High-throughput analysis of yeast replicative aging using a microfluidic system

Yeast EndoG prevents genome instability by degrading extranuclear DNA species

In metazoans mitochondrial DNA (mtDNA) or retrotransposon cDNA released to cytoplasm are degraded by nucleases to prevent sterile inflammation. It remains unknown whether degradation of these DNA also prevents nuclear genome instability. We used an amplicon sequencing-based method in yeast enabling analysis of millions of DSB repair products. In non-dividing stationary phase cells, Pol4-mediated non-homologous end-joining increases, resulting in frequent insertions of 1-3 nucleotides, and insertions of mtDNA (NUMTs) or retrotransposon cDNA. Yeast EndoG (Nuc1) nuclease limits insertion of cDNA and transfer of very long mtDNA ( >10 kb) to the nucleus, where it forms unstable circles, while promoting the formation of short NUMTs (~45-200 bp). Nuc1 also regulates transfer of extranuclear DNA to nucleus in aging or meiosis. We propose that Nuc1 preserves genome stability by degrading retrotransposon cDNA and long mtDNA, while short NUMTs originate from incompletely degraded mtDNA. This work suggests that nucleases eliminating extranuclear DNA preserve genome stability.

Capturing of extracellular vesicles derived from single cells of Escherichia coli

Bacteria secrete extracellular vesicles (EVs), also referred to as bacterial membrane vesicles, which carry, among other compounds, lipids, nucleic acids and virulence factors. Recent studies highlight the role of EVs in the emergence of antibiotic resistance, e.g. as carrier and absorbent particles of the drug to protect the cells, or as a pathway to disseminate resistance elements. In this study, we are interested in characterizing the secretion of EVs at the single bacterial level to ultimately understand how cells respond to antibiotic treatment. We introduce a microfluidic device that enables culture of single bacterial cells and capture of EVs secreted from these individuals. The device incorporates parallel, narrow winding channels to trap single rod-shaped E. coli cells at their entrances. The daughter cells are immediately removed by continuous flow on the open side of the trap, so that the trap contains always only a single cell. Cells grew in these traps over 24 h with a doubling time of 25 minutes. Under antibiotic treatment, the doubling time did not change, but we observed small changes in the cell length of the trapped cells (decrease from 4.0 μm to 3.6 μm for 0 and 250 ng mL-1 polymyxin B, respectively), and cells stopped growing within hours, depending on the drug concentration. Compared to bulk culture, the results indicate a higher susceptibility of on-chip-cultured cells (250 ng mL-1vs. >500 ng mL-1 in bulk), which may be caused, among other reasons, by the space limitation in the cell trap and shear forces. During the culture, EVs secreted by the trapped cells entered the winding channel. We developed a procedure to selectively coat these channels with poly-L-lysine resulting in a positively charged surface, which enabled electrostatic capture of negatively charged EVs. Subsequently, the immobilized EVs were stained with a lipophilic dye and detected by fluorescence microscopy. Our findings confirm large variations of EV secretion among individual bacteria and indicate a relative high rate of EV secretion under antibiotic treatment. The proposed method can be extended to the detection of other secreted substances of interest and may facilitate the elucidation of unknown heterogeneities in bacteria.

A computer vision and residual neural network (ResNet) combined method for automated and accurate yeast replicative aging analysis of high-throughput microfluidic single-cell images

With the rapid development of microfluidic platforms in high-throughput single-cell culturing, laborious operation to manipulate massive budding yeast cells (Saccharomyces cerevisiae) in replicative aging studies has been greatly simplified and automated. As a result, large datasets of microscopy images bring challenges to fast and accurately determine yeast replicative lifespan (RLS), which is the most important parameter to study cell aging. Based on our microfluidic diploid yeast long-term culturing (DYLC) chip that features 1100 traps to immobilize single cells and record their proliferation and aging via time-lapse imaging, herein, a dedicated algorithm combined with computer vision and residual neural network (ResNet) was presented to efficiently process tremendous micrographs in a high-throughput and automated manner. The image-processing algorithm includes following pivotal steps: (i) segmenting multi-trap micrographs into time-lapse single-trap sub-images, (ii) labeling 8 yeast budding features and training the 18-layer ResNet, (iii) converting the ResNet predictions in analog values into digital signals, (iv) recognizing cell dynamic events, and (v) determining yeast RLS and budding time interval (BTI) ultimately. The ResNet algorithm achieved high F1 scores (over 92%) demonstrating the effectiveness and accuracy in the recognition of yeast budding events, such as bud appearance, daughter dissection and cell death. Therefore, the results conduct that similar deep learning algorithms could be tailored to analyze high-throughput microscopy images and extract multiple cell behaviors in microfluidic single-cell analysis.

Yeast EndoG prevents genome instability by degrading cytoplasmic DNA

In metazoans release of mitochondrial DNA or retrotransposon cDNA to cytoplasm can cause sterile inflammation and disease 1. Cytoplasmic nucleases degrade these DNA species to limit inflammation 2,3. It remains unknown whether degradation these DNA also prevents nuclear genome instability. To address this question, we decided to identify the nuclease regulating transfer of these cytoplasmic DNA species to the nucleus. We used an amplicon sequencing-based method in yeast enabling analysis of millions of DSB repair products. Nuclear mtDNA (NUMTs) and retrotransposon cDNA insertions increase dramatically in nondividing stationary phase cells. Yeast EndoG (Nuc1) nuclease limits insertions of cDNA and transfer of very long mtDNA (>10 kb) that forms unstable circles or rarely insert in the genome, but it promotes formation of short NUMTs (~45-200 bp). Nuc1 also regulates transfer of cytoplasmic DNA to nucleus in aging or during meiosis. We propose that Nuc1 preserves genome stability by degrading retrotransposon cDNA and long mtDNA, while short NUMTs can originate from incompletely degraded mtDNA. This work suggests that nucleases eliminating cytoplasmic DNA play a role in preserving genome stability.

Measuring Replicative Lifespan in Cryptococcus neoformans

Advances in understanding cellular aging research have been possible due to the analysis of the replicative lifespan of yeast cells. Studying longevity in the pathogenic yeast Cryptococcus neoformans is essential because old yeast cells with age-related phenotypes accumulate during infection and are associated with increased virulence and antifungal tolerance. Microdissection and microfluidic devices are valuable tools for continuously tracking cells at the single-cell level. In this chapter, we describe the features of these two platforms and outline technical limitations and information to study aging mechanisms while assessing the lifespan of yeast cells.

