Liquid Handling Research Articles

Autonomous Materials Synthesis Strategies Towards Accelerated Discovery of Novel Functional Nanomaterials for Green Energy Production

Electrocatalysts designed by alloying two or more elements (e.g., transition metals) showed promising enhancement in catalytic activity and durability due to synergistic effects from alloying, such as strain engineering or electron exchange. The potential of the alloying approach is constrained by standard synthesis methods (e.g., wet chemistry and thermal decomposition techniques) due to the governing thermodynamics rules (e.g., miscibility of the different alloying elements). That renders the synthesis of high entropy alloys (HEA), with more than 3 elements, to be complicated and tedious to achieve by those conventional methods.In the presented talk we are presenting different strategies to synthesize metastable high entropy alloys (HEA) and their outstanding catalytic performance towards OER, in correlation to their unique chemistries and structures. Rapid cycling of temperature from room 25 °C to highly elevated levels (1700 °C), in conjunction with ultra-rapid cooling, within milli-second range have been demonstrated by different methods including rapid Joule heating, Intense light flashing, and microwave plasma shock. Our results show successful synthesis of non-noble metals HEA NPs, possessing higher catalytic activity than IrO2 catalyst for OER. The nature of the alloying elements dictates OER activity by promoting different oxidation states of the catalytically active transition metals (e.g., Fe, Ni and Co). In addition, a phenomenal in-situ chemical welding of HEA NP to carbon support, yielded HEA catalysts with two orders of magnitude longer durability than IrO2. Our developed techniques resulted in formation of super-strong metal-carbide bonds “chemically welding” HEA NP to the catalyst support.Synthesis of various HEA catalyst and their electrocatalytic performance screening has been carried out by using liquid handler robots and multi-axes robotic arm systems. Moreover, to optimize the design of materials (structure and chemistry), we are using active learning techniques to evaluate the achieved performance results by applying Gaussian process, followed by applying Bayesian Optimization techniques to propose novel chemistries and structures with a higher probability to achieve further improved performances. The presented the study does not open the door only towards developing novel catalysts for energy production. However, it presents a strategy with multiple successfully demonstrated platforms towards accelerated discovery of novel materials. The high-throughput nature of the synthesis protocols presented in this talk can produce tens of thousands of different novel chemistries, at the same time taken by conventional methods to synthesize just a few, at a minimal energy consumption, cost, and manpower.

Autonomous Catalyst Development for Alkaline Electrolysis

NiFe LDH based materials are promising candidates for cheap, high performance catalysts for alkaline OER. While suffering from degradation effects, the presence of Fe, even in trace amounts, increases their OER activity manifold compared to plain Ni hydroxide. Although discovered in the mid-80s, the exact catalytic mechanism of this “Fe effect” is still not fully understood. Additionally, other doping elements like Co, Cr, Al and others have shown to both further improve OER activity and increase stability. The properties of those materials are often highly dependent on the doping ratio, resulting in an enormous number of possible material combinations. Modern techniques like DFT simulations and machine learning can help to speed up the search for the optimal compositions, but ultimately manual experimentation often limits how fast better materials can be discovered, as the process remains both resource and time-consuming.In this work, we combine an autonomous high-throughput experiment with machine learning assisted optimization of material compositions to a closed-loop system in an attempt to substantially accelerate the search for high performance alkaline OER catalysts. The system screens an eight variable phase space of doped NiFe LDH for compositions that yield optimal OER performance. Its centerpiece is a 4-axis robotic arm from North Robotics with sample, vial and liquid handling capabilities. The samples are prepared by means of a dip-coating process on Ni foam substrates that allows for doping with different metals. Electrochemical investigations are carried out in 1M KOH in an automated test cell, including EIS, CV and CP measurements at current densities of up to 200mA/cm2. From these results, a figure of merit for the OER activity is calculated and fed into a bayesian optimizer (Dragonfly). This algorithm determines the most promising next test candidate based on the principles of exploration and exploitation and initiates the next experiment accordingly. The experimental procedure can be divided into independent sub-steps, allowing for smart scheduling. This can reduce downtime of the robotic arm and therefore increase the throughput significantly, such that up to 1000 experiments per week can be achieved.We present the first results of a screening study conducted with this system and compare it to a manual study in terms of accuracy, reproducibility and throughput. Selected, particularly high performing compositions found in this study are also tested in a flow cell setup under industrially relevant conditions (30 wt. % KOH, 60 °C) for several hundred hours.

