The Applications of MALDI-TOF MS in the Diagnosis of Microbiological Food Contamination

Abstract

Microbiological contamination of food remains a critical global public health concern, contributing to millions of foodborne illness cases each year. Traditional diagnostic methods, particularly culture-based techniques, have been widely employed but are often limited by low sensitivity, insufficient specificity, and lengthy turnaround times. Recent advances in molecular biology, biosensor technology, and analytical chemistry have enabled the development of more rapid and precise diagnostic tools. Among these, Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF MS) has emerged as a transformative method for microbial identification. This review provides a comprehensive overview of the current applications of MALDI-TOF MS in the diagnosis of microbiological contamination in food. The method offers rapid, accurate, and cost-effective identification of microorganisms and is increasingly used in food safety laboratories for the detection of foodborne pathogens, ensuring the safety and quality of food products. We highlight the fundamental principles of MALDI-TOF MS, discuss its methodologies, and examine its advantages, limitations, and future prospects in food microbiology and quality assurance.

1. Introduction

Ensuring food safety is a fundamental public health concern and a critical component of the global food supply chain. Each year, millions of cases of foodborne illnesses are reported worldwide, many resulting in hospitalization or death, particularly in vulnerable populations such as children, the elderly, and immunocompromised individuals. Contaminated food can serve as a vehicle for a diverse range of pathogenic microorganisms, including bacteria (Salmonella spp., Listeria monocytogenes, Escherichia coli O157:H7), viruses (e.g., norovirus, hepatitis A), fungi, and parasites. In addition to pathogens, spoilage organisms and microbial toxins also present significant challenges to food quality and shelf life, with substantial economic consequences for producers, retailers, and consumers alike [1,2,3,4,5,6,7,8,9].

Rapid and accurate detection and identification of microbial contaminants are essential for preventing outbreaks, minimizing product recalls, and ensuring compliance with food safety regulations such as those established by the Codex Alimentarius, the European Food Safety Authority (EFSA), and the U.S. Food and Drug Administration (FDA). Traditional microbiological methods, including culture-based identification, biochemical profiling, and serotyping, are often time-consuming, labor-intensive, and limited in resolution, particularly when distinguishing closely related species or subspecies [2,10,11,12,13].

In recent decades, the introduction of molecular diagnostics—including polymerase chain reaction (PCR), quantitative PCR (qPCR), next-generation sequencing (NGS), and whole genome sequencing (WGS)—has significantly improved the sensitivity and specificity of microbial detection. However, these techniques have limitations: they often require skilled personnel, costly reagents, extensive sample preparation, and, in some cases, cannot differentiate between viable and non-viable cells [14,15,16,17,18,19,20].

Within this evolving landscape, MALDI-TOF MS has emerged as a powerful tool, particularly in clinical microbiology, and is now rapidly gaining traction in food microbiology. MALDI-TOF MS enables the rapid identification of microorganisms based on the unique mass spectral fingerprints of their ribosomal proteins. It combines speed, low per-sample cost, and high-throughput capabilities, making it particularly attractive for routine monitoring in food safety laboratories, industrial quality assurance settings, and public health surveillance programs [21,22,23,24].

The principle of MALDI-TOF MS lies in the ionization of microbial peptides followed by their separation based on mass-to-charge (m/z) ratios. The resulting spectra are then matched against reference libraries to generate accurate identifications of microorganisms, often to the species level. This approach eliminates the need for time-consuming biochemical tests or DNA sequencing for many routine analyses and provides results within minutes, once a culture is available [15,25,26,27,28].

Beyond simple microbial identification, the versatility of MALDI-TOF MS extends to its applications in strain-level typing, detection of antimicrobial resistance, monitoring of fermentation processes, authentication of food origin, and traceability of contamination sources. These advanced capabilities make MALDI-TOF MS a valuable tool, not only for pathogen diagnostics, but also for broader microbial ecosystem surveillance and quality assurance [25,29,30,31,32,33].

Despite its many advantages, the deployment of MALDI-TOF MS in the food sector presents certain challenges, including the need for robust and curated spectral databases that reflect the diversity of microorganisms encountered in food environments, the difficulty in analyzing mixed or complex matrices, and the current dependence on cultured isolates. Addressing these limitations through ongoing technological advances and efforts to standardize procedures will be crucial for realizing the full potential of MALDI-TOF MS in food safety [15,28,34,35,36].

This review aims to provide a comprehensive overview of the principles, current applications, advantages, and limitations of MALDI-TOF MS in the diagnosis of microbiological contamination in food. Special emphasis is placed on the detection and identification of foodborne pathogens, microbial spoilage organisms, and the technique’s expanding role and traceability assessments. In doing so, the review also outlines future directions for research and technological development, emphasizing the integration of MALDI-TOF MS into modern food safety management systems.

2. The Principles of MALDI-TOF MS

MALDI-TOF MS is an analytical technique that has become a cornerstone in microbial identification, particularly due to its speed, high sensitivity, and low sample-preparation requirements [37,38,39]. The principle of MALDI-TOF MS is based on the ionization of biomolecules—primarily ribosomal proteins—followed by analysis of their mass-to-charge (m/z) ratios using a time-of-flight detector system (Figure 1). The technique enables the generation of distinct spectral fingerprints, characteristic of specific microorganisms, which can be matched against comprehensive spectral databases for accurate taxonomic identification [40].