Yeast EndoG prevents genome instability by degrading cytoplasmic DNA

In metazoans release of mitochondrial DNA or retrotransposon cDNA to cytoplasm can cause sterile inflammation and disease. Cytoplasmic nucleases degrade these DNA species to limit inflammation. It remains unknown whether degradation these DNA also prevents nuclear genome instability. To address this question, we decided to identify the nuclease regulating transfer of these cytoplasmic DNA species to the nucleus. We used an amplicon sequencing-based method in yeast enabling analysis of millions of DSB repair products. Nu clear mt DNA (NUMTs) and retrotransposon cDNA insertions increase dramatically in nondividing stationary phase cells. Yeast EndoG (Nuc1) nuclease limits insertions of cDNA and transfer of very long mtDNA (>10 kb) that forms unstable circles or rarely insert in the genome, but it promotes formation of short NUMTs (∼45-200 bp). Nuc1 also regulates transfer of cytoplasmic DNA to nucleus in aging or during meiosis. We propose that Nuc1 preserves genome stability by degrading retrotransposon cDNA and long mtDNA, while short NUMTs can originate from incompletely degraded mtDNA. This work suggests that nucleases eliminating cytoplasmic DNA play a role in preserving genome stability.

Sis2 regulates yeast replicative lifespan in a dose-dependent manner

Application of microfluidic platforms facilitated high-precision measurements of yeast replicative lifespan (RLS); however, comparative quantification of lifespan across strain libraries has been missing. Here we microfluidically measure the RLS of 307 yeast strains, each deleted for a single gene. Despite previous reports of extended lifespan in these strains, we found that 56% of them did not actually live longer than the wild-type; while the remaining 44% showed extended lifespans, the degree of extension was often different from what was previously reported. Deletion of SIS2 gene led to the largest RLS increase observed. Sis2 regulated yeast lifespan in a dose-dependent manner, implying a role for the coenzyme A biosynthesis pathway in lifespan regulation. Introduction of the human PPCDC gene in the sis2Δ background neutralized the lifespan extension. RNA-seq experiments revealed transcriptional increases in cell-cycle machinery components in sis2Δ background. High-precision lifespan measurement will be essential to elucidate the gene network governing lifespan.

Abruptly Autofocusing Vortex Beams for Rapid Controllable Femtosecond Two-Photon Polymerization

Micro-fabrication based on structured-beam-assisted Two-Photon Polymerization (2 PP) provides a rapid and flexible method for the manufacture of microstructures with complex morphologies. The tunable Abruptly Autofocusing Vortex (AAFV) beams were designed theoretically and generated experimentally based on a single-phase-only Spatial Light Modulator (SLM). Their specific spatial intensity distributions were further utilized to assist the fabrication of a bowl-shaped Three-Dimensional (3D) micro-trap array via 2 PP with a one-step exposure technique. Finally, the fabricated microstructures act as a novel tool for the trapping and spatial positioning of micro-particles with different diameters, which shows potential applications in fiber optics and cell study.

Identification and Elimination of Antifungal Tolerance in Candida auris

Antimicrobial resistance is a global health crisis to which pathogenic fungi make a substantial contribution. The human fungal pathogen C. auris is of particular concern due to its rapid spread across the world and its evolution of multidrug resistance. Fluconazole failure in C. auris has been recently attributed to antifungal “tolerance”. Tolerance is a phenomenon whereby a slow-growing subpopulation of tolerant cells, which are genetically identical to susceptible cells, emerges during drug treatment. We use microbroth dilution and disk diffusion assays, together with image analysis, to investigate antifungal tolerance in C. auris to all three classes of antifungal drugs used to treat invasive candidiasis. We find that (1) C. auris is tolerant to several common fungistatic and fungicidal drugs, which in some cases can be detected after 24 h, as well as after 48 h, of antifungal drug exposure; (2) the tolerant phenotype reverts to the susceptible phenotype in C. auris; and (3) combining azole, polyene, and echinocandin antifungal drugs with the adjuvant chloroquine in some cases reduces or eliminates tolerance and resistance in patient-derived C. auris isolates. These results suggest that tolerance contributes to treatment failure in C. auris infections for a broad range of antifungal drugs, and that antifungal adjuvants may improve treatment outcomes for patients infected with antifungal-tolerant or antifungal-resistant fungal pathogens.

Time-resolved microfluidics unravels individual cellular fates during double-strand break repair

BACKGROUND

Double-strand break repair (DSBR) is a highly regulated process involving dozens of proteins acting in a defined order to repair a DNA lesion that is fatal for any living cell. Model organisms such as Saccharomyces cerevisiae have been used to study the mechanisms underlying DSBR, including factors influencing its efficiency such as the presence of distinct combinations of microsatellites and endonucleases, mainly by bulk analysis of millions of cells undergoing repair of a broken chromosome. Here, we use a microfluidic device to demonstrate in yeast that DSBR may be studied at a single-cell level in a time-resolved manner, on a large number of independent lineages undergoing repair.

RESULTS

We used engineered S. cerevisiae cells in which GFP is expressed following the successful repair of a DSB induced by Cas9 or Cpf1 endonucleases, and different genetic backgrounds were screened to detect key events leading to the DSBR efficiency. Per condition, the progenies of 80-150 individual cells were analyzed over 24 h. The observed DSBR dynamics, which revealed heterogeneity of individual cell fates and their contributions to global repair efficacy, was confronted with a coupled differential equation model to obtain repair process rates. Good agreement was found between the mathematical model and experimental results at different scales, and quantitative comparisons of the different experimental conditions with image analysis of cell shape enabled the identification of three types of DSB repair events previously not recognized: high-efficacy error-free, low-efficacy error-free, and low-efficacy error-prone repair.

CONCLUSIONS

Our analysis paves the way to a significant advance in understanding the complex molecular mechanism of DSB repair, with potential implications beyond yeast cell biology. This multiscale and multidisciplinary approach more generally allows unique insights into the relation between in vivo microscopic processes within each cell and their impact on the population dynamics, which were inaccessible by previous approaches using molecular genetics tools alone.

