Three-Dimensional Microbiome and Metabolome Cartography of a Diseased Human Lung

Multi-omic approaches for host-microbiome data integration

The gut microbiome interacts with the host through complex networks that affect physiology and health outcomes. It is becoming clear that these interactions can be measured across many different omics layers, including the genome, transcriptome, epigenome, metabolome, and proteome, among others. Multi-omic studies of the microbiome can provide insight into the mechanisms underlying host-microbe interactions. As more omics layers are considered, increasingly sophisticated statistical methods are required to integrate them. In this review, we provide an overview of approaches currently used to characterize multi-omic interactions between host and microbiome data. While a large number of studies have generated a deeper understanding of host-microbiome interactions, there is still a need for standardization across approaches. Furthermore, microbiome studies would also benefit from the collection and curation of large, publicly available multi-omics datasets.

Mathematical models of cystic fibrosis as a systemic disease

Cystic fibrosis (CF) is widely known as a disease of the lung, even though it is in truth a systemic disease, whose symptoms typically manifest in gastrointestinal dysfunction first. CF ultimately impairs not only the pancreas and intestine but also the lungs, gonads, liver, kidneys, bones, and the cardiovascular system. It is caused by one of several mutations in the gene of the epithelial ion channel protein CFTR. Intense research and improved antimicrobial treatments during the past eight decades have steadily increased the predicted life expectancy of a person with CF (pwCF) from a few weeks to over 50 years. Moreover, several drugs ameliorating the sequelae of the disease have become available in recent years, and notable treatments of the root cause of the disease have recently generated substantial improvements in health for some but not all pwCF. Yet, numerous fundamental questions remain unanswered. Complicating CF, for instance in the lung, is the fact that the associated insufficient chloride secretion typically perturbs the electrochemical balance across epithelia and, in the airways, leads to the accumulation of thick, viscous mucus and mucus plaques that cannot be cleared effectively and provide a rich breeding ground for a spectrum of bacterial and fungal communities. The subsequent infections often become chronic and respond poorly to antibiotic treatments, with outcomes sometimes only weakly correlated with the drug susceptibility of the target pathogen. Furthermore, in contrast to rapidly resolved acute infections with a single target pathogen, chronic infections commonly involve multi-species bacterial communities, called "infection microbiomes," that develop their own ecological and evolutionary dynamics. It is presently impossible to devise mathematical models of CF in its entirety, but it is feasible to design models for many of the distinct drivers of the disease. Building upon these growing yet isolated modeling efforts, we discuss in the following the feasibility of a multi-scale modeling framework, known as template-and-anchor modeling, that allows the gradual integration of refined sub-models with different granularity. The article first reviews the most important biomedical aspects of CF and subsequently describes mathematical modeling approaches that already exist or have the potential to deepen our understanding of the multitude aspects of the disease and their interrelationships. The conceptual ideas behind the approaches proposed here do not only pertain to CF but are translatable to other systemic diseases. This article is categorized under: Congenital Diseases > Computational Models.

Alterations of lower respiratory tract microbiome and short-chain fatty acids in different segments in lung cancer: a multiomics analysis

Introduction

The lower respiratory tract microbiome is widely studied to pinpoint microbial dysbiosis of diversity or abundance that is linked to a number of chronic respiratory illnesses. However, it is vital to clarify how the microbiome, through the release of microbial metabolites, impacts lung health and oncogenesis.

Methods

In order to discover the powerful correlations between microbial metabolites and disease, we collected, under electronic bronchoscopy examinations, samples of paired bronchoalveolar lavage fluids (BALFs) from tumor-burden lung segments and ipsilateral non-tumor sites from 28 lung cancer participants, further performing metagenomic sequencing, short-chain fatty acid (SCFA) metabolomics, and multiomics analysis to uncover the potential correlations of the microbiome and SCFAs in lung cancer.

Results

In comparison to BALFs from normal lung segments of the same participant, those from lung cancer burden lung segments had slightly decreased microbial diversity in the lower respiratory tract. With 18 differentially prevalent microbial species, including the well-known carcinogens Campylobacter jejuni and Nesseria polysaccharea, the relative species abundance in the lower respiratory tract microbiome did not significantly differ between the two groups. Additionally, a collection of commonly recognized probiotic metabolites called short-chain fatty acids showed little significance in either group independently but revealed a strong predictive value when using an integrated model by machine learning. Multiomics also discovered particular species related to SCFAs, showing a positive correlation with Brachyspira hydrosenteriae and a negative one with Pseudomonas at the genus level, despite limited detection in lower airways. Of note, these distinct microbiota and metabolites corresponded with clinical traits that still required confirmation.

Conclusions

Further analysis of metagenome functional capacity revealed that genes encoding environmental information processing and metabolism pathways were enriched in the lower respiratory tract metagenomes of lung cancer patients, further supporting the oncogenesis function of various microbial species by different metabolites. These findings point to a potent relationship between particular components of the integrated microbiota-metabolites network and lung cancer, with implications for screening and diagnosis in clinical settings.

Visualization of metabolites and microbes at high spatial resolution using MALDI mass spectrometry imaging and in situ fluorescence labeling

Label-free molecular imaging techniques such as matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) enable the direct and simultaneous mapping of hundreds of different metabolites in thin sections of biological tissues. However, in host-microbe interactions it remains challenging to localize microbes and to assign metabolites to the host versus members of the microbiome. We therefore developed a correlative imaging approach combining MALDI-MSI with fluorescence in situ hybridization (FISH) on the same section to identify and localize microbial cells. Here, we detail metaFISH as a robust and easy method for assigning the spatial distribution of metabolites to microbiome members based on imaging of nucleic acid probes, down to single-cell resolution. We describe the steps required for tissue preparation, on-tissue hybridization, fluorescence microscopy, data integration into a correlative image dataset, matrix application and MSI data acquisition. Using metaFISH, we map hundreds of metabolites and several microbial species to the micrometer scale on a single tissue section. For example, intra- and extracellular bacteria, host cells and their associated metabolites can be localized in animal tissues, revealing their complex metabolic interactions. We explain how we identify low-abundance bacterial infection sites as regions of interest for high-resolution MSI analysis, guiding the user to a trade-off between metabolite signal intensities and fluorescence signals. MetaFISH is suitable for a broad range of users from environmental microbiologists to clinical scientists. The protocol requires ~2 work days.

Metabolomic Analysis of Polymicrobial Wound Infections and an Associated Adhesive Bandage

Concerns about ion suppression, spectral contamination, or interference have led to avoidance of polymers in mass spectrometry (MS)-based metabolomics. This avoidance, however, has left many biochemical fields underexplored, including wounds, which are often treated with adhesive bandages. Here, we found that despite previous concerns, the addition of an adhesive bandage can still result in biologically informative MS data. Initially, a test LC-MS analysis was performed on a mixture of known chemical standards and a polymer bandage extract. Results demonstrated successful removal of many polymer-associated features through a data processing step. Furthermore, the bandage presence did not interfere with metabolite annotation. This method was then implemented in the context of murine surgical wound infections covered with an adhesive bandage and inoculated with Staphylococcus aureus, Pseudomonas aeruginosa, or a 1:1 mix of these pathogens. Metabolites were extracted and analyzed by LC-MS. On the bandage side, we observed a greater impact of infection on the metabolome. Distance analysis showed significant differences between all conditions and demonstrated that coinfected samples were more similar to S. aureus-infected samples compared to P. aeruginosa-infected samples. We also found that coinfection was not merely a summative effect of each monoinfection. Overall, these results represent an expansion of LC-MS-based metabolomics to a novel, previously under-investigated class of samples, leading to actionable biological information.

