A Versatile Workflow for the Identification of Protein–Protein Interactions Using GFP-Trap Beads and Mass Spectrometry-Based Label-Free Quantification

2020 ◽  
pp. 257-271 ◽  
Author(s):  
Guillaume Née ◽  
Priyadarshini Tilak ◽  
Iris Finkemeier
Keyword(s):  
Mass Spectrometry ◽  
Protein Interactions ◽  
Label Free ◽  
Protein Protein Interactions ◽  
Label Free Quantification ◽  
Free Quantification

Profiling Drug‐Protein Interactions by Micro Column Affinity Purification Combined with Label Free Quantification Proteomics †

2020 ◽  
Vol 38 (12) ◽  
pp. 1681-1685
Author(s):  
Li Gong ◽  
Yao Xu ◽  
Guizhen Liu ◽  
Mengmeng Zheng ◽  
Xuepei Zhang ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Affinity Purification ◽  
Label Free ◽  
Label Free Quantification ◽  
Free Quantification

Label-Free Quantification by Data Independent Acquisition Mass Spectrometry to Map Cardiovascular Proteomes

2016 ◽  
pp. 227-245
Author(s):  
Sarah J. Parker ◽  
Ronald J. Holewinski ◽  
Irina Tchernyshyov ◽  
Vidya Venkatraman ◽  
Laurie Parker ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Label Free ◽  
Label Free Quantification ◽  
Data Independent Acquisition ◽  
Free Quantification

scholarly journals Host defense responses of CO441 and CL30 maize lines to Fusarium graminearum analyzed by comparative label-free quantitative proteomics

2019 ◽  
Author(s):  
Lana M. Reid ◽  
Illimar Altosaar
Keyword(s):  
Mass Spectrometry ◽  
Fusarium Graminearum ◽  
Fungal Pathogen ◽  
Detailed Knowledge ◽  
Label Free ◽  
Maize Line ◽  
Defense Proteins ◽  
Label Free Quantification ◽  
Host Pathogen ◽  
Free Quantification

AbstractGibberella ear rot is a disease of maize associated with low yields and the production of harmful mycotoxins therein. The disease is caused by the infection of host Zea mays with fungal pathogen Fusarium graminearum. Resistant (CO441) and susceptible (CL30) inbred maize line kernels were inoculated with conidial suspensions of F. graminearum or water (controls). Ears of maize (cobs) from each line were harvested upon maturation and proteins were extracted from the embryo tissue of the kernels to study tissue-specific response of the host. Embryo proteins from both CO441 and CL30 lines were sequenced using mass spectrometry (LC-MS/MS) and quantified using Label Free Quantification (LFQ). Following filtering, 509 proteins were identified. These proteins were grouped into nine functional categories: Fusarium-derived, late embryogenesis abundant, oil-body, metabolism, stress, cellular, protein storage, metabolism, and defense. Defense proteins were up-regulated in response to infection in both CO441 and CL30 lines. Furthermore, F. graminearum derived proteins were only found in CL30 infected kernels suggesting that resistance may be attributed in part to the inability of Fusarium to establish itself in the embryo. To our knowledge this is the first successful application of LFQ mass spectrometry to the study of host-pathogen response to F. graminearum.Biological significanceFungal pathogen Fusarium graminearum is responsible for billion dollar losses in crops and contamination of global grains with harmful mycotoxins. By studying host-pathogen interactions of Fusarium and maize on a proteomic level with resistant and susceptible genotypes, the biological interactions occurring during infection of the maturing seed were characterized. Mature kernels of the F. graminearum susceptible maize line CL30 and resistant CO441 line were dissected to permit a proteomic survey of the new sporophytic generation, the embryo. Detailed knowledge of this Host-pathogen interactome will assist development of new cereal lines resistant to the rot diseases caused by Fusarium graminearum.HighlightsSusceptible (CL30) and Resistant (CO441) lines were injected with water mock or F. graminearum LC-MS/MS of maize embryo protein extracts followed by Label Free Quantification (LFQ) permitted identification, quantification and comparison of proteomes between maize genotypes and treatments Fusarium-derived proteins were abundant only in the susceptible infected embryo Defense proteomes were up-regulated in both lines following infection nsLTP and Protease Inhibitor were significantly over-expressed in the Susceptible line after infection; chitinase and WIP1 were significantly over-expressed in the Resistant line after infection

