Integration of microRNAome, proteomics and metabolomics to analyze arsenic-induced malignant cell transformation

Multi-omics integration analysis: Tools and applications in environmental toxicology

Nowadays, traditional single-omics study is not enough to explain the causality between molecular alterations and toxicity endpoints for environmental pollutants. With the development of high-throughput sequencing technology and high-resolution mass spectrometry technology, the integrative analysis of multi-omics has become an efficient strategy to understand holistic biological mechanisms and to uncover the regulation network in specific biological processes. This review summarized sample preparation methods, integration analysis tools and the application of multi-omics integration analyses in environmental toxicology field. Currently, omics methods have been widely applied being as the sensitivity of early biological response, especially for low-dose and long-term exposure to environmental pollutants. Integrative omics can reveal the overall changes of genes, proteins, and/or metabolites in the cells, tissues or organisms, which provide new insights into revealing the overall toxicity effects, screening the toxic targets, and exploring the underlying molecular mechanism of pollutants.

Proteomic analysis of the effects of Dictyophora polysaccharide on arsenic-induced hepatotoxicity in rats

Arsenic (As) is a highly toxic environmental toxicant and a known human carcinogen. Long-term exposure to As can cause liver injury. Dictyophora polysaccharide (DIP) is a biologically active natural compound found in the Dictyophora with excellent antioxidation, anti-inflammation, and immune protection properties. In this study, the Sprague-Dawley (SD) rat model of As toxicity was established using a feeding method, followed by DIP treatment in rats with As-induced liver injury. The molecular mechanisms of As toxicity to the rat liver and the protective effect of DIP were investigated by proteomic studies. The results showed that 172, 328 and 191 differentially expressed proteins (DEPs) were identified between the As-exposed rats versus control rats (As/Ctrl), DIP treated rats versus As-exposed rats (DIP+As/As), and DIP treated rats versus control rats (DIP+As /Ctrl), respectively. Among them, the expression of 90 DEPs in the As/Ctrl groups was reversed by DIP treatment. As exposure caused dysregulation of metabolic pathways, mitochondria, oxidative stress, and apoptosis-related proteins in the rat liver. However, DIP treatment changed or restored the levels of these proteins, which attenuated the damage to the livers of rats caused by As exposure. The results provide new insights into the mechanisms of liver injury induced by As exposure and the treatment of DIP in As poisoning.

The Role of microRNAs in Arsenic-Induced Human Diseases: A Review

MicroRNAs (miRNAs) are noncoding RNAs with 20-22 nucleotides, which are encoded by endogenous genes and are capable of targeting the majority of human mRNAs. Arsenic is regarded as a human carcinogen, which can lead to many adverse health effects including diabetes, skin lesions, kidney disease, neurological impairment, male reproductive injury, and cardiovascular disease (CVD) such as cardiac arrhythmias, ischemic heart failure, and endothelial dysfunction. miRNAs can act as tumor suppressors and oncogenes via directly targeting oncogenes or tumor suppressors. Recently, miRNA dysregulation was considered to be an important mechanism of arsenic-induced human diseases and a potential biomarker to predict the diseases caused by arsenic exposure. Endogenic miRNAs such as miR-21, the miR-200 family, miR-155, and the let-7 family are involved in arsenic-induced human disease by inducing translational repression or RNA degradation and influencing multiple pathways, including mTOR/Arg 1, HIF-1α/VEGF, AKT, c-Myc, MAPK, Wnt, and PI3K pathways. Additionally, exogenous miRNAs derived from plants, such as miR-34a, miR-159, miR-2911, miR-159a, miR-156c, miR-168, etc., among others, can be transported from blood to specific tissue/organ systems in vivo. These exogenous miRNAs might be critical players in the treatment of human diseases by regulating host gene expression. This review summarizes the regulatory mechanisms of miRNAs in arsenic-induced human diseases, including cancers, CVD, and other human diseases. These special miRNAs could serve as potential biomarkers in the management and treatment of human diseases linked to arsenic exposure. Finally, the protective action of exogenous miRNAs, including antitumor, anti-inflammatory, anti-CVD, antioxidant stress, and antivirus are described.

miRNAs and arsenic-induced carcinogenesis

Arsenic-induced carcinogenesis is a worldwide health problem. Identifying the molecular mechanisms responsible for the induction of arsenic-induced cancers is important for developing treatment strategies. MicroRNA (miRNA) dysregulation is known to affect development and progression of human cancer. Several studies have identified an association between altered miRNA expression in cancers from individuals chronically exposed to arsenic and in cell models for arsenic-induced carcinogenesis. This chapter provides a comprehensive review for miRNA dysregulation in arsenic-induced cancer.

