Acetylation of lysines on affinity-purification matrices to reduce co-digestion of bead-bound ligands v1

2022 ◽  
Author(s):  
David M. Hollenstein ◽  
Margarita Maurer ◽  
Thomas Gossenreiter ◽  
Natascha Hartl ◽  
Dorothea Anrather ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
High Efficiency ◽  
Affinity Purification ◽  
Low Cost ◽  
Signal Strength ◽  
Liquid Chromatography Mass Spectrometry ◽  
Strong Reduction ◽  
Affinity Enrichment ◽  
Peptide Signals ◽  
Interaction Proteomics

In mass-spectrometry-based interaction proteomics on-bead digestion protocols are commonly applied after affinity-enrichment due to their simplicity and high efficiency. However, on-bead digestion often leads to strong background signals due to co-digestion of the bead-bound ligands such as streptavidin or antibodies. We present an effective, rapid and low-cost method to specifically reduce the peptide signals from co-digested matrix ligands. A short pre-incubation of matrix beads with Sulfo-NHS-Acetate (S-NHS-Ac) leads to acetylation of free amines on lysine side-chains of the bead-bound ligands making them resistant to Lys-C-mediated proteolysis. After binding of bait proteins to the acetylated beads we employ a two-step digestion protocol with the sequential use of Lys-C protease for on-bead digestion followed by in-solution digestion with trypsin. The strong reduction of interfering ligand peptides improves signal strength and data quality for the peptides of interest in liquid chromatography mass spectrometry (LC-MS).

scholarly journals Driving integrative structural modeling with serial capture affinity purification

2020 ◽  
Vol 117 (50) ◽  
pp. 31861-31870
Author(s):  
Xingyu Liu ◽  
Ying Zhang ◽  
Zhihui Wen ◽  
Yan Hao ◽  
Charles A. S. Banks ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Structural Model ◽  
Protein Complexes ◽  
Affinity Purification ◽  
Quantitative Imaging ◽  
Resonance Energy ◽  
Correlation Spectroscopy ◽  
Cross Linking ◽  
Affinity Enrichment

Streamlined characterization of protein complexes remains a challenge for the study of protein interaction networks. Here we describe serial capture affinity purification (SCAP), in which two separate proteins are tagged with either the HaloTag or the SNAP-tag, permitting a multistep affinity enrichment of specific protein complexes. The multifunctional capabilities of this protein-tagging system also permit in vivo validation of interactions using acceptor photobleaching Förster resonance energy transfer and fluorescence cross-correlation spectroscopy quantitative imaging. By coupling SCAP to cross-linking mass spectrometry, an integrative structural model of the complex of interest can be generated. We demonstrate this approach using the Spindlin1 and SPINDOC protein complex, culminating in a structural model with two SPINDOC molecules docked on one SPIN1 molecule. In this model, SPINDOC interacts with the SPIN1 interface previously shown to bind a lysine and arginine methylated sequence of histone H3. Our approach combines serial affinity purification, live cell imaging, and cross-linking mass spectrometry to build integrative structural models of protein complexes.

scholarly journals Getting more out of co-immunoprecipitation mass spectrometry experiments by reducing interference using FAIMS.

2021 ◽  
Author(s):  
Ching-Seng Ang ◽  
Joanna Sacharz ◽  
Michael G Leeming ◽  
Shuai Nie ◽  
Swati Varshney ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Ion Mobility ◽  
Protein Complexes ◽  
Affinity Purification ◽  
Mass Spectrometry Analysis ◽  
Modern Biology ◽  
Spectrometry Analysis ◽  
Affinity Enrichment ◽  
Unbiased Manner ◽  
Gas Phase Ion

