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.

Loss of vacuolar acidity results in iron-sulfur cluster defects and divergent homeostatic responses during aging in Saccharomyces cerevisiae.

The loss of vacuolar/lysosomal acidity is an early event during aging that has been linked to mitochondrial dysfunction. However, it is unclear how loss of vacuolar acidity results in age-related dysfunction. Through unbiased genetic screens, we determined that increased iron uptake can suppress the mitochondrial respiratory deficiency phenotype of yeast vma mutants, which have lost vacuolar acidity due to genetic disruption of the vacuolar ATPase proton pump. Yeast vma mutants exhibited nuclear localization of Aft1, which turns on the iron regulon in response to iron-sulfur cluster (ISC) deficiency. This led us to find that loss of vacuolar acidity with age in wild-type yeast causes ISC defects and a DNA damage response. Using microfluidics to investigate aging at the single-cell level, we observe grossly divergent trajectories of iron homeostasis within an isogenic and environmentally homogeneous population. One subpopulation of cells fails to mount the expected compensatory iron regulon gene expression program, and suffers progressively severe ISC deficiency with little to no activation of the iron regulon. In contrast, other cells show robust iron regulon activity with limited ISC deficiency, which allows extended passage and survival through a period of genomic instability during aging. These divergent trajectories suggest that iron regulation and ISC homeostasis represent a possible target for aging interventions.

Trajectories of Aging: How Systems Biology in Yeast Can Illuminate Mechanisms of Personalized Aging.

All organisms age, but the extent to which all organisms age the same way remains a fundamental unanswered question in biology. Across species, it is now clear that at least some aspects of aging are highly conserved and are perhaps universal, but other mechanisms of aging are private to individual species or sets of closely related species. Within the same species, however, it has generally been assumed that the molecular mechanisms of aging are largely invariant from one individual to the next. With the development of new tools for studying aging at the individual cell level in budding yeast, recent data has called this assumption into question. There is emerging evidence that individual yeast mother cells may undergo fundamentally different trajectories of aging. Individual trajectories of aging are difficult to study by traditional population level assays, but through the application of systems biology approaches combined with novel microfluidic technologies, it is now possible to observe and study these phenomena in real time. Understanding the spectrum of mechanisms that determine how different individuals age is a necessary step toward the goal of personalized geroscience, where healthy longevity is optimized for each individual.

DNA damage checkpoint activation impairs chromatin homeostasis and promotes mitotic catastrophe during aging.

Genome instability is a hallmark of aging and contributes to age-related disorders such as cancer and Alzheimer's disease. The accumulation of DNA damage during aging has been linked to altered cell cycle dynamics and the failure of cell cycle checkpoints. Here, we use single cell imaging to study the consequences of increased genomic instability during aging in budding yeast and identify striking age-associated genome missegregation events. This breakdown in mitotic fidelity results from the age-related activation of the DNA damage checkpoint and the resulting degradation of histone proteins. Disrupting the ability of cells to degrade histones in response to DNA damage increases replicative lifespan and reduces genomic missegregations. We present several lines of evidence supporting a model of antagonistic pleiotropy in the DNA damage response where histone degradation, and limited histone transcription are beneficial to respond rapidly to damage but reduce lifespan and genomic stability in the long term.

An inexpensive microscopy system for microfluidic studies in budding yeast.

Recently, microfluidic technologies have been developed to allow higher throughput collection of yeast replicative lifespan data. Adoption of these devices has been limited, in part, due to the high cost of the motorized microscopy instrumentation from mainline manufacturers. Inspired by recent development of open source microscopy hardware and software, we developed minimal-cost hardware attachments to provide long-term focus stabilization for lower-cost microscopes and open source software to manage concurrent time-lapse image acquisition from multiple microscopes. We hope that these tools will help spur the wider adoption of microfluidic technologies for the study of aging in yeast.

Age-dependent deterioration of nuclear pore assembly in mitotic cells decreases transport dynamics.

Nuclear transport is facilitated by the Nuclear Pore Complex (NPC) and is essential for life in eukaryotes. The NPC is a long-lived and exceptionally large structure. We asked whether NPC quality control is compromised in aging mitotic cells. Our images of single yeast cells during aging, show that the abundance of several NPC components and NPC assembly factors decreases. Additionally, the single-cell life histories reveal that cells that better maintain those components are longer lived. The presence of herniations at the nuclear envelope of aged cells suggests that misassembled NPCs are accumulated in aged cells. Aged cells show decreased dynamics of transcription factor shuttling and increased nuclear compartmentalization. These functional changes are likely caused by the presence of misassembled NPCs, as we find that two NPC assembly mutants show similar transport phenotypes as aged cells. We conclude that NPC interphase assembly is a major challenge for aging mitotic cells.

In vivo measurements reveal a single 5'-intron is sufficient to increase protein expression level in Caenorhabditis elegans.

