Biology subjects

Corbella, M.

Publications and source records attributed to Corbella, M..

13 recordsLinked to original sources

bioRxiv2026

Seven amino acids gate transcriptional activation by a minimal MarA Helix turn-helix DNA-binding domain

Prokaryotic transcription factors (TFs) lie at the core of antimicrobial resistance, controlling genes that let bacteria survive antibiotic exposure. The AraC/XylS family of TFs is defined by a ~99-residue DNA-binding domain composed of two helix-turn-helix (HTH) motifs. While this two-motif architecture is considered the minimal functional unit, the striking sequence and structural similarity between both HTH motifs raises the question of whether it evolved from a single ancestral HTH domain. Here, we designed two C-terminal truncations of MarA, comprising a single HTH motif, differing by seven-residues (IRSRKMT). Electrophoretic-mobility shift assays reveal that both constructs specifically bind the marbox sequence as reconstituted dimers, while size-exclusion chromatography shows they exist in a monomer-dimer equilibrium in solution. Despite retaining DNA-binding capacity, the truncations diverge functionally: while MarA64 (including IRSRKMT) activates transcription and confers regular erythromycin tolerance, MarA57 (lacking IRSRKMT) yields a transcriptionally inactive complex that suppresses reporter expression below baseline, suggesting competitive promoter occupancy. Molecular dynamics simulations and AlphaFold models suggest that the IRSRKMT extension forms an -helical element stabilizing a transcriptionally productive dimer interface. Conversely, its loss disrupts quaternary assembly, alters DNA bending, and misaligns RNA polymerase-contacting residues. Furthermore, free dimers explore non-productive conformations, suggesting that functional dimerization occurs upon DNA engagement. These findings establish that a single, correctly dimerized HTH domain is sufficient for both DNA binding and transcriptional activation, providing a structural rationale for short AraC/XylS-like proteins and offering a tuneable scaffold for synthetic biology and novel anti-virulence strategies.

molecular biology↗

bioRxiv2025

Ciprofloxacin resistance in Klebsiella pneumoniae: phenotype prediction from genotype and global distribution of resistance determinants

BACKGROUNDCiprofloxacin resistant Klebsiella pneumoniae is common or emerging in many geographies, and knowledge of local resistance rates is important for empirical therapy. Whilst there are known K. pneumoniae ciprofloxacin resistance determinants, there is a lack of systematic data on the effect of determinants, alone and in combination, and there are no publicly accessible tools for predicting resistance from whole genome sequence data. METHODSThe KlebNET-GSP AMR Genotype-Phenotype Group aggregated a matched genotype-phenotype dataset of n=12,167 K. pneumoniae species complex (KpSC) isolates from 27 countries between 2001-2021. We developed a rules-based classifier to predict ciprofloxacin resistance by categorizing the number of quinolone resistance determining regions mutations in gyrA and parC, the number of plasmid-mediated quinolone resistance genes, and the presence/absence of aac(6')-Ib-cr (which can acetylate ciprofloxacin). Predictive performance was assessed using the discovery dataset, for which we re-phenotyped discrepant isolates; and validated using externally contributed datasets (n=7,030 KpSC isolates). RESULTSThe rules-based classifier predicted R vs S/I with categorical agreement, sensitivity, and specificity >96%, and major/very major error rates <4%. Performance was similar across diverse KpSC sources (human, animal, other), species, and intra-species lineages. External validation of the classifier yielded overall 93.12% categorical agreement [95% confidence interval (CI), 92.50-93.74%], 8.65% major errors [95% CI, 7.34-9.97%], and 6.20% very major errors [95% CI, 5.51-6.90%]. We implemented the classifier in Kleborate, a command-line tool that is integrated into the Pathogenwatch web platform. Using this to assess the global distribution of ciprofloxacin resistance determinants in KpSC genomes available in Pathogenwatch (n=31,319, from 109 countries between years 2000-2023), we observed a significant positive association between national quinolone consumption rates and predicted ciprofloxacin resistance (R2=0.20, p=0.004). CONCLUSIONS Ciprofloxacin resistance phenotypes can be reasonably predicted from genotypes, which is sufficient for informing surveillance. However, unexplained resistance remains and accuracy is insufficient for clinical applications. We demonstrate the value of aggregating genotype-phenotype data to explore resistance mechanisms and develop predictors, but highlight complexities in combining phenotype data from different assays and standards.

