Controlled Oil/Water Partitioning of Hydrophobic Substrates Extending the Bioanalytical Applications of Droplet-Based Microfluidics.

Functional annotation of novel proteins lags behind the number of sequences discovered by the next-generation sequencing. The throughput of conventional testing methods is far too low compared to sequencing; thus, experimental alternatives are needed. Microfluidics offer high throughput and reduced sample consumption as a tool to keep up with a sequence-based exploration of protein diversity. The most promising droplet-based systems have a significant limitation: leakage of hydrophobic compounds from water compartments to the carrier prevents their use with hydrophilic reagents. Here, we present a novel approach of substrate delivery into microfluidic droplets and apply it to high-throughput functional characterization of enzymes that convert hydrophobic substrates. Substrate delivery is based on the partitioning of hydrophobic chemicals between the oil and water phases. We applied a controlled distribution of 27 hydrophobic haloalkanes from oil to reaction water droplets to perform substrate specificity screening of eight model enzymes from the haloalkane dehalogenase family. This droplet-on-demand microfluidic system reduces the reaction volume 65 000-times and increases the analysis speed almost 100-fold compared to the classical test tube assay. Additionally, the microfluidic setup enables a convenient analysis of dependences of activity on the temperature in a range of 5 to 90 °C for a set of mesophilic and hyperstable enzyme variants. A high correlation between the microfluidic and test tube data supports the approach robustness. The precision is coupled to a considerable throughput of >20 000 reactions per day and will be especially useful for extending the scope of microfluidic applications for high-throughput analysis of reactions including compounds with limited water solubility.ERC Advanced Investigator grant no. 69566

Fluorescent substrates for haloalkane dehalogenases: Novel probes for mechanistic studies and protein labeling

Haloalkane dehalogenases are enzymes that catalyze the cleavage of carbon-halogen bonds in halogenated compounds. They serve as model enzymes for studying structure-function relationships of >100.000 members of the alpha/beta-hydrolase superfamily. Detailed kinetic analysis of their reaction is crucial for understanding the reaction mechanism and developing novel concepts in protein engineering. Fluorescent substrates, which change their fluorescence properties during a catalytic cycle, may serve as attractive molecular probes for studying the mechanism of enzyme catalysis. In this work, we present the development of the first fluorescent substrates for this enzyme family based on coumarin and BODIPY chromophores. Steady-state and pre-steady-state kinetics with two of the most active haloalkane dehalogenases, DmmA and LinB, revealed that both fluorescent substrates provided specificity constant two orders of magnitude higher (0.14-12.6 mu M(-1)s(-1)) than previously reported representative substrates for the haloalkane dehalogenase family (0.00005-0.014 mu M(-1)s(-1)). Stopped-flow fluorescence/FRET analysis enabled for the first time monitoring of all individual reaction steps within a single experiment: (i) substrate binding, (ii-iii) two subsequent chemical steps and (iv) product release. The newly introduced fluorescent molecules are potent probes for fast steady-state kinetic profiling. In combination with rapid mixing techniques, they provide highly valuable information about individual kinetic steps and mechanism of haloalkane dehalogenases. Additionally, these molecules offer high specificity and efficiency for protein labeling and can serve as probes for studying protein hydration and dynamics as well as potential markers for cell imaging. (C) 2020 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology

Settling for second best: when should doctors agree to parental demands for suboptimal medical treatment?

Background Doctors sometimes encounter parents who object to prescribed treatment for their children, and request suboptimal substitutes be administered instead (suboptimal being defined as less effective and/or more expensive). Previous studies have focused on parental refusal of treatment and when this should be permitted, but the ethics of requests for suboptimal treatment has not been explored. Methods The paper consists of two parts: an empirical analysis and an ethical analysis. We performed an online survey with a sample of the general public to assess respondents’ thresholds for acceptable harm and expense resulting from parental choice, and the role that religion played in their judgement. We also identified and applied existing ethical frameworks to the case described in the survey to compare theoretical and empirical results. Results Two hundred and forty-two Mechanical Turk workers took our survey and there were 178 valid responses (73.6%). Respondents’ agreement to provide treatment decreased as the risk or cost of the requested substitute increased (p<0.001). More than 50% of participants were prepared to provide treatment that would involve a small absolute increased risk of death for the child (<5%) and a cost increase of US$<500, respectively. Religiously motivated requests were significantly more likely to be allowed (p<0.001). Existing ethical frameworks largely yielded ambiguous results for the case. There were clear inconsistencies between the theoretical and empirical results. Conclusion Drawing on both survey results and ethical analysis, we propose a potential model and thresholds for deciding about the permissibility of suboptimal treatment requests

