PubMed

Glutamate mediated metabolic neutralization mitigates propionate toxicity in intracellular Mycobacterium tuberculosis. Sci Rep. 2018 May 31;8(1):8506 Authors: Lee JJ, Lim J, Gao S, Lawson CP, Odell M, Raheem S, Woo J, Kang SH, Kang SS, Jeon BY, Eoh H Abstract Metabolic networks in biological systems are interconnected, such that malfunctioning parts can be corrected by other parts within the network, a process termed adaptive metabolism. Unlike Bacillus Calmette-Guérin (BCG), Mycobacterium tuberculosis (Mtb) better manages its intracellular lifestyle by executing adaptive metabolism. Here, we used metabolomics and identified glutamate synthase (GltB/D) that converts glutamine to glutamate (Q → E) as a metabolic effort used to neutralize cytoplasmic pH that is acidified while consuming host propionate carbon through the methylcitrate cycle (MCC). Methylisocitrate lyase, the last step of the MCC, is intrinsically downregulated in BCG, leading to obstruction of carbon flux toward central carbon metabolism, accumulation of MCC intermediates, and interference with GltB/D mediated neutralizing activity against propionate toxicity. Indeed, vitamin B12 mediated bypass MCC and additional supplement of glutamate led to selectively correct the phenotypic attenuation in BCG and restore the adaptive capacity of BCG to the similar level of Mtb phenotype. Collectively, a defective crosstalk between MCC and Q → E contributes to attenuation of intracellular BCG. Furthermore, GltB/D inhibition enhances the level of propionate toxicity in Mtb. Thus, these findings revealed a new adaptive metabolism and propose GltB/D as a synergistic target to improve the antimicrobial outcomes of MCC inhibition in Mtb. PMID: 29855554 [PubMed - in process]

Related Articles Non-invasive staging of chronic kidney allograft damage using urine metabolomic profiling. Pediatr Transplant. 2018 May 31;:e13226 Authors: Landsberg A, Sharma A, Gibson IW, Rush D, Wishart DS, Blydt-Hansen TD Abstract Chronic kidney allograft damage is characterized by IFTA and GS. We sought to identify urinary metabolite signatures associated with severity of IFTA and GS in pediatric kidney transplant recipients. Urine samples (n = 396) from 60 pediatric transplant recipients were obtained at the time of kidney biopsy and assayed for 133 metabolites by mass spectrometry. Metabolite profiles were quantified via PLS-DA. We used mixed-effects regression to identify laboratory and clinical predictors of histopathology. Urine samples (n = 174) without rejection or AKI were divided into training/validation sets (75:25%). Metabolite classifiers trained on IFTA severity and %GS showed strong statistical correlation (r = .73, P < .001 and r = .72; P < .001, respectively) and remained significant on the validation sets. Regression analysis identified additional clinical features that improved prediction: months post-transplant (GS, IFTA); and proteinuria, GFR, and age (GS only). Addition of clinical variables improved performance of the %GS classifier (AUC = 0.9; 95% CI = 0.85-0.96) but not for IFTA (AUC = 0.82; 95% CI = 0.71-0.92). Despite the presence of potentially confounding phenotypes, these findings were further validated in samples withheld for rejection or AKI. We identify urine metabolite classifiers for IFTA and GS, which may prove useful for non-invasive assessment of histopathological damage. PMID: 29855144 [PubMed - as supplied by publisher]

