Publications by authors named "Robert A Quinn"

49 Publications

Review: microbial transformations of human bile acids.

Microbiome 2021 Jun 14;9(1):140. Epub 2021 Jun 14.

Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, 48824, USA.

Bile acids play key roles in gut metabolism, cell signaling, and microbiome composition. While the liver is responsible for the production of primary bile acids, microbes in the gut modify these compounds into myriad forms that greatly increase their diversity and biological function. Since the early 1960s, microbes have been known to transform human bile acids in four distinct ways: deconjugation of the amino acids glycine or taurine, and dehydroxylation, dehydrogenation, and epimerization of the cholesterol core. Alterations in the chemistry of these secondary bile acids have been linked to several diseases, such as cirrhosis, inflammatory bowel disease, and cancer. In addition to the previously known transformations, a recent study has shown that members of our gut microbiota are also able to conjugate amino acids to bile acids, representing a new set of "microbially conjugated bile acids." This new finding greatly influences the diversity of bile acids in the mammalian gut, but the effects on host physiology and microbial dynamics are mostly unknown. This review focuses on recent discoveries investigating microbial mechanisms of human bile acids and explores the chemical diversity that may exist in bile acid structures in light of the new discovery of microbial conjugations. Video Abstract.
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http://dx.doi.org/10.1186/s40168-021-01101-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8204491PMC
June 2021

Metabolomic signatures of coral bleaching history.

Nat Ecol Evol 2021 04 8;5(4):495-503. Epub 2021 Feb 8.

Hawai'i Institute of Marine Biology, University of Hawai'i at Mānoa, Kāne'ohe, HI, USA.

Coral bleaching has a profound impact on the health and function of reef ecosystems, but the metabolomic effects of coral bleaching are largely uncharacterized. Here, untargeted metabolomics was used to analyse pairs of adjacent Montipora capitata corals that had contrasting bleaching phenotypes during a severe bleaching event in 2015. When these same corals were sampled four years later while visually healthy, there was a strong metabolomic signature of bleaching history. This was primarily driven by betaine lipids from the symbiont, where corals that did not bleach were enriched in saturated lyso-betaine lipids. Immune modulator molecules were also altered by bleaching history in both the coral host and the algal symbiont, suggesting a shared role in partner choice and bleaching response. Metabolomics from a separate set of validation corals was able to predict the bleaching phenotype with 100% accuracy. Experimental temperature stress induced phenotype-specific responses, which magnified differences between historical bleaching phenotypes. These findings indicate that natural bleaching susceptibility is manifested in the biochemistry of both the coral animal and its algal symbiont. This metabolome difference is stable through time and results in different physiological responses to temperature stress. This work provides insight into the biochemical mechanisms of coral bleaching and presents a valuable new tool for resilience-based reef restoration.
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http://dx.doi.org/10.1038/s41559-020-01388-7DOI Listing
April 2021

Metabotypes of Correlate with Antibiotic Resistance, Virulence and Clinical Outcome in Cystic Fibrosis Chronic Infections.

Metabolites 2021 Jan 21;11(2). Epub 2021 Jan 21.

Département de Biochimie, Faculté de médecine de Grenoble, CNRS, CHU Grenoble Alpes, University Grenoble Alpes, Grenoble INP*, TIMC-IMAG, 38000 Grenoble, France.

() is one of the most critical antibiotic resistant bacteria in the world and is the most prevalent pathogen in cystic fibrosis (CF), causing chronic lung infections that are considered one of the major causes of mortality in CF patients. Although several studies have contributed to understanding within-host adaptive evolution at a genomic level, it is still difficult to establish direct relationships between the observed mutations, expression of clinically relevant phenotypes, and clinical outcomes. Here, we performed a comparative untargeted LC/HRMS-based metabolomics analysis of sequential isolates from chronically infected CF patients to obtain a functional view of adaptation. Metabolic profiles were integrated with expression of bacterial phenotypes and clinical measurements following multiscale analysis methods. Our results highlighted significant associations between "metabotypes", expression of antibiotic resistance and virulence phenotypes, and frequency of clinical exacerbations, thus identifying promising biomarkers and therapeutic targets for difficult-to-treat infections.
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http://dx.doi.org/10.3390/metabo11020063DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7909822PMC
January 2021

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

Mining Public Mass Spectrometry Data to Characterize the Diversity and Ubiquity of Specialized Metabolites.

Metabolites 2020 Nov 5;10(11). Epub 2020 Nov 5.

Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48823, USA.

is a ubiquitous environmental bacterium that causes chronic infections of burn wounds and in the lungs of cystic fibrosis (CF) patients. Vital to its infection is a myriad of specialized metabolites that serve a variety of biological roles including quorum sensing, metal chelation and inhibition of other competing bacteria. This study employed newly available algorithms for searching individual tandem mass (MS/MS) spectra against the publicly available Global Natural Product Social Molecular Networking (GNPS) database to identify the chemical diversity of these compounds and their presence in environmental, laboratory and clinical samples. For initial characterization, the metabolomes of eight clinical isolates of were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and uploaded to GNPS for spectral searching. Quinolones, rhamnolipids, phenazines and siderophores were identified and characterized; including the discovery of modified forms of the iron chelator pyochelin. Quinolones were highly diverse with the three base forms quinolone signal 2-heptyl-3-hydroxy-4()-quinolone (PQS), 4-heptyl-4()-quinolone (HHQ) and 2-heptyl-4-quinolone--oxide (HQNO) having extensive variation in the length of their acyl chain from as small as 3 carbons to as large as 17. Rhamnolipids were limited to either one or two sugars with a limited set of fatty acyl chains, but the base lipid form without the rhamnose was also detected. These specialized metabolites were identified from diverse sources including ant-fungal mutualist dens, soil, plants, human teeth, feces, various lung mucus samples and cultured laboratory isolates. Their prevalence in fecal samples was particularly notable as is not known as a common colonizer of the human gut. The chemical diversity of the compounds identified, particularly the quinolones, demonstrates a broad spectrum of chemical properties within these the metabolite groups with likely significant impacts on their biological functions. Mining public data with GNPS enables a new approach to characterize the chemical diversity of biological organisms, which includes enabling the discovery of new chemistry from pathogenic bacteria.
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http://dx.doi.org/10.3390/metabo10110445DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7694397PMC
November 2020

Evaluating Organism-Wide Changes in the Metabolome and Microbiome following a Single Dose of Antibiotic.

mSystems 2020 Oct 6;5(5). Epub 2020 Oct 6.

Department of Pediatrics, UC San Diego, La Jolla, California, USA

Antibiotics are a mainstay of modern medicine, but as they kill their target pathogen(s), they often affect the commensal microbiota. Antibiotic-induced microbiome dysbiosis is a growing research focus and health concern, often assessed via analysis of fecal samples. However, such analysis does not inform how antibiotics influence the microbiome across the whole host or how such changes subsequently alter host chemistry. In this study, we investigated the acute (1 day postadministration) and delayed (6 days postadministration) effects of a single parenteral dose of two common antibiotics, ampicillin or vancomycin, on the global metabolome and microbiome of mice across 77 different body sites from 25 different organs. The broader-spectrum agent ampicillin had the greatest impact on the microbiota in the lower gastrointestinal tract (cecum and colon), where microbial diversity is highest. In the metabolome, the greatest effects were seen 1 day posttreatment, and changes in metabolite abundances were not confined to the gut. The local abundance of ampicillin and its metabolites correlated with increased metabolome effect size and a loss of alpha diversity versus control mice. Additionally, small peptides were elevated in the lower gastrointestinal tract of mice 1 day after antibiotic treatment. While a single parenteral dose of antibiotic did not drastically alter the microbiome, nevertheless, changes in the metabolome were observed both within and outside the gut. This study provides a framework for how whole-organism -omics approaches can be employed to understand the impact of antibiotics on the entire host. We are just beginning to understand the unintended effects of antibiotics on our microbiomes and health. In this study, we aimed to define an approach by which one could obtain a comprehensive picture of (i) how antibiotics spatiotemporally impact commensal microbes throughout the gut and (ii) how these changes influence host chemistry throughout the body. We found that just a single dose of antibiotic altered host chemistry in a variety of organs and that microbiome alterations were not uniform throughout the gut. As technological advances increase the feasibility of whole-organism studies, we argue that using these approaches can provide further insight on both the wide-ranging effects of antibiotics on health and how to restore microbial communities to mitigate these effects.
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http://dx.doi.org/10.1128/mSystems.00340-20DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7542558PMC
October 2020

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

High-Resolution Longitudinal Dynamics of the Cystic Fibrosis Sputum Microbiome and Metabolome through Antibiotic Therapy.

mSystems 2020 Jun 23;5(3). Epub 2020 Jun 23.

Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan, USA

Microbial diversity in the cystic fibrosis (CF) lung decreases over decades as pathogenic bacteria such as take over. The dynamics of the CF microbiome and metabolome over shorter time frames, however, remain poorly studied. Here, we analyze paired microbiome and metabolome data from 594 sputum samples collected over 401 days from six adult CF subjects (subject mean = 179 days) through periods of clinical stability and 11 CF pulmonary exacerbations (CFPE). While microbiome profiles were personalized (permutational multivariate analysis of variance [PERMANOVA]  = 0.79,  < 0.001), we observed significant intraindividual temporal variation that was highest during clinical stability (linear mixed-effects [LME] model,  = 0.002). This included periods where the microbiomes of different subjects became highly similar (UniFrac distance, <0.05). There was a linear increase in the microbiome alpha-diversity and in the log ratio of anaerobes to pathogens with time ( = 14 days) during the development of a CFPE (LME  = 0.0045 and  = 0.029, respectively). Collectively, comparing samples across disease states showed there was a reduction of these two measures during antibiotic treatment (LME  = 0.0096 and  = 0.014, respectively), but the stability data and CFPE data were not significantly different from each other. Metabolome alpha-diversity was higher during CFPE than during stability (LME  = 0.0085), but no consistent metabolite signatures of CFPE across subjects were identified. Virulence-associated metabolites from were temporally dynamic but were not associated with any disease state. One subject died during the collection period, enabling a detailed look at changes in the 194 days prior to death. This subject had over 90% in the microbiome at the beginning of sampling, and that level gradually increased to over 99% prior to death. This study revealed that the CF microbiome and metabolome of some subjects are dynamic through time. Future work is needed to understand what drives these temporal dynamics and if reduction of anaerobes correlate to clinical response to CFPE therapy. Subjects with cystic fibrosis battle polymicrobial lung infections throughout their lifetime. Although antibiotic therapy is a principal treatment for CF lung disease, we have little understanding of how antibiotics affect the CF lung microbiome and metabolome and how much the community changes on daily timescales. By analyzing 594 longitudinal CF sputum samples from six adult subjects, we show that the sputum microbiome and metabolome are dynamic. Significant changes occur during times of stability and also through pulmonary exacerbations (CFPEs). Microbiome alpha-diversity increased as a CFPE developed and then decreased during treatment in a manner corresponding to the reduction in the log ratio of anaerobic bacteria to classic pathogens. Levels of metabolites from the pathogen were also highly variable through time and were negatively associated with anaerobes. The microbial dynamics observed in this study may have a significant impact on the outcome of antibiotic therapy for CFPEs and overall subject health.
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http://dx.doi.org/10.1128/mSystems.00292-20DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7311317PMC
June 2020

A multiomic analysis of in situ coral-turf algal interactions.

Proc Natl Acad Sci U S A 2020 06 1;117(24):13588-13595. Epub 2020 Jun 1.

Department of Biology, San Diego State University, San Diego, CA 92182;

Viruses, microbes, and host macroorganisms form ecological units called holobionts. Here, a combination of metagenomic sequencing, metabolomic profiling, and epifluorescence microscopy was used to investigate how the different components of the holobiont including bacteria, viruses, and their associated metabolites mediate ecological interactions between corals and turf algae. The data demonstrate that there was a microbial assemblage unique to the coral-turf algae interface displaying higher microbial abundances and larger microbial cells. This was consistent with previous studies showing that turf algae exudates feed interface and coral-associated microbial communities, often at the detriment of the coral. Further supporting this hypothesis, when the metabolites were assigned a nominal oxidation state of carbon (NOSC), we found that the turf algal metabolites were significantly more reduced (i.e., have higher potential energy) compared to the corals and interfaces. The algae feeding hypothesis was further supported when the ecological outcomes of interactions (e.g., whether coral was winning or losing) were considered. For example, coral holobionts losing the competition with turf algae had higher Bacteroidetes-to-Firmicutes ratios and an elevated abundance of genes involved in bacterial growth and division. These changes were similar to trends observed in the obese human gut microbiome, where overfeeding of the microbiome creates a dysbiosis detrimental to the long-term health of the metazoan host. Together these results show that there are specific biogeochemical changes at coral-turf algal interfaces that predict the competitive outcomes between holobionts and are consistent with algal exudates feeding coral-associated microbes.
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http://dx.doi.org/10.1073/pnas.1915455117DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7306781PMC
June 2020

Global chemical effects of the microbiome include new bile-acid conjugations.

Nature 2020 03 26;579(7797):123-129. Epub 2020 Feb 26.

