Publications by authors named "Maryam Goudarzi"

26 Publications

  • Page 1 of 1

Erratum for Quinn et al., "Bridging the Gap between Analytical and Microbial Sciences in Microbiome Research".

mSystems 2021 Oct 5;6(5):e0117121. Epub 2021 Oct 5.

Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, USA.

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http://dx.doi.org/10.1128/mSystems.01171-21DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8547442PMC
October 2021

Bridging the Gap between Analytical and Microbial Sciences in Microbiome Research.

mSystems 2021 Oct 14;6(5):e0058521. Epub 2021 Sep 14.

Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, USA.

Metabolites from the microbiome influence human, animal, and environmental health, but the diversity and functional roles of these compounds have only begun to be elucidated. Comprehensively characterizing these molecules are significant challenges, as it requires expertise in analytical methods, such as mass spectrometry and nuclear magnetic resonance spectroscopy, skills that not many traditional microbiologists or microbial ecologists possess. This creates a gap between microbiome scientists that want to understand the role of microbial metabolites in microbiome systems and the skills required to generate and interpret complex metabolomics data sets. To bridge this gap, microbiome scientists should engage analytical chemists to best understand the underlying chemical principles of the data. Conversely, analytical scientists are encouraged to engage with microbiome scientists to better understand the biological questions being asked with metabolomics and to best communicate its intricacies. Better communication across the chemistry/biology disciplines will further reveal the "dark matter" within microbiomes that maintain healthy humans and environments.
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http://dx.doi.org/10.1128/mSystems.00585-21DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8547465PMC
October 2021

Metabolic Profiling of Skeletal Muscle During Ex-Vivo Normothermic Limb Perfusion.

Mil Med 2021 01;186(Suppl 1):358-363

Cleveland Clinic Department of Plastic Surgery, Cleveland, OH 44195, USA.

Introduction: Ex vivo normothermic limb perfusion (EVNLP) provides several advantages for the preservation of limbs following amputation: the ability to maintain oxygenation and temperature of the limb close to physiological values, a perfusion solution providing all necessary nutrients at optimal concentrations, and the ability to maintain physiological pH and electrolytes. However, EVNLP cannot preserve the organ viability infinitely. We identified evidence of mitochondrial injury (swelling, elongation, and membrane disruption) after 24 hours of EVNLP of human upper extremities. The goal of this study was to identify metabolic derangements in the skeletal muscle during EVNLP.

Materials And Methods: Fourteen human upper extremities were procured from organ donors after family consent. Seven limbs underwent EVNLP for an average of 41.6 ± 9.4 hours, and seven contralateral limbs were preserved at 4°C for the same amount of time. Muscle biopsies were performed at 24 hours of perfusion, both from the EVNLP and control limbs. Perturbations in the metabolic profiles of the muscle during EVNLP were determined via untargeted liquid chromatography-mass spectrometry (MS) operated in positive and negative electrospray ionization modes, over a mass range of 50 to 750 Da. The data were deconvoluted using the XCMS software and further statistically analyzed using the in-house statistical package, MetaboLyzer. Putative identification of metabolites using exact mass within ±7 ppm mass error and MS/MS spectral matching to the mzCloud spectral library were performed via Compound Discoverer v.2.1 (Thermo Scientific, Fremont, CA, USA). We further validated the identity of candidate metabolites by matching the fragmentation pattern of these metabolites to those of their reference pure chemicals. A nonparametric Mann-Whitney U-test was used to compare EVNLP and control group spectral features. Differences were considered significantly different when P-value < 0.05.

Results: We detected over 13,000 spectral features of which 58 met the significance criteria with biologically relevant putative identifications. Furthermore we were able to confirm the identities of the ions taurine (P-value: 0.002) and tryptophan (P-value: 0.002), which were among the most significantly perturbed ions at 24 hours between the experimental and control groups. Metabolites belonging to the following pathways were the most perturbed at 24 hours: neuroactive ligand-receptor interaction (P-values: 0.031 and 0.036) and amino acid metabolism, including tyrosine and tryptophan metabolism (P-values: 0.015, 0.002, and 0.017). Taurine abundance decreased and tryptophan abundance increased at 24 hours. Other metabolites also identified at 24 hours included phenylalanine, xanthosine, and citric acid (P-values: 0.002, 0.002, and 0.0152).

Discussion: This study showed presence of active metabolism during EVNLP and metabolic derangement toward the end of perfusion, which correlated with detection of altered mitochondrial structure, swelling, and elongation.
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http://dx.doi.org/10.1093/milmed/usaa268DOI Listing
January 2021

Serum Metabolomic Alterations Associated with Cesium-137 Internal Emitter Delivered in Various Dose Rates.

Metabolites 2020 Jun 30;10(7). Epub 2020 Jun 30.

Department of Oncology, Georgetown University Medical Center, Washington, DC 20007, USA.

Our laboratory and others have use radiation metabolomics to assess responses in order to develop biomarkers reflecting exposure and level of injury. To expand the types of exposure and compare to previously published results, metabolomic analysis has been carried out using serum samples from mice exposed to Cs internal emitters. Animals were injected intraperitoneally with CsCl solutions of varying radioactivity, and the absorbed doses were calculated. To determine the dose rate effect, serum samples were collected at 2, 3, 5, 7, and 14 days after injection. Based on the time for each group receiving the cumulative dose of 4 Gy, the dose rate for each group was determined. The dose rates analyzed were 0.16 Gy/day (low), 0.69 Gy/day (medium), and 1.25 Gy/day (high). The results indicated that at a cumulative dose of 4 Gy, the low dose rate group had the least number of statistically significantly differential spectral features. Some identified metabolites showed common changes for different dose rates. For example, significantly altered levels of oleamide and sphingosine 1-phosphate were seen in all three groups. On the other hand, the intensity of three amino acids, Isoleucine, Phenylalanine and Arginine, significantly decreased only in the medium dose rate group. These findings have the potential to be used in assessing the exposure and the biological effects of internal emitters.
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http://dx.doi.org/10.3390/metabo10070270DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7407308PMC
June 2020

The ABRF Metabolomics Research Group 2016 Exploratory Study: Investigation of Data Analysis Methods for Untargeted Metabolomics.

