陳 雪,羅 欣,2,梁榮蓉,朱立賢,楊嘯吟,韓明山,成海建,張一敏
代謝組學(xué)在肉及肉制品品質(zhì)監(jiān)測(cè)中的應(yīng)用
陳 雪1,羅 欣1,2,梁榮蓉1,朱立賢1,楊嘯吟1,韓明山3,成海建4,張一敏1※
(1. 山東農(nóng)業(yè)大學(xué)食品科學(xué)與工程學(xué)院,泰安 271018;2. 江蘇省肉類生產(chǎn)與加工質(zhì)量安全控制協(xié)同創(chuàng)新中心,南京 210095;3. 國(guó)家肉牛牦牛產(chǎn)業(yè)技術(shù)體系通遼站,通遼 028100;4. 國(guó)家肉牛牦牛產(chǎn)業(yè)技術(shù)體系濟(jì)南站,濟(jì)南 250000)
代謝組學(xué)是通過研究機(jī)體受外界干擾前后小分子代謝物(分子量<1 500 Da)的變化,進(jìn)而探究其代謝機(jī)制的新興科學(xué)。近年來,代謝組學(xué)在肉品科學(xué)研究領(lǐng)域受到廣泛關(guān)注。但目前基于該技術(shù)監(jiān)測(cè)宰前因素(遺傳因素、肌肉部位及飼喂方式)及宰后成熟(時(shí)間、方式)對(duì)肉及肉制品品質(zhì)影響的相關(guān)研究仍缺乏系統(tǒng)總結(jié)。同時(shí),代謝組學(xué)技術(shù)的引入,也為肉品貨架期預(yù)測(cè)、肉制品加工工藝優(yōu)選、產(chǎn)地溯源及真?zhèn)舞b別提供了新的思路。因此,該研究概述了近年來代謝組學(xué)常用的分析檢測(cè)技術(shù)(核磁共振技術(shù)、氣相色譜質(zhì)譜聯(lián)用技術(shù)、液相色譜質(zhì)譜聯(lián)用技術(shù))及數(shù)理統(tǒng)計(jì)方法(主成分分析、偏最小二乘判別分析等),重點(diǎn)對(duì)代謝組學(xué)在肉品生產(chǎn)諸多環(huán)節(jié)(動(dòng)物飼喂、屠宰、加工等)中的最新研究進(jìn)展進(jìn)行綜述,最后總結(jié)了目前肉品代謝組學(xué)研究中存在的代謝產(chǎn)物檢測(cè)有限、試驗(yàn)重復(fù)性差等問題并認(rèn)為多組學(xué)聯(lián)合分析是監(jiān)測(cè)肉品品質(zhì)的未來發(fā)展方向,以期為其在肉品科學(xué)領(lǐng)域的應(yīng)用提供參考。
肉;品質(zhì)控制;代謝組學(xué);貨架期;溯源;生物標(biāo)記物
肉品是消費(fèi)者膳食營(yíng)養(yǎng)的重要來源。近年來隨著生活水平的改善,消費(fèi)者對(duì)肉品品質(zhì)的關(guān)注度也逐漸提高。在肉類生產(chǎn)過程中,由于受到各環(huán)節(jié)諸多因素的影響,肉品的生化代謝過程也隨之發(fā)生改變,導(dǎo)致其品質(zhì)產(chǎn)生差異。因此,改善和提高肉品質(zhì)量對(duì)整個(gè)行業(yè)的發(fā)展具有重要意義。為此,現(xiàn)代肉品科學(xué)領(lǐng)域引入了代謝組學(xué)技術(shù)。代謝組學(xué)是繼蛋白質(zhì)組學(xué)、基因組學(xué)和轉(zhuǎn)錄組學(xué)之后系統(tǒng)生物學(xué)的重要分支,以高通量檢測(cè)技術(shù)和多元數(shù)據(jù)處理為手段,通過研究機(jī)體受干擾前后小分子代謝物(分子量<1 500 Da)的變化,進(jìn)而探究其代謝機(jī)制的新興科學(xué)[1-2]。近年來,代謝組學(xué)技術(shù)在肉品科學(xué)領(lǐng)域的研究與應(yīng)用不斷拓展,涉及動(dòng)物飼養(yǎng)-屠宰、加工-銷售多個(gè)方面[3]。而基于代謝圖譜分析和代謝標(biāo)志物的篩選有助于揭示上述生產(chǎn)環(huán)節(jié)諸多因素對(duì)肉品品質(zhì)的影響,完善從農(nóng)場(chǎng)至餐桌的“全鏈條”質(zhì)量監(jiān)控,已經(jīng)成為當(dāng)前的研究熱點(diǎn)。因此,本文從宰前因素(如遺傳因素、肌肉部位及飼喂方式等)、宰后成熟(時(shí)間、方式)、肉制品加工、貨架期預(yù)測(cè)、產(chǎn)地鑒別和摻假檢驗(yàn)等多個(gè)方面對(duì)代謝組學(xué)技術(shù)在肉品科學(xué)領(lǐng)域的最新研究成果進(jìn)行綜述,旨在為進(jìn)一步推動(dòng)代謝組學(xué)技術(shù)在肉品科學(xué)中的應(yīng)用提供理論支持。
1.1.1 核磁共振技術(shù)
核磁共振技術(shù)(Nuclear Magnetic Resonance spectroscopy,NMR)是目前肉品代謝組學(xué)研究中應(yīng)用最廣泛的檢測(cè)技術(shù),該技術(shù)的優(yōu)勢(shì)在于樣品前處理簡(jiǎn)單,可對(duì)所分析樣品實(shí)現(xiàn)無損檢測(cè)和無偏向分析,同時(shí)能夠進(jìn)行實(shí)時(shí)和動(dòng)態(tài)檢測(cè)[4-5]。目前,常用的有氫譜(1H-NMR)、碳譜(13C-NMR)和磷譜(31P-NMR)技術(shù),其中1H-NMR對(duì)含氫化合物均有響應(yīng),能實(shí)現(xiàn)樣品中絕大多數(shù)物質(zhì)的檢測(cè)[6],在肉品科學(xué)領(lǐng)域應(yīng)用最為廣泛,涉及品質(zhì)判別、真?zhèn)螜z驗(yàn)及加工肉制品品質(zhì)控制等多個(gè)方面[7-8]。但NMR技術(shù)也存在檢測(cè)靈敏度相對(duì)較低,對(duì)痕量物質(zhì)檢測(cè)存在誤差等缺點(diǎn)。近年來新發(fā)展的多維核磁共振技術(shù)(Multidimensional NMR,MNMR)、高效液相色譜-核磁共振聯(lián)用(High Performance Liquid Chromatography- Nuclear Magnetic Resonance Spectroscopy,LC-NMR)及高分辨魔角旋轉(zhuǎn)磁共振波譜(High-Resolution Magic Angle Spinning MR Spectroscopy,HRMAS MRS)等技術(shù)彌補(bǔ)了這一缺陷,提高了檢測(cè)分辨率,使基于NMR的肉品代謝組學(xué)研究日趨完善。
1.1.2 氣相色譜-質(zhì)譜聯(lián)用技術(shù)
氣相色譜-質(zhì)譜聯(lián)用技術(shù)(Gas Chromatography-Mass Spectroscopy,GC-MS)具有較高的分辨率、重現(xiàn)性和檢測(cè)靈敏度,可實(shí)現(xiàn)多組分混合物中未知組分的定性分析[9],是目前代謝組學(xué)研究中最成熟的分析技術(shù)。其中頂空固相微萃取-氣相色譜-質(zhì)譜聯(lián)用技術(shù)(Headspace Solid-Phase Microextraction-Gas Chromatography-Mass Spectrometry,HS-SPME-GC-MS)在肉品科學(xué)中應(yīng)用較為廣泛,特別適用于分析揮發(fā)性的化合物,主要用于揭示不同肉品之間風(fēng)味差異的潛在機(jī)制或預(yù)測(cè)貯藏期間肉品的貨架期[10-15]。但GC-MS也存在一定的局限性,分析難揮發(fā)的代謝組分需經(jīng)過衍生化處理(硅烷化試劑反應(yīng)、烷基化反應(yīng)和酰基化反應(yīng)),若衍生方法應(yīng)用不當(dāng),則會(huì)影響其檢測(cè)靈敏度[16]。
