Identification of a proteomic biomarker associated with invasive ST1, serotype VI Group B Streptococcus by MALDI-TOF MS

The clinical and molecular characteristics of invasive Streptococcus agalactiae diseases in nonpregnant adults in Taiwan

BACKGROUND

Streptococcus agalactiae (Group B Streptococcus, GBS) is a growing threat to nonpregnant adults. We aimed to describe the clinical and molecular characteristics of invasive GBS infections in adults.

METHODS

All adults with invasive GBS infections at a tertiary-level medical center in Taiwan between 2014 and 2020 were analyzed. Capsule serotyping, multilocus sequence typing and antibiotic susceptibility testing were performed.

RESULTS

A total of 666 adults with GBS infections were analyzed. The median age at onset was 65 years (range 19-102). The most common manifestation was bacteremia without focus (80.4 %). The younger patients (19-39 years old) had a significantly higher rate of non-bloodstream infections (24.6 %, P < 0.001) and were overweight in most cases (77.2 %). Most patients had underlying chronic comorbidities (82.3 %). Capsular types VI (33.0 %), Ia (19.4 %), III (15.0 %), and V (10.2 %) were predominant. Clonal complexes (CCs) 1, 12, 17, 19, 23 and 452 accounted for 96.3 % (464/482) of the cases. All GBS isolates were susceptible to β-lactam antibiotics. The rates of resistance to erythromycin and clindamycin were 42.6 % and 39.2 %, respectively, but were especially high in type III, Ib and V GBS isolates. The mortality rates at one month and one year were 5.0 % and 12.3 %, respectively, but were significantly higher in elderly patients.

CONCLUSION

The clinical manifestations of invasive GBS infections in adults are diverse. Elderly patients are susceptible to invasive GBS infections and have a relatively high mortality rate. Continuous surveillance of GBS epidemiology should be enforced given the increasing growing importance of antibiotic-resistant GBS isolates.

Automated classification of group B Streptococcus into different clonal complexes using MALDI-TOF mass spectrometry

Objectives

To evaluate the performance of Matrix-Assisted Laser Desorption/Ionization Time-of Flight Mass Spectra (MALDI-TOF MS) for automated classification of GBS (Group B Streptococcus) into five major CCs (clonal complexes) during routine GBS identification.

Methods

MALDI-TOF MS of 167 GBS strains belonging to five major CCs (CC10, CC12, CC17, CC19, CC23) were grouped into a reference set (n = 67) and a validation set (n = 100) for the creation and evaluation with GBS CCs subtyping main spectrum (MSP) and MSP-M using MALDI BioTyper and ClinProTools. GBS CCs subtyping MSPs-M was generated by resetting the discriminative peaks of GBS CCs subtyping MSP according to the informative peaks from the optimal classification model of five major CCs and the contribution of each peak to the model created by ClinProTools.

Results

The PPV for the GBS CCs subtyping MSP-M was greater than the subtyping MSP for CC10 (99.21% vs. 93.65%), but similar for CC12 (79.55% vs. 81.06%), CC17 (93.55% vs. 94.09%), and CC19 (92.59% vs. 95.37%), and lower for CC23 (66.67% vs. 83.33%).

Conclusion

MALDI-TOF MS could be a promising tool for the automated categorization of GBS into 5 CCs by both CCs subtyping MSP and MSP-M, GBS CCs subtyping MSP-M is preferred for the accurate prediction of CCs with highly discriminative peaks.

