High-throughput Strategy Research Articles

Real-time screening of hepatotoxins in natural medicine by peroxynitrite responsive lanthanide-based NIR-II luminescent probes

• An NIR-II nanoprobe was designed to monitor the ONOO ¯ in the liver of living mice. • The paracetamol-induced liver injury can be monitored in situ by the nanoprobe. • The probe enabled early diagnosis of liver injury prior to physiological disorder. • The probe successfully screened the hepatotoxic components from natural medicines. Herbal medicines and dietary supplements are widely used worldwide. However, reports have revealed that a large number of herbal medicines are implicated in the hepatic damage, which is referred to as Herbal medicines-induced liver injury (HILI). Traditional diagnostic methods for HILI include histological and serological assessments, which fail to offer real-time and unambiguous visualization of hepatotoxicity in vivo . Herein, we constructed a second near-infrared (NIR-II) luminescent nanoprobes to achieve accurate, high-efficiency, and non-invasive detection of HILI by the assembly of lanthanide-based NIR-II luminescence nanoparticles with a chromophore with absorption band in the NIR-II region. Specifically, the NIR-II luminescence of the lanthanide nanoparticles can be effectively quenched by the chromophores on the surface of nanoparticles via an absorption competition-induced quenching effect, and subsequently recovered by the pathophysiological biomarker peroxynitrite (ONOO − ) generated in early HILI. It is demonstrated that the nanoprobes are capable for the screening of liver toxins in a noninvasive pattern, which is more convenient than the conventional diagnostic approaches. Finally, our luminescence detection approach offers an immediate testing technique for the identification of hepatotoxic components of herbal medicine such as colchicine, monocrotaline and stibene glucoside, providing a high-throughput screening strategy for herbal medicine-induced hepatotoxicity.

A high-throughput strategy for rapid synthesis and characterization of Ni-based superalloys

A high-throughput strategy for rapid synthesis and characterization of Ni-based superalloys

Real-time and automated monitoring of antischistosomal drug activity profiles for screening of compound libraries

SummarySchistosomiasis is a neglected tropical disease that affects over 200 million people annually. As the antischistosomal drug pipeline is currently empty, repurposing of compound libraries has become a source for accelerating drug development, which demands the implementation of high-throughput and efficient screening strategies. Here, we present a parallelized impedance-based platform for continuous and automated viability evaluation of Schistosoma mansoni schistosomula in 128 microwells during 72 h to identify antischistosomal hits in vitro. By initially screening 57 repurposed compounds against larvae, five drugs are identified, which reduce parasite viability by more than 70%. The activity profiles of the selected drugs are then investigated via real-time dose-response monitoring, and four compounds reveal high potency and rapid action, which renders them suitable candidates for follow-up tests against adult parasites. The study shows that our device is a reliable tool for real-time drug screening analysis of libraries to identify new promising therapeutics against schistosomiasis.

Quantification of Microbial Robustness in Yeast.

Stable cell performance in a fluctuating environment is essential for sustainable bioproduction and synthetic cell functionality; however, microbial robustness is rarely quantified. Here, we describe a high-throughput strategy for quantifying robustness of multiple cellular functions and strains in a perturbation space. We evaluated quantification theory on experimental data and concluded that the mean-normalized Fano factor allowed accurate, reliable, and standardized quantification. Our methodology applied to perturbations related to lignocellulosic bioethanol production showed that the industrial bioethanol producing strain Saccharomyces cerevisiae Ethanol Red exhibited both higher and more robust growth rates than the laboratory strain CEN.PK and industrial strain PE-2, while a more robust product yield traded off for lower mean levels. The methodology validated that robustness is function-specific and characterized by positive and negative function-specific trade-offs. Systematic quantification of robustness to end-use perturbations will be important to analyze and construct robust strains with more predictable functions.

