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This Week in PNAS: Aug 12, 2014

In the early edition of the Proceedings of the National Academy of Sciences, researchers from Washington University present evidence suggesting gut microbial communities in infant guts vary with gestational age. The team did 16S ribosomal RNA sequencing on more than 900 stool samples to profile microbial community members in stool samples from 58 premature infants of different gestational ages tested over time. Results of the analysis indicated that gut microbiomes progress in a predictable way depending on gestational age, varying to a lesser extent with delivery method, antibiotic use, diet, or other environmental factors. "The pace of this progression is most strongly influenced by gestational age," the study's authors say, "with the microbial population assembling slowest for infant born most prematurely."

A team from the Massachusetts Institute of Technology and Harvard University describes the high-throughput combinatorial genetics approach it applied to enhancing the antibiotic effectiveness in resistant bacteria. The method — known as Combinatorial Genetics En Masse, or CombiGEM — considers barcoded genetic element combinations gleaned from next-generation sequencing data, researchers say. For their proof-of-principle application, they used CombiGEM to search transcription factor combinations that that dial down antibiotic resistance in strains of Escherichia coli that are normally impervious to carbapenem antibiotics. "We envision that CombiGEM could be extended to other model organisms, disease models, and phenotypes," they write, "where it could accelerate massively parallel combinatorial genetics studies for a broad range of biomedical and biotechnology applications, including the treatment of antibiotic-resistant infections."

A strategy known as genomic hybrid breeding appears to show promise for identifying hybrid rice plants with the potential for particularly favorable yields, according to another PNAS paper. Researchers from the US and China described the scheme, which is based on a genomic best linear unbiased prediction. After training it with genomic data for 278 rice hybrid developed from rice inbred lines, they went on to test its predictive prowess in simulation studies of almost 22,000 potential hybrid rice combinations. "Genotypes of the future hybrids are not measured but determined from their inbred parents," the team notes. "Although each pair of loci may be hard to detect because of the rare combination of some genotypes, all these rare events are given the same variance and thus are all combined together."