Environmental behavior, human health effect, and pollution control of heavy metal(loid)s toward full life cycle processes

Heavy metal(loid)s (HMs) have caused serious environmental pollution and health risks. Although the past few years have witnessed the achievements of studies on environmental behavior of HMs, the related toxicity mechanisms, and pollution control, their relationship remains a mystery. Researchers generally focused on one topic independently without comprehensive considerations due to the knowledge gap between environmental science and human health. Indeed, the full life cycle control of HMs is crucial and should be reconsidered with the combination of the occurrence, transport, and fate of HMs in the environment. Therefore, we started by reviewing the environmental behaviors of HMs which are affected by a variety of natural factors as well as their physicochemical properties. Furthermore, the related toxicity mechanisms were discussed according to exposure route, toxicity mechanism, and adverse consequences. In addition, the current state-of-the-art of available technologies for pollution control of HMs wastewater and solid wastes were summarized. Finally, based on the research trend, we proposed that advanced in-operando characterizations will help us better understand the fundamental reaction mechanisms, and big data analysis approaches will aid in establishing the prediction model for risk management.

Current Knowledge in Skin Metabolomics: Updates from Literature Review

Metabolomic profiling is an emerging field consisting of the measurement of metabolites in a biological system. Since metabolites can vary in relation to different stimuli, specific metabolic patterns can be closely related to a pathological process. In the dermatological setting, skin metabolomics can provide useful biomarkers for the diagnosis, prognosis, and therapy of cutaneous disorders. The main goal of the present review is to present a comprehensive overview of the published studies in skin metabolomics. A search for journal articles focused on skin metabolomics was conducted on the MEDLINE, EMBASE, Cochrane, and Scopus electronic databases. Only research articles with electronically available English full text were taken into consideration. Studies specifically focused on cutaneous microbiomes were also excluded from the present search. A total of 97 papers matched all the research criteria and were therefore considered for the present work. Most of the publications were focused on inflammatory dermatoses and immune-mediated cutaneous disorders. Skin oncology also turned out to be a relevant field in metabolomic research. Only a few papers were focused on infectious diseases and rarer genetic disorders. All the major metabolomic alterations published so far in the dermatological setting are described extensively in this review.

A systematic review: metabolomics-based identification of altered metabolites and pathways in the skin caused by internal and external factors

The skin's ability to function optimally is affected by many diverse factors. Metabolomics has a great potential to improve our understanding of the underlying metabolic changes and the affected pathways. Therefore, the objective of this study was to review the current state of the literature and to perform further metabolic pathway analysis on the obtained data. The aim was to gain an overview of the metabolic changes under altered conditions and to identify common and different patterns as a function of the investigated factors. A cross-study comparison of the extracted studies from different databases identified 364 metabolites, whose concentrations were considerably altered by the following factor groups: irradiation, xenobiotics, aging, and skin diseases (mainly psoriasis). Using metabolic databases and pathway analysis tools the individual metabolites were assigned to the corresponding metabolic pathways and the most strongly affected signaling pathways were identified. All factors induced oxidative stress. Thus, antioxidant defense systems, especially coenzyme Q₁₀  (aging) and the glutathione system (irradiation, aging, xenobiotics) were impacted. Lipid metabolism was also impacted by all factors studied. The carnitine shuttle as part of β-oxidation was activated by all factor groups except aging. Glycolysis, Krebs (TCA) cycle and purine metabolism were mainly affected by irradiation and xenobiotics. The pentose phosphate pathway was activated and Krebs cycle was downregulated in response to oxidative stress. In summary, it can be ascertained that mainly energy metabolism, lipid metabolism, antioxidative defense and DNA repair systems were impacted by the factors studied.

Temporal Modulation of Differential Alternative Splicing in HaCaT Human Keratinocyte Cell Line Chronically Exposed to Arsenic for up to 28 Wk

BACKGROUND

Chronic arsenic exposure via drinking water is associated with an increased risk of developing cancer and noncancer chronic diseases. Pre-mRNAs are often subject to alternative splicing, generating mRNA isoforms encoding functionally distinct protein isoforms. The resulting imbalance in isoform species can result in pathogenic changes in critical signaling pathways. Alternative splicing as a mechanism of arsenic-induced toxicity and carcinogenicity is understudied.