2.1. Sample Preparation

The effectiveness of MALDI-TOF MS is highly dependent on the quality of sample preparation. For microbiological applications, a single colony from a culture plate is typically transferred to a MALDI target plate. In the direct transfer method, the sample is overlaid with a matrix solution—most commonly α-cyano-4-hydroxycinnamic acid (HCCA)—which assists in the desorption and ionization of cellular components. For more robust or encapsulated microorganisms (e.g., Gram-positive bacteria, yeasts), a formic acid-based extraction step is often included to enhance protein solubilization and promote the release of ribosomal proteins, which are the primary targets for identification due to their high abundance and species-specific profiles [41,42,43,44,45,46].

2.2. Laser Desorption/Ionization

Upon drying, the co-crystallized matrix and sample are irradiated with a pulsed ultraviolet laser, typically a nitrogen laser emitting at 337 nm. The matrix absorbs the energy from the laser pulse and undergoes rapid sublimation, carrying the analyte molecules into the gas phase. During this process, the matrix also facilitates ionization—primarily via proton transfer mechanisms—resulting in the formation of mainly singly charged ions of microbial proteins. This soft ionization ensures minimal fragmentation, preserving the integrity of the protein ions for mass analysis [37,47,48,49].

2.3. Time-of-Flight Mass Analysis

Once ionized, the charged biomolecules are accelerated through an electric field into a field-free drift region (the flight tube). The ions are separated according to their mass-to-charge m/z ratios; lighter ions travel faster and reach the detector before heavier ones. The time each ion requires to reach the detector is recorded and converted into a mass spectrum. The resulting spectrum typically displays of multiple peaks within the 2000–20,000 Dalton range, corresponding primarily to ribosomal and housekeeping proteins [50,51,52,53,54].

2.4. Spectral Interpretation and Identification

The mass spectrum generated from each microorganism serves as a proteomic profile, which is reproducible under consistent growth and preparation conditions. These profiles are compared against a reference database using proprietary algorithms (e.g., Bruker Biotyper, VITEK MS). Matching is based on the presence, intensity, and position of peaks within the spectrum. A successful match provides identification at the genus or species level, and in some cases, subspecies or strain level, depending on database resolution [55,56,57].

2.5. Key Analytical Considerations

The successful implementation of MALDI-TOF MS in microbiological diagnostics, particularly within the complex domain of food microbiology, hinges not only on the underlying physical principles, but also on a number of critical analytical parameters that directly impact accuracy, reliability, and reproducibility. These considerations are essential for achieving high-quality, interpretable spectra that can be confidently matched against reference libraries. Among the most influential of these factors are instrumental resolution and mass accuracy, reproducibility of spectral acquisition, and the depth and quality of reference databases [26,41,58].

(a)

Resolution and Accuracy:

High-resolution mass spectrometric performance is fundamental to the discriminatory power of MALDI-TOF MS, especially when distinguishing between phylogenetically related microbial taxa. Modern MALDI-TOF MS instruments, particularly those used in clinical and food microbiology laboratories, routinely achieve mass accuracies better than 500 parts per million (ppm), with time-of-flight analyzers delivering resolutions sufficient to distinguish subtle differences in the proteomic fingerprints of closely related species [59,60,61].

The most informative region of the spectrum typically lies within the 2000 to 20,000 Da range, dominated by highly conserved ribosomal and housekeeping proteins. Precision in mass determination within this window ensures not only species-level resolution but, under optimized conditions, can also enable sub-species or even strain-level differentiation, particularly when used in tandem with advanced spectral analysis software and biomarker-based classification models [56,61,62].

Instrument calibration using standardized peptides or control strains is essential to maintain this level of accuracy over time. Additionally, environmental factors such as ambient temperature, laser power, and electronic noise must be carefully controlled or compensated for to avoid peak shifting or signal distortion, which could lead to false identification or poor reproducibility [25,42,63].

(b)

Reproducibility:

One of the core strengths of MALDI-TOF MS is its potential for reproducible, high-throughput microbial identification. However, this reproducibility is highly dependent on strict standardization of the entire analytical workflow—from culture conditions to matrix composition and sample deposition protocols [58,64,65,66].

Variability in microbial culture media, incubation times, or growth phase can significantly alter the expression profile of cellular proteins, resulting in spectra that deviate from reference standards. Similarly, inconsistencies in sample spotting (e.g., uneven drying, crystallization artifacts) or matrix application (e.g., saturation level, solvent composition) can produce variability in ionization efficiency and peak intensity. These discrepancies not only impact identification confidence scores, but may also hinder inter-laboratory comparability [64,67,68].

To mitigate such issues, many laboratories implement validated protocols that include defined growth conditions (e.g., temperature, media type, incubation duration), standardized extraction procedures (e.g., formic acid/acetonitrile treatment for Gram-positive bacteria or yeasts), and strict criteria for spectrum quality (e.g., signal-to-noise ratio thresholds, internal standard alignment). The use of automated spotting and matrix deposition systems can further enhance reproducibility, especially in high-throughput industrial environments [69,70,71].

(c)

Databases:

Perhaps the most critical determinant of identification accuracy in MALDI-TOF MS is the spectral reference database against which unknown profiles are matched. These databases comprise mass spectral fingerprints obtained under defined conditions and annotated at various taxonomic levels. The depth, diversity, and taxonomic breadth of these libraries directly influence the system’s capacity to identify a wide range of microorganisms, including rare, emerging, or atypical strains encountered in food matrices [12,72,73,74,75].

