This work was supported by the New College of Interdisciplinary Arts and Sciences at Arizona State University, Applied Maths NV, and by the National Science Foundation (ROA Supplement to Award No. MCB0604300). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

注意 ：どのような環境からの未確認細菌は病原性とすることができ、適切なバイオセーフティプロトコルを使用して、慎重に処理する必要があります。ライブ文化との仕事は生物学的安全レベル2（BSL-2）の手順を使用して、クラスII安全キャビネットで実行する必要があります。 BSL-2手続きの詳細については、CDC / NIHのタイトルのマニュアル、「微生物学的および生物医学研究所でバイオセーフティ、「ページ33-38で利用可能です。ドキュメントは、オンラインで利用可能です<a href="http://www.cdc.gov/biosafety/publications/bmbl5/BMBL.pdf">http://www.cdc.gov/biosafety/publications/bmbl5/BMBL.pdf</a> 。白衣/ガウン、安全眼鏡、及びニトリルまたはラテックス手袋など適切な個人用保護具（P​​PE）は、着用しなければならない。標準微生物学的慣行や注意事項に従わなければならず、バイオハザード廃棄物は適切に廃棄しなければならない。 このデモで使用される細菌は、カーチェナー洞窟から単離した、AZ、USA、ドライ鍾乳石、フロー石、湿った鍾乳石や鍾乳石のドリップ（ 表1）を含む4つの環境から。すべての分離株は、16S rDNAの塩基配列決定によって同定され、25％グリセロール、R 2 B培地中で-80℃で保存した。すべての実験は、室温で完了した。 注：私たちは、データベース構築と未知数の質量スペクトルのための質量スペクトルを取得するために、同じサンプル調製方法を使用することをお勧めします。試料調製法は、スペクトルの品質および再現3に影響することが以前に示されている。異なる試料調製方法を使用すると、（株レベルで、例えば 、）より高い分類学的解像度が所望される場合は特に、未知数の誤った識別を引き起こし得る。 MALDIターゲット1.沈着 注意 ：タンパク質抽出物を得るためのいくつかのプロトコルは、酸とのguidに従って利用されなければならない有機溶媒の使用を必要とするそれぞれの材料安全データシート（MSDS）に含まれるelines情報。適切なPPEは、アセトニトリルなどの毒性、引火性溶剤、かなりの量で作業するときに使用する必要があります着用しなければならないと種類とボリューム使用される化学物質の（ 例えば 、白衣/ガウン、手袋、安全眼鏡、および呼吸器保護により変動するため、ギ酸およびトリフルオロ酢酸などの腐食性の酸、）。 <ol><li>ステンレス製MALDIターゲットプレート上に、それを乾燥させ（必要に応じて、以前に記載されているプロトコル11-13を用いて得られた）は生細胞を含まないタンパク質抽出μlの預金1。 1μlのマトリックス溶液（αシアノ-4-ヒドロキシ桂皮酸溶液）を用いて乾燥させたタンパク質抽出物をオーバーレイし、それを乾燥させる。 </li><li>各生物学的反復のために、技術的反復（5から20技術的反復）の適切な数を見つける。ここでは、それぞれの生物学的複製のための10の技術的複製物および3生物学的複製ワットを発見ERE準備。 注意：我々は、タンパク質抽出試料調製方法を使用している場合に磨かMALDI鋼ターゲットプレートを使用することをお勧めします。グランド鋼ターゲットプレートを使用すると、個々のサンプルウェルの外側の異なるサンプルの混合を拡散意図しない引き起こすことがある。 </li><li>預金1μlの較正用ターゲットプレート上の標準とそれを乾燥させる。 1μlのマトリックス溶液とオーバーレイし、それを乾燥させる。 </li><li>陰性対照として、ターゲットプレート上に堆積物2μlのマトリックス溶液。 </li></ol> 2.マススペクトルの取得<ol><li>窒素レーザー（λ= 337nmで）を備えたMALDI-TOF質量分析計を使用したBruker FlexControlソフトウェアを使用して動作する。 </li><li> 100ショット単位で500レーザーショットの蓄積によって正の線形モードにおける各質量スペクトルを収集する。 20 kVのイオン源1の電圧を設定します。イオン源2電圧18.15 kVのに。と9.05 kVのにレンズ電圧。これらのパラメータは楽器-speciであることに注意してくださいFICと最適な結果を得るために、他の楽器に調整が必要になる場合があります。 </li><li> 2からの充電あたりの20kDaに自動化されたスペクトル評価のための質量電荷範囲を設定します。重心ピーク検出アルゴリズムを使用してください。 100ダでの最小分解能しきい値を設定します。 100での最小強度しきい値を設定2.しきい値：ノイズ比（N S）に信号を設定します。 </li></ol> 3.データベース構築<ol><li>データベース設計<ol><li> 「新しいデータベースウィザード」を使用してBioNumerics 7.1で新しいデータベースを作成します。 </li><li> 「実験タイプ」パネルでコマンドを使用して、 例えば 、のMALDIスペクトル実験タイプを作成します。 </li><li> 「データベース設計パネル」を使用してレベルを作成します。 「データベース」メニューの「レベル&gt;新しいレベルを追加... &quot;コマンドを使用して新しいレベルを追加。ここで、「種」レベル、「生物学的複製 &quot;レベル」と「技術複製」レベル、respectivを作成エリー。 </li></ol></li><li>生の質量スペクトルのインポートと前処理<ol><li> 「ファイル」メニューの「エクスポート&gt;マススペクトル」コマンドをクリックしてFlexAnalysisを使用して.txtファイルとして生の質量スペクトルをエクスポートします。 </li><li>技術的反復のレベルのデータベースに生の質量スペクトル（.txtファイル）をインポートします。 </li><li>生の質量スペクトル前処理を行います。 <ol><li>インポートとリサンプル（二次フィッティングアルゴリズムを使用して）。 </li><li> （50点の大きさと転がりディスク付き）ベースライン減算を実行します。 </li><li> （20ポイントと10ポイントのベータのウィンドウサイズとカイザー窓）なめらかな、ノイズ[連続ウェーブレット変換（CWT）]を計算し、第二のベースラインの減算（200ポイントの大きさと転がりディスク）を行う。 </li><li> [10：ノイズ比（N S）の最小信号CWT]ピークを検出する。 </li></ol></li><li>前処理した後、そのようなピークを含むピークリストなどの各マススペクトルの特徴的なパターンを保存大きさ、ピーク強度、S：データベース内のN など 。 </li></ol></li><li>複合質量スペクトルを作成する<ol><li> 「分析」メニューの「要約... &quot;コマンドを使用して、前処理済みのスペクトルから複合スペクトルを作成します。目標レベルとして「生物学的複製」を選択してください。 </li><li>ここでは、「生物学的複製」レベルでの分離株の3つの複合質量スペクトルで、その結果、そのコロニーのための複合質量スペクトルを得るために、同じコロニーの10技術的反復の質量スペクトルを兼ね備えています。 </li><li>ここでは、それは「種」レベルで分離するための一つの複合スペクトルを作成するために3複合スペクトルをまとめる。 注：複合スペクトルは、技術的反復のポイントバイポイント平均である。 95％未満（初期設定）の平均値との類似性（ピアソン相関）を複製する合成から除外される。彼らは、75％で存在する場合、複合スペクトル上のピークのみ（と呼ばれ含まの複製のデフォルト設定）。生物学的複製のために、これらの設定は、それぞれ、90および60％であった。 </li></ol></li></ol> 4.マススペクトルデータ解析<ol><li>データベース内のエントリを選択し、「比較」パネルに「新しい比較を作成する」コマンドをクリックして、比較を作成。 </li><li>ここで、比較·分析を表示するには「技術の複製」および/または「生物学的複製」のレベルで質量スペクトルを使用しています。 </li><li>類似性に基づくクラスター分析および多次元スケーリング（MDS） <ol><li>色でグループを作成します。 3生物学的複合マススペクトルを選択し、対応する分離株のためのグループを作成するには、「グループ」メニューの「選択範囲から新しいグループを作成」コマンドをクリックします。自動的にこれら3質量スペクトルに使用する色を指定します。 </li><li>あるいは、「でコマンドを使用して対応する色で、フィールドの状態を定義するこの定義されたフィールドに基づくグループ化がこのグループのために定義された同じ色を使用するように、データベースエントリ」パネル。 </li><li>クラスター分析を行います。 「クラスタリング」メニューの「クラスター分析の計算」コマンドをクリックします。比較設定の1ページ目で、「ピアソン相関」を選択し、デフォルトなどの他のパラメータを残す。 2ページ、「UPGMA」を選択します。その後、「完了」をクリックします。 </li><li> 「統計」メニューの「多次元スケーリング... &quot;コマンドを使用して、MDSプロットを取得します。 </li></ol></li><li>ピークマッチング<ol><li> 「実験」のパネルで、スペクトルタイプ「MALDI」をクリックします。その後、「レイアウト&gt;の表示画像」を選択します。スペクトルは、ゲルのバンドとして示されている。 </li><li> 「スペクトラ」メニューの「ピークマッチングを行い &quot;コマンドを使用してピークマッチングを行います。 </li></ol></li><li>ピーククラスの識別<ol><li>主成分分析（PCA）を実行する。強調表示」実験MALDI」の実験タイプ &quot;&quot;パネルと使用し、「PCAを実行するために統計的「メニュー」でコマンドを「主成分分析...。 </li><li> 2-Wayクラスタリングを実行します。 「比較」ウィンドウの「統計&gt;マトリックスマイニング」を...クリックします。ピークのクラスに一致するピークの強度は、異なる色（ヒートマップ）を用いて表される。 </li></ol></li></ol>カスタムデータベース5.細菌同定<ol><li>類似性係数に基づく方法<ol><li>比較を作成し、ステップ4.3.3で説明したように「技術の反復 &quot;レベルで質量スペクトルに基づく系統樹を生成する。類似性の比較のために系統樹を保存します。 </li><li> 「選択したエントリの識別&gt;分析 &quot;未知の質量スペクトルを選択し、クリックします。識別ダイアログボックスが表示されます。 </li><li> 「比較に基づく「分類器の種類（またはストアドclassifを選択IER）と「次へ」をクリックします。次のページで、「次の「参照比較として保存樹形図を選択し、[OK]をクリックします。 </li><li>識別方法として「基本類似性」を選択し、「次へ」をクリックします。 </li><li>採点方法として「最大類似性」を選択してください。各パラメータの適切なしきい値と最小差分値を入力し、「次へ」をクリックします。 </li><li>計算が完了すると、識別ウィンドウが表示されます。 「結果」パネルで、最高の未知の一致するデータベースのメ​​ンバーが一覧表示されます。 </li><li>識別プロジェクトを保存し、「識別プロジェクト」パネルで、「クロス検証解析」コマンドを使用して識別を検証する。 </li></ol></li><li>潜在的なバイオマーカーに基づく方法<ol><li>ピークのクラスを定義します。 「マトリックスマイニング」ウィンドウで、共通の特性を共有するピークのセットを選択し、speciとしてこれらのピークを定義する使用してFICピーククラス（潜在的なバイオマーカー）」スペクトル&gt;ピーククラスタイプの管理...」「比較ウィンドウ」で。 </li><li>ここでは、すべての15の分離株のために隔離するごとに、特定のピークのクラスを定義します。 </li><li>未知数の質量スペクトルを選択し、前述のように定義されたピークのクラスにこれらのスペクトルのピークと一致する。 </li></ol></li></ol>