Automated generation of hiPSC-derived hepatic progeny by cost-efficient compounds.

Human pluripotent stem cell (hPSC)-derived hepatocyte-like cells (HLCs) hold great promise for liver disease modeling, drug discovery and drug toxicity screens. Yet, several hurdles still need to be overcome, including among others decrease in the cost of goods to generate HLCs and automation of the differentiation process. We here describe that use of an automated liquid handling system results in highly reproducible HLC differentiation from hPSCs. This enabled us to screen 92 chemicals to replace expensive growth factors at each step of the differentiation protocol to reduce the cost of goods of the differentiation protocol by approximately 79%. In addition, we also evaluated several recombinant extracellular matrices (ECM) to replace Matrigel. We demonstrated that differentiation of hPSCs on Laminin-521 using an optimized small molecule combination resulted in HLCs that were transcriptionally identical to HLCs generated using the growth factor combinations. In addition, the HLCs created using the optimized small molecule combination secreted similar amounts of albumin and urea, and relatively low concentrations of alfa-fetoprotein (AFP), displayed similar CYP3A4 functionality and a similar drug toxicity susceptibility as HLCs generated with growth factor cocktails. The broad applicability of the new differentiation protocol was demonstrated for four different hPSC lines. This allowed the creation of a scalable, xeno-free, and cost-efficient hPSC-derived HLC culture, suitable for high throughput disease modeling and drug screenings, or even for the creation of HLCs for regenerative therapies.

High-resolution neuraminidase inhibition profiling of Arnebia euchroma (Royle) I.M. Johnst. based on HR-MS and target isolation: An example study of anti-infectious constituents in traditional Chinese medicine

Ethnopharmacological relevanceTraditional Chinese Medicines (TCMs) are an important source to discover new anti-infectious drugs. Neuraminidases (NAs) not only play a key role on human health, but also are promising targets for anti-infectious drugs. Arnebia euchroma which is a widely used traditional Chinese medicine with the effect of cooling blood and detoxifying showed potential inhibitory activities on both bacterial NA and virus NA, suggesting that the material basis of A. euchroma deserves in-depth study. Aim of the studyTo investigate the anti-infectious constituents of A. euchroma based on NA inhibition. Material and methodsA HPLC-DAD system incorporated an auto-sampler was used for micro-fractionation. A nanoliter liquid handler and a high sensitive multimode plate reader system were used for high throughput NA inhibition screening. Thus a high-resolution NA inhibition profiling platform was constructed. The structures of potential active components in A. euchroma obtained by the high-resolution bioassay profiling were identified by DAD and MS in parallel. Then, a target and rapid isolation of NAIs from A. euchroma was achieved under the guidance of the spectrum-effect relationship obtained above. Finally, the isolated compounds were elucidated by extensive spectroscopic methods and their bioactivities were validated by in vitro assay and molecular docking. Results16 potential active ingredients in A. euchroma were isolated and identified, including a new mero-monoterpenoid. The in vitro bioassay results revealed that 12 out of the 16 isolated compounds showed potent inhibitory activities on bacterial NA (IC50s = 1–6 μM) and five of them exhibited potent anti-microbial activities on methicillin-resistant Staphylococccus aureus (MRSA) with MICs in the range of 0.5–4 μg/mL. Furthermore, some isolated compounds showed equal or even better inhibitory activities on oseltamivir resistant viral NA than oseltamivir sensitive NA. The mechanism study in silicon revealed that these natural compounds possessed absolutely different binding modes on the bacterial and viral NAs. ConclusionsOur study gave a clear spectrum-effect relationship of A. euchroma, providing a scientific evidence for future study of the multi-components synergistic effect of TCMs.

