Rapid and inducible mislocalization of endogenous TDP43 in a novel human model of amyotrophic lateral sclerosis

ALS is a devastating neurodegenerative disorder characterized by the relentless degeneration of motor neurons (MNs) in both the brain and spinal cord (Brown and Al-Chalabi, 2017). This degeneration precipitates a cascade of symptoms including muscle weakness, atrophy, and paralysis, eventually leading to respiratory failure and death, typically within three to five years after the onset of symptoms (Hardiman et al., 2017).

A hallmark of ALS pathology is the aberrant behavior of the TAR DNA-binding protein 43 (hereafter TDP43). In ALS patients, TDP43, which normally resides in the nucleus, becomes mislocalized, forming aggregates in the cytoplasm of neurons and glial cells (Neumann et al., 2006). This phenomenon, termed TDP43 proteinopathy, is implicated in the majority of ALS cases and is considered a central player in the disease’s pathogenesis (Ling et al., 2013). TDP43 proteinopathy is a common feature in multiple age-associated neurodegenerative diseases, including ALS, limbic-predominant age-related TDP43 encephalopathy (LATE), frontotemporal dementia (FTD), and Alzheimer’s disease (AD) (de Boer et al., 2020). TDP43 (encoded by TARDBP) is an RNA-binding protein that plays a critical role in RNA metabolism, encompassing RNA splicing (Donde et al., 2019; Polymenidou et al., 2011; Arnold, 2012; Ling et al., 2015), stabilization (Sidibé et al., 2021), and transport (Nagano et al., 2020; Chu et al., 2019), thus ensuring proper neuronal function (Gimenez et al., 2023). For example, recent studies have demonstrated cryptic exon (CE) inclusion triggered by loss of nuclear TDP43 (Ling et al., 2015), especially in transcripts of important neuronal genes UNC13A (Brown et al., 2022; Ma et al., 2022) and STMN2 (Klim et al., 2019; Melamed et al., 2019). Additionally, TDP43 associates with the microRNA biogenesis machinery and affects microRNA expression (Buratti et al., 2010; Kawahara and Mieda-Sato, 2012; Paez-Colasante et al., 2020). Accordingly, widespread dysregulation of microRNA levels has been reported in spinal tissue obtained post-mortem from sporadic ALS cases (Reichenstein et al., 2019; Emde et al., 2015; Figueroa-Romero et al., 2016; Gagliardi et al., 2019).

Current cellular models aimed at investigating TDP43 mislocalization involve mutating the TDP43 nuclear-localization signal, using mutant versions identified in familial ALS patients, or the use of pharmacological agents to induce stress (Barmada et al., 2010; Zuo et al., 2021; Ziff et al., 2023; Walker et al., 2015). Despite the insights gained from these models, they harbor inherent limitations. Overexpression may not represent physiological conditions, TDP43 is found to be mutated in <0.5% of all ALS cases, and pharmacological induction might induce events unrelated to the disease. Furthermore, CEs identified in ALS/FTD cases are poorly conserved beyond primates, making it challenging to investigate the contribution of splicing defects to ALS pathophysiology using animal models (Baughn et al., 2023). Human induced pluripotent technology (iPSCs) offers a powerful platform that addresses some of these issues with animal models, enabling the development of human models of ALS in vitro (Giacomelli et al., 2022). A recent study employed sporadic ALS (spALS) spinal cord extracts to induce TDP43 proteinopathy in iPSC-derived MNs (Smethurst et al., 2020). However, the model’s utility is limited by the small percentage of neurons showing TDP43 pathology and the difficulty in producing spALS spinal extracts consistently and in large quantities.

In this study, we present an innovative human model of TDP43 proteinopathy that allows us to trigger cytoplasmic mislocalization of endogenous non-mutated TDP43 on demand in healthy control iPSC-MNs at scale (Figure 1A). This technological advancement offers an unprecedented level of insight into TDP43 proteinopathy and its role in ALS.

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R script to analyse CC3 intensities for clone E5 motor neuron (MN).

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R script to analyse CC3 intensities for clone E8 motor neuron (MN).

