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Comment on “Female toads engaging in adaptive hybridization prefer high-quality heterospecifics as mates”

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Abstract

Chen and Pfennig (Reports, 20 March 2020, p. 1377) analyze the fitness consequences of hybridization in toads but do not account for differences in survival among progeny. Apparent fitness effects depend on families with anomalously low survival, yet survival is crucial to evolutionary fitness. This and other analytical shortcomings demonstrate that a conclusion of adaptive mate choice is not yet justified.

Chen and Pfennig (1) extend the potential impact of hybrid zone studies with a report of adaptive heterospecific mate choice in spadefoot toads, a result with far-reaching implications (2). However, survival is crucial to evolutionary fitness (3), and hybrid vigor, while common, does not always predict fitness. We wondered how consideration of these issues would affect their conclusions.

Central to their claim is an experiment in which 20 female Spea bombifrons were paired with 20 male Spea multiplicata. Survival and growth of up to 50 progeny per pair were monitored for 12 days, when several measures were taken [mass, snout-vent length (SVL), Gosner stage (an ordinal scale of development)]. These measures were highly correlated, so the authors used principal components analysis to derive an overall proxy of tadpole fitness (PC1). They then analyzed several linear models to explore whether variation in this proxy was correlated with parental size, condition, genotype, and sire vocalizations. This analysis resulted in their figure 1, which illustrates their conclusion that tadpole fitness is predicted by father’s call (sire pulse rate).

We noticed that their results might depend on three outlier families at the upper or lower ends of the observed range in sire pulse rate (their figure 1). These three families also had low survival rates (≤30% versus mean of 64% for 17 families with surviving tadpoles) [table S2 of (1)]. The authors concluded that “Hybrid tadpole survivorship was not significantly predicted by any parental traits” [supplementary text of (1)], but they only considered linear models. In fact, a nonlinear, unimodal relationship between survival and sire pulse rate better fits the data (Fig. 1A), which suggests that survival should not be ignored. Furthermore, three families with zero survival were excluded (4) and two of these also had low sire pulse rates (Fig. 1A). The distribution of PC1 is surely truncated in families with low survival, but it is difficult to assess the impact of truncation given the experimental design.

Fig. 1 Relationships between sire pulse rate and fitness proxies do not support adaptive mate choice.

(A) Tadpole survival and sire pulse rates for 17 families analyzed by Chen and Pfennig (1) (black dots) and for three families not included in their analyses (red dots) (4). A nonlinear unimodal model (black line) for n = 17 families had P = 0.014 for the joint effect of the linear and quadratic terms. This model fits significantly better (ΔAICc = 6.35) than a linear model (12). AICc is the Akaike information criterion with correction for small sample sizes. (B) Estimated relationship of mean principal component 1 (PC1) scores and sire pulse rate for 17 families (n = 479 tadpoles) from a mixed-effects model with a random effect for family plus a linear fixed effect for sire pulse rate (black line) and for a model using only a random effect for family (red lines), which demonstrates lack of fit of the linear relationship. (C) Quantile splits for the separation of PC1 score distributions for tadpoles illustrate the lack of predictive power of sire pulse rate. The solid black line is the mean regression estimate from the mixed-effects model of Chen and Pfennig, as in (B). The lower and upper red lines are the 0.36 and 0.64 quantiles, respectively, and the lower and upper blue lines are the 0.21 and 0.79 quantiles, respectively, from the normal distribution. These correspond to quantile splits QS(1.93) = 0.36 and QS(4.31) = 0.21, indicating 36% and 21% overlap in PC1 probability distributions, respectively. The horizontal dashed red and blue lines depict separation distances = 1.93 (median – minimum) and 4.31 pulses/s (maximum – minimum), respectively. Quantile splits for the PC1 score distribution at any separation distance are computed as QS(separation distance) = Φ[–|estimated slope for sire pulse rate|×(separation distance)/(2 × estimated standard deviation of regression)], where Φ is the normal distribution function (8, 9). Here, the estimated slope is –0.928 and the estimated standard deviation of the regression is 2.528.

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Fig. 1 Relationships between sire pulse rate and fitness proxies do not support adaptive mate choice.

