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Programming T lymphocytes to distinguish self from non-self is a vital, multi-step process arising in the thymus(1–4). Signalling through the pre-T cell receptor (preTCR), a CD3-associated heterodimer comprising an invariant pTα chain and a clone-specific β chain, constitutes a critical early checkpoint in thymocyte development within the αβ T-cell lineage(5,6). PreTCRs arrayed on double negative (DN) thymocytes, like αβ TCRs appearing on double positive (DP) thymocytes, ligate peptides bound to MHC molecules (pMHC) on thymic stroma but via a different molecular docking strategy(7–10). Here we show the consequences of those distinctive interactions for thymocyte progression, using synchronized fetal thymic progenitor cultures differing in the presence or absence of pMHC on support stroma, determining single cell transcriptomes at key thymocyte developmental transitions. Although MHC negative stroma fosters αβ T lymphocyte differentiation, the absence of pMHC-preTCR interplay leads to deviant thymocyte transcriptional programming associated with dedifferentiation. Highly proliferative DN and DP subsets with antecedent characteristics of T cell lymphoblastic and myeloid malignancies emerge. Compensatory upregulation of diverse MHC class Ib proteins in B2m/H2-Ab1 MHC knockout mice partially safeguards in vivo thymocyte progression although, with ageing, disseminated DP thymic tumours may develop. Thus, beyond fostering β chain repertoire broadening for subsequent αβ TCR utilization, preTCR-pMHC interaction limits cellular plasticity to facilitate normal thymocyte differentiation and proliferation that, if absent, introduces developmental vulnerabilities.

PreTCRs use horizontal docking geometry The T cell receptor (TCR) recognizes peptide-bound major histocompatibility complex molecules (pMHCs) and consists of an α chain in association with a β chain. Both chains have hypervariable complementarity-determining regions (CDRs) that inform whether a particular TCR can recognize a given pMHC. To successfully graduate from the thymus, aspiring αβT cells must generate a functional TCR. During one early checkpoint in this process, the β chain is first paired with a preTβ chain to form the preTCR. Li et al. used x-ray crystallography to visualize how preTCRs recognize pMHCs. They report that the CDR3 loop of the preTCR β chain contacts the pMHC with a distinctive lateral topography. This is in contrast to the established binding modality of mature TCRs, whereby all three CDR loops on both α and β chains bind in a vertical orientation. These complexes help solve the mystery of how only functionally rearranged β chains using competent CDR3 loops can properly engage with pMHC at the preTCR stage. Science , this issue p. 181

Significance α β T cell receptors (TCRs) recognize antigenic peptide bound to major histocompatibility complex (pMHC) molecules with exquisite sensitivity. An emerging concept is that α β TCR functions as a mechanosensor whereby the complex between its ligand-binding TCR α β heterodimer and pMHC increases the bond lifetime under physiological-level force, the so-called catch bond. This study reveals the physical mechanism for catch bond behavior. Multiple layers of control are identified, including the dynamics of interfacial contacts, and the motion and geometry of the four subdomains of TCR α β , all of which are influenced by the load applied to the TCR α β -pMHC complex. These findings shall contribute to understanding the TCR mechanobiology and shall assist with design of future TCR-based immunotherapies.

We introduce a computational approach to build three-dimensional (3D) surface mesh models of the early-stage zebrafish brain primordia from time-series microscopy images. The complexity of the early-stage brain primordia and lack of recognizable landmarks pose a distinct challenge for feature segmentation and 3D modeling. Additional difficulty arises because of noise and variations in pixel intensity. We overcome these by using a hierarchical approach in which simple geometric elements, such as "beads" and "bonds," are assigned to represent local features and their connectivity is used to smoothen the surface while retaining high-curvature regions. We apply our method to build models of two zebrafish embryo phenotypes at discrete time points between 19 and 28 h post-fertilization and collect measurements to quantify development. Our approach is fast and applicable to building models of other biological systems, as demonstrated by models from magnetic resonance images of the human fetal brain. The source code, input scripts, sample image files, and generated outputs are publicly available on GitHub.