Methylocystis sp. Strain SC2 Acclimatizes to Increasing NH4+ Levels by a Precise Rebalancing of Enzymes and Osmolyte Composition

A high NH4+ load is known to inhibit bacterial methane oxidation. This is due to a competition between CH4 and NH3 for the active site of particulate methane monooxygenase (pMMO), which converts CH4 to CH3OH. Here, we combined global proteomics with amino acid profiling and nitrogen oxides measurements to elucidate the cellular acclimatization response of Methylocystis sp. strain SC2 to high NH4+ levels. Relative to 1 mM NH4+, a high (50 mM and 75 mM) NH4+ load under CH4-replete conditions significantly increased the lag phase duration required for proteome adjustment. The number of differentially regulated proteins was highly significantly correlated with an increasing NH4+ load. The cellular responses to increasing ionic and osmotic stress involved a significant upregulation of stress-responsive proteins, the K+ "salt-in" strategy, the synthesis of compatible solutes (glutamate and proline), and the induction of the glutathione metabolism pathway. A significant increase in the apparent Km value for CH4 oxidation during the growth phase was indicative of increased pMMO-based oxidation of NH3 to toxic hydroxylamine. The detoxifying activity of hydroxlyamine oxidoreductase (HAO) led to a significant accumulation of NO2- and, upon decreasing O2 tension, N2O. Nitric oxide reductase and hybrid cluster proteins (Hcps) were the candidate enzymes for the production of N2O. In summary, strain SC2 has the capacity to precisely rebalance enzymes and osmolyte composition in response to increasing NH4+ exposure, but the need to simultaneously combat both ionic-osmotic stress and the toxic effects of hydroxylamine may be the reason why its acclimatization capacity is limited to 75 mM NH4+. IMPORTANCE In addition to reducing CH4 emissions from wetlands and landfills, the activity of alphaproteobacterial methane oxidizers of the genus Methylocystis contributes to the sink capacity of forest and grassland soils for atmospheric methane. The methane-oxidizing activity of Methylocystis spp. is, however, sensitive to high NH4+ concentrations. This is due to the competition of CH4 and NH3 for the active site of particulate methane monooxygenase, thereby resulting in the production of toxic hydroxylamine with an increasing NH4+ load. An understanding of the physiological and molecular response mechanisms of Methylocystis spp. is therefore of great importance. Here, we combined global proteomics with amino acid profiling and NOx measurements to disentangle the cellular mechanisms underlying the acclimatization of Methylocystis sp. strain SC2 to an increasing NH4+ load.

Clinical characteristics of bacteremia caused by Haemophilus and Aggregatibacter species and antimicrobial susceptibilities of the isolates

BACKGROUND/PURPOSE

This study aimed to investigate the clinical characteristics and outcomes of bacteremia caused by Haemophilus and Aggregatibacter species in patients who were treated at a medical center between 2006 and 2018.

METHODS

Haemophilus and Aggregatibacter isolates were identified up to the species level using Bruker Biotyper MALDI-TOF analysis and ancillary 16S rRNA gene sequencing analysis (in case of ambiguity). Clinical characteristics and outcomes of patients with bacteremia caused by these organisms were evaluated.

RESULTS

Sixty-five Haemophilus and Aggregatibacter species isolates causing bacteremia were identified from nonduplicated patients, including 51 (78.5%) Haemophilus influenzae, 6 (9.2%) Haemophilus parainfluenzae, 1 (1.5%) Haemophilus haemolyticus, 3 (4.6%) A. aphrophilus, and 4 (6.2%) A. segnis. Hospital mortality was observed in 18 (28.1%) of 64 patients with bacteremia caused by Haemophilus (n = 57) and Aggregatibacter species (n = 7). The majority of patients with bacteremia had community-acquired disease with low severity. The average Sequential Organ Failure Assessment (SOFA) score was low (4.4 ± 4.7). But, a higher SOFA score (adjusted odds ratio 2.5, 95% confidence interval 1.22-5.12; P = 0.01) was an independent factor predicting poor 7-day clinical outcomes in patients with community-acquired H. influenzae bacteremia (n = 39).

CONCLUSIONS

The overall hospital mortality of 28.1% was observed among patients with bacteremia due to Haemophilus and Aggregatibacter species. A higher SOFA score was and independent predictor of poor 7-day clinical outcomes in patients with community-acquired H. influenzae bacteremia.

