波谱学杂志, 2024, 41(4): 373-381 doi: 10.11938/cjmr20243105

研究论文

基于核自旋单重态的活体谷胱甘肽分子MRS信号选择

朱向炜, 杨雪, 魏达秀,*, 姚叶锋,#

上海市磁共振重点实验室,华东师范大学 物理与电子科学学院,上海 200062

In Vivo Glutathione Molecular MRS Signal Selection Based on Nuclear Spin Singlet States

ZHU Xiangwei, YANG Xue, WEI Daxiu,*, YAO Yefeng,#

Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronic Science, East China Normal University, Shanghai 200062, China

通讯作者: * Tel: 021-62233281, E-mail:dxwei@phy.ecnu.edu.cn;# Tel: 021-62234328, E-mail:yfyao@phy.ecnu.edu.cn.

收稿日期: 2024-03-26   网络出版日期: 2024-04-28

基金资助: 上海市科委“科技创新行动计划”(22142200800)

Corresponding authors: * Tel: 021-62233281, E-mail:dxwei@phy.ecnu.edu.cn;# Tel: 021-62234328, E-mail:yfyao@phy.ecnu.edu.cn.

Received: 2024-03-26   Online: 2024-04-28

摘要

谷胱甘肽(GSH)是一种由谷氨酸、半胱氨酸和甘氨酸聚合而成的三肽,是人体还原驱动力的主要来源,能维持人体内部氧化还原平衡.谷胱甘肽还与生物体内自由基淬灭、肿瘤治疗密切相关.利用活体磁共振波谱(MRS)监测生物体中谷胱甘肽的含量变化对于理解其生物学作用具有重要意义.由于生物体内环境复杂,活体组织的磁共振信号往往重叠严重,难以实现特定分子的选择性检测及定量.本文介绍了一种利用核自旋单重态选择性检测活体谷胱甘肽分子的方法,通过在谷胱甘肽中选择合适的自旋体系,将其制备为单重态,借助梯度脉冲消除其它分子的信号,进而实现谷胱甘肽信号的选择性检测.该方法在健康人体大脑中得到了实验验证,理论和实验结果表明,与文献中报道的其它方法相比,本文的方法具有检测效率高、选择性强的特点.

关键词: 磁共振波谱; 谷胱甘肽; 分子靶向信号检测; 核自旋单重态; 优化控制脉冲

Abstract

Glutathione (GSH), a tripeptide derived from glutamic acid, cysteine, and glycine, as a vital source of reducing power in the body, is crucial for maintaining redox balance and combating free radicals. Its role in tumor therapy is also significant. Monitoring GSH levels in vivo using magnetic resonance spectroscopy (MRS) is essential for understanding its biological functions. However, due to complex biological environments, overlapping problem of MRS signals is often serious, which makes selective detection and accurate quantification challenging. This paper introduces a method to selectively detect GSH in vivo by using nuclear spin singlet states. Compared to other methods in literatures, our method offers high efficiency and strong selectivity.

Keywords: MRS; glutathione; molecular targeted signal selection; nuclear spin singlet state; optimal control pulse

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本文引用格式

朱向炜, 杨雪, 魏达秀, 姚叶锋. 基于核自旋单重态的活体谷胱甘肽分子MRS信号选择[J]. 波谱学杂志, 2024, 41(4): 373-381 doi:10.11938/cjmr20243105

ZHU Xiangwei, YANG Xue, WEI Daxiu, YAO Yefeng. In Vivo Glutathione Molecular MRS Signal Selection Based on Nuclear Spin Singlet States[J]. Chinese Journal of Magnetic Resonance, 2024, 41(4): 373-381 doi:10.11938/cjmr20243105

引言

谷胱甘肽是一种由谷氨酸、甘氨酸和半胱氨酸形成的三肽,具有很强的还原性.在生物活体中,谷胱甘肽分为还原型谷胱甘肽(GSH)和氧化型谷胱甘肽(GSSG),其中还原型谷胱甘肽占绝大多数,是人体主要的还原性驱动力,参与了如自由基淬灭、重金属解毒等生化反应[1,2].谷胱甘肽还与肿瘤治疗密切相关,例如,在放疗中利用活性氧杀伤肿瘤细胞,其效果会因为谷胱甘肽与活性氧发生反应而受到影响,在进行以生成活性氧为手段的肿瘤治疗中,肿瘤附近的谷胱甘肽浓度对于疗效的影响至关重要[3,4].作为人体内重要的解毒剂,谷胱甘肽含量变化能反映人体解毒器官(如肝脏)的功能和状态[5,6],脑部谷胱甘肽含量的下降可能与早期阿尔兹海默症及认知障碍相关[7,8].

