Mitochondrial ribosomes (mitoribosomes) are essential for the production and maintenance of the electron transport chain machinery. As with all other ribosomes, the biogenesis of mitoribosomes involves a complex series of coordinated steps during which the ribosomal RNA (rRNA) folds, proteins are incorporated and the active site is formed. The process is facilitated by specific biogenesis factors, including GTPases, rRNA modifying enzymes, RNA helicases, ribonucleases, chaperones, and other scaffolding and adaptor proteins (De Silva et al., 2015). Studying this process in molecular detail is clinically important because defective mitoribosome assembly can lead to encephalomyopathy, optic neuropathy, cardiomyopathy, and hereditary spastic paraplegia, among other disorders.

The general principles of ribosome assembly are well-conserved across species, but mitoribosome assembly has diverged in notable ways from, and involves different factors than bacterial 70S ribosomes. Analogous to bacterial and eukaryotic cytosolic ribosomes, mitoribosome assembly also proceeds via a series of quality-control checkpoints and GTP hydrolysis serves as the commitment step to drive the reaction forward (Britton, 2009; Karbstein, 2007). Four GTPases, GTPBP5, 6, 7, and 10 (and perhaps GTPBP8; Maiti et al., 2021) directly bind the 16S rRNA of the 39S mitoribosomal large subunit (mtLSU) to facilitate its maturation (Kotani et al., 2013), but their mechanistic roles and order of action remain poorly understood. Here, we present the cryo-electron microscopy (cryo-EM) structure of the human mtLSU in complex with GTPBP7, an RNA methyltransferase NSUN4 and an RNA scaffolding protein MTERF4, establish the importance of this complex during mitoribosome biogenesis in vivo and decipher the mechanism by which NSUN4·MTERF4·GTPBP7 ensure maturation of the peptidyl transferase center (PTC) of the mitochondrial ribosome.

To trap GTPBP7 and other GTPases that participate in human mitochondrial translation, we included the non-hydrolyzable GTP analog β,γ-methyleneguanosine 5′-triphosphate (GMPPCP) during mitoribosome purification. Single-particle cryo-EM (Figure 1—figure supplement 1, Figure 1—figure supplement 2, Table 1) of these and other mitoribosome-bound complexes (Desai et al., 2020) also yielded a 5% subset of mtLSU intermediates bound to GTPBP7·GMPPCP in a pre-hydrolysis state and arrested at an assembly state equivalent to the 45S (RI₅₀) to 50S transition of the bacterial LSU (Achila et al., 2012; Fahnestock et al., 1973; Seffouh et al., 2019). In this state, the PTC is not completely disordered as it is in PDB 5OOM, an earlier late assembly state (Brown et al., 2017), but key helices in the vicinity are held in an unfolded state.

Surprisingly, GTPBP7 was bound to a heterodimer of the 5-methyl cytosine (m⁵C) modifying enzyme, NOP2/Sun RNA methyltransferase 4 (NSUN4) and its binding partner, mitochondrial transcription termination factor 4 (MTERF4) (Cámara et al., 2011; Figure 1). NSUN4, MTERF4, and GTPBP7 bind the inter-subunit interface of the mtLSU in a radial arrangement centered about the peptidyl site (P site) and <30 Å from the PTC (Spåhr et al., 2012). Additionally, the anti-association factors MALSU1·L0R8F8·mt-ACP are also present on these particles to prevent premature SSU joining (Brown et al., 2017; Desai et al., 2020).

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The NSUN4 active site contains weak density for the methyl donor S-adenosyl methionine (SAM). Moreover, the cryo-EM density suggests that there is no m⁵C methylation of 16S rRNA located within ~20 Å of the NSUN4 active site indicating that methyltransferase activity is not involved at the mtLSU assembly checkpoint. Bisulfite sequencing studies across many species have also not revealed any m⁵C targets on the 16S rRNA, making this an unlikely site of NSUN4 methyltransferase activity (Metodiev et al., 2014).

Our structure represents an intermediate in which the proteins uL16m, bL27m, and bL36m have already bound, but before complete folding of rRNA domain IV helices 68–71 and dissociation of NSUN4, MTERF4, and GTPBP7 by GTP hydrolysis, and subsequent small subunit (mtSSU) joining. The 16S rRNA domain IV helices 68–71 (nucleotides 2542–2637) typically span the A, P, and E sites and pack against the D-loop, and anticodon arms of the P-site tRNA (Figure 2). Here, they are instead held in a partially unfolded state by MTERF4 at a location that would permit biogenesis factors to access to their binding sites, but clash with an incoming SSU (Figure 2C). Subsequent GTP hydrolysis by GTPBP7 would result in dissociation of the GTPase and MTERF4·NSUN4, allowing H68–71 to fold (compare Figure 2C,D).

