High-throughput Facility Research Articles

A high throughput facility for the RF characterisation Of planar superconducting thin films

Abstract Accelerator laboratories worldwide are researching copper radio frequency (RF) cavities coated with superconducting thin films to exceed the limits of bulk niobium. The development and RF testing of thin films on small planar samples is vital before cavity depositions. A team at Daresbury Laboratory have developed a cost-effective facility using a novel 7.8 GHz Choke Cavity for the RF characterisation of planar samples. RF chokes ensure that no electrical contact is required between the sample and the cavity. The main advantages are: a simple sample design (90 − 130 mm diameter disk with no sample-cavity welding) and easy operation using a LHe-free cryostat. This enables high sample throughput, with up to 3 sample tests per week, making the facility suitable for quick, systematic scanning of deposition parameters. With the sample thermally and physically isolated from the test cavity, it is possible to measure the average surface resistance, R s, directly using an RF-DC compensation method. Facility commissioning has been performed with bulk and thin film niobium samples. These tests have demonstrated the ability to measure R s at temperatures in the range 4 − 20 K and sample peak magnetic fields up to 3 mT. The minimum resolvable R s is 0.5 μΩ with typical uncertainties of 9 − 15%. The design, operation and commissioning of this facility is reported in this paper.

Development of a mobile, high-throughput, and low-cost image-based plant growth phenotyping system.

Nondestructive plant phenotyping forms a key technique for unraveling molecular processes underlying plant development and response to the environment. While the emergence of high-throughput phenotyping facilities can further our understanding of plant development and stress responses, their high costs greatly hinder scientific progress. To democratize high-throughput plant phenotyping, we developed sets of low-cost image- and weight-based devices to monitor plant shoot growth and evapotranspiration. We paired these devices to a suite of computational pipelines for integrated and straightforward data analysis. The developed tools were validated for their suitability for large genetic screens by evaluating a cowpea (Vigna unguiculata) diversity panel for responses to drought stress. The observed natural variation was used as an input for a genome-wide association study, from which we identified nine genetic loci that might contribute to cowpea drought resilience during early vegetative development. The homologs of the candidate genes were identified in Arabidopsis (Arabidopsis thaliana) and subsequently evaluated for their involvement in drought stress by using available T-DNA insertion mutant lines. These results demonstrate the varied applicability of this low-cost phenotyping system. In the future, we foresee these setups facilitating the identification of genetic components of growth, plant architecture, and stress tolerance across a wide variety of plant species.

RABiT-III: an Automated Micronucleus Assay at a Non-Specialized Biodosimetry Facility.

Micronuclei, detected through the cytokinesis-block micronucleus assay, are valuable indicators of ionizing radiation exposure, especially in short-term lymphocyte cultures. The peripheral human blood lymphocyte assay is recognized as a prime candidate for automated biodosimetry. In a prior project at the Columbia University Center for Radiological Research, we automated this assay using the 96-well ANSI/SLAS microplate standard format and relied on established biotech robotic systems named Rapid Automated Biodosimetry Tool (RABiT). In this study, we present the application of a similar automated biotech setup at an external high-throughput facility (RABiT-III) to implement the same automated cytokinesis-block micronucleus assay. Specifically, we employed the Agilent BRAVO liquid-handling system and GE IN Cell Analyzer 6000 imaging system in conjunction with the PerkinElmer Columbus image data storage and analysis system. Notably, this analysis system features an embedded PhenoLOGIC machine learning module, simplifying the creation of cell classification algorithms for CBMN assay image analysis and enabling the generation of radiation dose-response curves. This investigation underscores the adaptability of the RABiT-II CBMN protocol to diverse RABiT-III biotech robotic platforms in non-specialized biodosimetry centers. Furthermore, it highlights the advantages of machine learning in rapidly developing algorithms crucial for the high-throughput automated analysis of RABiT-III images.

Biofoundry-Scale DNA Assembly Validation Using Cost-Effective High-Throughput Long-Read Sequencing.

Biofoundries are automated high-throughput facilities specializing in the design, construction, and testing of engineered/synthetic DNA constructs (plasmids), often from genetic parts. A critical step of this process is assessing the fidelity of the assembled DNA construct to the desired design. Current methods utilized for this purpose are restriction digest or PCR followed by fragment analysis and sequencing. The Edinburgh Genome Foundry (EGF) has recently established a single-molecule sequencing quality control step using the Oxford Nanopore sequencing technology, along with a companion Nextflow pipeline and a Python package, to perform in-depth analysis and generate a detailed report. Our software enables researchers working with plasmids, including biofoundry scientists, to rapidly analyze and interpret sequencing data. In conclusion, we have created a laboratory and software protocol that validates assembled, cloned, or edited plasmids, using Nanopore long-reads, which can serve as a useful resource for the genetics, synthetic biology, and sequencing communities.

