Microfluidics towards single cell resolution protein analysis

Fully integrated and automated centrifugal microfluidic chip for point-of-care multiplexed molecular diagnostics

Public health events caused by pathogens have imposed significant economic and societal burdens. However, conventional methods still face challenges including complex operations, the need for trained operators, and sophisticated instruments. Here, we proposed a fully integrated and automated centrifugal microfluidic chip, also termed IACMC, for point-of-care multiplexed molecular diagnostics by harnessing the advantages of active and passive valves. The IACMC incorporates multiple essential components including a pneumatic balance module for sequential release of multiple reagents, a pneumatic centrifugation-assisted module for on-demand solution release, an on-chip silicon membrane module for nucleic acid extraction, a Coriolis force-mediated fluid switching module, and an amplification module. Numerical simulation and visual validation were employed to iterate and optimize the chip's structure. Upon sample loading, the chip automatically executes the entire process of bacterial sample lysis, nucleic acid capture, elution quantification, and isothermal LAMP amplification. By optimizing crucial parameters including centrifugation speed, direction of rotation, and silicone membrane thickness, the chip achieves exceptional sensitivity (twenty-five Salmonella or forty Escherichia coli) and specificity in detecting Escherichia coli and Salmonella within 40 min. The development of IACMC will drive advancements in centrifugal microfluidics for point-of-care testing and holds potential for broader applications in precision medicine including high-throughput biochemical analysis immune diagnostics, and drug susceptibility testing.

Open and closed microfluidics for biosensing

Biosensing is vital for many areas like disease diagnosis, infectious disease prevention, and point-of-care monitoring. Microfluidics has been evidenced to be a powerful tool for biosensing via integrating biological detection processes into a palm-size chip. Based on the chip structure, microfluidics has two subdivision types: open microfluidics and closed microfluidics, whose operation methods would be diverse. In this review, we summarize fundamentals, liquid control methods, and applications of open and closed microfluidics separately, point out the bottlenecks, and propose potential directions of microfluidics-based biosensing.

The isolation strategy and chemical analysis of oil cells from Asari Radix et Rhizoma

BACKGROUND

Single-cell analysis, a rapidly evolving field, encounters significant challenges in detecting individual cells within complex plant tissues, particularly oil cells (OCs). The intricate process of single-cell isolation, coupled with the inherent chemical volatility of oil cells, necessitates a comprehensive methodology.

RESULTS

This study presents a method for obtaining intact OC from Asari Radix et Rhizoma (ARR), a traditional herbal medicine. The developed approach facilitates both qualitative and quantitative analysis of diverse OCs. To determine the most reliable approach, four practical methods-laser capture microdissection, micromanipulation capturing, micromanipulation piping, and cell picking-were systematically compared and evaluated, unequivocally establishing cell picking as the most effective method for OC isolation and chemical analysis. Microscopic observations showed that OCs predominantly distribute in the cortex of adventitious and fibrous roots, as well as the pith and cortex of the rhizome, with distinct morphologies-oblong in roots and circular in rhizomes. Sixty-three volatile constituents were identified in OCs, with eighteen compounds exhibiting significant differences. Safrole, methyleugenol, and asaricin emerged as the most abundant constituents in OCs. Notably, cis-4-thujanol and tetramethylpyrazine were exclusive to rhizome OCs, while isoeugenol methyl ether was specific to fibrous root OCs based on the detections. ARR roots and rhizomes displayed marked disparities in OC distribution, morphology, and constituents.

CONCLUSION

The study highlights the efficacy of cell picking coupled with HS-SPME-GC-MS as a flexible, reliable, and sensitive method for OC isolation and chemical analysis, providing a robust methodology for future endeavors in single-cell analyses.

Capillarity Enabled Large-Array Liquid Metal Electrodes for Compact and High-Throughput Dielectrophoretic Microfluidics

Dielectrophoresis (DEP) particle separation has label-free, well-controllable, and low-damage merits. Sidewall microelectrodes made of liquid metal alloy (LMA) inherits the additional advantage of thick electrodes to generate impactful DEP force. However, existing LMA electrode-based devices lack the ability to integrate large-array electrodes in a compact footprint, severely limiting flow rate and thus throughput. Herein, a facile and versatile method is proposed to integrate high-density thick LMA electrodes in microfluidic devices, taking advantage of the passive control ability of capillary burst valves (CBVs). CBVs with carefully designed burst pressures are co-designed in microfluidic channels, allowing self-assembly of LMA electrode array through simple hand-push injection. The arrayed electrode configuration brings the accumulative DEP deflection effect. Specifically, The fabricated 5000 pairs of sidewall electrodes in a compact chip are demonstrted to achieve ten times higher throughput in DEP deflection. The 5000-electrode-pair device is applied to successfully separate four mixed samples, including human peripheral blood mononuclear cells and A549 cells with the flow rate of 70 µL min-1. It is envisioned that this work can greatly facilitate LMA electrode array fabrication and offer a robust and versatile platform for DEP separation applications.

