Microfluidic Pressure in Paper (µPiP): Rapid Prototyping and Low-Cost Liquid Handling for On-Chip Diagnostics

Paper-based microfluidics was initially developed for use in ultra-low-cost diagnostics powered passively by liquid wicking. However, there is significant untapped potential in using paper to internally guide porous microfluidic flows...

Volumeless reagent delivery: a liquid handling method for adding reagents to microscale droplets without increasing volume

The addition of reagents for assays in digital microfluidic (DMF) systems is traditionally done by merging of droplets containing different analytes or reagents in solution. However, this process significantly increases...

Microfluidic Chain Reaction: Conditional, Structurally Programmed Propagation of Capillary Flow Events

Chain reactions are characterized by initiation, propagation and termination, are stochastic at microscopic scales and underlie vital chemical (e.g. combustion engines), nuclear and biotechnological (e.g. polymerase chain reaction) applications.1-5 At macroscopic scales, chain reactions are deterministic and limited to applications for entertainment and art such as falling domino and Rube Goldberg machines. Appositely, the microfluidic lab-on-a-chips (also called a micro total analysis system),6,7 was envisioned as an integrated chip, akin to microelectronic integrated circuits, yet in practice remain dependent on cumbersome peripherals, connections, and a computer for automation.8-11 Capillary microfluidics integrate energy supply and flow control onto a single chip by using capillary phenomena, but programmability remains rudimentary with at most a handful (eight) operations possible.12-19 Here we introduce the microfluidic chain reaction (MCR) as the conditional, structurally programmed propagation of capillary flow events. Monolithic chips integrating a MCR are 3D printed, and powered by the free-energy of a paper pump, autonomously execute liquid handling algorithms step-by-step. With MCR, we automated (i) the sequential release of 300 aliquots across chained, interconnected chips, (ii) a protocol for SARS-CoV-2 antibodies detection in saliva, and (iii) a thrombin generation assay by continuous subsampling and analysis of coagulation-activated plasma with parallel operations including timers, iterative cycles of synchronous flow and stop-flow operations. MCRs are untethered from and unencumbered by peripherals, encode programs structurally in situ, and can form frugal, versatile, bona fide lab-on-a-chip with wide-ranging applications in liquid handling and point-of-care diagnostics.

An open-source automated PEG precipitation assay to measure the relative solubility of proteins with low material requirement

The solubility of proteins correlates with a variety of their properties, including function, production yield, pharmacokinetics, and formulation at high concentrations. High solubility is therefore a key requirement for the development of protein-based reagents for applications in life sciences, biotechnology, diagnostics, and therapeutics. Accurate solubility measurements, however, remain challenging and resource intensive, which limits their throughput and hence their applicability at the early stages of development pipelines, when long-lists of candidates are typically available in minute amounts. Here, we present an automated method based on the titration of a crowding agent (polyethylene glycol, PEG) to quantitatively assess relative solubility of proteins using about 200 µg of purified material. Our results demonstrate that this method is accurate and economical in material requirement and costs of reagents, which makes it suitable for high-throughput screening. This approach is freely-shared and based on a low cost, open-source liquid-handling robot. We anticipate that this method will facilitate the assessment of the developability of proteins and make it substantially more accessible.

Microfluidic Chain Reaction

Chain reactions are characterized by initiation, propagation and termination, are stochastic at microscopic scales and underlie vital chemical (e.g. combustion engines), nuclear and biotechnological (e.g. polymerase chain reaction) applications.1–5 At macroscopic scales, chain reactions are deterministic and limited to applications for entertainment and art such as falling domino and Rube Goldberg machines. Appositely, microfluidic lab-on-a-chip (also called a micro total analysis system),6,7 which were envisioned pursuant to microelectronic integrated circuits, are generally not integrated on a chip owing to an enduring dependency on cumbersome connections, peripherals, and on computers for automation.8–11 Capillary microfluidics integrate energy supply and flow control onto a single chip by using capillary phenomena, but programmability remains rudimentary with at most a handful (eight) operations possible.12–19 Here we introduce mesoscopic microfluidic chain reactions (MCRs) based on capillary phenomena for reliable programming and automation of complex liquid handling algorithms integrated in a chip. MCRs are encoded into the chip microarchitecture, 3D printed as a monolithic circuit, and deterministically propagated by the free-energy of a paper pump. With MCR, we sequentially triggered the release of 300 aliquots across chained, interconnected chips, and automated a protocol for SARS-CoV-2 antibodies detection in saliva with visual and quantitative results by cell phone imaging. We automated and miniaturized for the first time the labor-intensive thrombogram with serial and parallel operations including timers and iterative cycles of synchronous flow and stop-flow sequences. Thrombograms with normal, hemophilia-like, and anticoagulant-spiked plasma were generated. MCRs are generalizable, and both the density and number of chain reaction units are scalable. MCRs are untethered from and unencumbered by peripherals, encode programs structurally in situ, and form a frugal, versatile, bona fide lab-on-a-chip with wide-ranging applications in liquid handling and point-of-care diagnostics.

