Genome-wide transcriptomics identifies an early preclinical signature of prion infection
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We thank the Reviewers for the positive assessment of our work and their insightful remarks. Please find below a point-by-point response to each comment.
*Reviewer #1 (Evidence, reproducibility and clarity (Required)): *
*The authors present a well written article describing distinct transcriptomic profiles generated by RNA sequencing analysis of hippocampus, a distinct anatomical area, at well spaced and defined time points of clinical progression following prion inoculation in an established mouse model. The authors contribute significantly in the detailed transcriptomic definition of changes during disease progression, especially during the early and …
Note: This rebuttal was posted by the corresponding author to Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Reply to the reviewers
We thank the Reviewers for the positive assessment of our work and their insightful remarks. Please find below a point-by-point response to each comment.
*Reviewer #1 (Evidence, reproducibility and clarity (Required)): *
*The authors present a well written article describing distinct transcriptomic profiles generated by RNA sequencing analysis of hippocampus, a distinct anatomical area, at well spaced and defined time points of clinical progression following prion inoculation in an established mouse model. The authors contribute significantly in the detailed transcriptomic definition of changes during disease progression, especially during the early and almost asymptomatic stages.
The brain region chosen to perform their analysis is logical as the hippocampus shows clear signs of neuronal degeneration in prion disease progression and furthermore provides a well defined area for analysis that is easily accessible experimentally; Although, more information would be needed to strengthen this choice in relation to the hippocampus playing a key role in the initiation stages of the disease. It remains an anatomical subset of the whole brain and the study would benefit if extended to include other affected areas. *
The hippocampus is one of the most affected and therefore most studied regions during prion disease (Moreno et al., 2012, Nature). We have clarified this in the text (page 3). While the analysis of transcriptional changes in additional brain regions would be of interest, the main conclusions derived by the present analyses on the hippocampus already opens new perspectives to our understanding of this complex disease (e.g. premature pathological changes at 8 weeks occur long before the development of neuropathological and clinical signs). In light of the new findings observed from the first cohort of experimental animals, we designed the rest of the study to prioritize more analyses (e-g- splicing and RNA editing) and validations (e.g. second cohort, aging cohort, plasma administration cohort etc.) in order to provide comprehensive and robust dataset and corroborate our findings. We are currently working on a follow-up study thoroughly describing transcriptional changes during prion disease development in other brain regions. We believe that the inclusion of these data would not be instrumental to support the main conclusions of the present study and may unduly add complexity to the current manuscript.
*The article presents comprehensive bioinformatics analysis of the gene expression profiles, during disease progression and continues focusing on two early stages whose profiles clearly cluster together. The authors elegantly query the transcriptomic data extrapolating clusters representative of different cell types and conclude that at preclinical stages microglial-related DEGs are enriched. Importantly, data trends are replicated in an independent animal cohort supporting the experimental design, reproducibility and bioinformatics analysis. Enriched microglial populations from challenged animals compared to controls, would have added more value to the approach. *
We agree with the reviewer that certain cell types, including microglia should be investigated in more detail. We are currently working on a study investigating prion-induced changes in a cell-type specific manner using ribosomal profiling. While space reasons prevent us from adding these studies to the present manuscript, we are planning to publish a comprehensive searchable database that will include both the transcriptomics and translatomics data.
*The authors proceed to conclude that these transcriptomic enrichment of microglial related DEGs are suggestive of driver events in the initiation of prion disease. Although the statement is gaining a lot of interest in the current literature, it is yet immature to conclude from only RNA sequencing data that microglial neuroinflammation is the causative driver event and not the result of the infection and subsequent neurodegeneration. Taking also into consideration the route of infection (ic) which is expected to initiate an acute immune response in the brain. *
*Towards that comment, the immunohistochemistry data should show increased immune reaction from the early time points pi. *
While the simultaneous occurrence of microglia-related changes and motor decline suggests that microglia may be the ultimate drivers of prion disease progression, we agree that correlation does not prove causation, and have toned down our conclusions to this respect.
Clearly, microglia activation does not play a major role during the early stages of prion disease: we do not see any increased immune reaction at the early time points as the reviewer pointed out, nor do we see any RNA expression changes in microglia-enriched genes at the early time points.
We also don’t believe that the infection is the source of microglia activation for the following reason: if the inoculation itself would induce microglia activation we would expect a strong microglia response directly after the injection that should progressively decrease. Instead, we see no expression change in microglia-enriched genes until 16 wpi. We have clarified the corresponding sections in the text.