Cellular nucleus image-based smarter microscope system for single cell analysis

Cell imaging technology is undoubtedly a powerful tool for studying single-cell heterogeneity due to its non-invasive and visual advantages. It covers microscope hardware, software, and image analysis techniques, which are hindered by low throughput owing to abundant hands-on time and expertise. Herein, a cellular nucleus image-based smarter microscope system for single-cell analysis is reported to achieve high-throughput analysis and high-content detection of cells. By combining the hardware of an automatic fluorescence microscope and multi-object recognition/acquisition software, we have achieved more advanced process automation with the assistance of Robotic Process Automation (RPA), which realizes a high-throughput collection of single-cell images. Automated acquisition of single-cell images has benefits beyond ease and throughout and can lead to uniform standard and higher quality images. We further constructed a single-cell image database-based convolutional neural network (Efficient Convolutional Neural Network, E-CNN) exceeding 20618 single-cell nucleus images. Computational analysis of large and complex data sets enhances the content and efficiency of single-cell analysis with the assistance of Artificial Intelligence (AI), which breaks through the super-resolution microscope's hardware limitation, such as specialized light sources with specific wavelengths, advanced optical components, and high-performance graphics cards. Our system can identify single-cell nucleus images that cannot be artificially distinguished with an accuracy of 95.3%. Overall, we build an ordinary microscope into a high-throughput analysis and high-content smarter microscope system, making it a candidate tool for Imaging cytology.

Lysosomes Initiating and DNAzyme-Assisted Intracellular Signal Amplification Strategy for Quantification of Alpha-Fetoprotein in a Single Cell

Cellular trace proteins are critical for maintaining normal cell functions, with their quantitative analysis in individual cells aiding our understanding of the role of cell proteins in biological processes. This study proposes a strategy for the quantitative analysis of alpha-fetoprotein in single cells, utilizing a lysosome microenvironment initiation and a DNAzyme-assisted intracellular signal amplification technique based on electrophoretic separation. A nanoprobe targeting lysosomes was prepared, facilitating the intracellular signal amplification of alpha-fetoprotein. Following intracellular signal amplification, the levels of alpha-fetoprotein (AFP) in 20 HepG2 hepatoma cells and 20 normal HL-7702 hepatocytes were individually evaluated using microchip electrophoresis with laser-induced fluorescence detection (MCE-LIF). Results demonstrated overexpression of alpha-fetoprotein in hepatocellular carcinoma cells. This strategy represents a novel technique for single-cell protein analysis and holds significant potential as a powerful tool for such analyses.

High-throughput droplet microfluidics screening and genome sequencing analysis for improved amylase-producing Aspergillus oryzae

BACKGROUND

The exceptional protein secretion capacity, intricate post-translational modification processes, and inherent safety features of A. oryzae make it a promising expression system. However, heterologous protein expression levels of existing A. oryzae species cannot meet the requirement for industrial-scale production. Therefore, establishing an efficient screening technology is significant for the development of the A. oryzae expression system.

RESULTS

In this work, a high-throughput screening method suitable for A. oryzae has been established by combining the microfluidic system and flow cytometry. Its screening efficiency can reach 350 droplets per minute. The diameter of the microdroplet was enlarged to 290 µm to adapt to the polar growth of A. oryzae hyphae. Through enrichment and screening from approximately 450,000 droplets within 2 weeks, a high-producing strain with α-amylase increased by 6.6 times was successfully obtained. Furthermore, 29 mutated genes were identified by genome resequencing of high-yield strains, with 15 genes subjected to editing and validation. Two genes may individually influence α-amylase expression in A. oryzae by affecting membrane-associated multicellular processes and regulating the transcription of related genes.

CONCLUSIONS

The developed high-throughput screening strategy provides a reference for other filamentous fungi and Streptomyces. Besides, the strains with different excellent characteristics obtained by efficient screening can also provide materials for the analysis of genetic and regulatory mechanisms in the A. oryzae expression system.

