Chemical mutagenesis of a GPCR ligand: Detoxifying “inflammo-attraction” to direct therapeutic stem cell migration

A transplanted stem cell’s engagement with a pathologic niche is the first step in its restoring homeostasis to that site. Inflammatory chemokines are constitutively produced in such a niche; their binding to receptors on the stem cell helps direct that cell’s “pathotropism.” Neural stem cells (NSCs), which express CXCR4, migrate to sites of CNS injury or degeneration in part because astrocytes and vasculature produce the inflammatory chemokine CXCL12. Binding of CXCL12 to CXCR4 (a G protein-coupled receptor, GPCR) triggers repair processes within the NSC. Although a tool directing NSCs to where needed has been long-sought, one would not inject this chemokine in vivo because undesirable inflammation also follows CXCL12–CXCR4 coupling. Alternatively, we chemically “mutated” CXCL12, creating a CXCR4 agonist that contained a strong pure binding motif linked to a signaling motif devoid of sequences responsible for synthetic functions. This synthetic dual-moity CXCR4 agonist not only elicited more extensive and persistent human NSC migration and distribution than did native CXCL 12, but induced no host inflammation (or other adverse effects); rather, there was predominantly reparative gene expression. When co-administered with transplanted human induced pluripotent stem cell-derived hNSCs in a mouse model of a prototypical neurodegenerative disease, the agonist enhanced migration, dissemination, and integration of donor-derived cells into the diseased cerebral cortex (including as electrophysiologically-active cortical neurons) where their secreted cross-corrective enzyme mediated a therapeutic impact unachieved by cells alone. Such a “designer” cytokine receptor-agonist peptide illustrates that treatments can be controlled and optimized by exploiting fundamental stem cell properties (e.g., “inflammo-attraction”).

A transplanted stem cell’s engagement with a pathologic niche is the first step in cell-mediated restoration of homeostasis to that region, whether by cell replacement, protection, gene delivery, milieu alteration, toxin neutralization, or remodeling (1–4). Not surprisingly, the more host terrain covered by the stem cells, the greater their impact. We and others found that a propensity for neural stem cells (NSCs) to home in vivo to acutely injured or actively degenerating central nervous system (CNS) regions—a property called “pathotropism” (1–12), now viewed as central to stem cell biology—is undergirded, at least in part, by the presence of chemokine receptors on the NSC surface, enabling them to follow concentration gradients of inflammatory cytokines constitutively elaborated by pathogenic processes and expressed by reactive astrocytes and injured vascular endothelium within the pathologic niche (5–9). This engagement of NSC receptors was first described for the prototypical chemokine receptor CXCR4 (C-X-C chemokine receptor type 4; also known as fusin or cluster of differentiation-184 [CD184]) and its unique natural cognate agonist ligand, the inflammatory chemokine CXCL12 (C-X-C motif chemokine ligand-12; also known as stromal cell-derived factor 1α [SDF-1α]) (5), but has since been described for many chemokine receptor-agonist pairings (6–9). Chemokine receptors belong to a superfamily that is characterized by seven transmembrane GDP-binding protein-coupled receptors (GPCRs) (13–21). In addition to their role in mediating inflammatory reactions and immune responses (22, 23), these receptors and their agonists are components of the regulatory axes for hematopoiesis and organogenesis in other systems (21, 24). Therefore, it is not surprising that binding of CXCL12 to CXCR4 mediates not only an inflammatory response, but also triggers within the NSC a series of intracellular processes associated with migration (as well as proliferation, differentiation, survival, and, during early brain development, proper neuronal lamination) (10).A tool directing therapeutic NSCs to where they are needed has long been sought in regenerative medicine (11, 12). While it was appealing to contemplate electively directing reparative NSCs to any desired area by emulating this chemoattractive property through the targeted injection of exogenous recombinant inflammatory cytokines, it ultimately seemed inadvisable to risk increasing toxicity in brains already characterized by excessive and usually inimical inflammation from neurotraumatic or neurodegenerative processes. However, the notion of engaging the homing function of these NSC-borne receptors without triggering that receptor’s undesirable downstream inflammatory signaling [particularly given that the NSCs themselves can exert a therapeutic antiinflammatory action in the diseased region (1, 2)] seemed a promising heretofore unexplored “workaround.”There had already been an impetus to examine the structure–function relationships of CXCR4, known to be the entry route into cells for HIV-1, in order to create CXCR4 antagonists that block viral infection (25–30). Antagonists of CXCR4 were also devised to forestall hematopoietic stem cells from homing to the bone marrow, hence prolonging their presence in the peripheral blood (31) to treat blood dyscrasias. An agonist, however, particularly one with discrete and selective actions, had not been contemplated. In other words, if CXCL12 could be stripped of its undesirable actions while preserving its tropic activity, an ideal chemoattractant would be derived.Based on the concept that CXCR4’s functions are conveyed by two distinct molecular “pockets”—one mediating binding (i.e., allowing a ligand to engage CXCR4) and the other mediating signaling (i.e., enabling a ligand, after binding, to trigger CXCR4-mediated intracellular cascades that promote not only inflammation but also migration) (13–18)—we performed chemical mutagenesis that should optimize binding while narrowing the spectrum of signaling. We created a simplified de novo peptide agonist of CXCR4 that contained a strong pure binding motif derived from CXCR4’s strongest ligand, viral macrophage inflammatory protein-II (vMIP-II) and linked it to a truncated signaling motif (only 8 amino acid residues) derived from the N terminus of native CXCL12 (19, 20). This synthetic dual-moiety CXCR4 agonist, which is devoid of a large portion of CXCL12’s native sequence (presumably responsible for undesired functions such as inflammation) not only elicited (with great specificity) more extensive and long-lasting human NSC (hNSC) migration and distribution than native CXCL12 (overcoming migratory barriers), but induced no host inflammation (or other adverse effects). Furthermore, because all of the amino acids in the binding motif were in a D-chirality, rendering the peptide resistant to enzymatic degradation, persistence of this benign synthetic agonist in vivo was prolonged. The hNSC’s gene ontology expression profile was predominantly reparative in contrast to inflammatory as promoted by native CXCL12. When coadministered with transplanted human induced pluripotent stem cell (hiPSC)-derived hNSCs (hiPSC derivatives are now known to have muted migration) in a mouse model of a prototypical neurodegenerative disease [the lethal neuropathic lysosomal storage disorder (LSD) Sandhoff disease (29), where hiPSC-hNSC migration is particularly limited], the synthetic agonist enhanced migration, dissemination, and integration of donor-derived cells into the diseased cortex (including as electrophysiologically active cortical neurons), where their secreted cross-corrective enzyme could mediate a histological and functional therapeutic impact in a manner unachieved by transplanting hiPSC-derived cells alone.In introducing such a “designer” cytokine receptor agonist, we hope to offer proof-of-concept that stem cell-mediated treatments can be controlled and optimized by exploiting fundamental stem cell properties (e.g., “inflammo-attraction”) to alter a niche and augment specific actions. Additionally, when agonists are strategically designed, the various functions of chemokine receptors (and likely other GCPRs) may be divorced. We demonstrate that such a strategy might be used safely and effectively to direct cells to needed regions and broaden their chimerism. We discuss the future implications and uses within the life sciences of such a chemical engineering approach.     

