Mechanistic model of Rothia mucilaginosa adaptation toward persistence in the CF lung, based on a genome reconstructed from metagenomic data

Genome-scale model of Rothia mucilaginosa predicts gene essentialities and reveals metabolic capabilities

Cystic fibrosis (CF), an inherited genetic disorder caused by mutations in the cystic fibrosis transmembrane conductance regulator gene, results in sticky and thick mucosal fluids. This environment facilitates the colonization of various microorganisms, some of which can cause acute and chronic lung infections, while others may positively impact the disease. Rothia mucilaginosa, an oral commensal, is relatively abundant in the lungs of CF patients. Recent studies have unveiled its anti-inflammatory properties using in vitro three-dimensional lung epithelial cell cultures and in vivo mouse models relevant to chronic lung diseases. Apart from this, R. mucilaginosa has been associated with severe infections. However, its metabolic capabilities and genotype-phenotype relationships remain largely unknown. To gain insights into its cellular metabolism and genetic content, we developed the first manually curated genome-scale metabolic model, iRM23NL. Through growth kinetics and high-throughput phenotypic microarray testings, we defined its complete catabolic phenome. Subsequently, we assessed the model's effectiveness in accurately predicting growth behaviors and utilizing multiple substrates. We used constraint-based modeling techniques to formulate novel hypotheses that could expedite the development of antimicrobial strategies. More specifically, we detected putative essential genes and assessed their effect on metabolism under varying nutritional conditions. These predictions could offer novel potential antimicrobial targets without laborious large-scale screening of knockouts and mutant transposon libraries. Overall, iRM23NL demonstrates a solid capability to predict cellular phenotypes and holds immense potential as a valuable resource for accurate predictions in advancing antimicrobial therapies. Moreover, it can guide metabolic engineering to tailor R. mucilaginosa's metabolism for desired performance.IMPORTANCECystic fibrosis (CF) is a genetic disorder characterized by thick mucosal secretions, leading to chronic lung infections. Rothia mucilaginosa is a common bacterium found in various parts of the human body, acting as a normal part of the flora. In people with weakened immune systems, it can become an opportunistic pathogen, while it is prevalent and active in CF airways. Recent studies have highlighted its anti-inflammatory properties in the lower pulmonary system, indicating the intricate relationship between microbes and human health. Herein, we have developed the first manually curated metabolic model of R. mucilaginosa. Our study examined the previously unknown relationships between the bacterium's genotype and phenotype and identified essential genes that impact the metabolism under various conditions. With this, we opt for paving the way for developing new strategies in antimicrobial therapy and metabolic engineering, leading to enhanced therapeutic outcomes in cystic fibrosis and related conditions.

Comparison of metagenomic and traditional methods for diagnosis of E. coli enteric infections

Diarrheagenic Escherichia coli, collectively known as DEC, is a leading cause of diarrhea, particularly in children in low- and middle-income countries. Diagnosing infections caused by different DEC pathotypes traditionally relies on the cultivation and identification of virulence genes, a resource-intensive and error-prone process. Here, we compared culture-based DEC identification with shotgun metagenomic sequencing of whole stool using 35 randomly drawn samples from a cohort of diarrhea-afflicted patients. Metagenomic sequencing detected the cultured isolates in 97% of samples, revealing, overall, reliable detection by this approach. Genome binning yielded high-quality E. coli metagenome-assembled genomes (MAGs) for 13 samples, and we observed that the MAG did not carry the diagnostic DEC virulence genes of the corresponding isolate in 60% of these samples. Specifically, two distinct scenarios were observed: diffusely adherent E. coli (DAEC) isolates without corresponding DAEC MAGs appeared to be relatively rare members of the microbiome, which was further corroborated by quantitative PCR (qPCR), and thus unlikely to represent the etiological agent in 3 of the 13 samples (~23%). In contrast, ETEC virulence genes were located on plasmids and largely escaped binning in associated MAGs despite being prevalent in the sample (5/13 samples or ~38%), revealing limitations of the metagenomic approach. These results provide important insights for diagnosing DEC infections and demonstrate how metagenomic methods can complement isolation efforts and PCR for pathogen identification and population abundance.

IMPORTANCE

Diagnosing enteric infections based on traditional methods involving isolation and PCR can be erroneous due to isolation and other biases, e.g., the most abundant pathogen may not be recovered on isolation media. By employing shotgun metagenomics together with traditional methods on the same stool samples, we show that mixed infections caused by multiple pathogens are much more frequent than traditional methods indicate in the case of acute diarrhea. Further, in at least 8.5% of the total samples examined, the metagenomic approach reliably identified a different pathogen than the traditional approach. Therefore, our results provide a methodology to complement existing methods for enteric infection diagnostics with cutting-edge, culture-independent metagenomic techniques, and highlight the strengths and limitations of each approach.

New Phage-Derived Antibacterial Enzyme PolaR Targeting Rothia spp

Rothia is an opportunistic pathogen, particularly life-threatening for the immunocompromised. It is associated with pneumonia, endocarditis, peritonitis and many other serious infections, including septicemia. Of note, Rothia mucilaginousa produces metabolites that support and increase overgrowth of Pseudomonas aeruginosa, one of the ESKAPE bacteria. Endolysins are considered as antibacterial enzymes derived from bacteriophages that selectively and efficiently kill susceptible bacteria without harming human cells or the normal microbiome. Here, we applied a computational analysis of metagenomic sequencing data of the gastric mucosa phageome extracted from human patients' stomach biopsies. A selected candidate anti-Rothia sequence was produced in an expression system, purified and confirmed as a Rothia mucilaginosa- and Rothia dentocariosa-specific endolysin PolaR, able to destroy bacterial cells even when aggregated, as in a biofilm. PolaR had no cytotoxic or antiproliferative effects on mammalian cells. PolaR is the first described endolysin selectively targeting Rothia species, with a high potential to combat infections caused by Rothia mucilaginosa and Rothia dentocariosa, and possibly other bacterial groups. PolaR is the first antibacterial enzyme selected from the gastric mucosa phageome, which underlines the biological complexity and probably underestimated biological role of the phageome in the human gastric mucosa.

