Author response:
The following is the authors’ response to the original reviews.
Public Reviews:
Reviewer #1 (Public review):
This work provides a valuable toolkit for endogenous isolation of projection neuron subtypes. With further validation, it could present a solid method for low-input ribosome affinity purification using a ribosomal RNA (rRNA) antibody. The experimental evidence for the distinct ribosomal complexes is limited to this method and indirect support from complementary analyses of preexisting data.
However, with additional experimental data to support the specificity of ribosomal complex pulldown and confirmation of the putative ribosomal complex proteins of interest, the study would provide compelling evidence for translation regulation of neuronal development through compositional ribosome heterogeneity.
This work would be of interest to neuroscientists, developmental biologists, and those studying translational networks underlying gene regulation.
Strengths
(1) This in vivo labeling of specific projection neurons and ribosomal rRNA affinity purification method accommodates a low input of <100K somata per replicate, which is useful for the study of neuronal subtypes with limited input. In principle, this set of techniques could work across different cell types with limited input, depending on the molecule used for cell type labeling.
(2) The authors are also able to isolate endogenous neurons with minimal perturbation up to the point of collection, preserving the native state for the neuron in vivo as long as possible prior to processing.
(3) This study identified over a dozen potential non-ribosomal proteins associated with SCPN ribosomal complexes, as well as a ribosomal protein enriched in CPN.
We appreciate the reviewer's thoughtful and detailed review. We especially appreciate the positive evaluation of its strengths, including the use of rRNA affinity purification to access ribosomal complexes in low-input neuronal subtypes in vivo with minimal perturbation, and the resulting identification of distinct ribosomal complexes in SCPN and CPN with associated non-ribosomal proteins. We are also pleased by the recognition of its significance in advancing our understanding of neuronal subtype-specific post-transcriptional gene regulation. We have carefully addressed the limitations below.
Limitations
(1) In this study, the authors address the advantages of their ribosomal complex isolation method in SCPN and CPN against RPL22-HA affinity purification. While this does show more pull-down of the ribosomal RNA by the Y10B rRNA antibody, the authors claim this method identifies cell-type-specific ribosomal complex proteins without demonstrating a positive control for the method's specificity.
There are very limited experiments to truly delineate how "specific" this method is working and whether there could be contamination from other complexes bound by the antibody. I see this as the major limitation that should be addressed. To boost their claims of capturing cell-typespecific ribosomal complexes, the authors could consider applying their rRNA affinity purification pipeline to compare cell types with well-characterized ribosome-associated proteins, like mouse embryonic stem cells and HELA cells.
The reviewer can completely appreciate the elegance in the neural characterization here, but it seems there needs to be a solid foothold on the specificity of the method, perhaps facilitated by cell types that can be more readily scaled up and tested.
We thank the reviewer for the opportunity to further clarify how our experimental design addresses the question of specificity of ribosomal complex pulldown. The rRNA affinity purification pipeline was applied identically to both SCPN and CPN, with the analysis focused on comparative, differential analysis between the two subtypes. We employed this approach to subtract out potential background signal or non-specific binding to the Y10b antibody present in both subtypes. We have now clarified this experimental design in the text, at the end of the first result section.
(2) The authors followed up on their differentially enriched ribosomal complex proteins by analyzing the ribosome association of these proteins in external datasets. While this analysis supports the ribosome-association of these proteins, there is limited experimental validation of physical association with the ribosome, much less any functional characterization.
The reciprocal pulldown of PRKCE is promising; however, I would recommend orthogonal validation of several putative ribosomal complex proteins to increase confidence.
Specifically, the authors could use sucrose gradient fractionation of SCPN and CPN, followed by a western blot to identify the putative interaction with the 80S monosome or polysomes. This would also provide evidence towards the pulldown capturing association with mature ribosome species, which is currently unclear. This experiment would provide substantial evidence for the direct association of these non-ribosomal proteins with subtype-specific ribosomal complexes.
