Profiling phylogenetic marker genes, such as the 16S rRNA gene, is a key tool for studies of micr... more Profiling phylogenetic marker genes, such as the 16S rRNA gene, is a key tool for studies of microbial communities but does not provide direct evidence of a community's functional capabilities. Here we describe PICRUSt (phylogenetic investigation of communities by reconstruction of unobserved states), a computational approach to predict the functional composition of a metagenome using marker gene data and a database of reference genomes. PICRUSt uses an extended ancestral-state reconstruction algorithm to predict which gene families are present and then combines gene families to estimate the composite metagenome. Using 16S information, PICRUSt recaptures key findings from the Human Microbiome Project and accurately predicts the abundance of gene families in host-associated and environmental communities, with quantifiable uncertainty. Our results demonstrate that phylogeny and function are sufficiently linked that this 'predictive metagenomic' approach should provide useful insights into the thousands of uncultivated microbial communities for which only marker gene surveys are currently available. High-throughput sequencing has facilitated major advances in our understanding of microbial ecology and is now widespread in biotechnological applications from personalized medicine 1 to bioenergy 2 . Markers such as the 16S rRNA gene (16S) of bacteria and archaea are frequently used to characterize the taxonomic composition and phylogenetic diversity of environmental samples. Because marker gene studies focus on one or a few universal genes, they cannot directly identify metabolic or other functional capabilities of the microorganisms under study. Conversely, metagenomic sequencing aims to sample all genes from a community and can produce detailed metabolic and functional profiles. Although relatively little sequencing is needed to characterize the diversity of a sample , deep, and therefore costly, metagenomic sequencing is required to access rare organisms and genes 5 . Thus, marker gene profiling of large sample collections is now routine, but deep metagenomic sequencing across many samples is prohibitively expensive. Although marker gene and shotgun sequencing strategies differ in the type of information produced, phylogeny and biomolecular function are strongly, if imperfectly, correlated. Phylogenetic trees based on 16S closely resemble clusters obtained on the basis of shared gene content , and researchers often infer properties of uncultured organisms from cultured relatives. For example, the genome of a Bacteroides spp. might reasonably be inferred to contain many genes encoding glycoside hydrolase activity, based on the commonality of these activities in sequenced Bacteroides isolates 10 . This association is in turn closely related to the pan-and core-genomes of each phylogenetic subtree 11 , in that larger and more strongly conserved core genomes result in more confident linkages of genes with clades. Conversely, a clade's core genome consists of genes its members can be expected with high probability to carry in their genomes. The correlation between phylogeny and functional attributes depends on factors including the complexity of the trait 12 , but the overall degree of correlation suggests that it may be fruitful to predict the functions encoded in an organism's genome on the basis of functions encoded in closely related genomes. Recently, some 16S studies have extended these intuitions to infer the functional contribution of particular community members by mapping a subset of abundant 16S sequences to their nearest sequenced reference genome . The accuracy of such approaches has not been evaluated, but the correlation between gene content and phylogeny (excepting special cases such as laterally transferred elements and intracellular endosymbionts with reduced genomes) suggests that it may be possible to approximately predict the functional potential of microbial communities from phylogeny. Widespread and reproducible application of such a strategy requires an automated method that formalizes the relationship between evolutionary distance and functional potential across the entire metagenome, accounts
Residential segregation emerges from the interaction of many individuals and displays makedly dif... more Residential segregation emerges from the interaction of many individuals and displays makedly different global patterns depending on specific socioeconomic contexts. This paper presents a generative model of socioeconomic segregation that reproduces regular macro-patterns of the phenomenon through the specification of a minimal amount of parameters driving the agent's behaviour. The purpose of these experiments is to provide insights about the emergence of certain types of segregation patterns that have been identified in many modern cities and measure the relation between these distinct outputs and the degree of segregation they produce.
The Traveler's Dilemma game and the Minimum Effort Coordination game are two social dilemmas that... more The Traveler's Dilemma game and the Minimum Effort Coordination game are two social dilemmas that have attracted considerable attention due to the fact that the predictions of classical game theory are at odds with the results found when the games are studied experimentally. Moreover, a direct application of deterministic evolutionary game theory, as embodied in the replicator dynamics, to these games does not explain the observed behavior. In this work, we formulate natural variants of these two games as smoothed continuous-strategy games. We study the evolutionary dynamics of these continuous-strategy games, both analytically and through agent-based simulations, and show that the behavior predicted theoretically is in accord with that observed experimentally. Thus, these variants of the Traveler's Dilemma and the Minimum Effort Coordination games provide a simple resolution of the paradoxical behavior associated with the original games.
