dataesr/scientific-paragraphs-categorization huggingface dataset:
Deep influence of EF2 from Loki 3 on the topologies obtained Our analyses suggesting the presence of hidden eukaryotic contamination in the three Loki EF2 proteins prompted us to compare the concatenation of the 36 universal proteins with and without EF2. We decided to remove EF2 from the concatenations both with and without FES (i. e. the original concatenated alignment and the curated concatenated datasets, respectively). For the 36 concatenated proteins with and without FES (controls), we obtained ML phylogenies highly similar to the Bayesian Loki ancestor tree (Figs 4A and 5A, S19 and S20 Figs). However, the BS values at nodes supporting the Loki ancestor topology were slightly lower in the tree without FES (S20 Fig), indicating that this topology was partly supported by the presence of FES in the Spang et al.
dataset. Surprisingly, we observed that M. kandleri was correctly located as sister group to Methanobacteriales in the ML tree with FES (S19 Fig), whereas it was mis-located at the base of Archaea in the Bayesian tree published by Spang and coworkers  [14]. Remarkably, the Lokiarchaeota-Eukarya affiliation was lost after removing EF2 in our ML phylogenies with and without FES (Figs 4B and 5B, S21 and S22 Figs). Eukarya became sister group to "Ca. K. cryptophylum" in the tree with FES, and the three Lokiarchaea were now all located between Euryarchaeota and other Archaea ( In this tree, the three Lokiarchaea branched between Eukarya and Archaea. These results indicate that some signal in EF2 is sufficient not only to trigger the specific Lokiarchaeota-Eukarya association, but also to break the monophyly of Archaea.
Comparison between Lokiarchaeota and Thorarchaeota After the publication about Lokiarchaeota, three "partial to near-complete" genomes have been reconstructed from metagenomic data collected from estuary sedimentary samples, and were grouped within the candidate "Thorarchaeota" phylum, based on phylogenetic analyses of the 16 rRNA gene and ribosomal proteins  [30]. In a ML tree based on the concatenated alignment of 16 ribosomal proteins and using Eukarya as outgroup, "Candidatus Thorarchaeaota archaeon" were shown to be sister group to Lokiarchaeota. Considering this suggested relationship, we checked for the 36 universal proteins in the thorarchaeal genomes. We decided to focus on the two most complete genomes (SMTZ1-83 and SMTZ1-45, ~90% and ~87% complete, respectively), like Seitz and colleagues for their concatenation-based analysis.
We could find 34 and 27 universal proteins out of the 36 used by Spang et al. in these two genomes, respectively (the two proteins systematically missing being the ribosomal proteins S3 and S4; S4 Table ), and replaced the lokiarchaeal sequences by the thorarchaeal ones in the corresponding FES-curated datasets. We performed a ML analysis of the concatenated alignments of the 34 proteins without FES and obtained a tree in which Archaea were monophyletic and the "Ca. Thorarchaeaota archaeon" were sister group to Euryarchaeota (Fig  6.
RNA polymerase phylogeny supports the monophyly of Archaea In order to avoid, as much as possible, the pitfalls above-mentioned concerning the concatenation of many proteins from likely chimeric genomes, and to know if the position we obtained for the Thorarchaea by concatenating 34 universal proteins matches with Lokiarchaea, we decided to perform a robust phylogenetic analysis of the DNA-dependent RNA polymerase using a new species dataset. Indeed, we suspected that the original set of species used by Spang and co-workers was far from optimal for tree reconstruction, even after the removal of FES, because it was strongly unbalanced with 10 Bacteria, 10 Eukarya and 84 Archaea. This imbalance could lead to technical issues in downstream analysis such as alignment, trimming and selection of phylogenetically informative regions for tree reconstruction  [26].
The Loki 1 and 2 RNA polymerases A are closely related to each other and to Thorarchaea, suggesting that these proteins are the bona fide lokiarchaeal RNA polymerases. In contrast, the Loki 3 RNA polymerase A subunit is divergent from the A' and A" subunits of Loki 1 and seems more related to the fused Thaumarchaea and Bathyarchaea sequences, suggesting that it corresponds to a contaminant. We thus decided to consider the only complete Lokiarchaeal A'A"-type RNA polymerase (Loki 1) as the representative of the Lokiarchaeota for our phylogenetic analysis. We performed a ML and two independent BI analyses (LG and CAT-GTR models) of the concatenation of RNA polymerase A and B subunits using our new species dataset. All trees were highly similar, they all recovered the monophyly of Archaea and were fully congruent with the consensus internal archaeal phylogeny  [34, 38]   In all trees, the RNA polymerase of Lokiarchaea branched as a sister group to Euryarchaeota, with strong support (77% BS in ML; 0.
