This Program Project is aimed at understanding the mechanisms that control growth and multicellular development in Dictyostelium. By examining the functions of a large number of genes we will begin to formulate a global view of the regulatory networks In this organism. In the previous project period we took a functional genomics approach to high-throughput mutant phenotyping, using molecular barcodes, that has allowed us to draw functional inferences for hundreds of genes. We will revolutionize our parallel phenotyping platform using Next Generation Sequencing technologies that should yield dramatic improvements in barcode quantification so that more information can be gleaned from every new experiment. Over the next five years we will focus our efforts on understanding bacterial recognition in Dictyostelium, both during the growth of solitary amoebae and in the context of an innate immune response during development. We will define innate immune recognition of bacteria by amoebae in molecular terms by characterizing the genes and pathways involved. We will intersect the transcriptional profiling data from Project II with the physiological data provided by this project to uncover links between gene function and patterns of gene expression. The data we produce will also be used by Project III for extracting information about the genetic networks that coordinate bacterial recognition in Dictyostelium.
This work will help establish the amoeba as a model system for the study of innate immunity, leading to the development of tools and techniques that can be applied to understanding the response of eukaryotic cells to bacteria. Studying the response of amoebae to bacteria has a relation to infections in humans because the work will reveal conserved pathways used by eukaryotes to defend themselves against bacteria.
|Swatson, William S; Katoh-Kurasawa, Mariko; Shaulsky, Gad et al. (2017) Curcumin affects gene expression and reactive oxygen species via a PKA dependent mechanism in Dictyostelium discoideum. PLoS One 12:e0187562|
|Stajdohar, Miha; Rosengarten, Rafael D; Kokosar, Janez et al. (2017) dictyExpress: a web-based platform for sequence data management and analytics in Dictyostelium and beyond. BMC Bioinformatics 18:291|
|Rosengarten, Rafael D; Santhanam, Balaji; Kokosar, Janez et al. (2017) The Long Noncoding RNA Transcriptome of Dictyostelium discoideum Development. G3 (Bethesda) 7:387-398|
|Zhang, Xuezhi; Zhuchenko, Olga; Kuspa, Adam et al. (2016) Social amoebae trap and kill bacteria by casting DNA nets. Nat Commun 7:10938|
|Zitnik, Marinka; Zupan, Blaz (2016) COLLECTIVE PAIRWISE CLASSIFICATION FOR MULTI-WAY ANALYSIS OF DISEASE AND DRUG DATA. Pac Symp Biocomput 21:81-92|
|Katoh-Kurasawa, Mariko; Santhanam, Balaji; Shaulsky, Gad (2016) The GATA transcription factor gene gtaG is required for terminal differentiation in Dictyostelium. J Cell Sci :|
|Li, Cheng-Lin Frank; Santhanam, Balaji; Webb, Amanda Nicole et al. (2016) Gene discovery by chemical mutagenesis and whole-genome sequencing in Dictyostelium. Genome Res 26:1268-76|
|Chen, Xinlu; Köllner, Tobias G; Jia, Qidong et al. (2016) Terpene synthase genes in eukaryotes beyond plants and fungi: Occurrence in social amoebae. Proc Natl Acad Sci U S A 113:12132-12137|
|Zitnik, Marinka; Zupan, Blaz (2016) Jumping across biomedical contexts using compressive data fusion. Bioinformatics 32:i90-i100|
|Žitnik, Marinka; Nam, Edward A; Dinh, Christopher et al. (2015) Gene Prioritization by Compressive Data Fusion and Chaining. PLoS Comput Biol 11:e1004552|
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