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Significance A protein is a shape-shifter, but it is currently unclear which of the many structures a protein can adopt are relevant for its function. Here, we examine conformations that contain a “cryptic” pocket (i.e., a pocket absent in ligand-free structures). Cryptic pockets have potential utility in drug discovery efforts because they provide a means to target “undruggable” proteins (i.e., proteins lacking known pockets) or enhance rather than inhibit protein function. In this study, we use a combination of thiol-labeling and kinetic assays, NMR, and molecular dynamic simulations to identify the function of the Ω-loop cryptic pocket in β-lactamase enzymes. We find that an open pocket population is beneficial for hydrolysis of the substrate benzylpenicillin., Understanding the functional role of protein-excited states has important implications in protein design and drug discovery. However, because these states are difficult to find and study, it is still unclear if excited states simply result from thermal fluctuations and generally detract from function or if these states can actually enhance protein function. To investigate this question, we consider excited states in β-lactamases and particularly a subset of states containing a cryptic pocket which forms under the Ω-loop. Given the known importance of the Ω-loop and the presence of this pocket in at least two homologs, we hypothesized that these excited states enhance enzyme activity. Using thiol-labeling assays to probe Ω-loop pocket dynamics and kinetic assays to probe activity, we find that while this pocket is not completely conserved across β-lactamase homologs, those with the Ω-loop pocket have a higher activity against the substrate benzylpenicillin. We also find that this is true for TEM β-lactamase variants with greater open Ω-loop pocket populations. We further investigate the open population using a combination of NMR chemical exchange saturation transfer experiments and molecular dynamics simulations. To test our understanding of the Ω-loop pocket’s functional role, we designed mutations to enhance/suppress pocket opening and observed that benzylpenicillin activity is proportional to the probability of pocket opening in our designed variants. The work described here suggests that excited states containing cryptic pockets can be advantageous for function and may be favored by natural selection, increasing the potential utility of such cryptic pockets as drug targets.

Significance An important limiting factor for self-assembly processes is the time it takes to assemble large structures with high yield. While equilibrium self-assembly systems slowly relax toward a state of minimal free energy, nonequilibrium systems offer various ways to control assembly processes and to optimize their time efficiency. We show that these different control scenarios can informatively be characterized by their time complexity, i.e., their scaling of the assembly time with the structure size, analogous to algorithms for computational problems. Especially for large structures, differences in the time complexity of the scenarios lead to strongly diverging time efficiencies. Most significantly, we show that by effectively regulating the supply of constituents, high resource and time efficiency can be achieved for self-assembly processes., Time efficiency of self-assembly is crucial for many biological processes. Moreover, with the advances of nanotechnology, time efficiency in artificial self-assembly becomes ever more important. While structural determinants and the final assembly yield are increasingly well understood, kinetic aspects concerning the time efficiency, however, remain much more elusive. In computer science, the concept of time complexity is used to characterize the efficiency of an algorithm and describes how the algorithm’s runtime depends on the size of the input data. Here we characterize the time complexity of nonequilibrium self-assembly processes by exploring how the time required to realize a certain, substantial yield of a given target structure scales with its size. We identify distinct classes of assembly scenarios, i.e., “algorithms” to accomplish this task, and show that they exhibit drastically different degrees of complexity. Our analysis enables us to identify optimal control strategies for nonequilibrium self-assembly processes. Furthermore, we suggest an efficient irreversible scheme for the artificial self-assembly of nanostructures, which complements the state-of-the-art approach using reversible binding reactions and requires no fine-tuning of binding energies.

Significance When several sugars are at its disposition, the bacterium Escherichia coli consumes them in a specific order—a behavior called diauxie. We developed a framework combining dynamic methods and models of metabolism and gene expression to show that diauxie and its associated lag in cell growth can be explained simply as an optimal behavior under constraints on the protein amount and renewal in a cell. We validate our model by reproducing experimental results and successfully predict a diauxic behavior on a growth medium containing two types of sugar, glucose and lactose. Finally, we claim that the regulation mechanism inducing diauxie (the lac operon) is a control system to implement growth optimality at the cellular level., Diauxie, or the sequential consumption of carbohydrates in bacteria such as Escherichia coli, has been hypothesized to be an evolutionary strategy which allows the organism to maximize its instantaneous specific growth—giving the bacterium a competitive advantage. Currently, the computational techniques used in industrial biotechnology fall short of explaining the intracellular dynamics underlying diauxic behavior. In particular, the understanding of the proteome dynamics in diauxie can be improved. We developed a robust iterative dynamic method based on expression- and thermodynamically enabled flux models to simulate the kinetic evolution of carbohydrate consumption and cellular growth. With minimal modeling assumptions, we couple kinetic uptakes, gene expression, and metabolic networks, at the genome scale, to produce dynamic simulations of cell cultures. The method successfully predicts the preferential uptake of glucose over lactose in E. coli cultures grown on a mixture of carbohydrates, a manifestation of diauxie. The simulated cellular states also show the reprogramming in the content of the proteome in response to fluctuations in the availability of carbon sources, and it captures the associated time lag during the diauxie phenotype. Our models suggest that the diauxic behavior of cells is the result of the evolutionary objective of maximization of the specific growth of the cell. We propose that genetic regulatory networks, such as the lac operon in E. coli, are the biological implementation of a robust control system to ensure optimal growth.

