Allometric scaling of metabolic rate from molecules and mitochondria to cells and mammals

Dynamics of tumor-associated macrophages in a quantitative systems pharmacology model of immunotherapy in triple-negative breast cancer

Quantitative systems pharmacology (QSP) modeling is an emerging mechanistic computational approach that couples drug pharmacokinetics/pharmacodynamics and the course of disease progression. It has begun to play important roles in drug development for complex diseases such as cancer, including triple-negative breast cancer (TNBC). The combination of the anti-PD-L1 antibody atezolizumab and nab-paclitaxel has shown clinical activity in advanced TNBC with PD-L1-positive tumor-infiltrating immune cells. As tumor-associated macrophages (TAMs) serve as major contributors to the immuno-suppressive tumor microenvironment, we incorporated the dynamics of TAMs into our previously published QSP model to investigate their impact on cancer treatment. We show that through proper calibration, the model captures the macrophage heterogeneity in the tumor microenvironment while maintaining its predictive power of the trial results at the population level. Despite its high mechanistic complexity, the modularized QSP platform can be readily reproduced, expanded for new species of interest, and applied in clinical trial simulation.

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A mechanistic model of quantitative systems pharmacology in immuno-oncology

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Dynamics of tumor-associated macrophages are integrated into our previous work

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Conducting in silico clinical trials to predict clinical response to cancer therapy

Metabolic scaling is the product of life-history optimization

Organisms use energy to grow and reproduce, so the processes of energy metabolism and biological production should be tightly bound. On the basis of this tenet, we developed and tested a new theory that predicts the relationships among three fundamental aspects of life: metabolic rate, growth, and reproduction. We show that the optimization of these processes yields the observed allometries of metazoan life, particularly metabolic scaling. We conclude that metabolism, growth, and reproduction are inextricably linked; that together they determine fitness; and, in contrast to longstanding dogma, that no single component drives another. Our model predicts that anthropogenic change will cause animals to evolve decreased scaling exponents of metabolism, increased growth rates, and reduced lifetime reproductive outputs, with worrying consequences for the replenishment of future populations.

White Paper: An Integrated Perspective on the Causes of Hypometric Metabolic Scaling in Animals

Larger animals studied during ontogeny, across populations, or across species, usually have lower mass-specific metabolic rates than smaller animals (hypometric scaling). This pattern is usually observed regardless of physiological state (e.g. basal, resting, field, maximally-active). The scaling of metabolism is usually highly correlated with the scaling of many life history traits, behaviors, physiological variables, and cellular/molecular properties, making determination of the causation of this pattern challenging. For across-species comparisons of resting and locomoting animals (but less so for across populations or during ontogeny), the mechanisms at the physiological and cellular level are becoming clear. Lower mass-specific metabolic rates of larger species at rest are due to a) lower contents of expensive tissues (brains, liver, kidneys), and b) slower ion leak across membranes at least partially due to membrane composition, with lower ion pump ATPase activities. Lower mass-specific costs of larger species during locomotion are due to lower costs for lower-frequency muscle activity, with slower myosin and Ca++ ATPase activities, and likely more elastic energy storage. The evolutionary explanation(s) for hypometric scaling remain(s) highly controversial. One subset of evolutionary hypotheses relies on constraints on larger animals due to changes in geometry with size; for example, lower surface-to-volume ratios of exchange surfaces may constrain nutrient or heat exchange, or lower cross-sectional areas of muscles and tendons relative to body mass ratios would make larger animals more fragile without compensation. Another subset of hypotheses suggests that hypometric scaling arises from biotic interactions and correlated selection, with larger animals experiencing less selection for mass-specific growth or neurolocomotor performance. A additional third type of explanation comes from population genetics. Larger animals with their lower effective population sizes and subsequent less effective selection relative to drift may have more deleterious mutations, reducing maximal performance and metabolic rates. Resolving the evolutionary explanation for the hypometric scaling of metabolism and associated variables is a major challenge for organismal and evolutionary biology. To aid progress, we identify some variation in terminology use that has impeded cross-field conversations on scaling. We also suggest that promising directions for the field to move forward include: 1) studies examining the linkages between ontogenetic, population-level, and cross-species allometries, 2) studies linking scaling to ecological or phylogenetic context, 3) studies that consider multiple, possibly interacting hypotheses, and 4) obtaining better field data for metabolic rates and the life history correlates of metabolic rate such as lifespan, growth rate and reproduction.

Optimized scaling of translational factors in oncology: from xenografts to RECIST

Purpose

Tumor growth inhibition (TGI) models are regularly used to quantify the PK–PD relationship between drug concentration and in vivo efficacy in oncology. These models are typically calibrated with data from xenograft mice and before being used for clinical predictions, translational methods have to be applied. Currently, such methods are commonly based on replacing model components or scaling of model parameters. However, difficulties remain in how to accurately account for inter-species differences. Therefore, more research must be done before xenograft data can fully be utilized to predict clinical response.

Method

To contribute to this research, we have calibrated TGI models to xenograft data for three drug combinations using the nonlinear mixed effects framework. The models were translated by replacing mice exposure with human exposure and used to make predictions of clinical response. Furthermore, in search of a better way of translating these models, we estimated an optimal way of scaling model parameters given the available clinical data.

Results

The predictions were compared with clinical data and we found that clinical efficacy was overestimated. The estimated optimal scaling factors were similar to a standard allometric scaling exponent of − 0.25.

Conclusions

We believe that given more data, our methodology could contribute to increasing the translational capabilities of TGI models. More specifically, an appropriate translational method could be developed for drugs with the same mechanism of action, which would allow for all preclinical data to be leveraged for new drugs of the same class. This would ensure that fewer clinically inefficacious drugs are tested in clinical trials.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00280-022-04458-8.

Integration of Heterogeneous Biological Data in Multiscale Mechanistic Model Calibration: Application to Lung Adenocarcinoma

Mechanistic models are built using knowledge as the primary information source, with well-established biological and physical laws determining the causal relationships within the model. Once the causal structure of the model is determined, parameters must be defined in order to accurately reproduce relevant data. Determining parameters and their values is particularly challenging in the case of models of pathophysiology, for which data for calibration is sparse. Multiple data sources might be required, and data may not be in a uniform or desirable format. We describe a calibration strategy to address the challenges of scarcity and heterogeneity of calibration data. Our strategy focuses on parameters whose initial values cannot be easily derived from the literature, and our goal is to determine the values of these parameters via calibration with constraints set by relevant data. When combined with a covariance matrix adaptation evolution strategy (CMA-ES), this step-by-step approach can be applied to a wide range of biological models. We describe a stepwise, integrative and iterative approach to multiscale mechanistic model calibration, and provide an example of calibrating a pathophysiological lung adenocarcinoma model. Using the approach described here we illustrate the successful calibration of a complex knowledge-based mechanistic model using only the limited heterogeneous datasets publicly available in the literature.

