Klemm, L. | bioRxiv Science

bioRxiv2025

Membrane Proteins at Scale: Automated Copolymer Nanodisc Purification for Structure and Function

Membrane proteins remain among the most important yet least accessible classes of drug targets. Conventional detergents can remove native lipids, destabilizing proteins and limiting downstream biochemistry and structural biology. Amphiphilic copolymers offer a powerful alternative, directly extracting membrane proteins in their native lipid environment, but solubilization outcomes remain unpredictable, turning each new target into a slow empirical search. Here, we introduce an automated, plate-based copolymer screening platform that compresses this process from days to hours using millilitre-scale volumes. Lyophilized copolymer libraries combined with magnetic-bead affinity purification enable parallel testing of dozens of copolymers against multiple targets; across 14 diverse human membrane proteins, next-generation copolymers (AASTY, CyclAPol and Cubipol) systematically outperform classical scaffolds. In this work, we show that this automated copolymer screening robustly identifies the right target-copolymer combination, yielding native-like, active, ligand-binding competent protein suitable for structure determination, and establishes a scalable route to systematic exploration of the membrane proteome.

biochemistry↗

bioRxiv2023

Reduced dimension stimulus decoding and column-based modeling reveal architectural differences of primary somatosensory finger maps between younger and older adults

The primary somatosensory cortex (SI) contains fine-grained tactile representations of the body, arranged in an orderly fashion. Using ultra-high resolution fMRI data to describe such detailed individual topographic maps or to detect group differences is challenging, because group alignment often does not preserve the high spatial detail of the data. Here, we use shared response modeling (SRM), a technique that allows group analyses by mapping individual stimulus-driven responses to a lower dimensional shared feature space, to detect age-related differences in sensory representations between younger and older adults using 7T-fMRI data. Using this method, we show that finger representations are more precise in Brodmann-Area (BA) 3b and BA1 compared to BA2 and motor areas, and that this hierarchical processing is preserved across age groups. By combining SRM with column-based decoding (C-SRM), we further show that the number of columns that optimally describes finger maps in SI is higher in younger compared to older adults in BA1, indicating a greater columnar size in older adults SI. Taken together, we conclude that SRM is suitable for finding fine-grained group differences in SI fMRI data at ultra-high-resolution, and we provide first evidence that the columnar architecture of a functional area changes with increasing age.

neuroscience↗