Uncovering fine-grained phenotypes of live cell dynamics is pivotal for a comprehensive understanding of the heterogeneity in healthy and diseased biological processes. However, this endeavor poses significant technical challenges for unsupervised machine learning, requiring the extraction of features that not only faithfully preserve this heterogeneity but also effectively discriminate between established biological states, all while remaining interpretable. To tackle these challenges, a self-training deep learning framework designed for fine-grained and interpretable phenotyping is presented. This framework incorporates an unsupervised teacher model with interpretable features to facilitate feature learning in a student deep neural network (DNN). Significantly, an autoencoder-based regularizer is designed to encourage the student DNN to maximize the heterogeneity associated with molecular perturbations. This method enables the acquisition of features with enhanced discriminatory power, while simultaneously preserving the heterogeneity associated with molecular perturbations. This study successfully delineated fine-grained phenotypes within the heterogeneous protrusion dynamics of migrating epithelial cells, revealing specific responses to pharmacological perturbations. Remarkably, this framework adeptly captured a concise set of highly interpretable features uniquely linked to these fine-grained phenotypes, each corresponding to specific temporal intervals crucial for their manifestation. This unique capability establishes it as a valuable tool for investigating diverse cellular dynamics and their heterogeneity.

We present a method for learning \'spectrally descriptive\' edge weights for graphs. We generalize a previously known distance measure on graphs (graph diffusion distance [GDD]), thereby allowing it to be tuned to minimize an arbitrary loss function. Because all steps involved in calculating this modified GDD are differentiable, we demonstrate that it is possible for a small neural network model to learn edge weights which minimize loss. We apply this method to discriminate between graphs constructed from shoot apical meristem images of two genotypes of Arabidopsis thaliana specimens: wild-type and trm678 triple mutants with cell division phenotype. Training edge weights and kernel parameters with contrastive loss produce a learned distance metric with large margins between these graph categories. We demonstrate this by showing improved performance of a simple k -nearest-neighbour classifier on the learned distance matrix. We also demonstrate a further application of this method to biological image analysis. Once trained, we use our model to compute the distance between the biological graphs and a set of graphs output by a cell division simulator. Comparing simulated cell division graphs to biological ones allows us to identify simulation parameter regimes which characterize mutant versus wild-type Arabidopsis cells. We find that trm678 mutant cells are characterized by increased randomness of division planes and decreased ability to avoid previous vertices between cell walls.

Morphogenesis is a physical process that sculpts the final functional forms of tissues and organs. Remarkably, the lungs of terrestrial vertebrates vary dramatically in form across species, despite providing the same function of transporting oxygen and carbon dioxide. These divergent forms arise from distinct physical processes through which the epithelium of the embryonic lung responds to the mechanical properties of its surrounding mesenchymal microenvironment. Here we compare the physical processes that guide folding of the lung epithelium in mammals, birds, and reptiles, and suggest a conceptual framework that reconciles how conserved molecular signaling generates divergent mechanical forces across these species.

UNASSIGNED: Breast tumors often display an astonishing degree of spatial and temporal heterogeneity, which are associated with cancer progression, drug resistance, and relapse. Triple-negative breast cancer (TNBC) is a particularly aggressive and heterogeneous subtype for which targeted therapies are scarce. Consequently, patients with TNBC have a poorer overall prognosis compared to other breast cancer patients. Within heterogeneous tumors, individual clonal subpopulations may exhibit differences in their rates of growth and degrees of invasiveness. We hypothesized that such phenotypic heterogeneity at the single-cell level may accelerate tumor progression by enhancing the overall growth and invasion of the entire tumor.
UNASSIGNED: To test this hypothesis, we isolated and characterized clonal subpopulations with distinct morphologies and biomarker expression from the inherently heterogeneous 4T1 mouse mammary carcinoma cell line. We then leveraged a 3D microfluidic tumor model to reverse-engineer intratumoral heterogeneity and thus investigate how interactions between phenotypically distinct subpopulations affect tumor growth and invasion.
UNASSIGNED: We found that the growth and invasion of multiclonal tumors were largely dictated by the presence of cells with epithelial and mesenchymal traits, respectively. The latter accelerated overall tumor invasion, even when these cells comprised less than 1% of the initial population. Consistently, tumor progression was delayed by selectively targeting the mesenchymal subpopulation.
UNASSIGNED: This work reveals that highly invasive cells can dominate tumor phenotype and that specifically targeting these cells can slow the progression of heterogeneous tumors, which may help inform therapeutic approaches.
UNASSIGNED: The online version contains supplementary material available at 10.1007/s12195-023-00792-w.