Commercially available databases, such as those provided by Bruker (Biotyper) and bioMérieux (VITEK MS), are primarily optimized for clinical pathogens and often lack comprehensive coverage of environmental and food-associated microbiota, including beneficial fermentative species, food spoilage organisms, and region-specific variants [57,76,77,78]. As a result, organisms not represented in the library may yield “no identification” results or may be misidentified, based on the closest spectral match. In

Table 1. Commercial systems available for MALDI-TOF MS microorganism identification applications [79].

Software and Database	Microbe Lynx System (Waters Corporation and Manchester Metropolitan University)	Maldi Biotyper (Bruker Daltonics) (Billerica, MA, USA)	SARAMIS (AnagnosTec GmbH) (Potsdam, Germany)	MS-ID (BioM Rieux) (Craponne, France)
Mass Spectrometer	Micro MX (Waters Corporation, Milford, MA, USA)	Microflex (Bruker, Billerica, MA, USA)	Axima (Shimadzu, Tokyo, Japan)	Vitek MS (BioM Rieux, Craponne, France)
Identification	Areobic/anaerobic bacteria	Bacteria, yeast and filamentous	Bacteria, yeast and filamentous	Bacteria, yeast and filamentous
Range	500–15,000 Da	2000–20,000 Da	2000–20,000 Da	2000–20,000 Da
Requires Sample Preparation	Yes (depends on the culture medium)	No	No	No
Reproducibility	Low	High	High	High

, the comparison of commercial systems available for MALDI-TOF MS microorganism identification applications is shown.

To address this gap, many research and regulatory laboratories develop custom or extended in-house databases tailored to their specific analytical context. These curated libraries may include isolates from regional food products, artisanal fermentations, or environmental swabs from production facilities. Incorporating metadata such as source, serotype, virulence factors, and antimicrobial resistance genes can further enrich the interpretive value of the database.

Regular updating, validation, and sharing of these spectral libraries within the scientific community are crucial for improving cross-laboratory standardization and for supporting surveillance efforts against emerging foodborne threats. In the future, open-access global repositories may enable decentralized contributions and machine learning-enhanced classification models that transcend the limitations of static, vendor-locked libraries [36,61,79,80,81].

2.6. Advantages of MALDI-TOF over Conventional Techniques

The application of MALDI-TOF MS in microbiological diagnostics represents a paradigm shift from traditional identification methods. Its introduction into food microbiology has brought significant operational, analytical, and economic advantages that address many of the limitations associated with classical microbiological workflows. Compared to conventional phenotypic and molecular approaches, MALDI-TOF MS offers superior performance across several key dimensions, including speed, accuracy, cost-effectiveness, throughput, and versatility [25,71,82].

(a)

Rapid Turnaround Time:

Perhaps the most defining advantage of MALDI-TOF MS is its ability to deliver microbial identification within minutes, once a pure colony is available. In contrast to biochemical and phenotypic methods, which often require 24–72 h for completion, MALDI-TOF MS can generate high-confidence identifications in less than 5 min per isolate. This rapid turnaround is particularly valuable in food safety contexts, where timely detection of pathogens or spoilage organisms is essential to prevent product recalls, production delays, or public health crises. Furthermore, when integrated with streamlined culturing and automated sample preparation, MALDI-TOF MS facilitates same-day diagnostics—a capability largely unmatched by traditional techniques [59,83].

(b)

High Accuracy and Specificity:

MALDI-TOF MS exhibits high specificity in identifying microorganisms at the genus and species levels by analyzing highly conserved, yet species-distinctive, ribosomal proteins. Its accuracy has been demonstrated to rival, and in many cases surpass, that of biochemical identification systems such as API strips or VITEK cards, which rely on variable phenotypic traits influenced by environmental and growth conditions [78,84,85].

Unlike 16S rRNA gene sequencing—which is sometimes limited in resolving closely related species due to conserved sequence regions—MALDI-TOF MS can discriminate between taxa that share over 99% sequence identity. This protein-level resolution enhances its utility in differentiating foodborne pathogens from harmless commensals or distinguishing spoilage strains that require targeted mitigation [86,87,88].

(c)

Cost Efficiency and Low Per-Sample Expense:

While the initial capital investment for a MALDI-TOF MS system is relatively high, its operational cost per sample is substantially lower than most molecular or phenotypic assays. Reagents required for sample processing (e.g., matrix, formic acid, solvents) are inexpensive, and once a system is in place, the marginal cost of running hundreds of isolates is negligible [28,59].

Compared to molecular assays—such as PCR, which necessitate costly enzymes, primers, and thermal cyclers—or sequencing, which involves reagents and bioinformatics analysis, MALDI-TOF MS offers a highly economical alternative for routine surveillance and quality control testing in food laboratories [28].

(d)

Minimal Sample Preparation and High Throughput:

MALDI-TOF MS workflows are streamlined and highly adaptable for high-throughput processing. The minimal sample preparation—often involving direct transfer of a colony to a target plate, followed by matrix application—enables rapid handling of large sample volumes with limited hands-on time [41,89].

When combined with automation tools, such as robotic spotting systems or automated matrix dispensers, MALDI-TOF MS can process several hundred isolates per day. This makes it particularly suitable for industrial-scale food microbiology laboratories engaged in continuous environmental monitoring and product testing [36].

