Label-Free and Standard-Free Absolute Quantitative Proteomics Using the “Total Protein” and “Proteomic Ruler” Approaches

Wiśniewski, Jacek R.

doi:10.1016/bs.mie.2016.10.002

Cited by 51 publications

(45 citation statements)

References 16 publications

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“…Total protein in the SDS lysates and peptide concentration in the digests were determined using the WF assay [ 35 ]. Titers of protein were calculated by the 'total protein approach' using the raw spectral intensities from MaxQuant output [ 36 ].…”

Section: Methodsmentioning

confidence: 99%

Restoration of type 1 iodothyronine deiodinase expression in renal cancer cells downregulates oncoproteins and affects key metabolic pathways as well as anti-oxidative system

et al. 2017

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Type 1 iodothyronine deiodinase (DIO1) contributes to deiodination of 3,5,3’,5’-tetraiodo-L-thyronine (thyroxine, T4) yielding of 3,5,3’-triiodothyronine (T3), a powerful regulator of cell differentiation, proliferation, and metabolism. Our previous work showed that loss of DIO1 enhances proliferation and migration of renal cancer cells. However, the global effects of DIO1 expression in various tissues affected by cancer remain unknown. Here, the effects of stable DIO1 re-expression were analyzed on the proteome of renal cancer cells, followed by quantitative real-time PCR validation in two renal cancer-derived cell lines. DIO1-induced changes in intracellular concentrations of thyroid hormones were quantified by L-MS/MS and correlations between expression of DIO1 and potential target genes were determined in tissue samples from renal cancer patients. Stable re-expression of DIO1, resulted in 26 downregulated proteins while 59 proteins were overexpressed in renal cancer cells. The ‘downregulated’ group consisted mainly of oncoproteins (e.g. STAT3, ANPEP, TGFBI, TGM2) that promote proliferation, migration and invasion. Furthermore, DIO1 re-expression enhanced concentrations of two subunits of thyroid hormone transporter (SLC7A5, SLC3A2), enzymes of key pathways of cellular energy metabolism (e.g. TKT, NAMPT, IDH2), sex steroid metabolism and anti-oxidative response (AKR1C2, AKR1B10). DIO1 expression resulted in elevated intracellular concentration of T4. Expression of DIO1-affected genes strongly correlated with DIO1 transcript levels in tissue samples from renal cancer patients as well as with their poor survival. This first study addressing effects of deiodinase re-expression on proteome of cancer cells demonstrates that induced DIO1 re-expression in renal cancer robustly downregulates oncoproteins, affects key metabolic pathways, and triggers proteins involved in anti-oxidative protection. This data supports the notion that suppressed DIO1 expression and changes in local availability of thyroid hormones might favor a shift from a differentiated to a more proliferation-prone state of cancer tissues and cell lines.

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Section: Methodsmentioning

confidence: 99%

Restoration of type 1 iodothyronine deiodinase expression in renal cancer cells downregulates oncoproteins and affects key metabolic pathways as well as anti-oxidative system

et al. 2017

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“…Seminal works on L. (Viannia) proteomes used 2DE of cell lysates with the aim to differentiate distinct Leishmania species causing American tegumentary leishmaniasis [23]. Since that, advances in MS protein identification driven the first proteomic maps of L. braziliensis, L. panamensis and L. guyanensis [24][25][26][27][28][29][30][31][32][33][34][35]. Using different methods for sample preparation, up to some hundreds of proteins were identified in these species.…”

Section: Introductionmentioning

confidence: 99%

“…Here, we describe a comprehensive quantitative analysis of the proteome of three strains that represent distinct and clinically/epidemiologically relevant species of L. (Viannia) subgenus: L. braziliensis (strain MHOM/BR/2000/LTCP 13396), L. panamensis (strain MHOM/CO/ 2009/6634) and L. guyanensis (strain MHOM/BR/1997/NMT-MAO 292P). We combined the filter-aided sample preparation (FASP) method with the consecutive multi-enzyme digestion [31,32] followed by high accuracy mass spectrometry and the "Total Protein Approach" and "Proteomic Ruler" [34,35] for calculation of absolute protein abundances in those species. Our dataset comprises near 7000 proteins, representing the most complete Leishmania proteome yet reported, and provides the first comprehensive quantitative analysis of the proteomes of the three species in terms of protein concentration and copy numbers.…”