Significance TCR mechanosensing is thought necessary for digital sensitivity of αβT cell response to scant pMHC antigens. We use bioinformatic analysis, molecular dynamics, single-molecule optical tweezers techniques, cellular activation, and RNA-seq analysis to explore this paradigm in the γδT cell lineage. We find that, in keeping with its role in recognizing abundant cell-surface ligands, the γδTCR lacks force-dependent hallmarks of mechanosensing in αβT cells., High-acuity αβT cell receptor (TCR) recognition of peptides bound to major histocompatibility complex molecules (pMHCs) requires mechanosensing, a process whereby piconewton (pN) bioforces exert physical load on αβTCR–pMHC bonds to dynamically alter their lifetimes and foster digital sensitivity cellular signaling. While mechanotransduction is operative for both αβTCRs and pre-TCRs within the αβT lineage, its role in γδT cells is unknown. Here, we show that the human DP10.7 γδTCR specific for the sulfoglycolipid sulfatide bound to CD1d only sustains a significant load and undergoes force-induced structural transitions when the binding interface-distal γδ constant domain (C) module is replaced with that of αβ. The chimeric γδ–αβTCR also signals more robustly than does the wild-type (WT) γδTCR, as revealed by RNA-sequencing (RNA-seq) analysis of TCR-transduced Rag2−/− thymocytes, consistent with structural, single-molecule, and molecular dynamics studies reflective of γδTCRs as mediating recognition via a more canonical immunoglobulin-like receptor interaction. Absence of robust, force-related catch bonds, as well as γδTCR structural transitions, implies that γδT cells do not use mechanosensing for ligand recognition. This distinction is consonant with the fact that their innate-type ligands, including markers of cellular stress, are expressed at a high copy number relative to the sparse pMHC ligands of αβT cells arrayed on activating target cells. We posit that mechanosensing emerged over ∼200 million years of vertebrate evolution to fulfill indispensable adaptive immune recognition requirements for pMHC in the αβT cell lineage that are unnecessary for the γδT cell lineage mechanism of non-pMHC ligand detection.

Early studies of T cell structural biology using X-ray crystallography, surface plasmon resonance (SPR) and isothermal titration calorimetry (ITC) focused on a picture of the αβT cell receptor (αβTCR) component domains and their cognate ligands (peptides bound to MHC molecules, i.e. pMHCs) as static interaction partners. Moving forward requires integrating this corpus of data with dynamic technologies such as NMR, molecular dynamics (MD) simulations and real-time single molecule (SM) studies exemplified by optical tweezers (OT). NMR bridges relevant timescales and provides the potential for an all-atom dynamic description of αβTCR components prior to and during interactions with binding partners. SM techniques have opened up vistas in understanding the non-equilibrium nature of T cell signaling through the introduction of force-mediated binding measurements into the paradigm for T cell function. In this regard, bioforces consequent to T-lineage cell motility are now perceived as placing piconewton (pN)-level loads on single receptor-pMHC bonds to impact structural change and αβT-lineage biology, including peptide discrimination, cellular activation, and developmental progression. We discuss herein essential NMR technologies in illuminating the role of ligand binding in the preT cell receptor (preTCR), the αβTCR developmental precursor, and convergence of NMR, SM and MD data in advancing our comprehension of T cell development. More broadly we review the central hypothesis that the αβTCR is a mechanosensor, fostered by breakthrough NMR-based structural insights. Collectively, elucidating dynamic aspects through the integrative use of NMR, SM, and MD shall advance fundamental appreciation of the mechanism of T cell signaling as well as inform translational efforts in αβTCR and chimeric T cell (CAR-T) immunotherapies and T cell vaccinology.

The relationship between structure and function is a major constituent of the rules of life. Structures and functions occur across all levels of biological organization. Current efforts to integrate conceptual frameworks and approaches to address new and old questions promise to allow a more holistic and robust understanding of how different biological functions are achieved across levels of biological organization. Here, we provide unifying and generalizable definitions of both structure and function that can be applied across all levels of biological organization. However, we find differences in the nature of structures at the organismal level and below as compared to above the level of the organism. We term these intrinsic and emergent structures, respectively. Intrinsic structures are directly under selection, contributing to the overall performance (fitness) of the individual organism. Emergent structures involve interactions among aggregations of organisms and are not directly under selection. Given this distinction, we argue that while the functions of many intrinsic structures remain unknown, functions of emergent structures are the result of the aggregate of processes of individual organisms. We then provide a detailed and unified framework of the structure–function relationship for intrinsic structures to explore how their unknown functions can be defined. We provide examples of how these scalable definitions applied to intrinsic structures provide a framework to address questions on structure–function relationships that can be approached simultaneously from all subdisciplines of biology. We propose that this will produce a more holistic and robust understanding of how different biological functions are achieved across levels of biological organization.