Significance Recent experiments have suggested that the energy released by a chemical reaction can propel its enzyme catalyst (for example, alkaline phosphatase). However, this topic remains controversial, partially due to the indirect and ensemble nature of existing measurements. Here, we used recently developed single-molecule approaches to monitor directly the motions of individual proteins in aqueous solution and find that single alkaline phosphatase enzymes do not diffuse faster under catalysis. Instead, we demonstrate that interactions between the fluorescent dye and the enzyme’s substrate can produce the signature of apparent diffusion enhancement in fluorescence correlation spectroscopy, the standard ensemble assay currently used to study enzyme diffusion and indicate that single-molecule approaches provide a more robust means to investigate diffusion at the nanoscale., Theoretical and experimental observations that catalysis enhances the diffusion of enzymes have generated exciting implications about nanoscale energy flow, molecular chemotaxis, and self-powered nanomachines. However, contradictory claims on the origin, magnitude, and consequence of this phenomenon continue to arise. To date, experimental observations of catalysis-enhanced enzyme diffusion have relied almost exclusively on fluorescence correlation spectroscopy (FCS), a technique that provides only indirect, ensemble-averaged measurements of diffusion behavior. Here, using an anti-Brownian electrokinetic (ABEL) trap and in-solution single-particle tracking, we show that catalysis does not increase the diffusion of alkaline phosphatase (ALP) at the single-molecule level, in sharp contrast to the ∼20% enhancement seen in parallel FCS experiments using p-nitrophenyl phosphate (pNPP) as substrate. Combining comprehensive FCS controls, ABEL trap, surface-based single-molecule fluorescence, and Monte Carlo simulations, we establish that pNPP-induced dye blinking at the ∼10-ms timescale is responsible for the apparent diffusion enhancement seen in FCS. Our observations urge a crucial revisit of various experimental findings and theoretical models––including those of our own––in the field, and indicate that in-solution single-particle tracking and ABEL trap are more reliable means to investigate diffusion phenomena at the nanoscale.

Significance Determining the three-dimensional structures of protein complexes is critically important to guide biological research. Structural models of complexes can be built using powerful integrative approaches that combine emerging technologies in mass spectrometry, molecular modeling, and protein docking; however, preparing enriched biochemical samples suitable for analysis remains a major challenge. Here we describe serial capture affinity purification (SCAP), which can be used for the study of protein interactions in live cells and, when combined with cross-linking mass spectrometry, contribute distance restraints for integrative structural modeling. This broadly applicable technology can be used to study any protein complex in human tissue culture cells. We demonstrate SCAP capabilities on a poorly characterized epigenetic protein complex with roles in human cancer., Streamlined characterization of protein complexes remains a challenge for the study of protein interaction networks. Here we describe serial capture affinity purification (SCAP), in which two separate proteins are tagged with either the HaloTag or the SNAP-tag, permitting a multistep affinity enrichment of specific protein complexes. The multifunctional capabilities of this protein-tagging system also permit in vivo validation of interactions using acceptor photobleaching Förster resonance energy transfer and fluorescence cross-correlation spectroscopy quantitative imaging. By coupling SCAP to cross-linking mass spectrometry, an integrative structural model of the complex of interest can be generated. We demonstrate this approach using the Spindlin1 and SPINDOC protein complex, culminating in a structural model with two SPINDOC molecules docked on one SPIN1 molecule. In this model, SPINDOC interacts with the SPIN1 interface previously shown to bind a lysine and arginine methylated sequence of histone H3. Our approach combines serial affinity purification, live cell imaging, and cross-linking mass spectrometry to build integrative structural models of protein complexes.