genomics↗

bioRxiv2024

Genomic characterization of a persistent, azole-resistant C. parapsilosis strain responsible for a hospital outbreak during the first COVID-19 wave

Yeasts belonging to the Candida genus typically reside on the mucosal surface and within the respiratory and gastrointestinal tract as commensals. Under conditions of host vulnerability, they can act as opportunistic pathogens, leading to various forms of candidiasis, including candidemia. Such infections can be particularly problematic when caused by isolates that exhibit resistance to antifungal drugs, which is becoming more prevalent in many regions. One hundred and seven samples of Candida spp. were isolated from patients with candidemia in the hospital San Matteo in Pavia (Italy) over a period of 6 years, from 2015 to the first COVID wave in spring 2020. In order to understand the epidemiology of Candida infections in this hospital setting, the isolates were whole-genome sequenced which identified most as C. parapsilosis and C. albicans. Comparative genomics revealed that isolates of C. albicans were genomically diverse, indicating repeated introductions in the hospital from the community. C. parapsilosis isolates comprised two groups of highly similar isolates representing strains capable of long-term persistence in the hospital. All isolates of the main persistent group were resistant to fluconazole and presented variable levels of resistance to voriconazole and itraconazole, resulting from the Y132F substitution in erg11 and the N455D substitution in upc2. Interestingly, with the exception of the single isolate susceptible to both voriconazole and itraconazole, all the 61 isolates presented one unreported missense mutation in mrr1 (S1907C).

genomics↗

bioRxiv2024

Catalytic Redundancies and Conformational Plasticity Drives Selectivity and Promiscuity in Quorum Quenching Lactonases

Several enzymes from the metallo-{beta}-lactamase-like family of lactonases (MLLs) degrade N- acyl-L-homoserine lactones (AHLs). In doing so, they play a role in a microbial communication system, quorum sensing, which contributes to pathogenicity and biofilm formation. There is currently great interest in designing quorum quenching (QQ) enzymes that can interfere with this communication and be used in a range of industrial and biomedical applications. However, tailoring these enzymes for specific targets requires a thorough understanding of their mechanisms and the physicochemical properties that determine their substrate specificities. We present here a detailed biochemical, computational, and structural study of the MLL GcL, which is highly proficient, thermostable, and has broad substrate specificity. Strikingly, we show that GcL does not only accept a broad range of substrates but is also capable of utilizing different reaction mechanisms that are differentially used in function of the substrate structure or the remodeling of the active site via mutations. Comparison of GcL to other lactonases such as AiiA and AaL demonstrates similar mechanistic promiscuity, suggesting this is a shared feature across lactonases in this enzyme family. Mechanistic promiscuity has previously been observed in the lactonase/paraoxonase PON1, as well as with protein tyrosine phosphatases that operate via a dual general-acid mechanism. The apparent prevalence of this phenomenon is significant from both a biochemical and an engineering perspective: in addition to optimizing for specific substrates, it is possible to optimize for specific mechanisms, opening new doors not just for the design of novel quorum quenching enzymes, but also of other mechanistically promiscuous enzymes.

biochemistry↗

bioRxiv2024

Diversity, functional classification and genotyping of SHV β-lactamases in Klebsiella pneumoniae