Related Articles Association Between Newborn Metabolic Profiles and Pediatric Kidney Disease. Kidney Int Rep. 2018 May;3(3):691-700 Authors: Sood MM, Murphy MSQ, Hawken S, Wong CA, Potter BK, Burns KD, Tsampalieros A, Atkinson KM, Chakraborty P, Wilson K Abstract Introduction: Metabolomics offers considerable promise in early disease detection. We set out to test the hypothesis that routine newborn metabolic profiles at birth, obtained through screening for inborn errors of metabolism, would be associated with kidney disease and add incremental information to known clinical risk factors. Methods: We conducted a population-level cohort study in Ontario, Canada, using metabolic profiles from 1,288,905 newborns from 2006 to 2015. The primary outcome was chronic kidney disease (CKD) or dialysis. Individual metabolites and their ratio combinations were examined by logistic regression after adjustment for established risk factors for kidney disease and incremental risk prediction measured. Results: CKD occurred in 2086 (0.16%, median time 612 days) and dialysis in 641 (0.05%, median time 99 days) infants and children. Individual metabolites consisted of amino acids, acylcarnitines, markers of fatty acid oxidation, and others. Base models incorporating clinical risk factors only provided c-statistics of 0.61 for CKD and 0.70 for dialysis. The addition of identified metabolites to risk prediciton models resulted in significant incremental improvement in the performance of both models (CKD model: c-statistic 0.66 NRI 0.36 IDI 0.04, dialysis model: c-statistic 0.77 NRI 0.57 IDI 0.09). This was consistent after internal validation using bootstrapping and a sensitivity analysis excluding outcomes within the first 30 days. Conclusion: Routinely collected screening metabolites at birth are associated with CKD and the need for dialytic therapies in infants and children, and add incremental information to traditional clinical risk factors. PMID: 29854978 [PubMed]

Related Articles Identification of urinary metabolites that correlate with clinical improvements in children with autism treated with sulforaphane from broccoli. Mol Autism. 2018;9:35 Authors: Bent S, Lawton B, Warren T, Widjaja F, Dang K, Fahey JW, Cornblatt B, Kinchen JM, Delucchi K, Hendren RL Abstract Background: Children with autism spectrum disorder (ASD) have urinary metabolites suggesting impairments in several pathways, including oxidative stress, inflammation, mitochondrial dysfunction, and gut microbiome alterations. Sulforaphane, a supplement with indirect antioxidant effects that are derived from broccoli sprouts and seeds, was recently shown to lead to improvements in behavior and social responsiveness in children with ASD. We conducted the current open-label study to determine if we could identify changes in urinary metabolites that were associated with clinical improvements with the goal of identifying a potential mechanism of action. Methods: Children and young adults enrolled in a school for children with ASD and related neurodevelopmental disorders were recruited to participate in a 12-week, open-label study of sulforaphane. Fasting urinary metabolites and measures of behavior (Aberrant Behavior Checklist-ABC) and social responsiveness (Social Responsiveness Scale-SRS) were measured at baseline and at the end of the study. Pearson's correlation coefficient was calculated for the pre- to post-intervention change in each of the two clinical scales (ABS and SRS) versus the change in each metabolite. Results: Fifteen children completed the 12-week study. Mean scores on both symptom measures showed improvements (decreases) over the study period, but only the change in the SRS was significant. The ABC improved - 7.1 points (95% CI - 17.4 to 3.2), and the SRS improved - 9.7 points (95% CI - 18.7 to - 0.8). We identified 77 urinary metabolites that were correlated with changes in symptoms, and they clustered into pathways of oxidative stress, amino acid/gut microbiome, neurotransmitters, hormones, and sphingomyelin metabolism. Conclusions: Urinary metabolomics analysis is a useful tool to identify pathways that may be involved in the mechanism of action of treatments targeting abnormal physiology in ASD. Trial registration: This study was prospectively registered at clinicaltrials.gov (NCT02654743) on January 11, 2016. PMID: 29854372 [PubMed - in process]

