High-throughput Manner Research Articles

A Multiplex Assay to Simultaneously Monitor Apoptosis and Necrosis Using the Cellaca® PLX Image Cytometer.

Apoptosis is the programmed cell death pathway that is critical for maintaining homeostasis, in which cancer cells can evade to ensure survival. For pharmaceutical drug discovery, it is important to characterize and compare different cancer therapeutics (i.e., small molecules, antibody drugs, cell therapies) that can initiate the process of apoptosis, enabling the identification of potential therapeutic candidates. In this work, we developed and demonstrated a multiplex detection method for monitoring apoptosis and necrosis with Annexin V, Caspase-3, and Propidium Iodide (PI) using the Cellaca® PLX Image Cytometer(Revvity Health Sciences, Inc., Lawrence, MA). First, apoptosis was induced in Jurkat and K562 cell lines with staurosporine over the course of 24h, where apoptosis and necrosis were assessed at 0, 1, 1.5, 2, 4, 20, and 24h timepoints. Samples were stained with Hoechst 33342 (total dye), Annexin V-APC (early-stage apoptosis), Caspase-3 488 (late-stage apoptosis), and PI (necrosis) at each timepoint and evaluated using image cytometry. Results showed that apoptotic factors and cascades were successfully detected along the pathway from early- to late-stage apoptosis, and ultimately necrosis. A clear trend was observed analyzing apoptotic and necrotic populations during the first 1.5h, showing differences of up to ~15% in single Annexin V+ and Caspase-3+ populations in treated Jurkat cells, however, a significant increase in double positive apoptotic/necrotic cells for Annexin V+PI+ and Capase-3+PI+ was not observed until 20h. Upon further analysis between apoptotic populations only, Annexin V+ only populations were higher than Caspase-3+ only populations by up to ~20% between 0 and 1.5h. Conversely, K562 cells did not exhibit a notable change in apoptotic and necrotic populations due to low sensitivity to staurosporine. The proposed image cytometric detection method may provide an effective and efficient tool for rapid and reliable simultaneous detection of early- late-stage apoptosis, and necrosis. Therefore, allowing researchers to better characterize and screen potential cancer therapeutic drug candidates for their treatment efficacy in a higher throughput manner.

3D Bioprinted Liver-on-a-Chip for Drug Cytotoxicity Screening.

Tissues on a chip are sophisticated three-dimensional (3D) in vitro microphysiological systems designed to replicate human tissue conditions within dynamic physicochemical environments. However, the current fabrication methods for tissue spheroids on a chip require multiple parts and manual processing steps, including the deposition of spheroids onto prefabricated "chips." These challenges also lead to limitations regarding scalability and reproducibility. To overcome these challenges, we employed 3D printing techniques to automate the fabrication process of tissue spheroids on a chip. This allowed the simultaneous high-throughput printing of human liver spheroids and their surrounding polymeric flow chamber "chips" containing inner channels in a single step. The fabricated liver tissue spheroids on a liver-on-a-chip (LOC) were subsequently subjected to dynamic culturing by a peristaltic pump, enabling assessment of cell viability and metabolic activities. The 3D printed liver spheroids within the printed chips demonstrated high cell viability (>80%), increased spheroid size, and consistent adenosine triphosphate (ATP) activity and albumin production for up to 14 days. Furthermore, we conducted a study on the effects of acetaminophen (APAP), a nonsteroidal anti-inflammatory drug, on the LOC. Comparative analysis revealed a substantial decline in cell viability (<40%), diminished ATP activity, and reduced spheroid size after 7 days of culture within the APAP-treated LOC group, compared to the nontreated groups. These results underscore the potential of 3D bioprinted tissue chips as an advanced in vitro model that holds promise for accurately studying in vivo biological processes, including the assessment of tissue response to administered drugs, in a high-throughput manner.

Sequence-activity mapping via depletion reveals striking mutational tolerance and elucidates functional motifs in Tur1a antimicrobial peptide.

