e15661 Background: Cell-free DNA in blood originates from fragmented chromatin released by dying cells from both healthy and diseased tissues. These fragments carry rich molecular modalities that can reveal pathological alterations in tissues of origin. Design of sensitive technologies capturing the molecular modalities in body fluid should open a new revenue to greatly advance cancer diagnostics. Methods: cf-EpiTracing has been implemented on a Biomek i5 automated workstation to capture genome-wide multiple cell-free histone modifications in human plasma (50-100 μL). A two-round barcoding strategy was used to achieve high throughput, facilitating the parallel processing of 96 samples. Simplified procedures allow efficiently profiling cell-free epigenome in hundreds of samples within 6 h after antibody incubation. XGBoost machine learning models were developed to: classify colorectal cancer (CRC) patients and healthy individuals, and detect early colorectal precancerous lesions (colorectal adenoma, CRA). Results: By integrating multimodal chromatin states with machine learning, cf-EpiTracing enables accurate cancer detection and subtyping. The XGBoost model yielded robust CRC-healthy classification performance in both training (accuracy, 0.976) and independent validation group samples (accuracy, 0.922; Table 1). When applied to CRA detection, the model achieved a detection rate of 77.3%. Additionally, cf-EpiTracing achieved high classification accuracy for both colon and rectal cancer subtypes, in both early-stage (stage I, 66.7%; stage II, 69.2%) and advanced-stage (stage III, 80.0%; stage IV, 100.0%) patients. Conclusions: cf-EpiTracing leverages holistic epigenetic signatures, independently of knowledge for gene transcription, for realizing the noninvasive detection of pathological alterations in target tissues or cell types of origin. Thus, cf-EpiTracing represents a paradigm shift in colorectal diagnostics and may be widely applicable for other cancer types. Performance metrics of CRC detection. Sensitivity Specificity Accuracy Precision Recall F1 score Training dataset(93 healthy + 75 CRC) 0.987 0.968 0.976 0.989 0.968 0.978 Validation dataset(32 healthy + 32 CRC) 0.907 0.938 0.922 0.909 0.938 0.923

Cell-free DNA in blood originates from fragmented chromatin released by dying cells from both healthy and diseased tissues1,2. These fragments carry rich molecular modalities that can reveal pathological alterations in tissues of origin3-10. Here we develop cf-EpiTracing, a highly sensitive automated platform that profiles histone modifications in cell-free DNA from as little as 50 μl of human plasma. By integrating multimodal chromatin states with machine learning, cf-EpiTracing enables accurate deconvolution of cell types of origin. We generated 2,417 cf-EpiTracing profiles from plasma of 125 healthy individuals and 549 patients with inflammatory bowel disease, colorectal cancer, coronary heart disease or lymphoma. cf-EpiTracing enabled unbiased identification of primary diseased tissues and other organ involvement, stratification of B cell lymphoma subtypes with different genetic and epigenetic underpinnings, and detection of early-stage diseases or lesions. Surveying dynamics of epigenetic signatures uncovered disease transformation from follicular lymphoma to diffuse large B cell lymphoma. Further, cf-EpiTracing revealed genomic translocations and epigenetic alterations in patients with mantle cell lymphoma. Of note, our study leverages holistic epigenetic signatures, independently of knowledge of gene transcription, to accurately report recurrence risk and therapeutic response. Together, these findings establish cf-EpiTracing as an automated, non-invasive, epigenome-centric framework with broad applications in early diagnosis, molecular subtyping and prognostic prediction.

Mapping of the holistic cell behaviours sculpting the four-chambered mammalian heart has been a goal or previous studies, but so far only success in transparent invertebrates and lower vertebrates with two-chambered hearts has been achieved. Using a live-imaging system comprising a customized vertical light-sheet microscope equipped with a mouse embryo culture module, a heartbeat-gated imaging strategy and a digital image processing framework, we realized volumetric imaging of developing mouse hearts at single-cell resolution and with uninterrupted cell lineages for up to 1.5 d. Four-dimensional landscapes of Nppa(+) cardiomyocyte cell behaviours revealed a blueprint for ventricle chamber formation by which biased outward migration of the outermost cardiomyocytes is coupled with cell intercalation and horizontal division. The inner-muscle architecture of trabeculae was developed through dual mechanisms: early fate segregation and transmural cell arrangement involving both oriented cell division and directional migration. Thus, live-imaging reconstruction of uninterrupted cell lineages affords a transformative means for deciphering mammalian organogenesis. Yue, Zong, Li, Li, Zhang, Wu et al. introduce an in toto live-imaging system to track cardiac ventricle chamber formation at single-cell resolution for up to 1.5 days and digitally reconstruct cell dynamics.

