Biology subjects

Albanese, D.

Publications and source records attributed to Albanese, D..

8 recordsLinked to original sources

bioRxiv2023

Metagenomics untangles metabolic adaptations of Antarctic endolithic 1 bacteria at the fringe of habitability

BackgroundEndolithic niches offer an ultimate refuge, supplying buffered conditions for microorganisms that dwell inside rock airspaces. Yet, survival and growth strategies of Antarctic endolithic microbes residing in Earths driest and coldest desert remains virtually unknown. ResultsFrom 109 endolithic microbiomes, 4,539 metagenome-assembled genomes were generated, 49.3% of which were novel candidate bacterial species. We present evidence that trace gas oxidation and atmospheric chemosynthesis may be the prevalent strategies supporting metabolic activity and persistence of these ecosystems at the fringe of life and the limits of habitability. ConclusionsThese results represent the foundation to untangle adaptability at the edge of sustainability on Earth and on other dry Earth-like planetary bodies such as Mars.

microbiology↗

bioRxiv2023

aweMAGs: a fully automated workflow for quality assessment and annotation of eukaryotic genomes from metagenomes

Metagenomics is one of the most promising approaches to identify and characterize novel microbial species from environmental samples. While a large amount of prokaryotic metagenome assembled genomes (MAGs) have been published, only a few examples of eukaryotic MAGs have been reported. This is in part due to the absence of dedicated and easy-to-use processing pipelines. Quality assessment, annotation and phylogenomic placement of eukaryotic MAGs involve the use of several computational tools and reference databases that are often difficult to collect and maintain. We present metashot/aweMAGs, a fully automated workflow capable of performing all these steps. metashot/aweMAGs can run out-of-the-box on any platform that supports Docker, Singularity and Nextflow, including computing clusters or batch systems in the cloud.

bioinformatics↗

bioRxiv2022

Highly diverse and unknown viruses may enhance Antarctic endoliths' adaptability

Rock-dwelling microorganisms are key players in ecosystem functioning of Antarctic ice free-areas. Yet, little is known about their diversity and ecology. Here, we performed metagenomic analyses on rocks from across Antarctica comprising >75,000 viral operational taxonomic units (vOTUS). We found largely undescribed, highly diverse and spatially structured virus communities potentially influencing bacterial adaptation and biogeochemistry. This catalog lays the foundation for expanding knowledge of the virosphere in extreme environments.

microbiology↗

bioRxiv2022

Environmental thresholds in the functional mycobiome of global drylands

Fungi are major drivers of ecosystem functions. Increases in aridity are known to negatively impact fungal communities in dryland ecosystems globally, however, much less is known on the potential influence of other environmental drivers. To fill this knowledge gap, we reanalyzed fungal data from 912 soil samples, providing the largest and most complete fungal community dataset from global drylands. We used machine learning tools to examine geographical patterns in community composition and spatial, edaphic, and climatic factors driving them. Further, we determined critical thresholds of community turnover along those gradients. Our analysis identifies UV index, climate seasonality, and sand content as the most important environmental predictors of community shifts, harbouring greatest association with the richness of putative plant pathogens and saprobes. Important nonlinear relationships existed with each of these fungal guilds, with increases in UV and temperature seasonality above 7.5 and 900 SD, respectively, being associated with an increased probability of plant pathogens and unspecified saprotrophs occurrence. Conversely, these environmental parameters had a negative relationship with litter and soil saprotrophs richness. Consequently, these functional groups might be differentially sensitive to environmental changes, which might result in an inevitable disturbance of current plant-soil dynamics in drylands.

ecology↗

bioRxiv2021

Stability of microbiota in vineyard soils across consecutive years.