Rapid detection by MALDI-TOF MS of isolates from cystic fibrosis patients belonging to the epidemic clones Achromobacter xylosoxidans ST137 or Achromobacter ruhlandii DES

Objective: Achromobacter spp. are increasingly reported among cystic fibrosis patients. Genotyping requires time consuming methods such as Multilocus-Sequence-Typing or Pulsed-Field-Gel-Electrophoresis. Therefore, data on the prevalence of the multiresistant epidemic clones, especially A. xylosoxidans ST137 (AxST137) and the Danish Epidemic Strain A. ruhlandii (DES) are lacking. We recently developed and published a database for Achromobacter species identification by matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS, Bruker Daltonics). The aim of this study was to evaluate the ability of the MALDI-TOF MS to distinguish these multiresistant epidemic clones within Achromobacter species. Methods: All the spectra of A.xylosoxidans (n=1571) and A.ruhlandii (n=174) used to build the local database were analysed by ClinProTools™, MALDI Biotyper® PCA, MALDI Biotyper^® dendrogram and flexAnalysis™ softwares for biomarker peaks detection. Two-hundred-two isolates (including 48 isolates of AxST137 and 7 of DES) were tested. Results: Specific biomarker peaks were identified: absent peak at m/z 6651 for AxST137 isolates and present peak at m/z 9438 for DES isolates. All tested isolates were well typed by our local database and clustered within distinct groups (ST137 or non-ST137 and DES or non-DES) no matter the MALDI-TOF software or only by simple visual inspection of the spectra by any user. Conclusions: The use of MALDI-TOF MS allowed identifying isolates of A. xylosoxidans belonging to the AxST137 clone which spread in France and Belgium (the Belgian epidemic clone) and of A. ruhlandii belonging to the DES clone. This tool will help implementation of segregation measures to avoid inter-patient transmission of these resistant clones.

Matrix-Assisted Laser Desorption/Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS) Analysis for the Identification of Pathogenic Microorganisms: A Review

Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been used in the field of clinical microbiology since 2010. Compared with the traditional technique of biochemical identification, MALDI-TOF MS has many advantages, including convenience, speed, accuracy, and low cost. The accuracy and speed of identification using MALDI-TOF MS have been increasing with the development of sample preparation, database enrichment, and algorithm optimization. MALDI-TOF MS has shown promising results in identifying cultured colonies and rapidly detecting samples. MALDI-TOF MS has critical research applications for the rapid detection of highly virulent and drug-resistant pathogens. Here we present a scientific review that evaluates the performance of MALDI-TOF MS in identifying clinical pathogenic microorganisms. MALDI-TOF MS is a promising tool in identifying clinical microorganisms, although some aspects still require improvement.

Rapid Classification of Multilocus Sequence Subtype for Group B Streptococcus Based on MALDI-TOF Mass Spectrometry and Statistical Models

Group B Streptococcus (GBS) is an important etiological agent of maternal and neonatal infections as well as postpartum women and individuals with impaired immunity. We developed and evaluated a rapid classification method for sequence types (STs) of GBS based on statistic models with Matrix-Assisted Laser Desorption/Ionization Time-of Flight Mass Spectrometry (MALDI-TOF/MS). Whole-cell lysates MALDI-TOF/MS analysis was performed on 235 well-characterized GBS isolates from neonatal invasive infections in a multi-center study in China between 2015 and 2017. Mass spectra belonging to major STs (ST10, ST12, ST17, ST19, ST23) were selected for model generation and validation. Recognition and cross validation values were calculated by Genetic Algorithm-K Nearest Neighbor (GA-KNN), Supervised Neural Network (SNN), QuickClassifier (QC) to select models with the best performance for validation of diagnostic efficiency. Informative peaks were further screened through peak statistical analysis, ST subtyping MSP peak data and mass spectrum visualization. For major STs, the ML models generated by GA-KNN algorithms attained highest cross validation values in comparison to SNN and QC algorithms. GA-KNN models of ST10, ST17, and ST12/ST19 had good diagnostic efficiency, with high sensitivity (95–100%), specificity (91.46%–99.23%), accuracy (92.79–99.29%), positive prediction value (PPV, 80%–92.68%), negative prediction value (NPV, 94.32%–99.23%). Peak markers were firstly identified for ST10 (m/z 6250, 3125, 6891) and ST17 strains (m/z 2956, 5912, 7735, 5218). Statistical models for rapid GBS ST subtyping using MALDI-TOF/MS spectrometry contributes to easier epidemical molecular monitoring of GBS infection diseases.

