Gut microbiota modulates adoptive cell therapy via CD8α dendritic cells and IL-12

Adoptive T cell therapy (ACT) is a promising new modality for malignancies. Here, we report that adoptive T cell efficacy in tumor-bearing mice is significantly affected by differences in the native composition of the gut microbiome or treatment with antibiotics, or by heterologous fecal transfer. Depletion of bacteria with vancomycin decreased the rate of tumor growth in mice from The Jackson Laboratory receiving ACT, whereas treatment with neomycin and metronidazole had no effect, indicating the role of specific bacteria in host response. Vancomycin treatment induced an increase in systemic CD8α+ DCs, which sustained systemic adoptively transferred antitumor T cells in an IL-12-dependent manner. In subjects undergoing allogeneic hematopoietic cell transplantation, we found that oral vancomycin also increased IL-12 levels. Collectively, our findings demonstrate an important role played by the gut microbiota in the antitumor effectiveness of ACT and suggest potentially new avenues to improve response to ACT by altering the gut microbiota.

A role for bacterial urease in gut dysbiosis and Crohn's disease

Gut dysbiosis during inflammatory bowel disease involves alterations in the gut microbiota associated with inflammation of the host gut. We used a combination of shotgun metagenomic sequencing and metabolomics to analyze fecal samples from pediatric patients with Crohn's disease and found an association between disease severity, gut dysbiosis, and bacterial production of free amino acids. Nitrogen flux studies using 15N in mice showed that activity of bacterial urease, an enzyme that releases ammonia by hydrolysis of host urea, led to the transfer of murine host-derived nitrogen to the gut microbiota where it was used for amino acid synthesis. Inoculation of a conventional murine host (pretreated with antibiotics and polyethylene glycol) with commensal Escherichia coli engineered to express urease led to dysbiosis of the gut microbiota, resulting in a predominance of Proteobacteria species. This was associated with a worsening of immune-mediated colitis in these animals. A potential role for altered urease expression and nitrogen flux in the development of gut dysbiosis suggests that bacterial urease may be a potential therapeutic target for inflammatory bowel diseases.

Association Between Breast Milk Bacterial Communities and Establishment and Development of the Infant Gut Microbiome

IMPORTANCE

Establishment of the infant microbiome has lifelong implications on health and immunity. Gut microbiota of breastfed compared with nonbreastfed individuals differ during infancy as well as into adulthood. Breast milk contains a diverse population of bacteria, but little is known about the vertical transfer of bacteria from mother to infant by breastfeeding.

OBJECTIVE

To determine the association between the maternal breast milk and areolar skin and infant gut bacterial communities.

DESIGN, SETTING, AND PARTICIPANTS

In a prospective, longitudinal study, bacterial composition was identified with sequencing of the 16S ribosomal RNA gene in breast milk, areolar skin, and infant stool samples of 107 healthy mother-infant pairs. The study was conducted in Los Angeles, California, and St Petersburg, Florida, between January 1, 2010, and February 28, 2015.

EXPOSURES

Amount and duration of daily breastfeeding and timing of solid food introduction.

MAIN OUTCOMES AND MEASURES

Bacterial composition in maternal breast milk, areolar skin, and infant stool by sequencing of the 16S ribosomal RNA gene.

RESULTS

In the 107 healthy mother and infant pairs (median age at the time of specimen collection, 40 days; range, 1-331 days), 52 (43.0%) of the infants were male. Bacterial communities were distinct in milk, areolar skin, and stool, differing in both composition and diversity. The infant gut microbial communities were more closely related to an infant's mother's milk and skin compared with a random mother (mean difference in Bray-Curtis distances, 0.012 and 0.014, respectively; P < .001 for both). Source tracking analysis was used to estimate the contribution of the breast milk and areolar skin microbiomes to the infant gut microbiome. During the first 30 days of life, infants who breastfed to obtain 75% or more of their daily milk intake received a mean (SD) of 27.7% (15.2%) of the bacteria from breast milk and 10.3% (6.0%) from areolar skin. Bacterial diversity (Faith phylogenetic diversity, P = .003) and composition changes were associated with the proportion of daily breast milk intake in a dose-dependent manner, even after the introduction of solid foods.

CONCLUSIONS AND RELEVANCE

The results of this study indicate that bacteria in mother's breast milk seed the infant gut, underscoring the importance of breastfeeding in the development of the infant gut microbiome.

