Developmental differences in the intestinal microbiota of Chinese 1-year-old infants and 4-year-old children

The microbiota profile of children changes with age. To investigate the differences in the gut microbiota profile of 1- and 4-year-old children, we collected fecal samples and sequenced the V3–V4 hypervariable region of the 16S rRNA gene via high-throughput DNA sequencing. From phylum to species level, the microbiota underwent significant changes with age. The abundance of phyla Proteobacteria and Actinobacteria declined with age, whereas phyla Firmicutes and Bacteroidetes increased with age and dominated the gut microbiota of 4-year-olds. The intestinal environment of children at age four is closer to maturity. Hence, the abundance of Bifidobacterium significantly decreased in the gut of 4-year-olds, whereas Akkermansia muciniphila increased from 0.14% in 1-year-olds to 4.25% in 4-year-olds. The functional change in gut microbiota is consistent with changes in infant food, as microbiota participating in amino acid and vitamin metabolism were enriched in 1-year-olds, whereas microbiota involved in lipid metabolism increased with age.


Scientific Reports
| (2020) 10:19470 | https://doi.org/10.1038/s41598-020-76591-4 www.nature.com/scientificreports/ possess individually distinct microbial profiles by the end of the first year of life, but begin converging towards the characteristic microbiota of adults 24 , and by age three, the infant microbiota gradually changed towards an adult-like structure 25 . New opinion suggested that infant microbiota development may take longer than 3 years, but the gut microbiota composition in childhood beyond age three is often overlooked 26 .
To fill the knowledge gap about gut microbiota beyond age three, we collected the stool samples of 1-and 4-year-old healthy Chinese children and investigated whether they displayed a distinct microbial profile at age one and adult-like mature profile at age four.

Materials and methods
Sample collection. Study subjects were selected from the Shanghai-Minhang Birth Cohort Study (S-MBCS), which was reviewed and approved by the ethics committee board of the Shanghai Institute of Planned Parenthood Research (IRB00008297). Written informed consents were obtained from the parents of all participants involved in this study. All methods were performed in accordance with the Declaration of Helsinki. Fecal samples were collected from 1-year-old infants and 4-year-olds who were healthy, not overweight, had not taken antibiotics in one month, and had not developed eczema. All samples were stored at − 80 °C before DNA extraction.
DNA extraction, PCR amplification and 16S rRNA gene sequencing. DNA extraction and PCR amplification were performed as described previously 27 , with some modifications. In brief, the genomic DNA was extracted from 300 mg of feces using a QIAamp DNA stool mini kit (Qiagen, Hilden, Germany) according to the manufacturer's instructions. The integrity of extracted genomic DNA was checked by 1.5% agarose gel electrophoresis. To generate 16S rRNA gene amplicons, the V3-4 hypervariable region of the 16S rRNA genes was amplified using the primers 338F (5′-CCT ACG GGNGGC WGC AG-3′) and 806R (5′-GAC TAC HVGGG TAT CTA ATC C-3′) with a TransStart Fastpfu DNA Polymerase (TransGen, Beijing, China) in 20 cycles. All amplicons were purified using the QIAquick PCR Purification Kit (Qiagen), quantified on Qubit (Life Technologies), then pooled into equal concentrations. The pooled amplicons were ligated with adaptors using TruePrep DNA Library Prep Kit V2 for Illumina (Vazyme,China), then 2 × 300 bp paired-end sequencing was performed on an Illumina MiSeq instrument with MiSeq Reagent Kit v3.
Bioinformatics and statistical analysis. Paired-end 16S rRNA sequences were assembled using Mothur (version 1.41.1) 28 . DNA sequences were discarded using the following criteria: containing ambiguous bases, or containing chimeric or contaminant sequences, or homopolymers of > 8 nucleotides, or with lengths shorter than 350 bp. The chimeric sequences were identified by VSEARCH algorithm, and non-16S contaminants sequences were filtered based on the RDP database. Using SILVA reference databases (V132) 29 , the DNA sequences were clustered into OTUs at 97% similarity with reads number normalizing to 17,436. Community richness, evenness, and diversity (Shannon, Shannoneven, ACE, Chao, and Good's coverage) were also assessed using Mothur. The online software, Ribosomal Database Project (RDP) classifier 30 was used for taxonomy assignment for each Operational Taxonomic Units (OTU) 31 using default parameters. Differences in bacterial diversity were assessed using analysis of similarities (ANOSIM), based on the unweighted UniFrac distance metrics using Mothur. The differences in features (taxonomy and OTU) were determined using STAMP tool via the Benjamini-Hochberg FDR test 32 . The prediction of microbiome functions were analyzed using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) software 33 , based on Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways 34 .
Representative OTUs were identified as species against the SILVA SSU database (132) and the NCBI online database with > 99% identity and highest total score 29,35 .

