Evaluation of miRNAs regulation of BDNF and IGF1 genes in T2DM insulin resistance in experimental models: bioinformatics based approach

Avaliação da regulação por miRNAs dos genes BDNF e IGF1 na resistência a insulina no diabetes do tipo 2 em modelos experimentais: in silico

Abstract

microRNAs (miRNAs) are recognized as diabetes mellitus type 2 (T2DM) biomarkers useful for disease metabolism comprehension and have great potential as therapeutics targets. BDNF and IGF1 increased expression are highly involved in the benefits of insulin and glucose paths, however, they are down-regulated in insulin resistance conditions, while their expression increase is correlated to the improvement of glucose and insulin metabolism. Studies suggest the microRNA regulation of these genes in several different contexts, providing a novel investigation approach for comprehending T2DM metabolism and revealing potential therapeutic targets. In the present study, we investigate in different animal models (human, rat, and mouse) miRNAs that target BDNF and IGF1 in skeletal muscle tissue with T2DM physiological conditions. Bioinformatics tools and databases were used to miRNA prediction, molecular homology, experimental validation of interactions, expression in the studied physiological condition, and network interaction. The findings showed three miRNAs candidates for IGF1(miR-29a, miR-29b, and miR-29c) and one for BDNF (miR-206). The experimental evaluations and the search for the expression in skeletal muscle from T2DM subjects confirmed the predicted interaction between miRNA-mRNA for miR-29b and miR-206 through human, rat, and mouse models. This interaction was reaffirmed in multiple network analyses. In conclusion, our results show the regulation relationship between miR-29b and miR-206 with the investigated genes, in several tissues, suggesting an inhibition pattern. Nevertheless, these data show a large number of possible interaction physiological processes, for future biotechnological prospects.

Keywords:
miRNAs prediction; T2DM; IGF1/BDNF; therapeutics; interaction validation

Resumo

Os microRNAs (miRNAs) são reconhecidos como biomarcadores do diabetes mellitus tipo 2 (DM2), úteis para a compreensão do metabolismo da doença, e possuem grande potencial como alvos terapêuticos. O aumento da expressão de BDNF e IGF1 está altamente envolvido nos benefícios as vias de insulina e glicose, porém, são regulados negativamente em condições de resistência à insulina, enquanto seu aumento de expressão está correlacionado com a melhora do metabolismo da glicose e da insulina. Estudos sugerem a regulação desses genes por microRNA em vários contextos diferentes, proporcionando uma nova abordagem de investigação para compreender o metabolismo do DM2 e revelar potenciais alvos terapêuticos. No presente estudo, investigamos em diferentes modelos animais (humanos, ratos e camundongos) miRNAs que têm como alvo BDNF e IGF1 em tecido muscular esquelético com condições fisiológicas de DM2. As análises foram realizadas utilizando ferramentas de bioinformática e bancos de dados para predição de miRNA, homologia molecular, validação experimental de interações, expressão na condição fisiológica estudada e interação em rede. Os resultados mostraram três candidatos a miRNAs para IGF1 (miR-29a, miR-29b e miR-29c) e um para BDNF (miR-206). As avaliações experimentais e a busca pela expressão no músculo esquelético de indivíduos com DM2 confirmaram a interação prevista entre miRNA-mRNA para miR-29b e miR-206 através de modelos humanos, ratos e camundongos. Essa interação foi reafirmada em múltiplas análises de rede. Em conclusão, nossos resultados mostram a relação de regulação entre miR-29b e miR-206 com os genes investigados, em diversos tecidos, sugerindo um padrão de inibição. Contudo, esses dados mostram um grande número de possíveis processos fisiológicos de interação para perspectivas biotecnológicas.

Palavras-chave:
predição de miRNAS; DM2; IGF1/BDNF; terapêutica; validação de interação

1. Introduction

MicroRNAs (miRNAs) are small non-coding RNA molecules evolutionarily conserved, with approximately 22 nucleotides. They are involved in regulating numerous biological processes through post-transcription silencing mechanisms. These molecules can recognize and target specific messenger RNA (mRNA) by base pairing in seed sequence regions, a conserved heptameric sequence mainly situated at positions 2-7 from the miRNA 5´-end. These molecules lead to an inhibition mechanism mediated by a protein complex with endonucleases that cleavage the target causing its degradation and consequent translation repression (O’Brien et al., 2018).

