CD3ζ ITAMs enable ligand discrimination and antagonism by inhibiting TCR signaling in response to low-affinity peptides.

The T cell antigen receptor (TCR) contains ten immunoreceptor tyrosine-based activation motif (ITAM) signaling sequences distributed within six CD3 subunits; however, the reason for such structural complexity and multiplicity is unclear. Here we evaluated the effect of inactivating the three CD3ζ chain ITAMs on TCR signaling and T cell effector responses using a conditional 'switch' mouse model. Unexpectedly, we found that T cells expressing TCRs containing inactivated (non-signaling) CD3ζ ITAMs (6F-CD3ζ) exhibited reduced ability to discriminate between low- and high-affinity ligands, resulting in enhanced signaling and cytokine responses to low-affinity ligands because of a previously undetected inhibitory function of CD3ζ ITAMs. Also, 6F-CD3ζ TCRs were refractory to antagonism, as predicted by a new in silico adaptive kinetic proofreading model that revises the role of ITAM multiplicity in TCR signaling. Finally, T cells expressing 6F-CD3ζ displayed enhanced cytolytic activity against solid tumors expressing low-affinity ligands, identifying a new counterintuitive approach to TCR-mediated cancer immunotherapy.

Modulation of Phase Shift between Wnt and Notch Signaling Oscillations Controls Mesoderm Segmentation.

How signaling dynamics encode information is a central question in biology. During vertebrate development, dynamic Notch signaling oscillations control segmentation of the presomitic mesoderm (PSM). In mouse embryos, this molecular clock comprises signaling oscillations of several pathways, i.e., Notch, Wnt, and FGF signaling. Here, we directly address the role of the relative timing between Wnt and Notch signaling oscillations during PSM patterning. To this end, we developed a new experimental strategy using microfluidics-based entrainment that enables specific control of the rhythm of segmentation clock oscillations. Using this approach, we find that Wnt and Notch signaling are coupled at the level of their oscillation dynamics. Furthermore, we provide functional evidence that the oscillation phase shift between Wnt and Notch signaling is critical for PSM segmentation. Our work hence reveals that dynamic signaling, i.e., the relative timing between oscillatory signals, encodes essential information during multicellular development.

Latent space of a small genetic network: Geometry of dynamics and information.

The high-dimensional character of most biological systems presents genuine challenges for modeling and prediction. Here we propose a neural network-based approach for dimensionality reduction and analysis of biological gene expression data, using, as a case study, a well-known genetic network in the early Drosophila embryo, the gap gene patterning system. We build an autoencoder compressing the dynamics of spatial gap gene expression into a two-dimensional (2D) latent map. The resulting 2D dynamics suggests an almost linear model, with a small bare set of essential interactions. Maternally defined spatial modes control gap genes positioning, without the classically assumed intricate set of repressive gap gene interactions. This, surprisingly, predicts minimal changes of neighboring gap domains when knocking out gap genes, consistent with previous observations. Latent space geometries in maternal mutants are also consistent with the existence of such spatial modes. Finally, we show how positional information is well defined and interpretable as a polar angle in latent space. Our work illustrates how optimization of small neural networks on medium-sized biological datasets is sufficiently informative to capture essential underlying mechanisms of network function.

Endocytic proteins with prion-like domains form viscoelastic condensates that enable membrane remodeling.

Membrane invagination and vesicle formation are key steps in endocytosis and cellular trafficking. Here, we show that endocytic coat proteins with prion-like domains (PLDs) form hemispherical puncta in the budding yeast, Saccharomyces cerevisiae These puncta have the hallmarks of biomolecular condensates and organize proteins at the membrane for actin-dependent endocytosis. They also enable membrane remodeling to drive actin-independent endocytosis. The puncta, which we refer to as endocytic condensates, form and dissolve reversibly in response to changes in temperature and solution conditions. We find that endocytic condensates are organized around dynamic protein-protein interaction networks, which involve interactions among PLDs with high glutamine contents. The endocytic coat protein Sla1 is at the hub of the protein-protein interaction network. Using active rheology, we inferred the material properties of endocytic condensates. These experiments show that endocytic condensates are akin to viscoelastic materials. We use these characterizations to estimate the interfacial tension between endocytic condensates and their surroundings. We then adapt the physics of contact mechanics, specifically modifications of Hertz theory, to develop a quantitative framework for describing how interfacial tensions among condensates, the membrane, and the cytosol can deform the plasma membrane to enable actin-independent endocytosis.