Significance What defines the number and dynamics of the stem cells that generate and renew biological tissues? Although several molecular markers have been described to predict stem cell potential, we propose a complementary approach that mathematically describes “stemness” as an emergent property arising from a stochastic competition for space. We predict from that competition the robust emergence of a region made of functional stem cells, as well as give simple predictions on lineage-survival probability. We test our results with data obtained from intravital live-imaging experiments in mammary gland development, existing data from kidney development, and from the self-renewal of the crypt to show that our framework can predict the number of functional stem cells and lineage-survival probability., Understanding to what extent stem cell potential is a cell-intrinsic property or an emergent behavior coming from global tissue dynamics and geometry is a key outstanding question of systems and stem cell biology. Here, we propose a theory of stem cell dynamics as a stochastic competition for access to a spatially localized niche, giving rise to a stochastic conveyor-belt model. Cell divisions produce a steady cellular stream which advects cells away from the niche, while random rearrangements enable cells away from the niche to be favorably repositioned. Importantly, even when assuming that all cells in a tissue are molecularly equivalent, we predict a common (“universal”) functional dependence of the long-term clonal survival probability on distance from the niche, as well as the emergence of a well-defined number of functional stem cells, dependent only on the rate of random movements vs. mitosis-driven advection. We test the predictions of this theory on datasets of pubertal mammary gland tips and embryonic kidney tips, as well as homeostatic intestinal crypts. Importantly, we find good agreement for the predicted functional dependency of the competition as a function of position, and thus functional stem cell number in each organ. This argues for a key role of positional fluctuations in dictating stem cell number and dynamics, and we discuss the applicability of this theory to other settings.

Significance The discovery that more than 40% of the eukaryotic proteome is intrinsically disordered, and that these disordered segments are enriched in phosphorylation sites, suggests that conformational heterogeneity may be important to kinase selectivity. Indeed, phosphorylation prediction programs reliant on classic notions of conserved sequence information (i.e., “vertical information”) are only partially effective. We find that the conformational equilibrium of the phosphorylatable site, whose information is embedded in sequence-averaged energetic and structural properties of the protein (i.e., “horizontal information”), plays a major role in distinguishing phosphorylatable versus nonphosphorylatable sites. In fact, employing both horizontal and vertical information produces a state-of-the-art phosphorylation predictor, wherein the conformational equilibrium of the disordered chain is the dominant contributor., Phosphorylation sites are hyperabundant in the eukaryotic disordered proteome, suggesting that conformational fluctuations play a major role in determining to what extent a kinase interacts with a particular substrate. In biophysical terms, substrate selectivity may be determined not just by the structural–chemical complementarity between the kinase and its protein substrates but also by the free energy difference between the conformational ensembles that are, or are not, recognized by the kinase. To test this hypothesis, we developed a statistical-thermodynamics-based informatics framework, which allows us to probe for the contribution of equilibrium fluctuations to phosphorylation, as evaluated by the ability to predict Ser/Thr/Tyr phosphorylation sites in the disordered proteome. Essential to this framework is a decomposition of substrate sequence information into two types: vertical information encoding conserved kinase specificity motifs and horizontal information encoding substrate conformational equilibrium that is embedded, but often not apparent, within position-specific conservation patterns. We find not only that conformational fluctuations play a major role but also that they are the dominant contribution to substrate selectivity. In fact, the main substrate classifier distinguishing selectivity is the magnitude of change in local compaction of the disordered chain upon phosphorylation of these mostly singly phosphorylated sites. In addition to providing fundamental insights into the consequences of phosphorylation across the proteome, our approach provides a statistical-thermodynamic strategy for partitioning any sequence-based search into contributions from structural–chemical complementarity and those from changes in conformational equilibrium.

Significance DNA motors are widespread molecular machines that hydrolyze ATP to generate movement. Among them, the bacterial protein FtsK is unusual in that it translocates on double-stranded DNA and is also the fastest known translocase. However, its translocation mechanism is poorly characterized, and there is currently no structural data of an active double-stranded DNA translocase bound to its substrate. We reveal FtsK’s mechanism to be related to hexameric helicases that move on single-stranded DNA, but uniquely adapted to the double-stranded substrate. Our work also highlights the concomitant conformational changes occurring all around the hexameric ring for each step of the reaction cycle., FtsK protein contains a fast DNA motor that is involved in bacterial chromosome dimer resolution. During cell division, FtsK translocates double-stranded DNA until both dif recombination sites are placed at mid cell for subsequent dimer resolution. Here, we solved the 3.6-Å resolution electron cryo-microscopy structure of the motor domain of FtsK while translocating on its DNA substrate. Each subunit of the homo-hexameric ring adopts a unique conformation and one of three nucleotide states. Two DNA-binding loops within four subunits form a pair of spiral staircases within the ring, interacting with the two DNA strands. This suggests that simultaneous conformational changes in all ATPase domains at each catalytic step generate movement through a mechanism related to filament treadmilling. While the ring is only rotating around the DNA slowly, it is instead the conformational states that rotate around the ring as the DNA substrate is pushed through.