Metabolites 2020 Mar 27;10(4). Epub 2020 Mar 27.

Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC 20057, USA.

Lack of standardized applications of bioinformatics and statistical approaches for pre- and postprocessing of global metabolomic profiling data sets collected using high-resolution mass spectrometry platforms remains an inadequately addressed issue in the field. Several publications now recognize that data analysis outcome variability is caused by different data treatment approaches. Yet, there is a lack of interlaboratory reproducibility studies that have looked at the contribution of data analysis techniques toward variability/overlap of results. The goal of our study was to identify the contribution of data pre- and postprocessing methods on metabolomics analysis results. We performed urinary metabolomics from samples obtained from mice exposed to 5 Gray of external beam gamma rays and those exposed to sham irradiation (control group). The data files were made available to study participants for comparative analysis using commonly used bioinformatics and/or biostatistics approaches in their laboratories. The participants were asked to report back the top 50 metabolites/features contributing significantly to the group differences. Herein we describe the outcome of this study which suggests that data preprocessing is critical in defining the outcome of untargeted metabolomic studies.
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http://dx.doi.org/10.3390/metabo10040128DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7241086PMC
March 2020

Disparate Metabolomics Data Reassembler: A Novel Algorithm for Agglomerating Incongruent LC-MS Metabolomics Datasets.

Anal Chem 2020 04 10;92(7):5231-5239. Epub 2020 Mar 10.

Mass Spectrometry Data Center, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, Maryland 20899-8632, United States.

In the past decade, the field of LC-MS-based metabolomics has transformed from an obscure specialty into a major "-omics" platform for studying metabolic processes and biomolecular characterization. However, as a whole the field is still very fractured, as the nature of the instrumentation and the information produced by the platform essentially creates incompatible "islands" of datasets. This lack of data coherency results in the inability to accumulate a critical mass of metabolomics data that has enabled other -omics platforms to make impactful discoveries and meaningful advances. As such, we have developed a novel algorithm, called Disparate Metabolomics Data Reassembler (DIMEDR), which attempts to bridge the inconsistencies between incongruent LC-MS metabolomics datasets of the same biological sample type. A single "primary" dataset is postprocessed via traditional means of peak identification, alignment, and grouping. DIMEDR utilizes this primary dataset as a progenitor template by which data from subsequent disparate datasets are reassembled and integrated into a unified framework that maximizes spectral feature similarity across all samples. This is accomplished by a novel procedure for universal retention time correction and comparison via identification of ubiquitous features in the initial primary dataset, which are subsequently utilized as endogenous internal standards during integration. For demonstration purposes, two human and two mouse urine metabolomics datasets from four unrelated studies acquired over 4 years were unified via DIMEDR, which enabled meaningful analysis across otherwise incomparable and unrelated datasets.
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http://dx.doi.org/10.1021/acs.analchem.9b05763DOI Listing
April 2020

Fabric Phase Sorptive Extraction-A Metabolomic Preprocessing Approach for Ionizing Radiation Exposure Assessment.

J Proteome Res 2019 08 22;18(8):3020-3031. Epub 2019 May 22.

Center for Applied NanoBiosience and Medicine , University of Arizona , 475 North Fifth Street , Phoenix , Arizona 85004 , United States.

The modern application of mass spectrometry-based metabolomics to the field of radiation assessment and biodosimetry has allowed for the development of prompt biomarker screenings for radiation exposure. Our previous work on radiation assessment, in easily accessible biofluids (such as urine, blood, saliva), has revealed unique metabolic perturbations in response to radiation quality, dose, and dose rate. Nevertheless, the employment of swift injury assessment in the case of a radiological disaster still remains a challenge as current sample processing can be time consuming and cause sample degradation. To address these concerns, we report a metabolomics workflow using a mass spectrometry-compatible fabric phase sorptive extraction (FPSE) technique. FPSE employs a matrix coated with sol-gel poly(caprolactone--dimethylsiloxane--caprolactone) that binds both polar and nonpolar metabolites in whole blood, eliminating serum processing steps. We confirm that the FPSE preparation technique combined with liquid chromatography-mass spectrometry can distinguish radiation exposure markers such as taurine, carnitine, arachidonic acid, α-linolenic acid, and oleic acid found 24 h after 8 Gy irradiation. We also note the effect of different membrane fibers on both metabolite extraction efficiency and the temporal stabilization of metabolites in whole blood at room temperature. These findings suggest that the FPSE approach could work in future technology to triage irradiated individuals accurately, via biomarker screening, by providing a novel method to stabilize biofluids between collection and sample analysis.
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http://dx.doi.org/10.1021/acs.jproteome.9b00142DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7437658PMC
August 2019

Metabolomic alterations associated with Behçet's disease.

Arthritis Res Ther 2018 09 24;20(1):214. Epub 2018 Sep 24.

Georgetown University Medical Center, Georgetown University, Washington, DC, USA.

Background: The diagnosis of Behçet's disease (BD) remains challenging due to the lack of diagnostic biomarkers. This study aims to identify potential serum metabolites associated with BD and its disease activity.

Methods: Medical records and serum samples of 24 pretreated BD patients, 12 post-treated BD patients, and age-matched healthy controls (HC) were collected for metabolomics and lipidomics profiling using UPLC-QTOF-MS and UPLC-QTOF-MS approaches. Additionally, serum samples from an independent cohort of BD patients, disease controls including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), Takayasu's arteritis (TA), Crohn's disease (CD) patients, and HC were collected for further validation of two potential biomarkers using UPLC-QTOFMS analysis.