Clustering of Streptococcus gallolyticus subspecies pasteurianus bacteremia and meningitis in neonates

BACKGROUND/PURPOSE

Although Streptococcus gallolyticus subspecies pasteurianus (SGSP) is a rare pathogen in children, it can cause invasive infections among neonates and infants. Herein, we report bacteremia/meningitis caused by SGSP in three neonates and review the literature on bacteremia and/or meningitis caused by this organism.

METHODS

Three neonates, referred from an obstetrics clinic within a 2-month period, presented with invasive SGSP infections. The bacterial isolates were analyzed using Bruker Biotyper MALDI-TOF, sequencing of 16S rRNA and sodA genes (encoding manganese dependent superoxide dismutase), and PCR restriction fragment length polymorphism assay of groESL gene. Molecular typing was performed to evaluate the genetic relatedness.

RESULTS

The median onset age of infection in the three neonates was 3 days (range 2-5 days). They were delivered through cesarean section in the same operation room under different doctors, and were cared for by different nurses. Patient A presented with bacteremia, patient B with bacteremia and meningitis, and patient C with meningitis. Four isolates were identified as SGSP and were susceptible to penicillin G, cefotaxime, and vancomycin. All patients were treated with ampicillin plus cefotaxime for 14 days, and no complications were observed. The molecular typing results suggested that all isolates belonged to a single clone, which indicated the possibility of an outbreak in the obstetrics clinic.

CONCLUSION

Infection by a rare pathogen such as SGSP in multiple patients belonging to a single healthcare unit indicates that detailed investigation and stringent infection control policy are necessary for preventing further outbreaks of such diseases.

A simple, rapid typing method for Streptococcus agalactiae based on ribosomal subunit proteins by MALDI-TOF MS

Streptococcus agalactiae (Group B Streptococcus, GBS), is a frequent human colonizer and a leading cause of neonatal meningitis as well as an emerging pathogen in non-pregnant adults. GBS possesses a broad animal host spectrum, and recent studies proved atypical GBS genotypes can cause human invasive diseases through animal sources as food-borne zoonotic infections. We applied a MALDI-TOF MS typing method, based on molecular weight variations of predefined 28 ribosomal subunit proteins (rsp) to classify GBS strains of varying serotypes into major phylogenetic lineages. A total of 249 GBS isolates of representative and varying capsular serotypes from patients and animal food sources (fish and pig) collected during 2016-2018 in Hong Kong were analysed. Over 84% (143/171) noninvasive carriage GBS strains from patients were readily typed into 5 globally dominant rsp-profiles. Among GBS strains from food animals, over 90% (57/63) of fish and 13% (2/15) of pig GBS matched with existing rsp-profiles, while the remainder were classified into two novel rsp-profiles and we failed to assign a fish strain into any cluster. MALDI-TOF MS allowed for high-throughput screening and simultaneous detection of novel, so far not well described GBS genotypes. The method shown here is rapid, simple, readily transferable and adapted for use in a diagnostic microbiology laboratory with potential for the surveillance of emerging GBS genotypes with zoonotic potential.

Antibiotic Resistance and Molecular Epidemiological Characteristics of Streptococcus agalactiae Isolated from Pregnant Women in Guangzhou, South China

