Publications

Biomolecular condensates are membraneless organelles that can concentrate hundreds of different proteins in cells to operate essential biological functions. However, accurate identification of their components remains challenging and biased towards proteins with high structural disorder content with focus on self-phase separating (driver) proteins. Here, we present a machine learning algorithm, PICNIC (Proteins Involved in CoNdensates In Cells) to classify proteins that localize to biomolecular condensates regardless of their role in condensate formation. PICNIC successfully predicts condensate members by learning amino acid patterns in the protein sequence and structure in addition to the intrinsic disorder. Extensive experimental validation of 24 positive predictions in cellulo shows an overall ~82% accuracy regardless of the structural disorder content of the tested proteins. While increasing disorder content is associated with organismal complexity, our analysis of 26 species reveals no correlation between predicted condensate proteome content and disorder content across organisms. Overall, we present a machine learning classifier to interrogate condensate components at whole-proteome levels across the tree of life.

Cortical condensates, transient punctate-like structures rich in actin and the actin nucleation pathway member Neural Wiskott-Aldrich syndrome protein (N-WASP), form during activation of the actin cortex in the Caenorhabditis elegans oocyte. Their emergence and spontaneous dissolution is linked to a phase separation process driven by chemical kinetics. However, the mechanisms that drive the onset of cortical condensate formation near membranes remain unexplored. Here, using a reconstituted phase separation assay of cortical condensate proteins, we demonstrate that the key component, N-WASP, can collectively undergo surface condensation on supported lipid bilayers via a prewetting transition. Actin partitions into the condensates, where it polymerizes and counteracts the N-WASP prewetting transition. Taken together, the dynamics of condensate-assisted cortex formation appear to be controlled by a balance between surface-assisted condensate formation and polymer-driven condensate dissolution. This opens perspectives for understanding how the formation of complex intracellular structures is affected and controlled by phase separation.

We review empirical methods that can be used to provide physical descriptions of dynamic cellular processes during development and disease. Our focus will be non-spatial descriptions and the inference of underlying interaction networks including cell state lineages, gene regulatory networks, and molecular interactions in living cells. Our overarching questions are: How much can we learn from just observing? To what degree is it possible to infer causal and/or precise mathematical relationships from observations? We restrict ourselves to datasets arising from only observations, or experiments in which minimal perturbations have taken place to facilitate observation of the systems as they naturally occur. We discuss analysis perspectives in order from those offering the least descriptive power but requiring the least assumptions such as statistical associations. We end with those which are most descriptive, but require stricter assumptions and more prior knowledge of the systems such as causal inference and dynamical systems approaches. We hope to provide and encourage the use of a wide array of options for quantitative cell biologists to learn as much as possible from their observations at all stages of understanding of their system of interest. Finally, we provide our own recipe of how to empirically determine quantitative relationships and growth laws from live cell microscopy data, the resultant predictions of which can then be verified with perturbation experiments. We also include an extended supplement which describes further inference algorithms and theory for the interested reader.

Biomolecular condensates have been identified as a ubiquitous means of intracellular organization, exhibiting very diverse material properties. However, techniques to characterize these material properties and their underlying molecular interactions are scarce. Here, we introduce two optical techniques-Brillouin microscopy and quantitative phase imaging (QPI)-to address this scarcity. We establish Brillouin shift and linewidth as measures for average molecular interaction and dissipation strength, respectively, and we used QPI to obtain the protein concentration within the condensates. We monitored the response of condensates formed by fused in sarcoma (FUS) and by the low-complexity domain of hnRNPA1 (A1-LCD) to altering temperature and ion concentration. Conditions favoring phase separation increased Brillouin shift, linewidth, and protein concentration. In comparison to solidification by chemical cross-linking, the ion-dependent aging of FUS condensates had a small effect on the molecular interaction strength inside. Finally, we investigated how sequence variations of A1-LCD, that change the driving force for phase separation, alter the physical properties of the respective condensates. Our results provide a new experimental perspective on the material properties of protein condensates. Robust and quantitative experimental approaches such as the presented ones will be crucial for understanding how the physical properties of biological condensates determine their function and dysfunction.

