九十四年度台灣質譜學會教育課程

~ 當質譜儀遇上蛋白質 ~ 九十四年度台灣質譜學會教育課程質譜胜肽定序 (Peptide Sequencing by Mass Spectrometry) 利用質譜技術對胜肽定序，是目前進行蛋白質體學研究最重要的工具之一。本節將介紹(1)質譜胜肽定序所使用之串聯式質譜分析的發展歷史與實驗方法、(2) De novo 定序與利用搜尋資料庫定序兩者的關聯與差別、(3)質譜定序所產生的「信心度(confidence level)」問題、 (4)如何將質譜胜肽定序概念擴展至後轉譯修飾(post-translational modification)結構分析、及(5)現今用於胜肽定序常見的質譜儀型式。講員：廖寶琦成功大學環境醫學研究所

利用質譜技術對胜肽定序，是目前進行蛋白質體學研究最重要的工具之一利用質譜技術對胜肽定序，是目前進行蛋白質體學研究最重要的工具之一 Hanno and Mann, Nature Reviews, 2004

~ 當哈利遇見莎莉~ (1989) 哈利與莎莉這兩個人的的確確就是一對命中註定的戀人，唯一的問題是，他們自己並不知道。所以從敘事的觀點來看，他們不知道彼此應當相愛，就是阻礙他們相愛的原因，如何克服這個障礙就是故事推展的動力所在。影片討論李振亞

一個「當質譜儀遇上蛋白質」的真實案例 • 場景：某國立大學蛋白質體研究核心實驗室 • 時間：某位資深教授收到核心實驗室完成的蛋白質身分鑑定報告後的三天 • 資深教授：謝謝你們做的蛋白質身分鑑定報告，但是，能不能麻煩你們把蛋白質序列的「原始數據」給我一份。 • 核心實驗室助理：什麼是「蛋白質序列的原始數據」？

Two major techniquesfor sequencing a polypeptide • Edman degradation: Proposed by Pehr Edman in 1967. (Edman, P. 1967, Eur. J. Biochem. 1, 80−91.) • Mass Spectrometry: Pioneered by Klaus Biemann in 1980’s.

Protein Sequencing by Edman Chemistry(Edman Cycle)

在1980年代，Edman sequencing已經被廣泛的運用來定蛋白質的氨基酸序列 • 但是，Edman定序有一些使用上的限制。 • 一部Edman定序機器每小時約可定2 ~ 3個氨基酸序列，理論上質譜分析可以快上數十倍。 • 質譜分析比Edman定序靈敏度略好。 • 有些研究者相信，質譜技術可以克服Edman定序原有的限制。 • 包含Biemann在內的許多研究團隊，進行大量的研究活動，試圖利用質譜技術決定蛋白質序列。

1980年代科學家嘗試利用質譜技術分析蛋白質序列1980年代科學家嘗試利用質譜技術分析蛋白質序列 • 早在1984年Biemann等人就提出利用質譜數據確認蛋白質序列與DNA序列的關係

利用質譜分析可以得知蛋白質序列嗎？ 質譜數據 (now so-called “de novo sequencing”) 蛋白質序列

以串聯式質譜法分析胜肽碎片 當時有各種嘗試利用質譜技術決定蛋白質序列的策略被提出來，其中獲得多數學者重視的策略是－以串聯式質譜（tandem mass spectrometry, MS/MS）分析蛋白質以trypsin水解脢降解成胜肽碎片所得到的數據，推測胜肽的氨基酸序列。

Full MS scan 772.913 Mass analyzer scan Product ion scan (product of 772.9) select ion collision-induced dissociation (CID) scan Peptide Fragmentation Pattern Obtained by Tandem Mass Spectrometry(MS/MS)/Product Ion Scan of Peptide Ion

Biemann等人以串聯式質譜（MS/MS）分析蛋白質以trypsin水解脢降解成胜肽碎片所得到的數據Biemann等人以串聯式質譜（MS/MS）分析蛋白質以trypsin水解脢降解成胜肽碎片所得到的數據蛋白質序列磁電場串聯式質譜分析（MS/MS）

Nomenclature for peptide fragment ions Peptide fragmentation In addition to typical fragment ions, other types of fragments may also be observed!

Useful rules for de novo sequencing from peptide fragmentation data • For low energy collision data, usually b or y ions dominate. • Look for “sequence ladders” reflected by “mass intervals”. • Use a “try and error” strategy to establish an amino acid sequence. • Look for hints differentiating b or y ion series. • Make assumptions for N- or C-terminal amino acid residues, then check these assumptions. • The mass of a peptide is made by the sum of amino acid residues plus H2O. • The mass of precursor ion is easily calculated from the number of protons attached to the peptide. • In addition to b and y ions, other fragment ions, including a, c, x, z, side chain loss (d, w), internal fragments, and immonium ions, may be observed. • Although complete de novo sequencing may often be difficult, partial sequence or multiple possibilities are obtained.

