Mikroplack-Sonikatioun an Shotgun-Proteomik – Applikatiounsnotiz

Shotgun proteomics depends on efficient, reproducible sample preparation to convert complex biological material into LC-MS/MS-ready peptides. The UIP400MTP microplate sonicator supports this process by enabling standardized, parallel sonication of small-volume samples, helping laboratories improve disruption, extraction, and resolubilization in microplate-based workflows. This application note describes how the UIP400MTP can be integrated into proteomic sample preparation, using a published extracellular-vesicle workflow from PLA2G12A/Th17 studies as a lab-tested example.

Microplate Sonication for More Reproducible Shotgun Proteomics

For proteomics researchers, reproducible sample preparation is critical for high-quality LC-MS/MS data. The UIP400MTP microplate sonicator supports standardized, parallel sonication in plate-based and small-volume/high-throughput workflows.

It is especially useful for laboratories working with:

• Large sample sets that require consistent processing across many wells
• Limited-input material, where sample loss and variability must be minimized
• Lipid-rich samples, such as extracellular vesicles
• Complex biological preparations that require efficient disruption, extraction, or resolubilization
• Comparative shotgun proteomics, where reproducibility across conditions and replicates is essential

By integrating microplate sonication before digestion, researchers can improve sample readiness for:

• Protein extraction and resolubilization
• Trypsin/Lys-C Verdauung
• Nano-LC/MS/MS Akkusitioun
• Quantitativ nofolgend Proteomik-Analyse

 

Skaléiert Äre Proteomik-Probenvirbereedung mat Vertrauen!
Léiert wéi Mikroplattsonikatioun hëlleft manuell Variabilitéiten ze reduzéieren, d'Probenstéierung ze verbesseren an komplex biologesch Proben fir zouverlässeg LC-MS/MS Analyse virzebereeden.

Informatiounen Ufro


Email Adress (obligatoresch)


Produit oder Beräich vun Interessi



Ech averstanen der Privatsphär Politik









Ufro Informatiounen

Mikroplattsonikatioun kann profitéieren:

• Proteomik-Core-Facilitéiten
• EV Fuerschungslaboren
• Immunologie- an Zellbiologie-Laboren
• Translational Fuerschungsgruppen
• Liewenswëssenschaftsteams déi vum eenzelen Probe-Virbereedung bis zu héich-Duerchsatz Workflows skaléieren

High-Throughput Sample Preparation for Extracellular Vesicle Proteome Analysis

What is Shotgun Proteomics?

Shotgun proteomics has become a central analytical strategy for characterizing complex biological samples, from whole-cell lysates and tissue extracts to purified organelles, extracellular vesicles, and low-input clinical specimens. Its core strength lies in the coupling of protein digestion, high-resolution liquid chromatography-tandem mass spectrometry, and computational peptide-to-protein inference. However, the quality of the final proteome dataset is determined long before the sample reaches the mass spectrometer. Efficient sample disruption, protein solubilization, removal of interfering substances, reproducible enzymatic digestion, and robust peptide recovery are all decisive for depth of coverage and quantitative reliability.
Fir Proteomics Fuerscher an Liewenswëssenschaftslaboren, déi mat limitéierten oder wäertvollen Proben schaffen, ass d'Probenvirbereedung dacks de Flaschenhals.

D'Erausfuerderung vun extrazelluläre Vesikelen an der Proteomics

Extracellular vesicles (EVs), for example, represent a particularly demanding sample class. They are membrane-bound, lipid-rich, nanoscale particles with relatively low protein yield and a high potential for carry-over of lipids, salts, detergents, serum proteins, and other matrix components. These features can interfere with digestion efficiency, chromatographic performance, electrospray stability, and peptide identification. A preparation workflow for EV proteomics must therefore be strong enough to disrupt vesicle structures and solubilize protein cargo, while remaining compatible with downstream enzymatic digestion and LC-MS/MS analysis.
In this context, microplate-compatible ultrasonication offers a practical approach for reproducible, parallelized sample processing. The Hielscher microplate sonicator models UIP400MTP (400 W) and UIP550MTP (550 W) are designed for sonication of samples in multiwell plates and small-volume vessels, supporting higher-throughput workflows than conventional single-probe sonicators. For proteomics laboratories, this format is attractive because it can reduce hands-on variability, improve parallel treatment of multiple samples, and integrate more naturally into plate-based sample preparation pipelines.

Exemplary Workflow

A recent extracellular vesicle proteomics workflow in PLA2G12A-driven Th17-cell biology provides a useful, lab-tested example of how the microplate sonicator UIP400MTP can be incorporated into shotgun proteomics sample preparation. In that study series, EV samples were processed for proteome analysis using methanol treatment, UIP400MTP sonication, centrifugation, drying, trypsin/Lys-C digestion, and nano-flow LC-high-resolution tandem MS. The same biological work was first reported as a bioRxiv preprint and subsequently published in Cell Reports, where the proteomics analysis helped characterize how PLA2G12A alters EV cargo proteins in the context of pathogenic T-cell responses.

