[Show abstract][Hide abstract] ABSTRACT: Contributing reviewers
We are deeply grateful to all of the names listed below, who reviewed manuscripts submitted to Microbiome in 2014. We hope that you all will continue to support the journal as a reviewer or, better yet, as a contributing author.
[Show abstract][Hide abstract] ABSTRACT: Different bacteria in stool have markedly varied growth and survival when stored at ambient temperature. It is paramount to develop optimal biostabilization of stool samples during collection and assess long-term storage for clinical specimens and epidemiological microbiome studies. We evaluated the effect of collection media and delayed freezing up to 7 days on microbial composition. Ten participants collected triplicate stool samples each into no media as well as RNAlater® with and without kanamycin or ciprofloxacin. For each set of conditions, triplicate samples were frozen on dry ice immediately (time = 0) or frozen at -80 °C after 3-days and 7-days incubation at 25 °C. Microbiota metrics were estimated from Illumina MiSeq sequences of 16S rRNA gene fragments (V3-V4 region). Intraclass correlation coefficients (ICC) across triplicates, collection media, and incubation time were estimated for taxonomy and alpha and beta diversity metrics.
RNAlater® alone yielded the highest ICCs for diversity metrics at time = 0 [ICC median 0.935 (range 0.89-0.97)], but ICCs varied greatly (range 0.44-1.0) for taxa with relative abundances <1 %. The 3- and 7-day freezing delays were generally associated with stable beta diversity for all three media conditions. Freezing delay caused increased variance for Shannon index (median ICC 0.77) and especially for observed species abundance (median ICC 0.47). Variance in observed species abundance and in phylogenetic distance whole tree was similarly increased with a 7-day delay. Antibiotics did not mitigate variance. No media had inferior ICCs at time 0 and differed markedly from any media in microbiome composition (e.g., P = 0.01 for relative abundance of Bacteroidetes).
Bacterial community composition was stable for 7 days at room temperature in RNAlater® alone. RNAlater® provides some stability for beta diversity analyses, but analyses of rare taxa will be inaccurate if specimens are not frozen immediately. RNAlater® could be used as collection media with minimal change in the microbiota composition.
[Show abstract][Hide abstract] ABSTRACT: We investigated whether the gut microbiota differed in 48 postmenopausal breast cancer case patients, pretreatment, vs 48 control patients. Microbiota profiles in fecal DNA were determined by Illumina sequencing and taxonomy of 16S rRNA genes. Estrogens were quantified in urine. Case-control comparisons employed linear and unconditional logistic regression of microbiota α-diversity (PD_whole tree) and UniFrac analysis of β-diversity, with two-sided statistical tests. Total estrogens correlated with α-diversity in control patients (Spearman Rho = 0.37, P = .009) but not case patients (Spearman Rho = 0.04, P = .77). Compared with control patients, case patients had statistically significantly altered microbiota composition (β-diversity, P = .006) and lower α-diversity (P = .004). Adjusted for estrogens and other covariates, odds ratio of cancer was 0.50 (95% confidence interval = 0.30 to 0.85) per α-diversity tertile. Differences in specific taxa were not statistically significant when adjusted for multiple comparisons. This pilot study shows that postmenopausal women with breast cancer have altered composition and estrogen-independent low diversity of their gut microbiota. Whether these affect breast cancer risk and prognosis is unknown.
Published by Oxford University Press 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.
Journal of the National Cancer Institute 08/2015; 107(8). DOI:10.1093/jnci/djv147 · 12.58 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: ᅟ
The advancement of DNA/RNA, proteins, and metabolite analytical platforms, combined with increased computing technologies, has transformed the field of microbial community analysis. This transformation is evident by the exponential increase in the number of publications describing the composition and structure, and sometimes function, of the microbial communities inhabiting the human body. This rapid evolution of the field has been accompanied by confusion in the vocabulary used to describe different aspects of these communities and their environments. The misuse of terms such as microbiome, microbiota, metabolomic, and metagenome and metagenomics among others has contributed to misunderstanding of many study results by the scientific community and the general public alike. A few review articles have previously defined those terms, but mainly as sidebars, and no clear definitions or use cases have been published. In this editorial, we aim to propose clear definitions of each of these terms, which we would implore scientists in the field to adopt and perfect.