Interpreting phenotypes of blaSHV alleles in Klebsiella pneumoniae genomes is complex. While all strains are expected to carry a chromosomal copy conferring resistance to ampicillin, they may also carry mutations in chromosomal blaSHV alleles or additional plasmid-borne blaSHV alleles that have extended-spectrum {beta}-lactamase (ESBL) activity and/or {beta}-lactamase inhibitor (BLI) resistance activity. In addition, the role of individual mutations/amino acid changes is not completely documented or understood. This has led to confusion in the literature and in antimicrobial resistance (AMR) gene databases (e.g., NCBIs Reference Gene Catalog and the {beta}-lactamase database (BLDB)) over the specific functionality of individual SHV protein variants. Therefore, identification of ESBL-producing strains from K. pneumoniae genome data is complicated. Here, we reviewed the experimental evidence for the expansion of SHV enzyme function associated with specific amino-acid substitutions. We then systematically assigned SHV alleles to functional classes (wildtype, ESBL, BLI-resistant) based on the presence of these mutations. This resulted in the re-classification of 37 SHV alleles compared with current assignments in NCBIs Reference Gene Catalog and/or BLDB (21 to wildtype, 12 to ESBL, 4 to BLI-resistant). Phylogenetic and comparative genomic analyses support that; i) SHV-1 (encoded by blaSHV-1) is the ancestral chromosomal variant; ii) ESBL and BLI-resistant variants have evolved multiple times through parallel substitution mutations; iii) ESBL variants are mostly mobilised to plasmids; iv) BLI-resistant variants mostly result from mutations in chromosomal blaSHV. We used matched genome-phenotype data from the KlebNET-GSP Genotype-Phenotype Group to identify 3,999 K. pneumoniae isolates carrying one or more blaSHV alleles but no other acquired {beta}-lactamases, with which we assessed genotype-phenotype relationships for blaSHV. This collection includes human, animal, and environmental isolates collected between 2001 to 2021 from 24 countries across six continents. Our analysis supports that mutations at Ambler sites 238 and 179 confer ESBL activity, while most omega-loop substitutions do not. Our data also provide direct support for wildtype assignment of 67 protein variants, including eight that were noted in public databases as ESBL. We reclassified these eight variants as wildtype, because they lack ESBL-associated mutations, and our phenotype data support susceptibility to 3GCs (SHV-27, SHV-38, SHV-40, SHV-41, SHV-42, SHV-65, SHV-164, SHV-187). The approach and results outlined here have been implemented in Kleborate v2.4.1 (a software tool for genotyping K. pneumoniae from genome assemblies), whereby known and novel blaSHV alleles are classified based on causative mutations. Kleborate v2.4.1 was also updated to include ten novel protein variants from the KlebNET-GSP dataset and all alleles in public databases as of November 2023. This study demonstrates the power of sharing AMR phenotypes alongside genome data to improve understanding of resistance mechanisms. Impact statementSince every K. pneumoniae genome has an intrinsic SHV {beta}-lactamase and may also carry additional mobile forms, the correct interpretation of blaSHV genes detected in genome data can be challenging and can lead to K. pneumoniae being misclassified as ESBL-producing. Here, we use matched K. pneumoniae genome and drug susceptibility data contributed from dozens of studies, together with systematic literature review of experimental evidence, to improve our understanding of blaSHV allele variation and mapping of genotype to phenotype. This study shows the value of coordinated data sharing, in this case via the KlebNET-GSP Genotype-Phenotype Group, to improve our understanding of the evolutionary history and functionality of blaSHV genes. The results are captured in an open-source AMR dictionary utilised by the Kleborate genotyping tool, that could easily be incorporated into or used to update other tools and AMR gene databases. This work is part of the wider efforts of the KlebNET-GSP group to develop and support a unified platform tailored for the analysis and interpretation of K. pneumoniae genomes by a wide range of stakeholders. Data summaryBlaSHV allele sequences and class assignments are distributed with Kleborate, v2.4.1, DOI:10.5281/zenodo.10469001. Table S1 provides a summary of blaSHV alleles, including primary accessions, class-modifying mutations, and supporting evidence for class assignments that differ from NCBIs Reference Gene Catalog or BLDB. Whole genome sequence data are publicly available as reads and/or assemblies, individual accessions are given in Table S2; corresponding genotypes and antibiotic susceptibility phenotypes and measurements are available in Tables S3 and S4, respectively.