Constructing a full, multiple-layer interactome for SARS-CoV-2 in the context of lung disease: Linking the virus with human genes and microbes

The COVID-19 pandemic caused by the SARS-CoV-2 virus has resulted in millions of deaths worldwide. The disease presents with various manifestations that can vary in severity and long-term outcomes. Previous efforts have contributed to the development of effective strategies for treatment and prevention by uncovering the mechanism of viral infection. We now know all the direct protein-protein interactions that occur during the lifecycle of SARS-CoV-2 infection, but it is critical to move beyond these known interactions to a comprehensive understanding of the "full interactome" of SARS-CoV-2 infection, which incorporates human microRNAs (miRNAs), additional human protein-coding genes, and exogenous microbes. Potentially, this will help in developing new drugs to treat COVID-19, differentiating the nuances of long COVID, and identifying histopathological signatures in SARS-CoV-2-infected organs. To construct the full interactome, we developed a statistical modeling approach called MLCrosstalk (multiple-layer crosstalk) based on latent Dirichlet allocation. MLCrosstalk integrates data from multiple sources, including microbes, human protein-coding genes, miRNAs, and human protein-protein interactions. It constructs "topics" that group SARS-CoV-2 with genes and microbes based on similar patterns of co-occurrence across patient samples. We use these topics to infer linkages between SARS-CoV-2 and protein-coding genes, miRNAs, and microbes. We then refine these initial linkages using network propagation to contextualize them within a larger framework of network and pathway structures. Using MLCrosstalk, we identified genes in the IL1-processing and VEGFA-VEGFR2 pathways that are linked to SARS-CoV-2. We also found that Rothia mucilaginosa and Prevotella melaninogenica are positively and negatively correlated with SARS-CoV-2 abundance, a finding corroborated by analysis of single-cell sequencing data.

Impact of Cesarean Delivery and Breastfeeding on Secretory Immunoglobulin A in the Infant Gut Is Mediated by Gut Microbiota and Metabolites

How gut immunity in early life is shaped by birth in relation to delivery mode, intrapartum antibiotic prophylaxis (IAP) and labor remains undetermined. We aimed to address this gap with a study of secretory Immunoglobulin A (SIgA) in the infant gut that also tested SIgA-stimulating pathways mediated by gut microbiota and metabolites. Among 1017 Canadian full-term infants, gut microbiota of fecal samples collected at 3 and 12 months were profiled using 16S rRNA sequencing; C. difficile was quantified by qPCR; fecal metabolites and SIgA levels were measured by NMR and SIgA enzyme-linked immunosorbent assay, respectively. We assessed the putative causal relationships from birth events to gut microbiota and metabolites, and ultimately to SIgA, in statistical sequential mediation models, adjusted for maternal gravida status in 551 infants. As birth mode influences the ability to breastfeed, the statistical mediating role of breastfeeding status and milk metabolites was also evaluated. Relative to vaginal birth without maternal IAP, cesarean section (CS) after labor was associated with reduced infant gut SIgA levels at 3 months (6.27 vs. 4.85 mg/g feces, p < 0.05); this association was sequentially mediated through gut microbiota and metabolites of microbial or milk origin. Mediating gut microbiota included Enterobacteriaceae, C. difficile, and Streptococcus. The milk or microbial metabolites in CS-SIgA mediating pathways were galactose, fucose, GABA, choline, lactate, pyruvate and 1,2-propanediol. This cohort study documented the impact of birth on infant gut mucosal SIgA. It is the first to characterize gut microbe-metabolite mediated pathways for early-life SIgA maturation, pathways that require experimental verification.

Development of an in vitro homeostasis model between airway epithelial cells, bacteria and bacteriophages: a time-lapsed observation of cell viability and inflammatory response

Bacteriophages represent the most extensive group of viruses within the human virome and have a significant impact on general health and well-being by regulating bacterial population dynamics. Staphylococcus aureus, found in the anterior nostrils, throat and skin, is an opportunistic pathobiont that can cause a wide range of diseases, from chronic inflammation to severe and acute infections. In this study, we developed a human cell-based homeostasis model between a clinically isolated strain of S. aureus 141 and active phages for this strain (PYO^Sa141) isolated from the commercial Pyophage cocktail (PYO). The cocktail is produced by Eliava BioPreparations Ltd. (Tbilisi, Georgia) and is used as an add-on therapy for bacterial infections, mainly in Georgia. The triptych interaction model was evaluated by time-dependent analysis of cell death and inflammatory response of the nasal and bronchial epithelial cells. Inflammatory mediators (IL-8, CCL5/RANTES, IL-6 and IL-1β) in the culture supernatants were measured by enzyme-linked immunosorbent assay and cell viability was determined by crystal violet staining. By measuring trans-epithelial electrical resistance, we assessed the epithelial integrity of nasal cells that had differentiated under air-liquid interface conditions. PYO^Sa141 was found to have a prophylactic effect on airway epithelial cells exposed to S. aureus 141 by effectively down-regulating bacterial-induced inflammation, cell death and epithelial barrier disruption in a time-dependent manner. Overall, the proposed model represents an advance in the way multi-component biological systems can be simulated in vitro.

How Metagenomics Has Transformed Our Understanding of Bacteriophages in Microbiome Research

The microbiome is an essential part of most ecosystems. It was originally studied mostly through culturing but relatively few microbes can be cultured, so much of the microbiome was left unexplored. The emergence of metagenomic sequencing techniques changed that and allowed the study of microbiomes from all sorts of habitats. Metagenomic sequencing also allowed for a more thorough exploration of prophages, viruses that integrate into bacterial genomes, and how they benefit their hosts. One issue with using open-access metagenomic data is that sequences added to databases often have little to no metadata to work with, so finding enough sequences can be difficult. Many metagenomes have been manually curated but this is a time-consuming process and relies heavily on the uploader to be accurate and thorough when filling in metadata fields and the curators to be working with the same ontologies. Using algorithms to automatically sort metagenomes based on either the taxonomic profile or the functional profile may be a viable solution to the issues with manually curated metagenomes, but it requires that the algorithm is trained on carefully curated datasets and using the most informative profile possible in order to minimize errors.

Next-generation microbial drugs developed from microbiome's natural products

Scientists working in natural products chemistry have been enticed by the current advancements being made in the discovery of novel "magic bullets" from microbes homed to all conceivable environments. Even though researchers continue to face challenges funneling the novel bioactive compounds in the global therapeutic industries, it seems most likely that the discovery of some "hit molecules" with significant biomedical applications is not that far. We applaud novel natural products for their ability to combat the spread of superbugs and aid in the prevention of currently observed antibiotic resistance. This in-depth investigation covers a wide range of microbiomes with a proclivity for synthesizing novel compounds to combat the spread of superbugs. Furthermore, we use this opportunity to explore various groups of secondary metabolites and their biosynthetic pathways in various microbiota found in mammals, insects, and humans. This systematic study, when taken as a whole, offers detail understanding on the biomedical fate of various groups of compounds originated from diverse microbiomes. For gathering all information that has been uncovered and released so far, we have also presented the huge diversity of microbes that are associated with humans and their metabolic products. To conclude, this concrete review suggests novel ideas that will prove immensely helpful in reducing the danger posed by superbugs while also improving the efficacy of antibiotics.

