許彥陽(yáng)，姚桂曉,3，劉平香，趙潔，王昕璐，孫君茂，錢(qián)永忠

代謝組學(xué)在農(nóng)產(chǎn)品營(yíng)養(yǎng)品質(zhì)檢測(cè)分析中的應(yīng)用

許彥陽(yáng)1，姚桂曉1,3，劉平香1，趙潔1，王昕璐1，孫君茂2，錢(qián)永忠1

（1中國(guó)農(nóng)業(yè)科學(xué)院農(nóng)業(yè)質(zhì)量標(biāo)準(zhǔn)與檢測(cè)技術(shù)研究所/農(nóng)業(yè)農(nóng)村部農(nóng)產(chǎn)品質(zhì)量安全重點(diǎn)實(shí)驗(yàn)室，北京 100081；2農(nóng)業(yè)農(nóng)村部食物與營(yíng)養(yǎng)發(fā)展研究所， 北京 100081；3西安理工大學(xué)印刷包裝與數(shù)字媒體學(xué)院，西安 710048）

科學(xué)檢測(cè)和分析農(nóng)產(chǎn)品營(yíng)養(yǎng)品質(zhì)對(duì)提升優(yōu)質(zhì)農(nóng)產(chǎn)品的營(yíng)養(yǎng)水平具有重要作用。由于農(nóng)產(chǎn)品中營(yíng)養(yǎng)成分組成復(fù)雜，已有的分析方法只能針對(duì)已知營(yíng)養(yǎng)素的濃度、功能等進(jìn)行分析，無(wú)法對(duì)農(nóng)產(chǎn)品中存在的大量其他功能性活性物質(zhì)進(jìn)行分析鑒定。代謝組學(xué)技術(shù)通過(guò)高通量化學(xué)分析技術(shù)對(duì)生物樣品中的小分子代謝產(chǎn)物進(jìn)行定性和定量分析，在具有特殊營(yíng)養(yǎng)功能的小分子物質(zhì)分析中具有突出優(yōu)勢(shì)。代謝組學(xué)技術(shù)的引入，為農(nóng)產(chǎn)品營(yíng)養(yǎng)成分表征及差異性分析，產(chǎn)地溯源及真?zhèn)舞b別，生長(zhǎng)儲(chǔ)藏過(guò)程中營(yíng)養(yǎng)成分變化規(guī)律揭示，營(yíng)養(yǎng)功能成分作用機(jī)制研究等提供了新方法，也為膳食結(jié)構(gòu)的優(yōu)化調(diào)整提供了新策略。本文對(duì)代謝組學(xué)研究方法的新進(jìn)展，包括樣品制備、代謝物分析鑒定以及數(shù)據(jù)分析等進(jìn)行了綜述，總結(jié)了代謝組學(xué)技術(shù)在農(nóng)產(chǎn)品營(yíng)養(yǎng)成分表征及差異性分析、產(chǎn)地溯源及真?zhèn)舞b別、生長(zhǎng)儲(chǔ)藏過(guò)程中營(yíng)養(yǎng)成分變化規(guī)律以及營(yíng)養(yǎng)功能成分作用機(jī)制等方面的應(yīng)用，旨在為我國(guó)農(nóng)業(yè)高質(zhì)量發(fā)展提供思路。在樣品制備方法方面，首先通過(guò)快速改變樣品所處的環(huán)境條件，如添加強(qiáng)酸、強(qiáng)堿或液氮冷凍等技術(shù)終止新陳代謝相關(guān)酶的活性。然后針對(duì)代謝物的極性，選擇不同的提取溶劑，從而獲得較高的提取率。在樣品分析方法方面，核磁共振、色譜質(zhì)譜和毛細(xì)管電泳質(zhì)譜等技術(shù)得到了廣泛地應(yīng)用。其中，色譜質(zhì)譜聯(lián)用技術(shù)將色譜的有效分離和質(zhì)譜的準(zhǔn)確定量相結(jié)合，已經(jīng)成為代謝組學(xué)中使用最廣泛的分析技術(shù)。在數(shù)據(jù)處理及分析方面，無(wú)監(jiān)督分析中的主成分分析和有監(jiān)督分析中的正交偏最小二乘法－判別分析是目前應(yīng)用最多的數(shù)據(jù)分析方法。通過(guò)通路分析軟件的富集分析和拓?fù)浞治觯梢悦鞔_與代謝物差異相關(guān)性最高的代謝通路，對(duì)差異代謝產(chǎn)物的機(jī)制進(jìn)行分析和解釋。在農(nóng)產(chǎn)品營(yíng)養(yǎng)成分分析應(yīng)用方面，通過(guò)對(duì)農(nóng)產(chǎn)品中初生代謝產(chǎn)物及次生代謝產(chǎn)物進(jìn)行全面表征，形成農(nóng)產(chǎn)品獨(dú)特的代謝指紋圖譜，從而實(shí)現(xiàn)營(yíng)養(yǎng)成分的差異性分析；通過(guò)非特定目標(biāo)物的檢測(cè)和無(wú)監(jiān)督分析方法，實(shí)現(xiàn)不同產(chǎn)地農(nóng)產(chǎn)品的組間差異鑒別和差異化合物篩選；通過(guò)農(nóng)產(chǎn)品生長(zhǎng)過(guò)程中關(guān)鍵成分的消長(zhǎng)規(guī)律及合成機(jī)理分析，指導(dǎo)最佳收獲期；通過(guò)體液代謝譜和生物標(biāo)志物的檢測(cè)，系統(tǒng)研究營(yíng)養(yǎng)功能成分與生物體代謝之間的交互作用，為營(yíng)養(yǎng)功能成分作用機(jī)制研究及膳食指導(dǎo)提供有價(jià)值的信息。

代謝組學(xué)；農(nóng)產(chǎn)品；營(yíng)養(yǎng)；品質(zhì)