(A) Tadpole survival and sire pulse rates for 17 families analyzed by Chen and Pfennig (1) (black dots) and for three families not included in their analyses (red dots) (4). A nonlinear unimodal model (black line) for n = 17 families had P = 0.014 for the joint effect of the linear and quadratic terms. This model fits significantly better (ΔAICc = 6.35) than a linear model (12). AICc is the Akaike information criterion with correction for small sample sizes. (B) Estimated relationship of mean principal component 1 (PC1) scores and sire pulse rate for 17 families (n = 479 tadpoles) from a mixed-effects model with a random effect for family plus a linear fixed effect for sire pulse rate (black line) and for a model using only a random effect for family (red lines), which demonstrates lack of fit of the linear relationship. (C) Quantile splits for the separation of PC1 score distributions for tadpoles illustrate the lack of predictive power of sire pulse rate. The solid black line is the mean regression estimate from the mixed-effects model of Chen and Pfennig, as in (B). The lower and upper red lines are the 0.36 and 0.64 quantiles, respectively, and the lower and upper blue lines are the 0.21 and 0.79 quantiles, respectively, from the normal distribution. These correspond to quantile splits QS(1.93) = 0.36 and QS(4.31) = 0.21, indicating 36% and 21% overlap in PC1 probability distributions, respectively. The horizontal dashed red and blue lines depict separation distances = 1.93 (median – minimum) and 4.31 pulses/s (maximum – minimum), respectively. Quantile splits for the PC1 score distribution at any separation distance are computed as QS(separation distance) = Φ[–|estimated slope for sire pulse rate|×(separation distance)/(2 × estimated standard deviation of regression)], where Φ is the normal distribution function (8, 9). Here, the estimated slope is –0.928 and the estimated standard deviation of the regression is 2.528.

We were also concerned about relying on measures of tadpole growth as the sole fitness metric in a hybrid system. Hybridization is often maladaptive, as it is for female S. multiplicata in this system (2, 5). Heterosis (hybrid vigor) is common but does not always predict reproductive success: Mules are stronger than horses, but their lifetime fitness is zero. Although mass, SVL, and Gosner stage may sometimes be reasonable fitness proxies, these measures could reflect heterotic effects in this hybrid system. Moreover, these measures ignore critical later stages of the life cycle—including metamorphosis, survival, fertility, sex ratio, and mating success—all of which affect how selection operates on adult traits, such as male calling rate and female preference. Complete fitness estimates require following the fate of offspring from zygote until reproduction and ideally until death. These caveats, together with the question of how to deal with survival, led us to examine more closely the evidence that sire pulse rate predicts tadpole fitness.

Because the authors sought to estimate the partial effect of each fixed effect on mean PC1 scores, it was incorrect to model-average regression coefficients (6) without accounting for multicollinearity among the predictors in the standardization (7). In fact, neither is necessary. We explored the partial effects of sire pulse rate by examining estimates across the five models that included this term [table S3 of (1)] without standardization or model averaging. The models included random effects for each family and fixed effects for sire pulse rate and other parental predictors, each of which had a single unique value for each family. Thus, their analysis inherently considers parental predictors to enter models both as categorical variables (through random effects on family) and as fixed linear effects.

Comparing a model with only family effects (equivalent to a categorical model for sire pulse rate, conditional R2 = 0.289) to models that included a linear fixed effect for sire pulse rate indicated substantial lack of fit for the linear predictor (Fig. 1B) across the five models (marginal R2 = 0.042 to 0.057). This analysis revealed that there is no consistent decline in mean PC1 scores up to a sire pulse rate of 27; in fact, most of the decline is due to a single family, which also had low survival, with the highest pulse rate. Estimating models excluding this family, we found that regression coefficients for sire pulse rate diminished greatly and were not statistically different from zero (P > 0.05) for three of the five models. The combination of lack of fit of the linear relationship of sire pulse rate, the low proportion of variance attributed to it, and small effect size of sire pulse rate (β^ = –1.214 to –0.928) relative to the estimated standard deviation (σ^ = 2.526 to 2.529) of the regressions indicates extensive overlap in PC1 distributions with minimal explanatory ability for sire pulse rate (Fig. 1C) (8, 9).