Related Articles Combining mechanism-based prediction with patient-based profiling for psoriasis metabolomics biomarker discovery. AMIA Annu Symp Proc. 2017;2017:1734-1743 Authors: Wang Q, McCormick TS, Ward NL, Cooper KD, Conic R, Xu R Abstract Psoriasis is a chronic, debilitating skin condition that affects approximately 125 million individuals worldwide. The cause of psoriasis appears multifactorial, and no unified mitigating signal or single antigenic target has been identified to date. Metabolomic studies hold great potential for explaining disease mechanism, facilitating early diagnosis, and identifying potential therapeutic areas. Here, we present an integrated disease metabolomic biomarker discovery strategy that combines mechanism-based biomarker discovery with clinical sample-based metabolomic profiling. We applied this strategy in identifying and understanding metabolite biomarkers for psoriasis. The key innovation of our strategy is a novel mechanism-based metabolite prediction system, mmPredict, which assimilates vast amounts of existing knowledge of diseases and metabolites. mmPredict first constructed a psoriasis-specific mouse mutational phenotype profile. It then constructed phenotype profiles for a total of 259,170 chemicals/metabolites using known chemical genetics and human metabolomic data. Metabolites were then prioritized based on the phenotypic similarities between disease- and metabolites. We evaluated mmPredict using 150 metabolites identified using our in-house metabolome profiling study of psoriasis patient samples. mmPredict found 96 of the 150 metabolites and ranked them highly (recall: 0.64, mean ranking: 8.73%, median ranking: 2.33%, p-value: 4.75E-44). These results show that mmPredict is consistent with, as well as a complement to, traditional human metabolomic profiling studies. We then developed a strategy to combine outputs from both systems and found that the oxidative product of linoleic acid, 13(S)-hydroxy-9Z,11E-octadecadienoic acid (13- HODE), ranked highly by both mmPredict and our in-house experiments. Our integrated analysis indicates that 13- HODE may be a mechanistic link between psoriasis and cardiovascular comorbidities associated with psoriasis. In summary, we developed an integrated metabolomic prediction system that combines both human metabolomic studies and mechanism-based prediction and demonstrated its application in the skin disease psoriasis. Our system is highly general and can be applied to other diseases when patient-based metabolomic profiling data becomes more increasingly available. Data is publicly available at: http://nlp. CASE: edu/public/data/mmPredict_PSO. PMID: 29854244 [PubMed - in process]

Related Articles PROMIS, global analysis of PROtein-Metabolite Interactions using Size separation in Arabidopsis thaliana. J Biol Chem. 2018 May 31;: Authors: Veyel D, Sokolowska EM, Moreno JC, Kierszniowska S, Cichon J, Wojciechowska I, Luzarowski M, Kosmacz M, Szlachetko J, Gorka M, Méret M, Graf A, Meyer EH, Willmitzer L, Skirycz A Abstract Small molecules not only represent cellular building blocks and metabolic intermediates, but also regulatory ligands and signaling molecules that interact with proteins. Although these interactions affect cellular metabolism, growth, and development, they have been largely understudied. Herein, we describe a method, dubbed PROtein-Metabolite Interactions using Size separation (PROMIS) that allows simultaneous, global analysis of endogenous protein-small molecule and of protein‒protein complexes. To this end, a cell-free native lysate from Arabidopsis thaliana cell cultures was fractionated by size-exclusion chromatography, followed by quantitative metabolomic and proteomic analyses. Proteins and small molecules showing similar elution behavior, across protein containing fractions, constituted putative interactors. Applying PROMIS to an A. thaliana extract, we ascertained known protein‒protein (PPIs) and protein-metabolite (PMIs) interactions and reproduced binding between small-molecule protease inhibitors and their respective proteases. More importantly, we present examples of two experimental strategies that exploit the PROMIS dataset to identify novel PMIs. By looking for similar elution behavior of metabolites and enzymes belonging to the same biochemical pathways, we identified putative feedback and feed-forward regulations in pantothenate biosynthesis and the methionine salvage cycle, respectively. By combining PROMIS with an orthogonal affinity purification approach, we identified an interaction between the dipeptide Tyr-Asp and the glycolytic enzyme glyceraldehyde-3-phosphate dehydrogenase. In summary, we present proof of concept for a powerful experimental tool that enables system-wide analysis of PMIs and PPIs across all biological systems. The dataset obtained here comprises nearly 140 metabolites and 5000 proteins, which can be mined for putative interactors. PMID: 29853640 [PubMed - as supplied by publisher]

Related Articles Striking changes in tea metabolites due to elevational effects. Food Chem. 2018 Oct 30;264:334-341 Authors: Kfoury N, Morimoto J, Kern A, Scott ER, Orians CM, Ahmed S, Griffin T, Cash SB, Stepp JR, Xue D, Long C, Robbat A Abstract Climate effects on crop quality at the molecular level are not well-understood. Gas and liquid chromatography-mass spectrometry were used to measure changes of hundreds of compounds in tea at different elevations in Yunnan Province, China. Some increased in concentration while others decreased by 100's of percent. Orthogonal projection to latent structures-discriminant analysis revealed compounds exhibiting analgesic, antianxiety, antibacterial, anticancer, antidepressant, antifungal, anti-inflammatory, antioxidant, anti-stress, and cardioprotective properties statistically (p = 0.003) differentiated high from low elevation tea. Also, sweet, floral, honey-like notes were higher in concentration in the former while the latter displayed grassy, hay-like aroma. In addition, multivariate analysis of variance showed low elevation tea had statistically (p = 0.0062) higher concentrations of caffeine, epicatechin gallate, gallocatechin, and catechin; all bitter compounds. Although volatiles represent a small fraction of the total mass, this is the first comprehensive report illustrating how normal variations in temperature, 5 °C, due to elevational effects impact tea quality. PMID: 29853384 [PubMed - in process]