Results
Gut bacterial populations in 1-and 4-year-old children. A total of 10,210,871 (17,495) high-quality reads were obtained by high-throughput sequencing of 16S rRNA genes from 153 fecal samples (40 and 113 from 1-and 4-year-olds, respectively). To normalize data and avoid statistical bias, 17,436 16S rRNA genes of each sample were selected to calculate bacterial species richness, evenness, and diversity at 97% similarity. A total of 7195 OTUs (371 OTUs per sample on average) were obtained, and the Good's coverage was over 99.8% for both groups (1-and 4-year-olds, Table 1), indicating that the sequencing depth was sufficient for gut microbiota investigation in children of two different ages.
Bacterial composition changes with age. Based on the unweighted UniFrac distance metrics, principal coordinate analyses (PCoA) showed two significant parts divided by two different point of age (Fig. 1). ANO-SIM analysis suggested that the microbial composition was significantly different (p < 0.001, R = 0.731) between www.nature.com/scientificreports/ 1-and 4-year-olds. Bacterial population evaluation showed that the species richness (ACE and Chao), species evenness, and diversity were significantly lower in the gut of 1-year-olds than in that of 4-year-olds ( Fig. 2, p < 0.05). These results indicate that microbiota composition and diversity increased with the age of children. From phylum to species level, the microbiota differed significantly between 1-and 4-year-olds. At the phylum level, a total of 12 phyla were confirmed, with five major phyla (Actinobacteria, Bacteroidetes, Firmicutes, Proteobacteria, and Verrucomicrobia) composing > 99% of gut microbiota (Fig. 3), and three phyla unique to 4-year-olds. Phyla Actinobacteria and Proteobacteria showed significant enrichment in 1-year-olds (q < 0.05), while phyla Firmicutes, Synergistetes, and Verrucomicrobia were significantly enriched in 4-year-olds ( Fig. 4A).
At the class level, a total of 20 classes were revealed; 16 classes were identified in both 1-and 4-year-olds and nine classes were significantly different between both groups ( Figure S1), with Actinobacteria, Bacilli, Erysipelotrichia and Gammaproteobacteria significantly enriched in 1-year-olds, and Betaproteobacteria, Clostridia, Deltaproteobacteria, Synergistia and Verrucomicrobiae significantly increased in 4-year-olds.
At the order level, 38 orders were identified in total; 28 orders were identified in both groups, and nine orders were significantly different between the groups ( Figure S2), including Bifidobacteriales, Enterobacteriales, Erysipelotrichales and Lactobacillales enriched in 1-year-olds and Burkholderiales, Clostridiales, Desulfovibrionales, Synergistales, and Verrucomicrobiales enriched in 4-year-olds.

