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ABSTRACT: Infants in Neonatal Intensive Care Units (NICUs) are particularly susceptible to opportunistic infection. Infected infants have high mortality rates, and survivors often suffer life-long neurological disorders. The causes of many NICU infections go undiagnosed, and there is debate as to the importance of inanimate hospital environments (IHEs) in the spread of infections. We used culture-independent next-generation sequencing to survey bacterial diversity in two San Diego NICUs and to track the sources of microbes in these environments. Thirty IHE samples were collected from two Level-Three NICU facilities. We extracted DNA from these samples and amplified the bacterial small subunit (16S) ribosomal RNA gene sequence using 'universal' barcoded primers. The purified PCR products were pooled into a single reaction for pyrosequencing, and the data were analyzed using QIIME. On average, we detected 93+/-39 (mean +/- standard deviation) bacterial genera per sample in NICU IHEs. Many of the bacterial genera included known opportunistic pathogens, and many were skin-associated (e.g., Propionibacterium). In one NICU, we also detected fecal coliform bacteria (Enterobacteriales) in a high proportion of the surface samples. Comparison of these NICU-derived sequences to previously published high-throughput 16S rRNA amplicon studies of other indoor environments (offices, restrooms and healthcare facilities), as well as human- and soil-associated environments, found the majority of the NICU samples to be similar to typical building surface and air samples, with the notable exception of the IHEs which were dominated by Enterobacteriaceae. Our findings provide evidence that NICU IHEs harbor a high diversity of human-associated bacteria and demonstrate the potential utility of molecular methods for identifying and tracking bacterial diversity in NICUs.
PLoS ONE 01/2013; 8(1):e54703. · 4.09 Impact Factor
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ABSTRACT: Recent analyses of human-associated bacterial diversity have categorized individuals into 'enterotypes' or clusters based on the abundances of key bacterial genera in the gut microbiota. There is a lack of consensus, however, on the analytical basis for enterotypes and on the interpretation of these results. We tested how the following factors influenced the detection of enterotypes: clustering methodology, distance metrics, OTU-picking approaches, sequencing depth, data type (whole genome shotgun (WGS) vs.16S rRNA gene sequence data), and 16S rRNA region. We included 16S rRNA gene sequences from the Human Microbiome Project (HMP) and from 16 additional studies and WGS sequences from the HMP and MetaHIT. In most body sites, we observed smooth abundance gradients of key genera without discrete clustering of samples. Some body habitats displayed bimodal (e.g., gut) or multimodal (e.g., vagina) distributions of sample abundances, but not all clustering methods and workflows accurately highlight such clusters. Because identifying enterotypes in datasets depends not only on the structure of the data but is also sensitive to the methods applied to identifying clustering strength, we recommend that multiple approaches be used and compared when testing for enterotypes.
PLoS Computational Biology 01/2013; 9(1):e1002863. · 5.22 Impact Factor
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The ISME Journal 10/2012; · 7.38 Impact Factor
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Omry Koren,
Julia K Goodrich,
Tyler C Cullender,
Aymé Spor,
Kirsi Laitinen,
Helene Kling Bäckhed, Antonio Gonzalez,
Jeffrey J Werner,
Largus T Angenent,
Rob Knight,
Fredrik Bäckhed,
Erika Isolauri,
Seppo Salminen,
Ruth E Ley
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ABSTRACT: Many of the immune and metabolic changes occurring during normal pregnancy also describe metabolic syndrome. Gut microbiota can cause symptoms of metabolic syndrome in nonpregnant hosts. Here, to explore their role in pregnancy, we characterized fecal bacteria of 91 pregnant women of varying prepregnancy BMIs and gestational diabetes status and their infants. Similarities between infant-mother microbiotas increased with children's age, and the infant microbiota was unaffected by mother's health status. Gut microbiota changed dramatically from first (T1) to third (T3) trimesters, with vast expansion of diversity between mothers, an overall increase in Proteobacteria and Actinobacteria, and reduced richness. T3 stool showed strongest signs of inflammation and energy loss; however, microbiome gene repertoires were constant between trimesters. When transferred to germ-free mice, T3 microbiota induced greater adiposity and insulin insensitivity compared to T1. Our findings indicate that host-microbial interactions that impact host metabolism can occur and may be beneficial in pregnancy.