Manually annotated and curated Dataset of diverse Weed Species in Maize and Sorghum for Computer Vision

Sustainable weed management strategies are critical to feeding the world’s population while preserving ecosystems and biodiversity. Therefore, site-specific weed control strategies based on automation are needed to reduce the additional time and effort required for weeding. Machine vision-based methods appear to be a promising approach for weed detection, but require high quality data on the species in a specific agricultural area. Here we present a dataset, the Moving Fields Weed Dataset (MFWD), which captures the growth of 28 weed species commonly found in sorghum and maize fields in Germany. A total of 94,321 images were acquired in a fully automated, high-throughput phenotyping facility to track over 5,000 individual plants at high spatial and temporal resolution. A rich set of manually curated ground truth information is also provided, which can be used not only for plant species classification, object detection and instance segmentation tasks, but also for multiple object tracking.

Stress phenotyping analysis leveraging autofluorescence image sequences with machine learning.

Autofluorescence-based imaging has the potential to non-destructively characterize the biochemical and physiological properties of plants regulated by genotypes using optical properties of the tissue. A comparative study of stress tolerant and stress susceptible genotypes of Brassica rapa with respect to newly introduced stress-based phenotypes using machine learning techniques will contribute to the significant advancement of autofluorescence-based plant phenotyping research. Autofluorescence spectral images have been used to design a stress detection classifier with two classes, stressed and non-stressed, using machine learning algorithms. The benchmark dataset consisted of time-series image sequences from three Brassica rapa genotypes (CC, R500, and VT), extreme in their morphological and physiological traits captured at the high-throughput plant phenotyping facility at the University of Nebraska-Lincoln, USA. We developed a set of machine learning-based classification models to detect the percentage of stressed tissue derived from plant images and identified the best classifier. From the analysis of the autofluorescence images, two novel stress-based image phenotypes were computed to determine the temporal variation in stressed tissue under progressive drought across different genotypes, i.e., the average percentage stress and the moving average percentage stress. The study demonstrated that both the computed phenotypes consistently discriminated against stressed versus non-stressed tissue, with oilseed type (R500) being less prone to drought stress relative to the other two Brassica rapa genotypes (CC and VT). Autofluorescence signals from the 365/400 nm excitation/emission combination were able to segregate genotypic variation during a progressive drought treatment under a controlled greenhouse environment, allowing for the exploration of other meaningful phenotypes using autofluorescence image sequences with significance in the context of plant science.

An Overview of High-Throughput Crop Phenotyping: Platform, Image Analysis, Data Mining, and Data Management.

In this chapter, we explore the application of high-throughput crop phenotyping facilities for phenotype data acquisition and the extraction of significant information from the collected data through image processing and data mining methods. Additionally, the construction and outlook of crop phenotype databases are introduced and the need for global cooperation and data sharing is emphasized. High-throughput crop phenotyping significantly improves accuracy and efficiency compared to traditional measurements, making significant contributions to overcoming bottlenecks in the phenotyping field and advancing crop genetics.

Using metal nanoparticles (ZnO and Ag) to enhance DNA isolation and amplification

Recently, there have been significant improvements in the methods used to isolate and purify genomic DNA. The implementation of high-throughput facilities has accelerated the advancement of technology, enabling more rapid and effective DNA processing than ever before. The study's goal was to develop a cost-effective and efficient technique to enhance the characterization of isolated DNA that is suitable for subsequent molecular downstream applications. The DNA used as study object obtained from suspensions of pathogenic bacteria, Klebsiella pneumoniae (K. pneumoniae) and the Enterobacter cloacae complex (E. cloacae) using a manual salting out method. The method includes utilizing ZnO and Ag nanoparticles (Nps), to enhance isolation of genomic DNA. The study showed that using Nps at concentrations of 0.02 mg/ml for Ag and 0.004 mg/ml for ZnO led to better DNA quality and quantity compared to the control group without Nps, resulting in ideal outcomes. In addition, the presence of these Nps greatly increased the efficiency of PCR amplification for detecting the 16S ribosomal DNA (rDNA) of K. pneumoniae and E. cloacae. This resulted in the effective amplification of a 709 base pair segment in both type of Nps. The incorporation of nanoparticles technology into DNA extraction methods is in line with the current demands of the fast-progressing fields of molecular biology and biotechnology.

