We thank SP Gygi and GM Church for help and guidance. This work was supported by a CNRS chaire d'excellence to ACT.

NOTA: Este método fue descrito previamente 12. 1. De aislamiento de proteínas Prepare 1 mg de proteína celular por las células de lisis, preferiblemente por métodos físicos como la prensa francesa, golpes de talón, o ultrasonidos. Evitar la lisozima lisis celular mediada porque la enzima confundirá mediciones de espectrometría de masas. 2. Precipitación con TCA de las proteínas Añadir ácido tricloroacético 1 volumen (TCA) a 4 volúmenes de proteínas y se enfría en hielo durante 10 minutos para precipitar las proteínas. Centrifugar a 12.000 xg durante 5 min a 4 ° C y retirar el sobrenadante. Resuspender el precipitado en 1 ml de acetona enfriada con hielo y se centrifuga a 12.000 xg durante 5 min a 4 ° C. Eliminar el sobrenadante e invierta el tubo en el banco para secar el sedimento durante 15 min. Pellets de proteína Almacenar a -80 ° C. 3. Desnaturalizar las proteínas y reducir enlaces disulfuro Resuspender las proteínas a ~ 2 mg / ml en 500 l de tampón de desnaturalización y reducción (o bien 4 M de urea o SDS al 3% en 50 mM de HEPES, pH 8,5, DTT 5 mM). Opcionalmente, incluir un inhibidor de la proteasa en la memoria intermedia. Incubar las proteínas durante 30 min a 56 ° C, seguido por 10 min a temperatura ambiente. 4. Aklylate gratis Sulfidrilo Grupos de perturbar irreversiblemente disulfuro Formación Prepare fresco 0,3 M yodoacetamida en agua. ¡CUIDADO! Yodoacetamida es altamente tóxico. Añadir 25 l 0,3 M yodoacetamida (15 mM de concentración final) a 500 l de proteína y se incuba durante 20 min en la oscuridad a temperatura ambiente. Sacia yodoacetamida añadiendo 10 l de 300 mM DTT (5 mM concentración final TDT). Guarde proteínas alquiladas a -80 ° C. 5. La digestión de proteínas TCA precipitar proteínas (como se describe en el paso 2) y resuspender en 1 ml de HEPES 50 mM (pH 8,2), 1 M de urea. Preparar una solución madre de Lisil endoproteinASE (Lys-C) en agua a una concentración de 2 g / l y añadir 5 l de la solución de proteína. Incubar la mezcla durante 16 horas a temperatura ambiente. Asegúrese de que la concentración final Lys-C es 10 ng / l y la relación proteína-a-LysC (W / W) es 1/50 a 1/200. Resuspender 20 g de tripsina grado de secuenciación en 40 l de 50 mM de ácido acético, añadir 5 l (10 mg de tripsina) a la Lys-C digest, y se incuba durante 6 horas a 37 ° C. Utilice la misma concentración de proteasa y proporciones-proteasa-a proteína para Lys-C tal como se utiliza para la tripsina. 6. De fase inversa de péptidos Extracción <ol><li> Acidificar péptidos mediante la adición de ácido trifluoroacético (TFA) a una concentración final de 0,5% (pH ≈ 2). Adjuntar una columna C18 a un colector de extracción. Utilice el caudal más alto posible para todas las etapas, excepto carga y la elución de los péptidos. </li><li> Columna húmeda con 6 ml de acetonitrilo (ACN). Lavar la columna con 6 ml de 80% de ACN, 0,1% de TFA, a continuación, se equilibre con 6 ml de TFA al 0,1%. No permita que lacolumna para funcionar en seco entre los pasos. </li><li> Deja de presión de vacío y carga de 500 g de péptidos en la columna a un caudal de aproximadamente 1 ml / min. Una vez que los péptidos se han unido a la columna, de vacío reinicio y se lava con 6 ml de TFA al 0,1%, a continuación con 3 ml de tampón de ácido cítrico (0,09 M de ácido cítrico, 0,23 M de Na 2 HPO 4, pH 5,5). Nota: las cantidades de péptido más altas pueden ser etiquetados, pero la columna C18 capacidad de unión deben ser al menos dos veces mayores que la cantidad de péptido para evitar la pérdida de muestra. </li></ol> 7. En la columna de péptido etiquetado por reductiva dimethylation (REDI Etiquetado) Realice este paso en una campana química como cianuro de hidrógeno se libera en baja concentración durante el proceso de etiquetado. <ol><li> Preparar 12 ml de &quot;ligeros&quot; y tampones Redi &quot;pesados&quot; para metilar aminas péptido libres. Búfer Redi Luz consta de 0,8% de formaldehído y 0,12 M de cianoborohidruro de sodio llevar hidrógenos en their distribuciones isotópicas naturales en tampón de ácido cítrico. Búfer Redi pesado consiste en 0,8% de formaldehído deuterado y 0,12 M de cianoborohidruro de sodio deuterado en tampón ácido cítrico. </li><li> Incubar columna que contiene péptidos mediante la adición de 10 ml ya sea de luz o de amortiguamiento Redi pesada para las columnas que contienen péptidos a un caudal de 1 ml / min y repetir para asegurar el etiquetado completo. Lavar la columna con 6 ml de TFA al 0,1% y luego con ácido acético 1 ml de 0,5%. </li><li> Deja de vacío y eluir péptidos marcados primero con 1 ml de 40% de ACN, ácido acético 0,5%, luego con 1 ml de 80% de ACN, 0,5% de ácido acético utilizando un caudal de aproximadamente 0,5 ml / min. Si lo desea, mida la eficiencia de marcaje de muestras individuales por espectrometría de masas antes de mezclar muestras pesadas y ligeras (véase &quot;Los resultados representativos&quot;). Mezclar 01:01 péptido muestras pesadas y ligeras que llevan la etiqueta de ser cuantificados por espectrometría de masas. </li></ol> 8. Separate Péptido Mezcla por Basic pH Fase Invertida (BPRP) Cromatografía &lt;/ P&gt; PH básico cromatografía de fase inversa (BPRP) para separar la mezcla de