This work was supported in part by NIH awards F32-HL149191 to YH; R00-HL144829 to EL; R21-HL150456, R00-HL127302, R01-HL141278 to MPL. Figure&#160;1, Figure 2, Figure 3 are created with the aid of a web-based science illustration tool, BioRender.com.

<ol>
	<li>Geyer, P. 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=Revisiting+biomarker+discovery+by+plasma+proteomics.">Revisiting biomarker discovery by plasma proteomics.</a> Molecular Systems Biology. 13 (9), 942 (2017).</li><li>Coscia, F., 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=A+streamlined+mass+spectrometry-based+proteomics+workflow+for+large-scale+FFPE+tissue+analysis.">A streamlined mass spectrometry-based proteomics workflow for large-scale FFPE tissue analysis.</a> The Journal of Pathology. 251 (1), 100-112 (2020).</li><li>Yeung, Y. -. G., Neives, E., Angeletti, R., Stanley, E. R., 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=Removal+of+detergents+from+protein+digests+for+mass+spectrometry+analysis.">Removal of detergents from protein digests for mass spectrometry analysis.</a> Analytical Biochemistry. 382 (2), 135-137 (2008).</li><li>Addona, T. A., 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=Multi-site+assessment+of+the+precision+and+reproducibility+of+multiple+reaction+monitoring-based+measurements+of+proteins+in+plasma.">Multi-site assessment of the precision and reproducibility of multiple reaction monitoring-based measurements of proteins in plasma.</a> Nature Biotechnology. 27 (7), 633-641 (2009).</li><li>Lowenthal, M. S., Liang, Y., Phinney, K. W., Stein, S. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+bottom-up+proteomics+depends+on+digestion+conditions.">Quantitative bottom-up proteomics depends on digestion conditions.</a> Analytical Chemistry. 86 (1), 551-558 (2014).</li><li>Elliott, K. C., Resnik, D. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Scientific+reproducibility,+human+error,+and+public+policy.">Scientific reproducibility, human error, and public policy.</a> Bioscience. 65 (1), 5-6 (2015).</li><li>Brown, A. W., Kaiser, K. A., Allison, D. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Issues+with+data+and+analyses:+Errors,+underlying+themes,+and+potential+solutions.">Issues with data and analyses: Errors, underlying themes, and potential solutions.</a> Proceedings of the National Academy of Sciences of the United States of America. 115 (11), 2563-2570 (2018).</li><li>van den Broek, I., 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=Automated+multiplex+LC-MS/MS+assay+for+quantifying+serum+apolipoproteins+A-I,+B,+C-I,+C-II,+C-III,+and+E+with+qualitative+apolipoprotein+E+phenotypic.">Automated multiplex LC-MS/MS assay for quantifying serum apolipoproteins A-I, B, C-I, C-II, C-III, and E with qualitative apolipoprotein E phenotypic.</a> Clinical Chemistry. 62 (1), 188-197 (2016).</li><li>M&#252;ller, T., 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=Automated+sample+preparation+with+SP3+for+low-input+clinical+proteomics.">Automated sample preparation with SP3 for low-input clinical proteomics.</a> Molecular Systems Biology. 16 (1), 9111 (2020).</li><li>Fu, Q., 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=Highly+reproducible+automated+proteomics+sample+preparation+workflow+for+quantitative+mass+spectrometry.">Highly reproducible automated proteomics sample preparation workflow for quantitative mass spectrometry.</a> Journal of Proteome Research. 17 (1), 420-428 (2018).</li><li>Liu, X., Gygi, S. P., Paulo, J. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+semiautomated+paramagnetic+bead-based+platform+for+isobaric+tag+sample+preparation.">A semiautomated paramagnetic bead-based platform for isobaric tag sample preparation.</a> Journal of the American Society for Mass Spectrometry. 32 (6), 1519-1529 (2021).</li><li>Poulsen, K. M., Pho, T., Champion, J. A., Payne, C. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automation+and+low-cost+proteomics+for+characterization+of+the+protein+corona:+experimental+methods+for+big+data.">Automation and low-cost proteomics for characterization of the protein corona: experimental methods for big data.</a> Analytical and Bioanalytical Chemistry. 412 (24), 6543-6551 (2020).</li><li>Liang, 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=Fully+automated+sample+processing+and+analysis+workflow+for+low-input+proteome+profiling.">Fully automated sample processing and analysis workflow for low-input proteome profiling.</a> Analytical Chemistry. 93 (3), 1658-1666 (2021).</li><li>. Web URL Available from: <a target="_blank" href="https://opentrons.com/ot-app/">https://opentrons.com/ot-app/</a> (2021)</li><li>. Web URL Available from: <a target="_blank" href="https://docs.opentrons.com/v2/">https://docs.opentrons.com/v2/</a> (2021)</li><li>. Web URL Available from: <a target="_blank" href="https://www.cytivalifesciences.com/en/us/solutions/genomics/knowledge-center/cleanup-for-mass-spectrometry">https://www.cytivalifesciences.com/en/us/solutions/genomics/knowledge-center/cleanup-for-mass-spectrometry</a> (2021)</li><li>. Web URL Available from: <a target="_blank" href="https://www.thermofisher.com/order/catalog/product/23275#/23275">https://www.thermofisher.com/order/catalog/product/23275#/23275</a> (2021)</li><li>Han, Y., Wright, J. M., Lau, E., Lam, M. P. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Determining+alternative+protein+isoform+expression+using+RNA+sequencing+and+mass+spectrometry.">Determining alternative protein isoform expression using RNA sequencing and mass spectrometry.</a> STAR Protocols. 1 (3), 100138 (2020).</li></ol>