To address the reviewer’s point that the route of infection may contribute to the observed changes we have added the following datasets as new Supplemental Fig. 4:
We have analyzed prion induced changes 8wpi and the terminal stage from intraperitoneally inoculated mice (new Supplemental Fig. 4). The prion induced changes between the different routes of administration correlate at the respective timepoint, indicating that the induced changes are independent of the route of prion inoculation. To strengthen the point that the 8 wpi changes are indeed prion-dependent (and thus require in vivo prion replication by incorporation of cellular prion protein PrP), we have additionally included 8 wpi samples from PrP knock-out mice. The knockout mice don’t show any prion-induced changes at 8 wpi (new Supplemental Fig. 4), suggesting that the 8 wpi changes are not the result of the infection and more importantly, are in fact prion-dependent.
Also, the paper would gain significantly, if there were random as well as targeted (eg microglial specific) molecular targets selected, for independent validation by Real-time QC PCR and immunohistochemistry. This would be especially interesting if it was combined with the targets that showed selective splicing like Ctsa, a microglial related gene.
We respectfully disagree with the reviewer on this issue. In the early days of RNAseq, most scientists would validate their results with qPCR of select genes. However, by now RNAseq is widely accepted as the state-of-the-art technique to profile whole transcriptomes and is considered to be more reliable, accurate and sensitive compared to orthogonal methods such as RT-qPCR. Also, RNAseq and RT-qPCR data are highly correlated (typically ~85% and well above 90% when genes with a low expression are neglected; PMID: 28484260). The inclusion of an orthogonal technology is thus only needed when a) no biological replicates are available (potentially detrimental intra-group variability); b)definitive conclusions depend on genes with extremely low expression levels (potentially detrimental high dispersion); c) the main findings of an experiment revolve around one or a handful of genes (potentially detrimental false positives). None of the above applies to this study. Moreover, in terms of overall validation, we already include data from a second, independent cohort of mice with the same experimental settings (Supplementary Fig. 3), as well as from aged mice and from mice with plasma/saline treatment. We therefore maintain that qPCR verification is unnecessary in this instance and may potentially even produce confounders.
*RNA binding deaminase proteins show a similar pattern to a recent report, strengthening the finding that protein levels do not change and/or compensate with other RNA binding and editing enzymes, even though edited targets and editing frequency shift significantly.
The authors continue with RNA editing analysis concluding that they did not find any (apart from two targets being edited) differential RNA editing sites contradictory to a recent study. We believe that this contradiction is a premature conclusion since, the analysis was based on an older protocol that was published by the same group based on GTAK version 3.4.0 from 2011. The predicted RNA edited sites were only based in previously catalogued samples from hippocampus of young mice by Stilling et al 2014. They did not take into account C-U editing in all genomic locations in the whole brain regardless of aging or region. Also, the depth of sequencing was not taken into account which would increase the novel identification of editing sites instead of being limited to previously identified non-validated RNA editing. The study would significantly benefit from Sanger sequencing validation of random and non random edited targets. How do the identified targets validate? *
As suggested by the Reviewer, we have reanalyzed RNA editing using the same editing pipeline as Kanata et al. (PMID: 31492812), neither restricting the analysis to a pre-existing list of candidate sites, nor limiting the analysis to A-to-I editing events. Following this approach, a number of editing sites comparable to those reported by Kanata et al. were identified. However, we did not observe a statistical difference between control and PrD samples at the locus level.
As discussed in the manuscript Kanata et al, analyzed a different brain region using a different infection model. Furthermore, the fact that we assessed triplicates, and the application of strict filters in the selection of putative editing sites might have contributed to us not detecting differentially edited sites. While we used the same parameters linked to quality and depth of coverage, we only considered the intersection of both REDItools and VarScan2, and required that at least 2 out of 3 samples were edited. Regarding the validation of the editing events through Sanger sequencing, we believe it is outside of the scope of the present study because our main goal is not that of exactly pinpointing specific editing sites and hypothesizing on their potential effects. We rather view the editing analysis as an auxiliary layer to the main conclusions of the manuscript, and through the updated analysis and results we believe we have reached such a goal.
*Finally, the study concludes with the administration of young plasma at 8 weeks (early stage of the disease) and the authors support that this intervention improves the phenotype of the affected animals without lifespan changes. In our view, this part of the study should either be omitted, or full transcriptomic and clinicopathological improvement should be demonstrated with clear emphasis on microglial-related molecular targets. *
While plasma administration does not prolong lifespan and terminal prion-induced changes are very similar in plasma vs saline-treated animals (Fig. 6d-e), we did in fact observe a full transcriptomic improvement upon plasma administration at 8 wpi (Fig. 6b). We currently don’t know if prion-induced 8 wpi changes and the plasma-induced improved health span are linked to microglia-related changes (see also response above). We have therefore not put any additional emphasis on microglia-related targets. We therefore feel that the plasma experiments do add to the present paper, but we would be prepared to discuss with the editors whether it may be appropriate to omit this part and publish it separately.
