Analysis of the efficacy of MALDI-TOF MS technology in identifying microorganisms in cancer patients and oncology hospital environment

Abstract

Rapid diagnostics of microbes in hospitals are crucial for promptly identifying infections, enabling timely and appropriate treatment. The study was conducted to evaluate the effectiveness of the matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI TOF MS) technology in the microbial profiling of hospital environments and patient samples. The objective was to determine the microbial landscape in swabs collected from hospitalized patients and their immediate environments, using MALDI to compare the capabilities of two systems: BRUKER and ZYBIO. The analysis resulted in 1012 microbial identifications from patient samples (N = 81), encompassing 96 species, and 1496 identifications from hospital surface samples (N = 108), covering 124 species. Predominantly identified microorganisms in patients' samples included Staphylococcus epidermidis, Staphylococcus aureus, Staphylococcus capitis, Steptococcus salivarius, and Micrococcus luteus, whereas environmental samples chiefly yielded S. epidermidis, Staphylococcus hominis, Staphylococcus warneri, and Microcccus luteus. 33 species were found in both types of samples, highlighting a significant microbial interchange within hospital settings. Both MALDI systems showed high consistency in results at both genus and species levels. Nevertheless, mismatches in identification between both MALDI systems were noted, particularly within Brevibacterium, Streptococcus, Bacillus, Staphylococcus, and Neisseria genera. This study presents the precision of MALDI technology in microbial identification and highlights the need for ongoing enhancements, especially in the expansion and updating of databases, to bolster its diagnostic effectiveness further.

Keywords: Healthcare environments; MALDI-TOF MS; Microorganisms' identification; Opportunistic bacteria; Pathogen detection.

Fig. 1

Bacterial Composition and Gram Staining Classification Across Analyzed Specimens. a) distribution of Gram-positive (G+) and Gram-negative (G-) bacterial populations within the examined specimens, b) taxonomic identification of bacterial species derived from patient swabs (yellow labels indicate the quantity of statistically significant identifications by ZYBIO, white labels indicate BRUKER identifications), c) taxonomic distribution of bacterial species isolated from hospital environments. Species constituting less than 1 % of the total identified population are aggregated into an "Other" Category to enhance chart legibility.

Fig. 2

Quantitative Distribution of Eight Predominant Bacterial Species Isolated from Patient (a) and Hospital Environments (b) indicated by occurrence percentage in collected samples. The diameter of each circle is proportional to the relative abundance of corresponding bacterial species within the analyzed samples. Chromatic variation distinguishes among diverse bacterial species.

Fig. 3

The Proportion of High-confidents Identification of Unique and Coincident Bacteria Collected from Patient (P) (a) and Hospital Environment (HS) (b) with 33 bacteria Species Identified in Both Type of Samples. The same genus of bacteria identified in P and HS samples are presented as list. Identification results of the Bruker system.

Fig. 4

Comparative Analysis of Microorganism Identifications via BRUKER (B) and ZYBIO (Z) Systems from Hospital Surfaces and Patient Samples. Statistical significance between B and Z identification was assessed using Student's t-test, with p-values indicated by red asterisks: ∗p < 0.05, ∗∗p < 0.01.

Fig. 5

Variability in MALDI-TOF MS Identification Across Sample Types: (a) Patient Samples and (b) Hospital Environment. ZYBIO Identification Scores Are Highlighted in Yellow, with a Corresponding Yellow Line Illustrating the Trend in Score Fluctuations. Alternative species to BRUKER identification were denoted on the bar chart columns. To enhance chart clarity, only the most prevalent bacterial species were presented. Detailed descriptions of bacterial species identified exclusively by ZYBIO are provided in the Supplementary Materials.

Fig. 6

Two-Dimensional Scatter Plot Illustrating the Comparative Distribution of Identification Scores from BRUKER to ZYBIO. The percentage values assigned to four parts of the chart reflecting the quality of identification. Samples derived from hospital and environmental sources are represented as red and green points, respectively.

Fig. 7

The pie charts demonstrate the level of overall mismatch in patient (a) and hospital environmental samples (b).