1.1.3 液相色譜-質(zhì)譜聯(lián)用技術(shù)
液相色譜-質(zhì)譜聯(lián)用技術(shù)(High Performance Liquid Chromatography - Mass Spectroscopy,LC-MS)不需要對(duì)代謝物進(jìn)行衍生化處理,即可進(jìn)行定性和定量分析,具有較高的分辨率、檢測(cè)靈敏度和分析速度,適合沸點(diǎn)高、極性強(qiáng)的化合物分析,應(yīng)用范圍更廣,尤其適合代謝產(chǎn)物的代謝輪廓分析[17]。目前該技術(shù)已經(jīng)成為肉品代謝組學(xué)研究中強(qiáng)有力的手段,主要用于分析宰后肌肉能量代謝變化,旨在從代謝層面完善肌肉到食用肉轉(zhuǎn)化的內(nèi)在生物機(jī)制[18-19]。但該技術(shù)也尚存在系統(tǒng)穩(wěn)定性和輪廓譜重現(xiàn)性差,分析時(shí)間長(zhǎng),進(jìn)行單一分析時(shí)得到的分析物有限等問題[20]。針對(duì)這些不足,超高效液相色譜-質(zhì)譜聯(lián)用、毛細(xì)管柱液相色譜-質(zhì)譜聯(lián)用、多維液相色譜-質(zhì)譜聯(lián)用技術(shù)(High Performance Liquid Chromatography - Mass Spectroscopy,HPLC-MS)等在其基礎(chǔ)上應(yīng)運(yùn)而生,有效提高了對(duì)復(fù)雜樣品的檢測(cè)效率。
肉品代謝產(chǎn)物的復(fù)雜多樣性使得對(duì)分析技術(shù)的靈敏度、分辨率、通量等提出更高的要求。但目前基于某一檢測(cè)技術(shù)尚不能全面覆蓋肉品中的代謝產(chǎn)物信息[21]。有學(xué)者提出將LC-MS、NMR和GC-MS聯(lián)合應(yīng)用可為探究肉品品質(zhì)的調(diào)控機(jī)制提供更加全面的視角[22]。如,Warner等[23]就基于NMR和HPLC技術(shù),發(fā)現(xiàn)肌苷酸(Inosine Monophosphate,IMP)對(duì)肌動(dòng)球蛋白的弱化作用可能是超快速冷卻對(duì)嫩化牛肉的一大原因。由此可見,為提高代謝組學(xué)技術(shù)在肉品科學(xué)中的應(yīng)用潛力,多平臺(tái)集成聯(lián)合將會(huì)是未來的發(fā)展方向。
肉品代謝組學(xué)研究中通過高通量分析儀器生成的海量、高維、高噪聲、高變異性的數(shù)據(jù),需要采用化學(xué)計(jì)量學(xué)(主要為模式識(shí)別技術(shù))和生物信息學(xué)技術(shù)對(duì)其進(jìn)行降維歸類處理后才能有效地篩選出生物標(biāo)志物[24]。常用的模式識(shí)別方法主要包括兩種,一種為非監(jiān)督學(xué)習(xí)方法,如主成分分析(Principal Component Analysis,PCA)、聚類分析(Cluster Analysis,CA)、非線性映射(Nonlinear Mapping,NLM);另一種為有監(jiān)督學(xué)習(xí)方法,如K最鄰近法(K-Nearest Neighbor Classification method,K-NN),辨別分析(Discriminate Analysis,DA)、偏最小二乘判別分析(Partial Least Squares Discrimination Analysis,PLS-DA)、基于正交信號(hào)校正的偏最小二乘判別分(Orthogonal-PLS-DA,OPLS-DA)、人工神經(jīng)網(wǎng)絡(luò)(Artificial Neural Network,ANN)、支持向量機(jī)(Support Vector Machine, SVM)等[17]。其中PCA和PLS-DA是肉品代謝組學(xué)研究中最常用的模式識(shí)別方法[25-26]。這兩種方法通常以得分圖獲得對(duì)樣品分類的信息,載荷圖獲得對(duì)分類有貢獻(xiàn)的變量及其貢獻(xiàn)大小,從而用于發(fā)現(xiàn)可作為生物標(biāo)志物的變量。
本節(jié)分別從宰前因素(如遺傳因素、肌肉部位及飼喂方式等)、宰后成熟(時(shí)間、方式)、肉制品加工、貨架期預(yù)測(cè)、產(chǎn)地鑒別和摻假檢驗(yàn)等多個(gè)方面對(duì)代謝組學(xué)技術(shù)在肉品科學(xué)領(lǐng)域的最新研究成果進(jìn)行綜述,如圖1所示。
圖1 代謝組學(xué)在肉及肉制品品質(zhì)監(jiān)測(cè)中的應(yīng)用
2.1.1 遺傳因素(品種、年齡等)
動(dòng)物的品種、年齡及雜交種的親本等均會(huì)影響肉的品質(zhì),明確這些因素與某些特征代謝產(chǎn)物之間的聯(lián)系有助于揭示其品質(zhì)差異機(jī)制,并為優(yōu)質(zhì)肉類資源的開發(fā)提供理論支持。近年來,相關(guān)學(xué)者就基于代謝組學(xué)技術(shù)對(duì)牛肉、羊、豬、雞、鴨的種內(nèi)品質(zhì)差異進(jìn)行了研究(表1)。Gomez等[27]篩選出內(nèi)洛爾牛和內(nèi)洛爾?!涟哺袼闺s交牛之間乙酰肉堿、丙氨酸等15種關(guān)鍵差異代謝產(chǎn)物,主要涉及谷氨酰胺和谷氨酸代謝、纈氨酸、亮氨酸和異亮氨酸生物合成、谷胱甘肽代謝等通路。Straadt等[28]分析了5種雜交豬肉的代謝圖譜,發(fā)現(xiàn)了丙氨酸、肌肽及含膽堿化合物等10余種標(biāo)志性代謝物,信息學(xué)分析發(fā)現(xiàn):這主要?dú)w因于不同種間宰前能量代謝、肌纖維膜性質(zhì)、糖酵解潛力以及蛋白質(zhì)和脂肪水解程度的差異。此外,代謝產(chǎn)物的種類及豐度也是影響禽肉食用品質(zhì)的重要因素。Wang等[29]和Kim[30]分別對(duì)不同品種的雞肉和鴨肉進(jìn)行了代謝組學(xué)分析,并鑒定出多種特征代謝產(chǎn)物為地方品種的保護(hù)提供了有力支持。
總體來看,目前的研究已經(jīng)證實(shí)能量代謝、氨基酸代謝、蛋白質(zhì)或脂肪水解程度等的不同是導(dǎo)致品種間肉質(zhì)差異的重要原因。但關(guān)于上述代謝通路與表型之間的相關(guān)性分析相對(duì)較少,因此,未來可基于靶向代謝組學(xué)技術(shù)進(jìn)一步明確差異代謝物對(duì)不同品種肉質(zhì)的潛在影響。