Streptococcus agalactiae colonization in pregnant women can cause postpartum intrauterine infections and life-threatening neonatal infections. To formulate strategies for the prevention and treatment of S. agalactiae infections, we performed a comprehensive analysis of antibiotic resistance and a molecular-based epidemiological investigation of S. agalactiae in this study. Seventy-two S. agalactiae strains, collected from pregnant women, were subjected to antibiotic susceptibility tests; then, the screened erythromycin and clindamycin nonsusceptible isolates were used for macrolides and clindamycin resistance genes detection, respectively. Detection of resistance genes, serotyping, and determination of virulence genes were performed by polymerase chain reaction. The clonal relationships among the colonized strains were evaluated by multilocus sequence typing. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) mass peak analysis was performed to discriminate the specific sequence types (STs). In our study, 69.4% and 47.2% of the strains were nonsusceptible to erythromycin and clindamycin, respectively; the multidrug resistance rate was 66.7%. All erythromycin nonsusceptible strains harbored resistance genes, whereas only 52.9% of the clindamycin nonsusceptible strains possessed the linB gene. Erythromycin resistance was mainly mediated by the ermB or mefA/E genes. Four serotypes were identified, and the most common serotype was serotype III (52.8%), followed by Ib (22.2%), Ia (18.0%), and II (4.2%). All the strains were divided into 18 STs that were assigned to nine clonal complexes. Most of the major STs were distributed into specific serotypes, including ST19/serotype III, ST17/serotype III, ST485/serotype Ia, ST862/serotype III, and ST651/serotype III. Analysis of virulence genes yielded seven clusters, of which bca-cfb-scpB-lmb (61.6%) was the predominant virulence gene cluster. Among all ST strains distributed in this region, only the ST17 strains had a mass peak at 7620 Da. The outcomes of this study are beneficial for the epidemiological comparison of colonized S. agalactiae in different regions and may be helpful for developing the strategies for the prevention of S. agalactiae infection in Guangzhou. Furthermore, our results show that MALDI-TOF MS can be used for the rapid identification of the ST17 strains.

Rapid classification of group B Streptococcus serotypes based on matrix-assisted laser desorption ionization-time of flight mass spectrometry and machine learning techniques

Background

Group B streptococcus (GBS) is an important pathogen that is responsible for invasive infections, including sepsis and meningitis. GBS serotyping is an essential means for the investigation of possible infection outbreaks and can identify possible sources of infection. Although it is possible to determine GBS serotypes by either immuno-serotyping or geno-serotyping, both traditional methods are time-consuming and labor-intensive. In recent years, the matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has been reported as an effective tool for the determination of GBS serotypes in a more rapid and accurate manner. Thus, this work aims to investigate GBS serotypes by incorporating machine learning techniques with MALDI-TOF MS to carry out the identification.

Results

In this study, a total of 787 GBS isolates, obtained from three research and teaching hospitals, were analyzed by MALDI-TOF MS, and the serotype of the GBS was determined by a geno-serotyping experiment. The peaks of mass-to-charge ratios were regarded as the attributes to characterize the various serotypes of GBS. Machine learning algorithms, such as support vector machine (SVM) and random forest (RF), were then used to construct predictive models for the five different serotypes (Types Ia, Ib, III, V, and VI). After optimization of feature selection and model generation based on training datasets, the accuracies of the selected models attained 54.9–87.1% for various serotypes based on independent testing data. Specifically, for the major serotypes, namely type III and type VI, the accuracies were 73.9 and 70.4%, respectively.

Conclusion

The proposed models have been adopted to implement a web-based tool (GBSTyper), which is now freely accessible at http://csb.cse.yzu.edu.tw/GBSTyper/, for providing efficient and effective detection of GBS serotypes based on a MALDI-TOF MS spectrum. Overall, this work has demonstrated that the combination of MALDI-TOF MS and machine intelligence could provide a practical means of clinical pathogen testing.

Evaluation of an optimized method to directly identify bacteria from positive blood cultures using MALDI-TOF mass spectrometry

Background

Although various methods have been developed to directly identify bacteria from positive blood cultures by matrix‐assisted laser desorption ionization time‐of‐flight mass spectrometry (MALDI‐TOF MS), the necessity of using commercial kits still leads to a high cost and long assay time. Moreover, few evaluations of these methods have been conducted. This study aimed to evaluate the feasibility of an optimized MALDI‐TOF MS method for direct identification of bacteria in positive blood cultures.

