Dynamic cell cycle-dependent phosphorylation modulates CENP-L-CENP-N centromere recruitment

The kinetochore is a macromolecular structure that is required to ensure proper chromosome segregation during each cell division. The kinetochore is assembled upon a platform of the 16-subunit Constitutive Centromere Associated Network (CCAN), which is present at centromeres throughout the cell cycle. The nature and regulation of CCAN assembly, interactions, and dynamics required to facilitate changing centromere properties and requirements remain to be fully elucidated. The CENP-LN CCAN sub-complex displays a unique cell cycle-dependent localization behavior, peaking in S phase. Here, we demonstrate that phosphorylation of CENP-L and CENP-N controls CENP-LN complex formation and localization in a cell cycle-dependent manner. Mimicking constitutive phosphorylation of either CENP-L or CENP-N or simultaneously preventing phosphorylation of both proteins prevents CENP-LN localization and disrupts chromosome segregation. Together, our work suggests that cycles of phosphorylation and dephosphorylation are critical for CENP-LN complex recruitment and dynamics at centromeres to enable cell cycle-dependent CCAN reorganization.

A somatosensory computation that unifies bodies and tools

It is often claimed that tools are embodied by the user, but whether the brain actually repurposes its body-based computations to perform similar tasks with tools is not known. A fundamental body-based computation used by the somatosensory system is trilateration. Here, the location of touch on a limb is computed by integrating estimates of the distance between sensory input and its boundaries (e.g., elbow and wrist of the forearm). As evidence of this computational mechanism, tactile localization on a limb is most precise near its boundaries and lowest in the middle. If the brain repurposes trilateration to localize touch on a tool, we should observe this computational signature in behavior. In a large sample of participants, we indeed found that localizing touch on a tool produced the signature of trilateration, with highest precision close to the base and tip of the tool. A computational model of trilateration provided a good fit to the observed localization behavior. Importantly, model selection demonstrated that trilateration better explained each participant's behavior than an alternative model of localization. These results have important implications for how trilateration may be implemented by somatosensory neural populations. In sum, the present study suggests that tools are indeed embodied at a computational level, repurposing a fundamental spatial computation.

A lobster-inspired multi-robot control strategy for monitoring non-stationary concentration fields

We propose a new lobster-inspired chemotaxis decentralized control strategy for monitoring a non-stationary concentration field using a team of nonholonomic mobile robots. The task of the team is to locate and trace the movement of the point (or points) with the highest field value (i.e. source), provided that the robots are not aware of the dynamics of the field and can only periodically sample the field at their locations. As an example of the concentration field we consider a population of biological species modeled by a self-organizing multi-agent system with agents acting as individuals of the population in accordance with some flocking rules. The proposed strategy combines the lobsters’ plume localization behavior and flocking mechanisms to efficiently solve the problem even with a small group of robots. Simulations and experimental works on physical unicycle robots are performed to validate the efectiveness of the approach for the cases of non-stationary fields.

Illusory tactile movement crosses arms and legs and is coded in external space

Humans often misjudge where on the body a touch occurred. Theoretical accounts have ascribed such misperceptions to local interactions in peripheral and primary somatosensory neurons, positing that spatial-perceptual mechanisms adhere to limb boundaries and skin layout. Yet, perception often reflects integration of sensory signals with prior experience. On their trajectories, objects often touch multiple limbs; therefore, body-environment interactions should manifest in perceptual mechanisms that reflect external space. Here, we demonstrate that humans perceived the cutaneous rabbit illusion - the percept of multiple identical stimuli as hopping across the skin - along the Euclidian trajectory between stimuli on two body parts and regularly mislocalized stimuli from one limb to the other. A Bayesian model based on Euclidian, as opposed to anatomical, distance faithfully reproduced key aspects of participants' localization behavior. Our results suggest that prior experience of touch in space critically shapes tactile spatial perception and illusions beyond anatomical organization.

A massively parallel reporter assay reveals focused and broadly encoded RNA localization signals in neurons

Asymmetric subcellular localization of mRNA is a common cellular phenomenon that is thought to contribute to spatial gene regulation. In highly polar neurons, subcellular transcript localization and translation are thought to enhance cellular efficiency and timely responses to external cues. Although mRNA localization has been observed in many tissues and numerous examples of the functional importance of this process exist, we still lack a systematic understanding of how the transcript sorting machinery works in a sequence-specific manner.Here, we addressed these gaps by combining subcellular transcriptomics and rationally designed sequence libraries. We developed a massively parallel reporter assay (MPRA) for mRNA localization and tested ~50,000 sequences for their ability to drive RNA localization to neurites of neuronal cell lines. By scanning the 3’UTR of >300 genes we identified many previously unknown localization regions and mapped the localization potential of endogenous sequences. Our data suggest two ways the localization potential can be encoded in the 3’UTR: focused localization motifs and broadly encoded localization potential based on small contributions.We identified sequence motifs enriched in dendritically localized transcripts and tested the potential of these motifs to affect the localization behavior of an mRNA. This assay revealed sequence elements with the ability to bias localization towards neurite as well as soma. Depletion of RNA binding proteins predicted or experimentally shown to bind these motifs abolished the effect on localization, suggesting that these motifs act by recruiting specific RNA-binding proteins.Based on our dataset we developed machine learning models that accurately predict the localization behavior of novel sequences. Testing this predictor on native mRNA sequencing data showed good agreement between predicted and observed localization potential, suggesting that the rules uncovered by our MPRA also apply to the localization of native transcripts.Applying similar systematic high-throughput approaches to other cell types will open the door for a comparative perspective on RNA localization across tissues and reveal the commonalities and differences of this crucial regulatory mechanism.