“You” speaks to me: Effects of generic-you in creating resonance between people and ideas

Creating resonance between people and ideas is a central goal of communication. Historically, attempts to understand the factors that promote resonance have focused on altering the content of a message. Here we identify an additional route to evoking resonance that is embedded in the structure of language: the generic use of the word “you” (e.g., “You can’t understand someone until you’ve walked a mile in their shoes”). Using crowd-sourced data from the Amazon Kindle application, we demonstrate that passages that people highlighted—collectively, over a quarter of a million times—were substantially more likely to contain generic-you compared to yoked passages that they did not highlight. We also demonstrate in four experiments (n = 1,900) that ideas expressed with generic-you increased resonance. These findings illustrate how a subtle shift in language establishes a powerful sense of connection between people and ideas.

Consider the feeling evoked by watching a gripping scene in a film, hearing a moving song, or coming across a quotation that seems to be written just for you. Experiencing resonance, a sense of connection, is a pervasive human experience. Prior research examining the processes that promote this experience suggests that altering a message to evoke emotion (1–7), highlighting its applicability to a person’s life (2, 6, 8–10), or appealing to a person’s beliefs (4, 8, 11) can all contribute to an idea’s resonance. Here we examine an additional route to cultivating this experience, which is grounded in a message’s form rather than its content: the use of a linguistic device that frames an idea as applying broadly.The ability to frame an idea as general rather than specific is a universal feature of language (12–15). One frequently used device is the generic usage of the pronoun “you” (15–17). Although “you” is often used to refer to a specific person or persons (e.g., “How did you get to work today?”), in many languages, it can also be used to refer to people in general (e.g., “You avoid rush hour if you can.”). This general use of “you” is comparable to the more formal “one,” but is used much more frequently (18).Research indicates that people often use “you” in this way to generalize from their own experiences. For example, a person reflecting on getting fired from their job might say, “It makes you feel betrayed” (18). Here, we propose that using “you” to refer to people in general has additional social implications, affecting whether an idea evokes resonance.Two features of the general usage of “you” (hereafter, “generic-you”) motivate this hypothesis. First, generic-you conveys that ideas are generalizable. Rather than expressing information that applies to a particular situation (e.g., “Leo broke your heart”), generic-you expresses information that is timeless and applies across contexts (e.g., “Eventually, you recover from heartbreak”; 18–23). Second, generic-you is expressed with the same word ("you") that is used in nongeneric contexts to refer to the addressee. Thus, even when “you” is used generically, the association to its specific meaning may further pull in the addressee, heightening resonance. Together, these features suggest that generic-you should promote the resonance of an idea. We tested this hypothesis across five preregistered studies (24–28), using a combination of crowd-sourced data and online experimental paradigms. Data, code, and materials are publicly available via the Open Science Framework (https://osf.io/6J2ZC/) (29). Study 1 used publicly available data from the Amazon Kindle application. Studies 2–5 were approved by the University of Michigan Health Sciences and Behavioral Sciences institutional review board (IRB) under HUM00172473 and deemed exempt from ongoing IRB review. All participants who participated in studies 2–5 provided informed consent via a checkbox presented through the online survey platform, Qualtrics.     

Cholinergic suppression of hippocampal sharp-wave ripples impairs working memory

Learning and memory are assumed to be supported by mechanisms that involve cholinergic transmission and hippocampal theta. Using G protein–coupled receptor-activation–based acetylcholine sensor (GRAB_ACh3.0) with a fiber-photometric fluorescence readout in mice, we found that cholinergic signaling in the hippocampus increased in parallel with theta/gamma power during walking and REM sleep, while ACh3.0 signal reached a minimum during hippocampal sharp-wave ripples (SPW-R). Unexpectedly, memory performance was impaired in a hippocampus-dependent spontaneous alternation task by selective optogenetic stimulation of medial septal cholinergic neurons when the stimulation was applied in the delay area but not in the central (choice) arm of the maze. Parallel with the decreased performance, optogenetic stimulation decreased the incidence of SPW-Rs. These findings suggest that septo–hippocampal interactions play a task-phase–dependent dual role in the maintenance of memory performance, including not only theta mechanisms but also SPW-Rs.

The neurotransmitter acetylcholine is thought to be critical for hippocampus-dependent declarative memories (1, 2). Reduction in cholinergic neurotransmission, either in Alzheimer’s disease or in experiments with cholinergic antagonists, such as scopolamine, impairs memory function (3–8). Acetylcholine may bring about its beneficial effects on memory encoding by enhancing theta rhythm oscillations, decreasing recurrent excitation, and increasing synaptic plasticity (9–11). Conversely, drugs which activate cholinergic receptors enhance learning and, therefore, are a neuropharmacological target for the treatment of memory deficits in Alzheimer’s disease (5, 12, 13).The contribution of cholinergic mechanisms in the acquisition of long-term memories and the role of the hippocampal–entorhinal–cortical interactions are well supported by experimental data (5, 12, 13). In addition, working memory or “short-term” memory is also supported by the hippocampal–entorhinal–prefrontal cortex (14–16). Working memory in humans is postulated to be a conscious process to “keep things in mind” transiently (16). In rodents, matching to sample task, spontaneous alternation between reward locations, and the radial maze task have been suggested to function as a homolog of working memory [“working memory like” (17)].Cholinergic activity is a critical requirement for working memory (18, 19) and for sustaining theta oscillations (10, 20–22). In support of this contention, theta–gamma coupling and gamma power are significantly higher in the choice arm of the maze, compared with those in the side arms where working memory is no longer needed for correct performance (23–26). It has long been hypothesized that working memory is maintained by persistent firing of neurons, which keep the presented items in a transient store in the prefrontal cortex and hippocampal–entorhinal system (27–31), although the exact mechanisms are debated (32–37). An alternative hypothesis holds that items of working memory are stored in theta-nested gamma cycles (38). Common in these models of working memory is the need for an active, cholinergic system–dependent mechanism (39–41). However, in spontaneous alternation tasks, the animals are not moving continuously during the delay, and theta oscillations are not sustained either. During the immobility epochs, theta is replaced by intermittent sharp-wave ripples (SPW-R), yet memory performance does not deteriorate. On the contrary, artificial blockade of SPW-Rs can impair memory performance (42, 43), and prolongation of SPW-Rs improves performance (44). Under the cholinergic hypothesis of working memory, such a result is unexpected.To address the relationship between cholinergic/theta versus SPW-R mechanism in spontaneous alternation, we used a G protein–coupled receptor-activation–based acetylcholine sensor (GRAB_ACh3.0) (45) to monitor acetylcholine (ACh) activity during memory performance in mice. In addition, we optogenetically enhanced cholinergic tone, which suppresses SPW-Rs by a different mechanism than electrically or optogenetically induced silencing of neurons in the hippocampus (43, 44). We show that cholinergic signaling in the hippocampus increases in parallel with theta power/score during walking and rapid eye movement (REM) sleep and reaches a transient minimum during SPW-Rs. Selective optogenetic stimulation of medial septal cholinergic neurons decreased the incidence of SPW-Rs during non-REM sleep (46–48), as well as during the delay epoch of a working memory task and impaired memory performance. These findings demonstrate that memory performance is supported by complementary theta and SPW-R mechanisms.     