We show that the resolution-dependent loss of bimolecular reactions in spatiotemporal Reaction–Diffusion Master Equations (RDMEs) is in agreement with the mean-field Collins–Kimball (C–K) theory of diffusion-limited reaction kinetics. The RDME is a spatial generalization of the chemical master equation, which enables studying stochastic reaction dynamics in spatially heterogeneous systems. It uses a regular Cartesian grid to partition space into locally well-mixed reaction compartments and treats diffusion as a jump reaction between neighboring grid cells. As the chance for reactants to be in the same grid cell decreases for smaller cell widths, the RDME loses bimolecular reactions in finer grids. We show that for a single homo-bimolecular reaction, the mesh spacing can be interpreted as the reaction radius of a well-mixed C–K rate. Then, the bimolecular reaction loss is consistent with diffusion-limited kinetics in the mean-field steady state. In this interpretation, the constant in a bimolecular reaction propensity is no longer the macroscopic reaction rate but the rate of the ballistic C–K step. For the same grid resolution, different diffusion models in RDME, such as those based on finite differences and Gaussian jumps, represent different reaction radii.

Many aspects of neurodegenerative disease pathology remain unresolved. Why do certain neuronal subpopulations acquire vulnerability to stress or mutations in ubiquitously expressed genes, while others remain resilient? Do these neurons harbor intrinsic marks that make them prone to degeneration? Do these diseases have a neurodevelopmental component? Lacking this fundamental knowledge hampers the discovery of efficacious treatments. While it is well established that human organoids enable the modeling of brain-related diseases, we still lack an organoid model that recapitulates the regionalization complexity and physiology of the spinal cord. Here, we describe an advanced experimental protocol to generate neuromuscular organoids composed of a wide rostro-caudal (RC) diversity of spinal motor neurons (spMNs) and mesodermal progenitor-derived muscle cells. This model therefore allows for the robust and reproducible study of neuromuscular unit development and disease.

Cross-linking mass spectrometry (XL-MS) has seen significant improvements which have enhanced its utility for studying protein-protein interactions (PPIs), primarily due to the emergence of novel crosslinkers and the development of streamlined analysis workflows. Nevertheless, poor membrane permeability and side reactions with water limit the extent of productive intracellular crosslinking events that can be achieved with current crosslinkers. To address these problems, we have synthesized a novel crosslinker with o-nitrobenzyl-based photoresponsive groups. These o-nitrobenzyl ester (o-NBE) groups enhance the stability and hydrophobic properties of the crosslinker and add the potential for temporal resolution, i.e. the ability to control the initiation of the crosslinking reaction. Upon exposure to UV light the resulting aldehyde product reacts with adjacent amino groups and subsequent reductive amination of the formed Schiff-bases yields stable secondary amine linkages. This controlled activation mechanism enables precise UV-triggered protein crosslinking. We demonstrate proof-of principle of our o-NBE cross-linker to reliably detect PPIs by XL-MS using a recombinant model protein. We also demonstrate its ability to enter intact Hela cells, thereby indicating its future potential as a useful tool to study PPIs within the cellular environment.

Uncontrolled regeneration leads to neoplastic transformation1-3. The intestinal epithelium requires precise regulation during continuous homeostatic and damage-induced tissue renewal to prevent neoplastic transformation, suggesting that pathways unlinking tumour growth from regenerative processes must exist. Here, by mining RNA-sequencing datasets from two intestinal damage models4,5 and using pharmacological, transcriptomics and genetic tools, we identified liver X receptor (LXR) pathway activation as a tissue adaptation to damage that reciprocally regulates intestinal regeneration and tumorigenesis. Using single-cell RNA sequencing, intestinal organoids, and gain- and loss-of-function experiments, we demonstrate that LXR activation in intestinal epithelial cells induces amphiregulin (Areg), enhancing regenerative responses. This response is coordinated by the LXR-ligand-producing enzyme CYP27A1, which was upregulated in damaged intestinal crypt niches. Deletion of Cyp27a1 impaired intestinal regeneration, which was rescued by exogenous LXR agonists. Notably, in tumour models, Cyp27a1 deficiency led to increased tumour growth, whereas LXR activation elicited anti-tumour responses dependent on adaptive immunity. Consistently, human colorectal cancer specimens exhibited reduced levels of CYP27A1, LXR target genes, and B and CD8 T cell gene signatures. We therefore identify an epithelial adaptation mechanism to damage, whereby LXR functions as a rheostat, promoting tissue repair while limiting tumorigenesis.

We describe Phrikoceros jannetae sp. n., a new cotylean polyclad species from Ghar El Melh lagoon, a natural seawater lagoon situated in the north of Tunisia. The new species is characterized by the dorsal translucent white to brownish dorsal surface, with black round dots, red microdots, white blotches arranged as discrete lateral streaks, a mid-dorsal darker band and an interrupted slender black rim. We provide some insights into the biology of this species including the plastic tentacle configuration and the variability of body form and outline within the same specimen. Phrikoceros jannetae sp. n. was found among tunicates of the species Ciona intestinalis.