0 引言

當(dāng)前，我國(guó)進(jìn)入消費(fèi)結(jié)構(gòu)轉(zhuǎn)型升級(jí)和供給側(cè)結(jié)構(gòu)性改革的關(guān)鍵時(shí)期，面對(duì)“吃飽”到“吃好”的需求轉(zhuǎn)變，需要發(fā)展高品質(zhì)、高營(yíng)養(yǎng)的農(nóng)產(chǎn)品[1-2]。農(nóng)產(chǎn)品的品質(zhì)和營(yíng)養(yǎng)一般根據(jù)產(chǎn)品中營(yíng)養(yǎng)素的種類(lèi)、含量以及營(yíng)養(yǎng)素功能進(jìn)行判定。農(nóng)產(chǎn)品中的營(yíng)養(yǎng)素[3]主要包括蛋白質(zhì)、脂肪、碳水化合物、維生素、礦物質(zhì)元素、膳食纖維、水及其他各類(lèi)微量功能活性成分等8大類(lèi)，通過(guò)對(duì)8類(lèi)物質(zhì)成分含量和組分的檢測(cè)，建立食用農(nóng)產(chǎn)品的營(yíng)養(yǎng)成分?jǐn)?shù)據(jù)庫(kù)，從而評(píng)價(jià)農(nóng)產(chǎn)品的質(zhì)量。同時(shí)，針對(duì)不同農(nóng)產(chǎn)品中營(yíng)養(yǎng)素的特定功能性成分，如不飽和脂肪酸類(lèi)、多酚類(lèi)、黃酮類(lèi)、多糖類(lèi)、多肽類(lèi)等物質(zhì)進(jìn)行降血糖、降血壓、抗衰老、抗動(dòng)脈硬化等功能研究，評(píng)價(jià)農(nóng)產(chǎn)品的營(yíng)養(yǎng)功能。然而，農(nóng)產(chǎn)品中營(yíng)養(yǎng)成分組成復(fù)雜，已有的分析方法只能針對(duì)已知營(yíng)養(yǎng)素的濃度、功能等進(jìn)行分析，無(wú)法對(duì)農(nóng)產(chǎn)品中存在的大量其他功能性活性物質(zhì)進(jìn)行分析鑒定。

代謝組學(xué)以分子量在1 000以下的小分子為研究對(duì)象，通過(guò)對(duì)動(dòng)態(tài)多參數(shù)代謝應(yīng)答反應(yīng)進(jìn)行定量測(cè)量，研究生物體內(nèi)源性和外源性代謝物整體構(gòu)成及代謝途徑變化的新技術(shù)[4-6]，在疾病研究[7]、藥物開(kāi)發(fā)[8]、毒性評(píng)價(jià)[9]、環(huán)境科學(xué)[10]等領(lǐng)域已經(jīng)得到較為廣泛的應(yīng)用。由于代謝組學(xué)可以在全景角度揭示生物系統(tǒng)、生理狀態(tài)等優(yōu)勢(shì)，近年來(lái)被逐漸應(yīng)用于農(nóng)產(chǎn)品的營(yíng)養(yǎng)品質(zhì)研究。通過(guò)代謝組學(xué)分析，為農(nóng)產(chǎn)品營(yíng)養(yǎng)成分表征及差異性分析，產(chǎn)地溯源及真?zhèn)舞b別，生長(zhǎng)儲(chǔ)藏過(guò)程中營(yíng)養(yǎng)成分變化規(guī)律揭示，營(yíng)養(yǎng)功能成分作用機(jī)制研究等提供新方法[11-12]，也為膳食結(jié)構(gòu)的優(yōu)化調(diào)整提供新策略。

1 代謝組學(xué)研究進(jìn)展

代謝組學(xué)技術(shù)根據(jù)研究目的和研究層次不同分為非靶向代謝組學(xué)和靶向代謝組學(xué)[13]。非靶向代謝組學(xué)是對(duì)生物系統(tǒng)中代謝物進(jìn)行全面系統(tǒng)地分析，盡可能多地定性和相對(duì)定量生物體系中的代謝物，獲取大量數(shù)據(jù)并對(duì)其進(jìn)行處理，進(jìn)而分析獲得差異性代謝物；靶向代謝組學(xué)通常針對(duì)某個(gè)代謝通路或已知的某些特定代謝物，進(jìn)行高通量檢測(cè)和定量分析，主要用于驗(yàn)證差異性代謝物。應(yīng)用代謝組學(xué)技術(shù)開(kāi)展農(nóng)產(chǎn)品營(yíng)養(yǎng)品質(zhì)檢測(cè)分析研究主要包括樣品的收集和制備，代謝物分離、檢測(cè)和鑒定，數(shù)據(jù)統(tǒng)計(jì)分析等過(guò)程。

1.1 代謝組學(xué)樣品制備方法

樣品的收集和制備是代謝組學(xué)分析的基礎(chǔ)，主要包括樣品采集、淬滅、儲(chǔ)存、提取等[14-15]，旨在迅速、有效終止樣品新陳代謝反應(yīng)，最大限度地去除樣本中雜質(zhì)（如蛋白質(zhì)、糖類(lèi)、脂肪等），同時(shí)能較為完整地保留樣品中的整體代謝產(chǎn)物或特異性目標(biāo)代謝產(chǎn)物[16]。

代謝組學(xué)技術(shù)的研究對(duì)象包括組織、器官、提取液等，分析對(duì)象種類(lèi)多，結(jié)構(gòu)、性質(zhì)差異大，要獲得穩(wěn)定可重復(fù)的試驗(yàn)結(jié)果，需考慮試驗(yàn)?zāi)康摹x器平臺(tái)、分析方法等要求，選擇合適的樣品處理方法。目前，主要通過(guò)快速改變樣品所處的環(huán)境條件，如添加強(qiáng)酸、強(qiáng)堿或液氮冷凍等手段終止新陳代謝相關(guān)酶的活性。采用的前處理技術(shù)主要包括超聲波提取[17]、固相萃取[18]、固相微萃取[19]、分散液液微萃取[20]、超臨界流體萃取[21]等，使用的提取劑主要包括甲醇、乙醇、乙腈、異丙醇、氯仿、水以及混合溶劑等。Vargas等[22]比較了不同萃取劑、不同溫度和運(yùn)輸條件對(duì)代謝物提取效果的影響，結(jié)果顯示，提取溶劑對(duì)代謝產(chǎn)物具有顯著影響。

