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Nils Blüthgen

Publications and source records attributed to Nils Blüthgen.

13 recordsLinked to original sources

Measuring specialization in species interaction networks.

BACKGROUND: Network analyses of plant-animal interactions hold valuable biological information. They are often used to quantify the degree of specialization between partners, but usually based on qualitative indices such as 'connectance' or number of links. These measures ignore interaction frequencies or sampling intensity, and strongly depend on network size. RESULTS: Here we introduce two quantitative indices using interaction frequencies to describe the degree of specialization, based on information theory. The first measure (d') describes the degree of interaction specialization at the species level, while the second measure (H2') characterizes the degree of specialization or partitioning among two parties in the entire network. Both indices are mathematically related and derived from Shannon entropy. The species-level index d' can be used to analyze variation within networks, while H2' as a network-level index is useful for comparisons across different interaction webs. Analyses of two published pollinator networks identified differences and features that have not been detected with previous approaches. For instance, plants and pollinators within a network differed in their average degree of specialization (weighted mean d'), and the correlation between specialization of pollinators and their relative abundance also differed between the webs. Rarefied sampling effort in both networks and null model simulations suggest that H2' is not affected by network size or sampling intensity. CONCLUSION: Quantitative analyses reflect properties of interaction networks more appropriately than previous qualitative attempts, and are robust against variation in sampling intensity, network size and symmetry. These measures will improve our understanding of patterns of specialization within and across networks from a broad spectrum of biological interactions.

Adaptation, Physiological↗

Mathematical modeling identifies inhibitors of apoptosis as mediators of positive feedback and bistability.

The intrinsic, or mitochondrial, pathway of caspase activation is essential for apoptosis induction by various stimuli including cytotoxic stress. It depends on the cellular context, whether cytochrome c released from mitochondria induces caspase activation gradually or in an all-or-none fashion, and whether caspase activation irreversibly commits cells to apoptosis. By analyzing a quantitative kinetic model, we show that inhibition of caspase-3 (Casp3) and Casp9 by inhibitors of apoptosis (IAPs) results in an implicit positive feedback, since cleaved Casp3 augments its own activation by sequestering IAPs away from Casp9. We demonstrate that this positive feedback brings about bistability (i.e., all-or-none behaviour), and that it cooperates with Casp3-mediated feedback cleavage of Casp9 to generate irreversibility in caspase activation. Our calculations also unravel how cell-specific protein expression brings about the observed qualitative differences in caspase activation (gradual versus all-or-none and reversible versus irreversible). Finally, known regulators of the pathway are shown to efficiently shift the apoptotic threshold stimulus, suggesting that the bistable caspase cascade computes multiple inputs into an all-or-none caspase output. As cellular inhibitory proteins (e.g., IAPs) frequently inhibit consecutive intermediates in cellular signaling cascades (e.g., Casp3 and Casp9), the feedback mechanism described in this paper is likely to be a widespread principle on how cells achieve ultrasensitivity, bistability, and irreversibility.

Apoptosis↗

Global analysis of host tissue gene expression in the invasive front of colorectal liver metastases.

Host cell reactions are a crucial determinant for tumor invasion. We analyzed on a genomewide scale gene expression differences between microdissected tissues taken from unaffected liver tissue of a human colorectal tumor (LS174) growing in the livers of nude mice and tissue from the host part of the invasive front. Due to the low degree of interspecies cross-hybridization of 15% as determined on Affymetrix microarrays, our xenograft model allowed for the distinction of genes of murine versus human origin even if the respective tissues could not be isolated separately. Using the gene ontology (GO) classification, we were able to determine patterns of up- and downregulated genes in the liver part of the invasive front. We observed a pronounced overrepresentation, e.g., of the GO terms "extracellular matrix," "cell communication," "response to biotic stimulus," "structural molecule activity" and "cell growth," indicating a very pronounced host cell response to tumor invasion. On the single gene level, hepatic stellate cell (HSC) activation markers were overrepresented in the liver part of the invasion front. Immunohistochemistry and qPCR confirmed an activation of HSC as well as an increased number of HSC in the invasive front as compared to the noninvaded liver tissue. In summary, our data demonstrate the feasibility of an interspecies differential gene expression approach on a genomewide scale.

Adenocarcinoma↗

Sequestration shapes the response of signal transduction cascades.

Many signal transduction cascades are composed of covalent modification cycles such as kinase/phosphatase cycles. In the 1980s Goldbeter and Koshland showed that such cycles can exhibit non-linear input-output relations when the enzymes are saturated by their substrates, which may facilitate signal processing. Recent papers show that this mechanism is unlikely to cause non-linearity in mammalian signal transduction cascades as sequestration of the target due to enzyme concentrations present in these cascades will hamper this mechanism. However, sequestration due to high-affinity enzymes can shape the dynamics and steady-state behaviour of signal transduction cascades in different ways, some of which are discussed in this review.

