miR-1, miR-133a, miR-29b and Skeletal Muscle Fibrosis in Chronic Limb-Threatening Ischaemia.

miR-1, miR-133a, miR-29b and Skeletal Muscle Fibrosis in Chronic Limb-Threatening Ischaemia. | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article miR-1, miR-133a, miR-29b and Skeletal Muscle Fibrosis in Chronic Limb-Threatening Ischaemia. Alan Keane, Clara Sanz Nogues, Dulan Jayasooriya, Michael Creane, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4242453/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Nov, 2024 Read the published version in Scientific Reports → Version 1 posted 12 You are reading this latest preprint version Abstract Chronic limb-threatening ischaemia (CLTI), the most severe manifestation of peripheral arterial disease (PAD), is associated with a poor prognosis and high amputation rates. Despite novel therapeutics approaches being investigated, no significant clinical benefits habe been observed yet. Understanding the molecular pathways of skeletal muscle dysfunction in CLTI is crucial for designing successful treatments. This study aimed to identify miRNAs dysregulated in muscle biopsies from PAD cohorts. Using MI croRNA EN richment TUR ned NET work (MIENTURNET) on a publicly accessible RNA-sequencing database of PAD cohorts, we identified a list of miRNAs that were over-represented among the upregulated differentially expressed genes (DEGs) in CLTI. Next, we validated the altered expression of these miRNAs and their targets in mice with hindlimb ischaemia (HLI). Our results showed a significant downregulation in miR-1, miR-133a, and miR-29b leves in the ischaemic limbs versus the contralateral non-ischaemic limbs. A miRNA target protein-protein interaction network identified extracellular matrix components, including collagen-1a1, -3a1, and − 4a1, fibronectin-1, fibrin-1, matrix metalloproteinase-2 and − 14, and Sparc, which were upregulated in the ischaemic muscle of mice. This is the first study to identify miR-1, miR-133a, and miR-29b as potential contributors to fibrosis and vascular pathology in CLTI muscle, which supports their potential as novel therapeutic agents. Health sciences/Medical research/Pre clinical studies Health sciences/Medical research/Translational research chronic limb-threatening ischaemia fibrosis muscle regeneration microRNAs Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 BACKGROUND Peripheral arterial disease (PAD) most often occurs due to atherosclerotic disease in the peripheral arteries, resulting in skeletal muscle ischaemia distal to the point of vessel narrowing 1 . Most patients with PAD are asymptomatic. However, impaired perfusion of the lower limbs is associated with muscle atrophy, functional decline and increased risk of morbidity and mortality 2 – 5 , even in those patients without obvious symptoms 6 . Patients with PAD can exhibit intermittent claudication (IC), defined as limb pain during physical activity which resolves at rest 7 . This may occur when arterial narrowing is such that limb perfusion is insufficient to meet muscle metabolic demands during exercise. It is estimated that up to 10% of patients with PAD progress or present de novo with chronic limb-threatening ischaemia (CLTI), the most severe manifestation of PAD 8 . CLTI is characterised by chronic ischaemic rest pain, non-healing ulcers, and gangrene and is associated with a high risk of limb loss, cardiovascular morbidity and mortality 7 . Interestingly, most patients with IC do not naturally progress to CLTI 9 – 11 , suggesting that these two manifestations of PAD may represent distinct pathogenic stages of the disease despite similar ischaemic aetiology. Current bioinformatics and omics-based approaches have provided important insights into the pathophysiology of clinical PAD. Ryan et al. recently reported a unique skeletal muscle mitochondriopathy that distinguished patients with CLTI from those with IC 12 . Other authors have utilised this publicly available RNA-sequencing database of PAD cohorts to elucidate the pathological signatures that discriminated CLTI from IC. For instance, Cong et al. identified fibrosis pathways involving transforming growth factor-β (TGF-β), collagen deposition, and vascular endothelial growth factor (VEGF) signalling as a novel gene expression feature for CLTI but not IC 13 . Yao et al. identified several genes encoding subunits of the human complement system as promising markers for discriminating between CLTI and IC 14 . More recently, Ferrucci et al. multi-omics analysis using RNA sequencing and proteomics on PAD skeletal muscle (free from diabetes and CLTI) reported that mitochondrial dysfunction and fibrotic are processes active in PAD without CLTI 15 . These results contradict to some extent the findings from Ryan and Cong et al. In another study using a different transcriptomic dataset, Saini et al. reported differential gene and microRNA (miRNA) expression associated with PAD progression 16 . miRNAs are small non-coding RNAs ~ 22 nucleotides in length which regulate gene expression at the post-transcriptional level 17 and are considered robust regulators of muscle development and homeostasis 18 . miRNAs have been thoroughly investigated in the context of PAD 19 , 20 , in particular, as potential biomarkers in skeletal muscle 21 , 22 and circulation 23 – 26 . However, the full spectrum of dysregulated miRNAs associated with PAD stages is poorly understood. This study aimed to identify dysregulated miRNAs in gastrocnemius muscle biopsies that were differentially expressed in different PAD cohorts. We analysed a publicly available RNA-sequencing database of PAD cohorts 12 using MI croRNA EN richment TUR ned NET work (MIENTURNET), a web tool for miRNA target enrichment and network-based analysis 27 . We hypothesised that transcriptomic analysis using this bioinformatics tool will identify CLTI-specific dysregulated miRNAs and their associated targets. Subsequently, we validated the findings in hindlimb ischaemia (HLI) mice, a preclinical model of CLTI 28 , 29 . METHODS Data Acquisition . RNA-sequencing-based profiles from CLTI, IC and non-PAD adults were acquired from a dataset published by Ryan and colleagues (GSE120642) 12 . In Ryan et al. study, gastrocnemius muscle biopsies were obtained from patients with IC (n=27), CLTI (n=19) and non-PAD controls (n=32) for whole transcriptome sequencing. RNA sequencing was performed by sequencing paired-end (150 bp) reads on an Illumina HiSeq 4000. The authors identified differentially expressed genes (DEGs) in skeletal muscle from CLTI vs. non-PAD control, CLTI vs. IC and IC vs. non-PAD controls using edgeR with a p-value 1.5 12 . The diagnostic criteria, participant demographics, and further methodological detail are illustrated in Ryan et al. study. miRNA-Target Interaction Enrichment Analysi s . DEGs in CLTI vs. non-PAD controls, CLTI vs. IC and IC vs. non-PAD controls were analysed using the online bioinformatics tool MIENTURNET 27 . Upregulated and downregulated DEGs were analysed separately. DEGs were input to the MIENTURENT tool and miRNA-Target Interaction (MTI) enrichment was performed based on validated MTIs in the miRTarBase database. Results were filtered by setting a threshold for the minimum number of MTIs as 2 and FDR < 0.05. The enriched MTIs were visualised using Cytoscape 30 . Protein-Protein Interaction (PPI) Network Analyses . PPI networks were constructed using the STRING database (version 12) 31 and visualised using Cytoscape 30 . Full STRING networks were constructed using a multiple protein query. Network edges represented “evidence”. All available interaction sources were used i.e. text mining, experiments, databases, co‑expression, neighbourhood, gene fusion, and co‑occurrence. The minimum required interaction score was set to the default medium confidence (0.4). Hub nodes were identified in Cytoscape using the CytoHubba plug-in 32 . The maximal clique centrality (MCC) topological analysis method was used to calculate hub nodes. The top 20 hub nodes were visualised in a sub-network. Functional Enrichment using g:Profiler . Functional enrichment analysis was performed based on a previously published protocol 33 . First, functional enrichment was performed using g:Profiler 34 (version e109_eg56_p17). The significance threshold was set at 0.05 and the following data sources were used Gene Ontology (GO) molecular function, GO cellular component, GO biological process, KEGG, Reactome, and WikiPathways. If ambiguous query genes were found, these were manually disambiguated by selecting the most appropriate term when prompted and the query was re-run. Results were filtered in terms of the size of the functional category to facilitate the interpretability of the results. The minimum and maximum term sizes were set at 5 and 1000, respectively, to remove excessively small or large gene sets of limited interpretive value. All results were downloaded for further processing. For functional enrichment analysis, a custom background set based on the following criteria was used. Transcripts that are expressed in skeletal muscle and detected in this RNA-sequencing experiment were identified using the normalised read counts in non-PAD controls, IC and CLTI samples. The threshold cut-off was set as minimum median normalised read count of any DEG. Any transcript that had a normalised read count greater or equal to this value was included i.e. only transcripts that were detected at a level that would have a chance at being identified as a DEG were included as has been previously suggested 35 . “Custom over annotated genes” was selected, such that only annotated genes that were also in the background list were used as background genes. Enrichment Mapping using Cytoscape . Visualisation of functional enrichment data from the g:Profiler output was performed using Cytoscape v3.10.1 30 as well as the EnrichmentMap v3.3.6 36 , AutoAnnotate v1.4.1 37 , and ClusterMaker2 v2.3.4 38 plug-ins. First, using EnrichmentMapping, a new enrichment map was created. The analysis type was set as “Generic/g:Profiler”. The enrichments file from the g:Profiler output and the GMT file downloaded from g:Profiler were loaded into the tool. The FDR cut-off was set to 0.05. Other parameters were left at default settings. To identify major “biological themes”, the resulting enrichment map network was then clustered using AutoAnnotate, which in turn uses ClusterMaker2 and the Markov Clustering (MCL) algorithm 39 . Using the default settings in the “Quick Start” tab, the network was annotated. The automatically generated cluster names were edited manually to reflect the biological theme of the cluster. The clusters were manually arranged to separate sub-networks. For visualisation, clusters with two terms or fewer were manually removed unless connected to a larger cluster. Animals . Male 15 weeks BALB/c nude mice were purchased from Janvier Labs, (France) and were housed in the Bio-Resource Unit (BRU) at the University of Galway, with monitoring and support provided by qualified animal technicians and a veterinary surgeon. All animal experiments were carried out in compliance with the Directive 2010/63/EU and in accordance with ARRIVE guidelines. Ethical approval was granted by the Animal Care Research Ethics Committee (ACREC) at the University of Galway (Ireland) and appropriate individual and project authorizations were granted by the Health Products Regulatory Authority in Ireland (AE19125 /P076). At day 7 post-HLI, mice were euthanised by overdose of anaesthesia (225mg/kg ketamine and 1.5 mg/kg medetomidine solution injected subcutaneously) followed by cervical dislocation, and their body weights were recorded Induction of HLI and assessment of limb function . Unilateral hindlimb ischaemia (HLI) was induced in BALB/c nude mice by ligation of the femoral artery distal to the deep femoral artery, as previously described by our group 40 . Animals were anaesthetised with 75mg/kg ketamine and 0.5 mg/kg medetomidine (Domitor 10) solution injected subcutaneously. Anaesthesia was partially reversed with atipamezole (5 mg/kg). The mice received analgesia (0.05-0.1 mg/kg of buprenorphine 8-12h for three days, and as required thereafter) and prophylactic antibiotic (0.1 mg/kg of Enrofloxacin/Baytril) was also given once post-operatively. The laser Doppler perfusion imager (MoorLDI V6.0, Moor Instruments, Axminster, UK) was used to confirm drop in blood flow perfusion after HLI surgery as previously described 40 . Blood flow was measured in the soles of both feet, before (Pre-) and immediately after HLI surgery (Post-), and 7 days post-surgery, at which point, mice were humanely euthanised. Additionally, control mice of similar age not undergoing HLI surgery were euthanised. Assessment of limb functionality (ambulatory score) was performed on days 3 and days 7 post-surgery. The ambulatory score ranged from 0 to 3 depending on the limb mobility (3 = dragging the foot; 2 = no dragging the foot but no plantar flexion; 1 = plantar flexion but no flexion of toes; 0 = flexion of toes to resist traction on the tail similar to the non-operated foot). Tissue dissection and analysis. The calf muscles from the ischaemic (right) and non-ischaemic (left) hindlimbs of HLI mice and the right hindlimb of non-HLI mice were carefully dissected, and their weight was recorded. Calf muscle mass was calculated as a percentage per body weight (calf muscle weight [g]*100/ body weight [g]). Proximally, the soleus and gastrocnemius were separated and the proximal ~1/3 of both muscles were removed, snap-frozen in LN2 and stored at -80°C separately for molecular analysis. Distally, the soleus and gastrocnemius were kept intact and were fixed in 10% formalin for 48h, processed using the Epredia™ Excelsior™ AS Tissue Processor and embedded in paraffin blocks. Tissue cross-sections of 5mm thickness were taken from the mid-belly of the dissected calf muscles and rehydrated through a series of ethanol grades before staining with Haematoxylin and Eosin (H&E) and Mallory Trichrome staining using standard protocols. RNA Isolation . Total RNA was isolated from a portion of the proximal gastrocnemius muscle using the mirVana miRNA Isolation kit, with phenol (Invitrogen AM1560) according to the manufacturer's instructions. RNA was quantified using a Qubitä 4 fluorometer (Invitrogen) and the associated Qubitä RNA broad-range (BR) assay kit (Invitrogen, Q10211). miRNA RT-qPCR . 10 ng of total RNA was reverse transcribed using the Qiagen miRCURY LNA RT kit according to the manufacturer’s protocol. 1µL of each RNA sample was diluted to 5 ng/µL by adding an appropriate volume of RNase-free H2O. cDNA was diluted 1:60 and subsequently used in qPCR reaction using the miRCURY LNA qPCR SYBR Green kit and primer assays (See Major Resources Table ) on an Applied Biosystems™ StepOnePlus™ Real-Time PCR System. Relative expression of target miRNAs was normalised to miR-27b expression using the 2 -ΔCт method. mRNA RT-qPCR . 1000ng of total RNA was used for reverse transcription using the Invitrogen Superscript IV Kit according to the manufacturer’s instructions. qPCR was performed in 10uL reactions using Fast SYBR™ Green Master Mix (Applied Biosystems). 