RESUMEN
Introduction. The evolving SARS-CoV-2 coronavirus pandemic presents a series of challenges to clinical diagnostic services. Many proprietary PCR platforms deployed outside centralised laboratories have limited capacity to upscale when public health demands increase. We set out to develop and validate an open-platform mobile laboratory for remote area COVID-19 diagnosis, with a subsequent field trial.Gap Statement. In regional Western Australia, molecular diagnostic support is limited to near point-of-care devices. We therefore aimed to demonstrate open-platform capability in a rapidly deployable format within the context of the COVID-19 pandemic.Methodology. We compared, selected and validated components of a SARS-CoV-2 RT-PCR assay in order to establish a portable molecular diagnostics laboratory. The optimal combination of PCR assay equipment, reagents and consumables required for operation to national standards in regional laboratories was identified. This comprised RNA extraction and purification (QuickGene-480, Kurabo, Japan), a duplex RT-PCR assay (Logix Smart COVID-19, Co-Diagnostics, USA), a Myra liquid handling robot (Biomolecular Systems, Australia) and a magnetic induction thermal cycler (MIC, Biomolecular Systems).Results The 95 and 99% limits of detection were 1.01 copies µl-1 (5.05 copies per reaction) and 2.80 copies µl-1 (14.00 copies per reaction) respectively. The Co-Diagnostics assay amplified both SARS-CoV-1 and -2 RNA but showed no other cross reactivity. Qualitative results aligned with the reference laboratory SARS-CoV-2 assay (sensitivity 100% [95 % CI 96.48-100%], specificity 100% [95% CI 96.52-100%]). In field trials, the laboratory was operational within an hour of arrival on-site, can process up to 36 samples simultaneously, produces results in two and a half hours from specimen reception, and performed well during six consecutive runs during a 1 week deployment.Conclusion. Our mobile laboratory enables an adaptive response to increased test demand, and unlike many proprietary point-of-care PCR systems, rapid substitution with an alternative assay if gene targets change or reagent supply chains fail. We envisage operation of this RT-PCR assay as a standby capability to meet varying regional test demands under public health emergency operations guidance.
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Prueba de Ácido Nucleico para COVID-19 , COVID-19/diagnóstico , Unidades Móviles de Salud , SARS-CoV-2/aislamiento & purificación , COVID-19/epidemiología , Reacciones Cruzadas , Humanos , Límite de Detección , Sistemas de Atención de Punto , ARN Viral/genética , ARN Viral/aislamiento & purificación , SARS-CoV-2/genética , Sensibilidad y Especificidad , Australia Occidental/epidemiologíaRESUMEN
There is an urgent need to develop simple and fast antimicrobial susceptibility tests (ASTs) that allow informed prescribing of antibiotics. Here, we describe a label-free AST that can deliver results within an hour, using an actively dividing culture as starting material. The bacteria are incubated in the presence of an antibiotic for 30 min, and then approximately 105 cells are analysed one-by-one with microfluidic impedance cytometry for 2-3 min. The measured electrical characteristics reflect the phenotypic response of the bacteria to the mode of action of a particular antibiotic, in a 30-minute incubation window. The results are consistent with those obtained by classical broth microdilution assays for a range of antibiotics and bacterial species.
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Pruebas de Sensibilidad Microbiana/métodos , Bacterias/química , Bacterias/efectos de los fármacos , Fenómenos Biofísicos , Farmacorresistencia Bacteriana , Impedancia Eléctrica , Diseño de Equipo , Humanos , Klebsiella pneumoniae/química , Klebsiella pneumoniae/efectos de los fármacos , Dispositivos Laboratorio en un Chip , Meropenem/administración & dosificación , Pruebas de Sensibilidad Microbiana/instrumentación , Técnicas Analíticas Microfluídicas/instrumentación , Técnicas Analíticas Microfluídicas/métodosRESUMEN
Purpose. Antimicrobial susceptibility is slow to determine, taking several days to fully impact treatment. This proof-of-concept study assessed the feasibility of using machine-learning techniques for analysis of data produced by the flow cytometer-assisted antimicrobial susceptibility test (FAST) method we developed.Methods. We used machine learning to assess the effect of antimicrobial agents on bacteria, comparing FAST results with broth microdilution (BMD) antimicrobial susceptibility tests (ASTs). We used Escherichia coli (1), Klebsiella pneumoniae (1) and Staphylococcus aureus (2) strains to develop the machine-learning algorithm, an expanded panel including these plus E. coli (2), K. pneumoniae (3), Proteus mirabilis (1), Pseudomonas aeruginosa (1), S. aureus (2) and Enterococcus faecalis (1), tested against FAST and BMD (Sensititre, Oxoid), then two representative isolates directly from blood cultures.Results. Our data machines defined an antibiotic-unexposed population (AUP) of bacteria, classified the FAST result by antimicrobial concentration range, and determined a concentration-dependent antimicrobial effect (CDE) to establish a predicted inhibitory concentration (PIC). Reference strains of E. coli, K. pneumoniae and S. aureus tested with different antimicrobial agents demonstrated concordance between BMD results and machine-learning analysis (CA, categoric agreement of 91 %; EA, essential agreement of 100 %). CA was achieved in 35 (83 %) and EA in 28 (67 %) by machine learning on first pass in a challenge panel of 27 Gram-negative and 15 Gram-positive ASTs. Same-day AST results were obtained from clinical E. coli (1) and S. aureus (1) isolates.Conclusions. The combination of machine learning with the FAST method generated same-day AST results and has the potential to aid early antimicrobial treatment decisions, stewardship and detection of resistance.