The introduction of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has revolutionized infectious disease diagnostics over the past decade. In this review, we will first explore the history of how the once disparate fields of mass spectrometry (MS) and clinical microbiology inextricably merged. We will then review the rapid growth as well as current applications of MALDI-TOF MS in clinical microbiology. In the accompanying review, we will discuss some of the exciting and emerging applications of MS in pathogen detection, identification, and characterization.

For the last decade, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been the reference method for species identification in clinical microbiology. Hampered by a historical lack of open data, machine learning research towards models specifically adapted to MALDI-TOF MS remains in its infancy. Given the growing complexity of available datasets (such as large-scale antimicrobial resistance prediction), a need for models that (1) are specifically designed for MALDI-TOF MS data, and (2) have high representational capacity, presents itself. Here, we introduce Maldi Transformer, an adaptation of the state-of-the-art transformer architecture to the MALDI-TOF mass spectral domain. We propose the first self-supervised pre-training technique specifically designed for mass spectra. The technique is based on shuffling peaks across spectra, and pre-training the transformer as a peak discriminator. Extensive benchmarks confirm the efficacy of this novel design. The final result is a model exhibiting state-of-the-art (or competitive) performance on downstream prediction tasks. In addition, we show that Maldi Transformer's identification of noisy spectra may be leveraged towards higher predictive performance. All code supporting this study is distributed on PyPI and is packaged under: https://github.com/gdewael/maldi-nn.

Fermented milk products (FMP) have been consumed by humans for millennia and the associated health benefits are no longer to be demonstrated. Although the manufacturing procedure have been industrialized, FMPs are still produced traditionally in many parts of the world with variable manufacturing procedures and unknown sanitary conditions. In this study, we aimed at comparing the physico-chemical properties of industrial and traditional FMPs from France and Mali as well as their microbial diversity. Therefore, 43 FMPs from France (seven yoghurts and four curdled milk products) and Mali (seven yoghurts, five curdled milk products, and 18 traditional fermented milk products) have been collected. These samples were analyzed using the culturomics approach, and GC-MS to quantify the ethanol concentration. Additionally, products pH and salinity were assessed. The results showed that more than half (56 %) of traditional and industrial FMPs contained ethanol (min = 0.05 % and max = 3.70 % Alcohol By Volume (ABV)), with a pH and salinity range (min = 4.43 and max = 5.80 and min = 0.10 and max = 1.80 %, respectively). Among them, 14 % exceed the threshold of 1.2 % ABV authorized by French regulations for non-alcoholic beverages. While only traditional FMPs from the "Nônô kumu" category presented a lower pH value than the other FMPs, all traditional FMPs had a higher salinity than industrial FMPs. Taxonomic analysis at the bacterial species level showed that Lactiplantibacillus plantarum was the dominant species isolated in Malian FMPs whereas Lactobacillus delbrueckii was the most frequent species in French FMPs. Moreover, Candida tropicalis, Candida lusitaniae, Limosilactobacillus fermentum, Leuconostoc pseudomesenteroides, and Liquorilactobacillus mali were significantly correlated with alcohol production. These results were confirmed using an in vitro experimental model. This study provides novel insights into bacterium-fungus interactions and ethanol production. Moreover, these results confirmed the link between specific yeasts and lactic acid bacteria in food and ethanol content, further supporting a recently identified putative role of these microbes in liver diseases.

Treatment of Achromobacter infections remains challenging due to intrinsic and acquired resistance to commonly used antimicrobial agents and no established clinical breakpoints. We attempted accurate species-level identification and compared the presence of genotypic resistance markers to phenotypic susceptibility patterns in retrospectively collected clinical isolates of Achromobacter spp. Our study concludes that Achromobacter xylosoxidans is the most prevalent species. Commercial matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) systems cannot accurately identify all Achromobacter species due to the limited inclusion of spectra in the databases. Phenotypic antimicrobial susceptibility testing (AST) confirms resistance to the majority of antibiotics tested. Newer agents like delafloxacin, plazomicin, and omadacycline showed little or no activity, while minimum inhibitory concentrations were low for eravacycline. In general, the species other than A. xylosoxidans showed lower MIC50 and MIC90, especially to carbapenems and β-lactamase inhibitor combinations like piperacillin-tazobactam, meropenem-vaborbactam, and imipenem-relebactam. Genotypic analysis confirmed that A. xylosoxidans carries a high number of resistance genes, including multidrug efflux pump AxyXY-OprZ, several class D (OXA-type), and the Class A ß-lactamase blaAXC, while Achromobacter mucicolens has the lowest number of resistance genes and no efflux pumps. This study concludes that there is significant genotypic and phenotypic diversity within the different species of Achromobacter, which are important for the identification of the species and for appropriate antimicrobial therapy.IMPORTANCEIdentification and susceptibility testing of Gram-negative non-fermenting bacteria belonging to the genus Achromobacter is difficult due to the lack of robust databases in commercial identification systems such as matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) and clinical breakpoints for antimicrobial agents. Most clinical laboratories interpret minimum inhibitory concentration data using the "non-Enterobacterales" breakpoints included in the Clinical and Laboratory Standards Institute (CLSI) M100. These are breakpoints used for a group of organisms for which data is insufficient to provide species-specific interpretation. Our study provides phenotypic data regarding identification and susceptibility testing and correlates this with the genotypic characterization of 109 clinical isolates belonging to Achromobacter spp. This comprehensive study sheds light on the phenotypic and genotypic character of this bacteria, that is of increasing clinical relevance in hospital-acquired infections.

Spontaneous bacterial peritonitis (SBP) is a severe complication of cirrhosis, occurring in approximately 15% of cirrhotic patients. The most common causative pathogens of SBP are Escherichia coli and Klebsiella pneumoniae. Although brucellosis can cause various complications, it is a rare cause of peritonitis. Herein, we report a case of a 30-year-old male with chronic hepatitis B who presented with fever, night sweats, weight loss, abdominal pain, and distension. Brucella spp. was isolated from blood and peritoneal fluid cultures. The patient fully recovered following six weeks of treatment with oral doxycycline (100 mg twice daily) and rifampicin (900 mg/day). No relapses or complications were observed during follow-up.

In 2023, Helicobacter zhangjianzhongii was proposed as a new species in the Helicobacter genus. We here describe two human cases of H. zhangjianzhongii bacteremia.

