Comparative Genomic Analysis Revealed Genetic Divergence Between Bifidobacterium Catenulatum Subspecies Present in Infant Versus Adult Guts

Overview

Journal BMC Microbiol

Publisher Biomed Central

Specialty Microbiology

Date 2022 Jun 16

PMID 35710325

Authors

Jiaqi Liu

Weicheng Li

Caiqing Yao

Jie Yu

Heping Zhang

Affiliations

Soon will be listed here.

Abstract

Background: The two subspecies of Bifidobacterium catenulatum, B. catenulatum subsp. kashiwanohense and B. catenulatum subsp. catenulatum, are usually from the infant and adult gut, respectively. However, the genomic analysis of their functional difference and genetic divergence has been rare. Here, 16 B. catenulatum strains, including 2 newly sequenced strains, were analysed through comparative genomics.

Results: A phylogenetic tree based on 785 core genes indicated that the two subspecies of B. catenulatum were significantly separated. The comparison of genomic characteristics revealed that the two subspecies had significantly different genomic sizes (p < 0.05) but similar GC contents. The functional comparison revealed the most significant difference in genes of carbohydrate utilisation. Carbohydrate-active enzymes (CAZyme) present two clustering patterns in B. catenulatum. The B. catenulatum subsp. kashiwanohense specially including the glycoside hydrolases 95 (GH95) and carbohydrate-binding modules 51 (CBM51) families involved in the metabolism of human milk oligosaccharides (HMO) common in infants, also, the corresponding fucosylated HMO gene clusters were detected. Meanwhile, B. catenulatum subsp. catenulatum rich in GH3 may metabolise more plant-derived glycan in the adult intestine.

Conclusions: These findings provide genomic evidence of carbohydrate utilisation bias, which may be a key cause of the genetic divergence of two B. catenulatum subspecies.

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References

Abdelhamid A, El-Dougdoug N . Comparative genomics of the gut commensal Bifidobacterium bifidum reveals adaptation to carbohydrate utilization. Biochem Biophys Res Commun. 2021; 547:155-161. DOI: 10.1016/j.bbrc.2021.02.046. View

Page A, Cummins C, Hunt M, Wong V, Reuter S, Holden M . Roary: rapid large-scale prokaryote pan genome analysis. Bioinformatics. 2015; 31(22):3691-3. PMC: 4817141. DOI: 10.1093/bioinformatics/btv421. View

Vilella A, Severin J, Ureta-Vidal A, Heng L, Durbin R, Birney E . EnsemblCompara GeneTrees: Complete, duplication-aware phylogenetic trees in vertebrates. Genome Res. 2008; 19(2):327-35. PMC: 2652215. DOI: 10.1101/gr.073585.107. View

Chen C, Chen H, Zhang Y, Thomas H, Frank M, He Y . TBtools: An Integrative Toolkit Developed for Interactive Analyses of Big Biological Data. Mol Plant. 2020; 13(8):1194-1202. DOI: 10.1016/j.molp.2020.06.009. View

Zhang J, Guo Z, Xue Z, Sun Z, Zhang M, Wang L . A phylo-functional core of gut microbiota in healthy young Chinese cohorts across lifestyles, geography and ethnicities. ISME J. 2015; 9(9):1979-90. PMC: 4542028. DOI: 10.1038/ismej.2015.11. View

Assad S, Rolny I, Minnaard J, Perez P . Bifidobacteria from human origin: interaction with phagocytic cells. J Appl Microbiol. 2020; 130(4):1357-1367. DOI: 10.1111/jam.14861. View

Matsuki T, Watanabe K, Tanaka R . Genus- and species-specific PCR primers for the detection and identification of bifidobacteria. Curr Issues Intest Microbiol. 2003; 4(2):61-9. View

Turroni F, Milani C, Duranti S, Mancabelli L, Mangifesta M, Viappiani A . Deciphering bifidobacterial-mediated metabolic interactions and their impact on gut microbiota by a multi-omics approach. ISME J. 2016; 10(7):1656-68. PMC: 4918443. DOI: 10.1038/ismej.2015.236. View

Becerra J, Yebra M, Monedero V . An L-Fucose Operon in the Probiotic Lactobacillus rhamnosus GG Is Involved in Adaptation to Gastrointestinal Conditions. Appl Environ Microbiol. 2015; 81(11):3880-8. PMC: 4421073. DOI: 10.1128/AEM.00260-15. View

10.

Yoon S, Ha S, Lim J, Kwon S, Chun J . A large-scale evaluation of algorithms to calculate average nucleotide identity. Antonie Van Leeuwenhoek. 2017; 110(10):1281-1286. DOI: 10.1007/s10482-017-0844-4. View

11.

Li J, Hou Q, Zhang J, Xu H, Sun Z, Menghe B . Carbohydrate Staple Food Modulates Gut Microbiota of Mongolians in China. Front Microbiol. 2017; 8:484. PMC: 5359301. DOI: 10.3389/fmicb.2017.00484. View

12.

Seemann T . Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014; 30(14):2068-9. DOI: 10.1093/bioinformatics/btu153. View

13.

Firrman J, Liu L, Zhang L, Argoty G, Wang M, Tomasula P . The effect of quercetin on genetic expression of the commensal gut microbes Bifidobacterium catenulatum, Enterococcus caccae and Ruminococcus gauvreauii. Anaerobe. 2016; 42:130-141. DOI: 10.1016/j.anaerobe.2016.10.004. View

14.

Cuskin F, Flint J, Gloster T, Morland C, Basle A, Henrissat B . How nature can exploit nonspecific catalytic and carbohydrate binding modules to create enzymatic specificity. Proc Natl Acad Sci U S A. 2012; 109(51):20889-94. PMC: 3529030. DOI: 10.1073/pnas.1212034109. View

15.

Turroni F, Milani C, Duranti S, Ferrario C, Lugli G, Mancabelli L . Bifidobacteria and the infant gut: an example of co-evolution and natural selection. Cell Mol Life Sci. 2017; 75(1):103-118. PMC: 11105234. DOI: 10.1007/s00018-017-2672-0. View

16.

Junick J, Blaut M . Quantification of human fecal bifidobacterium species by use of quantitative real-time PCR analysis targeting the groEL gene. Appl Environ Microbiol. 2012; 78(8):2613-22. PMC: 3318781. DOI: 10.1128/AEM.07749-11. View

17.

Garrido D, Ruiz-Moyano S, Kirmiz N, Davis J, Totten S, Lemay D . A novel gene cluster allows preferential utilization of fucosylated milk oligosaccharides in Bifidobacterium longum subsp. longum SC596. Sci Rep. 2016; 6:35045. PMC: 5069460. DOI: 10.1038/srep35045. View

18.

Yang S, Xie X, Ma J, He X, Li Y, Du M . Selective Isolation of From Human Faeces Using Pangenomics, Metagenomics, and Enzymology. Front Microbiol. 2021; 12:649698. PMC: 8096985. DOI: 10.3389/fmicb.2021.649698. View

19.

Gregg K, Finn R, Abbott D, Boraston A . Divergent modes of glycan recognition by a new family of carbohydrate-binding modules. J Biol Chem. 2008; 283(18):12604-13. PMC: 2335362. DOI: 10.1074/jbc.M709865200. View

20.

Zhang W, Sun Z . Random local neighbor joining: a new method for reconstructing phylogenetic trees. Mol Phylogenet Evol. 2008; 47(1):117-28. DOI: 10.1016/j.ympev.2008.01.019. View