A general model of hippocampal and dorsal striatal learning and decision making

Humans and other animals use multiple strategies for making decisions. Reinforcement-learning theory distinguishes between stimulus–response (model-free; MF) learning and deliberative (model-based; MB) planning. The spatial-navigation literature presents a parallel dichotomy between navigation strategies. In “response learning,” associated with the dorsolateral striatum (DLS), decisions are anchored to an egocentric reference frame. In “place learning,” associated with the hippocampus, decisions are anchored to an allocentric reference frame. Emerging evidence suggests that the contribution of hippocampus to place learning may also underlie its contribution to MB learning by representing relational structure in a cognitive map. Here, we introduce a computational model in which hippocampus subserves place and MB learning by learning a “successor representation” of relational structure between states; DLS implements model-free response learning by learning associations between actions and egocentric representations of landmarks; and action values from either system are weighted by the reliability of its predictions. We show that this model reproduces a range of seemingly disparate behavioral findings in spatial and nonspatial decision tasks and explains the effects of lesions to DLS and hippocampus on these tasks. Furthermore, modeling place cells as driven by boundaries explains the observation that, unlike navigation guided by landmarks, navigation guided by boundaries is robust to “blocking” by prior state–reward associations due to learned associations between place cells. Our model, originally shaped by detailed constraints in the spatial literature, successfully characterizes the hippocampal–striatal system as a general system for decision making via adaptive combination of stimulus–response learning and the use of a cognitive map.

Behavioral and neuroscientific studies suggest that animals can apply multiple strategies to the problem of maximizing future reward, referred to as the reinforcement-learning (RL) problem (1, 2). One strategy is to build a model of the environment that can be used to simulate the future to plan optimal actions (3) and the past for episodic memory (4–6). An alternative, model-free (MF) approach uses trial and error to estimate a direct mapping from the animal’s state to its expected future reward, which the agent caches and looks up at decision time (7, 8), potentially supporting procedural memory (9). This computation is thought to be carried out in the brain through prediction errors signaled by phasic dopamine responses (10). These strategies are associated with different tradeoffs (2). The model-based (MB) approach is powerful and flexible, but computationally expensive and, therefore, slow at decision time. MF methods, in contrast, enable rapid action selection, but these methods learn slowly and adapt poorly to changing environments. In addition to MF and MB methods, there are intermediate solutions that rely on learning useful representations that reduce burdens on the downstream RL process (11–13).In the spatial-memory literature, a distinction has been observed between “response learning” and “place learning” (14–16). When navigating to a previously visited location, response learning involves learning a sequence of actions, each of which depends on the preceding action or sensory cue (expressed in egocentric terms). For example, one might remember a sequence of left and right turns starting from a specific landmark. An alternative place-learning strategy involves learning a flexible internal representation of the spatial layout of the environment (expressed in allocentric terms). This “cognitive map” is thought to be supported by the hippocampal formation, where there are neurons tuned to place and heading direction (17–19). Spatial navigation using this map is flexible because it can be used with arbitrary starting locations and destinations, which need not be marked by immediate sensory cues.We posit that the distinction between place and response learning is analogous to that between MB and MF RL (20). Under this view, associative reinforcement is supported by the DLS (21, 22). Indeed, there is evidence from both rodents (23–25) and humans (26, 27) that spatial-response learning relies on the same basal ganglia structures that support MF RL. Evidence also suggests an analogy between MB reasoning and hippocampus (HPC)-based place learning (28, 29). However, this equivalence is not completely straightforward. For example, in rodents, multiple hippocampal lesion and inactivation studies failed to elicit an effect on action-outcome learning, a hallmark of MB planning (30–35). Nevertheless, there are indications that HPC might contribute to a different aspect of MB RL: namely, the representation of relational structure. Tasks that require memory of the relationships between stimuli do show dependence on HPC (36–42).Here, we formalize the perspective that hippocampal contributions to MB learning and place learning are the same, as are the dorsolateral striatal contributions to MF and response learning. In our model, HPC supports flexible behavior by representing the relational structure among different allocentric states, while dorsolateral striatum (DLS) supports associative reinforcement over egocentric sensory features. The model arbitrates between the use of these systems by weighting each system’s action values by the reliability of the system, as measured by a recent average of prediction errors, following Wan Lee et al. (43). We show that HPC and DLS maintain these roles across multiple task domains, including a range of spatial and nonspatial tasks. Our model can quantitatively explain a range of seemingly disparate findings, including the choice between place and response strategies in spatial navigation (23, 44) and choices on nonspatial multistep decision tasks (45, 46). Furthermore, it explains the puzzling finding that landmark-guided navigation is sensitive to the blocking effect, whereas boundary-guided navigation is not (27), and that these are supported by the DLS and HPC, respectively (26). Thus, different RL strategies that manage competing tradeoffs can explain a longstanding body of spatial navigation and decision-making literature under a unified model.     

CYK-1/Formin activation in cortical RhoA signaling centers promotes organismal left–right symmetry breaking

Proper left–right symmetry breaking is essential for animal development, and in many cases, this process is actomyosin-dependent. In Caenorhabditis elegans embryos active torque generation in the actomyosin layer promotes left–right symmetry breaking by driving chiral counterrotating cortical flows. While both Formins and Myosins have been implicated in left–right symmetry breaking and both can rotate actin filaments in vitro, it remains unclear whether active torques in the actomyosin cortex are generated by Formins, Myosins, or both. We combined the strength of C. elegans genetics with quantitative imaging and thin film, chiral active fluid theory to show that, while Non-Muscle Myosin II activity drives cortical actomyosin flows, it is permissive for chiral counterrotation and dispensable for chiral symmetry breaking of cortical flows. Instead, we find that CYK-1/Formin activation in RhoA foci is instructive for chiral counterrotation and promotes in-plane, active torque generation in the actomyosin cortex. Notably, we observe that artificially generated large active RhoA patches undergo rotations with consistent handedness in a CYK-1/Formin–dependent manner. Altogether, we conclude that CYK-1/Formin–dependent active torque generation facilitates chiral symmetry breaking of actomyosin flows and drives organismal left–right symmetry breaking in the nematode worm.

