Rapid detection ofcfiAmetallo-β-lactamase-producingBacteroides fragilisby the combination of MALDI-TOF MS and CarbaNP

Rapid discrimination of Bifidobacterium longum subspecies based on MALDI-TOF MS and machine learning

Although MALDI-TOF mass spectrometry (MS) is widely known as a rapid and cost-effective reference method for identifying microorganisms, its commercial databases face limitations in accurately distinguishing specific subspecies of Bifidobacterium. This study aimed to explore the potential of MALDI-TOF MS protein profiles, coupled with prediction methods, to differentiate between Bifidobacterium longum subsp. infantis (B. infantis) and Bifidobacterium longum subsp. longum (B. longum). The investigation involved the analysis of mass spectra of 59 B. longum strains and 41 B. infantis strains, leading to the identification of five distinct biomarker peaks, specifically at m/z 2,929, 4,408, 5,381, 5,394, and 8,817, using Recurrent Feature Elimination (RFE). To facilate classification between B. longum and B. infantis based on the mass spectra, machine learning models were developed, employing algorithms such as logistic regression (LR), random forest (RF), and support vector machine (SVM). The evaluation of the mass spectrometry data showed that the RF model exhibited the highest performace, boasting an impressive AUC of 0.984. This model outperformed other algorithms in terms of accuracy and sensitivity. Furthermore, when employing a voting mechanism on multi-mass spectrometry data for strain identificaton, the RF model achieved the highest accuracy of 96.67%. The outcomes of this research hold the significant potential for commercial applications, enabling the rapid and precise discrimination of B. longum and B. infantis using MALDI-TOF MS in conjunction with machine learning. Additionally, the approach proposed in this study carries substantial implications across various industries, such as probiotics and pharmaceuticals, where the precise differentiation of specific subspecies is essential for product development and quality control.

Upregulation of the cfiA carbapenemase gene in a Bacteroides fragilis strain by the novel integrative and conjugative element Tn7563

We describe Tn7563, a 31,844-bp integrative and conjugative element (ICE) carrying promoters upregulating the cfiA carbapenemase gene in Bacteroides fragilis strain Tbg-22. Excision and circularization of Tn7563 was demonstrated by PCR. Previously, only insertion sequences (IS) have been shown to carry mobile promoters for cfiA.

Antimicrobial susceptibility of Bacteroides fragilis group organisms in Hong Kong, 2020-2021

OBJECTIVES

This retrospective study analyzed the susceptibility levels of Bacteroides fragilis group (BFG) in a hospital-based laboratory where disk diffusion test (DDT) was routinely performed. Isolates non-susceptible to imipenem and metronidazole by DDT were further investigated using a gradient method.

METHODS

The DDT and MIC susceptibility data of clindamycin, metronidazole, moxifloxacin and imipenem obtained on Brucella blood agar for 1264 non-duplicated isolates during 2020-2021 were analyzed. Species identification was obtained by matrix-assisted laser desorption ionization time-of-flight mass spectrometry and 16S rRNA sequencing. Interpretative agreement of DDT results using the 2015 EUCAST tentative and 2021 CA-SFM breakpoints was compared against MIC as the reference.

RESULTS

The dataset included 604 B. fragilis (483 division I, 121 division II isolates), 415 non-fragilis Bacteroides, 177 Phocaeicola and 68 Parabacteroides. Susceptibility rates for clindamycin (22.1-62.1%) and moxifloxacin (59.9-80.9%) were low and many had no inhibition zones. At the EUCAST and CA-SFM breakpoints, 83.0 and 89.4% were imipenem-susceptible, and 89.6% and 97.4 were metronidazole-susceptible. MIC testing confirmed 11.4% and 2.8% isolates as imipenem-non-susceptible and metronidazole-resistant, respectively. Significant numbers of false-susceptibility and/or false-resistance results were observed at the CA-SFM breakpoint but not the EUCAST breakpoint. Higher rates of imipenem and/or metronidazole resistance were detected in B. fragilis division II, B. caccae, B. ovatus, B. salyersiae, B. stercoris and Parabacteroides. Co-resistance to imipenem and metronidazole was detected in 3 B. fragilis division II isolates.

