Microfluidic Printing-Based Method for the Multifactorial Study of Cell-Free Protein Networks
Year: 2022
Type: article
Abstract: Protein networks can be assembled in vitro for basic biochemistry research, drug screening, and the creation of artificial cells. Two standard methodologies are used: manual pipetting and pipetting robots. Manual pipetting has limited throughput in the number of input reagents and the combination of reagents in a single sample. While pipetting robots are evident in improving pipetting efficiency and saving hands-on time, their liquid handling volume usually ranges from a few to hundreds of microliters. Microfluidic methods have been developed to minimize the reagent consumption and speed up screening but are challenging in multifactorial protein studies due to their reliance on complex structures and labeling dyes. Here, we engineered a new impact-printing-based methodology to generate printed microdroplet arrays containing water-in-oil droplets. The printed droplet volume was linearly proportional ( R 2 = 0.9999) to the single droplet number, and each single droplet volume was around 59.2 nL (coefficient of variation = 93.8%). Our new methodology enables the study of protein networks in both membrane-unbound and -bound states, without and with anchor lipids DGS–NTA(Ni), respectively. The methodology is demonstrated using a subnetwork of mitogen-activated protein kinase (MAPK). It takes less than 10 min to prepare 100 different droplet-based reactions, using <1 μL reaction volume at each reaction site. We validate the kinase (ATPase) activity of MEK1 (R4F)* and ERK2 WT individually and together under different concentrations, without and with the selective membrane attachment. Our new methodology provides a reagent-saving, efficient, and flexible way for protein network research and related applications.
Source: Analytical Chemistry
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
Funders: National Natural Science Foundation of China, Chinese Academy of Sciences, Government of Guangdong Province, Shenzhen Engineering Laboratory of Single-molecule Detection and Instrument Development, National Institutes of Health, Joint Research Fund for Overseas Chinese Scholars and Scholars in Hong Kong and Macao, National Institute of General Medical Sciences, National Institute of Biomedical Imaging and Bioengineering
OpenAlex ID: W4288439568
