Arthur Brady

Phymm and PhymmBL: Metagenomic Phylogenetic Classification with Interpolated Markov Models

Metagenomics projects collect DNA from uncharacterized environments that may contain thousands of species per sample. One main challenge facing metagenomic analysis is phylogenetic classification of raw sequence reads into groups representing the same or similar taxa, a prerequisite for genome assembly and for analyzing the biological diversity of a sample. New sequencing technologies have made metagenomics easier, by making sequencing faster, and more difficult, by producing shorter reads than previous technologies. Classifying sequences from reads as short as 100 base pairs has until now been relatively inaccurate, requiring researchers to use older, long-read technologies. We present Phymm, a classifier for metagenomic data, that has been trained on 539 complete, curated genomes and can accurately classify reads as short as 100 base pairs, a substantial improvement over previous composition-based classification methods. We also describe how combining Phymm with sequence alignment algorithms improves accuracy.

PhymmBL expanded: confidence scores, custom databases, parallelization and more

To the Editor: PhymmBL1 is a classification system designed for metagenomics experiments that assigns taxonomic labels to short DNA reads. Since the introduction of PhymmBL in 2009, we made extensive changes and added new features, of which we outline the most important ones here (Supplementary Table 1). We also describe results indicating that PhymmBL effectively classifies samples containing mixed eukaryotic and prokaryotic DNA. PhymmBL combines two components: (i) composition-directed taxonomic predictions from Phymm and (ii) basic local alignment search tool (BLAST)-based homology results2. PhymmBL combines these to label each input sequence with its best guess as to the taxonomy of the source organism. Input sequences as short as 100 base pairs can be phylogenetically classified with PhymmBL more accurately than with any other existing method1 including recently introduced methods (Supplementary Note 1). PhymmBL predicts species, genus, family, order, class and phylum for each read, allowing users to arrange results according to levels of specificity relevant to their research goals. We describe how to configure and operate PhymmBL in a parallelized or grid environment in Supplementary Note 2. PhymmBL’s open-source software runs on all UNIX-like systems, is written in Perl and C++ and can be downloaded free of charge (http://www.cbcb.umd.edu/software/phymmbl/; currently version 3.2). To demonstrate PhymmBL’s ability to classify eukaryotic DNA, we classified 2,278,901 short reads (average, 276 base pairs) from a permafrost-preserved woolly mammoth bone metagenome3. Before classification, we added a variety of genomes to PhymmBL’s local database, representing plants, multicellular animals and protests (Supplementary Table 2). We also built models for the elephant (Loxodonta africana) genome (Elephant Genome Project), expecting that woolly mammoth reads would be labeled as elephant. Our goal was to examine whether PhymmBL could identify eukaryotic DNA as accurately as it had identified bacterial DNA. The most abundant label (59.7%) was indeed elephant (Fig. 1). The next three most abundant predictions were Flavobacterium johnsoniae (2.4%), Polaromonas naphthalenivorans (1.6%) and Polaromonas sp. JS666 (1.0%), all three of which are known Arctic bacteria. These likely represent modern bacterial species present on the mammoth bone. PhymmBL therefore effectively separated eukaryotic from prokaryotic reads and accurately predicted the closest relative of the particular eukaryote that was sequenced, despite the presence of other potentially competing eukaryotic genomes in the local database. Details of the computational resources used by PhymmBL are available in Supplementary Note 3. Figure 1 Screenshot of predicted genus-level taxonomic distribution for the mammoth metagenome, focused on genus Loxodonta. PhymmBL output now includes scores reflecting the software’s confidence that its predictions are correct. A confidence score between 0 and 1 appears with each clade-level prediction for each input read. Polynomial functions estimate accuracy, mapping read length and raw score to these normalized confidence scores. For notes on use and algorithmic details of the confidence score computation, see Supplementary Note 4. Users now can add an arbitrary amount of custom genomic data (as single genomes or in batches) to their PhymmBL database, eliminating exclusive reliance on RefSeq bacterial and archaeal genomes. The default classification database can be augmented with private (or even synthetic) genomes or with additional publicly available genomic data. Eukaryotic and viral sequences can also be added, expanding PhymmBL’s classification mandate beyond prokaryotes. For viewing PhymmBL output (Fig. 1), the freely available Krona package (http://krona.sourceforge.net/) provides an interactive viewer (B. Ondov, N. Bergman and A. Phillippy; personal communication). Krona offers an intuitive HTML5 interface that helps users explore predicted taxonomies for metagenomic read sets. Interacting with a dynamic radial visualization (Fig. 1) that changes to highlight designated areas of interest, users can view predictions for their sample population at different levels of phylogenetic granularity, with clade metadata and population statistics displayed alongside.

