PubMed

A metabolomics strategy to assess the combined toxicity of polycyclic aromatic hydrocarbons (PAHs) and short-chain chlorinated paraffins (SCCPs). Environ Pollut. 2017 Dec 07;234:572-580 Authors: Wang F, Zhang H, Geng N, Ren X, Zhang B, Gong Y, Chen J Abstract The combined toxicity of mixed chemicals is usually evaluated according to several specific endpoints, and other potentially toxic effects are disregarded. In this study, we provided a metabolomics strategy to achieve a comprehensive understanding of toxicological interactions between mixed chemicals on metabolism. The metabolic changes were quantified by a pseudotargeted analysis, and the types of combined effects were quantitatively discriminated according to the calculation of metabolic effect level index (MELI). The metabolomics strategy was used to assess the combined effects of polycyclic aromatic hydrocarbons (PAHs) and short-chain chlorinated paraffins (SCCPs) on the metabolism of human hepatoma HepG2 cells. Our data suggested that exposure to a combination of PAHs and SCCPs at human internal exposure levels could result in an additive effect on the overall metabolism, whereas diverse joint effects were observed on various metabolic pathways. The combined exposure could induce a synergistic up-regulation of phospholipid metabolism, an additive up-regulation of fatty acid metabolism, an additive down-regulation of tricarboxylic acid cycle and glycolysis, and an antagonistic effect on purine metabolism. SCCPs in the mixture acted as the primary driver for the acceleration of phospholipid and fatty acid metabolism. Lipid metabolism disorder caused by exposure to a combination of PAHs and SCCPs should be an important concern for human health. PMID: 29223814 [PubMed - as supplied by publisher]

Isolated mangiferin and naringenin exert antidiabetic effect via PPARγ/GLUT4 dual agonistic action with strong metabolic regulation. Chem Biol Interact. 2017 Dec 06;: Authors: Singh AK, Raj V, Keshari AK, Rai A, Kumar P, Rawat A, Maity B, Kumar D, Prakash A, De A, Samanta A, Bhattacharya B, Saha S Abstract In this study, we isolated two compounds from the leaves of Salacia oblonga (SA1, mangiferin and SA2, naringenin), and their structures were confirmed by infrared spectroscopy, nuclear magnetic resonance (NMR) spectroscopy, and mass spectrometry. SA1 and SA2 were orally administered to streptozotocin-induced diabetic rats at 50 and 100 mg/kg daily for 15 days. Blood glucose level, serum lipid profile, oxidative stress parameters, histopathology, docking, molecular parameters, and NMR-based metabolic perturbation studies were performed to investigate the pharmacological activities of SA1 and SA2. Results suggested that both compounds reduced blood glucose level, restored body weight, and normalized lipid concentrations in the serum and oxidative stress biomarkers in the liver and pancreas. In addition, the docking study on several diabetes-associated targets revealed that both compounds had a strong binding affinity towards peroxisome proliferator-activated receptor gamma (PPARγ) and glucose transporter type 4 (GLUT4). Further real-time reverse transcription polymerase chain reaction and western blot analyses were performed to confirm the gene and protein expression levels of PPARγ and GLUT4 in the pancreatic tissues. Data obtained from the molecular studies showed that both compounds exhibited antidiabetic effects through dual activation of PPARγ/GLUT4 signaling pathways. Finally, the NMR-based metabolic studies showed that both compounds normalized the diabetogenic metabolites in the serum. Altogether, we concluded that SA1 and SA2 might be potential antidiabetic lead compounds for future drug development. PMID: 29223569 [PubMed - as supplied by publisher]