The trophectoderm produced from totipotent blastomeres initiates trophoblast development, while placental deficiencies can cause pregnancy disorders. Yet, a culture system that fully recapitulates the entire placenta development is still lacking, greatly limiting related studies. Here, we captured mouse trophectoderm-like stem cells (TELSCs), which can give rise to all trophoblast lineages and can be applied to generate trophoblast organoids. We achieved the induction and maintenance of TELSCs from totipotent blastomere-like stem cells or early embryos through a Hippo-YAP/Notch-to-TGFβ1 signaling switch. At the molecular level, TELSCs resemble E4.5 trophectoderm and are distinct from all previously known trophoblast-like stem cells. Functionally, TELSCs can generate all trophoblast lineages in both teratoma and chimera assays. We further applied TELSCs to generate trophoblast organoids containing various mature trophoblasts and a self-renewing extraembryonic ectoderm (ExE)-like progenitor population. Interestingly, we observed transiently formed rosette-like structures that rely on Itgb1, which are essential to induce ExE-like progenitors and to generate organoids eventually. Thus, the capture of TELSCs enables comprehensive insights into placental development.

e16073 Background: Early and reliable assessment of treatment response across heterogeneous gastric cancer (GC) regimens remains an unmet need. Circulating cell-free chromatin retains tissue-encoded epigenetic information that can be quantified longitudinally. We developed a plasma-based framework to compute cell-free epigenetic clearance rates from serial cell-free chromatin signals (integrating six core histone modifications) and evaluated its value for cross-regimen response assessment, benchmarking against standard clinical evaluation. Methods: We profiled a prospective cohort of 31 GC patients sampled at six longitudinal timepoints across peri-treatment and peri-operative windows, treated with XELOX chemotherapy, RC48 (HER2-targeted antibody–drug conjugate), or JS001 (PD-1 blockade). Using cf-EpiTracing plasma chromatin profiling (≤100 µL plasma; automated workflow), we quantified trajectory-based clearance kinetics and compared regimen-specific response patterns as assessed by (i) routine clinical evaluation (radiographic/clinical assessment and peri-operative pathology including ypTNM where available) and (ii) cf-EpiTracing-derived clearance metrics. Associations with recurrence and prognosis were analyzed during follow-up. Results: Clinical evaluation revealed differential response patterns across regimens in this cohort, and plasma cell-free epigenetic clearance kinetics recapitulated these between-regimen differences, enabling early discrimination of higher- versus lower-benefit treatment courses. Across regimens, clearance kinetics separated respondents from non-respondents at early on-treatment timepoints and provided an orthogonal, quantitative measure consistent with clinical response assessment. In peri-operative settings, clearance-derived metrics supported pre-surgical prediction of pathological outcomes, including identification of ypT0N0M0 status. Clearance trajectories further stratified recurrence risk; 5/31 patients developed recurrence within two-year follow-up. In a small independent pilot validation, the clearance metric showed concordant directionality with clinical outcomes. Conclusions: Longitudinal plasma epigenetic clearance kinetics offer a minimally invasive, quantitative approach for early response monitoring and for comparing treatment effectiveness across GC regimens in a small clinical cohort, while also providing preliminary real-world evidence on outcomes under newer regimens. Clinical trial information: CTR20233553.

Heterochromatin exerts pivotal functions of silencing specific genes and maintenance of genome stability. However, its formation and maintenance mechanisms remain unclear. Here, we discover that the mitotic regulator NuMA, as a nucleoskeleton protein, is required for constitutive heterochromatin organization at the nucleosome level in interphase. NuMA depletion results in shortened nucleosome repeat length, dispersed nucleosome clutches, increased chromatin accessibility, and disrupted transcription repression of long terminal repeats in heterochromatin regions. Such functions of NuMA rely on its interaction with linker histone H1, which stabilizes H1's binding to chromatin and facilitates nucleosome stacking, as directly visualized by in situ cryo-ET. Notably, NuMA oligomerizes into quasi-meshwork in the nucleoplasm, providing its organization basis as a nucleoskeleton protein. Collectively, our findings illuminate the concerted effect of nucleoskeleton and linker histone on chromatin compaction at the nucleosome level, unveiling a previously unexplored mechanism by which nucleoskeleton regulates heterochromatin formation and maintenance.