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R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+designed+experiments+approach+to+optimization+of+automated+data+acquisition+during+characterization+of+bacteria+with+MALDI-TOF+mass+spectrometry.">A designed experiments approach to optimization of automated data acquisition during characterization of bacteria with MALDI-TOF mass spectrometry.</a> Plos One. 9 (3), (2014).</li><li>Christner, M., Rohde, H., Wolters, M., Sobottka, I., Wegscheider, K., Aepfelbacher, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rapid+identification+of+bacteria+from+positive+blood+culture+bottles+by+use+of+matrix-assisted+laser+desorption-ionization+time+of+flight+mass+spectrometry+fingerprinting.">Rapid identification of bacteria from positive blood culture bottles by use of matrix-assisted laser desorption-ionization time of flight mass spectrometry fingerprinting.</a> J ClinMicrobiol. 48 (5), 1584-1591 (2010).</li></ol>

Authors Vranckx and Janssens are employees of Applied Maths NV, the manufacturer of data analysis software used in this video. Applied Maths NV provided select software modules highlighted in this video as well as a portion of the publication costs associated with this video.

このデモでは、特性評価およびMALDI-TOF MSおよびカスタム·データベースを使用して、細菌の同定の詳細な手順を示した。例えば、伝統的な分子的方法、16S rDNAの塩基配列決定と比較して、MALDI-TOF MSベースのフィンガープリント法は、多様な細菌のより迅速な識別を容易にする。 、そのロバスト性のため、この技術は、広く環境から臨床現場1,14-16細菌、ウイルス、真菌および酵母を特?...

Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) has been shown to be a rapid and reliable tool for identification of bacteria at the genus, species, and in some cases, strain levels1-4. MALDI-TOF MS ionizes biological molecules (typically proteins) that originate from cell surfaces, intracellular membranes, and ribosomes from bacterial whole cells or protein extracts1,5. The resulting peaks form characteristic patterns or &#8220;fingerprints&#8221; of the bacteria analyzed1. Identification of bacteria is based on these mass-to-charge &#8220;fingerprints&#8221;. 
Two of the most commonly used identification strategies are library-based and bioinformatics-based strategies1. Library-based approaches involve comparing the mass spectra of unknowns to previously collected mass spectra of known bacteria in databases/libraries for identification. Commercially available software, such as BioNumerics, Biotyper, and SARAMIS software packages, as well as open source software tools, such as SpectraBank6, are available to facilitate the comparison and quantification of similarity between mass spectra of unknowns and reference bacteria. Bioinformatics-based approaches usually rely on fully sequenced genomes of bacteria for identification. In contrast to library-based approaches which do not involve identification of the biological nature of particular peaks, bioinformatics-based approaches involve protein identification1. 
The majority of recent MALDI fingerprint-based studies have used library-based approaches to identify bacteria1. Library-based approaches require construction of databases and comparison of the similarity between mass spectra. Studies show that many experimental procedures, such as medium3,7, cultivation time8, sample preparation method3, and matrix used9, affect the mass spectra obtained. Furthermore, some closely-related species and strains generate spectra with only subtle differences. Thus, library-based approaches require rigorously standardized procedures to generate highly reproducible mass spectra between replicates. Minor variations in protocols may compromise the efficacy of identification, especially at the subspecies and strain levels1,3,10. However, neither manufacturer-provided reference databases nor reported custom databases include visually documented procedures for database construction and/or application of a data analysis pipeline. For this reason, the objective of this work was to develop, apply, and demonstrate a comprehensive and detailed procedure for library-based bacterial identification using MALDI-TOF MS. 
In this demonstration, mass spectra of 15 bacteria isolated from a karstic environment (Kartchner Cavern, AZ, USA) were collected and imported into software to construct a model database. Data processing and the analysis pipeline were detailed using the model database. Finally, mass spectra of blind-coded bacteria which were randomly selected from these 15 bacteria were collected again and compared to the reference spectra in the model database for identification. Results show that bacteria can be correctly identified either based on similarity coefficients or potential biomarkers/peak classes.

