This paper was converted on www.awesomepapers.org from LaTeX by an anonymous user.
Want to know more? Visit the Converter page.

Long-Range Repulsion Between Chromosomes in Mammalian Oocyte Spindles

Colm P. Kelleher Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138 Yash Rana John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138 Daniel J. Needleman Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138 John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138 Center for Computational Biology, Flatiron Institute, New York, NY 10010

During eukaryotic cell division, a microtubule-based structure called the spindle exerts forces on chromosomes, thereby organizing and segregating them [1]. Extensive work demonstrates that the forces acting parallel to the spindle axis, including those responsible for separating sister chromatids, are generated by microtubule polymerization and depolymerization, and molecular-motors  [2, 3, 4, 5]. In contrast, little is known about the forces acting perpendicular to the spindle axis, which determine the configuration of chromosomes at the metaphase plate, and thus impact nuclear localization and rates of segregation errors [6, 7]. Here, we use quantitative live-cell microscopy to show that metaphase chromosomes are spatially anti-correlated in mouse oocyte spindles, indicating the existence of hitherto unknown long-range forces acting perpendicular to the spindle axis. We explain this observation by first demonstrating that the spindle’s microtubule network behaves as a nematic liquid crystal, and then arguing that deformation of the nematic field around embedded chromosomes causes long-range repulsion between them. Our work highlights the surprising relevance of materials physics in understanding the structure, dynamics, and mechanics of cellular structures, and presents a novel and potentially generic mode of chromosome organization in large spindles.

Chromosome segregation is a physical and mechanical process, requiring precisely coordinated motion of micron-sized objects (chromosomes) through distances of tens of microns (the size of a typical metazoan cell) [1, 3]. The forces causing this motion are generated primarily by the spindle, a cellular structure comprising a network of microtubules – long, rigid polymers of the protein tubulin – in association with hundreds of additional proteins that modulate microtubule nucleation, polymerization/depolymerization, and interactions [8, 9]. However, despite our extensive knowledge of the spindle’s molecular constituents, we lack a general framework for understanding how it self-organizes to generate cellular-scale forces. This places a fundamental limit on our ability to predict when spindle dysfunction leads to errors in chromosomes segregation, and thus how it might contribute to diseases such as cancer and infertility [10, 11, 12].

Metaphase II (MII) spindles in mammalian oocytes provide an ideal model system in which to study spindle-self organization in vivo, since their large sizes and long steady-state lifetimes facilitate detailed microscopy measurements (Supplemental Information S.I. 1, [13, 11, 14]). To characterize the structure and dynamics of the microtubule network in these spindles, we acquired LC-PolScope movies (Fig. 1(a); Methods 1 & 2). The LC-PolScope is a label-free quantitative polarization microscope that simultaneously measures the optical retardance r(𝐫,t)r(\mathbf{r},t) and optical slow axis θ(𝐫,t)\theta(\mathbf{r},t) at a given time tt and each position 𝐫\mathbf{r} in a two-dimensional (2D) image [13]. These measurements provide quantitive information regarding the coarse-grained microtubule cross-sectional density ρ(𝐑,t)\rho(\mathbf{R},t) and the nematic director 𝐍^(𝐑,t)\mathbf{\hat{N}}(\mathbf{R},t), both defined at every point 𝐑\mathbf{R} in 3D space as well as in time [15]: if the spindle long axis 𝐱^\mathbf{\hat{x}} is perpendicular to the optical axis 𝐨^\mathbf{\hat{o}},

r(𝐫,t)A0Tρ(𝐑,t)do;𝐧^(𝐫,t)(cosθ(𝐫,t),sinθ(𝐫,t))T𝐍^(𝐑,t)doT𝐍^(𝐑,t)do,r(\mathbf{r},t)\approx A_{0}\int_{T}\rho(\mathbf{R},t)\,\text{d}o;\qquad\mathbf{\hat{n}}(\mathbf{r},t)\equiv(\cos{\theta(\mathbf{r},t)},\sin{\theta(\mathbf{r},t)})\approx\frac{\int_{T}\mathbf{\hat{N}}(\mathbf{R},t)\text{d}o}{||\int_{T}\mathbf{\hat{N}}(\mathbf{R},t)\text{d}o||}, (1)

where the integrals are taken over the optical axis 𝐨^\mathbf{\hat{o}}, the constant A07.5A_{0}\approx 7.5 nm2 characterizes the retardance contribution of a single microtubule, TT is the sample thickness along the optical axis, and the 2D vector 𝐧^(𝐫,t)\mathbf{\hat{n}}(\mathbf{r},t) is the normalized projection of 𝐍^(𝐑,t)\mathbf{\hat{N}}(\mathbf{R},t) into the LC-PolScope image plane (Fig. 1(a); S.I.  2 & 3;  [16, 17, 18]).

