Stem cells regenerate differentiated cells to maintain and repair tissues and organs. They also replenish themselves, i.e. self-renewal, for the regenerative process to last a lifetime. How stem cells renew is of critical biological and medical significance. Here we use the skeletal muscle stem cell (MuSC) to study this process. Using a combination of genetic, molecular, and biochemical approaches, we show that MPP7, AMOT, and TAZ/YAP form a complex that activates a common set of target genes. Among these targets, Carm1 can direct MuSC renewal. In the absence of MPP7, TAZ can support regenerative progenitors and activate Carm1 expression, but not to a level needed for self-renewal. Facilitated by the actin polymerization-responsive AMOT, TAZ recruits the L27 domain of MPP7 to up-regulate Carm1 to the level necessary to drive MuSC renewal. The promoter of Carm1, and those of other common downstream genes, also contain binding site(s) for YY1. We further demonstrate that the L27 domain of MPP7 enhances the interaction between TAZ and YY1 to activate Carm1. Our results define a renewal transcriptional program embedded within the progenitor program, by selectively up-regulating key gene(s) within the latter, through the combination of protein interactions and in a manner dependent on the promoter context.

Microbial phototrophic communities dominated early Earth and thrive to this day, particularly in extreme environments. We focus on the impact of diel oscillations on phototrophic biofilms, especially in hot springs, where oxygenic phototrophs are keystone species that use light energy to fix carbon and often nitrogen. They exhibit photo-motility and stratification, and alter the physicochemical environment by driving O2, CO2, and pH oscillations. Omics analyses reveal extensive genomic and functional diversity in biofilms, but linking this to a predictive understanding of their structure and dynamics remains challenging. This can be addressed by better spatiotemporal resolution of microbial interactions, improved tools for building and manipulating synthetic communities, and integration of empirical and theoretical approaches.

The Magellanic Stream (MS)-an enormous ribbon of gas spanning 140 degrees of the southern sky trailing the Magellanic Clouds-has been exquisitely mapped in the five decades since its discovery. However, despite concerted efforts, no stellar counterpart to the MS has been conclusively identified. This stellar stream would reveal the distance and 6D kinematics of the MS, constraining its formation and the past orbital history of the Clouds. We have been conducting a spectroscopic survey of the most distant and luminous red giant stars in the Galactic outskirts. From this data set, we have discovered a prominent population of 13 stars matching the extreme angular momentum of the Clouds, spanning up to 100(degrees) along the MS at distances of 60-120 kpc. Furthermore, these kinematically selected stars lie along an [alpha/Fe]-deficient track in chemical space from -2.5 < [Fe/H] <- 0.5, consistent with their formation in the Clouds themselves. We identify these stars as high-confidence members of the Magellanic Stellar Stream. Half of these stars are metal-rich and closely follow the gaseous MS, whereas the other half are more scattered and metal-poor. We argue that the metal-rich stream is the recently formed tidal counterpart to the MS, and we speculate that the metal-poor population was thrown out of the SMC outskirts during an earlier interaction between the Clouds. The Magellanic Stellar Stream provides a strong set of constraints-distances, 6D kinematics, and birth locations-that will guide future simulations toward unveiling the detailed history of the Clouds.

A longstanding goal of biology is to identify the key genes and species that critically impact evolution, ecology, and health. Network analysis has revealed keystone species that regulate ecosystems and master regulators that regulate cellular genetic networks. Yet these studies have focused on pairwise biological interactions, which can be affected by the context of genetic background and other species present, generating higher-order interactions. The important regulators of higher-order interactions are unstudied. To address this, we applied a high-dimensional geometry approach that quantifies epistasis in a fitness landscape to ask how individual genes and species influence the interactions in the rest of the biological network. We then generated and also reanalyzed 5-dimensional datasets (two genetic, two microbiome). We identified key genes (e.g., the rbs locus and pykF) and species (e.g., Lactobacilli) that control the interactions of many other genes and species. These higher-order master regulators can induce or suppress evolutionary and ecological diversification by controlling the topography of the fitness landscape. Thus, we provide a method and mathematical justification for exploration of biological networks in higher dimensions.

