Proteomics-Based Identification of Differentially Abundant Proteins from Human Keratinocytes Exposed to Arsenic Trioxide

Abstract

IntroductionArsenic is a widely distributed environmental toxicant that can cause multi-tissue pathologies. Proteomic assays allow for the identification of biological processes modulated by arsenic in diverse tissue types.MethodThe altered abundance of proteins from HaCaT human keratinocyte cell line exposed to arsenic was quantified using a label-free LC-MS/MS mass spectrometry workflow. Selected proteomics results were validated using western blot and RT-PCR. A functional annotation analytics strategy that included visual analytical integration of heterogeneous data sets was developed to elucidate functional categories. The annotations integrated were mainly tissue localization, biological process and gene family.ResultThe abundance of 173 proteins was altered in keratinocytes exposed to arsenic; in which 96 proteins had increased abundance while 77 proteins had decreased abundance. These proteins were also classified into 69 Gene Ontology biological process terms. The increased abundance of transferrin receptor protein (TFRC) was validated and also annotated to participate in response to hypoxia. A total of 33 proteins (11 increased abundance and 22 decreased abundance) were associated with 18 metabolic process terms. The Glutamate--cysteine ligase catalytic subunit (GCLC), the only protein annotated with the term sulfur amino acid metabolism process, had increased abundance while succinate dehydrogenase [ubiquinone] iron-sulfur subunit, mitochondrial precursor (SDHB), a tumor suppressor, had decreased abundance.ConclusionA list of 173 differentially abundant proteins in response to arsenic trioxide was grouped using three major functional annotations covering tissue localization, biological process and protein families. A possible explanation for hyperpigmentation pathologies observed in arsenic toxicity is that arsenic exposure leads to increased iron uptake in the normally hypoxic human skin. The proteins mapped to metabolic process terms and differentially abundant are candidates for evaluating metabolic pathways perturbed by arsenicals.

Proteomic characterization of HaCaT keratinocytes provides new insights into changes associated with SDS exposure

“…Two peak lists (unexposed and exposed to SDS cells) were generated and exported for a Mascot MS/MS search. In total, 962 proteins were detected in HaCaT cells, and this number of identified proteins is comparable with similar studies using shotgun proteomics (Udensi et al 2014).…”

“…In particular, a proteomic study of HaCaT keratinocytes through liquid chromatographytandem mass spectrometry and bioinformatics analysis was performed to identify proteins of circadian rhythms (Avitabile et al 2014). Recently, HaCaT cells were used to profiling proteins of inflammation and malignant transformation in nonmelanoma skin cancer (Paulitschke et al 2015) and the altered abundance of proteins after treatment with arsenic (Udensi et al 2014) by a label-free LC-MS/MS.…”

State of the science review of the health effects of inorganic arsenic: Perspectives for future research

“…Signaling molecules (eg, MAPK, NF‐κB, etc.) can also be activated in response to arsenic‐induced OS . It has been pointed out that the activator protein 1 (AP‐1) activity influences the differential effect between low (mitogenic) and high (proinflammatory) doses of exposure …”

Prediction of skin anti‐aging clinical benefits of an association of ingredients from marine and maritime origins: Ex vivo evaluation using a label‐free quantitative proteomic and customized data processing approach

“…It allows for various samples to be tested in vitro (primary fibroblasts or keratinocytes cultures), as well as ex vivo (skin explants and reconstituted epidermis) or in vivo, with skin swabs and D‐Squames. Dermatology, therapeutics as well as cosmetology, has used it for studying the mechanisms of UV damage and “photo‐aging,” inflammation, differentiation, skin barrier, and it allowed to discover potential diagnostic markers, to understand tegumentary structure and potential reinforcing treatment, or active substances or pollution effects on skin . It also has been shown recently that proteomics and transcriptomics may show discrepancies due to a variety of post‐transcriptional regulations, making proteomics the shortest, straightest path to phenotype .…”

“…Dermatology, therapeutics as well as cosmetology, has used it for studying the mechanisms of UV damage and "photo-aging," inflammation, differentiation, skin barrier, and it allowed to discover potential diagnostic markers, 10 to understand tegumentary structure and potential reinforcing treatment, 11 or active substances or pollution effects on skin. 12,13 It also has been shown recently that proteomics and transcriptomics may show discrepancies due to a variety of post-transcriptional regulations, making proteomics the shortest, straightest path to phenotype. 6,[14][15][16] The activity on the skin of ingredients from algal origin and, more broadly, from marine origin is hardly ever evaluated with "omics" technologies.…”