Lastly, using a principal component score to estimate fitness is undesirable because it is a synthetic mathematical construct that lacks straightforward interpretation. In this case, the authors combine two continuous variables (mass, SVL) with an ordinal one (Gosner stage) using covariances that fail to account for scale differences. A more direct, easily interpreted measure of tadpole condition is to estimate mass (M) as an allometric function of size (SVL); that is, M = β0SVLβ1 (10, 11). We estimated this model for median mass at SVL with separate intercepts and exponents for each of 16 families using quantile regression (Fig. 2A) (10). We did not include Gosner stage as a predictor, because it had a weak effect (P = 0.079) and only reduced the coefficient of determination by 0.002. Estimated median mass at SVL = 14 mm with 95% confidence intervals for each family reveals considerable overlap and no distinct pattern when plotted against sire pulse rate (Fig. 2B) or tadpole survival (Fig. 2C); these findings indicate that tadpole condition was not related to either variable (also true for female SVL, not shown).

Fig. 2 Allometric modeling reveals extensive overlap in tadpole condition.

(A) Allometric relationships of tadpole mass (g) and snout-vent length (SVL, mm) for 16 families of tadpoles from Chen and Pfennig (1). Family 15 with a single surviving tadpole was excluded from this analysis. This model indicates higher condition for tadpoles with greater mass at a common SVL achieved during the 12-day time interval. Estimated median regression relationships for the families with lowest (red) and highest (blue) sire pulse rates from the quantile regression model allow separate intercepts and slopes for each family, p = 32 parameters and n = 478. The allometric relationship was estimated in a linear model as log(M) = log(β0) + β1 log(SVL) and back-transformed to the multiplicative form. Here, we used log10 and included indicator variables for 16 families and their interaction with SVL. The coefficient of determination for this model is 0.691 in absolute deviations (P < 0.001), which is equivalent to 0.905 = 1.0 – (1.0 – 0.691)2 in squared deviations similar to R2. (B) Median mass at SVL = 14 mm and 95% confidence intervals (bootstrapped) estimated for each of the 16 families and graphed with respect to their corresponding sire pulse rates. Similar patterns were obtained for SVL = 12 and 16 mm, not shown. (C) Same as (B) but now plotted against tadpole survival.

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Fig. 2 Allometric modeling reveals extensive overlap in tadpole condition.

(A) Allometric relationships of tadpole mass (g) and snout-vent length (SVL, mm) for 16 families of tadpoles from Chen and Pfennig (1). Family 15 with a single surviving tadpole was excluded from this analysis. This model indicates higher condition for tadpoles with greater mass at a common SVL achieved during the 12-day time interval. Estimated median regression relationships for the families with lowest (red) and highest (blue) sire pulse rates from the quantile regression model allow separate intercepts and slopes for each family, p = 32 parameters and n = 478. The allometric relationship was estimated in a linear model as log(M) = log(β0) + β1 log(SVL) and back-transformed to the multiplicative form. Here, we used log10 and included indicator variables for 16 families and their interaction with SVL. The coefficient of determination for this model is 0.691 in absolute deviations (P < 0.001), which is equivalent to 0.905 = 1.0 – (1.0 – 0.691)2 in squared deviations similar to R2. (B) Median mass at SVL = 14 mm and 95% confidence intervals (bootstrapped) estimated for each of the 16 families and graphed with respect to their corresponding sire pulse rates. Similar patterns were obtained for SVL = 12 and 16 mm, not shown. (C) Same as (B) but now plotted against tadpole survival.

We conclude that the authors’ claim of adaptive heterospecific mate choice is not well supported by their analyses or available data, but we encourage them to continue their insightful work on this remarkable system.

References and Notes

  1. Data on these three families were provided by the authors (C. Chen and K. S. Pfennig). One of these families produced no eggs; the other two produced eggs, but embryos failed to develop beyond the hatching stage.
  2. R scripts for all modeling in this Comment are deposited in the DRUM archive at the University of Maryland with the following identifier: http://hdl.handle.net/1903/26347.

Acknowledgments: R. C. Bell and P. M. Dixon provided helpful comments on an earlier draft of this work.

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This 14-Year-Old’s Discovery Could Lead to a Cure for COVID-19

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With no clear end in sight to the pandemic, there is an urgent need for a cure to COVID-19. As scientists around the world work to develop possible vaccines, one 14-year-old girl from Texas has made a new discovery that could lead to a potential treatment.