How does mitochondrial function relate to thermogenic capacity and basal metabolic rate in small birds?

We investigated the role of mitochondrial function in the avian thermoregulatory response to a cold environment. Using black-capped chickadees (Poecile atricapillus) acclimated to cold (-10°C) and thermoneutral (27°C) temperatures, we expected to observe an upregulation of pectoralis muscle and liver respiratory capacity that would be visible in mitochondrial adjustments in cold-acclimated birds. We also predicted that these adjustments would correlate with thermogenic capacity (Msum) and basal metabolic rate (BMR). Using tissue high-resolution respirometry, mitochondrial performance was measured as respiration rate triggered by proton leak and the activity of complex I (OXPHOSCI) and complex I+II (OXPHOSCI+CII) in the liver and pectoralis muscle. The activity of citrate synthase (CS) and cytochrome c oxidase (CCO) was also used as a marker of mitochondrial density. We found 20% higher total CS activity in the whole pectoralis muscle and 39% higher total CCO activity in the whole liver of cold-acclimated chickadees relative to that of birds kept at thermoneutrality. This indicates that cold acclimation increased overall aerobic capacity of these tissues. Msum correlated positively with mitochondrial proton leak in the muscle of cold-acclimated birds while BMR correlated with OXPHOSCI in the liver with a pattern that differed between treatments. Consequently, this study revealed a divergence in mitochondrial metabolism between thermal acclimation states in birds. Some functions of the mitochondria covary with thermogenic capacity and basal maintenance costs in patterns that are dependent on temperature and body mass.

Evolving Perspective on the Origin and Diversification of Cellular Life and the Virosphere

The tree of life (TOL) is a powerful framework to depict the evolutionary history of cellular organisms through time, from our microbial origins to the diversification of multicellular eukaryotes that shape the visible biosphere today. During the past decades, our perception of the TOL has fundamentally changed, in part, due to profound methodological advances, which allowed a more objective approach to studying organismal and viral diversity and led to the discovery of major new branches in the TOL as well as viral lineages. Phylogenetic and comparative genomics analyses of these data have, among others, revolutionized our understanding of the deep roots and diversity of microbial life, the origin of the eukaryotic cell, eukaryotic diversity, as well as the origin, and diversification of viruses. In this review, we provide an overview of some of the recent discoveries on the evolutionary history of cellular organisms and their viruses and discuss a variety of complementary techniques that we consider crucial for making further progress in our understanding of the TOL and its interconnection with the virosphere.

Single-cell-resolution map of human retinal pigment epithelium helps discover subpopulations with differential disease sensitivity

Regional phenotypic and functional differences in the retinal pigment epithelium (RPE) monolayer have been suggested to account for regional susceptibility in ocular diseases such as age-related macular degeneration (AMD), late-onset retinal degeneration (L-ORD), and choroideremia (CHM). However, a comprehensive description of human topographical RPE diversity is not yet available, thus limiting the understanding of regional RPE diversity and degenerative disease sensitivity in the eye. To develop a complete morphometric RPE map of the human eye, artificial intelligence–based software was trained to recognize, segment, and analyze RPE borders. Five statistically different, concentric RPE subpopulations (P1 to P5) were identified using cell area as a parameter, including a subpopulation (P4) with cell area comparable to that of macular cells in the far periphery of the eye. This work provides a complete reference map of human RPE subpopulations and their location in the eye. In addition, the analysis of cadaver non-AMD and AMD eyes and ultra-widefield fundus images of patients revealed differential vulnerability of the five RPE subpopulations to different retinal diseases.

Why bears hibernate? Redefining the scaling energetics of hibernation

Hibernation is a natural state of suspended animation that many mammals experience and has been interpreted as an adaptive strategy for saving energy. However, the actual amount of savings that hibernation represents, and particularly its dependence on body mass (the 'scaling') has not been calculated properly. Here, we estimated the scaling of daily energy expenditure of hibernation (DEE_H), covering a range of five orders of magnitude in mass. We found that DEE_H scales isometrically with mass, which means that a gram of hibernating bat has a similar metabolism to that of a gram of bear, 20 000 times larger. Given that metabolic rate of active animals scales allometrically, the point where these scaling curves intersect with DEE_H represents the mass where energy savings by hibernation are zero. For BMR, these zero savings are attained for a relatively small bear (approx. 75 kg). Calculated on a per cell basis, the cellular metabolic power of hibernation was estimated to be 1.3 × 10^-12 ± 2.6 × 10^-13 W cell^-1, which is lower than the minimum metabolism of isolated mammalian cells. This supports the idea of the existence of a minimum metabolism that permits cells to survive under a combination of cold and hypoxia.

Cell Hypertrophy: A “Biophysical Roadblock” to Reversing Kidney Injury

In anamniotes cell loss can typically be compensated for through proliferation, but in amniotes, this capacity has been significantly diminished to accommodate tissue complexity. In order to cope with the increased workload that results from cell death, instead of proliferation highly specialised post-mitotic cells undergo polyploidisation and hypertrophy. Although compensatory hypertrophy is the main strategy of repair/regeneration in various parenchymal tissues, the long-term benefits and its capacity to sustain complete recovery of the kidney has not been addressed sufficiently. In this perspective article we integrate basic principles from biophysics and biology to examine whether renal cell hypertrophy is a sustainable adaptation that can efficiently regenerate tissue mass and restore organ function, or a maladaptive detrimental response.

Sperm metabolic rate predicts female mating frequency across Drosophila species

Female mating rates vary widely, even among closely related species, but the reasons for this variation are not fully understood. Across Drosophila species, female mating frequencies are positively associated with sperm length. This association may be due in part to sperm limitation, with longer-spermed species transferring fewer sperm, or to cryptic female choice. However, a previously overlooked factor is sperm metabolic rate, which may correlate with sperm length. If faster-metabolizing sperm accumulate age-related cellular damage more quickly, then females should remate sooner to obtain fresh sperm. Alternatively, frequent female mating may select for increased sperm competitiveness via increased metabolism. Here, we measure sperm metabolism across 13 Drosophila species and compare these measures to published data on female mating rate and on sperm length. Using fluorescent lifetime imaging microscopy, we quantify NAD(P)H metabolism ex vivo, in intact organs. Phylogenetically controlled regression reveals that sperm metabolic rate is positively associated with sperm length and with female mating frequency. Path analysis shows sperm length driving sperm metabolism and sperm metabolism either driving or being driven by female mating rate. While the causal directionality of these relationships remains to be fully resolved, and the effect of sperm metabolism on sperm aging and/or sperm competitiveness remains to be established, our results demonstrate the importance of sperm metabolism in sexual selection.

