High-throughput measurement of single-cell growth rates using serial microfluidic mass sensor arrays

Mutation and cell state compatibility is required and targetable in Ph+ acute lymphoblastic leukemia minimal residual disease

Efforts to cure BCR::ABL1 B cell acute lymphoblastic leukemia (Ph+ ALL) solely through inhibition of ABL1 kinase activity have thus far been insufficient despite the availability of tyrosine kinase inhibitors (TKIs) with broad activity against resistance mutants. The mechanisms that drive persistence within minimal residual disease (MRD) remain poorly understood and therefore untargeted. Utilizing 13 patient-derived xenograft (PDX) models and clinical trial specimens of Ph+ ALL, we examined how genetic and transcriptional features co-evolve to drive progression during prolonged TKI response. Our work reveals a landscape of cooperative mutational and transcriptional escape mechanisms that differ from those causing resistance to first generation TKIs. By analyzing MRD during remission, we show that the same resistance mutation can either increase or decrease cellular fitness depending on transcriptional state. We further demonstrate that directly targeting transcriptional state-associated vulnerabilities at MRD can overcome BCR::ABL1 independence, suggesting a new paradigm for rationally eradicating MRD prior to relapse. Finally, we illustrate how cell mass measurements of leukemia cells can be used to rapidly monitor dominant transcriptional features of Ph+ ALL to help rationally guide therapeutic selection from low-input samples.

Morphological Stability for in silico Models of Avascular Tumors

The landscape of computational modeling in cancer systems biology is diverse, offering a spectrum of models and frameworks, each with its own trade-offs and advantages. Ideally, models are meant to be useful in refining hypotheses, to sharpen experimental procedures and, in the longer run, even for applications in personalized medicine. One of the greatest challenges is to balance model realism and detail with experimental data to eventually produce useful data-driven models. We contribute to this quest by developing a transparent, highly parsimonious, first principle in silico model of a growing avascular tumor. We initially formulate the physiological considerations and the specific model within a stochastic cell-based framework. We next formulate a corresponding mean-field model using partial differential equations which is amenable to mathematical analysis. Despite a few notable differences between the two models, we are in this way able to successfully detail the impact of all parameters in the stability of the growth process and on the eventual tumor fate of the stochastic model. This facilitates the deduction of Bayesian priors for a given situation, but also provides important insights into the underlying mechanism of tumor growth and progression. Although the resulting model framework is relatively simple and transparent, it can still reproduce the full range of known emergent behavior. We identify a novel model instability arising from nutrient starvation and we also discuss additional insight concerning possible model additions and the effects of those. Thanks to the framework's flexibility, such additions can be readily included whenever the relevant data become available.

Microfluidic technologies for advanced antimicrobial susceptibility testing

Antimicrobial resistance is getting serious and becoming a threat to public health worldwide. The improper and excessive use of antibiotics is responsible for this situation. The standard methods used in clinical laboratories, to diagnose bacterial infections, identify pathogens, and determine susceptibility profiles, are time-consuming and labor-intensive, leaving the empirical antimicrobial therapy as the only option for the first treatment. To prevent the situation from getting worse, evidence-based therapy should be given. The choosing of effective drugs requires powerful diagnostic tools to provide comprehensive information on infections. Recent progress in microfluidics is pushing infection diagnosis and antimicrobial susceptibility testing (AST) to be faster and easier. This review summarizes the recent development in microfluidic assays for rapid identification and AST in bacterial infections. Finally, we discuss the perspective of microfluidic-AST to develop the next-generation infection diagnosis technologies.

Circulating tumor cells shed large extracellular vesicles in capillary-sized bifurcations

Circulating tumor cells (CTCs) and their clusters are the drivers of metastasis, but their interactions with capillary beds are poorly understood. Using microfluidic models mimicking human capillary bifurcations, we observed cell size- and bifurcation-dependent shedding of nuclei-free fragments by patient CTCs, CTC-derived explant cells and numerous cancer cell lines. Shedding reduced cell sizes up to 61%, facilitating their transit through bifurcations. We demonstrated that shed fragments were a novel class of large extracellular vesicles (LEVs), whose proteome was associated with immune-related and signaling pathways. LEVs were internalized by endothelial and immune cells, disrupted endothelial barrier integrity and polarized monocytes into M2 tumor-promoting macrophages. Cumulatively, these findings suggest that CTCs shed LEVs in capillary beds that drive key processes involved in the formation of pre-metastatic niches.

Resource allocation in mammalian systems

Cells execute biological functions to support phenotypes such as growth, migration, and secretion. Complementarily, each function of a cell has resource costs that constrain phenotype. Resource allocation by a cell allows it to manage these costs and optimize their phenotypes. In fact, the management of resource constraints (e.g., nutrient availability, bioenergetic capacity, and macromolecular machinery production) shape activity and ultimately impact phenotype. In mammalian systems, quantification of resource allocation provides important insights into higher-order multicellular functions; it shapes intercellular interactions and relays environmental cues for tissues to coordinate individual cells to overcome resource constraints and achieve population-level behavior. Furthermore, these constraints, objectives, and phenotypes are context-dependent, with cells adapting their behavior according to their microenvironment, resulting in distinct steady-states. This review will highlight the biological insights gained from probing resource allocation in mammalian cells and tissues.

Monitoring the mass, eigenfrequency, and quality factor of mammalian cells

The regulation of mass is essential for the development and homeostasis of cells and multicellular organisms. However, cell mass is also tightly linked to cell mechanical properties, which depend on the time scales at which they are measured and change drastically at the cellular eigenfrequency. So far, it has not been possible to determine cell mass and eigenfrequency together. Here, we introduce microcantilevers oscillating in the Ångström range to monitor both fundamental physical properties of the cell. If the oscillation frequency is far below the cellular eigenfrequency, all cell compartments follow the cantilever motion, and the cell mass measurements are accurate. Yet, if the oscillating frequency approaches or lies above the cellular eigenfrequency, the mechanical response of the cell changes, and not all cellular components can follow the cantilever motions in phase. This energy loss caused by mechanical damping within the cell is described by the quality factor. We use these observations to examine living cells across externally applied mechanical frequency ranges and to measure their total mass, eigenfrequency, and quality factor. The three parameters open the door to better understand the mechanobiology of the cell and stimulate biotechnological and medical innovations.

Characterizing induced pluripotent stem cells and derived cardiomyocytes: insights from nano scale mass measurements and mechanical properties

Our study reveals that the nano-mechanical measures of elasticity and cell mass change significantly through induced pluripotent stem cell (iPSC) differentiation to cardiomyocytes, providing a reliable method to evaluate such processes. The findings support the importance of identifying these properties, and highlight the potential of AFM for comprehensive characterization of iPSC at the nanoscale.

