生物起搏器:从生物实验到计算机模拟

Biological pacemaker: from biological experiments to computational simulation 生物起搏器:从生物实验到计算机模拟 1 first-author 1 1 3 1 2 3 corresp ‡Corresponding Author ‡Corresponding Author †E-mail:h.zhang-3@manchester.ac.uk †E-mail:h.zhang-3@manchester.ac.uk h.zhang-3@manchester.ac.uk School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China School of Physics and Astronomy, The University of Manchester, Manchester, M13 9PL, UK School of Physics and Astronomy, The University of Manchester, Manchester, M13 9PL, UK Peng Cheng Laboratory, Shenzhen 518052, China Peng Cheng Laboratory, Shenzhen 518052, China Pacemaking dysfunction has become a significant disease that may contribute to heart rhythm disorders, syncope, and even death. Up to now, the best way to treat it is to implant electronic pacemakers. However, these have many disadvantages such as limited battery life, infection, and fixed pacing rate. There is an urgent need for a biological pacemaker (bio-pacemaker). This is expected to replace electronic devices because of its low risk of complications and the ability to respond to emotion. Here we survey the contemporary development of the bio-pacemaker by both experimental and computational approaches. The former mainly includes gene therapy and cell therapy, whilst the latter involves the use of multi-scale computer models of the heart, ranging from the single cell to the tissue slice. Up to now, a bio-pacemaker has been successfully applied in big mammals, but it still has a long way from clinical uses for the treatment of human heart diseases. It is hoped that the use of the computational model of a bio-pacemaker may accelerate this process. Finally, we propose potential research directions for generating a bio-pacemaker based on cardiac computational modeling. 起搏功能障碍已成为威胁人类健康的一种重大疾病,严重时可能导致心律失常、晕厥,甚至死亡.到目前为止,治疗起搏功能障碍的最佳方案是植入电子起搏器.但是它存在一些缺点,例如电池寿命有限,手术过程具有感染的风险,起搏频率单一等.因此,对生物起搏器的研究显得尤为迫切.生物起搏器不但引起并发症的风险较低,而且能够对生理情绪做出反应,从而有望替 代电子起搏器,进行心脏起搏障碍治疗.本文从生物实验和计算机模拟两方面对生物起搏器的发展进行综述.前者主要包括基因疗法和细胞疗法的实验成果,而后者介绍了多尺度的心脏建模从单个细胞到组织切片进行起搏器研究的进展.迄今为止,生物起搏器已被应用于大型哺乳动物实验,但将其应用于临床心脏病治疗,仍有很长的路要走.利用计算机模型对生物起搏器诱发过程进行建模,有望加速研究进程.在本文中,我们首先回顾了生物起搏器实验研究的发展,然后介绍了生物起搏器计算机模型的目前的相关工作.最后,我们提出了基于心脏计算机模型研究生物起搏器的潜在研究方向. Biological pacemaker Gene therapy Cell therapy Cardiac simulation Computational modeling 生物起搏器 基因治疗 细胞治疗 心脏模拟 计算机模型 Introduction 1 Cardiovascular disease has become a severe health problem all over the world. In China, cardiac diseases account for about 40% of total mortality (Chen et al., 2018 2018 ). Particularly, the pacemaking dysfunction, such as sick sinus syndrome and atrioventricular heart-block, is one of the most serious cardiac diseases, and may result in heart failure and even death. Currently, the electronic pacemaker is the only treatment for pacing dysfunction. Since the clinical use of the electronic pacemaker from 1958, it has saved more than three million lives all over the world. However, there are still several shortcomings of the device. For instance, the batteries and leads have limited lives and therefore need to be changed periodically; the device may suffer interference from electromagnetics which may obstruct the normal life of the patients; open-chest surgery during implanting a pacemaker may induce infection; an electronic pacemaker cannot response to emotion; the device must be changed with the growth of a pediatric patient (Cohen et al., 2005 2005 ; Rosen et al., 2011 2011 ). What is more, the long-term use of electronic pacemakers will increase the risk of heart failure (Freudenberger et al., 2005 2005 ). Therefore, a biological pacemaker (bio-pacemaker) was proposed as a substitute for the electrical pacemaker (Starzl et al., 1963 1963 ; Mayer et al., 1967 1967 ; Morishita et al., 1981 1981 ). A bio-pacemaker is potentially a new treatment for pacing dysfunction. It is developed to conquer the defects of electronic pacemakers, sustaining a robust pacing activity in the whole heart. Bio-pacemaker implementation can be performed by injecting pacemaker cells into the heart, which then initiates and controls the spontaneous rhythms in the whole heart. This approach avoids the risk of repeated surgery and the rhythm can respond to emotion (Shlapakova et al., 2010 2010 ). We compared the performances of electronic pacemakers and bio-pacemakers (Table 1 1 ). Actually, several biological experiments have provided some promising evidence for the practicability of the bio-pacemaker. Quiescent heart-muscle cells have been successfully converted into pacemaker cells using viral gene transfer (Miake et al., 2002 2002 ). Also, human embryonic stem cells (hESCs) have been successfully differentiated into cardiomyocytes (CMs) which have the ability to activate quiescent ventricular myocytes (VMs) (Xue et al., 2005 2005 ). Indeed, human embryonic stem-derived CMs were transplanted to the