Editorial

2 pages, 179 KiB

Open AccessEditorial

Special Issue: “Bioinformatics and Omics Tools”

by Rui Vitorino

Int. J. Mol. Sci. 2023, 24(14), 11625; https://doi.org/10.3390/ijms241411625 - 19 Jul 2023

Cited by 1 | Viewed by 916

With the rapid introduction of high-throughput omics approaches such as genomics, transcriptomics, proteomics and metabolomics, the generation of large amounts of data has become a fundamental aspect of modern biological research [...] Full article

(This article belongs to the Special Issue Bioinformatics, Omics Tools and Tutorials)

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13 pages, 1572 KiB

Open AccessArticle

CuReSim-LoRM: A Tool to Simulate Metabarcoding Long Reads

by Yasmina Mesloub, Delphine Beury, Félix Vandermeeren and Ségolène Caboche

Int. J. Mol. Sci. 2023, 24(18), 14005; https://doi.org/10.3390/ijms241814005 - 12 Sep 2023

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Abstract

Metabarcoding DNA sequencing has revolutionized the study of microbial communities. Third-generation sequencing producing long reads had opened up new perspectives. Obtaining the full-length ribosomal RNA gene would permit one to reach a better taxonomic resolution at the species or the strain level. However, [...] Read more.

Metabarcoding DNA sequencing has revolutionized the study of microbial communities. Third-generation sequencing producing long reads had opened up new perspectives. Obtaining the full-length ribosomal RNA gene would permit one to reach a better taxonomic resolution at the species or the strain level. However, Oxford Nanopore Technologies (ONT) sequencing produces reads with high error rates, which introduces biases in analysis. Understanding the biases introduced during the analysis allows one to better interpret the biological results and take care of conclusions drawn from metabarcoding experiments. To benchmark an analysis process, the ground truth, i.e., the real composition of the microbial community, has to be known. In addition to artificial mock communities, simulated data are often used to evaluate the biases and performances of the bioinformatics analysis step. Currently, no specific tool has been developed to simulate metabarcoding long reads, mimic the error rate and the length distribution, and allow one to benchmark the analysis process. Here, we introduce CuReSim-LoRM, for the customized read simulator to generate long reads for metabarcoding. We showed that CuReSim-LoRM is able to produce reads with varying error rates and length distributions by mimicking the real data very well. Full article

(This article belongs to the Special Issue Bioinformatics, Omics Tools and Tutorials)

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18 pages, 5325 KiB

Open AccessArticle

Revisiting Assessment of Computational Methods for Hi-C Data Analysis

by Jing Yang, Xingxing Zhu, Rui Wang, Mingzhou Li and Qianzi Tang

Int. J. Mol. Sci. 2023, 24(18), 13814; https://doi.org/10.3390/ijms241813814 - 07 Sep 2023

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Abstract

The performances of algorithms for Hi-C data preprocessing, the identification of topologically associating domains, and the detection of chromatin interactions and promoter–enhancer interactions have been mostly evaluated using semi-quantitative or synthetic data approaches, without utilizing the most recent methods, since 2017. In this [...] Read more.

The performances of algorithms for Hi-C data preprocessing, the identification of topologically associating domains, and the detection of chromatin interactions and promoter–enhancer interactions have been mostly evaluated using semi-quantitative or synthetic data approaches, without utilizing the most recent methods, since 2017. In this study, we comprehensively evaluated 24 popular state-of-the-art methods for the complete end-to-end pipeline of Hi-C data analysis, using manually curated or experimentally validated benchmark datasets, including a CRISPR dataset for promoter–enhancer interaction validation. Our results indicate that, although no single method exhibited superior performance in all situations, HiC-Pro, DomainCaller, and Fit-Hi-C2 showed relatively balanced performances of most evaluation metrics for preprocessing, topologically associating domain identification, and chromatin interaction/promoter–enhancer interaction detection, respectively. The comprehensive comparison presented in this manuscript provides a reference for researchers to choose Hi-C analysis tools that best suit their needs. Full article

(This article belongs to the Special Issue Bioinformatics, Omics Tools and Tutorials)

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12 pages, 6350 KiB

Open AccessCommunication

Structural Insights into the Giardia lamblia Target of Rapamycin Homolog: A Bioinformatics Approach

by Patricia L. A. Muñoz-Muñoz, Rosa E. Mares-Alejandre, Samuel G. Meléndez-López and Marco A. Ramos-Ibarra

Int. J. Mol. Sci. 2023, 24(15), 11992; https://doi.org/10.3390/ijms241511992 - 26 Jul 2023

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Abstract

TOR proteins, also known as targets of rapamycin, are serine/threonine kinases involved in various signaling pathways that regulate cell growth. The protozoan parasite Giardia lamblia is the causative agent of giardiasis, a neglected infectious disease in humans. In this study, we used a [...] Read more.