péptidos en múltiples fracciones, que se analizan de forma independiente por LC-MS/MS para aumentar la cobertura del proteoma. <ol><li> Fraccionar la mezcla de péptidos en una columna C18-HPLC mediante la aplicación de un gradiente de concentración creciente de ACN en 10 mM de bicarbonato de amonio (pH 8). Comience con 5% (v / v) de ACN durante 5 min, aumentar a 35% de ACN en 60 min, y luego a 90% de ACN en 1 min. Conservar la ACN 90% durante 4 min antes de reducir la ACN a 5% para volver a equilibrar la columna para 9 min. Recoger 96 fracciones de igual volumen en una placa de 96 pocillos (A1 a H12). Supervisar el fraccionamiento utilizando un detector UV a 220 nm, mientras que los péptidos se eluyen de la columna (10-70 min durante las condiciones descritas aquí). </li><li> Se combinan las fracciones de los pozos A1, C1, E1, G1 y (fracción A1), a partir de los pocillos B1, D1, F1, y H1 (fracción B1), de los pozos A2, C2, E2, y G2 (fracción A2) y en consecuencia para la restantes fracciones. Retire la solvent usando una centrífuga de vacío. Péptidos Resuspender de fracciones A1, B2, A3, B4, A5, B6, A7, B8, A9, B10, A11 y B12 en 130 l de 1 M urea/0.5% TFA y purificar usando StageTips como se describe en el paso 9. Tienda fracciones B1, A2, B3, A4, B5, A6, B7, A8, B9, A10, B11 y A12 a -20 º C. </li></ol> 9. Purify péptidos por Stop and Go Extracción (StageTips) Preparar C18-StageTip 7 microcolumnas por el embalaje de 200 puntas de pipeta l con dos C18 discos con un diámetro interno (ID) de 1,07 mm. Poner Consejos Etapa en tubos Eppendorf. Utilice una microcentrífuga para lavar consejos con 130 l de metanol, a continuación, 130 ul 80% de ACN, ácido acético 0,5%. Equilibre StageTips con 130 l 0,1% de TFA. Transferir la mezcla de péptidos a StageTips y se lava con 130 l 0,1% de TFA, a continuación, 40 l 0,1% de TFA, a continuación, 40 l de ácido acético al 0,5%. Eluir péptidos primero con 20 l 40% de ACN, ácido acético 0,5%, a continuación, 20 l 80% de ACN, ácido acético 0,5%. Combine eluidos unnd seco por filtración al vacío. 10. Microcapilares LC-MS/MS <ol><li> Disolver péptidos en 1-5 l de ácido fórmico al 5%, 5% de ACN a una concentración de aproximadamente 1 g / l. Resolver ~ 1 g péptidos en un 100 micras × 20 cm C18-invertidas columna de HPLC de fase con un gradiente de 6-22% de ACN en ácido fórmico al 0,125% aplicado sobre 75 o 100 min a una velocidad de flujo de ~ 300 Nl / min. </li><li> Identificar péptidos usando un LTQ Velos Orbitrap 12 o plataforma similar cromatografía líquida-espectrometría de masas con un espectrómetro de masa que disponga de alta resolución y alta precisión en masa. Operar el espectrómetro de masas en modo dependiente de los datos con una MS de barrido completo (resolución de 60000) adquiridos en el analizador Orbitrap. Generar trampa de iones lineal espectros MS / MS para los 20 más abundantes iones detectados en el espectro MS. Ajuste el control automático de ganancia (AGC) objetivos a 1 x 10 6 para el pleno MS y 2000 para MS / MS. Establecer tiempos máximos de acumulación de iones para 1000 msegpara MS y 150 mseg para MS / MS. Excluir iones precursores de péptidos fragmentados de una selección adicional de MS / MS de 20-60 seg. </li></ol> 11. MS / MS de Adquisición de Datos Identificar péptidos mediante la comparación de archivos RAW espectros MS / MS a una base de datos teórica con un algoritmo tal como SEQUEST 8 usando estos parámetros (Tabla 1). Tabla 1. Péptido de bases de datos de parámetros de búsqueda. <table border="0" cellpadding="0" cellspacing="0" width="600"><tbody><tr height="19"><td height="19" rowspan="3" style="height:19px;" width="180"> Parámetros generales </td><td> digestión plenamente tríptico con hasta 2 perdió divisiones </td></tr><tr height="19"><td> 25 ppm de iones de precursor de la tolerancia </td></tr><tr height="19"><td> 1.0 Da fragmento de la tolerancia de iones </td></tr><tr height="35"><td height="35" rowspan="2" style="height:36px;"> Modificaciones estáticas </strong&gt; </td><td> 57.02146 Da en cisteína, carboxiamidometilación </td></tr><tr height="19"><td> 28.03130 Da en lisina y el péptido N-terminal, etiqueta dimethylation luz </td></tr><tr height="19"><td height="19" rowspan="2" style="height:19px;"> Modificaciones dinámicas </td><td> 15.99491 Da en metionina, la oxidación </td></tr><tr height="19"><td> 6.03766 Da en lisina y el péptido N-terminal, etiqueta dimethylation pesada </td></tr></tbody></table><ol><li> Filtrar péptidos a una tasa de falso descubrimiento 1% con un método como la estrategia de objetivo señuelo 9 usando una base de datos de los marcos de lectura abiertos en las orientaciones reales e invertidas. </li></ol> 12. Péptido Cuantificación Calcular las áreas de pares pesadas y ligeras de MS1 extrajeron los cromatogramas de iones (áreas de los picos MS1) y el péptido de señal a ruido (S / N) las relaciones de 10. Incluya pares peptídicos sólo cuando su media de señal a noirelación en sí está por encima de cinco. Cuantificar la abundancia relativa de un péptido en las dos muestras como la relación de áreas de los picos de MS1 versiones pesadas y ligeras de la misma péptido (proporción de área de pico MS1). Cálculo de las abundancias de proteínas relativos como la relación del área del pico MS1 mediana para todos los péptidos en la proteína.

