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Medical Genetics, Genomics and Bioinformatics – 2021
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Medical Genetics, Genomics and Bioinformatics – 2021

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".

Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 18974

Special Issue Editors

Prof. Dr. Yuriy L. Orlov

E-Mail Website
Guest Editor
The Digital Health Institute, I.M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University), 119991 Moscow, Russia
Interests: computer genomics; bioinformatics; digital medicine (e-Health); gene expression regulation; ChIP-seq
Special Issues, Collections and Topics in MDPI journals
Dr. Anastasia A. Anashkina

E-Mail Website1 Website2
Guest Editor
1. Engelhardt Institute of Molecular Biology RAS, 119991 Moscow, Russia
2. The Digital Health Institute, I.M. Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University), 119991 Moscow, Russia
Interests: structural bioinformatics; biophysics; bioinformatics
Special Issues, Collections and Topics in MDPI journals
Dr. Elena Yu. Leberfarb

E-Mail Website1 Website2
Guest Editor
1. Novosibirsk State Medial University, Novosibirsk, Russia
2. Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia
Interests: medical genetics; endocrinology; bioinformatics; human genetics

Special Issue Information

Dear Colleagues,

This Special issue collects papers on medical genomics, human population genetics, and computational biology applications in biomedicine continuing the topic presented earlier at MDPI IJMS special issues "Medical Genetics, Genomics and Bioinformatics" and “Medical Genetics, Genomics and Bioinformatics – 2020

https://0-www-mdpi-com.brum.beds.ac.uk/journal/ijms/special_issues/Medical_Genetics_Bioinformatics

https://0-www-mdpi-com.brum.beds.ac.uk/journal/ijms/special_issues/Medical_Genetics_Bioinformatics_2

Based on the readers’ interest to medical genetics and genomics we continue publication in this area based on novel technological approaches, gene networks and metabolic pathways analysis. Here, we focus on bioinformatics and systems biology approaches to medical genetics problems.

Topics of the Special Issue include:

- Bioinformatics approaches for medical genomics;

- Medical applications of genetics research.

- Systems biology and network medicine;

-- Interdisciplinary research in genetics;

- E-health and digital medicine tools;

The current collection continues the series of post-conference Special Journal Issues presenting the highlights from the set of international meetings on genetics in Russia SIBS 2020 (https://sechenov-sibs.confreg.org/), SBioMed-2020 (https://bgrssb.icgbio.ru/2020/symposium-systems-biology-and-biomedicine-human-genetics/) and MGNGS-2021(http://ngs.med-gen.ru/mgngs21/info/). We welcome novel materials beyond the conferences discussion.

Prof. Dr. Yuriy L. Orlov
Dr. Anastasia A. Anashkina
Dr. Elena Yu. Leberfarb
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Medical genetics
  • Population Genetics
  • Medical genomics
  • Bioinformatics
  • Computational biology
  • Molecular mechanisms of diseases
  • Systems biology for medicine
  • E-health

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Published Papers (32 papers)

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Editorial

Jump to: Research, Review

5 pages, 226 KiB  
Editorial
Recent Trends in Cancer Genomics and Bioinformatics Tools Development
by Anastasia A. Anashkina, Elena Y. Leberfarb and Yuriy L. Orlov
Int. J. Mol. Sci. 2021, 22(22), 12146; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms222212146 - 10 Nov 2021
Cited by 16 | Viewed by 3477
Abstract
We overview recent research trends in cancer genomics, bioinformatics tools development and medical genetics, based on results discussed in papers collections “Medical Genetics, Genomics and Bioinformatics” (https://www [...] Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics – 2021)
6 pages, 200 KiB  
Editorial
Medical Genetics, Genomics and Bioinformatics Aid in Understanding Molecular Mechanisms of Human Diseases
by Yuriy L. Orlov, Anastasia A. Anashkina, Vadim V. Klimontov and Ancha V. Baranova
Int. J. Mol. Sci. 2021, 22(18), 9962; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms22189962 - 15 Sep 2021
Cited by 21 | Viewed by 2601
Abstract
Molecular mechanisms of human disease progression often have complex genetic underpinnings, and sophisticated sequencing approaches coupled with advanced analytics [...] Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics – 2020)
5 pages, 179 KiB  
Editorial
Bioinformatics Methods in Medical Genetics and Genomics
by Yuriy L. Orlov, Ancha V. Baranova and Tatiana V. Tatarinova
Int. J. Mol. Sci. 2020, 21(17), 6224; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21176224 - 28 Aug 2020
Cited by 9 | Viewed by 3627
Abstract
Medical genomics relies on next-gen sequencing methods to decipher underlying molecular mechanisms of gene expression. This special issue collects materials originally presented at the “Centenary of Human Population Genetics” Conference-2019, in Moscow. Here we present some recent developments in computational methods tested on [...] Read more.
Medical genomics relies on next-gen sequencing methods to decipher underlying molecular mechanisms of gene expression. This special issue collects materials originally presented at the “Centenary of Human Population Genetics” Conference-2019, in Moscow. Here we present some recent developments in computational methods tested on actual medical genetics problems dissected through genomics, transcriptomics and proteomics data analysis, gene networks, protein–protein interactions and biomedical literature mining. We have selected materials based on systems biology approaches, database mining. These methods and algorithms were discussed at the Digital Medical Forum-2019, organized by I.M. Sechenov First Moscow State Medical University presenting bioinformatics approaches for the drug targets discovery in cancer, its computational support, and digitalization of medical research, as well as at “Systems Biology and Bioinformatics”-2019 (SBB-2019) Young Scientists School in Novosibirsk, Russia. Selected recent advancements discussed at these events in the medical genomics and genetics areas are based on novel bioinformatics tools. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics)

