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The evolutionary origin of language remains unknown despite many efforts to determine the origin of this signature human trait. Based on epigenetic inheritance, the current article hypothesizes that language evolved from cell-cell communication as the basis for generating structure and function embryologically and phylogenetically, as did all physiologic traits. Beginning with lipids forming the first micelle, a vertical integration of the evolved properties of the cell, from multicellular organisms to the introduction of cholesterol into the cell membrane, to the evolution of the peroxisome, the water-land transition and duplication of the βAdrenergic Receptor, the evolution of endothermy, leading to bipedalism, freeing the forelimbs for toolmaking and language, selection pressure for myelinization of the central nervous system to facilitate calcium flux, bespeaks human expression, culminating in the evolution of civilization. This process is epitomized by the Area of Broca as the structural-functional site for both motor control and language formation. The mechanistic interrelationship between motor control and language formation is underscored by the role of FoxP2 gene expression in both bipedalism and language. The effect of endothermy on bipedalism, freeing the forelimbs for toolmaking and language as the vertical integration from Cosmology to Physiology as the basis for language bespeaks human expression.

The coronavirus disease (COVID-19) pandemic, caused by the coronavirus SARS-CoV-2, has caused 60 million infections and 1 38 million fatalities Genomic analysis of SARS-CoV-2 can provide insights on drug design and vaccine development for controlling the pandemic Inverted repeats in a genome greatly impact the stability of the genome structure and regulate gene expression Inverted repeats involve cellular evolution and genetic diversity, genome arrangements, and diseases Here, we investigate the inverted repeats in the coronavirus SARS-CoV-2 genome We find that SARS-CoV-2 genome has an abundance of inverted repeats The inverted repeats are mainly located in the gene of the Spike protein This result suggests the Spike protein gene undergoes recombination events, therefore, is essential for fast evolution Comparison of the inverted repeat signatures in human and bat coronaviruses suggest that SARS-CoV-2 is mostly related SARS-related coronavirus, SARSr-CoV/RaTG13 The study also reveals that the recent SARS-related coronavirus, SARSr-CoV/RmYN02, has a high amount of inverted repeats in the spike protein gene Besides, this study demonstrates that the inverted repeat distribution in a genome can be considered as the genomic signature This study highlights the significance of inverted repeats in the evolution of SARS-CoV-2 and presents the inverted repeats as the genomic signature in genome analysis

Transfer RNAs (tRNAs) remain one of the very few classes of genes still encoded in the mitochondrial genome. These key components of the protein translation system must interact with a large enzymatic network of nuclear-encoded gene products to maintain mitochondrial function. Plants have an evolutionarily dynamic mitochondrial tRNA population, including ongoing tRNA gene loss and replacement by both horizontal gene transfer from diverse sources and import of nuclear-expressed tRNAs from the cytosol. Thus, plant mitochondria represent an excellent model for understanding how anciently divergent genes can act as "interchangeable parts" during the evolution of complex molecular systems. In particular, understanding the integration of the mitochondrial translation system with elements of the corresponding machinery used in cytosolic protein synthesis is a key area for eukaryotic cellular evolution. Here, we review the increasingly detailed phylogenetic data about the evolutionary history of mitochondrial tRNA gene loss, transfer, and functional replacement that has created extreme variation in mitochondrial tRNA populations across plant species. We describe emerging tRNA-seq methods with promise for refining our understanding of the expression and subcellular localization of tRNAs. Finally, we summarize current evidence and identify open questions related to coevolutionary changes in nuclear-encoded enzymes that have accompanied turnover in mitochondrial tRNA populations.

Owing to internal homeostatic mechanisms, cellular traits may experience long periods of stable selective pressures, during which the stochastic forces of drift and mutation conspire to generate variation. However, even in the face of invariant selection, the drift barrier defined by the genetic effective population size, which is negatively associated with organism size, can have a substantial influence on the location and dispersion of the long-term steady-state distribution of mean phenotypes. In addition, for multilocus traits, the multiplicity of alternative, functionally equivalent states can draw mean phenotypes away from selective optima, even in the absence of mutation bias. Using a framework for traits with an additive genetic basis, it is shown that 1) optimal phenotypic states may be only rarely achieved; 2) gradients of mean phenotypes with respect to organism size (i.e., allometric relationships) are likely to be molded by differences in the power of random genetic drift across the tree of life; and 3) for any particular set of population-genetic conditions, significant variation in mean phenotypes may exist among lineages exposed to identical selection pressures. These results provide a potentially useful framework for understanding numerous aspects of cellular diversification and illustrate the risks of interpreting such variation in a purely adaptive framework.

Background Protein transporters translocate hydrophilic segments of polypeptide across hydrophobic cell membranes. Two protein transporters are ubiquitous and date back to the last universal common ancestor: SecY and YidC. SecY consists of two pseudosymmetric halves, which together form a membrane-spanning protein-conducting channel. YidC is an asymmetric molecule with a protein-conducting hydrophilic groove that partially spans the membrane. Although both transporters mediate insertion of membrane proteins with short translocated domains, only SecY transports secretory proteins and membrane proteins with long translocated domains. The evolutionary origins of these ancient and essential transporters are not known. Results The features conserved by the two halves of SecY indicate that their common ancestor was an antiparallel homodimeric channel. Structural searches with SecY’s halves detect exceptional similarity with YidC homologs. The SecY halves and YidC share a fold comprising a three-helix bundle interrupted by a helical hairpin. In YidC, this hairpin is cytoplasmic and facilitates substrate delivery, whereas in SecY, it is transmembrane and forms the substrate-binding lateral gate helices. In both transporters, the three-helix bundle forms a protein-conducting hydrophilic groove delimited by a conserved hydrophobic residue. Based on these similarities, we propose that SecY originated as a YidC homolog which formed a channel by juxtaposing two hydrophilic grooves in an antiparallel homodimer. We find that archaeal YidC and its eukaryotic descendants use this same dimerisation interface to heterodimerise with a conserved partner. YidC’s sufficiency for the function of simple cells is suggested by the results of reductive evolution in mitochondria and plastids, which tend to retain SecY only if they require translocation of large hydrophilic domains. Conclusions SecY and YidC share previously unrecognised similarities in sequence, structure, mechanism, and function. Our delineation of a detailed correspondence between these two essential and ancient transporters enables a deeper mechanistic understanding of how each functions. Furthermore, key differences between them help explain how SecY performs its distinctive function in the recognition and translocation of secretory proteins. The unified theory presented here explains the evolution of these features, and thus reconstructs a key step in the origin of cells.

