Publications

2024
Yang HY, Leahy BD, Jang W-D, Wei D, Kalma Y, Rahav R, Carmon A, Kopel R, Azem F, Venturas M, et al. BlastAssist: a deep learning pipeline to measure interpretable features of human embryos. Human Reproduction. 2024.Abstract

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.

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2023
Wu H-Y, Kabacaoğlu G, Nazockdast E, Chang H-C, Shelley MJ, Needleman DJ. Laser ablation and fluid flows reveal the mechanism behind spindle and centrosome positioning. Nature Physics. 2023.Abstract

Few techniques are available for studying the nature of forces that drive subcellular dynamics. Here we develop two complementary ones. The first is femtosecond stereotactic laser ablation, which rapidly creates complex cuts of subcellular structures and enables precise dissection of when, where and in what direction forces are generated. The second is an assessment
of subcellular fluid flows by comparison of direct flow measurements
using microinjected fluorescent nanodiamonds with large-scale fluid-structure simulations of different force transduction models. We apply these techniques to study spindle and centrosome positioning in early Caenorhabditis elegans embryos and to probe the contributions
of microtubule pushing, cytoplasmic pulling and cortical pulling upon centrosomal microtubules. Based on our results, we construct a biophysical model to explain the dynamics of centrosomes. We demonstrate that cortical pulling forces provide a general explanation for many behaviours mediated by centrosomes, including pronuclear migration and centration, rotation, metaphase spindle positioning, asymmetric spindle elongation and spindle oscillations. This work establishes methodologies for disentangling the forces responsible for cell biological phenomena.

 

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Jang W-D, Lukyanenko S, Wei D, Yang J, Leahy B, Yang H, Ben-Yosef D, Needleman D, Pfister H. Multi-Task Curriculum Learning for Partially Labeled Data. IEEE 20th International Symposium on Biomedical Imaging (ISBI). 2023.Abstract
Incomplete labels are common in multi-task learning for biomedical applications due to several practical difficulties, e.g., expensive annotation efforts by experts, limit of data collection, different sources of data. A naive approach to enable joint learning for partially labeled data is adding self-supervised learning for tasks without ground truths by augmenting an input image and forcing the multi-task model to return the same outputs for both the input and augmented images. However, the partially labeled setting can result in imbalanced learning of tasks since not all tasks are trainable with ground truth supervisions for each data sample. In this work, we propose a multi-task curriculum learning method tailored for partially labeled data. For balanced learning of tasks, our multitask curriculum prioritizes less performing tasks during training by setting different supervised learning frequencies for each task. We demonstrate that our method outperforms standard approaches on one biomedical and two natural image datasets. Furthermore, our learning method with partially labeled data performs better than the standard multi-task learning methods with fully labeled data for the same number of annotations.
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Jang W-D, Wei D, Zhang X, Leahy B, Yang H, Tompkin J, Ben-Yosef D, Needleman D, Pfister H. Learning Vector Quantized Shape Code for Amodal Blastomere Instance Segmentation. IEEE 20th International Symposium on Biomedical Imaging (ISBI). 2023.Abstract
Blastomere instance segmentation is important for analyzing embryos’ abnormality. To measure the accurate shapes and sizes of blastomeres, their amodal segmentation is necessary. Amodal instance segmentation aims to recover an object’s complete silhouette even when the object is not fully visible. For each detected object, previous methods directly regress the target mask from input features. However, images of an object under different amounts of occlusion should have the same amodal mask output, making it harder to train the regression model. To alleviate the problem, we propose to classify input features into intermediate shape codes and recover complete object shapes. First, we pre-train the Vector Quantized Variational Autoencoder (VQ-VAE) model to learn these discrete shape codes from ground truth amodal masks. Then, we incorporate the VQ-VAE model into the amodal instance segmentation pipeline with an additional refinement module. We also detect an occlusion map to integrate occlusion information with a backbone feature. As such, our network faithfully detects bounding boxes of amodal objects. On an internal embryo cell image benchmark, the proposed method outperforms previous state-of-the-art methods. To show generalizability, we show segmentation results on the public KINS natural image benchmark. Our method would enable accurate measurement of blastomeres in In Vitro Fertilization (IVF) clinics, potentially increasing the IVF success rate.
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Venturas M, Yang X, Sakkas D, Needleman D. Noninvasive metabolic profiling of cumulus cells, oocytes, and embryos via fluorescence lifetime imaging microscopy: a mini-review. Human Reproduction. 2023.Abstract