Substantial epigenetic resetting during early embryo development from fertilization to blastocyst formation ensures zygotic genome activation and leads to progressive cellular heterogeneities1–3. Mapping single-cell epigenomic profiles of core histone modifications that cover each individual cell is a fundamental goal in developmental biology. Here we develop target chromatin indexing and tagmentation (TACIT), a method that enabled genome-coverage single-cell profiling of seven histone modifications across mouse early embryos. We integrated these single-cell histone modifications with single-cell RNA sequencing data to chart a single-cell resolution epigenetic landscape. Multimodal chromatin-state annotations showed that the onset of zygotic genome activation at the early two-cell stage already primes heterogeneities in totipotency. We used machine learning to identify totipotency gene regulatory networks, including stage-specific transposable elements and putative transcription factors. CRISPR activation of a combination of these identified transcription factors induced totipotency activation in mouse embryonic stem cells. Together with single-cell co-profiles of multiple histone modifications, we developed a model that predicts the earliest cell branching towards the inner cell mass and the trophectoderm in latent multimodal space and identifies regulatory elements and previously unknown lineage-specifying transcription factors. Our work provides insights into single-cell epigenetic reprogramming, multimodal regulation of cellular lineages and cell-fate priming during mouse pre-implantation development. Two new methods, target chromatin indexing and tagmentation (TACIT) and combined TACIT (CoTACIT), enabled single-cell profiling of the epigenome and lineage tracing from mouse zygotes to blastocysts.

In this Tools of the Trade article, Min Liu and Aibin He describe TACIT, a single-cell method that maps histone modifications at near genome-wide coverage, and its extension CoTACIT, which simultaneously maps up to six histone modifications in the same cell.

The myocardial wall arises from a single layer of cardiomyocytes, some delaminate to create trabeculae while others remain in the compact layer. However, the mechanisms governing cardiomyocyte fate decisions remain unclear. Using single-cell RNA sequencing, genetically encoded biosensors, and in toto live imaging, we observe intrinsic variations in erbb2 expression and its association with trabecular fate. Specifically, erbb2 promotes PI3K activity and recruits the Arp2/3 complex, inducing a polarized accumulation of the actomyosin network to drive cell delamination. Subsequently, the lineage-committed nascent trabeculae trigger Notch activity in neighboring cardiomyocytes to suppress erbb2 expression and reduce cell tension, thereby confining them to the compact layer. Overall, this genetic and cellular interplay governs compact and trabecular cell fate determination to orchestrate myocardial pattern formation.

Combinatorial control by transcription factors (TFs) is central to eukaryotic gene regulation, yet its mechanism, evolution, and regulatory impact are not well understood. Here we use natural variation in the yeast phosphate starvation (PHO) response to examine the genetic basis and species variation in TF interdependence. In Saccharomyces cerevisiae, the main TF Pho4 relies on the co-TF Pho2 to regulate ~28 genes, whereas in the related pathogen Candida glabrata, Pho4 has reduced Pho2 dependence and regulates ~70 genes. We found C. glabrata Pho4 (CgPho4) binds the same motif with 3-4 fold higher affinity. Machine learning and yeast one-hybrid assay identify two intrinsically disordered regions (IDRs) in CgPho4 that boost its activation domain's activity. In ScPho4, an IDR next to the DNA binding domain both allows for enhanced activity with Pho2 and inhibits activity without Pho2. This study reveals how IDR divergence drives TF interdependence evolution by influencing activation potential and autoinhibition.

Studies of molecular and cellular functions of small-molecule inhibitors in cancer treatment, eliciting effects by targeting genome and epigenome associated proteins, requires measurement of drug-target engagement in single-cell resolution. Here we present EpiChem for in situ single-cell joint mapping of small molecules and multimodal epigenomic landscape. We demonstrate single-cell co-assays of three small molecules together with histone modifications, chromatin accessibility or target proteins in human colorectal cancer (CRC) organoids. Integrated multimodal analysis reveals diverse drug interactions in the context of chromatin states within heterogeneous CRC organoids. We further reveal drug genomic binding dynamics and adaptive epigenome across cell types after small-molecule drug treatment in CRC organoids. This method provides a unique tool to exploit the mechanisms of cell type-specific drug actions.

