title: High-Specificity Targeted Functional Profiling in Microbial Communities with ShortBRED.
abstract: Profiling microbial community function from metagenomic sequencing data remains a computationally challenging problem. Mapping millions of DNA reads from such samples to reference protein databases requires long run-times, and short read lengths can result in spurious hits to unrelated proteins (loss of specificity). We developed ShortBRED (Short, Better Representative Extract Dataset) to address these challenges, facilitating fast, accurate functional profiling of metagenomic samples. ShortBRED consists of two components: (i) a method that reduces reference proteins of interest to short, highly representative amino acid sequences ("markers") and (ii) a search step that maps reads to these markers to quantify the relative abundance of their associated proteins. After evaluating ShortBRED on synthetic data, we applied it to profile antibiotic resistance protein families in the gut microbiomes of individuals from the United States, China, Malawi, and Venezuela. Our results support antibiotic resistance as a core function in the human gut microbiome, with tetracycline-resistant ribosomal protection proteins and Class A beta-lactamases being the most widely distributed resistance mechanisms worldwide. ShortBRED markers are applicable to other homology-based search tasks, which we demonstrate here by identifying phylogenetic signatures of antibiotic resistance across more than 3,000 microbial isolate genomes. ShortBRED can be applied to profile a wide variety of protein families of interest; the software, source code, and documentation are available for download at http://huttenhower.sph.harvard.edu/shortbred.
authors.affiliation: Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.
authors.forename: James
authors.initials: J
authors.lastname: Kaminski
authors.affiliation: Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, Missouri, United States of America.
authors.forename: Molly K
authors.initials: MK
authors.lastname: Gibson
authors.affiliation: Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.|Broad Institute, Cambridge, Massachusetts, United States of America.
authors.forename: Eric A
authors.initials: EA
authors.lastname: Franzosa
authors.affiliation: Centre for Integrative Biology (CIBIO), University of Trento, Trento, Trentino, Italy.
authors.forename: Nicola
authors.initials: N
authors.lastname: Segata
authors.affiliation: Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, Missouri, United States of America.|Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, Missouri, United States of America.|Department of Biomedical Engineering, Washington University, St. Louis, Missouri, United States of America.
authors.forename: Gautam
authors.initials: G
authors.lastname: Dantas
authors.affiliation: Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.|Broad Institute, Cambridge, Massachusetts, United States of America.
authors.forename: Curtis
authors.initials: C
authors.lastname: Huttenhower
mesh_terms: D000465:Algorithms; D001426:Bacterial Proteins / Q000145:classification* / Q000235:genetics*; D005819:Genetic Markers / Q000235:genetics; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D064307:Microbiota / Q000235:genetics*; D016366:Open Reading Frames / Q000235:genetics; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016415:Sequence Alignment / Q000379:methods*; D012984:Software
chemical_list: D001426:Bacterial Proteins; D005819:Genetic Markers