We thank the reviewer for the feedback and suggested future directions for candidate validation. We appreciate the recognition of our analysis of external datasets from independent approaches that provides support for physical ribosome association of these candidates. We respectfully submit that the scope of this work is an unbiased comparison of ribosomal complexes between SCPN and CPN to identify and nominate candidates for future investigation. We agree that future work to advance this direction of inquiry would optimally include further characterization of their subtype-specific physical interactions with ribosomes to further elucidate functional implications.
We appreciate the reviewer's suggestion of sucrose gradient fractionation for polysome profiling. We carefully considered this approach midway through this work, and we pursued pilot experiments to test feasibility. These pilot experiments reinforced findings in the existing literature that it typically requires on the order of 10⁷ cells, well beyond the feasible scope of these low-input purified neuronal subtypes. We respectfully submit that imaging-based approaches, such as proximity ligation assays and super-resolution microscopy, are likely more applicable to such very limited material, though would require extensive candidate-specific optimization beyond the scope of this project. We have now expanded future experimental consideration in the Discussion’s penultimate paragraph.
(3) The authors state interest in learning more about the differences underlying translational regulation of projection neuron development. This method only captures neuronal somata, which will only capture ribosomes in the main cell body. There are also ribosomes regulating local translation in the axons, which may also play a critical role in axonal circuit establishment and activity. These ribosomal complex interactions may also be rather transient and difficult to capture at only one developmental stage. Therefore, this method is currently limited to a single developmental snapshot of ribosomal complexes at P3 within the main cell body. It would be exciting to see the extended utility of this method to sample neurites and additional developmental stages to gain further resolution on the developmental translation regulation of these projection neurons.
We thank the reviewer for the opportunity to further highlight the foundational significance of this work in translational regulation of projection neuron development. Here, we identified subtype-specific differences in ribosomal complex composition within somata at a critical developmental time window for two PN subtypes. This work provides foundation for future investigation of local translation and its regulation in growth cones and axons. It will also enable direct comparison with potential future results from axons and growth cones, developmental subcellular specializations at axon tips that implement pathfinding and circuit formation (such work is not yet feasible due to exceptionally low available input). Our lab has significant ongoing work regarding subtype-specific axon and growth cone biology, including recent investigations of growth cone-localised RNA and protein molecular machinery that regulate circuit formation, maintenance, and function of distinct cardinal PN subtypes (Poulopoulos*, Murphy* et al. Nature 2019; Engmann*, Hatch* et al. Nature Prot 2022; Itoh et al. Cell Rep 2023; Veeraraghavan*, Engmann* et al. Nature Neurosci 2026; Durak*, Kim* et al. bioRxiv 2023; Veeraraghavan*, Tillman* et al. bioRxiv 2025; Tillman et al. bioRxiv 2026). Combining subtype-specific growth cone purification with ribosomal complex investigation represents a logical and exciting future direction. We appreciate the reviewer's encouragement of this future line of investigation and now highlight it in the revised Discussion.
Likely impact of the work on the field, and the utility of the methods and data to the community:
The authors introduce a unique pipeline of techniques to identify cell-type-specific ribosomal complex compositions. With more validation, there is certainly potential for those studying neuronal translation to leverage this method in limited primary cells as an alternative to existing methods that do not rely on ribosomal protein tagging, such as ARC-MS (Bartsch et al., 2023), RAPIDASH (Susanto and Hung et al., 2024), and RAPPL (Nature Communications, 2025).
Reviewer #2 (Public review):
Summary:
This study presents a sophisticated molecular dissection of ribosome-associated complexes (RCs) in two well-defined cortical projection neuron subtypes (ScPN and CPN) during early postnatal development.
The authors develop and optimize an rRNA immunoprecipitation-mass spectrometry (rRNA IPMS) workflow to recover RCs from FACS-purified, retrogradely labeled neurons, achieving remarkable subtype specificity and biochemical resolution. Through proteomic profiling, they reveal both shared and distinct ribosome-associated proteins between ScPN and CPN, with a focus on non-core RC components and their potential functional relevance. The work advances our understanding of cell-type-specific translation regulation, moving beyond the transcriptome to explore the proteome-level complexity in neuronal subtypes.
