Publications by authors named "Alexander A Aksenov"

49 Publications

Ion identity molecular networking for mass spectrometry-based metabolomics in the GNPS environment.

Nat Commun 2021 06 22;12(1):3832. Epub 2021 Jun 22.

Department of Pharmaceutical Sciences, College of Pharmacy, Oregon State University, Corvallis, OR, USA.

Molecular networking connects mass spectra of molecules based on the similarity of their fragmentation patterns. However, during ionization, molecules commonly form multiple ion species with different fragmentation behavior. As a result, the fragmentation spectra of these ion species often remain unconnected in tandem mass spectrometry-based molecular networks, leading to redundant and disconnected sub-networks of the same compound classes. To overcome this bottleneck, we develop Ion Identity Molecular Networking (IIMN) that integrates chromatographic peak shape correlation analysis into molecular networks to connect and collapse different ion species of the same molecule. The new feature relationships improve network connectivity for structurally related molecules, can be used to reveal unknown ion-ligand complexes, enhance annotation within molecular networks, and facilitate the expansion of spectral reference libraries. IIMN is integrated into various open source feature finding tools and the GNPS environment. Moreover, IIMN-based spectral libraries with a broad coverage of ion species are publicly available.
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http://dx.doi.org/10.1038/s41467-021-23953-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8219731PMC
June 2021

A antibiotic modulates human skin microbiota composition in hair follicles.

Sci Transl Med 2020 11;12(570)

Microbiology, Forsyth Institute, Cambridge, MA 02142, USA.

The composition of the skin microbiota varies widely among individuals when sampled at the same body site. A key question is which molecular factors determine strain-level variability within sub-ecosystems of the skin microbiota. Here, we used a genomics-guided approach to identify an antibacterial biosynthetic gene cluster in (formerly ), a human skin commensal bacterium that is widely distributed across individuals and skin sites. Experimental characterization of this biosynthetic gene cluster resulted in identification of a new thiopeptide antibiotic, cutimycin. Analysis of individual human skin hair follicles revealed that cutimycin contributed to the ecology of the skin hair follicle microbiota and helped to reduce colonization of skin hair follicles by species.
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http://dx.doi.org/10.1126/scitranslmed.aay5445DOI Listing
November 2020

Fungal-bacterial interaction selects for quorum sensing mutants with increased production of natural antifungal compounds.

Commun Biol 2020 11 12;3(1):670. Epub 2020 Nov 12.

Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Química Biológica Ranwel Caputto, Córdoba, Argentina.

Soil microorganisms coexist and interact showing antagonistic or mutualistic behaviors. Here, we show that an environmental strain of Bacillus subtilis undergoes heritable phenotypic variation upon interaction with the soil fungal pathogen Setophoma terrestris (ST). Metabolomics analysis revealed differential profiles in B. subtilis before (pre-ST) and after (post-ST) interacting with the fungus, which paradoxically involved the absence of lipopeptides surfactin and plipastatin and yet acquisition of antifungal activity in post-ST variants. The profile of volatile compounds showed that 2-heptanone and 2-octanone were the most discriminating metabolites present at higher concentrations in post-ST during the interaction process. Both ketones showed strong antifungal activity, which was lost with the addition of exogenous surfactin. Whole-genome analyses indicate that mutations in ComQPXA quorum-sensing system, constituted the genetic bases of post-ST conversion, which rewired B. subtilis metabolism towards the depletion of surfactins and the production of antifungal compounds during its antagonistic interaction with S. terrestris.
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http://dx.doi.org/10.1038/s42003-020-01342-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7661731PMC
November 2020

Progress Toward an Attract-and-Kill Device for Asian Citrus Psyllid (Hemiptera: Liviidae) Using Volatile Signatures of Citrus Infected With Huanglongbing as the Attractant.

J Insect Sci 2020 Nov;20(6)

Department of Entomology and Nematology, Citrus Research and Education Center, Lake Alfred, FL.

Asian citrus psyllid, Diaphorina citri (Kuwayama), preferentially orient toward citrus hosts infected with the phytopathogenic bacterium, Candidatus liberibacter asiaticus (CLas) the agent of citrus greening (Huanglongbing, HLB), compared to uninfected counterparts. We investigated whether this preference for the odors of infected plants could be useful for the development of an attract-and-kill (AK) device for D. citri. Twenty-nine blends of volatile organic compounds derived from the odor of citrus infected with CLas were tested in laboratory olfactometer tests, and two blends were also assessed under field conditions. A seven component blend of tricosane: geranial: methyl salicylate: geranyl acetone: linalool: phenylacetaldehyde: (E)-β-ocimene in a 0.40: 0.06: 0.08: 0.29: 0.08: 0.06: 0.03 ratio released from a proprietary slow-release matrix attracted twice more D. citri to yellow sticky traps compared with blank control traps. The attractive blend was subsequently co-formulated with spinosad insecticide into a slow-release matrix to create a prototype AK formulation against D. citri. This formulation effectively reduced the population density of D. citri up to 84% as measured with tap counts when deployed at a density of eight 2.5 g dollops per tree as compared with untreated controls in small plot field trials conducted in citrus orchards. Psyllid populations were not statistically affected at a deployment rate of four dollops per tree. Our results indicate that an AK formulation incorporating spinosad and a volatile blend signature of citrus greening into a slow-release matrix may be useful to suppress D. citri populations.
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http://dx.doi.org/10.1093/jisesa/ieaa126DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7751137PMC
November 2020