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RbgA, the bacterial homolog of GTPBP7, facilitates the incorporation of the mitoribosomal protein bL36m into the mtLSU (Britton, 2009; Kotani et al., 2013; Figure 2—figure supplement 1). On the other hand, two other ribosomal proteins uL16m and bL27m, whose incorporation in bacteria is also attributed to RbgA, are already present in an earlier assembly intermediate (PDB 5OOM). We suspect that this difference is likely because only two GTPases (ObgE being the other) regulate bacterial 50S assembly while at least four are implicated in ribosome assembly in human mitochondria (Maiti et al., 2021). Remarkably, GTPBP7 binds in the vicinity of 2′-O-methylated bases in the A and P loops of the PTC, which are critical rRNA elements that bind the aminoacyl and peptidyl tRNAs, respectively. Our structure reveals that the A and P loops move toward GTPBP7 and NSUN4, respectively, relative to their positions in the mature 55S (Figure 2—figure supplement 2) and His 34 of helix 1 of GTPBP7 directly contacts the highly conserved U3039 to verify 2′-O-methylation by mitochondrial methyltransferase 2 (MRM2) (Figure 2B; Lee and Bogenhagen, 2014). Given the universal importance of 2′-O-methylation of specific nucleotides in the PTC for translation (Pintard et al., 2002; Rorbach et al., 2014), it is striking that GTPBP7 directly contacts Um3039. In principle, slight rearrangements of helix 1 of GTPBP7 could also ensure G3040 methylation by MRM3. Similarly, G2815 (in the P loop), which is 2′-O-methylated by MRM1 (Lee and Bogenhagen, 2014; Rorbach et al., 2014) is in the vicinity of NSUN4 and GTPBP7 in our structure (Figure 2—figure supplement 2). We propose that GTPBP7 ensures 2′-O-methylation of these residues by coupling GTP hydrolysis and subsequent GTPBP7 egress from the 39S to its interaction with the methylated bases.

GTPBP7, MTERF4, and NSUN4 are highly conserved and their counterparts in Caenorhabditis elegans are MTG-1 (33% identical), MTER-4 (21%), and NSUN-4 (34%), respectively. In C. elegans, the methyltransferase activity of NSUN4 for mitochondrial protein synthesis was shown to be dispensable (Navarro et al., 2021), suggesting that its importance may instead lie in its interaction with the conserved core of the mtLSU. To test the importance of complex formation of the three protein factors with the mtLSU during assembly in vivo, we used C. elegans as a model organism and introduced mutations at locations in the three factors that we predicted would disrupt binding to the mtLSU without affecting expression, mitochondrial targeting or protein folding (Figure 3A, Figure 3—figure supplement 1, Figure 3—figure supplement 2).

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Mutations that disrupt mitoribosome binding to MTER-4 (MTER-4^{R178E,K262E,R263E}) and MTG-1 (MTG-1^{R171E,K178E,K180E}; the C. elegans orthologs of MTERF4 and GTPBP7, respectively), led to a substantial increase in the expression of the mitochondrial heat-shock protein HSP-6, consistent with activation of the mitochondrial unfolded protein response (Figure 3A). These findings are similar to the effects observed when mitochondrial ribosomal proteins are knocked down by RNAi (Houtkooper et al., 2013). By contrast, we found that mutations that disrupt the catalytic activity of NSUN-4 did not substantially activate hsp-6 expression (Figure 3A, NSUN-4 cd), nor did mutations that disrupt a weak contact between NSUN-4 and the mitoribosomal protein bL33m, NSUN-4^M225A,K226A. These results are consistent with the catalytic activity of NSUN-4 being dispensable for mitochondrial protein synthesis. However, NSUN-4 makes multiple contacts with the mitoribosome and the chosen M225A and K226A substitutions in NSUN-4 were likely insufficient to disrupt its interaction with the mitoribosome. We therefore introduced the additional mutations L286Y and A287Y, resulting in a dramatic mitochondrial stress response (Figure 3A, compare nsun-4^M225A,K226A and nsun-4^{M225A,K226A,L286Y,A287Y}). Therefore, disrupting NSUN-4, MTER-4, or MTG-1 binding to the conserved core of the mitoribosome potently activates mitochondrial stress, underscoring their importance during mitoribosome biogenesis.

To test whether these mutations weaken 39S binding and to rule out the possibility that the observed mitochondrial stress phenotypes result from off-pathway consequences such as gene silencing, protein misfolding, or mistargeting, we sought to quantify the total- and ribosome-bound NSUN-4, MTER-4, and MTG-1 levels in mutant strains relative to wild-type worms. Given the absence of antibodies against these proteins, we had to resort to a suitable alternative method of quantification. Tandem mass tag-mass spectrometry (TMT-MS) permits accurate quantification of changes in global protein levels between multiple strains in parallel (Zhang and Elias, 2017). Total protein extracts as well as total ribosomes (cytosolic and mitochondrial) from wild-type, nsun-4^M225A,K226A or mter-4^{R178E,K262E,R263E} worms were extracted and labeled in duplicate (yielding a total of 12 samples) using isobaric tags and analyzed by TMT-MS (Figure 3—figure supplement 3, Supplementary file 3).

The data sets were normalized between samples on cytosolic ribosomal protein levels following the reasonable assumption that manipulations to mitochondrial ribosome assembly/recycling factors do not affect cytosolic ribosomal protein levels. The results show that the levels of MTG-1, NSUN-4, and MTER-4, as well as the ribosomal proteins eL13 and mL53, are comparable to wild-type worms (1.05- to 1.57-fold; Supplementary file 3) in both nsun-4^M225A,K226A and mter-4^{R178E,K262E,R263E} worms (Figure 3—figure supplement 3, top), arguing against gene silencing, misfolding, or mistargeting of the designed mutants. This conclusion is also supported by the well-folded structures predicted by AlphaFold 2 (Figure 3—figure supplement 2; Jumper et al., 2021).

