Prion diseases disrupt the glutamate/glutamine metabolism in skeletal muscle

  1. Davide Caredio
  2. Maruša Koderman
  3. Karl Frontzek
  4. Silvia Sorce
  5. Mario Nuvolone
  6. Juliane Bremer
  7. Petra Schwarz
  8. Stefano Sellitto
  9. Nathalie Streichenberger
  10. Claudia Scheckel
  11. Adriano Aguzzi

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Abstract

In prion diseases, aggregates of misfolded prion protein (PrP Sc ) accumulate not only in the brain but also in extraneural organs. This raises the question whether prion-specific pathologies arise also extraneurally. Here we sequenced mRNA transcripts in skeletal muscle, spleen and blood of prion-inoculated mice at eight timepoints during disease progression. We detected gene-expression changes in all three organs, with skeletal muscle showing the most consistent alterations. The glutamate-ammonia ligase ( GLUL ) gene exhibited uniform upregulation in skeletal muscles of mice infected with three distinct scrapie prion strains (RML, ME7, and 22L) and in victims of human sporadic Creutzfeldt-Jakob disease. GLUL dysregulation was accompanied by changes in glutamate/glutamine metabolism, leading to reduced glutamate levels in skeletal muscle. None of these changes were observed in skeletal muscle of humans with amyotrophic lateral sclerosis, Alzheimer’s disease, or dementia with Lewy bodies, suggesting that they are specific to prion diseases. These findings reveal an unexpected metabolic dimension of prion infections and point to a potential role for GLUL dysregulation in the glutamate/glutamine metabolism in prion-affected skeletal muscle.

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    Reply to the reviewers

    We thank the referees for their insightful comments and constructive feedback, which have undoubtedly strengthened our manuscript.

    Reviewer #1 Comment:

    Absence of evidence demonstrating the presence of prions or prion-seeding activity in extraneural tissues.

    Response: Our study focuses on all pathophysiological alterations brought about by prion infections in extraneural organs, be they caused directly by prion infections of said organs or through indirect mechanisms. Nevertheless, we share the reviewer's curiosity about a possible correlation between these changes and the presence of prion-seeding activity. We propose to include additional data demonstrating prion presence and seeding activity in skeletal muscle at various timepoints. This will be achieved by employing proteinase K digestion followed by Western blot (PK-WB) and real-time quaking-induced conversion (RT-QuIC) assays to provide a robust correlation with our transcriptomic analyses and Glul upregulation.

    Revision: We have conducted preliminary experiments using PK-WB and RT-QuIC assays. These experiments were performed on terminal-stage prion-infected samples and related controls. If prion presence is detected at this stage, we plan to extend the analysis to earlier stages, specifically at 16 weeks post-inoculation (wpi) and 8 wpi, to track the progression of prion-seeding activity over time.

    Western blot analysis was performed on skeletal muscle homogenates at the terminal stage of prion disease in mice infected with three prion strains (RML6, ME7, and 22L) and related NBH control. Control samples include CNS brain homogenates, showing prion presence (PrPSc) in RML6 but not in NBH. Neither skeletal muscles from NBH nor from prion-infected samples show detectable prions, indicating that PK-WB may lack the sensitivity to detect prions in skeletal muscle or that prion levels are below detection thresholds (Revision Figure 1A) for this specific technique.

    Next, we performed RT-QuIC assays on muscle homogenates using different protocols, including sodium phosphotungstic acid (NaPTA) enrichment (Revision Figure 1B). NaPTA binds and precipitates PrPSc in the presence of MgCl2, removing contaminants and concentrating PrPSc. For this protocol, 100 µg of muscle homogenates were treated with benzonase to degrade DNA contaminants. Then, 4% NaPTA and 170 mM MgCl2 were added, resulting in a final NaPTA concentration of 0.3%. The samples were incubated at 37{degree sign}C while shaking at 1500 rpm for 2 hours, followed by centrifugation at 15,000 g for 30 minutes to precipitate PrPSc. The resulting pellets were used to seed RT-QuIC reactions. Each biological replicate was run in quadruplicate, and replicates were considered positive only if at least 3 out of 4 technical replicates showed detection. Results indicated no amplification for NBH samples. For RML6 skeletal muscles, 2 out of 3 biological replicates were positive. For ME7, 0 out of 4 biological replicates were positive. For 22L, 1 out of 3 biological replicates was positive.