5ng of cDNA was used per reaction A primer concentration of 200-500 nM and an annealing temperature of 60°C were used. Primer sequences (See Major Resources Table ) were retrieved from PrimerBank which have been validated to specifically amplify the target of interest 41 . Samples were run in technical duplicates and a no template control (NTC) was run for each primer pair using molecular grade H 2 O instead of a cDNA sample. Relative expression of target mRNAs was normalised to the geometric mean of S29 and Gapdh expression using the 2 -ΔCт method. Statistical Analysis . All statistical analyses were performed using GraphPad Prism Version 9.4.1. In general, data were presented as mean ± standard deviation (SD). D’Agostino & Pearson test was used to determine whether sample data came from a normally distributed population. Mean differences between the three groups were tested statistically with a one-way ANOVA followed by Tukey’s multiple comparison test. Statistical significance was assigned at p-value ≤ 0.05. RESULTS miRNA-Target Interaction Enrichment Analysis. The muscle transcriptomic dataset obtained from Ryan et al. identified a total of 3,627 genes expressed differentially in CLTI vs. non-PAD control; 3,999 genes differentially expressed in CLTI vs. IC; and 397 genes differentially expressed in IC vs. non-PAD controls 12 . Of these, 2,261 were upregulated (UpDEG) and 1,366 were downregulated (DownDEG) in CLTI vs. non-PAD controls; 2,514 were upregulated and 1,485 were downregulated in CLTI vs. IC; 182 were upregulated and 215 were downregulated in IC vs. non-PAD. MTI enrichment analysis was performed using MIENTURNET based on the validated MTIs in the miRTarBase database. MTI enrichment of UpDEGs identified 6 over-represented miRNAs in CLTI vs. non-PAD controls and 10 over-represented miRNAs in CLTI vs. IC (Table 1) . No miRNAs were found to be significantly enriched when comparing the DownDEGs of CLTI vs. non-PAD or CLTI vs. IC, or when comparing the UpDEGs or DownDEGs of IC vs. non-PAD controls ( Table S1 ). An MTI network of the significantly enriched miRNAs and the corresponding upregulated targets was constructed showing a total of 948 MTIs for the CLTI vs. non-PAD group and 1,288 MTIs for the CLTI vs. IC group (Fig 1) . Table 1. Significantly overrepresented miRNAs amongst UpDEGs based on experimentally validated MTIs using miRTarBase database. microRNA p-value FDR Odds ratio N. i nteractions CLTI vs. non-PAD control hsa-miR-124-3p 2.4187233E-11 6.19193E-08 0.68343878 261 hsa-miR-29b-3p 1.9913612E-07 0.00025489 0.51894390 62 hsa-miR-335-5p 9.3510492E-07 0.00079796 0.81163128 399 hsa-miR-1-3p 0.00001016 0.00650341 0.72315530 157 hsa-miR-133a-3p 0.00001543 0.00789847 0.47496759 34 hsa-miR-7110-5p 0.00010923 0.04660619 0.52479516 35 CLTI vs. IC hsa-miR-124-3p 6.83E-16 1.75E-12 0.65 298 hsa-miR-1-3p 2.02E-10 0.000000259 0.648 190 hsa-miR-335-5p 1.23E-09 0.00000105 0.783 449 hsa-miR-29b-3p 2.67E-08 0.0000171 0.513 68 hsa-miR-29a-3p 0.00000126 0.000648 0.554 64 hsa-miR-133a-3p 0.00000195 0.000833 0.461 38 hsa-miR-29c-3p 0.0000118 0.00431 0.576 59 hsa-miR-146a-5p 0.0000189 0.00606 0.551 49 hsa-miR-338-3p 0.0000378 0.0108 0.513 37 hsa-miR-6885-3p 0.000103 0.0265 0.531 36 Severe calf muscle pathology in HLI. A preclinical HLI model was established to validate the role of bioinformatically identified miRNAs in skeletal muscle ischaemia 42 . HLI surgery immediately reduced the blood flow perfusion to 5% in the ischaemic limb. Blood flow recovery increased over time, but it was still impaired on day 7 (Fig 2a) . At 7 days post-HLI, a significant muscle atrophy and functional decline were observed, as indicated by an overall decrease in the percentage of calf muscle weight per body weight in ischaemic hindlimbs vs. the contralateral limb, and vs. limbs of no-HLI control mice (Fig 2b) and a poor ambulatory score (Fig 2c) . Histologically, the skeletal muscle architecture was dramatically perturbed after ischaemic injury (Fig 2 d ) . Severe inflammation with leukocyte accumulation was found scattered across large areas of the muscle. This was accompanied by a significant loss of muscle fibre integrity and large areas of necrosis with active phagocytosis and fibrosis (collagen deposition in blue in the Mallory Trichrome images). Interestingly, mild inflammation and fibrosis were observed in the contralateral non-ischaemic limb of HLI mice in the absence of obvious disturbance of myofiber architecture. Muscle atrophy was assessed via RT-qPCR as an indicator of muscle pathology. Murf1 and Atrogin1 expresion (also known as Trim63 and Fbxo32 , respectively) was decreased in the ischaemic limb vs. the contralateral non-ischaemic limbs and vs. the control no-HLI control mice (Fig 2 e, f ) . Notably, the decrease in Murf1 expression was failed to reach significance (p = 0.0756). Myosin heavy chain 7 ( Myh7 ) expression was decreased in the ischaemic limb vs. the contralateral non-ischaemic limbs (p = 0.0295) and vs. the control no-HLI control mice (p = 0.0382) (Fig 2 g ) . Alpha skeletal muscle actin ( Acta1 ) expressoin was not significantly changed in any group however there was a trend towards a decrease in the ischaemic limb vs. the contralateral non-ischaemic limbs (p = 0.0954) (Fig 2h) . miRNA dysregulation in skeletal muscle ischaemia Since MTIs of identified miRNAs were over-represented among UpDEGs in ischaemic muscle, it was hypothesised that the levels of these miRNAs would be decreased. RT-qPCR was performed on RNA isolated from the gastrocnemius muscle of the ischaemic and non-ischaemic limbs of mice that underwent the HLI procedure, and control mice that did not undergo the procedure. The results showed a significant and marked ischaemia-induced decrease in miR-1, miR-133a, and miR-29b in the ischaemic limbs compared to the contralateral non-ischaemic limbs (p = 0.0001, p = 0.0005, p = 0.0292, respectively) and the no-HLI control mice (p < 0.0001, p = 0.0001, p = 0.0230, respectively) (Fig 3a, b, c) . Contrary to the hypothesis, miR-124 was not significantly dysregulated in the ischaemic limbs compared to the contralateral non-ischaemic limbs (p = 0.8792) or the control no-HLI control mice (p = 0.8662) ( Fig 3d ). miR-335 expression was significantly higher in the ischaemic limbs than the contralateral non-ischaemic limbs (p = 0.0015) and the control no-HLI control mice (p = 0.0014) (Fig 3e) . miR-7110 was not assessed as it was not annotated in mice in the miRbase database 43 . miR-1, miR-133a, and miR-29b Functional Enrichment Analysis As hypothesised, miR-1, miR-133a, and miR-29b expression was downregulated in ischaemic mouse muscle. It was then considered that these three miRNAs may co-operatively regulate the skeletal muscle pathology in CLTI. The mRNAs that were: a) targeted by one or more of these miRNAs, and b) upregulated in CLTI patient skeletal muscle, were further investigated. First, an MTI subnetwork was created for the three differentially expressed miRNAs and the network characteristics were assessed. Notably, most mRNAs were targeted by one miRNA and a minority were targeted by two miRNAs with only one targeted by all three miRNAs ( Fig 4a ). To understand the functional interactions of these enriched targets, PPI network analyses were performed using STRING. The STRING PPI network consisted of 235 nodes with 1134 edges, and the expected number of edges was 513 with a corresponding PPI enrichment p-value of < 1*10 -16 indicating a significant degree of interaction between the input targets ( Fig S 1 ). The most important of these interacting nodes, i.e. the “hub nodes”, were then identified by the Mean Clique Centrality algorithm using CytoHubba. The top 20 hub nodes are displayed in Fig 4b and they include many extracellular matrix (ECM) components such as collagens I, III, IV V, and VI as well as fibronectin-1 (FBN1) and fibrin-1 (FN1). Functional enrichment analysis was performed on this subset of DEGs and EnrichmentMapping was then obtained ( Fig 5 ). The largest cluster consisted of terms associated with ECM and collagen which was connected with neighbouring clusters associated with collagen fibrils, integrin/signaling receptor/cell adhesion molecule binding, and platelet-derived growth factor (PDGF). The second-largest cluster was associated with leukocyte activation which connected to positive regulation of development and cell junction/adhesion clusters. The third largest cluster contained terms related to cardiovascular/blood vessel development which had five first-degree neighbouring clusters. These were related to embryonic development, skeletal system/bone development, PDGF, positive regulation of development, and vascular smooth muscle cell (VS.MC) proliferation. There was a cluster of terms related to fibroblast proliferation connected to the VS.MC proliferation cluster. Other clusters included those related to negative regulation of development, regulation of cell migration, secretory vesicle/granule, focal adhesion, anchoring/cell-substrate junction, positive regulation of cell death, and cellular response to nitrogen/peptide/amino acid. EnrichmentMapping of the targets of individual miRNAs can be accessed in Fig S 2 . mRNA target validation in the HLI mouse model We validated specific targets of these miRNAs in the HLI mouse model. The transcripts of interest were selected from the top hub nodes as shown in Fig 4 . All the targets assessed were significantly increased in the ischaemic limbs compared the contralateral non-ischaemic limbs and the no-HLI control mice, except for Tgf b 2 , which did not change (Fig 6) . No target was differentially expressed between the non-ischaemic limbs of HLI mice and no-HLI control mice. DISCUSSION PAD is characterised by a complex, multifactorial skeletal muscle pathology that has devastating effects on patient QOL, with significant morbidity and mortality 2 – 5 . Despite some progress made in terms of medical and surgical interventions for PAD, the prognosis of CLTI remains poor with unacceptably high rates of amputation 44 . Furthermore, novel investigational approaches (e.g. gene therapy with proangiogenic agents and stem cell-based therapies) have not demonstrated significant benefits in promoting CLTI limb salvage 45 , 46 . One likely reason for this is the complex pathology of CLTI which is not affected by the dysfunction of a single gene; rather, it is characterised by broad gene dysregulation resulting in derangement of signalling pathways, processes, and networks in skeletal muscle 12 , 15 , 16 . Therefore, understanding the molecular regulation of skeletal muscle pathology in CLTI is imperative and will help in the rational design of novel therapeutics with a greater likelihood of success than previously attempted therapies. Considering the broad transcriptomic dysregulation in CLTI muscle 12 , we investigated whether miRNAs could regulate these differentially expressed genes. We performed MTI enrichment analysis on the DEGs using MIENTURNET to identify miRNAs which may regulate significant portions of the dysregulated transcriptome in CLTI muscle. The underlying rationale for this was two-fold. First, it may further elucidate the underlying molecular pathology of CLTI-induced skeletal muscle pathology. Second, miRNAs identified in such a manner may represent novel therapeutics that could be delivered (or inhibited) as novel therapeutics to influence pathological gene expression and restore homeostasis in the ischaemic limb. For the first time, our bioinformatic analysis has identified a CLTI-specific miRNA dysregulation signature. Among the investigated UpDEGs, we identified six over-represented miRNAs in CLTI vs. non-PAD controls (miR-124-3p, miR-1-3p, miR-133a-3p, miR-29b-3p, miR-335-5p, and miR-7110-5p) (Table 1 ). When comparing CLTI vs. IC, we obtained a list of 10 over-represented miRNAs: miR-124-3p, miR-1-3p, miR-133a-3p, miR-29b-3p and miR-335-5p, which were also obtained when comparing CLTI vs. non-PAD controls, as well as others including miR-29a-3p, miR-29c-3p, miR-338-5p, miR-146a-5p, and miR-6885-3p (Table 1 ). No over-represented miRNAs were found when comparing the IC and non-PAD controls. We then used the preclinical mouse model of CLTI to validate the predicted downregulation of miRNAs identified in CLTI vs. non-PAD controls. The rationale for choosing this group was that, in vivo , we compared skeletal muscles severely affected by ischaemic injury with control non-ischaemic muscles. First, skeletal muscle pathology was confirmed in the HLI model 7 days post-ischaemia induction. Significant skeletal muscle atrophy was indicated by decreased calf muscle mass and limb function, and downregulation of muscle mass-related genes ( Myh7 and Acta1) . Atrogin1 and Murf1 , which are common markers of muscle atrophy 47 , 48 , were also decreased (Fig. 2 c). A similar finding has been reported where these markers only transiently increased immediately after HLI injury and then decreased below pre-ischaemic levels by day 3 post-HLI 49 . Histologically, ischaemic muscle presented with severe inflammation, necrosis, and fibrosis with significant loss of muscle fibre integrity, which is consistent with human data 50 – 52 . Mild inflammation in the absence of obvious disturbance of myofibre architecture was observed in the contralateral non-ischaemic limb of HLI mice, which disappeared 28 days post-HLI surgery 40 . This is an interesting observation that may be important to consider when undertaking preclinical studies using this animal model. We then investigated whether the specific miRNAs were downregulated as predicted by our bioinformatics analysis. The most significantly enriched miRNA identified by our bioinformatics analysis was miR-124-3p (Table 1 ). Functional enrichment analysis of DEGs targeted by miR-124-3p identified enrichment for terms associated with ECM structure and collagen as well as vascular development and angiogenesis ( Fig S3a ). This is supported by previously published literature, where miR-124-3p has been shown to regulate angiogenesis in an HLI model 53 . Here, delivery of miR-124 mimics in an HLI model inhibited perfusion recovery and decreased capillary density at day 14, while antagomiRs had the opposite effect in both of these measures 53 . RT-qPCR validation of the HLI model on day 7 post-HLI revealed that miR-124 was not dysregulated. Interestingly, Shi et al. reported that miR-124 is transiently increased immediately in response to HLI, with a peak in expression at day 2 and restoration to pre-ischaemic levels by day 3 53 , which supports our findings. The identification of miR-29b is interesting as it is a well-known fibrosis-associated miRNA, together with miR-29a and miR-29c. The miR-29 family has been shown to be involved in inhibiting ECM synthesis indicating its antifibrotic function 54 . Despite the relatively low number of input genes (Table 1 ), there was a marked degree of functional enrichment among the targets related to the underlying fibrotic mechanisms ( Fig S2e ). The data presented here contributes to the already known role of miR-29b as a “fibromiR”. We hypothesised that in the ischaemic limb, miR-29b