<table border="0" cellpadding="0" cellspacing="0">
	<tbody>
		<tr>
			<td>&#945;-cyano-4-hydroxy-cinnamic acid</td>
			<td>ACROS Organics</td>
			<td align="right">163440050</td>
			<td>&#8805; 97%, CAS 28168-41-8</td>
		</tr>
		<tr>
			<td>MALDI calibration kit</td>
			<td>Aigma-Aldrich</td>
			<td>MSCAL1-1KT</td>
			<td>This kit also contains acetonitrile, trifluoroacetic acid , sinapinic acid, etc.</td>
		</tr>
		<tr>
			<td>MALDI target plate</td>
			<td>Bruker Daltonics</td>
			<td align="right">280800</td>
			<td>Polished Steel</td>
		</tr>
		<tr>
			<td>Bruker Microflex LRF MALDI-TOF mass spectrometer</td>
			<td>Bruker Daltonics</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Bruker FlexControl software</td>
			<td>Bruker Daltonics</td>
			<td></td>
			<td>version 3.0</td>
		</tr>
		<tr>
			<td>Bruker FlexAnalysis software</td>
			<td>Bruker Daltonics</td>
			<td></td>
			<td>version 3.0</td>
		</tr>
		<tr>
			<td>Bionumerics software</td>
			<td>Applied Maths</td>
			<td></td>
			<td>version 7.1</td>
		</tr>
	</tbody>
</table>

use of maldi-tof mass spectrometry and a custom database to characterize bacteria indigenous to a unique cave environment (kartchner caverns, az, usa)

MALDI-TOF mass spectrometry has been shown to be a rapid and reliable tool for identification of bacteria at the genus and species, and in some cases, strain levels. Commercially available and open source software tools have been developed to facilitate identification; however, no universal/standardized data analysis pipeline has been described in the literature. Here, we provide a comprehensive and detailed demonstration of bacterial identification procedures using a MALDI-TOF mass spectrometer. Mass spectra were collected from 15 diverse bacteria isolated from Kartchner Caverns, AZ, USA, and identified by 16S rDNA sequencing. Databases were constructed in BioNumerics 7.1. Follow-up analyses of mass spectra were performed, including cluster analyses, peak matching, and statistical analyses. Identification was performed using blind-coded samples randomly selected from these 15 bacteria. Two identification methods are presented: similarity coefficient-based and biomarker-based methods. Results show that both identification methods can identify the bacteria to the species level.

このデモで構築したデータベースは、「すべてのレベル」、「種」、それぞれ「生物学的複製」と「技術複製」、（ 図1A）を含む、最高に最低レベルから、4つのレベルを持っていた。 「技術の複製」レベルは技術的反復のすべての前処理されたスペクトルを含んでいた。 「生物学的複製」と「種」レベルはコンポジット（サマリー）スペクトルを含んでいた。 「すべてのレベ?...

Watch this Scientific Journal Video about Use of MALDI-TOF Mass Spectrometry and a Custom Database to Characterize Bacteria Indigenous to a Unique Cave Environment Kartchner Caverns, AZ, USA at JoVE.c

Use of MALDI-TOF Mass Spectrometry and a Custom Database to Characterize Bacteria Indigenous to a Unique Cave Environment Kartchner Caverns, AZ, USA

This work details procedures for rapid identification of bacteria using MALDI-TOF MS. The identification procedures include spectrum acquisition, database construction, and follow up analyses. Two identification methods, similarity coefficient-based and biomarker-based methods, are presented.