Mutating the mitoribosome binding surfaces of NSUN-4 or MTER-4 also significantly reduced their levels in the total ribosome fraction (63% and 86%, respectively) in mter-4^{R178E,K262E,R263E} worms. As expected, the reductions were more modest (84% and 98%, respectively) in nsun-4^M225A,K226A worms, which harbor more conservative mutations (Figure 3—figure supplement 3, bottom) and therefore also exhibit subtler stress responses (Figure 3A). More dramatic reductions would require all three proteins to be mutated simultaneously in the same strain, which was not done because these individual mutants already cause severe developmental defects, sterility, and poor viability. Taken together, the TMT-MS results confirm that the mitochondrial stress phenotypes are a direct consequence of disrupting the NSUN-4·MTER-4·MTG-1 complex and that these proteins play a crucial checkpoint role during mitoribosome biogenesis.

At the organismal level, destabilizing 39S binding by MTG-1 and MTER-4 resulted in delayed animal development and sterility (Figure 3B,C). Specifically, we found that mter-4 mutants exhibited delayed development and 14% of mutants were sterile (Figure 3B,C). Similarly, we observed a more severe phenotype in mtg-1 mutants and found that 100% of homozygous mtg-1 mutants were sterile (Figure 3B). The severity of the phenotypes of the nsun-4, mter-4, and mtg-1 mtLSU binding mutants underscores the importance of the role of NSUN4/NSUN-4, MTERF4/MTER-4, and GTPBP7/MTG-1 in the mitochondrion. In addition, our results suggest that the effects of disrupting GTPBP7/MTG-1 and MTERF4/MTER-4 interactions with the mitoribosome can be overcome in somatic tissues, potentially by activating the mitochondrial unfolded protein response, as mutant animals can indeed develop to adulthood. Germ cells, however, were particularly sensitive to these mutations, and disruption of mtLSU binding caused sterility. Notably, mutations in mitochondrial translational components, including mitochondrial tRNAs, are known to cause sterility in humans (Demain et al., 2017). We suggest that germ cell sensitivity to disruptions in mitochondrial translation is a conserved phenomenon throughout metazoans and establish a new model to study these effects.

To further confirm the effects of disrupting the interaction of these proteins with the mitoribosome, we performed next-generation RNA sequencing on the viable mter-4 mutants. We identified 3174 differentially expressed genes (DEGs) in mter-4 mutants when compared to wild-type animals (Supplementary file 1). Furthermore, we found that the genes upregulated in mter-4 mutants are enriched for genes associated with mitochondrial dysfunction and substantially overlap with genes that are upregulated in electron transport chain mutants (Yee et al., 2014; Figure 3D,E). These results support our structural data and further suggest that disrupting the interaction of these proteins with the mitoribosome activates the mitochondrial unfolded protein response and disrupts normal mitochondrial function.

We have previously reported the cryo-EM structures of two human late-stage mitoribosomal assembly intermediates (Brown et al., 2017). One intermediate (PDB 5OOM) lacks bL36m, contains the anti-association factors MALSU1·L0R8F8·mt-ACP, and awaits folding of ~20% of the 16S rRNA, including the entire PTC. The second intermediate (PDB 5OOL) comprises fully matured 16S rRNA and all ribosomal proteins, but is incompetent for subunit joining because the anti-association factors are still present. Several events must therefore occur around these intermediates, and the order of events can be inferred from the reasonable assumption that assembly proceeds outwards from the core of the mtLSU to the inter-subunit interface (Video 1). (a) bL36m must bind the mtLSU and pack against the folded domain V helices H89–93; (b) the only remaining domain II helices H34–35 must fold; (c) H65–67 of domain IV can also then fold; and finally, (d) H68–71 of domain IV can fold to yield a mature PTC. PTC maturation also includes the universally conserved and essential modifications to incorporate pseudouridine Ψ3067 by RNA pseudouridine synthase (RPUSD4) and 2′-O-methylation at Gm2815, Um3039, and Gm3040 by mitochondrial methyltransferases1-3 (MRM1-3), respectively. These modifications likely happen in concert with the above steps.

Video 1

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A comprehensive review of GTPases in human mitoribosomal assembly (Maiti et al., 2021) and four studies describing cryo-EM structures of mtLSU late assembly intermediates distinct from ours and from each other (Cheng et al., 2021; Cipullo et al., 2021; Hillen et al., 2021; Lenarčič et al., 2021), appeared during manuscript preparation. All five studies, including ours, have trapped MALSU1·L0R8F8·mt-ACP and NSUN4·MTERF4 at the same location on the mtLSU. The studies, however, differ notably in the precise step during assembly, the biogenesis factors recruited, and finally, the GTPase in control. The deleterious consequences of manipulating NSUN4 or MTERF4 binding to the mitoribosome in vivo illustrate the importance of these proteins in mediating not only the exact step during PTC maturation that we have trapped, but also the prior and subsequent steps described in Cheng et al., 2021; Cipullo et al., 2021; Hillen et al., 2021.

When taken together, these cryo-EM structures permit piecing together the order of events during the late-stage maturation of the mtLSU (Figure 4). The anti-association factors MALSU1, L0R8F8, and mt-ACP engage the mtLSU during early assembly of the mtLSU (Brown et al., 2017; Cheng et al., 2021). At this stage, ribosomal proteins bL27m and uL16m have already been incorporated (state I). GTPBP10, MRM3, and DDX28 hold the PTC helices H89–93 and the central protuberance H80–88 in an immature state (Figure 4, state II) (Cheng et al., 2021). Following dissociation of these factors, the central protuberance matures and bL33m and bL35m are incorporated to result in state III (Brown et al., 2017; Cheng et al., 2021).