Multi-Omics Study of Keystone Species in a Cystic Fibrosis Microbiome

Ecological networking and in vitro studies predict that anaerobic, mucus-degrading bacteria are keystone species in cystic fibrosis (CF) microbiomes. The metabolic byproducts from these bacteria facilitate the colonization and growth of CF pathogens like Pseudomonas aeruginosa. Here, a multi-omics study informed the control of putative anaerobic keystone species during a transition in antibiotic therapy of a CF patient. A quantitative metagenomics approach combining sequence data with epifluorescence microscopy showed that during periods of rapid lung function loss, the patient's lung microbiome was dominated by the anaerobic, mucus-degrading bacteria belonging to Streptococcus, Veillonella, and Prevotella genera. Untargeted metabolomics and community cultures identified high rates of fermentation in these sputa, with the accumulation of lactic acid, citric acid, and acetic acid. P. aeruginosa utilized these fermentation products for growth, as indicated by quantitative transcriptomics data. Transcription levels of P. aeruginosa genes for the utilization of fermentation products were proportional to the abundance of anaerobic bacteria. Clindamycin therapy targeting Gram-positive anaerobes rapidly suppressed anaerobic bacteria and the accumulation of fermentation products. Clindamycin also lowered the abundance and transcription of P. aeruginosa, even though this patient's strain was resistant to this antibiotic. The treatment stabilized the patient's lung function and improved respiratory health for two months, lengthening by a factor of four the between-hospitalization time for this patient. Killing anaerobes indirectly limited the growth of P. aeruginosa by disrupting the cross-feeding of fermentation products. This case study supports the hypothesis that facultative anaerobes operated as keystone species in this CF microbiome. Personalized multi-omics may become a viable approach for routine clinical diagnostics in the future, providing critical information to inform treatment decisions.

Rothia mucilaginosa is an anti-inflammatory bacterium in the respiratory tract of patients with chronic lung disease

Background

Chronic airway inflammation is the main driver of pathogenesis in respiratory diseases such as severe asthma, chronic obstructive pulmonary disease, cystic fibrosis (CF) and bronchiectasis. While the role of common pathogens in airway inflammation is widely recognised, the influence of other microbiota members is still poorly understood.

Methods

We hypothesised that the lung microbiota contains bacteria with immunomodulatory activity which modulate net levels of immune activation by key respiratory pathogens. Therefore, we assessed the immunomodulatory effect of several members of the lung microbiota frequently reported as present in CF lower respiratory tract samples.

Results

We show that Rothia mucilaginosa, a common resident of the oral cavity that is also often detectable in the lower airways in chronic disease, has an inhibitory effect on pathogen- or lipopolysaccharide-induced pro-inflammatory responses, in vitro (three-dimensional cell culture model) and in vivo (mouse model). Furthermore, in a cohort of adults with bronchiectasis, the abundance of Rothia species was negatively correlated with pro-inflammatory markers (interleukin (IL)-8 and IL-1β) and matrix metalloproteinase (MMP)-1, MMP-8 and MMP-9 in sputum. Mechanistic studies revealed that R. mucilaginosa inhibits NF-κB pathway activation by reducing the phosphorylation of IκBα and consequently the expression of NF-κB target genes.

Conclusions

These findings indicate that the presence of R. mucilaginosa in the lower airways potentially mitigates inflammation, which could in turn influence the severity and progression of chronic respiratory disorders.

A commensal bacterium of the lower airways, Rothia mucilaginosa, inhibits inflammation by NF-κB pathway inactivation. R. mucilaginosa abundance inversely correlates with sputum pro-inflammatory markers in chronic lung disease, indicating a beneficial role.https://bit.ly/3lNT9th

Citizen-science based study of the oral microbiome in Cystic fibrosis and matched controls reveals major differences in diversity and abundance of bacterial and fungal species

Introduction: Cystic fibrosis (CF) is an autosomal genetic disease, associated with the production of excessively thick mucosa and with life-threatening chronic lung infections. The microbiota of the oral cavity can act as a reservoir or as a barrier for infectious microorganisms that can colonize the lungs. However, the specific composition of the oral microbiome in CF is poorly understood.Methods: In collaboration with CF associations in Spain, we collected oral rinse samples from 31 CF persons (age range 7-47) and matched controls, and then performed 16S rRNA metabarcoding and high-throughput sequencing, combined with culture and proteomics-based identification of fungi to survey the bacterial and fungal oral microbiome.Results: We found that CF is associated with less diverse oral microbiomes, which were characterized by higher prevalence of Candida albicans and differential abundances of a number of bacterial taxa that have implications in both the connection to lung infections in CF, as well as potential oral health concerns, particularly periodontitis and dental caries.Conclusion: Overall, our study provides a first global snapshot of the oral microbiome in CF. Future studies are required to establish the relationships between the composition of the oral and lung microbiomes in CF.

The porcine corneal surface bacterial microbiome: A distinctive niche within the ocular surface

Purpose

The ocular surface microbiome has been described as paucibacterial. Until now, studies investigating the bacterial community associated with the ocular surface through high-throughput sequencing have focused on the conjunctiva. Conjunctival samples are thought to reflect and be representative of the microbiome residing on the ocular surface, including the cornea. Here, we hypothesized that the bacterial community associated with the corneal surface was different from those of the inferonasal and superotemporal conjunctival fornices, and from the tear film.

Methods

Both eyes from 15 healthy piglets were sampled using swabs (inferonasal fornix, superotemporal fornix, and corneal surface, n = 30 each) and Schirmer tear test strips (STT, n = 30). Negative sampling controls (swabs and STT, n = 2 each) and extraction controls (n = 4) were included. Total DNA was extracted and high-throughput sequencing targeting the 16S rRNA gene was performed. Bioinformatic analyses included multiple contamination-controlling steps.

Results

Corneal surface samples had a significantly lower number of taxa detected (P<0.01) and were compositionally different from all other sample types (Bray-Curtis dissimilarity, P<0.04). It also harbored higher levels of Proteobacteria (P<0.05), specifically Brevundimonas spp. (4.1-fold) and Paracoccus spp. (3.4-fold) than other sample types. Negative control STT strip samples yielded the highest amount of 16S rRNA gene copies across all sample types (P<0.05).

Conclusions

Our data suggests that the corneal surface provides a distinct environmental niche within the ocular surface, leading to a bacterial community compositionally different from all other sample types.

