In-Depth Analysis of Molecular Network Based on Liquid Chromatography Coupled with Tandem Mass Spectrometry in Natural Products: Importance of Redundant Nodes Discovery.

The identification of molecules within complex mixtures is a major bottleneck in natural products (NPs) research. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has emerged as the main tool for the high-throughput characterization of NPs. The large amount of data sets by LC-MS/MS presents a challenge for data processing and interpretation, and the LC-MS/MS molecular network (MN) is one of the most prominent tools for analyzing large MS/MS data sets, widely used for rapid classification, identification, and structural speculation of unknown compounds. However, the existence of a large number of redundant nodes leads to false-positive results. To solve this problem, we proposed the in-depth analysis of MN. In this study, in-depth analysis of MN of five NPs representing the common structures of saponin, steroid, flavonoid, alkaloid, and phenolic acid revealed the presence of redundant nodes (including other adducts, isotope, and in-source fragmentation) in addition to the normal nodes, which can lead to false-positive identification results. Additionally, the reasons for different redundant nodes are discussed and experimentally verified, and it was found that the impact of redundant nodes can be mitigated by optimizing the experimental conditions and employing Feature-Based Molecular Networking. Furthermore, Ion Identity Molecular Networking can rapidly discover and screen redundant nodes, simplifying the in-depth analysis of MN and improving the network connectivity of structurally related molecules. Finally, a combination formulation of 7 NPs is used as an example to provide a guide for in-depth analysis of MN for comprehensive characterization of complex systems. This study highlights the importance of an in-depth analysis of MN for better understanding and utilization of MS/MS data in complex systems to reduce the false-positive rate of identification by screening and filtering redundant nodes.

Quantitative Single-Cell Mass Spectrometry Provides a Highly Resolved Analysis of Natural Product Biosynthesis Partitioning in Plants.

Plants produce an extraordinary array of natural products (specialized metabolites). Notably, these structurally complex molecules are not evenly distributed throughout plant tissues but are instead synthesized and stored in specific cell types. Elucidating both the biosynthesis and function of natural products would be greatly facilitated by tracking the location of these metabolites at the cell-level resolution. However, detection, identification, and quantification of metabolites in single cells, particularly from plants, have remained challenging. Here, we show that we can definitively identify and quantify the concentrations of 16 molecules from four classes of natural products in individual cells of leaf, root, and petal of the medicinal plant Catharanthus roseus using a plate-based single-cell mass spectrometry method. We show that identical natural products show substantially different patterns of cell-type localization in different tissues. Moreover, we show that natural products are often found in a wide range of concentrations across a population of cells, with some natural products at concentrations of over 100 mM per cell. This single-cell mass spectrometry method provides a highly resolved picture of plant natural product biosynthesis partitioning at a cell-specific resolution.

Mitigating In-Column Artificial Modifications in High-Temperature LC-MS for Bottom-Up Proteomics and Quality Control of Protein Biopharmaceuticals.

Elevating the column temperature is an effective strategy for improving the chromatographic separation of peptides. However, high temperatures induce artificial modifications that compromise the quality of the peptide analysis. Here, we present a novel high-temperature LC-MS method that retains the benefits of a high column temperature while significantly reducing peptide modification and degradation during reversed-phase liquid chromatography. Our approach leverages a short inline trap column maintained at a near-ambient temperature installed upstream of a separation column. The retentivity and dimensions of the trap column were optimized to shorten the residence time of peptides in the heated separation column without compromising the separation performance. This easy-to-implement approach increased peak capacity by 1.4-fold within a 110 min peptide mapping of trastuzumab and provided 10% more peptide identifications in exploratory LC-MS proteomic analyses compared with analyses conducted at 30 °C while maintaining the extent of modifications close to the background level. In the peptide mapping of biopharmaceuticals, where in-column modifications can falsely elevate the levels of some critical quality attributes, the method reduced temperature-related artifacts by 66% for N-terminal pyroGlu and 63% for oxidized Met compared to direct injection at 60 °C, thus improving reliability in quality control of protein drugs. Our findings represent a promising advancement in LC-MS methodology, providing researchers and industry professionals with a valuable tool for improving the chromatographic separation of peptides while significantly reducing the unwanted modifications.