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R script to analyse dendritic complexity for clone E5 motor neuron (MN).

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R script to analyse dendritic complexity for clone E8 motor neuron (MN).

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We fused green fluorescent protein (GFP) to the C-terminus of TARDBP in its endogenous locus in healthy control iPSCs using CRISPR-Cas9 genome editing (Figure 1A) and selected iPSC clones with a homozygous knock-in (Figure 1—figure supplement 1A). We initially ascertained that the integration of GFP did not adversely impact the differentiation of iPSCs into motor neurons (MNs). To this end, iPSCs engineered with TDP43-GFP were subjected to differentiation directed towards the MN lineage, employing protocols we had established in previous studies (Namboori et al., 2021; Hawkins et al., 2022). Based on the expression of established MN markers - ISLET1 (ISL1) and neurofilament-M (NF-M) - we confirmed that the edited iPSCs (with GFP integration) efficiently differentiated into MNs (Figure 1—figure supplement 1B). Moreover, the TDP43-GFP knock-in MNs did not show significantly altered expression levels of TARDBP, UNC13A, and STMN2, nor did it cause any upregulation of cryptic transcripts in STMN2 or UNC13A (Figure 1—figure supplement 1C). Overall, these results support the premise that the GFP knock-in had no detrimental effects on the iPSCs' ability to differentiate into MNs or TDP43 function.

These engineered iPSCs, hereafter called TDP43-GFP iPSCs, were differentiated into MNs (called TDP43-GFP MNs) where ~80% of the cells in culture immunostained positive for ISL1. We expressed an anti-GFP nanobody (12 kDa) using adeno-associated viruses (AAVs) in the TDP43-GFP MNs. Expression of the nanobody (deemed the control nanobody) did not affect TDP43 localization from the nucleus (Figure 1B). We engineered the nanobody with a nuclear export signal (NES). Expression of the NES-nanobody in the TDP43-GFP neurons caused relocation of the fusion protein to the cytoplasm with a concomitant loss in the nucleus (Figure 1B,C, Figure 1—figure supplement 2A). We observed that TDP43 mislocalization leads to reduced dendrite complexity and neuronal soma swelling (Figure 1D, Figure 1—figure supplement 2A) and an increase in cleaved caspase-3 activation (Figure 1D, Figure 1—figure supplement 2B), which is an indicator of apoptosis. We confirmed that expression of the nanobodies in unedited iPSCs did not lead to apoptosis activation or dendrite defects, confirming that the observed phenotypes are due to TDP43 mislocalization (Figure 1—figure supplement 2C). Additionally, we observed TDP43 puncta reminiscent of aggregates in the cytoplasm of MNs displaying mislocalized TDP43 that varied in size and number across individual neurons (Figure 1E,F, Figure 1—figure supplement 1D).

Having demonstrated that our model can recapitulate cellular features observed in sporadic ALS, we next explored the molecular consequences triggered by TDP43 proteinopathy. Previous studies have highlighted the prevalence of alternative splicing defects affecting transcripts expressed from UNC13A and STMN2 in ALS (Brown et al., 2022; Ma et al., 2022; Klim et al., 2019; Melamed et al., 2019). These splicing defects are considered hallmarks in the progression of the disease. Given the significance of this phenomenon, we sought to ascertain if MNs expressing the NES nanobody exhibit these characteristic splicing defects. We performed RT-qPCR analysis on motor neurons that expressed the control or NES nanobody. The results strikingly mirrored the commonly observed ALS profile, showing inclusion of cryptic exons in both UNC13A and STMN2 and a reduction in the abundance of canonical transcripts (Figure 1—figure supplement 2D). This demonstrated that our model proficiently recapitulates the critical molecular features observed in sporadic ALS.