Research

Jump to: Editorial, Review

22 pages, 6241 KiB  
Article
MicroRNA-Mediated Regulation of the Virus Cycle and Pathogenesis in the SARS-CoV-2 Disease
by Rosalia Battaglia, Ruben Alonzo, Chiara Pennisi, Angela Caponnetto, Carmen Ferrara, Michele Stella, Cristina Barbagallo, Davide Barbagallo, Marco Ragusa, Michele Purrello and Cinzia Di Pietro
Int. J. Mol. Sci. 2021, 22(24), 13192; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms222413192 - 07 Dec 2021
Cited by 8 | Viewed by 3154
Abstract
In the last few years, microRNA-mediated regulation has been shown to be important in viral infections. In fact, viral microRNAs can alter cell physiology and act on the immune system; moreover, cellular microRNAs can regulate the virus cycle, influencing positively or negatively viral [...] Read more.
In the last few years, microRNA-mediated regulation has been shown to be important in viral infections. In fact, viral microRNAs can alter cell physiology and act on the immune system; moreover, cellular microRNAs can regulate the virus cycle, influencing positively or negatively viral replication. Accordingly, microRNAs can represent diagnostic and prognostic biomarkers of infectious processes and a promising approach for designing targeted therapies. In the past 18 months, the COVID-19 infection from SARS-CoV-2 has engaged many researchers in the search for diagnostic and prognostic markers and the development of therapies. Although some research suggests that the SARS-CoV-2 genome can produce microRNAs and that host microRNAs may be involved in the cellular response to the virus, to date, not enough evidence has been provided. In this paper, using a focused bioinformatic approach exploring the SARS-CoV-2 genome, we propose that SARS-CoV-2 is able to produce microRNAs sharing a strong sequence homology with the human ones and also that human microRNAs may target viral RNA regulating the virus life cycle inside human cells. Interestingly, all viral miRNA sequences and some human miRNA target sites are conserved in more recent SARS-CoV-2 variants of concern (VOCs). Even if experimental evidence will be needed, in silico analysis represents a valuable source of information useful to understand the sophisticated molecular mechanisms of disease and to sustain biomedical applications. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics – 2021)
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15 pages, 2392 KiB  
Article
Precise Characterization of Genetic Interactions in Cancer via Molecular Network Refining Processes
by Jinmyung Jung, Yongdeuk Hwang, Hongryul Ahn, Sunjae Lee and Sunyong Yoo
Int. J. Mol. Sci. 2021, 22(20), 11114; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms222011114 - 15 Oct 2021
Cited by 1 | Viewed by 1734
Abstract
Genetic interactions (GIs), such as the synthetic lethal interaction, are promising therapeutic targets in precision medicine. However, despite extensive efforts to characterize GIs by large-scale perturbation screening, considerable false positives have been reported in multiple studies. We propose a new computational approach for [...] Read more.
Genetic interactions (GIs), such as the synthetic lethal interaction, are promising therapeutic targets in precision medicine. However, despite extensive efforts to characterize GIs by large-scale perturbation screening, considerable false positives have been reported in multiple studies. We propose a new computational approach for improved precision in GI identification by applying constraints that consider actual biological phenomena. In this study, GIs were characterized by assessing mutation, loss of function, and expression profiles in the DEPMAP database. The expression profiles were used to exclude loss-of-function data for nonexpressed genes in GI characterization. More importantly, the characterized GIs were refined based on Kyoto Encyclopedia of Genes and Genomes (KEGG) or protein–protein interaction (PPI) networks, under the assumption that genes genetically interacting with a certain mutated gene are adjacent in the networks. As a result, the initial GIs characterized with CRISPR and RNAi screenings were refined to 65 and 23 GIs based on KEGG networks and to 183 and 142 GIs based on PPI networks. The evaluation of refined GIs showed improved precision with respect to known synthetic lethal interactions. The refining process also yielded a synthetic partner network (SPN) for each mutated gene, which provides insight into therapeutic strategies for the mutated genes; specifically, exploring the SPN of mutated BRAF revealed ELAVL1 as a potential target for treating BRAF-mutated cancer, as validated by previous research. We expect that this work will advance cancer therapeutic research. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics – 2021)
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20 pages, 3445 KiB  
Article
Unraveling the Relevance of ARL GTPases in Cutaneous Melanoma Prognosis through Integrated Bioinformatics Analysis
by Cheila Brito, Bruno Costa-Silva, Duarte C. Barral and Marta Pojo
Int. J. Mol. Sci. 2021, 22(17), 9260; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms22179260 - 26 Aug 2021
Cited by 6 | Viewed by 2453
Abstract
Cutaneous melanoma (CM) is the deadliest skin cancer, whose molecular pathways underlying its malignancy remain unclear. Therefore, new information to guide evidence-based clinical decisions is required. Adenosine diphosphate (ADP)-ribosylation factor-like (ARL) proteins are membrane trafficking regulators whose biological relevance in CM is undetermined. [...] Read more.
Cutaneous melanoma (CM) is the deadliest skin cancer, whose molecular pathways underlying its malignancy remain unclear. Therefore, new information to guide evidence-based clinical decisions is required. Adenosine diphosphate (ADP)-ribosylation factor-like (ARL) proteins are membrane trafficking regulators whose biological relevance in CM is undetermined. Here, we investigated ARL expression and its impact on CM prognosis and immune microenvironment through integrated bioinformatics analysis. Our study found that all 22 ARLs are differentially expressed in CM. Specifically, ARL1 and ARL11 are upregulated and ARL15 is downregulated regardless of mutational frequency or copy number variations. According to TCGA data, ARL1 and ARL15 represent independent prognostic factors in CM as well as ARL11 based on GEPIA and OncoLnc. To investigate the mechanisms by which ARL1 and ARL11 increase patient survival while ARL15 reduces it, we evaluated their correlation with the immune microenvironment. CD4+ T cells and neutrophil infiltrates are significantly increased by ARL1 expression. Furthermore, ARL11 expression was correlated with 17 out of 21 immune infiltrates, including CD8+ T cells and M2 macrophages, described as having anti-tumoral activity. Likewise, ARL11 is interconnected with ZAP70, ADAM17, and P2RX7, which are implicated in immune cell activation. Collectively, this study provides the first evidence that ARL1, ARL11, and ARL15 may influence CM progression, prognosis, and immune microenvironment remodeling. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics – 2021)
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12 pages, 3618 KiB  
Article
Hierarchical Structure of Protein Sequence
by Alexei N. Nekrasov, Yuri P. Kozmin, Sergey V. Kozyrev, Rustam H. Ziganshin, Alexandre G. de Brevern and Anastasia A. Anashkina
Int. J. Mol. Sci. 2021, 22(15), 8339; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms22158339 - 03 Aug 2021
Cited by 7 | Viewed by 2569
Abstract
Most non-communicable diseases are associated with dysfunction of proteins or protein complexes. The relationship between sequence and structure has been analyzed for a long time, and the analysis of the sequences organization in domains and motifs remains an actual research area. Here, we [...] Read more.
Most non-communicable diseases are associated with dysfunction of proteins or protein complexes. The relationship between sequence and structure has been analyzed for a long time, and the analysis of the sequences organization in domains and motifs remains an actual research area. Here, we propose a mathematical method for revealing the hierarchical organization of protein sequences. The method is based on the pentapeptide as a unit of protein sequences. Employing the frequency of occurrence of pentapeptides in sequences of natural proteins and a special mathematical approach, this method revealed a hierarchical structure in the protein sequence. The method was applied to 24,647 non-homologous protein sequences with sizes ranging from 50 to 400 residues from the NRDB90 database. Statistical analysis of the branching points of the graphs revealed 11 characteristic values of y (the width of the inscribed function), showing the relationship of these multiple fragments of the sequences. Several examples illustrate how fragments of the protein spatial structure correspond to the elements of the hierarchical structure of the protein sequence. This methodology provides a promising basis for a mathematically-based classification of the elements of the spatial organization of proteins. Elements of the hierarchical structure of different levels of the hierarchy can be used to solve biotechnological and medical problems. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics – 2021)
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12 pages, 1247 KiB  
Article
Genetic Contribution of Endometriosis to the Risk of Developing Hormone-Related Cancers
by Aintzane Rueda-Martínez, Aiara Garitazelaia, Ariadna Cilleros-Portet, Sergi Marí, Rebeca Arauzo, Jokin de Miguel, Bárbara P. González-García, Nora Fernandez-Jimenez, Jose Ramon Bilbao and Iraia García-Santisteban
Int. J. Mol. Sci. 2021, 22(11), 6083; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms22116083 - 04 Jun 2021
Cited by 7 | Viewed by 3432
Abstract
Endometriosis is a common gynecological disorder that has been associated with endometrial, breast and epithelial ovarian cancers in epidemiological studies. Since complex diseases are a result of multiple environmental and genetic factors, we hypothesized that the biological mechanism underlying their comorbidity might be [...] Read more.
Endometriosis is a common gynecological disorder that has been associated with endometrial, breast and epithelial ovarian cancers in epidemiological studies. Since complex diseases are a result of multiple environmental and genetic factors, we hypothesized that the biological mechanism underlying their comorbidity might be explained, at least in part, by shared genetics. To assess their potential genetic relationship, we performed a two-sample mendelian randomization (2SMR) analysis on results from public genome-wide association studies (GWAS). This analysis confirmed previously reported genetic pleiotropy between endometriosis and endometrial cancer. We present robust evidence supporting a causal genetic association between endometriosis and ovarian cancer, particularly with the clear cell and endometrioid subtypes. Our study also identified genetic variants that could explain those associations, opening the door to further functional experiments. Overall, this work demonstrates the value of genomic analyses to support epidemiological data, and to identify targets of relevance in multiple disorders. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics – 2021)