    Using the same protocol without NaPTA (Revision Figure 1C), two positive samples were observed in the NBH condition, suggesting that NaPTA is useful for specific prion enrichment.

    Similarly, we combined NaPTA and sarkosyl in our further trial. 10% weight/volume muscle homogenates in 1x PBS containing 2% sarkosyl were centrifuged at 80 g for 1 minute, and the supernatant (500 µl) was collected. If still dirty, further centrifugation at 2700 g for 5 minutes was performed. Then, 500 µl PBS containing 2% sarkosyl was added and incubated for 10 minutes at 37{degree sign}C. Benzonase and MgCl2 (final concentrations 50 U/ml and 1 mM, respectively) were added and incubated for 30 minutes at 37{degree sign}C with shaking at 1500 rpm. NaPTA was added to a final concentration of 0.3% and incubated for 30 minutes at 37{degree sign}C with shaking. Samples were centrifuged at 15,000 g for 30 minutes and resuspended in 20 µl of 0.1% sarkosyl-containing PBS condition (Revision Figure 1D). Using this protocol, we also detected signals in the NBH control.

    These results indicate ongoing challenges in optimizing prion extraction from skeletal muscle. Unlike brain tissue, where prion levels are significantly higher, skeletal muscle presents difficulties due to lower prion concentrations. In brain samples, dilutions still result in positive signals only from prion-enriched conditions. However, for skeletal muscle, prion extraction is not as straightforward, highlighting the need for further refinement of the protocol to achieve reliable detection and differentiation between prion-infected and control samples.

    Inclusion of prion strain with limited extraneural replication. Reliance on three prion strains limits the relevance. Inclusion of a strain with limited extraneural replication is suggested.

    Response: To address this limitation, we propose a comprehensive discussion on the systemic nature of prion diseases, emphasizing the need for future research to explore potential strains with restricted replication patterns.

    Revision: There is a significant interest in prion deposits in skeletal muscles as potential sources of prion spreading. The consumption of beef products from cattle infected with bovine spongiform encephalopathy (BSE) prions caused new variant Creutzfeldt-Jakob disease, raising early concerns about the transmission of prions from cervids to humans (1-3). This remains a hot topic in the field (4-7), underscoring the importance of our longitudinal transcriptomic analysis in different extraneural organs. However, prion strains with restricted extraneural replication which we could use as control have not been described in mice used as prion animal models. According to our knowledge and the existing literature, there is no documentation of any mouse-adapted prion strains that are unable to propagate prions outside the central nervous system (CNS). Although this does not apply to our study, it is important to note that hamster-derived prion strains such as HY and DY exhibit different replication patterns. Hamsters infected with HY TME prions show detectable infectivity and/or PrPSc in the CNS, lymphoreticular system, skeletal muscle, nasal secretions, and blood (8-11). Conversely, prion infectivity and/or PrPSc in DY TME-infected hamsters is restricted to the CNS (12-14).

    In mice, the situation is quite different, and there are no prion strains with restricted extraneural replication. Instead, studies have focused on models where prion protein (PrPC) is absent in all tissues except skeletal muscle, which is essentially the opposite of the condition requested by the reviewer. For instance, research has demonstrated that prion levels in skeletal muscles are 5-10% of those observed in the brain (1). Here, transgenic mice (Tg(α-actin-MoPrP)6906/Prnp0/0) expressing PrPC only in skeletal muscles (and barely detectable in the CNS) were created. After intramuscular prion injection, these mice showed that skeletal muscles could propagate prions (1). Additionally, another study found that prions were not detectable in skeletal muscle at early stages (32 and 60 days post intracerebral prion inoculation) unless experimental autoimmune myositis was induced, which increased prion spread to skeletal muscle (15).