Tuning DNA–nanoparticle conjugate properties allows modulation of nuclease activity

Enzyme–nanoparticle interactions can give rise to a range of new phenomena, most notably significant enzymatic rate enhancement. Accordingly, the careful study and optimization of such systems is likely to give rise to advanced biosensing applications. Herein, we report a systematic study of the interactions between nuclease enzymes and oligonucleotide-coated gold nanoparticles (spherical nucleic acids, SNAs), with the aim of revealing phenomena worthy of evolution into functional nanosystems. Specifically, we study two nucleases, an exonuclease (ExoIII) and an endonuclease (Nt.BspQI), via fluorescence-based kinetic experiments, varying parameters including enzyme and substrate concentrations, and nanoparticle size and surface coverage in non-recycling and a recycling formats. We demonstrate the tuning of nuclease activity by SNA characteristics and show that the modular units of SNAs can be leveraged to either accelerate or suppress nuclease kinetics. Additionally, we observe that the enzymes are capable of cleaving restriction sites buried deep in the oligonucleotide surface layer and that enzymatic rate enhancement occurs in the target recycling format but not in the non-recycling format. Furthermore, we demonstrate a new SNA phenomenon, we term ‘target stacking’, whereby nucleic acid hybridization efficiency increases as enzyme cleavage proceeds during the beginning of a reaction. This investigation provides important data to guide the design of novel SNAs in biosensing and in vitro diagnostic applications.ISSN:2040-3364ISSN:2040-337

Using Bland–Altman Analysis to Identify Appropriate Clonogenic Assay Colony Counting Techniques

Objective Determine the interchangeability of various methods utilized for counting colonies in clonogenic assays. Methods Clonogenic assays of 2 head and neck cancer cell lines were counted through 4 different counting modalities: Manual counting pen, via microscope, 1 publicly available automated algorithm, and a semiautomated algorithm presented by the authors. Each method counted individual wells (N = 24). Pen and microscopic counts were performed by 2 observers. Parameters included both low-growth (150 colonies/well) cell lines. Correlational and Bland–Altman analyses were performed using SPSS software. Results Interobserver manual pen count correlation R 2 value in both growth conditions was 0.902; controlling for only low-growth conditions decreased R 2 to 0.660. Correlation of microscopic versus pen counts R 2 values for observers 1 and 2 were 0.955 and 0.775, respectively. Comparing techniques, Bland–Altman revealed potential bias with respect to the magnitude of measurement ( P  < .001) for both observers. Correlation of microscopic counts for both interobserver ( R 2  = 0.902) and intraobserver ( R 2  = 0.916) were analyzed. Bland–Altman revealed no bias ( P  = .489). Automated versus microscopic counts revealed no bias between methodologies ( P  = .787) and a lower correlation coefficient ( R 2  = 0.384). Semiautomated versus microscopic counts revealed no bias with respect to magnitude of measurement for either observer ( P  = .327, .229); Pearson correlation was 0.985 ( R 2  = 0.970) and 0.965 ( R 2  = 0.931) for observer 1 and 2. Semiautomated versus manual pen colony counts revealed a significant bias with respect to magnitude of measurement ( P  < .001). Conclusion Counting with a manual pen demonstrated significant bias when compared to microscopic and semiautomated colony counts; 2 methods were deemed to be interchangeable. Thus, training algorithms based on manual counts may introduce this bias as well. Algorithms trained to select colonies based on size (pixels 2 ) and shape (circularity) should be prioritized. Solely relying on Bland–Altman or correlational analyses when determining method interchangeability should be avoided; they rather should be used in conjunction