PENGANTAR ANALISIS METABOLOMIK

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1 PENGANTAR ANALISIS METABOLOMIK M Rafi, R Heryanto DIVISI KIMIA ANALITIK 2015 Metabolomik Metabolomik adalah teknologi yang berkembang pesat dekade terakhir, sebagai bagian dari keluarga "omics" yang melengkapi analisis transkrip gen (transkriptomik) skala besar dan sidikjari protein (proteomik) Menjelaskan dan mengidentifikasi perbedaan antara organisme (misalnya perbedaan genotipe dan fenotipe dan klasifikasinya yang disebut kemotaksonomi) dan menjelaskan faktor-faktor lingkungan yang mempengaruhi reaksi-reaksi biokimia 1

2 Metabolomik (a) Skema umum organisasi Omics. The general flow of information is from genes to transcripts, to proteins, to metabolites, to function (or phenotype); whilst blue vertical arrows indicate interactions regulating respective omic expression. (b) Our traditional linear view of a metabolic pathway and scale free connections in a metabolite neighbourhood. R Goodacre Metabolomics 1: 2 Metabolomik The three cornerstones of metabolomics and the three main challenges related to metabolomic data analysis. J Boccard, S Rudaz J. Chemometrics 28: 1 2

3 Metabolomik A Krastanov Biotechnol. & Biotechnol. Eq. 24:1 Strategies dalam analisis metabolomik Term Metabolomics Metabolite profiling Metabolomik Deskripsi Identifikasi non-bias dan kuantifikasi semua metabolit dalam suatu sistem biologi. Persiapan sampel tidak harus mengecualikan suatu kelompok metabolit, dan selektivitas dan sensitivitas teknik analitis harus tinggi Identifikasi dan kuantifikasi sejumlah tertentu metabolit yang telah ada, umumnya terkait dengan jalur metabolit tertentu. Persiapan sampel dan instrumentasi yang digunakan dapat mengisolasi senyawa-senyawa target tersebut dari matriks lainnya sebelum deteksi, biasanya menggunakan teknik pemisahan kromatografi lalu dideteksi dengan MS. Dalam industri farmasi, cara ini secara luas digunakan untuk studi penemuan kandidat obat baru, produk metabolisme obat dan efek perawatan terapi 3

4 Metabolomik Term Metabolic fingerprinting Metabolite target analysis Deskripsi High-throughput, rapid, global analysis of samples to provide sample classification. Quantification and metabolic identification are generally not employed. A screening tool to discriminate between samples of different biological status or origin. Sample preparation is simple and, as chromatographic separation is absent, rapid analysis times are small (normally 1 min or less) Qualitative and quantitative analysis of one or a few metabolites related to a specific metabolic reaction. Extensive sample preparation and separation from other metabolites is required and this approach is especially employed when low limits of detection are required. Generally, chromatographic separation is used followed by sensitive MS or UV detection Metabolomik Term Metabonomics Deskripsi Evaluation of tissues and biological fluids for changes in endogenous metabolite levels that result from disease or therapeutic treatments WB Dunn, DI Ellis Trends in Analytical Chemistry 24: 285 4

5 Metabolomik WB Dunn, DI Ellis Trends in Analytical Chemistry 24: 285 Alur Analisis Metabolomik Flowchart of the metabolomic study in plants. Sample preparation steps can be changed depending on the analytical methods; however, in general many steps are common. *This step can be omitted in a certain analysis.) KEMOMETRIKA HK Kim, R Verpoorte Phytochemical Analysis 21: 4 5

6 Teknik Analitik Dalam Analisis Metabolomik R Goodacre et al Trends in Biotechnology 22: 245 Teknik Analitik Dalam Analisis Metabolomik Some standard techniques used in metabolomic analysis. In general, one technology is not sufficient for the analysis of all compounds, but any form of separation will inherently introduce a bias towards the analytes being detected. F Tugizimana, L Piater, I Dubery South African Journal of Science 109 6

7 Alur Analisis Metabolomik Pipa Saluran Metabolomik S Moco, RJ Bino, RCH De Vos, J Vervoort Trends in Analytical Chemistry, 26: 855 7

8 Metabolomik Dalam Riset Obat Herbal Key features of the technologies used in metabolomics for herbal medicine research LF Shyur, NS Yang Current Opinion in Chemical Biology 12: 66 Analisis Data Dalam Metabolomik C Hu, G Xu Trends in Analytical Chemistry 52: 36 8

9 Kemometrika Dalam Metabolomik Chemometrics A science of relating measurements made on a chemical system or process to the state of the system via application of mathematical or statistical method (International Chemometrics Society) Chemometrics Pattern recognition (qualitative) Multivariate calibration (quantitative) Principal component analysis Cluster analysis Discriminant analysis Multiple linear regression Partial least square H.A. Gad et al Phytochemical Analysis 24: 1 Kemometrik Dalam Metabolomik R Goodacre et al Trends in Biotechnology 22: 245 9