Significance Immune checkpoint blockade of programmed death-1 (PD-1) by monoclonal antibody drugs has transformed the treatment of cancer. Small-molecule PD-1 drugs have the potential to offer increased efficacy, safety, and global access. Despite substantial efforts, such small-molecule drugs have been out of reach. We identify a prominent pocket on the ligand-binding surface of human PD-1 that appears to be an attractive small-molecule drug target. The pocket forms when PD-1 is bound to one of its ligands, PD-L2. Our high-resolution crystal structure of the human PD-1/PD-L2 complex facilitates virtual drug-screening efforts and opens additional avenues for the design and discovery of small-molecule PD-1 inhibitors. Our work provides a strategy that may enable discovery of small-molecule inhibitors of other “undruggable” protein–protein interactions., Immune checkpoint blockade of programmed death-1 (PD-1) by monoclonal antibody drugs has delivered breakthroughs in the treatment of cancer. Nonetheless, small-molecule PD-1 inhibitors could lead to increases in treatment efficacy, safety, and global access. While the ligand-binding surface of apo-PD-1 is relatively flat, it harbors a striking pocket in the murine PD-1/PD-L2 structure. An analogous pocket in human PD-1 may serve as a small-molecule drug target, but the structure of the human complex is unknown. Because the CC′ and FG loops in murine PD-1 adopt new conformations upon binding PD-L2, we hypothesized that mutations in these two loops could be coupled to pocket formation and alter PD-1’s affinity for PD-L2. Here, we conducted deep mutational scanning in these loops and used yeast surface display to select for enhanced PD-L2 binding. A PD-1 variant with three substitutions binds PD-L2 with an affinity two orders of magnitude higher than that of the wild-type protein, permitting crystallization of the complex. We determined the X-ray crystal structures of the human triple-mutant PD-1/PD-L2 complex and the apo triple-mutant PD-1 variant at 2.0 Å and 1.2 Å resolution, respectively. Binding of PD-L2 is accompanied by formation of a prominent pocket in human PD-1, as well as substantial conformational changes in the CC′ and FG loops. The structure of the apo triple-mutant PD-1 shows that the CC′ loop adopts the ligand-bound conformation, providing support for allostery between the loop and pocket. This human PD-1/PD-L2 structure provide critical insights for the design and discovery of small-molecule PD-1 inhibitors.

Significance Comparisons among animals and their closest living relatives, the choanoflagellates, have begun to shed light on the origin of animal multicellularity and development. Here, we complement previous genetic perspectives on this process by focusing on the biophysical principles underlying choanoflagellate colony morphology and morphogenesis. Our study reveals the crucial role of the extracellular matrix in shaping the colonies and leads to a phase diagram that delineates the range of morphologies as a function of the biophysical mechanisms at play., Inspired by the patterns of multicellularity in choanoflagellates, the closest living relatives of animals, we quantify the biophysical processes underlying the morphogenesis of rosette colonies in the choanoflagellate Salpingoeca rosetta. We find that rosettes reproducibly transition from an early stage of 2-dimensional (2D) growth to a later stage of 3D growth, despite the underlying variability of the cell lineages. Our perturbative experiments demonstrate the fundamental importance of a basally secreted extracellular matrix (ECM) for rosette morphogenesis and show that the interaction of the ECM with cells in the colony physically constrains the packing of proliferating cells and, thus, controls colony shape. Simulations of a biophysically inspired model that accounts for the size and shape of the individual cells, the fraction of ECM, and its stiffness relative to that of the cells suffices to explain our observations and yields a morphospace consistent with observations across a range of multicellular choanoflagellate colonies. Overall, our biophysical perspective on rosette development complements previous genetic perspectives and, thus, helps illuminate the interplay between cell biology and physics in regulating morphogenesis.