The next generation of therapies is moving beyond the use of small molecules and proteins to using whole cells. Compared with the interactions of small-molecule drugs with biomolecules, which can largely be understood through chemistry, cell therapies act in a chemical and physical world and can actively adapt to that world, amplifying complexity but also the potential for truly breakthrough impact. Although there has been success in introducing targeting proteins into cells to achieve a therapeutic effect, for example, chimeric antigen receptor (CAR) T cells, our ability to engineer cells is generally limited to introducing proteins, but not modulating large-scale traits or structures of cellular "machines," which play critical roles in disease. Example traits include the ability to secrete compounds, deform through tissue, adhere to surrounding cells, apply force to phagocytose targets, or move through extracellular matrix. There is an opportunity to increase the efficacy of cell therapies through the use of quantitative automation tools, to analyze, sort, and select rare cells with beneficial traits. Combined with methods of genetic or epigenetic mutagenesis to create diversity, such approaches can enable the directed cellular evolution of new therapeutically optimal populations of cells and uncover genetic underpinnings of these optimal traits.

Motility and membrane deformation are crucial to motile cells. Therefore formation of protrusion in the membrane has been the subject of various studies. The stable shape of the membrane and also its movements are controlled by the forces exerted by actin filaments. In order to study the protrusion behavior, we represented a toy model based on actin filaments polar characteristic and elastic characteristic of the membrane. We also studied the effect of changing physical parameters such as filament density, the membrane tension, and the polymerization rate on the shape and the magnitude of the protrusion.

Significance The standard genetic code (SGC) is common to all sufficiently explored Earth biota, suggesting a common origin for protein biosynthesis in every known organism. The ancient events leading to this near-universal biological characteristic are manifestly of scientific importance. The accompanying text presents a detailed pathway for formation of the SGC, as well as a method for identifying essential origin events. Significantly, the SGC can evolve using only well-characterized chemical, biochemical, and physical mechanisms, paralleling other known evolutionary transitions., Minimally evolved codes are constructed here; these have randomly chosen standard genetic code (SGC) triplets, completed with completely random triplet assignments. Such “genetic codes” have not evolved, but retain SGC qualities. Retained qualities are basic, part of the underpinning of coding. For example, the sensitivity of coding to arbitrary assignments, which must be < ∼10%, is intrinsic. Such sensitivity comes from the elementary combinatorial properties of coding and constrains any SGC evolution hypothesis. Similarly, assignment of last-evolved functions is difficult because of late kinetic phenomena, likely common across codes. Census of minimally evolved code assignments shows that shape and size of wobble domains controls the code’s fit into a coding table, strongly shifting accuracy of codon assignments. Access to the SGC therefore requires a plausible pathway to limited randomness, avoiding difficult completion while fitting a highly ordered, degenerate code into a preset three-dimensional space. Three-dimensional late Crick wobble in a genetic code assembled by lateral transfer between early partial codes satisfies these varied, simultaneous requirements. By allowing parallel evolution of SGC domains, this origin can yield shortened evolution to SGC-level order and allow the code to arise in smaller populations. It effectively yields full codes. Less obviously, it unifies previously studied chemical, biochemical, and wobble order in amino acid assignment, including a stereochemical minority of triplet–amino acid associations. Finally, fusion of intermediates into the final SGC is credible, mirroring broadly accepted later cellular evolution.

PREMISE Whole-genome duplication (WGD) is ubiquitous in plants. Recent reviews and meta-analyses, aiming to understand how such phenotypic transition could facilitate neopolyploid establishment, demonstrated multifarious immediate effects of WGD on fitness and reproductive traits. Yet, little is known about how short-term modifications evolve through time. Such a comparison among new and established polyploid lineages is crucial to understand which effects of WGD promote or impede polyploid survival. METHODS We performed a meta-analysis to determine how WGD affects morphological, cellular, and fitness traits in autotetraploid individuals compared to their diploid progenitors. We studied how established tetraploids differed from diploids compared to neotetraploids, to further learn about the fate of WGD-associated phenotypic effects during polyploid establishment. RESULTS The short-term effects of WGD were an increase in size of morphological traits and cells, accompanied by a decrease in fitness and the number of cells. After establishment, the morphological effect persisted, but cellular and fitness components reverted back to the values observed in the diploid ancestors. CONCLUSIONS Our results suggest that the larger morphology of autotetraploids is not a constraint to establishment. However, other observable effects of genome doubling disappeared with time, suggesting that solving cellular and fitness constraints are critical aspects for polyploid establishment.

Gene exchange between viruses and their hosts acts as a key facilitator of horizontal gene transfer and is thought to be a major driver of evolutionary change 1–3. Our understanding of this process comes primarily from bacteria and phage co-evolution4, but the mode and functional significance of gene transfers between eukaryotes and their viruses remains more anecdotal. Here we show that viral-eukaryotic gene exchange can define infection strategies and has recurrently influenced eukaryotic evolution. Using a systematic, phylogenetically-informed approach, we characterized viral-eukaryotic gene exchange across diverse taxa, identifying thousands of transfers, and revealing their frequency, taxonomic distribution, and projected functions, across the eukaryotic tree of life. Eukaryote-derived viral genes revealed common viral host-manipulation strategies, including the key cellular pathways and compartments targeted during infection, identifying potential targets for broad-spectrum host-targeted antiviral therapeutics. Furthermore, viral-derived eukaryotic genes exposed a recurring role for viral glycosyltransferases in the diversification of eukaryotic morphology, as viral-derived genes have impacted the evolution of structures as diverse as algal cell walls, trypanosome mitochondria, and animal tissues. These findings illuminate the nature of viral-eukaryotic gene exchange and its impact on the biology of viruses and their eukaryotic hosts, providing novel perspectives for understanding viral infection mechanisms and revealing the influence of viruses on eukaryotic evolution.

