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Bry, Lynn

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Bry, Lynn
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    Thymus-derived regulatory T cells control tolerance to commensal microbiota
    (2013) Cebula, Anna; Seweryn, Michal; Rempala, Grzegorz A.; Pabla, Simarjot Singh; McIndoe, Richard A.; Denning, Timothy L.; Bry, Lynn; Kraj, Piotr; Kisielow, Pawel; Ignatowicz, Leszek
    Peripheral mechanisms preventing autoimmunity and maintaining tolerance to commensal microbiota involve CD4+Foxp3+ regulatory T cells1,2 generated in the thymus (tTregs) or extrathymically by induction of naive CD4+Foxp3− T cells (iTregs). Prior studies suggested that the T cell receptor (TCR) repertoires of tTregs and iTregs are biased towards self and non-self antigens, respectively 3–6 but their relative contribution in controlling immunopathology, e.g. colitis and other untoward inflammatory responses triggered by different types of antigens, remains unresolved 7. The intestine, and especially the colon, is a particularly suitable organ to study this question, given the variety of self-, microbiota- and food-derived antigens to which Tregs and other T cell populations are exposed. Intestinal environments can enhance conversion to a regulatory lineage 8,9 and favor tolerogenic presentation of antigens to naive CD4+ T cells 10,11, suggesting that intestinal homeostasis depends on microbiota-specific iTregs 12–15. Here, to identify the origin and antigen-specificity of intestinal Tregs, we performed single cell as well as high-throughput (HT) sequencing of the TCR repertoires of CD4+Foxp3+ and CD4+Foxp3− T cells and analyzed their reactivity against specific commensal species. We show that tTregs constitute the majority of Tregs in all lymphoid and intestinal organs, including colon, where their repertoire is heavily influenced by the composition of the microbiota. Our results suggest that tTregs, and not iTregs, dominantly mediate tolerance to antigens produced by intestinal commensals.
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    Dynamics of the Microbiota in Response to Host Infection
    (Public Library of Science, 2014) Belzer, Clara; Gerber, Georg; Roeselers, Guus; Delaney, Mary; DuBois, Andrea; Liu, Qing; Belavusava, Vera; Yeliseyev, Vladimir; Houseman, Andres; Onderdonk, Andrew; Cavanaugh, Colleen; Bry, Lynn
    Longitudinal studies of the microbiota are important for discovering changes in microbial communities that affect the host. The complexity of these ecosystems requires rigorous integrated experimental and computational methods to identify temporal signatures that promote physiologic or pathophysiologic responses in vivo. Employing a murine model of infectious colitis with the pathogen Citrobacter rodentium, we generated a 2-month time-series of 16S rDNA gene profiles, and quantitatively cultured commensals, from multiple intestinal sites in infected and uninfected mice. We developed a computational framework to discover time-varying signatures for individual taxa, and to automatically group signatures to identify microbial sub-communities within the larger gut ecosystem that demonstrate common behaviors. Application of this model to the 16S rDNA dataset revealed dynamic alterations in the microbiota at multiple levels of resolution, from effects on systems-level metrics to changes across anatomic sites for individual taxa and species. These analyses revealed unique, time-dependent microbial signatures associated with host responses at different stages of colitis. Signatures included a Mucispirillum OTU associated with early disruption of the colonic surface mucus layer, prior to the onset of symptomatic colitis, and members of the Clostridiales and Lactobacillales that increased with successful resolution of inflammation, after clearance of the pathogen. Quantitative culture data validated findings for predominant species, further refining and strengthening model predictions. These findings provide new insights into the complex behaviors found within host ecosystems, and define several time-dependent microbial signatures that may be leveraged in studies of other infectious or inflammatory conditions.
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    The business of genomic testing: a survey of early adopters
    (Nature Publishing Group, 2014) Crawford, James M.; Bry, Lynn; Pfeifer, John; Caughron, Samuel K.; Black-Schaffer, Stephen; Kant, Jeffrey A.; Kaufman, Jill H.