Caffeine - rich infusion from Cola nitida (kola nut) inhibits major carbohydrate catabolic enzymes; abates redox imbalance; and modulates oxidative dysregulated metabolic pathways and metabolites in Fe2+-induced hepatic toxicity. Biomed Pharmacother. 2017 Dec 06;: Authors: Erukainure OL, Oyebode OA, Sokhela MK, Koorbanally NA, Islam MS Abstract The antioxidative and antidiabetic effects and toxicity of caffeine-rich infusion of Cola nitida were investigated using in vitro, ex vivo and in silico models. C. nitida was infused in boiling water and allowed to cool before concentrating at <50°C. HPLC analysis of the infusion revealed a caffeine content of 80.08%. The infusion showed potent in vitro antioxidant activity by significantly (p<0.05) scavenging 2,2'-diphenyl-1-picrylhydrazyl (DPPH). It significantly (p<0.05) inhibited α-glucosidase and α-amylase activities. Treatment of Fe2+ induced oxidative hepatic tissues with the infusion led to increase Superoxide Dismutase (SOD) and catalase activities, and glutathione (GSH) level as well as decreased malondialdehyde (MDA) level. FTIR spectroscopy of hepatic metabolite revealed restoration of oxidative-induced depleted functional groups by the infusion. LC-MS analysis of the metabolite also revealed restoration of most depleted metabolites with concomitant generation of 4-O-Methylgallic, (-)-Epicatechin sulfate, L-Arginine, L-tyrosine, Citric acid and Decanoic acid in infusion-treated tissues. Pathway analysis of the identified metabolites revealed the presence of 21 metabolic pathways involved in normal hepatic tissues, 12 in oxidative injured tissues and 17 in the treated tissues. Treatment with the infusion restored 4 metabolic pathways common to the normal tissue and further activated 4 additional pathways. Prediction of oral toxicity of caffeine showed it to belong to class 3, with a LD50 of 127mg/kg. Its toxicity target was predicted as Adenosine Receptor A2a. It was also predicted to be an inhibitor of CYP1A2. These results suggest the antioxidative and antidiabetic properties of C. nitida infusion, with caffeine as the major constituent. PMID: 29223552 [PubMed - as supplied by publisher]

Left-Ventricular Assist Device Impact on Aortic Valve Mechanics, Proteomics and Ultrastructure. Ann Thorac Surg. 2017 Dec 06;: Authors: Stephens EH, Han J, Trawick EA, Di Martino ES, Akkiraju H, Brown LM, Connell JP, Grande-Allen KJ, Vunjak-Novakovic G, Takayama H Abstract BACKGROUND: Aortic regurgitation is a prevalent, detrimental complication of left ventricular assist devices (LVADs). The altered hemodynamics of LVADs results in aortic valves (AVs) having distinct mechanical stimulation. Our hypothesis was that the altered AV hemodynamics modulates the valve cells and matrix, resulting in changes in valvular mechanical properties that then can lead to regurgitation. METHODS: AVs were collected from 16 LVAD and 6 non-LVAD patients at time of heart transplant. Standard demographic and preoperative data were collected and comparisons between the two groups were calculated using standard statistical methods. Samples were analyzed using biaxial mechanical tensile testing, mass spectrometry-based proteomics, and transmission electron microscopy to assess ultrastructure. RESULTS: The maximum circumferential leaflet strain in LVAD patients was less than in non-LVAD patients (0.35 ± 0.10MPa versus 0.52 ± 0.18 MPa, p = 0.03) with a trend of reduced radial strain (p = 0.06) and a tendency for the radial strain to decrease with increasing LVAD duration (p = 0.063). Numerous proteins associated with actin and myosin, immune signaling and oxidative stress, and transforming growth factor β were increased in LVAD patients. Ultrastructural analysis showed a trend of increased fiber diameter in LVAD patients (46.2 ± 7.2 nm versus 45.1 ± 6.9 nm, p = 0.10), but no difference in fiber density. CONCLUSIONS: AVs in LVAD patients showed decreased compliance and increased expression of numerous proteins related to valve activation and injury compared to non-LVAD patients. Further knowledge of AV changes leading to regurgitation in LVAD patients and the pathways by which they occur may provide an opportunity for interventions to prevent and/or reverse this detrimental complication. PMID: 29223417 [PubMed - as supplied by publisher]

