Fully Automated Sample Processing and Analysis Workflow for Low-Input Proteome Profiling.
Anal Chem
; 93(3): 1658-1666, 2021 01 26.
Article
en En
| MEDLINE
| ID: mdl-33352054
ABSTRACT
Recent advances in sample preparation and analysis have enabled direct profiling of protein expression in single mammalian cells and other trace samples. Several techniques to prepare and analyze low-input samples employ custom fluidics for nanoliter sample processing and manual sample injection onto a specialized separation column. While being effective, these highly specialized systems require significant expertise to fabricate and operate, which has greatly limited implementation in most proteomic laboratories. Here, we report a fully automated platform termed autoPOTS (automated preparation in one pot for trace samples) that uses only commercially available instrumentation for sample processing and analysis. An unmodified, low-cost commercial robotic pipetting platform was utilized for one-pot sample preparation. We used low-volume 384-well plates and periodically added water or buffer to the microwells to compensate for limited evaporation during sample incubation. Prepared samples were analyzed directly from the well plate with a commercial autosampler that was modified with a 10-port valve for compatibility with 30 µm i.d. nanoLC columns. We used autoPOTS to analyze 1-500 HeLa cells and observed only a moderate reduction in peptide coverage for 150 cells and a 24% reduction in coverage for single cells compared to our previously developed nanoPOTS platform. To evaluate clinical feasibility, we identified an average of 1095 protein groups from â¼130 sorted B or T lymphocytes. We anticipate that the straightforward implementation of autoPOTS will make it an attractive option for low-input and single-cell proteomics in many laboratories.
Texto completo:
1
Base de datos:
MEDLINE
Asunto principal:
Automatización
/
Proteoma
/
Proteómica
Tipo de estudio:
Guideline
Límite:
Humans
Idioma:
En
Revista:
Anal Chem
Año:
2021
Tipo del documento:
Article
País de afiliación:
Estados Unidos