Automatic Discrimination of Species within the Enterobacter cloacae Complex Using Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry and Supervised Algorithms

The Enterobacter cloacae complex (ECC) encompasses heterogeneous clusters of species that have been associated with nosocomial outbreaks. These species may have different acquired antimicrobial resistance and virulence mechanisms, and their identification is challenging. This study aims to develop predictive models based on matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) profiles and machine learning for species-level identification. A total of 219 ECC and 118 Klebsiella aerogenes clinical isolates from three hospitals were included. The capability of the proposed method to differentiate the most common ECC species (Enterobacter asburiae, Enterobacter kobei, Enterobacter hormaechei, Enterobacter roggenkampii, Enterobacter ludwigii, and Enterobacter bugandensis) and K. aerogenes was demonstrated by applying unsupervised hierarchical clustering with principal-component analysis (PCA) preprocessing. We observed a distinctive clustering of E. hormaechei and K. aerogenes and a clear trend for the rest of the ECC species to be differentiated over the development data set. Thus, we developed supervised, nonlinear predictive models (support vector machine with radial basis function and random forest). The external validation of these models with protein spectra from two participating hospitals yielded 100% correct species-level assignment for E. asburiae, E. kobei, and E. roggenkampii and between 91.2% and 98.0% for the remaining ECC species; with data analyzed in the three participating centers, the accuracy was close to 100%. Similar results were obtained with the Mass Spectrometric Identification (MSI) database developed recently (https://msi.happy-dev.fr) except in the case of E. hormaechei, which was more accurately identified with the random forest algorithm. In short, MALDI-TOF MS combined with machine learning was demonstrated to be a rapid and accurate method for the differentiation of ECC species.

Statistical Evaluation of Metaproteomics and 16S rRNA Amplicon Sequencing Techniques for Study of Gut Microbiota Establishment in Infants with Cystic Fibrosis

Newborn screening for cystic fibrosis (CF) can identify affected but asymptomatic infants. The selection of omic technique for gut microbiota study is crucial due to both the small amount of feces available and the low microorganism load. Our aims were to compare the agreement between 16S rRNA amplicon sequencing and metaproteomics by a robust statistical analysis, including both presence and abundance of taxa, to describe the sequential establishment of the gut microbiota during the first year of life in a small size sample (8 infants and 28 fecal samples). The taxonomic assignations by the two techniques were similar, whereas certain discrepancies were observed in the abundance detection, mostly the lower predicted relative abundance of Bifidobacterium and the higher predicted relative abundance of certain Firmicutes and Proteobacteria by amplicon sequencing. During the first months of life, the CF gut microbiota is characterized by a significant enrichment of Ruminococcus gnavus, the expression of certain virulent bacterial traits, and the detection of human inflammation-related proteins. Metaproteomics provides information on composition and functionality, as well as data on host-microbiome interactions. Its strength is the identification and quantification of Actinobacteria and certain classes of Firmicutes, but alpha diversity indices are not comparable to those of amplicon sequencing. Both techniques detected an aberrant microbiota in our small cohort of infants with CF during their first year of life, dominated by the enrichment of R. gnavus within a human inflammatory environment. IMPORTANCE In recent years, some techniques have been incorporated for the study of microbial ecosystems, being 16S rRNA gene sequencing being the most widely used. Metaproteomics provides the advantage of identifying the interaction between microorganisms and human cells, but the available databases are less extensive as well as imprecise. Few studies compare the statistical differences between the two techniques to define the composition of an ecosystem. Our work shows that the two methods are comparable in terms of microorganism identification but provide different results in alpha diversity analysis. On the other hand, we have studied newborns with cystic fibrosis, for whom we have described the establishment of an intestinal ecosystem marked by the inflammatory response of the host and the enrichment of Ruminococcus gnavus.

The Human Mycobiome in Chronic Respiratory Diseases: Current Situation and Future Perspectives

Microbes play an important role in the pathogenesis of chronic lung diseases, such as chronic obstructive pulmonary disease, cystic fibrosis, non-cystic fibrosis bronchiectasis, and asthma. While the role of bacterial pathogens has been extensively studied, the contribution of fungal species to the pathogenesis of chronic lung diseases is much less understood. The recent introduction of next-generation sequencing techniques has revealed the existence of complex microbial lung communities in healthy individuals and patients with chronic respiratory disorders, with fungi being an important part of these communities’ structure (mycobiome). There is growing evidence that the components of the lung mycobiome influence the clinical course of chronic respiratory diseases, not only by direct pathogenesis but also by interacting with bacterial species and with the host’s physiology. In this article, we review the current knowledge on the role of fungi in chronic respiratory diseases, which was obtained by conventional culture and next-generation sequencing, highlighting the limitations of both techniques and exploring future research areas.

