Multilocus microsatellite analysis of European and African Candida glabrata isolates

This study aimed to elucidate the genetic relatedness and epidemiology of 127 clinical and environmental Candida glabrata isolates from Europe and Africa using multilocus microsatellite analysis. Each isolate was first identified using phenotypic and molecular methods and subsequently, six unlinked microsatellite loci were analyzed using automated fluorescent genotyping. Genetic relationships were estimated using the minimum-spanning tree (MStree) method. Microsatellite analyses revealed the existence of 47 different genotypes. The fungal population showed an irregular distribution owing to the over-representation of genetically different infectious haplotypes. The most common genotype was MG-9, which was frequently found in both European and African isolates. In conclusion, the data reported here emphasize the role of specific C. glabrata genotypes in human infections for at least some decades and highlight the widespread distribution of some isolates, which seem to be more able to cause disease than others.This research was supported in part by the EU Mare Nostrum (EUMN-III Call) program of the European Union, grant agreement number 2011-4050/001-EMA2. Dr Sanae Rharmitt was the recipient of a scholarship (10 months) signed within the EUMN program for PhD students (F.S. 1.04.11.01 UORI) under the supervision of Prof Orazio Romeo.info:eu-repo/semantics/publishedVersio

Massive NGS Data Analysis Reveals Hundreds Of Potential Novel Gene Fusions in Human Cell Lines

Background: gene fusions derive from chromosomal rearrangements. The resulting chimeric transcripts are often endowed with oncogenic potential. Furthermore, they serve as diagnostic tools for the clinical classification of cancer subgroups with different prognosis and, in some cases, they can provide specific drug targets. To date, many efforts have been carried out to study gene fusion events occurring in tumor samples. In recent years, the availability of a comprehensive next-generation sequencing dataset for all existing human tumor cell lines has provided the opportunity to further investigate these data in order to identify novel and still uncharacterized gene fusion events. Results: In our work, we have extensively reanalyzed 935 paired-end RNA-sequencing experiments downloaded from the Cancer Cell Line Encyclopedia repository, aiming at addressing novel putative cell-line specific gene fusion events in human malignancies. The bioinformatics analysis has been performed by the execution of four gene fusion detection algorithms. The results have been further prioritized by running a Bayesian classifier that makes an in silico validation. The collection of fusion events supported by all of the predictive software results in a robust set of ∼1,700 in silico predicted novel candidates suitable for downstream analyses. Given the huge amount of data and information produced, computational results have been systematized in a database named LiGeA. The database can be browsed through a dynamic and interactive web portal, further integrated with validated data from other well-known repositories. Taking advantage of the intuitive query forms, the users can easily access, navigate, filter, and select the putative gene fusions for further validations and studies. They can also find suitable experimental models for a given fusion of interest. Conclusions: We believe that the LiGeA resource can represent not only the first compendium of both known and putative novel gene fusion events in the catalog of all of the human malignant cell lines but it can also become a handy starting point for wet-lab biologists who wish to investigate novel cancer biomarkers and specific drug targets

HPC-REDItools: a novel HPC-aware tool for improved large scale RNA-editing analysis

Background RNA editing is a widespread co-/post-transcriptional mechanism that alters primary RNA sequences through the modification of specific nucleotides and it can increase both the transcriptome and proteome diversity. The automatic detection of RNA-editing from RNA-seq data is computational intensive and limited to small data sets, thus preventing a reliable genome-wide characterisation of such process. Results In this work we introduce HPC-REDItools, an upgraded tool for accurate RNA-editing events discovery from large dataset repositories. Availability: https://github.com/BioinfoUNIBA/REDItools2. Conclusions HPC-REDItools is dramatically faster than the previous version, REDItools, enabling big-data analysis by means of a MPI-based implementation and scaling almost linearly with the number of available cores

HPC-REDItools: A novel HPC-aware tool for improved large scale RNA-editing analysis

Background: RNA editing is a widespread co-/post-transcriptional mechanism that alters primary RNA sequences through the modification of specific nucleotides and it can increase both the transcriptome and proteome diversity. The automatic detection of RNA-editing from RNA-seq data is computational intensive and limited to small data sets, thus preventing a reliable genome-wide characterisation of such process. Results: In this work we introduce HPC-REDItools, an upgraded tool for accurate RNA-editing events discovery from large dataset repositories. Availability: https://github.com/BioinfoUNIBA/REDItools2. Conclusions: HPC-REDItools is dramatically faster than the previous version, REDItools, enabling big-data analysis by means of a MPI-based implementation and scaling almost linearly with the number of available cores

