Age structure landscapes emerge from the equilibrium between aging and rejuvenation in bacterial populations

Lineage-dependent variations in single-cell antibiotic susceptibility reveal the selective inheritance of phenotypic resistance in bacteria

Genetically identical bacterial cells often exhibit heterogeneous responses to antibiotics - some survive, others die. Here, we show that this heterogeneity propagates across generations to give rise to phenotypic resistance. Using real-time single-cell tracking, we exposed Escherichia coli to the β-lactam cefsulodin at its clinical breakpoint concentration and analyzed cell fate within genealogical trees statistically. Cell survival was strongly correlated among family members, driving the selective enrichment of robust lineages within an otherwise susceptible population. Our genealogical population model identified heritable phenotypic resistance as a key factor underlying this enrichment, which was validated experimentally. Comparing enrichment dynamics between the wild-type and a tolC knock-out strain, deficient in multidrug efflux, uncovered nuanced changes that increased the intergenerational memory of phenotypic resistance. Our findings provide evidence for heritable phenotypic resistance and demonstrate how its propagation through cell-to-cell heterogeneity enables the survival of minority cells within isogenic populations.

A link between aging and persistence

Despite the various strategies that microorganisms have evolved to resist antibiotics, survival to drug treatments can be driven by subpopulations of susceptible bacteria in a transient state of dormancy. This phenotype, known as bacterial persistence, arises due to a natural and ubiquitous heterogeneity of growth states in bacterial populations. Nonetheless, the unifying mechanism of persistence remains unknown, with several pathways being able to trigger the phenotype. Here, we show that asymmetric damage partitioning, a form of cellular aging, produces the underlying phenotypic heterogeneity upon which persistence is triggered. Using single-cell microscopy and microfluidic devices, we demonstrate that deterministic asymmetry in exponential phase populations leads to a state of growth stability, which prevents the spontaneous formation of persisters. However, as populations approach stationary phase, aging bacteria-those inheriting more damage upon division-exhibit a sharper growth rate decline, increased probability of growth arrest, and higher persistence rates. These results indicate that persistence triggers are biased by bacterial asymmetry, thus acting upon the deterministic heterogeneity produced by cellular aging. This work suggests unifying mechanisms for persistence and offers new perspectives on the treatment of recalcitrant infections.

Microfluidic biosensors for biomarker detection in body fluids: a key approach for early cancer diagnosis

Early detection of cancer significantly improves patient outcomes, with biomarkers offering a promising avenue for earlier and more precise diagnoses. Microfluidic biosensors have emerged as a powerful tool for detecting these biomarkers in body fluids, providing enhanced sensitivity, specificity, and rapid analysis. This review focuses on recent advances in microfluidic biosensors from 2018 to 2024, detailing their operational principles, fabrication techniques, and integration with nanotechnology for cancer biomarker detection. Additionally, we have reviewed recent innovations in several aspects of microfluidic biosensors, such as novel detection technologies, nanomaterials and novel microfluidic chip structures, which significantly enhance detection capabilities. We highlight key biomarkers pertinent to early cancer detection and explore how these innovations in biosensor technology contribute to the evolving landscape of personalized medicine. We further explore how these technologies could be incorporated into clinical cancer diagnostic workflows to improve early detection and treatment outcomes. These innovations could help enable more precise and personalized cancer diagnostics. In addition, this review addresses several important issues such as enhancing the scalability and sensitivity of these biosensors in clinical settings and points out future possibilities of combining artificial intelligence diagnostics with microfluidic biosensors to optimize their practical applications. This overview aims to guide future research and clinical applications by addressing current challenges and identifying opportunities for further development in the field of biomarker research.