De novo sequencing of a peptide using its fragmentation pattern generated from doubly-charged peptide ion, [M+2H]2+ Product ions from m/z 645.2 (2+) precursor ion Sequence : NH2 - (L/I,E)DES(L/I)(Q/K)VAER - COOH M=1288.4 [M+H]+=1289.4 304.2 1047.5 (R,E) A V (Q/K) (L/I) S E D (L/I,E) b ion y ion X X (m1+m2+1) 99 128 87 94 129 115 242 113 ( mn +mn-1+17+1+1) 71 Tryptic digest y5 (129+156+17+1+1) 1289.4-(1047.5-1)=113+129-1 y3 y4 b8-H2O y7 y6 b2 b3-H2O y2 y9 y8

Ri │ H -- N -- C – C -- OH H║ O i=1~n Masses of 20 Amino Acid Residues

De novo sequencing of another doubly-charged peptide ion (difficult to do !) Product ions from m/z 829.6 (2+) precursor ion (?,?,?,...)(L/I)(L/I.G)(?)SS(?,?,?,...) Sequence : NH2- -COOH (?,?,?,...)SS(?)(L/I.G)(L/I)(?,?,?,...) 580.3 ? 1252.6 (L/I) (L/I,G) (L/I) S S X (?,?,?,...) (?,?,?,...) (A,S,G)

However, the same data can be easily mapped to a sequence in database !

De novo sequencing of another triply-charged peptide ion (difficult to do !) Product ions from m/z 720.7 (3+) precursor ion Sequence : NH2 - (?,?,?,...)VT(G,V)TAVAQK - COOH b++ ion [ V T (G,V)T A V A Q ]2+ 593.8 1007.5 (?,?,?,...) K2+ y+ ion A T (G,V) T V 974.6 446.3 (?,?,?,...) (?,?,?,...) So complicated

Again, the data can be easily mapped to another sequence in database !

在1980年代結束時，科學家們仍未發展出來受到蛋白質化學家接受的蛋白質定序質譜儀。在1980年代結束時，科學家們仍未發展出來受到蛋白質化學家接受的蛋白質定序質譜儀。主要原因是，雖然由胜肽序列預測碎片離子似乎有某些特定模式可循，但單獨靠胜肽碎片離子的質譜數據推測胜肽序列(De novo sequencing)卻仍困難。那時候流傳的一個笑話是說，某人是利用質譜儀定序蛋白質的專家，將蛋白質樣本交給他，只消3 個月的光景，他便可以將該蛋白質定序出來。

De novo sequencing • “de novo”: “starting from the beginning” • “de novo sequencing”: deriving the amino-acid sequence of a peptide solely from the mass-spectrometry, peptide-fragmentation data (that is, without using databases). • In most cases, only partial/incomplete peptide sequence can be obtained. • Require the expertise of highly experienced protein mass spectrometrists and, therefore, not robust for consistent and routine analysis • Useful when genomic sequences are not available.

1993年，幾位科學家提出一個嶄新的概念來看待質譜數據與蛋白質序列間的關聯1993年，幾位科學家提出一個嶄新的概念來看待質譜數據與蛋白質序列間的關聯 De novo sequencing？質譜數據蛋白質序列

1993年，幾位科學家提出一個嶄新的概念來看待質譜數據與蛋白質序列間的關聯1993年，幾位科學家提出一個嶄新的概念來看待質譜數據與蛋白質序列間的關聯質譜數據蛋白質序列 Database search 基因圖譜計劃的主要產物：鹼基序列

The concepts behind database search and de novo sequencing are related, but fundamentally different (1) In early 1990s, researchers realized that the peptide-sequencing problem could be converted to a database-matching problem, which would be much simpler to solve. (2) The reason database searching is easier than de novo sequencing is that only an infinitesimal fraction of the possible peptide amino-acid sequences actually occur in nature. (3) A peptide-fragmentation data might not contain sufficient information to unambiguously derive the complete amino-acid sequence, but it may still have sufficient information to match it uniquely to a peptide sequence in the database.

MALDI-TOF LC-MS/MS peptide mass fingerprinting peptide fragmentation pattern more reliable less reliable protein sequence database search Two MS methods to map an unknown protein to sequence databases unknown protein spot 2-D gel trypsin digestion peptide mixture

2002年美國質譜學會（ASMS）將「Distinguished Contribution in Mass Spectrometry Award」頒給Henzel、Stults、Watanabe三位研究者，表揚他們將質譜技術應用於蛋白質體學的成就。 (proposed PMF in 1989)

unknown protein spot trypsin digestion peptide mixture Comparison for protein mapping Mapping algorithms #1:Peptide mass fingerprinting Protein/DNA sequence database P1, P2, P3, P4,... Computational tryptic digestion Secondary database P1(m11, m12, m13, m14, m15,…), P2 (m21, m22, m23, m24, m25,…), P3 (m31, m32, m33, m34, m35,…), P4 (m41, m42, m43, m44, m45,…), ... MALDI-TOF Peptide mass fingerprint

PMF search的優缺點 (from a workshop presented by JS Cottrel, Matrix Science, in ASMS 2005)

