Curtis Huttenhower

Massachusetts Department of Public Health, Boston, Massachusetts, United States

Are you Curtis Huttenhower?

Claim your profile

Publications (17)192.65 Total impact

  • X C Morgan, C Huttenhower
    [Show abstract] [Hide abstract]
    ABSTRACT: Nucleotide sequencing has become increasingly common and affordable, and is now a vital tool for studies of the human microbiome. Comprehensive microbial community surveys such as MetaHit and the Human Microbiome Project have described the composition and molecular functional profile of the healthy (normal) intestinal microbiome. This knowledge will increase our ability to analyze host and microbial DNA (genome) and RNA (transcriptome) sequences. Bioinformatic and statistical tools can then be used to identify dysbioses that might cause disease, and potential treatments. Analyses that identify perturbations in specific molecules can leverage thousands of culture-based isolate genomes to contextualize culture-independent sequences, or may integrate sequence data with whole-community functional assays such as metaproteomic or metabolomic analyses. We review the state of available systems-level models for studies of the intestinal microbiome, along with analytic techniques and tools that can be used to determine its functional capabilities in healthy and unhealthy individuals.
    Gastroenterology 01/2014; · 12.82 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Bacteria that cause disease rely on their ability to counteract and overcome host defenses. Here, we present a genome-scale study of Mycobacterium tuberculosis (Mtb) that uncovers the bacterial determinants of surviving host immunity, sets of genes we term "counteractomes." Through this analysis, we found that CD4 T cells attempt to contain Mtb growth by starving it of tryptophan-a mechanism that successfully limits infections by Chlamydia and Leishmania, natural tryptophan auxotrophs. Mtb, however, can synthesize tryptophan under stress conditions, and thus, starvation fails as an Mtb-killing mechanism. We then identify a small-molecule inhibitor of Mtb tryptophan synthesis, which converts Mtb into a tryptophan auxotroph and restores the efficacy of a failed host defense. Together, our findings demonstrate that the Mtb immune counteractomes serve as probes of host immunity, uncovering immune-mediated stresses that can be leveraged for therapeutic discovery. PAPERFLICK:
    Cell 12/2013; 155(6):1296-308. · 31.96 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Background: Necrotizing enterocolitis (NEC) is a devastating intestinal disease that afflicts 10% of extremely preterm infants. The contribution of early intestinal colonization to NEC onset is not understood, and predictive biomarkers to guide prevention are lacking. We analyzed banked stool and urine samples collected prior to disease onset from infants <29 weeks gestational age, including 11 infants who developed NEC and 21 matched controls who survived free of NEC. Stool bacterial communities were profiled by 16S rRNA gene sequencing. Urinary metabolomic profiles were assessed by NMR. Results: During postnatal days 4 to 9, samples from infants who later developed NEC tended towards lower alpha-diversity (Chao1 index, p=0.086) and lacked Propionibacterium (p=0.009) compared to controls. Furthermore, NEC was preceded by distinct forms of dysbiosis. During days 4 to 9, samples from four NEC cases were dominated by members of the Firmicutes (median relative abundance: >99% vs <17% in the remaining NEC and controls, p<0.001). During postnatal days 10 to 16, samples from the remaining NEC cases were dominated by Proteobacteria, specifically Enterobacteriaceae (median relative abundance >99% vs 38% in the other NEC cases and 84% in controls, p=0.01). NEC preceded by Firmicutes dysbiosis occurred earlier (onset, days 7 to 21) than NEC preceded by Proteobacteria dysbiosis (onset, days 19 to 39). All NEC cases lacked Propionibacterium and were preceded by either Firmicutes (>98% relative abundance, days 4 to 9) or Proteobacteria (>90% relative abundance, days 10 to 16) dysbiosis, while only 25% of controls had this phenotype (predictive value 88%, p=0.001). Analysis of days 4 to 9 urine samples found no metabolites associated with all NEC cases, but alanine was positively associated with NEC cases that were preceded by Firmicutes dysbiosis (p<0.001) and histidine was inversely associated with NEC cases preceded by Proteobacteria dysbiosis (p=0.013). A high urinary alanine:histidine ratio was associated with microbial characteristics (p<0.001) and provided good prediction of overall NEC (predictive value 78%, p=0.007). Conclusions: Early dysbiosis is strongly involved in the pathobiology of NEC. These striking findings require validation in larger studies but indicate that early microbial and metabolomic signatures may provide highly predictive biomarkers of NEC.
