Robustness of mitochondrial biogenesis and respiration explain aerobic glycolysis.

A long-standing observation is that in fast-growing cells, respiration rate declines with increasing growth rate and is compensated by an increase in fermentation, despite respiration being more efficient than fermentation. This apparent preference for fermentation even in the presence of oxygen is known as aerobic glycolysis, and occurs in bacteria, yeast, and cancer cells. Considerable work has focused on understanding the potential benefits that might justify this seemingly wasteful metabolic strategy, but its mechanistic basis remains unclear. Here we show that aerobic glycolysis results from the saturation of mitochondrial respiration and the decoupling of mitochondrial biogenesis from the production of other cellular components. Respiration rate is insensitive to acute perturbations of cellular energetic demands or nutrient supplies, and is explained simply by the amount of mitochondria per cell. Mitochondria accumulate at a nearly constant rate across different growth conditions, resulting in mitochondrial amount being largely determined by cell division time. In contrast, glucose uptake rate is not saturated, and is accurately predicted by the abundances and affinities of glucose transporters. Combining these models of glucose uptake and respiration provides a quantitative, mechanistic explanation for aerobic glycolysis. The robustness of specific respiration rate and mitochondrial biogenesis, paired with the flexibility of other bioenergetic and biosynthetic fluxes, may play a broad role in shaping eukaryotic cell metabolism.

Structure and dynamics of motor-driven microtubule bundles.

Connecting the large-scale emergent behaviors of active cytoskeletal materials to the microscopic properties of their constituents is a challenge due to a lack of data on the multiscale dynamics and structure of such systems. We approach this problem by studying the impact of depletion attraction on bundles of microtubules and kinesin-14 molecular motors. For all depletant concentrations, kinesin-14 bundles generate comparable extensile dynamics. However, this invariable mesoscopic behavior masks the transition in the microscopic motion of microtubules. Specifically, with increasing attraction, we observe a transition from bi-directional sliding with extension to pure extension with no sliding. Small-angle X-ray scattering shows that the transition in microtubule dynamics is concurrent with a structural rearrangement of microtubules from an open hexagonal to a compressed rectangular lattice. These results demonstrate that bundles of microtubules and molecular motors can display the same mesoscopic extensile behaviors despite having different internal structures and microscopic dynamics. They provide essential information for developing multiscale models of active matter.

Mechanics of spindle orientation in human mitotic cells is determined by pulling forces on astral microtubules and clustering of cortical dynein.

The forces that orient the spindle in human cells remain poorly understood due to a lack of direct mechanical measurements in mammalian systems. We use magnetic tweezers to measure the force on human mitotic spindles. Combining the spindle's measured resistance to rotation, the speed at which it rotates after laser ablating astral microtubules, and estimates of the number of ablated microtubules reveals that each microtubule contacting the cell cortex is subject to ∼5 pN of pulling force, suggesting that each is pulled on by an individual dynein motor. We find that the concentration of dynein at the cell cortex and extent of dynein clustering are key determinants of the spindle's resistance to rotation, with little contribution from cytoplasmic viscosity, which we explain using a biophysically based mathematical model. This work reveals how pulling forces on astral microtubules determine the mechanics of spindle orientation and demonstrates the central role of cortical dynein clustering.

Measuring and modeling the dynamics of mitotic error correction.

Error correction is central to many biological systems and is critical for protein function and cell health. During mitosis, error correction is required for the faithful inheritance of genetic material. When functioning properly, the mitotic spindle segregates an equal number of chromosomes to daughter cells with high fidelity. Over the course of spindle assembly, many initially erroneous attachments between kinetochores and microtubules are fixed through the process of error correction. Despite the importance of chromosome segregation errors in cancer and other diseases, there is a lack of methods to characterize the dynamics of error correction and how it can go wrong. Here, we present an experimental method and analysis framework to quantify chromosome segregation error correction in human tissue culture cells with live cell confocal imaging, timed premature anaphase, and automated counting of kinetochores after cell division. We find that errors decrease exponentially over time during spindle assembly. A coarse-grained model, in which errors are corrected in a chromosome-autonomous manner at a constant rate, can quantitatively explain both the measured error correction dynamics and the distribution of anaphase onset times. We further validated our model using perturbations that destabilized microtubules and changed the initial configuration of chromosomal attachments. Taken together, this work provides a quantitative framework for understanding the dynamics of mitotic error correction.

