Previous animal experiments have shown that fine particulate matter (PM_2.5) exposure can change the composition of gut microbiota in newborn mice, but there is no epidemiological evidence on the effects of PM_2.5 exposure during pregnancy on neonatal meconium microbiome.

This study is designed to evaluate the association between PM_2.5 exposure during pregnancy and neonatal meconium microbiome, and to explore the underlying functional pathways involved.

Based on Shanghai Maternal-Child Pairs Cohort, 600 pregnant women with complete follow-up data were randomly recruited. Maternal exposure levels of PM_2.5 were estimated through gestational exposure prediction model combining satellite-driven ambient concentrations and monitoring station data. According to the median PM_2.5 concentration, the pregnant women were divided into a PM_2.5 high-exposure group and a low-exposure group. After delivery, newborns' meconium was collected and 16S rDNA gene sequencing was performed on the Illumina MiSeq sequencing platform. The sequences of 522 samples that were successfully sequenced were analyzed. Based on multiple linear regression, single pollutant models and two-pollutant models were used to evaluate the effect of PM_2.5 on meconium microbiome alpha diversity (reflecting the composition of the flora, evaluation indicators: Chao1 index, observed species index, Shannon index, and Simpson index). Principal co-ordinates analysis and permutational multivariate analysis of variance, based on unweighted UniFrac distance, were used to compare beta diversity (reflecting the similarity of the flora). LDA Effect Size (LEfSe) was also used to analyze the different bacterial taxa between the two groups. Kyoto Encyclopedia of Genes and Genomes (KEGG) database (divided into three levels: L1, L2, and L3) was used to predict the functional pathways involved.

The median (P₂₅-P₇₅) PM_2.5 concentration in the low-exposure group was 38.3 μg·m^-3 (36.4-40.3 μg·m^-3), and the concentration in the high-exposure group was 45.4μg·m^-3 (44.5-46.4μg·m^-3). Gestational PM_2.5 exposure was inversely associated with the alpha diversity of newborns' meconium microbiome. In the single pollutant model, every 1 μg·m^-3 increment in PM_2.5 exposure was associated with 5.28 (95%CI: -7.73--2.83), 4.00 (95% CI: -5.75--2.23), 3.06 (95% CI: -4.66--1.45), and 4.54 (95% CI: -6.65--2.43) decrease in Chao1 index, observed species index, Shannon index, and Simpson index of meconium microbiome, respectively. Also, a significant difference in beta diversity between the two groups was observed (P=0.02). Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes were the dominant taxa in the meconium of the two groups. As shown in the LEfSe analysis, compared with the low-exposure group, the relative abundances of 13 bacterial taxa in the PM_2.5 high-exposure group were increased, while the relative abundances of 21 taxa was decreased. The functional analysis results showed that these bacterial taxa were involved in glycolipid metabolism, energy metabolism, amino acid metabolism, transmembrane transport, etc. The results of KEGG enrichment analysis of the L3 group suggested that transporters, ribosome, ABC transporters, glycolysis/gluconeogenesis, glycerolipid metabolism, cysteine and methionine metabolism, pyruvate metabolism, amino sugar and nucleotide sugar metabolism, and D-glutamine and D-glutamate metabolism were up-regulated in the PM_2.5 high-exposure group; while secretion system, bacterial motility proteins, two-component system, energy metabolism, lipopolysaccharide biosynthesis, glyoxylate and dicarboxylate metabolism, biosynthesis of unsaturated fatty acids, glutathione metabolism, WNT signaling pathway, and riboflavin metabolism were up-regulated in the low-exposure group.

Gestational PM_2.5 exposure is associated with the diversity and composition of neonatal meconium microbiome. High PM_2.5 exposure during pregnancy is associated with decreased alpha diversity of meconium microbiome. There is also significant differences in beta diversity and composition of the dominant microbiome between the high-exposure and the low-exposure groups..