Membrane systems reveal certain computing aspects of the living cells, representing also a formal model of the cell structure and activity. We introduce membrane systems with costs by assigning both storage costs to membranes and execution costs to their rules. A variant of Maude (namely Priced-Timed Maude) is used to implement these models of the cells enhanced by costs. We can simulate and analyze the evolution of cells enhanced with costs, and verify their properties by using proper tools of the complex software platform Maude.

Retroviruses originated over 400 million years ago, and were present throughout most or all of vertebrate evolution. Integration of a provirus into host-cell DNA is an essential step in the retrovirus replication cycle, which can produce persistent infections and chronic diseases that reduce host fitness. Integration is also inherently mutagenic, with a spectrum of phenotypic consequences, and if integration occurs in the germline, the result is an endogenous retrovirus (ERV) that can be passed on to the organism’s descendants. Thus, retroviruses have a dual role in vertebrate evolution, as agents of selection and as sources of genetic and phenotypic variation.

The capacity to learn new systemic behaviour is a fundamental issue to understand the adaptive mechanisms involved in cellular evolution. We have recently observed, in a preliminary analysis, the emergence of conditioned behaviour in individual amoebae cells. In these experiments, cells were able to acquire new migratory conduct and remember it for long periods of their cellular cycle, forgetting it later on. Here, following a similar conceptual framework of Pavlov’s experiments, we have exhaustively studied the migration trajectories of more than 2000 individual cells belonging to three different species: Amoeba proteus, Metamoeba leningradensis, and Amoeba borokensis. Fundamentally, we have analysed several properties of conditioned cells, such as the intensity of the responses, the directionality persistence, the total distance traveled, the directionality ratio, the average speed, and the persistence times. We have observed that these three species can modify the systemic response to a specific stimulus by associative conditioning. Our main analysis shows that such new behaviour is very robust and presents a similar structure of migration patterns in the three species, which was characterized by the presence of conditioning for long periods, remarkable straightness in their trajectories and strong directional persistence. Our quantitative results, compared with other studies on complex cellular responses in bacteria, protozoa, fungus-like organisms and metazoans, allow us to conclude that cellular associative conditioning might be a widespread characteristic of unicellular organisms. This finding could be essential to understand some key evolutionary principles involved in increasing the cellular adaptive fitness to microenvironments.

The coming of the Last Universal Cellular Ancestor (LUCA) was the singular watershed event in the making of the biotic world. If the coming of LUCA marked the crossing of the “Darwinian Threshold”, then pre-LUCA evolution must have been Pre-Darwinian and at least partly non-Darwinian. But how did Pre-Darwinian evolution before LUCA actually operate? I broaden our understanding of the central mechanism of biological evolution (i.e., variation-selection-inheritance) and then extend this broadened understanding to its natural starting point: the origin(s) of the First Universal Cellular Ancestors (FUCAs) before LUCA. My hypothesis centers upon vesicles’ making-and-remaking as variation and competition as selection. More specifically, I argue that vesicles’ acquisition and merger, via breaking-and-repacking, proto-endocytosis, proto-endosymbiosis, and other similar processes had been a central force of both variation and selection in the pre-Darwinian epoch. These new perspectives shed important new light upon the origin of FUCAs and their subsequent evolution into LUCA.

In contrast to Darwinian evolution, which is founded on the material competition between organisms, cellular epigenetic evolution focuses on cell-cell communication of data from one stage of life to another-developmentally, phylogenetically, as injury-repair - ultimately governed by the First Principles of Physiology. By merging ontogeny and phylogeny, since both are based on cell-cell communication mediated by soluble growth factors and their receptors, evolution complies as one holistic, unified process. As such, the material aspects of the organism can be seen as 'means' instead of 'ends', begging the question as to just what the 'ends' of evolution are ? Once the superficial material aspect of lifeforms is eliminated, only the flow of energy is left, within and between generations. Contemporary biology and physics are at a critical phase, unable to reduce their problems to practice. A paradigm shift to evolution as energy flow is proposed as the solution.

The early history of life harbours many unresolved evolutionary questions, none more important than the genomic origin and cellular evolution of eukaryotes. An issue central to eukaryote origin concerns the position of eukaryotes in the tree of life and the relationship of the host lineage that acquired the mitochondrion some two billion years ago to lineages of modern-day archaea. Recent analyses indicate that the host lineage branches within the Archaea, prompting the search for novel archaeal lineages that can improve our understanding of the cellular evolution of eukaryotes. Here we give a brief review of the studies on Archaea, the tree of life and the cellular evolution of eukaryotes, which is followed by an overview of recent progress fueled by new genomic technologies and recent status of archaeal research in China. Future directions for the study of early evolution are considered.

Background and objectives Several major risk factors for cancer involve vascular oversupply of energy to affected tissues. These include obesity, diabetes and chronic inflammation. Here, we propose a potential mechanistic explanation for the association between energy oversupply and cancer risk, which we call the metabolic cancer suppression hypothesis: We hypothesize that oncogenesis is normally suppressed by organismal physiology that regulates and strictly limits normal energy supply to somatic cells, and that this protection is removed by abnormal oversupply of energy. Methodology We evaluate this hypothesis using a computational model of somatic cell evolution to simulate experimental manipulation of the vascular energy supply to a tissue. The model simulates the evolutionary dynamics of somatic cells during oncogenesis. Results In our simulation experiment, we found that under plausible biological assumptions, elevated energy supply to a tissue led to the evolution of elevated energy uptake by somatic cells, leading to the rapid evolution of both defining traits of cancer cells: hyperproliferation, and tissue invasion. Conclusions and implications Our results support the hypothesis of metabolic cancer suppression, suggesting that vascular oversupply of energetic resources to somatic cells removes normal energetic limitations on cell proliferation, and that this accelerates cellular evolution toward cancer. Various predictions of this hypothesis are amenable to empirical testing, and have promising implications for translational research toward clinical cancer prevention.