Interactions of Bacteriophages and Bacteria at the Airway Mucosa: New Insights Into the Pathophysiology of Asthma

The airway epithelium is the primary site where inhaled and resident microbiota interacts between themselves and the host, potentially playing an important role on allergic asthma development and pathophysiology. With the advent of culture independent molecular techniques and high throughput technologies, the complex composition and diversity of bacterial communities of the airways has been well-documented and the notion of the lungs' sterility definitively rejected. Recent studies indicate that the microbial composition of the asthmatic airways across the spectrum of disease severity, differ significantly compared with healthy individuals. In parallel, a growing body of evidence suggests that bacterial viruses (bacteriophages or simply phages), regulating bacterial populations, are present in almost every niche of the human body and can also interact directly with the eukaryotic cells. The triptych of airway epithelial cells, bacterial symbionts and resident phages should be considered as a functional and interdependent unit with direct implications on the respiratory and overall homeostasis. While the role of epithelial cells in asthma pathophysiology is well-established, the tripartite interactions between epithelial cells, bacteria and phages should be scrutinized, both to better understand asthma as a system disorder and to explore potential interventions.

Bacterial Interference With Lactate Dehydrogenase Assay Leads to an Underestimation of Cytotoxicity

Models to study host-pathogen interactions in vitro are an important tool for investigating the infectious disease process and evaluating the efficacy of antimicrobial compounds. In these models, the viability of mammalian cells is often determined using the lactate dehydrogenase (LDH) cytotoxicity assay. In the present study we evaluated whether bacteria could interfere with the LDH assay. As a model for host-pathogen interactions, we co-cultured lung epithelial cells with eight bacteria encountered in the lower respiratory tract. We show that LDH activity is affected by Pseudomonas aeruginosa, Klebsiella pneumoniae, Stenotrophomonas maltophilia, and Streptococcus pneumoniae, and that this depends on the density of the start inoculum and the duration of infection. Two different mechanisms were discovered through which bacteria interfered with LDH activity, i.e., acidification of the cell culture medium (by K. pneumoniae and S. pneumoniae) and protease production (by P. aeruginosa and S. maltophilia). In addition, we developed and validated a modified protocol to evaluate cytotoxicity using the LDH assay, where bacterial interference with LDH quantification is avoided.

Commensal Oral Rothia mucilaginosa Produces Enterobactin, a Metal-Chelating Siderophore

Next-generation sequencing studies of saliva and dental plaque from subjects in both healthy and diseased states have identified bacteria belonging to the Rothia genus as ubiquitous members of the oral microbiota. To gain a deeper understanding of molecular mechanisms underlying the chemical ecology of this unexplored group, we applied a genome mining approach that targets functionally important biosynthetic gene clusters (BGCs). All 45 genomes that were mined, representing Rothia mucilaginosa, Rothia dentocariosa, and Rothia aeria, harbored a catechol-siderophore-like BGC. To explore siderophore production further, we grew the previously characterized R. mucilaginosa ATCC 25296 in liquid cultures, amended with glycerol, which led to the identification of the archetype siderophore enterobactin by using tandem liquid chromatography-mass spectrometry (LC-MS/MS), high-performance liquid chromatography (HPLC), and nuclear magnetic resonance (NMR) spectroscopy. Normally attributed to pathogenic gut bacteria, R. mucilaginosa is the first commensal oral bacterium found to produce enterobactin. Cocultivation studies including R. mucilaginosa or purified enterobactin revealed that enterobactin reduced growth of certain strains of cariogenic Streptococcus mutans and pathogenic strains of Staphylococcus aureus Commensal oral bacteria were either unaffected, reduced in growth, or induced to grow adjacent to enterobactin-producing R. mucilaginosa or the pure compound. Taken together with Rothia's known capacity to ferment a variety of carbohydrates and amino acids, our findings of enterobactin production add an additional level of explanation to R. mucilaginosa's prevalence in the oral cavity. Enterobactin is the strongest Fe(III) binding siderophore known, and its role in oral health requires further investigation.IMPORTANCE The communication language of the human oral microbiota is vastly underexplored. However, a few studies have shown that specialized small molecules encoded by BGCs have critical roles such as in colonization resistance against pathogens and quorum sensing. Here, by using a genome mining approach in combination with compound screening of growth cultures, we identified that the commensal oral community member R. mucilaginosa harbors a catecholate-siderophore BGC, which is responsible for the biosynthesis of enterobactin. The iron-scavenging role of enterobactin is known to have positive effects on the host's iron pool and negative effects on host immune function; however, its role in oral health remains unexplored. R. mucilaginosa was previously identified as an abundant community member in cystic fibrosis, where bacterial iron cycling plays a major role in virulence development. With respect to iron's broad biological importance, iron-chelating enterobactin may explain R. mucilaginosa's colonization success in both health and disease.

Saliva Microbiome Changes in Patients With Periodontitis With and Without Chronic Obstructive Pulmonary Disease

Objective: The oral microbiota plays a key part in the initial colonization by pathogens and the chronic inflammatory reaction of the host. We measured variations in the salivary microbiota and evaluated their potential associations with periodontitis and chronic obstructive pulmonary disease (COPD).

Methods: We investigated the salivary microbiota of patients with COPD and periodontitis (n = 21) compared with that in patients with periodontitis alone (n = 36) and with healthy controls (HCs; n = 14), using pyrosequencing of polymerase chain reaction-amplified 16s rRNA genes.

Results: Bacterial richness and diversity were significantly higher in patients suffering from COPD, and the bacterial family Lachnospiraceae was observed frequently only among patients with COPD and periodontitis. Veillonella, Rothia, Actinomyces, and Fusobacterium were the core bacterial genera that showed significant differences among patients with coincident COPD and periodontitis, patients with periodontitis alone, and HCs (p < 0.05). Veillonella, Rothia, and Actinomyces were observed much more frequently in patients with COPD and periodontitis, compared with that in HCs. All tested populations were divided into subgroups based on sex, smoking, or periodontitis index. In the subgroup with a bleeding index >2, Rothia was significantly different in periodontitis with and without COPD groups compared with HCs. In the subgroup with a plaque index >2.5, Rothia and Veillonella showed significant differences in periodontitis with and without COPD groups compared with HCs.

Conclusion: Variations in salivary microbiota may be associated with COPD and periodontitis.

Influence of the lung microbiome on antibiotic susceptibility of cystic fibrosis pathogens

The lungs of patients with cystic fibrosis (CF) are colonised by a microbial community comprised of pathogenic species, such as Pseudomonas aeruginosa and Staphylococcus aureus, and microorganisms that are typically not associated with worse clinical outcomes (considered as commensals). Antibiotics directed at CF pathogens are often not effective and a discrepancy is observed between activity of these agents in vitro and in the patient. This review describes how interspecies interactions within the lung microbiome might influence the outcome of antibiotic treatment targeted at common CF pathogens. Protective mechanisms by members of the microbiome such as antibiotic degradation (indirect pathogenicity), alterations of the cell wall, production of matrix components decreasing antibiotic penetration, and changes in metabolism are discussed. Interspecies interactions that increase bacterial susceptibility are also addressed. Furthermore, we discuss how experimental conditions, such as culture media, oxygen levels, incorporation of host–pathogen interactions, and microbial community composition may influence the outcome of microbial interaction studies related to antibiotic activity. Hereby, the importance to create in vitro conditions reflective of the CF lung microenvironment is highlighted. Understanding the role of the CF lung microbiome in antibiotic efficacy may help find novel therapeutic and diagnostic approaches to better tackle chronic lung infections in this patient population.