Recent Advances in Construction Strategies for Fluorescence Sensing Films

A year ago, film-based fluorescent sensors (FFSs) were recognized in the "IUPAC Top Ten Emerging Technologies in Chemistry 2022" due to their extensive application in detecting hidden explosives, illicit drugs, and volatile organic compounds. These sensors offer high sensitivity, specificity, immunity to light scattering, and noninvasiveness. The core of FFSs is the construction of high-performance fluorescent sensing films, which are dependent on the processes of "energy transfer" and "mass transfer" in the active layer and involve complex interactions between sensing molecules and analytes. This Perspective focuses on the latest strategies in constructing these films, emphasizing the design of sensing molecules with various innovative features and structures that enhance the mass transfer efficiency. Additionally, it discusses the ongoing challenges and potential advancements in the field of FFSs.

Fiber-Integrated Force Sensor using 3D Printed Spring-Composed Fabry-Perot Cavities with a High Precision Down to Tens of Piconewton

Developing microscale sensors capable of force measurements down to the scale of piconewtons is of fundamental importance for a wide range of applications. To date, advanced instrumentations such as atomic force microscopes and other specifically developed micro/nano-electromechanical systems face challenges such as high cost, complex detection systems and poor electromagnetic compatibility. Here, it presents the unprecedented design and 3D printing of general fiber-integrated force sensors using spring-composed Fabry-Perot cavities. It calibrates these microscale devices employing varied-diameter μ $\umu$ m-scale silica particles as standard weights. The force sensitivity and resolution reach values of (0.436 ± 0.007) nmnN-1 and (40.0 ± 0.7) pN, respectively, which are the best resolutions among all fiber-based nanomechanical probes so far. It also measured the non-linear airflow force distributions produced from a nozzle with an orifice of 2 μ $\umu$ m, which matches well with the full-sized simulations. With further customization of their geometries and materials, it anticipates the easy-to-use force probe can well extend to many other applications such as air/fluidic turbulences sensing, micro-manipulations, and biological sensing.

Measuring Drug Response with Single-Cell Growth Rate Quantification

Intratumoral heterogeneity is a substantial cause of drug resistance development during chemotherapy or other drug treatments for cancer. Therefore, monitoring and measuring cell exposure and response to drugs at the single-cell level are crucial. Previous research suggested that the single-cell growth rate can be used to investigate drug-cell interactions. However, currently established methods for quantifying single-cell growth are limited to isolated or monolayer cells. Here, we introduce a technique that accurately measures both 2D and 3D cell growth rates using label-free ratiometric stimulated Raman scattering (SRS) microscopy. We use deuterated amino acids, leucine, isoleucine, and valine, as tracers and measure the C-D SRS signal from deuterium-labeled proteins and the C-H SRS signal from unlabeled proteins simultaneously to determine the cell growth rate at the single-cell level. The technique offers single-cell level drug sensitivity measurement with a shorter turnaround time (within 12 h) than most traditional assays. The submicrometer resolution of the imaging technique allows us to examine the effects of chemotherapeutic drugs, including kinase inhibitors, mitotic inhibitors, and topoisomerase II inhibitors, on both the cell growth rate and morphology. The capability of quantifying 3D cell growth rates provides insight into a deeper understanding of the cell-drug interaction in the actual tumor environment.

Accurate Prediction of Antimicrobial Susceptibility for Point-of-Care Testing of Urine in Less than 90 Minutes via iPRISM Cassettes

The extensive and improper use of antibiotics has led to a dramatic increase in the frequency of antibiotic resistance among human pathogens, complicating infectious disease treatments. In this work, a method for rapid antimicrobial susceptibility testing (AST) is presented using microstructured silicon diffraction gratings integrated into prototype devices, which enhance bacteria-surface interactions and promote bacterial colonization. The silicon microstructures act also as optical sensors for monitoring bacterial growth upon exposure to antibiotics in a real-time and label-free manner via intensity-based phase-shift reflectometric interference spectroscopic measurements (iPRISM). Rapid AST using clinical isolates of Escherichia coli (E. coli) from urine is established and the assay is applied directly on unprocessed urine samples from urinary tract infection patients. When coupled with a machine learning algorithm trained on clinical samples, the iPRISM AST is able to predict the resistance or susceptibility of a new clinical sample with an Area Under the Receiver Operating Characteristic curve (AUC) of ∼ 0.85 in 1 h, and AUC > 0.9 in 90 min, when compared to state-of-the-art automated AST methods used in the clinic while being an order of magnitude faster.

Single-cell mass distributions reveal simple rules for achieving steady-state growth

IMPORTANCE

Microbiologists have watched clear liquid turn cloudy for over 100 years. While the cloudiness of a culture is proportional to its total biomass, growth rates from optical density measurements are challenging to interpret when cells change size. Many bacteria adjust their size at different steady-state growth rates, but also when shifting between starvation and growth. Optical density cannot disentangle how mass is distributed among cells. Here, we use single-cell mass measurements to demonstrate that a population of cells in batch culture achieves a stable mass distribution for only a short period of time. Achieving steady-state growth in rich medium requires low initial biomass concentrations and enough time for individual cell mass accumulation and cell number increase via cell division to balance out. Steady-state growth is important for reliable cell mass distributions and experimental reproducibility. We discuss how mass variation outside of steady-state can impact physiology, ecology, and evolution experiments.

Acoustic tweezers for high-throughput single-cell analysis

Acoustic tweezers provide an effective means for manipulating single cells and particles in a high-throughput, precise, selective and contact-free manner. The adoption of acoustic tweezers in next-generation cellular assays may advance our understanding of biological systems. Here we present a comprehensive set of instructions that guide users through device fabrication, instrumentation setup and data acquisition to study single cells with an experimental throughput that surpasses traditional methods, such as atomic force microscopy and micropipette aspiration, by several orders of magnitude. With acoustic tweezers, users can conduct versatile experiments that require the trapping, patterning, pairing and separation of single cells in a myriad of applications ranging across the biological and biomedical sciences. This procedure is widely generalizable and adaptable for investigations in materials and physical sciences, such as the spinning motion of colloids or the development of acoustic-based quantum simulations. Overall, the device fabrication requires ~12 h, the experimental setup of the acoustic tweezers requires 1-2 h and the cell manipulation experiment requires ~30 min to complete. Our protocol is suitable for use by interdisciplinary researchers in biology, medicine, engineering and physics.