Significance Learning biological properties from sequence data is a logical step toward generative and predictive artificial intelligence for biology. Here, we propose scaling a deep contextual language model with unsupervised learning to sequences spanning evolutionary diversity. We find that without prior knowledge, information emerges in the learned representations on fundamental properties of proteins such as secondary structure, contacts, and biological activity. We show the learned representations are useful across benchmarks for remote homology detection, prediction of secondary structure, long-range residue–residue contacts, and mutational effect. Unsupervised representation learning enables state-of-the-art supervised prediction of mutational effect and secondary structure and improves state-of-the-art features for long-range contact prediction., In the field of artificial intelligence, a combination of scale in data and model capacity enabled by unsupervised learning has led to major advances in representation learning and statistical generation. In the life sciences, the anticipated growth of sequencing promises unprecedented data on natural sequence diversity. Protein language modeling at the scale of evolution is a logical step toward predictive and generative artificial intelligence for biology. To this end, we use unsupervised learning to train a deep contextual language model on 86 billion amino acids across 250 million protein sequences spanning evolutionary diversity. The resulting model contains information about biological properties in its representations. The representations are learned from sequence data alone. The learned representation space has a multiscale organization reflecting structure from the level of biochemical properties of amino acids to remote homology of proteins. Information about secondary and tertiary structure is encoded in the representations and can be identified by linear projections. Representation learning produces features that generalize across a range of applications, enabling state-of-the-art supervised prediction of mutational effect and secondary structure and improving state-of-the-art features for long-range contact prediction.

Significance Genomic DNA must be compacted to fit in the cell but must simultaneously remain accessible for transcription. While genome organization influences gene expression, the impact of transcription on genome organization remains to be understood. The process of “loop extrusion” is central to chromosome organization. In bacteria, the condensin SMC complex performs extrusion by translocating along arms of the chromosome. During translocation, condensins encounter bulky transcription machinery, which could interfere with loop extrusion. This work investigates the interplay between 2 important active processes; it demonstrates that extruding SMCs can efficiently bypass transcribing RNA polymerases within mere seconds, thus allowing spatial organization of the transcriptionally active genome, and predicts that extruding SMC complexes have a mechanism to bypass other bulky DNA-bound obstacles., To separate replicated sister chromatids during mitosis, eukaryotes and prokaryotes have structural maintenance of chromosome (SMC) condensin complexes that were recently shown to organize chromosomes by a process known as DNA loop extrusion. In rapidly dividing bacterial cells, the process of separating sister chromatids occurs concomitantly with ongoing transcription. How transcription interferes with the condensin loop-extrusion process is largely unexplored, but recent experiments have shown that sites of high transcription may directionally affect condensin loop extrusion. We quantitatively investigate different mechanisms of interaction between condensin and elongating RNA polymerases (RNAPs) and find that RNAPs are likely steric barriers that can push and interact with condensins. Supported by chromosome conformation capture and chromatin immunoprecipitation for cells after transcription inhibition and RNAP degradation, we argue that translocating condensins must bypass transcribing RNAPs within ∼1 to 2 s of an encounter at rRNA genes and within ∼10 s at protein-coding genes. Thus, while individual RNAPs have little effect on the progress of loop extrusion, long, highly transcribed operons can significantly impede the extrusion process. Our data and quantitative models further suggest that bacterial condensin loop extrusion occurs by 2 independent, uncoupled motor activities; the motors translocate on DNA in opposing directions and function together to enlarge chromosomal loops, each independently bypassing steric barriers in their path. Our study provides a quantitative link between transcription and 3D genome organization and proposes a mechanism of interactions between SMC complexes and elongating transcription machinery relevant from bacteria to higher eukaryotes.

Significance Cellular behavior is ultimately governed by the genetic program encoded in the cell’s DNA and through the arsenal of molecular machines that actively transcribe its genes, yet we lack the ability to predict how an arbitrary DNA sequence will perform. To that end, we analyze the performance of over 10,000 regulatory sequences and develop a model that can predict the behavior of any sequence based on its composition. By considering promoters that vary only by one or two elements, we can characterize how different components interact, providing fundamental insights into the mechanisms of transcription., Although the key promoter elements necessary to drive transcription in Escherichia coli have long been understood, we still cannot predict the behavior of arbitrary novel promoters, hampering our ability to characterize the myriad sequenced regulatory architectures as well as to design new synthetic circuits. This work builds upon a beautiful recent experiment by Urtecho et al. [G. Urtecho, et al., Biochemistry, 68, 1539–1551 (2019)] who measured the gene expression of over 10,000 promoters spanning all possible combinations of a small set of regulatory elements. Using these data, we demonstrate that a central claim in energy matrix models of gene expression—that each promoter element contributes independently and additively to gene expression—contradicts experimental measurements. We propose that a key missing ingredient from such models is the avidity between the –35 and –10 RNA polymerase binding sites and develop what we call a multivalent model that incorporates this effect and can successfully characterize the full suite of gene expression data. We explore several applications of this framework, namely, how multivalent binding at the –35 and –10 sites can buffer RNA polymerase (RNAP) kinetics against mutations and how promoters that bind overly tightly to RNA polymerase can inhibit gene expression. The success of our approach suggests that avidity represents a key physical principle governing the interaction of RNA polymerase to its promoter.