<ol>
	<li>Washburn, M. P., Ulaszek, R., Deciu, C., Schieltz, D. M., Yates III, J. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+quantitative+proteomic+data+generated+via+multidimensional+protein+identification+technology.">Analysis of quantitative proteomic data generated via multidimensional protein identification technology.</a> Analytical chemistry. 74 (7), 1650-1657 (2002).</li><li>Ong, S. -. E., Blagoev, B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Stable+isotope+labeling+by+amino+acids+in+cell+culture,+SILAC,+as+a+simple+and+accurate+approach+to+expression+proteomics.">Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics.</a> Molecular &amp; cellular proteomics: MCP. 1 (5), 376-386 (2002).</li><li>Gygi, S. P., Rist, B., Gerber, S. A., Turecek, F., Gelb, M. H., Aebersold, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+analysis+of+complex+protein+mixtures+using+isotope-coded+affinity+tags.">Quantitative analysis of complex protein mixtures using isotope-coded affinity tags.</a> Nature biotechnology. 17 (10), 994-999 (1999).</li><li>Ross, P. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiplexed+protein+quantitation+in+Saccharomyces+cerevisiae+using+amine-reactive+isobaric+tagging+reagents.">Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents.</a> Molecular &amp; cellular proteomics: MCP. 3 (12), 1154-1169 (2004).</li><li>Hsu, J. -. L., Huang, S. -. Y., Chow, N. -. H., Chen, S. -. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Stable-isotope+dimethyl+labeling+for+quantitative+proteomics.">Stable-isotope dimethyl labeling for quantitative proteomics.</a> Analytical Chemistry. 75 (24), 6843-6852 (2003).</li><li>Chick, J. M., Haynes, P. A., Molloy, M. P., Bjellqvist, B., Baker, M. S., Len, A. C. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Characterization+of+the+rat+liver+membrane+proteome+using+peptide+immobilized+pH+gradient+isoelectric+focusing.">Characterization of the rat liver membrane proteome using peptide immobilized pH gradient isoelectric focusing.</a> Journal of Proteome Research. 7 (3), 1036-1045 (2008).</li><li>Rappsilber, J., Ishihama, Y., Mann, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Stop+and+go+extraction+tips+for+matrix-assisted+laser+desorption/ionization,+nanoelectrospray,+and+LC/MS+sample+pretreatment+in+proteomics.">Stop and go extraction tips for matrix-assisted laser desorption/ionization, nanoelectrospray, and LC/MS sample pretreatment in proteomics.</a> Analytical chemistry. 75 (3), 663-670 (2003).</li><li>Eng, J. K., McCormack, A. L., Yates III, J. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+approach+to+correlate+tandem+mass+spectral+data+of+peptides+with+amino+acid+sequences+in+a+protein+database.">An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database.</a> Journal of the American Society for Mass Spectrometry. 5 (11), 976-989 (1994).</li><li>Elias, J. E., Gygi, S. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Target-decoy+search+strategy+for+increased+confidence+in+large-scale+protein+identifications+by+mass+spectrometry.">Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry.</a> Nature methods. 4 (3), 207-214 (2007).</li><li>Bakalarski, C. E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+impact+of+peptide+abundance+and+dynamic+range+on+stable-isotope-based+quantitative+proteomic+analyses.">The impact of peptide abundance and dynamic range on stable-isotope-based quantitative proteomic analyses.</a> Journal of Proteome Research. 7 (11), 4756-4765 (2008).</li><li>Wilson-Grady, J. T., Haas, W., Gygi, S. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+comparison+of+the+fasted+and+re-fed+mouse+liver+phosphoproteomes+using+lower+pH+reductive+dimethylation.">Quantitative comparison of the fasted and re-fed mouse liver phosphoproteomes using lower pH reductive dimethylation.</a> Methods (San Diego, Calif.). , (2013).</li><li>Tolonen, A. C., Haas, W., Chilaka, A. C., Aach, J., Gygi, S. P., Church, G. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Proteome-wide+systems+analysis+of+a+cellulosic+biofuel-producing+microbe.">Proteome-wide systems analysis of a cellulosic biofuel-producing microbe.</a> Molecular Systems Biology. 7, 461 (2011).</li><li>Tolonen, A. C., Chilaka, A. C., Church, G. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Targeted+gene+inactivation+in+Clostridium+phytofermentans+shows+that+cellulose+degradation+requires+the+family+9+hydrolase+Cphy3367.">Targeted gene inactivation in Clostridium phytofermentans shows that cellulose degradation requires the family 9 hydrolase Cphy3367.</a> Molecular Microbiology. 74 (6), 1300-1313 (2009).</li><li>Munoz, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+quantitative+proteomes+of+human-induced+pluripotent+stem+cells+and+embryonic+stem+cells.">The quantitative proteomes of human-induced pluripotent stem cells and embryonic stem cells.</a> Molecular systems biology. 7, 550 (2011).</li><li>Kovanich, D., Cappadona, S., Raijmakers, R., Mohammed, S., Scholten, A., Heck, A. J. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Applications+of+stable+isotope+dimethyl+labeling+in+quantitative+proteomics.">Applications of stable isotope dimethyl labeling in quantitative proteomics.</a> Analytical and bioanalytical chemistry. 404 (4), 991-1009 (2012).</li><li>McAlister, G. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Increasing+the+multiplexing+capacity+of+TMTs+using+reporter+ion+isotopologues+with+isobaric+masses.">Increasing the multiplexing capacity of TMTs using reporter ion isotopologues with isobaric masses.</a> Analytical chemistry. 84 (17), 7469-7478 (2012).</li><li>Boersema, P. J., Aye, T. T., Van Veen, T. A. B., Heck, A. J. R., Mohammed, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Triplex+protein+quantification+based+on+stable+isotope+labeling+by+peptide+dimethylation+applied+to+cell+and+tissue+lysates.">Triplex protein quantification based on stable isotope labeling by peptide dimethylation applied to cell and tissue lysates.</a> Proteomics. 8 (22), 4624-4632 (2008).</li><li>Wu, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Five-plex+isotope+dimethyl+labeling+for+quantitative+proteomics.">Five-plex isotope dimethyl labeling for quantitative proteomics.</a> Chemical communications (Cambridge, England). , (2014).</li><li>Boersema, P. J., Raijmakers, R., Lemeer, S., Mohammed, S., Heck, A. J. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiplex+peptide+stable+isotope+dimethyl+labeling+for+quantitative+proteomics.">Multiplex peptide stable isotope dimethyl labeling for quantitative proteomics.</a> Nature Protocols. 4 (4), 484-494 (2009).</li><li>She, Y. -. M., Rosu-Myles, M., Walrond, L., Cyr, T. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantification+of+protein+isoforms+in+mesenchymal+stem+cells+by+reductive+dimethylation+of+lysines+in+intact+proteins.">Quantification of protein isoforms in mesenchymal stem cells by reductive dimethylation of lysines in intact proteins.</a> Proteomics. 12 (3), 369-379 (2012).</li><li>Chen, S. -. H., Chen, C. -. R., Chen, S. -. H., Li, D. -. T., Hsu, J. -. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Improved+N(&#945;)-acetylated+Peptide+Enrichment+Following+Dimethyl+Labeling+and+SCX.">Improved N(&#945;)-acetylated Peptide Enrichment Following Dimethyl Labeling and SCX.</a> Journal of proteome research. 12 (7), 3277-3287 (2013).</li><li>Sun, Z., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Capture+and+Dimethyl+Labeling+of+Glycopeptides+on+Hydrazide+Beads+for+Quantitative+Glycoproteomics+Analysis.">Capture and Dimethyl Labeling of Glycopeptides on Hydrazide Beads for Quantitative Glycoproteomics Analysis.</a> Analytical Chemistry. 84 (20), 8452-8456 (2012).</li></ol>