Significance In order to understand the evolution of complex biological machines like the bacterial flagellar motor, it is crucial to know what each component does and when it arose. Here, we show that a subcomplex of the motor thought to act as a bushing for the spinning motor likely also serves another function—it plugs the hole in the outer membrane left when the flagellum disassembles. Moreover, this component and function is ancient, since it appears in diverse phyla without evidence of recent gene transfer., The bacterial flagellum is an amazing nanomachine. Understanding how such complex structures arose is crucial to our understanding of cellular evolution. We and others recently reported that in several Gammaproteobacterial species, a relic subcomplex comprising the decorated P and L rings persists in the outer membrane after flagellum disassembly. Imaging nine additional species with cryo-electron tomography, here, we show that this subcomplex persists after flagellum disassembly in other phyla as well. Bioinformatic analyses fail to show evidence of any recent horizontal transfers of the P- and L-ring genes, suggesting that this subcomplex and its persistence is an ancient and conserved feature of the flagellar motor. We hypothesize that one function of the P and L rings is to seal the outer membrane after motor disassembly.

This article shows how a good understanding of the design principles that underlie life is crucial in understanding its evolution. It gives concrete examples on how designs can be applied to evolution in the same way an engineer uses designs in creating building or bridges, or a software engineer that designs programs that can evolve. If we apply the notion of a design for evolution and realize that it is in its basis an evolving system of molecular machines, we can start to reverse engineer evolution and understand life. This article shows scenario’s for the origin of life and cel- lular life and how eukaryotic cells evolved to multicellular organisms. The driving force for evolution would be the intrinsic capability of the molecular machines to evolve and this basic tendency to evolve its ultimate goal. The scenarios that can be deduced following a design framework are drastically different from the theories that have been proposed so far. Based on the premise that that evolution can be modeled on a design framework, we can deduce that life evolved inside-out and that ontology reflects phylogeny on a molecular basis

International audience; Extensive microbial gene flows affect how we understand virology, microbiology, medical sciences, genetic modification, and evolutionary biology. Phylogenies only provide a narrow view of these gene flows: plasmids and viruses, lacking core genes, cannot be attached to cellular life on phylogenetic trees. Yet viruses and plasmids have a major impact on cellular evolution, affecting both the gene content and the dynamics of microbial communities. Using bipartite graphs that connect up to 149,000 clusters of homologous genes with 8,217 related and unrelated genomes, we can in particular show patterns of gene sharing that do not map neatly with the organismal phylogeny. Homologous genes are recycled by lateral gene transfer, and multiple copies of homologous genes are carried by otherwise completely unrelated (and possibly nested) genomes, that is, viruses, plasmids and prokaryotes. When a homologous gene is present on at least one plasmid or virus and at least one chromosome, a process of " gene externalization, " affected by a postprocessed selected functional bias, takes place, especially in Bacteria. Bipartite graphs give us a view of vertical and horizontal gene flow beyond classic taxonomy on a single very large, analytically tractable, graph that goes beyond the cellular Web of Life.

The ability to efficiently and dynamically change information stored in genomes would enable powerful strategies for studying cell biology and controlling cellular phenotypes. Current recombineering-mediated DNA writing platforms in bacteria are limited to specific laboratory conditions, often suffer from suboptimal editing efficiencies, and are not suitable forin situapplications. To overcome these limitations, we engineered a retroelement-mediated DNA writing system that enables efficient and precise editing of bacterial genomes without the requirement for target-specific elements or selection. We demonstrate that this DNA writing platform enables a broad range of applications, including efficient, scarless, andcis-element-independent editing of targeted microbial genomes within complex communities, the high-throughput mapping of spatial information and cellular interactions into DNA memory, and the continuous evolution of cellular traits.One Sentence SummaryHighly-efficient, dynamic, and conditional genome writers are engineered for DNA memory, genome engineering, editing microbial communities, high-resolution mapping of cellular connectomes, and modulating cellular evolution.

Cells, sophisticated membrane-bound units that contain the fundamental molecules of life, provide a precious library for inspiration and motivation for both society and academia. Scientists from various disciplines have made great endeavors toward the understanding of the cellular evolution by engineering artificial counterparts (protocells) that mimic or initiate structural or functional cellular aspects. In this regard, several works have discussed possible building blocks, designs, functions, or dynamics that can be applied to achieve this goal. Although great progress has been made, fundamental-yet complex-behaviors such as cellular communication, responsiveness to environmental cues, and motility remain a challenge, yet to be resolved. Herein, recent efforts toward utilizing soft systems for cellular mimicry are summarized-following the main outline of cellular evolution, from basic compartmentalization, and biological reactions for energy production, to motility and communicative behaviors between artificial cell communities or between artificial and natural cell communities. Finally, the current challenges and future perspectives in the field are discussed, hoping to inspire more future research and to help the further advancement of this field.

The bacterial flagellar motor is an amazing nanomachine. Understanding how such complex structures arose is crucial to our understanding of cellular evolution. We and others recently reported that in several Gammaproteobacterial species, a relic sub-complex comprising the decorated P- and L-rings persists in the outer membrane after flagellum disassembly. Imaging nine additional species with cryo-electron tomography, here we show that this sub-complex persists after flagellum disassembly in other phyla as well. Bioinformatic analyses fail to show evidence of any recent horizontal transfers of the P- and L-ring genes, suggesting that this sub-complex and its persistence is an ancient and conserved feature of the flagellar motor. We hypothesize that one function of the P- and L-rings is to seal the outer membrane after motor disassembly.

Natural selection has shaped the evolution of cells and multi-cellular organisms such that social cooperation can often be preferred over an individualistic approach to metabolic regulation. This paper extends a framework for dynamic metabolic resource allocation based on the maximum entropy principle to spatiotemporal models of metabolism with cooperation. Much like the maximum entropy principle encapsulates `bet-hedging' behaviour displayed by organisms dealing with future uncertainty in a fluctuating environment, its cooperative extension describes how individuals adapt their metabolic resource allocation strategy to further accommodate limited knowledge about the welfare of others within a community. The resulting theory explains why local regulation of metabolic cross-feeding can fulfil a community-wide metabolic objective if individuals take into consideration an ensemble measure of total population performance as the only form of global information. The latter is likely supplied by quorum sensing in microbial systems or signalling molecules such as hormones in multi-cellular eukaryotic organisms., 26 pages including 4 figures, appendix, and references: v3 revisions and expansion in line with referee comments

RNA transcription errors are transient, yet frequent, events that do have consequences for the cell. However, until recently we lacked the tools to empirically measure and study these errors. Advances in RNA library preparation and next generation sequencing (NGS) have allowed the spectrum of transcription errors to be empirically measured over the entire transcriptome and in nascent transcripts. Combining these powerful methods with forward and reverse genetic strategies has refined our understanding of transcription factors known to enhance RNA accuracy and will enable the discovery of new candidates. Furthermore, these approaches will shed additional light on the complex interplay between transcription fidelity and other DNA transactions, such as replication and repair, and explore a role for transcription errors in cellular evolution and disease.