MALDI-TOF質量分析およびカスタムデータベースを使用すると、ユニークな洞窟環境（カーチェナー洞窟、AZ、USA）を常在菌を特徴づけるために

MALDI-TOF mass spectrometry has been shown to be a rapid and reliable tool for identification of bacteria at the genus and species, and in some cases, ...

use-maldi-tof-mass-spectrometry-custom-database-to-characterize

Research

JoVE Journal

Biology

Use of MALDI-TOF Mass Spectrometry and a Custom Database to Characterize Bacteria Indigenous to a Unique Cave Environment (Kartchner Caverns, AZ, USA)

13.9K ビュー.  Arizona State University. This work details procedures for rapid identification of bacteria using MALDI-TOF MS. The identification procedures include spectrum acquisition, database construction, and follow up analyses. Two identification methods, similarity coefficient-based and biomarker-based methods, are presented. 

ビデオ: Use of MALDI-TOF Mass Spectrometry and a Custom Database to Characterize Bacteria Indigenous to a Unique Cave Environment Kartchner Caverns, AZ, USA

MALDI Sample Preparation: the Ultra Thin Layer Method

This video demonstrates the preparation of an ultra-thin matrix/analyte layer for analyzing peptides and proteins by Matrix-Assisted Laser Desorption Ionization Mass Spectrometry (MALDI-MS) 1,2. The ultra-thin layer method involves the production of a substrate layer of matrix crystals (alpha-cyano-4-hydroxycinnamic acid) on the sample plate, which serves as a seeding ground for subsequent crystallization of a matrix/analyte mixture. Advantages of the ultra-thin layer method over other sample deposition approaches (e.g. dried droplet) are that it provides (i) greater tolerance to impurities such as salts and detergents, (ii) better resolution, and (iii) higher spatial uniformity. This method is especially useful for the accurate mass determination of proteins. The protocol was initially developed and optimized for the analysis of membrane proteins and used to successfully analyze ion channels, metabolite transporters, and receptors, containing between 2 and 12 transmembrane domains 2. Since the original publication, it has also shown to be equally useful for the analysis of soluble proteins. Indeed, we have used it for a large number of proteins having a wide range of properties, including those with molecular masses as high as 380 kDa 3. It is currently our method of choice for the molecular mass analysis of all proteins. The described procedure consistently produces high-quality spectra, and it is sensitive, robust, and easy to implement.

This video demonstrates the preparation of an ultra-thin matrix/analyte layer for analyzing peptides and proteins by Matrix-Assisted Laser Desorption Ionization Mass Spectrometry (MALDI-MS).

MALDIサンプル調製：超薄層法

This video demonstrates the preparation of an ultra-thin matrix/analyte layer for analyzing peptides and proteins by Matrix-Assisted Laser Desorption ...

生物学

Quantification of Proteins Using Peptide Immunoaffinity Enrichment Coupled with Mass Spectrometry

There is a great need for quantitative assays in measuring proteins. Traditional sandwich immunoassays, largely considered the gold standard in quantitation, are associated with a high cost, long lead time, and are fraught with drawbacks (e.g. heterophilic antibodies, autoantibody interference, 'hook-effect').1 An alternative technique is affinity enrichment of peptides coupled with quantitative mass spectrometry, commonly referred to as SISCAPA (Stable Isotope Standards and Capture by Anti-Peptide Antibodies).2 In this technique, affinity enrichment of peptides with stable isotope dilution and detection by selected/multiple reaction monitoring mass spectrometry (SRM/MRM-MS) provides quantitative measurement of peptides as surrogates for their respective proteins. SRM/MRM-MS is well established for accurate quantitation of small molecules 3, 4 and more recently has been adapted to measure the concentrations of proteins in plasma and cell lysates.5-7 To achieve quantitation of proteins, these larger molecules are digested to component peptides using an enzyme such as trypsin. One or more selected peptides whose sequence is unique to the target protein in that species (i.e. "proteotypic" peptides) are then enriched from the sample using anti-peptide antibodies and measured as quantitative stoichiometric surrogates for protein concentration in the sample. Hence, coupled to stable isotope dilution (SID) methods (i.e. a spiked-in stable isotope labeled peptide standard), SRM/MRM can be used to measure concentrations of proteotypic peptides as surrogates for quantification of proteins in complex biological matrices. The assays have several advantages compared to traditional immunoassays. The reagents are relatively less expensive to generate, the specificity for the analyte is excellent, the assays can be highly multiplexed, enrichment can be performed from neat plasma (no depletion required), and the technique is amenable to a wide array of proteins or modifications of interest.8-13 In this video we demonstrate the basic protocol as adapted to a magnetic bead platform.

Stable Isotope Standards and Capture by Anti-Peptide Antibodies (SISCAPA) couples affinity enrichment of peptides with stable isotope dilution mass spectrometry (MRM-MS) to provide quantitative measurement of peptides as surrogates for their respective proteins. Here we describe the protocol using magnetic particles in a partially automated format.

質量分析法とあいまってペプチドイムノエンリッチメントを使用したタンパク質の定量化

There is a great need for quantitative assays in measuring proteins. Traditional sandwich immunoassays, largely considered the gold standard in ...