An algorithm-driven intelligent mining and identification strategy for natural product mass spectrometry.

Efficiently mining and identification of new compounds from the extensive MS/MS datasets of plant extracts poses a significant challenge due to the structural diversity and compositional complexity inherent in natural products (NPs). Various data post-processing techniques have been developed to simplify the interpretation of MS/MS data; however, they often suffer from limited specificity and precision. Meanwhile, structure annotation following data post-processing is particularly time-consuming. In this study, we introduced an innovative strategy named MS-SMART, which integrates three intelligent algorithms: automatic mining of diagnostic ions, rapid filtration of alkaloids from untargeted MS/MS data, and structural recommendations for filtered components. The feasibility of this approach for rapidly discovering novel compounds was demonstrated using berberine-type alkaloids as an example. Firstly, diagnostic ions were automatically extracted and validated using available reference data. Subsequently, berberine-type compounds were filtered from raw MS/MS data. Finally, the structures of the target components were recommended using building blocks derived from berberines reported in various plants. A total of 103, 198, 60, 80 and 51 berberines were efficiently identified in diverse families and genera, including Stephaniae Epigaeae Radix, Coptidis Rhizoma, Phellodendri Chinensis Cortex, Phellodendri Amurensis Cortex and Corydalis Decumbentis Rhizoma, with 99, 169, 50, 64 and 40 new compounds identified, respectively. Among these, 8, 14, 8, 7 and 12 berberines were confirmed by reference compounds. This strategy provides a new research paradigm for the rapid discovery and identification of different types of new compounds in complex samples.

Multiobjective optimization of effect-directed planar chromatography as a promising tool for fast selection of polypotent natural products.

A new method for efficiently selecting polypotent natural products is proposed in this study. The method involves using effect-directed HPTLC data and multiobjective optimization algorithms to extract chromatographic signals from HPTLC bioassay images. Three different multiobjective optimization methods, namely Derringer's desirability approach, Technique for order of preference by similarity to ideal solution (TOPSIS), and Sum of ranking differences (SRD), were applied to the chromatographic signals. In combination with jackknife cross-validation, Derringer's approach and TOPSIS demonstrated high similarity in finding the best (most polypotent), next to the best, next to the worst, and worst (least polypotent) extracts, while the SRD resulted in slightly different outcomes. Furthermore, a new method for identifying the chromatographic features that characterize the most polypotent extracts was proposed. This method is based on partial least square regression (PLS) and can be used in combination with HPTLC-chemical fingerprints to predict the desirability of new extracts. The resulting PLS models demonstrated high statistical performance with determination coefficients ranging from R2 = 0.885 in the case of Derringer's desirability, to 0.986 for TOPSIS. However, the PLS modeling of SRD values was not successful.

High-Throughput Fluorometric Assay For Quantifying Polysorbate In Biopharmaceutical Products Using Micelle Activated Fluorescence Probe N-Phenyl-1-Naphthylamine.