Studying metabolism with multi-organ chips: new tools for disease modelling, pharmacokinetics and pharmacodynamics

Non-clinical models to study metabolism including animal models and cell assays are often limited in terms of species translatability and predictability of human biology. This field urgently requires a push towards more physiologically accurate recapitulations of drug interactions and disease progression in the body. Organ-on-chip systems, specifically multi-organ chips (MOCs), are an emerging technology that is well suited to providing a species-specific platform to study the various types of metabolism (glucose, lipid, protein and drug) by recreating organ-level function. This review provides a resource for scientists aiming to study human metabolism by providing an overview of MOCs recapitulating aspects of metabolism, by addressing the technical aspects of MOC development and by providing guidelines for correlation with in silico models. The current state and challenges are presented for two application areas: (i) disease modelling and (ii) pharmacokinetics/pharmacodynamics. Additionally, the guidelines to integrate the MOC data into in silico models could strengthen the predictive power of the technology. Finally, the translational aspects of metabolizing MOCs are addressed, including adoption for personalized medicine and prospects for the clinic. Predictive MOCs could enable a significantly reduced dependence on animal models and open doors towards economical non-clinical testing and understanding of disease mechanisms.

Universal relation for life-span energy consumption in living organisms: Insights for the origin of aging

Metabolic energy consumption has long been thought to play a major role in the aging process (Pearl, The rate of living. University of London Press, London, 1928). Across species, a gram of tissue expends approximately the same amount of energy during the lifespan on average (Speakman, J Exp Biol 208:1717–1730, 2005). Energy restriction has also been shown to increase the maximum lifespan (McCay et al. J Nutr 10:63–79, 1935) and to retard age-associated changes (Weindruch and Walford, The retardation of aging and disease by dietary restriction. CC Thomas, Springfield, 1988). However, there are significant exceptions to universal energy consumption during the lifespan, mainly found by interclass comparison (Ramsey et al. Free Rad Biol Med 29:946–968, 2000; Atanasov, Trakia J Sci 10(3):1–14, 2012). Here, we present a universal relation that relates lifespan energy consumption to several physiological variables, such as body mass, temperature and the ratio of heart rate to respiratory rate, which have been shown to be valid for \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sim 300$$\end{document}∼300 species representing different classes of living organisms, from unicellular organisms to the largest mammals. This relation has an average scattered pattern restricted to factors of 2, with 95% (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$2-\sigma$$\end{document}2-σ) of the organisms having departures of less than a factor of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\pi$$\end{document}π from the relation, despite the difference of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\sim 20$$\end{document}∼20 orders of magnitude in body mass, reducing any possible interclass variation in the relation to only a geometrical factor. This result can be interpreted as supporting evidence for the existence of an approximately constant total number \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathrm{N}}_{{\mathrm{r}}} \sim 10^8$$\end{document}Nr∼108 of respiration cycles per lifetime for all organisms studied, effectively predetermining the extension of life through the basic energetics of respiration (quantified by \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathrm{t}}_{{\mathrm{life}}} = \mathrm{N}_\mathrm{r}/\mathrm{f}_{{\mathrm{resp}}}$$\end{document}tlife=Nr/fresp); this is an incentive to conduct future studies on the relation of such a constant number \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathrm{N}}_{\mathrm{r}}$$\end{document}Nr of cycles per lifetime due to the production rates of free radicals and oxidants or alternative mechanisms, which may yield definite constraints on the origin of aging.

The Effect of the Protein Synthesis Entropy Reduction on the Cell Size Regulation and Division Size of Unicellular Organisms

The underlying mechanism determining the size of a particular cell is one of the fundamental unknowns in cell biology. Here, using a new approach that could be used for most of unicellular species, we show that the protein synthesis and cell size are interconnected biophysically and that protein synthesis may be the chief mechanism in establishing size limitations of unicellular organisms. This result is obtained based on the free energy balance equation of protein synthesis and the second law of thermodynamics. Our calculations show that protein synthesis involves a considerable amount of entropy reduction due to polymerization of amino acids depending on the cytoplasmic volume of the cell. The amount of entropy reduction will increase with cell growth and eventually makes the free energy variations of the protein synthesis positive (that is, forbidden thermodynamically). Within the limits of the second law of thermodynamics we propose a framework to estimate the optimal cell size at division.

Identifying physiological traits of species resilience against environmental stress in freshwater mussels

The advent of global warming events on already stressed organisms by pollution and loss of habitats raised concerns on the sustainability of local mussel populations. The purpose of this study was to study the physiology 6 commonly found species of freshwater mussels in the attempt to identify species at risk from global warming and pollution. The following species were examined for mass/length, energy metabolism, air survival and lipid peroxidation (LPO): Elliptio complanata (EC), Eurynia dilatata (ED), Pyganodon cataracta (PC), Pyganodon species (Psp), Lasmigona costata (LC) and Dreissena bugenis (DB). The data revealed that the estimated longevity of each species was associated with mussel mass, mitochondria electron transport (MET), temperature-dependent MET but negatively related with mitochondria levels in LPO and the colonization potential. The colonization potential was derived from the scaling of MET activity and mass, which confirmed that DB mussels are more invasive than the other species followed by Psp. Resistance to air emersion was significantly associated with longevity, mass and length and mitochondria LPO. Hence, organisms with low lifetimes, mass or length with high LPO are less able to survive for longer periods in air. In conclusion, longevity and air survival was positively associated with mass and energy metabolism but negatively with oxidative damage. This study proposes key markers in identifying species more at risk to contaminant stress, decreased water levels and global warming.

Systematic shifts in scaling behavior based on organizational strategy in universities

To build better theories of cities, companies, and other social institutions such as universities, requires that we understand the tradeoffs and complementarities that exist between their core functions, and that we understand bounds to their growth. Scaling theory has been a powerful tool for addressing such questions in diverse physical, biological and urban systems, revealing systematic quantitative regularities between size and function. Here we apply scaling theory to the social sciences, taking a synoptic view of an entire class of institutions. The United States higher education system serves as an ideal case study, since it includes over 5,800 institutions with shared broad objectives, but ranges in strategy from vocational training to the production of novel research, contains public, nonprofit and for-profit models, and spans sizes from 10 to roughly 100,000 enrolled students. We show that, like organisms, ecosystems and cities, universities and colleges scale in a surprisingly systematic fashion following simple power-law behavior. Comparing seven commonly accepted sectors of higher education organizations, we find distinct regimes of scaling between a school's total enrollment and its expenditures, revenues, graduation rates and economic added value. Our results quantify how each sector leverages specific economies of scale to address distinct priorities. Taken together, the scaling of features within a sector along with the shifts in scaling across sectors implies that there are generic mechanisms and constraints shared by all sectors, which lead to tradeoffs between their different societal functions and roles. We highlight the strong complementarity between public and private research universities, and community and state colleges, that all display superlinear returns to scale. In contrast to the scaling of biological systems, our results highlight that much of the observed scaling behavior is modulated by the particular strategies of organizations rather than an immutable set of constraints.

