title: Whole-genome analysis of mycobacteria from birds at the San Diego Zoo.
abstract: METHODS
  Mycobacteria isolated from more than 100 birds diagnosed with avian mycobacteriosis at the San Diego Zoo and its Safari Park were cultured postmortem and had their whole genomes sequenced. Computational workflows were developed and applied to identify the mycobacterial species in each DNA sample, to find single-nucleotide polymorphisms (SNPs) between samples of the same species, to further differentiate SNPs between as many as three different genotypes within a single sample, and to identify which samples are closely clustered genomically.
  
  
  RESULTS
  Nine species of mycobacteria were found in 123 samples from 105 birds. The most common species were Mycobacterium avium and Mycobacterium genavense, which were in 49 and 48 birds, respectively. Most birds contained only a single mycobacterial species, but two birds contained a mixture of two species. The M. avium samples represent diverse strains of M. avium avium and M. avium hominissuis, with many pairs of samples differing by hundreds or thousands of SNPs across their common genome. By contrast, the M. genavense samples are much closer genomically; samples from 46 of 48 birds differ from each other by less than 110 SNPs. Some birds contained two, three, or even four genotypes of the same bacterial species. Such infections were found in 4 of 49 birds (8%) with M. avium and in 11 of 48 birds (23%) with M. genavense. Most were mixed infections, in which the bird was infected by multiple mycobacterial strains, but three infections with two genotypes differing by ≤ 10 SNPs were likely the result of within-host evolution. The samples from 31 birds with M. avium can be grouped into nine clusters within which any sample is ≤ 12 SNPs from at least one other sample in the cluster. Similarly, the samples from 40 birds with M. genavense can be grouped into ten such clusters. Information about these genomic clusters is being used in an ongoing, companion study of mycobacterial transmission to help inform management of bird collections.
authors.affiliation: San Diego Supercomputer Center, University of California, San Diego, La Jolla, California, United States of America.
authors.forename: Wayne
authors.initials: W
authors.lastname: Pfeiffer
authors.affiliation: Wildlife Disease Laboratories, San Diego Zoo Global, San Diego, California, United States of America.
authors.forename: Josephine
authors.initials: J
authors.lastname: Braun
authors.affiliation: Wildlife Disease Laboratories, San Diego Zoo Global, San Diego, California, United States of America.
authors.forename: Jennifer
authors.initials: J
authors.lastname: Burchell
authors.affiliation: Wildlife Disease Laboratories, San Diego Zoo Global, San Diego, California, United States of America.
authors.forename: Carmel L
authors.initials: CL
authors.lastname: Witte
authors.affiliation: Wildlife Disease Laboratories, San Diego Zoo Global, San Diego, California, United States of America.
authors.forename: Bruce A
authors.initials: BA
authors.lastname: Rideout
mesh_terms: D000818:Animals; D001715:Bird Diseases / Q000382:microbiology*; D002140:California; D019295:Computational Biology / Q000379:methods; D030561:Databases, Nucleic Acid; D016680:Genome, Bacterial; D023281:Genomics / Q000379:methods; D005838:Genotype; D059014:High-Throughput Nucleotide Sequencing; D009161:Mycobacterium / Q000145:classification* / Q000235:genetics*; D009164:Mycobacterium Infections / Q000662:veterinary*; D009162:Mycobacterium avium / Q000235:genetics; D010802:Phylogeny; D020641:Polymorphism, Single Nucleotide