We first used LC-PolScope movies to determine the relationship between the surface geometry of MII oocyte spindles and microtubule orientation in the spindle interior. To characterize surface geometry, we identified spindle boundaries from time-averaged retardance images, rt\langle r\rangle_{t}, calculated in a spindle-referenced coordinate system where 𝐳^=𝐨^\mathbf{\hat{z}}=\mathbf{\hat{o}} and 𝐲^=𝐳^×𝐱^\mathbf{\hat{y}}=\mathbf{\hat{z}}\times\mathbf{\hat{x}} (Fig. 1(b, left column), Methods 2-4). We find that those portions of the spindle boundary that are furthest from the central axis are well-fitted by a pair of circle arcs that intersect at “virtual poles” at (±L0,0)(\pm L_{0},0), outside the spindle boundary. In 3D, the corresponding portion of the spindle surface is convex, and approximates a tactoid, the shape generated by rotating a circle arc about its chord. Since the convex surfaces of MII spindles do not extend all the way to the poles, we model them as “polar-indented tactoids,” truncated tactoids with concave spherical caps of radius r0r_{0} replacing the poles (Fig. 1(c & d); S.I. 4). In materials physics, tactoid and tactoid-like droplets are a characteristic feature of nematic liquid crystals, and have been observed under a wide variety of conditions in both experiments and simulations [19, 20, 21]. We next examined how microtubule orientation at the spindle boundary depends on surface geometry. We found close agreement between the observed microtubule orientation and a purely geometrical model in which microtubules lie tangent to the spindle’s convex (tactoid) surface, and perpendicular to its concave (polar cap) surfaces (Fig. 1(e & f)). Thus, at the spindle surface, microtubules obey a “strong anchoring” boundary condition [22]. In tactoid-shaped nematic droplets with strong anchoring, the director is predicted to lie tangent to the unique family of circle arcs that intersect at (±L0,0,0)(\pm L_{0},0,0) [23, 24]. To test whether this is the case in MII spindles, we compared the time-averaged slow axis images θt\langle\theta\rangle_{t} to the predictions of the circle arcs model (Methods 5). For individual spindles, we find good agreement between the observed pattern of microtubule orientation and that predicted by the model (Fig. 1(b, bottom right); S.I. 5). To further probe the validity of the circle arcs model, we investigated whether steady-state orientation fields from different spindles collapse onto a master field when they are properly rescaled, as that model predicts they should. Using previously measured values of L0L_{0} (and no additional fit parameters), we rescaled the orientation field of all spindles, θt(𝐫)θt(𝐫/L0)\langle\theta\rangle_{t}(\mathbf{r})\rightarrow\langle\theta\rangle_{t}(\mathbf{r}/L_{0}), and observed excellent data collapse (Fig. 1(g & h)). Taken together, these results provide strong evidence for a model of spindle self-organization in which microtubule orientation is determined by a well-defined anchoring condition on the spindle boundary, together with a tendency for microtubules in the spinde interior to locally align with each other, i.e. nematic elasticity.

Since the steady-state orientation of microtubules in MII spindles is well-described by nematic liquid crystal physics, we next investigated if such a model can also describe the fluctuations in microtubule orientation around that steady-state. In synthetic materials, spatiotemporal correlations of fluctuations have long been used to characterize material properties [25, 22]. More recently, fluctuation analysis was used to show that the microtubule network of in vitro reconstituted Xenopus egg extract spindles behaves as an active nematic material [26]. To determine if a similar approach can be applied to spindles in living oocytes, we first subtracted the best-fit 2D director field, 𝐧^𝟎(𝐫)\mathbf{\hat{n}_{0}}(\mathbf{r}), from the instantaneous field 𝐧^(𝐫,t)\mathbf{\hat{n}}(\mathbf{r},t) to calculate the fluctuations δ𝐧(𝐫,t)=𝐧^(𝐫,t)𝐧^𝟎(𝐫)\delta\mathbf{n}(\mathbf{r},t)=\mathbf{\hat{n}}(\mathbf{r},t)-\mathbf{\hat{n}_{0}}(\mathbf{r}) in a box of side length λ0=8μm\lambda_{0}=8\,\mu\text{m} placed at the center of the spindle (Fig. 2(a)). Fluctuations take a particularly simple form in this region since, to lowest order in δθ\delta\theta, δ𝐧δny𝐲^\delta\mathbf{n}\approx\delta n_{y}\mathbf{\hat{y}} and δny=δ(sinθ)δθ\delta n_{y}=\delta(\sin{\theta})\approx\delta\theta (Fig. 2(b)). To quantify the fluctuation pattern, we plotted the equal time correlation function, snn(q0,qy)s_{\text{nn}}(q_{0},q_{y}), as a function of the wave-vector component qyq_{y} perpendicular to the spindle axis, with the parallel component fixed at the lowest available mode q0=2π/λ0q_{0}=2\pi/\lambda_{0} (Methods 6). For the lowest and highest values of qyq_{y}, snn(q0,qy)s_{\text{nn}}(q_{0},q_{y}) displays behavior consistent with the inverse square power law predicted by active nematic theory and observed in previous experiments on reconstituted Xenopus spindles (Fig. 2(c), S.I. 6). At intermediate value of qyq_{y}, however, snn(q0,qy)s_{\text{nn}}(q_{0},q_{y}) displays a prominent feature neither predicted by theory nor observed in Xenopus extract: a peak centered at qy=(2.9±0.1)q_{y}^{*}=(2.9\pm 0.1) rad μm1\,\mu\text{m}^{-1}, corresponding to a real-space wavelength λ=2π/qy=(2.2±0.1)μm\lambda^{*}=2\pi/q_{y}^{*}=(2.2\pm 0.1)\,\mu\text{m}.