Identifying genomic regions determining shoot and root traits related to nitrogen uptake efficiency in a multiparent advanced generation intercross (MAGIC) winter wheat population in a high-throughput phenotyping facility

In the context of a continuously increasing human population that needs to be fed, with environmental protection in mind, nitrogen use efficiency (NUE) improvement is becoming very important. To understand the natural variation of traits linked to nitrogen uptake efficiency (UPE), one component of NUE, the multiparent advanced generation intercross (MAGIC) winter wheat population WM-800 was phenotyped under two contrasting nitrogen (N) levels in a high-throughput phenotyping facility for six weeks. Three biomass-related, three root-related, and two reflectance-related traits were measured weekly under each treatment. Subsequently, the population was genetically analysed using a total of 13,060 polymorphic haplotypes and singular SNPs for a genome-wide association study (GWAS). In total, we detected 543 quantitative trait loci (QTL) across all time points and traits, which were pooled into 42 stable QTL (sQTL; present in at least three of the six weeks). Besides Rht-B1 and Rht-D1, candidate genes playing a role in gibberellic acid-regulated growth and nitrate transporter genes from the NPF gene family, like NRT 1.1, were linked to sQTL. Two novel sQTL on chromosomes 5 A and 6D showed pleiotropic effects on several traits. The high number of N-specific sQTL indicates that selection for UPE is useful specifically under N-limited conditions.

Malaria Molecular Surveillance in the Peruvian Amazon with a Novel Highly Multiplexed Plasmodium falciparum AmpliSeq Assay.

Molecular surveillance for malaria has great potential to support national malaria control programs (NMCPs). To bridge the gap between research and implementation, several applications (use cases) have been identified to align research, technology development, and public health efforts. For implementation at NMCPs, there is an urgent need for feasible and cost-effective tools. We designed a new highly multiplexed deep sequencing assay (Pf AmpliSeq), which is compatible with benchtop sequencers, that allows high-accuracy sequencing with higher coverage and lower cost than whole-genome sequencing (WGS), targeting genomic regions of interest. The novelty of the assay is its high number of targets multiplexed into one easy workflow, combining population genetic markers with 13 nearly full-length resistance genes, which is applicable for many different use cases. We provide the first proof of principle for hrp2 and hrp3 deletion detection using amplicon sequencing. Initial sequence data processing can be performed automatically, and subsequent variant analysis requires minimal bioinformatic skills using any tabulated data analysis program. The assay was validated using a retrospective sample collection (n = 254) from the Peruvian Amazon between 2003 and 2018. By combining phenotypic markers and a within-country 28-single-nucleotide-polymorphism (SNP) barcode, we were able to distinguish different lineages with multiple resistance haplotypes (in dhfr, dhps, crt and mdr1) and hrp2 and hrp3 deletions, which have been increasing in recent years. We found no evidence to suggest the emergence of artemisinin (ART) resistance in Peru. These findings indicate a parasite population that is under drug pressure but is susceptible to current antimalarials and demonstrate the added value of a highly multiplexed molecular tool to inform malaria strategies and surveillance systems. IMPORTANCE While the power of next-generation sequencing technologies to inform and guide malaria control programs has become broadly recognized, the integration of genomic data for operational incorporation into malaria surveillance remains a challenge in most countries where malaria is endemic. The main obstacles include limited infrastructure, limited access to high-throughput sequencing facilities, and the need for local capacity to run an in-country analysis of genomes at a large-enough scale to be informative for surveillance. In addition, there is a lack of standardized laboratory protocols and automated analysis pipelines to generate reproducible and timely results useful for relevant stakeholders. With our standardized laboratory and bioinformatic workflow, malaria genetic surveillance data can be readily generated by surveillance researchers and malaria control programs in countries of endemicity, increasing ownership and ensuring timely results for informed decision- and policy-making.

