Biology subjects

Di Gregorio, S.

Publications and source records attributed to Di Gregorio, S..

4 recordsLinked to original sources

bioRxiv2024

Co-Metabolic Growth and Microbial Diversity: Keys for the depletion of the α, δ, β and γ-HCH isomers.

The objective of this study was to select and enhance microbiomes capable of degrading the , {delta}, {beta} and {gamma}-HCH isomers. These microbiomes were isolated and enriched from an HCH-contaminated dumpsite in Italy, both in the presence of HCH isomers (1:1:1:1) as the sole carbon sources and under co-metabolic growth conditions in presence of glucose (0.1%). Four microbiomes were assessed for their relevant metabolic capabilities. A quantitative metabarcoding approach was employed to analyze the compositional evolution of the four microbiomes during the enrichment phase and the phase of tsting of the HCH isomers degradation kinetics. The use of a co-metabolic substrate during enrichment process was essential for selecting microbiomes with higher biodiversity. All microbiomes efficiently degraded the , {delta}, and {gamma}-HCH isomers. The highest efficiency in the {beta}-HCH degradation capacity was associated to the highest biodiversity of the microbiome, and the involvement of Chryseobacterium and Asinibacterium sps. has been proposed for a recorded increment in bacterial load during the HCH degradation process. Statement of environmental implicationsSoil contaminated with hexachlorocyclohexane (HCH), including all four isomers, poses a significant risk to environmental and public health. This study isolates and selects microbiomes capable of degrading HCH, demonstrating their degradation efficiency using GC-MS analysis, and studies the microbial communities through metabarcoding of both the initial soils and the selected microbiomes. The contaminated soil originates from the historically polluted area of Italy known as SIN-Valle del Sacco. Developing and optimizing microbiome selection techniques for application on contaminated sites can significantly enhance soil bioremediation, thereby reducing contamination and protecting the environment.

microbiology↗

bioRxiv2024

Revisiting typing systems for group B Streptococcus (GBS) prophages: an application in prophage detection and classification in GBS isolates from Argentina

Group B Streptococcus (GBS) causes severe infections in neonates and adults with comorbidities. Prophages have been reported to contribute to GBS evolution and pathogenicity. However, no studies are available to date on the presence and diversity of prophages in GBS isolates from humans in South America. This study provides insights into the prophage content of 365 GBS isolates collected from clinical samples in the context of an Argentinean multicentric study. Using whole genome sequence data, we implemented two previously proposed methods for prophage typing: a PCR approach (carried out in silico) coupled with a blastx-based method to classify prophages based on their prophage group and integrase type, respectively. We manually searched the genomes and identified 325 prophages. However, only 80% of prophages could be accurately categorised with the previous approaches. Integration of phylogenetic analysis, prophage group and integrase type allowed for all to be classified into 19 prophage types, which correlated with GBS clonal complex grouping. The revised prophage typing approach was additionally improved by using a blastn search after enriching the database with 10 new genes for prophage group classification combined with the existing integrase typing method. This modified and integrated typing system was applied to the analysis of 615 GBS genomes (365 GBS from Argentina and 250 from public databases), which revealed 29 prophage types, including 2 novel integrase subtypes. Their characterization and comparative analysis revealed major differences in the lysogeny and replication modules. Genes related to bacterial fitness, virulence or adaptation to stressful environments were detected in all prophage types. Considering prophage prevalence, distribution and their association with bacterial virulence, it is important to study their role in GBS epidemiology. In this context, we propose the use of an improved and integrated prophage typing system suitable for rapid phage detection and classification with little computational processing. Author summaryBacteriophages, which are viruses that infect bacteria, exert a profound influence on microbial evolution when integrated into the bacterial genome, a state in which they are called prophages. It has been proposed that prophage acquisition played a role in the emergence of Streptococcus agalactiae (GBS) as a human pathogen in European countries. Further study and characterization of prophages of GBS from around the world would provide valuable insights into the mechanisms underlying GBS adaptation, evolution and epidemiology. Unfortunately, existing tools for prophage screening exhibit limitations in the detection and classification of all prophages present in GBS genomes. To address this issue, in this work we propose a new prophage typing system that allows the detection and classification of GBS prophages based on both their phylogenetic lineage and integration site within the bacterial genome. Using this methodology we were able to identify 29 prophage types in 615 GBS isolated globally. We further characterised these prophages and found that they carried genes that could give an evolutionary advantage to their host and that different lineages of GBS carried different prophage types. Comprehensive exploration and characterization of prophages represent an indispensable endeavour, providing critical insights into microbial evolution, epidemiology, and potential therapeutic interventions.

bioinformatics↗

bioRxiv2024

hAMRonization: Enhancing antimicrobial resistance prediction using the PHA4GE AMR detection specification and tooling

The detection of antimicrobial resistance (AMR) markers directly from genomic or metagenomic data is becoming a standard clinical and public health procedure. This has resulted in the development of a number of different bioinformatic AMR prediction tools. Although many may implement similar principles, these tools differ significantly in their supported inputs, search algorithms, parameterisation, and underlying reference databases. Each of these tools generates a report of detected AMR genes or variants in a distinct, non-standard, format. This presents a huge barrier to the comparison of results and to the modularity of tools for AMR gene prediction within bioinformatic workflows. In collaboration with 17 public health laboratories across 10 countries, the Public Health Alliance for Genomic Epidemiology (PHA4GE) (https://pha4ge.org) data structures working group has developed and piloted a standardized output specification for the bioinformatic detection of AMR from microbial genomes. In this report, we discuss hAMRonization, a python package and command-line utility, which implements PHA4GEs AMR specification to combine the outputs of disparate antimicrobial resistance gene detection tools into a single unified format. hAMRonization can be easily extended and currently supports 18 different tools (both species-agnostic and species-specific) for the detection of genes and/or variants conferring AMR. The harmonized reports are available in tabular form, JSON format or through an interactive HTML file (e.g., https://maguire-lab.github.io/assets/interactive_report_demo.html) that can be opened within the browser for navigable data exploration. As of 2024-03-07 hAMRonization has been downloaded [~]12,500 times, incorporated into >9 public bioinformatic tools and workflows, and been internally adopted by several national and international public health groups. The hAMRonization tool and underlying specification are open-source and freely available through PyPI, conda and GitHub (https://github.com/pha4ge/hAMRonization).

bioinformatics↗

bioRxiv2023

Bio-based decontamination and detoxification of total petroleum hydrocarbon contaminated dredged sediments: perspectives to produce constructed technosols in the frame of the circular economy.

To accelerate the depletion of total petroleum hydrocarbons, a hydrocarburoclastic ascomycetes, Lambertella sp. MUT 5852, was bioaugmented to dredged sediments co-composting with a lignocellulosic matrix. After only 28 days of incubation, a complete depletion of the contamination was observed. The 16S rDNA metabarcoding of the bacterial community and a predictive functional metagenomic analysis was adopted to evaluate potential bacterial degrading and detoxifying functions. A combination of toxicological assays on two eukaryotic models, the root tips of Vicia faba and the human intestinal epithelial Caco-2 cells, was adopted to assess the robustness of the process not only for the decontamination but also for the detoxification of the dredged sediments. Bacterial taxa, such as Kocuria and Sphingobacterium sps. resulted to be involved in both the decontamination and detoxification of the co-composting dredged sediments by potential activation of diverse oxidative processes. At the same time, the Kocuria sp. showed plant growth promoting activity by the potential expression of the 1-aminocyclopropane-1-carboxylate deaminase activity, providing functional traits of interest for a technosol in terms of sustaining primary producer growth and development.

microbiology↗