Each [Formula: see text]T cell receptor (TCR) functions as a mechanosensor. The TCR is comprised of a clonotypic TCR[Formula: see text] ligand-binding heterodimer and the noncovalently associated CD3 signaling subunits. When bound by ligand, an antigenic peptide arrayed by a major histocompatibility complex molecule (pMHC), the TCR[Formula: see text] has a longer bond lifetime under piconewton-level loads. The atomistic mechanism of this "catch bond" behavior is unknown. Here, we perform molecular dynamics simulation of a TCR[Formula: see text]-pMHC complex and its variants under physiologic loads to identify this mechanism and any attendant TCR[Formula: see text] domain allostery. The TCR[Formula: see text]-pMHC interface is dynamically maintained by contacts with a spectrum of occupancies, introducing a level of control via relative motion between Vα and Vβ variable domains containing the pMHC-binding complementarity-determining region (CDR) loops. Without adequate load, the interfacial contacts are unstable, whereas applying sufficient load suppresses Vα-Vβ motion, stabilizing the interface. A second level of control is exerted by Cα and Cβ constant domains, especially Cβ and its protruding FG-loop, that create mismatching interfaces among the four TCR[Formula: see text] domains and with a pMHC ligand. Applied load enhances fit through deformation of the TCR[Formula: see text] molecule. Thus, the catch bond involves the entire TCR[Formula: see text] conformation, interdomain motion, and interfacial contact dynamics, collectively. This multilayered architecture of the machinery fosters fine-tuning of cellular response to load and pMHC recognition. Since the germline-derived TCR[Formula: see text] ectodomain is structurally conserved, the proposed mechanism can be universally adopted to operate under load during immune surveillance by diverse [Formula: see text]TCRs constituting the T cell repertoire.

Proline-rich motifs (PRMs) are widely used for mediating protein-protein interactions with weak binding affinities. Because they are intrinsically disordered when unbound, conformational entropy plays a significant role for the binding. However, residue-level differences of the entropic contribution in the binding of different ligands remain not well understood. We use all-atom molecular dynamics simulation and the maximal information spanning tree formalism to analyze conformational entropy associated with the binding of two PRMs, one from the Abl kinase and the other from the nonstructural protein 1 of the 1918 Spanish influenza A virus, to the N-terminal SH3 (nSH3) domain of the CrkII protein. Side chains of the stably folded nSH3 experience more entropy change upon ligand binding than the backbone, whereas PRMs involve comparable but heterogeneous entropy changes among the backbone and side chains. In nSH3, two conserved nonpolar residues forming contacts with the PRM experience the largest side-chain entropy loss. In contrast, the C-terminal charged residues of PRMs that form polar contacts with nSH3 experience the greatest side-chain entropy loss, although their “fuzzy” nature is attributable to the backbone that remains relatively flexible. Thus, residues that form high-occupancy contacts between nSH3 and PRM do not reciprocally contribute to entropy loss. Furthermore, certain surface residues of nSH3 distal to the interface with PRMs gain entropy, indicating a nonlocal effect of ligand binding. Comparing between the PRMs from cAbl and nonstructural protein 1, the latter involves a larger side-chain entropy loss and forms more contacts with nSH3. Consistent with experiments, this indicates stronger binding of the viral ligand at the expense of losing the flexibility of side chains, whereas the backbone experiences less entropy loss. The entropy “hotspots” as identified in this study will be important for tuning the binding affinity of various ligands to a receptor.

The 1918 influenza A virus (IAV) caused the most severe flu pandemic in recorded human history. Nonstructural protein 1 (NS1) is an important virulence factor of the 1918 IAV. NS1 antagonizes host defense mechanisms through interactions with multiple host factors. One pathway by which NS1 increases virulence is through the activation of phosphoinositide 3-kinase (PI3K) by binding to its p85β subunit. Here we present the mechanism underlying the molecular recognition of the p85β subunit by 1918 NS1. Using X-ray crystallography, we determine the structure of 1918 NS1 complexed with p85β of human PI3K. We find that the 1918 NS1 effector domain (1918 NS1 ED ) undergoes a conformational change to bind p85β. Using NMR relaxation dispersion and molecular dynamics simulation, we identify that free 1918 NS1 ED exists in a dynamic equilibrium between p85β-binding–competent and –incompetent conformations in the submillisecond timescale. Moreover, we discover that NS1 ED proteins of 1918 (H1N1) and Udorn (H3N2) strains exhibit drastically different conformational dynamics and binding kinetics to p85β. These results provide evidence of strain-dependent conformational dynamics of NS1. Using kinetic modeling based on the experimental data, we demonstrate that 1918 NS1 ED can result in the faster hijacking of p85β compared to Ud NS1 ED , although the former has a lower affinity to p85β than the latter. Our results suggest that the difference in binding kinetics may impact the competition with cellular antiviral responses for the activation of PI3K. We anticipate that our findings will increase the understanding of the strain-dependent behaviors of influenza NS1 proteins.

