In yeast, the protein kinase Gin4 locally controls plasma membrane lipid asymmetry, which is necessary for optimal cytokinesis.

Escherichia coli is able to shift between anaerobic and aerobic metabolism by adapting its gene expression, e.g., of metabolic genes, to the new environment. The dynamics of gene expression that result from environmental shifts are limited, amongst others, by the time needed for regulation and transcription elongation. In this study, we examined gene expression dynamics after an anaerobic-to-aerobic shift on a short time scale (0.5, 1, 2, 5, and 10 min) by RNA sequencing with emphasis on delay times and transcriptional elongation rates (TER). Transient expression patterns and timing of differential expression, characterized by delay and elongation, were identified as key features of the dataset. Gene ontology enrichment analysis revealed early upregulation of respiratory and iron-related gene sets. We inferred specific TERs of 89 operons with a mean TER of 42.0 nt/s and mean delay time of 22.4 s. TERs correlate with sequence features, such as codon bias, whereas delay times correlate with the involvement of regulators. The presented data illustrate that at very short times after a shift in oxygenation, extensional changes of the transcriptome, such as temporary responses, can be observed. Besides regulation, TERs contribute to the dynamics of gene expression.

Hematopoietic stem cells are the stem cells of the blood that are applied to treat hematological disorders by transplanting donor cells to a patient. Rarity of donors and low cell counts in alternative hematopoietic stem cell sources such as cord blood limit the clinical use of hematopoietic stem cells. Here, it is shown that bifunctional surfaces containing the adhesive RGD peptide together with the Notch‐activating Delta‐like 1 (DLL1)—provided in a nanopatterned or unpatterned manner in different densities—are able to enhance hematopoietic stem and progenitor cell proliferation. Nanopatterning allows determining the maximal distance between DLL1 molecules that results in efficient cell stimulation (40 nm). Applying unpatterned substrates with statistically distributed DLL1 shows that the elicited effects depend on ligand density and clustering (minimum 2 molecules/cluster). Thereby, the present study contributes to the development of cost‐efficient bioreactors for hematopoietic stem cell expansion and to deciphering how cells gain control over Notch signaling by DLL1 clustering.

The facultative anaerobic bacterium Escherichia coli is frequently forced to adapt to changing environmental conditions. One important determinant for metabolism is the availability of oxygen allowing a more efficient metabolism. Especially in large scale bioreactors, the distribution of oxygen is inhomogeneous and individual cells encounter frequent changes. This might contribute to observed yield losses during process upscaling. Short-term gene expression data exist of an anaerobic E. coli batch culture shifting to aerobic conditions. The data reveal temporary upregulation of genes that are less efficient in terms of energy conservation than the genes predicted by conventional flux balance analyses. In this study, we provide evidence for a positive correlation between metabolic fluxes and gene expression. We then hypothesize that the more efficient enzymes are limited by their low expression, restricting flux through their reactions. We define a demand that triggers expression of the demanded enzymes that we explicitly include in our model. With these features we propose a method, demand-directed dynamic flux balance analysis, dddFBA, bringing together elements of several previously published methods. The introduction of additional flux constraints proportional to gene expression provoke a temporary demand for less efficient enzymes, which is in agreement with the transient upregulation of these genes observed in the data. In the proposed approach, the applied objective function of growth rate maximization together with the introduced constraints triggers expression of metabolically less efficient genes. This finding is one possible explanation for the yield losses observed in large scale bacterial cultivations where steady oxygen supply cannot be warranted.

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