Insights into In Vivo Environmental Effects on Quantitative Biochemistry in Single Cells

Biomacromolecules exist and function in a crowded and spatially confined intracellular milieu. Single-cell analysis has been an essential tool for deciphering the molecular mechanisms of cell biology and cellular heterogeneity. However, a sound understanding of in vivo environmental effects on single-cell quantification has not been well established. In this study, via cell mimicking with giant unilamellar vesicles and single-cell analysis by an approach called plasmonic immunosandwich assay (PISA) that we developed previously, we investigated the effects of two in vivo environmental factors, i.e., molecular crowding and spatial confinement, on quantitative biochemistry in the cytoplasm of single cells. We find that molecular crowding greatly affects the biomolecular interactions and immunorecognition-based detection while the effect of spatial confinement in cell-sized space is negligible. Without considering the effect of molecular crowding, the results by PISA were found to be apparently under-quantitated, being only 29.5-50.0% of those by the calibration curve considering the effect of molecular crowding. We further demonstrated that the use of a calibration curve established with standard solutions containing 20% (wt) polyethylene glycol 6000 can well offset the effect of intracellular crowding and thereby provide a simple but accurate calibration for the PISA measurement. Thus, this study not only sheds light on how intracellular environmental factors influence biomolecular interactions and immunorecognition-based single-cell quantification but also provides a simple but effective strategy to make the single-cell analysis more accurate.

Multiphase Chemistry under Nanoconfinement: An Electrochemical Perspective

Most relevant systems of interest to modern chemists rarely consist of a single phase. Real-world problems that require a rigorous understanding of chemical reactivity in multiple phases include the development of wearable and implantable biosensors, efficient fuel cells, single cell metabolic characterization techniques, and solar energy conversion devices. Within all of these systems, confinement effects at the nanoscale influence the chemical reaction coordinate. Thus, a fundamental understanding of the nanoconfinement effects of chemistry in multiphase environments is paramount. Electrochemistry is inherently a multiphase measurement tool reporting on a charged species traversing a phase boundary. Over the past 50 years, electrochemistry has witnessed astounding growth. Subpicoampere current measurements are routine, as is the study of single molecules and nanoparticles. This Perspective focuses on three nanoelectrochemical techniques to study multiphase chemistry under nanoconfinement: stochastic collision electrochemistry, single nanodroplet electrochemistry, and nanopore electrochemistry.

Microwell Confined Electro-Coalescence for Rapid Formation of High-Throughput Droplet Array

Droplet array is widely applied in single cell analysis, drug screening, protein crystallization, etc. This work proposes and validates a method for rapid formation of uniform droplet array based on microwell confined droplets electro-coalescence of screen-printed emulsion droplets, namely electro-coalescence droplet array (ECDA). The electro-coalescence of droplets is according to the polarization induced electrostatic and dielectrophoretic forces, and the dielectrowetting effect. The photolithographically fabricated microwells are highly regular and reproducible, ensuring identical volume and physical confinement to achieve uniform droplet array, and meanwhile the microwell isolation protects the paired water droplets from further fusion and broadens its feasibility to different fluidic systems. Under optimized conditions, a droplet array with an average diameter of 85 µm and a throughput of 106 in a 10 cm × 10 cm chip can be achieved within 5 s at 120 Vpp and 50 kHz. This ECDA chip is validated for various microwell geometries and functional materials. The optimized ECDA are successfully applied for digital viable bacteria counting, showing comparable results to the plate culture counting. Such an ECDA chip, as a digitizable and high-throughput platform, presents excellent potential for high-throughput screening, analysis, absolute quantification, etc.

Ultrafast Subcellular Biolabeling and Bioresponsive Real-Time Monitoring for Targeting Cancer Theranostics

Cell heterogeneity poses a formidable challenge for tumor theranostics, requiring high-resolution strategies for intercellular bioanalysis between single cells. Nanoelectrode-based electrochemical analysis has attracted much attention due to its advantages of label-free characteristics, relatively low cost, and ultra-high resolution for single-cell analysis. Here, we have designed and developed a subcellular biolabeling and bioresponsive real-time monitoring strategy for precise bioimaging-guided cancer diagnosis and theranostics. Our observations revealed the apparent intracellular migration of biosynthetic Au nanoclusters (Au NCs) at different subcellular locations, i.e., from the mitochondria to the mitochondrion-free region in the cytoplasm, which may be helpful for controlling over the biosynthesis of Au NCs. Considering the precise biolabeling advantage of the intracellular biosynthetic Au NCs for biomedical imaging of cancers, it is important to realize the biosynthetic Au NC-enabled precise control in real-time theranostics of cancer cells. Therefore, this work raises the possibility to achieve subcellular monitoring of H2O2 for targeting cancer theranostics, thereby providing a new way to explore the underlying mechanism and imaging-guided tumor theranostics.