PURPOSE: Polysorbates are among the most used surfactants in biopharmaceutical products containing proteins. Our work aims to develop a high-throughput fluorometric assay to further diversify the analytical toolbox for quantification of PSs. METHOD: The assay leverages the micelle activated fluorescence signal from N-Phenyl-1-Naphthylamine (NPN). The development and optimization of assay parameters were guided by the pre-defined analytical target profile. Furthermore, NMR was used to probe the interaction between protein, PS80 and NPN in the measurement system and understand protein interference. RESULTS: All assay parameters including excitation and emission wavelengths, standard curve, NPN concentration, and incubation time have been optimized and adapted to a microplate format, making it compatible with automated solutions that will be pursued in the near future to drive consistency and efficiency in our workflows. The specificity, accuracy, and precision of the assay have been demonstrated through a case study. Furthermore, NMR results provided additional insight into the change of the interaction dynamics between PS80 and NPN as the protein concentration increases. The results indicate minimal interaction between the protein and PS80 at lower concentration. However, when the concentration exceeds 75 mg/mL, there is a significant interaction between the protein and PS-80 micelle and monomer. CONCLUSION: A high-throughput fluorometric assay has been developed for quantification of polysorbates in biopharmaceutical samples including in-process samples, drug substance and drug product. The assay reported herein could serve as a powerful analytical tool for polysorbate quantification and control, complementing the widely used liquid chromatography with charged aerosol detection method.

Pyrrolizidine Alkaloids as Hazardous Toxins in Natural Products: Current Analytical Methods and Latest Legal Regulations.

Pyrrolizidine alkaloids (PAs) are toxic compounds that occur naturally in certain plants, however, there are many secondary pathways causing PA contamination of other plants, including medicinal herbs and plant-based food products, which pose a risk of human intoxication. It is proven that chronic exposure to PAs causes serious adverse health consequences resulting from their cytotoxicity and genotoxicity. This review briefly presents PA occurrence, structures, chemistry, and toxicity, as well as a set of analytical methods. Recently developed sensitive electrochemical and chromatographic methods for the determination of PAs in honey, teas, herbs, and spices were summarized. The main strategies for improving the analytical efficiency of PA determination are related to the use of mass spectrometric (MS) detection; therefore, this review focuses on advances in MS-based methods. Raising awareness of the potential health risks associated with the presence of PAs in food and herbal medicines requires ongoing research in this area, including the development of sensitive methods for PA determination and rigorous legal regulations of PA intake from herbal products. The maximum levels of PAs in certain products are regulated by the European Commission; however, the precise knowledge about which products contain trace but significant amounts of these alkaloids is still insufficient.

Quantification of binding capacity of natural products to target proteins by sensors integrating SERS labeling and photocrosslinked molecular probes.

Natural products-based screening of active ingredients and their interactions with target proteins is an important ways to discover new drugs. Assessing the binding capacity of target proteins, particularly when multiple components are involved, presents a significant challenge for sensors. As far as we know, there is currently no sensor that can accomplish high-throughput quantitative analysis of natural product-target protein binding capacity based on Raman spectroscopy. In this study, a novel sensor model has been developed for the quantitative analysis of binding capacity based on Surface-Enhanced Raman Spectroscopy (SERS) and Photocrosslinked Molecular Probe (PCMP) technology. This sensor, named SERS-PCMP, leverages the high throughput of molecular probe technology to investigate the active ingredients in natural products, along with the application of SERS labelling technology for target proteins. Thus it significantly improves the efficiency and accuracy of target protein identification. Based on the novel strategy, quantitative analysis of the binding capacity of 20 components from Shenqi Jiangtang Granules (SJG) to α-Glucosidase were completed. Ultimately, the binding capacity of these active ingredients was ranked based on the detected Raman Intensity. The compounds with higher binding capacity were Astragaloside IV (Intensity, 138.17), Ginsenoside Rh2 (Intensity, 87.46), Ginsenoside Rg3 (Intensity, 73.92) and Ginsenoside Rh1 (Intensity, 64.37), which all exceeded the binding capacity of the positive drug Acarbose (Intensity, 28.75). Furthermore, this strategy also performed a high detection sensitivity. The limit of detection for the enzyme using 0.1 mg of molecular probe magnetic nanoparticles (MP MNPs) was determined to be no less than 0.375 µg/mL. SERS-PCMP sensor integrating SERS labeling and photocrosslinked molecular probes which offers a fresh perspective for future drug discovery studies. Such as high-throughput drug screening and the exploration of small molecule-target protein interactions in vitro.

