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.

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 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 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.

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.

Establishment of low-cost laboratory automation processes using AutoIt and 4-axis robots.

In most small laboratories, many processes are not yet automated because existing laboratory automation solutions are usually expensive and inflexible to use. Examples of this are autosamplers that are only compatible with one specific laboratory instrument or larger liquid handling stations that are expensive and usually self-contained. A flexible and inexpensive way to automate laboratory processes would be to automate existing laboratory equipment with the help of suitable robotic arms. In this study, we investigate the feasibility of such a strategy based on a low-cost 4-axis robot and freely available software. We used the scripting language AutoIt that automates any Windows-based instrument control software. Using these tools, we automated three fundamentally different laboratory processes: a pipetting process, a use as an autosampler for an atomic absorption spectroscopy instrument, and a more complex process involving the inoculation of bacterial cultures. We also integrated a conventional webcam for 2D barcode recognition. Compared to a trained professional who performed all experiments manually, all setups showed no significant differences in accuracy and precision. In summary, the tested system consisting of a 4-axis robot and freely available software is suitable for flexible automation and has potential for even more complex laboratory processes. Limitations such as a lack of collaboration and speed will be addressed in follow-up studies. The system thus represents a well-suited flexible laboratory automation system for both research and teaching purposes.

Total Laboratory Automation for Rapid Detection and Identification of Microorganisms and Their Antimicrobial Resistance Profiles.

At a time when diagnostic bacteriological testing procedures have become more complex and their associated costs are steadily increasing, the expected benefits of Total laboratory automation (TLA) cannot just be a simple transposition of the traditional manual procedures used to process clinical specimens. In contrast, automation should drive a fundamental change in the laboratory workflow and prompt users to reconsider all the approaches currently used in the diagnostic work-up including the accurate identification of pathogens and the antimicrobial susceptibility testing methods. This review describes the impact of TLA in the laboratory efficiency improvement, as well as a new fully automated solution for AST by disk diffusion testing, and summarizes the evidence that implementing these methods can impact clinical outcomes.

ViralFlow: A Versatile Automated Workflow for SARS-CoV-2 Genome Assembly, Lineage Assignment, Mutations and Intrahost Variant Detection.

The COVID-19 pandemic is driven by Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) that emerged in 2019 and quickly spread worldwide. Genomic surveillance has become the gold standard methodology used to monitor and study this fast-spreading virus and its constantly emerging lineages. The current deluge of SARS-CoV-2 genomic data generated worldwide has put additional pressure on the urgent need for streamlined bioinformatics workflows. Here, we describe a workflow developed by our group to process and analyze large-scale SARS-CoV-2 Illumina amplicon sequencing data. This workflow automates all steps of SARS-CoV-2 reference-based genomic analysis: data processing, genome assembly, PANGO lineage assignment, mutation analysis and the screening of intrahost variants. The pipeline is capable of processing a batch of around 100 samples in less than half an hour on a personal laptop or in less than five minutes on a server with 50 threads. The workflow presented here is available through Docker or Singularity images, allowing for implementation on laptops for small-scale analyses or on high processing capacity servers or clusters. Moreover, the low requirements for memory and CPU cores and the standardized results provided by ViralFlow highlight it as a versatile tool for SARS-CoV-2 genomic analysis.

Deep learning model for fully automated breast cancer detection system from thermograms.

Breast cancer is one of the most common diseases among women worldwide. It is considered one of the leading causes of death among women. Therefore, early detection is necessary to save lives. Thermography imaging is an effective diagnostic technique which is used for breast cancer detection with the help of infrared technology. In this paper, we propose a fully automatic breast cancer detection system. First, U-Net network is used to automatically extract and isolate the breast area from the rest of the body which behaves as noise during the breast cancer detection model. Second, we propose a two-class deep learning model, which is trained from scratch for the classification of normal and abnormal breast tissues from thermal images. Also, it is used to extract more characteristics from the dataset that is helpful in training the network and improve the efficiency of the classification process. The proposed system is evaluated using real data (A benchmark, database (DMR-IR)) and achieved accuracy = 99.33%, sensitivity = 100% and specificity = 98.67%. The proposed system is expected to be a helpful tool for physicians in clinical use.

Experience of quantity and quality of DNA and RNA extraction from limited pediatric blood samples: A comparative analysis of automated and manual kit-based method.

INTRODUCTION: Optimal DNA and RNA quantity and purity is essential for downstream molecular biology experimentation and to avoid re-processing of sample. Despite availability of different kits and automated systems for nucleic acid isolation there is limited data on their performance evaluation, more so with pediatric blood samples, that are usually compromised in quantity. Hence, we evaluated the performance of automated QIAcube platform using pediatric blood samples in parallel with manual Qiagen extraction kits. MATERIALS AND METHODS: : A total of 500 samples were analyzed based on groups of PBMC and direct blood input. The isolated DNA and RNA were surveyed for quantity and quality tests by spectrophotometric and downstream analysis. RESULTS: : There was no significant difference in the DNA quantity (ng/ul) between manual and automated method based on similar sample input but quality (260/280) was significantly better with the QIAcube platform when direct blood and or PBMCs were used for extraction respectively (1.82 ± 004 Vs. 1.84.002; P-0.000008 and 1.859 ± 005 Vs. 1.843 ± 0.003; P-0.02). Moreover, the standard error mean was low for both quantity and quality in the QIAcube method suggesting uniformity. Comparison of quality assessment by spectrophotometer and qubit fluorimeter showed that QIAcube sheared DNA less (P- 0.038) as compared to manual method (P-0.013). Also, time taken to process the samples in QIAcube was 23% less than the kit-based method. CONCLUSION: Overall analysis of QIAcube platform suggests that it yields more better, uniform, and less-sheared quality of nucleic acid in a relatively less time as compared to manual extraction kits.