(e)

Broad Taxonomic Coverage:

A single MALDI-TOF MS platform can identify a wide range of microorganisms—including Gram-positive and Gram-negative bacteria, yeasts, molds, and even some filamentous fungi—without the need for organism-specific primers or biochemical panels. This universal applicability eliminates the need for multiple parallel assays and reduces the risk of overlooking unexpected contaminants [46,85,90].

In mixed-product environments such as dairy, meat, and fermented foods, this breadth is especially useful for detecting both pathogens and quality-relevant microbes (e.g., Lactobacillus, Saccharomyces), providing a comprehensive microbiological profile from a single-assay platform [33,55,58].

(f)

Reduced Dependence on Reagents and Kits:

MALDI-TOF MS does not rely on enzymatic reagents, diagnostic kits, or colorimetric substrates, all of which are subject to lot-to-lot variability, expiration, and supply chain interruptions. This independence enhances the robustness and sustainability of laboratory workflows, especially in resource-constrained or high-throughput settings [19,26,91].

Furthermore, since the technique is label-free and non-destructive (in some protocols), remaining culture material can often be used for confirmatory testing, strain preservation, or downstream genomic analysis [17,25].

(g)

Compatibility with Emerging Data Analytics

MALDI-TOF MS is inherently digital, generating mass spectral data that are well suited to advanced computational analyses, including machine learning, biomarker discovery, and predictive modeling. As a result, it integrates naturally with digital microbiology platforms and laboratory information management systems (LIMSs), enabling real-time surveillance, data mining, and integration with broader food safety informatics systems [32,61,92].

The potential to link spectral data with genomic, phenotypic, and metadata (e.g., product type, geography, antimicrobial resistance) will enhance traceability and outbreak-investigation capabilities in the coming years.

To sum up, MALDI-TOF MS offers a compelling combination of speed, accuracy, affordability, and versatility, which positions it as a superior alternative to many conventional microbial identification methods in food microbiology. While it does not fully replace all traditional techniques—particularly in applications requiring strain-level typing, toxin detection, or culture-independent diagnostics—it significantly enhances the efficiency and diagnostic power of food safety laboratories across the globe.

3. Applications in Food Microbiology

3.1. Identification of Foodborne Pathogens

The identification of foodborne pathogens is a critical component of food safety monitoring, public health surveillance, and outbreak investigation. Traditional microbiological techniques for identifying these pathogens—such as biochemical profiling, serotyping, and molecular assays—are often labor-intensive, time-consuming, and require skilled personnel. In contrast, MALDI-TOF MS offers a high-throughput, rapid, and cost-effective alternative for the routine identification of microbial contaminants, e.g., in food microbiology (Figure 2) [19,93].

MALDI-TOF MS enables the identification of a wide spectrum of foodborne bacterial pathogens, including, but not limited to, Salmonella enterica, Escherichia coli (including enterohemorrhagic strains), Listeria monocytogenes, Campylobacter jejuni, Clostridium perfringens, Staphylococcus aureus, and Bacillus cereus. These organisms are among the most prevalent causes of foodborne illnesses worldwide, and are often associated with meat, dairy, and poultry produce, and processed food products [26,94,95].

The identification process is based on the generation of mass spectral fingerprints from intact cells or extracted proteins, primarily ribosomal proteins ranging from 2 to 20 kDa. Each microbial species yields a unique and reproducible spectrum that is compared to a reference database using pattern-matching algorithms. This approach allows for the discrimination of microorganisms at the species level and, in certain cases, the subspecies or strain level, depending on the resolution of the spectral database employed [41,58,79].

Several studies have demonstrated the robustness of MALDI-TOF MS in accurately identifying foodborne pathogens directly from culture plates within minutes. For instance, Bruker’s MALDI Biotyper system and bioMérieux’s VITEK MS system have been validated for use in food microbiology laboratories and are widely employed across regulatory and industrial settings. These platforms support compliance with ISO 16140-2: 2016 standards for alternative microbiological methods in food testing [28,96,97].

A significant advantage of MALDI-TOF MS is its ability to differentiate between closely related species and even distinguish between pathogenic and non-pathogenic strains, under optimized conditions. For example, it can differentiate E. coli from Shigella spp. or discriminate between Listeria monocytogenes and other non-pathogenic Listeria species, provided the reference library includes high-quality strain-level entries [98,99,100,101].

Moreover, MALDI-TOF MS has been applied in outbreak investigations where rapid identification of the etiological agent is critical. Its speed facilitates near real-time identification, supporting traceability efforts and minimizing the extent of food recalls. In addition to fresh and minimally processed foods, MALDI-TOF MS has also been used to monitor microbial contaminants in processed and fermented products, where the microbiota is more complex [96,102].

Despite its advantages, some limitations persist in the direct application of MALDI-TOF MS to food samples, due to complex matrices and low microbial loads. Therefore, enrichment steps or selective culturing are often necessary prior to analysis. Nevertheless, ongoing improvements in sample preparation protocols, matrix optimization, and database expansion continue to enhance the sensitivity and specificity of the method.

In summary, MALDI-TOF MS has emerged as a transformative tool in the rapid and accurate identification of foodborne pathogens, contributing significantly to microbial risk assessment, quality control, and outbreak prevention in the food industry.