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20 pages, 1263 KiB  
Article
Bioinformatic Reconstruction and Analysis of Gene Networks Related to Glucose Variability in Diabetes and Its Complications
by Olga V. Saik and Vadim V. Klimontov
Int. J. Mol. Sci. 2020, 21(22), 8691; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21228691 - 18 Nov 2020
Cited by 23 | Viewed by 4148
Abstract
Glucose variability (GV) has been recognized recently as a promoter of complications and therapeutic targets in diabetes. The aim of this study was to reconstruct and analyze gene networks related to GV in diabetes and its complications. For network analysis, we used the [...] Read more.
Glucose variability (GV) has been recognized recently as a promoter of complications and therapeutic targets in diabetes. The aim of this study was to reconstruct and analyze gene networks related to GV in diabetes and its complications. For network analysis, we used the ANDSystem that provides automatic network reconstruction and analysis based on text mining. The network of GV consisted of 37 genes/proteins associated with both hyperglycemia and hypoglycemia. Cardiovascular system, pancreas, adipose and muscle tissues, gastrointestinal tract, and kidney were recognized as the loci with the highest expression of GV-related genes. According to Gene Ontology enrichment analysis, these genes are associated with insulin secretion, glucose metabolism, glycogen biosynthesis, gluconeogenesis, MAPK and JAK-STAT cascades, protein kinase B signaling, cell proliferation, nitric oxide biosynthesis, etc. GV-related genes were found to occupy central positions in the networks of diabetes complications (cardiovascular disease, diabetic nephropathy, retinopathy, and neuropathy) and were associated with response to hypoxia. Gene prioritization analysis identified new gene candidates (THBS1, FN1, HSP90AA1, EGFR, MAPK1, STAT3, TP53, EGF, GSK3B, and PTEN) potentially involved in GV. The results expand the understanding of the molecular mechanisms of the GV phenomenon in diabetes and provide molecular markers and therapeutic targets for future research. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics – 2020)
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15 pages, 10395 KiB  
Article
New Model for Stacking Monomers in Filamentous Actin from Skeletal Muscles of Oryctolagus cuniculus
by Anna V. Glyakina, Alexey K. Surin, Sergei Yu. Grishin, Olga M. Selivanova, Mariya Yu. Suvorina, Liya G. Bobyleva, Ivan M. Vikhlyantsev and Oxana V. Galzitskaya
Int. J. Mol. Sci. 2020, 21(21), 8319; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21218319 - 06 Nov 2020
Cited by 5 | Viewed by 2379
Abstract
To date, some scientific evidence (limited proteolysis, mass spectrometry analysis, electron microscopy (EM)) has accumulated, which indicates that the generally accepted model of double-stranded of filamentous actin (F-actin) organization in eukaryotic cells is not the only one. This entails an ambiguous understanding of [...] Read more.
To date, some scientific evidence (limited proteolysis, mass spectrometry analysis, electron microscopy (EM)) has accumulated, which indicates that the generally accepted model of double-stranded of filamentous actin (F-actin) organization in eukaryotic cells is not the only one. This entails an ambiguous understanding of many of the key cellular processes in which F-actin is involved. For a detailed understanding of the mechanism of F-actin assembly and actin interaction with its partners, it is necessary to take into account the polymorphism of the structural organization of F-actin at the molecular level. Using electron microscopy, limited proteolysis, mass spectrometry, X-ray diffraction, and structural modeling we demonstrated that F-actin presented in the EM images has no double-stranded organization, the regions of protease resistance are accessible for action of proteases in F-actin models. Based on all data, a new spatial model of filamentous actin is proposed, and the F-actin polymorphism is discussed. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics – 2020)
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12 pages, 713 KiB  
Article
Prediction of Protein–ligand Interaction Based on Sequence Similarity and Ligand Structural Features
by Dmitry Karasev, Boris Sobolev, Alexey Lagunin, Dmitry Filimonov and Vladimir Poroikov
Int. J. Mol. Sci. 2020, 21(21), 8152; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21218152 - 31 Oct 2020
Cited by 6 | Viewed by 1996
Abstract
Computationally predicting the interaction of proteins and ligands presents three main directions: the search of new target proteins for ligands, the search of new ligands for targets, and predicting the interaction of new proteins and new ligands. We proposed an approach providing the [...] Read more.
Computationally predicting the interaction of proteins and ligands presents three main directions: the search of new target proteins for ligands, the search of new ligands for targets, and predicting the interaction of new proteins and new ligands. We proposed an approach providing the fuzzy classification of protein sequences based on the ligand structural features to analyze the latter most complicated case. We tested our approach on five protein groups, which represented promised targets for drug-like ligands and differed in functional peculiarities. The training sets were built with the original procedure overcoming the data ambiguity. Our study showed the effective prediction of new targets for ligands with an average accuracy of 0.96. The prediction of new ligands for targets displayed the average accuracy 0.95; accuracy estimates were close to our previous results, comparable in accuracy to those of other methods or exceeded them. Using the fuzzy coefficients reflecting the target-to-ligand specificity, we provided predicting interactions for new proteins and new ligands; the obtained accuracy values from 0.89 to 0.99 were acceptable for such a sophisticated task. The protein kinase family case demonstrated the ability to account for subtle features of proteins and ligands required for the specificity of protein–ligand interaction. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics – 2020)
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17 pages, 2812 KiB  
Article
Gene Expression Regulation and Secretory Activity of Mesenchymal Stem Cells upon In Vitro Contact with Microarc Calcium Phosphate Coating
by Larisa Litvinova, Kristina Yurova, Valeria Shupletsova, Olga Khaziakhmatova, Vladimir Malashchenko, Egor Shunkin, Elena Melashchenko, Natalia Todosenko, Marina Khlusova, Yurii Sharkeev, Ekaterina Komarova, Maria Sedelnikova and Igor Khlusov
Int. J. Mol. Sci. 2020, 21(20), 7682; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21207682 - 16 Oct 2020
Cited by 8 | Viewed by 2568
Abstract
The manufacture of biomaterial surfaces with desired physical and chemical properties that can directly induce osteogenic differentiation without the need for biochemical additives is an excellent strategy for controlling the behavior of mesenchymal stem cells (MSCs) in vivo. We studied the cellular and [...] Read more.
The manufacture of biomaterial surfaces with desired physical and chemical properties that can directly induce osteogenic differentiation without the need for biochemical additives is an excellent strategy for controlling the behavior of mesenchymal stem cells (MSCs) in vivo. We studied the cellular and molecular reactions of MSCs to samples with a double-sided calcium phosphate (CaP) coating and an average roughness index (Ra) of 2.4–4.6 µm. The study aimed to evaluate the effect of a three-dimensional matrix on the relative mRNA expression levels of genes associated with the differentiation and maturation of MSCs toward osteogenesis (RUNX2, BMP2, BMP6, BGLAP, and ALPL) under conditions of distant interaction in vitro. Correlations were revealed between the mRNA expression of some osteogenic and cytokine/chemokine genes and the secretion of cytokines and chemokines that may potentiate the differentiation of cells into osteoblasts, which indicates the formation of humoral components of the extracellular matrix and the creation of conditions supporting the establishment of hematopoietic niches. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics – 2020)
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25 pages, 3387 KiB  
Article
Natural Catalytic IgGs Hydrolyzing Histones in Schizophrenia: Are They the Link between Humoral Immunity and Inflammation?
by Evgeny A. Ermakov, Daria A. Parshukova, Georgy A. Nevinsky and Valentina N. Buneva
Int. J. Mol. Sci. 2020, 21(19), 7238; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21197238 - 30 Sep 2020
Cited by 11 | Viewed by 2142
Abstract
Schizophrenia is known to be accompanied not only with an imbalance in the neurotransmitter systems but also with immune system dysregulation and chronic low-grade inflammation. Extracellular histones and nucleosomes as damage-associated molecular patterns (DAMPs) trigger systemic inflammatory and toxic reactions by activating Toll-like [...] Read more.
Schizophrenia is known to be accompanied not only with an imbalance in the neurotransmitter systems but also with immune system dysregulation and chronic low-grade inflammation. Extracellular histones and nucleosomes as damage-associated molecular patterns (DAMPs) trigger systemic inflammatory and toxic reactions by activating Toll-like receptors. In this work, we obtained the first evidence that polyclonal IgGs of patients with schizophrenia effectively hydrolyze five histones (H1, H2a, H2b, H3, and H4). Several strict criteria were used to demonstrate that histone-hydrolyzing activity is a property of the analyzed IgGs. The IgGs histone-hydrolyzing activity level, depending on the type of histone (H1–H4), was statistically significantly 6.1–20.2 times higher than that of conditionally healthy donors. The investigated biochemical properties (pH and metal ion dependences, kinetic characteristics) of these natural catalytic IgGs differed markedly from canonical proteases. It was previously established that the generation of natural catalytic antibodies is an early and clear sign of impaired humoral immunity. One cannot, however, exclude that histone-hydrolyzing antibodies may play a positive role in schizophrenia pathogenesis because histone removal from circulation or the inflamed area minimizes the inflammatory responses. Thus, it can be assumed that histone-hydrolyzing antibodies are a link between humoral immunity and inflammatory responses in schizophrenia. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics – 2020)
