DOI: 10.5061/dryad.vx0k6djnm
title: Genomics of new ciliate lineages provides insight into the evolution of obligate anaerobiosis - single gene datasets for phylogenomic analysis of anaerobic ciliates (SAL, Ciliophora), protein datasets for mitochondrial pathways prediction, and mitochondrial genomes

description: Oxygen plays a crucial role in energetic metabolism of most eukaryotes.
 Yet, adaptations to low oxygen concentrations leading to anaerobiosis have
 independently arisen in many eukaryotic lineages, resulting in a broad
 spectrum of reduced and modified mitochondrial organelles (MROs). In this
 study, we present the discovery of two new class-level lineages of
 free-living marine anaerobic ciliates, Muranotrichea, cl. nov. and
 Parablepharismea, cl. nov., that, together with the class Armophorea, form
 a major clade of obligate anaerobes (APM ciliates) within the SAL
 (Spirotrichea, Armophorea, Litostomatea) group. To deepen our
 understanding of the evolution of anaerobiosis in ciliates, we predicted
 the mitochondrial metabolism of cultured representatives from all three
 classes in the APM clade, using transcriptomic and metagenomic data, and
 performed phylogenomic analyses to assess their evolutionary
 relationships. The predicted mitochondrial metabolism of representatives
 from the APM ciliates reveals functional adaptations of metabolic pathways
 that were present in their last common ancestor and likely led to the
 successful colonization and diversification of the group in various anoxic
 environments. Furthermore, we discuss the possible relationship of
 Parablepharismea to the uncultured deep-sea class Cariacotrichea based on
 single gene analyses. Like most anaerobic ciliates, all studied species of
 the APM clade host symbionts, which we propose to be a significant
 accelerating factor in the transitions to an obligately anaerobic
 lifestyle. Our results provide an insight into the evolutionary mechanisms
 of early transitions to anaerobiosis and shed light on fine-scale
 adaptations in MROs over a relatively short evolutionary timeframe.
description: <b>Illumina NextSeq Sequencing </b>
 Metagenomes were sequenced from the picked cells and a culture
 using Illumina NextSeq (Illumina Inc.) (150-bp paired-end reads, 300-bp
 insert size). Transcriptome was sequenced by EMBL Genomics Core Facility
 (GeneCore), Heidelberg, Germany. <b>Metagenomic
 and Transcriptomic Assemblies</b> For
 metagenomes, Trimmomatic v0.36 was used to filter and trim paired reads
 from all samples. Filtered and trimmed reads were then combined and
 co-assembled with IDBA-UD v.1.1.1. Metagenomic contigs &gt; 1 kb were
 binned using CONCOCT as implemented in Anvi’o v2.0.3, which bins contigs
 based on nucleotide composition and differential coverage data from
 mapping reads to the co-assembly. The reads mapping to an affiliated
 genomic bin of each target ciliate from the initial binning results were
 re-assembled with IDBA-UD v.1.1.1 to improve bin quality. CheckM was used
 to evaluate the completeness, contamination and taxonomy of genomic bins,
 as well as to identify rRNA gene sequences. Additional metagenomic reads
 from <i>Muranothrix gubernata</i> SUMMARTIN, sequenced
 subsequently in order to obtain mitochondrial genome from Muranotrichea,
 were quality trimmed using Trimmomatic v0.39, corrected by Rcorrector and
 assembled using Metaspades (SPAdes genome assembler v3.13.1) with default
 settings for paired-end reads in "only-assembler" mode. Contigs
 representing mitogenomes were identified in metagenome assemblies by BLAST
 using available protein sequences from ciliate mitogenomes as a query
 (GU057832.1, JN383843.1, NC_014262.1). Subsequently, we used manual
 approach based on iterative searches in Illumina reads (BLASTN) followed
 by read alignment to the corresponding contig (Geneious Prime; “map to
 reference” option) to unambiguously extend the longest
 <i>Parablepharisma </i>sp.<i> </i>mitogenome
 fragment. This resulted in 41,931 bp long sequence (opposed to original
 contig length 35,877 bp). Initial annotations of mitogenome sequences were
 obtained using MFannot (online version from October 23, 2019). Predicted
 genes recovered by MFannot (including hypothetical proteins) were
 individually checked to confirm/reveal their identity and to exclude
 possible bacterial contamination using BLAST against the nr GenBank
 database. Graphical genome maps were produced by OrganellarGenomeDRAW
 (OGDRAW) v1.3.1. For transcriptomic data, quality trimming and Illumina
 adapter and sequence contamination removal was done using the program
 Trimmomatic. Transcriptomes were assembled using the software package
 Trinity. <b>Datasets preparation and rRNA gene
 phylogenetic analyses</b> Two data sets,
 containing 18S rRNA gene sequences/18S and 28S rRNA gene sequences
 concatenated using Mesquite [86], consisted of 17/2 newly determined
