Evolutionary Landscapes of Host-Virus Arms Races.

Vertebrate immune systems suppress viral infection using both innate restriction factors and adaptive immunity. Viruses mutate to escape these defenses, driving hosts to counterevolve to regain fitness. This cycle recurs repeatedly, resulting in an evolutionary arms race whose outcome depends on the pace and likelihood of adaptation by host and viral genes. Although viruses evolve faster than their vertebrate hosts, their proteins are subject to numerous functional constraints that impact the probability of adaptation. These constraints are globally defined by evolutionary landscapes, which describe the fitness and adaptive potential of all possible mutations. We review deep mutational scanning experiments mapping the evolutionary landscapes of both host and viral proteins engaged in arms races. For restriction factors and some broadly neutralizing antibodies, landscapes favor the host, which may help to level the evolutionary playing field against rapidly evolving viruses. We discuss the biophysical underpinnings of these landscapes and their therapeutic implications.

Global epistasis and the emergence of function in microbial consortia.

The many functions of microbial communities emerge from a complex web of interactions between organisms and their environment. This poses a significant obstacle to engineering microbial consortia, hindering our ability to harness the potential of microorganisms for biotechnological applications. In this study, we demonstrate that the collective effect of ecological interactions between microbes in a community can be captured by simple statistical models that predict how adding a new species to a community will affect its function. These predictive models mirror the patterns of global epistasis reported in genetics, and they can be quantitatively interpreted in terms of pairwise interactions between community members. Our results illuminate an unexplored path to quantitatively predicting the function of microbial consortia from their composition, paving the way to optimizing desirable community properties and bringing the tasks of predicting biological function at the genetic, organismal, and ecological scales under the same quantitative formalism.

A synthetic differentiation circuit in Escherichia coli for suppressing mutant takeover.

Differentiation is crucial for multicellularity. However, it is inherently susceptible to mutant cells that fail to differentiate. These mutants outcompete normal cells by excessive self-renewal. It remains unclear what mechanisms can resist such mutant expansion. Here, we demonstrate a solution by engineering a synthetic differentiation circuit in Escherichia coli that selects against these mutants via a biphasic fitness strategy. The circuit provides tunable production of synthetic analogs of stem, progenitor, and differentiated cells. It resists mutations by coupling differentiation to the production of an essential enzyme, thereby disadvantaging non-differentiating mutants. The circuit selected for and maintained a positive differentiation rate in long-term evolution. Surprisingly, this rate remained constant across vast changes in growth conditions. We found that transit-amplifying cells (fast-growing progenitors) underlie this environmental robustness. Our results provide insight into the stability of differentiation and demonstrate a powerful method for engineering evolutionarily stable multicellular consortia.

Discovery of a Regulatory Subunit of the Yeast Fatty Acid Synthase.

Fatty acid synthases (FASs) are central to metabolism but are also of biotechnological interest for the production of fine chemicals and biofuels from renewable resources. During fatty acid synthesis, the growing fatty acid chain is thought to be shuttled by the dynamic acyl carrier protein domain to several enzyme active sites. Here, we report the discovery of a γ subunit of the 2.6 megadalton α6-ß6S. cerevisiae FAS, which is shown by high-resolution structures to stabilize a rotated FAS conformation and rearrange ACP domains from equatorial to axial positions. The γ subunit spans the length of the FAS inner cavity, impeding reductase activities of FAS, regulating NADPH turnover by kinetic hysteresis at the ketoreductase, and suppressing off-pathway reactions at the enoylreductase. The γ subunit delineates the functional compartment within FAS. As a scaffold, it may be exploited to incorporate natural and designed enzymatic activities that are not present in natural FAS.

A Common Embryonic Origin of Stem Cells Drives Developmental and Adult Neurogenesis.

