AbstractThe sinus node (SN) serves as the primary pacemaker of the heart and is the first component of the cardiac conduction system. Due to its anatomical properties and sample scarcity, the cellular composition of the human SN has been historically challenging to study. Here, we employed a novel deep learning deconvolution method, namely Bulk2space, to characterise the cellular heterogeneity of the human SN using existing single-cell datasets of non-human species.

摘要窦房结（SN）是心脏的主要起搏器，是心脏传导系统的第一个组成部分。由于其解剖学特性和样品稀缺性，人类SN的细胞组成在历史上一直具有挑战性。在这里，我们采用了一种新的深度学习反卷积方法，即Bulk2space，使用现有的非人类物种单细胞数据集来表征人类SN的细胞异质性。

As a proof of principle, we used Bulk2Space to profile the cells of the bulk human right atrium using publicly available mouse scRNA-Seq data as a reference. 18 human cell populations were identified, with cardiac myocytes being the most abundant. Each identified cell population correlated to its published experimental counterpart.

作为原理证明，我们使用公开可用的小鼠scRNA-Seq数据作为参考，使用Bulk2Space对人体右心房的细胞进行了分析。鉴定出18个人类细胞群，其中心肌细胞最为丰富。每个鉴定的细胞群与其公布的实验对应物相关。

Subsequently, we applied the deconvolution to the bulk transcriptome of the human SN and identified 11 cell populations, including a population of pacemaker cardiomyocytes expressing pacemaking ion channels (HCN1, HCN4, CACNA1D) and transcription factors (SHOX2 and TBX3). The connective tissue of the SN was characterised by adipocyte and fibroblast populations, as well as key immune cells.

随后，我们将解卷积应用于人类SN的大量转录组，并鉴定了11个细胞群，包括表达起搏离子通道（HCN1，HCN4，CACNA1D）和转录因子（SHOX2和TBX3）的起搏器心肌细胞群。SN的结缔组织以脂肪细胞和成纤维细胞群以及关键免疫细胞为特征。

Our work unravelled the unique single cell composition of the human SN by leveraging the power of a novel machine learning method..

我们的工作通过利用新型机器学习方法的强大功能，揭示了人类SN独特的单细胞组成。。

IntroductionThe cardiac conduction system orchestrates the electrical activity of the heart, with the sinus node (SN) located in the right atrium serving as the primary pacemaker1. The SN is a small, heterogenous and compartmentalized structure of the myocardium that initiates the action potential and controls the heart rate1,2,3.

引言心脏传导系统协调心脏的电活动，位于右心房的窦房结（SN）作为主要起搏器1。SN是心肌的一种小的，异质的和分隔的结构，它启动动作电位并控制心率1,2,3。

The joint effect of Ca2+ regulators and ion channels contribute to the pacemaking activity within the SN2,4.Single cell RNA sequencing (scRNA-Seq) has paved the way to unravel the cellular heterogenicity within the cardiac tissue5,6. The cellular landscape of the SN has been characterised across several mammalian species7, with mice being the most used animal model7,8.

Ca2+调节剂和离子通道的联合作用有助于SN2,4内的起搏活动。单细胞RNA测序（scRNA-Seq）为揭示心脏组织内的细胞异质性铺平了道路5,6。SN的细胞景观已在几种哺乳动物物种中得到表征7，小鼠是最常用的动物模型7,8。

It is now evident that the initiation and propagation of the electrical activity within the SN originates from a subpopulation of cardiomyocytes, which express key conduction genes and transcription factors7,8,9. Moreover, the abundant extracellular matrix found in the SN1 is thought to isolate the electrical activity of the pacemaking cardiomyocytes from their surrounding atrial cells10,11,12.

现在很明显，SN内电活动的起始和传播起源于心肌细胞亚群，其表达关键的传导基因和转录因子7,8,9。此外，在SN1中发现的丰富的细胞外基质被认为可以将起搏心肌细胞的电活动与其周围的心房细胞分离10,11,12。

The cellular heterogeneity of the SN includes fibroblasts, adipocytes and macrophages, residing in compartmentalised areas8,9. However, our knowledge of the cellular composition of the SN at single cell resolution is currently limited to animal models5,7,8,13, with only one study performed in humans9.Ongoing adoption of scRNA-Seq and other ‘omics methods is exponentially increasing the wealth of publicly available biological data.