The emergence of left–right asymmetry is essential for normal animal development and, in the majority of animal species, one type of handedness is dominant (1). The actin cytoskeleton plays an instrumental role in establishing the left–right asymmetric body plan of invertebrates like fruit flies (2–6), nematodes (7–11), and pond snails (12–15). Moreover, an increasing number of studies showed that vertebrate left–right patterning also depends on a functional actomyosin cytoskeleton (13, 16–22). Actomyosin-dependent chiral behavior has even been reported in isolated cells (23–28) and such cell-intrinsic chirality has been shown to promote left–right asymmetric morphogenesis of tissues (29, 30), organs (21, 31), and entire embryonic body plans (12, 13, 32, 33). Active force generation in the actin cytoskeleton is responsible for shaping cells and tissues during embryo morphogenesis. Torques are rotational forces with a given handedness and it has been proposed that in plane, active torque generation in the actin cytoskeleton drives chiral morphogenesis (7, 8, 34, 35).What could be the molecular origin of these active torques? The actomyosin cytoskeleton consists of actin filaments, actin-binding proteins, and Myosin motors. Actin filaments are polar polymers with a right-handed helical pitch and are therefore chiral themselves (36, 37). Due to the right-handed pitch of filamentous actin, Myosin motors can rotate actin filaments along their long axis while pulling on them (33, 38–42). Similarly, when physically constrained, members of the Formin family rotate actin filaments along their long axis while elongating them (43). In both cases the handedness of this rotation is determined by the helical nature of the actin polymer. From this it follows that both Formins and Myosins are a potential source of molecular torque generation that could drive cellular and organismal chirality. Indeed, chiral processes across different length scales, and across species, are dependent on Myosins (19), Formins (13–15, 26), or both (7, 8, 21, 44). It is, however, unclear how Formins and Myosins contribute to active torque generation and the emergence chiral processes in developing embryos.In our previous work we showed that the actomyosin cortex of some Caenorhabditis elegans embryonic blastomeres undergoes chiral counterrotations with consistent handedness (7, 35). These chiral actomyosin flows can be recapitulated using active chiral fluid theory that describes the actomyosin layer as a thin-film, active gel that generates active torques (7, 45, 46). Chiral counterrotating cortical flows reorient the cell division axis, which is essential for normal left–right symmetry breaking (7, 47). Moreover, cortical counterrotations with the same handedness have been observed in Xenopus one-cell embryos (32), suggesting that chiral counterrotations are conserved among distant species. Chiral counterrotating actomyosin flow in C. elegans blastomeres is driven by RhoA signaling and is dependent on Non-Muscle Myosin II motor proteins (7). Moreover, the Formin CYK-1 has been implicated in actomyosin flow chirality during early polarization of the zygote as well as during the first cytokinesis (48, 49). Despite having identified a role for Myosins and Formins, the underlying mechanism by which active torques are generated remains elusive.Here we show that the Diaphanous-like Formin, CYK-1/Formin, is a critical determinant for the emergence of actomyosin flow chirality, while Non-Muscle Myosin II (NMY-2) plays a permissive role. Our results show that cortical CYK-1/Formin is recruited by active RhoA signaling foci and promotes active torque generation, which in turn tends to locally rotate the actomyosin cortex clockwise. In the highly connected actomyosin meshwork, a gradient of these active torques drives the emergence of chiral counterrotating cortical flows with uniform handedness, which is essential for proper left–right symmetry breaking. Together, these results provide mechanistic insight into how Formin-dependent torque generation drives cellular and organismal left–right symmetry breaking.     

From the Cover: Overexpression of CD47 is associated with brain overgrowth and 16p11.2 deletion syndrome

Copy number variation (CNV) at the 16p11.2 locus is associated with neuropsychiatric disorders, such as autism spectrum disorder and schizophrenia. CNVs of the 16p gene can manifest in opposing head sizes. Carriers of 16p11.2 deletion tend to have macrocephaly (or brain enlargement), while those with 16p11.2 duplication frequently have microcephaly. Increases in both gray and white matter volume have been observed in brain imaging studies in 16p11.2 deletion carriers with macrocephaly. Here, we use human induced pluripotent stem cells (hiPSCs) derived from controls and subjects with 16p11.2 deletion and 16p11.2 duplication to understand the underlying mechanisms regulating brain overgrowth. To model both gray and white matter, we differentiated patient-derived iPSCs into neural progenitor cells (NPCs) and oligodendrocyte progenitor cells (OPCs). In both NPCs and OPCs, we show that CD47 (a “don’t eat me” signal) is overexpressed in the 16p11.2 deletion carriers contributing to reduced phagocytosis both in vitro and in vivo. Furthermore, 16p11.2 deletion NPCs and OPCs up-regulate cell surface expression of calreticulin (a prophagocytic “eat me” signal) and its binding sites, indicating that these cells should be phagocytosed but fail to be eliminated due to elevations in CD47. Treatment of 16p11.2 deletion NPCs and OPCs with an anti-CD47 antibody to block CD47 restores phagocytosis to control levels. While the CD47 pathway is commonly implicated in cancer progression, we document a role for CD47 in psychiatric disorders associated with brain overgrowth.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social interaction and communication. Copy number variation (CNV) at the 16p11.2 locus is associated with ASD (1–8). People who have 16p11.2 deletion syndrome tend to have larger head circumferences (macrocephaly), with disproportionate enlargement in both gray and white matter volume (8–13). Individuals with ASD and macrocephaly have more severe behavioral and cognitive problems and are less responsive to standard medical and therapeutic interventions than those with ASD and normal head circumferences (14). In addition, prior work has documented a very strong cross-sectional and temporal association between macrocephaly and ASD symptoms (8, 9, 11, 12, 14–17). These findings suggest that understanding the underlying mechanisms regulating macrocephaly could provide a window of opportunity for intervention or mitigation of symptoms.Here, we used patient-derived human induced pluripotent stem cells (hiPSCs) to interrogate the underlying mechanisms contributing to gray and white matter enlargement. We focused on individuals with intellectual disability (IQ < 70) or ASD associated with brain overgrowth in 16p11.2 deletion carriers. We differentiated the iPSCs into neural progenitor cells (NPCs) and oligodendrocyte progenitor cells (OPCs) and investigate the hypothesis that brain enlargement in 16p11.2 deletion carriers may be due to improper cellular elimination. Under normal conditions, classic “eat me” and “don’t eat me” signaling mechanisms associated with phagocytosis maintain cellular homeostasis across diverse tissue types (18, 19). CD47 (a “don’t eat me” signal) protects normal cells from getting cleared (18), but can become overexpressed in many types of cancer cells, preventing tumorigenic cells from getting engulfed or phagocytosed (20–22). In fact, CD47 plays an important role in many pathological disorders associated with an overproduction of cells and cell removal, including cancer (20–22), atherosclerosis (23), and fibrotic diseases (24). NPCs derived from iPSCs of autistic individuals with macrocephaly have increased proliferation relative to controls (25, 26). Therefore, we hypothesized that CD47 may be involved in these disorders.We find that CD47 is overexpressed in NPCs and OPCs derived from 16p11.2 deletion carriers, leading to reduced phagocytosis by macrophages and microglia. Furthermore, the 16p11.2 deletion NPCs and OPCs have increased cell surface expression of calreticulin (CRT, a prophagocytic “eat me” signal), indicating that these cells should be eliminated but are not due to high levels of CD47 (27). Importantly, treatment with a CD47 blocking antibody restores phagocytosis of 16p11.2 deletion NPCs and OPCs to control levels, particularly in 16p_del NPCs and OPCs that have increased cell surface expression of CRT, indicating that the changes in phagocytosis are mediated by cell surface expression of CD47. We thus identify a role for CD47 in 16p11.2 deletion syndrome and highlight the potential importance of blocking CD47 to promote clearance of unhealthy NPCs and OPCs in 16p11.2 deletion with brain overgrowth.     

