The tandem repeat modules of Xist lncRNA: a swiss army knife for the control of X-chromosome inactivation

X-inactive-specific transcript (Xist) is a long non-coding RNA (lncRNA) essential for X-chromosome inactivation (XCI) in female placental mammals. Thirty years after its discovery, it is still puzzling how this lncRNA triggers major structural and transcriptional changes leading to the stable silencing of an entire chromosome. Recently, a series of studies in mouse cells have uncovered domains of functional specialization within Xist mapping to conserved tandem repeat regions, known as Repeats A-to-F. These functional domains interact with various RNA binding proteins (RBPs) and fold into distinct RNA structures to execute specific tasks in a synergistic and coordinated manner during the inactivation process. This modular organization of Xist is mostly conserved in humans, but recent data point towards differences regarding functional specialization of the tandem repeats between the two species. In this review, we summarize the recent progress on understanding the role of Xist repetitive blocks and their involvement in the molecular mechanisms underlying XCI. We also discuss these findings in the light of the similarities and differences between mouse and human Xist.

Mounting, structure and autocleavage of a type VI secretion-associated Rhs polymorphic toxin

Bacteria have evolved toxins to outcompete other bacteria or to hijack host cell pathways. One broad family of bacterial polymorphic toxins gathers multidomain proteins with a modular organization, comprising a C-terminal toxin domain fused to a N-terminal domain that adapts to the delivery apparatus. Polymorphic toxins include bacteriocins, contact-dependent growth inhibition systems, and specialized Hcp, VgrG, PAAR or Rhs Type VI secretion (T6SS) components. We recently described and characterized Tre23, a toxin domain fused to a T6SS-associated Rhs protein in Photorhabdus laumondii, Rhs1. Here, we show that Rhs1 forms a complex with the T6SS spike protein VgrG and the EagR chaperone. Using truncation derivatives and cross-linking mass spectrometry, we demonstrate that VgrG-EagR-Rhs1 complex formation requires the VgrG C-terminal β-helix and the Rhs1 N-terminal region. We then report the cryo-electron-microscopy structure of the Rhs1-EagR complex, demonstrating that the Rhs1 central region forms a β-barrel cage-like structure that encapsulates the C-terminal toxin domain, and provide evidence for processing of the Rhs1 protein through aspartyl autoproteolysis. We propose a model for Rhs1 loading on the T6SS, transport and delivery into the target cell.

The overlapping modular organization of human brain functional networks across the adult lifespan

Previous lifespan studies have demonstrated that the brain functional modular organization would change along with the adult lifespan. Yet, they assumed mutual exclusion among functional modules, ignoring convergent evidence for the existence of modular overlap. To reveal how age affects the overlapping functional modular organization, this study applied a detection algorithm requiring no prior knowledge of the resting-state fMRI data of a healthy cohort (N = 570, 18-88 years). Age-related regression analyses found a linear decrease in the overlapping modularity and the similarity of modular structure and overlapping node (i.e., region involved in multiple modules) distribution. The number of overlapping nodes increased with age, but the increment was distributed unevenly. In addition, across the adult lifespan and within each age group, the nodal overlapping probability consistently exhibited positive correlations with both functional gradient and flexibility. Further, we showed that the influence of age on memory-related cognitive performance might be explained by the change in the overlapping functional modular organization. Together, our results revealed age-related decreased segregation from the perspective of brain functional overlapping modular organization, providing new insight into the adult lifespan change in brain function and its influence on cognitive performance.