作为一种无损伤且非侵入性的方法,磁共振波谱(MRS)在研究活体代谢分子及疾病标记物的含量变化中表现出独特的优越性, 其在临床应用中发展迅速.例如,MRS可以连续观察多种在神经生物学上起重要作用的代谢物的浓度,通过比较脑组织及肿瘤内某些代谢物的浓度变化,实现对病变的代谢成像和定性诊断[9,10].同时,由于生物活体环境十分复杂,器官、组织、体液中含有大量的生物大分子、无机物、有机代谢产物等,常规的1H-MRS谱往往谱峰重叠严重.为了选择性地检测不同分子信号的MEGA-PRESS(MEshcher-GArwood Point RESolved Spectroscopy)技术、多量子滤波等技术应运而生,先后被应用于对γ-氨基丁酸(GABA)、谷氨酸(Glu)、谷胱甘肽、乳酸等内源分子的靶向信号选择[11-14].2009年,Choi等人[15,16]利用双量子滤波方法实现了谷胱甘肽分子的活体MRS信号选择,该方法对传统双量子滤波进行了进一步的优化,通过零量子态和双量子态的相互转化和对双量子态的二次编码,实现对特定分子信号的高效选择.但其也存在一定的不足:用于激发信号的选择性脉冲的时长过长,导致信号衰减严重,当适当减小脉冲时长时,分子的选择性则会变差.近年来,核自旋单重态被应用于活体分子的靶向选择,根据分子的化学参数设计特定的磁共振脉冲,将分子中的核自旋转化为单重态,利用其寿命长、不受梯度场影响[17-19]的特殊性质实现分子信号选择.优化脉冲根据GRAPE(Gradient Ascent Pulse Engineering)算法计算获得[20],计算过程中脉冲的变量多,可编辑性强,单重态的制备效率高.作者所在课题组前期利用优化控制和数值计算脉冲实现了Glu和GABA分子中的单重态制备及活体分子的选择性检测[21,22],并对多自旋体系中单重态的制备方法进行了理论研究[23,24],为其它分子的单重态制备积累了一定经验.

本文进一步将优化脉冲制备单重态及实现分子滤波的方法应用于活体的谷胱甘肽分子,选择谷胱甘肽分子中两个合适的氢原子核自旋对,通过施加优化的射频脉冲,制备核自旋单重态,同时利用梯度脉冲将其它自旋的信号散相,实现谷胱甘肽分子的选择性检测.该方法针对健康人脑进行了实验验证,结果表明设计的脉冲序列能成功地对不同脑区的谷胱甘肽分子进行选择性检测.

1 材料与方法

1.1 脉冲序列

图1展示了利用核自旋单重态实现活体谷胱甘肽分子选择性信号检测的脉冲序列图.其主要思想是在PRESS(Point-Resolved Spectroscopy Sequence)[25]脉冲序列的基础上增加了单重态滤波模块,整个序列由预饱和水信号压制模块、单重态滤波模块和信号采集模块组成.其中单重态滤波模块是实现滤波的关键所在,由两组优化控制脉冲(OC1、OC2)、去耦脉冲(DC)和两组梯度脉冲组成.预饱和脉冲对水信号进行压制之后,OC1脉冲将靶向分子中特定基团制备为核自旋单重态,连续波(CW)去耦脉冲被用于保存单重态,避免其演化为其它状态.利用核自旋单重态不受梯度场影响的特性,使用两组梯度脉冲将非单重态信号散相,实现分子靶向信号选择.核自旋单重态不能直接检测,需要施加第二个优化脉冲OC2将单重态转变为可观测态,最后施加PRESS采集模块进行信号采集.