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13 pages, 810 KiB  
Article
Immunohistochemistry and Mutation Analysis of SDHx Genes in Carotid Paragangliomas
by Anastasiya V. Snezhkina, Dmitry V. Kalinin, Vladislav S. Pavlov, Elena N. Lukyanova, Alexander L. Golovyuk, Maria S. Fedorova, Elena A. Pudova, Maria V. Savvateeva, Oleg A. Stepanov, Andrey A. Poloznikov, Tatiana B. Demidova, Nataliya V. Melnikova, Alexey A. Dmitriev, George S. Krasnov and Anna V. Kudryavtseva
Int. J. Mol. Sci. 2020, 21(18), 6950; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21186950 - 22 Sep 2020
Cited by 13 | Viewed by 2884
Abstract
Carotid paragangliomas (CPGLs) are rare neuroendocrine tumors often associated with mutations in SDHx genes. The immunohistochemistry of succinate dehydrogenase (SDH) subunits has been considered a useful instrument for the prediction of SDHx mutations in paragangliomas/pheochromocytomas. We compared the mutation status of SDHx genes [...] Read more.
Carotid paragangliomas (CPGLs) are rare neuroendocrine tumors often associated with mutations in SDHx genes. The immunohistochemistry of succinate dehydrogenase (SDH) subunits has been considered a useful instrument for the prediction of SDHx mutations in paragangliomas/pheochromocytomas. We compared the mutation status of SDHx genes with the immunohistochemical (IHC) staining of SDH subunits in CPGLs. To identify pathogenic/likely pathogenic variants in SDHx genes, exome sequencing data analysis among 42 CPGL patients was performed. IHC staining of SDH subunits was carried out for all CPGLs studied. We encountered SDHx variants in 38% (16/42) of the cases in SDHx genes. IHC showed negative (5/15) or weak diffuse (10/15) SDHB staining in most tumors with variants in any of SDHx (94%, 15/16). In SDHA-mutated CPGL, SDHA expression was completely absent and weak diffuse SDHB staining was detected. Positive immunoreactivity for all SDH subunits was found in one case with a variant in SDHD. Notably, CPGL samples without variants in SDHx also demonstrated negative (2/11) or weak diffuse (9/11) SDHB staining (42%, 11/26). Obtained results indicate that SDH immunohistochemistry does not fully reflect the presence of mutations in the genes; diagnostic effectiveness of this method was 71%. However, given the high sensitivity of SDHB immunohistochemistry, it could be used for initial identifications of patients potentially carrying SDHx mutations for recommendation of genetic testing. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics – 2020)
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32 pages, 1378 KiB  
Article
Gene Expression Changes in the Ventral Tegmental Area of Male Mice with Alternative Social Behavior Experience in Chronic Agonistic Interactions
by Olga Redina, Vladimir Babenko, Dmitry Smagin, Irina Kovalenko, Anna Galyamina, Vadim Efimov and Natalia Kudryavtseva
Int. J. Mol. Sci. 2020, 21(18), 6599; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21186599 - 09 Sep 2020
Cited by 8 | Viewed by 2151
Abstract
Daily agonistic interactions of mice are an effective experimental approach to elucidate the molecular mechanisms underlying the excitation of the brain neurons and the formation of alternative social behavior patterns. An RNA-Seq analysis was used to compare the ventral tegmental area (VTA) transcriptome [...] Read more.
Daily agonistic interactions of mice are an effective experimental approach to elucidate the molecular mechanisms underlying the excitation of the brain neurons and the formation of alternative social behavior patterns. An RNA-Seq analysis was used to compare the ventral tegmental area (VTA) transcriptome profiles for three groups of male C57BL/6J mice: winners, a group of chronically winning mice, losers, a group of chronically defeated mice, and controls. The data obtained show that both winners and defeated mice experience stress, which however, has a more drastic effect on defeated animals causing more significant changes in the levels of gene transcription. Four genes (Nrgn, Ercc2, Otx2, and Six3) changed their VTA expression profiles in opposite directions in winners and defeated mice. It was first shown that Nrgn (neurogranin) expression was highly correlated with the expression of the genes involved in dopamine synthesis and transport (Th, Ddc, Slc6a3, and Drd2) in the VTA of defeated mice but not in winners. The obtained network of 31 coregulated genes, encoding proteins associated with nervous system development (including 24 genes associated with the generation of neurons), may be potentially useful for studying their role in the VTA dopaminergic neurons maturation under the influence of social stress. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics – 2020)
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24 pages, 2189 KiB  
Article
Potential Associations Among Alteration of Salivary miRNAs, Saliva Microbiome Structure, and Cognitive Impairments in Autistic Children
by Marco Ragusa, Maria Santagati, Federica Mirabella, Giovanni Lauretta, Matilde Cirnigliaro, Duilia Brex, Cristina Barbagallo, Carla Noemi Domini, Mariangela Gulisano, Rita Barone, Laura Trovato, Salvatore Oliveri, Gino Mongelli, Ambra Spitale, Davide Barbagallo, Cinzia Di Pietro, Stefania Stefani, Renata Rizzo and Michele Purrello
Int. J. Mol. Sci. 2020, 21(17), 6203; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21176203 - 27 Aug 2020
Cited by 26 | Viewed by 4659
Abstract
Recent evidence has demonstrated that salivary molecules, as well as bacterial populations, can be perturbed by several pathological conditions, including neuro-psychiatric diseases. This relationship between brain functionality and saliva composition could be exploited to unveil new pathological mechanisms of elusive diseases, such as [...] Read more.
Recent evidence has demonstrated that salivary molecules, as well as bacterial populations, can be perturbed by several pathological conditions, including neuro-psychiatric diseases. This relationship between brain functionality and saliva composition could be exploited to unveil new pathological mechanisms of elusive diseases, such as Autistic Spectrum Disorder (ASD). We performed a combined approach of miRNA expression profiling by NanoString technology, followed by validation experiments in qPCR, and 16S rRNA microbiome analysis on saliva from 53 ASD and 27 neurologically unaffected control (NUC) children. MiR-29a-3p and miR-141-3p were upregulated, while miR-16-5p, let-7b-5p, and miR-451a were downregulated in ASD compared to NUCs. Microbiome analysis on the same subjects revealed that Rothia, Filifactor, Actinobacillus, Weeksellaceae, Ralstonia, Pasteurellaceae, and Aggregatibacter increased their abundance in ASD patients, while Tannerella, Moryella and TM7-3 decreased. Variations of both miRNAs and microbes were statistically associated to different neuropsychological scores related to anomalies in social interaction and communication. Among miRNA/bacteria associations, the most relevant was the negative correlation between salivary miR-141-3p expression and Tannerella abundance. MiRNA and microbiome dysregulations found in the saliva of ASD children are potentially associated with cognitive impairments of the subjects. Furthermore, a potential cross-talking between circulating miRNAs and resident bacteria could occur in saliva of ASD. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics – 2020)
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18 pages, 6817 KiB  
Article
Disparity between Inter-Patient Molecular Heterogeneity and Repertoires of Target Drugs Used for Different Types of Cancer in Clinical Oncology
by Marianna A. Zolotovskaia, Maxim I. Sorokin, Ivan V. Petrov, Elena V. Poddubskaya, Alexey A. Moiseev, Marina I. Sekacheva, Nicolas M. Borisov, Victor S. Tkachev, Andrew V. Garazha, Andrey D. Kaprin, Peter V. Shegay, Alf Giese, Ella Kim, Sergey A. Roumiantsev and Anton A. Buzdin
Int. J. Mol. Sci. 2020, 21(5), 1580; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21051580 - 26 Feb 2020
Cited by 16 | Viewed by 3290
Abstract
Inter-patient molecular heterogeneity is the major declared driver of an expanding variety of anticancer drugs and personalizing their prescriptions. Here, we compared interpatient molecular heterogeneities of tumors and repertoires of drugs or their molecular targets currently in use in clinical oncology. We estimated [...] Read more.
Inter-patient molecular heterogeneity is the major declared driver of an expanding variety of anticancer drugs and personalizing their prescriptions. Here, we compared interpatient molecular heterogeneities of tumors and repertoires of drugs or their molecular targets currently in use in clinical oncology. We estimated molecular heterogeneity using genomic (whole exome sequencing) and transcriptomic (RNA sequencing) data for 4890 tumors taken from The Cancer Genome Atlas database. For thirteen major cancer types, we compared heterogeneities at the levels of mutations and gene expression with the repertoires of targeted therapeutics and their molecular targets accepted by the current guidelines in oncology. Totally, 85 drugs were investigated, collectively covering 82 individual molecular targets. For the first time, we showed that the repertoires of molecular targets of accepted drugs did not correlate with molecular heterogeneities of different cancer types. On the other hand, we found that the clinical recommendations for the available cancer drugs were strongly congruent with the gene expression but not gene mutation patterns. We detected the best match among the drugs usage recommendations and molecular patterns for the kidney, stomach, bladder, ovarian and endometrial cancers. In contrast, brain tumors, prostate and colorectal cancers showed the lowest match. These findings provide a theoretical basis for reconsidering usage of targeted therapeutics and intensifying drug repurposing efforts. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics)
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21 pages, 1127 KiB  
Article
The Impact of MNRI Therapy on the Levels of Neurotransmitters Associated with Inflammatory Processes
by Tatiana V. Tatarinova, Trina Deiss, Lorri Franckle, Susan Beaven and Jeffrey Davis
Int. J. Mol. Sci. 2020, 21(4), 1358; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21041358 - 18 Feb 2020
Cited by 3 | Viewed by 5085
Abstract