may directly regulate fibrosis-associated pathology, a hallmark feature of CLTI 13 , by targeting ECM-associated transcripts. We validated the downregulation of miR-29b in skeletal muscle and upregulation of its ECM-related target mRNAs in response to ischaemic injury, at a time point where intermuscular fibrosis was already observed histologically. Other studies have reported decreased levels of miR-29b in fibrosis 55 – 58 , which support our findings. In addition, decreased expression in circulation is associated with increased mortality in patients with pulmonary fibrosis 59 . Functional enrichment analysis also identified enrichment for terms associated with arterial dissection/aneurysm and vascular development/angiogenesis and interconnection with fibrosis-associated clusters ( Fig S2e ). This may be indicative of the fibrotic changes seen in the microvasculature of the PAD/CLTI muscle 60 , in which VSMCs show increased TGF-β levels and collagen deposition. miR-29b has been investigated as a potential anti-fibrotic agent, particularly in the context of pulmonary fibrosis 61 . Delivery of miR-29b mimics has also demonstrated pre-clinical and early clinical efficacy in cutaneous fibrosis (drug name: Remlarsen or MRG-201) 57 . While miR-29b has not been delivered in an HLI model, its family member, miR-29a has been investigated in this context. In murine diabetic HLI models, inhibition of miR-29a enhanced perfusion recovery, muscle regeneration and function, and capillary density by day 21 62,63 . However, while ischaemia induced a decrease in miR-29a expression in the gastrocnemius, diabetic HLI was associated with an increase in miR-29a vs. non-diabetic HLI 62 . This observation was consistent in humans with and without diabetes 62 . The molecular mechanisms by which hyperglycaemia impairs miR-29a expression is not well known. The compounding effects of metabolic dysfunction in the context of ischaemia may have specific effects on miRNA dysregulation that must be considered. miR-1 and miR-133a are two of the canonical “myomiRs” and were also found to be CLTI-specific (Table 1 ). myomiRs are muscle-enriched miRNAs with key roles in the regulation of muscle function and pathology 64 – 66 . Early work by Chen et al. identified distinct roles for miR-1 and miR-133a in promoting myogenesis and myoblast proliferation, respectively 67 . Despite increasing acknowledgement of the importance of skeletal muscle pathology in CLTI, myomiRs remain relatively understudied in this context. Greco et al. suggested that a decrease in miR-1 levels (and also miR-29c) in response to ischaemia was not seen in isolated myofibres but only in the total muscle bulk. This suggests that the decrease in expression may be due to the loss or atrophy of myofibres and relative over-representation in the cellular mass in the muscle of non-myofibre cell types 68 . Fibrosis is a key feature of muscle pathology in CLTI, and myogenic progenitor cell dysfunction is also observed 12 , 69 , 70 . The clinical implications of this remain to be fully understood; however, recent in vivo studies using knockout models, have indicated that Pax7 + myogenic progenitor cells are necessary for regeneration after HLI injury. In the absence of these cells, fibroadipogenic progenitor cells (FAPs) are activated and contribute to ischaemic muscle pathology by increasing adipogenesis 71 . Dysregulation of the adipogenic and fibrotic differentiation of FAPs due to age, trauma, or disease can lead to abnormal intermuscular fat infiltration and excessive fibrosis, resulting in muscle loss and dysfunction 72 . It is not unreasonable that ischaemia-induced impairments in muscle progenitor cell (MPC) function and relative reductions in myomiR levels may regulate fibrosis. For instance, in muscle injury, MPCs traffic miR-206 to fibrogenic cells via extracellular vesicles (EVs.) and thereby regulate ECM deposition in the muscle 73 . To the best of our knowledge, miR-1 has not been investigated in terms of its ability to regulate recovery in a pre-clinical HLI model. In contrast, miR-133a has been investigated in a pre-clinical model of diabetic HLI 74 . Interestingly, the delivery of miR-133a was detrimental (and its inhibition was beneficial) in this model in terms of perfusion recovery, and its expression in the skeletal muscle was upregulated compared to that in non-diabetic mice. Here, in a non-diabetic HLI mouse model, we found a marked downregulation of miR-133a. It is possible that the diabetic milieu may alter miR-133a expression in skeletal muscle ischaemia and impact the effect of modulation of this miRNA, similar to what has been observed for miR-29a 62 . This finding raises important concerns for the field of miRNA therapy in cardiovascular disease as diabetes is one of the most significant risk factors for PAD and differences in the roles of specific miRNAs in vascular diseases with or without diabetes are not inconsequential. miR-335 had the highest number of targets upregulated in the CLTI muscle (Table 1 ). Functional enrichment analysis indicated that this miRNA may regulate the inflammatory response in ischaemia ( Fig S2c ). In sepsis-induced myocardial injury, miR-335 exerts a protective effect by regulating the inflammatory response 75 . In the peripheral blood of PAD patients, miR-335 was reported to be downregulated 76 . As an anecdotal observation within our group, in various unrelated and related analyses using MIENTURNET, miR-335 is frequently enriched. It is possible that it may be a common false positive miRNA when using this tool. This highlights the importance of validating bioinformatically identified targets in relevant models. miR-7110-5p was not assessed in a pre-clinical model as it has not been annotated in mice 43 . Unlike other miRNAs, this is a relatively novel miRNA. However, recent investigations have suggested that miR-7110-5p is downregulated in diabetes 77 and hypertrophic cardiomyopathy 78 . Additionally, it has been suggested that miR-7110-3p is implicated in pulmonary arterial hypertension 79 . Primer sequences are commercially available for this miRNA, both − 3p and − 5p strands, so investigation in human CLTI samples is warranted. In summary, several miRNAs with a potential regulatory role in skeletal muscle pathology in CLTI have been identified by MTI analysis. In pre-clinical validation, three of these miRNAs (miR-1, miR-133a, and miR-29b) were differentially expressed in the HLI model in the opposite direction to their targets in patient samples. Therefore, we hypothesised that these three miRNAs may represent a signature of skeletal muscle pathology in CLTI. To understand the potential role of these three miRNA panels in skeletal muscle ischaemia, we created a sub-MTI network of miR-1, miR-133a, and miR-29b and their targets that were upregulated in the CLTI muscle. A PPI network was constructed to understand the functional association between the targets of these miRNAs in skeletal muscle ischaemia. Our results revealed a significant degree of interaction between the input targets, indicating a functional relationship between the targets ( Fig. 1 S ) . The hub nodes of this PPI network were identified as the most important nodes in the network 32 . Several ECM components were identified in this network including fibrillar collagens I, III, and V, the helical collagen IV, collagen VI, fibronectin, and fibrin. Known anti-angiogenic factors thrombospondin1 and thrombospondin2 were also present in this network. The expression for the selection of targets from these hub nodes was validated using the HLI model. Concurrent with the downregulation of the three miRNAs, their targets were upregulated, except for Tgfβ2 (Fig. 6 ). We further investigated the roles of these targets by functional enrichment analysis using enrichment mapping 33 . This aimed to understand the pathways and biological functions that may be regulated by this three-miRNA signature in skeletal muscle ischaemia. Here, the over-representation of several “biological themes” was identified. Firstly, the largest biological theme identified was fibrosis. Numerous clusters related to the ECM and collagen, PDGF, cell adhesion, and fibroblast proliferation were identified. Fibrosis is a pathological process whereby there is excessive deposition of ECM (in particular, collagen), impairment in ECM degradation, or both of these processes 80 , 81 . Fibrosis is a hallmark feature of skeletal muscle pathology in CLTI and has been suggested to be a central mechanism of disease progression 13 . Additionally, vascular development and the VS.MC cluster may further pertain to the CLTI-associated vascular pathology and associated fibrotic process as there is an ischaemia-induced increase in expression of Tgfβ1 in VS.MCs which is associated with fibroblast accumulation and collagen deposition 60 , 82 . This study has several limitations. There is an inherent limitation of using the HLI model to validate the predicted dysregulation of miRNAs and their targets in CLTI patients, as this model only allows the study if muscle regeneration in response to acute ischaemic injury compared to chronic ischaemia in CLTI patients. We also only validated miRNAs that were enriched in the CLTI vs. non-PAD control group. It is plausible that other miRNAs enriched in the CLTI vs. IC group could also be dysregulated in HLI ischaemic muscles, especially miRNAs from the miR-29 family, including miR-29a and miR-29c. It is also possible that specific miRNAs play different physiological and/or pathological roles in different ischaemic contexts. Therefore, miRNA dysregulation should be investigated in muscle samples from CLTI, IC, and non-PAD controls. CONCLUSIONS To the best of our knowledge, this is the first study to identify miR-1, miR-133a, and miR-29b as potential regulators of skeletal muscle pathology in patients with CLTI. The results presented here indicate miR-1, miR-133a, and miR-29b as a miRNA signature of skeletal muscle fibrosis in CLTI. Given the enrichment of these miRNAs in transcriptomic data, these miRNAs likely represent central regulators of this muscle pathology and warrant further investigation as potential therapeutics. A defining feature of miRNAs is their pleiotropic nature: a single miRNA can regulate many mRNAs, and a single mRNA can be regulated by many miRNAs 83 . From a therapeutic perspective, this makes miRNAs an attractive candidate for novel ‘systems-based’ therapies that could regulate this broad transcriptomic and pathway dysregulation 19 , 84 . Each of these miRNAs individually possesses therapeutically relevant properties in this context. However, miRNA-based therapy poses the risk of off-target effects, which must be considered 85 . Considering the potential for off-target effects, it is likely that the translation of miRNA therapeutics will require rational identification and validation of candidate miRNAs along with targeting strategies such as modification of the oligonucleotide to target specific cell types. The former has been investigated recently in the case of MRG-229, a miR-29b mimic which was modified with a bicyclic peptide specific for PDGFR-β to be internalised by fibrogenic cells in the lung 59 . Such novel therapeutics may restore homeostasis in the ischaemic limb by targeting pathological transcriptomic dysregulation, restoring it to non-ischaemic levels, and ultimately, preventing amputation and improving patient outcomes. Additionally, there is a distinct possibility to investigate the miR-1, miR-133a, and miR-29b panels as potential combinatorial miRNA therapeutics. The co-delivery of multiple miRNAs that may co-operatively regulate complementary targets in on-target pathways may allow a lower dose of each individual miRNA to be administered and reduce the likelihood of perturbing off-target pathways 84 . Nevertheless, the roles of these specific miRNAs remain relatively novel in the context of PAD/CLTI and ischaemic skeletal muscle regeneration, and investigation of these miRNAs as potential therapeutics is still warranted. Declarations Ethical Approval . All animal experiments were carried out in compliance with the Directive 2010/63/EU. Ethical approval was granted by the Animal Care Research Ethics Committee (ACREC) at the University of Galway (Ireland) and appropriate individual and project authorizations were granted by the Health Products Regulatory Authority in Ireland (AE19125 /P076). Availability of data and materials. RNA-sequencing-based profiles from CLTI, IC and non-PAD adults utilised here (GSE120642) can be publicly accessed at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE120642. The authors declare that the data supporting the findings of this study are available within the article and its supplementary information files and also available from the corresponding author upon request. Disclosures: TOB is a founder, director, and equity holder in Orbsen Therapeutics Ltd. The other authors do not have competing interests to declare. Author’s contributions. AJK, CSN, DJ, MC, XZ, CJL and IS carried out experiments, analysis, and/or interpretation of results. AJK, CSN, DJ, MC, CJL, KGW, and TOB conceived the study, participated in the design of the study, and/or helped to draft the manuscript. The final manuscript was read and approved by all the authors. Sources of Funding . This publication has emanated from the research supported by Irish Research Council grant no. 