Constant surface area-to-volume ratio during cell growth as a design principle in mammalian cells.

All cells are subject to geometric constraints, such as surface area-to-volume (SA/V) ratio, that impact cell functions and force biological adaptations. Like the SA/V ratio of a sphere, it is generally assumed that the SA/V ratio of cells decreases as cell size increases. Here, we investigate this in near-spherical mammalian cells using single-cell measurements of cell mass and surface proteins, as well as imaging of plasma membrane morphology. We find that the SA/V ratio remains surprisingly constant as cells grow larger. This observation is largely independent of the cell cycle and the amount of cell growth. Consequently, cell growth results in increased plasma membrane folding, which simplifies cellular design by ensuring sufficient membrane area for cell division, nutrient uptake and deformation at all cell sizes.

Cell size, density, and nutrient dependency of unicellular algal gravitational sinking velocities.

Eukaryotic phytoplankton, also known as algae, form the basis of marine food webs and drive marine carbon sequestration. Algae must regulate their motility and gravitational sinking to balance access to light at the surface and nutrients in deeper layers. However, the regulation of gravitational sinking remains largely unknown, especially in motile species. Here, we quantify gravitational sinking velocities according to Stokes' law in diverse clades of unicellular marine microalgae to reveal the cell size, density, and nutrient dependency of sinking velocities. We identify a motile algal species, Tetraselmis sp., that sinks faster when starved due to a photosynthesis-driven accumulation of carbohydrates and a loss of intracellular water, both of which increase cell density. Moreover, the regulation of cell sinking velocities is connected to proliferation and can respond to multiple nutrients. Overall, our work elucidates how cell size and density respond to environmental conditions to drive the vertical migration of motile algae.

Cell-intrinsic mechanical regulation of plasma membrane accumulation at the cytokinetic furrow.

Cytokinesis is the process where the mother cell's cytoplasm separates into daughter cells. This is driven by an actomyosin contractile ring that produces cortical contractility and drives cleavage furrow ingression, resulting in the formation of a thin intercellular bridge. While cytoskeletal reorganization during cytokinesis has been extensively studied, less is known about the spatiotemporal dynamics of the plasma membrane. Here, we image and model plasma membrane lipid and protein dynamics on the cell surface during leukemia cell cytokinesis. We reveal an extensive accumulation and folding of the plasma membrane at the cleavage furrow and the intercellular bridge, accompanied by a depletion and unfolding of the plasma membrane at the cell poles. These membrane dynamics are caused by two actomyosin-driven biophysical mechanisms: the radial constriction of the cleavage furrow causes local compression of the apparent cell surface area and accumulation of the plasma membrane at the furrow, while actomyosin cortical flows drag the plasma membrane toward the cell division plane as the furrow ingresses. The magnitude of these effects depends on the plasma membrane fluidity, cortex adhesion, and cortical contractility. Overall, our work reveals cell-intrinsic mechanical regulation of plasma membrane accumulation at the cleavage furrow that is likely to generate localized differences in membrane tension across the cytokinetic cell. This may locally alter endocytosis, exocytosis, and mechanotransduction, while also serving as a self-protecting mechanism against cytokinesis failures that arise from high membrane tension at the intercellular bridge.

Measuring single-cell density with high throughput enables dynamic profiling of immune cell and drug response from patient samples.

Cell density, the ratio of cell mass to volume, is an indicator of molecular crowding and therefore a fundamental determinant of cell state and function. However, existing density measurements lack the precision or throughput to quantify subtle differences in cell states, particularly in primary samples. Here we present an approach for measuring the density of 30,000 single cells per hour with a precision of 0.03% (0.0003 g/mL) by integrating fluorescence exclusion microscopy with a suspended microchannel resonator. Applying this approach to human lymphocytes, we discovered that cell density and its variation decrease as cells transition from quiescence to a proliferative state, suggesting that the level of molecular crowding decreases and becomes more regulated upon entry into the cell cycle. Using a pancreatic cancer patient-derived xenograft model, we found that the ex vivo density response of primary tumor cells to drug treatment can predict in vivo tumor growth response. Our method reveals unexpected behavior in molecular crowding during cell state transitions and suggests density as a new biomarker for functional precision medicine.

Cell intrinsic mechanical regulation of plasma membrane accumulation at the cytokinetic furrow.

