Publications

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29 Publications visible to you, out of a total of 29

Abstract (Expand)

BACKGROUND: Long-term environmental exposure to metals leads to epigenetic changes and may increase risks to human health. The relationship between the type and level of metal exposure and epigenetic changes in subjects exposed to high concentrations of metals in the environment is not yet clear. The aim of our study is to find the possible association of environmental long-term exposure to metals with DNA methylation changes of genes related to immune response and carcinogenesis. We investigated the association of plasma levels of 21 essential and non-essential metals detected by ICP-MS and the methylation level of 654 CpG sites located on NFKB1, CDKN2A, ESR1, APOA5, IGF2 and H19 genes assessed by targeted bisulfite sequencing in a cohort of 40 subjects living near metal mining area and 40 unexposed subjects. Linear regression was conducted to find differentially methylated positions with adjustment for gender, age, BMI class, smoking and metal concentration. RESULTS: In the metal-exposed group, five CpGs in the NFKB1 promoter region were hypomethylated compared to unexposed group. Four differentially methylated positions (DMPs) were associated with multiple metals, two of them are located on NFKB1 gene, and one each on CDKN2A gene and ESR1 gene. Two DMPs located on NFKB1 (chr4:102500951, associated with Be) and IGF2 (chr11:2134198, associated with U) are associated with specific metal levels. The methylation status of the seven CpGs located on NFKB1 (3), ESR1 (2) and CDKN2A (2) positively correlated with plasma levels of seven metals (As, Sb, Zn, Ni, U, I and Mn). CONCLUSIONS: Our study revealed methylation changes in NFKB1, CDKN2A, IGF2 and ESR1 genes in individuals with long-term human exposure to metals. Further studies are needed to clarify the effect of environmental metal exposure on epigenetic mechanisms and pathways involved.

Authors: A. Stepanyan, A. Petrackova, S. Hakobyan, J. Savara, S. Davitavyan, E. Kriegova, A. Arakelyan

Date Published: 7th Aug 2023

Publication Type: Journal

Abstract (Expand)

The molecular mechanisms of the liver metastasis of colorectal cancer (CRLM) remain poorly understood. Here, we applied machine learning and bioinformatics trajectory inference to analyze a gene expression dataset of CRLM. We studied the co-regulation patterns at the gene level, the potential paths of tumor development, their functional context, and their prognostic relevance. Our analysis confirmed the subtyping of five liver metastasis subtypes (LMS). We provide gene-marker signatures for each LMS, and a comprehensive functional characterization that considers both the hallmarks of cancer and the tumor microenvironment. The ordering of CRLMs along a pseudotime-tree revealed a continuous shift in expression programs, suggesting a developmental relationship between the subtypes. Notably, trajectory inference and personalized analysis discovered a range of epigenetic states that shape and guide metastasis progression. By constructing prognostic maps that divided the expression landscape into regions associated with favorable and unfavorable prognoses, we derived a prognostic expression score. This was associated with critical processes such as epithelial-mesenchymal transition, treatment resistance, and immune evasion. These factors were associated with responses to neoadjuvant treatment and the formation of an immuno-suppressive, mesenchymal state. Our machine learning-based molecular profiling provides an in-depth characterization of CRLM heterogeneity with possible implications for treatment and personalized diagnostics.

Authors: O. Ashekyan, N. Shahbazyan, Y. Bareghamyan, A. Kudryavzeva, D. Mandel, M. Schmidt, H. Loeffler-Wirth, M. Uduman, D. Chand, D. Underwood, G. Armen, A. Arakelyan, L. Nersisyan, H. Binder

Date Published: 28th Jul 2023

Publication Type: Journal

Abstract (Expand)