Multicenter Performance Evaluation of MALDI-TOF MS for Rapid Detection of Carbapenemase Activity in Enterobacterales: The Future of Networking Data Analysis With Online Software

In this study, we evaluate the performance of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) for rapid detection of carbapenemase activity in Enterobacterales in clinical microbiology laboratories during a multicenter networking validation study. The study was divided into three different stages: “software design,” “intercenter evaluation,” and “clinical validation.” First, a standardized procedure with an online software for data analysis was designed. Carbapenem resistance was detected by measuring imipenem hydrolysis and the results were automatically interpreted using the Clover MS data analysis software (Clover BioSoft, Spain). Second, a series of 74 genotypically characterized Enterobacterales (46 carbapenemase-producers and 28 non carbapenemase-producers) were analyzed in 8 international centers to ensure the reproducibility of the method. Finally, the methodology was evaluated independently in all centers during a 2-month period and results were compared with the reference standard for carbapenemase detection used in each center. The overall agreement rate relative to the reference method for carbapenemase resistance detection in clinical samples was 92.5%. The sensitivity was 93.9% and the specificity, 100%. Results were obtained within 60 min and accuracy ranged from 83.3 to 100% among the different centers. Further, our results demonstrate that MALDI-TOF MS is an outstanding tool for rapid detection of carbapenemase activity in Enterobacterales in clinical microbiology laboratories. The use of a simple in-house procedure with online software allows routine screening of carbapenemases in diagnostics, thereby facilitating early and appropriate antimicrobial therapy.

Travel-related fever in the time of COVID-19 travel restrictions

Travel-related infections with prolonged incubation periods should be considered in febrile patients despite the current epidemiological situation, especially if alternative more frequent diagnoses, such as COVID-19, are not confirmed.

Antimicrobial susceptibility of non-fermenting Gram-negative pathogens isolated from cystic fibrosis patients

Non-fermenting Gram-negative bacteria (NFGNB) are increasingly cultured in respiratory samples from cystic fibrosis (CF) patients. This study determined the antimicrobial susceptibility of clinical CF respiratory isolates from distinct geographical regions. A total of 286 isolates (106 Stenotrophomonas maltophilia, 100 Burkholderia spp., 59 Achromobacter spp., 12 Pandoraea spp., 9 Ralstonia spp.) from the Netherlands, Northern Ireland, Spain, USA and Australia were tested. MIC_50/90 values and susceptibility categorisation were determined. Trimethoprim/sulfamethoxazole (SXT) was the most active compound for all micro-organisms (MIC₅₀, 0.12-4 mg/L; MIC₉₀, 1-16 mg/L). For S. maltophilia, 47% and 62% of isolates were susceptible to SXT according to CLSI and EUCAST breakpoints, respectively. Ceftazidime presented lower susceptibility (35%; MIC₅₀, 32 mg/L; MIC₉₀, 256 mg/L). MIC₉₀ values for tobramycin and colistin were >128 mg/L and >16 mg/L, respectively. Regarding Burkholderia, 72%, 56% and 44% were susceptible to SXT, ceftazidime and meropenem, respectively. For both ceftazidime and meropenem, MIC₅₀ and MIC₉₀ values were within the intermediate or resistant category. The most active antibiotics for Achromobacter spp. were SXT (MIC₅₀, 0.5 mg/L; MIC₉₀, 8 mg/L) and imipenem (MIC₅₀, 2 mg/L; MIC₉₀, 8 mg/L). SXT, imipenem and ciprofloxacin were active against 12 Pandoraea spp. (MIC₅₀, 0.12-4 mg/L; MIC₉₀, 1-8 mg/L). Ciprofloxacin (MIC₅₀, 4 mg/L) and SXT (MIC₅₀, 1 mg/L) were the only active antibiotics for Ralstonia spp. There were no statistically significant differences in susceptibility rates between countries. NFGNB other than Pseudomonas aeruginosa are potential pathogens in CF. SXT was demonstrated to be the most active compound against these isolates.

Antibiotic resistance and population structure of cystic fibrosis Pseudomonas aeruginosa isolates from a Spanish multi-centre study

The first Spanish multi-centre study on the microbiology of cystic fibrosis (CF) was conducted from 2013 to 2014. The study involved 24 CF units from 17 hospitals, and recruited 341 patients. The aim of this study was to characterise Pseudomonas aeruginosa isolates, 79 of which were recovered from 75 (22%) patients. The study determined the population structure, antibiotic susceptibility profile and genetic background of the strains. Fifty-five percent of the isolates were multi-drug-resistant, and 16% were extensively-drug-resistant. Defective mutS and mutL genes were observed in mutator isolates (15.2%). Considerable genetic diversity was observed by pulsed-field gel electrophoresis (70 patterns) and multi-locus sequence typing (72 sequence types). International epidemic clones were not detected. Fifty-one new and 14 previously described array tube (AT) genotypes were detected by AT technology. This study found a genetically unrelated and highly diverse CF P. aeruginosa population in Spain, not represented by the epidemic clones widely distributed across Europe, with multiple combinations of virulence factors and high antimicrobial resistance rates (except for colistin).