Optimizing methods and dodging pitfalls in microbiome research

Research on the human microbiome has yielded numerous insights into health and disease, but also has resulted in a wealth of experimental artifacts. Here, we present suggestions for optimizing experimental design and avoiding known pitfalls, organized in the typical order in which studies are carried out. We first review best practices in experimental design and introduce common confounders such as age, diet, antibiotic use, pet ownership, longitudinal instability, and microbial sharing during cohousing in animal studies. Typically, samples will need to be stored, so we provide data on best practices for several sample types. We then discuss design and analysis of positive and negative controls, which should always be run with experimental samples. We introduce a convenient set of non-biological DNA sequences that can be useful as positive controls for high-volume analysis. Careful analysis of negative and positive controls is particularly important in studies of samples with low microbial biomass, where contamination can comprise most or all of a sample. Lastly, we summarize approaches to enhancing experimental robustness by careful control of multiple comparisons and to comparing discovery and validation cohorts. We hope the experimental tactics summarized here will help researchers in this exciting field advance their studies efficiently while avoiding errors.

Normalization and microbial differential abundance strategies depend upon data characteristics

BACKGROUND

Data from 16S ribosomal RNA (rRNA) amplicon sequencing present challenges to ecological and statistical interpretation. In particular, library sizes often vary over several ranges of magnitude, and the data contains many zeros. Although we are typically interested in comparing relative abundance of taxa in the ecosystem of two or more groups, we can only measure the taxon relative abundance in specimens obtained from the ecosystems. Because the comparison of taxon relative abundance in the specimen is not equivalent to the comparison of taxon relative abundance in the ecosystems, this presents a special challenge. Second, because the relative abundance of taxa in the specimen (as well as in the ecosystem) sum to 1, these are compositional data. Because the compositional data are constrained by the simplex (sum to 1) and are not unconstrained in the Euclidean space, many standard methods of analysis are not applicable. Here, we evaluate how these challenges impact the performance of existing normalization methods and differential abundance analyses.

RESULTS

Effects on normalization: Most normalization methods enable successful clustering of samples according to biological origin when the groups differ substantially in their overall microbial composition. Rarefying more clearly clusters samples according to biological origin than other normalization techniques do for ordination metrics based on presence or absence. Alternate normalization measures are potentially vulnerable to artifacts due to library size. Effects on differential abundance testing: We build on a previous work to evaluate seven proposed statistical methods using rarefied as well as raw data. Our simulation studies suggest that the false discovery rates of many differential abundance-testing methods are not increased by rarefying itself, although of course rarefying results in a loss of sensitivity due to elimination of a portion of available data. For groups with large (~10×) differences in the average library size, rarefying lowers the false discovery rate. DESeq2, without addition of a constant, increased sensitivity on smaller datasets (<20 samples per group) but tends towards a higher false discovery rate with more samples, very uneven (~10×) library sizes, and/or compositional effects. For drawing inferences regarding taxon abundance in the ecosystem, analysis of composition of microbiomes (ANCOM) is not only very sensitive (for >20 samples per group) but also critically the only method tested that has a good control of false discovery rate.

CONCLUSIONS

These findings guide which normalization and differential abundance techniques to use based on the data characteristics of a given study.

INSPIIRED: Quantification and Visualization Tools for Analyzing Integration Site Distributions

Analysis of sites of newly integrated DNA in cellular genomes is important to several fields, but methods for analyzing and visualizing these datasets are still under development. Here, we describe tools for data analysis and visualization that take as input integration site data from our INSPIIRED pipeline. Paired-end sequencing allows inference of the numbers of transduced cells as well as the distributions of integration sites in target genomes. We present interactive heatmaps that allow comparison of distributions of integration sites to genomic features and that support numerous user-defined statistical tests. To summarize integration site data from human gene therapy samples, we developed a reproducible report format that catalogs sample population structure, longitudinal dynamics, and integration frequency near cancer-associated genes. We also introduce a novel summary statistic, the UC50 (unique cell progenitors contributing the most expanded 50% of progeny cell clones), which provides a single number summarizing possible clonal expansion. Using these tools, we characterize ongoing longitudinal characterization of a patient from the first trial to treat severe combined immunodeficiency-X1 (SCID-X1), showing successful reconstitution for 15 years accompanied by persistence of a cell clone with an integration site near the cancer-associated gene CCND2. Software is available at https://github.com/BushmanLab/INSPIIRED.