Deciphering phase evolution in complex metal oxide thin films via high-throughput materials synthesis and characterization

Discovery of structure-property relationships in thin film alloys of complex metal oxides enabled by high-throughput materials synthesis and characterization facilities is demonstrated here with a case-study. Thin films of binary transition metal oxides (Ti–Zn) are prepared by pulsed laser deposition with continuously varying Ti:Zn ratio, creating combinatorial samples for exploration of the properties of this material family. The atomic structure and electronic properties are probed by spatially resolved techniques including x-ray absorption near edge structures (XANES) and x-ray fluorescence (XRF) at the Ti and Zn K-edge, x-ray diffraction, and spectroscopic ellipsometry. The observed properties as a function of Ti:Zn ratio are resolved into mixtures of five distinguishable phases by deploying multivariate curve resolution analysis on the XANES spectral series, under constraints set by results from the other characterization techniques. First-principles computations based on density function theory connect the observed properties of each distinct phase with structural and spectral characteristics of crystalline polymorphs of Ti–Zn oxide. Continuous tuning of the optical absorption edge as a function of Ti:Zn ratio, including the unusual observation of negative optical bowing, exemplifies a functional property of the film correlated to the phase evolution.

A Strategy for the Acquisition and Analysis of Image-Based Phenome in Rice during the Whole Growth Period.

As one of the most widely grown crops in the world, rice is not only a staple food but also a source of calorie intake for more than half of the world's population, occupying an important position in China's agricultural production. Thus, determining the inner potential connections between the genetic mechanisms and phenotypes of rice using dynamic analyses with high-throughput, nondestructive, and accurate methods based on high-throughput crop phenotyping facilities associated with rice genetics and breeding research is of vital importance. In this work, we developed a strategy for acquiring and analyzing 58 image-based traits (i-traits) during the whole growth period of rice. Up to 84.8% of the phenotypic variance of the rice yield could be explained by these i-traits. A total of 285 putative quantitative trait loci (QTLs) were detected for the i-traits, and principal components analysis was applied on the basis of the i-traits in the temporal and organ dimensions, in combination with a genome-wide association study that also isolated QTLs. Moreover, the differences among the different population structures and breeding regions of rice with regard to its phenotypic traits demonstrated good environmental adaptability, and the crop growth and development model also showed high inosculation in terms of the breeding-region latitude. In summary, the strategy developed here for the acquisition and analysis of image-based rice phenomes can provide a new approach and a different thinking direction for the extraction and analysis of crop phenotypes across the whole growth period and can thus be useful for future genetic improvements in rice.

High Throughput Synthesis of Perovskite Oxides for Alkaline Oxygen Evolution Reaction Electrocatalysis: Nature of the a and B Sites

Electrochemical energy conversion technologies based on the oxygen evolution reaction (OER) are at the heart of many efforts to achieve a sustainable future, carbon-free fuel, and a circular economy. The sluggish kinetics of oxygen electrocatalysis, as well as the high overpotential required to attain practical current densities, limit the efficiency of several promising electrochemical technologies, including water and carbon dioxide electrolyzers, metal–oxygen batteries, and fuel cells. The most efficient OER catalysts are precious metals such as iridium- and ruthenium-based materials (i.e., IrO2 and RuO2). This fact represents a challenge against the cost-effective implementation of these electrolysis technologies.1-3 As a result, there is a necessity for the development of cost effective PGM-free OER catalysts, with equivalent or superior activity and durability to the PGM catalysts.This presentation will discuss the development and implementation of high-throughput synthesis methodology for PGM-free OER catalysts exploiting the rich chemistry of nanoporous materials4-7 and Argonne National Laboratory's High-Throughput Research Facility. The developed high-throughput methodology will expedite the assessment of the effect of composition and synthesis parameters on the activity of perovskite oxide alkaline electrolyte OER catalysts.AcknowledgementsThis work was supported by the U.S. Department of Energy, Advanced Research Projects Agency Energy (ARPA-E) under the DIFFERENTIATE program. This work was authored in part by Argonne National Laboratory, a U.S. Department of Energy (DOE) Office of Science laboratory operated for DOE by UChicago Argonne, LLC under contract no. DE-AC02-06CH11357.References Katsounaros, Ioannis, Serhiy Cherevko, Aleksandar R. Zeradjanin, and Karl JJ Mayrhofer. "Oxygen electrochemistry as a cornerstone for sustainable energy conversion." Angewandte Chemie International Edition53, no. 1 (2014): 102-121.Lee, Youngmin, Jin Suntivich, Kevin J. May, Erin E. Perry, and Yang Shao-Horn. "Synthesis and activities of rutile IrO2 and RuO2 nanoparticles for oxygen evolution in acid and alkaline solutions." The journal of physical chemistry letters3, no. 3 (2012): 399-404.Cherevko, S. et al. Oxygen and hydrogen evolution reactions on Ru, RuO2, Ir, and IrO2 thin film electrodes in acidic and alkaline electrolytes: A comparative study on activity and stability. Today 262, 170–180 (2016).Nahar, Lamia, Ahmed A. Farghaly, Richard J. Alan Esteves, and Indika U. Arachchige. "Shape controlled synthesis of Au/Ag/Pd nanoalloys and their oxidation-induced self-assembly into electrocatalytically active aerogel monoliths." Chemistry of Materials29, no. 18 (2017): 7704-7715.Farghaly, Ahmed A., Rezaul K. Khan, and Maryanne M. Collinson. "Biofouling-resistant platinum bimetallic alloys." ACS applied materials & interfaces10, no. 25 (2018): 21103-21112.Khan, Rezaul K., Ahmed A. Farghaly, Tiago A. Silva, Dexian Ye, and Maryanne M. Collinson. "Gold-Nanoparticle-Decorated Titanium Nitride Electrodes Prepared by Glancing-Angle Deposition for Sensing Applications." ACS Applied Nano Materials2, no. 3 (2019): 1562-1569.Farghaly, Ahmed A., Mai Lam, Christopher J. Freeman, Badharinadh Uppalapati, and Maryanne M. Collinson. "Potentiometric measurements in biofouling solutions: comparison of nanoporous gold to planar gold." Journal of The Electrochemical Society 163, no. 4 (2015): H3083.

