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34 results for “dietary adaptation”

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zenodo44/100

Metagenomics uncovers dietary adaptations for chitin digestion in the gut microbiota of convergent myrmecophagous mammals

<p><strong>Metagenomics uncovers dietary adaptations for chitin digestion in the gut microbiota of convergent myrmecophagous mammals</strong></p> <p>Sophie Teullet<sup>a,#</sup>, Marie-Ka Tilak<sup>a</sup>, Amandine Magdeleine<sup>a</sup>, Roxane Schaub<sup>b,c</sup>, Nora M. Weyer<sup>d</sup>, Wendy Panaino<sup>d,e</sup>, Andrea Fuller<sup>d</sup>, William. J. Loughry<sup>f</sup>, Nico L. Avenant<sup>g</sup>, Benoit de Thoisy<sup>h,i</sup>, Guillaume Borrel<sup>j</sup> and Fr&eacute;d&eacute;ric Delsuc<sup>a,#</sup></p> <p><sup>a</sup>Institut des Sciences de l&rsquo;Evolution de Montpellier (ISEM), Univ Montpellier, CNRS, IRD, Montpellier, France</p> <p><sup>b</sup>CIC AG/Inserm 1424, Centre Hospitalier de Cayenne Andr&eacute;e Rosemon, Cayenne, French Guiana</p> <p><sup>c</sup>Tropical Biome and immunopathology, Universit&eacute; de Guyane, Labex CEBA, DFR Sant&eacute;, Cayenne, French Guiana</p> <p><sup>d</sup>Brain Function Research Group, School of Physiology, University of the Witwatersrand, Johannesburg, South Africa</p> <p><sup>e</sup>Centre for African Ecology, School of Animals, Plant, and Environmental Sciences, University of the Witwatersrand, Johannesburg, South Africa</p> <p><sup>f</sup>Department of Biology, Valdosta State University, Valdosta, GA, USA</p> <p><sup>g</sup>National Museum and Centre for Environmental Management, University of the Free State, Bloemfontein, South Africa</p> <p><sup>h</sup>Institut Pasteur de la Guyane, Cayenne, French Guiana, France</p> <p><sup>i</sup>Kwata NGO, Cayenne, French Guiana, France</p> <p><sup>j</sup>Institut Pasteur, Universit&eacute; Paris Cit&eacute;, UMR CNRS 6047, Evolutionary Biology of the Microbial Cell, Paris, France</p> <p><sup>#</sup>Corresponding authors: sophie.teullet@umontpellier.fr; frederic.delsuc@umontpellier.fr</p> <p>&nbsp;</p> <p><em><strong>Abstract</strong></em></p> <p>In mammals, myrmecophagy (ant and termite consumption) represents a striking example of dietary convergence. This trait evolved independently at least five times in placentals with myrmecophagous species comprising aardvarks, anteaters, some armadillos, pangolins, and aardwolves. The gut microbiome plays an important role in dietary adaptation, and previous analyses of 16S rRNA metabarcoding data have revealed convergence in the composition of the gut microbiota among some myrmecophagous species. However, the functions performed by these gut bacterial symbionts and their potential role in the digestion of prey chitinous exoskeletons remain open questions. Using long- and short-read sequencing of fecal samples, we generated 29 gut metagenomes from nine myrmecophagous and closely related insectivorous species sampled in French Guiana, South Africa, and the USA. From these, we reconstructed 314 high-quality bacterial genome bins of which 132 carried chitinase genes, highlighting their potential role in insect prey digestion. These chitinolytic bacteria belonged mainly to the family Lachnospiraceae, and some were likely convergently recruited in the different myrmecophagous species as they were detected in several host orders (i.e., <em>Enterococcus faecalis</em>, <em>Blautia</em> sp), suggesting that they could be directly involved in the adaptation to myrmecophagy. Others were found to be more host-specific, possibly reflecting phylogenetic constraints and environmental influences. Overall, our results highlight the potential role of the gut microbiome in chitin digestion in myrmecophagous mammals and provide the basis for future comparative studies performed at the mammalian scale to further unravel the mechanisms underlying the convergent adaptation to myrmecophagy.</p> <p>&nbsp;</p> <p><em><strong>Main figures and corresponding datasets</strong></em></p> <p><strong>Figure_1_dataset.zip</strong>&nbsp;contains:</p> <ul> <li><strong>FIGURE 1.</strong> Phylogenetic position of the 314 high-quality selected bins reconstructed from 29 gut metagenomes of the nine focal myrmecophagous species within a reference prokaryotic phylogeny. A: Phylogeny of the 314 selected bins (red branches) with 2496 prokaryote reference genomes. Circles respectively indicate (from inner to outer circles): the bacterial phyla and kingdom to which these genome bins were assigned based on the Genome Taxonomy Database release 7 (Parks <em>et al</em>, 2021). Clades, where a subtree was defined, are highlighted in blue for the Firmicutes (Fig. 1B), green for the Bacteroidetes, and pink for the Proteobacteria (Figs. S2 A and B, respectively). B: Subtree within Fimircutes showing myrmecophagous-specific clades (blue highlights; dark blue corresponds to the three clades mentioned in the results, light blue to the other clades). The outer circle indicates the bacterial family to which these genome bins were assigned based on the Genome Taxonomy Database. Bins&rsquo; names of the myrmecophagous-specific clades are indicated at leaves of the phylogenetic tree together with the genus to which they were assigned to.