代謝物的極性不同，提取溶劑也應(yīng)不同。如極性代謝物的提取溶劑主要為含水的有機(jī)溶劑，如甲醇/水溶液、乙腈/水溶液、氯仿/甲醇/水溶液等[23]。脂溶性代謝物常用的提取溶劑主要有氯仿、甲基叔丁醚和二氯甲烷等[23-24]，獲得較高提取率的關(guān)鍵是氯仿/甲醇/水的比例。BLIGH等[25]在FOLCH等[26]提取方法的基礎(chǔ)上進(jìn)行了進(jìn)一步的優(yōu)化，指出提取鱈魚(yú)組織中脂質(zhì)的氯仿/甲醇/水的最佳比例為1﹕2﹕0.8。鑒于氯仿具有高毒性，作為其替代物的二氯甲烷逐漸被用于脂溶性代謝產(chǎn)物的提取[27]。此外，使用氯仿/甲醇法提取脂質(zhì)代謝產(chǎn)物時(shí)，目標(biāo)物位于下方的氯仿層，操作時(shí)需穿過(guò)上方水層，操作不方便。MATYASH等[28]基于甲基叔丁醚密度小于水的原理，提出了以甲基叔丁醚代替氯仿或二氯甲烷提取脂質(zhì)的方法，使得脂質(zhì)所在的甲基叔丁醚層位于水層上方，簡(jiǎn)化了脂質(zhì)提取的操作過(guò)程。

生物體內(nèi)的部分代謝物極性強(qiáng)、揮發(fā)性低，如氨基酸、脂肪酸、胺類(lèi)、糖類(lèi)和核苷酸類(lèi)物質(zhì)，前處理過(guò)程中需要進(jìn)行化學(xué)衍生化，常用的衍生化方法包括硅烷化、甲酯化、烷基化、?；萚29]。另外，代謝物的基質(zhì)不同，所選擇的提取方法和提取試劑也各不相同，在實(shí)際操作過(guò)程中應(yīng)結(jié)合基質(zhì)特點(diǎn)，妥善選擇前處理方法，以達(dá)到最佳提取效果。在非靶向代謝組學(xué)研究中，通常需要制備質(zhì)控（QC）樣品，保證分析數(shù)據(jù)的穩(wěn)定性和可靠性。

1.2 代謝組學(xué)分析方法

代謝組學(xué)基于高通量分析技術(shù)對(duì)生物樣品中小分子代謝產(chǎn)物的組成、含量及其變化進(jìn)行定性和定量分析，通過(guò)代謝物信息與生物體生理變化的關(guān)聯(lián)分析，尋找生物標(biāo)志物。樣品中的成分復(fù)雜多樣，有效分離并準(zhǔn)確鑒定各種物質(zhì)是代謝組學(xué)研究的前提。目前，代謝組學(xué)主要的分析技術(shù)包括核磁共振、色譜質(zhì)譜和毛細(xì)管電泳質(zhì)譜等。

1.2.1 核磁共振技術(shù) 核磁共振（nuclear magnetic resonance，NMR）技術(shù)是指核磁矩不為零的原子核，在外磁場(chǎng)的作用下，共振吸收某一特定頻率的電磁波。通過(guò)能量吸收曲線(xiàn)分析，判斷該原子在分子中所處的位置及相對(duì)數(shù)目，從而實(shí)現(xiàn)定量分析和結(jié)構(gòu)分析。NMR技術(shù)可以對(duì)樣品實(shí)現(xiàn)無(wú)偏性分析，具有前處理較少、不破壞樣品結(jié)構(gòu)和性質(zhì)等優(yōu)點(diǎn)，能夠?qū)ν旰媒M織、生物液等進(jìn)行代謝成分分析，并確定代謝物結(jié)構(gòu)式[30]。適用于農(nóng)產(chǎn)品中脂肪、多元醇類(lèi)、有機(jī)酸、糖類(lèi)等營(yíng)養(yǎng)成分的檢測(cè)分析。應(yīng)用最為廣泛的一維氫譜核磁共振（1H-NMR）對(duì)含氫代謝產(chǎn)物具有普適性，具有無(wú)需標(biāo)準(zhǔn)品、無(wú)損等特點(diǎn)，可得到豐富的樣品信息，在農(nóng)產(chǎn)品組分分析、產(chǎn)品質(zhì)量鑒別、質(zhì)量控制等方面應(yīng)用廣泛[31-32]。許茜等[33]采用NOESY脈沖序列對(duì)14個(gè)不同來(lái)源的固體動(dòng)物膠樣品進(jìn)行原料來(lái)源鑒定，結(jié)果顯示，1H-NMR技術(shù)能夠區(qū)分不同樣品的來(lái)源，判別正確率達(dá)91.67%。對(duì)復(fù)雜樣品的代謝物鑒定需結(jié)合二維核磁共振波譜，如總相干轉(zhuǎn)移光譜（total correlation spectroscopy，TOCSY）[34]，TOCSY可以解決重疊峰的問(wèn)題，能進(jìn)一步提高分辨率[35]。另外，核磁共振技術(shù)與色譜結(jié)合使用可有效提高分析的靈敏度，如液相核磁共振聯(lián)用（LC-NMR）解決了NMR中干擾過(guò)多等問(wèn)題，有效提高了分析的檢測(cè)限[36]。BRAUNBERGER等[37]綜合液相質(zhì)譜技術(shù)、液相核磁共振聯(lián)用和離線(xiàn)NMR技術(shù)，分析了茅膏菜中黃酮類(lèi)和鞣花酸衍生物，并解析了13種化合物的結(jié)構(gòu)。

1.2.2 質(zhì)譜分析技術(shù) 色譜質(zhì)譜聯(lián)用技術(shù)將色譜的有效分離和質(zhì)譜的準(zhǔn)確定量相結(jié)合，已經(jīng)成為代謝組學(xué)中使用最廣泛的分析技術(shù)。經(jīng)過(guò)近年來(lái)的發(fā)展，目前，質(zhì)譜分析技術(shù)主要包括四級(jí)桿質(zhì)譜（quadrupole mass spectrometer, QMS）、三重四級(jí)桿質(zhì)譜（triple quadrupole mass spectrometer，QQQ）、飛行時(shí)間質(zhì)譜（time-of-flight mass spectrometry，TOF-MS）、四級(jí)桿飛行時(shí)間串聯(lián)質(zhì)譜（quadrupole time-of-flight mass spectrometry，Q-TOF-MS）、離子阱質(zhì)譜（ion trap mass spectrometer，ITMS）等，所使用的電離源主要包括電噴霧電離源（electron spray ionization，ESI）[38]、大氣壓化學(xué)電離源（atmospheric-pressure chemical ionization，APCI）、基質(zhì)輔助激光解析電離源（matrix- assisted laser desorption ionization，MALDI）[39]、大氣壓光電離源（atmospheric-pressure photoionization，APPI）、質(zhì)子轉(zhuǎn)移反應(yīng)器（proton transfer reaction，PTR）[40]、實(shí)時(shí)直接分析（direct analysis in real time，DART）[41]等。相較于NMR技術(shù)，質(zhì)譜的靈敏度更高，但穩(wěn)定性不足，在不同儀器甚至不同日期獲得的數(shù)據(jù)之間存在差異，為保證結(jié)果的穩(wěn)定，需采用標(biāo)準(zhǔn)化的操作步驟[42]。

