Individual-specific changes in the human gut microbiota after challenge with enterotoxigenic Escherichia coli and subsequent ciprofloxacin treatment

Acknowledgements The authors wish to thank Mark Stares, Richard Rance, and other members of the Wellcome Trust Sanger Institute’s 454 sequencing team for generating the 16S rRNA gene data. Lili Fox Vélez provided editorial support. Funding IA, JNP, and MP were partly supported by the NIH, grants R01-AI-100947 to MP, and R21-GM-107683 to Matthias Chung, subcontract to MP. JNP was partly supported by an NSF graduate fellowship number DGE750616. IA, JNP, BRL, OCS and MP were supported in part by the Bill and Melinda Gates Foundation, award number 42917 to OCS. JP and AWW received core funding support from The Wellcome Trust (grant number 098051). AWW, and the Rowett Institute of Nutrition and Health, University of Aberdeen, receive core funding support from the Scottish Government Rural and Environmental Science and Analysis Service (RESAS).Peer reviewedPublisher PD

Probabilistic Algorithmic Knowledge

The framework of algorithmic knowledge assumes that agents use deterministic knowledge algorithms to compute the facts they explicitly know. We extend the framework to allow for randomized knowledge algorithms. We then characterize the information provided by a randomized knowledge algorithm when its answers have some probability of being incorrect. We formalize this information in terms of evidence; a randomized knowledge algorithm returning ``Yes'' to a query about a fact \phi provides evidence for \phi being true. Finally, we discuss the extent to which this evidence can be used as a basis for decisions.Comment: 26 pages. A preliminary version appeared in Proc. 9th Conference on Theoretical Aspects of Rationality and Knowledge (TARK'03

Diarrhea in young children from low-income countries leads to large-scale alterations in intestinal microbiota composition

Acknowledgments This work was funded in part by the William and Melinda Gates Foundation, award 42917 to JPN and OCS; US National Institutes of Health grants 5R01HG005220 to HCB, 5R01HG004885 to MP; US National Science Foundation Graduate Research Fellowship award DGE0750616 to JNP; AWW and JP are funded by The Wellcome Trust (Grant No. WT098051).Peer reviewedPublisher PD

Multivariable association discovery in population-scale meta-omics studies.

It is challenging to associate features such as human health outcomes, diet, environmental conditions, or other metadata to microbial community measurements, due in part to their quantitative properties. Microbiome multi-omics are typically noisy, sparse (zero-inflated), high-dimensional, extremely non-normal, and often in the form of count or compositional measurements. Here we introduce an optimized combination of novel and established methodology to assess multivariable association of microbial community features with complex metadata in population-scale observational studies. Our approach, MaAsLin 2 (Microbiome Multivariable Associations with Linear Models), uses generalized linear and mixed models to accommodate a wide variety of modern epidemiological studies, including cross-sectional and longitudinal designs, as well as a variety of data types (e.g., counts and relative abundances) with or without covariates and repeated measurements. To construct this method, we conducted a large-scale evaluation of a broad range of scenarios under which straightforward identification of meta-omics associations can be challenging. These simulation studies reveal that MaAsLin 2\u27s linear model preserves statistical power in the presence of repeated measures and multiple covariates, while accounting for the nuances of meta-omics features and controlling false discovery. We also applied MaAsLin 2 to a microbial multi-omics dataset from the Integrative Human Microbiome (HMP2) project which, in addition to reproducing established results, revealed a unique, integrated landscape of inflammatory bowel diseases (IBD) across multiple time points and omics profiles

Minimal genetic change in Vibrio cholerae in Mozambique over time: Multilocus variable number tandem repeat analysis and whole genome sequencing.

Although cholera is a major public health concern in Mozambique, its transmission patterns remain unknown. We surveyed the genetic relatedness of 75 Vibrio cholerae isolates from patients at Manhiça District Hospital between 2002-2012 and 3 isolates from river using multilocus variable-number tandem-repeat analysis (MLVA) and whole genome sequencing (WGS). MLVA revealed 22 genotypes in two clonal complexes and four unrelated genotypes. WGS revealed i) the presence of recombination, ii) 67 isolates descended monophyletically from a single source connected to Wave 3 of the Seventh Pandemic, and iii) four clinical isolates lacking the cholera toxin gene. This Wave 3 strain persisted for at least eight years in either an environmental reservoir or circulating within the human population. Our data raises important questions related to where these isolates persist and how identical isolates can be collected years apart despite our understanding of high change rate of MLVA loci and the V. cholerae molecular clock