The Hypothesis of a "Living Pulse" in Cells

Motility is a great biosignature and its pattern is characteristic for specific microbes. However, motion does also occur within the cell by the myriads of ongoing processes within the cell and the exchange of gases and nutrients with the outside environment. Here, we propose that the sum of these processes in a microbial cell is equivalent to a pulse in complex organisms and suggest a first approach to measure the "living pulse" in microorganisms. We emphasize that if a "living pulse" can be shown to exist, it would have far-reaching applications, such as for finding life in extreme environments on Earth and in extraterrestrial locations, as well as making sure that life is not present where it should not be, such as during medical procedures and in the food processing industry.

Mycobacterium tuberculosis grows linearly at the single-cell level with larger variability than model organisms

The ability of bacterial pathogens to regulate growth is crucial to control homeostasis, virulence, and drug response. Yet, we do not understand the growth and cell cycle behaviors of Mycobacterium tuberculosis (Mtb), a slow-growing pathogen, at the single-cell level. Here, we use time-lapse imaging and mathematical modeling to characterize these fundamental properties of Mtb. Whereas most organisms grow exponentially at the single-cell level, we find that Mtb exhibits a unique linear growth mode. Mtb growth characteristics are highly variable from cell-to-cell, notably in their growth speeds, cell cycle timing, and cell sizes. Together, our study demonstrates that growth behavior of Mtb diverges from what we have learned from model bacteria. Instead, Mtb generates a heterogeneous population while growing slowly and linearly. Our study provides a new level of detail into how Mtb grows and creates heterogeneity, and motivates more studies of growth behaviors in bacterial pathogens.

Tailoring the Sensitivity of Microcantilevers To Monitor the Mass of Single Adherent Living Cells

Microcantilevers are widely employed as mass sensors for biological samples, from single molecules to single cells. However, the accurate mass quantification of living adherent cells is impaired by the microcantilever's mass sensitivity and cell migration, both of which can lead to detect masses mismatching by ≫50%. Here, we design photothermally actuated microcantilevers to optimize the accuracy of cell mass measurements. By reducing the inertial mass of the microcantilever using a focused ion beam, we considerably increase its mass sensitivity, which is validated by finite element analysis and experimentally by gelatin microbeads. The improved microcantilevers allow us to instantly monitor at much improved accuracy the mass of both living HeLa cells and mouse fibroblasts adhering to different substrates. Finally, we show that the improved cantilever design favorably restricts cell migration and thus reduces the large measurement errors associated with this effect.

SERS-based antibiotic susceptibility testing: Towards point-of-care clinical diagnosis

Emerging antibiotic resistant bacteria constitute one of the biggest threats to public health. Surface-enhanced Raman scattering (SERS) is highly promising for detecting such bacteria and for antibiotic susceptibility testing (AST). SERS is fast, non-destructive (can probe living cells) and it is technologically flexible (readily integrated with robotics and machine learning algorithms). However, in order to integrate into efficient point-of-care (PoC) devices and to effectively replace the current culture-based methods, it needs to overcome the challenges of reliability, cost and complexity. Recently, significant progress has been made with the emergence of both new questions and new promising directions of research and technological development. This article brings together insights from several representative SERS-based AST studies and approaches oriented towards clinical PoC biosensing. It aims to serve as a reference source that can guide progress towards PoC routines for identifying antibiotic resistant pathogens. In turn, such identification would help to trace the origin of sporadic infections, in order to prevent outbreaks and to design effective medical treatment and preventive procedures.

Assessing the growth kinetics and stoichiometry of Escherichia coli at the single-cell level

Microfluidic cultivation and single-cell analysis are inherent parts of modern microbial biotechnology and microbiology. However, implementing biochemical engineering principles based on the kinetics and stoichiometry of growth in microscopic spaces remained unattained. We here present a novel integrated framework that utilizes distinct microfluidic cultivation technologies and single-cell analytics to make the fundamental math of process-oriented biochemical engineering applicable at the single-cell level. A combination of non-invasive optical cell mass determination with sub-pg sensitivity, microfluidic perfusion cultivations for establishing physiological steady-states, and picoliter batch reactors, enabled the quantification of all physiological parameters relevant to approximate a material balance in microfluidic reaction environments. We determined state variables (biomass concentration based on single-cell dry weight and mass density), biomass synthesis rates, and substrate affinities of cells grown in microfluidic environments. Based on this data, we mathematically derived the specific kinetics of substrate uptake and growth stoichiometry in glucose-grown Escherichia coli with single-cell resolution. This framework may initiate microscale material balancing beyond the averaged values obtained from populations as a basis for integrating heterogeneous kinetic and stoichiometric single-cell data into generalized bioprocess models and descriptions.

A pipeline for malignancy and therapy agnostic assessment of cancer drug response using cell mass measurements

Functional precision medicine offers a promising complement to genomics-based cancer therapy guidance by testing drug efficacy directly on a patient's tumor cells. Here, we describe a workflow that utilizes single-cell mass measurements with inline brightfield imaging and machine-learning based image classification to broaden the clinical utility of such functional testing for cancer. Using these image-curated mass measurements, we characterize mass response signals for 60 different drugs with various mechanisms of action across twelve different cell types, demonstrating an improved ability to detect response for several slow acting drugs as compared with standard cell viability assays. Furthermore, we use this workflow to assess drug responses for various primary tumor specimen formats including blood, bone marrow, fine needle aspirates (FNA), and malignant fluids, all with reports generated within two days and with results consistent with patient clinical responses. The combination of high-resolution measurement, broad drug and malignancy applicability, and rapid return of results offered by this workflow suggests that it is well-suited to performing clinically relevant functional assessment of cancer drug response.

High-throughput determination of dry mass of single bacterial cells by ultrathin membrane resonators

How bacteria are able to maintain their size remains an open question. Techniques that can measure the biomass (dry mass) of single cells with high precision and high-throughput are demanded to elucidate this question. Here, we present a technological approach that combines the transport, guiding and focusing of individual bacteria from solution to the surface of an ultrathin silicon nitride membrane resonator in vacuum. The resonance frequencies of the membrane undergo abrupt variations at the instants where single cells land on the membrane surface. The resonator design displays a quasi-symmetric rectangular shape with an extraordinary capture area of 0.14 mm², while maintaining a high mass resolution of 0.7 fg (1 fg = 10⁻¹⁵g) to precisely resolve the dry mass of single cells. The small rectangularity of the membrane provides unprecedented frequency density of vibration modes that enables to retrieve the mass of individual cells with high accuracy by specially developed inverse problem theory. We apply this approach for profiling the dry mass distribution in Staphylococcus epidermidis and Escherichia coli cells. The technique allows the determination of the dry mass of single bacterial cells with an accuracy of about 1% at an unparalleled throughput of 20 cells/min. Finally, we revisit Koch & Schaechter model developed during 60 s to assess the intrinsic sources of stochasticity that originate cell size heterogeneity in steady-state populations. The results reveal the importance of mass resolution to correctly describe these mechanisms.