Related Articles Metabolic Model Reconstruction and Analysis of an Artificial Microbial Ecosystem. Methods Mol Biol. 2018;1716:219-238 Authors: Ye C, Xu N, Chen X, Liu L Abstract Microbial communities are widespread in the environment, and to isolate and identify species or to determine relations among microorganisms, some 'omics methods like metagenomics, proteomics, and metabolomics have been used. When combined with various 'omics data, models known as artificial microbial ecosystems (AME) are powerful methods that can make functional predictions about microbial communities. Reconstruction of an AME model is the first step for model analysis. Many techniques have been applied to the construction of AME models, e.g., the compartmentalization approach, community objectives method, and dynamic analysis approach. Of these approaches, species compartmentalization is the most relevant to genetics. Besides, some algorithms have been developed for the analysis of AME models. In this chapter, we present a general protocol for the use of the species compartmentalization method to reconstruct a model of microbial communities. Then, the analysis of an AME is discussed. PMID: 29222756 [PubMed - in process]

Related Articles Tail domain of the Aspergillus fumigatus class V myosin orchestrates septal localization and hyphal growth. J Cell Sci. 2017 Dec 08;: Authors: Renshaw H, Vargas-Muñiz JM, Juvvadi PR, Richards AD, Waitt G, Soderblom EJ, Moseley MA, Steinbach WJ Abstract Myosins are critical motor proteins that contribute to the secretory pathway, polarized growth, and cytokinesis. The globular tail domains of class V myosins have been shown to be important for cargo binding and actin cable organization. Additionally, phosphorylation plays a role in class V myosin cargo choice. Our previous studies on the class V myosin, MyoE, in the fungal pathogen Aspergillus fumigatus confirmed its requirement for normal morphology and virulence. However, the domains and molecular mechanisms governing MyoE's function remain unknown. Here, by analyzing tail mutants we demonstrate that the tail is required for radial growth, conidiation, septation frequency, and MyoE localization at the septum. Furthermore, MyoE is phosphorylated at multiple residues in vivo; however, alanine substitution mutants revealed that no single phosphorylated residue was critical. Importantly, in the absence of the phosphatase calcineurin, an additional residue was phosphorylated in its tail domain. Mutation of this tail residue led to mislocalization of MyoE from the septa. This work reveals the importance of the MyoE tail domain and its phosphorylation/dephosphorylation in the growth and morphology of A. fumigatus. PMID: 29222113 [PubMed - as supplied by publisher]

Related Articles Plasma protein profiling of patients with intraductal papillary mucinous neoplasm of the pancreas as potential precursor lesions of pancreatic cancer. Clin Chim Acta. 2017 Dec 05;: Authors: Ilies M, Sappa PK, Iuga CA, Loghin F, Salazar MG, Weiss FU, Beyer G, Lerch MM, Völker U, Mayerle J, Hammer E Abstract Efforts for the early diagnosis of the pancreatic ductal adenocarcinoma (PDAC) have recently been driven to one of the precursor lesions, namely intraductal papillary mucinous neoplasm of the pancreas (IPMN). Only a few studies have focused on IPMN molecular biology and its overall progression to cancer. Therefore, IPMN lacks comprehensive characterization which makes its clinical management controversial. In this study, we characterized plasma proteins in the presence of IPMNs in comparison to healthy controls, chronic pancreatitis, and PDAC by a proteomics approach using data-independent acquisition based mass spectrometry. We describe several protein sets that could aid IPMN diagnosis, but also differentiation of IPMN from healthy controls, as well as from benign and malignant diseases. Among all, high levels of carbonic anhydrases and hemoglobins were characteristic for the IPMN group. By employing ELISA based quantification we validated our results for human tissue inhibitor of metalloproteinase inhibitor 1 (TIMP-1). We consider IPMN management directed towards an early potential cancer development a crucial opportunity before PDAC initiation and thus its early detection and cure. PMID: 29221926 [PubMed - as supplied by publisher]

