Eukaryotes have evolved to dominate the biosphere today, accounting for most documented living species and the vast majority of the Earth\'s biomass. Consequently, understanding how these biologically complex organisms initially diversified in the Proterozoic Eon over 539 million years ago is a foundational question in evolutionary biology. Over the last 70 years, palaeontologists have sought to document the rise of eukaryotes with fossil evidence. However, the delicate and microscopic nature of their sub-cellular features affords early eukaryotes diminished preservation potential. Chemical biomarker signatures of eukaryotes and the genetics of living eukaryotes have emerged as complementary tools for reconstructing eukaryote ancestry. In this review, we argue that exceptionally preserved Proterozoic microfossils are critical to interpreting these complementary tools, providing crucial calibrations to molecular clocks and testing hypotheses of palaeoecology. We highlight recent research on their preservation and biomolecular composition that offers new ways to enhance their utility.

Environmental DNA (eDNA) is becoming an increasingly important tool in diverse scientific fields from ecological biomonitoring to wastewater surveillance of viruses. The fundamental challenge in eDNA analyses has been the bioinformatical assignment of reads to taxonomic groups. It has long been known that full probabilistic methods for phylogenetic assignment are preferable, but unfortunately, such methods are computationally intensive and are typically inapplicable to modern next-generation sequencing data. We present a fast approximate likelihood method for phylogenetic assignment of DNA sequences. Applying the new method to several mock communities and simulated datasets, we show that it identifies more reads at both high and low taxonomic levels more accurately than other leading methods. The advantage of the method is particularly apparent in the presence of polymorphisms and/or sequencing errors and when the true species is not represented in the reference database.

Horizontal gene transfer (HGT) is a widely acknowledged phenomenon in prokaryotes for generating genetic diversity. However, the impact of this process in eukaryotes, particularly interdomain HGT, is a topic of debate. Although there have been observed biases in interdomain HGT detection, little exploration has been conducted on the effects of imbalanced databases. In our study, we conducted experiments to assess how different databases affect the detection of interdomain HGT using proteomes from the Pezizomycotina fungal subphylum as our focus group. Our objective was to simulate the database imbalance commonly found in public biological databases, where bacterial and eukaryotic sequences are unevenly represented, and demonstrate that an increase in uploaded eukaryotic sequences leads to a decrease in predicted HGTs. For our experiments, four databases with varying proportions of eukaryotic sequences but consistent proportions of bacterial sequences were utilized. We observed a significant reduction in detected interdomain HGT candidates as the proportion of eukaryotes increased within the database. Our data suggest that the imbalance in databases bias the interdomain HGT detection and highlights challenges associated with confirming the presence of interdomain HGT among Pezizomycotina fungi and potentially other groups within Eukarya.

Here, we present a method for expressing multiple open reading frames (ORFs) from single transcripts using the leaky scanning model of translation initiation. In this approach termed \"stoichiometric expression of mRNA polycistrons by eukaryotic ribosomes\" (SEMPER), adjacent ORFs are translated from a single mRNA at tunable ratios determined by their order in the sequence and the strength of their translation initiation sites. We validate this approach by expressing up to three fluorescent proteins from one plasmid in two different cell lines. We then use it to encode a stoichiometrically tuned polycistronic construct encoding gas vesicle acoustic reporter genes that enables efficient formation of the multi-protein complex while minimizing cellular toxicity. We also demonstrate that SEMPER enables polycistronic expression of recombinant monoclonal antibodies from plasmid DNA and of two fluorescent proteins from single mRNAs made through in vitro transcription. Finally, we provide a probabilistic model to elucidate the mechanisms underlying SEMPER. A record of this paper\'s transparent peer review process is included in the supplemental information.

Steroids are indispensable components of the eukaryotic cellular membrane and the acquisition of steroid biosynthesis was a key factor that enabled the evolution of eukaryotes. The polycyclic carbon structures of steroids can be preserved in sedimentary rocks as chemical fossils for billions of years and thus provide invaluable clues to trace eukaryotic evolution from the distant past. Steroid biosynthesis consists of (1) the production of protosteroids and (2) the subsequent modifications toward \"modern-type\" steroids such as cholesterol and stigmasterol. While protosteroid biosynthesis requires only two genes for the cyclization of squalene, complete modification of protosteroids involves ~10 additional genes. Eukaryotes universally possess at least some of those additional genes and thus produce modern-type steroids as major final products. The geological biomarker records suggest a prolonged period of solely protosteroid production in the mid-Proterozoic before the advent of modern-type steroids in the Neoproterozoic. It has been proposed that mid-Proterozoic protosteroids were produced by hypothetical stem-group eukaryotes that presumably possessed genes only for protosteroid production, even though in modern environments protosteroid production as a final product is found exclusively in bacteria. The host identity of mid-Proterozoic steroid producers is crucial for understanding the early evolution of eukaryotes. In this perspective, we discuss how geological biomarker data and genetic data complement each other and potentially provide a more coherent scenario for the evolution of steroids and associated early eukaryotes. We further discuss the potential impacts that steroids had on the evolution of aerobic metabolism in eukaryotes, which may have been an important factor for the eventual ecological dominance of eukaryotes in many modern environments.