Cell pairing for biological analysis in microfluidic devices

Cell pairing at the single-cell level usually allows a few cells to contact or seal in a single chamber and provides high-resolution imaging. It is pivotal for biological research, including understanding basic cell functions, creating cancer treatment technologies, developing drugs, and more. Laboratory chips based on microfluidics have been widely used to trap, immobilize, and analyze cells due to their high efficiency, high throughput, and good biocompatibility properties. Cell pairing technology in microfluidic devices provides spatiotemporal research on cellular interactions and a highly controlled approach for cell heterogeneity studies. In the last few decades, many researchers have emphasized cell pairing research based on microfluidics. They designed various microfluidic device structures for different biological applications. Herein, we describe the current physical methods of microfluidic devices to trap cell pairs. We emphatically summarize the practical applications of cell pairing in microfluidic devices, including cell fusion, cell immunity, gap junction intercellular communication, cell co-culture, and other applications. Finally, we review the advances and existing challenges of the presented devices and then discuss the possible development directions to promote medical and biological research.

Measurement and Characterization of Yeast Cell Size Using a Digital Optical Microscope

Yeast produces flavor components as by-products of fermentation. Such components, which account for considerable yeast quality value, may influence cell membrane fluidity and regulate cell size. In this study, yeast cell size was measured using various methods, and cell sizes were characterized for each strain of yeast. Herein, a method for measuring the cell size and automatically acquiring the cell area was proposed using inexpensive methylene blue staining and a versatile digital microscope to automatically acquire the cell area. To evaluate the efficiency, data on cell length and area were compared using the conventional and proposed methods. Additionally, the advantages of automated measurement and the ability to count cell numbers in the future are discussed through the acquisition of cell size data, which would be required for microfabrication and cell fabrication techniques. Although there are various candidate methods for evaluating the properties of each yeast strain, the present technique may be useful for evaluating the productivity of flavor components and selecting a yeast strain for producing food and drink products with high commodity values.

Microfluidics for long-term single-cell time-lapse microscopy: Advances and applications

Cells are inherently dynamic, whether they are responding to environmental conditions or simply at equilibrium, with biomolecules constantly being made and destroyed. Due to their small volumes, the chemical reactions inside cells are stochastic, such that genetically identical cells display heterogeneous behaviors and gene expression profiles. Studying these dynamic processes is challenging, but the development of microfluidic methods enabling the tracking of individual prokaryotic cells with microscopy over long time periods under controlled growth conditions has led to many discoveries. This review focuses on the recent developments of one such microfluidic device nicknamed the mother machine. We overview the original device design, experimental setup, and challenges associated with this platform. We then describe recent methods for analyzing experiments using automated image segmentation and tracking. We further discuss modifications to the experimental setup that allow for time-varying environmental control, replicating batch culture conditions, cell screening based on their dynamic behaviors, and to accommodate a variety of microbial species. Finally, this review highlights the discoveries enabled by this technology in diverse fields, such as cell-size control, genetic mutations, cellular aging, and synthetic biology.

Fungi-on-a-Chip: microfluidic platforms for single-cell studies on fungi

This review highlights new advances in the emerging field of 'Fungi-on-a-Chip' microfluidics for single-cell studies on fungi and discusses several future frontiers, where we envisage microfluidic technology development to be instrumental in aiding our understanding of fungal biology. Fungi, with their enormous diversity, bear essential roles both in nature and our everyday lives. They inhabit a range of ecosystems, such as soil, where they are involved in organic matter degradation and bioremediation processes. More recently, fungi have been recognized as key components of the microbiome in other eukaryotes, such as humans, where they play a fundamental role not only in human pathogenesis, but also likely as commensals. In the food sector, fungi are used either directly or as fermenting agents and are often key players in the biotechnological industry, where they are responsible for the production of both bulk chemicals and antibiotics. Although the macroscopic fruiting bodies are immediately recognizable by most observers, the structure, function, and interactions of fungi with other microbes at the microscopic scale still remain largely hidden. Herein, we shed light on new advances in the emerging field of Fungi-on-a-Chip microfluidic technologies for single-cell studies on fungi. We discuss the development and application of microfluidic tools in the fields of medicine and biotechnology, as well as in-depth biological studies having significance for ecology and general natural processes. Finally, a future perspective is provided, highlighting new frontiers in which microfluidic technology can benefit this field.

Non-genetic resistance facilitates survival while hindering the evolution of drug resistance due to intraspecific competition

Rising rates of resistance to antimicrobial drugs threaten the effective treatment of infections across the globe. Drug resistance has been established to emerge from non-genetic mechanisms as well as from genetic mechanisms. However, it is still unclear how non-genetic resistance affects the evolution of genetic drug resistance. We develop deterministic and stochastic population models that incorporate resource competition to quantitatively investigate the transition from non-genetic to genetic resistance during the exposure to static and cidal drugs. We find that non-genetic resistance facilitates the survival of cell populations during drug treatment while hindering the development of genetic resistance due to competition between the non-genetically and genetically resistant subpopulations. Non-genetic resistance in the presence of subpopulation competition increases the fixation times of drug resistance mutations, while increasing the probability of mutation before population extinction during cidal drug treatment. Intense intraspecific competition during drug treatment leads to extinction of susceptible and non-genetically resistant subpopulations. Alternating between drug and no drug conditions results in oscillatory population dynamics, increased resistance mutation fixation timescales, and reduced population survival. These findings advance our fundamental understanding of the evolution of resistance and may guide novel treatment strategies for patients with drug-resistant infections.

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.

Microfluidic chip for precise trapping of single cells and temporal analysis of signaling dynamics

Microfluidic designs are versatile examples of technology miniaturisation that find their applications in various cell biology research, especially to investigate the influence of environmental signals on cellular response dynamics. Multicellular systems operate in intricate cellular microenvironments where environmental signals govern well-orchestrated and robust responses, the understanding of which can be realized with integrated microfluidic systems. In this study, we present a fully automated and integrated microfluidic chip that can deliver input signals to single and isolated suspension or adherent cells in a precisely controlled manner. In respective analyses of different single cell types, we observe, in real-time, the temporal dynamics of caspase 3 activation during DMSO-induced apoptosis in single cancer cells (K562) and the translocation of STAT-1 triggered by interferon γ (IFNγ) in single fibroblasts (NIH3T3). Our investigations establish the employment of our versatile microfluidic system in probing temporal single cell signaling networks where alternations in outputs uncover signal processing mechanisms.

