A GPCR-based yeast biosensor for biomedical, biotechnological, and point-of-use cannabinoid determination

The decriminalization of cannabis and the growing interest in cannabinoids as therapeutics require efficient methods to discover novel compounds and monitor cannabinoid levels in human samples and products. However, current methods are limited by the structural diversity of the active compounds. Here, we construct a G-protein coupled receptor-based yeast whole-cell biosensor, optimize it to achieve high sensitivity and dynamic range, and prove its effectiveness in three real-life applications. First, we screen a library of compounds to discover two novel agonists and four antagonists and demonstrate that our biosensor can democratize GPCR drug discovery by enabling low-cost high-throughput analysis using open-source automation. Subsequently, we bioprospect 54 plants to discover a novel phytocannabinoid, dugesialactone. Finally, we develop a robust portable device, analyze body-fluid samples, and confidently detect illicit synthetic drugs like “Spice”/“K2”. Taking advantage of the extensive sensing repertoire of GPCRs, this technology can be extended to detect numerous other compounds.

The Origins and the Current Applications of Microfluidics-Based Magnetic Cell Separation Technologies

The magnetic separation of cells based on certain traits has a wide range of applications in microbiology, immunology, oncology, and hematology. Compared to bulk separation, performing magnetophoresis at micro scale presents advantages such as precise control of the environment, larger magnetic gradients in miniaturized dimensions, operational simplicity, system portability, high-throughput analysis, and lower costs. Since the first integration of magnetophoresis and microfluidics, many different approaches have been proposed to magnetically separate cells from suspensions at the micro scale. This review paper aims to provide an overview of the origins of microfluidic devices for magnetic cell separation and the recent technologies and applications grouped by the targeted cell types. For each application, exemplary experimental methods and results are discussed.

High-throughput analysis of ANRIL circRNA isoforms in human pancreatic islets

The antisense non-coding RNA in the INK locus (ANRIL) is a hotspot for genetic variants associated with cardiometabolic disease. We recently found increased ANRIL abundance in human pancreatic islets from donors with certain Type II Diabetes (T2D) risk-SNPs, including a T2D risk-SNP located within ANRIL exon 2 associated with beta cell proliferation. Recent studies have found that expression of circular species of ANRIL is linked to the regulation of cardiovascular phenotypes. Less is known about how the abundance of circular ANRIL may influence T2D phenotypes. Herein, we sequence circular RNA in pancreatic islets to characterize circular isoforms of ANRIL. We identify highly expressed circular ANRIL isoforms whose expression is correlated across dozens of individuals and characterize ANRIL splice sites that are commonly involved in back-splicing. We find that samples with the T2D risk allele in ANRIL exon 2 had higher ratios of circular to linear ANRIL compared to protective-allele carriers, and that higher circular:linear ANRIL was associated with decreased beta cell proliferation. Our study points to a combined involvement of both linear and circular ANRIL species in T2D phenotypes and opens the door for future studies of the molecular mechanisms by which ANRIL impacts cellular function in pancreatic islets.

An ultra-sensitive and easy-to-use multiplexed single-cell proteomic analysis

Proteins analysis from an average cell population often overlooks the cellular heterogeneity of expressed effector molecules, and knowledge about the regulations of key biological processes may remain obscure. Therefore, the necessity of single-cell proteomics (SCP) technologies arises. Without microfluidic chip, expensive ultrasonic equipment, or reformed liquid chromatogram (LC) system, we established an Ultra-sensitive and Easy-to-use multiplexed Single-Cell Proteomic workflow (UE-SCP). Specifically, the flexible sorting system ensured outstanding cell activity, high accuracy, remarkable efficiency, and robustness during single-cell isolation. Multiplex isobaric labeling realized the high-throughput analysis in trapped ion mobility spectrometry coupled with quadrupole time-of-flight mass spectrometry (timsTOF MS). Using this pipeline, we achieved single-cell protein quantities to a depth of over 2,000 protein groups in two human cell lines, Hela and HEK-293T. A small batch experiment can identify and quantify more than 3200 protein groups in 32 single cells, while a large batch experiment can identify and quantify about 4000 protein groups in 96 single cells. All the 128 single cells from different cell lines could been unsupervised clustered based on their proteomes. After the integration of data quality control, data cleaning, and data analysis, we are confident that our UE-SCP platform will be easy-to-marketing popularization and will promote biological applications of single-cell proteomics.

High-Throughput Analysis of Protein with Tandem Fluorescent Protein Timers

Tandem fluorescent protein timers (tFTs) are versatile reporters of protein dynamics. A tFT consists of two fluorescent proteins with different maturation kinetics and provides a ratiometric readout of protein age, which can be exploited to follow intracellular trafficking, inheritance and turnover of tFT-tagged proteins. Here, we detail a protocol for high-throughput analysis of protein turnover with tFTs in yeast using fluorescence measurements of ordered colony arrays. We describe guidelines on optimization of experimental design with regard to the layout of colony arrays, growth conditions, and instrument choice. Combined with semi-automated genetic crossing using synthetic genetic array (SGA) methodology and high-throughput protein tagging with SWAp-Tag (SWAT) libraries, this approach can be used to compare protein turnover across the proteome and to identify regulators of protein turnover genome-wide.

fingeRNAt - a novel tool for high-throughput analysis of nucleic acid-ligand interactions

