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. 2024 May 28;15(6):708.
doi: 10.3390/mi15060708.

An Automated Versatile Diagnostic Workflow for Infectious Disease Detection in Low-Resource Settings

Miren Urrutia Iturritza  1   2 , Phuthumani Mlotshwa  1 , Jesper Gantelius  1   2 , Tobias Alfvén  1 , Edmund Loh  3 , Jens Karlsson  3 , Chris Hadjineophytou  3 , Krzysztof Langer  2 , Konstantinos Mitsakakis  4   5 , Aman Russom  2 , Håkan N Jönsson  2 , Giulia Gaudenzi  1   2
Affiliations

An Automated Versatile Diagnostic Workflow for Infectious Disease Detection in Low-Resource Settings

Miren Urrutia Iturritza et al. Micromachines (Basel). .

Abstract

Laboratory automation effectively increases the throughput in sample analysis, reduces human errors in sample processing, as well as simplifies and accelerates the overall logistics. Automating diagnostic testing workflows in peripheral laboratories and also in near-patient settings -like hospitals, clinics and epidemic control checkpoints- is advantageous for the simultaneous processing of multiple samples to provide rapid results to patients, minimize the possibility of contamination or error during sample handling or transport, and increase efficiency. However, most automation platforms are expensive and are not easily adaptable to new protocols. Here, we address the need for a versatile, easy-to-use, rapid and reliable diagnostic testing workflow by combining open-source modular automation (Opentrons) and automation-compatible molecular biology protocols, easily adaptable to a workflow for infectious diseases diagnosis by detection on paper-based diagnostics. We demonstrated the feasibility of automation of the method with a low-cost Neisseria meningitidis diagnostic test that utilizes magnetic beads for pathogen DNA isolation, isothermal amplification, and detection on a paper-based microarray. In summary, we integrated open-source modular automation with adaptable molecular biology protocols, which was also faster and cheaper to perform in an automated than in a manual way. This enables a versatile diagnostic workflow for infectious diseases and we demonstrated this through a low-cost N. meningitidis test on paper-based microarrays.

Keywords: infectious diseases; microarray; modular automation; open-source; recombinase polymerase amplification; signal enhancement.

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Conflict of interest statement

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1
Figure 1
The automated workflow for N. meningitidis detection using the OT-One Hood robot consists of four modules: (1) the ‘DNA isolation with Dynabeads’, (2) the ‘DNA amplification’, (3) the ‘DNA digestion’, and (4) the ‘DNA detection’ module. All the steps were performed automatically by the robot, except for the opening and closing of tube lids before and after the DNA amplification, and the exonuclease digestion steps on the MiniPCR® mini8 thermal cycler. The indicated times are as programmed.
Figure 2
Figure 2
Layout of the N. meningitidis Vertical Flow Microarray (VFM). Synthetic probes with 5′-end biotin-TEG tag modifications are printed at the positive control spots. The negative control spots contain unmodified synthetic probes. Capture probes complementary to the ctrA gene from N. meningitidis are printed on the detection spots. The ctrA amplicons generated from the RPA reaction contain a 5′-end biotin-TEG tag. Anti-biotin gold nanoparticles (ab-AuNPs) bind the biotin tags and produce a colorimetric signal. A frame of ink spots is printed on the array to ensure the user handles the VFM in the correct orientation.
Figure 3
Figure 3
Photograph showing the set-up for the diagnostic workflow on the OT-One Hood robot. A MiniPCR® mini8 was used as a thermocycler for the amplification and enzymatic digestion steps.
Figure 4
Figure 4
(A) Gel electrophoresis results from the Agilent Bioanalyzer for an RPA reaction, showing amplified products from the spiked samples. Both spiked water replicates (R1 and R2) showed clear amplification while only one spiked CSF sample replicate (R1) showed amplification. (B) Scans of the VFM after performing the signal enhancement procedure, with the corresponding signal intensity measurement graphs obtained from the analysis of the membranes. Color changes were not observed on the ctrA microarray spots for CSF spiked samples, while the color change was visible for spiked water samples. The error bars are derived from averaging the three R1 and three R2 spots. R2 samples were replicates of R1 samples.
Figure 4
Figure 4
(A) Gel electrophoresis results from the Agilent Bioanalyzer for an RPA reaction, showing amplified products from the spiked samples. Both spiked water replicates (R1 and R2) showed clear amplification while only one spiked CSF sample replicate (R1) showed amplification. (B) Scans of the VFM after performing the signal enhancement procedure, with the corresponding signal intensity measurement graphs obtained from the analysis of the membranes. Color changes were not observed on the ctrA microarray spots for CSF spiked samples, while the color change was visible for spiked water samples. The error bars are derived from averaging the three R1 and three R2 spots. R2 samples were replicates of R1 samples.
Figure 5
Figure 5
Average estimation of the time required for the liquid-handling robot to analyze eight samples in parallel. The time requirement of each of the modules was quantified over five independent experiments.
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Grants and funding

The research leading to these results received funding from The Swedish Research Council (Vetenskapsrådet) Development Research Network Grant 2020-05396 to A.R., G.G.; International post-doc grant 2019-05170 to G.G.; The European Commission Horizon Europe Research and Innovation Program Grant Agreement Nº 101057596 (‘HOLICARE’) to A.R., K.M., T.A., G.G. and P.M.; The SLS project grant 935435 to G.G.

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