To elucidate the origins of the anomalous behavior of snn(q0,qy)s_{\text{nn}}(q_{0},q_{y}), we next explored the relationship between orientational fluctuations and microtubule density. We observed that the time-averaged orientational fluctuation magnitude |δθ|t\langle|\delta\theta|\rangle_{t} was negatively correlated with the time-averaged retardance rt\langle r\rangle_{t} in 15 out of 16 spindles (Fig. 2(d & e); S.I. 7). To investigate the basis of this negative correlation, we used a local binarization filter (Methods 7), which revealed that spindles contain elongated regions with low microtubule density (Fig. 2(f)) in which orientational fluctuations are larger (Fig. 2(g)).

To understand the origins of these micron-scale density inhomogeneities and how they might affect orientational fluctuations, we labeled chromosomes by expressing H2B-EGFP and microtubules by SiR-tubulin staining, and used 3D confocal microscopy to image the internal structure of living oocyte spindles (Methods 8 & 9). Confocal micrographs show that the microtubule network is a contiguous material perforated by voids (i.e. regions of low microtubule density) surrounding each embedded chromosome (Fig. 3(a&b)). Consistent with recent results demonstrating that condensed chromosomes are microtubule-impermeable [27], void cross-sections in the metaphase plate (i.e. the x=0x=0 plane) closely follow chromosome boundaries, and may be approximated as ellipses with long and short axes aa and bb respectively, where a/b2.5a/b\approx 2.5 (S.I. 8). In the 𝐱^\mathbf{\hat{x}}-direction, the voids extend much further than chromosomes, along most of the length of the spindle (Fig. 3(c)).

We were not able to use the micrographs to quantify individual void profiles along 𝐱^\mathbf{\hat{x}} because, for a significant portion of their lengths, void widths are smaller than the microscope’s resolution. Instead, we used LC-PolScope data to infer the average void profile along 𝐱^\mathbf{\hat{x}}. To do this, we fit the microtubule cross-sectional density ρx(x)=ρ(𝐑,t)y,z,t\rho_{x}(x)=\langle\rho(\mathbf{R},t)\rangle_{y,z,t} as a function of position xx along the spindle long axis (Fig. 3 (d & e); S.I. 3). The density profile ρx(x)\rho_{x}(x) reaches a minimum at the metaphase plate and a maximum near the poles (Fig. 3(e)). By assuming all of this “missing” density in the central spindle is due to voids, we infer that \sim10% of the total volume, and \sim15 % of the metaphase plate area, of MII spindles is taken up by voids. Assuming further that all spindles contain nchr=20n_{\text{chr}}=20 voids (one per chromosome), we find that average void profiles along 𝐱^\mathbf{\hat{x}} are well-approximated by circle arcs with waist diameter around 1μm1\,\mu\text{m} (Fig. 3 (f)), which may be interpreted as the geometric mean of the long and short axes of the void’s x=0x=0 cross-section, ab\sqrt{ab} (Fig. 3(c, bottom left inset)). The simplest 3D shape that would generate such a missing retardance profile is a tactoid, the form generated by revolving a circle arc of chord length β\beta about its chord, which would have a circular cross-section in the metaphase plate (a=ba=b). Since the voids in MII spindles have non-circular x=0x=0 cross-sections (aba\neq b), their 3D shapes are not true tactoids, but rather are “tactoid-like” in the sense that their average profile along 𝐱^\mathbf{\hat{x}} is a circle arc. Tactoid-shaped holes have been observed previously in both synthetic and biological nematics, and are known as “negative tactoids” or “atactoids” [28, 29, 30]; as in spindles, these strutures tend to spontaneously align with the nematic director ([31, 32, 33], Fig. 3(g)).

To investigate the configuration of voids within the metaphase plate, we took advantage of the fact that, in the x=0x=0 plane, chromosome cross-sections provide a good proxy for void cross-sections (Fig. 3(b)), but are easier to identify since chromosomes are high-contrast, isolated, compact objects. To study chromosome cross-section configurations, we binarized images of the metaphase plates of several spindles (Fig. 4(a)). To detect correlations between chromosome positions, we use the pair correlation function gII(s)g_{II}(s), which quantifies the average correlation between the pixel value II at pairs of points separated by a distance ss in the metaphase plate (S.I. 8). At separations much less than the smaller chromosome dimension (sb1μms\ll b\approx 1\,\mu\text{m}), gII(s)1g_{II}(s)\gg 1; this reflects the fact that a white pixel is very likely to immediately neighbor other white pixels. At larger separations, we observe a local minimum at (1.27±0.04)μm(1.27\pm 0.04)\,\mu\text{m} corresponding to the the presence of a ring around each chromosome that is depleted of other chromosomes, and a local maximum at s=(2.4±0.1)μms^{*}=(2.4\pm 0.1)\,\mu\text{m} indicating a ring enriched in chromosomes (Fig. 4(b), black and white arrows; uncertainty given by empirical bootstrapping). To confirm this interpretation, we ran a Monte Carlo simulation that takes as inputs the experimentally determined set of binarized chromosome sections, and re-arranges them into a random configuration (S.I. 9). Random configurations appear strikingly different to the experimentally observed ones, and the corresponding gII(s)g_{II}(s) lacks local maxima and minima (Fig. 4(c)), indicating that these simulations lack the local order (i.e. spatial anti-correlation) observed in the experimental data. Local ordering of chromosomes and their associated voids also explains the previously noted peak in snn(q0,qy)s_{\text{nn}}(q_{0},q_{y}) (Fig. 2(c)), since large fluctuations concentrated in regularly-spaced voids cause a peak in the orientational correlation function (S.I. 6). Consistent with this interpretation, the characteristic spacing between voids, s=(2.4±0.1)μms^{*}=(2.4\pm 0.1)\,\mu\text{m}, agrees, within experimental uncertainty, with the position of the correlation function peak, λ=(2.2±0.1)μm\lambda^{*}=(2.2\pm 0.1)\,\mu\text{m}.