Antibiotic prescription patterns in Spanish cystic fibrosis patients: results from a national multicenter study

OBJECTIVE

Information about antibiotic prescription patterns for cystic fibrosis (CF) patients and, specifically, about inhaled treatment strategies for their management is lacking in Spain due to the absence of a national patient registry. In this study we present data about antibiotic prescription in the Spanish CF context that were obtained in a multicenter study, being inhaled treatment strategies the special focus of this work.

METHODS

Twenty-four specialized CF units (12 adult, 12 pediatric) from 17 tertiary-care hospitals covering all Spanish Autonomous Communities provided sputa and clinical data from 15 consecutive patients. Data about antibiotic and non-antibiotic therapies prescribed to these patients during the year prior inclusion (2013) were retrospectively collected.

RESULTS

The multicenter study included 341 CF patients from all age groups and clinical status. The prevalence of oral, inhaled and intravenous therapies was 89% (n = 302), 80% (n = 273) and 31% (n = 105), respectively. The most prevalent oral agents were ciprofloxacin (n = 177, 59%), cotrimoxazole (n = 109, 36%) and amoxicillin-clavulanate (n = 99, 33%), whereas ceftazidime (n = 53, 50%), tobramycin (n = 43, 41%) and meropenem (n = 41, 49%) were the most prevalent intravenous ones. Two or more different inhaled antibiotics were administered to 67 patients (24%), 51 of them receiving 2 drugs continuously in alternating schemes. Nebulization of intravenous specific antibiotics was common (n = 39) and, in some cases, was used for maintenance purposes.

CONCLUSIONS

These results show that the treatment of CF patients is evolving more rapidly than clinical consensus guidelines. Clinical trials evaluating new specific inhaled combinations and new alternative treatment regimes of the existing ones are needed.

Shortcomings of the Commercial MALDI-TOF MS Database and Use of MLSA as an Arbiter in the Identification of Nocardia Species

Nocardia species are difficult to identify, a consequence of the ever increasing number of species known and their homogeneous genetic characteristics. 16S rRNA analysis has been the gold standard for identifying these organisms, but proteomic techniques such as matrix-assisted laser desorption ionization-time of flight (MALDI-TOF MS) and housekeeping gene analysis, have also been explored. One hundred high (n = 25), intermediate (n = 20), and low (n = 55) prevalence (for Spain) Nocardia strains belonging to 30 species were identified via 16S rRNA and MALDI-TOF MS analysis. The manufacturer-provided database MALDI Biotyper library v4.0 (5.627 entries, Bruker Daltonik) was employed. In the high prevalence group (Nocardia farcinica, N. abscessus, N. cyriacigeorgica and N. nova), the 16S rRNA and MALDI-TOF MS methods provided the same identification for 76% of the strains examined. For the intermediate prevalence group (N. brasiliensis, N. carnea, N. otitidiscaviarum and N. transvalensis complex), this figure fell to 45%. In the low-prevalence group (22 species), these two methods were concordant only in six strains at the species level. Tetra-gene multi-locus sequencing analysis (MLSA) involving the concatemer gyrB-16S rRNA-hsp65-secA1 was used to arbitrate between discrepant identifications (n = 67). Overall, the MLSA confirmed the results provided at species level by 16S rRNA analysis in 34.3% of discrepancies, and those provided by MALDI-TOF MS in 13.4%. MALDI-TOF MS could be a strong candidate for the identification of Nocardia species, but only if its reference spectrum database improves, especially with respect to unusual, recently described species and species included in the described Nocardia complexes.

Microbiological diagnostic procedures for respiratory cystic fibrosis samples in Spain: towards standard of care practices

BACKGROUND

The microbiological procedures for cystic fibrosis (CF) samples of 17 participating Spanish centers were examined to verify their compliance with current international and national guidelines and to implement the best standards of care for microbiology practices. A 47-item questionnaire covering different CF microbiology aspects was sent to participant laboratories. Telephone interviews were performed when necessary. Data about samples processing for bacteria, mycobacteria and fungi were collected.

RESULTS

Gene sequencing (71%), MALDI-TOF (59%) or both (94%) were available for most laboratories. Susceptibility testing was performed by automated microdilution systems (94%) and manual diffusion methods (59%). However, a low use of selective media for Staphylococcus aureus (59%) and Burkholderia cepacia complex (71%), and of epidemiological typing methods (41%) was reported.

CONCLUSIONS

Most Spanish laboratories are in agreement with consensus guidelines for the processing of CF respiratory samples, but need to improve in the use of specific selective media and typing methods for epidemiologic studies.