Auto-deconvolution and molecular networking of gas chromatography-mass spectrometry data.

Nat Biotechnol 2021 02 9;39(2):169-173. Epub 2020 Nov 9.

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

We engineered a machine learning approach, MSHub, to enable auto-deconvolution of gas chromatography-mass spectrometry (GC-MS) data. We then designed workflows to enable the community to store, process, share, annotate, compare and perform molecular networking of GC-MS data within the Global Natural Product Social (GNPS) Molecular Networking analysis platform. MSHub/GNPS performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization and quantifies the reproducibility of fragmentation patterns across samples.
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http://dx.doi.org/10.1038/s41587-020-0700-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7971188PMC
February 2021

Feature-based molecular networking in the GNPS analysis environment.

Nat Methods 2020 09 24;17(9):905-908. Epub 2020 Aug 24.

Univ. Grenoble Alpes, CNRS, Grenoble INP, CHU Grenoble Alpes, TIMC-IMAG, Grenoble, France.

Molecular networking has become a key method to visualize and annotate the chemical space in non-targeted mass spectrometry data. We present feature-based molecular networking (FBMN) as an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools. FBMN enables quantitative analysis and resolution of isomers, including from ion mobility spectrometry.
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http://dx.doi.org/10.1038/s41592-020-0933-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7885687PMC
September 2020

ReDU: a framework to find and reanalyze public mass spectrometry data.

Nat Methods 2020 09 17;17(9):901-904. Epub 2020 Aug 17.

Grupo de Investigación en Ciencias Biológicas y Bioprocesos (CIBIOP), Department of Biological Sciences, Universidad EAFIT, Medellín, Colombia.

We present ReDU ( https://redu.ucsd.edu/ ), a system for metadata capture of public mass spectrometry-based metabolomics data, with validated controlled vocabularies. Systematic capture of knowledge enables the reanalysis of public data and/or co-analysis of one's own data. ReDU enables multiple types of analyses, including finding chemicals and associated metadata, comparing the shared and different chemicals between groups of samples, and metadata-filtered, repository-scale molecular networking.
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http://dx.doi.org/10.1038/s41592-020-0916-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7968862PMC
September 2020

Reproducible molecular networking of untargeted mass spectrometry data using GNPS.

Nat Protoc 2020 06 13;15(6):1954-1991. Epub 2020 May 13.

Department of Drug Discovery and Development, Harrison School of Pharmacy, Auburn University, Auburn, AL, USA.

Global Natural Product Social Molecular Networking (GNPS) is an interactive online small molecule-focused tandem mass spectrometry (MS) data curation and analysis infrastructure. It is intended to provide as much chemical insight as possible into an untargeted MS dataset and to connect this chemical insight to the user's underlying biological questions. This can be performed within one liquid chromatography (LC)-MS experiment or at the repository scale. GNPS-MassIVE is a public data repository for untargeted MS data with sample information (metadata) and annotated MS spectra. These publicly accessible data can be annotated and updated with the GNPS infrastructure keeping a continuous record of all changes. This knowledge is disseminated across all public data; it is a living dataset. Molecular networking-one of the main analysis tools used within the GNPS platform-creates a structured data table that reflects the molecular diversity captured in tandem mass spectrometry experiments by computing the relationships of the MS spectra as spectral similarity. This protocol provides step-by-step instructions for creating reproducible, high-quality molecular networks. For training purposes, the reader is led through a 90- to 120-min procedure that starts by recalling an example public dataset and its sample information and proceeds to creating and interpreting a molecular network. Each data analysis job can be shared or cloned to disseminate the knowledge gained, thus propagating information that can lead to the discovery of molecules, metabolic pathways, and ecosystem/community interactions.
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http://dx.doi.org/10.1038/s41596-020-0317-5DOI Listing
June 2020

A Genomic Toolkit for the Mechanistic Dissection of Intractable Human Gut Bacteria.

Cell Host Microbe 2020 06 28;27(6):1001-1013.e9. Epub 2020 Apr 28.

Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA; Chan Zuckerberg Biohub, San Francisco, CA 94158, USA. Electronic address:

Despite the remarkable microbial diversity found within humans, our ability to link genes to phenotypes is based upon a handful of model microorganisms. We report a comparative genomics platform for Eggerthella lenta and other Coriobacteriia, a neglected taxon broadly relevant to human health and disease. We uncover extensive genetic and metabolic diversity and validate a tool for mapping phenotypes to genes and sequence variants. We also present a tool for the quantification of strains from metagenomic sequencing data, enabling the identification of genes that predict bacterial fitness. Competitive growth is reproducible under laboratory conditions and attributable to intrinsic growth rates and resource utilization. Unique signatures of in vivo competition in gnotobiotic mice include an adhesin enriched in poor colonizers. Together, these computational and experimental resources represent a strong foundation for the continued mechanistic dissection of the Coriobacteriia and a template that can be applied to study other genetically intractable taxa.
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http://dx.doi.org/10.1016/j.chom.2020.04.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7292766PMC
June 2020

SPME-based mobile field device for active sampling of volatiles.

Microchem J 2019 May 5;146:407-413. Epub 2019 Jan 5.

Department of Mechanical and Aerospace Engineering; University of California, Davis; One Shields Avenue; Davis, CA 95616; U.S.A.

Monitoring plant volatile organic compound (VOC) profiles can reveal information regarding the health state of the plant, such as whether it is nutrient stressed or diseased. Typically, plant VOC sampling uses sampling enclosures. Enclosures require time and equipment which are not easily adapted to high throughput sampling in field environments. We have developed a new, easily assembled active sampling device using solid phase microextraction (SPME) that uses a commercial off the shelf (COTS) hand vacuum base to provide rapid and easy mobile plant VOC collection. Calibration curves for three representative plant VOCs (α-pinene, limonene, and ocimene) were developed to verify device functionality and enable the quantification of field-samples from a Meyer lemon tree. We saw that the active sampling allowed us to measure and quantify this chemical in an orchard setting. This device has the potential to be used for VOC sampling as a preliminary diagnostic in precision agriculture applications due to its ease of manufacturing, availability, and low cost of the COTS hand vacuum module.
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http://dx.doi.org/10.1016/j.microc.2019.01.012DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6867132PMC
May 2019

Interleukin-17 Inhibition in Spondyloarthritis Is Associated With Subclinical Gut Microbiome Perturbations and a Distinctive Interleukin-25-Driven Intestinal Inflammation.

Arthritis Rheumatol 2020 04 12;72(4):645-657. Epub 2020 Mar 12.

New York University School of Medicine, New York, New York.

Objective: To characterize the ecological effects of biologic therapies on the gut bacterial and fungal microbiome in psoriatic arthritis (PsA)/spondyloarthritis (SpA) patients.

Methods: Fecal samples from PsA/SpA patients pre- and posttreatment with tumor necrosis factor inhibitors (TNFi; n = 15) or an anti-interleukin-17A monoclonal antibody inhibitor (IL-17i; n = 14) underwent sequencing (16S ribosomal RNA, internal transcribed spacer and shotgun metagenomics) and computational microbiome analysis. Fecal levels of fatty acid metabolites and cytokines/proteins implicated in PsA/SpA pathogenesis or intestinal inflammation were correlated with sequence data. Additionally, ileal biopsies obtained from SpA patients who developed clinically overt Crohn's disease (CD) after treatment with IL-17i (n = 5) were analyzed for expression of IL-23/Th17-related cytokines, IL-25/IL-17E-producing cells, and type 2 innate lymphoid cells (ILC2s).

Results: There were significant shifts in abundance of specific taxa after treatment with IL-17i compared to TNFi, particularly Clostridiales (P = 0.016) and Candida albicans (P = 0.041). These subclinical alterations correlated with changes in bacterial community co-occurrence, metabolic pathways, IL-23/Th17-related cytokines, and various fatty acids. Ileal biopsies showed that clinically overt CD was associated with expansion of IL-25/IL-17E-producing tuft cells and ILC2s (P < 0.05), compared to pre-IL-17i treatment levels.

Conclusion: In a subgroup of SpA patients, the initiation of IL-17A blockade correlated with features of subclinical gut inflammation and intestinal dysbiosis of certain bacterial and fungal taxa, most notably C albicans. Further, IL-17i-related CD was associated with overexpression of IL-25/IL-17E-producing tuft cells and ILC2s. These results may help to explain the potential link between inhibition of a specific IL-17 pathway and the (sub)clinical gut inflammation observed in SpA.
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http://dx.doi.org/10.1002/art.41169DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7113119PMC
April 2020

Learning representations of microbe-metabolite interactions.

Nat Methods 2019 12 4;16(12):1306-1314. Epub 2019 Nov 4.

Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA.