The authors have no conflicts to declare.

Critical steps within the protocol 
For the best performance, Opentrons-verified labware, modules, and consumables&#160;compatible with OT-2 should be used. Custom labware can be created following Opentrons&#39; instruction at Reference14. Make sure to calibrate the OT-2 deck, pipettes, and labware when used for the first time. It is also critical to follow guidelines from SP3 beads&#39; manufacturer to prepare beads for peptide and protein clean-up. Notably, during the bead ...

Mass spectrometry-based shotgun proteomics is a powerful tool to measure the abundance of many proteins in biological samples simultaneously. Proteomics experiments with bioinformatics analysis are routinely employed to identify biomarkers and discover associated biological complexes and pathways underpinning pathological mechanisms. With its high analyte specificity and potential quantitative accuracy, shotgun proteomics also has excellent potential to be adopted by research facilities and diagnostic laboratories for clinical sample analysis without the need to rely on antibodies1,2.
To prepare protein samples for shotgun proteomics analysis, proteins extracted from biological samples (e.g., cells and tissues) typically first need to be processed using lengthy protocols, including measuring the sample protein concentration, protein reduction, and alkylation, and enzymatic digestion into peptides. Moreover, proteins extracted in common lysis buffers containing detergents often require additional steps of buffer exchange or detergent removal before analysis because detergent can interfere with trypsin digestion and significantly degrade the performance of downstream liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis3. Peptides are typically further desalted, dried, and reconstituted in LC-MS/MS compatible solvents following enzymatic digestion. These protein biochemistry procedures can be labor-intensive and time-consuming. Thus, they continue to limit the throughput of proteomics workflows and contribute to the variability of acquired data4,5. Human errors and biases have been recognized as crucial factors affecting data variance and reproducibility6,7. To minimize human errors in mass spectrometry sample preparation workflows, automated pipetting robotic systems have been utilized to improve the throughput and reproducibility of protein identification and quantification from shotgun proteomics and targeted mass spectrometry analysis, where such advances have been hailed as instrumental for continuing the push for widespread adoption of proteomics technologies in critical research and clinical settings8,9,10,11,12,13. However, most existing protocols utilize robotic liquid handling platforms that require substantial investment and training, limiting their utility in many laboratories in the academic environment or otherwise with a limited budget.
This article describes a protocol that utilizes a low-cost, open-source robotic liquid handling system, the OT-2, to semi-automate a typical shotgun proteomics sample preparation workflow. The OT-2 has a lower cost than many other robotic liquid handling systems, and at the time of writing, costs approximately $5,000 US dollars. When factoring in the prices of different modules and labware, the total cost to set up experiments in this protocol at the time of writing is around $10,000, which renders it more affordable to a considerably broader set of laboratories over more expensive options. The OT-2 is compatible with open-source programming through Python scripts and offers great flexibilities in user-defined DIY protocol design. Using three in-house developed scripts, the protocols below cover executing a typical shotgun proteomics sample preparation workflow on the OT-2 station with an archetypical protein standard (bovine serum albumin; BSA) and a complex protein sample of a normal human heart lysate (Figure 1). The procedures for processing (1) a BSA sample and (2) a complex cardiac lysate sample are detailed in Protocol sections 1, 2, 5, 6 and 3, 4, 5, 6, respectively. Sera-Mag carboxylate-modified magnetic beads are utilized in single-pot solid-phase-enhanced sample preparation (SP3) to remove detergents and salts in the protein and peptide samples. Tryptic digests from bovine serum albumin and human heart proteins are further cleaned by SP3 beads and submitted for LC-MS/MS analysis. Mass spectra are then analyzed using the MaxQuant software for peptide and protein identification. Representative results performed by us show that the protocol achieves excellent technical coefficients of variation (CV) while saving bench time and is non-inferior to hand digest.