Deep learning with microfluidics for on-chip droplet generation, control, and analysis

Droplet microfluidics has gained widespread attention in recent years due to its advantages of high throughput, high integration, high sensitivity and low power consumption in droplet-based micro-reaction. Meanwhile, with the rapid development of computer technology over the past decade, deep learning architectures have been able to process vast amounts of data from various research fields. Nowadays, interdisciplinarity plays an increasingly important role in modern research, and deep learning has contributed greatly to the advancement of many professions. Consequently, intelligent microfluidics has emerged as the times require, and possesses broad prospects in the development of automated and intelligent devices for integrating the merits of microfluidic technology and artificial intelligence. In this article, we provide a general review of the evolution of intelligent microfluidics and some applications related to deep learning, mainly in droplet generation, control, and analysis. We also present the challenges and emerging opportunities in this field.

Microfluidics as a Ray of Hope for Microplastic Pollution

Microplastic (MP) pollution is rising at an alarming rate, imposing overwhelming problems for the ecosystem. The impact of MPs on life and environmental cycles has already reached a point of no return; yet global awareness of this issue and regulations regarding MP exposure could change this situation in favor of human health. Detection and separation methods for different MPs need to be deployed to achieve the goal of reversing the effect of MPs. Microfluidics is a well-established technology that enables to manipulate samples in microliter volumes in an unprecedented manner. Owing to its low cost, ease of operation, and high efficiency, microfluidics holds immense potential to tackle unmet challenges in MP. In this review, conventional MP detection and separation technologies are comprehensively reviewed, along with state-of-the-art examples of microfluidic platforms. In addition, we herein denote an insight into future directions for microfluidics and how this technology would provide a more efficient solution to potentially eradicate MP pollution.

Current advances of Pichia pastoris as cell factories for production of recombinant proteins

Pichia pastoris (syn. Komagataella spp.) has attracted extensive attention as an efficient platform for recombinant protein (RP) production. For obtaining a higher protein titer, many researchers have put lots of effort into different areas and made some progress. Here, we summarized the most recent advances of the last 5 years to get a better understanding of its future direction of development. The appearance of innovative genetic tools and methodologies like the CRISPR/Cas9 gene-editing system eases the manipulation of gene expression systems and greatly improves the efficiency of exploring gene functions. The integration of novel pathways in microorganisms has raised more ideas of metabolic engineering for enhancing RP production. In addition, some new opportunities for the manufacture of proteins have been created by the application of novel mathematical models coupled with high-throughput screening to have a better overview of bottlenecks in the biosynthetic process.

An integrated microfluidics platform with high-throughput single-cell cloning array and concentration gradient generator for efficient cancer drug effect screening

BACKGROUND

Tumor cell heterogeneity mediated drug resistance has been recognized as the stumbling block of cancer treatment. Elucidating the cytotoxicity of anticancer drugs at single-cell level in a high-throughput way is thus of great value for developing precision therapy. However, current techniques suffer from limitations in dynamically characterizing the responses of thousands of single cells or cell clones presented to multiple drug conditions.

METHODS

We developed a new microfluidics-based "SMART" platform that is Simple to operate, able to generate a Massive single-cell array and Multiplex drug concentrations, capable of keeping cells Alive, Retainable and Trackable in the microchambers. These features are achieved by integrating a Microfluidic chamber Array (4320 units) and a six-Concentration gradient generator (MAC), which enables highly efficient analysis of leukemia drug effects on single cells and cell clones in a high-throughput way.

RESULTS

A simple procedure produces 6 on-chip drug gradients to treat more than 3000 single cells or single-cell derived clones and thus allows an efficient and precise analysis of cell heterogeneity. The statistic results reveal that Imatinib (Ima) and Resveratrol (Res) combination treatment on single cells or clones is much more efficient than Ima or Res single drug treatment, indicated by the markedly reduced half maximal inhibitory concentration (IC₅₀). Additionally, single-cell derived clones demonstrate a higher IC₅₀ in each drug treatment compared to single cells. Moreover, primary cells isolated from two leukemia patients are also found with apparent heterogeneity upon drug treatment on MAC.

CONCLUSION

This microfluidics-based "SMART" platform allows high-throughput single-cell capture and culture, dynamic drug-gradient treatment and cell response monitoring, which represents a new approach to efficiently investigate anticancer drug effects and should benefit drug discovery for leukemia and other cancers.

