Microtubule (MT) dynamics is tightly regulated by microtubule-associated proteins (MAPs) and various post-translational modifications (PTMs) of tubulin. Here, we introduce OligoMT and OligoTIP as genetically encoded oligomeric MT binders designed for real-time visualization and manipulation of MT behaviors within living cells. OligoMT acts as a reliable marker to label the MT cytoskeleton, while OligoTIP allows for live monitoring of the growing MT plus-ends. These engineered MT binders have been successfully utilized to label the MT network, monitor cell division, track MT plus-ends, and assess the effect of tubulin acetylation on the MT stability at the single-cell level. Moreover, OligoMT and OligoTIP can be repurposed as biosensors for quantitative assessment of drug actions and for reporting enzymatic activity. Overall, these engineered MT binders hold promise for advancing the mechanistic dissection of MT biology and have translational applications in cell-based high-throughput drug discovery efforts.

The global increase in antibiotic resistances demands for additional efforts to identify novel antimicrobials such as bacteriocins. These antimicrobial peptides of bacterial origin are already used widely in food preservation and promising alternatives for antibiotics in animal feed and some clinical setting. Identification of novel antimicrobials is facilitated by appropriate high throughput screening (HTS) methods. Previously, we have described a rapid, simple and cost-efficient assay based on live biosensor bacteria for detection of antimicrobial compounds that act on membrane integrity using the ratiometric pH-dependent fluorescent protein pHluorin2 (pHin2). Here, we use these biosensors to develop an integrated pipeline for high-throughput identification of bacteriocin producers and their biosynthetic gene clusters. We extend the existing portfolio of biosensors by generating pHin2 expressing strains of Escherichia coli, Bacillus cereus, Staphylococcus epidermidis, and methicillin-resistant Staphylococcus aureus. These strains were characterized, and control experiments were performed to assess heterogeneity of these biosensors in response to known bacteriocins and develop a robust HTS system. To allow detection of compounds that inhibit target bacteria by inhibiting growth without disturbing membrane integrity, the HTS system was extended with a growth-dependent readout. Using this HTS system, we screened supernatants of a total of 395 strains of a collection of lactic acid bacteria. After two rounds of screening 19 strains of the collection were identified that produced antimicrobial activity against Listeria innocua and Listeria monocytogenes. Genomes of confirmed hits were sequenced and annotated. In silico analysis revealed that the identified strains encode between one and six biosynthetic gene clusters (BGCs) for bacteriocins. Our results suggest that pHin2 biosensors provides a flexible, cheap, fast, robust and easy to handle HTS system for identification of potential bacteriocins and their BGCs in large strain collections.

Bacteroides spp. are prominent gut commensals that are believed to modulate the intestinal environment, in part, by producing outer membrane vesicles (OMVs). Bacteroides OMVs have been ascribed many functions in vitro, but the genetic underpinnings behind OMV biogenesis and regulation are unclear. Understanding the mechanism of OMV biogenesis is required to determine the importance of Bacteroides OMVs in vivo. Here, we describe our methodology for screening Bacteroides thetaiotaomicron VPI-5482 to identify genes required for OMV biogenesis and regulation in a high-throughput format. This protocol is easily adaptable and can potentially be employed to further our knowledge of OMV biogenesis in other bacteria.

The development of an efficient adsorbent for the simultaneous capture of large amounts of benzene, toluene, ethylbenzene, and xylene isomers (BTEX) is an important and challenging issue. Here, through a stepwise screening of 10,142 metal-organic framework (MOF) structures from the computation-ready, experimental (CoRE) MOF database, 65 MOFs are proposed as promising adsorbent candidates for BTEX capture by considering the structures with accessible pore sizes for BTEX adsorption, sufficient hydrophobicity, high benzene selectivity (>0.2), and large total BTEX uptake (>3 mmol/g). Among the top-performing MOFs in terms of the BTEXmatrix (total BTEX uptake × benzene selectivity), EGUELUY01 was synthesized, and it exhibited large uptakes (≈5 mmol/g) for all BTEX components at concentrations of 1200-1500 ppm, which are superior to the BTEX uptake of the benchmark adsorbent, activated carbon. Moreover, some structure-property relationships required for BTEX adsorbents are provided through the obtained large-scale simulation data and machine learning analysis. The determined relationships will be useful for the future development of efficient BTEX adsorbents.

Canavan disease is caused by mutations in the ASPA gene, leading to diminished catalytic activity of aspartoacylase in the brain. Clinical missense mutations are found throughout the enzyme structure, with many of these mutated enzymes having not only decreased activity but also compromised stability. High-throughput screening of a small molecule library has identified several compounds that significantly increase the thermal stability of the E285A mutant enzyme, the most predominant clinical mutation in Canavan disease, while having a negligible effect on the native enzyme. Based on the initial successes, some structural analogs of these initial hits were selected for further examination. Glutathione, NAAG and patulin were each confirmed to be competitive inhibitors, indicating the binding of these compounds at the dimer interface or near the active site of the E285A enzyme. The experimental results were theoretically examined with the help of the docking analysis method. The structure activity-guided optimization of these compounds can potentially lead to potential pharmacological chaperones that could alleviate the detrimental effect of ASPA mutations in Canavan patients.