We next turned to the origin of the forces responsible for chromosome ordering in the metaphase plate. In liquid crystal physics, it is well-known that deformation of the nematic field around micron-size inclusions can create long-range forces that cause the inclusions to self-organize into structured arrays [34, 35]. We therefore hypothesized that, in MII spindles, a similar force might cause the regularly spaced chromosome configurations we observe. To explore this effect, we constructed an analytically tractable 2D model in which the void surrounding a chromosome is represented as a topological quadrupole made up of two +1/2+1/2 and two 1/2-1/2 defects ([36]; Fig. 4(d, top left)). In this model, void boundaries are defined as those integral curves of the director that pass through the outer pair of 1/2-1/2 defects. With this construction, the length β\beta and width DD of the void uniquely determine the spacing of the defects within a row and thus, for an isolated void, the orientation field everywhere in space (S.I. 10). For a pair of parallel, director-aligned voids whose centers lie along a line perpendicular to the far-field director 𝐱^\mathbf{\hat{x}}, the deformation-induced interaction potential Uint(d)U_{\text{int}}(d) decays monotonically for all values of β,D\beta,D, and center-to-center separation dd, implying the existence of a repulsive force between 2D voids, independent of the details of void geometry (Fig. 4(d); S.I. 10).

To investigate whether long-range repulsion between 3D voids can account for the observed metaphase plate configurations, we performed a series of simulations where chromosome/void sections are represented by ellipses interacting via a long-ranged repulsive potential (S.I. 9). In each simulation, the ellipse geometry and metaphase plate boundary are determined from a specific experimental data set. Since we do not know the form of the interactions between non-axisymmetric voids in 3D, we repeat our simulations using four different long-range repulsive potentials, and find that the specific form of the interaction does not significantly affect the final chromosome configuration: all simulations produce configurations similar to the experimentally observed one, with features such as an outer ring of \sim15 mostly radially oriented chromosomes/ellipses, and local extrema of gII(s)g_{II}(s) near 1.3 and 2.4μm2.4\,\mu\text{m} (Fig. 4(e), S.I. 9). Thus, our observations of local ordering of chromosomes in the metaphase plate are consistent with the presence of long-range repulsion arising from deformation of the nematic field.

In this work, we have demonstrated that chromosomes are locally ordered in the metaphase plate of MII mouse oocytes, implying the existence of repulsive interchromsomal forces acting perpendicular to the spindle axis (Fig. 4). The micron-scale distances between chromosome surfaces (S.I. 9) are far larger than can be accounted for by known forces, such as those arising from electrostatic repulsion [37] or steric interactions between chromosome-associated proteins [38]. To explain this observation, we proposed a novel mechanism whereby distortion of the microtubule network around chromosomes causes repulsion between them. Our model relies on the key assumption that stress and torque propagate through the microtubule network according to the predictions of nematic elasticity, i.e. that the microtubule network has the mechanical properties of a nematic liquid crystal. This assumption is consistent with several other observations of mouse oocyte spindles, in particular the shape of the spindle boundary (Fig. 1(b-f)), the steady-state pattern of microtubule orientation in the spindle interior (Fig. 1(g&h)), the functional form of spatial correlations of orientational fluctuations (Fig. 2(c)), and the appearance of director-aligned, tactoid-like voids around embedded chromosomes (Fig. 3). Consistent with our findings, previous work in Xenopus egg extract [26, 39] and human tissue culture cells [15] showed that nematic models accurately predict several aspects of spindle structure and dynamics in those systems also. Taken together, these results suggest that nematic elasticity plays a fundamental role in determining both spindle structure and chromosome organization in large spindles across organisms and cell types.