Strengths:
This work stands out for its technical sophistication and innovation. The authors combine retrograde labeling, FACS purification, and an optimized rRNA IP-MS approach (low input) to isolate ribosome-associated complexes from highly specific neuronal subtypes in vivo, a challenging issue that they execute with impressive rigor. The methodological pipeline is both elegant and well-controlled, yielding high-quality, reproducible data. The depth of proteomic coverage is remarkable, with nearly all known cytoplasmic ribosomal proteins identified, along with hundreds of ribosome- associated proteins (RAPs), including translation factors, chaperones, and RNA-binding proteins.
The analysis not only reveals shared components between ScPN and CPN RCs but also uncovers subtype-specific differences in associated proteins. Particularly notable is the integration of this new proteomic dataset with previously published transcriptomic and ribosome footprinting data, which helps to validate the specificity and relevance of the findings. Overall, the clarity of the writing, the robustness of the data, and the transparency of the methods make this a strong and compelling contribution.
Weaknesses:
Despite the depth and high quality of the dataset, the study remains descriptive. While the identification of subtype-specific RC components is intriguing, the current version of the manuscript does not explore their functional roles or the biological consequences of their alterations. There is no perturbation, causal testing, in vitro or in vivo manipulation to demonstrate whether these proteins are necessary for ScPN or CPN identity, specific axonal targeting, metabolism, or synaptic function. One important point highlighted by the authors in the discussion - and critical for establishing the subtype specificity of the identified proteins - is that some ribosomal complexes may be specialized for specific developmental stages, rather than exclusively for the subtype-specific needs of projection neuron development. The work presented here provides a valuable starting point for further investigation into such RC specialization.
However, it will be essential to determine to what extent these RCs exhibit true subtype specificity, independently of their temporal maturation context. As a result, key mechanistic insights remain a bit speculative. Although several of the identified proteins have known roles in processes like synaptogenesis or metabolism, their relevance to the specific neuronal subtypes under study is not experimentally addressed.
That said, given its rich content and the comprehensive early postnatal dataset, the manuscript represents an extremely valuable resource for the community. While primarily exploratory, it lays a strong foundation for future functional studies aimed at uncovering the biological impact of the identified ribosomal complexes.
We thank the reviewer for their excellent summary and for their very positive assessment of our work. We are pleased that the methodological rigor, proteomic depth, and integrative analyses were well-received. We thank the reviewer for highlighting that our “work presented here provides a valuable starting point for further investigation into such RC specialization” and that “it lays a strong foundation for future functional studies aimed at uncovering the biological impact of the identified ribosomal complexes.” This is exactly how we view this contribution – as a foundation to share with broader field so such functional investigation and investigation of developmental dynamics can be pursued by multiple groups in the broader related field.
We again thank the reviewer for the very positive and insightful comments.
Recommendations for the authors:
Reviewer #1 (Recommendations for the authors):
Suggestions for improved or additional experiments, data, or analyses:
(1) As listed in the limitations, I would recommend that the authors consider applying their rRNA affinity purification to additional cell lines to confirm the specificity of the method as a positive control, where just demonstrating the technology may be easier to carry out than with more limited samples.
As we noted in our response above to Limitation 1: “The rRNA affinity purification pipeline was applied identically to both SCPN and CPN, with the analysis focused on comparative, differential analysis between the two subtypes. We employed this approach to subtract out potential background signal or nonspecific binding to the Y10b antibody present in both subtypes. We have now clarified this experimental design in the text, at the end of the first result section.”
(2) Also, as listed in the limitations, I recommend that the authors provide orthogonal experimental evidence for the putative SCPN and CPN ribosomal complex proteins of interest (e.g., sucrose gradient > western blot).
As we noted in our response to Limitation 2 above: “We appreciate the recognition of our analysis of external datasets from independent approaches that provides support for physical ribosome association of these candidates. We respectfully submit that the scope of this work is an unbiased comparison of ribosomal complexes between SCPN and CPN to identify and nominate candidates for future investigation. We agree that future work to advance this direction of inquiry would optimally include further characterization of their subtype-specific physical interactions with ribosomes to further elucidate functional implications.”
