Significance Cell signaling involves interpreting information from the environment and implementing the appropriate regulatory control. The ppGpp signaling system is known to exert a fundamental control in bacteria, coordinating ribosome synthesis with the rate of cellular growth, but how this system can sense the cellular growth rate in different environments is unclear. Here we establish a striking linear relation between ppGpp level and the reciprocal of the translation elongation rate (ER) and show how bacteria can process complex nutritional information by monitoring this rate and using it to control ribosome synthesis. Importantly, the sensing of ER through ppGpp quantitatively and mechanistically explains bacterial growth laws which robustly relate the ribosome content and translation ERs to the growth rate.

Botulism, a disease of humans characterized by prolonged paralysis, is caused by botulinum neurotoxins (BoNTs), the most poisonous substances known. There are seven serotypes of BoNT (A-G) which differ from each other by 34-64% at the amino acid level. Each serotype is uniquely recognized by polyclonal antibodies, which originally were used to classify serotypes. To determine if there existed monoclonal antibodies (mAbs) capable of binding two or more serotypes, we evaluated the ability of 35 yeast-displayed single-chain variable fragment antibodies generated from vaccinated humans or mice for their ability to bind multiple BoNT serotypes. Two such clonally related human mAbs (1B18 and 4E17) were identified that bound BoNT serotype A (BoNT/A) and B or BoNT/A, B, E and F, respectively, with high affinity. Using molecular evolution techniques, it proved possible to both increase affinity and maintain cross-serotype reactivity for the 4E17 mAb. Both 1B18 and 4E17 bound to a relatively conserved epitope at the tip of the BoNT translocation domain. Immunoglobulin G constructed from affinity matured variants of 1B18 and 4E17 were evaluated for their ability to neutralize BoNT/B and E, respectively, in vivo. Both antibodies potently neutralized BoNT in vivo demonstrating that this epitope is functionally important in the intoxication pathway. Such cross-serotype binding and neutralizing mAbs should simplify the development of antibody-based BoNT diagnostics and therapeutics.

Quantitation of individual mAbs within a combined antibody drug product is required for preclinical and clinical drug development. We have developed two antitoxins (XOMA 3B and XOMA 3E) each consisting of three monoclonal antibodies (mAbs) that neutralize type B and type E botulinum neurotoxin (BoNT/B and BoNT/E) to treat serotype B and E botulism. To develop mAb-specific binding assays for each antitoxin, we mapped the epitopes of the six mAbs. Each mAb bound an epitope on either the BoNT light chain (LC) or translocation domain (HN). Epitope mapping data was used to design LC-HN domains with orthogonal mutations to make them specific for only one mAb in either XOMA 3B or 3E. Mutant LC-HN domains were cloned, expressed, and purified from E. coli. Each mAb bound only to its specific domain with affinity comparable to the binding to holotoxin. Further engineering of domains allowed construction of ELISAs that could characterize the integrity, binding affinity, and identity of each of the six mAbs in XOMA 3B, and 3E without interference from the three BoNT/A mAbs in XOMA 3AB. Such antigen engineering is a general method allowing quantitation and characterization of individual mAbs in a mAb cocktail that bind the same protein.

Biosensors are key components in engineered biological systems, providing a means of measuring and acting upon the large biochemical space in living cells. However, generating small molecule sensing elements and integrating them into in vivo biosensors have been challenging. Here, using aptamer-coupled ribozyme libraries and a ribozyme regeneration method, de novo rapid in vitro evolution of RNA biosensors (DRIVER) enables multiplexed discovery of biosensors. With DRIVER and high-throughput characterization (CleaveSeq) fully automated on liquid-handling systems, we identify and validate biosensors against six small molecules, including five for which no aptamers were previously found. DRIVER-evolved biosensors are applied directly to regulate gene expression in yeast, displaying activation ratios up to 33-fold. DRIVER biosensors are also applied in detecting metabolite production from a multi-enzyme biosynthetic pathway. This work demonstrates DRIVER as a scalable pipeline for engineering de novo biosensors with wide-ranging applications in biomanufacturing, diagnostics, therapeutics, and synthetic biology.