Next, we ventured to explore the molecular consequences triggered by TDP43 proteinopathy across the whole transcriptome. We performed transcriptomic analysis on day 40 TDP43-GFP MNs to assess changes in the gene expression profiles due to TDP43 mislocalization. Principal component analysis (PCA) demonstrated that the primary axis of variance (90%) is related to the expression of the control and NES nanobody, while the much smaller second PC component is related to the two clones (Figure 2A). Subsequently, we conducted a differential gene expression analysis using DESeq2 and visualized the results via a volcano plot. Our analysis revealed differential expression of hundreds of genes with a fold change of ≥2 and false discovery rate (FDR)<0.01, suggesting a profound impact of TDP43 dysfunction on the transcriptome of MNs (Figure 2B). Gene ontology (GO) analysis of the differentially expressed genes highlighted a significant enrichment of pathways related to synaptic dysfunction and cytoskeletal defects in axons and dendrites amongst downregulated genes (Figure 2C). This finding is of considerable relevance to ALS pathogenesis, as neurons affected by ALS often exhibit impairments in these functions. In contrast, upregulated genes were enriched for GO terms related to RNA processing, including the nonsense-mediated decay (Figure 2C).

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Leafcutter analysis to analyse splicing changes due to TDP43 mislocalisation.

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Given that alternative splicing (AS) defects are a hallmark of sporadic ALS, we utilized Leafcutter (Li, 2018) to analyze potential alternative splicing in MNs caused by TDP43 mislocalization. Our analysis identified alterations in the splicing of 175 genes, including UNC13A and STMN2 (ΔPSI >0.1, adjusted p-value <0.01). To gain functional insights into these splicing defects, we performed pathway enrichment analysis on affected genes, identifying a significant enrichment of terms related to synaptic development (FDR <0.01). Furthermore, to gain a mechanistic understanding of the role of TDP43 in the observed splicing defects, we compared the splicing results with TDP43 eCLIP data generated in the SH-SY5Y neuroblastoma cell line (Tam et al., 2019). Interestingly, only 35% of the splicing changes were proximal to a TDP43 binding site (Figure 2—figure supplements 1 and 2). This suggests that the loss of TDP43 from the nucleus may be responsible for a subset of the observed splicing defects, but not all. This indicates the possibility of additional indirect underlying mechanisms that may include dysregulation of other RBPs or epitranscriptomic modifications of the RNA targets (McMillan et al., 2023). To gain deeper insights into the observed splicing patterns due to TDP43 mislocalization, we employed the Oxford Nanopore Technologies (ONT) long-read sequencing platform to generate RNA-seq data at the isoform level. Our investigation predominantly focused on STMN2 due to its significance in ALS and a substantial number of reads (>100) mapping to this gene. Employing our FICLE pipeline (Leung et al., 2023), we identified a total of 476 isoforms related to STMN2. Out of these, 17 isoforms were congruent with the exonic structure of known reference isoforms. Notably, 40 isoforms, accounting for 8.4% of the total, were characterized by a cryptic exon (CE) starting at chr8:80529057 (Figure 2—figure supplement 3A). These isoforms with the CE were exclusively expressed in TDP43-GFP MNs that expressed the NES nanobody. Furthermore, the ONT data revealed that STMN2 isoforms exhibit variable CE lengths, with different CE lengths corresponding to widely varying expression levels of the parent isoform (Figure 2—figure supplement 3B). Importantly, the isoforms containing the CE were predominantly short, truncated, and predicted to be non-protein coding. Surprisingly, four of these CE-containing isoforms manifested a novel exon, 114 bp in length, positioned upstream of the CE (Figure 2—figure supplement 3A). Our findings reveal a potentially significant variability in the splicing alterations induced by TDP43 proteinopathies, even within a single gene. This highlights the power of using long-read sequencing as a method for uncovering nuanced changes in splicing alterations in neurodegenerative diseases.

