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Functional Genomics and Proteomics of the Cellular Osmotic Stress 1593 The Journal of Experimental Biology 210, 1593-1601 Published by The Company of Biologists 2007 doi:10.1242/jeb.000141 Functional genomics and proteomics of the cellular osmotic stress response in ‘non-model’ organisms Dietmar Kültz1,*, Diego Fiol1, Nelly Valkova1, Silvia Gomez-Jimenez2, Stephanie Y. Chan1 and Jinoo Lee1 1Physiological Genomics Group, Department of Animal Science, One Shields Avenue, University of California, Davis, CA 95616, USA and 2Laboratorio de Fisiología de Invertebrados Marinos, CIAD, A.C. Carr. a la Victoria Km. 0.6, CP 83000, Hermosillo, Sonora, México *Author for correspondence (e-mail: [email protected]) Accepted 3 January 2007 Summary All organisms are adapted to well-defined extracellular identified genes and proteins for modeling molecular salinity ranges. Osmoregulatory mechanisms spanning all mechanisms of environmental adaptation. Current levels of biological organization, from molecules to limitations for proteomics in non-model species can be behavior, are central to salinity adaptation. Functional overcome by improving sequence coverage, N- and C- genomics and proteomics approaches represent powerful terminal sequencing and analysis of intact proteins. tools for gaining insight into the molecular basis of salinity Dependence on information about biochemical pathways adaptation and euryhalinity in animals. In this review, we and gene ontology databases for model species represents a discuss our experience in applying such tools to so-called more severe barrier for work with non-model species. To ‘non-model’ species, including euryhaline animals that are minimize such dependence, focusing on a single biological well-suited for studies of salinity adaptation. Suppression process (rather than attempting to describe the system as a subtractive hybridization, RACE-PCR and mass whole) is key when applying ‘omics’ approaches to non- spectrometry-driven proteomics can be used to identify model organisms. genes and proteins involved in salinity adaptation or other environmental stress responses in tilapia, sharks and Glossary available online at sponges. For protein identification in non-model species, http://jeb.biologists.org/cgi/content/full/210/9/1593/DC1 algorithms based on sequence homology searches such as MSBLASTP2 are most powerful. Subsequent gene Key words: salinity adaptation, osmotic stress, systems biology, ontology and pathway analysis can then utilize sets of euryhaline fish, proteomics. Systems biology approaches in traditional comparative The ultimate goal of this approach is to generate a biology mathematical model that describes the biological system and Major advances in high-throughput technologies for the has predictive power (Aggarwal and Lee, 2003). Achieving this detection and quantification of nucleic acids, proteins and tremendously ambitious goal depends on in-depth knowledge metabolites have led to a paradigm shift in biological research. about each element constituting the system of interest. For The new field of systems biology attempts to integrate the instance, experimental data about the expression, regulation, complex data sets generated by high-throughput approaches to function, compartmentation, interaction, modification and develop a holistic understanding of complex biological structures, stability of individual RNAs and proteins have to be collected their dynamics and their responsiveness to external stimuli such and integrated for each state of the system that is described by as salinity stress. The level of complexity of structures modeled the model. Systems biology approaches have largely been by systems biology ranges from molecular networks via cells and applied to organisms whose genomes have been sequenced (so- organs to whole organisms (Kitano, 2002). Systems biology called ‘model’ organisms) because many of the available organizes data obtained by genomic, transcriptomic, proteomic bioinformatics tools are based on prior genome sequencing and and metabolomic approaches to attempt to build descriptive and annotation of the encoded transcriptome and proteome. mechanistic models of integrative biological phenomena such as However, most high-throughput technologies for analyzing the development or interactions of organisms with their environment. transcriptome, proteome and metabolome do not strictly THE JOURNAL OF EXPERIMENTAL BIOLOGY 1594 D. Kültz and others depend on prior knowledge of genomic sequence. Therefore, in gill epithelial cells of tilapia. Tilapia are strongly euryhaline these approaches can also be applied to ‘non-model’ organisms teleosts that are capable