Biology subjects

Early, B. P.

Publications and source records attributed to Early, B. P..

4 recordsLinked to original sources

bioRxiv2023

Top-down Proteomics of 10,000 Single Brain Cells

We introduce single-cell Proteoform imaging Mass Spectrometry (scPiMS), which realizes the benefit of direct analysis of intact proteins to process 10,836 single cells from the rat hippocampus. This new platform addresses the throughput bottleneck for single cell proteomics using mass spectrometry, boosting cell processing rates by >20-fold in the field. We identified 169 proteoforms <70 kDa from single brain cells and classified 2758 of them as neurons, astrocytes or microglia cell types.

biochemistry↗

bioRxiv2021

Direct Imaging and Identification of Proteoforms up to 70 kDa from Human Tissue

Imaging of proteoforms in human tissues is hindered by low molecular specificity and limited proteome coverage. Here, we introduce proteoform imaging mass spectrometry (PiMS), which increases the size limit for proteoform detection and identification by 4-fold compared to reported methods, and reveals tissue localization of proteoforms at <80 m spatial resolution. PiMS advances proteoform imaging by combining ambient nanospray desorption electrospray ionization (nano-DESI) with ion detection using individual ion mass spectrometry (I2MS). We demonstrate the first proteoform imaging of human kidney, identifying 169 of 400 proteoforms <70 kDa using top-down mass spectrometry and database lookup from the human proteoform atlas, including dozens of key enzymes in primary metabolism. PiMS images reveal distinct spatial localizations of proteoforms to both anatomical structures and cellular neighborhoods in the vasculature, medulla, and cortex regions of the human kidney. The benefits of PiMS are poised to increase proteome coverage for label-free protein imaging of tissues. TeaserNano-DESI combined with individual ion mass spectrometry generates images of proteoforms up to 70 kDa.

biochemistry↗

bioRxiv2019

Multiplexed Single Ion Mass Spectrometry Improves Measurement of Proteoforms and Their Complexes

A new Orbitrap-based single ion analysis procedure is shown to be possible by determining the direct charge on numerous measurements of individual protein ions to generate true mass spectra. The deployment of an Orbitrap system for charge detection enables the characterization of highly complicated mixtures of proteoforms and their complexes in both denatured and native modes of operation, revealing information not obtainable by traditional measurement of an ensemble of ions.

biochemistry↗

bioRxiv2018

Analysing protein post-translational modform regions by linear programming

Post-translational modifications (PTMs) at multiple sites can collectively influence protein function but the scope of such PTM coding has been challenging to determine. The number of potential combinatorial patterns of PTMs on a single molecule increases exponentially with the number of modification sites and a population of molecules exhibits a distribution of such \"modforms\". Estimating these \"modform distributions\" is central to understanding how PTMs influence protein function. Although mass-spectrometry (MS) has made modforms more accessible, we have previously shown that current MS technology cannot recover the modform distribution of heavily modified proteins. However, MS data yield linear equations for modform amounts, which constrain the distribution within a high-dimensional, polyhedral \"modform region\". Here, we show that linear programming (LP) can efficiently determine a range within which each modform value must lie, thereby approximating the modform region. We use this method on simulated data for mitogen-activated protein kinase 1 with the 7 phosphorylations reported on UniProt, giving a modform region in a 128 dimensional space. The exact dimension of the region is determined by the number of linearly independent equations but its size and shape depend on the data. The average modform range, which is a measure of size, reduces when data from bottom-up (BU) MS, in which proteins are first digested into peptides, is combined with data from top-down (TD) MS, in which whole proteins are analysed. Furthermore, when the modform distribution is structured, as might be expected of real distributions, the modform region for BU and TD combined has a more intricate polyhedral shape and is substantially more constrained than that of a random distribution. These results give the first insights into high-dimensional modform regions and confirm that fast LP methods can be used to analyse them. We discuss the problems of using modform regions with real data, when the actual modform distribution will not be known.

systems biology↗