An inexpensive semi-automated sample processing pipeline for cell-free RNA extraction.

Despite advances in automated liquid handling and microfluidics, preparing samples for RNA sequencing at scale generally requires expensive equipment, which is beyond the reach of many academic laboratories. Manual sample preparation remains a slow, expensive and error-prone process. Here, we describe a low-cost, semi-automated pipeline to extract cell-free RNA using one of two commercially available, inexpensive and open-source robotic systems: the Opentrons OT1.0 or OT2.0. Like many RNA isolation protocols, ours can be decomposed into three subparts: RNA extraction, DNA digestion and RNA cleaning and concentration. RT-qPCR data using a synthetic spike-in confirms comparable RNA quality to the gold standard, manual sample processing. The semi-automated pipeline also shows improvement in sample throughput (+12×), time spent (-11×), cost (-3×) and biohazardous waste produced (-4×) compared with its manual counterpart. This protocol enables cell-free RNA extraction from 96 samples simultaneously in 4.5 h; in practice, this dramatically improves the time to results, as we recently demonstrated. Importantly, any laboratory already has most of the parts required (manual pipette and corresponding tips and kits for RNA isolation, cleaning and concentration) to build a semi-automated sample processing pipeline of their own and would only need to purchase or three-dimensionally print a few extra parts (US$5.5 K-12 K in total). This pipeline is also generalizable for many nucleic acid extraction applications, thereby increasing the scale of studies, which can be performed in small research laboratories.

Miniaturization and Automation Protocol of a Urinary Organic Acid Liquid-Liquid Extraction Method on GC-MS.

The aim of this study was to improve the extraction method for urinary organic acids by miniaturizing and automating the process. Currently, manual extraction methods are commonly used, which can be time-consuming and lead to variations in test results. To address these issues, we reassessed and miniaturized the in-house extraction method, reducing the number of steps and the sample-to-solvent volumes required. The evaluated miniaturized method was translated into an automated extraction procedure on a MicroLab (ML) Star (Hamilton Technologies) liquid handler. This was then validated using samples obtained from the ERNDIM External Quality Assurance program. The organic acid extraction method was successfully miniaturized and automated using the Autosampler robot. The linear range for most of the thirteen standard analytes fell between 0 to 300 mg/L in spiked synthetic urine, with low (50 mg/L), medium (100 mg/L), and high (500 mg/L) levels. The correlation coefficient (r) for most analytes was >0.99, indicating a strong relationship between the measured values. Furthermore, the automated extraction method demonstrated acceptable precision, as most organic acids had coefficients of variation (CVs) below 20%. In conclusion, the automated extraction method provided comparable or even superior results compared to the current in-house method. It has the potential to reduce solvent volumes used during extraction, increase sample throughput, and minimize variability and random errors in routine diagnostic settings.

Incorporation of automated buffer exchange empowers high-throughput protein and plasmid purification for downstream uses.

The continued acceleration of time-to-market product development and rising demand for biotherapeutics have hastened the need for higher throughput within the biopharmaceutical industry. Automated liquid handlers (ALH) are increasingly popular due to flexible programming that enables processing of multiple samples with an array of functions. This flexibility is useful in streamlining research that requires chromatographic procedures to achieve product purity for downstream analysis. However, purification of biologics often requires additional off-deck buffer exchange steps due to undesirable elution conditions such as high acid or high salt content. Expanding the capability of ALHs to perform purification in sequence with buffer exchange would, therefore, increase workflow efficiency by eliminating the need for manual intervention, thus expediting sample preparation. Here we demonstrate two different automated purifications using pipet-based dispersive solid-phase extraction (dSPE). The first is an affinity purification of His-tagged proteins from bacterial lysate. The second is an anion-exchange purification of plasmid DNA. Both methods are followed by buffer exchange performed by an ALH. Percent recoveries for the three purified recombinant proteins ranged from 51 ± 1.2 to 86 ± 10%. The yields were inversely correlated to starting sample load and protein molecular weight. Yields for plasmid purification ranged between 11.4 ± 0.8 and 13.7 ± 0.9 µg, with the largest plasmid providing the highest yield. Both programs were rapid, with protein purification taking <80 minutes and plasmid purification <60 minutes. Our results demonstrate that high-quality, ready-to-use biologics can be obtained rapidly from a crude sample after two separate chromatographic processes without manual intervention.

