"High-throughput screening of catalytically active inclusion bodies using laboratory automation and Bayesian optimization".

BACKGROUND: In recent years, the production of inclusion bodies that retain substantial catalytic activity was demonstrated. These catalytically active inclusion bodies (CatIBs) are formed by genetic fusion of an aggregation-inducing tag to a gene of interest via short linker polypeptides. The resulting CatIBs are known for their easy and cost-efficient production, recyclability as well as their improved stability. Recent studies have outlined the cooperative effects of linker and aggregation-inducing tag on CatIB activities. However, no a priori prediction is possible so far to indicate the best combination thereof. Consequently, extensive screening is required to find the best performing CatIB variant. RESULTS: In this work, a semi-automated cloning workflow was implemented and used for fast generation of 63 CatIB variants with glucose dehydrogenase of Bacillus subtilis (BsGDH). Furthermore, the variant BsGDH-PT-CBDCell was used to develop, optimize and validate an automated CatIB screening workflow, enhancing the analysis of many CatIB candidates in parallel. Compared to previous studies with CatIBs, important optimization steps include the exclusion of plate position effects in the BioLector by changing the cultivation temperature. For the overall workflow including strain construction, the manual workload could be reduced from 59 to 7 h for 48 variants (88%). After demonstration of high reproducibility with 1.9% relative standard deviation across 42 biological replicates, the workflow was performed in combination with a Bayesian process model and Thompson sampling. While the process model is crucial to derive key performance indicators of CatIBs, Thompson sampling serves as a strategy to balance exploitation and exploration in screening procedures. Our methodology allowed analysis of 63 BsGDH-CatIB variants within only three batch experiments. Because of the high likelihood of TDoT-PT-BsGDH being the best CatIB performer, it was selected in 50 biological replicates during the three screening rounds, much more than other, low-performing variants. CONCLUSIONS: At the current state of knowledge, every new enzyme requires screening for different linker/aggregation-inducing tag combinations. For this purpose, the presented CatIB toolbox facilitates fast and simplified construction and screening procedures. The methodology thus assists in finding the best CatIB producer from large libraries in short time, rendering possible automated Design-Build-Test-Learn cycles to generate structure/function learnings.

The Duckbot: A system for automated imaging and manipulation of duckweed.

Laboratory automation can boost precision and reproducibility of science workflows. However, current laboratory automation systems are difficult to modify for custom applications. Automating new experiment workflows therefore requires development of one-off research platforms, a process which requires significant time, resources, and experience. In this work, we investigate systems to lower the threshold to automation for plant biologists. Our approach establishes a direct connection with a generic motion platform to support experiment development and execution from a computational notebook environment. Specifically, we investigate the use of the open-source tool-changing motion platform Jubilee controlled using Jupyter notebooks. We present the Duckbot, a machine customized for automating laboratory research workflows with duckweed, a common multicellular plant. The Duckbot comprises (1) a set of end-effectors relevant for plant biology, (2) software modules which provide flexible control of these tools, and (3) computational notebooks which make use of these tools to automate duckweed experiments. We demonstrate the Duckbot's functionality by automating a particular laboratory research workflow, namely, duckweed growth assays. The Duckbot supports setting up sample plates with duckweed and growth media, gathering image data, and conducting relevant data analysis. We discuss the opportunities and limitations for developing custom laboratory automation with this platform and provide instructions on usage and customization.

Conversion of a classical microbiology laboratory to a total automation laboratory enhanced by the application of lean principles.

Laboratory automation in microbiology improves productivity and reduces sample turnaround times (TATs). However, its full potential can be unlocked through the optimization of workflows by adopting lean principles. This study aimed to explore the relative impact of laboratory automation and continuous improvement events (CIEs) on productivity and TATs. Laboratory automation took place in November 2020 and consisted of the introduction of WASPLab and VITEK MS systems. CIEs were run in May and September 2021. Before the conversion, the laboratory processed about ~492 samples on weekdays and had 10 full-time equivalent (FTE) staff for a productivity of 49 samples/FTE/day. In March 2021, after laboratory automation, the caseload went up to ~621 while the FTEs decreased to 8.5, accounting for productivity improvement to 73 samples/FTE/day. The hypothetical productivity went up to 110 samples/FTE/day following CIEs, meaning that the laboratory could at that point deal with a caseload increase to ~935 with unchanged FTEs. Laboratory conversion also led to an improvement in TATs for all sample types. For vaginal swabs and urine samples, median TATs decreased from 70.3 h [interquartile range (IQR): 63.5-93.1] and 73.7 h (IQR: 35.6-50.7) to 48.2 h (IQR: 44.8-67.7) and 40.0 h (IQR: 35.6-50.7), respectively. Automation alone was responsible for 37.2% and 75.8% of TAT reduction, respectively, while the remaining reduction of 62.8% and 24.2%, respectively, was achieved due to CIEs. The laboratory reached productivity and TAT goals predefined by the management after CIEs. In conclusion, automation substantially improved productivity and TATs, while the subsequent implementation of lean management further unlocked the potential of laboratory automation.IMPORTANCEIn this study, we combined total laboratory automation with lean management to show that appropriate laboratory work organization enhanced the benefit of the automation and substantially contributed to productivity improvements. Globally, the rapid availability of accurate results in the setting of a clinical microbiology laboratory is part of patient-centered approaches to treat infections and helps the implementation of antibiotic stewardship programs backed by the World Health Organization. Locally, from the point of view of laboratory management, it is important to find ways of maximizing the benefits of the use of technology, as total laboratory automation is an expensive investment.