Proline-rich antimicrobial peptides (PrAMPs) are attractive antibiotic candidates that target gram-negative bacteria ribosomes. We elucidated the sequence-function landscape of 43 000 variants of a recently discovered family member, Tur1a, using the validated SAMP-Dep platform that measures intracellular AMP potency in a high-throughput manner via self-depletion of the cellular host. The platform exhibited high replicate reproducibility (ρ = 0.81) and correlation between synonymous genetic variants (R2 = 0.93). Only two segments within Tur1a exhibited stringent mutational requirements to sustain potency: residues 9YLP11 and 19FP20. This includes the aromatic residue in the hypothesized binding domain but not the PRP domain. Along with unexpected mutational tolerance of PRP, the data contrast hypothesized importance of the 1RRIR4 motif and arginines in general. In addition to mutational tolerance of residue segments with presumed significance, 77% of mutations are functionally neutral. Multimutant performance mainly shows compounding effects from removed combinations of prolines and arginines in addition to the two segments of residues showing individual importance. Several variants identified as active from SAMP-Dep were externally produced and maintained activity when applied to susceptible species exogenously.

Toolkits for detailed and high-throughput interrogation of synapses in C. elegans.

Visualizing synaptic connectivity has traditionally relied on time-consuming electron microscopy-based imaging approaches. To scale the analysis of synaptic connectivity, fluorescent protein-based techniques have been established, ranging from the labeling of specific pre- or post-synaptic components of chemical or electrical synapses to transsynaptic proximity labeling technology such as GRASP and iBLINC. In this paper, we describe WormPsyQi, a generalizable image analysis pipeline that automatically quantifies synaptically localized fluorescent signals in a high-throughput and robust manner, with reduced human bias. We also present a resource of 30 transgenic strains that label chemical or electrical synapses throughout the nervous system of the nematode Caenorhabditis elegans, using CLA-1, RAB-3, GRASP (chemical synapses), or innexin (electrical synapse) reporters. We show that WormPsyQi captures synaptic structures in spite of substantial heterogeneity in neurite morphology, fluorescence signal, and imaging parameters. We use these toolkits to quantify multiple obvious and subtle features of synapses - such as number, size, intensity, and spatial distribution of synapses - in datasets spanning various regions of the nervous system, developmental stages, and sexes. Although the pipeline is described in the context of synapses, it may be utilized for other 'punctate' signals, such as fluorescently tagged neurotransmitter receptors and cell adhesion molecules, as well as proteins in other subcellular contexts. By overcoming constraints on time, sample size, cell morphology, and phenotypic space, this work represents a powerful resource for further analysis of synapse biology in C. elegans.

Toolkits for detailed and high-throughput interrogation of synapses in C. elegans

Visualizing synaptic connectivity has traditionally relied on time-consuming electron microscopy-based imaging approaches. To scale the analysis of synaptic connectivity, fluorescent protein-based techniques have been established, ranging from the labeling of specific pre- or post-synaptic components of chemical or electrical synapses to transsynaptic proximity labeling technology such as GRASP and iBLINC. In this paper, we describe WormPsyQi, a generalizable image analysis pipeline that automatically quantifies synaptically localized fluorescent signals in a high-throughput and robust manner, with reduced human bias. We also present a resource of 30 transgenic strains that label chemical or electrical synapses throughout the nervous system of the nematode Caenorhabditis elegans, using CLA-1, RAB-3, GRASP (chemical synapses), or innexin (electrical synapse) reporters. We show that WormPsyQi captures synaptic structures in spite of substantial heterogeneity in neurite morphology, fluorescence signal, and imaging parameters. We use these toolkits to quantify multiple obvious and subtle features of synapses – such as number, size, intensity, and spatial distribution of synapses – in datasets spanning various regions of the nervous system, developmental stages, and sexes. Although the pipeline is described in the context of synapses, it may be utilized for other ‘punctate’ signals, such as fluorescently tagged neurotransmitter receptors and cell adhesion molecules, as well as proteins in other subcellular contexts. By overcoming constraints on time, sample size, cell morphology, and phenotypic space, this work represents a powerful resource for further analysis of synapse biology in C. elegans.

