Daniela Eggle | Search PubMed

PubMed2006

Indoleamine 2,3-dioxygenase-expressing dendritic cells form suppurative granulomas following Listeria monocytogenes infection.

Control of pathogens by formation of abscesses and granulomas is a major strategy of the innate immune system, especially when effector mechanisms of adaptive immunity are insufficient. We show in human listeriosis that DCs expressing indoleamine 2,3-dioxygenase (IDO), together with macrophages, are major cellular components of suppurative granulomas in vivo. Induction of IDO by DCs is a cell-autonomous response to Listeria monocytogenes infection and was also observed in other granulomatous infections with intracellular bacteria, such as Bartonella henselae. Reporting on our use of the clinically applied anti-TNF-alpha antibody infliximab, we further demonstrate in vitro that IDO induction is TNF-alpha dependent. Repression of IDO therefore might result in exacerbation of granulomatous diseases observed during anti-TNF-alpha therapy. These findings place IDO(+) DCs not only at the intersection of innate and adaptive immunity but also at the forefront of bacterial containment in granulomatous infections.

Antigens, CD↗

PubMed2004

Wnt pathway curation using automated natural language processing: combining statistical methods with partial and full parse for knowledge extraction.

MOTIVATION: Wnt signaling is a very active area of research with highly relevant publications appearing at a rate of more than one per day. Building and maintaining databases describing signal transduction networks is a time-consuming and demanding task that requires careful literature analysis and extensive domain-specific knowledge. For instance, more than 50 factors involved in Wnt signal transduction have been identified as of late 2003. In this work we describe a natural language processing (NLP) system that is able to identify references to biological interaction networks in free text and automatically assembles a protein association and interaction map. RESULTS: A 'gold standard' set of names and assertions was derived by manual scanning of the Wnt genes website (http://www.stanford.edu/~rnusse/wntwindow.html) including 53 interactions involved in Wnt signaling. This system was used to analyze a corpus of peer-reviewed articles related to Wnt signaling including 3369 Pubmed and 1230 full text papers. Names for key Wnt-pathway associated proteins and biological entities are identified using a chi-squared analysis of noun phrases over-represented in the Wnt literature as compared to the general signal transduction literature. Interestingly, we identified several instances where generic terms were used on the website when more specific terms occur in the literature, and one typographic error on the Wnt canonical pathway. Using the named entity list and performing an exhaustive assertion extraction of the corpus, 34 of the 53 interactions in the 'gold standard' Wnt signaling set were successfully identified (64% recall). In addition, the automated extraction found several interactions involving key Wnt-related molecules which were missing or different from those in the canonical diagram, and these were confirmed by manual review of the text. These results suggest that a combination of NLP techniques for information extraction can form a useful first-pass tool for assisting human annotation and maintenance of signal pathway databases. AVAILABILITY: The pipeline software components are freely available on request to the authors. CONTACT: dstates@umich.edu SUPPLEMENTARY INFORMATION: http://stateslab.bioinformatics.med.umich.edu/software.html.

Animals↗