The miRNAs are well known for their regulation roles in illnesses such as cancer, acting as tumor suppressors; in heart disorders, working like critical regulators of cardiovascular function, and neurodegenerative diseases, through the regulation of gene expression, being described as biomarkers for prognostics and diagnostics (Vishnoi and Rani, 2017). The knowledge about the mechanisms trigged by miRNAs is being elucidated for therapeutic uses, usually through the expression modulation causing its inhibition using designed specific small interference RNAs (siRNAs) or “antagomirs” (Krützfeldt et al., 2005).

Type 2 Diabetes Mellitus (T2DM) is a worldwide disorder strictly related to the subject lifestyle, being recurrent in overweight and sedentary individuals. T2DM disorder is characterized by hyperglycemic clinical conditions mediated by insulin functioning failures in target tissues (Kharroubi and Darwish, 2015). One of the main issues is insulin resistance (IR), characterized by the decrease of the cell sensibility to insulin action response, disabling the glucose capture by tissues, which leads to the increase of glucose in the blood flow. IR is highly related to T2DM and metabolic syndrome (Sinaiko and Caprio, 2012).

The genes BDNF and IGF1 have been related to improvements in glucose homeostasis and have an impressive expression regulation decrease in IR conditions (McDonald et al., 2007; Rozanska et al., 2020). In the T2DM profile, these genes are down-regulated, enabling their action through signaling beneficial mechanisms in the disorder pathogenesis (Fujinami et al., 2008; Suda et al., 2016). BDNF and IGF1 are genes that present a history of regulation by miRNAs in several different tissues (Numakawa et al., 2011; Jung and Suh, 2015).

miRNAs have an altered profile in T2DM, being useful as biomarkers for prognosis and diagnostics. Nevertheless, studies indicate that this non-coding RNA class is important for understanding the mechanisms involved in T2DM pathogenesis (Kim and Zhang, 2019). So, the investigation of specific miRNAs that target key genes can provide novel data for the comprehension of miRNA's role in T2DM and, through its interpretation, can reveal the metabolic paths and networks that they are involved which can allow the selection of potential candidates for future therapeutic approaches elaboration.

Thus, in the present, we explore the novelty of bioinformatics and data mining tools in view to provide an accurate and relevant investigation of the regulation by miRNAs in T2DM metabolism through the evaluation of these molecules in BDNF and IGF1 targeting, and the networks paths evolved. The study also prospects future in vivo application, so, for this, we performed an aggregated organisms approach for Homo sapiens, Rattus norvegicus and Mus musculus.

2. Methodology

2.1. Prediction of miRNAs candidates

The miRNAs prediction evaluation was performed in an aggregated methodology approach using the web-based bioinformatics sources: TargetScan (2021), miRDB (2021), and microT-CDS (Diana Lab, 2021) (Agarwal et al., 2015; Chen and Wang, 2020; Paraskevopoulou et al., 2013).

The miRNAs were selected according to the following statistical measures: TargerScan - score percentile ≳ 90%; miRDB - target score ≳ 90 and microT-CDS - miTG score ≳ 0.90. These variables are based on the probability of miRNAs repressing the target gene. The score percentile calculates the most favorable miRNA repression sites, the target score represents the confidence level of target prediction. In contrast, the miTG score is a general score for the predicted interaction, where the closer to 1, the better the confidence.

In view to produce a multiple organism approach, the query used for this predictions were the homologous genes: BDNF (ENSG00000176697) and IGF1 (ENSG00000017427) from humans (Homo sapiens); Igf1 (ENSRNOG00000004517) and Bdnf (ENSRNOG00000047466) from rat (Rattus norvegicus), and Igf1 (ENSMUSG00000020053) and Bdnf – (ENSMUSG00000048482) from mouse (Mus musculus).