Integrated web portal for non-destructive salt sensitivity detection of Camelina sativa seeds using fluorescent and visible light images coupled with machine learning algorithms.

Climate change has created unprecedented stresses in the agricultural sector, driving the necessity of adapting agricultural practices and developing novel solutions to the food crisis. Camelina sativa (Camelina) is a recently emerging oilseed crop with high nutrient-density and economic potential. Camelina seeds are rich in essential fatty acids and contain potent antioxidants required to maintain a healthy diet. Camelina seeds are equally amenable to economic applications such as jet fuel, biodiesel and high-value industrial lubricants due to their favorable proportions of unsaturated fatty acids. High soil salinity is one of the major abiotic stresses threatening the yield and usability of such crops. A promising mitigation strategy is automated, non-destructive, image-based phenotyping to assess seed quality in the food manufacturing process. In this study, we evaluate the effectiveness of image-based phenotyping on fluorescent and visible light images to quantify and qualify Camelina seeds. We developed a user-friendly web portal called SeedML that can uncover key morpho-colorimetric features to accurately identify Camelina seeds coming from plants grown in high salt conditions using a phenomics platform equipped with fluorescent and visible light cameras. This portal may be used to enhance quality control, identify stress markers and observe yield trends relevant to the agricultural sector in a high throughput manner. Findings of this work may positively contribute to similar research in the context of the climate crisis, while supporting the implementation of new quality controls tools in the agri-food domain.

High-Throughput Sorting and Single-Cell Mechanotyping by Hydrodynamic Sorting-Mechanotyping Cytometry.

The existence of many background blood cells hinders the accurate identification of circulating tumor cells (CTCs) in the blood of cancer patients. To unlock this limitation, a hydrodynamic sorting-mechanotyping cytometry (HSMC) integrated with a sorting-concentration chip and a detection chip is proposed for simultaneously achieving the high-throughput cell sorting and the multi-parameter mechanotyping of the sorted tumor cells. The HSMC adopts the spiral inertial microfluidics for label-free sorting of cells in a high-throughput manner, allowing the efficient enrichment of tumor cells from the large background blood cells. Then, the sorted cells are concentrated by the concentration unit and finally passed through the detection unit for hydrodynamic deformation. The HSMC has a high throughput for sorting and detection and can successfully reveal the differences in the cellular mechanical properties. After characterizing and optimizing the single chips, the identification of white blood cells (WBCs) and three types of tumor cells (A549, MCF-7, and MDA-MB-231 cells) is successfully achieved. The identification accuracies for WBCs and different tumor cells are all larger than 94%, while the highest identification accuracy is up to 99.2%. This study envisions that the HSMC will offer an avenue for the analysis of single cell intrinsic mechanics in clinical medicine.

Controlled mean dynamics of red blood cells by two orthogonal ultrasonic standing waves

A computational model is developed to study the time-averaged mean dynamics of red blood cells (RBCs) driven by the time-averaged mean stress generated by two phase-shifted orthogonal ultrasonic standing waves in a viscous fluid. The cell is modelled as an ellipsoidal viscoelastic membrane enclosing the viscous fluid cytoplasm, the motion of which is described by the inclination angle of the ellipsoidal cell shape and the phase angle of the potential membrane cycle. Based on the acoustic perturbation method, the acoustic field and acoustic streaming field are solved to obtain the time-averaged mean stress, and then the temporal evolution equations of the inclination and phase angles of the cell are determined considering the torque balance and energy conservation. At a small acoustic pressure amplitude, this model reproduces the experimentally observed features of cell motion in orthogonal standing waves: the transition from steady stationary orientation to unsteady tumbling with the increase of the phase difference between the two standing waves. By turning up the acoustic pressure amplitude above a critical value, it is further predicted that the previously observed motions can be accompanied by the membrane tank-treading rotation. Observations of these motions, combined with the present computational model, can help to evaluate the mechanical properties of RBC membranes in an automated and high-throughput manner by acoustic methods.