New neurons arise from quiescent adult neural progenitors throughout life in specific regions of the mammalian brain. Little is known about the embryonic origin and establishment of adult neural progenitors. Here, we show that Hopx+ precursors in the mouse dentate neuroepithelium at embryonic day 11.5 give rise to proliferative Hopx+ neural progenitors in the primitive dentate region, and they, in turn, generate granule neurons, but not other neurons, throughout development and then transition into Hopx+ quiescent radial glial-like neural progenitors during an early postnatal period. RNA-seq and ATAC-seq analyses of Hopx+ embryonic, early postnatal, and adult dentate neural progenitors further reveal common molecular and epigenetic signatures and developmental dynamics. Together, our findings support a "continuous" model wherein a common neural progenitor population exclusively contributes to dentate neurogenesis throughout development and adulthood. Adult dentate neurogenesis may therefore represent a lifelong extension of development that maintains heightened plasticity in the mammalian hippocampus.

The Molecular Basis of G Protein-Coupled Receptor Activation.

G protein-coupled receptors (GPCRs) mediate the majority of cellular responses to external stimuli. Upon activation by a ligand, the receptor binds to a partner heterotrimeric G protein and promotes exchange of GTP for GDP, leading to dissociation of the G protein into α and ßγ subunits that mediate downstream signals. GPCRs can also activate distinct signaling pathways through arrestins. Active states of GPCRs form by small rearrangements of the ligand-binding, or orthosteric, site that are amplified into larger conformational changes. Molecular understanding of the allosteric coupling between ligand binding and G protein or arrestin interaction is emerging from structures of several GPCRs crystallized in inactive and active states, spectroscopic data, and computer simulations. The coupling is loose, rather than concerted, and agonist binding does not fully stabilize the receptor in an active conformation. Distinct intermediates whose populations are shifted by ligands of different efficacies underlie the complex pharmacology of GPCRs.

Analysis of Genetically Diverse Macrophages Reveals Local and Domain-wide Mechanisms that Control Transcription Factor Binding and Function.

Non-coding genetic variation is a major driver of phenotypic diversity and allows the investigation of mechanisms that control gene expression. Here, we systematically investigated the effects of >50 million variations from five strains of mice on mRNA, nascent transcription, transcription start sites, and transcription factor binding in resting and activated macrophages. We observed substantial differences associated with distinct molecular pathways. Evaluating genetic variation provided evidence for roles of ∼100 TFs in shaping lineage-determining factor binding. Unexpectedly, a substantial fraction of strain-specific factor binding could not be explained by local mutations. Integration of genomic features with chromatin interaction data provided evidence for hundreds of connected cis-regulatory domains associated with differences in transcription factor binding and gene expression. This system and the >250 datasets establish a substantial new resource for investigation of how genetic variation affects cellular phenotypes.

Hypoxic niches attract and sequester tumor-associated macrophages and cytotoxic T cells and reprogram them for immunosuppression.

Glioblastoma (GBM), a highly lethal brain cancer, is notorious for immunosuppression, but the mechanisms remain unclear. Here, we documented a temporospatial patterning of tumor-associated myeloid cells (TAMs) corresponding to vascular changes during GBM progression. As tumor vessels transitioned from the initial dense regular network to later scant and engorged vasculature, TAMs shifted away from perivascular regions and trafficked to vascular-poor areas. This process was heavily influenced by the immunocompetence state of the host. Utilizing a sensitive fluorescent UnaG reporter to track tumor hypoxia, coupled with single-cell transcriptomics, we revealed that hypoxic niches attracted and sequestered TAMs and cytotoxic T lymphocytes (CTLs), where they were reprogrammed toward an immunosuppressive state. Mechanistically, we identified chemokine CCL8 and cytokine IL-1ß as two hypoxic-niche factors critical for TAM trafficking and co-evolution of hypoxic zones into pseudopalisading patterns. Therefore, perturbation of TAM patterning in hypoxic zones may improve tumor control.

Systematic conformation-to-phenotype mapping via limited deep sequencing of proteins.

Non-native conformations drive protein-misfolding diseases, complicate bioengineering efforts, and fuel molecular evolution. No current experimental technique is well suited for elucidating them and their phenotypic effects. Especially intractable are the transient conformations populated by intrinsically disordered proteins. We describe an approach to systematically discover, stabilize, and purify native and non-native conformations, generated in vitro or in vivo, and directly link conformations to molecular, organismal, or evolutionary phenotypes. This approach involves high-throughput disulfide scanning (HTDS) of the entire protein. To reveal which disulfides trap which chromatographically resolvable conformers, we devised a deep-sequencing method for double-Cys variant libraries of proteins that precisely and simultaneously locates both Cys residues within each polypeptide. HTDS of the abundant E. coli periplasmic chaperone HdeA revealed distinct classes of disordered hydrophobic conformers with variable cytotoxicity depending on where the backbone was cross-linked. HTDS can bridge conformational and phenotypic landscapes for many proteins that function in disulfide-permissive environments.