Controlling Clinical States Governed by Different Temporal Dynamics With Closed-Loop Deep Brain Stimulation: A Principled Framework

Closed-loop strategies for deep brain stimulation (DBS) are paving the way for improving the efficacy of existing neuromodulation therapies across neurological disorders. Unlike continuous DBS, closed-loop DBS approaches (cl-DBS) optimize the delivery of stimulation in the temporal domain. However, clinical and neurophysiological manifestations exhibit highly diverse temporal properties and evolve over multiple time-constants. Moreover, throughout the day, patients are engaged in different activities such as walking, talking, or sleeping that may require specific therapeutic adjustments. This broad range of temporal properties, along with inter-dependencies affecting parallel manifestations, need to be integrated in the development of therapies to achieve a sustained, optimized control of multiple symptoms over time. This requires an extended view on future cl-DBS design. Here we propose a conceptual framework to guide the development of multi-objective therapies embedding parallel control loops. Its modular organization allows to optimize the personalization of cl-DBS therapies to heterogeneous patient profiles. We provide an overview of clinical states and symptoms, as well as putative electrophysiological biomarkers that may be integrated within this structure. This integrative framework may guide future developments and become an integral part of next-generation precision medicine instruments.

Modular origins of high-amplitude cofluctuations in fine-scale functional connectivity dynamics

The topology of structural brain networks shapes brain dynamics, including the correlation structure of brain activity (functional connectivity) as estimated from functional neuroimaging data. Empirical studies have shown that functional connectivity fluctuates over time, exhibiting patterns that vary in the spatial arrangement of correlations among segregated functional systems. Recently, an exact decomposition of functional connectivity into frame-wise contributions has revealed fine-scale dynamics that are punctuated by brief and intermittent episodes (events) of high-amplitude cofluctuations involving large sets of brain regions. Their origin is currently unclear. Here, we demonstrate that similar episodes readily appear in silico using computational simulations of whole-brain dynamics. As in empirical data, simulated events contribute disproportionately to long-time functional connectivity, involve recurrence of patterned cofluctuations, and can be clustered into distinct families. Importantly, comparison of event-related patterns of cofluctuations to underlying patterns of structural connectivity reveals that modular organization present in the coupling matrix shapes patterns of event-related cofluctuations. Our work suggests that brief, intermittent events in functional dynamics are partly shaped by modular organization of structural connectivity.

Spontaneous emergence of topologically robust grid cell modules: A multiscale instability theory

Modular structures in the brain play a central role in compositionality and intelligence, however the general mechanisms driving module emergence have remained elusive. Studying entorhinal grid cells as paradigmatic examples of modular architecture and function, we demonstrate the spontaneous emergence of a small number of discrete spatial and functional modules from an interplay between continuously varying lateral interactions generated by smooth cortical gradients. We derive a comprehensive analytic theory of modularization, revealing that the process is highly generic with its robustness deriving from topological origins. The theory generates universal predictions for the sequence of grid period ratios, furnishing the most accurate explanation of grid cell data to date. Altogether, this work reveals novel principles by which simple bottom-up dynamical interactions lead to macroscopic modular organization.

Sex-specific tuning of modular muscle activation patterns for locomotion in young and older adults

There is increasing evidence that including sex as a biological variable is of crucial importance to promote rigorous, repeatable and reproducible science. In spite of this, the body of literature that accounts for the sex of participants in human locomotion studies is small and often produces controversial results. Here, we investigated the modular organization of muscle activation patterns for human locomotion using the concept of muscle synergies with a double purpose: i) uncover possible sex-specific characteristics of motor control and ii) assess whether these are maintained in older age. We recorded electromyographic activities from 13 ipsilateral muscles of the lower limb in young and older adults of both sexes walking (young and old) and running (young) on a treadmill. The data set obtained from the 215 participants was elaborated through non-negative matrix factorization to extract the time-independent (i.e., motor modules) and time-dependent (i.e., motor primitives) coefficients of muscle synergies. We found sparse sex-specific modulations of motor control. Motor modules showed a different contribution of hip extensors, knee extensors and foot dorsiflexors in various synergies. Motor primitives were wider (i.e., lasted longer) in males in the propulsion synergy for walking (but only in young and not in older adults) and in the weight acceptance synergy for running. Moreover, the complexity of motor primitives was similar in younger adults of both sexes, but lower in older females as compared to older males. In essence, our results revealed the existence of small but defined sex-specific differences in the way humans control locomotion and that these strategies are not entirely maintained in older age.