Microfluidic cartridges preloaded with nanoliter plugs of reagents: an alternative to 96-well plates for screening

In traditional screening with 96-well plates, microliters of substrates are consumed for each reaction. Further miniaturization is limited by the special equipment and techniques required to dispense nanoliter volumes of fluid. Plug-based microfluidics confines reagents in nanoliter plugs (droplets surrounded by fluorinated carrier fluid), and uses simple pumps to control the flow of plugs. By using cartridges pre-loaded with nanoliter plugs of reagents, only two pumps and a merging junction are needed to set up a screen. Screening with preloaded cartridges uses only nanoliters of substrate per reaction, and requires no microfabrication. The low cost and simplicity of this method has the potential of replacing 96-well and other multi-well plates, and has been applied to enzymatic assays, protein crystallization and optimization of organic reactions

Microgram-scale testing of reaction conditions in solution using nanoliter plugs in microfluidics with detection by MALDI-MS

This paper describes a microfluidic system to screen and optimize organic reaction conditions on a submicrogram scale. The system uses discrete droplets (plugs) as microreactors separated and transported by a continuous phase of a fluorinated carrier fluid. Previously, we demonstrated the use of a microfabricated PDMS plug-based microfluidic system to perform assays and crystallization experiments in aqueous solutions with optical detection. Here, we developed an approach that does not require microfabrication of microfluidic devices, is applicable to synthetic reactions in organic solvents, and uses detection by MALDI-MS. As a demonstration, conditions for selective deacetylation of ouabain hexaacetate were tested, and the optimum conditions for mono-, bis-, or trisdeacetylation have been identified. These conditions were validated by scale-up reactions and isolating these potentially neurotoxic products. Mono- and bisdeacetylated products are unstable intermediates in the deacetylation and were isolated for the first time. This system enables no-loss handling of submicroliter volumes containing a few micrograms of a compound of interest. It could become valuable for investigating or optimizing reactions of precious substrates (e.g., products of long synthetic sequences and natural products that can be isolated only in small quantities)

Reactions in droplets in microfluidic channels

Fundamental and applied research in chemistry and biology benefits from opportunities provided by droplet-based microfluidic systems. These systems enable the miniaturization of reactions by compartmentalizing reactions in droplets of femoliter to microliter volumes. Compartmentalization in droplets provides rapid mixing of reagents, control of the timing of reactions on timescales from milliseconds to months, control of interfacial properties, and the ability to synthesize and transport solid reagents and products. Droplet-based microfluidics can help to enhance and accelerate chemical and biochemical screening, protein crystallization, enzymatic kinetics, and assays. Moreover, the control provided by droplets in microfluidic devices can lead to new scientific methods and insights

Using microfluidics to observe the effect of mixing on nucleation of protein crystals

This paper analyzes the effect of mixing on nucleation of protein crystals. The mixing of protein and precipitant was controlled by changing the flow rate in a plug-based microfluidic system. The nucleation rate inversely depended on the flow rate, and flow rate could be used to control nucleation. For example, at higher supersaturations, precipitation happened at low flow rates while large crystals grew at high flow rates. Mixing at low flow velocities in a winding channel induces nucleation more effectively than mixing in straight channels. A qualitative scaling argument that relies on a number of assumptions is presented to understand the experimental results. In addition to helping fundamental understanding, this result may be used to control nucleation, using rapid chaotic mixing to eliminate formation of precipitates at high supersaturation and using slow chaotic mixing to induce nucleation at lower supersaturation

Analysis of microbial communities in wheat, alfalfa, and oat crops after Tilletia laevis Kühn infection

Common bunt caused by Tilletia laevis Kühn is one of the most serious fungal diseases of wheat. The root–microbial associations play key roles in protecting plants against biotic and abiotic factors. Managing these associations offers a platform for improving the sustainability and efficiency of agriculture production. Here, by using high throughput sequencing, we aimed to identify the bacterial and fungal associations in wheat, alfalfa, and oat crops cultivated in different years in the Gansu province of China. Soil samples (0–6 cm below the surface) from infected wheat by T. laevis had significantly more bacterial and fungal richness than control samples as per the Chao1 analysis. We found some dominant fungi and bacterial phyla in infected wheat by T. laevis, such as Proteobacteria, Acidobacteria, Actinobacteria, Chloroflexi, Ascomycota, Basidiomycota, and Mortierello mycota. We also analyzed the chemical and enzymatic properties of soil samples after T. laevis inoculation. The total nitrogen, total kalium (TK), ammonium nitrogen, available kalium, organic carbon, invertase, phosphatase, and catalase were more in T. laevis-infected samples as compared to the control samples, while pH, total phosphorus, nitrate nitrogen, available phosphorus, and urease were more in control samples compared to T. laevis-infected samples. The results of this study will contribute to the control of wheat common bunt by candidate antagonistic microorganisms and adverse properties of soil