INSPIIRED: A Pipeline for Quantitative Analysis of Sites of New DNA Integration in Cellular Genomes

Integration of new DNA into cellular genomes mediates replication of retroviruses and transposons; integration reactions have also been adapted for use in human gene therapy. Tracking the distributions of integration sites is important to characterize populations of transduced cells and to monitor potential outgrow of pathogenic cell clones. Here, we describe a pipeline for quantitative analysis of integration site distributions named INSPIIRED (integration site pipeline for paired-end reads). We describe optimized biochemical steps for site isolation using Illumina paired-end sequencing, including new technology for suppressing recovery of unwanted contaminants, then software for alignment, quality control, and management of integration site sequences. During library preparation, DNAs are broken by sonication, so that after ligation-mediated PCR the number of ligation junction sites can be used to infer abundance of gene-modified cells. We generated integration sites of known positions in silico, and we describe optimization of sample processing parameters refined by comparison to truth. We also present a novel graph-theory-based method for quantifying integration sites in repeated sequences, and we characterize the consequences using synthetic and experimental data. In an accompanying paper, we describe an additional set of statistical tools for data analysis and visualization. Software is available at https://github.com/BushmanLab/INSPIIRED.

Comparison of placenta samples with contamination controls does not provide evidence for a distinct placenta microbiota

BACKGROUND

Recent studies have suggested that bacteria associated with the placenta-a "placental microbiome"-may be important in reproductive health and disease. However, a challenge in working with specimens with low bacterial biomass, such as placental samples, is that some or all of the bacterial DNA may derive from contamination in dust or commercial reagents. To investigate this, we compared placental samples from healthy deliveries to a matched set of contamination controls, as well as to oral and vaginal samples from the same women.

RESULTS

We quantified total 16S rRNA gene copies using quantitative PCR and found that placental samples and negative controls contained low and indistinguishable copy numbers. Oral and vaginal swab samples, in contrast, showed higher copy numbers. We carried out 16S rRNA gene sequencing and community analysis and found no separation between communities from placental samples and contamination controls, though oral and vaginal samples showed characteristic, distinctive composition. Two different DNA purification methods were compared with similar conclusions, though the composition of the contamination background differed. Authentically present microbiota should yield mostly similar results regardless of the purification method used-this was seen for oral samples, but no placental bacterial lineages were (1) shared between extraction methods, (2) present at >1 % of the total, and (3) present at greater abundance in placental samples than contamination controls.

CONCLUSIONS

We conclude that for this sample set, using the methods described, we could not distinguish between placental samples and contamination introduced during DNA purification.

Dietary Regulation of the Gut Microbiota Engineered by a Minimal Defined Bacterial Consortium

We have recently reported that Altered Schaedler Flora (ASF) can be used to durably engineer the gut microbiota to reduce ammonia production as an effective modality to reduce morbidity and mortality in the setting of liver injury. Here we investigated the effects of a low protein diet on ASF colonization and its ability to engineer the microbiota. Initially, ASF inoculation was similar between mice fed a normal protein diet or low protein diet, but the outgrowth of gut microbiota differed over the ensuing month. Notable was the inability of the dominant Parabacteroides ASF taxon to exclude other taxa belonging to the Bacteroidetes phylum in the setting of a low protein diet. Instead, a poorly classified yet highly represented Bacteroidetes family, S24-7, returned within 4 weeks of inoculation in mice fed a low protein diet, demonstrating a reduction in ASF resilience in response to dietary stress. Nevertheless, fecal ammonia levels remained significantly lower than those observed in mice on the same low protein diet that received a transplant of normal feces. No deleterious effects were observed in host physiology due to ASF inoculation into mice on a low protein diet. In total, these results demonstrate that low protein diet can have a pronounced effect on engineering the gut microbiota but modulation of ammonia is preserved.

Composition and dynamics of the respiratory tract microbiome in intubated patients

BACKGROUND

Lower respiratory tract infection (LRTI) is a major contributor to respiratory failure requiring intubation and mechanical ventilation. LRTI also occurs during mechanical ventilation, increasing the morbidity and mortality of intubated patients. We sought to understand the dynamics of respiratory tract microbiota following intubation and the relationship between microbial community structure and infection.

