Enhanced cell segmentation with limited training datasets using cycle generative adversarial networks.

Deep learning is transforming bioimage analysis, but its application in single-cell segmentation is limited by the lack of large, diverse annotated datasets. We addressed this by introducing a CycleGAN-based architecture, cGAN-Seg, that enhances the training of cell segmentation models with limited annotated datasets. During training, cGAN-Seg generates annotated synthetic phase-contrast or fluorescent images with morphological details and nuances closely mimicking real images. This increases the variability seen by the segmentation model, enhancing the authenticity of synthetic samples and thereby improving predictive accuracy and generalization. Experimental results show that cGAN-Seg significantly improves the performance of widely used segmentation models over conventional training techniques. Our approach has the potential to accelerate the development of foundation models for microscopy image analysis, indicating its significance in advancing bioimage analysis with efficient training methodologies.

Self-organization of embryonic stem cells into a reproducible embryo model through epigenome editing.

Embryonic stem cells (ESCs) can self-organize in vitro into developmental patterns with spatial organization and molecular similarity to that of early embryonic stages. This self-organization of ESCs requires transmission of signaling cues, via addition of small molecule chemicals or recombinant proteins, to induce distinct embryonic cellular fates and subsequent assembly into structures that can mimic aspects of early embryonic development. During natural embryonic development, different embryonic cell types co-develop together, where each cell type expresses specific fate-inducing transcription factors through activation of non-coding regulatory elements and interactions with neighboring cells. However, previous studies have not fully explored the possibility of engineering endogenous regulatory elements to shape self-organization of ESCs into spatially-ordered embryo models. Here, we hypothesized that cell-intrinsic activation of a minimum number of such endogenous regulatory elements is sufficient to self-organize ESCs into early embryonic models. Our results show that CRISPR-based activation (CRISPRa) of only two endogenous regulatory elements in the genome of pluripotent stem cells is sufficient to generate embryonic patterns that show spatial and molecular resemblance to that of pre-gastrulation mouse embryonic development. Quantitative single-cell live fluorescent imaging showed that the emergence of spatially-ordered embryonic patterns happens through the intrinsic induction of cell fate that leads to an orchestrated collective cellular motion. Based on these results, we propose a straightforward approach to efficiently form 3D embryo models through intrinsic CRISPRa-based epigenome editing and independent of external signaling cues. CRISPRa-Programmed Embryo Models (CPEMs) show highly consistent composition of major embryonic cell types that are spatially-organized, with nearly 80% of the structures forming an embryonic cavity. Single cell transcriptomics confirmed the presence of main embryonic cell types in CPEMs with transcriptional similarity to pre-gastrulation mouse embryos and revealed novel signaling communication links between different embryonic cell types. Our findings offer a programmable embryo model and demonstrate that minimum intrinsic epigenome editing is sufficient to self-organize ESCs into highly consistent pre-gastrulation embryo models.

Cell growth dilutes the cell cycle inhibitor Rb to trigger cell division.

Cell size is fundamental to cell physiology. For example, cell size determines the spatial scale of organelles and intracellular transport and thereby affects biosynthesis. Although some genes that affect mammalian cell size have been identified, the molecular mechanisms through which cell growth drives cell division have remained elusive. We show that cell growth during the G1 phase of the cell division cycle dilutes the cell cycle inhibitor Retinoblastoma protein (Rb) to trigger division in human cells. RB overexpression increased cell size and G1 duration, whereas RB deletion decreased cell size and removed the inverse correlation between cell size at birth and the duration of the G1 phase. Thus, Rb dilution through cell growth in G1 provides one of the long-sought molecular mechanisms that promotes cell size homeostasis.

Cyclin D-Cdk4,6 Drives Cell-Cycle Progression via the Retinoblastoma Protein's C-Terminal Helix.

The cyclin-dependent kinases Cdk4 and Cdk6 form complexes with D-type cyclins to drive cell proliferation. A well-known target of cyclin D-Cdk4,6 is the retinoblastoma protein Rb, which inhibits cell-cycle progression until its inactivation by phosphorylation. However, the role of Rb phosphorylation by cyclin D-Cdk4,6 in cell-cycle progression is unclear because Rb can be phosphorylated by other cyclin-Cdks, and cyclin D-Cdk4,6 has other targets involved in cell division. Here, we show that cyclin D-Cdk4,6 docks one side of an alpha-helix in the Rb C terminus, which is not recognized by cyclins E, A, and B. This helix-based docking mechanism is shared by the p107 and p130 Rb-family members across metazoans. Mutation of the Rb C-terminal helix prevents its phosphorylation, promotes G1 arrest, and enhances Rb's tumor suppressive function. Our work conclusively demonstrates that the cyclin D-Rb interaction drives cell division and expands the diversity of known cyclin-based protein docking mechanisms.

DNA Damage Regulates Translation through ß-TRCP Targeting of CReP.

The Skp1-Cul1-F box complex (SCF) associates with any one of a number of F box proteins, which serve as substrate binding adaptors. The human F box protein ßTRCP directs the conjugation of ubiquitin to a variety of substrate proteins, leading to the destruction of the substrate by the proteasome. To identify ßTRCP substrates, we employed a recently-developed technique, called Ligase Trapping, wherein a ubiquitin ligase is fused to a ubiquitin-binding domain to "trap" ubiquitinated substrates. 88% of the candidate substrates that we examined were bona fide substrates, comprising twelve previously validated substrates, eleven new substrates and three false positives. One ßTRCP substrate, CReP, is a Protein Phosphatase 1 (PP1) specificity subunit that targets the translation initiation factor eIF2α to promote the removal of a stress-induced inhibitory phosphorylation and increase cap-dependent translation. We found that CReP is targeted by ßTRCP for degradation upon DNA damage. Using a stable CReP allele, we show that depletion of CReP is required for the full induction of eIF2α phosphorylation upon DNA damage, and contributes to keeping the levels of translation low as cells recover from DNA damage.

Hst3 is turned over by a replication stress-responsive SCF(Cdc4) phospho-degron.

Hst3 is the histone deacetylase that removes histone H3K56 acetylation. H3K56 acetylation is a cell-cycle- and damage-regulated chromatin marker, and proper regulation of H3K56 acetylation is important for replication, genomic stability, chromatin assembly, and the response to and recovery from DNA damage. Understanding the regulation of enzymes that regulate H3K56 acetylation is of great interest, because the loss of H3K56 acetylation leads to genomic instability. HST3 is controlled at both the transcriptional and posttranscriptional level. Here, we show that Hst3 is targeted for turnover by the ubiquitin ligase SCF(Cdc4) after phosphorylation of a multisite degron. In addition, we find that Hst3 turnover increases in response to replication stress in a Rad53-dependent way. Turnover of Hst3 is promoted by Mck1 activity in both conditions. The Hst3 degron contains two canonical Cdc4 phospho-degrons, and the phosphorylation of each of these is required for efficient turnover both in an unperturbed cell cycle and in response to replication stress.