Evaluation of a targeted drug delivery system on breast tumor spheroids on a chip

Targeted combination nanomedicine can be employed as a potent approach for cancer treatment. However, the inadequacy of most preclinical tumor models for drug/nanotherapeutic screening has limited their clinical translation. As promising in vitro models, three-dimensional (3D)-printed microfluidic devices can be fabricated in a high-throughput cost-effective manner for various biomedical applications. In this study, using a 3D printed mold, a microwell-based breast tumor-on-a-chip was developed. A modified protocol was devised for the surface treatment of the resin-based 3D-printed template making it suitable for repeated long-term polydimethylsiloxane (PDMS) casting. The versatility of the chip was demonstrated through both biorelevant scaffold-free 3D tumor spheroid culture and nanomedicine screening. Representative of avascular tumor tissues, tumor spheroids were generated in this platform and exhibited tight structure with a size range of 300–500 μm, internal cellular layers, and in vivo pathophysiology conditions. A targeted drug delivery system of 5-fluorouracil, curcumin, and piperine co-loaded folate-conjugated human serum albumin nanoparticles (FA-5FU-CUR-PIP-HSA-NPs) was synthesized by the self-assembly method and both hydrophobic and hydrophilic drugs were encapsulated in the NPs. The transport mechanism and efficacy of the NPs were investigated on the tumor model tissue. Possessing proper physical, biological, and pharmaceutical drug combination, the targeted NPs formulation with the potential of cancer theranostics demonstrated enhanced internalization and accumulation into triple-negative MDA-MB-231 breast cancer microtissues upon both passive and active targeting. The increased penetration and uptake of the targeted NPs in tumor spheroids were translated into boosted anticancer activity. Compatible with the uptake and cytotoxicity test, higher cell apoptosis was observed for the targeted nanomedicine than for the non-targeted NPs. Together, the combination of microfluidics and nanomedicine approaches can benefit basic research related to human disease.

The journey towards clinical adoption of MALDI-MS-based imaging proteomics: from current challenges to future expectations.

Among the spatial omics techniques available, mass spectrometry imaging (MSI) represents one of the most promising owing to its capability to map the distribution of hundreds of peptides and proteins, as well as other classes of biomolecules, within a complex sample background in a multiplexed and relatively high-throughput manner. In particular, matrix-assisted laser desorption/ionisation (MALDI-MSI) has come to the fore and established itself as the most widely used technique in clinical research. However, the march of this technique towards clinical utility has been hindered by issues related to method reproducibility, appropriate biocomputational tools, and data storage. Notwithstanding these challenges, significant progress has been achieved in recent years regarding multiple facets of the technology and has rendered it more suitable for a possible clinical role. As such, there is now more robust and extensive evidence to suggest that the technology has the potential to support clinical decision-making processes under appropriate circumstances. In this review, we will discuss some of the recent developments that have facilitated this progress and outline some of the more promising clinical proteomics applications which have been developed with a clear goal towards implementation in mind.

One-step biofabrication of liquid core-GelMa shell microbeads for in situ hollow cell ball self-assembly.

There are many instances of hollow-structure morphogenesis in the development of tissues. Thus, the fabrication of hollow structures in a simple, high-throughput and homogeneous manner with proper natural biomaterial combination is valuable for developmental studies and tissue engineering, while it is a significant challenge in biofabrication field. We present a novel method for the fabrication of a hollow cell module using a coaxial co-flow capillary microfluidic device. Sacrificial gelatin laden with cells in the inner layer and GelMa in the outer layer are used via a coaxial co-flow capillary microfluidic device to produce homogenous micro-beads. The overall and core sizes of core-shell microbeads were well controlled. When using human vein vascular endothelial cells to demonstrate how cells line the inner surface of core-shell beads, as the core liquifies, a hollow cell ball with asymmetric features is fabricated. After release from the GelMa shell, individual cell balls are obtained and deformed cell balls can self-recover. This platform paves way for complex hollow tissue modeling in vitro, and further modulation of matrix stiffness, curvature and biochemical composition to mimic in vivo microenvironments.

