88 research outputs found

    Cytotoxicity and toxicoproteomics analysis of thiazolidinedione exposure in human-derived cardiomyocytes

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    Thiazolidinediones (TZDs) (e.g., pioglitazone and rosiglitazone), known insulin sensitiser agents for type II diabetes mellitus, exhibit controversial effects on cardiac tissue. Despite consensus on their association with increased heart failure risk, limiting TZD use in diabetes management, the underlying mechanisms remain uncharacterised. Herein, we report a comprehensive in vitro investigation utilising a novel toxicoproteomics pipeline coupled with cytotoxicity assays in human adult cardiomyocytes to elucidate mechanistic insights into TZD cardiotoxicity. The cytotoxicity assay findings showed a significant loss of mitochondrial adenosine triphosphate production upon exposure to either TZD agents, which may underpin TZD cardiotoxicity. Our toxicoproteomics analysis revealed that mitochondrial dysfunction primarily stems from oxidative phosphorylation impairment, with distinct signalling mechanisms observed for both agents. The type of cell death differed strikingly between the two agents, with rosiglitazone exhibiting features of caspase-dependent apoptosis and pioglitazone implicating mitochondrial-mediated necroptosis, as evidenced by the protein upregulation in the phosphoglycerate mutase family 5–dynamin-related protein 1 axis. Furthermore, our analysis revealed additional mechanistic aspects of cardiotoxicity, showcasing drug specificity. The downregulation of various proteins involved in protein machinery and protein processing in the endoplasmic reticulum was observed in rosiglitazone-treated cells, implicating proteostasis in the rosiglitazone cardiotoxicity. Regarding pioglitazone, the findings suggested the potential activation of the interplay between the complement and coagulation systems and the disruption of the cytoskeletal architecture, which was primarily mediated through the integrin-signalling pathways responsible for pioglitazone-induced myocardial contractile failure. Collectively, this study unlocks substantial mechanistic insight into TZD cardiotoxicity, providing the rationale for future optimisation of antidiabetic therapies

    Sex differences in colon cancer metabolism reveal a novel subphenotype

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    Women have a lower incidence of colorectal cancer (CRC) than men, however, they have a higher incidence of right-sided colon cancer (RCC). This is of concern as patients with RCC have the poorest clinical outcomes among all CRC patients. Aberrant metabolism is a known hallmark and therapeutic target for cancer. We propose that metabolic subphenotypes exist between CRCs due to intertumoral molecular and genomic variation, and differences in environmental milieu of the colon which vary between the sexes. Metabolomics analysis of patient colon tumors (n = 197) and normal tissues (n = 39) revealed sex-specific metabolic subphenotypes dependent on anatomic location. Tumors from women with RCC were nutrient-deplete, showing enhanced energy production to fuel asparagine synthesis and amino acid uptake. The clinical importance of our findings were further investigated in an independent data set from The Cancer Genomic Atlas, and demonstrated that high asparagine synthetase (ASNS) expression correlated with poorer survival for women. This is the first study to show a unique, nutrient-deplete metabolic subphenotype in women with RCC, with implications for tumor progression and outcomes in CRC patients

    e-Fungi: a data resource for comparative analysis of fungal genomes.

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    BACKGROUND: The number of sequenced fungal genomes is ever increasing, with about 200 genomes already fully sequenced or in progress. Only a small percentage of those genomes have been comprehensively studied, for example using techniques from functional genomics. Comparative analysis has proven to be a useful strategy for enhancing our understanding of evolutionary biology and of the less well understood genomes. However, the data required for these analyses tends to be distributed in various heterogeneous data sources, making systematic comparative studies a cumbersome task. Furthermore, comparative analyses benefit from close integration of derived data sets that cluster genes or organisms in a way that eases the expression of requests that clarify points of similarity or difference between species. DESCRIPTION: To support systematic comparative analyses of fungal genomes we have developed the e-Fungi database, which integrates a variety of data for more than 30 fungal genomes. Publicly available genome data, functional annotations, and pathway information has been integrated into a single data repository and complemented with results of comparative analyses, such as MCL and OrthoMCL cluster analysis, and predictions of signaling proteins and the sub-cellular localisation of proteins. To access the data, a library of analysis tasks is available through a web interface. The analysis tasks are motivated by recent comparative genomics studies, and aim to support the study of evolutionary biology as well as community efforts for improving the annotation of genomes. Web services for each query are also available, enabling the tasks to be incorporated into workflows. CONCLUSION: The e-Fungi database provides fungal biologists with a resource for comparative studies of a large range of fungal genomes. Its analysis library supports the comparative study of genome data, functional annotation, and results of large scale analyses over all the genomes stored in the database. The database is accessible at http://www.e-fungi.org.uk, as is the WSDL for the web services.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

    An optimised monophasic faecal extraction method for LC-MS analysis and its application in gastrointestinal disease