Results: Unsupervised principal component analysis (PCA) showed a clear separation of metabolomics profiles of BD patients from HC. Statistical analysis of the data revealed differential metabolites between BD patients and HC. The serum levels of some phosphatidylcholines (PCs) were found to be significantly lower in BD patients, while the levels of several polyunsaturated fatty acids (PUFAs) were increased markedly in the BD group compared with HC. Furthermore, the serum level of two omega-6 PUFAs, linoleic acid (LA) and arachidonic acid (AA), were dramatically decreased in patients with remission. A validation cohort confirmed that the serum LA and AA levels in BD patients were significantly higher than those in HC and patients with RA, SLE, TA, and CD. In addition, receiver operating characteristic (ROC) analysis indicated good sensitivity and specificity.

Conclusions: The serum metabolomics profiles in BD patients are altered. Serum LA and AA are promising diagnostic biomarkers for BD.
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http://dx.doi.org/10.1186/s13075-018-1712-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6154820PMC
September 2018

A Disease-Associated Microbial and Metabolomics State in Relatives of Pediatric Inflammatory Bowel Disease Patients.

Cell Mol Gastroenterol Hepatol 2016 Nov 2;2(6):750-766. Epub 2016 Jul 2.

Susan and Leonard Feinstein Inflammatory Bowel Disease Center, Department of Pediatrics, Icahn School of Medicine, Mount Sinai, New York.

Background & Aims: Microbes may increase susceptibility to inflammatory bowel disease (IBD) by producing bioactive metabolites that affect immune activity and epithelial function. We undertook a family based study to identify microbial and metabolic features of IBD that may represent a predisease risk state when found in healthy first-degree relatives.

Methods: Twenty-one families with pediatric IBD were recruited, comprising 26 Crohn's disease patients in clinical remission, 10 ulcerative colitis patients in clinical remission, and 54 healthy siblings/parents. Fecal samples were collected for 16S ribosomal RNA gene sequencing, untargeted liquid chromatography-mass spectrometry metabolomics, and calprotectin measurement. Individuals were grouped into microbial and metabolomics states using Dirichlet multinomial models. Multivariate models were used to identify microbes and metabolites associated with these states.

Results: Individuals were classified into 2 microbial community types. One was associated with IBD but irrespective of disease status, had lower microbial diversity, and characteristic shifts in microbial composition including increased Enterobacteriaceae, consistent with dysbiosis. This microbial community type was associated similarly with IBD and reduced microbial diversity in an independent pediatric cohort. Individuals also clustered bioinformatically into 2 subsets with shared fecal metabolomics signatures. One metabotype was associated with IBD and was characterized by increased bile acids, taurine, and tryptophan. The IBD-associated microbial and metabolomics states were highly correlated, suggesting that they represented an integrated ecosystem. Healthy relatives with the IBD-associated microbial community type had an increased incidence of elevated fecal calprotectin.

Conclusions: Healthy first-degree relatives can have dysbiosis associated with an altered intestinal metabolome that may signify a predisease microbial susceptibility state or subclinical inflammation. Longitudinal prospective studies are required to determine whether these individuals have a clinically significant increased risk for developing IBD.
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http://dx.doi.org/10.1016/j.jcmgh.2016.06.004DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5247316PMC
November 2016

Microbial, metabolomic, and immunologic dynamics in a relapsing genetic mouse model of colitis induced by T-synthase deficiency.

Gut Microbes 2017 01 22;8(1):1-16. Epub 2016 Nov 22.

b Department of Pathology , University of California Los Angeles , Los Angeles , California , USA.

Intestinal dysbiosis is thought to confer susceptibility to inflammatory bowel disease (IBD), but it is unknown whether dynamic changes in the microbiome contribute to fluctuations in disease activity. We explored this question using mice with intestine-specific deletion of C1galt1 (also known as T-synthase) (Tsyn mice). These mice develop spontaneous microbiota-dependent colitis with a remitting/relapsing course due to loss of mucin core-1 derived O-glycans. 16S rRNA sequencing and untargeted metabolomics demonstrated age-specific perturbations in the intestinal microbiome and metabolome of Tsyn mice compare with littermate controls at weeks 3 (disease onset), 5 (during remission), and 9 (after relapse). Colitis remission corresponded to increased levels of FoxP3+RORγt+CD4+ T cells in the colonic lamina propria that were positively correlated with operational taxonomic units (OTUs) in the S24-7 family and negatively correlated with OTUs in the Clostridiales order. Relapse was characterized by marked expansion of FoxP3-RORγt+CD4+ T cells expressing IFNγ and IL17A, which were associated with Clostridiales OTUs distinct from those negatively correlated with FoxP3+RORγt+CD4+ T cells. Our findings suggest that colitis remission and relapse in the Tsyn model may reflect alterations in the microbiome due to reduced core-1 O-glycosylation that shift the balance of regulatory and pro-inflammatory T cell subsets. We investigated whether genetic variation in C1galt1 correlated with the microbiome in a cohort of 78 Crohn's disease patients and 101 healthy controls. Polymorphisms near C1galt1 (rs10486157) and its molecular chaperone, Cosmc (rs4825729), were associated with altered composition of the colonic mucosal microbiota, supporting the relevance of core-1 O-glycosylation to host regulation of the microbiome.
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http://dx.doi.org/10.1080/19490976.2016.1257469DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5341916PMC
January 2017

Regulation of Cytochrome P450 2B10 (CYP2B10) Expression in Liver by Peroxisome Proliferator-activated Receptor-β/δ Modulation of SP1 Promoter Occupancy.