Target product profile: diagnostic test for Trypanosoma brucei gambiense.

Human African trypanosomiasis is a life-threatening parasitic infection endemic to sub-Saharan Africa. Around 95% of cases are due to Trypanosoma brucei gambiense, found in western and central Africa. Clinical signs and symptoms are nonspecific, current diagnostic tests are not sufficiently accurate, and parasitological confirmation of infection requires microscopic examination of body fluids and specialized techniques for concentrating parasites. Moreover, current treatment is not recommended on the basis of suspicion alone because it is not sufficiently safe. The availability of a simple and accurate diagnostic test to identify individuals harbouring parasites would widen treatment and help decrease disease prevalence. A subcommittee of the World Health Organization's Neglected Tropical Diseases Diagnostics Technical Advisory Group has developed a target product profile for a diagnostic tool to identify T. b. gambiense infection. This tool should have a high sensitivity for detecting T. b. gambiense but be simple enough to use in rural Africa. Ideally, the tool could be applied by any minimally trained individual in an unsophisticated peripheral health facility, or a mobile team in a village with little infrastructure. The test should be able to function under hot and humid conditions. Basic training should take under 2hours and the test should involve fewer than five steps. There should be no need for instrumentation or precision liquid handling. The test should yield a qualitative result in under 20minutes that can be easily observed, and one test should be sufficient for determining treatment. A unit cost below 1United States dollar (US$) would enable mass screening.

A fast, low-cost, robust and high-throughput method for viral nucleic acid isolation based on NAxtra magnetic nanoparticles

The year of 2020 was profoundly marked by a global pandemic caused by a strain of coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of coronavirus disease 2019 (COVID-19). To control disease spread, a key strategy adopted by many countries was the regular testing of individuals for infection. This led to the rapid development of diagnostic testing technologies. In Norway, within a week, our group developed a test kit to quickly isolate viral RNA and safely detect SARS-CoV-2 infection with sensitivity comparable to available kits. Herein, the procedure employed for the detection of SARS-CoV-2 in swab samples from patients using the NTNU-COVID-19 test kit is described in detail. This procedure, based on NAxtra magnetic nanoparticles and an optimized nucleic acid extraction procedure, is robust, reliable, and straightforward, providing high-quality nucleic acids within 14 min. The NAxtra protocol is adaptable and was further validated for extraction of DNA and RNA from other types of viruses. A comparison of the protocol on different liquid handling systems is also presented. Due to the simplicity and low cost of this method, implementation of this technology to diagnose virus infections on a clinical setting would benefit health care systems, promoting sustainability.

Phenotypic Profiling of Human Stem Cell-Derived Midbrain Dopaminergic Neurons.

Parkinson's disease (PD) is linked to a range of cell biological processes that cause midbrain dopaminergic (mDA) neuron loss. Many current in vitro PD cellular models lack complexity and do not take multiple phenotypes into account. Phenotypic profiling in human induced pluripotent stem cell (iPSC)-derived mDA neurons can address these shortcomings by simultaneously measuring a range of neuronal phenotypes in a PD-relevant cell type in parallel. Here, we describe a protocol to obtain and analyze phenotypic profiles from commercially available human mDA neurons. A neuron-specific fluorescent staining panel is used to visualize the nuclear, α-synuclein, Tyrosine hydroxylase (TH), and Microtubule-associated protein 2 (MAP2) related phenotypes. The described phenotypic profiling protocol is scalable as it uses 384-well plates, automatic liquid handling and high-throughput microscopy. The utility of the protocol is exemplified using healthy donor mDA neurons and mDA neurons carrying the PD-linked G2019S mutation in the Leucine-rich repeat kinase 2 (LRRK2) gene. Both cell lines were treated with the LRRK2 kinase inhibitor PFE-360 and phenotypic changes were measured. Additionally, we demonstrate how multidimensional phenotypic profiles can be analyzed using clustering or machine learning-driven supervised classification methods. The described protocol will particularly interest researchers working on neuronal disease modeling or studying chemical compound effects in human neurons.