Kinetics↗

Effects of sequestration on signal transduction cascades.

The building blocks of most signal transduction pathways are pairs of enzymes, such as kinases and phosphatases, that control the activity of protein targets by covalent modification. It has previously been shown [Goldbeter A & Koshland DE (1981) Proc Natl Acad Sci USA 78, 6840-6844] that these systems can be highly sensitive to changes in stimuli if their catalysing enzymes are saturated with their target protein substrates. This mechanism, termed zero-order ultrasensitivity, may set thresholds that filter out subthreshold stimuli. Experimental data on protein abundance suggest that the enzymes and their target proteins are present in comparable concentrations. Under these conditions a large fraction of the target protein may be sequestrated by the enzymes. This causes a reduction in ultrasensitivity so that the proposed mechanism is unlikely to account for ultrasensitivity under the conditions present in most in vivo signalling cascades. Furthermore, we show that sequestration changes the dynamics of a covalent modification cycle and may account for signal termination and a sign-sensitive delay. Finally, we analyse the effect of sequestration on the dynamics of a complex signal transduction cascade: the mitogen-activated protein kinase (MAPK) cascade with negative feedback. We show that sequestration limits ultrasensitivity in this cascade and may thereby abolish the potential for oscillations induced by negative feedback.

MAP Kinase Signaling System↗

Ultrasensitization: switch-like regulation of cellular signaling by transcriptional induction.

Cellular signaling networks are subject to transcriptional and proteolytic regulation under both physiological and pathological conditions. For example, the expression of proteins subject to covalent modification by phosphorylation is known to be altered upon cellular differentiation or during carcinogenesis. However, it is unclear how moderate alterations in protein expression can bring about large changes in signal transmission as, for example, observed in the case of haploinsufficiency, where halving the expression of signaling proteins abrogates cellular function. By modeling a fundamental motif of signal transduction, the phosphorylation-dephosphorylation cycle, we show that minor alterations in the concentration of the protein subject to phosphorylation (or the phosphatase) can affect signal transmission in a highly ultrasensitive fashion. This "ultrasensitization" is strongly favored by substrate sequestration on the catalyzing enzymes, and can be observed with experimentally measured enzymatic rate constants. Furthermore, we show that coordinated transcription of multiple proteins (i.e., synexpression) within a protein kinase cascade results in even more pronounced all-or-none behavior with respect to signal transmission. Finally, we demonstrate that ultrasensitization can account for specificity and modularity in the regulation of cellular signal transduction. Ultrasensitization can result in all-or-none cell-fate decisions and in highly specific cellular regulation. Additionally, switch-like phenomena such as ultrasensitization are known to contribute to bistability, oscillations, noise reduction, and cellular heterogeneity.

Animals↗

Transcriptional profiling of Saccharomyces cerevisiae cells under adhesion-inducing conditions.

The ability to adhere to other cells is one of the most prominent determinants of fungal pathogenicity. Thus, adherence of fungi to human tissues or plastics triggers hospital-acquired fungal infections, which are an increasing clinical problem, especially in immunocompromised persons. In the model fungus Saccharomyces cerevisiae adhesion can be induced by starvation for amino acids, and depends on the transcriptional activator of the general amino acid control system, Gcn4p. However, not much is known about the transcriptional program that mediates adhesive growth under such conditions. In this study, we present a genome-wide transcriptional analysis of Sigma1278b yeast cells that were subjected to adhesion-inducing conditions imposed by amino acid starvation. Twenty-two novel genes were identified as inducible by amino acid starvation; 72 genes belonging to different functional groups, which were not previously known to be regulated by Gcn4p, require Gcn4p for full transcriptional induction under adhesion-inducing conditions. In addition, several genes were identified in Sigma1278b cells that were inducible by amino acid starvation in a Gcn4p-independent manner. Our data suggest that adhesion of yeast cells induced by amino acid starvation is regulated by a complex, Sigma1278b-specific transcriptional response.

Adaptor Proteins, Signal Transducing↗

Inferring combinatorial regulation of transcription in silico.

In this paper, we propose a functional view on the in silico prediction of transcriptional regulation. We present a method to predict biological functions regulated by a combinatorial interaction of transcription factors. Using a rigorous statistic, this approach intersects the presence of transcription factor binding sites in gene upstream sequences with Gene Ontology terms associated with these genes. We demonstrate that for the well-studied set of skeletal muscle-related transcription factors Myf-2, Mef and TEF, the correct functions are predicted. Furthermore, starting from the well-characterized promoter of a gene expressed upon lipopolysaccharide stimulation, we predict functional targets of this stimulus. These results are in excellent agreement with microarray data.