On Wednesday, Anika Chebrolu from Frisco, Texas was named the winner of the 3M Young Scientist Challenge after discovering a molecule that can selectively bind to the spike protein of the SARS-COV-2 virus, which causes COVID-19.

The competition opened in December 2019 and invited students in grades five to eight to find a unique solution to an everyday problem. Anika won $25,000, a special destination trip, and the title of “America’s Top Young Scientist” for her achievement.

Her discovery could lead to important developments in COVID-19 research. By binding to the spike protein in the coronavirus, the molecule she found can potentially prevent virus entry into the host cell, and can be used in creating a potential drug to cure COVID-19.

Anika used in-silico methodology — methods and experiments that make use of computers — to screen millions of small molecules. She originally planned for her project to focus on the influenza virus, but pivoted once COVID-19 hit and she realized the severity of the pandemic. Anika was in eighth grade when she submitted the project.

She told CNN that she hopes to work with other scientists and researchers to develop her discovery into an actual cure for the virus.

At the moment, the World Health Organization (WHO) is tracking over 170 candidate vaccines around the world. However, since many of them are still in early development, the effectiveness of these vaccines are still unknown. Vaccines go through multiple stages of testing and experts predict that a vaccine will only be available to the public in 2021, at the earliest.

In August, Russia was the first country to claim to have developed a vaccine for COVID-19. However, many were skeptical as President Vladimir Putin had ordered to speed up clinical trials. The vaccine, which was not subject to the extensive Phase III testing, was registered after less than two months of human testing. Experts have said that the vaccine is based on a common cold virus, which many people have been exposed to, potentially limiting its effectiveness. Other countries working on vaccines include the United Kingdom, Germany, and China.

At the moment, there are no specific vaccines or drugs for COVID-19. Developing one to prevent or cure infection from the novel coronavirus could help decrease the number of fatalities and help hospitals manage patients better.

As of posting, there have been a total of over 40 million cases of COVID-19 and 1.1 million deaths around the world. The United States and India have the most number of cases, with 8.1 million and 7.5 million total COVID-19 cases respectively. Few places across the globe have successfully managed  the virus, including New Zealand, Taiwan, and Singapore.

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Mammalian lipid droplets are innate immune hubs integrating cell metabolism and host defense

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Cells drop a bomb on pathogens

Lipid droplets (LDs) accumulate in cells to serve as lipid storage organelles. They are also an attractive source of nutrients for many pathogens. Bosch et al. show that various proteins involved in innate immunity form complexes on LDs in response to bacterial lipopolysaccharide (see the Perspective by Green). Upon activation, LDs became physically uncoupled from mitochondria, driving a shift in cells from oxidative phosphorylation to aerobic glycolysis. This work highlights the ability of LDs both to kill pathogens directly and to establish a metabolic environment conducive to host defense. This may inform future antimicrobial strategies in the age of antibiotic resistance.

Science, this issue p. eaay8085; see also p. 294

Structured Abstract

INTRODUCTION

In all eukaryotic cells, lipid droplets (LDs) store and supply essential lipids to produce signaling molecules, membrane building blocks, and metabolic energy. The LD monolayer also accommodates proteins not obviously related to lipids, such as transcription factors, chromatin components, and toxic proteins.

Common parasites (such as trypanosomes and Plasmodium falciparum), bacteria (such as mycobacteria and Chlamydia), and viruses (such as hepatitis C and dengue) induce and target LDs during their life cycles. The current view is that LDs support infection, providing microorganisms with substrates for effective growth.

RATIONALE

Successful innate defense is critical for survival, and host species have efficiently coevolved with pathogens to develop a plethora of immune responses. Multiple cues, including cellular stress and danger-associated molecular patterns such as lipopolysaccharide (LPS), induce LD formation. Thus, LD localization and dynamics may potentially be advantageous for organizing an intracellular host defense. We have investigated the possibility that mammalian LDs have a direct and regulated role in innate immunity.

RESULTS

We show that mammalian LDs are endowed with a protein-mediated antimicrobial capacity, which is up-regulated during polymicrobial sepsis and by LPS. Light and electron microscopy demonstrated specific association of LDs and bacteria in human macrophages, suggesting the existence of docking mechanisms that facilitate the engagement of antibacterial LD proteins with bacteria.