Interspecies interactions in the lung microbiome may influence the outcome of antibiotic treatment targeted at cystic fibrosis pathogenshttp://bit.ly/2WQp0iQ

Antibiotic resistance genes in the Actinobacteria phylum

The Actinobacteria phylum is one of the oldest bacterial phyla that have a significant role in medicine and biotechnology. There are a lot of genera in this phylum that are causing various types of infections in humans, animals, and plants. As well as antimicrobial agents that are used in medicine for infections treatment or prevention of infections, they have been discovered of various genera in this phylum. To date, resistance to antibiotics is rising in different regions of the world and this is a global health threat. The main purpose of this review is the molecular evolution of antibiotic resistance in the Actinobacteria phylum.

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

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 Escherichia coli. The incorporation of the CFRR within the CF clinic could increase the life span and quality of life of CF patients.

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 Escherichia coli (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.

Characterization of Microbiota in Bronchiectasis Patients with Different Disease Severities

The applications of the 16S rRNA gene pyrosequencing has expanded our knowledge of the respiratory tract microbiome originally obtained using conventional, culture-based methods. In this study, we employed DNA-based molecular techniques for examining the sputum microbiome in bronchiectasis patients, in relation to disease severity. Of the sixty-three study subjects, forty-two had mild and twenty-one had moderate or severe bronchiectasis, which was classified by calculating the FACED score, based on the FEV₁ (forced expiratory volume in 1 s, %) (F, 0–2 points), age (A, 0–2 points), chronic colonization by Pseudomonas aeruginosa (C, 0–1 point), radiographic extension (E, 0–1 point), and dyspnoea (D, 0–1 point). Bronchiectasis was defined as mild, at 0–2 points, moderate at 3–4 points, and severe at 5–7 points. The mean age was 68.0 ± 9.3 years; thirty-three patients were women. Haemophilus (p = 0.005) and Rothia (p = 0.043) were significantly more abundant in the mild bronchiectasis group, whereas Pseudomonas (p = 0.031) was significantly more abundant in the moderate or severe group. However, in terms of the alpha and beta diversity, the sputum microbiota of the two groups did not significantly differ, i.e., the same dominant genera were found in all samples. Further large-scale studies are needed to investigate the sputum microbiome in bronchiectasis.

Cystic fibrosis respiratory microbiota: unraveling complexity to inform clinical practice

INTRODUCTION

Cystic fibrosis (CF) lung disease is characterized by chronic cycles of pulmonary infection, inflammation, and mucus obstruction, beginning early in life, and eventually leading to progressive lung damage and early mortality. During the past ~15 years, culture-independent analyses of CF respiratory samples have identified diverse bacterial communities in CF airways, and relationships between respiratory microbiota and clinical outcomes. Areas covered: This paper reviews recent advances in our understanding of the relationships between respiratory microbiota and CF lung disease. The paper focuses on measures of airway bacterial community diversity and estimates of the relative abundance of anaerobic species. Finally, this paper will review the opportunities for advancing patient care suggested by these studies and highlight some of the ongoing challenges and unmet needs in translating this knowledge into clinical practice. Expert commentary: Culture-independent analyses of respiratory microbiota have suggested new strategies for advancing CF care, but have also highlighted challenges in understanding the complexity of CF respiratory infections. Development of more sophisticated models and analytic approaches to better account for this complexity are needed to elucidate mechanistic links between CF respiratory microbiota and clinical outcomes, and to ultimately translate this knowledge into better patient care.

Marked Response in Microbial Community and Metabolism in the Ileum and Cecum of Suckling Piglets After Early Antibiotics Exposure

In modern swine husbandry systems, antibiotics have been used as growth promoters for piglets during suckling or weaning period. However, while early colonization of intestinal microbiota has been regarded crucial for the host’s later life performance and well-being, little is known about the impact of antibiotics on intestinal microbiota in suckling piglets. The present study aimed to investigate the effects of early antibiotics exposure on gut microbiota and microbial metabolism of suckling piglets. Sixteen litters of suckling piglets were fed a creep feed diet with (Antibiotic) or without (Control) antibiotics from postnatal days 7–23 (n = 8). The ileal and cecal digesta were obtained for microbial composition and microbial metabolites analysis. The results showed that the antibiotics significantly altered the bacterial community composition by decreasing (P < 0.05) the diversity and richness in the ileum. The antibiotics significantly reduced the abundance of Lactobacillus in both the ileum and cecum, increased the abundance of Streptococcus, unclassified Enterococcaceae, unclassified Fusobacteriales, and Corynebacterium in the ileum, and the abundance of unclassified Ruminococcaceae and unclassified Erysipelotrichaceae in the cecum. The antibiotics decreased (P < 0.05) ileal lactate concentration and cecal concentration of total short-chain fatty acids (SCFAs). But the antibiotics enhanced protein fermentation (P < 0.05) in the ileum and cecum, as ileal concentrations of putrescine and cadaverine, and cecal concentrations of isobutyrate, isovalerate, putrescine, cadaverine, spermine, and spermidine were significantly increased (P < 0.05). These results indicated that early antibiotics exposure significantly altered the microbial composition of suckling piglets toward a vulnerable and unhealthy gut environment. The findings provide a new insight on the antibiotics impact on neonates and may provide new framework for designing alternatives to the antibiotics toward a healthy practice for suckling piglets.

Tracking Polymicrobial Metabolism in Cystic Fibrosis Airways: Pseudomonas aeruginosa Metabolism and Physiology Are Influenced by Rothia mucilaginosa-Derived Metabolites

Pseudomonas aeruginosa is a dominant and persistent cystic fibrosis pathogen. Although P. aeruginosa is accompanied by other microbes in the airways of cystic fibrosis patients, few cystic fibrosis studies show how P. aeruginosa is affected by the metabolism of other bacteria. Here, we demonstrate that P. aeruginosa generates primary metabolites using substrates produced by another microbe that is prevalent in the airways of cystic fibrosis patients, Rothia mucilaginosa. These results indicate that P. aeruginosa may get a metabolic boost from its microbial neighbor, which might contribute to its pathogenesis in the airways of cystic fibrosis patients.

