Wolfgang Schmidt-Heck

Recombinant Laminins Drive the Differentiation and Self-Organization of hESC-Derived Hepatocytes

Summary Stem cell-derived somatic cells represent an unlimited resource for basic and translational science. Although promising, there are significant hurdles that must be overcome. Our focus is on the generation of the major cell type of the human liver, the hepatocyte. Current protocols produce variable populations of hepatocytes that are the product of using undefined components in the differentiation process. This serves as a significant barrier to scale-up and application. To tackle this issue, we designed a defined differentiation process using recombinant laminin substrates to provide instruction. We demonstrate efficient hepatocyte specification, cell organization, and significant improvements in cell function and phenotype. This is driven in part by the suppression of unfavorable gene regulatory networks that control cell proliferation and migration, pluripotent stem cell self-renewal, and fibroblast and colon specification. We believe that this represents a significant advance, moving stem cell-based hepatocytes closer toward biomedical application.

Transcription factors ETF, E2F, and SP-1 are involved in cytokine-independent proliferation of murine hepatocytes.

The cellular basis of liver regeneration has been intensely investigated for many years. However, the mechanisms initiating hepatocyte “plasticity” and priming for proliferation are not yet fully clear. We investigated alterations in gene expression patterns during the first 72 hours of C57BL/6N mouse hepatocyte culture on collagen monolayers (CM), which display a high basal frequency of proliferation in the absence of cytokines. Although many metabolic genes were down‐regulated, genes related to mitogen‐activated protein kinase (MAPK) signaling and cell cycle were up‐regulated. The latter genes showed an overrepresentation of transcription factor binding sites (TFBS) for ETF (TEA domain family member 2), E2F1 (E2F transcription factor 1), and SP‐1 (Sp1 transcription factor) (P < 0.001), all depending on MAPK signaling. Time‐dependent increase of ERK1/2 phosphorylation occurred during the first 48 hours (and beyond) in the absence of cytokines, accompanied by an enhanced bromodeoxyuridine labeling index of 20%. The MEK inhibitor PD98059 blunted these effects indicating MAPK signaling as major trigger for this cytokine‐independent proliferative response. In line with these in vitro findings, liver tissue of mice challenged with CCl4 displayed hepatocytes with intense p‐ERK1/2 staining and nuclear SP‐1 and E2F1 expression. Furthermore, differentially expressed genes in mice after partial hepatectomy contained overrepresented TFBS for ETF, E2F1, and SP‐1 and displayed increased expression of E2F1. Conclusion: Cultivation of murine hepatocytes on CM primes cells for proliferation through cytokine‐independent activation of MAPK signaling. The transcription factors ETF, E2F1, and SP‐1 seem to play a pronounced role in mediating proliferation‐dependent differential gene expression. Similar events, but on a shorter time‐scale, occur very early after liver damage in vivo. (HEPATOLOGY 2010;.)

Monitoring of transcriptome and proteome profiles to investigate the cellular response of E. coli towards recombinant protein expression under defined chemostat conditions

The use of strong promoter systems for recombinant protein production generates high product yields, but also overburdens the host cell metabolism and compromises production. Escherichia coli has highly developed regulatory pathways that are immediately responsive to adverse conditions. To gain insight into stress response mechanisms and to detect marker genes and proteins for stress specific monitoring time course analysis of controlled chemostat cultivations was performed using E. coli total microarray and difference gel electrophoresis (Ettan DIGE). In order to detect differences and consistencies of stress response as well as the impact of the inducer isopropyl-beta-d-thiogalactopyranosid on cells, expression of two recombinant proteins (hSOD and GFPmut3.1) was investigated. Genes involved in aerobic metabolism under control of the ArcB/ArcA two component system were found to be down-regulated, and the interplay of the psp operon, ArcA system and guanosine tetraphosphate is suggested to be involved in stress regulatory mechanisms. A distinct impact of the two recombinant proteins was observed, particularly on levels of known stress regulatory genes and proteins, as well as on the response associated with ArcA and psp. Altogether, 62 genes as well as seven proteins showed consistent expression levels due to recombinant gene expression, and are therefore suggested to be appropriate monitoring targets.