GC-MS是指氣化后的樣品根據(jù)各組分的熔沸點(diǎn)、吸附性及極性不同在色譜柱中實(shí)現(xiàn)分離，在質(zhì)譜系統(tǒng)中經(jīng)電離產(chǎn)生具有不同質(zhì)荷比的離子后進(jìn)行分析的技術(shù)。GC-MS技術(shù)具有分離能力強(qiáng)，靈敏度高，分析速度快，操作方便，標(biāo)準(zhǔn)譜庫(kù)成熟等優(yōu)點(diǎn)，通常用于揮發(fā)性、半揮發(fā)性、低分子量和熱穩(wěn)定化合物的鑒定和定量檢測(cè)。適用于農(nóng)產(chǎn)品中精油、酯類(lèi)、類(lèi)十二烷酸、類(lèi)胡蘿卜素、類(lèi)黃酮、脂質(zhì)等極性較小物質(zhì)的分析。相對(duì)于NMR技術(shù)，GC-MS分析技術(shù)樣品前處理較為復(fù)雜，部分代謝物在分析前需要衍生化處理，以增強(qiáng)揮發(fā)性[43]。MARI等[44]使用甲硅烷基化混合物，經(jīng)兩步衍生化后，對(duì)蕨麻植物樣品中的53種代謝物進(jìn)行了分析。也有學(xué)者[45]采用甲氧基胺化/三甲基硅基化衍生化后，分析了乙烯利處理后甜櫻桃代謝譜變化規(guī)律。為同時(shí)分析盡可能多的代謝物，具有較高分離能力和靈敏度的質(zhì)譜分析技術(shù)被逐漸應(yīng)用于組學(xué)分析，如WONG等[46]采用二維氣相色譜飛行時(shí)間質(zhì)譜（GC- GC-TOF/MS）對(duì)桉樹(shù)葉油代謝譜進(jìn)行了全面分析。

LC-MS是根據(jù)樣品中各組分在液相色譜柱中保留時(shí)間不同實(shí)現(xiàn)分離，在質(zhì)譜系統(tǒng)中經(jīng)離子源電離后產(chǎn)生具有不同質(zhì)荷比的離子后進(jìn)行分析的技術(shù)。LC-MS技術(shù)可以在常溫下實(shí)現(xiàn)分離，相較于NMR靈敏度低、GC-MS樣品處理較復(fù)雜等問(wèn)題，LC-MS更靈敏，不受試樣揮發(fā)性和熱穩(wěn)定性的限制，樣品前處理簡(jiǎn)單，可對(duì)農(nóng)產(chǎn)品中糖類(lèi)、氨基酸、多酚、萜類(lèi)化合物等極性較強(qiáng)的代謝產(chǎn)物進(jìn)行分析[47]。GARCIA等[38]基于UPLC-ESI-QToF-MS建立了非靶向的分析方法，對(duì)生菜代謝譜進(jìn)行了分析。此外，基于HPLC-QToF-MS的非靶向技術(shù)在雞蛋蛋黃[48]及大蒜[49]小分子物質(zhì)分析方面也得到了很好的應(yīng)用。但LC-MS沒(méi)有綜合性數(shù)據(jù)庫(kù)，給后期代謝物的分析造成了一定的困難與挑戰(zhàn)。

毛細(xì)管電泳質(zhì)譜（capillary electrophoresis–mass spectrometry，CE-MS）[50]是基于樣品中各組分間淌度和分配行為差異實(shí)現(xiàn)分離，經(jīng)質(zhì)譜系統(tǒng)中電離源電離產(chǎn)生不同質(zhì)荷比的離子，從而實(shí)現(xiàn)離子型化合物的分析。CE-MS技術(shù)能夠檢測(cè)離子型化合物，在含氨基化合物等復(fù)雜基質(zhì)食品分析中有很大優(yōu)勢(shì)，常用于氨基酸類(lèi)物質(zhì)的分析。CE-MS能夠同時(shí)測(cè)定丁醇衍生后的6種氨基酸（鳥(niǎo)氨酸、丙氨酸、γ-氨基丁酸、異亮氨酸、瓜氨酸和焦谷氨酸），該方法已成功應(yīng)用于大豆油、橄欖油摻假分析[51]。

目前，代謝組學(xué)的研究大部分依賴(lài)成本相對(duì)較高的高分辨質(zhì)譜或核磁技術(shù)，但LAN等[52]成功開(kāi)發(fā)了HPLC-UV技術(shù)，分析了不同批次草藥提取物含量，該方法簡(jiǎn)單、廉價(jià)，可以作為農(nóng)產(chǎn)品營(yíng)養(yǎng)成分分析的初步方法。由于農(nóng)產(chǎn)品代謝物種類(lèi)多，結(jié)構(gòu)、性質(zhì)差異大，僅采用單一分析手段很難實(shí)現(xiàn)代謝物的全景定性及定量分析，可采用多種分析手段，取長(zhǎng)補(bǔ)短，盡可能全面地覆蓋農(nóng)產(chǎn)品代謝物。