CONCLUSIONS

The data demonstrated emerging BFG resistance to several important anti-anaerobic antibiotics and highlights the importance of anaerobic susceptibility testing in clinical laboratories to guide therapy.

Differentiation between Weissella cibaria and Weissella confusa Using Machine-Learning-Combined MALDI-TOF MS

Although Weissella cibaria and W. confusa are essential food-fermenting bacteria, they are also opportunistic pathogens. Despite these species being commercially crucial, their taxonomy is still based on inaccurate identification methods. In this study, we present a novel approach for identifying two important Weissella species, W. cibaria and W. confusa, by combining matrix-assisted laser desorption/ionization and time-of-flight mass spectrometer (MALDI-TOF MS) data using machine-learning techniques. After on- and off-plate protein extraction, we observed that the BioTyper database misidentified or could not differentiate Weissella species. Although Weissella species exhibited very similar protein profiles, these species can be differentiated on the basis of the results of a statistical analysis. To classify W. cibaria, W. confusa, and non-target Weissella species, machine learning was used for 167 spectra, which led to the listing of potential species-specific mass-to-charge (m/z) loci. Machine-learning techniques including artificial neural networks, principal component analysis combined with the K-nearest neighbor, support vector machine (SVM), and random forest were used. The model that applied the Radial Basis Function kernel algorithm in SVM achieved classification accuracy of 1.0 for training and test sets. The combination of MALDI-TOF MS and machine learning can efficiently classify closely-related species, enabling accurate microbial identification.

Phenotypic and genotypic identification of carbapenem resistance in Bacteroides fragilis clinical strains

Bacteroides fragilis is an important etiological agent of serious infections in humans. Rapid methods, readily adaptable to use in medical laboratories, are needed to detect antibiotic resistance and decrease the likelihood of therapy failure. The aim of this study was to determine the prevalence of B. fragilis cfiA-positive isolates. The second purpose was to investigate the carbapenemase activity in B. fragilis strains by Carba NP test. In the study, 5.2% of B. fragilis isolates are phenotypically resistant to meropenem. The cfiA gene was identified in 6.1% of B. fragilis isolates. The MICs of meropenem were significantly higher in cfiA-positive strains. The presence of the cfiA gene along with the IS1186 was detected in one B. fragilis strain which was resistant to meropenem (MIC 1.5 mg/L). The Carba NP test results were positive for all the cfiA-positive strains, including those susceptible to carbapenems based on their MIC values. A review of the literature revealed that the rate of B. fragilis with the cfiA gene varies from 7.6 to 38.9% worldwide. Presented results are in line with the other European studies. Phenotypic testing with the Carba NP test, it seems to be a viable alternative for the cfiA gene detection in B. fragilis isolates. The positive result obtained is of greater clinical importance than the detection of the gene cfiA.

High prevalence of cfiA positive Bacteroides fragilis isolates collected at a teaching hospital in Hohhot, China

OBJECTIVES

Carbapenem-resistant Bacteroides fragilis has emerged globally and cfiA is the key underlying factor. However, the prevalence of cfiA-positive carbapenem-resistant B. fragilis varies among countries. Therefore, we investigated the prevalence of cfiA-positive B. fragilis clinical isolates in a tertiary hospital in China.

METHODS

Carbapenem-resistant cfiA-positive B. fragilis isolates were identified using polymerase chain reaction. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was used to identify the characteristic mass spectra of cfiA-positive B. fragilis.

RESULTS

The prevalence of cfiA among 153 B. fragilis isolates was 22.2% (34/153), when 20.6% (7/34) cfiA-positive B. fragilis strains were isolated from pediatric patients. Twenty-one carbapenem-resistant B. fragilis isolates were identified and were all positive with cfiA gene. Two characteristic peaks (4825 and 9642 Da) were identified using MALDI-TOF MS, and the sensitivity, specificity, and both the positive and negative predictive values of these two peaks were 100%. A new peak shift from 9627 Da for cfiA-negative isolates to 9642 Da for cfiA-positive isolates was observed.

CONCLUSIONS

A high prevalence of cfiA was observed among B.fragilis isolates in this study, especially those isolated from pediatric patients. Characteristic MS spectra can accurately discriminate cfiA-positive and -negative B. fragilis isolates and can contribute to the rapid screening of cfiA-positive B. fragilis isolates in clinical laboratories.