**Minor comment:**
Other behavioral tests such as T-maze, Morris water-maze, novel object recognition, wouldn't it be better suited for memory assessment? *
Although we agree with the reviewer that these tests are better suited for memory assessment, the purpose of the rotarod evaluation (together with histological and biochemical tests) was to obtain an objective monitoring of clinical disease development. Rotarod assessment has been instrumental to objectivate the genetic or pharmacological modulation of prion disease development (e.g PMID: 29176838; PMID: 26246168; PMID:25502554). A more sophisticated behavioral assessment would go beyond the scope of this study and would require access to specific infrastructures which are not available in our veterinary bio contained research facility allowing the handling of prion-infected mice.
*Reviewer #1 (Significance (Required)):
The authors present a very detailed and informative transcriptomic profiling of a well structured in vivo experiment with a satisfactory number of time points that has provided significant transcriptomic and splicing information at the preclinical stage of the disease. The field would definitely benefit from such a profile oriented approach however the above should be sufficiently addressed. *
*Reviewer #2 (Evidence, reproducibility and clarity (Required)): **
In the present paper by Sorce et al. the authors studied mRNA changes, splicing and editing alterations during the progression of prion disease in an experimental animal model (inocculated mice). The main findings are that changes in RNA processing and abundance occured very early at around 8 wpi. Interestingly, changes in microglia-enriched genes appeared early and coincided with the onset of clinical symptoms while neuronal genes were unchanged and played a more prominent role at later stages of the disease suggesting that glial cells might be the driving force and pivotal for the early stages and disease progression. Young plasma restored mRNA alterations and was beneficial for delaying neurological symptoms. This conclusion seems to be supported by the data and overall the study was well performed. The findings are clearly presented, the discussion is insightful and balanced and the figures are in general of high quality but there are some concerns that need to be clarified.
The authors could tackle the following comments with a straightforward revision:
- On Page 3 it is mentioned that RNA sequencing was performed in n=3 samples per time point and for the 20 wpi time point in controls only n=2 samples have been used. Overall this is a very low sample size that needs to be increased. More samples need to be analyzed in order to provide biological relevance. *
We agree with the reviewer that, like in any other biological study entailing a certain degree of experimental variability, increased sample sizes always increase the statistical power and may allow for the detection of changes that might otherwise go undetected. However, there are opportunity costs that go along with enlarging the study. Also, the Swiss Animal Protection Law requires us to adhere to the 3R principles (Replacement, Reduction and Refinement of animal experimentations). We have aimed at using the minimum number of animals allowing us to identify a subset statistically significant and robust changes. Animal welfare considerations and an attempt to prevent an escalation of cost resulted in the majority of experiments being performed with 3 samples per time point.
It is accepted in the field that three replicates are sufficient to identify the vast majority of biologically relevant changes in mRNA abundance. Unless major claims are made about individual genes at the lower end of the expression’s dynamic range (which is not the case in this study), three replicates ensure that about 85 % of the relevant changes are accurately captured (PMID: 29767357; PMID: 26813401). This is particularly true when the variability across replicates is low and appropriate analysis tools, such as edgeR, are employed (PMID: 30726870).
We used age and gender matched inbred C57BL/6J mice in a microbiologically tightly-controlled environment (see Methods) to minimize interindividual variability. This allowed us to identify thousands of statistically significant prion-dependent changes, despite the low sample number.In few exceptions we sequenced two instead of three replicates (eg because a sample got lost, the RNA was degraded, or the sample did not pass quality control after sequencing). In these instances, we ensured that both replicates showed a high correlation and could thus still yield reliable results. Furthermore, we have validated the RNA expression changes in an independent cohort of mice with the same experimental settings (Supplementary Fig. 3), as well as from aged mice and from mice with plasma/saline treatment, indicating that the observed changes are robust.
2) On page 4 it is written that 'While clusters 2 and 3 consist predominantly of microglia and neuronal genes, cluster 1 and 4 contain genes enriched in multiple cell types'. A few sentences later, the authors write, that 'Neuronal genes almost exclusively belonged to clusters 3 and 4................, whereas microglia genes were essentially contained in clusters 1 and 2. These two statements are contradictory. Please explain and clarify.