BlastAssist: a deep learning pipeline to measure interpretable features of human embryos.

STUDY QUESTION: Can the BlastAssist deep learning pipeline perform comparably to or outperform human experts and embryologists at measuring interpretable, clinically relevant features of human embryos in IVF? SUMMARY ANSWER: The BlastAssist pipeline can measure a comprehensive set of interpretable features of human embryos and either outperform or perform comparably to embryologists and human experts in measuring these features. WHAT IS KNOWN ALREADY: Some studies have applied deep learning and developed 'black-box' algorithms to predict embryo viability directly from microscope images and videos but these lack interpretability and generalizability. Other studies have developed deep learning networks to measure individual features of embryos but fail to conduct careful comparisons to embryologists' performance, which are fundamental to demonstrate the network's effectiveness. STUDY DESIGN, SIZE, DURATION: We applied the BlastAssist pipeline to 67 043 973 images (32 939 embryos) recorded in the IVF lab from 2012 to 2017 in Tel Aviv Sourasky Medical Center. We first compared the pipeline measurements of individual images/embryos to manual measurements by human experts for sets of features, including: (i) fertilization status (n = 207 embryos), (ii) cell symmetry (n = 109 embryos), (iii) degree of fragmentation (n = 6664 images), and (iv) developmental timing (n = 21 036 images). We then conducted detailed comparisons between pipeline outputs and annotations made by embryologists during routine treatments for features, including: (i) fertilization status (n = 18 922 embryos), (ii) pronuclei (PN) fade time (n = 13 781 embryos), (iii) degree of fragmentation on Day 2 (n = 11 582 embryos), and (iv) time of blastulation (n = 3266 embryos). In addition, we compared the pipeline outputs to the implantation results of 723 single embryo transfer (SET) cycles, and to the live birth results of 3421 embryos transferred in 1801 cycles. PARTICIPANTS/MATERIALS, SETTING, METHODS: In addition to EmbryoScope™ image data, manual embryo grading and annotations, and electronic health record (EHR) data on treatment outcomes were also included. We integrated the deep learning networks we developed for individual features to construct the BlastAssist pipeline. Pearson's χ2 test was used to evaluate the statistical independence of individual features and implantation success. Bayesian statistics was used to evaluate the association of the probability of an embryo resulting in live birth to BlastAssist inputs. MAIN RESULTS AND THE ROLE OF CHANCE: The BlastAssist pipeline integrates five deep learning networks and measures comprehensive, interpretable, and quantitative features in clinical IVF. The pipeline performs similarly or better than manual measurements. For fertilization status, the network performs with very good parameters of specificity and sensitivity (area under the receiver operating characteristics (AUROC) 0.84-0.94). For symmetry score, the pipeline performs comparably to the human expert at both 2-cell (r = 0.71 ± 0.06) and 4-cell stages (r = 0.77 ± 0.07). For degree of fragmentation, the pipeline (acc = 69.4%) slightly under-performs compared to human experts (acc = 73.8%). For developmental timing, the pipeline (acc = 90.0%) performs similarly to human experts (acc = 91.4%). There is also strong agreement between pipeline outputs and annotations made by embryologists during routine treatments. For fertilization status, the pipeline and embryologists strongly agree (acc = 79.6%), and there is strong correlation between the two measurements (r = 0.683). For degree of fragmentation, the pipeline and embryologists mostly agree (acc = 55.4%), and there is also strong correlation between the two measurements (r = 0.648). For both PN fade time (r = 0.787) and time of blastulation (r = 0.887), there's strong correlation between the pipeline and embryologists. For SET cycles, 2-cell time (P < 0.01) and 2-cell symmetry (P < 0.03) are significantly correlated with implantation success rate, while other features showed correlations with implantation success without statistical significance. In addition, 2-cell time (P < 5 × 10-11), PN fade time (P < 5 × 10-10), degree of fragmentation on Day 3 (P < 5 × 10-4), and 2-cell symmetry (P < 5 × 10-3) showed statistically significant correlation with the probability of the transferred embryo resulting in live birth. LIMITATIONS, REASONS FOR CAUTION: We have not tested the BlastAssist pipeline on data from other clinics or other time-lapse microscopy (TLM) systems. The association study we conducted with live birth results do not take into account confounding variables, which will be necessary to construct an embryo selection algorithm. Randomized controlled trials (RCT) will be necessary to determine whether the pipeline can improve success rates in clinical IVF. WIDER IMPLICATIONS OF THE FINDINGS: BlastAssist provides a comprehensive and holistic means of evaluating human embryos. Instead of using a black-box algorithm, BlastAssist outputs meaningful measurements of embryos that can be interpreted and corroborated by embryologists, which is crucial in clinical decision making. Furthermore, the unprecedentedly large dataset generated by BlastAssist measurements can be used as a powerful resource for further research in human embryology and IVF. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by Harvard Quantitative Biology Initiative, the NSF-Simons Center for Mathematical and Statistical Analysis of Biology at Harvard (award number 1764269), the National Institute of Heath (award number R01HD104969), the Perelson Fund, and the Sagol fund for embryos and stem cells as part of the Sagol Network. The authors declare no competing interests. TRIAL REGISTRATION NUMBER: Not applicable.