Related Articles A high-resolution HPLC-QqTOF platform using parallel reaction monitoring for in-depth lipid discovery and rapid profiling. Anal Chim Acta. 2018 Oct 05;1026:87-100 Authors: Yu D, Rupasinghe TWT, Boughton BA, Natera SHA, Hill CB, Tarazona P, Feussner I, Roessner U Abstract Here, we developed a robust lipidomics workflow merging both targeted and untargeted approaches on a single liquid chromatography coupled to quadrupole-time of flight (LC-QqTOF) mass spectrometry platform with parallel reaction monitoring (PRM). PRM assays integrate both untargeted profiling from MS1 scans and targeted profiling obtained from MS/MS data. This workflow enabled the discovery of more than 2300 unidentified features and identification of more than 600 lipid species from 23 lipid classes at the level of fatty acid/long chain base/sterol composition in a barley root extracts. We detected the presence of 142 glycosyl inositol phosphorylceramides (GIPC) with HN(Ac)-HA as the core structure of the polar head, 12 cardiolipins and 17 glucuronosyl diacylglycerols (GlcADG) which have been rarely reported previously for cereal crops. Using a scheduled algorithm with up to 100 precursors multiplexed per duty cycle, the PRM assay was able to achieve a rapid profiling of 291 species based on MS/MS data by a single injection. We used this novel approach to demonstrate the applicability and efficiency of the workflow to study salt stress induced changes in the barley root lipidome. Results show that 221 targeted lipids and 888 unknown features were found to have changed significantly in response to salt stress. This combined targeted and untargeted single workflow approach provides novel applications of lipidomics addressing biological questions. PMID: 29852998 [PubMed - in process]

Related Articles Model selection for within-batch effect correction in UPLC-MS metabolomics using quality control - Support vector regression. Anal Chim Acta. 2018 Oct 05;1026:62-68 Authors: Sánchez-Illana Á, Pérez-Guaita D, Cuesta-García D, Sanjuan-Herráez JD, Vento M, Ruiz-Cerdá JL, Quintás G, Kuligowski J Abstract Ultra performance liquid chromatography - mass spectrometry (UPLC-MS) is increasingly being used for untargeted metabolomics in biomedical research. Complex matrices and a large number of samples per analytical batch lead to gradual changes in the instrumental response (i.e. within-batch effects) that reduce the repeatability and reproducibility and limit the power to detect biological responses. A strategy for within-batch effect correction based on the use of quality control (QC) samples and Support Vector Regression (QC-SVRC) with a radial basis function kernel was recently proposed. QC-SVRC requires the optimization of three hyperparameters that determine the accuracy of the within-batch effects elimination: the tolerance threshold (ε), the penalty term (C) and the kernel width (γ). This work compares three widely used strategies for QC-SVRC hyperparameter optimization (grid search, random search and particle swarm optimization) using a UPLC-MS data set containing 193 urine injections as model example. Results show that QC-SVRC is robust to hyperparameter selection and that a pre-selection of C and ε, followed by optimization of γ is competitive in terms of accuracy, precision and number of function evaluations with full grid analysis, random search and particle swarm optimization. The QC-SVRC optimization procedure can be regarded as a useful non-parametric tool for efficiently complementing alternative approaches such as QC-robust splines correction (RSC). PMID: 29852994 [PubMed - in process]

