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Deutschmann, I. M.

Publications and source records attributed to Deutschmann, I. M..

9 recordsLinked to original sources

Ecological processes shaping marine microbial assemblages diverge between equatorial and temperate time-series

Marine microbial communities are structured by a complex interplay of deterministic and stochastic processes, yet how these vary across latitudes remains poorly understood. Most long-term microbial observatories are restricted to temperate regions, limiting our ability to assess latitudinal contrasts in microbial dynamics. Here, we compare coastal microbial communities from two contrasting marine time-series stations using standardized molecular protocols: a new tropical site in the Equatorial Atlantic (EAMO, 6{degrees}S) and a well-studied temperate site in the Mediterranean Sea (BBMO, 41{degrees}N). Monthly 16S and 18S rRNA gene sequencing of two size-fractions (0.22-3 {micro}m and >3 {micro}m) over 41 months (from April 2013 to August 2016) revealed marked differences in taxonomic composition, temporal variability, and ecological assembly processes. Temperate communities exhibited strong seasonal turnover, higher beta-diversity, and tighter coupling with environmental variables such as temperature and daylength. In contrast, tropical communities were compositionally more stable and more governed by biotic factors and stochastic processes such as historical contingency and ecological drift. These patterns were consistent across taxonomic domains and size-fractions, though selection was generally stronger in prokaryotes and the smallest size-fraction. Co-occurrence networks at the temperate site were more densely connected and environmentally responsive compared to tropical networks, where stochastic processes and putative biological interactions gain prominence. This study highlights the importance of integrating observatories from underrepresented latitudes into global microbial monitoring efforts, particularly as climate change alters the amplitude and frequency of environmental drivers across the ocean.

ecology↗

Molecular mechanisms reconstruction from single-cell multi-omics data with HuMMuS

The molecular identity of a cell results from a complex interplay between heterogeneous molecular layers. Recent advances in single-cell sequencing technologies have opened the possibility to measure such molecular layers of regulation. Here, we present HuMMuS, a new method for inferring regulatory mechanisms from single-cell multi-omics data. Differently from the state-of-the-art, HuMMuS captures cooperation between biological macromolecules and can easily include additional layers of molecular regulation. We benchmarked HuMMuS with respect to the state-of-the-art on both paired and unpaired multi-omics datasets. Our results proved the improvements provided by HuMMus in terms of TF targets, TF binding motifs and regulatory regions prediction. Finally, once applied to snmC-seq, scATAC-seq and scRNA-seq data from mouse brain cortex, HuMMuS enabled to accurately cluster scRNA profiles and to identify potential driver TFs.

bioinformatics↗

Paired single-cell multi-omics data integration with Mowgli

The profiling of multiple molecular layers from the same set of cells has recently become possible. There is thus a growing need for multi-view learning methods able to jointly analyze these data. We here present Multi-Omics Wasserstein inteGrative anaLysIs (Mowgli), a novel method for the integration of paired multi-omics data with any type and number of omics. Of note, Mowgli combines integrative Nonnegative Matrix Factorization (NMF) and Optimal Transport (OT), enhancing at the same time the clustering performance and interpretability of integrative NMF. We apply Mowgli to multiple paired single-cell multi-omics data profiled with 10X Multiome, CITE-seq and TEA-seq. Our in depth benchmark demonstrates that Mowglis performance is competitive with the state-of-the-art in cell clustering and superior to the state-of-the-art once considering biological interpretability. Mowgli is implemented as a Python package seamlessly integrated within the scverse ecosystem and it is available at http://github.com/cantinilab/mowgli.

bioinformatics↗

Disentangling environmental effects in microbial association networks

BackgroundEcological interactions among microorganisms are fundamental for ecosystem function, yet they are mostly unknown or poorly understood. High-throughput-omics can indicate microbial interactions through associations across time and space, which can be represented as association networks. Associations could result from either ecological interactions between microorganisms, or from environmental selection, where the associations are environmentally-driven. Therefore, before downstream analysis and interpretation, we need to distinguish the nature of the association, particularly if it is due to environmental selection or not. ResultsWe present EnDED (Environmentally-Driven Edge Detection), an implementation of four approaches as well as their combination to predict which links between microorganisms in an association network are environmentally-driven. The four approaches are Sign Pattern, Overlap, Interaction Information, and Data Processing Inequality. We tested EnDED on networks from simulated data of 50 microorganisms. The networks contained on average 50 nodes and 1087 edges, of which 60 were true interactions but 1026 false associations (i.e. environmentally-driven or due to chance). Applying each method individually, we detected a moderate to high number of environmentally-driven edges--87% Sign Pattern and Overlap, 67% Interaction Information, and 44% Data Processing Inequality. Combining these methods in an intersection approach resulted in retaining more interactions, both true and false (32% of environmentally-driven associations). After validation with the simulated datasets, we applied EnDED on a marine microbial network inferred from 10 years of monthly observations of microbial-plankton abundance. The intersection combination predicted that 8.3% of the associations were environmentally-driven, while individual methods predicted 24.8% (Data Processing Inequality), 25.7% (Interaction Information), and up to 84.6% (Sign Pattern as well as Overlap). The fraction of environmentally-driven edges among negative microbial associations in the real network increased rapidly with the number of environmental factors. ConclusionsTo reach accurate hypotheses about ecological interactions, it is important to determine, quantify, and remove environmentally-driven associations in marine microbial association networks. For that, EnDED offers up to four individual methods as well as their combination. However, especially for the intersection combination, we suggest using EnDED with other strategies to reduce the number of false associations and consequently the number of potential interaction hypotheses.