Spatial and temporal distribution of ribosomes in single cells reveals aging differences between old and new daughters of Escherichia coli

Lineages of rod-shaped bacteria such as Escherichia coli exhibit a temporal decline in elongation rate in a manner comparable to cellular or biological aging. The effect results from the production of asymmetrical daughters, one with a lower elongation rate, by the division of a mother cell. The slower daughter compared to the faster daughter, denoted respectively as the old and new daughters, has more aggregates of damaged proteins and fewer expressed gene products. We have examined further the degree of asymmetry by measuring the density of ribosomes between old and new daughters and between their poles. We found that ribosomes were denser in the new daughter and also in the new pole of the daughters. These ribosome patterns match the ones we previously found for expressed gene products. This outcome suggests that the asymmetry is not likely to result from properties unique to the gene expressed in our previous study, but rather from a more fundamental upstream process affecting the distribution of ribosomal abundance. Because damage aggregates and ribosomes are both more abundant at the poles of E. coli cells, we suggest that competition for space between the two could explain the reduced ribosomal density in old daughters. Using published values for aggregate sizes and the relationship between ribosomal number and elongation rates, we show that the aggregate volumes could in principle displace quantitatively the amount of ribosomes needed to reduce the elongation rate of the old daughters.

Progressive decline in old pole gene expression signal enhances phenotypic heterogeneity in bacteria

Cell growth and gene expression are heterogeneous processes at the single-cell level, leading to the emergence of multiple physiological states within bacterial populations. Aging is a known deterministic driver of growth asymmetry; however, its role in gene expression heterogeneity remains elusive. Here, we show that aging mother cells undergo a progressive decline in old pole activity, generating asymmetry in protein partitioning, gene expression, and cell morphology. We demonstrate that mother cells, when compared to their daughters, exhibit lower product inheritance and gene expression rates independently of promoter dynamics. The declining activity of maternal old poles generates gene expression gradients that manifest as mother-daughter asymmetry upon division, showing that asymmetry is progressively built over time within the maternal intracellular environment. Moreover, old pole aging correlates with a gradual increase in cell length, leading to morphological asymmetry. These findings provide further evidence for aging as a mechanism to enhance phenotypic heterogeneity in bacterial populations, with possible consequences for stress response and survival.

Synergistic and antagonistic effects of deterministic and stochastic cell-cell variations

By diversifying, cells in a clonal population can together overcome the limits of individuals. Diversity in single-cell growth rates allows the population to survive environmental stresses, such as antibiotics, and grow faster than the undiversified population. These functional cell-cell variations can arise stochastically, from noise in biochemical reactions, or deterministically, by asymmetrically distributing damaged components. While each of the mechanisms is well understood, the effect of the combined mechanisms is unclear. To evaluate the contribution of the deterministic component we developed a mathematical model by mapping the growing population to the Ising model. To analyze the combined effects of stochastic and deterministic contributions we introduced the analytical results of the Ising-mapping into an Euler-Lotka framework. Model results, confirmed by simulations and experimental data, show that deterministic cell-cell variations increase near-linearly with stress. As a consequence, we predict that the gain in population doubling time from cell-cell variations is primarily stochastic at low stress but may cross over to deterministic at higher stresses. Furthermore, we find that while the deterministic component minimizes population damage, stochastic variations antagonize this effect. Together our results may help identifying stress-tolerant pathogenic cells and thus inspire novel antibiotic strategies.

Impact of Protein Aggregates on Sporulation and Germination of Bacillus subtilis

In order to improve our general understanding of protein aggregate (PA) management and impact in bacteria, different model systems and processes need to be investigated. As such, we developed an inducible synthetic PA model system to investigate PA dynamics in the Gram-positive model organism Bacillus subtilis. This confirmed previous observations that PA segregation in this organism seems to follow the Escherichia coli paradigm of nucleoid occlusion governing polar localization and asymmetric segregation during vegetative growth. However, our findings also revealed that PAs can readily persist throughout the entire sporulation process after encapsulation in the forespore during sporulation. Moreover, no deleterious effects of PA presence on sporulation, germination and spore survival against heat or UV stress could be observed. Our findings therefore indicate that the sporulation process is remarkably robust against perturbations by PAs and misfolded proteins.