Bacteriophage Therapy of Multidrug-resistant Achromobacter in an 11-Year-old Boy With Cystic Fibrosis Assessed by Metagenome Analysis

BACKGROUND

Cystic fibrosis (CF) is a genetic disease associated with lung disease characterized by chronic pulmonary infection, increasingly caused by multiple drug-resistant pathogens after repeated antibiotic exposure, limiting antibiotic treatment options. Bacteriophages can provide a pathogen-specific bactericidal treatment used with antibiotics to improve microbiologic and clinical outcomes in CF.

METHODS

Achromobacter species isolates from sputum of a chronically infected person with CF, were assessed for susceptibility to bacteriophages: 2 highly active, purified bacteriophages were administered intravenously every 8 hours, in conjunction with a 14-day piperacillin/tazobactam course for CF exacerbation. Sputum and blood were collected for metagenome analysis during treatment, with sputum analysis at 1-month follow-up. Assessments of clinical status, pulmonary status and laboratory evaluation for safety were conducted.

RESULTS

Bacteriophage administration was well-tolerated, with no associated clinical or laboratory adverse events. Metagenome analysis documented an 86% decrease in the relative proportion of Achromobacter DNA sequence reads in sputum and a 92% decrease in blood, compared with other bacterial DNA reads, comparing pretreatment and posttreatment samples. Bacteriophage DNA reads were detected in sputum after intravenous administration during treatment, and at 1-month follow-up. Reversal of antibiotic resistance to multiple antibiotics occurred in some isolates during treatment. Stabilization of lung function was documented at 1-month follow-up.

CONCLUSIONS

Bacteriophage/antibiotic treatment decreased the host pulmonary bacterial burden for Achromobacter assessed by metagenome analysis of sputum and blood, with ongoing bacteriophage replication documented in sputum at 1-month follow-up. Prospective controlled studies are needed to define the dose, route of administration and duration of bacteriophage therapy for both acute and chronic infection in CF.

Characterization of the Microbiome and Host's Metabolites of the Lower Respiratory Tract During Acute Community-Acquired Pneumonia Identifies Potential Novel Markers

Purpose

Community-acquired pneumonia (CAP) is one of the most frequently encountered infectious diseases worldwide. Few studies have explored the microbial composition of the lower respiratory tract (LRT) and host metabolites of CAP. We analyzed the microbial composition of the LRT and levels of host metabolites to explore new biomarkers for CAP.

Patients and Methods

Bronchoalveolar lavage fluid (BALF) was collected from 28 CAP patients and 20 healthy individuals. Following centrifugation, BALF pellets were used for amplicon sequencing of a variable region of the bacterial 16S rDNA gene to characterize the microbial composition. Non-targeted metabolomics was used to detect host's metabolites in the supernatant.

Results

Compared with healthy individuals, the bacterial alpha diversity in the LRT of CAP patients was significantly lower in CAP patients (p<0.05). On the bacterial genus level, over 20 genera were detected with lower relative abundance (p<0.05), while the relative abundance of Ruminiclostridium-6 was significantly higher in CAP patients. The levels of the host metabolites dimethyldisulfide, choline, pyrimidine, oleic acid and N-acetyl-neuraminic acid were all increased in BALF of CAP patients (p<0.05), while concentrations of lysophosphatidylcholines (LPC (12:0/0:0)) and phosphatidic acid (PA (20:4/2:0)) were decreased (p<0.05). Furthermore, the relative abundance of Parvimonas, Treponema-2, Moraxella, Aggregatibacter, Filifactor, Fusobacterium, Lautropia and Neisseria negatively correlated with concentrations of oleic acid (p<0.05). A negative correlation between the relative abundance of Treponema-2, Moraxella, Filifactor, Fusobacterium and dimethyldisulfide concentrations was also observed (p<0.05). In contrast, the relative abundance of Treponema-2, Moraxella, Filifactor, and Fusobacterium was found to be positively associated with concentrations of LPC (12:0/0:0) and PA (20:4/2:0) (p<0.05).

Conclusion

The composition of the LRT microbiome differed between healthy individuals and CAP patients. We propose that some respiratory microbial components and host metabolites are potentially novel diagnostic markers of CAP.

Progress and opportunities in microbial community metabolomics

The metabolome lies at the interface of host-microbiome crosstalk. Previous work has established links between chemically diverse microbial metabolites and a myriad of host physiological processes and diseases. Coupled with scalable and cost-effective technologies, metabolomics is thus gaining popularity as a tool for characterization of microbial communities, particularly when combined with metagenomics as a window into microbiome function. A systematic interrogation of microbial community metabolomes can uncover key microbial compounds, metabolic capabilities of the microbiome, and also provide critical mechanistic insights into microbiome-linked host phenotypes. In this review, we discuss methods and accompanying resources that have been developed for these purposes. The accomplishments of these methods demonstrate that metabolomes can be used to functionally characterize microbial communities, and that microbial properties can be used to identify and investigate chemical compounds.

Membrane lipid renovation in Pseudomonas aeruginosa - implications for phage therapy?

Pseudomonas aeruginosa is an important Gram-negative pathogen with intrinsic resistance to many clinically used antibiotics. It is particularly troublesome in nosocomial infections, immunocompromised patients, and individuals with cystic fibrosis. Antimicrobial resistance (AMR) is a huge threat to global health, with a predicted 10 million people dying from resistant infections by 2050. A promising therapy for combatting AMR infections is phage therapy. However, more research is required to investigate mechanisms that may influence the efficacy of phage therapy. An important overlooked aspect is the impact of membrane lipid remodelling on phage binding ability. P. aeruginosa undergoes changes in membrane lipids when it encounters phosphorus stress, an environmental perturbation that is likely to occur during infection. Lipid changes include the substitution of glycerophospholipids with surrogate glycolipids and the over-production of ornithine-containing aminolipids. Given that membrane lipids are known to influence the structure and function of membrane proteins, we propose that changes in the composition of membrane lipids during infection may alter phage binding and subsequent phage infection dynamics. Consideration of such effects needs to be urgently prioritised in order to develop the most effective phage therapy strategies for P. aeruginosa infections.

Microenvironmental Factors that Shape Bacterial Metabolites in Inflammatory Bowel Disease

Inflammatory bowel disease (IBD) is a significant global health problem that involves chronic intestinal inflammation and can involve severe comorbidities, including intestinal fibrosis and inflammation-associated colorectal cancer (CRC). Disease-associated alterations to the intestinal microbiota often include fecal enrichment of Enterobacteriaceae, which are strongly implicated in IBD development. This dysbiosis of intestinal flora accompanies changes in microbial metabolites, shaping host:microbe interactions and disease risk. While there have been numerous studies linking specific bacterial taxa with IBD development, our understanding of microbial function in the context of IBD is limited. Several classes of microbial metabolites have been directly implicated in IBD disease progression, including bacterial siderophores and genotoxins. Yet, our microbiota still harbors thousands of uncharacterized microbial products. In-depth discovery and characterization of disease-associated microbial metabolites is necessary to target these products in IBD treatment strategies. Towards improving our understanding of microbiota metabolites in IBD, it is important to recognize how host relevant factors influence microbiota function. For example, changes in host inflammation status, metal availability, interbacterial community structure, and xenobiotics all play an important role in shaping gut microbial ecology. In this minireview, we outline how each of these factors influences gut microbial function, with a specific focus on IBD-associated Enterobacteriaceae metabolites. Importantly, we discuss how altering the intestinal microenvironment could improve the treatment of intestinal inflammation and associated disorders, like intestinal fibrosis and CRC.