Los autores declaran no tener que compiten intereses financieros u otros conflictos de intereses.

Varios puntos hacen que el etiquetado de isótopos estables de péptidos utilizando un método atractivo para proteómica cuantitativa dimethylation reductora (etiquetado REDI): reactivos baratos etiquetado (reactivos cuestan menos de $ 1 por muestra), la velocidad de reacción rápida (~ 10 min), ausencia de productos secundarios, altas reproducibilidad (Figuras 3, 4), productos de reacción estable, capacidad de utilizar cualquier proteasa y de alta eficiencia de ionización de péptidos marcados. Eti...

Medición de diferencias de concentración de muchas proteínas entre muestras complejas es un reto central en la proteómica. Cada vez más, esto se hace mediante el etiquetado de proteínas en cada muestra con diferentes etiquetas isotópicas, la combinación de las muestras, y el uso de la espectrometría de masas para cuantificar las diferencias de concentración. Existen varios métodos para el marcaje isotópico estable de proteínas y péptidos. 15 N etiquetado 1 y 2 SILAC introducen marcadores isotópicos metabólicamente in vivo, mientras que iCAT 3, iTRAQ 4, y la reducción de dimethylation 5 agregan etiquetas de isótopos estables después de la extracción de proteínas y la digestión. Entre estos métodos, dimetilación reductora (etiquetado Redi) está ganando popularidad como un método económico y reproducible para cuantificar las diferencias de concentración de proteína en casi cualquier tipo de muestra. Etiquetado Redi implica péptidos que reaccionan con el formaldehído para formar una base de Schiff, que se reduce luegode cianoborohidruro. Esta reacción dimethylates grupos amino libres en N-terminales y cadenas laterales de lisina y monomethylates prolinas N-terminales. El protocolo descrito aquí methylates péptidos en la muestra 1 con una etiqueta de &quot;luz&quot; usando reactivos con átomos de hidrógeno en su distribución isotópica natural y la muestra 2 con una etiqueta de &quot;pesado&quot; con formaldehído deuterado y cianoborohidruro (Figura 1). Cada grupo amino dimetilado en un péptido da como resultado una diferencia de masa de 6,0377 Da entre la luz y las formas pesados, que se emplea para distinguir entre las dos formas utilizando un espectrómetro de masas. Específicamente, las abundancias relativas de péptidos se cuantifican como la relación de áreas cromatograma de iones extraídos MS1 (relación de área de pico MS1) de la luz y la versión pesada para cada par de iones de péptido. La abundancia relativa de una proteína se calcula como la mediana relación de área de pico MS1 entre todos los péptidos en la proteína. En este reporte se describe un protocolo robusto por conductaing experimentos de etiquetado Redi por LC-MS/MS que incluye la extracción de fase inversa de péptidos en fase sólida, etiquetado Redi en columna, fraccionamiento por pH básico péptido en fase inversa (BPRP) cromatografía, y la purificación de mezclas de péptidos utilizando StageTips (Figura 2) . Se discuten las ventajas y limitaciones del uso de etiquetado Redi para proteómica cuantitativa.

