ABSTRACT
A single mutagen can generate multiple different types of DNA lesions. How different repair pathways cooperate in complex DNA lesions, however, remains largely unclear. Here we measured, clustered, and modeled the kinetics of recruitment and dissociation of 70 DNA repair proteins to laser-induced DNA damage sites in HeLa cells. The precise timescale of protein recruitment reveals that error-prone translesion polymerases are considerably delayed compared to error-free polymerases. We show that this is ensured by the delayed recruitment of RAD18 to double-strand break sites. The time benefit of error-free polymerases disappears when PARP inhibition significantly delays PCNA recruitment. Moreover, removal of PCNA from complex DNA damage sites correlates with RPA loading during 5'-DNA end resection. Our systematic study of the dynamics of DNA repair proteins in complex DNA lesions reveals the multifaceted coordination between the repair pathways and provides a kinetics-based resource to study genomic instability and anticancer drug impact.
Subject(s)
DNA Breaks, Double-Stranded , DNA Repair , DNA-Binding Proteins/metabolism , Uterine Cervical Neoplasms/metabolism , DNA Breaks, Double-Stranded/drug effects , DNA Repair/drug effects , DNA-Binding Proteins/genetics , DNA-Directed DNA Polymerase/genetics , DNA-Directed DNA Polymerase/metabolism , Female , Genomic Instability , HeLa Cells , Humans , Kinetics , Models, Genetic , Phthalazines/pharmacology , Poly(ADP-ribose) Polymerase Inhibitors/pharmacology , Proliferating Cell Nuclear Antigen/genetics , Proliferating Cell Nuclear Antigen/metabolism , Protein Binding , Ubiquitin-Protein Ligases/genetics , Ubiquitin-Protein Ligases/metabolism , Uterine Cervical Neoplasms/drug therapy , Uterine Cervical Neoplasms/genetics , Uterine Cervical Neoplasms/pathologyABSTRACT
Clustering of membrane-associated molecules is thought to promote interactions with the actomyosin cortex, enabling size-dependent transport by actin flows. Consistent with this model, in the Caenorhabditis elegans zygote, efficient anterior segregation of the polarity protein PAR-3 requires oligomerization. However, through direct assessment of local coupling between motion of PAR proteins and the underlying cortex, we find no links between PAR-3 oligomer size and the degree of coupling. Indeed, both anterior and posterior PAR proteins experience similar advection velocities, at least over short distances. Consequently, differential cortex engagement cannot account for selectivity of PAR protein segregation by cortical flows. Combining experiment and theory, we demonstrate that a key determinant of differential segregation of PAR proteins by cortical flow is the stability of membrane association, which is enhanced by clustering and enables transport across cellular length scales. Thus, modulation of membrane binding dynamics allows cells to achieve selective transport by cortical flows despite widespread coupling between membrane-associated molecules and the cell cortex.
Subject(s)
Actins , Caenorhabditis elegans Proteins , Protein Serine-Threonine Kinases , Animals , Actins/metabolism , Actomyosin/metabolism , Caenorhabditis elegans/genetics , Caenorhabditis elegans/metabolism , Caenorhabditis elegans Proteins/metabolism , Cell Polarity , Cytoplasm/metabolism , Embryo, Nonmammalian/metabolism , Protein Serine-Threonine Kinases/metabolismABSTRACT
Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep neural networks, and machine learning are all niche terms describing computational methods that have gained a pivotal role in microscopy-based research over the past decade. This Roadmap is written collectively by prominent researchers and encompasses selected aspects of how machine learning is applied to microscopy image data, with the aim of gaining scientific knowledge by improved image quality, automated detection, segmentation, classification and tracking of objects, and efficient merging of information from multiple imaging modalities. We aim to give the reader an overview of the key developments and an understanding of possibilities and limitations of machine learning for microscopy. It will be of interest to a wide cross-disciplinary audience in the physical sciences and life sciences.