We thus suggest considering all these lineages as members of the phylum Thaumarchaeota, to be consistent with the original definition of this major archaeal phylum that was proposed to include all archaea previously considered to be mesophilic Crenarchaeota, as long as they form a monophyletic group  [39]. We also obtained a strong support for a clade grouping Thorarchaea with Lokiarchaea that branched between Crenarchaeota and Euryarchaea whereas Hadesarchaea and MSBL1 branched between Lokiarchaeota/Thorarchaeota and Euryarchaeota. Finally, including sequences from recently described genomes related to Lokiarchaeota (forming altogether the putative Asgard superphylum  [31] ) to our RNA polymerase dataset supports our conclusion. The ML and BI phylogenies obtained displayed the same topology, with the monophyly of the Asgards (including Lokiarchaea and Thorarchaea) at the base of the Euryarchaeota with strong support (Fig 8, S36 and S37 Figs) and the rooting of the archaeal tree between Thaumarchaeota and all other Archaea.
Discussion Our detailed reanalysis of the Spang et al. dataset revealed that the Woese versus eocyte topology was likely determined by a combination of i) the choice of protein markers to include in the supermatrix, and ii) the inclusion of fast-evolving species (FES) in the dataset that could lead to biases. In addition, we show here that the emergence of Eukarya specifically within paraphyletic Lokiarchaeota, and to some extent the global Eukarya-Lokiarchaeota association, was likely due to the lokiarchaeal EF2 protein and its very probable chimeric structure. We identified insertions similar to eukaryotic EF2 proteins and paralogs in the lokiarchaeal EF2 proteins, especially in Loki 3 EF2 protein. The artefactual branching of lokiarchaeal EF2 proteins between Archaea and Eukarya could originate from sequences of EF2 paralog from eukaryotes and/or other Archaea present in the Arctic sample.
These sequences may have been acquired by horizontal gene transfer followed by recombination and/or during the in silico assemblage, by combining archaeal and eukaryotic sequences. Notably, it was possible to break the Lokiarchaea-Eukarya association by removing this unique protein from the initial data set, but also to retrieve the monophyly of Archaea when removing it from the FES-curated dataset. Interestingly, it has been shown that EF2 has probably a very complex evolutionary history, with at least 8 duplications in Bacteria and two in Eukaryotes (predating their last common ancestor), and a possible EF2 duplication before LUCA could not be excluded  [56]. Our conclusions over the impact of this single protein, EF2, on the global topology reminds the observations made recently by Shen and colleagues  [57].
These authors have studied the distribution of the phylogenetic signal in a data matrix used to identify the earliest-branching phylum among Metazoa. They showed that the resolution of specific nodes in ML analyses can be very sensitive to small subsets of very large data matrice. They also demonstrated that the resolution of some branches can rely on a single gene (or even a few sites) and that its removal from concatenation analyses can alter the inferred topology. In our case, we observed the loss of the Eukaryotes-Lokiarchaea affiliation we observed after removing EF2 from our concatenations in both ML and Bayesian analyses. It should be therefore interesting to repeat the simulations performed by Shen and coworkers in a Bayesian framework. We still recovered eocyte topologies after removing EF2 from the original dataset containing FES and from the 25 eocyte proteins of the curated datasets.
This clearly indicates that, beside EF2, other universal proteins favor the eocyte scenario. Which topology is favored by a given protein seems however strongly dependent on the presence of FES in the dataset, and our analysis also revealed that FES present in the dataset favor eocyte trees. Removal of species we presumed to be FES from the initial dataset improved individual phylogenies (somehow supporting their fast-evolving status), and suggested the high heterogeneity between the three Loki. This was confirmed by the results of quality control of the Lokiarchaeum genome by CheckM and Anvi'o that indicate that this genome is highly heterogeneous and very highly contaminated. In addition to the biases introduced by FES proteins, the choice of markers also strongly influences the outcome of the concatenation, favoring either the Woese or eocyte scenario.