The results of the prediction were separated by organism and tool in a Venn diagram using the InteractiVenn (2021) web-based tool (Heberle et al., 2015). The results were compared to select the miRNAs that were recurrent between the different prediction tools for the same organism, and later these results were confronted in view to select miRNAs recurrent between the three organisms.

2.2. miRNA conservation evaluation through the studied organisms

The miRNAs selected were compared for their similarity in nucleotide size, sequence, and chromosomic location through human, rat, and mouse genomes. The seed binding in the three target organisms was also compared using the TargetScan algorithm to select the most statistically significant binding site for each miRNA-mRNA combination (Agarwal et al., 2015).

2.3. miRNA-mRNA interaction validation

Were used the databases miRTArbase (2021) e TarBase V.08 (DIANA Tools, 2021) to investigate the experimental validation of the interactions between the selected miRNAs and the target genes. This evaluation were considerate the three organisms, target tissues, and the methodology used to confirm the interaction (Huang et al., 2020; Karagkouni et al., 2018).

2.4. Differential expression in T2DM skeletal muscle

Genome Expression Omnibus (GEO) (NCBI, 2021) were used to confront miRNAs candidates with datasets about healthy and T2DM conditions from skeletal muscle tissue of humans, rat, and mouse (Edgar et al., 2002). The skeletal muscle tissue was chosen due to its importance in the T2DM context, being one of the most affected organs in insulin resistance conditions and is highly deteriorated since it is responsible for the majority of insulin-stimulated body glucose disposal (Phielix and Mensink, 2008). This evaluation was considered in vitro and in vivo studies, where were identified the expression profile of the selected miRNAs in the T2DM condition.

2.5. Network multiple analyses

In miRnet (2021) platform were performed multiple evaluations for interactions between target genes, miRNAs selected, and other molecules in the genome, in view to identify the network relationship paths evolved. From that were investigated gene ontology (GO: BP) and diseases that were statistically related to the cluster by the same tool (Chang et al., 2020).

All the steps mentioned in the methodology are described in Figure 1.

Figure 1
Methodological pipeline followed in the study.

3. Results

3.1. In silico selection of the miRNAs candidates for targeting IGF1 and BDNF genes in humans, mouse, and rats

3.1.1. IGF-1 – miRNA target predictive evaluation

The predictive analyses of IGF1 (Figure 2) showed a total of 423 miRNAs, among these 260 were for humans (Figure 2A), 123 for a mouse (Figure 2B), and 40 for rat (Figure 2C). The comparison between the results of the different organisms' (Figure 2. D and Table 1) showed miR-29a, miR-29b, and miR-29c were recurrent for the three animal models. The list of the predicted miRNAs for IGF1 from each tool and organism is available in Table S1 of the Supplementary material.

Figure 2
Comparative Prediction for miRNA that targets IGF1 genes. (A) IGF1 – Human; (B) Igf1 – Mouse; (C) Igf1 – Rat; (D) Comparative results from Human, mouse, and rat.

Table 1
List of miRNAs obtained in the comparative prediction analyses using IGF1 as target for human, mouse and rat.

Human (hsa)	Mouse (mmu)	Rat (rno)	All
miR-206, miR-603, miR-1-3p	miR-1b, miR-206, miR-495	miR-10a, miR-1, miR-1b, miR-206, miR-495	miR-206

The comparations between the different tools and organisms (Figure 2, Table 1), showed in human (Figure 2A) 15 equal miRNAs between the tools, while in mouse and rat, the prediction evaluation reported only three equal miRNAs, each one. Between all organisms studied, three miRNAs were equal (miR-29a, miR-29b, and miR-29c), all from the same family.

3.1.2. BDNF – miRNA target predictive evaluation

BDNF evaluation (Figure 3) presented a total of 259 miRNAs, 102 of them, were from human (Figure 3A), 120 mouse (Figure 3B), and 37 rat (Figure 3C). Moreover, the evaluation comparing these results (Figure 3D, Table 2), showed mir-206 as the only predicted miRNA recurrent to target BDNF in the three organisms. The list of the predicted miRNAs for BDNF from each tool and organism is available in Table S2.

