Millions Of Droplets Research Articles

Combining Acoustic Bioprinting with AI-Assisted Raman Spectroscopy for High-Throughput Identification of Bacteria in Blood.

Identifying pathogens in complex samples such as blood, urine, and wastewater is critical to detect infection and inform optimal treatment. Surface-enhanced Raman spectroscopy (SERS) and machine learning (ML) can distinguish among multiple pathogen species, but processing complex fluid samples to sensitively and specifically detect pathogens remains an outstanding challenge. Here, we develop an acoustic bioprinter to digitize samples into millions of droplets, each containing just a few cells, which are identified with SERS and ML. We demonstrate rapid printing of 2 pL droplets from solutions containing S. epidermidis, E. coli, and blood; when they are mixed with gold nanorods (GNRs), SERS enhancements of up to 1500× are achieved.We then train a ML model and achieve ≥99% classification accuracy from cellularly pure samples and ≥87% accuracy from cellularly mixed samples. We also obtain ≥90% accuracy from droplets with pathogen:blood cell ratios <1. Our combined bioprinting and SERS platform could accelerate rapid, sensitive pathogen detection in clinical, environmental, and industrial settings.

Droplet Detection and Sorting System in Microfluidics: A Review.

Since being invented, droplet microfluidic technologies have been proven to be perfect tools for high-throughput chemical and biological functional screening applications, and they have been heavily studied and improved through the past two decades. Each droplet can be used as one single bioreactor to compartmentalize a big material or biological population, so millions of droplets can be individually screened based on demand, while the sorting function could extract the droplets of interest to a separate pool from the main droplet library. In this paper, we reviewed droplet detection and active sorting methods that are currently still being widely used for high-through screening applications in microfluidic systems, including the latest updates regarding each technology. We analyze and summarize the merits and drawbacks of each presented technology and conclude, with our perspectives, on future direction of development.

Combination of high-throughput microfluidics and FACS technologies to leverage the numbers game in natural product discovery.

SummaryHigh‐throughput platforms facilitating screening campaigns of environmental samples are needed to discover new products of natural origin counteracting the spreading of antimicrobial resistances constantly threatening human and agricultural health. We applied a combination of droplet microfluidics and fluorescence‐activated cell sorting (FACS)‐based technologies to access and assess a microbial environmental sample. The cultivation performance of our microfluidics workflow was evaluated in respect to the utilized cultivation media by Illumina amplicon sequencing of a pool of millions of droplets, respectively. This enabled the rational selection of a growth medium supporting the isolation of microbial diversity from soil (five phyla affiliated to 57 genera) including a member of the acidobacterial subgroup 1 (genus Edaphobacter). In a second phase, the entire diversity covered by 1071 cultures was used for an arrayed bioprospecting campaign, resulting in > 6000 extracts tested against human pathogens and agricultural pests. After redundancy curation by using a combinatorial chemical and genomic fingerprinting approach, we assigned the causative agents present in the extracts. Utilizing UHPLC‐QTOF‐MS/MS‐guided fractionation and microplate‐based screening assays in combination with molecular networking the production of bioactive ionophorous macrotetrolides, phospholipids, the cyclic lipopetides massetolides E, F, H and serratamolide A and many derivatives thereof was shown.

PSV-14 Genome Centric Approaches to Understand Antimicrobial Resistance in the Rumen Microbiome