genomics↗

bioRxiv2024

The N-terminal helix of MarA as a key element in the mechanism of DNA binding

Efflux is one of the mechanisms employed by Gram-negative bacteria to become resistant to routinely used antibiotics. The inhibition of efflux by targeting their regulators is a promising strategy to re-sensitise bacterial pathogens to antibiotics. AcrAB-TolC is the main Resistance-Nodulation-Division efflux pump in Enterobacteriaceae. MarA is an AraC/XylS family global regulator that regulates more than 40 genes related to the antimicrobial resistance phenotype, including acrAB. The aim of this work was to understand the role of the N-terminal helix of MarA in the mechanism of DNA binding. An N-terminal deletion of MarA showed that the N-terminal helix has a role in the recognition of the functional marboxes. By engineering two double cysteine variants of MarA, and combining in vitro electrophoretic mobility assays and in vivo measurements of acrAB transcription with molecular dynamic simulations, it was shown that the immobilization of the N-terminal helix of MarA prevents binding to DNA. This new mechanism of inhibition seems to be universal for the monomeric members of the AraC/XylS family, as suggested by additional molecular dynamics simulations of the two-domain protein Rob. These results point to the N-terminal helix of the AraC/XylS family monomeric regulators as a promising target for the development of inhibitors.

molecular biology↗

bioRxiv2024

Convergence and global epidemiology of Klebsiella pneumoniae plasmids harbouring the iuc3 virulence locus.

BackgroundKlebsiella pneumoniae (Kp) is an important pathogen of humans and animals, and recent reports of convergent strains that carry both virulence and antimicrobial resistance genes (ARGs) have raised serious public health concern. The plasmid-borne iuc locus, encoding the siderophore aerobactin, is a key virulence factor in this species. The variant iuc3 is associated with porcine and human clinical isolates and is carried by mostly uncharacterised IncF plasmids. MethodsWe used a combination of short-read and long-read sequencing to characterise IncFIB(K)/IncFII iuc3-carrying plasmids harboured by 79 Kp isolates and one K. oxytoca isolate recovered as part of two large One-Health studies in Italy (SpARK) and Thailand (OH-DART). Adding data from public repositories gave a combined dataset of 517 iuc3 isolates, and the plasmids were analysed using both clustering and phylogenetic methods. FindingsWe note seven large, convergent, plasmids from Thailand that have emerged through the hybridisation of co-circulating plasmids harbouring iuc3 and antimicrobial resistance genes (ARGs) encoding extended-spectrum beta-lactamases (ESBLs). We were also able to identify putative parental plasmids which were mostly associated with two neighbouring meat markets, as were the hybrid plasmids. Clustering and global phylogenetic analyses resolved an iuc3 plasmid sub-group circulating throughout Asia, with occasional examples in Europe and elsewhere. This variant carries multiple ARGs and is commonly harboured by clinical isolates, thus warranting targeted plasmid surveillance. InterpretationOur study reveals that plasmid hybridisation leading to the convergence of resistance and virulence traits may be very common, even in non-clinical ( One-Health) settings. Population-scale plasmid genomics makes it possible to identify putative parental plasmids, which will help to identify plasmid types that are most likely to hybridise, and what the selective consequences may be for the plasmid and host. A distinct iuc3 plasmid sub-variant is associated with clinical isolates in Asia which requires close monitoring. Research In ContextMultiple reports of convergent clones of Klebsiella pneumoniae that combine both hypervirulence and multidrug resistance (MDR-hvKp) have been published recently; a PubMed search in November 2023 using the key words convergence Klebsiella pneumoniae returned 143 papers, 99 of which were published from 2020 onwards. Our study demonstrates that the hybridisation of plasmids carrying AMR and virulence genes is a frequent, ongoing, process in natural populations. The subsequent transfer of plasmids conferring both traits is thus likely to be a key driver behind the spread of convergent strains. Our study also provides an exemplar of how hybrid assemblies can facilitate large-scale global genomic plasmid epidemiology. Evidence before the studyAlthough multiple recent reports highlight the emergence and spread of convergent Kp strains, the confluence of resistance and virulence genes within the same plasmid has not been studied at a population level, and putative parental plasmids are rarely identified. Moreover, there have been few high-resolution genomic epidemiology studies on closely related plasmids using both long and short-read data on a global scale. Added valueWe more than double the number of complete sequences available for plasmids harbouring iuc3 from 58 to 139 and provide evidence on the host lineages most likely to harbour these plasmids (e.g., ST35), and epidemiological source (e.g., pig, wild animal, human). Our comparative analysis of phylogenetic and clustering approaches will help to inform future plasmid epidemiological studies. ImplicationsThe hybridisation of plasmids harbouring virulence and resistance genes occurs frequently in natural populations, even within One-Health settings. However, the selective drivers (if any) and evolutionary consequences of this phenomenon are unclear. There is clear utility in generating closed plasmid genomes on a population scale, and targeted plasmid surveillance on a clinical sub-variant of iuc3 plasmids is warranted.