A major challenge in ART is to select high-quality oocytes and embryos. The metabolism of oocytes and embryos has long been linked to their viability, suggesting the potential utility of metabolic measurements to aid in selection. Here, we review recent work on noninvasive metabolic imaging of cumulus cells, oocytes, and embryos. We focus our discussion on fluorescence lifetime imaging microscopy (FLIM) of the autofluorescent coenzymes NAD(P)H and flavine adenine dinucleotide (FADþ), which play central roles in many metabolic pathways. FLIM measurements provide quantitative information on NAD(P)H and FADþ concentrations and engagement with enzymes, leading to a robust means of characterizing the metabolic state of cells. We argue that FLIM is a promising approach to aid in oocyte and embryo selection.

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Foster PJ, Bae J, Lemma B, Zheng J, Ireland W, Chandrakar P, Boros R, Dogic Z, Needleman DJ, Vlassak JJ. Dissipation and energy propagation across scales in an active cytoskeletal material. PNAS. 2023;120 (14).Abstract

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 thermody- namics of living systems.

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2022
Arunachalam E, Ireland W, Yang X, Needleman D. Dissecting Flux Balances to Measure Energetic Costs in Cell Biology: Techniques and Challenges. Annual Review of Condensed Matter Physics. 2022.Abstract
Life is a nonequilibrium phenomenon: Metabolism provides a continuous supply of energy that drives nearly all cellular processes. However, very little is known about how much energy different cellular processes use, i.e., their energetic costs. The most direct experimental measurements of these costs involve modulating the activity of cellular processes and determining the resulting changes in energetic fluxes. In this review, we present a flux balance framework to aid in the design and interpretation of such experiments and discuss the challenges associated with measuring the relevant metabolic fluxes. We then describe selected techniques that enable measurement of these fluxes. Finally, we review prior experimental and theoretical work that has employed techniques from biochemistry and nonequilibrium physics to determine the energetic costs of cellular processes.
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Conway W, Kiewisz R, Fabig G, Kelleher CP, Wu H-Y, Anjur-Dietrich M, Müller-Reichert T, Needleman DJ. Self-organization of kinetochore-fibers in human mitotic spindles. eLife. 2022.Abstract

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 anal- ysis 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 contin- ually 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.

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Kiewisz R, Fabig G, Conway W, Baum D, Needleman D, Müller-Reichert T. Three-dimensional structure of kinetochore-fibers in human mitotic spindles. eLife. 2022.Abstract

During cell division, kinetochore microtubules (KMTs) provide a physical linkage between the chromosomes and the rest of the spindle. KMTs in mammalian cells are organized into bundles, so-called kinetochore-fibers (k-fibers), but the ultrastructure of these fibers is currently not well characterized. Here, we show by large-scale electron tomography that each k-fiber in HeLa cells in metaphase is composed of approximately nine KMTs, only half of which reach the spindle pole. Our comprehensive reconstructions allowed us to analyze the three-dimensional (3D) morphology of k-fibers and their surrounding MTs in detail. We found that k-fibers exhibit remarkable variation
in circumference and KMT density along their length, with the pole-proximal side showing a broad- ening. Extending our structural analysis then to other MTs in the spindle, we further observed that the association of KMTs with non-KMTs predominantly occurs in the spindle pole regions. Our 3D reconstructions have implications for KMT growth and k-fiber self-organization models as covered
in a parallel publication applying complementary live-cell imaging in combination with biophysical modeling (Conway et al., 2022). Finally, we also introduce a new visualization tool allowing an inter- active display of our 3D spindle data that will serve as a resource for further structural studies on mitosis in human cells.

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Lemma B, Mitchell NP, Subramanian R, Needleman DJ, Dogic Z. Active Microphase Separation in Mixtures of Microtubules and Tip-Accumulating Molecular Motors. Physical Review X. 2022;12.Abstract

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.