Free-living amoebae (FLA) are prevalent in nature and man-made environments, and they can survive in harsh conditions by forming cysts. Studies have discovered that some FLA species are able to show pathogenicity to human health, leading to severe infections of central nervous systems, eyes, etc. with an extremely low rate of recovery. Therefore, it is imperative to establish a surveillance framework for FLA in environmental habitats. While many studies investigated the risks of independent FLA, interactions between FLA and surrounding microorganisms determined microbial communities in ecosystems and further largely influenced public health. Here we systematically discussed the interactions between FLA and different types of microorganisms and corresponding influences on behaviors and health risks of FLA in the environment. Specifically, bacteria, viruses, and eukaryotes can interact with FLA and cause either enhanced or inhibited effects on FLA infectivity, along with microorganism community changes. Therefore, considering the co-existence of FLA and other microorganisms in the environment is of great importance for reducing environmental health risks.

Despite the fact that introns mean an energy and time burden for eukaryotic cells, they play an irreplaceable role in the diversification and regulation of protein production. As a common feature of eukaryotic genomes, it has been reported that in protein-coding genes, the longest intron is usually one of the first introns. The goal of our work was to find a possible difference in the biological function of genes that fulfill this common feature compared to genes that do not. Data on the lengths of all introns in genes were extracted from the genomes of six vertebrates (human, mouse, koala, chicken, zebrafish and fugu) and two other model organisms (nematode worm and arabidopsis). We showed that more than 40% of protein-coding genes have the relative position of the longest intron located in the second or third tertile of all introns. Genes divided according to the relative position of the longest intron were found to be significantly increased in different KEGG pathways. Genes with the longest intron in the first tertile predominate in a range of pathways for amino acid and lipid metabolism, various signaling, cell junctions or ABC transporters. Genes with the longest intron in the second or third tertile show increased representation in pathways associated with the formation and function of the spliceosome and ribosomes. In the two groups of genes defined in this way, we further demonstrated the difference in the length of the longest introns and the distribution of their absolute positions. We also pointed out other characteristics, namely the positive correlation between the length of the longest intron and the sum of the lengths of all other introns in the gene and the preservation of the exact same absolute and relative position of the longest intron between orthologous genes.

Life on Earth comprises prokaryotes and a broad assemblage of endosymbioses. The pages of Molecular Biology and Evolution and Genome Biology and Evolution have provided an essential window into how these endosymbiotic interactions have evolved and shaped biological diversity. Here, we provide a current perspective on this knowledge by drawing on decades of revelatory research published in Molecular Biology and Evolution and Genome Biology and Evolution, and insights from the field at large. The accumulated work illustrates how endosymbioses provide hosts with novel phenotypes that allow them to transition between adaptive landscapes to access environmental resources. Such endosymbiotic relationships have shaped and reshaped life on Earth. The early serial establishment of mitochondria and chloroplasts through endosymbioses permitted massive upscaling of cellular energetics, multicellularity, and terrestrial planetary greening. These endosymbioses are also the foundation upon which all later ones are built, including everything from land-plant endosymbioses with fungi and bacteria to nutritional endosymbioses found in invertebrate animals. Common evolutionary mechanisms have shaped this broad range of interactions. Endosymbionts generally experience adaptive and stochastic genome streamlining, the extent of which depends on several key factors (e.g. mode of transmission). Hosts, in contrast, adapt complex mechanisms of resource exchange, cellular integration and regulation, and genetic support mechanisms to prop up degraded symbionts. However, there are significant differences between endosymbiotic interactions not only in how partners have evolved with each other but also in the scope of their influence on biological diversity. These differences are important considerations for predicting how endosymbioses will persist and adapt to a changing planet.

Intrinsic disorder predictors were evaluated in several studies including the two large CAID experiments. However, these studies are biased towards eukaryotic proteins and focus primarily on the residue-level predictions. We provide first-of-its-kind assessment that comprehensively covers the taxonomy and evaluates predictions at the residue and disordered region levels. We curate a benchmark dataset that uniformly covers eukaryotic, archaeal, bacterial, and viral proteins. We find that predictive performance differs substantially across taxonomy, where viruses are predicted most accurately, followed by protists and higher eukaryotes, while bacterial and archaeal proteins suffer lower levels of accuracy. These trends are consistent across predictors. We also find that current tools, except for flDPnn, struggle with reproducing native distributions of the numbers and sizes of the disordered regions. Moreover, analysis of two variants of disorder predictions derived from the AlphaFold2 predicted structures reveals that they produce accurate residue-level propensities for archaea, bacteria and protists. However, they underperform for higher eukaryotes and generally struggle to accurately identify disordered regions. Our results motivate development of new predictors that target bacteria and archaea and which produce accurate results at both residue and region levels. We also stress the need to include the region-level assessments in future assessments.

OBJECTIVE: The eukaryotic tree of life has been subject of numerous studies ever since the nineteenth century, with more supergroups and their sister relations being decoded in the last years. In this study, we reconstructed the phylogeny of eukaryotes using complete 18S rDNA sequences and their individual secondary structures simultaneously. After the sequence-structure data was encoded, it was automatically aligned and analyzed using sequence-only as well as sequence-structure approaches. We present overall neighbor-joining trees of 211 eukaryotes as well as the respective profile neighbor-joining trees, which helped to resolve the basal branching pattern. A manually chosen subset was further inspected using neighbor-joining, maximum parsimony, and maximum likelihood analyses. Additionally, the 75 and 100 percent consensus structures of the subset were predicted.
RESULTS: All sequence-structure approaches show improvements compared to the respective sequence-only approaches: the average bootstrap support per node of the sequence-structure profile neighbor-joining analyses with 90.3, was higher than the average bootstrap support of the sequence-only profile neighbor-joining analysis with 73.9. Also, the subset analyses using sequence-structure data were better supported. Furthermore, more subgroups of the supergroups were recovered as monophyletic and sister group relations were much more comparable to results as obtained by multi-marker analyses.