Automatization of metabolite extraction for high-throughput metabolomics: case study on transgenic isoprene-emitting birch.

Metabolomics studies are becoming increasingly common for understanding how plant metabolism responds to changes in environmental conditions, genetic manipulations and treatments. Despite the recent advances in metabolomics workflow, the sample preparation process still limits the high-throughput analysis in large-scale studies. Here, we present a highly flexible robotic system that integrates liquid handling, sonication, centrifugation, solvent evaporation and sample transfer processed in 96-well plates to automatize the metabolite extraction from leaf samples. We transferred an established manual extraction protocol performed to a robotic system, and with this, we show the optimization steps required to improve reproducibility and obtain comparable results in terms of extraction efficiency and accuracy. We then tested the robotic system to analyze the metabolomes of wild-type and four transgenic silver birch (Betula pendula Roth) lines under unstressed conditions. Birch trees were engineered to overexpress the poplar (Populus × canescens) isoprene synthase and to emit various amounts of isoprene. By fitting the different isoprene emission capacities of the transgenic trees with their leaf metabolomes, we observed an isoprene-dependent upregulation of some flavonoids and other secondary metabolites as well as carbohydrates, amino acid and lipid metabolites. By contrast, the disaccharide sucrose was found to be strongly negatively correlated to isoprene emission. The presented study illustrates the power of integrating robotics to increase the sample throughput, reduce human errors and labor time, and to ensure a fully controlled, monitored and standardized sample preparation procedure. Due to its modular and flexible structure, the robotic system can be easily adapted to other extraction protocols for the analysis of various tissues or plant species to achieve high-throughput metabolomics in plant research.

A novel transcription factor combination for direct reprogramming to a spontaneously contracting human cardiomyocyte-like state

The reprogramming of somatic cells to a spontaneously contracting cardiomyocyte-like state using defined transcription factors has proven successful in mouse fibroblasts. However, this process has been less successful in human cells, thus limiting the potential clinical applicability of this technology in regenerative medicine. We hypothesized that this issue is due to a lack of cross-species concordance between the required transcription factor combinations for mouse and human cells. To address this issue, we identified novel transcription factor candidates to induce cell conversion between human fibroblasts and cardiomyocytes, using the network-based algorithm Mogrify. We developed an automated, high-throughput method for screening transcription factor, small molecule, and growth factor combinations, utilizing acoustic liquid handling and high-content kinetic imaging cytometry. Using this high-throughput platform, we screened the effect of 4960 unique transcription factor combinations on direct conversion of 24 patient-specific primary human cardiac fibroblast samples to cardiomyocytes. Our screen revealed the combination of MYOCD, SMAD6, and TBX20 (MST) as the most successful direct reprogramming combination, which consistently produced up to 40% TNNT2+ cells in just 25 days. Addition of FGF2 and XAV939 to the MST cocktail resulted in reprogrammed cells with spontaneous contraction and cardiomyocyte-like calcium transients. Gene expression profiling of the reprogrammed cells also revealed the expression of cardiomyocyte associated genes. Together, these findings indicate that cardiac direct reprogramming in human cells can be achieved at similar levels to those attained in mouse fibroblasts. This progress represents a step forward towards the clinical application of the cardiac direct reprogramming approach.