Remarkably, our analysis of the 36 universal markers after removal of FES revealed at least two different evolutionary histories within universal proteins. Notably, we obtained highly similar topologies with both ML and Bayesian inferences (CAT-GTR model) in our analyses of the AU-relevant concatenations (Woese and eocyte proteins). This adds credit to these results and confirms that recovering the phylogenetic signal strongly depends on the dataset  [9]  (taxon sampling, markers selection, so on), either with ML or Bayesian methods. The fact that the support provided to the eocyte or the Woese scenario depends on the universal markers included could perhaps explain why several authors keep recovering the overall same eocyte tree in their analyses. They indeed often use datasets containing FES and/or lacking some of the proteins that gave strong support to the Woese's tree in our analysis, such as the two RNA polymerase subunits or some ribosomal proteins  [18, 34, 58, 59 ].
Some of these authors justified the presence of FES in their dataset by arguing that taxon sampling should be as broad as possible to break up long branches and to minimize LBA  [60]. However, simulation analyses have shown that even Bayesian methods with recent models cannot correct strong LBA when the outgroup sequences are too divergent  [9]. The addition of taxa that break up long branches is valid as long as the added taxa are not themselves FES with long branches and/or unknown taxonomic affiliation, as it is the case for archaea such as M. kandleri, Nanoarchaea or Ca. K. cryptophylum. It is often argued that probabilistic methods that model sequence heterogeneity in a Bayesian framework are essential to recover eocyte trees  [60, 61]. Our result shows that it is not the case since both ML and Bayesian analyses recovered the eocyte tree with the concatenation of the 36 protein datasets.
Notably, we notice that in that case, the position of the FES M. kandleri is not correct in the Bayesian tree published by Spang et al. (at the base of the Archaea) whereas it is correct in the ML tree (sister group to Methanobacteriales). We suspect that the Bayesian analysis could be more sensitive to the presence of FES and possible artefacts when outgroup have long branches, in agreement with simulation data recently reported by Gouy and colleagues  [9]. In opposition with the general assumption that most universal proteins have a congruent evolutionary history (hence leading to a majority rule to overcome the impact from conflictual evolutionary histories), our results in reanalysing the Loki dataset suggest instead that separate clusters of universal proteins have their own congruent history.
Finally, our analyses of the concatenated two largest DNA-dependent RNA polymerase subunits with a new balanced dataset yielded highly similar trees with both ML (LG model) and Bayesian inferences (LG and CAT-GTR models), displaying a topology congruent with a parsimonious scenario of the A subunit split distribution. Interestingly, despite the long bacterial branch, the phylogenies allowed recovering not only the internal consensus phylogeny of Archaea, but also the monophyly of several internal groups that are often difficult to obtain in phylogenetic analyses, such as the Proteobacteria in Bacteria and the Amorpha in Eukaryotes. This supports the robustness of RNA polymerase large subunits in deep phylogeny, and gives additional weight to the Woese scenario. Consequently, this suggests that the same characteristic should be sought in other universal markers to check the scenario they support.
Altogether, these observations raise major questions concerning the reconstruction of genomes from metagenomic data, especially if a MDA amplification was made during the sequencing process. A troublesome implication of the likely presence of hidden contaminating sequences in the lokiarchaeal genomes is that sequences of artificial hybrid proteins could start to accumulate in public databases. Some biochemists are thus probably already working without awareness on proteins that do not exist in nature. However, it is also possible that some ESPs genuinely belong to lokiarchaeal genomes, as it has been shown for thaumarchaeal genomes, and were lost during evolution in the other archaeal branches. Indeed, it has been suggested that reductive evolution could be the major direction in archaeal evolution  [4, 63].
Concluding remarks Our analyses demonstrate here that the specific affiliation between Eukarya and Lokiarchaeota previously described is most likely an artefact of genome reconstruction and phylogenetic analyses. Several recent publications based on the lokiarchaeal genomes should thus be revisited and scientists mining these genomes should be particularly cautious. Our work emphasizes the importance to carefully analyze individual protein datasets and trees before drawing any conclusion from phylogenies based on concatenations. It appears especially important to check for the presence of different congruent histories among the universal markers that can be mixed in global analyses, as we observed in the 36 universal proteins used in the Lokiarchaea analysis. Our results indicated that the Lokiarchaea, and probably the other Asgards, correspond to a new monophyletic archaeal lineage sister group to Euryarchaeota, not to Eukarya.