另外,動(dòng)物在生長(zhǎng)過程中其代謝水平的改變也貫穿始終。因此,借助小分子代謝產(chǎn)物(如鵝肌肽和肌肽等)有助于對(duì)肉品質(zhì)量進(jìn)行合理評(píng)估,進(jìn)而優(yōu)選出最佳的養(yǎng)殖時(shí)間[31]。Liu等[32]發(fā)現(xiàn)隨日齡(27~500 d)的增加櫻桃谷鴨肉中乳酸和鵝肌肽的含量增加,而延胡索酸、甜菜堿、?;撬帷⒓≤盏葏s呈現(xiàn)降低趨勢(shì)。綜合考慮(嫩度、風(fēng)味、持水力等),50 d日齡的櫻桃谷鴨品質(zhì)最優(yōu)。此外,還有學(xué)者對(duì)比了不同日齡(110~230 d)武定雞的代謝圖譜,發(fā)現(xiàn)140 d日齡的武定雞中牛磺酸和肌肽及其相關(guān)化合物(Carnosine Related Compounds,CRCs)含量最高且與其他組間總代謝產(chǎn)物無顯著差異;主要通過丙氨酸、天門冬氨酸和谷氨酸代謝、嘌呤代謝、甘氨酸、絲氨酸和蘇氨酸代謝等生化通路來調(diào)控不同日齡雞肉的風(fēng)味[33]。除上述代謝產(chǎn)物外,后續(xù)研究中也需重點(diǎn)關(guān)注脂肪酸等風(fēng)味前體物質(zhì)的變化??傮w來看,基于代謝圖譜可以輔助對(duì)由年齡導(dǎo)致的禽肉肉質(zhì)差異進(jìn)行綜合分析。
表1 代謝組學(xué)在研究不同品種肉品質(zhì)中的應(yīng)用
2.1.2 肌肉部位
不同部位肌肉間在代謝水平上(糖酵解、TCA循環(huán)、核苷酸代謝等)的差異,也會(huì)進(jìn)一步影響肌肉到食用肉的轉(zhuǎn)化及后續(xù)貯藏期間的品質(zhì)[34]?;诖x組學(xué)技術(shù),England等[18]發(fā)現(xiàn)與糖酵解相關(guān)的內(nèi)在生物因素(糖酵解相關(guān)內(nèi)源酶的豐度、三磷酸腺苷(Adenosine Triphosphate,ATP)等是調(diào)控豬肉宰后24 h酵解型肌肉和氧化型肌肉pH值下降速率的關(guān)鍵。亦有學(xué)者發(fā)現(xiàn)親水氨基酸和-丙氨酸及相關(guān)化合物與牛肉部位(背最長(zhǎng)?。?,LL)和骨中間?。?,VI))存在一定的相關(guān)性;代謝通路分析顯示糖酵解代謝、嘌呤代謝、氨基酸及多肽等生化通路對(duì)兩部位肌肉品質(zhì)起調(diào)控作用[34]。此外,LL和半膜?。?,SM)之間的宰后早期代謝模式也存在不同,其中內(nèi)源酶(如乳酸脫氫酶、蘋果酸脫氫酶等)的活性、丙酮酸的含量以及涉及三羧酸循環(huán)的代謝產(chǎn)物等均存在一定的差異[19]。與此同時(shí),該學(xué)者在研究中也證實(shí)了牛肉不同部位肌肉宰后早期有氧代謝時(shí)間及強(qiáng)度、糖酵解潛力等的差異是影響其貯藏及零售期間品質(zhì)的重要因素[19]。
目前,關(guān)于不同部位肌肉的生化代謝機(jī)制研究仍然十分有限,雖然已經(jīng)初步表明宰后早期能量代謝是導(dǎo)致肉質(zhì)差異的關(guān)鍵,但基于特征代謝產(chǎn)物對(duì)于不同部位肌肉肉質(zhì)特性的調(diào)控機(jī)制尚不明確。因此,后期需進(jìn)一步完善研究策略,可采用多組學(xué)集成聯(lián)合將有助于更加系統(tǒng)地闡明不同部位肌肉到食用肉轉(zhuǎn)化的生化機(jī)制及其對(duì)后續(xù)品質(zhì)的影響。
2.1.3 飼喂方式
飼喂方式(日糧等)不僅影響動(dòng)物的生產(chǎn)性能,也會(huì)對(duì)其宰后肉的品質(zhì)及代謝產(chǎn)物產(chǎn)生影響。Antonelo等[35]研究發(fā)現(xiàn)與飼喂基礎(chǔ)日糧相比,添加3.5%大豆油會(huì)影響牛肉中甜菜堿、甘油、延胡索酸和肌肽等代謝物質(zhì)的含量,可能通過調(diào)控甘油酯類物質(zhì)代謝、甘氨酸、絲氨酸和蘇氨酸代謝,谷氨酰胺和谷氨酸代謝等通路,最終導(dǎo)致其較差的感官品質(zhì)。若日糧添加抗氧化成分可通過影響肌肉代謝,提高宰后肉的抗氧化能力。Zawadzki等[36]對(duì)比了日糧中添加不同濃度的巴拉圭茶提取物對(duì)牛肉品質(zhì)及代謝產(chǎn)物的影響。結(jié)果發(fā)現(xiàn):在不影響動(dòng)物生產(chǎn)性能的情況下飼喂添加該物質(zhì)可提高肉中磷酸肌酸、肌酸、肌肽以及共軛亞油酸的含量,降低自由基的形成趨勢(shì),提高牛肉的氧化穩(wěn)定性。類似的,Baira等[37]發(fā)現(xiàn)在肉雞日糧中添加橙皮苷(1.5 g/kg)可增加宰后肉品中的?;鈮A和脂肪酸的水平,降低脂質(zhì)氧化程度。由此可見,基于宰后代謝組學(xué)的研究結(jié)果不僅能夠有效區(qū)分飼喂方式的不同,同時(shí)也能為肉品品質(zhì)的改善提供新的解決方案。
宰后成熟是改善肉品適口性的重要過程,期間隨脂肪酸、氨基酸的氧化以及蛋白質(zhì)的降解等,會(huì)產(chǎn)生與肉風(fēng)味相關(guān)的多種代謝產(chǎn)物。如氨基酸類(谷氨酸、蛋氨酸、亮氨酸等)可促進(jìn)肉的滋味;核苷酸類(肌苷酸(Inosine Monophosphate,IMP),鳥苷酸等)可促進(jìn)肉的鮮味[38]。Koutsidis等[39]采用GC-MS技術(shù)對(duì)牛肉成熟期間生成的代謝產(chǎn)物進(jìn)行研究,發(fā)現(xiàn)苯丙氨酸、蛋氨酸、賴氨酸、亮氨酸和異亮氨酸等均逐漸增加,其中甲硫氨酸豐度增長(zhǎng)近7倍。Consolo等[40]也發(fā)現(xiàn)牛肉成熟21 d后代謝產(chǎn)物豐度增加了近1/3,其中大部分代謝物質(zhì)對(duì)肉的風(fēng)味有促進(jìn)作用。另外,還有學(xué)者指出牛肉成熟期間纈氨酸、亮氨酸和異亮氨酸與成熟時(shí)間具有良好的相關(guān)性[41]。因此,基于代謝組學(xué)技術(shù),有望預(yù)測(cè)肉牛宰后的成熟時(shí)間。
成熟方式也會(huì)影響肉的風(fēng)味,有學(xué)者研究發(fā)現(xiàn)與濕法成熟相比,干法成熟會(huì)提高生鮮肉特有風(fēng)味[42]。為了進(jìn)一步明確這一原因,Kim等[43]對(duì)比了牛肉在不同成熟方式下的代謝產(chǎn)物。發(fā)現(xiàn)相較于濕法成熟,干法成熟會(huì)提高牛肉中谷氨酸等多種氨基酸等的含量,但I(xiàn)MP的含量卻低于濕法成熟牛肉,這一結(jié)果也初步表明可能是由于干法成熟方式下蛋白水解程度更高所致。Mungure[44]也發(fā)現(xiàn)干法成熟會(huì)促進(jìn)鹿肉中某些呈味氨基酸的產(chǎn)生。但干法成熟由于過多的汁液損失和修整損失也使得其出品率較濕法成熟低。為了改善這一不足,Zhang[45]嘗試采用逐步成熟的方式(先干法成熟7d,后濕法成熟14 d),發(fā)現(xiàn)這一成熟方式可提高牛肉中磷脂酰膽堿、磷脂酰乙醇胺和谷氨酸等代謝產(chǎn)物的含量,在改善風(fēng)味的同時(shí)提高了出品率??梢娊柚x組學(xué)技術(shù)能有效監(jiān)測(cè)期間呈味小分子物質(zhì)的變化,并為成熟方式的優(yōu)化提供理論參考。
