Sequence Tagging Reveals Unexpected Modifications in Toxicoproteomics

Dasari, Surendra; Chambers, Matthew; Codreanu, Simona G.; Liebler, Daniel C.; Collins, Ben C.; Gallagher, William M.; Tabb, David L.

doi:10.1021/tx100275t

Cited by 27 publications

(31 citation statements)

References 43 publications

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“…Second, DirecTag-TagRecon software interrogated the subset of FASTA proteins for unanticipated PTMs (11). DirecTag generated the 50 best tags of three amino acids from each MS/MS.…”

Section: Methodsmentioning

confidence: 99%

“…IDPicker version 3.0 filtered the resulting peptide identifications at 2% FDR, as described above. Detected PTMs were attested following previously published guidelines (11). Relative expression of protein PTMs (at sample level) between two groups was performed using peptide intensities as described previously (24) and then displayed as percent difference between study days.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Release of skeletal muscle peptide fragments identifies individual proteins degraded during insulin deprivation in type 1 diabetic humans and mice

Robinson

Dasari

Karakelides

et al. 2016

American Journal of Physiology-Endocrinology and Metabolism

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Robinson MM, Dasari S, Karakelides H, Bergen HR 3rd, Nair KS. Release of skeletal muscle peptide fragments identifies individual proteins degraded during insulin deprivation in type 1 diabetic humans and mice. Am J Physiol Endocrinol Metab 311: E628 -E637, 2016. First published July 19, 2016; doi:10.1152/ajpendo.00175.2016.-Insulin regulates skeletal muscle protein degradation, but the types of proteins being degraded in vivo remain to be determined due to methodological limitations. We present a method to assess the types of skeletal muscle proteins that are degraded by extracting their degradation products as low-molecular weight (LMW) peptides from muscle samples. High-resolution mass spectrometry was used to identify the original intact proteins that generated the LMW peptides, which we validated in rodents and then applied to humans. We deprived insulin from insulin-treated streptozotocin (STZ) diabetic mice for 6 and 96 h and for 8 h in type 1 diabetic humans (T1D) for comparison with insulin-treated conditions. Protein degradation was measured using activation of autophagy and proteasome pathways, stable isotope tracers, and LMW approaches. In mice, insulin deprivation activated proteasome pathways and autophagy in muscle homogenates and isolated mitochondria. Reproducibility analysis of LMW extracts revealed that ϳ80% of proteins were detected consistently. As expected, insulin deprivation increased whole body protein turnover in T1D. Individual protein degradation increased with insulin deprivation, including those involved in mitochondrial function, proteome homeostasis, nDNA support, and contractile/cytoskeleton. Individual mitochondrial proteins that generated more LMW fragment with insulin deprivation included ATP synthase subunit-␥ (ϩ0.5-fold, P ϭ 0.007) and cytochrome c oxidase subunit 6 (ϩ0.305-fold, P ϭ 0.03).In conclusion, identifying LMW peptide fragments offers an approach to determine the degradation of individual proteins. Insulin deprivation increases degradation of select proteins and provides insight into the regulatory role of insulin in maintaining proteome homeostasis, especially of mitochondria.peptidomics; isotope tracer; low molecular weight; method; autophagy THE ANTICATABOLIC EFFECT OF INSULIN was evident from early reports of humans with type 1 diabetes (T1D) showing dramatic atrophy of skeletal muscle without insulin and then restoration of muscle mass with insulin treatment (17). Skeletal muscle protein content represents the balance between protein synthesis and protein degradation. Previous studies demonstrated that skeletal muscle catabolism during insulin deprivation in T1D is due primarily to increased protein degradation, with little change to mixed muscle protein synthesis, representing the average of multiple protein pools (8,16,35). Separating specific muscle protein fractions revealed that insulin has a stimulatory effect on mitochondrial proteins when amino acids are provided (36,40). In contrast, the synthesis rates of contractile proteins, such as myosin heavy cha...