Integrating multiomics datasets is critical for microbiome research; however, inferring interactions across omics datasets has multiple statistical challenges. We solve this problem by using neural networks (https://github.com/biocore/mmvec) to estimate the conditional probability that each molecule is present given the presence of a specific microorganism. We show with known environmental (desert soil biocrust wetting) and clinical (cystic fibrosis lung) examples, our ability to recover microbe-metabolite relationships, and demonstrate how the method can discover relationships between microbially produced metabolites and inflammatory bowel disease.
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http://dx.doi.org/10.1038/s41592-019-0616-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6884698PMC
December 2019

Molecular and Microbial Microenvironments in Chronically Diseased Lungs Associated with Cystic Fibrosis.

mSystems 2019 Sep 24;4(5). Epub 2019 Sep 24.

Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California, USA

To visualize the personalized distributions of pathogens and chemical environments, including microbial metabolites, pharmaceuticals, and their metabolic products, within and between human lungs afflicted with cystic fibrosis (CF), we generated three-dimensional (3D) microbiome and metabolome maps of six explanted lungs from three cystic fibrosis patients. These 3D spatial maps revealed that the chemical environments differ between patients and within the lungs of each patient. Although the microbial ecosystems of the patients were defined by the dominant pathogen, their chemical diversity was not. Additionally, the chemical diversity between locales in the lungs of the same individual sometimes exceeded interindividual variation. Thus, the chemistry and microbiome of the explanted lungs appear to be not only personalized but also regiospecific. Previously undescribed analogs of microbial quinolones and antibiotic metabolites were also detected. Furthermore, mapping the chemical and microbial distributions allowed visualization of microbial community interactions, such as increased production of quorum sensing quinolones in locations where was in contact with and , consistent with observations of bacteria isolated from these patients. Visualization of microbe-metabolite associations within a host organ in early-stage CF disease in animal models will help elucidate the complex interplay between the presence of a given microbial structure, antibiotics, metabolism of antibiotics, microbial virulence factors, and host responses. Microbial infections are now recognized to be polymicrobial and personalized in nature. Comprehensive analysis and understanding of the factors underlying the polymicrobial and personalized nature of infections remain limited, especially in the context of the host. By visualizing microbiomes and metabolomes of diseased human lungs, we reveal how different the chemical environments are between hosts that are dominated by the same pathogen and how community interactions shape the chemical environment or vice versa. We highlight that three-dimensional organ mapping methods represent hypothesis-building tools that allow us to design mechanistic studies aimed at addressing microbial responses to other microbes, the host, and pharmaceutical drugs.
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http://dx.doi.org/10.1128/mSystems.00375-19DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6759567PMC
September 2019

Untargeted mass spectrometry-based metabolomics approach unveils molecular changes in raw and processed foods and beverages.

Food Chem 2020 Jan 30;302:125290. Epub 2019 Jul 30.

Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, United States; Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, United States; Center for Microbiome Innovation, University of California, San Diego, United States; Scripps Institution of Oceanography, University of California, San Diego, United States.

In our daily lives, we consume foods that have been transported, stored, prepared, cooked, or otherwise processed by ourselves or others. Food storage and preparation have drastic effects on the chemical composition of foods. Untargeted mass spectrometry analysis of food samples has the potential to increase our chemical understanding of these processes by detecting a broad spectrum of chemicals. We performed a time-based analysis of the chemical changes in foods during common preparations, such as fermentation, brewing, and ripening, using untargeted mass spectrometry and molecular networking. The data analysis workflow presented implements an approach to study changes in food chemistry that can reveal global alterations in chemical profiles, identify changes in abundance, as well as identify specific chemicals and their transformation products. The data generated in this study are publicly available, enabling the replication and re-analysis of these data in isolation, and serve as a baseline dataset for future investigations.
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http://dx.doi.org/10.1016/j.foodchem.2019.125290DOI Listing
January 2020

High Asymmetric Longitudinal Field Ion Mobility Spectrometry Device for Low Power Mobile Chemical Separation and Detection.

Anal Chem 2019 05 11;91(9):5523-5529. Epub 2019 Apr 11.

Department of Mechanical and Aerospace Engineering , University of California Davis , Davis , California 95616 , United States.