Regarding sucrose gradient fractionation (for polysome profiling), we also noted in our response to Limitation 2: “We carefully considered this approach midway through this work, and we pursued pilot experiments to test feasibility. These pilot experiments reinforced findings in the existing literature that it typically requires on the order of 10⁷ cells, well beyond the feasible scope of these low-input purified neuronal subtypes. We respectfully submit that imaging-based approaches, such as proximity ligation assays and super-resolution microscopy, are likely more applicable to such very limited material, though would require extensive candidate-specific optimization beyond the scope of this project. We have now expanded future experimental consideration in the Discussion’s penultimate paragraph”.
(3) The authors are interested in preserving the native state of the projection neurons to isolate ribosomal complexes; therefore, they may consider using biotin-conjugated CTB (Thermo Fisher) sorting through anti-biotin MACS columns (Miltenyi Biotech) as opposed to FACS in the future. While it does not allow for the same visualization as using a CTB-FP, this slight pipeline adjustment could help save time and physical processing of the projection neurons, helping preserve their endogenous state.
While we appreciate the reviewer’s constructive suggestion for this theoretically alternative approach, we respectfully submit that this approach is unlikely to effectively isolate projection neurons from the living brain as effectively as FACS approach employed here. We considered this approach. We respectfully offer that CTB standardly enters neurons by binding GM1 gangliosides at the axon terminal, after which it is internalized and undergoes retrograde transport to the soma, several millimeters or more away depending on the projection. By the time CTB reaches the soma, we further respectfully offer that it is standardly fully internalized and is no longer surface-exposed for the theoretically suggested antibiotin capture for MACS. We used magnetic bead-based pull-down for the ribosomes themselves and find those molecular approaches very beneficial. Despite our use and openness to magnetic-conjugate-based separation approaches, we judge that fluorophore-conjugated CTB and FACS remain the most efficient and feasible approach for isolation of these exceptionally polarized projection neurons while maintaining cell viability.
(4) While the authors provided a comparison of overall protein detection levels between SCPN and CPN, I recommend an additional analysis and potential normalization for the average core ribosomal protein abundance across samples. I will note that this is more accessible when samples are prepared using TMT-labeling methods, which might be considered for future experiments.
We thank the reviewer for these suggestions. We appreciate the opportunity to address them together, to further clarify our deeply considered choice of MS-based proteomic analysis and corresponding primary normalization approach. To complement our initial normalization approach, we have now also implemented the reviewer’s suggested approach of normalization to the average intensity of core ribosomal proteins. Notably, these new results agree with those from our initial normalization approach. This insightful suggestion has further strengthened the paper’s results and interpretation.
Here, we employed label-free quantification (LFQ), wherein samples are assayed sequentially rather than simultaneously, to most rigorously establish which proteins are truly present in some neuronal subtypes but absent in others. As the reviewer is aware, this capability to determine absence vs. presence of MS-detectable peptides distinguishes LFQ from approaches that assay samples simultaneously, such as isobaric tandem mass tag (TMT) labeling, which standardly offers advantages in relative quantification studies. Advances in sample preparation, instrumentation, and data analytical algorithms (from recent developments in single-cell proteomics and related approaches) now enable application of LFQ in quantitative differential analysis, even in the ultra-low-input regime. We now include both detailed discussion of these points and relevant citation in the text.
As the reviewer is also aware, in LFQ, normalization is crucial to ensure the protein quantification is accurate and comparable across sequential runs. For quantitative differential analysis of proteins detected in both subtypes, we have implemented a primary normalization approach employing “median-of-ratios” normalization across all detected proteins for robustness against outliers and technical variability. This primary approach results in similar overall distributions of protein abundances across CPN and SCPN samples (Figure S2A), providing confidence in quantitative comparison between SCPN and CPN in the ultra-lowinput regime.
