Biology subjects

Fernandez-Guerra, A.

Publications and source records attributed to Fernandez-Guerra, A..

13 recordsLinked to original sources

bioRxiv2024

CarpeDeam: A De Novo Metagenome Assemblerfor Heavily Damaged Ancient Datasets

De novo assembly of ancient metagenomic datasets is a challenging task. Ultra-short fragment size and characteristic postmortem damage patterns of sequenced ancient DNA molecules leave current tools ill-equipped for ideal assembly. We present CarpeDeam, a novel damage-aware de novo assembler designed specifically for ancient metagenomic samples. Utilizing maximum-likelihood frameworks that integrate sample-specific damage patterns, CarpeDeam demonstrates improved recovery of longer continuous sequences and protein sequences in many simulated and empirical datasets compared to existing assemblers. As a pioneering ancient metagenome assembler, CarpeDeam opens the door for new opportunities in functional and taxonomic analyses of ancient microbial communities.

genomics↗

bioRxiv2023

The landscape of ancient human pathogens in Eurasia from the Stone Age to historical times

Infectious diseases have had devastating impacts on human populations throughout history, but important questions about their origins and past dynamics remain1. To create the first archaeogenetic-based spatiotemporal map of human pathogens, we screened shotgun sequencing data from 1,313 ancient humans covering 37,000 years of Eurasian history. We demonstrate the widespread presence of ancient bacterial, viral and parasite DNA, identifying 5,486 individual hits against 492 species from 136 genera. Among those hits, 3,384 involve known human pathogens2, many of which were detected for the first time in ancient human remains. Grouping the ancient microbial species according to their likely reservoir and type of transmission, we find that most groups are identified throughout the entire sampling period. Intriguingly, zoonotic pathogens are only detected [~]6,500 years ago, peaking [~]5,000 years ago, coinciding with the widespread domestication of livestock3. Our findings provide the first direct evidence that this lifestyle change resulted in an increased infectious disease burden. Importantly, they also suggest that the spread of these pathogens increased substantially during subsequent millenia, coinciding with the pastoralist migrations from the Eurasian Steppe4,5.

evolutionary biology↗

bioRxiv2023

A 2-million-year-old microbial and viral communities from the Kap Kobenhavn Formation in North Greenland

Environmental DNA (eDNA) from the 2-million-year-old Kap Kobenhavn Formation of northern Greenland has revealed an ecosystem of plants and animals with no contemporary analogue1. Here, we reconstruct the microbial (bacterial, archaeal, and viral) communities that thrived at the site during this time. By leveraging a novel analytical framework that integrates taxonomic profiling, DNA damage estimates, and functional reconstructions, we identify and distinguish pioneer microbial communities from later permafrost microbial assemblages. We show that at the time of sediment deposition, the terrestrial input at the Kap Kobenhavn site originated from a palustrine wetland, suggesting warmer, non-permafrost conditions. During this period, the detection of methanogenic archaea and signals of their carbon metabolism is consistent with Kap Kobenhavn and similar northern ecosystems contributing moderate methane emissions. Intriguingly, we discover a remarkable nucleotide sequence similarity--exceeding 98%--between pioneer methanogens and present-day analogues in thawing permafrost. This aligns with the concept of "time-traveling" microbes2 surviving across geological time and waiting for conditions to turn favourable rather than evolving to adapt to changing conditions. Importantly, in contrast to the plant and animal communities of the Kap Kobenhavn, a striking similarity in microbial composition to that of a contemporary thawing Arctic suggests that microbial communities may serve as the first indication of broader climate-driven ecosystem disruptions.

microbiology↗

bioRxiv2023

Microbes with higher metabolic independence are enriched in human gut microbiomes under stress