    This comprehensive discussion underscores the absence of a mouse model prion strain with limited extraneural replication, highlighting a gap in current research that our study aims to address indirectly through our systemic approach.

    Clarification on statistical methods. Lack of details on statistical tests used for comparing GLUL levels in Figures 3 and 4.

    Response: We clarified the statistical tests used, specifying whether they are parametric or non-parametric, and provide a rationale for the chosen methods. It is important to note that GLUL upregulation is significant, as evident from Figure 4. At 8 wpi, the fold change for RML6 is above 3, for ME7 is above 1.5, and for 22L is above 2. The fold change in later timepoints is increasingly larger.

    Revision: For Figure 3E, normalized raw counts for the GLUL gene in control and sCJD patients were analyzed using the DESeq2 package, with related false discovery rate (FDR) calculations. DESeq2 is appropriate for RNA-seq data as it models count data using a negative binomial distribution, suitable for overdispersed count data commonly found in RNA-seq experiments. The normalization and FDR calculation ensure that the comparisons between control and sCJD patients are statistically robust.

    In Figure 3G, Western blot densitometry data were analyzed using the Mann-Whitney U test, resulting in a p-value of 0.01072. The Mann-Whitney U test is a non-parametric test that does not assume normal distribution, making it suitable for small sample sizes and non-normally distributed data, which is often the case in Western blot densitometry. For statistical analyses in Figure 4A, Mann-Whitney U test was used. In Figure 4C, we applied the t-test (as the standard deviations were consistent) with Bonferroni correction to account for multiple comparisons. The t-test is a parametric test suitable for normally distributed data, and the Bonferroni correction adjusts for the increased risk of Type I errors when multiple comparisons are made, ensuring the results are not due to chance. Additionally, we used one-way ANOVA corrected with Kruskal-Wallis, a non-parametric method, to confirm our findings (Revision Figure 2). The results from both statistical tests were in strong agreement, validating our analysis.

    In Supplementary Figure 6, the Mann-Whitney U test was used due to its non-parametric nature, which is suitable for data that do not assume a normal distribution. This test was chosen to provide a robust analysis of the data, which did not fit the assumptions required for parametric tests.

    These methods were selected based on the data distribution and the need for accurate statistical analysis to validate the significance of our findings. The choice of DESeq2 for RNA-seq data, Mann-Whitney U for non-normally distributed data, and t-tests with Bonferroni correction for normally distributed data ensures that our analyses are appropriately tailored to the characteristics of the data, providing reliable and valid results.

    Details on CJD cases analyzed. Information regarding the types of CJD analyzed is missing.

    Response: We ensured that details on the types of CJD cases analyzed, including genotype, strain type, and age, are clearly presented in the main text and supplementary materials.

    Revision: A comprehensive description of the sCJD cases, including genotype, strain type, and age, was accessible in Supplementary Table 5 (and here, in Revision Figure 3). This table also provides the reasons why some biosamples were excluded from the final bulk RNA sequencing and downstream analysis.

    Recent publications on prion seeding activity. Mention recent publications showing prion seeding activity in extraneural tissues.

    Response: We will update the Introduction section to include references to recent studies demonstrating prion seeding activity in extraneural tissues of sCJD and vCJD patients using RT-QuIC or PMCA assays.

    Revision: We will discuss and cite additional papers on this topic, highlighting the growing body of evidence for prion seeding activity in extraneural tissues. These references will provide a comprehensive background on the detection and significance of prion seeding in peripheral tissues, thereby strengthening the context and relevance of our study.

    Reviewer #2 Comment:

    The RNA sequencing of human skeletal muscle samples identified only one common gene between human and mouse conditions. There is concern that this gene may be a bystander result of terminal disease stage pathophysiology in both animals and human.

    Response: We strengthened the evidence supporting GLUL as early and altered gene by including additional timepoint analyses and showing its presence at earlier disease stages.