1.3 代謝組學(xué)的數(shù)據(jù)處理及分析

在代謝組學(xué)分析中，代謝物數(shù)據(jù)量大、樣本分析產(chǎn)生的數(shù)據(jù)復(fù)雜，需要能自動(dòng)、無(wú)歧視分析原始數(shù)據(jù)文件[53]。為使數(shù)據(jù)更簡(jiǎn)潔、分析簡(jiǎn)便，儀器分析獲得的數(shù)據(jù)通常需要預(yù)處理，主要包括信號(hào)濾噪、代謝特征提取、色譜與質(zhì)譜匹配、缺失值過(guò)濾與補(bǔ)值、信號(hào)歸一化、化合物定性定量等步驟[54-55]。經(jīng)過(guò)預(yù)處理后的代謝組學(xué)數(shù)據(jù)需要借助數(shù)據(jù)分析軟件實(shí)現(xiàn)單變量分析和多元變量等統(tǒng)計(jì)分析，數(shù)據(jù)分析方法包括無(wú)監(jiān)督分析和有監(jiān)督分析兩種，其中無(wú)監(jiān)督分析包括主成分分析（principal component analysis，PCA）[56]、聚類(lèi)分析（hierarchical cluster analysis，HCA）[57]等。由于無(wú)監(jiān)督分析法不能忽略組內(nèi)誤差，不利于組間差異的鑒別，需要進(jìn)一步結(jié)合有監(jiān)督分析突出組間差異；有監(jiān)督分析主要包括偏最小二乘分析（partial least squares discrimination analysis，PLS-DA）[58]、正交偏最小二乘法－判別分析（orthogonal partial least squares discriminant analysis，OPLS-DA）等。數(shù)據(jù)分析時(shí)也可以通過(guò)數(shù)據(jù)分析軟件特有的分析功能揭示代謝物上/下調(diào)情況、變量權(quán)重（variable importance，VIP值）和顯著性變化，經(jīng)多種組合數(shù)據(jù)分析后，可以揭示不同組別樣本中小分子代謝物的差異，篩選獲得差異代謝物。隨著組學(xué)技術(shù)的發(fā)展，多家儀器公司結(jié)合數(shù)據(jù)采集軟件開(kāi)發(fā)了多種數(shù)據(jù)分析軟件，如Agilent公司的MPP軟件、Waters公司的QI軟件、SCIEX公司的Lipid View軟件等[59-61]。上述數(shù)據(jù)分析軟件的成功研發(fā)給從事代謝組學(xué)研究的學(xué)者們提供了便利條件，簡(jiǎn)化了數(shù)據(jù)分析工作。

通過(guò)組學(xué)軟件篩選出的差異代謝物需要進(jìn)一步借助通路分析軟件、網(wǎng)站或大量相關(guān)文獻(xiàn)，實(shí)現(xiàn)生物標(biāo)志物的重要性和功能性解讀，了解其在生命活動(dòng)過(guò)程中參與的代謝通路，繼而進(jìn)一步為物質(zhì)靶點(diǎn)分析、營(yíng)養(yǎng)功能評(píng)價(jià)等提供參考依據(jù)[62]。HMDB[63]、KEGG、METLIN[64]、NIST[65]等數(shù)據(jù)庫(kù)是常用的代謝物結(jié)構(gòu)鑒定和代謝通路分析的數(shù)據(jù)庫(kù)。我國(guó)學(xué)者WANG等[66]也開(kāi)發(fā)了代謝途徑延伸（MPE）的方法快速表征代謝組學(xué)生物標(biāo)志物，即通過(guò)已知的代謝途徑連接未知的代謝物到特定的核心化合物，然后通過(guò)定量測(cè)定匹配代謝物的MS/MS譜進(jìn)行驗(yàn)證，獲得93種生物標(biāo)志物（95%覆蓋）的結(jié)構(gòu)后，通過(guò)MS/MS匹配確認(rèn)獲得66種代謝物（70%覆蓋），快速闡明了肉堿的靶向代謝網(wǎng)絡(luò)。

2 代謝組學(xué)在農(nóng)產(chǎn)品營(yíng)養(yǎng)品質(zhì)檢測(cè)分析中的應(yīng)用

代謝組學(xué)能在生物學(xué)水平上檢測(cè)農(nóng)產(chǎn)品中小分子代謝產(chǎn)物的差別，定性與定量分析不同品種、不同產(chǎn)地和不同生長(zhǎng)儲(chǔ)藏條件下農(nóng)產(chǎn)品營(yíng)養(yǎng)成分的差異。同時(shí)，經(jīng)過(guò)非靶向代謝組學(xué)全面系統(tǒng)分析和靶向代謝組學(xué)的確證后，新的生物標(biāo)志物的發(fā)現(xiàn)進(jìn)一步推動(dòng)了代謝組學(xué)在產(chǎn)地溯源、作用機(jī)制、育種策略以及種養(yǎng)方式等方面的應(yīng)用，見(jiàn)表1。

2.1 農(nóng)產(chǎn)品營(yíng)養(yǎng)成分表征及差異性分析

不同農(nóng)產(chǎn)品具有不同的特征營(yíng)養(yǎng)成分，代謝組學(xué)技術(shù)可對(duì)農(nóng)產(chǎn)品中初生代謝產(chǎn)物及次生代謝產(chǎn)物進(jìn)行全面表征，形成農(nóng)產(chǎn)品獨(dú)特的代謝指紋圖譜。ZHU等[67]采用廣泛靶向的LC-MS/MS分析方法，研究了442份成熟番茄果實(shí)果皮組織中代謝物，共發(fā)現(xiàn)了980個(gè)不同的代謝物。B?TTCHER等[68]采用LC/ESI-QTOF-MS技術(shù)對(duì)洋蔥中的低聚果糖、氨基酸、多肽、S-半胱氨酸、黃酮及皂苷類(lèi)等極性及半極性成分進(jìn)行了全面的代謝輪廓分析。對(duì)葡萄代謝組的研究發(fā)現(xiàn)，野生品種的葡萄花色苷及芪類(lèi)化合物組成比雜交品種及歐亞種葡萄復(fù)雜，歐亞種葡萄果皮和種籽中原花青素含量更高[69]。意大利‘藍(lán)蟹’等3個(gè)品種代謝組學(xué)分析結(jié)果顯示，谷氨酸、丙氨酸、甘氨酸、龍蝦堿、乳酸、甜菜堿和?；撬岬?種代謝物含量具有顯著差異[70]。

