Chimeric Origin and Dynamic Evolution Central Carbon Metabolism in Eukaryotes
Creators: name: Santana-Molina, Carlos
name: Tom A. Williams
name: Snel, Berend
name: Spang, Anja
Publisher: name: Zenodo
Year: 2024
Subjects: subject: eukaryogenesis
subject: central carbon metabolism
subject: Molecular evolution
subject: Glycolysis
subject: Pentose Phosphate pathway
subject: TCA cycle

description: Abstract

The origin of eukaryotes was a key event in the history of life and is thought to have been the result of a symbiotic interaction between at least two partner organisms: an asgardarchaeal host and an alphaproteobacterial symbiont giving rise to the mitochondria. It is generally assumed that informational processing and operational genes originated from the archaeal  and bacterial partner(s), respectively, with the eukaryotic metabolism being primarily of bacterial origin. This is seemingly at odds with symbiogenetic models which generally hypothesize that syntrophic interactions were a key driver for eukaryogenesis. For example, under syntrophy scenarios, it may be expected that both the host and symbiont contributed to major metabolic pathways of eukaryotes such as the central carbon metabolism (CCM). Here, we systematically analyse the evolutionary origins of the eukaryotic CCM. Our phylogenetic and sequence analyses reveal that the eukaryotic CCM has diverse origins including asgardarchaeal contributions. Furthermore, the evolution of the eukaryotic CCM post-LECA is highly dynamic due to gene gain and losses and organelle targeting, as well as correlated with eukaryotic lifestyles. Our work suggests that metabolic gene families preserve important information on eukaryotic evolution and support syntrophy scenarios on the origin of the eukaryotic cell.

CCM_phylogenies/

This folder includes the data for the phylogenetic trees of central carbon metabolism enzymes.  Each folder contains sequences, multiple sequence alignments (raw and trimmed), and respective phylogenetic trees (*treefile and *log files). Descriptions of the subfolders:

 





seqs/original_seqs, contains the original sequences from the core dataset (local dataset of 483 archaea, 487 bacteria and 224 eukaryotic proteomes). 



 





seqs/clean_seqs, contains the sequences after cover alignment filtering (MSA cover > 80%), and visual inspection of MSA for removing poorly aligned sequences. 



 





01.initial/, contains the final sequences, MSAs and phylogenetic trees made through automatic pipeline (see Scripts). Final MSAs were obtained through Mafft-L-INS-i, trimmed with trimAl (-gt 0.7), and trees were constructed with IQ-TREE using LG empirical models (-mset LG) and mixture models (-m  LG+C20+G+F), corrected ultrafast bootstraps, SH-aLRT test, and additional parameters (-bb 1000 -bnni -alrt -nstop 500 -pers 0.2). 



 









01.initial/strict_trimming_for_sistergroups/preliminary_phase/, contains the data for the final trees of preliminary phase, based on the core dataset. MSA cover allowed higher than 80%. 





 









01.initial/strict_trimming_for_sistergroups/expanded_phase/, contains the data for the final trees of expanded phase, based on the addition of sequences obtained from HMMSEARCHES of LECA groups against expanded dataset (NCBI Prokaryotes and Viruses; see methods). MSA cover allowed higher than 80%. These trees were used for the identification of the sister groups of eukaryotic clades (Figure 2, and Supp. Figures 3-20, with some exceptions, see 02.remade)





 









01.initial/inclusive_trimming_for_profile/,  contains the data for the final trees of expanded phase, including eukaryotic sequences that were filtered out in previous analyses. MSA cover allowed for eukaryotic sequences included higher than 20%. These trees were used for the taxonomic composition of the eukaryotic orthogroups shown in the phylogenetic profile (Figure 3). 





 





02.remade/, contains the data for phylogenetic trees that required further phylogenetic analyses like subtree selection, addition of gene families, Pfam domain phylogenies (eg. PFK), concatenation (eg. ACLA-B-Y) or separation of domains (eg. ACDA-B). These include the following enzymes: ADPGK, GLK-HK-ROK, PFK, PK, TPI, EDD-EDA, H6PD-G6PD, TAL-TKT, ACD, PDHD, POR, ACL-A-B-Y, ACEA, ACO, FUM, IDH, LSC, SDH and MDH/LDH. 



