Biology subjects

Cheng, M.

Publications and source records attributed to Cheng, M..

At least 55 records · Page 3Linked to original sources

bioRxiv2023

Utilizing tumor microenvironment microbial profiles and host gene expressions for survival subtyping in diverse types of cancers

The tumor microbiome, a complex community of microbes found in tumors, has been found to be linked to cancer development, progression, and treatment outcome. However, it remains a bottleneck in distangling the relationship between the tumor microbiome and patient survival. In this study, we aimed to decode this complex relationship by developing ASD-cancer (autoencoder-based subtypes detector for cancer), a semi-supervised deep learning framework that could extract survival-related features from tumor microbiome and transcriptome data, and identify patients survival subtypes. By using samples from The Cancer Genome Atlas database, we identified two statistically distinct survival subtypes across all 20 types of cancer. Our framework provided improved risk-stratification (e.g., for Liver hepatocellular carcinoma, LIHC, log-rank test, P = 8.12E-6) compared to PCA (e.g., for LIHC, log-rank test, P = 0.87), predicted survival subtypes accurately, and identified biomarkers for survival subtypes. Additionally, we identified potential interactions between microbes and genes that may play roles in survival. For instance, in LIHC, Arcobacter, Methylocella, and Isoptericola may regulate host survival through interactions with host genes enriched in the HIF-1 signaling pathway, indicating these species as potential therapy targets. Further experiments on validation dataset have also supported these patterns. Collectively, ASD-cancer has enabled accurate survival subtyping and biomarker discovery, which could facilitate personalized treatment for a broad-spectrum types of cancers.

bioinformatics↗

bioRxiv2023

C-type natriuretic peptide improves maternally aged oocytes quality by inhibiting excessive PINK1/Parkin-mediated mitophagy

The overall oocyte quality declines with ageing, and this effect is strongly associated with a higher reactive oxygen species (ROS) level and the resultant oxidative damage. C-type natriuretic peptide (CNP) is a well-characterized physiological meiotic inhibitor that has been successfully used to improve immature oocyte quality during in vitro maturation (IVM). However, the underlying roles of CNP in maternally aged oocytes have not been reported. Here, we found that the age-related reduction in the serum CNP concentration was highly correlated with decreased oocyte quality. Treatment with exogenous CNP promoted follicle growth and ovulation in aged mice and enhanced meiotic competency and fertilization ability. Interestingly, the cytoplasmic maturation of aged oocytes was thoroughly improved by CNP treatment, as assessed by spindle/chromosome morphology and redistribution of organelles (mitochondria, the endoplasmic reticulum [ER], cortical granules [CGs], and the Golgi apparatus). CNP treatment also ameliorated DNA damage and apoptosis caused by ROS accumulation in aged oocytes. Importantly, oocyte RNA-seq revealed that the beneficial effect of CNP on aged oocytes was mediated by restoration of mitochondrial oxidative phosphorylation, eliminating excessive mitophagy. CNP reversed the defective phenotypes in aged oocytes by alleviating oxidative damage and suppressing excessive PINK1/Parkin-mediated mitophagy. Mechanistically, CNP functioned as a cAMP/PKA pathway modulator to decrease PINK1 stability and inhibit Parkin recruitment. In summary, our results demonstrated that CNP supplementation constitutes an alternative therapeutic approach for advanced maternal age-related oocyte deterioration and may improve the overall success rates of clinically assisted reproduction in older women.

developmental biology↗

bioRxiv2023

RNPS1 stabilizes NAT10 protein to facilitate translation in cancer via tRNA ac4C modification

NAT10 is dysregulated and plays an essential role in various types of cancers. However, the exact machenism of how NAT10 regulates cancer progression remains debatable. In this report, we show that NAT10 affects tumorigeneis mainly based on its acetylation function on tRNA. In addition, we found NAT10 regulate the ac4C of tRNA in cancer via interaction with RNPS1, which in turn protect NAT10 from degradation by E3 ubiquitin ligase ZSWIM6. We developed TRMC-seq method to compreshensively profile tRNA ac4C sites and uncovered the presence of ac4C in a broader range of tRNA isoacceptors than previous studies. Multi-omics analysis identified AP-1 signaling pathway as a major downstream mediator of NAT10. Mechanistically, we found NAT10 is responsible for the translation efficiency genes which contain higher ac4C-tRNA codon. Importantly, our genetic mouse model validated our in vitro findings of NAT10 in cancer. Our study highlights a role of NAT10 in mediating tRNA ac4C to regulate the translation and tumorigenesis of cancer.