(Invited) Machine Learning Driven Discovery and Optimization of Perovskite Alkaline Electrolyte Oxygen Evolution Reaction Electrocatalysts

Electrochemical energy conversion technologies based on the oxygen evolution reaction (OER) are at the heart of many efforts to achieve a sustainable future, carbon-free fuel, and a circular economy. The sluggish kinetics of oxygen electrocatalysis, as well as the high overpotential required to attain practical current densities, limit the efficiency of several promising electrochemical technologies, including water and carbon dioxide electrolyzers, metal–oxygen batteries, and fuel cells. The most efficient OER catalysts are precious metals such as iridium- and ruthenium-based materials (i.e., IrO2 and RuO2). This fact represents a challenge against the cost-effective implementation of these electrolysis technologies.1-3 As a result, there is a necessity for the development of cost effective PGM-free OER catalysts, with equivalent or superior activity and durability to the PGM catalysts.This presentation will describe the application of machine learning (ML)-guided materials discovery and high-throughput synthesis to address these concerns, taking advantage of the intriguing properties and rich chemistry of nanoporous materials, the demonstrated capability of machine learning (ML)-guided materials discovery, and the high OER electrocatalytic activity of perovskites especially in alkaline media.4-10 Simulation of over 8,000 perovskites across a variety of cell sizes, space groups, and compositions using density functional theory (DFT) has been performed. Mining of the simulation data indicated that experimentally-known perovskites are characterized by low energy above the thermodynamic convex hull. Efficient search algorithms, deep learning-based models, and DFT calculations have been used to explore the space of perovskite oxides to produce novel compositions with tailored electronic descriptors. Promising compositions designed for high activity and stability are then selected for high throughput automated synthesis using the High-Throughput Research Facility at Argonne National Laboratory. A correlation between the phase purity, annealing temperature and OER activity has been identified.AcknowledgementsThis work was supported by the U.S. Department of Energy, Advanced Research Projects Agency-Energy (ARPA-E) under the DIFFERENTIATE program. This work was authored in part by Argonne National Laboratory, a U.S. Department of Energy (DOE) Office of Science laboratory operated for DOE by UChicago Argonne, LLC under contract no. DE-AC02-06CH11357.References Katsounaros, Ioannis, Serhiy Cherevko, Aleksandar R. Zeradjanin, and Karl JJ Mayrhofer. "Oxygen electrochemistry as a cornerstone for sustainable energy conversion." Angewandte Chemie International Edition53, no. 1 (2014): 102-121.Lee, Youngmin, Jin Suntivich, Kevin J. May, Erin E. Perry, and Yang Shao-Horn. "Synthesis and activities of rutile IrO2 and RuO2 nanoparticles for oxygen evolution in acid and alkaline solutions." The journal of physical chemistry letters3, no. 3 (2012): 399-404.Cherevko, S. et al. Oxygen and hydrogen evolution reactions on Ru, RuO2, Ir, and IrO2 thin film electrodes in acidic and alkaline electrolytes: A comparative study on activity and stability. Today 262, 170–180 (2016).Nahar, Lamia, Ahmed A. Farghaly, Richard J. Alan Esteves, and Indika U. Arachchige. "Shape controlled synthesis of Au/Ag/Pd nanoalloys and their oxidation-induced self-assembly into electrocatalytically active aerogel monoliths." Chemistry of Materials29, no. 18 (2017): 7704-7715.Farghaly, Ahmed A., Rezaul K. Khan, and Maryanne M. Collinson. "Biofouling-resistant platinum bimetallic alloys." ACS applied materials & interfaces10, no. 25 (2018): 21103-21112.Khan, Rezaul K., Ahmed A. Farghaly, Tiago A. Silva, Dexian Ye, and Maryanne M. Collinson. "Gold-Nanoparticle-Decorated Titanium Nitride Electrodes Prepared by Glancing-Angle Deposition for Sensing Applications." ACS Applied Nano Materials2, no. 3 (2019): 1562-1569.Farghaly, Ahmed A., Mai Lam, Christopher J. Freeman, Badharinadh Uppalapati, and Maryanne M. Collinson. "Potentiometric measurements in biofouling solutions: comparison of nanoporous gold to planar gold." Journal of The Electrochemical Society163, no. 4 (2015): H3083.Suntivich, Jin, Kevin J. May, Hubert A. Gasteiger, John B. Goodenough, and Yang Shao-Horn. "A perovskite oxide optimized for oxygen evolution catalysis from molecular orbital principles." Science334, no. 6061 (2011): 1383-1385.Hwang, Jonathan, Zhenxing Feng, Nenian Charles, Xiao Renshaw Wang, Dongkyu Lee, Kelsey A. Stoerzinger, Sokseiha Muy et al. "Tuning perovskite oxides by strain: electronic structure, properties, and functions in (electro) catalysis and ferroelectricity." Materials Today31 (2019): 100-118.Gómez-Bombarelli, Rafael, Jennifer N. Wei, David Duvenaud, José Miguel Hernández-Lobato, Benjamín Sánchez-Lengeling, Dennis Sheberla, Jorge Aguilera-Iparraguirre, Timothy D. Hirzel, Ryan P. Adams, and Alán Aspuru-Guzik. "Automatic chemical design using a data-driven continuous representation of molecules." ACS central science 4, no. 2 (2018): 268-276.