OBJECTIVE

This study aimed to accurately profile differential alternative splicing events in human keratinocytes induced by chronic arsenic exposure that might play a role in carcinogenesis.

METHODS

Independent quadruplicate cultures of immortalized human keratinocytes (HaCaT) were maintained continuously for 28 wk with 0 or 100 nM sodium arsenite. RNA-sequencing (RNA-Seq) was performed with poly(A) RNA isolated from cells harvested at 7, 19, and 28 wk with subsequent replicate multivariate analysis of transcript splicing (rMATS) analysis to detect and quantify differential alternative splicing events. Reverse transcriptase-polymerase chain reaction (RT-PCR) for selected alternative splicing events was performed to validate RNA-Seq predictions. Functional enrichment was performed by gene ontology (GO) analysis of the differential alternative splicing event data set at each time point.

RESULTS

At least 600 differential alternative splicing events were detected at each time point tested, comprising all the five main types of alternative splicing and occurring in both open reading frames (ORFs) and untranslated regions (UTRs). Based on functional relevance ELK4, SHC1, and XRRA1 were selected for validation of predicted alternative splicing events at 7 wk by RT-PCR. Densitometric analysis of RT-PCR data corroborated the rMATS predicted alternative splicing for all three events. Protein expression validation of the selected alternative splicing events was challenging given that very few isoform-specific antibodies are available. GO analysis demonstrated that the enriched terms in differential alternatively spliced mRNAs changed dynamically with the time of exposure. Notably, RNA metabolism and splicing regulation pathways were enriched at the 7-wk time point, when the greatest number of differentially alternatively spliced mRNAs are detected. Our preliminary proteomic analysis demonstrated that the expression of the canonical isoforms of the splice regulators DDX42, RMB25, and SRRM2 were induced upon chronic arsenic exposure, corroborating the splicing predictions.

DISCUSSION

These results using cultures of HaCaT cells suggest that arsenic exposure disrupted an alternative splice factor network and induced time-dependent genome-wide differential alternative splicing that likely contributed to the changing proteomic landscape in arsenic-induced carcinogenesis. However, significant challenges remain in corroborating alternative splicing data at the proteomic level. https://doi.org/10.1289/EHP9676.

A Metabolic Profiling Study of Realgar-Induced Acute Kidney Injury in Mice

Realgar has been used as a type of mineral drug that contains arsenic for thousands of years. Previous studies have shown that Realgar-induced acute kidney injury is associated with abnormal metabolism, but the underlying mechanism is poorly understood. The aim of this study is to investigate the metabolic changes in serum and kidney tissues of mice exposed to Realgar by using a metabolomic approach and explore the molecular mechanisms of acute kidney injury induced by Realgar. Forty mice were randomly divided into four groups: Control group, 0.5-, 1.0, and 2.0 g/kg Realgar group. After 1 week, the body weight and kidney weight of the mice were measured. The serum and kidney samples were used for LC-MS spectroscopic metabolic profiling. Principal component analysis (PCA), correlation analysis, and pathway analysis were used to detect the nephrotoxic effects of Realgar. Body weight decreased significantly in the 2.0 g/kg group, and the kidney weight index also showed a dose-dependent increase in Realgar. The PCA score plot showed the serum and kidney tissue metabolic profile of mice exposed to 2.0 g/kg Realgar separated from the control group, while the lower-doses of 0.5 g/kg and 1.0 g/kg Realgar shown a similar view to the Control group. Thirty-three metabolites and seventeen metabolites were screened and identified in the serum and kidney of mice in a dose-dependent manner. respectively. Correlation analysis showed a strong correlation among these metabolites. Amino acid metabolism, lipid metabolism, glutathione metabolism, and purine metabolism pathways were found to be mainly associated with Realgar nephrotoxicity. This work illustrated the metabolic alterations in Realgar-induced nephrotoxic mice through a metabolomic approach.

Proteomics analysis in the kidney of mice following oral feeding Realgar

ETHNOPHARMACOLOGICAL RELEVANCE

Realgar, a famous traditional Chinese mineral medicine, has been toxic to the renal system. However, the underlying mechanism of Realgar nephrotoxicity is still unclear.