    Microbiome Journal. 04/2013; 1(1):13.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Complex microbial communities are an integral part of the Earth's ecosystem and of our bodies in health and disease. In the last two decades, culture-independent approaches have provided new insights into their structure and function, with the exponentially decreasing cost of high-throughput sequencing resulting in broadly available tools for microbial surveys. However, the field remains far from reaching a technological plateau, as both computational techniques and nucleotide sequencing platforms for microbial genomic and transcriptional content continue to improve. Current microbiome analyses are thus starting to adopt multiple and complementary meta'omic approaches, leading to unprecedented opportunities to comprehensively and accurately characterize microbial communities and their interactions with their environments and hosts. This diversity of available assays, analysis methods, and public data is in turn beginning to enable microbiome-based predictive and modeling tools. We thus review here the technological and computational meta'omics approaches that are already available, those that are under active development, their success in biological discovery, and several outstanding challenges.
    Molecular Systems Biology 01/2013; 9:666. · 11.34 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: This article introduces a manually curated data collection for gene expression meta-analysis of patients with ovarian cancer and software for reproducible preparation of similar databases. This resource provides uniformly prepared microarray data for 2970 patients from 23 studies with curated and documented clinical metadata. It allows users to efficiently identify studies and patient subgroups of interest for analysis and to perform meta-analysis immediately without the challenges posed by harmonizing heterogeneous microarray technologies, study designs, expression data processing methods and clinical data formats. We confirm that the recently proposed biomarker CXCL12 is associated with patient survival, independently of stage and optimal surgical debulking, which was possible only through meta-analysis owing to insufficient sample sizes of the individual studies. The database is implemented as the curatedOvarianData Bioconductor package for the R statistical computing language, providing a comprehensive and flexible resource for clinically oriented investigation of the ovarian cancer transcriptome. The package and pipeline for producing it are available from http://bcb.dfci.harvard.edu/ovariancancer. Database URL: http://bcb.dfci.harvard.edu/ovariancancer.
    Database The Journal of Biological Databases and Curation 01/2013; 2013:bat013. · 4.20 Impact Factor
  • Source
    Xochitl C Morgan, Curtis Huttenhower
    [Show abstract] [Hide abstract]
    ABSTRACT: Humans are essentially sterile during gestation, but during and after birth, every body surface, including the skin, mouth, and gut, becomes host to an enormous variety of microbes, bacterial, archaeal, fungal, and viral. Under normal circumstances, these microbes help us to digest our food and to maintain our immune systems, but dysfunction of the human microbiota has been linked to conditions ranging from inflammatory bowel disease to antibiotic-resistant infections. Modern high-throughput sequencing and bioinformatic tools provide a powerful means of understanding the contribution of the human microbiome to health and its potential as a target for therapeutic interventions. This chapter will first discuss the historical origins of microbiome studies and methods for determining the ecological diversity of a microbial community. Next, it will introduce shotgun sequencing technologies such as metagenomics and metatranscriptomics, the computational challenges and methods associated with these data, and how they enable microbiome analysis. Finally, it will conclude with examples of the functional genomics of the human microbiome and its influences upon health and disease.
    PLoS Computational Biology 12/2012; 8(12):e1002808. · 4.87 Impact Factor
  • Xochitl C Morgan, Nicola Segata, Curtis Huttenhower
    [Show abstract] [Hide abstract]
    ABSTRACT: Over the course of our lives, humans are colonized by a tremendous diversity of commensal microbes, which comprise the human microbiome. The collective genetic potential (metagenome) of the human microbiome is orders of magnitude more than the human genome, and it profoundly affects human health and disease in ways we are only beginning to understand. Advances in computing and high-throughput sequencing have enabled population-level surveys such as MetaHIT and the recently released Human Microbiome Project, detailed investigations of the microbiome in human disease, and mechanistic studies employing gnotobiotic model organisms. The resulting knowledge of human microbiome composition, function, and range of variation across multiple body sites has begun to assemble a rich picture of commensal host-microbe and microbe-microbe interactions as well as their roles in human health and disease and their potential as diagnostic and therapeutic tools.
    Trends in Genetics 11/2012; · 9.77 Impact Factor
  • Source
    Dirk Gevers, Mihai Pop, Patrick D Schloss, Curtis Huttenhower
