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Yang, M.

Publications and source records attributed to Yang, M..

At least 145 records · Page 8Linked to original sources

Collective biosynthesis of plant spirooxindole alkaloids through enzyme discovery and engineering

Collective synthesis is a well-established strategy to produce natural product collections from common intermediates. Extending this concept to enzymatic systems, collective biosynthesis offers a sustainable approach to diverse molecular collections but faces distinct challenges, including incomplete pathway knowledge and narrow substrate specificity of biosynthetic enzymes. Here, we overcome these limitations through enzyme discovery and protein engineering to achieve collective biosynthesis of spirooxindole alkaloids, an important class of natural products with diverse biological activities. We identified two key enzymes that catalyze enzymatic epimerization, working sequentially with a previously discovered cytochrome P450 enzyme to fully elucidate the biosynthetic pathway of pentacyclic spirooxindole alkaloids. Structure-guided engineering expanded substrate scope, enabling collective biosynthesis of 12 tetracyclic and pentacyclic spirooxindole natural products. We also generated new-to-nature fluorinated and deuterated derivatives through precursor-directed biosynthesis. This work provides crucial insights into plant spirooxindole alkaloid biosynthesis while establishing a powerful approach for sustainable production of complex natural products.

biochemistry↗

Decoding Mechanisms of PTEN Missense Mutations in Cancer and Autism Spectrum Disorder using Interpretable Machine Learning Approaches

Missense mutations in oncogenic proteins that are concurrently associated with neurodevelopmental disorders have garnered significant attention. Phosphatase and tensin homolog (PTEN) serves as a paradigmatic model for mapping its mutational landscape and identifying genotypic predictors of distinct phenotypic outcomes, including cancer and autism spectrum disorder (ASD). Despite extensive research into the genotype-phenotype correlations of PTEN mutations, the mechanisms underlying the dual association of specific PTEN mutations with both cancer and ASD (PTEN-cancer/ASD mutations) remain elusive. This study introduces an integrative approach that combines machine learning (ML) with structural dynamics to elucidate the molecular effects of PTEN-cancer/ASD mutations. Analysis of biophysical and network biology-based signatures reveals a complex energetic and functional landscape. Subsequently, an ML model and corresponding integrated score were developed to classify and predict PTEN-cancer/ASD mutations, underscoring the significance of protein dynamics in predicting cellular phenotypes. Further molecular dynamics simulations demonstrated that PTEN-cancer/ASD mutations induce dynamic alterations characterized by open conformational changes restricted to the P loop and coupled with inter-domain allosteric regulation. This research aims to enhance the genotypic and phenotypic understanding of PTEN-cancer/ASD mutations through an interpretable ML model integrated with structural dynamics analysis. By identifying shared mechanisms between cancer and ASD, the findings pave the way for the development of novel therapeutic strategies.

bioinformatics↗

Branched chain fatty acid-rich diet promotes lipid droplet enlargement and impacts organismal health in Caenorhabditis elegans

Considerable amounts of branched chain fatty acids (BCFAs) are present in the human diet from beef and dairy products. BCFAs can also be produced by the human gut microbiota and synthesized from branched chain amino acids. However, the physiological impact of a BCFA-rich diet on lipid metabolism and organismal health is unclear. In this study, by screening a collection of dietary bacteria, we find that the BCFA-rich Microbacterium diet causes the formation of supersized LDs and delays development, reduces brood size, and shortens lifespan of C. elegans. The high-BCFA diet downregulates argk-1/creatine kinase to inhibit the AMPK pathway and {beta}-oxidation and upregulates fat-7/desaturase to promote the accumulation of PUFA, which enhances lipogenesis and LD expansion. We also isolate a gain-of-function mutation in scav-4/CD36, which enhances BCFA absorption and exacerbates BCFA-induced LD enlargement, demonstrating that host genetic variation in a fatty acid transporter could influence the susceptibility to a high-BCFA diet.