Related Articles Yale school of public health symposium on lifetime exposures and human health: the exposome; summary and future reflections. Hum Genomics. 2017 Dec 08;11(1):32 Authors: Johnson CH, Athersuch TJ, Collman GW, Dhungana S, Grant DF, Jones DP, Patel CJ, Vasiliou V Abstract The exposome is defined as "the totality of environmental exposures encountered from birth to death" and was developed to address the need for comprehensive environmental exposure assessment to better understand disease etiology. Due to the complexity of the exposome, significant efforts have been made to develop technologies for longitudinal, internal and external exposure monitoring, and bioinformatics to integrate and analyze datasets generated. Our objectives were to bring together leaders in the field of exposomics, at a recent Symposium on "Lifetime Exposures and Human Health: The Exposome," held at Yale School of Public Health. Our aim was to highlight the most recent technological advancements for measurement of the exposome, bioinformatics development, current limitations, and future needs in environmental health. In the discussions, an emphasis was placed on moving away from a one-chemical one-health outcome model toward a new paradigm of monitoring the totality of exposures that individuals may experience over their lifetime. This is critical to better understand the underlying biological impact on human health, particularly during windows of susceptibility. Recent advancements in metabolomics and bioinformatics are driving the field forward in biomonitoring and understanding the biological impact, and the technological and logistical challenges involved in the analyses were highlighted. In conclusion, further developments and support are needed for large-scale biomonitoring and management of big data, standardization for exposure and data analyses, bioinformatics tools for co-exposure or mixture analyses, and methods for data sharing. PMID: 29221465 [PubMed - in process]

Physiological effects caused by microcystin-producing and non-microcystin producing Microcystis aeruginosa on medaka fish: A proteomic and metabolomic study on liver. Environ Pollut. 2017 Dec 05;234:523-537 Authors: Le Manach S, Sotton B, Huet H, Duval C, Paris A, Marie A, Yépremian C, Catherine A, Mathéron L, Vinh J, Edery M, Marie B Abstract Cyanobacterial blooms have become a common phenomenon in eutrophic freshwater ecosystems worldwide. Microcystis is an important bloom-forming and toxin-producing genus in continental aquatic ecosystems, which poses a potential risk to Human populations as well as on aquatic organisms. Microcystis is known to produce along with various bioactive peptides, the microcystins (MCs) that have attracted more attention notably due to their high hepatotoxicity. To better understand the effects of cyanobacterial blooms on fish, medaka fish (Oryzias latipes) were sub-chronically exposed to either non-MC-producing or MC-producing living strains and, for this latter, to its subsequent MC-extract of Microcystis aeruginosa. Toxicological effects on liver have been evaluated through the combined approach of histopathology and 'omics' (i.e. proteomics and metabolomics). All treatments induce sex-dependent effects at both cellular and molecular levels. Moreover, the modalities of exposure appear to induce differential responses as the direct exposure to the cyanobacterial strains induce more acute effects than the MC-extract treatment. Our histopathological observations indicate that both non-MC-producing and MC-producing strains induce cellular impairments. Both proteomic and metabolomic analyses exhibit various biological disruptions in the liver of females and males exposed to strain and extract treatments. These results support the hypothesis that M. aeruginosa is able to produce bioactive peptides, other than MCs, which can induce toxicological effects in fish liver. Moreover, they highlight the importance of considering cyanobacterial cells as a whole to assess the realistic environmental risk of cyanobacteria on fish. PMID: 29220784 [PubMed - as supplied by publisher]

Fully Automated Pipetting Sorting System for Different Morphological Phenotypes of Zebrafish Embryos. SLAS Technol. 2017 Dec 01;:2472630317745780 Authors: Breitwieser H, Dickmeis T, Vogt M, Ferg M, Pylatiuk C Abstract Systems biology methods, such as transcriptomics and metabolomics, require large numbers of small model organisms, such as zebrafish embryos. Manual separation of mutant embryos from wild-type embryos is a tedious and time-consuming task that is prone to errors, especially if there are variable phenotypes of a mutant. Here we describe a zebrafish embryo sorting system with two cameras and image processing based on template-matching algorithms. In order to evaluate the system, zebrafish rx3 mutants that lack eyes due to a patterning defect in brain development were separated from their wild-type siblings. These mutants show glucocorticoid deficiency due to pituitary defects and serve as a model for human secondary adrenal insufficiencies. We show that the variable phenotypes of the mutant embryos can be safely distinguished from phenotypic wild-type zebrafish embryos and sorted from one petri dish into another petri dish or into a 96-well microtiter plate. On average, classification of a zebrafish embryo takes approximately 1 s, with a sensitivity and specificity of 87% to 95%, respectively. Other morphological phenotypes may be classified and sorted using similar techniques. PMID: 29220613 [PubMed - as supplied by publisher]