AIM OF THE STUDY

This study aimed to investigate the potential mechanism of Realgar-induced nephrotoxicity by using a label-free quantitative proteomic method.

MATERIALS AND METHODS

36 mice were randomly divided into four groups: Control group, 0.5-, 1.0, and 2.0 g/kg Realgar group. After one week, serum biochemical parameters and renal histopathological examination were performed. Label-free quantitative proteomics was used to identify differentially expressed proteins which were subsequently analyzed with bioinformatics methods. Western blot was utilized to verify the six representative protein expressions.

RESULTS

The results showed that 2.0 g/kg Realgar significantly increased blood urea nitrogen and induced the formation of tube cast of renal tubules, while the lower-dose of 0.5 g/kg and 1.0 g/kg Realgar showed no changes. Label-free proteomic analysis identified 3138 proteins, and 272 of those proteins were screened for significant changes in a dose-dependent manner. Functional enrichment analysis suggested that these proteins could affect the apoptotic process and oxidative stress. Representative proteins in the 2.0 g/kg Realgar group, including Cat, Bad, Cycs, Nqo1, Podxl, and Hmox1, were verified by western blot.

CONCLUSIONS

The results in this study suggest that apoptosis and oxidative stress might be related to the Realgar-induced nephrotoxicity in mice. Moreover, the strategy of proteomics could contribute to the understanding of the mechanisms of nephrotoxicity in mice exposed to Realgar.

Integrated tissue proteome and metabolome reveal key elements and regulatory pathways in cutaneous squamous cell carcinoma

Cutaneous squamous cell carcinoma (CSCC) is a widespread malignancy but has a very low long-term survival rate for patients at the metastatic stage. Therefore, it is urgent to identify prognostic biomarkers for CSCC and improve our understanding of disease progression. Here we took advantage of a data-independent acquisition (DIA)-based nano liquid chromatography equipped with an orbitrap mass spectrometry (nLC-MS/MS) and ultraperformance LC coupled to a time-of-flight tandem MS (UPLC-TOF-MS/MS) technique to analyze cancer and corresponding noncancerous tissues from 20 CSCC patients for integrated proteomic and metabolomic analyses. Overall, 6241 tissue proteins were detected, while 136 proteins were significantly expressed in CSCC tissues. Further functional analysis revealed that various biological processes were highly enriched and participated in the pathogenesis of CSCC, especially DNA damage responses. Moreover, 641 named metabolites in total were identified, among which 181 were significantly changed in CSCC tissues. A total of 101 pathways were significantly enriched including apoptosis, autophagy, PI3K-Akt and mTOR signaling pathways. Interestingly, two pathways, protein digestion & absorption and platelet activation were both enriched in proteomic and metabolomic studies involving 5 proteins and 11 metabolites. Accordingly, a four-metabolite panel consisting of arachidonate, glutamine, glutamic acid, and proline (all area under the curve (AUC) values more than 0.9) was developed with a high accuracy (0.971) to distinguish the 20 detected cancer tissues from their noncancerous tissues. Collectively, our work highlighted the key elements and regulatory pathways involved in the pathogenesis of CSCC. More importantly, the present study not only provided potential biomarkers for the early diagnosis of CSCC, but also expanded our knowledge of the physiopathology of the disease. SIGNIFICANCE: CSCC is the second most common human cancer but has few treatment options and few sensitive biomarkers for diagnosis. Here we comprehensively revealed its molecular characteristics by performing integrated tissue proteomic and metabolomic analyses. Significantly distinct profiles and certain enriched pathways including DNA damage responses were identified as associated with CSCC. Moreover, protein digestion & absorption and platelet activation were both enriched in the proteome and metabolome. These identified molecular changes probably play significant roles in CSCC development. Finally, we developed a four-metabolite panel to distinguish CSCC with high accuracy. Overall, our data not only provided potential diagnostic biomarkers, but also extended knowledge on the pathogenesis of CSCC.