1 References

References

  • [1] Bruce Alberts, Alexander Johnson, Julian Lewis, David Morgan, Martin Raff, Keith Roberts, and Peter Walter. Molecular Biology of the Cell. Garland Science, 6 edition, 2015.
  • [2] Helder Maiato, Ana Gomes, Filipe Sousa, and Marin Barisic. Mechanisms of chromosome congression during mitosis. Biology, 6:13, 2 2017.
  • [3] Maya I. Anjur-Dietrich, Colm P. Kelleher, and Daniel J. Needleman. Mechanical mechanisms of chromosome segregation. Cells, 10:465, 2 2021.
  • [4] Nenad Pavin and Iva M. Tolić. Self-organization and forces in the mitotic spindle. Annual Review of Biophysics, 45:279–298, 7 2016.
  • [5] Ehssan Nazockdast and Stefanie Redemann. Mechanics of the spindle apparatus. Seminars in Cell & Developmental Biology, 107:91–102, 11 2020.
  • [6] Daniel Gerlich, Joël Beaudouin, Bernd Kalbfuss, Nathalie Daigle, Roland Eils, and Jan Ellenberg. Global chromosome positions are transmitted through mitosis in mammalian cells. Cell, 112:751–764, 3 2003.
  • [7] Sjoerd J. Klaasen, My Anh Truong, Richard H. van Jaarsveld, Isabella Koprivec, Valentina Štimac, Sippe G. de Vries, Patrik Risteski, Snježana Kodba, Kruno Vukušić, Kim L. de Luca, Joana F. Marques, Elianne M. Gerrits, Bjorn Bakker, Floris Foijer, Jop Kind, Iva M. Tolić, Susanne M. A. Lens, and Geert J. P. L. Kops. Nuclear chromosome locations dictate segregation error frequencies. Nature, 607:604–609, 7 2022.
  • [8] Ulrike S. Eggert, Timothy J. Mitchison, and Christine M. Field. Animal cytokinesis: From parts list to mechanisms. Annual Review of Biochemistry, 75:543–566, 6 2006.
  • [9] Binyam Mogessie, Kathleen Scheffler, and Melina Schuh. Assembly and positioning of the oocyte meiotic spindle. Annual Review of Cell and Developmental Biology, 34:381–403, 10 2018.
  • [10] William T Silkworth and Daniela Cimini. Transient defects of mitotic spindle geometry and chromosome segregation errors. Cell Division, 7:19, 2012.
  • [11] Zuzana Holubcová, Martyn Blayney, Kay Elder, and Melina Schuh. Error-prone chromosome-mediated spindle assembly favors chromosome segregation defects in human oocytes. Science, 348:1143–1147, 6 2015.
  • [12] Tamara Potapova and Gary Gorbsky. The consequences of chromosome segregation errors in mitosis and meiosis. Biology, 6:12, 2 2017.
  • [13] Lin Liu, Rudolf Oldenbourg, James R. Trimarchi, and David L. Keefe. A reliable, noninvasive technique for spindle imaging and enucleation of mammalian oocytes. Nature Biotechnology, 18:223–225, 2 2000.
  • [14] Aleksandar I. Mihajlović and Greg FitzHarris. Segregating chromosomes in the mammalian oocyte. Current Biology, 28:R895–R907, 8 2018.
  • [15] William Conway, Robert Kiewisz, Gunar Fabig, Colm P Kelleher, Hai-Yin Wu, Maya Anjur-Dietrich, Thomas Müller-Reichert, and Daniel J Needleman. Self-organization of kinetochore-fibers in human mitotic spindles. eLife, 11, 7 2022.
  • [16] H Sato, G W Ellis, and S Inoué. Microtubular origin of mitotic spindle form birefringence. demonstration of the applicability of wiener’s equation. Journal of Cell Biology, 67:501–517, 12 1975.
  • [17] R. Oldenbourg, E.D. Salmon, and P.T. Tran. Birefringence of single and bundled microtubules. Biophysical Journal, 74:645–654, 1 1998.
  • [18] Rudolf Oldenbourg. Polarized light microscopy: Principles and practice. Cold Spring Harbor Protocols, 2013:pdb.top078600, 11 2013.
  • [19] Andrew DeBenedictis and Timothy J. Atherton. Shape minimisation problems in liquid crystals. Liquid Crystals, 43:2352–2362, 12 2016.
  • [20] Pei-Xi Wang and Mark J. MacLachlan. Liquid crystalline tactoids: ordered structure, defective coalescence and evolution in confined geometries. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 376:20170042, 2 2018.
  • [21] Anja Kuhnhold and Paul van der Schoot. Structure of nematic tactoids of hard rods. The Journal of Chemical Physics, 156:104501, 3 2022.
  • [22] P.G. De Gennes and J. Prost. Physics of Liquid Crystals. Oxford Science Publications, 2 edition, 1993.
  • [23] R D Williams. Two transitions in tangentially anchored nematic droplets. Journal of Physics A: Mathematical and General, 19:3211–3222, 11 1986.
  • [24] Peter Prinsen and Paul van der Schoot. Shape and director-field transformation of tactoids. Physical Review E, 68:021701, 8 2003.
  • [25] Dynamics of fluctuations in nematic liquid crystals. The Journal of Chemical Physics, 51:816–822, 7 1969.
  • [26] Jan Brugués and Daniel Needleman. Physical basis of spindle self-organization. Proceedings of the National Academy of Sciences, 111:18496–18500, 12 2014.