Sandy beaches are land-sea transitional habitats experiencing \'multidirectional\' habitat loss due to coastal developments (e.g. armoring and/or conversion of natural vegetation into manmade structures) and beach erosion. This \'coastal squeeze\' is a chronic and progressive process; however, its impacts on beach biodiversity across morphodynamic gradients are still to be unveiled. We hypothesized that the effects of multidirectional habitat loss would be more severe on dissipative than on reflective beaches, due to the higher elevation, amount of built up sediment, and width of the backshore compartment of the latter. We, thus, examined the effects of coastal developments and erosion on density and size structure of the Atlantic ghost crab, Ocypode quadrata, on beaches with different morphodynamics. Given that the living area of ghost crabs spans all cross-shore compartments and the whole dissipative-to-reflective morphodynamic gradient, they are appropriate organisms to access the synergic effects of coastal developments and beach erosion under different morphodynamic regimes. On dissipative beaches, density and mean crab size increased with moderate erosion, attributed to the effects of space loss, which might increase territorial competition, favoring the remaining larger individuals. However, mean size and density decreased with high erosion given the more intense reduction in the abundance of large-sized crabs living in up-shore habitats. Mean crab size also decreased in the presence of coastal development while crab density did not vary with loss of backshore habitats occupied by larger individuals. On reflective beaches, both density and crab size decreased with coastal development; the crab size decrease recorded under moderate erosion was more evident in the presence of coastal development. Under high erosion, mean crab sizes declined, reflecting those under low erosion conditions. Overall, populations on reflective beaches appeared more resilient to extreme erosion. Notwithstanding, coastal developments affected population structure across all beach types, and especially in areas subjected to high erosion, exhibiting a synergic effect. We predict that, in combination, these stressors may lead to functionally extinct populations where conditions necessary for individuals to reach sexual maturity (i.e. occurrence of only small-sized and immature individuals) are not met. Thus, the connectivity between water, beach compartments and dunes/coastal plain, on both local and regional scales, may be essential to maintain viable and connected populations of ghost crabs. Further, our results strongly suggest that both size and density (complemented with crab abundance) must be considered equally important and in combination in future efforts to assess anthropogenic stressors on ghost crab populations and when guiding conservation strategies and policies to prevent their local and regional extinctions.

Rho-GTPases are central regulators within a complex signaling network that controls cytoskeletal organization and cell movement. The network includes multiple GTPases, such as the most studied Rac1, Cdc42, and RhoA, along with their numerous effectors that provide mutual regulation through feedback loops. Here we investigate the temporal and spatial relationship between Rac1 and Cdc42 during membrane ruffling, using a simulation model that couples GTPase signaling with cell morphodynamics and captures the GTPase behavior observed with FRET-based biosensors. We show that membrane velocity is regulated by the kinetic rate of GTPase activation rather than the concentration of active GTPase. Our model captures both uniform and polarized ruffling. We also show that cell-type specific time delays between Rac1 and Cdc42 activation can be reproduced with a single signaling motif, in which the delay is controlled by feedback from Cdc42 to Rac1. The resolution of our simulation output matches those of time-lapsed recordings of cell dynamics and GTPase activity. Our data-driven modeling approach allows us to validate simulation results with quantitative precision using the same pipeline for the analysis of simulated and experimental data.

The invariant cell lineage of Caenorhabditis elegans allows unambiguous assignment of the identity for each cell, which offers a unique opportunity to study developmental dynamics such as the timing of cell division, dynamics of gene expression, and cell fate decisions at single-cell resolution. However, little is known about cell morphodynamics, including the extent to which they are variable between individuals, mainly due to the lack of sufficient amount and quality of quantified data. In this study, we systematically quantified the cell morphodynamics in 52 C. elegans embryos from the two-cell stage to mid-gastrulation at the high spatiotemporal resolution, 0.5 μm thickness of optical sections, and 30-second intervals of recordings. Our data allowed systematic analyses of the morphological features. We analyzed sphericity dynamics and found a significant increase at the end of metaphase in every cell, indicating the universality of the mitotic cell rounding. Concomitant with the rounding, the volume also increased in most but not all cells, suggesting less universality of the mitotic swelling. Combining all features showed that cell morphodynamics was unique for each cell type. The cells before the onset of gastrulation could be distinguished from all the other cell types. Quantification of reproducibility in cell-cell contact revealed that variability in division timings and cell arrangements produced variability in contacts between the embryos. However, the area of such contacts occupied less than 5% of the total area, suggesting the high reproducibility of spatial occupancies and adjacency relationships of the cells. By comparing the morphodynamics of identical cells between the embryos, we observed diversity in the variability between cells and found it was determined by multiple factors, including cell lineage, cell generation, and cell-cell contact. We compared the variabilities of cell morphodynamics and cell-cell contacts with those in ascidian Phallusia mammillata embryos. The variabilities were larger in C. elegans, despite smaller differences in embryo size and number of cells at each developmental stage.