<table><tbody><tr><td>300 &amp;micro;L pipette tips</td><td>Opentrons</td><td></td><td></td></tr><tr><td>4-in-1 tube rack set</td><td>Opentrons</td><td></td><td>Each set includes 2 base stands and 4 tube holder tops 1.5mL, 2mL, 15mL + 50mL, 15mL, and 50mL. We use 2mL and 15 mL + 50 mL tops in this study.</td></tr><tr><td>Acclaim PepMap 100 C18 HPLC Column</td><td>Thermo Scientific</td><td>#164568</td><td>3 &amp;mu;m particle; 100 &amp;Aring; pore; 75 &amp;mu;m x 150 mm</td></tr><tr><td>Acetonitrile LC-MS grade</td><td>VWR</td><td>#JT9829</td><td></td></tr><tr><td>Aluminum block set</td><td>Opentrons</td><td></td><td>This block set includes 3 tops that are compatible with 96-well, 2.0 mL tubes and a PCR strip to use with the OT-2 temperature module. We use the 2.0mL tube holder in this manuscript.</td></tr><tr><td>Ammonium Bicarbonate</td><td>Sigma-Aldrich</td><td># A6141</td><td></td></tr><tr><td>Bovine Serum Albumin Standard, 2 mg/mL</td><td>Thermo Scientific</td><td>#23210</td><td></td></tr><tr><td>Dimethylsulfoxide (DMSO) LC-MS grade</td><td>Thermo Scientific</td><td>#85190</td><td></td></tr><tr><td>Dithiothreitol</td><td>Sigma-Aldrich</td><td>#D5545</td><td></td></tr><tr><td>EASY-Spray HPLC Columns</td><td>Thermo Scientific</td><td>#ES800A</td><td></td></tr><tr><td>EasynLC 1200 Nano LC</td><td>Thermo Scientific</td><td>#LC140</td><td></td></tr><tr><td>Ethanol Proof 195-200</td><td>Fisher</td><td>#04-355-720</td><td></td></tr><tr><td>Formic Acid LC-MS grade</td><td>Thermo Scientific</td><td>#85178</td><td></td></tr><tr><td>Human heart lysate</td><td>Novus Biologicals</td><td>NB820-59217</td><td></td></tr><tr><td>Iodoacetamide</td><td>Sigma-Aldrich</td><td>#I1149</td><td></td></tr><tr><td>Magnetic tube rack</td><td>Thermo Scientific</td><td>#MR02</td><td></td></tr><tr><td>MAXQuant v.1.6.10.43</td><td></td><td></td><td>Tyanova et al., 2016 (https://www.maxquant.org/)</td></tr><tr><td>mySPIN 6 Mini Centrifuge</td><td>Thermo Scientific</td><td>#75004061</td><td>benchtop mini centrifuge for quick spin</td></tr><tr><td>NEST 2 mL 96-Well Deep Well Plate, V Bottom</td><td>Opentrons</td><td></td><td></td></tr><tr><td>OT-2 magnetic module</td><td>Opentrons</td><td></td><td>GEN1</td></tr><tr><td>OT-2 P300 single channel pipette</td><td>Opentrons</td><td></td><td>GEN1</td></tr><tr><td>OT-2 P50 single channel pipette</td><td>Opentrons</td><td></td><td>GEN1</td></tr><tr><td>OT-2 robot pipetting robot</td><td>Opentrons</td><td>OT-2</td><td></td></tr><tr><td>OT-2 temperature module</td><td>Opentrons</td><td></td><td>GEN1</td></tr><tr><td>Pierce Quantitative Colorimetric Peptide Assay</td><td>Thermo Scientific</td><td>#23275</td><td></td></tr><tr><td>Protein LoBind tubes 2.0 mL</td><td>Eppendorf</td><td>#022431102</td><td></td></tr><tr><td>Protein Sequence Database</td><td>UniProt/SwissProt</td><td></td><td>https://www.uniprot.org/uniprot/?query=proteome:UP000005640%&lt;br/&gt; 20reviewed:yes</td></tr><tr><td>Sera-Mag SpeedBead Carboxylate-Modified Magnetic Particles, Hydrophobic</td><td>Cytiva</td><td>#65152105050250</td><td></td></tr><tr><td>Sera-Mag SpeedBead Carboxylate-Modified Magnetic Particles, Hydrophylic</td><td>Cytiva</td><td>#45152105050250</td><td></td></tr><tr><td>SpeedVac</td><td>Thermo Scientific</td><td></td><td>Vacuum evaporator</td></tr><tr><td>Thermo Q Exactive HF Mass Spectrometer</td><td>Thermo Scientific</td><td>#IQLAAEGAAPFALGMBFZ</td><td></td></tr><tr><td>Trypsin MS Grade</td><td>Thermo Scientific</td><td>#90057</td><td></td></tr><tr><td>Water LC-MS grade</td><td>VWR</td><td>#BDH83645.400</td><td></td></tr></tbody></table>