Compared to clusters 2 and 3, the enriched genes in clusters 1 and 4 don’t predominantly fall into one category (eg cluster 4 contains ~30% neuronal-enriched genes, ~25% oligodendrocyte enriched genes, 20% endothelial-enriched genes – see Fig. 1d). However, of 203 neuronal-enriched DEGs, 143 are cluster 3 genes (~70%), 50 are cluster 4 genes (~25%), while only 10 are cluster 1 genes (~5%) and 0 are cluster 2 genes. To better illustrate this point, we have included these numbers as an additional Table in Supplementary Fig. 2.
*3) On page 5 the authors claim that 'astro- and microgliosis became evident at 16 wpi...........' This statement is based solely on histological images and needs to be confirmed by quantification. However in Supplementary figure 5c astrocytes and microglia (GFAP and Iba1 staining) are almost not visible and the overview images too superficial. I recommend high resolution images and additional inserts and a solid quantification. *
We have added high resolution pictures, additional inserts and a quantification of the stainings (new Supplementary Fig. 6).
*4) On Page 6 the authors write 'We observed progressive decline in motor performance starting 18 wpi'. However, the graph in figure 3a clearly shows only a significant difference at 19 wpi'. This needs to be corrected. *
- The decline in motor performance shows a visible trend at 18 wpi but only becomes statistically significant at 19 wpi. We have clarified this in the text.*
*5) Figure 6c: it would make sense to combine both graphs (saline and plasma) for a direct comparison of prion infected mice that received saline or plasma so that potential differences would be easier to recognize ......although they seem to be pretty modest. *
We have combined both graphs from Fig. 6c into one but believe that it becomes very difficult to extract any information from the figure. We shall defer to the reviewer’s judgment but we would prefer to keep the original figure.
Reviewer #2 (Significance (Required)):
The findings are of interest to a wide readership and the paper thus seems suited to be published, but there are some concerns that need to be clarified (see specific comments above).
-
Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Referee #2
Evidence, reproducibility and clarity
In the present paper by Sorce et al. the authors studied mRNA changes, splicing and editing alterations during the progression of prion disease in an experimental animal model (inocculated mice). The main findings are that changes in RNA processing and abundance occured very early at around 8 wpi. Interestingly, changes in microglia-enriched genes appeared early and coincided with the onset of clinical symptoms while neuronal genes were unchanged and played a more prominent role at later stages of the disease suggesting that glial cells might be the driving force and pivotal for the early stages and disease progression. Young plasma …
Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Referee #2
Evidence, reproducibility and clarity
In the present paper by Sorce et al. the authors studied mRNA changes, splicing and editing alterations during the progression of prion disease in an experimental animal model (inocculated mice). The main findings are that changes in RNA processing and abundance occured very early at around 8 wpi. Interestingly, changes in microglia-enriched genes appeared early and coincided with the onset of clinical symptoms while neuronal genes were unchanged and played a more prominent role at later stages of the disease suggesting that glial cells might be the driving force and pivotal for the early stages and disease progression. Young plasma restored mRNA alterations and was beneficial for delaying neurological symptoms. This conclusion seems to be supported by the data and overall the study was well performed. The findings are clearly presented, the discussion is insightful and balanced and the figures are in general of high quality but there are some concerns that need to be clarified.
The authors could tackle the following comments with a straightforward revision:
On Page 3 it is mentioned that RNA sequencing was performed in n=3 samples per time point and for the 20 wpi time point in controls only n=2 samples have been used. Overall this is a very low sample size that needs to be increased. More samples need to be analyzed in order to provide biological relevance.
On page 4 it is written that 'While clusters 2 and 3 consist predominantly of microglia and neuronal genes, cluster 1 and 4 contain genes enriched in multiple cell types'. A few sentences later, the authors write, that 'Neuronal genes almost exclusively belonged to clusters 3 and 4................, whereas microglia genes were essentially contained in clusters 1 and 2. These two statements are contradictory. Please explain and clarify.
On page 5 the authors claim that 'astro- and microgliosis became evident at 16 wpi...........' This statement is based solely on histological images and needs to be confirmed by quantification. However in Supplementary figure 5c astrocytes and microglia (GFAP and Iba1 staining) are almost not visible and the overview images too superficial. I recommend high resolution images and additional inserts and a solid quantification.
On Page 6 the authors write 'We observed progressive decline in motor performance starting 18 wpi'. However, the graph in figure 3a clearly shows only a significant difference at 19 wpi'. This needs to be corrected.
