Skip to main content
Premium Trial:

Request an Annual Quote

This Week in PNAS: Apr 30, 2019

Researchers from Massachusetts General Hospital, Harvard Medical School, and the Broad Institute focus in on the core, essential genome for Pseudomonas aeruginosa, a clinically important microbe with the capability of becoming antibiotic resistant. The team performed transposon insertion sequencing on nine P. aeruginosa strains grown in several types of media, using a statistical model known as "Finding Tn-Seq Essential genes" (FiTnEss) to define 321 core, essential genes encoded by less than 7 percent of the P. aeruginosa genome. "[W]e suggest that a major factor in the failure of genomics to transform antibiotic discovery in the late 19902 to early 2000s was due not to a fundamental flaw with the concept of defining essential genes, but rather to challenges in implementing the approach," the authors write. "[O]ur hope is that defining a core essential genome by selecting diverse strains across its phylogenetic tree will enable more effective discovery and development of much needed antibacterial therapeutics."

A University of Nottingham-led team takes a look at ancient Paget's disease of the bone (PDB) cases with paleoproteomic, ancient DNA sequencing, and small RNA sequencing analyses. Using targeted proteomics, the researchers searched for informative proteins in half a dozen Medieval skeletons from sites in northwestern England that showed signs PDB pathology, uncovering a protein called sequestosome 1, or p62, that has been linked to present-day PDB cases in the ancient remains. Even so, their targeted sequencing experiments suggest ancient individuals with PDB-like symptoms did not carry the mutations in the p62-coding gene SQSTM1 that have been implicated in contemporary PDB cases. "Our work displays the use of proteomics to inform diagnosis of ancient diseases such as atypical PDB," they conclude, "which has unusual features presumably potentiated by yet-unidentified environmental or genetic factors."

Researchers at Columbia University, Stanford University, and elsewhere explore de novo germline mutation sources using sequence data for more than 1,500 parent-child trios profiled by Decode. Based on the de novo mutations identified in these families, the team suggests that DNA damage may play a more pronounced role in mutations arising from fathers than DNA replication during sperm production, while maternal age appeared to impact the number of new mutations that arose in eggs before and after fertilization. Indeed, the authors report that "a substantial fraction of mutations are not replicative in origin and uncover a potential effect of a mother's age on the number of mutations that happen early in the development of the embryo."