ELIXIR-IT HPC@CINECA: high performance computing resources for the bioinformatics community

Background: The advent of Next Generation Sequencing (NGS) technologies and the concomitant reduction in sequencing costs allows unprecedented high throughput profiling of biological systems in a cost-efficient manner. Modern biological experiments are increasingly becoming both data and computationally intensive and the wealth of publicly available biological data is introducing bioinformatics into the “Big Data” era. For these reasons, the effective application of High Performance Computing (HPC) architectures is becoming progressively more recognized also by bioinformaticians. Here we describe HPC resources provisioning pilot programs dedicated to bioinformaticians, run by the Italian Node of ELIXIR (ELIXIR-IT) in collaboration with CINECA, the main Italian supercomputing center. Results: Starting from April 2016, CINECA and ELIXIR-IT launched the pilot Call “ELIXIR-IT HPC@CINECA”, offering streamlined access to HPC resources for bioinformatics. Resources are made available either through web front-ends to dedicated workflows developed at CINECA or by providing direct access to the High Performance Computing systems through a standard command-line interface tailored for bioinformatics data analysis. This allows to offer to the biomedical research community a production scale environment, continuously updated with the latest available versions of publicly available reference datasets and bioinformatic tools. Currently, 63 research projects have gained access to the HPC@CINECA program, for a total handout of ~ 8 Millions of CPU/hours and, for data storage, ~ 100 TB of permanent and ~ 300 TB of temporary space. Conclusions: Three years after the beginning of the ELIXIR-IT HPC@CINECA program, we can appreciate its impact over the Italian bioinformatics community and draw some considerations. Several Italian researchers who applied to the program have gained access to one of the top-ranking public scientific supercomputing facilities in Europe. Those investigators had the opportunity to sensibly reduce computational turnaround times in their research projects and to process massive amounts of data, pursuing research approaches that would have been otherwise difficult or impossible to undertake. Moreover, by taking advantage of the wealth of documentation and training material provided by CINECA, participants had the opportunity to improve their skills in the usage of HPC systems and be better positioned to apply to similar EU programs of greater scale, such as PRACE. To illustrate the effective usage and impact of the resources awarded by the program - in different research applications - we report five successful use cases, which have already published their findings in peer-reviewed journals

Cerebrospinal Fluid and Peripheral Blood Lymphomonocyte Single-Cell Transcriptomics in a Subject with Multiple Sclerosis Acutely Infected with HIV

Signatures of neurodegeneration in clinical samples from a subject with multiple sclerosis (MS) acutely infected with HIV were investigated with single-cell transcriptomics using 10X Chromium technology. Sequencing was carried out on NovaSeq-TM, and the analysis was performed with Cell Ranger software (v 7.1.0) associated with a specifically established bioinformatic pipeline. A total of 1446 single-cell transcriptomes in cerebrospinal fluid (CSF) and 4647 in peripheral blood mononuclear cells (PBMCs) were obtained. In the CSF, many T-cell lymphocytes with an enriched amount of plasma cells and plasmacytoid dendritic (pDC) cells, as compared to the PBMCs, were detected. An unsupervised cluster analysis, putting together our patient transcriptomes with those of a publicly available MS scRNA-seq dataset, showed up-regulated microglial neurodegenerative gene expression in four clusters, two of which included our subject's transcriptomes. A few HIV-1 transcripts were found only in the CD4 central memory T-cells of the CSF compartment, mapping to the gag-pol, vpu, and env regions. Our data, which describe the signs of neurodegenerative gene expression in a very peculiar clinical situation, did not distinguish the cause between multiple sclerosis and HIV infection, but they can give a glimpse of the high degree of resolution that may be obtained by the single-cell transcriptomic approach

Genetic and structural characterization of dengue virus involved in the 2023 autochthonous outbreaks in central Italy