微生物過度增殖導(dǎo)致的肉類腐敗也一直是困擾肉類工業(yè)的重要問題[46]。貯藏期間,致腐微生物會(huì)優(yōu)先利用肉中的葡萄糖作為能量物質(zhì),當(dāng)葡萄糖消耗殆盡時(shí)其他物質(zhì)(如乳酸、丙酮酸、氨基酸、核苷酸等)也會(huì)被分解代謝[47]。由此,借助代謝組學(xué)技術(shù)可以通過監(jiān)測(cè)產(chǎn)生的初級(jí)代謝產(chǎn)物及多種腐敗氣味分子(醇類、醛類等)預(yù)測(cè)肉類的腐敗程度[48]。如表2所示,Argyri等[49]研究了不同包裝及貯藏條件下碎牛肉的代謝產(chǎn)物,發(fā)現(xiàn)有機(jī)酸可以作為標(biāo)志牛肉腐敗程度的潛在物質(zhì)。Frank等[11]也發(fā)現(xiàn)乳酸為真空包裝牛肉冰溫貯藏期間的典型代謝產(chǎn)物。
肉品貯藏期間由微生物代謝產(chǎn)生的揮發(fā)性物質(zhì)(Volatile Organic Compounds,VOCs)主要包括醇類、醛類、酯類、揮發(fā)性脂肪酸、硫化物等[47]。近年來相關(guān)學(xué)者對(duì)這些VOCs進(jìn)行廣泛的研究,并確定了多個(gè)與肉品腐敗相關(guān)的生物標(biāo)志物(表2)。其中,對(duì)于包裝方式而言,不同氣體成分會(huì)影響肉的菌群結(jié)構(gòu),并激發(fā)特定腐敗菌(Specific Spoilage Organisms,SSOs)啟動(dòng)相應(yīng)的代謝通路,導(dǎo)致肉品腐敗時(shí)釋放出特征VOCs。眾多學(xué)者研究發(fā)現(xiàn)透氧托盤包裝條件下,2,3-丁二醇、2-丁酮、二乙酰、乙偶姻等為潛在的腐敗標(biāo)志物[12-13,15],主要?dú)w因于假單胞菌、熱殺索絲菌等優(yōu)勢(shì)腐敗菌的生長(zhǎng)代謝;真空包裝條件下,乙酸、丁酸、戊酸等有機(jī)酸為典型的VOCs[13-14,48],主要與乳酸菌等微生物密切相關(guān);高氧氣調(diào)包裝下乙偶姻和己酸等為多種優(yōu)勢(shì)腐敗菌產(chǎn)生的特征VOCs[13-14]。另外,VOCs也受基質(zhì)中營(yíng)養(yǎng)物質(zhì)可利用程度等內(nèi)在因素及微生物污染狀況等外在因素的影響,使得不同研究結(jié)果稍有差異。但基于目前的研究,關(guān)于肉中致腐微生物代謝活動(dòng)與其腐?。ǜ泄伲┲g的關(guān)系仍未完全闡明,且肉中的內(nèi)源酶及SSOs均能催化代謝反應(yīng)生成VOCs[54],使得據(jù)此對(duì)肉品貨架期進(jìn)行準(zhǔn)確評(píng)估還存在一定困難。
目前,代謝組學(xué)技術(shù)也被廣泛地用于監(jiān)控、預(yù)測(cè)肉制品不同加工階段品質(zhì)變化(表3)。García-García等[55]分析了西班牙發(fā)酵干香腸加工期間代謝產(chǎn)物變化,發(fā)現(xiàn)加工初期乳酸、肌酸/磷酸肌酸/肌肽信號(hào)占據(jù)主導(dǎo);發(fā)酵過程中(2 d)-葡萄糖、-葡萄糖含量降低,但乙醇、乳酸、乙酸以及氨基酸等含量逐漸增加,隨著干燥成熟的進(jìn)行,乙醇、乙酸和甲酸的含量顯著降低(<0.05),氨基酸信號(hào)增強(qiáng),有效實(shí)現(xiàn)了發(fā)酵香腸生產(chǎn)過程監(jiān)控。
醬鹵制品是中國(guó)傳統(tǒng)熟肉制品的典型代表,不同的加工工藝賦予了不同產(chǎn)品獨(dú)特風(fēng)味。但目前傳統(tǒng)手工作坊式生產(chǎn)仍占有較大比重。基于代謝組學(xué)技術(shù),有助于改進(jìn)其加工技術(shù),實(shí)現(xiàn)醬鹵制品的規(guī)?;a(chǎn)。Yang等[56]發(fā)現(xiàn)多種氨基酸、蔗糖、-葡萄糖、醋酸和肌酐等均隨鹵豬肘熟制時(shí)間(0~90 min)逐漸增加,其中熟制60 min和90 min時(shí)代謝產(chǎn)物豐度及感官品質(zhì)較高。Yang等[57]研究了150~300 MPa高壓腌制對(duì)于鹵肉制品代謝物的影響,發(fā)現(xiàn)高壓處理可提高大部分代謝產(chǎn)物含量,但壓力水平對(duì)于丙氨酸、乳酸、醋酸、甲酸、延胡索酸等物質(zhì)影響不顯著,最終優(yōu)選出150 MPa高壓腌制為最經(jīng)濟(jì)的改善鹵肉風(fēng)味的加工方式。依據(jù)代謝組學(xué)的研究結(jié)果,周楠楠等[58]發(fā)現(xiàn)相比于干糟,濕糟過程對(duì)糟鴨的滋味化合物影響更顯著。
較長(zhǎng)的加工周期是形成干腌火腿獨(dú)特風(fēng)味的關(guān)鍵,而這主要?dú)w因于加工期間所生成的多種小分子代謝產(chǎn)物。明確干腌火腿的呈味機(jī)制,將有助于縮短加工時(shí)間,提高產(chǎn)業(yè)效率。Zhang等[59]分析了干腌火腿不同加工階段代謝產(chǎn)物的變化。大部分代謝產(chǎn)物的含量隨加工時(shí)間逐漸增加,其中多種氨基酸,有機(jī)酸和核苷酸衍生物(次黃嘌呤氨基酸)等有助于最終產(chǎn)品風(fēng)味的改善。Sugimoto等[60]指出日本干腌火腿成熟540 d時(shí)鳥嘌呤和核苷酸含量以及谷氨酰胺和天冬酰胺在總氨基酸中占比最高,整體感官評(píng)分最佳。此外,Shi等[61]基于代謝組學(xué)探究了大河烏豬干腌火腿風(fēng)味及其形成機(jī)制,發(fā)現(xiàn)己醛、3-甲基丁醛、壬醛、辛醛為其特征風(fēng)味物質(zhì),主要來源于脂肪酸的氧化及氨基酸的降解。
表2 不同貯藏條件下肉及肉制品中(潛在)腐敗生物標(biāo)志物
注:TSQ為三重四極桿;PRT為質(zhì)子轉(zhuǎn)移反應(yīng);SPME為固相微萃??;TOF為飛行時(shí)間質(zhì)譜儀;FDA為多因素判別分析;HAC為層次聚類;NMDS為非度量多維尺度分析;MS/O為質(zhì)譜/嗅覺;PROC MIXED為混合線性模型。
Note:TSQ is Triple-Stage Quadrupole; PRT is Proton-Transfer-Reaction; SPME is Solid Phase Micro-Extraction; TOF is Time of Flight Mass Spectrometer; FDA is Factorial Discriminant Analysis; HAC is Hierarchical Agglomerative Clustering; NMDS is Non-Metric Multidimensional Scaling Analysis; MS/O is Mass Spectrometry/Olfactometry; PROC MIXED is mixed model.