“Omic” Approaches to Bacteria and Antibiotic Resistance Identification

The quick and accurate identification of microorganisms and the study of resistance to antibiotics is crucial in the economic and industrial fields along with medicine. One of the fastest-growing identification methods is the spectrometric approach consisting in the matrix-assisted laser ionization/desorption using a time-of-flight analyzer (MALDI-TOF MS), which has many advantages over conventional methods for the determination of microorganisms presented. Thanks to the use of a multiomic approach in the MALDI-TOF MS analysis, it is possible to obtain a broad spectrum of data allowing the identification of microorganisms, understanding their interactions and the analysis of antibiotic resistance mechanisms. In addition, the literature data indicate the possibility of a significant reduction in the time of the sample preparation and analysis time, which will enable a faster initiation of the treatment of patients. However, it is still necessary to improve the process of identifying and supplementing the existing databases along with creating new ones. This review summarizes the use of “-omics” approaches in the MALDI TOF MS analysis, including in bacterial identification and antibiotic resistance mechanisms analysis.

Comprehensive investigation of antibiotic resistance gene content in cfiA-harboring Bacteroides fragilis isolates of human and animal origins by whole genome sequencing

INTRODUCTION

The emergence of multidrug resistance in Bacteroides fragilis, especially the phylogenetic lineage carrying the carbapenemase gene cfiA, represents an increasing threat to human health. However, knowledge on the diversity of the multidrug-resistant strains and the genetic elements carrying the antibiotic resistance genes (ARGs) remains limited.

AIM

The objective of the study was to describe the resistome in cfiA-positive B. fragilis.

METHODS

A collection of cfiA-positive B. fragilis from diverse human (8 bacteremias, 15 wound infections) and animal (2 chickens, 2 pigs, 6 dogs, 3 cats) sources in Hong Kong, 2015-2017 was analysed by whole genome sequencing.

RESULTS

In the 36 isolates, 13 distinct ARGs (total number 83, median 2, range 0-7 per isolate) other than cfiA were detected. ARGs encoding resistance to aminoglycosides, β-lactams, macrolides, sulphonamides and tetracyclines were carried by CTn341-like, CTnHyb-like, Tn5220-like, Tn4555-like and Tn613-like transposons and were detected in phylogenetically diverse isolates of different host sources. Only few ARGs encoding resistance to metronidazole and tetracyclines were localized on plasmids. In two chicken isolates, a novel transposon (designated as Tn6994) was found to be involved in the dissemination of multiple ARGs mediating resistance to multiple antibiotics, including metronidazole and linezolid that are critically important for treatment of anaerobic infections. In mating experiments, Tn6994 and the associated phenotypic resistance could be transferred to Bacteroides nordii recipient.

CONCLUSION

This study illustrates the importance of transposons in the dissemination of ARGs in the cfiA-positive division of B. fragilis. One Health approach is necessary to track the dissemination of ARGs.

Time for Some Group Therapy: Update on Identification, Antimicrobial Resistance, Taxonomy, and Clinical Significance of the Bacteroides fragilis Group

Bacteroides fragilis group (BFG) species are common members of the human microbiota that provide several benefits to healthy hosts, yet BFG are also the most common anaerobes isolated from human infections, including intra-abdominal infections, abscesses, and bloodstream infection. Compared to many other anaerobes associated with disease, members of the BFG are more likely to be resistant to commonly used antimicrobials, including penicillin (>90% resistant), carbapenems (2 to 20% resistant), and metronidazole (0.2 to 4% resistant). As a result, infection with BFG bacteria can be associated with poor clinical outcomes. Here, we discuss the role of BFG in human health and disease, proposed taxonomic reclassifications within the BFG, and updates in methods for species-level identification. The increasing availability of whole-genome sequencing (WGS) supports recent proposals that the BFG now span two families (Bacteroidaceae and "Tannerellaceae") and multiple genera (Bacteroides, Parabacteroides, and Phocaeicola) within the phylum Bacteroidota. While members of the BFG are often reported to "group" rather than "species" level in many clinical settings, new reports of species-specific trends in antimicrobial resistance profiles and improved resolution of identification tools support routine species-level reporting in clinical practice. Empirical therapy may not be adequate for treatment of serious infections with BFG, warranting susceptibility testing for serious infections. We summarize methods for antimicrobial susceptibility testing and resistance prediction for BFG, including broth microdilution, agar dilution, WGS, and matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). We examine global trends in BFG antimicrobial resistance and review genomics of BFG, revealing insights into rapid activation and dissemination of numerous antimicrobial resistance mechanisms.