Clustering of cortical dynein regulates the mechanics of spindle orientation in human mitotic cells.

The forces which orient the spindle in human cells remain poorly understood due to a lack of direct mechanical measurements in mammalian systems. We use magnetic tweezers to measure the force on human mitotic spindles. Combining the spindle's measured resistance to rotation, the speed it rotates after laser ablating astral microtubules, and estimates of the number of ablated microtubules reveals that each microtubule contacting the cell cortex is subject to ~1 pN of pulling force, suggesting that each is pulled on by an individual dynein motor. We find that the concentration of dynein at the cell cortex and extent of dynein clustering are key determinants of the spindle's resistance to rotation, with little contribution from cytoplasmic viscosity, which we explain using a biophysically based mathematical model. This work reveals how pulling forces on astral microtubules determine the mechanics of spindle orientation and demonstrates the central role of cortical dynein clustering.

Dissipation and energy propagation across scales in an active cytoskeletal material.

Living systems are intrinsically nonequilibrium: They use metabolically derived chemical energy to power their emergent dynamics and self-organization. A crucial driver of these dynamics is the cellular cytoskeleton, a defining example of an active material where the energy injected by molecular motors cascades across length scales, allowing the material to break the constraints of thermodynamic equilibrium and display emergent nonequilibrium dynamics only possible due to the constant influx of energy. Notwithstanding recent experimental advances in the use of local probes to quantify entropy production and the breaking of detailed balance, little is known about the energetics of active materials or how energy propagates from the molecular to emergent length scales. Here, we use a recently developed picowatt calorimeter to experimentally measure the energetics of an active microtubule gel that displays emergent large-scale flows. We find that only approximately one-billionth of the system's total energy consumption contributes to these emergent flows. We develop a chemical kinetics model that quantitatively captures how the system's total thermal dissipation varies with ATP and microtubule concentrations but that breaks down at high motor concentration, signaling an interference between motors. Finally, we estimate how energy losses accumulate across scales. Taken together, these results highlight energetic efficiency as a key consideration for the engineering of active materials and are a powerful step toward developing a nonequilibrium thermodynamics of living systems.

Self-organization of kinetochore-fibers in human mitotic spindles.

During eukaryotic cell division, chromosomes are linked to microtubules (MTs) in the spindle by a macromolecular complex called the kinetochore. The bound kinetochore microtubules (KMTs) are crucial to ensuring accurate chromosome segregation. Recent reconstructions by electron tomography (Kiewisz et al., 2022) captured the positions and configurations of every MT in human mitotic spindles, revealing that roughly half the KMTs in these spindles do not reach the pole. Here, we investigate the processes that give rise to this distribution of KMTs using a combination of analysis of large-scale electron tomography, photoconversion experiments, quantitative polarized light microscopy, and biophysical modeling. Our results indicate that in metaphase, KMTs grow away from the kinetochores along well-defined trajectories, with the speed of the KMT minus ends continually decreasing as the minus ends approach the pole, implying that longer KMTs grow more slowly than shorter KMTs. The locations of KMT minus ends, and the turnover and movements of tubulin in KMTs, are consistent with models in which KMTs predominately nucleate de novo at kinetochores in metaphase and are inconsistent with substantial numbers of non-KMTs being recruited to the kinetochore in metaphase. Taken together, this work leads to a mathematical model of the self-organization of kinetochore-fibers in human mitotic spindles.