</li> <li><strong>phylophlan_LR_SR_ToL_FINAL_concatenated.aln</strong>: Alignment of the concatenated markers assembled by PhyloPhlAn v3.0.58.</li> <li><strong>phylophlan_LR_SR_ToL_FINAL.tre</strong>: Phylogenetic tree reconstructed by PhyloPhlAn v3.0.58&nbsp;for the 314 high quality selected genome bins and the 2496 prokaryote reference genomes.</li> </ul> <p><strong>Figure_2_dataset.zip&nbsp;</strong>contains:</p> <ul> <li><strong>FIGURE 2</strong>. Phylogeny of the 394 GH18 sequences identified in 132 high-quality selected bins reconstructed from 29 gut metagenomes of the nine focal myrmecophagous species and relatives. Red branches indicate the 237 sequences having an active chitinolytic site (DXXDXDXE). Circles respectively indicate (from inner to outer circles): the bacterial family and phyla of the bin the sequence was retrieved from. Colored sequence names indicate the host species. Colored circles at certain nodes indicate enzymes to which sequences are similar when blasting them against the NCBI non-redundant protein database. Sequence names are indicated at leaves of the tree and begin with the genus to which the bin they were identified in was assigned to.&nbsp;</li> <li><strong>GH18_sequences_from_selected_bins_alignment.fasta</strong>: Alignment of the 394 GH18 sequences identified in 132 high quality selected bins computed with MAFFT v7.450.</li> <li><strong>GH18__sequences_from_selected_bins_tree.newick</strong>: Phylogenetic tree of the 394 GH18 sequences inferred&nbsp;with RAxML v8.2.11 within Geneious Prime 2022.0.2.</li> </ul> <p><strong>Figure_3_dataset.zip</strong>&nbsp;contains:</p> <ul> <li><strong>FIGURE&nbsp;3</strong>. Detection of the 314 high-quality bacterial genomes (lines) in the 29 gut metagenomes (columns) of the nine focal species. Each square indicates the detection of a genome bin in a sample as estimated by anvi&rsquo;o v7 (Eren <em>et al</em>, 2021). Names of bins are indicated on the left with red indicating chitinolytic bins (Table S2). The names begin with the genus to which the bin was assigned to. Asterisks (*) indicate bins detected in at least one soil sample (detection &gt; 0.25) (Fig. S4, Table S2, and detection table available via Zenodo). Phylogenetic relationships of host species distinguished by different color strips are represented at the bottom of the graph. Columns on the right indicate (from left to right): the number of GH18 sequences identified in each bin (from 0 to 17), the bin&rsquo;s taxonomic phylum, class, order, and family. The phylogeny of the 314 selected bins inferred with PhyloPhlAn v3.0.58 (Asnicar <em>et al</em>, 2020) is also represented on the right of the graph (see Fig. S1). Silhouettes were downloaded from phylopic.org.</li> <li><strong>detection_bins_across_gut_metagenomes.txt</strong>: Detection table as tab-delimited file containing the detection values inferred by anvi&#39;o v7&nbsp;for the 314 high quality selected bins across the 29 gut metagenomes from the nine focal myrmecophagous species.&nbsp;</li> </ul> <p><strong>Figure_4_dataset.zip</strong>&nbsp;contains:</p> <ul> <li><strong>FIGURE 4</strong>. Distribution of chitinolytic selected bins (red links) among the nine focal myrmecophagous species and relatives. Phylogenies of the 314 high-quality selected bins (Fig. S1) and of the nine host species (downloaded from timetree.org) are represented respectively on the left and the right of the graph. Links illustrate, for each bin, in which host species the bin was detected (detection threshold &gt; 0.25). Red links indicate bins in which at least one GH18 sequence with an active chitinolytic site (DXXDXDXE) was found (chitinolytic bins). The size of the circles at the tips of the host phylogeny is proportional to the number of samples (n = 1 for <em>D. kap</em>; n = 2 for <em>D. nov</em>, <em>C. uni</em> and <em>M. tri</em>; n = 3 for <em>T. tet </em>and <em>O. af</em>e; n = 4 for <em>D. sp. nov </em>FG; n = 6 for <em>P. cri </em>and <em>S. tem</em>). Bins&rsquo; names are indicated at the tip of the bins&rsquo; phylogeny and main bacterial phyla are indicated by colored vertical bars. This graph was done with the cophylo R package within the phytools suite (Revell, 2012). Silhouettes were downloaded from phylopic.org.</li> <li><strong>presence_absence_MAGs_in_metagenomes.txt</strong>: Presence/absence matrix of the 314 selected genome bins across the 29 gut metagenomes.</li> <li><strong>host_species_phylo_reduced_fig4.newick</strong>: Host phylogenetic timetree.</li> </ul> <p><strong>Table_1_sample_infos.xls: </strong>Detailed sample information for the 33 fecal samples collected. <em>N.B</em>.: Diet was determined based on field observations (i.e., dissections) and the literature.