Figure 4

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MTERF4 binds to and holds open H68–71 in an unfolded state and recruits NSUN4 to the mtLSU (Cámara et al., 2011). The ribosomal protein bL36m is incorporated, and MRM2 and GTPBP5 also then bind to 2′-O-methylate U3039 in the A loop and assist with H89–93 maturation (state IV) (Cipullo et al., 2021). Curiously, GTPBP7 is also present in state IV, but at a different location than in our structure. The close proximity of helices H34–35 and H65–67 to this location leads us to propose that GTPBP7 binds here to ensure that these helices have folded. GTPBP6, whose binding to the mtLSU is incompatible with the presence of NSUN4 (Hillen et al., 2021), displaces NSUN4 and GTPBP5 and helps to further mature the PTC (state V).

Next, GTPBP7, which was not actually seen in state V (Hillen et al., 2021), dissociates and repositions to the location on the PTC seen in our study (state VI). It then re-recruits NSUN4•MTERF4 and together NSUN4·MTERF4·GTPBP7 unfold H68–71 and check U3039 methylation and proper maturation of the PTC by the actions in the prior states III–V. This hypothesis if correct, would be consistent with (i) the dual roles of GTPBP6 during mitoribosome biogenesis and recycling (Hillen et al., 2021; Lavdovskaia et al., 2020), and (ii) the intriguing idea that not only GTPBP6 (Hillen et al., 2021) and MALSU1·L0R8F8·mt-ACP (Desai et al., 2020), but also NSUN4·MTERF4·GTPBP7 may have dual roles during mitoribosome recycling after termination and perhaps rescue.

This idea is supported by the facts that (i) we trapped our intermediate from Pde12 knockout (KO) cells which are a model for ribosome stalling (and subsequent recycling) (Desai et al., 2020; Pearce et al., 2017), (ii) during mitoribosome recycling, GTPBP6 rearranges the PTC of the 39S to a slightly immature state that could require subsequent checking by GTPBP7 (Hillen et al., 2021; Lavdovskaia et al., 2020), (iii) GTPBP7 is also involved in 39S–28S subunit joining (Kim and Barrientos, 2018; Maiti et al., 2021).

Given that we trapped GTPBP7 using the non-hydrolyzable GMPPCP, GTPBP7 may then dissociate upon GTP hydrolysis, eject NSUN4·MTERF4, thus allowing H68–71 to refold into the PTC and mediate subunit joining to result in a mature 55S (state VIII) (Amunts et al., 2015). How the anti-association factors dissociate prior to subunit joining is not yet known (Kim and Barrientos, 2018; Maiti et al., 2021).

The pathological significance of GTPBP7, MTERF4, and NSUN4 is demonstrated by their association with cardiomyopathy, which is a common feature of mitochondrial diseases. Cardiomyocyte-specific MTERF4 KO mouse models develop mitochondrial cardiomyopathy, and global KO mice are embryonically lethal (Cámara et al., 2011). Variant alleles of MTERF4 have also been documented in a pediatric patient with hypertrophic cardiomyopathy (Maribel et al., 2018). Similarly, GTPBP7 and NSUN4 silencing in human cardiomyocytes (Kim and Barrientos, 2018) and conditional KO mice have been shown to lead to impaired cardiac physiology and progressive cardiomyopathy (Metodiev et al., 2014), respectively.

Our observations of severe mitochondrial defects and activation of the mitochondrial unfolded protein response in mter-4 mutants, but not nsun-4 catalytic dead mutants, suggest that the major function of these proteins is as a checkpoint in mitochondrial ribosome assembly and not in RNA methylation. Consistent with this idea, MTERF4 does not participate during NSUN4-mediated methylation of the decoding center of the mtSSU (Cámara et al., 2011). We have thus shown, using structure-directed mutagenesis in vivo, that while the methyltransferase activity of NSUN4 on the small subunit can be dispensed with without resulting in a strong phenotype, the protein has a more important non-enzymatic function as a biogenesis factor in the final stages of the formation of the PTC and the tRNA binding sites in the large subunit.

The proper folding of the PTC, the universally conserved active site of the ribosome, along with the tRNA binding sites, is one of the crucial steps in the assembly of the large subunit. We conclude that this assembly occurs in multiple steps, moving from one in which the elements of the PTC are in a highly disordered state to one where they are ordered but not yet finally folded into their final structure in the large subunit. This assembly requires several protein factors to act together to yield the mature ribosomal subunit. By coupling cryo-EM analysis of human mitoribosome assembly intermediates with in vitro and in vivo studies in C. elegans, we have identified the physiological importance of three factors in an essential, conserved late-stage mtLSU maturation checkpoint. Although our studies were specifically on mitoribosomes, given the universally conserved nature of the PTC and its importance to the ribosome, we expect that other domains of life will have a similarly complex and orchestrated process requiring multiple factors to facilitate the formation of the active sites of the large ribosomal subunit.

Cryo-EM movies have been deposited to the EMPIAR database (EMPIAR-10809). Coordinates and maps have been deposited to the PDB (7PD3) and EMDB (EMD-13329), respectively. RNA-seq data is available through NCBI GEO using the accession code GSE169089 and as a supplementary item. Further information and material requests may be made to the corresponding authors.