Related Articles The α-melanocyte stimulating hormone/peroxisome proliferator activated receptor-γ pathway down-regulates proliferation in melanoma cell lines. J Exp Clin Cancer Res. 2017 Oct 11;36(1):142 Authors: Flori E, Rosati E, Cardinali G, Kovacs D, Bellei B, Picardo M, Maresca V Abstract BACKGROUND: The α-Melanocyte Stimulating Hormone (αMSH)/Melanocortin-1 receptor (MC1R) interaction promotes melanogenesis through the cAMP/PKA pathway. The direct induction of this pathway by Forskolin (FSK) is also known to enhance melanocyte proliferation. αMSH acts as a mitogenic agent in melanocytes and its effect on proliferation of melanoma cells is less known. We previously identified the αMSH/Peroxisome Proliferator Activated Receptor (PPARγ) pathway as a new pathway on the B16-F10 mouse melanoma cell line. αMSH induced the translocation of PPARγ into the nucleus as an active transcription factor. This effect was independent of the cAMP/PKA pathway and was mediated by the activation of the PI(4,5)P2/PLC pathway, a pathway which we have described to be triggered by the αMSH-dependent MC1R stimulation. Moreover, in the same study, preliminary experiments showed that mouse melanoma cells responded to αMSH by reducing proliferation and that PPARγ was involved in this effect. Due to its key role in the control of cell proliferation, PPARγ agonists are used in therapeutic models for different forms of cancer, including melanoma. The purpose of this study was: (a) to confirm the different proliferative behavior in response to αMSH in healthy and in melanoma condition; (b) to verify whether the cAMP/PKA pathway and the PLC/PPARγ pathway could exert an antagonistic function in the control of proliferation; (c) to deepen the knowledge of the molecular basis responsible for the down-proliferative response of melanoma cells after exposure to αMSH. METHODS: We employed B16-F10 cell line, a human melanoma cell line (Mel 13) and two primary cultures of human melanocytes (NHM 1 and NHM 2, respectively), all expressing a wild type MC1R and responding to the αMSH in terms of pigmentation. We evaluated cell proliferation through: a) cell counting, b) cell cycle analysis c) protein expression of proliferation modulators (p27, p21, cyclin D1 and cyclin E). RESULTS: The αMSH acted as a mitogenic agent in primary cultures of human melanocytes, whereas it determined a slow down of proliferation in melanoma cell lines. FSK, as an inducer of the cAMP/PKA pathway, reproduced the αMSH mediated effect on proliferation in NHMs but it did not mimic the αMSH effect on proliferation in B16-F10 and Mel 13 melanoma cell lines. Meanwhile, 3 M3-FBS (3 M3), as an inducer of PI(4,5)P2/PLC pathway, reproduced the αMSH proliferative effect. Further experiments, treating melanoma cell lines with αMSH in the presence/absence of GW9662, as an inhibitor of PPARγ, confirmed the key role of this transcription factor in decreasing cell proliferation in response to the hormone exposure. CONCLUSIONS: In both melanoma cell lines, αMSH determined the reduction of proliferation through the PI(4,5)P2/PLC pathway, employing PPARγ as an effector element. These evidence could offer perspectives for new therapeutic approaches for melanoma. PMID: 29020973 [PubMed - indexed for MEDLINE]

19 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 2018/06/01PubMed 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.

19 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 2018/06/01PubMed 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.

25 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 2018/05/31PubMed 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.

25 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 2018/05/31PubMed 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.

31 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 2018/05/29PubMed 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.