Liquid handling properties of carboxymethyl modified chitosan nonwovens for medical dressings

Chitosan (CS) is known to have excellent antibacterial, anti-inflammatory and hemostatic properties, while its liquid handling performances are dissatisfactory, making it hard to maintain a moist environment as wound dressings. In this study, the carboxymethyl chitosan (CMCS) needle-punched nonwovens were prepared by chloroacetic acid method. The structure and properties of CS and CMCS nonwovens were characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), mass per unit area and thickness. Moreover, the liquid handling properties, including liquid absorption, retention, diffusion and contact angle were further investigated. The optimal parameters for carboxymethyl modification were explored via orthogonal experiments. Results demonstrated that CMCS nonwovens were successfully prepared, and the optimal conditions for carboxymethyl reaction were NaOH concentration of 30%, NaOH to chloroacetic acid molar ratio of 5:1, and etherification time of 4 h. The liquid absorption, retention, diffusion and hydrophilic properties of CMCS nonwovens were evidently enhanced compared with pristine CS nonwovens. Owing to the outstanding liquid handling properties, the proposed CMCS nonwovens might have potential application as medical dressings.

Public Perception of The Implementation of an Eco Fishig Port Priciple at The Fish Auction Place of Karangantu, Serang City

Eco port is a predicate of a port that has implemented systematic efforts or steps to build and maintain an environmentally friendly port area. Poor sanitation and hygiene conditions such as large amounts of waste from fishing port activities can cause environmental pollution and affect public health. This research aims to determine public perception towards the management of the Fish Landing Place (TPI) of Karangantu in accordance with the principle of eco fishing port. Primary data was obtained through observations in July-August 2022 on ship unloading activities until the transaction process at Karangantu TPI. Interviews with Karangantu Archipelagic Fishing Port (PPN) employees, TPI managers and TPI service users were conducted to find out each stakeholder's perception of environmental sanitation conditions and hygiene of fish catches. Secondary data were obtained from various publications available in Karangantu PPN. Data were analyzed descriptively qualitatively (tables and graphs) and quantitatively (Likert scale). The results showed that the management of Karangantu TPI is in accordance with the eco port principle. However, the public considers that the parameters of liquid waste handling and the quality of fish catches landed at TPI Karangantu must be improved.

Technical upgrade of an open-source liquid handler to support bacterial colony screening.

The optimization of genetically engineered biological constructs is a key step to deliver high-impact biotechnological applications. The use of high-throughput DNA assembly methods allows the construction of enough genotypic variants to successfully cover the target design space. This, however, entails extra workload for researchers during the screening stage of candidate variants. Despite the existence of commercial colony pickers, their high price excludes small research laboratories and budget-adjusted institutions from accessing such extensive screening capability. In this work we present COPICK, a technical solution to automatize colony picking in an open-source liquid handler Opentrons OT-2. COPICK relies on a mounted camera to capture images of regular Petri dishes and detect microbial colonies for automated screening. COPICK's software can then automatically select the best colonies according to different criteria (size, color and fluorescence) and execute a protocol to pick them for further analysis. Benchmark tests performed for E. coli and P. putida colonies delivers a raw picking performance over pickable colonies of 82% with an accuracy of 73.4% at an estimated rate of 240 colonies/h. These results validate the utility of COPICK, and highlight the importance of ongoing technical improvements in open-source laboratory equipment to support smaller research teams.