Cell 08/2012; 150(3):470-80. · 32.40 Impact Factor
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ABSTRACT: Until recently, the study of microbial diversity has mainly been limited to descriptive approaches, rather than predictive model-based analyses. The development of advanced analytical tools and decreasing cost of high-throughput multi-omics technologies has made the later approach more feasible. However, consensus is lacking as to which spatial and temporal scales best facilitate understanding of the role of microbial diversity in determining both public and environmental health. Here, we review the potential for combining these new technologies with both traditional and nascent spatio-temporal analysis methods. The fusion of proper spatio-temporal sampling, combined with modern multi-omics and computational tools, will provide insight into the tracking, development and manipulation of microbial communities.
Current opinion in biotechnology 06/2012; 23(3):431-6. · 7.82 Impact Factor
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ABSTRACT: The vast number of microbial sequences resulting from sequencing efforts using new technologies require us to re-assess currently available analysis methodologies and tools. Here we describe trends in the development and distribution of software for analyzing microbial sequence data. We then focus on one widely used set of methods, dimensionality reduction techniques, which allow users to summarize and compare these vast datasets. We conclude by emphasizing the utility of formal software engineering methods for the development of computational biology tools, and the need for new algorithms for comparing microbial communities. Such large-scale comparisons will allow us to fulfill the dream of rapid integration and comparison of microbial sequence data sets, in a replicable analytical environment, in order to describe the microbial world we inhabit.
Current opinion in biotechnology 12/2011; 23(1):64-71. · 7.82 Impact Factor
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ABSTRACT: As microbial ecologists take advantage of high-throughput analytical techniques to describe microbial communities across ever-increasing numbers of samples, the need for new analysis tools that reveal the intrinsic spatial patterns and structures of these populations is crucial. Here we present SitePainter, an interactive graphical tool that allows investigators to create or upload pictures of their study site, load diversity analyses data and display both diversity and taxonomy results in a spatial context. Features of SitePainter include: visualizing α -diversity, using taxonomic summaries; visualizing β -diversity, using results from multidimensional scaling methods; and animating relationships among microbial taxa or pathways overtime. SitePainter thus increases the visual power and ability to explore spatially explicit studies. AVAILABILITY: https://sourceforge.net/projects/sitepainter SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. CONTACT: antoniog@colorado.edu, Rob.Knight@colorado.edu.
Bioinformatics 12/2011; 28(3):436-8. · 5.47 Impact Factor
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ABSTRACT: Advances in DNA sequencing have allowed us to characterize microbial communities--including those associated with the human body--at a broader range of spatial and temporal scales than ever before. We can now answer fundamental questions that were previously inaccessible and use well-tested ecological theories to gain insight into changes in the microbiome that are associated with normal development and human disease. Perhaps unsurprisingly, the ecosystems associated with our body follow trends identified in communities at other sites and scales, and thus studies of the microbiome benefit from ecological insight. Here, we assess human microbiome research in the context of ecological principles and models, focusing on diversity, biological drivers of community structure, spatial patterning and temporal dynamics, and suggest key directions for future research that will bring us closer to the goal of building predictive models for personalized medicine.
EMBO Reports 07/2011; 12(8):775-84. · 7.36 Impact Factor
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J Gregory Caporaso,
Christian L Lauber,
Elizabeth K Costello,
Donna Berg-Lyons, Antonio Gonzalez,
Jesse Stombaugh,
Dan Knights,
Pawel Gajer,
Jacques Ravel,
Noah Fierer,
Jeffrey I Gordon,
Rob Knight
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ABSTRACT: Understanding the normal temporal variation in the human microbiome is critical to developing treatments for putative microbiome-related afflictions such as obesity, Crohn’s disease, inflammatory bowel disease and malnutrition. Sequencing and computational technologies, however, have been a limiting factor in performing dense time series analysis of the human microbiome. Here, we present the largest human microbiota time series analysis to date, covering two individuals at four body sites over 396 timepoints.
We find that despite stable differences between body sites and individuals, there is pronounced variability in an individual’s microbiota across months, weeks and even days. Additionally, only a small fraction of the total taxa found within a single body site appear to be present across all time points, suggesting that no core temporal microbiome exists at high abundance (although some microbes may be present but drop below the detection threshold). Many more taxa appear to be persistent but non-permanent community members.
DNA sequencing and computational advances described here provide the ability to go beyond infrequent snapshots of our human-associated microbial ecology to high-resolution assessments of temporal variations over protracted periods, within and between body habitats and individuals. This capacity will allow us to define normal variation and pathologic states, and assess responses to therapeutic interventions.