Abstract Global meat and milk demands are projected to increase by 50% by the year 2050, making a highly efficient cattle industry a top priority. Widespread use of antibiotics over the last 70 years has led to increases in antibiotic resistance genes (ARGs) in microbial populations, posing health risks to animal and human populations. Thus, a thorough understanding of where antibiotic resistance genes reside in microbial ecosystems surrounding livestock is paramount in developing strategies to mitigate transfer of antibiotic resistance. Recent advances in metagenome sequencing have made it possible to predict microbial genomes from shotgun metagenome datasets. However, genomes binned from metagenome data are often smaller than genomes from pure cultures, omitting genetic information that is not part of the core genome e.g. antibiotic resistance. This study uses a new linked-read metagenome sequencing approach, partitioning long fragments of DNA (&amp;gt;40Kbp) into millions of droplets which are individually barcoded giving each strand a unique index, improving metagenome assembly and increasing access to genetic information pertaining to antibiotic resistance. Rumen samples from four animals which received daily antibiotics in feed as well as antibiotic injections were pooled for linked-read metagenome sequencing. Additionally, soil samples from the animal pen were collected from three locations and pooled for analysis. Linked-read sequencing reads were assembled using MEGAHIT and ATHENA assemblers (N50 &amp;gt; 2702bp, 578,838 contigs &amp;gt;1000bp). Metagenome assembled genomes (MAGs) were binned using MetaBAT2, yielding 341 genome bins. Of these, 144 bins were of intermediate to high quality (&amp;gt;70% completeness, &amp;lt; 10% contamination), 79 genomes from rumen and 65 from soil samples, respectively. Genomes were scanned for ARGs (ABRicate), revealing 12 genomes containing ARGs, 5 from rumen, 7 from soil. MAGs possessed genes conferring resistance to penicillin, macrolide, nitroimidazole, aminoglycoside, and tetracycline class antibiotics, helping uncover information about where ARGs are sequestered in their respective environments. USDA is an equal opportunity provider and employer.

Effect of steam velocity during dropwise condensation

Dropwise condensation (DWC) is a complex phenomenon involving droplets nucleation, coalescence and motion. Starting from the nanoscale up to the macroscale, DWC involves millions of droplets per square meter. The maximum dimension assumed by a droplet before sliding is characterized by the departing radius: it is the radius at which the droplet starts to sweep through the surface as a consequence of the acting forces (gravity force, adhesion force, drag force induced by the flowing vapor). In the literature, very few works investigate the effect of vapor velocity on the heat transfer coefficient (HTC) and on the droplet departing radius during DWC. Furthermore, the effect of vapor velocity is not accounted for in available DWC models. In the present paper, DWC of steam has been promoted on an aluminum sol-gel coated surface. Heat transfer coefficients and droplets departing diameters have been measured at 107 °C saturation temperature, heat flux of 335 kW m−2 and average vapor velocity between 2.7 m s−1 and 11 m s−1. A method for the estimation of the droplet departing radius in presence of non-negligible vapor velocity is here proposed. The equation accounting for vapor velocity has been included in the model by Miljkovic et al. [1] for heat transfer coefficient prediction during DWC and has been assessed using the present data and two other datasets from independent laboratories.

Xdrop: Targeted sequencing of long DNA molecules from low input samples using droplet sorting.

Long‐read sequencing can resolve regions of the genome that are inaccessible to short reads, and therefore are ideal for genome‐gap closure, solving structural rearrangements and sequencing through repetitive elements. Here we introduce the Xdrop technology: a novel microfluidic‐based system that allows for targeted enrichment of long DNA molecules starting from only a few nanograms of DNA. Xdrop is based on the isolation of long DNA fragments in millions of droplets, where the droplets containing a target sequence of interest are fluorescently labeled and sorted using flow cytometry. The final product from the Xdrop procedure is an enriched population of long DNA molecules that can be investigated by sequencing. To demonstrate the capability of Xdrop, we performed enrichment of the human papilloma virus 18 integrated into the genome of human HeLa cells. Analysis of the sequencing reads resolved three HPV18‐chr8 integrations at base‐pair resolution, and the captured fragments extended up to 30 kb into the human genome at the integration sites. Further, we enriched the complete TP53 locus in a leukemia cell line and could successfully phase coexisting mutations using PacBio sequencing. In summary, our results show that Xdrop is an efficient enrichment technology for studying complex genomic regions.

Coding of Experimental Conditions in Microfluidic Droplet Assays Using Colored Beads and Machine Learning Supported Image Analysis.