Expediting online liquid chromatography for real-time monitoring of product attributes to advance process analytical technology in downstream processing of biopharmaceuticals.

The application of Process Analytical Technology (PAT) principles for manufacturing of biotherapeutics proffers the prospect of ensuring consistent product quality along with increased productivity as well as substantial cost and time savings. Although this paradigm shift from a traditional, rather rigid manufacturing model to a more scientific, risk-based approach has been advocated by health authorities for almost two decades, the practical implementation of PAT in the biopharmaceutical industry is still limited by the lack of fit-for-purpose analytical methods. In this regard, most of the proposed spectroscopic techniques are sufficiently fast but exhibit deficiencies in terms of selectivity and sensitivity, while well-established offline methods, such as (ultra-)high-performance liquid chromatography, are generally considered as too slow for this task. To address these reservations, we introduce here a novel online Liquid Chromatography (LC) setup that was specifically designed to enable real-time monitoring of critical product quality attributes during time-sensitive purification operations in downstream processing. Using this online LC solution in combination with fast, purpose-built analytical methods, sampling cycle times between 1.30 and 2.35 min were achieved, without compromising on the ability to resolve and quantify the product variants of interest. The capabilities of our approach are ultimately assessed in three case studies, involving various biotherapeutic modalities, downstream processes and analytical chromatographic separation modes. Altogether, our results highlight the expansive opportunities of online LC based applications to serve as a PAT tool for biopharmaceutical manufacturing.

Development and validation of an analytical method for determination of citrinin in red rice and red yeast rice-based food supplements by ultra-high performance liquid chromatography tandem mass spectrometry.

Citrinin is a hepato-nephrotoxic mycotoxin produced by fungal species. The Monascus purpureus fungus plays a crucial role in the fermentation of red rice to produce red yeast rice-based food supplements, which represent the primary source of human exposure to citrinin. In this study, a simple and sensitive analytical method was successfully developed and validated for the citrinin determination in these products. The extraction process involved a QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe) step and citrinin determination by ultra high-performance liquid chromatography coupled with tandem mass spectrometry (UHPLC-MS/MS). The proposed method provided satisfactory linearity, percentage of recovery from 82 to 104% with relative standard deviations (RSD) lower than 14%, and limits of detection and quantification of 0.07 µg/Kg and 0.24 µg/kg, respectively. Among the 14 samples analyzed, citrinin was found in two red rice samples (0.24 and 0.46 µg/kg) and in six food supplements (from 0.44 to 87 µg/kg).

The influence of biological products and growth regulators on the yield and quality indicators of pea seeds of various varieties.

Peas are an important agricultural crop of great importance in human and animal nutrition. Peas, being a legume crop, help replenish nitrogen reserves in the soil. In field studies of the Federal State Budgetary Scientific Institution of the Federal Scientific Center of Legumes and Goat Crops (Oryol region), the influence of various growth regulators and biological products on the yield and quality indicators of pea seeds of the Nord and Multik varieties was studied. Pea plants are grown on dark gray forest, medium loamy soil of average cultivation. Before sowing, pea seeds were treated with solutions of Kornevin, Albit and Epin-extra by soaking for 5 hours. Solutions of the drugs were used at a concentration of 10-6 M, then dried and treated with Rizotorfin before sowing. Growth rates during the growing season and the yield of pea plants were determined. The content of protein, starch and amylose in starch was determined in the seeds. Research results have shown that the yield of pea plants depends on weather conditions. Under favorable weather conditions, the highest yield was obtained from the pea variety Nord (42.2 c/ha) in the variant with seed treatment with Kornevin, and in the Multik variety (43.0 c/ha) when treated with Rizotorfin. In arid conditions, the highest yield of peas of the Nord variety was obtained using the preparations Epin-extra and Kornevin. The highest yield of peas of the Multik variety was obtained using the preparations Rizotorfin, Kornevin and Epin-Extra. The research results, confirmed by statistical evaluation, showed that bioregulators and growth regulators help stimulate the amount of nitrogen supplied to plants, as well as the synthetic processes of protein synthesis. This contributed to improving the quality of seeds and green mass.