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

A mosaic of cross-phylum chemical interactions occurs between all metazoans and their microbiomes. A number of molecular families that are known to be produced by the microbiome have a marked effect on the balance between health and disease. Considering the diversity of the human microbiome (which numbers over 40,000 operational taxonomic units), the effect of the microbiome on the chemistry of an entire animal remains underexplored. Here we use mass spectrometry informatics and data visualization approaches to provide an assessment of the effects of the microbiome on the chemistry of an entire mammal by comparing metabolomics data from germ-free and specific-pathogen-free mice. We found that the microbiota affects the chemistry of all organs. This included the amino acid conjugations of host bile acids that were used to produce phenylalanocholic acid, tyrosocholic acid and leucocholic acid, which have not previously been characterized despite extensive research on bile-acid chemistry. These bile-acid conjugates were also found in humans, and were enriched in patients with inflammatory bowel disease or cystic fibrosis. These compounds agonized the farnesoid X receptor in vitro, and mice gavaged with the compounds showed reduced expression of bile-acid synthesis genes in vivo. Further studies are required to confirm whether these compounds have a physiological role in the host, and whether they contribute to gut diseases that are associated with microbiome dysbiosis.
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http://dx.doi.org/10.1038/s41586-020-2047-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7252668PMC
March 2020

Involvement of the Gut Microbiota and Barrier Function in Glucocorticoid-Induced Osteoporosis.

J Bone Miner Res 2020 04 23;35(4):801-820. Epub 2020 Jan 23.

Department of Physiology, Michigan State University, East Lansing, MI, USA.

Glucocorticoids (GCs) are potent immune-modulating drugs with significant side effects, including glucocorticoid-induced osteoporosis (GIO). GCs directly induce osteoblast and osteocyte apoptosis but also alter intestinal microbiota composition. Although the gut microbiota is known to contribute to the regulation of bone density, its role in GIO has never been examined. To test this, male C57/Bl6J mice were treated for 8 weeks with GC (prednisolone, GC-Tx) in the presence or absence of broad-spectrum antibiotic treatment (ABX) to deplete the microbiota. Long-term ABX prevented GC-Tx-induced trabecular bone loss, showing the requirement of gut microbiota for GIO. Treatment of GC-Tx mice with a probiotic (Lactobacillus reuteri [LR]) prevented trabecular bone loss. Microbiota analyses indicated that GC-Tx changed the abundance of Verrucomicobiales and Bacteriodales phyla and random forest analyses indicated significant differences in abundance of Porphyromonadaceae and Clostridiales operational taxonomic units (OTUs) between groups. Furthermore, transplantation of GC-Tx mouse fecal material into recipient naïve, untreated WT mice caused bone loss, supporting a functional role for microbiota in GIO. We also report that GC caused intestinal barrier breaks, as evidenced by increased serum endotoxin level (2.4-fold), that were prevented by LR and ABX treatments. Enhancement of barrier function with a mucus supplement prevented both GC-Tx-induced barrier leakage and trabecular GIO. In bone, treatment with ABX, LR or a mucus supplement reduced GC-Tx-induced osteoblast and osteocyte apoptosis. GC-Tx suppression of Wnt10b in bone was restored by the LR and high-molecular-weight polymer (MDY) treatments as well as microbiota depletion. Finally, we identified that bone-specific Wnt10b overexpression prevented GIO. Taken together, our data highlight the previously unappreciated involvement of the gut microbiota and intestinal barrier function in trabecular GIO pathogenesis (including Wnt10b suppression and osteoblast and osteocyte apoptosis) and identify the gut as a novel therapeutic target for preventing GIO. © 2019 American Society for Bone and Mineral Research.
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http://dx.doi.org/10.1002/jbmr.3947DOI Listing
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

Optimizing sequencing protocols for leaderboard metagenomics by combining long and short reads.

Genome Biol 2019 10 31;20(1):226. Epub 2019 Oct 31.

Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA.

As metagenomic studies move to increasing numbers of samples, communities like the human gut may benefit more from the assembly of abundant microbes in many samples, rather than the exhaustive assembly of fewer samples. We term this approach leaderboard metagenome sequencing. To explore protocol optimization for leaderboard metagenomics in real samples, we introduce a benchmark of library prep and sequencing using internal references generated by synthetic long-read technology, allowing us to evaluate high-throughput library preparation methods against gold-standard reference genomes derived from the samples themselves. We introduce a low-cost protocol for high-throughput library preparation and sequencing.
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http://dx.doi.org/10.1186/s13059-019-1834-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6822431PMC
October 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

Microbial Transformations of Organically Fermented Foods.

