Biology subjects

Xavier, B. B.

Publications and source records attributed to Xavier, B. B..

4 recordsLinked to original sources

bioRxiv2024

Enhancing antimicrobial resistance monitoring: Core Plasmid Multi-Locus sequence typing (cpMLST) with Oxford Nanopore sequencing technology (ONT)

BackgroundThe spread of antimicrobial resistance (AMR) poses a significant threat to global public health, primarily driven by the horizontal gene transfer of resistance genes via plasmids. Understanding the dynamics of plasmid transmission within (intra) and between (inter) bacterial species is crucial for developing effective countermeasures. In this study, we utilize long-read sequencing technology to develop an innovative approach called core plasmid Multi-Locus Sequence Typing (cpMLST) and track the global plasmid transmission pathways. MethodsWe collected wastewater samples from six different hospitals in Germany. Within 24 hours of collection, we isolated extensively drug-resistant (XDR) bacteria using CHROMagar plates (CHROMagar, Paris, France). Species identification was done using MALDI-TOF MS (Bruker Daltonics, Bremen, Germany). Genomic DNA from the isolates was extracted using the PureLink Genomic DNA Mini Kit (Invitrogen, Carlsbad, USA) and subsequently sequenced using Oxford Nanopore Technologies (ONT) sequencing (Oxford Nanopore Technologies). We employed the SQK-RBK114.24 kit on an R10.4.1 flow cell, achieving a minimum of 250 Mb of raw data for each isolate with an accuracy of 98.9%. The reads were assembled using Unicycler, and the quality of the assemblies was assessed using QUAST and Bandage. The assembled genomes were then uploaded to the Center for Genomic Epidemiology (CGE) https://www.genomicepidemiology.org/ platform to determine incompatibility (Inc) types and antimicrobial resistance (AMR) genes. Additionally, we performed core plasmid analysis using chewBBACA v.3.3.10 to assess plasmid relatedness. ResultsThe analysis confirmed the identification of various bacterial isolates. Among the most prevalent XDR isolate were Enterobacter roggenkampii (n=38), Serratia marcescens (n=12), Klebseilla oxytoca (n=11), Klebseilla michiganensis (n=8), and Citrobacter freundii (n=7). We conducted a cpMLST analysis to examine the highly prevalent plasmids and reveal evolutionary relationships and transmission patterns. Each isolate harbored different types of complete plasmids. Among those were the IncFII (n=45), IncHI (n=26), IncX3 (n=21), and other incompatibility groups. By focusing on shared Inc types among the bacterial species, their transfer within a single bacterial species (intra-species transfer) and between different species (inter-species transfer) were identified. The allelic differences ranged from 3-55 (IncHI), 2-32 (IncFII) and 2-24 (IncX3). Moreover, these plasmids, typically identified as smaller plasmids (IncX3), were larger than their commonly reported sizes. The analysis of plasmid dynamics across diverse bacterial hosts provides valuable insight into the mechanisms driving the spread of antimicrobial resistance, offering potential strategies for better controlling the dissemination of antimicrobial resistance and its transmission in clinical environments. ConclusionIn conclusion, long-read sequencing technologies emerge as an essential tool for investigating the transmission dynamics of antimicrobial resistance genes among plasmids. By implementing cp-MLST, we anticipate achieving an unparalleled understanding of the global dissemination and evolutionary patterns of resistance-carrying plasmids. This approach offers superior resolution to conventional plasmid typing methods, potentially opening new avenues for innovative strategies to combat the escalating AMR crisis.

microbiology↗

bioRxiv2020

Molecular pathways to high-level azithromycin resistance in Neisseria gonorrhoeae

ObjectivesThe prevalence of azithromycin resistance in Neisseria gonorrhoeae is increasing in numerous populations worldwide. The aim of this study was to characterize the genetic pathways leading to high-level azithromycin resistance. MethodsA customized morbidostat was used to subject two N. gonorrhoeae reference strains (WHO-F and WHO-X) to dynamically sustained azithromycin pressure. We tracked stepwise evolution of resistance by whole genome sequencing. ResultsWithin 26 days, all cultures evolved high-level azithromycin resistance. Typically, the first step towards resistance was found in transitory mutations in genes rplD, rplV and rpmH (encoding the ribosomal proteins L4, L22 and L34 respectively), followed by mutations in the MtrCDE-encoded efflux pump and the 23S rRNA gene. Low-to high-level resistance was associated with mutations in the ribosomal proteins and MtrCDE-encoded efflux pump. However, high-level resistance was consistently associated with mutations in the 23S ribosomal RNA - mainly the well-known A2059G and C2611T mutations, but also at position A2058G. ConclusionsThis study enabled us to track previously reported mutations and identify novel mutations in ribosomal proteins (L4, L22 and L34) that may play a role in the genesis of azithromycin resistance in N. gonorrhoeae.

microbiology↗

bioRxiv2019

Comparison of biofilm dispersal approaches in Pseudomonas aeruginosa and evaluation of dispersed cells in acute infection mouse model

Biofilm dispersal is biologically significant process to fully understand its consequences during biofilm based infections. The mechanism for biofilm dispersal may involve response to environmental cues and changes in intracellular secondary messengers. Considering range of cues for biofilm dispersal, it is significant to study if dispersed cells generated by different methods have similar phenotype. In the present study, we have compared four type of biofilm dispersal in P. aeruginosa based in response to environment cues (starvation and nutrient rich), c-di-GMP knockdown and signaling molecule NO. We have determined their dispersal efficiency, susceptibility of dispersed cells for antibiotics, their transcriptomic changes compared to planktonic and biofilm. We also determined if dispersed cells can cause acute infections in mouse models. In vitro experiments showed that NO and c-di-GMP based dispersal methods had high biofilm reduction efficiency of 50 and 75% respectively, however, the nutrient induced dispersion showed low efficiency ({approx}30%) and more tolerance to colistin. We also showed that in vitro dispersed cells induced >10-fold transcriptomic expression of genes (at significance level of p < 0.005) related to efflux pumps (mexCD-oprJ), antibiotic resistance (arnDET) in dispersed cells induced by NO and nutrient change, while denitrification pathway and virulence (T3SS, VreI, T2SS) genes in all dispersed cells compared to planktonic and biofilm state. When the ability of the dispersed cells was tested in mouse model of lung infection, c-di-GMP and NO based dispersed cells displayed enhanced infections and haematogenous spread to liver and spleen and higher mortality. Although degree of immune response (cytokines) does not differ based on phenotypes inoculated in our experimental conditions. Based on our data most efficient dispersal methods increase murine mortality. This indicates their capability of making biofilm associated infection more complicated. Our data encourage to be more careful for studies suggesting biofilm dispersal during treatment of biofilm infections.

microbiology↗

bioRxiv2019

The COMPARE Data Hubs

Data sharing enables research communities to exchange findings and build upon the knowledge that arises from their discoveries. Areas of public and animal health as well as food safety would benefit from rapid data sharing when it comes to emergencies. However, ethical, regulatory, and institutional challenges, as well as lack of suitable platforms which provide an infrastructure for data sharing in structured formats often lead to data not being shared, or at most shared in form of supplementary materials in journal publications. Here, we describe an informatics platform that includes workflows for structured data storage, managing and pre-publication sharing of pathogen sequencing data and its analysis interpretations with relevant stakeholders.

bioinformatics↗