Microbiota that affect risk for shigellosis in children in low-income countries

Pathogens in the gastrointestinal tract exist within a vast population of microbes. We examined associations between pathogens and composition of gut microbiota as they relate to Shigella spp./enteroinvasive Escherichia coli infection. We analyzed 3,035 stool specimens (1,735 nondiarrheal and 1,300 moderate-to-severe diarrheal) from the Global Enteric Multicenter Study for 9 enteropathogens. Diarrheal specimens had a higher number of enteropathogens (diarrheal mean 1.4, nondiarrheal mean 0.95; p<0.0001). Rotavirus showed a negative association with Shigella spp. in cases of diarrhea (odds ratio 0.31, 95% CI 0.17–0.55) and had a large combined effect on moderate-to-severe diarrhea (odds ratio 29, 95% CI 3.8–220). In 4 Lactobacillus taxa identified by 16S rRNA gene sequencing, the association between pathogen and disease was decreased, which is consistent with the possibility that Lactobacillus spp. are protective against Shigella spp.–induced diarrhea. Bacterial diversity of gut microbiota was associated with diarrhea status, not high levels of the Shigella spp. ipaH gene.publishedVersio

Pathogen-induced activation of disease-suppressive functions in the endophytic root microbiome

Microorganisms living inside plants can promote plant growth and health, but their genomic and functional diversity remain largely elusive. Here, metagenomics and network inference show that fungal infection of plant roots enriched for Chitinophagaceae and Flavobacteriaceae in the root endosphere and for chitinase genes and various unknown biosynthetic gene clusters encoding the production of nonribosomal peptide synthetases (NRPSs) and polyketide synthases (PKSs). After strain-level genome reconstruction, a consortium of Chitinophaga and Flavobacterium was designed that consistently suppressed fungal root disease. Site-directed mutagenesis then revealed that a previously unidentified NRPS-PKS gene cluster from Flavobacterium was essential for disease suppression by the endophytic consortium. Our results highlight that endophytic root microbiomes harbor a wealth of as yet unknown functional traits that, in concert, can protect the plant inside out.</p

Mentholation affects the cigarette microbiota by selecting for bacteria resistant to harsh environmental conditions and selecting against potential bacterial pathogens

There is a paucity of data regarding the microbial constituents of tobacco products and their impacts on public health. Moreover, there has been no comparative characterization performed on the bacterial microbiota associated with the addition of menthol, an additive that has been used by tobacco manufacturers for nearly a century. To address this knowledge gap, we conducted bacterial community profiling on tobacco from user- and custom-mentholated/non-mentholated cigarette pairs, as well as a commercially-mentholated product. Total genomic DNA was extracted using a multi-step enzymatic and mechanical lysis protocol followed by PCR amplification of the V3-V4 hypervariable regions of the 16S rRNA gene from five cigarette products (18 cigarettes per product for a total of 90 samples): Camel Crush, user-mentholated Camel Crush, Camel Kings, custom-mentholated Camel Kings, and Newport Menthols. Sequencing was performed on the Illumina MiSeq platform and sequences were processed using the Quantitative Insights Into Microbial Ecology (QIIME) software package. In all products, Pseudomonas was the most abundant genera and included Pseudomonas oryzihabitans and Pseudomonas putida, regardless of mentholation status. However, further comparative analysis of the five products revealed significant differences in the bacterial compositions across products. Bacterial community richness was higher among non-mentholated products compared to those that were mentholated, particularly those that were custom-mentholated. In addition, mentholation appeared to be correlated with a reduction in potential human bacterial pathogens and an increase in bacterial species resistant to harsh environmental conditions. Taken together, these data provide preliminary evidence that the mentholation of commercially available cigarettes can impact the bacterial community of these products.https://doi.org/10.1186/s40168-017-0235-

Signal transducer and activator of transcription 1 (STAT1) gain-of-function mutations and disseminated coccidioidomycosis and histoplasmosis