Capturing crop adaptation to abiotic stress using image-based technologies.

Farmers and breeders aim to improve crop responses to abiotic stresses and secure yield under adverse environmental conditions. To achieve this goal and select the most resilient genotypes, plant breeders and researchers rely on phenotyping to quantify crop responses to abiotic stress. Recent advances in imaging technologies allow researchers to collect physiological data non-destructively and throughout time, making it possible to dissect complex plant responses into quantifiable traits. The use of image-based technologies enables the quantification of crop responses to stress in both controlled environmental conditions and field trials. This paper summarizes phenotyping imaging technologies (RGB, multispectral and hyperspectral sensors, among others) that have been used to assess different abiotic stresses including salinity, drought and nitrogen deficiency, while discussing their advantages and drawbacks. We present a detailed review of traits involved in abiotic tolerance, which have been quantified by a range of imaging sensors under high-throughput phenotyping facilities or using unmanned aerial vehicles in the field. We also provide an up-to-date compilation of spectral tolerance indices and discuss the progress and challenges in machine learning, including supervised and unsupervised models as well as deep learning.

Automated Bioprocess Feedback Operation in a High-Throughput Facility via the Integration of a Mobile Robotic Lab Assistant

The development of biotechnological processes is challenging due to the diversity of process parameters. For efficient upstream development, parallel cultivation systems have proven to reduce costs and associated timelines successfully while offering excellent process control. However, the degree of automation of such small-scale systems is comparatively low, and necessary sample analysis requires manual steps. Although the subsequent analysis can be performed in a high-throughput manner, the integration of analytical devices remains challenging, especially when cultivation and analysis laboratories are spatially separated. Mobile robots offer a potential solution, but their implementation in research laboratories is not widely adopted. Our approach demonstrates the integration of a small-scale cultivation system into a liquid handling station for an automated cultivation and sample procedure. The samples are transported via a mobile robotic lab assistant and subsequently analyzed by a high-throughput analyzer. The process data are stored in a centralized database. The mobile robotic workflow guarantees a flexible solution for device integration and facilitates automation. Restrictions regarding spatial separation of devices are circumvented, enabling a modular platform throughout different laboratories. The presented cultivation platform is evaluated on the basis of industrially relevant E. coli BW25113 high cell density fed-batch cultivation. The necessary magnesium addition for reaching high cell densities in mineral salt medium is automated via a feedback operation loop between the analysis station located in the adjacent room and the cultivation system. The modular design demonstrates new opportunities for advanced control options and the suitability of the platform for accelerating bioprocess development. This study lays the foundation for a fully integrated facility, where the physical connection of laboratory equipment is achieved through the successful use of a mobile robotic lab assistant, and different cultivation scales can be coupled through the common data infrastructure.

A method comparison study of the high throughput automated HISCL® SARS-CoV-2 antigen assay using nasopharyngeal swab samples from symptomatic and asymptomatic subjects against conventional RT-PCR.