Preparing for laboratory automation and consolidation-Establishing the validity of pediatric-like low-volume urine samples in boric-acid containing tubes.

Microbiological services consolidation has increased the usage of preservative-containing urine tubes, potentially inhibiting pathogens in low-volume pediatric urine samples, yielding false-negative results. Our study demonstrates comparable growth with 1 ml versus the recommended 3 ml urine, following different shipping intervals. We advocate for regulators to consider similar large-scale validations, ensuring results' consistency.

Physical Laboratory Automation in Synthetic Biology.

Synthetic Biology has overcome many of the early challenges facing the field and is entering a systems era characterized by adoption of Design-Build-Test-Learn (DBTL) approaches. The need for automation and standardization to enable reproducible, scalable, and translatable research has become increasingly accepted in recent years, and many of the hardware and software tools needed to address these challenges are now in place or under development. However, the lack of connectivity between DBTL modules and barriers to access and adoption remain significant challenges to realizing the full potential of lab automation. In this review, we characterize and classify the state of automation in synthetic biology with a focus on the physical automation of experimental workflows. Though fully autonomous scientific discovery is likely a long way off, impressive progress has been made toward automating critical elements of experimentation by combining intelligent hardware and software tools. It is worth questioning whether total automation that removes humans entirely from the loop should be the ultimate goal, and considerations for appropriate automation versus total automation are discussed in this light while emphasizing areas where further development is needed in both contexts.

The Laboratory Automation Protocol (LAP) Format and Repository: A Platform for Enhancing Workflow Efficiency in Synthetic Biology.

Laboratory automation deals with eliminating manual tasks in high-throughput protocols. It therefore plays a crucial role in allowing fast and reliable synthetic biology. However, implementing open-source automation solutions often demands experimental scientists to possess scripting skills, and even when they do, there is no standardized toolkit available for their use. To address this, we present the Laboratory Automation Protocol (LAP) Format and Repository. LAPs adhere to a standardized script-based format, enhancing end-user implementation and simplifying further development. With a modular design, LAPs can be seamlessly combined to create customized, target-specific workflows. Furthermore, all LAPs undergo experimental validation, ensuring their reliability. Detailed information is provided within each repository entry, allowing users to validate the LAPs in their own laboratory settings. We advocate for the adoption of the LAP Format and Repository as a community resource, which will continue to expand, improving the reliability and reproducibility of the automation processes.

Hierarchical AI enables global interpretation of culture plates in the era of digital microbiology.

Full Laboratory Automation is revolutionizing work habits in an increasing number of clinical microbiology facilities worldwide, generating huge streams of digital images for interpretation. Contextually, deep learning architectures are leading to paradigm shifts in the way computers can assist with difficult visual interpretation tasks in several domains. At the crossroads of these epochal trends, we present a system able to tackle a core task in clinical microbiology, namely the global interpretation of diagnostic bacterial culture plates, including presumptive pathogen identification. This is achieved by decomposing the problem into a hierarchy of complex subtasks and addressing them with a multi-network architecture we call DeepColony. Working on a large stream of clinical data and a complete set of 32 pathogens, the proposed system is capable of effectively assist plate interpretation with a surprising degree of accuracy in the widespread and demanding framework of Urinary Tract Infections. Moreover, thanks to the rich species-related generated information, DeepColony can be used for developing trustworthy clinical decision support services in laboratory automation ecosystems from local to global scale.

Automation protocol for high-efficiency and high-quality genomic DNA extraction from Saccharomyces cerevisiae.

Although many protocols have been previously developed for genomic DNA (gDNA) extraction from S. cerevisiae, to take advantage of recent advances in laboratory automation and DNA-barcode sequencing, there is a need for automated methods that can provide high-quality gDNA at high efficiency. Here, we describe and demonstrate a fully automated protocol that includes five basic steps: cell wall and RNA digestion, cell lysis, DNA binding to magnetic beads, washing with ethanol, and elution. Our protocol avoids the use of hazardous reagents (e.g., phenol, chloroform), glass beads for mechanical cell disruption, or incubation of samples at 100°C (i.e., boiling). We show that our protocol can extract gDNA with high efficiency both from cells grown in liquid culture and from colonies grown on agar plates. We also show results from gel electrophoresis that demonstrate that the resulting gDNA is of high quality.