Arsenic-induced changes in miRNA expression in cancer and other diseases

miRNAs (miRNA) are essential players regulating gene expression affecting cellular processes contributing to disease development. Dysregulated miRNA expression has been observed in numerous diseases including hepatitis, cardiovascular diseases and cancers. In cardiovascular diseases, several miRNAs function as mediators of pathogenic stress-related signaling pathways that may lead to an excessive extracellular matrix production and collagen deposition causing cardiac stress resulting in fibrosis. In cancers, many miRNAs function as oncogenes or tumor suppressors facilitating tumor growth, invasion and angiogenesis. Furthermore, the association between distinct miRNA profile and tumor development, progression and treatment response has identified miRNAs as potential biomarkers for disease diagnosis and prognosis. Growing evidence demonstrates changes in miRNA expression levels in experimental settings or observational studies associated with environmental chemical exposures such as arsenic. Arsenic is one of the most well-known human carcinogens. Long-term exposure through drinking water increases risk of developing skin, lung and urinary bladder cancers, as well as cardiovascular disease. The mechanism(s) by which arsenic causes disease remains elusive. Proposed mechanisms include miRNA dysregulation. Epidemiological studies identified differential miRNA expression between arsenic-exposed and non-exposed individuals from India, Bangladesh, China and Mexico. In vivo and in vitro studies have shown that miRNAs are critically involved in arsenic-induced malignant transformation. Few studies analyzed miRNAs in other diseases associated with arsenic exposure. Importantly, there is no consensus on a consistent miRNA profile for arsenic-induced cancers because most studies analyze only particular miRNAs. Identifying miRNA expression changes common among humans, rodents and cell lines might guide future miRNA investigations.

The association of tryptophan and phenylalanine are associated with arsenic-induced skin lesions in a Chinese population chronically exposed to arsenic via drinking water: a case-control study

OBJECTIVES

We investigated the association of specific serum amino acids (AAs) with the odds of arsenic-induced skin lesions (AISL) and their ability to distinguish patients with AISL from people chronically exposed to arsenic.

DESIGN

Case-control study.

SETTING

Three arsenic-exposed villages in Wuyuan County, Hetao Plain, Inner Mongolia, China were evaluated.

PARTICIPANTS

Among the 450 residents aged 18-79 years, who were chronically exposed to arsenic via drinking water, 56 were diagnosed as having AISL (defined as cases). Another 56 participants without AISL, matched by gender and age (±1 year) from the same population, were examined as controls.

MAIN OUTCOME MEASURES AND METHODS

AA levels were determined by ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry-based metabolomics analysis. Potential confounding variables were identified via a standardised questionnaire and clinical examination. Multivariable conditional logistic regression model and receiver operating characteristic curve analyses were performed to investigate the relationship between specific AAs and AISL.

RESULTS

Tryptophan and phenylalanine levels were negatively associated with AISL (p<0.05). Compared with that in the first quartile, the adjusted OR of AISL in the second, third and fourth quartiles were decreased by 44%, 88% and 79% for tryptophan and 30%, 80% and 80% for phenylalanine, respectively. The combination of these two higher-level AAs showed the lowest OR for AISL (OR=0.08; 95% CI 0.02 to 0.25; p<0.001). Furthermore, both AAs showed a moderate ability to distinguish patients with AISL from the control, with the area under the curve (AUC; 95% CI) as 0.67 (0.57 to 0.77) for tryptophan and 0.70 (0.60 to 0.80) for phenylalanine (p<0.05). The combined pattern with AUC (95% CI) was 0.72 (0.62 to 0.81), showing a sensitivity of 76.79% and specificity of 58.93% (p<0.001).

CONCLUSIONS

Specific AAs may be linked to AISL and play important roles in early AISL identification.

TRIAL REGISTRATION NUMBER

NCT02235948.

Analysis of the dynamic aberrant landscape of DNA methylation and gene expression during arsenic-induced cell transformation

Inorganic arsenic is a well-known carcinogen associated with several types of cancer, but the mechanisms involved in arsenic-induced carcinogenesis are not fully understood. Recent evidence points to epigenetic dysregulation as an important mechanism in this process; however, the effects of epigenetic alterations in gene expression have not been explored in depth. Using microarray data and applying a multivariate clustering analysis in a Gaussian mixture model, we describe the alterations in DNA methylation around the promoter region and the impact on gene expression in HaCaT cells during the transformation process caused by chronic exposure to arsenic. Using this clustering approach, the genes were grouped according to their methylation and expression status in the epigenetic landscape, and the changes that occurred during the cellular transformation were identified adequately. Thus, we present a valuable method for identifying epigenomic dysregulation.