Does an early post traumatic knee brace reduce the incidence of knee rotational instability?

PURPOSE: Several anterolateral stabilization procedures have been developed recently to address rotational instability of the knee. Currently, these procedures tend to be systematically used by some practitioners. However, antero-lateral structures of the knee (including the anterolateral ligament, ALL) have a self-healing potential which can reduce the need to perform an antero-lateral procedure. In this study, it was hypothesized that early post-traumatic immobilization of the knee with a knee brace would allow partial healing of antero-lateral structures and also allow control of the pivot shift, thus avoiding antero-lateral extra-articular stabilization. The objective of this study was to compare the severity of pivot shift between two groups of patients who all experienced anterior cruciate ligament (ACL) tear and respectively underwent post-traumatic immobilization of the knee versus no immobilization. METHODS: This was a comparative, multicentric (three centers' study) retrospective, consecutive study including 168 patients who underwent ACL reconstruction between May and September 2022. The application or not of post-traumatic immobilization and its duration, the severity of pivot shift observed in the operating room under general anesthesia, the presence of anterolateral lesions as revealed by MRI and the patients' pre-injury sport activity were recorded. RESULTS: A grade 3 pivot shift was found in 44 patients (27%). It was more frequently observed in the group without a brace compared to the group with a knee brace (18 patients out of 36: 50% versus 26 patients out of 132: 19.7%; p = 0.0012). Wearing a brace, whether hinged (OR = 0.221, [0.070-0.652]; p = 0.006) or not (OR = 0.232, [0.076-0.667]; p = 0.0064), was protective from the risk of developing a significant pivot shift. CONCLUSION: This study demonstrated that the presence of pivot-shift was lower in the patients that had an early post-injury knee brace before their ACL reconstruction. Based on this result, systematic brace placement could be advocated for in patients after knee trauma. LEVEL OF EVIDENCE: III, prognostic retrospective case-control study.

Clinical evaluation of a resurfacing device implant for femoral osteochondral defects greater than 1 cm2 with a minimal follow-up of 4 years: a prospective cohort study.

PURPOSE: Osteochondral defects have a limited capacity to heal and can evolve to an early osteoarthritis. A surgical possibility is the replacement of the affected cartilaginous area with a resurfacing device BioPoly™ RS Partial Resurfacing Knee Implant. The aim of this study was to report the clinical and survival outcomes of the BioPoly™ after a minimum follow-up of 4 years. METHODS: This study included all patients who had a BioPoly™ for femoral osteochondral defects greater than 1 cm2 and at least ICRS grade 2. The main outcome was to observe the KOOS and the Tegner activity score were used to assess outcomes preoperatively and at the last follow-up. The secondary outcomes were the VAS for pain, the complications rate post-surgery and survival rate of BioPoly™ at the last FU. RESULTS: Eighteen patients with 44.4% (8/18) of women were included with a mean age of 46.6 years (11.4), a mean body mass index (BMI) of 21.5 (kg/m2) (2.3). The mean follow-up was 6.3 years (1.3). We found a significant difference comparing pre-operative KOOS score and at last follow-up [respectively, 66.56(14.37) vs 84.17(7.656), p < 0.01]. At last follow-up, the Tegner score was different [respectively, 3.05(1.3) vs 3.6(1.3), p < 0.01]. At 5 years, the survival rate was of 94.7%. CONCLUSIONS: BioPoly™ is a real alternative for femoral osteochondral defects greater than 1 cm2 and at least ICRS grade 2. It will be interesting to compare this implant to mosaicplasty technic and/or microfracture at 5 years postoperatively regarding clinical outcomes and survival rate. LEVEL OF EVIDENCE: Therapeutic level III. Prospective cohort study.

Numerical Parameter Space Compression and Its Application to Biophysical Models.

Physical models of biological systems can become difficult to interpret when they have a large number of parameters. But the models themselves actually depend on (i.e., are sensitive to) only a subset of those parameters. This phenomenon is due to parameter space compression (PSC), in which a subset of parameters emerges as "stiff" as a function of time or space. PSC has only been used to explain analytically solvable physics models. We have generalized this result by developing a numerical approach to PSC that can be applied to any computational model. We validated our method against analytically solvable models of a random walk with drift and protein production and degradation. We then applied our method to a simple computational model of microtubule dynamic instability. We propose that numerical PSC has the potential to identify the low-dimensional structure of many computational models in biophysics. The low-dimensional structure of a model is easier to interpret and identifies the mechanisms and experiments that best characterize the system.

