Dynamic alternations in mother-infant dyad’s gut microbiota over the period of six months

doi:10.21203/rs.3.rs-1672810/v1

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Research Article

Dynamic alternations in mother-infant dyad’s gut microbiota over the period of six months

https://doi.org/10.21203/rs.3.rs-1672810/v1

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posted 01 Jun, 2022

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Since birth, the human microbiome plays a pivotal role in health. It is intriguing to understand the establishing roles of intestinal microbiota in infants. This study aimed to investigate the dynamic changes in maternal and infant’s gut microbiota, the interaction between intestinal microbiota, and the function of intestinal microbiota. This study recruited one pregnant woman > 35 weeks gestational age. Faeces of the mother-infant dyad were regularly collected until six months of infant’s age for metagenomic analysis. The results showed the infant’s gut microbiota was different from the mother’s, majorly, encompassing Bacteroides fragilis, Ruminococcus gnavus, Klebsiella pneumoniae and Klebsiella michiganensis. Infant- or mother-specific differential metabolic pathways were found between the mother and infant’s gut microbiome, implicating differences in the intestinal metagenomic potential/function. In conclusion, the gut microbes and functions were gradually established as infant grew.

metagenomic analysis

gut microbiome

mother

infant

The human gut harbours trillions of symbiotic bacteria (Rosenberg & Zilber-Rosenberg, 2016). Everyone has hundreds different gut microbial species. To date, about 1,500 different microbial species have been identified from human gut. Since birth, the human microbiome plays a crucial role in maturing immune system and regulates health. Various maternal factors, vertical microbial transmission from mother, as well as horizontal environmental transmission and internal factors associated with the infant, play an indispensable role in regulating the gut microbiome (Kumbhare et al., 2019).

Gut microbiome ecology and function is dynamic and highly unstable during infancy, especially during the first year of life. The gut microbiota changes dramatically through interactions with the developing immune system in the gut (Tanaka et al., 2017). The healthy microbiome maintains the health of the host. The interaction between the microbiome and the host is substantially critical in early life because the abundance and composition of the microbiome undergo major changes in early life, and these changes become stable and remain constant throughout the life, thereby determine the healthy adult life (Neu et al., 2015). In early life, the gut microbiome is relatively active, and these initial inhabitants have the key impact on the health of the host throughout the life cycle (Scholtens et al., 2012;Tanaka & Nakayama, 2017). Understanding microbiome composition and structure in the intestine, and the factors that influence them in early life could provide a platform for developing strategies to maintain the host health by restoring the gut microbiota.

High-throughput sequencing is a powerful method that unfolds both the cultivable and uncultivable microbial population in samples. Metagenomic analysis has been used to describe the taxonomic composition and functional potential of microbial communities, as well as to assemble the entire genome sequence of a specific strain (Quince et al., 2017). Metagenomic data analysis has also enabled us to gain comprehensive understanding of microbial diversity, composition, community function, and their relationship with the colonic environment. Cost-effective and high-throughput metagenomic techniques have been widely used, and deep phylogenetic characteristics of intestinal microbiome have been successfully analyzed. It could be used as a nifty approach to analyze the structure and function of intestinal microflora in infants.

In this study, microbial metagenomic DNA was extracted from 1 mother-infant dyad’s fecal samples using DNA kit, and a metagenomic library containing genomic DNA was constructed and sequenced by Illumina sequencer. The dynamic changes of intestinal microflora of the mother before and after delivery were analyzed along with infant’s microflora over 6 months. Furthermore, the relationship between the structure and function of intestinal microflora of mother and infant was analyzed, so as to explore the influencing factors of intestinal microflora composition and establishment in early life.

Ethics statement

This work was approved by the Ethics Committee of Inner Mongolia Medical University (under the registration number ChiCTR2100044607, Chinese Clinical Trial Registry). T he participant provided the written informed consent prior to starting the study.

