Early Microbial Evolution

Project Information

eMicrobevol

Grant agreement ID: 666053

DOI

10.3030/666053

Project closed

EC signature date 11 September 2015

Start date 1 November 2015

End date 31 October 2020

Funded under

• EXCELLENT SCIENCE - European Research Council (ERC)

Total cost

€ 2 393 447,50

EU contribution

€ 2 393 447,50

Coordinated by

HEINRICH-HEINE-UNIVERSITAET DUESSELDORF
Germany

Periodic Reporting for period 4 - eMicrobevol (Early Microbial Evolution)

Reporting period: 2020-05-01 to 2020-10-31

Summary of the context and overall objectives of the project

What is at the focus of this project about early microbial evolution?
The goals of the project are to obtain a better understanding of early microbial evolution. In the foreground are general questions like: Which lineages of microbes are the most ancient, how and where did the first cells on Earth live, how did complex cells (eukaryotes) arise from simple cells (prokaryotes)? Those questions need to be placed in the context of Earth history. The Earth is 4.5 billion years old. The first signs of life on Earth appear almost 4 billion years ago, while the first life on land appeared less than 500 million years ago. That means that the first 3.5 billion years of evolution took place in aquatic environments. The first eukaryotes appeared about 1.2 billion years ago. Thus, the first 2.8 billion years of life's history was among microbes, which have very little to offer in the way of a fossil record. Isotope data from ancient sediments can tell us about what kinds of processes were going on, but not which lineages of modern microbes (if any) were involved. Our richest source of information about microbial evolution is genomes.

Why is this project important for society?
It is part of human nature to want to know more about our biological past — in our human lineage, in our animal ancestors and back to the origin of the first living things. Every human society has a narrative about how everything began, where the living things in the world we know came from, where the first humans came from and, roughly, how that links to our current direct experience in modern times. Humans generally want to know about the past. That appears to be important, and it is a main reason why we are doing this research. The basic motivation is scientific curiosity, humans are generally curious beings. It is difficult to predict where findings from basic research might have applications.

What are the overall objectives?
Just like the Earth records its own history, genomes record the history of life. But reading the history of life in microbial genomes is complicated, almost irremediably so, by lateral gene transfer (LGT). LGT is a pervasive factor in prokaryotic genome evolution and it was important at the origin of mitochondria, the powerhouses of eukaryotic cells, that were present in the eukaryote common ancestor. If we want to read early microbial history from genomes, we need to find ways to deal with LGT in such a way as to separate wheat (true evolutionary signals) from chaff (spurious evolutionary signals) in genome data. That means that we need to find ways to identify genes that have been affected by LGT, and the simplest way to do that, we contend, is to make trees from all genes — a new frontier that has not been extensively explored outside the ongoing projects in our group.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

We have developed methods that allow us to make trees from all genes and to extract information from those trees using computers so that specific questions can be posed to sets of thousands (or hundreds of thousands) of trees. We have developed robust tests to discriminate vertical from lateral modes of inheritance for specified biological groups.

In the early phase of the project, our findings uncovered novel insights into eukaryote origins [1], into early microbial evolution [2,4] and into the nature of the first cells [3].

[1] Ku C, Nelson-Sathi S, Roettger M, Sousa FL, Lockhart PJ, Bryant D, Hazkani-Covo E, McInerney JO, Landan G, Martin WF: Endosymbiotic origin and differential loss of eukaryotic genes. Nature 524:427–432 (2015). citations: 226

[2] Nelson-Sathi S, Sousa FL, Roettger M, Lozada-Chávez N, Thiergart T, Janssen A, Bryant D, Landan G, Schönheit P, Siebers B, McInerney JO, Martin WF: Origins of major archaeal clades correspond to gene acquisitions from bacteria. Nature 517:77–80 (2015). citations: 199

[3] Weiss MC, Sousa FL, Mrnjavac N, Neukirchen S, Roettger M, Nelson-Sathi S, Martin WF: The physiology and habitat of the last universal common ancestor. Nature Microbiology 1:16116 (2016). citations: 494