Amide Hydrogen/Deuterium Exchange &amp; MALDI-TOF Mass Spectrometry Analysis of Pak2 Activation

Amide hydrogen/deuterium exchange (H/D exchange) coupled with mass spectrometry has been widely used to analyze the interface of protein-protein interactions, protein conformational changes, protein dynamics and protein-ligand interactions. H/D exchange on the backbone amide positions has been utilized to measure the deuteration rates of the micro-regions in a protein by mass spectrometry1,2,3. The resolution of this method depends on pepsin digestion of the deuterated protein of interest into peptides that normally range from 3-20 residues. Although the resolution of H/D exchange measured by mass spectrometry is lower than the single residue resolution measured by the Heteronuclear Single Quantum Coherence (HSQC) method of NMR, the mass spectrometry measurement in H/D exchange is not restricted by the size of the protein4. H/D exchange is carried out in an aqueous solution which maintains protein conformation. We provide a method that utilizes the MALDI-TOF for detection2, instead of a HPLC/ESI (electrospray ionization)-MS system5,6. The MALDI-TOF provides accurate mass intensity data for the peptides of the digested protein, in this case protein kinase Pak2 (also called &gamma;-Pak). Proteolysis of Pak 2 is carried out in an offline pepsin digestion. This alternative method, when the user does not have access to a HPLC and pepsin column connected to mass spectrometry, or when the pepsin column on HPLC does not result in an optimal digestion map, for example, the heavily disulfide-bonded secreted Phospholipase A2 (sPLA2). Utilizing this method, we successfully monitored changes in the deuteration level during activation of Pak2 by caspase 3 cleavage and autophosphorylation7,8,9.

MALDI-TOF mass spectrometry was successfully utilized to monitor the amide hydrogen/deuterium exchange in protein kinase Pak2 activation.

PAK2活性化のアミド水素/重水素交換とMALDI - TOF質量分析

Amide hydrogen/deuterium exchange (H/D exchange) coupled with mass spectrometry has been widely used to analyze the interface of protein-protein ...

A Fluorescence-based Exonuclease Assay to Characterize DmWRNexo, Orthologue of Human Progeroid WRN Exonuclease, and Its Application to Other Nucleases

WRN exonuclease is involved in resolving DNA damage that occurs either during DNA replication or following exposure to endogenous or exogenous genotoxins. It is likely to play a role in preventing accumulation of recombinogenic intermediates that would otherwise accumulate at transiently stalled replication forks, consistent with a hyper-recombinant phenotype of cells lacking WRN. In humans, the exonuclease domain comprises an N-terminal portion of a much larger protein that also possesses helicase activity, together with additional sites important for DNA and protein interaction. By contrast, in Drosophila, the exonuclease activity of WRN (DmWRNexo) is encoded by a distinct genetic locus from the presumptive helicase, allowing biochemical (and genetic) dissection of the role of the exonuclease activity in genome stability mechanisms. Here, we demonstrate a fluorescent method to determine WRN exonuclease activity using purified recombinant DmWRNexo and end-labeled fluorescent oligonucleotides. This system allows greater reproducibility than radioactive assays as the substrate oligonucleotides remain stable for months, and provides a safer and relatively rapid method for detailed analysis of nuclease activity, permitting determination of nuclease polarity, processivity, and substrate preferences.

Exonucleases play critical roles in ensuring genome stability. Loss of WRN exonuclease function results in premature aging. Studying substrates and other requirements of the nuclease in vitro can help elucidate its role in vivo. Here we demonstrate a rapid and reproducible fluorescence-based assay to measure its nuclease activity.

WRN exonuclease is involved in resolving DNA damage that occurs either during DNA replication or following exposure to endogenous or exogenous genotoxins. ...

Capture Compound Mass Spectrometry - A Powerful Tool to Identify Novel c-di-GMP Effector Proteins

Considerable progress has been made during the last decade towards the identification and characterization of enzymes involved in the synthesis (diguanylate cyclases) and degradation (phosphodiesterases) of the second messenger c-di-GMP. In contrast, little information is available regarding the molecular mechanisms and cellular components through which this signaling molecule regulates a diverse range of cellular processes. Most of the known effector proteins belong to the PilZ family or are degenerated diguanylate cyclases or phosphodiesterases that have given up on catalysis and have adopted effector function. Thus, to better define the cellular c-di-GMP network in a wide range of bacteria experimental methods are required to identify and validate novel effectors for which reliable in silico predictions fail.
We have recently developed a novel Capture Compound Mass Spectrometry (CCMS) based technology as a powerful tool to biochemically identify and characterize c-di-GMP binding proteins. This technique has previously been reported to be applicable to a wide range of organisms1. Here we give a detailed description of the protocol that we utilize to probe such signaling components. As an example, we use Pseudomonas aeruginosa, an opportunistic pathogen in which c-di-GMP plays a critical role in virulence and biofilm control. CCMS identified 74% (38/51) of the known or predicted components of the c-di-GMP network. This study explains the CCMS procedure in detail, and establishes it as a powerful and versatile tool to identify novel components involved in small molecule signaling.

