Consistency Analysis of the UF-1500 and UF-5000 Automated Urine Particle Analyzers.

BACKGROUND: The aim was to evaluate the consistency of the results between the UF-1500 and UF-5000, fully automated urine particle analyzers. METHODS: A total of 554 randomly selected inpatient and outpatient urine samples were collected for analysis using the UF-1500, the UF-5000, and by manual microscopic examination. The coincidence rate, intraday repeatability, and interday reproducibility were evaluated on the UF-1500 and UF-5000. To analyze the review flags from the UF-1500, the UF-1500 results were compared to manual microscopy as the gold standard. RESULTS: The repeatability of red blood cells (RBCs), white blood cells (WBCs), epithelial cells (ECs), casts, and bacteria using the UF-1500 and UF-5000 is expressed as the relative standard deviations of the intraday and inter-day measurements. For the UF-1500, the relative standard deviation values ranged from 5.9% to 12.6% and 4.9% to 17.2% for the low and 1.6% to 9.3% and 2.3% to 16.9% for the high samples, respectively. The correlation co-efficient for RBCs, WBCs, ECs, SECs, casts, crystals, and bacteria for the UF-1500 were 0.981, 0.993, 0.968, 0.963, 0.821, 0.783, and 0.992, respectively. Review samples from the UF-1500 were confirmed by microscopic examination. Review flags for all 554 samples included 3 samples with "DEBRIS High" and 23 samples with "RBCs/YLC Abnormal classification". CONCLUSIONS: The identification of various urine components by both instruments meets laboratory requirements. These two instruments with different performances have specific characteristics and should be used based upon the needs of each laboratory.

Automated detection of methicillin-resistant Staphylococcus aureus with the MRSA CHROM imaging application on BD Kiestra Total Lab Automation System.

The virulence of methicillin-resistant Staphylococcus aureus (MRSA) and its potentially fatal outcome necessitate rapid and accurate detection of patients colonized with MRSA in healthcare settings. Using the BD Kiestra Total Lab Automation (TLA) System in conjunction with the MRSA Application (MRSA App), an imaging application that uses artificial intelligence to interpret colorimetric information (mauve-colored colonies) indicative of MRSA pathogen presence on CHROMagar chromogenic media, anterior nares specimens from three sites were evaluated for the presence of mauve-colored colonies. Results obtained with the MRSA App were compared to manual reading of agar plate images by proficient laboratory technologists. Of 1,593 specimens evaluated, 1,545 (96.98%) were concordant between MRSA App and laboratory technologist reading for the detection of MRSA growth [sensitivity 98.15% (95% CI, 96.03, 99.32) and specificity 96.69% (95% CI, 95.55, 97.60)]. This multi-site study is the first evaluation of the MRSA App in conjunction with the BD Kiestra TLA System. Using the MRSA App, our results showed 98.15% sensitivity and 96.69% specificity for the detection of MRSA from anterior nares specimens. The MRSA App, used in conjunction with laboratory automation, provides an opportunity to improve laboratory efficiency by reducing laboratory technologists' labor associated with the review and interpretation of cultures.

Development and evaluation of an artificial intelligence for bacterial growth monitoring in clinical bacteriology.

In clinical bacteriology laboratories, reading and processing of sterile plates remain a significant part of the routine workload (30%-40% of the plates). Here, an algorithm was developed for bacterial growth detection starting with any type of specimens and using the most common media in bacteriology. The growth prediction performance of the algorithm for automatic processing of sterile plates was evaluated not only at 18-24 h and 48 h but also at earlier timepoints toward the development of an early growth monitoring system. A total of 3,844 plates inoculated with representative clinical specimens were used. The plates were imaged 15 times, and two different microbiologists read the images randomly and independently, creating 99,944 human ground truths. The algorithm was able, at 48 h, to discriminate growth from no growth with a sensitivity of 99.80% (five false-negative [FN] plates out of 3,844) and a specificity of 91.97%. At 24 h, sensitivity and specificity reached 99.08% and 93.37%, respectively. Interestingly, during human truth reading, growth was reported as early as 4 h, while at 6 h, half of the positive plates were already showing some growth. In this context, automated early growth monitoring in case of normally sterile samples is envisioned to provide added value to the microbiologists, enabling them to prioritize reading and to communicate early detection of bacterial growth to the clinicians.

