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Zeba Wunderlich

Publications and source records attributed to Zeba Wunderlich.

4 recordsLinked to original sources

A genome-wide survey reveals a diverse array of enhancers coordinate the Drosophila innate immune response.

To defend against microbes, animals regulate a complex immune response. The Drosophila innate immune system deploys a large transcriptional induction of signaling proteins, antimicrobial effectors, and other critical immune factors. This transcriptional response is encoded in enhancers, cis-regulatory sequences that modulate gene expression by binding transcription factors (TFs). While enhancers and transcription factor binding sites (TFBS) have been identified for several immune responsive genes in Drosophila, most enhancers that regulate immune-induced genes are unknown. By identifying enhancers, we can understand how their composition controls expression and contributes to infection outcome. We employed STARR-seq (Self Transcribing Active Regulatory-Region sequencing) in a hemocyte-like cell line to identify immune-specific enhancers across the D. melanogaster genome and performed ATAC-seq in hemocytes extracted from adult flies to assess the chromatin state of these enhancers before and after immune stimulus. We identified thousands of enhancers responsive to IMD stimulation, one of the two primary immune signaling pathways in Drosophila. As expected, immune enhancers are enriched for motifs of Relish, an NF-κB factor, and Kay/Jra, a bZip heterodimer pair, involved in the Imd and JNK pathways respectively, compared to enhancers active in unstimulated cells. However, when grouping enhancers by their target gene's expression timing or functional role or by the enhancers' chromatin accessibility pre- or post-stimulus, different groups of TFBS motifs are enriched, suggesting distinct regulatory logic for different parts of the immune response. Identification and characterization of the diverse array of enhancers that regulate the innate immune response expands our understanding of how animals fight infections.

Drosophila immunity↗

Using the topology of metabolic networks to predict viability of mutant strains.

Understanding the relationships between the structure (topology) and function of biological networks is a central question of systems biology. The idea that topology is a major determinant of systems function has become an attractive and highly disputed hypothesis. Although structural analysis of interaction networks demonstrates a correlation between the topological properties of a node (protein, gene) in the network and its functional essentiality, the analysis of metabolic networks fails to find such correlations. In contrast, approaches utilizing both the topology and biochemical parameters of metabolic networks, e.g., flux balance analysis, are more successful in predicting phenotypes of knockout strains. We reconcile these seemingly conflicting results by showing that the topology of the metabolic networks of both Escherichia coli and Saccharomyces cerevisiae are, in fact, sufficient to predict the viability of knockout strains with accuracy comparable to flux balance analysis on large, unbiased mutant data sets. This surprising result is obtained by introducing a novel topology-based measure of network transport: synthetic accessibility. We also show that other popular topology-based characteristics such as node degree, graph diameter, and node usage (betweenness) fail to predict the viability of E. coli mutant strains. The success of synthetic accessibility demonstrates its ability to capture the essential properties of the metabolic network, such as the branching of chemical reactions and the directed transport of material from inputs to outputs. Our results strongly support a link between the topology and function of biological networks and, in agreement with recent genetic studies, emphasize the minimal role of flux rerouting in providing robustness of mutant strains.

Algorithms↗

SPINE 2: a system for collaborative structural proteomics within a federated database framework.

We present version 2 of the SPINE system for structural proteomics. SPINE is available over the web at http://nesg.org. It serves as the central hub for the Northeast Structural Genomics Consortium, allowing collaborative structural proteomics to be carried out in a distributed fashion. The core of SPINE is a laboratory information management system (LIMS) for key bits of information related to the progress of the consortium in cloning, expressing and purifying proteins and then solving their structures by NMR or X-ray crystallography. Originally, SPINE focused on tracking constructs, but, in its current form, it is able to track target sample tubes and store detailed sample histories. The core database comprises a set of standard relational tables and a data dictionary that form an initial ontology for proteomic properties and provide a framework for large-scale data mining. Moreover, SPINE sits at the center of a federation of interoperable information resources. These can be divided into (i) local resources closely coupled with SPINE that enable it to handle less standardized information (e.g. integrated mailing and publication lists), (ii) other information resources in the NESG consortium that are inter-linked with SPINE (e.g. crystallization LIMS local to particular laboratories) and (iii) international archival resources that SPINE links to and passes on information to (e.g. TargetDB at the PDB).

Cooperative Behavior↗