Figure 3
Comparative Prediction for miRNA that targets BDNF genes. (A) Human; (B) Mouse; (C) Rat; (D) Comparative results from Human, mouse, and rat).

Table 2
List of miRNAs obtained in the comparative prediction analyses using IGF1 as target for human, mouse and rat.

Human (hsa)	Mouse (mmu)	Rat (rno)	All
miR-301b, miR-301a, miR-130b, miR-130a, miR-4295, miR-3666, miR-454, miR-19a, miR-19b, miR-29b, miR-29a, miR-29c, miR-495, miR-5590, miR-486.	miR-1a, miR-206, miR-325, miR-29c, miR-29b, miR-29a, let-7e-5p	miR-29c, miR-29b, miR-29a	miR-29a, miR-29b, miR-29c

In human and mouse evaluation, three miRNAs were found recurrent between the results of the tools. In comparison, mouse presented a total of three and rat four. These evaluation results are disposable in Table 2. In the present evaluation, were not found match results in miRNA target prediction for Bdnf gene in rat using microT-CDS.

3.2. Molecular homology between the miRNAs candidates in the query organisms

The evaluation of molecular conservation investigated the similarity between the predicted miRNAs candidates through human, mouse, and rat genomes (Table 3). The results demonstrated an exact similarity for miR-206 and the three miR-29 family members in sequence size and nucleotide number in the organisms studied. However, all the chromosomic locations were different.

Table 3
miR-29 family and miR-206 conserved through human, mouse and rat.

Organism	Molecular Conserved miR	Chromossomic Location
Human	hsa-miR-29a 3p UAGCACCAUCUGAAAUCGGUUA	7q32.3
	| | | | | | | | | | | | | | | | | | | | | |
	mmu-miR-29a 3p UAGCACCAUCUGAAAUCGGUUA
Mouse	| | | | | | | | | | | | | | | | | | | | | |	6; 6 A3.3
Rat	rno-miR-29a 5p UAGCACCAUCUGAAAUCGGUUA	4q22
Human	hsa-miR-29b 3p UAGCACCAUUUGAAAUCAGUGUU	7q32.3
	| | | | | | | | | | | | | | | | | | | | | | |
	mmu-miR-29b 3p UAGCACCAUUUGAAAUCAGUGUU
Mouse	| | | | | | | | | | | | | | | | | | | | | | |	6; 6 A3.3
Rat	rno-miR-29b 3p UAGCACCAUUUGAAAUCAGUGUU	1
Human	hsa-miR-29c 5p UUGUGACUAAAGUUUACCACGAU	1q32.2
	| | | | | | | | | | | | | | | | | | | | | | |
	mmu-miR-29c 5p UUGUGACUAAAGUUUACCACGAU
Mouse	| | | | | | | | | | | | | | | | | | | | | | |	1; 1 H6
Rat	rno-miR-29c 5p UUGUGACUAAAGUUUACCACGAU	13q27
Human	hsa-miR-206-3p UGGAAUGUAAGGAAGUGUGUGG	6p12.2
	| | | | | | | | | | | | | | | | | | | | | |
	mmu-miR-206-3p UGGAAUGUAAGGAAGUGUGUGG
Mouse	| | | | | | | | | | | | | | | | | | | | | |	1; 1 A4
Rat	rno-miR-206-3p UGGAAUGUAAGGAAGUGUGUGG	9q13

3.3. miRNA-mRNA seed binding region through the human, mouse, and rat genomes

The evaluation of the miRNA-mRNA interaction position is described in Tables 4 and 5. The findings demonstrated a common sequence site of recurrent seven nucleotides (UGGUGCU) in the 8mer seed region, between the miRNAs (miR-29a, miR-29b, and miR-29c) and the IGF1 genes from the animal models.

