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Genome-wide association studies of birth weight have focused on fetal genetics, whereas relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth. We meta-analysed data on up to 8.7 million SNPs in up to 86 577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother–child pairs to quantify the separate maternal and fetal genetic effects. Maternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9, CYP3A7) were associated with offspring birth weight at P < 5 Â 10 À8 . In SEM analyses, at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose (MTNR1B, GCK and TCF7L2) and sex hormone levels (CYP3A7), and one (EBF1) with gestational duration. The identified associations indicate that genetic effects on maternal glucose, cytochrome P450 activity and gestational duration, and potentially on maternal blood pressure and immune function, are relevant for fetal growth. Further characterization of these associations in mechanistic and causal analyses will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights.
Natural products and their semisynthetic derivatives are an important source of drugs for the pharmaceutical industry. Bacteria are prolific producers of natural products and encode a vast diversity of natural product biosynthetic gene clusters. However, much of this diversity is inaccessible to natural product discovery. Here, we use a combination of phylogenomic analysis of the microviridin biosynthetic pathway and chemo-enzymatic synthesis of bioinformatically predicted microviridins to yield new protease inhibitors. Phylogenomic analysis demonstrated that microviridin biosynthetic gene clusters occur across the bacterial domain and encode three distinct subtypes of precursor peptides. Our analysis shed light on the evolution of microviridin biosynthesis and enabled prioritization of their chemo-enzymatic production. Targeted one-pot synthesis of four microviridins encoded by the cyanobacterium Cyanothece sp. PCC 7822 identified a set of novel and potent serine protease inhibitors, the most active of which had an IC50 value of 21.5 nM. This study advances the genome mining techniques available for natural product discovery and obviates the need to culture bacteria.