The Seeding Story and Spawning Story have a different story to tell. The former begins with a consortium of sophisticated, complex cells while the latter begins with a simple self-replicating molecule able to co-opt from a huge assortment of potentially useful chemicals in the thick prebiotic broth. Does it really make sense to think such two radically different starting points cannot leave any traces that would help us distinguish between the two?
If only we had a time machine. We could send a robotic probe back into time to take samples from the prebiotic Earth at different points in ancient history and see what we get. If the Spawning Story was correct, our earliest probe samples would return a slew of organic building blocks. Set the timer for a few millions years later, and we’d pull out a variety of polymers in addition to the building blocks. Some time later, and we’d retrieve from self-replicating entities. Later yet, and a whole set of simple proto-cells would lay before our eyes. On the other hand, if the Seeding Story was correct, we’d probably retrieve something else. As with the Spawning Story, we might also get a soup of building blocks and perhaps even other more complex ingredients. But what would signal the truth of the Seeding Story is the retrieval of sophisticated, complex bacteria-like cells when our previous sampling from a slightly earlier time returned no hint of any cellular life. In essence, we’d detect a quantum leap indicative of a seeding event.
While we have no time machine, not all is lost. Evolution, by its nature, helps to preserve the past in the structure of its offspring. For example, the protein ubiquitin has nearly the same amino acid sequence in humans as it does in baker’s yeast. This tells us that the last common ancestor of humans and yeast likely had ubiquitin, sharing this same amino acid sequence. And since ubiquitin is intimately involved in the control of protein degradation in both yeast and humans, it stands to reason it was doing essentially the same thing in their common ancestor. From there, we move outward and look for other commonalities. For example, since ubiquitin essentially marks proteins for destruction, perhaps yeast and humans also share the same machine that actually degrades the marked proteins – the proteasome. And they do! So we can now infer that some ancient ancestor of humans and yeast, estimated to be living at least a billion years ago, possessed essentially the same sophisticated ubiquitin-proteasome degradation system. To help us decide whether the Seeding Story has any support, we’d need to trace our evolutionary steps even further back in time, to the point where the first true cells appeared on the Earth. The closest we can come is to infer the essential nature of the last universal common ancestor (LUCA), since this is the cell type that resides at very base of the evolutionary tree.
Was it complex or was it simple? Was is sophisticated or was it sloppy? The Spawning Story really offers no guidance here, as it can explain either one. That is, if LUCA was sophisticated and complex, we simply postulate a long history of evolution, involving simpler and sloppier entities, prior to LUCA. The Seeding Story, on the other hand, takes a risk. A simple and sloppy LUCA does not fit if the original ancestors of all living cells were themselves sophisticated and complex. Thus, while the Spawning Story can easily accommodate either a complex or simple LUCA, the Seeding Story predicts a complex ancestor.
So how do we hunt down LUCA? We start by considering the basic cell types that permeate the Earth and then we start comparing. After all, just as a comparison of yeast and human proteins gives us insight into the ancestor of yeast and humans, so too would a comparison of all the most different types of cells known to exist help us estimate what the founding cells looked like. Modern cell and molecular biology have uncovered the fact that all of the immense biological diversity that covers this planet is built from only three basic cells types that form three domains of life: Eukarya, Bacteria, and Archaea (the latter two are considered prokaryotes, since they lack a nucleus).
The relationship between these three domains is illustrated in the phylogenetic tree as shown in the following figure:
To trace our steps back to LUCA, we simply take a comparative approach and look for all the shared features that are common among these three domains. Features shared by all the domains are then explained as features that already existed in LUCA and were thus passed on as LUCA gave rise to the three basic cell types. We then simply count up the shared features, consider the functions involved, and then contemplate what it all means in terms of the cell biology that likely existed as part of LUCA.
However, a significant caveat is in order. This common comparative approach is really the application of the least common denominator. I have previously proposed that it is unlikely that the planet would have been seeded with a clonal population of a single cell type, as some element of diversity would have been more likely to enhance the success rate of the seeding event (see Planting the Seeds and Successful Seeding). In other words, the Seeding Story predicts that there never was a last universal common ancestor. What was seeded was a set of common ancestors. The least common denominator approach would thus vastly underestimate the complexity of these cells.
There are other reasons to expect the least common denominator approach to underestimate the complexity of LUCA. First, multiple genome studies have shown that it is very common for genes to be lost in various lineages over time. For example, consider the findings of this study:
Lineage-specific gene loss, to a large extent, accounts for the differences in gene repertoires between genomes, particularly among eukaryotes. We derived a parsimonious scenario ofgene losses for eukaryotic orthologous groups (KOGs) from seven complete eukaryotic genomes. The scenario involves substantial gene loss in fungi, nematodes, and insects. Based on this evolutionary scenario and estimates of the divergence times between major eukaryotic phyla, we introduce a numerical measure, the propensity for gene loss (PGL). We explore the connection among the propensity of a gene to be lost in evolution (PGL value), protein sequence divergence, the effect of gene knockout on fitness, the number of protein-protein interactions, and expression level for the genes in KOGs. Significant correlations between PGL and each of these variables were detected. Genes that have a lower propensity to be lost in eukaryotic evolution accumulate fewer substitutions in their protein sequences and tend to be essential for the organism viability, tend to be highly expressed, and have many interaction partners. The dependence between PGL and gene dispensability and interactivity is much stronger than that for sequence evolution rate. Thus, propensity of a gene to be lost during evolution seems to be a direct reflection of its biological importance.
Given information, front-loaded to evolve something akin to metazoa, might not be essential to unicellular life, we might expect such front-loaded information to be vulnerable to such gene loss. Second, as of today, there are not many eukaryotic genomes sequenced and there are only a small number of protozoan genomes sequenced. Thus, genes that may truly exist among some eukaryotic lineages might be missed because of this limited sampling.
On the other hand, other factors might cause us to overestimate the complexity. For example, if certain features were front-loaded, they might have evolved independently, meaning that a shared feature need not trace back to an ancestral state. Furthermore, there is the phenomenon of lateral gene transfer, where genes from one cells type can be passed to another cell type, much as modern day genetic engineers put foreign DNA in bacteria. Such lateral gene transfer has been a major force in evolution.
Since the least common denominator can both lead to underestimating and overestimating things, we’ll assume these concerns balance each other out and employ it simply as a rough guide. Although LUCA is probably an imaginary creature, our attempt to find him will help us uncover what is shared by the three basic cell designs. So the hunt for LUCA may turn out to be a very useful endeaver.
Are ya ready to go on a hunt?