Development and Validation of a Novel Anaerobic Carbapenem Inactivation Method (Ana-CIM) for the Detection of Carbapenemase Production in Bacteroides fragilis

Antibiotic resistance, particularly to carbapenems, is of increasing concern in Bacteroides fragilis. Carbapenem resistance in B. fragilis is most often mediated by the activation of chromosomally encoded metallo-β-lactamase cfiA by the presence of an upstream insertion sequence (IS). While traditional phenotypic susceptibility methods and molecular tests to detect carbapenem resistance in B. fragilis exist, they are not available in most clinical microbiology laboratory settings. Here, we describe the development of the anaerobic carbapenem inactivation method (Ana-CIM) for predicting carbapenemase production in B. fragilis based off the principles of the well-established modified carbapenem inactivation method (mCIM) for Enterobacterales and Pseudomonas aeruginosa. We also present the clinical validation and reproducibility of the Ana-CIM at three clinical laboratory sites (with 60 clinical isolates, 45% ertapenem resistant). Compared to ertapenem susceptibility by Etest interpreted by CLSI M100 Ed30, the Ana-CIM accurately detected carbapenem resistance in B. fragilis with categorical agreement (CA) of 87% (52/60) and 0% (0/21) very major error (VME), 11% (4/36) major error (ME), and 7% (4/60) minor error (mE) rates across all sites. Additionally, the Ana-CIM demonstrated high reproducibility with 5 clinical and 3 quality control (QC) isolates tested in triplicate with 3 commercial Mueller-Hinton media across all sites, with 93% (604/648) of replicates within a 2-mm zone size of the mode for each isolate. We conclude that the Ana-CIM can be readily deployed in clinical laboratories at a low cost for detection of carbapenemase-mediated resistance in B. fragilis.

MALDI-TOF MS Using a Custom-Made Database, Biomarker Assignment, or Mathematical Classifiers Does Not Differentiate Shigella spp. and Escherichia coli

Shigella spp. and E. coli are closely related and cannot be distinguished using matrix-assisted laser desorption-ionization time-of-flight mass spectrometry (MALDI-TOF MS) with commercially available databases. Here, three alternative approaches using MALDI-TOF MS to identify and distinguish Shigella spp., E. coli, and its pathotype EIEC were explored and evaluated using spectra of 456 Shigella spp., 42 E. coli, and 61 EIEC isolates. Identification with a custom-made database resulted in >94% Shigella identified at the genus level and >91% S. sonnei and S. flexneri at the species level, but the distinction of S. dysenteriae, S. boydii, and E. coli was poor. With biomarker assignment, 98% S. sonnei isolates were correctly identified, although specificity was low. Discriminating markers for S. dysenteriae, S. boydii, and E. coli were not assigned at all. Classification models using machine learning correctly identified Shigella in 96% of isolates, but most E. coli isolates were also assigned to Shigella. None of the proposed alternative approaches were suitable for clinical diagnostics for identifying Shigella spp., E. coli, and EIEC, reflecting their relatedness and taxonomical classification. We suggest the use of MALDI-TOF MS for the identification of the Shigella spp./E. coli complex, but other tests should be used for distinction.