Our study aim was to evaluate the performance of the automated Sysmex HISCL® severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) antigen assay against reverse‐transcription polymerase chain reaction (RT‐PCR). We tested 277 remnant frozen nasopharyngeal swab samples, stored in universal transport medium (UTM), yielding a sensitivity of 94.9% against historical RT‐PCR results with cycle threshold (C t) < 30, and a sensitivity of 76.7% for C t < 35, and specificity of 100% (all C t values) confirming compatibility of UTM‐diluted samples with the assay system. Thereafter, we prospectively collected 141 nasopharyngeal swab samples in UTM from healthcare workers and 1369 paired swabs (400 UTM; 969 dry) from individuals at a public health testing center, with the first swab (UTM) reserved for RT‐PCR, yielding a positivity rate of 4.6%. HISCL assay performance using UTM swabs was superior to dry swabs, with a sensitivity of 100% (95% confidence interval [CI] 71.5%–100%) at C t < 30 versus 92.3% (95%CI 81.5%–97.9%), and a specificity of 99.3% (95% CI 98.1–99.89) against 83.3% (95%CI 80.7%–85.6%). We conclude that this antigen assay is suitable for high throughput facilities where the primary indication for testing is to rule out infection with low RT‐PCR C t values (proxy for high viral loads) to curb viral spread.

Germplasm, Breeding, and Genomics in Potato Improvement of Biotic and Abiotic Stresses Tolerance.

Potato is one of the most important food crops in the world. Late blight, viruses, soil and tuber-borne diseases, insect-pests mainly aphids, whiteflies, and potato tuber moths are the major biotic stresses affecting potato production. Potato is an irrigated and highly fertilizer-responsive crop, and therefore, heat, drought, and nutrient stresses are the key abiotic stresses. The genus Solanum is a reservoir of genetic diversity, however, a little fraction of total diversity has been utilized in potato breeding. The conventional breeding has contributed significantly to the development of potato varieties. In recent years, a tremendous progress has been achieved in the sequencing technologies from short-reads to long-reads sequence data, genomes of Solanum species (i.e., pan-genomics), bioinformatics and multi-omics platforms such as genomics, transcriptomics, proteomics, metabolomics, ionomics, and phenomics. As such, genome editing has been extensively explored as a next-generation breeding tool. With the available high-throughput genotyping facilities and tetraploid allele calling softwares, genomic selection would be a reality in potato in the near future. This mini-review covers an update on germplasm, breeding, and genomics in potato improvement for biotic and abiotic stress tolerance.

A novel approach to concentrate human and animal viruses from wastewater using receptors-conjugated magnetic beads

Viruses are present at low concentrations in wastewater; therefore, an effective method for concentrating virus particles is necessary for accurate wastewater-based epidemiology (WBE). We designed a novel approach to concentrate human and animal viruses from wastewater using porcine gastric mucin-conjugated magnetic beads (PGM-MBs). We systematically evaluated the performances of the PGM-MBs method (sensitivity, specificity, and robustness to environmental inhibitors) with six viral species, including Tulane virus (a surrogate for human norovirus), rotavirus, adenovirus, porcine coronavirus (transmissible gastroenteritis virus or TGEV), and two human coronaviruses (NL63 and SARS-CoV-2) in influent wastewater and raw sewage samples. We determined the multiplication factor (the ratio of genome concentration of the final solution to that of the initial solution) for the PGM-MBs method, which ranged from 1.3 to 64.0 depending on the viral species. Because the recovery efficiency was significantly higher when calculated with virus titers than it was with genome concentration, the PGM-MBs method could be an appropriate tool for assessing the risk to humans who are inadvertently exposed to wastewater contaminated with infectious viruses. Furthermore, PCR inhibitors were not concentrated by PGM-MBs, suggesting that this tool will be successful for use with environmental samples. In addition, the PGM-MBs method is cost-effective (0.5 USD/sample) and has a fast turnaround time (3 h from virus concentration to genome quantification). Thus, this method can be implemented in high throughput facilities. Because of its strong performance, intrinsic characteristics of targeting the infectious virus, robustness to wastewater, and adaptability to high throughput systems, the PGM-MBs method can be successfully applied to WBE and ultimately provides valuable public health information.

