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

Abstract

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.

Keywords: Colibri; Copan; Radian; WASPLab artificial intelligence; WASPLab® platform; antimicrobial susceptibility testing; total laboratory automation.

Figure 1

High-resolution digital images of one culture media plate taken at different incubation times on the WASPLab™. Time-series image acquisitions for a clinical specimen positive with Bacillus sp., at ascending time points, is depicted here, highlighting the progressive growth of bacterial colonies. Source of all images: A. Cherkaoui, Geneva University Hospitals.

Figure 2

Total Lab automation workflows. A supposed advantage of TLA in microbiology is an improved efficiency by reducing the repetitive tasks with moderate added-value. Automated incubators with digital imaging drastically reduce the number of manipulations of the culture media plates. Currently, 97% of the identified “automatable” specimens are processed by TLA in our lab. The residual 3% corresponds to specimens that require manual sample preparation or manual inoculation of the media plates before incubation on the WASPLab (e.g., catheters, vascular or orthopedic prostheses, and chirurgical devices). Source of all images: A. Cherkaoui, Geneva University Hospitals.

Figure 3

Automated System for Colony Picking and MALDI-TOF Targets Preparation (Copan Colibrı™́ ). A pipetting system permits: i) the picking of the specific colonies determined by the technologists during the reading step on the WASPLab screen; ii) the transfer of the microorganisms’ cells on the MALDI-target; and iii) the deposition of the matrix. Two protocols are available with (or without) extraction using a formic acid. Source of all images: A. Cherkaoui, Geneva University Hospitals.

Figures 4

Improving Turn-Around Times (TAT) in clinical bacteriology by MALDI-TOF/MS. Several studies have highlighted that MALDI-TOF/MS is highly accurate to identify bacteria and yeasts isolated from clinical specimens. This approach is efficient, inexpensive, and rapid. The positive impact of the MALDI-TOF/MS in the enhancement of turn-around times (TAT) was assessed in various reports. (A) Depicts the traditional workflow using manual inoculation of the culture media plates, identification of the pathogen by traditional phenotypic methods, and manual AST by disk diffusion. (B) MALDI-TOF/MS reduces the TATs by an average of 1.45 days in comparison with the traditional phenotypic methods used for identification (Tan et al., 2012). Hence, this approach contributes to swiftly support treatment decisions, especially when the identification of the pathogen is unexpected (Angeletti et al., 2015; Verroken et al., 2016; Theparee et al., 2018). Source of all images: A. Cherkaoui, Geneva University Hospitals.

Figure 5

The antibiotics panels of the MDR (CHE2HUG / Panel A) and anaerobes (CHE1ANA / Panel B) Thermo Scientific™ Sensititre™ plates Source of all images: A. Cherkaoui, Geneva University Hospitals.