molecular biology↗

bioRxiv2023

Single-cell transcriptional analysis of lamina propria lymphocytes in the jejunum reveals ILC-like cells in pigs

Pigs are the most suitable model to study various therapeutic strategies and drugs for human beings, while knowledge about tissue- and cell-type-specific transcriptomes and heterogeneity is poorly available. Here, we focused on the intestinal immunity of pigs. Through single-cell sequencing (scRNA-seq) and flow cytometry analysis of the types of immune cells in the jejunum of pigs, we found that innate lymphoid cells (ILCs) existed in the lamina propria lymphocytes (LPLs) of the jejunum. Then, through flow sorting of Live/Dead (L/D)-Lineage(LIN)-CD45+ cells and scRNA-seq, we found that ILCs in the porcine jejunum were mainly ILC3s, with a small number of ILC1s, ILC2s, and NK cells. Through a gene expression map, we found that ILCs coexpressed IL-7R, ID2, and other genes and differentially expressed RORC, GATA3, and other genes but did not express the CD3 gene. According to their gene expression profiles, ILC3s can be divided into four subgroups, and genes such as CXCL8, CXCL2, IL-22, IL-17, and NCR2 are differentially expressed. To further detect and identify ILC3s, we prepared RORC monoclonal antibodies and verified the classification of ILCs in the porcine jejunum subgroup and the expression of related hallmark genes at the protein level by flow cytometry. For systematically characterizing of ILCs in the porcine intestines, we combined our pig ILCs dataset with publicly available human and mice ILCs data and identified that the humans and pigs ILCs shared more common features than those mice ILCs in gene signatures and cell states. For the first time, our results showed in detail the gene expression of porcine jejunal ILCs, the subtype classification of ILCs, and the markers of various ILCs, which provides a basis for an in-depth exploration of porcine intestinal mucosal immunity. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=199 SRC="FIGDIR/small/522424v3_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@184fd80org.highwire.dtl.DTLVardef@1efc00org.highwire.dtl.DTLVardef@328a04org.highwire.dtl.DTLVardef@3296e_HPS_FORMAT_FIGEXP M_FIG Graphical abstract C_FIG

immunology↗

bioRxiv2022

Detection of PatIent-Level distances from single cell genomics and pathomics data with Optimal Transport (PILOT)

Although clinical applications represent the next challenge in single-cell genomics and digital pathology, we still lack computational methods to analyze single-cell and pathomics data to find sample level trajectories or clusters associated with diseases. This remains challenging as single-cell/pathomics data are multi-scale, i.e., a sample is represented by clusters of cells/structures and samples cannot be easily compared with each other. Here we propose PatIent Level analysis with Optimal Transport (PILOT). PILOT uses optimal transport to compute the Wasserstein distance between two individual single-cell samples. This allows us to perform unsupervised analysis at the sample level and uncover trajectories or cellular clusters associated with disease progression. We evaluate PILOT and competing approaches in single-cell genomics and pathomics studies involving various human diseases with up to 600 samples/patients and millions of cells or tissue structures. Our results demonstrate that PILOT detects disease-associated samples from large and complex single-cell and pathomics data. Moreover, PILOT provides a statistical approach to delineate non-linear changes in cell populations, gene expression, and tissue structures related to the disease trajectories supporting interpretation of predictions.

bioinformatics↗

bioRxiv2022

HDL-C as a potential medium between depletion of Lachnospiraceae genera and hypertension under high-calorie diet