A wide variety of human diseases are associated with loss of microbial diversity in the human gut, inspiring a great interest in the diagnostic or therapeutic potential of the microbiota. However, the ecological forces that drive diversity reduction in disease states remain unclear, rendering it difficult to ascertain the role of the microbiota in disease emergence or severity. One hypothesis to explain this phenomenon is that microbial diversity is diminished as disease states select for microbial populations that are more fit to survive environmental stress caused by inflammation or other host factors. Here, we tested this hypothesis on a large scale, by developing a software framework to quantify the enrichment of microbial metabolisms in complex metagenomes as a function of microbial diversity. We applied this framework to over 400 gut metagenomes from individuals who are healthy or diagnosed with inflammatory bowel disease (IBD). We found that high metabolic independence (HMI) is a distinguishing characteristic of microbial communities associated with individuals diagnosed with IBD. A classifier we trained using the normalized copy numbers of 33 HMI-associated metabolic modules not only distinguished states of health versus IBD, but also tracked the recovery of the gut microbiome following antibiotic treatment, suggesting that HMI is a hallmark of microbial communities in stressed gut environments.

microbiology↗

bioRxiv2023

Genomic adaptation of giant viruses in polar oceans

Despite being perennially frigid, polar oceans form an ecosystem hosting high and unique biodiversity. Various organisms show different adaptative strategies in this habitat, but how viruses adapt to this environment is largely unknown. Viruses of phyla Nucleocytoviricota and Mirusviricota are groups of eukaryote-infecting large and giant DNA viruses with genomes encoding a variety of functions. Here, by leveraging the Global Ocean Eukaryotic Viral database, we investigate the biogeography and functional repertoire of these viruses at a global scale. We first confirm the existence of an ecological barrier that clearly separates polar and nonpolar viral communities, and demonstrate that temperature drives dramatic changes in the virus-host network at the polar/nonpolar boundary. Ancestral niche reconstruction suggests that adaptation of these viruses to polar conditions has occurred repeatedly over the course of evolution, with polar-adapted viruses in the modern ocean being scattered across their phylogeny. Numerous viral genes are specifically associated with polar adaptation, although most of their homologues are not identified as polar-adaptive genes in eukaryotes. These results suggest that giant viruses adapt to cold environments by changing their functional repertoire, and this viral evolutionary strategy is independent of the polar adaptation of their hosts.

microbiology↗

bioRxiv2022

metaDMG - A Fast and Accurate Ancient DNA Damage Toolkit for Metagenomic Data

O_LIMotivation Under favourable conditions DNA molecules can persist for hundreds of thousands of years. Such genetic remains make up invaluable resources to study past assemblages, populations, and even the evolution of species. However, DNA is subject to degradation, and hence over time decrease to ultra low concentrations which makes it highly prone to contamination by modern sources. Strict precautions are therefore necessary to ensure that DNA from modern sources does not appear in the final data is authenticated as ancient. The most generally accepted and widely applied authenticity for ancient DNA studies is to test for elevated deaminated cytosine residues towards the termini of the molecules: DNA damage. To date, this has primarily been used for single organisms and recently for read assemblies, however, these methods are not applicable for estimating DNA damage for ancient metagenomes with tens and even hundreds of thousands of species. C_LIO_LIMethods We present metaDMG, a novel framework and toolkit that allows for the estimation, quantification and visualization of postmortem damage for single reads, single genomes and even metagenomic environmental DNA by utilizing the taxonomic branching structure. It bypasses any need for initial classification, splitting reads by individual organisms, and realignment. We have implemented a Bayesian approach that combines a modified geometric damage profile with a beta-binomial model to fit the entire model to the individual misincorporations at all taxonomic levels. C_LIO_LIResults We evaluated the performance using both simulated and published environmental DNA datasets and compared to existing methods when relevant. We find metaDMG to be an order of magnitude faster than previous methods and more accurate - even for complex metagenomes. Our simulations show that metaDMG can estimate DNA damage at taxonomic levels down to 100 reads, that the estimated uncertainties decrease with increased number of reads and that the estimates are more significant with increased number of C to T misincorporations. C_LIO_LIConclusion metaDMG is a state-of-the-art program for aDNA damage estimation and allows for the computation of nucleotide misincorporation, GC-content, and DNA fragmentation for both simple and complex ancient genomic datasets, making it a complete package for ancient DNA damage authentication. C_LI