RESULTS

We enrolled a cohort of 15 subjects with respiratory failure requiring intubation and mechanical ventilation from the medical intensive care unit at an academic medical center. Oropharyngeal (OP) and deep endotracheal (ET) secretions were sampled within 24 h of intubation and every 48-72 h thereafter. Bacterial community profiling was carried out by purifying DNA, PCR amplification of 16S ribosomal RNA (rRNA) gene sequences, deep sequencing, and bioinformatic community analysis. We compared enrolled subjects to a cohort of healthy subjects who had lower respiratory tract sampling by bronchoscopy. In contrast to the diverse upper respiratory tract and lower respiratory tract microbiota found in healthy controls, critically ill subjects had lower initial diversity at both sites. Diversity further diminished over time on the ventilator. In several subjects, the bacterial community was dominated by a single taxon over multiple time points. The clinical diagnosis of LRTI ascertained by chart review correlated with low community diversity and dominance of a single taxon. Dominant taxa matched clinical bacterial cultures where cultures were obtained and positive. In several cases, dominant taxa included bacteria not detected by culture, including Ureaplasma parvum and Enterococcus faecalis.

CONCLUSIONS

Longitudinal analysis of respiratory tract microbiota in critically ill patients provides insight into the pathogenesis and diagnosis of LRTI. 16S rRNA gene sequencing of endotracheal aspirate samples holds promise for expanded pathogen identification.

A comparison of rumen microbial profiles in dairy cows as retrieved by 454 Roche and Ion Torrent (PGM) sequencing platforms

Next generation sequencing (NGS) technology is a widely accepted tool used by microbial ecologists to explore complex microbial communities in different ecosystems. As new NGS platforms continue to become available, it becomes imperative to compare data obtained from different platforms and analyze their effect on microbial community structure. In the present study, we compared sequencing data from both the 454 and Ion Torrent (PGM) platforms on the same DNA samples obtained from the rumen of dairy cows during their transition period. Despite the substantial difference in the number of reads, error rate and length of reads among both platforms, we identified similar community composition between the two data sets. Procrustes analysis revealed similar correlations (M (2) = 0.319; P = 0.001) in the microbial community composition between the two platforms. Both platforms revealed the abundance of the same bacterial phyla which were Bacteroidetes and Firmicutes; however, PGM recovered an additional four phyla. Comparisons made at the genus level by each platforms revealed differences in only a few genera such as Prevotella, Ruminococcus, Succiniclasticum and Treponema (p < 0.05; chi square test). Collectively, we conclude that the output generated from PGM and 454 yielded concurrent results, provided stringent bioinformatics pipelines are employed.

Comparative metabolomics in vegans and omnivores reveal constraints on diet-dependent gut microbiota metabolite production

OBJECTIVE

The consumption of an agrarian diet is associated with a reduced risk for many diseases associated with a 'Westernised' lifestyle. Studies suggest that diet affects the gut microbiota, which subsequently influences the metabolome, thereby connecting diet, microbiota and health. However, the degree to which diet influences the composition of the gut microbiota is controversial. Murine models and studies comparing the gut microbiota in humans residing in agrarian versus Western societies suggest that the influence is large. To separate global environmental influences from dietary influences, we characterised the gut microbiota and the host metabolome of individuals consuming an agrarian diet in Western society.

DESIGN AND RESULTS

Using 16S rRNA-tagged sequencing as well as plasma and urinary metabolomic platforms, we compared measures of dietary intake, gut microbiota composition and the plasma metabolome between healthy human vegans and omnivores, sampled in an urban USA environment. Plasma metabolome of vegans differed markedly from omnivores but the gut microbiota was surprisingly similar. Unlike prior studies of individuals living in agrarian societies, higher consumption of fermentable substrate in vegans was not associated with higher levels of faecal short chain fatty acids, a finding confirmed in a 10-day controlled feeding experiment. Similarly, the proportion of vegans capable of producing equol, a soy-based gut microbiota metabolite, was less than that was reported in Asian societies despite the high consumption of soy-based products.

CONCLUSIONS

Evidently, residence in globally distinct societies helps determine the composition of the gut microbiota that, in turn, influences the production of diet-dependent gut microbial metabolites.