It has been proposed that smooth muscle differentiation may physically sculpt airway epithelial branches in mammalian lungs. Serum response factor (SRF) acts with its co-factor myocardin to activate the expression of contractile smooth muscle markers. In the adult, however, smooth muscle exhibits a variety of phenotypes beyond contractile, and these are independent of SRF/myocardin-induced transcription. To determine whether a similar phenotypic plasticity is exhibited during development, we deleted Srf from the mouse embryonic pulmonary mesenchyme. Srf-mutant lungs branch normally, and the mesenchyme displays mechanical properties indistinguishable from controls. scRNA-seq identified an Srf-null smooth muscle cluster, wrapping the airways of mutant lungs, which lacks contractile smooth muscle markers but retains many features of control smooth muscle. Srf-null embryonic airway smooth muscle exhibits a synthetic phenotype, compared with the contractile phenotype of mature wild-type airway smooth muscle. Our findings identify plasticity in embryonic airway smooth muscle and demonstrate that a synthetic smooth muscle layer promotes airway branching morphogenesis.

Many emergent, non-fundamental models of complex systems can be described naturally by the temporal evolution of spatial structures with some nontrivial discretized topology, such as a graph with suitable parameter vectors labeling its vertices. For example, the cytoskeleton of a single cell, such as the cortical microtubule network in a plant cell or the actin filaments in a synapse, comprises many interconnected polymers whose topology is naturally graph-like and dynamic. The same can be said for cells connected dynamically in a developing tissue. There is a mathematical framework suitable for expressing such emergent dynamics, \"stochastic parameterized graph grammars,\" composed of a collection of the graph- and parameter-altering rules, each of which has a time-evolution operator that suitably moves probability. These rule-level operators form an operator algebra, much like particle creation/annihilation operators or Lie group generators. Here, we present an explicit and constructive calculation, in terms of elementary basis operators and standard component notation, of what turns out to be a general combinatorial expression for the operator algebra that reduces products and, therefore, commutators of graph grammar rule operators to equivalent integer-weighted sums of such operators. We show how these results extend to \"dynamical graph grammars,\" which include rules that bear local differential equation dynamics for some continuous-valued parameters. Commutators of such time-evolution operators have analytic uses, including deriving efficient simulation algorithms and approximations and estimating their errors. The resulting formalism is complementary to spatial models in the form of partial differential equations or stochastic reaction-diffusion processes. We discuss the potential application of this framework to the remodeling dynamics of the microtubule cytoskeleton in cortical microtubule networks relevant to plant development and of the actin cytoskeleton in, for example, a growing or shrinking synaptic spine head. Both cytoskeletal systems underlie biological morphodynamics.

During development of the embryonic mouse lung, the pulmonary mesenchyme differentiates into smooth muscle that wraps around the airway epithelium. Inhibiting smooth muscle differentiation leads to cystic airways, while enhancing it stunts epithelial branching. These findings support a conceptual model wherein the differentiation of smooth muscle sculpts the growing epithelium into branches at precise positions and with stereotyped morphologies. Unfortunately, most approaches to manipulate the differentiation of airway smooth muscle rely on pharmacological or physical perturbations that are conducted ex vivo. Here, we explored the use of diphtheria toxin-based genetic ablation strategies to eliminate airway smooth muscle in the embryonic mouse lung. Surprisingly, neither airway smooth muscle wrapping nor epithelial branching were affected in embryos in which the expression of diphtheria toxin or its receptor were driven by several different smooth muscle-specific Cre lines. Close examination of spatial patterns of Cre activity in the embryonic lung revealed that none of these commonly used Cre lines target embryonic airway smooth muscle robustly or specifically. Our findings demonstrate the need for airway smooth muscle-specific Cre lines that are active in the embryonic lung, and serve as a resource for researchers contemplating the use of these commonly used Cre lines for studying embryonic airway smooth muscle.