Four clinical strains from the Helicobacter genus isolated from blood culture between 2017 and 2023 were studied. They were initially identified as H. canis by MALDI-TOF and 16S rDNA sequencing. The strains were biochemically characterized and tested at different temperatures and atmospheres. Two databases were used to characterize the isolates: the Bruker® MBT compass Version 4.1.1 database and a in-house spectrum-enriched database. After bacterial DNA extraction the genomes were sequenced on NovaSeq 6000 (Illumina) and analyzed using an in-house pipeline.

Case 1 involved a 58-year-old woman who was hospitalized in a thoracic oncology unit because her general condition deteriorated in a setting of small-cell carcinoma. She presented with abdominal pain associated with significant hepatomegaly. Case 2 involved a 78-year-old woman on rituximab who was hospitalized to treat chest pain, anemia, and inflammatory syndrome. Both strains exhibited very similar microbiological and genomic characteristics, thus growth in a microaerobic atmosphere at 37°C and 42°C, oxidase-positivity, and urease- and catalase-negativity. Both were formally identified by whole-genome sequencing as H. zhangjianzhongii (ANI > 99% and DDH > 94%).

This proposed species is associated with bacteremia in humans. It is thus likely to be a novel human pathogen. Dogs may have been the source of infection.

BluePoint MoldID can identify 43 fungal species through nucleic acid array hybridization and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) can identify 247 filamentous fungi through mass spectrometry. First, 43 standard isolates from the Bioresource Collection and Research Center, Taiwan, and the College of American Pathologists and 41 clinical Aspergillus species isolates confirmed by rDNA-ITS sequencing were analyzed using BluePoint MoldID and Bruker MALDI-TOF MS. BluePoint MoldID accurately identified 79% (34/43) of the standard isolates to the species level but failed to recognize nine isolates absent from its database; additionally, 87.8% (36/41) of the clinical isolates were identified at the species level, with 80.5% (33/41) accuracy. MALDI-TOF MS identified 86% (37/43) of the standard isolates, with 81.4% (35/43) accurately identified at the species level and two at the genus level, and identified all the clinical isolates, with 92.6% (38/41) accurately identified at the species level. Next, we analyzed 93 clinical Aspergillus species and compared the results by rDNA-ITS sequencing. BluePoint MoldID identified 87.1% (81/93) of the isolates at the species level, with 80.6% (75/93) accuracy. MALDI-TOF MS identified 97.8% (91/93) of the isolates, including some uncommon species, with 90.3% (84/93) accuracy at the species level. BluePoint MoldID and MALDI-TOF MS had turnaround times of 8 and 2 h, respectively, significantly reducing the time needed to identify filamentous fungi.

The BluePoint MoldID kit is an oligonucleotide array used for the identification of filamentous fungi, and it has not yet been mentioned in recent studies. We used a BluePoint MoldID kit to identify standard and clinical filamentous fungal isolates and compared its performance with that of Bruker MALDI-TOF MS. The former accurately identified 80.2% of the isolates (142/177), and the latter identified 92.6% of the isolates (164/177). The performance of the BluePoint MoldID kit was slightly inferior to that of Bruker MALDI-TOF MS because of the smaller database. However, the BluePoint MoldID kit can cover most clinically common opportunistic fungal infections; thus, it offers an alternative method for laboratories that lack MALDI-TOF MS equipment, as the device is less expensive.

Today, MALDI-ToF MS is an established technique to characterize and identify pathogenic bacteria. The technique is increasingly applied by clinical microbiological laboratories that use commercially available complete solutions, including spectra databases covering clinically relevant bacteria. Such databases are validated for clinical, or research applications, but are often less comprehensive concerning highly pathogenic bacteria (HPB). To improve MALDI-ToF MS diagnostics of HPB we initiated a program to develop protocols for reliable and MALDI-compatible microbial inactivation and to acquire mass spectra thereof many years ago. As a result of this project, databases covering HPB, closely related bacteria, and bacteria of clinical relevance have been made publicly available on platforms such as ZENODO. This publication in detail describes the most recent version of this database. The dataset contains a total of 11,055 spectra from altogether 1,601 microbial strains and 264 species and is primarily intended to improve the diagnosis of HPB. We hope that our MALDI-ToF MS data may also be a valuable resource for developing machine learning-based bacterial identification and classification methods.

Clostridium tetani (C. tetani) bacteraemia is a rare situation, with only four case reports in the literature. Fourteen teeth from the 1590 plague site in Fédons, France, were surface decontaminated before the pulp was cultured under strict anaerobiosis with negative controls. Colonies were identified by mass spectrometry and whole genome sequencing, and C. tetani-specific PCR was performed using DNA extracted from dental pulps, calculus and sediments. C. tetani cultured in two dental pulp specimens from two individuals was firmly identified by MALDI-TOF mass spectrometry, and whole genome sequencing confirmed toxigenic C. tetani. In the remaining twelve individuals, no such C. tetani was recovered and further detection by PCR and palaeoculturomics of dental calculus and sediments surrounding the teeth in these two individuals remained negative. Toxigenic C. tetani which did not result from mere environmental contamination, caused bacteraemia in two individuals from a modern time plague site in France.

This study aims to evaluate the impact of the pathogen's sensitivity to the loaded antibiotics on infection resolution, the number of revisions, and the associated costs in patients undergoing revision total knee arthroplasty (rTKA) due to PJI.

We reviewed the treatment and follow-up processes of 61 patients who underwent rTKA for late-stage PJI following primary total knee arthroplasty in our clinic. The study included 11 patients in the resistant group and 50 in the sensitive group in line with the power analysis results. Patients' demographic characteristics and comorbidities were recorded. All patients received dual antibiotic-loaded cement. Microbiological examinations of patients were analyzed, and the number of revision surgeries each patient underwent was determined. We analyzed all surgeries related to infection treatment, including open irrigation, debridement, polyethylene exchange, implant extractions, antibiotic-loaded cement spacer placements, spacer changes, and debridements, and the implantation of revision prostheses, including tumor prostheses. The total number of surgeries each patient underwent was recorded. We also reviewed hospital system records of total protocol costs during patient admissions.

Of 61 patients undergoing revision total knee arthroplasty (rTKA) for periprosthetic joint infection, 11 had antibiotic-resistant infections and 50 had antibiotic-sensitive infections. The groups had similar demographics. Polymicrobial infections were more frequent in the resistant group (p = 0.017), with all resistant cases showing gentamicin resistance and two showing teicoplanin resistance. The resistant group required more surgeries (average 3.91 ± 2.7 vs. 2.34 ± 1.3, p = 0.043) compared to the sensitive group, with teicoplanin resistance doubling revision surgeries (p = 0.005). Costs were similar between groups, averaging $6536.96. Gram-negative infections led to more revisions (p = 0.013). Polymicrobial infections did not significantly affect the number of surgeries or costs compared to single strain infections.