    Revision: The upregulation of GLUL cannot be attributed to a bystander effect result of terminal disease stage pathophysiology, as it is consistently upregulated across all analyzed timepoints. We performed weighted gene co-expression network analysis (WGCNA) grouped by disease stages and GLUL belongs to the orange module (upregulated genes throughout all timestages in both main (Figure 2A - original manuscript) and validation (Figure 3A - original manuscript) cohort). We also included a comparison of GLUL expression between RML6 and NBH. As shown in the figure (Revision Figure 4), GLUL is upregulated at all individual timepoints. This finding is corroborated at both the transcriptional and protein levels, including other prion strains (Figure 4 - original manuscript) from a further animal cohort for RML6 condition. This consistent upregulation across various stages supports GLUL as a robust altered genes and possible biomarker for prion disease progression.

    Cautious interpretation of GLUL dysregulation specificity. The claim that GLUL dysregulation is specific to prion diseases should be mentioned more cautiously due to the small sample number of other neurodegenerative diseases (NDs). The finding would be stronger if a meta-analysis of possible available data from human ND cohorts could be examined.

    Response: We will rephrase our conclusion to acknowledge the sample size limitation and suggest further studies for confirmation. However, due to the poor sample availability of skeletal muscles biopsis from other NDs, related metadata are complicated to be found.

    Revision: Modify the discussion section to reflect a more cautious interpretation, emphasizing the need for larger cohort studies to confirm GLUL specificity.

    Post-transcriptional modifications of GLUL. Explore the possibility of GLUL being modified through RNA editing affecting its expression.

    Response: We investigated the potential post-transcriptional modifications of GLUL, such as RNA editing, and their impact on its expression and function.

    Revision: We will add a paragraph named "Lack of post-transcriptional changes in extra-neural organs of prion-inoculated mice".

    Results: We calculated the genome-wide adenosine-to-inosine editing index (AEI) to measure global RNA editing levels (16), the preferential site of RNA editing in mammals. Blood global editing levels rose steadily during aging but were independent of prion inoculation (Revision Figure 5A). No AEI differences were seen in muscle or spleen (Revision Figure 5B and C). To determine recoding of individual transcripts, we aligned our sequencing results to previously published high-confidence AEI recoding sites (17). We found Flnb and Copa in the spleen and Cog3 in blood to be significantly recoded (Revision Figure 5D). However, Glul did not show significant recoding.

    Alternative splicing can give rise to disease-associated differentially used transcripts (18). In contrast to our previous results in the brain (19), the present alternative splicing analyses in extraneural organs showed only minor alterations (Revision Figure 5E). Necap2, Myl6 and Srsf5 transcripts were alternatively spliced across multiple organs and prion incubation times (Revision Table 1). Only in two out of a total of 21 splice variants differential transcript usage was accompanied by differential gene expression: upregulation of Myl6 in blood at 4 wpi and downregulation of *Ms4a6c *in blood at 14 wpi.

    Discussion: Except for Flnb, Copa and Cog3, we were unable to find evidence for broad dysregulation of posttranscriptional RNA editing, in contrast a recent report (20) but in line with our previous findings (19). Furthermore, splicing analysis suggests that alternative splicing was largely unlinked from gene expression changes.

    Method: Adenosine-to-inosine editing index (AEI) was calculated as previously published (16). Herein, raw fastq reads were uniquely aligned to a murine mm10 reference genome using STAR v2.7.3 with the filter outFilterMultimapNmax=1. RNAEditingIndexer (https://github.com/a2iEditing/RNAEditingIndexer) was used to calculate per-sample AEI.

