Raman-Activated, Interactive Sorting of Isotope-Labeled Bacteria

Due to its high spatial resolution, Raman microspectroscopy allows for the analysis of single microbial cells. Since Raman spectroscopy analyzes the whole cell content, this method is phenotypic and can therefore be used to evaluate cellular changes. In particular, labeling with stable isotopes (SIPs) enables the versatile use and observation of different metabolic states in microbes. Nevertheless, static measurements can only analyze the present situation and do not allow for further downstream evaluations. Therefore, a combination of Raman analysis and cell sorting is necessary to provide the possibility for further research on selected bacteria in a sample. Here, a new microfluidic approach for Raman-activated continuous-flow sorting of bacteria using an optical setup for image-based particle sorting with synchronous acquisition and analysis of Raman spectra for making the sorting decision is demonstrated, showing that active cells can be successfully sorted by means of this microfluidic chip.

Illuminating the Tiny World: A Navigation Guide for Proper Raman Studies on Microorganisms

Raman spectroscopy is an emerging method for the identification of bacteria. Nevertheless, a lot of different parameters need to be considered to establish a reliable database capable of identifying real-world samples such as medical or environmental probes. In this review, the establishment of such reliable databases with the proper design in microbiological Raman studies is demonstrated, shining a light into all the parts that require attention. Aspects such as the strain selection, sample preparation and isolation requirements, the phenotypic influence, measurement strategies, as well as the statistical approaches for discrimination of bacteria, are presented. Furthermore, the influence of these aspects on spectra quality, result accuracy, and read-out are discussed. The aim of this review is to serve as a guide for the design of microbiological Raman studies that can support the establishment of this method in different fields.

High-Frequency Dielectrophoresis Reveals That Distinct Bio-Electric Signatures of Colorectal Cancer Cells Depend on Ploidy and Nuclear Volume

Aneuploidy, or an incorrect chromosome number, is ubiquitous among cancers. Whole-genome duplication, resulting in tetraploidy, often occurs during the evolution of aneuploid tumors. Cancers that evolve through a tetraploid intermediate tend to be highly aneuploid and are associated with poor patient prognosis. The identification and enrichment of tetraploid cells from mixed populations is necessary to understand the role these cells play in cancer progression. Dielectrophoresis (DEP), a label-free electrokinetic technique, can distinguish cells based on their intracellular properties when stimulated above 10 MHz, but DEP has not been shown to distinguish tetraploid and/or aneuploid cancer cells from mixed tumor cell populations. Here, we used high-frequency DEP to distinguish cell subpopulations that differ in ploidy and nuclear size under flow conditions. We used impedance analysis to quantify the level of voltage decay at high frequencies and its impact on the DEP force acting on the cell. High-frequency DEP distinguished diploid cells from tetraploid clones due to their size and intracellular composition at frequencies above 40 MHz. Our findings demonstrate that high-frequency DEP can be a useful tool for identifying and distinguishing subpopulations with nuclear differences to determine their roles in disease progression.

Current Methods for Extraction and Concentration of Foodborne Bacteria with Glycan-Coated Magnetic Nanoparticles: A Review

Rapid and accurate food pathogen detection is an essential step to preventing foodborne illnesses. Before detection, removal of bacteria from the food matrix and concentration to detectable levels are often essential steps. Although many reviews discuss rapid concentration methods for foodborne pathogens, the use of glycan-coated magnetic nanoparticles (MNPs) is often omitted. This review seeks to analyze the potential of this technique as a rapid and cost-effective solution for concentration of bacteria directly from foods. The primary focus is the mechanism of glycan-coated MNP binding, as well as its current applications in concentration of foodborne pathogens. First, a background on the synthesis, properties, and applications of MNPs is provided. Second, synthesis of glycan-coated particles and their theorized mechanism for bacterial adhesion is described. Existing research into extraction of bacteria directly from food matrices is also analyzed. Finally, glycan-coated MNPs are compared to the magnetic separation technique of immunomagnetic separation (IMS) in terms of cost, time, and other factors. At its current state, glycan-coated MNPs require more research to fully identify the mechanism, potential for optimization, and extraction capabilities directly in food matrices. However, current research indicates glycan-coated MNPs are an incredibly cost-effective method for rapid food pathogen extraction and concentration.

