SP 7: Molecular Genetic, Metagenomic and Bioinformatic Studies on Endometrium and Placenta
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Research questions, aims
The aim is to improve understanding of misconduction of non-coding genes and metagenomics in infertile women. We will study the molecular genetic differences between infertile and fertile women before pregnancy, in the first trimester and at term. The study will be conducted basically bioinformatically by transcriptomic analyses of the endometrium, decidua and placenta. It will focus especially on non-coding RNAs next to protein-coding transcripts. Furthermore, we will study the metagenomic composition of viruses and bacteria (cooperating with subprogram 2) in the uterus and their differences in infertile and fertile women.
Scientific Background
Less than 3% of the human genome encodes for proteins. Non-(protein-)coding RNAs (ncRNAs) are known to regulate any molecular processes in the cell. However, they are studied only rarely in detail. In the context of placenta several ncRNAs, especially miRNAs and lncRNAs have been described (1). Surprisingly, beside miRNAs, almost no ncRNAs have been identified to play a role in endometrium. During the last two years only, several studies showed the influence of the endometrial microbiome to female infertility (3, 4). The precise components of the microbiome leading to infertility are unknown yet.
Own preceding work
The Marz group has a long-standing expertise in computational discovery and description of ncRNAs in human (1, 2, 5-8). Thereby, the prediction of secondary structures of ncRNAs are essential for better understanding of their functional role (9, 10) and interaction with proteins (11, 12). In the context of placenta we have described miRNAs and other ncRNAs to play a role in pregnancy (1, 2). During the last five years, the description of the microbiome with a special focus on usually neglected viruses, has been the major focus of the Marz group (13-18). Prof. Marz is the director of the European Virus Bioinformatics Center and in the SAB of the Rfam database for ncRNAs.
Method spectrum, involvement of the Medical Scientist
The Medical Scientist will be introduced in all basic bioinformatic analyses necessary for the comparison of transcriptomic samples from two different cohorts. This includes sample preparation, sequencing, raw read analysis, assembly, and differential expression analysis. Depending on the results, the Medical Scientist is offered to additionally study SNP analysis, RNA secondary structure analysis and isoform description. All tools will be introduced via the bioinformatics core facility at the FSU, which provides support and training to students. The sequencing can be performed by the Medical Scientist on the Illumina or ONT platform. For the metagenomic analysis the Medical Scientist will be trained on classification of reads, meta-assembly and analysis and comparison of bacteria. A special focus will lay in the comparison of viruses in the endometrium. In close cooperation with the Germany-wide “NFDI4microbiota” network, novel virus data from samples from all over Germany can be used for the analysis. The Medical Scientist can become a member of the European Virus Bioinformatics Center, which makes novel recently developed tools directly accesible for studying viruses from metagenomes.
Relevance for CEPRE and for Reproductive Health
This sub-program will contribute with high-end molecular genetic, transgenomic and bioinformatic approaches to the identification of novel, thus far in reproductive science widely neglected factors, to discriminate fertile and infertile women with future perspectives for new strategies in diagnostics and treatment. Additionally, a bioinformatical service will be provided to the CEPRE consortium.
References
1. Zarkovic M, Hufsky F, Markert UR, Marz M. The Role of Non-Coding RNAs in the Human Placenta. Cells. 2022;11(9).
2. Morales-Prieto DM, Barth E, Murrieta-Coxca JM, Favaro RR, Gutierrez-Samudio RN, Chaiwangyen W, Ospina-Prieto S, Gruhn B, Schleussner E, Marz M, Markert UR. Identification of miRNAs and associated pathways regulated by Leukemia Inhibitory Factor in trophoblastic cell lines. Placenta. 2019;88:20-7.
3. Vanstokstraeten R, Mackens S, Callewaert E, Blotwijk S, Emmerechts K, Crombe F, Soetens O, Wybo I, Vandoorslaer K, Mostert L, De Geyter D, Muyldermans A, Blockeel C, Pierard D, Demuyser T. Culturomics to Investigate the Endometrial Microbiome: Proof-of-Concept. Int J Mol Sci. 2022;23(20).