Nidhi Sinha, Haowen Yang and colleagues report a microfluidic large-scale integration chip to probe temporal single-cell signalling networks via the delivery of patterns of input signalling molecules. The researchers use their device to investigate drug-induced cancer cell apoptosis and single cell transcription (STAT-1) protein signalling dynamics.

Single-cell stable isotope probing in microbial ecology

Environmental and host-associated microbiomes are typically diverse assemblages of organisms performing myriad activities and engaging in a network of interactions that play out in spatially structured contexts. As the sum of these activities and interactions give rise to overall microbiome function, with important consequences for environmental processes and human health, elucidating specific microbial activities within complex communities is a pressing challenge. Single-cell stable isotope probing (SC-SIP) encompasses multiple techniques that typically utilize Raman microspectroscopy or nanoscale secondary ion mass spectrometry (NanoSIMS) to enable spatially resolved tracking of isotope tracers in cells, cellular components, and metabolites. SC-SIP techniques are uniquely suited for illuminating single-cell activities in microbial communities and for testing hypotheses about cellular functions generated for example from meta-omics datasets. Here, we illustrate the insights enabled by SC-SIP techniques by reviewing selected applications in microbiology and offer a perspective on their potential for future research.

Oridonin Delays Aging Through the AKT Signaling Pathway

Aging is a major risk factor for chronic diseases and disability in humans. Nowadays, no effective anti-aging treatment is available clinically. In this study, oridonin was selected based on the drug screening strategy similar to Connectivity MAP (CMAP) but upon transcriptomes of 102 traditional Chinese medicines treated cell lines. Oridonin is a diterpenoid isolated from Rabdosia rubescens. As reported, Oridonin exhibits a variety of pharmacological activities, including antitumor, antibacterial and anti-inflammatory activities. Here, we found that oridonin inhibited cellular senescence in human diploid fibroblasts (2BS and WI-38), manifested by decreased senescence-associated β-galactosidase (SA-β-gal) staining. Compared with the elderly control group, the positive cell rate in the oridonin intervention group was reduced to 48.5%. Notably, oridonin prolonged the lifespan of yeast by 48.9%, and extended the average life span of naturally aged mice by 21.6%. Our mice behavior experiments exhibited that oridonin significantly improved the health status of naturally aged mice. In addition, oridonin also delayed doxorubicin-induced cellular senescence and mouse senescence. Compared with the model group, the percentage of SA-β-gal positive cells in the oridonin treatment group was reduced to 59.8%. It extended the average lifespan of mice by 53.8% and improved healthspan. Mechanistically, we showed that oridonin delayed aging through the AKT signaling pathway and reversed the genetic changes caused by doxorubicin-induced cell senescence. Therefore, oridonin is a potential candidate for the development of anti-aging drugs.

Synthetic condensate size correlates with yeast replicative cell age

Yeast divides asymmetrically, with an aging mother cell and a 'rejuvenated' daughter cell, and serves as a model organism for studying aging. At the same time, determining the age of yeast cells is technically challenging, requiring complex experimental setups or genetic strategies. We developed a synthetic system composed of two interacting oligomers, which forms condensates in living yeast cells. Here, we report that these synthetic condensates' size correlates with yeast replicative age, making these condensates age reporters for this model organism.

Phenomics approaches to understand genetic networks and gene function in yeast

Over the past decade, major efforts have been made to systematically survey the characteristics or phenotypes associated with genetic variation in a variety of model systems. These so-called phenomics projects involve the measurement of 'phenomes', or the set of phenotypic information that describes an organism or cell, in various genetic contexts or states, and in response to external factors, such as environmental signals. Our understanding of the phenome of an organism depends on the availability of reagents that enable systematic evaluation of the spectrum of possible phenotypic variation and the types of measurements that can be taken. Here, we highlight phenomics studies that use the budding yeast, a pioneer model organism for functional genomics research. We focus on genetic perturbation screens designed to explore genetic interactions, using a variety of phenotypic read-outs, from cell growth to subcellular morphology.

rDNA array length is a major determinant of replicative lifespan in budding yeast

The complex processes and interactions that regulate aging and determine lifespan are not fully defined for any organism. Here, taking advantage of recent technological advances in studying aging in budding yeast, we discovered a previously unappreciated relationship between the number of copies of the ribosomal RNA gene present in its chromosomal array and replicative lifespan (RLS). Specifically, the chromosomal ribosomal DNA (rDNA) copy number (rDNA CN) positively correlated with RLS and this interaction explained over 70% of variability in RLS among a series of wild-type strains. In strains with low rDNA CN, SIR2 expression was attenuated and extrachromosomal rDNA circle (ERC) accumulation was increased, leading to shorter lifespan. Suppressing ERC formation by deletion of FOB1 eliminated the relationship between rDNA CN and RLS. These data suggest that previously identified rDNA CN regulatory mechanisms limit lifespan. Importantly, the RLSs of reported lifespan-enhancing mutations were significantly impacted by rDNA CN, suggesting that changes in rDNA CN might explain the magnitude of some of those reported effects. We propose that because rDNA CN is modulated by environmental, genetic, and stochastic factors, considering rDNA CN is a prerequisite for accurate interpretation of lifespan data.

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.

A high-throughput microfluidic diploid yeast long-term culturing (DYLC) chip capable of bud reorientation and concerted daughter dissection for replicative lifespan determination

Background

Budding yeast, Saccharomyces cerevisiae, has been extensively favored as a model organism in aging and age-related studies, thanks to versatile microfluidic chips for cell dynamics assay and replicative lifespan (RLS) determination at single-cell resolution. However, previous microfluidic structures aiming to immobilize haploid yeast may impose excessive spatial constraint and mechanical stress on cells, especially for larger diploid cells that sprout in a bipolar pattern.

