That may seem less powerfull than cell division with lineages. For negating the catastrophe, it turns out to be dramatically better.

My personal stance has been to abandon scenarios, to escape endless scenario-specific efforts rooted in assumptions we can no longer ignore. @CyrJeancolas provides a constructive, scenario-wide approach: studying the thresholds that unite all scenarios, and thereby refine them.

Studying those thresholds is rewarding more generally. They pop up outside origins (arguably every time you can draw a phase diagram). Rallying around a concerted effort to rigorously study thresholds may inadvertently solve all sorts of other open problems in science.

One last, more broader development I'd like to highlight is illustrated by the screencapped quote below (it's open access so you may prefer to just read it there). Increasingly, it is appreciated that plausibility is not the only tool in the shed, paradoxes are underappreciated.

Note that paradoxes gave us thermodynamics and general relativity and many results in classical physics. Used correctly, they have the power to provide the foundation of whole branches of science. In 2018 Benner made a provocative case for more paradoxes: doi.org/10.1038/s41467….

Whether we solve abiogenesis or not, constructive developments on new methodologies are on their way. I'm curious where that will take us.

Sidenote: to appreciate what's out there in the origins literature and understand where that comes from in a broader context, the bibliometric analysis by @Arsevu and @zehrataskin is required reading. That paper taught me more about origins than all its review papers combined.