Discussion
In this study, we compared the gut microbiota of 1-and 4-year-old Chinese children by investigating the V3-V4 hypervariable region of the 16S rRNA gene via high-throughput DNA sequencing. Our results revealed that the gut microbiota in children increased significantly from age 1 to 4. In terms of population, species richness, species evenness, and diversity were mainly dominated by five phyla (Actinobacteria, Proteobacteria, Firmicutes, Bacteroidetes and Verrucombicrobia). These findings are consistent with previous reports that the gut microbiome of children gradually mature as that of adults during the first three years of life 25 . A lot of research in the past decades have focused on the development of the infant gut microbiota during the first 3 years of life; only, few reports have investigated the variation in gut microbiota in children above 3 years of age 26 , and further studies are needed. For example, Fiona et al. indicated that the gut microbiota of children was dynamic before age four due to the effects of perinatal factors 36 , and Ringel-Kulka et al. revealed that by age four the microbiota of children were still not as mature as those of adults, suggesting that the microbiota of children continue to progress after age 4 37 .
Hence, our research paid attention to the development of children's gut microbiota at age four for a deeper understanding of the intestinal microbiota of children. Through the unweighted UniFrac distance metrics, we demonstrated that there was a significant difference in gut microbiota compositions between 1-and 4-year-old children, suggesting that the gut microbiota of infants matures with age.
We analyzed specific differences from the phylum to the species level. At the phylum level, Actinobacteria and Proteobacteria were significantly reduced in the intestines of 4-year-olds. This result is consistent with previous reports that Actinobacteria, represented by Bifidobacterium, declined after weaning due to decreased protein requirements 22,38,39 . However, Firmicutes, Synergistetes, and Verrucomicrobia increased significantly in www.nature.com/scientificreports/ the intestines of 4-year-olds. It was recently noted that the abundance of Firmicutes is suppressed while children receive breast milk 20 . Once weaning begins, Firmicutes increase in abundance and dominate gut microbiota. It is supposed that the introduction of solid foods can increase bacterial load and short-chain fatty acid levels, which may be due to the ability of Firmicutes, such as Roseburia spp., to metabolize carbohydrates in the diet 40,41 . Bacteroides, which can breakdown complex plant polysaccharides 42 , maintain dominance of the gut microbiota with age, indicating that Bacteroides already attained stability at infancy. These results are consistent with previous reports that Firmicutes and Bacteroidetes are the most dominant phyla in healthy adult subjects 43 , suggesting a maturation of gut microbiota at age 4. At the genus level, Bifidobacterium, Escherichia/Shigella, and Veillonella were enriched in the intestines of 1-year-olds. Bifidobacterium levels declined with age, in agreement with reports that Bifidobacterium is more abundant in children than in adults 44 . It is generally known that Bifidobacterium has several subspecies relating to infants. Bifidobacterium longum subsp. is a kind of archetypical bacteria capable of using human milk oligosaccharide (HMO) as substrates. B. longum subsp. infantis is an infant commensal that thrives in the presence of milk 45 . Our results showed that the abundance of Bifidobacterium decreased significantly in the gut microbiota of 4-year-olds, coinciding with the beginning of weaning and the introduction of table foods. In the gut   E. coli, B. pseudocatenulatum, B. longum, B. wexlerae, F. saccharivorans, R. timonensis, R. gnavus, S. salivarius, V. dispar and B. breve were more abundant in the intestines of 1-year-olds than in those of 4-year-olds. F. prausnitzii is one of the most abundant microorganisms in the intestinal tract of healthy people; it can generate butyrate as an anti-inflammatory to help slow down inflammatory bowel disease 46 . A. muciniphila, a mucin-degrading probiotic, increased from 0.14% in 1-year-olds to 4.25% in 4-year-olds. A. muciniphila can regulate immune responses by promoting relevant gene expression 47 , and reverse high-fat diet-induced metabolic disorders by improving host metabolism 46 . R. inulinivorans belong to the genus Roseburia, which was reported to produce short-chain fatty acids and play a major role in maintaining gut health and immune defense 48 . The increased levels of these profitable species suggest that the intestinal environment of 4-year-olds is attaining adult-like maturity.
Bifidobacterium is able to thrive on HMOs and is dominant in infant gut microbiota before weaning 24 . The abundance of these milk-related Bifidobacterium, including B. pseudocatenulatum, B. longum, and B. breve, significantly decreased in 4-year-olds due to the change in their diet (from milk to solid food). The onset of weaning is usually associated with an increase in a diversity of intestinal microbiota, with Bifidobacteria-dominated www.nature.com/scientificreports/ intestinal microbiota gradually being replaced by more complex microbial communities capable of degrading carbohydrates from plant and animal sources. In this study, PICRUSt software was used to predict the potential function of the gut microbiota of 1-and 4-year-olds. Bacteria involved in galactose metabolism, amino acid metabolism, cofactor and vitamin metabolism like folate biosynthesis, nicotinate and nicotinamide metabolism, vitamin B6 metabolism, etc., were significantly enriched in 1-year-olds. While the abundance of microbiota participating in lipid metabolism, metabolism of Table 2. Dominant genera and significant difference between 1-year and 4-years old children. www.nature.com/scientificreports/ terpenoids and polyketides pathways increased with age. This functional change in microbiota is consistent with children's diet changes. Nevertheless, the current study has limitations as this study used fecal samples. As is known, the fecal microbiota does not fully represent the luminal or mucosal communities of the GI tract 49,50 . Although previous study revealed that fecal microbial community has a good potential to identify most taxa in the chicken gut 51 , noninvasively sampling at different gut locations would be preferred, and recently developed smart sampling capsule would achieve this goal 52 . Another limitation of our study is lacking of paying attention to the factors influencing the development of intestinal microbiota in children, such as breast milk feeding, dietary habits and antibiotic use.
In conclusion, the first 4 years of life is a crucial period for the formation of intestinal microbiota in young children, and has a profound impact on subsequent physical development and health. Our study demonstrates that the intestinal microbiota composition of infants changed from Bifidobacteria-dominated to a more complex microbiota, and attained adult-like intestinal microbiota maturation by age four. It is worthy of note that owing to various influencing factors, there are great differences in the composition and development of intestinal microbiota among different populations; our study is scientifically relevant among existing studies involving other ethnic groups.

Data availability
The microbiota sequence data for the 1-and 4-year-old children have been deposited in the National Omics Data Encyclopedia (NODE, https ://www.biosi no.org/node/index ) under the accession numbers OEX010570 and OEX010571, respectively.