Significance Despite being a leading cause of foodborne illnesses, accounting for 58% of all outbreaks and over 96% of nonbacterial outbreaks, there are no approved treatments available for norovirus infections. Assembled shells of the viruses without genetic materials enclosed are currently being used as candidates for vaccine trials. Although the virus shells have been thought to exist in a single-sized assembly, our structures in near-atomic detail reveal clear variations in size between different outbreak strains, and in spatial and angular arrangements of the antigenic surface spikes. The structures we present serve as valuable templates for facilitating vaccine formulations., Noroviruses are a leading cause of foodborne illnesses worldwide. Although GII.4 strains have been responsible for most norovirus outbreaks, the assembled virus shell structures have been available in detail for only a single strain (GI.1). We present high-resolution (2.6- to 4.1-Å) cryoelectron microscopy (cryo-EM) structures of GII.4, GII.2, GI.7, and GI.1 human norovirus outbreak strain virus-like particles (VLPs). Although norovirus VLPs have been thought to exist in a single-sized assembly, our structures reveal polymorphism between and within genogroups, with small, medium, and large particle sizes observed. Using asymmetric reconstruction, we were able to resolve a Zn2+ metal ion adjacent to the coreceptor binding site, which affected the structural stability of the shell. Our structures serve as valuable templates for facilitating vaccine formulations.

Significance The combination of molecular dynamics simulation, single-molecule imaging, and functional assays described here reveals a mechanism of substrate selectivity in the SLC6 family of neurotransmitter transporters. We show that the rotameric state of a volumetric sensor in the substrate binding site is allosterically coupled to conformational changes necessary for transport, and as a consequence, upon binding large substrates, the transporter becomes stabilized in an inactive, nontransporting state upon binding larger substrates. This mechanistic insight suggests the possibility that medically relevant SLC6 transporters may be targeted by inhibitors that specifically modulate this sensor., Neurotransmitter:sodium symporters (NSSs) in the SLC6 family terminate neurotransmission by coupling the thermodynamically favorable transport of ions to the thermodynamically unfavorable transport of neurotransmitter back into presynaptic neurons. Results from many structural, functional, and computational studies on LeuT, a bacterial NSS homolog, have provided critical insight into the mechanism of sodium-coupled transport, but the mechanism underlying substrate-specific transport rates is still not understood. We present a combination of molecular dynamics simulations, single-molecule fluorescence resonance energy transfer (smFRET) imaging, and measurements of Na+ binding and substrate transport that reveals an allosteric substrate specificity mechanism. In this mechanism, residues F259 and I359 in the substrate binding pocket couple the binding of substrate to Na+ release from the Na2 site by allosterically modulating the stability of a partially open, inward-facing state. We propose a model for transport selectivity in which residues F259 and I359 act as a volumetric sensor that inhibits the transport of bulky amino acids.

Significance Voltage-gated sodium channels play a central role in cellular excitability and are key targets for drug development. Recent breakthroughs in high-resolution cryo-electron microscopy protein structure determination, Rosetta computational protein structure modeling, and multimicrosecond molecular dynamics simulations are empowering advances in structural biology to study the atomistic details of channel−drug interactions. We used Rosetta structural computational modeling and molecular dynamics simulations to study the interactions of antiarrhythmic and local anesthetic drugs with cardiac sodium channel. Our results provide crucial atomic-scale mechanistic insights into the channel–drug interactions, necessary for the rational design of novel modulators of the human cardiac sodium channel to be used for the treatment of cardiac arrhythmias., The human voltage-gated sodium channel, hNaV1.5, is responsible for the rapid upstroke of the cardiac action potential and is target for antiarrhythmic therapy. Despite the clinical relevance of hNaV1.5-targeting drugs, structure-based molecular mechanisms of promising or problematic drugs have not been investigated at atomic scale to inform drug design. Here, we used Rosetta structural modeling and docking as well as molecular dynamics simulations to study the interactions of antiarrhythmic and local anesthetic drugs with hNaV1.5. These calculations revealed several key drug binding sites formed within the pore lumen that can simultaneously accommodate up to two drug molecules. Molecular dynamics simulations identified a hydrophilic access pathway through the intracellular gate and a hydrophobic access pathway through a fenestration between DIII and DIV. Our results advance the understanding of molecular mechanisms of antiarrhythmic and local anesthetic drug interactions with hNaV1.5 and will be useful for rational design of novel therapeutics.