Single-cell multiomics (sc-multiomics) is a burgeoning field that simultaneously integrates multiple layers of molecular information, enabling the characterization of dynamic cell states and activities in development and disease as well as treatment response. Studying drug actions and responses using sc-multiomics technologies has revolutionized our understanding of how small molecules intervene for specific cell types in cancer treatment and how they are linked with disease etiology and progression. Here, we summarize recent advances in sc-multiomics technologies that have been adapted and improved in drug research and development, with a focus on genome-wide examination of drug-chromatin engagement and the applications in drug response and the mechanisms of drug resistance. Furthermore, we discuss how state-of-the-art technologies can be taken forward to devise innovative personalized treatment modalities in biomedical research.

We present scEpiChem, a unique method to jointly measure the genomic interactions of small molecules and epigenetic states, such as histone modifications and chromatin accessibility, within single cells. scEpiChem utilizes split-pool barcoding strategy and protein A-Tn5 (PAT)-anti-biotin antibody to capture biotinylated small molecule binding sites within individual cells. Through sequential targeted tagmentation by different PAT-antibody complexes or Tn5, scEpiChem allows for the simultaneous detection of small molecule drug-target engagement and multimodal epigenome. The efficacy of the protocol is demonstrated through the profiling of biotinylated inhibitors JQ1, THZ1, and Dox. This approach provides valuable insights into cell state-specific drug targeting and gene regulation, facilitating the development of precise therapeutic interventions and the exploitation of drug resistance mechanisms.

Sculpting the epigenome with a combination of histone modifications and transcription factor occupancy determines gene transcription and cell fate specification. Here, we first develop uCoTarget, utilizing a split-pool barcoding strategy for realizing ultrahigh-throughput single-cell joint profiling of multiple epigenetic proteins. Through extensive optimization for sensitivity and multimodality resolution, we demonstrate that uCoTarget enables simultaneous detection of five histone modifications (H3K27ac, H3K4me3, H3K4me1, H3K36me3, and H3K27me3) in 19,860 single cells. We applied uCoTarget to the in vitro generation of hematopoietic stem/progenitor cells (HSPCs) from human embryonic stem cells, presenting multimodal epigenomic profiles in 26,418 single cells. uCoTarget reveals establishment of pairing of HSPC enhancers (H3K27ac) and promoters (H3K4me3) and RUNX1 engagement priming for H3K27ac activation along the HSPC path. We then develop uCoTargetX, an expansion of uCoTarget to simultaneously measure transcriptome and multiple epigenome targets. Together, our methods enable generalizable, versatile multimodal profiles for reconstructing comprehensive epigenome and transcriptome landscapes and analyzing the regulatory interplay at single-cell level.

The emergence of single-cell genomic and transcriptomic sequencing accelerates the development of single-cell epigenomic technologies, providing an unprecedented opportunity for decoding cell fate decisions largely encoded in the epigenome. Recent advances in single-cell multimodality epigenomic technologies facilitate directly interrogating the regulatory relationship between multi-layer molecular information in the same cell. In this review, we discuss recent progress in development of single-cell multimodality epigenomic technologies and applications in elucidating cellular diversifications in development and diseases, with a focus on protein-DNA interactomics and regulatory links between epigenome and transcriptome. Further, we provide perspective on the future direction of single-cell multiomics tool development as well as challenges facing ahead.

