Showing papers by "Daniel McDonald published in 2016"

Extreme Dysbiosis of the Microbiome in Critical Illness

Abstract: Critical illness is hypothesized to associate with loss of "health-promoting" commensal microbes and overgrowth of pathogenic bacteria (dysbiosis). This dysbiosis is believed to increase susceptibility to nosocomial infections, sepsis, and organ failure. A trial with prospective monitoring of the intensive care unit (ICU) patient microbiome using culture-independent techniques to confirm and characterize this dysbiosis is thus urgently needed. Characterizing ICU patient microbiome changes may provide first steps toward the development of diagnostic and therapeutic interventions using microbiome signatures. To characterize the ICU patient microbiome, we collected fecal, oral, and skin samples from 115 mixed ICU patients across four centers in the United States and Canada. Samples were collected at two time points: within 48 h of ICU admission, and at ICU discharge or on ICU day 10. Sample collection and processing were performed according to Earth Microbiome Project protocols. We applied SourceTracker to assess the source composition of ICU patient samples by using Qiita, including samples from the American Gut Project (AGP), mammalian corpse decomposition samples, childhood (Global Gut study), and house surfaces. Our results demonstrate that critical illness leads to significant and rapid dysbiosis. Many taxons significantly depleted from ICU patients versus AGP healthy controls are key "health-promoting" organisms, and overgrowth of known pathogens was frequent. Source compositions of ICU patient samples are largely uncharacteristic of the expected community type. Between time points and within a patient, the source composition changed dramatically. Our initial results show great promise for microbiome signatures as diagnostic markers and guides to therapeutic interventions in the ICU to repopulate the normal, "health-promoting" microbiome and thereby improve patient outcomes. IMPORTANCE Critical illness may be associated with the loss of normal, "health promoting" bacteria, allowing overgrowth of disease-promoting pathogenic bacteria (dysbiosis), which, in turn, makes patients susceptible to hospital-acquired infections, sepsis, and organ failure. This has significant world health implications, because sepsis is becoming a leading cause of death worldwide, and hospital-acquired infections contribute to significant illness and increased costs. Thus, a trial that monitors the ICU patient microbiome to confirm and characterize this hypothesis is urgently needed. Our study analyzed the microbiomes of 115 critically ill subjects and demonstrated rapid dysbiosis from unexpected environmental sources after ICU admission. These data may provide the first steps toward defining targeted therapies that correct potentially "illness-promoting" dysbiosis with probiotics or with targeted, multimicrobe synthetic "stool pills" that restore a healthy microbiome in the ICU setting to improve patient outcomes.

Role of the microbiome, probiotics, and 'dysbiosis therapy' in critical illness.

Abstract: Purpose of reviewLoss of ‘health-promoting’ microbes and overgrowth of pathogenic bacteria (dysbiosis) in ICU is believed to contribute to nosocomial infections, sepsis, and organ failure (multiple organ dysfunction syndrome). This review discusses new understanding of ICU dysbiosis, new data for pr

Fat and vitamin intakes during pregnancy have stronger relations with a pro-inflammatory maternal microbiota than does carbohydrate intake

Abstract: Although diet is known to have a major modulatory influence on gut microbiota, knowledge of the specific roles of particular vitamins, minerals, and other nutrients is limited. Modulation of the composition of the microbiota in pregnant women is especially important as maternal microbes are transferred during delivery and initiate the colonization process in the infant. We studied the associations between intake of specific dietary nutrients during pregnancy and gut microbiota composition. Utilizing the Norwegian NoMIC cohort, we examined the relations between intakes of 28 dietary macro- and micronutrients during pregnancy, derived from food frequency questionnaires administered to 60 women in the second trimester, and observed taxonomic differences in their gut microbiota four days after delivery (assessed through Illumina 16S rRNA amplicon analysis). Higher dietary intakes of fat-soluble vitamins, especially vitamin D, were associated with reduced microbial alpha diversity (p value <0.001). Furthermore, using recently developed statistical methodology, we discovered that the variations in fat-soluble vitamins, saturated and mono-unsaturated fat, and cholesterol intake, were associated with changes in phyla composition. Specifically, vitamin D, mono-unsaturated fat, cholesterol, and retinol were associated with relative increases in Proteobacteria, which is a phylum known to encompass multiple pathogens and to have pro-inflammatory properties. In contrast, saturated fat, vitamin E, and protein were associated with relative decreases in Proteobacteria. The results in this article indicate that fats and fat-soluble vitamins are among the most potent dietary modulators of gut microbiota in mothers. The shifts in microbiota due to diet need to be further studied alongside gut microbiota changes during pregnancy to better understand the impact on infant gut microbiota.