Gut microbial dysbiosis has been associated with hypertension. An extremely high incidence of essential hypertension was found in the Han and the Yugur who resided in Sunan county in East Asias nomadic steppes with little population movement. In attempt to investigate the gut microbial role in hypertension, we recruited a total of 1, 242 Yugur and Han people, who had resided in Sunan County for more than 15 years and accounted for 3% of the local population. The epidemiological survey of 1,089 individuals indicated their nearly 1.8 times higher prevalence of hypertension (38.2-43.3%) than the average in China (23.2%), under a special high-calorie diet based on wheat, cattle, mutton, and animal offal. The 16S rRNA gene sequencing on the fecal samples of 153 individuals revealed that certain Lachnospiraceae genera were negatively correlated with high-density lipoprotein cholesterol (HDL-C, P = 5.46 x 10-6), systolic blood pressure (SBP, P = 7.22 x 10-3), diastolic blood pressure (DBP, P = 1.8 x 10-3). HDL-C was positively correlated with SBP (P = 0.023). We further observed that serum butyrate content was lower in both Han (P = 1.99 x 10-3) and Yugur people (P = 0.031) with hypertension than those without hypertension. This study gives a novel insight into the role of gut microbial dysbiosis in hypertension modulation under a high-calorie diet, where the notable depletion of Lachnospiraceae genera might lead to less production of butyrate, contributing to the lower level of HDL-C, and elevating blood pressure in hypertension. IMPORTANCEDietary nutrients can be converted by gut microbiota into metabolites such as short-chain fatty acids, which may serve as disease-preventing agents in hypertension. Due to limited population mobility and a unique high-calorie dietary habit, the recruited cohort in this study could be a representative for elucidating the associations between gut microbiota and hypertension under high-calorie diet. Moreover, low levels of HDL-C have previously been associated with an increased risk of various cardiovascular diseases (CVDs). Our findings provide a new insight that low levels of HDL-C may be a potential medium between depletion of Lachnospiraceae genera and hypertension under high-calorie diet, which might also be a potential candidate for other CVDs.

microbiology↗

bioRxiv2022

Targeting Chromatin Effector Pygo2 to Enhance Immunotherapy in Prostate Cancer

The noninflamed microenvironment in prostate cancer represents a barrier to immunotherapy. Genetic alterations underlying cancer cell-intrinsic oncogenic signaling have emerging roles in shaping the immune landscape. Recently, we identified Pygopus 2 (PYGO2) as the driver oncogene for the amplicon at 1q21.3. Here, using transgenic mouse models of metastatic prostate adenocarcinoma, we found that Pygo2 deletion decelerated tumor progression, diminished metastases, and extended survival. Pygo2 loss augmented the infiltration of cytotoxic T lymphocytes (CTLs) and sensitized tumor cells to T cell killing. Mechanistically, Pygo2 orchestrated a p53/Sp1/Kit/Ido1 signaling network to foster a microenvironment hostile to CTLs. Genetic or pharmacological inhibition of Pygo2 enhanced the anti-tumor efficacy of immunotherapies using immune checkpoint blockade, adoptive cell transfer, or myeloid-derived suppressor cell inhibitors. In human prostate cancer samples, Pygo2 expression was inversely correlated with CD8+ T cells. Our results highlight a promising path to improving immunotherapy with targeted therapy for lethal prostate cancer.

cancer biology↗

bioRxiv2022

A Genomically and Clinically Annotated Patient Derived Xenograft (PDX) Resource for Preclinical Research in Non-Small Cell Lung Cancer

Patient-derived xenograft models (PDXs) are an effective preclinical in vivo platform for testing the efficacy of novel drug and drug combinations for cancer therapeutics. Here we describe a repository of 79 genomically and clinically annotated lung cancer PDXs available from The Jackson Laboratory that have been extensively characterized for histopathological features, mutational profiles, gene expression, and copy number aberrations. Most of the PDXs are models of non-small cell lung cancer (NSCLC), including 37 lung adenocarcinoma (LUAD) and 33 lung squamous cell carcinoma (LUSC) models. Other lung cancer models in the repository include four small cell carcinomas, two large cell neuroendocrine carcinomas, two adenosquamous carcinomas, and one pleomorphic carcinoma. Models with both de novo and acquired resistance to targeted therapies with tyrosine kinase inhibitors are available in the collection. The genomic profiles of the LUAD and LUSC PDX models are consistent with those observed in patient tumors of the same tumor type from The Cancer Genome Atlas (TCGA) and to previously characterized gene expression-based molecular subtypes. Clinically relevant mutations identified in the original patient tumors were confirmed in engrafted tumors. Treatment studies performed for a subset of the models recapitulated the responses expected based on the observed genomic profiles. SignificanceThe collection of lung cancer Patient Derived Xenograft (PDX) models maintained at The Jackson Laboratory retain both the histologic features and treatment-relevant genomic alterations observed in the originating patient tumors and show expected responses to treatment with standard-of-care agents. The models serve as a valuable preclinical platform for translational cancer research. Information and data for the models are freely available from the Mouse Models of Human Cancer database (MMHCdb, http://tumor.informatics.jax.org/mtbwi/pdxSearch.do).