Cytokinesis is the process where the mother cell's cytoplasm separates into daughter cells. This is driven by an actomyosin contractile ring that produces cortical contractility and drives cleavage furrow ingression, resulting in the formation of a thin intercellular bridge. While cytoskeletal reorganization during cytokinesis has been extensively studied, little is known about the spatiotemporal dynamics of the plasma membrane. Here, we image and model plasma membrane lipid and protein dynamics on the cell surface during leukemia cell cytokinesis. We reveal an extensive accumulation and folding of plasma membrane at the cleavage furrow and the intercellular bridge, accompanied by a depletion and unfolding of plasma membrane at the cell poles. These membrane dynamics are caused by two actomyosin-driven biophysical mechanisms: the radial constriction of the cleavage furrow causes local compression of the apparent cell surface area and accumulation of the plasma membrane at the furrow, while actomyosin cortical flows drag the plasma membrane towards the cell division plane as the furrow ingresses. The magnitude of these effects depends on the plasma membrane fluidity, cortex adhesion and cortical contractility. Overall, our work reveals cell intrinsic mechanical regulation of plasma membrane accumulation at the cleavage furrow that is likely to generate localized differences in membrane tension across the cytokinetic cell. This may locally alter endocytosis, exocytosis and mechanotransduction, while also serving as a self-protecting mechanism against cytokinesis failures that arise from high membrane tension at the intercellular bridge.

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.

The human cell count and size distribution.

Cell size and cell count are adaptively regulated and intimately linked to growth and function. Yet, despite their widespread relevance, the relation between cell size and count has never been formally examined over the whole human body. Here, we compile a comprehensive dataset of cell size and count over all major cell types, with data drawn from >1,500 published sources. We consider the body of a representative male (70 kg), which allows further estimates of a female (60 kg) and 10-y-old child (32 kg). We build a hierarchical interface for the cellular organization of the body, giving easy access to data, methods, and sources (https://humancelltreemap.mis.mpg.de/). In total, we estimate total body counts of ≈36 trillion cells in the male, ≈28 trillion in the female, and ≈17 trillion in the child. These data reveal a surprising inverse relation between cell size and count, implying a trade-off between these variables, such that all cells within a given logarithmic size class contribute an equal fraction to the body's total cellular biomass. We also find that the coefficient of variation is approximately independent of mean cell size, implying the existence of cell-size regulation across cell types. Our data serve to establish a holistic quantitative framework for the cells of the human body, and highlight large-scale patterns in cell biology.

Metabolic regulation of species-specific developmental rates.

Animals display substantial inter-species variation in the rate of embryonic development despite a broad conservation of the overall sequence of developmental events. Differences in biochemical reaction rates, including the rates of protein production and degradation, are thought to be responsible for species-specific rates of development1-3. However, the cause of differential biochemical reaction rates between species remains unknown. Here, using pluripotent stem cells, we have established an in vitro system that recapitulates the twofold difference in developmental rate between mouse and human embryos. This system provides a quantitative measure of developmental speed as revealed by the period of the segmentation clock, a molecular oscillator associated with the rhythmic production of vertebral precursors. Using this system, we show that mass-specific metabolic rates scale with the developmental rate and are therefore higher in mouse cells than in human cells. Reducing these metabolic rates by inhibiting the electron transport chain slowed down the segmentation clock by impairing the cellular NAD+/NADH redox balance and, further downstream, lowering the global rate of protein synthesis. Conversely, increasing the NAD+/NADH ratio in human cells by overexpression of the Lactobacillus brevis NADH oxidase LbNOX increased the translation rate and accelerated the segmentation clock. These findings represent a starting point for the manipulation of developmental rate, with multiple translational applications including accelerating the differentiation of human pluripotent stem cells for disease modelling and cell-based therapies.

Heart rate variability responses to cognitive stress in fibromyalgia are characterised by inadequate autonomous system stress responses: a clinical trial.