Fractal analysis reveals functional unit of ventilation in the lung

Ventilation is inhomogeneous in the lungs across species. It has been hypothesized that ventilation inhomogeneity is largely determined by the design of the airway branching network. Because exchange of gases at the alveolar barrier is more efficient when gas concentrations are evenly distributed at subacinar length scales, it is assumed that a 'functional unit' of ventilation exists within the lung periphery, where gas concentration becomes uniform. On the other hand, because the morphology of pulmonary airways and alveoli, and the distribution of inhaled fluorescent particles show self-similar fractal properties over a wide range of length scales, it has been predicted that fractal dimension of ventilation approaches unity within an internally homogeneous functional unit of ventilation. However, the existence of such a functional unit has never been demonstrated experimentally due to lack of in situ gas concentration measurements of sufficient spatial resolution in the periphery of a complex bifurcating network. Here, using energy-subtractive synchrotron radiation tomography, we measured the distribution of an inert gas (Xe) in the in vivo rabbit lung during Xe wash-in breathing manoeuvres. The effects of convective flow rate, diffusion and cardiac motion were also assessed. Fractal analysis of resulting gas concentration and tissue density maps revealed that fractal dimension was always smaller for Xe than for tissue density, and that only for the gas, a length scale existed where fractal dimension approached unity. The length scale where this occurred was seen to correspond to that of a rabbit acinus, the terminal structure comprising only alveolated airways. KEY POINTS: Gas ventilation is inhomogeneous in the lung of many species. However, it is not known down to what length scales this inhomogeneity persists. It is generally assumed that ventilation becomes homogeneous at subacinar length scales, beyond the spatial resolution of commonly available imaging techniques, hence this has not been demonstrated experimentally. Here we measured the distribution of inhaled Xe gas in the rabbit lung using synchrotron radiation energy-subtractive imaging and used fractal analysis to show that ventilation becomes internally uniform within regions about the size of rabbit lung acini.

A quantitative systems pharmacology approach to predict the safe-equivalent dose of doxorubicin in patients with cardiovascular comorbidity

Patients with cardiovascular comorbidity are less tolerant to cardiotoxic drugs and should be treated with reduced doses to prevent cardiotoxicity. However, the safe‐equivalent dose of antitumor drugs in patients with cardiovascular disease/risk is difficult to predict because they are usually excluded from clinical trials as a result of ethical considerations. In this study, a translational quantitative system pharmacology‐pharmacokinetic‐pharmacodynamic (QSP‐PK‐PD) model was developed based on preclinical study to predict the safe‐equivalence dose of doxorubicin in patients with or without cardiovascular disease. Virtual clinical trials were conducted to validate the translational QSP‐PK‐PD model. The model replicated several experimental and clinical observations: the left ventricular ejection fraction (LVEF) was reduced and the left ventricular end‐diastolic volume (LVEDV) was elevated in systolic dysfunction rats, the LVEF was preserved and LVEDV reduced in diastolic dysfunction rats, and patients with preexisting cardiovascular disease were more vulnerable to doxorubicin‐induced cardiac dysfunction than cardiovascular healthy patients. A parameter sensitivity analysis showed that doxorubicin‐induced cardiovascular dysfunction was mainly determined by the sensitivity of cardiomyocytes to cardiotoxic drugs and the baseline value of LVEDV, reflected in LVEF change percentage from the baseline. Blood pressure was the least sensitive factor affecting doxorubicin‐induced cardiotoxicity.

Scaling of joint mass and metabolism fluctuations in in silico cell-laden spheroids

Allometric scaling has many applications, from the prediction of pharmacokinetics in animals and humans to the probing of ecosystem dynamics. Most studies have neglected to account for variations and fluctuations, although they are intrinsic features of all biological systems. To understand how metabolic scaling emerges in the presence of variations, we developed computer-generated models of cell-laden spheroids to define the experimental size range of cell cultures with quantifiable similitudes in terms of fluctuations and metabolic scaling with living organisms. We show that the estimates of scaling exponents may change with increasing variability in both mass and metabolic rate. The computational pipeline described underpins the sound design of statistically meaningful cell-based models, with impacts in both biomedical science and ecology.

Variations and fluctuations are characteristic features of biological systems and are also manifested in cell cultures. Here, we describe a computational pipeline for identifying the range of three-dimensional (3D) cell-aggregate sizes in which nonisometric scaling emerges in the presence of joint mass and metabolic rate fluctuations. The 3D cell-laden spheroids with size and single-cell metabolic rates described by probability density functions were randomly generated in silico. The distributions of the resulting metabolic rates of the spheroids were computed by modeling oxygen diffusion and reaction. Then, a method for estimating scaling exponents of correlated variables through statistically significant data collapse of joint probability distributions was developed. The method was used to identify a physiologically relevant range of spheroid sizes, where both nonisometric scaling and a minimum oxygen concentration (0.04 mol⋅m⁻³) is maintained. The in silico pipeline described enables the prediction of the number of experiments needed for an acceptable collapse and, thus, a consistent estimate of scaling parameters. Using the pipeline, we also show that scaling exponents may be significantly different in the presence of joint mass and metabolic-rate variations typically found in cells. Our study highlights the importance of incorporating fluctuations and variability in size and metabolic rates when estimating scaling exponents. It also suggests the need for taking into account their covariations for better understanding and interpreting experimental observations both in vitro and in vivo and brings insights for the design of more predictive and physiologically relevant in vitro models.

The allometry of cellular DNA and ribosomal gene content among microbes and its use for the assessment of microbiome community structure

BACKGROUND

The determination of taxon-specific composition of microbiomes by combining high-throughput sequencing of ribosomal genes with phyloinformatic analyses has become routine in microbiology and allied sciences. Systematic biases to this approach based on the demonstrable variability of ribosomal operon copy number per genome were recognized early. The more recent realization that polyploidy is probably the norm, rather than the exception, among microbes from all domains of life, points to an even larger source bias.

RESULTS

We found that the number of 16S or 18S RNA genes per cell, a combined result of the number of RNA gene loci per genome and ploidy level, follows an allometric power law of cell volume with an exponent of 2/3 across 6 orders of magnitude in small subunit copy number per cell and 9 orders of magnitude in cell size. This stands in contrast to cell DNA content, which follows a power law with an exponent of ¾.