Multi-omics approach characterises CRLS1 deficiency, a novel mitochondrial disorder

Introduction: The increasing integration of high-throughput genomic strategies, particularly whole exome (WES) and genome sequencing (WGS) has revolutionised mitochondrial diagnostics with the discovery of a growing list of novel disease genes. Application of ‘multi-omics’ technologies including proteomics, lipidomics and transcriptomics will improve the diagnostic gap. Case report: We present two individuals with progressive encephalopathy and biallelic variants identified on WES in the cardiolipin synthase 1 (CRLS1) gene. Additionally, the female infant had hypertrophic cardiomyopathy, bull’s eye maculopathy, auditory neuropathy, diabetes insipidus and died at 3.5 months. The 19-year-old male presented with neurodevelopmental regression, congenital nystagmus, sensorineural hearing loss and acquired microcephaly. Results: Respiratory chain enzyme analysis of skeletal muscle showed low Complex IV activity in the first patient. Mitochondrial morphology and biogenesis were impaired in her fibroblasts. Expression of wild-type CRLS1 restored her abnormal fibroblast morphology. Fibroblast proteomic profiling and mouse Crls1 knockout cell lines identified endoplasmic reticular, mitochondrial stress responses, and varying degrees of cardiolipin insufficiency. Lipid profiling in both demonstrated reduced cardiolipin levels, altered acyl-chain composition and significantly increased levels of phosphatidylglycerol. Collectively, these findings support that deleterious CRLS1 variants cause a novel mitochondrial disorder with multisystemic involvement. Conclusion: Innovative multi-omics approaches help establish novel diagnoses and provide insights into disease mechanisms.

A Simple and Accurate Method Based on a Water-Consumption Model for Phenotyping Soybean Genotypes under Hydric Deficit Conditions

Drought limits crop productivity and reduces yield stability. Drought tolerance as a selection criterion in breeding programs requires the development of high-throughput, precise, and low-cost phenotyping strategies. We developed a mathematical model, based on biological approaches, for evaluating soybean plants’ response to drought under controlled growth conditions. The model describes the kinetics of water consumption of a plant pot substrate system (PPS) with low sampling requirements. The model generated two parameters, t0.5 (time necessary for the PPS to reach half of the maximum amount of evapotranspirable water) and Gw(t0.5) (stomatal conductance [Gw] at t0.5), which determined the water- consumption curve of each genotype. An analysis of the kinetics of water consumption in response to a progressive water deficit in a biparental and breeding population was performed as a preliminary test of the model. A correspondence analysis between the t0.5 and Gw(t0.5) parameters with the genetic structure of the populations shows a genetic association. The phenotyping methodology presented in this work and drought susceptibility in field conditions are discussed based on previous results. This work could be useful for improving the selection of soybean genotypes in relation to their performance under drought conditions.

Liquid chromatography-mass spectrometry method for discovering the metabolic markers to reveal the potential therapeutic effects of naringin on osteoporosis

The pharmacological effects and therapeutic targets of naringin (NG) against osteoporosis (OP) is still unclear. Liquid chromatography quadrupole time-of-flight mass spectrometry (LC-Q-TOF/MS) based non-targeted metabonomics has been used to explore the differentiated metabolites and potential biological pathways of NG in the pathological process of OP. Using network pharmacology analysis, the key protein targets of NG against OP were also screened. By the metabonomics analysis, a total of 33 differentiated metabolites in serum were discovered, of which 21 were significantly regulated by NG treatment. These metabolites majorly associated with to amino acid metabolism,polyunsaturated fatty acid metabolism, pyruvate metabolism and glycerophospholipidmetabolism. Using the network pharmacology prediction analysis, NG was related to the expression changes of 13 important protein targets. It showed that high-throughput metabonomics strategy integrated with network pharmacology could insight into molecular mechanisms of natural products.

High-Throughput Time-Lapse Fluorescence Microscopy Screening for Heterogeneously Expressed Genes in Bacillus subtilis.

