Application of Label-Free Proteomics for Differential Analysis of Lung Carcinoma Cell Line A549

Sitek, Barbara; Waldera-Lupa, Daniel M.; Poschmann, Gereon; Meyer, Helmut E.

doi:10.1007/978-1-61779-885-6_16

Cited by 16 publications

(19 citation statements)

References 2 publications

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“…Mass spectrometric analyses of secretomes were carried out using the highly reproducible and stable LC-MS/MS system and a label-free approach for quantitation as described elsewhere (Sitek et al, 2012). For detailed information see Supplementary Material online.…”

Section: Mass Spectrometrymentioning

confidence: 99%

Characterization of Skin Aging–Associated Secreted Proteins (SAASP) Produced by Dermal Fibroblasts Isolated from Intrinsically Aged Human Skin

Lupa

Kalfalah

Safferling

et al. 2015

Journal of Investigative Dermatology

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157

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Most molecular hallmarks of cellular senescence have been identified in studies of cells aged in vitro by driving them into replicative or stress-induced senescence. Comparatively, less is known about the characteristic features of cells that have aged in vivo. Here we provide a systematic molecular analysis of normal human dermal fibroblasts (NHDFs) that were isolated from intrinsically aged human skin of young versus middle aged versus old donors. Intrinsically aged NHDFs in culture exhibited more frequently nuclear foci positive for p53 binding protein 1 and promyelocytic leukemia protein reminiscent of 'DNA segments with chromatin alterations reinforcing senescence (DNA-SCARS)'. Formation of such foci was neither accompanied by increased DNA double strand breaks, nor decreased cell viability, nor telomere shortening. However, it was associated with the development of a secretory phenotype, indicating incipient cell senescence. By quantitative analysis of the entire secretome present in conditioned cell culture supernatant, combined with a multiplex cytokine determination, we identified 998 proteins secreted by intrinsically aged NHDFs in culture. Seventy of these proteins exhibited an age-dependent secretion pattern and were accordingly denoted 'skin aging-associated secreted proteins (SAASP)'. Systematic comparison of SAASP with the classical senescence-associated secretory phenotype (SASP) revealed that matrix degradation as well as proinflammatory processes are common aspects of both conditions. However, secretion of 27 proteins involved in the biological processes of 'metabolism' and 'adherens junction interactions' was unique for NHDFs isolated from intrinsically aged skin. In conclusion, fibroblasts isolated from intrinsically aged skin exhibit some, but not all, molecular hallmarks of cellular senescence. Most importantly, they secrete a unique pattern of proteins that is distinct from the canonical SASP and might reflect specific processes of skin aging.

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Section: Mass Spectrometrymentioning

confidence: 99%

Characterization of Skin Aging–Associated Secreted Proteins (SAASP) Produced by Dermal Fibroblasts Isolated from Intrinsically Aged Human Skin

Lupa

Kalfalah

Safferling

et al. 2015

Journal of Investigative Dermatology

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157

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“…Coomassie stained nPsbH bands were excised from the gel after comparison with the corresponding pattern of nPsbH variants in the immunoblot. Each gel slice was digested with trypsin and analyzed with a nano‐HPLC/ESI‐MS system (Sitek et al ., ).…”

Section: Methodsmentioning

confidence: 97%

Expression of a nuclear‐encoded psbH gene complements the plastidic RNA processing defect in the PSII mutant hcf107 in Arabidopsis thaliana

2014

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SUMMARYThe helical-repeat RNA-binding protein HCF107 is required for processing, stabilization and translation of plastid-encoded psbH mRNA. The psbH gene encodes a small, hydrophilic subunit of the PSII complex and is part of the plastidic psbB-psbT-psbH-petB-petD transcription unit. In Arabidopsis hcf107 mutants, only trace amounts of PSII proteins can be detected. Beside drastically reduced synthesis of PsbH, the synthesis of CP47 was also reduced in these mutants, although the corresponding psbB transcripts accumulate to wild type levels. This situation raises the question, whether the reduction of CP47 is a direct consequence of the mutation, based on targeting of HCF107 to the psbB mRNA, or a secondary affect due to the absent PsbH. To clarify this issue we introduced a chimeric psbH construct comprising a sequence encoding a chloroplast transit peptide into the hcf107-2 background. We found that the nucleus-localized psbH was able to complement the mutant defect resulting in photoautotrophic plants. The PSII proteins CP47 and D1 accumulated to barely half of the wild type level. Further experiments showed that cytosolically synthesized PsbH was imported into chloroplasts and assembled into PSII complexes. Using this approach, we showed that the tetratricopeptide repeat protein HCF107 of Arabidopsis is only responsible for expression of PsbH and not for synthesis of CP47. In addition the data suggest the necessity of the small, one-helix membrane spanning protein PsbH for the accumulation of CP47 in higher plants.

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“…The actual feature selection takes place in (10). Recalling the observation model from (8), we conclude that the i-th sample is correctly classified by a vector ω if and only if y i x i , ω > 0.…”

Section: Step 2: Smoothing By Gaussian Densitymentioning

confidence: 95%

Sparse Proteomics Analysis – a compressed sensing-based approach for feature selection and classification of high-dimensional proteomics mass spectrometry data

et al. 2017

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BackgroundHigh-throughput proteomics techniques, such as mass spectrometry (MS)-based approaches, produce very high-dimensional data-sets. In a clinical setting one is often interested in how mass spectra differ between patients of different classes, for example spectra from healthy patients vs. spectra from patients having a particular disease. Machine learning algorithms are needed to (a) identify these discriminating features and (b) classify unknown spectra based on this feature set. Since the acquired data is usually noisy, the algorithms should be robust against noise and outliers, while the identified feature set should be as small as possible.ResultsWe present a new algorithm, Sparse Proteomics Analysis (SPA), based on the theory of compressed sensing that allows us to identify a minimal discriminating set of features from mass spectrometry data-sets. We show (1) how our method performs on artificial and real-world data-sets, (2) that its performance is competitive with standard (and widely used) algorithms for analyzing proteomics data, and (3) that it is robust against random and systematic noise. We further demonstrate the applicability of our algorithm to two previously published clinical data-sets.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-017-1565-4) contains supplementary material, which is available to authorized users.

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Application of Label-Free Proteomics for Differential Analysis of Lung Carcinoma Cell Line A549

Cited by 16 publications

References 2 publications

Characterization of Skin Aging–Associated Secreted Proteins (SAASP) Produced by Dermal Fibroblasts Isolated from Intrinsically Aged Human Skin

Characterization of Skin Aging–Associated Secreted Proteins (SAASP) Produced by Dermal Fibroblasts Isolated from Intrinsically Aged Human Skin

Expression of a nuclear‐encoded psbH gene complements the plastidic RNA processing defect in the PSII mutant hcf107 in Arabidopsis thaliana

Sparse Proteomics Analysis – a compressed sensing-based approach for feature selection and classification of high-dimensional proteomics mass spectrometry data

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