J Biol Chem 2016 Nov 20;291(48):25255-25263. Epub 2016 Oct 20.

From the Department of Veterinary and Biomedical Sciences and the Center of Molecular Toxicology and Carcinogenesis, Pennsylvania State University, University Park, Pennsylvania 16802,

Alcoholic liver disease is a pathological condition caused by overconsumption of alcohol. Because of the high morbidity and mortality associated with this disease, there remains a need to elucidate the molecular mechanisms underlying its etiology and to develop new treatments. Because peroxisome proliferator-activated receptor-β/δ (PPARβ/δ) modulates ethanol-induced hepatic effects, the present study examined alterations in gene expression that may contribute to this disease. Chronic ethanol treatment causes increased hepatic CYP2B10 expression inPparβ/δ mice but not in Pparβ/δ mice. Nuclear and cytosolic localization of the constitutive androstane receptor (CAR), a transcription factor known to regulate Cyp2b10 expression, was not different between genotypes. PPARγ co-activator 1α, a co-activator of both CAR and PPARβ/δ, was up-regulated in Pparβ/δ liver following ethanol exposure, but not in Pparβ/δ liver. Functional mapping of the Cyp2b10 promoter and ChIP assays revealed that PPARβ/δ-dependent modulation of SP1 promoter occupancy up-regulated Cyp2b10 expression in response to ethanol. These results suggest that PPARβ/δ regulates Cyp2b10 expression indirectly by modulating SP1 and PPARγ co-activator 1α expression and/or activity independent of CAR activity. Ligand activation of PPARβ/δ attenuates ethanol-induced Cyp2b10 expression in Pparβ/δ liver but not in Pparβ/δ liver. Strikingly, Cyp2b10 suppression by ligand activation of PPARβ/δ following ethanol treatment occurred in hepatocytes and was mediated by paracrine signaling from Kupffer cells. Combined, results from the present study demonstrate a novel regulatory role of PPARβ/δ in modulating CYP2B10 that may contribute to the etiology of alcoholic liver disease.
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http://dx.doi.org/10.1074/jbc.M116.755447DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5122791PMC
November 2016

An Integrated Multi-Omic Approach to Assess Radiation Injury on the Host-Microbiome Axis.

Radiat Res 2016 09 11;186(3):219-34. Epub 2016 Aug 11.

a   Department of Biochemistry and Molecular and Cellular Biology and.

Medical responders to radiological and nuclear disasters currently lack sufficient high-throughput and minimally invasive biodosimetry tools to assess exposure and injury in the affected populations. For this reason, we have focused on developing robust radiation exposure biomarkers in easily accessible biofluids such as urine, serum and feces. While we have previously reported on urine and serum biomarkers, here we assessed perturbations in the fecal metabolome resulting from exposure to external X radiation in vivo. The gastrointestinal (GI) system is of particular importance in radiation biodosimetry due to its constant cell renewal and sensitivity to radiation-induced injury. While the clinical GI symptoms such as pain, bloating, nausea, vomiting and diarrhea are manifested after radiation exposure, no reliable bioindicator has been identified for radiation-induced gastrointestinal injuries. To this end, we focused on determining a fecal metabolomic signature in X-ray irradiated mice. There is overwhelming evidence that the gut microbiota play an essential role in gut homeostasis and overall health. Because the fecal metabolome is tightly correlated with the composition and diversity of the microorganism in the gut, we also performed fecal 16S rRNA sequencing analysis to determine the changes in the microbial composition postirradiation. We used in-house bioinformatics tools to integrate the 16S rRNA sequencing and metabolomic data, and to elucidate the gut integrated ecosystem and its deviations from a stable host-microbiome state that result from irradiation. The 16S rRNA sequencing results indicated that radiation caused remarkable alterations of the microbiome in feces at the family level. Increased abundance of common members of Lactobacillaceae and Staphylococcaceae families, and decreased abundances of Lachnospiraceae, Ruminococcaceae and Clostridiaceae families were found after 5 and 12 Gy irradiation. The metabolomic data revealed statistically significant changes in the microbial-derived products such as pipecolic acid, glutaconic acid, urobilinogen and homogentisic acid. In addition, significant changes were detected in bile acids such as taurocholic acid and 12-ketodeoxycholic acid. These changes may be associated with the observed shifts in the abundance of intestinal microbes, such as R. gnavus , which can transform bile acids.
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http://dx.doi.org/10.1667/RR14306.1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5304359PMC
September 2016

Quantitative Metabolomic Analysis of Urinary Citrulline and Calcitroic Acid in Mice after Exposure to Various Types of Ionizing Radiation.

Int J Mol Sci 2016 May 20;17(5). Epub 2016 May 20.

Department of Biochemistry and Molecular & Cellular Biology, Georgetown University, 3970 Reservoir Road NW, Washington, DC 20057, USA.

With the safety of existing nuclear power plants being brought into question after the Fukushima disaster and the increased level of concern over terrorism-sponsored use of improvised nuclear devices, it is more crucial to develop well-defined radiation injury markers in easily accessible biofluids to help emergency-responders with injury assessment during patient triage. Here, we focused on utilizing ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) to identify and quantitate the unique changes in the urinary excretion of two metabolite markers, calcitroic acid and citrulline, in mice induced by different forms of irradiation; external γ irradiation at a low dose rate (LDR) of 3.0 mGy/min and a high dose rate (HDR) of 1.1 Gy/min, and internal exposure to Cesium-137 ((137)Cs) and Strontium-90 ((90)Sr). The multiple reaction monitoring analysis showed that, while exposure to (137)Cs and (90)Sr induced a statistically significant and persistent decrease, similar doses of external γ beam at the HDR had the opposite effect, and the LDR had no effect on the urinary levels of these two metabolites. This suggests that the source of exposure and the dose rate strongly modulate the in vivo metabolomic injury responses, which may have utility in clinical biodosimetry assays for the assessment of exposure in an affected population. This study complements our previous investigations into the metabolomic profile of urine from mice internally exposed to (90)Sr and (137)Cs and to external γ beam radiation.
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http://dx.doi.org/10.3390/ijms17050782DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4881599PMC
May 2016

Serum Dyslipidemia Is Induced by Internal Exposure to Strontium-90 in Mice, Lipidomic Profiling Using a Data-Independent Liquid Chromatography-Mass Spectrometry Approach.