如上所述,利用代謝組學(xué)技術(shù)能夠有效表征肉制品加工期間呈味物質(zhì)的變化,為其加工工藝的優(yōu)化奠定良好的理論基礎(chǔ)。另外,中國(guó)傳統(tǒng)肉制品種類繁多,采用該技術(shù)測(cè)定傳統(tǒng)肉制品的特征成分,有助于傳承優(yōu)良的加工工藝,預(yù)期將會(huì)為中國(guó)傳統(tǒng)肉制品產(chǎn)業(yè)的發(fā)展帶來良好契機(jī)。
產(chǎn)地溯源不僅是食品產(chǎn)業(yè)鏈風(fēng)險(xiǎn)監(jiān)測(cè)的有效措施,也是地理標(biāo)志產(chǎn)品保護(hù)的必要手段。不同產(chǎn)地肉及肉制品由于動(dòng)物飼喂、產(chǎn)品加工方式等的不同最終會(huì)導(dǎo)致其代謝產(chǎn)物存在差異(表3)。Shintu等[62]對(duì)來自5個(gè)國(guó)家的牛肉干進(jìn)行代謝組學(xué)分析,發(fā)現(xiàn)脯氨酸、苯丙氨酸、谷氨酸/谷氨酰胺、琥珀酸等可作為區(qū)分不同產(chǎn)地的特征代謝產(chǎn)物。此外,Jung等[63]分析了來自4個(gè)國(guó)家市售牛肉的代謝產(chǎn)物,發(fā)現(xiàn)琥珀酸、異亮氨酸、蛋氨酸、酪氨酸和纈氨酸在不同產(chǎn)地牛肉間差異顯著。除以上代謝產(chǎn)物外,脂質(zhì)在肉品中的分布也具有地域性特征,目前也已成功作為肉品產(chǎn)地溯源的靶標(biāo)。程碧君[64]基于脂肪酸圖譜,篩選出a-C18:3、C14:0、C17:0和MUFA作為我國(guó)四大牛肉主產(chǎn)區(qū)產(chǎn)地溯源的指標(biāo)體系并建立了溯源判別模型,整體判別率可達(dá)83.6%。Mi等[65]對(duì)中國(guó)不同地域豬肉進(jìn)行了脂質(zhì)代謝組分析,共鑒定出100種差異脂質(zhì)代謝產(chǎn)物,并建立了豬肉來源的定性辨別模型,正確辨別率可達(dá)91.1%。Vasilev等[66]也利用脂肪酸指紋圖譜實(shí)現(xiàn)了北馬其頓不同牧區(qū)羊肉的溯源。另外,穩(wěn)定同位素、礦物元素指紋圖譜技術(shù)等是也在肉品溯源研究中應(yīng)用較廣[70]。有學(xué)者將代謝組學(xué)與上述檢測(cè)技術(shù)聯(lián)合用于牛肉產(chǎn)品鑒別,有效提高了檢測(cè)準(zhǔn)確度[71]。
表3 代謝組學(xué)在肉制品加工、產(chǎn)地溯源及鑒別中的應(yīng)用
注:-C18:3為a-亞麻酸;C14:0為肉豆蔻酸;C17:0為十七烷酸;MUFA為單不飽和脂肪酸;C18:3n3為-亞麻酸甲酯;C18:1n9c為油酸甲酯;C20:5n3為二十碳五烯酸。
Note:-C18:3 is a-linolenic acid; C14:0 is myristic acid; C17:0 is heptadecanoic acid; MUFA is monounsaturated fatty acids; C18:3n3 is methyl linolenate; C18:1n9c is methyl oleate; C20:5n3 is eicosapentaenoic acid.
由此可見,代謝組學(xué)技術(shù)在肉品產(chǎn)地溯源研究中具有良好的應(yīng)用前景。但肉品代謝產(chǎn)物復(fù)雜,且受外界多種因素影響,使得該方法的重復(fù)性受到一定限制。因此,為提高甄別準(zhǔn)確度,后續(xù)研究中可將鑒別出的特異性代謝產(chǎn)物基于靶向代謝組學(xué)技術(shù)進(jìn)一步定量分析,有助于提高模型鑒別能力;或?qū)⒃摷夹g(shù)與其他分析技術(shù)聯(lián)合應(yīng)用于肉品產(chǎn)地溯源。
隨著肉類需求增多,在經(jīng)濟(jì)利益的驅(qū)使下食品產(chǎn)業(yè)鏈中摻雜摻假、以次充好問題時(shí)有發(fā)生,嚴(yán)重破壞了市場(chǎng)秩序,損害了消費(fèi)者的利益。目前,基于不同肉中的特征代謝產(chǎn)物的差異,已經(jīng)成功實(shí)現(xiàn)了牛肉、羊肉、豬肉等的有效鑒別(表3)。Pavlidis等[67]基于揮發(fā)性代謝產(chǎn)物對(duì)豬肉、牛肉及其混合肉進(jìn)行鑒別,發(fā)現(xiàn)庚醛、辛醛、丁醇等與牛肉樣品存在相關(guān)性;戊醛、己醛、癸醛等與豬肉樣品存在相關(guān)性;而2-丁醇、1-辛烯-3-醇等則是混合樣品典型的代謝產(chǎn)物。孟新濤等[68]建立了基于氣相離子遷移譜(GC Ion Mobility Spectrometry,GC-IMS)的羊肉摻假鑒別的新方法,發(fā)現(xiàn)當(dāng)羊肉中摻入豬肉比例大于5%時(shí),芝麻酚、2-乙基-1-己醇、2-戊酮等5種特征風(fēng)味物質(zhì)含量減少;當(dāng)羊肉中雞肉摻入比例達(dá)到10%時(shí),3-甲硫基丙醛、正己醇、反-2-辛烯醛等46種特征風(fēng)味物質(zhì)含量減少。另外,Jakes等[69]通過檢測(cè)牛肉和馬肉樣品中甘油三酯圖譜,發(fā)現(xiàn)馬肉中含有更高比例的不飽和脂肪酸,尤其是亞麻酸,依據(jù)代謝組學(xué)結(jié)果這兩種肉均可被有效的鑒別。目前,基于代謝組學(xué)技術(shù)對(duì)肉及肉制品的鑒別多基于對(duì)樣品小分子物質(zhì)整體輪廓進(jìn)行篩選。雖然該技術(shù)針對(duì)非特定目標(biāo)物的檢測(cè)優(yōu)勢(shì)明顯,但其特異性相對(duì)其他檢測(cè)技術(shù)(蛋白質(zhì)組學(xué)技術(shù)、DNA法、傳感器法等)較差。而且,代謝組學(xué)技術(shù)也存在耗時(shí)長(zhǎng)且操作復(fù)雜等缺陷,以至于在肉品摻雜摻假檢測(cè)中的應(yīng)用潛力仍受到一定限制。
代謝組學(xué)作為一種新興技術(shù),彌補(bǔ)了基因組學(xué)、蛋白質(zhì)組學(xué)等研究中的不足,在肉品科學(xué)領(lǐng)域展現(xiàn)出巨大的潛力和優(yōu)勢(shì)?;诖x組學(xué)技術(shù)有助于我們深入理解動(dòng)物的品種、年齡、飼喂及宰前管理方式等宰前因素及宰后條件對(duì)肉品品質(zhì)的影響,并為生鮮肉貨架期預(yù)測(cè)、肉制品加工工藝優(yōu)選等提供新的角度。
但目前關(guān)于肉品代謝組學(xué)研究仍存在一些問題。
1)與藥物學(xué)、醫(yī)學(xué)等領(lǐng)域相比,代謝組學(xué)在肉品科學(xué)中的應(yīng)用仍處于發(fā)展階段。同時(shí),肉品代謝產(chǎn)物復(fù)雜多樣,使得經(jīng)現(xiàn)有檢測(cè)技術(shù)識(shí)別出的代謝產(chǎn)物依然十分有限。因此,為提高代謝組學(xué)技術(shù)在肉品科學(xué)中的應(yīng)用潛力,多平臺(tái)集成聯(lián)合將會(huì)是未來的發(fā)展方向。
2)雖然現(xiàn)有的研究已經(jīng)獲取了大量涉及肉品品質(zhì)的差異代謝產(chǎn)物,但這些研究多是基于非靶向代謝組學(xué)技術(shù)對(duì)小分子代謝產(chǎn)物整體輪廓進(jìn)行篩選,雖然對(duì)非特定目標(biāo)物優(yōu)勢(shì)明顯,但實(shí)驗(yàn)的重復(fù)性較差。因此在肉品產(chǎn)地溯源、真?zhèn)舞b別等方面的應(yīng)用受到一定限制。此外,不同研究采用的檢測(cè)技術(shù)、分析方法等有所不同,使得研究結(jié)果有所差異。因此,今后可將識(shí)別出的差異代謝產(chǎn)物進(jìn)行定量分析,或通過驗(yàn)證實(shí)驗(yàn)進(jìn)一步明確特征代謝產(chǎn)物的影響機(jī)制。
3)目前肉品相關(guān)代謝物數(shù)據(jù)庫(kù)還不完善,以至于未能準(zhǔn)確建立代謝生物標(biāo)志物與肉品品質(zhì)之間的相關(guān)性。
另外,針對(duì)上述問題,今后也需在提高代謝組學(xué)檢測(cè)技術(shù)分辨率的基礎(chǔ)上,建立統(tǒng)一的數(shù)據(jù)分析方法;將代謝組學(xué)與其他組學(xué)(基因組學(xué)、蛋白質(zhì)組學(xué)等)整合分析,有助于生物信息挖掘和系統(tǒng)生物學(xué)集成,這也將為肉品品質(zhì)監(jiān)測(cè)及改善提供新的契機(jī)。
[1] Li S, Tian Y, Jiang P, et al. Recent advances in the application of metabolomics for food safety control and food quality analyses[J]. Critical Reviews in Food Science and Nutrition, 2020, 4: 1-22.