cell biology↗

DNALONGBENCH: A Benchmark Suite for Long-Range DNA Prediction Tasks

Modeling long-range DNA dependencies is crucial for understanding genome structure and function across a wide range of biological contexts. However, effectively capturing these extensive dependencies, which may span millions of base pairs in tasks such as three-dimensional (3D) chromatin folding prediction, remains a significant challenge. Furthermore, a comprehensive benchmark suite for evaluating tasks that rely on long-range dependencies is notably absent. To address this gap, we introduce DNALO_SCPLOWONGC_SCPLOWBO_SCPLOWENCHC_SCPLOW, a benchmark dataset encompassing five important genomics tasks that consider long-range dependencies up to 1 million base pairs: enhancer-target gene interaction, expression quantitative trait loci, 3D genome organization, regulatory sequence activity, and transcription initiation signals. To comprehensively assess DNALO_SCPLOWONGC_SCPLOWBO_SCPLOWENCHC_SCPLOW, we evaluate the performance of five methods: a task-specific expert model, a convolutional neural network (CNN)-based model, and three fine-tuned DNA foundation models - HyenaDNA, Caduceus-Ph, and Caduceus-PS. We envision DNALO_SCPLOWONGC_SCPLOWBO_SCPLOWENCHC_SCPLOW as a standardized resource with the potential to facilitate comprehensive comparisons and rigorous evaluations of emerging DNA sequence-based deep learning models that account for long-range dependencies.

bioinformatics↗

protPheMut: An Interpretable Machine Learning Tool for Classification of Cancer and Neurodevelopmental Disorders in Human Missense Variants

MotivationRecent advances in human genomics have revealed that missense mutations in a single protein can lead to distinctly different phenotypes. In particular, some mutations in oncoproteins like Ras, MEK, PI3K, PTEN, and SHP2 are linked various cancers and Neurodevelopmental Disorders (NDDs). While numerous tools exist for predicting the pathogenicity of missense mutations, linking these variants to certain phenotypes remains a major challenge, particularly in the context of personalized medicine. ResultsTo fill this gap, we developed protPheMut (Protein Phenotypic Mutations Analyzer), leveraging multiple interpretable machine learning methods and integrate diverse biophysics and network dynamics-based signatures, for the prediction of mutations of the same protein can promote cancer, or NDDs. We illustrate the utility of protPheMut in phenotypes (cancer/NDDs) prediction by the mutation analysis of two protein cases, that are PI3K and PTEN. Compared to seven other predictive tools, protPheMut demonstrated exceptional accuracy in forecasting phenotypic effects, achieving an AUROC of 0.8501 for PI3K mutations related to cancer and Cowden syndrome. For multi-phenotypes prediction of PTEN mutations related to cancer, PHTS, and HCPS, protPheMut achieved an AUC of 0.9349 through micro-averaging. Using SHAP model explanations, we gained insights into the mechanisms driving phenotype formation. A userfriendly website deployment is also provided. AvailabilitySource code and data are available at https://github.com/Spencer-JRWang/protPheMut. We also provide a user-friendly website at http://netprotlab.com/protPheMut. Supplementary informationSupplementary data are available at Bioinformatics online. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=64 SRC="FIGDIR/small/631365v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@df55e3org.highwire.dtl.DTLVardef@7fe3f9org.highwire.dtl.DTLVardef@501cccorg.highwire.dtl.DTLVardef@192c98e_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

Exploring the effects of metformin on the body by urine proteome

Metformin is the first-line medication for treating type 2 diabetes mellitus (T2DM), with over 200 million patients taking it daily. Its effects are extensive and play a positive role in multiple areas. Can we explore its effects and potential mechanisms by urine proteome? In this study, a total of 166 differential proteins were identified after rats were given a dose of 150 mg/(kg{middle dot}d) of metformin for 5 consecutive days, including complement component C6, pyruvate kinase, coagulation factor X, growth differentiation factor 15 (GDF15), carboxypeptidase A4, chymotrypsin-like elastase family member 1, and L-lactate dehydrogenase C chain (LDH-C). Several of these proteins have been reported to be directly affected by metformin or associated with the effects of metformin. Several biological pathways enriched by the differential proteins or proteins where the differentially modified peptides are located have been reported to be associated with metformin, including glutathione metabolic process, negative regulation of gluconeogenesis, and renin-angiotensin system. Additionally, some significantly enriched biological pathways that have not been reported to be related to the effects of metformin may provide clues for the study of metformins potential mechanisms. In conclusion, the application of urine proteome offers a comprehensive and systematic approach to exploring both the known and unknown effects of drugs, thus opening a new window to study the mechanisms of metformin.

