Biology subjects

Esposito, F.

Publications and source records attributed to Esposito, F..

3 recordsLinked to original sources

bioRxiv2018

Yersiniabactin, Colibactin and Wider Resistome Contribute to Enhanced Virulence and Persistence of KPC-2-Producing Klebsiella pneumoniae CG258 in South America

The emergence and dissemination of carbapenem-resistant hypervirulent Klebsiella pneumoniae (CR-hvKp) is a worrisome public health issue compromising the treatment and outcome of infections caused by this pathogen. We performed a detailed virulome and resistome analysis of representative KPC- and/or CTX-M-producing K. pneumoniae belonging to clonal group (CG) 258 (sequence types ST11, ST258, ST340, ST437), circulating in Argentina, Brazil, Chile, Colombia and Peru; with further evaluation of the virulence behavior using the Galleria mellonella infection model. Genomic analysis of K. pneumoniae strains recovered from the human-animal-environment interface revealed a wide resistome characterized by the presence of genes and mutations conferring resistance to human and veterinary antibiotics, quaternary ammonium compounds (QACs) and heavy metals. Plasmid Inc typing revealed the presence of a wide diversity of replicon types with IncF, IncN, IncR and Col-like being frequently detected. Moreover, KPC-2-producing K. pneumoniae belonging to ST11 (KL-64 andKL-105) and ST340 (KL-15) carried multiple variants of distinct yersiniabactin siderophore (ybt) and/or genotoxic colibactin (clb) genes. In this regard, ICEKp3, ICEKp4 and ICEKp12 were identified in strains belonging to ST11 and ST340, recovered from Argentina, Brazil, Chile and Colombia; whereas ybt 17 and a novel ybt sequence type (YbST346) were identified together with clb in ICEKp10 structures from ST11 and ST258, from Brazil and Colombia, respectively. K. pneumoniae ST11 (ICEKp10/YbST346 and ICEKp4/ybt 10) strains killed 100% of wax moth larvae, in a similar way to hypervirulent K1/ST23 strain (ybt- and clb-negative) carrying the pLVPK-like plasmid, indicating enhanced virulence. In summary, our results indicate that yersiniabactin, colibactin and an expanded resistome have contributed to enhanced virulence and persistence of KPC-2-producing K. pneumoniae CG258 in South America. Therefore, active surveillance of hospital-associated lineages of K. pneumoniae should not only focus on clonal origin and antimicrobial resistance, but also on the virulence factors ybt and clb.

microbiology↗

bioRxiv2018

Stochastic rank aggregation for the identification of functional neuromarkers

Background and aimsThe main challenge in analysing functional magnetic resonance imaging (fMRI) data from extended samples of subject (N>100) is to extract as much relevant information as possible from big amounts of noisy data. When studying neurodegenerative diseases with resting-state fMRI, one of the objectives is to determine regions with abnormal background activity with respect to a healthy brain and this is often attained with comparative statistical models applied to single voxels or brain parcels within one or several functional networks. In this work, we propose a novel approach based on clustering and stochastic rank aggregation to identify parcels that exhibit a coherent behaviour in groups of subjects affected by the same disorder and apply it to default-mode network independent component maps from resting-state fMRI data sets.\n\nMethodsBrain voxels are partitioned into parcels through k-means clustering, then solutions are enhanced by means of consensus techniques. For each subject, clusters are ranked according to their median value and a stochastic rank aggregation method, TopKLists, is applied to combine the individual rankings within each class of subjects. For comparison, the same approach was tested on an anatomical parcellation.\n\nResultsWe found parcels for which the rankings were different among control subjects and subjects affected by Parkinsons disease and amyotrophic lateral sclerosis and found evidence in literature for the relevance of top ranked regions in default-mode brain activity.\n\nConclusionsThe proposed framework represents a valid method for the identification of functional neuromarkers from resting-state fMRI data, and it might therefore constitute a step forward in the development of fully automated data-driven techniques to support early diagnoses of neurodegenerative diseases.

neuroscience↗

bioRxiv2018

Small effect size leads to reproducibility failure in resting-state fMRI studies

Thousands of papers using resting-state functional magnetic resonance imaging (RS-fMRI) have been published on brain disorders. Results in each paper may have survived correction for multiple comparison. However, since there have been no robust results from large scale meta-analysis, we do not know how many of published results are truly positives. The present meta-analytic work included 60 original studies, with 57 studies (4 datasets, 2266 participants) that used a between-group design and 3 studies (1 dataset, 107 participants) that employed a within-group design. To evaluate the effect size of brain disorders, a very large neuroimaging dataset ranging from neurological to psychiatric isorders together with healthy individuals have been analyzed. Parkinsons disease off levodopa (PD-off) included 687 participants from 15 studies. PD on levodopa (PD-on) included 261 participants from 9 studies. Autism spectrum disorder (ASD) included 958 participants from 27 studies. The meta-analyses of a metric named amplitude of low frequency fluctuation (ALFF) showed that the effect size (Hedges g) was 0.19 - 0.39 for the 4 datasets using between-group design and 0.46 for the dataset using within-group design. The effect size of PD-off, PD-on and ASD were 0.23, 0.39, and 0.19, respectively. Using the meta-analysis results as the robust results, the between-group design results of each study showed high false negative rates (median 99%), high false discovery rates (median 86%), and low accuracy (median 1%), regardless of whether stringent or liberal multiple comparison correction was used. The findings were similar for 4 RS-fMRI metrics including ALFF, regional homogeneity, and degree centrality, as well as for another widely used RS-fMRI metric namely seed-based functional connectivity. These observations suggest that multiple comparison correction does not control for false discoveries across multiple studies when the effect sizes are relatively small. Meta-analysis on un-thresholded t-maps is critical for the recovery of ground truth. We recommend that to achieve high reproducibility through meta-analysis, the neuroimaging research field should share raw data or, at minimum, provide un-thresholded statistical images.

neuroscience↗