The cerebral cortex varies dramatically in size and complexity between amniotes due to differences in neuron number and composition. These differences emerge during embryonic development as a result of variations in neurogenesis, which are thought to recapitulate modifications occurred during evolution that culminated in the human neocortex. Here, we review work from the last few decades leading to our current understanding of the evolution of neurogenesis and size of the cerebral cortex. Focused on specific examples across vertebrate and amniote phylogeny, we discuss developmental mechanisms regulating the emergence, lineage, complexification and fate of cortical germinal layers and progenitor cell types. At the cellular level, we discuss the fundamental impact of basal progenitor cells and the advent of indirect neurogenesis on the increased number and diversity of cortical neurons and layers in mammals, and on cortex folding. Finally, we discuss recent work that unveils genetic and molecular mechanisms underlying this progressive expansion and increased complexity of the amniote cerebral cortex during evolution, with a particular focus on those leading to human-specific features. Whereas new genes important in human brain development emerged the recent hominid lineage, regulation of the patterns and levels of activity of highly conserved signaling pathways are beginning to emerge as mechanisms of central importance in the evolutionary increase in cortical size and complexity across amniotes., Work in our lab is funded by the Spanish Ministry of Science, Innovation and Universities (SAF2015-69168-R; SAF2017-92781-EXP; PGC2018-102172-B-I00), Consejo Superior de Investigaciones Científicas (201820E129) and the “Severo Ochoa” Programme for Centers of Excellence in Research and Development (Reference SEV-2017-0723).

Here we focus on understanding mechanisms that drive dynamic changes in gene expression and epigenetic marks that enable triple negative breast cancer cells to change states, and to thereby invade tissues and seed secondary tumors. The epithelial-to-mesenchymal transition (EMT) facilitates invasion and migration away from the primary tumor site. However, it is increasingly apparent that the reverse process, the mesenchymal-to-epithelial transition (MET), enhances metastatic colonization and growth via reacquisition of the epithelial phenotype. With no therapies currently available to stop metastatic tumor growth, we aim to uncover the mechanisms driving the MET towards identifying novel anti-metastatic therapies. We use the 3D in vitro mammosphere model system where single tumor-initiating cells residing in a partial-EMT state develop into a 3D organoid over 30 days. We sampled cells at 5 time points and performed scRNA-seq and scATAC-seq to analyze cell states. We develop a novel computational model of cellular development based on the theory of dynamic optimal transport (OT) and continuous normalizing flows. Our model TrajectoryNet is a neural ODE (ordinary differential equation) network that models the gradient of cell state with respect to time continuously over the input space and over time from cross-sectional single-cell data. TrajectoryNet interpolates between collected timepoints and learns a continuous realistic progression that describes cellular evolution in terms of gene expression and chromatin accessibility. Key to TrajectoryNet is a unique regularization to penalize the magnitude of the gradient over the flow. We prove this results in dynamic OT, thereby discouraging the neural network from taking circuitous or unrealistic paths. In contrast to TrajectoryNet, pseudotime, and RNA velocity are best at analyzing within a particular timepoint and do not handle large gaps in timepoints. We compare TrajectoryNet to RNA velocity and static OT and show that TrajectoryNet achieves better trajectories in terms of predicting withheld timepoints. Using TrajectoryNet, we identify a continuous ordering of events that occur during MET that show when and how the epithelial cell states begin to emerge. Such a continuous ordering can give rise to causal associations that can be inhibited to alter MET mechanisms. We also differentiate between trajectories that show self-renewal and maintenance of the tumor-initiating cells, and trajectories that revert to an epithelial state. Further we find that only ~10% of the initial seeded cells develop into mammospheres and identify which initial cells have the potential to seed secondary tumors. Hence, we can refine features (gene and epigenetic states) that define aggressive tumor-initiating cells in triple negative breast cancer, as well as their dynamics through the MET in order to find therapeutic targets. Citation Format: Alexander Tong, Beatriz P. San Juan, Brandon Zhu, Christine L. Chaffer, Smita Krishnaswamy. Understanding the mesenchymal-to-epithelial transition and its drivers in triple-negative breast cancer with continuous normalizing flows [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2839.

Cancer is a disease of cellular evolution. For this cellular evolution to take place, a population of cells must contain functional heterogeneity and an assessment of this heterogeneity in the form of natural selection. Cancer cells from advanced malignancies are genomically and functionally very different compared to the healthy cells from which they evolved. Genomic alterations include aneuploidy (numerical and structural changes in chromosome content) and polyploidy (e.g., whole genome doubling), which can have considerable effects on cell physiology and phenotype. Likewise, conditions in the tumor microenvironment are spatially heterogeneous and vastly different than in healthy tissues, resulting in a number of environmental niches that play important roles in driving the evolution of tumor cells. While a number of studies have documented abnormal conditions of the tumor microenvironment and the cellular consequences of aneuploidy and polyploidy, a thorough overview of the interplay between karyotypically abnormal cells and the tissue and tumor microenvironments is not available. Here, we examine the evidence for how this interaction may unfold during tumor evolution. We describe a bidirectional interplay in which aneuploid and polyploid cells alter and shape the microenvironment in which they and their progeny reside; in turn, this microenvironment modulates the rate of genesis for new karyotype aberrations and selects for cells that are most fit under a given condition. We conclude by discussing the importance of this interaction for tumor evolution and the possibility of leveraging our understanding of this interplay for cancer therapy. Published version

Big-data-omics have promised the success of precision medicine. However, most common diseases belong to adaptive systems where the precision is all but difficult to achieve. In this commentary, I propose a heterogeneity-mediated cellular adaptive model to search for the general model of diseases, which also illustrates why in most non-infectious non-Mendelian diseases the involvement of cellular evolution is less predictable when gene profiles are used. This synthesis is based on the following new observations/concepts: 1) the gene only codes "parts inheritance" while the genome codes "system inheritance" or the entire blueprint; 2) the nature of somatic genetic coding is fuzzy rather than precise, and genetic alterations are not just the results of genetic error but are in fact generated from internal adaptive mechanisms in response to environmental dynamics; 3) stress-response is less specific within cellular evolutionary context when compared to known biochemical specificities; and 4) most medical interventions have their unavoidable uncertainties and often can function as negative harmful stresses as trade-offs. The acknowledgment of diseases as adaptive systems calls for the action to integrate genome- (not simply individual gene-) mediated cellular evolution into molecular medicine.