Our study demonstrates that in rTKA surgeries using dual antibiotic-loaded bone cement, infections caused by antibiotic-resistant microorganisms are more challenging and time-consuming to treat. This underscores the necessity of exploring new methods to enhance local efficacy by loading cement with antibiotics based on specific pathogen culture and sensitivity results, while also providing clinical evidence of the effectiveness of current treatment methods against sensitive microorganisms.

Level 3 (a retrospective cohort study).

In general, periprosthetic joint infection (PJI) is regarded as one of the most common complications of total joint arthroplasty (TJA) and may lead to surgical failure, revision surgery, amputation or death. Nowadays, PJI has become a global health concern, which brings a great burden to public healthcare. In addition, there are still obstacles to achieve high success rates in the prevention, diagnosis and treatment of PJI. However, promising studies are also available with the advancements in biotechnology. This article will present an overview of the current methods used in the prevention, diagnosis and management of PJI while underlining the new technologies utilized.

Infective endocarditis (IE) is a bacterial infection of the heart's inner lining. A low incidence rate combined with a high mortality rate mean that IE can be difficult to treat effectively. There is currently substantial evidence supporting a link between oral health and IE with the oral microbiome impacting various aspects of IE, including pathogenesis, diagnosis, treatment, and mortality rates. The oral microbiome is highly diverse and plays a crucial role in maintaining oral health by providing protective functions. However, when dysbiosis occurs, conditions such as periodontal or peri-implant disease can arise, offering a pathway for bacteraemia to develop. The role of the oral microbiome as a coloniser, facilitator and driver of IE remains to be uncovered by next-generation sequencing techniques. Understanding the dysbiosis and ecology of the oral microbiome of IE patients will allow improvements into the diagnosis, treatment, and prognosis of the disease. Furthermore, an increased awareness amongst those at high-risk of developing IE may encourage improved oral hygiene methods and lower incidence rates. This narrative review examines current findings on the relationship between oral health and IE. It draws from key studies on both topics, with manuscripts selected for their pertinence to the subject. It highlights the link between the oral microbiome and IE by exploring diagnostic techniques and treatments for IE caused by oral commensals.

Significant quantities of salmon are processed daily in the industry's indoor facilities. Occupational exposure contributes to an individual's exposome. The aim of this study is to obtain knowledge about potential exposure to viable airborne species of bacteria and fungi as related to workstations in the salmon processing industry. The study was conducted in nine salmon plants along the Norwegian coast over one or two days with a one-year interval. The MAS100 was used for sampling and MALDI-TOF MS for species identification. The geometric mean concentrations of bacteria and fungi were 200 CFU/m3 and 50 CFU/m3, respectively, with the highest concentrations of bacteria found in slaughtering areas and fungi in trimming of fillets. In total 125 gram-negative and 90 gram-positive bacterial and 32 different fungal species were identified. Some genera were represented by several species e.g. Chryseobacterium (15 species), Flavobacterium (13 species), Microbacterium (12 species), Pseudomonas (37 species), and Psychrobacter (13 species). Risk class 2 (RC2, human pathogens) were found in all types of workstations and plants. Seventeen bacterial species belong to RC2, some were fish pathogens, food spoilage bacteria, or species causing foodborne disease. Among fungi, Aspergillus nidulans was frequently detected across different workstations and plants. In conclusion, bacterial and fungal concentrations were low. Fish and sea-related bacteria were found along the salmon processing line. Bacterial concentrations and species compositions differ between workstations. No particular bacterial or fungal species constituted a large fraction of all airborne species. Based on the presence of human pathogens, using protective gloves is important for the workers. The presence of human and fish pathogens and food spoilage bacteria reveals air as a transmission route for bacteria, potentially affecting workers, consumers, fish, and hygiene of processing equipment. To limit the spread of these bacteria an interdisciplinary cooperation with a One Health perspective may be relevant.

Respiratory disease outbreaks frequently occur in settings where individuals are in close contact, for example, schools and factories. However, the transmission patterns of oropharyngeal microbiota among healthy individuals living in clusters are unclear. Therefore, we aimed to investigate the respiratory tract bacteria distribution and transmission patterns among individuals in close contact.

A total of 36 freshmen from Peking University Medical School participated in the study. We collected pharyngeal swabs on the first day of enrollment, 15, 30, and 60 days after cohabitation. DNA was extracted from the swabs and subjected to high-throughput sequencing to profile the microbial composition. Statistical analyses were performed to assess diversity and significance.

Neisseriaceae, Prevotellaceae, and Streptococcaceae were the most abundant bacterial families detected. Over time, changes were observed in the bacterial communities, with a tendency for increased similarity between dormitory room members. By day 60 of cohabitation, the bacterial communities appeared to be more similar compared to the baseline (prior to cohabitation). The transmission patterns included spreading with colonization, spreading without colonization, and non-spreading. Bacteria belonging to the core genera are most likely to spread and colonize easily.

The risk of healthy cohabitants acquiring respiratory pathogens through close contact may be overestimated in epidemiological studies. Therefore, monitoring the spread of core genera that are easily transmitted and colonized is crucial for effective prevention of respiratory pathogen transmission.

Salmonella spp. are known pathogens in fish, with their presence potentially resulting from the contamination of the aquatic environment or improper handling. Accurate bacterial identification is crucial across various fields, including medicine, microbiology, and the food industry, and thus a range of techniques are available for this purpose. In this study, Salmonella spp. and other hydrogen sulphide-positive bacteria were investigated in the digestive contents of fish destined for consumption from the Atlantic area of Macaronesia. Two identification techniques were compared: the traditional API method and the MALDI-TOF MS technique. For the identification of Salmonella spp. carriers, 59 samples were processed following ISO 6579-1:2017. A total of 47 strains of Gram-negative bacilli were obtained. No Salmonella spp. isolates were detected. The most frequent genus was Enterobacter (76.50%), followed by Shewanella (10.63%). The MALDI-TOF MS technique showed a high concordance with the API technique, with 72.34% concordance at the species level. Both techniques demonstrated a high degree of concordance in the identification of Enterobacter cloacae, with 87.23% genus-level concordance and 12.76% non-concordant identifications. This study highlights the limitations of the API technique and the speed and precision of MALDI-TOF MS. The identified bacteria could pose a health risk to humans.