Section: Introductionmentioning

confidence: 99%

In-depth quantitative proteomics uncovers specie-specific metabolic programs in Leishmania (Viannia) species

et al. 2020

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Leishmania species are responsible for a broad spectrum of diseases, denominated Leishmaniasis, affecting over 12 million people worldwide. During the last decade, there have been impressive efforts for sequencing the genome of most of the pathogenic Leishmania spp. as well as hundreds of strains, but large-scale proteomics analyses did not follow these achievements and the Leishmania proteome remained mostly uncharacterized. Here, we report a comprehensive comparative study of the proteomes of strains representing L. braziliensis, L. panamensis and L. guyanensis species. Proteins extracted by SDS-mediated lysis were processed following the multi-enzyme digestion-filter aided sample preparation (FASP) procedure and analysed by high accuracy mass spectrometry. "Total Protein Approach" and "Proteomic Ruler" were applied for absolute quantification of proteins. Principal component analysis demonstrated very high reproducibility among biological replicates and a very clear differentiation of the three species. Our dataset comprises near 7000 proteins, representing the most complete Leishmania proteome yet known, and provides a comprehensive quantitative picture of the proteomes of the three species in terms of protein concentration and copy numbers. Analysis of the abundance of proteins from the major energy metabolic processes allow us to highlight remarkably differences among the species and suggest that these parasites depend on distinct energy substrates to obtain ATP. Whereas L. braziliensis relies the more on glycolysis, L. panamensis and L. guyanensis seem to depend mainly on mitochondrial respiration. These results were confirmed by biochemical assays showing opposite profiles for glucose uptake and O 2 consumption in these species. In addition, we provide quantitative data about different membrane proteins, transporters, and lipids, all of which contribute for significant species-specific differences and PLOS NEGLECTED TROPICAL DISEASES

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“…High resolution and high accuracy data and optimal use of software tools are critical for the success of label‐free methods. Whereas label‐free quantification is widely used for measuring relative changes, it has also been implemented for determination of absolute protein abundances using the total protein approach (TPA) . In TPA, the fractional amount of a protein in the sample is calculated by dividing the sum of signal from all peptides of the protein by the signal of all detectable peptides in the sample .…”

Section: Quantitative Proteomic Methodsmentioning

confidence: 99%

“…Whereas label-free quantification is widely used for measuring relative changes, it has also been implemented for determination of absolute protein abundances using the total protein approach (TPA). 65 In TPA, the fractional amount of a protein in the sample is calculated by dividing the sum of signal from all peptides of the protein by the signal of all detectable peptides in the sample. 45 This promising approach allows calculation of concentrations of thousands of proteins in the sample without standards.…”

Section: Data Acquisition Approachesmentioning

confidence: 99%

Toward a Consensus on Applying Quantitative Liquid Chromatography‐Tandem Mass Spectrometry Proteomics in Translational Pharmacology Research: A White Paper

Prasad

Achour

Artursson

et al. 2019

Clin Pharma and Therapeutics

129

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Quantitative translation of information on drug absorption, disposition, receptor engagement, and drug–drug interactions from bench to bedside requires models informed by physiological parameters that link in vitro studies to in vivo outcomes. To predict in vivo outcomes, biochemical data from experimental systems are routinely scaled using protein quantity in these systems and relevant tissues. Although several laboratories have generated useful quantitative proteomic data using state‐of‐the‐art mass spectrometry, no harmonized guidelines exit for sample analysis and data integration to in vivo translation practices. To address this gap, a workshop was held on September 27 and 28, 2018, in Cambridge, MA, with 100 experts attending from academia, the pharmaceutical industry, and regulators. Various aspects of quantitative proteomics and its applications in translational pharmacology were debated. A summary of discussions and best practices identified by this expert panel are presented in this “White Paper” alongside unresolved issues that were outlined for future debates.

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Label-Free and Standard-Free Absolute Quantitative Proteomics Using the “Total Protein” and “Proteomic Ruler” Approaches

Cited by 51 publications

References 16 publications

Restoration of type 1 iodothyronine deiodinase expression in renal cancer cells downregulates oncoproteins and affects key metabolic pathways as well as anti-oxidative system

Restoration of type 1 iodothyronine deiodinase expression in renal cancer cells downregulates oncoproteins and affects key metabolic pathways as well as anti-oxidative system

In-depth quantitative proteomics uncovers specie-specific metabolic programs in Leishmania (Viannia) species

Toward a Consensus on Applying Quantitative Liquid Chromatography‐Tandem Mass Spectrometry Proteomics in Translational Pharmacology Research: A White Paper

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