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Theodor Sperlea

Theodor Sperlea
Adress:
Leibniz-Institut für Ostseeforschung
Seestrasse 15
18119 Rostock
Telefon:
+49 381 5197 3402
Fax:
+49 381 5197 440
E-Mail:
theonulldor.sperlea@iow.de
ORCID:
0000-0003-4307-2963

Research Interests

  • The biology, ecology and dynamics of microbial communities
  • Machine Learning in high-dimensional biological datasets
  • Microbial and microbiome-based biomonitoring
  • Complexity, chaos and ecological theory

 

Publications

2026

  • Glackin, C.C., Riedinger, D., Zschaubitz, E., Vogel, L., Sperlea, T., Benterbusch, H., Nietz, C., Labrenz, M., AI-driven forecasting of Vibrio vulnificus in the Southern Baltic Sea using high-resolution data. Water Research, doi: 10.1016/j.watres.2026.125647
  • Klett, A., Hassenrück, C., Labrenz, M., Sperlea, T., Liskow, I., & Voss, M. (2026). Benthic Nitrogen Fixation and Primary Production in the Shallow Coastal Zone of the Baltic Sea. Estuaries and Coasts. doi:10.1007/s12237-026-01692-8
  • Sperlea, T., Glackin, C. C., Vogel, L., Zschaubitz, E., Nietz, C., Karsten, S., Dippner, J. W., Elferink, S., Loose, C., Schröder, H., Hassenrück, C., & Labrenz, M. (2026). Semi-Annual Cycles in the Biotic Communities of Temperate Aquatic Habitats. bioRxiv. doi: 10.64898/2026.05.01.721460
  • Kujat, A. S., Hassenrück, C., Lüdtke, S., Labrenz, M., & Sperlea, T. (2026). Enhancing the Understanding of Environmental Microbiomes through Topic Modeling: A Quantitative and Qualitative Analysis. bioRxiv. doi: 10.64898/2026.04.28.721390

2025

  • Sperlea, T., Glackin, C. C., Vogel, L., Zschaubitz, E., Nietz, C., Elferink, S., Loose, C., Schröder, H., Hassenrück, C., & Labrenz, M. (2025). Dynamics of an estuarine biotic community captured in high spatio-temporal resolution using metabarcoding. Scientific Data. doi: 10.1038/s41597-025-06249-1
  • Vogel, L., Sperlea, T., Fisch, K., Glackin, C. C., Zschaubitz, E., Schulz-Bull, D. E., Labrenz, M., & Kanwischer, M. (2025). High-resolution sampling reveals a considerable year-round risk potential for aquatic organisms in an urban estuary of the Baltic Sea due to anthropogenic pollution mixture. Environmental Pollution. doi: 10.1016/j.envpol.2025.126916
  • Zschaubitz, E., Schröder, H., Glackin, C. C., Vogel, L., Labrenz, M., & Sperlea, T. (2025). A benchmark analysis of feature selection and machine learning methods for environmental metabarcoding datasets. Computational and Structural Biotechnology Journal. doi: 10.1016/j.csbj.2025.04.017
  • Jia, X., Schubert, T., Beeloo, R., Litos, A., Doijad, S., van Helvoort, P., Sperlea, T., Labrenz, M., & Dutilh, B. E. (2025). Bacterial community adaptation after freshwater and seawater coalescence. bioRxiv. doi: 10.1101/2025.09.09.675091
  • Sperlea, T., Labrenz, M., Kreikemeyer, B., Schenk, A., & Tagg, A. S. (2025). Predicting Antifouling Paint Particle Contamination based on 16S rRNA Gene Sequencing Data using Random Forest-Based Machine Learning. Openrxiv. doi: 10.1101/2025.09.03.673959
  • Delgado, L. F., Riedinger, D. J., Fernández-Juárez, V., Herlemann, D. P. R., Pansch, C., Kataržytė, M., Gyraitė, G., Reusch, T. B. H., Rakowski, M., Piwosz, K., Woźniczka, A., Benterbusch-Brockmöller, H., Sperlea, T., Dupke, S., Scholz, H. C., Kube, S., Riemann, L., Labrenz, M., & Andersson, A. F. (2025). Phylogeny-aware comparative genomics of Vibrio vulnificus links genetic traits to pathogenicity. bioRxiv. doi: 10.1101/2025.06.02.657354