hearts of swine with complete atrioventricular block, and successfully drove the whole heart (Kehat et al., 2004 2004 ). These approaches provide an encouraging perspective on arrhythmia treatment. Pacemaker Extra power Fixed size Electromagnetic interference Transplant surgery Emotion response Risk of heart failure Electronic pacemaker Yes Yes Yes Yes No Yes Biological pacemaker No No No No Yes Maybe Theoretically, the construction of a bio-pacemaker is based on the differences in cellular electrophysiology between pacemaking sinoatrial node (SAN) cells and non-autorhythmic cardiac cells. SAN is the origin of intrinsic automaticity. The pacing ability of SAN cells results from a low expression of the inward rectifier potassium channel current ( I K1 ) and a high expression of hyperpolarization-activated channel current (funny current ( I f )) as compared with atrial myocytes (AMs) and VMs. I K1 is an outward current, repolarizing cellular action potential (AP) during the terminal phase of the AP. Thus, the low expression of I K1 could reduce the level of hyperpolarization and elevate the maximum diastolic potential, which makes depolarization easier. I f is generally regarded as the “pacemaker current,” playing a dominant role in initiating the diastolic depolarization and pacing activity (Ravagli et al., 2016 2016 ). In non-autorhythmic cells, I K1 is highly expressed (Miake et al., 2002 2002 ; Azene et al., 2005 2005 ; Cho et al., 2007 2007 ), but I f expression is low or even absent (Yu et al., 1993 1993 ). The high expression of I K1 and absence of I f jointly result in the loss of auto-rhythm in non-autorhythmic cells. In contrast, overexpressing I f and inhibiting I K1 in non-autorhythmic cells are possible approaches to turn non-autorhythmic cells into autorhythmic cells, creating a bio-pacemaker. At the high-dimensional level, the intercellular coupling between SAN cells and neighboring cells is weak, which helps to conduct the spontaneous electrical signal to the neighboring cells. When producing the bio-pacemaker at the two-dimensional or three-dimensional level, reducing the intercellular coupling should be taken into consideration. After over five decades’ studies of bio-pacemaker, there has been considerable progress. However, limitations such as funding and moral issues are limiting experimental research. Thus, the computational simulation of a bio-pacemaker based on the cardiac computational model is a necessity. In this review, we first introduce the progress in the development of a bio-pacemaker aiming for gene therapy and cell therapy. Then, we summarize current progress of autologous therapy and highlight the obstacles in producing a bio-pacemaker. Finally, we propose possible future trends in bio-pacemaker research—computational simulation. This review provides a systematic view on generating a bio-pacemaker from biological experiment to computational simulation. This may be helpful for the better design of a future generation of stable and robust bio-pacemakers. Biological experiments for producing biological pacemakers 1 In the heart, there are three aspects to causing auto-rhythmicity: trigger cells with spontaneous beats, substrate cells with the function of delivering signal, and trigger–substrate connection (Rosen et al., 2011 2011 ). In the cases of SAN cell failure, a possible treatment could be inducing rhythm in other positions, such as AMs or VMs, and making them take over the function of SAN. To realize this scenario, first, autonomic pacemaker cells should be developed. Generally, some methods have been used to create pacemaker cells: expressing a specific gene which controls pacemaking-related ionic channels by cell fusion (called gene therapy), and differentiating ESCs into pacemaker cells (called cell therapy) (Munshi and Olson, 2014 2014 ; Rosen, 2014 2014 ). Cell therapy is always accompanied by gene therapy so that cardiac myocytes transformed from stem cells could produce a pacemaking function, which is called hybrid therapy. The experiments by hybrid therapy are described in the section of “Cell therapy.” Then, a certain amount of pacemaker cells should be injected into specific locations of the heart in vivo to induce heartbeats. The number and location of pacemaker cells should ensure the ability and stability of pacing activity. Gene therapy 2 Up to now, bio-pacemaker gene therapy usually controls the expression of hyperpolarization-activated cyclic nucleotide-gated ( HCN ) gene family (Santoro and Tibbs, 1999 1999 ), Kir2.1 and Kir2.2 genes (Zaritsky et al., 2001 2001 ), and transcription factor T-box 18 ( TBX18 ) (Kapoor et al., 2013 2013 ). The AP characteristics and I f density of bio-pacemaker cells created by gene therapy are shown in Table 2 2 . HCN : hyperpolarization-activated cyclic nucleotide-gated; HCN1 / 2 : HCN channel 1/2; SkM1 : skeletal muscle