Germline genetic contribution to the immune landscape of cancer.

Understanding the contribution of the host's genetic background to cancer immunity may lead to improved stratification for immunotherapy and to the identification of novel therapeutic targets. We investigated the effect of common and rare germline variants on 139 well-defined immune traits in ∼9000 cancer patients enrolled in TCGA. High heritability was observed for estimates of NK cell and T cell subset infiltration and for interferon signaling. Common variants of IFIH1, TMEM173 (STING1), and TMEM108 were associated with differential interferon signaling and variants mapping to RBL1 correlated with T cell subset abundance. Pathogenic or likely pathogenic variants in BRCA1 and in genes involved in telomere stabilization and Wnt-ß-catenin also acted as immune modulators. Our findings provide evidence for the impact of germline genetics on the composition and functional orientation of the tumor immune microenvironment. The curated datasets, variants, and genes identified provide a resource toward further understanding of tumor-immune interactions.

A Conserved Noncoding Locus Regulates Random Monoallelic Xist Expression across a Topological Boundary.

cis-Regulatory communication is crucial in mammalian development and is thought to be restricted by the spatial partitioning of the genome in topologically associating domains (TADs). Here, we discovered that the Xist locus is regulated by sequences in the neighboring TAD. In particular, the promoter of the noncoding RNA Linx (LinxP) acts as a long-range silencer and influences the choice of X chromosome to be inactivated. This is independent of Linx transcription and independent of any effect on Tsix, the antisense regulator of Xist that shares the same TAD as Linx. Unlike Tsix, LinxP is well conserved across mammals, suggesting an ancestral mechanism for random monoallelic Xist regulation. When introduced in the same TAD as Xist, LinxP switches from a silencer to an enhancer. Our study uncovers an unsuspected regulatory axis for X chromosome inactivation and a class of cis-regulatory effects that may exploit TAD partitioning to modulate developmental decisions.

Dominance and multi-locus interaction.

Dominance is usually considered a constant value that describes the relative difference in fitness or phenotype between heterozygotes and the average of homozygotes at a focal polymorphic locus. However, the observed dominance can vary with the genetic background of the focal locus. Here, alleles at other loci modify the observed phenotype through position effects or dominance modifiers that are sometimes associated with pathogen resistance, lineage, sex, or mating type. Theoretical models have illustrated how variable dominance appears in the context of multi-locus interaction (epistasis). Here, we review empirical evidence for variable dominance and how the observed patterns may be captured by proposed epistatic models. We highlight how integrating epistasis and dominance is crucial for comprehensively understanding adaptation and speciation.

A geometrical model of cell fate specification in the mouse blastocyst.

The lineage decision that generates the epiblast and primitive endoderm from the inner cell mass (ICM) is a paradigm for cell fate specification. Recent mathematics has formalized Waddington's landscape metaphor and proven that lineage decisions in detailed gene network models must conform to a small list of low-dimensional stereotypic changes called bifurcations. The most plausible bifurcation for the ICM is the so-called heteroclinic flip that we define and elaborate here. Our re-analysis of recent data suggests that there is sufficient cell movement in the ICM so the FGF signal, which drives the lineage decision, can be treated as spatially uniform. We thus extend the bifurcation model for a single cell to the entire ICM by means of a self-consistently defined time-dependent FGF signal. This model is consistent with available data and we propose additional dynamic experiments to test it further. This demonstrates that simplified, quantitative and intuitively transparent descriptions are possible when attention is shifted from specific genes to lineages. The flip bifurcation is a very plausible model for any situation where the embryo needs control over the relative proportions of two fates by a morphogen feedback.

A mathematical framework for measuring and tuning tempo in developmental gene regulatory networks.