    Purpose: The practice of “genomic” (or “personalized”) medicine requires the availability of appropriate diagnostic testing. Our study objective was to identify the reasons for health systems to bring next-generation sequencing into their clinical laboratories and to understand the process by which such decisions were made. Such information may be of value to other health systems seeking to provide next-generation sequencing testing to their patient populations. Methods: A standardized open-ended interview was conducted with the laboratory medical directors and/or department of pathology chairs of 13 different academic institutions in 10 different states. Results: Genomic testing for cancer dominated the institutional decision making, with three primary reasons: more effective delivery of cancer care, the perceived need for institutional leadership in the field of genomics, and the premise that genomics will eventually be cost-effective. Barriers to implementation included implementation cost; the time and effort needed to maintain this newer testing; challenges in interpreting genetic variants; establishing the bioinformatics infrastructure; and curating data from medical, ethical, and legal standpoints. Ultimate success depended on alignment with institutional strengths and priorities and working closely with institutional clinical programs. Conclusion: These early adopters uniformly viewed genomic analysis as an imperative for developing their expertise in the implementation and practice of genomic medicine.
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    Alterations of the human gut microbiome in multiple sclerosis
    (Nature Publishing Group, 2016) Jangi, Sushrut; Gandhi, Roopali; Cox, Laura; Li, Ning; von Glehn, Felipe; Yan, Raymond; Patel, Bonny; Mazzola, Maria; Liu, Shirong; Glanz, Bonnie; Cook, Sandra; Tankou, Stephanie; Stuart, Fiona; Melo, Kirsy; Nejad, Parham; Smith, Kathleen; Topçuolu, Begüm D.; Holden, James; Kivisakk, Pia; Chitnis, Tanuja; De Jager, Philip; Quintana, Francisco; Gerber, Georg; Bry, Lynn; Weiner, Howard
    The gut microbiome plays an important role in immune function and has been implicated in several autoimmune disorders. Here we use 16S rRNA sequencing to investigate the gut microbiome in subjects with multiple sclerosis (MS, n=60) and healthy controls (n=43). Microbiome alterations in MS include increases in Methanobrevibacter and Akkermansia and decreases in Butyricimonas, and correlate with variations in the expression of genes involved in dendritic cell maturation, interferon signalling and NF-kB signalling pathways in circulating T cells and monocytes. Patients on disease-modifying treatment show increased abundances of Prevotella and Sutterella, and decreased Sarcina, compared with untreated patients. MS patients of a second cohort show elevated breath methane compared with controls, consistent with our observation of increased gut Methanobrevibacter in MS in the first cohort. Further study is required to assess whether the observed alterations in the gut microbiome play a role in, or are a consequence of, MS pathogenesis.
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    MDSINE: Microbial Dynamical Systems INference Engine for microbiome time-series analyses
    (BioMed Central, 2016) Bucci, Vanni; Tzen, Belinda; Li, Ning; Simmons, Matt; Tanoue, Takeshi; Bogart, Elijah; Deng, Luxue; Yeliseyev, Vladimir; Delaney, Mary; Liu, Qing; Olle, Bernat; Stein, Richard R.; Honda, Kenya; Bry, Lynn; Gerber, Georg
    Predicting dynamics of host-microbial ecosystems is crucial for the rational design of bacteriotherapies. We present MDSINE, a suite of algorithms for inferring dynamical systems models from microbiome time-series data and predicting temporal behaviors. Using simulated data, we demonstrate that MDSINE significantly outperforms the existing inference method. We then show MDSINE’s utility on two new gnotobiotic mice datasets, investigating infection with Clostridium difficile and an immune-modulatory probiotic. Using these datasets, we demonstrate new capabilities, including accurate forecasting of microbial dynamics, prediction of stable sub-communities that inhibit pathogen growth, and identification of bacteria most crucial to community integrity in response to perturbations. Electronic supplementary material The online version of this article (doi:10.1186/s13059-016-0980-6) contains supplementary material, which is available to authorized users.