Crocadepsins - Depsipeptides from the Myxobacterium Chondromyces crocatus found by a Genome Mining Approach. ACS Chem Biol. 2017 Dec 08;: Authors: Surup F, Viehrig K, Rachid S, Plaza A, Maurer CK, Hartmann RW, Müller R Abstract Analysis of the genome sequence of the myxobacterium Chondromyces crocatus Cm c5 revealed the presence of numerous cryptic megasynthetase gene clusters, one of which we here assign to two previously unknown chlorinated metabolites by a comparative gene inactivation and secondary metabolomics approach. Structure elucidation of these compounds revealed a unique cyclic depsipeptide skeleton featuring β- and δ-amide bonds of aspartic acid and 3-methyl ornithine moieties, respectively. Insights into their biosynthesis were obtained by targeted gene inactivation and feeding experiments employing isotope-labeled precursors. The compounds were produced ubiquitously by the species Chondromyces crocatus and were found to inhibit the carbon storage regulator-RNA interaction. PMID: 29220569 [PubMed - as supplied by publisher]

Mitochondrial metabolism and cancer. Cell Res. 2017 Dec 08;: Authors: Porporato PE, Filigheddu N, Pedro JMB, Kroemer G, Galluzzi L Abstract Glycolysis has long been considered as the major metabolic process for energy production and anabolic growth in cancer cells. Although such a view has been instrumental for the development of powerful imaging tools that are still used in the clinics, it is now clear that mitochondria play a key role in oncogenesis. Besides exerting central bioenergetic functions, mitochondria provide indeed building blocks for tumor anabolism, control redox and calcium homeostasis, participate in transcriptional regulation, and govern cell death. Thus, mitochondria constitute promising targets for the development of novel anticancer agents. However, tumors arise, progress, and respond to therapy in the context of an intimate crosstalk with the host immune system, and many immunological functions rely on intact mitochondrial metabolism. Here, we review the cancer cell-intrinsic and cell-extrinsic mechanisms through which mitochondria influence all steps of oncogenesis, with a focus on the therapeutic potential of targeting mitochondrial metabolism for cancer therapy.Cell Research advance online publication 8 December 2017; doi:10.1038/cr.2017.155. PMID: 29219147 [PubMed - as supplied by publisher]

Related Articles [Preliminary screening of biomarkers for curcumin's antidepressant effect based on metabonomics method]. Zhongguo Zhong Yao Za Zhi. 2017 Sep;42(18):3596-3601 Authors: Ma ZJ, Zhang W, Dong JM, Yu XH, Zhao XM, Pu SB Abstract To screen potential biomarkers of curcumin related to treating depression rats by using metabolomics means, so as to explore the antidepressant action mechanism of curcumin. The healthy male SD rats were randomly divided into four groups. Chronic unpredictable mild stress (CUMS) stimulation was conducted for modeling for 2 weeks, and then curcumin (200 mg•kg⁻¹) or venlafaxine (40 mg•kg⁻¹) was given by gavage administration. The blank group and model group rats were given with the same volume of 1% CMCNa normal saline, once per day for two weeks. The rats serum for each group was collected and LC/MS-IT-TOF method was used to characterize the metabolic differences. Also multivariate statistical analysis was used to screen possible potential biomarkers and analyze the possible metabolic pathways. After administration of curcumin and venlafaxine respectively, the depression indexes of CUMS model rats were all improved significantly (P<0.05), but there were no significant differences between curcumin and venlafaxine groups. In PCA and PLS-DA analysis after curcumin or venlafaxine intervention on CUMS model group rats, the small molecule metabolites level reflects a normal trend, and particularly for the curcumin group. Through metabonomics technology, 11 biomarkers associated with curcumin antidepressant effect were screened, and at the same time seven metabolic pathways were involved. The results showed that curcumin had antidepressant effects, which was evident in both macro and micro levels, comparable with positive drug of venlafaxine. The antidepressant effect of curcumin may be associated with the glycerol phospholipid metabolism, linoleic acid metabolism, pentose and glucuronic acid ester and ether lipid metabolism, but still need further exploration in the future. PMID: 29218948 [PubMed - in process]