2024

  • Choisnard, N., T. Sperlea, I. Liskow and M. Voss (2024). Nitrification in the Amazon River plume. Mar. Ecol. Prog. Ser. 730: 1-14, doi: 10.3354/meps14530
  • Riedinger, D. J., Fernández-Juárez, V., Delgado, L. F., Sperlea, T., Hassenrück, C., Herlemann, D. P. R., Pansch, C., Kataržytė, M., Bruck, F., Ahrens, A., Rakowski, M., Piwosz, K., Stevenson, A., Reusch, T. B. H., Gyraitė, G., Schulz-Bull, D., Benterbusch-Brockmöller, H., Kube, S., Dupke, S., Andersson, A. F., Riemann, L. & Labrenz, M. (2024). Control of Vibrio vulnificus proliferation in the Baltic Sea through eutrophication and algal bloom management. Communications Earth & Environment 5:246
  • Tagg, A. S., T. Sperlea, C. Hassenrück, B. Kreikemeyer, D. Fischer and M. Labrenz (2024). Microplastic-antifouling paint particle contamination alters microbial communities in surrounding marine sediment. Sci. Total Environ. 926: 171863, doi:10.1016/j.scitotenv.2024.171863


2022

  • A. S. Tagg, T. Sperlea, M. Labrenz, J. P. Harrison, J. J. Ojeda, M. Sapp (2022). Year-Long Microbial Succession on Microplastics in Wastewater: Chaotic Dynamics Outweigh Preferential Growth. Microorganisms 10(9), 1775; DOI: 10.3390/microorganisms10091775
  • T. Sperlea, D. Heider, G. Hattab (2022). A theoretical basis for bioindication in complex ecosystems. Ecological Indicators 140 (109050); DOI: 10.1016/j.ecolind.2022.109050
  • T. Sperlea, J.P. Schenk, H. Dreßler, D. Beisser, G. Hattab, J. Boenigk, D. Heider (2022). The relationship between land cover and microbial community composition in European lakes. Science of The Total Environment 825 (153732); DOI: 10.1016/j.scitotenv.2022.153732

2021

  • T. Sperlea, N. Kreuder, D. Beisser, G. Hattab, J. Boenigk, D. Heider (2021). Quantification of the covariation of lake microbiomes and environmental variables using a machine learning‐based framework. Molecular Ecology 30 (9), 2131-2144; DOI: 10.1111/mec.15872

2020

  • T. Sperlea, L. Muth, R. Martin, C. Weigel, T. Waldminghaus, D. Heider (2020). gammaBOriS: identification and taxonomic classification of origins of replication in gammaproteobacteria using Motif-based machine learning. Scientific reports 10 (1), 1-9; DOI: 10.1038/s41598-020-63424-7
  • H. F. Löchel, D. Eger, T. Sperlea, Dominik Heider (2020). Deep learning on chaos game representation for proteins. Bioinformatics 36 (1), 272-279; DOI: 10.1093/bioinformatics/btz493
2019
  • T. Richardson, D. Stevens, S. Pelliciari, O. Harran, T. Sperlea, H. Murray (2019). Identification of a basal system for unwinding a bacterial chromosome origin
    The EMBO journal 38 (15), e101649; DOI: 10.15252/embj.2019101649
  • F. S. Kemter, N. Schallopp, T. Sperlea, J. Serrania, P. Sobetzko, G. Fritz, T. Waldminghaus (2019). Stringent response leads to continued cell division and a temporal restart of DNA replication after initial shutdown in Vibrio cholerae. Molecular microbiology 111 (6), 1617-1637; DOI: 10.1111/mmi.14241

2018

  • T. Sperlea, S. Füser, J. Boenigk, D. Heider (2018). SEDE-GPS: socio-economic data enrichment based on GPS information. BMC bioinformatics 19 (15), 73-83; DOI: 10.1186/s12859-018-2419-4
  • N. Schallopp, S. Milbredt, T. Sperlea, F. S. Kemter, M. Bruhn, D. Schindler, T. Waldminghaus (2018) Establishing a system for testing replication inhibition of the Vibrio cholerae secondary chromosome in Escherichia coli. Antibiotics 7 (1), 3; DOI:
    10.3390/antibiotics7010003

2016

  • D. Schindler, S. Milbredt, T. Sperlea, T. Waldminghaus (2016). Design and Assembly of DNA Sequence Libraries for Chromosomal Insertion in Bacteria Based on a Set of Modified MoClo Vectors. ACS synthetic biology 5 (12), 1362-1368; DOI:
    10.1021/acssynbio.6b00089

 

Books

  • T. Sperlea. Multiple Sequence Alignments: Which Program Fits My Data? Springer Berlin Heidelberg, 2022; ISBN: 978-3-662-64472-0

  • T. Sperlea. Multiple Sequenzalignments: Welches Programm passt zu meinen Daten? Springer Spektrum, 2019; ISBN: 978-3-662-58811-6

Arbeitsgruppe

 

Projekt