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    Liquid chromatography coupled with mass spectrometry (LC-MS) metabolomic approaches are widely used to investigate underlying pathogenesis of gastrointestinal disease and mechanism of action of treatments. However, there is an unmet requirement to assess faecal metabolite extraction methods for large-scale metabolomics studies. Current methods often rely on biphasic extractions using harmful halogenated solvents, making automation and large-scale studies challenging. The present study reports an optimised monophasic faecal extraction protocol that is suitable for untargeted and targeted LC-MS analyses. The impact of several experimental parameters, including sample weight, extraction solvent, cellular disruption method, and sample-to-solvent ratio, were investigated. It is suggested that a 50 mg freeze-dried faecal sample should be used in a methanol extraction (1:20) using bead beating as the means of cell disruption. This is revealed by a significant increase in number of metabolites detected, improved signal intensity, and wide metabolic coverage given by each of the above extraction parameters. Finally, we addressed the applicability of the method on faecal samples from patients with Crohn’s disease (CD) and coeliac disease (CoD), two distinct chronic gastrointestinal diseases involving metabolic perturbations. Untargeted and targeted metabolomic analysis demonstrated the ability of the developed method to detect and stratify metabolites extracted from patient groups and healthy controls (HC), highlighting characteristic changes in the faecal metabolome according to disease. The method developed is, therefore, suitable for the analysis of patients with gastrointestinal disease and can be used to detect and distinguish differences in the metabolomes of CD, CoD, and HC

    Tumor tissue-specific biomarkers of colorectal cancer by anatomic location and stage

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    The progress in the discovery and validation of metabolite biomarkers for the detection of colorectal cancer (CRC) has been hampered by the lack of reproducibility between study cohorts. The majority of discovery-phase biomarker studies have used patient blood samples to identify disease-related metabolites, but this pre-validation phase is confounded by non-specific disease influences on the metabolome. We therefore propose that metabolite biomarker discovery would have greater success and higher reproducibility for CRC if the discovery phase was conducted in tumor tissues, to find metabolites that have higher specificity to the metabolic consequences of the disease, that are then validated in blood samples. This would thereby eliminate any non-tumor and/or body response effects to the disease. In this study, we performed comprehensive untargeted metabolomics analyses on normal (adjacent) colon and tumor tissues from CRC patients, revealing tumor tissue-specific biomarkers (n = 39/group). We identified 28 highly discriminatory tumor tissue metabolite biomarkers of CRC by orthogonal partial least-squares discriminant analysis (OPLS-DA) and univariate analyses (VIP > 1.5, p 0.96, using various models. We further identified five biomarkers that were specific to the anatomic location of tumors in the colon (n = 236). The combination of these five metabolites (S-adenosyl-L-homocysteine, formylmethionine, fucose 1-phosphate, lactate, and phenylalanine) demonstrated high differentiative capability for left- and right-sided colon cancers at stage I by internal cross-validation (AUC = 0.804, 95% confidence interval, CI 0.670–0.940). This study thus revealed nine discriminatory biomarkers of CRC that are now poised for external validation in a future independent cohort of samples. We also discovered a discrete metabolic signature to determine the anatomic location of the tumor at the earliest stage, thus potentially providing clinicians a means to identify individuals that could be triaged for additional screening regimens

    Electronic cigarette exposure triggers neutrophil inflammatory responses

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    Background The use of electronic cigarettes (e-cigs) is increasing and there is widespread perception that e-cigs are safe. E-cigs contain harmful chemicals; more research is needed to evaluate the safety of e-cig use. Our aim was to investigate the effects of e-cigs on the inflammatory response of human neutrophils. Methods Neutrophils were exposed to e-cig vapour extract (ECVE) and the expression of CD11b and CD66b was measured by flow cytometry and MMP-9 and CXCL8 by ELISA. We also measured the activity of neutrophil elastase (NE) and MMP-9, along with the activation of inflammatory signalling pathways. Finally we analysed the biochemical composition of ECVE by ultra-high performance liquid chromatography mass spectrometry. Results ECVE caused an increase in the expression of CD11b and CD66b, and increased the release of MMP-9 and CXCL8. Furthermore, there was an increase in NE and MMP-9 activity and an increase in p38 MAPK activation. We also identified several harmful chemicals in ECVE, including known carcinogens. Conclusions ECVE causes a pro-inflammatory response from human neutrophils. This raises concerns over the safety of e-cig use

    Distinct ecological fitness factors coordinated by a conserved Escherichia coli regulator during systemic bloodstream infection