Significance The human mitochondrial ribosome (mitoribosome) recycling factor (RRFmt) is known to play essential roles in mitochondrial physiology, including protein synthesis, and it has been implicated in human genetic diseases. The RRFmt is among the few protein molecules that carry their N-terminal signal peptide sequence into the mitochondrial matrix that is required for RRFmt’s interaction with the mitoribosome. In this study, we present a cryo-electron microscopic structure of the human mitoribosome in complex with the RRFmt. The structure reveals hitherto unknown features of RRFmt and its interactions with the functionally important regions of the ribosomal RNA that constitute the peptidyl-transferase center and that are linked to the GTPase-associated center of the mitoribosome, shedding light on the mechanism of ribosome recycling in mitochondria., Mammalian mitochondrial ribosomes (mitoribosomes) are responsible for synthesizing proteins that are essential for oxidative phosphorylation (ATP generation). Despite their common ancestry with bacteria, the composition and structure of the human mitoribosome and its translational factors are significantly different from those of their bacterial counterparts. The mammalian mitoribosome recycling factor (RRFmt) carries a mito-specific N terminus extension (NTE), which is necessary for the function of RRFmt. Here we present a 3.9-Å resolution cryo-electron microscopic (cryo-EM) structure of the human 55S mitoribosome-RRFmt complex, which reveals α-helix and loop structures for the NTE that makes multiple mito-specific interactions with functionally critical regions of the mitoribosome. These include ribosomal RNA segments that constitute the peptidyl transferase center (PTC) and those that connect PTC with the GTPase-associated center and with mitoribosomal proteins L16 and L27. Our structure reveals the presence of a tRNA in the pe/E position and a rotation of the small mitoribosomal subunit on RRFmt binding. In addition, we observe an interaction between the pe/E tRNA and a mito-specific protein, mL64. These findings help understand the unique features of mitoribosome recycling.

Significance We introduce an interdisciplinary approach to understanding global modulation of gene expression in mammalian cells. Conventional transcription factors target a limited subset of genes, whereas global modulators bind the genome broadly. An example of the latter is MeCP2, which is mutated in neurological disorders. MeCP2 has millions of genomic binding sites, but its effects on gene expression are mostly small scale and incompletely understood at a mechanistic level. Using datasets from genetically modified human neurons, our mathematical approach rigorously distinguishes global effects from experimental noise. This allows us to integrate theory with experiments to discriminate competing mechanistic models. The results indicate that MeCP2 creates “roadblocks” in gene bodies that slow down elongating RNA polymerase II, leading to polymerase queueing., Patterns of gene expression are primarily determined by proteins that locally enhance or repress transcription. While many transcription factors target a restricted number of genes, others appear to modulate transcription levels globally. An example is MeCP2, an abundant methylated-DNA binding protein that is mutated in the neurological disorder Rett syndrome. Despite much research, the molecular mechanism by which MeCP2 regulates gene expression is not fully resolved. Here, we integrate quantitative, multidimensional experimental analysis and mathematical modeling to indicate that MeCP2 is a global transcriptional regulator whose binding to DNA creates “slow sites” in gene bodies. We hypothesize that waves of slowed-down RNA polymerase II formed behind these sites travel backward and indirectly affect initiation, reminiscent of defect-induced shockwaves in nonequilibrium physics transport models. This mechanism differs from conventional gene-regulation mechanisms, which often involve direct modulation of transcription initiation. Our findings point to a genome-wide function of DNA methylation that may account for the reversibility of Rett syndrome in mice. Moreover, our combined theoretical and experimental approach provides a general method for understanding how global gene-expression patterns are choreographed.