 sequences of Muranotrichea and Parablepharismea, 1/2 newly determined and
 24/0 GenBank sequences of Metopida (Armophorea), 12/1 GenBank sequences of
 Clevelandellida (Armophorea), 3/0 GenBank sequences of Armophorida
 (Armophorea), 8/6 GenBank sequences of Litostomatea, 28/31 GenBank
 sequences of Spirotrichea <i>sensu lato</i>, 2/1 GenBank
 sequences of Odontostomatea, 1/0 GenBank sequence of Cariacotrichea, and
 41/41 GenBank sequences of other ciliates (CONThreeP, Protocruziiea,
 Heterotrichea, Karyorelictea) used as outgroup. Environmental GenBank
 sequences KT346287 and KT346288, affiliated as related to the newly
 described taxa by BLAST, were excluded from the analyses due to chimeric
 origin. The sequences were aligned using MAFFT on the MAFFT 7 server
 (http://mafft.cbrc.jp/alignment/server/) with L-INS-i algorithm and
 default settings. The alignments were manually checked for chimeras and
 edited using BioEdit 7.0.9.0. 18S rRNA, and concatenated 18S and 28S rRNA
 phylogenetic trees were constructed by maximum likelihood (ML) and
 Bayesian analyses. ML analyses were performed in RAxML 8.0.0 under the
 GTRGAMMAI model with 1000 rapid bootstraps. Node support was assessed by
 ML analysis of 1000 bootstrap data sets. Bayesian analyses were performed
 using Phylobayes with GTR CAT. For 18S rRNA gene, four independent chains
 were run for 34,720 generations (maxdiff = 0.0531, 20% burnin). For
 concatenated 18S and 28S rRNA genes, four independent chains were run for
 150,000 generations (maxdiff = 0.14, 20% burnin).
 <b>Phylogenomic
 analyses</b> Extensive
 phylogenomic datasets of ciliates, containing ~160 and 124 genes,
 respectively, were used as reference datasets. Up to five best hits were
 recovered (E-value &lt; 1E-5) for each gene from the
 <i>Muranothrix</i> transcriptome using BLAST and translated
 into protein sequences using the Barrel-O-Monkeys package (http://rogerlab.biochemistryandmolecularbiology.dal.ca/monkeybarrel.php). In the case of metagenomes, genes of interest were recovered using in-house script (https://github.com/DavidZihala/raw_gene_prediction?fbclid=IwAR2xbkMEUe8Fvl2A_6uJF2r4oT9IJWx7iopVQMxjqgows5VcxsXTYCi5lP8). Each recovered sequence was then reciprocally blasted against reference datasets enriched with well-defined known paralogs (e.g., EF-1α and EFL) to assist in the identification and removal of deep-paralogs. BLAST searches against the Swissprot database was used to trim away non-homologous sequence data at the end of predicted genes. Subsequently, all sequences were added to single-gene alignments. These were then aligned using the MAFFT-LINSI algorithm (with default parameters), trimmed in BMGE (gap threshold set to 0.3) and single gene trees were reconstructed using RAxML (model setting PROTGAMMALGF) with 100 rapid bootstraps. Single gene trees were then investigated by eye and proper orthologs were selected from targeted taxa, while putative paralogs were removed, creating final version of the single gene datasets. Each single gene dataset was then aligned by MAFFT LINSI algorithm (with default parameters), followed by trimming using BMGE v 1.2 (gap threshold set to 0.3). Trimmed alignments were then concatenated into one super-matrix using the program alvert from the Barrel-O-Monkeys package. The maximum likelihood phylogenomic tree was constructed in IqTree using the C40+LG+F+G model with 1000 PMSF bootstraps. Bayesian analysis was performed using Phylobayes with CAT-GTR+G with constant sites removed. Four independent chains were run for 16,000 generations (maxdiff = 0.002, 20% burnin). <b><i>In-silico</i></b><b> predictions of mitochondrial metabolism</b> Genes of interests were collected from previously published studies of anaerobic mitochondria and from the published mitochondrial proteome of <i>Tetrahymena thermophila</i>. Candidate sequences from ciliates were recovered by blast and hits with e-value &lt; 1e-10 were extracted and added to the initial datasets for each gene. Published datasets were used as starting datasets, where available. When a published dataset was not available, starting datasets were constructed by blast searches of a seed sequence against nr (max target seqs = 100). Additionally, sequences from taxonomically diverse eukaryotic and prokaryotic representatives identified through searches of the gene name in NCBI protein and RefSeq databases. The resulting sequences were combined into a single dataset and clustered in CD-Hit at 75%. Each gene dataset was aligned using MAFFT-LINSI (default settings), trimmed using trimal (gappyout) and trees were constructed using RAxML (PROTGAMMALG with 100 rapid bootstraps). Each alignment/tree has been repeatedly inspected by eye and sequences were added/removed as necessary. Each tree was then manually evaluated for presence absence of genes of interest in studied lineages.