Two mechanisms have been proposed for the function of motor proteins: The power stroke and the Brownian ratchet. The former refers to generation of a large downhill free energy gradient over which the motor protein moves nearly irreversibly in making a step, whereas the latter refers to biasing or rectifying the diffusive motion of the motor. Both mechanisms require input of free energy, which generally involves the processing of an ATP (adenosine 5′-triphosphate) molecule. Recent advances in experiments that reveal the details of the stepping motion of motor proteins, together with computer simulations of atomistic structures, have provided greater insights into the mechanisms. Here, we compare the various models of the power stroke and the Brownian ratchet that have been proposed. The 2 mechanisms are not mutually exclusive, and various motor proteins employ them to different extents to perform their biological function. As examples, we discuss linear motor proteins Kinesin-1 and myosin-V, and the rotary motor F 1 -ATPase, all of which involve a power stroke as the essential element of their stepping mechanism.

The major cytoskeletal protein actin forms complex networks to provide structural support and perform vital functions in cells. In vitro studies have revealed that the structure of the higher-order actin network is determined primarily by the type of actin binding protein (ABP). By comparison, there are far fewer studies about the role of the mechanical environment for the organization of the actin network. In particular, the duration over which cells reorganize their shape in response to functional demands is relatively short compared to the in vitro protein polymerization time, suggesting that such changes can influence the actin network formation. We hypothesize that mechanical flows in the cytoplasm generated by exogenous and endogenous stimulation play a key role in the spatiotemporal regulation of the actin architecture. To mimic cytoplasmic streaming, we generated a circulating flow using surface acoustic wave in a microfluidic channel and investigated its effect on the formation of networks by actin and ABPs. We found that the mechanical flow affected the orientation and thickness of actin bundles, depending on the type and concentration of ABPs. Our computational model shows that the extent of alignment and thickness of actin bundle are determined by the balance between flow-induced drag forces and the tendency of ABPs to crosslink actin filaments at given angles. These results suggest that local intracellular flows can affect the assembly dynamics and morphology of the actin cytoskeleton. STATEMENT OF SIGNIFICANCE: Spatiotemporal regulation of actin cytoskeleton structure is essential in many cellular functions. It has been shown that mechanical cues including an applied force and geometric boundary can alter the structural characteristics of actin network. However, even though the cytoplasm accounts for a large portion of the cell volume, the effect of the cytoplasmic streaming flow produced during cell dynamics on actin network organization has not been reported. In this study, we demonstrated that the mechanical flow exerted during actin network organization play an important role in determining the orientation and dimension of actin bundle network. Our result will be beneficial in understanding the mechanism of the actin network reorganization occurred during physiological and pathological processes.

Cytosine methylation affects mechanical properties of DNA and potentially alters the hydration fingerprint for recognition by proteins. The atomistic origin for these effects is not well understood, and we address this via all-atom molecular dynamics simulations. We find that the stiffness of the methylated dinucleotide step changes marginally, whereas the neighboring steps become stiffer. Stiffening is further enhanced for consecutively methylated steps, providing a mechanistic origin for the effect of hypermethylation. Steric interactions between the added methyl groups and the nonpolar groups of the neighboring nucleotides are responsible for the stiffening in most cases. By constructing hydration maps, we found that methylation also alters the surface hydration structure in distinct ways. Its resistance to deformation may contribute to the stiffening of DNA for deformational modes lacking steric interactions. These results highlight the sequence- and deformational-mode-dependent effects of cytosine methylation.

Many intrinsically disordered proteins (IDPs) form fuzzy complexes upon binding to their targets. Although many IDPs are weakly bound in fuzzy complexes, some IDPs form high-affinity complexes. One example is the nonstructural protein 1 (NS1) of the 1918 Spanish influenza A virus, which hijacks cellular CRKII through the strong binding affinity (K d ∼10 nM) of its proline-rich motif (PRM NS1 ) to the N-terminal Src-homology 3 domain of CRKII. However, its molecular mechanism remains elusive. Here, we examine the interplay between structural disorder of a bound PRM NS1 and its long-range electrostatic interactions. Using x-ray crystallography and NMR spectroscopy, we found that PRM NS1 retains substantial conformational flexibility in the bound state. Moreover, molecular dynamics simulations showed that structural disorder of the bound PRM NS1 increases the number of electrostatic interactions and decreases the mean distances between the positively charged residues in PRM NS1 and the acidic residues in the N-terminal Src-homology 3 domain. These results are analyzed using a polyelectrostatic model. Our results provide an insight into the molecular recognition mechanism for a high-affinity fuzzy complex.