Development of an automated amplicon-based next-generation sequencing pipeline for rapid detection of bacteria and fungi directly from clinical specimens.

The timely identification of microbial pathogens is essential to guide targeted antimicrobial therapy and ultimately, successful treatment of an infection. However, the yield of standard microbiology testing (SMT) is directly related to the duration of antecedent antimicrobial therapy as SMT culture methods are dependent on the recovery of viable organisms, the fastidious nature of certain pathogens, and other pre-analytic factors. In the last decade, metagenomic next-generation sequencing (mNGS) has been successfully utilized as a diagnostic tool for various applications within the clinical laboratory. However, mNGS is resource, time, and labor-intensive-requiring extensive laborious preliminary benchwork, followed by complex bioinformatic analysis. We aimed to address these shortcomings by developing a largely Automated targeted Metagenomic next-generation sequencing (tmNGS) PipeLine for rapId inFectIous disEase Diagnosis (AMPLIFIED) to detect bacteria and fungi directly from clinical specimens. Therefore, AMPLIFIED may serve as an adjunctive approach to complement SMT. This tmNGS pipeline requires less than 1 hour of hands-on time before sequencing and less than 2 hours of total processing time, including bioinformatic analysis. We performed tmNGS on 50 clinical specimens with concomitant cultures to assess feasibility and performance in the hospital laboratory. Of the 50 specimens, 34 (68%) were from true clinical infections. Specimens from cases of true infection were more often tmNGS positive compared to those from the non-infected group (82.4% vs 43.8%, respectively, P = 0.0087). Overall, the clinical sensitivity of AMPLIFIED was 54.6% with 85.7% specificity, equating to 70.6% and 75% negative and positive predictive values, respectively. AMPLIFIED represents a rapid supplementary approach to SMT; the typical time from specimen receipt to identification of potential pathogens by AMPLIFIED is roughly 24 hours which is markedly faster than the days, weeks, and months required to recover bacterial, fungal, and mycobacterial pathogens by culture, respectively. IMPORTANCE: To our knowledge, this represents the first application of an automated sequencing and bioinformatics pipeline in an exclusively pediatric population. Next-generation sequencing is time-consuming, labor-intensive, and requires experienced personnel; perhaps contributing to hesitancy among clinical laboratories to adopt such a test. Here, we report a strong case for use by removing these barriers through near-total automation of our sequencing pipeline.

Multi-center evaluation of the Research Use Only NeuMoDx monkeypox virus (MPXV) fully automated real-time PCR assay.