biochemistry↗

Characterizing Tyrosine Ring Flips in Proteins by 19F NMR

Aromatic ring-flip dynamics are hallmarks of concerted protein "breathing" motions that are essential for biological function. Ring flips occur on a broad range of timescales (ns-s) and have been primarily studied by NMR spectroscopy, typically requiring expensive isotope labeling of aromatic side chains, thereby limiting such studies to a few proteins. Here, we report two novel di-fluorotyrosine probes, 3,5-F2Y and 2,6-F2Y, that can be incorporated into proteins cost-effectively for characterizing and modulating tyrosine ring-flip dynamics. We show that 19F rotating-frame (R1{rho}) relaxation dispersion is powerful for quantifying ring flips on the {micro}s-ms timescale. Importantly, the tyrosine ring-flip rates (kflip) for 3,5-F2Y in GB1 and HPr are comparable to those measured by 1H and 13C NMR studies, validating 3,5-F2Y as a largely non-perturbing, native-like ring-flip probe. In contrast, 2,6-F2Y acts as an effective "brake" on ring flips, enabling direct visualization and quantitative characterization of previously undetected tyrosine ring flips in ubiquitin via 19F lineshape analysis. Furthermore, we use 2,6-F2Y to assess the environmental effects on ring-flip dynamics in crowding reagents and in living X. laevis oocytes. Collectively, our study opens a new avenue for measuring and modulating ring-flip dynamics in vitro and in living cells. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=165 SRC="FIGDIR/small/630691v2_ufig1.gif" ALT="Figure 1"> View larger version (61K): org.highwire.dtl.DTLVardef@dcf8e1org.highwire.dtl.DTLVardef@1578887org.highwire.dtl.DTLVardef@1c481d0org.highwire.dtl.DTLVardef@268ae0_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

Maize TIR-only Proteins ZmTIR1 and ZmTIR2, but not ZmTIR3 Confer Auto-active Hypersensitive Response Likely by Forming Condensation

Nucleotide binding, leucine-rich-repeat (NLR) proteins are the major intracellular receptors for defending against pathogen infection. The recognition between NLRs and pathogen secreted effectors often triggers a localized programmed cell death termed hypersensitive response (HR). Despite significant progresses have been achieved in understanding canonical NLRs with the N-terminal Toll/interleukin-1 receptor (TIR) domains, the molecular mechanisms underlying TIR-only proteins in plant immune responses remain unclear. In this study, we identified six TIR-containing proteins in maize, including three TIR-only proteins. Functional analysis showed that ZmTIR1 and ZmTIR2, but not ZmTIR3, confer autoactive HR when transiently expressed in N. benthamiana. The autoactivity conferred by ZmTIR1 and ZmTIR2 depends on EDS1-PAD4-RNL module and their putative NADase activities. Interestingly, ZmTIR1 and ZmTIR2 predominantly localize in the punctate dots and likely form condensation, while ZmTIR3 mainly localizes in the cytoplasm and the nucleus. Two specific amino acids in the BB-loop region were identified to be required for ZmTIR1- and ZmTIR2-mediated condensation formation and auto-HR. Furthermore, ZmTIR and ZmTIR2 are induced by Cochliobolus heterostrophus, the causal agent of southern leaf blight (SLB) in maize, and knock-down the expression of ZmTIR1 or ZmTIR2 decreased the resistance to SLB in maize. Our study reveals a novel mechanism of monocot TIR-only proteins in maize immune responses.

plant biology↗

Fbxo42 promotes the degradation of Ataxin-2 granules to trigger terminal Xbp1 signaling

The Unfolded Protein Response (UPR) is composed by homeostatic signaling pathways that are activated by the accumulation of misfolded proteins in the Endoplasmic Reticulum (ER), a condition known as ER stress. Prolonged ER stress and activation of the UPR causes cell death, by mechanisms that remain poorly understood. Here, we report that regulation of Ataxin-2 by Fbxo42 is a crucial step during UPR-induced cell death. From a genetic screen in Drosophila, we identified loss of function mutations in Fbxo42 that suppress cell death and retinal degeneration induced by the overexpression of Xbp1spliced, an important mediator of the UPR. We identified the RNA binding protein Ataxin-2 as a substrate of Fbxo42, which, as part of a Skp-A/Cullin-1 complex, promotes the ubiquitylation and degradation of Ataxin-2. Upon ER-stress, the mRNA of Xbp1 is not immediately translated but instead it is sequestered and stabilized in Ataxin-2 granules, until the Fbxo42 recruitment to these granules promotes the degradation of Ataxin-2, allowing the translation of Xbp1 mRNA at later stages of UPR activation. Our results identify Fbxo42-mediated degradation of Ataxin-2 as a key mechanism regulating the levels of Xbp1 mRNA and protein, to trigger cell death during the terminal stages of UPR activation.