1. 1. Chandrasekaran V
   2. Desai N
   3. Burton NO
   4. Yang H
   5. Price J
   6. Miska EA
   7. Ramakrishnan V

   (2021) RCSB Protein Data Bank

   ID 7PD3. Structure of the human mitoribosomal large subunit in complex with NSUN4.MTERF4.GTPBP7 and MALSU1.L0R8F8.mt-ACP.

   https://www.rcsb.org/structure/7PD3
2. 1. Price J
   2. Burton NO
   3. Miska EA

   (2021) NCBI Gene Expression Omnibus

   ID GSE169089. mter-4 C. elegans RNA-seq.

   https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE169089
3. 1. Desai N
   2. Yang H
   3. Chandrasekaran V
   4. Kazi R
   5. Minczuk M
   6. Ramakrishnan V

   (2021) Electron Microscopy Public Image Archive

   ID EMPIAR-10809. Single particle cryo-EM of human mitochondrial ribosomes from Pde12 KO cells.

   https://www.ebi.ac.uk/empiar/EMPIAR-10809/
4. 1. Chandrasekaran V
   2. Desai N
   3. Burton NO
   4. Yang H
   5. Price J
   6. Miska EA
   7. Ramakrishnan V

   (2021) Electron Microscopy Data Bank

   ID EMDB-13329. Structure of the human mitoribosomal large subunit in complex with NSUN4.MTERF4.GTPBP7 and MALSU1.L0R8F8.mt-ACP.

   https://www.ebi.ac.uk/pdbe/entry/emdb/EMD-13329

1. 1. Achila D
   2. Gulati M
   3. Jain N
   4. Britton RA

   (2012) Biochemical characterization of ribosome assembly GTPase RbgA in Bacillus subtilis

   Journal of Biological Chemistry 287:8417–8423.

   https://doi.org/10.1074/jbc.M111.331322

   • Google Scholar
2. 1. Adams PD
   2. Afonine PV
   3. Bunkóczi G
   4. Chen VB
   5. Davis IW
   6. Echols N
   7. Headd JJ
   8. Hung L-W
   9. Kapral GJ
   10. Grosse-Kunstleve RW
   11. McCoy AJ
   12. Moriarty NW
   13. Oeffner R
   14. Read RJ
   15. Richardson DC
   16. Richardson JS
   17. Terwilliger TC
   18. Zwart PH

   (2010) PHENIX: a comprehensive Python-based system for macromolecular structure solution

   Acta Crystallographica Section D Biological Crystallography 66:213–221.

   https://doi.org/10.1107/S0907444909052925

   • Google Scholar
3. 1. Afonine PV
   2. Poon BK
   3. Read RJ
   4. Sobolev OV
   5. Terwilliger TC
   6. Urzhumtsev A
   7. Adams PD

   (2018) Real-space refinement in PHENIX for cryo-EM and crystallography

   Acta Crystallographica Section D Structural Biology 74:531–544.

   https://doi.org/10.1107/S2059798318006551

   • Google Scholar
4. 1. Amunts A
   2. Brown A
   3. Toots J
   4. Scheres SHW
   5. Ramakrishnan V

   (2015) The structure of the human mitochondrial ribosome

   Science 348:95–98.

   https://doi.org/10.1126/science.aaa1193

   • Google Scholar
5. 1. Anders S
   2. Pyl PT
   3. Huber W

   (2015) HTSeq--a Python framework to work with high-throughput sequencing data

   Bioinformatics 31:166–169.

   https://doi.org/10.1093/bioinformatics/btu638

   • Google Scholar
6. 1. Biesiada M
   2. Purzycka KJ
   3. Szachniuk M
   4. Blazewicz J
   5. Adamiak RW

   (2016) Automated RNA 3D structure prediction with RNAComposer

   Methods in Molecular Biology 1490:199–215.

   https://doi.org/10.1007/978-1-4939-6433-8_13

   • PubMed
   • Google Scholar
7. 1. Bolger AM
   2. Lohse M
   3. Usadel B

   (2014) Trimmomatic: a flexible trimmer for Illumina sequence data

   Bioinformatics 30:2114–2120.

   https://doi.org/10.1093/bioinformatics/btu170

   • Google Scholar
8. 1. Britton RA

   (2009) Role of GTPases in bacterial ribosome assembly

   Annual Review of Microbiology 63:155–176.

   https://doi.org/10.1146/annurev.micro.091208.073225

   • PubMed
   • Google Scholar
9. 1. Brown A
   2. Rathore S
   3. Kimanius D
   4. Aibara S
   5. Bai X-C
   6. Rorbach J
   7. Amunts A
   8. Ramakrishnan V

   (2017) Structures of the human mitochondrial ribosome in native states of assembly

   Nature Structural & Molecular Biology 24:866–869.

   https://doi.org/10.1038/nsmb.3464

   • Google Scholar
10. 1. Cámara Y
    2. Asin-Cayuela J
    3. Park CB
    4. Metodiev MD
    5. Shi Y
    6. Ruzzenente B
    7. Kukat C
    8. Habermann B
    9. Wibom R
    10. Hultenby K
    11. Franz T
    12. Erdjument-Bromage H
    13. Tempst P
    14. Hallberg BM
    15. Gustafsson CM
    16. Larsson NG

    (2011) MTERF4 regulates translation by targeting the methyltransferase NSUN4 to the mammalian mitochondrial ribosome

    Cell Metabolism 13:527–539.

    https://doi.org/10.1016/j.cmet.2011.04.002

    • PubMed
    • Google Scholar
11. 1. Casañal A
    2. Lohkamp B
    3. Emsley P

    (2020) Current developments in Coot for macromolecular model building of Electron Cryo‐microscopy and Crystallographic Data

    Protein Science 29:1055–1064.