Innovation, Automation and Informatics Improves Quality in Lerdsin Hospital, Thailand.

This paper describes a planned, continuous improvement journey, of a laboratory that has installed a system with a single sample touch from blood draw to result. To achieve this, physical connectivity of systems from phlebotomy through pre-analytical to the analytical phase were paired with informatics connectivity from the patient's national identity card to the hospital and laboratory informatics management systems (LIMS) and associated middleware. This allowed accurate time stamps to track turnaround time (TAT). TAT metrics were collected from the LIMS for inpatient, emergency room and outpatient samples and tests over a period of 7 months. This time span incorporated the 2-month period before automation was implemented. The results for all tests and specific tests are shown and the results of an analysis of the outpatient phlebotomy workflow are given. The implemented solution has improved outpatient TAT by over 54% and has shown that samples can be collected, and results obtained without touching the sample. Improving intra-laboratory TAT is an important quality goal for all laboratories. The implementation of automation is important in achieving this albeit more about obtaining predictable TAT. Automation does not necessarily improve TAT it removes variation which leads to predictable TAT (PTAT). Automation should only be considered with a strategic vision for the future as it is important to have clear goals and objectives based on the individual laboratories process and needs. Automating a poor process leads to an automated poor process. Here, an innovative use of automation, hardware and software has resulted in marked improvement in TAT across all samples processed in the central laboratory.

Laboratory automation, informatics, and artificial intelligence: current and future perspectives in clinical microbiology.

Clinical diagnostic laboratories produce one product-information-and for this to be valuable, the information must be clinically relevant, accurate, and timely. Although diagnostic information can clearly improve patient outcomes and decrease healthcare costs, technological challenges and laboratory workflow practices affect the timeliness and clinical value of diagnostics. This article will examine how prioritizing laboratory practices in a patient-oriented approach can be used to optimize technology advances for improved patient care.

Implementing laboratory automation for next-generation sequencing: benefits and challenges for library preparation.

In the wake of COVID-19, the importance of next-generation sequencing (NGS) for diagnostic testing and surveillance-based screening has never been more evident. Considering this, continued investment is critical to ensure more public health laboratories can adopt these advanced molecular technologies. However, many facilities may face potential barriers such as limited staff available to routinely prepare, test, and analyze samples, lack of expertise or experience in sequencing, difficulties in assay standardization, and an inability to handle throughput within expected turnaround times. Workflow automation provides an opportunity to overcome many of these challenges. By identifying these types of sustainable solutions, laboratories can begin to utilize more advanced molecular-based approaches for routine testing. Nevertheless, the introduction of automation, while valuable, does not come without its own challenges. This perspective article aims to highlight the benefits and difficulties of implementing laboratory automation used for sequencing. We discuss strategies for implementation, including things to consider when selecting instrumentation, how to approach validations, staff training, and troubleshooting.

The Effect of Total Laboratory Automation on Urine Culture Result Times in a Consolidated Laboratory.

BACKGROUND: The Provincial Health Directorate of Istanbul province (Turkey) established a consolidated laboratory network consisting of four regional central laboratories to reduce general laboratory costs and increase laboratory efficiency and quality in all affiliated hospitals. As part of the consolidation project, the Total Laboratory Automation (TLA) system was installed in the microbiology department of the ISLAB-2 central laboratory. In this study, the turnaround time (TAT) of urine samples of a satellite laboratory where the system was not installed and the ISLAB-2 central laboratory were compared to evaluate the effect of consolidation and the TLA. METHODS: The TAT values of all urine samples processed between March 2021, when the TLA was installed, and October 2021, were retrospectively examined in the laboratory information system. While the TLA was used for the processing and evaluation of samples in the ISLAB-2 central laboratory, manual methods were employed in the satellite laboratory. Both laboratories used MALDI-TOF MS (bioMérieux, France) for bacterial identification and VITEK 2 Compact (bioMérieux, France) for antibiotic sensitivity testing. Kruskal-Wallis test was used to compare TAT between the two laboratories. p < 0.05 was taken as the level of statistical significance. RESULTS: A total of 78,592 urine cultures (71,906 in the central laboratory and 6,686 in the satellite laboratory) were included in the study. Negative samples were reported in 23.5 hours in the central laboratory and 37.1 hours in the satellite laboratory and positive samples in 55 hours and 61.7 hours in the same laboratories, respectively. The mean TAT of both positive and negative urine cultures were found statistically significantly lower in the central laboratory than in the satellite laboratory (p < 0.0001). While 82% of negative urine cultures were completed within the first 24 hours in the central laboratory, only 17% were processed in the satellite laboratory. While 61% of positive samples were processed within the first 48 hours in the central laboratory, 38% were completed in the satellite laboratory. CONCLUSIONS: We assume that TLA has a positive effect on the diagnosis and treatment of patients, thanks to its contribution to standardization, efficiency, increased quality, and earlier reporting.