shotgun proteomics sample processing automated by an open-source lab robot

Mass spectrometry-based shotgun proteomics experiments require multiple sample preparation steps, including enzymatic protein digestion and clean-up, which can take up significant person-hours of bench labor and present a source of batch-to-batch variability. Lab automation with pipetting robots can reduce manual work, maximize throughput, and increase research reproducibility. Still, the steep starting prices of standard automation stations make them unaffordable for many academic laboratories. This article describes a proteomics sample preparation workflow using an affordable, open-source automation system (The Opentrons OT-2), including instructions for setting up semi-automated protein reduction, alkylation, digestion, and clean-up steps; as well as accompanying open-source Python scripts to program the OT-2 system through its application programming interface.

Three Python scripts are provided here that are compatible with the OT-2 robot, and that perform sample preparation for mass spectrometry proteomics with a single protein standard bovine serum albumin (technical replicates n = 5 digestions) and a detergent-containing human heart lysate sample (n = 5 digestions). Each digest product is partitioned into two peptide clean-up reactions. The number of identified peptide-spectrum matches (PSMs), peptides, and proteins in each run of the BSA and heart samples are shown in <stro...

Watch this Scientific Journal Video about Shotgun Proteomics Sample Processing Automated by an Open-Source Lab Robot at JoVE.com

Shotgun Proteomics Sample Processing Automated by an Open-Source Lab Robot

Detailed protocol and three Python scripts are provided for operating an open-source robotic liquid handling system to perform semi-automated protein sample preparation for mass spectrometry experiments, covering detergent removal, protein digestion, and peptide desalting steps.

Mass spectrometry-based shotgun proteomics experiments require multiple sample preparation steps, including enzymatic protein digestion and clean-up, ...