<table border="0" cellpadding="0" cellspacing="0" width="973">
	<tbody>
		<tr height="19">
			<td height="19" style="height:19px;width:377px;">trichloroacetic acid</td>
			<td style="width:141px;">Sigma-Aldrich</td>
			<td style="width:136px;">T9159</td>
			<td style="width:319px;">protein precipitation</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">acetone</td>
			<td>Sigma-Aldrich</td>
			<td style="width:136px;">650501</td>
			<td>protein precipitation</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">Sodium dodecyl sulfate</td>
			<td>Sigma-Aldrich</td>
			<td style="width:136px;">71736</td>
			<td>denature, reduce protein</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">sodium hydroxide</td>
			<td>Sigma-Aldrich</td>
			<td style="width:136px;">S8045</td>
			<td>denature, reduce protein</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">DL-Dithiothreitol</td>
			<td>Sigma-Aldrich</td>
			<td style="width:136px;">43816</td>
			<td>denature, reduce, alkylate protein</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">protease Inhibitor Complete Mini Cocktail</td>
			<td>Roche</td>
			<td>4693124001</td>
			<td>denature, reduce protein</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">iodoacetamide</td>
			<td>Sigma-Aldrich</td>
			<td>I6125</td>
			<td>alkylate protein</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">HEPES</td>
			<td>Sigma-Aldrich</td>
			<td style="width:136px;">H7523</td>
			<td>resuspend, extract, label protein</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">calcium chloride</td>
			<td>Sigma-Aldrich</td>
			<td style="width:136px;">C5670</td>
			<td>resuspend protein</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;width:377px;">Lysyl Endoprotease</td>
			<td>Wako Chemicals</td>
			<td style="width:136px;">129-02541</td>
			<td>protein digestion</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">sequencing grade trypsin</td>
			<td>Promega</td>
			<td style="width:136px;">V5111</td>
			<td>protein digestion</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">acetic acid</td>
			<td>Sigma-Aldrich</td>
			<td style="width:136px;">320099</td>
			<td>protein digestion</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">trifluoroacetic acid</td>
			<td>Sigma-Aldrich</td>
			<td>299537</td>
			<td>Reversed-phase peptide extraction</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">tC18 Sep-Pak C18 cartridges</td>
			<td>Waters</td>
			<td>WAT054960</td>
			<td>Reversed-phase peptide extraction</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">extraction manifold</td>
			<td>Waters</td>
			<td>WAT200609</td>
			<td>Reversed-phase peptide extraction</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">acetonitrile</td>
			<td>Sigma-Aldrich</td>
			<td style="width:136px;">14261</td>
			<td>various</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">formaldehyde</td>
			<td>Sigma-Aldrich</td>
			<td>252549</td>
			<td>&#8220;light&#8221; peptide labeling</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">cyanoborohydride</td>
			<td>Sigma-Aldrich</td>
			<td style="width:136px;">71435</td>
			<td>&#8220;light&#8221; peptide labeling</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">deuterated formaldehyde</td>
			<td>Sigma-Aldrich</td>
			<td>492620</td>
			<td>&#8220;heavy&#8221; peptide labeling</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">sodium cyanoborodeuteride</td>
			<td>CDN isotopes</td>
			<td style="width:136px;">D-1797</td>
			<td>&#8220;heavy&#8221; peptide labeling</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">MES</td>
			<td>Sigma-Aldrich</td>
			<td>M3671</td>
			<td>peptide labeling</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">C18-HPLC column (4.6 x 250 mm, 5 &#181;m particle size)</td>
			<td>Agilent</td>
			<td style="width:136px;">770450-902</td>
			<td>basic pH reversed-phase chromatography</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">formic acid</td>
			<td>Sigma-Aldrich</td>
			<td style="width:136px;">399388</td>
			<td>various</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">C18 Empore Disks</td>
			<td>3M</td>
			<td style="width:136px;">14-386-3&#160;</td>
			<td>STAGE tips</td>
		</tr>
		<tr height="19">
			<td height="19" style="height:19px;">methanol</td>
			<td>Sigma-Aldrich</td>
			<td style="width:136px;">494437</td>
			<td>STAGE tips</td>
		</tr>
	</tbody>
</table>

quantitative proteomics using reductive dimethylation for stable isotope labeling

Etiquetado de isótopos estables de péptidos por dimethylation reductora (etiquetado REDI) es un método para cuantificar con precisión las diferencias de expresión de proteínas entre muestras mediante espectrometría de masas. Etiquetado REDI se lleva a cabo utilizando formas regulares deuterados (pesados) de formaldehído y cianoborohidruro de sodio (luz) o para agregar dos grupos metilo a cada amina libre. Aquí se demuestra un protocolo robusto para el etiquetado Redi y la comparación cuantitativa de mezclas complejas de proteínas. Proteína muestras para la comparación se digieren en péptidos, etiquetados para llevar la luz o las etiquetas de metilo pesados, mezclados, y co-analizados por LC-MS/MS. Abundancias de proteínas relativas se cuantificaron mediante la comparación de las áreas de los picos del cromatograma de iones de versiones pesadas y ligeras marcados de la péptido constituyente extraído de la plena espectros de MS. El método descrito aquí incluye preparación de la muestra por extracción en fase sólida de fase inversa, etiquetado Redi en columna de péptidos, péptido fraccionamiento por rev de pH básicofase ersed (BPRP) cromatografía y purificación de péptidos StageTip. Se discuten las ventajas y limitaciones de etiquetado Redi con respecto a otros métodos para la incorporación de isótopos estables. Destacamos las nuevas aplicaciones utilizando el etiquetado Redi como un método rápido, económico y preciso para comparar la abundancia de proteínas en casi cualquier tipo de muestra.

Se evaluó la exactitud, precisión y reproducibilidad de etiquetado Redi utilizando Saccharomyces cerevisiae y Clostridium phytofermentans lisados ​​de células enteras. Primero cuantificamos el etiquetado de eficiencia Redi de una mezcla de C. phytofermentans lisados ​​de proteínas a partir de celulosa culturas (pesada etiqueta, H) y glucosa (etiqueta de la luz, L). Cuando se filtra a un péptido falso descubrimiento tasa del 1%, la muestra contenía 11.194 secuencias de péptidos ?...

Watch this Scientific Journal Video about Quantitative Proteomics Using Reductive Dimethylation for Stable Isotope Labeling at JoVE.com

Quantitative Proteomics Using Reductive Dimethylation for Stable Isotope Labeling

Etiquetado de isótopos estables de péptidos por dimethylation reductora (etiquetado REDI) es una estrategia rápida, de bajo costo para la proteómica precisas de masa basados ​​en espectrometría cuantitativos. Aquí se demuestra un método robusto para la preparación y el análisis de mezclas de proteínas utilizando el enfoque Redi que se puede aplicar a casi cualquier tipo de muestra.

Proteómica cuantitativos utilizando reductiva dimethylation de isótopos estables de etiquetado

Stable isotope labeling of peptides by reductive dimethylation (ReDi labeling) is a method to accurately quantify protein expression differences between ...

quantitative-proteomics-using-reductive-dimethylation-for-stable

Research

JoVE Journal

Chemistry

16.0K vistas.  Genoscope.  Etiquetado de isótopos estables de péptidos por dimethylation reductora (etiquetado REDI) es una estrategia rápida, de bajo costo para la proteómica precisas de masa basados ​​en espectrometría cuantitativos. Aquí se demuestra un método robusto para la preparación y el análisis de mezclas de proteínas utilizando el enfoque Redi que se puede aplicar a casi cualquier tipo de muestra. 