Metabolomics Analysis of Bacterial Pathogen Burkholderia thailandensis and Mammalian Host Cells in Co-culture

The Tier 1 HHS/USDA Select Agent Burkholderia pseudomallei is a bacterial pathogen that is highly virulent when introduced into the respiratory tract and intrinsically resistant to many antibiotics. Transcriptomic- and proteomic-based methodologies have been used to investigate mechanisms of virulence employed by B. pseudomallei and Burkholderia thailandensis, a convenient surrogate; however, analysis of the pathogen and host metabolomes during infection is lacking. Changes in the metabolites produced can be a result of altered gene expression and/or post-transcriptional processes. Thus, metabolomics complements transcriptomics and proteomics by providing a chemical readout of a biological phenotype, which serves as a snapshot of an organism's physiological state. However, the poor signal from bacterial metabolites in the context of infection poses a challenge in their detection and robust annotation. In this study, we coupled mammalian cell culture-based metabolomics with feature-based molecular networking of mono- and co-cultures to annotate the pathogen's secondary metabolome during infection of mammalian cells. These methods enabled us to identify several key secondary metabolites produced by B. thailandensis during infection of airway epithelial and macrophage cell lines. Additionally, the use of in silico approaches provided insights into shifts in host biochemical pathways relevant to defense against infection. Using chemical class enrichment analysis, for example, we identified changes in a number of host-derived compounds including immune lipids such as prostaglandins, which were detected exclusively upon pathogen challenge. Taken together, our findings indicate that co-culture of B. thailandensis with mammalian cells alters the metabolome of both pathogen and host and provides a new dimension of information for in-depth analysis of the host-pathogen interactions underlying Burkholderia infection.

Spatial bacterial subpopulations of a human lung lobe and their potential impact on the progression of pulmonary tuberculosis

Better understanding the spatial variation in resident pulmonary bacteria can help to link the disease severity of pulmonary tuberculosis (TB) with lung bacteriomes. This study aimed to investigate bacterial compositions in subniches of a lung lobe from pulmonary TB patient with two separate visible lesions. There were no significant differences between the bacterial compositions in normal tissue and TB lesions, but the bacterial compositions of the two TB lesions differed significantly (P = 0.009). Interestingly, 52 OTUs (relative abundance >1%) that specifically inhabiting certain lung niches were observed and they were affiliated with five phyla. Specific OTUs affiliated with Firmicutes mainly inhabited normal tissues. The dominant phylum in the lung subniches was Proteobacteria, with a relative abundance between 67.03% and 99.99%. Ralstonia, Achromobacter, and Pseudomonas were the most abundant genera, collectively accounting for 34.02% of total bacterial species. A total of 667 of the 700 bacterial connections in a co-correlation network of 145 OTUs (Operational Taxonomic Unit) were positive, indicating a cooperative relationship between bacterial members. Using PICRUSt tool, we do predict bacterial MetaCyc functions responsible for lipid synthesis and heme biosynthesis across the lung lobe that are essential for generation of caseous necrosis and TB disease pathology. MetaCyc pathways responsible for the degradation of aromatic biogenic amines, sulfur oxidation, and denitrification were all related to M.tb growth status, and they were significantly enriched in the lesion with necrosis than that with inflammation. These results open a new insight for us to comprehend the spatial profile of bacteriomes in a pulmonary TB human lung lobe, and shed light on the design of future diagnosis and treatment for pulmonary TB disease.

Spatial Metabolomics Reveals Localized Impact of Influenza Virus Infection on the Lung Tissue Metabolome

The influenza virus (IAV) is a major cause of respiratory disease, with significant infection increases in pandemic years. Vaccines are a mainstay of IAV prevention but are complicated by IAV’s vast strain diversity and manufacturing and vaccine uptake limitations. While antivirals may be used for treatment of IAV, they are most effective in early stages of the infection, and several virus strains have become drug resistant. Therefore, there is a need for advances in IAV treatment, especially host-directed therapeutics. Given the spatial dynamics of IAV infection and the relationship between viral spatial distribution and disease severity, a spatial approach is necessary to expand our understanding of IAV pathogenesis. We used spatial metabolomics to address this issue. Spatial metabolomics combines liquid chromatography-tandem mass spectrometry of metabolites extracted from systematic organ sections, 3D models, and computational techniques to develop spatial models of metabolite location and their role in organ function and disease pathogenesis. In this project, we analyzed serum and systematically sectioned lung tissue samples from uninfected or infected mice. Spatial mapping of sites of metabolic perturbations revealed significantly lower metabolic perturbation in the trachea compared to other lung tissue sites. Using random forest machine learning, we identified metabolites that responded differently in each lung position based on infection, including specific amino acids, lipids and lipid-like molecules, and nucleosides. These results support the implementation of spatial metabolomics to understand metabolic changes upon respiratory virus infection.

IMPORTANCE The influenza virus is a major health concern. Over 1 billion people become infected annually despite the wide distribution of vaccines, and antiviral agents are insufficient to address current clinical needs. In this study, we used spatial metabolomics to understand changes in the lung and serum metabolome of mice infected with influenza A virus compared to uninfected controls. We determined metabolites altered by infection in specific lung tissue sites and distinguished metabolites perturbed by infection between lung tissue and serum samples. Our findings highlight the utility of a spatial approach to understanding the intersection between the lung metabolome, viral infection, and disease severity. Ultimately, this approach will expand our understanding of respiratory disease pathogenesis.

Characterization of the Achromobacter xylosoxidans Type VI Secretion System and Its Implication in Cystic Fibrosis

Bacteria of the genus Achromobacter are environmental germs, with an unknown reservoir. It can become opportunistic pathogens in immunocompromised patients, causing bacteremia, meningitis, pneumonia, or peritonitis. In recent years, Achromobacter xylosoxidans has emerged with increasing incidence in patients with cystic fibrosis (CF). Recent studies showed that A. xylosoxidans is involved in the degradation of the respiratory function of patients with CF. The respiratory ecosystem of patients with CF is colonized by bacterial species that constantly fight for space and access to nutrients. The type VI secretion system (T6SS) empowers this constant bacterial antagonism, and it is used as a virulence factor in several pathogenic bacteria. This study aimed to investigate the prevalence of the T6SS genes in A. xylosoxidans isolated in patients with CF. We also evaluated clinical and molecular characteristics of T6SS-positive A. xylosoxidans strains. We showed that A. xylosoxidans possesses a T6SS gene cluster and that some environmental and clinical isolates assemble a functional T6SS nanomachine. A. xylosoxidans T6SS is used to target competing bacteria, including other CF-specific pathogens. Finally, we demonstrated the importance of the T6SS in the internalization of A. xylosoxidans in lung epithelial cells and that the T6SS protein Hcp is detected in the sputum of patients with CF. Altogether, these results suggest for the first time a role of T6SS in CF-lung colonization by A. xylosoxidans and opens promising perspective to target this virulence determinant as innovative theranostic options for CF management.