Why do we get cancer? Why is cancer highly associated with old age? Of course, aging is associated with the accumulation of more mutations, and some of these mutations can contribute to cancer phenotypes. But we now understand that carcinogenesis is much more complex than originally appreciated. In particular, there are tissue environmental forces that both impede and promote cancer evolution. Just as organismal evolution is known to be driven by environmental changes, cellular (somatic) evolution in our bodies is similarly driven by changes in tissue environments, whether caused by the normal process of aging, by lifestyle choices or by extrinsic exposures. Environmental change promotes selection for new phenotypes that are adaptive to the new context. In our tissues, aging or insult-driven alterations in tissues drives selection for adaptive mutations, and some of these mutations can confer malignant phenotypes. We have been using mouse models of cancer initiation, mathematical models of cellular evolution, and analyses of human tissue samples to better understand the evolutionary forces that control somatic cell evolution and thus cancer risk. We have shown that aging and inflammation dependent changes in tissue environments dramatically dictate whether cancer-causing mutations are advantageous to stem cells in our tissues, starting the cells down the path to cancer. Our studies have focused on cancer initiation within the hematopoietic system and the lung. These studies have also uncovered molecular explanations for mutation-driven adaptation to aged and inflammatory tissue environments. In all, these studies indicate that strategies to prevent or treat cancers will need to incorporate interventions that alter tissue microenvironments. While we largely cannot prevent mutation accumulation through our lives, we do have the ability to manipulate tissue environments so as to change the evolutionary trajectories of cells with cancer-causing mutations. Citation Format: Catherine Pham-Danis, Andrii Rozhok, Hannah Scarborough, Nathaniel Little, Curtis Henry, Travis Nemkov, Kirk Hansen, James DeGregori. In the light of evolution: Why do we get more cancers in old age? [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr IA13.

One of the key differences between Bacteria and Archaea is their canonical membrane phospholipids, which are synthesized by distinct biosynthetic pathways with nonhomologous enzymes. This “lipid divide” has important implications for the early evolution of cells and the type of membrane phospholipids present in the last universal common ancestor. One of the main challenges in studies of membrane evolution is that the key biosynthetic genes are ancient and their evolutionary histories are poorly resolved. This poses major challenges for traditional rooting methods because the only available outgroups are distantly related. Here, we address this issue by using the best available substitution models for single-gene trees, by expanding our analyses to the diversity of uncultivated prokaryotes recently revealed by environmental genomics, and by using two complementary approaches to rooting that do not depend on outgroups. Consistent with some previous analyses, our rooted gene trees support extensive interdomain horizontal transfer of membrane phospholipid biosynthetic genes, primarily from Archaea to Bacteria. They also suggest that the capacity to make archaeal-type membrane phospholipids was already present in last universal common ancestor.

The role and extent of horizontal gene transfer (HGT) in eukaryotes are hotly disputed topics that impact our understanding regarding the origin of metabolic processes and the role of organelles in cellular evolution. We addressed this issue by analyzing 10 novel Cyanidiales genomes and determined that 1% of their gene inventory is HGT-derived. Numerous HGT candidates originated from polyextremophilic prokaryotes that live in similar habitats as the Cyanidiales and encodes functions related to polyextremophily. HGT candidates differ from native genes in GC-content, number of splice sites, and gene expression. HGT candidates are more prone to loss, which may explain the nonexistence of a eukaryotic pan-genome. Therefore, absence of a pan-genome and cumulative effects fail to provide substantive arguments against our hypothesis of recurring HGT followed by differential loss in eukaryotes. The maintenance of 1% HGTs, even under selection for genome reduction underlines the importance of non-endosymbiosis related foreign gene acquisition.

We define convergent evolution as the repeated and independent emergence of a given adaptive trait in two or more lineages whose last common ancestor did not possess the respective character. The genomic basis of convergent evolution is not well understood but constitutes a decisive element in understanding its origins, prevalence, and adaptive value throughout the three domains of life. Recent studies indicate that convergent evolution is actually occurring on the molecular sequence level and, indeed, genome-wide at multiple loci in many instances. So far, a number of different mechanisms for genome evolution have been identified that drive an increase in biological novelty and complexity. Information and (biological) systems theory are beginning to reframe the phenomenon of convergent evolution in terms of top-down causation and resulting functional equivalence classes. Comparative genomic studies of convergent evolution will benefit from such a theoretical perspective, since convergence appears to be a fundamental property of complex adaptive systems, especially in biology and technology. Here we explore the convergent emergence of complex traits across different levels of organizational bio-complexity within a phylogenetically inspired context that is being supported by the ever-increasing wealth of available genome data. The discipline of comparative genomics is maturing into a decisive factor in the systems biology revolution of the twenty-first century by providing a computational paradigm for exploring the evolutionary sequence space across multiple levels and scales of bio-complexity.

Climate change is associated to how weather patterns change over decades or longer due to natural and human influences. Since the industrial revolution, humans have contributed to climate change through the emission of greenhouse gases and aerosols as well as changes in land use resulting in an increase in global temperature. To overcome climatic challenges, plants evolved various metabolic pathways, which is a crucial step in molecular and cellular evolution. Climate change led to evolutionary divergence, thus, genes coding for new metabolic abilities emerged. However, the pace of the present and future trajectory indicate the possibility of disruptive responses of plants unlike what evolutionary history has revealed.