The neurotransmitter levels of representatives from five different diagnosis groups were tested before and after participation in the MNRI®—Masgutova Neurosensorimotor Reflex Intervention. The purpose of this study was to ascertain neurological impact on (1) Developmental disorders, (2) Anxiety disorders/OCD (Obsessive Compulsive [...] Read more.
The neurotransmitter levels of representatives from five different diagnosis groups were tested before and after participation in the MNRI®—Masgutova Neurosensorimotor Reflex Intervention. The purpose of this study was to ascertain neurological impact on (1) Developmental disorders, (2) Anxiety disorders/OCD (Obsessive Compulsive Disorder), PTSD (Post-Traumatic Stress disorder), (3) Palsy/Seizure disorders, (4) ADD/ADHD (Attention Deficit Disorder/Attention Deficit Disorder Hyperactive Disorder), and (5) ASD (Autism Spectrum Disorder) disorders. Each participant had a form of neurological dysregulation and typical symptoms respective to their diagnosis. These diagnoses have a severe negative impact on the quality of life, immunity, stress coping, cognitive skills, and social assimilation. This study showed a trend towards optimization and normalization of neurological and immunological functioning, thus supporting the claim that the MNRI method is an effective non-pharmacological neuromodulation treatment of neurological disorders. The effects of MNRI on inflammation have not yet been assessed. The resulting post-MNRI changes in participants’ neurotransmitters show significant adjustments in the regulation of the neurotransmitter resulting in being calmer, a decrease of hypervigilance, an increase in stress resilience, behavioral and emotional regulation improvements, a more positive emotional state, and greater control of cognitive processes. In this paper, we demonstrate that the MNRI approach is an intervention that reduces inflammation. It is also likely to reduce oxidative stress and encourage homeostasis of excitatory neurotransmitters. MNRI may facilitate neurodevelopment, build stress resiliency, neuroplasticity, and optimal learning opportunity. There have been no reported side effects of MNRI treatments. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics)
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9 pages, 1791 KiB  
Article
A Post-Processing Algorithm for miRNA Microarray Data
by Stepan Nersisyan, Maxim Shkurnikov, Andrey Poloznikov, Andrey Turchinovich, Barbara Burwinkel, Nikita Anisimov and Alexander Tonevitsky
Int. J. Mol. Sci. 2020, 21(4), 1228; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21041228 - 12 Feb 2020
Cited by 16 | Viewed by 3514
Abstract
One of the main disadvantages of using DNA microarrays for miRNA expression profiling is the inability of adequate comparison of expression values across different miRNAs. This leads to a large amount of miRNAs with high scores which are actually not expressed in examined [...] Read more.
One of the main disadvantages of using DNA microarrays for miRNA expression profiling is the inability of adequate comparison of expression values across different miRNAs. This leads to a large amount of miRNAs with high scores which are actually not expressed in examined samples, i.e., false positives. We propose a post-processing algorithm which performs scoring of miRNAs in the results of microarray analysis based on expression values, time of discovery of miRNA, and correlation level between the expressions of miRNA and corresponding pre-miRNA in considered samples. The algorithm was successfully validated by the comparison of the results of its application to miRNA microarray breast tumor samples with publicly available miRNA-seq breast tumor data. Additionally, we obtained possible reasons why miRNA can appear as a false positive in microarray study using paired miRNA sequencing and array data. The use of DNA microarrays for estimating miRNA expression profile is limited by several factors. One of them consists of problems with comparing expression values of different miRNAs. In this work, we show that situation can be significantly improved if some additional information is taken into consideration in a comparison. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics)
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41 pages, 5541 KiB  
Article
Candidate SNP Markers of Atherogenesis Significantly Shifting the Affinity of TATA-Binding Protein for Human Gene Promoters Show Stabilizing Natural Selection as a Sum of Neutral Drift Accelerating Atherogenesis and Directional Natural Selection Slowing It
by Mikhail Ponomarenko, Dmitry Rasskazov, Irina Chadaeva, Ekaterina Sharypova, Irina Drachkova, Dmitry Oshchepkov, Petr Ponomarenko, Ludmila Savinkova, Evgeniya Oshchepkova, Maria Nazarenko and Nikolay Kolchanov
Int. J. Mol. Sci. 2020, 21(3), 1045; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21031045 - 05 Feb 2020
Cited by 7 | Viewed by 3105
Abstract
(1) Background: The World Health Organization (WHO) regards atherosclerosis-related myocardial infarction and stroke as the main causes of death in humans. Susceptibility to atherogenesis-associated diseases is caused by single-nucleotide polymorphisms (SNPs). (2) Methods: Using our previously developed public web-service SNP_TATA_Comparator, we estimated statistical [...] Read more.
(1) Background: The World Health Organization (WHO) regards atherosclerosis-related myocardial infarction and stroke as the main causes of death in humans. Susceptibility to atherogenesis-associated diseases is caused by single-nucleotide polymorphisms (SNPs). (2) Methods: Using our previously developed public web-service SNP_TATA_Comparator, we estimated statistical significance of the SNP-caused alterations in TATA-binding protein (TBP) binding affinity for 70 bp proximal promoter regions of the human genes clinically associated with diseases syntonic or dystonic with atherogenesis. Additionally, we did the same for several genes related to the maintenance of mitochondrial genome integrity, according to present-day active research aimed at retarding atherogenesis. (3) Results: In dbSNP, we found 1186 SNPs altering such affinity to the same extent as clinical SNP markers do (as estimated). Particularly, clinical SNP marker rs2276109 can prevent autoimmune diseases via reduced TBP affinity for the human MMP12 gene promoter and therefore macrophage elastase deficiency, which is a well-known physiological marker of accelerated atherogenesis that could be retarded nutritionally using dairy fermented by lactobacilli. (4) Conclusions: Our results uncovered SNPs near clinical SNP markers as the basis of neutral drift accelerating atherogenesis and SNPs of genes encoding proteins related to mitochondrial genome integrity and microRNA genes associated with instability of the atherosclerotic plaque as a basis of directional natural selection slowing atherogenesis. Their sum may be stabilizing the natural selection that sets the normal level of atherogenesis. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics)
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18 pages, 3927 KiB  
Article
Unique k-mers as Strain-Specific Barcodes for Phylogenetic Analysis and Natural Microbiome Profiling
by Valery V. Panyukov, Sergey S. Kiselev and Olga N. Ozoline
Int. J. Mol. Sci. 2020, 21(3), 944; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21030944 - 31 Jan 2020
Cited by 6 | Viewed by 3347
Abstract
The need for a comparative analysis of natural metagenomes stimulated the development of new methods for their taxonomic profiling. Alignment-free approaches based on the search for marker k-mers turned out to be capable of identifying not only species, but also strains of [...] Read more.
The need for a comparative analysis of natural metagenomes stimulated the development of new methods for their taxonomic profiling. Alignment-free approaches based on the search for marker k-mers turned out to be capable of identifying not only species, but also strains of microorganisms with known genomes. Here, we evaluated the ability of genus-specific k-mers to distinguish eight phylogroups of Escherichia coli (A, B1, C, E, D, F, G, B2) and assessed the presence of their unique 22-mers in clinical samples from microbiomes of four healthy people and four patients with Crohn’s disease. We found that a phylogenetic tree inferred from the pairwise distance matrix for unique 18-mers and 22-mers of 124 genomes was fully consistent with the topology of the tree, obtained with concatenated aligned sequences of orthologous genes. Therefore, we propose strain-specific “barcodes” for rapid phylotyping. Using unique 22-mers for taxonomic analysis, we detected microbes of all groups in human microbiomes; however, their presence in the five samples was significantly different. Pointing to the intraspecies heterogeneity of E. coli in the natural microflora, this also indicates the feasibility of further studies of the role of this heterogeneity in maintaining population homeostasis. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics)
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21 pages, 5659 KiB  
Article
Elucidating Binding Sites and Affinities of ERα Agonists and Antagonists to Human Alpha-Fetoprotein by In Silico Modeling and Point Mutagenesis
by Nurbubu T. Moldogazieva, Daria S. Ostroverkhova, Nikolai N. Kuzmich, Vladimir V. Kadochnikov, Alexander A. Terentiev and Yuri B. Porozov
Int. J. Mol. Sci. 2020, 21(3), 893; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21030893 - 30 Jan 2020
Cited by 13 | Viewed by 3472
Abstract
Alpha-fetoprotein (AFP) is a major embryo- and tumor-associated protein capable of binding and transporting a variety of hydrophobic ligands, including estrogens. AFP has been shown to inhibit estrogen receptor (ER)-positive tumor growth, which can be attributed to its estrogen-binding ability. Despite AFP having [...] Read more.