    We identified gene-specific RNA editing based on a recently published list of high-confidence targets of Adar (17)as follows. RediToolsKnown.py from REDItools (21) was applied on uniquely aligned samples as mentioned above. This yielded per-site lists of A-to-I editing on which we applied the following thresholds: (a) a minimum of 3 alternative reads per site per sample (b) a minimal editing frequency of 1 % per site (c) criteria a) and b) are fulfilled in at least floor(2/3 * n) biological replicates, n is total number of biological replicates per group (d) transcripts of site present in at least 2 biological control replicates. Multiple testing of sites passing above-mentioned thresholds was performed using REDIT (https://github.com/gxiaolab/REDITs) and adjusted for false discovery rate (FDR) according to Benjamini-Hochberg, we considered sites with an FDR For alternative splicing, SGSeq R package (22) was employed to find splicing events characterized by two or more splice variants. Exons and splice junction predictions were obtained from BAM filesPrediction of exons and splice junctions was first made for each sample individually. Then the predictions for all samples were merged and we obtained a common set of transcript features. Overlapping exons were disjoint into non-overlapping exon bins and a genome-wide splice graph was compiled based on splice junctions and exon bins. A single value for each variant was produced by adding up the 5' and 3' counts, or, if these represented the same transcript features, by considering the unique value. These counts were then fed to DEXSeq (23). We analyzed differential usage of variants across a single event, in-stead of quantifying differential usage of exons across a single gene. We retained only variants with at least five counts in at least three samples (of any condition). After filtering, the events associated with a single variant were discarded. Differential analysis was then performed implementing a sam-ple+exon+condition:exon model in DEXSeq. Differentially expressed isoforms were defined as isoforms changing with FDR < 0.05. In the case of differentially used splice variants in muscle on 12 wpi, this dataset was considered as an outlier and hence excluded due to excessively reported splice variants (1,788 events compared to 5 or less on all other time-points and extraneural organs).

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    Referee #2

    Evidence, reproducibility and clarity

    Summary: The authors present a comprehensive transcriptomic analysis of different organ tissue samples (blood, spleen and muscle) from established prion models RML6, or 22L, or ME7 strain mouse-adapted scrapie, at a significant number of timepoints recapitulating early, asymptomatic preclinical, clinical and terminal stages of disease. The transcriptome profile of each tissue at each progression stage is a very useful information, on disease relevant transcriptional changes of variable significance. Eigengene networks were constructed to study the relationships between 39 modules only 2 were significant (orange and dark green) in skeletal muscle from all 3 tissues examined. The authors support they reveal a higher order organization of the late-stage disease transcriptome and provide insights into the modular architecture of gene expression during disease progression (early, presymptomatic and symptomatic) followed by 20 gene hub identification. In the context of network analysis, a high preservation with a Z-summary statistic > 1.96 suggests that the module's connectivity pattern is significantly preserved across different networks of the module's structure as RML6 disease progresses and it is not random compared to control.

    The RNA sequencing of human skeletal muscle samples further validated and only 1 common gene between human and mouse condition confirmed by immunoblotting. The GLUL gene was further investigated in terms of gene and protein expression in various mouse disease models along with human skeletal muscle CJD autopsy material. Their findings did not correlate between human and all mice models completely. The increase in GLUL expression is accompanied by changes in glutamate/glutamine metabolism and reduced glutamate levels in CJD skeletal muscle. These alterations were only specific to prion diseases, as they were not confirmed in other neurodegenerative conditions such as amyotrophic lateral sclerosis, Alzheimer's disease, or dementia with Lewy bodies. The authors propose GLUL dysregulation as a potential novel biomarker for prion disease progression, during the preclinical stages with potentially useful efficacy for monitoring of therapies.

    Comments

    • The RNA sequencing of human skeletal muscle samples identified only 1 common gene between human and mouse condition confirmed by immunoblotting at the terminal stage of the disease. How can they conclude that this specific gene is not a bystander result of the known pathophysiology at the terminal disease stage? The mouse data are not solidly consistent with the biomarker expression.
    • The claim that GLUL dysregulation with a result in glutamate/glutamine metabolism is only specific to prion progression only eventhough interesting should be mentioned with a more cautious way as the sample number of other NDs is small. The finding would be significantly stronger if metanalysis of possible available data of human ND cohorts could be examined.
    • Post-transcriptional modifications have been described as potential contributors to prion pathogenesis therefore, the authors should also explore the possibility of GLUL being modified through RNA editing affecting its expression.
    • The experiments are well designed and executed and the analysis methods are explained in detail. The figures are elegantly presented with adequate information.

