Publications

The High Level Panel for Sustainable Ocean Economy (https://oceanpanel.org/) has commissioned a series of “Blue Papers” to explore pressing challenges at the nexus of the ocean and the economy. This paper is part of a series of 16 papers to be published between November 2019 and October 2020. It addresses how multiple human impacts will impact biodiversity underpinning ecosystem services such as marine fisheries, aquaculture, coastal protection and tourism. The paper examines the distribution of marine species and critical marine habitats around the world; analyses trends in drivers, pressures, impacts and response; and establishes thresholds for protecting biodiversity hot spots, and indicators to monitor change. From this scientific base, it assesses the current legal framework and available tools for biodiversity protection, current gaps in ocean governance and management and the implications for achieving a sustainable ocean economy tailored to individual coastal states grouped by social indicators.

Abstract Strong purifying selection is considered a major evolutionary force behind small microbial genomes in the resource-poor photic ocean. However, very little is currently known about how the size of prokaryotic genomes evolves in the global ocean and whether patterns reflect shifts in resource availability in the epipelagic and relatively stable deep-sea environmental conditions. Using 364 marine microbial metagenomes, we investigate how the average genome size of uncultured planktonic prokaryotes varies across the tropical and polar oceans to the hadal realm. We find that genome size is highest in the perennially cold polar ocean, reflecting elongation of coding genes and gene dosage effects due to duplications in the interior ocean microbiome. Moreover, the rate of change in genome size due to temperature is 16-fold higher than with depth up to 200 m. Our results demonstrate how environmental factors can influence marine microbial genome size selection and ecological strategies of the microbiome.

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 present a conceptual framework, its translation into the computational workflow AGNOSTOS and a demonstration on how we can bridge the known-unknown gap in genomes and metagenomes. By analyzing 415,971,742 genes predicted from 1749 metagenomes and 28,941 bacterial and archaeal genomes, we quantify the extent of the unknown fraction, its diversity, and its relevance across multiple organisms and environments. The unknown sequence space is exceptionally diverse, phylogenetically more conserved than the known fraction and predominantly taxonomically restricted at the species level. From the 71 M genes identified to be of unknown function, we compiled a collection of 283,874 lineage-specific genes of unknown function for

Abstract Since the first alert launched by the World Health Organization (5 January, 2020), COVID-19 has been spreading out to almost 200 countries and territories. As of January 23, 2022, in total, over 346 million confirmed cases and over 5.5 million deaths have been reported worldwide. This causes massive losses in the economy and jobs globally and confining about 58% of the global population. In this paper, we introduce SenWave, a novel sentimental analysis work using 106+ million collected tweets and Weibo messages to evaluate the global rise and falls of sentiments during the COVID-19 pandemic. To make a fine-grained analysis on the feeling when we face this global health crisis, we annotate 10K tweets in English and 10K tweets in Arabic in 10 categories, including optimistic, thankful, empathetic, pessimistic, anxious, sad, annoyed, denial, official report, and joking. We then utilize an integrated transformer framework, called simpletransformer, to conduct multi-label sentimental classification by fine-tuning the pre-trained language model on the labeled data. Meanwhile, in order for a more complete analysis, we also translate the annotated English tweets into different languages (Spanish, Italian, and French) to generated training data for building sentiment analysis models for these languages. We provide detailed analysis and interesting discoveries on how the emotions evolve overtime. SenWave thus reveals the sentiment of global conversation in six different languages on COVID-19 (covering English, Spanish, French, Italian, Arabic and Chinese), followed the spread of the epidemic. The conversation showed a remarkably similar pattern of rapid rise and slow decline over time across all nations, as well as on special topics like the herd immunity strategies, to which the global conversation reacts strongly negatively. Overall, SenWave shows that optimistic and positive sentiments increased over time, foretelling a desire to seek, together, a reset for an improved COVID-19 world. We share the dataset with public to help other social impact studies of Covid-19, and fine-grained sentimental analysis tasks.

