Identification of Acinetobacter Species Using MicrobialTrack and Benchtop MALDI-TOF MS

Significance of the topic

Acinetobacter species are ubiquitous Gram-negative bacteria with diverse roles ranging from environmental biodegradation to clinically relevant, multidrug-resistant pathogens. Accurate species-level identification is essential for environmental monitoring, industrial strain selection and clinical microbiology (infection control and epidemiology). Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) combined with advanced bioinformatics offers rapid, cost-effective identification but some Acinetobacter species are historically difficult to discriminate. This study demonstrates the application of benchtop MALDI-TOF MS together with MicrobialTrack software to resolve closely related Acinetobacter species with high reliability.

Objectives and overview of the study

The study aimed to evaluate the ability of a benchtop MALDI-TOF MS workflow and MicrobialTrack identification software to accurately identify 16 type strains of Acinetobacter that are typically challenging to distinguish. Key goals were to (1) acquire high-quality MALDI mass spectra from cultured strains, (2) assign observed peaks to theoretical protein masses using a large genomic database, and (3) validate species calls and their reliability using a resampling (polyphasic) algorithm and alternative extraction methods when required.

Methodology

- Samples: Sixteen Acinetobacter strains obtained from recognized culture collections (NBRC, JCM). Strains were cultured on recommended agar at 30 °C for 24 h.
- Sample preparation: Primary approach was direct smear of bacterial cells on MALDI target with α-cyano-4-hydroxycinnamic acid (CHCA) matrix (1 µL). If identification confidence was low, on-plate 25% formic acid extraction was applied; if still inconclusive, an in-tube formic acid/acetonitrile extraction was performed.
- Acquisition: Spectra were recorded in positive-ion linear mode across m/z 3,500–20,000 using a Shimadzu benchtop linear MALDI-TOF instrument (study text references MALDI-8020 for acquisition and MALDI-8030 as the benchtop model family).
- Data handling and identification: Spectra exported as ASCII and processed with MicrobialTrack, which references a database built from ~400,000 genomes representing ~85,000 prokaryotic species. Identification confidence categories included "High" and "Very High" (accepted) and lower tiers prompting further extraction and analysis. A resampling algorithm assessed robustness by randomly omitting detected peaks and repeating identifications.

Used instrumentation

- MALDI-8020 / MALDI-8030 benchtop linear MALDI-TOF mass spectrometer (Shimadzu) used for spectral acquisition and cited as the platform family.
- Matrix reagent: α-cyano-4-hydroxycinnamic acid (CHCA).
- MicrobialTrack microbial identification software, with a comprehensive genome-derived theoretical mass database and a resampling reliability function.

Main results and discussion

- Identification success: Using the direct smear CHCA method, 15 of 16 strains were identified to their reference species names with "Very High" reliability. One strain (Acinetobacter pittii NBRC 110505) required in-tube formic acid/acetonitrile extraction to reach a reliable identification, with resampling indicating 93% support for A. pittii and 3% for the closely related A. lactucae.
- Peak assignment: MicrobialTrack assigned many peaks to ribosomal proteins (classically strong MALDI peaks useful as phylogenetic markers) but also to numerous non-ribosomal proteins that appeared as major spectral features. Notable non-ribosomal assignments included glutaredoxin, bacterioferritin-associated ferredoxin, beta-lactamase hydrolase-like protein, lactoylglutathione lyase, major cold shock protein CspA, DNA-binding protein Fis, translational regulator CsrA, potassium-binding protein Kbp, regulatory protein HvrA, and TatB translocase protein.
- Interpretation caveat: Assignments are based on matching observed masses to theoretical masses (including consideration of unmodified proteins and predicted N-terminal methionine truncations). A matched mass within the accepted error does not constitute absolute biochemical confirmation of protein identity, only a plausible assignment for biomarker and typing purposes.
- Resampling validation: The proprietary resampling approach (random removal of detected peaks and reanalysis) supported the robustness of identifications for all strains except the close A. pittii/A. lactucae pair, for which resampling still strongly supported the A. pittii call.

Benefits and practical applications

- Rapid species-level identification: The benchtop MALDI-TOF workflow enables fast acquisition and identification compared with conventional biochemical or DNA-sequencing methods, valuable for clinical labs, environmental monitoring and industrial strain screening.
- High discriminatory power: Integration with MicrobialTrack's large theoretical-mass database and resampling improves discrimination within the Acinetobacter genus, including closely related members of the A. baumannii complex.
- Flexible sample preparation: A tiered extraction strategy (direct smear → on-plate formic acid → in-tube extraction) provides a pragmatic route to improve identification confidence when spectra are ambiguous.
- Typing potential: By reporting matched amino acid sequences for assigned peaks, the workflow supports biomarker-based sub-species or strain-level typing based on subtle sequence variations in target proteins.

Future trends and potential applications

- Expansion of databases: Increasing the breadth and curation of genome-derived theoretical mass libraries will further improve identification scope and accuracy, especially for environmental and rare taxa.
- Improved protein confirmation: Complementary methods (targeted proteomics, MS/MS fragmentation, or orthogonal biochemical validation) could confirm protein identifications suggested by mass matching and strengthen biomarker-based typing.
- Automated quality control: Integration of automated sample-prep decision trees and confidence-driven extraction protocols could streamline workflows in high-throughput clinical and industrial settings.
- Real-time epidemiology: Rapid MALDI-TOF identification coupled with strain-level typing could accelerate outbreak detection and antimicrobial stewardship efforts for problematic Acinetobacter pathogens.
- Machine learning: Advanced pattern recognition and ML models trained on spectral and theoretical-mass features may enhance discrimination between very closely related species and improve robustness to sample variability.

Conclusion

The combined use of a benchtop MALDI-TOF MS platform and MicrobialTrack software reliably identified 15 of 16 tested Acinetobacter type strains directly from CHCA-smear spectra and resolved the remaining ambiguous strain after optimized extraction. The approach leverages both ribosomal and non-ribosomal protein signals and employs a resampling algorithm to quantify identification robustness. While theoretical-mass assignments are powerful for rapid identification and typing, they should be interpreted with awareness of their inferential nature and, when needed, supported by orthogonal validation for definitive protein confirmation.

References

1. Teramoto K., Nishikaze T. Identification of Acinetobacter Species Using MicrobialTrack and Benchtop MALDI-TOF MS. Shimadzu Application News. First Edition: March 2026. Shimadzu Corporation.
2. MicrobialTrack product documentation and database description. Shimadzu Corporation, 2026.