A technological approach combines transport, guiding and focusing of individual bacteria from solution to ultrathin membrane resonators for dry mass determination of single cells with accuracy within 1% and throughput of 20 cells/min.

Combining denoising of RNA-seq data and flux balance analysis for cluster analysis of single cells

Background

Sophisticated methods to properly pre-process and analyze the increasing collection of single-cell RNA sequencing (scRNA-seq) data are increasingly being developed. On the contrary, the best practices to integrate these data into metabolic networks, aiming at describing metabolic phenotypes within a heterogeneous cell population, have been poorly investigated. In this regard, a critical factor is the presence of false zero values in reactions essential for a fundamental metabolic function, such as biomass or energy production. Here, we investigate the role of denoising strategies in mitigating this problem.

Methods

We applied state-of-the-art denoising strategies - namely MAGIC, ENHANCE, and SAVER - on three public scRNA-seq datasets. We then associated a metabolic flux distribution with every single cell by embedding its noise-free transcriptomics profile in the constraints of the optimization of a core metabolic model. Finally, we used the obtained single-cell optimal metabolic fluxes as features for cluster analysis. We compared the results obtained with different techniques, and with or without the use of denoising. We also investigated the possibility of applying denoising directly on the Reaction Activity Scores, which are metabolic features extracted from the read counts, rather than on the read counts.

Results

We show that denoising of transcriptomics data improves the clustering of single cells. We also illustrate that denoising restores important metabolic properties, such as the correlation between cell cycle phase and biomass accumulation, and between the RAS scores of reactions belonging to the same metabolic pathway. We show that MAGIC performs better than ENHANCE and SAVER, and that, denoising applied directly on the RAS matrix could be an effective alternative in removing false zero values from essential metabolic reactions.

Conclusions

Our results indicate that including denoising as a pre-processing operation represents a milestone to integrate scRNA-seq data into Flux Balance Analysis simulations and to perform single-cell cluster analysis with a focus on metabolic phenotypes.

Nanomechanical Sensing Using Heater-Integrated Fluidic Resonators

Micro/nanochannel resonators have been used to measure cells, suspended nanoparticles, or liquids, primarily at or near room temperature while their high temperature operation can offer promising applications such as calorimetric measurements and thermogravimetric analysis. To date, global electrothermal or local photothermal heating mechanisms have been attempted for channel resonators, but both approaches are intrinsically limited by a narrow temperature modulation range, slow heating/cooling, less quantitative heating, or time-consuming optical alignment. Here, we introduce heater-integrated fluidic resonators (HFRs) that enable fast, quantitative, alignment-free, and wide-range temperature modulation and simultaneously offer resistive thermometry and resonant densitometry. HFRs with or without a dispensing nozzle are fabricated, thoroughly characterized, and used for high throughput thermophysical properties measurements, microchannel boiling studies, and atomized spray dispensing. The HFR, without a doubt, opens a new avenue for nanoscale thermal analysis and processing and further encourages the integration of additional functions into channel resonators.

Concentration fluctuations in growing and dividing cells: Insights into the emergence of concentration homeostasis

Intracellular reaction rates depend on concentrations and hence their levels are often regulated. However classical models of stochastic gene expression lack a cell size description and cannot be used to predict noise in concentrations. Here, we construct a model of gene product dynamics that includes a description of cell growth, cell division, size-dependent gene expression, gene dosage compensation, and size control mechanisms that can vary with the cell cycle phase. We obtain expressions for the approximate distributions and power spectra of concentration fluctuations which lead to insight into the emergence of concentration homeostasis. We find that (i) the conditions necessary to suppress cell division-induced concentration oscillations are difficult to achieve; (ii) mRNA concentration and number distributions can have different number of modes; (iii) two-layer size control strategies such as sizer-timer or adder-timer are ideal because they maintain constant mean concentrations whilst minimising concentration noise; (iv) accurate concentration homeostasis requires a fine tuning of dosage compensation, replication timing, and size-dependent gene expression; (v) deviations from perfect concentration homeostasis show up as deviations of the concentration distribution from a gamma distribution. Some of these predictions are confirmed using data for E. coli, fission yeast, and budding yeast.

Advanced density-based methods for the characterization of materials, binding events, and kinetics

Investigations of the densities of chemicals and materials bring valuable insights into the fundamental understanding of matter and processes. Recently, advanced density-based methods have been developed with wide measurement ranges (i.e. 0-23 g cm^-3), high resolutions (i.e. 10^-6 g cm^-3), compatibility with different types of samples and the requirement of extremely low volumes of sample (as low as a single cell). Certain methods, such as magnetic levitation, are inexpensive, portable and user-friendly. Advanced density-based methods are, therefore, beneficially used to obtain absolute density values, composition of mixtures, characteristics of binding events, and kinetics of chemical and biological processes. Herein, the principles and applications of magnetic levitation, acoustic levitation, electrodynamic balance, aqueous multiphase systems, and suspended microchannel resonators for materials science are discussed.

Microfluidics for antibiotic susceptibility testing

The rise of antibiotic resistance is a threat to global health. Rapid and comprehensive analysis of infectious strains is critical to reducing the global use of antibiotics, as informed antibiotic use could slow down the emergence of resistant strains worldwide. Multiple platforms for antibiotic susceptibility testing (AST) have been developed with the use of microfluidic solutions. Here we describe microfluidic systems that have been proposed to aid AST. We identify the key contributions in overcoming outstanding challenges associated with the required degree of multiplexing, reduction of detection time, scalability, ease of use, and capacity for commercialization. We introduce the reader to microfluidics in general, and we analyze the challenges and opportunities related to the field of microfluidic AST.

Versatile Approach of Silicon Nanofabrication without Resists: Helium Ion-Bombardment Enhanced Etching

Herein, we report a helium ion-bombardment enhanced etching method for silicon nanofabrication without the use of resists; furthermore, we demonstrate its unique advantages for straightforward fabrication on irregular surfaces and prototyping nano-electro-mechanical system devices, such as self-enclosed Si nanofluidic channels and mechanical nano-resonators. This method employs focused helium ions to selectively irradiate single-crystal Si to disrupt the crystal lattice and transform it into an amorphous phase that can be etched at a rate 200 times higher than that of the non-irradiated Si. Due to the unique raindrop shape of the interaction volumes between helium ions and Si, buried Si nanofluidic channels can be constructed using only one dosing step, followed by one step of conventional chemical etching. Moreover, suspended Si nanobeams can be fabricated without an additional undercut step for release owing to the unique raindrop shape. In addition, we demonstrate nanofabrication directly on 3D micro/nano surfaces, such as an atomic force microscopic probe, which is challenging for conventional nanofabrication due to the requirement of photoresist spin coating. Finally, this approach can also be extended to assist in the etching of other materials that are difficult to etch, such as silicon carbide (SiC).