</p> <p><strong>&nbsp;</strong></p> <p><em><strong>Supplementary results</strong></em></p> <p><strong>Supplementary_results_Teullet_etal_2023.zip&nbsp;</strong>includes a comparison of genome statistics of the selected bins reconstructed from the long-read&nbsp;vs the short-read datasets, a phylogeny of the set of selected bins before dereplication (n = 407) and a comparison of the distribution of shared and specific genome bins carrying GH18 among host orders.</p> <p>&nbsp;</p> <p><em><strong>Supplementary material</strong></em></p> <p><strong>Supplementary_material_Teullet_etal_2023.zip&nbsp;</strong>contains</p> <ul> <li>Supplementary figures (S1-S4)&nbsp;and tables (S1-S4).</li> <li><strong>phylophlan_314_bins_phylogeny_FINAL_concatenated.aln and phylophlan_314_bins_phylogeny_FINAL.tre</strong>: Alignment&nbsp;of the concatenated markers and the final tree (respectively) reconstructed by PhyloPhlAn v3.0.58&nbsp;for the 314 high-quality selected and dereplicated genome bins.</li> <li><strong>phylophlan_407_selected_bins_nodRep_concatenated.aln and phylophlan_407_selected_bins_phylogeny_FINAL.tre</strong>: Alignment&nbsp;of the concatenated markers and the final tree (respectively) reconstructed by PhyloPhlAn v3.0.58&nbsp;for the 407 high-quality selected genome bins before dereplication.</li> <li><strong>abundance_bins_across_gut_metagenomes.txt</strong>: A tab-delimited file corresponding to the&nbsp;absolute abundance values inferred by anvi&#39;o v7 for the 314 high-quality selected bins across the 29 gut metagenomes from the nine focal myrmecophagous species.&nbsp;</li> <li><strong>detection_bins_across_soil_samples.txt</strong>: A tab-delimited file corresponding to the detection values inferred by anvi&#39;o v7 for the 140 high-quality selected bins reconstructed from the aardvark, ground pangolin and southern aardwolf gut metagenomes across the eight&nbsp;soil samples collected on sample sites in&nbsp;South Africa.</li> </ul> <p>&nbsp;</p> <p><strong><em>Assemblies</em></strong></p> <p><strong>Long-read_metagenomic_assemblies_polished.zip</strong> contains the 31&nbsp;long-read metagenomes assembled with metaFlye strain v2.9 and polished with short reads using Pilon v1.4, which were&nbsp;used for binning.</p> <p><strong>Long-read_metagenomic_assemblies_not_polished.zip</strong> contains the 33&nbsp;long-read metagenomes assembled with metaFlye strain v2.9 before polishing.</p> <p><strong>Short-read_metagenomic_assemblies.zip</strong> contains the 31 short-read metagenomes assembled with metaSPAdes and MEGAHIT.</p> <p><em>N.B</em>:</p> <ol> <li>Two samples (DASY M1746 and DASY VLD168) were not sequenced using Illumina short reads.&nbsp;Only long reads were generated and assembled for these two samples and are made available here. As these assemblies could not be polished, these samples were not included in downstream analyses.</li> <li>Two samples (CAB M3141 and MYR M5293)&nbsp;were highly contaminated by host reads&nbsp;and not used in downstream analyses. As they were still assembled with the other samples, the corresponding metagenomes are made available here.</li> </ol> <p>&nbsp;</p> <p><strong><em>Binning: genome bins and dereplication results</em></strong></p> <p><strong>High-quality_selected_bins_dereplicated.zip</strong> contains the 314 high quality selected bins (&gt;90% completion, &lt;5% redundancy) reconstructed from long- and short-read metagenomes with metaBAT2 and dereplicated with dRep at 98% ANI.</p> <p><strong>metaBAT2_short-read_assemblies_bins.zip </strong>contains all bins reconstructed from the short-read assemblies with metaBAT2 (i.e., output of metaBAT2).</p> <p><strong>metaBAT2_long-read_assemblies_bins.zip</strong> contains all bins reconstructed from the long-read polished assemblies with metaBAT2 (i.e., output of metaBAT2).</p> <p><strong>Output_dRep_98ANI_407_bins_long-short-reads.zip</strong> contains the output of the dereplication analysis done on the set of 407 high-quality selected genome bins reconstructed from long- (n = 201) and short-read (n = 206; labeled &quot;spad&quot;) metagenomes. It was performed with dRep using&nbsp;default parameters. After this step, the final dataset included 314 high-quality non-redundant&nbsp;genome bins. This folder includes:</p> <ul> <li><strong>LR_SR_407_bins_dRep_98ANI_Primary_clustering_dendrogram.pdf</strong>: The primary clustering of selected genome bins&nbsp;using the Mash algorithm with an ANI threshold of 90%.</li> <li><strong>LR_SR_407_bins_dRep_98ANI_Secondary_clustering_dendrograms.pdf</strong>: The secondary clustering of selected genome bins&nbsp;using the fastANI algorithm with an ANI threshold of 98%.</li> <li><strong>LR_SR_407_bins_dRep_98ANI_Cluster_scoring.pdf</strong>: The clustering score attributed to each genome bin during&nbsp;dereplication. Asteriks (*) indicate&nbsp;genomes chosen to be the representative genomes of their cluster.</li> </ul> <ul> </ul>

