Women with gestational diabetes mellitus (GDM) have different gut microbiota in late pregnancy compared to women without GDM. It remains unclear whether alterations of gut microbiota can be identified prior to the diagnosis of GDM. This study characterized dynamic changes of gut microbiota from the first trimester (T1) to the second trimester (T2) and evaluated their relationship with later development of GDM. Compared with the control group (n = 103), the GDM group (n = 31) exhibited distinct dynamics of gut microbiota, evidenced by taxonomic, functional, and structural shifts from T1 to T2. Linear discriminant analysis (LDA) revealed that there were 10 taxa in T1 and 7 in T2 that differed in relative abundance between the GDM and control groups, including a consistent decrease in the levels of Coprococcus and Streptococcus in the GDM group. While the normoglycemic women exhibited substantial variations of gut microbiota from T1 to T2, their GDM-developing counterparts exhibited clearly reduced inter-time point shifts, as corroborated by the results of Wilcoxon signed-rank test and balance tree analysis. Moreover, cooccurrence network analysis revealed that the interbacterial interactions in the GDM group were minimal compared with those in the control group. In conclusion, lower numbers of dynamic changes in gut microbiota in the first half of pregnancy are associated with the development of GDM. IMPORTANCE GDM is one of the most common metabolic disorders during pregnancy and is associated with adverse short-term and long-term maternal and fetal outcomes. The aim of this study was to examine the connection between dynamic variations in gut microbiota and development of GDM. Whereas shifts in gut microbiota composition and function have been previously reported to be associated with GDM, very little is known regarding the early microbial changes that occur before the diagnosis of GDM. This study demonstrated that the dynamics in gut microbiota during the first half of pregnancy differed significantly between GDM and normoglycemic women. Our findings suggested that gut microbiota may potentially serve as an early biomarker for GDM.
SummaryAbiotic stresses are a major cause of crop loss. Ascorbic acid (AsA) promotes stress tolerance by scavenging reactive oxygen species (ROS), which accumulate when plants experience abiotic stress. Although the biosynthesis and metabolism of AsA are well established, the genes that regulate these pathways remain largely unexplored. Here, we report on a novel regulatory gene from tomato (Solanum lycopersicum) named SlZF3 that encodes a Cys2/His2‐type zinc‐finger protein with an EAR repression domain. The expression of SlZF3 was rapidly induced by NaCl treatments. The overexpression of SlZF3 significantly increased the levels of AsA in tomato and Arabidopsis. Consequently, the AsA‐mediated ROS‐scavenging capacity of the SlZF3‐overexpressing plants was increased, which enhanced the salt tolerance of these plants. Protein–protein interaction assays demonstrated that SlZF3 directly binds CSN5B, a key component of the COP9 signalosome. This interaction inhibited the binding of CSN5B to VTC1, a GDP‐mannose pyrophosphorylase that contributes to AsA biosynthesis. We found that the EAR domain promoted the stability of SlZF3 but was not required for the interaction between SlZF3 and CSN5B. Our findings indicate that SlZF3 simultaneously promotes the accumulation of AsA and enhances plant salt‐stress tolerance.
The Beijing genotype of Mycobacterium tuberculosis has frequently been found to be associated with drug resistance. Mutation analysis of the genes encoding 16S rRNA (rrs) and ribosomal protein S12 (rpsL) revealed a high frequency (97/102; 95.1%) of alterations in streptomycin-resistant M. tuberculosis isolates from Singapore, with rpsL K43R being the most common rpsL mutation (82/92; 89%), which was significantly associated with Beijing strains compared to non-Beijing strains (odds ratio = 10.88, 95% confidence interval = 3.48-34.1). This is the first study to report the association of Beijing strains with the rpsL K43R mutation in STR-resistant M. tuberculosis isolates with de novo resistance, as determined by clustering analysis.