bioinformatics↗

bioRxiv2021

An ecological perspective on microbial genes of unknown function in soil

Genes that remain hypothetical, uncharacterized, and unannotated comprise a substantial portion of metagenomic datasets and are likely to be particularly prevalent in soils where poorly characterized taxa predominate. Documenting the prevalence, distribution, and potential roles of these genes of unknown function is an important first step to understanding their functional contributions in soil communities. We identified genes of unknown function from 50 soil metagenomes and analyzed their environmental distributions and ecological associations. We found that genes of unknown function are prevalent in soils, particularly fine-textured, higher pH soils that harbor greater abundances of Crenarchaeota, Gemmatimonadota, Nitrospirota, and Methylomirabilota. We identified 43 dominant (abundant and ubiquitous) gene clusters of unknown function and determined their associations with soil microbial phyla and other "known" genes. We found that these dominant unknown genes were commonly associated with microbial phyla that are relatively uncharacterized, with the majority of these dominant unknown genes associated with mobile genetic elements. This work demonstrates a strategy for investigating genes of unknown function in soils, emphasizes the biological insights that can be learned by adopting this strategy, and highlights specific hypotheses that warrant further investigation regarding the functional roles of abundant and ubiquitous genes of unknown function in soil metagenomes.

microbiology↗

bioRxiv2021

AGNOSTOS-DB: a resource to unlock the uncharted regions of the coding sequence space

Genomes and metagenomes contain a considerable percentage of genes of unknown function, which are often excluded from downstream analyses limiting our understanding of the studied biological systems. To address this challenge, we developed AGNOSTOS, a combined database-computational workflow resource that unifies the known and unknown coding sequence space of genomes and metagenomes. Here, we present AGNOSTOS-DB, an extensive database of high-quality gene clusters enriched with functional, ecological and phylogenetic information. Moreover, AGNOSTOS allows integrating new data into existing AGNOSTOS-DBs, maximizing the information retrievable for the genes of unknown function. As a proof of concept, we provide a seed database that integrates the predicted genes from marine and human metagenomes, as well as from Bacteria, Archaea, Eukarya and giant viruses environmental and cultivar genomes. The seed database comprises 6,572,081 gene clusters connecting 342 million genes and represents a comprehensive and scalable resource for the inclusion and exploration of the unknown fraction of genomes and metagenomes.

microbiology↗

bioRxiv2021

Mining metagenomes for natural product biosynthetic gene clusters: unlocking new potential with ultrafast techniques

Microorganisms produce an immense variety of natural products through the expression of Biosynthetic Gene Clusters (BGCs): physically clustered genes that encode the enzymes of a specialized metabolic pathway. These natural products cover a wide range of chemical classes (e.g., aminoglycosides, lantibiotics, nonribosomal peptides, oligosaccharides, polyketides, terpenes) that are highly valuable for industrial and medical applications1. Metagenomics, as a culture-independent approach, has greatly enhanced our ability to survey the functional potential of microorganisms and is growing in popularity for the mining of BGCs. However, to effectively exploit metagenomic data to this end, it will be crucial to more efficiently identify these genomic elements in highly complex and ever-increasing volumes of data2. Here, we address this challenge by developing the ultrafast Biosynthetic Gene cluster MEtagenomic eXploration toolbox (BiG-MEx). BiG-MEx rapidly identifies a broad range of BGC protein domains, assess their diversity and novelty, and predicts the abundance profile of natural product BGC classes in metagenomic data. We show the advantages of BiG-MEx compared to standard BGC-mining approaches, and use it to explore the BGC domain and class composition of samples in the TARA Oceans3 and Human Microbiome Project datasets4. In these analyses, we demonstrate BiG-MExs applicability to study the distribution, diversity, and ecological roles of BGCs in metagenomic data, and guide the exploration of natural products with clinical applications.

bioinformatics↗

bioRxiv2020

Community-curated and standardised metadata of published ancient metagenomic samples with AncientMetagenomeDir