The ubiquitous second messenger c-di-GMP controls growth and behavior of many bacteria. We have developed a novel Capture Compound Mass Spectrometry based technology to biochemically identify and characterize c-di-GMP binding proteins in virtually any bacterial species.

捕獲化合物質量分析 - 小説のc-ジ-GMPエフェクタータンパク質を同定するための強力なツール

Considerable progress has been made during the last decade towards the identification and characterization of enzymes involved in the synthesis ...

Using Digital Image Correlation to Characterize Local Strains on Vascular Tissue Specimens

Characterization of the mechanical behavior of biological and engineered soft tissues is a central component of fundamental biomedical research and product development. Stress-strain relationships are typically obtained from mechanical testing data to enable comparative assessment among samples and in some cases identification of constitutive mechanical properties. However, errors may be introduced through the use of average strain measures, as significant heterogeneity in the strain field may result from geometrical non-uniformity of the sample and stress concentrations induced by mounting/gripping of soft tissues within the test system. When strain field heterogeneity is significant, accurate assessment of the sample mechanical response requires measurement of local strains. This study demonstrates a novel biomechanical testing protocol for calculating local surface strains using a mechanical testing device coupled with a high resolution camera and a digital image correlation technique. A series of sample surface images are acquired and then analyzed to quantify the local surface strain of a vascular tissue specimen subjected to ramped uniaxial loading. This approach can improve accuracy in experimental vascular biomechanics and has potential for broader use among other native soft tissues, engineered soft tissues, and soft hydrogel/polymeric materials. In the video, we demonstrate how to set up the system components and perform a complete experiment on native vascular tissue.

We describe the use of digital image correlation to characterize the local surface strain field on vascular tissue samples subjected to uniaxial tensile testing. These measurements facilitate precise quantification of the sample mechanical response and the generation of constitutive stress-strain relations.

デジタル画像相関を使用すると、血管の組織標本のローカル株を特徴づけるために、

Characterization of the mechanical behavior of biological and engineered soft tissues is a central component of fundamental biomedical research and ...

Identification of MyoD Interactome Using Tandem Affinity Purification Coupled to Mass Spectrometry

Skeletal muscle terminal differentiation starts with the commitment of pluripotent mesodermal precursor cells to myoblasts. These cells have still the ability to proliferate or they can differentiate and fuse into multinucleated myotubes, which maturate further to form myofibers. Skeletal muscle terminal differentiation is orchestrated by the coordinated action of various transcription factors, in particular the members of the Muscle Regulatory Factors or MRFs (MyoD, Myogenin, Myf5, and MRF4), also called the myogenic bHLH transcription factors family. These factors cooperate with chromatin-remodeling complexes within elaborate transcriptional regulatory network to achieve skeletal myogenesis. In this, MyoD is considered the master myogenic transcription factor in triggering muscle terminal differentiation. This notion is strengthened by the ability of MyoD to convert non-muscle cells into skeletal muscle cells. Here we describe an approach used to identify MyoD protein partners in an exhaustive manner in order to elucidate the different factors involved in skeletal muscle terminal differentiation. The long-term aim is to understand the epigenetic mechanisms involved in the regulation of skeletal muscle genes, i.e., MyoD targets. MyoD partners are identified by using Tandem Affinity Purification (TAP-Tag) from a heterologous system coupled to mass spectrometry (MS) characterization, followed by validation of the role of relevant partners during skeletal muscle terminal differentiation. Aberrant forms of myogenic factors, or their aberrant regulation, are associated with a number of muscle disorders: congenital myasthenia, myotonic dystrophy, rhabdomyosarcoma and defects in muscle regeneration. As such, myogenic factors provide a pool of potential therapeutic targets in muscle disorders, both with regard to mechanisms that cause disease itself and regenerative mechanisms that can improve disease treatment. Thus, the detailed understanding of the intermolecular interactions and the genetic programs controlled by the myogenic factors is essential for the rational design of efficient therapies.

MyoD is a myogenic transcription factor with a strong capacity to induce myogenic transdifferentiation of many fully differentiated non-muscle cell lines. The epigenetic mechanisms involved in this transdifferentiation are largely unknown. Here we describe a double-affinity purification method followed by mass spectrometry to exhaustively characterize MyoD partners.

タンデムアフィニティー精製を使用してのMyoDインタラクトームの同定は、質量分析に結合します

Skeletal muscle terminal differentiation starts with the commitment of pluripotent mesodermal precursor cells to myoblasts. These cells have still the ...

