High-content imaging for compound and genetic profiling is popular for drug discovery but limited to endpoint images of fixed cells. Conversely, electronic-based devices offer label-free, live cell functional information but suffer from limited spatial resolution or throughput. Here, we introduce a semiconductor 96-microplate platform for high-resolution, real-time impedance imaging. Each well features 4096 electrodes at 25 µm spatial resolution and a miniaturized data interface allows 8× parallel plate operation (768 total wells) for increased throughput. Electric field impedance measurements capture >20 parameter images including cell barrier, attachment, flatness, and motility every 15 min during experiments. We apply this technology to characterize 16 cell types, from primary epithelial to suspension cells, and quantify heterogeneity in mixed co-cultures. Screening 904 compounds across 13 semiconductor microplates reveals 25 distinct responses, demonstrating the platform’s potential for mechanism of action profiling. The scalability and translatability of this semiconductor platform expands high-throughput mechanism of action profiling and phenotypic drug discovery applications.

Evolution of complex communities of coexisting microbes remains poorly understood. The long-term evolution experiment on Escherichia coli (LTEE) revealed the spontaneous emergence of stable coexistence of multiple ecotypes, which persisted for more than 14,000 generations of continuous evolution. Here, using a combination of experiments and computer simulations, we show that the emergence and persistence of this phenomenon can be explained by the combination of two interacting trade-offs, rooted in biochemical constraints: First, faster growth is enabled by higher fermentation and obligate acetate excretion. Second, faster growth results in longer lag times when utilizing acetate after glucose is depleted. This combination creates an ecological niche for a slower-growing ecotype, specialized in switching to acetate. These findings demonstrate that trade-offs can give rise to surprisingly complex communities with evolutionarily stable coexistence of multiple variants in even the simplest environments.

Bacteria reorganize their physiology upon entry to stationary phase. What part of this reorganization improves starvation survival is a difficult question because the change in physiology includes a global reorganization of the proteome, envelope, and metabolism of the cell. In this work, we used several trade-offs between fast growth and long survival to statistically score over 2,000 Escherichia coli proteins for their global correlation with death rate. The combined ranking allowed us to narrow down the set of proteins that positively correlate with survival and validate the causal role of a subset of proteins. Remarkably, we found that important survival genes are related to the cell envelope, i.e., periplasm and outer membrane, because the maintenance of envelope integrity of E. coli plays a crucial role during starvation. Our results uncover a new protective feature of the outer membrane that adds to the growing evidence that the outer membrane is not only a barrier that prevents abiotic substances from reaching the cytoplasm but also essential for bacterial proliferation and survival.

Adaptive stress resistance in microbes is mostly attributed to the expression of stress response genes, including heat-shock proteins. Here, we report a response of E. coli to heat stress caused by degradation of an enzyme in the methionine biosynthesis pathway (MetA). While MetA degradation can inhibit growth, which by itself is detrimental for fitness, we show that it directly benefits survival at temperatures exceeding 50°C, increasing survival chances by more than 1,000-fold. Using both experiments and mathematical modeling, we show quantitatively how protein expression, degradation rates, and environmental stressors cause long-term growth inhibition in otherwise habitable conditions. Because growth inhibition can be abolished with simple mutations, namely point mutations of MetA and protease knockouts, we interpret the breakdown of methionine synthesis as a system that has evolved to halt growth at high temperatures, analogous to “thermal fuses” in engineering that shut off electricity to prevent overheating.