Ancient DNA and RNA are valuable data sources for a wide range of disciplines. Within the field of ancient metagenomics, the number of published genetic datasets has risen dramatically in recent years, and tracking this data for reuse is particularly important for large-scale ecological and evolutionary studies of individual microbial taxa, microbial communities, and metagenomic assemblages. AncientMetagenomeDir (archived at https://doi.org/10.5281/zenodo.3980833) is a collection of indices of published genetic data deriving from ancient microbial samples that provides basic, standardised metadata and accession numbers to allow rapid data retrieval from online repositories. These collections are community-curated and span multiple sub-disciplines in order to ensure adequate breadth and consensus in metadata definitions, as well as longevity of the database. Internal guidelines and automated checks to facilitate compatibility with established sequence-read archives and term-ontologies ensure consistency and interoperability for future meta-analyses. This collection will also assist in standardising metadata reporting for future ancient metagenomic studies.

bioinformatics↗

bioRxiv2020

Light into the darkness: Unifying the known and unknown coding sequence space in microbiome analyses

Genes of unknown function are among the biggest challenges in molecular biology, especially in microbial systems, where 40%-60% of the predicted genes are unknown. Despite previous attempts, systematic approaches to include the unknown fraction into analytical workflows are still lacking. Here, we propose a conceptual framework and a computational workflow that bridge the known-unknown gap in genomes and metagenomes. We showcase our approach by exploring 415,971,742 genes predicted from 1,749 metagenomes and 28,941 bacterial and archaeal genomes. We quantify the extent of the unknown fraction, its diversity, and its relevance across multiple biomes. Furthermore, we provide a collection of 283,874 lineage-specific genes of unknown function for Cand. Patescibacteria, being a significant resource to expand our understanding of their unusual biology. Finally, by identifying a target gene of unknown function for antibiotic resistance, we demonstrate how we can enable the generation of hypotheses that can be used to augment experimental data.

microbiology↗

bioRxiv2019

Genomic evidence for global ocean plankton biogeography shaped by large-scale current systems

Biogeographical studies have traditionally focused on readily visible organisms, but recent technological advances are enabling analyses of the large-scale distribution of microscopic organisms, whose biogeographical patterns have long been debated. Here we assessed the global structure of plankton geography and its relation to the biological, chemical and physical context of the ocean (the seascape) by analyzing metagenomes of plankton communities sampled across oceans during the Tara Oceans expedition, in light of environmental data and ocean current transport. Using a consistent approach across organismal sizes that provides unprecedented resolution to measure changes in genomic composition between communities, we report a pan-ocean, size-dependent plankton biogeography overlying regional heterogeneity. We found robust evidence for a basin-scale impact of transport by ocean currents on plankton biogeography, and on a characteristic timescale of community dynamics going beyond simple seasonality or life history transitions of plankton.

ecology↗

bioRxiv2018

A computational framework for systematic exploration of biosynthetic diversity from large-scale genomic data

Genome mining has become a key technology to explore and exploit natural product diversity through the identification and analysis of biosynthetic gene clusters (BGCs). Initially, this was performed on a single-genome basis; currently, the process is being scaled up to large-scale mining of pan-genomes of entire genera, complete strain collections and metagenomic datasets from which thousands of bacterial genomes can be extracted at once. However, no bioinformatic framework is currently available for the effective analysis of datasets of this size and complexity. Here, we provide a streamlined computational workflow, tightly integrated with antiSMASH and MIBiG, that consists of two new software tools, BiG-SCAPE and CORASON. BiG-SCAPE facilitates rapid calculation and interactive visual exploration of BGC sequence similarity networks, grouping gene clusters at multiple hierarchical levels, and includes a glocal alignment mode that accurately groups both complete and fragmented BGCs. CORASON employs a phylogenomic approach to elucidate the detailed evolutionary relationships between gene clusters by computing high-resolution multi-locus phylogenies of all BGCs within and across gene cluster families (GCFs), and allows researchers to comprehensively identify all genomic contexts in which particular biosynthetic gene cassettes are found. We validate BiG-SCAPE by correlating its GCF output to metabolomic data across 403 actinobacterial strains. Furthermore, we demonstrate the discovery potential of the platform by using CORASON to comprehensively map the phylogenetic diversity of the large detoxin/rimosamide gene cluster clan, prioritizing three new detoxin families for subsequent characterization of six new analogs using isotopic labeling and analysis of tandem mass spectrometric data.

bioinformatics↗