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Biology subjects

Manda, S.

Publications and source records attributed to Manda, S..

2 recordsLinked to original sources

DNA nanopores as artificial membrane channels for origami based bioelectronics

Biological membrane channels mediate information exchange between cells and facilitate molecular recognition1-4. While tuning the shape and function of membrane channels for precision molecular sensing via de-novo routes is complex, an even more significant challenge is interfacing membrane channels with electronic devices for signal readout5-8. This challenge at the biotic-abiotic interface results in low efficiency of information transfer - one of the major barriers to the continued development of high-performance bioelectronic devices9. To this end, we integrate membrane spanning DNA nanopores with bioprotonic contacts to create programmable, modular, and efficient artificial ion-channel interfaces that resolve the iono-electronic disparity between the biotic environment and electronics. Through simulations and experiments, we show that cholesterol modified DNA nanopores spontaneously and with remarkable affinity span the lipid bilayer formed over the planar bio-protonic electrode surface and mediate proton transport across the bilayer. Using the ability to easily modify DNA nanostructures, we illustrate that this bioelectronic device can be programmed for electronic recognition of biomolecular signals such as presence of Streptavidin, without disrupting the native environment of the biomolecule. We anticipate this robust biotic-abiotic interface will allow facile electronic measurement of inter-cellular ionic communication and also open the door for active control of cell behavior through externally controlled selective gating of the channels.

bioengineering↗

Pan-cancer proteomic map of 949 human cell lines reveals principles of cancer vulnerabilities

The proteome provides unique insights into biology and disease beyond the genome and transcriptome. Lack of large proteomic datasets has restricted identification of new cancer biomarkers. Here, proteomes of 949 cancer cell lines across 28 tissue types were analyzed by mass spectrometry. Deploying a clinically-relevant workflow to quantify 8,498 proteins, these data capture evidence of cell type and post-transcriptional modifications. Integrating multi-omics, drug response and CRISPR-Cas9 gene essentiality screens with a deep learning-based pipeline revealed thousands of protein-specific biomarkers of cancer vulnerabilities. Proteomic data had greater power to predict drug response than the equivalent portion of the transcriptome. Further, random downsampling to only 1,500 proteins had limited impact on predictive power, consistent with protein networks being highly connected and co-regulated. This pan-cancer proteomic map (ProCan-DepMapSanger), available at https://cellmodelpassports.sanger.ac.uk, is a comprehensive resource revealing principles of protein regulation with important implications for future clinical studies.

systems biology↗