Related Articles Analyzing metabolomics data for association with genotypes using two-component Gaussian mixture distributions. Pac Symp Biocomput. 2018;23:496-506 Authors: Westra J, Hartman N, Lake B, Shearer G, Tintle N Abstract Standard approaches to evaluate the impact of single nucleotide polymorphisms (SNP) on quantitative phenotypes use linear models. However, these normal-based approaches may not optimally model phenotypes which are better represented by Gaussian mixture distributions (e.g., some metabolomics data). We develop a likelihood ratio test on the mixing proportions of two-component Gaussian mixture distributions and consider more restrictive models to increase power in light of a priori biological knowledge. Data were simulated to validate the improved power of the likelihood ratio test and the restricted likelihood ratio test over a linear model and a log transformed linear model. Then, using real data from the Framingham Heart Study, we analyzed 20,315 SNPs on chromosome 11, demonstrating that the proposed likelihood ratio test identifies SNPs well known to participate in the desaturation of certain fatty acids. Our study both validates the approach of increasing power by using the likelihood ratio test that leverages Gaussian mixture models, and creates a model with improved sensitivity and interpretability. PMID: 29218908 [PubMed - in process]

Related Articles Considerations for automated machine learning in clinical metabolic profiling: Altered homocysteine plasma concentration associated with metformin exposure. Pac Symp Biocomput. 2018;23:460-471 Authors: Orlenko A, Moore JH, Orzechowski P, Olson RS, Cairns J, Caraballo PJ, Weinshilboum RM, Wang L, Breitenstein MK Abstract With the maturation of metabolomics science and proliferation of biobanks, clinical metabolic profiling is an increasingly opportunistic frontier for advancing translational clinical research. Automated Machine Learning (AutoML) approaches provide exciting opportunity to guide feature selection in agnostic metabolic profiling endeavors, where potentially thousands of independent data points must be evaluated. In previous research, AutoML using high-dimensional data of varying types has been demonstrably robust, outperforming traditional approaches. However, considerations for application in clinical metabolic profiling remain to be evaluated. Particularly, regarding the robustness of AutoML to identify and adjust for common clinical confounders. In this study, we present a focused case study regarding AutoML considerations for using the Tree-Based Optimization Tool (TPOT) in metabolic profiling of exposure to metformin in a biobank cohort. First, we propose a tandem rank-accuracy measure to guide agnostic feature selection and corresponding threshold determination in clinical metabolic profiling endeavors. Second, while AutoML, using default parameters, demonstrated potential to lack sensitivity to low-effect confounding clinical covariates, we demonstrated residual training and adjustment of metabolite features as an easily applicable approach to ensure AutoML adjustment for potential confounding characteristics. Finally, we present increased homocysteine with long-term exposure to metformin as a potentially novel, non-replicated metabolite association suggested by TPOT; an association not identified in parallel clinical metabolic profiling endeavors. While warranting independent replication, our tandem rank-accuracy measure suggests homocysteine to be the metabolite feature with largest effect, and corresponding priority for further translational clinical research. Residual training and adjustment for a potential confounding effect by BMI only slightly modified the suggested association. Increased homocysteine is thought to be associated with vitamin B12 deficiency - evaluation for potential clinical relevance is suggested. While considerations for clinical metabolic profiling are recommended, including adjustment approaches for clinical confounders, AutoML presents an exciting tool to enhance clinical metabolic profiling and advance translational research endeavors. PMID: 29218905 [PubMed - in process]