Profiling phylogenetic marker genes, such as the 16S rRNA gene, is a key tool for studies of micr... more Profiling phylogenetic marker genes, such as the 16S rRNA gene, is a key tool for studies of microbial communities but does not provide direct evidence of a community's functional capabilities. Here we describe PICRUSt (phylogenetic investigation of communities by reconstruction of unobserved states), a computational approach to predict the functional composition of a metagenome using marker gene data and a database of reference genomes. PICRUSt uses an extended ancestral-state reconstruction algorithm to predict which gene families are present and then combines gene families to estimate the composite metagenome. Using 16S information, PICRUSt recaptures key findings from the Human Microbiome Project and accurately predicts the abundance of gene families in host-associated and environmental communities, with quantifiable uncertainty. Our results demonstrate that phylogeny and function are sufficiently linked that this 'predictive metagenomic' approach should provide useful insights into the thousands of uncultivated microbial communities for which only marker gene surveys are currently available. High-throughput sequencing has facilitated major advances in our understanding of microbial ecology and is now widespread in biotechnological applications from personalized medicine 1 to bioenergy 2 . Markers such as the 16S rRNA gene (16S) of bacteria and archaea are frequently used to characterize the taxonomic composition and phylogenetic diversity of environmental samples. Because marker gene studies focus on one or a few universal genes, they cannot directly identify metabolic or other functional capabilities of the microorganisms under study. Conversely, metagenomic sequencing aims to sample all genes from a community and can produce detailed metabolic and functional profiles. Although relatively little sequencing is needed to characterize the diversity of a sample , deep, and therefore costly, metagenomic sequencing is required to access rare organisms and genes 5 . Thus, marker gene profiling of large sample collections is now routine, but deep metagenomic sequencing across many samples is prohibitively expensive. Although marker gene and shotgun sequencing strategies differ in the type of information produced, phylogeny and biomolecular function are strongly, if imperfectly, correlated. Phylogenetic trees based on 16S closely resemble clusters obtained on the basis of shared gene content , and researchers often infer properties of uncultured organisms from cultured relatives. For example, the genome of a Bacteroides spp. might reasonably be inferred to contain many genes encoding glycoside hydrolase activity, based on the commonality of these activities in sequenced Bacteroides isolates 10 . This association is in turn closely related to the pan-and core-genomes of each phylogenetic subtree 11 , in that larger and more strongly conserved core genomes result in more confident linkages of genes with clades. Conversely, a clade's core genome consists of genes its members can be expected with high probability to carry in their genomes. The correlation between phylogeny and functional attributes depends on factors including the complexity of the trait 12 , but the overall degree of correlation suggests that it may be fruitful to predict the functions encoded in an organism's genome on the basis of functions encoded in closely related genomes. Recently, some 16S studies have extended these intuitions to infer the functional contribution of particular community members by mapping a subset of abundant 16S sequences to their nearest sequenced reference genome . The accuracy of such approaches has not been evaluated, but the correlation between gene content and phylogeny (excepting special cases such as laterally transferred elements and intracellular endosymbionts with reduced genomes) suggests that it may be possible to approximately predict the functional potential of microbial communities from phylogeny. Widespread and reproducible application of such a strategy requires an automated method that formalizes the relationship between evolutionary distance and functional potential across the entire metagenome, accounts
Residential segregation emerges from the interaction of many individuals and displays makedly dif... more Residential segregation emerges from the interaction of many individuals and displays makedly different global patterns depending on specific socioeconomic contexts. This paper presents a generative model of socioeconomic segregation that reproduces regular macro-patterns of the phenomenon through the specification of a minimal amount of parameters driving the agent's behaviour. The purpose of these experiments is to provide insights about the emergence of certain types of segregation patterns that have been identified in many modern cities and measure the relation between these distinct outputs and the degree of segregation they produce.
The Traveler's Dilemma game and the Minimum Effort Coordination game are two social dilemmas that... more The Traveler's Dilemma game and the Minimum Effort Coordination game are two social dilemmas that have attracted considerable attention due to the fact that the predictions of classical game theory are at odds with the results found when the games are studied experimentally. Moreover, a direct application of deterministic evolutionary game theory, as embodied in the replicator dynamics, to these games does not explain the observed behavior. In this work, we formulate natural variants of these two games as smoothed continuous-strategy games. We study the evolutionary dynamics of these continuous-strategy games, both analytically and through agent-based simulations, and show that the behavior predicted theoretically is in accord with that observed experimentally. Thus, these variants of the Traveler's Dilemma and the Minimum Effort Coordination games provide a simple resolution of the paradoxical behavior associated with the original games.
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Papers by Joshua Reyes