The mpox outbreak, caused by monkeypox virus (MPXV), accelerated the development of molecular diagnostics. In this study, we detail the evaluation of the Research Use Only (RUO) NeuMoDx MPXV assay by multiple European and US sites. The assay was designed and developed by Qiagen for the NeuMoDx Molecular Systems. Primers and probes were tested for specificity and inclusivity in silico. The analytical sensitivity of the assay was determined by testing dilutions of synthetic and genomic MPXV DNA. A total of 296 clinical samples were tested by three sites; the Johns Hopkins University (US), UZ Gent (Belgium, Europe), and Hospital Universitario San Cecilio (Spain, Europe). The analytical sensitivity of the assay was 50 copies/mL for both clades I and II. The assay showed 100% in silico identity for 80 clade I and 99.98% in silico identity for 5,162 clade II genomes. Clade II primers and probes showed 100% in silico specificity; however, identity of at least one of the two sets of clade I primers and probes with variola, cowpox, camelpox, and vaccinia viruses was noticed. The clinical validation showed sensitivity of 99.21% [95% confidence interval (CI): 95.66-99.98%] and specificity of 96.64% (95% CI: 91.62-99.08%) for lesion swab samples. The NeuMoDx MPXV Test shows acceptable analytical and clinical performance. The assay improves the laboratory's workflow as it consolidates nucleic acid extraction, PCR, data analysis, and interpretation and can be interfaced. The Test Strip can differentiate clades I and II, which has important laboratory safety implications. IMPORTANCE: In this manuscript, we provide detailed in silico analysis and clinical evaluation of the assay using a large cohort of clinical samples across three academic centers in Europe and the United States. Because the assay differentiates MPXV clades I and II, this manuscript is timely due to the current need to rule out the regulated clade I by diagnostic clinical laboratories. In December 2023, and due to first report of cases of sexually transmitted clade I infections in the Democratic Republic of the Congo, when generic assays that do not differentiate the clades are used, samples are considered regulated. The assay meets the need of full automation and has a marked positive impact on the laboratory workflow.

Comparison Evaluation of Automated Nucleated Red Blood Cell Enumeration by Sysmex XN 1000 in Comparison With Microscopic Reference in Children Under 1 Year.

BACKGROUND: In newborns, elevated nucleated red blood cell (NRBC) levels can be associated with enhanced erythropoietic stress and might be predictive for adverse outcome. Also, the presence of NRBC in peripheral blood might lead to erroneous enumeration results of white blood cells in automated hematology analyzers. We aimed to assess the comparability of the Sysmex XN 1000 to manual slide reviews and correlation of NRBC with inflammation markers. METHODS: Specimens of 3397 children under 1 year were compared by automated and microscopic NRBC enumeration. Additionally, potential correlations between NRBC and age and inflammation markers were examined. RESULTS: Overall, there was good correlation (r = 0.97) between automated (range: 0%-3883%) and microscopic enumeration (range: 0%-3694%) of NRBC with high comparability up to a NRBC value of 200% and an increase in the variation between the two methods with increasing NRBC numbers. When 94 samples with ≤ 200% NRBC and ≥ 30% divergence between methods were separately reanalyzed with respect to overlapping cell populations in their scattergrams, Sysmex would have generated unrecognized incorrect automated results in 47 samples, corresponding to 1.4% of total study samples. NRBC counts were negatively correlated to age, but not to inflammation markers. CONCLUSION: Sysmex XN 1000 is highly precise in the enumeration of NRBC in children under 1 year up to counts of 200% and might replace time-intense manual counting in routine diagnostics. In the setting of neonatal and intensive care diagnostics, microscopic control and supervision of scattergrams are highly recommended for any automated NRBC enumeration processes.

Automated imaging analysis of Ki-67 immunohistochemistry on whole slide images of cell blocks from pancreatic neuroendocrine neoplasms.

INTRODUCTION: Accurate grading of pancreatic neuroendocrine tumors (PanNETs) relies on the assessment of Ki-67 immunohistochemistry (IHC). While digital imaging analysis (DIA) has been employed for Ki-67 IHC assessment in surgical specimens, its applicability to cytologic specimens remains underexplored. This study aimed to evaluate an automated DIA for assessing Ki-67 IHC on PanNET cell blocks. MATERIALS AND METHODS: The study included 61 consecutive PanNETs and 5 pancreatic neuroendocrine carcinomas. Ki-67 IHC slides from cell blocks were digitally scanned into whole slide images using Philips IntelliSite Scanners and analyzed in batches using the Visiopharm Ki-67 App in a digital workflow. Ki-67 scores obtained through DIA were compared to pathologists' manual scores. RESULTS: The Pearson correlation coefficient of the percentage of Ki-67-stained nuclei between DIA reads and the originally reported reads was 0.9681. Concordance between DIA Ki-67 grades and pathologists' Ki-67 grades was observed in 92.4% (61/66) of cases with the calculated Cohen's Kappa coefficient of 0.862 (almost perfect agreement). Discordance between DIA and pathologists' consensus reads occurred in 5 PanNET cases which were upgraded from G1 to G2 by DIA due to contaminated Ki-67-stained inflammatory cells. CONCLUSIONS: DIA demonstrated excellent concordance with pathologists' assessments, with only minor grading discrepancies. However, the essential role of pathologists in confirming results is emphasized to enhance overall accuracy.