Fluorescence lifetime imaging microscopy (FLIM) detects differences in metabolic signatures between euploid and aneuploid human blastocysts.

STUDY QUESTION: Can non-invasive imaging with fluorescence lifetime imaging microscopy (FLIM) detect metabolic differences in euploid versus aneuploid human blastocysts? SUMMARY ANSWER: FLIM has identified significant metabolic differences between euploid and aneuploid blastocysts. WHAT IS KNOWN ALREADY: Prior studies have demonstrated that FLIM can detect metabolic differences in mouse oocytes and embryos and in discarded human blastocysts. STUDY DESIGN, SIZE, DURATION: This was a prospective observational study from August 2019 to February 2020. Embryo metabolic state was assessed using FLIM to measure the autofluorescence metabolic factors nicotinamide adenine dinucleotide dehydrogenase together with nicotinamide adenine phosphate dinucleotide dehydrogenase (NAD(P)H) and flavin adenine dinucleotide (FAD). Eight metabolic FLIM parameters were obtained from each blastocyst (four for NAD(P)H and four for FAD): short (T1) and long (T2) fluorescence lifetime, fluorescence intensity (I) and fraction of the molecules engaged with enzymes (F). The redox ratio (NAD(P)H-I)/(FAD-I) was also calculated for each image. PARTICIPANTS/MATERIALS, SETTING, METHODS: This study was performed at a single academically affiliated centre where there were 156 discarded frozen blastocysts (n = 17 euploids; 139 aneuploids) included. Ploidy status was determined by pre-implantation genetic testing for aneuploidy (PGT-A). Discarded human blastocysts were compared using single FLIM parameters. Additionally, inner cell mass (ICM) and trophectoderm (TE) were also evaluated. Multilevel models were used for analysis. A post-hoc correction used Benjamini-Hochberg's false discovery rate, at a q-value of 0.05. MAIN RESULTS AND THE ROLE OF CHANCE: Comparing euploid (n = 17) versus aneuploid (n = 139) embryos, a significant difference was seen in NAD(P)H-F (P < 0.04), FAD-I (P < 0.04) and redox ratio (P < 0.05). Euploid ICM (n = 15) versus aneuploid ICM (n = 119) also demonstrated significantly different signatures in NAD(P)H-F (P < 0.009), FAD-I (P < 0.03) and redox ratio (P < 0.03). Similarly, euploid TE (n = 15) versus aneuploid TE (n = 119) had significant differences in NAD(P)H-F (P < 0.0001) and FAD-I (P < 0.04). LIMITATIONS, REASONS FOR CAUTION: This study utilized discarded human blastocysts, and these embryos may differ metabolically from non-discarded human embryos. The blastocysts analysed were vitrified after PGT-A biopsy and it is unclear how the vitrification process may affect the metabolic profile of blastocysts. Our study was also limited by the small number of rare donated euploid embryos available for analysis. Euploid embryos are very rarely discarded due to their value to patients trying to conceive, which limits their use for research purposes. However, we controlled for the imbalance with the bootstrap resampling analysis. WIDER IMPLICATIONS OF THE FINDINGS: These findings provide preliminary evidence that FLIM may be a useful non-invasive clinical tool to assist in identifying the ploidy status of embryos. STUDY FUNDING/COMPETING INTEREST(S): The study was supported by the Blavatnik Biomedical Accelerator Grant at Harvard University. Becker and Hickl GmbH and Boston Electronics sponsored research with the loaning of equipment for FLIM. D.J.N. is an inventor on patent US20170039415A1. There are no other conflicts of interest to declare. TRIAL REGISTRATION NUMBER: N/A.

Active Microphase Separation in Mixtures of Microtubules and Tip-Accumulating Molecular Motors.