We have developed a novel chemical sensing technique termed high asymmetric longitudinal field ion mobility spectrometry (HALF-IMS), which allows separation of ions based on mobility differences in high and low electric fields. Our device is microfabricated, has a miniature format, and uses exceptionally low power due to the lack of RF separation fields normally associated with ion mobility spectrometry (IMS) or differential mobility spectrometry (DMS). It operates at room temperature and atmospheric pressure. This HALF-IMS chip contains a microscale drift cell where spatially varying electric field regions of high and low strengths are generated by direct current (DC) applied to the electrodes that are physically placed to cause ionic separation as the ionized chemical flows along the drift cell. Power and complexity are reduced at the chip and system levels by reducing the voltage magnitude and using DC-powered electronics. A testing platform utilizing an ultraviolet (UV) photoionization source was used with custom electronic circuit boards to interface with the chip and provide data inputs and outputs. Precise control of the electrode voltages allowed filtering of the passage of the ion of interest through the drift cell, and ionic current was measured at the detector. The device was tested by scanning of electrode voltages and obtaining ion peaks for methyl salicylate, naphthalene, benzene, and 2-butanone. The current experimental setup was capable of detecting as low as ∼80 ppb of methyl salicylate and naphthalene. The use of benzene as a dopant with 2-butanone allowed one to see two ion peaks, corresponding to benzene and 2-butanone.
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http://dx.doi.org/10.1021/acs.analchem.8b05577DOI Listing
May 2019

SIRIUS 4: a rapid tool for turning tandem mass spectra into metabolite structure information.

Nat Methods 2019 04 18;16(4):299-302. Epub 2019 Mar 18.

Chair for Bioinformatics, Friedrich-Schiller University, Jena, Germany.

Mass spectrometry is a predominant experimental technique in metabolomics and related fields, but metabolite structural elucidation remains highly challenging. We report SIRIUS 4 (https://bio.informatik.uni-jena.de/sirius/), which provides a fast computational approach for molecular structure identification. SIRIUS 4 integrates CSI:FingerID for searching in molecular structure databases. Using SIRIUS 4, we achieved identification rates of more than 70% on challenging metabolomics datasets.
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http://dx.doi.org/10.1038/s41592-019-0344-8DOI Listing
April 2019

Neutrophilic proteolysis in the cystic fibrosis lung correlates with a pathogenic microbiome.

Microbiome 2019 02 13;7(1):23. Epub 2019 Feb 13.

Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA.

Background: Studies of the cystic fibrosis (CF) lung microbiome have consistently shown that lung function decline is associated with decreased microbial diversity due to the dominance of opportunistic pathogens. However, how this phenomenon is reflected in the metabolites and chemical environment of lung secretions remains poorly understood.

Methods: Here we investigated the microbial and molecular composition of CF sputum samples using 16S rRNA gene amplicon sequencing and untargeted tandem mass spectrometry to determine their interrelationships and associations with clinical measures of disease severity.

Results: The CF metabolome was found to exist in two states: one from patients with more severe disease that had higher molecular diversity and more Pseudomonas aeruginosa and the other from patients with better lung function having lower metabolite diversity and fewer pathogenic bacteria. The two molecular states were differentiated by the abundance and diversity of peptides and amino acids. Patients with severe disease and more pathogenic bacteria had higher levels of peptides. Analysis of the carboxyl terminal residues of these peptides indicated that neutrophil elastase and cathepsin G were responsible for their generation, and accordingly, these patients had higher levels of proteolytic activity from these enzymes in their sputum. The CF pathogen Pseudomonas aeruginosa was correlated with the abundance of amino acids and is known to primarily feed on them in the lung.

Conclusions: In cases of severe CF lung disease, proteolysis by host enzymes creates an amino acid-rich environment that P. aeruginosa comes to dominate, which may contribute to the pathogen's persistence by providing its preferred carbon source.
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http://dx.doi.org/10.1186/s40168-019-0636-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6375204PMC
February 2019

Effect of temperature control on the metabolite content in exhaled breath condensate.

Anal Chim Acta 2018 May 30;1006:49-60. Epub 2017 Dec 30.

Department of Mechanical and Aerospace Engineering, One Shields Avenue, University of California, Davis, Davis, CA 95616, USA. Electronic address:

The non-invasive, quick, and safe collection of exhaled breath condensate makes it a candidate as a diagnostic matrix in personalized health monitoring devices. The lack of standardization in collection methods and sample analysis is a persistent limitation preventing its practical use. The collection method and hardware design are recognized to significantly affect the metabolomic content of EBC samples, but this has not been systematically studied. Here, we completed a series of experiments to determine the sole effect of collection temperature on the metabolomic content of EBC. Temperature is a likely parameter that can be controlled to standardize among different devices. The study considered six temperature levels covering two physical phases of the sample; liquid and solid. The use of a single device in our study allowed keeping saliva filtering and collector surface effects as constant parameters and the temperature as a controlled variable; the physiological differences were minimized by averaging samples from a group of volunteers and a period of time. After EBC collection, we used an organic solvent rinse to collect the non-water-soluble compounds from the condenser surface. This additional matrix enhanced metabolites recovery, was less dependent on temperature changes, and may possibly serve as an additional pointer to standardize EBC sampling methodologies. The collected EBC samples were analyzed with a set of mass spectrometry methods to provide an overview of the compounds and their concentrations present at each temperature level. The total number of volatile and polar non-volatile compounds slightly increased in each physical phase as the collection temperature was lowered to minimum, 0 °C for liquid and -30, -56 °C for solid. The low-polarity non-volatile compounds showed a weak dependence on the collection temperature. The metabolomic content of EBC samples may not be solely dependent on temperature but may be influenced by other phenomena such as greater sample dilution due to condensation from the ambient air at colder temperatures, or due to adhesion properties of the collector surface and occurring chemical reactions. The relative importance of other design parameters such as condenser coating versus temperature requires further investigation.
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http://dx.doi.org/10.1016/j.aca.2017.12.025DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6050983PMC
May 2018