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J Clin Med 9:2575. https://doi.org/10.3390/jcm9082575 Orang AV, Safaralizadeh R, Kazemzadeh-Bavili M (2014) Mechanisms of miRNA-Mediated Gene Regulation from Common Downregulation to mRNA-Specific Upregulation. Int J Genom 2014:970607. https://doi.org/10.1155/2014/970607 Lai X, Eberhardt M, Schmitz U, Vera J (2019) Systems biology-based investigation of cooperating microRNAs as monotherapy or adjuvant therapy in cancer. Nucleic Acids Res 47:7753–7766. https://doi.org/10.1093/nar/gkz638 Diener C, Keller A, Meese E (2022) Emerging concepts of miRNA therapeutics: from cells to clinic. Trends Genet 38:613–626. https://doi.org/10.1016/j.tig.2022.02.006 Additional Declarations Competing interest reported. TOB is a founder, director, and equity holder in Orbsen Therapeutics Ltd. The other authors do not have competing interests to declare. Supplementary Files Graphicalabstract.png Cite Share Download PDF Status: Published Journal Publication published 26 Nov, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 03 Jun, 2024 Reviews received at journal 31 May, 2024 Reviewers agreed at journal 22 May, 2024 Reviews received at journal 17 May, 2024 Reviews received at journal 09 May, 2024 Reviewers agreed at journal 25 Apr, 2024 Reviewers agreed at journal 25 Apr, 2024 Reviewers invited by journal 20 Apr, 2024 Editor assigned by journal 20 Apr, 2024 Editor invited by journal 16 Apr, 2024 Submission checks completed at journal 16 Apr, 2024 First submitted to journal 09 Apr, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4242453","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":292065009,"identity":"c51ed86f-5281-4f2e-ba33-fca325d4ebae","order_by":0,"name":"Alan Keane","email":"","orcid":"","institution":"University of Galway","correspondingAuthor":false,"prefix":"","firstName":"Alan","middleName":"","lastName":"Keane","suffix":""},{"id":292065010,"identity":"b88076d7-1385-433f-9ee4-ddbed73aa72e","order_by":1,"name":"Clara Sanz Nogues","email":"data:image/png;base64,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","orcid":"","institution":"University of Galway","correspondingAuthor":true,"prefix":"","firstName":"Clara","middleName":"Sanz","lastName":"Nogues","suffix":""},{"id":292065011,"identity":"4238f44d-5025-42a4-8aa1-d15742b81222","order_by":2,"name":"Dulan Jayasooriya","email":"","orcid":"","institution":"University of Galway","correspondingAuthor":false,"prefix":"","firstName":"Dulan","middleName":"","lastName":"Jayasooriya","suffix":""},{"id":292065012,"identity":"9dbd84ba-4324-4566-afbc-fa49dcd5319f","order_by":3,"name":"Michael Creane","email":"","orcid":"","institution":"University of Galway","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"","lastName":"Creane","suffix":""},{"id":292065013,"identity":"4c0b5df2-b7ba-458c-8066-cb29101e8b14","order_by":4,"name":"Xizhe Chen","email":"","orcid":"","institution":"University of Galway","correspondingAuthor":false,"prefix":"","firstName":"Xizhe","middleName":"","lastName":"Chen","suffix":""},{"id":292065014,"identity":"1f5464e9-0f7b-4639-8399-1f327fa80dc2","order_by":5,"name":"Caomhán Lyons","email":"","orcid":"","institution":"University of Galway","correspondingAuthor":false,"prefix":"","firstName":"Caomhán","middleName":"","lastName":"Lyons","suffix":""},{"id":292065015,"identity":"1a62efff-fd7a-47c9-ac28-ce2e01ee892c","order_by":6,"name":"Isha Sikri","email":"","orcid":"","institution":"University of Galway","correspondingAuthor":false,"prefix":"","firstName":"Isha","middleName":"","lastName":"Sikri","suffix":""},{"id":292065016,"identity":"765b76ae-0f21-43ab-a136-3fdab9b8f6b6","order_by":7,"name":"Katarzyna Goljanek-Whysal","email":"","orcid":"","institution":"University of Galway","correspondingAuthor":false,"prefix":"","firstName":"Katarzyna","middleName":"","lastName":"Goljanek-Whysal","suffix":""},{"id":292065017,"identity":"dc72e913-31ae-4f03-b723-f47639d460e7","order_by":8,"name":"Timothy O'Brien","email":"","orcid":"","institution":"University of Galway","correspondingAuthor":false,"prefix":"","firstName":"Timothy","middleName":"","lastName":"O'Brien","suffix":""}],"badges":[],"createdAt":"2024-04-09 13:59:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4242453/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4242453/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-76415-9","type":"published","date":"2024-11-26T15:56:54+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":54967288,"identity":"890a9b99-b93a-4aae-bf62-b3dfa721a951","added_by":"auto","created_at":"2024-04-19 10:04:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":3416857,"visible":true,"origin":"","legend":"\u003cp\u003eNetwork representation of the enriched MTIs in upregulated DEGs in skeletal muscle from patients with CLTI and IC. The MIENTURNET tool was used to create an MTI network of the significantly enriched MTIs in CLTI \u003cem\u003evs. \u003c/em\u003enon-PAD muscle (a) and CLTI \u003cem\u003evs.\u003c/em\u003eIC muscle (b) using the miRTarBase database for experimentally validated MTIs. No MTI network was created for IC \u003cem\u003evs.\u003c/em\u003e non-PAD muscle as there were no significantly enriched MTIs when comparing these two groups. The MTI network was visualised using Cytoscape. miRNAs are represented by grey nodes and mRNA targets are represented by yellow nodes. Edges represent validated MTIs.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-4242453/v1/86c0692e9e1bb6e771f96b60.png"},{"id":54965929,"identity":"8a64b0c3-51b3-4591-a56f-b5095aeda66e","added_by":"auto","created_at":"2024-04-19 09:48:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":4113233,"visible":true,"origin":"","legend":"\u003cp\u003eSevere calf muscle pathology 7 days post-HLI. (a) Blood flow perfusion of mice foot using Laser Doppler Imaging. Colour-coded images displayed poor perfusion as dark blue, and the highest perfusion level was displayed as red. (b) Percentage of calf muscle wet weight per body weight. Data are mean ± SD. **\u003cem\u003ep\u003c/em\u003e\u0026lt;0.01, *\u003cem\u003ep\u003c/em\u003e\u0026lt;0.05 (one-way ANOVA, Tukey’s multiple comparisons test). (c) Assessment of limb functionality using the ambulatory score (3=dragging the foot; 2=no dragging the foot but no plantar flexion; 1=plantar flexion but no flexion of toes; 0=flexion of toes to resist traction on the tail similar to the non-operated foot) (d) Representative images of skeletal muscle sections stained with Mallory’s Trichrome Stain and H\u0026amp;E stain. Scale bar 10X=250 μm; 20X = 50μm. The expression levels of (e) \u003cem\u003eMurf1\u003c/em\u003e, (f) \u003cem\u003eAtrogin1\u003c/em\u003e, (g) \u003cem\u003eMyh7\u003c/em\u003e, and (h) \u003cem\u003eActa1\u003c/em\u003e were assessed \u003cem\u003evia\u003c/em\u003e RT-qPCR. Cт values were normalised to the geometric mean of S29 and \u003cem\u003eGapdh\u003c/em\u003e using the 2\u003csup\u003e-ΔCт\u003c/sup\u003e method. Data are presented as mean \u0026nbsp;± SD. * p \u0026lt; 0.05, ** p \u0026lt; 0.01 (one-way ANOVA, Tukey’s multiple comparison test).\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-4242453/v1/4ec31a64a1acd6cd4e820fe3.png"},{"id":54966617,"identity":"3d4b7555-31ad-4d5b-881e-8b33f032556c","added_by":"auto","created_at":"2024-04-19 09:56:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":144257,"visible":true,"origin":"","legend":"\u003cp\u003eValidation of over-represented miRNAs in CLTI skeletal muscle using HLI mouse model. The expression levels of (a) miR-1-3p, (b) miR-133a-3p, (c) miR-29b-3p, (d) miR-124-3p and (e) miR-335-5p were assessed in the gastrocnemius muscle of no HLI (control) mice and of HLI mice \u003cem\u003evia\u003c/em\u003e RT-qPCR. miRNA Cт values were normalised to miR-27b using the 2\u003csup\u003e-ΔCт\u003c/sup\u003e method. Data are presented as mean \u003cimg width=\"11\" height=\"26\" src=\"file:///C:/Users/btr8097/AppData/Local/Packages/oice_16_974fa576_32c1d314_3651/AC/Temp/msohtmlclip1/01/clip_image002.gif\"/\u003eSD. * p \u0026lt; 0.05, ** p \u0026lt; 0.01, *** p \u0026lt; 0.001, and **** p \u0026lt; 0.0001. One-way ANOVA and Tukey’s multiple comparison test.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-4242453/v1/0e4d0dba0ef6ace3943e8133.png"},{"id":54967287,"identity":"eb828844-e261-49ce-bf98-089b1564ec18","added_by":"auto","created_at":"2024-04-19 10:04:56","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1338499,"visible":true,"origin":"","legend":"\u003cp\u003eThe top 20 hub nodes in the miR-1, miR-133a, and miR-29b target PPI network. (a) A subnetwork using Cytoscape of the MTI network in Fig 1 of miR-1, miR-133a, and miR-29b and their targets that are upregulated in CLTI. miRNAs are represented by grey nodes and mRNA targets are represented by yellow nodes; edges represent validated MTI from the miRTarBase database. (b) The hub nodes of the PPI network in Fig S1 were identified in Cytoscape using CytoHubba and the MCC topological analysis method. The top 20 hub nodes were used to create a subnetwork. Node colour indicates hub node essentiality, red indicates greater hub node rank and yellow indicates lesser hub node rank.\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-4242453/v1/cc12fb48ed68f519f58033d2.png"},{"id":54965933,"identity":"980d885f-f5e4-43cd-babf-8a707e16648f","added_by":"auto","created_at":"2024-04-19 09:48:56","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2533887,"visible":true,"origin":"","legend":"\u003cp\u003eEnrichment map of miR-1, miR-133a, and miR-29b targets upregulated in CLTI. Functional enrichment analysis was performed on the targets of miR-1, miR-133a, and miR-29b that are upregulated in CLTI gastrocnemius using g:Profiler. EnrichmentMapping was performed using the EnrichmentMap plugin in Cytoscape. Cluster labels created using the AutoAnnotate plugin were manually edited. Nodes represent enriched pathways identified using g:Profiler. Edges represent, and are weighted by, pathway gene set overlap. Node colour is mapped to pathway enrichment significance (orange = lower Q value and white = higher Q value). Node size is mapped to gene set size.\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-4242453/v1/fb4ca5f38c8cbe1163f73213.png"},{"id":54965927,"identity":"d9883b26-3b85-4418-9c66-582ac02fd972","added_by":"auto","created_at":"2024-04-19 09:48:56","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":253222,"visible":true,"origin":"","legend":"\u003cp\u003eExpression of hub nodes of the miR-1, miR-133a, and miR-29b target PPI network in skeletal muscle ischaemia. The expression levels of (a) \u003cem\u003eCol1a1\u003c/em\u003e, (b) \u003cem\u003eCol3a1\u003c/em\u003e, (c) \u003cem\u003eCol4a1\u003c/em\u003e, (d) \u003cem\u003eFn1\u003c/em\u003e, (e) \u003cem\u003eFbn1\u003c/em\u003e, (f) \u003cem\u003eSparc\u003c/em\u003e, (g) \u003cem\u003eMmp2\u003c/em\u003e, (h) \u003cem\u003eMmp14\u003c/em\u003e, and (i) \u003cem\u003eTgfb2 \u003c/em\u003ewere assessed in the gastrocnemius muscle of no-HLI (control) mice and of HLI mice \u003cem\u003evia\u003c/em\u003e RT-qPCR. miRNA Cт values were normalised the geometric mean of \u003cem\u003eS29\u003c/em\u003e and \u003cem\u003eGapdh\u003c/em\u003e expression using the 2\u003csup\u003e-ΔCт\u003c/sup\u003e method. Data are presented as mean \u003cimg width=\"14\" height=\"26\" src=\"file:///C:/Users/btr8097/AppData/Local/Packages/oice_16_974fa576_32c1d314_3651/AC/Temp/msohtmlclip1/01/clip_image002.gif\"/\u003eSD. * p \u0026lt; 0.05, ** p \u0026lt; 0.01, *** p \u0026lt; 0.001, and **** p \u0026lt; 0.0001. One-way ANOVA and Tukey’s multiple comparison test.\u003c/p\u003e","description":"","filename":"Fig6.png","url":"https://assets-eu.researchsquare.com/files/rs-4242453/v1/dca24a38d14734301ab9d57f.png"},{"id":70381467,"identity":"8311a963-64a4-423a-953c-f53b6723feca","added_by":"auto","created_at":"2024-12-02 16:10:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":14242604,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4242453/v1/f566abf9-b5d0-4f43-bcad-8d4b9e2ff68b.pdf"},{"id":54966619,"identity":"54819e7e-7549-4564-8ed1-fae3cd17da96","added_by":"auto","created_at":"2024-04-19 09:56:56","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1245383,"visible":true,"origin":"","legend":"","description":"","filename":"Graphicalabstract.png","url":"https://assets-eu.researchsquare.com/files/rs-4242453/v1/d50d1cfd6ea0265749d98e60.png"}],"financialInterests":"Competing interest reported. TOB is a founder, director, and equity holder in Orbsen Therapeutics Ltd. The other authors do not have competing interests to declare.","formattedTitle":"miR-1, miR-133a, miR-29b and Skeletal Muscle Fibrosis in Chronic Limb-Threatening Ischaemia.","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003ePeripheral arterial disease (PAD) most often occurs due to atherosclerotic disease in the peripheral arteries, resulting in skeletal muscle ischaemia distal to the point of vessel narrowing\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Most patients with PAD are asymptomatic. However, impaired perfusion of the lower limbs is associated with muscle atrophy, functional decline and increased risk of morbidity and mortality\u003csup\u003e\u003cspan additionalcitationids=\"CR3 CR4\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, even in those patients without obvious symptoms\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Patients with PAD can exhibit intermittent claudication (IC), defined as limb pain during physical activity which resolves at rest\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. This may occur when arterial narrowing is such that limb perfusion is insufficient to meet muscle metabolic demands during exercise. It is estimated that up to 10% of patients with PAD progress or present \u003cem\u003ede novo\u003c/em\u003e with chronic limb-threatening ischaemia (CLTI), the most severe manifestation of PAD\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. CLTI is characterised by chronic ischaemic rest pain, non-healing ulcers, and gangrene and is associated with a high risk of limb loss, cardiovascular morbidity and mortality\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Interestingly, most patients with IC do not naturally progress to CLTI\u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, suggesting that these two manifestations of PAD may represent distinct pathogenic stages of the disease despite similar ischaemic aetiology.\u003c/p\u003e \u003cp\u003eCurrent bioinformatics and omics-based approaches have provided important insights into the pathophysiology of clinical PAD. Ryan \u003cem\u003eet al.\u003c/em\u003e recently reported a unique skeletal muscle mitochondriopathy that distinguished patients with CLTI from those with IC\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Other authors have utilised this publicly available RNA-sequencing database of PAD cohorts to elucidate the pathological signatures that discriminated CLTI from IC. For instance, Cong \u003cem\u003eet al.\u003c/em\u003e identified fibrosis pathways involving transforming growth factor-β (TGF-β), collagen deposition, and vascular endothelial growth factor (VEGF) signalling as a novel gene expression feature for CLTI but not IC\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Yao \u003cem\u003eet al.\u003c/em\u003e identified several genes encoding subunits of the human complement system as promising markers for discriminating between CLTI and IC\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. More recently, Ferrucci \u003cem\u003eet al.\u003c/em\u003e multi-omics analysis using RNA sequencing and proteomics on PAD skeletal muscle (free from diabetes and CLTI) reported that mitochondrial dysfunction and fibrotic are processes active in PAD without CLTI\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. These results contradict to some extent the findings from Ryan and Cong \u003cem\u003eet al.\u003c/em\u003e In another study using a different transcriptomic dataset, Saini \u003cem\u003eet al.