Mixtures of filaments and molecular motors form active materials with diverse dynamical behaviors that vary based on their constituents' molecular properties. To develop a multiscale of these materials, we map the nonequilibrium phase diagram of microtubules and tip-accumulating kinesin-4 molecular motors. We find that kinesin-4 can drive either global contractions or turbulentlike extensile dynamics, depending on the concentrations of both microtubules and a bundling agent. We also observe a range of spatially heterogeneous nonequilibrium phases, including finite-sized radial asters, 1D wormlike chains, extended 2D bilayers, and system-spanning 3D active foams. Finally, we describe intricate kinetic pathways that yield microphase separated structures and arise from the inherent frustration between the orientational order of filamentous microtubules and the positional order of tip-accumulating molecular motors. Our work reveals a range of novel active states. It also shows that the form of active stresses is not solely dictated by the properties of individual motors and filaments, but is also contingent on the constituent concentrations and spatial arrangement of motors on the filaments.

Cell cycle regulation of ER membrane biogenesis protects against chromosome missegregation.

Failure to reorganize the endoplasmic reticulum (ER) in mitosis results in chromosome missegregation. Here, we show that accurate chromosome segregation in human cells requires cell cycle-regulated ER membrane production. Excess ER membranes increase the viscosity of the mitotic cytoplasm to physically restrict chromosome movements, which impedes the correction of mitotic errors leading to the formation of micronuclei. Mechanistically, we demonstrate that the protein phosphatase CTDNEP1 counteracts mTOR kinase to establish a dephosphorylated pool of the phosphatidic acid phosphatase lipin 1 in interphase. CTDNEP1 control of lipin 1 limits the synthesis of fatty acids for ER membrane biogenesis in interphase that then protects against chromosome missegregation in mitosis. Thus, regulation of ER size can dictate the biophysical properties of mitotic cells, providing an explanation for why ER reorganization is necessary for mitotic fidelity. Our data further suggest that dysregulated lipid metabolism is a potential source of aneuploidy in cancer cells.

A coarse-grained NADH redox model enables inference of subcellular metabolic fluxes from fluorescence lifetime imaging.

Mitochondrial metabolism is of central importance to diverse aspects of cell and developmental biology. Defects in mitochondria are associated with many diseases, including cancer, neuropathology, and infertility. Our understanding of mitochondrial metabolism in situ and dysfunction in diseases are limited by the lack of techniques to measure mitochondrial metabolic fluxes with sufficient spatiotemporal resolution. Herein, we developed a new method to infer mitochondrial metabolic fluxes in living cells with subcellular resolution from fluorescence lifetime imaging of NADH. This result is based on the use of a generic coarse-grained NADH redox model. We tested the model in mouse oocytes and human tissue culture cells subject to a wide variety of perturbations by comparing predicted fluxes through the electron transport chain (ETC) to direct measurements of oxygen consumption rate. Interpreting the fluorescence lifetime imaging microscopy measurements of NADH using this model, we discovered a homeostasis of ETC flux in mouse oocytes: perturbations of nutrient supply and energy demand of the cell do not change ETC flux despite significantly impacting NADH metabolic state. Furthermore, we observed a subcellular spatial gradient of ETC flux in mouse oocytes and found that this gradient is primarily a result of a spatially heterogeneous mitochondrial proton leak. We concluded from these observations that ETC flux in mouse oocytes is not controlled by energy demand or supply, but by the intrinsic rates of mitochondrial respiration.

Extensive analysis of mitochondrial DNA quantity and sequence variation in human cumulus cells and assisted reproduction outcomes.