Results

We developed a high-throughput microfluidic chip for diploid yeast long-term culturing (DYLC), optical inspection and cell-aging analysis. The DYLC chip features 1100 “leaky bowl”-shaped traps formatted in an array to dock single cells under laminar-perfused medium and effectively remove daughter cells by hydraulic shear forces. The delicate microstructures of cell traps enable hydrodynamic rotation of newborn buds, so as to ensure bud reorientation towards downstream and concerted daughter dissection thereafter. The traps provide sufficient space for cell-volume enlargement during aging, and thus properly alleviate structural compression and external stress on budding yeast. Trapping efficiency and long-term maintenance of single cells were optimized according to computational fluid dynamics simulations and experimental characterization in terms of critical parameters of the trap and array geometries. Owing to the self-filling of daughter cells dissected from traps upstream, an initial trapping efficiency of about 70% can rapidly reach a high value of over 92% after 4-hour cell culturing. During yeast proliferation and aging, cellular processes of growth, budding and daughter dissection were continuously tracked for over 60 h by time-lapse imaging. Yeast RLS and budding time interval (BTI) were directly calculated by the sequential two-digit codes indicating the budding status in images. With the employed diploid yeast strain, we obtained an RLS of 24.29 ± 3.65 generations, and verified the extension of BTI in the first couple of generations after birth and the last several generations approaching death, as well as cell de-synchronization along diploid yeast aging.

Conclusions

The DYLC chip offers a promising platform for reliable capture and culturing of diploid yeast cells and for life-long tracking of cell dynamics and replicative aging processes so that grasping comprehensive insights of aging mechanism in complex eukaryotic cells.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12951-022-01379-9.

The role of NAD and NAD precursors on longevity and lifespan modulation in the budding yeast, Saccharomyces cerevisiae

Molecular causes of aging and longevity interventions have witnessed an upsurge in the last decade. The resurgent interests in the application of small molecules as potential geroprotectors and/or pharmacogenomics point to nicotinamide adenine dinucleotide (NAD) and its precursors, nicotinamide riboside, nicotinamide mononucleotide, nicotinamide, and nicotinic acid as potentially intriguing molecules. Upon supplementation, these compounds have shown to ameliorate aging related conditions and possibly prevent death in model organisms. Besides being a molecule essential in all living cells, our understanding of the mechanism of NAD metabolism and its regulation remain incomplete owing to its omnipresent nature. Here we discuss recent advances and techniques in the study of chronological lifespan (CLS) and replicative lifespan (RLS) in the model unicellular organism Saccharomyces cerevisiae. We then follow with the mechanism and biology of NAD precursors and their roles in aging and longevity. Finally, we review potential biotechnological applications through engineering of microbial lifespan, and laid perspective on the promising candidature of alternative redox compounds for extending lifespan.

Microfluidic Surgery in Single Cells and Multicellular Systems

Microscale surgery on single cells and small organisms has enabled major advances in fundamental biology and in engineering biological systems. Examples of applications range from wound healing and regeneration studies to the generation of hybridoma to produce monoclonal antibodies. Even today, these surgical operations are often performed manually, but they are labor intensive and lack reproducibility. Microfluidics has emerged as a powerful technology to control and manipulate cells and multicellular systems at the micro- and nanoscale with high precision. Here, we review the physical and chemical mechanisms of microscale surgery and the corresponding design principles, applications, and implementations in microfluidic systems. We consider four types of surgical operations: (1) sectioning, which splits a biological entity into multiple parts, (2) ablation, which destroys part of an entity, (3) biopsy, which extracts materials from within a living cell, and (4) fusion, which joins multiple entities into one. For each type of surgery, we summarize the motivating applications and the microfluidic devices developed. Throughout this review, we highlight existing challenges and opportunities. We hope that this review will inspire scientists and engineers to continue to explore and improve microfluidic surgical methods.

Real-Time Monitoring of Dissection Events of Single Budding Yeast in a Microfluidic Cell-Culturing Device Integrated With Electrical Impedance Biosensor

Microfluidic devices in combination with fluorescent microscopy offer high-resolution and high-content platforms to study single-cell morphology, behavior and dynamic process in replicative aging of budding yeast, Saccharomyces cerevisiae. However, a huge mass of recorded images makes the data processing labor-intensive and time-consuming to determine yeast replicative lifespan (RLS), a primary criterion in yeast aging. To address this limitation and pursue label-free RLS assays, electrical impedance spectroscopy (EIS) that can be easily functionalized through microelectrodes in microfluidic devices, was introduced to monitor cell growth and division of budding yeast. Herein, a microfluidic device integrated with EIS biosensor was proposed to perform in-situ impedance measurement of yeast proliferation in single-cell resolution so as to identify the momentary events of daughter dissection from its mother. Single yeast cells were reliably immobilized at the bottleneck-like traps for continuous culturing, during which daughter cells were effectively detached from their mother cells by hydraulic shear forces. Time-lapse impedance measurement was performed every 2 min to monitor the cellular process including budding, division and dissection. By using the K-means clustering algorithm to analyze a self-defined parameter "Dissection Indicator," to our knowledge for the first time, the momentary event of a daughter removing from its mother cell was accurately extracted from EIS signals. Thus, the identification of daughter dissection events based on impedance sensing technology has been validated. With further development, this microfluidic device integrated with electrical impedance biosensor holds promising applications in high-throughput, real-time and label-free analysis of budding yeast aging and RLS.

Modeling aging and its impact on cellular function and organismal behavior

Aging is a complex phenomenon of functional decay in a biological organism. Although the effects of aging are readily recognizable in a wide range of organisms, the cause(s) of aging are ill defined and poorly understood. Experimental methods on model organisms have driven significant insight into aging as a process, but have not provided a complete model of aging. Computational biology offers a unique opportunity to resolve this gap in our knowledge by generating extensive and testable models that can help us understand the fundamental nature of aging, identify the presence and characteristics of unaccounted aging factor(s), demonstrate the mechanics of particular factor(s) in driving aging, and understand the secondary effects of aging on biological function. In this review, we will address each of the above roles for computational biology in aging research. Concurrently, we will explore the different applications of computational biology to aging in single-celled versus multicellular organisms. Given the long history of computational biogerontological research on lower eukaryotes, we emphasize the key future goals of gradually integrating prior models into a holistic map of aging and translating successful models to higher-complexity organisms.