sodium channel 1; TBX18 : transcription factor T-box 18; VMs: ventricular myocytes; CL: cycle length; APD 50 : action potential duration at 50% repolarization; APD 90 : action potential duration at 90% repolarization; MDP: maximum diastolic potential; V 1/2 : average half-maximal activation voltage of funny current’s activation gate; I f : funny current; pA/pF: unit of current density, (10 −12 A)/(10 −12 F). No auto-rhythm was observed; Data are expressed as mean±standard error of the mean (SEM) Reference Gene type Subject CL (ms) APD 50 (ms) APD 90 (ms) MDP (mV) V 1/2 (mV) I f density at −70 mV (pA/pF) Qu et al., 2003 2003 HCN2 Canine left atrium −94.00 −3.2 Plotnikov et al., 2004 2004 HCN2 Canine left bundle-branch 340 100 180 −74.7 −31.0 Qu et al., 2001 2001 HCN2 Neonatal rat VMs 681 170 255 −42.5±1.6 # # ( n =11) −78.00 −41.3 Boink et al., 2013 2013 HCN2 / SkM1 Canine left bundle-branch 625 195±5 # # ( n =6) 213±5 # # ( n =6) −85.0±2.0 # # ( n =6) Valiunas et al., 2009 2009 Mouse HCN2 Canine VMs 648 266 479 −66.0 Cho et al., 2007 2007 HCN1 Guinea pig VMs 279 113 155 −70.0 −12.5 Miake et al., 2002 2002 Kir2.1 -AAA Guinea pig VMs 598 230 295 −63.0 Zaritsky et al., 2001 2001 Kir2.1 −/− Neonatal mouse VMs Non * * −11.7±1.2 # # ( n =8) 2 Kapoor et al., 2013 2013 2 TBX18 Neonatal rat VMs 631 242 320 −47.0±10.0 # # ( n =6) −3.46 −8.0 Guinea pig VMs 443 137 189 −55.8±6.0 # # ( n =5) Hu et al., 2014 2014 TBX18 Porcine VMs 730 Bakker et al., 2012 2012 TBX3 Neonatal rat VMs 580 HCN gene family controls the expression of I f . Overexpressing the HCN gene into non-autorhythmic cells could promote the expression of I f in these cells, promoting depolarization during the diastolic interval, hence inducing spontaneous beats. In the mammalian heart, injecting HCN channel 2 ( HCN2 ) into the canine left atrium (LA) (Qu et al., 2003 2003 ) and the left bundle-branch (LBB) (Plotnikov et al., 2004 2004 ) via adenoviral constructs has successfully produced escape beats. That experiment also indicated that the LBB was a preferable location when creating pacemaker cells because it was proximal to the ventricular conducting system and easy to conduct the electrical signal into the ventricle (Plotnikov et al., 2004 2004 ). As for rodent animals, highly expressing HCN2 in neonatal rat VMs caused spontaneous beats. However, in adult rat VMs, it did not work, because the I K1 density was higher in adult rat VMs than in neonatal rat cells (Qu et al., 2001 2001 ), which inhibited the depolarization. In addition to single gene expression, a dual gene therapy, which co-expressed skeletal muscle sodium channel 1 ( SkM1 ) with HCN2 in the canine left bundle branch, showed a more efficient pacemaking activity than single gene expression. SkM1 could maximize the opening of a sodium current channel, which led to a quick depolarization and a more positive AP (Boink et al., 2013 2013 ). This is the first report that cardiac auto-rhythms were induced by bio-pacemaker in large animals. An experiment in a two-cell system verified that an HCN2 -expressing cell could propagate spontaneous electrical signals to a quiescent VM cell (Valiunas et al., 2009 2009 ). This provides evidence for the possibility of creating a bio-pacemaker by overexpressing HCN2 . HCN1 was also used to induce spontaneous rhythms. Spontaneous oscillations could be initiated in guinea pig VMs fused with HCN1 -expressing fibroblasts under inhibition of I K1 (Cho et al., 2007 2007 ). HCN1 currents needed a long period (approximately 3000 ms) to reach equilibrium (Azene et al., 2005 2005 ), but the pacing cycle is only 250 ms in guinea pigs and 1000 ms in humans, which would be a potential problem for the stability of HCN1 -induced bio-pacemaker cells. Also, some experiments indicated that acute expression of HCN gene suppresses cardiac automaticity (Azene et al., 2005 2005 ; Cho et al., 2007 2007 ; Lieu et al., 2008 2008 ; Sun et al., 2017 2017 ) and the expression of the HCN gene in VMs may raise the risk of arrhythmicity (Kuwabara et al., 2013 2013 ). Thus, the stability and robustness of HCN gene therapy need to be proved. Kir2.1 and Kir2.2 encode I K1 in many cell types, including CMs. Knocking out the Kir2.1 and Kir2.2 could depress I K1 and initiate spontaneous beats in isolated CMs. Removing Kir2.1 and Kir2.2 in newborn murine VMs could elevate the resting potential and promote spontaneous rhythms (Zaritsky et al., 2001 2001 ). Replacing three amino-acid residues in the pore structure of Kir2.1 produced a dominant negative construct called Kir2.1 -AAA, which could inhibit I K1 . Miake et al. ( 2002 2002 ) transduced Kir2.1 -AAA in the left ventricular cavity of guinea-pigs, discovering that destroying Kir2.1 caused an 80% decline of I K1 . They first verified that infecting Kir2.1 -AAA in VMs produced more rapid beats than native pacing activity. After this study, they