Subject recruitment

Pregnant woman was recruited by the Inner Mongolia Agricultural University, Hohhot, China. One normal pregnant woman at 35th week of gestational age, normal BMI, no periodontal disease, no type Ⅱ diabetes, no vaginitis, and without other history of serious/chronic diseases was recruited for this study. The mother did not take antibiotics or probiotics during pregnancy and lactation, and the fetus was delivered by natural labour at full term and fed by a mixture of breast milk and infant formula milk powder. The participant underwent ultrasound examination to assess the state of fetal wellbeing.

Study design and sample collection

The participant was requested not to take antibiotics and probiotic-containing foods during the trial period and to notify her doctor of any abnormalities. The participant was also asked to return the probiotic packaging materials for compliance assessment.

The first sample was collected 30 days before the expected date of confinement until the day of delivery (D-30) and was performed by trained professionals under strict aseptic conditions using standard procedures. Meanwhile, the participant was taught the standard sampling method. About 10 g of fecal samples were collected each time. From the first sample collection to the day of delivery, fecal samples were collected every seven days counting. Sampling, after the delivery, was continued from the mother and the infant. For the first week after delivery, samples were collected on the day of delivery (D0) and days 1, 2, 3, and 7 after delivery (D1, D2, D3, and D7, respectively). From the second week to two months after delivery (D14 to D56), fecal samples were collected every seven days. From the third to sixth month after delivery (D70 to D182), sampling was done every 14 days. The complete sampling lasted 212 days; however, as the participants did not defecate at certain time points, only a total of 33 faecal samples were collected from the mother (18 samples) and the infant (15 samples).

Fecal samples were collected into sterile tubes provided by our laboratory beforehand. Collected samples were stored temporarily in a household refrigerator (-20 ^◦C) and were transported to the laboratory by our staff within 24 hours of sample collection. They were stored at -80 ^◦C until total DNA was extracted.

DNA extraction

Metagenomic DNA was extracted from fecal samples using QIAamp Fast DNA Stool Mini-kit (QIAGEN, Hilden, Germany). The quality of extracted DNA was evaluated by agarose gel electrophoresis and Nanodrop spectrophotometry (optical density ratio at 260 nm/280 nm). All DNA samples were stored at -20 ^◦C until further processing.

Whole genome metagenomics sequencing and quality control

Metagenomic libraries containing 2 µg of genomic DNA were constructed according to the Illumina TruSeq DNA Sample Prep V2 Guide. The qualities of all libraries were assessed by an Agilent bioanalyzer and the DNA LabChip 1000 Kit. Sequencing was performed on an Illumina HiSeq XTEN sequencer (Illumina, San Diego, USA). The quality control filters were set according to Liu et al., 2016. Briefly, (1) Reads with adaptor sequences were removed by the software Seqprep. (2) Reads were trimmed from the 3’ end using a quality threshold of 30. (3) Low quality (Q30) reads comprised more than 50% of the bases were removed. (4) Reads less than 70 bp were removed by Sickle software. (5) Reads of host genome sequences were removed. High-quality reads (a total of 363.45 Gb, average of 11.01 Gb per sample) were retained and used for the further analysis.

Bioinformatic analysis

MetaPhlAn3 (Ver. 3.0) was used for species-level taxonomic assignment of fecal microbiota using default settings via the search engine Bowtie2 (Ver. 2.2.9) (Nousias & Montesanto, 2021; Langmead & Salzberg, 2012). PanPhlAn3 (Ver. 3.0.1) was used for species-level analysis (Scholz et al., 2016). If a strain was identified by PanPhlAn3, the abundance of the strain would be regarded as the species abundance. High-quality Illumina sequencing-generated metagenomic datasets were assembled by MegaHit (Ver. 1.0; Li et al., 2015). QUAST (Ver. 5.0.0) was used to evaluate the metagenomic assembly results. MetaBAT2 (Ver. 2.12.1) and Maxbin2 (Ver. 2.0) were used for binning the assemblies using a minimum scaffold length threshold of 1500 bp (Kang et al., 2019; Wu et al., 2016). Das Tool (Ver. 1.1.2) was used to connect the contigs assembled by MetaBAT2 and Maxbin2 (Sieber et al., 2018). Metagenome-assembly genomes (MAGs) in conformity with quality requirements (integrity > 80%, contamination < 10%) were selected. CheckM (Ver. 1.0.18) was then used to evaluate the integrity and contamination degree of each MAG (Parks et al., 2015), and high-quality MAGs were used for further analysis.