cancer biology↗

bioRxiv2022

Microbial dysbiosis and metabolic disorders promote rheumatoid arthritis progression across successive stages

BackgroundRheumatoid arthritis (RA) is a chronic inflammatory disease that typically progresses through four stages, from mild stiffness to severe disability. The critical involvement of gut microbial dysbiosis in promoting RA has been intriguing. The aim of this study was to investigate stage-specific roles of microbial dysbiosis and metabolic disorders in pathogenesis across successive stages of RA. MethodsIn this multi-omics cohort study, fecal metagenomic, plasma metabolomic data were collected from 76 patients grouped into four RA stages, 19 patients with osteoarthritis, and 27 healthy individuals in China. A non-redundant gene catalogue was constructed, functionally annotated, and clustered into metagenomic species (MGS). Leave-one-out analysis was performed to determine the MGS that most drove the microbial dysfunctions with RA across stages. Random forest algorithm was performed to investigate diagnostic potential of microbial or metabolic features for each stage. Additionally, to verify the bacterial invasion of the joint synovial fluid, we conducted 16S rRNA gene sequencing, bacterial isolation, and scanning electron microscopy on joint synovial fluid from another cohort of 271 RA patients grouped into four RA stages. FindingsWe found that microbial dysbiosis and metabolic disorders had stage-specific effects on RA progression. For instance, arginine succinyltransferase pathway was elevated mainly in the second and third stages of RA (p=1{middle dot}4x10-3), which was driven by Escherichia coli, and it was correlated with the increase of the rheumatoid factor (p=1{middle dot}35x10-3). Considerable elevation of methoxyacetic acid (p=1{middle dot}28x10-8) and cysteine-S-sulfate (p=4{middle dot}66x10-12) might inhibit osteoblasts in the second stage and enhance osteoclasts in the third stage, respectively. Moreover, fecal microbes Eggerthella lenta and Bifidobacterium longum that were exclusively elevated in the fourth stage, were also detected in the joint synovial fluid. InterpretationOur findings elucidate for the first time the stage-specific roles of microbial dysbiosis and metabolic disorders across successive stages of RA, which open up new avenues for RA prognosis and therapy. We demonstrate the buildup of these effects might induce microbial invasion of the joint synovial fluid in the fourth stage of RA.

microbiology↗

bioRxiv2022

MOJITOO: a fast and universal method for integration of multimodal single cell data

The advent of multi-modal single cell sequencing techniques have shed new light on molecular mechanisms by simultaneously inspecting transcriptomes, epigenomes and proteomes of the same cell. However, to date, the existing computational approaches for integration of multimodal single cell data are either computationally expensive, require the delineation of parameters or can only be applied to particular modalities. We present a single cell multi-modal integration method, named MOJITOO (Multi-mOdal Joint IntegraTion of cOmpOnents). MOJITOO uses canonical correlation analysis for a fast and parameter free detection of a shared representation of cells from multimodal single cell data. Moreover, estimated canonical components can be used for interpretation, i.e. association of modality specific molecular features with the latent space. We evaluate MOJITOO using bi- and tri-modal single cell data sets and show that MOJITOO outperforms existing methods regarding computational requirements, preservation of original latent spaces and clustering.

bioinformatics↗

bioRxiv2021

Transcriptomic Profiling Reveals Cancer-Associated Fibroblasts as Potential Targets for the Prognosis and Treatment of Cervical Squamous Cell Carcinoma

Effective treatment of advanced invasive cervical cancer remains challenging nowadays. Herein, single-nucleus RNA sequencing (snRNA-seq) and SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq) technology are used to investigate the immunological microenvironment of cervical squamous cell carcinoma (CSCC), a major type of cervical cancers. The expression levels of most immune checkpoint genes in tumor and inflammation areas of CSCC were not significantly higher than those in the non-cancer samples except for LGALS9 and IDO1. Stronger signals of CD56+ NK cells and immature dendritic cells are found in the hypermetabolic tumor areas, while more eosinophils, immature B cells, and Treg cells are found in the hypometabolic tumor areas. Moreover, a cluster of cancer-associated fibroblasts (CAFs) are identified around some tumors, which highly expressed ACTA2, POSTN, ITGB4, and FAP. The CAFs might support the growth and metastasis of tumors by inhibiting lymphocyte infiltration and remodeling the tumor extracellular matrix. Furthermore, CAFs are associated with poorer survival probability in CSCC patients and might be present in a small fraction ([~]20%) of advanced cancer patients. Collectively, these findings might enhance understanding of the CSCC immunological microenvironment and shed some light on the treatment of advanced CSCC.

