Computational identification of a systemic antibiotic for gram-negative bacteria.

Discovery of antibiotics acting against Gram-negative species is uniquely challenging due to their restrictive penetration barrier. BamA, which inserts proteins into the outer membrane, is an attractive target due to its surface location. Darobactins produced by Photorhabdus, a nematode gut microbiome symbiont, target BamA. We reasoned that a computational search for genes only distantly related to the darobactin operon may lead to novel compounds. Following this clue, we identified dynobactin A, a novel peptide antibiotic from Photorhabdus australis containing two unlinked rings. Dynobactin is structurally unrelated to darobactins, but also targets BamA. Based on a BamA-dynobactin co-crystal structure and a BAM-complex-dynobactin cryo-EM structure, we show that dynobactin binds to the BamA lateral gate, uniquely protruding into its ß-barrel lumen. Dynobactin showed efficacy in a mouse systemic Escherichia coli infection. This study demonstrates the utility of computational approaches to antibiotic discovery and suggests that dynobactin is a promising lead for drug development.

A selective antibiotic for Lyme disease.

Lyme disease is on the rise. Caused by a spirochete Borreliella burgdorferi, it affects an estimated 500,000 people in the United States alone. The antibiotics currently used to treat Lyme disease are broad spectrum, damage the microbiome, and select for resistance in non-target bacteria. We therefore sought to identify a compound acting selectively against B. burgdorferi. A screen of soil micro-organisms revealed a compound highly selective against spirochetes, including B. burgdorferi. Unexpectedly, this compound was determined to be hygromycin A, a known antimicrobial produced by Streptomyces hygroscopicus. Hygromycin A targets the ribosomes and is taken up by B. burgdorferi, explaining its selectivity. Hygromycin A cleared the B. burgdorferi infection in mice, including animals that ingested the compound in a bait, and was less disruptive to the fecal microbiome than clinically relevant antibiotics. This selective antibiotic holds the promise of providing a better therapeutic for Lyme disease and eradicating it in the environment.

A Distinct Microbiome Signature in Posttreatment Lyme Disease Patients.

Lyme disease is the most common vector-borne disease in the United States, with an estimated incidence of 300,000 infections annually. Antibiotic intervention cures Lyme disease in the majority of cases; however, 10 to 20% of patients develop posttreatment Lyme disease syndrome (PTLDS), a debilitating condition characterized by chronic fatigue, pain, and cognitive difficulties. The underlying mechanism responsible for PTLDS symptoms, as well as a reliable diagnostic tool, has remained elusive. We reasoned that the gut microbiome may play an important role in PTLDS given that the symptoms overlap considerably with conditions in which a dysbiotic microbiome has been observed, including mood, cognition, and autoimmune disorders. Analysis of sequencing data from a rigorously curated cohort of patients with PTLDS revealed a gut microbiome signature distinct from that of healthy control subjects, as well as from that of intensive care unit (ICU) patients. Notably, microbiome sequencing data alone were indicative of PTLDS, which presents a potential, novel diagnostic tool for PTLDS.IMPORTANCE Most patients with acute Lyme disease are cured with antibiotic intervention, but 10 to 20% endure debilitating symptoms such as fatigue, neurological complications, and myalgias after treatment, a condition known as posttreatment Lyme disease syndrome (PTLDS). The etiology of PTLDS is not understood, and objective diagnostic tools are lacking. PTLDS symptoms overlap several diseases in which patients exhibit alterations in their microbiome. We found that patients with PTLDS have a distinct microbiome signature, allowing for an accurate classification of over 80% of analyzed cases. The signature is characterized by an increase in Blautia, a decrease in Bacteroides, and other changes. Importantly, this signature supports the validity of PTLDS and is the first potential biological diagnostic tool for the disease.