[Show abstract][Hide abstract] ABSTRACT: Background:
Sequencing of the PCR-amplified 16S rRNA gene has become a common approach to microbial community investigations in the fields of human health and environmental sciences. This approach, however, is difficult when the amount of DNA is too low to be amplified by standard PCR. Nested PCR can be employed as it can amplify samples with DNA concentration several-fold lower than standard PCR. However, potential biases with nested PCRs that could affect measurement of community structure have received little attention.
In this study, we used 17 DNAs extracted from vaginal swabs and 12 DNAs extracted from stool samples to study the influence of nested PCR amplification of the 16S rRNA gene on the estimation of microbial community structure using Illumina MiSeq sequencing. Nested and standard PCR methods were compared on alpha- and beta-diversity metrics and relative abundances of bacterial genera. The effects of number of cycles in the first round of PCR (10 vs. 20) and microbial diversity (relatively low in vagina vs. high in stool) were also investigated. Vaginal swab samples showed no significant difference in alpha diversity or community structure between nested PCR and standard PCR (one round of 40 cycles). Stool samples showed significant differences in alpha diversity (except Shannon's index) and relative abundance of 13 genera between nested PCR with 20 cycles in the first round and standard PCR (P<0.01), but not between nested PCR with 10 cycles in the first round and standard PCR. Operational taxonomic units (OTUs) that had low relative abundance (sum of relative abundance <0.167) accounted for most of the distortion (>27% of total OTUs in stool).
Nested PCR introduced bias in estimated diversity and community structure. The bias was more significant for communities with relatively higher diversity and when more cycles were applied in the first round of PCR. We conclude that nested PCR could be used when standard PCR does not work. However, rare taxa detected by nested PCR should be validated by other technologies.
PLoS ONE 07/2015; 10(7):e0132253. DOI:10.1371/journal.pone.0132253 · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: In this study, we evaluated the association between high-risk human papillomavirus (hrHPV) and the vaginal microbiome. Participants were recruited in Nigeria between April and August 2012. Vaginal bacterial composition was characterized by deep sequencing of barcoded 16S rRNA gene fragments (V4) on Illumina MiSeq and HPV was identified using the Roche Linear Array® HPV genotyping test. We used exact logistic regression models to evaluate the association between community state types (CSTs) of vaginal microbiota and hrHPV infection, weighted UniFrac distances to compare the vaginal microbiota of individuals with prevalent hrHPV to those without prevalent hrHPV infection, and the Linear Discriminant Analysis effect size (LEfSe) algorithm to characterize bacteria associated with prevalent hrHPV infection. We observed four CSTs: CST IV-B with a low relative abundance of Lactobacillus spp. in 50% of participants; CST III (dominated by L. iners) in 39·2%; CST I (dominated by L. crispatus) in 7·9%; and CST VI (dominated by proteobacteria) in 2·9% of participants. LEfSe analysis suggested an association between prevalent hrHPV infection and a decreased abundance of Lactobacillus sp. with increased abundance of anaerobes particularly of the genera Prevotella and Leptotrichia in HIV-negative women (P < 0·05). These results are hypothesis generating and further studies are required.