Alpha-fetoprotein (AFP) is a major embryo- and tumor-associated protein capable of binding and transporting a variety of hydrophobic ligands, including estrogens. AFP has been shown to inhibit estrogen receptor (ER)-positive tumor growth, which can be attributed to its estrogen-binding ability. Despite AFP having long been investigated, its three-dimensional (3D) structure has not been experimentally resolved and molecular mechanisms underlying AFP–ligand interaction remains obscure. In our study, we constructed a homology-based 3D model of human AFP (HAFP) with the purpose of molecular docking of ERα ligands, three agonists (17β-estradiol, estrone and diethylstilbestrol), and three antagonists (tamoxifen, afimoxifene and endoxifen) into the obtained structure. Based on the ligand-docked scoring functions, we identified three putative estrogen- and antiestrogen-binding sites with different ligand binding affinities. Two high-affinity binding sites were located (i) in a tunnel formed within HAFP subdomains IB and IIA and (ii) on the opposite side of the molecule in a groove originating from a cavity formed between domains I and III, while (iii) the third low-affinity binding site was found at the bottom of the cavity. Here, 100 ns molecular dynamics (MD) simulation allowed us to study their geometries and showed that HAFP–estrogen interactions were caused by van der Waals forces, while both hydrophobic and electrostatic interactions were almost equally involved in HAFP–antiestrogen binding. Molecular mechanics/Generalized Born surface area (MM/GBSA) rescoring method exploited for estimation of binding free energies (ΔGbind) showed that antiestrogens have higher affinities to HAFP as compared to estrogens. We performed in silico point substitutions of amino acid residues to confirm their roles in HAFP–ligand interactions and showed that Thr132, Leu138, His170, Phe172, Ser217, Gln221, His266, His316, Lys453, and Asp478 residues, along with two disulfide bonds (Cys224–Cys270 and Cys269–Cys277), have key roles in both HAFP–estrogen and HAFP–antiestrogen binding. Data obtained in our study contribute to understanding mechanisms underlying protein–ligand interactions and anticancer therapy strategies based on ERα-binding ligands. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics)
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12 pages, 3073 KiB  
Article
Practical Guidance in Genome-Wide RNA:DNA Triple Helix Prediction
by Elena Matveishina, Ivan Antonov and Yulia A. Medvedeva
Int. J. Mol. Sci. 2020, 21(3), 830; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21030830 - 28 Jan 2020
Cited by 14 | Viewed by 3234
Abstract
Long noncoding RNAs (lncRNAs) play a key role in many cellular processes including chromatin regulation. To modify chromatin, lncRNAs often interact with DNA in a sequence-specific manner forming RNA:DNA triple helices. Computational tools for triple helix search do not always provide genome-wide predictions [...] Read more.
Long noncoding RNAs (lncRNAs) play a key role in many cellular processes including chromatin regulation. To modify chromatin, lncRNAs often interact with DNA in a sequence-specific manner forming RNA:DNA triple helices. Computational tools for triple helix search do not always provide genome-wide predictions of sufficient quality. Here, we used four human lncRNAs (MEG3, DACOR1, TERC and HOTAIR) and their experimentally determined binding regions for evaluating triplex parameters that provide the highest prediction accuracy. Additionally, we combined triplex prediction with the lncRNA secondary structure and demonstrated that considering only single-stranded fragments of lncRNA can further improve DNA-RNA triplexes prediction. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics)
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13 pages, 1877 KiB  
Article
A Computational Approach for the Prediction of Treatment History and the Effectiveness or Failure of Antiretroviral Therapy
by Olga Tarasova, Nadezhda Biziukova, Dmitry Kireev, Alexey Lagunin, Sergey Ivanov, Dmitry Filimonov and Vladimir Poroikov
Int. J. Mol. Sci. 2020, 21(3), 748; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21030748 - 23 Jan 2020
Cited by 12 | Viewed by 2788
Abstract
Human Immunodeficiency Virus Type 1 (HIV-1) infection is associated with high mortality if no therapy is provided. Currently, the treatment of an HIV-1 positive patient requires that several drugs should be taken simultaneously. The resistance of the virus to an antiretroviral drug may [...] Read more.
Human Immunodeficiency Virus Type 1 (HIV-1) infection is associated with high mortality if no therapy is provided. Currently, the treatment of an HIV-1 positive patient requires that several drugs should be taken simultaneously. The resistance of the virus to an antiretroviral drug may lead to treatment failure. Our approach focuses on predicting the exposure of a particular viral variant to an antiretroviral drug or drug combination. It also aims at the prediction of drug treatment success or failure. We utilized nucleotide sequences of HIV-1 encoding protease and reverse transcriptase to perform such types of prediction. The PASS (Prediction of Activity Spectra for Substances) algorithm based on the naive Bayesian classifier was used to make a prediction. We calculated the probability of whether a sequence belonged (P1) or did not belong (P0) to the class associated with exposure of the viral sequence to the set of drugs that can be associated with resistance to the set of drugs. The accuracy calculated as the average Area Under the ROC (Receiver Operating Characteristic) Curve (AUC/ROC) for classifying exposure of the sequence to the HIV-1 protease inhibitors was 0.81 (±0.07), and for HIV-1 reverse transcriptase, it was 0.83 (±0.07). To predict cases of treatment effectiveness or failure, we used P1 and P0 values, obtained in PASS, along with the binary vector constructed based on short nucleotide descriptors and the applied random forest classifier. Average AUC/ROC prediction accuracy for the prediction of treatment effectiveness or failure for the combinations of HIV-1 protease inhibitors was 0.82 (±0.06) and of HIV-1 reverse transcriptase was 0.76 (±0.09). Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics)
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20 pages, 2124 KiB  
Article
Flexible Data Trimming Improves Performance of Global Machine Learning Methods in Omics-Based Personalized Oncology
by Victor Tkachev, Maxim Sorokin, Constantin Borisov, Andrew Garazha, Anton Buzdin and Nicolas Borisov
Int. J. Mol. Sci. 2020, 21(3), 713; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21030713 - 22 Jan 2020
Cited by 18 | Viewed by 3203
Abstract
(1) Background: Machine learning (ML) methods are rarely used for an omics-based prescription of cancer drugs, due to shortage of case histories with clinical outcome supplemented by high-throughput molecular data. This causes overtraining and high vulnerability of most ML methods. Recently, we proposed [...] Read more.
(1) Background: Machine learning (ML) methods are rarely used for an omics-based prescription of cancer drugs, due to shortage of case histories with clinical outcome supplemented by high-throughput molecular data. This causes overtraining and high vulnerability of most ML methods. Recently, we proposed a hybrid global-local approach to ML termed floating window projective separator (FloWPS) that avoids extrapolation in the feature space. Its core property is data trimming, i.e., sample-specific removal of irrelevant features. (2) Methods: Here, we applied FloWPS to seven popular ML methods, including linear SVM, k nearest neighbors (kNN), random forest (RF), Tikhonov (ridge) regression (RR), binomial naïve Bayes (BNB), adaptive boosting (ADA) and multi-layer perceptron (MLP). (3) Results: We performed computational experiments for 21 high throughput gene expression datasets (41–235 samples per dataset) totally representing 1778 cancer patients with known responses on chemotherapy treatments. FloWPS essentially improved the classifier quality for all global ML methods (SVM, RF, BNB, ADA, MLP), where the area under the receiver-operator curve (ROC AUC) for the treatment response classifiers increased from 0.61–0.88 range to 0.70–0.94. We tested FloWPS-empowered methods for overtraining by interrogating the importance of different features for different ML methods in the same model datasets. (4) Conclusions: We showed that FloWPS increases the correlation of feature importance between the different ML methods, which indicates its robustness to overtraining. For all the datasets tested, the best performance of FloWPS data trimming was observed for the BNB method, which can be valuable for further building of ML classifiers in personalized oncology. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics)
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16 pages, 613 KiB  
Article
Epidemiology of Hereditary Diseases in the Karachay-Cherkess Republic
by Rena A. Zinchenko, Amin Kh. Makaov, Andrey V. Marakhonov, Varvara A. Galkina, Vitaly V. Kadyshev, Galina I. El’chinova, Elena L. Dadali, Lyudmila K. Mikhailova, Nika V. Petrova, Nina E. Petrina, Tatyana A. Vasilyeva, Polina Gundorova, Alexander V. Polyakov, Oksana Y. Alexandrova, Sergey I. Kutsev and Eugeny K. Ginter
Int. J. Mol. Sci. 2020, 21(1), 325; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21010325 - 03 Jan 2020
Cited by 15 | Viewed by 3020
Abstract
Prevalence and allelic heterogeneity of hereditary diseases (HDs) could vary significantly in different human populations. Current knowledge of HDs distribution in populations is generally limited to either European data or analyses of isolated populations which were performed several decades ago. Thus, an acknowledgement [...] Read more.
Prevalence and allelic heterogeneity of hereditary diseases (HDs) could vary significantly in different human populations. Current knowledge of HDs distribution in populations is generally limited to either European data or analyses of isolated populations which were performed several decades ago. Thus, an acknowledgement of the HDs prevalence in different modern open populations is important. The study presents the results of a genetic epidemiological study of hereditary diseases (HDs) in the population of the Karachay-Cherkess Republic (KChR). Clinical screening of a population of 410,367 people for the identification of HDs was conducted. The population surveyed is represented by five major ethnic groups—Karachays, Russians, Circassians, Abazins, Nogais. The study of the populations was carried out in accordance with the proprietary protocol of genetic epidemiological examination designed to identify >3500 HDs easily diagnosed during clinical examination by qualified specialists specializing in the HDs. The protocol consists of the population genetic and medical genetic sections and is intended for comprehensive population analysis based on the data on different genetic systems, including the genes of HDs, DNA polymorphisms, demographic data collected during hospital-based survey. 8950 families (with 10,125 patients) with presumably the HDs were initially identified as a result of the survey and data collection through various sources of registration (from 1156 medical workers from 163 medical institutions). A diagnosis of hereditary pathology was established in 1849 patients (from 1295 families). Two hundred and thirty nosological forms were revealed (in 1857 patients from 1295 families). The total prevalence of HDs was 1:221. Differences between populations and ethnic groups were identified: 1:350 in Russians, 1:195 in Karachays, 1:199 in Circassians, 1:218 in Abazins, 1:135 in Nogais. Frequent diseases were determined, the presence of marked genetic heterogeneity was identified during the confirmatory DNA diagnosis. To explain the reasons for the differentiation of populations by load of HD, a correlation analysis was carried out between the FST (random inbreeding) in populations and HDs load values. This analysis showed genetic drift is probably one of the leading factors determining the differentiation of KChR populations by HDs load. For the first time, the size of the load and spectrum of HDs in the populations of the KChR are determined. We have demonstrated genetic drift to be one of the main factors of the population dynamics in studied population. A significant genetic heterogeneity of HDs, both allelic and locus, was revealed in KChR. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics)