\u003c/em\u003e reported differential gene and microRNA (miRNA) expression associated with PAD progression\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003emiRNAs are small non-coding RNAs\u0026thinsp;~\u0026thinsp;22 nucleotides in length which regulate gene expression at the post-transcriptional level\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e and are considered robust regulators of muscle development and homeostasis\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. miRNAs have been thoroughly investigated in the context of PAD\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, in particular, as potential biomarkers in skeletal muscle\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e and circulation\u003csup\u003e\u003cspan additionalcitationids=\"CR24 CR25\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. However, the full spectrum of dysregulated miRNAs associated with PAD stages is poorly understood. This study aimed to identify dysregulated miRNAs in gastrocnemius muscle biopsies that were differentially expressed in different PAD cohorts. We analysed a publicly available RNA-sequencing database of PAD cohorts\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e using \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eMI\u003c/span\u003ecroRNA \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eEN\u003c/span\u003erichment \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eTUR\u003c/span\u003ened \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eNET\u003c/span\u003ework (MIENTURNET), a web tool for miRNA target enrichment and network-based analysis\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. We hypothesised that transcriptomic analysis using this bioinformatics tool will identify CLTI-specific dysregulated miRNAs and their associated targets. Subsequently, we validated the findings in hindlimb ischaemia (HLI) mice, a preclinical model of CLTI\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eData Acquisition\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e\u0026nbsp;RNA-sequencing-based profiles from CLTI, IC and non-PAD adults were acquired from a dataset published by Ryan and colleagues\u0026nbsp;(GSE120642)\u003csup\u003e12\u003c/sup\u003e. In Ryan\u0026nbsp;\u003cem\u003eet al.\u003c/em\u003e study, gastrocnemius muscle biopsies were obtained from patients with IC (n=27), CLTI (n=19) and non-PAD controls (n=32) for whole transcriptome sequencing. RNA sequencing was performed by sequencing\u0026nbsp;paired-end (150 bp) reads on an Illumina HiSeq 4000.\u0026nbsp;The authors identified differentially expressed genes (DEGs) in skeletal muscle from CLTI vs. non-PAD control, CLTI vs. IC and IC vs. non-PAD controls using edgeR with a p-value \u0026lt;0.05 and a fold change\u0026gt;1.5\u003csup\u003e12\u003c/sup\u003e.\u0026nbsp;The diagnostic criteria, participant demographics, and further methodological detail are illustrated in Ryan\u0026nbsp;\u003cem\u003eet al.\u003c/em\u003e study.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003emiRNA-Target Interaction Enrichment Analysi\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e\u003cem\u003es\u003c/em\u003e. \u003c/strong\u003eDEGs in CLTI \u003cem\u003evs.\u003c/em\u003e non-PAD controls, CLTI\u0026nbsp;\u003cem\u003evs.\u003c/em\u003e IC and IC\u0026nbsp;\u003cem\u003evs.\u003c/em\u003e non-PAD controls were analysed using the online bioinformatics tool MIENTURNET\u003csup\u003e27\u003c/sup\u003e. Upregulated and downregulated DEGs were analysed separately. DEGs were input to the MIENTURENT tool and miRNA-Target Interaction (MTI) enrichment was performed based on validated MTIs\u0026nbsp;in the miRTarBase database. Results were filtered by setting a threshold for the minimum number of MTIs as 2 and FDR \u0026lt; 0.05. The enriched MTIs were visualised using Cytoscape\u003csup\u003e30\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eProtein-Protein Interaction (PPI) Network Analyses\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e\u0026nbsp;PPI networks were constructed using the STRING database (version 12)\u003csup\u003e31\u003c/sup\u003e and visualised using Cytoscape\u003csup\u003e30\u003c/sup\u003e. Full STRING networks were constructed using a multiple protein query. Network edges represented \u0026ldquo;evidence\u0026rdquo;. All available interaction sources were used i.e. text mining, experiments, databases, co‑expression, neighbourhood, gene fusion, and co‑occurrence. The minimum required interaction score was set to the default medium confidence (0.4). Hub nodes were identified in Cytoscape using the CytoHubba plug-in\u003csup\u003e32\u003c/sup\u003e. The maximal clique centrality (MCC) topological analysis method was used to calculate hub nodes. The top 20 hub nodes were visualised in a sub-network.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eFunctional Enrichment using g:Profiler\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. \u003c/strong\u003eFunctional enrichment analysis was performed based on a previously published protocol\u003csup\u003e33\u003c/sup\u003e. First, functional enrichment was performed using g:Profiler\u003csup\u003e34\u003c/sup\u003e (version e109_eg56_p17). The significance threshold was set at 0.05 and the following data sources were used Gene Ontology (GO) molecular function, GO cellular component, GO biological process, KEGG, Reactome, and WikiPathways. If ambiguous query genes were found, these were manually disambiguated by selecting the most appropriate term when prompted and the query was re-run. Results were filtered in terms of the size of the functional category to facilitate the interpretability of the results. The minimum and maximum term sizes were set at 5 and 1000, respectively, to remove excessively small or large gene sets of limited interpretive value. All results were downloaded for further processing. For functional enrichment analysis, a custom background set based on the following criteria was used. Transcripts that are expressed in skeletal muscle and detected in this RNA-sequencing experiment were identified using the normalised read counts in non-PAD controls, IC and CLTI samples. The threshold cut-off was set as minimum median normalised read count of any DEG. Any transcript that had a normalised read count greater or equal to this value was included i.e. only transcripts that were detected at a level that would have a chance at being identified as a DEG were included as has been previously suggested\u003csup\u003e35\u003c/sup\u003e. \u0026ldquo;Custom over annotated genes\u0026rdquo; was selected, such that only annotated genes that were also in the background list were used as background genes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEnrichment Mapping using Cytoscape\u003c/strong\u003e. Visualisation of functional enrichment data from the g:Profiler output was performed using Cytoscape v3.10.1\u003csup\u003e30\u003c/sup\u003e as well as the EnrichmentMap v3.3.6\u003csup\u003e36\u003c/sup\u003e, AutoAnnotate v1.4.1\u003csup\u003e37\u003c/sup\u003e, and ClusterMaker2 v2.3.4\u003csup\u003e38\u003c/sup\u003e plug-ins. First, using EnrichmentMapping, a new enrichment map was created. The analysis type was set as \u0026ldquo;Generic/g:Profiler\u0026rdquo;. The enrichments file from the g:Profiler output and the GMT file downloaded from g:Profiler were loaded into the tool. The FDR cut-off was set to 0.05. Other parameters were left at default settings. To identify major \u0026ldquo;biological themes\u0026rdquo;, the resulting enrichment map network was then clustered using AutoAnnotate, which in turn uses ClusterMaker2 and the Markov Clustering (MCL) algorithm\u003csup\u003e39\u003c/sup\u003e. Using the default settings in the \u0026ldquo;Quick Start\u0026rdquo; tab, the network was annotated. The automatically generated cluster names were edited manually to reflect the biological theme of the cluster. The clusters were manually arranged to separate sub-networks. For visualisation, clusters with two terms or fewer were manually removed unless connected to a larger cluster.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAnimals\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e.\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eMale 15 weeks BALB/c nude mice were purchased from Janvier Labs, (France) and were housed in the\u0026nbsp;Bio-Resource Unit (BRU)\u0026nbsp;at the\u0026nbsp;University of Galway,\u0026nbsp;with monitoring and support provided by qualified animal\u0026nbsp;technicians and a veterinary surgeon.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eAll animal experiments were carried out in compliance with the Directive 2010/63/EU and in accordance with ARRIVE guidelines. Ethical approval was granted by the Animal Care Research Ethics Committee (ACREC) at the University of Galway (Ireland) and appropriate individual and project authorizations were granted by the Health Products Regulatory Authority in Ireland (AE19125 /P076). At day 7 post-HLI, mice were euthanised by overdose of anaesthesia (225mg/kg ketamine and 1.5 mg/kg medetomidine solution injected subcutaneously)\u0026nbsp;followed by cervical dislocation,\u0026nbsp;and their body weights were recorded\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eInduction of HLI and assessment of limb function\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e.\u003c/strong\u003e Unilateral hindlimb ischaemia (HLI) was induced in BALB/c nude mice by ligation of the femoral artery distal to the deep femoral artery, as previously described by our group\u003csup\u003e40\u003c/sup\u003e.\u0026nbsp;Animals were anaesthetised with 75mg/kg ketamine and 0.5 mg/kg medetomidine (Domitor 10) solution injected subcutaneously. Anaesthesia was partially reversed with atipamezole (5 mg/kg). The mice received analgesia (0.05-0.1 mg/kg of buprenorphine 8-12h for three days, and as required thereafter) and prophylactic antibiotic (0.1 mg/kg of Enrofloxacin/Baytril) was also given once post-operatively.\u0026nbsp;The laser Doppler perfusion imager (MoorLDI V6.0, Moor Instruments, Axminster, UK) was used to confirm drop in blood flow perfusion after HLI surgery as previously described\u003csup\u003e40\u003c/sup\u003e. Blood flow was measured in the soles of both feet, before (Pre-) and immediately after HLI surgery (Post-), and 7 days post-surgery, at which point, mice were humanely euthanised. Additionally, control mice of similar age not undergoing HLI surgery were euthanised.\u0026nbsp;Assessment of limb functionality (ambulatory score) was performed on days 3 and days 7 post-surgery. The ambulatory score ranged from 0 to 3 depending on the limb mobility (3 = dragging the foot; 2 = no dragging the foot but no plantar flexion; 1 = plantar flexion but no flexion of toes; 0 = flexion of toes to resist traction on the tail similar to the non-operated foot).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eTissue dissection and analysis.\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe calf muscles from the ischaemic (right) and non-ischaemic (left) hindlimbs of HLI mice and the right hindlimb of non-HLI mice\u0026nbsp;were carefully dissected, and their weight was recorded. Calf muscle mass was calculated as a percentage per body weight (calf muscle weight [g]*100/ body weight [g]).\u0026nbsp;Proximally, the soleus and gastrocnemius were separated and the proximal ~1/3 of both muscles were removed, snap-frozen in LN2 and stored at -80\u0026deg;C separately for molecular analysis. Distally, the soleus and gastrocnemius were kept intact and were fixed in 10% formalin for\u0026nbsp;48h, processed using the\u0026nbsp;Epredia\u0026trade; Excelsior\u0026trade; AS Tissue Processor\u0026nbsp;and embedded in paraffin blocks. Tissue cross-sections of\u0026nbsp;5mm thickness\u0026nbsp;were taken from the mid-belly of the dissected calf muscles and\u0026nbsp;rehydrated through a series of ethanol grades before staining with Haematoxylin and Eosin (H\u0026amp;E) and Mallory Trichrome staining using standard protocols.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eRNA Isolation\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. \u003c/strong\u003eTotal RNA was isolated from a portion of the proximal gastrocnemius muscle using the mirVana miRNA Isolation kit, with phenol (Invitrogen AM1560) according to the manufacturer\u0026apos;s instructions. RNA was quantified using a Qubit\u0026auml;\u0026nbsp;4 fluorometer (Invitrogen) and the associated Qubit\u0026auml;\u0026nbsp;RNA broad-range (BR) assay kit (Invitrogen, Q10211).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003emiRNA RT-qPCR\u003c/em\u003e\u003c/strong\u003e. 10 ng of total RNA was reverse transcribed using the Qiagen miRCURY LNA RT kit according to the manufacturer\u0026rsquo;s protocol. 1\u0026micro;L of each RNA sample was diluted to 5 ng/\u0026micro;L by adding an appropriate volume of RNase-free H2O. cDNA was diluted 1:60 and subsequently used in qPCR reaction using the miRCURY LNA qPCR SYBR Green kit and primer assays\u0026nbsp;(See\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eMajor Resources Table\u003c/strong\u003e)\u0026nbsp;on an\u0026nbsp;Applied Biosystems\u0026trade; StepOnePlus\u0026trade; Real-Time PCR System.\u0026nbsp;Relative expression of target miRNAs was normalised to miR-27b expression using the 2\u003csup\u003e-\u0026Delta;Cт\u0026nbsp;\u003c/sup\u003emethod.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003emRNA RT-qPCR\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e.\u003c/em\u003e\u003c/strong\u003e 1000ng of total RNA was used for reverse transcription using the Invitrogen Superscript IV Kit according to the manufacturer\u0026rsquo;s instructions. qPCR was performed in 10uL reactions using Fast SYBR\u0026trade; Green Master Mix (Applied Biosystems). 5ng of cDNA was used per reaction\u0026nbsp;A primer concentration of 200-500 nM and an annealing temperature of 60\u0026deg;C were used. Primer sequences (See\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eMajor Resources Table\u003c/strong\u003e)\u0026nbsp;were retrieved from PrimerBank which have been validated to specifically amplify the target of interest\u003csup\u003e41\u003c/sup\u003e. Samples were run in technical duplicates and a no template control (NTC) was run for each primer pair using molecular grade H\u003csub\u003e2\u003c/sub\u003eO instead of a cDNA sample. Relative expression of target mRNAs was normalised to the geometric mean of\u0026nbsp;\u003cem\u003eS29\u003c/em\u003e and\u0026nbsp;\u003cem\u003eGapdh\u003c/em\u003e expression using the 2\u003csup\u003e-\u0026Delta;Cт\u0026nbsp;\u003c/sup\u003emethod.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. \u003c/strong\u003eAll statistical analyses were performed using GraphPad Prism Version 9.4.1. In general, data were presented as mean \u0026plusmn; standard deviation (SD). D\u0026rsquo;Agostino \u0026amp; Pearson test was used to determine whether sample data came from a normally distributed population. Mean differences between the three groups were tested statistically with a one-way ANOVA followed by Tukey\u0026rsquo;s multiple comparison test. Statistical significance was assigned at p-value \u0026le; 0.05.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003ch2\u003emiRNA-Target Interaction Enrichment Analysis.\u003c/h2\u003e\n\u003cp\u003eThe muscle transcriptomic dataset obtained from Ryan \u003cem\u003eet al.\u003c/em\u003e identified a total of 3,627 genes expressed differentially in CLTI \u003cem\u003evs.\u003c/em\u003e non-PAD control; 3,999 genes differentially \u0026nbsp;expressed in CLTI \u003cem\u003evs.\u003c/em\u003e IC; and 397 genes differentially expressed in IC \u003cem\u003evs.\u003c/em\u003e non-PAD controls \u003csup\u003e12\u003c/sup\u003e. Of these, 2,261 were upregulated (UpDEG) and 1,366 were downregulated (DownDEG) in CLTI \u003cem\u003evs.\u003c/em\u003e non-PAD controls; 2,514 were upregulated and 1,485 were downregulated in CLTI \u003cem\u003evs.