microbiology↗

Disentangling temporal associations in marine microbial networks

BackgroundMicrobial interactions are fundamental for Earths ecosystem functioning and biogeochemical cycling. Nevertheless, they are challenging to identify and remain barely known. Omics-based censuses are helpful in predicting microbial interactions through the statistical inference of single (static) association networks. Yet, microbial interactions are dynamic and we have limited knowledge of how they change over time. Here we investigate the dynamics of microbial associations in a 10-year marine time series in the Mediterranean Sea using an approach inferring a time-resolved (temporal) network from a single static network. ResultsA single static network including microbial eukaryotes and bacteria was built using metabarcoding data derived from 120 monthly samples. For the decade, we aimed to identify persistent, seasonal, and temporary microbial associations by determining a temporal network that captures the interactome of each individual sample. We found that the temporal network appears to follow an annual cycle, collapsing and reassembling when transiting between colder and warmer waters. We observed higher association repeatability in colder than in warmer months. Only 16 associations could be validated using observations reported in literature, underlining our knowledge gap in marine microbial ecological interactions. ConclusionsOur results indicate that marine microbial associations follow recurrent temporal dynamics in temperate zones, which need to be accounted for to better understand the functioning of the ocean microbiome. The constructed marine temporal network may serve as a resource for testing season-specific microbial interaction hypotheses. The applied approach can be transferred to microbiome studies in other ecosystems.

microbiology↗

Disentangling marine microbial networks across space

Microbial interactions underpin ocean ecosystem function, but they remain barely known. Multiple studies have analyzed microbial interactions using static association networks based on omics data, yet microbial interactions are dynamic and can change across spatiotemporal scales. Understanding the dynamics of microbial interactions is needed for a better comprehension of ocean ecosystems. Here, we explored associations between archaea, bacteria, and picoeukaryotes along the water column, from the surface to the deep ocean, across the northern subtropical to the southern temperate ocean and the Mediterranean Sea by defining sample-specific subnetworks, which allowed us to examine changes in microbial associations across space. We found that associations tend to change with depth as well as with geographical scale, with a few associations being global (i.e., present across regions within the same depth layer) and 11-36% being regional within specific water layers. The lowest fraction of global associations was found in the bathypelagic zone, while associations restricted to certain regions increased with depth. The majority of associations observed in surface waters disappeared with depth, suggesting that surface ocean associations are not transferred to the deep sea, despite microbial sinking. Altogether, our results suggest that microbial associations have highly heterogeneous distributions in the horizontal and vertical dimensions of the ocean and that such distributions do not mirror taxonomic distributions. Our work contributes to better understand the dynamics of microbial interactions in the global ocean, which is urgently needed in a context of global change.

microbiology↗

Long-term patterns of an interconnected core marine microbiota

BackgroundOcean microbes constitute [~]70% of the marine biomass, are responsible for [~]50% of the Earths primary production, and are crucial for global biogeochemical cycles. Marine microbiotas include core taxa that are usually key for ecosystem function. Despite their importance, core marine microbes are relatively unknown, which reflects the lack of consensus on how to identify them. So far, most core microbiotas have been defined based on species occurrence and abundance. Yet, species interactions are also important to identify core microbes, as communities include interacting species. Here, we investigate interconnected bacteria and small protists of the core pelagic microbiota populating a long-term marine-coastal observatory in the Mediterranean Sea over a decade. ResultsCore microbes were defined as those present in >30% of the monthly samples over 10 years, with the strongest associations. The core microbiota included 259 Operational Taxonomic Units (OTUs) including 182 bacteria, 77 protists, and 1,411 strong and mostly positive ([~]95%) associations. Core bacteria tended to be associated with other bacteria, while core protists tended to be associated with bacteria. The richness and abundance of core OTUs varied annually, decreasing in stratified warmers waters and increasing in colder mixed waters. Most core OTUs had a preference for one season, mostly winter, which featured subnetworks with the highest connectivity. Groups of highly associated taxa tended to include protists and bacteria with predominance in the same season, particularly winter. A group of 13 highly-connected hub-OTUs, with potentially important ecological roles dominated in winter and spring. Similarly, 18 connector OTUs with a low degree but high centrality were mostly associated with summer or autumn and may represent transitions between seasonal communities. ConclusionsWe found a relatively small and dynamic interconnected core microbiota in a model temperate marine-coastal site, with potential interactions being more deterministic in winter than in other seasons. These core microbes would be essential for the functioning of this ecosystem over the year. Other non-core taxa may also carry out important functions but would be redundant and non-essential. Our work contributes to the understanding of the dynamics and potential interactions of core microbes possibly sustaining ocean ecosystem function.