genomics↗

bioRxiv2023

Optimising machine learning prediction of minimum inhibitory concentrations in Klebsiella pneumoniae

Minimum Inhibitory Concentrations (MICs) are the gold standard for quantitatively measuring antibiotic resistance. However, lab-based MIC determination can be time-consuming and suffers from low reproducibility, and interpretation as sensitive or resistant relies on guidelines which change over time. Genome sequencing and machine learning promise to allow in-silico MIC prediction as an alternative approach which overcomes some of these difficulties, albeit the interpretation of MIC is still needed. Nevertheless, precisely how we should handle MIC data when dealing with predictive models remains unclear, since they are measured semi-quantitatively, with varying resolution, and are typically also left- and right-censored within varying ranges. We therefore investigated genome-based prediction of MICs in the pathogen Klebsiella pneumoniae using 4367 genomes with both simulated semi-quantitative traits and real MICs. As we were focused on clinical interpretation, we used interpretable rather than black-box machine learning models, namely, Elastic Net, Random Forests, and linear mixed models. Simulated traits were generated accounting for oligogenic, polygenic, and homoplastic genetic effects with different levels of heritability. Then we assessed how model prediction accuracy was affected when MICs were framed as regression and classification. Our results showed that treating the MICs differently depending on the number of concentration levels of antibiotic available was the most promising learning strategy. Specifically, to optimise both prediction accuracy and inference of the correct causal variants, we recommend considering the MICs as continuous and framing the learning problem as a regression when the number of observed antibiotic concentration levels is large, whereas with a smaller number of concentration levels they should be treated as a categorical variable and the learning problem should be framed as a classification. Our findings also underline how predictive models can be improved when prior biological knowledge is taken into account, due to the varying genetic architecture of each antibiotic resistance trait. Finally, we emphasise that incrementing the population database is pivotal for the future clinical implementation of these models to support routine machine-learning based diagnostics. Data SummaryThe scripts used to run and fit the models can be found at https://github.com/gbatbiff/Kpneu_MIC_prediction. The Illumina sequences from Thorpe et al. are available from the European Nucleotide Archive under accession PRJEB27342. All the other genomes are available on https://www.bv-brc.org/ database. Impact statementKlebsiella pneumoniae is a leading cause of hospital and community acquired infections worldwide, highly contributing to the global burden of antimicrobial resistance (AMR). Ordinary methods to assess antibiotic resistance are not always satisfactory, and may not be effective in terms of costs and delays, so robust methods able to accurately predict AMR are increasingly needed. Genome-based prediction of minimum inhibitory concentrations (MICs) through machine learning methods is a promising tool to assist clinical diagnosis, also offsetting phenotypic MIC discordance between the different culture-based assays. However, benchmarking predictive models against phenotypic data is problematic due to inconsistencies in the way these data are generated and how they should be handled remains unclear. In this work, we focused on genome-based prediction of MIC and evaluated the performance of interpretable machine learning models across different genetic architectures and data encodings. Our workflow highlighted how MICs need to be treated as different types of data depending on the method used to measure them, in particular considering each antibiotic separately. Our findings shed further light on the factors affecting model performance, paving the way to future improvements of antibiotic resistance prediction.