Drosophila melanogaster Neuromuscular Junction as a Model to Study Synaptopathies and Neuronal Autophagy.

Neuronal synapse dysfunction is a key characteristic of several neurodegenerative disorders, such as Alzheimer's disease, spinocerebellar ataxias, and Huntington's disease. Modeling these disorders to study synaptic dysfunction requires a robust and reproducible method for assaying the subtle changes associated with synaptopathies in terms of structure and function of the synapses. Drosophila melanogaster neuromuscular junctions (NMJs) serve as good models to study such alterations. Further, modifications in the microenvironment of synapses can sometimes reflect in the behavior of the animal, which can also be assayed in a high-throughput manner. The methods outlined in this chapter highlight assays to study the behavioral changes associated with synaptic dysfunction in a spinocerebellar ataxia type 3 (SCA3) model. Further, molecular assessment of alterations in NMJ structure and function is also summarized, followed by effects of autophagy pathway upregulation in providing neuroprotection. These methods can be further extended and modified to study the therapeutic effects of drugs or small molecules in providing neuroprotection for any synaptopathy models.

Development of a 3D printed perfusable in vitro blood-brain barrier model for use as a scalable screening tool.

Despite recent technological advances in drug discovery, the success rate for neurotherapeutics remains alarmingly low compared to treatments for other areas of the body. One of the biggest challenges for delivering therapeutics to the central nervous system (CNS) is the presence of the blood-brain barrier (BBB). In vitro blood-brain barrier models with high predictability are essential to aid in designing parameters for new therapeutics, assess their ability to cross the BBB, and investigate therapeutic strategies that can be employed to enhance transport. Here, we demonstrate the development of a 3D printable hydrogel blood-brain barrier model that mimics the cellular composition and structure of the blood-brain barrier with human brain endothelial cells lining the surface, pericytes in direct contact with the endothelial cells on the abluminal side of the endothelium, and astrocytes in the surrounding printed bulk matrix. We introduce a simple, static printed hemi-cylinder model to determine design parameters such as media selection, co-culture ratios, and cell incorporation timing in a resource-conservative and high-throughput manner. Presence of cellular adhesion junction, VE-Cadherin, efflux transporters, P-glycoprotein (P-gp) and Breast cancer resistance protein (BCRP), and receptor-mediated transporters, Transferrin receptor (TfR) and low-density lipoprotein receptor-related protein 1 (LRP1) were confirmed via immunostaining demonstrating the ability of this model for screening in therapeutic strategies that rely on these transport systems. Design parameters determined in the hemi-cylinder model were translated to a more complex, perfusable vessel model to demonstrate its utility for determining barrier function and assessing permeability to model therapeutic compounds. This 3D-printed blood-brain barrier model represents one of the first uses of projection stereolithography to fabricate a perfusable blood-brain barrier model, enabling the patterning of complex vessel geometries and precise arrangement of cell populations. This model demonstrates potential as a new platform to investigate the delivery of neurotherapeutic compounds and drug delivery strategies through the blood-brain barrier, providing a useful in vitro screening tool in central nervous system drug discovery and development.

CRISPRi-Driven Genetic Screening for Designing Novel Microbial Phenotypes.

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 system has enabled rapid advances in genomic engineering and transcriptional regulation. Specifically, CRISPR interference (CRISPRi) system has been used to systematically investigate the gene functions of microbial strains in a high-throughput manner. This method involves growth profiling using cells that have been transformed with the deactivated Cas9 (dCas9) and single-guide RNA (sgRNA) libraries that target individual genes. The fitness scores of each gene are calculated by measuring the abundance of individual sgRNAs during cell growth and represent gene essentiality. In this chapter, a process is described for functional genetic screening using CRISPRi at the whole-genome scale, starting from the synthesis of sgRNA libraries, construction of CRISPRi libraries, and identification of essential genes through growth profiling. The commensal bacterium Bacteroides thetaiotaomicron was used to implement the protocol. This method is expected to be applicable to a broader range of microorganisms to explore the novel phenotypic characteristics of microorganisms.

