High-Throughput Microorganism Research Accelerated with Bioreactor Systems and Automated RNA-Seq Analysis

Scientists at the Technical University Munich (TU Munich) have successfully developed a powerful strategy to accelerate bioprocess development using parallel bioreactor systems and automated RNA-Seq analysis. Their research, published in the journal Microorganisms, demonstrates the effectiveness of combining liquid handling stations with high-throughput experiments to gain a molecular understanding of microbial production strains. The team's innovative approach allows for rapid identification of differentially expressed genes in response to varying carbon sources, providing valuable insights for bioreactor cultures.

Key Takeaways:

• The research team developed a sample preparation workflow consisting of at-line cell disruption, total RNA extraction, nucleic acid concentration normalization, and Nanopore cDNA Library preparation for automated RNA-Seq experiments.
• The team used a pH-controlled aerobic batch growth of Saccharomyces cerevisiae with six different carbon sources in 24 parallel stirred tank bioreactors integrated into a liquid handling station.
• Off-line Nanopore sequencing yielded 20.97 M classified reads with a Q-score of 9, revealing significant differences in transcriptomic profiles when comparing growth with glucose and pyruvate.
• The study identified 674 downregulated and 709 upregulated genes in response to stress conditions, demonstrating the effectiveness of the developed approach for transcriptomic profiling of bioreactor cultures.
• The researchers concluded that insignificant changes in gene expression patterns were measured when comparing growth with glucose and fructose, yielding only 64 differentially expressed genes.

Statistics:

• 24 parallel stirred tank bioreactors were used in the study.
• 24 cDNA libraries were prepared over 11.5 hours.
• Off-line Nanopore sequencing yielded 20.97 M classified reads.
• 1,383 genes (674 downregulated and 709 upregulated) showed significant changes in expression patterns.
• Research was conducted at the Technical University Munich (TU Munich) by Karlis Blums, Josha Herzog, Jonathan Costa, Lara Quirico, Jonas Turber, and Dirk Weuster-Botz.

Sources:

• Automation of RNA-Seq Sample Preparation and Miniaturized Parallel Bioreactors Enable High-Throughput Differential Gene Expression Studies. Microorganisms, 2025,13(4):849. (Microorganisms - http://www.mdpi.com/journal/microorganisms)
• DOI: https://doi-org.sdpl.idm.oclc.org/10.3390/microorganisms13040849.