Bloodstream infection caused by Bacteroides caccae in a patient with renal hypertension: a case report

Bacteroides caccae is an anaerobic bacterium with a reportedly high isolation rate; however, it rarely causes bloodstream infections. Patients with hypertension are at increased risk of developing anaerobic bacterial infection. In this study, we report a case of bacteremia caused by B. caccae in a patient with renal hypertension and gastrointestinal hemorrhage. This study describes the clinical manifestations of bloodstream infection involving B. caccae to provide guidance for laboratory technicians and clinicians. A 42-year-old Chinese man was admitted for gastrointestinal hemorrhage and subsequently diagnosed with anaerobic blood infection. The pathogenic bacteria isolated from anaerobic blood culture bottles were identified as B. caccae by using an automatic bacterial identification instrument and mass spectrometry (MS). B. caccae is an intestinal opportunistic pathogen that can invade the intestinal mucosa and cause anaerobic bloodstream infection. Two or more sets of blood cultures and MS identification can greatly improve the positive detection rate of blood cultures of anaerobic bacteria. Furthermore, the increased drug resistance of anaerobic bacteria necessitates drug sensitivity tests for anaerobic bacteria in many hospitals. Thus, the early prevention and control of primary diseases with appropriate diagnoses and timely anti-infection therapies are necessary to reduce B. caccae bloodstream infection.

Role of Rapid Diagnostics in Diagnosis and Management of Patients With Sepsis

Delayed administration of active anti-infective therapy is associated with increased rates of adverse events, mortality, and costs among sepsis patients. Inherent limitations of conventional culture identification methods and the lengthy turnaround time of antimicrobial susceptibility testing are significant barriers to the timely delivery of life-saving therapy, particularly among antibiotic-resistant infections. Culture-independent diagnostic techniques that detect pathogens and antimicrobial resistance genes within clinical samples present a tremendous benefit to timely diagnosis and management of patients. Improved outcomes for rapid intervention with rapid diagnostics have been documented and include decreased mortality rates, decreased health care delivery costs, and faster delivery of appropriate therapeutics.

Topological and kernel-based microbial phenotype prediction from MALDI-TOF mass spectra

MOTIVATION

Microbial species identification based on matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) has become a standard tool in clinical microbiology. The resulting MALDI-TOF mass spectra also harbour the potential to deliver prediction results for other phenotypes, such as antibiotic resistance. However, the development of machine learning algorithms specifically tailored to MALDI-TOF MS-based phenotype prediction is still in its infancy. Moreover, current spectral pre-processing typically involves a parameter-heavy chain of operations without analyzing their influence on the prediction results. In addition, classification algorithms lack quantification of uncertainty, which is indispensable for predictions potentially influencing patient treatment.

RESULTS

We present a novel prediction method for antimicrobial resistance based on MALDI-TOF mass spectra. First, we compare the complex conventional pre-processing to a new approach that exploits topological information and requires only a single parameter, namely the number of peaks of a spectrum to keep. Second, we introduce PIKE, the peak information kernel, a similarity measure specifically tailored to MALDI-TOF mass spectra which, combined with a Gaussian process classifier, provides well-calibrated uncertainty estimates about predictions. We demonstrate the utility of our approach by predicting antibiotic resistance of three clinically highly relevant bacterial species. Our method consistently outperforms competitor approaches, while demonstrating improved performance and security by rejecting out-of-distribution samples, such as bacterial species that are not represented in the training data. Ultimately, our method could contribute to an earlier and precise antimicrobial treatment in clinical patient care.

AVAILABILITY AND IMPLEMENTATION

We make our code publicly available as an easy-to-use Python package under https://github.com/BorgwardtLab/maldi_PIKE.

Recent evolutions of machine learning applications in clinical laboratory medicine

Machine learning (ML) is gaining increased interest in clinical laboratory medicine, mainly triggered by the decreased cost of generating and storing data using laboratory automation and computational power, and the widespread accessibility of open source tools. Nevertheless, only a handful of ML-based products are currently commercially available for routine clinical laboratory practice. In this review, we start with an introduction to ML by providing an overview of the ML landscape, its general workflow, and the most commonly used algorithms for clinical laboratory applications. Furthermore, we aim to illustrate recent evolutions (2018 to mid-2020) of the techniques used in the clinical laboratory setting and discuss the associated challenges and opportunities. In the field of clinical chemistry, the reviewed applications of ML algorithms include quality review of lab results, automated urine sediment analysis, disease or outcome prediction from routine laboratory parameters, and interpretation of complex biochemical data. In the hematology subdiscipline, we discuss the concepts of automated blood film reporting and malaria diagnosis. At last, we handle a broad range of clinical microbiology applications, such as the reduction of diagnostic workload by laboratory automation, the detection and identification of clinically relevant microorganisms, and the detection of antimicrobial resistance.

