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The origin of eukaryotes remains unclear 1 – 4 . Current data suggest that eukaryotes may have emerged from an archaeal lineage known as ‘Asgard’ archaea 5 , 6 . Despite the eukaryote-like genomic features that are found in these archaea, the evolutionary transition from archaea to eukaryotes remains unclear, owing to the lack of cultured representatives and corresponding physiological insights. Here we report the decade-long isolation of an Asgard archaeon related to Lokiarchaeota from deep marine sediment. The archaeon—‘ Candidatus Prometheoarchaeum syntrophicum’ strain MK-D1—is an anaerobic, extremely slow-growing, small coccus (around 550 nm in diameter) that degrades amino acids through syntrophy. Although eukaryote-like intracellular complexes have been proposed for Asgard archaea 6 , the isolate has no visible organelle-like structure. Instead, Ca . P. syntrophicum is morphologically complex and has unique protrusions that are long and often branching. On the basis of the available data obtained from cultivation and genomics, and reasoned interpretations of the existing literature, we propose a hypothetical model for eukaryogenesis, termed the entangle–engulf–endogenize (also known as E 3 ) model. Isolation and characterization of an archaeon that is most closely related to eukaryotes reveals insights into how eukaryotes may have evolved from prokaryotes.

The origin and cellular complexity of eukaryotes represent a major enigma in biology. Current data support scenarios in which an archaeal host cell and an alphaproteobacterial (mitochondrial) endosymbiont merged together, resulting in the first eukaryotic cell. The host cell is related to Lokiarchaeota, an archaeal phylum with many eukaryotic features. The emergence of the structural complexity that characterizes eukaryotic cells remains unclear. Here we describe the ‘Asgard’ superphylum, a group of uncultivated archaea that, as well as Lokiarchaeota, includes Thor-, Odin- and Heimdallarchaeota. Asgard archaea affiliate with eukaryotes in phylogenomic analyses, and their genomes are enriched for proteins formerly considered specific to eukaryotes. Notably, thorarchaeal genomes encode several homologues of eukaryotic membrane-trafficking machinery components, including Sec23/24 and TRAPP domains. Furthermore, we identify thorarchaeal proteins with similar features to eukaryotic coat proteins involved in vesicle biogenesis. Our results expand the known repertoire of ‘eukaryote-specific’ proteins in Archaea, indicating that the archaeal host cell already contained many key components that govern eukaryotic cellular complexity. This work describes the Asgard superphylum, an assemblage of diverse archaea that comprises Odinarchaeota, Heimdallarchaeota, Lokiarchaeota and Thorarchaeota, offering insights into the earliest days of eukaryotic cells and their complex features. Archaea with eukaryotic tendencies Although the origin of eukaryotic cells from prokaryotic ancestors remains an enigma, it has become clear that the root of eukaryotes lies among a group of prokaryotes known as archaea. The recent identification of newly described archaea belonging to the Asgard superphylum, including Lokiarchaeota and Thorarchaeota, revealed a group of prokaryotes containing many proteins and genetic sequences that are otherwise found only in eukaryotes. Thijs Ettema and colleagues extend the search for eukaryotic roots by describing further additions to the Asgard superphylum: the Odinarchaeota and Heimdallarchaeota. The new Asgard genomes encode homologues of several components of eukaryotic membrane-trafficking machineries, suggesting that the archaeal ancestor of eukaryotes was well equipped to evolve the complex cellular features that are characteristic of eukaryotic cells.

Biomolecular condensates are found throughout eukaryotic cells, including in the nucleus, in the cytoplasm and on membranes. They are also implicated in a wide range of cellular functions, organizing molecules that act in processes ranging from RNA metabolism to signalling to gene regulation. Early work in the field focused on identifying condensates and understanding how their physical properties and regulation arise from molecular constituents. Recent years have brought a focus on understanding condensate functions. Studies have revealed functions that span different length scales: from molecular (modulating the rates of chemical reactions) to mesoscale (organizing large structures within cells) to cellular (facilitating localization of cellular materials and homeostatic responses). In this Roadmap, we discuss representative examples of biochemical and cellular functions of biomolecular condensates from the recent literature and organize these functions into a series of non-exclusive classes across the different length scales. We conclude with a discussion of areas of current interest and challenges in the field, and thoughts about how progress may be made to further our understanding of the widespread roles of condensates in cell biology.Biomolecular condensates are membraneless molecular assemblies formed via liquid–liquid phase separation. They have a plethora of roles, ranging from controlling biochemical reactions to regulating cell organization and cell function. This article provides a framework for the study of condensate functions across these cellular length scales, offering to bring new understanding of biological processes.