CONCLUSION

In practical terms, that relationship allows for a single, simple correction for variations in both copy number per genome and ploidy level in ribosomal gene analyses of taxa-specific abundance. In biological terms, it points to the uniqueness of ribosomal gene content among microbial properties that scale with size. Video Abstract.

Larger cells have relatively smaller nuclei across the Tree of Life

Larger cells have larger nuclei, but the precise relationship between cell size and nucleus size remains unclear, and the evolutionary forces that shape this relationship are debated. We compiled data for almost 900 species - from yeast to mammals - at three scales of biological organisation: among-species, within-species, and among-lineages of a species that was artificially selected for cell size. At all scales, we showed that the ratio of nucleus size to cell size (the 'N: C' ratio) decreased systematically in larger cells. Size evolution appears more constrained in nuclei than cells: cell size spans across six orders of magnitude, whereas nucleus size varies by only three. The next important challenge is to determine the drivers of this apparently ubiquitous relationship in N:C ratios across such a diverse array of organisms.

Scale-up economics for cultured meat

This analysis examines the potential of "cultured meat" products made from edible animal cell culture to measurably displace the global consumption of conventional meat. Recognizing that the scalability of such products must in turn depend on the scale and process intensity of animal cell production, this study draws on technoeconomic analysis perspectives in industrial fermentation and upstream biopharmaceuticals to assess the extent to which animal cell culture could be scaled like a fermentation process. Low growth rate, metabolic inefficiency, catabolite inhibition, and shear-induced cell damage will all limit practical bioreactor volume and attainable cell density. Equipment and facilities with adequate microbial contamination safeguards have high capital costs. The projected costs of suitably pure amino acids and protein growth factors are also high. The replacement of amino-acid media with plant protein hydrolysates is discussed and requires further study. Capital- and operating-cost analyses of conceptual cell-mass production facilities indicate economics that would likely preclude the affordability of their products as food. The analysis concludes that metabolic efficiency enhancements and the development of low-cost media from plant hydrolysates are both necessary but insufficient conditions for displacement of conventional meat by cultured meat.

Extrapolating Acute Contact Bee Sensitivity to Insecticides Based on Body Weight Using a Phylogenetically Informed Interspecies Scaling Framework

Plant protection products, including insecticides, are important for global food production but can have adverse effects on nontarget organisms including bees. Historically, research investigating such effects has focused mainly on the honeybee (Apis mellifera), whereas less information is available for non-Apis bees. Consequently, a comprehensive hazard (sensitivity) assessment for the majority of bees is lacking, which in turn hinders accurate risk characterization and consequently bee protection. Interspecies sensitivity extrapolation based on body weight might be a way to improve the situation, but in the past such approaches often ignored the phylogenetic background of the species used, which in turn potentially reduces the robustness of such results. Published acute contact sensitivity data (median lethal dose per bee) of bees to insecticides, their body weight, and their phylogenetic background were used to build interspecies scaling models to predict bee sensitivity based on their weight. The results indicate that 1) bee body weight is a predictor of acute contact bee sensitivity to a range of insecticides, and 2) phylogeny (nonindependence of data points) needs to be considered in cross-species analysis, although it does not always confound the observed effects.  Environ Toxicol Chem 2021;40:2044-2052. © 2021 SETAC.

Metabolomics of aging in primary fibroblasts from small and large breed dogs

Among several animal groups (eutherian mammals, birds, reptiles), lifespan positively correlates with body mass over several orders of magnitude. Contradicting this pattern are domesticated dogs, with small dog breeds exhibiting significantly longer lifespans than large dog breeds. The underlying mechanisms of differing aging rates across body masses are unclear, but it is generally agreed that metabolism is a significant regulator of the aging process. Herein, we performed a targeted metabolomics analysis on primary fibroblasts isolated from small and large breed young and old dogs. Regardless of size, older dogs exhibited lower glutathione and ATP, consistent with a role for oxidative stress and bioenergetic decline in aging. Furthermore, several size-specific metabolic patterns were observed with aging, including the following: (i) An apparent defect in the lower half of glycolysis in large old dogs at the level of pyruvate kinase. (ii) Increased glutamine anaplerosis into the TCA cycle in large old dogs. (iii) A potential defect in coenzyme A biosynthesis in large old dogs. (iv) Low nucleotide levels in small young dogs that corrected with age. (v) An age-dependent increase in carnitine in small dogs that was absent in large dogs. Overall, these data support the hypothesis that alterations in metabolism may underlie the different lifespans of small vs. large breed dogs, and further work in this area may afford potential therapeutic strategies to improve the lifespan of large dogs.

Patient-Specific Organoid and Organ-on-a-Chip: 3D Cell-Culture Meets 3D Printing and Numerical Simulation

The last few decades have witnessed diversified in vitro models to recapitulate the architecture and function of living organs or tissues and contribute immensely to advances in life science. Two novel 3D cell culture models: 1) Organoid, promoted mainly by the developments of stem cell biology and 2) Organ-on-a-chip, enhanced primarily due to microfluidic technology, have emerged as two promising approaches to advance the understanding of basic biological principles and clinical treatments. This review describes the comparable distinct differences between these two models and provides more insights into their complementarity and integration to recognize their merits and limitations for applicable fields. The convergence of the two approaches to produce multi-organoid-on-a-chip or human organoid-on-a-chip is emerging as a new approach for building 3D models with higher physiological relevance. Furthermore, rapid advancements in 3D printing and numerical simulations, which facilitate the design, manufacture, and results-translation of 3D cell culture models, can also serve as novel tools to promote the development and propagation of organoid and organ-on-a-chip systems. Current technological challenges and limitations, as well as expert recommendations and future solutions to address the promising combinations by incorporating organoids, organ-on-a-chip, 3D printing, and numerical simulation, are also summarized.

Rational Clinical Dose Selection of Adeno-Associated Virus-Mediated Gene Therapy Based on Allometric Principles

One of the challenges in translational medicine is to select first-in-human doses of investigational drugs based on findings in preclinical studies. Despite substantial progress in the optimization of recombinant adeno-associated virus (AAV) vectors of in vivo gene therapy for treating various diseases, there remain significant limitations to the use of preclinical data to guide dose selection in clinical trials. Here we introduce a novel concept of gene efficiency factor (GEF) to describe the efficiency of the gene transfer system and describe and apply the concept of GEF in AAV-mediated in vivo gene transfer systems. We explore the utility of allometric scaling to translate GEF across species using AAV-mediated in vivo factor IX (FIX) gene therapy for hemophilia B and to demonstrate the use of GEF in predicting efficacious AAV vector doses in humans. We show for the first time that an allometric relationship exists for GEF of AAV-mediated in vivo gene therapy. Furthermore, we demonstrate the feasibility of using the allometric relationship of GEF to select efficacious first-in-human doses of virus-mediated invivo gene therapy. Based on our findings, allometry of GEF can be used to translate biological efficiency from animal studies to clinical studies and provide a rational basis of setting first-in-human doses for new virus-mediated invivo gene therapy products.