Due to a lack of effective immune clearance, the airways of cystic fibrosis patients are colonized by polymicrobial communities. One of the most widespread and destructive opportunistic pathogens is Pseudomonas aeruginosa; however, P. aeruginosa does not colonize the airways alone. Microbes that are common in the oral cavity, such as Rothia mucilaginosa, are also present in cystic fibrosis patient sputum and have metabolic capacities different from those of P. aeruginosa. Here we examine the metabolic interactions of P. aeruginosa and R. mucilaginosa using stable-isotope-assisted metabolomics. Glucose-derived ¹³C was incorporated into glycolysis metabolites, namely, lactate and acetate, and some amino acids in R. mucilaginosa grown aerobically and anaerobically. The amino acid glutamate was unlabeled in the R. mucilaginosa supernatant but incorporated the ¹³C label after P. aeruginosa was cross-fed the R. mucilaginosa supernatant in minimal medium and artificial-sputum medium. We provide evidence that P. aeruginosa utilizes R. mucilaginosa-produced metabolites as precursors for generation of primary metabolites, including glutamate.

IMPORTANCEPseudomonas aeruginosa is a dominant and persistent cystic fibrosis pathogen. Although P. aeruginosa is accompanied by other microbes in the airways of cystic fibrosis patients, few cystic fibrosis studies show how P. aeruginosa is affected by the metabolism of other bacteria. Here, we demonstrate that P. aeruginosa generates primary metabolites using substrates produced by another microbe that is prevalent in the airways of cystic fibrosis patients, Rothia mucilaginosa. These results indicate that P. aeruginosa may get a metabolic boost from its microbial neighbor, which might contribute to its pathogenesis in the airways of cystic fibrosis patients.

Airway microbial metagenomics

High-throughput untargeted metagenome sequencing provides information about the composition of the microbial communities of viruses, bacteria, archaea and unicellular eukaryotes in the habitat of interest. This review outlines the sampling, processing, sequencing and bioinformatic analysis of secretions of the respiratory tract and summarizes our current knowledge of the upper and lower human airways metagenome in health and disease.

Airway microbiome research: a modern perspective on surveillance cultures?

The incidence of ventilator-associated pneumonia (VAP) is estimated to be around 10% in a high-risk population. Over the last decade, major improvements have been made in the prevention of VAP, with great cost-effectiveness. However, we still do not understand the exact pathogenesis of VAP. A better understanding might explain why some patients develop ventilator-associated tracheobronchitis, while others develop VAP even though they are infected with the same types of pathogens. Microbiome research has been a hot topic in translational medicine over the past decade. Slowly, microbiome research has also been introduced to the intensive care setting. One of the areas where it may influence our pathophysiological considerations is in VAP. The adapted island has been proposed for the colonization and infection of the respiratory tract. In this model, not only the immigration of bacteria into the lung is important, but elimination and regional growth factors are of equal significance. The importance of these factors can be supported by epidemiological studies. Several small observational studies on the development of the pulmonary microbiome during mechanical ventilation also support this theory. We speculate on the consequences of the newest insights in microbiome research on the prevention and targeted treatment of VAP. We conclude that there is still a strong need for more in-depth analyses of the changes in the microbial composition of the pulmonary microbiome during mechanical ventilation and with the development of VAP.

Stable isotope profiles reveal active production of VOCs from human-associated microbes

Volatile organic compounds (VOCs) measured from exhaled breath have great promise for the diagnosis of bacterial infections. However, determining human or microbial origin of VOCs detected in breath remains a great challenge. For example, the microbial fermentation product 2,3-butanedione was recently found in the breath of Cystic Fibrosis (CF) patients; parallel culture-independent metagenomic sequencing of the same samples revealed that Streptococcus and Rothia spp. have the genetic capacity to produce 2,3-butanedione. To investigate whether the genetic capacity found in metagenomes translates to bacterial production of a VOC of interest such as 2,3-butanedione, we fed stable isotopes to three bacterial strains isolated from patients: two gram-positive bacteria, Rothia mucilaginosa and Streptococcus salivarius, and a dominant opportunistic gram-negative pathogen, Pseudomonas aeruginosa. Culture headspaces were collected and analyzed using a gas chromatographic system to quantify the abundance of VOCs of interest; mass spectroscopy was used to determine whether the stable isotope label had been incorporated. Our results show that R. mucilaginosa and S. salivarius consumed D-Glucose-¹³C₆ to produce labeled 2,3-butanedione. R. mucilaginosa and S. salivarius also produced labeled acetaldehyde and ethanol when grown with ²H₂O. Additionally, we find that P. aeruginosa growth and dimethyl sulfide production are increased when exposed to lactic acid in culture. These results highlight the importance VOCs produced by P. aeruginosa, R. mucilaginosa, and S. salivarius as nutrients and signals in microbial communities, and as potential biomarkers in a CF infection.

Piggyback-the-Winner in host-associated microbial communities

Phages can exploit their bacterial hosts by lytic infection, when many viral particles are released at cell lysis, or by lysogeny, when phages integrate into the host's genome. We recently proposed a new dynamic model of bacteria-phage interactions in which lysogeny predominates at high microbial abundance and growth rates. This model, named Piggyback-the-Winner (PtW), contrasts to current accepted models on the frequency of lysis and lysogeny and predicts that phages integrate into their hosts' genomes as prophages when microbial abundances and growth rates are high. According to PtW, switching to the temperate life cycle reduces phage predation control on bacterial abundance and confers superinfection exclusion, preventing that a closely-related phage infects the same bacterial cell. Here we examine how PtW is important for metazoans. Specifically, we postulate that PtW and the recently described bacteriophage adherence to mucus (BAM) model are strongly interrelated and have an important role in the development of the microbiome. In BAM, phage produced by the microbiome attach to mucins and protect underlying epithelial cells from invading bacteria. Spatial structuring of the mucus creates a gradient of phage replication strategies consistent with PtW. We predict that lysogeny is favored at the top mucosal layer and lytic predation predominates in the bacteria-sparse intermediary layers. The lysogeny confers competitive advantage to commensals against niche invasion and the lytic infection eliminates potential pathogens from deeper mucus layers.

