DOI: 10.5061/dryad.hqbzkh1t3
title: The avian mycobiome: Phylogenetic trees and alignments for key fungal groups

description: Vertebrate lungs contain diverse microbial communities, but little is
 known regarding the drivers of community composition or consequences for
 health. Microbiome assembly by processes such as dispersal, coevolution,
 and host-switching can be probed with comparative surveys; however, few
 studies exist for lung microbiomes, particularly for the fungal component,
 the mycobiome. Distinguishing among fungal taxa that are generalist or
 specialist symbionts, potential pathogens, or incidentally inhaled spores
 is urgent because of potential for emerging diseases. Here, we provide the
 first characterization of the avian lung mycobiome, and we test the
 relative influences of environment, phylogeny, and functional traits. We
 used metabarcoding and culturing from 195 lung samples representing 32
 bird species across 20 families. We identified 526 fungal taxa as
 estimated by distinct sequence types (zOTUs) including many opportunistic
 pathogens. These were predominantly from the phylum Ascomycota (79%)
 followed by Basidiomycota (16%) and Mucoromycota (5%). Yeast and
 yeast-like taxa (Malassezia, Filobasidium, Saccharomyces, Meyerozyma, and
 Aureobasidium) and filamentous fungi (Cladosporium, Alternaria,
 Neurospora, Fusarium, and Aspergillus) were abundant. Lung mycobiomes were
 strongly shaped by environmental exposure, and further modulated by host
 identity, traits, and phylogenetic affinities. Our results implicate
 migratory bird species as potential vectors for long-distance dispersal of
 opportunistically pathogenic fungi.
description: The data represent ribosomal internal transcribed spacer (ITS)
 sequences obtained by a combination of typing fungal isolates and amplicon
 analysis with Illumina sequencing. Sequences were aligned with MAFFT and
 subjected to maximum likelihood tree-builidng analyses with IQ-Tree using
 the best subsititution model as determined by ModelFinder. Alignments and
 Newick files are presented in NEXUS formats.
description: # The avian mycobiome: Phylogenetic trees and alignments for key fungal
 groups
 [https://doi.org/10.5061/dryad.hqbzkh1t3](https://doi.org/10.5061/dryad.hqbzkh1t3) ## Description of the data and file structure ***Contacts for datasets*** 1. Donald Natvig, Department of Biology, University of New Mexico, Albuquerque 87131, [dnatvig@unm.edu](mailto:dnatvig@unm.edu) 2. Paris Salazar-Hamm, Department of Biology, University of New Mexico, Albuquerque 87131, [psh102@unm.edu](mailto:psh102@unm.edu) ***Related manuscript in press*** Paris S. Salazar-Hamm, Chauncey R. Gadek, Michael A. Mann, Madeline Steinberg, Kyana N. Montoya, Mahgol Behnia, Ethan F. Gyllenhaal, Serina S. Brady, Oona M. Takano, Jessie L. Williamson, Christopher C. Witt, and Donald O. Natvig. 2025. Phylogenetic and ecological drivers of the avian lung mycobiome and its potentially pathogenic component. *Communications Biology* (Nature). Corresponding authors: Paris Salazar-Hamm, [psh102@unm.edu](mailto:psh102@unm.edu); Chauncey Gadek, [cgadek@unm.edu](mailto:cgadek@unm.edu) ***Sources of DNA and cultures employed in this study*** Whole-DNA preparations and cultured isolates were obtained from the lung tissues of 1) Sandhill cranes sampled at a hunter checkpoint near Bernardo, New Mexico, and 2) salvaged birds obtained from diverse counties in New Mexico. ***Included data files*** Sequence alignments and phylogenetic analyses employed ribosomal ITS sequences derived from cultured isolates and amplicon analysis of lung tissues, along with sequences obtained from GenBank for related fungi. The GenBank accession numbers for all sequences are presented below and in the included file *Sequence_name_key_Supplementary_Table_4.xlsx.* * Aspergillus_alignment_nexus.txt (84.08 KB): 697-base** **nucleotide sequence alignment of ribosomal ITS sequences generated with MAFFT. * Aspergillus_tree.nexus (2.16 KB): Maximum likelihood tree in Nexus format derived from the Aspergillus alignment included here. The tree was generated with IQ-Tree using best fitting model TIM2e+G4**.