STUDY QUESTION: Are relative mitochondrial DNA (mtDNA) content and mitochondrial genome (mtGenome) variants in human cumulus cells (CCs) associated with oocyte reproductive potential and assisted reproductive technology (ART) outcomes? SUMMARY ANSWER: Neither the CC mtDNA quantity nor the presence of specific mtDNA genetic variants was associated with ART outcomes, although associations with patient body mass index (BMI) were detected, and the total number of oocytes retrieved differed between major mitochondrial haplogroups. WHAT IS KNOWN ALREADY: CCs fulfil a vital role in the support of oocyte developmental competence. As with other cell types, appropriate cellular function is likely to rely upon adequate energy production, which in turn depends on the quantity and genetic competence of the mitochondria. mtDNA mutations can be inherited or they can accumulate in somatic cells over time, potentially contributing to aging. Such mutations may be homoplasmic (affecting all mtDNA in a cell) or they may display varying levels of heteroplasmy (affecting a proportion of the mtDNA). Currently, little is known concerning variation in CC mitochondrial genetics and how this might influence the reproductive potential of the associated oocyte. STUDY DESIGN, SIZE, DURATION: This was a prospective observational study involving human CCs collected with 541 oocytes from 177 IVF patients. mtDNA quantity was measured in all the samples with a validated quantitative PCR method and the entire mtGenome was sequenced in a subset of 138 samples using a high-depth massively parallel sequencing approach. Associations between relative mtDNA quantity and mtGenome variants in CCs and patient age, BMI (kg/m2), infertility diagnosis and ART outcomes were investigated. PARTICIPANTS/MATERIALS, SETTING, METHODS: Massively parallel sequencing permitted not only the accurate detection of mutations but also the precise quantification of levels of mutations in cases of heteroplasmy. Sequence variants in the mtDNA were evaluated using Mitomaster and HmtVar to predict their potential impact. MAIN RESULTS AND THE ROLE OF CHANCE: The relative mtDNA CC content was significantly associated with BMI. No significant associations were observed between CC mtDNA quantity and patient age, female infertility diagnosis or any ART outcome variable. mtGenome sequencing revealed 4181 genetic variants with respect to a reference genome. The COXI locus contained the least number of coding sequence variants, whereas ATPase8 had the most. The number of variants predicted to affect the ATP production differed significantly between mitochondrial macrohaplogroups. The total number of retrieved oocytes was different between the H-V and J-T as well as the U-K and J-T macrohaplogroups. There was a non-significant increase in mtDNA levels in CCs with heteroplasmic mitochondrial mutations. LARGE SCALE DATA: N/A. LIMITATIONS, REASONS FOR CAUTION: Although a large number of samples were analysed in this study, it was not possible to analyse all the CCs from every patient. Also, the results obtained with respect to specific clinical outcomes and macrohaplogroups should be interpreted with caution due to the smaller sample sizes when subdividing the dataset. WIDER IMPLICATIONS OF THE FINDINGS: These findings suggest that the analysis of mtDNA in CCs is unlikely to provide an advantage in terms of improved embryo selection during assisted reproduction cycles. Nonetheless, our data raise interesting biological questions, particularly regarding the interplay of metabolism and BMI and the association of mtDNA haplogroup with oocyte yield in ovarian stimulation cycles. STUDY FUNDING/COMPETING INTEREST(S): This study was funded by National Institutes of Health grant 5R01HD092550-02. D.J.N. and C.R. co-hold patent US20150346100A1 and D.J.N. holds US20170039415A1, both for metabolic imaging methods. D.W. receives support from the NIHR Oxford Biomedical Research Centre. The remaining authors have no conflicts of interest to declare.

Metabolic imaging of human cumulus cells reveals associations among metabolic profiles of cumulus cells, patient clinical factors, and oocyte maturity.

OBJECTIVE: To determine whether fluorescence lifetime imaging microscopy (FLIM) detects differences in metabolic state among cumulus cell samples and whether their metabolic state is associated with patient age, body mass index (BMI), and antimüllerian hormone (AMH) level and maturity of the oocyte. DESIGN: Prospective observational study. SETTING: Academic laboratory. PATIENT(S): Cumulus cell (CC) clusters from cumulus-oocyte complexes were collected from patients undergoing assisted reproductive technology treatment after oocyte retrieval and vitrified. INTERVENTION(S): Cumulus cell metabolism was assessed using FLIM to measure autofluorescence of nicotinamide adenine (phosphate) dinucleotide and flavine adenine dinucleotide, endogenous coenzymes essential for cellular respiration and glycolysis. Patient age, BMI, and AMH level and the maturity of the corresponding oocytes were recorded. MAIN OUTCOME MEASURE(S): Quantitative information from FLIM was obtained regarding metabolite concentrations from fluorescence intensity and metabolite enzyme engagement from fluorescence lifetimes. Associations were investigated between each FLIM parameter and oocyte maturity and patient age, BMI, and AMH. Variance between CC clusters within and between patients was determined. RESULT(S): Of 619 CC clusters from 193 patients, 90 were associated with immature oocytes and 505 with metaphase II oocytes. FLIM enabled quantitative measurements of the metabolic state of CC clusters. These parameters were significantly correlated with patient age and AMH independently, but not with BMI. Cumulus cell nicotinamide adenine (phosphate) dinucleotide FLIM parameters and redox ratio were significantly associated with maturity of the enclosed oocyte. CONCLUSION(S): FLIM detects variations in the metabolic state of CCs, showing a greater variance among clusters from each patient than between patients. Fluorescence lifetime imaging microscopy can detect CC metabolic associations with patient age and AMH and variations between mature and immature oocytes, suggesting the potential utility of this technique to help identify superior oocytes.