Figure 6c: it would make sense to combine both graphs (saline and plasma) for a direct comparison of prion infected mice that received saline or plasma so that potential differences would be easier to recognize ......although they seem to be pretty modest.
Significance
The findings are of interest to a wide readership and the paper thus seems suited to be published, but there are some concerns that need to be clarified (see specific comments above).
-
Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Referee #1
Evidence, reproducibility and clarity
The authors present a well written article describing distinct transcriptomic profiles generated by RNA sequencing analysis of hippocampus, a distinct anatomical area, at well spaced and defined time points of clinical progression following prion inoculation in an established mouse model. The authors contribute significantly in the detailed transcriptomic definition of changes during disease progression, especially during the early and almost asymptomatic stages.
The brain region chosen to perform their analysis is logical as the hippocampus shows clear signs of neuronal degeneration in prion disease progression and furthermore …
Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.
Learn more at Review Commons
Referee #1
Evidence, reproducibility and clarity
The authors present a well written article describing distinct transcriptomic profiles generated by RNA sequencing analysis of hippocampus, a distinct anatomical area, at well spaced and defined time points of clinical progression following prion inoculation in an established mouse model. The authors contribute significantly in the detailed transcriptomic definition of changes during disease progression, especially during the early and almost asymptomatic stages.
The brain region chosen to perform their analysis is logical as the hippocampus shows clear signs of neuronal degeneration in prion disease progression and furthermore provides a well defined area for analysis that is easily accessible experimentally; Although, more information would be needed to strengthen this choice in relation to the hippocampus playing a key role in the initiation stages of the disease. It remains an anatomical subset of the whole brain and the study would benefit if extended to include other affected areas.
The article presents comprehensive bioinformatics analysis of the gene expression profiles, during disease progression and continues focusing on two early stages whose profiles clearly cluster together. The authors elegantly query the transcriptomic data extrapolating clusters representative of different cell types and conclude that at preclinical stages microglial-related DEGs are enriched. Importantly, data trends are replicated in an independent animal cohort supporting the experimental design, reproducibility and bioinformatics analysis. Enriched microglial populations from challenged animals compared to controls, would have added more value to the approach.
The authors proceed to conclude that these transcriptomic enrichment of microglial related DEGs are suggestive of driver events in the initiation of prion disease. Although the statement is gaining a lot of interest in the current literature, it is yet immature to conclude from only RNA sequencing data that microglial neuroinflammation is the causative driver event and not the result of the infection and subsequent neurodegeneration. Taking also into consideration the route of infection (ic) which is expected to initiate an acute immune response in the brain.
Towards that comment, the immunohistochemistry data should show increased immune reaction from the early time points pi. Also, the paper would gain significantly, if there were random as well as targeted (eg microglial specific) molecular targets selected, for independent validation by Real-time QC PCR and immunohistochemistry. This would be especially interesting if it was combined with the targets that showed selective splicing like Ctsa, a microglial related gene.
RNA binding deaminase proteins show a similar pattern to a recent report, strengthening the finding that protein levels do not change and/or compensate with other RNA binding and editing enzymes, even though edited targets and editing frequency shift significantly.
The authors continue with RNA editing analysis concluding that they did not find any (apart from two targets being edited) differential RNA editing sites contradictory to a recent study. We believe that this contradiction is a premature conclusion since, the analysis was based on an older protocol that was published by the same group based on GTAK version 3.4.0 from 2011. The predicted RNA edited sites were only based in previously catalogued samples from hippocampus of young mice by Stilling et al 2014. They did not take into account C-U editing in all genomic locations in the whole brain regardless of aging or region. Also, the depth of sequencing was not taken into account which would increase the novel identification of editing sites instead of being limited to previously identified non-validated RNA editing. The study would significantly benefit from Sanger sequencing validation of random and non random edited targets. How do the identified targets validate?
Finally, the study concludes with the administration of young plasma at 8 weeks (early stage of the disease) and the authors support that this intervention improves the phenotype of the affected animals without lifespan changes. In our view, this part of the study should either be omitted, or full transcriptomic and clinicopathological improvement should be demonstrated with clear emphasis on microglial-related molecular targets.
Minor comment:
Other behavioral tests such as T-maze, Morris water-maze, novel object recognition, wouldn't it be better suited for memory assessment?
Significance
The authors present a very detailed and informative transcriptomic profiling of a well structured in vivo experiment with a satisfactory number of time points that has provided significant transcriptomic and splicing information at the preclinical stage of the disease. The field would definitely benefit from such a profile oriented approach however the above should be sufficiently addressed.
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