BACKGROUND: Base editing is a powerful tool for artificial evolution to create allelic diversity and improve agronomic traits. However, the great evolutionary potential for every sgRNA target has been overlooked. And there is currently no high-throughput method for generating and characterizing as many changes in a single target as possible based on large mutant pools to permit rapid gene directed evolution in plants.
RESULTS: In this study, we establish an efficient germline-specific evolution system to screen beneficial alleles in Arabidopsis which could be applied for crop improvement. This system is based on a strong egg cell-specific cytosine base editor and the large seed production of Arabidopsis, which enables each T1 plant with unedited wild type alleles to produce thousands of independent T2 mutant lines. It has the ability of creating a wide range of mutant lines, including those containing atypical base substitutions, and as well providing a space- and labor-saving way to store and screen the resulting mutant libraries. Using this system, we efficiently generate herbicide-resistant EPSPS, ALS, and HPPD variants that could be used in crop breeding.
CONCLUSIONS: Here, we demonstrate the significant potential of base editing-mediated artificial evolution for each sgRNA target and devised an efficient system for conducting deep evolution to harness this potential.

High-throughput assays that efficiently link genotype and phenotype with high fidelity are key to successful enzyme engineering campaigns. Among these assays, the tyramide/peroxidase proximity labeling method converts the product of an enzymatic reaction of a surface expressed enzyme to a highly reactive fluorescent radical, which labels the cell surface. In this context, maintaining the proximity of the readout reagents to the cell surface is crucial to prevent crosstalk and ensure that short-lived radical species react before diffusing away. Here, we investigated improvements in tyramide/peroxidase proximity labeling for enzyme screening. We modified chitosan (Cs) chains with horseradish peroxidase (HRP) and evaluated the effects of these conjugates on the efficiency of proximity labeling reactions on yeast cells displaying d-amino acid oxidase. By tethering HRP to chitosan through different chemical approaches, we localized the auxiliary enzyme close to the cell surface and enhanced the sensitivity of tyramide-peroxidase labeling reactions. We found that immobilizing HRP onto chitosan through a 5 kDa PEG linker improved labeling sensitivity by over 3.5-fold for substrates processed with a low turnover rate (e.g., d-lysine), while the sensitivity of the labeling for high activity substrates (e.g., d-alanine) was enhanced by over 0.6-fold. Such improvements in labeling efficiency broaden the range of enzymes and conditions that can be studied and screened by tyramide/peroxidase proximity labeling.

The characterization of interactions between autophagy modifiers (Atg8-family proteins) and their natural ligands (peptides and proteins) or small molecules is important for a detailed understanding of selective autophagy mechanisms and for the design of potential Atg8 inhibitors that affect the autophagy processes in cells. The fluorescence polarization (FP) assay is a rapid, cost-effective, and robust method that provides affinity and selectivity information for small molecules and peptide ligands targeting human Atg8 proteins.This chapter introduces the basic principles of FP assays. In addition, a case study on peptide interaction with human Atg8 proteins (LC3/GABARAPs) is described. Finally, data analysis and quality control of FP assays are discussed for the proper calculation of Ki values for the measured compounds.

In recent years, genetic circuit-based regulation of metabolic flux in microbial cell factories has received significant attention. In this review, we describe a pipeline for the design and construction of genetic circuits for metabolic flux optimization. In particular, we summarize the recent advances in computationally assisted prediction of critical metabolic nodes and genetic circuit design automation. Further, we introduce strategies for constructing high-performance genetic circuits. We also summarize the latest applications of genetic circuits in the dynamic regulation of metabolism and high-throughput screening. Finally, we discuss the challenges and prospects associated with the design and construction of sophisticated genetic circuits. Through this review, we aim to provide a theoretical basis for designing and constructing high-performance genetic circuits to optimize metabolic flux.

Nanoparticle-mediated mRNA delivery has emerged as a promising therapeutic modality, but its growth is still limited by the discovery and optimization of effective and well-tolerated delivery strategies. Lipid nanoparticles containing charged or ionizable lipids are an emerging standard for in vivo mRNA delivery, so creating facile, tunable strategies to synthesize these key lipid-like molecules is essential to advance the field. Here, we generate a library of N-substituted glycine oligomers, peptoids, and undertake a multistage down-selection process to identify lead candidate peptoids as the ionizable component in our Nutshell nanoparticle platform. First, we identify a promising peptoid structural motif by clustering a library of >200 molecules based on predicted physical properties and evaluate members of each cluster for reporter gene expression in vivo. Then, the lead peptoid motif is optimized using design of experiments methodology to explore variations on the charged and lipophilic portions of the peptoid, facilitating the discovery of trends between structural elements and nanoparticle properties. We further demonstrate that peptoid-based Nutshells leads to expression of therapeutically relevant levels of an anti-respiratory syncytial virus antibody in mice with minimal tolerability concerns or induced immune responses compared to benchmark ionizable lipid, DLin-MC3-DMA. Through this work, we present peptoid-based nanoparticles as a tunable delivery platform that can be optimized toward a range of therapeutic programs.