Phenazines and toxoflavin act as interspecies modulators of resilience to diverse antibiotics

Bacterial opportunistic pathogens make diverse secondary metabolites both in the natural environment and when causing infections, yet how these molecules mediate microbial interactions and their consequences for antibiotic treatment are still poorly understood. Here, we explore the role of three redox-active secondary metabolites, pyocyanin, phenazine-1-carboxylic acid and toxoflavin, as interspecies modulators of antibiotic resilience. We find that these molecules dramatically change susceptibility levels of diverse bacteria to clinical antibiotics. Pyocyanin and phenazine-1-carboxylic acid are made by Pseudomonas aeruginosa, while toxoflavin is made by Burkholderia gladioli, organisms that infect cystic fibrosis and other immunocompromised patients. All molecules alter the susceptibility profile of pathogenic species within the "Burkholderia cepacia complex" to different antibiotics, either antagonizing or potentiating their effects, depending on the drug's class. Defense responses regulated by the redox-sensitive transcription factor SoxR potentiate the antagonistic effects these metabolites have against fluoroquinolones, and the presence of genes encoding SoxR and the efflux systems it regulates can be used to predict how these metabolites will affect antibiotic susceptibility of different bacteria. Finally, we demonstrate that inclusion of secondary metabolites in standard protocols used to assess antibiotic resistance can dramatically alter the results, motivating the development of new tests for more accurate clinical assessment.

Long-Term In Vitro Culture Systems to Study Human Microbiome

Microbial communities are eubiotic ecosystems that interact dynamically and synergistically with the human body. Imbalances in these interactions may cause dysbiosis by enhancing the occurrence of inflammatory conditions, such as periodontal or inflammatory bowel diseases. However, the mechanisms that lie behind eubiosis-dysbiosis transitions are still unclear and constantly being redefined. While the societal impact of these diseases is steadily increasing, the lack of a clear understanding behind the onset of the inflammatory conditions prevents the proper clinical strategies from being formulated. Although preclinical and clinical models and short-term planar in vitro cultures represent superb research tools, they are still lacking human relevance and long-term use. Bioreactors and organs-on-a-chip have attracted interest because of their ability to recreate and sustain the physical, structural, and mechanical features of the native environment, as well as to support long-term coculture of mammalian cells and the microbiome through modulation of pH and oxygen gradients. Existing devices, however, are still under development to sustain the microbiome-host coculture over long periods of time. In this scenario, to understand disease triggers and develop therapeutics, research efforts should command the development of three-dimensional constructs that would allow the investigation of processes underlying the microbial community assembly and how microorganisms influence host traits in both acute and chronic conditions.

Microbial Community Composition in Explanted Cystic Fibrosis and Control Donor Lungs

To date, investigations of the microbiota in the lungs of people with Cystic Fibrosis (PWCF) have primarily focused on microbial community composition in luminal mucus, with fewer studies observing the microbiota in tissue samples from explanted lung tissue. Here, we analysed both tissue and airway luminal mucus samples extracted from whole explanted lungs of PWCF and unused donor lungs. We determined if the lung microbiota in end-stage CF varied within and between patients, was spatially heterogeneous and related to localized structural damage. Microbial community composition was determined by Illumina MiSeq sequencing and related to the CF-Computed Tomography (CT) score and features of end-stage lung disease on micro-CT. Ninety-eight CF tissue (n=11 patients), 20 CF luminal mucus (n=8 patients) and 33 donor tissue (n=4 patients) samples were analysed. Additionally, we compared 20 paired CF tissue and luminal mucus samples that enabled a direct “geographical” comparison of the microbiota in these two niches. Significant differences in microbial communities were apparent between the 3 groups. However, overlap between the three groups, particularly between CF and donor tissue and CF tissue and CF luminal mucus was also observed. Microbial diversity was lower in CF luminal mucus compared to CF tissue, with dominance higher in luminal mucus. For both CF and donor tissue, intra- and inter-patient variability in ecological parameters was observed. No relationships were observed between ecological parameters and CF-CT score, or features of end-stage lung disease. The end-stage CF lung is characterised by a low diversity microbiota, differing within and between individuals. No clear relationship was observed between regional microbiota variation and structural lung damage.

Mass spectrometry-based metabolomics in microbiome investigations

Microbiotas are a malleable part of ecosystems, including the human ecosystem. Microorganisms affect not only the chemistry of their specific niche, such as the human gut, but also the chemistry of distant environments, such as other parts of the body. Mass spectrometry-based metabolomics is one of the key technologies to detect and identify the small molecules produced by the human microbiota, and to understand the functional role of these microbial metabolites. This Review provides a foundational introduction to common forms of untargeted mass spectrometry and the types of data that can be obtained in the context of microbiome analysis. Data analysis remains an obstacle; therefore, the emphasis is placed on data analysis approaches and integrative analysis, including the integration of microbiome sequencing data.

The biogeography of infection revisited

Many microbial communities, including those involved in chronic human infections, are patterned at the micron scale. In this Review, we summarize recent work that has defined the spatial arrangement of microorganisms in infection and begun to demonstrate how changes in spatial patterning correlate with disease. Advances in microscopy have refined our understanding of microbial micron-scale biogeography in samples from humans. These findings then serve as a benchmark for studying the role of spatial patterning in preclinical models, which provide experimental versatility to investigate the interplay between biogeography and pathogenesis. Experimentation using preclinical models has begun to show how spatial patterning influences the interactions between cells, their ability to coexist, their virulence and their recalcitrance to treatment. Future work to study the role of biogeography in infection and the functional biogeography of microorganisms will further refine our understanding of the interplay of spatial patterning, pathogen virulence and disease outcomes.

Advances in Microbiome-Derived Solutions and Methodologies Are Founding a New Era in Skin Health and Care

The microbiome, as a community of microorganisms and their structural elements, genomes, metabolites/signal molecules, has been shown to play an important role in human health, with significant beneficial applications for gut health. Skin microbiome has emerged as a new field with high potential to develop disruptive solutions to manage skin health and disease. Despite an incomplete toolbox for skin microbiome analyses, much progress has been made towards functional dissection of microbiomes and host-microbiome interactions. A standardized and robust investigation of the skin microbiome is necessary to provide accurate microbial information and set the base for a successful translation of innovations in the dermo-cosmetic field. This review provides an overview of how the landscape of skin microbiome research has evolved from method development (multi-omics/data-based analytical approaches) to the discovery and development of novel microbiome-derived ingredients. Moreover, it provides a summary of the latest findings on interactions between the microbiomes (gut and skin) and skin health/disease. Solutions derived from these two paths are used to develop novel microbiome-based ingredients or solutions acting on skin homeostasis are proposed. The most promising skin and gut-derived microbiome interventional strategies are presented, along with regulatory, safety, industrial, and technical challenges related to a successful translation of these microbiome-based concepts/technologies in the dermo-cosmetic industry.