Fibromyalgia (FM) is associated with sympathetically dominant dysautonomia, but the connection between dysautonomia and FM symptoms is unclear. Dysautonomia can be analysed with heart rate variability (HRV) and it has been proposed that FM patients comprise subgroups with differing profiles of symptom severity. In our study, 51 female FM patients aged 18 to 65 years and 31 age-matched healthy female controls followed a 20-min protocol of alternating relaxation and cognitive stress (mental arithmetic). Heart rates and electrocardiograms were registered. The HRV measures of heart rate (HR), mean interval between heart beats (RRmean), root mean squared interval differences of successive beats (RMSSD), and the standard deviation of intervals between normal heart beats (SDNN) were analysed with generalized linear modelling. Features in HRV reactivity which differed between FM patients and controls were used to cluster the FM patients and cluster characteristics were analysed. FM patients had higher baseline HR (72.3 [SD 12.7] vs 64.5 [7.80], p < 0.001) and lower RRmean (0.844 [0.134] vs 0.934 [0.118], p = 0.002), compared with controls. They also reacted to repeated cognitive stress with an attenuated rise in HR (- 4.41 [95% CI - 7.88 to - 0.93], p = 0.013) and attenuated decrease of RRmean (0.06 [95 CI 0.03 to 0.09], p < 0.001), compared with controls. Clustering of FM patients by HRV reactivity resulted in three clusters characterised by (1) normal levels of HRV and HRV reactivity with low levels of depressive mood and anxiety, (2) reduced levels of HRV and impaired HRV reactivity with increased levels of depressive mood and high levels of anxiety, and (3) lowest HRV and most impaired HRV reactivity with the highest scores for depressive mood and anxiety. Our results show that FM patients have lower HRV than healthy controls and their autonomous reactions to cognitive stress are attenuated. Dysautonomia in FM associates with mood disturbance. Trial registration ClinicalTrials.gov (NCT03300635). Registered October 3 2017-Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT03300635 .

Nucleotide imbalance decouples cell growth from cell proliferation.

Nucleotide metabolism supports RNA synthesis and DNA replication to enable cell growth and division. Nucleotide depletion can inhibit cell growth and proliferation, but how cells sense and respond to changes in the relative levels of individual nucleotides is unclear. Moreover, the nucleotide requirement for biomass production changes over the course of the cell cycle, and how cells coordinate differential nucleotide demands with cell cycle progression is not well understood. Here we find that excess levels of individual nucleotides can inhibit proliferation by disrupting the relative levels of nucleotide bases needed for DNA replication and impeding DNA replication. The resulting purine and pyrimidine imbalances are not sensed by canonical growth regulatory pathways like mTORC1, Akt and AMPK signalling cascades, causing excessive cell growth despite inhibited proliferation. Instead, cells rely on replication stress signalling to survive during, and recover from, nucleotide imbalance during S phase. We find that ATR-dependent replication stress signalling is activated during unperturbed S phases and promotes nucleotide availability to support DNA replication. Together, these data reveal that imbalanced nucleotide levels are not detected until S phase, rendering cells reliant on replication stress signalling to cope with this metabolic problem and disrupting the coordination of cell growth and division.

Machine Learning and Pathway Analysis-Based Discovery of Metabolomic Markers Relating to Chronic Pain Phenotypes.

Recent scientific evidence suggests that chronic pain phenotypes are reflected in metabolomic changes. However, problems associated with chronic pain, such as sleep disorders or obesity, may complicate the metabolome pattern. Such a complex phenotype was investigated to identify common metabolomics markers at the interface of persistent pain, sleep, and obesity in 71 men and 122 women undergoing tertiary pain care. They were examined for patterns in d = 97 metabolomic markers that segregated patients with a relatively benign pain phenotype (low and little bothersome pain) from those with more severe clinical symptoms (high pain intensity, more bothersome pain, and co-occurring problems such as sleep disturbance). Two independent lines of data analysis were pursued. First, a data-driven supervised machine learning-based approach was used to identify the most informative metabolic markers for complex phenotype assignment. This pointed primarily at adenosine monophosphate (AMP), asparagine, deoxycytidine, glucuronic acid, and propionylcarnitine, and secondarily at cysteine and nicotinamide adenine dinucleotide (NAD) as informative for assigning patients to clinical pain phenotypes. After this, a hypothesis-driven analysis of metabolic pathways was performed, including sleep and obesity. In both the first and second line of analysis, three metabolic markers (NAD, AMP, and cysteine) were found to be relevant, including metabolic pathway analysis in obesity, associated with changes in amino acid metabolism, and sleep problems, associated with downregulated methionine metabolism. Taken together, present findings provide evidence that metabolomic changes associated with co-occurring problems may play a role in the development of severe pain. Co-occurring problems may influence each other at the metabolomic level. Because the methionine and glutathione metabolic pathways are physiologically linked, sleep problems appear to be associated with the first metabolic pathway, whereas obesity may be associated with the second.