Related Articles Plasma N-Glycan Signatures Associate With Features of Inflammatory Bowel Diseases. Gastroenterology. 2018 May 21;: Authors: Clerc F, Novokmet M, Dotz V, Reiding KR, de Haan N, Kammeijer GSM, Dalebout H, Bladergroen MR, Vukovic F, Rapp E, IBD-BIOM consortium, Targan SR, Barron G, Manetti N, Latiano A, McGovern DPB, Annese V, Lauc G, Wuhrer M Abstract BACKGROUND & AIMS: Biomarkers are needed for early detection of Crohn's disease (CD) and ulcerative colitis (UC) or to predict patient outcomes. Glycosylation is a common and complex post-translational modification of proteins that affects their structure and activity. We compared plasma N-glycosylation profiles between patients with CD or UC and healthy individuals (controls). METHODS: We analyzed the total plasma N-glycomes of 2635 patients with inflammatory bowel diseases and 996 controls by mass spectrometry with a linkage-specific sialic acid derivatization technique. Plasma samples were acquired from 2 hospitals in Italy (discovery cohort, 1989 patients with IBD and 570 controls) and 1 medical center in the United States (validation cohort, 646 cases of IBD and 426 controls). Sixty-three glycoforms met our criteria for relative quantification and were extracted from the raw data with the software MassyTools. Common features shared by the glycan compositions were combined in 78 derived traits, including the number of antennae of complex-type glycans and levels of fucosylation, bisection, galactosylation, and sialylation. Associations of plasma N-glycomes with age, sex, CD, UC and IBD-related parameters such as disease location, surgery and medication, level of C-reactive protein, and sedimentation rate were tested by linear and logistic regression. RESULTS: Plasma samples from patients with IBD had a higher abundance of large-size glycans compared with controls, a decreased relative abundance of hybrid and high-mannose structures, lower fucosylation, lower galactosylation, and higher sialylation (alpha2,3- and alpha2,6-linked). We could discriminate plasma from patients with CD from that of patients with UC based on higher bisection, lower galactosylation and higher sialylation (alpha2,3-linked). Glycosylation patterns associated with disease location and progression, the need for a more potent medication, and surgery. These results were replicated in a large independent cohort. CONCLUSIONS: We performed high-throughput analysis to compare total plasma N-glycomes of individuals with vs. without IBD and to identify patterns associated with disease features and the need for treatment. These profiles might be used in diagnosis and for predicting patients' response to treatment. PMID: 29792883 [PubMed - as supplied by publisher]

Related Articles Metabolomics Reveals the Molecular Mechanisms of Copper Induced Cucumber Leaf (Cucumis sativus) Senescence. Environ Sci Technol. 2018 May 24;: Authors: Zhao L, Huang Y, Paglia K, Vaniya A, Wancewicz B, Keller AA Abstract Excess copper may disturb plant photosynthesis and induce leaf senescence. The underlying toxicity mechanism is not well understood. Here, 3-week-old cucumber plants were foliar exposed to different copper concentrations (10, 100 and 500 mg/L) for a final dose of 0.21, 2.1 and 10 mg/plant, using CuSO4 as the Cu ion source for seven days, three times per day. Metabolomics quantified 149 primary and 79 secondary metabolites. A number of intermediates of the tricarboxylic acid (TCA) cycle were significantly down-regulated 1.4-2.4 fold, indicating a perturbed carbohydrate metabolism. Ascorbate and aldarate metabolism and shikimate-phenylpropanoid biosynthesis (antioxidant and defense related pathways) were perturbed by excess copper. These metabolic responses occur even at the lowest copper dose considered although no phenotype changes were observed at this dose. High copper dose resulted in a 2-fold increase in phytol, a degradation product of chlorophyll. Polyphenol metabolomics revealed that some flavonoids were down-regulated, while the nonflavonoid 4-hydroxycinnamic acid and trans-2-hydroxycinnamic acid were significantly up-regulated 4- and 26-fold compared to the control. This study enhances current understanding of copper toxicity to plants, and demonstrates that metabolomics profiling provides a more comprehensive view of plant responses to stressors, which can be applied to other plant species and contaminants. PMID: 29792813 [PubMed - as supplied by publisher]