We compared our splicing results with publicly available transcriptomic data generated from cortical neuronal nuclei with or without TDP43 purified from ALS patient tissue post-mortem. At a stringent FDR threshold of 0.01 and ΔPSI >0.1, we detected 90 genes as alternatively spliced in nuclei that showed a loss of TDP43 using Leafcutter. Thirty-four out of these 90 genes were also detected in our iPSC model (Figure 2D), indicating strong concordance between the iPSC model and patient data, despite the differences in sample origin and neuronal subtype. Importantly, all 34 genes displayed an identical splicing event. To evaluate whether the observed splicing changes were due to nuclear loss of TDP43, we compared our splicing results with transcriptomic data generated in iPSC-derived MNs and iNeurons after TDP43 knockdown (KD) (Figure 2E and F). In accordance with the model that nuclear loss of TDP43 drives splicing changes, we observed a significant overlap between splicing defects due to a global loss of TDP43 and our mislocalization model (Figure 2E and F). However, a number of genes that displayed splicing changes due to TDP43 mislocalization were not affected by TDP43 KD in either dataset (143 genes for the GSE121569 and 79 genes for the PRJEB42763 dataset). This indicates that nuclear loss of TDP43 alone cannot entirely explain the widespread defects in AS.

To generate a robust list of AS events associated with TDP43 pathology, we compared genes identified in our RNA-seq data with those from ALS/FTD post-mortem tissue. We applied an adjusted p-value threshold of 0.01 and a ΔPSI >0.1. Additionally, to ensure further confidence in the identified changes, we required that each event be statistically significant at a stringent p-value threshold of 1e-4 in at least one dataset. Our analysis identified 12 genes, including STMN2 and UNC13A, that we further investigated using RT-qPCR. This confirmed AS events in all the genes identified, where 9/12 genes displayed a decrease in expression of their canonical transcript levels (Figure 2G). Furthermore, most of these genes also displayed AS changes due to TDP43 KD in iPSC-MNs, although the extent of these changes for a subset of the genes tested was less dramatic (Figure 2—figure supplement 4).

A key drawback with earlier TDP43 models was the inability to characterize early changes after TDP43 mislocalization in neurons. To enable inducible control of TDP43 cytoplasmic localization in our model, we expressed the nanobody under a doxycycline-inducible promoter, and the entire circuit was knocked into the AAVS1 locus in the E8 homozygous TDP43-GFP iPSCs. We called these iPSCs TDP43-GFP-CTRL or TDP43-GFP-NES iPSCs (Figure 3A). We first confirmed that we could induce TDP43 mislocalization in the TDP43-GFP-CTRL/NES iPSC-derived MNs using doxycycline (Dox). Dox (1 µg/ml) triggered significant TDP43 mislocalization in the TDP43-GFP-NES MNs, while the TDP43-GFP-CTRL MNs and the TDP43-GFP-NES MNs without Dox maintained nuclear TDP43 (Figure 3B). Furthermore, we observed cytoplasmic TDP43 puncta in the NES line (Figure 3C), and a significant increase in phosphorylated TDP43 without a change in the total TDP43 protein levels upon mislocalization (Figure 3D, E, Figure 3—figure supplement 2). We noted that the TDP43 mislocalization alone did not induce significant levels of G3BP1+ stress granules (SG) (Figure 3—figure supplement 1). When treated with sodium arsenite, both control and NES MNs displayed cytoplasmic SG (Figure 3—figure supplement 1). However, in NES MNs treated with SA, only a subset of cytoplasmic TDP43 puncta co-localized with G3BP1+ stress granules (Figure 3—figure supplement 1).

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To detect early changes in expression and splicing post-TDP43 mislocalization, we performed a time-course analysis of TDP43-GFP-NES at 4-, 8-, 12-, and 24-hr post-Dox addition. Notably, we observed TDP43 mislocalization as early as 8 hr after Dox treatment (Figure 4A), which was accompanied by significant AS errors in all 12 genes (Figure 4B). This suggests that dysfunctional AS could be one of the incipient molecular events in ALS pathogenesis due to TDP43 mislocalization. Transcriptomic analysis of day 40 MNs uncovered splicing defects, including cryptic exon inclusions and isoform switching in 494 genes (adjusted p-value <0.01 and ΔPSI >0.1), with significant enrichment in pathways related to synaptic function and the cytoskeleton (Figure 3—figure supplement 3).