Machine Learning-Driven Multiobjective Optimization: An Opportunity of Microfluidic Platforms Applied in Cancer Research

Cancer metastasis is one of the primary reasons for cancer-related fatalities. Despite the achievements of cancer research with microfluidic platforms, understanding the interplay of multiple factors when it comes to cancer cells is still a great challenge. Crosstalk and causality of different factors in pathogenesis are two important areas in need of further research. With the assistance of machine learning, microfluidic platforms can reach a higher level of detection and classification of cancer metastasis. This article reviews the development history of microfluidics used for cancer research and summarizes how the utilization of machine learning benefits cancer studies, particularly in biomarker detection, wherein causality analysis is useful. To optimize microfluidic platforms, researchers are encouraged to use causality analysis when detecting biomarkers, analyzing tumor microenvironments, choosing materials, and designing structures.

Recent advances in the development of Aspergillus for protein production

Aspergillus had been widely used in the industrial production of recombinant proteins. In addition to the safety and broad substrate utilization spectrum, its efficient post-translational modification and strong protein secretion capacity have significant advantages for developing an excellent protein-producing cell factory in industrial production. However, the difficulties in genetic manipulation of Aspergillus and varying expression levels of different heterologous proteins hampered its further development and application. Recently, the development of CRISPR genome editing and high-throughput screening platforms has facilitated the Aspergillus development of a wide range of modifications and applications. Meanwhile, multi-omics analysis and multiplexed genetic engineering have promoted effective knowledge mining. This paper provides a comprehensive and updated review of these advances, including high-throughput screening, genome editing, protein expression modules, and fermentation optimization. It also highlights and discusses the latest significant progress, aiming to provide a practical guide for implementing Aspergillus as an efficient protein-producing cell factory.

Multiphysics microfluidics for cell manipulation and separation: a review

Multiphysics microfluidics, which combines multiple functional physical processes in a microfluidics platform, is an emerging research area that has attracted increasing interest for diverse biomedical applications. Multiphysics microfluidics is expected to overcome the limitations of individual physical phenomena through combining their advantages. Furthermore, multiphysics microfluidics is superior for cell manipulation due to its high precision, better sensitivity, real-time tunability, and multi-target sorting capabilities. These exciting features motivate us to review this state-of-the-art field and reassess the feasibility of coupling multiple physical processes. To confine the scope of this paper, we mainly focus on five common forces in microfluidics: inertial lift, elastic, dielectrophoresis (DEP), magnetophoresis (MP), and acoustic forces. This review first explains the working mechanisms of single physical phenomena. Next, we classify multiphysics techniques in terms of cascaded connections and physical coupling, and we elaborate on combinations of designs and working mechanisms in systems reported in the literature to date. Finally, we discuss the possibility of combining multiple physical processes and associated design schemes and propose several promising future directions.

Detection and separation of proteins using micro/nanofluidics devices

Microfluidics is the technology or system wherein the behavior of fluids' is studied onto a miniaturized device composed of chambers and tunnels. In biological and biomedical sciences, microfluidic technology/system or device serves as an ultra-high-output approach capable of detecting and separating the biomolecules present even in trace quantities. Given the essential role of protein, the identification and quantification of proteins help understand the various living systems' biological function regulation. Microfluidics has enormous potential to enable biological investigation at the cellular and molecular level and maybe a fair substitution of the sophisticated instruments/equipment used for proteomics, genomics, and metabolomics analysis. The current advancement in microfluidic systems' development is achieving momentum and opening new avenues in developing innovative and hybrid methodologies/technologies. This chapter attempts to expound the micro/nanofluidic systems/devices for their wide-ranging application to detect and separate protein. It covers microfluidic chip electrophoresis, microchip gel electrophoresis, and nanofluidic systems as protein separation systems, while methods such as spectrophotometric, mass spectrometry, electrochemical detection, magneto-resistive sensors and dynamic light scattering (DLS) are discussed as proteins' detection system.

Exploiting machine learning for bestowing intelligence to microfluidics

Intelligent microfluidics is an emerging cross-discipline research area formed by combining microfluidics with machine learning. It uses the advantages of microfluidics, such as high throughput and controllability, and the powerful data processing capabilities of machine learning, resulting in improved systems in biotechnology and chemistry. Compared to traditional microfluidics using manual analysis methods, intelligent microfluidics needs less human intervention, and results in a more user-friendly experience with faster processing. There is a paucity of literature reviewing this burgeoning and highly promising cross-discipline. Therefore, we herein comprehensively and systematically summarize several aspects of microfluidic applications enabled by machine learning. We list the types of microfluidics used in intelligent microfluidic applications over the last five years, as well as the machine learning algorithms and the hardware used for training. We also present the most recent advances in key technologies, developments, challenges, and the emerging opportunities created by intelligent microfluidics.