    PLoS Computational Biology 11/2012; 8(11):e1002779. · 4.87 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: BACKGROUND: The inflammatory bowel diseases (IBD) Crohn's disease and ulcerative colitis result from alterations in intestinal microbes and the immune system. However, the precise dysfunctions of microbial metabolism in the gastrointestinal microbiome during IBD remain unclear. We analyzed the microbiota of intestinal biopsies and stool samples from 231 IBD and healthy subjects by 16S gene pyrosequencing and followed up a subset using shotgun metagenomics. Gene and pathway composition were assessed, based in 16S data on phylogenetically-related reference genomes, and associated using sparse multivariate linear modeling with medications, environmental factors, and IBD status. RESULTS: Firmicutes and Enterobacteriaceae abundances were associated with disease status as expected, but also with treatment and subject characteristics. Microbial function, though, was more consistently perturbed than composition, with 12% of analyzed pathways changed compared with 2% of genera. We identified major shifts in oxidative stress pathways, as well as decreased carbohydrate metabolism and amino acid biosynthesis in favor of nutrient transport and uptake. The microbiome of ileal Crohn's disease was notable for increases in virulence and secretion pathways. CONCLUSIONS: This inferred functional metagenomic information provides the first insights into community-wide microbial processes and pathways that underpin IBD pathogenesis.
    Genome biology 09/2012; 13(9):R79. · 10.30 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Identifying genomic elements required for viability is central to our understanding of the basic physiology of bacterial pathogens. Recently, the combination of high-density mutagenesis and deep sequencing has allowed for the identification of required and conditionally required genes in many bacteria. Genes, however, make up only a part of the complex genomes of important bacterial pathogens. Here, we use an unbiased analysis to comprehensively identify genomic regions, including genes, domains, and intergenic elements, required for the optimal growth of Mycobacterium tuberculosis, a major global health pathogen. We found that several proteins jointly contain both domains required for optimal growth and domains that are dispensable. In addition, many non-coding regions, including regulatory elements and non-coding RNAs, are critical for mycobacterial growth. Our analysis shows that the genetic requirements for growth are more complex than can be appreciated using gene-centric analysis.
    PLoS Pathogens 09/2012; 8(9):e1002946. · 8.14 Impact Factor
  • Source
    Nature 06/2012; 486(7402):215–221. · 38.60 Impact Factor
  • Source
    Nature 06/2012; 486(7402):207–214. · 38.60 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: While current major national research efforts (i.e., the NIH Human Microbiome Project) will enable comprehensive metagenomic characterization of the adult human microbiota, how and when these diverse microbial communities take up residence in the host and during reproductive life are unexplored at a population level. Because microbial abundance and diversity might differ in pregnancy, we sought to generate comparative metagenomic signatures across gestational age strata. DNA was isolated from the vagina (introitus, posterior fornix, midvagina) and the V5V3 region of bacterial 16S rRNA genes were sequenced (454FLX Titanium platform). Sixty-eight samples from 24 healthy gravidae (18 to 40 confirmed weeks) were compared with 301 non-pregnant controls (60 subjects). Generated sequence data were quality filtered, taxonomically binned, normalized, and organized by phylogeny and into operational taxonomic units (OTU); principal coordinates analysis (PCoA) of the resultant beta diversity measures were used for visualization and analysis in association with sample clinical metadata. Altogether, 1.4 gigabytes of data containing >2.5 million reads (averaging 6,837 sequences/sample of 493 nt in length) were generated for computational analyses. Although gravidae were not excluded by virtue of a posterior fornix pH >4.5 at the time of screening, unique vaginal microbiome signature encompassing several specific OTUs and higher-level clades was nevertheless observed and confirmed using a combination of phylogenetic, non-phylogenetic, supervised, and unsupervised approaches. Both overall diversity and richness were reduced in pregnancy, with dominance of Lactobacillus species (L. iners crispatus, jensenii and johnsonii, and the orders Lactobacillales (and Lactobacillaceae family), Clostridiales, Bacteroidales, and Actinomycetales. This intergroup comparison using rigorous standardized sampling protocols and analytical methodologies provides robust initial evidence that the vaginal microbial 16S rRNA gene catalogue uniquely differs in pregnancy, with variance of taxa across vaginal subsite and gestational age.