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12 pages, 1828 KiB  
Article
The Human Isoform of RNA Polymerase II Subunit hRPB11bα Specifically Interacts with Transcription Factor ATF4
by Sergey A. Proshkin, Elena K. Shematorova and George V. Shpakovski
Int. J. Mol. Sci. 2020, 21(1), 135; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21010135 - 24 Dec 2019
Cited by 6 | Viewed by 3169
Abstract
Rpb11 subunit of RNA polymerase II of Eukaryotes is related to N-terminal domain of eubacterial α subunit and forms a complex with Rpb3 subunit analogous to prokaryotic α2 homodimer, which is involved in RNA polymerase assembly and promoter recognition. In humans, a [...] Read more.
Rpb11 subunit of RNA polymerase II of Eukaryotes is related to N-terminal domain of eubacterial α subunit and forms a complex with Rpb3 subunit analogous to prokaryotic α2 homodimer, which is involved in RNA polymerase assembly and promoter recognition. In humans, a POLR2J gene family has been identified that potentially encodes several hRPB11 proteins differing mainly in their short C-terminal regions. The functions of the different human specific isoforms are still mainly unknown. To further characterize the minor human specific isoform of RNA polymerase II subunit hRPB11bα, the only one from hRPB11 (POLR2J) homologues that can replace its yeast counterpart in vivo, we used it as bait in a yeast two-hybrid screening of a human fetal brain cDNA library. By this analysis and subsequent co-purification assay in vitro, we identified transcription factor ATF4 as a prominent partner of the minor RNA polymerase II (RNAP II) subunit hRPB11bα. We demonstrated that the hRPB11bα interacts with leucine b-Zip domain located on the C-terminal part of ATF4. Overexpression of ATF4 activated the reporter more than 10-fold whereas co-transfection of hRPB11bα resulted in a 2.5-fold enhancement of ATF4 activation. Our data indicate that the mode of interaction of human RNAP II main (containing major for of hRPB11 subunit) and minor (containing hRPB11bα isoform of POLR2J subunit) transcription enzymes with ATF4 is certainly different in the two complexes involving hRPB3–ATF4 (not hRPB11a–ATF4) and hRpb11bα–ATF4 platforms in the first and the second case, respectively. The interaction of hRPB11bα and ATF4 appears to be necessary for the activation of RNA polymerase II containing the minor isoform of the hRPB11 subunit (POLR2J) on gene promoters regulated by this transcription factor. ATF4 activates transcription by directly contacting RNA polymerase II in the region of the heterodimer of α-like subunits (Rpb3–Rpb11) without involving a Mediator, which provides fast and highly effective activation of transcription of the desired genes. In RNA polymerase II of Homo sapiens that contains plural isoforms of the subunit hRPB11 (POLR2J), the strength of the hRPB11–ATF4 interaction appeared to be isoform-specific, providing the first functional distinction between the previously discovered human forms of the Rpb11 subunit. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics)
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11 pages, 1146 KiB  
Article
Prediction of Protein–Ligand Interaction Based on the Positional Similarity Scores Derived from Amino Acid Sequences
by Dmitry Karasev, Boris Sobolev, Alexey Lagunin, Dmitry Filimonov and Vladimir Poroikov
Int. J. Mol. Sci. 2020, 21(1), 24; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21010024 - 18 Dec 2019
Cited by 10 | Viewed by 2993
Abstract
The affinity of different drug-like ligands to multiple protein targets reflects general chemical–biological interactions. Computational methods estimating such interactions analyze the available information about the structure of the targets, ligands, or both. Prediction of protein–ligand interactions based on pairwise sequence alignment provides reasonable [...] Read more.
The affinity of different drug-like ligands to multiple protein targets reflects general chemical–biological interactions. Computational methods estimating such interactions analyze the available information about the structure of the targets, ligands, or both. Prediction of protein–ligand interactions based on pairwise sequence alignment provides reasonable accuracy if the ligands’ specificity well coincides with the phylogenic taxonomy of the proteins. Methods using multiple alignment require an accurate match of functionally significant residues. Such conditions may not be met in the case of diverged protein families. To overcome these limitations, we propose an approach based on the analysis of local sequence similarity within the set of analyzed proteins. The positional scores, calculated by sequence fragment comparisons, are used as input data for the Bayesian classifier. Our approach provides a prediction accuracy comparable or exceeding those of other methods. It was demonstrated on the popular Gold Standard test sets, presenting different sequence heterogeneity and varying from the group, including different protein families to the more specific groups. A reasonable prediction accuracy was also found for protein kinases, displaying weak relationships between sequence phylogeny and inhibitor specificity. Thus, our method can be applied to the broad area of protein–ligand interactions. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics)
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14 pages, 3330 KiB  
Article
The mTOR Signaling Pathway Activity and Vitamin D Availability Control the Expression of Most Autism Predisposition Genes
by Ekaterina A. Trifonova, Alexandra I. Klimenko, Zakhar S. Mustafin, Sergey A. Lashin and Alex V. Kochetov
Int. J. Mol. Sci. 2019, 20(24), 6332; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms20246332 - 15 Dec 2019
Cited by 22 | Viewed by 5578
Abstract
Autism spectrum disorder (ASD) has a strong and complex genetic component with an estimate of more than 1000 genes implicated cataloged in SFARI (Simon′s Foundation Autism Research Initiative) gene database. A significant part of both syndromic and idiopathic autism cases can be attributed [...] Read more.
Autism spectrum disorder (ASD) has a strong and complex genetic component with an estimate of more than 1000 genes implicated cataloged in SFARI (Simon′s Foundation Autism Research Initiative) gene database. A significant part of both syndromic and idiopathic autism cases can be attributed to disorders caused by the mechanistic target of rapamycin (mTOR)-dependent translation deregulation. We conducted gene-set analyses and revealed that 606 out of 1053 genes (58%) included in the SFARI Gene database and 179 out of 281 genes (64%) included in the first three categories of the database (“high confidence”, “strong candidate”, and “suggestive evidence”) could be attributed to one of the four groups: 1. FMRP (fragile X mental retardation protein) target genes, 2. mTOR signaling network genes, 3. mTOR-modulated genes, 4. vitamin D3 sensitive genes. The additional gene network analysis revealed 43 new genes and 127 new interactions, so in the whole 222 out of 281 (79%) high scored genes from SFARI Gene database were connected with mTOR signaling activity and/or dependent on vitamin D3 availability directly or indirectly. We hypothesized that genetic and/or environment mTOR hyperactivation, including provocation by vitamin D deficiency, might be a common mechanism controlling the expressivity of most autism predisposition genes and even core symptoms of autism. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics)
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18 pages, 1507 KiB  
Article
Y-chromosome and Surname Analyses for Reconstructing Past Population Structures: The Sardinian Population as a Test Case
by Viola Grugni, Alessandro Raveane, Giulia Colombo, Carmen Nici, Francesca Crobu, Linda Ongaro, Vincenza Battaglia, Daria Sanna, Nadia Al-Zahery, Ornella Fiorani, Antonella Lisa, Luca Ferretti, Alessandro Achilli, Anna Olivieri, Paolo Francalacci, Alberto Piazza, Antonio Torroni and Ornella Semino
Int. J. Mol. Sci. 2019, 20(22), 5763; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms20225763 - 16 Nov 2019
Cited by 3 | Viewed by 13168
Abstract
Many anthropological, linguistic, genetic and genomic analyses have been carried out to evaluate the potential impact that evolutionary forces had in shaping the present-day Sardinian gene pool, the main outlier in the genetic landscape of Europe. However, due to the homogenizing effect of [...] Read more.
Many anthropological, linguistic, genetic and genomic analyses have been carried out to evaluate the potential impact that evolutionary forces had in shaping the present-day Sardinian gene pool, the main outlier in the genetic landscape of Europe. However, due to the homogenizing effect of internal movements, which have intensified over the past fifty years, only partial information has been obtained about the main demographic events. To overcome this limitation, we analyzed the male-specific region of the Y chromosome in three population samples obtained by reallocating a large number of Sardinian subjects to the place of origin of their monophyletic surnames, which are paternally transmitted through generations in most of the populations, much like the Y chromosome. Three Y-chromosome founding lineages, G2-L91, I2-M26 and R1b-V88, were identified as strongly contributing to the definition of the outlying position of Sardinians in the European genetic context and marking a significant differentiation within the island. The present distribution of these lineages does not always mirror that detected in ancient DNAs. Our results show that the analysis of the Y-chromosome gene pool coupled with a sampling method based on the origin of the family name, is an efficient approach to unravelling past heterogeneity, often hidden by recent movements, in the gene pool of modern populations. Furthermore, the reconstruction and comparison of past genetic isolates represent a starting point to better assess the genetic information deriving from the increasing number of available ancient DNA samples. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics)
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Review