A rate threshold mechanism regulates MAPK stress signaling and survival

Cells are exposed to changes in extracellular stimulus concentration that vary as a function of rate. However, how cells integrate information conveyed from stimulation rate along with concentration remains poorly understood. Here, we examined how varying the rate of stress application alters budding yeast mitogen-activated protein kinase (MAPK) signaling and cell behavior at the single-cell level. We show that signaling depends on a rate threshold that operates in conjunction with stimulus concentration to determine the timing of MAPK signaling during rate-varying stimulus treatments. We also discovered that the stimulation rate threshold and stimulation rate-dependent cell survival are sensitive to changes in the expression levels of the Ptp2 phosphatase, but not of another phosphatase that similarly regulates osmostress signaling during switch-like treatments. Our results demonstrate that stimulation rate is a regulated determinant of cell behavior and provide a paradigm to guide the dissection of major stimulation rate dependent mechanisms in other systems.

All cells employ signal transduction pathways to respond to physiologically relevant changes in extracellular stressors, nutrient levels, hormones, morphogens, and other stimuli that vary as functions of both concentration and rate in healthy and diseased states (1–7). Switch-like “instantaneous” changes in the concentrations of stimuli in the extracellular environment have been widely used to show that the strength of signaling and overall cellular response are dependent on the stimulus concentration, which in many cases needs to exceed a certain threshold (8, 9). Previous studies have shown that the rate of stimulation can also influence signaling output in a variety of pathways (10–17) and that stimulation profiles of varying rates can be used to probe underlying signaling pathway circuitry (4, 18, 19). However, it is still not clear how cells integrate information conveyed by changes in both the stimulation rate and concentration in determining signaling output. It is also not clear if cells require stimulation gradients to exceed a certain rate in order to commence signaling.Recent investigations have demonstrated that stimulation rate can be a determining factor in signal transduction. In contrast to switch-like perturbations, which trigger a broad set of stress-response pathways, slow stimulation rates activate a specific response to the stress applied in Bacillus subtilis cells (10). Meanwhile, shallow morphogen gradient stimulation fails to activate developmental pathways in mouse myoblast cells in culture, even when concentrations sufficient for activation during pulsed treatment are delivered (12). These observations raise the possibility that stimulation profiles must exceed a set minimum rate or rate threshold to achieve signaling activation. Although such rate thresholds would help cells decide if and how to respond to dynamic changes in stimulus concentration, the possibility of signaling regulation by a rate threshold has never been directly investigated in any system. Further, no study has experimentally examined how stimulation rate requirements impact cell phenotype or how cells molecularly regulate the stimulation rate required for signaling activation. As such, the biological significance of any existing rate threshold regulation of signaling remains unknown.The budding yeast Saccharomyces cerevisiae high osmolarity glycerol (HOG) pathway provides an ideal model system for addressing these issues (Fig. 1A). The evolutionarily conserved mitogen-activated protein kinase (MAPK) Hog1 serves as the central signaling mediator of this pathway (20–22). It is well established that instantaneous increases in osmotic stress concentration induce Hog1 phosphorylation, activation, and translocation to the nucleus (18, 21, 23–30). Activated Hog1 governs the majority of the cellular osmoadaptation response that enables cells to survive (23, 31, 32). Multiple apparently redundant MAPK phosphatases dephosphorylate and inactivate Hog1, which, along with the termination of upstream signaling after adaptation, results in its return to the cytosol (Fig. 1A) (23, 25, 26, 33–39). Because of this behavior, time-lapse analysis of Hog1 nuclear enrichment in single cells has proven an excellent and sensitive way to monitor signaling responses to dynamic stimulation patterns in real time (18, 27–30, 40, 41). Further, such assays have been readily combined with traditional growth and molecular genetic approaches to link observed signaling responses with cell behavior and signaling pathway architecture (27–29).Open in a separate windowFig. 1.Hog1 signaling and cell survival are sensitive to the rate of preconditioning osmotic stress application. (A) Schematic of the budding yeast HOG response. (B) Preconditioning protection assay workflow indicating the first stress treatments to a final concentration of 0.4 M NaCl (Left), high-stress exposure (Middle), and colony formation readout (Right). (C) High-stress survival as a function of each first treatment relative to the untreated first stress condition. Bars and errors are means and SD from three biological replicates. *Statistically significant by Kolmogorov–Smirnov test (P < 0.05). NS = not significant. (D) Treatment concentration over time. (E) Treatment rate over time for quadratic and pulse treatment. The rate for the pulse is briefly infinite (blue vertical line) before it drops to 0. (F) Hog1 nuclear localization during the treatments depicted in D and E. (Inset) Localization pattern in the quadratic-treated sample. Lines represent means and shaded error represents the SD from three to four biological replicates.Here, we use systematically designed osmotic stress treatments imposed at varying rates of increase to show that a rate threshold condition regulates yeast high-stress survival and Hog1 MAPK signaling. We demonstrate that only stimulus profiles that satisfy both this rate threshold condition and a concentration threshold condition result in robust signaling. We go on to show that the protein tyrosine phosphatase Ptp2, but not the related Ptp3 phosphatase, serves as a major rate threshold regulator. By expressing PTP2 under the control of a series of different enhancer–promoter DNA constructs, we demonstrate that changes in the level of Ptp2 expression can alter the stimulation rate required for signaling induction and survival. These findings establish rate thresholds as a critical and regulated component of signaling biology akin to concentration thresholds.     

Heading perception depends on time-varying evolution of optic flow

There is considerable support for the hypothesis that perception of heading in the presence of rotation is mediated by instantaneous optic flow. This hypothesis, however, has never been tested. We introduce a method, termed “nonvarying phase motion,” for generating a stimulus that conveys a single instantaneous optic flow field, even though the stimulus is presented for an extended period of time. In this experiment, observers viewed stimulus videos and performed a forced-choice heading discrimination task. For nonvarying phase motion, observers made large errors in heading judgments. This suggests that instantaneous optic flow is insufficient for heading perception in the presence of rotation. These errors were mostly eliminated when the velocity of phase motion was varied over time to convey the evolving sequence of optic flow fields corresponding to a particular heading. This demonstrates that heading perception in the presence of rotation relies on the time-varying evolution of optic flow. We hypothesize that the visual system accurately computes heading, despite rotation, based on optic acceleration, the temporal derivative of optic flow.