Each MAG was annotated by BLASTn using the Non-redundant Nucleotide Sequence Database (NT) of National Center for Biotechnology Information (NCBI), phylogenetic trees were constructed using 400 generic PhyloPhlAn markers, and the MAGs were clustered by dRep (Ver. 2.2.4) to define species-level genome bins (SGBs; Olm et al., 2017).

Statistical analysis

R package vegan was used for alpha and beta diversity analyses. Statistical differences in alpha diversity were assessed by Wilcoxon rank-sum tests. Multivariate analysis, such as principal coordinate analysis (PCoA), was performed by R software (Ver. 4.0.3; https://www.rproject.org/). Differential metabolic pathways between mother and infant’s gut microbiome were identified by t-tests. Correlations between different biological indicators were assessed with the Spearman’s rank correlation coefficient and visualized by Cytoscape 3.5.1. Spearman's correlation analysis was also performed to find significant correlations between the microbial community (r > 0.6, P < 0.05).

Microbial dynamics of mother’s and infant’s faecal microbiomes

The dynamics of the fecal microbiome composition and diversity of the mother-infant dyad was tracked over a period of 212 days. Species-level taxonomic annotation was performed with MetaPhlAn3. In total, the fecal microbiota of mother and infant contained sequences representing 310 species that belonged to 10 phyla and 55 families. There were 18 major species in the complete dataset (average relative abundance > 1.0%; Fig. 1A). Generally, the microbial complexity was rather low in the infant’s faeces having four major species, including Bacteroides fragilis, Ruminococcus gnavus, Klebsiella pneumoniae and Klebsiella michiganensis. Comparatively, the mother’s fecal microbiota was relatively complex, comprising a number of major species, e.g., Bacteroides vulgatus, Bacteroides stercoris, Faecalibacterium prausnitzii, Bacteroides uniformis, Eubacterium rectale, Bifidobacterium pseudocatenulatum and Alistipes putredinis.

The metagenomic data were subjected to PCoA (Bray-Curtis distance; Fig. 1B). Symbols representing the mother and infant’s microbiota which showed distinct clustering patterns on the PCoA score plot, confirming great differences in the fecal microbiota between the two individuals and little variation among samples of the same person. While the correlation between the gut microbiota of mother and infant was worth to explore.

Correlation network of fecal microbiota of mother and infant

A correlation network of fecal microbiota of the mother and infant was constructed to explore the relationship between mother and infant intestinal microbiota (Fig. 2). The top 30 species were included in the correlation analysis. Interestingly, most species showed significantly positive correlation (r = 0.8, P < 0.05), while a few species exhibited significantly negative correlation (r = 0.8, P < 0.05). Bacteroides fragilis (predominantly present in infant’s sample) showed significant positive correlation with Methanobrevibacter smithii and Anaerostipes hadrus, as well as Klebsiella pneumoniae with Klebsiella variicola. Some bacteria of mother, such as Bacteroides vulgatus with Bacteroides stercoris, Eubacterium rectale, Bifidobacterium pseudocatenulatum and Bacteroides uniformis, Faecalibacterium prausnitzii with Bifidobacterium pseudocatenulatum, Bacteroides vulgatus, Eubacterium rectale, Bacteroides uniformis and Bacteroides stercoris, Bacteroides stercoris with Bifidobacterium pseudocatenulatum, Eubacterium rectale and Bacteroides uniformis as well as Eubacterium rectale with Bifidobacterium pseudocatenulatum, they showed the significantly positive correlation. These results showed that there was a complex correlation between mother’s and infant’s gut microbiota.