"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.

Effect of Extraction Procedure Substitution on Automated Tacrolimus, Sirolimus, and Cyclosporine Assays.

BACKGROUND: An erroneously high tacrolimus level was reported to a clinician. A root cause analysis investigation failed to determine the cause of the error. It was suspected that the incorrect preanalytical extraction reagent and procedure was used during testing; however, how this would affect the assayed drug concentration was unclear. Here we investigated the effect of the substitution of sirolimus, tacrolimus, and cyclosporine extraction reagents on assayed drug concentration. METHODS: Tacrolimus, sirolimus, and cyclosporine concentration were measured on the Abbott Architect i2000 analyzer. Each assay requires a preanalytical extraction step, with a distinct reagent. We investigated the effect of the substitution of the extraction reagents and procedure between the 3 assays on the measured drug concentration. Two experiments were performed, one on samples of known drug concentration and one on samples with no drug present. RESULTS: Substituting cyclosporine and sirolimus extraction procedures increased assayed tacrolimus concentrations from 5.6 to 8.47 (+51.25%) and 8.13 (+45.18%) ng/mL, respectively. Extraction procedure substitutions decreased assayed sirolimus from 13.63 to 4.60 (-66.25%) and 8.07 (-40.79%) ng/mL for cyclosporine and tacrolimus. Cyclosporine concentration increased from 274.60 to 391.30 (+42.50%) ng/mL using sirolimus extraction reagents and to 757.30 (+175.78%) ng/mL using tacrolimus extraction reagents. Cross-reactivity was observed between the tacrolimus assay and sirolimus and cyclosporine extraction reagents. CONCLUSIONS: Significant changes, both positive and negative, are observed in assayed drug concentration when incorrect extraction procedures are used in the Abbott i2000 tacrolimus, sirolimus, and cyclosporine assays. Preanalytic extraction procedures should be investigated when performing root cause analysis for erroneous therapeutic drug values.

A Novel Approach for Routinely Assessing Laboratory Sigma Metrics for a Broad Range of Automated Assays.

BACKGROUND: Sigma metrics have been adapted for the clinical laboratory to incorporate observed accuracy, precision, and total error allowed. The higher the Sigma level for a process, the better performance that process has. A limitation of studies assessing Sigma metrics is that they are performed on a small number of well-controlled systems. METHODS: An algorithm was developed to extract QC data and derive the Sigma metric for 115 analytes from sites connected to the QuidelOrtho E-Connectivity® database. The median of these results was then used to derive the Sigma metric for each assay. RESULTS: In this analysis, 79 out of 115 (68.7%) of the assays assessed achieved 6 Sigma or better and 98 out of 115 (85.2%) achieved 5 Sigma or better. CONCLUSIONS: This study has demonstrated a methodology that can be used to condense Sigma metrics from hundreds of analyzers into a single metric of assay quality. Because these analyzers are running in working laboratories from around the world, this analysis can serve as a baseline for understanding the assay performance achieved in the presence of variabilities such as lab-to-lab, instrument-to-instrument, material handling, environmental conditions, and reagent lot. The significant number of assays demonstrating high Sigma levels did so despite this variation. The ability of the methods reported here to include hundreds of analyzers represents a novel approach for assessing Sigma metrics in clinical laboratories.

Performance comparison of two automated digital morphology analyzers for leukocyte differential in patients with malignant hematological diseases: Mindray MC-80 and Sysmex DI-60.