Embryo development is a dynamic process governed by the regulation of timing and sequences of gene expression, which control the proper growth of the organism. Although many genetic programmes coordinating these sequences are common across species, the timescales of gene expression can vary significantly among different organisms. Currently, substantial experimental efforts are focused on identifying molecular mechanisms that control these temporal aspects. In contrast, the capacity of established mathematical models to incorporate tempo control while maintaining the same dynamical landscape remains less understood. Here, we address this gap by developing a mathematical framework that links the functionality of developmental programmes to the corresponding gene expression orbits (or landscapes). This unlocks the ability to find tempo differences as perturbations in the dynamical system that preserve its orbits. We demonstrate that this framework allows for the prediction of molecular mechanisms governing tempo, through both numerical and analytical methods. Our exploration includes two case studies: a generic network featuring coupled production and degradation, with a particular application to neural progenitor differentiation; and the repressilator. In the latter, we illustrate how altering the dimerisation rates of transcription factors can decouple the tempo from the shape of the resulting orbits. We conclude by highlighting how the identification of orthogonal molecular mechanisms for tempo control can inform the design of circuits with specific orbits and tempos.

Local vs. cooperative: Unraveling glass transition mechanisms with SEER.

Which phenomenon slows down the dynamics in supercooled liquids and turns them into glasses is a long-standing question of condensed matter. Most popular theories posit that as the temperature decreases, many events must occur in a coordinated fashion on a growing length scale for relaxation to occur. Instead, other approaches consider that local barriers associated with the elementary rearrangement of a few particles or "excitations" govern the dynamics. To resolve this conundrum, our central result is to introduce an algorithm, Systematic Excitation ExtRaction, which can systematically extract hundreds of excitations and their energy from any given configuration. We also provide a measurement of the activation energy, characterizing the liquid dynamics, based on fast quenching and reheating. We use these two methods in a popular liquid model of polydisperse particles. Such polydisperse models are known to capture the hallmarks of the glass transition and can be equilibrated efficiently up to millisecond time scales. The analysis reveals that cooperative effects do not control the fragility of such liquids: the change of energy of local barriers determines the change of activation energy. More generally, these methods can now be used to measure the degree of cooperativity of any liquid model.

Reassessing the exon-foldon correspondence using frustration analysis.

Protein folding and evolution are intimately linked phenomena. Here, we revisit the concept of exons as potential protein folding modules across a set of 38 abundant and conserved protein families. Taking advantage of genomic exon-intron organization and extensive protein sequence data, we explore exon boundary conservation and assess the foldon-like behavior of exons using energy landscape theoretic measurements. We found deviations in the exon size distribution from exponential decay indicating selection in evolution. We show that when taken together there is a pronounced tendency to independent foldability for segments corresponding to the more conserved exons, supporting the idea of exon-foldon correspondence. While 45% of the families follow this general trend when analyzed individually, there are some families for which other stronger functional determinants, such as preserving frustrated active sites, may be acting. We further develop a systematic partitioning of protein domains using exon boundary hotspots, showing that minimal common exons correspond with uninterrupted alpha and/or beta elements for the majority of the families but not for all of them.

Landscape fragmentation overturns classical metapopulation thinking.

Habitat loss and isolation caused by landscape fragmentation represent a growing threat to global biodiversity. Existing theory suggests that the process will lead to a decline in metapopulation viability. However, since most metapopulation models are restricted to simple networks of discrete habitat patches, the effects of real landscape fragmentation, particularly in stochastic environments, are not well understood. To close this major gap in ecological theory, we developed a spatially explicit, individual-based model applicable to realistic landscape structures, bridging metapopulation ecology and landscape ecology. This model reproduced classical metapopulation dynamics under conventional model assumptions, but on fragmented landscapes, it uncovered general dynamics that are in stark contradiction to the prevailing views in the ecological and conservation literature. Notably, fragmentation can give rise to a series of dualities: a) positive and negative responses to environmental noise, b) relative slowdown and acceleration in density decline, and c) synchronization and desynchronization of local population dynamics. Furthermore, counter to common intuition, species that interact locally ("residents") were often more resilient to fragmentation than long-ranging "migrants." This set of findings signals a need to fundamentally reconsider our approach to ecosystem management in a noisy and fragmented world.