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    The ability of bacterial pathogens to adapt to host niches is driven by the carriage and regulation of genes that benefit pathogenic lifestyles. Genes that encode virulence or fitness-enhancing factors must be regulated in response to changing host environments to allow rapid response to challenges presented by the host. Furthermore, this process can be controlled by preexisting transcription factors (TFs) that acquire new roles in tailoring regulatory networks, specifically in pathogens. However, the mechanisms underlying this process are poorly understood. The highly conserved Escherichia coli TF YhaJ exhibits distinct genome-binding dynamics and transcriptome control in pathotypes that occupy different host niches, such as uropathogenic E. coli (UPEC). Here, we report that this important regulator is required for UPEC systemic survival during murine bloodstream infection (BSI). This advantage is gained through the coordinated regulation of a small regulon comprised of both virulence and metabolic genes. YhaJ coordinates activation of both Type 1 and F1C fimbriae, as well as biosynthesis of the amino acid tryptophan, by both direct and indirect mechanisms. Deletion of yhaJ or the individual genes under its control leads to attenuated survival during BSI. Furthermore, all three systems are up-regulated in response to signals derived from serum or systemic host tissue, but not urine, suggesting a niche-specific regulatory trigger that enhances UPEC fitness via pleiotropic mechanisms. Collectively, our results identify YhaJ as a pathotype-specific regulatory aide, enhancing the expression of key genes that are collectively required for UPEC bloodstream pathogenesis

    Normalizing untargeted periconceptional urinary metabolomics data : a comparison of approaches

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    Metabolomics studies of the early-life exposome often use maternal urine specimens to investigate critical developmental windows, including the periconceptional period and early pregnancy. During these windows changes in kidney function can impact urine concentration. This makes accounting for differential urinary dilution across samples challenging. Because there is no consensus on the ideal normalization approach for urinary metabolomics data, this study’s objective was to determine the optimal post-analytical normalization approach for untargeted metabolomics analysis from a periconceptional cohort of 45 women. Urine samples consisted of 90 paired pre- and post-implantation samples. After untargeted mass spectrometry-based metabolomics analysis, we systematically compared the performance of three common approaches to adjust for urinary dilution—creatinine adjustment, specific gravity adjustment, and probabilistic quotient normalization (PQN)—using unsupervised principal components analysis, relative standard deviation (RSD) of pooled quality control samples, and orthogonal partial least-squares discriminant analysis (OPLS-DA). Results showed that creatinine adjustment is not a reliable approach to normalize urinary periconceptional metabolomics data. Either specific gravity or PQN are more reliable methods to adjust for urinary concentration, with tighter quality control sample clustering, lower RSD, and better OPLS-DA performance compared to creatinine adjustment. These findings have implications for metabolomics analyses on urine samples taken around the time of conception and in contexts where kidney function may be altered

    Bile acid distributions, sex-specificity, and prognosis in colorectal cancer

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    Background Bile acids are known to be genotoxic and contribute to colorectal cancer (CRC). However, the link between CRC tumor bile acids to tumor location, patient sex, microbiome, immune-regulatory cells, and prognosis is not clear. Methods We conducted bile acid analysis using targeted liquid chromatography–mass spectrometry (LC–MS) on tumor tissues from CRC patients (n = 228) with survival analysis. We performed quantitative immunofluorescence (QIF) on tumors to examine immune cells. Results Twelve of the bile acids were significantly higher in right-sided colon tumors compared to left-sided colon tumors. Furthermore, in male patients, right-sided colon tumors had elevated secondary bile acids (deoxycholic acid, lithocholic acid, ursodeoxycholic acid) compared to left-sided colon tumors, but this difference between tumors by location was not observed in females. A high ratio of glycoursodeoxycholic to ursodeoxycholic was associated with 5-year overall survival (HR = 3.76, 95% CI = 1.17 to 12.1, P = 0.026), and a high ratio of glycochenodeoxycholic acid to chenodeoxycholic acid was associated with 5-year recurrence-free survival (HR = 3.61, 95% CI = 1.10 to 11.84, P = 0.034). We also show correlation between these bile acids and FoxP3 + T regulatory cells. Conclusions This study revealed that the distribution of bile acid abundances in colon cancer patients is tumor location-, age- and sex-specific, and are linked to patient prognosis. This study provides new implications for targeting bile acid metabolism, microbiome, and immune responses for colon cancer patients by taking into account primary tumor location and sex

    Global serum profiling: an opportunity for earlier cancer detection

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    The advances in cancer research achieved in the last 50 years have been remarkable and have provided a deeper knowledge of this disease in many of its conceptual and biochemical aspects. From viewing a tumor as a ‘simple’ aggregate of mutant cells and focusing on detecting key cell changes leading to the tumorigenesis, the understanding of cancer has broadened to consider it as a complex organ interacting with its close and far surroundings through tumor and non-tumor cells, metabolic mechanisms, and immune processes. Metabolism and the immune system have been linked to tumorigenesis and malignancy progression along with cancer-specific genetic mutations. However, most technologies developed to overcome the barriers to earlier detection are focused solely on genetic information. The concept of cancer as a complex organ has led to research on other analytical techniques, with the quest of finding a more sensitive and cost-effective comprehensive approach. Furthermore, artificial intelligence has gained broader consensus in the oncology community as a powerful tool with the potential to revolutionize cancer diagnosis for physicians. We herein explore the relevance of the concept of cancer as a complex organ interacting with the bodily surroundings, and focus on promising emerging technologies seeking to diagnose cancer earlier, such as liquid biopsies. We highlight the importance of a comprehensive approach to encompass all the tumor and non-tumor derived information salient to earlier cancer detection
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