Mass spectrometry (MS) has long been considered a cornerstone technique in analytical chemistry. However, the use of MS in animal health laboratories (AHLs) has been limited, however, largely because of the expense involved in purchasing and maintaining these systems. Nevertheless, since ~2020, the use of MS techniques has increased significantly in AHLs. As expected, developments in new instrumentation have shown significant benefits in veterinary analytical toxicology as well as bacteriology. Creative researchers continue to push the boundaries of MS analysis, and MS now promises to impact disciplines other than toxicology and bacteriology. I include a short discussion of MS instrumentation, more detailed discussions of the MS techniques introduced since ~2020, and a variety of new techniques that promise to bring the benefits of MS to disciplines such as virology and pathology.

The intensification of livestock farming has led to the widespread use of massive amounts of antibiotics worldwide. Poultry production, including white meat, eggs and the use of their manure as fertiliser, has been identified as one of the most crucial reservoirs for the emergence and spread of resistant bacteria, including E. coli in poultry as an important opportunistic pathogen representing the greatest biological hazard to human and wildlife health. Thus, this study aimed to analyse E. coli in the faecal carriage of healthy poultry flocks and to investigate the phenotypic and genotypic characteristics of antimicrobial resistance, including integrons genes and phylogenetic groups. A total of 431 cloacal swabs from apparently healthy poultry from four regions in Eastern Algeria from December 2021 to October 2022. 360 E. coli were isolated; from broilers (n = 151), broiler breeders (n = 91), laying hens (n = 72), and breeding hens (n = 46). Among this, 281 isolates exhibited multidrug resistance (MDR) phenotype, 17 of the 360 E. coli isolates exhibited ESBL, and one isolate exhibited both ESBL/pAmpC. A representative collection of 183 among 281 MDR E. coli was selected for further analysis by PCR to detect genes encoding resistance to different antibiotics, and sequencing was performed on all positive PCR products of blaCTX-M and blaCMY-2 genes. Phylogenetic groups were determined in 80 E. coli isolates (20 from each of the four kinds of poultry). The blaCTX-M gene was found in 16 (94.11 %) ESBL-producing E. coli isolates within 11 strains co-expressing the blaSHV gene and 8 strains co-expressing the blaTEM gene. Sequence analysis showed frequent diversity in CTX-M-group-1, with blaCTX-M-15 being the most predominant (n = 11), followed by blaCTX-M-1 (n = 5). The blaCMY-2 gene was detected only in one ESBL/pAmpC isolate. Among the 183 tested isolates, various antimicrobial resistance genes were found (number of strains) blaTEM (n = 121), blaSHV (n = 12), tetA (n = 100), tetB (n = 29), sul1(n = 67), sul2 (n = 32), qnrS (n = 45), qnrB (n = 10), qnrA (n = 1), catA1(n = 13), aac-(6')-Ib (n = 3). Furthermore, class 1 and class 2 integrons were found in 113 and 2 E. coli, respectively. The isolates were classified into multiple phylogroups, including A (35 %), B1 (27.5 %), B2 and D each (18.75 %). The detection of integrons and different classes of resistance genes in the faecal carriage of healthy poultry production indicates that commensal E. coli could potentially act as a reservoir for antimicrobial resistance, posing a significant One Health challenge encompassing the interconnected domains of human, animal health and the environment. Here, we present the first investigation to describe the diversity of blaCTX-M producing E. coli isolates with widespread detection of CTX-M-15 and CTX-M-1 in healthy breeders (Broiler and breeding hens) in Eastern Algeria.

Rapid and accurate identification of bacterial species is essential for the effective treatment of infectious diseases and suppression of antibiotic-resistant strains. The unique autofluorescence properties of bacterial cells are exploited for rapid and cost-effective identification that is suitable for point-of-care applications. Fluorescence spectroscopy is combined with machine learning to improve the diagnostic accuracy. Good training data for machine learning can be obtained to achieve the same diagnostic accuracy for bacterial species as when each wavelength is measured in detail over a broad spectral width. Experiments were performed testing 14 bacterial strains. The excitation-emission matrix was analyzed, and Bayesian optimization was used to identify the most effective combinations of wavelengths. The results showed that fluorescence spectra using three specific excitation light regions or excitation spectra using two broad fluorescence detection regions could be used as supervised data to realize diagnostic accuracy comparable to that obtained with more complex instruments.

One of the most feared complications of arthroplasty surgery is septic loosening. Periprosthetic joint infection (PJI) requires an accurate and fast diagnosis, and identification of pathogen microorganisms is essential for successful treatment. While standard bacteriological cultures can identify bacteria in seven to 14 days with sensitivity ranging from 35% to 70% that could further be increased by sonication of the explanted prosthesis, we would like to review a more novel and faster method of PJI detection and bacterial identification. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF/MS) is a technique that identifies bacteria based on peptides and protein ions from the cell surface, comparing the obtained results within a database. While MALDI-TOF/MS is not a novel method, being already successfully used in microbiology, its role in PJI is still being researched. With this paper, we would like to reveal the current state of development in implementing MALDI-TOF/MS as an alternative or auxiliary test to classic bacterial cultures in orthopedic implant infectious pathology to increase the accuracy of detecting and identifying bacteria.

The complex biology of the microbiome was elucidated once the genomics era began. The proteogenomic approach analyzes and integrates genetic makeup (genomics) and microbial communities' expressed proteins (proteomics). Therefore, researchers gained insights into gene expression, protein functions, and metabolic pathways, understanding microbial dynamics and behavior, interactions with host cells, and responses to environmental stimuli. In this context, our work aims to bring together data regarding the application of genomics, proteomics, and bioinformatics in microbiome research and to provide new perspectives for applying microbiota modulation in clinical practice with maximum efficiency. This review also synthesizes data from the literature, shedding light on the potential biomarkers and therapeutic targets for various diseases influenced by the microbiome.

The emission of glyphosate and antibiotic residues from human activities threatens the diversity and functioning of the microbial community. This study examines the impact of a glyphosate-based herbicide (GBH) and common antibiotics on Gram-negative bacteria within the ESKAPEE group (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp. and Escherichia coli). Ten strains, including type and multidrug-resistant strains for each species were analysed and eight antibiotics (cefotaxime, meropenem, aztreonam, ciprofloxacin, gentamicin, tigecycline, sulfamethoxazole-trimethoprim, and colistin) were combined with the GBH. While most combinations yielded additive or indifferent effects in 70 associations, antagonistic effects were observed with ciprofloxacin and gentamicin in five strains. GBH notably decreased the minimum inhibitory concentration of colistin in eight strains and displayed synergistic activity with meropenem against metallo-β-lactamase (MBL)-producing strains. Investigation into the effect of GBH properties on outer membrane permeability involved exposing strains to a combination of this GBH and vancomycin. Results indicated that GBH rendered strains sensitive to vancomycin, which is typically ineffective against Gram-negative bacteria. Furthermore, we examined the impact of GBH in combination with three carbapenem agents on 14 strains exhibiting varying carbapenem-resistance mechanisms to assess its effect on carbapenemase activity. The GBH efficiently inhibited MBL activity, demonstrating similar effects to EDTA (ethylenediaminetetraacetic acid). Chelating effect of GBH may have multifaceted impacts on bacterial cells, potentially by increasing outer membrane permeability and inactivating metalloenzyme activity.