The authors thankfully acknowledge the computer resources at MareNostrum and the technical support provided by Barcelona Supercomputing Center (RES-AECT-2014-2-0085), the BMBF795 funded de.NBI Cloud within the German Network for Bioinformatics Infrastructure (de.NBI) (031A537B, 031A533A, 031A538A, 031A533B, 031A535A, 031A537C, 031A534A, 031A532B), the University of Oxford Advanced Research Computing (http://dx.doi.org/10.5281/zenodo.22558) and the MARBITS bioinformatics core at ICM-CSIC. CV was supported by the Max Planck Society. AFG received funding from the European Union’s Horizon 2020 research and innovation program Blue Growth: Unlocking the potential of Seas and Oceans under grant agreement no. 634486 (project acronym INMARE). AM was supported by the Biotechnology and Biological Sciences Research Council [BB/M011755/1, BB/R015228/1] and RDF by the European Molecular Biology Laboratory core funds. EOC was supported by project INTERACTOMA RTI2018-101205-B-I00 from the Spanish Agency of Science MICIU/AEI. SGA and PS received additional funding by the project MAGGY (CTM2017-87736-R) from the Spanish Ministry of Economy and Competitiveness. The Malaspina 2010 Expedition was supported by the Spanish Ministry of Economy and Competitiveness (MINECO) through the Consolider-Ingenio program (ref. CSD2008-00077). The authors thank Johannes Soding and Alex Bateman for helpful discussions.

Abstract Viruses play important roles on the biogeochemical cycles that take place in the ocean.Yet, deep ocean viruses are one of the most under-explored fractions of the global biosphere. Little is known about the environmental factors that control the composition and functioning of their communities, or how they interact with their free-living or particle-attached microbial hosts. Thus, we analysed 58 viral communities associated to size fractionated free-living (0.2–0.8 μm) and particle-attached (0.8–20 μm) cellular metagenomes from bathypelagic (2,150-4,018 m deep) microbiomes obtained during the Malaspina expedition. These metagenomes yielded 6,631 viral sequences, 91% of which were novel, and 67 represented high-quality genomes. Taxonomic classification assigned 53% of the viral sequences to families of tailed viruses from the order Caudovirales. Computational host prediction associated 886 viral sequences to dominant members of the deep ocean microbiome, such as Alphaproteobacteria (284), Gammaproteobacteria (241), SAR324 (23), Marinisomatota (39), and Chloroflexota (61). Free-living and particle-attached viral communities had markedly distinct taxonomic composition, host prevalence, and auxiliary metabolic gene content, which led to the discovery of novel viral encoded metabolic genes involved in the folate and nucleotide metabolisms. Water mass age emerged as an important factor driving viral community composition. We postulated this was due to changes in quality and concentration of dissolved organic matter acting on the host communities, leading to an increase of viral auxiliary metabolic genes associated with energy metabolism among older water masses. These results shed light on the mechanisms by which environmental gradients of deep ocean ecosystems structure the composition and functioning of free-living and particle-attached viral communities.

Aquaculture has existed for millennia, reaching industrial scales in recent decades, and will play an increasingly important role in feeding the world (1–6). As this industry grows, we must ensure that it is ecologically and socially sustainable. However, the current production process for the food given to farmed fish still threatens coastal ecosystems and the livelihoods of local fishers, especially in the Global South (2–7). Before aquaculture is scaled up further, its global environmental and socioeconomic footprint should be carefully reimagined.

Abstract. We assessed the relationship between zooplankton metabolism (respiration and inorganic N and P excretion) and "in situ" temperature through a grid of stations representing a range of natural temperature variation during the ATOS-Arctic cruise (July 2007). The objective was to explore not only the direct effects of temperature on O2 consumption and NH4-N and PO4-P excretion, but also to investigate the possible relationships between temperature and the stoichiometry of the metabolic products. Zooplankton metabolic rates increased according to the rising temperature conditions, following the Arrhenius equation. However, the activation energy differed for the various metabolic processes considered. Respiration was the metabolic activity less affected by temperature, followed by NH4-N and PO4-P excretion, and as a consequence the values of the C : N, C : P and N : P quotients of the metabolic products were inversely related to temperature. The effects of temperature on the stoichiometry of the excretion products would contribute to modify the nutrient pool available for phytoplankton and induce qualitative and quantitative shifts in the characteristics of primary producers that could possibly translate into the whole Arctic marine food web.