Recent Advances in Microfluidic Platforms for Programming Cell-Based Living Materials

Cell-based living materials, including single cells, cell-laden fibers, cell sheets, organoids, and organs, have attracted intensive interests owing to their widespread applications in cancer therapy, regenerative medicine, drug development, and so on. Significant progress in materials, microfabrication, and cell biology have promoted the development of numerous promising microfluidic platforms for programming these cell-based living materials with a high-throughput, scalable, and efficient manner. In this review, the recent progress of novel microfluidic platforms for programming cell-based living materials is presented. First, the unique features, categories, and materials and related fabrication methods of microfluidic platforms are briefly introduced. From the viewpoint of the design principles of the microfluidic platforms, the recent significant advances of programming single cells, cell-laden fibers, cell sheets, organoids, and organs in turns are then highlighted. Last, by providing personal perspectives on challenges and future trends, this review aims to motivate researchers from the fields of materials and engineering to work together with biologists and physicians to promote the development of cell-based living materials for human healthcare-related applications.

Microfabrication and its use in investigating fungal biology

Advances in microfabrication technology, and its increasing accessibility, allow us to explore fungal biology as never before. By coupling molecular genetics with fluorescence live-cell imaging in custom-designed chambers, we can now probe single yeast cell responses to changing conditions over a lifetime, characterise population heterogeneity and investigate its underlying causes. By growing filamentous fungi in complex physical environments, we can identify cross-species commonalities, reveal species-specific growth responses and examine physiological differences relevant to diverse fungal lifestyles. As affordability and expertise broadens, microfluidic platforms will become a standard technique for examining the role of fungi in cross-kingdom interactions, ranging from rhizosphere to microbiome to interconnected human organ systems. This review brings together the perspectives already gained from studying fungal biology in microfabricated systems and outlines their potential in understanding the role of fungi in the environment, health and disease.

A novel two-layer-integrated microfluidic device for high-throughput yeast proteomic dynamics analysis at the single-cell level

Current microfluidic methods for studying multicell strains (e.g., m-types) with multienvironments (e.g., n-types) require large numbers of inlets/outlets (m*n), a complicated procedure or expensive machinery. Here, we developed a novel two-layer-integrated method to combine different PDMS microchannel layers with different functions into one chip by a PDMS through-hole array, which improved the design of a PDMS-based microfluidic system. Using this method, we succeeded in converting 2 × m × n inlets/outlets into m + n inlets/outlets and reduced the time cost of loading processing (from m × n to m) of the device for studying multicell strains (e.g., m-types) in varied multitemporal environments (i.e., n-types). Using this device, the dynamic behavior of the cell-stress-response proteins was studied when the glucose concentration decreased from 2% to a series of lower concentrations. Our device could also be widely used in high-throughput studies of various stress responses, and the new concept of a multilayer-integrated fabrication method could greatly improve the design of PDMS-based microfluidic systems.

A quantitative yeast aging proteomics analysis reveals novel aging regulators

Calorie restriction (CR) is the most robust longevity intervention, extending lifespan from yeast to mammals. Numerous conserved pathways regulating aging and mediating CR have been identified; however, the overall proteomic changes during these conditions remain largely unexplored. We compared proteomes between young and replicatively aged yeast cells under normal and CR conditions using the Stable-Isotope Labeling by Amino acids in Cell culture (SILAC) quantitative proteomics and discovered distinct signatures in the aging proteome. We found remarkable proteomic similarities between aged and CR cells, including induction of stress response pathways, providing evidence that CR pathways are engaged in aged cells. These observations also uncovered aberrant changes in mitochondria membrane proteins as well as a proteolytic cellular state in old cells. These proteomics analyses help identify potential genes and pathways that have causal effects on longevity.

Understanding the Impact of Industrial Stress Conditions on Replicative Aging in Saccharomyces cerevisiae

In yeast, aging is widely understood as the decline of physiological function and the decreasing ability to adapt to environmental changes. Saccharomyces cerevisiae has become an important model organism for the investigation of these processes. Yeast is used in industrial processes (beer and wine production), and several stress conditions can influence its intracellular aging processes. The aim of this review is to summarize the current knowledge on applied stress conditions, such as osmotic pressure, primary metabolites (e.g., ethanol), low pH, oxidative stress, heat on aging indicators, age-related physiological changes, and yeast longevity. There is clear evidence that yeast cells are exposed to many stressors influencing viability and vitality, leading to an age-related shift in age distribution. Currently, there is a lack of rapid, non-invasive methods allowing the investigation of aspects of yeast aging in real time on a single-cell basis using the high-throughput approach. Methods such as micromanipulation, centrifugal elutriator, or biotinylation do not provide real-time information on age distributions in industrial processes. In contrast, innovative approaches, such as non-invasive fluorescence coupled flow cytometry intended for high-throughput measurements, could be promising for determining the replicative age of yeast cells in fermentation and its impact on industrial stress conditions.

Design and 3D modeling investigation of a microfluidic electrode array for electrical impedance measurement of single yeast cells

High-resolution microscopic imaging may cause intensive image processing and potential impact of light irradiation on yeast replicative lifespan (RLS). Electrical impedance spectroscopy (EIS) could be alternatively used to perform high-throughput and label-free yeast RLS assays. Prior to fabricating EIS-integrated microfluidic devices for yeast RLS determination, systematic modeling and theoretical investigation are crucial for device design and optimization. Here, we report three-dimensional (3D) finite-element modeling and simulations of EIS measurement in a microfluidic single yeast in-situ impedance array (SYIIA), which is designed by patterning an electrode matrix underneath a cell-trapping array. SYIIA was instantiated and modeled as a 5 × 5 sensing array comprising 25 units for cell immobilization, culturing, and time-lapse EIS recording. Simulations of yeast growing and budding in a sensing unit demonstrated that EIS signals enable the characterization of cell growth and daughter-cell dissections. In the 5 × 5 sensing array, simulation results indicated that when monitoring a target cell, daughter dissections in its surrounding traps may induce variations of the recorded EIS signals, which could cause mistakes in identifying target daughter-cell dissections. To eliminate the mis-identifications, electrode array pitch was optimized. Therefore, the results could conduct the design and optimization of microfluidic electrode-array-integrated devices for high-throughput and accurate yeast RLS assays.