analyzed the role of I K1 in the excitability of VM via adenoviral gene transfection (Miake et al., 2003 2003 ). They reported that Kir2.1 -AAA caused a 50%–90% decline of I K1 and only a greater than 80% suppression of I K1 resulted in pacemaking activity, contributing to a longer AP duration, a slow phase 3 repolarization, and a more positive resting membrane potential. This experiment provided a possible direction for pacemaker creation. However, an unfavorable finding was that decreased I K1 caused a long-QT phenotype and produced arrhythmia (Miake et al., 2003 2003 ). Also, Kir2.1 -knockout was readily reported to cause death in the adult animals, so that the experimental subjects were limited to the newborn animals (Zaritsky et al., 2001 2001 ; Miake et al., 2003 2003 ). As a result, developing a pacemaker by I K1 -knocking-out seems not to be an excellent approach. Sun et al. ( 2017 2017 ) showed that neither I f overexpression nor I K1 suppression alone could initiate automaticity rhythm in CMs. As a result, the gene that codes I K1 and I f at the same time may be a promising candidate of bio-pacemaker gene therapy. The embryonic transcription factor TBX18 has effects on the expression of several pacemaking-related genes such as the HCN gene family and Cx43 gene family as well as encodes the activation of I K1 (Choudhury et al., 2018 2018 ). Cx43 encodes electrical propagation between cells and downregulating intercellular coupling facilitates the transmission of automatic rhythms between cardiac cells. All these facts imply that TBX18 has tremendous potential for producing a bio-pacemaker. In rodent animals, VMs, which were infected with TBX18 via adenoviral vectors, showed pacemaker cell morphology and appropriate autonomic responses in the induced SAN (iSAN) (Kapoor et al., 2013 2013 ). The expression of TBX18 caused a 78% reduction in the density of I K1 , a 1.4-fold increase in the HCN4 expression level as well as the downregulation of Cx43 , which produced a reduction of coupling between cells (Kapoor et al., 2013 2013 ). These factors caused the auto-rhythmicity jointly. Experiment in large animals exhibited similar results. Hu et al. ( 2014 2014 ) created iSAN cells in porcine VMs by reprogramming TBX18 , which was the second report of a bio-pacemaker created in the large animals. Indeed, the injected site showed a downregulated Kir2.1 , a promoted HCN4 , and a sparse Cx43 , which had the result that the iSAN cells had the ability to support both heart rate and physical activity. Although this was just a transient bio-pacemaker, an excellent result was that TBX18 expression did not increase the risk of arrhythmia. Apart from TBX18 , TBX3 could also reduce I K1 and intercellular coupling in the mice atrium (Bakker et al., 2012 2012 ). In the rat right atrium, overexpressing TBX3 caused upregulation of HCN1 , HCN2 , and RYR2 , but downregulation of HCN4 was witnessed (Bakker et al., 2012 2012 ). There was no evidence that overexpressing TBX3 could create a bio-pacemaker. Cell therapy 2 Generally, four kinds of cells were used to differentiate into bio-pacemakers: ESCs, bone marrow stem cells (BMSCs), adipose-derived stem cells (ADSCs) and induced pluripotent stem cells (iPSCs). Other types of cells were also deemed as candidates in cell therapy, such as SAN (Zhang et al., 2008 2008 ) and CM progenitor cells (Végh et al., 2019 2019 ). To create preferable autonomic pacing CMs, pacing-related genes are usually expressed into induced CMs. This is a hybrid therapy. In this paper, we consider hybrid therapy as a kind of cell therapy, which is introduced in this section. The cycle length (CL) and I f density of bio-pacemaker cells created by cell therapy as well as the CL of co-cultured cells are presented in Table 3 3 . ESCs: embryonic stem cells; MSCs: mesenchymal stem cells; BMSCs: bone marrow stem cells; ADSCs: adipose-derived stem cells; CMs: cardiac myocytes; iPSCs: induced pluripotent stem cells; HCN : hyperpolarization-activated cyclic nucleotide-gated; HCN1 / 2 / 4 : HCN channel 1/2/4; TBX18 : transcription factor T-box 18; CL: cycle length; I f : funny current; pA/pF: unit of current density, (10 −12 A)/(10 −12 F); VMs: ventricular myocytes. CL of pacemaker cell; CL of co-cultured cell. No auto-rhythm was observed on that occasion; Data are expressed as mean±standard error of the mean (SEM) Reference Cell type Gene type CL 1 1 (ms) I f density at −70 mV (pA/pF) Co-cultured subject CL 2 2 (ms) Kehat et al., 2004 2004 Human ESCs 1351 2 Xue et al., 2005 2005 2 Human ESCs 2 Neonatal rat VMs 1224 Adult guinea pig heart 740 Saito et al., 2015 2015 Mouse ESCs HCN4 724 Ionta et al., 2015 2015 Mouse ESCs Shox2 192 −1.80 Rat heart with complete heart block 1416 2 Potapova et al., 2004 2004 2 Human MSCs 2 Mouse HCN2 2 −7.90 Canine VMs 983 Neonatal rat VMs 372 Plotnikov et al., 2007 2007 