4. Sirota I, Zarek SM, Segars JH. Potential influence of the microbiome on infertility and assisted reproductive technology. Semin Reprod Med. 2014;32(1):35-42.
5. Marz M, Stadler PF. Comparative analysis of eukaryotic U3 snoRNA. RNA Biol. 2009;6(5):503-7.
6. Marz M, Ferracin M, Klein C. MicroRNAs as biomarker of Parkinson disease? Small but mighty. Neurology. 2015;84(7):636-8.
7. Marz M, Mosig A, Stadler BM, Stadler PF. U7 snRNAs: a computational survey. Genomics Proteomics Bioinformatics. 2007;5(3-4):187-95.
8. Gerresheim GK, Dunnes N, Nieder-Rohrmann A, Shalamova LA, Fricke M, Hofacker I, Honer Zu Siederdissen C, Marz M, Niepmann M. microRNA-122 target sites in the hepatitis C virus RNA NS5B coding region and 3' untranslated region: function in replication and influence of RNA secondary structure. Cell Mol Life Sci. 2017;74(4):747-60.
9. Marz M, Stadler PF. RNA interactions. Adv Exp Med Biol. 2011;722:20-38.
10. Li AX, Marz M, Qin J, Reidys CM. RNA-RNA interaction prediction based on multiple sequence alignments. Bioinformatics. 2011;27(4):456-63.
11. Gruber AR, Koper-Emde D, Marz M, Tafer H, Bernhart S, Obernosterer G, Mosig A, Hofacker IL, Stadler PF, Benecke BJ. Invertebrate 7SK snRNAs. J Mol Evol. 2008;66(2):107-15.
12. Marz M, Donath A, Verstraete N, Nguyen VT, Stadler PF, Bensaude O. Evolution of 7SK RNA and its protein partners in metazoa. Mol Biol Evol. 2009;26(12):2821-30.
13. Kalvari I, Nawrocki EP, Ontiveros-Palacios N, Argasinska J, Lamkiewicz K, Marz M, Griffiths-Jones S, Toffano-Nioche C, Gautheret D, Weinberg Z, Rivas E, Eddy SR, Finn RD, Bateman A, Petrov AI. Rfam 14: expanded coverage of metagenomic, viral and microRNA families. Nucleic Acids Res. 2021;49(D1):D192-D200.
14. Chaudhari NM, Overholt WA, Figueroa-Gonzalez PA, Taubert M, Bornemann TLV, Probst AJ, Holzer M, Marz M, Kusel K. The economical lifestyle of CPR bacteria in groundwater allows little preference for environmental drivers. Environ Microbiome. 2021;16(1):24.
15. Kallies R, Holzer M, Brizola Toscan R, Nunes da Rocha U, Anders J, Marz M, Chatzinotas A. Evaluation of Sequencing Library Preparation Protocols for Viral Metagenomic Analysis from Pristine Aquifer Groundwaters. Viruses. 2019;11(6).
16. Overholt WA, Holzer M, Geesink P, Diezel C, Marz M, Kusel K. Inclusion of Oxford Nanopore long reads improves all microbial and viral metagenome-assembled genomes from a complex aquifer system. Environ Microbiol. 2020;22(9):4000-13.
17. Salem H, Bauer E, Strauss AS, Vogel H, Marz M, Kaltenpoth M. Vitamin supplementation by gut symbionts ensures metabolic homeostasis in an insect host. Proc Biol Sci. 2014;281(1796):20141838.
18. Bauer E, Salem H, Marz M, Vogel H, Kaltenpoth M. Transcriptomic immune response of the cotton stainer Dysdercus fasciatus to experimental elimination of vitamin-supplementing intestinal symbionts. Plos One. 2014;9(12):e114865.