Computational methods play a pivotal role in drug discovery and are widely applied in virtual screening, structure optimization, and compound activity profiling. Over the last decades, almost all the attention in medicinal chemistry has been directed to protein-ligand binding, and computational tools have been created with this target in mind. With novel discoveries of functional RNAs and their possible applications, RNAs have gained considerable attention as potential drug targets. However, the availability of bioinformatics tools for nucleic acids is limited. Here, we introduce fingeRNAt - a software tool for detecting non-covalent interactions formed in complexes of nucleic acids with ligands. The program detects nine types of interactions: (i) hydrogen and (ii) halogen bonds, (iii) cation-anion, (iv) pi-cation, (v) pi-anion, (vi) pi-stacking, (vii) inorganic ion-mediated, (viii) water-mediated, and (ix) lipophilic interactions. However, the scope of detected interactions can be easily expanded using a simple plugin system. In addition, detected interactions can be visualized using the associated PyMOL plugin, which facilitates the analysis of medium-throughput molecular complexes. Interactions are also encoded and stored as a bioinformatics-friendly Structural Interaction Fingerprint (SIFt) - a binary string where the respective bit in the fingerprint is set to 1 if a particular interaction is present and to 0 otherwise. This output format, in turn, enables high-throughput analysis of interaction data using data analysis techniques. We present applications of fingeRNAt-generated interaction fingerprints for visual and computational analysis of RNA-ligand complexes, including analysis of interactions formed in experimentally determined RNA-small molecule ligand complexes deposited in the Protein Data Bank. We propose interaction-based similarity based on fingerprints as an alternative measure to RMSD to recapitulate complexes with similar interactions but different folding. We present an application of molecular fingerprints for the clustering of molecular complexes. This approach can be used to group ligands that form similar binding networks and thus have similar biological properties.

Identifying C. elegans Lifespan Mutants by Screening for Early-Onset Protein Aggregation

Genetic screens have been widely used to identify genetic pathways that control specific biological functions. In C. elegans, forward genetic screens rely on the isolation of reproductively active mutants that can self-propagate clonal populations. Since aged individuals are unable to generate clonal populations, screens that target post-reproductive phenotypes, such as longevity, are challenging. In this work, we developed an approach that combines microfluidic technologies and image processing to perform a high-throughput, automated screen for mutants with shortened lifespan using protein aggregation as a marker for aging. We take advantage of microfluidics for maintaining a reproductively-active adult mutagenized population and for performing serial high-throughput analysis and sorting of animals with increased protein aggregation, using fluorescently labeled PAB-1 as a readout. We identified five mutants with increased aggregation levels, of which two exhibited a reduced lifespan. We demonstrate that lifespan mutants can be identified by screening for accelerated protein aggregation through quantitative analysis of fluorescently-labeled aggregates in populations that do not require conditional sterilization or manual separation of parental and progeny populations. We further analyzed the morphology of protein aggregates and reveal that patterns of aggregation in naturally-aging animals differ from mutants with increased aggregation, suggesting aggregate growth is time-dependent. This screening approach can be customized to other non-developmental phenotypes that appear during adulthood, as well as to other aging markers to identify additional longevity-regulating genetic pathways.

High-Throughput Analysis of Amino Acids for Protein Quantification in Plant and Animal-Derived Samples Using High Resolution Mass Spectrometry

Current methods for measuring the abundance of proteogenic amino acids in plants require derivatisation, extended run times, very sensitive pH adjustments of the protein hydrolysates, and the use of buffers in the chromatographic phases. Here, we describe a fast liquid chromatography–mass spectrometry (LC–MS) method for the determination of amino acids that requires only three steps: hydrolysis, neutralisation, and sample dilution with a borate buffer solution for pH and retention time stability. The method shows excellent repeatability (repeated consecutive injections) and reproducibility (repeated hydrolysis) in the amino acid content, peak area, and retention time for all the standard amino acids. The chromatographic run time is 20 min with a reproducibility and repeatability of <1% for the retention time and <11% for the peak area of the BSA and quality control (QC) lentil samples. The reproducibility of the total protein levels in the hydrolysis batches 1–4 was <12% for the BSA and the lentil samples. The level of detection on column was below 0.1 µM for most amino acids (mean 0.017 µM).

Use of Microfluidic Capillary Electrophoresis for the Determination of Multi-Component Protein Adsorption Isotherms: Application to High-Throughput Analysis for Hydrophobic Interaction Chromatography

Chromatography is a widely used separation process for purification of biopharmaceuticals that is able to obtain high purities and concentrations. The phenomena that occur during separation, mass transfer and adsorption are quite complex. To better understand these phenomena and their mechanisms, multi-component adsorption isotherms must be investigated. High-throughput methodologies are a very powerful tool to determine adsorption isotherms and they waste very small amounts of sample and chemicals, but the quantification of component concentrations is a real bottleneck in multi-component isotherm determination. The behavior of bovine serum albumin, Corynebacterium diphtheriae CRM197 protein and lysozyme, selected as model proteins in binary mixtures with hydrophobic resin, is investigated here. In this work we propose a new method for determining multi-component adsorption isotherms using high-throughput experiments with filter plates, by exploiting microfluidic capillary electrophoresis. The precision and accuracy of the microfluidic capillary electrophoresis platform were evaluated in order to assess the procedure; they were both found to be high and the procedure is thus reliable in determining adsorption isotherms for binary mixtures. Multi-component adsorption isotherms were determined with a totally high-throughput procedure that turned out to be a very fast and powerful tool. The same procedure can be applied to every kind of high-throughput screening.