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The seasonal cycle of sea ice variability in the Bering Sea, together with the thermodynamic and dynamic processes that control it, are examined in a fine resolution (1/10°) global coupled ocean/sea-ice model configured in the Community Earth System Model (CESM) framework. The ocean/sea-ice model consists of the Los Alamos National Laboratory Parallel Ocean Program (POP) and the Los Alamos Sea Ice Model (CICE). The model was forced with time-varying reanalysis atmospheric forcing for the time period 1970-1989. This study focuses on the time period 1980-1989. The simulated seasonal-mean fields of sea ice concentration strongly resemble satellite-derived observations, as quantified by root-mean-square errors and pattern correlation coefficients. The sea ice energy budget reveals that the seasonal thermodynamic ice volume changes are dominated by the surface energy flux between the atmosphere and the ice in the northern region and by heat flux from the ocean to the ice along the southern ice edge, especially on the western side. The sea ice force balance analysis shows that sea ice motion is largely associated with wind stress. The force due to divergence of the internal ice stress tensor is large near the land boundaries in the north, and it is small in the central and southern ice-covered region. During winter, which dominates the annual mean, it is found that the simulated sea ice was mainly formed in the northern Bering Sea, with the maximum ice growth rate occurring along the coast due to cold air from northerly winds and ice motion away from the coast. South of St Lawrence Island, winds drive the model sea ice southwestward from the north to the southwestern part of the ice-covered region. Along the ice edge in the western Bering Sea, model sea ice is melted by warm ocean water, which is carried by the simulated Bering Slope Current flowing to the northwest, resulting in the S-shaped asymmetric ice edge. In spring and fall, similar thermodynamic and dynamic patterns occur in the model, but with typically smaller magnitudes and with season-specific geographical and directional differences.

A fine-resolution (1/10°) ocean/sea ice model configured in the Community Earth System Model framework is compared with observations and studied to determine the basin-scale and local balances controlling the variability of sea ice anomalies from the mean seasonal cycle in the Bering Sea for the time period 1980–1989. The model produces variations in total Bering Sea ice area anomalies that are highly correlated with observations. Surface air temperature, which is specified from reanalysis atmospheric forcing, strongly controls the ice volume variability in this simulation. The thermodynamic ice volume change is dominated by surface energy flux via atmosphere-ice sensible heat flux, except near the southern ice edge where it is largely controlled by ocean-ice heat flux. While thermodynamic processes dominate the variations in ice volume in the Bering Sea on the large scale, dynamic processes are important on the local scale near ice margins (both oceanic and land), where dynamic and thermodynamic ice volume changes have opposite signs and nearly cancel each other. Ice motion is generally consistent with winds driving the flow, except near certain straits in the north where ice motion largely follows ocean currents. Two key climate events, strong ice growth with cold air temperature and northerly wind anomalies in February 1984 and weak ice growth with warm air temperature and southerly wind anomalies in February 1989, are studied here in detail. While the processes controlling the ice changes are generally similar to those in other years, these large events help reveal the characteristic spatial patterns of ice growth/melt and transport anomalies.

To investigate the fundamental question of how cellular variations arise across spatiotemporal scales in a population of identical healthy cells, we focused on nuclear growth in hiPS cell colonies as a model system. We generated a 3D timelapse dataset of thousands of nuclei over multiple days, and developed open-source tools for image and data analysis and an interactive timelapse viewer for exploring quantitative features of nuclear size and shape. We performed a data-driven analysis of nuclear growth variations across timescales. We found that individual nuclear volume growth trajectories arise from short timescale variations attributable to their spatiotemporal context within the colony. We identified a strikingly time-invariant volume compensation relationship between nuclear growth duration and starting volume across the population. Notably, we discovered that inheritance plays a crucial role in determining these two key nuclear growth features while other growth features are determined by their spatiotemporal context and are not inherited., Competing Interests: Declaration of interests The authors declare no competing interests.

