Cardiomyocyte hypertrophy and apoptosis underlie cardiomyopathies and heart failure. While previous studies have reported both hypertrophy and apoptosis at the population level, how individual cells commit to these distinct analog and digital fates is unclear. To elucidate how individual cells decide to grow and/or die, we developed a high-content microscopy approach to track single-cell dynamics of neonatal rat cardiomyocytes. Even untreated cells exhibited substantial single-cell variability in growth and death. Uniform treatments of staurosporine or phenylephrine induced distinctive morphological programs resulting in apoptosis and hypertrophy, respectively, but only in cell subpopulations. Increasing concentrations of the β-adrenergic receptor agonist isoproterenol caused a population-level biphasic induction of hypertrophy and then apoptosis, consistent with either apoptosis in the most hypertrophic cells (a grow-and-die model) or an early decision between hypertrophy and delayed apoptosis (a grow-or-die model). By tracking single-cell fates, we found that when stressed with either isoproterenol or phenylephrine, individual cells that hypertrophy are protected from later apoptosis. Further, caspase 3 inhibition shifted the single-cell probability from apoptosis to hypertrophy fates. Machine learning models found that a cell's initial size and DNA content or condensation could predict a cell's bias for hypertrophy or apoptosis. Together, these data support a grow-or-die conceptual model for cardiomyocyte decisions. This single-cell profiling method for tracking joint analog-digital cell decisions reveals that despite hypertrophy and apoptosis co-occurring at the population level, individual cardiomyocytes decide early whether to grow or die.
The epitranscriptome embodies many new and largely unexplored functions of RNA. A significant roadblock hindering progress in epitranscriptomics is the identification of more than one modification in individual transcript molecules. We address this with CHEUI (CH3 (methylation) Estimation Using Ionic current). CHEUI predicts N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual molecules from the same sample, the stoichiometry at transcript reference sites, and differential methylation between any two conditions. CHEUI processes observed and expected nanopore direct RNA sequencing signals to achieve high single-molecule, transcript-site, and stoichiometry accuracies in multiple tests using synthetic RNA standards and cell line data. CHEUI’s capability to identify two modification types in the same sample reveals a co-occurrence of m6A and m5C in individual mRNAs in cell line and tissue transcriptomes. CHEUI provides new avenues to discover and study the function of the epitranscriptome.
Species distribution models (SDMs) are widely used to gain ecological understanding and guide conservation decisions. These models are developed with a wide variety of algorithms – from statistic-based approaches to machine learning approaches – but a requirement almost all share is the use of predictor variables that strongly simplify the temporal variability of driving factors. Conversely, novel architectures of deep learning neural networks allow dealing with fully explicit spatiotemporal dynamics and thus fitting SDMs without the need to simplify the temporal and spatial dimension of predictor data. We present and demonstrate a deep learning based SDM approach that uses time series of spatial data as predictors using distribution data for 74 species from a well-established benchmark dataset. The deep learning approach provided consistently accurate models, directly using time series of predictor data and thus avoiding the use of pre-processed predictor sets that can obscure relevant aspects of environmental variation.
Primordial follicles are quiescent ovarian structures comprised of a single oocyte surrounded by a layer of somatic supporting pregranulosa cells. Primordial follicle activation is the first step towards oocyte maturation and, ultimately, ovulation. As there is a finite number of primordial follicles within the ovary, their rate of activation is a critical parameter of the female reproductive lifespan. Follicle activation is characterised by morphological and molecular changes in both pregranulosa cells and oocytes. However, the signal initiating activation, and even the cell-type responding to this signal, remain unidentified. Through single-cell transcriptomic profiling of neonatal mouse ovaries we identify a putative gene expression signature of activating pregranulosa cells. We find precocious expression of this putative pregranulosa cell signature in the Cdkn1b-/- or p27kip1-null model, which has ubiquitous follicle activation neonatally. We confirm that the protein product of one of these genes, Tnni3, is present within mouse granulosa cells, which has also been described recently for human granulosa cells. We demonstrate that expression of cardiac troponin I (TNNI3), an actin-binding protein, is upregulated upon cell-cycle resumption in activating pregranulosa cells. This indicates pregranulosa cells likely initiate primordial follicle activation and support the broader hypothesis that changes in cell tension are involved in triggering follicle activation.
To maintain CO2 fixation in the Calvin Benson-Bassham cycle, multi-step regulation of the chloroplast ATP synthase (CF1Fo) is crucial to balance the ATP output of photosynthesis with protection of the apparatus. A well-studied mechanism is thiol modulation; a light/dark regulation through reversible cleavage of a disulfide in the CF1Fo γ-subunit. The disulfide hampers ATP synthesis and hydrolysis reactions in dark-adapted CF1Fo from land plants by increasing the required transmembrane electrochemical proton gradient . Here, we show in Chlamydomonas reinhardtii that algal CF1Fo is differently regulated in vivo. A specific hairpin structure in the γ-subunit redox domain disconnects activity regulation from disulfide formation in the dark. Electrochromic shift measurements suggested that the hairpin kept wild type CF1Fo active whereas the enzyme was switched off in algal mutant cells expressing a plant-like hairpin structure. The hairpin segment swap resulted in an elevated threshold to activate plant-like CF1Fo, increased by ∼1.4 photosystem (PS) I charge separations. The resulting dark-equilibrated dropped in the mutants by ∼2.7 PSI charge separation equivalents. Photobioreactor experiments showed no phenotypes in autotrophic aerated mutant cultures. In contrast, chlorophyll fluorescence measurements under heterotrophic dark conditions point to a reduced plastoquinone pool in cells with the plant-like CF1Fo as the result of bioenergetic bottlenecks. Our results suggest that the lifestyle of Chlamydomonas reinhardtii requires a specific CF1Fo dark regulation that partakes in metabolic coupling between the chloroplast and acetate-fueled mitochondria. Significance Statement The microalga Chlamydomonas reinhardtii exhibits a non-classical thiol modulation of the chloroplast ATP synthase for the sake of metabolic flexibility. The redox switch, although established, was functionally disconnected in vivo thanks to a hairpin segment in the γ-subunit redox domain. Dark enzymatic activity was prevented by replacing the algal hairpin segment with the one from land plants, restoring a classical thiol modulation pattern. Thereby, ATP was saved at the expense of thylakoid membrane energization levels in the dark. However, metabolism was impaired upon silencing dark ATPase activity, indicating that a functional disconnect from the redox switch represents an adaptation to different ecological niches.