J Proteome Res 2015 Sep 18;14(9):4039-49. Epub 2015 Aug 18.

Department of Biochemistry and Molecular & Cellular Biology, Georgetown University , 3970 Reservoir Rd. NW, Washington, D.C. 20057, United States.

Despite considerable research into the environmental risks and biological effects of exposure to external beam γ rays, incorporation of radionuclides has largely been understudied. This dosimetry and exposure risk assessment is challenging for first responders in the field during a nuclear or radiological event. Therefore, we have developed a workflow for assessing injury responses in easily obtainable biofluids, such as urine and serum, as the result of exposure to internal emitters cesium-137 ((137)Cs) and strontium-90 ((90)Sr) in mice. Here we report on the results of the untargeted lipidomic profiling of serum from mice exposed to (90)Sr. We also compared these results to those from previously published (137)Cs exposure to determine any differences in cellular responses based on exposure type. The results of this study conclude that there is a gross increase in the serum abundance of triacylglycerides and cholesterol esters, while phostaphatidylcholines and lysophosphatidylcholines displayed decreases in their serum levels postexposure at study days 4, 7, 9, 25, and 30, with corresponding average cumulative skeleton doses ranging from 1.2 ± 0.1 to 5.2 ± 0.73 Gy. The results show significant perturbations in serum lipidome as early as 2 days postexposure persisting until the end of the study (day 30).
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http://dx.doi.org/10.1021/acs.jproteome.5b00576DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5327919PMC
September 2015

The effects of stress inoculation training on perceived stress in pregnant women.

J Health Psychol 2016 12 6;21(12):2977-2982. Epub 2015 Jul 6.

Arak University, Iran.

A total of 64 pregnant women were assigned into two groups of cases and controls. Both groups filled out the Perceived Stress Scale at pre-test. Cognitive-behavioral coping skill training was delivered to the case group. After the end of the intervention, both groups completed the same scale again. The results showed that the mean perceived stress of the cases and controls was 27.77 ± 6.033 and 18.97 ± 3.268, respectively (p = 0.001). Therefore, midwives are recommended to plan educational interventions to decrease perceived stress in pregnant women.
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http://dx.doi.org/10.1177/1359105315589800DOI Listing
December 2016

A Comprehensive Metabolomic Investigation in Urine of Mice Exposed to Strontium-90.

Radiat Res 2015 Jun 26;183(6):665-74. Epub 2015 May 26.

a  Biochemistry and Molecular and Cellular Biology, Georgetown University, Washington D.C.;

Internal emitters such as Strontium-90 ((90)Sr) pose a substantial health risk during and immediately after a nuclear disaster or detonation of an improvised device. The environmental persistency and potency of (90)Sr calls for urgent development of high-throughput tests to establish levels of exposure and to help triage potentially exposed individuals who were in the immediate area of the disaster. In response to these concerns, our team focused on developing a robust metabolomic profile for (90)Sr exposure in urine using a mouse model. The sensitivity of modern time-of-flight mass spectrometry (TOFMS) combined with the separation power of ultra performance liquid chromatography (UPLC) was used to determine perturbations in the urinary metabolome of mice exposed to (90)Sr. The recently developed statistical suite, MetaboLyzer, was used to explore the mass spectrometry data. The results indicated a significant change in the urinary abundances of metabolites pertaining to butanoate metabolism, vitamin B metabolism, glutamate and fatty acid oxidation. All of these pathways are either directly or indirectly connected to the central energy production pathway, the tricarboxylic acid (TCA) cycle. To our knowledge, this is the first in vivo metabolomics to evaluate the effects of exposure to (90)Sr using the easily accessible biofluid, urine.
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http://dx.doi.org/10.1667/RR14011.1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5320572PMC
June 2015

Selective paired ion contrast analysis: a novel algorithm for analyzing postprocessed LC-MS metabolomics data possessing high experimental noise.

Anal Chem 2015 Mar 26;87(6):3177-86. Epub 2015 Feb 26.

§Center of Excellence in Genomic Medicine Research (CEGMR), King Abdulaziz University, Jeddah 22254, Saudi Arabia.

One of the consequences in analyzing biological data from noisy sources, such as human subjects, is the sheer variability of experimentally irrelevant factors that cannot be controlled for. This holds true especially in metabolomics, the global study of small molecules in a particular system. While metabolomics can offer deep quantitative insight into the metabolome via easy-to-acquire biofluid samples such as urine and blood, the aforementioned confounding factors can easily overwhelm attempts to extract relevant information. This can mar potentially crucial applications such as biomarker discovery. As such, a new algorithm, called Selective Paired Ion Contrast (SPICA), has been developed with the intent of extracting potentially biologically relevant information from the noisiest of metabolomic data sets. The basic idea of SPICA is built upon redefining the fundamental unit of statistical analysis. Whereas the vast majority of algorithms analyze metabolomics data on a single-ion basis, SPICA relies on analyzing ion-pairs. A standard metabolomic data set is reinterpreted by exhaustively considering all possible ion-pair combinations. Statistical comparisons between sample groups are made only by analyzing the differences in these pairs, which may be crucial in situations where no single metabolite can be used for normalization. With SPICA, human urine data sets from patients undergoing total body irradiation (TBI) and from a colorectal cancer (CRC) relapse study were analyzed in a statistically rigorous manner not possible with conventional methods. In the TBI study, 3530 statistically significant ion-pairs were identified, from which numerous putative radiation specific metabolite-pair biomarkers that mapped to potentially perturbed metabolic pathways were elucidated. In the CRC study, SPICA identified 6461 statistically significant ion-pairs, several of which putatively mapped to folic acid biosynthesis, a key pathway in colorectal cancer. Utilizing support vector machines (SVMs), SPICA was also able to unequivocally outperform binary classifiers built from classical single-ion feature based SVMs.
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http://dx.doi.org/10.1021/ac504012aDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4519008PMC
March 2015