description: <strong>Single gene datasets for phylogenomic
 analysis:</strong> AAC1.faa ACO.faa ACS_ab1.faa
 ACS_ab2.faa ALT.faa AOX.faa ArcA.faa ASCT_1A.faa
 ASCT_1C.faa AST.faa ATM1.faa Atp1.faa Atp12.faa Atp2.faa
 Atp3.faa Atp5.faa Atp9.faa BCKDHa.faa BCKDHb.faa CBS.faa
 cox19.faa cox5b.faa cyt_c1.faa DHFS.faa Fd.faa FKBP.faa
 FtsH.faa FUM.faa G3PD.faa GCSH.faa GCSL.faa GCSP1.faa
 GCSP2.faa GCST.faa GDH.faa GR.faa hAAC.faa Hcp.faa
 hmp31.faa HscB.faa hsp10.faa hsp40.faa hsp60.faa hsp70.faa
 hsp90.faa HydA.faa IND1.faa IscA2.faa IscS.faa IscU.faa Isd11.faa
 KBL.faa MAS5.faa MC.faa MCF.faa MDH.faa ME.faa MMM.faa
 MOC.faa MPPa.faa NAD11.faa NuoE.faa NuoF.faa OGDH.faa
 PCCa.faa PCCb.faa PDH-E1a.faa PDH-E1b.faa PDHe2.faa
 PDI.faa Pet8.faa PrA.faa PRX.faa PSAT.faa Rieske.faa SCSa.faa
 SCSb.faa SDHa.faa SDHb.faa SHMT.faa SOD_Fe.faa SOD_Mn.faa
 TOM34.faa TPN.faa TXN.faa
   <strong>Protein datasets for
 prediction of mitochondrial pathways:</strong>
 ar21.fas arc20.fas capz.fas cct-A.fas cct-B.fas cct-D.fas
 cct-E.fas cct-G.fas cct-N.fas cct-T.fas cct-Z.fas
 cpn60.fas crfg.fas fh.fas gdi2.fas glcn.fas grc5.fas
 Gtub.fas hmt1.fas HSP70C.fas HSP70-E.fas hsp70mt.fas
 HSP90.fas if2b.fas if2g.fas if2p.fas if6.fas ino1.fas l12e-A.fas
 mcm-A.fas mcm-B.fas mcm-C.fas mcm-D.fas mcm-E.fas
 mcm-F.fas metap2.fas mra1.fas nsf1-E.fas nsf1-G.fas
 nsf1-I.fas nsf1-J.fas nsf1-K.fas nsf1-L.fas nsf1-M.fas
 nsf2-B.fas nsf2-F.fas oplah.fas orf2.fas pace2-A.fas pace2B.fas
 Pace2C.fas pace5.fas psma-A.fas psma-B.fas psma-C.fas psma-D.fas
 psma-E.fas psma-G.fas psma-H.fas psma-I.fas psma-J.fas
 psmb-K.fas psmb-L.fas psmb-M.fas psmb-N.fas psmd.fas
 rad23.fas Rad51A.fas rf1.fas rla2a.fas rla2b.fas
 rpl11.fas rpl12.fas Rpl13A.fas Rpl13e.fas Rpl15.fas Rpl18.fas
 rpl20.fas rpl21.fas rpl26.fas Rpl3.fas rpl30.fas rpl32.fas
 rpl33.fas rpl35.fas rpl43.fas rpl44.fas Rpl4b.fas
 Rpl5.fas rpl6.fas rpl9.fas rpo-A.fas rpo-C.fas rppO.fas
 rps10.fas rps11.fas rps14.fas rps15.fas rps16.fas
 rps17.fas rps18.fas rps20.fas rps23.fas rps26.fas rps27.fas
 rps3.fas rps4.fas rps5.fas rps6.fas rps8.fas s15a.fas s15p.fas
 sap40.fas sra.fas srp54.fas srs.fas suca.fas tfiid.fas
 topo1.fas trs.fas vata.fas vatb.fas vatc.fas
 wrs.fas  
 <strong>Mitochondrial genomes:</strong>
 HeterometopusCSS_scaffold_52.gb
 Heterometopus_scaffold_11415.gb
 Metopus_SK_scaffold_139.gb
 summartin_part4_RC_12800bp_curated.gb
 summartin_part2_6617bp_curated.gb
 summartin.part1_4655bp_curated.gb
 parablepharisma.2.gb
 parablepharisma.1.gb