Single-cell monitoring of dry mass and dry mass density reveals exocytosis of cellular dry contents in mitosis.

Cell mass and composition change with cell cycle progression. Our previous work characterized buoyant mass dynamics in mitosis (Miettinen et al., 2019), but how dry mass and cell composition change in mitosis has remained unclear. To better understand mitotic cell growth and compositional changes, we develop a single-cell approach for monitoring dry mass and the density of that dry mass every ~75 s with 1.3% and 0.3% measurement precision, respectively. We find that suspension grown mammalian cells lose dry mass and increase dry mass density following mitotic entry. These changes display large, non-genetic cell-to-cell variability, and the changes are reversed at metaphase-anaphase transition, after which dry mass continues accumulating. The change in dry mass density causes buoyant and dry mass to differ specifically in early mitosis, thus reconciling existing literature on mitotic cell growth. Mechanistically, cells in early mitosis increase lysosomal exocytosis, and inhibition of lysosomal exocytosis decreases the dry mass loss and dry mass density increase in mitosis. Overall, our work provides a new approach for monitoring single-cell dry mass and dry mass density, and reveals that mitosis is coupled to extensive exocytosis-mediated secretion of cellular contents.

Sleep problems in pain patients entering tertiary pain care: the role of pain-related anxiety, medication use, self-reported diseases, and sleep disorders.

ABSTRACT: Chronic pain and sleep problems frequently co-occur. Pain itself disturbs sleep, but other factors may also contribute to sleep problems in pain patients. This cross-sectional study of 473 patients (69.9% female, mean age 47 years) entering tertiary pain management compared normally sleeping pain patients with those having recurring sleep problems to determine the relationship between pain and sleep. Groups were compared for pain and pain aetiology, pain-related anxiety, childhood adversities, use of sleep and pain medications, self-reported diseases, and sleep disorders. Furthermore, the association of pain-related anxiety (cognitive anxiety, escape/avoidance, fear, and physiological anxiety) with more disturbing sleep problems was investigated in the whole cohort. The main results were that those with sleep problems more often reported multiple health conditions than those sleeping normally (depression 31.6% vs 5.0%; angina pectoris 6.5% vs 0.0%; asthma 19.6% vs 1.7%; low back problems 55.1% vs 23.3%; joint disease other than rheumatoid arthritis 32.3% vs 18.3%). Accumulations of 5 or more childhood adversities were more often present in those with sleep problems. Restless legs symptoms were more common in those with sleep problems than those sleeping normally (33.2% vs 11.7%). Patients having sleep problems reported more use of sleep and pain medications than those sleeping normally. Findings about pain-related anxiety suggest physiological reactions as significant factors for increased sleep disturbances. These factors need to be addressed in the management of the comorbidity of pain and sleep problems, and research to understand mechanisms in these is sorely needed.

Cell size is a determinant of stem cell potential during aging.

Stem cells are remarkably small. Whether small size is important for stem cell function is unknown. We find that hematopoietic stem cells (HSCs) enlarge under conditions known to decrease stem cell function. This decreased fitness of large HSCs is due to reduced proliferation and was accompanied by altered metabolism. Preventing HSC enlargement or reducing large HSCs in size averts the loss of stem cell potential under conditions causing stem cell exhaustion. Last, we show that murine and human HSCs enlarge during aging. Preventing this age-dependent enlargement improves HSC function. We conclude that small cell size is important for stem cell function in vivo and propose that stem cell enlargement contributes to their functional decline during aging.

Directed evolution of rRNA improves translation kinetics and recombinant protein yield.

In bacteria, ribosome kinetics are considered rate-limiting for protein synthesis and cell growth. Enhanced ribosome kinetics may augment bacterial growth and biomanufacturing through improvements to overall protein yield, but whether this can be achieved by ribosome-specific modifications remains unknown. Here, we evolve 16S ribosomal RNAs (rRNAs) from Escherichia coli, Pseudomonas aeruginosa, and Vibrio cholerae towards enhanced protein synthesis rates. We find that rRNA sequence origin significantly impacted evolutionary trajectory and generated rRNA mutants with augmented protein synthesis rates in both natural and engineered contexts, including the incorporation of noncanonical amino acids. Moreover, discovered consensus mutations can be ported onto phylogenetically divergent rRNAs, imparting improved translational activities. Finally, we show that increased translation rates in vivo coincide with only moderately reduced translational fidelity, but do not enhance bacterial population growth. Together, these findings provide a versatile platform for development of unnatural ribosomal functions in vivo.