    https://doi.org/10.1002/pro.3791

    • Google Scholar
12. 1. Cheng J
    2. Berninghausen O
    3. Beckmann R

    (2021) A distinct assembly pathway of the human 39S late pre-mitoribosome

    Nature Communications 12:4544.

    https://doi.org/10.1038/s41467-021-24818-x

    • Google Scholar
13. 1. Cipullo M
    2. Gesé GV
    3. Khawaja A
    4. Hällberg BM
    5. Rorbach J

    (2021) Structural basis for late maturation steps of the human mitoribosomal large subunit

    Nature Communications 12:3673.

    https://doi.org/10.1038/s41467-021-23617-8

    • Google Scholar
14. 1. De Silva D
    2. Tu Y-T
    3. Amunts A
    4. Fontanesi F
    5. Barrientos A

    (2015) Mitochondrial ribosome assembly in health and disease

    Cell Cycle 14:2226–2250.

    https://doi.org/10.1080/15384101.2015.1053672

    • Google Scholar
15. 1. Demain LAM
    2. Conway GS
    3. Newman WG

    (2017) Genetics of mitochondrial dysfunction and infertility

    Clinical Genetics 91:199–207.

    https://doi.org/10.1111/cge.12896

    • Google Scholar
16. 1. Desai N
    2. Yang H
    3. Chandrasekaran V
    4. Kazi R
    5. Minczuk M
    6. Ramakrishnan V

    (2020) Elongational stalling activates mitoribosome-associated quality control

    Science 370:1105–1110.

    https://doi.org/10.1126/science.abc7782

    • Google Scholar
17. 1. Ewels P
    2. Magnusson M
    3. Lundin S
    4. Käller M

    (2016) MultiQC: summarize analysis results for multiple tools and samples in a single report

    Bioinformatics 32:3047–3048.

    https://doi.org/10.1093/bioinformatics/btw354

    • Google Scholar
18. 1. Fahnestock S
    2. Erdmann V
    3. Nomura M

    (1973) Reconstitution of 50S ribosomal subunits from protein-free ribonucleic acid

    Biochemistry 12:220–224.

    https://doi.org/10.1021/bi00726a007

    • Google Scholar
19. 1. Hillen HS
    2. Lavdovskaia E
    3. Nadler F
    4. Hanitsch E
    5. Linden A
    6. Bohnsack KE
    7. Urlaub H
    8. Richter-Dennerlein R

    (2021) Structural basis of GTPase-mediated mitochondrial ribosome biogenesis and recycling

    Nature Communications 12:3672.

    https://doi.org/10.1038/s41467-021-23702-y

    • Google Scholar
20. 1. Houtkooper RH
    2. Mouchiroud L
    3. Ryu D
    4. Moullan N
    5. Katsyuba E
    6. Knott G
    7. Williams RW
    8. Auwerx J

    (2013) Mitonuclear protein imbalance as a conserved longevity mechanism

    Nature 497:451–457.

    https://doi.org/10.1038/nature12188

    • Google Scholar
21. 1. Jumper J
    2. Evans R
    3. Pritzel A
    4. Green T
    5. Figurnov M
    6. Ronneberger O
    7. Tunyasuvunakool K
    8. Bates R
    9. Žídek A
    10. Potapenko A
    11. Bridgland A
    12. Meyer C
    13. Kohl SAA
    14. Ballard AJ
    15. Cowie A
    16. Romera-Paredes B
    17. Nikolov S
    18. Jain R
    19. Adler J
    20. Back T
    21. Petersen S
    22. Reiman D
    23. Clancy E
    24. Zielinski M
    25. Steinegger M
    26. Pacholska M
    27. Berghammer T
    28. Bodenstein S
    29. Silver D
    30. Vinyals O
    31. Senior AW
    32. Kavukcuoglu K
    33. Kohli P
    34. Hassabis D

    (2021) Highly accurate protein structure prediction with AlphaFold

    Nature 15:03819-2.

    https://doi.org/10.1038/s41586-021-03819-2

    • Google Scholar
22. 1. Karbstein K

    (2007) Role of GTPases in ribosome assembly

    Biopolymers 87:1–11.

    https://doi.org/10.1002/bip.20762

    • Google Scholar
23. 1. Kim D
    2. Paggi JM
    3. Park C
    4. Bennett C
    5. Salzberg SL

    (2019) Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype

    Nature Biotechnology 37:907–915.

    https://doi.org/10.1038/s41587-019-0201-4

    • Google Scholar
24. 1. Kim H-J
    2. Barrientos A

    (2018) MTG1 couples mitoribosome large subunit assembly with intersubunit bridge formation

    Nucleic Acids Research 46:8435–8453.

    https://doi.org/10.1093/nar/gky672

    • Google Scholar
25. 1. Kopylova E
    2. Noé L
    3. Touzet H

    (2012) SortMeRNA: fast and accurate filtering of ribosomal RNAs in metatranscriptomic data

    Bioinformatics 28:3211–3217.

    https://doi.org/10.1093/bioinformatics/bts611

    • Google Scholar
26. 1. Kotani T
    2. Akabane S
    3. Takeyasu K
    4. Ueda T
    5. Takeuchi N

    (2013) Human G-proteins, ObgH1 and Mtg1, associate with the large mitochondrial ribosome subunit and are involved in translation and assembly of respiratory complexes

    Nucleic Acids Research 41:3713–3722.

    https://doi.org/10.1093/nar/gkt079

    • Google Scholar
27. 1. Lavdovskaia E
    2. Denks K
    3. Nadler F
    4. Steube E
    5. Linden A
    6. Urlaub H
    7. Rodnina MV
    8. Richter-Dennerlein R