Chestnut polysaccharides restore impaired spermatogenesis by adjusting gut microbiota and the intestinal structure

Our previous study confirmed the beneficial effects of chestnut polysaccharides (CPs) on the spermatogenesis process, but the exact mechanism is not clear. Several studies have demonstrated the importance of balanced gut microbiota in maintaining normal reproductive function. In this study, we investigated the biological functions of CPs from the perspective of gut microbiota function, expecting to find out the specific mechanism of CPs in restoring impaired spermatogenesis. Compared with the control group, the mice treated with busulfan showed a reduced number of germ cells, structural changes in the small intestine and composition alteration in the gut microbiota at several levels, including the phylum and genus. In contrast, the number of germ cells in seminiferous tubules was significantly increased, and the structure of the small intestine and the composition of the gut microbiota were altered in the busulfan-treated mice after the CPs treatment. The 16s rRNA analysis results showed that the Firmicutes was the predominant phylum in all groups followed by Proteobacteria, Bacteroidetes, Actinobacteria, Tenericutes, Cyanobacteria and unidentified bacteria. Interestingly, the subsequent functional analysis implied that the steroid hormone biosynthesis process is the major metabolic pathway in the CPs-mediated restoration process and the experimental results confirmed this speculation. In conclusion, this study confirmed that CPs can restore the impaired spermatogenesis process by adjusting the gut microbiota and intestinal structure, which will also provide technical support and a theoretical basis for the subsequent treatment of male infertility.

Molecular networking in infectious disease models

Small molecule metabolites are the product of many enzymatic reactions. Metabolomics thus opens a window into enzyme activity and function, integrating effects at the post-translational, proteome, transcriptome and genome level. In addition, small molecules can themselves regulate enzyme activity, expression and function both via substrate availability mechanisms and through allosteric regulation. Metabolites are therefore at the nexus of infectious diseases, regulating nutrient availability to the pathogen, immune responses, tropism, and host disease tolerance and resilience. Analysis of metabolomics data is however complex, particularly in terms of metabolite annotation. An emerging valuable approach to extend metabolite annotations beyond existing compound libraries and to identify infection-induced chemical changes is molecular networking. In this chapter, we discuss the applications of molecular networking in the context of infectious diseases specifically, with a focus on considerations relevant to these biological systems.

Sweat metabolomics before and after intravenous antibiotics for pulmonary exacerbation in people with cystic fibrosis

BACKGROUND

People with cystic fibrosis (PWCF) suffer from acute unpredictable reductions in pulmonary function associated with a pulmonary exacerbation (PEx) that may require hospitalization. PEx symptoms vary between PWCF without universal diagnostic criteria for diagnosis and response to treatment.

RESEARCH QUESTION

We characterized sweat metabolomes before and after intravenous (IV) antibiotics in PWCF hospitalized for PEx to determine feasibility and define biological alterations by IV antibiotics for PEx.

STUDY DESIGN AND METHODS

PWCF with PEx requiring hospitalization for IV antibiotics were recruited from clinic. Sweat samples were collected using the Macroduct® Sweat Collection System at admission prior to initiation of IV antibiotics and after completion prior to discharge. Samples were analyzed for metabolite changes using ultra-high-performance liquid chromatography/tandem accurate mass spectrometry.

RESULTS

Twenty-six of 29 hospitalized PWCF completed the entire study. A total of 326 compounds of known identity were detected in sweat samples. Of detected metabolites, 147 were significantly different between pre-initiation and post-completion of IV antibiotics for PEx (average treatment 14 days). Global sweat metabolomes changed from before and after IV antibiotic treatment. We discovered specific metabolite profiles predictive of PEx status as well as enriched biologic pathways associated with PEx. However, metabolomic changes were similar in PWCF who failed to return to baseline pulmonary function and those who did not.

INTERPRETATION

Our findings demonstrate the feasibility of non-invasive sweat metabolomic profiling in PWCF and the potential for sweat metabolomics as a prospective diagnostic and research tool to further advance our understanding of PEx in PWCF.

Cell-Cell Communication Networks in Tissue: Toward Quantitatively Linking Structure with Function

Forefront techniques for molecular interrogation of mammalian tissues, such as multiplexed tissue imaging, intravital microscopy, and single-cell RNA sequencing (scRNAseq), can combine to quantify cell-type abundance, co-localization, and global levels of receptors and their ligands. Nonetheless, it remains challenging to translate these various quantities into a more comprehensive understanding of how cell-cell communication networks dynamically operate. Therefore, construction of computational models for network-level functions - including niche-dependent actions, homeostasis, and multi-scale coordination - will be valuable for productively integrating the battery of experimental approaches. Here, we review recent progress in understanding cell-cell communication networks in tissue. Featured examples include ligand-receptor dissection of immunosuppressive and mitogenic signaling in the tumor microenvironment. As a future direction, we highlight an unmet potential to bridge high-level statistical approaches with low-level physicochemical mechanisms.

Alkyl-Quinolones derivatives as potential biomarkers for Pseudomonas aeruginosa infection chronicity in Cystic Fibrosis

In Cystic Fibrosis (CF), a rapid and standardized definition of chronic infection would allow a better management of Pseudomonas aeruginosa (Pa) infections, as well as a quick grouping of patients during clinical trials allowing better comparisons between studies. With this purpose, we compared the metabolic profiles of 44 in vitro cultures of Pa strains isolated from CF patients at different stages of infection in order to identify metabolites differentially synthetized according to these clinical stages. Compounds produced and secreted by each strain in the supernatant of a liquid culture were analysed by metabolomic approaches (UHPLC-DAD-ESI/QTOF, UV and UPLC-Orbitrap, MS). Multivariate analyses showed that first colonization strains could be differentiated from chronic colonization ones, by producing notably more Alkyl-Quinolones (AQs) derivatives. Especially, five AQs were discriminant: HQC5, HQNOC7, HQNOC7:1, db-PQS C9 and HQNOC9:1. However, the production of HHQ was equivalent between strain types. The HHQ/HQNOC9:1 ratio was then found to be significantly different between chronic and primo-colonising strains by using both UV (p = 0.003) and HRMS data (p = 1.5 × 10^-5). Our study suggests that some AQ derivatives can be used as biomarkers for an improved management of CF patients as well as a better definition of the clinical stages of Pa infection.

The Lung Microbiome during Health and Disease

Healthy human lungs have traditionally been considered to be a sterile organ. However, culture-independent molecular techniques have reported that large numbers of microbes coexist in the lung and airways. The lungs harbor diverse microbial composition that are undetected by previous approaches. Many studies have found significant differences in microbial composition between during health and respiratory disease. The lung microbiome is likely to not only influence susceptibility or causes of diseases but be affected by disease activities or responses to treatment. Although lung microbiome research has some limitations from study design to reporting, it can add further dimensionality to host-microbe interactions. Moreover, there is a possibility that extending understanding to the lung microbiome with new multiple omics approaches would be useful for developing both diagnostic and prognostic biomarkers for respiratory diseases in clinical settings.

The cystic fibrosis lung microenvironment alters antibiotic activity: causes and effects

Chronic airway colonisation by Pseudomonas aeruginosa, a hallmark of cystic fibrosis (CF) lung disease, is associated with increased morbidity and mortality and despite aggressive antibiotic treatment, P. aeruginosa is able to persist in CF airways. In vitro antibiotic susceptibility assays are poor predictors of antibiotic efficacy to treat respiratory tract infections in the CF patient population and the selection of the antibiotic(s) is often made on an empirical base. In the current review, we discuss the factors that are responsible for the discrepancies between antibiotic activity in vitro and clinical efficacy in vivo We describe how the CF lung microenvironment, shaped by host factors (such as iron, mucus, immune mediators and oxygen availability) and the microbiota, influences antibiotic activity and varies widely between patients. A better understanding of the CF microenvironment and population diversity may thus help improve in vitro antibiotic susceptibility testing and clinical decision making, in turn increasing the success rate of antibiotic treatment.