Expanding evolutionary theories of ageing to better account for symbioses and interactions throughout the Web of Life

How, when, and why organisms age are fascinating issues that can only be fully addressed by adopting an evolutionary perspective. Consistently, the main evolutionary theories of ageing, namely the Mutation Accumulation theory, the Antagonistic Pleiotropy theory, and the Disposable Soma theory, have formulated stimulating hypotheses that structure current debates on both the proximal and ultimate causes of organismal ageing. However, all these theories leave a common area of biology relatively under-explored. The Mutation Accumulation theory and the Antagonistic Pleiotropy theory were developed under the traditional framework of population genetics, and therefore are logically centred on the ageing of individuals within a population. The Disposable Soma theory, based on principles of optimising physiology, mainly explains ageing within a species. Consequently, current leading evolutionary theories of ageing do not explicitly model the countless interspecific and ecological interactions, such as symbioses and host-microbiomes associations, increasingly recognized to shape organismal evolution across the Web of Life. Moreover, the development of network modelling supporting a deeper understanding on the molecular interactions associated with ageing within and between organisms is also bringing forward new questions regarding how and why molecular pathways associated with ageing evolved. Here, we take an evolutionary perspective to examine the effects of organismal interactions on ageing across different levels of biological organisation, and consider the impact of surrounding and nested systems on organismal ageing. We also apply this perspective to suggest open issues with potential to expand the standard evolutionary theories of ageing.

Current Trends and Approaches to the Search for Genetic Determinants of Aging and Longevity

Aging is a natural process of extinction of the body and the main aspect that determines the life expectancy for individuals who have survived to the post-reproductive period. The process of aging is accompanied by certain physiological, immune, and metabolic changes in the body, as well as the development of age-related diseases. The contribution of genetic factors to human life expectancy is estimated at about 25-30%. Despite the success in identifying genes and metabolic pathways that may be involved in the life extension process in model organisms, the key question remains to what extent these data can be extrapolated to humans, for example, because of the complexity of its biological and sociocultural systems, as well as possible species differences in life expectancy and causes of mortality. New molecular genetic methods have significantly expanded the possibilities for searching for genetic factors of human life expectancy and identifying metabolic pathways of aging, the interaction of genes and transcription factors, the regulation of gene expression at the level of transcription, and epigenetic modifications. The review presents the latest research and current strategies for studying the genetic basis of human aging and longevity: the study of individual candidate genes in genetic population studies, variations identified by the GWAS method, immunogenetic differences in aging, and genomic studies to identify factors of "healthy aging." Understanding the mechanisms of the interaction between factors affecting the life expectancy and the possibility of their regulation can become the basis for developing comprehensive measures to achieve healthy longevity.

Supplementary Information

The online version contains supplementary material available at 10.1134/S1022795422120067.

Microplankton life histories revealed by holographic microscopy and deep learning

The marine microbial food web plays a central role in the global carbon cycle. However, our mechanistic understanding of the ocean is biased toward its larger constituents, while rates and biomass fluxes in the microbial food web are mainly inferred from indirect measurements and ensemble averages. Yet, resolution at the level of the individual microplankton is required to advance our understanding of the microbial food web. Here, we demonstrate that, by combining holographic microscopy with deep learning, we can follow microplanktons throughout their lifespan, continuously measuring their three-dimensional position and dry mass. The deep-learning algorithms circumvent the computationally intensive processing of holographic data and allow rapid measurements over extended time periods. This permits us to reliably estimate growth rates, both in terms of dry mass increase and cell divisions, as well as to measure trophic interactions between species such as predation events. The individual resolution provides information about selectivity, individual feeding rates, and handling times for individual microplanktons. The method is particularly useful to detail the rates and routes of organic matter transfer in micro-zooplankton, the most important and least known group of primary consumers in the oceans. Studying individual interactions in idealized small systems provides insights that help us understand microbial food webs and ultimately larger-scale processes. We exemplify this by detailed descriptions of micro-zooplankton feeding events, cell divisions, and long-term monitoring of single cells from division to division.

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.