Microfluidic technology for multiple single-cell capture

Microfluidic devices are widely used in single-cell capture and for pairing single cells or groups of cells for cell-cell interaction analysis; these advances have improved drug screening and cell signal transduction analysis. The complex in vivo environment involves interactions between two cells and among multiple cells of the same or different phenotypes. This study reviewed the core principles and performance of several microfluidic multiple- and single-cell capture methods, namely, the microwell, valve, trap, and droplet methods. The advantages and disadvantages of the methods were compared, and suggestions regarding their application to multiple-cell capture were provided. The results may serve as a reference for research on microfluidic multiple single-cell coculture technology.

Investigation of Different Free Image Analysis Software for High-Throughput Droplet Detection

Droplet microfluidics has revealed innovative strategies in biology and chemistry. This advancement has delivered novel quantification methods, such as droplet digital polymerase chain reaction (ddPCR) and an antibiotic heteroresistance analysis tool. For droplet analysis, researchers often use image-based detection techniques. Unfortunately, the analysis of images may require specific tools or programming skills to produce the expected results. In order to address the issue, we explore the potential use of standalone freely available software to perform image-based droplet detection. We select the four most popular software and classify them into rule-based and machine learning-based types after assessing the software's modules. We test and evaluate the software's (i) ability to detect droplets, (ii) accuracy and precision, and (iii) overall components and supporting material. In our experimental setting, we find that the rule-based type of software is better suited for image-based droplet detection. The rule-based type of software also has a simpler workflow or pipeline, especially aimed for non-experienced users. In our case, CellProfiler (CP) offers the most user-friendly experience for both single image and batch processing analyses.

Proteomics for Low Cell Numbers: How to Optimize the Sample Preparation Workflow for Mass Spectrometry Analysis

Nowadays, massive genomics and transcriptomics data can be generated at the single-cell level. However, proteomics in this setting is still a big challenge. Despite the great improvements in sensitivity and performance of mass spectrometry instruments and the better knowledge on sample preparation processing, it is widely acknowledged that multistep proteomics workflows may lead to substantial sample loss, especially when working with paucicellular samples. Still, in clinical fields, frequently limited sample amounts are available for downstream analysis, thereby hampering comprehensive characterization at protein level. To aim at better protein and peptide recoveries, we compare existing and novel approaches in the multistep sample preparation protocols for mass spectrometry studies, from sample collection, cell lysis, protein quantification, and electrophoresis/staining to protein digestion, peptide recovery, and LC-MS/MS instruments. From this critical evaluation, we conclude that the recent innovations and technologies, together with high quality management of samples, make proteomics on paucicellular samples possible, which will have immediate impact for the proteomics community.

Pushing the detection limits: strategies towards highly sensitive optical-based protein detection

Proteins are one of the main constituents of living cells. Studying the quantities of proteins under physiological and pathological conditions can give valuable insights into health status, since proteins are the functional molecules of life. To be able to detect and quantify low-abundance proteins in biofluids for applications such as early disease diagnostics, sensitive analytical techniques are desired. An example of this application is using proteins as biomarkers for detecting cancer or neurological diseases, which can provide early, lifesaving diagnoses. However, conventional methods for protein detection such as ELISA, mass spectrometry, and western blotting cannot offer enough sensitivity for certain applications. Recent advances in optical-based micro- and nano-biosensors have demonstrated promising results to detect proteins at low quantities down to the single-molecule level, shining lights on their capacities for ultrasensitive disease diagnosis and rare protein detection. However, to date, there is a lack of review articles synthesizing and comparing various optical micro- and nano-sensing methods of enhancing the limits of detections of the antibody-based protein assays. The purpose of this article is to critically review different strategies of improving assay sensitivity using miniaturized biosensors, such as assay miniaturization, improving antibody binding capacity, sample purification, and signal amplification. The pros and cons of different methods are compared, and the future perspectives of this research field are discussed.

Recent Advances in Microfluidically Spun Microfibers for Tissue Engineering and Drug Delivery Applications

In recent years, the unique and tunable properties of microfluidically spun microfibers have led to tremendous advancements for the field of biomedical engineering, which have been applied to areas such as tissue engineering, wound dressing, and drug delivery, as well as cell encapsulation and cell seeding. In this article, we analyze the most recent advances in microfluidics and microfluidically spun microfibers, with an emphasis on biomedical applications. We explore in detail these new and innovative experiments, how microfibers are made, the experimental purpose of making microfibers, and the future work that can be done as a result of these new types of microfibers. We also focus on the applications of various materials used to fabricate microfibers, as well as their many promises and limitations.