Chemometric analysis in Raman spectroscopy from experimental design to machine learning-based modeling

Raman spectroscopy is increasingly being used in biology, forensics, diagnostics, pharmaceutics and food science applications. This growth is triggered not only by improvements in the computational and experimental setups but also by the development of chemometric techniques. Chemometric techniques are the analytical processes used to detect and extract information from subtle differences in Raman spectra obtained from related samples. This information could be used to find out, for example, whether a mixture of bacterial cells contains different species, or whether a mammalian cell is healthy or not. Chemometric techniques include spectral processing (ensuring that the spectra used for the subsequent computational processes are as clean as possible) as well as the statistical analysis of the data required for finding the spectral differences that are most useful for differentiation between, for example, different cell types. For Raman spectra, this analysis process is not yet standardized, and there are many confounding pitfalls. This protocol provides guidance on how to perform a Raman spectral analysis: how to avoid these pitfalls, and strategies to circumvent problematic issues. The protocol is divided into four parts: experimental design, data preprocessing, data learning and model transfer. We exemplify our workflow using three example datasets where the spectra from individual cells were collected in single-cell mode, and one dataset where the data were collected from a raster scanning-based Raman spectral imaging experiment of mice tissue. Our aim is to help move Raman-based technologies from proof-of-concept studies toward real-world applications.

Label-Free Isolation of Exosomes Using Microfluidic Technologies

Exosomes are cell-derived structures packaged with lipids, proteins, and nucleic acids. They exist in diverse bodily fluids and are involved in physiological and pathological processes. Although their potential for clinical application as diagnostic and therapeutic tools has been revealed, a huge bottleneck impeding the development of applications in the rapidly burgeoning field of exosome research is an inability to efficiently isolate pure exosomes from other unwanted components present in bodily fluids. To date, several approaches have been proposed and investigated for exosome separation, with the leading candidate being microfluidic technology due to its relative simplicity, cost-effectiveness, precise and fast processing at the microscale, and amenability to automation. Notably, avoiding the need for exosome labeling represents a significant advance in terms of process simplicity, time, and cost as well as protecting the biological activities of exosomes. Despite the exciting progress in microfluidic strategies for exosome isolation and the countless benefits of label-free approaches for clinical applications, current microfluidic platforms for isolation of exosomes are still facing a series of problems and challenges that prevent their use for clinical sample processing. This review focuses on the recent microfluidic platforms developed for label-free isolation of exosomes including those based on sieving, deterministic lateral displacement, field flow, and pinched flow fractionation as well as viscoelastic, acoustic, inertial, electrical, and centrifugal forces. Further, we discuss advantages and disadvantages of these strategies with highlights of current challenges and outlook of label-free microfluidics toward the clinical utility of exosomes.

Microscale electrokinetic-based analysis of intact cells and viruses

Miniaturized electrokinetic methods have proven to be robust platforms for the analysis and assessment of intact microorganisms, offering short response times and higher integration than their bench-scale counterparts. The present review article discusses three types of electrokinetic-based methodologies: electromigration or motion-based techniques, electrode-based electrokinetics, and insulator-based electrokinetics. The fundamentals of each type of methodology are discussed and relevant examples from recent reports are examined, to provide the reader with an overview of the state-of-the-art on the latest advancements on the analysis of intact cells and viruses with microscale electrokinetic techniques. The concluding remarks discuss the potential applications and future directions.

Particle trapping in electrically driven insulator-based microfluidics: Dielectrophoresis and induced-charge electrokinetics

Electrokinetically driven insulator‐based microfluidic devices represent an attractive option to manipulate particle suspensions. These devices can filtrate, concentrate, separate, or characterize micro and nanoparticles of interest. Two decades ago, inspired by electrode‐based dielectrophoresis, the concept of insulator‐based dielectrophoresis (iDEP) was born. In these microfluidic devices, insulating structures (i.e., posts, membranes, obstacles, or constrictions) built within the channel are used to deform the spatial distribution of an externally generated electric field. As a result, particles suspended in solution experience dielectrophoresis (DEP). Since then, it has been assumed that DEP is responsible for particle trapping in these devices, regardless of the type of voltage being applied to generate the electric field—direct current (DC) or alternating current. Recent findings challenge this assumption by demonstrating particle trapping and even particle flow reversal in devices that prevent DEP from occurring (i.e., unobstructed long straight channels stimulated with a DC voltage and featuring a uniform electric field). The theory introduced to explain those unexpected observations was then applied to conventional “DC‐iDEP” devices, demonstrating better prediction accuracy than that achieved with the conventional DEP‐centered theory. This contribution summarizes contributions made during the last two decades, comparing both theories to explain particle trapping and highlighting challenges to address in the near future.