Connecting single-cell ATP dynamics to overflow metabolism, cell growth, and the cell cycle in Escherichia coli

Adenosine triphosphate (ATP) is an abundant and essential metabolite that cells consume and regenerate in large amounts to support growth. Although numerous studies have inferred the intracellular concentration of ATP in bacterial cultures, what happens in individual bacterial cells under stable growth conditions is less clear. Here, we use the QUEEN-2m biosensor to quantify ATP dynamics in single Escherichia coli cells in relation to their growth rate, metabolism, cell cycle, and cell lineage. We find that ATP dynamics are more complex than expected from population studies and are associated with growth-rate variability. Under stable nutrient-rich condition, cells can display large fluctuations in ATP level that are partially coordinated with the cell cycle. Abrogation of aerobic acetate fermentation (overflow metabolism) through genetic deletion considerably reduces both the amplitude of ATP level fluctuations and the cell-cycle trend. Similarly, growth in media in which acetate fermentation is lower or absent results in the reduction of ATP level fluctuation and cell-cycle trend. This suggests that overflow metabolism exhibits temporal dynamics, which contributes to fluctuating ATP levels during growth. Remarkably, at the single-cell level, growth rate negatively correlates with the amplitude of ATP fluctuation for each tested condition, linking ATP dynamics to growth-rate heterogeneity in clonal populations. Our work highlights the importance of single-cell analysis in studying metabolism and its implication to phenotypic diversity and cell growth.

Long-time behavior and Darwinian optimality for an asymmetric size-structured branching process

We study the long time behavior of an asymmetric size-structured measure-valued growth-fragmentation branching process that models the dynamics of a population of cells taking into account physiological and morphological asymmetry at division. We show that the process exhibits a Malthusian behavior; that is that the global population size grows exponentially fast and that the trait distribution of individuals converges to some stable distribution. The proof is based on a generalization of Lyapunov function techniques for non-conservative semi-groups. We then investigate the fluctuations of the growth rate with respect to the parameters guiding asymmetry. In particular, we exhibit that, under some special assumptions, symmetric division is sub-optimal in a Darwinian sense.

Interspecific interactions that affect ageing: Age-distorters manipulate host ageing to their own evolutionary benefits

Genetic causes for ageing are traditionally investigated within a species. Yet, the lifecycles of many organisms intersect. Additional evolutionary and genetic causes of ageing, external to a focal species/organism, may thus be overlooked. Here, we introduce the phrase and concept of age-distorters and its evidence. Age-distorters carry ageing interfering genes, used to manipulate the biological age of other entities upon which the reproduction of age-distorters relies, e.g. age-distorters bias the reproduction/maintenance trade-offs of cells/organisms for their own evolutionary interests. Candidate age-distorters include viruses, parasites and symbionts, operating through specific, genetically encoded interferences resulting from co-evolution and arms race between manipulative non-kins and manipulable species. This interference results in organismal ageing when age-distorters prompt manipulated organisms to favor their reproduction at the expense of their maintenance, turning these hosts into expanded disposable soma. By relying on reproduction/maintenance trade-offs affecting disposable entities, which are left ageing to the reproductive benefit of other physically connected lineages with conflicting evolutionary interests, the concept of age-distorters expands the logic of the Disposable Soma theory beyond species with fixed germen/soma distinctions. Moreover, acknowledging age-distorters as external sources of mutation accumulation and antagonistic pleiotropic genes expands the scope of the mutation accumulation and of the antagonistic pleiotropy theories.

The role of memory in non-genetic inheritance and its impact on cancer treatment resistance

Intra-tumour heterogeneity is a leading cause of treatment failure and disease progression in cancer. While genetic mutations have long been accepted as a primary mechanism of generating this heterogeneity, the role of phenotypic plasticity is becoming increasingly apparent as a driver of intra-tumour heterogeneity. Consequently, understanding the role of this plasticity in treatment resistance and failure is a key component of improving cancer therapy. We develop a mathematical model of stochastic phenotype switching that tracks the evolution of drug-sensitive and drug-tolerant subpopulations to clarify the role of phenotype switching on population growth rates and tumour persistence. By including cytotoxic therapy in the model, we show that, depending on the strategy of the drug-tolerant subpopulation, stochastic phenotype switching can lead to either transient or permanent drug resistance. We study the role of phenotypic heterogeneity in a drug-resistant, genetically homogeneous population of non-small cell lung cancer cells to derive a rational treatment schedule that drives population extinction and avoids competitive release of the drug-tolerant sub-population. This model-informed therapeutic schedule results in increased treatment efficacy when compared against periodic therapy, and, most importantly, sustained tumour decay without the development of resistance.