Introns can increase gene expression levels using a variety of mechanisms collectively referred to as Intron Mediated Enhancement (IME). IME has been measured in cell culture and plant models by quantifying expression of intronless and intron-bearing reporter genes in vitro. We developed hardware and software to implement microfluidic chip-based gene expression quantification in vivo. We altered position, number and sequence of introns in reporter genes controlled by the hsp-90 promoter. Consistent with plant and mammalian studies, we determined a single, natural or synthetic, 5'-intron is sufficient for the full IME effect conferred by three synthetic introns, while a 3'-intron is not. We found coding sequence can affect IME; the same three synthetic introns that increase mcherry protein concentration by approximately 50%, increase mEGFP by 80%. We determined IME effect size is not greatly affected by the stronger vit-2 promoter. Our microfluidic imaging approach should facilitate screens for factors affecting IME and other intron-dependent processes.

Rb analog Whi5 regulates G1 to S transition and cell size but not replicative lifespan in budding yeast.

An increase in cell size with age is a characteristic feature of replicative aging in budding yeast. Deletion of the gene encoding Whi5 results in shortened duration of G1 and reduced cell size, and has been previously suggested to increase replicative lifespan. Upon careful analysis of multiple independently derived haploid and homozygous diploid whi5Δ mutants, we find no effect on lifespan, but we do confirm the reduction in cell size. We suggest that instead of antagonizing lifespan, the elongated G1 phase of the cell cycle during aging may actually play an important role in allowing aged cells time to repair accumulating DNA damage.

Transition between fermentation and respiration determines history-dependent behavior in fluctuating carbon sources.

Cells constantly adapt to environmental fluctuations. These physiological changes require time and therefore cause a lag phase during which the cells do not function optimally. Interestingly, past exposure to an environmental condition can shorten the time needed to adapt when the condition re-occurs, even in daughter cells that never directly encountered the initial condition. Here, we use the molecular toolbox of Saccharomyces cerevisiae to systematically unravel the molecular mechanism underlying such history-dependent behavior in transitions between glucose and maltose. In contrast to previous hypotheses, the behavior does not depend on persistence of proteins involved in metabolism of a specific sugar. Instead, presence of glucose induces a gradual decline in the cells' ability to activate respiration, which is needed to metabolize alternative carbon sources. These results reveal how trans-generational transitions in central carbon metabolism generate history-dependent behavior in yeast, and provide a mechanistic framework for similar phenomena in other cell types.

The paths of mortality: how understanding the biology of aging can help explain systems behavior of single cells.

Aging is a fundamental aspect of life, yet also one of the most confounding. In individual cells, aging results in a progressive decline which affects all organelles and reduces a cell's ability to maintain homeostasis. Because of the interconnected nature of cellular systems, the failure of even a single organelle can have cascading effects. We are just beginning to understand the dramatic physiological changes that occur during aging. Because most aging research has focused on population dynamics, or differences between wild-type and mutant populations, single-cell behavior has been largely overlooked. An open question is whether aging cells are defined by predictable sequences of physiological changes, or whether they proceed along divergent aging trajectories defined by whichever system begins to fail first. Can aging be best characterized by a cell-cycle like model with stereotyped states all cells progress through, or a Waddington landscape with divergent trajectories? Here we present work on understanding the changing physiological states of aging cells, why it will impact systems and synthetic biologists, and how the systems community can contribute significantly to the study of aging.

Morphologically constrained and data informed cell segmentation of budding yeast.

Motivation: Although high-content image cytometry is becoming increasingly routine, processing the large amount of data acquired during time-lapse experiments remains a challenge. The majority of approaches for automated single-cell segmentation focus on flat, uniform fields of view covered with a single layer of cells. In the increasingly popular microfluidic devices that trap individual cells for long term imaging, these conditions are not met. Consequently, most techniques for segmentation perform poorly. Although potentially constraining the generalizability of software, incorporating information about the microfluidic features, flow of media and the morphology of the cells can substantially improve performance. Results: Here we present DISCO (Data Informed Segmentation of Cell Objects), a framework for using the physical constraints imposed by microfluidic traps, the shape based morphological constraints of budding yeast and temporal information about cell growth and motion to allow tracking and segmentation of cells in microfluidic devices. Using manually curated datasets, we demonstrate substantial improvements in both tracking and segmentation when compared with existing software. Availability and implementation: The MATLAB code for the algorithm and for measuring performance is available at https://github.com/pswain/segmentation-software and the test images and the curated ground-truth results used for comparing the algorithms are available at http://datashare.is.ed.ac.uk/handle/10283/2002. Contact: mcrane2@uw.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

Distributing tasks via multiple input pathways increases cellular survival in stress.