To produce abundant cell culture samples to generate large, standardized image datasets of human induced pluripotent stem (hiPS) cells, we developed an automated workflow on a Hamilton STAR liquid handler system. This was developed specifically for culturing hiPS cell lines expressing fluorescently tagged proteins, which we have used to study the principles by which cells establish and maintain robust dynamic localization of cellular structures. This protocol includes all details for the maintenance, passage and seeding of cells, as well as Matrigel coating of 6-well plastic plates and 96-well optical-grade, glass plates. We also developed an automated image-based hiPS cell colony segmentation and feature extraction pipeline to streamline the process of predicting cell count and selecting wells with consistent morphology for high-resolution three-dimensional (3D) microscopy. The imaging samples produced with this protocol have been used to study the integrated intracellular organization and cell-to-cell variability of hiPS cells to train and develop deep learning-based label-free predictions from transmitted-light microscopy images and to develop deep learning-based generative models of single-cell organization. This protocol requires some experience with robotic equipment. However, we provide details and source code to facilitate implementation by biologists less experienced with robotics. The protocol is completed in less than 10 h with minimal human interaction. Overall, automation of our cell culture procedures increased our imaging samples' standardization, reproducibility, scalability and consistency. It also reduced the need for stringent culturist training and eliminated culturist-to-culturist variability, both of which were previous pain points of our original manual pipeline workflow., (© 2023. Crown.)

Understanding how a subset of expressed genes dictates cellular phenotype is a considerable challenge owing to the large numbers of molecules involved, their combinatorics and the plethora of cellular behaviours that they determine 1,2 . Here we reduced this complexity by focusing on cellular organization-a key readout and driver of cell behaviour 3,4 -at the level of major cellular structures that represent distinct organelles and functional machines, and generated the WTC-11 hiPSC Single-Cell Image Dataset v1, which contains more than 200,000 live cells in 3D, spanning 25 key cellular structures. The scale and quality of this dataset permitted the creation of a generalizable analysis framework to convert raw image data of cells and their structures into dimensionally reduced, quantitative measurements that can be interpreted by humans, and to facilitate data exploration. This framework embraces the vast cell-to-cell variability that is observed within a normal population, facilitates the integration of cell-by-cell structural data and allows quantitative analyses of distinct, separable aspects of organization within and across different cell populations. We found that the integrated intracellular organization of interphase cells was robust to the wide range of variation in cell shape in the population; that the average locations of some structures became polarized in cells at the edges of colonies while maintaining the 'wiring' of their interactions with other structures; and that, by contrast, changes in the location of structures during early mitotic reorganization were accompanied by changes in their wiring., (© 2023. The Author(s).)

Although some cell types may be defined anatomically or by physiological function, a rigorous definition of cell state remains elusive. Here, we develop a quantitative, imaging-based platform for the systematic and automated classification of subcellular organization in single cells. We use this platform to quantify subcellular organization and gene expression in >30,000 individual human induced pluripotent stem cell-derived cardiomyocytes, producing a publicly available dataset that describes the population distributions of local and global sarcomere organization, mRNA abundance, and correlations between these traits. While the mRNA abundance of some phenotypically important genes correlates with subcellular organization (e.g., the beta-myosin heavy chain, MYH7), these two cellular metrics are heterogeneous and often uncorrelated, which suggests that gene expression alone is not sufficient to classify cell states. Instead, we posit that cell state should be defined by observing full distributions of quantitative, multidimensional traits in single cells that also account for space, time, and function., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