Video: Quantitative Proteomics Using Reductive Dimethylation for Stable Isotope Labeling

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)

Non-targeted metabolite profiling by ultra performance liquid chromatography coupled with mass spectrometry (UPLC-MS) is a powerful technique to investigate metabolism. The approach offers an unbiased and in-depth analysis that can enable the development of diagnostic tests, novel therapies, and further our understanding of disease processes. The inherent chemical diversity of the metabolome creates significant analytical challenges and there is no single experimental approach that can detect all metabolites. Additionally, the biological variation in individual metabolism and the dependence of metabolism on environmental factors necessitates large sample numbers to achieve the appropriate statistical power required for meaningful biological interpretation. To address these challenges, this tutorial outlines an analytical workflow for large scale non-targeted metabolite profiling of serum by UPLC-MS. The procedure includes guidelines for sample organization and preparation, data acquisition, quality control, and metabolite identification and will enable reliable acquisition of data for large experiments and provide a starting point for laboratories new to non-targeted metabolite profiling by UPLC-MS.

Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry UPLC-MS

Non-targeted metabolite profiling by ultra performance liquid chromatography coupled with mass spectrometry (UPLC-MS) is a powerful technique to investigate metabolism. This article outlines a typical workflow utilized for non-targeted metabolite profiling of serum including sample organization and preparation, data acquisition, data analysis, quality control, and metabolite identification.

A gran escala que no son objeto de perfiles metabolómicos de Serum Ultra Performance Liquid Chromatography-espectrometría de masas (UPLC-MS)

Non-targeted metabolite profiling by ultra performance liquid chromatography coupled with mass spectrometry (UPLC-MS) is a powerful technique to ...

Investigación

Química

Improved In-gel Reductive &#946;-Elimination for Comprehensive O-linked and Sulfo-glycomics by Mass Spectrometry

Separation of proteins by SDS-PAGE followed by in-gel proteolytic digestion of resolved protein bands has produced high-resolution proteomic analysis of biological samples. Similar approaches, that would allow in-depth analysis of the glycans carried by glycoproteins resolved by SDS-PAGE, require special considerations in order to maximize recovery and sensitivity when using mass spectrometry (MS) as the detection method. A major hurdle to be overcome in achieving high-quality data is the removal of gel-derived contaminants that interfere with MS analysis. The sample workflow presented here is robust, efficient, and eliminates the need for in-line HPLC clean-up prior to MS. Gel pieces containing target proteins are washed in acetonitrile, water, and ethyl acetate to remove contaminants, including polymeric acrylamide fragments. O-linked glycans are released from target proteins by in-gel reductive &#946;-elimination and recovered through robust, simple clean-up procedures. An advantage of this workflow is that it improves sensitivity for detecting and characterizing sulfated glycans. These procedures produce an efficient separation of sulfated permethylated glycans from non-sulfated (sialylated and neutral) permethylated glycans by a rapid phase-partition prior to MS analysis, and thereby enhance glycomic and sulfoglycomic analyses of glycoproteins resolved by SDS-PAGE.

Improved In-gel Reductive &amp;#946;-Elimination for Comprehensive O-linked and Sulfo-glycomics by Mass Spectrometry

In order to comprehensively explore the diversity of O-linked glycans, a new procedure for in-gel reductive &#946;-elimination, combined with permethylation and a rapid phase-partition method, is applied to the analysis of O-linked glycans directly released from glycoproteins resolved by SDS-PAGE and amenable to subsequent glycomic analysis by mass spectrometry.

Mejora En-gel β-eliminación para ligada al O y exhaustiva sulfo-glycomics reductoras de Espectrometría de Masas

Separation of proteins by SDS-PAGE followed by in-gel proteolytic digestion of resolved protein bands has produced high-resolution proteomic analysis of ...

Quantitative and Qualitative Examination of Particle-particle Interactions Using Colloidal Probe Nanoscopy

Colloidal Probe Nanoscopy (CPN), the study of the nano-scale interactive forces between a specifically prepared colloidal probe and any chosen substrate using the Atomic Force Microscope (AFM), can provide key insights into physical interactions present within colloidal systems. Colloidal systems are widely existent in several applications including, pharmaceuticals, foods, paints, paper, soil and minerals, detergents, printing and much more.1-3 Furthermore, colloids can exist in many states such as emulsions, foams and suspensions. Using colloidal probe nanoscopy one can obtain key information on the adhesive properties, binding energies and even gain insight into the physical stability and coagulation kinetics of the colloids present within. Additionally, colloidal probe nanoscopy can be used with biological cells to aid in drug discovery and formulation development. In this paper we describe a method for conducting colloidal probe nanoscopy, discuss key factors that are important to consider during the measurement, and show that both quantitative and qualitative data that can be obtained from such measurements.

Colloidal probe nanoscopy can be used within a variety of fields to gain insight into the physical stability and coagulation kinetics of colloidal systems and aid in drug discovery and formulation sciences using biological systems. The method described within provides a quantitative and qualitative means to study such systems.

El examen cuantitativo y cualitativo de las interacciones entre partículas Uso coloidal Sonda Nanoscopia

Colloidal Probe Nanoscopy (CPN), the study of the nano-scale interactive forces between a specifically prepared colloidal probe and any chosen substrate ...

A Quantitative Glycomics and Proteomics Combined Purification Strategy

There is a growing desire in the biological and clinical sciences to integrate and correlate multiple classes of biomolecules to unravel biology, define pathways, improve treatment, understand disease, and aid biomarker discovery. N-linked glycosylation is one of the most important and robust post-translational modifications on proteins and regulates critical cell functions such as signaling, adhesion, and enzymatic function. Analytical techniques to purify and analyze N-glycans have remained relatively static over the last decade. While accurate and effective, they commonly require significant expertise and resources. Though some high-throughput purification schemes have been developed, they have yet to find widespread adoption and often rely on the enrichment of glycopeptides. One promising method, developed by Thomas-Oates et al., filter aided N-glycan separation (FANGS), was qualitatively demonstrated on tissues. Herein, we adapted FANGS to plasma and coupled it to the individuality normalization when labeling with glycan hydrazide tags strategy in order to achieve accurate relative quantification by liquid chromatography mass spectrometry and enhanced electrospray ionization. Furthermore, we designed new functionality to the protocol by achieving tandem, shotgun proteomics and glycosylation site analysis on hen plasma. We showed that N-glycans purified on filter and derivatized by hydrophobic hydrazide tags were comparable in terms of abundance and class to those by solid phase extraction (SPE); the latter is considered a gold standard in the field. Importantly, the variability in the two protocols was not statistically different. Proteomic data that was collected in-line with glycomic data had the same depth compared to a standard trypsin digest. Peptide deamidation is minimized in the protocol, limiting non-specific deamidation detected at glycosylation motifs. This allowed for direct glycosylation site analysis, though the protocol can accommodate 18O site labeling as well. Overall, we demonstrated a new in-line high-throughput, unbiased, filter based protocol for quantitative glycomics and proteomics analysis.

