Pregnancy is an extra-ordinary biologic process that women may experience during their lives, which involves a variety of physiologic changes. Some of these changes have been demonstrated, such as alterations in hormonal and metabolic levels. Only in recent years, investigators have gradually appreciated that the gut microbiota (GM) dynamics during pregnancy may also participate in physiologic activities and further regulate metabolism, thereby affecting the health of both mother and offspring (Nuriel-Ohayon et al., 2016).

Several reports observed have revealed attenuated microbial diversity of the GM accordance with pregnancy progression throughout the three trimesters (Koren et al., 2012; DiGiulio et al., 2015; Cortez et al., 2019; Wu et al., 2020). During early pregnancy, the composition of the GM resembles that of healthy non-pregnant individuals (Koren et al., 2012; Cortez et al., 2019). However, the composition of the GM gradually changes with the progression of pregnancy; that is, a diminution in α-diversity (the diversity of species within individuals) and commensurate elevation in β-diversity (a dissimilarity between individuals). In the third trimester of pregnancy, the relative abundance of Proteobacteria and Actinobacteria with their pro-inflammatory effects increase significantly, becoming the dominant microbiota (Ponzo et al., 2019a). In contrast, the relative abundances of butyrate-producing bacteria, such as Clostridium and Eubacterium decreased (Koren et al., 2012; DiGiulio et al., 2015; Wu et al., 2020). These results suggest that the GM may be involved in mediating glucose and lipid metabolism and inflammatory responses during pregnancy, and that these metabolic changes modulate intestinal microecology throughout pregnancy and even postpartum, thus constituting one of the ways by which the health of offspring is affected. However, the mechanism underlying this action remains unclear. A previous study showed that obese pregnant women had reduced abundances of intestinal Bifidobacteria and Bacteroides, and significantly increased abundances of Staphylococcus and Escherichia coli, compared with normal weight women during pregnancy (Santacruz et al., 2010; Gomez-Arango et al., 2016). Gestational weight gain (GWG) can reduce the diversity of the GM during pregnancy, increase the abundance of E. coli, and decrease the number of Bifidobacterium and Akk bacteria (Stanislawski et al., 2017). GM dynamics were also altered for pregnant women with pregnancy complications such as gestational diabetes mellitus (GDM) and hypertension (Kuang et al., 2017; Liu et al., 2017; Chen et al., 2020). Studies have shown that the GM may be a key factor affecting the occurrence and development of GDM. The α-diversity of the GM in GDM patients was significantly reduced, and the content of Parobacteria and Klebsiella was higher, while the abundances of Bifidobacterium and Eubacterium were higher in healthy pregnant women (Kuang et al., 2017), indicating that the GDM state is related to the GM imbalance. In addition, the abundances of Actinobacteria, Collinsella and Desulfovibrio in the gut of the GDM women were elevated relative to that of euglycemic pregnant women, and this difference persisted until after delivery. The diversity of the GM was also reduced in patients with preeclampsia, with the numbers of pathogenic bacteria such as Clostridium perfringens and Breedella increasing and the numbers of beneficial bacteria such as Coprococcus dextris decreasing as the pregnancy progressed (Liu et al., 2017; Stanislawski et al., 2017), this indicated the GM of patients with preeclampsia contained a certain degree of pathogenicity and was involved in the procession of this disease. In brief, GM plays an important role in the occurrence and development of various pregnancy-related diseases by participating in various metabolic pathways, and in immune regulation and inflammation in the human body. In addition, the association between maternal GM and spontaneous preterm birth, gestational hypothyroidism, postpartum depression and other factors also needs to be explored by supplemental studies.

Intriguingly, the GM can be orchestrated by various factors such as host genetics and lifestyle (Rothschild et al., 2018; Redondo-Useros et al., 2020). Investigators have recently ascertained that environments imposed dominant effects on the GM (He et al., 2018; Sun et al., 2021), suggesting differential GM dynamics during pregnancy in distinct populations. Therefore, exploration of GM variations during pregnancy in diverse populations should improve GM-targeted interventions (Deschasaux et al., 2018; Rothschild et al., 2018).

There are few extent reports on gestational variations in the GM for Chinese women in particular environments and who have adopted special dietary styles. In this study, we conducted a prospective cohort study to evaluate the related factors affecting GM the dynamics in pregnant women in Shijiazhuang, Hebei Province. The aim of this study was to evaluate the changes in the GM structure and function from early to late pregnancy and to discern the main factors that affected the changes in intestinal microecology in this specific geographic region and wit respect to specific dietary style. Our study should provide novel evidence for the presence fo the GM dynamics during pregnancy, based on findings from our specific population.