  • [27] Maximilian W. G. Schneider, Bryan A. Gibson, Shotaro Otsuka, Maximilian F. D. Spicer, Mina Petrovic, Claudia Blaukopf, Christoph C. H. Langer, Paul Batty, Thejaswi Nagaraju, Lynda K. Doolittle, Michael K. Rosen, and Daniel W. Gerlich. A mitotic chromatin phase transition prevents perforation by microtubules. Nature, 609:183–190, 9 2022.
  • [28] J D Bernal and I Fankuchen. X-ray and crystallographic studies of plant virus preparations : I. introduction and preparation of specimens ii. modes of aggregation of the virus particles. The Journal of general physiology, 25:111–46, 9 1941.
  • [29] Yu. A. Nastishin, H. Liu, T. Schneider, V. Nazarenko, R. Vasyuta, S. V. Shiyanovskii, and O. D. Lavrentovich. Optical characterization of the nematic lyotropic chromonic liquid crystals: Light absorption, birefringence, and scalar order parameter. Physical Review E, 72:041711, 10 2005.
  • [30] Hamed Almohammadi, Sandra Martinek, Ye Yuan, Peter Fischer, and Raffaele Mezzenga. Disentangling kinetics from thermodynamics in heterogeneous colloidal systems. Nature Communications, 14:607, 2 2023.
  • [31] Youngwoo Yi and Noel A. Clark. Orientation of chromonic liquid crystals by topographic linear channels: multi-stable alignment and tactoid structure. Liquid Crystals, 40:1736–1747, 12 2013.
  • [32] Shuang Zhou, Andrey Sokolov, Oleg D. Lavrentovich, and Igor S. Aranson. Living liquid crystals. Proceedings of the National Academy of Sciences, 111:1265–1270, 1 2014.
  • [33] Mikhail M Genkin, Andrey Sokolov, and Igor S Aranson. Spontaneous topological charging of tactoids in a living nematic. New Journal of Physics, 20:043027, 4 2018.
  • [34] Philippe Poulin, Holger Stark, T. C. Lubensky, and D. A. Weitz. Novel colloidal interactions in anisotropic fluids. Science, 275:1770–1773, 3 1997.
  • [35] Prerna Sharma, Andrew Ward, T. Gibaud, Michael F. Hagan, and Zvonimir Dogic. Hierarchical organization of chiral rafts in colloidal membranes. Nature, 513:77–80, 9 2014.
  • [36] Farzan Vafa, Mark J. Bowick, M. Cristina Marchetti, and Boris I. Shraiman. Multi-defect dynamics in active nematics.
  • [37] Vladimir Kesler, Boris Murmann, and H. Tom Soh. Going beyond the debye length: Overcoming charge screening limitations in next-generation bioelectronic sensors. ACS Nano, 14:16194–16201, 12 2020.
  • [38] Sara Cuylen, Claudia Blaukopf, Antonio Z. Politi, Thomas Müller-Reichert, Beate Neumann, Ina Poser, Jan Ellenberg, Anthony A. Hyman, and Daniel W. Gerlich. Ki-67 acts as a biological surfactant to disperse mitotic chromosomes. Nature, 535:308–312, 7 2016.
  • [39] David Oriola, Frank Jülicher, and Jan Brugués. Active forces shape the metaphase spindle through a mechanical instability. Proceedings of the National Academy of Sciences, 117:16154–16159, 7 2020.
Refer to caption
Figure 1: In living mouse oocyte spindles, steady-state microtubule orientation is fully determined by surface geometry. (a) For a spindle oriented with its long axis 𝐱^\mathbf{\hat{x}} perpendicular to the optical axis 𝐨^\mathbf{\hat{o}}, the retardance rr is related to the cross-sectional density ρ(𝐑)\rho(\mathbf{R}) of microtubules integrated over 𝐨^\mathbf{\hat{o}}. The coarse-grained 3D microtubule orientation is described by a field of unit vectors 𝐍^(𝐑)\mathbf{\hat{N}}(\mathbf{R}); at each pixel of a 2D LC-PolScope image, the optical slow axis angle θ(𝐫)\theta(\mathbf{r}) specifies 𝐧^(𝐫)\mathbf{\hat{n}}(\mathbf{r}), the normalized projection of 𝐍^(𝐑)\mathbf{\hat{N}}(\mathbf{R}) over 𝐨^\mathbf{\hat{o}}. (b) Upper and Middle Rows: Snapshots and time averages (500 frames, 40 mins) of rr and θ\theta for an MII spindle with 𝐱^𝐨^\mathbf{\hat{x}}\perp\mathbf{\hat{o}}. Scale bar 5μm5\,\mu\text{m}. Bottom Left: The spindle boundary (black solid curve) is fitted to a pole-indented tactoid (white dashed curve) with L0=15.2μmL_{0}=15.2\,\mu\text{m}. Bottom Right: Using the same value of L0L_{0}, the circle arcs model generates an angle field that closely matches the experimentally observed microtubule orientation. (c) 3D view of a pole-indented tactoid, representing the average fit parameters of MII spindles (Methods 4). (d) Generatrix of a pole-indented tactoid, with virtual poles at (±L0,0)(\pm L_{0},0). (e) On the convex [concave] part of the spindle boundary, η(ϕ)\eta(\phi) is defined as the angle tangent [perpendicular] to the best-fit pole-indented tactoid, where ϕ\phi is the polar angle in the xyxy-plane. (f) Inset: In polar coordinates, the spindle boundary is parameterized by the curve 𝐛(ϕ)\mathbf{b}(\phi). Main: Without additional fit parameters, the measured microtubule orientation at the spindle boundary θt(𝐛(ϕ))\langle\theta\rangle_{t}(\mathbf{b}(\phi)) (thin purple curves & black points with error bars) closely follows the predicted form