A comparative mass spectrometry profiling of proteins differentially associated with LDs in response to LPS (LPS-LDs) revealed the profound remodeling of the organelle proteome. A stringent evaluation identified 689 proteins differentially regulated on LPS-LDs (317 enriched and 372 reduced). Ingenuity Pathway Analysis revealed an enrichment of innate immune system–related components and reduction of metabolism-related LD-resident proteins. Additional analyses suggested that LDs serve as innate immune hubs, integrating major intra- and extracellular immune responses.

Among the five members of the perilipin family of LD surface proteins (PLINs), PLIN5 was the only one down-regulated on LPS-LDs. PLIN5 reduction promoted physical and functional disconnection of LPS-LDs and mitochondria, with a concomitant reduction of oxidative metabolism and ketogenesis. Forced PLIN5 reexpression increased the number of LD-mitochondria contacts, reducing LD-bacteria interactions and compromising the antimicrobial capacity of cells.

By contrast, PLIN2 was the most up-regulated PLIN on LPS-LDs. Gene interaction analysis revealed that multiple immune proteins nucleated around PLIN2 in response to LPS. LPS-LDs accrued several interferon-inducible proteins such as viperin, IGTP, IIGP1, TGTP1, and IFI47. Furthermore, LPS-LDs also accumulated cathelicidin (CAMP), a broad-spectrum antimicrobial peptide with chemotactic properties. Cells overexpressing a LD-associated CAMP were more resistant to different bacterial species, including Escherichia coli, methicillin-resistant Staphylococcus aureus, and Listeria monocytogenes.

CONCLUSION

These results demonstrate that LDs form a first-line intracellular defense. They act as a molecular switch in innate immunity, responding to danger signals by both reprogramming cell metabolism and eliciting protein-mediated antimicrobial mechanisms. Mechanisms of LD trafficking and docking with phagocytic and parasitophorous membranes, observed here and described for several pathogens, may facilitate the delivery of immune proteins located on the LD surface. Intracellular LDs can provide infected cells with several biological benefits, serving as a location to attract pathogens as well as coordinating different immune systems that operate simultaneously against different classes of pathogens. LDs may also sequester cytotoxic compounds (such as antimicrobial peptides), reducing damage to other cellular organelles. In view of the widespread resistance to current antibiotics, this study helps decipher molecular mechanisms involved in antimicrobial defense that could be exploited for development of new anti-infective agents.

LDs mediate innate immune defense.

Serial blockface scanning electron microscopy data reconstruction showing an infected macrophage. Bacteria (blue) and LDs (green) in the three-dimensional dataset have been colored and projected onto a single image. LDs associate with the bacteria surface (black square). This interaction is proposed to bring a specific set of antipathogenic proteins in contact with the membrane-enclosing bacteria (inset).

Abstract

Lipid droplets (LDs) are the major lipid storage organelles of eukaryotic cells and a source of nutrients for intracellular pathogens. We demonstrate that mammalian LDs are endowed with a protein-mediated antimicrobial capacity, which is up-regulated by danger signals. In response to lipopolysaccharide (LPS), multiple host defense proteins, including interferon-inducible guanosine triphosphatases and the antimicrobial cathelicidin, assemble into complex clusters on LDs. LPS additionally promotes the physical and functional uncoupling of LDs from mitochondria, reducing fatty acid metabolism while increasing LD-bacterial contacts. Thus, LDs actively participate in mammalian innate immunity at two levels: They are both cell-autonomous organelles that organize and use immune proteins to kill intracellular pathogens as well as central players in the local and systemic metabolic adaptation to infection.

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The nucleus acts as a ruler tailoring cell responses to spatial constraints

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The nucleus makes the rules

Single cells continuously experience and react to mechanical challenges in three-dimensional tissues. Spatial constraints in dense tissues, physical activity, and injury all impose changes in cell shape. How cells can measure shape deformations to ensure correct tissue development and homeostasis remains largely unknown (see the Perspective by Shen and Niethammer). Working independently, Venturini et al. and Lomakin et al. now show that the nucleus can act as an intracellular ruler to measure cellular shape variations. The nuclear envelope provides a gauge of cell deformation and activates a mechanotransduction pathway that controls actomyosin contractility and migration plasticity. The cell nucleus thereby allows cells to adapt their behavior to the local tissue microenvironment.