1-Datasets Initial dataset, and original concatenated alignment. The initial dataset used for the original Lokiarchaea analysis  [14]  was kindly provided by Guy L. and Ettema T. J. G. , and comprises a maximum of 10 species for both Bacteria and Eukarya and 84 species for Archaea (some species are missing in some proteins; e. g. in the arCOG4064 where there are only 3 eukaryotic species). The original concatenated alignment, already trimmed was also provided. Curated dataset. To reanalyze the original phylogenies obtained for the different arCOGs, the initial datasets were trimmed of ambiguous sequences that could provide a bias in the phylogenetic analyses (fast-evolving species, FES; sole representatives of their family; sequences not related to specific species; metagenomics reconstructions).
We also noticed that the RNA polymerase of "Ca. K. cryptophylum" contains long specific insertions reminding those of M. kandleri RNA polymerases  [32]. However, these indels are not homologous to those of M. kandleri, confirming that these two fast-evolving species are not evolutionarily related (S38A Fig). Notably, Ca. K. cryptophylum also exhibits an indel in the region of the Kae1 protein strictly conserved, except in fast-evolving species (S38B Fig). EF2 dataset. We added the amino-acid sequences of four EF2 proteins of Bathyarchaeota to the initial dataset curated of FES (see S5 Table for additional information on taxon sampling). Thorarchaeota dataset. We replaced the lokiarchaeal sequences in the curated dataset by the sequences corresponding to the same proteins from the two most complete thorarchaeal genomes («Candidatus Thorarchaeota archaeon » SMTZ1-83 and SMTZ1-45)  [30].
Two out of the 36 universal proteins could not be found in any of these genomes: the ribosomal proteins S3 and S4 (arCOG04097 and arCOG04239, respectively). The list and access numbers of the 34 proteins included is presented in supplementary S4 Table. RNA polymerase dataset. The new dataset built to analyze the phylogeny of the largest RNA polymerase subunits was based on datasets used in recent publications  [67, 68]  and on the NCBI taxonomic online platform (http://www. ncbi. nlm. nih. gov/Taxonomy/taxonomyhome. html). The amino-acid sequences were retrieved from the protein database on the NCBI server. For Lokiarchaea, we observed that the initial dataset contained one A-type (Loki 3) and two A'A"-type RNA polymerases (Loki 1 and 2). In addition, we observed only A'A"-type RNA polymerases in the genomes available for the new proposed 'Thorarchaeota' phylum, shown to be sister group to Lokiarchaeota  [30].
The A-type RNA polymerase is now attributed to an "uncultured organism" in the NCBI database, and only one of the A'A"-type is complete and still annotated as Lokiarchaeum sp. GC14_75 (KKK42229-30). For all these reasons, we decided to use this sequence to represent the Lokiarchaeota in our analyses. We avoided ambiguous species, i. e. sole representatives of their family and fast-evolving species with long branches such as those described before  [27, 33, 34]. When possible, we replaced these fast-evolving species with slow-evolving ones from the same phylum. The final database contained 39 species of each domain. To find the position of the recently described phyla Bathyarchaeota, Thorarchaeota, Hadesarchaeota and candidate Division MSBL1 archaea (Candidate division "Mediterranean Sea Brine Lakes 1")  [30, [53] [54] [55] , we added 3, 2, 3 and 2 sequences of each respectively in the dataset (see S5 Table for more information).
2-Phylogenetic analyses Indels analysis. Lokiarchaeal indels were detected after alignment of the initial dataset. The screening of similar indels in other species was made with a BlastP search against the NCBI non-redundant sequence database using the insertions and their surrounding 40-amino-acids regions, corresponding to strong anchors. The alignments presented in the figures (S13-S16 Figs) were done on these restricted regions. The presentation of the insertions conservation is visualized with SeaView  [69]. The presence of indels was also checked by aligning the sequences with PRANK, a probability alignment software  [70]. Alignments and trimming. Each alignment used for phylogenetic analyses was performed using MAFFT v7 with default settings  [71]  and trimmed with BMGE  [2]  with a BLO-SUM30 matrix.
8% and 29. 9%, respectively), could not be verified, at the time of the Lokiarchaeum (Loki 1) genome publication. Indeed, for these two lineages, only 21 and 34 coding sequences (CDS) were available on the NCBI database (S4 Table ). From the 57 Gbp produced from the MDA of the Loki Castle sample, only 226 Mbp were available on the NCBI database (SRA access: SRX684860). We looked with Anvi'o for the reads coverage onto the metagenome assembly, the genome of Loki 1, and the CDS of Loki 2 and Loki 3, using read mapping with Bowtie 2  [79] , and BlastN search against the non-amplified and the MDA amplified reads from the SRA databases (SRX684860 and SRX684858, respectively). This showed that most of the 226 Mbp available reads correspond to the MDA amplified reads that map on the Lokiarchaeum genome (Loki 1).
