Changed life course upon defective replication of ribosomal RNA genes.

Genome instability is a major cause of aging. In the budding yeast Saccharomyces cerevisiae, instability of the ribosomal RNA gene repeat (rDNA) is known to shorten replicative lifespan. In yeast, rDNA instability in an aging cell is associated with accumulation of extrachromosomal rDNA circles (ERCs) which titrate factors critical for lifespan maintenance. ERC accumulation is not detected in mammalian cells, where aging is linked to DNA damage. To distinguish effects of DNA damage from those of ERC accumulation on senescence, we re-analyzed a yeast strain with a replication initiation defect in the rDNA, which limits ERC multiplication. In aging cells of this strain (rARS-∆3) rDNA became unstable, as in wild-type cells, whereas significantly fewer ERCs accumulated. Single-cell aging analysis revealed that rARS-∆3 cells follow a linear survival curve and can have a wild-type replicative lifespan, although a fraction of the cells stopped dividing earlier than wild type. The doubling time of rARS-∆3 cells appears to increase in the final cell divisions. Our results suggest that senescence in rARS-∆3 is linked to the accumulation of DNA damage as in mammalian cells, rather than to elevated ERC level. Therefore, this strain should be a good model system to study ERC-independent aging.

Distinct mechanisms underlie H2O2 sensing in C. elegans head and tail.

Environmental oxidative stress threatens cellular integrity and should therefore be avoided by living organisms. Yet, relatively little is known about environmental oxidative stress perception. Here, using microfluidics, we showed that like I2 pharyngeal neurons, the tail phasmid PHA neurons function as oxidative stress sensing neurons in C. elegans, but display different responses to H2O2 and light. We uncovered that different but related receptors, GUR-3 and LITE-1, mediate H2O2 signaling in I2 and PHA neurons. Still, the peroxiredoxin PRDX-2 is essential for both, and might promote H2O2-mediated receptor activation. Our work demonstrates that C. elegans can sense a broad range of oxidative stressors using partially distinct H2O2 signaling pathways in head and tail sensillae, and paves the way for further understanding of how the integration of these inputs translates into the appropriate behavior.

DetecDiv, a generalist deep-learning platform for automated cell division tracking and survival analysis.

Automating the extraction of meaningful temporal information from sequences of microscopy images represents a major challenge to characterize dynamical biological processes. So far, strong limitations in the ability to quantitatively analyze single-cell trajectories have prevented large-scale investigations to assess the dynamics of entry into replicative senescence in yeast. Here, we have developed DetecDiv, a microfluidic-based image acquisition platform combined with deep learning-based software for high-throughput single-cell division tracking. We show that DetecDiv can automatically reconstruct cellular replicative lifespans with high accuracy and performs similarly with various imaging platforms and geometries of microfluidic traps. In addition, this methodology provides comprehensive temporal cellular metrics using time-series classification and image semantic segmentation. Last, we show that this method can be further applied to automatically quantify the dynamics of cellular adaptation and real-time cell survival upon exposure to environmental stress. Hence, this methodology provides an all-in-one toolbox for high-throughput phenotyping for cell cycle, stress response, and replicative lifespan assays.

A Microfluidic Platform for Tracking Individual Cell Dynamics during an Unperturbed Nutrients Exhaustion.

Microorganisms have evolved adaptive strategies to respond to the autonomous degradation of their environment. Indeed, a growing culture progressively exhausts nutrients from its media and modifies its composition. Yet, how single cells react to these modifications remains difficult to study since it requires population-scale growth experiments to allow cell proliferation to have a collective impact on the environment, while monitoring the same individuals exposed to this environment for days. For this purpose, we have previously described an integrated microfluidic pipeline, based on continuous separation of the cells from the media and subsequent perfusion of the filtered media in an observation chamber containing isolated single cells. Here, we provide a detailed protocol to implement this methodology, including the setting up of the microfluidic system and the processing of timelapse images.

DNA circles promote yeast ageing in part through stimulating the reorganization of nuclear pore complexes.

The nuclear pore complex (NPC) mediates nearly all exchanges between nucleus and cytoplasm, and in many species, it changes composition as the organism ages. However, how these changes arise and whether they contribute themselves to ageing is poorly understood. We show that SAGA-dependent attachment of DNA circles to NPCs in replicatively ageing yeast cells causes NPCs to lose their nuclear basket and cytoplasmic complexes. These NPCs were not recognized as defective by the NPC quality control machinery (SINC) and not targeted by ESCRTs. They interacted normally or more effectively with protein import and export factors but specifically lost mRNA export factors. Acetylation of Nup60 drove the displacement of basket and cytoplasmic complexes from circle-bound NPCs. Mutations preventing this remodeling extended the replicative lifespan of the cells. Thus, our data suggest that the anchorage of accumulating circles locks NPCs in a specialized state and that this process is intrinsically linked to the mechanisms by which ERCs promote ageing.

Monitoring single-cell dynamics of entry into quiescence during an unperturbed life cycle.

The life cycle of microorganisms is associated with dynamic metabolic transitions and complex cellular responses. In yeast, how metabolic signals control the progressive choreography of structural reorganizations observed in quiescent cells during a natural life cycle remains unclear. We have developed an integrated microfluidic device to address this question, enabling continuous single-cell tracking in a batch culture experiencing unperturbed nutrient exhaustion to unravel the coordination between metabolic and structural transitions within cells. Our technique reveals an abrupt fate divergence in the population, whereby a fraction of cells is unable to transition to respiratory metabolism and undergoes a reversible entry into a quiescence-like state leading to premature cell death. Further observations reveal that nonmonotonous internal pH fluctuations in respiration-competent cells orchestrate the successive waves of protein superassemblies formation that accompany the entry into a bona fide quiescent state. This ultimately leads to an abrupt cytosolic glass transition that occurs stochastically long after proliferation cessation. This new experimental framework provides a unique way to track single-cell fate dynamics over a long timescale in a population of cells that continuously modify their ecological niche.

Self-Learning Microfluidic Platform for Single-Cell Imaging and Classification in Flow.

Single-cell analysis commonly requires the confinement of cell suspensions in an analysis chamber or the precise positioning of single cells in small channels. Hydrodynamic flow focusing has been broadly utilized to achieve stream confinement in microchannels for such applications. As imaging flow cytometry gains popularity, the need for imaging-compatible microfluidic devices that allow for precise confinement of single cells in small volumes becomes increasingly important. At the same time, high-throughput single-cell imaging of cell populations produces vast amounts of complex data, which gives rise to the need for versatile algorithms for image analysis. In this work, we present a microfluidics-based platform for single-cell imaging in-flow and subsequent image analysis using variational autoencoders for unsupervised characterization of cellular mixtures. We use simple and robust Y-shaped microfluidic devices and demonstrate precise 3D particle confinement towards the microscope slide for high-resolution imaging. To demonstrate applicability, we use these devices to confine heterogeneous mixtures of yeast species, brightfield-image them in-flow and demonstrate fully unsupervised, as well as few-shot classification of single-cell images with 88% accuracy.