Strains, functions and dynamics in the expanded Human Microbiome Project

The characterization of baseline microbial and functional diversity in the human microbiome has enabled studies of microbiome-related disease, diversity, biogeography, and molecular function. The National Institutes of Health Human Microbiome Project has provided one of the broadest such characterizations so far. Here we introduce a second wave of data from the study, comprising 1,631 new metagenomes (2,355 total) targeting diverse body sites with multiple time points in 265 individuals. We applied updated profiling and assembly methods to provide new characterizations of microbiome personalization. Strain identification revealed subspecies clades specific to body sites; it also quantified species with phylogenetic diversity under-represented in isolate genomes. Body-wide functional profiling classified pathways into universal, human-enriched, and body site-enriched subsets. Finally, temporal analysis decomposed microbial variation into rapidly variable, moderately variable, and stable subsets. This study furthers our knowledge of baseline human microbial diversity and enables an understanding of personalized microbiome function and dynamics.

Functional Dynamics of the Gut Microbiome in Elderly People during Probiotic Consumption

ABSTRACT A mechanistic understanding of the purported health benefits conferred by consumption of probiotic bacteria has been limited by our knowledge of the resident gut microbiota and its interaction with the host. Here, we detail the impact of a single-organism probiotic, Lactobacillus rhamnosus GG ATCC 53103 (LGG), on the structure and functional dynamics (gene expression) of the gut microbiota in a study of 12 healthy individuals, 65 to 80 years old. The analysis revealed that while the overall community composition was stable as assessed by 16S rRNA profiling, the transcriptional response of the gut microbiota was modulated by probiotic treatment. Comparison of transcriptional profiles based on taxonomic composition yielded three distinct transcriptome groups that displayed considerable differences in functional dynamics. The transcriptional profile of LGG in vivo was remarkably concordant across study subjects despite the considerable interindividual nature of the gut microbiota. However, we identified genes involved in flagellar motility, chemotaxis, and adhesion from Bifidobacterium and the dominant butyrate producers Roseburia and Eubacterium whose expression was increased during probiotic consumption, suggesting that LGG may promote interactions between key constituents of the microbiota and the host epithelium. These results provide evidence for the discrete functional effects imparted by a specific single-organism probiotic and challenge the prevailing notion that probiotics substantially modify the resident microbiota within nondiseased individuals in an appreciable fashion. IMPORTANCE Probiotic bacteria have been used for over a century to promote digestive health. Many individuals report that probiotics alleviate a number of digestive issues, yet little evidence links how probiotic microbes influence human health. Here, we show how the resident microbes that inhabit the healthy human gut respond to a probiotic. The well-studied probiotic Lactobacillus rhamnosus GG ATCC 53103 (LGG) was administered in a clinical trial, and a suite of measurements of the resident microbes were taken to evaluate potential changes over the course of probiotic consumption. We found that LGG transiently enriches for functions to potentially promote anti-inflammatory pathways in the resident microbes. Probiotic bacteria have been used for over a century to promote digestive health. Many individuals report that probiotics alleviate a number of digestive issues, yet little evidence links how probiotic microbes influence human health. Here, we show how the resident microbes that inhabit the healthy human gut respond to a probiotic. The well-studied probiotic Lactobacillus rhamnosus GG ATCC 53103 (LGG) was administered in a clinical trial, and a suite of measurements of the resident microbes were taken to evaluate potential changes over the course of probiotic consumption. We found that LGG transiently enriches for functions to potentially promote anti-inflammatory pathways in the resident microbes.

MetaRef: a pan-genomic database for comparative and community microbial genomics

Microbial genome sequencing is one of the longest-standing areas of biological database development, but high-throughput, low-cost technologies have increased its throughput to an unprecedented number of new genomes per year. Several thousand microbial genomes are now available, necessitating new approaches to organizing information on gene function, phylogeny and microbial taxonomy to facilitate downstream biological interpretation. MetaRef, available at http://metaref.org, is a novel online resource systematically cataloguing a comprehensive pan-genome of all microbial clades with sequenced isolates. It organizes currently available draft and finished bacterial and archaeal genomes into quality-controlled clades, reports all core and pan gene families at multiple levels in the resulting taxonomy, and it annotates families’ conservation, phylogeny and consensus functional information. MetaRef also provides a comprehensive non-redundant reference gene catalogue for metagenomic studies, including the abundance and prevalence of all gene families in the >700 shotgun metagenomic samples of the Human Microbiome Project. This constitutes a systematic mapping of clade-specific microbial functions within the healthy human microbiome across multiple body sites and can be used as reference for identifying potential functional biomarkers in disease-associate microbiomes. MetaRef provides all information both as an online browsable resource and as downloadable sequences and tabular data files that can be used for subsequent offline studies.