農(nóng)產(chǎn)品中代謝物種類(lèi)及水平通常與其感官特征具有重要相關(guān)性，如番茄中鄰甲基苯乙酮、苯甲酮等揮發(fā)性成分對(duì)番茄氣味形成起關(guān)鍵作用[71]，蕪菁中L-谷氨酰胺、L-天冬酰胺與苦味呈負(fù)相關(guān)，而金縷梅糖、麥芽糖和蘋(píng)果酸與苦味呈正相關(guān)，異硫氰酸烯丙酯等芥子甙降解產(chǎn)物與“銳”度呈正相關(guān)[72]。此外，不同農(nóng)產(chǎn)品品種、不同組織及器官營(yíng)養(yǎng)成分不同，如不同品種蔓越莓[73]、樹(shù)莓[74]花青素的含量及水平，馬鈴薯皮和塊莖組織[75]、番茄果肉與種子[76]代謝物種類(lèi)及水平均存在較大差異，借助代謝組學(xué)分析，可以獲得不同品種、組織及器官的營(yíng)養(yǎng)成分組成及含量，從而應(yīng)用于不同的農(nóng)產(chǎn)品加工和消費(fèi)。

轉(zhuǎn)基因技術(shù)提高了糧食產(chǎn)量，但由此而來(lái)的安全問(wèn)題引起廣泛爭(zhēng)論，代謝組學(xué)技術(shù)能在生物學(xué)水平上鑒別和篩選轉(zhuǎn)基因與非轉(zhuǎn)基因農(nóng)產(chǎn)品代謝差異物，揭示轉(zhuǎn)基因帶來(lái)的本質(zhì)性變化以及各種非預(yù)期變異效應(yīng)[77]。RAO等[78]對(duì)轉(zhuǎn)基因玉米與常規(guī)玉米中210種代謝產(chǎn)物進(jìn)行分析，在考慮自然變異后發(fā)現(xiàn)4種差異代謝物。番茄經(jīng)基因修飾后氨基酸和多酚等物質(zhì)含量水平發(fā)生顯著性改變，其中山奈酚、桂皮素苷含量水平較對(duì)照組提高10倍以上[79]。非靶向代謝組學(xué)在考慮自然變異的情況下能為轉(zhuǎn)基因作物代謝產(chǎn)物分析提供技術(shù)手段。

2.2 農(nóng)產(chǎn)品產(chǎn)地溯源及真?zhèn)舞b別

農(nóng)產(chǎn)品的產(chǎn)地來(lái)源是消費(fèi)者選擇食品的重要依據(jù)，食品摻假等問(wèn)題引起了消費(fèi)者的廣泛關(guān)注。代謝組學(xué)技術(shù)在非特定目標(biāo)物的檢測(cè)方面有著其他方法無(wú)法比擬的優(yōu)勢(shì)，有監(jiān)督分析方法可以有效減少同一產(chǎn)地農(nóng)產(chǎn)品的組內(nèi)誤差，實(shí)現(xiàn)不同產(chǎn)地農(nóng)產(chǎn)品的組間差異鑒別和差異化合物篩選，為農(nóng)產(chǎn)品產(chǎn)地溯源和真?zhèn)舞b別提供了重要技術(shù)手段[80-81]。ISABAL等[82]基于非靶向代謝組學(xué)方法分析了4種不同地理來(lái)源枸杞的化學(xué)成分區(qū)別，發(fā)現(xiàn)了蒙古枸杞中槲皮素、山奈酚糖苷、二咖啡?？鼘幩岷头铀岷匡@著高于其他地區(qū)的枸杞。對(duì)捷克、中國(guó)和西班牙3個(gè)國(guó)家的大蒜進(jìn)行代謝輪廓分析[83]，獲得了蒜氨酸、PC（16﹕0/18﹕2）和精氨酸3種標(biāo)志性差異化合物。RITOTA等[84]采用高分辨率魔角旋轉(zhuǎn)核磁共振技術(shù)（HRMAS-NMR）及偏最小二乘法判別分析（PLS-DA）等多元數(shù)據(jù)統(tǒng)計(jì)分析方法，成功實(shí)現(xiàn)意大利4個(gè)產(chǎn)地、2個(gè)品種大蒜（白皮蒜、紫皮蒜）的分類(lèi)及溯源。CAMARGO[85]、VADALA[86]和SMITH等[87]也分別通過(guò)礦物質(zhì)元素及痕量金屬元素實(shí)現(xiàn)了大蒜不同產(chǎn)地的溯源。

表1 代謝組學(xué)在農(nóng)產(chǎn)品營(yíng)養(yǎng)品質(zhì)檢測(cè)分析中的應(yīng)用

經(jīng)非靶向代謝組學(xué)篩查獲得差異代謝物后，靶向代謝組學(xué)可以對(duì)產(chǎn)品中的特異性指標(biāo)如氨基酸、揮發(fā)性成分等化合物成分進(jìn)行定量分析[88-89]，進(jìn)一步提高模型鑒別能力。KLOCKMANN等[90]采用UPLC- QTOF-MS對(duì)來(lái)自德國(guó)、法國(guó)、意大利、土耳其和格魯吉亞共196個(gè)榛子進(jìn)行了產(chǎn)地溯源，篩選確定了20種關(guān)鍵差異代謝物（5種磷脂酰膽堿，3種磷脂酰乙醇胺，4種甘油二酯，7種三?；视秃挺?生育酚），PCA-LDA訓(xùn)練精度可達(dá)99.5%。隨后，對(duì)鑒定出的差異代謝物采用LC-ESI-QqQ-MS進(jìn)行了靶向分析[91]，預(yù)測(cè)模型訓(xùn)練精度達(dá)到100%，交叉驗(yàn)證精度達(dá)到97%。