James Gibson first remarked that the instantaneous motion of points on the retina (Fig. 1A) can be formally described as a two-dimensional (2D) field of velocity vectors called the “optic flow field” (or “optic flow”) (1). Such optic flow, caused by an observer’s movement relative to the environment, conveys information about self-motion and the structure of the visual scene (1–15). When an observer translates in a given direction along a straight path, the optic flow field radiates from a point in the image with zero velocity, or singularity, called the focus of expansion (Fig. 1B). It is well known that under such conditions, one can accurately estimate one’s “heading” (i.e., instantaneous direction of translation in retinocentric coordinates) by simply locating the focus of expansion (SI Appendix). However, if there is angular rotation in addition to translation (by moving along a curved path or by a head or eye movement), the singularity in the optic flow field will be displaced such that it no longer corresponds to the true heading (Fig. 1 C and D). In this case, if one estimates heading by locating the singularity, the estimate will be biased away from the true heading. This is known as the rotation problem (14).Open in a separate windowFig. 1.Projective geometry, the rotation problem, time-varying optic flow, and the optic acceleration hypothesis. (A) Viewer-centered coordinate frame and perspective projection. Because of motion between the viewpoint and the scene, a 3D surface point traverses a path in 3D space. Under perspective projection, the 3D path of this point projects onto a 2D path in the image plane (retina), the temporal derivative of which is called image velocity. The 2D velocities associated with all visible points define a dense 2D vector field called the optic flow field. (B–D) Illustration of the rotation problem. (B) Optic flow for pure translation (1.5-m/s translation speed, 0° heading, i.e., heading in the direction of gaze). Optic flow singularity (red circle) corresponds to heading (purple circle). (C) Pure rotation, for illustrative purposes only and not corresponding to any experimental condition (2°/s rightward rotation). (D) Translation + rotation (1.5 m/s translation speed, 0° heading, 2°/s rightward rotation). Optic flow singularity (red circle) is displaced away from heading (purple circle). (E) Three frames from a video depicting movement along a circular path with the line-of-sight initially perpendicular to a single fronto-parallel plane composed of black dots. (F) Time-varying evolution of optic flow. The first optic flow field reflects image motion between the first and second frames of the video. The second optic flow field reflects image motion between the second and third frames of the video. For this special case (circular path), the optic flow field evolves (and the optic flow singularity drifts) only due to the changing depth of the environment relative to the viewpoint. (G) Illustration of the optic acceleration hypothesis. Optic acceleration is the derivative of optic flow over time (here, approximated as the difference between the second and first optic flow fields). The singularity of the optic acceleration field corresponds to the heading direction. Acceleration vectors autoscaled for visibility.Computer vision researchers and vision scientists have developed a variety of algorithms that accurately and precisely extract observer translation and rotation from optic flow, thereby solving the rotation problem. Nearly all of these rely on instantaneous optic flow (i.e., a single optic flow field) (4, 9, 16–25) with few exceptions (26–29). However, it is unknown whether these algorithms are commensurate with the neural computations underlying heading perception.The consensus of opinion in the experimental literature is that human observers can estimate heading (30, 31) from instantaneous optic flow, in the absence of additional information (5, 10, 15, 32–34). Even so, there are reports of systematic biases in heading perception (11); the visual consequences of rotation (eye, head, and body) can bias heading judgments (10, 15, 35–37), with the amount of bias typically proportional to the magnitude of rotation. Other visual factors, such as stereo cues (38, 39), depth structure (8, 10, 40–43), and field of view (FOV) (33, 42–44) can modulate the strength of these biases. Errors in heading judgments have been reported to be greater when eye (35–37, 45, 46) or head movements (37) are simulated versus when they are real, which has been taken to mean that observers require extraretinal information, although there is also evidence to the contrary (10, 15, 33, 40, 41, 44, 47–50). Regardless, to date no one has tested whether heading perception (even with these biases) is based on instantaneous optic flow or on the information available in how the optic flow field evolves over time. Some have suggested that heading estimates rely on information accumulated over time (32, 44, 51), but no one has investigated the role of time-varying optic flow without confounding it with stimulus duration (i.e., the duration of evidence accumulation).In this study, we employed an application of an image processing technique that ensured that only a single optic flow field was available to observers, even though the stimulus was presented for an extended period of time. We called this condition “nonvarying phase motion” or “nonvarying”: The phases of two component gratings comprising each stationary stimulus patch shifted over time at a constant rate, causing a percept of motion in the absence of veridical movement (52). Phase motion also eliminated other cues that may otherwise have been used for heading judgments, including image point trajectories (15, 32) and their spatial compositions (i.e., looming) (53, 54). For nonvarying phase motion, observers exhibited large biases in heading judgments in the presence of rotation. A second condition, “time-varying phase motion,” or “time-varying,” included acceleration by varying the velocity of phase motion over time to match the evolution of a sequence of optic flow fields. Doing so allowed observers to compensate for the confounding effect of rotation on optic flow, making heading perception nearly veridical. This demonstrates that heading perception in the presence of rotation relies on the time-varying evolution of optic flow.     

Molecular switch architecture determines response properties of signaling pathways

Many intracellular signaling pathways are composed of molecular switches, proteins that transition between two states—on and off. Typically, signaling is initiated when an external stimulus activates its cognate receptor that, in turn, causes downstream switches to transition from off to on using one of the following mechanisms: activation, in which the transition rate from the off state to the on state increases; derepression, in which the transition rate from the on state to the off state decreases; and concerted, in which activation and derepression operate simultaneously. We use mathematical modeling to compare these signaling mechanisms in terms of their dose–response curves, response times, and abilities to process upstream fluctuations. Our analysis elucidates several operating principles for molecular switches. First, activation increases the sensitivity of the pathway, whereas derepression decreases sensitivity. Second, activation generates response times that decrease with signal strength, whereas derepression causes response times to increase with signal strength. These opposing features allow the concerted mechanism to not only show dose–response alignment, but also to decouple the response time from stimulus strength. However, these potentially beneficial properties come at the expense of increased susceptibility to upstream fluctuations. We demonstrate that these operating principles also hold when the models are extended to include additional features, such as receptor removal, kinetic proofreading, and cascades of switches. In total, we show how the architecture of molecular switches govern their response properties. We also discuss the biological implications of our findings.