HIGH THROUGHPUT DRUG SCREENING OF SMALL MOLECULES TARGETING ADENOID CYSTIC CARCINOMA FROM THE SALIVARY GLANDS

Objective The objective of this study was to tackle the current lack of effective drugs capable of managing adenoid cystic carcinomas (ACC) tumor progression. We also aim to identify new drugs capable of working effectively in combination with cisplatin in targeting ACC tumor cells. Study Design UM-ACC-2A cell line was seeded using a robotic liquid handler system (Opentrons) and cultured in two 96-well plates. Changes in cell viability and morphology were analyzed 24 hrs after adding drugs using a high-content imaging system (ImageXpress). Aiming at changes associated with epithelial-mesenchyme transition (EMT), we used SNAIL antibody while using H3 acetylated at lysine 9 as indicative of epigenetic modifications. Results We identified a pool of drugs capable of reducing ACC tumor cell viability; however, we also observed that other small molecules enhanced EMT. Of particular interest, we have identified a small pool of drugs that, when used in combination with cisplatin, reduced tumor viability and reversed the EMT phenotype. Conclusion Using a drug library in combination with cisplatin, we effectively reduced ACC tumor viability while reversing EMT. Altogether, we have identified novel drugs that hold the promise for new therapeutic strategies to manage ACC tumors from the salivary glands. The objective of this study was to tackle the current lack of effective drugs capable of managing adenoid cystic carcinomas (ACC) tumor progression. We also aim to identify new drugs capable of working effectively in combination with cisplatin in targeting ACC tumor cells. UM-ACC-2A cell line was seeded using a robotic liquid handler system (Opentrons) and cultured in two 96-well plates. Changes in cell viability and morphology were analyzed 24 hrs after adding drugs using a high-content imaging system (ImageXpress). Aiming at changes associated with epithelial-mesenchyme transition (EMT), we used SNAIL antibody while using H3 acetylated at lysine 9 as indicative of epigenetic modifications. We identified a pool of drugs capable of reducing ACC tumor cell viability; however, we also observed that other small molecules enhanced EMT. Of particular interest, we have identified a small pool of drugs that, when used in combination with cisplatin, reduced tumor viability and reversed the EMT phenotype. Using a drug library in combination with cisplatin, we effectively reduced ACC tumor viability while reversing EMT. Altogether, we have identified novel drugs that hold the promise for new therapeutic strategies to manage ACC tumors from the salivary glands.

Using Exonucleases for Aptamer Characterization, Engineering, and Sensing.

ConspectusAptamers are short, single-stranded nucleic acids that have been selected from random libraries to bind specific molecules with high affinity via an in vitro method termed systematic evolution of ligands by exponential enrichment (SELEX). They have been generated for diverse targets ranging from metal ions to small molecules to proteins and have demonstrated considerable promise as biorecognition elements in sensors for applications including medical diagnostics, environmental monitoring, food safety, and forensic analysis. While aptamer sensors have made great strides in terms of sensitivity, specificity, turnaround time, and ease of use, several challenges have hindered their broader adoption. These include inadequate sensitivity, bottlenecks in aptamer binding characterization, and the cost and labor associated with aptamer engineering. In this Account, we describe our successes in using nuclease enzymes to address these problems. While working with nucleases to enhance the sensitivity of split aptamer sensors via enzyme-assisted target recycling, we serendipitously discovered that the digestion of DNA aptamers by exonucleases is inhibited when an aptamer is bound to a ligand. This finding served as the foundation for the development of three novel aptamer-related methodologies in our laboratory. First, we used exonucleases to truncate nonessential nucleotides from aptamers to generate structure-switching aptamers in a single step, greatly simplifying the aptamer engineering process. Second, we used exonucleases to develop a label-free aptamer-based detection platform that can utilize aptamers directly obtained from in vitro selection to detect analytes with ultralow background and high sensitivity. Through this approach, we were able to detect analytes at nanomolar levels in biological samples, with the capacity for achieving multiplexed detection by using molecular beacons. Finally, we used exonucleases to develop a high throughput means of characterizing aptamer affinity and specificity for a variety of ligands. This approach has enabled more comprehensive analysis of aptamers by greatly increasing the number of aptamer candidates and aptamer-ligand pairs that can be tested in a single experiment. We have also demonstrated the success of this method as a means for identifying new mutant aptamers with augmented binding properties and for quantifying aptamer-target affinity. Our enzymatic technologies can greatly streamline the aptamer characterization and sensor development process, and with the adoption of robotics or liquid handling systems in the future, it should be possible to rapidly identify the most suitable aptamers for a particular application from hundreds to thousands of candidates.