Improving in one aspect of a task can undermine performance in another, but how such opposing demands play out in single cells and impact on fitness is mostly unknown. Here we study budding yeast in dynamic environments of hyperosmotic stress and show how the corresponding signalling network increases cellular survival both by assigning the requirements of high response speed and high response accuracy to two separate input pathways and by having these pathways interact to converge on Hog1, a p38 MAP kinase. Cells with only the less accurate, reflex-like pathway are fitter in sudden stress, whereas cells with only the slow, more accurate pathway are fitter in increasing but fluctuating stress. Our results demonstrate that cellular signalling is vulnerable to trade-offs in performance, but that these trade-offs can be mitigated by assigning the opposing tasks to different signalling subnetworks. Such division of labour could function broadly within cellular signal transduction.

Environmental Canalization of Life Span and Gene Expression in Caenorhabditis elegans.

Animals, particularly poikilotherms, exhibit distinct physiologies at different environmental temperatures. Here, we hypothesized that temperature-based differences in physiology could affect the amount of variation in complex quantitative traits. Specifically, we examined, in Caenorhabditis elegans, how different temperatures (15°C, 20°C, and 25°C) affected the amount of interindividual variation in life span and also expression of three reporter genes-transcriptional reporters for vit-2, gpd-2, and hsp-16.2 (a life-span biomarker). We found the expected inverse relationship between temperature and average life span. Surprisingly, we found that at the highest temperature, there were fewer differences between individuals in life span and less interindividual variation in expression of all three reporters. We suggest that growth at 25°C might canalize (reduce interindividual differences in) life span and expression of some genes by eliciting a small constitutive heat shock response. Growth at 25°C requires wild-type hsf-1, which encodes the main heat shock response transcriptional activator. We speculate that increased chaperone activity at 25°C may reduce interindividual variation in gene expression by increasing protein folding efficiency. We hypothesize that reduced variation in gene expression may ultimately cause reduced variation in life span.

Transaldolase inhibition impairs mitochondrial respiration and induces a starvation-like longevity response in Caenorhabditis elegans.

Mitochondrial dysfunction can increase oxidative stress and extend lifespan in Caenorhabditis elegans. Homeostatic mechanisms exist to cope with disruptions to mitochondrial function that promote cellular health and organismal longevity. Previously, we determined that decreased expression of the cytosolic pentose phosphate pathway (PPP) enzyme transaldolase activates the mitochondrial unfolded protein response (UPRmt) and extends lifespan. Here we report that transaldolase (tald-1) deficiency impairs mitochondrial function in vivo, as evidenced by altered mitochondrial morphology, decreased respiration, and increased cellular H2O2 levels. Lifespan extension from knockdown of tald-1 is associated with an oxidative stress response involving p38 and c-Jun N-terminal kinase (JNK) MAPKs and a starvation-like response regulated by the transcription factor EB (TFEB) homolog HLH-30. The latter response promotes autophagy and increases expression of the flavin-containing monooxygenase 2 (fmo-2). We conclude that cytosolic redox established through the PPP is a key regulator of mitochondrial function and defines a new mechanism for mitochondrial regulation of longevity.

Caenorhabditis elegans Genes Affecting Interindividual Variation in Life-span Biomarker Gene Expression.

Genetically identical organisms grown in homogenous environments differ in quantitative phenotypes. Differences in one such trait, expression of a single biomarker gene, can identify isogenic cells or organisms that later manifest different fates. For example, in isogenic populations of young adult Caenorhabditis elegans, differences in Green Fluorescent Protein (GFP) expressed from the hsp-16.2 promoter predict differences in life span. Thus, it is of interest to determine how interindividual differences in biomarker gene expression arise. Prior reports showed that the thermosensory neurons and insulin signaling systems controlled the magnitude of the heat shock response, including absolute expression of hsp-16.2. Here, we tested whether these regulatory signals might also influence variation in hsp-16.2 reporter expression. Genetic experiments showed that the action of AFD thermosensory neurons increases interindividual variation in biomarker expression. Further genetic experimentation showed the insulin signaling system acts to decrease interindividual variation in life-span biomarker expression; in other words, insulin signaling canalizes expression of the hsp-16.2-driven life-span biomarker. Our results show that specific signaling systems regulate not only expression level, but also the amount of interindividual expression variation for a life-span biomarker gene. They raise the possibility that manipulation of these systems might offer means to reduce heterogeneity in the aging process.

Microfluidic technologies for yeast replicative lifespan studies.

The budding yeast Saccharomyces cerevisiae has been used as a model organism for the study of aging for over 50 years. In this time, the canonical aging experiment-replicative lifespan analysis by manual microdissection-has remained essentially unchanged. Recently, microfluidic technologies have been developed that may be able to substitute for this time- and labor-intensive procedure. These technologies also allow cell physiology to be observed throughout the entire lifetime. Here, we review these devices, novel observations they have made possible, and some of the current system limitations.