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Yang X, Ha G, Needleman DJ. A coarse-grained NADH redox model enables inference of subcellular metabolic fluxes from fluorescence lifetime imaging. eLife. 2022.Abstract
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
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Chandrakar P, Berezney J, Lemma B, Hishamunda B, Berry A, Wu K-T, Subramanian R, Chung J, Needleman D, Gelles J, et al. Engineering stability, longevity, and miscibility of microtubule-based active fluids. Soft Matter. 2022.Abstract
Microtubule-based active matter provides insight into the self-organization of motile interacting constituents. We describe several formulations of microtubule-based 3D active isotropic fluids. Dynamics of these fluids is powered by three types of kinesin motors: a processive motor, a nonprocessive motor, and a motor which is permanently linked to a microtubule backbone. Another modification uses a specific microtubule crosslinker to induce bundle formation instead of a nonspecific polymer depletant. In comparison to the already established system, each formulation exhibits distinct properties. These developments reveal the temporal stability of microtubule-based active fluids while extending their reach and the applicability
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Shah JS, Venturas M, Sanchez TH, Penzias AS, Needleman DJ, Sakkas D. Fluorescence lifetime imaging microscopy (FLIM) detects differences in metabolic signatures between euploid and aneuploid human blastocysts. Human Reproduction. 2022.Abstract
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 ¼ 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 ¼ 17) versus aneuploid (n ¼ 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 ¼ 15) versus aneuploid ICM (n ¼ 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 ¼ 15) versus aneuploid TE (n ¼ 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  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 Key words: fluorescence lifetime imaging microscopy / FLIM / mitochondria / euploid / aneuploid
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Venturas M, Shah JS, Yang X, Sanchez TH, Conway W, Sakkas D, Needleman DJ. Metabolic state of human blastocysts measured by fluorescence lifetime imaging microscopy. Human Reproduction. 2022.Abstract

STUDY QUESTION: Can non-invasive metabolic imaging via fluorescence lifetime imaging microscopy (FLIM) detect variations in metabolic profiles between discarded human blastocysts?

SUMMARY ANSWER: FLIM revealed extensive variations in the metabolic state of discarded human blastocysts associated with blastocyst development over 36 h, the day after fertilization and blastocyst developmental stage, as well as metabolic heterogeneity within individual blastocysts.

WHAT IS KNOWN ALREADY: Mammalian embryos undergo large changes in metabolism over the course of preimplantation development. Embryo metabolism has long been linked to embryo viability, suggesting its potential utility in ART to aid in selecting high quality embryos. However, the metabolism of human embryos remains poorly characterized due to a lack of non-invasive methods to measure their metabolic state. STUDY DESIGN, SIZE, DURATION: We conducted a prospective observational study. We used 215 morphologically normal human embryos from 137 patients that were discarded and donated for research under an approved institutional review board protocol. These embryos were imaged using metabolic imaging via FLIM to measure the autofluorescence of two central coenzymes, nicotinamide adenine (phosphate) dinucleotide (NAD(P)H) and flavine adenine dinucleotide (FADþ), which are essential for cellular respiration and glycolysis.

PARTICIPANTS/MATERIALS, SETTING, METHODS: Here, we used non-invasive FLIM to measure the metabolic state of human blastocysts. We first studied spatial patterns in the metabolic state within human blastocysts and the association of the metabolic state of the whole blastocysts with stage of expansion, day of development since fertilization and morphology. We explored the sensitivity of this technique in detecting metabolic variations between blastocysts from the same patient and between patients. Next, we explored whether FLIM can quantitatively measure metabolic changes through human blastocyst expansion and hatching via time-lapse imaging. For all test conditions, the level of significance was set at P < 0.05 after correction for multiple comparisons using Benjamini–Hochberg’s false discovery rate.

MAIN RESULTS AND THE ROLE OF CHANCE: We found that FLIM is sensitive enough to detect significant metabolic differences between blastocysts. We found that metabolic variations between blastocyst are partially explained by both the time since fertilization and their developmental expansion stage (P< 0.05), but not their morphological grade. Substantial metabolic variations between blastocysts from the same patients remain, even after controlling for these factors. We also observe significant metabolic heterogeneity within individual blastocysts, including between the inner cell mass and the trophectoderm, and between the portions of hatching blastocysts within and without the zona pellucida (P< 0.05). And finally, we observed that the metabolic state of human blastocysts continuously varies over time.

LIMITATIONS, REASONS FOR CAUTION: Although we observed significant variations in metabolic parameters, our data are taken from human blastocysts that were discarded and donated for research and we do not know their clinical outcome. Moreover, the embryos used in this study are a mixture of aneuploid, euploid and embryos of unknown ploidy.

WIDER IMPLICATIONS OF THE FINDINGS: This work reveals novel aspects of the metabolism of human blastocysts and suggests that FLIM is a promising approach to assess embryo viability through non-invasive, quantitative measurements of their metabolism. These results further demonstrate that FLIM can provide biologically relevant information that may be valuable for the assessment of embryo quality.