Reciprocity of Cell Mechanics with Extracellular Stimuli: Emerging Opportunities for Translational Medicine

Human cells encounter dynamic mechanical cues in healthy and diseased tissues, which regulate their molecular and biophysical phenotype, including intracellular mechanics as well as force generation. Recent developments in bio/nanomaterials and microfluidics permit exquisitely sensitive measurements of cell mechanics, as well as spatiotemporal control over external mechanical stimuli to regulate cell behavior. In this review, the mechanobiology of cells interacting bidirectionally with their surrounding microenvironment, and the potential relevance for translational medicine are considered. Key fundamental concepts underlying the mechanics of living cells as well as the extracelluar matrix are first introduced. Then the authors consider case studies based on 1) microfluidic measurements of nonadherent cell deformability, 2) cell migration on micro/nano-topographies, 3) traction measurements of cells in three-dimensional (3D) matrix, 4) mechanical programming of organoid morphogenesis, as well as 5) active mechanical stimuli for potential therapeutics. These examples highlight the promise of disease diagnosis using mechanical measurements, a systems-level understanding linking molecular with biophysical phenotype, as well as therapies based on mechanical perturbations. This review concludes with a critical discussion of these emerging technologies and future directions at the interface of engineering, biology, and medicine.

Self-Powered Active Sensing Based on Triboelectric Generators

The demand for portable and wearable chemical or biosensors and their expeditious development in recent years has created a scientific challenge in terms of their continuous powering. As a result, mechanical energy harvesters such as piezoelectric and triboelectric generators (TEGs) have been explored recently either as sensors or harvesters to store charge in small, but long-life, energy-storage devices to power the sensors. The use of energy harvesters as sensors is particularly interesting, as with such multifunctional operations it is possible to reduce the number devices needed in a system, which also helps overcome the integration complexities. In this regard, TEGs are promising, particularly for energy autonomous chemical and biological sensors, as they can be developed with a wide variety of materials, and their mechanical energy to electricity conversion can be modulated by various analytes. This review focuses on this interesting dimension of TEGs and presents various self-powered active chemical and biological sensors. A brief discussion about the development of TEG-based physical, magnetic, and optical sensors is also included. The influence of environmental factors, various figures of merit, and the significance of TEG design are explained in context with the active sensing. Finally, the key applications, challenges, and future perspective of chemical and biological detection via TEGs are discussed with a view to drive further advances in the field of self-powered sensors.

Microtoxicology by microfluidic instrumentation: a review

Microtoxicology is concerned with the toxic effects of small amounts of substances. This review paper discusses the application of small amounts of noxious substances for toxicological investigation in small volumes. The vigorous development of miniaturized methods in microfluidics over the last two decades involves chip-based devices, micro droplet-based procedures, and the use of micro-segmented flow for microtoxicological studies. The studies have shown that the microfluidic approach is particularly valuable for highly parallelized and combinatorial dose-response screenings. Accurate dosing and mixing of effector substances in large numbers of microcompartments supplies detailed data of dose-response functions by highly concentration-resolved assays and allows evaluation of stochastic responses in case of small separated cell ensembles and single cell experiments. The investigations demonstrate that very different biological targets can be studied using miniaturized approaches, among them bacteria, eukaryotic microorganisms, cell cultures from tissues of multicellular organisms, stem cells, and early embryonic states. Cultivation and effector exposure tests can be performed in small volumes over weeks and months, confirming that the microfluicial strategy is also applicable for slow-growing organisms. Here, the state of the art of miniaturized toxicology, particularly for studying antibiotic susceptibility, drug toxicity testing in the miniaturized system like organ-on-chip, environmental toxicology, and the characterization of combinatorial effects by two and multi-dimensional screenings, is discussed. Additionally, this review points out the practical limitations of the microtoxicology platform and discusses perspectives on future opportunities and challenges.

Methods to monitor bacterial growth and replicative rates at the single-cell level

The heterogeneity of bacterial growth and replicative rates within a population was proposed a century ago notably to explain the presence of bacterial persisters. The term "growth rate" at the single-cell level corresponds to the increase in size or mass of an individual bacterium while the "replicative rate" refers to its division capacity within a defined temporality. After a decades long hiatus, recent technical innovative approaches allow population growth and replicative rates heterogeneity monitoring at the single-cell level resuming in earnest. Among these techniques, the oldest and widely used is time-lapse microscopy, most recently combined with microfluidics. We also discuss recent fluorescence dilution methods informing only on replicative rates and best suited. Some new elegant single cell methods so far only sporadically used such as buoyant mass measurement and stable isotope probing have emerged. Overall, such tools are widely used to investigate and compare the growth and replicative rates of bacteria displaying drug-persistent behaviors to that of bacteria growing in specific ecological niches or collected from patients. In this review, we describe the current methods available, discussing both the type of queries these have been used to answer and the specific strengths and limitations of each method.

Shining light in blind alleys: deciphering bacterial attachment in silicon microstructures

With new advances in infectious disease, antifouling surfaces, and environmental microbiology research comes the need to understand and control the accumulation and attachment of bacterial cells on a surface. Thus, we employ intrinsic phase-shift reflectometric interference spectroscopic measurements of silicon diffraction gratings to non-destructively observe the interactions between bacterial cells and abiotic, microstructured surfaces in a label-free and real-time manner. We conclude that the combination of specific material characteristics (i.e., substrate surface charge and topology) and characteristics of the bacterial cells (i.e., motility, cell charge, biofilm formation, and physiology) drive bacteria to adhere to a particular surface, often leading to a biofilm formation. Such knowledge can be exploited to predict antibiotic efficacy and biofilm formation, and enhance surface-based biosensor development, as well as the design of anti-biofouling strategies.

Deep Learning-Enabled Technologies for Bioimage Analysis

Deep learning (DL) is a subfield of machine learning (ML), which has recently demonstrated its potency to significantly improve the quantification and classification workflows in biomedical and clinical applications. Among the end applications profoundly benefitting from DL, cellular morphology quantification is one of the pioneers. Here, we first briefly explain fundamental concepts in DL and then we review some of the emerging DL-enabled applications in cell morphology quantification in the fields of embryology, point-of-care ovulation testing, as a predictive tool for fetal heart pregnancy, cancer diagnostics via classification of cancer histology images, autosomal polycystic kidney disease, and chronic kidney diseases.