A high-throughput protocol was developed for combined proteomics and glycomics purification and LC-MS/MS quantification in plasma. Deamidation analysis of N-linked glycosylation motifs was specific to deglycosylated sites. Accurate quantitation of N-glycans was achieved by coupling filter aided N-glycan separation to the individuality normalization when labeling with glycan hydrazide tags strategy.

Un Glicómica cuantitativa y Proteómica estrategia de purificación combinada

There is a growing desire in the biological and clinical sciences to integrate and correlate multiple classes of biomolecules to unravel biology, define ...

Standards for Quantitative Metalloproteomic Analysis Using Size Exclusion ICP-MS

Metals are essential for protein function as cofactors to catalyze chemical reactions. Disruption of metal homeostasis is implicated in a number of diseases including Alzheimer's and Parkinson's disease, but the exact role these metals play is yet to be fully elucidated. Identification of metalloproteins encounters many challenges and difficulties. Here we report an approach that allows metalloproteins in complex samples to be quantified. This is achieved using size exclusion chromatography coupled with inductively coupled plasma - mass spectrometry (SEC-ICP-MS). Using six known metalloproteins, the size exclusion column can be calibrated and the respective trace elements (iron, copper, zinc, cobalt, iodine) can be used for quantification. SEC-ICP-MS traces of human brain and plasma are presented. The use of these metalloprotein standards provides the means to quantitatively compare metalloprotein abundances between biological samples. This technique is poised to help shed light on the role of metalloproteins in neurodegenerative disease as well as other diseases where imbalances in trace elements are implicated.

Size exclusion chromatography hyphenated with inductively coupled plasma - mass spectrometry (ICP-MS) is a powerful tool to measure changes in the abundance of metalloproteins directly from biological samples. Here we describe a set of metalloprotein standards used to estimate molecular mass and the amount of metal associated with unknown proteins.

Estándares para el Análisis Cuantitativo de Metalloproteomic Uso de exclusión por tamaños ICP-MS

Metals are essential for protein function as cofactors to catalyze chemical reactions. Disruption of metal homeostasis is implicated in a number of ...

Peptide and Protein Quantification Using Automated Immuno-MALDI (iMALDI)

Mass spectrometry (MS) is one of the most commonly used technologies for quantifying proteins in complex samples, with excellent assay specificity as a result of the direct detection of the mass-to-charge ratio of each target molecule. However, MS-based proteomics, like most other analytical techniques, has a bias towards measuring high-abundance analytes, so it is challenging to achieve detection limits of low ng/mL or pg/mL in complex samples, and this is the concentration range for many disease-relevant proteins in biofluids such as human plasma. To assist in the detection of low-abundance analytes, immuno-enrichment has been integrated into the assay to concentrate and purify the analyte before MS measurement, significantly improving assay sensitivity. In this work, the immuno- Matrix-Assisted Laser Desorption/Ionization (iMALDI) technology is presented for the quantification of proteins and peptides in biofluids, based on immuno-enrichment on beads, followed by MALDI-MS measurement without prior elution. The anti-peptide antibodies are functionalized on magnetic beads, and incubated with samples. After washing, the beads are directly transferred onto a MALDI target plate, and the signals are measured by a MALDI-Time of Flight (MALDI-TOF) instrument after the matrix solution has been applied to the beads. The sample preparation procedure is simplified compared to other immuno-MS assays, and the MALDI measurement is fast. The whole sample preparation is automated with a liquid handling system, with improved assay reproducibility and higher throughput. In this article, the iMALDI assay is used for determining the peptide angiotensin I (Ang I) concentration in plasma, which is used clinically as readout of plasma renin activity for the screening of primary aldosteronism (PA).

Peptide and Protein Quantification Using Automated Immuno-MALDI iMALDI

A protocol for the protein quantification in complex biological fluids using automated immuno-MALDI (iMALDI) technology is presented.

Péptido y proteína cuantificación usando automatizado inmuno-MALDI (iMALDI)

Mass spectrometry (MS) is one of the most commonly used technologies for quantifying proteins in complex samples, with excellent assay specificity as a ...

Large-scale Top-down Proteomics Using Capillary Zone Electrophoresis Tandem Mass Spectrometry

Capillary zone electrophoresis-electrospray ionization-tandem mass spectrometry (CZE-ESI-MS/MS) has been recognized as a useful tool for top-down proteomics that aims to characterize proteoforms in complex proteomes. However, the application of CZE-MS/MS for large-scale top-down proteomics has been impeded by the low sample-loading capacity and narrow separation window of CZE. Here, a protocol is described using CZE-MS/MS with a microliter-scale sample-loading volume and a 90-min separation window for large-scale top-down proteomics. The CZE-MS/MS platform is based on a linear polyacrylamide (LPA)-coated separation capillary with extremely low electroosmotic flow, a dynamic pH-junction-based online sample concentration method with a high efficiency for protein stacking, an electro-kinetically pumped sheath flow CE-MS interface with extremely high sensitivity, and an ion trap mass spectrometer with high mass resolution and scan speed. The platform can be used for the high-resolution characterization of simple intact protein samples and the large-scale characterization of proteoforms in various complex proteomes. As an example, a highly efficient separation of a standard protein mixture and a highly sensitive detection of many impurities using the platform is demonstrated. As another example, this platform can produce over 500 proteoform and 190 protein identifications from an Escherichia coli proteome in a single CZE-MS/MS run.

A detailed protocol is described for the separation, identification, and characterization of proteoforms in protein samples using capillary zone electrophoresis-electrospray ionization-tandem mass spectrometry (CZE-ESI-MS/MS). The protocol can be used for the high-resolution characterization of proteoforms in simple protein samples and the large-scale identification of proteoforms in complex proteome samples.

Proteómica de arriba hacia abajo a gran escala mediante electroforesis capilar de zona Spectrometry total en tándem

Capillary zone electrophoresis-electrospray ionization-tandem mass spectrometry (CZE-ESI-MS/MS) has been recognized as a useful tool for top-down ...