Three-dimensional label-free visualization and quantification of polyhydroxyalkanoates in individual bacterial cell in its native state

Polyhydroxyalkanoates (PHAs) are biodegradable polyesters that are intracellularly accumulated as distinct insoluble granules by various microorganisms. PHAs have attracted much attention as sustainable substitutes for petroleum-based plastics. However, the formation of PHA granules and their characteristics, such as localization, volume, weight, and density of granules, in an individual live bacterial cell are not well understood. Here, we report the results of three-dimensional (3D) quantitative label-free analysis of PHA granules in individual live bacterial cells through measuring the refractive index distributions by optical diffraction tomography (ODT). The formation and growth of PHA granules in the cells of Cupriavidus necator, the best-studied native PHA producer, and recombinant Escherichia coli harboring C. necator poly(3-hydroxybutyrate) (PHB) biosynthesis pathway are comparatively examined. Through the statistical ODT analyses of the bacterial cells, the distinctive characteristics for density and localization of PHB granules in vivo could be observed. The PHB granules in recombinant E. coli show higher density and localization polarity compared with those of C. necator, indicating that polymer chains are more densely packed and granules tend to be located at the cell poles, respectively. The cells were investigated in more detail through real-time 3D analyses, showing how differently PHA granules are processed in relation to the cell division process in native and nonnative PHA-producing strains. We also show that PHA granule-associated protein PhaM of C. necator plays a key role in making these differences between C. necator and recombinant E. coli strains. This study provides spatiotemporal insights into PHA accumulation inside the native and recombinant bacterial cells.

Senescence in Bacteria and Its Underlying Mechanisms

Bacteria have been thought to flee senescence by dividing into two identical daughter cells, but this notion of immortality has changed over the last two decades. Asymmetry between the resulting daughter cells after binary fission is revealed in physiological function, cell growth, and survival probabilities and is expected from theoretical understanding. Since the discovery of senescence in morphologically identical but physiologically asymmetric dividing bacteria, the mechanisms of bacteria aging have been explored across levels of biological organization. Quantitative investigations are heavily biased toward Escherichia coli and on the role of inclusion bodies—clusters of misfolded proteins. Despite intensive efforts to date, it is not evident if and how inclusion bodies, a phenotype linked to the loss of proteostasis and one of the consequences of a chain of reactions triggered by reactive oxygen species, contribute to senescence in bacteria. Recent findings in bacteria question that inclusion bodies are only deleterious, illustrated by fitness advantages of cells holding inclusion bodies under varying environmental conditions. The contributions of other hallmarks of aging, identified for metazoans, remain elusive. For instance, genomic instability appears to be age independent, epigenetic alterations might be little age specific, and other hallmarks do not play a major role in bacteria systems. What is surprising is that, on the one hand, classical senescence patterns, such as an early exponential increase in mortality followed by late age mortality plateaus, are found, but, on the other hand, identifying mechanisms that link to these patterns is challenging. Senescence patterns are sensitive to environmental conditions and to genetic background, even within species, which suggests diverse evolutionary selective forces on senescence that go beyond generalized expectations of classical evolutionary theories of aging. Given the molecular tool kits available in bacteria, the high control of experimental conditions, the high-throughput data collection using microfluidic systems, and the ease of life cell imaging of fluorescently marked transcription, translation, and proteomic dynamics, in combination with the simple demographics of growth, division, and mortality of bacteria, make the challenges surprising. The diversity of mechanisms and patterns revealed and their environmental dependencies not only present challenges but also open exciting opportunities for the discovery and deeper understanding of aging and its mechanisms, maybe beyond bacteria and aging.