ghost-tree: creating hybrid-gene phylogenetic trees for diversity analyses

Abstract: Fungi play critical roles in many ecosystems, cause serious diseases in plants and animals, and pose significant threats to human health and structural integrity problems in built environments. While most fungal diversity remains unknown, the development of PCR primers for the internal transcribed spacer (ITS) combined with next-generation sequencing has substantially improved our ability to profile fungal microbial diversity. Although the high sequence variability in the ITS region facilitates more accurate species identification, it also makes multiple sequence alignment and phylogenetic analysis unreliable across evolutionarily distant fungi because the sequences are hard to align accurately. To address this issue, we created ghost-tree, a bioinformatics tool that integrates sequence data from two genetic markers into a single phylogenetic tree that can be used for diversity analyses. Our approach starts with a “foundation” phylogeny based on one genetic marker whose sequences can be aligned across organisms spanning divergent taxonomic groups (e.g., fungal families). Then, “extension” phylogenies are built for more closely related organisms (e.g., fungal species or strains) using a second more rapidly evolving genetic marker. These smaller phylogenies are then grafted onto the foundation tree by mapping taxonomic names such that each corresponding foundation-tree tip would branch into its new “extension tree” child. We applied ghost-tree to graft fungal extension phylogenies derived from ITS sequences onto a foundation phylogeny derived from fungal 18S sequences. Our analysis of simulated and real fungal ITS data sets found that phylogenetic distances between fungal communities computed using ghost-tree phylogenies explained significantly more variance than non-phylogenetic distances. The phylogenetic metrics also improved our ability to distinguish small differences (effect sizes) between microbial communities, though results were similar to non-phylogenetic methods for larger effect sizes. The Silva/UNITE-based ghost tree presented here can be easily integrated into existing fungal analysis pipelines to enhance the resolution of fungal community differences and improve understanding of these communities in built environments. The ghost-tree software package can also be used to develop phylogenetic trees for other marker gene sets that afford different taxonomic resolution, or for bridging genome trees with amplicon trees. ghost-tree is pip-installable. All source code, documentation, and test code are available under the BSD license at https://github.com/JTFouquier/ghost-tree .

Turning Participatory Microbiome Research into Usable Data: Lessons from the American Gut Project.

Abstract: The role of the human microbiome is the subject of continued investigation resulting in increased understanding. However, current microbiome research has only scratched the surface of the variety of healthy microbiomes. Public participation in science through crowdsourcing and crowdfunding microbiome research provides a novel opportunity for both participants and investigators. However, turning participatory science into publishable data can be challenging. Clear communication with the participant base and among researchers can ameliorate some challenges. Three major aspects need to be considered: recruitment and ongoing interaction, sample collection, and data analysis. Usable data can be maximized through diligent participant interaction, careful survey design, and maintaining an open source pipeline. While participatory science will complement rather than replace traditional avenues, it presents new opportunities for studies in the microbiome and beyond.

Avoiding Pandemic Fears in the Subway and Conquering the Platypus

Abstract: Metagenomics is increasingly used not just to show patterns of microbial diversity but also as a culture-independent method to detect individual organisms of intense clinical, epidemiological, conservation, forensic, or regulatory interest. A widely reported metagenomic study of the New York subway suggested that the pathogens Yersinia pestis and Bacillus anthracis were part of the "normal subway microbiome." In their article in mSystems, Hsu and collaborators (mSystems 1(3):e00018-16, 2016, http://dx.doi.org/10.1128/mSystems.00018-16) showed that microbial communities on transit surfaces in the Boston subway system are maintained from a metapopulation of human skin commensals and environmental generalists and that reanalysis of the New York subway data with appropriate methods did not detect the pathogens. We note that commonly used software pipelines can produce results that lack prima facie validity (e.g., reporting widespread distribution of notorious endemic species such as the platypus or the presence of pathogens) but that appropriate use of inclusion and exclusion sets can avoid this issue.

Personalized nutrition through big data.

Abstract: A systems model of glycemic response identifies individually tailored diets that keep blood sugar in check.