Analysis of Lung Microbiota in Bronchoalveolar Lavage, Protected Brush and Sputum Samples from Subjects with Mild-To-Moderate Cystic Fibrosis Lung Disease

Individuals with cystic fibrosis (CF) often acquire chronic lung infections that lead to irreversible damage. We sought to examine regional variation in the microbial communities in the lungs of individuals with mild-to-moderate CF lung disease, to examine the relationship between the local microbiota and local damage, and to determine the relationships between microbiota in samples taken directly from the lung and the microbiota in spontaneously expectorated sputum. In this initial study, nine stable, adult CF patients with an FEV₁>50% underwent regional sampling of different lobes of the right lung by bronchoalveolar lavage (BAL) and protected brush (PB) sampling of mucus plugs. Sputum samples were obtained from six of the nine subjects immediately prior to the procedure. Microbial community analysis was performed on DNA extracted from these samples and the extent of damage in each lobe was quantified from a recent CT scan. The extent of damage observed in regions of the right lung did not correlate with specific microbial genera, levels of community diversity or composition, or bacterial genome copies per ml of BAL fluid. In all subjects, BAL fluid from different regions of the lung contained similar microbial communities. In eight out of nine subjects, PB samples from different regions of the lung were also similar in microbial community composition, and were similar to microbial communities in BAL fluid from the same lobe. Microbial communities in PB samples were more diverse than those in BAL samples, suggesting enrichment of some taxa in mucus plugs. To our knowledge, this study is the first to examine the microbiota in different regions of the CF lung in clinically stable individuals with mild-to-moderate CF-related lung disease.

Dysbiotic gut microbiome: A key element of Crohn's disease

Since the first publication on "regional ileitis", the relevance of this chronic inflammatory disease condition termed finally as Crohn's disease is continuously increasing. Although we are beginning to comprehend certain aspects of its pathogenesis, many facets remain unexplored. Host's gut microbiota is involved in a wide range of physiological and pathological processes including immune system development, and pathogen regulation. Further, the microbiome is thought to play a key role in Crohn's disease. The presence of Crohn's-associated variants of NOD2 and ATG16L genes appears to be associated not only with alterations of mucosal barrier functions, and bacterial killing, but the gut microbiota, as well, reflecting a potential relationship between the host's genotype and intestinal dysbiosis, involved in disease etiology. This review aims to characterize some exciting new aspect of Crohn's disease pathology, focusing mainly on the role of intestinal microbes, and their interplay with the immune system of the host.

Cystic fibrosis lung microbiome: opportunities to reconsider management of airway infection

The importance of infection in the pathogenesis of cystic fibrosis (CF) lung disease has been long recognized, and the use of antibiotics targeting bacteria identified in cultures of respiratory specimens has played a critical role in improving outcomes for individuals with CF. Over the past ∼15 years, the use of culture-independent methods to assess airway microbiology in CF has revealed complex and dynamic CF airway bacterial communities. Recent areas of investigation of the CF lung microbiome have included exploring how bacterial community structures change over time, particularly with respect to disease progression or pulmonary exacerbation, and in response to antibiotic therapies. This review will discuss what has been learned from these studies as well as how these findings offer opportunities to further refine management of CF airway infection.

Complete Genome Sequence of Rothia mucilaginosa Strain NUM-Rm6536, Isolated from a Human Oral Cavity

Here, we present the complete genome sequence of Rothia mucilaginosa NUM-Rm6536, a strain isolated from the tongue plaque of a healthy human adult. This strain is amenable to genetic manipulation by transformation and so provides a useful foundation for more detailed investigation of this species.

Changes in cystic fibrosis airway microbial community associated with a severe decline in lung function

Cystic fibrosis (CF) is a genetic disease resulting in chronic polymicrobial infections of the airways and progressive decline in lung function. To gain insight into the underlying causes of severe lung diseases, we aimed at comparing the airway microbiota detected in sputum of CF patients with stable lung function (S) versus those with a substantial decline in lung function (SD). Microbiota composition was investigated by using culture-based and culture-independent methods, and by performing multivariate and statistical analyses. Culture-based methods identified some microbial species associated with a worse lung function, i.e. Pseudomonas aeruginosa, Rothia mucilaginosa, Streptococcus pneumoniae and Candida albicans, but only the presence of S. pneumoniae and R. mucilaginosa was found to be associated with increased severe decline in forced expiratory volume in 1 second (FEV₁). Terminal-Restriction Fragment Length Polymorphism (T-RFLP) analysis revealed a higher bacterial diversity than that detected by culture-based methods. Molecular signatures with a statistically significant odds ratio for SD status were detected, and classified as Pseudomonas, Burkholderia and Shewanella, while for other Terminal Restriction Fragments (T-RFs) no species assignation was achieved. The analysis of T-RFLP data using ecological biodiversity indices showed reduced Evenness in SD patients compared to S ones, suggesting an impaired ecology of the bacterial community in SD patients. Statistically significant differences of the ecological biodiversity indices among the three sub-groups of FEV₁ (normal/mild vs moderate vs severe) were also found, suggesting that the patients with moderate lung disease experienced changes in the airway assembly of taxa. Overall, changes in CF airway microbial community associated with a severe lung function decline were detected, allowing us to define some discriminatory species as well as some discriminatory T-RFs that represent good candidates for the development of predictive biomarkers of substantial decline in lung function.

A Winogradsky-based culture system shows an association between microbial fermentation and cystic fibrosis exacerbation

There is a poor understanding of how the physiology of polymicrobial communities in cystic fibrosis (CF) lungs contributes to pulmonary exacerbations and lung function decline. In this study, a microbial culture system based on the principles of the Winogradsky column (WinCF system) was developed to study the physiology of CF microbes. The system used glass capillary tubes filled with artificial sputum medium to mimic a clogged airway bronchiole. Chemical indicators were added to observe microbial physiology within the tubes. Characterization of sputum samples from seven patients showed variation in pH, respiration, biofilm formation and gas production, indicating that the physiology of CF microbial communities varied among patients. Incubation of homogenized tissues from an explant CF lung mirrored responses of a Pseudomonas aeruginosa pure culture, supporting evidence that end-stage lungs are dominated by this pathogen. Longitudinal sputum samples taken through two exacerbation events in a single patient showed that a two-unit drop in pH and a 30% increase in gas production occurred in the tubes prior to exacerbation, which was reversed with antibiotic treatment. Microbial community profiles obtained through amplification and sequencing of the 16S rRNA gene showed that fermentative anaerobes became more abundant during exacerbation and were then reduced during treatment where P. aeruginosa became the dominant bacterium. Results from the WinCF experiments support the model where two functionally different CF microbial communities exist, the persistent Climax Community and the acute Attack Community. Fermentative anaerobes are hypothesized to be the core members of the Attack Community and production of acidic and gaseous products from fermentation may drive developing exacerbations. Treatment targeting the Attack Community may better resolve exacerbations and resulting lung damage.