Electrode-based impedance and electrochemical measurements can provide cell-biology information that is difficult to obtain using optical-microscopy techniques. Such electrical methods are non-invasive, label-free, and continuous, eliminating the need for fluorescence reporters and overcoming optical imaging's throughput/temporal resolution limitations. Nonetheless, electrode-based techniques have not been heavily employed because devices typically contain few electrodes per well, resulting in noisy aggregate readouts. Complementary metal-oxide-semiconductor (CMOS) microelectrode arrays (MEAs) have sometimes been used for electrophysiological measurements with thousands of electrodes per well at sub-cellular pitches, but only basic impedance mappings of cell attachment have been performed outside of electrophysiology. Here, we report on new field-based impedance mapping and electrochemical mapping/patterning techniques to expand CMOS-MEA cell-biology applications. The methods enable accurate measurement of cell attachment, growth/wound healing, cell–cell adhesion, metabolic state, and redox properties with single-cell spatial resolution (20 μm electrode pitch). These measurements allow the quantification of adhesion and metabolic differences of cells expressing oncogenes versus wild-type controls. The multi-parametric, cell-population statistics captured by the chip-scale integrated device opens up new avenues for fully electronic high-throughput live-cell assays for phenotypic screening and drug discovery applications.

Central carbon metabolism is highly conserved across microbial species, but can catalyze very different pathways depending on the organism and their ecological niche. Here, we study the dynamic reorganization of central metabolism after switches between the two major opposing pathway configurations of central carbon metabolism, glycolysis, and gluconeogenesis in Escherichia coli, Pseudomonas aeruginosa, and Pseudomonas putida. We combined growth dynamics and dynamic changes in intracellular metabolite levels with a coarse-grained model that integrates fluxes, regulation, protein synthesis, and growth and uncovered fundamental limitations of the regulatory network: After nutrient shifts, metabolite concentrations collapse to their equilibrium, rendering the cell unable to sense which direction the flux is supposed to flow through the metabolic network. The cell can partially alleviate this by picking a preferred direction of regulation at the expense of increasing lag times in the opposite direction. Moreover, decreasing both lag times simultaneously comes at the cost of reduced growth rate or higher futile cycling between metabolic enzymes. These three trade-offs can explain why microorganisms specialize for either glycolytic or gluconeogenic substrates and can help elucidate the complex growth patterns exhibited by different microbial species.

The majority of microbes on earth, whether they live in the ocean, the soil or in animals, are not growing, but instead struggling to survive starvation^1–6. Some genes and environmental conditions affecting starvation survival have been identified^7–13, but despite almost a century of study^14–16, we do not know which processes lead to irreversible loss of viability, which maintenance processes counteract them and how lifespan is determined from the balance of these opposing processes. Here, we used time-lapse microscopy to capture and characterize the cell death process of E. coli during carbon starvation for the first time. We found that a lack of nutrients results in the collapse of ion homeostasis, triggering a positive-feedback cascade of osmotic swelling and membrane permeabilization that ultimately results in lysis. Based on these findings, we hypothesized that ion transport is the major energetic requirement for starving cells and the primary determinant of the timing of lysis. We therefore developed a mathematical model that integrates ion homeostasis and ‘cannibalistic’ nutrient recycling from perished cells^16,17 to predict lifespan changes under diverse conditions, such as changes of cell size, medium composition, and prior growth conditions. Guided by model predictions, we found that cell death during starvation could be dramatically slowed by replacing inorganic ions from the medium with a non-permeating osmoprotectant, removing the cost of ion homeostasis and preventing lysis. Our quantitative and predictive model explains how survival kinetics are determined in starvation and elucidates the mechanistic underpinnings of starvation survival.

Cell mass and chemical composition are important aggregate cellular properties that are especially relevant to physiological processes, such as growth control and tissue homeostasis. Despite their importance, it has been difficult to measure these features quantitatively at the individual cell level in intact tissue. Here, we introduce normalized Raman imaging (NoRI), a stimulated Raman scattering (SRS) microscopy method that provides the local concentrations of protein, lipid, and water from live or fixed tissue samples with high spatial resolution. Using NoRI, we demonstrate that protein, lipid, and water concentrations at the single cell are maintained in a tight range in cells under the same physiological conditions and are altered in different physiological states, such as cell cycle stages, attachment to substrates of different stiffness, or by entering senescence. In animal tissues, protein and lipid concentration varies with cell types, yet an unexpected cell-to-cell heterogeneity was found in cerebellar Purkinje cells. The protein and lipid concentration profile provides means to quantitatively compare disease-related pathology, as demonstrated using models of Alzheimer’s disease. This demonstration shows that NoRI is a broadly applicable technique for probing the biological regulation of protein mass, lipid mass, and water mass for studies of cellular and tissue growth, homeostasis, and disease.