Related Articles Potential biotechnological capabilities of cultivable mycobiota from carwash effluents. Microbiologyopen. 2017 Oct;6(5): Authors: Sibanda T, Selvarajan R, Tekere M, Nyoni H, Meddows-Taylor S Abstract Urban life has created man-made extreme environments like carwashes. These environments have, however, not been sufficiently explored for mycobiota that can be sources of biotechnologically useful products, as has been the case with natural extreme environments. Using a combination of culture and molecular techniques, fungi from carwash effluents was characterized for production of lipase and cellulase enzymes, nonpolar and polar biotechnologically relevant secondary metabolites and hydrocarbon utilization. The isolated fungal strains belonged to the genera Alternaria, Cladosporium, Penicillium, Peyronellaea, Rhizopus, Spegazzinia, Trichoderma, Ulocladium and Yarrowia. Sixty-six percent (66%) of the fungal isolates were found to be able to metabolize naphthalene and benzanthracene, showing potential for application in bioremediation of hydrocarbon polluted sites. Lipase production by the isolates Penicillium sp. BPS3 (2.61 U/ml), Trichoderma sp. BPS9 (2.01 U/ml), Rhizopus sp. CAL1 (2.05 U/ml), Penicillium sp. PCW1 (2.99 U/ml) and Penicillium sp. SAS1 (2.16 U/ml) compared well with previously recorded lipase production levels by other fungi. The highest producers of cellulase were Penicillium sp. SAS1 (12.10 U/ml), Peyronella sp. CAW5 (4.49 U/ml) and Cladosporium sp. SAS3 (4.07 U/ml), although these activities were lower than previously reported levels. GC-MS analysis of the fungal secondary metabolites resulted in identification of 572 compounds, including azulene, methanamine, N-pentylidene, metoclopramide, and mepivacaine while compounds determined by UHPLC-MS included 10-undecen-1-ol, piquerol A, 10-undecyn-1-ol, cyclo(leucylprolyl) and rac-etomidate. These compounds were previously determined to have various activities including anticancer, antibacterial, antifungal, antihypertensive, antidiabetic and anti-inflammatory properties. The study demonstrated that fungi from carwash effluents are natural sources of some biotechnologically important products. PMID: 28714266 [PubMed - indexed for MEDLINE]

Related Articles Brachiaria Grasses (Brachiaria spp.) harbor a diverse bacterial community with multiple attributes beneficial to plant growth and development. Microbiologyopen. 2017 Oct;6(5): Authors: Mutai C, Njuguna J, Ghimire S Abstract Endophytic and plant-associated bacteria were isolated from plants and rhizoplane soil of naturally grown Brachiaria grasses at International Livestock Research Institute in Nairobi, Kenya. Eighty-four bacterial strains were isolated from leaf tissues, root tissues, and rhizoplane soil on nutrient agar and 869 media. All bacterial strains were identified to the lowest possible taxonomic unit using 16S rDNA primers and were characterized for the production of Indole-3-acetic acid, hydrogen cyanide, and ACC deaminase; phosphate solubilization; siderophore production; antifungal properties; and plant biomass production. The 16S rDNA-based identification grouped these 84 bacterial strains into 3 phyla, 5 classes, 8 orders, 12 families, 16 genera, and 50 unique taxa. The four most frequently isolated genera were Pseudomonas (23), Pantoea (17), Acinetobacter (9), and Enterobacter (8). The functional characterization of these strains revealed that 41 of 84 strains had a minimum of three plant beneficial properties. Inoculation of maize seedlings with Acinetobacter spp., Microbacterium spp., Pectobacterium spp., Pseudomonas spp., and Enterobacter spp. showed positive effects on seedling biomass production. The ability of Brachiaria grasses to host genetically diverse bacteria, many of them with multiple plant growth-promoting attributes, might have contributed to high biomass production and adaptation of Brachiaria grasses to drought and low fertility soils. PMID: 28639414 [PubMed - indexed for MEDLINE]

Related Articles Minimal Information About an Immuno-Peptidomics Experiment (MIAIPE). Proteomics. 2018 May 23;:e1800110 Authors: Lill JR, van Veelen PA, Tenzer S, Admon A, Caron E, Elias J, Heck AJR, Marcilla M, Marino F, Müller M, Peters B, Purcell A, Sette A, Sturm T, Ternette N, Vizcaíno JA, Bassani-Sternberg M Abstract Minimal Information about an Immuno-Peptidomics Experiment (MIAIPE) is an initiative of the members of the Human Immuno-Peptidome Project (HIPP), an international program organized by the Human Proteome Organization (HUPO). The aim of the MIAIPE guidelines is to deliver technical guidelines representing the minimal information required to sufficiently support the evaluation and interpretation of immunopeptidomics experiments. The MIAIPE document has been designed to report essential information about sample preparation, mass spectrometric measurement and associated mass spectrometry (MS)-related bioinformatics aspects that are unique to immunopeptidomics and may not be covered by the general proteomics MIAPE (Minimal Information About a Proteomics Experiment) guidelines. This article is protected by copyright. All rights reserved. PMID: 29791771 [PubMed - as supplied by publisher]