Rapid Production of PDMS Microdevices for Electrodriven Separations and Microfluidics by 3D-Printed Scaffold Removal

In our work, we produced PDMS-based microfluidic devices by mechanical removal of 3D-printed scaffolds inserted in PDMS. Two setups leading to the fabrication of monolithic PDMS-based microdevices and bonded (or stamped) PDMS-based microdevices were designed. In the monolithic devices, the 3D-printed scaffolds were fully inserted in the PDMS and then carefully removed. The bonded devices were produced by forming imprints of the 3D-printed scaffolds in PDMS, followed by bonding the PDMS parts to glass slides. All these microfluidic devices were then successfully employed in three proof-of-concept applications: capture of magnetic microparticles, formation of droplets, and isotachophoresis separation of model organic dyes.

Highly Integrated Cell-Imprinted Biomimetic Interface for All-in-One Diagnosis of Heterogeneous Circulating Tumor Cells

Single-cell capture and in situ analysis of circulating tumor cells (CTCs) in blood are of great significance for early cancer diagnosis, prognosis, and individualized treatment. However, designing an all-in-one platform that enables not only efficiently specific isolation of CTCs but also in situ analysis of heterogeneity and drug screening is challenging. Here, a cell-imprinted alginate hydrogel (CIAH) interface with all-in-one functions was developed for the capture, in situ analysis, and drug-response study at a single-cell level. Based on the equivalent morphology and "specific odor" left by template cells and supplemented by natural antibody, the CIAH interface exhibited outstanding performance in isolating CTCs from samples suffering from cancers. Beyond capture, the CIAH interface was also able to serve as a high-throughput platform for subpopulation analysis and drug response of heterogeneous CTCs. We demonstrated that the highly integrated multifunctional CIAH interface is a promising new tool for single-cell profiling of phenotypic heterogeneity and guiding of personalized anticancer therapy.

Fabrication Protocol for Thermoplastic Microfluidic Devices: Nanoliter Volume Bioreactors for Cell Culturing

Microfluidic devices consist of microchannels etched or embossed into substrates made of polymer, glass or silicon. Intricate connections of the microchannels to reactors with some smart mechanical structures such as traps or curvatures fulfil the desired functionalities such as mixing, separation, flow control or setting the environment for biochemical reactions. Here, we describe the fabrication methods of a thermoplastic microbioreactor step by step. First, material selection is made, then, production methods are determined with the equipment that can be easily procured in a laboratory. COP with its outstanding characteristics among many polymers was chosen. Two types of microbioreactors, with and without electrodes, are designed with AutoCAD and L-edit softwares. Photolithography and electrochemical wet etching are used for master mold preparation. Thermal evaporator is employed for pure chromium and gold deposition on COP substrate and etchants are used to form the interdigitated electrodes. Once the master mold produced, hot embossing is used to obtain the designed shape on drilled and planarized COP. Cover COP, with or without electrodes, is bonded to the hot embossed COP via thermo-compression and thermoplastic microfluidic device is realized. Tubings are connected to the device and a bridge between the macro and micro world is established. Yeast or mammalian cells labeled or tagged with GFP/RFP on specific gene products are loaded into the microfluidic device, and real time data on cell dimensions and fluorescence intensity are collected using inverted fluorescence microscope, and finally image processing is used to analyze the acquired data.

Construction of a microfluidic platform integrating online protein fractionation, denaturation, digestion, and peptide enrichment

Microfluidic system with multi-functional integration of high-throughput protein/peptide separation ability has great potential for improving the identification capacity of biological samples in proteomics. In this paper, a sample treatment platform was constructed by integrating reversed phase chromatography, immobilized enzyme reactor (IMER) and imprinted monolith through a microfluidic chip to achieve the online proteins fractionation, denaturation, digestion and peptides enrichment. We firstly synthesized a poly-allyl phenoxyacetate (AP) monolith and a lysine-glycine-glycine (KGG) imprinted monolith separately, and investigated in detail their performance in fractionating proteins and extracting KGG from the protein digests of MCF-7 cell. The removal percentage of 94.6% for MCF-7 cell protein and the recovery of 90.8% for KGG were obtained. The number of proteins and peptides identified on this microfluidic platform was 2,004 and 8,797, respectively, which was 2.8-fold and 3.0-fold higher than that of untreatment sample. The time consumed by this platform for a sample treatment was about 9.6 h, less than that of conventional method (approximate 13.3 h). In addition, this platform can enrich some peptide fragments containing KGG based on imprinted monolith, which can be served for the identification of ubiquitin-modified proteomics. The successful construction of this integrated microfluidic platform provides a considerable and efficient technical tool for simultaneous identification of proteomics and post-translational modification proteomics information.