Several molecules involved in intracellular signaling pathways act as molecular switches. These are proteins that can be temporarily modified to transition between two conformations, one corresponding to an on (active) state and another to an off (inactive) state. Two prominent examples of such switches are proteins that are modified by phosphorylation and dephosphorylation and GTPases that bind nucleotides. For phosphorylation–dephosphorylation cycles, it is common for the covalent addition of a phosphate by a kinase to cause activation of the modified protein. A phosphatase removes the phosphate to turn the protein off. In the GTPase cycle, the protein is on when bound to guanosine triphosphate (GTP) and off when bound to guanosine diphosphate (GDP). The transition from the GDP-bound state to the GTP-bound state requires nucleotide exchange, whereas the transition from the GTP-bound to the GDP-bound state is achieved via hydrolysis of the γ phosphate on GTP. The basal rates of nucleotide exchange and hydrolysis are often small. These reaction rates are increased severalfold by Guanine Exchange Factors (GEFs) and GTPase Accelerating Proteins (GAPs), respectively (1, 2).A signaling pathway is often initiated upon recognition of a stimulus by its cognate receptor, which then activates a downstream switch. In principle, a switch may be turned on by three mechanisms: (a) activation, by increasing the transition rate from the off state to the on state; (b) derepression, by decreasing the transition rate from the on state to the off state; and (c) concerted activation and derepression. Examples of these three mechanisms are found in the GTPase cycles in different organisms. In animals, signaling through many pathways is initiated by G-protein-coupled receptors (GPCRs) that respond to a diverse set of external stimuli. These receptors act as GEFs to activate heterotrimeric G proteins (3–6). Thus, pathway activation relies upon increasing the transition rate from the off state to the on state. There are no GPCRs in plants and other bikonts; the nucleotide exchange occurs spontaneously, without requiring GEF activity (7–9). G proteins are kept in the off state by a repressor such as a GAP or some other protein that holds the self-activating G protein in its inactive state. In this scenario, the presence of a stimulus results in derepression, i.e., removal of the repressing activity (10–12). Concerted activation and dererpression occur in the GTPase cycle of the yeast mating-response pathway (13, 14), in which the inactive GPCRs recruit a GAP protein and act to repress, whereas active receptors have GEF activity and act to activate. Thus, perception of a stimulus leads to concerted activation and derepression by increasing GEF activity while decreasing GAP activity.These three mechanisms of signaling through molecular switches also occur in many other systems. For example, the activation mechanism described here is a simpler abstraction of a linear signaling cascade, a classical framework used to study general properties of signaling pathways (15–19), as well as to model specific signaling pathways (20–22). While derepression may seem like an unusual mechanism, it occurs in numerous important signaling pathways in plants (e.g., auxin, ethylene, gibberellin, and phytochrome), as well as gene regulation (23–27). In many of these cases, derepression occurs through a decrease in the degradation rate of a component instead of its deactivation rate. Concerted mechanisms are found in bacterial two-component systems, wherein the same component acts as kinase and phosphatase (28–35).Many previous studies have focused on the properties of a single switch mechanism without drawing comparisons between the three potential ways for initiating signaling. For example, the classical Goldbeter–Koshland model studied zero-order ultrasensitivity of an activation mechanism (15). Further analyses examined the effect of receptor numbers (36–38), feedback mechanisms (39, 40), and removal of active receptors via endocytosis and degradation (41, 42). Similarly, important properties of the concerted mechanism have been elucidated, such as its ability to perform ratiometric signaling (13, 14), to align dose responses at different stages of the signaling pathway (43), as well as its robustness (29, 44). The derepression mechanism is relatively less studied. Although there are models of G-signaling in Arabidopsis thaliana (45–47), these models have a large number of states and parameters and do not specifically examine distinct behaviors conferred by derepression.What are the evolutionary constraints that may favor activation over derepression and vice versa? Seminal studies have investigated this question for gene-regulatory networks (48–50). However, an analysis of differences in the functional characteristics of activation, derepression, and concerted mechanisms in the context of cell signaling is still lacking. To address this deficiency, we perform a systematic comparison of the three mechanisms using the following metrics: 1) dose–response, 2) response time, and 3) ability to suppress or filter stochastic fluctuations in upstream components. The rationale behind comparing dose–response curves is that they provide information about the input sensitivity range and the output dynamic range, both of which are of pharmacological importance. We supplement this comparison with response times, which provide information about the dynamics of the signaling activity. The third metric of comparison is motivated from the fact that signaling pathways are subject to intrinsic fluctuations that occur due to the stochastic nature of biochemical reactions (51–56).We construct and analyze both deterministic ordinary differential equation (ODE) models and stochastic models based on continuous-time Markov chains. We show that activation has the following two effects: It makes the switch response more sensitive than that of the receptor, and it speeds up the response with the stimulus strength. In contrast, derepression makes the switch response less sensitive than the receptor occupancy and slows down the response speed as stimulus strength increases. These counteracting behaviors of activation and derepression lead to intermediate sensitivity and intermediate response time for the concerted mechanism. In the special case of a perfect concerted mechanism (equal activation and repression), the dose–response curve of the pathway aligns with the receptor occupancy, and the response time does not depend upon the stimulus level. The noise comparison reveals that the concerted mechanism is more susceptible to fluctuations than the activation and derepression mechanisms, which perform similarly. We further show that these results qualitatively hold for more complex models, such as those incorporating receptor removal and proofreading. We finally discuss our findings to suggest reasons that might have led biological systems to evolve one of these mechanisms over the others, a question that has received considerable attention in the context of gene regulation (48–50).     

Layer and rhythm specificity for predictive routing

In predictive coding, experience generates predictions that attenuate the feeding forward of predicted stimuli while passing forward unpredicted “errors.” Different models have suggested distinct cortical layers, and rhythms implement predictive coding. We recorded spikes and local field potentials from laminar electrodes in five cortical areas (visual area 4 [V4], lateral intraparietal [LIP], posterior parietal area 7A, frontal eye field [FEF], and prefrontal cortex [PFC]) while monkeys performed a task that modulated visual stimulus predictability. During predictable blocks, there was enhanced alpha (8 to 14 Hz) or beta (15 to 30 Hz) power in all areas during stimulus processing and prestimulus beta (15 to 30 Hz) functional connectivity in deep layers of PFC to the other areas. Unpredictable stimuli were associated with increases in spiking and in gamma-band (40 to 90 Hz) power/connectivity that fed forward up the cortical hierarchy via superficial-layer cortex. Power and spiking modulation by predictability was stimulus specific. Alpha/beta power in LIP, FEF, and PFC inhibited spiking in deep layers of V4. Area 7A uniquely showed increases in high-beta (∼22 to 28 Hz) power/connectivity to unpredictable stimuli. These results motivate a conceptual model, predictive routing. It suggests that predictive coding may be implemented via lower-frequency alpha/beta rhythms that “prepare” pathways processing-predicted inputs by inhibiting feedforward gamma rhythms and associated spiking.