Multi-scale quantification of tissue behavior during amniote embryo axis elongation.

Embryonic axis elongation is a complex multi-tissue morphogenetic process responsible for the formation of the posterior part of the amniote body. How movements and growth are coordinated between the different posterior tissues (e.g. neural tube, axial and paraxial mesoderm, lateral plate, ectoderm, endoderm) to drive axis morphogenesis remain largely unknown. Here, we use quail embryos to quantify cell behavior and tissue movements during elongation. We quantify the tissue-specific contribution to axis elongation using 3D volumetric techniques, then quantify tissue-specific parameters such as cell density and proliferation. To study cell behavior at a multi-tissue scale, we used high-resolution 4D imaging of transgenic quail embryos expressing fluorescent proteins. We developed specific tracking and image analysis techniques to analyze cell motion and compute tissue deformations in 4D. This analysis reveals extensive sliding between tissues during axis extension. Further quantification of tissue tectonics showed patterns of rotations, contractions and expansions, which are consistent with the multi-tissue behavior observed previously. Our approach defines a quantitative and multi-scale method to analyze the coordination between tissue behaviors during early vertebrate embryo morphogenetic events.

Speed regulation of genetic cascades allows for evolvability in the body plan specification of insects.

During the anterior-posterior fate specification of insects, anterior fates arise in a nonelongating tissue (called the "blastoderm"), and posterior fates arise in an elongating tissue (called the "germband"). However, insects differ widely in the extent to which anterior-posterior fates are specified in the blastoderm versus the germband. Here we present a model in which patterning in both the blastoderm and germband of the beetle Tribolium castaneum is based on the same flexible mechanism: a gradient that modulates the speed of a genetic cascade of gap genes, resulting in the induction of sequential kinematic waves of gap gene expression. The mechanism is flexible and capable of patterning both elongating and nonelongating tissues, and hence converting blastodermal to germband fates and vice versa. Using RNAi perturbations, we found that blastodermal fates could be shifted to the germband, and germband fates could be generated in a blastoderm-like morphology. We also suggest a molecular mechanism underlying our model, in which gradient levels regulate the switch between two enhancers: One enhancer is responsible for sequential gene activation, and the other is responsible for freezing temporal rhythms into spatial patterns. This model is consistent with findings in Drosophila melanogaster, where gap genes were found to be regulated by two nonredundant "shadow" enhancers.

φ-evo: A program to evolve phenotypic models of biological networks.

Molecular networks are at the core of most cellular decisions, but are often difficult to comprehend. Reverse engineering of network architecture from their functions has proved fruitful to classify and predict the structure and function of molecular networks, suggesting new experimental tests and biological predictions. We present φ-evo, an open-source program to evolve in silico phenotypic networks performing a given biological function. We include implementations for evolution of biochemical adaptation, adaptive sorting for immune recognition, metazoan development (somitogenesis, hox patterning), as well as Pareto evolution. We detail the program architecture based on C, Python 3, and a Jupyter interface for project configuration and network analysis. We illustrate the predictive power of φ-evo by first recovering the asymmetrical structure of the lac operon regulation from an objective function with symmetrical constraints. Second, we use the problem of hox-like embryonic patterning to show how a single effective fitness can emerge from multi-objective (Pareto) evolution. φ-evo provides an efficient approach and user-friendly interface for the phenotypic prediction of networks and the numerical study of evolution itself.

Scaling of embryonic patterning based on phase-gradient encoding.