Following the reviewer’s suggestion, to further ensure rigor of identification of differential proteins, we have also implemented a second normalization approach, rescaling each sample to the average intensity of its core ribosomal proteins alone (new Figure panels S2B, C). Subsequent differential analysis reveals equivalent CPN > SCPN enrichment of RPS30/eS30, GUCY1A1, and CELF3 (proteins identified as CPN-enriched with the primary normalization approach). These three proteins rank among the five proteins with lowest p-values, though false-discovery-rate-corrected significance is reduced. This confirmation by a second normalization approach further strengthens the findings.
We have included clarifications in the main text, added the second normalization approach and subsequent analysis in both the main text and Figure S2. In addition, we have now noted in the discussion that TMT labeling with correspondingly appropriate normalization approaches might better define relative quantitative differences between functional candidates present in multiple subtypes.
Recommendations for improving the writing and presentation:
(1) I recommend this as a Tools or Resource article, seeing as the biological conclusions are limited.
We respectfully submit that this work investigated biological questions and identified biological answers beyond pure development of Tools or offering a dataset as a Resource. We further respectfully submit that the question of differential neuronal subtype-specific translation of shared transcripts has become an emerging area of interest in regulation of precise neuronal and circuit development, maintenance, and function, as well as the neurobiological basis of disease. This has been quite hard to study, and this paper brings a first level of answers to that biological question. Of course, the biological results of this paper are not the complete answer, but as with all biological discovery papers, it provides a foundation for many further studies by multiple labs.
(2) In the rationale for studying ribosomal complex machinery, it may be helpful to say that ribosome composition and associated proteins that are present in the cytoplasm provide a way in which ribosomes can tune translation rapidly. This is especially important, seeing as this affords post-mitotic neurons the opportunity to remodel and repair by using readily available proteins while also avoiding the energetic demands of producing new ribosomal complex proteins.
We thank the reviewer for this insightful comment and fully agree. We have now added this rationale to the Introduction.
(3) Is there a need for a CTB injection control? Does GM1 binding affect translation pathways? Please list citations, if possible.
We respectfully submit that a CTB injection control is not necessary. As noted in our response to Limitation 1 in the Public Review portion, both PN subtypes underwent retrograde labeling with CTB in this work. While it remains unknown whether CTB-GM1 binding affects translation, potential effects of CTB are expected to apply equivalently to both subtypes and would therefore not confound these between-subtype comparisons. Please also see our response to recommendation 4 immediately below, in which we further clarify that retrograde tracing with CTB is a long-standing, well-accepted method shown to cause minimal damage and not interfere with continued neuronal development.
(4) Do the traced/labeled PNs keep developing normally? In other words, does retrograde tracing inhibit proper PN development? Please list citations, if available.
We thank the reviewer for encouraging us to further clarify that these are longstanding and well-accepted methods in the field, found to cause minimal damage and not to interfere with continued neuronal development. These and related retrograde labeling methods have led to the identification of the field's cardinal regulatory genes and molecules of axonal connectivity. This includes substantial work from our own lab (PMID in parentheses): Arlotta*, Molyneaux* et al. Neuron, 2005 (15664173); Lai*, Jabaudon* et al. Neuron, 2008 (18215621); Molyneaux*, Arlotta* et al. J. Neurosci., 2009 (19793993); Galazo et al. Neuron, 2016 (27321927); and more recently Sahni et al. Cell Rep., 2021a (34686320); and Sahni et al. Cell Rep., 2021b (34686337). These methods have also employed by other groups, such as Bin Chen (e.g. McKenna et al. PNAS, 2015 (26324926)) and Marta Nieto (e.g. De León Reyes et al. Nat. Commun., 2019 (31591398)). We have now clarified this in the text and included references for the benefit of the readers.
(5) It may be helpful to mention that RPS30 associates with immature ribosomes during biogenesis (PMID: 25706898).