ABSTRACTElucidating phenotypic heterogeneity in clonal bacterial populations is important for both the fundamental understanding of bacterial behavior and the synthetic engineering of bacteria in biotechnology. In this study, we present and validate a high-throughput and high-resolution time-lapse fluorescence microscopy-based strategy to easily and systematically screen for heterogeneously expressed genes in the Bacillus subtilis model bacterium. This screen allows detection of expression patterns at high spatial and temporal resolution, which often escape detection by other approaches, and can readily be extrapolated to other bacteria. A proof-of-concept screening in B. subtilis revealed both recognized and yet unrecognized heterogeneously expressed genes, thereby validating the approach.IMPORTANCE Differential gene expression among isogenic siblings often leads to phenotypic heterogeneity and the emergence of complex social behavior and functional capacities within clonal bacterial populations. Despite the importance of such features for both the fundamental understanding and synthetic engineering of bacterial behavior, approaches to systematically map such population heterogeneity are scarce. In this context, we have elaborated a new time-lapse fluorescence microscopy-based strategy to easily and systematically screen for such heterogeneously expressed genes in bacteria with high resolution and throughput. A proof-of-concept screening in the Bacillus subtilis model bacterium revealed both recognized and yet unrecognized heterogeneously expressed genes, thereby validating our approach.

High-throughput discovery of novel lanthipeptides and producers by metagenomic mining of isolates population (MMIP) from Chinese spicy cabbage

Lanthipeptides are known antimicrobial agents having great potential for application in food preservation. Many lanthipeptide biosynthetic gene clusters (BGCs) were mined in fermented food microbiota, however, it is difficult to obtain the bioactive lanthipeptides and their producing strains. Here, we established a high-throughput strategy designated Metagenomic Mining of Isolates Population (MMIP) to efficiently excavate and obtain novel lanthipeptides, especially their potential producing strains. MMIP procedure involves gathering bacteria isolates using culturable strategy, metagenomic mining for lanthipeptides and screening their producers, and characterization of specific lanthipeptides. 928 biosynthetic gene clusters including 139 ribosomally synthesized and post-translationally modified peptides (RiPPs) gene clusters were discovered in the metagenomic data of the isolates by antiSMASH. Entianin, lactocin S, lichenicidin, and 17 novel lanthipeptides gene clusters corresponding to 29 possible producers were further found from the harvested isolates population. Entianin and a novel two-component lanthipeptide paralicin were purified from Bacillus subtilis C5B1 and Bacillus paralicheniformis BaC1-8, respectively. They showed strong inhibitory activity to food spoilage bacteria Bacillus cereus and Listeria monocytogenes, and have great potential for application in food preservation. A novel lanthipeptide polysacin was also obtained using semi-in vitro biosynthesis. MMIP affords a novel strategy for effectively excavating lanthipeptides, especially their producers from diverse environmental niches.

MALDI-TOF MS profiling and exopolysaccharide production properties of lactic acid bacteria from Kunu-zaki - A cereal-based Nigerian fermented beverage

MALDI-TOF MS is a technique for high-throughput characterization of foodborne microbiota, however, its application for studying African traditional fermented foods is limited. A total of 164 out of 220 lactic acid bacterial (LAB) isolates from Kunu-zaki were identified using MALDI-TOF MS, with 100% identity of representative strains compared to 16S rRNA gene sequencing. MALDI-TOF MS profiling combined with 16S rRNA gene sequencing revealed a total of 15 LAB species in Kunu-zaki, where the most predominant species were Lactiplantibacillus plantarum (40.46%), Weissella confusa (27.27%), and Pediococcus pentosaceus (15.00%). Phenotypic screening of all isolates revealed strains of W. confusa (57), Lactiplantibacillus sp. (9), Companilactobacillus musae (1), Ligilactobacillus saerimneri (1) and Leuconostoc citreum (1) that are capable of producing dextran and/or fructan. Dextransucrase genes were detected in all EPS-producing strains by PCR. Weissella confusa YKDIA1 and YKDIA4 produced 11.93 and 11.70 g/L dextran from millet-sorghum flour hydrolysate-sucrose, respectively. Kunu-zaki produced using W. confusa YKDIA1 had high water holding capacity (100%) and viscosity ranging from 49.46–139.24 mPas. In this study, MALDI-TOF MS adequately revealed the LAB species composition in Kunu-zaki in a high-throughput strategy and further, the dominant occurrence of EPS-producing LAB strains and their potentials to influence the rheological properties of Kunu-zaki were demonstrated.