A fundamental feature of embryonic patterning is the ability to scale and maintain stable proportions despite changes in overall size, for instance during growth. A notable example occurs during vertebrate segment formation: after experimental reduction of embryo size, segments form proportionally smaller, and consequently, a normal number of segments is formed. Despite decades of experimental and theoretical work, the underlying mechanism remains unknown. More recently, ultradian oscillations in gene activity have been linked to the temporal control of segmentation; however, their implication in scaling remains elusive. Here we show that scaling of gene oscillation dynamics underlies segment scaling. To this end, we develop a new experimental model, an ex vivo primary cell culture assay that recapitulates mouse mesoderm patterning and segment scaling, in a quasi-monolayer of presomitic mesoderm cells (hereafter termed monolayer PSM or mPSM). Combined with real-time imaging of gene activity, this enabled us to quantify the gradual shift in the oscillation phase and thus determine the resulting phase gradient across the mPSM. Crucially, we show that this phase gradient scales by maintaining a fixed amplitude across mPSM of different lengths. We identify the slope of this phase gradient as a single predictive parameter for segment size, which functions in a size- and temperature-independent manner, revealing a hitherto unrecognized mechanism for scaling. Notably, in contrast to molecular gradients, a phase gradient describes the distribution of a dynamical cellular state. Thus, our phase-gradient scaling findings reveal a new level of dynamic information-processing, and provide evidence for the concept of phase-gradient encoding during embryonic patterning and scaling.

Predicting Ancestral Segmentation Phenotypes from Drosophila to Anopheles Using In Silico Evolution.

Molecular evolution is an established technique for inferring gene homology but regulatory DNA turns over so rapidly that inference of ancestral networks is often impossible. In silico evolution is used to compute the most parsimonious path in regulatory space for anterior-posterior patterning linking two Dipterian species. The expression pattern of gap genes has evolved between Drosophila (fly) and Anopheles (mosquito), yet one of their targets, eve, has remained invariant. Our model predicts that stripe 5 in fly disappears and a new posterior stripe is created in mosquito, thus eve stripe modules 3+7 and 4+6 in fly are homologous to 3+6 and 4+5 in mosquito. We can place Clogmia on this evolutionary pathway and it shares the mosquito homologies. To account for the evolution of the other pair-rule genes in the posterior we have to assume that the ancestral Dipterian utilized a dynamic method to phase those genes in relation to eve.

Dynamics of the slowing segmentation clock reveal alternating two-segment periodicity.

The formation of reiterated somites along the vertebrate body axis is controlled by the segmentation clock, a molecular oscillator expressed within presomitic mesoderm (PSM) cells. Although PSM cells oscillate autonomously, they coordinate with neighboring cells to generate a sweeping wave of cyclic gene expression through the PSM that has a periodicity equal to that of somite formation. The velocity of each wave slows as it moves anteriorly through the PSM, although the dynamics of clock slowing have not been well characterized. Here, we investigate segmentation clock dynamics in the anterior PSM in developing zebrafish embryos using an in vivo clock reporter, her1:her1-venus. The her1:her1-venus reporter has single-cell resolution, allowing us to follow segmentation clock oscillations in individual cells in real-time. By retrospectively tracking oscillations of future somite boundary cells, we find that clock reporter signal increases in anterior PSM cells and that the periodicity of reporter oscillations slows to about ∼1.5 times the periodicity in posterior PSM cells. This gradual slowing of the clock in the anterior PSM creates peaks of clock expression that are separated at a two-segment periodicity both spatially and temporally, a phenomenon we observe in single cells and in tissue-wide analyses. These results differ from previous predictions that clock oscillations stop or are stabilized in the anterior PSM. Instead, PSM cells oscillate until they incorporate into somites. Our findings suggest that the segmentation clock may signal somite formation using a phase gradient with a two-somite periodicity.

Chemodetection in fluctuating environments: receptor coupling, buffering, and antagonism.

Variability in the chemical composition of the extracellular environment can significantly degrade the ability of cells to detect rare cognate ligands. Using concepts from statistical detection theory, we formalize the generic problem of detection of small concentrations of ligands in a fluctuating background of biochemically similar ligands binding to the same receptors. We discover that in contrast with expectations arising from considerations of signal amplification, inhibitory interactions between receptors can improve detection performance in the presence of substantial environmental variability, providing an adaptive interpretation to the phenomenon of ligand antagonism. Our results suggest that the structure of signaling pathways responsible for chemodetection in fluctuating and heterogeneous environments might be optimized with respect to the statistics and dynamics of environmental composition. The developed formalism stresses the importance of characterizing nonspecific interactions to understand function in signaling pathways.

Untangling the Hairball: Fitness-Based Asymptotic Reduction of Biological Networks.