cancer biology↗

bioRxiv2021

Cell transcriptomic atlas of the non-human primate Macaca fascicularis

Studying tissue composition and function in non-human primates (NHP) is crucial to understand the nature of our own species. Here, we present a large-scale single-cell and single-nucleus transcriptomic atlas encompassing over one million cells from 43 tissues from the adult NHP Macaca fascicularis. This dataset provides a vast, carefully annotated, resource to study a species phylogenetically close to humans. As proof of principle, we have reconstructed the cell-cell interaction networks driving Wnt signalling across the body, mapped the distribution of receptors and co-receptors for viruses causing human infectious diseases and intersected our data with human genetic disease orthologous coordinates to identify both expected and unexpected associations. Our Macaca fascicularis cell atlas constitutes an essential reference for future single-cell studies in human and NHP.

cell biology↗

bioRxiv2021

Spatiotemporal transcriptome at single-cell resolution reveals key radial glial cell population in axolotl telencephalon development and regeneration

Brain regeneration requires a precise coordination of complex responses in a time- and region-specific manner. Identifying key cell types and molecules that direct brain regeneration would provide potential targets for the advance of regenerative medicine. However, progress in the field has been hampered largely due to limited regeneration capacity of the mammalian brain and understanding of the regeneration process at both cellular and molecular level. Here, using axolotl brain with extrodinary regeneration ability upon injury, and the SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq), we reconstructed the first architecture of axolotl telencephalon with gene expression profiling at single-cell resolution, and fine cell dynamics maps throughout development and regeneration. Intriguingly, we discovered a marked heterogeneity of radial glial cell (RGC) types with distinct behaviors. Of note, one subtype of RGCs is activated since early regeneration stages and proliferates while other RGCs remain dormant. Such RGC subtype appears to be the major cell population involved in early wound healing response and gradually covers the injured area before presumably transformed into the lost neurons. Altogether, our work systematically decoded the complex cellular and molecular dynamics of axolotl telencephalon in development and regeneration, laying the foundation for studying the regulatory mechanism of brain regeneration in the future.

developmental biology↗

bioRxiv2021

Spatially-resolved transcriptomics analyses of invasive fronts in solid tumors

Solid tumors are complex ecosystems, and heterogeneity is the major challenge for overcoming tumor relapse and metastasis. Uncovering the spatial heterogeneity of cell types and functional states in tumors is essential for developing effective treatment, especially in invasive fronts of tumor, the most active region for tumor cells infiltration and invasion. We firstly used SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq) with a nanoscale resolution to characterize the tumor microenvironment of intrahepatic cholangiocarcinoma (ICC). Enrichment of distinctive immune cells, suppressive immune microenvironment and metabolic reprogramming of tumor cells were identified in the 500{micro}m-wide zone centered bilaterally on the tumor boundary, namely invasive fronts of tumor. Furthermore, we found the damaged states of hepatocytes with overexpression of Serum Amyloid A (SAA) in invasive fronts, recruiting macrophages for facilitating further tumor invasion, and thus resulting in a worse prognosis. We also confirmed these findings in hepatocellular carcinoma and other liver metastatic cancers. Our work highlights the remarkable potential of high-resolution-spatially resolved transcriptomic approaches to provide meaningful biological insights for comprehensively dissecting the tumor ecosystem and guiding the development of novel therapeutic strategies for solid tumors.

cancer biology↗

bioRxiv2021

High-resolution spatiotemporal transcriptomic maps of developing Drosophila embryos and larvae