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A significant area of research in the field of ALS involves pinpointing the upstream triggers responsible for causing the mislocalization of TDP43. The underlying premise of these investigations is that eliminating the trigger may potentially reverse the mislocalization of TDP43. However, it remains to be confirmed whether this hypothesis holds true. We wanted to ascertain whether TDP43, once mislocalized, self-perpetuates in its mislocalized state even after the initial trigger has been removed.

To investigate whether TDP43 mislocalization is self-perpetuating, we tagged both the control and NES nanobody with a V5 tag to track their expression. These were introduced into TDP43-GFP MNs using lentiviruses under a doxycycline (Dox)-inducible promoter. We induced TDP43 mislocalization by adding Dox to iPSC-derived MNs at day 20. After five days (day 25), Dox was withdrawn, and neurons were harvested 21 days later (day 46). As a benchmark of successful mislocalization, cultures were continuously treated with Dox (Constant Dox), while neurons expressing the control nanobody served as controls, displaying nuclear TDP43. TDP43 localization was assessed using immunofluorescence microscopy, and nanobody expression was evaluated via V5 immunostaining.

As expected, neurons in the Constant Dox NES condition exhibited significant TDP43 mislocalization, while TDP43 remained nuclear in the Constant Dox control MNs, confirming the specificity of Dox-induced mislocalization (Figure 5A and B). Following Dox withdrawal, TDP43 localization was largely restored to the nucleus. However, a subset of neurons retained cytoplasmic TDP43 even after 21 days (Figure 5A). Super-resolution microscopy further revealed persistent cytoplasmic TDP43 in these neurons, despite near undetectable nanobody expression (Figure 5C), suggesting that in some cells, TDP43 mislocalization may become self-sustaining. Our data indicates that removal of the initial trigger may be insufficient to completely reverse TDP43 once it has been mislocalized.

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Finally, since TDP43 is involved in microRNA biogenesis, we sought to analyze changes in the microRNA profiles associated with TDP43 mislocalization. For this purpose, we carried out small RNA sequencing on day 40 MNs after triggering TDP43 mislocalization at day 20 by the addition of doxycycline. Our analysis revealed a striking alteration in the landscape of microRNA expression as a result of TDP43 mislocalization. Principal component analysis (PCA) demonstrated distinct separation of the control and mislocalized samples (PC1 77%), emphasizing the profound impact of TDP43 mislocalization on microRNA profile (Figure 3—figure supplement 4A).

Around 150 microRNAs were found to be significantly altered (FDR <0.01 and fold change ≥1.5) upon TDP43 mislocalization. Our data captured downregulation of the microRNAs miR-218, and miR-9, which have previously been shown to be downregulated in ALS MNs (Reichenstein et al., 2019; Zhang et al., 2013). Interestingly, these changes were not unidirectional; almost equal numbers of microRNAs were upregulated or downregulated (Figure 3—figure supplement 4B). The results of this study indicate that TDP43 mislocalization leads to global dysregulation of microRNA expression in iPSC-derived MNs. However, it is noteworthy that our observations contrast with those found in postmortem tissue studies, where all differentially expressed microRNAs were reported to be downregulated. This divergence in findings may suggest that the uniform downregulation observed in postmortem tissues could be attributed to changes that are triggered by end-stage dying neurons, which might not represent the whole spectrum of molecular alterations, especially early in the disease progression.