η(ϕ)\eta(\phi) (red solid curve). (g) Rescaling of experimental data by pole spacing, 𝐫𝐫/L0\mathbf{r}\rightarrow\mathbf{r}/L_{0}, allows averaging over spindles (Methods 5). The circle arcs model predicts that rescaled data is well-described by a master field generated by the tangent angles to family of arcs that intersect at (±1,0)(\pm 1,0), outside the region shown in these images. (h) Horizontal and vertical line profiles of microtubule orientation. Faint curves show the line profiles of individual spindles, which are binned to generate the points with error bars. The predictions of the master circle arcs model (L0=1L_{0}=1), which contains no fit parameters, are shown as bold curves. Error bars in (f) and (h) indicate SE.
Refer to caption
Figure 2: Orientational fluctuations in mouse oocyte spindles are highest in regions of low microtubule density. (a) Fluctuations are calculated by subtracting steady-state values of the microtubule orientation field, given by the circle-arcs model, from instantaneous values. Correlation functions are calculated in the white dashed box (side length λ0\lambda_{0}) in the middle of the spindle, where 𝐧^𝟎𝐱^\mathbf{\hat{n}_{0}}\approx\mathbf{\hat{x}}. (b) Near the middle of the spindle, δ𝐧𝐧^𝟎δ𝐧𝐱^=0\delta\mathbf{n}\cdot\mathbf{\hat{n}_{0}}\approx\delta\mathbf{n}\cdot\mathbf{\hat{x}}=0 and, to lowest order in δθ\delta\theta, δ𝐧=δθ𝐲^\delta\mathbf{n}=\delta\theta\,\mathbf{\hat{y}}. (c) Spatial correlation function snn(q0,qy)s_{\text{nn}}(q_{0},q_{y}) for 16 spindles, where q0=2π/λ0q_{0}=2\pi/\lambda_{0} and qyq_{y} is the wave-vector component perpendicular to the spindle axis. Correlation functions for individual spindles are plotted in color; binned data points are obtained by averaging; error bars indicate SE. At the longest and shortest wavelengths (smallest and largest qyq_{y}), snns_{\text{nn}} decays as qy2q_{y}^{-2}; around qy=(2.9±0.1)q_{y}^{*}=(2.9\pm 0.1) rad μm1\,\mu\text{m}^{-1} (black arrow; uncertainty estimate in S.I. 6), a peak appears. (d) Time-averaged retardance rt\langle r\rangle_{t} (top, yellow) and orientational fluctuations |δθ|t\langle|\delta\theta|\rangle_{t} (bottom, purple). Scale bar 5 μm\,\mu\text{m}; spindle boundary shown as thin black curve in |δθ|t\langle|\delta\theta|\rangle_{t} image; inset shows a 5μm×5μm5\,\mu\text{m}\times 5\,\mu\text{m} box at the center of the spindle. (e) Top: Near the center of the spindle (white box in (d)), orientational fluctuations are negatively correlated with retardance. Black line shows best fit to binned data, with slope (0.017±0.007)(-0.017\pm 0.007) rad nm-1 (95% CI). Bottom: Orientational fluctuations are negatively correlated with retardance in all but one spindle; the average slope is (0.010±0.002)(-0.010\pm 0.002) rad nm-1 (mean ±\pm SE). (f) Applying a local binarization filter (radius 2μm2\,\mu\text{m}) to rt\langle r\rangle_{t} and |δθ|t\langle|\delta\theta|\rangle_{t} reveals elongated regions of low microtubule density, whose long axes are roughly parallel to the spindle axis; orientational fluctuations are larger in these low-density regions. All images are masked to only show features inside the spindle boundary (thin white curve in bottom left image). (g) Histogram of the ratio of the magnitude of orientational fluctuations in high-retardance regions and low-retardance regions, as identified by local binarization. Orientational fluctuations are on average larger in lower-density regions; the average value of |δθ|low r/|δθ|high r\langle|\delta\theta|\rangle_{\text{low }r}/\langle|\delta\theta|\rangle_{\text{high }r} over all spindles is 1.07±0.021.07\pm 0.02 (mean ±\pm SE).
Refer to caption
Figure 3: Chromosomes create long, tactoid-like voids in the microtubule network of mouse oocyte spindles. (a) Confocal micrographs of living oocytes, taken with the spindle long axis in the confocal plane. Microtubules are labeled with SiR-tubulin, chromosomes with H2B-EGFP. (b) Micrographs of the metaphase plate (x=0x=0 plane). In this plane, chromosome positions (top image, cyan) correspond to regions of low microtubule density, i.e. voids (middle image, black gaps in red spindle). (c) The typical void has a tactoid-like 3D shape. Along 𝐱^\mathbf{\hat{x}}, the void length β\beta is much greater than the chromosome size. In the metaphase plate, the void cross-section closely matches the chromosome cross-section and may be approximated as an ellipse with major and minor axes aa and bb. Bottom Left Inset: The true tactoid of equal volume to the void shown has a circular cross section with waist diameter ab\sqrt{ab}. (d) Top Row: For spindles with their long axes perpendicular to the optical