A linear programming-based strategy to save pipette tips in automated DNA assembly

Laboratory automation and mathematical optimisation are key to improving the efficiency of synthetic biology research. While there are algorithms optimising the construct designs and synthesis strategies for DNA assembly, the optimisation of how DNA assembly reaction mixes are prepared remains largely unexplored. Here, we focus on reducing the pipette tip consumption of a liquid-handling robot as it delivers DNA parts across a multi-well plate where several constructs are being assembled in parallel. We propose a linear programming formulation of this problem based on the capacitated vehicle routing problem, along with an algorithm which applies a linear programming solver to our formulation, hence providing a strategy to prepare a given set of DNA assembly mixes using fewer pipette tips. The algorithm performed well in randomly generated and real-life scenarios concerning several modular DNA assembly standards, proving capable of reducing the pipette tip consumption by up to 61% in large-scale cases. Combining automatic process optimisation and robotic liquid-handling, our strategy promises to greatly improve the efficiency of DNA assembly, either used alone or in combination with other algorithmic methods.

Semi-automated high-throughput substrate screening assay for nucleoside kinases

Nucleoside kinases (NKs) are key enzymes involved in the in vivo phosphorylation of nucleoside analogues used as drugs to treat cancer or viral infections. Having different specificities, the characterization of NKs is essential for drug design and the production of nucleotide analogues in an in vitro enzymatic process. Therefore, a fast and reliable substrate screening assay for NKs is of great importance. Here, we report the validation of a well-known luciferase-based assay for the detection of NK activity in 96-well plate format. The assay was semi-automated using a liquid handling robot. A good linearity was demonstrated (r² >0.98) in the range of 0 to 500 µM ATP, and it was shown that also alternative phosphate donors like dATP or CTP were accepted by the luciferase. The developed high-throughput assay revealed comparable results to HPLC analysis. The assay was exemplary used for the comparison of the substrate spectra of four nucleoside kinases using 20 (8 natural and 12 modified) substrates. The screening results correlated well with literature data and, additionally, previously unknown substrates were identified for three of the NKs studied. Our results demonstrate that the developed semi-automated high-throughput assay is suitable to identify best performing NKs for a wide range of substrates.

‘TeeBot’: A High Throughput Robotic Fermentation and Sampling System

When fermentation research requires the comparison of many strains or conditions, the major bottleneck is a technical one. Microplate approaches are not able to produce representative fermentative performance due to their inability to truly operate anaerobically, whilst more traditional methods do not facilitate sample density sufficient to assess enough candidates to be considered even medium throughput. Two robotic platforms have been developed that address these technological shortfalls. Both are built on commercially available liquid handling platforms fitted with custom labware. Results are presented detailing fermentation performance as compared to current best practice, i.e., shake flasks fitted with airlocks and sideports. The ‘TeeBot’ is capable sampling from 96 or 384 fermentations in 100 mL or 30 mL volumes, respectively, with airlock sealing and minimal headspace. Sampling and downstream analysis are facilitated by automated liquid handling, use of 96-well sample plate format and temporary cryo-storage (<0 °C).

Automation assisted anaerobic phenotyping for metabolic engineering

Background Microorganisms can be metabolically engineered to produce a wide range of commercially important chemicals. Advancements in computational strategies for strain design and synthetic biological techniques to construct the designed strains have facilitated the generation of large libraries of potential candidates for chemical production. Consequently, there is a need for high-throughput laboratory scale techniques to characterize and screen these candidates to select strains for further investigation in large scale fermentation processes. Several small-scale fermentation techniques, in conjunction with laboratory automation have enhanced the throughput of enzyme and strain phenotyping experiments. However, such high throughput experimentation typically entails large operational costs and generate massive amounts of laboratory plastic waste. Results In this work, we develop an eco-friendly automation workflow that effectively calibrates and decontaminates fixed-tip liquid handling systems to reduce tip waste. We also investigate inexpensive methods to establish anaerobic conditions in microplates for high-throughput anaerobic phenotyping. To validate our phenotyping platform, we perform two case studies—an anaerobic enzyme screen, and a microbial phenotypic screen. We used our automation platform to investigate conditions under which several strains of E. coli exhibit the same phenotypes in 0.5 L bioreactors and in our scaled-down fermentation platform. We also propose the use of dimensionality reduction through t-distributed stochastic neighbours embedding (t-SNE) in conjunction with our phenotyping platform to effectively cluster similarly performing strains at the bioreactor scale. Conclusions Fixed-tip liquid handling systems can significantly reduce the amount of plastic waste generated in biological laboratories and our decontamination and calibration protocols could facilitate the widespread adoption of such systems. Further, the use of t-SNE in conjunction with our automation platform could serve as an effective scale-down model for bioreactor fermentations. Finally, by integrating an in-house data-analysis pipeline, we were able to accelerate the ‘test’ phase of the design-build-test-learn cycle of metabolic engineering.