More than just a metabolic regulator - elucidation and validation of new targets of PdhR in Escherichia coli

BackgroundThe pyruvate dehydrogenase regulator protein (PdhR) of Escherichia coli acts as a transcriptional regulator in a pyruvate dependent manner to control central metabolic fluxes. However, the complete PdhR regulon has not yet been uncovered. To achieve an extended understanding of its gene regulatory network, we combined large-scale network inference and experimental verification of results obtained by a systems biology approach.Results22 new genes contained in two operons controlled by PdhR (previously only 20 regulatory targets in eight operons were known) were identified by analysing a large-scale dataset of E. coli from the Many Microbes Microarray Database and novel expression data from a pdhR knockout strain, as well as a PdhR overproducing strain. We identified a regulation of the glycolate utilization operon glcDEFGBA using chromatin immunoprecipitation and gel shift assays. We show that this regulation could be part of a cross-induction between genes necessary for acetate and pyruvate utilisation controlled through PdhR. Moreover, a link of PdhR regulation to the replication machinery of the cell via control of the transcription of the dcw-cluster was verified in experiments. This augments our knowledge of the functions of the PdhR-regulon and demonstrates its central importance for further cellular processes in E. coli.ConclusionsWe extended the PdhR regulon by 22 new genes contained in two operons and validated the regulation of the glcDEFGBA operon for glycolate utilisation and the dcw-cluster for cell division proteins experimentally. Our results provide, for the first time, a plausible regulatory link between the nutritional status of the cell and cell replication mediated by PdhR.

Hepatic Hedgehog signaling contributes to the regulation of IGF1 and IGFBP1 serum levels

BackgroundHedgehog signaling plays an important role in embryonic development, organogenesis and cancer. In the adult liver, Hedgehog signaling in non-parenchymal cells has been found to play a role in certain disease states such as fibrosis and cirrhosis. However, whether the Hedgehog pathway is active in mature healthy hepatocytes and is of significance to liver function are controversial.FindingsTwo types of mice with distinct conditional hepatic deletion of the Smoothened gene, an essential co-receptor protein of the Hedgehog pathway, were generated for investigating the role of Hedgehog signaling in mature hepatocytes. The knockout animals (KO) were inconspicuous and healthy with no changes in serum transaminases, but showed a slower weight gain. The liver was smaller, but presented a normal architecture and cellular composition. By quantitative RT-PCR the downregulation of the expression of Indian hedgehog (Ihh) and the Gli3 transcription factor could be demonstrated in healthy mature hepatocytes from these mice, whereas Patched1 was upregulated. Strong alterations in gene expression were also observed for the IGF axis. While expression of Igf1 was downregulated, that of Igfbp1 was upregulated in the livers of both genders. Corresponding changes in the serum levels of both proteins could be detected by ELISA. By activating and inhibiting the transcriptional output of Hedgehog signaling in cultured hepatocytes through siRNAs against Ptch1 and Gli3, respectively, in combination with a ChIP assay evidence was collected indicating that Igf1 expression is directly dependent on the activator function of Gli3. In contrast, the mRNA level of Igfbp1 appears to be controlled through the repressor function of Gli3, while that of Igfbp2 and Igfbp3 did not change. Interestingly, body weight of the transgenic mice correlated well with IGF-I levels in both genders and also with IGFBP-1 levels in females, whereas it did not correlate with serum growth hormone levels.ConclusionsOur results demonstrate for the first time that Hedgehog signaling is active in healthy mature mouse hepatocytes and that it has considerable importance for IGF-I homeostasis in the circulation. These findings may have various implications for mouse physiology including the regulation of body weight and size, glucose homeostasis and reproductive capacity.