Analysis of microorganisms with nonlinear electrokinetic microsystems

Nonlinear electrokinetics (EK), specifically electrophoresis of the second kind, dielectrophoresis (DEP) and electrorotation (EROT), have gained significant interest recently for their flexibility and labeless discriminant manner of operation. The current applications of these technologies are a clear advancement from what they were when first discovered, but also still show strong signs of future growth. The present review article presents a discussion of the current uses of microscale nonlinear EK technologies as analytical, sensing, and purification tools for microorganisms. The discussion is focused on some of the latest discoveries with various nonlinear EK microfluidic techniques, such as DEP particle trapping and EROT for particle assessments, for the analysis of microorganisms ranging from viruses to parasites. Along the way, special focus was given to key research articles from within the past two years to provide the most up-to-date knowledge on the current state-of-the-art within the field of microscale EK, and from there, an outlook on where the future of the field is headed is also included.

Comparability of Raman Spectroscopic Configurations: A Large Scale Cross-Laboratory Study

The variable configuration of Raman spectroscopic platforms is one of the major obstacles in establishing Raman spectroscopy as a valuable physicochemical method within real-world scenarios such as clinical diagnostics. For such real world applications like diagnostic classification, the models should ideally be usable to predict data from different setups. Whether it is done by training a rugged model with data from many setups or by a primary-replica strategy where models are developed on a 'primary' setup and the test data are generated on 'replicate' setups, this is only possible if the Raman spectra from different setups are consistent, reproducible, and comparable. However, Raman spectra can be highly sensitive to the measurement conditions, and they change from setup to setup even if the same samples are measured. Although increasingly recognized as an issue, the dependence of the Raman spectra on the instrumental configuration is far from being fully understood and great effort is needed to address the resulting spectral variations and to correct for them. To make the severity of the situation clear, we present a round robin experiment investigating the comparability of 35 Raman spectroscopic devices with different configurations in 15 institutes within seven European countries from the COST (European Cooperation in Science and Technology) action Raman4clinics. The experiment was developed in a fashion that allows various instrumental configurations ranging from highly confocal setups to fibre-optic based systems with different excitation wavelengths. We illustrate the spectral variations caused by the instrumental configurations from the perspectives of peak shifts, intensity variations, peak widths, and noise levels. We conclude this contribution with recommendations that may help to improve the inter-laboratory studies.

Wirelessly powered dielectrophoresis of metal oxide particles using spark-gap Tesla coil

Wirelessly powered dielectrophoresis (DEP) of metal oxide particles was performed using a spark-gap Tesla coil (TC). The main contribution of this work is the simplification of the conventional DEP setup that requires attaching wires directly to the electrodes. Wireless power from the TC generates a high output frequency and voltage, which corresponds to that used for the DEP. Therefore, a spark-gap TC was built and utilized to conduct the DEP process. Metal oxides (ZnO and Fe2 O3 ) were used as targets for the assembly. The results showed that the wirelessly powered DEP technique via a TC was successful in assembling the metal oxide particles. Positive and negative DEP phenomena were observed. Positive DEP occurred during ZnO assembly, making particles chain grow 0.92 mm toward the sparks within 60 s. Negative DEP was observed during Fe2 O3 assembly, where the repulsion of particles formed a void around the sparks with a 1.45 mm radius. The mechanism of this wireless DEP system is discussed.