2.3 農(nóng)產(chǎn)品生長(zhǎng)儲(chǔ)藏過(guò)程中營(yíng)養(yǎng)成分變化規(guī)律

農(nóng)產(chǎn)品不同生長(zhǎng)階段營(yíng)養(yǎng)成分存在較大差異，研究農(nóng)產(chǎn)品生長(zhǎng)過(guò)程中關(guān)鍵成分的消長(zhǎng)規(guī)律及合成機(jī)理，對(duì)于確定最佳收獲期和改善果蔬的保質(zhì)期具有重要意義。ZHANG等[92]對(duì)草莓生長(zhǎng)過(guò)程中的揮發(fā)性成分進(jìn)行了定性和定量分析，發(fā)現(xiàn)草莓成熟之前游離氨基酸含量逐漸下降，過(guò)熟后快速上升，涉及的代謝通路包括酯生物合成、三羧酸循環(huán)、莽草酸途徑和氨基酸代謝。對(duì)‘赤霞珠’和‘梅洛’2個(gè)不同葡萄品種在生長(zhǎng)、發(fā)育及成熟過(guò)程中營(yíng)養(yǎng)成分變化規(guī)律及代謝途徑研究發(fā)現(xiàn)，葡萄在坐果和顏色轉(zhuǎn)化期代謝物變化較大，且在果實(shí)成熟過(guò)程中，糖類(lèi)和氨基酸呈現(xiàn)相反的變化趨勢(shì)[93]。農(nóng)產(chǎn)品在采后、儲(chǔ)藏過(guò)程中，營(yíng)養(yǎng)成分會(huì)發(fā)生轉(zhuǎn)化或降解，對(duì)其營(yíng)養(yǎng)品質(zhì)產(chǎn)生影響。OMS-OLIU等[94]鑒定發(fā)現(xiàn)，甘露糖、檸檬酸、葡萄糖酸和酮-1-古洛糖酸等4種代謝產(chǎn)物與番茄采后階段密切相關(guān)。JOHNSON等[48]研究了不同儲(chǔ)藏時(shí)間蛋黃內(nèi)小分子代謝物的變化規(guī)律，確定膽堿為不同儲(chǔ)藏時(shí)間的差異代謝物，隨后靶向驗(yàn)證結(jié)果顯示，12周儲(chǔ)藏時(shí)間內(nèi)膽堿水平由6.8 μg?g-1上升至28.7 μg?g-1。

此外，外界環(huán)境以及灌溉、施肥、管理措施等因素均會(huì)對(duì)農(nóng)產(chǎn)品生長(zhǎng)發(fā)育過(guò)程中營(yíng)養(yǎng)品質(zhì)的變化規(guī)律產(chǎn)生影響[95]，借助代謝組學(xué)高通量檢測(cè)技術(shù)研究不同環(huán)境條件下農(nóng)產(chǎn)品的生物標(biāo)志物，可為農(nóng)產(chǎn)品的品質(zhì)優(yōu)化提供科學(xué)的指導(dǎo)意見(jiàn)。我國(guó)西南地區(qū)在大豆收獲期溫度低，濕度大，持續(xù)降雨天氣易導(dǎo)致霉菌爆發(fā)，DENG等[96]研究了豆莢、種皮和子葉對(duì)霉菌的抵抗機(jī)制，發(fā)現(xiàn)不同組織代謝輪廓存在差異，脯氨酸、賴(lài)氨酸和硫在子葉、種皮和豆莢代謝中發(fā)揮重要作用。

2.4 農(nóng)產(chǎn)品中營(yíng)養(yǎng)功能成分作用機(jī)制及對(duì)代謝的影響

代謝組學(xué)通過(guò)體液代謝譜和生物標(biāo)志物的檢測(cè)，可以系統(tǒng)性地研究營(yíng)養(yǎng)功能成分與生物體代謝之間的交互作用[97]，為營(yíng)養(yǎng)功能成分作用機(jī)制研究及膳食指導(dǎo)提供有價(jià)值的信息[98-99]。代謝組學(xué)為食藥兩用農(nóng)產(chǎn)品中功能成分作用機(jī)制研究提供了可靠便利的方法。LIU等[100]基于雄性C57BL/6小鼠模型，研究了生姜中姜精油（GEO）和檸檬醛的抗氧化能力和肝臟保護(hù)作用，采用HPLC-QTOF-MS分析技術(shù)對(duì)小鼠血清中的代謝產(chǎn)物進(jìn)行了分析，結(jié)果顯示，服用姜精油（GEO）和檸檬醛后，因食用含酒精液體飲食而導(dǎo)致的D-葡糖醛酸-6,3-內(nèi)酯、甘油-3-磷酸、丙酮酸、石膽酸、2-吡啶酸和前列腺素E1等異常代謝產(chǎn)物可恢復(fù)至正常水平，上述代謝產(chǎn)物的改變主要涉及碳代謝、氨基酸代謝等代謝通路。枸杞多糖（lycium barbarum polysaccharides，LBP）的降糖作用研究結(jié)果顯示[101]，枸杞多糖干預(yù)一個(gè)月后，2型糖尿病模型大鼠血清中丙氨酸、胸腺嘧啶脫氧核苷酸含量有所上升，氨基酸代謝和核苷酸代謝通路的確認(rèn)為進(jìn)一步研究LBP的降糖作用機(jī)制提供了參考。除小鼠和大鼠模型外，也有學(xué)者采用細(xì)胞模型分析農(nóng)產(chǎn)品中營(yíng)養(yǎng)素的作用機(jī)制，如FUJIMURA等[102]基于人臍靜脈內(nèi)皮細(xì)胞，研究了不同品種綠茶抑制肌球蛋白調(diào)節(jié)輕鏈（MRLC）磷酸化的活性，分析獲得了能夠顯著抑制MRLC磷酸化的品種，并發(fā)現(xiàn)多酚含量與其獨(dú)特的代謝特征和生物活性相關(guān)。

此外，通過(guò)對(duì)膳食攝入后人體尿液、血液、糞便等生物樣本的研究，代謝組學(xué)可以了解機(jī)體對(duì)單一物質(zhì)或復(fù)雜物質(zhì)的代謝應(yīng)答[103-104]，從而為全面考察農(nóng)產(chǎn)品攝入對(duì)機(jī)體代謝的影響提供參考[105-106]。邊會(huì)喜[107]基于小鼠模型研究了苦瓜及苦瓜的不同提取組分對(duì)降低血脂的作用，通過(guò)對(duì)尿液樣本的NMR代謝組分析識(shí)別了37種差異代謝物，確定了泛酸和輔酶a合成、淀粉和蔗糖代謝、三羧酸循環(huán)等3條主要作用途徑，發(fā)現(xiàn)苦瓜的正丁醇提取物和胰島素對(duì)小鼠體重及多種脂肪組織的抵抗效應(yīng)高于其他提取物。人體尿液樣品的代謝譜分析發(fā)現(xiàn)[108]，適量飲用白茶使機(jī)體內(nèi)馬尿酸和檸檬酸上調(diào)、肌酐下降。1H-NMR光譜技術(shù)結(jié)合多元統(tǒng)計(jì)分析研究素食、少肉、多肉3種飲食模式對(duì)人體代謝的影響顯示，肌酸、肉堿、乙酰肉堿和三甲胺-N-氧化物等代謝物在多肉飲食模式中含量較高，而對(duì)-羥基苯基在素食飲食模式下含量較高[109]。

