Determining absolute protein numbers by quantitative fluorescence microscopy

Biological questions are increasingly being addressed using a wide range of quantitative analytical tools to examine protein complex composition. Knowledge of the absolute number of proteins present provides insights into organization, function, and maintenance and is used in mathematical modeling of complex cellular dynamics. In this chapter, we outline and describe three microscopy-based methods for determining absolute protein numbers—fluorescence correlation spectroscopy, stepwise photobleaching, and ratiometric comparison of fluorescence intensity to known standards. In addition, we discuss the various fluorescently labeled proteins that have been used as standards for both stepwise photobleaching and ratiometric comparison analysis. A detailed procedure for determining absolute protein number by ratiometric comparison is outlined in the second half of this chapter. Counting proteins by quantitative microscopy is a relatively simple yet very powerful analytical tool that will increase our understanding of protein complex composition

Transient crosslinking kinetics optimize gene cluster interactions

Our understanding of how chromosomes structurally organize and dynamically interact has been revolutionized through the lens of long-chain polymer physics. Major protein contributors to chromosome structure and dynamics are condensin and cohesin that stochastically generate loops within and between chains, and entrap proximal strands of sister chromatids. In this paper, we explore the ability of transient, protein-mediated, gene-gene crosslinks to induce clusters of genes, thereby dynamic architecture, within the highly repeated ribosomal DNA that comprises the nucleolus of budding yeast. We implement three approaches: live cell microscopy; computational modeling of the full genome during G1 in budding yeast, exploring four decades of timescales for transient crosslinks between 5k bp domains in the nucleolus on Chromosome XII; and, temporal network models with automated community detection algorithms applied to the full range of 4D modeling datasets. The data analysis tools detect and track gene clusters, their size, number, persistence time, and their plasticity. Of biological significance, our analysis reveals an optimal mean crosslink lifetime that promotes pairwise and cluster gene interactions through "flexible" clustering. In this state, large gene clusters self-assemble yet frequently interact, marked by gene exchanges between clusters, which in turn maximizes global gene interactions in the nucleolus. This regime stands between two limiting cases each with far less global gene interactions: with shorter crosslink lifetimes, "rigid" clustering emerges with clusters that interact infrequently; with longer crosslink lifetimes, there is a dissolution of clusters. These observations are compared with imaging experiments on a normal yeast strain and two condensin-modified mutant cell strains, applying the same image analysis pipeline to the experimental and simulated datasets

Entropy gives rise to topologically associating domains

We investigate chromosome organization within the nucleus using polymer models whose formulation is closely guided by experiments in live yeast cells. We employ bead-spring chromosome models together with loop formation within the chains and the presence of nuclear bodies to quantify the extent to which these mechanisms shape the topological landscape in the interphase nucleus. By investigating the genome as a dynamical system, we show that domains of high chromosomal interactions can arise solely from the polymeric nature of the chromosome arms due to entropic interactions and nuclear confinement. In this view, the role of bio-chemical related processes is to modulate and extend the duration of the interacting domains

ChromoShake: a chromosome dynamics simulator reveals that chromatin loops stiffen centromeric chromatin

A novel chromosome simulator recapitulates the position and dynamics of centromeric chromatin in a model composed of cross-linked intramolecular loops. Simulations reveal that chromatin loops stiffen the centromere and dictate the distribution of pericentric cohesin.ChromoShake is a three-dimensional simulator designed to find the thermodynamically favored states for given chromosome geometries. The simulator has been applied to a geometric model based on experimentally determined positions and fluctuations of DNA and the distribution of cohesin and condensin in the budding yeast centromere. Simulations of chromatin in differing initial configurations reveal novel principles for understanding the structure and function of a eukaryotic centromere. The entropic position of DNA loops mirrors their experimental position, consistent with their radial displacement from the spindle axis. The barrel-like distribution of cohesin complexes surrounding the central spindle in metaphase is a consequence of the size of the DNA loops within the pericentromere to which cohesin is bound. Linkage between DNA loops of different centromeres is requisite to recapitulate experimentally determined correlations in DNA motion. The consequences of radial loops and cohesin and condensin binding are to stiffen the DNA along the spindle axis, imparting an active function to the centromere in mitosis

Enrichment of dynamic chromosomal crosslinks drive phase separation of the nucleolus

Regions of highly repetitive DNA, such as those found in the nucleolus, show a self-organization that is marked by spatial segregation and frequent self-interaction. The mechanisms that underlie the sequestration of these sub-domains are largely unknown. Using a stochastic, bead-spring representation of chromatin in budding yeast, we find enrichment of protein-mediated, dynamic chromosomal cross-links recapitulates the segregation, morphology and self-interaction of the nucleolus. Rates and enrichment of dynamic crosslinking have profound consequences on domain morphology. Our model demonstrates the nucleolus is phase separated from other chromatin in the nucleus and predicts that multiple rDNA loci will form a single nucleolus independent of their location within the genome. Fluorescent labeling of budding yeast nucleoli with CDC14-GFP revealed that a split rDNA locus indeed forms a single nucleolus. We propose that nuclear sub-domains, such as the nucleolus, result from phase separations within the nucleus, which are driven by the enrichment of protein-mediated, dynamic chromosomal crosslinks