STUDY FUNDING/COMPETING INTEREST(S): 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.

TRIAL REGISTRATION NUMBER: N/A

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2021
Merta H, Rodrıguez JWC, Anjur-Dietrich MI, Vitale T, Granade ME, Harris TE, Needleman DJ, Bahmanyar S. Cell cycle regulation of ER membrane biogenesis protects against chromosome missegregation. Developmental Cell. 2021;56.Abstract
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.
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Kumar K, Venturas M, Needleman DJ, Racowsky C, Racowsky C. Extensive analysis of mitochondrial DNA quantity and sequence variation in human cumulus cells and assisted reproduction outcomes. Human Reproduction. 2021.Abstract
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
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Leahy B, Racowsky C, Needleman DJ. Inferring simple but precise quantitative models of human oocyte and early embryo development. Interface. 2021;18 (20210475).Abstract
Macroscopic, phenomenological models are useful as concise framings of our understandings in fields from statistical physics to finance to biology. Constructing a phenomenological model for development would provide a framework for understanding the complicated, regulatory nature of oogenesis and embryogenesis. Here, we use a data-driven approach to infer quantitative, precise models of human oocyte maturation and pre-implantation embryo development, by analysing clinical in-vitro fertilization (IVF) data on 7399 IVF cycles resulting in 57 827 embryos. Surprisingly, we find that both oocyte maturation and early embryo development are quantitatively described by simple models with minimal interactions. This simplicity suggests that oogenesis and embryogenesis are composed of modular processes that are relatively siloed from one another. In particular, our analysis provides strong evidence that (i) preantral follicles produce anti-Müllerian hormone independently of effects from other follicles, (ii) oocytes mature to metaphase-II independently of the woman’s age, her BMI and other factors, (iii) early embryo development is memoryless for the variables assessed here, in that the probability of an embryo transitioning from its current developmental stage to the next is independent of its previous stage. Our results both provide insight into the fundamentals of oogenesis and embryogenesis and have implications for the clinical IVF.
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Venturas M, Yang X, Kumar K, Wells D, Rancowsky C, Needleman DJ. Metabolic imaging of human cumulus cells reveals associations among metabolic profiles of cumulus cells, patient clinical factors, and oocyte maturity. Fertility and Sterility. 2021.Abstract
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 antimullerian hor- € mone (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. (Fertil Steril 2021;-:-–-. 2021 by American Society for Reproductive Medicine.) Key Words: Cumulus cells, cumulus-oocyte complexes, fluorescence lifetime imaging microscopy, human oocytes, maturity, metabolism
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Lukyanenko S, Jang W-D, Wei D, Struyven R, Kim Y, Leahy B, Yang H, Rush A, Ben-Yose D, Needleman D, et al. Developmental Stage Classification of Embryos Using Two-Stream Neural Network with Linear-Chain Conditional Random Field. arXiv. 2021. Publisher's VersionAbstract
The developmental process of embryos follows a monotonic order. An embryo can progressively cleave from one cell to multiple cells and finally transform to morula and blastocyst. For time-lapse videos of embryos, most existing developmental stage classification methods conduct per-frame predictions using an image frame at each time step. However, classification using only images suffers from overlapping between cells and imbalance between stages. Temporal information can be valuable in addressing this problem by capturing movements between neighboring frames. In this work, we propose a two-stream model for developmental stage classification. Unlike previous methods, our twostream model accepts both temporal and image information. We develop a linear-chain conditional random field (CRF) on top of neural network features extracted from the temporal and image streams to make use of both modalities. The linear-chain CRF formulation enables tractable training of global sequential models over multiple frames while also making it possible to inject monotonic development order constraints into the learning process explicitly. We demonstrate our algorithm on two timelapse embryo video datasets: i) mouse and ii) human embryo datasets. Our method achieves 98.1% and 80.6% for mouse and human embryo stage classification, respectively. Our approach will enable more profound clinical and biological studies and suggests a new direction for developmental stage classification by utilizing temporal information.
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Yang X, Heminemannc M, Howard J, Hubere G, Iyer-Biswasf S, Treut GL, Lynch M, Montooth KL, Needleman DJ, Pigolotti S, et al. Physical bioenergetics: Energy fluxes, budgets, and constraints in cells. PNAS. 2021;118 (28).Abstract
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.
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