Human MSCs Mouse HCN2 −7.12 Canine heart 1153 Bruzauskaite et al., 2016 2016 Human BMSCs Mouse HCN2 Non * * −3.15 Zhou et al., 2007 2007 Rabbit BMSCs Human HCN2 Cardiac myocytes 402 Zhou et al., 2013 2013 Rabbit MSCs Human HCN1 Neonatal rabbit VMs 465 Zhang et al., 2013 2013 Porcine BMSCs Human HCN4 −1.26 Porcine VMs 1224 Planat-Benard et al., 2004 2004 Mouse ADSCs 909 Yang et al., 2016 2016 ADSCs TBX18 Non * * −5.30 Neonatal rat VMs 800 Chen et al., 2017 2017 ADSCs TBX18 181 Ruhparwar et al., 2002 2002 Fetal atrial CMs Canine left VMs 710±30 # # ( n =2) Zhang et al., 2011 2011 Sino atrial nodes Canine right ventricle 1200 Chauveau et al., 2017 2017 Human iPSCs 435 −24.50 Canine VMs 1395 Kehat et al. ( 2001 2001 ) reported that hESCs could differentiate into CMs. Then, they verified that rat CMs derived from hESCs could generate embryonic-like AP and pacing activity. They first demonstrated that hESCs-induced CMs (hESC-CMs) could successfully create electromechanical integration and drive the heart in the pig with complete atrioventricular block (Kehat et al., 2004 2004 ). Then, researchers began focusing on the pacing function of CMs differentiated from ESCs. In vivo, under atrioventricular nodal cryoablation condition, the hESC-CMs-injected adult guinea pig heart presented induced automaticity, and no evidence showed that hESC-CMs led to tumor or arrhythmias (Xue et al., 2005 2005 ). To enhance the ability of pacing, pacing-related genes were injected into the ESCs in hybrid therapy. Overexpressing HCN4 in mouse ESCs (mESCs) generated considerably larger I f currents, and hence a faster spontaneous rate of (87.4±11.9) beats/min (bpm) than the control (Saito et al., 2015 2015 ). Actually, in human iPSCs (hiPSCs) co-cultured with HCN4 -overexpressing mESC-CMs, there was a higher beating rate at (82.8±4.8) bpm than that in the control condition (hiPSCs co-cultured with enhanced green fluorescent protein with a beating rate of (55.2±13.8) bpm) (Saito et al., 2015 2015 ). It meant that overexpressing HCN4 promoted the pacing ability of mESC-CMs in co-culture system with other excitable cells in vitro. Shox2 is a homeodomain transcription factor that controls the development and function of the native cardiac pacemaker, specifically expressing in the SAN but not in the atrium or ventricle. In the single cell, expressing Shox2 caused a lager I f , a shorter AP duration, and a faster spontaneous pacing rate (Ionta et al., 2015 2015 ). In vitro, under the overexpression of Shox2 , the proportion of mESCs with spontaneous beats increased and its beating rate was considerably faster than that under the control condition (Ionta et al., 2015 2015 ). Meanwhile, in vivo, injecting Shox2 -mESCs into the left ventricular apex of the rat heart contributed to a higher rate (at (44±3) bpm) than the control (Ionta et al., 2015 2015 ). After that, this team established an ESC-based cardiac differentiation model using Shox2 as a molecular tool (Hoffmann et al., 2017 2017 ), which provides a fundamental basis for the investigation of molecular pathways. These studies indicate that ESCs have great potential to differentiate into sinoatrial-like cells. Compared with ESCs, mesenchymal stem cells (MSCs) are easier to achieve and culture. Some experiments verified that implanting MSCs loaded with the pacemaker gene in the myocardium could induce pacemaker function. For instance, the expression of mouse HCN2 ( mHCN2 ) in human MSCs (hMSCs) could create I f -like current and initiate spontaneous rates in rat VMs at (93±16) bpm (Potapova et al., 2004 2004 ). mHCN2 -induced hMSCs could also generate electrical coupling in canine VMs and drive the canine heart with idioventricular rates at (61±5) bpm during sinus arrest (Potapova et al., 2004 2004 ). This team also investigated the influence of the size and location of mHCN2 -hMSCs on the pacing function, concluding that injecting 70 000 hMSCs into the conducting system could drive the ventricle (Plotnikov et al., 2007 2007 ). The MSCs are usually extracted from bone marrow and adipose tissues; these are called BMSCs and ADSCs, respectively. Both BMSCs (Zhou et al., 2007 2007 , 2013 2013 ; Huang et al., 2010 2010 , 2012 2012 ; Zhang et al., 2013 2013 ; Bruzauskaite et al., 2016 2016 ) and ADSCs (Rangappa et al., 2003 2003 ; Planat-Benard et al., 2004 2004 ; Choi et al., 2010 2010 ; Yang J et al., 2012 2012 ; Zhao et al., 2012 2012 ; Yang M et al., 2016 2016 ; Chen et al., 2017 2017 ) show the ability to differentiate into CMs. This provides another option for creating a bio-pacemaker by cell therapy. Experiments showed that fluid shear stress (Huang et al., 2010 2010 ) and cyclic strain (Huang et al., 2012 2012 ) could transdifferentiate BMSCs into CMs. Except for physiotherapy, BMSCs are ideal candidates in hybrid therapy. Transfecting human HCN2 ( hHCN2 ) into rabbit BMSCs could express