Boston IVF

Chromatin organization underlies gene regulation and cell fate specification, yet how nucleosome-scale chromatin structure contributes to lineage segregation during early development remains unknown. Here, we resolved chromatin ultrastructure during the first lineage decision in mouse and human, which forms the pluripotent inner cell mass (ICM) and trophectoderm (TE). To achieve this, we developed dual-tilt chromatin electron tomography (2T-ChromEMT) that allows multiscale visualization of chromatin architecture. Our analysis reveals that TE cells of both species display denser chromatin with nucleosome aggregation at the nuclear periphery. We show upregulation of the nuclear matrix protein Lamin A/C within the TE lineage across mouse, human, and opossum embryos, indicating that its regulatory role is conserved across eutherian and marsupial species. Loss of Lamin A/C reduces heterochromatin at the nuclear lamina in TE cells, reactivates pluripotency genes, and impairs mouse blastocyst expansion and human blastoid formation. These findings define the nucleosome-resolution chromatin signatures of early mammalian lineages and establish Lamin A/C–mediated chromatin organization as a conserved mechanism in the exit from pluripotency and maintenance of trophectoderm identity.

People in low- and middle-income countries face many obstacles when trying to access fertility treatments. These challenges include high costs, the need for specialized medical facilities, and cultural beliefs that may discourage seeking help. This paper explores how artificial intelligence (AI) and automation could help overcome some of these barriers and make fertility treatments more widely available. It examines how AI may improve the accuracy, efficiency, and consistency of different steps in fertility treatments, such as choosing the healthiest embryos, analyzing sperm, evaluating eggs, and planning treatment. The paper also discusses how automation could simplify laboratory procedures, from growing embryos and freezing them for future use to the possibility of fully automating the in vitro fertilization (IVF) process, which could help lower costs and make these treatments more accessible. Finally, this paper addresses the ethical and practical challenges associated with using these technologies, including potential biases in AI, equitable access, quality control, data privacy, job implications, and cultural sensitivities.Lay summaryThis paper explores how AI and automation could help make fertility treatments more accessible in low- and middle-income countries (LMICs). Many individuals and couples face difficulties conceiving, and assisted reproductive technology (ART) – which includes procedures such as intrauterine insemination (IUI) and IVF – offers them a chance to build a family. However, ART is often out of reach in LMICs due to high costs, the need for specialized medical facilities, and cultural barriers. AI and automation have the potential to improve accuracy, efficiency, and consistency in ART procedures, such as embryo selection, sperm and egg assessment, and treatment planning. Automation could also streamline laboratory processes, including embryo culture and freezing, which may eventually lead to more affordable and scalable fertility treatments. By reducing human error and dependence on highly trained specialists, AI-driven technologies could help lower costs and make ART available to more people. This paper also considers the ethical and practical challenges of using AI in reproductive medicine, including potential biases in AI algorithms, fairness in access to treatment, data privacy, workforce impact, and cultural sensitivities. Fertility treatments can be life-changing for those struggling with infertility due to medical conditions, age, or personal circumstances. They also provide opportunities for same-sex couples and individuals who want to start a family. However, in LMICs, infertility is often surrounded by social stigma, economic hardship, and limited medical resources, making access to ART even more difficult. By integrating AI and automation into reproductive medicine, it may be possible to break down these barriers, reduce costs, and create more inclusive and accessible fertility care. These advancements have the potential to bring hope to millions who dream of parenthood but currently lack the means to pursue it.

Following fertilization, the preimplantation embryo undergoes successive rounds of cell division and must accurately propagate the genetic material to ensure successful development. However, early mammalian embryos lack efficient spindle assembly mechanisms, and it remains unclear how error-free chromosome segregation is achieved. In this work, we imaged early mouse embryos and identified a network of nuclear actin cables that organize prophase chromosomes at the nuclear periphery. Following nuclear envelope breakdown, the network contracts and gathers chromosomes toward the cell center. Network contraction was driven by filament disassembly in a myosin II-independent manner. Additionally, we identified a network of branched actin filaments that attenuates metaphase spindle elongation. We also visualized nuclear actin in human embryos, suggesting a conserved role for actin in ensuring mitotic fidelity during early mammalian development.

Abstract Human induced pluripotent stem cells (hiPSCs) show great promise in the development of novel strategies to mitigate reproductive diseases and promote successful reproductive outcomes. Recently, a novel approach for the fast and efficient differentiation of ovarian support cells (OSCs) to generate a versatile platform for basic research and clinical applications was demonstrated. This study details the clinical process development and application of an OSC product, known asFertilo, to improve thein vitromaturation (IVM) of human oocytes, a method referred to as OSC-IVM. First, transcription factor (TF) mediated OSC differentiation using research-grade raw materials was shown to produce granulosa-like cells that improve the MII maturation rate of human oocytes. To support clinical application, several raw material upgrades were initiated, including substitution of the differentiation matrix with a higher-quality alternative, laminin-521, and the generation of a clinically suitable hiPSC seed bank and master cell bank. Single cell RNA sequencing of OSCs generated using the updated protocol for clinical translation demonstrated the consistency and reproducibility of cellular outcomes. Next, analytical release testing of the clinical product was performed and a murine oocyte maturation assay was developed to establish the potency of OSCs for use in OSC-IVM. Finally, the qualifiedFertiloproduct was applied in a two-phase longitudinal cohort analysis, with the results showing improvement in key outcomes compared to traditional IVM treatment. Our findings demonstrate the first-time clinical development and application of an hiPSC-derived product to improve reproductive outcomes after IVM and advance women’s health.

Pre-implantation genetic testing for aneuploidy (PGT-A) via embryo biopsy helps in embryo selection by assessing embryo ploidy. However, clinical practice needs to consider the invasive nature of embryo biopsy, potential mosaicism, and inaccurate representation of the entire embryo. This creates a significant clinical need for improved diagnostic practices that do not harm embryos or raise treatment costs. Consequently, there has been an increasing focus on developing non-invasive technologies to enhance embryo selection. Such innovations include non-invasive PGT-A, artificial intelligence (AI) algorithms, and non-invasive metabolic imaging. The latter measures cellular metabolism through autofluorescence of metabolic cofactors. Notably, hyperspectral microscopy and fluorescence lifetime imaging microscopy (FLIM) have revealed unique metabolic activity signatures in aneuploid embryos and human fibroblasts. These methods have demonstrated high accuracy in distinguishing between euploid and aneuploid embryos. Thus, this review discusses the clinical challenges associated with PGT-A and emphasizes the need for novel solutions such as metabolic imaging. Additionally, it explores how aneuploidy affects cell behaviour and metabolism, offering an opinion perspective on future research directions in this field of research.