Infections caused by viruses and bacteria pose a significant threat to global public health, emphasizing the critical importance of timely and precise detection methods. Inductively coupled plasma mass spectrometry (ICP-MS), a contemporary approach for pathogen detection, offers distinct advantages such as high sensitivity, a wide linear range, and multi-index capabilities. This review elucidates the underexplored application of ICP-MS in conjunction with functional nanoparticles (NPs) for the identification of viruses and bacteria. The review commences with an elucidation of the underlying principles, procedures, target pathogens, and NP requirements for this innovative approach. Subsequently, a thorough analysis of the advantages and limitations associated with these techniques is provided. Furthermore, the review delves into a comprehensive examination of the challenges encountered when utilizing NPs and ICP-MS for pathogen detection, culminating in a forward-looking assessment of the potential pathways for advancement in this domain. Thus, this review contributes novel perspectives to the field of pathogen detection in biomedicine by showcasing the promising synergy of ICP-MS and NPs.

Our work aims at establishing a proof-of-concept for a method that allows the early prediction of the bactericidal and bacteriostatic effects of antibiotics on bacteria using scanning electron microscopy (SEM) as compared to traditional culture-based methods.

We tested these effects using Imipenem (bactericidal) and Doxycycline (bacteriostatic) with several strains of sensitive and resistant Escherichia coli. We developed a SEM-based predictive score based on three main criteria: Bacterial Density, Morphology/Ultrastructure, and Viability. We determined the results for each of these criteria using SEM micrographs taken with the TM4000Plus II-Tabletop-SEM (Hitachi, Japan) following an optimized, rapid, and automated acquisition and analysis protocol. We compared our method with the traditional culture colony counting gold standard method and classic definitions of the two effects.

Our method revealed total agreement with the CFU method and classic definition by visualizing the effect of the antibiotic at 60 minutes and 120 minutes using SEM.

This early prediction allows a rapid and early identification of the bactericidal and bacteriostatic effects as compared to culture that would take a minimum of 18 hours. This has several future applications in the development of SEM-automated assays coupled to machine learning models that identify the antibiotic effect and facilitate determination of bacterial susceptibility.

Legionella bacteria can proliferate in poorly maintained water systems, posing risks to users. All Legionella species are potentially pathogenic, but Legionella pneumophila (L. pneumophila) is usually the primary focus of testing. However, Legionella anisa (L. anisa) also colonizes water distribution systems, is frequently found with L. pneumophila, and could be a good indicator for increased risk of nosocomial infection. Anonymized data from three commercial Legionella testing laboratories afforded an analysis of 565,750 water samples. The data covered July 2019 to August 2021, including the COVID-19 pandemic. The results confirmed that L. anisa commonly colonizes water distribution systems, being the most frequently identified non-L. pneumophila species. The proportions of L. anisa and L. pneumophila generally remained similar, but increases in L. pneumophila during COVID-19 lockdown suggest static water supplies might favor its growth. Disinfection of hospital water systems was effective, but re-colonization did occur, appearing to favor L. pneumophila; however, L. anisa colony numbers also increased as a proportion of the total. While L. pneumophila remains the main species of concern as a risk to human health, L. anisa's role should not be underestimated, either as a potential infection risk or as an indicator of the need to intervene to control Legionella's colonization of water supplies.

We aimed to identify specific anaerobic bacteria causing bacteraemia and a subsequent diagnosis of colorectal cancer.

A nationwide population-based cohort study, which included all episodes of defined specific anaerobic bacteraemia from 2010 (5,534,738 inhabitants) through 2020 (5,822,763 inhabitants) and all cases of colorectal cancer diagnosed from 2010 through 2021 in Denmark. We calculated the incidence and risk of colorectal cancer after bacteraemia with specific anaerobic bacteria using Escherichia coli bacteraemia as reference.

Nationwide data on colorectal cancer and specific anaerobic bacteraemia (100% complete, representing 11,124 episodes). The frequencies of colorectal cancer within one year following anaerobic bacteraemia were higher for species, which almost exclusively reside in the colon, such as Phocaeicola vulgatus/dorei (5.5%), Clostridium septicum (24.2%), and Ruminococcus gnavus (4.6%) compared to 0.6% in 50,650 E. coli bacteraemia episodes. Bacteroides spp. had a subhazard ratio for colorectal cancer of 3.9 (95% confidence interval [CI], 3.0 to 5.1) and for Clostridium spp. it was 8.9 (95% CI, 6.7 to 11.8, with C. septicum 50.0 [95% CI, 36.0 to 69.5]) compared to E. coli (reference).

This nationwide study identified specific colorectal cancer-associated anaerobic bacteria, which almost exclusively reside in the colon. Bacteraemia with these bacteria could be an indicator of colorectal cancer.

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is extensively employed for the identification of filamentous fungi on MALDI Biotyper (Bruker Daltonics) and Vitek MS (biomerieux), but the performance of fungi identification on new EXS2600 (Zybio) is still unknow. Our study aims to evaluate the new EXS2600 system's (Zybio) ability to rapidly identify filamentous fungi and determine its effect on turnaround time (TAT) in our laboratory.

We tested 117 filamentous fungi using two pretreatment methods: the formic acid sandwich (FA-sandwich) and a commercial mold extraction kit (MEK, Zybio). All isolates were confirmed via sequence analysis. Laboratory data were extracted from our laboratory information system over two 9-month periods: pre-EXS (April to December 2022) and post-EXS (April to December 2023), respectively.

The total correct identification (at the species, genus, or complex/group level) rate of fungi was high, FA-sandwich (95.73%, 112/117), followed by MEK (94.02%, 110/117). Excluding 6 isolates not in the database, species-level identification accuracy was 92.79% (103/111) for FA-sandwich and 91.89% (102/111) for MEK; genus-level accuracy was 97.29% (108/111) and 96.39% (107/111), respectively. Both methods attained a 100% correct identification rate for Aspergillus, Lichtheimia, Rhizopus Mucor and Talaromyces species, and were able to differentiate between Fusarium verticillioides and Fusarium proliferatum within the Fusarium fujikuroi species complex. Notably, high confidence was observed in the species-level identification of uncommon fungi such as Trichothecium roseum and Geotrichum candidum. The TAT for all positive cultures decreased from pre EXS2600 to post (108.379 VS 102.438, P < 0.05), and the TAT for tissue decreased most (451.538 VS 222.304, P < 0.001).