\u003c/em\u003e IC; 182 were upregulated and 215 were downregulated in IC \u003cem\u003evs.\u003c/em\u003e non-PAD. MTI enrichment analysis was performed using MIENTURNET based on the validated MTIs in the miRTarBase database. MTI enrichment of UpDEGs identified 6 over-represented miRNAs in CLTI \u003cem\u003evs.\u003c/em\u003e non-PAD controls and 10\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eover-represented miRNAs in CLTI \u003cem\u003evs.\u003c/em\u003e IC \u003cstrong\u003e(Table 1)\u003c/strong\u003e. No miRNAs were found to be significantly enriched when comparing the DownDEGs of CLTI \u003cem\u003evs.\u003c/em\u003e non-PAD or CLTI \u003cem\u003evs.\u003c/em\u003e IC, or when comparing the UpDEGs or DownDEGs of IC \u003cem\u003evs.\u003c/em\u003e non-PAD controls (\u003cstrong\u003eTable S1\u003c/strong\u003e).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eAn MTI network of the significantly enriched miRNAs and the corresponding upregulated targets was constructed showing a total of 948 MTIs for the CLTI \u003cem\u003evs.\u003c/em\u003e non-PAD group and 1,288 MTIs for the CLTI \u003cem\u003evs.\u003c/em\u003e IC group \u003cstrong\u003e(Fig 1)\u003c/strong\u003e. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 1. Significantly overrepresented miRNAs amongst UpDEGs based on experimentally validated MTIs using miRTarBase database.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"612\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.875816993464053%\"\u003e\n \u003cp\u003e\u003cstrong\u003emicroRNA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.07843137254902%\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.07843137254902%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFDR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.196078431372548%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOdds ratio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.77124183006536%\"\u003e\n \u003cp\u003e\u003cstrong\u003eN. i\u003c/strong\u003e\u003cstrong\u003enteractions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eCLTI vs. non-PAD control\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.875816993464053%\"\u003e\n \u003cp\u003ehsa-miR-124-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.07843137254902%\"\u003e\n \u003cp\u003e2.4187233E-11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.07843137254902%\"\u003e\n \u003cp\u003e6.19193E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.196078431372548%\"\u003e\n \u003cp\u003e0.68343878\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.77124183006536%\"\u003e\n \u003cp\u003e261\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.875816993464053%\"\u003e\n \u003cp\u003ehsa-miR-29b-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.07843137254902%\"\u003e\n \u003cp\u003e1.9913612E-07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.07843137254902%\"\u003e\n \u003cp\u003e0.00025489\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.196078431372548%\"\u003e\n \u003cp\u003e0.51894390\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.77124183006536%\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.875816993464053%\"\u003e\n \u003cp\u003ehsa-miR-335-5p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.07843137254902%\"\u003e\n \u003cp\u003e9.3510492E-07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.07843137254902%\"\u003e\n \u003cp\u003e0.00079796\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.196078431372548%\"\u003e\n \u003cp\u003e0.81163128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.77124183006536%\"\u003e\n \u003cp\u003e399\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.875816993464053%\"\u003e\n \u003cp\u003ehsa-miR-1-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.07843137254902%\"\u003e\n \u003cp\u003e0.00001016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.07843137254902%\"\u003e\n \u003cp\u003e0.00650341\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.196078431372548%\"\u003e\n \u003cp\u003e0.72315530\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.77124183006536%\"\u003e\n \u003cp\u003e157\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.875816993464053%\"\u003e\n \u003cp\u003ehsa-miR-133a-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.07843137254902%\"\u003e\n \u003cp\u003e0.00001543\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.07843137254902%\"\u003e\n \u003cp\u003e0.00789847\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.196078431372548%\"\u003e\n \u003cp\u003e0.47496759\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.77124183006536%\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.875816993464053%\"\u003e\n \u003cp\u003ehsa-miR-7110-5p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.07843137254902%\"\u003e\n \u003cp\u003e0.00010923\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.07843137254902%\"\u003e\n \u003cp\u003e0.04660619\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.196078431372548%\"\u003e\n \u003cp\u003e0.52479516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.77124183006536%\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eCLTI vs. IC\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003ehsa-miR-124-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e6.83E-16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e1.75E-12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e298\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003ehsa-miR-1-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e2.02E-10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.000000259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.648\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e190\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003ehsa-miR-335-5p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e1.23E-09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.00000105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.783\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e449\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003ehsa-miR-29b-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e2.67E-08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.0000171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.513\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003ehsa-miR-29a-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.00000126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.000648\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.554\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003ehsa-miR-133a-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.00000195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.000833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.461\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003ehsa-miR-29c-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.0000118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.00431\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.576\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003ehsa-miR-146a-5p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.0000189\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.00606\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.551\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003ehsa-miR-338-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.0000378\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.0108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.513\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003ehsa-miR-6885-3p\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.000103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.0265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e0.531\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"NaN%\" valign=\"top\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003e\u003cbr\u003e\u003c/h2\u003e\n\u003ch2\u003e\u003cem\u003eSevere\u0026nbsp;\u003c/em\u003e\u003cem\u003ecalf muscle pathology in HLI.\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eA preclinical HLI model was established to validate the role of bioinformatically identified miRNAs in skeletal muscle ischaemia\u003csup\u003e42\u003c/sup\u003e. HLI surgery immediately reduced the blood flow perfusion to 5% in the ischaemic limb. Blood flow recovery increased over time, but it was still impaired on day 7 \u003cstrong\u003e(Fig 2a)\u003c/strong\u003e. At 7 days post-HLI, a significant muscle atrophy and functional decline were observed, as indicated by an overall decrease in the percentage of calf muscle weight per body weight in ischaemic hindlimbs \u003cem\u003evs.\u003c/em\u003e the contralateral limb, and \u003cem\u003evs.\u003c/em\u003e limbs of no-HLI control mice \u003cstrong\u003e(Fig 2b)\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eand a poor ambulatory score \u003cstrong\u003e(Fig 2c)\u003c/strong\u003e. Histologically, the skeletal muscle architecture was dramatically perturbed after ischaemic injury \u003cstrong\u003e(Fig 2\u003c/strong\u003e\u003cstrong\u003ed\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e. Severe inflammation with leukocyte accumulation was found scattered across large areas of the muscle. This was accompanied by a significant loss of muscle fibre integrity and large areas of necrosis with active phagocytosis and fibrosis (collagen deposition in blue in the Mallory Trichrome images). Interestingly, mild inflammation and fibrosis were observed in the contralateral non-ischaemic limb of HLI mice in the absence of obvious disturbance of myofiber architecture. Muscle atrophy was assessed \u003cem\u003evia\u003c/em\u003e RT-qPCR as an indicator of muscle pathology. \u0026nbsp;\u003cem\u003eMurf1\u003c/em\u003e and \u003cem\u003eAtrogin1\u003c/em\u003e expresion (also known as \u003cem\u003eTrim63\u003c/em\u003e and \u003cem\u003eFbxo32\u003c/em\u003e, respectively) was decreased in the ischaemic limb \u003cem\u003evs.\u003c/em\u003e the contralateral non-ischaemic limbs and \u003cem\u003evs.\u003c/em\u003e the control no-HLI control mice \u003cstrong\u003e(Fig 2\u003c/strong\u003e\u003cstrong\u003ee, f\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e. Notably, the decrease in \u003cem\u003eMurf1\u003c/em\u003e expression was failed to reach significance (p = 0.0756). Myosin heavy chain 7 (\u003cem\u003eMyh7\u003c/em\u003e) expression was decreased in the ischaemic limb \u003cem\u003evs.\u003c/em\u003e the contralateral non-ischaemic limbs (p = 0.0295) and \u003cem\u003evs.\u003c/em\u003e the control no-HLI control mice (p = 0.0382) \u003cstrong\u003e(Fig 2\u003c/strong\u003e\u003cstrong\u003eg\u003c/strong\u003e\u003cstrong\u003e)\u003c/strong\u003e.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eAlpha skeletal muscle actin (\u003cem\u003eActa1\u003c/em\u003e) expressoin was not significantly changed in any group however there was a trend towards a decrease in the ischaemic limb \u003cem\u003evs.\u003c/em\u003e the contralateral non-ischaemic limbs (p = 0.0954) \u003cstrong\u003e(Fig 2h)\u003c/strong\u003e.\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003e\u003cem\u003emiRNA dysregulation in skeletal muscle ischaemia\u003c/em\u003e\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eSince MTIs of identified miRNAs were over-represented among UpDEGs in ischaemic muscle, it was hypothesised that the levels of these miRNAs would be decreased. RT-qPCR was performed on RNA isolated from the gastrocnemius muscle of the ischaemic and non-ischaemic limbs of mice that underwent the HLI procedure, and control mice that did not undergo the procedure. The results showed a significant and marked ischaemia-induced decrease in miR-1, miR-133a, and miR-29b in the ischaemic limbs compared to the contralateral non-ischaemic limbs (p = 0.0001, p = 0.0005, p = 0.0292, respectively) and the no-HLI control mice (p \u0026lt; 0.0001, p = 0.0001, p = 0.0230, respectively) \u003cstrong\u003e(Fig 3a, b, c)\u003c/strong\u003e. Contrary to the hypothesis, miR-124 was not significantly dysregulated in the ischaemic limbs\u0026nbsp;compared to\u003cem\u003e\u0026nbsp;\u003c/em\u003ethe contralateral non-ischaemic limbs (p = 0.8792) or the control no-HLI control mice (p = 0.8662)\u0026nbsp;(\u003cstrong\u003eFig 3d\u003c/strong\u003e). miR-335 expression was significantly higher in the ischaemic limbs than the contralateral non-ischaemic limbs (p = 0.0015) and the control no-HLI control mice (p = 0.0014) \u003cstrong\u003e(Fig 3e)\u003c/strong\u003e. miR-7110 was not assessed as it was not annotated in mice in the miRbase database\u003csup\u003e43\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003emiR-1, miR-133a, and miR-29b Functional Enrichment Analysis\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eAs hypothesised,\u0026nbsp;miR-1, miR-133a, and miR-29b\u0026nbsp;expression was\u0026nbsp;downregulated\u0026nbsp;in ischaemic mouse muscle. It was\u0026nbsp;then\u0026nbsp;considered that these three miRNAs may co-operatively regulate the skeletal muscle pathology in CLTI.\u0026nbsp;The\u0026nbsp;mRNAs that were:\u0026nbsp;a) targeted by one or more of these miRNAs, and b) upregulated in CLTI patient skeletal muscle, were further investigated. First, an MTI subnetwork was created for the three differentially expressed miRNAs and the network characteristics were assessed. Notably, most mRNAs were targeted by one miRNA and a minority were targeted by two miRNAs with only one targeted by all three miRNAs (\u003cstrong\u003eFig 4a\u003c/strong\u003e). To understand the functional interactions of these enriched targets, PPI network analyses were performed using STRING. The STRING PPI network consisted of 235 nodes with 1134 edges, and the expected number of edges was 513 with a corresponding PPI enrichment p-value of \u0026lt; 1*10\u003csup\u003e-16\u003c/sup\u003e indicating a significant degree of interaction between the input targets (\u003cstrong\u003eFig S\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e). The most important of these interacting nodes, i.e. the \u0026ldquo;hub nodes\u0026rdquo;, were then identified by the Mean Clique Centrality algorithm using CytoHubba. The top 20 hub nodes are displayed in \u003cstrong\u003eFig 4b\u003c/strong\u003e and they include many extracellular matrix (ECM) components such as collagens I, III, IV V, and VI as well as fibronectin-1 (FBN1) and fibrin-1 (FN1). Functional enrichment analysis was performed on this subset of DEGs and \u0026nbsp;EnrichmentMapping was then obtained (\u003cstrong\u003eFig 5\u003c/strong\u003e). The largest cluster consisted of terms associated with ECM and collagen which was connected with neighbouring clusters associated with collagen fibrils, integrin/signaling receptor/cell adhesion molecule binding, and platelet-derived growth factor (PDGF). The second-largest cluster was associated with leukocyte activation which connected to positive regulation of development and cell junction/adhesion clusters. The third largest cluster contained terms related to cardiovascular/blood vessel development which had five first-degree neighbouring clusters. These were related to embryonic development, skeletal system/bone development, PDGF, positive regulation of development, and vascular smooth muscle cell (VS.MC) proliferation. There was a cluster of terms related to fibroblast proliferation connected to the VS.MC proliferation cluster. Other clusters included those related to negative regulation of development, regulation of cell migration, secretory vesicle/granule, focal adhesion, anchoring/cell-substrate junction, positive regulation of cell death, and cellular response to nitrogen/peptide/amino acid. EnrichmentMapping of the targets of individual miRNAs can be accessed in \u003cstrong\u003eFig S\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003emRNA target validation in the HLI mouse model\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eWe\u0026nbsp;validated\u0026nbsp;specific targets of these miRNAs in the HLI mouse model.