Automated Sample Multiplexing by using Combined Precursor Isotopic Labeling and Isobaric Tagging (cPILOT)

We have introduced a high throughput quantitative proteomics workflow, combined precursor isotopic labeling and isobaric tagging (cPILOT) capable of multiplexing up to 22 or 24 samples with tandem mass tags or isobaric N,N-dimethyl leucine isobaric tags, respectively, in a single experiment. This enhanced sample multiplexing considerably reduces mass spectrometry acquisition times and increases the utility of the expensive commercial isobaric reagents. However, the manual process of sample handling and pipetting steps in the strategy can be labor intensive, time consuming, and introduce sample loss and quantitative error. These limitations can be overcome through the incorporation of automation. Here we transferred the manual cPILOT protocol to an automated liquid handling device that can prepare large sample numbers (i.e., 96 samples) in parallel. Overall, automation increases feasibility and reproducibility of cPILOT and allows for broad usage by other researchers with comparable automation devices.

Automated Sample Multiplexing by using Combined Precursor Isotopic Labeling and Isobaric Tagging cPILOT

Combined precursor isotopic labeling and isobaric tagging (cPILOT) is an enhanced sample multiplexing strategy that is capable of increasing the number of samples that can be analyzed simultaneously with available isobaric tags. Incorporation of a robotic platform has greatly increased experimental throughput, reproducibility, and quantitative accuracy.

Multiplexación automática de muestras mediante el etiquetado isotópico de precursor combinado y el etiquetado isobárico (cPILOT)

We have introduced a high throughput quantitative proteomics workflow, combined precursor isotopic labeling and isobaric tagging (cPILOT) capable of ...

Stable Aqueous Suspensions of Manganese Ferrite Clusters with Tunable Nanoscale Dimension and Composition

Manganese ferrite clusters (MFCs) are spherical assemblies of tens to hundreds of primary nanocrystals whose magnetic properties are valuable in diverse applications. Here we describe how to form these materials in a hydrothermal process that permits the independent control of product cluster size (from 30 to 120 nm) and manganese content of the resulting material. Parameters such as the total amount of water added to the alcoholic reaction media and the ratio of manganese to iron precursor are important factors in achieving multiple types of MFC nanoscale products. A fast purification method uses magnetic separation to recover the materials making production of grams of magnetic nanomaterials quite efficient. We overcome the challenge of magnetic nanomaterial aggregation by applying highly charged sulfonate polymers to the surface of these nanomaterials yielding colloidally stable MFCs that remain non-aggregating even in highly saline environments. These non-aggregating, uniform, and tunable materials are excellent prospective materials for biomedical and environmental applications.

We report a one-pot hydrothermal synthesis of manganese ferrite clusters (MFCs) that offers independent control over material dimension and composition. Magnetic separation allows rapid purification while surface functionalization using sulfonated polymers ensures the materials are non-aggregating in biologically relevant medium. The resulting products are well positioned for biomedical applications.

Suspensiones acuosas estables de grupos de ferrita de manganeso con dimensión y composición a nanoescala sintonizables

Manganese ferrite clusters (MFCs) are spherical assemblies of tens to hundreds of primary nanocrystals whose magnetic properties are valuable in diverse ...

Identificación de órganos primarios en plantas medicinales mediante el marcaje con 13C6-glucosa

13C6&#45;Glucose Labeling Associated with LC&#45;MS&#58; Identification of Plant Primary Organs in Secondary Metabolite Synthesis

This paper presents a novel and efficient method for certifying primary organs involved in secondary metabolite synthesis. As the most important secondary metabolite in Parispolyphylla var. yunnanensis (Franch.) Hand. -Mzt. (PPY), Paris saponin (PS) has a variety of pharmacological activities and PPY is in increasing demand. This study established leaf, rhizome, and stem-vascular-bundle 13C6-Glucose feeding and non-feeding four treatments to precisely certify the primary organs involved in Paris saponins VII (PS VII) synthesis. By combining liquid chromatography-mass spectrometry (LC-MS), the 13C/12C ratios of leaf, rhizome, stem, and root in different treatments were quickly and accurately calculated, and four types of PS isotopic ion peak(M&#8722;) ratios were found: (M+1) &#8722;/M&#8722;, (M+2) &#8722;/M&#8722;, (M+3) &#8722;/M&#8722; and (M+4) &#8722;/M&#8722;. The results showed that the ratio of 13C/12C in the rhizomes of the stem-vascular-bundle and rhizome feeding treatments was significantly higher than that in the non-feeding treatment. Compared to the non-feeding treatment, the ratio of PS VII molecules (M+2) &#8722;/M&#8722; in the leaves increased significantly under leaf and stem-vascular-bundle feeding treatments. Simultaneously, compared to the non-feeding treatment, the ratio of PS VII molecules (M+2) &#8722;/M&#8722; in the leaves under rhizome treatment showed no significant difference. Furthermore, the ratio of PS VII molecules (M+2) &#8722;/M&#8722; in the stem, root, and rhizome showed no differences among the four treatments. Compared to the non-feeding treatment, the ratio of the Paris saponin II (PS II) molecule (M+2) &#8722;/M&#8722; in leaves under leaf feeding treatment showed no significant difference, and the (M+3) &#8722;/M&#8722; ratio of PS II molecules in leaves under leaf feeding treatment were lower. The data confirmed that the primary organ for the synthesizing of PS VII is the leaves. It lays the foundation for future identification of the primary organs and pathways involved in the synthesis of secondary metabolites in medicinal plants.

Autor destacado: Perfil de órganos primarios de plantas mediante el etiquetado de 13C6-glucosa y LC-MS

The developed method of 13C6-Glucose labeling combined with liquid chromatography high-resolution mass spectrometry is versatile and lays the foundation for future studies on the primary organs and pathways involved in the synthesis of secondary metabolites in medicinal plants, as well as the comprehensive utilization of these secondary metabolites.

13Marcaje deC-6-glucosa asociado con LC-MS: identificación de órganos primarios de plantas en la síntesis de metabolitos secundarios

This paper presents a novel and efficient method for certifying primary organs involved in secondary metabolite synthesis. As the most important secondary ...