3.2. Detection of Spoilage Organisms

Microbial spoilage of food products leads to significant economic losses and poses a risk to consumer health, even in the absence of overt pathogenicity. Spoilage organisms—such as psychotropic bacteria, lactic acid bacteria, yeasts, and molds—degrade food through enzymatic and metabolic activities, resulting in undesirable sensory changes including off-odors, discoloration, gas production, and texture alterations. Early and accurate detection of these microorganisms is critical for maintaining product quality, extending shelf life, and ensuring consumer satisfaction [7,9,28,103].

MALDI-TOF MS has proven to be a powerful tool for the rapid identification of spoilage-associated microorganisms in diverse food matrices, including dairy, meat, fish, beverages, and ready-to-eat products. Unlike traditional microbiological methods, which often require days of culturing followed by extensive biochemical testing, MALDI-TOF MS enables species-level identification in under one hour post-culture, significantly accelerating decision-making in food production and distribution [28,104,105].

Spoilage organisms commonly identified using MALDI-TOF MS include species from the genera Pseudomonas, Brochothrix, Shewanella, Leuconostoc, Lactobacillus, Candida, Saccharomyces, and Penicillium. These organisms are responsible for a range of spoilage phenomena, depending on the food matrix and storage conditions. For instance, Pseudomonas fluorescens and Shewanella putrefaciens are the predominant spoilage bacteria in aerobically stored chilled meat and fish, while lactic acid bacteria such as Leuconostoc mesenteroides are frequently implicated in gas formation and package swelling in vacuum-packed products [28,33,71,106,107,108].

The identification workflow for spoilage organisms using MALDI-TOF MS follows a similar procedure to that for pathogens: isolated colonies are subjected to direct spotting or a protein extraction protocol, followed by matrix application, laser desorption/ionization, and spectral comparison against a curated database. The resulting identification enables food producers to determine spoilage trends, validate shelf-life claims, and adjust storage or packaging conditions accordingly.

In quality assurance programs, MALDI-TOF MS is increasingly used as part of spoilage monitoring systems. It allows for the longitudinal tracking of microbiota changes during food processing and storage, providing insights into the ecological succession of spoilage organisms. This can inform predictive microbiology models and help manufacturers design better intervention strategies to prevent spoilage.

Furthermore, MALDI-TOF MS has been utilized to monitor spoilage organisms in controlled fermentation processes (e.g., cheese, yogurt, salami), where a balance between desired and undesired microbial populations is essential. In such cases, the technique supports the rapid verification of starter culture integrity and early detection of spoilage contaminants that may compromise product consistency or safety [109,110,111].

However, challenges remain in distinguishing closely related spoilage strains, especially those with similar proteomic profiles. Moreover, low biomass and the presence of complex food components (e.g., fats, polyphenols) can interfere with spectral quality. Efforts to improve detection sensitivity include pre-enrichment, differential culturing, and optimization of protein extraction protocols. The development of spoilage-specific spectral libraries is also crucial to improving taxonomic resolution in food microbiology applications [28,102,112].

In conclusion, MALDI-TOF MS offers a robust, efficient, and scalable solution for the detection and identification of spoilage organisms in food production environments. Its implementation enhances quality control, reduces food waste, and strengthens consumer trust through improved product stability and shelf-life management.

3.3. Authentication and Traceability

Authentication and traceability are critical components of food quality assurance, regulatory compliance, and supply chain transparency. Food authentication refers to the verification of the origin, species, or production methods of food products, while traceability involves the systematic tracking of food through all stages of production, processing, and distribution. Both are essential to combat food fraud, ensure labeling accuracy, protect regional designations (e.g., Protected Designation of Origin, PDO), and respond swiftly to food safety incidents [105,113,114].

MALDI-TOF MS has emerged as a valuable analytical tool in supporting both authentication and traceability efforts in food systems. Its ability to generate species- or strain-specific proteomic fingerprints allows for the discrimination of microbial communities associated with specific foods, production environments, or geographic regions. These microbial signatures, often referred to as “microbiomes” or “microbial terroirs,” can act as biological indicators of product origin and production history [5,103].

One of the most promising applications of MALDI-TOF MS in this context is the identification and differentiation of microbial populations in fermented and processed foods. Fermentation processes, whether natural or starter culture-driven, result in complex and relatively stable microbial consortia that can be characteristic of specific production methods or regions. For example, MALDI-TOF MS has been used to differentiate Lactobacillus and Streptococcus species in cheeses produced in different regions, or to identify unique yeast strains in traditional sourdoughs, beers, or wines, enabling verification of artisanal or protected-status products [111,115,116].

In addition to product authentication, MALDI-TOF MS supports traceability by enabling the monitoring of microbial contaminants or environmental isolates throughout the food production chain. By constructing a microbial fingerprint database specific to a facility, raw material, or processing step, it is possible to rapidly trace sources of contamination or spoilage. This is especially valuable in ready-to-eat foods or minimally processed products, where microbial control is paramount and the identification of contamination sources must be both rapid and precise [105,108,113].

Furthermore, strain-level typing using MALDI-TOF MS has been investigated as a method for tracking pathogen outbreaks. Although MALDI-TOF MS is less discriminatory than WGS or pulsed-field gel electrophoresis (PFGE), recent advances in spectral analysis algorithms and the development of strain-specific biomarker libraries have improved its utility in epidemiological investigations. It can serve as a rapid preliminary screening tool to identify potential outbreak clones before confirmatory genotyping methods are applied [117,118,119,120].