bioinformatics↗

bioRxiv2023

On the forces shaping diversity and adaptation in the opportunistic pathogen Serratia marcescens

Bacterial species often comprise well-separated lineages, likely emerged and maintained by genetic isolation and/or ecological divergence. How these two evolutionary actors interact in the shaping of bacterial population structure is currently not fully understood. In this study, we investigated the genetic and ecological drivers underlying the evolution of Serratia marcescens, an opportunistic pathogen with high genomic flexibility and able to colonise diverse environments. Comparative genomic analyses revealed a population structure composed of five deeply-demarcated genetic clusters with open pan-genome but limited inter-cluster gene flow, partially explained by Restriction-Modification (R-M) systems incompatibility. Furthermore, a large-scale research on hundred-thousands metagenomic datasets revealed only a partial ecological separation of the clusters. Globally, two clusters only showed a peculiar gene composition and evident ecological adaptations. These results suggest that genetic isolation preceded ecological adaptations in the shaping of the species diversity, suggesting an evolutionary scenario for several bacterial species.

evolutionary biology↗

bioRxiv2021

One Health or Three? Transmission modelling of Klebsiella isolates reveals ecological barriers to transmission between humans, animals and the environment

The Klebsiella group is highly diverse both genetically and ecologically, being commonly recovered from humans, livestock, plants, soil, water, and wild animals. Many species are opportunistic pathogens, and can harbour diverse classes of antimicrobial resistance (AMR) genes. K. pneumoniae is responsible for a high public-health burden, due in part to the rapid spread of health-care associated clones that are non-susceptible to carbapenems. Klebsiella thus represents a highly pertinent taxon for assessing the risk to public health posed by animal and environmental reservoirs. Here we report an analysis of 6548 samples and 3,482 genome sequences representing 15 Klebsiella species sampled over a 15-month period from a wide range of clinical, community, animal and environmental settings in and around the city of Pavia, in the northern Italian region of Lombardy. Despite carbapenem-resistant clones circulating at a high frequency in the hospitals, we find no genotypic or phenotypic evidence for non-susceptibility to carbapenems outside of the clinical environment. The non-random distribution of species and strains across sources point to ecological barriers that are likely to limit AMR transmission. Although we find evidence for occasional transmission between settings, hierarchical modelling and intervention analysis suggests that direct transmission from the multiple non-human (animal and environmental) sources included in our sample accounts for less than 1% of hospital disease, with the vast majority of clinical cases originating from other humans.

microbiology↗

bioRxiv2021

Hypervariable-Locus Melting Typing (HLMT): a novel, fast and inexpensive sequencing-free approach to pathogen typing based on High Resolution Melting (HRM) analysis

ObjectivesSubspecies pathogen typing is a pivotal tool to detect the emergence of high-risk clones in hospital settings and to limit their spreading among patients. Unfortunately, the most used subspecies typing methods (i.e. Pulsed-field Gel Electrophoresis - PFGE, Multi-Locus Sequence Typing - MLST and Whole Genome Sequencing - WGS) are too expensive and time consuming to be suitable for real-time surveillance. Here we present Hypervariable-Locus Melting Typing (HLMT), a novel subspecies typing approach based on High Resolution Melting (HRM) analysis, which allows pathogen typing in a few hours and with [~]5 euros per sample. MethodsHLMT types the strains by clustering them using melting temperatures (HLMT-clustering) and/or by assigning them to Melting Types (MTs) on the basis of a reference dataset (HLMT-assignment). We applied HLMT (clustering and typing) to 134 Klebsiella pneumoniae strains collected during outbreaks or surveillance programs in four hospitals. Then, we compared HLMT typing results to PFGE, MLST and WGS. ResultsHLMT-clustering distinguishes most of the K. pneumoniae high-risk clones with a sensitivity comparable to PFGE and MLST. It also drawed surveillance epidemiological curves comparable to those obtained by MLST, PFGE and WGS typing. Furthermore, the results obtained by HLMT-assignment were coherent to MLST for 96% of the typed strains with a Jaccard index of 0.912. ConclusionsHLMT is a fast and scalable method for pathogen typing, suitable for real-time hospital microbiological surveillance. HLMT is also inexpensive and thus it is applicable to infection control programs in low-middle income countries.

microbiology↗

bioRxiv2019

Description of Klebsiella spallanzanii sp. nov. and of Klebsiella pasteurii sp. nov.