图1

图1   利用核自旋单重态实现活体谷胱甘肽分子选择性信号检测的脉冲序列图. 其中OC1、OC2分别为制备和转移单重态的优化脉冲模块, 下方两幅波形图为OC1脉冲的功率与相位随时间变化的示意图

Fig. 1   Pulse sequence diagram for selective signal detection of in vivo glutathione molecules using nuclear spin singlet, in which OC1 and OC2 represent the optimized pulse modules for singlet preparation and transferring, respectively. The two waveforms below illustrate the variation of amplitude and phase of the OC1 pulse


1.2 样品与实验参数

实验使用的仪器包括Bruker AVANCE 11.7 T NMR波谱仪和西门子MAGNETOM 3T-Prisma成像仪.

在Bruker AVANCE 11.7 T NMR波谱仪实验中使用的混合水模为肌酸(Cr,北京百灵威科技有限公司,99%)、还原型谷胱甘肽(GSH,MACKLIN,99%,生物技术级)和γ-氨基丁酸(GABA,Aladdin,99%)依次按照物质的量浓度7:3:1的比例混合,溶于重水(damas-beta,99.9%)中,并使用氘代盐酸和氢氧化钠(damas-beta,99.5%)调节pH值为7.2,取600 μL于NMR样品管中.将Cr、GSH、GABA分别溶于重水中,调整pH至7.2,浓度为50 mmol/L,作为单种物质的水模,取600 μL于NMR样品管中,用以测定滤波效率、评估滤波效果.NMR实验温度设置为37 ℃,去耦脉冲功率和时长分别为0.1 W和0.1 s,两段优化脉冲功率和时长均为0.000 3 W和0.07 s,优化脉冲后的散相梯度场强度分别为107.5 mT/m和215.0 mT/m.

在西门子MAGNETOM 3T-Prisma成像仪实验中使用的水模为10 mmol/L GSH水模,称取谷胱甘肽粉末0.76 g溶于去离子水中,使用盐酸和氢氧化钠调节pH至7.2,定容至250 mL.在MRS实验中,TR为1 500 ms,TE为30 ms,采样点数为512,选择的体素大小为20 mm×30 mm×20 mm,去耦脉冲强度为50 Hz,时长为1 000 μs,两个散相梯度场强场度分别为15 mT/m和20 mT/m,为避免产生梯度回波,梯度持续时间1 000 μs.扫描平均次数128次,单次扫描总时长3 min 16 s.

2 OC脉冲理论与计算

优化脉冲在开源软件Simpson平台上实现.一个优化控制脉冲包含2 000个小的脉冲片段,这些小脉冲片段具有不同的功率与相位,通过将脉冲片段依次施加到初始态上,可以以最大的效率实现初始态到目标态的转化.

整个脉冲序列包含两个优化脉冲(OC1和OC2),其中OC1的作用将热平衡态转化为核自旋单重态,OC2则是将核自旋单重态转化为可观测态.GSH分子包含多个氢原子核,选定半胱氨酸(Cys)残基上的亚甲基上的两个氢原子核为研究对象,其初始态为热平衡态,对应的密度算符为:

${{\rho }_{0}}={{I}_{1z}}+{{I}_{2z}}+\Sigma {{I}_{iz}}$

这里I1I2代表亚甲基上的两个氢原子核,$\Sigma I_{i z}$为脉冲计算时包含的其它自旋体系.施加优化脉冲OC1之后,自旋体系的状态变为:

$\begin{matrix} & {{\rho }_{1}}=2{{I}_{1x}}{{I}_{2x}}+2{{I}_{1y}}{{I}_{2y}}+\Sigma {{I}_{ix}}=({{I}_{1x}}{{I}_{2x}}+{{I}_{1y}}{{I}_{2y}}+{{I}_{1z}}{{I}_{2z}})-{{I}_{1x}}{{I}_{2x}}-{{I}_{1y}}{{I}_{2y}}-{{I}_{1z}}{{I}_{2z}}+\Sigma {{I}_{ix}} \\ & \text{ }=\frac{1}{2}(|{{T}_{0}}>-|{{S}_{0}}>)+\Sigma {{I}_{ix}} \\ \end{matrix}$