MALDI-TOF MS has also demonstrated value in verifying the authenticity of probiotic products. In this context, it is used to confirm that marketed strains match the label claim and that no undesired or potentially harmful microbial species are present. This application is increasingly important, given the growing consumer demand for functional foods, the regulatory need to substantiate probiotic efficacy, and safety [3,111].

However, successful deployment of MALDI-TOF MS for authentication and traceability requires robust and curated databases, as well as standardized protocols for sample handling and data interpretation. Matrix effects, especially in complex food substrates, can hinder spectral quality and affect identification reliability. Thus, continuous development of food-specific spectral libraries, combined with metadata such as geographic origin and production details, is essential for maximizing the discriminatory power of the technology.

In conclusion, MALDI-TOF MS holds significant potential in enhancing the authentication and traceability of food products by providing rapid, reproducible, and high-resolution microbial fingerprints. When integrated into food-quality management systems, it offers a proactive approach to verifying product integrity, combating fraud, and reinforcing consumer confidence in the global food supply.

3.4. Section Summary

To sum up, the applications of MALDI-TOF MS in the detection and identification of various foodborne pathogens are summarized in

Table 2. Selected Applications of MALDI-TOF MS for the Detection of Foodborne Pathogens.

Application Type	Food Matrix	Target Organism(s)	MALDI-TOF MS Role	Reference
Routine pathogen identification	Meat	Salmonella spp., Listeria spp.	Rapid identification from colony isolates	[121]
Quality control during production	Cheese and milk	E. coli	Strain-level identification	[122]
Post-processing contamination detection	Ready-to-eat foods	Listeria monocytogenes	Confirmation of isolates	[123]
Detection of spoilage bacteria	Vacuum-packed meat	Brochothrix thermosphacta	Differentiation of spoilage flora	[124]
Microbiota profiling	Fermented vegetables	Lactobacillus spp.	Typing of beneficial microorganisms	[125]
Outbreak-source tracing	Infant formula	Cronobacter sakazakii	Strain tracking in epidemiology	[126]
Seafood pathogen monitoring	Raw seafood	Vibrio spp., Aeromonas spp.	Identification of marine bacteria	[127]
Hygiene monitoring	Food-contact surfaces	Various Gram-negative bacteria	Surface swab screening	[128]
Detection of resistant strains	Mixed food products	Klebsiella pneumoniae, A. baumannii	Species ID with resistance context	[129]
Rapid detection of outbreaks	Mixed retail samples	E. coli O157:H7	Fast confirmation of pathogen	[130]
Rapid detection of Listeria monocytogenes	Various food products	Listeria monocytogenes	Reduced detection time	[131]
Detection of food adulterations	Milk	Bovine and non-dairy milk	Lipid fingerprinting	[132]
Detection of Cronobacter spp.	Environmental samples	Cronobacter spp.	Identification in environmental surveillance	[133]
Identification of atypical Listeria spp.	Various food products	Listeria spp.	Identification of atypical strains	[134]
Discrimination of Salmonella Enteritidis	Poultry	Salmonella enteritidis	Rapid serovar discrimination	[135]

. It includes information about the food matrices in which MALDI-TOF MS is used, the target microorganisms, the role of MALDI-TOF MS in the diagnostic process, and the corresponding references.

The MALDI-TOF MS method is widely used for rapid identification of bacterial strains, detection of contamination in food products, and epidemiological studies, including outbreak investigations and strain tracking.

4. Limitations and Challenges

Despite the numerous advantages and growing adoption of MALDI-TOF MS in food microbiology, the technique is not without its limitations. These constraints span technical, operational, and biological aspects that can impact the reliability, resolution, and scope of microbial identification in complex food systems. A nuanced understanding of these challenges is essential for the appropriate application of the technology and for guiding future developments.

4.1. Dependence on Reference Databases

One of the primary limitations of MALDI-TOF MS is its reliance on comprehensive and high-quality spectral reference databases. The identification of an unknown microorganism is contingent on the presence of its reference profile within the database. Many commercially available databases are heavily biased toward clinically relevant bacteria and may lack sufficient coverage of foodborne pathogens, spoilage organisms, or environmental isolates commonly encountered in food production. Consequently, rare, novel, or region-specific strains may remain unidentified or be misclassified [81,136,137].

To address this, laboratories are encouraged to develop custom in-house libraries, tailored to the specific microbial profiles encountered in their operational settings. However, creating and validating these databases requires considerable time, resources, and expertise, and standardization across laboratories remains limited.

4.2. Limited Discrimination Between Closely Related Strains

While MALDI-TOF MS is effective at genus- and species-level identification, its ability to discriminate at the subspecies or strain level is inherently limited. Closely related species, such as Escherichia coli and Shigella spp., or Bacillus cereus group members, often share highly similar ribosomal protein profiles, making them difficult to resolve without additional confirmatory tests. For applications requiring high-resolution typing—such as outbreak tracking, virulence profiling, or regulatory differentiation—more discriminatory techniques like WGS or multi-locus sequence typing (MLST) are preferred [66,71,138].

Ongoing efforts to enhance strain-level resolution through improved algorithms, machine learning, and biomarker discovery are promising, but not yet widely implemented in commercial platforms.