To efficiently exploit the potential of several millions of droplets that can be considered as individual bioreactors in microfluidic experiments, methods to encode different experimental conditions in droplets are needed. The approach presented here is based on coencapsulation of colored polystyrene beads with biological samples. The decoding of the droplets, as well as content quantification, are performed by automated analysis of triggered images of individual droplets in-flow using bright-field microscopy. The decoding strategy combines bead classification using a random forest classifier and Bayesian inference to identify different codes and thus experimental conditions. Antibiotic susceptibility testing of nine different antibiotics and the determination of the minimal inhibitory concentration of a specific antibiotic against a laboratory strain of Escherichia coli are presented as a proof-of-principle. It is demonstrated that this method allows successful encoding and decoding of 20 different experimental conditions within a large droplet population of more than 105 droplets per condition. The decoding strategy correctly assigns 99.6% of droplets to the correct condition and a method for the determination of minimal inhibitory concentration using droplet microfluidics is established. The current encoding and decoding pipeline can readily be extended to more codes by adding more bead colors or color combinations.

Integrated, Continuous Emulsion Creamer.

Automated and reproducible sample handling is a key requirement for high-throughput compound screening and currently demands heavy reliance on expensive robotics in screening centers. Integrated droplet microfluidic screening processors are poised to replace robotic automation by miniaturizing biochemical reactions to the droplet scale. These processors must generate, incubate, and sort droplets for continuous droplet screening, passively handling millions of droplets with complete uniformity, especially during the key step of sample incubation. Here, we disclose an integrated microfluidic emulsion creamer that packs ("creams") assay droplets by draining away excess oil through microfabricated drain channels. The drained oil coflows with creamed emulsion and then reintroduces the oil to disperse the droplets at the circuit terminus for analysis. Creamed emulsion assay incubation time dispersion was 1.7%, 3-fold less than other reported incubators. The integrated, continuous emulsion creamer (ICEcreamer) was used to miniaturize and optimize measurements of various enzymatic activities (phosphodiesterase, kinase, bacterial translation) under multiple- and single-turnover conditions. Combining the ICEcreamer with current integrated microfluidic DNA-encoded library bead processors eliminates potentially cumbersome instrumentation engineering challenges and is compatible with assays of diverse target class activities commonly investigated in drug discovery.

Controlled droplet microfluidic systems for multistep chemical and biological assays.

Droplet microfluidics is a relatively new and rapidly evolving field of science focused on studying the hydrodynamics and properties of biphasic flows at the microscale, and on the development of systems for practical applications in chemistry, biology and materials science. Microdroplets present several unique characteristics of interest to a broader research community. The main distinguishing features include (i) large numbers of isolated compartments of tiny volumes that are ideal for single cell or single molecule assays, (ii) rapid mixing and negligible thermal inertia that all provide excellent control over reaction conditions, and (iii) the presence of two immiscible liquids and the interface between them that enables new or exotic processes (the synthesis of new functional materials and structures that are otherwise difficult to obtain, studies of the functions and properties of lipid and polymer membranes and execution of reactions at liquid-liquid interfaces). The most frequent application of droplet microfluidics relies on the generation of large numbers of compartments either for ultrahigh throughput screens or for the synthesis of functional materials composed of millions of droplets or particles. Droplet microfluidics has already evolved into a complex field. In this review we focus on 'controlled droplet microfluidics' - a portfolio of techniques that provide convenient platforms for multistep complex reaction protocols and that take advantage of automated and passive methods of fluid handling on a chip. 'Controlled droplet microfluidics' can be regarded as a group of methods capable of addressing and manipulating droplets in series. The functionality and complexity of controlled droplet microfluidic systems can be positioned between digital microfluidics (DMF) addressing each droplet individually using 2D arrays of electrodes and ultrahigh throughput droplet microfluidics focused on the generation of hundreds of thousands or even millions of picoliter droplets that cannot be individually addressed by their location on a chip.