Metabolites 2019 Aug 10;9(8). Epub 2019 Aug 10.

Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA.

Fermenting food is an ancient form of preservation ingrained many in human societies around the world. Westernized diets have moved away from such practices, but even in these cultures, fermented foods are seeing a resurgent interested due to their believed health benefits. Here, we analyze the microbiome and metabolome of organically fermented vegetables, using a salt brine, which is a common 'at-home' method of food fermentation. We found that the natural microbial fermentation had a strong effect on the food metabolites, where all four foods (beet, carrot, peppers and radishes) changed through time, with a peak in molecular diversity after 2-3 days and a decrease in diversity during the final stages of the 4-day process. The microbiome of all foods showed a stark transition from one that resembled a soil community to one dominated by Enterobacteriaceae, such as spp., within a single day of fermentation and increasing amounts of Lactobacillales through the fermentation process. With particular attention to plant natural products, we observed significant transformations of polyphenols, triterpenoids and anthocyanins, but the degree of this metabolism depended on the food type. Beets, radishes and peppers saw an increase in the abundance of these compounds as the fermentation proceeded, but carrots saw a decrease through time. This study showed that organically fermenting vegetables markedly changed their chemistry and microbiology but resulted in high abundance of Enterobacteriaceae which are not normally considered as probiotics. The release of beneficial plant specialized metabolites was observed, but this depended on the fermented vegetable.
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http://dx.doi.org/10.3390/metabo9080165DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6724132PMC
August 2019

Cystic Fibrosis Rapid Response: Translating Multi-omics Data into Clinically Relevant Information.

mBio 2019 04 16;10(2). Epub 2019 Apr 16.

Department of Biology, San Diego State University, San Diego, California, USA

Pulmonary exacerbations are the leading cause of death in cystic fibrosis (CF) patients. To track microbial dynamics during acute exacerbations, a CF rapid response (CFRR) strategy was developed. The CFRR relies on viromics, metagenomics, metatranscriptomics, and metabolomics data to rapidly monitor active members of the viral and microbial community during acute CF exacerbations. To highlight CFRR, a case study of a CF patient is presented, in which an abrupt decline in lung function characterized a fatal exacerbation. The microbial community in the patient's lungs was closely monitored through the multi-omics strategy, which led to the identification of pathogenic shigatoxigenic (STEC) expressing Shiga toxin. This case study illustrates the potential for the CFRR to deconstruct complicated disease dynamics and provide clinicians with alternative treatments to improve the outcomes of pulmonary exacerbations and expand the life spans of individuals with CF. Proper management of polymicrobial infections in patients with cystic fibrosis (CF) has extended their life span. Information about the composition and dynamics of each patient's microbial community aids in the selection of appropriate treatment of pulmonary exacerbations. We propose the cystic fibrosis rapid response (CFRR) as a fast approach to determine viral and microbial community composition and activity during CF pulmonary exacerbations. The CFRR potential is illustrated with a case study in which a cystic fibrosis fatal exacerbation was characterized by the presence of shigatoxigenic The incorporation of the CFRR within the CF clinic could increase the life span and quality of life of CF patients.
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http://dx.doi.org/10.1128/mBio.00431-19DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6469968PMC
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

Niche partitioning of a pathogenic microbiome driven by chemical gradients.

Sci Adv 2018 09 26;4(9):eaau1908. Epub 2018 Sep 26.

Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California at San Diego, La Jolla, CA 92093, USA.

Environmental microbial communities are stratified by chemical gradients that shape the structure and function of these systems. Similar chemical gradients exist in the human body, but how they influence these microbial systems is more poorly understood. Understanding these effects can be particularly important for dysbiotic shifts in microbiome structure that are often associated with disease. We show that pH and oxygen strongly partition the microbial community from a diseased human lung into two mutually exclusive communities of pathogens and anaerobes. Antimicrobial treatment disrupted this chemical partitioning, causing complex death, survival, and resistance outcomes that were highly dependent on the individual microorganism and on community stratification. These effects were mathematically modeled, enabling a predictive understanding of this complex polymicrobial system. Harnessing the power of these chemical gradients could be a drug-free method of shaping microbial communities in the human body from undesirable dysbiotic states.
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http://dx.doi.org/10.1126/sciadv.aau1908DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6157970PMC
September 2018

Before platelets: the production of platelet-activating factor during growth and stress in a basal marine organism.

Proc Biol Sci 2018 08 15;285(1884). Epub 2018 Aug 15.