Significance Many filamentous fungi colonizing animal or plant tissue, waste matter, or soil must find optimal paths through the constraining geometries of their microenvironment. Imaging of live fungal growth in custom-built microfluidics structures revealed the intracellular mechanisms responsible for this remarkable efficiency. In meandering channels, the Spitzenkörper (an assembly of vesicles at the filament tip) acted like a natural gyroscope, conserving the directional memory of growth, while the fungal cytoskeleton organized along the shortest growth path. However, if an obstacle could not be negotiated, the directional memory was lost due to the disappearance of the Spitzenkörper gyroscope. This study can impact diverse environmental, industrial, and medical applications, from fungal pathogenicity in plants and animals to biology-inspired computation., Filamentous fungi that colonize microenvironments, such as animal or plant tissue or soil, must find optimal paths through their habitat, but the biological basis for negotiating growth in constrained environments is unknown. We used time-lapse live-cell imaging of Neurospora crassa in microfluidic environments to show how constraining geometries determine the intracellular processes responsible for fungal growth. We found that, if a hypha made contact with obstacles at acute angles, the Spitzenkörper (an assembly of vesicles) moved from the center of the apical dome closer to the obstacle, thus functioning as an internal gyroscope, which preserved the information regarding the initial growth direction. Additionally, the off-axis trajectory of the Spitzenkörper was tracked by microtubules exhibiting “cutting corner” patterns. By contrast, if a hypha made contact with an obstacle at near-orthogonal incidence, the directional memory was lost, due to the temporary collapse of the Spitzenkörper–microtubule system, followed by the formation of two “daughter” hyphae growing in opposite directions along the contour of the obstacle. Finally, a hypha passing a lateral opening in constraining channels continued to grow unperturbed, but a daughter hypha gradually branched into the opening and formed its own Spitzenkörper–microtubule system. These observations suggest that the Spitzenkörper–microtubule system is responsible for efficient space partitioning in microenvironments, but, in its absence during constraint-induced apical splitting and lateral branching, the directional memory is lost, and growth is driven solely by the isotropic turgor pressure. These results further our understanding of fungal growth in microenvironments relevant to environmental, industrial, and medical applications.

Significance Human DNA is 2 m long and is folded into a 10-μm-sized cellular nucleus. Experiments have revealed two major features of genome organization: Segregation of alternating active and inactive regions into compartments, and formation of compacted local domains. These were hypothesized to be formed by different mechanisms: Compartments can be formed by microphase separation and domains by active, motor-driven, loop extrusion. Here, we integrate these mechanisms into a polymer model and show that their interplay coherently explains diverse experimental data for wild-type and mutant cells. Our results provide a framework for the interpretation of chromosome organization in cellular phenotypes and highlight that chromatin is a complex, active matter shaped by an interplay of phase segregation and loop extrusion., Mammalian chromatin is spatially organized at many scales showing two prominent features in interphase: (i) alternating regions (1–10 Mb) of active and inactive chromatin that spatially segregate into different compartments, and (ii) domains (

Significance When and at what size to divide are critical decisions, requiring cells to integrate internal and external cues. While it is known that the 24-h circadian clock and the environment modulate division timings across organisms, how these signals combine to set the size at which cells divide is not understood. Iterating between modeling and experiments, we show that, in both constant and light−dark conditions, the cyanobacterial clock produces distinctly sized and timed subpopulations. These arise from continuous coupling of the clock to the cell cycle, which, in light−dark cycles, steers cell divisions away from dawn and dusk. Stochastic modeling allows us to predict how these effects emerge from the complex interactions between the environment, clock, and cell size control., How cells maintain their size has been extensively studied under constant conditions. In the wild, however, cells rarely experience constant environments. Here, we examine how the 24-h circadian clock and environmental cycles modulate cell size control and division timings in the cyanobacterium Synechococcus elongatus using single-cell time-lapse microscopy. Under constant light, wild-type cells follow an apparent sizer-like principle. Closer inspection reveals that the clock generates two subpopulations, with cells born in the subjective day following different division rules from cells born in subjective night. A stochastic model explains how this behavior emerges from the interaction of cell size control with the clock. We demonstrate that the clock continuously modulates the probability of cell division throughout day and night, rather than solely applying an on−off gate to division, as previously proposed. Iterating between modeling and experiments, we go on to identify an effective coupling of the division rate to time of day through the combined effects of the environment and the clock on cell division. Under naturally graded light−dark cycles, this coupling narrows the time window of cell divisions and shifts divisions away from when light levels are low and cell growth is reduced. Our analysis allows us to disentangle, and predict the effects of, the complex interactions between the environment, clock, and cell size control.