Effect of Intestinal Flora Clearance on Liver Proteomics in Mice

2019 ◽  
Vol 16 (3) ◽  
pp. 199-209
Author(s):  
Zhenghu Jia ◽  
Hui Liu ◽  
Mei Song ◽  
Chengmao Yang ◽  
Yapu Zhao ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Concanavalin A ◽  
Intestinal Flora ◽  
Label Free ◽  
Protein Protein Interactions ◽  
Rt Pcr ◽  
Proteome Level ◽  
And Control ◽  
The Relationship ◽  
Free Quantification

Background: Intestinal flora dynamically affects the host&#039;s systemic immune system. Liver is one of the organs that may be affected by intestinal microbiota. </P><P> Materials and Methods: In this study, we aimed to identify proteome level differences between liver tissue from mice cleared intestinal flora and control using tandem mass spectrometry (LC-MS/MS) and label free quantification. Additionally, protein-protein interactions were mapped by STRING, and also, the enrichment of inflammation-related signaling pathways and biological processes was identified using GO and IPA network system. RT-PCR and Western blot were used for validation of the proteomics findings. Results: Our study demonstrated that mice with cleared intestinal flora exhibited decreased sensitivity to Concanavalin A induced acute hepatitis. 324 Proteins in liver were differently expressed after intestinal flora clearance for one week while 210 proteins were differently expressed after intestinal flora clearance for two weeks. Furthermore, five of the identified proteins were validated by western blotting and further investigated by semi-quantitative RT-PCR. Conclusion: Our results showed that intestinal flora clearance in mice could reduce sensitivity to Concanavalin A induced liver injury and influence the expression of proteins in liver, which provides a clue for studying the relationship between gut bacteria and Concanavalin A induced hepatitis.

Label-free quantitative proteomic analysis of the YAP/TAZ interactome

2014 ◽  
Vol 306 (9) ◽  
pp. C805-C818 ◽  
Author(s):  
Priyanka Kohli ◽  
Malte P. Bartram ◽  
Sandra Habbig ◽  
Caroline Pahmeyer ◽  
Tobias Lamkemeyer ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Interactions ◽  
Affinity Purification ◽  
Single Copy ◽  
Single Step ◽  
Mass Spectrometry Analysis ◽  
Single Shot ◽  
Label Free ◽  
Protein Protein Interactions ◽  
Spectrometry Analysis

The function of an individual protein is typically defined by protein-protein interactions orchestrating the formation of large complexes critical for a wide variety of biological processes. Over the last decade the analysis of purified protein complexes by mass spectrometry became a key technique to identify protein-protein interactions. We present a fast and straightforward approach for analyses of interacting proteins combining a Flp-in single-copy cellular integration system and single-step affinity purification with single-shot mass spectrometry analysis. We applied this protocol to the analysis of the YAP and TAZ interactome. YAP and TAZ are the downstream effectors of the mammalian Hippo tumor suppressor pathway. Our study provides comprehensive interactomes for both YAP and TAZ and does not only confirm the majority of previously described interactors but, strikingly, revealed uncharacterized interaction partners that affect YAP/TAZ TEAD-dependent transcription. Among these newly identified candidates are Rassf8, thymopoetin, and the transcription factors CCAAT/enhancer-binding protein (C/EBP)β/δ and core-binding factor subunit β (Cbfb). In addition, our data allowed insights into complex stoichiometry and uncovered discrepancies between the YAP and TAZ interactomes. Taken together, the stringent approach presented here could help to significantly sharpen the understanding of protein-protein networks.

scholarly journals Automated Label-free Quantification of Metabolites from Liquid Chromatography–Mass Spectrometry Data

2013 ◽  
Vol 13 (1) ◽  
pp. 348-359 ◽  
Author(s):  
Erhan Kenar ◽  
Holger Franken ◽  
Sara Forcisi ◽  
Kilian Wörmann ◽  
Hans-Ulrich Häring ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Liquid Chromatography ◽  
Mass Spectrometry Data ◽  
Label Free ◽  
Liquid Chromatography Mass Spectrometry ◽  
Label Free Quantification ◽  
Chromatography Mass Spectrometry ◽  
Free Quantification
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