Metabolomic and lipidomic analysis of serum from mice exposed to an internal emitter, cesium-137, using a shotgun LC-MS(E) approach.

J Proteome Res 2015 Jan 5;14(1):374-84. Epub 2014 Nov 5.

Biochemistry and Molecular and Cellular Biology, Georgetown University , 3970 Reservoir Road NW, Washington, DC 20057, United States.

In this study ultra performance liquid chromatography (UPLC) coupled to time-of-flight mass spectrometry in the MS(E) mode was used for rapid and comprehensive analysis of metabolites in the serum of mice exposed to internal exposure by Cesium-137 ((137)Cs). The effects of exposure to (137)Cs were studied at several time points after injection of (137)CsCl in mice. Over 1800 spectral features were detected in the serum of mice in positive and negative electrospray ionization modes combined. Detailed statistical analysis revealed that several metabolites associated with amino acid metabolism, fatty acid metabolism, and the TCA cycle were significantly perturbed in the serum of (137)Cs-exposed mice compared with that of control mice. While metabolites associated with the TCA cycle and glycolysis increased in their serum abundances, fatty acids such as linoleic acid and palmitic acid were detected at lower levels in serum after (137)Cs exposure. Furthermore, phosphatidylcholines (PCs) were among the most perturbed ions in the serum of (137)Cs-exposed mice. This is the first study on the effects of exposure by an internal emitter in serum using a UPLC-MS(E) approach. The results have put forth a panel of metabolites, which may serve as potential serum markers to (137)Cs exposure.
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http://dx.doi.org/10.1021/pr500913nDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4286155PMC
January 2015

The effect of low dose rate on metabolomic response to radiation in mice.

Radiat Environ Biophys 2014 Nov 22;53(4):645-57. Epub 2014 Jul 22.

Biochemistry and Molecular and Cellular Biology, Georgetown University, Washington, DC, USA.

Metabolomics has been shown to have utility in assessing responses to exposure by ionizing radiation (IR) in easily accessible biofluids such as urine. Most studies to date from our laboratory and others have employed γ-irradiation at relatively high dose rates (HDR), but many environmental exposure scenarios will probably be at relatively low dose rates (LDR). There are well-documented differences in the biologic responses to LDR compared to HDR, so an important question is to assess LDR effects at the metabolomics level. Our study took advantage of a modern mass spectrometry approach in exploring the effects of dose rate on the urinary excretion levels of metabolites 2 days after IR in mice. A wide variety of statistical tools were employed to further focus on metabolites, which showed responses to LDR IR exposure (0.00309 Gy/min) distinguishable from those of HDR. From a total of 709 detected spectral features, more than 100 were determined to be statistically significant when comparing urine from mice irradiated with 1.1 or 4.45 Gy to that of sham-irradiated mice 2 days post-exposure. The results of this study show that LDR and HDR exposures perturb many of the same pathways such as TCA cycle and fatty acid metabolism, which also have been implicated in our previous IR studies. However, it is important to note that dose rate did affect the levels of particular metabolites. Differences in urinary excretion levels of such metabolites could potentially be used to assess an individual's exposure in a radiobiological event and thus would have utility for both triage and injury assessment.
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http://dx.doi.org/10.1007/s00411-014-0558-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4206600PMC
November 2014

Reprograming of gut microbiome energy metabolism by the FUT2 Crohn's disease risk polymorphism.

ISME J 2014 Nov 29;8(11):2193-206. Epub 2014 Apr 29.

1] Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA [2] Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.

Fucosyltransferase 2 (FUT2) is an enzyme that is responsible for the synthesis of the H antigen in body fluids and on the intestinal mucosa. The H antigen is an oligosaccharide moiety that acts as both an attachment site and carbon source for intestinal bacteria. Non-secretors, who are homozygous for the loss-of-function alleles of FUT2 gene (sese), have increased susceptibility to Crohn's disease (CD). To characterize the effect of FUT2 polymorphism on the mucosal ecosystem, we profiled the microbiome, meta-proteome and meta-metabolome of 75 endoscopic lavage samples from the cecum and sigmoid of 39 healthy subjects (12 SeSe, 18 Sese and 9 sese). Imputed metagenomic analysis revealed perturbations of energy metabolism in the microbiome of non-secretor and heterozygote individuals, notably the enrichment of carbohydrate and lipid metabolism, cofactor and vitamin metabolism and glycan biosynthesis and metabolism-related pathways, and the depletion of amino-acid biosynthesis and metabolism. Similar changes were observed in mice bearing the FUT2(-/-) genotype. Metabolomic analysis of human specimens revealed concordant as well as novel changes in the levels of several metabolites. Human metaproteomic analysis indicated that these functional changes were accompanied by sub-clinical levels of inflammation in the local intestinal mucosa. Therefore, the colonic microbiota of non-secretors is altered at both the compositional and functional levels, affecting the host mucosal state and potentially explaining the association of FUT2 genotype and CD susceptibility.
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http://dx.doi.org/10.1038/ismej.2014.64DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4992076PMC
November 2014

Integrative analysis of the microbiome and metabolome of the human intestinal mucosal surface reveals exquisite inter-relationships.