Automation in the Thrombosis and Hemostasis Laboratory.

Automation continues to advance into hemostasis and thrombosis laboratories. Integration of hemostasis testing into an existing chemistry track systems and adoption of a separate hemostasis track systems are important considerations. Unique issues must be addressed to maintain quality and efficiency when automation is introduced. Among other challenges, this chapter discusses centrifugation protocols, incorporation of specimen-check modules in the workflow, and inclusion of tests amenable to automation.

Label-free high-throughput screening via acoustic ejection mass spectrometry put into practice.

Acoustic droplet ejection-open port interface-mass spectrometry (ADE-OPI-MS) is a novel label-free analytical technique, promising to become a versatile readout for high-throughput screening (HTS) applications. The recent introduction of ADE-OPI-MS devices to the laboratory equipment market, paired with their compatibility with laboratory automation platforms, should facilitate the adoption of this technology by a broader community. Towards this goal, instrument robustness in the context of HTS campaigns - where up to millions of samples in complex matrices are tested in a short time frame - represents a major challenge, which explains the absence of detailed literature reports on this subject. Here, we present the results of our first fully automated HTS campaign, based on the ADE-OPI-MS technology, aiming to identify inhibitors of a metabolic enzyme in a >1 million compound library. The report encompasses the assay development and validation steps, as well as the adaptation for HTS requirements, where refinement of the capillary cleaning concept was crucial for final success. Altogether, our study unequivocally demonstrates the applicability of the ADE-OPI-MS technology for HTS-based drug discovery.

SAGAS: Simulated annealing and greedy algorithm scheduler for laboratory automation.

During laboratory automation of life science experiments, coordinating specialized instruments and human experimenters for various experimental procedures is important to minimize the execution time. In particular, the scheduling of life science experiments requires the consideration of time constraints by mutual boundaries (TCMB) and can be formulated as the "scheduling for laboratory automation in biology" (S-LAB) problem. However, existing scheduling methods for the S-LAB problems have difficulties in obtaining a feasible solution for large-size scheduling problems at a time sufficient for real-time use. In this study, we proposed a fast schedule-finding method for S-LAB problems, SAGAS (Simulated annealing and greedy algorithm scheduler). SAGAS combines simulated annealing and the greedy algorithm to find a scheduling solution with the shortest possible execution time. We have performed scheduling on real experimental protocols and shown that SAGAS can search for feasible or optimal solutions in practicable computation time for various S-LAB problems. Furthermore, the reduced computation time by SAGAS enables us to systematically search for laboratory automation with minimum execution time by simulating scheduling for various laboratory configurations. This study provides a convenient scheduling method for life science automation laboratories and presents a new possibility for designing laboratory configurations.

Dried blood spots for doping controls-Development of a comprehensive initial testing procedure with fully automated sample preparation.

Currently, primarily urine, whole blood and serum samples are analyzed for doping-relevant substances in professional sports, but recently dried blood spots (DBS) have been introduced as complementary matrix, offering advantageous features, e.g. a minimally invasive sampling procedure. In order to cope with the increased application of DBS, a comprehensive initial testing procedure (ITP) was developed, optimized and validated, comprising a total of 233 substances representing all groups on the World Anti-Doping Agency's (WADA's) Prohibited List. The sample preparation was conducted by employing a fully automated system using an efficient flow-through extraction of a 4 mm diameter spot followed by LC-HRMS/MS analysis. The procedure was successfully validated in terms of selectivity, limit of detection, reproducibility, carryover and robustness with respect to an alternative manual sample preparation, an alternative dried blood collection device and the sample extract stability, and was thus found to meet the required criteria of the relevant guidelines published by WADA for routine application. As a proof-of-concept, DBS samples were analyzed after the administration of the glucocorticoids prednisone and dexamethasone, as well as the stimulant pseudoephedrine and the beta-blocker propranolol. All substances were detected in post-administration samples for at least 4 h and up to 24 h after intake, depending on the collection time period, using the developed testing procedure. In particular, for substances that are only banned in-competition, data obtained from DBS samples can be useful for the interpretation of adverse analytical findings. In conclusion, the developed ITP accounts for the anticipated increasing relevance of DBS in anti-doping analysis in the future and provides a foundation for optimized approaches for specific substance classes.