Survival of the first rather than the fittest in a Shewanella electrode biofilm

For natural selection to operate there must exist heritable variation among individuals that affects their survival and reproduction. Among free-living microbes, where differences in growth rates largely define selection intensities, competitive exclusion is common. However, among surface attached communities, these dynamics become less predictable. If extreme circumstances were to dictate that a surface population is immortal and all offspring must emigrate, the offspring would be unable to contribute to the composition of the population. Meanwhile, the immortals, regardless of reproductive capacity, would remain unchanged in relative abundance. The normal cycle of birth, death, and competitive exclusion would be broken. We tested whether conditions required to set up this idealized scenario can be approximated in a microbial biofilm. Using two differentially-reproducing strains of Shewanella oneidensis grown on an anode as the sole terminal electron acceptor - a system in which metabolism is obligately tied to surface attachment - we found that selection against a slow-growing competitor is drastically reduced. This work furthers understanding of natural selection dynamics in sessile microbial communities, and provides a framework for designing stable microbial communities for industrial and experimental applications.

Challenges of analysing stochastic gene expression in bacteria using single-cell time-lapse experiments

Stochastic gene expression causes phenotypic heterogeneity in a population of genetically identical bacterial cells. Such non-genetic heterogeneity can have important consequences for the population fitness, and therefore cells implement regulation strategies to either suppress or exploit such heterogeneity to adapt to their circumstances. By employing time-lapse microscopy of single cells, the fluctuation dynamics of gene expression may be analysed, and their regulatory mechanisms thus deciphered. However, a careful consideration of the experimental design and data-analysis is needed to produce useful data for deriving meaningful insights from them. In the present paper, the individual steps and challenges involved in a time-lapse experiment are discussed, and a rigorous framework for designing, performing, and extracting single-cell gene expression dynamics data from such experiments is outlined.

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.

Aging a little: On the optimality of limited senescence in Escherichia coli

Recent studies have shown that even in the absence of extrinsic stress, the morphologically symmetrically dividing model bacteria Escherichia coli do not generate offspring with equal reproductive fitness. Instead, daughter cells exhibit asymmetric division times that converge to two distinct growth states. This represents a limited senescence/rejuvenation process derived from asymmetric division that is stable for hundreds of generations. It remains unclear why the bacteria do not continue the senescence beyond this asymptote. Although there are inherent fitness benefits for heterogeneity in population growth rates, the two growth equilibria are surprisingly similar, differing by a few percent. In this work we derive an explicit model for the growth of a bacterial population with two growth equilibria, based on a generalized Fibonacci recurrence, in order to quantify the fitness benefit of a limited senescence process and examine costs associated with asymmetry that could generate the observed behavior. We find that a simple saturating effect of asymmetric partitioning of subcellular components is sufficient to explain why two distinct but similar growth states may be optimal while providing evolutionarily significant growth advantages.

Allocation of gene products to daughter cells is determined by the age of the mother in single Escherichia coli cells

Gene expression and growth rate are highly stochastic in Escherichia coli. Some of the growth rate variations result from the deterministic and asymmetric partitioning of damage by the mother to its daughters. One daughter, denoted the old daughter, receives more damage, grows more slowly and ages. To determine if expressed gene products are also allocated asymmetrically, we compared the levels of expressed green fluorescence protein in growing daughters descending from the same mother. Our results show that old daughters were less fluorescent than new daughters. Moreover, old mothers, which were born as old daughters, produced daughters that were more asymmetric when compared to new mothers. Thus, variation in gene products in a clonal E. coli population also has a deterministic component. Because fluorescence levels and growth rates were positively correlated, the aging of old daughters appears to result from both the presence of both more damage and fewer expressed gene products.

