Discriminative Potential of the Vitek MS In Vitro Diagnostic Device Regarding Haemophilus influenzae and Haemophilus haemolyticus

Prevalence of piperacillin/tazobactam resistance in invasive Haemophilus influenzae in Germany

Background

Haemophilus influenzae (Hi) is a Gram-negative bacterium that may cause sepsis or meningitis, treatment of which mainly includes β-lactam antibiotics. Since 2019 EUCAST breakpoints for piperacillin/tazobactam have been available. Little is known about the prevalence and mechanisms of piperacillin/tazobactam resistance in Hi.

Objectives

To provide reliable prevalence data for piperacillin/tazobactam resistance in Hi in Germany, to evaluate different antibiotic susceptibility testing methods and to examine possible resistance mechanisms.

Methods

According to EUCAST breakpoints, the MIC for piperacillin/tazobactam resistance is >0.25 mg/L. All invasive Hi in Germany from 2019 were examined by gradient agar diffusion (GAD) for piperacillin/tazobactam susceptibility. Piperacillin/tazobactam broth microdilution (BMD), piperacillin GAD on tazobactam-containing agar [piperacillin GAD on Mueller-Hinton agar with horse blood (MH-F)/tazobactam) and piperacillin/tazobactam agar dilution (AD) were used for confirmation. Phenotypic testing was complemented by ftsI sequencing.

Results

Piperacillin/tazobactam GAD resulted in 2.9% (21/726) resistant Hi. BMD did not confirm piperacillin/tazobactam resistance. Two strains were found resistant by AD, of which one was also resistant using piperacillin GAD on MH-F/tazobactam. Overall, we found two strains with a piperacillin/tazobactam MIC >0.25 mg/L in at least two different tests (0.3%). Both were β-lactamase-producing amoxicillin/clavulanate-resistant with PBP3 mutations characterized as group III-like+. Relevant PBP3 mutations occurred in six strains without phenotypic piperacillin/tazobactam resistance. These mutations suggest a reduced efficacy of β-lactam antibiotics in these isolates.

Conclusions

Piperacillin/tazobactam resistance prevalence in invasive Hi is low in Germany. Reduced susceptibility was correlated with PBP3 mutations, in particular with group III mutations.

Whole genome sequencing-based classification of human-related Haemophilus species and detection of antimicrobial resistance genes

Background

Bacteria belonging to the genus Haemophilus cause a wide range of diseases in humans. Recently, H. influenzae was classified by the WHO as priority pathogen due to the wide spread of ampicillin resistant strains. However, other Haemophilus spp. are often misclassified as H. influenzae. Therefore, we established an accurate and rapid whole genome sequencing (WGS) based classification and serotyping algorithm and combined it with the detection of resistance genes.

Methods

A gene presence/absence-based classification algorithm was developed, which employs the open-source gene-detection tool SRST2 and a new classification database comprising 36 genes, including capsule loci for serotyping. These genes were identified using a comparative genome analysis of 215 strains belonging to ten human-related Haemophilus (sub)species (training dataset). The algorithm was evaluated on 1329 public short read datasets (evaluation dataset) and used to reclassify 262 clinical Haemophilus spp. isolates from 250 patients (German cohort). In addition, the presence of antibiotic resistance genes within the German dataset was evaluated with SRST2 and correlated with results of traditional phenotyping assays.

Results

The newly developed algorithm can differentiate between clinically relevant Haemophilus species including, but not limited to, H. influenzae, H. haemolyticus, and H. parainfluenzae. It can also identify putative haemin-independent H. haemolyticus strains and determine the serotype of typeable Haemophilus strains. The algorithm performed excellently in the evaluation dataset (99.6% concordance with reported species classification and 99.5% with reported serotype) and revealed several misclassifications. Additionally, 83 out of 262 (31.7%) suspected H. influenzae strains from the German cohort were in fact H. haemolyticus strains, some of which associated with mouth abscesses and lower respiratory tract infections.

Resistance genes were detected in 16 out of 262 datasets from the German cohort. Prediction of ampicillin resistance, associated with bla_TEM-1D, and tetracycline resistance, associated with tetB, correlated well with available phenotypic data.

Conclusions

Our new classification database and algorithm have the potential to improve diagnosis and surveillance of Haemophilus spp. and can easily be coupled with other public genotyping and antimicrobial resistance databases. Our data also point towards a possible pathogenic role of H. haemolyticus strains, which needs to be further investigated.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-022-01017-x.