ecology↗

Evolutionary diversification of tiny ocean predators

Unicellular eukaryotic predators have a crucial role in the functioning of the ocean ecosystem by recycling nutrients and energy that are channeled to upper trophic levels. Traditionally, these evolutionary-diverse organisms have been combined into a single functional group (Heterotrophic flagellates), overlooking their organismal differences. Here we investigate four evolutionary related species belonging to one cosmopolitan family of uncultured marine picoeukaryotic predators: MAST-4 (species A, B, C, and E). Co-occurrence and distribution analyses in the global surface ocean indicated contrasting patterns in MAST-4A & C, suggesting adaptation to different temperatures. We then investigated whether these spatial distribution patterns were mirrored by MAST-4 genomic content using Single-Cell Genomics. Analyses of 69 single-cells recovered 66-83% of the MAST-4A/B/C/E genomes, which displayed substantial inter-species divergence. MAST-4 genomes were similar in terms of broad gene functional categories, but they differed in enzymes of ecological relevance, such as glycoside hydrolases (GHs), which are part of the food degradation machinery in MAST-4. Interestingly, MAST-4 species featuring a similar GH composition co-excluded each other (A & C) in the surface global ocean, while species with a different set of GHs appeared to be able to co-exist (species B & C) suggesting further niche diversification associated to prey digestion. We propose that differential niche adaptation to temperature and prey type has promoted adaptive evolutionary diversification in MAST-4. Altogether, we show that minute ocean predators from the same family may have different biogeography and genomic content, which need to be accounted to better comprehend marine food webs.

ecology↗

Different processes shape prokaryotic and picoeukaryotic assemblages in the sunlit ocean microbiome

The smallest members of the sunlit-ocean microbiome (prokaryotes and picoeukaryotes) participate in a plethora of ecosystem functions with planetary-scale effects. Understanding the processes determining the spatial turnover of this assemblage can help us better comprehend the links between microbiome species composition and ecosystem function. Ecological theory predicts that selection, dispersal and drift are main drivers of species distributions, yet, the relative quantitative importance of these ecological processes in structuring the surface-ocean microbiome is barely known. Here we quantified the role of selection, dispersal and drift in structuring surface-ocean prokaryotic and picoeukaryotic assemblages by using community DNA-sequence data collected during the global Malaspina expedition. We found that dispersal limitation was the dominant process structuring picoeukaryotic communities, while a balanced combination of dispersal limitation, selection and drift shaped prokaryotic counterparts. Subsequently, we determined the agents exerting abiotic selection as well as the spatial patterns emerging from the action of different ecological processes. We found that selection exerted via temperature had a strong influence on the structure of prokaryotic communities, particularly on species co-occurrences, a pattern not observed among communities of picoeukaryotes. Other measured abiotic variables had limited selective effects on microbiome structure. Picoeukaryotes presented a higher differentiation between neighbouring communities and a higher distance-decay when compared to prokaryotes, agreeing with their higher dispersal limitation. Finally, drift seemed to have a limited role in structuring the sunlit-ocean microbiome. The different predominance of ecological processes acting on particular subsets of the ocean microbiome suggests uneven responses to environmental change.\n\nSIGNIFICANCE STATEMENTThe global ocean contains one of the largest microbiomes on Earth and changes on its structure can impact the functioning of the biosphere. Yet, we are far from understanding the mechanisms that structure the global ocean microbiome, that is, the relative importance of environmental selection, dispersal and random events (drift). We evaluated the role of these processes at the global scale, based on data derived from a circumglobal expedition and found that these ecological processes act differently on prokaryotes and picoeukaryotes, two of the main components of the ocean microbiome. Our work represents a significant contribution to understand the assembly of marine microbial communities, providing also insights on the links between ecological mechanisms, microbiome structure and ecosystem function.

ecology↗