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    Genomically Informed Surveillance for Carbapenem-Resistant Enterobacteriaceae in a Health Care System
    (American Society of Microbiology, 2015) Pecora, Nicole D.; Li, Ning; Allard, Marc; Li, Cong; Albano, Esperanza; Delaney, Mary; Dubois, Andrea; Onderdonk, Andrew; Bry, Lynn
    ABSTRACT Carbapenem-resistant Enterobacteriaceae (CRE) are an urgent public health concern. Rapid identification of the resistance genes, their mobilization capacity, and strains carrying them is essential to direct hospital resources to prevent spread and improve patient outcomes. Whole-genome sequencing allows refined tracking of both chromosomal traits and associated mobile genetic elements that harbor resistance genes. To enhance surveillance of CREs, clinical isolates with phenotypic resistance to carbapenem antibiotics underwent whole-genome sequencing. Analysis of 41 isolates of Klebsiella pneumoniae and Enterobacter cloacae, collected over a 3-year period, identified K. pneumoniae carbapenemase (KPC) genes encoding KPC-2, −3, and −4 and OXA-48 carbapenemases. All occurred within transposons, including multiple Tn4401 transposon isoforms, embedded within more than 10 distinct plasmids representing incompatibility (Inc) groups IncR, -N, -A/C, -H, and -X. Using short-read sequencing, draft maps were generated of new KPC-carrying vectors, several of which were derivatives of the IncN plasmid pBK31551. Two strains also had Tn4401 chromosomal insertions. Integrated analyses of plasmid profiles and chromosomal single-nucleotide polymorphism (SNP) profiles refined the strain patterns and provided a baseline hospital mobilome to facilitate analysis of new isolates. When incorporated with patient epidemiological data, the findings identified limited outbreaks against a broader 3-year period of sporadic external entry of many different strains and resistance vectors into the hospital. These findings highlight the utility of genomic analyses in internal and external surveillance efforts to stem the transmission of drug-resistant strains within and across health care institutions.
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    Implementation of Electronic Consent at a Biobank: An Opportunity for Precision Medicine Research
    (MDPI, 2016) Boutin, Natalie T.; Mathieu, Kathleen; Hoffnagle, Alison G.; Allen, Nicole L.; Castro, Victor M.; Morash, Megan; O’Rourke, P. Pearl; Hohmann, Elizabeth; Herring, Neil; Bry, Lynn; Slaugenhaupt, Susan; Karlson, Elizabeth; Weiss, Scott; Smoller, Jordan
    The purpose of this study is to characterize the potential benefits and challenges of electronic informed consent (eIC) as a strategy for rapidly expanding the reach of large biobanks while reducing costs and potentially enhancing participant engagement. The Partners HealthCare Biobank (Partners Biobank) implemented eIC tools and processes to complement traditional recruitment strategies in June 2014. Since then, the Partners Biobank has rigorously collected and tracked a variety of metrics relating to this novel recruitment method. From June 2014 through January 2016, the Partners Biobank sent email invitations to 184,387 patients at Massachusetts General Hospital and Brigham and Women’s Hospital. During the same time period, 7078 patients provided their consent via eIC. The rate of consent of emailed patients was 3.5%, and the rate of consent of patients who log into the eIC website at Partners Biobank was 30%. Banking of biospecimens linked to electronic health records has become a critical element of genomic research and a foundation for the NIH’s Precision Medicine Initiative (PMI). eIC is a feasible and potentially game-changing strategy for these large research studies that depend on patient recruitment.
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    Improving microbial fitness in the mammalian gut by in vivo temporal functional metagenomics
    (BlackWell Publishing Ltd, 2015) Yaung, Stephanie J.; Deng, Luxue; Li, Ning; Braff, Jonathan; Church, George; Bry, Lynn; Wang, Harris H; Gerber, Georg
    Elucidating functions of commensal microbial genes in the mammalian gut is challenging because many commensals are recalcitrant to laboratory cultivation and genetic manipulation. We present Temporal FUnctional Metagenomics sequencing (TFUMseq), a platform to functionally mine bacterial genomes for genes that contribute to fitness of commensal bacteria in vivo. Our approach uses metagenomic DNA to construct large-scale heterologous expression libraries that are tracked over time in vivo by deep sequencing and computational methods. To demonstrate our approach, we built a TFUMseq plasmid library using the gut commensal Bacteroides thetaiotaomicron (Bt) and introduced Escherichia coli carrying this library into germfree mice. Population dynamics of library clones revealed Bt genes conferring significant fitness advantages in E. coli over time, including carbohydrate utilization genes, with a Bt galactokinase central to early colonization, and subsequent dominance by a Bt glycoside hydrolase enabling sucrose metabolism coupled with co-evolution of the plasmid library and E. coli genome driving increased galactose utilization. Our findings highlight the utility of functional metagenomics for engineering commensal bacteria with improved properties, including expanded colonization capabilities in vivo.