Binding of 2-(Triazolylthio)acetamides to Metallo-β-lactamase CcrA Determined with NMR

Metallo-β-lactamase (MBL)-producing bacteria resistant to β-lactam antibiotics are a serious threat to human health. Despite great efforts and important progress in the discovery of MBL inhibitors (MBLIs), there is none in clinical use. Herein, inhibitor complexes of the MBL CcrA were investigated by NMR spectroscopy to provide perspectives on the further development of 2-(triazolylthio)acetamide-type MBLIs. By using the NMR-based chemical shift perturbation (CSP) and direction of CSP methodologies together with molecular docking, the spatial orientation of three compounds in the CcrA active site was investigated (4-6). Inhibitor 6 showed the best binding affinity (K _d ≈ 2.3 ± 0.3 μM), followed by 4 (K _d = 11 ± 11 μM) and 5 (K _d = 34 ± 43 μM), as determined from the experimental NMR data. Based on the acquired knowledge, analogues of other MBLIs (1-3) were designed and evaluated in silico with the purpose of examining a strategy for promoting their interactions with the catalytic zinc ions.

How MALDI-TOF mass spectrometry can aid the diagnosis of hard-to-identify pathogenic bacteria - the rare and the unknown

Introduction: Ten years after its introduction into clinical microbiology, MALDI-TOF mass spectrometry has become the standard routine identification tool for bacteria in most laboratories. The technology has accelerated analyses and improved the quality of results. The greatest significance has been observed for bacteria that were challenging to be identified by traditional methods. Areas covered: We searched in existing literature (Pubmed) for reports how MALDI-TOF MS has contributed to identification of rare and unknown bacteria from different groups. We describe how this has improved the diagnostics in different groups of bacteria. Reference patterns for strains which yet cannot be assigned to a known species even enable the search for related bacteria in studies as well as in routine diagnostics. MALDI-TOF MS can help to discover and investigate new species and their clinical relevance. It is a powerful tool in the elucidation of the bacterial composition of complex microbiota in culturomics studies. Expert opinion: MALDI-TOF MS has improved the diagnosis of bacterial infections. It also enables knowledge generation for prospective diagnostics. The term 'hard-to-identify' might only be rarely attributed to bacteria in the future. Novel applications are being developed, e.g. subspecies differentiation, typing, and antibiotic resistance testing which may further contribute to improved microbial diagnostics.

Antimicrobial susceptibility of Bacteroides fragilis group organisms in Hong Kong by the tentative EUCAST disc diffusion method

This study used a recently developed EUCAST disc diffusion method to measure the susceptibility of 741 B. fragilis group isolates to six antibiotics. Isolates nonsusceptible to imipenem and metronidazole by the disc method were further investigated by E-test. Species identification was obtained by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS), PCR assays and 16S rRNA sequencing. The most common species were B. fragilis (n = 424, including 81 division II and 343 division I isolates), B. thetaiotaomicron (n = 111), B. ovatus (n = 53) and B. vulgatus (n = 46). Overall, metronidazole following by imipenem and amoxicillin-clavulanate are the most active agents with over 90% of all the isolates being susceptible at the tentative disc breakpoints. Susceptibility rates for moxifloxacin (69.5%), piperacillin-tazobactam (58.2%) and clindamycin (37.2%) were much lower. Metronidazole is the only agent active against >90% of B. fragilis, non-fragilis Bacteroides and Parabacteroides isolates. With the exception of B. fragilis division II, imipenem was active against 88.0%-98.3% of isolates of the other species. Susceptibility rates for clindamycin (14.4%-54.3%) and moxifloxacin (33.3%-80.6%) were low across all species and many isolates had no inhibition zone around the discs. E-test testing confirmed 8.2% (61/741) and 1.6% (12/741) isolates as nonsusceptible to imipenem and metronidazole, respectively with B. fragilis and B. thetaoiotaomicron accounting for a large share of the observed resistance to both agents. Two imipenem-resistant and one metronidazole-resistant B. dorei were misidentified as B. vulgatus by MALDI-TOF MS. These data highlights the importance anaerobic susceptibility testing in clinical laboratories to guide therapy.