SN的细胞异质性包括成纤维细胞，脂肪细胞和巨噬细胞，位于分隔区域8,9。然而，我们对单细胞分辨率下SN细胞组成的了解目前仅限于动物模型5,7,8,13，只有一项研究在人类中进行[9]。scRNA-Seq和其他组学方法的持续采用正在成倍增加可公开获得的生物数据的财富。

Concurrently, new computational tools are emerging as novel solutions to interrogate new and existing data using machine learning techniques14,15. Recently, a deep learning deconvolution algorithm, namely Bulk2Space16, was introduced as a powerful tool to resolv.

同时，新的计算工具正在成为使用机器学习技术查询新数据和现有数据的新解决方案14,15。最近，引入了一种深度学习反卷积算法，即Bulk2Space16，作为解析的强大工具。

Data availability

数据可用性

The human bulk RNA-Seq data of the right atrium and SN has been previously described20 and is available upon request. Deconvoluted count matrices of the human SN and RA can be accessed at: https://figshare.com/articles/dataset/Deconvoluted_scRNA-seq_datasets/25605297. The mouse scRNA-Seq data used as reference for the right atrium can be accessed at: https://cellxgene.cziscience.com/collections/0b9d8a04-bb9d-44da-aa27-705bb65b54eb.

。人类SN和RA的解卷积计数矩阵可以在以下位置访问：https://figshare.com/articles/dataset/Deconvoluted_scRNA-seq_datasets/25605297.用作右心房参考的小鼠scRNA-Seq数据可以在以下位置访问：https://cellxgene.cziscience.com/collections/0b9d8a04-bb9d-44da-aa27-705bb65b54eb.

The human scRNA-Seq data used as reference for the right atrium can be accessed at: https://figshare.com/articles/dataset/Tabula_Sapiens_release_1_0/14267219?file=34701976. The mouse snRNA-Seq data used as reference for the SN can be accessed from the Gene Expression Omnibus under the “GSE130710” accession code..

用作右心房参考的人类scRNA-Seq数据可以在以下位置访问：https://figshare.com/articles/dataset/Tabula_Sapiens_release_1_0/14267219?file=34701976.可以从“GSE130710”登录号下的Gene Expression Omnibus访问用作SN参考的小鼠snRNA-Seq数据。。

Code availability

代码可用性

All code used for this study can be found in the author’s Github page: https://github.com/AlexUOM/Sinus-node-deconvolution.

本研究使用的所有代码都可以在作者的Github页面中找到：https://github.com/AlexUOM/Sinus-node-deconvolution.

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Download referencesAcknowledgementsThis work was supported by a Leducq Foundation grant (TNE FANTASY 19CV03) awarded to HD and a British Heart Foundation Ph.D. Studentship Programme (FS/4yPhD/F/20/34131).Author informationAuthors and AffiliationsDivision of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, M13 9PL, UKAlexandru Chelu, Elizabeth J.

下载参考文献致谢这项工作得到了授予HD的Leducq基金会赠款（TNE FANTASY 19CV03）和英国心脏基金会博士生项目（FS/4yPhD/F/20/34131）的支持。作者信息作者和附属机构曼彻斯特大学生物、医学与健康学院心血管科学系，M13 9PL，UKAlexandru Chelu，Elizabeth J。

Cartwright & Halina DobrzynskiDepartment of Anatomy, Jagiellonian University Medical College, 31-008, Kraków, PolandHalina DobrzynskiAuthorsAlexandru CheluView author publicationsYou can also search for this author in.

Cartwright＆Halina DobrzynskidDepartment of Anatomy，Jagiellonian University Medical College，31-008，Kraków，PolandHalina DobrzynskiauthorsAlexandruCheluview author Publications你也可以在中搜索这位作者。

PubMed Google ScholarElizabeth J. CartwrightView author publicationsYou can also search for this author in

PubMed Google ScholarElizabeth J.CartwrightView作者出版物您也可以在

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PubMed Google ScholarContributionsHD conceived the study, provided the bulk RNA-Seq data, and supervised the project. AC conducted the experiments and wrote the manuscript. AC, EJC and HD critically reviewed the manuscript.Corresponding authorCorrespondence to

PubMed Google ScholarContributionsHD构思了这项研究，提供了大量RNA-Seq数据，并监督了该项目。AC进行了实验并撰写了手稿。AC，EJC和HD严格审查了手稿。对应作者对应

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Reprints and permissionsAbout this articleCite this articleChelu, A., Cartwright, E.J. & Dobrzynski, H. Empowering artificial intelligence in characterizing the human primary pacemaker of the heart at single cell resolution.

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Sci Rep 14, 14041 (2024). https://doi.org/10.1038/s41598-024-63542-6Download citationReceived: 14 May 2024Accepted: 29 May 2024Published: 18 June 2024DOI: https://doi.org/10.1038/s41598-024-63542-6Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard.

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