Variations of intracellular density during the cell cycle arise from tip-growth regulation in fission yeast.

Intracellular density impacts the physical nature of the cytoplasm and can globally affect cellular processes, yet density regulation remains poorly understood. Here, using a new quantitative phase imaging method, we determined that dry-mass density in fission yeast is maintained in a narrow distribution and exhibits homeostatic behavior. However, density varied during the cell cycle, decreasing during G2, increasing in mitosis and cytokinesis, and dropping rapidly at cell birth. These density variations were explained by a constant rate of biomass synthesis, coupled to slowdown of volume growth during cell division and rapid expansion post-cytokinesis. Arrest at specific cell-cycle stages exacerbated density changes. Spatially heterogeneous patterns of density suggested links between density regulation, tip growth, and intracellular osmotic pressure. Our results demonstrate that systematic density variations during the cell cycle are predominantly due to modulation of volume expansion, and reveal functional consequences of density gradients and cell-cycle arrests.

Muscle activity and acute stress in fibromyalgia.

BACKGROUND: Fibromyalgia (FM) patients are likely to differ from healthy controls in muscle activity and in reactivity to experimental stress. METHODS: We compared psychophysiological reactivity to cognitive stress between 51 female FM patients aged 18 to 65 years and 31 age- and sex-matched healthy controls. They underwent a 20-minute protocol consisting of three phases of relaxation and two phases of cognitive stress. We recorded surface electromyography normalized to maximum voluntary muscle contraction (%EMG), the percentage of time with no muscle activity (EMG rest time), and subjective pain and stress intensities. We compared group reactivity using linear modelling and adjusted for psychological and life-style factors. RESULTS: The FM patients had a significantly higher mean %EMG (2.2 % vs. 1.0 %, p < 0.001), pain intensity (3.6 vs. 0.2, p < 0.001), and perceived stress (3.5 vs. 1.4, p < 0.001) and lower mean EMG rest time (26.7 % vs. 47.2 %, p < 0.001). In the FM patients, compared with controls, the pain intensity increased more during the second stress phase (0.71, p = 0.028), and the %EMG decreased more during the final relaxation phase (-0.29, p = 0.036). Within the FM patients, higher BMI predicted higher %EMG but lower stress. Leisure time physical activity predicted lower %EMG and stress and higher EMG rest time. Higher perceived stress predicted lower EMG rest time, and higher trait anxiety predicted higher pain and stress overall. CONCLUSIONS: Our results suggest that repeated cognitive stress increases pain intensity in FM patients. FM patients also had higher resting muscle activity, but their muscle activity did not increase with pain. Management of stress and anxiety might help control FM flare-ups. TRIAL REGISTRATION: Retrospectively registered on ClinicalTrials.gov ( NCT03300635 ).

Machine learning suggests sleep as a core factor in chronic pain.

Patients with chronic pain have complex pain profiles and associated problems. Subgroup analysis can help identify key problems. We used a data-based approach to define pain phenotypes and their most relevant associated problems in 320 patients undergoing tertiary pain management. Unsupervised machine learning analysis of parameters "pain intensity," "number of pain areas," "pain duration," "activity pain interference," and "affective pain interference," implemented as emergent self-organizing maps, identified 3 patient phenotype clusters. Supervised analyses, implemented as different types of decision rules, identified "affective pain interference" and the "number of pain areas" as most relevant for cluster assignment. These appeared 698 and 637 times, respectively, in 1000 cross-validation runs among the most relevant characteristics in an item categorization approach in a computed ABC analysis. Cluster assignment was achieved with a median balanced accuracy of 79.9%, a sensitivity of 74.1%, and a specificity of 87.7%. In addition, among 59 demographic, pain etiology, comorbidity, lifestyle, psychological, and treatment-related variables, sleep problems appeared 638 and 439 times among the most important characteristics in 1000 cross-validation runs where patients were assigned to the 2 extreme pain phenotype clusters. Also important were the parameters "fear of pain," "self-rated poor health," and "systolic blood pressure." Decision trees trained with this information assigned patients to the extreme pain phenotype with an accuracy of 67%. Machine learning suggested sleep problems as key factors in the most difficult pain presentations, therefore deserving priority in the treatment of chronic pain.