Table 4
Seed sequence pairing when targeting IGF1 and its homologous.

mRNA-miRNA pairing
HUMAN	901-908 of IGF1 3' UTR	5'UGUUUUUUAGUAUAAUGGUGCUA...	8mer
		| | | | | | |
	hsa-miR-29a-3p	3' AUUGGCUAAAGUCUACCACGAU
	901-908 of IGF1 3' UTR	5'UGUUUUUUAGUAUAAUGGUGCUA...	8mer
		| | | | | | |
	hsa-miR-29b-3p	3'UUGUGACUAAAGUUUACCACGAU
	901-908 of IGF1 3' UTR	5'UGUUUUUUAGUAUAAUGGUGCUA | | | | | | |	8mer
	hsa-miR-29c-3p	3'AUUGGCUAAAGUUUACCACGAU
MOUSE	3602-3609 of Igf1 3' UTR	5'CCAGCUACGCCAAUGUGGUGCUA...	8mer
		| | | | | | |
	mmu-miR-29a-3p	3'AUUGGCUAAAGUCUACCACGAU
	3602-3609 of Igf1 3' UTR	5'CCAGCUACGCCAAUGUGGUGCUA...	8mer
		| | | | | | |
	mmu-miR-29b-3p	3'UUGUGACUAAAGUUUACCACGAU
	3602-3609 of Igf1 3' UTR	5'CCAGCUACGCCAAUGUGGUGCUA...	8mer
		| | | | | | |
	mmu-miR-29c-3p	3'AUUGGCUAAAGUUUACCACGAU
RAT	979-986 of Igf1 3' UTR	5'UUGUUUUUAGUACAAUGGUGCUA... | | | | | | |	8mer
	rno-miR-29a-3p	3'AUUGGCUAAAGUCUACCACGAU
	979-986 of Igf1 3' UTR	5'UUGUUUUUAGUACAAUGGUGCUA...	8mer
		| | | | | | |
	rno-miR-29b-3p	3'UUGUGACUAAAGUUUACCACGAU
	979-986 of Igf1 3' UTR	5'UUGUUUUUAGUACAAUGGUGCUA...	8mer
		| | | | | | |
	rno-miR-29c-3p	3'UUGUGACUAAAGUUUACCACGAU

Table 5
Seed position miR-206 and BDNF.

mRNA-miRNA pairing
Human	220-226 of BDNF 3' UTR	5'UAAAAAGUCUGCAUUACAUUCCU...	7mer-m8
		| | | | | | |
	hsa-miR-206	3'GGUGUGUGAAGGAAUGUAAGGU
Mouse	213-219 of Bdnf 3' UTR	5'UUAAAAGUCUGCAUUACAUUCCU...	7mer-m8
		| | | | | | |
	mmu-miR-206-3p	3'GGUGUGUGAAGGAAUGUAAGGU
Rat	214-220 of Bdnf 3' UTR	5'UUAAAAGUCUGCAUUACAUUCCU...	7mer-m8
		| | | | | | |
	rno-miR-206-3p	3'GGUGUGUGAAGGAAUGUAAGGU

In miR-206 evaluation (Table 5), the interaction with BDNF genes among the studied species demonstrated that the binding site was at the 7mer-m8 seed region, where the seed sequence was equal for human, rat, and mouse (UGUAAGG). However, the miRNA-mRNA binding position in each organism was different for the four miRNAs candidates to target the studied genes.

3.3.1. IGF1 genes interaction with miR-29a, miR-29b, and miR-29c in human, rat, and mouse

All the three miRNAs selected presented interactions with IGF1 genes by experimental approaches (Tables 6 and 7), but only in humans and mouse, in rats, the interaction was not described by any of the investigated databases.

Table 6
miRNA-IGF1 - Human Interaction validation experimentally.

Experimental Interaction
	miRTarbase 2020			TarBase V.08
miRNAS	Tissue	Validation Method	Reference	Tissue	Validation Method	Reference
miR-29a	Epididymis	Luciferase reporter assay qRTPCR Western blot	Ma et al. (2012)	Brain	HITS-CLIP	Boudreau et al. (2014)
miR-29b	-	-	-	Brain	HITS-CLIP	Boudreau et al. (2014)
miR-29c	-	-	-	Brain	HITS-CLIP	Boudreau et al. (2014)

• (-) Ausence of Correlation data.

