Automated high-throughput dense matrix protein folding screen using a liquid handling robot combined with microfluidic capillary electrophoresis

Standardized high-throughput biomonitoring using DNA metabarcoding: Strategies for the adoption of automated liquid handlers

Reliable and comprehensive monitoring data are required to trace and counteract biodiversity loss. High-throughput metabarcoding using DNA extracted from community samples (bulk) or from water or sediment (environmental DNA) has revolutionized biomonitoring, given the capability to assess biodiversity across the tree of life rapidly with feasible effort and at a modest price. DNA metabarcoding can be upscaled to process hundreds of samples in parallel. However, while automated high-throughput analysis workflows are well-established in the medical sector, manual sample processing still predominates in biomonitoring laboratory workflows limiting the upscaling and standardization for routine monitoring applications. Here we present an automated, scalable, and reproducible metabarcoding workflow to extract DNA from bulk samples, perform PCR and library preparation on a liquid handler. Key features are the independent sample replication throughout the workflow and the use of many negative controls for quality assurance and quality control. We generated two datasets: i) a validation dataset consisting of 42 individual arthropod specimens of different species, and ii) a routine monitoring dataset consisting of 60 stream macroinvertebrate bulk samples. As a marker, we used the mitochondrial COI gene. Our results show that the developed single-deck workflow is free of laboratory-derived contamination and produces highly consistent results. Minor deviations between replicates are mostly due to stochastic differences for low abundant OTUs. Thus, we successfully demonstrated that robotic liquid handling can be used reliably from DNA extraction to final library preparation on a single deck, thereby substantially increasing throughput, reducing costs, and increasing data robustness for biodiversity assessments and monitoring.

Semi-automation of process analytics reduces operator effect

The aim of this study was to semi-automate process analytics for the quantification of common impurities in downstream processing such as host cell DNA, host cell proteins and endotoxins using a commercial liquid handling station. By semi-automation, the work load to fully analyze the elution peak of a purification run was reduced by at least 2.41 h. The relative standard deviation of results among different operators over a time span of up to 6 months was at the best reduced by half, e.g. from 13.7 to 7.1% in dsDNA analysis. Automation did not improve the reproducibility of results produced by one operator but released time for data evaluation and interpretation or planning of experiments. Overall, semi-automation of process analytics reduced operator-specific influence on test results. Such robust and reproducible analytics is fundamental to establish process analytical technology and get downstream processing ready for Quality by Design approaches.

A High-Throughput Automated Protein Folding System

In vitro protein folding can be employed to produce complex proteins expressed as insoluble inclusion bodies in E. coli from laboratory to commercial scale. Often the most challenging step is identification of renaturation conditions that will enable the denatured protein to form the native structure at an acceptable yield. Generally this requires screening a matrix of buffers and stabilizers to find an appropriate solution. Herein, we describe an automated and quantitative method to identify optimal in vitro protein folding parameters with a high rate of success.

A Systematic Protein Refolding Screen Method using the DGR Approach Reveals that Time and Secondary TSA are Essential Variables

Refolding of proteins derived from inclusion bodies is very promising as it can provide a reliable source of target proteins of high purity. However, inclusion body-based protein production is often limited by the lack of techniques for the detection of correctly refolded protein. Thus, the selection of the refolding conditions is mostly achieved using trial and error approaches and is thus a time-consuming process. In this study, we use the latest developments in the differential scanning fluorimetry guided refolding approach as an analytical method to detect correctly refolded protein. We describe a systematic buffer screen that contains a 96-well primary pH-refolding screen in conjunction with a secondary additive screen. Our research demonstrates that this approach could be applied for determining refolding conditions for several proteins. In addition, it revealed which “helper” molecules, such as arginine and additives are essential. Four different proteins: HA-RBD, MDM2, IL-17A and PD-L1 were used to validate our refolding approach. Our systematic protocol evaluates the impact of the “helper” molecules, the pH, buffer system and time on the protein refolding process in a high-throughput fashion. Finally, we demonstrate that refolding time and a secondary thermal shift assay buffer screen are critical factors for improving refolding efficiency.