Epidemiology and Infection 06/2015; -1:1-15. DOI:10.1017/S0950268815000965 · 2.54 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Candida albicans, the major invasive fungal pathogen of humans, can cause both debilitating mucosal infections and fatal invasive infections. Understanding the complex nature of the host-pathogen interaction in each of these contexts is essential to developing desperately needed therapies to treat fungal infections. RNA-seq enables a systems-level understanding of infection by facilitating comprehensive analysis of transcriptomes from multiple species (e.g., host and pathogen) simultaneously. We used RNA-seq to characterize the transcriptomes of both C. albicans and human endothelial cells or oral epithelial cells during in vitro infection. Network analysis of the differentially expressed genes identified the activation of several signaling pathways that have not previously been associated with the host response to fungal pathogens. Using an siRNA knockdown approach, we demonstrate that two of these pathways-platelet-derived growth factor BB (PDGF BB) and neural precursor-cell-expressed developmentally down-regulated protein 9 (NEDD9)-govern the host-pathogen interaction by regulating the uptake of C. albicans by host cells. Using RNA-seq analysis of a mouse model of hematogenously disseminated candidiasis (HDC) and episodes of vulvovaginal candidiasis (VVC) in humans, we found evidence that many of the same signaling pathways are activated during mucosal (VVC) and/or disseminated (HDC) infections in vivo. Our analyses have uncovered several signaling pathways at the interface between C. albicans and host cells in various contexts of infection, and suggest that PDGF BB and NEDD9 play important roles in this interaction. In addition, these data provide a valuable community resource for better understanding host-fungal pathogen interactions.
Genome Research 05/2015; 25(5). DOI:10.1101/gr.187427.114 · 14.63 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Screening for colorectal cancer (CRC) and precancerous colorectal adenoma (CRA) can detect curable disease. However, participation in colonoscopy and sensitivity of fecal heme for CRA are low.
Microbiota metrics were determined by Illumina sequencing of 16S rRNA genes amplified from DNA extracted from feces self-collected in RNAlater. Among fecal immunochemical test-positive (FIT +) participants, colonoscopically-defined normal versus CRA patients were compared by regression, permutation, and random forest plus leave-one-out methods.
Of 95 FIT + participants, 61 had successful fecal microbiota profiling and colonoscopy, identifying 24 completely normal patients, 20 CRA patients, 2 CRC patients, and 15 with other conditions. Phylum-level fecal community composition differed significantly between CRA and normal patients (permutation P = 0.02). Rank phylum-level abundance distinguished CRA from normal patients (area under the curve = 0.767, permutation P = 0.006). CRA prevalence was 59% in phylum-level cluster B versus 20% in cluster A (exact P = 0.01). Most of the difference reflected 3-fold higher median relative abundance of Proteobacteria taxa (Wilcoxon signed-rank P = 0.03, positive predictive value = 67%). Antibiotic exposure and other potential confounders did not affect the associations.
If confirmed in larger, more diverse populations, fecal microbiota analysis might be employed to improve screening for CRA and ultimately to reduce mortality from CRC.
[Show abstract][Hide abstract] ABSTRACT: Background
We identified predominant vaginal microbiota communities, changes over time, and how this varied by HIV status and other factors in a cohort of 64 women.
Bacterial DNA was extracted from reposited cervicovaginal lavage samples collected annually over an 8–10 year period from Chicago Women’s Interagency HIV Study participants: 22 HIV-negative, 22 HIV-positive with stable infection, 20 HIV-positive with progressive infection. The vaginal microbiota was defined by pyrosequencing of the V1/V2 region of the 16S rRNA gene. Scheduled visits included Bacterial vaginsosis (BV) screening; clinically detected cases were referred for treatment. Hierarchical clustering identified bacterial community state types (CST). Multinomial mixed effects modeling determined trends over time in CST, by HIV status and other factors.