Methods

A total of 829 non‐repeated positive cultures were collected from July 2018 to August 2019, and direct identification was performed by an optimized MALDI‐TOF MS method. The same positive blood cultures were sub‐cultivated to obtain a single bacterial colony and identified by classical biochemical BD testing, which is the gold standard to compare the accuracy of direct identification of positive blood cultures by MALDI‐TOF MS.

Results

After excluding 7 false‐positive samples from the 829 positive blood cultures, the most accurate rate of direct identification by this optimized MALDI‐TOF MS method was for gram‐negative bacteria (91.5%), followed by gram‐positive bacteria (88.3%), fungi (84.8%), anaerobic bacteria (80%), and other rare bacteria (66.67%).

Conclusion

Common bacteria in positive blood cultures can be identified directly within 1 hour by MALDI‐TOF MS, and thus, this optimized method can be used as a primary identification method by clinicians. Routine implementation of this method may significantly increase the optimal utilization rate of antibiotics and decrease mortality in bacteremia patients.

Clinical and Microbiological Characteristics of Group B Streptococcus from Pregnant Women and Diseased Infants in Intrapartum Antibiotic Prophylaxis Era in Taiwan

Group B Streptococcus (GBS) is one of the most important pathogens for neonates. This study included 69 invasive GBS diseases in neonates, including 7 early-onset disease (EOD), 55 late-onset disease, and 7 very-late-onset disease from 2013 to 2017. A significant reduction of EOD after the deployment of intrapartum antibiotic prophylaxis (IAP) in 2012 was observed. A previously-recognized hypervirulent clone GBS III ST17, accounting for 68% of the overall infections and 71% of the meningitis, was identified among the 69 cases. A novel GBS Ia ST890 emerged, becoming the fourth most common clone. Overall 96% of the invasive GBS infections were caused by serotypes Ia, Ib, and III. We collected 300 GBS isolates from vagina of the healthy pregnant women in 2014 and 2017. The serotype distribution of the maternal colonization isolates was VI (35%), III (21%), V (15%), Ib (13%) and Ia (11%) in 2014, and VI (32%), III (22%), V (16%), Ia (16%), and Ib (8%) in 2017. The most common sequence types were ST1 (32%), ST12 (22%), and ST23 (15%). Serotype diversity of maternal colonization strains did not change between 2014 and 2017. The study provides useful information in surveillance of GBS disease in the era of IAP.

Subspecies Typing of Streptococcus agalactiae Based on Ribosomal Subunit Protein Mass Variation by MALDI-TOF MS

Background: A ribosomal subunit protein (rsp)-based matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) method was developed for fast subspecies-level typing of Streptococcus agalactiae (Group B Streptococcus, GBS), a major cause of neonatal sepsis and meningitis.

Methods: A total of 796 GBS whole genome sequences, covering the genetic diversity of the global GBS population, were used to in silico predict molecular mass variability of 28 rsp and to identify unique rsp mass combinations, termed “rsp-profiles”. The in silico established GBS typing scheme was validated by MALDI-TOF MS analysis of GBS isolates at two independent research sites in Europe and South East Asia.

Results: We identified in silico 62 rsp-profiles, with the majority (>80%) of the 796 GBS isolates displaying one of the six rsp-profiles 1–6. These dominant rsp-profiles classify GBS strains in high concordance with the core-genome based phylogenetic clustering. Validation of our approach by in-house MALDI-TOF MS analysis of 248 GBS isolates and external analysis of 8 GBS isolates showed that across different laboratories and MALDI-TOF MS platforms, the 28 rsp were detected reliably in the mass spectra, allowing assignment of clinical isolates to rsp-profiles at high sensitivity (99%) and specificity (97%). Our approach distinguishes the major phylogenetic GBS genotypes, identifies hyper-virulent strains, predicts the probable capsular serotype and surface protein variants and distinguishes between GBS genotypes of human and animal origin.

Conclusion: We combine the information depth of whole genome sequences with the highly cost efficient, rapid and robust MALDI-TOF MS approach facilitating high-throughput, inter-laboratory, large-scale GBS epidemiological and clinical studies based on pre-defined rsp-profiles.