** * Cryptococcus_alignment_nexus.txt (37.91 KB): 263-base** **nucleotide sequence alignment of ribosomal ITS sequences generated with MAFFT. * Cryptococcus_tree.nexus (2.61 KB): Maximum likelihood tree in Nexus format derived from the Cryptococcus alignment included here. The tree was generated with IQ-Tree using best fitting model TVMe+I+G4. * Onygenales_alignment.nexus.txt (41.62 KB): 540-base nucleotide sequence alignment of ribosomal ITS sequences generated with MAFFT. * Onygenales_tree.nexus (1.5 KB): Maximum likelihood tree in Nexus format derived from the Onygenales alignment included here. The tree was generated with IQ-Tree using best fitting model TNe+G4. * Saccharomycetales_alignment_nexus.txt (86.02 KB): 301-base** **nucleotide sequence alignment of ribosomal ITS sequences generated with MAFFT. * Saccharomycetales_tree_nexus (4.04 KB): Maximum likelihood tree in Nexus format derived from the Onygenales alignment included here. The tree was generated with IQ-Tree using best fitting model HKY+F+I+G4. * Sequence_name_key_Supplementary_Table_4.xlsx (16.28 KB): Full sequence names, taxonomy, and GenBank accession numbers for sequences and taxa employed in phylogenetic analyses. ***Phylogenetic analyses*** We explored the diversity of amplicon sequences and cultured isolates for select fungal groups that have consequences for human and animal health using a phylogenetics approach with ribosomal ITS sequences. Target groups included Aspergillacaeae, Onygenales, and Saccharomycetales fungi, as well as *Cryptococcus*-like yeasts (e.g., species of *Naganishia*, *Vishniacozyma*, *and Filobasidium*). Reference sequences from GenBank[ ](https://www.zotero.org/google-docs/?tRgBtV)as well as those from a previous study of the lung communities of small mammals in the southwestern U.S.[ ](https://www.zotero.org/google-docs/?ODMnbX)were included. We aligned sequences with mafft v.7.487 using default settings and trimmed the resulting alignment with trimal v.1.4.1 in *automated1* mode. The final alignments were 697 bp for Aspergillaceae, 263 bp for *Cryptococcus*-like yeasts, 540 bp for Onygenales, and 301 bp for Saccharomycetales. We inferred maximum likelihood trees with the best fitting model according to ModelFinder in IQ-Tree[ ](https://www.zotero.org/google-docs/?c5vagg)v.1.6.12 with 10,000 ultrafast bootstraps. The best fitting model was TIM2e+G4 for Aspergillaceae, TVMe+I+G4 for *Cryptococcus*-like yeasts, TNe+G4 for Onygenales, and HKY+F+I+G4 for Saccharomycetales. Phylogenies were rooted with standard outgroups: *Aspergillus fumigatus* for Onygenales, *Coccidioides immitis* for Aspergillaceae, *Mycosarcoma* *(Ustilago*) maydis for Cryptococcus-like yeasts, and *Neurospora crassa* for Saccharomycetales. The resulting trees were visualized in ggtree. Nexus-formatted alignments and Newick trees are deposited here and are available in the Supplementary Data of Salazar-Hamm et al. ***Sequence data at GenBank*** Ribosomal ITS region sequences (barcodes) obtained from Sanger Big-Dye sequencing of PCR products from cultured fungi were deposited at GenBank under accession numbers PP804255-PP804425. ITS2 amplicon sequences acquired with Illumina sequencing were deposited in the NCBI Short Read Archive (SRA) under BioProject PRJNA1136563. ## Access information Other publicly accessible locations of the data: * Supplemental Data in article referenced above. Data was derived from the following sources: * The alignments and trees were produced from ribosomal internal transcribed spacer (ITS) sequences derived from the lung tissues of Sandhill cranes and other birds obtained in New Mexico. The sequences are from fungal isolates (Sanger Big-Dye) and ITS2 amplicons sequenced with the Illumina sequencing platform. Sequences were aligned with MAFFT and subjected to maximum likelihood tree-builidng analyses with IQ-Tree using the best subsititution model as determined by ModelFinder. Alignments and Newick files are presented here in NEXUS formats.