NP3 MS Workflow: An Open-Source Software System to Empower Natural Product-Based Drug Discovery Using Untargeted Metabolomics.

Natural products (or specialized metabolites) are historically the main source of new drugs. However, the current drug discovery pipelines require miniaturization and speeds that are incompatible with traditional natural product research methods, especially in the early stages of the research. This article introduces the NP3 MS Workflow, a robust open-source software system for liquid chromatography-tandem mass spectrometry (LC-MS/MS) untargeted metabolomic data processing and analysis, designed to rank bioactive natural products directly from complex mixtures of compounds, such as bioactive biota samples. NP3 MS Workflow allows minimal user intervention as well as customization of each step of LC-MS/MS data processing, with diagnostic statistics to allow interpretation and optimization of LC-MS/MS data processing by the user. NP3 MS Workflow adds improved computing of the MS2 spectra in an LC-MS/MS data set and provides tools for automatic [M + H]+ ion deconvolution using fragmentation rules; chemical structural annotation against MS2 databases; and relative quantification of the precursor ions for bioactivity correlation scoring. The software will be presented with case studies and comparisons with equivalent tools currently available. NP3 MS Workflow shows a robust and useful approach to select bioactive natural products from complex mixtures, improving the set of tools available for untargeted metabolomics. It can be easily integrated into natural product-based drug-discovery pipelines and to other fields of research at the interface of chemistry and biology.

Development of an analytical platform for the affinity screening of natural extracts by SEC-MS towards PPARα and PPARγ receptors.

BACKGROUND: Peroxisome proliferator-activated receptors (PPARs) belong to the superfamily of nuclear receptors and represent the targets for the therapeutical treatment of type 2 diabetes, dyslipidemia and hyperglycemia associated with metabolic syndrome. Some medicinal plants have been traditionally used to treat this kind of metabolic diseases. Today only few drugs targeting PPARs have been approved and for this reason, the rapid identification of novel ligands and/or chemical scaffolds starting from natural extracts would benefit of a selective affinity ligand fishing assay. RESULTS: In this paper we describe the development of a new ligand fishing assay based on size exclusion chromatography (SEC) coupled to LC-MS for the analysis of complex samples such as botanical extracts. The known PPARα and PPARγ ligands, WY-14643 and rosiglitazone respectively, were used for system development and evaluation. The system has found application on an Allium lusitanicum methanolic extract, containing saponins, a class of chemical compounds which have attracted interest as PPARs ligands because of their hypolipidemic and insulin-like properties. SIGNIFICANCE: A new SEC-AS-MS method has been developed for the affinity screening of PPARα and PPARγ ligands. The system proved to be highly specific and will be used to improve the throughput for the identification of new selective metabolites from natural souces targeting PPARα and PPARγ.

Chemometric-based drug discovery approaches from natural origins using hyphenated chromatographic techniques.

INTRODUCTION: Isolation and characterization of bioactive components from complex matrices of marine or terrestrial biological origins are the most challenging issues for natural product chemists. Biochemometric is a new potential scope in natural product analytical science, and it is a methodology to find the compound's correlation to their bioactivity with the help of hyphenated chromatographic techniques and chemometric tools. OBJECTIVES: The present review aims to evaluate the application of chemometric tools coupled to chromatographic techniques for drug discovery from natural resources. METHODS: The searching keywords "biochemometric," "chemometric," "chromatography," "natural products bioassay," and "bioassay" were selected to search the published articles between 2010-2023 using different search engines including "Pubmed", "Web of Science," "ScienceDirect," and "Google scholar." RESULTS: An initial stage in natural product analysis is applying the chromatographic hyphenated techniques in conjunction with biochemometric approaches. Among the applied chromatographic techniques, liquid chromatography (LC) techniques, have taken up more than half (53%) and also, mass spectroscopy (MS)-based chromatographic techniques such as LC-MS are the most widely used techniques applied in combination with chemometric methods for natural products bioassay. Considering the complexity of dataset achieved from chromatographic hyphenated techniques, chemometric tools have been increasingly employed for phytochemical studies in the context of determining botanicals geographical origin, quality control, and detection of bioactive compounds. CONCLUSION: Biochemometric application is expected to be further improved with advancing in data acquisition methods, new efficient preprocessing, model validation and variable selection methods which would guarantee that the applied model to have good prediction ability in compound relation to its bioactivity.