cell biology↗

Expression of Intron-containing HIV-1 RNA Induces NLRP1 Inflammasome Activation in Myeloid Cells

Despite the success of antiretroviral therapy (ART) in suppressing plasma viremia in people living with human immunodeficiency virus type-1 (HIV-1), persistent viral RNA expression in tissue reservoirs is observed and can contribute to HIV-1-induced immunopathology and comorbidities. Infection of long-lived innate immune cells, such as tissue-resident macrophages and microglia may contribute to persistent viral RNA production and chronic inflammation. We recently reported that de-novo cytoplasmic expression of HIV-1 intron-containing RNA (icRNA) in macrophages and microglia leads to MDA5 and MAVS-dependent innate immune sensing and induction of type I IFN responses, demonstrating that HIV icRNA is a pathogen-associated molecular pattern (PAMP). In this report, we show that cytoplasmic expression of HIV-1 icRNA also induces NLRP1 inflammasome activation and IL-1{beta} secretion in macrophages and microglia in a RLR- and endosomal TLR-independent manner. Infection of both macrophages and microglia with either replication-competent or single-cycle HIV-1 induced IL-1{beta} secretion, which was attenuated when cytoplasmic expression of viral icRNA was prevented. While IL-1{beta} secretion was blocked by treatment with caspase-1 inhibitors or knockdown of NLRP1 or caspase-1 expression in HIV- infected macrophages, overexpression of NLRP1 significantly enhanced IL-1{beta} secretion in an HIV-icRNA-dependent manner. Immunoprecipitation analysis revealed interaction of HIV-1 icRNA, but not multiply-spliced HIV-1 RNA, with NLRP1, suggesting that HIV-1 icRNA sensing by NLRP1 is sufficient to trigger inflammasome activation. Together, these findings reveal a pathway of NLRP1 inflammasome activation induced by de novo expressed HIV icRNA in HIV- infected myeloid cells.

microbiology↗

Mapping histological and functional maturation of human endocrine pancreas across early postnatal periods

Human endocrine cell differentiation and islet morphogenesis play critical roles in determining islet cell mass and function, but the events and timeline of these processes are incompletely defined. To better understand early human islet cell development and maturation, we collected 115 pediatric pancreata and mapped morphological and spatiotemporal changes from birth through the first ten years of life. Using quantitative analyses and a combination of complementary tissue imaging approaches, including confocal microscopy and whole-slide imaging, we developed an integrated model for endocrine cell formation and islet architecture, including endocrine cell type heterogeneity and abundance, endocrine cell proliferation, and islet vascularization and innervation. We also assessed insulin and glucagon secretory profiles in isolated islet preparations from pediatric donors aged 2 months to 10 years and found a temporal difference in the maturation of insulin secretion compared to glucagon secretion. This comprehensive summary of postnatal and pediatric pancreatic islet development provides a framework for future studies and integration of emerging genetic and genomic data related to islet biology and diabetes risk.

developmental biology↗

AMPK acts to remove immune barriers to CD8+ T cell-mediated immunity against hepatocellular carcinoma

Dysregulated metabolism in tumor tissues, and para-tumor tissues alike, can lead to immunosuppression, which may underlie cancer development. However, metabolic intervention as a therapeutic strategy has been of no avail. In this study, we explored the anti-cancer therapeutic effect of aldometanib that specifically targets lysosome-associated aldolase to mimic glucose starvation and thereby activates the lysosomal AMP-activated protein kinase (AMPK), a master regulator of metabolic homeostasis. We show that aldometanib inhibits the growth of HCC in an AMPK-dependent manner, allowing hepatoma-bearing mice to survive to mature ages, although aldometanib does not possess cytotoxicity towards HCC or normal cells. Intriguingly, aldometanib exerts anti-cancer effects only in immune-competent host mice, but not in immune-defective mice. We have further found that the HCC tissues in aldometanib-treated mice are massively infiltrated with CD8+ T cells, which is not seen in mice with liver-specific knockout of AMPK. Our findings thus suggest that the metabolic regulator AMPK rebalances the tumor microenvironment to allow the cytotoxic immune cells inside the body to eliminate cancer cells and effectively contain the tumor tissues. The finding that metabolic intervention can make cancer a life-long manageable disease, may potentially usher in a new era of cancer therapy.