    (2020) Dual function of GTPBP6 in biogenesis and recycling of human mitochondrial ribosomes

    Nucleic Acids Research 48:12929–12942.

    https://doi.org/10.1093/nar/gkaa1132

    • Google Scholar
28. 1. Lee K-W
    2. Bogenhagen DF

    (2014) Assignment of 2′-O-Methyltransferases to modification sites on the mammalian mitochondrial large subunit 16 S ribosomal RNA (rRNA)

    Journal of Biological Chemistry 289:24936–24942.

    https://doi.org/10.1074/jbc.C114.581868

    • Google Scholar
29. 1. Lenarčič T
    2. Jaskolowski M
    3. Leibundgut M
    4. Scaiola A
    5. Schönhut T
    6. Saurer M
    7. Lee RG
    8. Rackham O
    9. Filipovska A
    10. Ban N

    (2021) Stepwise maturation of the peptidyl transferase region of human mitoribosomes

    Nature Communications 12:3671.

    https://doi.org/10.1038/s41467-021-23811-8

    • PubMed
    • Google Scholar
30. 1. Lorenz R
    2. Bernhart SH
    3. Höner zu Siederdissen C
    4. Tafer H
    5. Flamm C
    6. Stadler PF
    7. Hofacker IL

    (2011) ViennaRNA Package 2.0

    Algorithms for Molecular Biology 6:26.

    https://doi.org/10.1186/1748-7188-6-26

    • Google Scholar
31. 1. Love MI
    2. Huber W
    3. Anders S

    (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

    Genome Biology 15:550.

    https://doi.org/10.1186/s13059-014-0550-8

    • Google Scholar
32. 1. Maiti P
    2. Lavdovskaia E
    3. Barrientos A
    4. Richter-Dennerlein R

    (2021) Role of GTPases in driving mitoribosome assembly

    Trends in Cell Biology 31:284–297.

    https://doi.org/10.1016/j.tcb.2020.12.008

    • PubMed
    • Google Scholar
33. 1. Maribel M
    2. Chris M-R
    3. Mike G
    4. Daniel H
    5. Dimmock David P
    6. Verbsky James W
    7. Geurts Aron M

    (2018) Abstract 378: evaluation of patient specific MTERF4 variants in gene edited human iPSC-derived cardiomyocytes

    Circulation Research 123:A378.

    https://doi.org/10.1161/res.123.suppl_1.378

    • Google Scholar
34. 1. Metodiev MD
    2. Spåhr H
    3. Loguercio Polosa P
    4. Meharg C
    5. Becker C
    6. Altmueller J
    7. Habermann B
    8. Larsson NG
    9. Ruzzenente B

    (2014) NSUN4 is a dual function mitochondrial protein required for both methylation of 12S rRNA and coordination of mitoribosomal assembly

    PLOS Genetics 10:e1004110.

    https://doi.org/10.1371/journal.pgen.1004110

    • PubMed
    • Google Scholar
35. 1. Navarro IC
    2. Tuorto F
    3. Jordan D
    4. Legrand C
    5. Price J
    6. Braukmann F
    7. Hendrick AG
    8. Akay A
    9. Kotter A
    10. Helm M
    11. Lyko F
    12. Miska EA

    (2021) Translational adaptation to heat stress is mediated by RNA 5‐methylcytosine in Caenorhabditis elegans

    The EMBO Journal 40:e105496.

    https://doi.org/10.15252/embj.2020105496

    • Google Scholar
36. 1. Pearce SF
    2. Rorbach J
    3. Haute LV
    4. D’Souza AR
    5. Rebelo-Guiomar P
    6. Powell CA
    7. Brierley I
    8. Firth AE
    9. Minczuk M

    (2017) Maturation of selected human mitochondrial tRNAs requires deadenylation

    eLife 6:e27596.

    https://doi.org/10.7554/eLife.27596

    • Google Scholar
37. 1. Pettersen EF
    2. Goddard TD
    3. Huang CC
    4. Couch GS
    5. Greenblatt DM
    6. Meng EC
    7. Ferrin TE

    (2004) UCSF Chimera?A visualization system for exploratory research and analysis

    Journal of Computational Chemistry 25:1605–1612.

    https://doi.org/10.1002/jcc.20084

    • Google Scholar
38. 1. Pintard L
    2. Lecointe F
    3. Bujnicki JM
    4. Bonnerot C
    5. Grosjean H
    6. Lapeyre B

    (2002) Trm7p catalyses the formation of two 2'-O-methylriboses in yeast tRNA anticodon loop

    The EMBO Journal 21:1811–1820.

    https://doi.org/10.1093/emboj/21.7.1811

    • Google Scholar
39. 1. Raudvere U
    2. Kolberg L
    3. Kuzmin I
    4. Arak T
    5. Adler P
    6. Peterson H
    7. Vilo J

    (2019) g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update)

    Nucleic Acids Research 47:W191–W198.

    https://doi.org/10.1093/nar/gkz369

    • Google Scholar
40. 1. Rohou A
    2. Grigorieff N

    (2015) CTFFIND4: Fast and accurate defocus estimation from electron micrographs

    Journal of Structural Biology 192:216–221.

    https://doi.org/10.1016/j.jsb.2015.08.008

    • Google Scholar
41. 1. Rorbach J
    2. Boesch P
    3. Gammage PA
    4. Nicholls TJJ
    5. Pearce SF
    6. Patel D
    7. Hauser A
    8. Perocchi F
    9. Minczuk M