[2] Miggiels P, Wouters B, Westen Van G, et al. Novel technologies for metabolomics: More for less[J]. Trends in Analytical Chemistry, 2019, 120: 1-9.
[3] Muroya S, Ueda S, Komatsu T, et al. MEATabolomics: Muscle and meat metabolomics in domestic animals[J]. Metabolites, 2020, 10: 1-12.
[4] Liu X, Locasale J W. Metabolomics: A Primer[J]. Trends in Biochemical Sciences, 2017, 42(4): 274-284.
[5] Wishart D S. NMR metabolomics: A look ahead[J]. Journal of Magnetic Resonance, 2019, 306: 155-161.
[6] Takis P G, Ghini V, Tenori L, et al. Uniqueness of the NMR approach to metabolomics[J]. Trends in Analytical Chemistry, 2019, 120: 1-9.
[7] Purslow P P. New Aspects of Meat Quality[M]//Bertram H C. NMR Spectroscopy and NMR Metabolomics in Relation to Meat Quality. Cambridge: Woodhead Publishing, 2017: 355-371.
[8] 秦澤宇,王浩,溫榮欣,等. 基于核磁共振的代謝組學(xué)技術(shù)在肉品科學(xué)中的應(yīng)用[J]. 食品工業(yè)科技,2019,40(2):312-315.
Qin Zeyu, Wang Hao, Wen Rongxin, et al. Application of metabolomics based on nuclear magnetic resonance (NMR) in meat science[J]. Science and Technology of Food Industry, 2019, 40(2): 312-315. (in Chinese with English abstract)
[9] 李娟,任路靜,孫冠男,等. 氣相色譜-質(zhì)譜聯(lián)用技術(shù)及其在代謝組學(xué)中的應(yīng)用[J]. 生物工程學(xué)報(bào),2013,29(40):434-446.
Li Juan, Ren Lujing, Sun Guannan, et al. Gas chromatography-mass spectrometry (GC-MS) and its application in metabonomics[J]. Chinese Journal of Biotechnology, 2013, 29(40): 434-446. (in Chinese with English abstract)
[10] 劉暢,羅玉龍,竇露,等. 亞麻籽飼喂對(duì)蘇尼特羊肉風(fēng)味品質(zhì)的影響[J]. 農(nóng)業(yè)工程學(xué)報(bào),2019,35(21):304-311.
Liu Chang, Luo Yulong, Dou Lu, et al. Effect of feeding flaxseed on meat flavor quality of Sunit lambs[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2019, 35(21): 304-311.
[11] Frank D, Hughes J, Piyasiri U, et al. Volatile and non-volatile metabolite changes in 140-day stored vacuum packaged chilled beef and potential shelf life markers[J]. Meat Science. 2020, 161:108016.
[12] Argyri A A, Mallouchos A, Panagou E Z, et al. The dynamics of the HS/SPME-GC/MS as a tool to assess the spoilage of minced beef stored under different packaging and temperature conditions[J]. International Journal of Food Microbiology, 2015, 193: 51-58.
[13] Ercolini D, Ferrocino I, Nasi A, et al. Monitoring of microbial metabolites and bacterial diversity in beef stored under different packaging conditions[J]. Applied and Environmental Microbiology, 2011, 77: 7372-7381.
[14] J??skel?inen E, Hultman J, Parshintsev J, et al. Development of spoilage bacterial community and volatile compounds in chilled beef under vacuum or high oxygen atmospheres[J]. International Journal of Food Microbiology, 2016, 223: 25-32.
[15] Storia A L, Ferrocino I, Torrieri E, et al. A combination of modified atmosphere and antimicrobial packaging to extend the shelf-life of beefsteaks stored at chill temperature[J]. International Journal of Food Microbiology, 2012, 158: 186-194.
[16] 李娟,任路靜,孫冠男,等. 氣相色譜-質(zhì)譜聯(lián)用技術(shù)及其在代謝組學(xué)中的應(yīng)用[J]. 生物工程學(xué)報(bào),2013,29(4):434-446.
Li Juan, Ren Lujing, Sun Guannan, et al. Gas chromatography-mass spectrometry (GC-MS) and its application in metabonomics[J]. Chinese Journal of Biotechnology, 2013, 29(4): 434-446. (in Chinese with English abstract)
[17] 林艷萍,司端運(yùn),劉昌孝. 液相色譜和質(zhì)譜聯(lián)用技術(shù)結(jié)合化學(xué)計(jì)量學(xué)應(yīng)用于代謝組學(xué)的研究進(jìn)展[J]. 分析化學(xué),2007,35(10):1535-1540.
Lin Yanping, Si Duanyun, Liu Changxiao. Advances of liquid chromatography/mass spectrometry combined with chemometric approaches applied to metabonomics[J]. Chinese Journal of Analytical Chemistry, 2007, 35(10): 1535-1540. (in Chinese with English abstract)
[18] England E M, Matarneh S K, Oliver E M, et al. Excess glycogen does not resolve high ultimate pH of oxidative muscle[J]. Meat Science, 2016, 114: 95-102.
[19] Yu Q, Tian X, Shao L, et al. Targeted metabolomics to reveal muscle-specifc energy metabolism between bovine longissimus lumborum and psoas major during early postmortem periods[J]. Meat Science, 2019, 156: 166-173.
[20] 齊小城,章弘揚(yáng),梁瓊麟,等. 液質(zhì)聯(lián)用技術(shù)及其在代謝組學(xué)研究中的應(yīng)用[J]. 中成藥,2009,31(1):106-112.
[21] Jacyna J, Kordalewska M, Markuszewski M J. Design of experiments in metabolomics-related studies: An overview[J]. Journal of Pharmaceutical and Biomedical Analysis, 2019, 164: 598-606.
[22] Graham S F, Farrell D, Kennedy T, et al. Comparing GC-MS, HPLC and1H NMR analysis of beef longissimus dorsi tissue extracts to determine the effect of suspension technique and ageing[J]. Food Chemistry, 2012, 134: 1633-1639.
[23] Warner R D, Jacob R H, Rosenvold K. Altered post-mortemmetabolism identified in very fast chilled lamb M. longissimus thoracis et lumborum using metabolomic analysis[J]. Meat Science, 2015, 108: 155-164.
[24] 許彥陽(yáng),姚桂曉,劉平香. 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[J]. 中國(guó)農(nóng)業(yè)科學(xué),2019,52(18):3163-3176.