Klebsiella oxytoca causes opportunistic human infections and post-antibiotic haemorrhagic diarrhoea. This Enterobacteriaceae species is genetically heterogeneous and is currently subdivided into seven phylogroups (Ko1 to Ko4, Ko6 to Ko8). Here we investigated the taxonomic status of phylogroups Ko3 and Ko4. Genomic sequence-based phylogenetic analyses demonstrate that Ko3 and Ko4 formed well-defined sequence clusters related to, but distinct from, Klebsiella michiganensis (Ko1), Klebsiella oxytoca (Ko2), K. huaxiensis (Ko8) and K. grimontii (Ko6). The average nucleotide identity of Ko3 and Ko4 were 90.7% with K. huaxiensis and 95.5% with K. grimontii, respectively. In addition, three strains of K. huaxiensis, a species so far described based on a single strain from a urinary tract infection patient in China, were isolated from cattle and human faeces. Biochemical and MALDI-ToF mass spectrometry analysis allowed differentiating Ko3, Ko4 and Ko8 from the other K. oxytoca species. Based on these results, we propose the names Klebsiella spallanzanii for the Ko3 phylogroup, with SPARK_775_C1T (CIP 111695T, DSM 109531T) as type strain, and Klebsiella pasteurii for Ko4, with SPARK_836_C1T (CIP 111696T, DSM 109530T) as type strain. Strains of K. spallanzanii were isolated from human urine, cow faeces and farm surfaces, while strains of K. pasteurii were found in faecal carriage from humans, cows and turtles.\n\nAccession numbersThe nucleotide sequences generated in this study were deposited in ENA and are available through the INSDC databases under accession numbers MN091365 (SB6411T = SPARK775C1T), MN091366 (SB6412 T = SPARK836C1T) and MN104661 to MN104677 (16S rRNA), MN076606 to MN076643 (gyrA and rpoB), and MN030558 to MN030567 (blaOXY). Complete genomic sequences were submitted to European Nucleotide Archive under the BioProject number PRJEB15325.\n\nAbbreviationsANI, average nucleotide identity; HCCA, a-cyano-4-hydroxycinnamic acid; isDDH, in silico DNA-DNA hybridization; SCAI, Simmons citrate agar with inositol; MALDI57 ToF MS: Matrix-assisted laser desorption/ionization time of flight mass spectrometry

microbiology↗

bioRxiv2019

Fast Klebsiella pneumoniae typing for outbreak reconstruction: an highly discriminatory HRM protocol on wzi capsular gene developed using EasyPrimer tool

In this work we present EasyPrimer, a user-friendly online tool developed to assist pan-PCR and High Resolution Melting (HRM) primer design. The tool finds the most suitable regions for primer design in a gene alignment and returns a clear graphical representation of their positions on the gene. EasyPrimer is particularly useful in difficult contexts, e.g. on gene alignments of hundreds of sequences and/or on highly variable genes. HRM analysis is an emerging method for fast and cost saving bacterial typing and an HRM scheme of six primer sets on five Multi-Locus Sequence Type (MLST) genes is already available for Klebsiella pneumoniae. We validated the tool designing a scheme of two HRM primer sets on the hypervariable gene wzi of Klebsiella pneumoniae and compared the two schemes. The wzi scheme resulted to have a discriminatory power comparable to the HRM MLST scheme, using only one third of primer sets. Then we successfully used the wzi HRM primer scheme to reconstruct a Klebsiella pneumoniae nosocomial outbreak in few hours. The use of hypervariable genes reduces the number of HRM primer sets required for bacterial typing allowing to perform cost saving, large-scale surveillance programs.

epidemiology↗