Enhanced single-cell encapsulation in microfluidic devices: From droplet generation to single-cell analysis

Single-cell analysis to investigate cellular heterogeneity and cell-to-cell interactions is a crucial compartment to answer key questions in important biological mechanisms. Droplet-based microfluidics appears to be the ideal platform for such a purpose because the compartmentalization of single cells into microdroplets offers unique advantages of enhancing assay sensitivity, protecting cells against external stresses, allowing versatile and precise manipulations over tested samples, and providing a stable microenvironment for long-term cell proliferation and observation. The present Review aims to give a preliminary guidance for researchers from different backgrounds to explore the field of single-cell encapsulation and analysis. A comprehensive and introductory overview of the droplet formation mechanism, fabrication methods of microchips, and a myriad of passive and active encapsulation techniques to enhance single-cell encapsulation efficiency were presented. Meanwhile, common methods for single-cell analysis, especially for long-term cell proliferation, differentiation, and observation inside microcapsules, are briefly introduced. Finally, the major challenges faced in the field are illustrated, and potential prospects for future work are discussed.

Advances of Single-Cell Protein Analysis

Proteins play a significant role in the key activities of cells. Single-cell protein analysis provides crucial insights in studying cellular heterogeneities. However, the low abundance and enormous complexity of the proteome posit challenges in analyzing protein expressions at the single-cell level. This review summarizes recent advances of various approaches to single-cell protein analysis. We begin by discussing conventional characterization approaches, including fluorescence flow cytometry, mass cytometry, enzyme-linked immunospot assay, and capillary electrophoresis. We then detail the landmark advances of microfluidic approaches for analyzing single-cell protein expressions, including microfluidic fluorescent flow cytometry, droplet-based microfluidics, microwell-based assay (microengraving), microchamber-based assay (barcoding microchips), and single-cell Western blotting, among which the advantages and limitations are compared. Looking forward, we discuss future research opportunities and challenges for multiplexity, analyte, throughput, and sensitivity of the microfluidic approaches, which we believe will prompt the research of single-cell proteins such as the molecular mechanism of cell biology, as well as the clinical applications for tumor treatment and drug development.

Injection Molded Microfluidics for Establishing High-Density Single Cell Arrays in an Open Hydrogel Format

Here, we develop an injection molded microfluidic approach for single cell analysis by making use of (1) rapidly curing injectable hydrogels, (2) a high density microfluidic weir trap array, and (3) reversibly bonded PDMS lids that are strong enough to withstand the injection molding process, but which can be peeled off after the hydrogel sets. This approach allows for single cell patterns to be created with densities exceeding 40 cells per mm2, is amenable to high speed imaging, and creates microfluidic devices that enable efficient nutrient and gas exchange and the delivery of specific biological and chemical reagents to individual cells. We show that it is possible to organize up to 10 000 single cells in a few minutes on the device, and we developed an image analysis program to automatically analyze the single-cell capture efficiency. The results show single cell trapping rates were better than 80%. We also demonstrate that the genomic DNA of the single cells trapped in the hydrogel can be amplified via localized, multiple displacement amplification in a massively parallel format, which offers a promising strategy for analyzing single cell genomes. Finally, we show the ability to perform selective staining of individual cells with a commercial bioprinter, providing proof of concept of its ability to deliver tailored reagents to specific cells in an array for future downstream analysis. This injection molded microfluidic approach leverages the benefits of both closed and open microfluidics, allows multiday single cell cultures, direct access to the trapped cells for genotypic end point studies.

High-Throughput Screening Technology in Industrial Biotechnology

Based on the development of automatic devices and rapid assay methods, various high-throughput screening (HTS) strategies have been established for improving the performance of industrial microorganisms. We discuss the most significant factors that can improve HTS efficiency, including the construction of screening libraries with high diversity and the use of new detection methods to expand the search range and highlight target compounds. We also summarize applications of HTS for enhancing the performance of industrial microorganisms. Current challenges and potential improvements to HTS in industrial biotechnology are discussed in the context of rapid developments in synthetic biology, nanotechnology, and artificial intelligence. Rational integration will be an important driving force for constructing more efficient industrial microorganisms with wider applications in biotechnology.