4.3. Inability to Detect Viable but Non-Culturable (VBNC) Organisms

MALDI-TOF MS identification typically requires cultured isolates. As such, it is inherently limited in detecting microorganisms in a VBNC state or in environments where selective media are ineffective. Many foodborne pathogens, including Campylobacter, Salmonella, and Listeria, can enter VBNC states under stress conditions (e.g., cold storage, disinfectants), yet retain pathogenic potential. Their absence in culture does not equate to absence in the product. To overcome this, MALDI-TOF MS must be integrated into techniques capable of detecting non-culturable cells, such as flow cytometry, viability PCR, or molecular assays targeting active transcription [15,28,139].

4.4. Sample-Matrix Interference

Food samples often contain complex matrices—including fats, polysaccharides, polyphenols, and proteins—that can interfere with ionization efficiency and spectrum quality. These matrix effects are particularly pronounced in direct-from-food applications where enrichment or culture-free methods are desired. Such interference can result in poor spectra, weak signals, or background noise, compromising identification accuracy [49,50,51,52,140].

Although protocols exist for sample clean-up and matrix optimization, they introduce additional steps, potentially reducing the speed and simplicity that make MALDI-TOF MS so attractive. Robust protocols for high-fat, high-sugar, or polyphenol-rich foods remain under development, and are not yet standardized across laboratories [49,78,99].

4.5. Identification of Mixed Cultures

MALDI-TOF MS is optimized for the analysis of pure microbial isolates. When multiple organisms are present in a single spot, the resulting spectrum becomes a composite of overlapping signals, making accurate identification difficult or impossible. This limitation poses challenges in polymicrobial contamination events, spontaneous fermentations, or environmental monitoring samples where co-colonization is common [29,35,103,118].

Although some advanced data deconvolution algorithms and software enhancements aim to identify dominant species in mixed spectra, their accuracy and routine utility are still limited. For mixed populations, pre-isolation steps, such as selective culturing or physical separation (e.g., flow cytometry), are generally required [30,120,141,142].

4.6. Instrument and Operational Limitations

The acquisition and maintenance of MALDI-TOF MS instruments entail significant capital investment, typically exceeding EUR100,000, which may be prohibitive for small or resource-limited laboratories. Furthermore, the need for trained personnel, regular calibration, and adherence to strict quality-control protocols are essential, to ensure reproducibility and reliability of results [36,72,143].

Additionally, although operational costs are low per sample, long-term return on investment depends on high sample throughput and consistent demand. For occasional or small-batch testing scenarios, the economic advantages may be less compelling.

4.7. Regulatory and Standardization Gaps

In the clinical microbiology domain, MALDI-TOF MS has received widespread regulatory acceptance. However, its application in food microbiology is still evolving. Regulatory agencies, including the EFSA and the U.S. FDA, have yet to issue comprehensive guidance or standard protocols for the use of MALDI-TOF MS in food pathogen detection. As a result, validation and acceptance of results in official food control contexts can vary by jurisdiction [11,12,28,144,145].

The standardization of workflows, databases, quality assurance protocols, and interpretation criteria will be critical for wider regulatory adoption and international harmonization.

4.8. Section Summary

In conclusion, while MALDI-TOF MS represents a major advancement in microbial diagnostics, its effective use in food microbiology requires awareness of its current limitations and the implementation of complementary techniques and strategies. Future innovations in hardware, software, and database curation, along with regulatory standardization, will be essential to overcome these challenges and fully realize the potential of MALDI-TOF MS in ensuring global food safety.

5. Future Perspectives

As the global food system becomes increasingly complex, the demand for advanced, rapid, and reliable microbiological diagnostic tools will continue to rise. In this context, MALDI-TOF MS is poised to play an even more significant role in food microbiology, both through technological innovations and strategic integration into broader food-safety frameworks. Future developments are expected to focus on improving resolution, expanding database diversity, enhancing automation, and enabling direct-from-sample identification [18,22,28].

5.1. Expansion and Curation of Databases

One of the most impactful advancements in the future of MALDI-TOF MS will be the continued expansion and refinement of microbial reference databases. A global effort to systematically catalog foodborne pathogens, spoilage organisms, and beneficial microbes—across diverse geographies, processing environments, and food types—will greatly enhance identification accuracy and coverage. Open-access, peer-reviewed databases with strain-level spectral data and associated metadata (e.g., isolation source, geographic origin, genomic background) are expected to emerge as central resources [12,81,105,136].

Additionally, advances in machine learning and bioinformatics will facilitate automated spectral matching and classification beyond current rule-based algorithms, allowing more nuanced discrimination among closely related strains and subspecies.

5.2. Direct-from-Sample Identification

A key limitation of current MALDI-TOF MS workflows is the reliance on culturable isolates. Future research is likely to focus on overcoming this constraint through the development of protocols for direct analysis of food matrices without prior culturing. Innovations in sample preparation—such as selective protein extraction, immunoaffinity capture, and microfluidics—could allow for the selective enrichment and concentration of microbial proteins directly from complex food substrates (e.g., raw meat, leafy greens, dairy products) [18,28,110,121].

This capability would enable real-time, culture-independent microbial surveillance, significantly reducing diagnostic turnaround times and enhancing outbreak responsiveness. The integration of MALDI-TOF MS with front-end enrichment steps such as dielectrophoresis, aptamer-based capture, or nano-filtration may further improve sensitivity for low-abundance organisms [146,147,148,149].