其中$\left|T_0\right\rangle$为三重态,$\left|S_0\right\rangle$为单重态,在CW去耦脉冲的作用下,单重态被保存,其余非单重态组分被G1、G2两个梯度脉冲散相.但核自旋单重态属于多量子态,不能被直接检测[26,27].在单重态滤波模块与PRESS结合时,需要施加第二个优化脉冲OC2将单重态转变为纵向磁化矢量,经过之后的体素选择后被转化为可观测信号.本文将这一滤波方法称为GSH-SFOC(GSH-Singlet-Filtered method based on Optimal Control pulse,GSH-SFOC)方法.

3 结果与讨论

3.1 GSH分子靶向滤波目标信号的选取与测试

GSH由谷氨酸、半胱氨酸和甘氨酸组成,三个氨基酸分子通过肽键互相连接.选择2.95 ppm位置的半胱氨酸残基亚甲基上的两个氢原子核为研究目标,这也是此前较多GSH分子靶向滤波所选择的目标基团[28]. 半胱氨酸残基上的亚甲基和次甲基的三个质子构成了一个典型的ABX自旋体系.亚甲基上的两个质子不完全等价,且分别受到来自次甲基质子的耦合作用,产生了八重裂分.用于制备单重态的两个氢原子δ = 0.05 ppm,J = -14.14 Hz.利用NMR测量水模中分子的化学位移和J耦合常数,编译Simpson软件进行优化控制脉冲的计算.将计算生成的脉冲应用于水模中,得到的谱图如图2所示.分析实验谱图可知,在应用GSH-SFOC方法滤波后,除目标基团外,其他信号几乎被完全抑制.这表明GSH-SFOC对GSH Cys-CH2的信号具有较好的选择效果,与单脉冲谱图的信号强度对比,测得滤波后的效率约为50%.

图2

图2   在Bruker AVANCE 11.7 T NMR波谱仪平台采集的GSH分子水模及滤波后的1H NMR谱图. (a)使用90˚单脉冲采集到的GSH 1H NMR谱;(b) GSH-SFOC方法滤波后的GSH 1H NMR谱

Fig. 2   1H NMR spectrum and filtered spectrum of GSH molecular phantom acquired on the Bruker AVANCE 11.7 T NMR spectrometer. (a) GSH 1H NMR spectrum collected by using a 90˚single pulse; (b) GSH 1H NMR spectrum after filtering using the GSH-SFOC method


3.2 混合水模GSH分子靶向滤波

在活体人脑中,GSH分子中基团Cys-CH2与GABA、Cr的氢质子化学位移相近.为了验证滤波方法在活体条件下的可行性,本文配置了三种分子的混合水模,进一步验证GSH-SFOC滤波方法的有效性.实验在Bruker AVANCE 11.7 T NMR波谱仪上完成,结果如图3所示.在常规1H NMR谱[图3(a)图3(c)]中可以观察到,3.00 ppm附近存在GABA三重峰,GSH八重峰和Cr单峰,三种信号紧密相邻,甚至存在部分重叠.可以预见,在主磁场强度和均匀度相对较低的3 T磁共振成像仪中,随着信号的展宽,重叠会更加严重.Cr的单峰将掩盖GSH的信号,而GABA的信号也会被包含其中.对混合体系施加GSH-SFOC滤波方法,滤波后的1H NMR谱图如图3(b)所示,位于3.03 ppm的Cr信号和3.00 ppm附近的GABA信号几乎完全消失,而3.00 ppm的GSH信号依然清晰可辨,实验结果证明在接近人体环境的混合水模中,GSH-SFOC方法可以有效地滤除Cr、GABA等干扰信号,同时保留GSH中Cys-CH2的信号.