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    Maternal intestinal flora and wheeze in early childhood
    (Wiley-Blackwell, 2011) Lange, Nancy E; Celedón, Juan C.; Forno, Erick; Ly, Ngoc P.; Onderdonk, Andrew; Bry, Lynn; Delaney, Mary; DuBois, Andrea M.; Gold, Diane; Weiss, Scott; Litonjua, Augusto A.
    Background: Increasing evidence links altered intestinal flora in infancy to eczema and asthma. No studies have investigated the influence of maternal intestinal flora on wheezing and eczema in early childhood. Objective: To investigate the link between maternal intestinal flora during pregnancy and development of wheeze and eczema in infancy. Methods: Sixty pregnant women from the Boston area gave stool samples during the third trimester of their pregnancy and answered questions during pregnancy about their own health, and about their children’s health when the child was 2 and 6 months of age. Quantitative culture was performed on stool samples and measured in log10colony-forming units(CFU)/gram stool. Primary outcomes included infant wheeze and eczema in the first 6 months of life. Atopic wheeze, defined as wheeze and eczema, was analyzed as a secondary outcome. Results: In multivariate models adjusted for breastfeeding, daycare attendance and maternal atopy, higher counts of maternal total aerobes (TA) and enterococci (E) were associated with increased risk of infant wheeze (TA: OR 2.32 for 1 log increase in CFU/g stool [95% CI 1.22, 4.42]; E: OR 1.57 [95% CI 1.06, 2.31]). No organisms were associated with either eczema or atopic wheeze. Conclusions & Clinical Relevance: In our cohort, higher maternal total aerobes and enterococci were related to increased risk of infant wheeze. Maternal intestinal flora may be an important environmental exposure in early immune system development.
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    Inferring Dynamic Signatures of Microbes in Complex Host Ecosystems
    (Public Library of Science, 2012) Gerber, Georg; Onderdonk, Andrew; Bry, Lynn
    The human gut microbiota comprise a complex and dynamic ecosystem that profoundly affects host development and physiology. Standard approaches for analyzing time-series data of the microbiota involve computation of measures of ecological community diversity at each time-point, or measures of dissimilarity between pairs of time-points. Although these approaches, which treat data as static snapshots of microbial communities, can identify shifts in overall community structure, they fail to capture the dynamic properties of individual members of the microbiota and their contributions to the underlying time-varying behavior of host ecosystems. To address the limitations of current methods, we present a computational framework that uses continuous-time dynamical models coupled with Bayesian dimensionality adaptation methods to identify time-dependent signatures of individual microbial taxa within a host as well as across multiple hosts. We apply our framework to a publicly available dataset of 16S rRNA gene sequences from stool samples collected over ten months from multiple human subjects, each of whom received repeated courses of oral antibiotics. Using new diversity measures enabled by our framework, we discover groups of both phylogenetically close and distant bacterial taxa that exhibit consensus responses to antibiotic exposure across multiple human subjects. These consensus responses reveal a timeline for equilibration of sub-communities of micro-organisms with distinct physiologies, yielding insights into the successive changes that occur in microbial populations in the human gut after antibiotic treatments. Additionally, our framework leverages microbial signatures shared among human subjects to automatically design optimal experiments to interrogate dynamic properties of the microbiota in new studies. Overall, our approach provides a powerful, general-purpose framework for understanding the dynamic behaviors of complex microbial ecosystems, which we believe will prove instrumental for future studies in this field.