IHUP: An Integrated High-Throughput Universal Phenotyping Software Platform to Accelerate Unmanned-Aerial-Vehicle-Based Field Plant Phenotypic Data Extraction and Analysis.

With the threshold for crop growth data collection having been markedly decreased by sensor miniaturization and cost reduction, unmanned aerial vehicle (UAV)-based low-altitude remote sensing has shown remarkable advantages in field phenotyping experiments. However, the requirement of interdisciplinary knowledge and the complexity of the workflow have seriously hindered researchers from extracting plot-level phenotypic data from multisource and multitemporal UAV images. To address these challenges, we developed the Integrated High-Throughput Universal Phenotyping (IHUP) software as a data producer and study accelerator that included 4 functional modules: preprocessing, data extraction, data management, and data analysis. Data extraction and analysis requiring complex and multidisciplinary knowledge were simplified through integrated and automated processing. Within a graphical user interface, users can compute image feature information, structural traits, and vegetation indices (VIs), which are indicators of morphological and biochemical traits, in an integrated and high-throughput manner. To fulfill data requirements for different crops, extraction methods such as VI calculation formulae can be customized. To demonstrate and test the composition and performance of the software, we conducted case-related rice drought phenotype monitoring experiments. In combination with a rice leaf rolling score predictive model, leaf rolling score, plant height, VIs, fresh weight, and drought weight were efficiently extracted from multiphase continuous monitoring data. Despite the significant impact of image processing during plot clipping on processing efficiency, the software can extract traits from approximately 500 plots/min in most application cases. The software offers a user-friendly graphical user interface and interfaces for customizing or integrating various feature extraction algorithms, thereby significantly reducing barriers for nonexperts. It holds the promise of significantly accelerating data production in UAV phenotyping experiments.

Antimicrobial effects of silver nanoparticle-microspots on the mechanical properties of single bacteria.

Silver nanoparticles (AgNPs) conjugated with polymers are well-known for their powerful and effective antimicrobial properties. In particular, the incorporation of AgNPs in biocompatible catecholamine-based polymers, such as polydopamine (PDA), has recently shown promising antimicrobial activity, due to the synergistic effects of the AgNPs, silver(I) ions released and PDA. In this study, we generated AgNPs-PDA-patterned surfaces by localised electrochemical depositions, using a double potentiostatic method via scanning electrochemical cell microscopy (SECCM). This technique enabled the assessment of a wide parameter space in a high-throughput manner. The optimised electrodeposition process resulted in stable and homogeneously distributed AgNP-microspots, and their antimicrobial activity against Escherichia coli was assessed using atomic force microscopy (AFM)-based force spectroscopy, in terms of bacterial adhesion and cell elasticity. We observed that the bacterial outer membrane underwent significant structural changes, when in close proximity to the AgNPs, namely increased hydrophilicity and stiffness loss. The spatially varied antimicrobial effect found experimentally was rationalised by numerical simulations of silver(I) concentration profiles.

Experimental observation of near-wall effects during the puncture of soft solids.

Performing conventional mechanical characterization techniques on soft materials can be challenging due to issues such as limited sample volumes and clamping difficulties. Deep indentation and puncture is a promising alternative as it is an information-rich measurement with the potential to be performed in a high-throughput manner. Despite its promise, the method lacks standardized protocols, and open questions remain about its possible limitations. Addressing these shortcomings is vital to ensure consistent methodology, measurements, and interpretation across samples and labs. To fill this gap, we examine the role of finite sample dimensions (and by extension, volume) on measured forces to determine the sample geometry needed to perform and unambiguously interpret puncture tests. Through measurements of puncture on a well-characterized elastomer using systematically varied sample dimensions, we show that the apparent mechanical response of a material is in fact sensitive to near-wall effects, and that additional properties, such as the sliding friction coefficient, can only be extracted in the larger dimension case where such effects are negligible.