The FA-sandwich method is more efficient and accurate for identifying filamentous fungi with EXS2600 than the MEK. Our study firstly evaluated the performance of fungi identification on EXS2600 and showed it is suitable for clinical microbiology laboratories use.

Protein analysis using matrix-assisted laser desorption/ionisation time-of-flight mass-spectrometry (MALDI-TOF MS) represents a promising tool for entomological surveillance. In this study we tested the discriminative power of this tool for measuring species and blood meal source of main Afrotropical malaria vectors on the Kenyan coast.

Mosquito collections were conducted along the coastal region of Kenya. MALDI-TOF MS spectra were obtained from each individual mosquito's cephalothorax as well as the abdomens of blood-engorged mosquitoes. The same mosquitoes were also processed using gold standard tests: polymerase chain reaction (PCR) for species identification and enzyme linked immunosorbent assay (ELISA) for blood meal source identification.

Of the 2,332 mosquitoes subjected to MALDI-TOF MS, 85% (1,971/2,332) were considered for database creation and validation. There was an overall accuracy of 97.5% in the identification of members of the An. gambiae ( An. gambiae, 100%; An. arabiensis, 91.9%; An. merus, 97.5%; and An. quadriannulatus, 90.2%) and An. funestus ( An. funestus, 94.2%; An. rivulorum, 99.4%; and An. leesoni, 94.1%) complexes. Furthermore, MALDI-TOF MS also provided accurate (94.5% accuracy) identification of blood host sources across all mosquito species.

This study provides further evidence of the discriminative power of MALDI-TOF MS to identify sibling species and blood meal source of Afrotropical malaria vectors, further supporting its utility in entomological surveillance. The low cost per sample (<0.2USD) and high throughput nature of the method represents a cost-effective alternative to molecular methods and could enable programs to increase the number of samples analysed and therefore improve the data generated from surveillance activities.

The gut microbiome is closely associated with human health and the development of diseases. Isolating, characterizing, and identifying gut microbes are crucial for research on the gut microbiome and essential for advancing our understanding and utilization of it. Although culture-independent approaches have been developed, a pure culture is required for in-depth analysis of disease mechanisms and the development of biotherapy strategies. Currently, microbiome research faces the challenge of expanding the existing database of culturable gut microbiota and rapidly isolating target microorganisms. This review examines the advancements in gut microbe isolation and cultivation techniques, such as culturomics, droplet microfluidics, phenotypic and genomics selection, and membrane diffusion. Furthermore, we evaluate the progress made in technology for identifying gut microbes considering both non-targeted and targeted strategies. The focus of future research in gut microbial culturomics is expected to be on high-throughput, automation, and integration. Advancements in this field may facilitate strain-level investigation into the mechanisms underlying diseases related to gut microbiota.

Colistin (Polymyxin E) has reemerged in the treatment of MDR Gram-negative infections. Traditional Colistin AST methods have long turnaround times and are cumbersome for routine use. We present a SEM-AST technique enabling rapid detection of Colistin resistance through direct observation of morphological and quantitative changes in bacteria exposed to Colistin.

Forty-four Gram-negative reference organisms were chosen based on their Colistin susceptibility profiles. Bacterial suspensions of ∼107 CFU/mL were exposed to Colistin at EUCAST-ECOFF, with controls not exposed, incubated at 37°C, and then sampled at 0, 15, 30, 60, and 120 minutes. Phosphotungstic Acid (PTA) staining was applied, followed by SEM imaging using Hitachi TM4000PlusII-Tabletop-SEM at ×2000, ×5000 and ×7000 magnifications. Bacterial viability analysis was performed for all conditions by quantifying viable and dead organisms based on PTA-staining and morphologic changes.

We identified a significant drop in the percentage of viable organisms starting 30 minutes after exposure in susceptible strains, as compared to nonsignificant changes in resistant strains across all tested organisms. The killing effect of Colistin was best observed after 120 minutes of incubation with the antibiotic, with significant changes in morphologic features, including bacterial inflation, fusion, and lysis, observed as early as 30 minutes. Our observation matched the results of the gold standard-based broth microdilution method.

We provide an extended application of the proof of concept for the utilization of the SEM-AST assay for Colistin for a number of clinically relevant bacterial species, providing a rapid and reliable susceptibility profile for a critical antibiotic.

Periprosthetic joint infection (PJI) is a rare but most vital complication after joint arthroplasty and requires a revision surgery. Synovial fluid analysis is essential in diagnosis of the PJI, and conventional and molecular microbiologic investigations may help in determining the cause of the infection. With this unusual case, we aimed to present the second instance in the literature of PJI of the knee caused by Streptococcus dysgalactiae subspecies dysgalactiae (SDSD). S. dysgalactiae PJI in the literature are commonly Streptococcus dysgalactiae subspecies equisimilis (SDSE), and SDSD mostly infects animals. A farmer with comorbid illnesses who works with cattle and sheep experienced periprosthetic knee joint infection caused by SDSD. Surgical excisional debridement with open washing, decompression, and liner exchange were performed. The identification of the bacteria was done with VITEK MS as SDSD. After 1-year follow-up, the patient has fully recovered without recurrence.

Antimicrobial resistance (AMR) is a global health problem that requires early and effective treatments to prevent the indiscriminate use of antimicrobial drugs and the outcome of infections. Mass Spectrometry (MS), and more particularly MALDI-TOF, have been widely adopted by routine clinical microbiology laboratories to identify bacterial species and detect AMR. The analysis of AMR with deep learning is still recent, and most models depend on filters and preprocessing techniques manually applied on spectra.

This study propose a deep neural network, MSDeepAMR, to learn from raw mass spectra to predict AMR. MSDeepAMR model was implemented for Escherichia coli, Klebsiella pneumoniae, and Staphylococcus aureus under different antibiotic resistance profiles. Additionally, a transfer learning test was performed to study the benefits of adapting the previously trained models to external data.

MSDeepAMR models showed a good classification performance to detect antibiotic resistance. The AUROC of the model was above 0.83 in most cases studied, improving the results of previous investigations by over 10%. The adapted models improved the AUROC by up to 20% when compared to a model trained only with external data.