The brain exploits predictability. It makes cortical processing more efficient. Visuomotor integration, visual/auditory speech perception, and visual perception all benefit when sensory inputs are predictable (1–3). The brain has an arsenal of mechanisms to tamp down and improve processing of familiar, repeated, or predictable inputs. One example is stimulus-specific adaptation. All over cortex, there is less spiking and smaller blood-oxygen-level-dependent (BOLD) responses when a stimulus is repeated (4–9). Responsiveness is recovered if the stimulus is changed or a pattern is violated (i.e., to “oddballs”) (10, 11). This can lead to fewer activated neurons but finer-tuned, more robust representations (8).But the brain does more than adapt to repeated inputs. A wide variety of evidence indicates that it makes mental models of the world that actively generate predictions, a process known as predictive coding (12–14). Moment-to-moment predictions are used to inhibit processing of expected inputs which, because they were expected, are not informative. Unexpected sensory inputs that deviate from a prediction, are “prediction errors” (PEs). They are informative and thus not inhibited, fed forward, processed, affect behavior, and are used to update the prediction models.Much of the work on the neural mechanisms of prediction and its violation has focused on spiking activity (2, 15–17). But there is mounting evidence that oscillatory dynamics play a role in regulating cortical processing and thus can also play a role, especially the gamma (40 to 90 Hz) and alpha/beta (10 to 30 Hz) bands (1, 18–25). A key observation is that, all across cortex, gamma power (>35 Hz)/spiking is higher during bottom-up sensory inputs. They are anticorrelated with alpha/beta (8 to 30 Hz) power (26–29), which is higher under conditions of top-down control (e.g., attention and response inhibition) (30–34). This suggests that top-down alpha/beta help regulate the processing of bottom-up inputs served by gamma and spiking. The idea is that alpha/beta carries the top-down predictions that inhibit the gamma/spiking that process expected inputs. This is consistent with gamma power being higher in the superficial, feedforward, cortical layers, and alpha/beta power being higher in the deep, feedback, cortical layers (26, 35–40). Indeed, superficial cortical layers have been hypothesized to be specialized for computing PEs and feeding PEs forward at gamma frequency (1, 19). In addition, computational modeling studies have shown the plausibility of superficial gamma circuits to engage in prediction error computations (38, 41, 42). Direct evidence for alpha/beta and gamma in predictive coding per se comes from observations of increased gamma power to stimuli that are prediction errors (22, 24, 25).How these rhythms (and their relation to spiking) differ with stimulus repetition/predictability as well as their stimulus specificity is not well known. Most neurophysiological studies of the effects of stimulus predictability have focused on spiking activity, often in a single area. And none of them to date have examined and compared activity in different cortical layers. We recorded local field potentials (LFPs) and spiking using multiarea, multilaminar recordings from a visual area (V4) and higher-order cortical areas (posterior parietal cortex and prefrontal cortex [PFC]) simultaneously. Area V4 was selected as previous studies have shown this area to be a target of top-down signals such as attention (43, 44). Frontoparietal cortex was targeted because of its well-established role in top-down attention and working memory, cognitive processes that are engaged in the task employed here (30, 31). We manipulated the predictability of objects used in a working memory task. This revealed layer and frequency-specific associations with stimulus repetition/predictability as well as evidence for the direction of flow of these signals. The findings suggest an update of neural models of prediction and predictive coding.     

Rules of contact inhibition of locomotion for cells on suspended nanofibers

Contact inhibition of locomotion (CIL), in which cells repolarize and move away from contact, is now established as a fundamental driving force in development, repair, and disease biology. Much of what we know of CIL stems from studies on two-dimensional (2D) substrates that do not provide an essential biophysical cue—the curvature of extracellular matrix fibers. We discover rules controlling outcomes of cell–cell collisions on suspended nanofibers and show them to be profoundly different from the stereotyped CIL behavior on 2D substrates. Two approaching cells attached to a single fiber do not repolarize upon contact but rather usually migrate past one another. Fiber geometry modulates this behavior; when cells attach to two fibers, reducing their freedom to reorient, only one cell repolarizes on contact, leading to the cell pair migrating as a single unit. CIL outcomes also change when one cell has recently divided and moves with high speed—cells more frequently walk past each other. Our computational model of CIL in fiber geometries reproduces the core qualitative results of the experiments robustly to model parameters. Our model shows that the increased speed of postdivision cells may be sufficient to explain their increased walk-past rate. We also identify cell–cell adhesion as a key mediator of collision outcomes. Our results suggest that characterizing cell–cell interactions on flat substrates, channels, or micropatterns is not sufficient to predict interactions in a matrix—the geometry of the fiber can generate entirely new behaviors.

Cell migration is an essential component of various physiological processes such as morphogenesis, wound healing, and metastasis (1). Cell–cell interactions in which cell–cell contact reorients cell polarity are necessary for the correct function of many developmental events (2). One of the earliest such interactions known was termed “contact inhibition of locomotion” (CIL) by Abercombie and Heaysman over five decades ago in chick fibroblasts cultured on flat two-dimensional (2D) substrates (2–4). In CIL, two approaching cells isolated from the rest of the cell population first make contact, followed by protrusion inhibition at the site of contact, which leads to cell repolarization through formation of new protrusions away from the site of contact. Subsequently, cells migrate away from each other in the direction of newly formed protrusions (1). This sequence can, however, be altered in specific conditions such as metastasis in which a loss of CIL allows malignant cells to invade fibroblast cultures—this is a loss of CIL between different cell types (heterotypic CIL) (4, 5). Recent work has also begun to identify the molecular players that initiate and regulate CIL, including Rac activity, microtubules, Eph/Ephrin binding, and E- and N-cadherin expression (6–10).CIL is most commonly studied and analyzed on flat 2D substrates using several invasion and collision assays (2, 3, 11). By contrast, cells traveling in matrix in vivo are constrained to move along narrow fibers. A common shortcoming in featureless 2D assays is thus the inability to study CIL under natural constraints (11–13). Recently, micropatterned substrates have been used to understand restricted motility, developing one-dimensional (1D) collision assays where cell migration is constrained to straight lines, allowing for a greater occurrence of cell–cell collisions to quantify rates and outcomes of different types of cell–cell interactions (11, 13–15). These interactions do not necessarily resemble the stereotyped CIL behavior. Broadly, experiments and simulations (16–18) have observed the following: 1) the classical stereotype of CIL with two cells contacting head-on, with both cells repolarizing (referred to as “reversal” or “mutual CIL”); 2) after a head-on collision, only one cell reverses (“training” or “nonmutual CIL”); and 3) cells manage to crawl past or over one another, exchanging positions (“walk past” or “sliding”). Within the well-studied neural-crest cell explants, walk past is extremely rare (11), but it can occur in epithelial cells, especially in those that have been metastatically transformed or that have decreased E-cadherin expression (15).Both 2D substrates and micropatterned stripes provide controllable and reproducible environments but neither fully models the details of in vivo native cellular environments, which consist of extracellular matrices (ECM) of fibrous proteins, with these fibers having different radii. Our earlier in vitro recapitulation of the effects of fiber curvature showed that both protrusive and migratory behavior is sensitive to fiber diameter (19–21). Furthermore, we have shown that suspended, flat 2D ribbons do not capture the protrusive behavior observed on suspended round fibers (19); thus, we wanted to inquire if the CIL rules developed on 1D collision and 2D assays extend to contextually relevant fibrous environments. To understand CIL in fibrous environments that mimic native ECM, we use suspended and aligned nanofiber networks to study CIL behavior in NIH/3T3 fibroblast cell–cell pairs exhibiting two distinct elongated morphologies: spindle, attached to a single fiber and parallel cuboidal, attached to two fibers (22). We further investigate the effect of cell division on CIL by studying the encounters of cells that have recently divided (daughter cells) with other cells; these recently divided cells are much faster, consistent with earlier work (23). Our work allows us to determine the types and rates of cell–cell contact outcomes—the “rules of CIL”—in a biologically relevant system with a controlled geometry. These rules are radically different from the known stereotypical behavior in 2D assays, but the essential features of these rules emerge robustly from a minimal computational model of CIL in confined geometries.