Agricultural soils harbor rich and diverse microbial communities that have a deep influence on soil properties and productivity. Large scale studies have shown the impact of environmental parameters like climate or chemical composition on the distribution of bacterial and fungal species. Comparatively, little data exists documenting how soil microbial communities change between different years. Quantifying the temporal stability of soil microbial communities will allow us to better understand the relevance of the differences between environments and their impact on ecological processes on the global and local scale. We characterized the bacterial and fungal components of the soil microbiota in ten vineyards in two consecutive years. Despite differences of species richness and diversity between the two years, we found a general stability of the taxonomic structure of the soil microbiota. Temporal differences were smaller than differences due to geographical location, vineyard land management or differences between sampling sites within the same vineyard. Using machine learning, we demonstrated that each site was characterized by a distinctive microbiota, and we identified a reduced set of indicator species that could classify samples according to their geographic origin across different years with high accuracy. ImportanceThe temporal stability of the soil microbiota is important to understand the relevance of the differences that are found in response to a variety of environmental factors. By comparing fungal and bacterial microbiota from samples collected in the same sites in two consecutive years, we found a remarkable stability of both components, with characteristic differences between bacteria and fungi. Our work fills an important gap toward the definition of a microbial cartography of agricultural soils.

microbiology↗

bioRxiv2020

Antarctic cryptoendolithic bacterial lineages of pre-Cambrian origin as proxy for Mars colonization

Cryptoendolithic communities are microbial ecosystems dwelling inside porous rocks. They are able to persist at the edge of the biological potential for life in the ice-free areas of continental Antarctica. These areas include the McMurdo Dry Valleys, often cited as a Terrestrial analog of the Martian environment. Despite their interest as a model for the early colonization by living organisms of terrestrial ecosystems and for adaptation to extreme conditions of stress, little is known about the evolution, diversity and genetic makeup of bacterial species that reside in these environments. We performed metagenomic sequencing of 18 communities from rocks collected in Antarctic desert areas over a distance of about 350 km. A total of 469 draft bacterial genome sequences were assembled, and clustered into 269 candidate species that lack a representative genome in public databases. The majority of these new species belong to monophyletic bacterial clades that diverged from related taxa in a range from 1.2 billion to 410 Ma, much earlier than the glaciation of Antarctica, and that are functionally distinct from known related taxa. The hypothesis that Antarctic cryptoendolithic bacterial lineages were generated by the selection of pre-existing cold-tolerant organisms whose origin dates back to the Tonian glaciations gives new insights for the possibility of life on Mars.

microbiology↗

bioRxiv2019

Metagenomes in the borderline ecosystems of the Antarctic cryptoendolithic communities

Antarctic cryptoendolithic communities are microbial ecosystems dwelling inside rocks of ice-free areas in Continental Antarctica. In Antarctica, these ecosystems were first described from the McMurdo Dry Valleys, accounted as the best analogous of the Martian environment on Earth and thought to be devoid of life until the discovery of these cryptic life-forms. Our results present the first shotgun metagenomes of Antarctic cryptoendolithic lichen-dominated communities from 18 differently sun-exposed rock samples collected during the XXXI Italian Antarctic Expedition (2015-16), along an altitudinal transect from 834 up to 3100 m a.s.l. Here, we provide the raw data obtained with Illumina Novaseq sequencer, followed by initial functional and taxonomic analysis.\n\nOur results extend understanding of the microbial diversity and biological processes in the Antarctic desert and represent an invaluable resource for the scientific community as a base-line for further studies of this kind to examine the mechanisms and pathways necessary for life to adapt and evolve in the extremes.

microbiology↗

bioRxiv2017

A practical tool for Maximal Information Coefficient analysis

BackgroundThe ability of finding complex associations in large omics datasets, assessing their significance, and prioritizing them according to their strength can be of great help in the data exploration phase. Mutual Information based measures of association are particularly promising, in particular after the recent introduction of the TICe and MICe estimators, which combine computational efficiency with good bias/variance properties. Despite that, a complete software implementation of these two measures and of a statistical procedure to test the significance of each association is still missing.\n\nFindingsIn this paper we present MICtools, a comprehensive and effective pipeline which combines TICe and MICe into a multi-step procedure that allows the identification of relationships of various degrees of complexity. MICtools calculates their strength assessing statistical significance using a permutation-based strategy. The performances of the proposed approach are assessed by an extensive investigation in synthetic datasets and an example of a potential application on a metagenomic dataset is also illustrated.\n\nConclusionsWe show that MICtools, combining TICe and MICe, is able to highlight associations that would not be captured by conventional strategies. MICtools is implemented in Python, and is available for download at https://github.com/minepy/mictools.

bioinformatics↗