The nature of the last universal common ancestor (LUCA), its age and its impact on the Earth system have been the subject of vigorous debate across diverse disciplines, often based on disparate data and methods. Age estimates for LUCA are usually based on the fossil record, varying with every reinterpretation. The nature of LUCA’s metabolism has proven equally contentious, with some attributing all core metabolisms to LUCA, whereas others reconstruct a simpler life form dependent on geochemistry. Here we infer that LUCA lived ~4.2 Ga (4.09–4.33 Ga) through divergence time analysis of pre-LUCA gene duplicates, calibrated using microbial fossils and isotope records under a new cross-bracing implementation. Phylogenetic reconciliation suggests that LUCA had a genome of at least 2.5 Mb (2.49–2.99 Mb), encoding around 2,600 proteins, comparable to modern prokaryotes. Our results suggest LUCA was a prokaryote-grade anaerobic acetogen that possessed an early immune system. Although LUCA is sometimes perceived as living in isolation, we infer LUCA to have been part of an established ecological system. The metabolism of LUCA would have provided a niche for other microbial community members and hydrogen recycling by atmospheric photochemistry could have supported a modestly productive early ecosystem.

The CODEML program in the PAML package has been widely used to analyze protein-coding gene sequences to estimate the synonymous and nonsynonymous rates (d_S and d_N) and to detect positive Darwinian selection driving protein evolution. For users not familiar with molecular evolutionary analysis, the program is known to have a steep learning curve. Here, we provide a step-by-step protocol to illustrate the commonly used tests available in the program, including the branch models, the site models, and the branch-site models, which can be used to detect positive selection driving adaptive protein evolution affecting particular lineages of the species phylogeny, affecting a subset of amino acid residues in the protein, and affecting a subset of sites along prespecified lineages, respectively. A data set of the myxovirus (Mx) genes from ten mammal and two bird species is used as an example. We discuss a new feature in CODEML that allows users to perform positive selection tests for multiple genes for the same set of taxa, as is common in modern genome-sequencing projects. The PAML package is distributed at https://github.com/abacus-gene/paml under the GNU license, with support provided at its discussion site (https://groups.google.com/g/pamlsoftware). Data files used in this protocol are available at https://github.com/abacus-gene/paml-tutorial.

Microbial life has dominated Earth’s history but left a sparse fossil record, greatly hindering our understanding of evolution in deep time. However, bacterial metabolism has left signatures in the geochemical record, most conspicuously the Great Oxidation Event (GOE). We combine machine learning and phylogenetic reconciliation to infer ancestral bacterial transitions to aerobic lifestyles, linking them to the GOE to calibrate the bacterial time tree. Extant bacterial phyla trace their diversity to the Archaean and Proterozoic, and bacterial families prior to the Phanerozoic. We infer that most bacterial phyla were ancestrally anaerobic and adopted aerobic lifestyles after the GOE. However, in the cyanobacterial ancestor, aerobic metabolism likely predated the GOE, which may have facilitated the evolution of oxygenic photosynthesis.

The use of computational tools for virtual screening provides a cost-efficient approach to select starting points for drug development. We have developed VSpipe, a user-friendly semi-automated pipeline for structure-based virtual screening. VSpipe uses the existing tools AutoDock and OpenBabel together with software developed in-house, to create an end-to-end virtual screening workflow ranging from the preparation of receptor and ligands to the visualisation of results. VSpipe is efficient and flexible, allowing the users to make choices at different steps, and it is amenable to use in both local and cluster mode. We have validated VSpipe using the human protein tyrosine phosphatase PTP1B as a case study. Using a combination of blind and targeted docking VSpipe identified both new and known functional ligand binding sites. Assessment of different binding clusters using the ligand efficiency plots created by VSpipe, defined a drug-like chemical space for development of PTP1B inhibitors with potential applications to other PTPs. In this study, we show that VSpipe can be deployed to identify and compare different modes of inhibition thus guiding the selection of initial hits for drug discovery.

We investigate the evolution of microbial metabolisms from the last universal common ancestor to the extant biota through comparative phylogenomics, reconciling the evolution of the genes that underpin metabolic pathways with a time-calibrated tree of life. We find that the majority of metabolic pathways were established within the first 2 billion years of Earth history, with pathways accreting at different rates. Methanogenesis and acetogenesis are recovered to be among the earliest energy metabolisms, whereas photosynthetic pathways achieved completeness by 2 Ga, much later than most previous studies have envisaged. Horizontal exchange of metabolic genes is widespread, but it has occurred largely among closely related lineages and for some pathways there is a strong signal of vertical inheritance. We also find that the rate of horizontal gene transfer has been higher in Bacteria than in Archaea through evolutionary history. Finally, we evaluate how our reconstructed history of metabolism can help to constrain hypotheses of biospheric evolution, considering the entropic and Darwinized Gaia hypotheses as well as a simple neutral model for the assembly of biogeochemical cycles. This article is part of the discussion meeting issue ‘Chance and purpose in the evolution of biospheres’.

The average long-term impact of Darwinian evolution on Earth’s habitability remains extremely uncertain. Recent attempts to reconcile this uncertainty by “Darwinizing” nonreplicating biogeochemical processes subject to persistence-based selection conform with the historicity of the geochemical record but lack mechanistic clarity. Here, we present a theoretical framework showing how: 1) A biogeochemical “cycle-biota-variant” (CBV) can be defined non-arbitrarily as one biologically facilitated pathway for net recycling of an essential element, plus the genotypes driving the relevant interconversion reactions. 2) Distinct CBVs can be individuated if they have climatic or geochemical side effects that feed-back on relative persistence. 3) The separation of spatial/temporal scales between the dynamics of such effects and those of conventional Darwinian evolution can introduce a degree of randomness into the relationship between CBVs and their Earth system impact properties, loosely analogous to that between the biochemical causes and evolutionary effects of genetic mutation. 4) Threshold behavior in climate feedback can accentuate biotic impacts and lead to CBV-level “competitive exclusion”. 5) CBV-level persistence selection is observationally distinguishable from genotype-level selection by strong covariance between “internal” CBV properties (genotypes and reactions) and “external” climatic effects, which we argue is analogous to the covariance between fitness and traits under conventional Darwinian selection. These factors cannot circumvent the basic fact that local natural selection will often favor phenotypes that ultimately destabilize large-scale geochemical/climatic properties. However, we claim that our results nevertheless demonstrate the theoretical coherence of persistence-selection between non-replicating life–environment interaction patterns and therefore have broad biogeochemical applicability.