Evidence supporting the microbiota-gut-brain axis in a songbird
Data files
Oct 20, 2020 version files 1.18 GB
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aligned-rep-seqs.qza
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alpha-rarefaction.qzv
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bray_curtis_distance_matrix.qza
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bray_curtis_emperor.qzv
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bray_curtis_pcoa_results.qza
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cognition_assay_metadata.csv
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Cognitive_performance_data.xlsx
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deblur_rep_seqs_final.qza
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deblur_rep_seqs_final.qzv
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deblur_rep_seqs_ncp_nmc.qza
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deblur_rep_seqs_ncp_nmc.qzv
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deblur_rep_seqs_nmc.qza
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deblur_rep_seqs_nmc.qzv
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deblur_rep_seqs_summary.qzv
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deblur_rep_seqs.qza
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deblur_stats.qzv
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deblur_table_final.qza
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deblur_table_final.qzv
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deblur_table_ncp_nmc.qza
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deblur_table_ncp_nmc.qzv
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deblur_table_nmc.qza
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deblur_table_nmc.qzv
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deblur_table_summary.qzv
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deblur_table.qza
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debur_stats.qza
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evenness_vector.qza
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faith_pd_vector.qza
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feature-table.biom
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feature-table.tsv
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jaccard_distance_matrix.qza
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jaccard_emperor.qzv
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jaccard_pcoa_results.qza
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masked-aligned-rep-seqs.qza
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observed_otus_vector.qza
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rarefied_table.qza
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ReadMe.txt
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reads_trimmed_joined_filter_stats.qza
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reads_trimmed_joined_filtered.qza
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reads_trimmed_joined_filtered.qzv
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reads_trimmed_joined.qza
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reads_trimmed_joined.qzv
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reads_trimmed.qza
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reads_trimmed.qzv
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rooted-tree.qza
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RSBL2020-0430-R3_Rscript.R
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shannon_vector.qza
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table-with-taxonomy.biom
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taxa-bar-plots.qzv
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taxonomy.qza
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taxonomy.qzv
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taxonomy.tsv
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taxonomy2.tsv
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tree.nwk
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unrooted-tree.qza
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unweighted_unifrac_distance_matrix.qza
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unweighted_unifrac_emperor.qzv
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unweighted_unifrac_pcoa_results.qza
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weighted_unifrac_distance_matrix.qza
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weighted_unifrac_emperor.qzv
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weighted_unifrac_pcoa_results.qza
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zebra_finch_sequences.zip
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ZEFI_mapping_file.txt
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Abstract
Recent research in mammals supports a link between cognitive ability and the gut microbiome, but little is known about this relationship in other taxa. In a captive population of 38 Zebra Finches (Taeniopygia guttata), we quantified performance on cognitive tasks measuring learning and memory. We sampled the gut microbiome via cloacal swab and quantified bacterial alpha and beta diversity. Performance on cognitive tasks related to beta diversity but not alpha diversity. We then identified differentially abundant genera influential in the beta diversity differences among cognitive performance categories. Though correlational, this study provides some of the first evidence of an avian microbiota-gut-brain axis, building foundations for future microbiome research in wild populations and during host development.
Adult Zebra Finch gut microbiome data was assessed via cloacal swab. We extracted DNA using PowerSoil DNA Isolation Kits (Qiagen, Germany) following slight modification to manufacturer instructions, amplified the V4 region of the 16S rRNA gene using modified primers 515F/806R with Illumina adaptors following the Earth Microbiome Protocol for PCR, and submitted final pooled PCR products to Cornell’s Biotechnology Resource Center for quantification, normalization, library preparation, and sequencing. In total, we sequenced 72 cloacal swab samples, and14 negative controls in one Illumina MiSeq paired-end 2 x 250 bp run.
Using Quantitative Insights into Microbial Ecology 2 (QIIME2), raw sequences were trimmed of their primers, joined, per-nucleotide-quality-filtered, and denoised. Amplicon Sequence Variants (ASVs) were annotated using Scikit-learn system and the SILVA 132 database; mitochondria, chloroplasts, and unassigned sequences were filtered out. ASVs were aligned using MAFFT and masked to make a midpoint-rooted phylogenetic tree using FASTTREE. We decontaminated samples with package decontam in R (52) using negative controls and DNA yield. ASVs with <10 sequences across all samples were removed. Filtered sequences were CSS-normalized using package metagenomeSeq in R. Mean sequencing depth was 18758.5±1234.9 reads before decontamination, filtering, and normalization, and 380440.2±47429.3 reads afterwards. Raw sequences were submitted to NCBI’s Sequence Read Archive (BioProject PRJNA636961). Snakemake files (pre-configured coding loops) used for sequence analysis, and R scripts for statistical analysis, are available on github: (https://github.com/djbradshaw2/General_16S_Amplicon_Sequencing_Analysis).
For comparison to microbiome characteristics, we quantified cognitive performance on three tasks that measure learning and memory: a novel foraging task, a color association task, and a color reversal task, with birds first presented with a neophobia test (latency to approach the foraging grid used in cognitive tasks. Briefly, The novel foraging task employs operant conditioning and stepwise shaping to teach a novel foraging technique: birds learned to pry opaque blue and white lids from wells to obtain a seed reward (same seed as regular diet). The performance measure was the number of trials required to learn to remove lids to obtain the reward. Once birds mastered prying lids from wells, they were again presented with blue and white lids, but only one color was rewarded. This color association task tests associative learning: the ability to form a mental connection between multiple stimuli. The performance measure was the number of trials required to learn to remove the rewarded lids first before any unrewarded lids. Finally, the color reversal task (the rewarded color is switched) is also an associative learning task, but also tests for behavioral flexibility. Performance was measured as the number of trials to stop removing the formerly rewarded lid color and instead remove the newly rewarded color. For all tasks, cognitive performance is an inverted variable: a low number of trials required to pass signifies high performance. Subjects were tested after 4 hours of food restriction, ensuring motivation to obtain food rewards. Each bird was tested individually (visually but not acoustically isolated from other test subjects) for 4 hours each day, consisting of eight two-min trials separated by 20 min. We viewed and scored trials remotely via video. Continued motivation to eat was confirmed at the end of each test day by returning the normal full seed dish and observing the bird’s latency to eat.
Refer to "ReadMe.txt" for file descriptions.