Dengue virus (DENV) has been expanding its range to temperate areas that are not usually affected, where the spread of vectors has been facilitated by global trade and climate change. In Europe, there have been many cases of DENV imported from other regions in the past few years, leading to local outbreaks of DENV among people without travel history. Here we describe the epidemiological and molecular investigations of three transmission events locally acquired DENV infections caused by serotypes 1, 2 and 3, respectively, in the Latium Region from August to November 2023. Next-generation or Sanger sequencing was used to obtain the whole genomes, or the complete E-gene of the viruses, respectively. The structure of the DENV-1 and DENV-3 sequences was analysed to identify amino acid changes that were not found in the closest related sequences. The major cluster was supported by DENV-1 (originated in South America), with 42 autochthonous infections almost occurring in the eastern area of Rome, probably due to a single introduction followed by local sustained transmission. Seven DENV-1 subclusters have been identified by mutational and phylogenetic analysis. Structural analysis indicated changes whose meaning can be explained by the adaptation of the virus to human hosts and vectors and their interactions with antibodies and cell receptors

One-Year Monitoring of the Evolution of SARS-CoV-2 Omicron Subvariants Through Wastewater Analysis (Central Italy, August 2023–July 2024)

Wastewater surveillance has proven to be a cost-effective, non-invasive method for monitoring the spread and evolution of SARS-CoV-2, yet its value during today’s low-incidence phase is still being defined. Between August 2023 and July 2024, 42 composite wastewater samples were collected in Perugia, Italy and analyzed using RT-qPCR and whole-genome sequencing to identify circulating SARS-CoV-2 lineages. In parallel, clinical samples (respiratory tract samples) were collected and analyzed, allowing for direct comparisons to confirm the robustness of the wastewater findings. The sewage viral loads ranged from 8.9 × 105 to 4.9 × 107 genome copies inhabitant−1 day−1, outlining two modest community waves (September–December 2023 and May–July 2024). Sequencing resolved 403 Omicron lineages and revealed three successive subvariant phases: (i) XBB.* dominance (August–October 2023), when late-Omicron XBB subvariants (mainly EG.5.* and XBB.1.5) accounted for almost all genomes; (ii) a BA.2.86/JN surge (November 2023–March 2024), during which the BA.2.86 subvariant, driven mainly by its JN descendants (especially JN.1), rapidly displaced XBB.* and peaked at 89% in February 2024; and (iii) KP.* takeover (April–July 2024), with JN.1-derived KP subvariants rising steadily and KP.3 reaching 81% by July 2024, thereby becoming the dominant lineage. Comparisons of data from wastewater and clinical surveillance demonstrated how the former presented a much higher diversity of circulating viral lineages. Importantly, some subvariants (including BA.2.86*) were detected in wastewater weeks to months prior to clinical identification, and for longer periods. Taken together, the obtained data validated wastewater surveillance as an effective early warning system, especially during periods of low infection prevalence and/or limited molecular testing efforts. This methodology can thus complement clinical surveillance by offering valuable insights into viral dynamics at the community level and enhancing pandemic preparedness

Fracture–dislocation of the shoulder and brachial plexus palsy: a terrible association

Primary post-traumatic anterior dislocation of the shoulder with associated fracture of the greater tuberosity and brachial plexus injury is rare and, to our knowledge, has never previously been reported in the literature. We present a case of this unhappy triad in which a brachial plexus injury was diagnosed and treated 3 weeks later. The characteristics of this rare condition are discussed on the basis of our case and the published literature in order to improve early diagnosis and treatment of this lesion

CoVaCS : a consensus variant calling system

Background: The advent and ongoing development of next generation sequencing technologies (NGS) has led to a rapid increase in the rate of human genome re-sequencing data, paving the way for personalized genomics and precision medicine. The body of genome resequencing data is progressively increasing underlining the need for accurate and time-effective bioinformatics systems for genotyping - a crucial prerequisite for identification of candidate causal mutations in diagnostic screens. Results: Here we present CoVaCS, a fully automated, highly accurate system with a web based graphical interface for genotyping and variant annotation. Extensive tests on a gold standard benchmark data-set -the NA12878 Illumina platinum genome- confirm that call-sets based on our consensus strategy are completely in line with those attained by similar command line based approaches, and far more accurate than call-sets from any individual tool. Importantly our system exhibits better sensitivity and higher specificity than equivalent commercial software. Conclusions: CoVaCS offers optimized pipelines integrating state of the art tools for variant calling and annotation for whole genome sequencing (WGS), whole-exome sequencing (WES) and target-gene sequencing (TGS) data. The system is currently hosted at Cineca, and offers the speed of a HPC computing facility, a crucial consideration when large numbers of samples must be analysed. Importantly, all the analyses are performed automatically allowing high reproducibility of the results. As such, we believe that CoVaCS can be a valuable tool for the analysis of human genome resequencing studies. CoVaCS is available at: https://bioinformatics.cineca.it/covacs