Related Articles Best practices and lessons learned from reuse of 4 patient-derived metabolomics datasets in Alzheimer's disease. Pac Symp Biocomput. 2018;23:280-291 Authors: Tenenbaum JD, Blach C Abstract The importance of open data has been increasingly recognized in recent years. Although the sharing and reuse of clinical data for translational research lags behind best practices in biological science, a number of patient-derived datasets exist and have been published enabling translational research spanning multiple scales from molecular to organ level, and from patients to populations. In seeking to replicate metabolomic biomarker results in Alzheimer's disease our team identified three independent cohorts in which to compare findings. Accessing the datasets associated with these cohorts, understanding their content and provenance, and comparing variables between studies was a valuable exercise in exploring the principles of open data in practice. It also helped inform steps taken to make the original datasets available for use by other researchers. In this paper we describe best practices and lessons learned in attempting to identify, access, understand, and analyze these additional datasets to advance research reproducibility, as well as steps taken to facilitate sharing of our own data. PMID: 29218889 [PubMed - in process]

Related Articles Temporal-Spatial Profiling of Pedunculopontine Galanin-Cholinergic Neurons in the Lactacystin Rat Model of Parkinson's Disease. Neurotox Res. 2017 Dec 07;: Authors: Elson JL, Kochaj R, Reynolds R, Pienaar IS Abstract Parkinson's disease (PD) is conventionally seen as resulting from single-system neurodegeneration affecting nigrostriatal dopaminergic neurons. However, accumulating evidence indicates multi-system degeneration and neurotransmitter deficiencies, including cholinergic neurons which degenerate in a brainstem nucleus, the pedunculopontine nucleus (PPN), resulting in motor and cognitive impairments. The neuropeptide galanin can inhibit cholinergic transmission, while being upregulated in degenerating brain regions associated with cognitive decline. Here we determined the temporal-spatial profile of progressive expression of endogenous galanin within degenerating cholinergic neurons, across the rostro-caudal axis of the PPN, by utilizing the lactacystin-induced rat model of PD. First, we show progressive neuronal death affecting nigral dopaminergic and PPN cholinergic neurons, reflecting that seen in PD patients, to facilitate use of this model for assessing the therapeutic potential of bioactive peptides. Next, stereological analyses of the lesioned brain hemisphere found that the number of PPN cholinergic neurons expressing galanin increased by 11%, compared to sham-lesioned controls, and increasing by a further 5% as the neurodegenerative process evolved. Galanin upregulation within cholinergic PPN neurons was most prevalent closest to the intra-nigral lesion site, suggesting that galanin upregulation in such neurons adapt intrinsically to neurodegeneration, to possibly neuroprotect. This is the first report on the extent and pattern of galanin expression in cholinergic neurons across distinct PPN subregions in both the intact rat CNS and lactacystin-lesioned rats. The findings pave the way for future work to target galanin signaling in the PPN, to determine the extent to which upregulated galanin expression could offer a viable treatment strategy for ameliorating PD symptoms associated with cholinergic degeneration. PMID: 29218504 [PubMed - as supplied by publisher]

Related Articles Panomics for Precision Medicine. Trends Mol Med. 2017 Dec 04;: Authors: Sandhu C, Qureshi A, Emili A Abstract Medicine is poised to undergo a digital transformation. High-throughput platforms are creating terabytes of genomic, transcriptomic, proteomic, and metabolomic data. The challenge is to interpret these data in a meaningful manner - to uncover relationships that are not readily apparent between molecular profiles and states of health or disease. This will require the development of novel data pipelines and computational tools. The combined analysis of multi-dimensional data is referred to as 'panomics'. The ultimate hope of integrative panomics is that it will lead to the discovery and application of novel markers and targeted therapeutics that drive forward a new era of 'precision medicine' where inter-individual variation is accounted for in the treatment of patients. PMID: 29217119 [PubMed - as supplied by publisher]

16 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2017/12/08PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

16 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2017/12/08PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.