We hypothesize that (1) there are differences in the composition of the GM among the first (P1), second (P2), and third trimesters (P3) of pregnancy. (2) nutrient intake or health status comprise the main factors affecting the changes in the GM. (3) there are also differences in the composition and function of the GM with respect to the primary affecting factors.

The raw data were submitted to the CNGB Sequence Archive (CNSA) under Project no. CNP0003669. The sample-related metadata in this article are available upon reasonable request.

Emerging studies have revealed the presence of GM dynamics during pregnancy (Koren et al., 2012; DiGiulio et al., 2015; Nuriel-Ohayon et al., 2016, Neuman and Koren, 2017, Cortez et al., 2019). As GM structures can be modulated by host and environmental factors, it is important to explore gestational GM dynamics for different populations and then apply personalized GM-targeted interventions to improve health during pregnancy.

Consistent with prior reports (Koren et al., 2012; DiGiulio et al., 2015; Ferrocino et al., 2018; Abdullah et al., 2022), we observed gradual GM changes that paralleled the progression of pregnancy. We herein found a gradual increase in the α-diversity index (Shannon index) during P1, P2 and P3 of pregnancy, as reported in a previous Italian study (Ferrocino et al., 2018). In contrast, other reports found no obvious changes in GM diversity during pregnancy (DiGiulio et al., 2015; Abdullah et al., 2022). This discrepancy may be partially explained by different health statuses, diet and lifestyles specific to distinct populations (He et al., 2018; Rothschild et al., 2018; Redondo-Useros et al., 2020; Sun et al., 2021). Congruent with previous studies, we identified increased β-diversity of the GM in normal pregnancies (Koren et al., 2012; Ferrocino et al., 2018). Compositional GM changes were also reported during pregnancies, including increased Proteobacteria and decreased Bacteroides as trimesters progressed (Ponzo et al., 2019a), and this was consistent with our findings. Increased Proteobacteria may reduce glucose homeostasis, insulin resistance and low inflammatory responses in pregnant women (Koren et al., 2012; Ponzo et al., 2019a), suggesting an association between gestational changes in GM and health status.

In the current study, we observed that GDM was the most significant contributor to GM dynamics when compared to hypertension, age, diet or other factors; this was in accordance with various reports that indicated disproportionate GM structures in pregnant women with GDM (Karlsson et al., 2013; Le Chatelier et al., 2013; Crusell et al., 2018; Ferrocino et al., 2018; Wu et al., 2020; Zheng et al., 2020; Mokkala et al., 2021; Abdullah et al., 2022). Women with GDM tend to exhibit reduced insulin sensitivity and increased inflammation, which are generally related to reduced diversity of GM (Le Chatelier et al., 2013). Previous studies (Wu et al., 2020; Ferrocino et al., 2018; Abdullah et al., 2022) have also shown a relatively lower tendency for GM α-diversity indices (Ace, Chao, Shannon, and Simpson) in pregnant women with GDM compared to women without GDM. In addition, some studies failed to report any differences in α-diversity between GDM and non-GDM groups in late pregnancy (Crusell et al., 2018; Zheng et al., 2020). We speculate that these inconsistent findings were caused by specifically individualized GM, which can be modulated by host genetics and lifestyle (Rothschild et al., 2018; Redondo-Useros et al., 2020). Some studies (Barrett et al., 2018; Ponzo et al., 2019a) showed that dietary composition during pregnancy was an important factor affecting GM during pregnancy. However, we did not find any significant correlation between nutrient intake and GM in our sdury, and nutritional composition was not the primary factor affecting the dynamic changes of GM; this may be relate to the fact that our participants were all from the same region and had similar dietary structure and habits. In the future, larger-sample and multi-center studies are needed to explore the correlation between dietary intake and GM in Chinese pregnant women and its impact on the dynamic changes inherent to GM.