Bidirectional interactions between indomethacin and the murine intestinal microbiota

The vertebrate gut microbiota have been implicated in the metabolism of xenobiotic compounds, motivating studies of microbe-driven metabolism of clinically important drugs. Here, we studied interactions between the microbiota and indomethacin, a nonsteroidal anti-inflammatory drug (NSAID) that inhibits cyclooxygenases (COX) -1 and -2. Indomethacin was tested in both acute and chronic exposure models in mice at clinically relevant doses, which suppressed production of COX-1- and COX-2-derived prostaglandins and caused small intestinal (SI) damage. Deep sequencing analysis showed that indomethacin exposure was associated with alterations in the structure of the intestinal microbiota in both dosing models. Perturbation of the intestinal microbiome by antibiotic treatment altered indomethacin pharmacokinetics and pharmacodynamics, which is probably the result of reduced bacterial β-glucuronidase activity. Humans show considerable inter-individual differences in their microbiota and their responses to indomethacin - thus, the drug-microbe interactions described here provide candidate mediators of individualized drug responses.

Alterations of the Subgingival Microbiota in Pediatric Crohn's Disease Studied Longitudinally in Discovery and Validation Cohorts

BACKGROUND

Oral manifestations are common in Crohn's disease (CD). Here we characterized the subgingival microbiota in pediatric patients with CD initiating therapy and after 8 weeks to identify microbial community features associated with CD and therapy.

METHODS

Pediatric patients with CD were recruited from The Children's Hospital of Pennsylvania. Healthy control subjects were recruited from primary care or orthopedics clinic. Subgingival plaque samples were collected at initiation of therapy and after 8 weeks. Treatment exposures included 5-ASAs, immunomodulators, steroids, and infliximab. The microbiota was characterized by 16S rRNA gene sequencing. The study was repeated in separate discovery (35 CD, 43 healthy) and validation cohorts (43 CD, 31 healthy).

RESULTS

Most subjects in both cohorts demonstrated clinical response after 8 weeks of therapy (discovery cohort 88%, validation cohort 79%). At week 0, both antibiotic exposure and disease state were associated with differences in bacterial community composition. Seventeen genera were identified in the discovery cohort as candidate biomarkers, of which 11 were confirmed in the validation cohort. Capnocytophaga, Rothia, and TM7 were more abundant in CD relative to healthy controls. Other bacteria were reduced in abundance with antibiotic exposure among CD subjects. CD-associated genera were not enriched compared with healthy controls after 8 weeks of therapy.

CONCLUSIONS

Subgingival microbial community structure differed with CD and antibiotic use. Results in the discovery cohort were replicated in a separate validation cohort. Several potentially pathogenic bacterial lineages were associated with CD but were not diminished in abundance by antibiotic treatment, suggesting targets for additional surveillance.

Improved characterization of medically relevant fungi in the human respiratory tract using next-generation sequencing

BACKGROUND

Fungi are important pathogens but challenging to enumerate using next-generation sequencing because of low absolute abundance in many samples and high levels of fungal DNA from contaminating sources.

RESULTS

Here, we analyze fungal lineages present in the human airway using an improved method for contamination filtering. We use DNA quantification data, which are routinely acquired during DNA library preparation, to annotate output sequence data, and improve the identification and filtering of contaminants. We compare fungal communities and bacterial communities from healthy subjects, HIV+ subjects, and lung transplant recipients, providing a gradient of increasing lung impairment for comparison. We use deep sequencing to characterize ribosomal rRNA gene segments from fungi and bacteria in DNA extracted from bronchiolar lavage samples and oropharyngeal wash. Comparison to clinical culture data documents improved detection after applying the filtering procedure.

CONCLUSIONS

We find increased representation of medically relevant organisms, including Candida, Cryptococcus, and Aspergillus, in subjects with increasingly severe pulmonary and immunologic deficits. We analyze covariation of fungal and bacterial taxa, and find that oropharyngeal communities rich in Candida are also rich in mitis group Streptococci,a community pattern associated with pathogenic polymicrobial biofilms. Thus, using this approach, it is possible to characterize fungal communities in the human respiratory tract more accurately and explore their interactions with bacterial communities in health and disease.