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Research

JoVE Journal

Biochemistry

3.6K Views.  University of Colorado Anschutz Medical Campus. Dit protocol maakt gebruik van automatisering om eiwitbiochemische preparaten uit te voeren voorafgaand aan massaspectrometrie-experimenten, waardoor een hogere doorvoer en lagere variabiliteit voor proteomische studies mogelijk is. Dit protocol maakt gebruik van een goedkoop, programmeerbaar vloeistofbehandelingssysteem dat betaalbaar is voor meer laboratoria. Wij bieden open source Python scripts die kunnen worden aangepast voor verdere ontwikkeling.De procedure wordt gedemonstreerd ...

Video: Shotgun Proteomics Sample Processing Automated by an Open-Source Lab Robot

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Many exceptional advances have been made in mass spectrometry (MS)-based proteomics, with particular technical progress in liquid chromatography (LC) coupled to tandem mass spectrometry (LC-MS/MS) and isobaric labeling multiplexing capacity. Here, we introduce a deep-proteomics profiling protocol that combines 10-plex tandem mass tag (TMT) labeling with an extensive LC/LC-MS/MS platform, and post-MS computational interference correction to accurately quantitate whole proteomes. This protocol includes the following main steps: protein extraction and digestion, TMT labeling, 2-dimensional (2D) LC, high-resolution mass spectrometry, and computational data processing. Quality control steps are included for troubleshooting and evaluating experimental variation. More than 10,000 proteins in mammalian samples can be confidently quantitated with this protocol. This protocol can also be applied to the quantitation of post translational modifications with minor changes. This multiplexed, robust method provides a powerful tool for proteomic analysis in a variety of complex samples, including cell culture, animal tissues, and human clinical specimens.

We present a protocol to accurately quantitate proteins with isobaric labelling, extensive fractionation, bioinformatics tools, and quality control steps in combination with liquid chromatography interfaced to a high-resolution mass spectrometer.

Many exceptional advances have been made in mass spectrometry (MS)-based proteomics, with particular technical progress in liquid chromatography (LC) ...

High-throughput, Automated Extraction of DNA and RNA from Clinical Samples using TruTip Technology on Common Liquid Handling Robots

TruTip is a simple nucleic acid extraction technology whereby a porous, monolithic binding matrix is inserted into a pipette tip. The geometry of the monolith can be adapted for specific pipette tips ranging in volume from 1.0 to 5.0 ml. The large porosity of the monolith enables viscous or complex samples to readily pass through it with minimal fluidic backpressure. Bi-directional flow maximizes residence time between the monolith and sample, and enables large sample volumes to be processed within a single TruTip. The fundamental steps, irrespective of sample volume or TruTip geometry, include cell lysis, nucleic acid binding to the inner pores of the TruTip monolith, washing away unbound sample components and lysis buffers, and eluting purified and concentrated nucleic acids into an appropriate buffer. The attributes and adaptability of TruTip are demonstrated in three automated clinical sample processing protocols using an Eppendorf epMotion 5070, Hamilton STAR and STARplus liquid handling robots, including RNA isolation from nasopharyngeal aspirate, genomic DNA isolation from whole blood, and fetal DNA extraction and enrichment from large volumes of maternal plasma (respectively).

TruTip is a simple nucleic acid extraction technology whereby a porous, monolithic binding matrix is inserted into a pipette tip. Consequently, the sample preparation format is compatible with most liquid handling instruments, and can be used for many medium to high-throughput clinical applications and sample types.

TruTip is a simple nucleic acid extraction  technology whereby a porous, monolithic binding matrix is inserted into a  pipette tip. The geometry of the ...

Bioengineering

High Sensitivity Measurement of Transcription Factor-DNA Binding Affinities by Competitive Titration Using Fluorescence Microscopy