Single-cell RNA sequencing (scRNA-seq) allows researchers to collect large catalogues detailing the transcriptomes of individual cells. Unsupervised clustering is of central importance for the analysis of these data, as it is used to identify putative cell types. However, there are many challenges involved. We discuss why clustering is a challenging problem from a computational point of view and what aspects of the data make it challenging. We also consider the difficulties related to the biological interpretation and annotation of the identified clusters.

Key Points In addition to the classical clathrin-dependent mechanisms of endocytosis, there are several pathways that do not use a clathrin coat and are, therefore, referred to as clathrin-independent (CI) mechanisms. CI mechanisms of uptake have gained much attention with the realization that they have important roles in the regulation of cell growth and development as well as important implications in the study of certain diseases and pathogens. Two well-known CI mechanisms are the caveolar pathway and fluid-phase endocytosis. However, there is much debate concerning the number of distinct CI mechanisms that exist, the best cargo molecules for the study of a particular pathway, and the underlying protein machinery that regulates these pathways. To organize the extensive literature on CI endocytosis for the purpose of arriving at a mechanistic understanding, this Review classifies CI mechanisms as follows: first, on whether or not they are dynamin dependent and, second, according to the involvement of the small GTPases CDC42, RhoA or ARF6. Protein-based mechanisms (for example, ubiquitylation) and lipid-based mechanisms (for example, nanoscale clustering of lipid-tethered proteins) may both function in the selection of cargo for CI endocytosis. The mechanism of budding in the dynamin-independent pathways remains elusive; however, recent theoretical studies provide testable ideas in this area. Classically, endocytosis involves the formation of clathrin-coated carriers that bud from the plasma membrane by dynamin-dependent mechanisms. Recently, several clathrin-independent endocytic pathways have been identified, which represent the main pathway of entry into cells for a diverse array of cargoes, including receptors, lipids and pathogens. There are numerous ways that endocytic cargo molecules may be internalized from the surface of eukaryotic cells. In addition to the classical clathrin-dependent mechanism of endocytosis, several pathways that do not use a clathrin coat are emerging. These pathways transport a diverse array of cargoes and are sometimes hijacked by bacteria and viruses to gain access to the host cell. Here, we review our current understanding of various clathrin-independent mechanisms of endocytosis and propose a classification scheme to help organize the data in this complex and evolving field.

The ribosome is a molecular machine responsible for protein synthesis and a major target for small-molecule inhibitors. Compared to the wealth of structural information available on ribosome-targeting antibiotics in bacteria, our understanding of the binding mode of ribosome inhibitors in eukaryotes is currently limited. Here we used X-ray crystallography to determine 16 high-resolution structures of 80S ribosomes from Saccharomyces cerevisiae in complexes with 12 eukaryote-specific and 4 broad-spectrum inhibitors. All inhibitors were found associated with messenger RNA and transfer RNA binding sites. In combination with kinetic experiments, the structures suggest a model for the action of cycloheximide and lactimidomycin, which explains why lactimidomycin, the larger compound, specifically targets the first elongation cycle. The study defines common principles of targeting and resistance, provides insights into translation inhibitor mode of action and reveals the structural determinants responsible for species selectivity which could guide future drug development. Whereas previous structural investigation of ribosome inhibitors has been done using the prokaryotic ribosome, this work presents X-ray crystal structures of the yeast ribosome in complex with 16 inhibitors including eukaryotic-specific inhibitors; the inhibitors all bind the mRNA or tRNA binding sites, larger molecules appear to target specifically the first elongation cycle. Mechanisms of eukaryotic ribosome inhibition As the ribosome is a common target of antibiotics, there is a wealth of structural data on the binding of the bacterial ribosome to various inhibitors. Our understanding of inhibitor binding to the larger eukaryotic ribosome is limited. Marat Yusupov and colleagues present the structure of the yeast 80S ribosome bound to 12 eukaryote-specific and 4 broad-spectrum inhibitors. On the basis of structural data and kinetic studies, the authors propose a model for the action of cycloheximide and lactimidomycin that demonstrates that the size of an inhibitor can dictate its accessibility to the ribosome and thus its mechanism of action. This new model suggests general principles for structure-based design of new antibiotics as well as therapeutics against fungal and protozoan infections, cancers and genetic disorders induced by premature stop codons.