Author Correction: Inflammation-induced IgA cells dismantle anti-liver cancer immunity.

Nature 2018 09;561(7721):E1

Laboratory of Gene Regulation and Signal Transduction, Department of Pharmacology, School of Medicine, University of California San Diego (UCSD), 9500 Gilman Drive, La Jolla, California, 92093, USA.

In this Article, the sentence: "After 7 months of HFD, MUP-uPA mice developed HCC, which contained numerous (usually 50-100 per tumour) non-recurrent coding mutations in pathways that are mutated in human HCC (Fig. 2d and Extended Data Fig. 6a).", should have read: "After 7 months of HFD, MUP-uPA mice developed HCC, which contained numerous (usually 50-100 per tumour) non-recurrent mutations in pathways that are mutated in human HCC (Fig. 2d and Extended Data Fig. 6a).". This has been corrected online. In Extended Data Fig. 6a and b, which show the number of point mutations identified per sample and the mutational signatures, all sequence variants (including non-coding mutations) are shown. Fig. 2d also presents all variants compared to human mutations. In the Supplementary Information to this Amendment, we now provide the comparisons of all variants and coding variants to human mutations.
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http://dx.doi.org/10.1038/s41586-018-0304-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7871211PMC
September 2018

American Gut: an Open Platform for Citizen Science Microbiome Research.

mSystems 2018 May-Jun;3(3). Epub 2018 May 15.

Human Food Project, Terlingua, Texas, USA.

Although much work has linked the human microbiome to specific phenotypes and lifestyle variables, data from different projects have been challenging to integrate and the extent of microbial and molecular diversity in human stool remains unknown. Using standardized protocols from the Earth Microbiome Project and sample contributions from over 10,000 citizen-scientists, together with an open research network, we compare human microbiome specimens primarily from the United States, United Kingdom, and Australia to one another and to environmental samples. Our results show an unexpected range of beta-diversity in human stool microbiomes compared to environmental samples; demonstrate the utility of procedures for removing the effects of overgrowth during room-temperature shipping for revealing phenotype correlations; uncover new molecules and kinds of molecular communities in the human stool metabolome; and examine emergent associations among the microbiome, metabolome, and the diversity of plants that are consumed (rather than relying on reductive categorical variables such as veganism, which have little or no explanatory power). We also demonstrate the utility of the living data resource and cross-cohort comparison to confirm existing associations between the microbiome and psychiatric illness and to reveal the extent of microbiome change within one individual during surgery, providing a paradigm for open microbiome research and education. We show that a citizen science, self-selected cohort shipping samples through the mail at room temperature recaptures many known microbiome results from clinically collected cohorts and reveals new ones. Of particular interest is integrating = 1 study data with the population data, showing that the extent of microbiome change after events such as surgery can exceed differences between distinct environmental biomes, and the effect of diverse plants in the diet, which we confirm with untargeted metabolomics on hundreds of samples.
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http://dx.doi.org/10.1128/mSystems.00031-18DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5954204PMC
May 2018

Characterization of Mega-Dalton-Sized Nanoparticles by Superconducting Tunnel Junction Cryodetection Mass Spectrometry.

ACS Nano 2018 03 6;12(3):2591-2602. Epub 2018 Mar 6.

Center for Molecular Analysis, Department of Chemistry , Carnegie Mellon University , Pittsburgh , Pennsylvania 15213-2683 United States.