\u0026nbsp;The transcripts\u0026nbsp;of interest\u0026nbsp;were selected from the\u0026nbsp;top\u0026nbsp;hub nodes\u0026nbsp;as shown in\u0026nbsp;\u003cstrong\u003eFig 4\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eAll\u0026nbsp;the\u0026nbsp;targets\u0026nbsp;assessed\u0026nbsp;were significantly increased in\u0026nbsp;the\u0026nbsp;ischaemic limbs compared the contralateral non-ischaemic limbs and the no-HLI control mice, except for \u003cem\u003eTgf\u003c/em\u003e\u003cem\u003eb\u003c/em\u003e\u003cem\u003e2\u003c/em\u003e,\u0026nbsp;which did not change \u003cstrong\u003e(Fig 6)\u003c/strong\u003e. No target was differentially expressed between the non-ischaemic limbs of HLI mice and no-HLI control mice.\u0026nbsp;\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003ePAD is characterised by a complex, multifactorial skeletal muscle pathology that has devastating effects on patient QOL, with significant morbidity and mortality\u003csup\u003e\u003cspan additionalcitationids=\"CR3 CR4\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Despite some progress made in terms of medical and surgical interventions for PAD, the prognosis of CLTI remains poor with unacceptably high rates of amputation\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. Furthermore, novel investigational approaches (e.g. gene therapy with proangiogenic agents and stem cell-based therapies) have not demonstrated significant benefits in promoting CLTI limb salvage\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. One likely reason for this is the complex pathology of CLTI which is not affected by the dysfunction of a single gene; rather, it is characterised by broad gene dysregulation resulting in derangement of signalling pathways, processes, and networks in skeletal muscle\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Therefore, understanding the molecular regulation of skeletal muscle pathology in CLTI is imperative and will help in the rational design of novel therapeutics with a greater likelihood of success than previously attempted therapies.\u003c/p\u003e \u003cp\u003eConsidering the broad transcriptomic dysregulation in CLTI muscle\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, we investigated whether miRNAs could regulate these differentially expressed genes. We performed MTI enrichment analysis on the DEGs using MIENTURNET to identify miRNAs which may regulate significant portions of the dysregulated transcriptome in CLTI muscle. The underlying rationale for this was two-fold. First, it may further elucidate the underlying molecular pathology of CLTI-induced skeletal muscle pathology. Second, miRNAs identified in such a manner may represent novel therapeutics that could be delivered (or inhibited) as novel therapeutics to influence pathological gene expression and restore homeostasis in the ischaemic limb. For the first time, our bioinformatic analysis has identified a CLTI-specific miRNA dysregulation signature. Among the investigated UpDEGs, we identified six over-represented miRNAs in CLTI \u003cem\u003evs.\u003c/em\u003e non-PAD controls (miR-124-3p, miR-1-3p, miR-133a-3p, miR-29b-3p, miR-335-5p, and miR-7110-5p) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). When comparing CLTI \u003cem\u003evs.\u003c/em\u003e IC, we obtained a list of 10 over-represented miRNAs: miR-124-3p, miR-1-3p, miR-133a-3p, miR-29b-3p and miR-335-5p, which were also obtained when comparing CLTI \u003cem\u003evs.\u003c/em\u003e non-PAD controls, as well as others including miR-29a-3p, miR-29c-3p, miR-338-5p, miR-146a-5p, and miR-6885-3p (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). No over-represented miRNAs were found when comparing the IC and non-PAD controls.\u003c/p\u003e \u003cp\u003eWe then used the preclinical mouse model of CLTI to validate the predicted downregulation of miRNAs identified in CLTI \u003cem\u003evs.\u003c/em\u003e non-PAD controls. The rationale for choosing this group was that, \u003cem\u003ein vivo\u003c/em\u003e, we compared skeletal muscles severely affected by ischaemic injury with control non-ischaemic muscles. First, skeletal muscle pathology was confirmed in the HLI model 7 days post-ischaemia induction. Significant skeletal muscle atrophy was indicated by decreased calf muscle mass and limb function, and downregulation of muscle mass-related genes (\u003cem\u003eMyh7\u003c/em\u003e and \u003cem\u003eActa1)\u003c/em\u003e. \u003cem\u003eAtrogin1\u003c/em\u003e and \u003cem\u003eMurf1\u003c/em\u003e, which are common markers of muscle atrophy\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e, were also decreased (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). A similar finding has been reported where these markers only transiently increased immediately after HLI injury and then decreased below pre-ischaemic levels by day 3 post-HLI\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. Histologically, ischaemic muscle presented with severe inflammation, necrosis, and fibrosis with significant loss of muscle fibre integrity, which is consistent with human data\u003csup\u003e\u003cspan additionalcitationids=\"CR51\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. Mild inflammation in the absence of obvious disturbance of myofibre architecture was observed in the contralateral non-ischaemic limb of HLI mice, which disappeared 28 days post-HLI surgery\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. This is an interesting observation that may be important to consider when undertaking preclinical studies using this animal model.\u003c/p\u003e \u003cp\u003eWe then investigated whether the specific miRNAs were downregulated as predicted by our bioinformatics analysis. The most significantly enriched miRNA identified by our bioinformatics analysis was miR-124-3p (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Functional enrichment analysis of DEGs targeted by miR-124-3p identified enrichment for terms associated with ECM structure and collagen as well as vascular development and angiogenesis (\u003cb\u003eFig S3a\u003c/b\u003e). This is supported by previously published literature, where miR-124-3p has been shown to regulate angiogenesis in an HLI model\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. Here, delivery of miR-124 mimics in an HLI model inhibited perfusion recovery and decreased capillary density at day 14, while antagomiRs had the opposite effect in both of these measures\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. RT-qPCR validation of the HLI model on day 7 post-HLI revealed that miR-124 was not dysregulated. Interestingly, Shi \u003cem\u003eet al.\u003c/em\u003e reported that miR-124 is transiently increased immediately in response to HLI, with a peak in expression at day 2 and restoration to pre-ischaemic levels by day 3\u003csup\u003e53\u003c/sup\u003e, which supports our findings.\u003c/p\u003e \u003cp\u003eThe identification of miR-29b is interesting as it is a well-known fibrosis-associated miRNA, together with miR-29a and miR-29c. The miR-29 family has been shown to be involved in inhibiting ECM synthesis indicating its antifibrotic function\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. Despite the relatively low number of input genes (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), there was a marked degree of functional enrichment among the targets related to the underlying fibrotic mechanisms (\u003cb\u003eFig S2e\u003c/b\u003e). The data presented here contributes to the already known role of miR-29b as a \u0026ldquo;fibromiR\u0026rdquo;. We hypothesised that in the ischaemic limb, miR-29b may directly regulate fibrosis-associated pathology, a hallmark feature of CLTI\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, by targeting ECM-associated transcripts. We validated the downregulation of miR-29b in skeletal muscle and upregulation of its ECM-related target mRNAs in response to ischaemic injury, at a time point where intermuscular fibrosis was already observed histologically. Other studies have reported decreased levels of miR-29b in fibrosis \u003csup\u003e\u003cspan additionalcitationids=\"CR56 CR57\" citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e, which support our findings. In addition, decreased expression in circulation is associated with increased mortality in patients with pulmonary fibrosis\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e. Functional enrichment analysis also identified enrichment for terms associated with arterial dissection/aneurysm and vascular development/angiogenesis and interconnection with fibrosis-associated clusters (\u003cb\u003eFig S2e\u003c/b\u003e). This may be indicative of the fibrotic changes seen in the microvasculature of the PAD/CLTI muscle\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e, in which VSMCs show increased TGF-β levels and collagen deposition. miR-29b has been investigated as a potential anti-fibrotic agent, particularly in the context of pulmonary fibrosis \u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. Delivery of miR-29b mimics has also demonstrated pre-clinical and early clinical efficacy in cutaneous fibrosis (drug name: Remlarsen or MRG-201)\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. While miR-29b has not been delivered in an HLI model, its family member, miR-29a has been investigated in this context. In murine diabetic HLI models, inhibition of miR-29a enhanced perfusion recovery, muscle regeneration and function, and capillary density by day 21\u003csup\u003e62,63\u003c/sup\u003e. However, while ischaemia induced a decrease in miR-29a expression in the gastrocnemius, diabetic HLI was associated with an increase in miR-29a \u003cem\u003evs.\u003c/em\u003e non-diabetic HLI\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. This observation was consistent in humans with and without diabetes\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. The molecular mechanisms by which hyperglycaemia impairs miR-29a expression is not well known. The compounding effects of metabolic dysfunction in the context of ischaemia may have specific effects on miRNA dysregulation that must be considered.\u003c/p\u003e \u003cp\u003emiR-1 and miR-133a are two of the canonical \u0026ldquo;myomiRs\u0026rdquo; and were also found to be CLTI-specific (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). myomiRs are muscle-enriched miRNAs with key roles in the regulation of muscle function and pathology\u003csup\u003e\u003cspan additionalcitationids=\"CR65\" citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e. Early work by Chen \u003cem\u003eet al.\u003c/em\u003e identified distinct roles for miR-1 and miR-133a in promoting myogenesis and myoblast proliferation, respectively\u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e. Despite increasing acknowledgement of the importance of skeletal muscle pathology in CLTI, myomiRs remain relatively understudied in this context. Greco \u003cem\u003eet al.\u003c/em\u003e suggested that a decrease in miR-1 levels (and also miR-29c) in response to ischaemia was not seen in isolated myofibres but only in the total muscle bulk. This suggests that the decrease in expression may be due to the loss or atrophy of myofibres and relative over-representation in the cellular mass in the muscle of non-myofibre cell types \u003csup\u003e\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e. Fibrosis is a key feature of muscle pathology in CLTI, and myogenic progenitor cell dysfunction is also observed\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e,\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e. The clinical implications of this remain to be fully understood; however, recent \u003cem\u003ein vivo\u003c/em\u003e studies using knockout models, have indicated that Pax7\u003csup\u003e+\u003c/sup\u003e myogenic progenitor cells are necessary for regeneration after HLI injury. In the absence of these cells, fibroadipogenic progenitor cells (FAPs) are activated and contribute to ischaemic muscle pathology by increasing adipogenesis\u003csup\u003e\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e. Dysregulation of the adipogenic and fibrotic differentiation of FAPs due to age, trauma, or disease can lead to abnormal intermuscular fat infiltration and excessive fibrosis, resulting in muscle loss and dysfunction\u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e. It is not unreasonable that ischaemia-induced impairments in muscle progenitor cell (MPC) function and relative reductions in myomiR levels may regulate fibrosis. For instance, in muscle injury, MPCs traffic miR-206 to fibrogenic cells \u003cem\u003evia\u003c/em\u003e extracellular vesicles (EVs.) and thereby regulate ECM deposition in the muscle\u003csup\u003e\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTo the best of our knowledge, miR-1 has not been investigated in terms of its ability to regulate recovery in a pre-clinical HLI model. In contrast, miR-133a has been investigated in a pre-clinical model of diabetic HLI\u003csup\u003e\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u003c/sup\u003e. Interestingly, the delivery of miR-133a was detrimental (and its inhibition was beneficial) in this model in terms of perfusion recovery, and its expression in the skeletal muscle was upregulated compared to that in non-diabetic mice. Here, in a non-diabetic HLI mouse model, we found a marked downregulation of miR-133a. It is possible that the diabetic milieu may alter miR-133a expression in skeletal muscle ischaemia and impact the effect of modulation of this miRNA, similar to what has been observed for miR-29a\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. This finding raises important concerns for the field of miRNA therapy in cardiovascular disease as diabetes is one of the most significant risk factors for PAD and differences in the roles of specific miRNAs in vascular diseases with or without diabetes are not inconsequential.