Cell therapies based on inducible pluripotent stem cells offer promising new treatments for a variety of different illnesses. However, the sensitivity of stem cells to hydrodynamic stress makes developing reliable stem cell production processes challenging. Understanding hydrodynamic stress conditions experienced by stem cells during early-stage process development is important to guide scale-up and design scale-down experiments. We characterize the hydrodynamic stresses in a 125 mL shake flask using Lattice-Boltzmann implicit large eddy simulations (LB-ILES). First, we validated the LB-ILES shake flask simulations using volumetric power input measurements and experimental liquid distribution data showing good overall agreement, while also numerical challenges of the LB-ILES method regarding grid and time step dependencies are discussed. The mean shear stress in the shake flask increases from 0.01 to 0.24 Pa when increasing the shaking frequency from 55 to 250 rpm, and the mean Kolmogorov length scale decreases from 185 to 51 μm. Furthermore, time-averaged distributions of the shear stress and Kolmogorov length scales were evaluated and compared to reported stress thresholds for stem cells. Based on the shear stress and Kolmogorov length scale distributions, our developed shake flask CFD model can help to design small-scale experiments to characterize stem cell cultures in terms of their hydrodynamic stress tolerance, and ultimately guide scale-up stem cell cultures to larger cultivation systems.@en

The tremendous progress in sequencing technologies has made DNA sequencing routine for microbiome studies. Additionally, advances in mass spectrometric techniques have extended conventional proteomics into the field of microbial ecology. However, systematic studies that provide a better understanding of the complementary nature of these 'omics' approaches, particularly for complex environments such as wastewater treatment sludge, are urgently needed. Here, we describe a comparative metaomics study on aerobic granular sludge from three different wastewater treatment plants. For this, we employed metaproteomics, whole metagenome, and 16S rRNA amplicon sequencing to study the same granule material with uniform size. We furthermore compare the taxonomic profiles using the Genome Taxonomy Database (GTDB) to enhance the comparability between the different approaches. Though the major taxonomies were consistently identified in the different aerobic granular sludge samples, the taxonomic composition obtained by the different omics techniques varied significantly at the lower taxonomic levels, which impacts the interpretation of the nutrient removal processes. Nevertheless, as demonstrated by metaproteomics, the genera that were consistently identified in all techniques cover the majority of the protein biomass. The established metaomics data and the contig classification pipeline are publicly available, which provides a valuable resource for further studies on metabolic processes in aerobic granular sludge.

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