Ambient mass spectrometry imaging of food natural products by angled direct analysis in real time high-resolution mass spectrometry.

Direct surface analysis in ambient conditions provides information on the position and chemical composition of an object at the time of investigation. An angled sampling probe is developed in this work for direct analysis in real time (DART) ionization high-resolution mass spectrometry. The DART ion source and the interface were modified for improved surface resolution, increased ion transfer efficiency, as well as enabling two-dimensional surface scanning. The angled probe DART-MS system was used for investigating a variety of food samples including fruit peels, ginseng root, plant leaves and sections of radish. Abundant signals and distinct chemical profiles are obtained in seconds, and spatial distribution of different molecules across the sample surfaces can be observed. In addition, the developed system can quickly identify the chemical changes when the surfaces were treated. The method is capable of directly evaluating food sample surfaces with different shapes, hardness, and conditions, without any sample pretreatments.

Size exclusion chromatography of biopharmaceutical products: From current practices for proteins to emerging trends for viral vectors, nucleic acids and lipid nanoparticles.

The 21st century has been particularly productive for the biopharmaceutical industry, with the introduction of several classes of innovative therapeutics, such as monoclonal antibodies and related compounds, gene therapy products, and RNA-based modalities. All these new molecules are susceptible to aggregation and fragmentation, which necessitates a size variant analysis for their comprehensive characterization. Size exclusion chromatography (SEC) is one of the reference techniques that can be applied. The analytical techniques for mAbs are now well established and some of them are now emerging for the newer modalities. In this context, the objective of this review article is: i) to provide a short historical background on SEC, ii) to suggest some clear guidelines on the selection of packing material and mobile phase for successful method development in modern SEC; and iii) to highlight recent advances in SEC, such as the use of narrow-bore and micro-bore columns, ultra-wide pore columns, and low-adsorption column hardware. Some important innovations, such as recycling SEC, the coupling of SEC with mass spectrometry, and the use of alternative detectors such as charge detection mass spectrometry and mass photometry are also described. In addition, this review discusses the use of SEC in multidimensional setups and shows some of the most recent advances at the preparative scale. In the third part of the article, the possibility of SEC for the characterization of new modalities is also reviewed. The final objective of this review is to provide a clear summary of opportunities and limitations of SEC for the analysis of different biopharmaceutical products.

Quantification of Biopharmaceutically Relevant Nonionic Surfactant Excipients Using Benchtop qNMR.