 





03.introns/, contains the data for inferring shared introns within or between protein families. This includes the original MSAs generated with MAFFT L-INS-i, and the files generated with imapper containing the information for the introns in the MSA. single_read_intron.py and multi_read_intron_distribution_LECA.py scripts, were used to identified those positions with relevant abundance of introns, for a single family (eg. GPI or PGD) and various families (eg ACS, MDH1/2) respectively. 



 

eToL_phylogenies/

This folder contains the data for reconstructing the eukaryotic tree of life based on the concatenation of 317 phylogenetic markers in 207 eukaryotes. 

 





eToL_phylogenies/marker_hmms/, contains protein Hidden-Markov models (HMM) used for searching phylogenetic markers. Original sequences were obtained from previous studies (Strassert et al, 2020), sequences were obtained through Mafft-L-INS-i and trimAl (-gt 0.4) and HMMBUILD. 



 





eToL_phylogenies/markers_final_seqs/, contains final orthologous sequences for 317 phylogenetic markers obtained through three phylogenetic rounds and manual inspections. 



 





eToL_phylogenies/markers_final_MSA_TREES/, contains final MSAs and phylogenies of individual phylogenetic markers. MSAs were obtained though Mafft-L-INS-i, trimmed with BMGE (-h 0.55) and trees were built with IQ-TREE (-mset LG -madd LG+C10,LG+C20,LG+C10+R+F,LG+C20+R+F --score-diff all -wbtl -bb 1000 -bnni). 



 





eToL_phylogenies/CONCATENATION/, contains data for the phylogenetic analyses of the concatenation of 317 markers. 



 





eToL_phylogenies/CONCATENATION/heterogenenous_sites, contains the full (only BMGE -h 0.55 on individual MSAs) and the trimmed concatenated MSA (from 0.1 to 0.9 of heterogeneity thresholds using https://github.com/novigit/davinciCode/blob/master/perl/alignment_pruner.pl) and respective files generated with IQ-TREE (*log, *treefile, ufboot). Trees were made through IQ-TREE (-mset LG -madd LG+C60 --score-diff all -wbtl -bb 1000). iq.ALL_207-bnni.* files correspond to the tree shown in Figure 1 with optimized bootstrap analyses and setting gamma distributions (adding -bnni and LG+C60+G options to the previous command). 



 

Scripts/

This folder contains the scripts and jupyter notebooks for different methodology steps. 

 





contaminations, contains the data for the orthologous clustering generated with Broccoli, and the jupyter notebook with ETE script for detecting the contaminations (see Methods in original manuscript). 



 





declusterization_MMSEQS_clusters, contains python script read_clusters_mmseqs_declusterization.py, for correcting flawed clusters generated by MMSEQS (options easy-cluster, --cluster-mode 2, --cov-mode 1, -c 1 --min-seq-id 0.95). See README.txt file for execution. 



 





extended_searches_and_phylogenies, contains scripts for making extended searches against local database of NCBI proteomes with GTDB taxonomy. This database also contained viruses with the respective NCBI taxonomy (referred in the main text as expanded dataset). See README.txt file for execution. 



 





phylogenetic_profile_data,  contains the jupyter notebook for analyzing the orthogroups  and the respective sister groups identified in the carbon metabolisms gene trees. 






COMBINED, contains the list of sequences forming eukaryotic orthogroups per each KO. Name of the orthogroups are defined by ‘#’ and indicate  GENENAME_KO-LECA/postLECA-DomainDonor(B/A)-MainTaxonomy (eg. HK_K00844-LECA-B-U; U means unknown). Note that the names of orthogroups are descriptive, see supplementary text for additional discussion. 




COMBINED_SISTERGROUP,  contains the information of the unique sister group of the respective orthogroup (exclusively for potential LECA clades).




COMBINED_consortium, contains the information of the closely related sister groups of the respective orthogroup (exclusively for potential LECA clades).




 



 GPI_partitions, contains the data for analyzing UfBoot2 across GPI’s MSA partitions. The MSA partitions were generated with range_MSApartitions.py script. The phylogenies of individual partitions were performed with IQ-TREE using empirical (LG+G+F) and mixture model (C20+G+F), and the Ufboot2 values for given monophyletic relationships were inferred using the script at Read_UfBoot2_GPI_partitons.ipynb jupyter notebook.