This study demonstrate the potential of the MSDeepAMR model to predict antibiotic resistance and their use on external MS data. This allow the extrapolation of the MSDeepAMR model to de used in different laboratories that need to study AMR and do not have the capacity for an extensive sample collection.

Since their radiation in the Middle Triassic period ∼240 million years ago, stony corals have survived past climate fluctuations and five mass extinctions. Their long-term survival underscores the inherent resilience of corals, particularly when considering the nutrient-poor marine environments in which they have thrived. However, coral bleaching has emerged as a global threat to coral survival, requiring rapid advancements in coral research to understand holobiont stress responses and allow for interventions before extensive bleaching occurs. This review encompasses the potential, as well as the limits, of multiomics data applications when applied to the coral holobiont. Synopses for how different omics tools have been applied to date and their current restrictions are discussed, in addition to ways these restrictions may be overcome, such as recruiting new technology to studies, utilizing novel bioinformatics approaches, and generally integrating omics data. Lastly, this review presents considerations for the design of holobiont multiomics studies to support lab-to-field advancements of coral stress marker monitoring systems. Although much of the bleaching mechanism has eluded investigation to date, multiomic studies have already produced key findings regarding the holobiont's stress response, and have the potential to advance the field further.

Ventilator-associated pneumonia (VAP) is a prevalent disease caused by microbial infection, resulting in significant morbidity and mortality within the intensive care unit (ICU). The rapid and accurate identification of pathogenic bacteria causing VAP can assist clinicians in formulating timely treatment plans. In this study, we attempted to differentiate bacterial species in VAP by utilizing the volatile organic compounds (VOCs) released by pathogens. We cultured 6 common bacteria in VAP in vitro, including Acinetobacter baumannii, Enterobacter cloacae, Escherichia coli, Pseudomonas aeruginosa, Stenotrophomonas maltophilia, and Staphylococcus aureus, which covered most cases of VAP infection in clinic. After the VOCs released by bacteria were collected in sampling bags, they were quantitatively detected by a proton transfer reaction-mass spectrometry (PTR-MS), and the characteristic ions were qualitatively analyzed through a fast gas chromatography-proton transfer reaction-mass spectrometry (FGC-PTR-MS). After conducting principal component analysis (PCA) and analysis of similarities (ANOSIM), we discovered that the VOCs released by 6 bacteria exhibited differentiation following 3 h of quantitative cultivation in vitro. Additionally, we further investigated the variations in the types and concentrations of bacterial VOCs. The results showed that by utilizing the differences in types of VOCs, 6 bacteria could be classified into 5 sets, except for A. baumannii and E. cloacae which were indistinguishable. Furthermore, we observed significant variations in the concentration ratio of acetaldehyde and methyl mercaptan released by A. baumannii and E. cloacae. In conclusion, the VOCs released by bacteria could effectively differentiate the 6 pathogens commonly associated with VAP, which was expected to assist doctors in formulating treatment plans in time and improve the survival rate of patients.

Freshwater snails of the genera Bulinus spp., Biomphalaria spp., and Oncomelania spp. are the main intermediate hosts of human and animal schistosomiasis. Identification of these snails has long been based on morphological and/or genomic criteria, which have their limitations. These limitations include a lack of precision for the morphological tool and cost and time for the DNA-based approach. Recently, Matrix-Assisted Laser Desorption/Ionization Time-Of-Flight (MALDI-TOF) mass spectrometry, a new tool used which is routinely in clinical microbiology, has emerged in the field of malacology for the identification of freshwater snails. This study aimed to evaluate the ability of MALDI-TOF MS to identify Biomphalaria pfeifferi and Bulinus forskalii snail populations according to their geographical origin.

This study was conducted on 101 Bi. pfeifferi and 81 Bu. forskalii snails collected in three distinct geographical areas of Senegal (the North-East, South-East and central part of the country), and supplemented with wild and laboratory strains. Specimens which had previously been morphologically described were identified by MALDI-TOF MS [identification log score values (LSV) ≥ 1.7], after an initial blind test using the pre-existing database. After DNA-based identification, new reference spectra of Bi. pfeifferi (n = 10) and Bu. forskalii (n = 5) from the geographical areas were added to the MALDI-TOF spectral database. The final blind test against this updated database was performed to assess identification at the geographic source level.

MALDI-TOF MS correctly identified 92.1% of 101 Bi. pfeifferi snails and 98.8% of 81 Bu. forskalii snails. At the final blind test, 88% of 166 specimens were correctly identified according to both their species and sampling site, with LSVs ranging from 1.74 to 2.70. The geographical source was adequately identified in 90.1% of 91 Bi. pfeifferi and 85.3% of 75 Bu. forskalii samples.

Our findings demonstrate that MALDI-TOF MS can identify and differentiate snail populations according to geographical origin. It outperforms the current DNA-based approaches in discriminating laboratory from wild strains. This inexpensive high-throughput approach is likely to further revolutionise epidemiological studies in areas which are endemic for schistosomiasis.

There are very few studies using Benzalkonium Chloride (BAC) as an active disinfection agent for immersion techniques and there are no studies investigating the efficacy of repeated use of a disinfectant solution.

This study evaluated an impression disinfectant by testing bacterial contamination of disinfectant batches used in a clinical setting after repeated use.

Liquid samples were collected from impression disinfectant solutions used to disinfect dental impressions taken at a university dental clinic. The experimental samples (500 ml from 1 L of solution) were collected from teaching and professional clinics and the in-house commercial processing laboratory and stored at room temperature each day of clinic operation over five weeks. To determine to what extent the disinfectant efficacy of the active product decreased over time, the following tests were carried out: a. Inoculation b. Gram staining technique c. Matrix Assisted Laser Desorption/Ionization Mass spectrometry (MALDI- MS). Microbial growth was monitored and photographed. A culture revival was made from colonies grown on sheep blood agar, to isolate pure colonies incubated for 24 h at 37 °C. Each morphologically distinct type of colony was gram stained and MALDI spectrometry analysis was performed using the VITEK MS (BioMerieux Inc.).

Evidence of growth of bacteria was detected in teaching clinics' samples, and no growth from the professional clinic or the commercial laboratory.

The study demonstrated that impression disinfectanat solution tested is effective against common oral bacteria, despite some rare species such as Bacillus circulans, Bacillus horneckiae, Bacillus altitudinis/pumilus and Bacillus cereus showing evidence of survival in solutions used for disinfection of impressions. However, in a high use teaching clinic environment its efficacy deteriorated. Though a second level disinfection protocol in the commercial laboratory-maintained impression disinfection.