5.3. Strain-Level Discrimination and Typing

As foodborne outbreaks become more complex and globally dispersed, the ability to resolve microorganisms at the strain level will be increasingly vital. Ongoing efforts to improve the discriminatory power of MALDI-TOF MS include the incorporation of high-resolution mass spectrometers (e.g., MALDI-TOF/TOF or MALDI-FTICR), development of biomarker panels for clonal lineages, and hybrid approaches combining spectral and genomic data (proteogenomics). These strategies will support high-resolution typing suitable for outbreak-source tracing, virulence profiling, and antimicrobial resistance (AMR) surveillance. Coupling MALDI-TOF MS with rapid genotypic assays—such as CRISPR-based detection or multiplex qPCR—may offer powerful hybrid platforms for both phenotypic and genetic characterization in one workflow [59,138,150].

5.4. Integration with Food Quality Management Systems

The future of MALDI-TOF MS lies not only in technical advancement, but also in its seamless integration into digitalized food quality management systems. Internet of Things (IoT)-enabled instruments, cloud-based spectral storage, and real-time alerting systems will allow for continuous microbiological monitoring across the food supply chain. Spectral metadata could be used to trace microbial signatures across raw materials, production batches, and geographic locations, supporting blockchain-based traceability and predictive risk analytics [25,32,41,146].

Furthermore, MALDI-TOF MS data can be used to develop microbial risk models and shelf-life prediction algorithms, particularly when linked with environmental, process, and sensory data in artificial intelligence (AI)-driven platforms [30,120].

5.5. Applications Beyond Bacteria: Mycotoxins, Viruses, and Metabolomics

While current MALDI-TOF MS applications in food microbiology are largely limited to bacterial and fungal identification, future iterations may expand into other domains, such as the following:

(a)

Mycotoxin detection: by modifying matrix chemistry and ionization protocols, MALDI-TOF MS could be adapted for the rapid screening of fungal toxins (e.g., aflatoxins, ochratoxins) in grain, nut, and dairy products. However, it is still needed to develop methods for simultaneous detection of multiple mycotoxins [3,151,152].

(b)

Viral diagnostics: although viruses pose unique challenges due to their small size and lack of abundant proteins, preliminary research suggests potential for detecting viral capsid proteins or host-cell biomarkers using MALDI-based methods [72,153,154].

(c)

Microbial metabolomics: high-resolution MALDI-TOF/TOF instruments may facilitate the profiling of volatile and non-volatile microbial metabolites, supporting spoilage prediction, fermentation monitoring, and identification of food fraud [33,39,102].

5.6. Regulatory Acceptance and Standardization

For MALDI-TOF MS to realize its full potential in food microbiology, broader regulatory recognition and harmonized guidelines are essential. The future will likely see the development of international standards for MALDI-TOF MS in food testing, akin to those established for molecular diagnostics. Collaborative validation studies, led by entities such as the International Organization for Standardization (ISO), EFSA, and U.S. FDA, will be crucial in defining performance criteria, reproducibility metrics, and minimum database requirements. Training programs and professional certification pathways for MALDI-TOF MS in food laboratories will also support workforce readiness and method adoption [39,72,155,156].

5.7. Section Summary

To sum up, the future of MALDI-TOF MS in food microbiology is promising and multidimensional. Through continued technological innovation, enhanced data infrastructure, and regulatory alignment, MALDI-TOF MS will evolve from a powerful identification tool into a central platform for microbial risk management, authenticity verification, and real-time traceability across global food systems. Moreover, the future development of MALDI-TOF-MS in microbiological food contamination is also needed. However, implementing this into the industry on a large scale creates the need to train a professional workforce, which will be one of the challenges in the near future.

6. Conclusions

MALDI-TOF MS has rapidly become a transformative technology in the field of food microbiology, offering unparalleled speed, accuracy, and efficiency in the identification of microorganisms associated with foodborne disease, spoilage, and fermentation. Its capacity to generate species-specific proteomic fingerprints with minimal sample preparation and at a low operational cost has led to its widespread adoption in both industrial and regulatory laboratories.

This review has highlighted the multifaceted applications of MALDI-TOF MS in food microbiology, including the detection of foodborne pathogens, identification of spoilage organisms, and its emerging role in food authentication and traceability. These applications have significant implications for food safety monitoring, outbreak response, shelf-life prediction, and the verification of food origin and labeling claims. When integrated into food-quality assurance programs, MALDI-TOF MS strengthens microbial surveillance systems and supports a proactive approach to food safety.

Nonetheless, several limitations remain, including dependence on curated databases, limited strain-level discrimination, and challenges related to complex sample matrices and mixed cultures. Moreover, the current necessity for cultured isolates precludes direct-from-sample applications in many cases, limiting its utility in scenarios requiring immediate or culture-independent diagnostics. Continued technological and methodological innovations—including database expansion, enhanced spectral resolution, improved sample-preparation protocols, and hybrid diagnostic workflows—are expected to address many of these challenges.

Looking forward, the integration of MALDI-TOF MS into digitalized food safety ecosystems, its potential for direct food matrix analysis, and its application in microbial metabolomics and viral detection represent exciting frontiers. Regulatory standardization and the development of globally harmonized protocols will be essential for the broader adoption and legal acceptance of MALDI-TOF MS in official food control programs.

In conclusion, while not without its challenges, MALDI-TOF MS stands at the forefront of modern food microbiology. As the food industry continues to prioritize rapid, reliable, and cost-effective microbial diagnostics, MALDI-TOF MS will remain a cornerstone technology, advancing food safety, quality, and authenticity, in an increasingly complex global food system.