We wanted to evaluate whether alterations in microRNA expression profiles induced by TDP43 mislocalization are congruent with the changes caused by TDP43 knockdown. For this investigation, small RNA sequencing was utilized to assess microRNA expression in motor neurons (MNs) at day 30 following the knockdown of TDP43 using shRNAs. Again, principal component analysis revealed a distinct separation between all control and TDP43 knockdown samples, indicating a clear impact of TDP43 knockdown on microRNA expression profiles (Figure 3—figure supplement 4C). However, a striking contrast was observed in the number of microRNAs affected by TDP43 knockdown as compared to TDP43 mislocalization. Specifically, in the case of TDP43 knockdown, only one microRNA (miR-1249–3 p) exhibited a significant change (FDR <0.01 and a fold change of 1.5) (Figure 3—figure supplement 4D). This is in stark contrast to the observations made when TDP43 was mislocalized, where over 150 microRNAs displayed altered expression. To avoid setting thresholds in our comparisons, we first ranked the microRNAs impacted by TDP43 knockdown based on their fold changes. Subsequently, we utilized gene set enrichment analysis (GSEA) to determine if the microRNAs disrupted by TDP43 mislocalization significantly coincided with our knockdown data. We observed a substantial overlap between microRNAs that were downregulated due to TDP43 mislocalization and those downregulated following TDP43 knockdown (Figure 3—figure supplement 4E). However, we did not observe a significant overlap for microRNAs that were upregulated in both scenarios (Figure 3—figure supplement 4F). Our data suggest that mislocalized TDP43 selectively affects the expression of a subset of microRNAs. Additionally, these observations highlight the possibility that the nuclear loss and cytoplasmic gain of TDP43 induce distinct molecular alterations within motor neurons that converge to hasten neuronal dysfunction and demise.

However, we acknowledge that another explanation for the observed differences between microRNA dysregulation and splicing could be the extent of nuclear TDP43 loss. Our knockdown approach resulted in a 60% reduction in TDP43 transcripts. Though this was sufficient to cause splicing defects, it is possible that microRNA dysregulation might be more resilient to TDP43 loss as compared to splicing changes.

The RNA-seq data is available on the Gene Expression Omnibus database with the following accession IDs: GSE290436, GSE290437, GSE290441. All qPCR and western blot analysis data have been included in the supplementary excel file. All data generated or analysed during this study are included in the manuscript and supporting files.

1. 1. Bhinge A
   2. Ganssauge J
   3. Namboori S
   4. Leung S

   (2025) NCBI Gene Expression Omnibus

   ID GSE290441. Rapid and Inducible Mislocalization of Endogenous TDP43 in a Novel Human Model of Amyotrophic Lateral Sclerosis.

   https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE290441
2. 1. Bhinge A
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   4. Leung S

   (2025) NCBI Gene Expression Omnibus

   ID GSE290437. Rapid and Inducible Mislocalization of Endogenous TDP43 in a Novel Human Model of Amyotrophic Lateral Sclerosis.

   https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE290437
3. 1. Bhinge A
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   3. Namboori S
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   (2025) NCBI Gene Expression Omnibus

   ID GSE290436. Rapid and Inducible Mislocalization of Endogenous TDP43 in a Novel Human Model of Amyotrophic Lateral Sclerosis.

   https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE290436

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Author details

1. Johanna Ganssauge

   1. Living Systems Institute, University of Exeter, Exeter, United Kingdom
   2. Biosciences, University of Exeter, Exeter, United Kingdom

   Contribution

   Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-5150-5445

2. Sophie Hawkins

   1. Living Systems Institute, University of Exeter, Exeter, United Kingdom
   2. Clinical and Biomedical Sciences, University of Exeter, Exeter, United Kingdom

   Contribution

   Software, Formal analysis, Writing – review and editing

   Contributed equally with

   Seema Chandramohan Namboori

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-1977-5255

3. Seema Chandramohan Namboori

   1. Living Systems Institute, University of Exeter, Exeter, United Kingdom
   2. Clinical and Biomedical Sciences, University of Exeter, Exeter, United Kingdom

   Contribution

   Validation, Methodology, Writing – review and editing

   Contributed equally with

   Sophie Hawkins

   Competing interests

   No competing interests declared

4. Szi Kay Leung

   Clinical and Biomedical Sciences, University of Exeter, Exeter, United Kingdom

   Contribution

   Software, Formal analysis, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-5607-4688

5. Jonathan Mill

   Clinical and Biomedical Sciences, University of Exeter, Exeter, United Kingdom

   Contribution

   Supervision, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-1115-3224

6. Akshay Bhinge

   1. Living Systems Institute, University of Exeter, Exeter, United Kingdom
   2. Clinical and Biomedical Sciences, University of Exeter, Exeter, United Kingdom

   Contribution

   Conceptualization, Data curation, Software, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing

   For correspondence

   a.bhinge@exeter.ac.uk

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-2939-099X

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