Inflammation, Antibiotics, and Diet as Environmental Stressors of the Gut Microbiome in Pediatric Crohn's Disease

Abnormal composition of intestinal bacteria--"dysbiosis"-is characteristic of Crohn's disease. Disease treatments include dietary changes and immunosuppressive anti-TNFα antibodies as well as ancillary antibiotic therapy, but their effects on microbiota composition are undetermined. Using shotgun metagenomic sequencing, we analyzed fecal samples from a prospective cohort of pediatric Crohn's disease patients starting therapy with enteral nutrition or anti-TNFα antibodies and reveal the full complement and dynamics of bacteria, fungi, archaea, and viruses during treatment. Bacterial community membership was associated independently with intestinal inflammation, antibiotic use, and therapy. Antibiotic exposure was associated with increased dysbiosis, whereas dysbiosis decreased with reduced intestinal inflammation. Fungal proportions increased with disease and antibiotic use. Dietary therapy had independent and rapid effects on microbiota composition distinct from other stressor-induced changes and effectively reduced inflammation. These findings reveal that dysbiosis results from independent effects of inflammation, diet, and antibiotics and shed light on Crohn disease treatments.

Engineering the gut microbiota to treat hyperammonemia

Increasing evidence indicates that the gut microbiota can be altered to ameliorate or prevent disease states, and engineering the gut microbiota to therapeutically modulate host metabolism is an emerging goal of microbiome research. In the intestine, bacterial urease converts host-derived urea to ammonia and carbon dioxide, contributing to hyperammonemia-associated neurotoxicity and encephalopathy in patients with liver disease. Here, we engineered murine gut microbiota to reduce urease activity. Animals were depleted of their preexisting gut microbiota and then inoculated with altered Schaedler flora (ASF), a defined consortium of 8 bacteria with minimal urease gene content. This protocol resulted in establishment of a persistent new community that promoted a long-term reduction in fecal urease activity and ammonia production. Moreover, in a murine model of hepatic injury, ASF transplantation was associated with decreased morbidity and mortality. These results provide proof of concept that inoculation of a prepared host with a defined gut microbiota can lead to durable metabolic changes with therapeutic utility.

Power and sample-size estimation for microbiome studies using pairwise distances and PERMANOVA

MOTIVATION

The variation in community composition between microbiome samples, termed beta diversity, can be measured by pairwise distance based on either presence-absence or quantitative species abundance data. PERMANOVA, a permutation-based extension of multivariate analysis of variance to a matrix of pairwise distances, partitions within-group and between-group distances to permit assessment of the effect of an exposure or intervention (grouping factor) upon the sampled microbiome. Within-group distance and exposure/intervention effect size must be accurately modeled to estimate statistical power for a microbiome study that will be analyzed with pairwise distances and PERMANOVA.

RESULTS

We present a framework for PERMANOVA power estimation tailored to marker-gene microbiome studies that will be analyzed by pairwise distances, which includes: (i) a novel method for distance matrix simulation that permits modeling of within-group pairwise distances according to pre-specified population parameters; (ii) a method to incorporate effects of different sizes within the simulated distance matrix; (iii) a simulation-based method for estimating PERMANOVA power from simulated distance matrices; and (iv) an R statistical software package that implements the above. Matrices of pairwise distances can be efficiently simulated to satisfy the triangle inequality and incorporate group-level effects, which are quantified by the adjusted coefficient of determination, omega-squared (ω2). From simulated distance matrices, available PERMANOVA power or necessary sample size can be estimated for a planned microbiome study.

Viral metagenomics reveal blooms of anelloviruses in the respiratory tract of lung transplant recipients

Few studies have examined the lung virome in health and disease. Outcomes of lung transplantation are known to be influenced by several recognized respiratory viruses, but global understanding of the virome of the transplanted lung is incomplete. To define the DNA virome within the respiratory tract following lung transplantation we carried out metagenomic analysis of allograft bronchoalveolar lavage (BAL), and compared with healthy and HIV+ subjects. Viral concentrates were purified from BAL and analyzed by shotgun DNA sequencing. All of the BAL samples contained reads mapping to anelloviruses, with high proportions in lung transplant samples. Anellovirus populations in transplant recipients were complex, with multiple concurrent variants. Quantitative polymerase chain reaction quantification revealed that anellovirus sequences were 56-fold more abundant in BAL from lung transplant recipients compared with healthy controls or HIV+ subjects (p < 0.0001). Anellovirus sequences were also more abundant in upper respiratory tract specimens from lung transplant recipients than controls (p = 0.006). Comparison to metagenomic data on bacterial populations showed that high anellovirus loads correlated with dysbiotic bacterial communities in allograft BAL (p = 0.008). Thus the respiratory tracts of lung transplant recipients contain high levels and complex populations of anelloviruses, warranting studies of anellovirus lung infection and transplant outcome.