We thank the reviewer for the opportunity to further clarify background knowledge of RPS30. As the reviewer is aware, RPS30/eS30 is definitively part of the mature 80S ribosome, as established, e.g., by cryo-EM of human 80S ribosomes (PMID: 25901680). Like multiple other ribosomal proteins, RPS30/eS30 also associates with immature ribosomes during biogenesis (PMID: 25706898). Intriguingly, RPS30/eS30 is produced by cleavage of a fusion protein comprising ubiquitin-like FUBI and RPS30/eS30, with cleavage recently identified as a late step in cytoplasmic 40S maturation (PMID: 34318747). As noted in the text, we confirmed that the peptides used for RPS30/eS30 identification appropriately map only to the amino acid sequence of RPS30/eS30 and not FUBI. We now mention that it is a core component of the mature 80S ribosome and its immature ribosomal association.
(6) Please clarify how the rRNA-IP is pulling down mature ribosomes. If not, this should be incorporated into the discussion.
We thank the reviewer for raising this interesting point. As the reviewer notes, it is well established in the ribogenesis field that ribosomes are continuously produced and therefore exist at various stages of maturation. Our protocol removes a major source of immature ribosomes by subjecting FACS-purified cells to two centrifugal spins that remove the nucleus, the site of ribogenesis and early steps of maturation. In pilot experiments, nuclear removal was confirmed by the absence of a contaminating genomic DNA peak on Bioanalyzer electropherograms of total RNA extracted from input samples (without genomic DNA removal) immediately prior to rRNA-IP. However, ribosomes also undergo cytoplasmic maturation steps, and various functional states of ribosomes have been found to be present in the cytoplasmic fraction. For these reasons, we have referred to what we pulled down as "ribosomal complexes" throughout the manuscript. We now explain this nuclear/immature ribosome depletion and cytoplasmic ribosomal enrichment in the text.
(7) Would have been interested to see some discussion of the most enriched CPN RAPs or why these might not exist in most replicates (inter-subtype heterogeneity?)
The reviewer asks an interesting question. As the reviewer is aware, when considering a single sample in isolation, absence of mass spectrometry-based detection is not definitive proof of absence, especially not within this work’s ultralow input regime. One of us (B. Budnik) has substantial experience with ultra-low-input samples across multiple cell types outside of the nervous system, and identifying a protein in three of four identical samples is not uncommon. We therefore used detection in three or four samples as an indicator of presence, while absence across all samples was taken to indicate true absence.
That said, the reviewer is correct that further diversity and heterogeneity within both CPN and SCPN subtypes additionally might be involved. This is an interesting question for future research, and we have added relevant text to the Discussion.
(8) It may be helpful to mention that RPL22, while not stoichiometric, is known to have extraribosomal functions and can pull down independently from assembled ribosomes (PMID: 17381311, PMID: 28575669. Moreover, RPL22/eL22-3xFLAG has been previously used as a control for ribosome affinity-based pulldowns and could be added to citations for Figure S1 (PMID: 28625553, PMID: 28625553).
We thank the reviewer for this helpful recommendation. We have added relevant text and citations.
Minor corrections to the text and figures:
(1) Want to confirm that in Figure 2, P adj is <0.1 is correct?
Yes
(2) It is not necessary to show MS spectra in Figure 2.
While we understand the spectra are not strictly necessary, we respectfully submit that they enhance the figure and aid readers in assessing data quality.
Reviewer #2 (Recommendations for the authors):
To strengthen the impact and interpretation of the authors' findings, we encourage consideration of the addition of functional validation experiments for at least one (or more) of the ribosomeassociated proteins that are differentially enriched in ScPN. This could include genetic manipulation (e.g., knockdown or overexpression) to test whether these proteins influence subtype-specific features or neuronal function. Even a limited set of perturbation experiments, such as targeting PRKCE, which is particularly interesting due to its known role in synaptogenesis, would help move the study from descriptive to a more mechanistic nature of the work.
There appear to be no issues related to data availability, ethics, or compliance, assuming all raw proteomic data and associated code for differential analysis are made publicly available.
We again thank the reviewer for this encouragement and highlighting that our work provides the foundation for further functional and developmental dynamic investigations. We view this work as providing that foundation for further investigation by multiple labs in the broader fields, beyond the scope of this paper.