Accurate quantification of transcription factor (TF)-DNA interactions is essential for understanding the regulation of gene expression. Since existing approaches suffer from significant limitations, we have developed a new method for determining TF-DNA binding affinities with high sensitivity on a large scale. The assay relies on the established fluorescence anisotropy (FA) principle but introduces important technical improvements. First, we measure a full FA competitive titration curve in a single well by incorporating TF and a fluorescently labeled reference DNA in a porous agarose gel matrix. Unlabeled DNA oligomer is loaded on the top as a competitor and, through diffusion, forms a spatio-temporal gradient. The resulting FA gradient is then read out using a customized epifluorescence microscope setup. This improved setup greatly increases the sensitivity of FA signal detection, allowing both weak and strong binding to be reliably quantified, even for molecules of similar molecular weights. In this fashion, we can measure one titration curve per well of a multi-well plate, and through a fitting procedure, we can extract both the absolute dissociation constant (KD) and active protein concentration. By testing all single-point mutation variants of a given consensus binding sequence, we can survey the entire binding specificity landscape of a TF, typically on a single plate. The resulting position weight matrices (PWMs) outperform those derived from other methods in predicting in vivo TF occupancy. Here, we present a detailed guide for implementing HiP-FA on a conventional automated fluorescent microscope and the data analysis pipeline.

Here we present a novel method for determining binding affinities at equilibrium and in solution with high sensitivity on a large scale. This improves the quantitative analysis of transcription factor-DNA binding. The method is based on automated fluorescence anisotropy measurements in a controlled delivery system.

Accurate quantification of transcription factor (TF)-DNA interactions is essential for understanding the regulation of gene expression. Since existing ...

A Plasma Sample Preparation for Mass Spectrometry using an Automated Workstation

Sample preparation for mass spectrometry analysis in proteomics requires enzymatic cleavage of proteins into a peptide mixture. This process involves numerous incubation and liquid transfer steps in order to achieve denaturation, reduction, alkylation, and cleavage. Adapting this workflow onto an automated workstation can increase efficiency and reduce coefficients of variance, thereby providing more reliable data for statistical comparisons between sample types. We previously described an automated proteomic sample preparation workflow1. Here, we report the development of a more efficient and better controlled workflow with the following advantages: 1) The number of liquid transfer steps is reduced from nine to six by combining reagents; 2) Pipetting time is reduced by selective tip pipetting using a 96-position pipetting head with multiple channels; 3) Potential throughput is increased by the availability of up to 45 deck positions; 4) Complete enclosure of the system provides improved temperature and environmental control and reduces the potential for contamination of samples or reagents; and 5) The addition of stable isotope labeled peptides, as well as &#946;-galactosidase protein, to each sample makes monitoring and quality control possible throughout the entire process. These hardware and process improvements provide good reproducibility and improve intra-assay and inter-assay precision (CV of less than 20%) for LC-MS based protein and peptide quantification. The entire workflow for digesting 96 samples in a 96-well plate can be completed in approximately 5 hours.

Here, we present an automated plasma protein digestion method for mass spectrometry-based quantitative proteomic analysis. In this protocol, the liquid transferring and incubation steps for protein denaturation, reduction, alkylation, and trypsin digestion reactions are streamlined and automated. It takes approximately five hours to prepare a 96-well plate with desired precision.

Sample preparation for mass spectrometry analysis in proteomics requires enzymatic cleavage of proteins into a peptide mixture. This process involves ...

Platform Incubator with Movable XY Stage: A New Platform for Implementing In-Cell Fast Photochemical Oxidation of Proteins

Fast Photochemical Oxidation of proteins (FPOP) coupled with mass spectrometry (MS) has become an invaluable tool in structural proteomics to interrogate protein interactions, structure, and protein conformational dynamics as a function of solvent accessibility. In recent years, the scope of FPOP, a hydroxyl radical protein foot printing (HRPF) technique, has been expanded to protein labeling in live cell cultures, providing the means to study protein interactions in the convoluted cellular environment. In-cell protein modifications can provide insight into ligand induced structural changes or conformational changes accompanying protein complex formation, all within the cellular context. Protein footprinting has been accomplished employing a customary flow-based system and a 248 nm KrF excimer laser to yield hydroxyl radicals via photolysis of hydrogen peroxide, requiring 20 minutes of analysis for one cell sample.To facilitate time-resolved FPOP experiments, the use of a new 6-well plate-based IC-FPOP platform was pioneered. In the current system, a single laser pulse irradiates one entire well, which truncates the FPOP experimental time frame resulting in 20 seconds of analysis time, a 60-fold decrease. This greatly reduced analysis time makes it possible to research cellular mechanisms such as biochemical signaling cascades, protein folding, and differential experiments (i.e., drug-free vs. drug bound) in a time-dependent manner. This new instrumentation, entitled Platform Incubator with Movable XY Stage (PIXY), allows the user to perform cell culture and IC-FPOP directly on the optical bench using a platform incubator with temperature, CO2 and humidity control. The platform also includes a positioning stage, peristaltic pumps, and mirror optics for laser beam guidance. IC-FPOP conditions such as optics configuration, flow rates, transient transfections, and H2O2 concentration in PIXY have been optimized and peer-reviewed. Automation of all components of the system will reduce human manipulation and increase throughput.