Deep phenotyping unveils hidden traits and genetic relations in subtle mutants.

Discovering mechanistic insights from phenotypic information is critical for the understanding of biological processes. For model organisms, unlike in cell culture, this is currently bottlenecked by the non-quantitative nature and perceptive biases of human observations, and the limited number of reporters that can be simultaneously incorporated in live animals. An additional challenge is that isogenic populations exhibit significant phenotypic heterogeneity. These difficulties limit genetic approaches to many biological questions. To overcome these bottlenecks, we developed tools to extract complex phenotypic traits from images of fluorescently labelled subcellular landmarks, using C. elegans synapses as a test case. By population-wide comparisons, we identified subtle but relevant differences inaccessible to subjective conceptualization. Furthermore, the models generated testable hypotheses of how individual alleles relate to known mechanisms or belong to new pathways. We show that our model not only recapitulates current knowledge in synaptic patterning but also identifies novel alleles overlooked by traditional methods.

Automated Processing of Imaging Data through Multi-tiered Classification of Biological Structures Illustrated Using Caenorhabditis elegans.

Quantitative imaging has become a vital technique in biological discovery and clinical diagnostics; a plethora of tools have recently been developed to enable new and accelerated forms of biological investigation. Increasingly, the capacity for high-throughput experimentation provided by new imaging modalities, contrast techniques, microscopy tools, microfluidics and computer controlled systems shifts the experimental bottleneck from the level of physical manipulation and raw data collection to automated recognition and data processing. Yet, despite their broad importance, image analysis solutions to address these needs have been narrowly tailored. Here, we present a generalizable formulation for autonomous identification of specific biological structures that is applicable for many problems. The process flow architecture we present here utilizes standard image processing techniques and the multi-tiered application of classification models such as support vector machines (SVM). These low-level functions are readily available in a large array of image processing software packages and programming languages. Our framework is thus both easy to implement at the modular level and provides specific high-level architecture to guide the solution of more complicated image-processing problems. We demonstrate the utility of the classification routine by developing two specific classifiers as a toolset for automation and cell identification in the model organism Caenorhabditis elegans. To serve a common need for automated high-resolution imaging and behavior applications in the C. elegans research community, we contribute a ready-to-use classifier for the identification of the head of the animal under bright field imaging. Furthermore, we extend our framework to address the pervasive problem of cell-specific identification under fluorescent imaging, which is critical for biological investigation in multicellular organisms or tissues. Using these examples as a guide, we envision the broad utility of the framework for diverse problems across different length scales and imaging methods.

Regulation of synaptic extracellular matrix composition is critical for proper synapse morphology.

Synapses are surrounded by a layer of extracellular matrix (ECM), which is instrumental for their development and maintenance. ECM composition is dynamically controlled by proteases, but how the precise composition of the ECM affects synaptic morphology is largely unknown. Through an unbiased forward genetic screen, we found that Caenorhabditis elegans gon-1, a conserved extracellular ADAMTS protease, is required for maintaining proper synaptic morphology at the neuromuscular junction. In gon-1 mutants, once synapse formation is complete, motor neuron presynaptic varicosities develop into large bulbous protrusions that contain synaptic vesicles and active zone proteins. A concomitant overgrowth of postsynaptic muscle membrane is found in close apposition to presynaptic axonal protrusions. Mutations in the muscle-specific, actin-severing protein cofilin (unc-60) suppress the axon phenotype, suggesting that muscle outgrowth is necessary for presynaptic protrusions. gon-1 mutants can also be suppressed by loss of the ECM components collagen IV (EMB-9) and fibulin (FBL-1). We propose that GON-1 regulates a developmental switch out of an initial "pro-growth" phase during which muscle arms grow out and form synapses with motor neuron axons. We postulate that this switch involves degradation or reorganization of collagen IV (EMB-9), whereas FBL-1 opposes GON-1 by stabilizing EMB-9. Our results describe a mechanism for regulating synaptic ECM composition and reveal the importance of precise ECM composition for neuronal morphology and synapse integrity.

A microfluidic system for studying ageing and dynamic single-cell responses in budding yeast.

Recognition of the importance of cell-to-cell variability in cellular decision-making and a growing interest in stochastic modeling of cellular processes has led to an increased demand for high density, reproducible, single-cell measurements in time-varying surroundings. We present ALCATRAS (A Long-term Culturing And TRApping System), a microfluidic device that can quantitatively monitor up to 1000 cells of budding yeast in a well-defined and controlled environment. Daughter cells are removed by fluid flow to avoid crowding allowing experiments to run for over 60 hours, and the extracellular media may be changed repeatedly and in seconds. We illustrate use of the device by measuring ageing through replicative life span curves, following the dynamics of the cell cycle, and examining history-dependent behaviour in the general stress response.