Xu Yanyang, Yao Guixiao, Liu Pingxiang, et al. Review on the application of metabolomic approaches to investigate and analysis the nutrition and quality of agro-products[J]. Scientia Agricultura Sinica, 2019, 52(18): 3163-3176. (in Chinese with English abstract)
[25] Lu X, Zhao X, Bai C, et al. LC-MS-based metabonomics analysis[J]. Journal of Chromatography B, 2008, 866: 64-76.
[26] Cevallos-Cevallosa J M, Reyes-De-Corcuera J I, Etxeberria E, et al. Metabolomic analysis in food science: A review[J]. Trends in Food Science & Technology, 2009, 20: 557-566.
[27] Gomez J F M. Meat metabolomic pathway of Nellore and crossbred Angus × Nellore cattle [C]// 65thInternational Congress of Meat Science and Technology. Potsdam, Germany. 2019: 833-836.
[28] Straadt I K, Aaslyng M D, Bertram H C. An NMR-based metabolomics study of pork from different crossbreeds and relation to sensory perception[J]. Meat Science, 2014, 96: 719-728.
[29] Wang X,Fang C, He J, et al. Comparison of the meat metabolite composition of Linwu and Pekin ducks using 600 MHz1H nuclear magnetic resonance spectroscopy[J]. Poultry Science, 2017, 96:192-199.
[30] Kim H C. NMR-based metabolomic comparison of chicken meat from di?erent breeds with multivariable analyses[C]// 65thInternational Congress of Meat Science and Technology. Potsdam, Germany. 2019: 797-800.
[31] Wang X, Jiang G, Kebreab E, et al.1H NMR-based metabolomics study of breast meat from Pekin and Linwu duck of different ages and relation to meat quality[J]. Food Research international, 2020, 133: 109126.
[32] Liu C, Pan D, Ye Y, et al.1H NMR and multivariate data analysis of the relationship between the age and quality of duck meat[J]. Food Chemistry, 2013, 141: 1281-1286.
[33] Xiao Z, Ge C, Zhou G, et al.1H NMR-based metabolic characterization of Chinese Wuding chicken meat[J]. Food Chemistry, 2019, 274: 574-582.
[34] Muroya S, Oe M, Nakajima I, et al. CE-TOF MS-based metabolomic profiling revealed characteristic metabolic pathways in postmortem porcine fast and slow type muscles[J]. Meat Science, 2014, 98(4): 726-735.
[35] Antonelo D S, C?nsoloa N R B, Gómez J F M, et al. Metabolite profile and consumer sensory acceptability of meat from lean Nellore and Angus × Nellore crossbreed cattle fed soybean oil[J]. Food Research International, 2020, 132: 109056.
[36] Zawadzki A, Arrivetti L O R, Vidal M P, et al. Mate extract as feed additive for improvement of beef quality[J]. Food Research International, 2017, 99: 336-347.
[37] Baira E, Dagla L, Siapi E, et al. UHPLC-HRMS-based tissue untargeted metabolomics study of naringin and hesperidin after dietary supplementation in chickens[J]. Food Chemistry, 2018, 269: 276-285.
[38] 李敬,楊媛媛,趙青余. 肉風(fēng)味前體物質(zhì)與風(fēng)味品質(zhì)的關(guān)系研究進(jìn)展[J]. 中國(guó)畜牧雜志,2019,55(11):1-7.
[39] Koutsidis G, Elmore J S, Oruna-Concha M J, et al. Water-soluble precursors of beef flavour. Part II: Effect of post-mortem conditioning[J]. Meat Science, 2008, 79: 270-277.
[40] Consolo N R B. Meat metabolites profile changed by ageing time[C]// 65thInternational Congress of Meat Science and Technology. Potsdam, Germany. August, 2019: 793-796.
[41] Bischof G. Analysis of aging type and time of beef by1H-NMR spectroscopy[C]// 65thInternational Congress of Meat Science and Technology. Potsdam, Germany. 2019: 824-826.
[42] Warren K E, Kastner C L. A comparison of dry-aged and vacuum-aged beef strip loins[J]. Journal of Muscle Foods, 1992, 3(2): 151-157.
[43] Kim Y H B, Kemp R, Samuelsson L M. Effects of dry-aging on meat quality attributes and metabolite profiles of beef loins[J]. Meat Science, 2016, 111: 168-176.
[44] Mungure T. NMR-based metabolites profiling of wet and dry aged pulsed electric fields treated venison[C]// 65thInternational Congress of Meat Science and Technology. Potsdam, Germany. 2019: 819-821
[45] Zhang R. Effect of step-wise dry-ageing and trimming on the metabolite profiles of dry-aged bull beef[C]//65thInternational Congress of Meat Science and Technology. Potsdam, Germany. 2019: 788-790.
[46] Nychas G J E, Skandamis P N, Tassou C C, et al. Meat spoilage during distribution[J]. Meat Science, 2008, 78: 77-89.
[47] Casaburi A, Piombino P, Nychas G, et al. Bacterial populations and the volatilome associated to meat spoilage[J]. Food Microbiology. 2015, 45: 83-102.
[48] Mansur A R, Seo D H, Song E J, et al. Identifying potential spoilage markers in beef stored in chilled air or vacuum packaging by HS-SPME-GC-TOF/MS coupled with multivariate analysis[J]. LWT - Food Science and Technology, 2019, 112: 1-6.
[49] Argyri A A, Doulgeraki A I, Blana V A, et al. Potential of a simple HPLC-based approach for the identification of the spoilage status of minced beef stored at various temperatures and packaging systems[J]. International Journal of Food Microbiology, 2011, 150: 25-33.
[50] Reis M M, Reis M G, Mills J, et al. Characterization of volatile metabolites associated with confinement odour during the shelf-life of vacuum packed lamb meat under different storage conditions[J]. Meat Science, 2016, 113: 80-91.
[51] Zareian M, B?hner N, Loos H M, et al. Evaluation of volatile organic compound release in modified atmosphere packaged minced raw pork in relation to shelf-life[J]. Food Packaging and Shelf Life, 2018, 18: 51-61.
[52] Nieminen T T, Dalgaard P, Bj?rkroth J. Volatile organic compounds and Photobacterium phosphoreum associated with spoilage of modified-atmosphere-packaged raw pork[J]. International Journal of Food Microbiology, 2016, 218: 86-95.
[53] Lyte J M, Legako J F, Martin J N, et al. Volatile compound characterization of modified atmosphere packaged ground beef held under temperature abuse[J]. Food Control, 2016, 59: 1-6.
[54] Remenant B, Jaffrès E, Dousset X, et al. Bacterial spoilers of food: Behavior, fitness and functional properties[J]. Food Microbiology, 2015, 45: 45-53.
[55] García-Garcíaa A B, Lamichhanec S, Castejónb D, et al.1H HR-MAS NMR-based metabolomics analysis for dry-fermented sausage characterization[J]. Food Chemistry, 2018, 240: 514-523.
[56] Yang Y, Pan D, Sun Y, et al.1H NMR-based metabolomics profiling and taste of stewed pork-hock in soy sauce[J]. Food Research International, 2019, 121: 658-665.
[57] Yang Y, Ye Y, Wang Y, et al. Effect of high pressure treatment on metabolite profile of marinated meat in soy sauce[J]. Food Chemistry, 2018, 240: 662-669.
[58] 周楠楠,樓宵瑋,王穎,等.1H核磁共振結(jié)合多元統(tǒng)計(jì)方法分析糟鴨加工過程中滋味化合物的變化[J]. 食品科學(xué),2019,40(6):233-239.
Zhou Nannan, Lou Xiaowei, Wang Ying, et al. Changes in taste compounds during processing of vinasse-cured duck as studied by 1h nmr combined with multivariate data analysis[J]. Food Science, 2019, 40(6): 233-239. (in Chinese with English abstract)
[59] Zhang J, Yi Y, Pan D, et al.1H NMR-based metabolomics profiling and taste of boneless dry-cured hams during processing[J]. Food Research International, 2019, 122: 114-122.
[60] Sugimoto M, Sugawara T, Obiya S, et al. Sensory properties and metabolomic profiles of dry-cured ham during the ripening process[J]. Food Research International, 2020, 129: 1-9.