The microtubule (MT)-associated motor protein kinesin utilizes its conserved ATPase head to achieve diverse motility characteristics. Despite considerable knowledge about how its ATPase activity and MT binding are coupled to the motility cycle, the atomic mechanism of the core events remain to be found. To obtain insights into the mechanism, we performed 38.5 microseconds of all-atom molecular dynamics simulations of kinesin-MT complexes in different nucleotide states. Local subdomain dynamics were found to be essential for nucleotide processing. Catalytic water molecules are dynamically organized by the switch domains of the nucleotide binding pocket while ATP is torsionally strained. Hydrolysis products are 'pulled' by switch-I, and a new ATP is 'captured' by a concerted motion of the α0/L5/switch-I trio. The dynamic and wet kinesin-MT interface is tuned for rapid interactions while maintaining specificity. The proposed mechanism provides the flexibility necessary for walking in the crowded cellular environment., eLife digest Motor proteins called kinesins perform a number of different roles inside cells, including transporting cargo and organizing filaments called microtubules to generate the force needed for a cell to divide. Kinesins move along the microtubules, with different kinesins moving in different ways: some ‘walk’, some jump, and some destroy the microtubule as they travel along it. All kinesins power their movements using the same molecule as fuel – adenosine triphosphate, known as ATP for short. Energy stored in ATP is released by a chemical reaction known as hydrolysis, which uses water to break off specific parts of the ATP molecule. The site to which ATP binds in a kinesin has a similar structure to the ATP binding site of many other proteins that use ATP. However, little was known about the way in which kinesin uses ATP as a fuel, including how ATP binds to kinesin and is hydrolyzed, and how the products of hydrolysis are released. These events are used to power the motor protein. Hwang et al. have used powerful computer simulation methods to examine in detail how ATP interacts with kinesin whilst moving across a microtubule. The simulations suggest that regions (or 'domains') of kinesin near the ATP binding site move around to help in processing ATP. These kinesin domains trap a nearby ATP molecule from the environment and help to deliver water molecules to ATP for hydrolysis. Hwang et al. also found that the domain motion subsequently helps in the release of the hydrolysis products by kinesin. The domains around the ATP pocket vary among the kinesins and these differences may enable kinesins to fine-tune how they use ATP to move. Further investigations will help us understand why different kinesin families behave differently. They will also contribute to exploring how kinesin inhibitors might be used as anti-cancer drugs.

Summary During cell division, the mitotic kinesin-5 Eg5 generates most of the force required to separate centrosomes during spindle assembly. However, Kif15, another mitotic kinesin, can replace Eg5 function, permitting mammalian cells to acquire resistance to Eg5 poisons. Unlike Eg5, the mechanism by which Kif15 generates centrosome separation forces is unknown. Here we investigated the mechanical properties and force generation capacity of Kif15 at the single-molecule level using optical tweezers. We found that the non-motor microtubule-binding tail domain interacts with the microtubule's E-hook tail with a rupture force higher than the stall force of the motor. This allows Kif15 dimers to productively and efficiently generate forces that could potentially slide microtubules apart. Using an in vitro optical trapping and fluorescence assay, we found that Kif15 slides anti-parallel microtubules apart with gradual force buildup while parallel microtubule bundles remain stationary with a small amount of antagonizing force generated. A stochastic simulation shows the essential role of Kif15's tail domain for load storage within the Kif15-microtubule system. These results suggest a mechanism for how Kif15 rescues bipolar spindle assembly.

Degradation of fibrillar collagen is critical for tissue maintenance. Yet, understanding collagen catabolism has been challenging partly due to a lack of atomistic picture for its load-dependent conformational dynamics, as both mechanical load and local unfolding of collagen affect its cleavage by matrix metalloproteinase (MMP). We use molecular dynamics simulation to find the most cleavage-prone arrangement of α chains in a collagen triple helix and find amino acids that modulate stability of the MMP cleavage domain depending on the chain registry within the molecule. The native-like state is mechanically inhomogeneous, where the cleavage site interfaces a stiff region and a locally unfolded and flexible region along the molecule. In contrast, a triple helix made of the stable glycine-proline-hydroxyproline motif is uniformly flexible and is dynamically stabilized by short-lived, low-occupancy hydrogen bonds. These results provide an atomistic basis for the mechanics, conformation, and stability of collagen that affect catabolism.