Identification of hypoxia-inducible target genes of Aspergillus fumigatus by transcriptome analysis reveals cellular respiration as an important contributor to hypoxic survival.

ABSTRACT Aspergillus fumigatus is an opportunistic, airborne pathogen that causes invasive aspergillosis in immunocompromised patients. During the infection process, A. fumigatus is challenged by hypoxic microenvironments occurring in inflammatory, necrotic tissue. To gain further insights into the adaptation mechanism, A. fumigatus was cultivated in an oxygen-controlled chemostat under hypoxic and normoxic conditions. Transcriptome analysis revealed a significant increase in transcripts associated with cell wall polysaccharide metabolism, amino acid and metal ion transport, nitrogen metabolism, and glycolysis. A concomitant reduction in transcript levels was observed with cellular trafficking and G-protein-coupled signaling. To learn more about the functional roles of hypoxia-induced transcripts, we deleted A. fumigatus genes putatively involved in reactive nitrogen species detoxification (fhpA), NAD+ regeneration (frdA and osmA), nitrogen metabolism (niaD and niiA), and respiration (rcfB). We show that the nitric oxygen (NO)-detoxifying flavohemoprotein gene fhpA is strongly induced by hypoxia independent of the nitrogen source but is dispensable for hypoxic survival. By deleting the nitrate reductase gene niaD, the nitrite reductase gene niiA, and the two fumarate reductase genes frdA and osmA, we found that alternative electron acceptors, such as nitrate and fumarate, do not have a significant impact on growth of A. fumigatus during hypoxia, but functional mitochondrial respiratory chain complexes are essential under these conditions. Inhibition studies indicated that primarily complexes III and IV play a crucial role in the hypoxic growth of A. fumigatus.

The extended TILAR approach: a novel tool for dynamic modeling of the transcription factor network regulating the adaption to in vitro cultivation of murine hepatocytes

BackgroundNetwork inference is an important tool to reveal the underlying interactions of biological systems. In the liver, a complex system of transcription factors is active to distribute signals and induce the cellular response following extracellular stimuli. Plenty of information is available about single transcription factors important for the different functions of the liver, but little is known about their causal relations to each other.ResultsGiven a DNA microarray time series dataset of collagen monolayers cultured murine hepatocytes, we identified 22 differentially expressed genes for which the corresponding protein is known to exhibit transcription factor activity. We developed the Extended TILAR (ExTILAR) network inference algorithm based on the modeling concept of the previously published TILAR algorithm. Using ExTILAR, we inferred a transcription factor network based on gene expression data which puts these important genes into a functional context. This way, we identified a previously unknown relationship between Tgif1 and Atf3 which we validated experimentally. Beside its known role in metabolic processes, this extends the knowledge about Tgif1 in hepatocytes towards a possible influence of processes such as proliferation and cell cycle. Moreover, two positive (i.e. double negative) regulatory loops were predicted that could give rise to bistable behavior. We further evaluated the performance of ExTILAR by systematic inference of an in silico network.ConclusionsWe present the ExTILAR algorithm, which combines the advantages of the regression based inference algorithm TILAR, like large network sizes processable and low computational costs, with the advantages of dynamic network models based on ordinary differential equation (i.e. in silico knock-down simulations). Like TILAR, ExTILAR makes use of various prior-knowledge types such as transcription factor binding site information and gene interaction knowledge to infer biologically meaningful gene regulatory networks. Therefore, ExTILAR is especially useful when a large number of genes is modeled using a small number of experimental data points.

Two compartment model of diazepam biotransformation in an organotypical culture of primary human hepatocytes.