Protein aggregation in bacteria

Protein aggregation occurs as a consequence of perturbations in protein homeostasis that can be triggered by environmental and cellular stresses. The accumulation of protein aggregates has been associated with aging and other pathologies in eukaryotes, and in bacteria with changes in growth rate, stress resistance and virulence. Numerous past studies, mostly performed in Escherichia coli, have led to a detailed understanding of the functions of the bacterial protein quality control machinery in preventing and reversing protein aggregation. However, more recent research points toward unexpected diversity in how phylogenetically different bacteria utilize components of this machinery to cope with protein aggregation. Furthermore, how persistent protein aggregates localize and are passed on to progeny during cell division and how their presence impacts reproduction and the fitness of bacterial populations remains a controversial field of research. Finally, although protein aggregation is generally seen as a symptom of stress, recent work suggests that aggregation of specific proteins under certain conditions can regulate gene expression and cellular resource allocation. This review discusses recent advances in understanding the consequences of protein aggregation and how this process is dealt with in bacteria, with focus on highlighting the differences and similarities observed between phylogenetically different groups of bacteria.

Bacterial ageing in the absence of external stressors

Evidence of ageing in the bacterium Escherichia coli was a landmark finding in senescence research, as it suggested that even organisms with morphologically symmetrical fission may have evolved strategies to permit damage accumulation. However, recent work has suggested that ageing is only detectable in this organism in the presence of extrinsic stressors, such as the fluorescent proteins and strong light sources typically used to excite them. Here we combine microfluidics with brightfield microscopy to provide evidence of ageing in E. coli in the absence of these stressors. We report (i) that the doubling time of the lineage of cells that consistently inherits the 'maternal old pole' progressively increases with successive rounds of cell division until it reaches an apparent asymptote, and (ii) that the parental cell divides asymmetrically, with the old pole daughter showing a longer doubling time and slower glucose accumulation than the new pole daughter. Notably, these patterns arise without the progressive accumulation or asymmetric partitioning of observable misfolded-protein aggregates, phenomena previously hypothesized to cause the ageing phenotype. Our findings suggest that ageing is part of the naturally occurring ecologically-relevant phenotype of this bacterium and highlight the importance of alternative mechanisms of damage accumulation in this context. This article is part of a discussion meeting issue 'Single cell ecology'.

Nucleoid-mediated positioning and transport in bacteria

Precise management of the spatiotemporal position of subcellular components is critical to a number of essential processes in the bacterial cell. The bacterial nucleoid is a highly structured yet dynamic object that undergoes significant reorganization during the relatively short cell cycle, e.g. during gene expression, chromosome replication, and segregation. Although the nucleoid takes up a large fraction of the volume of the cell, the mobility of macromolecules within these dense regions is relatively high and recent results suggest that the nucleoid plays an integral role of dynamic localization in a host of seemingly disparate cellular processes. Here, we review a number of recent reports of nucleoid-mediated positioning and transport in the model bacteria Escherichia coli. These results viewed as a whole suggest that the dynamic, cellular-scale structure of the nucleoid may be a key driver of positioning and transport within the cell. This model of a global, default positioning and transport system may help resolve many unanswered questions about the mechanisms of partitioning and segregation in bacteria.

Revamping the evolutionary theories of aging

Radical lifespan disparities exist in the animal kingdom. While the ocean quahog can survive for half a millennium, the mayfly survives for less than 48 h. The evolutionary theories of aging seek to explain why such stark longevity differences exist and why a deleterious process like aging evolved. The classical mutation accumulation, antagonistic pleiotropy, and disposable soma theories predict that increased extrinsic mortality should select for the evolution of shorter lifespans and vice versa. Most experimental and comparative field studies conform to this prediction. Indeed, animals with extreme longevity (e.g., Greenland shark, bowhead whale, giant tortoise, vestimentiferan tubeworms) typically experience minimal predation. However, data from guppies, nematodes, and computational models show that increased extrinsic mortality can sometimes lead to longer evolved lifespans. The existence of theoretically immortal animals that experience extrinsic mortality - like planarian flatworms, panther worms, and hydra - further challenges classical assumptions. Octopuses pose another puzzle by exhibiting short lifespans and an uncanny intelligence, the latter of which is often associated with longevity and reduced extrinsic mortality. The evolutionary response to extrinsic mortality is likely dependent on multiple interacting factors in the organism, population, and ecology, including food availability, population density, reproductive cost, age-mortality interactions, and the mortality source.