The median follow-up time was 8.1 years (range 5.5–15.3). Six CSTs were identified. The mean relative abundance (RA) of Lactobacillus spp. by CST (with median number of bacterial taxa) was: CST-1–25.7% (10), CST-2–27.1% (11), CST-3–34.6% (9), CST-4–46.8% (9), CST-5–57.9% (4), CST-6–69.4% (2). The two CSTs representing the highest RA of Lactobacillus and lowest diversity increased with each additional year of follow-up (CST-5, adjusted odds ratio (aOR) = 1.62 [95% CI: 1.34–1.94]; CST-6, aOR = 1.57 [95 CI: 1.31–1.89]), while the two CSTs representing lowest RA of Lactobacillus and higher diversity decreased with each additional year (CST-1, aOR = 0.89 [95% CI: 0.80–1.00]; CST-2, aOR = 0.86 [95% CI: 0.75–0.99]). There was no association between HIV status and CST at baseline or over time. CSTs representing lower RA of Lactobacillus were associated with current cigarette smoking.
The vaginal microbial community significantly improved over time in this cohort of women with HIV and at high risk for HIV who had regular detection and treatment referral for BV.
PLoS ONE 02/2015; 10(2):e0116894. DOI:10.1371/journal.pone.0116894 · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Objective Despite widespread use of antibiotics for the treatment of life-threatening infections and for research on the role of commensal microbiota, our understanding of their effects on the host is still very limited.
Design Using a popular mouse model of microbiota depletion by a cocktail of antibiotics, we analysed the effects of antibiotics by combining intestinal transcriptome together with metagenomic analysis of the gut microbiota. In order to identify specific microbes and microbial genes that influence the host phenotype in antibiotic-treated mice, we developed and applied analysis of the transkingdom network.
Results We found that most antibiotic-induced alterations in the gut can be explained by three factors: depletion of the microbiota; direct effects of antibiotics on host tissues and the effects of remaining antibiotic-resistant microbes. Normal microbiota depletion mostly led to downregulation of different aspects of immunity. The two other factors (antibiotic direct effects on host tissues and antibiotic-resistant microbes) primarily inhibited mitochondrial gene expression and amounts of active mitochondria, increasing epithelial cell death. By reconstructing and analysing the transkingdom network, we discovered that these toxic effects were mediated by virulence/quorum sensing in antibiotic-resistant bacteria, a finding further validated using in vitro experiments.
Conclusions In addition to revealing mechanisms of antibiotic-induced alterations, this study also describes a new bioinformatics approach that predicts microbial components that regulate host functions and establishes a comprehensive resource on what, why and how antibiotics affect the gut in a widely used mouse model of microbiota depletion by antibiotics.
Gut 01/2015; DOI:10.1136/gutjnl-2014-308820 · 14.66 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: For centuries, cholera has been one of the most feared diseases. The causative agent Vibrio cholerae is a waterborne Gram-negative enteric pathogen eliciting a severe watery diarrheal disease. In October 2010, the seventh pandemic reached Haiti, a country that had not experienced cholera for more than a century. By using whole-genome sequence typing and mapping strategies of 116 serotype O1 strains from global sources, including 44 Haitian genomes, we present a detailed reconstructed evolutionary history of the seventh pandemic with a focus on the Haitian outbreak. We catalogued subtle genomic alterations at the nucleotide level in the genome core and architectural rearrangements from whole-genome map comparisons. Isolates closely related to the Haitian isolates caused several recent outbreaks in southern Asia. This study provides evidence for a single-source introduction of cholera from Nepal into Haiti followed by rapid, extensive, and continued clonal expansion. The phylogeographic patterns in both southern Asia and Haiti argue for the rapid dissemination of V. cholerae across the landscape necessitating real-time surveillance efforts to complement the whole-genome epidemiological analysis. As eradication efforts move forward, phylogeographic knowledge will be important for identifying persistent sources and monitoring success at regional levels. The results of molecular and epidemiological analyses of this outbreak suggest that an indigenous Haitian source of V. cholerae is unlikely and that an indigenous source has not contributed to the genomic evolution of this clade.
[Show abstract][Hide abstract] ABSTRACT: The human microbiome has become a recognized factor in promoting and maintaining health. We outline opportunities in interdisciplinary research, analytical rigor, standardization, and policy development for this relatively new and rapidly developing field. Advances in these aspects of the research community may in turn advance our understanding of human microbiome biology.