Resolving cryptic species complexes in marine protists: phylogenetic haplotype networks meet global DNA metabarcoding datasets

Marine protists have traditionally been assumed to be lowly diverse and cosmopolitan. Yet, several recent studies have shown that many protist species actually consist of cryptic complexes of species whose members are often restricted to particular biogeographic regions. Nonetheless, detection of cryptic species is usually hampered by sampling coverage and application of methods (e.g. phylogenetic trees) that are not well suited to identify relatively recent divergence and ongoing gene flow. In this paper, we show how these issues can be overcome by inferring phylogenetic haplotype networks from global metabarcoding datasets. We use the Chaetoceros curvisetus (Bacillariophyta) species complex as study case. Using two complementary metabarcoding datasets (Ocean Sampling Day and Tara Oceans), we equally resolve the cryptic complex in terms of number of inferred species. We detect new hypothetical species in both datasets. Gene flow between most of species is absent, but no barcoding gap exists. Some species have restricted distribution patterns whereas others are widely distributed. Closely related taxa occupy contrasting biogeographic regions, suggesting that geographic and ecological differentiation drive speciation. In conclusion, we show the potential of the analysis of metabarcoding data with evolutionary approaches for systematic and phylogeographic studies of marine protists.

Recent Trends in Underwater Wireless Sensor Networks (UWSNs) – A Systematic Literature Review

Underwater Wireless Sensor Networks (UWSNs) is an emerging technology for the monitoring of aquatic assets and frequently applied in several domains like underwater information gathering, ocean sampling network, anonymous vehicles, disaster prevention and submarine detection. Recently, UWSNs have been getting significant attention of researchers from both academia and industry. As a result, several studies have been carried out to perform certain improvements in UWSNs techniques, tools, protocols and architectures. In this regard, there is a dire need to investigate and summarize the modern UWSNs trends altogether within a single study. To achieve this, a Systematic Literature Review (SLR) is performed in this article to comprehensively analyze the latest developments in UWSNs. Particularly, 34 research studies published during 2012-2020 have been selected and examined in the area of UWSNs. This leads to the identification of 21 modern routing protocols and 11 tools. Furthermore, 5 different architecture types and 3 communication media technologies are presented in the context of UWSNs. Finally, a comparative analysis of routing protocols is done on the basis of important evaluation metrics. It has been concluded that there exist adequate approaches, protocols and tools for the monitoring of UWSNs. However, the design verification capabilities of existing approaches are insufficient to meet the growing demands of UWSNs. The findings of this article provide solid platform to enhance the current UWSNs tools and techniques for large and complex networks.

Functional metagenomics of the Thioredoxin superfamily

Environmental sequence data of microbial communities now makes up the majority of public genomic information. The assignment of a function to sequences from these metagenomic sources is challenging, because organisms associated with the data are often uncharacterized and not cultivable. To overcome these challenges, we created a rationally designed expression library of metagenomic proteins covering the sequence space of the thioredoxin superfamily. This library of 100 individual proteins represents more than 22’000 thioredoxins found in the Global Ocean Sampling dataset. We screened this library for the functional rescue of Escherichia coli mutants lacking the thioredoxin-type reductase (∆trxA), isomerase (∆dsbC), or oxidase (∆dsbA). We were able to assign functions to more than a quarter of our representative proteins. The in vivo function of a given representative could not be predicted by phylogenetic relation but did correlate with the predicted isoelectric surface potential of the protein. Selected proteins were then purified and we determined their activity using a standard insulin reduction assay and measured their redox potential. An unexpected gel shift of protein E5 during the redox potential determination revealed a redox cycle distinct from that of typical thioredoxin-superfamily oxidoreductases. Instead of the intramolecular disulfide bond formation typical for thioredoxins, this protein forms an intermolecular disulfide between the attacking cysteines of two separate subunits during its catalytic cycle. Our functional metagenomic approach proved not only useful to assign in vivo functions to representatives of thousands of proteins, but also uncovered a novel reaction mechanism in a seemingly well-known protein superfamily.

How Deep Argo Will Improve the Deep Ocean in an Ocean Reanalysis

Global ocean sampling with autonomous floats going to 4000–6000 m, known as the deep Argo array, constitutes one of the next challenges for tracking climate change. The question here is how such a global deep array will impact ocean reanalyses. Based on the different behavior of four ocean reanalyses, we first identified that large uncertainty exists in current reanalyses in representing local heat and freshwater fluxes in the deep ocean (1 W m−2 and 10 cm yr−1 regionally). Additionally, temperature and salinity comparison with deep Argo observations demonstrates that reanalysis errors in the deep ocean are of the same size as, or even stronger than, the deep ocean signal. An experimental approach, using the 1/4° GLORYS2V4 (Global Ocean Reanalysis and Simulation) system, is then presented to anticipate how the evolution of the global ocean observing system (GOOS), with the advent of deep Argo, would contribute to ocean reanalyses. Based on observing system simulation experiments (OSSE), which consist in extracting observing system datasets from a realistic simulation to be subsequently assimilated in an experimental system, this study suggests that a global deep Argo array of 1200 floats will significantly constrain the deep ocean by reducing temperature and salinity errors by around 50%. Our results also show that such a deep global array will help ocean reanalyses to reduce error in temperature changes below 2000 m, equivalent to global ocean heat fluxes from 0.15 to 0.07 W m−2, and from 0.26 to 0.19 W m−2 for the entire water column. This work exploits the capabilities of operational systems to provide comprehensive information for the evolution of the GOOS.