Microbial ageing and longevity

Longevity reflects the ability to maintain homeostatic conditions necessary for life as an organism ages. A long-lived organism must contend not only with environmental hazards but also with internal entropy and macromolecular damage that result in the loss of fitness during ageing, a phenomenon known as senescence. Although central to many of the core concepts in biology, ageing and longevity have primarily been investigated in sexually reproducing, multicellular organisms. However, growing evidence suggests that microorganisms undergo senescence, and can also exhibit extreme longevity. In this Review, we integrate theoretical and empirical insights to establish a unified perspective on senescence and longevity. We discuss the evolutionary origins, genetic mechanisms and functional consequences of microbial ageing. In addition to having biomedical implications, insights into microbial ageing shed light on the role of ageing in the origin of life and the upper limits to longevity.

Cell aging preserves cellular immortality in the presence of lethal levels of damage

Cellular aging, a progressive functional decline driven by damage accumulation, often culminates in the mortality of a cell lineage. Certain lineages, however, are able to sustain long-lasting immortality, as prominently exemplified by stem cells. Here, we show that Escherichia coli cell lineages exhibit comparable patterns of mortality and immortality. Through single-cell microscopy and microfluidic techniques, we find that these patterns are explained by the dynamics of damage accumulation and asymmetric partitioning between daughter cells. At low damage accumulation rates, both aging and rejuvenating lineages retain immortality by reaching their respective states of physiological equilibrium. We show that both asymmetry and equilibrium are present in repair mutants lacking certain repair chaperones, suggesting that intact repair capacity is not essential for immortal proliferation. We show that this growth equilibrium, however, is displaced by extrinsic damage in a dosage-dependent response. Moreover, we demonstrate that aging lineages become mortal when damage accumulation rates surpass a threshold, whereas rejuvenating lineages within the same population remain immortal. Thus, the processes of damage accumulation and partitioning through asymmetric cell division are essential in the determination of proliferative mortality and immortality in bacterial populations. This study provides further evidence for the characterization of cellular aging as a general process, affecting prokaryotes and eukaryotes alike and according to similar evolutionary constraints.

A study of Escherichia coli shows that bacterial lineages maintain replicative immortality by reaching an equilibrium between aging and rejuvenation; when this equilibrium is disrupted, aging lineages cross their immortality threshold, becoming mortal, while rejuvenating lineages are favored by asymmetry and retain immortality within the same population.

Temporal scaling of aging as an adaptive strategy of Escherichia coli

Natural selection is thought to shape the evolution of aging patterns, although how life-history trajectories orchestrate the inherently stochastic processes associated with aging is unclear. Tracking clonal growth-arrested Escherichia coli cohorts in an homogeneous environment at single-cell resolution, we demonstrate that the Gompertz law of exponential mortality characterizes bacterial lifespan distributions. By disentangling the rate of aging from age-independent components of longevity, we find that increasing cellular maintenance through the general stress pathway reduces the aging rate and rescales the lifespan distribution at the expense of growth. This trade-off between aging and growth underpins the evolutionary tuning of the general stress response pathway in adaptation to the organism's feast-or-famine lifestyle. It is thus necessary to involve both natural selection and stochastic physiology to explain aging patterns.

Stress-induced protein aggregates shape population heterogeneity in bacteria

The concept of phenotypic heterogeneity preparing a subpopulation of isogenic cells to better cope with anticipated stresses has been well established. However, less is known about how stress itself can drive subsequent cellular individualization in clonal populations. In this perspective, we focus on the impact of stress-induced cellular protein aggregates, and how their segregation and disaggregation can act as a deterministic incentive for heterogeneity in the population emerging from a stressed ancestor.