Detection and Quantification of Cryptococcus Uptake by Phagocytic Cells Using Imaging Flow Cytometry.

Cryptococcus neoformans, the predominant etiological agent of cryptococcosis, is an encapsulated fungal pathogen found ubiquitously in the environment that causes pneumonia and life-threatening infections of the central nervous system. Following inhalation of yeasts or desiccated basidiospores into the lung alveoli, resident pulmonary phagocytic cells aid in the identification and eradication of Cryptococcus yeast through their arsenal of pattern recognition receptors (PRRs). PRRs recognize conserved pathogen-associated molecular patterns (PAMPs), such as branched mannans, β-glucans, and chitins that are the major components of the fungal cell wall. However, the key receptors/ligand interactions required for cryptococcal recognition and eventual fungal clearance have yet to be elucidated. Here we present an imaging flow cytometer (IFC) method that offers a novel quantitative cellular imaging and population statistics tool to accurately measure phagocytosis of fungal cells. It has the capacity to measure two distinct steps of phagocytosis: association/attachment and internalization in a high-throughput and quantitative manner that is difficult to achieve with other technologies. Results from these IFC studies allow for the potential to identify PRRs required for recognition, uptake, and subsequent activation of cytokine production, as well as other effector cell responses required for fungal clearance.

Intermittent proton bursts of single lactic acid bacteria.

Lactic acid bacteria are a kind of probiotic microorganisms that efficiently convert carbohydrates to lactic acids, thus playing essential roles in fermentation and food industry. While conventional wisdom often suggests continuous release of protons from bacteria during acidification, here we developed a methodology to measure the dynamics of proton release at the single bacteria level, and report on the discovery of a proton burst phenomenon, i.e., the intermittent efflux of protons, of single Lactobacillus plantarum bacteria. When placing an individual bacterium in an oil-sealed microwell, efflux and accumulation of protons consequently reduced the pH in the confined extracellular medium, which was monitored with fluorescent pH indicators in a high-throughput and real-time manner. In addition to the slow and continuous proton release behavior (as expected), stochastic and intermittent proton burst events were surprisingly observed with a typical timescale of several seconds. It was attributed to the regulatory response of bacteria by activating H+-ATPase to compensate the stochastic and transient depolarizations of membrane potential. These findings not only revealed an unprecedented proton burst phenomenon in lactic acid bacteria, but also shed new lights on the intrinsic roles of H+-ATPase in membrane potential homeostasis, with implications for both fermentation industry and bacterial electrophysiology.

High-Throughput RNA-HCR-FISH Detection of Endogenous Pre-mRNA Splice Variants.

RNA-fluorescence in situ hybridization (RNA-FISH) is an essential and widely used tool for visualizing RNA molecules in intact cells. Recent advances have increased RNA-FISH sensitivity, signal detection efficiency, and throughput. However, detection of endogenous mRNA splice variants has been challenging due to the limits of visualization of RNA-FISH fluorescence signals and due to the limited number of RNA-FISH probes per target. HiFENS (high-throughput FISH detection of endogenous pre-mRNA splicing isoforms) is a method that enables visualization and relative quantification of mRNA splice variants at single-cell resolution in an automated high-throughput manner. HiFENS incorporates HCR (hybridization chain reaction) signal amplification strategies to enhance the fluorescence signal generated by low abundance transcripts or a small number of FISH probes targeting short stretches of RNA, such as single exons. The technique offers a significant advance in high-throughput FISH-based RNA detection and provides a powerful tool that can be used as a readout in functional genomics screens to discover and dissect cellular pathways regulating gene expression and alternative pre-mRNA splicing events.