TOR proteins, also known as targets of rapamycin, are serine/threonine kinases involved in various signaling pathways that regulate cell growth. The protozoan parasite Giardia lamblia is the causative agent of giardiasis, a neglected infectious disease in humans. In this study, we used a bioinformatics approach to examine the structural features of GTOR, a G. lamblia TOR-like protein, and predict functional associations. Our findings confirmed that it shares significant similarities with functional TOR kinases, including a binding domain for the FKBP-rapamycin complex and a kinase domain resembling that of phosphatidylinositol 3-kinase-related kinases. In addition, it can form multiprotein complexes such as TORC1 and TORC2. These results provide valuable insights into the structure–function relationship of GTOR, highlighting its potential as a molecular target for controlling G. lamblia cell proliferation. Furthermore, our study represents a step toward rational drug design for specific anti-giardiasis therapeutic agents. Full article

(This article belongs to the Special Issue Bioinformatics, Omics Tools and Tutorials)

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19 pages, 9329 KiB

Open AccessArticle

PARM1 Drives Smooth Muscle Cell Proliferation in Pulmonary Arterial Hypertension via AKT/FOXO3A Axis

by Zhen He, Teding Chang, Yu Chen, Hongjie Wang, Lei Dai and Hesong Zeng

Int. J. Mol. Sci. 2023, 24(7), 6385; https://doi.org/10.3390/ijms24076385 - 28 Mar 2023

Cited by 3 | Viewed by 1840

Abstract

Pulmonary arterial hypertension (PAH) is a group of severe, progressive, and debilitating diseases with limited therapeutic options. This study aimed to explore novel therapeutic targets in PAH through bioinformatics and experiments. Weighted gene co-expression network analysis (WGCNA) was applied to detect gene modules [...] Read more.

Pulmonary arterial hypertension (PAH) is a group of severe, progressive, and debilitating diseases with limited therapeutic options. This study aimed to explore novel therapeutic targets in PAH through bioinformatics and experiments. Weighted gene co-expression network analysis (WGCNA) was applied to detect gene modules related to PAH, based on the GSE15197, GSE113439, and GSE117261. GSE53408 was applied as validation set. Subsequently, the validated most differentially regulated hub gene was selected for further ex vivo and in vitro assays. PARM1, TSHZ2, and CCDC80 were analyzed as potential intervention targets for PAH. Consistently with the bioinformatic results, our ex vivo and in vitro data indicated that PARM1 expression increased significantly in the lung tissue and/or pulmonary artery of the MCT-induced PAH rats and hypoxia-induced PAH mice in comparison with the respective controls. Besides, a similar expression pattern of PARM1 was found in the hypoxia- and PDGF--treated isolated rat primary pulmonary arterial smooth muscle cells (PASMCs). In addition, hypoxia/PDGF--induced PARM1 protein expression could promote the elevation of phosphorylation of AKT, phosphorylation of FOXO3A and PCNA, and finally the proliferation of PASMCs in vitro, whereas PARM1 siRNA treatment inhibited it. Mechanistically, PARM1 promoted PAH via AKT/FOXO3A/PCNA signaling pathway-induced PASMC proliferation. Full article

(This article belongs to the Special Issue Bioinformatics, Omics Tools and Tutorials)

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14 pages, 6064 KiB

Open AccessArticle

Predicting Key Genes and Therapeutic Molecular Modelling to Explain the Association between Porphyromonas gingivalis (P. gingivalis) and Alzheimer’s Disease (AD)

by Ahmed Hamarsha, Kumarendran Balachandran, Ahmad Tarmidi Sailan and Nurrul Shaqinah Nasruddin

Int. J. Mol. Sci. 2023, 24(6), 5432; https://doi.org/10.3390/ijms24065432 - 12 Mar 2023

Cited by 2 | Viewed by 2366

Abstract

The association between Porphyromonas gingivalis (P. gingivalis) and Alzheimer’s disease (AD) remains unclear. The major aim of this study was to elucidate the role of genes and molecular targets in P. gingivalis-associated AD. Two Gene Expression Omnibus (GEO) datasets, GSE5281 [...] Read more.

The association between Porphyromonas gingivalis (P. gingivalis) and Alzheimer’s disease (AD) remains unclear. The major aim of this study was to elucidate the role of genes and molecular targets in P. gingivalis-associated AD. Two Gene Expression Omnibus (GEO) datasets, GSE5281 for AD (n = 84 Alzheimer’s, n = 74 control) and GSE9723 (n = 4 P. gingivalis, n = 4 control), were downloaded from the GEO database. Differentially expressed genes (DEGs) were obtained, and genes common to both diseases were drawn. Additionally, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis was performed from the top 100 genes (50 upregulated and 50 downregulated genes). We then proceeded with CMap analysis to screen for possible small drug molecules targeting these genes. Subsequently, we performed molecular dynamics simulations. A total of 10 common genes (CALD1, HES1, ID3, PLK2, PPP2R2D, RASGRF1, SUN1, VPS33B, WTH3DI/RAB6A, and ZFP36L1) were identified with a p-value < 0.05. The PPI network of the top 100 genes showed UCHL1, SST, CHGB, CALY, and INA to be common in the MCC, DMNC, and MNC domains. Out of the 10 common genes identified, only 1 was mapped in CMap. We found three candidate small drug molecules to be a fit for PLK2, namely PubChem ID: 24971422, 11364421, and 49792852. We then performed molecular docking of PLK2 with PubChem ID: 24971422, 11364421, and 49792852. The best target, 11364421, was used to conduct the molecular dynamics simulations. The results of this study unravel novel genes to P. gingivalis-associated AD that warrant further validation. Full article