Pump-free microfluidic magnetic levitation approach for density-based cell characterization

Magnetic levitation (MagLev) provides a simple but promising method for density-based analysis and detection down to the individual cell level. However, each existing MagLev configuration for the single-cell density measurement, mainly consisting of a capillary (∼50 mm) placed between two magnets, yields a fairly low sample utilization because of no knowledge about the sample cells in the regions other than the limited microscope vision. Moreover, the quantitative analysis may be affected due to the unclearly defined measurement area, which is specifically associated with the uneven magnetization of magnets, cell size, degree of aggregation. In this work, we explore a pump-free microfluidic magnetic levitation approach for density-based cell characterization, enabling sensitive and effective cellular density measurement on small sample volumes. The microfluidic MagLev comprises a pump-free microfluidic chip placed between two ring magnets with like poles facing. With no external pumps, connectors or control facility, much smaller amounts of fluids (∼4 μL) could be driven automatically in the entire microchannel in 16 s. Based on the pump-free mechanism, unique density signatures of cells from different lineages (ARPE-19, HCT116, HeLa, HT1080, Huh7) are characterized by monitoring the levitation profiles. Furthermore, variation in density of A549 lung cancer cells subjected to a drug treatment are observed in our platform, allowing evaluation of the efficacy of the drug treatment at the individual cell level. Thereby, the proposed pump-free microfluidic MagLev platform, a low-cost, fully automatic and portable design for label-free density-based cell characterization, provides a universal detection tool that operates efficiently within small-volume environments.

Physical Cytometry: Detecting Mass-Related Properties of Single Cells

The physical properties of a single cell, such as mass, volume, and density, are important indications of the cell's metabolic characteristics and homeostasis. Precise measurement of a single cell's mass has long been a challenge due to its minute size. It is only in the past 10 years that a variety of instruments for measuring living cellular mass have emerged with the development of MEMS, microfluidics, and optics technologies. In this review, we discuss the current developments of physical cytometry for quantifying mass-related physical properties of single cells, highlighting the working principle, applications, and unique merits. The review mainly covers these measurement methods: single-cell mass cytometry, levitation image cytometry, suspended microchannel resonator, phase-shifting interferometry, and opto-electrokinetics cell manipulation. Comparisons are made between these methods in terms of throughput, content, invasiveness, compatibility, and precision. Some typical applications of these methods in pathological diagnosis, drug efficacy evaluation, disease treatment, and other related fields are also discussed in this work.

Volume growth in animal cells is cell cycle dependent and shows additive fluctuations

The way proliferating animal cells coordinate the growth of their mass, volume, and other relevant size parameters is a long-standing question in biology. Studies focusing on cell mass have identified patterns of mass growth as a function of time and cell cycle phase, but little is known about volume growth. To address this question, we improved our fluorescence exclusion method of volume measurement (FXm) and obtained 1700 single-cell volume growth trajectories of HeLa cells. We find that, during most of the cell cycle, volume growth is close to exponential and proceeds at a higher rate in S-G2 than in G1. Comparing the data with a mathematical model, we establish that the cell-to-cell variability in volume growth arises from constant-amplitude fluctuations in volume steps rather than fluctuations of the underlying specific growth rate. We hypothesize that such 'additive noise' could emerge from the processes that regulate volume adaptation to biophysical cues, such as tension or osmotic pressure.

Characterizing non-exponential growth and bimodal cell size distributions in fission yeast: An analytical approach

Unlike many single-celled organisms, the growth of fission yeast cells within a cell cycle is not exponential. It is rather characterized by three distinct phases (elongation, septation, and reshaping), each with a different growth rate. Experiments also showed that the distribution of cell size in a lineage can be bimodal, unlike the unimodal distributions measured for the bacterium Escherichia coli. Here we construct a detailed stochastic model of cell size dynamics in fission yeast. The theory leads to analytic expressions for the cell size and the birth size distributions, and explains the origin of bimodality seen in experiments. In particular, our theory shows that the left peak in the bimodal distribution is associated with cells in the elongation phase, while the right peak is due to cells in the septation and reshaping phases. We show that the size control strategy, the variability in the added size during a cell cycle, and the fraction of time spent in each of the three cell growth phases have a strong bearing on the shape of the cell size distribution. Furthermore, we infer all the parameters of our model by matching the theoretical cell size and birth size distributions to those from experimental single-cell time-course data for seven different growth conditions. Our method provides a much more accurate means of determining the size control strategy (timer, adder or sizer) than the standard method based on the slope of the best linear fit between the birth and division sizes. We also show that the variability in added size and the strength of size control in fission yeast depend weakly on the temperature but strongly on the culture medium. More importantly, we find that stronger size homeostasis and larger added size variability are required for fission yeast to adapt to unfavorable environmental conditions.

Advances in microscopy enable us to follow single cells over long timescales from which we can understand how their size varies with time and the nature of innate strategies developed to control cell size. These data show that in many cell types, growth is exponential and the distribution of cell size has one peak, namely there is a single characteristic cell size. However data for fission yeast show remarkable differences: growth is non-exponential and the distribution of cell sizes has two peaks, corresponding to different growth phases. Here we construct a detailed stochastic mathematical model of this organism; by solving the model analytically, we show that it is able to predict the two peaked distributions of cell size seen in data and provide an explanation for each peak in terms of various growth phases of the single-celled organism. Furthermore, by fitting the model to the data, we infer values for the rates of all microscopic processes in our model. This method is shown to provide a much more reliable inference than current methods and shed light on how the strategy used by fission yeast cells to control their size varies with external conditions.

Fabricating Silicon Resonators for Analysing Biological Samples

The adaptability of microscale devices allows microtechnologies to be used for a wide range of applications. Biology and medicine are among those fields that, in recent decades, have applied microtechnologies to achieve new and improved functionality. However, despite their ability to achieve assay sensitivities that rival or exceed conventional standards, silicon-based microelectromechanical systems remain underutilised for biological and biomedical applications. Although microelectromechanical resonators and actuators do not always exhibit optimal performance in liquid due to electrical double layer formation and high damping, these issues have been solved with some innovative fabrication processes or alternative experimental approaches. This paper focuses on several examples of silicon-based resonating devices with a brief look at their fundamental sensing elements and key fabrication steps, as well as current and potential biological/biomedical applications.

