Biology subjects

Agostinetto, G.

Publications and source records attributed to Agostinetto, G..

5 recordsLinked to original sources

bioRxiv2023

MADAME: a user-friendly bioinformatic tool for data and metadata retrieval in microbiome research

Microbiome research advancements have provided countless insights. Despite the massive amount of data currently stored in public repositories, these resources remain vastly underutilized due to the intricacy of data and metadata retrieval from these databases. However, leveraging data-driven approaches is crucial for microbiome research progress by overcoming variations between studies and identifying generalizable trends. We designed the open-access and user-friendly bioinformatic tool MADAME (MetADAta MicrobiomE) to streamline the data and metadata retrieval process. MADAME addresses the challenges posed by the public repositories current limitations, allowing users to retrieve publications associated with the accession codes of interest. Additionally, MADAME allows users to visually explore retrieved results through the generation of a comprehensive report with plots and statistics. These unique features of MADAME let users maximize their time and resources, enabling them to assess metadata suitability before pursuing data download. To showcase its diverse functionalities, we recreate several scenarios to meet the diverse requirements that researchers may have.

bioinformatics↗

bioRxiv2022

Dealing with the promise of metabarcoding in mega-event biomonitoring: EXPO2015 unedited data

As human activities on our planet persist, causing widespread and irreversible environmental degradation, the need to biomonitor ecosystems has never been more pressing. These circumstances have required a renewal in monitoring techniques, encouraged by necessity to develop more rapid and accurate tools which will support timely observations of ecosystem structure and function. The World Exposition (from now EXPO2015) hosted in Milan from May to October 2015 was a global event that could be categorized as a mega-event, which can be defined as an acute environmental stressor, possibly generating biodiversity alteration and disturbance. During the six months of EXPO2015, exhibitors from more than 135 countries and 22 million visitors insisted on a 1.1 million square meters area. Faced with such a massive event, we explore the potential of DNA metabarcoding using three molecular markers to improve the understanding of anthropogenic impacts in the area, both considering air and water monitoring. Furthermore, we explore the effectiveness of the taxonomy assignment phase considering different taxonomic levels of analysis and the use of data mining approaches to predict sample origin. Unless the degree of taxa identification still remains open, our results showed that DNA metabarcoding is a powerful genomic-based tool to monitor biodiversity at the microscale, allowing us to capture exact fingerprints of specific event sites and to explore in a comprehensive manner the eukaryotic community alteration. With this work, we aim to disentangle and overcome the crucial issues related to the generalization of DNA metabarcoding in order to support future applications.

molecular biology↗

bioRxiv2021

SKIOME Project: a curated collection of skin microbiome datasets enriched with study-related metadata

Large amounts of data from microbiome-related studies have been (and are currently being) deposited on international public databases. These datasets represent a valuable resource for the microbiome research community and could serve future researchers interested in integrating multiple datasets into powerful meta-analyses. However, this huge amount of data lacks harmonization and is far from being completely exploited in its full potential to build a foundation that places microbiome research at the nexus of many subdisciplines within and beyond biology. Thus, urges the need for data accessibility and reusability, according to FAIR (Findable, Accessible, Interoperable, and Reusable) principles, as supported by National Microbiome Data Collaborative and FAIR Microbiome. To tackle the challenge of accelerating discovery and advances in skin microbiome research, we collected, integrated and organized existing microbiome data resources from human skin 16S rRNA amplicon sequencing experiments. We generated a comprehensive collection of datasets, enriched in metadata, and organized this information into data frames ready to be integrated into microbiome research projects and advanced post-processing analysis, such as data science applications (e.g. machine learning). Furthermore, we have created a data retrieval and curation framework built on three different stages to maximize the retrieval of datasets and metadata associated with them. Lastly, we highlighted some caveats regarding metadata retrieval and suggested ways to improve future metadata submissions. Overall, our work resulted in a curated skin microbiome datasets collection accompanied by a state-of-the-art analysis of the last 10 years of the skin microbiome field.

bioinformatics↗

bioRxiv2020

ExTaxsI: an exploration tool of biodiversity molecular data

BackgroundThe increasing availability of multi omics data is leading to continually revise estimates of existing biodiversity data. In particular, the molecular data enable to characterize novel species yet unknown and to increase the information linked to those already observed with new genomic data. For this reason, the management and visualization of existing molecular data, and their related metadata, through the implementation of easy to use IT tools have become a key point for the development of future research. The more users are able to access biodiversity related information, the greater the ability of the scientific community to expand the knowledge in this area. ResultsIn our research we have focused on the development of ExTaxsI (Exploring Taxonomies Information), an IT tool able to retrieve biodiversity data stored in NCBI databases and provide a simple and explorable visualization. Through the three case studies presented here, we have shown how an efficient organization of the data already present can lead to obtaining new information that is fundamental as a starting point for new research. Our approach was also able to highlight the limits in the distribution data availability, a key factor to consider in the experimental design phase of broad spectrum studies, such as metagenomics. ConclusionsExTaxI can easily produce explorable visualization of molecular data and its metadata, with the aim to help researchers to improve experimental designs and highlight the main gaps in the coverage of available data.

bioinformatics↗

bioRxiv2020

Tasting the differences: microbiota analysis of different insect-based novel food

Traceability, quality and safety of edible insects are important both for the producers and the consumers. Today, alongside the burst of edible insects in western countries, we are facing a gap of knowledge of insect microbiota associated with the microbial ecosystems of insect-based products. Recent studies suggest that the insect microbiota can vary between insect species and that can be shaped by additional factors, such as rearing conditions. Also, the production processes of raw materials (i.e. insect flour) into final food products can affect the insect microbiota too. This has consequences for the evaluation of food safety and food traceability. In this context, High-Throughput DNA Sequencing (HTS) techniques can give insight into the carryover of insect microbiota into final food products. In this study, we investigated the microbiota composition of insect-based commercial food products, applying HTS techniques coupled with bioinformatic analysis. The aim of this work was to analyse the microbiota variability of different categories of insect-based products made of A. domesticus (house cricket), T. molitor (mealworm beetle), and A. diaperinus (lesser mealworm or litter beetle), including commercial raw materials and processed food items, purchased via e-commerce from different companies. Our data revealed that samples cluster per insect species based on microbiota profile and preliminary results suggested that a small number of prevalent bacteria formed a "core microbiota" characterizing the products depending on the insect, suggesting that a resident microbiota is conserved. This microbial signature can be recognized despite the different food processing levels, rearing conditions selling companies. We showed that differences exist when comparing raw vs processed food made of the same insect, or similar products produced by different companies as well, laying the groundwork for further analyses. These results support the application of HTS analysis for studying the composition of processed insect food in a wider perspective, for food traceability and food quality control.

microbiology↗