Department of Biology, San Diego State University, San Diego, CA 92182-4614, USA

Corals and humans represent two extremely disparate metazoan lineages and are therefore useful for comparative evolutionary studies. Two lipid-based molecules that are central to human immunity, platelet-activating factor (PAF) and Lyso-PAF were recently identified in scleractinian corals. To identify processes in corals that involve these molecules, PAF and Lyso-PAF biosynthesis was quantified in conditions known to stimulate PAF production in mammals (tissue growth and exposure to elevated levels of ultraviolet light) and in conditions unique to corals (competing with neighbouring colonies over benthic space). Similar to observations in mammals, PAF production was higher in regions of active tissue growth and increased when corals were exposed to elevated levels of ultraviolet light. PAF production also increased when corals were attacked by the stinging cells of a neighbouring colony, though only the attacked coral exhibited an increase in PAF. This reaction was observed in adjacent areas of the colony, indicating that this response is coordinated across multiple polyps including those not directly subject to the stress. PAF and Lyso-PAF are involved in coral stress responses that are both shared with mammals and unique to the ecology of cnidarians.
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http://dx.doi.org/10.1098/rspb.2018.1307DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6111180PMC
August 2018

Best practices for analysing microbiomes.

Nat Rev Microbiol 2018 07;16(7):410-422

Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA.

Complex microbial communities shape the dynamics of various environments, ranging from the mammalian gastrointestinal tract to the soil. Advances in DNA sequencing technologies and data analysis have provided drastic improvements in microbiome analyses, for example, in taxonomic resolution, false discovery rate control and other properties, over earlier methods. In this Review, we discuss the best practices for performing a microbiome study, including experimental design, choice of molecular analysis technology, methods for data analysis and the integration of multiple omics data sets. We focus on recent findings that suggest that operational taxonomic unit-based analyses should be replaced with new methods that are based on exact sequence variants, methods for integrating metagenomic and metabolomic data, and issues surrounding compositional data analysis, where advances have been particularly rapid. We note that although some of these approaches are new, it is important to keep sight of the classic issues that arise during experimental design and relate to research reproducibility. We describe how keeping these issues in mind allows researchers to obtain more insight from their microbiome data sets.
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http://dx.doi.org/10.1038/s41579-018-0029-9DOI Listing
July 2018

Meta-mass shift chemical profiling of metabolomes from coral reefs.

Proc Natl Acad Sci U S A 2017 10 12;114(44):11685-11690. Epub 2017 Oct 12.

Department of Biology, San Diego State University, San Diego, CA 92182.

Untargeted metabolomics of environmental samples routinely detects thousands of small molecules, the vast majority of which cannot be identified. Meta-mass shift chemical (MeMSChem) profiling was developed to identify mass differences between related molecules using molecular networks. This approach illuminates metabolome-wide relationships between molecules and the putative chemical groups that differentiate them (e.g., H, CH, COCH). MeMSChem profiling was used to analyze a publicly available metabolomic dataset of coral, algal, and fungal mat holobionts (i.e., the host and its associated microbes and viruses) sampled from some of Earth's most remote and pristine coral reefs. Each type of holobiont had distinct mass shift profiles, even when the analysis was restricted to molecules found in all samples. This result suggests that holobionts modify the same molecules in different ways and offers insights into the generation of molecular diversity. Three genera of stony corals had distinct patterns of molecular relatedness despite their high degree of taxonomic relatedness. MeMSChem profiles also partially differentiated between individuals, suggesting that every coral reef holobiont is a potential source of novel chemical diversity.
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http://dx.doi.org/10.1073/pnas.1710248114DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5676912PMC
October 2017

Ecological networking of cystic fibrosis lung infections.

NPJ Biofilms Microbiomes 2016 2;2. Epub 2016 Dec 2.

CUBE, Department of Microbiology and Ecosystem Science, University of Vienna, Althanstr.14 A-1090, Vienna, Austria.