    PLoS ONE 06/2012; 7(6):e36466. · 3.73 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Microbial communities carry out the majority of the biochemical activity on the planet, and they play integral roles in processes including metabolism and immune homeostasis in the human microbiome. Shotgun sequencing of such communities' metagenomes provides information complementary to organismal abundances from taxonomic markers, but the resulting data typically comprise short reads from hundreds of different organisms and are at best challenging to assemble comparably to single-organism genomes. Here, we describe an alternative approach to infer the functional and metabolic potential of a microbial community metagenome. We determined the gene families and pathways present or absent within a community, as well as their relative abundances, directly from short sequence reads. We validated this methodology using a collection of synthetic metagenomes, recovering the presence and abundance both of large pathways and of small functional modules with high accuracy. We subsequently applied this method, HUMAnN, to the microbial communities of 649 metagenomes drawn from seven primary body sites on 102 individuals as part of the Human Microbiome Project (HMP). This provided a means to compare functional diversity and organismal ecology in the human microbiome, and we determined a core of 24 ubiquitously present modules. Core pathways were often implemented by different enzyme families within different body sites, and 168 functional modules and 196 metabolic pathways varied in metagenomic abundance specifically to one or more niches within the microbiome. These included glycosaminoglycan degradation in the gut, as well as phosphate and amino acid transport linked to host phenotype (vaginal pH) in the posterior fornix. An implementation of our methodology is available at http://huttenhower.sph.harvard.edu/humann. This provides a means to accurately and efficiently characterize microbial metabolic pathways and functional modules directly from high-throughput sequencing reads, enabling the determination of community roles in the HMP cohort and in future metagenomic studies.
    PLoS Computational Biology 06/2012; 8(6):e1002358. · 4.87 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: As metagenomic studies continue to increase in their number, sequence volume and complexity, the scalability of biological analysis frameworks has become a rate-limiting factor to meaningful data interpretation. To address this issue, we have developed JCVI Metagenomics Reports (METAREP) as an open source tool to query, browse, and compare extremely large volumes of metagenomic annotations. Here we present improvements to this software including the implementation of a dynamic weighting of taxonomic and functional annotation, support for distributed searches, advanced clustering routines, and integration of additional annotation input formats. The utility of these improvements to data interpretation are demonstrated through the application of multiple comparative analysis strategies to shotgun metagenomic data produced by the National Institutes of Health Roadmap for Biomedical Research Human Microbiome Project (HMP) (http://nihroadmap.nih.gov). Specifically, the scalability of the dynamic weighting feature is evaluated and established by its application to the analysis of over 400 million weighted gene annotations derived from 14 billion short reads as predicted by the HMP Unified Metabolic Analysis Network (HUMAnN) pipeline. Further, the capacity of METAREP to facilitate the identification and simultaneous comparison of taxonomic and functional annotations including biological pathway and individual enzyme abundances from hundreds of community samples is demonstrated by providing scenarios that describe how these data can be mined to answer biological questions related to the human microbiome. These strategies provide users with a reference of how to conduct similar large-scale metagenomic analyses using METAREP with their own sequence data, while in this study they reveal insights into the nature and extent of variation in taxonomic and functional profiles across body habitats and individuals. Over one thousand HMP WGS datasets and the latest open source code are available at http://www.jcvi.org/hmp-metarep.
    PLoS ONE 01/2012; 7(6):e29044. · 3.73 Impact Factor
  • Source
    Curtis Huttenhower
    [Show abstract] [Hide abstract]
    ABSTRACT: A variety of genome-scale functional data is available for many microbial species, but determining the biological functionality and metabolic potential of a sequenced organism remains a significant challenge. Biological network integration and mining algorithms provide a means of assembling this body of data, understanding it from a systems level, and applying it to the study of uncharacterized species and communities. We compare supervised and unsupervised Bayesian approaches to biological network integration; this process provides maps of functional activity and genomewide interactomes in over 100 areas of cellular biology, using information from ~5,000 genome-scale experiments pertaining to 13 microbial species. In combination with graph alignment, these network manipulation tools provide a means for analyzing the functional activity unique to particular pathogens, transferring putative functional annotations to uncharacterized organisms, and potentially inferring interactomes using weighted network integration for metagenomic communities.
  • PLoS Computational Biology 8(6):e1002358. · 4.87 Impact Factor

Publication Stats

439 Citations
192.65 Total Impact Points

Institutions

  • 2014
    • Massachusetts Department of Public Health
      Boston, Massachusetts, United States
  • 2013
    • Università degli Studi di Trento
      Trient, Trentino-Alto Adige, Italy
  • 2012
    • DOE Joint Genome Institute
      Walnut Creek, California, United States
    • Harvard University
      • Department of Biostatistics
      Boston, MA, United States
    • Broad Institute of MIT and Harvard
      Cambridge, Massachusetts, United States