Drug biotransformation is one of the most important parameters of preclinical screening tests for the registration of new drug candidates. Conventional existing tests rely on nonhuman models which deliver an incomplete metabolic profile of drugs due to the lack of proper CYP450 expression as seen in human liver in vivo. In order to overcome this limitation, we used an organotypical model of human primary hepatocytes for the biotransformation of the drug diazepam with special reference to metabolites in both the cell matrix phase and supernatant and its interaction of three inducers (phenobarbital, dexamethasone, aroclor 1254) in different time responses (1, 2, 4, 8, 24 h). Phenobarbital showed the strongest inducing effect in generating desmethyldiazepam and induced up to a 150 fold increase in oxazepam-content which correlates with the increased availability of the precursor metabolites (temazepam and desmethyldiazepam). Aroclor 1254 and dexamethasone had the strongest inducing effect on temazepam and the second strongest on oxazepam. The strong and overlapping inductive role of phenobarbital strengthens the participation of CYP2B6 and CYP3A in diazepam N-demethylation and CYP3A in temazepam formation. Aroclor 1254 preferentially generated temazepam due to the interaction with CYP3A and potentially CYP2C19. In parallel we represented these data in the form of a mathematical model with two compartments explaining the dynamics of diazepam metabolism with the effect of these other inducers in human primary hepatocytes. The model consists of ten differential equations, with one for each concentration c(i,j) (i=diazepam, temazepam, desmethyldiazepam, oxazepam, other metabolites) and one for each compartment (j= cell matrix phase, supernatant), respectively. The parameters p(k) (k=1, 2, 3, 4, 13) are rate constants describing the biotransformation of diazepam and its metabolites and the other parameters (k=5, 6, 7, 8, 9, 10, 11, 12, 14, 15) explain the concentration changes in the two compartments.

Gene Expression Data Mining for Functional Genomics using Fuzzy Technology

Methods for supervised and unsupervised clustering and machine learning were studied in order to automatically model relationships between gene expression data and gene functions of the microorganism Escherichia coli. From a pre-selected subset of 265 genes (belonging to 3 functional groups) the function has been predicted with an accuracy of 63–71 % by various data mining methods described in this paper. Whereas some of these methods, i.e. K-means clustering, Kohonen’s self-organizing maps (SOM), Eisen’s hierarchical clustering and Quinlan’s C4.5 decision tree induction algorithm have been applied to gene expression data analysis in the literature already, the fuzzy approach for gene expression data analysis is introduced by the authors. The fuzzy-C-means algorithm (FCM) and the Gustafson-Kessel algorithm for unsupervised clustering as well as the Adaptive Neuro-Fuzzy Inference System (ANFIS) were successfully applied to the functional classification of E. coli genes.

Transcriptome analysis of cyclic AMP‐dependent protein kinase A–regulated genes reveals the production of the novel natural compound fumipyrrole by Aspergillus fumigatus

Aspergillus fumigatus is an opportunistic human pathogenic fungus causing life‐threatening infections in immunocompromised patients. Adaptation to different habitats and also virulence of the fungus depends on signal perception and transduction by modules such as the cyclic AMP‐dependent protein kinase A (PKA) pathway. Here, by transcriptome analysis, 632 differentially regulated genes of this important signaling cascade were identified, including 23 putative transcriptional regulators. The highest upregulated transcription factor gene was located in a previously unknown secondary metabolite gene cluster, which we named fmp, encoding an incomplete non‐ribosomal peptide synthetase, FmpE. Overexpression of the regulatory gene fmpR using the TetOn system led to the specific expression of the other six genes of the fmp cluster. Metabolic profiling of wild type and fmpR overexpressing strain by HPLC‐DAD and HPLC‐HRESI‐MS and structure elucidation by NMR led to identification of 5‐benzyl‐1H‐pyrrole‐2‐carboxylic acid, which we named fumipyrrole. Fumipyrrole was not described as natural product yet. Chemical synthesis of fumipyrrole confirmed its structure. Interestingly, deletion of fmpR or fmpE led to reduced growth and sporulation of the mutant strains. Although fmp cluster genes were transcribed in infected mouse lungs, deletion of fmpR resulted in wild‐type virulence in a murine infection model.