4-Proteome analysis The Best BLASTP hit was made for all Loki 1 proteins against the NCBI Reference Sequence Database (available the 4 August 2015 in the Pasteur Server at http://mobyle. pasteur. fr), with 0. 001 as limiting expect value (as in  [14] ). The E-utilities Application Programming Interface (https://www. ncbi. nlm. nih. gov/home/tools. shtml) was used to access the NCBI databases: Taxonomy IDs for all best hits were extracted using efetch and xtract functions on the protein database. Then the taxonomic lineages of best-hit proteins were extracted from the taxonomy NCBI database using efetch and xtract functions. sequences are indicated in red and blue respectively, while lokiarchaeal sequences are indicated in green. In each tree, a red arrow indicates the lokiarchaeal sequence corresponding to Lokiarchaeon 1.
The comparison of theses two contigs showed an insertion of five putative genes in the loki 1 contig 29 compared to the loki metagenome contig 946. The values indicated over the red arrows correspond to the total number of mapped pair-end reads (SRR1555743 and SRR1555748 runs combined) that support the absence on the five putative genes insertion and those that support both sides of the insertion. (PDF) S1 Dataset. Concatenated alignments. Concatenated alignments used in this study: the 6 AU-relevant Woese's proteins (phylip format), the 25 AU-relevant eocyte proteins (phylip format), the 36 universal markers (phylip format) used for the Lokiarchaea analyses, the 34 universal markers (phylip format) used for the Thorarchaea analysis, and the two DNAdependent RNA polymerase large subunits with the new dataset (fasta format) and with the Asgards archaea (phylip format).
The positions of each individual markers within the concantenations are indicated within a text file. The alignment of EF2 performed with PRANK is included (fasta format). (ZIP) S1 Supporting information. Detailed results of the Loki 1 genome quality analysis with Anvi'o. The data related to the Loki 1 genome quality analysis can be interactively browsed through the included index. html file with an internet browser software. (ZIP).
datasets after removal of the EF2 protein (7,724 positions). c. ML phylogenetic tree of the concatenated curated datasets after removal of the Loki 3 EF2 sequence (8,425 positions). Detailed trees in S20, S22 and S25 Figs. The scale-bars represent the average number of substitutions per site. Values at nodes represent support calculated by nonparametric bootstrap (out of 100). https://doi. org/10. 1371/journal. pgen. 1006810. g005.
). An analysis with Anvi'o of the different Loki 1 contigs suggested, by hierarchical clustering based on their tetra-nucleotide sequence composition and their differential reads coverage across the different sequencing runs (SRR1555743, SRR1555748, SRR1555750), that the Loki 1 genome present in the NCBI database (Lokiarchaeum sp. GC14_75) can be divided into separated sets of contigs (S12B Fig). The observed heterogeneity could not be only due to gene duplication because most duplicated markers observed are not located within the same contig. As shown in S12B Fig, we observed that the number of redondant markers detected by Anvi'o increased with the addition of new sets, meaning that similar marker genes are located within different contigs. This observation reflects the fact that the Loki 1 genome was formed by the accretion or assembly of at least two related lokiarchaeum genomes.
(PDF) S3 Fig. ML phylogenetic tree of the concatenation of the 11 Woese's proteins from the curated datasets (3,499 positions). In this tree, bacterial and eukaryotic sequences are indicated in red and blue, respectively. For Archaea, Thaumarchaeota and Aigarchaeota are indicated in pink, Crenarchaeota in orange and Euryarchaeota in olive-green. The Lokiarchaeota are indicated in light-green. The scale-bar represents the average number of substitutions per site. Values at nodes represent support calculated by nonparametric bootstrap (out of 100). (PDF) S4 Fig. ML phylogenetic tree of the concatenation of the 25 eocyte proteins from the curated datasets (4,868 positions). In this tree, bacterial and eukaryotic sequences are indicated in red and blue, respectively. For Archaea, Thaumarchaeota and Aigarchaeota are indicated in pink, Crenarchaeota in orange and Euryarchaeota in olive-green.