High prevalence of PRDM9-independent recombination hotspots in placental mammals.

In many mammals, recombination events are concentrated in hotspots directed by a sequence-specific DNA-binding protein named PRDM9. Intriguingly, PRDM9 has been lost several times in vertebrates, and notably among mammals, it has been pseudogenized in the ancestor of canids. In the absence of PRDM9, recombination hotspots tend to occur in promoter-like features such as CpG islands. It has thus been proposed that one role of PRDM9 could be to direct recombination away from PRDM9-independent hotspots. However, the ability of PRDM9 to direct recombination hotspots has been assessed in only a handful of species, and a clear picture of how much recombination occurs outside of PRDM9-directed hotspots in mammals is still lacking. In this study, we derived an estimator of past recombination activity based on signatures of GC-biased gene conversion in substitution patterns. We quantified recombination activity in PRDM9-independent hotspots in 52 species of boreoeutherian mammals. We observe a wide range of recombination rates at these loci: several species (such as mice, humans, some felids, or cetaceans) show a deficit of recombination, while a majority of mammals display a clear peak of recombination. Our results demonstrate that PRDM9-directed and PRDM9-independent hotspots can coexist in mammals and that their coexistence appears to be the rule rather than the exception. Additionally, we show that the location of PRDM9-independent hotspots is relatively more stable than that of PRDM9-directed hotspots, but that PRDM9-independent hotspots nevertheless evolve slowly in concert with DNA hypomethylation.

Cryo-EM structure and functional landscape of an RNA polymerase ribozyme.

The emergence of an RNA replicase capable of self-replication is considered an important stage in the origin of life. RNA polymerase ribozymes (PR) - including a variant that uses trinucleotide triphosphates (triplets) as substrates - have been created by in vitro evolution and are the closest functional analogues of the replicase, but the structural basis for their function is poorly understood. Here we use single-particle cryogenic electron microscopy (cryo-EM) and high-throughput mutation analysis to obtain the structure of a triplet polymerase ribozyme (TPR) apoenzyme and map its functional landscape. The cryo-EM structure at 5-Å resolution reveals the TPR as an RNA heterodimer comprising a catalytic subunit and a noncatalytic, auxiliary subunit, resembling the shape of a left hand with thumb and fingers at a 70° angle. The two subunits are connected by two distinct kissing-loop (KL) interactions that are essential for polymerase function. Our combined structural and functional data suggest a model for templated RNA synthesis by the TPR holoenzyme, whereby heterodimer formation and KL interactions preorganize the TPR for optimal primer-template duplex binding, triplet substrate discrimination, and templated RNA synthesis. These results provide a better understanding of TPR structure and function and should aid the engineering of more efficient PRs.

An encompassed representation of timescale hierarchies in first-order reaction network.

Complex networks are pervasive in various fields such as chemistry, biology, and sociology. In chemistry, first-order reaction networks are represented by a set of first-order differential equations, which can be constructed from the underlying energy landscape. However, as the number of nodes increases, it becomes more challenging to understand complex kinetics across different timescales. Hence, how to construct an interpretable, coarse-graining scheme that preserves the underlying timescales of overall reactions is of crucial importance. Here, we develop a scheme to capture the underlying hierarchical subsets of nodes, and a series of coarse-grained (reduced-dimensional) rate equations between the subsets as a function of time resolution from the original reaction network. Each of the coarse-grained representations guarantees to preserve the underlying slow characteristic timescales in the original network. The crux is the construction of a lumping scheme incorporating a similarity measure in deciphering the underlying timescale hierarchy, which does not rely on the assumption of equilibrium. As an illustrative example, we apply the scheme to four-state Markovian models and Claisen rearrangement of allyl vinyl ether (AVE), and demonstrate that the reduced-dimensional representation accurately reproduces not only the slowest but also the faster timescales of overall reactions although other reduction schemes based on equilibrium assumption well reproduce the slowest timescale but fail to reproduce the second-to-fourth slowest timescales with the same accuracy. Our scheme can be applied not only to the reaction networks but also to networks in other fields, which helps us encompass their hierarchical structures of the complex kinetics over timescales.