Integrating automated liquid handling in the separation workflow of extracellular vesicles enhances specificity and reproducibility

BackgroundExtracellular vesicles (EV) are extensively studied in human body fluids as potential biomarkers for numerous diseases. Major impediments of EV-based biomarker discovery include the specificity and reproducibility of EV sample preparation as well as intensive manual labor. We present an automated liquid handling workstation for the density-based separation of EV from human body fluids and compare its performance to manual handling by (in)experienced researchers.ResultsAutomated versus manual density-based separation of trackable recombinant extracellular vesicles (rEV) spiked in PBS significantly reduces variability in rEV recovery as quantified by fluorescent nanoparticle tracking analysis and ELISA. To validate automated density-based EV separation from complex body fluids, including blood plasma and urine, we assess reproducibility, recovery, and specificity by mass spectrometry-based proteomics and transmission electron microscopy. Method reproducibility is the highest in the automated procedure independent of the matrix used. While retaining (in urine) or enhancing (in plasma) EV recovery compared to manual liquid handling, automation significantly reduces the presence of body fluid specific abundant proteins in EV preparations, including apolipoproteins in plasma and Tamm-Horsfall protein in urine.ConclusionsIn conclusion, automated liquid handling ensures cost-effective EV separation from human body fluids with high reproducibility, specificity, and reduced hands-on time with the potential to enable larger-scale biomarker studies.Graphical

A microfluidics-enabled automated workflow of sample preparation for MS-based immunopeptidomics

Mass spectrometry (MS)-based immunopeptidomics is an attractive antigen discovery method with growing clinical implications. However, the current experimental approach to extract HLA-restricted peptides requires a bulky sample source, which remains a challenge for obtaining clinical specimens. We present an innovative workflow that requires a low sample volume, which streamlines the immunoaffinity purification (IP) and C18 peptide cleanup on a single microfluidics platform with automated liquid handling and minimal sample transfers, resulting in higher assay sensitivity. We also demonstrate how the state-of-the-art data-independent acquisition (DIA) method further enhances the depth of tandem MS spectra-based peptide sequencing. Consequently, over 4,000 and 5,000 HLA-I-restricted peptides were identified from as few as 0.2 million RA957 cells and a melanoma tissue of merely 5mg, respectively. We also identified multiple immunogenic tumor-associated antigens and hundreds of peptides derived from non-canonical protein sources. This workflow represents a powerful tool for identifying the immunopeptidome of sparse samples.

Effect of Wettability on the Collision Behavior of Acoustically Excited Droplets.

Acoustic droplet ejection (ADE) is a noncontact technique for micro-liquid handling (usually nanoliters or picoliters) that is not restricted by nozzles and enables high-throughput liquid dispensing without sacrificing precision. It is widely regarded as the most advanced solution for liquid handling in large-scale drug screening. Stable coalescence of the acoustically excited droplets on the target substrate is a fundamental requirement during the application of the ADE system. However, it is challenging to investigate the collision behavior of nanoliter droplets flying upward during the ADE. In particular, the dependence of the droplet's collision behavior on substrate wettability and droplet velocity has yet to be thoroughly analyzed. In this paper, the kinetic processes of binary droplet collisions were investigated experimentally for different wettability substrate surfaces. Four states occur as the droplet collision velocity increases: coalescence after minor deformation, complete rebound, coalescence during rebound, and direct coalescence. For the hydrophilic substrate, there are wider ranges of Weber number (We) and Reynolds number (Re) in the complete rebound state. And with the decrease of the substrate wettability, the critical Weber and Reynolds numbers for the coalescence during rebound and the direct coalescence decrease. It is further revealed that the hydrophilic substrate is susceptible to droplet rebound because the sessile droplet has a larger radius of curvature and the viscous energy dissipation is greater. Besides, the prediction model of the maximum spreading diameter was established by modifying the droplet morphology in the complete rebound state. It is found that, under the same Weber and Reynolds numbers, droplet collisions on the hydrophilic substrate achieve a smaller maximum spreading coefficient and greater viscous energy dissipation, so the hydrophilic substrate is prone to droplet bounce.