PMF web sites (from a workshop presented by JS Cottrel, Matrix Science, in ASMS 2005)

unknown protein spot trypsin digestion peptide mixture Peptide fragmentation patterns p11(m11, m12, m13,…), p12 (m21, m22, m23,…), p13 (m31, m32, m33,…), ... Peptide fragmentation patterns p11(m11, m12, m13,…), p12 (m21, m22, m23,…), p13 (m31, m32, m33,…), ... Peptide fragmentation patterns p11(m11, m12, m13,…), p12 (m21, m22, m23,…), p13 (m31, m32, m33,…), ... Peptide fragmentation patterns p11(m11, m12, m13,…), p12 (m21, m22, m23,…), p13 (m31, m32, m33,…), ... M3 M2 M1 . . . Comparison for protein mapping Mapping algorithms #2: Peptide fragmentation pattern Protein/DNA sequence database P1, P2, P3, P4,... Computational tryptic digestion Secondary database P1(p11, p12, p13,…), P2 (p21, p22, p23,…), P3 (p31, p32, p33,…), P4 (p41, p42, p43,…), ... LC-MS/MS LC MS Theoretical fragmentation patterns MS/MS MS/MS fragmentation patterns

J. Eng and J. Yates proposed SEQUEST in 1994 (from a workshop presented by JS Cottrel, Matrix Science, in ASMS 2005)

Peptide fragmentation search的優缺點 (from a workshop presented by JS Cottrel, Matrix Science, in ASMS 2005)

Peptide fragmentation search web sites (from a workshop presented by JS Cottrel, Matrix Science, in ASMS 2005)

Mapping fragmentation pattern to sequence MS/MS Fragmentation of HGTDDGVVWMNWK

Mascot Search Results Database : NCBInr 20040204 (1624011 sequences; 534067077 residues) Taxonomy : Homo sapiens (human) (111278 sequences) Probability Based Mowse Score Score is -10*Log(P), where P is the probability that the observed match is a random event.Individual ions scores > 46 indicate identity or extensive homology (p<0.05). Significant hits: gi|2781208Total score: 941Chain B, Crystal Structure Of Fibrinogen Fragment D gi|1346343Total score: 180Keratin, type II cytoskeletal 1 gi|7428712Total score: 153keratin 1, type II, cytoskeletal

您ID了嗎? Are you sure that you ever identify the protein by mass spectrometry? －The criteria of MS-based protein identification.

場景一：ｘｘ大學ｘｘ研究室group meeting. 學生：報告老師，好消息，Ｉhave identified 1016 proteins in CSF. 老師: Great! But, what do you mean EXACTLY you have IDENTIFIED 1016 proteins?

場景二：ｘｘ大學ｘｘ資深教授辦公室 資深教授：ｘｘ助理教授！你们實驗室上次identified的蛋白質，我用了三種不同的antibodies都無法確認，你說到底是怎麼一回事？資淺助理教授：＠＃＄％＆！

場景三：ｘｘ學術研討會演講會場 聽眾：ｘｘ蛋白質只出現在細胞核，為甚麼會出現在extracellular matrix? 演講者：因為…… 我要是知道就好了!

What can be learned from these experiences! “Confidence level” in protein identification by mass spectrometry is not only a matter of research interest, but also a vital information for decision-making in daily business for protein mass spectrometrist.

Black Box ? Protein(s) Identification Mass spectrometry

Breaking down the black box of protein ID by MS Black Box ? Protein(s) Identification fractionation MS/MS proteolysis MS/MS raw data x N Protein(s) Peptide(s) peak selection sequence database search Peptide list MS/MS peak list x N sorting confirmation Protein list Biological significance

Breaking down the black box of protein ID by MS Black Box ? Protein(s) Identification fractionation MS/MS proteolysis MS/MS raw data x N Protein(s) Peptide(s) ion trap, Q-TOF, TOF/TOF FT-MS? protease? chroma- tography? peak selection algorithm? deisotoped? sequence database search Peptide list MS/MS peak list x N algorithm? mass error tolerance? database? cutoff criteria? manual validation? spectral quality? PROBIBILITY-BASED SCORING? sorting algorithm? criteria? validation? probability model? confirmation Protein list Biological significance immunoassay? functional assay?

A last word on protein identification by MS and database searching (From John S. Cottrell, Tutorial on “Database Searching for Protein Identification”, ASMS 2005, San Antonio, USA)

Basic ideas behind extending MS sequencing to post-translational modifications (PTMs) • De novo sequencing is only possible when a limited and small number (i.e., 20) of amino acids are existing and each amino acid residue has distinct mass. • Considering any one particular type of PTM (i.e., phosphorylation) increases the complexity of de novo sequencing. • Various types of PTMs (acetylation, sulfation, oxidation, deamidation, glycocylation, lipid attachment, …etc) have been observed. • PTM site determination is often performed when the sequence is known

九十四年度台灣質譜學會教育課程

九十四年度台灣質譜學會教育課程

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