Classification of pathogens by Raman spectroscopy combined with generative adversarial networks

Rapid identification of marine pathogens is very important in marine ecology. Artificial intelligence combined with Raman spectroscopy is a promising choice for identifying marine pathogens due to its rapidity and efficiency. However, considering the cost of sample collection and the challenging nature of the experimental environment, only limited spectra are typically available to build a classification model, which hinders qualitative analysis. In this paper, we propose a novel method to classify marine pathogens by means of Raman spectroscopy combined with generative adversarial networks (GANs). Three marine strains, namely, Staphylococcus hominis, Vibrio alginolyticus, and Bacillus licheniformis, were cultured. Using Raman spectroscopy, we acquired 100 spectra of each strain, and we fitted them into GAN models for training. After 30,000 training iterations, the spectra generated by G were similar to the actual spectra, and D was used to test the accuracy of the spectra. Our results demonstrate that our method not only improves the accuracy of machine learning classification but also solves the problem of requiring a large amount of training data. Moreover, we have attempted to find potential identifying regions in the Raman spectra that can be used for reference in subsequent related work in this field. Therefore, this method has tremendous potential to be developed as a tool for pathogen identification.

Determination of Dielectric Properties of Cells using AC Electrokinetic-based Microfluidic Platform: A Review of Recent Advances

Cell dielectric properties, a type of intrinsic property of cells, can be used as electrophysiological biomarkers that offer a label-free way to characterize cell phenotypes and states, purify clinical samples, and identify target cancer cells. Here, we present a review of the determination of cell dielectric properties using alternating current (AC) electrokinetic-based microfluidic mechanisms, including electro-rotation (ROT) and dielectrophoresis (DEP). The review covers theoretically how ROT and DEP work to extract cell dielectric properties. We also dive into the details of differently structured ROT chips, followed by a discussion on the determination of cell dielectric properties and the use of these properties in bio-related applications. Additionally, the review offers a look at the future challenges facing the AC electrokinetic-based microfluidic platform in terms of acquiring cell dielectric parameters. Our conclusion is that this platform will bring biomedical and bioengineering sciences to the next level and ultimately achieve the shift from lab-oriented research to real-world applications.

Self-aligned microfluidic contactless dielectrophoresis device fabricated by single-layer imprinting on cyclic olefin copolymer

The trapping and deflection of biological cells by dielectrophoresis (DEP) at field non-uniformities in a microfluidic device is often conducted in a contactless dielectrophoresis (cDEP) mode, wherein the electrode channel is in a different layer than the sample channel, so that field penetration through the interceding barrier causes DEP above critical cut-off frequencies. In this manner, through physical separation of the electrode and sample channels, it is possible to spatially modulate electric fields with no electrode-induced damage to biological cells in the sample channel. However, since this device requires interlayer alignment of the electrode to sample channel and needs to maintain a thin interceding barrier (~ 15 μm) over the entire length over which DEP is needed (~ 1 cm), variations in alignment and microstructure fidelity cause wide variations in cDEP trapping level and frequency response across devices. We present a strategy to eliminate interlayer alignment by fabricating self-aligned electrode and sample channels, simultaneously with the interceding barrier layer (14-μm width and 50-μm depth), using a single-layer imprint and bond process on cyclic olefin copolymer. Specifically, by designing support structures, we preserve fidelity of the high aspect ratio insulating posts in the sample channel and the interceding barrier between the sample and electrode channels over the entire device footprint (~ 1 cm). The device operation is validated based on impedance measurements to quantify field penetration through the interceding barrier and by DEP trapping measurements. The presented fabrication strategy can eventually improve cDEP device manufacturing protocols to enable more reproducible DEP performance. Graphical abstract.

Effect of growth media and phase on Raman spectra and discrimination of mycobacteria

When developing a Raman spectral library to identify bacteria, differences between laboratory and real world conditions must be considered. For example, culturing bacteria in laboratory settings is performed under conditions for ideal bacteria growth. In contrast, culture conditions in the human body may differ and may not support optimized bacterial growth. To address these differences, researchers have studied the effect of conditions such as growth media and phase on Raman spectra. However, the majority of these studies focused on Gram-positive or Gram-negative bacteria. This article focuses on the influence of growth media and phase on Raman spectra and discrimination of mycobacteria, an acid-fast genus. Results showed that spectral differences from growth phase and media can be distinguished by spectral observation and multivariate analysis. Results were comparable to those found for other types of bacteria, such as Gram-positive and Gram-negative. In addition, the influence of growth phase and media had a significant impact on machine learning models and their resulting classification accuracy. This study highlights the need for machine learning models and their associated spectral libraries to account for various growth parameters and stages to further the transition of Raman spectral analysis of bacteria from laboratory to clinical settings.