Our results also implied that there were differences in the composition of and trends in changes between the GDM group and the non-GDM group as the pregnancy progressed; this was in accordance with various reports that indicated inordinate GM structures in pregnant women with GDM (Kuang et al., 2017; Crusell et al., 2018; Ferrocino et al., 2018; Wang et al., 2018; Cortez et al., 2019; Ponzo et al., 2019b; Liu et al., 2020; Zheng et al., 2020). Several scientific groups have reported increases in the Firmicutes/Bacteroidetes ratio, Blautia, Roche, Bilophila, and Bifidobacterium among women with GDM compared to those without GDM (Ferrocino et al., 2018; Ponzo et al., 2019b; Zheng et al., 2020), as well as increases in Collinsella, Megamonas, and Doreas among GDM women in the P3 (Kuang et al., 2017; Crusell et al., 2018; Cortez et al., 2019). However, the abundances of short-chain fatty acid (SCFA)-producing bacteria, such as Faecalibacterium, Ruminococcus, Roseburia, Coprococcus, Akkermansia, Phascolarctobacterium, and Eubacterium were reduced (Kuang et al., 2017; Crusell et al., 2018; Wang et al., 2018; Cortez et al., 2019; Liu et al., 2020). In the resent study, we noted that the relative abundance of P.copri decreased continuously throughout pregnancy in the GDM group; and that Parabacteroides_distasonis, Lactobacillus_rogosae, Bacteroides_thetaiotaomicron, Bacteroides_uniformis, R.gnavus and B.vulgatus were enriched from early pregnancy onward. Firmicutes_bacterium_CAG_83 and Ruthenibacterium_lactatiformans were enriched from P2 onward, while Blautia_obeum and Dorea_longicatena increased in P3. We herein also found that some bacterial species, such as Akkermansia_muciniphila, Ruminococcus_bicirculans, Roseburia_hominis, and Clostridium_leptum accumulated in women with GDM, while other studies showed diminutions in women with GDM (Kuang et al., 2017; Liu et al., 2020; Wang et al., 2020; Wu et al., 2020; Xu et al., 2020). These distinctions emphasize the differential findings with respect to GM dynamics in GDM, and the necessity for the adoption of personalized GM-targeted interventions in different populations.

Other reports further revealed a role for the forementioned GM components in GDM. In a Chinese population-based study (Li et al., 2021), R.gnavus was found to be associated with elevated fasting blood glucose. It was also reported that R.gnavus could synthesize and secrete glucorhamnan, a complex polysaccharide with a rhamnose skeleton and glucose side chain, and that it effectively induced dendritic cells to secrete inflammatory cytokines (such as tumor necrosis factor, TNF-α) (Henke et al., 2019). We recognize that inflammation can impair glucose homeostasis, thereby altering insulin signaling (Mokkala et al., 2017), and we observed a correlation between GDM group-enriched GM components and the insulin-signaling pathway. For example, R.gnavus was found to be enriched in P1 of pregnancy and positively correlated with the insulin-signaling pathway. This finding may support the concept that increased R.gnavus in early pregnancy is associated with the development of GDM. In addition, GDM group-enriched B.vulgatus (among the microorganisms enriched in early pregnancy) also showed a significant positive correlation with the insulin-signaling pathway.

We identified a marked association between R. gnavus and B. vulgatus with the biosynthesis of lipopolysaccharide (LPS), an endotoxin that can induce low-grade inflammation and insulin resistance (Rosadini and Kagan, 2017; Cardona et al., 2018; Huang et al., 2021). The LPS contained in Bacteroidetes is a strong activator of Toll-like receptor 4 (TLR4), and the combination of LPS and TLR4 can activate a wide range of cell-signaling pathways, thereby inducing inflammatory responses and the expression and secretion of cytokines (Medzhitov and Horng, 2009). LPS biosynthesis is also positively correlated with blood glucose at the individual level (Kuang et al., 2017). In contrast, P.copri (which was more abundant in non-GDM women) was significantly negatively correlated with LPS biosynthesis.

Although our study encompasses changes in the GM during the natural course of pregnancy and the chief factors affecting these changes, and provides potential microbial markers for GDM monitoring, there were some limitations. (1) The single-center design is not extrapolable to the situation in different regional populations of China and (2) the small sample size of the present study, which contained only 55 participants, may lead to some bias in the analysis. Therefore, more work is needed in future studies. We posit (1) conducting large multicenter cohort studies to confirm our findings; (2) validating microbial markers for different geographic regions and ethnic groups; and (3) further analyzing the gut microbial functional pathways associated with GDM.

In conclusion, we observed variations in intestinal microecology from P1 to P3 of pregnancy, particular in P3, and noted that GDM was the primary factor affecting the changes in gut microbiota during pregnancy. Moreover, in women with and without GDM, the specific composition of GM varied at different pregnancy periods and associated with the insulin-signaling pathway as well as LPS biosynthesis, suggesting a potential role for GM in GDM development while providing potential GM-targeted prevention of GDM. This study could provide an additional reference for understanding the dynamics of gestational GM in disparate populations.

The data presented in this study are deposited in the CNGB (https://db.cngb.org/search/project/CNP0003669/) repository, accession number: CNP0003669.

The studies involving human participants were reviewed and approved by the Peking University Biomedical Ethics Committee (IR0001052-19150). The patients/participants provided their written informed consent to participate in this study.

GM managed the project. QZ and LC recruited the participants. ML, CM, and RC performed the sampling and information collection. LZ and QZ performed the bioinformatics analysis and guided the statistic analysis in this work. ML interpreted the analysis results and wrote the manuscript. NZ and GM supervised and polished the manuscript. All authors reviewed the manuscript.