Nonlethal deleterious mutation-induced stress accelerates bacterial aging.

Random mutagenesis, including when it leads to loss of gene function, is a key mechanism enabling microorganisms' long-term adaptation to new environments. However, loss-of-function mutations are often deleterious, triggering, in turn, cellular stress and complex homeostatic stress responses, called "allostasis," to promote cell survival. Here, we characterize the differential impacts of 65 nonlethal, deleterious single-gene deletions on Escherichia coli growth in three different growth environments. Further assessments of select mutants, namely, those bearing single adenosine triphosphate (ATP) synthase subunit deletions, reveal that mutants display reorganized transcriptome profiles that reflect both the environment and the specific gene deletion. We also find that ATP synthase α-subunit deleted (ΔatpA) cells exhibit elevated metabolic rates while having slower growth compared to wild-type (wt) E. coli cells. At the single-cell level, compared to wt cells, individual ΔatpA cells display near normal proliferation profiles but enter a postreplicative state earlier and exhibit a distinct senescence phenotype. These results highlight the complex interplay between genomic diversity, adaptation, and stress response and uncover an "aging cost" to individual bacterial cells for maintaining population-level resilience to environmental and genetic stress; they also suggest potential bacteriostatic antibiotic targets and -as select human genetic diseases display highly similar phenotypes, - a bacterial origin of some human diseases.

Non-genetic inheritance restraint of cell-to-cell variation.

Heterogeneity in physical and functional characteristics of cells (e.g. size, cycle time, growth rate, protein concentration) proliferates within an isogenic population due to stochasticity in intracellular biochemical processes and in the distribution of resources during divisions. Conversely, it is limited in part by the inheritance of cellular components between consecutive generations. Here we introduce a new experimental method for measuring proliferation of heterogeneity in bacterial cell characteristics, based on measuring how two sister cells become different from each other over time. Our measurements provide the inheritance dynamics of different cellular properties, and the 'inertia' of cells to maintain these properties along time. We find that inheritance dynamics are property specific and can exhibit long-term memory (∼10 generations) that works to restrain variation among cells. Our results can reveal mechanisms of non-genetic inheritance in bacteria and help understand how cells control their properties and heterogeneity within isogenic cell populations.

All the different forms of life on our planet ­ including animals, plants, fungi and bacteria ­ tend to grow, multiply and expand. This happens through a process called cell division, where one cell becomes two; two cells become four; four cells become eight; and so on. Each dividing cell passes on the same set of genetic instructions to its two daughter cells in the form of DNA. Its remaining contents, made up of a mixture of proteins, RNA and other chemicals, also get divided up equally between the two new cells. This division of cellular assets establishes a form of 'cellular memory', where daughter cells retain very similar properties to their ancestors, which helps them remain stable over time. Yet this memory can fade, and small changes in how a cell looks or acts can appear over many generations of cell division. This happens even when the exact same set of DNA-based genetic instructions have been passed down to daughter cells, confirming that other factors aside from DNA do influence cellular properties and can act to maintain them or introduce variation over time. Here, Vashistha, Kohram and Salman set out to understand how long cellular memory could be maintained in dividing E. coli bacteria. To do this, they created a technique to track cellular memory as it passed down from a single mother cell to two daughter cells over dozens of generations. Using this technique, Vashistha, Kohram and Salman found that some inherited elements, including cell size and the time cells took to divide, were maintained between mother and daughter cells for almost 10 generations. Other elements, such as the density of proteins inside each cell, started changing almost immediately after daughter cells were formed, and only remained similar for about two generations. These findings suggest that cellular memory may be long, but is not infinite, and that inheritance of non-genetic elements can help maintain cellular memory and reduce variation among new-born cells for considerable number of generations. Building on this research to achieve a better understanding of cellular memory may allow researchers to harness these insights to direct the evolution of different cellular properties over time. This could have a wide range of potential applications, such as designing new infection control measures for viruses or bacteria; enhancing our ability to grow working organs for tissue transplant; or improving the texture and consistency of cultured, lab-grown meat.

Bacterial Growth Control Mechanisms Inferred from Multivariate Statistical Analysis of Single-Cell Measurements.

