Redox proteomic identification of carbonylated proteins in autism plasma: insight into oxidative stress and its related biomarkers in autism

Feng, Chengyun; Chen, Youjiao; Pan, Jintao; Yang, Aochu; Niu, Li; Min, Jie; Xian-ling, Meng; Liao, Liping; Zhang, Kaoyuan; Shen, Liming

doi:10.1186/s12014-017-9138-0

Cited by 36 publications

(29 citation statements)

References 41 publications

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“…Both of these processes are known to occur as a result of γ-radiation exposure, primarily due to both the activity of the proteasome to clear damaged cellular constituents, and the well-known phenomenon of radiation-induced protein oxidation [ 5 , 47 , 48 , 49 , 50 ]. Either of these processes would, in turn, make protein identification using MS-based methods less reliable [ 51 , 52 , 53 , 54 ]. In this case, the lower levels of WT protein may reflect the increased sensitivity of these cells and macromolecules inside the cells to γ-radiation compared with the Evolved strain.…”

Section: Resultsmentioning

confidence: 99%

Proteomics Reveals Distinct Changes Associated with Increased Gamma Radiation Resistance in the Black Yeast Exophiala dermatitidis

Schultzhaus

Romsdahl

et al. 2020

Genes

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The yeast Exophiala dermatitidis exhibits high resistance to γ-radiation in comparison to many other fungi. Several aspects of this phenotype have been characterized, including its dependence on homologous recombination for the repair of radiation-induced DNA damage, and the transcriptomic response invoked by acute γ-radiation exposure in this organism. However, these findings have yet to identify unique γ-radiation exposure survival strategies—many genes that are induced by γ-radiation exposure do not appear to be important for recovery, and the homologous recombination machinery of this organism is not unique compared to more sensitive species. To identify features associated with γ-radiation resistance, here we characterized the proteomes of two E. dermatitidis strains—the wild type and a hyper-resistant strain developed through adaptive laboratory evolution—before and after γ-radiation exposure. The results demonstrate that protein intensities do not change substantially in response to this stress. Rather, the increased resistance exhibited by the evolved strain may be due in part to increased basal levels of single-stranded binding proteins and a large increase in ribosomal content, possibly allowing for a more robust, induced response during recovery. This experiment provides evidence enabling us to focus on DNA replication, protein production, and ribosome levels for further studies into the mechanism of γ-radiation resistance in E. dermatitidis and other fungi.

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Section: Resultsmentioning

confidence: 99%

Proteomics Reveals Distinct Changes Associated with Increased Gamma Radiation Resistance in the Black Yeast Exophiala dermatitidis

Schultzhaus

Romsdahl

et al. 2020

Genes

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“…This is also true for recent studies examining metabolomics,6162 markers of inflammation63 and oxidative stress,64 and salivary proteomics 65. Such findings cannot be readily generalized to early detection because biomarkers generally reflect dynamic processes that change over the course of development.…”

Section: Potential For Presymptomatic Detection: Advances In Biomarkementioning

confidence: 99%

Autism spectrum disorder: advances in diagnosis and evaluation

Zwaigenbaum

Penner

2018

BMJ

170

137

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Autism spectrum disorder (ASD) has a variety of causes, and its clinical expression is generally associated with substantial disability throughout the lifespan. Recent advances have led to earlier diagnosis, and deep phenotyping efforts focused on high risk infants have helped advance the characterization of early behavioral trajectories. Moreover, biomarkers that measure early structural and functional connectivity, visual orienting, and other biological processes have shown promise in detecting the risk of autism spectrum disorder even before the emergence of overt behavioral symptoms. Despite these advances, the mean age of diagnosis is still 4-5 years. Because of the broad consistency in published guidelines, parameters for high quality comprehensive assessments are available; however, such models are resource intensive and high demand can result in greatly increased waiting times. This review describes advances in detecting early behavioral and biological markers, current options and controversies in screening for the disorder, and best practice in its diagnostic evaluation including emerging data on innovative service models.

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“…Fewer proteomics studies on ASD have been published than those based on other disciplines, such as genomics or transcriptomics. Many of them rely on post-mortem brain tissues [ 50 , 51 , 52 ], serum [ 53 , 54 , 55 , 56 ], plasma [ 57 , 58 , 59 ], urine [ 63 ], saliva [ 60 , 61 , 62 ] direct samples or lymphoblastoid cell lines [ 64 ] ( Table 1 ).…”

Section: Translational and Clinical Proteomicsmentioning

confidence: 99%

Proteomics and Metabolomics Approaches towards a Functional Insight onto AUTISM Spectrum Disorders: Phenotype Stratification and Biomarker Discovery

Ristori

Mortera

Marzano

et al. 2020

IJMS

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Autism spectrum disorders (ASDs) are neurodevelopmental disorders characterized by behavioral alterations and currently affect about 1% of children. Significant genetic factors and mechanisms underline the causation of ASD. Indeed, many affected individuals are diagnosed with chromosomal abnormalities, submicroscopic deletions or duplications, single-gene disorders or variants. However, a range of metabolic abnormalities has been highlighted in many patients, by identifying biofluid metabolome and proteome profiles potentially usable as ASD biomarkers. Indeed, next-generation sequencing and other omics platforms, including proteomics and metabolomics, have uncovered early age disease biomarkers which may lead to novel diagnostic tools and treatment targets that may vary from patient to patient depending on the specific genomic and other omics findings. The progressive identification of new proteins and metabolites acting as biomarker candidates, combined with patient genetic and clinical data and environmental factors, including microbiota, would bring us towards advanced clinical decision support systems (CDSSs) assisted by machine learning models for advanced ASD-personalized medicine. Herein, we will discuss novel computational solutions to evaluate new proteome and metabolome ASD biomarker candidates, in terms of their recurrence in the reviewed literature and laboratory medicine feasibility. Moreover, the way to exploit CDSS, performed by artificial intelligence, is presented as an effective tool to integrate omics data to electronic health/medical records (EHR/EMR), hopefully acting as added value in the near future for the clinical management of ASD.

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Redox proteomic identification of carbonylated proteins in autism plasma: insight into oxidative stress and its related biomarkers in autism

Cited by 36 publications

References 41 publications

Proteomics Reveals Distinct Changes Associated with Increased Gamma Radiation Resistance in the Black Yeast Exophiala dermatitidis

Proteomics Reveals Distinct Changes Associated with Increased Gamma Radiation Resistance in the Black Yeast Exophiala dermatitidis

Autism spectrum disorder: advances in diagnosis and evaluation

Proteomics and Metabolomics Approaches towards a Functional Insight onto AUTISM Spectrum Disorders: Phenotype Stratification and Biomarker Discovery

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