Biogeographical Landscape of the Human Face Skin Microbiome Viewed in High Definition

The bacterial community that colonizes the human face imparts physiochemical and physiological effects on the facial skin. These skin-microbe interactions impact dermatological, cosmetic and skincare applications due to the centrality of the human face in daily interactions. However, fine-scale characterization of the human face skin microbiome is lacking. Using 16S rRNA sequencing and 3D cartography, this study plotted and characterized the facial skin microbiome in high-definition, based on 1,649 samples from 12 individuals. Analysis yielded a number of novel insights, including that of the relative uniformity of skin microbiome composition within skin sites, site localization of certain microbes, and the interpersonal variability of the skin microbiome. The results show that high-resolution topographical mapping of the skin microbiome is a powerful tool for studying the human skin microbiome. Despite a decade of skin microbiome research, there is still much to be discovered.

Impact of artificial sputum media formulation on Pseudomonas aeruginosa secondary metabolite production

In vitro culture media are being developed to understand how host site-specific nutrient profiles influence microbial pathogenicity and ecology. To mimic the cystic fibrosis (CF) lung environment, a variety of artificial sputum media (ASM) have been created. However, the composition of these ASM vary in the concentration of key nutrients, including amino acids, lipids, DNA, and mucin. In this work, we used feature-based molecular networking (FBMN) to perform comparative metabolomics of Pseudomonas aeruginosa, the predominant opportunistic pathogen infecting the lungs of people with CF, cultured in nine different ASM. We found that the concentration of aromatic amino acids and iron from mucin added to the media contributes to differences in the production of P. aeruginosa virulence-associated secondary metabolites.

IMPORTANCE Different media formulations aiming to replicate in vivo infection environments contain different nutrients, which affects interpretation of experimental results. Inclusion of undefined components, such as commercial porcine gastric mucin (PGM), in an otherwise chemically defined medium can alter the nutrient content of the medium in unexpected ways and influence experimental outcomes.

The lung microbiome: progress and promise

The healthy lung was long thought of as sterile, but recent advances using molecular sequencing approaches have detected bacteria at low levels. Healthy lung bacteria largely reflect communities present in the upper respiratory tract that enter the lung via microaspiration, which is balanced by mechanical and immune clearance and likely involves limited local replication. The nature and dynamics of the lung microbiome, therefore, differ from those of ecological niches with robust self-sustaining microbial communities. Aberrant populations (dysbiosis) have been demonstrated in many pulmonary diseases not traditionally considered microbial in origin, and potential pathways of microbe-host crosstalk are emerging. The question now is whether and how dysbiotic microbiota contribute to initiation or perpetuation of injury. The fungal microbiome and virome are less well studied. This Review highlights features of the lung microbiome, unique considerations in studying it, examples of dysbiosis in selected disease, emerging concepts in lung microbiome-host interactions, and critical areas for investigation.

mSphere of Influence: Forgotten Questions

Laura-Isobel McCall studies the relationship between location and disease pathogenesis, with a focus on infectious diseases and neglected diseases of poverty. In this mSphere of Influence article, she reflects on how three papers, "Opposing effects of fasting metabolism on tissue tolerance in bacterial and viral inflammation" (A. Wang, S. C. Huen, H. H. Luan, S. Yu, et al., Cell 166:1512-1525.e12, 2016, https://doi.org/10.1016/j.cell.2016.07.026), "Three-dimensional microbiome and metabolome cartography of a diseased human lung" (N. Garg, M. Wang, E. Hyde, R. R. da Silva, et al., Cell Host Microbe 22:705-716.e4, 2017, https://doi.org/10.1016/j.chom.2017.10.001), and "'It's like a phantom disease': patient perspectives on access to treatment for Chagas disease in the United States" (C. J. Forsyth, S. Hernandez, C. A. Flores, M. F. Roman, et al., Am J Trop Med Hyg 98:735-741, 2018, https://doi.org/10.4269/ajtmh.17-0691), shaped her spatial approach to infectious disease pathogenesis and helped her broaden her perspective from a pathogen-centric focus to a holistic view that include diseases tolerance mechanisms and barriers to health care access.

Breath-Based Diagnosis of Infectious Diseases: A Review of the Current Landscape

Various analytical methods can be applied to concentrate, separate, and examine trace volatile organic metabolites in the breath, with the potential for noninvasive, rapid, real-time identification of various disease processes, including an array of microbial infections. Although biomarker discovery and validation in microbial infections can be technically challenging, it is an approach that has shown great promise, especially for infections that are particularly difficult to identify with standard culture and molecular amplification-based approaches. This article discusses the current state of breath analysis for the diagnosis of infectious diseases.

Recent progress in analyzing the spatial structure of the human microbiome: distinguishing biogeography and architecture in the oral and gut communities

Fueled by technological advances in methods for sample collection and preservation in sequencing studies, and in advances in computational analyses of high content image data, the spatial structure of the human microbiome is coming to light. In this mini-review, we summarize recent developments in our understanding of the structure of two human microbiomes: the lower gut and the oral cavity. We focus on only the most recent literature and we make an important distinction between two forms of spatial structure, governed by scale: biogeography and architecture. By segmenting the study of microbiome spatial structure into two categories, we demonstrate the potential to greatly advance our understanding of the mechanistic principles that link structure and function in the microbiome.

Cross-species RNA-seq for deciphering host-microbe interactions

The human body is constantly exposed to microorganisms, which entails manifold interactions between human cells and diverse commensal or pathogenic bacteria. The cellular states of the interacting cells are decisive for the outcome of these encounters such as whether bacterial virulence programmes and host defence or tolerance mechanisms are induced. This Review summarizes how next-generation RNA sequencing (RNA-seq) has become a primary technology to study host-microbe interactions with high resolution, improving our understanding of the physiological consequences and the mechanisms at play. We illustrate how the discriminatory power and sensitivity of RNA-seq helps to dissect increasingly complex cellular interactions in time and space down to the single-cell level. We also outline how future transcriptomics may answer currently open questions in host-microbe interactions and inform treatment schemes for microbial disorders.

Liquid Chromatography Mass Spectrometry Detection of Antibiotic Agents in Sputum from Persons with Cystic Fibrosis

Antibiotic therapy is expected to impact host microbial communities considerably, yet many studies focused on microbiome and health are often confounded by limited information about antibiotic exposure. Given that antibiotics have diverse pharmacokinetic and antimicrobial properties, investigating the type and concentration of these agents in specific host specimens would provide much needed insight into their impact on the microbes therein. Here, we developed liquid chromatography mass spectrometry (LC-MS) methods to detect 18 antibiotic agents in sputum from persons with cystic fibrosis. Antibiotic spike-in control samples were used to compare three liquid extraction methods on the Waters Acquity Quattro Premier XE. Extraction with dithiothreitol captured the most antibiotics and was used to detect antibiotics in sputum samples from 11 people with cystic fibrosis, with results being compared to the individuals' self-reported antibiotic use. For the sputum samples, two LC-MS assays were used; the Quattro Premier detected nanomolar or micromolar concentrations of 16 antibiotics, whereas the Xevo TQ-XS detected all 18 antibiotics, most at subnanomolar levels. In 45% of tested sputum samples (71/158), at least one antibiotic that was not reported by the subject was detected by both LC-MS methods, a discordance largely explained by the thrice weekly administration and long half-life of azithromycin. For ∼37% of samples, antibiotics reported as taken by the individual were not detected by either instrument. Our results provide an approach for detecting a variety of antibiotics at the site of infection, thereby providing a means to include antibiotic usage data into microbiome studies.