Tools and approaches for analyzing the role of mitochondria in health, development and disease using human cerebral organoids

Mitochondria are cellular organelles involved in generating energy to power various processes in the cell. Although the pivotal role of mitochondria in neurogenesis was demonstrated (first in animal models), very little is known about their role in human embryonic neurodevelopment and its pathology. In this respect human-induced pluripotent stem cells (hiPSC)-derived cerebral organoids provide a tractable, alternative model system of the early neural development and disease that is responsive to pharmacological and genetic manipulations, not possible to apply in humans. Although the involvement of mitochondria in the pathogenesis and progression of neurodegenerative diseases and brain dysfunction has been demonstrated, the precise role they play in cell life and death remains unknown, compromising the development of new mitochondria-targeted approaches to treat human diseases. The cerebral organoid model of neurogenesis and disease in vitro provides an unprecedented opportunity to answer some of the most fundamental questions about mitochondrial function in early human neurodevelopment and neural pathology. Largely an unexplored territory due to the lack of tools and approaches, this review focuses on recent technological advancements in fluorescent and molecular tools, imaging systems, and computational approaches for quantitative and qualitative analyses of mitochondrial structure and function in three-dimensional cellular assemblies-cerebral organoids. Future developments in this direction will further facilitate our understanding of the important role or mitochondrial dynamics and energy requirements during early embryonic development. This in turn will provide a further understanding of how dysfunctional mitochondria contribute to disease processes.

How should functional relationships be evaluated using phylogenetic comparative methods? A case study using metabolic rate and body temperature

Phylogenetic comparative methods are often used to test functional relationships between traits. However, million-year macroevolutionary observational datasets cannot definitively prove causal links between traits-correlation does not equal causation and experimental manipulation over such timescales is impossible. Although this caveat is widely understood, it is less appreciated that different phylogenetic approaches imply different causal assumptions about the functional relationships of traits. To make meaningful inferences, it is critical that our statistical methods make biologically reasonable assumptions. Here we illustrate the importance of causal reasoning in comparative biology by examining a recent study by Avaria-Llautureo et al (2019). that tested for the evolutionary coupling of metabolic rate and body temperature across endotherms and found that these traits were unlinked through evolutionary time and that body temperatures were, on average, higher in the early Cenozoic than they are today. We argue that the causal assumptions embedded into their models made it impossible for them to test the relevant functional and evolutionary hypotheses. We reanalyze their data using more biologically appropriate models and find support for the exact opposite conclusions, corroborating previous evidence from physiology and paleontology. We highlight the vital need for causal thinking, even when experiments are impossible.

Multi-organ-on-a-chip for pharmacokinetics and toxicokinetic study of drugs

Introduction: Accurate prediction of pharmacokinetic (PK) and toxicokinetics (TK) of drugs is imperative for successful development of new pharmaceutics. Although conventional in vitro methods for predicting the PK and TK of drugs are well established, limitations still exist and more advanced chip-based in vitro platforms combined with mathematical models can help researchers overcome the limitations. Areas covered: We will review recent progress in the development of multi-organ-on-a-chip platforms for predicting PK and TK of drugs, as well as mathematical approaches that can be combined with these platforms for experiment design, data analysis and in vitro-in vivo extrapolation (IVIVE) for application to humans. Expert opinion: Although there remain some challenges to be addressed, the remarkable progress in the area of multi-organ-on-a-chip in recent years indicate that we will see tangible outcomes that can be utilized in the pharmaceutical industry in near future.

Diversity of Dominant Soil Bacteria Increases with Warming Velocity at the Global Scale

Understanding global soil bacterial diversity is important because of its role in maintaining a healthy global ecosystem. Given the effects of environmental changes (e.g., warming and human impact) on the diversity of animals and plants, effects on soil bacterial diversity are expected; however, they have been poorly evaluated at the global scale to date. Thus, in this study, we focused on the dominant soil bacteria, which are likely critical drivers of key soil processes worldwide, and investigated the effects of warming velocity and human activities on their diversity. Using a global dataset of bacteria, we performed spatial analysis to evaluate the effects of warming velocity and human activities, while statistically controlling for the potentially confounding effects of current climate and geographic parameters with global climate and geographic data. We demonstrated that the diversity of the dominant soil bacteria was influenced globally, not only by the aridity index (dryness) and pH but also by warming velocity from the Last Glacial Maximum (21,000 years ago) to the present, showing significant increases. The increase in bacterial diversity with warming velocity was particularly significant in forests and grasslands. An effect of human activity was also observed, but it was secondary to warming velocity. These findings provide robust evidence and advance our understanding of the effects of environmental changes (particularly global warming) on soil bacterial diversity at the global scale.

A Micromachined Picocalorimeter Sensor for Liquid Samples with Application to Chemical Reactions and Biochemistry

Calorimetry has long been used to probe the physical state of a system by measuring the heat exchanged with the environment as a result of chemical reactions or phase transitions. Application of calorimetry to microscale biological samples, however, is hampered by insufficient sensitivity and the difficulty of handling liquid samples at this scale. Here, a micromachined calorimeter sensor that is capable of resolving picowatt levels of power is described. The sensor consists of low-noise thermopiles on a thin silicon nitride membrane that allow direct differential temperature measurements between a sample and four coplanar references, which significantly reduces thermal drift. The partial pressure of water in the ambient around the sample is maintained at saturation level using a small hydrogel-lined enclosure. The materials used in the sensor and its geometry are optimized to minimize the noise equivalent power generated by the sensor in response to the temperature field that develops around a typical sample. The experimental response of the sensor is characterized as a function of thermopile dimensions and sample volume, and its capability is demonstrated by measuring the heat dissipated during an enzymatically catalyzed biochemical reaction in a microliter-sized liquid droplet. The sensor offers particular promise for quantitative measurements on biological systems.