    (2014) MRM2 and MRM3 are involved in biogenesis of the large subunit of the mitochondrial ribosome

    Molecular Biology of the Cell 25:2542–2555.

    https://doi.org/10.1091/mbc.e14-01-0014

    • Google Scholar
42. 1. Rosenthal PB
    2. Henderson R

    (2003) Optimal determination of particle orientation, absolute hand, and contrast loss in single-particle electron cryomicroscopy

    Journal of Molecular Biology 333:721–745.

    https://doi.org/10.1016/j.jmb.2003.07.013

    • PubMed
    • Google Scholar
43. Preprint

    1. Sanchez-Garcia R
    2. Gomez-Blanco J
    3. Cuervo A
    4. Carazo JM
    5. Sorzano COS
    6. Vargas J

    (2020) DeepEMhancer: a deep learning solution for cryo-EM volume post-processing

    bioRxiv.

    https://doi.org/10.1101/2020.06.12.148296

    • Google Scholar
44. 1. Seffouh A
    2. Jain N
    3. Jahagirdar D
    4. Basu K
    5. Razi A
    6. Ni X
    7. Guarné A
    8. Britton RA
    9. Ortega J

    (2019) Structural consequences of the interaction of RbgA with a 50S ribosomal subunit assembly intermediate

    Nucleic Acids Research 47:10414–10425.

    https://doi.org/10.1093/nar/gkz770

    • Google Scholar
45. 1. Spåhr H
    2. Habermann B
    3. Gustafsson CM
    4. Larsson N-G
    5. Hallberg BM

    (2012) Structure of the human MTERF4–NSUN4 protein complex that regulates mitochondrial ribosome biogenesis

    PNAS 109:15253–15258.

    https://doi.org/10.1073/pnas.1210688109

    • Google Scholar
46. 1. Yang J
    2. Anishchenko I
    3. Park H
    4. Peng Z
    5. Ovchinnikov S
    6. Baker D

    (2020) Improved protein structure prediction using predicted interresidue orientations

    PNAS 117:1496–1503.

    https://doi.org/10.1073/pnas.1914677117

    • Google Scholar
47. 1. Yee C
    2. Yang W
    3. Hekimi S

    (2014) The intrinsic apoptosis pathway mediates the pro-longevity response to mitochondrial ROS in C. elegans

    Cell 157:897–909.

    https://doi.org/10.1016/j.cell.2014.02.055

    • PubMed
    • Google Scholar
48. 1. Zhang L
    2. Elias JE

    (2017) Relative protein quantification using tandem mass tag mass spectrometry

    Methods Mol Biol Clifton NJ 1550:185–198.

    https://doi.org/10.1007/978-1-4939-6747-6_14

    • Google Scholar
49. 1. Zheng SQ
    2. Palovcak E
    3. Armache J-P
    4. Verba KA
    5. Cheng Y
    6. Agard DA

    (2017) MotionCor2: anisotropic correction of beam-induced motion for improved cryo-electron microscopy

    Nature Methods 14:331–332.

    https://doi.org/10.1038/nmeth.4193

    • Google Scholar
50. 1. Zivanov J
    2. Nakane T
    3. Forsberg BO
    4. Kimanius D
    5. Hagen WJH
    6. Lindahl E
    7. Scheres SHW

    (2018) New tools for automated high-resolution cryo-EM structure determination in RELION-3

    eLife 7:e42166.

    https://doi.org/10.7554/eLife.42166

    • Google Scholar

Author details

1. Viswanathan Chandrasekaran

   MRC Laboratory of Molecular Biology, Cambridge, United Kingdom

   Contribution

   Conceptualization, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing

   Contributed equally with

   Nirupa Desai and Nicholas O Burton

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0871-4740

2. Nirupa Desai

   MRC Laboratory of Molecular Biology, Cambridge, United Kingdom

   Contribution

   Formal analysis, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing

   Contributed equally with

   Viswanathan Chandrasekaran and Nicholas O Burton

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-6046-653X

3. Nicholas O Burton

   1. Centre for Trophoblast Research, Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, United Kingdom
   2. Gurdon Institute, University of Cambridge, Cambridge, United Kingdom

   Contribution

   Conceptualization, Resources, Data curation, Formal analysis, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing

   Contributed equally with

   Viswanathan Chandrasekaran and Nirupa Desai

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-5495-3988

4. Hanting Yang

   MRC Laboratory of Molecular Biology, Cambridge, United Kingdom

   Contribution

   Data curation, Funding acquisition, Investigation, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-3383-2204

5. Jon Price

   1. Gurdon Institute, University of Cambridge, Cambridge, United Kingdom
   2. Department of Genetics, University of Cambridge, Cambridge, United Kingdom

   Contribution

   Data curation, Formal analysis, Investigation, Methodology

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-6554-5667

6. Eric A Miska

   1. Gurdon Institute, University of Cambridge, Cambridge, United Kingdom
   2. Department of Genetics, University of Cambridge, Cambridge, United Kingdom
   3. Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, United Kingdom

   Contribution

   Supervision, Funding acquisition, Project administration, Writing - review and editing

   For correspondence

   eam29@cam.ac.uk

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4450-576X

7. V Ramakrishnan

   MRC Laboratory of Molecular Biology, Cambridge, United Kingdom

   Contribution

   Resources, Supervision, Funding acquisition, Project administration, Writing - review and editing

   For correspondence

   ramak@mrc-lmb.cam.ac.uk

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4699-2194

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