In the context of a polymicrobial infection, treating a specific pathogen poses challenges because of unknown consequences on other members of the community. The presence of ecological interactions between microbes can change their physiology and response to treatment. For example, in the cystic fibrosis lung polymicrobial infection, antimicrobial susceptibility testing on clinical isolates is often not predictive of antibiotic efficacy. Novel approaches are needed to identify the interrelationships within the microbial community to better predict treatment outcomes. Here we used an ecological networking approach on the cystic fibrosis lung microbiome characterized using 16S rRNA gene sequencing and metagenomics. This analysis showed that the community is separated into three interaction groups: Gram-positive anaerobes, and . The and groups both anti-correlate with the anaerobic group, indicating a functional antagonism. When patients are clinically stable, these major groupings were also stable, however, during exacerbation, these communities fragment. Co-occurrence networking of functional modules annotated from metagenomics data supports that the underlying taxonomic structure is driven by differences in the core metabolism of the groups. Topological analysis of the functional network identified the non-mevalonate pathway of isoprenoid biosynthesis as a keystone for the microbial community, which can be targeted with the antibiotic fosmidomycin. This study uses ecological theory to identify novel treatment approaches against a polymicrobial disease with more predictable outcomes.
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http://dx.doi.org/10.1038/s41522-016-0002-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5460249PMC
December 2016

Integrating Microbiome and Metabolome Data to Understand Infectious Airway Disease.

Authors:
Robert A Quinn

Am J Respir Crit Care Med 2017 10;196(7):806-807

1 Skaggs School of Pharmacy and Pharmaceutical Sciences and.

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http://dx.doi.org/10.1164/rccm.201704-0671EDDOI Listing
October 2017

The WinCF Model - An Inexpensive and Tractable Microcosm of a Mucus Plugged Bronchiole to Study the Microbiology of Lung Infections.

J Vis Exp 2017 05 8(123). Epub 2017 May 8.

Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego;

Many chronic airway diseases result in mucus plugging of the airways. Lungs of an individual with cystic fibrosis are an exemplary case where their mucus-plugged bronchioles create a favorable habitat for microbial colonization. Various pathogens thrive in this environment interacting with each other and driving many of the symptoms associated with CF disease. Like any microbial community, the chemical conditions of their habitat have a significant impact on the community structure and dynamics. For example, different microorganisms thrive in differing levels of oxygen or other solute concentrations. This is also true in the CF lung, where oxygen concentrations are believed to drive community physiology and structure. The methods described here are designed to mimic the lung environment and grow pathogens in a manner more similar to that from which they cause disease. Manipulation of the chemical surroundings of these microbes is then used to study how the chemistry of lung infections governs its microbial ecology. The method, called the WinCF system, is based on artificial sputum medium and narrow capillary tubes meant to provide an oxygen gradient similar to that which exists in mucus-plugged bronchioles. Manipulating chemical conditions, such as the media pH of the sputum or antibiotics pressure, allows for visualization of the microbiological differences in those samples using colored indicators, watching for gas or biofilm production, or extracting and sequencing the nucleic acid contents of each sample.
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http://dx.doi.org/10.3791/55532DOI Listing
May 2017

Real-time PCR assay for Aquimarina macrocephali subsp. homaria and its distribution in shell disease lesions of Homarus americanus, Milne-Edwards, 1837, and environmental samples.

J Microbiol Methods 2017 08 3;139:61-67. Epub 2017 Apr 3.

Department of Biology, University of Louisiana at Lafayette, Lafayette, LA, United States. Electronic address:

Epizootic shell disease (ESD) is causing major losses to the lobster fishery in southern New England. Potential pathogens have been identified in lesion communities, but there are currently no efficient means of detecting and quantifying their presence. A qPCR assay was developed for a key potential pathogen, Aquimarina macrocephali subsp. homaria found to be ubiquitous in ESD lesions but not the unaffected integument. Application of the assay to various samples demonstrated that A. macrocephali subsp. homaria is ubiquitous and abundant in lobster lesions, commonly associated with healthy surfaces of crabs and is scarce in water and sediment samples from southern New England suggesting the affinity of this microorganism to the Arthropod integument. The qPCR assay developed here can be applied in future in vivo and in vitro studies to better understand the ecology and role of A. macrocephali subsp.homaria. in shell disease.
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http://dx.doi.org/10.1016/j.mimet.2017.04.001DOI Listing
August 2017

Balance Trees Reveal Microbial Niche Differentiation.

mSystems 2017 Jan-Feb;2(1). Epub 2017 Jan 17.

Department of Pediatrics, University of California San Diego, La Jolla, California, USA; Department of Computer Science and Engineering, University of California San Diego, La Jolla, California, USA.