opencc-by-4.0Jun 2023View details →
dryad40/100

Data from: The spotted parrotfish genome provides evolutionary insight into the ecological adaptation of a keystone dietary specialist

<p>With over 600 valid species, the wrasses (family Labridae) are among the largest and most successful of the marine teleosts. They feature prominently on coral reefs where they are known not only for their impressive diversity in colouration and form, but also in their functional specialization and ability to occupy a wide variety of trophic guilds. Among the wrasses, the parrotfishes (tribe Scarini) display some one of the most dramatic examples of trophic specialization. Using abrasion-resistant biomineralized teeth, parrotfishes are able to mechanically extract protein-rich micro-photoautotrophs growing in and amongst reef carbonate material, a dietary niche that is inaccessible to most other teleost fishes. This ability to exploit an otherwise untapped trophic resource is thought to have played a role in the diversification and evolutionary success of the parrotfishes. In order to better understand the key evolutionary innovations leading to the success of these dietary specialists, we sequenced and analysed the genome of a representative species, the spotted parrotfish (<em>Cetoscarus ocellatus</em>). We find significant expansion, selection, and duplication within several detoxification gene families and a novel poly-glutamine expansion in the enamel protein ameloblastin, and we consider their evolutionary implications. Our genome provides a useful resource for comparative genomic studies investigating the evolutionary history of this highly specialized teleostean radiation.</p>

opencc-zeroMar 2024View details →
dryad40/100

Data from: Metagenomic insights into the dietary diversity of the adaptive radiation of cichlid fishes in Lake Tanganyika

Open the record for dataset details and reuse information.

publicApr 2025View details →
dryad40/100

Data from: The spotted parrotfish genome provides evolutionary insight into the ecological adaptation of a keystone dietary specialist

Open the record for dataset details and reuse information.

publicMar 2024View details →
dryad36/100

A type 2 immune circuit in the stomach controls mammalian adaptation to dietary chitin

<p>Dietary fiber improves metabolic health, but host-encoded mechanisms for digesting fibrous polysaccharides are unclear. Here, we describe a mammalian adaptation to dietary chitin that is coordinated by gastric innate immune activation and acidic mammalian chitinase (AMCase). Chitin consumption causes gastric distension and cytokine production by stomach tuft cells and group 2 innate lymphoid cells (ILC2s), driving expansion of AMCase-expressing zymogenic chief cells that facilitate chitin digestion. Although chitin influences microbial composition, ILC2-mediated tissue adaptation and gastrointestinal responses are preserved in germ-free mice. In the absence of AMCase, sustained chitin intake leads to heightened basal type 2 immunity, reduced adiposity, and resistance to obesity. These data define an endogenous metabolic circuit that enables nutrient extraction from an insoluble dietary constituent by enhancing digestive function.</p>

opencc-zeroAug 2023View details →
dryad36/100

Dietary adaptations along the Northern limit of distribution: What does the smooth snake (Coronella austriaca) eat in Norway? Metabarcoding of stomach content and visual analysis of faeces