immunology↗

Changes in urinary proteome of rats before and after noise exposure

This study established an acute noise exposure model in which 10 rats were exposed to a 119 dB noise environment for 9 hours daily over a period of 7 consecutive days. Proteomic analysis was performed on urine samples collected from the rats. A comparison of protein expression profiles before and after noise exposure identified 219 differentially expressed proteins, 30 of which are known to be associated with hearing loss. Notably, Gelsolin plays a critical role in regulating the growth and stability of the mechanosensory hair bundles in mammalian cochlear outer hair cells. Deficiency of Lysosome-associated membrane glycoprotein 1 has been reported to cause vacuolization and structural alterations in lysosomal membrane proteins in cochlear marginal cells, leading to hearing loss in mice. Similarly, SLIT and NTRK-like family member 6 deficiency is linked to delayed synaptogenesis and auditory dysfunction in mice. These findings indicate that high-decibel noise exposure induces significant changes in urinary protein expression, many of which are associated with auditory damage as previously reported.

molecular biology↗

A gene co-expression network-based analysis of mesenchymal stromal cells reveals novel genes and molecular pathways underlying heterotopic ossification

BackgroundHeterotopic ossification (HO) represents a frequently seen refractory disease second to musculoskeletal injury, in which bone tissue ectopically exists within soft tissue, resulting in serious extremity loss-of-function. This work focused on identifying regulating factors and gene network associated with HO pathology. Material and MethodsWe randomized the heterotopic ossification dataset GSE94683 as HO and NON-HO group. Weighted gene co-expression network analysis (WGCNA) was applied in identifying HO related modules. We discovered differentially expressed genes (DEGs) between the two groups. Then, we integrated protein-protein interaction (PPI) network, co-expression network, enrichment analysis, gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) for identifying the HO-related pathways. We also employed GSE126118 test set to investigate hub genes related to HO. Eventually, potential therapeutics for reversing abnormal hub gene levels were predict by DGIdb. ResultsWe discovered twelve HO status modules and 1,483 DEGs in HO samples compared with NON-HO counterparts. Four hub genes were obtained from the overlap of HO related PPI and coexpression networks. Training and test sets were adopted for verification, and three abnormally high hub gene expression in HO were obtained. Functional enrichment of DEGs indicated that these genes were involved in the stem cell pluripotency regulatory pathways, cytokine-cytokine receptor interaction, as well as rap1 pathway. Based on the results from GSEA and GSVA, many hub gene sets were mainly enriched in immune responses. ConclusionWe identified a gene coexpression network associated with regulatory factors in HO, which provided a new perspective on the pathogenesis and provided potential biomarkers or therapeutic targets.

bioinformatics↗

CBAM-ResNet34-based classification and evaluation method for developmental processes of greenhouse strawberries

Strawberries, known for their economic significance and rich nutritional value, are cultivated extensively worldwide. However, a host of workers need to be employed every year to identify and categorize the developmental stages of the strawberries in the greenhouses, which is not only time-consuming, inefficient, increasing the cultivation cost, but also difficult to guarantee the classification accuracy. Meanwhile, affected by the complicated background, occlusions, and color interference, the features of strawberries are proven challenging to be extracted via the traditional neural networks due to serious gradient disappearance. Therefore, an improved CBAM-ResNet34- based classification evaluation method for developmental processes of greenhouse strawberries is investigated. The procedure of this method is as follows: firstly, the developmental stages of greenhouse strawberries are classified by experts into four stages: Stage I (initial stage), Stage II (green and white fruit stage), Stage III (early ripening stage), and Stage IV (fully ripe stage). The 627, 640, 604, and 340 strawberry images for these four stages are captured. Subsequently, the images are divided into training, validation, as well as testing sets and then undergo image pre- processing, expansion, and augmentation. Whereafter, the 7x7 convolution kernel in the first layer of the network is replaced by three consecutive 3x3 convolution cores to eliminate the redundant weights and unnecessary model parameters, and the BasicBlocks configuration is adjusted. Finally, the CBAM attention mechanism is added to each BasicBlock so as to pinpoint the spatial position of the strawberries and extract their major features such as shape, size, and color. Comparison experiments with the conventional deep neural networks LeNet5, AlexNet, VGG16, ResNet18, ResNet34, and every improved part of CBAM-ResNet34 demonstrated that when the learning rate is 0.001, the Dropout rate is 0.3, and the Adams weight decay parameter is 0.001, the accuracies for validation and testing sets can reach to 92.36% and 87.56% with F1 scores of 0.92, 0.87, 0.85 and 0.88.