A microfluidic single-cell array for in situ laminar-flow-based comparative culturing of budding yeast cells

To facilitate in situ comparative culturing of budding yeast cells in a precisely controlled microenvironment, we developed a microfluidic single-cell array (MiSCA) with 96 traps (16 rows × 6 columns) for single-cell immobilization. Through optimization of the distances between neighboring traps and the applied flow rates by using a hydraulic equivalent circuit of the fluidic network, yeast cells were delivered to each column of the array by laminar focused flows and reliably captured at the traps by hydrodynamic forces with about 90% efficiency of cell immobilization. Immobilized cells in different columns within the same device can then be cultured in parallel while being exposed to different media and compounds delivered by laminar flows. For biological validation of the comparative cell-culturing device, we used budding yeast that can express yellow fluorescent protein upon the addition of β-estradiol in cell-culturing medium. Experimental results show successful induction of fluorescence in cells immobilized in desired columns that have been dosed with β-estradiol. The MiSCA system allows for performing sets of experiments and control experiments in parallel in the same device, or for executing comparative experiments under well-defined laminar-perfusion conditions with different media, as well as in situ monitoring of dynamic cellular responses upon different analytical compounds or reagents for single-cell analysis.

Inactivating histone deacetylase HDA promotes longevity by mobilizing trehalose metabolism

Histone acetylations are important epigenetic markers for transcriptional activation in response to metabolic changes and various stresses. Using the high-throughput SEquencing-Based Yeast replicative Lifespan screen method and the yeast knockout collection, we demonstrate that the HDA complex, a class-II histone deacetylase (HDAC), regulates aging through its target of acetylated H3K18 at storage carbohydrate genes. We find that, in addition to longer lifespan, disruption of HDA results in resistance to DNA damage and osmotic stresses. We show that these effects are due to increased promoter H3K18 acetylation and transcriptional activation in the trehalose metabolic pathway in the absence of HDA. Furthermore, we determine that the longevity effect of HDA is independent of the Cyc8-Tup1 repressor complex known to interact with HDA and coordinate transcriptional repression. Silencing the HDA homologs in C. elegans and Drosophila increases their lifespan and delays aging-associated physical declines in adult flies. Hence, we demonstrate that this HDAC controls an evolutionarily conserved longevity pathway.

Protein interaction potential landscapes for yeast replicative aging

We proposed a novel interaction potential landscape approach to map the systems-level profile changes of gene networks during replicative aging in Saccharomyces cerevisiae. This approach enabled us to apply quasi-potentials, the negative logarithm of the probabilities, to calibrate the elevation of the interaction landscapes with young cells as a reference state. Our approach detected opposite landscape changes based on protein abundances from transcript levels, especially for intra-essential gene interactions. We showed that essential proteins play different roles from hub proteins on the age-dependent interaction potential landscapes. We verified that hub proteins tend to avoid other hub proteins, but essential proteins prefer to interact with other essential proteins. Overall, we showed that the interaction potential landscape is promising for inferring network profile change during aging and that the essential hub proteins may play an important role in the uncoupling between protein and transcript levels during replicative aging.

Complementary performances of convolutional and capsule neural networks on classifying microfluidic images of dividing yeast cells

Microfluidic-based assays have become effective high-throughput approaches to examining replicative aging of budding yeast cells. Deep learning may offer an efficient way to analyze a large number of images collected from microfluidic experiments. Here, we compare three deep learning architectures to classify microfluidic time-lapse images of dividing yeast cells into categories that represent different stages in the yeast replicative aging process. We found that convolutional neural networks outperformed capsule networks in terms of accuracy, precision, and recall. The capsule networks had the most robust performance in detecting one specific category of cell images. An ensemble of three best-fitted single-architecture models achieves the highest overall accuracy, precision, and recall due to complementary performances. In addition, extending classification classes and data augmentation of the training dataset can improve the predictions of the biological categories in our study. This work lays a useful framework for sophisticated deep-learning processing of microfluidic-based assays of yeast replicative aging.

Investigation of daughter cell dissection coincidence of single budding yeast cells immobilized in microfluidic traps

Microfluidic methodologies allow for automatic and high-throughput replicative lifespan (RLS) determination of single budding yeast cells. However, the resulted RLS is highly impacted by the robustness of experimental conditions, especially the microfluidic yeast-trapping structures, which are designed for cell retention, growth, budding, and daughter cell dissection. In this work, four microfluidic yeast-trapping structures, which were commonly used to immobilize mother cells and remove daughter cells for entire lifespan of budding yeast, were systematically investigated by means of finite element modeling (FEM). The results from this analysis led us to propose an optimized design, the yeast rotation (YRot) trap, which is a "leaky bowl"-shaped structure composed of two mirrored microcolumns facing each other. The YRot trap enables stable retention of mother cells in its "bowl" and hydrodynamic rotation of buds into its "leaky orifice" such that matured progenies can be dissected in a coincident direction. We validated the functions of the YRot trap in terms of cell rotation and daughter dissection by both FEM simulations and experiments. With the integration of denser YRot traps in microchannels, the microfluidic platform with stable single-yeast immobilization, long-term cell culturing, and coincident daughter dissection could potentially improve the robustness of experimental conditions for precise RLS determination in yeast aging studies.

Replicative Aging in Pathogenic Fungi

Candida albicans, Candida auris, Candida glabrata, and Cryptococcus neoformans are pathogenic yeasts which can cause systemic infections in immune-compromised as well as immune-competent individuals. These yeasts undergo replicative aging analogous to a process first described in the nonpathogenic yeast Saccharomyces cerevisiae. The hallmark of replicative aging is the asymmetric cell division of mother yeast cells that leads to the production of a phenotypically distinct daughter cell. Several techniques to study aging that have been pioneered in S. cerevisiae have been adapted to study aging in other pathogenic yeasts. The studies indicate that aging is relevant for virulence in pathogenic fungi. As the mother yeast cell progressively ages, every ensuing asymmetric cell division leads to striking phenotypic changes, which results in increased antifungal and antiphagocytic resistance. This review summarizes the various techniques that are used to study replicative aging in pathogenic fungi along with their limitations. Additionally, the review summarizes some key phenotypic variations that have been identified and are associated with changes in virulence or resistance and thus promote persistence of older cells.