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publicMar 2025View details →
dryad36/100

A type 2 immune circuit in the stomach controls mammalian adaptation to dietary chitin

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publicAug 2023View details →
dryad36/100

Data from: Unpredictability and adaptive responses to dietary variability in Japanese quail

Open the record for dataset details and reuse information.

publicNov 2025View details →
dryad36/100

Data from: Dietary adaptations and paleoecology of Lophialetidae (Mammalia: Tapiroidea) from the Eocene of the Erlian Basin, China: Combined evidence from mesowear and stable isotope analyses

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publicDec 2019View details →
dryad36/100

Data from: TAS2R20 variants confer dietary adaptation to high-quercitrin bamboo leaves in Qinling giant pandas

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publicApr 2021View details →
zenodo32/100

FIGURE 2 in Ultrastructural observation of digestive tract and the adaptative characteristics of dietary habits for ground-dwelling and omnivorous insects

FIGURE 2. Scanning electron microscope observation of the L. taicoun. A–D. Crop (Cr). (The long and thin spines on the inner surface of the crop are pointed out with arrows.) E–M. Proventriculus (Pv). (ST: Sclerotized lobes; MT: Median tooth; SL: Sclerotized lobes) N–P. Gastric caecum (Gc). Q–S. Midgut. T–U. Ileum. V–Y. Malpighian tubules (MTs). (The micro-tracheae and internal microvilli are pointed out with arrows.) Z–BB. Colon. CC–DD. Rectum.

opennotspecifiedNov 2023View details →
zenodo32/100

FIGURE 4 in Ultrastructural observation of digestive tract and the adaptative characteristics of dietary habits for ground-dwelling and omnivorous insects

FIGURE 4. Scanning electron microscope observation of the V. micado. A–D. Crop (Cr). (The long and thin spines on the inner surface of the crop are pointed out with arrows.) E–L. Proventriculus (Pv). (ST: Sclerotized lobes; MT: Median tooth; SL: Sclerotized lobes) M–N. Gastric caecum (Gc). O–Q. Midgut. R–T. Ileum. U. Malpighian tubules (MTs). (The micro-tracheae are pointed out with arrows.) V–W. Colon. X–Y. Rectum.

opennotspecifiedNov 2023View details →
ClinicalTrials.gov32/100

Intestinal Sweet Taste Receptor Function and Adaptation to Dietary Sugars and Sweeteners

ClinicalTrials.gov study NCT02835859. IPD Sharing: NO. Countries: 1. Publications: 25.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov32/100

Plant-based Dietary Protein and Resistance-training Adaptations

ClinicalTrials.gov study NCT03907059. IPD Sharing: Not stated. Countries: 1. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →
dryad32/100

Specialist savvy vs generalist grit: elucidating the trade-offs in adaptive dietary ecomorphology amongst African Green and Bush Snakes

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publicMay 2025View details →
dryad32/100

Low costs of adaptation to dietary restriction

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publicMar 2020View details →
ClinicalTrials.gov28/100

Effects of a Pre-Workout Dietary Supplement on Training Adaptations

ClinicalTrials.gov study NCT02999581. IPD Sharing: NO. Countries: 0. Publications: 1.

closedIPD-NOFeb 2026View details →
ClinicalTrials.gov28/100

Adaptive Dietary Intervention (ADI) for Asian Americans With Type 2 Diabetes

ClinicalTrials.gov study NCT07278531. IPD Sharing: YES. Countries: 1. Publications: 0.

controlledIPD-YESFeb 2026View details →
ClinicalTrials.gov28/100

Culturally Adapted Dietary Clinical Trial in PR

ClinicalTrials.gov study NCT05962372. IPD Sharing: YES. Countries: 1. Publications: 0.

controlledIPD-YESFeb 2026View details →
geo24/100

Effects of dietary forage and calf starter on ruminal pH and transcriptomic adaptation of the rumen epithelium in Holstein calves during the weaning transition

GEO Series GSE83813. Bos taurus. 7 samples. Type: Expression profiling by array.

openGEO-OpenJun 2016View details →

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