10 Kebutuhan Dalam Studi Metabolomik 1. How can we extract all metabolites? 2. How can we separate or detect the metabolites extracted? 3. How can we reduce the huge data set obtained from analytical detection? 4. How can we identify the metabolites? Contoh Kajian Metabolomik 10

11 Karakteristik Obat Herbal Lingkungan tumbuh Genetik Sinergi Multikomponen Budidaya Panen dan pascapanen Obat Herbal Produksi senyawa bioaktif Karakteristik Obat Herbal Kadar gingerol and shogaol pada tiga varietas jahe Indonesia mg/g M. Rafi, L.W. Lim, T. Takeuchi, L.K. Darusman Talanta 103:

12 Karakteristik Obat Herbal Metode Kendali Mutu Berbasis Metabolomik Identifikasi Diskriminasi Autentikasi Kendali Mutu dengan Senyawa Kimia Patternoriented (Fingerprint analysis) Compoundoriented (Marker analysis) Kemometrika Z. Zeng et al., Chin. Med., 3 (2008) 9 S. Govindaraghavan et al., Fitoterapia, 83 (2012)

13 Sidikjari KLT Sidikjari KLT Diskriminasi Kunyit, Temulawak, dan Bangle a b c Pola KLT sidikjari dengan visualisasi sinar tampak (a), UV 254 nm (b), dan UV 366 nm (c) Keterangan: CCM = kurkumin BDC = bisdemetoksikurkumin KNY = Kunyit DMC = demetoksikurkumin TMK = Temulawak BNGL = Bangle M Rafi, E Rohaeti, A Miftahudin, LK Darusman Indonesia Journal of Chemistry 11: 71 13

14 Sidikjari KLT a c b Pola KLT sidikjari bangle (a), kunyit (b), dan temulawak (c) dengan visualisasi sinar tampak Keterangan: STD = senyawa standar kurkuminoid NGD = Ngadirejo, Wonogiri TMB = Tembalang, Semarang TWN = Tawangmangu, Karanganyar SMN = Semen, Kediri SLH = Slahung, Ponorogo NGR = Ngrayun, Ponorogo TJK = Tanjung Kerta, Sumedang RCK = Rancakalong, Sumedang CKR = Cikembar, Sukabumi DMG = Dramaga, Bogor Sidikjari KLT a Pola KLT sidikjari bangle (a), kunyit (b), dan temulawak (c) dengan visualisasi UV 254 nm Keterangan: STD = senyawa standar kurkuminoid NGD = Ngadirejo, Wonogiri TMB = Tembalang, Semarang TWN = Tawangmangu, Karanganyar SMN = Semen, Kediri SLH = Slahung, Ponorogo NGR = Ngrayun, Ponorogo TJK = Tanjung Kerta, Sumedang RCK = Rancakalong, Sumedang CKR = Cikembar, Sukabumi DMG = Dramaga, Bogor b c 14

15 Sidikjari KLT a b c Pola KLT sidikjari bangle (a), kunyit (b), dan temulawak (c) dengan visualisasi UV 366 nm Keterangan: STD = senyawa standar kurkuminoid NGD = Ngadirejo, Wonogiri TMB = Tembalang, Semarang TWN = Tawangmangu, Karanganyar SMN = Semen, Kediri SLH = Slahung, Ponorogo NGR = Ngrayun, Ponorogo TJK = Tanjung Kerta, Sumedang RCK = Rancakalong, Sumedang CKR = Cikembar, Sukabumi DMG = Dramaga, Bogor Metode Kendali Mutu --- Kemometrik Langkah-langkah dalam mengembangkan metode kendali mutu obat herbal menggunakan kemometrik Preparasi Sampel Koleksi sinyal dan prapemrosesan Analisis kemometrik Validasi 15

16 Metode Kendali Mutu --- Kemometrik Data spektrum original Spektrum original dari sampel X Prapemrosesan sinyal, data pretreatment Pemilihan model Set kalibrasi Set validasi Set prediksi Model IDA I. C. Yang et al., J. Food Drug Anal. 21 (2013) 268 The pretreatments and the logical flow of different calibration, validation, and prediction sets Metode Kendali Mutu --- Kemometrik 16