Modular development enables rapid design of media for alternative hosts.

Developing media to sustain cell growth and production is an essential and ongoing activity in bioprocess development. Modifications to media can often address host or product-specific challenges, such as low productivity or poor product quality. For other applications, systematic design of new media can facilitate the adoption of new industrially relevant alternative hosts. Despite manifold existing methods, common approaches for optimization often remain time and labor-intensive. We present here a novel approach to conventional media blending that leverages stable, simple, concentrated stock solutions to enable rapid improvement of measurable phenotypes of interest. We applied this modular methodology to generate high-performing media for two phenotypes of interest: biomass accumulation and heterologous protein production, using high-throughput, milliliter-scale batch fermentations of Pichia pastoris as a model system. In addition to these examples, we also created a flexible open-source package for modular blending automation on a low-cost liquid handling system to facilitate wide use of this method. Our modular blending method enables rapid, flexible media development, requiring minimal labor investment and prior knowledge of the host organism, and should enable developing improved media for other hosts and phenotypes of interest.

Post-Alignment Adjustment and Its Automation.

Multiple sequence alignment (MSA) is the basis for almost all sequence comparison and molecular phylogenetic inferences. Large-scale genomic analyses are typically associated with automated progressive MSA without subsequent manual adjustment, which itself is often error-prone because of the lack of a consistent and explicit criterion. Here, I outlined several commonly encountered alignment errors that cannot be avoided by progressive MSA for nucleotide, amino acid, and codon sequences. Methods that could be automated to fix such alignment errors were then presented. I emphasized the utility of position weight matrix as a new tool for MSA refinement and illustrated its usage by refining the MSA of nucleotide and amino acid sequences. The main advantages of the position weight matrix approach include (1) its use of information from all sequences, in contrast to other commonly used methods based on pairwise alignment scores and inconsistency measures, and (2) its speedy computation, making it suitable for a large number of long viral genomic sequences.

High-Throughput Selection and Characterisation of Aptamers on Optical Next-Generation Sequencers.

Aptamers feature a number of advantages, compared to antibodies. However, their application has been limited so far, mainly because of the complex selection process. 'High-throughput sequencing fluorescent ligand interaction profiling' (HiTS-FLIP) significantly increases the selection efficiency and is consequently a very powerful and versatile technology for the selection of high-performance aptamers. It is the first experiment to allow the direct and quantitative measurement of the affinity and specificity of millions of aptamers simultaneously by harnessing the potential of optical next-generation sequencing platforms to perform fluorescence-based binding assays on the clusters displayed on the flow cells and determining their sequence and position in regular high-throughput sequencing. Many variants of the experiment have been developed that allow automation and in situ conversion of DNA clusters into base-modified DNA, RNA, peptides, and even proteins. In addition, the information from mutational assays, performed with HiTS-FLIP, provides deep insights into the relationship between the sequence, structure, and function of aptamers. This enables a detailed understanding of the sequence-specific rules that determine affinity, and thus, supports the evolution of aptamers. Current variants of the HiTS-FLIP experiment and its application in the field of aptamer selection, characterisation, and optimisation are presented in this review.

Sequential Injection Analysis for Automation and Evaluation of Drug Liberation Profiles: Clotrimazole Liberation Monitoring.

A fully automated sequential injection system was tested in terms of its application in liberation testing, and capabilities and limitations were discussed for clotrimazole liberation from three semisolid formulations. An evaluation based on kinetic profiles obtained in short and longer sampling intervals and steady-state flux values were applied as traditional methods. The obtained clotrimazole liberation profile was faster in the case of Delcore and slower for Clotrimazol AL and Canesten cream commercial formulations. The steady-state flux values for the tested formulations were 52 µg cm-2 h-1 for Canesten, 35 µg cm-2 h-1 for Clotrimazol AL, and 7.2 µg cm-2 h-1 for Delcore measured in 4 min sampling intervals. A simplified approach for the evaluation of the initial rate based on the gradient between the second and third sampling points was used for the first time and was found to correspond well with the results of the conventional methods. A comparison based on the ratio of the steady-state flux and the initial rate values for Canesten and Clotrimazol AL proved the similarity of the obtained results. The proposed alternative was successfully implemented for the comparison of short-term kinetic profiles. Consequently, a faster and simpler approach for dissolution/liberation testing can be used.

Automation assisted anaerobic phenotyping for metabolic engineering.

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