A new static platform is used to characterize protein structure and interaction sites in the native cell environment utilizing a protein footprinting technique called in-cell fast photochemical oxidation of proteins (IC-FPOP).

Fast Photochemical Oxidation of proteins (FPOP) coupled with mass spectrometry (MS) has become an invaluable tool in structural proteomics to interrogate ...

Digital Microfluidics for Automated Proteomic Processing

Clinical proteomics has emerged as an important new discipline, promising the discovery of biomarkers that will be useful for early diagnosis and prognosis of disease. While clinical proteomic methods vary widely, a common characteristic is the need for (i) extraction of proteins from extremely heterogeneous fluids (i.e. serum, whole blood, etc.) and (ii) extensive biochemical processing prior to analysis. Here, we report a new digital microfluidics (DMF) based method integrating several processing steps used in clinical proteomics. This includes protein extraction, resolubilization, reduction, alkylation and enzymatic digestion. Digital microfluidics is a microscale fluid-handling technique in which nanoliter-microliter sized droplets are manipulated on an open surface. Droplets are positioned on top of an array of electrodes that are coated by a dielectric layer - when an electrical potential is applied to the droplet, charges accumulate on either side of the dielectric. The charges serve as electrostatic handles that can be used to control droplet position, and by biasing a sequence of electrodes in series, droplets can be made to dispense, move, merge, mix, and split on the surface. Therefore, DMF is a natural fit for carrying rapid, sequential, multistep, miniaturized automated biochemical assays. This represents a significant advance over conventional methods (relying on manual pipetting or robots), and has the potential to be a useful new tool in clinical proteomics.
Mais J. Jebrail, Vivienne N. Luk, and Steve C. C. Shih contributed equally to this work.
Sergio L. S. Freire's current address is at the University of the Sciences in Philadelphia located at 600 South 43rd Street, Philadelphia, PA 19104.

Digital Microfluidics is a technique characterized by the manipulation of discrete droplets (~nL - mL) on an array of electrodes by the application of electrical fields. It is well-suited for carrying out rapid, sequential, miniaturized automated biochemical assays. Here, we report a platform capable of automating several proteomic processing steps.

Clinical proteomics has emerged as an important new discipline, promising the discovery of biomarkers that will be useful for early diagnosis and ...

Biology

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.

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

Chemistry

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Recent advances in modular DNA assembly techniques have enabled synthetic biologists to test significantly more of the available &#34;design space&#34; represented by &#34;devices&#34; created as combinations of individual genetic components. However, manual assembly of such large numbers of devices is time-intensive, error-prone, and costly. The increasing sophistication and scale of synthetic biology research necessitates an efficient, reproducible way to accommodate large-scale, complex, and high throughput device construction.
Here, a DNA assembly protocol using the Type-IIS restriction endonuclease based Modular Cloning (MoClo) technique is automated on two liquid-handling robotic platforms. Automated liquid-handling robots require careful, often times tedious optimization of pipetting parameters for liquids of different viscosities (e.g. enzymes, DNA, water, buffers), as well as explicit programming to ensure correct aspiration and dispensing of DNA parts and reagents. This makes manual script writing for complex assemblies just as problematic as manual DNA assembly, and necessitates a software tool that can automate script generation. To this end, we have developed a web-based software tool, http://mocloassembly.com, for generating combinatorial DNA device libraries from basic DNA parts uploaded as Genbank files. We provide access to the tool, and an export file from our liquid handler software which includes optimized liquid classes, labware parameters, and deck layout. All DNA parts used are available through Addgene, and their digital maps can be accessed via the Boston University BDC ICE Registry. Together, these elements provide a foundation for other organizations to automate modular cloning experiments and similar protocols.
The automated DNA assembly workflow presented here enables the repeatable, automated, high-throughput production of DNA devices, and reduces the risk of human error arising from repetitive manual pipetting. Sequencing data show the automated DNA assembly reactions generated from this workflow are ~95% correct and require as little as 4% as much hands-on time, compared to manual reaction preparation.