17 Diskriminasi Tiga Varietas Jahe Diskriminasi Tiga Varietas Jahe 17

18 DF-2 (27.17 %) 2016/12/20 Diskriminasi Tiga Varietas Jahe mg/g Diskriminasi Tiga Varietas Jahe Instrumentasi: KCKT Prapemrosesan sinyal: koreksi garis dasar Metode kemometrik: analisis diskriminant/discrimin ant analysis (DA) ZOO-10 ZOO-9 ZOO-11 DF-1 (72.83 %) ZOR-11 ZOO-12 ZOO-1 ZOO-6 ZOR-1 ZOR-6 ZOR-9 ZOR-12 ZOR-8 ZOR-2 ZOR-7 ZOR-5 ZOO-4 ZOO-5 ZOR-3 ZOO-2 ZOO-3 ZOO-8 ZOR-10 ZOA-7 ZOA-13 ZOR-4 ZOA-4 ZOA-11 ZOA-5 ZOA-10 ZOA-8 ZOO-7 ZOA-2 ZOA-1 ZOA-12 ZOA-9 ZOA-3 ZOA

19 Diskriminasi Bangle, Lempuyang Emprit, dan Lempuyang Gajah Diskriminasi Bangle, Lempuyang Emprit, dan Lempuyang Gajah Analisis sidikjari + Kemometrik Identifikasi & Diskriminasi Z. montanum 19

20 Diskriminasi Bangle, Lempuyang Emprit, dan Lempuyang Gajah v Reference peak min Kromatogram sidikjari KCKT Z. montanum (a), Z. americans (b) dan Z. zerumbet (c) Analisis Komponen Utama Diskriminasi Bangle, Lempuyang Emprit, dan Lempuyang Gajah Analisis Diskriminan 20

21 Identifikasi Kunyit, Temulawak dan Bangle Identifikasi Kunyit, Temulawak dan Bangle Turmeric (C. longa) Java turmeric (C. xanthorrhiza) Cassumunar ginger (Z. cassumunar) Turmeric?? Java turmeric?? Cassumunar ginger?? 21

22 Identifikasi Kunyit, Temulawak dan Bangle Spektra FTIR representatif dari C. longa (A), C. xanthorrhiza (B), and Z. cassumunar (C) Identifikasi Kunyit, Temulawak dan Bangle Instrumentasi: Spektroskopi FTIR Prapemrosesan sinyal: standar normal variate Metode kemometrik: analisis variat kanonik/canonical variate analysis (CVA) ZC CL CX Plot CVA 22

23 Autentikasi Temulawak --- Sidikjari KCKT Autentikasi Temulawak --- Sidikjari KCKT Kadar kurkuminoid mg/g 30 CUR DMC 25 BDMC

24 CV2 (1.1%) 2016/12/20 Autentikasi Temulawak --- Sidikjari KCKT 1.5 [ 10 5 ] v c b a min Kromatogram CX (a), 5% CL dalam CX (b), 25% CL dalam CX (c), 50% CL dalam CX (d) and CL (e) (UV 254 nm) d e Autentikasi Temulawak --- Sidikjari KCKT Analisis Variat Kanonik CV1 (98.9%) Plot CVA CX ( ), 5% CL dalam CX ( ), 25% CL dalam CX ( ), 50% CL dalam CX ( ) and CL ( ) 24

25 GC-MS Based Metabolomics GC-MS Based Metabolomics ABSTRACT Introduction Metabonomic analysis is an important molecular phenotyping method for characterising plant ecotypic variations; hence, it may become a powerful tool for quality control and discrimination of traditional Chinese medicine (TCM). Objective To discriminate and assess the quality of Curcuma phaeocaulis, C. kwangsiensis and C. wenyujin from different ecotypes. The identification of the compositions of essential oils from the three Curcuma species was included in this study. Methodology Metabolomics analysis was carried out on all samples by gas chromatography mass spectrometry (GC MS) coupled with multivariate statistical analysis. Characterisation of phytochemicals in essential oils was performed by automated matching to the MS library and comparison of their mass spectra (NIST05 database). 25

26 GC-MS Based Metabolomics Results Principal component analysis (PCA) effectively distinguished the samples from different species and ecotypes. Partial least squares discrimination analysis (PLS DA) was successfully employed in classifying the GC MS data of authentic, commercial and introduction cultivation samples. Furthermore, the components contributing significantly to the discrimination, namely curzerenone, germacrone, curdione and epicurzerenone, were screened by PCA and PLS DA loading plots and further can be used as chemical markers for discrimination and quality control among different groups of samples. GC-MS Based Metabolomics Representative GC MS chromatograms of the essential oil from (a) C. wenyujin, (b) C. kwangsiensis and (c) C. phaeocaulis. 26

27 GC-MS Based Metabolomics Score plots of (a) PCA and (b) PLS DA, and loading plots of (c) PCA and (d) PLS DA for the 62 samples, using common components as input data. (a) PCA and (b) PLS DA projection plots for the 62 samples, using peak areas of four chemical markers as input data. 27

28 NMR Based Metabolomics NMR Based Metabolomics 28

29 Terima Kasih Atas Perhatiannya! 29