ABSTRACT
Key processes of biological condensates are diffusion and material exchange with their environment. Experimentally, diffusive dynamics are typically probed via fluorescent labels. However, to date, a physics-based, quantitative framework for the dynamics of labeled condensate components is lacking. Here, we derive the corresponding dynamic equations, building on the physics of phase separation, and quantitatively validate the related framework via experiments. We show that by using our framework, we can precisely determine diffusion coefficients inside liquid condensates via a spatio-temporal analysis of fluorescence recovery after photobleaching (FRAP) experiments. We showcase the accuracy and precision of our approach by considering space- and time-resolved data of protein condensates and two different polyelectrolyte-coacervate systems. Interestingly, our theory can also be used to determine a relationship between the diffusion coefficient in the dilute phase and the partition coefficient, without relying on fluorescence measurements in the dilute phase. This enables us to investigate the effect of salt addition on partitioning and bypasses recently described quenching artifacts in the dense phase. Our approach opens new avenues for theoretically describing molecule dynamics in condensates, measuring concentrations based on the dynamics of fluorescence intensities, and quantifying rates of biochemical reactions in liquid condensates.
Subject(s)
Fluorescence Recovery After Photobleaching/methods , Polyelectrolytes/chemistry , Proteins/chemistry , Biomolecular Condensates/chemistry , Diffusion , Spatio-Temporal AnalysisABSTRACT
Aberrant liquid-to-solid phase transitions of biomolecular condensates have been linked to various neurodegenerative diseases. However, the underlying molecular interactions that drive aging remain enigmatic. Here, we develop quantitative time-resolved crosslinking mass spectrometry to monitor protein interactions and dynamics inside condensates formed by the protein fused in sarcoma (FUS). We identify misfolding of the RNA recognition motif of FUS as a key driver of condensate aging. We demonstrate that the small heat shock protein HspB8 partitions into FUS condensates via its intrinsically disordered domain and prevents condensate hardening via condensate-specific interactions that are mediated by its α-crystallin domain (αCD). These αCD-mediated interactions are altered in a disease-associated mutant of HspB8, which abrogates the ability of HspB8 to prevent condensate hardening. We propose that stabilizing aggregation-prone folded RNA-binding domains inside condensates by molecular chaperones may be a general mechanism to prevent aberrant phase transitions.
Subject(s)
Heat-Shock Proteins/metabolism , Molecular Chaperones/metabolism , RNA-Binding Protein FUS/metabolism , RNA/metabolism , HeLa Cells , Heat-Shock Proteins/chemistry , Heat-Shock Proteins/genetics , Humans , Molecular Chaperones/chemistry , Molecular Chaperones/genetics , Mutation , Protein Binding , Protein Folding , Protein Interaction Domains and Motifs , Protein Stability , RNA-Binding Protein FUS/chemistry , RNA-Binding Protein FUS/genetics , Structure-Activity Relationship , Time FactorsABSTRACT
The notion that graded distributions of signals underlie the spatial organization of biological systems has long been a central pillar in the fields of cell and developmental biology. During morphogenesis, morphogens spread across tissues to guide development of the embryo. Similarly, a variety of dynamic gradients and pattern-forming networks have been discovered that shape subcellular organization. Here we discuss the principles of intracellular pattern formation by these intracellular morphogens and relate them to conceptually similar processes operating at the tissue scale. We will specifically review mechanisms for generating cellular asymmetry and consider how intracellular patterning networks are controlled and adapt to cellular geometry. Finally, we assess the general concept of intracellular gradients as a mechanism for positional control in light of current data, highlighting how the simple readout of fixed concentration thresholds fails to fully capture the complexity of spatial patterning processes occurring inside cells.