[4] C Ku, S Nelson-Sathi, M Roettger, S Garg, E Hazkani-Covo, WF Martin: Endosymbiotic gene transfer from prokaryotic pangenomes: Inherited chimerism in eukaryotes. Proc Natl Acad Sci USA 112, 10139-10146 (2016). citations: 97

These four papers provided proof of principle that we can extract important information from genomes by studying the evolution of all genes and have been cited over 1000 times. Newer papers that I would consider highlights from the project are

[5] Martin WF: Older than genes: The acetyl-CoA pathway and origins. Frontiers Microbiol. 11:817 (2020). citations: 4

[6] Fan L, Wu D, Goremykin VV, Xiao J, Xu Y, Garg S, Zhang C, Martin WF, Zhu R: Mitochondria branch within alphaproteobacteria. Nature Ecol. Evol. 4:1213–1219. citations: 7

[7] Preiner M, Igarashi K, Muchowska KB, Yu M, Varma SJ, Kleinermanns K, Nobu MK, Kamagata Y, Tüysüz H, Moran J, Martin WF: A hydrogen dependent geochemical analogue of primordial carbon and energy metabolism. Nature Ecol. Evol. 4:534–542 (2020). citations: 22

[8] Xavier JC, Hordijk W, Kauffman S, Steel M, Martin WF: Autocatalytic chemical networks at the origin of metabolism. Proc. Roy. Soc. Lond. B. 287: 20192377 (2020). citations: 22

[9] Zimorski V, Mentel M, Tielens AGM, Martin WF: Energy metabolism in anaerobic eukaryotes and Earth's late oxygenation. Free Radicals Biol. Med. 140:279–294 (2019). citations: 22

[10] Martin WF, Bryant DA, Beatty JT: A physiological perspective on the origin and evolution of photosynthesis. FEMS Microbiol Rev 42: 205-231 (2018). citations: 58

[11] Weiss M, Preiner M, Xavier JC, Zimorski V, Martin WF: The last universal common ancestor between ancient Earth chemistry and the onset of genetics. PLoS Genetics 14: e1007518 (2018). citations: 47

[11] Martin WF, Tielens AGM, Mentel M, Garg SG, Gould SB: The physiology of phagocytosis in the context of mitochondrial origin. Microbiol Mol Biol Rev 81:e00008-17 (2017) citations: 64

[12] Gould SB, Garg S, Martin WF: Bacterial vesicle secretion and the evolutionary origin of the eukaryotic endomembrane system. Trends Microbiol. 24:525–534 (2016). citations: 105

[13] Brueckner J, Martin WF: Bacterial genes outnumber archaeal genes in eukaryotic genomes. Genome Biol. Evol. 12:282–292 (2020). citations: 9

[14] Nagies FSP, Brueckner J, Tria FDK, Martin WF: A spectrum of verticality across genes.PLoS Genetics. 16:e1009200 (2020). citations: 0 (my most recent paper, it is significant)


Over the 60 month funding period, eMicrobevol has generated 58 publications that have been cited >2500 times to date (Google Scholar; >1400 IS), avg. 44 citations per paper, demonstrating a commitment to productivity and ability to have impact on the field.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

We have found ways to make trees from all genes and to extract information from those trees using computers so that specific questions can be posed to sets of thousands (or hundreds of thousands) of trees. We have developed tests to determine whether two sets of trees are drawn from the same distribution by comparting their sets of splits, also for the case that the trees have overlapping but non-identical leaf sets. This has proved very useful in discriminating vertical from lateral modes of inheritance for specified biological groups. Our approach to analyze all genes is finding considerable resonance in the literature.

An autocatalytic network in primiordial metabolism

Mitochondrial origin in a prokaryotic host

Evolution of anaerobes and the plastid

The overall chemical reaction of a primitive cell

A geochemical analogue of primordial metabolism

LUCA reconstructed from genome data

Distribution of taxa in eukaryote–prokaryote clusters

Archaeal gene acquisition network