Ultra-high throughput detection (1 million droplets per second) of fluorescent droplets using a cell phone camera and time domain encoded optofluidics.

Droplet-based assays-in which ultra-sensitive molecular measurements are made by performing millions of parallel experiments in picoliter droplets-have generated enormous enthusiasm due to their single molecule resolution and robustness to reaction conditions. These assays have great untapped potential for point of care diagnostics but are currently confined to laboratory settings due to the instrumentation necessary to serially generate, control, and measure tens of millions of droplets. To address this challenge, we have developed the microdroplet megascale detector (μMD) that can generate and detect the fluorescence of millions of droplets per second (1000× faster than conventional approaches) using only a conventional cell phone camera. The key innovation of our approach is borrowed from the telecommunications industry, wherein we modulate the excitation light with a pseudorandom sequence that enables individual droplets to be resolved that would otherwise overlap due to the limited frame rate of digital cameras. Using this approach, the μMD measures droplets at a rate of 106 droplets per sec (ϕ = 166 mL h-1) in 120 parallel microfluidic channels and achieves a limit of detection LOD = 1 μM Rhodamine dye, sufficient for typical droplet based assays. We incorporate this new droplet detection technology with our previously reported parallelized droplet production strategy, incorporating 200 parallel droplet makers and only one set of continuous and droplet phase inputs and one output line. By miniaturizing and integrating droplet based diagnostics into a handheld format, the μMD platform can translate ultra-sensitive droplet based assays into a self-contained platform for practical use in clinical and industrial settings.

Recent Development of Droplet Microfluidics in Digital Polymerase Chain Reaction

Digital polymerase chain reaction (PCR) has been experiencing a rapid development during the past few years. Compared with the traditional qPCR, the accuracy of digital PCR for the absolute quantification of target gene has been significantly improved with the same primer and probe as qPCR. The development of digital PCR is directly related to the development of microfluidics. The integrated fluid circuit, which has a complicated fabrication process with high cost, is an early integration of the microfluidics and digital PCR. Recently, researchers are trying to apply the droplet microfluidics in digital PCR. A droplet microfluidic chip is able to generate millions of droplets within a short time. Each of these droplets containing no more than one target gene is a reaction chamber during the amplification process. After amplification, each droplet is tested to obtain the absolute quantification of the target gene. This paper reviews the recent progress of droplet digital PCR and the application of droplet digital PCR in biological, medical and environmental area.

A Phenomenological Model for Predicting Entropy Generation during Vaporization of Droplets in Engine Fuel Sprays

Modern internal combustion (IC) engines employ a variety of injection techniques for preparing a combustible mixture of fuel and air. In a fuel injection-based system, the vaporization of the atomized hydrocarbon fuel droplets has significant influence on engine performance and emissions. The entropy generation associated with droplet vaporization is particularly important as it is directly related to the destruction of exergy i.e. the potential to produce useful work. Since a fuel spray could involve millions of droplets, solving the entire set of governing equations for individual droplets in a spatiotemporally discretized domain is impractical. The present work explores the utility of a simple phenomenological model in predicting the entropy generation history. The results indicate that this model ensures computational efficiency without much sacrifice in accuracy.

Functional Protein Microarrays by Electrohydrodynamic Jet Printing

This paper reports the use of advanced forms of electrohydrodynamic jet (e-jet) printing for creating micro- and nanoscale patterns of proteins on various surfaces ranging from flat silica substrates to structured plasmonic crystals, suitable for micro/nanoarray analysis and other applications in both fluorescent and plasmonic detection modes. The approaches function well with diverse classes of proteins, including streptavidin, IgG, fibrinogen, and γ-globulin. Detailed study reveals that the printing process does not adversely alter the protein structure or function, as demonstrated in the specific case of streptavidin through measurements of its binding specificity to biotin-modified DNA. Multinozzle printing systems enable several types of proteins (up to four currently) to be patterned on a single substrate, in rapid fashion and with excellent control over spatial dimensions and registration. High-speed, pulsed operational modes allow large-area printing, with narrow statistical distributions of drop size and spacing in patterns that include millions of droplets. The process is also compatible with the structured surfaces of plasmonic crystal substrates to enable detection without fluorescence. These collective characteristics suggest potential utility of e-jet techniques in wide-ranging areas of biotechnology, where its compatibility with various biomaterials and substrates with different topographies and surface chemistries, and ability to form deposits that range from thick films to submonolayer coatings, derive from the remote, noncontacting physical material transfer mode of operation.