Table 7
miRNA-Igf1 - Mouse Interaction validation experimentally.

Experimental Interaction
	miRTarbase 2020			TarBase V.08
miRNAS	Tissue	Validation Method	Reference	Tissue	Validation Method	Reference
miR-29a	Brain	ELISA Luciferase repórter assay qRT-PCR	Fenn et al. (2013)	Embryo	Luciferase reporter qPCR	(Hand et al. 2012)
miR-29b	Brain	ELISA Luciferase repórter assay qRT-PCR	Fenn et al. (2013)	Muscle (C2C2)	HITS-CLIP	Zhang et al. (2014)
				Liver	HITS-CLIP	Schug et al. (2013)
miR-29c	-	-	-	-	-	-

• (-) Ausence of Correlation data.

Reports from humans showed miR-29a and IGF1 gene interaction in the epididymis and the brain. The confirmation methodology for the first tissue was Luciferase reporter assay, qRT-PCR and Western blot. In the brain, the validation was performed with HITS-CLIP technology. miR-29b and miR-29c were also reported to target IGF1 in the brain by the same method.

Data from mouse experiments demonstrated that miR-29a targets Igf1 in the brain and embryo tissue. Both results were findings achieved by the use of the luciferase reporter assay method. Meanwhile, miR-29b was shown to target Igf1 in the brain, muscle (C2C12 cells), and liver. In the first, interactions were confirmed by ELISA, luciferase reporter assay, and qRT-PCR. In the others, interactions were validated by HITS-CLIP technology.

3.3.2. BDNF genes interaction with miR-206 in human, rat, and mouse

The search for the interactions from miR-206 for target BDNF genes miR-206 in experimentally validated experiments (Table 8), resulted in the confirmation of this interaction in human, mouse, and rat by miRTarbase database. However, in TarBase V.08. was not found the same results.

Table 8
mir-206-BDNF – Human, Mouse and Rat Interaction validation experimentally.

miRTarbase 2020
Human			Mouse			Rat
Tissue	Validation Method	Reference	Tissue	Validation Method	Reference	Tissue	Validation Method	Reference
Gastric Cancer Cells	Flow qRT-PCR	Ren et al. (2014)	C2C12	Luciferase reporter assay Microarray	Kim et al. (2006)	Brain	Luciferase reporter assay qRT-PCR ELISA Western Blot	(Sun et al.,2017)

Reports from humans show miR-206 targets BDNF in gastric cancer cells, data validated by flow cytometry and qRT-PCR. In mouse skeletal muscle, C2C12 cells the interaction was confirmed by microarray and Luciferase assay in healthy conditions. In rat, miRTarbase confirmed the interaction between miR-206 and Bdnf in the brain by the use of rt-PCR, western blot, and luciferase assay.

3.3.3. Predicted miRNAs expression in T2DM skeletal muscle

The studies selected in GEO datasets contemplate in vivo and in silico data in humans and rats, all with microarray methodology. Was not found studies with the mouse in the database that contemplates the conditions searched. The miR-29a, miR-29b, miR-29c, and miR-206 presence or absence as differentially expressed in these studies' datasets are described in Table 9.

Table 9
Analyses of miRNA Expression with T2DM Datasets from rat and human.

Expression Analyses
	Rat datasets		Human datasets
miRNAS	GSE68226 in vivo	GSE26167 in vivo	GSE68224 in vivo	GSE86069 in vitro
miR-29a	*	X	*	*
miR-29b	*	X	X	*
miR-29c	*	X	*	*
miR-206	*	X	X	X

• ^*
  Expressed in the study but not differentially.

In human, dataset GSE68224 demonstrated that miR-29b and miR-206 were present as up-regulated in vastus lateralis skeletal muscle from prediabetics and T2DM subjects. However, from the same consortium, GSE68226 dataset contemplates rat subjects and found the expression of miR-29a, miR-29b, miR-29c, and miR-206 expressed in healthy and insulin resistance induced by high-fat diet conditions.