I f current (Zhou et al., 2007 2007 ). Rabbit CMs co-cultured with hHCN2 -transfected MSCs showed spontaneous beats at (149±14) bpm, which was significantly higher than the control at (87±11) bpm (Zhou et al., 2007 2007 ). High cell viability and spontaneous beating activity were witnessed in mHCN2 -transfected hMSCs, but the proliferative activity was somewhat low (Bruzauskaite et al., 2016 2016 ). In terms of other kinds of HCN gene, injecting HCN1 into BMSCs can initiate spontaneous automaticity in co-cultured neonatal rabbit VMs (Zhou et al., 2013 2013 ). Also, HCN4 -expressed BMSCs can drive the porcine ventricle (Zhang et al., 2013 2013 ). In addition, infecting TBX18 into rat BMSCs can make them differentiate into a phenotypic and functional pacemaker. More specifically, the TBX18 -BMSCs expressed structural proteins—α-actin, Ca 2+ dynamic proteins—cTnI, HCN4 gene and repressed Cx43 (Li et al., 2018 2018 ). The vector used to transform the pacemaking-related gene is also a vital factor in long-term gene expression. Adenovirus is the most frequently used vector in gene transfection, but the gene expression by adenovirus vector showed a decline in one month (Zhang et al., 2013 2013 ) and the adenovirus vector easily induced an immune reaction (Li et al., 2018 2018 ). To create a durable pacemaker, lentiviral vector (LentiV) was used to transfect hHCN2 into rabbit BMSCs because of its function of generating persistent transgene expression. Indeed, the rabbit CMs co-cultured with LentiV-transfected MSCs produced a persistent gene expression (Zhou et al., 2007 2007 ). Compared with BMSCs, ADSCs appear to be a superior source to be used to differentiate into a sinus node-like cell, because the sample is available, easy to culture and reproduce. Also, ADSCs present more attractive pacing properties than BMSCs, such as a superior ability to differentiate into CMs as well as readily expressing the HCN gene (Yang et al., 2012 2012 ). In the rat, 5-azacytidine (5-aza) chemical treatment can cause spontaneous beats in rabbit ADSCs at three weeks’ culture (Rangappa et al., 2003 2003 ). Also, adult mouse ADSCs can be induced into pacemaker cells with CM-like morphology and AP with a pacing rate of 66 bpm (Planat-Benard et al., 2004 2004 ). However, 5-aza could not differentiate human ADSCs into pacemaker cells (Choi et al., 2010 2010 ). Except for chemical substances like 5-aza, some genes could also influence the differentiation of ADSCs into CMs. For example, the TBX18 gene is helpful in differentiating ADSCs into a pacemaker-like cell. An experiment indicated that silencing TBX18 inhibited the expression of TBX3 and Shox2 , and terminated the differentiation of ADSCs into a pacemaker phenotype (Chen et al., 2017 2017 ). Not surprisingly, expressing TBX18 into ADSCs promoted the expression of HCN4 and hence increased the expression of I f (Yang et al., 2016 2016 ). TBX18 -ADSC showed a similar morphology to pacemaker cells (Zhang and Huang, 2019 2019 ). The neonatal rat VMs co-cultured with TBX18 -transfected ADSCs presented autonomous synchronized beatings (Yang et al., 2016 2016 ). Nkx2.5 is an essential transcription factor that regulates CM differentiation. It has been used to affect the differentiation of ADSCs into a pacemaker, although the results were not satisfactory. In mouse ADSCs, the overexpression of Nkx2.5 and cardiac α-actin can increase the expression of cardiac-related proteins but inhibit beating function (Zhao et al., 2012 2012 ). Dramatically, an experiment successfully differentiated ADSCs into beating CMs by direct cell–cell interaction with rat CMs (Choi et al., 2010 2010 ), but the reason for this is not clear. Although further experiments are required to ensure the safety of ADSCs-induced bio-pacemakers, the work provides a new research direction for clinical bio-pacemakers. Another candidate for creating CMs is iPSC. Human iPSCs can be generated from various types of somatic cells, particularly fibroblasts (Novak et al., 2010 2010 ; Chauveau et al., 2017 2017 ) and can be induced into CMs by the LentiV (Novak et al., 2010 2010 ) and chemical means (Burridge et al., 2014 2014 ). Zhang et al. ( 2009 2009 ) indicated that hiPSC could differentiate into nodal, atrial, and ventricular phenotypes. iPSC from human hair follicle keratinocytes also had potential to differentiate into functional CMs and this kind of iPSC-CMs showed intracellular calcium concentration ([Ca 2+ ] i ) transient and contraction amplitudes under the action of β-adrenergic (Novak et al., 2010 2010 ). In addition, iPSC from human foreskin fibroblast presented [Ca 2+ ] i handling and excitation–contraction coupling (Germanguz et al., 2011 2011 ). Moreover, the iPSC-CMs can respond to ivabradine and iPSC-CMs-injected canine heart can display rhythms with the infusion of epinephrine (Chauveau et al., 2017 2017 ). These experiments suggest the possibility of creating a biological pacemaker cell based on iPSC. Based on these facts, it is hoped that the iPSC-CM can produce automaticity. Gorabi et al. ( 2019b 2019b ) used a hybrid therapy to produce a pacemaker cell based on iPSC. They successfully transfected TBX18 into hiPSC-CMs by a LentiV and TBX18 -hiPSC-CMs appeared to present more pacemaker-like traits than the control (8% vs. 2%). A further study, which transferred TBX18 lentiviruses or TBX18 -hiPSC-pacemakers into the rat ventricle, indicated that the function of TBX18 -transduced VMs (cell therapy) was better than that of TBX18 -hiPSC-pacemakers (hybrid therapy) on some measures, such as heart rate (Gorabi et al., 2019a 2019a ). The TBX18- hiPSC-pacemaker injection seemed to be a safer therapy because the coupling between pacemaker cells and native myocytes could be controlled and optimized. Autologous therapy 2 Up to now, most bio-pacemaker experiments are xenograft, which has the risk of delayed rejection and ethical issues. Also the function of pacemakers may be damaged by their low durability (Gorabi et al., 2019a 2019a ). Zhang et al. ( 2013 2013 ) showed that autograft HCN4 -transferred porcine BMSCs could create a pacemaking function in the porcine heart with complete heart blocks. Moreover, 5-aza chemical treatment is potentially an autologous therapy for a bio-pacemaker (Rangappa et al., 2003 2003 ). In addition, human somatic cells such as hair follicle keratinocytes or skin cells have been verified to be reprogrammed to iPSC and differentiated into CMs (Zhang et al., 2009 2009 ), and this provides a possible approach for creating an autograft human pacemaker. Apart from autograft stem cell therapy and chemical treatment, autologous-SAN-injection is also a hopeful therapy for a bio-pacemaker. Fetal canine atrial CMs were implanted into the adult canine left ventricle, and an escape rhythm was observed in the site where the atrial CMs were injected (Ruhparwar et al., 2002 2002 ). Zhang et al. ( 2008 2008 ) showed that injecting autologous SAN cells in the canine right ventricle could create spontaneous beats with a rate of approximately 50 bpm. However, its biological pacing properties are distinct from native SAN. This may relate to the difference of substrate (Zhang et al., 2011 2011 ). The mortality of the SAN cells in the injected site is somewhat high, and stable pacing is difficult to ensure. Therefore, the dose of SAN cells for injection is a research interest for the future. It is hoped that these approaches will eliminate the immunosuppression of the xenograft. Obstacles to producing biological pacemakers 2 Research on creating a bio-pacemaker by gene and cell therapies has provided many useful results. However, biological experiments have to overcome several obstacles in producing a bio-pacemaker. For instance, it is not easy to explain the synchronous mechanism of bio-pacemaker by biological experiment. The molecular mechanisms of how a bio-pacemaker works in healthy and diseased conditions are barely understood. In addition, experiments are limited by errors caused by experimental condition and by species difference. The current–voltage ( I – V ) curves of I f in different bio-pacemaker experiments are shown in Fig. 1 1 . The current density shows a great difference because it is not easy to control in experiments. In addition, considering the great effects of the location and size of bio-pacemaker cells on the cardiac electrical and mechanical dynamics, pacemaker cells should be injected into a certain position and in a certain pattern, which is not easy to accurately control. Also, culturing materials and subjects needs a lot of time and expenditure. Last but not least, biological experiments have ethical and moral issues, such as with the xenograft (Zhang et al., 2008 2008 ). All these shortcomings prompt us to build a computational model of a bio-pacemaker to simulate the process and results of bio-experiments. This is a more feasible approach for studying the bio-pacemaker mechanism. I – V : current–voltage; I f : funny current; pA/pF: unit of current density, (10 −12 A)/(10 −12 F) Computational simulations of biological pacemaker 1 Although there have been plenty of experiments on the bio-pacemaker, up to now, few bio-pacemaker computational models have been published. To build a bio-pacemaker computational model, first, an appropriate chamber of the heart should be chosen as the initiation of heartbeats. It has been verified that VMs can be induced as pacemaker cells via adenoviral gene transfection (Hu et al., 2014 2014 ), which makes VMs a candidate for a pacemaking origin. A series of simulations have been done to examine the effect of different ion currents on the ventricular automaticity. Kurata et al. ( 2005 2005 ) elucidated the roles of individual ionic currents in