Complex mathematical models of interaction networks are routinely used for prediction in systems biology. However, it is difficult to reconcile network complexities with a formal understanding of their behavior. Here, we propose a simple procedure (called ϕ¯) to reduce biological models to functional submodules, using statistical mechanics of complex systems combined with a fitness-based approach inspired by in silico evolution. The ϕ¯ algorithm works by putting parameters or combination of parameters to some asymptotic limit, while keeping (or slightly improving) the model performance, and requires parameter symmetry breaking for more complex models. We illustrate ϕ¯ on biochemical adaptation and on different models of immune recognition by T cells. An intractable model of immune recognition with close to a hundred individual transition rates is reduced to a simple two-parameter model. The ϕ¯ algorithm extracts three different mechanisms for early immune recognition, and automatically discovers similar functional modules in different models of the same process, allowing for model classification and comparison. Our procedure can be applied to biological networks based on rate equations using a fitness function that quantifies phenotypic performance.

Evolving phenotypic networks in silico.

Evolved gene networks are constrained by natural selection. Their structures and functions are consequently far from being random, as exemplified by the multiple instances of parallel/convergent evolution. One can thus ask if features of actual gene networks can be recovered from evolutionary first principles. I review a method for in silico evolution of small models of gene networks aiming at performing predefined biological functions. I summarize the current implementation of the algorithm, insisting on the construction of a proper "fitness" function. I illustrate the approach on three examples: biochemical adaptation, ligand discrimination and vertebrate segmentation (somitogenesis). While the structure of the evolved networks is variable, dynamics of our evolved networks are usually constrained and present many similar features to actual gene networks, including properties that were not explicitly selected for. In silico evolution can thus be used to predict biological behaviours without a detailed knowledge of the mapping between genotype and phenotype.

Phenotypic spandrel: absolute discrimination and ligand antagonism.

We consider the general problem of sensitive and specific discrimination between biochemical species. An important instance is immune discrimination between self and not-self, where it is also observed experimentally that ligands just below the discrimination threshold negatively impact response, a phenomenon called antagonism. We characterize mathematically the generic properties of such discrimination, first relating it to biochemical adaptation. Then, based on basic biochemical rules, we establish that, surprisingly, antagonism is a generic consequence of any strictly specific discrimination made independently from ligand concentration. Thus antagonism constitutes a 'phenotypic spandrel': a phenotype existing as a necessary by-product of another phenotype. We exhibit a simple analytic model of discrimination displaying antagonism, where antagonism strength is linear in distance from the detection threshold. This contrasts with traditional proofreading based models where antagonism vanishes far from threshold and thus displays an inverted hierarchy of antagonism compared to simpler models. The phenotypic spandrel studied here is expected to structure many decision pathways such as immune detection mediated by TCRs and FCϵRIs, as well as endocrine signalling/disruption.

A random cell motility gradient downstream of FGF controls elongation of an amniote embryo.

Vertebrate embryos are characterized by an elongated antero-posterior (AP) body axis, which forms by progressive cell deposition from a posterior growth zone in the embryo. Here, we used tissue ablation in the chicken embryo to demonstrate that the caudal presomitic mesoderm (PSM) has a key role in axis elongation. Using time-lapse microscopy, we analysed the movements of fluorescently labelled cells in the PSM during embryo elongation, which revealed a clear posterior-to-anterior gradient of cell motility and directionality in the PSM. We tracked the movement of the PSM extracellular matrix in parallel with the labelled cells and subtracted the extracellular matrix movement from the global motion of cells. After subtraction, cell motility remained graded but lacked directionality, indicating that the posterior cell movements associated with axis elongation in the PSM are not intrinsic but reflect tissue deformation. The gradient of cell motion along the PSM parallels the fibroblast growth factor (FGF)/mitogen-activated protein kinase (MAPK) gradient, which has been implicated in the control of cell motility in this tissue. Both FGF signalling gain- and loss-of-function experiments lead to disruption of the motility gradient and a slowing down of axis elongation. Furthermore, embryos treated with cell movement inhibitors (blebbistatin or RhoK inhibitor), but not cell cycle inhibitors, show a slower axis elongation rate. We propose that the gradient of random cell motility downstream of FGF signalling in the PSM controls posterior elongation in the amniote embryo. Our data indicate that tissue elongation is an emergent property that arises from the collective regulation of graded, random cell motion rather than by the regulation of directionality of individual cellular movements.