Maternal smoking during pregnancy increases the risk of gut microbiome-associated childhood overweight and obesity.

Childhood obesity is linked to maternal smoking during pregnancy. Gut microbiota may partially mediate this association and could be potential targets for intervention; however, its role is understudied. We included 1,592 infants from the Canadian Healthy Infants Longitudinal Development Cohort. Data on environmental exposure and lifestyle factors were collected prenatally and throughout the first three years. Weight outcomes were measured at one and three years of age. Stool samples collected at 3 and 12 months were analyzed by sequencing the V4 region of 16S rRNA to profile microbial compositions and magnetic resonance spectroscopy to quantify the metabolites. We showed that quitting smoking during pregnancy did not lower the risk of offspring being overweight. However, exclusive breastfeeding until the third month of age may alleviate these risks. We also reported that maternal smoking during pregnancy significantly increased Firmicutes abundance and diversity. We further revealed that Firmicutes diversity mediates the elevated risk of childhood overweight and obesity linked to maternal prenatal smoking. This effect possibly occurs through excessive microbial butyrate production. These findings add to the evidence that women should quit smoking before their pregnancies to prevent microbiome-mediated childhood overweight and obesity risk, and indicate the potential obesogenic role of excessive butyrate production in early life.

COVID-19 mRNA vaccine-mediated antibodies in human breast milk and their association with breast milk microbiota composition.

Newborns can acquire immunological protection to SARS-CoV-2 through vaccine-conferred antibodies in human breast milk. However, there are some concerns around lactating mothers with regards to potential short- and long-term adverse events and vaccine-induced changes to their breast milk microbiome composition, which helps shape the early-life microbiome. Thus, we sought to explore if SARS-CoV-2 mRNA vaccine could change breast milk microbiota and how the changes impact the levels of antibodies in breast milk. We recruited 49 lactating mothers from Hong Kong who received two doses of BNT162b2 vaccine between June 2021 and August 2021. Breast milk samples were self-collected by participants pre-vaccination, one week post-first dose, one week post-second dose, and one month post-second dose. The levels of SARS-CoV-2 spike-specific IgA and IgG in breast milk peaked at one week post-second dose. Subsequently, the levels of both antibodies rapidly waned in breast milk, with IgA levels returning to baseline levels one month post-second dose. The richness and composition of human breast milk microbiota changed dynamically throughout the vaccination regimen, but the abundances of beneficial microbes such as Bifidobacterium species did not significantly change after vaccination. Additionally, we found that baseline breast milk bacterial composition can predict spike-specific IgA levels at one week post-second dose (Area Under Curve: 0.72, 95% confidence interval: 0.58-0.85). Taken together, our results identified specific breast milk microbiota markers associated with high levels of IgA in the breast milk following BNT162b2 vaccine. Furthermore, in lactating mothers, BNT162b2 vaccines did not significantly reduce probiotic species in breast milk.

A Universal LC-MS/MS Method for Simultaneous Detection of Antibiotic Residues in Animal and Environmental Samples.

Detecting and monitoring the usage of antibiotics is a critical aspect of efforts to combat antimicrobial resistance. Antibiotic residue testing with existing LC-MS/MS methods is limited in detection range. Current methods also lack the capacity to detect multiple antibiotic residues in different samples simultaneously. In this study, we demonstrate a methodology that permits simultaneous extraction and detection of antibiotic residues in animal and environmental samples. A total of 30 different antibiotics from 13 classes could be qualitatively detected with our methodology. Further study to reduce analytes' matrix effect would allow for quantification of antibiotic residues.

Metagenomic Survey Reveals More Diverse and Abundant Antibiotic Resistance Genes in Municipal Wastewater Than Hospital Wastewater.

Alongside antibiotic resistance, co-selection of antibiotics, biocides, and metal resistance is a growing concern. While hospital wastewater is considered a hotspot for antibiotic-resistant bacteria (ARB) and genes (ARGs), the scenario in India, one of the biggest consumers of antibiotics, remains poorly described. In this study, we used metagenomic sequencing to characterize ARGs and biocide/metal resistance genes (BMRGs) in four wastewater treatment plants (WWTPs) in Jaipur City of India. We observed a significantly lower richness and abundance of ARGs in the influent of a WWTP exclusively receiving hospital wastewater when compared to other three WWTPs involving municipal wastewater treatment. Several tetracycline and macrolide-lincosamide-streptogramin resistance genes were enriched in influents of these three municipal wastewater-related treatment plants, whereas hospital wastewater had a higher abundance of genes conferring resistance to disinfectant-related compounds such as synergize and wex-cide-128, reflecting the patterns of antibiotic/disinfectant use. Of note, in the wastewater system with more chemicals, there was a strong correlation between the numbers of ARGs and BMRGs potentially harbored by common hosts. Our study highlights significant influxes of ARGs from non-hospital sources in Jaipur City, and thus more attention should be paid on the emergence of ARGs in general communities.