Correlation between intraluminal oxygen gradient and radial partitioning of intestinal microbiota

BACKGROUND & AIMS

The gut microbiota is a complex and densely populated community in a dynamic environment determined by host physiology. We investigated how intestinal oxygen levels affect the composition of the fecal and mucosally adherent microbiota.

METHODS

We used the phosphorescence quenching method and a specially designed intraluminal oxygen probe to dynamically quantify gut luminal oxygen levels in mice. 16S ribosomal RNA gene sequencing was used to characterize the microbiota in intestines of mice exposed to hyperbaric oxygen, human rectal biopsy and mucosal swab samples, and paired human stool samples.

RESULTS

Average Po2 values in the lumen of the cecum were extremely low (<1 mm Hg). In altering oxygenation of mouse intestines, we observed that oxygen diffused from intestinal tissue and established a radial gradient that extended from the tissue interface into the lumen. Increasing tissue oxygenation with hyperbaric oxygen altered the composition of the gut microbiota in mice. In human beings, 16S ribosomal RNA gene analyses showed an increased proportion of oxygen-tolerant organisms of the Proteobacteria and Actinobacteria phyla associated with rectal mucosa, compared with feces. A consortium of asaccharolytic bacteria of the Firmicute and Bacteroidetes phyla, which primarily metabolize peptones and amino acids, was associated primarily with mucus. This could be owing to the presence of proteinaceous substrates provided by mucus and the shedding of the intestinal epithelium.

CONCLUSIONS

In an analysis of intestinal microbiota of mice and human beings, we observed a radial gradient of microbes linked to the distribution of oxygen and nutrients provided by host tissue.

Coinfection. Virus-helminth coinfection reveals a microbiota-independent mechanism of immunomodulation

The mammalian intestine is colonized by beneficial commensal bacteria and is a site of infection by pathogens, including helminth parasites. Helminths induce potent immunomodulatory effects, but whether these effects are mediated by direct regulation of host immunity or indirectly through eliciting changes in the microbiota is unknown. We tested this in the context of virus-helminth coinfection. Helminth coinfection resulted in impaired antiviral immunity and was associated with changes in the microbiota and STAT6-dependent helminth-induced alternative activation of macrophages. Notably, helminth-induced impairment of antiviral immunity was evident in germ-free mice, but neutralization of Ym1, a chitinase-like molecule that is associated with alternatively activated macrophages, could partially restore antiviral immunity. These data indicate that helminth-induced immunomodulation occurs independently of changes in the microbiota but is dependent on Ym1.

Fungi of the murine gut: episodic variation and proliferation during antibiotic treatment

Antibiotic use in humans has been associated with outgrowth of fungi. Here we used a murine model to investigate the gut microbiome over 76 days of treatment with vancomycin, ampicillin, neomycin, and metronidazole and subsequent recovery. Mouse stool was studied as a surrogate for the microbiota of the lower gastrointestinal tract. The abundance of fungi and bacteria was measured using quantitative PCR, and the proportional composition of the communities quantified using 454/Roche pyrosequencing of rRNA gene tags. Prior to treatment, bacteria outnumbered fungi by >3 orders of magnitude. Upon antibiotic treatment, bacteria dropped in abundance >3 orders of magnitude, so that the predominant 16S sequences detected became transients derived from food. Upon cessation of treatment, bacterial communities mostly returned to their previous numbers and types after 8 weeks, though communities remained detectably different from untreated controls. Fungal communities varied substantially over time, even in the untreated controls. Separate cages within the same treatment group showed radical differences, but mice within a cage generally behaved similarly. Fungi increased ∼40-fold in abundance upon antibiotic treatment but declined back to their original abundance after cessation of treatment. At the last time point, Candida remained more abundant than prior to treatment. These data show that 1) gut fungal populations change radically during normal mouse husbandry, 2) fungi grow out in the gut upon suppression of bacterial communities with antibiotics, and 3) perturbations due to antibiotics persist long term in both the fungal and bacterial microbiota.