Ecological Succession of Polymicrobial Communities in the Cystic Fibrosis Airways

Antimicrobial therapies against cystic fibrosis (CF) lung infections are largely aimed at the traditional, well-studied CF pathogens such as Pseudomonas aeruginosa and Burkholderia cepacia complex, despite the fact that the CF lung harbors a complex and dynamic polymicrobial community. A clinical focus on the dominant pathogens ignores potentially important community-level interactions in disease pathology, perhaps explaining why these treatments are often less effective than predicted based on in vitro testing.

Antimicrobial therapies against cystic fibrosis (CF) lung infections are largely aimed at the traditional, well-studied CF pathogens such as Pseudomonas aeruginosa and Burkholderia cepacia complex, despite the fact that the CF lung harbors a complex and dynamic polymicrobial community. A clinical focus on the dominant pathogens ignores potentially important community-level interactions in disease pathology, perhaps explaining why these treatments are often less effective than predicted based on in vitro testing. A better understanding of the ecological dynamics of this ecosystem may enable clinicians to harness these interactions and thereby improve treatment outcomes. Like all ecosystems, the CF lung microbial community develops through a series of stages, each of which may present with distinct microbial communities that generate unique host-microbe and microbe-microbe interactions, metabolic profiles, and clinical phenotypes. While insightful models have been developed to explain some of these stages and interactions, there is no unifying model to describe how these infections develop and persist. Here, we review current perspectives on the ecology of the CF airway and present the CF Ecological Succession (CFES) model that aims to capture the spatial and temporal complexity of CF lung infection, address current challenges in disease management, and inform the development of ecologically driven therapeutic strategies.

Metabolites from Microbes Isolated from the Skin of the Panamanian Rocket Frog Colostethus panamansis (Anura: Dendrobatidae)

The Panamanian rocket frog Colostethus panamansis (family Dendrobatidae) has been affected by chytridiomycosis, a deadly disease caused by the fungus Batrachochytrium dendrobatidis (Bd). While there are still uninfected frogs, we set out to isolate microbes from anatomically distinct regions in an effort to create a cultivable resource within Panama for potential drug/agricultural/ecological applications that perhaps could also be used as part of a strategy to protect frogs from infections. To understand if there are specific anatomies that should be explored in future applications of this resource, we mapped skin-associated bacteria of C. panamansis and their metabolite production potential by mass spectrometry on a 3D model. Our results indicate that five bacterial families (Enterobacteriaceae, Comamonadaceae, Aeromonadaceae, Staphylococcaceae and Pseudomonadaceae) dominate the cultivable microbes from the skin of C. panamansis. The combination of microbial classification and molecular analysis in relation to the anti-Bd inhibitory databases reveals the resource has future potential for amphibian conservation.

Host and Pathogen Communication in the Respiratory Tract: Mechanisms and Models of a Complex Signaling Microenvironment

Chronic lung diseases are a leading cause of morbidity and mortality across the globe, encompassing a diverse range of conditions from infections with pathogenic microorganisms to underlying genetic disorders. The respiratory tract represents an active interface with the external environment having the primary immune function of resisting pathogen intrusion and maintaining homeostasis in response to the myriad of stimuli encountered within its microenvironment. To perform these vital functions and prevent lung disorders, a chemical and biological cross-talk occurs in the complex milieu of the lung that mediates and regulates the numerous cellular processes contributing to lung health. In this review, we will focus on the role of cross-talk in chronic lung infections, and discuss how different cell types and signaling pathways contribute to the chronicity of infection(s) and prevent effective immune clearance of pathogens. In the lung microenvironment, pathogens have developed the capacity to evade mucosal immunity using different mechanisms or virulence factors, leading to colonization and infection of the host; such mechanisms include the release of soluble and volatile factors, as well as contact dependent (juxtracrine) interactions. We explore the diverse modes of communication between the host and pathogen in the lung tissue milieu in the context of chronic lung infections. Lastly, we review current methods and approaches used to model and study these host-pathogen interactions in vitro, and the role of these technological platforms in advancing our knowledge about chronic lung diseases.

Metabolomics profiling of tobacco exposure in children with cystic fibrosis

BACKGROUND

Inflammation is integral to early disease progression in children with CF. The effect of modifiable environmental factors on infection and inflammation in persons with CF is poorly understood. Our prior studies determined that secondhand smoke exposure (SHSe) is highly prevalent in young children with CF. SHSe is associated with increased inflammation, heightened bacterial burden, and worsened clinical outcomes. However, the specific metabolite and signaling pathways that regulate responses to SHSe in CF are relatively unknown.

METHODS

High-resolution metabolomics was performed on plasma samples from infants (n = 25) and children (n = 40) with CF compared to non-CF controls (n = 15). CF groups were stratified according to infant or child age and SHSe status.

RESULTS

Global metabolomic profiles segregated by age and SHSe status. SHSe in CF was associated with changes in pathways related to steroid biosynthesis, fatty acid metabolism, cysteine metabolism, and oxidative stress. CF infants with SHSe demonstrated enrichment for altered metabolite localization to the small intestine, liver, and striatum. CF children with SHSe demonstrated metabolite enrichment for organs/tissues associated with oxidative stress including mitochondria, peroxisomes, and the endoplasmic reticulum. In a confirmatory analysis, SHSe was associated with changes in biomarkers of oxidative stress and cellular adhesion including MMP-9, MPO, and ICAM-1.

CONCLUSIONS

SHSe in young children and infants with CF is associated with altered global metabolomics profiles and specific biochemical pathways, including enhanced oxidative stress. SHSe remains an important but understudied modifiable variable in early CF disease.

Single-cell reporters for pathogen responses to antimicrobial host attacks

Host-pathogen interactions are often heterogeneous involving individual encounters between host and pathogen cells with diverse molecular mechanisms, response networks, and diverging outcomes. Single-cell reporters can identify the various types of interactions and participating pathogen subsets, help to unravel underlying molecular mechanism, and determine individual outcomes and their impact on disease progression. In this review, we discuss reporters-based on fluorescent proteins. We present different types of reporters and their experimental advantages and challenges, and describe how different strategies can interrogate exposure to antimicrobial host mechanism, pathogen response, inflicted damage, and impact on pathogen fitness at the single-cell level. We find many gaps in available tools but also exciting avenues to address these issues.