Most cellular features have a range of states, but understanding the mechanisms responsible for interspecific divergence is a challenge for evolutionary cell biology. Models are developed for the distribution of mean phenotypes likely to evolve under the joint forces of mutation and genetic drift in the face of constant selection pressures. Mean phenotypes will deviate from optimal states to a degree depending on the effective population size, potentially leading to substantial divergence in the absence of diversifying selection. The steady-state distribution for the mean can even be bimodal, with one domain being largely driven by selection and the other by mutation pressure, leading to the illusion of phenotypic shifts being induced by movement among alternative adaptive domains. These results raise questions as to whether lineage-specific selective pressures are necessary to account for interspecific divergence, providing a possible platform for the establishment of null models for the evolution of cell-biological traits., eLife digest When most people think about evolution, they commonly think of natural selection: the evolutionary force that helps populations to develop toward an optimum state for their environment. The observable traits and features of a cell or organism are known as its phenotype. Under natural selection, genes that produce phenotypes that help a cell or organism to thrive and reproduce are more likely to be passed on to future generations. This means that over several generations the population becomes – on average – better adapted to its environment. Other ‘non-adaptive’ evolutionary forces also influence phenotype. For example, damage to DNA can introduce mutations into the genes that a cell or organism passes on to their offspring. Some mutations are more likely to produce working variants of a gene than others; this is known as a mutation bias. In addition, even in the absence of natural selection, the proportion of particular gene variants in a population changes over the generations because genes are randomly transmitted and not all individuals reproduce. This is known as genetic drift. Together, mutation bias and genetic drift could prevent a population’s average phenotype from reaching an optimal state. Lynch has now developed mathematical models that describe how certain biological features of cells – such as the structure of the proteins they produce – are likely to evolve due to mutation bias and genetic drift. These models show that these evolutionary processes can cause the features of the cells in a population to diversify, which often leads to a suboptimal average phenotype. Lynch calculated that two alternative phenotypes could even emerge in isolated populations in cases where there is only one optimum phenotype. For example, a mutation bias could drive some cells in one population to evolve one phenotype, while natural selection drives another population towards the other phenotype. Overall, the model emphasizes that natural selection is not the only force that drives diversity in cells. Future research into cell biology needs to take a broad view of the joint roles played by natural selection, mutation bias and genetic drift.

One of the key differences between Bacteria and Archaea are their canonical membrane phospholipids, which are synthesized by distinct biosynthetic pathways with non-homologous enzymes. This “lipid divide” has important implications for the early evolution of cells and the type of membrane phospholipids present in the last universal common ancestor (LUCA). One of the main challenges in studies of membrane evolution is that the key biosynthetic genes are ancient and their evolutionary histories are poorly resolved. This poses major challenges for traditional rooting methods because the only available outgroups are distantly related. Here, we address this issue by using the best available substitution models for single gene trees, by expanding our analyses to the diversity of uncultivated prokaryotes recently revealed by environmental genomics, and by using two complementary approaches to rooting that do not depend on outgroups. Consistent with some previous analyses, our rooted gene trees support extensive inter-domain horizontal transfer of membrane phospholipid biosynthetic genes, primarily from Archaea to Bacteria. They also suggest that the capacity to make archaeal-type membrane phospholipids was already present in LUCA.

The significance of experiments that claim to simulate the properties of prebiotic small peptides and polypeptides as models of the polymers that may have preceded proteins is critically addressed. As discussed here, most of these experiments are based only on a small number of a larger set of amino acids that may have been present in the prebiotic environment, supported by both experimental simulations and the repertoire of organic compounds reported in carbonaceous chondrites. Model experiments with small peptides may offer some insights into the processes that contributed to generate the chemical environment leading to the emergence of informational oligomers, but not to the origin of proteins. The large body of circumstantial evidence indicating that catalytic RNA played a key role in the origin of protein synthesis during the early stages of cellular evolution implies that the emergence of the genetic code and of protein biosynthesis are no longer synonymous with the origin of life. Hence, reports on the abiotic synthesis of small catalytic peptides under potential prebiotic conditions do not provide information on the origin of triplet encoded protein biosynthesis, but in some cases may serve as models to understand the properties of the earliest proteins.

Cells from the three domains of life produce extracellular membrane vesicles (EMVs), suggesting that EMV production is an important aspect of cellular physiology. EMVs have been implicated in many aspects of cellular life in all domains, including stress response, toxicity against competing strains, pathogenicity, detoxification and resistance against viral attack. These EMVs represent an important mode of inter-cellular communication by serving as vehicles for transfer of DNA, RNA, proteins and lipids between cells. Here, we review recent progress in the understanding of EMV biology and their various roles. We focus on the role of membrane vesicles in early cellular evolution and how they would have helped shape the nature of the last universal common ancestor. A membrane-protected micro-environment would have been a key to the survival of spontaneous molecular systems and efficient metabolic reactions. Interestingly, the morphology of EMVs is strongly reminiscent of the morphology of some virions. It is thus tempting to make a link between the origin of the first protocell via the formation of vesicles and the origin of viruses.

Eukaryotic cells, with complex features such as membrane-bound nuclei, evolved from prokaryotic cells that lack these components. A newly identified prokaryotic group reveals intermediate steps in eukaryotic-cell evolution. See Article p.353 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.

The cells of malignant cancers result in the evolution of cells with stem-like characteristics, commonly known as cancer stem cells (CSCs). Progress of anticancer therapies is severely hampered because of disease relapse mostly in a more aggressive form due to CSCs. These CSCs are more or less like embryonic or tissue stem cells, known for their capacity of self-renewal, exactly recapitulate of the original tumor. Deregulation of key stem cell pathways like Wnt, Hedgehog (Hh), and Notch is attributed towards the rise of CSCs. Recent breakthroughs offer better insights into CSC signaling. Scientists have developed several combinatorial therapies like targeting one/multiple of these CSC pathways. The article summarized various markers used to identify CSCs and discuss major signaling pathways in them. The futuristic probabilities to use CSC therapeutics in clinical development have been discussed. Our views have been highlighted on the future directions for targeting advances in the clinical development.