Co-immunoprecipitation of proteins coupled to mass spectrometry has transformed modern biology understanding of protein interaction networks. These approaches exploit the selective isolation of tagged proteins by affinity enrichment / purification to identify protein binding partners at scale and in an unbiased manner. In instances where a suitable antibody is not be available it is common to graft synthetic tags such as FLAG or His Tags onto target protein sequences allowing the use of commercially available and validated antibodies for affinity purification. To allow the selective elution of protein complexes competitive displacement using a large molar excess of the tag peptide is widely used. Yet, this creates downstream challenges for the mass spectrometry analysis due to the presence of large quantities of a contaminating peptide. Here, we demonstrate that Field Asymmetric Ion Mobility Spectrometry (FAIMS), a gas phase ion separation device can be applied to FLAG-Tag and His-Tag pull down assay to increase the depth of protein coverage in these experiments. By excluding tag peptides based on their ion mobility profiles we demonstrate that single compensation voltage, or stepped compensation voltages strategies can significantly increase the coverage of total proteins by up to 2.5-fold and unique proteins by up to 15-fold versus experiments that do not use FAIMS. Combined these results highlight FAIMS is able to improve proteome depth by excluding interfering peptides without the need for additional sample handling or altering sample preparation protocols.

Secondary Ion Mass Spectrometry Studies of Polycrystalline Thin-Film Cdte/Cds Solar Cells

1990 ◽  
Vol 48 (2) ◽  
pp. 304-305
Author(s):  
S.E. Asher
Keyword(s):  
Thin Film ◽  
Mass Spectrometry ◽  
High Temperature ◽  
High Efficiency ◽  
Secondary Ion Mass Spectrometry ◽  
Spray Pyrolysis Technique ◽  
Low Cost ◽  
Large Area ◽  
Ion Mass Spectrometry ◽  
Secondary Ion

Polycrystalline thin films of CdTe deposited on CdS are one of the most promising materials systems currently being investigated for the fabrication of low cost, large area, high efficiency photovoltaic devices. However, many of the deposition processes being used to fabricate these thin film materials have not yet been well characterized. It has been found that a post-fabrication heat-treatment is necessary to improve the quantum efficiency of these devices. Secondary ion mass spectrometry (SIMS) was used to study the interdiffusion of S and Te in CdTe/CdS structures grown by two different methods. The depth profiles revealed significant differences in the sputtering behavior depending on the film morphology.Two sets of CdTe/CdS samples were studied. The first set of films was deposited at high temperature using a spray pyrolysis technique with no post deposition anneal. The second set of films was electroplated, followed by treatment with CdCl2 and a high temperature anneal.

scholarly journals HepParser: An Intelligent Software Program for Deciphering Low-Molecular-Weight Heparin Based on Mass Spectrometry

2021 ◽  
Vol 9 ◽  
Author(s):  
Hui Wang ◽  
Yu Wang ◽  
Meijie Hou ◽  
Chunming Zhang ◽  
Yaojun Wang ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Molecular Weight ◽  
High Efficiency ◽  
High Accuracy ◽  
Low Molecular Weight ◽  
Liquid Chromatography Mass Spectrometry ◽  
High Similarity ◽  
Low Molecular Weight Heparins ◽  
Intelligent Software ◽  
Main Components

Low-molecular-weight heparins (LMWHs) are considered to be the most successful carbohydrate-based drugs because of their wide use as anticoagulants in clinics. The efficacy of anticoagulants made by LMWHs mainly depends on the components and structures of LMWHs. Therefore, deciphering the components and identifying the structures of LMWHs are critical to developing high-efficiency anticoagulants. However, most LMWHs are mixtures of linear polysaccharides which are comprised of several disaccharide repeating units with high similarity, making it extremely challenging to separate and decipher each component in LMWHs. Here, we present a new algorithm named hepParser to decipher the main components of LMWHs automatically and precisely based on the liquid chromatography/mass spectrometry (LC/MS) data. When tested on the general LMWH using hepParser, profiling of the oligosaccharides with different degrees of polymerization (dp’s) was completed with high accuracy within 1 minute. When compared with the results of GlycReSoft on heparan sulfate samples, hepParser achieved more comprehensive and reasonable results automatically.

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