Evolution of Cooperation Definition: Acts by one organism that benefit another (Not necessarily mutual) Cooperation at no cost

Cooperation without Cost Cross feeding – unidirectional – also called “Syntrophy” –one organism lives off by-products of another organism – can lead to mutualism (bidirectional) Important reducer of greenhouse gas emissions (90% of marine methane from marine sediments oxidized by AMO) Unable to culture in lab – could be obligate syntrophy Unclear which intermediates are exchanged Anaerobic methane oxidation (AOM) Sulfate Reducing Bacteria Methanotropic Archaea methane is oxidized with sulfate as the terminal electron acceptor: CH4 + SO42- → HCO3- + HS- + H2O Sulfide Oxidizing Bacteria

The Importance of Cooperation It is often more difficult to understand how cooperation evolves because it comes with a cost “Cooperation among individuals is necessary for evolutionary transitions to higher levels of biological organization. In such transitions, groups of individuals at one level (such as single cells) cooperate to form selective units at a higher level (such as multicellular organisms).” (Velicer & Yu, 2003)

Symbiosis MutualismParasitism Altruism** (*reciprocal mutualism) Spite** Any interaction of organisms living together Actor Recipient Cost Benefit (Barash, 1982; Lee, Molla, Cantor, Collins, 2010) *Sometimes mutualism with a time delay is mistaken for altruism (you scratch my back, I’ll scratch yours later) ** Not observed outside of humans?

What happens when cooperation is disrupted? Study cases where “cheaters” emerge

Costly Cooperation: Wrinkley Spreaders Cells cooperate by each producing a costly polysaccharide to form a biofilm Benefit: Increased oxygen exposure Benefit outweighs the cost Cheaters can emerge that stick to the biofilm, but contribute no polysaccharide! Benfit without suffering the cost – cheaters are more fit! Problem: Too many cheaters dilutes the polysaccharide and biofilm sinks. Cheaters are a common problem…

Costly Cooperation: Spore Forming Behavior (Kuner & Kaiser, 1982) Myxococcus xanthus: a social bacteria When hungry, M. Xanthus cells aggregate into fruiting bodies Only a small fraction of bacteria become spores, the rest are structural “Cheaters” emerge that do not contribute to fruiting body formation, but produce disproportionately large amounts of spores

Experimental Design: Compete cheaters vs. cooperators (cheaters cannot form fruiting bodies unless mixed with cooperators) -Create mixed cheater/cooperator populations – 3 different cheaters -Force populations to sporulate -Collect spores -Grow spores to form new population -Repeat 5-6 times (Fiegna & Velicer, 2003) Does cooperation ever work despite cheaters?

(Fiegna & Velicer, 2003) Cheaters can coexist with cooperators What was different? -This cheater had faster growth, but inferior sporulation -It never rose to high enough frequency to prevent entire population from forming a fruiting body -It could coexist with cooperators without causing population collapse Dashed = cheaterControl, both lines are cooperators

A “chicken game” (Fiegna & Velicer, 2003) Cheaters can cause population disruption When cheaters rise in frequency, population sporulation efficiency suffers Cheaters suffer more, and decrease disproportionately more than cooperators Cooperators restore sporulation efficiency It is safe for cheaters to rise again Dashed = cheater

(Fiegna & Velicer, 2003) Cheaters can cause population collapse Cheater rises to high frequency Sporulation produces few to zero spores Complete extinction or cheater self extinction Dashed = cheater Solid = cooperator

(Velicer & Yu, 2003) Cheaters learn to cooperate Experimental Design: -Plate cheaters deficient in pili production -Scrape section from edge of cheaters -Re-plate -Repeat 32 times Results: -All 8 cheaters became more mobile -Two were even better than WT -Used fibrils to swarm across plates -Fibril production is also costly WT cooperator Cheater Cooperator evolved from cheater Cooperator evolved from cheater

When is cooperation stable? Without considering defectors: Benefit (B) – Cost (C) > 0 With defectors (d) and cooperaters (c): B c – C c > B d What conditions could lead to cooperation? (maximize the benefits to cooperators while minimizing benefits to defectors?) Spatial distribution Kin selection Group Selection – Chuang et. al. 2009

Simpson’s Paradox Band Aid RemovalOpen Heart SurgeryTotal Overall 36/90 (40%) 7/10 (70%) 43/100 3/10 (30%) 54/90 (60%) 57/100 Dr. Nick Dr. Hibbert Winner per Category Dr. Hibbert Dr. Nick The winner in all sub sections may be the loser overall

Haystack Model Maynard Smith Organisms live in separate haystacks Once in a while, all leave their haystack at the same moment to mate They then divide into equal groups and go back to a random haystack v v v v v v v v v v v v v v v v v v v v v v v v v Cooperator v v v v v v

Haystack Model v v v v v v v v v v v v v Cooperator v Cheater v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v Cheaters emerge and do disproportionately well within each haystack (selection within haystacks leads to increase of cheaters) v v v v v v v v v v v v v v v v v v v v v v v v v v v v

Haystack Model v v v v v v v v v v v v v v v v v v v v v v v v v Cooperator v Cheater v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v Between matings, haystacks accumulate differences Some cheaters and cooperators are better than others v v v v v v v v v v v v v vv

Haystack Model v v v v v v v v v v Specific Cooperator from one haystack v Cheater v v v v v v v v v v v v v v v v v v v v v v v v v Too many cheaters causes population decline v v v v v v v v v v v v v v v v v v v v v vv v Cooperator

Haystack Model v v v v v v v v v v v v v Cooperator v Cheater v v v v v v v v v v v v v v v v v v v v v v v v v v v v v v When populations emerge and mate, the haystack with the most organisms “wins” by having the most individuals in each haystack Between group selection favors cooperators Between individual selection favors cheaters v v v v v v v v v v v v v v v v v v v v v v v v v v v v Specific Cooperator from one haystack v

The Prisoner’s Dilemma Prisoner Two: your accomplice Although cooperation leads to the best outcome for everyone, natural selection usually maximizes an individual’s benefits – not the group’s. (Turner and Chao, 1999) Give up your accomplice/accomplice keeps quiet: No prison time Keep quiet while your accomplice gives you up: Twenty years in jail Both talk: Ten years each Both quiet: 5 years each Prisoner One: You

Phage do not choose to cooperate Phage Ancestor = Φ6, a cooperator produces beneficial resource Derived = ΦH2, a cheater produces less, sequesters more Strategy: everyone should defect (Turner and Chao, 1999)

Escape from the Prisoner’s Dilemma However, sometimes phage can “Escape the prisoner’s dilemma” (under clonal selection) (Turner and Chao, 2003) In a low density population, everyone is related

(Sachs & Bull, 2005) Conflict Mediation Organisms go through cycles where either cooperation or selfishness is favored Experimental Design: Co-infection Obligate paired vertical transmission Production of independent bacteriaphage x50 Compete to be better infector But dual infection required for reproduction

(Sachs & Bull, 2005) Conflict Resolution Both phage packaged together to ensure double infection One genome shrunk to three genes