Key Points Both general and selective autophagy are critical regulators of cellular homeostasis with intricate links to cell metabolism, growth control, the balance between cell survival and cell death, as well as ageing. Not surprisingly these autophagy pathways also have important roles in human health and disease. Selective autophagy requires, in addition to the core autophagy machinery, one or more selectivity factors, the most important of which are the selective autophagy receptors, which tag the specific cargo for engulfment in an autophagosome and delivery to the lysosome (vacuole in yeast and plants). Each pathway may use one or more such receptors. Although the selectivity factors required for the plethora of selective autophagy pathways are not highly conserved, their mechanisms of activation and the signalling pathways that activate them are. Selective autophagy receptors are regulated by phosphorylation by protein kinases. Phosphorylation of the selective autophagy receptors regulates their ability to recruit and engage other components of the core autophagy machinery for phagophore membrane expansion around the selective cargo. Selective autophagy pathways engage selective autophagy receptors (SARs) that identify and bind to cellular cargoes (proteins or organelles) destined for degradation. Recent yeast studies have provided insights into the regulation and mechanisms underlying SAR function. As these mechanisms are conserved from yeast to mammals, it is now possible to formulate general principles of how selectivity during autophagy is achieved. Autophagy has burgeoned rapidly as a field of study because of its evolutionary conservation, the diversity of intracellular cargoes degraded and recycled by this machinery, the mechanisms involved, as well as its physiological relevance to human health and disease. This self-eating process was initially viewed as a non-selective mechanism used by eukaryotic cells to degrade and recycle macromolecules in response to stress; we now know that various cellular constituents, as well as pathogens, can also undergo selective autophagy. In contrast to non-selective autophagy, selective autophagy pathways rely on a plethora of selective autophagy receptors (SARs) that recognize and direct intracellular protein aggregates, organelles and pathogens for specific degradation. Although SARs themselves are not highly conserved, their modes of action and the signalling cascades that activate and regulate them are. Recent yeast studies have provided novel mechanistic insights into selective autophagy pathways, revealing principles of how various cargoes can be marked and targeted for selective degradation.

Key Points Until recently, RNA profiling was limited to ensemble-based approaches, which average over bulk populations of cells. Technological advances in single-cell RNA sequencing (scRNA-seq) now enable the transcriptomes of large numbers of individual cells to be assayed in an unbiased manner. To ensure that scRNA-seq data are fully exploited and interpreted correctly, it is important to apply appropriate computational and statistical approaches. Methods and principles previously developed for bulk RNA sequencing can be reused for this purpose; however, scRNA-seq data analysis poses several unique challenges that require new analytical strategies. At the experimental design stage, unique molecular identifiers and quantitative standards such as spike-ins need to be considered to allow accurate normalization and quality control of the raw data. Prior to using scRNA-seq data for biological discovery, it is important to consider both technical variability and confounding factors such as batch effects, the cell cycle or apoptosis. Computational methods that account for technical variation and remove confounding factors are beginning to emerge. The processed and normalized scRNA-seq data provide unique analysis opportunities that allow novel biological discoveries to be made. These include identification and characterization of cell types and the study of their organization in space and/or time; inference of gene regulatory networks and their robustness across individual cells; and characterization of the stochastic component of transcription. High-throughput RNA sequencing (RNA-seq) is a powerful method for transcriptome-wide analysis that has recently been applied to single cells. This Review discusses the analytical and computational challenges of processing and analysing single-cell RNA-seq data, paying special consideration to differences relative to the analysis of RNA-seq data generated from bulk cell populations and discussing how single-cell-specific biological insights can be obtained. The development of high-throughput RNA sequencing (RNA-seq) at the single-cell level has already led to profound new discoveries in biology, ranging from the identification of novel cell types to the study of global patterns of stochastic gene expression. Alongside the technological breakthroughs that have facilitated the large-scale generation of single-cell transcriptomic data, it is important to consider the specific computational and analytical challenges that still have to be overcome. Although some tools for analysing RNA-seq data from bulk cell populations can be readily applied to single-cell RNA-seq data, many new computational strategies are required to fully exploit this data type and to enable a comprehensive yet detailed study of gene expression at the single-cell level.

With the ultimate aim to construct a living cell, bottom-up synthetic biology strives to reconstitute cellular phenomena in vitro – disentangled from the complex environment of a cell. Recent work towards this ambitious goal has provided new insights into the mechanisms governing life. With the fast-growing library of functional modules for synthetic cells, their classification and integration become increasingly important. We discuss strategies to reverse-engineer and recombine functional parts for synthetic eukaryotes, mimicking the characteristics of nature’s own prototype. Particularly, we focus on large outer compartments, complex endomembrane systems with organelles, and versatile cytoskeletons as hallmarks of eukaryotic life. Moreover, we identify microfluidics and DNA nanotechnology as two technologies that can integrate these functional modules into sophisticated multifunctional synthetic cells. Bottom-up synthetic biology thrives in reverse-engineering a particular biological function using a minimal set of molecular components, like purified proteins. Recently, precision technologies, like microfluidics, have been used to recombine functional modules towards multifunctional synthetic cells. Synthetic biology can capitalize on a variety of pre-existing on-chip functions, which greatly increases the scope for complexity in the field. Advances in DNA nanotechnology gave rise to a diverse range of fully synthetic functional modules, like DNA-based ion channels or motors, which can replace some protein-based parts. Noteworthy progress has been made in achieving large and stable compartments, organelle-like multicompartment systems, and sophisticated cytoskeletal structures.