Phylogenetic Reconstruction Shows Independent Evolutionary Origins of Mitochondrial Transcription Factors from an Ancient Family of RNA Methyltransferase Proteins

A consensus view of the proteome of the last universal common ancestor

The availability of genomic and proteomic data from across the tree of life has made it possible to infer features of the genome and proteome of the last universal common ancestor (LUCA). A number of studies have done so, all using a unique set of methods and bioinformatics databases. Here, we compare predictions across eight such studies and measure both their agreement with one another and with the consensus predictions among them. We find that some LUCA genome studies show a strong agreement with the consensus predictions of the others, but that no individual study shares a high or even moderate degree of similarity with any other individual study. From these observations, we conclude that the consensus among studies provides a more accurate depiction of the core proteome of the LUCA and its functional repertoire. The set of consensus LUCA protein family predictions between all of these studies portrays a LUCA genome that, at minimum, encoded functions related to protein synthesis, amino acid metabolism, nucleotide metabolism, and the use of common, nucleotide-derived organic cofactors.

Scaling laws in enzyme function reveal a new kind of biochemical universality

Known examples of life all share the same core biochemistry going back to the last universal common ancestor (LUCA), but whether this feature is universal to other examples, including at the origin of life or alien life, is unknown. We show how a physics-inspired statistical approach identifies universal scaling laws across biochemical reactions that are not defined by common chemical components but instead, as macroscale patterns in the reaction functions used by life. The identified scaling relations can be used to predict statistical features of LUCA, and network analyses reveal some of the functional principles that underlie them. They are, therefore, prime candidates for developing new theory on the “laws of life” that might apply to all possible biochemistries.

All life on Earth is unified by its use of a shared set of component chemical compounds and reactions, providing a detailed model for universal biochemistry. However, this notion of universality is specific to known biochemistry and does not allow quantitative predictions about examples not yet observed. Here, we introduce a more generalizable concept of biochemical universality that is more akin to the kind of universality found in physics. Using annotated genomic datasets including an ensemble of 11,955 metagenomes, 1,282 archaea, 11,759 bacteria, and 200 eukaryotic taxa, we show how enzyme functions form universality classes with common scaling behavior in their relative abundances across the datasets. We verify that these scaling laws are not explained by the presence of compounds, reactions, and enzyme functions shared across known examples of life. We demonstrate how these scaling laws can be used as a tool for inferring properties of ancient life by comparing their predictions with a consensus model for the last universal common ancestor (LUCA). We also illustrate how network analyses shed light on the functional principles underlying the observed scaling behaviors. Together, our results establish the existence of a new kind of biochemical universality, independent of the details of life on Earth’s component chemistry, with implications for guiding our search for missing biochemical diversity on Earth or for biochemistries that might deviate from the exact chemical makeup of life as we know it, such as at the origins of life, in alien environments, or in the design of synthetic life.

The draft nuclear genome sequence and predicted mitochondrial proteome of Andalucia godoyi, a protist with the most gene-rich and bacteria-like mitochondrial genome

Background

Comparative analyses have indicated that the mitochondrion of the last eukaryotic common ancestor likely possessed all the key core structures and functions that are widely conserved throughout the domain Eucarya. To date, such studies have largely focused on animals, fungi, and land plants (primarily multicellular eukaryotes); relatively few mitochondrial proteomes from protists (primarily unicellular eukaryotic microbes) have been examined. To gauge the full extent of mitochondrial structural and functional complexity and to identify potential evolutionary trends in mitochondrial proteomes, more comprehensive explorations of phylogenetically diverse mitochondrial proteomes are required. In this regard, a key group is the jakobids, a clade of protists belonging to the eukaryotic supergroup Discoba, distinguished by having the most gene-rich and most bacteria-like mitochondrial genomes discovered to date.

Results

In this study, we assembled the draft nuclear genome sequence for the jakobid Andalucia godoyi and used a comprehensive in silico approach to infer the nucleus-encoded portion of the mitochondrial proteome of this protist, identifying 864 candidate mitochondrial proteins. The A. godoyi mitochondrial proteome has a complexity that parallels that of other eukaryotes, while exhibiting an unusually large number of ancestral features that have been lost particularly in opisthokont (animal and fungal) mitochondria. Notably, we find no evidence that the A. godoyi nuclear genome has or had a gene encoding a single-subunit, T3/T7 bacteriophage-like RNA polymerase, which functions as the mitochondrial transcriptase in all eukaryotes except the jakobids.

Conclusions

As genome and mitochondrial proteome data have become more widely available, a strikingly punctuate phylogenetic distribution of different mitochondrial components has been revealed, emphasizing that the pathways of mitochondrial proteome evolution are likely complex and lineage-specific. Unraveling this complexity will require comprehensive comparative analyses of mitochondrial proteomes from a phylogenetically broad range of eukaryotes, especially protists. The systematic in silico approach described here offers a valuable adjunct to direct proteomic analysis (e.g., via mass spectrometry), particularly in cases where the latter approach is constrained by sample limitation or other practical considerations.