图3

图3   在Bruker AVANCE 11.7 T NMR波谱仪平台采集的混合物水模的1H NMR谱. (a) Cr-GABA-GSH混合物水模的90˚单脉冲1H NMR谱图;(b)对混合物施加GSH-SFOC滤波脉冲后采集的1H NMR谱图;(c)为(a)、(b)中2.9 ppm~3.2 ppm区间的放大图

Fig. 3   1H NMR spectrum and filtered spectrum of Cr-GABA-GSH mixture phantom acquired on the Bruker AVANCE 11.7 T NMR spectrometer. (a) 1H NMR spectrum of the Cr-GABA-GSH mixture phantom using a 90˚ single pulse; (b) 1H NMR spectrum collected after applying GSH-SFOC filtering pulses to the mixture; (c) Enlarged view of the 2.9 ppm~3.2 ppm range of (a) and (b)


为了进一步测试GSH-SFOC脉冲对Cr、GABA信号的压制效果,对GSH、Cr、GABA的水模的分别施加GSH-SFOC脉冲实验结果如图4,其中图4(a)从上至下依次为GSH、Cr和GABA水模的单脉冲1H NMR谱;图4(b)为施加GSH-SFOC脉冲滤波后的1H NMR谱图,谱峰的放大倍数为2.对比发现,GSH-SFOC可以将Cr的信号强度降低至500倍以下;对于GABA分子,GSH-SFOC则能将其信号压制1 000倍以上,而GSH中Cys-CH2信号则能以50%的效率被保留下来.该实验说明本文设计的GSH-SFOC脉冲能选择性地检测GSH的信号,同时极大地抑制其它分子的信号.

图4

图4   在Bruker AVANCE 11.7 T NMR波谱仪平台采集的GSH、Cr和GABA水模的1H NMR谱. (a)从上至下依次为GSH、Cr和GABA的水模对应的90˚单脉冲1H NMR谱图;(b)施加GSH-SFOC脉冲后采集的1H NMR谱图

Fig. 4   1H NMR spectra for GSH, Cr, and GABA phantoms acquired on the Bruker AVANCE 11.7 T NMR spectrometer platform. (a) The 90˚ single-pulse 1H NMR spectra corresponding to the GSH, Cr and GABA phantoms (from top to bottom); (b) The 1H NMR spectra acquired after applying the GSH-SFOC pulse


3.3 活体GSH分子靶向滤波

GSH-SFOC脉冲的滤波效果进一步在人体大脑中得到了实验验证,具体脉冲波形见图S1.在实验前,对包含Cr、胆碱(Cholin,Cho)以及GSH的五自旋体系算符随脉冲施加演化轨迹模拟如图S2所示,模拟表明OC脉冲可以高效的完成对相应算符的转化,具有进一步开展活体实验的理论基础. 使用西门子MAGNETOM 3T-Prisma成像仪平台进行测试,实验共招募了5位健康志愿者,年龄为22~27岁,包含4位男性和1位女性.实验通过了华东师范大学伦理委员会的批准(批准文号HR 167-2024).实验结果如图5所示,(a)为所选体素位置结构相示意图,(b)为使用PRESS序列采集的常规1H-MRS谱.此处仅展示了化学位移区间2.5 ppm~3.5 ppm内的谱图,其中2.95 ppm的GSH信号完全被包埋于Cr的尖峰中.2.96 ppm附近还包含有GABA的信号.该区域三种分子的信号重叠严重.(c)为施加了GSH-SFOC滤波脉冲之后的1H-MRS谱,位于2.95 ppm的信号即为GSH中Cys-CH2信号,Cr和GABA的信号几乎完全被抑制.

图5

图5   基于Siemens 3T-Prisma成像仪平台的人脑活体GSH分子靶向1H-MRS图. (a)所选体素位置结构相示意图,其中白色方框即为所选体素范围;(b)运用PRESS序列采集的1H-MRS谱图,截取2.5 ppm~3.5 ppm范围的谱图;(c)应用GSH-SFOC方法采集的5位不同被试者的1H-MRS谱图,截取2.5 ppm~3.5 ppm范围的谱图,谱图被放大5倍. 其中用方框标记的范围为GSH中Cys-CH2的信号. 所有1H-MRS谱图均充零至32 k个数据点,运用大小为3.8的高斯窗函数进行了处理