Congenital hypothyroidism (CH) is one of the most common neonatal endocrine diseases. This retrospective cohort study aimed to identify the potential perinatal risk factors for CH and to differentiate between transient and permanent CH (TCH and PCH, respectively) as well as determine their prevalence in a southeastern Chinese population. This study was based on an 18-year surveillance of a neonatal CH screening program in a large tertiary hospital. A retrospective review of the maternal and neonatal perinatal exposures was conducted. Of the 205,834 newborns screened between 2000 and 2018, 189 were diagnosed with CH (1/1089). Among the 131 CH patients who again underwent thyroid function testing (TFT) after discontinuation of levothyroxine at the age of 3 years, 61 (46.6%) were diagnosed with PCH and 70 (53.4%) were diagnosed with TCH. In the maternal characteristics model, women aged 35 years or older and those who had thyroid disease and/or diabetes mellitus during pregnancy had increased risk of having an offspring with CH (P = .001, .000, and .001, respectively). Significant associations were found with regard to parity and the risk of CH in the offspring (P = .000). In the neonatal characteristics model, infants with female sex, preterm birth, post-term birth, low birth weight, other birth defects, and those born as part of multiple births (P = .011, .034, .001, .000, .000, and .003, respectively) had increased risk of CH. The rate of newborns with other birth defects was higher in the PCH group than that in the TCH group (P = .008), whereas the rate of maternal thyroid disease, newborns with low birth weight, and newborns with preterm birth was higher in the TCH group than that in the PCH group (P = .041, .020, and .013, respectively). The levothyroxine dose (μg/kg/day) at 1 year, 2 years, and 3 years old was significantly lower in the TCH group than that in the PCH group (P = .000, .000, and .000, respectively). Perinatal factors should be considered during the diagnosis and treatment of CH.
Gestational diabetes mellitus (GDM), defined as dysglycaemia that is detected during pregnancy for the first time, has become a global health burden. GDM was found to be correlated to epigenetic changes, which would cause abnormal expression of placental genes. In the present study, we performed multi-omic weighted gene coexpression network analysis (WGCNA) to systematically identify the hub genes for GDM using both epigenome-and transcriptomewide microarray data. Two microarray datasets (GSE70493 and GSE70494) were downloaded from the Gene Expression Omnibus (GEO) database. GEO2R was used to screen differentially expressed genes (DEGs) and differentially methylated genes (DMGs) between normal and GDM samples, separately. The results of WGCNA found that 15 modules were identified and the MEblack module had a significantly negative correlation with GDM (r = −.28, P = .03). GO enrichment analysis by BinGO of the MEblack module showed that genes were primarily enriched for the presentation of antigen processing, regulation of interferon-α production and interferon-γ-mediated signaling pathway. By comparing the DEGs, DMGs and hub genes in the coexpression network, we identified five hypermethylated, lowly expressed genes (ABLIM1, GRHL1, HLA-F, NDRG1, and SASH1) and one hypomethylated, highly expressed gene (EIF3F) as GDM-related hub DMGs. Moreover, the expression levels of ABLIM1, GRHL1, HLA-F, NDRG1, and SASH11 in the GDM patients and healthy controls were validated by a real-time quantitative polymerase chain reaction. Finally, gene set enrichment analysis showed that the biological function of cardiac muscle contraction was enriched for four GDM-related hub DMGs (ABLIM1, GRHL1, NDRG1, and SASH1). Analysis of this study revealed that dysmethylated hub genes in GDM placentas might affect the placental function and thus, take part in GDM pathogenesis and fetal cardiac development. K E Y W O R D S epigenome, gestational diabetes mellitus, transcriptome, WGCNA
Background: To establish age-standardized charts of weight gain for term twin pregnancies in Southeast China. Methods: We designed a retrospective study on data from women pregnant with twins, a gestational age beyond 36 weeks and an average weight ≥ 2500 g. We established hierarchical linear regression models to express gestational weight gain patterns. Results: We analyzed data from 884 women pregnant with twins (151 underweight, 597 normal weight, and 136 overweight). Our final models fit the crude weight measurement data well. The means of weight gain generally decreased as the pre-pregnancy BMI increased. For each BMI category, the mean weight gains increased with the gestational age and the standard deviation increased slightly. The mean weight gains were 18.82 ± 6.73, 18.53 ± 6.74, and 16.97 ± 6.95 kg at 37 weeks in underweight, normal weight, and overweight women, respectively. Conclusion: The weight gain chart can be used to estimate maternal weight gain to be gestational agestandardized z scores by pre-pregnancy BMI and may serve as an innovative tool for perinatal care providers to guide the weight gain of women pregnant with twins.
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