BACKGROUND: The MC-80 (Mindray, Shenzhen, China), a newly available artificial intelligence (AI)-based digital morphology analyzer, is the focus of this study. We aim to compare the leukocyte differential performance of the Mindray MC-80 with that of the Sysmex DI-60 and the gold standard, manual microscopy. METHODS: A total of 100 abnormal peripheral blood (PB) smears were compared across the MC-80, DI-60, and manual microscopy. Sensitivity, specificity, predictive value, and efficiency were calculated according to the Clinical and Laboratory Standards Institute (CLSI) EP12-A2 guidelines. Comparisons were made using Bland-Altman analysis and Passing-Bablok regression analysis. Additionally, within-run imprecision was evaluated using five samples, each with varying percentages of mature leukocytes and blasts, in accordance with CLSI EP05-A3 guidelines. RESULTS: The within-run coefficient of variation (%CV) of the MC-80 for most cell classes in the five samples was lower than that of the DI-60. Sensitivities for the MC-80 ranged from 98.2% for nucleated red blood cells (NRBC) to 28.6% for reactive lymphocytes. The DI-60's sensitivities varied between 100% for basophils and reactive lymphocytes, and 11.1% for metamyelocytes. Both analyzers demonstrated high specificity, negative predictive value, and efficiency, with over 90% for most cell classes. However, the DI-60 showed relatively lower specificity for lymphocytes (73.2%) and lower efficiency for blasts and lymphocytes (80.1% and 78.6%, respectively) compared with the MC-80. Bland-Altman analysis indicated that the absolute mean differences (%) ranged from 0.01 to 4.57 in MC-80 versus manual differential and 0.01 to 3.39 in DI-60 versus manual differential. After verification by technicians, both analyzers exhibited a very high correlation (r = 0.90-1.00) with the manual differential results in neutrophils, lymphocytes, and blasts. CONCLUSIONS: The Mindray MC-80 demonstrated good performance for leukocyte differential in PB smears, notably exhibiting higher sensitivity for blasts identification than the DI-60.

Evaluation of a New NT-proBNP Immunoassay on an Automated Core Laboratory System.

BACKGROUND: Heart failure remains a major cause of morbidity and mortality despite improvements in treatment. This study aimed to evaluate the Alere N-terminal pro B-type natriuretic peptide (NT-proBNP) immunoassay on the Abbott Alinity i platform. METHODS: The analytical performance including precision, linearity, limit of quantitation (LOQ), carryover, dilution-recovery, and stability was evaluated. A method comparison between the Abbott Alere NT-proBNP assay and Roche Elecsys proBNP II assay was performed using 70 residual plasma samples. RESULTS: Total imprecision was 4.1%, 3.5%, and 2.3% for low (120.9 ng/L), medium (333.9 ng/L), and high (4767.4 ng/L) QC levels, respectively. The manufacturer's claimed LOQ of 8.3 ng/L was verified. Method comparison between the Alere NT-proBNP assay and the Elecsys proBNP II assay showed good agreement between assays with an R value of 0.998, a slope of 1.05 (95% CI, 1.03-1.06), and an intercept of 45.81 (95% CI, -46.6.84 to 138.22). The Bland-Altman plot showed an absolute bias of 250 ng/L or 6.02%. Subrange analysis (NT-proBNP <2000 ng/L) showed good agreement with an R value of 0.998, a slope of 1.04 (95% CI, 1.02-1.06), and an intercept of -4.83 (95% CI, -26.95 to 17.28), with a mean bias of 26 ng/L or 3.2%. The stability of NT-proBNP was also verified in lithium heparin plasma samples stored at 4°C over a 7-day period. Hemolysis and lipemia interference thresholds were verified, but icterus impacted NT-proBNP recovery by >20% at low analyte concentrations. CONCLUSIONS: The Alere NT-proBNP assay demonstrated acceptable analytical performance and very good clinical concordance with the Elecsys proBNP II assay.

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.

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.

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.

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.