Slipstreaming Mother Machine: A Microfluidic Device for Single-Cell Dynamic Imaging of Yeast

The yeast Saccharomyces cerevisiae is one of the most basic model organisms for studies of aging and other phenomena such as division strategies. These organisms have been typically studied with the use of microfluidic devices to keep cells trapped while under a flow of fresh media. However, all of the existing devices trap cells mechanically, subjecting them to pressures that may affect cell physiology. There is evidence mechanical pressure affects growth rate and the movement of intracellular components, so it is quite possible that it affects other physiological aspects such as aging. To allow studies with the lowest influence of mechanical pressure, we designed and fabricated a device that takes advantage of the slipstreaming effect. In slipstreaming, moving fluids that encounter a barrier flow around it forming a pressure gradient behind it. We trap mother cells in this region and force daughter cells to be in the negative pressure gradient region so that they are taken away by the flow. Additionally, this device can be fabricated using low resolution lithography techniques, which makes it less expensive than devices that require photolithography masks with resolution under 5 µm. With this device, it is possible to measure some of the most interesting aspects of yeast dynamics such as growth rates and Replicative Life Span. This device should allow future studies to eliminate pressure bias as well as extending the range of labs that can do these types of measurements.

Translational control of gene expression noise and its relationship to ageing in yeast

Gene expression noise influences organism evolution and fitness but is poorly understood. There is increasing evidence that the functional roles of components of the translation machinery influence noise intensity. In addition, modulation of the activities of at least some of these same components affects the replicative lifespan of a broad spectrum of organisms. In a novel comparative approach, we modulate the activities of the translation initiation factors eIFG1 and eIF4G2, both of which are involved in the process of recruiting ribosomal 43S preinitiation complexes to the 5' end of eukaryotic mRNAs. We show that tagging of the cell wall using a fluorescent dye allows us to follow gene expression noise as different yeast strains progress through successive cycles of replicative ageing. This procedure reveals a relationship between global protein synthesis rate and gene expression noise (cell-to-cell heterogeneity), which is accompanied by a parallel correlation between gene expression noise and the replicative age of mother cells. An alternative approach, based on microfluidics, confirms the interdependence between protein synthesis rate, gene expression noise and ageing. We additionally show that it is important to characterize the influence of the design of the microfluidic device on the nutritional state of the cells during such experiments. Analysis of the noise data derived from flow cytometry and fluorescence microscopy measurements indicates that both the intrinsic and the extrinsic noise components increase as a function of ageing.

Damage Repair versus Aging in an Individual-Based Model of Biofilms

Damage is an inevitable consequence of life. For unicellular organisms, this leads to a trade-off between allocating resources into damage repair or into growth coupled with segregation of damage upon cell division, i.e., aging and senescence. Few studies considered repair as an alternative to senescence. None considered biofilms, where the majority of unicellular organisms live, although fitness advantages in well-mixed systems often turn into disadvantages in spatially structured systems such as biofilms. We compared the fitness consequences of aging versus an adaptive repair mechanism based on sensing damage, using an individual-based model of a generic unicellular organism growing in biofilms. We found that senescence is not beneficial provided that growth is limited by substrate availability. Instead, it is useful as a stress response to deal with damage that failed to be repaired when (i) extrinsic mortality was high; (ii) a degree of multicellularity was present; and (iii) damage segregation was effective.

The extent of senescence due to damage accumulation—or aging—is evidently evolvable as it differs hugely between species and is not universal, suggesting that its fitness advantages depend on life history and environment. In contrast, repair of damage is present in all organisms studied. Despite the fundamental trade-off between investing resources into repair or into growth, repair and segregation of damage have not always been considered alternatives. For unicellular organisms, unrepaired damage could be divided asymmetrically between daughter cells, leading to senescence of one and rejuvenation of the other. Repair of “unicells” has been predicted to be advantageous in well-mixed environments such as chemostats. Most microorganisms, however, live in spatially structured systems, such as biofilms, with gradients of environmental conditions and cellular physiology as well as a clonal population structure. To investigate whether this clonal structure might favor senescence by damage segregation (a division-of-labor strategy akin to the germline-soma division in multicellular organisms), we used an individual-based computational model and developed an adaptive repair strategy where cells respond to their current intracellular damage levels by investing into repair machinery accordingly. Our simulations showed that the new adaptive repair strategy was advantageous provided that growth was limited by substrate availability, which is typical for biofilms. Thus, biofilms do not favor a germline-soma-like division of labor between daughter cells in terms of damage segregation. We suggest that damage segregation is beneficial only when extrinsic mortality is high, a degree of multicellularity is present, and an active mechanism makes segregation effective.

IMPORTANCE Damage is an inevitable consequence of life. For unicellular organisms, this leads to a trade-off between allocating resources into damage repair or into growth coupled with segregation of damage upon cell division, i.e., aging and senescence. Few studies considered repair as an alternative to senescence. None considered biofilms, where the majority of unicellular organisms live, although fitness advantages in well-mixed systems often turn into disadvantages in spatially structured systems such as biofilms. We compared the fitness consequences of aging versus an adaptive repair mechanism based on sensing damage, using an individual-based model of a generic unicellular organism growing in biofilms. We found that senescence is not beneficial provided that growth is limited by substrate availability. Instead, it is useful as a stress response to deal with damage that failed to be repaired when (i) extrinsic mortality was high; (ii) a degree of multicellularity was present; and (iii) damage segregation was effective.

A physicochemical perspective of aging from single-cell analysis of pH, macromolecular and organellar crowding in yeast

Cellular aging is a multifactorial process that is characterized by a decline in homeostatic capacity, best described at the molecular level. Physicochemical properties such as pH and macromolecular crowding are essential to all molecular processes in cells and require maintenance. Whether a drift in physicochemical properties contributes to the overall decline of homeostasis in aging is not known. Here, we show that the cytosol of yeast cells acidifies modestly in early aging and sharply after senescence. Using a macromolecular crowding sensor optimized for long-term FRET measurements, we show that crowding is rather stable and that the stability of crowding is a stronger predictor for lifespan than the absolute crowding levels. Additionally, in aged cells, we observe drastic changes in organellar volume, leading to crowding on the micrometer scale, which we term organellar crowding. Our measurements provide an initial framework of physicochemical parameters of replicatively aged yeast cells.

New methodologies in ageing research

Ageing is arguably the most complex phenotype that occurs in humans. To understand and treat ageing as well as associated diseases, highly specialised technologies are emerging that reveal critical insight into the underlying mechanisms and provide new hope for previously untreated diseases. Herein, we describe the latest developments in cutting edge technologies applied across the field of ageing research. We cover emerging model organisms, high-throughput methodologies and machine-driven approaches. In all, this review will give you a glimpse of what will be pushing the field onwards and upwards.