Nonionic surfactant excipients (NISEs) are commonly added to biologics formulations to mitigate the effects of stress incurred by the active biotherapeutic during manufacturing, transport, and storage. During manufacturing, NISEs are added by dilution of a stock solution directly into a protein formulation, and their accurate addition is critical in maintaining the quality and integrity of the drug product and thus ensuring patient safety. This is especially true for the common NISEs, polysorbates 20 and 80 (PS20 and PS80, respectively) and poloxamer 188 (P188). With the increasing diversity of biologic modalities within modern pharmaceutical pipelines, there is thus a critical need to develop and deploy convenient and user-accessible analytical techniques that can rapidly and reliably quantify these NISEs under biopharmaceutically relevant conditions. We thus pursued 60 MHz benchtop quantitative NMR (qNMR) as a nondestructive and user-friendly analytical technique for the quantification of PS20, PS80, and P188 under such conditions. We demonstrated the ability of benchtop qNMR (1) to quantify simulated PS20, PS80, and P188 stock solutions representative of those used during the drug substance (DS) formulation step in biomanufacturing and (2) to quantify these NISEs at and below their target concentrations (≤0.025% w/v) directly in biologics formulations containing histidine, sucrose, and one of three biotherapeutic modalities (monoclonal antibody, antibody-drug conjugate, and Fc-fusion protein). Our results demonstrate that benchtop qNMR offers a fit-for-purpose, reliable, user-friendly, and green analytical route by which NISE of interest to the biopharmaceutical industry may be readily and reliably quantified. We conclude that benchtop qNMR has the potential to be applied to other excipient formulation components in the presence of various biological modalities as well as the potential for routine integration within analytical and QC laboratories across pharmaceutical development and manufacturing sites.

Novel EDTA mediated ethanol protein precipitation method and the application for polysorbate quantification in high protein concentration biopharmaceuticals.

Non-ionic surfactants such as Polysorbate 20/ 80 (PS20/ PS80), are commonly used in protein drug formulations to increase protein stability by protecting against interfacial stress and surface absorption. Polysorbate is susceptible to degradation which can impact product stability, leading to the formation of sub-visible and/or visible particles in the drug product during its shelf-life, affecting patient safety and efficacy. Therefore, it is important to monitor polysorbate concentration in drug product formulations of biotherapeutic drugs. The common method for measuring polysorbate concentration in drug product formulations uses mixed mode ion exchange reversed phase HPLC (MAX) coupled to evaporative light scattering detection (ELSD). However, high protein concentration can adversely impact method performance due to high sample viscosity, gel formation, column clogging, interfering peaks and loss of accuracy. To overcome this, a new method was developed based on EDTA mediated ethanol protein precipitation (EDTA/EtOH). This method was successfully implemented for the analysis of polysorbate in antibody formulations with wide range of protein concentration (10-250 mg/mL).

Searching for the optimal microbial factory: high-throughput biosensors and analytical techniques for screening small molecules.

High-throughput screening technologies have been lacking in comparison to the plethora of high-throughput genetic diversification techniques developed in biotechnology. This review explores the challenges and advancements in high-throughput screening for high-value natural products, focusing on the critical need to expand ligand targets for biosensors and increase the throughput of analytical techniques in screening microbial cell libraries for optimal strain performance. The engineering techniques to broaden the scope of ligands for biosensors, such as transcription factors, G protein-coupled receptors and riboswitches are discussed. On the other hand, integration of microfluidics with traditional analytical methods is explored, covering fluorescence-activated cell sorting, Raman-activated cell sorting and mass spectrometry, emphasising recent developments in maximising throughput.

Application of eco-friendly natural deep eutectic solvents (NADES) in HPLC for separation of complex natural products: Current limitations and future directions.

Natural deep eutectic solvents (NADES) have been used in chromatography as extraction media and HPLC mobile phase additives, but only once have they been used as HPLC major mobile phase component. This review illustrates current knowledge and major limitations on use of NADES in HPLC mobile phase as well as to propose possible NADES may be ready for use as HPLC mobile phases and the detectors they can be used with. High viscosity is one of the major roadblocks encountered when using NADES as a mobile phase component in HPLC regardless of detectors employed. A comprehensive review of published literature was conducted to identify articles that focused on using NADES as extraction solvents for natural products, particularly polyphenols or reported NADES viscosities to establish a database of NADES which could be used as HPLC mobile phases under various conditions. Other identified challenges that limit NADES application in HPLC mobile phase include low volatility, NADES wavelength cutoff (UV and Fluorescent detectors) and impurities. Methods for overcoming these limitations are discussed so that NADES may be more integrated into HPLC systems in the future.