We describe a multistep method for endogenous tagging of transcriptionally silent genes in human induced pluripotent stem cells (hiPSCs). A monomeric EGFP (mEGFP) fusion tag and a constitutively expressed mCherry fluorescence selection cassette were delivered in tandem via homology-directed repair to five genes not expressed in hiPSCs but important for cardiomyocyte sarcomere function: TTN, MYL7, MYL2, TNNI1, and ACTN2. CRISPR/Cas9 was used to deliver the selection cassette and subsequently mediate its excision via microhomology-mediated end-joining and non-homologous end-joining. Most excised clones were effectively tagged, and all properly tagged clones expressed the mEGFP fusion protein upon differentiation into cardiomyocytes, allowing live visualization of these cardiac proteins at the sarcomere. This methodology provides a broadly applicable strategy for endogenously tagging transcriptionally silent genes in hiPSCs, potentially enabling their systematic and dynamic study during differentiation and morphogenesis., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

The microtubule (MT) cytoskeleton plays an essential role in mitosis, intracellular transport, cell shape, and cell migration. The assembly and disassembly of MTs, which can occur through the addition or loss of subunits at the plus- or minus-ends of the polymer, is essential for MTs to carry out their biological functions. A variety of proteins act on MT ends to regulate their dynamics, including a recently described family of MT minus-end binding proteins called calmodulin-regulated spectrin-associated protein (CAMSAP)/Patronin/Nezha. Patronin, the single member of this family in Drosophila, was previously shown to stabilize MT minus-ends against depolymerization in vitro and in vivo. Here, we show that all three mammalian CAMSAP family members also bind specifically to MT minus-ends and protect them against kinesin-13-induced depolymerization. However, these proteins differ in their abilities to suppress tubulin addition at minus-ends and to dissociate from MTs. CAMSAP1 does not interfere with polymerization and tracks along growing minus-ends. CAMSAP2 and CAMSAP3 decrease the rate of tubulin incorporation and remain bound, thereby creating stretches of decorated MT minus-ends. By using truncation analysis, we find that somewhat different minimal domains of CAMSAP and Patronin are involved in minus-end localization. However, we find that, in both cases, a highly conserved C-terminal domain and a more variable central domain cooperate to suppress minus-end dynamics in vitro and that both regions are required to stabilize minus-ends in Drosophila S2 cells. These results show that members of the CAMSAP/Patronin family all localize to and protect minus-ends but have evolved distinct effects on MT dynamics.

Control of gene expression by the phosphatidylinositol (PI) 3-kinase/Akt pathway plays an important role in mammalian cell proliferation and survival, and numerous transcription factors and genes regulated by PI 3-kinase signaling have been identified. Because steady-state levels of mRNA are regulated by degradation as well as transcription, we have investigated the importance of mRNA degradation in controlling gene expression downstream of PI 3-kinase. We previously performed global expression analyses that identified a set of approximately 50 genes that were downregulated following inhibition of PI 3-kinase in proliferating T98G cells. By blocking transcription with actinomycin D, we found that almost 40% of these genes were regulated via effects of PI 3-kinase on mRNA stability. Analyses of β-globin-3' untranslated region (UTR) fusion transcripts indicated that sequences within 3' UTRs were the primary determinants of rapid mRNA decay. Small interfering RNA (siRNA) experiments further showed that knockdown of BRF1 or KSRP, both ARE binding proteins (ARE-BPs) regulated by Akt, stabilized the mRNAs of a majority of the downregulated genes but that knockdown of ARE-BPs that are not regulated by PI 3-kinase did not affect degradation of these mRNAs. These results show that PI 3-kinase regulation of mRNA stability, predominantly mediated by BRF1, plays a major role in regulating gene expression.

Multiple oil drops bouncing on the surface of a vertically vibrating bath of the same oil exhibit self-organization behavior in two dimensions [S. Protière, Y. Couder, E. Fort, and A. Boudaoud, J. Phys.: Condens. Matter 17, S3529 (2005)]. We describe further the morphology and dynamic behavior of stable assemblies of large bouncing oil drops, for which we find that both the spacing and the lattice structure itself change with frequency, with variants of both square and hexagonal structures being observed. Large "rafts" of drops form soft triangular lattices with faceted boundaries. Small clusters of drops are unstable to coherent, collective spinning under certain driving conditions, manifesting spontaneous rotational symmetry breaking.