The rate of cell growth is crucial for bacterial fitness and drives the allocation of bacterial resources, affecting, for example, the expression levels of proteins dedicated to metabolism and biosynthesis. It is unclear, however, what ultimately determines growth rates in different environmental conditions. Moreover, increasing evidence suggests that other objectives are also important, such as the rate of physiological adaptation to changing environments. A common challenge for cells is that these objectives cannot be independently optimized, and maximizing one often reduces another. Many such trade-offs have indeed been hypothesized on the basis of qualitative correlative studies. Here we report a trade-off between steady-state growth rate and physiological adaptability in Escherichia coli, observed when a growing culture is abruptly shifted from a preferred carbon source such as glucose to fermentation products such as acetate. These metabolic transitions, common for enteric bacteria, are often accompanied by multi-hour lags before growth resumes. Metabolomic analysis reveals that long lags result from the depletion of key metabolites that follows the sudden reversal in the central carbon flux owing to the imposed nutrient shifts. A model of sequential flux limitation not only explains the observed trade-off between growth and adaptability, but also allows quantitative predictions regarding the universal occurrence of such tradeoffs, based on the opposing enzyme requirements of glycolysis versus gluconeogenesis. We validate these predictions experimentally for many different nutrient shifts in E. coli, as well as for other respiro-fermentative microorganisms, including Bacillus subtilis and Saccharomyces cerevisiae.

Elucidating strategies of resource allocation and metabolism is crucial for a better understanding of microbial phenotypes. In particular, uncovering the governing principles underlying these processes would be a crucial step for achieving a central aim of systems microbiology, which is to quantitatively predict phenotypes of microbial cells or entire populations in diverse conditions. Here, some of the key concepts for understanding cellular resource allocation and metabolism that have been suggested over the past years are reviewed. In particular, recent experimental studies that have shown how phenotypic patterns from orthogonal genetic and environmental perturbations can help to differentiate between competing hypotheses and their respective predictions are discussed. Phenomenological models have proven to be a valuable addition to genome-scale models, capable of making quantitative predictions with only few parameters and having aided the identification of molecular mechanisms.

Overflow metabolism in the presence of oxygen occurs at fast growth rates in a wide range of organisms including bacteria, yeast and cancer cells and plays an important role in biotechnology during production of proteins or metabolic compounds. As recently suggested, overflow metabolism can be understood in terms of proteome allocation, since fermentation has lower proteome cost for energy production than respiration. Here, we demonstrate that ArcA overexpression in aerobic conditions, results in downregulation of respiratory pathways and enhanced growth rates on glycolytic substrates of E. coli, coinciding with acetate excretion and increased carbon uptake rates. These results suggest that fermentation enables faster growth and demonstrate that fermentation on many glycolytic carbon sources is not limited by carbon uptake. Hence, these findings are difficult to reconcile with many alternative hypotheses that have been proposed for the origin of overflow metabolism and the growth rate dependence of fermentation and respiration, which are based on limited capacity of respiration or limitations in uptake rates and catabolic pathways. Instead, as suggested by increased lag phases of ArcA overexpression strains, respiratory energy metabolism may be related to a general preparatory response, observed for decreasing growth rates, but with limited advantages for maximizing steady-state growth rate.

Overflow metabolism refers to the seemingly wasteful strategy in which cells use fermentation instead of the more efficient respiration to generate energy, despite the availability of oxygen. Known as the Warburg effect in the context of cancer growth, this phenomenon occurs ubiquitously for fast-growing cells, including bacteria, fungi and mammalian cells, but its origin has remained unclear despite decades of research. Here we study metabolic overflow in Escherichia coli, and show that it is a global physiological response used to cope with changing proteomic demands of energy biogenesis and biomass synthesis under different growth conditions. A simple model of proteomic resource allocation can quantitatively account for all of the observed behaviours, and accurately predict responses to new perturbations. The key hypothesis of the model, that the proteome cost of energy biogenesis by respiration exceeds that by fermentation, is quantitatively confirmed by direct measurement of protein abundances via quantitative mass spectrometry.