Distinguishing different modes of growth using single-cell data

Collection of high-throughput data has become prevalent in biology. Large datasets allow the use of statistical constructs such as binning and linear regression to quantify relationships between variables and hypothesize underlying biological mechanisms based on it. We discuss several such examples in relation to single-cell data and cellular growth. In particular, we show instances where what appears to be ordinary use of these statistical methods leads to incorrect conclusions such as growth being non-exponential as opposed to exponential and vice versa. We propose that the data analysis and its interpretation should be done in the context of a generative model, if possible. In this way, the statistical methods can be validated either analytically or against synthetic data generated via the use of the model, leading to a consistent method for inferring biological mechanisms from data. On applying the validated methods of data analysis to infer cellular growth on our experimental data, we find the growth of length in E. coli to be non-exponential. Our analysis shows that in the later stages of the cell cycle the growth rate is faster than exponential.

Heterogeneous recruitment abilities to RNA polymerases generate nonlinear scaling of gene expression with cell volume

While most genes' expression levels are proportional to cell volumes, some genes exhibit nonlinear scaling between their expression levels and cell volume. Therefore, their mRNA and protein concentrations change as the cell volume increases, which often have crucial biological functions such as cell-cycle regulation. However, the biophysical mechanism underlying the nonlinear scaling between gene expression and cell volume is still unclear. In this work, we show that the nonlinear scaling is a direct consequence of the heterogeneous recruitment abilities of promoters to RNA polymerases based on a gene expression model at the whole-cell level. Those genes with weaker (stronger) recruitment abilities than the average ability spontaneously exhibit superlinear (sublinear) scaling with cell volume. Analysis of the promoter sequences and the nonlinear scaling of Saccharomyces cerevisiae's mRNA levels shows that motifs associated with transcription regulation are indeed enriched in genes exhibiting nonlinear scaling, in concert with our model.

Measurement methods of single cell drug response

In the last decades, a wide multitude of research activity has been focused on the development of new drugs, and devoted to overcome the challenges of high cost and low efficiency in drug evaluation. The measurement of drug response at the single cell level is a quicker, more direct and more accurate way to reflect drug efficacy, which can shorten the drug development period and reduce research costs. Therefore, the single cell drug response (SCDR) measurement technology has aroused extensive attention from researchers, and has become a hot topic in the fields of drug research and cell biology. Recent years have seen the emergence of various SCDR measurement technologies that feature different working principles and different levels of measurement performance. To better examine, compare and summarize the characteristics and functions of these technologies, we select signal-to-noise ratio, throughput, content, invasion, and device complexity as the criteria to evaluate them from the drug efficacy perspective. This review aims to highlight sixteen kinds of SCDR measurement technologies, including patch-clamp technique, live-cell interferometry, capillary electrophoresis, secondary ion mass spectrometry, and more, and report widespread representative examples of SCDR measurement the recent approaches for over the past forty years. Based on their reaction principles, these technologies are classified into four categories: electrical, optical, electrochemical, and mass spectrometry, and a detailed comparison is made between them. After in-depth understanding of these technologies, it is expected to improve or integrate these technologies to propose better SCDR measurement strategies, and explore methods in new drug development and screening, as well as disease diagnosis and treatment.

Microfluidic encapsulation for controlled release and its potential for nanofertilisers

Nanotechnology is increasingly being utilized to create advanced materials with improved or new functional attributes. Converting fertilizers into a nanoparticle-form has been shown to improve their efficacy but the current procedures used to fabricate nanofertilisers often have poor reproducibility and flexibility. Microfluidic systems, on the other hand, have advantages over traditional nanoparticle fabrication methods in terms of energy and materials consumption, versatility, and controllability. The increased controllability can result in the formation of nanoparticles with precise and complex morphologies (e.g., tuneable sizes, low polydispersity, and multi-core structures). As a result, their functional performance can be tailored to specific applications. This paper reviews the principles, formation, and applications of nano-enabled delivery systems fabricated using microfluidic approaches for the encapsulation, protection, and release of fertilizers. Controlled release can be achieved using two main routes: (i) nutrients adsorbed on nanosupports and (ii) nutrients encapsulated inside nanostructures. We aim to highlight the opportunities for preparing a new generation of highly versatile nanofertilisers using microfluidic systems. We will explore several main characteristics of microfluidically prepared nanofertilisers, including droplet formation, shell fine-tuning, adsorbate fine-tuning, and sustained/triggered release behavior.

Oncogenic HSP90 Facilitates Metabolic Alterations in Aggressive B-cell Lymphomas

HSP90 is critical for maintenance of the cellular proteostasis. In cancer cells, HSP90 also becomes a nucleating site for the stabilization of multiprotein complexes including signaling pathways and transcription complexes. Here we described the role of this HSP90 form, referred to as oncogenic HSP90, in the regulation of cytosolic metabolic pathways in proliferating B-cell lymphoma cells. Oncogenic HSP90 assisted in the organization of metabolic enzymes into non-membrane-bound functional compartments. Under experimental conditions that conserved cellular proteostasis, oncogenic HSP90 coordinated and sustained multiple metabolic pathways required for energy production and maintenance of cellular biomass as well as for secretion of extracellular metabolites. Conversely, inhibition of oncogenic HSP90, in absence of apparent client protein degradation, decreased the efficiency of MYC-driven metabolic reprogramming. This study reveals that oncogenic HSP90 supports metabolism in B-cell lymphoma cells and patients with diffuse large B-cell lymphoma, providing a novel mechanism of activity for HSP90 inhibitors. SIGNIFICANCE: The oncogenic form of HSP90 organizes and maintains functional multienzymatic metabolic hubs in cancer cells, suggesting the potential of repurposing oncogenic HSP90 selective inhibitors to disrupt metabolism in lymphoma cells.

Cellular and biomolecular detection based on suspended microchannel resonators

Suspended microchannel resonators (SMRs) have been developed to measure the buoyant mass of single micro-/nanoparticles and cells suspended in a liquid. They have significantly improved the mass resolution with the aid of vacuum packaging and also increased measurement throughput by fast resonance frequency tracking while target objects travel through the microchannel without stopping or even slowing down. Since their invention, various biological applications have been enabled, including simultaneous measurements of cell growth and cell cycle progression, and measurements of disease associated physicochemical change, to name a few. Extension and advancement towards other promising applications with SMRs are continuously ongoing by adding multiple functionalities or incorporating other complementary analytical metrologies. In this paper, we will thoroughly review the development history, basic and advanced operations, and key applications of SMRs to introduce them to researchers working in biological and biomedical sciences who mostly rely on classical and conventional methodologies. We will also provide future perspectives and projections for SMR technologies.