Science, this issue p. eaba2644, p. eaba2894; see also p. 295

Structured Abstract

INTRODUCTION

The human body is a crowded place. This crowding is even more acute when the regulation of cell growth and proliferation fails during the formation of a tumor. Dealing with the lack of space in crowded environments presents cells with a challenge. This is especially true for immune cells, whose task is to patrol tissues, causing them to experience both acute and sustained deformation as they move. Although changes in tissue crowding and associated cell shape alterations have been known by pathologists to be key diagnostic traits of late-stage tumors since the 19th century, the impact of these changes on the biology of cancer and immune cells remains unclear. Moreover, it is not known whether cells can detect and adaptively respond to deformations in densely packed spaces.

RATIONALE

To test the hypothesis that cells possess an ability to detect and respond to environmentally induced changes in their shape, we fabricated artificial microenvironments that mimic the conditions experienced by tumor and immune cells in a crowded tissue. By combining dynamic confinement, force measurements, and live cell imaging, we were able to quantify cell responses to precisely controlled physical perturbations of their shape.

RESULTS

Our results show that, although cells are surprisingly resistant to compressive forces, they monitor their own shape and develop an active contractile response when deformed below a specific height. Notably, we find that this is achieved by cells monitoring the deformation of their largest internal compartment: the nucleus. We establish that the nucleus provides cells with a precise measure of the extent of their deformation. Once cell compression exceeds the size of the nucleus, it causes the bounding nuclear envelope (NE) to unfold and stretch. The onset of the contractile response occurs when the NE reaches a fully unfolded state. This transition in the mechanical state of the NE and its membranes permits calcium release from internal membrane stores and activates the calcium-dependent phospholipase cPLA2, an enzyme known to operate as a molecular sensor of nuclear membrane tension and a critical regulator of signaling and metabolism. Activated cPLA2 catalyzes the formation of arachidonic acid, an omega-6 fatty acid that, among other processes, potentiates the adenosine triphosphatase activity of myosin II. This induces contractility of the actomyosin cortex, which produces pushing forces to resist physical compression and to rapidly squeeze the cell out of its compressive microenvironment in an “evasion reflex” mechanism.

CONCLUSION

Although the nucleus has traditionally been considered a passive storehouse for genetic material, our work identifies it as an active compartment that rapidly convers mechanical inputs into signaling outputs, with a critical role of its envelope in this sensing function. The nucleus is able to detect environmentally imposed compression and respond to it by generating a signal that is used to change cell behaviors. This phenomenon plays a critical role in ensuring that cells, such as the immune cells within a tumor, can adapt, survive, and efficiently move through a crowded and mechanically heterogeneous microenvironment. Characterizing the full spectrum of signals triggered by nuclear compression has the potential to elucidate mechanisms underlying signaling, epigenetic, and metabolic adaptations of cells to their mechanoenvironment and is thus an exciting avenue for future research.

The nuclear ruler and its contribution to the “life cycle” of a confined cell.

(1) Cell confinement below resting nucleus size, leading to nuclear deformation and to unfolding, and stretching of the nuclear envelope. (2) Nuclear membrane tension increase, which triggers calcium release, cPLA2 activation, and arachidonic acid (ARA) production. (3) Actomyosin force (F) generation. (4) Increased cell migratory capacity and escape from confinement.

Abstract

The microscopic environment inside a metazoan organism is highly crowded. Whether individual cells can tailor their behavior to the limited space remains unclear. In this study, we found that cells measure the degree of spatial confinement by using their largest and stiffest organelle, the nucleus. Cell confinement below a resting nucleus size deforms the nucleus, which expands and stretches its envelope. This activates signaling to the actomyosin cortex via nuclear envelope stretch-sensitive proteins, up-regulating cell contractility. We established that the tailored contractile response constitutes a nuclear ruler–based signaling pathway involved in migratory cell behaviors. Cells rely on the nuclear ruler to modulate the motive force that enables their passage through restrictive pores in complex three-dimensional environments, a process relevant to cancer cell invasion, immune responses, and embryonic development.

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