Ricolinostat promotes the generation of megakaryocyte progenitors from human hematopoietic stem and progenitor cells

BackgroundEx vivo production of induced megakaryocytes (MKs) and platelets from stem cells is an alternative approach for supplying transfusible platelets. However, it is difficult to generate large numbers of MKs and platelets from hematopoietic stem cells and progenitor cells (HSPCs).MethodsTo optimize the differentiation efficiency of megakaryocytic cells from HSPCs, we first employed a platelet factor 4 (PF4)-promoter reporter and high-throughput screening strategy to screen for small molecules. We also investigated the effects and possible mechanisms of candidate small molecules on megakaryocytic differentiation of human HSPCs.ResultsThe small molecule Ricolinostat remarkably promoted the expression of PF4-promoter reporter in the megakaryocytic cell line. Notably, Ricolinostat significantly enhanced the cell fate commitment of MK progenitors (MkPs) from cord blood HSPCs and promoted the proliferation of MkPs based on cell surface marker detection, colony-forming unit-MK assay, and quantitative real-time PCR analyses. MkPs generated from Ricolinostat-induced HSPCs differentiated into mature MKs and platelets. Mechanistically, we found that Ricolinostat enhanced MkP fate mainly by inhibiting the secretion of IL-8 and decreasing the expression of the IL-8 receptor CXCR2.ConclusionThe addition of Ricolinostat to the culture medium promoted MkP differentiation from HSPCs and enhanced the proliferation of MkPs mainly by suppressing the IL-8/CXCR2 pathway. Our results can help the development of manufacturing protocols for the efficient generation of MKs and platelets from stem cells in vitro.

High-throughput calculations combining machine learning to investigate the corrosion properties of binary Mg alloys

Magnesium (Mg) alloys have shown great prospects as both structural and biomedical materials, while poor corrosion resistance limits their further application. In this work, to avoid the time-consuming and laborious experiment trial, a high-throughput computational strategy based on first-principles calculations is designed for screening corrosion-resistant binary Mg alloy with intermetallics, from both the thermodynamic and kinetic perspectives. The stable binary Mg intermetallics with low equilibrium potential difference with respect to the Mg matrix are firstly identified. Then, the hydrogen adsorption energies on the surfaces of these Mg intermetallics are calculated, and the corrosion exchange current density is further calculated by a hydrogen evolution reaction (HER) kinetic model. Several intermetallics, e.g. Y3Mg, Y2Mg and La5Mg, are identified to be promising intermetallics which might effectively hinder the cathodic HER. Furthermore, machine learning (ML) models are developed to predict Mg intermetallics with proper hydrogen adsorption energy employing work function (Wf) and weighted first ionization energy (WFIE). The generalization of the ML models is tested on five new binary Mg intermetallics with the average root mean square error (RMSE) of 0.11 eV. This study not only predicts some promising binary Mg intermetallics which may suppress the galvanic corrosion, but also provides a high-throughput screening strategy and ML models for the design of corrosion-resistant alloy, which can be extended to ternary Mg alloys or other alloy systems.

High-throughput methods for genome editing: the more the better.

During the last decade, targeted genome-editing technologies, especially clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein (Cas) technologies, have permitted efficient targeting of genomes, thereby modifying these genomes to offer tremendous opportunities for deciphering gene function and engineering beneficial traits in many biological systems. As a powerful genome-editing tool, the CRISPR/Cas systems, combined with the development of next-generation sequencing and many other high-throughput techniques, have thus been quickly developed into a high-throughput engineering strategy in animals and plants. Therefore, here, we review recent advances in using high-throughput genome-editing technologies in animals and plants, such as the high-throughput design of targeted guide RNA (gRNA), construction of large-scale pooled gRNA, and high-throughput genome-editing libraries, high-throughput detection of editing events, and high-throughput supervision of genome-editing products. Moreover, we outline perspectives for future applications, ranging from medication using gene therapy to crop improvement using high-throughput genome-editing technologies.