In the GSE86069 dataset, the expression of miR-29a, miR-29b, miR-29c, and miR-206 were elucidated as being present in all phases of muscle differentiation from healthy and T2DM human samples. Of the miRNAs candidates, only miR-206 was found with differential expression in the late muscle differentiation stage.

In rat dataset GSE26167, was reported that miR-29a, miR-29b, and miR-29c presented significant expression changes in T2DM rats when compared to control.

3.3.4. Network multiple analyses of miRNAs candidates and targets

The multiple analyses were performed with the human genome; the results demonstrated the network interactions with miR-29a, miR-29b, miR-29c, miR-206, and its submitted respective targets IGF1 and BDNF (Figure 4). Each gene and miRNA formed an isolated complex network with statistically and experimentally correlations to miRNA or target genes.

Figure 4
Network interaction miRNA-mRNA generate cluster.

BDNF was correlated to miR-206 and other 48 miRNAs. While, IGF1 was correlated to a variety of 109 miRNAs, including the miR-29a, miR-29b, and miR-29c. The constructed network based on miRNAs candidates also demonstrated correlation to the respective target genes candidates (IGF1 and BDNF) as in the previous prediction evaluations. miR-29a-3p, were report to target 265 genes; miR-29b - 262, miR-29c - 255 and miR-206 - 122.

In Figure 5, are the top 10 pathways found in the network-generated enrichment analyses for GO: BP and diseases (Supplementary Material Table S3 and S4). The investigation demonstrated that the genes and miRNAs present in the gene-created cluster are highly related to regulation processes, mainly in metabolism. Of the miRNAs in the network, 22 were related to T2DM, including mir-29b and miR-206 in the evaluation for correlation with disease.

Figure 5
Top 10 enriched terms from GO Biological Process and Diseases.

4. Discussion

Aggregated prediction approach unites different algorithms in view to increase the quality of results. Predictions considering only one type of tool tend to have few characteristics for carrying out the evaluation. Since each tool considers different features, this combined approach can provide a multifactorial evaluation and help the improvement of the prediction in view to improve the sensibility of the miRNAs selection.

Most of the predicted miRNAs for human IGF1 were members of the same family. miRNAs families are classified according to the miRNAs ancestor’s derivation. Generally, members of the same family intend to perform roles in the same biological functions (Huang et al., 2009; Tapocik et al., 2014). The miR-29 family was highlighted in the evaluation for being recurrent in the three organisms. This agreement between them suggests that experimental genetic approaches in animals can be able to mimic gene modulation results in humans.

Among the miRNAs predicted to target BDNF genes, rat presented a reduced number, which was a consequence of the absence of results from microT CDS tool. This result is befitting of the small number of rat cataloged miRNAs in miRBase, where are 496 (Kozomara et al., 2019). miR-206 targets BDNF genes from human, mouse, and rat predictions and were also predicted to target Igf1 in the mouse. Thus, this data points to miRNA multiple target functioning, which endorses the need for specific approaches to predict the best seed binding affinity and specificity (Elton and Yalowich, 2015).

The convergency found in the miRNAs candidates in number and sequence suggests that the functioning of these molecules also can be similar due to the high evolutionary conservation between the studied animal models. Most of the RNA sequences are conserved through beings with the same direct ancestor. In this context, mammals use to present close molecular relationships also in miRNAs. The miRNA repression depends on the seed binding position, where the interaction happens with a match between 7 nucleotides. The most common targeting sites are 6mer, 7 mer-m8, and 8mer (Penso-Dolfin et al., 2018). Our analyses showed that the miRNAs found fit these criteria.