Advances in sequencing technologies have enabled novel insights into microbial niche differentiation, from analyzing environmental samples to understanding human diseases and informing dietary studies. However, identifying the microbial taxa that differentiate these samples can be challenging. These issues stem from the compositional nature of 16S rRNA gene data (or, more generally, taxon or functional gene data); the changes in the relative abundance of one taxon influence the apparent abundances of the others. Here we acknowledge that inferring properties of individual bacteria is a difficult problem and instead introduce the concept of balances to infer meaningful properties of subcommunities, rather than properties of individual species. We show that balances can yield insights about niche differentiation across multiple microbial environments, including soil environments and lung sputum. These techniques have the potential to reshape how we carry out future ecological analyses aimed at revealing differences in relative taxonomic abundances across different samples. By explicitly accounting for the compositional nature of 16S rRNA gene data through the concept of balances, balance trees yield novel biological insights into niche differentiation. The software to perform this analysis is available under an open-source license and can be obtained at https://github.com/biocore/gneiss. : An author video summary of this article is available.
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http://dx.doi.org/10.1128/mSystems.00162-16DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5264246PMC
January 2017

Molecular Networking As a Drug Discovery, Drug Metabolism, and Precision Medicine Strategy.

Trends Pharmacol Sci 2017 02 11;38(2):143-154. Epub 2016 Nov 11.

Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, CA, USA; Departments of Pharmacology and Pediatrics, University of California, San Diego, San Diego, CA, USA. Electronic address:

Molecular networking is a tandem mass spectrometry (MS/MS) data organizational approach that has been recently introduced in the drug discovery, metabolomics, and medical fields. The chemistry of molecules dictates how they will be fragmented by MS/MS in the gas phase and, therefore, two related molecules are likely to display similar fragment ion spectra. Molecular networking organizes the MS/MS data as a relational spectral network thereby mapping the chemistry that was detected in an MS/MS-based metabolomics experiment. Although the wider utility of molecular networking is just beginning to be recognized, in this review we highlight the principles behind molecular networking and its use for the discovery of therapeutic leads, monitoring drug metabolism, clinical diagnostics, and emerging applications in precision medicine.
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http://dx.doi.org/10.1016/j.tips.2016.10.011DOI Listing
February 2017

From Sample to Multi-Omics Conclusions in under 48 Hours.

mSystems 2016 Mar-Apr;1(2). Epub 2016 Apr 26.

Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, San Diego, California, USA; Department of Pediatrics, University of California, San Diego, San Diego, California, USA; Department of Computer Science and Engineering, University of California, San Diego, San Diego, California, USA; Center for Microbiome Innovation, University of California, San Diego, San Diego, California, USA.

Multi-omics methods have greatly advanced our understanding of the biological organism and its microbial associates. However, they are not routinely used in clinical or industrial applications, due to the length of time required to generate and analyze omics data. Here, we applied a novel integrated omics pipeline for the analysis of human and environmental samples in under 48 h. Human subjects that ferment their own foods provided swab samples from skin, feces, oral cavity, fermented foods, and household surfaces to assess the impact of home food fermentation on their microbial and chemical ecology. These samples were analyzed with 16S rRNA gene sequencing, inferred gene function profiles, and liquid chromatography-tandem mass spectrometry (LC-MS/MS) metabolomics through the Qiita, PICRUSt, and GNPS pipelines, respectively. The human sample microbiomes clustered with the corresponding sample types in the American Gut Project (http://www.americangut.org), and the fermented food samples produced a separate cluster. The microbial communities of the household surfaces were primarily sourced from the fermented foods, and their consumption was associated with increased gut microbial diversity. Untargeted metabolomics revealed that human skin and fermented food samples had separate chemical ecologies and that stool was more similar to fermented foods than to other sample types. Metabolites from the fermented foods, including plant products such as procyanidin and pheophytin, were present in the skin and stool samples of the individuals consuming the foods. Some food metabolites were modified during digestion, and others were detected in stool intact. This study represents a first-of-its-kind analysis of multi-omics data that achieved time intervals matching those of classic microbiological culturing. Polymicrobial infections are difficult to diagnose due to the challenge in comprehensively cultivating the microbes present. Omics methods, such as 16S rRNA sequencing, metagenomics, and metabolomics, can provide a more complete picture of a microbial community and its metabolite production, without the biases and selectivity of microbial culture. However, these advanced methods have not been applied to clinical or industrial microbiology or other areas where complex microbial dysbioses require immediate intervention. The reason for this is the length of time required to generate and analyze omics data. Here, we describe the development and application of a pipeline for multi-omics data analysis in time frames matching those of the culture-based approaches often used for these applications. This study applied multi-omics methods effectively in clinically relevant time frames and sets a precedent toward their implementation in clinical medicine and industrial microbiology.
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http://dx.doi.org/10.1128/mSystems.00038-16DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5069746PMC
April 2016