[61] Shi Y, Li X, Huang A. A metabolomics-based approach investigates volatile flavor formation and characteristic compounds of the Dahe black pig dry-cured ham[J]. Meat Science, 2019, 158: 1-8.
[62] Shintu L, Caldarelli S, Franke B M. Pre-selection of potential molecular markers for the geographic origin of dried beef by HR-MAS NMR spectroscopy[J]. Meat Science, 2007, 76: 700-707.
[63] Jung Y, Lee J, Kwon J, et al. Discrimination of the geographical origin of beef by1H NMR-based metabolomics[J]. Journal of Agricultural Food Chemistry, 2010, 58: 10458-10466.
[64] 程碧君. 基于脂肪酸指紋分析的牛肉產(chǎn)地溯源研究[D]. 北京:中國(guó)農(nóng)業(yè)科學(xué)院,2012:40-48.
Cheng Bijun. Study on Beef Geographical Origin Traceability based on Fatty Acid Fingerprint Analysis[D]. Beijing: Chinese Academy of Agricultural Sciences, 2012:
40-48. (in Chinese with English abstract)
[65] Mi S, Shang K, Li X, et al. Characterization and discrimination of selected China’s domestic pork using an LC-MS-based lipidomics approach[J]. Food Control, 2019, 100: 305-314.
[66] Vasilev D, Dimovska N, Hajrulai-Musliu Z, et al. Fatty acid profile as a discriminatory tool for the origin of lamb muscle and adipose tissue from different pastoral grazing areas in North Macedonia - A short communication[J]. Meat Science, 2020, 162: 1-5.
[67] Pavlidis D E, Mallouchos A, Ercolini D, et al. A volatilomics approach for off-line discrimination of minced beef and pork meat and their admixture using HS-SPME GC/MS in tandem with multivariate data analysis[J]. Meat Science, 2019, 151: 43-53.
[68] 孟新濤,張婷,許銘強(qiáng),等. 基于氣相離子遷移譜的羊肉摻偽快速鑒別方法[J]. 新疆農(nóng)業(yè)科學(xué),2019,56(10):1939-1947.
Meng Xintao, Zhang Ting, Xu Mingqiang, et al. Detection of authenticity of mutton with Gas Chromatography - Ion Mobility Spectrometry (GC-IMS) [J].Xinjiang Agricultural Sciences, 2019, 56(10): 1939-1947. (in Chinese with English abstract)
[69] Jakes W, Gerdova A, Defernez M A D, et al. Authentication of beef versus horse meat using 60 MHz1H NMR spectroscopy[J]. Food Chemistry, 2015, 175: 1-9.
[70] Monahana F J, Schmidta O, Moloney A P. Meat provenance: Authentication of geographical origin and dietary background of meat[J]. Meat Science, 2018, 144: 2-14.
[71] Renou J P, Bielicki G, Deponge C, et al. Characterization of animal products according to geographic origin and feeding diet using nuclear magnetic resonance and isotope ratio mass spectrometry. Part II: Beef meat[J]. Food Chemistry, 2004, 86: 251-256.
Application of metabolomics in monitoring the qualities of meat and meat products
Chen Xue1, Luo Xin1,2, Liang Rongrong1, Zhu Lixian1, Yang Xiaoyin1, Han Mingshan3, Cheng Haijian4, Zhang Yimin1※
(1.,,271018,; 2.,210095,;3.,,028100,;4.,,250000,)
Meat and meat products have been the most important sources of proteins in the human diet, particularly on directly linking to public health and welfare. Meat quality has attracted much more attention for the meat industry worldwide, as the meat consumption is increasing in recent years, due to the improvement of living standards. Generally, the meat quality depends highly on pre-slaughter factors, including breed, age, muscle types, as well as the ways of post-slaughter processing, where the alteration of metabolites normally occurs all over the stages during meat production. Thus, the intrinsic mechanism of meat quality at the metabolites level has been a highly relevant issue for improving the nutritional value of meat. As a branch of systems biology, metabolomics mainly focuses on the whole metabolome, metabolites of molecular weight below 1 500 Da, to represent in a biological system, whether it being stimulated or disturbed. Recently, the interest in the application of metabolomics has been extended to the field of meat science with constantly rising studies. This present review systematically summarized the main techniques that used in metabolomics, based on the methodology of recent studies, including the Nuclear Magnetic Resonance (NMR) spectroscopy, Gas Chromatography-Mass Spectroscopy (GC-MS), and High-Performance Liquid Chromatography-Mass Spectroscopy (HPLC-MS), as well as the applied methods for data analysis. Five aspects were also overviewed, according to the recent findings in metabolomics associated with meat quality traits. 1) In pre-slaughter factors, animal breed, ages, muscle types, and diet can be recognized as the most significant indictors of meat quality. Most previous studies confirmed that the metabolomics profiling related to age or breed can contribute to the assessment of meat quality, and thereby to provide theoretical support for the development of high-quality meat resources. Moreover, the different types of muscle in an animal have shown the distinct metabolic characteristics of individual energy. In recent reports, these differences in postmortem muscle metabolites were identified to provide useful theoretical information regarding the biochemistry process of muscle to meat conversion. Additionally, metabolomics has shown a promising potential to distinguish the various feeding regime, and dietary addition of mate extract, such as naringin, hesperidin, further to facilitate the creation of novel management schemes for mitigating limitation in meat quality. 2) Metabolomics can offer a new perspective to predict the post-mortem ageing time, shelf-life of meat and meat products. Previous studies also found that the metabolomics can achieved data information on the flavor and taste that related to metabolites changes, particularly occurring on ageing of meat, predicting ageing time, and differentiating various aging conditions. The reason is that the metabolites variation in meat depended mainly on the ageing time and conditions after post-mortem. The growth and enzymatic activity of microorganisms can cause the meat decomposition and formation of metabolites, resulting in the meat spoilage. Hence, those changes have also been reviewed on critical metabolites that exploited for monitoring the shelf-life of meat. 3) In processed meat products, numerous biochemical and biophysical reactions can pose some influence on the final quality during meat handling and cooking. These changes detected by metabolomics can be contributed to the optimization of the processing technology. 4) A potential technique of metabolomics was applied to identify metabolic markers that selected for the substantiation of the claim, and further to aid in the certification of the geographical origin of meat product. 5) Metabolomics has also been developed as a useful tool for the adulteration detection of meat and meat products, showing the reliable meat identification. Finally, an insightful prospect was made, in order to provide a sound theoretical basis for the further application of metabolomics to meat science.
meat; quality control; metabolomics; shelf life; geographical origin traceability; biomarker
陳雪,羅欣,梁榮蓉,等. 代謝組學(xué)在肉及肉制品品質(zhì)監(jiān)測(cè)中的應(yīng)用[J]. 農(nóng)業(yè)工程學(xué)報(bào),2020,36(17):291-300.doi:10.11975/j.issn.1002-6819.2020.17.034 http://www.tcsae.org
Chen Xue, Luo Xin, Liang Rongrong, et al. Application of metabolomics in monitoring the qualities of meat and meat products[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2020, 36(17): 291-300. (in Chinese with English abstract) doi:10.11975/j.issn.1002-6819.2020.17.034 http://www.tcsae.org
2020-04-02
2020-08-31
現(xiàn)代農(nóng)業(yè)產(chǎn)業(yè)技術(shù)體系建設(shè)專項(xiàng)資金資助(肉牛CARS-37);山東省現(xiàn)代農(nóng)業(yè)產(chǎn)業(yè)技術(shù)體系創(chuàng)新團(tuán)隊(duì)建設(shè)專項(xiàng)資金(SDAIT-09-09)
陳 雪,博士生,主要從事肉品科學(xué)研究。Email:2019010030@sdau.edu.cn
張一敏,博士,副教授,主要從事肉品科學(xué)研究。Email:ymzhang@sdau.edu.cn
10.11975/j.issn.1002-6819.2020.17.034
TS251.1
A
1002-6819(2020)-17-0291-10