Functional drug susceptibility testing using single-cell mass predicts treatment outcome in patient-derived cancer neurosphere models

Functional precision medicine aims to match individual cancer patients to optimal treatment through ex vivo drug susceptibility testing on patient-derived cells. However, few functional diagnostic assays have been validated against patient outcomes at scale because of limitations of such assays. Here, we describe a high-throughput assay that detects subtle changes in the mass of individual drug-treated cancer cells as a surrogate biomarker for patient treatment response. To validate this approach, we determined ex vivo response to temozolomide in a retrospective cohort of 69 glioblastoma patient-derived neurosphere models with matched patient survival and genomics. Temozolomide-induced changes in cell mass distributions predict patient overall survival similarly to O⁶-methylguanine-DNA methyltransferase (MGMT) promoter methylation and may aid in predictions in gliomas with mismatch-repair variants of unknown significance, where MGMT is not predictive. Our findings suggest cell mass is a promising functional biomarker for cancers and drugs that lack genomic biomarkers.

Measuring kinetics and metastatic propensity of CTCs by blood exchange between mice

Existing preclinical methods for acquiring dissemination kinetics of rare circulating tumor cells (CTCs) en route to forming metastases have not been capable of providing a direct measure of CTC intravasation rate and subsequent half-life in the circulation. Here, we demonstrate an approach for measuring endogenous CTC kinetics by continuously exchanging CTC-containing blood over several hours between un-anesthetized, tumor-bearing mice and healthy, tumor-free counterparts. By tracking CTC transfer rates, we extrapolated half-life times in the circulation of between 40 and 260 s and intravasation rates between 60 and 107,000 CTCs/hour in mouse models of small-cell lung cancer (SCLC), pancreatic ductal adenocarcinoma (PDAC), and non-small cell lung cancer (NSCLC). Additionally, direct transfer of only 1-2% of daily-shed CTCs using our blood-exchange technique from late-stage, SCLC-bearing mice generated macrometastases in healthy recipient mice. We envision that our technique will help further elucidate the role of CTCs and the rate-limiting steps in metastasis.

Inertial and viscous flywheel sensing of nanoparticles

Rotational dynamics often challenge physical intuition while enabling unique realizations, from the rotor of a gyroscope that maintains its orientation regardless of the outer gimbals, to a tennis racket that rotates around its handle when tossed face-up in the air. In the context of inertial sensing, which can measure mass with atomic precision, rotational dynamics are normally considered a complication hindering measurement interpretation. Here, we exploit the rotational dynamics of a microfluidic device to develop a modality in inertial sensing. Combining theory with experiments, we show that this modality measures the volume of a rigid particle while normally being insensitive to its density. Paradoxically, particle density only emerges when fluid viscosity becomes dominant over inertia. We explain this paradox via a viscosity-driven, hydrodynamic coupling between the fluid and the particle that activates the rotational inertia of the particle, converting it into a ‘viscous flywheel’. This modality now enables the simultaneous measurement of particle volume and mass in fluid, using a single, high-throughput measurement.

Balances for nanoparticles such as resonating fluid-filled cantilevers usually probe only mass through changes in oscillation frequency. Katsikis and Collis et al. tap information from previously ignored rotational motion to simultaneously measure particle mass and volume.

Robust surface-to-mass coupling and turgor-dependent cell width determine bacterial dry-mass density

Intracellular biomass density is an important variable for cellular physiology. It defines the crowded state of the cytoplasm and thus influences macromolecular interactions and transport. To control density during growth, bacteria must expand their cell volumes in synchrony with biomass. The regulation of volume growth and biomass density remain fundamentally not understood—in bacteria or any other organism. Using advanced microscopy, we demonstrate that cells control dry-mass density indirectly through two independent processes. First, cells expand surface area, rather than volume, in proportion with biomass growth. Second, cell width is controlled independently, with an important influence of turgor pressure. Our findings overturn a long-standing paradigm of mass-density constancy in bacteria and reveal fundamental determinants of dry-mass density and shape.

During growth, cells must expand their cell volumes in coordination with biomass to control the level of cytoplasmic macromolecular crowding. Dry-mass density, the average ratio of dry mass to volume, is roughly constant between different nutrient conditions in bacteria, but it remains unknown whether cells maintain dry-mass density constant at the single-cell level and during nonsteady conditions. Furthermore, the regulation of dry-mass density is fundamentally not understood in any organism. Using quantitative phase microscopy and an advanced image-analysis pipeline, we measured absolute single-cell mass and shape of the model organisms Escherichia coli and Caulobacter crescentus with improved precision and accuracy. We found that cells control dry-mass density indirectly by expanding their surface, rather than volume, in direct proportion to biomass growth—according to an empirical surface growth law. At the same time, cell width is controlled independently. Therefore, cellular dry-mass density varies systematically with cell shape, both during the cell cycle or after nutrient shifts, while the surface-to-mass ratio remains nearly constant on the generation time scale. Transient deviations from constancy during nutrient shifts can be reconciled with turgor-pressure variations and the resulting elastic changes in surface area. Finally, we find that plastic changes of cell width after nutrient shifts are likely driven by turgor variations, demonstrating an important regulatory role of mechanical forces for width regulation. In conclusion, turgor-dependent cell width and a slowly varying surface-to-mass coupling constant are the independent variables that determine dry-mass density.

A distinct growth physiology enhances bacterial growth under rapid nutrient fluctuations

It has long been known that bacteria coordinate their physiology with their nutrient environment, yet our current understanding offers little intuition for how bacteria respond to the second-to-minute scale fluctuations in nutrient concentration characteristic of many microbial habitats. To investigate the effects of rapid nutrient fluctuations on bacterial growth, we couple custom microfluidics with single-cell microscopy to quantify the growth rate of E. coli experiencing 30 s to 60 min nutrient fluctuations. Compared to steady environments of equal average concentration, fluctuating environments reduce growth rate by up to 50%. However, measured reductions in growth rate are only 38% of the growth loss predicted from single nutrient shifts. This enhancement derives from the distinct growth response of cells grown in environments that fluctuate rather than shift once. We report an unexpected physiology adapted for growth in nutrient fluctuations and implicate nutrient timescale as a critical environmental parameter beyond nutrient identity and concentration.

Here the authors use microfluidics and single-cell microscopy to quantify the growth dynamics of individual E. coli cells exposed to nutrient fluctuations with periods as short as 30 seconds, finding that nutrient fluctuations reduce growth rates up to 50% compared to a steady nutrient delivery of equal average concentration, implying that temporal variability is an important parameter in bacterial growth.