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      Age-related alterations in metabolome and microbiome provide insights in dietary transition in giant pandas

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          ABSTRACT

          We conducted UPLC-MS-based metabolomics, 16S rRNA, and metagenome sequencing on the fecal samples of 44 captive giant pandas ( Ailuropoda melanoleuca) from four age groups (i.e., Cub, Young, Adult, and Old) to comprehensively understand age-related changes in the metabolism and gut microbiota of giant pandas. We characterized the metabolite profiles of giant pandas based on 1,376 identified metabolites, with 152 significantly differential metabolites (SDMs) found across the age groups. We found that the metabolites and the composition/function of the gut microbiota changed in response to the transition from a milk-dominant diet in panda cubs to a bamboo-specific diet in young and adult pandas. Lipid metabolites such as choline and hippuric acid were enriched in the Cub group, and many plant secondary metabolites were significantly higher in the Young and Adult groups, while oxidative stress and inflammatory related metabolites were only found in the Old group. However, there was a decrease in the α-diversity of gut microbiota in adult and old pandas, who exclusively consume bamboo. The abundance of bacteria related to the digestion of cellulose-rich food, such as Firmicutes, Streptococcus, and Clostridium, significantly increased from the Cub to the Adult group, while the abundance of beneficial bacteria such as Faecalibacterium, Sarcina, and Blautia significantly decreased. Notably, several potential pathogenic bacteria had relatively high abundances, especially in the Young group. Metagenomic analysis identified 277 CAZyme genes including cellulose degrading genes, and seven of the CAZymes had abundances that significantly differed between age groups. We also identified 237 antibiotic resistance genes (ARGs) whose number and diversity increased with age. We also found a significant positive correlation between the abundance of bile acids and gut bacteria, especially Lactobacillus and Bifidobacterium. Our results from metabolome, 16S rRNA, and metagenome data highlight the important role of the gut microbiota-bile acid axis in the regulation of age-related metabolism and provide new insights into the lipid metabolism of giant pandas.

          IMPORTANCE

          The giant panda is a member of the order Carnivora but is entirely herbivorous. The giant panda’s specialized diet and related metabolic mechanisms have not been fully understood. It is therefore crucial to investigate the dynamic changes in metabolites as giant pandas grow and physiologically adapt to their herbivorous diet. This study conducted UPLC-MS-based metabolomics 16S rRNA, and metagenome sequencing on the fecal samples of captive giant pandas from four age groups. We found that metabolites and the composition/function of gut microbiota changed in response to the transition from a milk-dominant diet in cubs to a bamboo-specific diet in young and adult pandas. The metabolome, 16S rRNA, and metagenome results highlight that the gut microbiota-bile acid axis has an important role in the regulation of age-related metabolism, and our study provides new insights into the lipid metabolism of giant pandas.

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          Most cited references96

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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              DADA2: High resolution sample inference from Illumina amplicon data

              We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
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                Author and article information

                Contributors
                Role: Formal analysisRole: Writing – original draft
                Role: InvestigationRole: Methodology
                Role: Formal analysis
                Role: Project administration
                Role: Investigation
                Role: Writing – review and editing
                Role: Funding acquisitionRole: InvestigationRole: Supervision
                Role: Editor
                Journal
                mSystems
                mSystems
                mSystems
                mSystems
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2379-5077
                05 June 2023
                May-Jun 2023
                05 June 2023
                : 8
                : 3
                : e00252-23
                Affiliations
                [1 ] Key Laboratory of Bio-resources and Eco-environment (Ministry of Education), College of Life Sciences, Sichuan University; , Chengdu, Sichuan, China
                [2 ] China Conservation and Research Center for the Giant Panda; , Dujiangyan, Sichuan, China
                [3 ] Key Laboratory of State Forestry and Grassland Administration on Conservation Biology for Rare Animals of the Giant Panda State Park; , Dujiangyan, Sichuan, China
                [4 ] China Wildlife Conservation Association; , Beijing, China
                Institute for Systems Biology; , Seattle, Washington, USA
                Author notes
                Address correspondence to Jing Li, ljtjf@ 123456126.com

                Accession numbers: The raw sequencing reads from this study have been submitted to the CNGBdb with the project accession CNP0003316.

                Fangyuan Liu, Rengui Li, and Yi Zhong contributed equally to this article. Author order was determined by drawing straws.

                The authors declare no conflict of interest.

                Article
                00252-23 msystems.00252-23
                10.1128/msystems.00252-23
                10308887
                37273228
                a2762e58-4e07-499c-bfc9-e0dd2f09a3ee
                Copyright © 2023 Liu et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 24 March 2023
                : 04 April 2023
                Page count
                supplementary-material: 10, authors: 8, Figures: 4, Tables: 1, References: 100, Pages: 21, Words: 13799
                Funding
                Funded by: National Forestry and Grassland Administration (NFGA);
                Award ID: KLSFGAGP2020.006
                Award Recipient :
                Categories
                Research Article
                microbial-genetics, Microbial Genetics
                Custom metadata
                May/June 2023

                giant pandas,metabolomics,16s rrna,metagenomics,age,bile acid-gut microbiota axis

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