Margarete M.S. Heck, professor of cell biology and genetics, University of Edinburgh, died peacefully at home amid her loving family under a blue moon on August 30, 2023, after a long journey with ovarian cancer.

One of the largest explosive eruptions instrumentally recorded occurred at Hunga volcano on 15 January 2022. The magma plumbing system under this volcano is unexplored because of inherent difficulties caused by its submarine setting. We use marine gravity data derived from satellite altimetry combined with multibeam bathymetry to model the architecture and dynamics of the magmatic system before and after the January 2022 eruption. We provide geophysical evidence for substantial high-melt content magma accumulation in three reservoirs at shallow depths (2 to 10 kilometers) under the volcano. We estimate that less than ~30% of the existing magma was evacuated by the main eruptive phases, enough to trigger caldera collapse. The eruption and caldera collapse reorganized magma storage, resulting in an increased connectivity between the two spatially distinct reservoirs. Modeling global satellite altimetry-derived gravity data at undersea volcanoes offer a promising reconnaissance tool to probe the subsurface for eruptible magma.

We report on a chemo-dynamical analysis of SPLUS J142445.34-254247.1 (SPLUS J1424-2542), an extremely metal-poor halo star enhanced in elements formed by the rapid neutron-capture process (r-process). This star was first selected as a metal-poor candidate from its narrowband S-PLUS photometry and followed up spectroscopically in medium resolution with Gemini-South/GMOS, which confirmed its low-metallicity status. High-resolution spectroscopy was gathered with GHOST at Gemini-South, allowing for the determination of the chemical abundances for 36 elements, from carbon to thorium. At [Fe/H] = -3.39, SPLUS J1424-2542 is one of the lowest-metallicity stars with measured Th and has the highest log is an element of(Th/Eu) observed to date, making it part of the "actinide-boost" category of r-process-enhanced stars. The analysis presented here suggests that the gas cloud from which SPLUS J1424-2542 formed must have been enriched by at least two progenitor populations. The light-element (Z <= 30) abundance pattern is consistent with the yields from a supernova explosion of metal-free stars with 11.3-13.4 M circle dot, and the heavy-element (Z >= 38) abundance pattern can be reproduced by the yields from a neutron star merger (1.66 M circle dot and 1.27 M circle dot) event. A kinematical analysis also reveals that SPLUS J1424-2542 is a low-mass, old halo star with a likely in situ origin, not associated with any known early merger events in the Milky Way.

Protein O-glycosylation is a nutrient signaling mechanism that plays an essential role in maintaining cellular homeostasis across different species. In plants, SPINDLY (SPY) and SECRET AGENT (SEC) posttranslationally modify hundreds of intracellular proteins with O-fucose and O-linked N-acetylglucosamine, respectively. SPY and SEC play overlapping roles in cellular regulation, and loss of both SPY and SEC causes embryo lethality in Arabidopsis (Arabidopsis thaliana). Using structure-based virtual screening of chemical libraries followed by in vitro and in planta assays, we identified a SPY O-fucosyltransferase inhibitor (SOFTI). Computational analyses predicted that SOFTI binds to the GDP-fucose-binding pocket of SPY and competitively inhibits GDP-fucose binding. In vitro assays confirmed that SOFTI interacts with SPY and inhibits its O-fucosyltransferase activity. Docking analysis identified additional SOFTI analogs that showed stronger inhibitory activities. SOFTI treatment of Arabidopsis seedlings decreased protein O-fucosylation and elicited phenotypes similar to the spy mutants, including early seed germination, increased root hair density, and defective sugar-dependent growth. In contrast, SOFTI did not visibly affect the spy mutant. Similarly, SOFTI inhibited the sugar-dependent growth of tomato (Solanum lycopersicum) seedlings. These results demonstrate that SOFTI is a specific SPY O-fucosyltransferase inhibitor that can be used as a chemical tool for functional studies of O-fucosylation and potentially for agricultural management.