Bioenergetics in environmental adaptation and stress tolerance of aquatic ectotherms: linking physiology and ecology in a multi-stressor landscape

Energy metabolism (encompassing energy assimilation, conversion and utilization) plays a central role in all life processes and serves as a link between the organismal physiology, behavior and ecology. Metabolic rates define the physiological and life-history performance of an organism, have direct implications for Darwinian fitness, and affect ecologically relevant traits such as the trophic relationships, productivity and ecosystem engineering functions. Natural environmental variability and anthropogenic changes expose aquatic ectotherms to multiple stressors that can strongly affect their energy metabolism and thereby modify the energy fluxes within an organism and in the ecosystem. This Review focuses on the role of bioenergetic disturbances and metabolic adjustments in responses to multiple stressors (especially the general cellular stress response), provides examples of the effects of multiple stressors on energy intake, assimilation, conversion and expenditure, and discusses the conceptual and quantitative approaches to identify and mechanistically explain the energy trade-offs in multiple stressor scenarios, and link the cellular and organismal bioenergetics with fitness, productivity and/or ecological functions of aquatic ectotherms.

Uncoupling proteins in the mitochondrial defense against oxidative stress

Oxidative stress is a major component of most major retinal diseases. Many extrinsic anti-oxidative strategies have been insufficient at counteracting one of the predominant intrinsic sources of reactive oxygen species (ROS), mitochondria. The proton gradient across the inner mitochondrial membrane is a key driving force for mitochondrial ROS production, and this gradient can be modulated by members of the mitochondrial uncoupling protein (UCP) family. Of the UCPs, UCP2 shows a widespread distribution and has been shown to uncouple oxidative phosphorylation, with concomitant decreases in ROS production. Genetic studies using transgenic and knockout mice have documented the ability of increased UCP2 activity to provide neuroprotection in models of a number of diseases, including retinal diseases, indicating that it is a strong candidate for a therapeutic target. Molecular studies have identified the structural mechanism of action of UCP2 and have detailed the ways in which its expression and activity can be controlled at the transcriptional, translational and posttranslational levels. These studies suggest a number of ways in control of UCP2 expression and activity can be used therapeutically for both acute and chronic conditions. The development of such therapeutic approaches will greatly increase the tools available to combat a broad range of serious retinal diseases.

Image-based scaling laws for somatic growth and pulmonary artery morphometry from infancy to adulthood

Pulmonary artery (PA) morphometry has been extensively explored in adults, with particular focus on intra-acinar arteries. However, scaling law relationships for length and diameter of extensive preacinar PAs by age have not been previously reported for in vivo human data. To understand preacinar PA growth spanning children to adults, we performed morphometric analyses of all PAs visible in the computed tomography (CT) and magnetic resonance (MR) images from a healthy subject cohort [n = 16; age: 1-51 yr; body surface area (BSA): 0.49-2.01 m²]. Subject-specific anatomic PA models were constructed from CT and MR images, and morphometric information-diameter, length, tortuosity, bifurcation angle, and connectivity-was extracted and sorted into diameter-defined Strahler orders. Validation of Murray's law, describing optimal scaling exponents of radii for branching vessels, was performed to determine how closely PAs conform to this classical relationship. Using regression analyses of vessel diameters and lengths against orders and patient metrics (BSA, age, height), we found that diameters increased exponentially with order and allometrically with patient metrics. Length increased allometrically with patient metrics, albeit weakly. The average tortuosity index of all vessels was 0.026 ± 0.024, average bifurcation angle was 28.2 ± 15.1°, and average Murray's law exponent was 2.92 ± 1.07. We report a set of scaling laws for vessel diameter and length, along with other morphometric information. These provide an initial understanding of healthy structural preacinar PA development with age, which can be used for computational modeling studies and comparison with diseased PA anatomy.NEW & NOTEWORTHY Pulmonary artery (PA) morphometry studies to date have focused primarily on large arteries and intra-acinar arteries in either adults or children, neglecting preacinar arteries in both populations. Our study is the first to quantify in vivo preacinar PA morphometry changes spanning infants to adults. For preacinar arteries > 1 mm in diameter, we identify scaling laws for vessel diameters and lengths with patient metrics of growth and establish a healthy PA morphometry baseline for most preacinar PAs.

Enamel multidien biological timing and body size variability among individuals of Chinese Han and Tibetan origins

AIMS

To measure the number of days of enamel formation between periodic striae of Retzius growth lines, the Retzius periodicity (RP), and to compare this multi-day, or multidien rhythm, to body height and weight among people from Beijing, China and Lhasa, Tibet/China.

SUBJECTS AND METHODS

Subjects requiring dental extractions from clinics in Beijing, China (N = 338) and Lhasa, Tibet/China (N = 227) provided a tooth and body size information. Multiple observers examined histological sections of the teeth and recorded RP. RP values were statistically compared to body height and weight.

RESULTS

In Beijing and Lhasa samples, respectively, average height was 166.38 and 165.70 cm, average weight was 59.53 and 66.53 kg, and average RP was 7.47 and 7.69 d. Statistically significant differences were found between Beijing and Lhasa weight and RP means. Correlations for height and weight against RP were significant, but only comparatively strong for height.

CONCLUSIONS

Supporting the negative correlation presented in previous studies, RP is negatively associated with height and weight among a large intraspecific sample of people from Beijing and Lhasa. RP represents a metabolic-mediated multidien biological timing mechanism responsible for the rate of cell proliferation and maintenance of the body.

Mitochondrial performance of a continually growing marine bivalve, Mytilus edulis, depends on body size

Allometric decline of mass-specific metabolic rate with increasing body size in organisms is a well-documented phenomenon. Despite a long history of research, the mechanistic causes of metabolic scaling with body size remain under debate. Some hypotheses suggest that intrinsic factors such as allometry of cellular and mitochondrial metabolism may contribute to the organismal-level metabolic scaling. The aim of our present study was to determine the metabolic allometry at the mitochondrial level using a continually growing marine ectotherm, the mussel Mytilus edulis, as a model. Mussels from a single cohort that considerably differed in body size were selected, implying faster growth in the larger specimens. We determined the body mass-dependent scaling of the mitochondrial proton leak respiration, respiration in the presence of ADP indicative of the oxidative phosphorylation (OXPHOS), and maximum activity of the mitochondrial electron transport system (ETS) and cytochrome c oxidase (COX). Respiration was measured at normal (15°C), and elevated (27°C) temperatures. The results demonstrated a pronounced allometric increase in both proton leak respiration and OXPHOS activity of mussel mitochondria. Mussels with faster growth (larger body size) showed an increase in OXPHOS rate, proton leak respiration rate, and ETS and COX activity (indicating an overall improved mitochondrial performance) and higher respiratory control ratio (indicating better mitochondrial coupling and potentially lower costs of mitochondrial maintenance at the same OXPHOS capacity) compared with slower growing (smaller) individuals. Our data show that the metabolic allometry at the organismal level cannot be directly explained by mitochondrial functioning.