Regulation of messenger RNA stability is pivotal for programmed gene expression in bacteria and is achieved by a myriad of molecular mechanisms. By bulk sequencing of 5' monophosphorylated mRNA decay intermediates (5'P), we show that cotranslational mRNA degradation is conserved among both Gram-positive and -negative bacteria. We demonstrate that, in species with 5'-3' exonucleases, the exoribonuclease RNase J tracks the trailing ribosome to produce an in vivo single-nucleotide toeprint of the 5' position of the ribosome. In other species lacking 5'-3' exonucleases, ribosome positioning alters endonucleolytic cleavage sites. Using our metadegradome (5'P degradome) sequencing approach, we characterize 5'P mRNA decay intermediates in 96 species including Bacillus subtilis, Escherichia coli, Synechocystis spp. and Prevotella copri and identify codon- and gene-level ribosome stalling responses to stress and drug treatment. We also apply 5'P sequencing to complex clinical and environmental microbiomes and demonstrate that metadegradome sequencing provides fast, species-specific posttranscriptional characterization of responses to drug or environmental perturbations. Finally we produce a degradome atlas for 96 species to enable analysis of mechanisms of RNA degradation in bacteria. Our work paves the way for the application of metadegradome sequencing to investigation of posttranscriptional regulation in unculturable species and complex microbial communities.

Authors: S. Huch, L. Nersisyan, M. Ropat, D. Barrett, M. Wu, J. Wang, V. D. Valeriano, N. Vardazaryan, J. Huerta-Cepas, W. Wei, J. Du, L. M. Steinmetz, L. Engstrand, V. Pelechano

Date Published: 5th Jun 2023

Publication Type: Journal

Abstract (Expand)

We elucidate grapevine evolution and domestication histories with 3525 cultivated and wild accessions worldwide. In the Pleistocene, harsh climate drove the separation of wild grape ecotypes caused by continuous habitat fragmentation. Then, domestication occurred concurrently about 11,000 years ago in Western Asia and the Caucasus to yield table and wine grapevines. The Western Asia domesticates dispersed into Europe with early farmers, introgressed with ancient wild western ecotypes, and subsequently diversified along human migration trails into muscat and unique western wine grape ancestries by the late Neolithic. Analyses of domestication traits also reveal new insights into selection for berry palatability, hermaphroditism, muscat flavor, and berry skin color. These data demonstrate the role of the grapevines in the early inception of agriculture across Eurasia.

Authors: Y. Dong, S. Duan, Q. Xia, Z. Liang, X. Dong, K. Margaryan, M. Musayev, S. Goryslavets, G. Zdunic, P. F. Bert, T. Lacombe, E. Maul, P. Nick, K. Bitskinashvili, G. D. Bisztray, E. Drori, G. De Lorenzis, J. Cunha, C. F. Popescu, R. Arroyo-Garcia, C. Arnold, A. Ergul, Y. Zhu, C. Ma, S. Wang, S. Liu, L. Tang, C. Wang, D. Li, Y. Pan, J. Li, L. Yang, X. Li, G. Xiang, Z. Yang, B. Chen, Z. Dai, Y. Wang, A. Arakelyan, V. Kuliyev, G. Spotar, N. Girollet, S. Delrot, N. Ollat, P. This, C. Marchal, G. Sarah, V. Laucou, R. Bacilieri, F. Rockel, P. Guan, A. Jung, M. Riemann, L. Ujmajuridze, T. Zakalashvili, D. Maghradze, M. Hohn, G. Jahnke, E. Kiss, T. Deak, O. Rahimi, S. Hubner, F. Grassi, F. Mercati, F. Sunseri, J. Eiras-Dias, A. M. Dumitru, D. Carrasco, A. Rodriguez-Izquierdo, G. Munoz, T. Uysal, C. Ozer, K. Kazan, M. Xu, Y. Wang, S. Zhu, J. Lu, M. Zhao, L. Wang, S. Jiu, Y. Zhang, L. Sun, H. Yang, E. Weiss, S. Wang, Y. Zhu, S. Li, J. Sheng, W. Chen

Date Published: 3rd Mar 2023

Publication Type: Journal

Abstract (Expand)