Here, an automated workflow to perform modular DNA &#34;device&#34; assembly using a modular cloning DNA assembly method on liquid-handling robots is presented. The protocol uses an intuitive software tool for generating liquid handler picklists for combinatorial DNA device library generation, which we demonstrate using two liquid handling platforms.

Recent advances in modular DNA assembly techniques have enabled synthetic biologists to test significantly more of the available &#34;design space&#34; ...

Shotgun Lipidomics of Rodent Tissues

Lipids play a vital role as essential components of all prokaryotic and eukaryotic cells. Constant technological improvements in mass spectrometry have made lipidomics a powerful analytical tool for monitoring tissue lipidome compositions in homeostatic as well as disease states. This paper presents a step-by-step protocol for a shotgun lipid analysis method that supports the simultaneous detection and quantification of a few hundred molecular lipid species in different tissue and biofluid samples at high throughput. This method leverages automated nano-flow direct injection of a total lipid extract spiked with labeled internal standards without chromatographic separation into a high-resolution mass spectrometry instrument. Starting from sub-microgram amounts of rodent tissue, the MS analysis takes 10 min per sample and covers up to 400 lipids from 14 lipid classes in mouse lung tissue. The method presented here is well suited for studying disease mechanisms and identifying and quantifying biomarkers that indicate early toxicity or beneficial effects within rodent tissues.

Shotgun mass spectrometry-based lipidomics delivers a sensitive quantitative snapshot of a broad spectrum of lipid classes simultaneously in a single measurement from various rodent tissues.

Lipids play a vital role as essential components of all prokaryotic and eukaryotic cells. Constant technological improvements in mass spectrometry have ...

Comprehensive Workflow of Mass Spectrometry-based Shotgun Proteomics of Tissue Samples

Recent advances in mass spectrometry have resulted in deep proteomic&#160;analysis along with the generation of&#160;robust and&#160;reproducible datasets. However, despite the considerable technical advancements, sample preparation from biospecimens such as patient blood, CSF, and tissue still poses considerable challenges. For identifying biomarkers, tissue proteomics often provides an attractive sample source to translate the research findings from the bench to the clinic. It can reveal potential candidate biomarkers for early diagnosis of cancer and neurodegenerative diseases such as Alzheimer&#39;s disease, Parkinson&#39;s disease, etc. Tissue proteomics also yields a wealth of systemic information based on the abundance of proteins and helps to address interesting biological questions.
Quantitative proteomics analysis can be grouped into two broad categories: a label-based and a label-free approach. In the label-based approach, proteins or peptides are labeled using stable isotopes such as SILAC (stable isotope labeling with amino acids in cell culture) or by chemical tags such as ICAT (isotope-coded affinity tags), TMT (tandem mass tag) or iTRAQ (isobaric tag for relative and absolute quantitation). Label-based approaches have the advantage of more accurate quantitation of proteins and using isobaric labels, multiple samples can be analyzed in a single experiment. The label-free approach provides a cost-effective alternative to label-based approaches. Hundreds of patient samples belonging to a particular cohort can be analyzed and compared with other cohorts based on clinical features. Here, we have described an optimized quantitative proteomics workflow for tissue samples using label-free and label-based proteome profiling methods, which is crucial for applications in life sciences, especially biomarker discovery-based projects.

The described protocol provides an optimized quantitative proteomics analysis of tissue samples using two approaches: label-based and label free quantitation. Label-based approaches have the advantage of more accurate quantitation of proteins, while a label-free approach is more cost-effective and used to analyze hundreds of samples of a cohort.

Shotgun Proteomics Sample Processing Automated by an Open-Source Lab Robot

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