Bacterial vaginosis (BV) is a common dysbiosis of unclear etiology but with potential consequences representing a public health problem. The diagnostic strategies vary widely. The Amsel criteria and Nugent score have obvious limitations, while molecular biology techniques are expensive and not yet widespread. We set out to evaluate different diagnostic strategies from vaginal samples using (1) a combination of abnormal vaginal discharge and vaginal pH > 4.5; (2) the Amsel-like criteria (replacing the "whiff test" with "malodorous discharge"); (3) the Nugent score; (4) the molecular quantification of Fannyhessea vaginae and Gardnerella vaginalis (qPCR); (5) and MALDI-TOF mass spectrometry (we also refer to it as "VAGI-TOF"). Overall, 54/129 patients (42%) were diagnosed with BV using the combination of vaginal discharge and pH, 46/118 (39%) using the Amsel-like criteria, 31/130 (24%) using qPCR, 32/130 (25%) using "VAGI-TOF", and 23/84 (27%) using the Nugent score (not including the 26 (31%) with intermediate flora). Of the 84 women for whom the five diagnostic strategies were performed, the diagnosis of BV was considered for 38% using the combination of vaginal discharge and pH, 34.5% using the Amsel-like criteria, 27% using the Nugent score, 25% using qPCR, and 25% using "VAGI-TOF". When qPCR was considered as the reference, the sensitivity rate for BV was 76.2% for the combination of vaginal discharge and pH, 90.5% for the Amsel-like criteria, 95.2% for the Nugent score, and 90.5% for "VAGI-TOF", while the specificity rates were 74.6%, 84.1%, 95.3%, and 95.3%, respectively. When the Nugent score was considered as the reference, the sensitivity for BV was 69.6% for the combination of vaginal discharge and pH, 82.6% for the Amsel-like criteria, 87% for qPCR, and 78.7% for "VAGI-TOF", while the specificity rates were 80%, 94.3%, 100%, and 97.1%, respectively. Overall, the use of qPCR and "VAGI-TOF" provided a consistent diagnosis of BV, followed by the Nugent score. If qPCR seems tedious and for some costly, "VAGI-TOF" could be an inexpensive, practical, and less time-consuming alternative.

The Colibrí™ is a new instrument that automates picking and placement of colonies on target plates for MALDI identification. This study compared the performance of the Colibrí™ to standard manual spotting using the VITEK® MS for bacterial identification. Colonies were selected from cultures of urine, wound, respiratory, and positive blood cultures. The Colibrí™ sampled the colonies, transferred them to a MALDI target slide, and overlayed each spot with matrix. Manual spotting was then performed using the same or similar colonies. A total of 444 bacteria were compared. Identification was achieved with both methods for 432 organisms with only 2 discrepant results, overall agreement of 99.54%. Twelve organisms (2.70%) gave no identification using Colibrí™. The Colibrí™ provides automation to a manual process with a high accuracy. Use of the Colibrí™ instrumentation provides an opportunity to reallocate technologist time to more complicated tasks and provides complete traceability from plating to organism identification.

When rare bacterial species are identified in blood cultures, determining the clinical significance is sometimes difficult. This study aimed to analyze the clinical significance of rare bacterial species detected in blood cultures using matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOFMS) by comparing their contamination rates with those of common species. We retrospectively analyzed medical records of adult patients with positive blood cultures at Kyoto City Hospital from 2014 to 2022. Rare species were defined by low detection rates and few PubMed reports. Of 4880 microorganisms identified from 3441 individuals, 1150 (23.6%) were classified as contamination. Meanwhile, 24 rare microorganisms were identified, of which 14 (58.3%) were classified as contamination, which was significantly higher than common species (odds ratio 4.56, 95% confidence Interval 1.88-11.50, P < 0.001). These findings may help in determining the clinical significance of rare bacterial species in blood cultures with few reported cases.

The aim of this study was to compare the performance of two MALDI-TOF MS systems in the identification of clinically relevant strict anaerobic bacteria. The 16S rRNA gene sequencing was the gold standard method when discrepancies or inconsistencies were observed between platforms. A total of 333 isolates were recovered from clinical samples of different centers in Buenos Aires City between 2016 and 2021. The isolates were identified in duplicate using two MALDI-TOF MS systems, BD Bruker Biotyper (Bruker Daltonics, Bremen, Germany) and Vitek MS (bioMèrieux, Marcy-l'Etoile, France). Using the Vitek MS system, the identification of anaerobic isolates yielded the following percentages: 65.5% (n: 218) at the species or species-complex level, 71.2% (n: 237) at the genus level, 29.4% (n: 98) with no identification and 5.1% (n: 17) with misidentification. Using the Bruker Biotyper system, the identification rates were as follows: 85.3% (n: 284) at the species or species-complex level, 89.7% (n: 299) at the genus level, 14.1% (n: 47) with no identification and 0.6% (n: 2) with misidentification. Differences in the performance of both methods were statistically significant (p-values <0.0001). In conclusion, MALDI-TOF MS systems speed up microbial identification and are particularly effective for slow-growing microorganisms, such as anaerobic bacteria, which are difficult to identify by traditional methods. In this study, the Bruker system showed greater accuracy than the Vitek system. In order to be truly effective, it is essential to update the databases of both systems by increasing the number of each main spectrum profile within the platforms.

Differentiating Streptococcus pneumoniae among nonpneumococcal viridans group streptococci (VGS) is challenging in conventional laboratories. Therefore, we aimed to evaluate the performance of the latest Bruker Biotyper matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) system in identifying VGS by comparing the results to those of the specific gene sequencing approach. Clinical isolates were initially identified using the BD Phoenix system to identify Streptococcus species. The optochin test was used to distinguish nonpneumococcal VGS from S. pneumoniae. The species of individual reference strains and clinical isolates were determined by comparing the sequences of the 16S rDNA, gyrB, sodA, groESL, or coaE genes with those in the GenBank sequence databases. We evaluated the performance of the Bruker Biotyper MALDI-TOF MS in VGS identification using two different machines with three databases. We collected a total of 103 nonpneumococcal VGS and 29 S. pneumoniae blood isolates at a medical center in northern Taiwan. Among these isolates, only seven could not be identified at the species level by the specific gene sequencing approach. We found that none of the nonpneumococcal VGS isolates were misidentified as pneumococci by the latest Biotyper system, and vice versa. However, certain strains, especially those in the mitis and bovis groups, could still not be correctly identified. The latest Bruker Biotyper 4.1 (DB_10833) showed significant improvement in identifying VGS strains. However, a specific gene sequencing test is still needed to precisely differentiate the species of strains in the mitis and bovis groups.