Microbial and chemical dynamics of a toxic dinoflagellate bloom

Harmful Algal Blooms (HABs) exert considerable ecological and economic damage and are becoming increasingly frequent worldwide. However, the biological factors underlying HABs remain uncertain. Relationships between algae and bacteria may contribute to bloom formation, strength, and duration. We investigated the microbial communities and metabolomes associated with a HAB of the toxic dinoflagellate Karenia brevis off the west coast of Florida in June 2018. Microbial communities and intracellular metabolite pools differed based on both bacterial lifestyle and bloom level, suggesting a complex role for blooms in reshaping microbial processes. Network analysis identified K. brevis as an ecological hub in the planktonic ecosystem, with significant connections to diverse microbial taxa. These included four flavobacteria and one sequence variant unidentified past the domain level, suggesting uncharacterized diversity in phytoplankton-associated microbial communities. Additionally, intracellular metabolomic analyses associated high K. brevis levels with higher levels of aromatic compounds and lipids. These findings reveal water column microbial and chemical characteristics with potentially important implications for understanding HAB onset and duration.

Bacterial Quorum Sensing During Infection

Bacteria are highly interactive and possess an extraordinary repertoire of intercellular communication and social behaviors, including quorum sensing (QS). QS has been studied in detail at the molecular level, so mechanistic details are well understood in many species and are often involved in virulence. The use of different animal host models has demonstrated QS-dependent control of virulence determinants and virulence in several human pathogenic bacteria. QS also controls virulence in several plant pathogenic species. Despite the role QS plays in virulence during animal and plant laboratory-engineered infections, QS mutants are frequently isolated from natural infections, demonstrating that the function of QS during infection and its role in pathogenesis remain poorly understood and are fruitful areas for future research. We discuss the role of QS during infection in various organisms and highlight approaches to better understand QS during human infection. This is an important consideration in an era of growing antimicrobial resistance, when we are looking for new ways to target bacterial infections.

Surface sensing triggers a broad-spectrum antimicrobial response in Pseudomonas aeruginosa

Interspecies bacterial competition may occur via cell‐associated or secreted determinants and is key to successful niche colonization. We previously evolved Pseudomonas aeruginosa in the presence of Staphylococcus aureus and identified mutations in the Wsp surface‐sensing signalling system. Surprisingly, a ΔwspF mutant, characterized by increased c‐di‐GMP levels and biofilm formation capacity, showed potent killing activity towards S. aureus in its culture supernatant. Here, we used an unbiased metabolomic analysis of culture supernatants to identify rhamnolipids, alkyl quinoline N‐oxides and two siderophores as members of four chemical clusters, which were more abundant in the ΔwspF mutant supernatants. Killing activities were quorum‐sensing controlled but independent of c‐di‐GMP levels. Based on the metabolomic analysis, we formulated a synthetic cocktail of four compounds, showing broad‐spectrum anti‐bacterial killing, including both Gram‐positive and Gram‐negative bacteria. The combination of quorum‐sensing‐controlled killing and Wsp‐system mediated biofilm formation endows P. aeruginosa with capacities essential for niche establishment and host colonization.

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

Microbial diversity in the cystic fibrosis (CF) lung decreases over decades as pathogenic bacteria such as Pseudomonas aeruginosa 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] r ² = 0.79, P < 0.001), we observed significant intraindividual temporal variation that was highest during clinical stability (linear mixed-effects [LME] model, P = 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 (n = 14 days) during the development of a CFPE (LME P = 0.0045 and P = 0.029, respectively). Collectively, comparing samples across disease states showed there was a reduction of these two measures during antibiotic treatment (LME P = 0.0096 and P = 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 P = 0.0085), but no consistent metabolite signatures of CFPE across subjects were identified. Virulence-associated metabolites from P. aeruginosa 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% Pseudomonas 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.IMPORTANCE 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 P. aeruginosa 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.

Achromobacter xylosoxidans Cellular Pathology Is Correlated with Activation of a Type III Secretion System

Achromobacter xylosoxidans is increasingly recognized as a colonizer of cystic fibrosis (CF) patients, but the role that A. xylosoxidans plays in pathology remains unknown. This knowledge gap is largely due to the lack of model systems available to study the toxic potential of this bacterium. Recently, a phospholipase A₂ (PLA₂) encoded by a majority of A. xylosoxidans genomes, termed AxoU, was identified. Here, we show that AxoU is a type III secretion system (T3SS) substrate that induces cytotoxicity to mammalian cells. A tissue culture model was developed showing that a subset of A. xylosoxidans isolates from CF patients induce cytotoxicity in macrophages, suggestive of a pathogenic or inflammatory role in the CF lung. In a toxic strain, cytotoxicity is correlated with transcriptional activation of axoU and T3SS genes, demonstrating that this model can be used as a tool to identify and track expression of virulence determinants produced by this poorly understood bacterium.

A multiomic analysis of in situ coral-turf algal interactions

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.

Reproducible molecular networking of untargeted mass spectrometry data using GNPS

Global Natural Product Social Molecular Networking (GNPS) is an interactive online small molecule-focused tandem mass spectrometry (MS2) data curation and analysis infrastructure. It is intended to provide as much chemical insight as possible into an untargeted MS2 dataset and to connect this chemical insight to the user's underlying biological questions. This can be performed within one liquid chromatography (LC)-MS2 experiment or at the repository scale. GNPS-MassIVE is a public data repository for untargeted MS2 data with sample information (metadata) and annotated MS2 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 MS2 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.

Chemical Mechanisms of Colonization Resistance by the Gut Microbial Metabolome

The gut microbiome, the collection of 100 trillion microorganisms that resides in the intestinal lumen, plays major roles in modulating host physiology. One well-established function of the gut microbiota is that of colonization resistance or the ability of the microbial collective to protect the host against enteric pathogens. Although evidence suggests that these microbes may outcompete some pathogens, there remains a lack of mechanistic understanding that underlies this competitive exclusion. In recent years, there has been great interest in small-molecule metabolites that are produced by the gut microbiota and in understanding how these molecules regulate host-pathogen interactions. In this review, we briefly summarize these findings by focusing on several classes of metabolites that mediate this important process. Understanding these host-microbe interactions in the gut may lead to identification of potential candidates for the development of prophylactics and therapeutics for many infectious diseases that are impacted by the gut microbiome.

The Microbiome in Cystic Fibrosis Pulmonary Disease

Cystic fibrosis (CF) is a genetic disease with mutational changes leading to profound dysbiosis, both pulmonary and intestinal, from a very young age. This dysbiosis plays an important role in clinical manifestations, particularly in the lungs, affected by chronic infection. The range of microbiological tools has recently been enriched by metagenomics based on next-generation sequencing (NGS). Currently applied essentially in a gene-targeted manner, metagenomics has enabled very exhaustive description of bacterial communities in the CF lung niche and, to a lesser extent, the fungi. Aided by progress in bioinformatics, this now makes it possible to envisage shotgun sequencing and opens the door to other areas of the microbial world, the virome, and the archaeome, for which almost everything remains to be described in cystic fibrosis. Paradoxically, applying NGS in microbiology has seen a rebirth of bacterial culture, but in an extended manner (culturomics), which has proved to be a perfectly complementary approach to NGS. Animal models have also proved indispensable for validating microbiome pathophysiological hypotheses. Description of pathological microbiomes and correlation with clinical status and therapeutics (antibiotic therapy, cystic fibrosis transmembrane conductance regulator (CFTR) modulators) revealed the richness of microbiome data, enabling description of predictive and follow-up biomarkers. Although monogenic, CF is a multifactorial disease, and both genotype and microbiome profiles are crucial interconnected factors in disease progression. Microbiome-genome interactions are thus important to decipher.