Jump to: Editorial, Research

16 pages, 1013 KiB  
Review
Current Insights in Elucidation of Possible Molecular Mechanisms of the Juvenile Form of Batten Disease
by Elena K. Shematorova and George V. Shpakovski
Int. J. Mol. Sci. 2020, 21(21), 8055; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21218055 - 29 Oct 2020
Cited by 5 | Viewed by 3670
Abstract
The neuronal ceroid lipofuscinoses (NCLs) collectively constitute one of the most common forms of inherited childhood-onset neurodegenerative disorders. They form a heterogeneous group of incurable lysosomal storage diseases that lead to blindness, motor deterioration, epilepsy, and dementia. Traditionally the NCL diseases were classified [...] Read more.
The neuronal ceroid lipofuscinoses (NCLs) collectively constitute one of the most common forms of inherited childhood-onset neurodegenerative disorders. They form a heterogeneous group of incurable lysosomal storage diseases that lead to blindness, motor deterioration, epilepsy, and dementia. Traditionally the NCL diseases were classified according to the age of disease onset (infantile, late-infantile, juvenile, and adult forms), with at least 13 different NCL varieties having been described at present. The current review focuses on classic juvenile NCL (JNCL) or the so-called Batten (Batten-Spielmeyer-Vogt; Spielmeyer-Sjogren) disease, which represents the most common and the most studied form of NCL, and is caused by mutations in the CLN3 gene located on human chromosome 16. Most JNCL patients carry the same 1.02-kb deletion in this gene, encoding an unusual transmembrane protein, CLN3, or battenin. Accordingly, the names CLN3-related neuronal ceroid lipofuscinosis or CLN3-disease sometimes have been used for this malady. Despite excessive in vitro and in vivo studies, the precise functions of the CLN3 protein and the JNCL disease mechanisms remain elusive and are the main subject of this review. Although the CLN3 gene is highly conserved in evolution of all mammalian species, detailed analysis of recent genomic and transcriptomic data indicates the presence of human-specific features of its expression, which are also under discussion. The main recorded to date changes in cell metabolism, to some extent contributing to the emergence and progression of JNCL disease, and human-specific molecular features of CLN3 gene expression are summarized and critically discussed with an emphasis on the possible molecular mechanisms of the malady appearance and progression. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics – 2020)
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26 pages, 744 KiB  
Review
Multiple Endocrine Neoplasia Type 1: The Potential Role of microRNAs in the Management of the Syndrome
by Simone Donati, Simone Ciuffi, Francesca Marini, Gaia Palmini, Francesca Miglietta, Cinzia Aurilia and Maria Luisa Brandi
Int. J. Mol. Sci. 2020, 21(20), 7592; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21207592 - 14 Oct 2020
Cited by 9 | Viewed by 2526
Abstract
Multiple endocrine neoplasia type 1 (MEN1) is a rare inherited tumor syndrome, characterized by the development of multiple neuroendocrine tumors (NETs) in a single patient. Major manifestations include primary hyperparathyroidism, gastro-entero-pancreatic neuroendocrine tumors, and pituitary adenomas. In addition to these main NETs, various [...] Read more.
Multiple endocrine neoplasia type 1 (MEN1) is a rare inherited tumor syndrome, characterized by the development of multiple neuroendocrine tumors (NETs) in a single patient. Major manifestations include primary hyperparathyroidism, gastro-entero-pancreatic neuroendocrine tumors, and pituitary adenomas. In addition to these main NETs, various combinations of more than 20 endocrine and non-endocrine tumors have been described in MEN1 patients. Despite advances in diagnostic techniques and treatment options, which are generally similar to those of sporadic tumors, patients with MEN1 have a poor life expectancy, and the need for targeted therapies is strongly felt. MEN1 is caused by germline heterozygous inactivating mutations of the MEN1 gene, which encodes menin, a tumor suppressor protein. The lack of a direct genotype–phenotype correlation does not permit the determination of the exact clinical course of the syndrome. One of the possible causes of this lack of association could be ascribed to epigenetic factors, including microRNAs (miRNAs), single-stranded non-coding small RNAs that negatively regulate post-transcriptional gene expression. Some miRNAs, and their deregulation, have been associated with MEN1 tumorigenesis. Recently, an extracellular class of miRNAs has also been identified (c-miRNAs); variations in their levels showed association with various human diseases, including tumors. The aim of this review is to provide a general overview on the involvement of miRNAs in MEN1 tumor development, to be used as possible targets for novel molecular therapies. The potential role of c-miRNAs as future non-invasive diagnostic and prognostic biomarkers of MEN1 will be discussed as well. Full article
(This article belongs to the Special Issue Medical Genetics, Genomics and Bioinformatics – 2020)
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