High-throughput microfluidic strategy based on RAA-CRISPR/Cas13a dual signal amplification for accurate identification of pathogenic Listeria

Listeria spp. is a kind of important food-borne pathogen with a high fatality rate and is widely distributed in food chain, posing a potential threat to the public health. It is urgently necessary to develop a pathogenic Listeria detection platform with high specificity, sensitivity, high-throughput, and user-friendliness to meet the requirements of on-line monitoring of food production. We therefore developed a one-step detection method (hMC-CRISPR) based on recombinase aided amplification (RAA) and CRISPR on a high-throughput microfluidic chip. This strategy coordinates the nucleic acid amplification and the cleavage efficiency of CRISPR/Cas13a through the transcription process, thereby preventing the complete cleavage of all genomic DNA and amplicons from being cleaved. The corresponding RAA-CRISPER/Cas13a system was designed based on the specific markers of Listeria spp., L. monocytogenes, L. innocua and L. ivanovii, and the reaction volume was limited to 5 µL to match the microfluidic chip. This strategy achieved sensitive and robust detection of pathogenic Listeria with a sample-to-answer time of ~60 min, and a detection limit of each index reached aM level. More importantly, hMC-CRISPR can detect pathogenic Listeria in eight samples at one time and avoid the influence of aerosol on the test results. It is practically validated by quantitatively determining four types of spiked samples and 24 natural samples. Collectively, this new strategy has great potential to improve the current rapid screening of pathogenic Listeria.

Decellularized Colorectal Cancer Matrices as Bioactive Scaffolds for Studying Tumor-Stroma Interactions.

Simple SummaryColorectal cancer is an increasingly prevalent disease that accounts for substantial mortality and morbidity and is responsible for an impaired quality of life. This scenario highlights the urgent need to better understand the biological mechanisms underlying colorectal cancer onset, progression and spread to improve diagnosis and establish tailored therapeutic strategies. Therefore, understanding tumor microenvironment dynamics could be crucial, since it is where the tumorigenic process begins and evolves under the heavy influence of the complex crosstalk between all elements: the cellular component (cancer cells and the non-malignant stromal cells), the non-cellular component (extracellular matrix) and the interstitial fluids. Bioengineered models that can accurately mimic the tumor microenvironment are the golden key to comprehending disease biology. Therefore, the focus of this review addresses the advanced 3D-based models of the decellularized extracellular matrix as high-throughput strategies in colorectal cancer research that potentially fill some of the gaps between in vitro two-dimensional and in vivo models.More than a physical structure providing support to tissues, the extracellular matrix (ECM) is a complex and dynamic network of macromolecules that modulates the behavior of both cancer cells and associated stromal cells of the tumor microenvironment (TME). Over the last few years, several efforts have been made to develop new models that accurately mimic the interconnections within the TME and specifically the biomechanical and biomolecular complexity of the tumor ECM. Particularly in colorectal cancer, the ECM is highly remodeled and disorganized and constitutes a key component that affects cancer hallmarks, such as cell differentiation, proliferation, angiogenesis, invasion and metastasis. Therefore, several scaffolds produced from natural and/or synthetic polymers and ceramics have been used in 3D biomimetic strategies for colorectal cancer research. Nevertheless, decellularized ECM from colorectal tumors is a unique model that offers the maintenance of native ECM architecture and molecular composition. This review will focus on innovative and advanced 3D-based models of decellularized ECM as high-throughput strategies in colorectal cancer research that potentially fill some of the gaps between in vitro 2D and in vivo models. Our aim is to highlight the need for strategies that accurately mimic the TME for precision medicine and for studying the pathophysiology of the disease.

Quantitative biophysical metrics for rapid evaluation of ovarian cancer metastatic potential.