Genome biology 05/2011; 12(5):R50. · 6.63 Impact Factor
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Pelin Yilmaz,
Renzo Kottmann,
Dawn Field,
Rob Knight,
James R Cole,
Linda Amaral-Zettler,
Jack A Gilbert,
Ilene Karsch-Mizrachi,
Anjanette Johnston,
Guy Cochrane, [......],
James M Tiedje,
Doyle V Ward,
George M Weinstock,
Doug Wendel,
Owen White,
Andrew Whiteley,
Andreas Wilke,
Jennifer R Wortman,
Tanya Yatsunenko,
Frank Oliver Glöckner
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ABSTRACT: Here we present a standard developed by the Genomic Standards Consortium (GSC) for reporting marker gene sequences--the minimum information about a marker gene sequence (MIMARKS). We also introduce a system for describing the environment from which a biological sample originates. The 'environmental packages' apply to any genome sequence of known origin and can be used in combination with MIMARKS and other GSC checklists. Finally, to establish a unified standard for describing sequence data and to provide a single point of entry for the scientific community to access and learn about GSC checklists, we present the minimum information about any (x) sequence (MIxS). Adoption of MIxS will enhance our ability to analyze natural genetic diversity documented by massive DNA sequencing efforts from myriad ecosystems in our ever-changing biosphere.
Nature Biotechnology 05/2011; 29(5):415-20. · 29.50 Impact Factor
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Amanda Birmingham,
Jose C Clemente,
Narayan Desai,
Jack Gilbert, Antonio Gonzalez,
Nikos Kyrpides,
Folker Meyer,
Eric Nawrocki,
Peter Sterk,
Jesse Stombaugh,
Zasha Weinberg,
Doug Wendel,
Neocles B Leontis,
Craig Zirbel,
Rob Knight,
Alain Laederach
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ABSTRACT: This report summarizes the proceedings of the structure mapping working group meeting of the RNA Ontology Consortium (ROC), held in Kona, Hawaii on January 8-9, 2011. The ROC hosted this workshop to facilitate collaborations among those researchers formalizing concepts in RNA, those developing RNA-related software, and those performing genome annotation and standardization. The workshop included three software presentations, extended round-table discussions, and the constitution of two new working groups, the first to address the need for better software integration and the second to discuss standardization and benchmarking of existing RNA annotation pipelines. These working groups have subsequently pursued concrete implementation of actions suggested during the discussion. Further information about the ROC and its activities can be found at http://roc.bgsu.edu/.
Standards in Genomic Sciences 04/2011; 4(2):252-6. · 1.62 Impact Factor
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ABSTRACT: Our understanding of the vast collection of microbes that live on and inside us (microbiota) and their collective genes (microbiome) has been revolutionized by culture-independent "metagenomic" techniques and DNA sequencing technologies. Most of our microbes live in our gut, where they function as a metabolic organ and provide attributes not encoded in our human genome. Metagenomic studies are revealing shared and distinctive features of microbial communities inhabiting different humans. A central question in psychiatry is the relative role of genes and environment in shaping behavior. The human microbiome serves as the interface between our genes and our history of environmental exposures; explorations of our microbiomes thus offer the possibility of providing new insights into our neurodevelopment and our behavioral phenotypes by affecting complex processes such as inter- and intra personal variations in cognition, personality, mood, sleep, and eating behavior, and perhaps even a variety of neuropsychiatric diseases ranging from affective disorders to autism. Better understanding of microbiome-encoded pathways for xenobiotic metabolism also has important implications for improving the efficacy of pharmacologic interventions with neuromodulatory agents.
Dialogues in clinical neuroscience 01/2011; 13(1):55-62.
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Pelin Yilmaz,
Renzo Kottmann,
Dawn Field,
Rob Knight,
James R Cole,
Linda Amaral-Zettler,
Jack A Gilbert,
Ilene Karsch-Mizrachi,
Anjanette Johnston,
Guy Cochrane, [......],
Aymé Spor,
Jesse Stombaugh,
James M Tiedje,
Doyle V Ward,
George M Weinstock,
Doug Wendel,
Owen White,
Andreas Wilke,
Jennifer Wortmann,
Frank Oliver Glöckner
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ABSTRACT: We present the Genomic Standards Consortium’s (GSC) “Minimum Information about an ENvironmental Sequence” (MIENS) standard for describing marker genes. Adoption of MIENS will enhance our ability to analyze natural genetic diversity across the Tree of Life as it is currently being documented by massive DNA sequencing efforts from myriad ecosystems in our ever-changing biosphere.
Nature Precedings.