Microbiome 2013 Jun 5;1(1):17. Epub 2013 Jun 5.

Pathology and Laboratory Medicine UCLA, Los Angeles, CA, USA.

Background: Consistent compositional shifts in the gut microbiota are observed in IBD and other chronic intestinal disorders and may contribute to pathogenesis. The identities of microbial biomolecular mechanisms and metabolic products responsible for disease phenotypes remain to be determined, as do the means by which such microbial functions may be therapeutically modified.

Results: The composition of the microbiota and metabolites in gut microbiome samples in 47 subjects were determined. Samples were obtained by endoscopic mucosal lavage from the cecum and sigmoid colon regions, and each sample was sequenced using the 16S rRNA gene V4 region (Illumina-HiSeq 2000 platform) and assessed by UPLC mass spectroscopy. Spearman correlations were used to identify widespread, statistically significant microbial-metabolite relationships. Metagenomes for identified microbial OTUs were imputed using PICRUSt, and KEGG metabolic pathway modules for imputed genes were assigned using HUMAnN. The resulting metabolic pathway abundances were mostly concordant with metabolite data. Analysis of the metabolome-driven distribution of OTU phylogeny and function revealed clusters of clades that were both metabolically and metagenomically similar.

Conclusions: The results suggest that microbes are syntropic with mucosal metabolome composition and therefore may be the source of and/or dependent upon gut epithelial metabolites. The consistent relationship between inferred metagenomic function and assayed metabolites suggests that metagenomic composition is predictive to a reasonable degree of microbial community metabolite pools. The finding that certain metabolites strongly correlate with microbial community structure raises the possibility of targeting metabolites for monitoring and/or therapeutically manipulating microbial community function in IBD and other chronic diseases.
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http://dx.doi.org/10.1186/2049-2618-1-17DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3971612PMC
June 2013

Development of urinary biomarkers for internal exposure by cesium-137 using a metabolomics approach in mice.

Radiat Res 2014 Jan 30;181(1):54-64. Epub 2013 Dec 30.

a Biochemistry and Molecular and Cellular Biology, Georgetown University, Washington DC;

Cesium-137 is a fission product of uranium and plutonium in nuclear reactors and is released in large quantities during nuclear explosions or detonation of an improvised device containing this isotope. This environmentally persistent radionuclide undergoes radioactive decay with the emission of beta particles as well as gamma radiation. Exposure to (137)Cs at high doses can cause acute radiation sickness and increase risk for cancer and death. The serious health risks associated with (137)Cs exposure makes it critical to understand how it affects human metabolism and whether minimally invasive and easily accessible samples such as urine and serum can be used to triage patients in case of a nuclear disaster or a radiologic event. In this study, we have focused on establishing a time-dependent metabolomic profile for urine collected from mice injected with (137)CsCl. The samples were collected from control and exposed mice on days 2, 5, 20 and 30 after injection. The samples were then analyzed by ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry (UPLC/TOFMS) and processed by an array of informatics and statistical tools. A total of 1,412 features were identified in ESI(+) and ESI(-) modes from which 200 were determined to contribute significantly to the separation of metabolomic profiles of controls from those of the different treatment time points. The results of this study highlight the ease of use of the UPLC/TOFMS platform in finding urinary biomarkers for (137)Cs exposure. Pathway analysis of the statistically significant metabolites suggests perturbations in several amino acid and fatty acid metabolism pathways. The results also indicate that (137)Cs exposure causes: similar changes in the urinary excretion levels of taurine and citrate as seen with external-beam gamma radiation; causes no attenuation in the levels of hexanoylglycine and N-acetylspermidine; and has unique effects on the levels of isovalerylglycine and tiglylglycine.
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http://dx.doi.org/10.1667/RR13479.1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4029349PMC
January 2014

MetaboLyzer: a novel statistical workflow for analyzing Postprocessed LC-MS metabolomics data.

Anal Chem 2014 Jan 22;86(1):506-13. Epub 2013 Nov 22.

Lombardi Comprehensive Cancer Center, ‡Biochemistry and Molecular & Cellular Biology Georgetown University Medical Center , New Research Building E504/508 3970 Reservoir Road, NW Washington, DC 20057, United States.

Metabolomics, the global study of small molecules in a particular system, has in the past few years risen to become a primary -omics platform for the study of metabolic processes. With the ever-increasing pool of quantitative data yielded from metabolomic research, specialized methods and tools with which to analyze and extract meaningful conclusions from these data are becoming more and more crucial. Furthermore, the depth of knowledge and expertise required to undertake a metabolomics oriented study is a daunting obstacle to investigators new to the field. As such, we have created a new statistical analysis workflow, MetaboLyzer, which aims to both simplify analysis for investigators new to metabolomics, as well as provide experienced investigators the flexibility to conduct sophisticated analysis. MetaboLyzer's workflow is specifically tailored to the unique characteristics and idiosyncrasies of postprocessed liquid chromatography-mass spectrometry (LC-MS)-based metabolomic data sets. It utilizes a wide gamut of statistical tests, procedures, and methodologies that belong to classical biostatistics, as well as several novel statistical techniques that we have developed specifically for metabolomics data. Furthermore, MetaboLyzer conducts rapid putative ion identification and putative biologically relevant analysis via incorporation of four major small molecule databases: KEGG, HMDB, Lipid Maps, and BioCyc. MetaboLyzer incorporates these aspects into a comprehensive workflow that outputs easy to understand statistically significant and potentially biologically relevant information in the form of heatmaps, volcano plots, 3D visualization plots, correlation maps, and metabolic pathway hit histograms. For demonstration purposes, a urine metabolomics data set from a previously reported radiobiology study in which samples were collected from mice exposed to γ radiation was analyzed. MetaboLyzer was able to identify 243 statistically significant ions out of a total of 1942. Numerous putative metabolites and pathways were found to be biologically significant from the putative ion identification workflow.
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http://dx.doi.org/10.1021/ac402477zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3973431PMC
January 2014

PPARβ/δ modulates ethanol-induced hepatic effects by decreasing pyridoxal kinase activity.