Subject(s)
Body Patterning , Drosophila Proteins/metabolism , Drosophila melanogaster/physiology , Embryo, Nonmammalian/physiology , Gene Expression Regulation, Developmental , Models, Biological , Subcellular Fractions/physiology , Animals , Drosophila Proteins/genetics , Drosophila melanogaster/embryology , Embryo, Nonmammalian/cytologyABSTRACT
How do cells polarize at the correct time and in response to the correct cues? In the C. elegans zygote, the timing and geometry of polarization rely on a single dominant cue-the sperm centrosome-that matures at the end of meiosis and specifies the nascent posterior. Polarization requires that the conserved PAR proteins, which specify polarity in the zygote, be poised to respond to the centrosome. Yet, how and when PAR proteins achieve this unpolarized, but responsive, state is unknown. We show that oocyte maturation initiates a fertilization-independent PAR activation program. PAR proteins are initially not competent to polarize but gradually acquire this ability following oocyte maturation. Surprisingly, this program allows symmetry breaking even in unfertilized oocytes lacking centrosomes. Thus, if PAR proteins can respond to multiple polarizing cues, how is specificity for the centrosome achieved? Specificity is enforced by Polo-like and Aurora kinases (PLK-1 and AIR-1 in C. elegans), which impose a delay in the activation of the PAR network so that it coincides with maturation of the centrosome cue. This delay suppresses polarization by non-centrosomal cues, which can otherwise trigger premature polarization and multiple or reversed polarity domains. Taken together, these findings identify a regulatory program that enforces proper polarization by synchronizing PAR network activation with cell cycle progression, thereby ensuring that PAR proteins respond specifically to the correct cue. Temporal control of polarity network activity is likely to be a common strategy to ensure robust, dynamic, and specific polarization in response to developmentally deployed cues.
Subject(s)
Caenorhabditis elegans Proteins/genetics , Caenorhabditis elegans/physiology , Animals , Caenorhabditis elegans/genetics , Caenorhabditis elegans/growth & development , Caenorhabditis elegans Proteins/metabolism , Cues , Oocytes/growth & development , Oocytes/physiology , Orientation, Spatial , Protein Serine-Threonine Kinases/genetics , Protein Serine-Threonine Kinases/metabolismABSTRACT
Reaction-diffusion networks underlie pattern formation in a range of biological contexts, from morphogenesis of organisms to the polarisation of individual cells. One requirement for such molecular networks is that output patterns be scaled to system size. At the same time, kinetic properties of constituent molecules constrain the ability of networks to adapt to size changes. Here we explore these constraints and the consequences thereof within the conserved PAR cell polarity network. Using the stem cell-like germ lineage of the C. elegans embryo as a model, we find that the behaviour of PAR proteins fails to scale with cell size. Theoretical analysis demonstrates that this lack of scaling results in a size threshold below which polarity is destabilized, yielding an unpolarized system. In empirically-constrained models, this threshold occurs near the size at which germ lineage cells normally switch between asymmetric and symmetric modes of division. Consistent with cell size limiting polarity and division asymmetry, genetic or physical reduction in germ lineage cell size is sufficient to trigger loss of polarity in normally polarizing cells at predicted size thresholds. Physical limits of polarity networks may be one mechanism by which cells read out geometrical features to inform cell fate decisions.
ABSTRACT
The conserved polarity effector proteins PAR-3, PAR-6, CDC-42, and atypical protein kinase C (aPKC) form a core unit of the PAR protein network, which plays a central role in polarizing a broad range of animal cell types. To functionally polarize cells, these proteins must activate aPKC within a spatially defined membrane domain on one side of the cell in response to symmetry-breaking cues. Using the Caenorhabditis elegans zygote as a model, we find that the localization and activation of aPKC involve distinct, specialized aPKC-containing assemblies: a PAR-3-dependent assembly that responds to polarity cues and promotes efficient segregation of aPKC toward the anterior but holds aPKC in an inactive state, and a CDC-42-dependent assembly in which aPKC is active but poorly segregated. Cycling of aPKC between these distinct functional assemblies, which appears to depend on aPKC activity, effectively links cue-sensing and effector roles within the PAR network to ensure robust establishment of polarity.