Background: Impaired signaling in the IFN-g/IL-12 pathway causes susceptibility to severe disseminated infections with mycobacteria and dimorphic yeasts. Dominant gain-of-function mutations in signal transducer and activator of transcription 1 (STAT1) have been associated with chronic mucocutaneous candidiasis. Objective: We sought to identify the molecular defect in patients with disseminated dimorphic yeast infections. Methods: PBMCs, EBV-transformed B cells, and transfected U3A cell lines were studied for IFN-g/IL-12 pathway function. STAT1 was sequenced in probands and available relatives. Interferon-induced STAT1 phosphorylation, transcriptional responses, protein-protein interactions, target gene activation, and function were investigated. Results: We identified 5 patients with disseminated Coccidioides immitis or Histoplasma capsulatum with heterozygous missense mutations in the STAT1 coiled-coil or DNA-binding domains. These are dominant gain-of-function mutations causing enhanced STAT1 phosphorylation, delayed dephosphorylation, enhanced DNA binding and transactivation, and enhanced interaction with protein inhibitor of activated STAT1. The mutations caused enhanced IFN-g–induced gene expression, but we found impaired responses to IFN-g restimulation. Conclusion: Gain-of-function mutations in STAT1 predispose to invasive, severe, disseminated dimorphic yeast infections, likely through aberrant regulation of IFN-g–mediated inflammationFil: Sampaio, Elizabeth P.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados Unidos. Instituto Oswaldo Cruz. Laboratorio de Leprologia; BrasilFil: Hsu, Amy P.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Pechacek, Joseph. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Hannelore I.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados Unidos. Erasmus Medical Center. Department of Medical Microbiology and Infectious Disease; Países BajosFil: Dias, Dalton L.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Paulson, Michelle L.. Clinical Research Directorate/CMRP; Estados UnidosFil: Chandrasekaran, Prabha. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Rosen, Lindsey B.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Carvalho, Daniel S.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados Unidos. Instituto Oswaldo Cruz, Laboratorio de Leprologia; BrasilFil: Ding, Li. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Vinh, Donald C.. McGill University Health Centre. Division of Infectious Diseases; CanadáFil: Browne, Sarah K.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Datta, Shrimati. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Allergic Diseases. Allergic Inflammation Unit; Estados UnidosFil: Milner, Joshua D.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Allergic Diseases. Allergic Inflammation Unit; Estados UnidosFil: Kuhns, Douglas B.. Clinical Services Program; Estados UnidosFil: Long Priel, Debra A.. Clinical Services Program; Estados UnidosFil: Sadat, Mohammed A.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Host Defenses. Infectious Diseases Susceptibility Unit; Estados UnidosFil: Shiloh, Michael. University of Texas. Southwestern Medical Center. Division of Infectious Diseases; Estados UnidosFil: De Marco, Brendan. University of Texas. Southwestern Medical Center. Division of Infectious Diseases; Estados UnidosFil: Alvares, Michael. University of Texas. Southwestern Medical Center. Division of Allergy and Immunology; Estados UnidosFil: Gillman, Jason W.. University of Texas. Southwestern Medical Center. Division of Infectious Diseases; Estados UnidosFil: Ramarathnam, Vivek. University of Texas. Southwestern Medical Center. Division of Infectious Diseases; Estados UnidosFil: de la Morena, Maite. University of Texas. Southwestern Medical Center. Division of Allergy and Immunology; Estados UnidosFil: Bezrodnik, Liliana. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutierrez"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Moreira, Ileana. Gobierno de la Ciudad de Buenos Aires. Hospital General de Niños "Ricardo Gutierrez"; ArgentinaFil: Uzel, Gulbu. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Johnson, Daniel. University of Chicago. Comer Children; Estados UnidosFil: Spalding, Christine. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Zerbe, Christa S.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados UnidosFil: Wiley, Henry. National Eye Institute. Clinical Trials Branch; Estados UnidosFil: Greenberg, David E.. University of Texas. Southwestern Medical Center. Division of Infectious Diseases; Estados UnidosFil: Hoover, Susan E.. University of Arizona. College of Medicine. Valley Fever Center for Excellence; Estados UnidosFil: Rosenzweig, Sergio D.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Host Defenses Infectious Diseases Susceptibility Unit; Estados Unidos. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Primary Immunodeficiency Clinic; Estados UnidosFil: Galgiani, John N.. University of Arizona. College of Medicine. Valley Fever Center for Excellence; Estados UnidosFil: Holland, Steven M.. National Institutes of Health. National Institute of Allergy and Infectious Diseases. Laboratory of Clinical Infectious Diseases. Immunopathogenesis Section; Estados Unido