Physical bioenergetics: Energy fluxes, budgets, and constraints in cells.

Cells are the basic units of all living matter which harness the flow of energy to drive the processes of life. While the biochemical networks involved in energy transduction are well-characterized, the energetic costs and constraints for specific cellular processes remain largely unknown. In particular, what are the energy budgets of cells? What are the constraints and limits energy flows impose on cellular processes? Do cells operate near these limits, and if so how do energetic constraints impact cellular functions? Physics has provided many tools to study nonequilibrium systems and to define physical limits, but applying these tools to cell biology remains a challenge. Physical bioenergetics, which resides at the interface of nonequilibrium physics, energy metabolism, and cell biology, seeks to understand how much energy cells are using, how they partition this energy between different cellular processes, and the associated energetic constraints. Here we review recent advances and discuss open questions and challenges in physical bioenergetics.

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.

Mechanical Mechanisms of Chromosome Segregation.

Chromosome segregation-the partitioning of genetic material into two daughter cells-is one of the most crucial processes in cell division. In all Eukaryotes, chromosome segregation is driven by the spindle, a microtubule-based, self-organizing subcellular structure. Extensive research performed over the past 150 years has identified numerous commonalities and contrasts between spindles in different systems. In this review, we use simple coarse-grained models to organize and integrate previous studies of chromosome segregation. We discuss sites of force generation in spindles and fundamental mechanical principles that any understanding of chromosome segregation must be based upon. We argue that conserved sites of force generation may interact differently in different spindles, leading to distinct mechanical mechanisms of chromosome segregation. We suggest experiments to determine which mechanical mechanism is operative in a particular spindle under study. Finally, we propose that combining biophysical experiments, coarse-grained theories, and evolutionary genetics will be a productive approach to enhance our understanding of chromosome segregation in the future.

Stoichiometric interactions explain spindle dynamics and scaling across 100 million years of nematode evolution.

The spindle shows remarkable diversity, and changes in an integrated fashion, as cells vary over evolution. Here, we provide a mechanistic explanation for variations in the first mitotic spindle in nematodes. We used a combination of quantitative genetics and biophysics to rule out broad classes of models of the regulation of spindle length and dynamics, and to establish the importance of a balance of cortical pulling forces acting in different directions. These experiments led us to construct a model of cortical pulling forces in which the stoichiometric interactions of microtubules and force generators (each force generator can bind only one microtubule), is key to explaining the dynamics of spindle positioning and elongation, and spindle final length and scaling with cell size. This model accounts for variations in all the spindle traits we studied here, both within species and across nematode species spanning over 100 million years of evolution.

Probing and manipulating embryogenesis via nanoscale thermometry and temperature control.

Understanding the coordination of cell-division timing is one of the outstanding questions in the field of developmental biology. One active control parameter of the cell-cycle duration is temperature, as it can accelerate or decelerate the rate of biochemical reactions. However, controlled experiments at the cellular scale are challenging, due to the limited availability of biocompatible temperature sensors, as well as the lack of practical methods to systematically control local temperatures and cellular dynamics. Here, we demonstrate a method to probe and control the cell-division timing in Caenorhabditis elegans embryos using a combination of local laser heating and nanoscale thermometry. Local infrared laser illumination produces a temperature gradient across the embryo, which is precisely measured by in vivo nanoscale thermometry using quantum defects in nanodiamonds. These techniques enable selective, controlled acceleration of the cell divisions, even enabling an inversion of division order at the two-cell stage. Our data suggest that the cell-cycle timing asynchrony of the early embryonic development in C. elegans is determined independently by individual cells rather than via cell-to-cell communication. Our method can be used to control the development of multicellular organisms and to provide insights into the regulation of cell-division timings as a consequence of local perturbations.