Drosophila has long been a successful model organism in multiple fields such as genetics and developmental biology. Drosophila genome is relatively smaller and less redundant, yet largely conserved with mammals, making it a productive model in studies of embryogenesis, cell signaling, disease mechanisms, etc. Spatial gene expression pattern is critical for understanding of complex signaling pathways and cell-cell interactions, whereas temporal gene expression changes need to be tracked during highly dynamic activities such as tissue development and disease progression. Systematic studies in Drosophila as a whole are still impeded by lack of these spatiotemporal transcriptomic information. Drosophila embryos and tissues are of relatively small size, limiting the application of current technologies to comprehensively resolve their spatiotemporal gene expression patterns. Here, utilizing SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq), we dissected the spatiotemporal transcriptomic changes of developing Drosophila with high resolution and sensitivity. Our data recapitulated the spatial transcriptomes of embryonic and larval development in Drosophila. With these data, we identified known and previously undetected subregions in several tissues during development, and revealed known and potential gene regulatory networks of transcription factors within their topographic background. We further demonstrated that Stereo-seq data can be used for 3D reconstruction of Drosophila embryo spatial transcriptomes. Our data provides Drosophila research community with useful resources of spatiotemporally resolved transcriptomic information across developmental stages.

developmental biology↗

bioRxiv2020

Spatial multi-omic map of human myocardial infarction

Myocardial infarction is a leading cause of mortality. While advances in the acute treatment have been made, the late-stage mortality is still high, driven by an incomplete understanding of cardiac remodeling processes1,2. Here we used single-cell gene expression, chromatin accessibility and spatial transcriptomic profiling of different physiological zones and timepoints of human myocardial infarction and human control myocardium to generate an integrative high-resolution map of cardiac remodeling. This approach allowed us to increase spatial resolution of cell-type composition and provide spatially resolved insights into the cardiac transcriptome and epigenome with identification of distinct cellular zones of injury, repair and remodeling. We here identified and validated mechanisms of fibroblast to myofibroblast differentiation that drive cardiac fibrosis. Our study provides an integrative molecular map of human myocardial infarction and represents a reference to advance mechanistic and therapeutic studies of cardiac disease.

systems biology↗

bioRxiv2020

An Engineered Genetic Circuit for Lactose Intolerance Alleviation Coupled with Gut Microbiota Recovery

BackgroundLactose malabsorption occurs in around 68% of the world populations, causing lactose intolerance (LI) symptoms such as abdominal pain, bloating and diarrhoea. To alleviate LI, previous studies mainly focused on strengthening intestinal {beta}-galactosidase activity but neglected the inconspicuous colon pH drop caused by gut microbes fermentation on non-hydrolysed lactose. The colon pH drop will reduce intestinal {beta}-galactosidase activity and influence the intestinal homeostasis. ResultsHere, we synthesized a tri-stable-switch circuit equipped with high {beta}-galactosidase activity and pH rescue ability. This circuit can switch in functionality between expression of {beta}-galactosidase and expression of l-lactate dehydrogenase in respond to intestinal lactose signal and intestinal pH signal. We confirmed the circuit functionality was efficient using 12-hrs in vitro culture at a range of pH levels, as well as 6-hrs in vivo simulations in mice colon. Moreover, another 21-days mice trial indicated that this circuit can recover lactose-effected gut microbiota of mice to the status (enterotypes) similar to that of mice without lactose intake. ConclusionsTaken together, the tri-stable-switch circuit can serve as a promising prototype for LI symptoms relief, especially by flexibly adapting to environmental variation, stabilizing colon pH and restoring gut microbiota.

bioengineering↗

bioRxiv2020

Team flow is a unique brain state associated with enhanced information integration and neural synchrony

Team flow occurs when a group of people reaches high task engagement while sharing a common goal as in sports teams and music bands. While team flow is a superior enjoyable experience to individuals experiencing flow or regular socialization, the neural basis for such superiority is still unclear. Here, we addressed this question utilizing a music rhythm task and electroencephalogram hyper-scanning. Experimental manipulations held the motor task constant while disrupted the hedonic musical correspondence to blocking flow or occluded the partners body and task feedback to block social interaction. The manipulations effectiveness was confirmed using psychometric ratings and an objective measure for the depth of flow experience through the inhibition of the auditory-evoked potential to a task-irrelevant stimulus. Spectral power analysis revealed higher beta/gamma power specific to team flow at the left temporal cortex. Causal interaction analysis revealed that the left temporal cortex receives information from areas encoding individual flow or socialization. The left temporal cortex was also significantly involved in integrated information at both the intra- and inter-brains levels. Moreover, team flow resulted in enhanced global inter-brain integrated information and neural synchrony. Thus, our report presents neural evidence that team flow results in a distinct brain state and suggests a neurocognitive mechanism by which the brain creates this unique experience. Data AvailabilityAll data and analysis codes used in the preparation of this article are available at https://osf.io/3b4hp.

neuroscience↗