Fault Tolerance in Protein Interaction Networks: Stable Bipartite Subgraphs and Redundant Pathways

As increasing amounts of high-throughput data for the yeast interactome become available, more system-wide properties are uncovered. One interesting question concerns the fault tolerance of protein interaction networks: whether there exist alternative pathways that can perform some required function if a gene essential to the main mechanism is defective, absent or suppressed. A signature pattern for redundant pathways is the BPM (between-pathway model) motif, introduced by Kelley and Ideker. Past methods proposed to search the yeast interactome for BPM motifs have had several important limitations. First, they have been driven heuristically by local greedy searches, which can lead to the inclusion of extra genes that may not belong in the motif; second, they have been validated solely by functional coherence of the putative pathways using GO enrichment, making it difficult to evaluate putative BPMs in the absence of already known biological annotation. We introduce stable bipartite subgraphs, and show they form a clean and efficient way of generating meaningful BPMs which naturally discard extra genes included by local greedy methods. We show by GO enrichment measures that our BPM set outperforms previous work, covering more known complexes and functional pathways. Perhaps most importantly, since our BPMs are initially generated by examining the genetic-interaction network only, the location of edges in the protein-protein physical interaction network can then be used to statistically validate each candidate BPM, even with sparse GO annotation (or none at all). We uncover some interesting biological examples of previously unknown putative redundant pathways in such areas as vesicle-mediated transport and DNA repair.

Erratum: Strains, functions and dynamics in the expanded Human Microbiome Project

This corrects the article DOI: 10.1038/nature23889

Compositional and Functional Differences in the Human Gut Microbiome Correlate with Clinical Outcome following Infection with Wild-Type Salmonella enterica Serovar Typhi

ABSTRACT Insights into disease susceptibility as well as the efficacy of vaccines against typhoid and other enteric pathogens may be informed by better understanding the relationship between the effector immune response and the gut microbiota. In the present study, we characterized the composition (16S rRNA gene profiling) and function (RNA sequencing [RNA-seq]) of the gut microbiota following immunization and subsequent exposure to wild-type Salmonella enterica serovar Typhi in a human challenge model to further investigate the central hypothesis that clinical outcomes may be linked to the gut microbiota. Metatranscriptome analysis of longitudinal stool samples collected from study subjects revealed two stable patterns of gene expression for the human gut microbiota, dominated by transcripts from either Methanobrevibacter or a diverse representation of genera in the Firmicutes phylum. Immunization with one of two live oral attenuated vaccines against S. Typhi had minimal effects on the composition or function of the gut microbiota. It was observed that subjects harboring the methanogen-dominated transcriptome community at baseline displayed a lower risk of developing symptoms of typhoid following challenge with wild-type S. Typhi. Furthermore, genes encoding antioxidant proteins, metal homeostasis and transport proteins, and heat shock proteins were expressed at a higher level at baseline or after challenge with S. Typhi in subjects who did not develop symptoms of typhoid. These data suggest that functional differences relating to redox potential and ion homeostasis in the gut microbiota may impact clinical outcomes following exposure to wild-type S. Typhi. IMPORTANCE S. Typhi is a significant cause of systemic febrile morbidity in settings with poor sanitation and limited access to clean water. It has been demonstrated that the human gut microbiota can influence mucosal immune responses, but there is little information available on the impact of the human gut microbiota on clinical outcomes following exposure to enteric pathogens. Here, we describe differences in the composition and function of the gut microbiota in healthy adult volunteers enrolled in a typhoid vaccine trial and report that these differences are associated with host susceptibility to or protection from typhoid after challenge with wild-type S. Typhi. Our observations have important implications in interpreting the efficacy of oral attenuated vaccines against enteric pathogens in diverse populations. S. Typhi is a significant cause of systemic febrile morbidity in settings with poor sanitation and limited access to clean water. It has been demonstrated that the human gut microbiota can influence mucosal immune responses, but there is little information available on the impact of the human gut microbiota on clinical outcomes following exposure to enteric pathogens. Here, we describe differences in the composition and function of the gut microbiota in healthy adult volunteers enrolled in a typhoid vaccine trial and report that these differences are associated with host susceptibility to or protection from typhoid after challenge with wild-type S. Typhi. Our observations have important implications in interpreting the efficacy of oral attenuated vaccines against enteric pathogens in diverse populations.

Compact routing with additive stretch using distance labelings

Distance labelings -- introduced as a new way to encode graph topology in a distributed fashion -- have been an active area of research (see [1, 2] for details). In both exact and approximate settings, results in distance labelings and compact routing (for an introduction, esp. for definitions of routing tables and headers, see [3]) seem to go hand in hand, but so far these results have been produced separately. It was already known that graphs with constantsized separators such as trees, outerplanar graphs, seriesparallel graphs and graphs of bounded treewidth, support both exact distance labelings and optimal (additive stretch 0, multiplicative stretch 1) compact routing schemes, but there are classes of graphs known to admit exact distance labelings which do not have constant-sized separators. Our main result is to demonstrate that every n-vertex graph which supports an exact distance labeling with O(l(n))-sized labels also supports a compact routing scheme with O(l(n) + log2 n)-sized headers, O(√n(l(n) + log2 n))-sized routing tables, and an additive stretch of 6. Our general result produces the first known compact routing schemes for classes of graphs where no previous compact routing scheme was known, such as permutation graphs.We note that it is possible to improve substantially on our general result for the classes of interval graphs and circular arc graphs (neither of which admits constant-sized separators). In both cases, a compact routing scheme exists with polylogarithmic headers and routing tables, and an additive stretch of 1; due to space constraints, we defer further discussion of these cases to future presentations of this work.