Understanding how the homeostasis of cellular size and composition is accomplished by different organisms is an outstanding challenge in biology. For exponentially growing Escherichia coli cells, it is long known that the size of cells exhibits a strong positive relation with their growth rates in different nutrient conditions. Here, we characterized cell sizes in a set of orthogonal growth limitations. We report that cell size and mass exhibit positive or negative dependences with growth rate depending on the growth limitation applied. In particular, synthesizing large amounts of “useless” proteins led to an inversion of the canonical, positive relation, with slow growing cells enlarged 7‐ to 8‐fold compared to cells growing at similar rates under nutrient limitation. Strikingly, this increase in cell size was accompanied by a 3‐ to 4‐fold increase in cellular DNA content at slow growth, reaching up to an amount equivalent to ~8 chromosomes per cell. Despite drastic changes in cell mass and macromolecular composition, cellular dry mass density remained constant. Our findings reveal an important role of protein synthesis in cell division control.

A central aim of cell biology was to understand the strategy of gene expression in response to the environment. Here, we study gene expression response to metabolic challenges in exponentially growing Escherichia coli using mass spectrometry. Despite enormous complexity in the details of the underlying regulatory network, we find that the proteome partitions into several coarse‐grained sectors, with each sector's total mass abundance exhibiting positive or negative linear relations with the growth rate. The growth rate‐dependent components of the proteome fractions comprise about half of the proteome by mass, and their mutual dependencies can be characterized by a simple flux model involving only two effective parameters. The success and apparent generality of this model arises from tight coordination between proteome partition and metabolism, suggesting a principle for resource allocation in proteome economy of the cell. This strategy of global gene regulation should serve as a basis for future studies on gene expression and constructing synthetic biological circuits. Coarse graining may be an effective approach to derive predictive phenomenological models for other ‘omics’ studies.

Cells migrate collectively during development, wound healing, and cancer metastasis. Recently, a method has been developed to recover intercellular stress in monolayers from measured traction forces upon the substrate. To calculate stress maps in two dimensions, the cell sheet was assumed to behave like an elastic material, and it remains unclear to what extent this assumption is valid. In this study, we simulate our recently developed model for collective cell migration, and compute intercellular stress maps using the method employed in the experiments. We also compute these maps using a method that does not depend on the traction forces or material properties. The two independently obtained stress patterns agree well for the parameters we have probed and provide a verification of the validity of the experimental method.

In wound healing assays, a monolayer of epithelial cells is allowed to migrate onto empty surface area. When the motile cells close the artificial wound, the edge of the tissue does usually not move uniformly but characteristic fingerlike protrusions are observed. We model the collectively moving cells as a system of self-propelled particles using the Toner-Tu equations for an active fluid. A linear stability analysis of perturbations at the tissue edge reveals an instability in the disordered nonmoving state. The instability is purely due to spontaneous motility and velocity alignment between cells. It can account for finger formation in wound healing experiments.

Interfaces between stratified epithelia and their supporting stromas commonly exhibit irregular shapes. Undulations are particularly pronounced in dysplastic tissues and typically evolve into long, finger-like protrusions in carcinomas. In previous work (Basan et al 2011 Phys. Rev. Lett. 106 158101), we demonstrated that an instability arising from viscous shear stresses caused by the constant flow due to cell turnover in the epithelium could drive this phenomenon. While interfacial tension between the two tissues as well as mechanical resistance of the stroma tend to maintain a flat interface, an instability occurs for sufficiently large viscosity, cell-division rate and thickness of the dividing region in the epithelium. Here, extensions of this work are presented, where cell division in the epithelium is coupled to the local concentration of nutrients or growth factors diffusing from the stroma. This enhances the instability by a mechanism similar to that of the Mullins–Sekerka instability in single-diffusion processes of crystal growth. We furthermore present the instability for the generalized case of a viscoelastic stroma.