The characterization of nanomaterials is critical to understand the size/structure-dependent properties of these particles. In this report, a form of heavy ion mass spectrometry, namely, superconducting tunnel junction (STJ) cryodetection mass spectrometry (MS) is used to characterize quantum dot semiconductor nanocrystals and gold nanoparticles. The nanoparticles studied ranged in mass from 200 kDa to >1.5 MDa and included lead sulfide quantum dots, various cadmium selenide and/or telluride-based core-shell quantum dots coated with different ligands, and gold nanoparticles. Nanoparticles were ionized by both matrix-assisted laser desorption ionization (MALDI) and laser desorption ionization (LDI), shot with an aimed ion gun into a flight tube, mass separated by time-of-flight (TOF), and detected by an energy-sensitive STJ cryodetector. STJ cryodetection MS can be used to analyze intact heterogeneous nanoparticles, allowing determination of average particle mass, dispersity, and ligand loading. Some nanoparticles, however, do undergo fragmentation during the MALDI or LDI-TOF mass analyses. The measurement of the energy deposited into the detector was found to be different for different types of particles. Metastable fragments from these nanoparticles were observed at lower energies. The lower energies deposited for metastable fragments can provide insight into the stability and surface compositions of these materials. Cadmium selenide core-shell quantum dots (655 nm emission) conjugated to biomacromolecules, such as cholera toxin B and human serum transferrin, were also analyzed. When compared to unconjugated particles by mass, it was determined that ∼96 cholera toxin B and ∼14 transferrin proteins were attached to the surface of these nanoparticles.
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http://dx.doi.org/10.1021/acsnano.7b08541DOI Listing
March 2018

3D molecular cartography using LC-MS facilitated by Optimus and 'ili software.

Nat Protoc 2018 Jan 21;13(1):134-154. Epub 2017 Dec 21.

Structural and Computational Biology, European Molecular Biology Laboratory, Heidelberg, Germany.

Our skin, our belongings, the world surrounding us, and the environment we live in are covered with molecular traces. Detecting and characterizing these molecular traces is necessary to understand the environmental impact on human health and disease, and to decipher complex molecular interactions between humans and other species, particularly microbiota. We recently introduced 3D molecular cartography for mapping small organic molecules (including metabolites, lipids, and environmental molecules) found on various surfaces, including the human body. Here, we provide a protocol and open-source software for 3D molecular cartography. The protocol includes step-by-step procedures for sample collection and processing, liquid chromatography-mass spectrometry (LC-MS)-based metabolomics, quality control (QC), molecular identification using MS/MS, data processing, and visualization with 3D models of the sampled environment. The LC-MS method was optimized for a broad range of small organic molecules. We enable scientists to reproduce our previously obtained results, and illustrate the broad utility of our approach with molecular maps of a rosemary plant and an ATM keypad after a PIN code was entered. To promote reproducibility, we introduce cartographical snapshots: files that describe a particular map and visualization settings, and that can be shared and loaded to reproduce the visualization. The protocol enables molecular cartography to be performed in any mass spectrometry laboratory and, in principle, for any spatially mapped data. We anticipate applications, in particular, in medicine, ecology, agriculture, biotechnology, and forensics. The protocol takes 78 h for a molecular map of 100 spots, excluding the reagent setup.
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http://dx.doi.org/10.1038/nprot.2017.122DOI Listing
January 2018

Inflammation-induced IgA+ cells dismantle anti-liver cancer immunity.

Nature 2017 11 8;551(7680):340-345. Epub 2017 Nov 8.

Laboratory of Gene Regulation and Signal Transduction, Department of Pharmacology, School of Medicine, University of California San Diego (UCSD), 9500 Gilman Drive, La Jolla, California 92093, USA.

The role of adaptive immunity in early cancer development is controversial. Here we show that chronic inflammation and fibrosis in humans and mice with non-alcoholic fatty liver disease is accompanied by accumulation of liver-resident immunoglobulin-A-producing (IgA) cells. These cells also express programmed death ligand 1 (PD-L1) and interleukin-10, and directly suppress liver cytotoxic CD8 T lymphocytes, which prevent emergence of hepatocellular carcinoma and express a limited repertoire of T-cell receptors against tumour-associated antigens. Whereas CD8 T-cell ablation accelerates hepatocellular carcinoma, genetic or pharmacological interference with IgA cell generation attenuates liver carcinogenesis and induces cytotoxic T-lymphocyte-mediated regression of established hepatocellular carcinoma. These findings establish the importance of inflammation-induced suppression of cytotoxic CD8 T-lymphocyte activation as a tumour-promoting mechanism.
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http://dx.doi.org/10.1038/nature24302DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5884449PMC
November 2017

Exhaled breath condensate methods adapted from human studies using longitudinal metabolomics for predicting early health alterations in dolphins.

Anal Bioanal Chem 2017 Nov 23;409(28):6523-6536. Epub 2017 Oct 23.

Department of Mechanical and Aerospace Engineering, University of California, Davis, One Shields Avenue, Davis, CA, 95616, USA.