3 展望

隨著組學(xué)技術(shù)的不斷發(fā)展和完善，代謝組學(xué)技術(shù)將在農(nóng)產(chǎn)品營(yíng)養(yǎng)品質(zhì)檢測(cè)分析中發(fā)揮越來(lái)越重要的作用，該類(lèi)技術(shù)在提升農(nóng)產(chǎn)品營(yíng)養(yǎng)的同時(shí)還有助于提升農(nóng)產(chǎn)品品質(zhì)，對(duì)農(nóng)產(chǎn)品育種策略、種養(yǎng)模式調(diào)整和膳食指導(dǎo)等方面具有重要指導(dǎo)意義。然而，當(dāng)前階段組學(xué)分析中存在樣品分析結(jié)果不穩(wěn)定、儀器分析范圍局限和數(shù)據(jù)庫(kù)不完善等諸多挑戰(zhàn)，因此，如何優(yōu)化代謝組學(xué)的樣品前處理技術(shù)，建立高通量的檢測(cè)技術(shù)，如何使數(shù)據(jù)處理過(guò)程更加標(biāo)準(zhǔn)和規(guī)范，以便獲得更多更準(zhǔn)確的代謝物信息，在取樣方法、分析技術(shù)研發(fā)和數(shù)據(jù)庫(kù)構(gòu)建等方面，都需要進(jìn)一步的研究。另外，基于代謝組學(xué)技術(shù)發(fā)現(xiàn)了許多農(nóng)產(chǎn)品中的生物標(biāo)志物，但對(duì)農(nóng)產(chǎn)品中生物活性成分的作用機(jī)制研究還不夠系統(tǒng)和深入，需結(jié)合基因組學(xué)、轉(zhuǎn)錄組學(xué)和蛋白組學(xué)等組學(xué)技術(shù)，形成系統(tǒng)生物學(xué)數(shù)據(jù)鏈，通過(guò)多組學(xué)聯(lián)合分析技術(shù)，從表型-通路等多角度解釋功能活性成分的作用機(jī)制，為膳食結(jié)構(gòu)的優(yōu)化調(diào)整提供技術(shù)手段。

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Review on the Application of Metabolomic Approaches to Investigate and Analysis the Nutrition and Quality of Agro-products

XU YanYang1, YAO GuiXiao1, 3, LIU PingXiang1, ZHAO Jie1, WANG XinLu1, SUN JunMao2, QIAN YongZhong1

(1Institute of Quality Standards and Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences/Key Laboratory of Agro-Product Quality and Safety, Ministry of Agriculture and Rural Affairs, Beijing 100081;2Institute of Food and Nutrition Development, Ministry of Agriculture and Rural Affairs, Beijing 100081;3Xi’an University of Technology, Xi’an 710048)

Scientific evaluation of the nutrition and quality of agricultural products is essential for improving the nutrition level of agro-products. Because of the complex composition of nutrients in agro-products, the existing analytical methods can only analyze the concentration and function of known nutrients but cannot analyze and identify a large number of unknown functional substances. On the basis of high-throughput chemical analyses, metabolomics can qualitatively and quantitatively analyze endogenous and exogenous metabolites of biological samples. Therefore, metabolomics has outstanding advantages in the analysis of small molecular substances with special nutritional functions in agricultural products; it has advantages like providing new methods for the characterization and differential analysis of nutrient components, traceability and authenticity of identification, variation analysis of functional substances during growth and storage, and the effect mechanisms of functional components. It also provides new strategies for structural optimization of dietary requirements. In this paper, the recent advances in metabolomics research, including sample preparation, metabolite analysis, data processing, differential metabolite identification, and metabolic pathway analysis were reviewed. This work summed up the application of metabolomics in the characterization and difference analysis of metabolites, traceability and authenticity identification of origin, metabolite variation in the process of storage, and the evaluation of nutritional functions to provide theoretical bases and practical references for high-quality agricultural development in China. In the field of sample preparation, the activity of metabolism-related enzymes is first terminated by rapidly changing the environmental conditions, such as adding strong acid (alkali) or freezing in liquid nitrogen. Different extraction solvents are selected based on the polarities of the metabolites to obtain a higher extraction rate. In the field of sample analysis methods, technologies, such as nuclear magnetic resonance spectroscopy, chromatography mass spectrometry and capillary electrophoresis-mass spectrometry, have been widely used. Among them, the combination of chromatography and mass spectrometry has become the most commonly used analytical technique in metabolomics. In the field of data processing and analysis, principal component analysis and orthogonal partial least squares-discriminant analysis are the most common data analysis techniques. Through enrichment and topological analysis, the metabolic pathway with the highest correlation to differential metabolites can be identified, and the reason of differential metabolites can be explained and analyzed. In the field of evaluation of nutrition and quality of agricultural products, through the comprehensive characterization of primary metabolites and secondary metabolites in agricultural products, unique fingerprints of agricultural products are established and used for differential analysis, whereas through non-specific target analysis and unsupervised analysis methods, differences between groups and relating metabolites can be identified. Via concentration analysis of key components in the growth process of agricultural products, the best harvest periods can be provided. Interaction studies between functional components and metabolism of organisms based on the detection of humoral metabolism and biomarkers can provide valuable information for dietary guidance.

metabolomics; agro-product; nutrition; quality

10.3864/j.issn.0578-1752.2019.18.009

2019-02-22；

2019-04-23

國(guó)家自然科學(xué)基金（31701519）、科技部食品安全關(guān)鍵技術(shù)研發(fā)專(zhuān)項(xiàng)（2017YFC1600705）

許彥陽(yáng)，Tel：010-82106539；E-mail：xuyanyang@caas.cn。

錢(qián)永忠，Tel：010-82106298；E-mail：qianyongzhong@caas.cn。通信作者孫君茂，Tel：010-82109887；E-mail：sunjunmao@caas.cn

（責(zé)任編輯 趙伶俐）