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“…Second, DirecTag-TagRecon software interrogated the subset of FASTA proteins for unanticipated PTMs (11). DirecTag generated the 50 best tags of three amino acids from each MS/MS.…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Release of skeletal muscle peptide fragments identifies individual proteins degraded during insulin deprivation in type 1 diabetic humans and mice

Robinson

Dasari

Karakelides

et al. 2016

American Journal of Physiology-Endocrinology and Metabolism

Self Cite

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“…The family would be even larger if the roster included algorithms that employ very different strategies than SEQUEST and yet compute XCorr scores [42]. SEQUEST has stood the test of time for two main reasons; cross-correlation has demonstrated itself to be an excellent discriminator in the presence of noise peaks, and a variety of fully automated processing pipelines can work from SEQUEST identifications to simplify determining which spectra were confidently identified and to assemble protein inferences from the peptide-spectrum matches.…”

Section: Mapping the Futurementioning

confidence: 99%

The SEQUEST Family Tree

Tabb

2015

J. Am. Soc. Mass Spectrom.

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Since its introduction in 1994, SEQUEST has gained many important new capabilities, and a host of successor algorithms have built upon its successes. This Account and Perspective maps the evolution of this important tool and charts the relationships among contributions to the SEQUEST legacy. Many of the changes represented improvements in computing speed by clusters and graphics cards. Mass spectrometry innovations in mass accuracy and activation methods led to shifts in fragment modeling and scoring strategies. These changes, as well as the movement of laboratories and lab members, have led to great diversity among the members of the SEQUEST family.

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“…To facilitate SRM assay development we built a substantial library of MS/MS spectra assigned with high confidence to tryptic peptides arising from a large pool of rat liver samples. The MS/MS spectral library data set has been deposited in PeptideAtlas and has additionally already been exploited by additional studies aimed at elucidating unanticipated post translational modifications relating to drug toxicology (50). Specific SRM assays for 48 biomarker candidates were developed via iterative rounds of optimization and quality control.…”

Section: Targeted Measurement Of a Putative Hepatotoxicity Biomarker mentioning

confidence: 99%

Development of a Pharmaceutical Hepatotoxicity Biomarker Panel Using a Discovery to Targeted Proteomics Approach

Collins

Miller

Sposny

et al. 2012

Molecular & Cellular Proteomics

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There is a pressing and continued need for improved predictive power in preclinical pharmaceutical toxicology assessment as substantial numbers of drugs are still removed from the market, or from late-stage development, because of unanticipated issues of toxicity. In recent years a number of consortia have been formed with a view to integrating -omics molecular profiling strategies to increase the sensitivity and predictive power of preclinical toxicology evaluation. In this study we report on the LC-MS based proteomic analysis of the effects of the hepatotoxic compound EMD 335823 on liver from rats using an integrated discovery to targeted proteomics approach. This compound was one of a larger panel studied by a variety of molecular profiling techniques as part of the InnoMed PredTox Consortium. Label-free LC-MS analysis of hepatotoxicant EMD 335823 treated animals revealed only moderate correlation of individual protein expression with changes in mRNA expression observed by transcriptomic analysis of the same liver samples. Significantly however, analysis of the protein and transcript changes at the pathway level revealed they were in good agreement. This higher level analysis was also consistent with the previously suspected PPAR␣ activity of the compound. Subsequently, a panel of potential biomarkers of liver toxicity was assembled from the label-free LC-MS proteomics discovery data, the previously acquired transcriptomics data and selected candidates identified from the literature. We developed and then deployed optimized selected reaction monitoring assays to undertake multiplexed measurement of 48 putative toxicity biomarkers in liver tissue. The development of the selected reaction monitoring assays was facilitated by the construction of a peptide MS/MS spectral library from pooled control and treated rat liver lysate using peptide fractionation by strong cation exchange and off-gel electrophoresis cou- The inability of current preclinical toxicology evaluation methods to predict early, and with good accuracy, that a drug candidate will have to be removed from development (or from the market) because of toxicicity/safety issues is a serious bottleneck in the drug development pipeline (1). Novel omics profiling technologies have the potential to provide more effective preclinical predictive models for toxicity (2). By performing detailed and comprehensive molecular profiling of animal or cell-based models that have been exposed to known toxic insults, it should be possible to catalog the spectrum of molecular changes that cause or accompany a particular mechanism of toxicity. It is reasonable to assume that molecular changes underlying, or induced by, toxicologic mechanisms will be manifested at earlier time points and at lower dose levels than are required for classical toxicology evaluation endpoints. Hence, the basic premise of preclinical predictive systems toxicology is to perform molecular profiling experiments for a range of compounds, potentially hundreds, displaying various toxicities and derivin...

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Sequence Tagging Reveals Unexpected Modifications in Toxicoproteomics

Cited by 27 publications

References 43 publications

Release of skeletal muscle peptide fragments identifies individual proteins degraded during insulin deprivation in type 1 diabetic humans and mice

Release of skeletal muscle peptide fragments identifies individual proteins degraded during insulin deprivation in type 1 diabetic humans and mice

The SEQUEST Family Tree

Development of a Pharmaceutical Hepatotoxicity Biomarker Panel Using a Discovery to Targeted Proteomics Approach

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