The miR-29 family showed high potential in targeting IGF1 in animal models studied. This interaction was strongly reported in the brain of human and mouse, causing a decrease in gene expression and, consequently, it is functioning (Fenn et al., 2013; Boudreau et al., 2014). miR-29b had many reports between the searched miR-29 family members. In mouse, this miRNA was identified to target Igf1 gene in a study with C2C12 cells of mitochondrial protein synthesis during muscle myogenesis, where miR-29b was identified as downregulated in myoblast and myocytes in healthy conditions (Zhang et al., 2014).

In mouse liver regeneration, miR-29b is downregulated, while, studies recognized it in the opposite process, having an upregulation profile in liver disease pathogenesis. Thus, there is also suggested that in T2DM condition, it has some effects on non-alcoholic fatty liver disease (NAFLD). It was reported that NAFLD is prevalent in 56,67% of T2DM patients (Schug et al., 2013; Dharmalingam and Yamasandhi, 2018).

For human organisms, the miR-206 – BDNF interaction is experimentally validated in gastric cancer, where the miRNA was up-regulated and the gene repressed (Ren et al., 2014). The “myomir” miR-206 is present in muscle differentiation from C2C12 lineage cells and is predicted to target Bdnf (Kim et al., 2006). In vitro approach confirmed that miR-206 suppressed Bdnf in C2C12 by rt-PCR, ELISA, and Northern Blot, validating the role of miR-206 in muscle differentiation signaling (Miura et al., 2012).

In the diabetes context, the datasets selected showed in rat GSE68226 dataset results insulin resistance induced by high-fat diet did not present differential expression of miR-29b, while, in prediabetics human and T2DM (GSE68224) this miRNA were differentially expressed (Latouche et al., 2016). This discrepancy may be due to insulin resistance conditions in rats since it is a predisposition step for diabetes, so at this state different miRNAs can be expressed (Taylor, 2012).

In the GSE26167 study, between the four candidates, miR-29a was relevant for being highly up-regulated in T2DM, which was later validated by rtPCR. The miR-29a expression profile was also described in human blood from T2DM subjects from the same cohort study (GSE21321) (Karolina et al., 2011).

GSE86069 investigated the stages of muscle proliferation and differentiation in human muscle healthy and T2DM donors. miR-206 was found in this context, with a reduced expression signature through the muscle differentiation stage in T2DM, and this finding was correlated to the reduction in myogenesis in T2DM cells (Henriksen et al., 2017).

In view to emphasize the potential therapeutic application for the human genome, the miRNA found and targets were submitted to network analyses. The results confirmed the interaction between miRNA and the target gene and also demonstrate that are a large number of interaction possibilities and physiological processes related. This result remits the importance of direct and indirect miRNA-mRNA interaction identification in the selection of functional mechanisms, excluding the interactions that are only biological noise (Cloonan, 2015). All the interactions disposed of in the network were obtained by the tool for construction are based on well-known prediction tools and data experimentally validated with also a well-annotated database (Edgar et al., 2002).

4. Conclusion

The evaluations of the presented study brought data that evidenced through in silico investigation a strong targeting relationship between the miRNAs mir-29 family and mir-206 with IGF1 and BDNF. Furthermore, the investigations showed high similarity and conservation between the related interactions in the three organisms studied, demonstrating a potential for reproducing these findings in different models. The evaluation of in vitro and in vivo studies in databases also corroborates these findings in several different tissues and also in the T2DM context, in which was observed that the miRNAs found were differentially expressed. The network evaluation results included metabolic paths and T2DM. Nevertheless, these results point to miRNA-mRNA strong interaction for future biotechnological prospects.

Supplementary material

Table S1 List of miRNA predictions using IGF1 as query for human, rat and mouse Table S2 List of miRNA predictions using BDNF as the query for human, rat, and mouse Table S3 List generate in miRNet Enrichment Results for GO BP Table S4 List generate in miRNet Enrichment Results for diseases

This material is available as part of the online article from https://www.scielo.br/j/bjb

Acknowledgements

We cordially thank the Coordination for Personal Improvement of Higher Education Personal (CAPES).

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Publication Dates

• Publication in this collection
  04 May 2022
• Date of issue
  2024

History

• Received
  24 Sept 2021
• Accepted
  30 Mar 2022