Toxicology 2013 Sep 10;311(3):87-98. Epub 2013 Jul 10.

Lombardi Comprehensive Cancer Center, Department of Biochemistry and Molecular & Cellular Biology, Georgetown University, Washington, DC, USA.

Because of the significant morbidity and lethality caused by alcoholic liver disease (ALD), there remains a need to elucidate the regulatory mechanisms that can be targeted to prevent and treat ALD. Toward this goal, minimally invasive biomarker discovery represents an outstanding approach for these purposes. The mechanisms underlying ALD include hepatic lipid accumulation. As the peroxisome proliferator-activated receptor-β/δ (PPARβ/δ) has been shown to inhibit steatosis, the present study examined the role of PPARβ/δ in ALD coupling metabolomic, biochemical and molecular biological analyses. Wild-type and Pparβ/δ-null mice were fed either a control or 4% ethanol diet and examined after 4-7 months of treatment. Ethanol fed Pparβ/δ-null mice exhibited steatosis after short-term treatment compared to controls, the latter effect appeared to be due to increased activity of sterol regulatory element binding protein 1c (SREBP1c). The wild-type and Pparβ/δ-null mice fed the control diet showed clear differences in their urinary metabolomic profiles. In particular, metabolites associated with arginine and proline metabolism, and glycerolipid metabolism, were markedly different between genotypes suggesting a constitutive role for PPARβ/δ in the metabolism of these amino acids. Interestingly, urinary excretion of taurine was present in ethanol-fed wild-type mice but markedly lower in similarly treated Pparβ/δ-null mice. Evidence suggests that PPARβ/δ modulates pyridoxal kinase activity by altering Km, consistent with the observed decreased in urinary taurine excretion. These data collectively suggest that PPARβ/δ prevents ethanol-induced hepatic effects by inhibiting hepatic lipogenesis, modulation of amino acid metabolism, and altering pyridoxal kinase activity.
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http://dx.doi.org/10.1016/j.tox.2013.07.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3811069PMC
September 2013

Development of a novel proteomic approach for mitochondrial proteomics from cardiac tissue from patients with atrial fibrillation.

J Proteome Res 2011 Aug 8;10(8):3484-92. Epub 2011 Jul 8.

Center for Applied Proteomics and Molecular Medicine, George Mason University, Manassas, Virginia, USA.

Atrial fibrillation (AF) is the most common cardiac arrhythmia affecting approximately 2.2 million Americans. Because several studies have suggested that changes in mitochondrial function and morphology may contribute to AF, we developed a novel proteomic workflow focused on the identification of differentially expressed mitochondrial proteins in AF patients. Right human atrial tissue was collected from 20 patients, 10 with and 10 without AF, and the tissue was subjected to hydrostatic pressure cycling-based lysis followed by label-free mass spectrometric (MS) analysis of mitochondrial enriched isolates. Approximately 5% of the 700 proteins identified by MS analysis were differentially expressed between the AF and non-AF samples. We chose four differentially abundant proteins for further verification using reverse phase protein microarray analysis based on their known importance in energy production and regulatory association with atrial ion channels: four and a half LIM, destrin, heat shock protein 2, and chaperonin-containing TCP1. These initial study results provide evidence that a workflow to identify AF-related proteins that combines a powerful upfront tissue cell lysis with high resolution MS for discovery and protein array technology for verification may be an effective strategy for discovering candidate markers in highly fibrous tissue samples.
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http://dx.doi.org/10.1021/pr200108mDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5564307PMC
August 2011

Purification and characterization of Thermotoga maritima homoserine transsuccinylase indicates it is a transacetylase.

Extremophiles 2006 Oct 18;10(5):469-78. Epub 2006 May 18.

Department of Chemistry and Biochemistry, George Mason University, 10900 University Boulevard, Manassas, VA 20110, USA.

The methionine biosynthetic pathway found in bacteria is controlled at the first step, acylation of the gamma-hydroxyl of homoserine. This reaction is catalyzed by one of two unique enzymes, homoserine transacetylase or homoserine transsuccinylase, which have no amino acid sequence similarity. We cloned, expressed, and purified homoserine transsuccinylase from the thermophilic bacterium Thermotoga maritima. Substrate specificity experiments demonstrated that acetyl-coenzyme A (CoA) is the preferred acyl donor and is used at least 30-fold more efficiently than succinyl-CoA. Steady-state kinetic experiments confirm that the enzyme utilizes a ping-pong kinetic mechanism in which the acetate group of acetyl-CoA is initially transferred to an enzyme nucleophile before subsequent transfer to homoserine. The maximal velocity, V/K (acetyl-CoA) and V/K (homoserine), all exhibited bell-shaped pH curves with apparent pKs of 6.0-6.9 and 8.2-8.8. The enzyme was inactivated by iodoacetamide in a pH-dependent manner, with an apparent pK of 6.3, suggesting the presence of an active-site cysteine residue which forms an acetyl-enzyme thioester intermediate during catalytic turnover, similar to observations with other transsuccinylases. In addition, the enzyme is highly stable at elevated temperatures, maintaining full activity at 70 degrees C. Taken together, these data suggest that the T. maritima enzyme functions biochemically as a transacetylase, despite having the sequence of a transsuccinylase.
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http://dx.doi.org/10.1007/s00792-006-0522-3DOI Listing
October 2006
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