\u003c/p\u003e \u003cp\u003emiR-335 had the highest number of targets upregulated in the CLTI muscle (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Functional enrichment analysis indicated that this miRNA may regulate the inflammatory response in ischaemia (\u003cb\u003eFig S2c\u003c/b\u003e). In sepsis-induced myocardial injury, miR-335 exerts a protective effect by regulating the inflammatory response\u003csup\u003e\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e. In the peripheral blood of PAD patients, miR-335 was reported to be downregulated \u003csup\u003e\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u003c/sup\u003e. As an anecdotal observation within our group, in various unrelated and related analyses using MIENTURNET, miR-335 is frequently enriched. It is possible that it may be a common false positive miRNA when using this tool. This highlights the importance of validating bioinformatically identified targets in relevant models.\u003c/p\u003e \u003cp\u003emiR-7110-5p was not assessed in a pre-clinical model as it has not been annotated in mice\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Unlike other miRNAs, this is a relatively novel miRNA. However, recent investigations have suggested that miR-7110-5p is downregulated in diabetes\u003csup\u003e\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e and hypertrophic cardiomyopathy\u003csup\u003e\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u003c/sup\u003e. Additionally, it has been suggested that miR-7110-3p is implicated in pulmonary arterial hypertension\u003csup\u003e\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u003c/sup\u003e. Primer sequences are commercially available for this miRNA, both \u0026minus;\u0026thinsp;3p and \u0026minus;\u0026thinsp;5p strands, so investigation in human CLTI samples is warranted.\u003c/p\u003e \u003cp\u003eIn summary, several miRNAs with a potential regulatory role in skeletal muscle pathology in CLTI have been identified by MTI analysis. In pre-clinical validation, three of these miRNAs (miR-1, miR-133a, and miR-29b) were differentially expressed in the HLI model in the opposite direction to their targets in patient samples. Therefore, we hypothesised that these three miRNAs may represent a signature of skeletal muscle pathology in CLTI. To understand the potential role of these three miRNA panels in skeletal muscle ischaemia, we created a sub-MTI network of miR-1, miR-133a, and miR-29b and their targets that were upregulated in the CLTI muscle. A PPI network was constructed to understand the functional association between the targets of these miRNAs in skeletal muscle ischaemia. Our results revealed a significant degree of interaction between the input targets, indicating a functional relationship between the targets \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eS\u003cb\u003e)\u003c/b\u003e. The hub nodes of this PPI network were identified as the most important nodes in the network \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Several ECM components were identified in this network including fibrillar collagens I, III, and V, the helical collagen IV, collagen VI, fibronectin, and fibrin. Known anti-angiogenic factors thrombospondin1 and thrombospondin2 were also present in this network. The expression for the selection of targets from these hub nodes was validated using the HLI model. Concurrent with the downregulation of the three miRNAs, their targets were upregulated, except for \u003cem\u003eTgfβ2\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). We further investigated the roles of these targets by functional enrichment analysis using enrichment mapping \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. This aimed to understand the pathways and biological functions that may be regulated by this three-miRNA signature in skeletal muscle ischaemia. Here, the over-representation of several \u0026ldquo;biological themes\u0026rdquo; was identified. Firstly, the largest biological theme identified was fibrosis. Numerous clusters related to the ECM and collagen, PDGF, cell adhesion, and fibroblast proliferation were identified. Fibrosis is a pathological process whereby there is excessive deposition of ECM (in particular, collagen), impairment in ECM degradation, or both of these processes\u003csup\u003e\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e,\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e. Fibrosis is a hallmark feature of skeletal muscle pathology in CLTI and has been suggested to be a central mechanism of disease progression\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Additionally, vascular development and the VS.MC cluster may further pertain to the CLTI-associated vascular pathology and associated fibrotic process as there is an ischaemia-induced increase in expression of \u003cem\u003eTgfβ1\u003c/em\u003e in VS.MCs which is associated with fibroblast accumulation and collagen deposition\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e,\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis study has several limitations. There is an inherent limitation of using the HLI model to validate the predicted dysregulation of miRNAs and their targets in CLTI patients, as this model only allows the study if muscle regeneration in response to acute ischaemic injury compared to chronic ischaemia in CLTI patients. We also only validated miRNAs that were enriched in the CLTI \u003cem\u003evs.\u003c/em\u003e non-PAD control group. It is plausible that other miRNAs enriched in the CLTI vs. IC group could also be dysregulated in HLI ischaemic muscles, especially miRNAs from the miR-29 family, including miR-29a and miR-29c. It is also possible that specific miRNAs play different physiological and/or pathological roles in different ischaemic contexts. Therefore, miRNA dysregulation should be investigated in muscle samples from CLTI, IC, and non-PAD controls.\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eTo the best of our knowledge, this is the first study to identify miR-1, miR-133a, and miR-29b as potential regulators of skeletal muscle pathology in patients with CLTI. The results presented here indicate miR-1, miR-133a, and miR-29b as a miRNA signature of skeletal muscle fibrosis in CLTI. Given the enrichment of these miRNAs in transcriptomic data, these miRNAs likely represent central regulators of this muscle pathology and warrant further investigation as potential therapeutics. A defining feature of miRNAs is their pleiotropic nature: a single miRNA can regulate many mRNAs, and a single mRNA can be regulated by many miRNAs\u003csup\u003e\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e\u003c/sup\u003e. From a therapeutic perspective, this makes miRNAs an attractive candidate for novel \u0026lsquo;systems-based\u0026rsquo; therapies that could regulate this broad transcriptomic and pathway dysregulation\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e\u003c/sup\u003e. Each of these miRNAs individually possesses therapeutically relevant properties in this context. However, miRNA-based therapy poses the risk of off-target effects, which must be considered\u003csup\u003e\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e\u003c/sup\u003e. Considering the potential for off-target effects, it is likely that the translation of miRNA therapeutics will require rational identification and validation of candidate miRNAs along with targeting strategies such as modification of the oligonucleotide to target specific cell types. The former has been investigated recently in the case of MRG-229, a miR-29b mimic which was modified with a bicyclic peptide specific for PDGFR-β to be internalised by fibrogenic cells in the lung\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e. Such novel therapeutics may restore homeostasis in the ischaemic limb by targeting pathological transcriptomic dysregulation, restoring it to non-ischaemic levels, and ultimately, preventing amputation and improving patient outcomes. Additionally, there is a distinct possibility to investigate the miR-1, miR-133a, and miR-29b panels as potential combinatorial miRNA therapeutics. The co-delivery of multiple miRNAs that may co-operatively regulate complementary targets in on-target pathways may allow a lower dose of each individual miRNA to be administered and reduce the likelihood of perturbing off-target pathways\u003csup\u003e\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e\u003c/sup\u003e. Nevertheless, the roles of these specific miRNAs remain relatively novel in the context of PAD/CLTI and ischaemic skeletal muscle regeneration, and investigation of these miRNAs as potential therapeutics is still warranted.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eAll animal experiments were carried out in compliance with the Directive 2010/63/EU. Ethical approval was granted by the Animal Care Research Ethics Committee (ACREC) at the University of Galway (Ireland) and appropriate individual and project authorizations were granted by the Health Products Regulatory Authority in Ireland (AE19125 /P076).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials.\u003c/strong\u003e RNA-sequencing-based profiles from CLTI, IC and non-PAD adults utilised here (GSE120642) can be publicly accessed at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE120642. The authors declare that the data supporting the findings of this study are available within the article and its supplementary information files and also available from the corresponding author upon request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosures:\u0026nbsp;\u003c/strong\u003eTOB is a founder, director, and equity holder in Orbsen Therapeutics Ltd.\u0026nbsp;The\u0026nbsp;other\u0026nbsp;authors\u0026nbsp;do not have\u0026nbsp;competing interests\u0026nbsp;to declare.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s contributions.\u0026nbsp;\u003c/strong\u003eAJK,\u0026nbsp;CSN, DJ,\u0026nbsp;MC,\u0026nbsp;XZ, CJL and IS\u0026nbsp;carried out\u0026nbsp;experiments,\u0026nbsp;analysis, and/or interpretation of results.\u0026nbsp;AJK,\u0026nbsp;CSN, DJ,\u0026nbsp;MC, CJL,\u0026nbsp;KGW, and TOB conceived the study, participated in the design of the study, and/or\u0026nbsp;helped to draft the manuscript. The final manuscript was read and approved by all the authors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSources of Funding\u003c/strong\u003e. This publication has emanated from the research supported by Irish Research Council grant no. GOIPG/2020/1235 (AJK) and GOIPG/2017/1993 (DJ).\u0026nbsp;The authors acknowledge the facilities and scientific and technical assistance of the University of Galway Screening and Genomics Core\u0026nbsp;and the Bio-Resource Unit (BRU) staff.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements.\u0026nbsp;\u003c/strong\u003eGraphical Abstract was created with BioRender.com.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eNorgren L, Hiatt WR, Dormandy JA, et al. 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Trends Genet 38:613\u0026ndash;626. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.tig.2022.02.006\u003c/span\u003e\u003cspan address=\"10.1016/j.tig.2022.02.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"chronic limb-threatening ischaemia, fibrosis, muscle regeneration, microRNAs","lastPublishedDoi":"10.21203/rs.3.rs-4242453/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4242453/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eChronic limb-threatening ischaemia (CLTI), the most severe manifestation of peripheral arterial disease (PAD), is associated with a poor prognosis and high amputation rates. Despite novel therapeutics approaches being investigated, no significant clinical benefits habe been observed yet. Understanding the molecular pathways of skeletal muscle dysfunction in CLTI is crucial for designing successful treatments. This study aimed to identify miRNAs dysregulated in muscle biopsies from PAD cohorts. Using \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eMI\u003c/span\u003ecroRNA \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eEN\u003c/span\u003erichment \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eTUR\u003c/span\u003ened \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eNET\u003c/span\u003ework (MIENTURNET) on a publicly accessible RNA-sequencing database of PAD cohorts, we identified a list of miRNAs that were over-represented among the upregulated differentially expressed genes (DEGs) in CLTI. Next, we validated the altered expression of these miRNAs and their targets in mice with hindlimb ischaemia (HLI). Our results showed a significant downregulation in miR-1, miR-133a, and miR-29b leves in the ischaemic limbs versus the contralateral non-ischaemic limbs. A miRNA target protein-protein interaction network identified extracellular matrix components, including collagen-1a1, -3a1, and \u0026minus;\u0026thinsp;4a1, fibronectin-1, fibrin-1, matrix metalloproteinase-2 and \u0026minus;\u0026thinsp;14, and Sparc, which were upregulated in the ischaemic muscle of mice. This is the first study to identify miR-1, miR-133a, and miR-29b as potential contributors to fibrosis and vascular pathology in CLTI muscle, which supports their potential as novel therapeutic agents.\u003c/p\u003e","manuscriptTitle":"miR-1, miR-133a, miR-29b and Skeletal Muscle Fibrosis in Chronic Limb-Threatening Ischaemia.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-19 09:48:51","doi":"10.21203/rs.3.rs-4242453/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-06-03T05:20:41+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-31T12:44:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"227341808439789019991012994722178370504","date":"2024-05-23T01:39:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-17T09:03:31+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-10T00:38:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"87bc7c03-ce82-4a5d-ad4c-06419f36ccef","date":"2024-04-25T07:56:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"c12af487-80ee-403c-a30d-4f0a38437a2e","date":"2024-04-25T07:35:25+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-04-20T23:40:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-20T23:10:19+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-04-16T14:34:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-16T14:30:27+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-04-09T13:58:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"67a47b29-3aa2-40f3-b9b6-669a42ce2119","owner":[],"postedDate":"April 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":30770209,"name":"Health sciences/Medical research/Pre clinical studies"},{"id":30770210,"name":"Health sciences/Medical research/Translational research"}],"tags":[],"updatedAt":"2024-12-02T15:59:03+00:00","versionOfRecord":{"articleIdentity":"rs-4242453","link":"https://doi.org/10.1038/s41598-024-76415-9","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-11-26 15:56:54","publishedOnDateReadable":"November 26th, 2024"},"versionCreatedAt":"2024-04-19 09:48:51","video":"","vorDoi":"10.1038/s41598-024-76415-9","vorDoiUrl":"https://doi.org/10.1038/s41598-024-76415-9","workflowStages":[]},"version":"v1","identity":"rs-4242453","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4242453","identity":"rs-4242453","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}