The power of amphibians to elucidate mechanisms of size control and scaling

Size is a fundamental feature of biology that affects physiology at all levels, from the organism to organs and tissues to cells and subcellular structures. How size is determined at these different levels, and how biological structures scale to fit together and function properly are important open questions. Historically, amphibian systems have been extremely valuable to describe scaling phenomena, as they occupy some of the extremes in biological size and are amenable to manipulations that alter genome and cell size. More recently, the application of biochemical, biophysical, and embryological techniques to amphibians has provided insight into the molecular mechanisms underlying scaling of subcellular structures to cell size, as well as how perturbation of normal size scaling impacts other aspects of cell and organism physiology.

Body Mass Dynamics Is Determined by the Metabolic Ohm's Law and Adipocyte-Autonomous Fat Mass Homeostasis

An ODE model integrating metabolic mechanisms with clinical data reveals an Ohm's law governing lifetime body mass dynamics, where fat and lean tissues are analogous to a parallel nonlinear capacitor and resistor, respectively. The law unexpectedly decouples weight stability (a cell-autonomous property of adipocytes) and weight change (a parabolic trajectory governed by Ohm's law). In middle age, insulin resistance causes fat accumulation to avoid excessive body shrinkage in old age. Moderate middle-age spread is thus natural, not an anomaly caused by hypothalamic defects, as proposed by lipostatic theory. These discoveries provide valuable insights into health care practices such as weight control and health assessment, explain certain observed phenomena, make testable predictions, and may help to resolve major conundrums in the field. The ODE model, which is more comprehensive than Ohm's law, is useful to study metabolism at the detailed microscopic levels.

Toward Engineering Biosystems With Emergent Collective Functions

Many complex behaviors in biological systems emerge from large populations of interacting molecules or cells, generating functions that go beyond the capabilities of the individual parts. Such collective phenomena are of great interest to bioengineers due to their robustness and scalability. However, engineering emergent collective functions is difficult because they arise as a consequence of complex multi-level feedback, which often spans many length-scales. Here, we present a perspective on how some of these challenges could be overcome by using multi-agent modeling as a design framework within synthetic biology. Using case studies covering the construction of synthetic ecologies to biological computation and synthetic cellularity, we show how multi-agent modeling can capture the core features of complex multi-scale systems and provide novel insights into the underlying mechanisms which guide emergent functionalities across scales. The ability to unravel design rules underpinning these behaviors offers a means to take synthetic biology beyond single molecules or cells and toward the creation of systems with functions that can only emerge from collectives at multiple scales.

Mass measurements during lymphocytic leukemia cell polyploidization decouple cell cycle- and cell size-dependent growth

Cell size is believed to influence cell growth through limited transport efficiency in larger cells. However, this has not been experimentally investigated due to a lack of noninvasive, high-precision growth quantification methods suitable for measuring large cells. Here, we have engineered large versions of microfluidic mass sensors called suspended microchannel resonators in order to study the growth of single mammalian cells that range 100-fold in mass. Our measurements, which decouple growth effects caused by cell cycle and cell size, revealed that absolute cell size does not impose strict transport or other limitations that would inhibit growth and that cell cycle has a large influence on growth.

Cell size is believed to influence cell growth and metabolism. Consistently, several studies have revealed that large cells have lower mass accumulation rates per unit mass (i.e., growth efficiency) than intermediate-sized cells in the same population. Size-dependent growth is commonly attributed to transport limitations, such as increased diffusion timescales and decreased surface-to-volume ratio. However, separating cell size- and cell cycle-dependent growth is challenging. To address this, we monitored growth efficiency of pseudodiploid mouse lymphocytic leukemia cells during normal proliferation and polyploidization. This was enabled by the development of large-channel suspended microchannel resonators that allow us to monitor buoyant mass of single cells ranging from 40 pg (small pseudodiploid cell) to over 4,000 pg, with a resolution ranging from ∼1% to ∼0.05%. We find that cell growth efficiency increases, plateaus, and then decreases as cell cycle proceeds. This growth behavior repeats with every endomitotic cycle as cells grow into polyploidy. Overall, growth efficiency changes 33% throughout the cell cycle. In contrast, increasing cell mass by over 100-fold during polyploidization did not change growth efficiency, indicating exponential growth. Consistently, growth efficiency remained constant when cell cycle was arrested in G₂. Thus, cell cycle is a primary determinant of growth efficiency. As growth remains exponential over large size scales, our work finds no evidence for transport limitations that would decrease growth efficiency.

Sub-nanowatt resolution direct calorimetry for probing real-time metabolic activity of individual C. elegans worms

Calorimetry has been widely used in metabolic studies, but direct measurements from individual small biological model organisms such as C. elegans or isolated single cells have been limited by poor sensitivity of existing techniques and difficulties in resolving very small heat outputs. Here, by careful thermal engineering, we developed a robust, highly sensitive and bio-compatible calorimetric platform that features a resolution of ~270 pW—more than a 500-fold improvement over the most sensitive calorimeter previously used for measuring the metabolic heat output of C. elegans. Using this calorimeter, we demonstrate time-resolved metabolic measurements of single C. elegans worms from larval to adult stages. Further, we show that the metabolic output is significantly lower in long-lived C. elegans daf-2 mutants. These demonstrations clearly highlight the broad potential of this tool for studying the role of metabolism in disease, development and aging of small model organisms and single cells.

Calorimetry is widely used for metabolic studies, but measurements of single cells and small organisms are limited by the sensitivity of current techniques. Here the authors develop a sensitive platform for performing time-resolved metabolic measurements of single C. elegans worms from larval to adult stages.

Sub-nanowatt microfluidic single-cell calorimetry

Non-invasive and label-free calorimetry could become a disruptive technique to study single cell metabolic heat production without altering the cell behavior, but it is currently limited by insufficient sensitivity. Here, we demonstrate microfluidic single-cell calorimetry with 0.2-nW sensitivity, representing more than ten-fold enhancement over previous record, which is enabled by (i) a low-noise thermometry platform with ultralow long-term (10-h) temperature noise (80 μK) and (ii) a microfluidic channel-in-vacuum design allowing cell flow and nutrient delivery while maintaining a low thermal conductance of 2.5 μW K⁻¹. Using Tetrahymena thermophila as an example, we demonstrate on-chip single-cell calorimetry measurement with metabolic heat rates ranging from 1 to 4 nW, which are found to correlate well with the cell size. Finally, we perform real-time monitoring of metabolic rate stimulation by introducing a mitochondrial uncoupling agent to the microchannel, enabling determination of the spare respiratory capacity of the cells.

Calorimetrically measuring the heat of single cells is currently not possible due to the sensitivity of existing calorimeters. Here the authors present on-chip single cell calorimetry, with a sensitivity over ten-fold greater than the current gold-standard.