Analysis of single-cell measurements of bacterial growth and division often relied on testing preconceived models of cell size control mechanisms. Such an approach could limit the scope of data analysis and prevent us from uncovering new information. Here, we take an "agnostic" approach by applying regression methods to multiple simultaneously measured cellular variables, which allow us to infer dependencies among those variables from their apparent correlations. Besides previously observed correlations attributed to particular cell size control mechanisms, we identify dependencies that point to potentially new mechanisms. In particular, cells born smaller than their sisters tend to grow faster and make up for the size difference acquired during division. We also find that sister cells are correlated beyond what single-cell, size-control models predict. These trends are consistently found in repeat experiments, although the dependencies vary quantitatively. Such variation highlights the sensitivity of cell growth to environmental variations and the limitation of currently used experimental setups.

Adjustment in tumbling rates improves bacterial chemotaxis on obstacle-laden terrains.

The mechanisms of bacterial chemotaxis have been extensively studied for several decades, but how the physical environment influences the collective migration of bacterial cells remains less understood. Previous models of bacterial chemotaxis have suggested that the movement of migrating bacteria across obstacle-laden terrains may be slower compared with terrains without them. Here, we show experimentally that the size or density of evenly spaced obstacles do not alter the average exit rate of Escherichia coli cells from microchambers in response to external attractants, a function that is dependent on intact cell-cell communication. We also show, both by analyzing a revised theoretical model and by experimentally following single cells, that the reduced exit time in the presence of obstacles is a consequence of reduced tumbling frequency that is adjusted by the E. coli cells in response to the topology of their environment. These findings imply operational short-term memory of bacteria while moving through complex environments in response to chemotactic stimuli and motivate improved algorithms for self-autonomous robotic swarms.

Individuality and slow dynamics in bacterial growth homeostasis.

Microbial growth and division are fundamental processes relevant to many areas of life science. Of particular interest are homeostasis mechanisms, which buffer growth and division from accumulating fluctuations over multiple cycles. These mechanisms operate within single cells, possibly extending over several division cycles. However, all experimental studies to date have relied on measurements pooled from many distinct cells. Here, we disentangle long-term measured traces of individual cells from one another, revealing subtle differences between temporal and pooled statistics. By analyzing correlations along up to hundreds of generations, we find that the parameter describing effective cell size homeostasis strength varies significantly among cells. At the same time, we find an invariant cell size, which acts as an attractor to all individual traces, albeit with different effective attractive forces. Despite the common attractor, each cell maintains a distinct average size over its finite lifetime with suppressed temporal fluctuations around it, and equilibration to the global average size is surprisingly slow ([Formula: see text] cell cycles). To show a possible source of variable homeostasis strength, we construct a mathematical model relying on intracellular interactions, which integrates measured properties of cell size with those of highly expressed proteins. Effective homeostasis strength is then influenced by interactions and by noise levels and generally varies among cells. A predictable and measurable consequence of variable homeostasis strength appears as distinct oscillatory patterns in cell size and protein content over many generations. We discuss implications of our results to understanding mechanisms controlling division in single cells and their characteristic timescales.

Interactions and Translational Dynamics of Phosphatidylinositol Bisphosphate (PIP2) Lipids in Asymmetric Lipid Bilayers.

Phosphatidylinositol phosphate (PIP) lipids are critical to many cell signaling pathways, in part by acting as molecular beacons that recruit peripheral membrane proteins to specific locations within the plasma membrane. Understanding the biophysics of PIP-protein interactions is critical to developing a chemically detailed model of cell communication. Resolving such interactions is challenging, even in model membrane systems, because of the difficulty in preparing PIP-containing membranes with high fluidity and integrity. Here we report on a simple, vesicle-based protocol for preparing asymmetric supported lipid bilayers in which fluorescent PIP lipid analogues are found only on the top leaflet of the supported membrane facing the bulk solution. With this asymmetric distribution of lipids between the leaflets, the fluorescent signal from the PIP lipid analogue reports directly on interactions between the peripheral molecules and the top leaflet of the membrane. Asymmetric PIP-containing bilayers are an ideal platform to investigate the interaction of PIP with peripheral membrane proteins using fluorescence-based imaging approaches. We demonstrate their usefulness here with a combined fluorescence correlation spectroscopy and single particle tracking study of the interaction between PIP2 lipids and a polycationic polymer, quaternized polyvinylpyridine (QPVP). With this approach we are able to quantify the microscopic features of the mobility coupling between PIP2 lipids and polybasic QPVP. With single particle tracking we observe individual PIP2 lipids switch from Brownian to intermittent motion as they become transiently trapped by QPVP.