pacemaking by bifurcation analyses based on the first human VM model (PB model (Priebe and Beuckelmann, 1998 1998 )). They claimed that L-type calcium current ( I CaL ) is responsible for equilibrium point instability, whereas the deactivation of Na + /Ca 2+ exchanger current ( I NaCa ) and rapid delayed rectifier current ( I Kr ) contributes to phase 4 depolarization. Another simulation (Zhang et al., 2014 2014 ) demonstrated that I CaL and I NaCa play a positive role in the initiation of automatic depolarization, while I Kr and Na + /K + pump current ( I NaK ) have a contrary effect. Although these ion channels show a degree of influence on cardiac pacing, I K1 , I f , and cell coupling are still the crucial factors that induce automatic depolarization. Inhibiting I K1 , overexpressing I f , and downregulating the diffusion constant are the main approaches to causing automatic activity in the VM single cell and tissue model. There has been some research on the role of I K1 in induced pacing. For example, Silva and Rudy ( 2003 2003 ) clarified the mechanism of pacing activity in I K1 -downregulated VMs by adjusting conductance of I K1 ( G K1 ) in a guinea pig VM model (Luo-Rudy model (Luo and Rudy, 1991 1991 )). They verified that it was I NaCa that carried the pacemaking current, and this process depended on the oscillation of [Ca 2+ ] i . Then, Tong and Holden ( 2005 2005 ) used a continuation algorithm to analyze the stability of induced pacemaker activity by downregulating G K1 in a human VM model (TP04 model (ten Tusscher et al., 2004 2004 )) and found that the stable periodic oscillations appeared when G K1 was 0.02–0.05 times the value of original G K1 . Based on the result of the single cell model, the number of bio-pacemaker cells, which are needed for successful pacing, was investigated in a two-dimensional (2D) model. The result was that adjacent VMs suppressed the depolarization of automatic cells. Therefore, Purkinje fiber was added as a medium for propagating electric excitation from pacemakers to VMs. In this model, only 500 automatic cells were needed to drive the tissue slice (Zhang et al., 2016 2016 ). As for cell coupling, biological experiments showed that overexpressing TBX18 in the rat (Cho et al., 2007 2007 ) and the pig (Azene et al., 2005 2005 ) VMs could downregulate Cx43 , and then diminish intercellular coupling, thus inducing auto-rhythms in VMs. A simulation verified that decreasing coupling conductance could increase ventricular pacing activity (Zhang et al., 2015 2015 ), which was consistent with the experimental result. According to the experiment by Qu et al. ( 2001 2001 ), increasing the density of I f is helpful to enhance the CL and give rise to pacemaker activity. It is hoped that computational simulation will reveal the effect of I f on pacing activity in a non-autorhythmic CM model. In addition, an experiment has preliminarily explored the synergetic actions of I K1 and I f . A simulation (Sun et al., 2017 2017 ) showed that it was the ratio of I K1 and I f that regulated the frequency of rhythmic oscillation. However, this model included I K1 and I f only, which was not a whole CM model. Computational study based on CM model provides a fundamental basis for the investigation of molecular pathways for creating a bio-pacemaker under physiological conditions. Some publications (Azene et al., 2005 2005 ; Sun et al., 2017 2017 ) have combined the biological experiments and computational approaches, setting an example for guiding biological research by computational simulation. The conclusions of simulation could be verified by biological experiments, i.e., establishing the feasibility of model forecasts. The computational approach will be a trend for bio-pacemaker research. Conclusions 1 The bio-pacemaker is an attractive therapy for cardiac rhythm disturbances. Because of its biological properties, it has shown many advantages over electrical pacemakers. For example, the bio-pacemaker needs no open-chest surgery, and this could reduce the risk of complications. Also, the pacing frequency of a bio-pacemaker can respond to emotion rather than remaining a fixed rhythm. However, some problems still need to be solved, such as the approaches of producing pacemaker cells, the magnitude of pacing cells, as well as the location for injection of the pacing cells. Fortunately, the computational model could be used to simulate the production of pacemaker cells and its effect on the cardiac pacemaking activity. 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JCYJ20151029173639477 and JSGG20160229125049615), and the China Postdoctoral Science Foundation (No. 2015M581448) 2019-11-05 2020-03-11 2022-01-05 Copyright © Zhejiang University and Springer-Verlag GmbH Germany, part of Springer Nature 2020 2020 Journal of Zhejiang University-SCIENCE B (Biomedicine and Biotechnology) 07 21