Spindle assembly checkpoint proteins are positioned close to core microtubule attachment sites at kinetochores

Depletion analyses and nanometer-scale mapping of spindle assembly checkpoint proteins reveal how these proteins are integrated within the substructure of the kinetochore.Spindle assembly checkpoint proteins have been thought to reside in the peripheral corona region of the kinetochore, distal to microtubule attachment sites at the outer plate. However, recent biochemical evidence indicates that checkpoint proteins are closely linked to the core kinetochore microtubule attachment site comprised of the Knl1–Mis12–Ndc80 (KMN) complexes/KMN network. In this paper, we show that the Knl1–Zwint1 complex is required to recruit the Rod–Zwilch–Zw10 (RZZ) and Mad1–Mad2 complexes to the outer kinetochore. Consistent with this, nanometer-scale mapping indicates that RZZ, Mad1–Mad2, and the C terminus of the dynein recruitment factor Spindly are closely juxtaposed with the KMN network in metaphase cells when their dissociation is blocked and the checkpoint is active. In contrast, the N terminus of Spindly is ∼75 nm outside the calponin homology domain of the Ndc80 complex. These results reveal how checkpoint proteins are integrated within the substructure of the kinetochore and will aid in understanding the coordination of microtubule attachment and checkpoint signaling during chromosome segregation

Microtubule dynamics drive enhanced chromatin motion and mobilize telomeres in response to DNA damage

Chromatin exhibits increased mobility on DNA damage, but the biophysical basis for this behavior remains unknown. To explore the mechanisms that drive DNA damage–induced chromosome mobility, we use single-particle tracking of tagged chromosomal loci during interphase in live yeast cells together with polymer models of chromatin chains. Telomeres become mobilized from sites on the nuclear envelope and the pericentromere expands after exposure to DNA-damaging agents. The magnitude of chromatin mobility induced by a single double-strand break requires active microtubule function. These findings reveal how relaxation of external tethers to the nuclear envelope and internal chromatin–chromatin tethers, together with microtubule dynamics, can mobilize the genome in response to DNA damage

Performance of deep learning restoration methods for the extraction of particle dynamics in noisy microscopy image sequences

Particle tracking in living systems requires low light exposure and short exposure times to avoid phototoxicity and photobleaching and to fully capture particle motion with high-speed imaging. Low-excitation light comes at the expense of tracking accuracy. Image restoration methods based on deep learning dramatically improve the signal-to-noise ratio in low-exposure data sets, qualitatively improving the images. However, it is not clear whether images generated by these methods yield accurate quantitative measurements such as diffusion parameters in (single) particle tracking experiments. Here, we evaluate the performance of two popular deep learning denoising software packages for particle tracking, using synthetic data sets and movies of diffusing chromatin as biological examples. With synthetic data, both supervised and unsupervised deep learning restored particle motions with high accuracy in two-dimensional data sets, whereas artifacts were introduced by the denoisers in three-dimensional data sets. Experimentally, we found that, while both supervised and unsupervised approaches improved tracking results compared with the original noisy images, supervised learning generally outperformed the unsupervised approach. We find that nicer-looking image sequences are not synonymous with more precise tracking results and highlight that deep learning algorithms can produce deceiving artifacts with extremely noisy images. Finally, we address the challenge of selecting parameters to train convolutional neural networks by implementing a frugal Bayesian optimizer that rapidly explores multidimensional parameter spaces, identifying networks yielding optimal particle tracking accuracy. Our study provides quantitative outcome measures of image restoration using deep learning. We anticipate broad application of this approach to critically evaluate artificial intelligence solutions for quantitative microscopy

DNA loops generate intracentromere tension in mitosis

The centromere is the DNA locus that dictates kinetochore formation and is visibly apparent as heterochromatin that bridges sister kinetochores in metaphase. Sister centromeres are compacted and held together by cohesin, condensin, and topoisomerase-mediated entanglements until all sister chromosomes bi-orient along the spindle apparatus. The establishment of tension between sister chromatids is essential for quenching a checkpoint kinase signal generated from kinetochores lacking microtubule attachment or tension. How the centromere chromatin spring is organized and functions as a tensiometer is largely unexplored. We have discovered that centromere chromatin loops generate an extensional/poleward force sufficient to release nucleosomes proximal to the spindle axis. This study describes how the physical consequences of DNA looping directly underlie the biological mechanism for sister centromere separation and the spring-like properties of the centromere in mitosis

Point centromeres contain more than a single centromere-specific Cse4 (CENP-A) nucleosome

Quantitative measurement of the number of Cse4, CBF3, and Ndc80 proteins at kinetochores reveals a 2.5–3-fold increased copy number relative to prior estimates