High Throughput Synthesis and Characterization of Multi-Metallic PGM-Free Aerogels for Catalyzing the Oxygen Evolution Reaction

Electrochemical energy conversion and storage technologies are at the heart of the societal pursuit towards circular economy, greenhouse gas emission-free fuel and sustainable energy future. The oxygen evolution reaction (OER) plays a central role in many of these electrochemical technologies, such as electrolyzers and metal-air batteries. The sluggish kinetics of the 4-electron oxidation of water to O2 and the resulting large overpotential limit the efficiency of these devices. The low abundance, prohibitive cost, and moderate stability of state-of-the-art OER catalysts, iridium- and ruthenium-based materials (i.e., IrO2 and RuO2) are obstacles against the cost-effective implementation of electrolysis technologies.1-3 To address these concerns and take the advantage of the intriguing properties and rich chemistry of nanoporous materials,4-7 we have developed a high throughput synthesis route for multi-metallic PGM-free aerogels for catalyzing the OER. The synthesis route is capable of producing 100 samples per batch using the High-Throughput Research Facility at Argonne National Laboratory. The effect of electrocatalyst composition (metal ion ratio) as well as the nature of the metal centers on the OER electrocatalytic activity have been evaluated.AcknowledgementsThis work was supported by the U.S. Department of Energy, Advanced Research Projects Agency Energy (ARPA-E) under the DIFFERENTIATE program. This work was authored in part by Argonne National Laboratory, a U.S. Department of Energy (DOE) Office of Science laboratory operated for DOE by UChicago Argonne, LLC under contract no. DE-AC02-06CH11357.References Katsounaros, Ioannis, Serhiy Cherevko, Aleksandar R. Zeradjanin, and Karl JJ Mayrhofer. "Oxygen electrochemistry as a cornerstone for sustainable energy conversion." Angewandte Chemie International Edition53, no. 1 (2014): 102-121.Lee, Youngmin, Jin Suntivich, Kevin J. May, Erin E. Perry, and Yang Shao-Horn. "Synthesis and activities of rutile IrO2 and RuO2 nanoparticles for oxygen evolution in acid and alkaline solutions." The journal of physical chemistry letters3, no. 3 (2012): 399-404.Cherevko, S. et al. Oxygen and hydrogen evolution reactions on Ru, RuO2, Ir, and IrO2 thin film electrodes in acidic and alkaline electrolytes: A comparative study on activity and stability. Today 262, 170–180 (2016).Nahar, Lamia, Ahmed A. Farghaly, Richard J. Alan Esteves, and Indika U. Arachchige. "Shape controlled synthesis of Au/Ag/Pd nanoalloys and their oxidation-induced self-assembly into electrocatalytically active aerogel monoliths." Chemistry of Materials29, no. 18 (2017): 7704-7715.Farghaly, Ahmed A., Rezaul K. Khan, and Maryanne M. Collinson. "Biofouling-resistant platinum bimetallic alloys." ACS applied materials & interfaces10, no. 25 (2018): 21103-21112.Khan, Rezaul K., Ahmed A. Farghaly, Tiago A. Silva, Dexian Ye, and Maryanne M. Collinson. "Gold-Nanoparticle-Decorated Titanium Nitride Electrodes Prepared by Glancing-Angle Deposition for Sensing Applications." ACS Applied Nano Materials2, no. 3 (2019): 1562-1569.Farghaly, Ahmed A., Mai Lam, Christopher J. Freeman, Badharinadh Uppalapati, and Maryanne M. Collinson. "Potentiometric measurements in biofouling solutions: comparison of nanoporous gold to planar gold." Journal of The Electrochemical Society163, no. 4 (2015): H3083.