Viruses are the most abundant biological entities on modern Earth. They are highly diverse both in structure and genomic sequence, play critical roles in evolution, strongly influence terran biogeochemistry, and are believed to have played important roles in the origin and evolution of life. However, there is yet very little focus on viruses in astrobiology. Viruses arguably have coexisted with cellular life-forms since the earliest stages of life, may have been directly involved therein, and have profoundly influenced cellular evolution. Viruses are the only entities on modern Earth to use either RNA or DNA in both single- and double-stranded forms for their genetic material and thus may provide a model for the putative RNA-protein world. With this review, we hope to inspire integration of virus research into astrobiology and also point out pressing unanswered questions in astrovirology, particularly regarding the detection of virus biosignatures and whether viruses could be spread extraterrestrially. We present basic virology principles, an inclusive definition of viruses, review current virology research pertinent to astrobiology, and propose ideas for future astrovirology research foci. Key Words: Astrobiology-Virology-Biosignatures-Origin of life-Roadmap. Astrobiology 18, 207-223.

While the core of cancer research is concerned with molecular cell biology, principles from the fields of population dynamics and evolutionary biology can provide important, complementary insights that can improve our understanding of disease development and therapy outcomes. Cell division and death processes, mutations, and selection are central to carcinogenesis, the response to treatment, and the evolution of drug resistance. Mathematical models have become an increasingly important tool to study these dynamical interactions and evolutionary processes, allowing us to capture a set of biological assumptions and to follow them to their logical conclusions. This review discusses different ways in which mathematical models can be useful in cancer research: mathematical models can lead to the formulation of new concepts; application of mathematical models to clinical data can allow us to estimate central kinetic parameters; and parameterized mathematical models can be used to make predictions about disease and therapy outcomes. Examples of these approaches will be discussed in the context of case studies from our own research and brought into context with the broader oncology literature. The first half of the review is concerned with dynamical and evolutionary processes that contribute to the development of cancer, while the second part concentrates on the dynamics and evolution of cells during therapeutic and preventative interventions. We will explore, how mathematical models and clinical data can be combined to make patient-specific predictions about treatment outcomes.

The origin and evolution of viruses remain mysterious. Here, we focus on the distribution of viral replicons in host organisms, their morphological features, and the evolution of highly conserved protein and nucleic acid structures. The apparent inability of RNA viral replicons to infect contemporary akaryotic species suggests an early origin of RNA viruses and their subsequent loss in akaryotes. A census of virion morphotypes reveals that advanced forms were unique to viruses infecting a specific supergroup, while simpler forms were observed in viruses infecting organisms in all forms of cellular life. Results hint toward an ancient origin of viruses from an ancestral virus harboring either filamentous or spherical virions. Finally, phylogenetic trees built from protein domain and tRNA structures in thousands of genomes suggest that viruses evolved via reductive evolution from ancient cells. The analysis presents a complete account of the evolutionary history of cells and viruses and identifies viruses as crucial agents influencing cellular evolution.

A key question in evolutionary biology is to explain the causes and consequences of the so-called “major transitions in evolution,” which resulted in the progressive evolution of cells, organisms, and animal societies (1⇓–3). Several studies, for example, have now aimed to determine which suite of adaptive changes occurred following the evolution of sociality in insects (4). In this context, a long-standing hypothesis is that the evolution of the spectacular sociality seen in insects, such as ants, bees, or wasps, should have gone hand in hand with the evolution of more complex chemical communication systems, to allow them to coordinate their complex social behavior (5). Indeed, whereas solitary insects are known to use pheromone signals mainly in the context of mate attraction and species-recognition, social insects use chemical signals in a wide variety of contexts: to communicate their caste or reproductive status, recognize nestmates from invaders, mark the way to food sources, or alarm nestmates about imminent danger (5). Well-controlled studies of the change in investment in chemical communication systems in highly eusocial insects, such as ants, termites, or Corbiculate bees, however, have proven hard to conduct, because eusociality in these taxa evolved long ago in the Cretaceous (6) and closely related solitary species are no longer around (Fig. 1). In PNAS, Wittwer et al. (7) now provide an elegant solution to this problem. By studying Halictinae sweat bees—a group of primitively eusocial insects that evolved sociality more recently and on several occasions reverted back to a solitary lifestyle (8) (Fig. 1)—they succeed in making an accurate comparison of the investment in chemosensory systems made by social and derived, closely related, nonsocial species. Fig. 1. Cladogram showing the independent origins and secondary losses of sociality in the Hymenoptera (after refs. 6 and 20⇓⇓⇓–24). For clarity, … [↵][1]1To whom correspondence should be addressed. Email: tom.wenseleers{at}kuleuven.be. [1]: #xref-corresp-1-1

Micronuclei research has regained its popularity due to the realization that genome chaos, a rapid and massive genome re-organization under stress, represents a major common mechanism for punctuated cancer evolution. The molecular link between micronuclei and chromothripsis (one subtype of genome chaos which has a selection advantage due to the limited local scales of chromosome re-organization), has recently become a hot topic, especially since the link between micronuclei and immune activation has been identified. Many diverse molecular mechanisms have been illustrated to explain the causative relationship between micronuclei and genome chaos. However, the newly revealed complexity also causes confusion regarding the common mechanisms of micronuclei and their impact on genomic systems. To make sense of these diverse and even conflicting observations, the genome theory is applied in order to explain a stress mediated common mechanism of the generation of micronuclei and their contribution to somatic evolution by altering the original set of information and system inheritance in which cellular selection functions. To achieve this goal, a history and a current new trend of micronuclei research is briefly reviewed, followed by a review of arising key issues essential in advancing the field, including the re-classification of micronuclei and how to unify diverse molecular characterizations. The mechanistic understanding of micronuclei and their biological function is re-examined based on the genome theory. Specifically, such analyses propose that micronuclei represent an effective way in changing the system inheritance by altering the coding of chromosomes, which belongs to the common evolutionary mechanism of cellular adaptation and its trade-off. Further studies of the role of micronuclei in disease need to be focused on the behavior of the adaptive system rather than specific molecular mechanisms that generate micronuclei. This new model can clarify issues important to stress induced micronuclei and genome instability, the formation and maintenance of genomic information, and cellular evolution essential in many common and complex diseases such as cancer.