Using MALDI-TOF spectra in epidemiological surveillance for the detection of bacterial subgroups with a possible epidemic potential

Audrey Giraud-Gatineau, Gaetan Texier, Pierre-Edouard Fournier, Didier Raoult, Hervé Chaudet, Audrey Giraud-Gatineau, Gaetan Texier, Pierre-Edouard Fournier, Didier Raoult, Hervé Chaudet

Abstract

Background: For the purpose of epidemiological surveillance, the Hospital University Institute Méditerranée infection has implemented since 2013 a system named MIDaS, based on the systematic collection of routine activity materials, including MALDI-TOF spectra, and results. The objective of this paper is to present the pipeline we use for processing MALDI-TOF spectra during epidemiological surveillance in order to disclose proteinic cues that may suggest the existence of epidemic processes in complement of incidence surveillance. It is illustrated by the analysis of an alarm observed for Streptococcus pneumoniae.

Methods: The MALDI-TOF spectra analysis process looks for the existence of clusters of spectra characterized by a double time and proteinic close proximity. This process relies on several specific methods aiming at contrasting and clustering the spectra, presenting graphically the results for an easy epidemiological interpretation, and for determining the discriminating spectra peaks with their possible identification using reference databases.

Results: The use of this pipeline in the case of an alarm issued for Streptococcus pneumoniae has made it possible to reveal a cluster of spectra with close proteinic and temporal distances, characterized by the presence of three discriminant peaks (5228.8, 5917.8, and 8974.3 m/z) and the absence of peak 4996.9 m/z. A further investigation on UniProt KB showed that peak 5228.8 is possibly an OxaA protein and that the absent peak may be a transposase.

Conclusion: This example shows this pipeline may support a quasi-real time identification and characterization of clusters that provide essential information on a potentially epidemic situation. It brings valuable information for epidemiological sensemaking and for deciding on the continuation of the epidemiological investigation, in particular the involving of additional costly resources to confirm or invalidate the alarm.

Clinical trials registration: NCT03626987.

Keywords: Cluster analysis; Epidemic; Epidemiological surveillance; MALDI-TOF.

Conflict of interest statement

All authors report no potential conflicts.

© 2021. The Author(s).

Figures

Fig. 1
Fig. 1
Process flow of the matrix-assisted laser desorption ionization mass spectrometry mass spectra analysis, from databases to system outputs
Fig. 2
Fig. 2
Number of Streptococcus pneumoniae samples from 10 October 2019 to 12 March 2020 at AP-HM, Marseille
Fig. 3
Fig. 3
Complete Time-heated dendrogram of the 125 main spectrum profiles of S. pneumoniae illustrating the use of leaf label coloring. The colorscale shows the case recency, from to most ancient (blue color) to the most recent (red color), and then case concomitance. The interest cluster (red square) is indicated with an enlargement of the dendodragrm illustrating the possible leaf labelling using surveillance data. The stars near the leaves are the spectra involved in the alarm emitted by BALYSES
Fig. 4
Fig. 4
Double time-protein proximity heatmap resulting from the analysis of the 125 main spectrum profiles (MSP) of S. pneumoniae. The interest cluster is indicated. The bottom-right hemi-matrix shows the samples’ proteinic proximity. The top-left hemi-matrix shows the samples’ time concomitance. The colorscale is the same for the two hemi-matrices: blue corresponds to the largest distances and red to the closest ones. Spectra with closed time-protein distances appears as a square in hot colour along the matrix diagonal, as subtree A. The stars near the leaves are the spectra involved in the alarm emitted by BALYSES. Subtree D has a less epidemiological interest with a temporal heterogeneity
Fig. 5
Fig. 5
Binary discriminant analysis of the 125 main spectrum profiles (MSP) of S. pneumoniae showing the 40 top ranking peaks contrasting the 7 samples belonging to interest cluster against the other ones. Peaks are indicated using their m/z. For each selected peak the entropic ranking t-score is represented, positive when the peak is associated with the group

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