    Significance

    The authors present a very well designed and comprehensive transcriptomic analysis of several tissue organs related to prion disease progression and validation data from multiple mouse models as well as human CJD skleletal muscle tissue.

    They provide a strong and logic experimental strategy with adequate validation comparing multiple strains with disease onset differences and human tissue. The result was to identify GLUL as a potential biomarker of prion specific disease progression without any overlap with other NDs sharing pathophysiology.

    The finding is interesting to the field but most importantly the established transcriptome profiles available will by of great use for future use from relevant basic research and also translational studies.

    The presented study is an important addition to the field without any other comparable datasets regarding skeletal muscle analysis in CJD.

    Any novel biomarker for progression of prion disease is extremely important and its potential link with pathogenesis would be of paramount importance.

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    Referee #1

    Evidence, reproducibility and clarity

    The manuscript by Caredio et al is a follow-up of their previous work (Sorce et al,PloS Pathogens 2020), wherein they conducted genome-wide transcriptomic analyses on the brains of prion-infected mice throughout the course of the experimental disease. In the present study, the authors extended their analysis to extraneural tissues of prion-infected mice, including hindlimb skeletal muscles, spleen and blood. Their key findings indicate upregulation of the glutamate-ammonia ligase (GLUL) gene in the skeletal muscle, a pattern also observed across different mouse prion strains and notably in human cases of sporadic CJD, albeit in a relatively small cohort.

    A major limitation of the manuscript is the absence of evidence demonstrating the presence of prions or prion-seeding activity, and the lack of correlation with transcriptomic analyses, in any of the extraneural tissues and different timepoints. This omission is surprising given its inclusion in their initial publication in PloS Pathogens. Particularly concerning are the mouse experiments, where intracerebral inoculations were performed, suggesting potential presence of prions in terminal nerve endings and then muscles only at late stage of the disease, due to anterograde axonal transport. The reliance on three prion strains (22L, ME7, and RML) that replicate extraneurally limits the relevance of the study. Including at least one strain with limited or no capacity for extraneural replication could help distinguish whether observed transcriptomic alterations are directly linked to prion replication or are indirect consequences, particularly within the brain. This would also have prevented a significant misinterpretation in the discussion section. The authors delve into the alterations observed in the spleens of affected mice at the terminal disease stage. They attribute these alterations to the consequence of intracerebral inoculation, suggesting a delayed accumulation of prions in lymphatic tissues compared to oral or intraperitoneal inoculation routes. However, considering the high volume and dose inoculated (30 µL 10%), there is likely spillover from the brain, resulting in an intravenous-like inoculation concurrent with the intracerebral infection. Consequently, prion replication occurs rapidly in the lymphoid tissue. Given this, the tardy transcriptomic alterations observed in the spleens become even more surprising.

    Information regarding the statistical tests used to compare GLUL levels in Figures 3 and 4, and whether these tests are parametric or not, is missing. Given the relatively low differences observed and the substantial SEM, clarification on statistical methods is imperative for interpreting the results accurately.

    Providing details on the types of CJD analyzed, such as genotype, strain type, and age, would enhance the manuscript's comprehensiveness. While this information may be available in supplementary Table 8, we had no access to it.

    Minor point: in the introduction, it may be worth mentioning recent publications showing presence of prion seeding activity in many extraneural tissues from humans infected with sporadic CJD and or vCJD, using RT-QuIC or PMCA assays.

    Significance

    Given the aforementioned concerns, the correlates between prion replication and the GLUL/glutamate-glutamine metabolism alterations are thus highly uncertain. This limits the general significance of the study.

  4. Version published to 10.1101/2023.10.31.564879v2 on bioRxiv
  5. Version published to 10.1101/2023.10.31.564879v1 on bioRxiv