Metagenomic potential of mother’s and infant’s microbiota

The metagenomic potential of mother and infant’s gut microbiota was annotated, and differential metabolic pathways were identified between the mother and infant’s data subsets (Fig. 3). In this study, Hierarchical Cluster Analysis was performed on the metabolic pathways of all samples (Fig. 3A).

Interestingly, the gene abundance of these metabolic pathways was relatively stable in mother’s microbiome but not in infant’s microbiome over time. The results of cluster heatmap broadly classified these metabolic pathways into three groups. The first group comprised nine metabolic pathways, including PWY-7204, PWY0-1241, and PWY-7269. Genes coding these metabolic pathways were mainly detected in the infant’s fecal samples. The second group contained eight metabolic pathways, including P562-PWY, PWY-6863, and P162-PWY. Genes coding these metabolic pathways were mainly observed in the maternal samples, but with a relatively low amount. The third category possessed 11 metabolic pathways, including PWY-5676, GALACT-GLUCUROCAT-PWY, and PRPP-PWY. These pathways were also mainly encoded in the maternal fecal microbiome. However, their relative contents were relatively high compared with those in the second group. These results indicated obvious differences existed in the metagenomic potential between the mother and infant’s gut microbiota, suggesting different physiological conditions within the mother and infant’s gut, which might in turn shape the functions of their microbial communities, respectively.

As one of the highest densities of microecology on earth, intestinal microbiota is a community of common future for human nutrition. The gut microbiota is closely related to human health and nutrition. Since birth, the human microbiome plays a crucial role in influencing the health of the host. Understanding the changes in the human gut microbiome helps to construct the intestinal microecosystem. Metagenomic sequencing analyses have been performed to explore the structure and function of human gut microbiota. This study used metagenomic sequencing to investigate the dynamic variation in mother and infant’s gut microbiota, the interaction between intestinal microbiota, and the function of intestinal microbiota.

The development of intestinal microbiota during the first 1,000 days of life will affect a person’s health throughout life (Agosti et al., 2017; Selma-Royo et al., 2019). Many factors determine the composition of intestinal microbiota in newborns. The method of delivery method plays an important role in the initial establishment of infant gut microbes (Yang et al., 2021). Arboleya and colleagues proposed that vaginal delivery and exclusive reliance on breastfeeding in early life are the gold standards for the establishment and development of healthy gut microbiota in infants (Arboleya et al., 2015). Bifidobacterium, Bacteroides, and Clostridium proliferate and become the dominant genera associated with early life (Thompson-Chagoyán et al., 2007). In the data we collected from our experiment, although Bifidobacterium was not found in the intestine of the newborn, Bacteroides was the dominant genus in the intestine. This was consistent with previous research. With the growth of the infant, the intestinal microbiota was more abundant, such as Ruminococcus gnavus, Klebsiella Pneumoniae, among others. Nevertheless, before six months, Bacteroides fragilis was still the highest relative abundance species in the infant’s intestine, which was beneficial to maintain the healthy environment of intestine and worthy of continuous attention and exploration. Our data also showed that the gut microbiota composition of the infant was much less complicated than that of the mother, which were in line with findings of previous studies.

Interestingly, we also observed differences in the richly differentiated taxonomic symbiotic network between the mother and infant. For example, in the infant’s intestine, Bacteroides fragilis, Methanobrevibacter smithii, etc were significantly positively correlated (P < 0.05), while Methanobrevibacter smithii generally appeared in the intestine of adults (Dridi et al., 2009). After obtaining this result, we repeated the investigation on the mother, and learned that the infant was fed by a mixture of breast milk and infant formula milk powder. In the study of Simpson M.R. et al., breastfeeding was one of the main factors affecting the early development of intestinal microbiota in infants (Simpson et al., 2018), which confirmed the important influence of breastfeeding on the development of intestinal microbiota in infants. For mixed infant, the composition of infant formula milk powder was very different from breast milk. For example, infant formula milk powder lacked key compounds found in human breast milk, such as HMOs (Kirmiz et al., 2018), which cause the intestinal microbiota of infants fed formula milk powder and breast milk very different (Schwarzenberg et al., 2018). Some studies have shown that formula milk powder might lead to the lack of Bifidobacteria in the intestinal microbial composition of infants (Hegar et al., 2019; Li et al., 2020), which was consistent with our findings.