Algorithms↗

Quantitative analysis of ultrasensitive responses.

Ultrasensitive responses are common in cellular information transfer because they allow cells to decode extracellular stimuli in an all-or-none manner. Biochemical responses are usually analyzed by fitting the Hill equation, and the estimated Hill coefficient is taken as a measure of sensitivity. However, this approach is not appropriate if the response under consideration significantly deviates from the best-fit Hill equation. In addition, Hill coefficients greater than unity do not necessarily imply ultrasensitive behaviour if basal activation is significant. In order to circumvent these problems we propose a general method for the quantitative analysis of sensitivity, the relative amplification plot, which is based on the response coefficient defined in metabolic control analysis. To quantify sensitivity globally (i.e. over the whole stimulus range) we introduce the integral-based relative amplification coefficient. Our relative amplification approach can easily be extended to monotonically decreasing, bell-shaped or nonsaturated responses.

Cells↗

Biological profiling of gene groups utilizing Gene Ontology.

Increasingly used high throughput experimental techniques, like DNA or protein microarrays give as a result groups of interesting, e.g. differentially regulated genes which require further biological interpretation. With the systematic functional annotation provided by the Gene Ontology the information required to automate the interpretation task is now accessible. However, the determination of statistical significance of a biological process within these groups is still an open question. In answering this question, multiple testing issues must be taken into account to avoid misleading results. Here we present a statistical framework that tests whether functions, processes or locations described in the Gene Ontology are significantly enriched within a group of interesting genes when compared to a reference group. First we define an exact analytical expression for the expected number of false positives that allows us to calculate adjusted p-values to control the false discovery rate. Next, we demonstrate and discuss the capabilities of our approach using publicly available microarray data on cell-cycle regulated genes. Further, we analyze the robustness of our framework with respect to the exact gene group composition and compare the performance with earlier approaches. The software package GOSSIP implements our method and is made freely available at http://gossip.gene-groups.net/.

Binding Sites↗

HOMGL-comparing genelists across species and with different accession numbers.

UNLABELLED: Homology Gene List (HOMGL) is a web-based tool for comparing gene lists with different accession numbers and identifiers and between different organisms. UniGene, LocusLink, HomoloGene and Ensembl databases are utilized to map between these lists and to retrieve upstream or transcribed sequences for genes in these lists. We illustrate the use of HOMGL with respect to microarray studies and promoter analysis. AVAILABILITY: http://homgl.biologie.hu-berlin.de/

Algorithms↗

Prediction of cis-regulatory elements of coregulated genes.

We present a computational pipeline to predict cis-regulatory elements composing results based on different algorithms: Clover, Cluster-Buster, an own implementation of human/rat/mouse sequence identity and our ITB algorithm. The procedure uses information from the human genome sequence, NCBI gene annotations, verified eukaryotic promoters (EPD), experimentally proven binding sites (Transfac) and homologies to mouse and rat (HomGL/HomoloGene). We test the approach on 18 upstream regions of experimentally verified AP-1 target genes. About a half of the known sites belong to high-scoring candidates. Three top-scoring elements are confirmed by Cluster-Buster and high homologies. The same analysis we applied to genes found to be up- or downregulated due to mutated RAS. We performed a detailed literature and computational search for promoter regions. Indications of overrepresented Elk-1 and AP-1 motifs are found via a comparison with shuffled sequences. In some promoters consistent predictions of clustered binding sites were obtained.

Animals↗

How robust are switches in intracellular signaling cascades?

Since all-or-none decisions of the cell are controlled by extracellular signals, cells have biochemical switches within their intracellular signaling networks. Central elements of these switches are multisite phosphorylation, enzymic saturation, and amplification by cascades. Moreover, positive feedback can contribute to switch-like behavior termed also ultrasensitivity. Here we analyse the robustness of these mechanisms exemplified by models of the three-molecule MAPK-cascade and the single-molecule Goldbeter-Koshland switch. We show that the ultrasensitivity in the MAPK-cascades is more robust against changes of the kinetic parameters than the Goldbeter-Koshland switch. If multiple parameters are changed randomly, the effects of parameter changes can compensate each other in the cascade leading to a remarkable robustness of the switch-like behavior. The different degrees of robustness can be traced back to the different mechanisms of generating ultrasensitivity. While in the Goldbeter-Koshland switch the saturation of the enzymes are crucial, in the MAPK-cascade the adjustment of working ranges determines the ultrasensitivity. Our results indicate that amplification of ultrasensitivity in cascades and multisite phosphorylation might be a design principle to achieve robust switches.

Animals↗