Light color acclimation is a key process in the global ocean distribution of Synechococcus cyanobacteria

Understanding the functional diversity of specific microbial groups at the global scale is critical yet poorly developed. By combining the considerable knowledge accumulated through recent years on the molecular bases of photosynthetic pigment diversity in marine Synechococcus, a major phytoplanktonic organism, with the wealth of metagenomic data provided by the Tara Oceans expedition, we have been able to reliably quantify all known pigment types along its transect and provide a global distribution map. Unexpectedly, cells able to dynamically change their pigment content to match the ambient light color were ubiquitous and predominated in many environments. Altogether, our results unveiled the role of adaptation to light quality on niche partitioning in a key primary producer

Disentangling the mechanisms shaping the surface ocean microbiota

BACKGROUND: The ocean microbiota modulates global biogeochemical cycles and changes in its configuration may have large-scale consequences. Yet, the underlying ecological mechanisms structuring it are unclear. Here, we investigate how fundamental ecological mechanisms (selection, dispersal and ecological drift) shape the smallest members of the tropical and subtropical surface-ocean microbiota: prokaryotes and minute eukaryotes (picoeukaryotes). Furthermore, we investigate the agents exerting abiotic selection on this assemblage as well as the spatial patterns emerging from the action of ecological mechanisms. To explore this, we analysed the composition of surface-ocean prokaryotic and picoeukaryotic communities using DNA-sequence data (16S- and 18S-rRNA genes) collected during the circumglobal expeditions Malaspina-2010 and TARA-Oceans. RESULTS: We found that the two main components of the tropical and subtropical surface-ocean microbiota, prokaryotes and picoeukaryotes, appear to be structured by different ecological mechanisms. Picoeukaryotic communities were predominantly structured by dispersal-limitation, while prokaryotic counterparts appeared to be shaped by the combined action of dispersal-limitation, selection and drift. Temperature-driven selection appeared as a major factor, out of a few selected factors, influencing species co-occurrence networks in prokaryotes but not in picoeukaryotes, indicating that association patterns may contribute to understand ocean microbiota structure and response to selection. Other measured abiotic variables seemed to have limited selective effects on community structure in the tropical and subtropical ocean. Picoeukaryotes displayed a higher spatial differentiation between communities and a higher distance decay when compared to prokaryotes, consistent with a scenario of higher dispersal limitation in the former after considering environmental heterogeneity. Lastly, random dynamics or drift seemed to have a more important role in structuring prokaryotic communities than picoeukaryotic counterparts. CONCLUSIONS: The differential action of ecological mechanisms seems to cause contrasting biogeography, in the tropical and subtropical ocean, among the smallest surface plankton, prokaryotes and picoeukaryotes. This suggests that the idiosyncrasy of the main constituents of the ocean microbiota should be considered in order to understand its current and future configuration, which is especially relevant in a context of global change, where the reaction of surface ocean plankton to temperature increase is still unclear. Video Abstract

A consensus protocol for the recovery of mercury methylation genes from metagenomes

Mercury (Hg) methylation genes (hgcAB) mediate the formation of the toxic methylmercury and have been identified from diverse environments, including freshwater and marine ecosystems, Arctic permafrost, forest and paddy soils, coal-ash amended sediments, chlor-alkali plants discharges and geothermal springs. Here we present the first attempt at a standardized protocol for the detection, identification and quantification of hgc genes from metagenomes. Our Hg-cycling microorganisms in aquatic and terrestrial ecosystems (Hg-MATE) database, a catalogue of hgc genes, provides the most accurate information to date on the taxonomic identity and functional/metabolic attributes of microorganisms responsible for Hg methylation in the environment. Furthermore, we introduce "marky-coco", a ready-to-use bioinformatic pipeline based on de novo single-metagenome assembly, for easy and accurate characterization of hgc genes from environmental samples. We compared the recovery of hgc genes from environmental metagenomes using the marky-coco pipeline with an approach based on coassembly of multiple metagenomes. Our data show similar efficiency in both approaches for most environments except those with high diversity (i.e., paddy soils) for which a coassembly approach was preferred. Finally, we discuss the definition of true hgc genes and methods to normalize hgc gene counts from metagenomes

Unifying the known and unknown microbial coding sequence space

5 figures, 13 appendixes.-- Data availability: We used public data as described in the Methods section and Appendix 1-table 5.The code used for the analyses in the manuscript is available at https://github.com/functional-dark-side/functional-dark-side.github.io/tree/master/scripts. A list with the program versions can be found in https://github.com/functional-dark-side/functional-dark-side.github.io/blob/master/programs_and_versions.txt.The code to create the figures is available at https://github.com/functional-dark-side/vanni_et_al-figures, and the data for the figure can be downloaded from https://doi.org/10.6084/m9.figshare.12738476.v2. A reproducible version of the workflow is available at https://github.com/functional-dark-side/agnostos-wf.The data is publicly available at https://doi.org/10.6084/m9.figshare.12459056Genes 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 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 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 71M genes identified to be of unknown function, we compiled a collection of 283,874 lineage-specific genes of unknown function for Cand. Patescibacteria (also known as Candidate Phyla Radiation, CPR), which provides 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.The authors thankfully acknowledge the computer resources at MareNostrum and the technical support provided by Barcelona Supercomputing Center (RES-AECT-2014-2-0085), the BMBF877 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. S 887 GA 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 Söding and Alex Bateman for helpful discussions.Peer reviewedWith the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)