Fig. 5   Results of in vivo GSH molecular targeted 1H-MRS in human brain collected on the Siemens 3T-Prisma imaging system. (a) The schematic diagram of the selected voxel position with the white box indicating the selected voxel range. (b) The 1H-MRS spectrum acquired using the PRESS sequence, with a schematic representation of the 2.5~3.5 ppm range. (c) The 1H-MRS spectra collected using the SFOC method, with the spectra magnified by 5 times and the 2.5~3.5 ppm range highlighted in the box indicating the GSH Cys-CH2 signal. All 1H-MRS spectra were zero-filled to 32 k data points and processed using a Gaussian window function with a size of 3.8


为了验证GSH-SFOC-MRS方法的滤波效率与浓度之间的关系,配置了GSH浓度梯度水模进行滤波测试,对滤波后的目标信号峰面积进行拟合,拟合结果见图S3.实验结果表明,GSH-SFOC的效率不会随GSH浓度变化而变化,其目标信号积分面积与浓度呈线性关系.以2.95 ppm为中心,设定±0.1 ppm范围内为GSH信号,对其进行基线校正之后求积分,通过由水模获取的效率系数进行校正,再与已知浓度的水模中的信号进行比对,计算了所选体素内GSH的相对含量.定量结果如表1所示,5位被试的定量结果为(1.1±0.3)mmol/L,符合文献报道的大脑顶叶GSH浓度范围[29].

表1   活体GSH浓度定量分析

Table 1  Quantitative analysis of in vivo GSH concentration

编号体素大小/cm3SFOC目标峰面积浓度/(mmol/L)
1(水模)2×3×2695.4610
22×3×281.791.16
32×3×286.491.23
42×3×256.680.81
52×3×296.711.38
62×3×286.511.23

注:以人脑活体GSH靶向1H-MRS数据与已知浓度水模GSH-SFOC-MRS滤波后的目标信号峰面积的积分为计算参数,获取了5位被试者顶叶体素中的GSH浓度. 计算所使用的公式为${{c}_{\text{vivo}}}={{c}_{\text{phantom}}}\times \frac{{{S}_{\text{vivo}}}}{{{S}_{\text{phantom}}}}$,其中${{c}_{\text{vivo}}}$${{c}_{\text{phantom}}}$分别为活体、水模中的GSH浓度,${{S}_{\text{vivo}}}$${{S}_{\text{phantom}}}$分别为对活体、水模中目标峰积分的峰面积.

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在活体中的实验结果证明GSH-SFOC滤波方法能够用于GSH分子的选择性检测及定量.该方法能较好地压制与GSH重叠的Cr和GABA的信号,有助于GSH分子的准确定量.

在本方法提出之前,Choi等人提出的dual-DQC脉冲也能通过一次扫描获得GSH分子靶向谱图,该方法通过半选择性脉冲制备双量子态实现信号选择[16].本文模拟了GSH-SFOC-MRS方法的理论效率并与dual-DQC对比,模拟结果见图S4. 针对3 T上GSH分子自旋的特点,dual-DQC方法的理论滤波效率为49%.为了得到相同的信号强度,GSH-SFOC-MRS脉冲所需的采样时间远短于dual-DQC脉冲的时间.

4 总结

本文提出了一种针对GSH分子的滤波方法,该方法通过施加优化脉冲将GSH分子中的两个氢原子核制备为核自旋单重态,利用单重态的性质实现分子的靶向信号选择.脉冲序列分别在水模和活体人脑中进行了实验验证,实验结果表明本文的滤波方法能有效地对GSH分子信号进行选择性检测,同时还能有效地验证与之重合的Cr和GABA的信号.该脉冲序列有望进一步应用于人脑不同区域GSH信号的检测,为研究与GSH相关的疾病或者生理过程提供直接的实验依据.

利益冲突

附件材料

附件材料(可在《波谱学杂志》官网 http://magres.wipm.ac.cn浏览该论文网页版获取)

图S1 OC脉冲波形图

图S2 OC脉冲算符演化轨迹示意图

图S3 浓度梯度水模实验拟合

图S4 SFOC和dual-DQC效率模拟对比图

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