plant biology↗

The virulence and motility of Pseudomonas syringae pv. Actinidiae mediated by a temperature sensor HktS-HktR

Kiwifruit bacterial canker (KBC), caused by Pseudomonas syringae pv. actinidiae (Psa) is one of the most devastating diseases of kiwifruit and can damage almost all kiwifruit varieties. The severity of the disease occurrence is closely related to the temperature. Our previous research indicated that Psa showed stronger pathogenicity and expansion ability at relatively cool temperatures, but how Psa senses environmental temperature and regulates its virulence mechanism remains unclear. In this study, 69 Histidine kinases (HK) in Psa were predicted through bioinformatics analysis, and 9 differentially expressed HK genes were identified at varying temperatures through pathogenicity detection and quantitative reverse transcription PCR (qRT-PCR). Among them, HktS as a temperature signal receiver was identified, and its response regulator (RR) HktR was determined through structure analysis and cotranscription assay. The results showed that HktR can bind to transcription factor RpoD, and RpoD bind to hrpRS promoter region, thus initiating the expression level of the type III secretion system (T3SS), which plays an important role in the pathogenesis of Psa. In addition, the motility of Psa was also regulated by HktS-HktR in a temperature-dependent manner. These findings reveal the molecular mechanism by which HktS-HktR acts as a temperature sensor to regulate bacterial virulence and motility of Psa, providing a new potential target for KBC control.

microbiology↗

Spatially Resolved in vivo CRISPR Screen Sequencing via Perturb-DBiT

Perturb-seq enabled the profiling of transcriptional effects of genetic perturbations in single cells but lacks the ability to examine the impact on tissue environments. We present Perturb-DBiT for simultaneous co- sequencing of spatial transcriptome and guide RNAs (gRNAs) on the same tissue section for in vivo CRISPR screen with genome-scale gRNA libraries, offering a comprehensive understanding of how genetic modifications affect cellular behavior and tissue architecture. This platform supports a variety of delivery vectors, gRNA library sizes, and tissue preparations, along with two distinct gRNA capture methods, making it adaptable to a wide range of experimental setups. In applying Perturb-DBiT, we conducted un-biased knockouts of tens of genes or at genome-wide scale across three cancer models. We mapped all gRNAs in individual colonies and corresponding transcriptomes in a human cancer metastatic colonization model, revealing clonal dynamics and cooperation. We also examined the effect of genetic perturbation on the tumor immune microenvironment in an immune-competent syngeneic model, uncovering differential and synergistic perturbations in promoting immune infiltration or suppression in tumors. Perturb-DBiT allows for simultaneously evaluating the impact of each knockout on tumor initiation, development, metastasis, histopathology, and immune landscape. Ultimately, it not only broadens the scope of genetic inquiry, but also lays the groundwork for developing targeted therapeutic strategies.

genomics↗

Chromosomal Instability in Human Trophoblast Stem Cells and Placentas

The human placenta, a unique tumor-like organ, is typically thought to exhibit rare aneuploidy associated with adverse pregnancy outcomes. Discrepancies in reported aneuploidy prevalence in placenta likely stem from limitations in modeling and the resolution of detection methods. Here, we used isogenic trophoblast stem cells (TSCs) derived from both naive and primed human pluripotent stem cells (hPSCs) to reveal the spontaneous occurrence of aneuploidy, suggesting chromosomal instability (CIN) as an inherent feature of the trophoblast lineage. We identified potential pathways contributing to the occurrence and tolerance of CIN. These findings were further validated using single cell multiome data from human placentas, where we observed a high prevalence of heterogeneous aneuploidy across trophoblast cells. Despite extensive chromosomal abnormalities, TSCs maintained their proliferative and differentiation capacities, suggesting that CIN is a typical aspect of placental development. Our study challenges the traditional view of aneuploidy in the placenta and provides new insights into the role of CIN in normal placental function.

developmental biology↗