The composition and activity of the intestinal microbiota co-develop with the host from birth, and are influenced by complex interactions with the host genome, nutrition, and lifestyle. Intestinal microbiota is involved in the regulation of multiple host metabolic pathways, mediating interactions between the host and bacterial metabolism, signal transduction, and immune and inflammatory nexus. These nexuses connect the gut, liver, muscle, and brain physiologically. An in-depth understanding of these nexuses is the prerequisite for optimizing therapeutic strategies to manipulate the gut microbiome to fight disease and improve health (Nicholson et al., 2012). Within these metabolic nexuses, multiple bacterial genomes could sequentially regulate metabolic responses, leading to combined metabolism of microbiome and host genomes to substrates (Nicholson & Wilson, 2003). The gut microbiota communicates metabolically with the host in a coordinated manner. After clustering analysis of metabolic pathways in the samples, we found that PWY-5676, GALACT-GLUCUROCAT-PWY, PRPP-PWY and others were consistent metabolic pathways in the infant and mother. Among of them, PWY-5676: acetyl-CoA fermentation to butanoate II pathway regulated the synthesis of butyric acid. Acetic acid, propionic acid, and butyric acid were the main short chain fatty acids (SCFAs) in the intestine. As the main energy source of intestinal cells, SCFAs regulate the absorption of a variety of nutrients in the intestinal tract, and are widely involved in energy metabolism, which are one kind of the most important products of intestinal microorganisms (Kasubuchi et al., 2015). This is also the evidence that the infant’s intestinal metabolic pathway is closer to adults. We speculated this might be due to the large differences in protein composition, lactose, fat, etc., between breast milk and infant formula milk powder. As a result, the structure and function of the microbiota in mixed diet fed infant were different from those in breastfed infants.

In conclusion, we found that the gut microbes were gradually established and perfected with the as the infant grew. Eutocia could promote the colonization of beneficial species in infant’s intestine, bringing the positive effects on the infant’s intestinal microflora. For the mixed diet feeding infant, the structure and function of intestinal microbiota were more similar to adults. Intestinal microbiota affects human development. Effectively using the information about intestinal microbiota could augment the human health. Better understanding about establishing mechanisms of intestinal microbiota in infants, and the prediction of infant’s intestinal microbiota, could provide a theoretical basis and guidance to promote the intestinal health of mothers and infants. However, this study was a scientific phenomenon discovered accidentally in experiment, further large-scale population experiments are needed.

AUTHORS’ CONTRIBUTIONS

Lan Yang: conducted the bench work, data analysis and interpretation, and manuscript writing; Hafiz Arbab Sakandar: provided advice and extensively edited and revised the manuscript; Heping Zhang and Zhihong Sun: conception and design of the study and final approval of the submitted manuscript.

CONFLICT OF INTEREST

The authors declare that they have no conflict of interest.

DATA AVAILABILITY STATEMENT

The datasets generated by the whole genome metagenomics sequencing that support the findings of this study are openly available in the NCBI Short Read Archive (SRA) database under accession number PRJNA770101, http://www.ncbi.nlm.nih.gov/bioproject/770101.

FUNDING DECLARATION

This work was supported by Science and Technology Major Projects of Inner Mongolia Autonomous Region (2021ZD0014).

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No competing interests reported.

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Dynamic alternations in mother-infant dyad’s gut microbiota over the period of six months

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Abstract

Figures

Introduction

Materials And Methods

Ethics statement

Subject recruitment

Study design and sample collection

DNA extraction

Whole genome metagenomics sequencing and quality control

Bioinformatic analysis

Statistical analysis

Results

Microbial dynamics of mother’s and infant’s faecal microbiomes

Correlation network of fecal microbiota of mother and infant

Metagenomic potential of mother’s and infant’s microbiota

Discussion

Declarations

References

Competing Interests

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