Combined noninvasive metabolic and spindle imaging as potential tools for embryo and oocyte assessment.

STUDY QUESTION: Is the combined use of fluorescence lifetime imaging microscopy (FLIM)-based metabolic imaging and second harmonic generation (SHG) spindle imaging a feasible and safe approach for noninvasive embryo assessment? SUMMARY ANSWER: Metabolic imaging can sensitively detect meaningful metabolic changes in embryos, SHG produces high-quality images of spindles and the methods do not significantly impair embryo viability. WHAT IS KNOWN ALREADY: Proper metabolism is essential for embryo viability. Metabolic imaging is a well-tested method for measuring metabolism of cells and tissues, but it is unclear if it is sensitive enough and safe enough for use in embryo assessment. STUDY DESIGN, SIZE, DURATION: This study consisted of time-course experiments and control versus treatment experiments. We monitored the metabolism of 25 mouse oocytes with a noninvasive metabolic imaging system while exposing them to oxamate (cytoplasmic lactate dehydrogenase inhibitor) and rotenone (mitochondrial oxidative phosphorylation inhibitor) in series. Mouse embryos (n = 39) were measured every 2 h from the one-cell stage to blastocyst in order to characterize metabolic changes occurring during pre-implantation development. To assess the safety of FLIM illumination, n = 144 illuminated embryos were implanted into n = 12 mice, and n = 108 nonilluminated embryos were implanted into n = 9 mice. PARTICIPANTS/MATERIALS, SETTING, METHODS: Experiments were performed in mouse embryos and oocytes. Samples were monitored with noninvasive, FLIM-based metabolic imaging of nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD) autofluorescence. Between NADH cytoplasm, NADH mitochondria and FAD mitochondria, a single metabolic measurement produces up to 12 quantitative parameters for characterizing the metabolic state of an embryo. For safety experiments, live birth rates and pup weights (mean ± SEM) were used as endpoints. For all test conditions, the level of significance was set at P < 0.05. MAIN RESULTS AND THE ROLE OF CHANCE: Measured FLIM parameters were highly sensitive to metabolic changes due to both metabolic perturbations and embryo development. For oocytes, metabolic parameter values were compared before and after exposure to oxamate and rotenone. The metabolic measurements provided a basis for complete separation of the data sets. For embryos, metabolic parameter values were compared between the first division and morula stages, morula and blastocyst and first division and blastocyst. The metabolic measurements again completely separated the data sets. Exposure of embryos to excessive illumination dosages (24 measurements) had no significant effect on live birth rate (5.1 ± 0.94 pups/mouse for illuminated group; 5.7 ± 1.74 pups/mouse for control group) or pup weights (1.88 ± 0.10 g for illuminated group; 1.89 ± 0.11 g for control group). LIMITATIONS, REASONS FOR CAUTION: The study was performed using a mouse model, so conclusions concerning sensitivity and safety may not generalize to human embryos. A limitation of the live birth data is also that although cages were routinely monitored, we could not preclude that some runt pups may have been eaten. WIDER IMPLICATIONS OF THE FINDINGS: Promising proof-of-concept results demonstrate that FLIM with SHG provide detailed biological information that may be valuable for the assessment of embryo and oocyte quality. Live birth experiments support the method's safety, arguing for further studies of the clinical utility of these techniques. STUDY FUNDING/COMPETING INTEREST(S): Supported by the Blavatnik Biomedical Accelerator Grant at Harvard University and by the Harvard Catalyst/The Harvard Clinical and Translational Science Center (National Institutes of Health Award UL1 TR001102), by NSF grants DMR-0820484 and PFI-TT-1827309 and by NIH grant R01HD092550-01. T.S. was supported by a National Science Foundation Postdoctoral Research Fellowship in Biology grant (1308878). S.F. and S.A. were supported by NSF MRSEC DMR-1420382. Becker and Hickl GmbH sponsored the research with the loaning of equipment for FLIM. T.S. and D.N. are cofounders and shareholders of LuminOva, Inc., and co-hold patents (US20150346100A1 and US20170039415A1) for metabolic imaging methods. D.S. is on the scientific advisory board for Cooper Surgical and has stock options with LuminOva, Inc.