Purifying the impure: sequencing metagenomes and metatranscriptomes from complex animal-associated samples

The accessibility of high-throughput sequencing has revolutionized many fields of biology. In order to better understand host-associated viral and microbial communities, a comprehensive workflow for DNA and RNA extraction was developed. The workflow concurrently generates viral and microbial metagenomes, as well as metatranscriptomes, from a single sample for next-generation sequencing. The coupling of these approaches provides an overview of both the taxonomical characteristics and the community encoded functions. The presented methods use Cystic Fibrosis (CF) sputum, a problematic sample type, because it is exceptionally viscous and contains high amount of mucins, free neutrophil DNA, and other unknown contaminants. The protocols described here target these problems and successfully recover viral and microbial DNA with minimal human DNA contamination. To complement the metagenomics studies, a metatranscriptomics protocol was optimized to recover both microbial and host mRNA that contains relatively few ribosomal RNA (rRNA) sequences. An overview of the data characteristics is presented to serve as a reference for assessing the success of the methods. Additional CF sputum samples were also collected to (i) evaluate the consistency of the microbiome profiles across seven consecutive days within a single patient, and (ii) compare the consistency of metagenomic approach to a 16S ribosomal RNA gene-based sequencing. The results showed that daily fluctuation of microbial profiles without antibiotic perturbation was minimal and the taxonomy profiles of the common CF-associated bacteria were highly similar between the 16S rDNA libraries and metagenomes generated from the hypotonic lysis (HL)-derived DNA. However, the differences between 16S rDNA taxonomical profiles generated from total DNA and HL-derived DNA suggest that hypotonic lysis and the washing steps benefit in not only removing the human-derived DNA, but also microbial-derived extracellular DNA that may misrepresent the actual microbial profiles.

Specialized metabolites from the microbiome in health and disease

The microbiota, and the genes that comprise its microbiome, play key roles in human health. Host-microbe interactions affect immunity, metabolism, development, and behavior, and dysbiosis of gut bacteria contributes to disease. Despite advances in correlating changes in the microbiota with various conditions, specific mechanisms of host-microbiota signaling remain largely elusive. We discuss the synthesis of microbial metabolites, their absorption, and potential physiological effects on the host. We propose that the effects of specialized metabolites may explain present knowledge gaps in linking the gut microbiota to biological host mechanisms during initial colonization, and in health and disease.

The treatment-naive microbiome in new-onset Crohn's disease

Inflammatory bowel diseases (IBDs), including Crohn's disease (CD), are genetically linked to host pathways that implicate an underlying role for aberrant immune responses to intestinal microbiota. However, patterns of gut microbiome dysbiosis in IBD patients are inconsistent among published studies. Using samples from multiple gastrointestinal locations collected prior to treatment in new-onset cases, we studied the microbiome in the largest pediatric CD cohort to date. An axis defined by an increased abundance in bacteria which include Enterobacteriaceae, Pasteurellacaea, Veillonellaceae, and Fusobacteriaceae, and decreased abundance in Erysipelotrichales, Bacteroidales, and Clostridiales, correlates strongly with disease status. Microbiome comparison between CD patients with and without antibiotic exposure indicates that antibiotic use amplifies the microbial dysbiosis associated with CD. Comparing the microbial signatures between the ileum, the rectum, and fecal samples indicates that at this early stage of disease, assessing the rectal mucosal-associated microbiome offers unique potential for convenient and early diagnosis of CD.

Stochastic tracking of infection in a CF lung

Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) scan are the two ubiquitous imaging sources that physicians use to diagnose patients with Cystic Fibrosis (CF) or any other Chronic Obstructive Pulmonary Disease (COPD). Unfortunately the cost constraints limit the frequent usage of these medical imaging procedures. In addition, even though both CT scan and MRI provide mesoscopic details of a lung, in order to obtain microscopic information a very high resolution is required. Neither MRI nor CT scans provide micro level information about the location of infection in a binary tree structure the binary tree structure of the human lung. In this paper we present an algorithm that enhances the current imaging results by providing estimated micro level information concerning the location of the infection. The estimate is based on a calculation of the distribution of possible mucus blockages consistent with available information using an offline Metropolis-Hastings algorithm in combination with a real-time interpolation scheme. When supplemented with growth rates for the pockets of mucus, the algorithm can also be used to estimate how lung functionality as manifested in spirometric tests will change in patients with CF or COPD.

The upper respiratory tract as a microbial source for pulmonary infections in cystic fibrosis. Parallels from island biogeography

A continuously mixed series of microbial communities inhabits various points of the respiratory tract, with community composition determined by distance from colonization sources, colonization rates, and extinction rates. Ecology and evolution theory developed in the context of biogeography is relevant to clinical microbiology and could reframe the interpretation of recent studies comparing communities from lung explant samples, sputum samples, and oropharyngeal swabs. We propose an island biogeography model of the microbial communities inhabiting different niches in human airways. Island biogeography as applied to communities separated by time and space is a useful parallel for exploring microbial colonization of healthy and diseased lungs, with the potential to inform our understanding of microbial community dynamics and the relevance of microbes detected in different sample types. In this perspective, we focus on the intermixed microbial communities inhabiting different regions of the airways of patients with cystic fibrosis.

Whole genome sequencing of bacteria in cystic fibrosis as a model for bacterial genome adaptation and evolution

Cystic fibrosis (CF) airways harbor a wide variety of new and/or emerging multidrug resistant bacteria which impose a heavy burden on patients. These bacteria live in close proximity with one another, which increases the frequency of lateral gene transfer. The exchange and movement of mobile genetic elements and genomic islands facilitate the spread of genes between genetically diverse bacteria, which seem to be advantageous to the bacterium as it allows adaptation to the new niches of the CF lungs. Niche adaptation is one of the major evolutionary forces shaping bacterial genome composition and in CF the chronic strains adapt and become less virulent. The purpose of this review is to shed light on CF bacterial genome alterations. Next-generation sequencing technology is an exciting tool that may help us to decipher the genome architecture and the evolution of bacteria colonizing CF lungs.

Clinical insights from metagenomic analysis of sputum samples from patients with cystic fibrosis

As DNA sequencing becomes faster and cheaper, genomics-based approaches are being explored for their use in personalized diagnoses and treatments. Here, we provide a proof of principle for disease monitoring using personal metagenomic sequencing and traditional clinical microbiology by focusing on three adults with cystic fibrosis (CF). The CF lung is a dynamic environment that hosts a complex ecosystem composed of bacteria, viruses, and fungi that can vary in space and time. Not surprisingly, the microbiome data from the induced sputum samples we collected revealed a significant amount of species diversity not seen in routine clinical laboratory cultures. The relative abundances of several species changed as clinical treatment was altered, enabling the identification of the climax and attack communities that were proposed in an earlier work. All patient microbiomes encoded a diversity of mechanisms to resist antibiotics, consistent with the characteristics of multidrug-resistant microbial communities that are commonly observed in CF patients. The metabolic potentials of these communities differed by the health status and recovery route of each patient. Thus, this pilot study provides an example of how metagenomic data might be used with clinical assessments for the development of treatments tailored to individual patients.