What's New Is Old: Resolving the Identity of Leptothrix ochracea Using Single Cell Genomics, Pyrosequencing and FISH

Leptothrix ochracea is a common inhabitant of freshwater iron seeps and iron-rich wetlands. Its defining characteristic is copious production of extracellular sheaths encrusted with iron oxyhydroxides. Surprisingly, over 90% of these sheaths are empty, hence, what appears to be an abundant population of iron-oxidizing bacteria, consists of relatively few cells. Because L. ochracea has proven difficult to cultivate, its identification is based solely on habitat preference and morphology. We utilized cultivation-independent techniques to resolve this long-standing enigma. By selecting the actively growing edge of a Leptothrix-containing iron mat, a conventional SSU rRNA gene clone library was obtained that had 29 clones (42% of the total library) related to the Leptothrix/Sphaerotilus group (≤96% identical to cultured representatives). A pyrotagged library of the V4 hypervariable region constructed from the bulk mat showed that 7.2% of the total sequences also belonged to the Leptothrix/Sphaerotilus group. Sorting of individual L. ochracea sheaths, followed by whole genome amplification (WGA) and PCR identified a SSU rRNA sequence that clustered closely with the putative Leptothrix clones and pyrotags. Using these data, a fluorescence in-situ hybridization (FISH) probe, Lepto175, was designed that bound to ensheathed cells. Quantitative use of this probe demonstrated that up to 35% of microbial cells in an actively accreting iron mat were L. ochracea. The SSU rRNA gene of L. ochracea shares 96% homology with its closet cultivated relative, L. cholodnii, This establishes that L. ochracea is indeed related to this group of morphologically similar, filamentous, sheathed microorganisms

Massively Parallel Haplotyping on Microscopic Beads for the High-Throughput Phase Analysis of Single Molecules

In spite of the many advances in haplotyping methods, it is still very difficult to characterize rare haplotypes in tissues and different environmental samples or to accurately assess the haplotype diversity in large mixtures. This would require a haplotyping method capable of analyzing the phase of single molecules with an unprecedented throughput. Here we describe such a haplotyping method capable of analyzing in parallel hundreds of thousands single molecules in one experiment. In this method, multiple PCR reactions amplify different polymorphic regions of a single DNA molecule on a magnetic bead compartmentalized in an emulsion drop. The allelic states of the amplified polymorphisms are identified with fluorescently labeled probes that are then decoded from images taken of the arrayed beads by a microscope. This method can evaluate the phase of up to 3 polymorphisms separated by up to 5 kilobases in hundreds of thousands single molecules. We tested the sensitivity of the method by measuring the number of mutant haplotypes synthesized by four different commercially available enzymes: Phusion, Platinum Taq, Titanium Taq, and Phire. The digital nature of the method makes it highly sensitive to detecting haplotype ratios of less than 1∶10,000. We also accurately quantified chimera formation during the exponential phase of PCR by different DNA polymerases

Variable Copy Number, Intra-Genomic Heterogeneities and Lateral Transfers of the 16S rRNA Gene in Pseudomonas

Even though the 16S rRNA gene is the most commonly used taxonomic marker in microbial ecology, its poor resolution is still not fully understood at the intra-genus level. In this work, the number of rRNA gene operons, intra-genomic heterogeneities and lateral transfers were investigated at a fine-scale resolution, throughout the Pseudomonas genus. In addition to nineteen sequenced Pseudomonas strains, we determined the 16S rRNA copy number in four other Pseudomonas strains by Southern hybridization and Pulsed-Field Gel Electrophoresis, and studied the intra-genomic heterogeneities by Denaturing Gradient Gel Electrophoresis and sequencing. Although the variable copy number (from four to seven) seems to be correlated with the evolutionary distance, some close strains in the P. fluorescens lineage showed a different number of 16S rRNA genes, whereas all the strains in the P. aeruginosa lineage displayed the same number of genes (four copies). Further study of the intra-genomic heterogeneities revealed that most of the Pseudomonas strains (15 out of 19 strains) had at least two different 16S rRNA alleles. A great difference (5 or 19 nucleotides, essentially grouped near the V1 hypervariable region) was observed only in two sequenced strains. In one of our strains studied (MFY30 strain), we found a difference of 12 nucleotides (grouped in the V3 hypervariable region) between copies of the 16S rRNA gene. Finally, occurrence of partial lateral transfers of the 16S rRNA gene was further investigated in 1803 full-length sequences of Pseudomonas available in the databases. Remarkably, we found that the two most variable regions (the V1 and V3 hypervariable regions) had probably been laterally transferred from another evolutionary distant Pseudomonas strain for at least 48.3 and 41.6% of the 16S rRNA sequences, respectively. In conclusion, we strongly recommend removing these regions of the 16S rRNA gene during the intra-genus diversity studies