Multi-omics high-throughput technologies produce data sets which are not restricted to only one but consist of multiple omics modalities, often as patient-matched tumour specimens. The integrative analysis of these omics modalities is essential to obtain a holistic view on the otherwise fragmented information hidden in this data. We present an intuitive method enabling the combined analysis of multi-omics data based on self-organizing maps machine learning. It "portrays" the expression, methylation and copy number variations (CNV) landscapes of each tumour using the same gene-centred coordinate system. It enables the visual evaluation and direct comparison of the different omics layers on a personalized basis. We applied this combined molecular portrayal to lower grade gliomas, a heterogeneous brain tumour entity. It classifies into a series of molecular subtypes defined by genetic key lesions, which associate with large-scale effects on DNA methylation and gene expression, and in final consequence, drive with cell fate decisions towards oligodendroglioma-, astrocytoma- and glioblastoma-like cancer cell lineages with different prognoses. Consensus modes of concerted changes of expression, methylation and CNV are governed by the degree of co-regulation within and between the omics layers. The method is not restricted to the triple-omics data used here. The similarity landscapes reflect partly independent effects of genetic lesions and DNA methylation with consequences for cancer hallmark characteristics such as proliferation, inflammation and blocked differentiation in a subtype specific fashion. It can be extended to integrate other omics features such as genetic mutation, protein expression data as well as extracting prognostic markers.

Authors: H. Binder, M. Schmidt, L. Hopp, S. Davitavyan, A. Arakelyan, H. Loeffler-Wirth

Date Published: 4th Jun 2022

Publication Type: Journal

Abstract (Expand)

Mutually linked expression and methylation dynamics in the brain govern genome regulation over the whole lifetime with an impact on cognition, psychological disorders, and cancer. We performed a joint study of gene expression and DNA methylation of brain tissue originating from the human prefrontal cortex of individuals across the lifespan to describe changes in cellular programs and their regulation by epigenetic mechanisms. The analysis considers previous knowledge in terms of functional gene signatures and chromatin states derived from independent studies, aging profiles of a battery of chromatin modifying enzymes, and data of gliomas and neuropsychological disorders for a holistic view on the development and aging of the brain. Expression and methylation changes from babies to elderly adults decompose into different modes associated with the serial activation of (brain) developmental, learning, metabolic and inflammatory functions, where methylation in gene promoters mostly represses transcription. Expression of genes encoding methylome modifying enzymes is very diverse reflecting complex regulations during lifetime which also associates with the marked remodeling of chromatin between permissive and restrictive states. Data of brain cancer and psychotic disorders reveal footprints of pathophysiologies related to brain development and aging. Comparison of aging brains with gliomas supports the view that glioblastoma-like and astrocytoma-like tumors exhibit higher cellular plasticity activated in the developing healthy brain while oligodendrogliomas have a more stable differentiation hierarchy more resembling the aged brain. The balance and specific shifts between volatile and stable and between more irreversible and more plastic epigenomic networks govern the development and aging of healthy and diseased brain.

Authors: H. Loeffler-Wirth, L. Hopp, M. Schmidt, R. Zakharyan, A. Arakelyan, H. Binder

Date Published: 21st Jan 2022

Publication Type: Journal

Abstract (Expand)

organizing maps portraying has been proven to be a powerful approach for analysis of transcriptomic, genomic, epigenetic, single-cell, and pathway-level data as well as for “multi-omic” integrative analyses. However, the SOM method has a major disadvantage: it requires the retraining of the entire dataset once a new sample is added, which can be resource- and time-demanding. It also shifts the gene landscape, thus complicating the interpretation and comparison of results. To overcome this issue, we have developed two approaches of transfer learning that allow for extending SOM space with new samples, meanwhile preserving its intrinsic structure. The extension SOM (exSOM) approach is based on adding secondary data to the existing SOM space by “meta-gene adaptation”, while supervised SOM portrayal (supSOM) adds support vector machine regression model on top of the original SOM algorithm to “predict” the portrait of a new sample. Both methods have been shown to accurately combine existing and new data. With simulated data, exSOM outperforms supSOM for accuracy, while supSOM significantly reduces the computing time and outperforms exSOM for this parameter. Analysis of real datasets demonstrated the validity of the projection methods with independent datasets mapped on existing SOM space. Moreover, both methods well handle the projection of samples with new characteristics that were not present in training datasets.

Authors: Maria Nikoghosyan, Henry Loeffler-Wirth, Suren Davidavyan, Hans Binder, Arsen Arakelyan

Date Published: 27th Dec 2021

Publication Type: Journal

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