Using three-phase flow of immiscible liquids to prevent coalescence of droplets in microfluidic channels: Criteria to identify the third liquid and validation with protein crystallization

This manuscript describes the effect of interfacial tensions on three-phase liquid-liquid-liquid flow in microfluidic channels and the use of this flow to prevent microfluidic plugs from coalescing. One problem in using microfluidic plugs as microreactors is the coalescence of adjacent plugs caused by the relative motion of plugs during flow. Here, coalescence of reagent plugs was eliminated by using plugs of a third immiscible liquid as spacers to separate adjacent reagent plugs. This work tested the requirements of interfacial tensions for plugs of a third liquid to be effective spacers. Two candidates satisfying the requirements were identified, and one of these liquids was used in the crystallization of protein human Tdp1 to demonstrate its compatibility with protein crystallization in plugs. This method for identifying immiscible liquids for use as a spacer will also be useful for applications involving manipulation of large arrays of droplets in microfluidic channels

Degradable Terpolymers with Alkyl Side Chains Demonstrate Enhanced Gene Delivery Potency and Nanoparticle Stability

Degradable, cationic poly(β-amino ester)s (PBAEs) with alkyl side chains are developed for non-viral gene delivery. Nanoparticles formed from these PBAE terpolymers exhibit significantly enhanced DNA transfection potency and resistance to aggregation. These hydrophobic PBAE terpolymers, but not PBAEs lacking alkyl side chains, support interaction with PEG-lipid conjugates, facilitating their functionalization with shielding and targeting moieties and accelerating the in vivo translation of these materials.National Heart, Lung, and Blood InstituteNational Institutes of Health (U.S.) (Program of Excellence in Nanotechnology (PEN) Award, Contract #HHSN268201000045C)National Institutes of Health (U.S.) (NIH Grant R01-EB000244-27)National Institutes of Health (U.S.) (NIH Grant 5-R01-CA132091-04)National Institutes of Health (U.S.) (NIH Grant R01-DE016516-03)National Science Foundation (U.S.) (Graduate Research Fellowship)Juvenile Diabetes Research Foundation International (Grant 17–2007-1063

SlipChip for immunoassays in nanoliter volumes

This article describes a SlipChip-based approach to perform bead-based heterogeneous immunoassays with multiple nanoliter-volume samples. As a potential device to analyze the output of the chemistrode, the performance of this platform was tested using low concentrations of biomolecules. Two strategies to perform the immunoassay in the SlipChip were tested: (1) a unidirectional slipping method to combine the well containing a sample with a series of wells preloaded with reagents and (2) a back-and-forth slipping method to introduce a series of reagents to a well containing the sample by reloading and slipping the well containing the reagent. The SlipChips were fabricated with hydrophilic surfaces on the interior of the wells and with hydrophobic surfaces on the face of the SlipChip to enhance filling, transferring, and maintaining aqueous solutions in shallow wells. Nanopatterning was used to increase the hydrophobic nature of the SlipChip surface. Magnetic beads containing the capture antibody were efficiently transferred between wells and washed by serial dilution. An insulin immunoenzymatic assay showed a detection of limit of ∼13 pM. A total of 48 droplets of nanoliter volume were analyzed in parallel, including an on-chip calibration. The design of the SlipChip is flexible to accommodate other types of immunoassays, both heterogeneous and homogeneous. This work establishes the possibility of using SlipChip-based immunoassays in small volumes for a range of possible applications, including analysis of plugs from a chemistrode, detection of molecules from single cells, and diagnostic monitoring

Contextual Dictionary Lookup for Knowledge Graph Completion

Knowledge graph completion (KGC) aims to solve the incompleteness of knowledge graphs (KGs) by predicting missing links from known triples, numbers of knowledge graph embedding (KGE) models have been proposed to perform KGC by learning embeddings. Nevertheless, most existing embedding models map each relation into a unique vector, overlooking the specific fine-grained semantics of them under different entities. Additionally, the few available fine-grained semantic models rely on clustering algorithms, resulting in limited performance and applicability due to the cumbersome two-stage training process. In this paper, we present a novel method utilizing contextual dictionary lookup, enabling conventional embedding models to learn fine-grained semantics of relations in an end-to-end manner. More specifically, we represent each relation using a dictionary that contains multiple latent semantics. The composition of a given entity and the dictionary's central semantics serves as the context for generating a lookup, thus determining the fine-grained semantics of the relation adaptively. The proposed loss function optimizes both the central and fine-grained semantics simultaneously to ensure their semantic consistency. Besides, we introduce two metrics to assess the validity and accuracy of the dictionary lookup operation. We extend several KGE models with the method, resulting in substantial performance improvements on widely-used benchmark datasets