Complete Workflow for Analysis of Histone Post-translational Modifications Using Bottom-up Mass Spectrometry: From Histone Extraction to Data Analysis

Nucleosomes are the smallest structural unit of chromatin, composed of 147 base pairs of DNA wrapped around an octamer of histone proteins. Histone function is mediated by extensive post-translational modification by a myriad of nuclear proteins. These modifications are critical for nuclear integrity as they regulate chromatin structure and recruit enzymes involved in gene regulation, DNA repair and chromosome condensation. Even though a large part of the scientific community adopts antibody-based techniques to characterize histone PTM abundance, these approaches are low throughput and biased against hypermodified proteins, as the epitope might be obstructed by nearby modifications. This protocol describes the use of nano liquid chromatography (nLC) and mass spectrometry (MS) for accurate quantification of histone modifications. This method is designed to characterize a large variety of histone PTMs and the relative abundance of several histone variants within single analyses. In this protocol, histones are derivatized with propionic anhydride followed by digestion with trypsin to generate peptides of 5 - 20 aa in length. After digestion, the newly exposed N-termini of the histone peptides are derivatized to improve chromatographic retention during nLC-MS. This method allows for the relative quantification of histone PTMs spanning four orders of magnitude.

This protocol outlines a fully integrated workflow for characterizing histone post-translational modifications using mass spectrometry (MS). The workflow includes histone purification from cell cultures or tissues, histone derivatization and digestion, MS analysis using nano-flow liquid chromatography and instructions for data analysis. The protocol is designed for completion within 2 - 3 days.

ヒストンの抽出からデータ解析まで：ボトムアップ質量分析法を用いてヒストンの翻訳後修飾の解析のための完全なワークフロー

Nucleosomes are the smallest structural unit of chromatin, composed of 147 base pairs of DNA wrapped around an octamer of histone proteins. Histone ...

At-Risk Butterfly Captive Propagation Programs to Enhance Life History Knowledge and Effective Ex Situ Conservation Techniques

Improving knowledge of ex situ best practices for at-risk butterflies is important for generating successful conservation and recovery program outcomes. Research on such captive populations can also yield valuable data to address key information gaps about the behavior, life history, and ecology of the target taxa. We describe a protocol for captive propagation of the federally endangered Cyclargus thomasi bethunebakeri that can be used as a model for other at-risk butterfly ex situ programs, especially those in the family Lycaenidae. We further provide a simple and straightforward protocol for recording various life history metrics that can be useful for informing ex situ methodologies as well as adapted for laboratory studies of other lepidoptera.

Here, we present protocols for 1) the laboratory captive propagation of the federally endangered Miami blue butterfly (Cyclargus thomasi bethunebakeri), and 2) assessing basic life history information such as immature development time and number of larval stadia. Both methods can be adapted for use with other ex situ conservation programs.

生命史知識と効果的な元現場保全技術を強化するための危険な蝶捕虜伝播プログラム

Improving knowledge of ex situ best practices for at-risk butterflies is important for generating successful conservation and recovery program outcomes. ...

Mass Spectrometry Analysis to Identify Ubiquitylation of EYFP-tagged CENP-A (EYFP-CENP-A)

Studying the structure and the dynamics of kinetochores and centromeres is important in understanding chromosomal instability (CIN) and cancer progression. How the chromosomal location and function of a centromere (i.e., centromere identity) are determined and participate in accurate chromosome segregation is a fundamental question. CENP-A is proposed to be the non-DNA indicator (epigenetic mark) of centromere identity, and CENP-A ubiquitylation is required for CENP-A deposition at the centromere, inherited through dimerization between cell division, and indispensable to cell viability.
Here we describe mass spectrometry analysis to identify ubiquitylation of EYFP-CENP-A K124R mutant suggesting that ubiquitylation at a different lysine is induced because of the EYFP tagging in the CENP-A K124R mutant protein. Lysine 306 (K306) ubiquitylation in EYFP-CENP-A K124R was successfully identified, which corresponds to lysine 56 (K56) in CENP-A through mass spectrometry analysis. A caveat is discussed in the use of GFP/EYFP or the tagging of high molecular weight protein as a tool to analyze the function of a protein. Current technical limit is also discussed for the detection of ubiquitylated bands, identification of site-specific ubiquitylation(s), and visualization of ubiquitylation in living cells or a specific single cell during the whole cell cycle.
The method of mass spectrometry analysis presented here can be applied to human CENP-A protein with different tags and other centromere-kinetochore proteins. These combinatory methods consisting of several assays/analyses could be recommended for researchers who are interested in identifying functional roles of ubiquitylation.

Mass Spectrometry Analysis to Identify Ubiquitylation of EYFP-tagged CENP-A EYFP-CENP-A

CENP-A ubiquitylation is an important requirement for CENP-A deposition at the centromere, inherited through dimerization between cell division, and indispensable to cell viability. Here we describe mass spectrometry analysis to identify ubiquitylation of EYFP-tagged CENP-A (EYFP-CENP-A) protein.