Ovarian cancer is routinely diagnosed long after the disease has metastasized through the fibrous submesothelium. Despite extensive research in the field linking ovarian cancer progression to increasingly poor prognosis, there are currently no validated cellular markers or hallmarks of ovarian cancer that can predict metastatic potential. To discern disease progression across a syngeneic mouse ovarian cancer progression model, here we fabricated extracellular matrix mimicking suspended fiber networks: cross-hatches of mismatch diameters for studying protrusion dynamics, aligned same diameter networks of varying interfiber spacing for studying migration, and aligned nanonets for measuring cell forces. We found that migration correlated with disease while a force-disease biphasic relationship exhibited F-actin stress fiber network dependence. However, unique to suspended fibers, coiling occurring at the tips of protrusions and not the length or breadth of protrusions displayed the strongest correlation with metastatic potential. To confirm that our findings were more broadly applicable beyond the mouse model, we repeated our studies in human ovarian cancer cell lines and found that the biophysical trends were consistent with our mouse model results. Altogether, we report complementary high throughput and high content biophysical metrics capable of identifying ovarian cancer metastatic potential on a timescale of hours.

Development of a Microfluidic Droplet Platform with an Antibody-Free Magnetic-Bead-Based Strategy for High Through-Put and Efficient Evs Isolation

Development of a Microfluidic Droplet Platform with an Antibody-Free Magnetic-Bead-Based Strategy for High Through-Put and Efficient Evs Isolation

Ligand Selection by Combination of Recombinant and Cell Panning Selection Techniques.

High-throughput protein selection methods are a cornerstone for protein engineering and pharmaceutical development. Traditional high-throughput selection strategies rely largely on recombinant antigen to generate target specificity. Though effective, this selection strategy can be limited by soluble target quality, particularly in the case of recombinant extracellular domains of transmembrane proteins. Recent advances in cell-based selection techniques provide new opportunities for improving the outcomes of ligand selection campaigns but can introduce technical challenges in maintaining antigen specificity due to the heterogeneity of biomacromolecule expression on the mammalian cell surface. Here, we describe a combination technique using recombinant antigen to "train" library target specificity followed by cell panning selections to ensure that isolated ligands bind cell-expressed target, as well as a facile microscopy technique for assessing target specificity on a clonal basis without the need to produce soluble ligand.

Cotranscriptional RNA Chemical Probing.

Cotranscriptional folding is a fundamental step in RNA biogenesis and the basis for many RNA-mediated gene regulation systems. Understanding how RNA folds as it is synthesized requires experimental methods that can systematically identify intermediate RNA structures that form during transcription. Cotranscriptional RNA chemical probing experiments achieve this by applying high-throughput RNA structure probing to an in vitro transcribed array of cotranscriptionally folded intermediate transcripts. In this chapter, we present guidelines and procedures for integrating single-round in vitro transcription using E. coli RNA polymerase with high-throughput RNA chemical probing workflows. We provide an overview of key concepts including DNA template design, transcription roadblocking strategies, single-round in vitro transcription with E. coli RNA polymerase, and RNA chemical probing and describe procedures for DNA template preparation, cotranscriptional RNA chemical probing, RNA purification, and 3' adapter ligation. The end result of these procedures is a purified RNA library that can be prepared for Illumina sequencing using established high-throughput RNA structure probing library construction strategies.

A High-Throughput Strategy for T-Cell Receptor Cloning and Expression.

Expression of T-cell receptor (TCR) genes is a critical step for TCR characterization and epitope identification. The recent interest in using specific TCRs for cancer immunotherapy has further increased the demand for practical and robust methods to rapidly clone and express TCRs. We show that a recombination-based cloning protocol facilitates simple and rapid transfer of the TCR transgene into different expression systems. In this protocol, we first constructed all the human TRAV and TRBV genes into individual plasmid. To clone any TCR, we only need to ligate a short CDR3 fragment to its corresponding V gene plasmid using Golden Gate cloning. This strategy significantly improves the efficiency of individual TCR cloning and mutagenesis, providing a flexible high-throughput method for TCR analysis and TCR-mediated therapeutics.