Advances in ligand-specific biosensing for structurally similar molecules

The specificity of biological systems makes it possible to develop biosensors targeting specific metabolites, toxins, and pollutants in complex medical or environmental samples without interference from structurally similar compounds. For the last two decades, great efforts have been devoted to creating proteins or nucleic acids with novel properties through synthetic biology strategies. Beyond augmenting biocatalytic activity, expanding target substrate scopes, and enhancing enzymes' enantioselectivity and stability, an increasing research area is the enhancement of molecular specificity for genetically encoded biosensors. Here, we summarize recent advances in the development of highly specific biosensor systems and their essential applications. First, we describe the rational design principles required to create libraries containing potential mutants with less promiscuity or better specificity. Next, we review the emerging high-throughput screening techniques to engineer biosensing specificity for the desired target. Finally, we examine the computer-aided evaluation and prediction methods to facilitate the construction of ligand-specific biosensors.

Exploitation of Schottky-Junction-based Sensors for Specifically Detecting ppt-Concentration Gases

Gas species and concentrations of human-exhaled breath correlate with health, wherein disease markers contain volatile organic compounds (VOCs) of concentrations in parts per billion. It is expected that a gas-sensing strategy possesses a gas specificity and detection limit in the parts per trillion (ppt) range; however, it is still a challenge. This investigation has exploited the Schottky junction of gas sensors for detecting the reactance signal of ppt VOC, aiming for a specific and rapid detection toward disease marker acetone. In this new sensing paradigm, formed by the engineered energy band between metal-semiconductor contact, the Schottky junction is accessed to specific modulation of different adsorbate dopings and the corresponding reactance signal is measured. Regarding the detection toward ppt concentration of acetone, this sensing paradigm possesses rapid (∼100 s) and room-temperature response, molecular specificity, and 34 ppt of detection limit. The proposed detection paradigm is demonstrated to show a high feasibility toward detection of disease marker acetone.

In Vitro Infant Fecal Fermentation Characteristics of Human Milk Oligosaccharides Were Controlled by Initial Microbiota Composition More than Chemical Structure

SCOPE

Human milk oligosaccharides (HMOs), multifunctional glycans naturally present in human milk, are known to contribute to the infant's microbiota and immune system development. However, the molecular specificity of HMOs on microbiota and associated fermentation is not yet fully understood, and is important for the development of infant formula optimum functionality.

METHODS AND RESULTS

In vitro fermentation is carried out on structurally different HMOs with infant fecal inocula dominated by Bifidobacterium longum, Bifidobacterium breve, and Bacteroides. The gas, metabolite (SCFA, lactate, and succinate) profiles, and microbiota responses differ between individual microbiota inocula patterns regardless of HMO structure. In terms of HMO pairs with same sugar composition but different glycosidic bonds, gas and metabolite profiles are similar with the B. longum- and B. breve-dominated inocula. However, large individual variations are observed with the Bacteroides-dominated inocula. The microbial communities at the end of fermentation are closely related to the initial microbiota composition.

CONCLUSION

The findings demonstrate that short-term in vitro fermentation outcomes largely depend on the initial gut microbiota composition more than the impact of HMO molecular specificity. These results advance the current understanding for the design of personalized infant nutritional solutions and therapies in future.

Phosphate-binding protein from Polaromonas JS666: purification, characterization, crystallization and sulfur SAD phasing

Phosphate-binding proteins (PBPs) are key proteins that belong to the bacterial ABC-type phosphate transporters. PBPs are periplasmic (or membrane-anchored) proteins that capture phosphate anions from the environment and release them to the transmembrane transporter. Recent work has suggested that PBPs have evolved for high affinity as well as high selectivity. In particular, a short, unique hydrogen bond between the phosphate anion and an aspartate residue has been shown to be critical for selectivity, yet is not strictly conserved in PBPs. Here, the PBP from Polaromonas JS666 is focused on. Interestingly, this PBP is predicted to harbor different phosphate-binding residues to currently known PBPs. Here, it is shown that the PBP from Polaromonas JS666 is capable of binding phosphate, with a maximal binding activity at pH 8. Its structure is expected to reveal its binding-cleft configuration as well as its phosphate-binding mode. Here, the expression, purification, characterization, crystallization and X-ray diffraction data collection to 1.35 Å resolution of the PBP from Polaromonas JS666 are reported.

Motif-directed redesign of enzyme specificity

Computational protein design relies on several approximations, including the use of fixed backbones and rotamers, to reduce protein design to a computationally tractable problem. However, allowing backbone and off-rotamer flexibility leads to more accurate designs and greater conformational diversity. Exhaustive sampling of this additional conformational space is challenging, and often impossible. Here, we report a computational method that utilizes a preselected library of native interactions to direct backbone flexibility to accommodate placement of these functional contacts. Using these native interaction modules, termed motifs, improves the likelihood that the interaction can be realized, provided that suitable backbone perturbations can be identified. Furthermore, it allows a directed search of the conformational space, reducing the sampling needed to find low energy conformations. We implemented the motif-based design algorithm in Rosetta, and tested the efficacy of this method by redesigning the substrate specificity of methionine aminopeptidase. In summary, native enzymes have evolved to catalyze a wide range of chemical reactions with extraordinary specificity. Computational enzyme design seeks to generate novel chemical activities by altering the target substrates of these existing enzymes. We have implemented a novel approach to redesign the specificity of an enzyme and demonstrated its effectiveness on a model system.