(This article belongs to the Special Issue Bioinformatics, Omics Tools and Tutorials)

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17 pages, 2497 KiB

Open AccessArticle

Quasispecies Fitness Partition to Characterize the Molecular Status of a Viral Population. Negative Effect of Early Ribavirin Discontinuation in a Chronically Infected HEV Patient

by Josep Gregori, Sergi Colomer-Castell, Carolina Campos, Marta Ibañez-Lligoña, Damir Garcia-Cehic, Ariadna Rando-Segura, Caroline Melanie Adombie, Rosa Pintó, Susanna Guix, Albert Bosch, Esteban Domingo, Isabel Gallego, Celia Perales, Maria Francesca Cortese, David Tabernero, Maria Buti, Mar Riveiro-Barciela, Juan Ignacio Esteban, Francisco Rodriguez-Frias and Josep Quer

Int. J. Mol. Sci. 2022, 23(23), 14654; https://doi.org/10.3390/ijms232314654 - 24 Nov 2022

Cited by 4 | Viewed by 1471

Abstract

The changes occurring in viral quasispecies populations during infection have been monitored using diversity indices, nucleotide diversity, and several other indices to summarize the quasispecies structure in a single value. In this study, we present a method to partition quasispecies haplotypes into four [...] Read more.

The changes occurring in viral quasispecies populations during infection have been monitored using diversity indices, nucleotide diversity, and several other indices to summarize the quasispecies structure in a single value. In this study, we present a method to partition quasispecies haplotypes into four fractions according to their fitness: the master haplotype, rare haplotypes at two levels (those present at <0.1%, and those at 0.1–1%), and a fourth fraction that we term emerging haplotypes, present at frequencies >1%, but less than that of the master haplotype. We propose that by determining the changes occurring in the volume of the four quasispecies fitness fractions together with those of the Hill number profile we will be able to visualize and analyze the molecular changes in the composition of a quasispecies with time. To develop this concept, we used three data sets: a technical clone of the complete SARS-CoV-2 spike gene, a subset of data previously used in a study of rare haplotypes, and data from a clinical follow-up study of a patient chronically infected with HEV and treated with ribavirin. The viral response to ribavirin mutagenic treatment was selection of a rich set of synonymous haplotypes. The mutation spectrum was very complex at the nucleotide level, but at the protein (phenotypic/functional) level the pattern differed, showing a highly prevalent master phenotype. We discuss the putative implications of this observation in relation to mutagenic antiviral treatment. Full article

(This article belongs to the Special Issue Bioinformatics, Omics Tools and Tutorials)

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13 pages, 2341 KiB

Open AccessArticle

Coronary Artery Disease and Aortic Valve Stenosis: A Urine Proteomics Study

by Luís Perpétuo, António S. Barros, Jéssica Dalsuco, Rita Nogueira-Ferreira, Pedro Resende-Gonçalves, Inês Falcão-Pires, Rita Ferreira, Adelino Leite-Moreira, Fábio Trindade and Rui Vitorino

Int. J. Mol. Sci. 2022, 23(21), 13579; https://doi.org/10.3390/ijms232113579 - 05 Nov 2022

Cited by 5 | Viewed by 2010

Abstract

Coronary artery disease (CAD) and the frequently coexisting aortic valve stenosis (AVS) are heart diseases accounting for most cardiac surgeries. These share many risk factors, such as age, diabetes, hypertension, or obesity, and similar pathogenesis, including endothelial disruption, lipid and immune cell infiltration, [...] Read more.

Coronary artery disease (CAD) and the frequently coexisting aortic valve stenosis (AVS) are heart diseases accounting for most cardiac surgeries. These share many risk factors, such as age, diabetes, hypertension, or obesity, and similar pathogenesis, including endothelial disruption, lipid and immune cell infiltration, inflammation, fibrosis, and calcification. Unsuspected CAD and AVS are sometimes detected opportunistically through echocardiography, coronary angiography, and magnetic resonance. Routine biomarkers for early detection of either of these atherosclerotic-rooted conditions would be important to anticipate the diagnosis. With a noninvasive collection, urine is appealing for biomarker assessment. We conducted a shotgun proteomics exploratory analysis of urine from 12 CAD and/or AVS patients and 11 controls to identify putative candidates to differentiate these diseases from healthy subjects. Among the top 20 most dysregulated proteins, TIMP1, MMP2 and vWF stood out, being at least 2.5× increased in patients with CAD/AVS and holding a central position in a network of protein-protein interactions. Moreover, their assessment in an independent cohort (19 CAD/AVS and 10 controls) evidenced strong correlations between urinary TIMP1 and vWF levels and a common cardiovascular risk factor - HDL (r = 0.59, p < 0.05, and r = 0.64, p < 0.01, respectively). Full article

(This article belongs to the Special Issue Bioinformatics, Omics Tools and Tutorials)

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