Multi-Well Plate Sonicator UIP400MTP

Why microplate sonication?
Den UIP400MTP erméiglecht standardiséiert, parallel Sonikatioun vu klenge Probes. Dëst ass nëtzlech wann Reproduzéierbarkeet, niddreg Probiemenge a Multi-Proben duerchlaf wichteg sinn.

Quality Control Checklist

• Confirm equal EV protein-equivalent input across all samples.
• Use randomized or balanced sample processing layouts.
• Keep methanol volume, sonication time, drying time, and digestion volume consistent.
• Monitor peptide yield and total protein identifications.
• Check missed-cleavage rate and peptide length distribution.
• Inspect chromatographic peak shape and retention-time reproducibility.
• Include blanks to monitor carryover.
• Use pooled QC samples for larger studies.
• Evaluate replicate coefficient of variation.
• Use PCA or related methods to identify batch effects or outlier samples.

Protocolling Recommendations

Beim Verëffentlechen oder Dokumentéiere vun dësem Workflow sollt Dir d'EV-Input-Quantitéit, d'Plackformat, d'Methanolvolumen, d'Amplitude an d'Sonikatiounszäit vum UIP400MTP, d'Zentrifugatiounsbedéngungen, d'Trocknungsmethod, d'Digestipuffer, d'Enzymkonzentratioun, d'Digestzäit, d'Sauerbedéngungen, d'LC-MS/MS-Plattform, den Erwerbsmodus, d'Softwareversioun, d'Datebank, den FDR-Schwelle, d'Normméierungsmethod, an den statistesche Workflow mellen.
All Hielscher Mikroplacksonikatoren protokolléieren automatesch wichteg Prozessparameter wéi Amplitude, Sonikatiounsdauer an Temperatur mat Datum- an Zäitstempel als CVS-Datei op der integréierter SD-Kaart. D'Donnéeënprotokolléierung fir Reproduzierbarkeet an Qualitéitskontroll war nach ni sou einfach!

The Study in Detail: EV Shotgun Proteomics in PLA2G12A Study

The PLA2G12A study provides a concrete example of UIP400MTP use in a shotgun proteomics workflow. The biological question was how the secreted phospholipase PLA2G12A modifies Th17-cell-derived extracellular vesicles and thereby influences pathogenic T-cell differentiation. The authors showed that PLA2G12A acts on EV membranes to produce lysophospholipids, including 1-oleoyl-lysophosphatidylethanolamine, and that downstream lysophosphatidic acid signaling via LPA2 contributes to Th17 differentiation. Beyond lipid signaling, the studies also examined EV cargo, including RNA and protein content, making shotgun proteomics an important component of the characterization strategy.
In the EV preparation workflow, Th17 cells were cultured in medium containing exosome-depleted fetal bovine serum. Culture supernatants were first centrifuged to remove cells, filtered through a 0.22 µm filter, concentrated by ultrafiltration/ultracentrifugation, washed, resuspended in PBS, and quantified by BCA protein assay. This upstream EV preparation ensured that a defined protein-equivalent amount of EV material could be carried into the proteomics workflow.
For shotgun proteomic analysis, the authors used EV samples corresponding to 5 µg protein equivalents. These samples were dried in PCR tubes, and 25 µL methanol was added. The samples were then sonicated for 3 minutes using the UIP400MTP microplate sonicator. Following sonication, the samples were centrifuged at 4°C for 20 minutes at 19,000 × g. After removal of 20 µL supernatant, the samples were centrifuged to dryness. Proteins were then dissolved by sonication in 4 µL trypsin/Lys-C solution at 100 ng/µL in 50 mM ammonium bicarbonate. Digestion was performed for 2 hours at 37°C with shaking at 300 rpm. The digest was acidified with 1 µL of 1.25% trifluoroacetic acid and submitted to nano-flow LC-high-resolution tandem mass spectrometry.
This workflow highlights several useful principles for low-input EV proteomics. First, the input was normalized by protein equivalent, which is important when comparing EVs from different genotypes or treatments. Second, methanol was used before sonication, supporting disruption and extraction while avoiding detergent systems that may complicate LC-MS/MS. Third, the sonication step was short and standardized, which is compatible with parallel sample processing. Fourth, trypsin/Lys-C digestion was performed in a very small volume, reducing dilution and supporting low-input peptide recovery. Finally, direct transition from digestion to acidification and LC-MS/MS minimized unnecessary handling steps.
The downstream LC-MS/MS method used nano-flow reversed-phase separation coupled to a Q-Exactive HF Orbitrap mass spectrometer. Samples were trapped on a C18 pre-column, then separated on a 50 µm inner-diameter analytical column at 200 nL/min and 40°C. The gradient ran from low organic solvent to 35% solvent B over 60 minutes, followed by high-organic washing and re-equilibration. MS acquisition was performed in positive-ion mode using data-independent acquisition with higher-energy collisional dissociation. DIA raw files were analyzed using DIA-NN 1.8 with an in silico predicted spectral library.