About the lab
At the log[lab] we are interested in understanding different aspects of the microbial world. The main research lines aim at 1) understanding the structuring and dynamics of natural microbial communities using ecological theory, 2) disentangling the network of microbial interactions in ecosystems and 3) linking the gene content of genomes, communities and their variation, with ecological function and evolutionary processes. We are located at the ICM-CSIC in Barcelona, including close colleagues at the UiO in Oslo; we love to play with programs and large computers.
Featured projects (1)
Comprehending the magnitude of the population genomic diversity in microbes as well as the evolution of their populations over short timescales represent two fundamental challenges for microbiology, evolutionary biology, biological oceanography and global change research. This project addresses these challenges by 1) investigating the population genomic diversity of microbial strains over 12 years in two coastal time series in the Mediterranean Sea using metagenomics and contrasting the results against the global ocean , 2) analysing evolutionary processes occurring over 12 years using the DNA collected in both time series as an evolutionary record, 3) examining experimentally the fine-grained evolutionary response of marine microbes to main global change stressors in the ocean (increased temperature and CO2 concentrations).
Featured research (14)
Background Ocean microbes constitute ~ 70% of the marine biomass, are responsible for ~ 50% of the Earth’s 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. Results Core 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 1411 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. Conclusions We 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.
Background Ecological 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 association is 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. Results We 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. Conclusions To 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.
Rivers connect the carbon cycle in land with that in aquatic ecosystems by transporting and transforming terrestrial organic matter (TeOM). The Amazon River receives huge loads of TeOM from the surrounding rainforest, promoting a substantial microbial heterotrophic activity and consequently, CO2 outgassing. In the Amazon River, microbes degrade up to 55% of the lignin present in the TeOM. Yet, the main microbial genomes involved in TeOM degradation were unknown. Here, we characterize 51 Population Genomes (PGs) representing some of the most abundant microbes in the Amazon River deriving from 106 metagenomes. The 51 reconstructed PGs are among the most abundant microbes in the Amazon River, and 53% of them are not able to degrade TeOM. Among the PGs capable of degrading TeOM, 20% were exclusively cellulolytic, while the others could also oxidize lignin. The transport and consumption of lignin oxidation by‐products seemed to be decoupled from the oxidation process, being apparently performed by different groups of microorganisms. By connecting the genomic features of abundant microbes in the Amazon River with the degradation machinery of TeOM, we suggest that a complex microbial consortium could explain the quick turnover of TeOM previously observed in this ecosystem.
Unicellular eukaryotic predators play a crucial role in the functioning of the ocean ecosystem by recycling nutrients and energy that are channeled to upper trophic levels. Traditionally, these evolutionarily diverse organisms have been combined into a single functional group (heterotrophic flagellates), overlooking their organismal differences. Here, we investigated four evolutionarily related species belonging to one cosmopolitan group of uncultured marine picoeukaryotic predators: marine stramenopiles (MAST)-4 (species A, B, C, and E). Co-occurrence and distribution analyses in the global surface ocean indicated contrasting patterns in MAST-4A and 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 to 83% of the MAST-4A/B/C/E genomes, which displayed substantial interspecies 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 (A and C) coexcluded each other in the surface global ocean, while species with a different set of GHs (B and C) appeared to be able to coexist, suggesting further niche diversification associated with prey digestion. We propose that differential niche adaptation to temperature and prey type has promoted adaptive evolutionary diversification in MAST-4. We show that minute ocean predators from the same phylogenetic group may have different biogeography and genomic content, which needs to be accounted for to better comprehend marine food webs.
Microbial interactions are fundamental for Earth’s ecosystem functioning and biogeochemical cycling. Nevertheless, they are challenging to identify and remain barely known. The omics-based censuses are helpful to predict microbial interactions through the inference of static association networks. However, since microbial interactions are highly dynamic, we have developed an approach to generate a temporal network from a single static network. We applied it to understand the monthly microbial associations’ dynamics occurring over ten years in the Blanes Bay Microbial Observatory (Mediterranean Sea). For the decade, we identified persistent, seasonal, and temporary microbial associations. Moreover, 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 repeatability in colder than warmer months. Altogether, our results indicate that marine microbial networks follow recurrent temporal dynamics, which need to be accounted to better understand the dynamics of the ocean microbiome.
- Marine Biology and Oceanography
About Ramiro Logares
- I am a computational ecologist & evolutionary biologist investigating the microbial world. My main research lines aim at 1) understanding the structuring and dynamics of natural microbial communities using ecological theory, 2) disentangling the network of microbial interactions in ecosystems and 3) linking the gene content of genomes, communities and their variation, with ecological function and evolutionary processes.