Abstract Glioblastoma Multiforme (GBM) is the most common and aggressive brain tumor, containing intrinsic resistance to current therapies leading to poor clinical outcomes. Therefore, understanding the underlying mechanisms of GBM is an urgent medical need. Although radiotherapy contributes significantly to patient survival, GBMs recur typically within the initial radiation target volume, suggesting remaining GBM cells are highly radioresistant. Deregulation of the protein translation mechanism has been shown to contribute to cancer progression by driving translational control of specific mRNA transcripts involved in cancer cell regulation. To identify new potential therapeutic targets for the treatment of GBM we pioneered ribosome profiling of glioblastoma sphere cultures (GSCs) under normal and radiotherapeutic conditions. We found that the global translation of genes matched and overlapped with previously published GBM subtypes, based on the transcriptional level. In addition, we revealed a broad spectrum of open reading frame types in both coding and non-coding regions, including a set of lncRNAs and pseudogenes undergoing active translation. In addition, we identified new mRNA transcripts being translated. Finally, we show that translation of histones is inhibited while splicing factors are more intensively translated after irradiation of GSCs. Together, our unprecedented GBM riboprofiling provides new insights in real time protein synthesis in GBM under normal and radiotherapeutic conditions which forms a resource for future research and provides potential new targets for therapy. Teaser We show a pioneering riboprofiling effort of glioblastoma (GBM), which provides new insights in real-time protein synthesis under normal and radiotherapeutic conditions. We found that the global translation of genes matched and overlapped with previously published GBM subtypes, as based on the transcriptional level. In addition, we revealed a broad spectrum of open reading frame types in both coding and non-coding regions, including a set of lncRNAs and pseudogenes undergoing active translation. In addition, we identified new mRNA transcripts being translated. Finally, we show that translation of histones is inhibited while splicing factors are more intensively translated after irradiation of GSCs. Our data form a resource for future research and provides potential new targets for therapy.

Mechanical forces are known to be important in mammalian blastocyst formation; however, due to limited tools, specific force inputs and how they relay to first cell fate control of inner cell mass (ICM) and/or trophectoderm (TE) remain elusive. Combining in toto live imaging and various perturbation experiments, we demonstrate and measure fluid flow forces existing in the mouse blastocyst cavity and identify Klf2(Krueuroppel-like factor 2) as a fluid force reporter with force-responsive enhancers. Long-term live imaging and lineage reconstructions reveal that blastomeres subject to higher fluid flow forces adopt ICM cell fates. These are reinforced by internal ferrofluid-induced flow force assays. We also utilize ex vivo fluid flow force mimicking and pharmacological perturbations to confirm mechanosensing specificity. Together, we report a genetically encoded reporter for continuously monitoring fluid flow forces and cell fate decisions and provide a live imaging framework to infer force information enriched lineage landscape during development.

Acquired stress resistance (ASR) enables organisms to prepare for environmental changes that occur after an initial stressor. However, the genetic basis for ASR and how the underlying network evolved remain poorly understood. In this study, we discovered that a short phosphate starvation induces oxidative stress response (OSR) genes in the pathogenic yeast C. glabrata and protects it against a severe H2O2 stress; the same treatment, however, provides little benefit in the low pathogenic-potential relative, S. cerevisiae. This ASR involves the same transcription factors (TFs) as the OSR, but with different combinatorial logics. We show that Target-of-Rapamycin Complex 1 (TORC1) is differentially inhibited by phosphate starvation in the two species and contributes to the ASR via its proximal effector, Sch9. Therefore, evolution of the phosphate starvation-induced ASR involves the rewiring of TORC1's response to phosphate limitation and the repurposing of TF-target gene networks for the OSR using new regulatory logics.

ABSTRACT Sculpting the epigenome with a combination of histone modifications and transcription factor (TF) occupancy determines gene transcription and cell fate specification. Here we first develop uCoTarget, utilizing a split-pool barcoding strategy for realizing ultra-high throughput single-cell joint profiling of multiple epigenetic proteins. Through extensive optimization for sensitivity and multimodality resolution, we demonstrate that uCoTarget enables simultaneous detection of five histone modifications (H3K27ac, H3K4me3, H3K4me1, H3K36me3 and H3K27me3) in 19,860 single cells. We applied uCoTarget to the in vitro generation of hematopoietic stem/progenitor cells (HSPCs) from human embryonic stem cells, presenting multimodal epigenomic profiles in 26,418 single cells. uCoTarget with high sensitivity per modality reveals establishment of pairing of HSPC enhancers (H3K27ac) and promoters (H3K4me3) along the differentiation trajectory and RUNX1 engagement priming for the H3K27ac activation along the HSPC path. We then develop uCoTargetX, an expansion of uCoTarget to simultaneously measure transcriptome and multiple epigenome targets. Together, our methods enable generalizable, versatile multi-modal profiles for reconstructing comprehensive epigenome and transcriptome landscapes and analyzing the regulatory interplay at single-cell level.