axis, the time-averaged LC-PolScope retardance profile r(xi,y)r(x_{i},y) at a given position xix_{i} along the long axis can be fitted to the formula rpred(xi,y)=2A0ρx(xi)(R(xi)2y2)1/2r_{\text{pred}}(x_{i},y)=2A_{0}\rho_{x}(x_{i})(R(x_{i})^{2}-y^{2})^{1/2}, where ρx(xi)\rho_{x}(x_{i}) is the microtubule cross-sectional density and R(xi)R(x_{i}) the spindle radius in the plane x=xix=x_{i} (S.I. 3). Assuming microtubule density is constant outside the voids, larger values of ρx(xi)\rho_{x}(x_{i}) correspond to less area taken up by voids. Bottom Row: Fits to rt(xi,y)\langle r\rangle_{t}(x_{i},y) at three different positions x1x_{1}, x2x_{2}, x3x_{3}, along the spindle axis. (e) Best-fit values of microtubule cross-section density ρx\rho_{x} as a function of position xx along the spindle long axis. Faint solid curves represent data from individual spindles; points with error bars represent the average over all spindles. (f) By assuming that the “missing” density in the middle of each spindle is due to the presence of nchr=20n_{\text{chr}}=20 identical voids, we can infer the average void profile, which is well-approximated by a circle arc (solid curve) with waist diameter ab=(1.0±0.1)μm\sqrt{ab}=(1.0\pm 0.1)\,\mu\text{m} and length β=(11±1)μm\beta=(11\pm 1)\,\mu\text{m} (both 95% CI). To aid visualization of the physical shape of the void, the fit is also shown reflected in the xx-axis (dashed curve). (g) The formation of director-aligned, tactoid-like voids around compact inclusions can be seen in everyday nematic materials, for example cylindrical lip gloss tubes inserted into a straw broom head whose loose end is wrapped with a hair tie. A US quarter dollar coin is included for scale. Error bars in (e) and (f) show SE. All scale bars 5μm5\,\mu\text{m}.
Refer to caption
Figure 4: Metaphase plate configurations in MII spindles are consistent with a model in which chromosomes repel each other over distances of several microns, but inconsistent with random positioning of non-overlapping chromosomes. (a) Top: Confocal micrograph of the metaphase plate (x=0x=0 plane) of a living MII spindle, labeled as in Fig. 3. Middle: Binarization identifies nchr=20n_{\text{chr}}=20 chromosome sections, with centers spaced 2μm\sim 2\,\mu\text{m} apart. Spindle boundary in white. Bottom: Chromosome sections approximated by 20 identical ellipsoids. In this spindle, a=2.1μma=2.1\,\mu\text{m} and b=0.8μmb=0.8\,\mu\text{m}. Scale bar 5μm5\,\mu\text{m}. (b) Left: At separations ss significantly less than the typical chromosome size (sbs\ll b), the correlation function gII(s)g_{II}(s) is much greater than one (dashed black line). At larger separations, gII(s)g_{II}(s) first reaches a local minimum at (1.27±0.04)μm(1.27\pm 0.04)\,\mu\text{m} (black arrow) and a local maximum at s=(2.4±0.1)μms^{*}=(2.4\pm 0.1)\,\mu\text{m} (white arrow). Right: The separation ss^{*} corresponds to the distance away from each chromosome where it is most probable to find another chromosome. (c) Left: Pair correlation functions for simulated data of non-overlapping, randomly placed 2D chromosome sections lack local extrema, and decay monotonically to 1. Each colored curve is obtained from a simulation initialized with one experimental data set. Right: Snapshot of one simulation, initialized with the spindle boundary and binarized chromosome sections shown in (a). (d) Model for deformation-induced long-range repulsion between negative-tactoid-like inclusions in a 2D nematic. In this model, the orientation field (thin gray curves) everywhere in the z=0z=0 plane is fully specified by two rows of ±1/2\pm 1/2 topological defects; each row is parallel to 𝐱^\mathbf{\hat{x}} and their centers lie along x=0x=0 (dashed black line). Inclusion boundaries (thick black curves) are those integral curves of the nematic field that pass through both 1/2-1/2 defects in a given row (S.I. 10). Defect spacings within a row are determined by the geometric parameters β\beta and DD, chosen to match the experimentally observed void length and waist curvature (Fig. 3 (c & f)). The interaction potential UintU_{\text{int}}, normalized by elastic constant kk, induced by deformation of the nematic field is repulsive at all center-to-center distances dd. (e) Left: Correlation functions for simulated data of 20 ellipsoids interacting in the x=0x=0 plane via a repulsive U(s)s6U(s)\propto s^{-6} potential display a local minimum [maximum] at (1.32±0.04)μm(1.32\pm 0.04)\,\mu\text{m} [(2.4±0.1)μm(2.4\pm 0.1)\,\mu\text{m}]. Right: Snapshot of one simulation performed with spindle boundary and chromosome shape parameters from (a) (S.I. 9). Error bars in all plots indicate SE.