Novel microfluidic technologies for portable diagnostics systems

Novel microfluidic technologies being developed for portable diagnostic systems have potential for use in TB serodiagnosis or as platforms for cell and biomolecular assays. Using microfluidics, with its miniaturized channels and reservoirs for portable devices, offers many advantages, including: high surface-to-volume ratio; a low Reynolds number; increased speed of reaction; reduced cost of reagents; decreased cost of power consumption; precise mixing/dosage and heating. Its integration capability offers advantages as well, such as low manufacturing cost and multiplex capability, i.e. an increased number of parameters can be monitored per sample. Two microfluidic platforms may be helpful in protein microarray analysis. Microfluidic electrical sensing platforms are capable of detecting antigen/antibody binding in real time. The development of this platform will allow for faster detection of certain diseases with a patient’s sample compared to standard techniques such as ELISA. This platform requires microchannel-sealed microarrays with electrical detection capability. By measuring electrical charges, the scientists can determine protein-binding activity. Additionally, microfluidic colorimetric platforms are being developed using acoustic micromixing instead of fluorescence scanning. The process uses a scanner that detects an enzyme–based change of color that allows measurement of the protein-binding event. Our team is developing these platforms using components that have very small energy requirements, which means the device may not require batteries to operate. A ‘lab-in-a-droplet’ technique using digital microfluidics rather than using microarrays, which produce a static substrate, diffuses samples into as many as millions of droplets, presenting a three-dimensional picoliter reactor array. This process has several advantages including: rapid mixing, homogeneous reactions, precise control of volumes and concentrations, and an ability to mimic cellular reactions. Our team is using this technique in the development of lipoplexes and to encapsulate a cell in a single droplet. Lastly, a platform is under development for cell sorting using electrodes to track cells in order to determine what function the cell will take on. In addition to its value in the diagnosis of TB, microfluidics technology has several other applications, including: broader distribution of new assays to biologic labs, rapid analyses in the field for epidemiologic studies, and the ability to study hybridization of molecules on microarrays. For example, Lab-on-a-chip technologies are an excellent vehicle for integrating diagnostic and therapeutic functions. Digital (droplet) microfluidics enables high throughput cellular and molecular assays and cell sorting technologies enable more practical cellular analyses and therapies.

Cloud Droplet Growth by Condensation in Homogeneous Isotropic Turbulence

AbstractThe growth of cloud droplets by diffusion of water vapor in a three-dimensional homogeneous isotropic turbulent flow is considered. Within a simple model of advection and condensation, the dynamics and growth of millions of droplets are integrated. A droplet-size spectra broadening is obtained and it is shown to increase with the Reynolds number of turbulence by means of two series of direct numerical simulations at increasing resolution. This is a key point toward a proper evaluation of the effects of turbulence for condensation in warm clouds, where the Reynolds numbers typically achieve extreme values. The obtained droplet spectral broadening as a function of the Reynolds number is shown to be consistent with dimensional arguments. A generalization of this expectation to Reynolds numbers not accessible by direct numerical simulation (DNS) is proposed, yielding upper and lower bounds to the actual size spectra broadening. It is argued that the lower bound is the relevant limit at high Reynolds numbers. A further DNS matching the large scales of the system suggests consistency of the picture drawn. The assumptions underlying the model are expected to hold up to spatial scales on the order of 100 m; no direct comparison with in situ measures is possible. Additional effort is needed to evaluate the impact of this effect for condensation in more realistic cloud conditions.