Monitoring health conditions is essential to detect early asymptomatic stages of a disease. To achieve this, blood, urine and breath samples are commonly used as a routine clinical diagnostic. These samples offer the opportunity to detect specific metabolites related to diseases and provide a better understanding of their development. Although blood samples are commonly used routinely to monitor health, the implementation of a relatively noninvasive technique, such as exhaled breath condensate (EBC) analysis, may further benefit the well-being of both humans and other animals. EBC analysis can be used to track possible physical or biochemical alterations caused by common diseases of the bottlenose dolphin (Tursiops truncatus), such as infections or inflammatory-mediated processes. We have used an untargeted metabolomic method with liquid chromatography-mass spectrometry analysis of EBC samples to determine biomarkers related to disease development. In this study, five dolphins under human care were followed up for 1 year. We collected paired blood, physical examination information, and EBC samples. We then statistically correlated this information to predict specific health alterations. Three dolphins provided promising case study information about biomarkers related to cutaneous infections, respiratory infections, dental disease, or hormonal changes (pregnancy). The use of complementary liquid chromatography platforms, with hydrophilic interaction chromatography and reverse-phased columns, allowed us to detect a wide spectrum of EBC biomarker compounds that could be related to these health alterations. Moreover, these two analytical techniques not only provided complementary metabolite information but in both cases they also provided promising diagnostic information for these health conditions. Graphical abstract Collection of the exhaled condensed breath from a bottlenose dolphin from U.S. Navy Marine Mammal Program (MMP).
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http://dx.doi.org/10.1007/s00216-017-0581-6DOI Listing
November 2017

An Easy to Manufacture Micro Gas Preconcentrator for Chemical Sensing Applications.

ACS Sens 2017 Aug 9;2(8):1167-1174. Epub 2017 Aug 9.

Department of Internal Medicine, Division of Pulmonary and Critical Care Medicine, University of California, Davis , Sacramento, California 95617, United States.

We have developed a simple-to-manufacture microfabricated gas preconcentrator for MEMS-based chemical sensing applications. Cavities and microfluidic channels were created using a wet etch process with hydrofluoric acid, portions of which can be performed outside of a cleanroom, instead of the more common deep reactive ion etch process. The integrated heater and resistance temperature detectors (RTDs) were created with a photolithography-free technique enabled by laser etching. With only 28 V DC (0.1 A), a maximum heating rate of 17.6 °C/s was observed. Adsorption and desorption flow parameters were optimized to be 90 SCCM and 25 SCCM, respectively, for a multicomponent gas mixture. Under testing conditions using Tenax TA sorbent, the device was capable of measuring analytes down to 22 ppb with only a 2 min sample loading time using a gas chromatograph with a flame ionization detector. Two separate devices were compared by measuring the same chemical mixture; both devices yielded similar peak areas and widths (fwhm: 0.032-0.033 min), suggesting reproducibility between devices.
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http://dx.doi.org/10.1021/acssensors.7b00289DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6541441PMC
August 2017

Analytical methodologies for broad metabolite coverage of exhaled breath condensate.

J Chromatogr B Analyt Technol Biomed Life Sci 2017 Sep 27;1061-1062:17-25. Epub 2017 Jun 27.

Mechanical and Aerospace Engineering, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA. Electronic address:

Breath analysis has been gaining popularity as a non-invasive technique that is amenable to a broad range of medical uses. One of the persistent problems hampering the wide application of the breath analysis method is measurement variability of metabolite abundances stemming from differences in both sampling and analysis methodologies used in various studies. Mass spectrometry has been a method of choice for comprehensive metabolomic analysis. For the first time in the present study, we juxtapose the most commonly employed mass spectrometry-based analysis methodologies and directly compare the resultant coverages of detected compounds in exhaled breath condensate in order to guide methodology choices for exhaled breath condensate analysis studies. Four methods were explored to broaden the range of measured compounds across both the volatile and non-volatile domain. Liquid phase sampling with polyacrylate Solid-Phase MicroExtraction fiber, liquid phase extraction with a polydimethylsiloxane patch, and headspace sampling using Carboxen/Polydimethylsiloxane Solid-Phase MicroExtraction (SPME) followed by gas chromatography mass spectrometry were tested for the analysis of volatile fraction. Hydrophilic interaction liquid chromatography and reversed-phase chromatography high performance liquid chromatography mass spectrometry were used for analysis of non-volatile fraction. We found that liquid phase breath condensate extraction was notably superior compared to headspace extraction and differences in employed sorbents manifested altered metabolite coverages. The most pronounced effect was substantially enhanced metabolite capture for larger, higher-boiling compounds using polyacrylate SPME liquid phase sampling. The analysis of the non-volatile fraction of breath condensate by hydrophilic and reverse phase high performance liquid chromatography mass spectrometry indicated orthogonal metabolite coverage by these chromatography modes. We found that the metabolite coverage could be enhanced significantly with the use of organic solvent as a device rinse after breath sampling to collect the non-aqueous fraction as opposed to neat breath condensate sample. Here, we show the detected ranges of compounds in each case and provide a practical guide for methodology selection for optimal detection of specific compounds.
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http://dx.doi.org/10.1016/j.jchromb.2017.06.038DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5573623PMC
September 2017
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