of adaptation to a wide range of for which few if any genome sequence data are available. Such environmental salinity. Therefore, mechanisms and molecules organisms account for the majority of species used in involved in salinity adaptation are very prominent in this fish traditional comparative biology. and can be effectively studied. We utilized high-throughput transcriptomics and proteomics SSH was performed with mRNA from control fish approaches for identifying key molecular constituents transferred for 4·h from freshwater (FW) to FW (as the Driver associated with osmoregulatory functions in euryhaline tilapia sample) and the corresponding mRNA from fish transferred for and other animals. Our work shows that these data can be used 4·h from FW to seawater (SW) (as the Tester sample). The final for bioinformatics analysis to generate models about biological resulting PCR products were cloned into pGEM-Teasy vector processes, cellular pathways and molecular functions (Promega, Madison, WI, USA) to generate a subtracted cDNA associated with osmotic stress responses. Nevertheless, many library. This library was screened by colony PCR to yield 650 obstacles are encountered when attempting a systems biology individual clones. Only 72 clones were selected for sequencing approach with non-model species. In the following, we briefly because many of the 650 clones had similar lengths and likely review our efforts to apply high-throughput transcriptomics represented the same sequence. Thirty-two unique cDNAs and proteomics methods to euryhaline tilapia, dogfish shark were represented by the 72 clones that were sequenced. and an intertidal sponge to pave the way towards a systems Increased mRNA abundance after 4·h SW transfer was biology approach for studying osmoregulation. confirmed for 22 of these 32 cDNAs by quantitative real-time PCR (qPCR). This result demonstrates that the rate of false- positive identification by SSH is low (less than one-third of the Identification of an immediate-early gene network analyzed clones were false positives). Full-length coding involved in osmoregulation sequences for most of the 22 cDNAs were obtained by RACE- Approaches for studying environmental regulation of the PCR and degenerate primer PCR, starting with original SSH transcriptome clones, many of which represented 3Ј terminal fragments of Organisms have osmoregulatory mechanisms that span all cDNAs (Fiol and Kültz, 2005; Fiol et al., 2006a). Based on levels of biological organization from molecules to behavior. amino acid homology in the coding sequences, we were able Therefore, understanding responses of fishes and other animals to identify more than 90% of the SSH genes cloned from tilapia to salinity stress requires knowledge of the biological system (Table·1). as a whole, starting with its molecular components. A very popular approach for gaining insight into genes that are Induction kinetics suggests that tilapia SSH cDNAs are regulated by environmental stimuli is based on the use of DNA immediate-early genes microarray chips. However, to harness the full power of this Hyperosmotic induction of tilapia SSH genes was confirmed approach, sequence knowledge of the entire transcriptome of and the kinetics of their induction analyzed by real-time qPCR. the species of interest is required. Although DNA microarrays Most SSH genes show a rapid and transient increase in mRNA can also be used very effectively for non-model species abundance, with peak levels observed between 2 and 8·h after (Buckley, 2007; Gracey, 2007), prior sequence knowledge SW transfer. An example of a time course depicting the salinity- greatly facilitates their production and use and maximizes induced induction of a tilapia SSH gene (protein phosphatase 2A, coverage of the transcriptome during the analysis. Serial catalytic subunit) is shown in Fig.·1. Most of the SSH genes analysis of gene expression (SAGE) and recent modifications differ only slightly in the kinetics of their induction, suggesting of SAGE represent alternative approaches to DNA microarrays that they participate in a common cellular network as part of an that identify very short sequence tags that can then be matched overall essential and coordinated adaptive response that involves against existing sequences (Maillard et al., 2005). In addition changes in metabolism, transport, damage repair, etc. (Fiol and to SAGE and DNA microarrays, the identification of a subset Kültz, 2005; Fiol et al., 2006a). A notable single exception is a of RNAs whose levels are regulated by salinity can be achieved cDNA clone (SSH#7) that displays a robust sustained induction by methods that are based on differential analysis of RNA in response to SW transfer. This cDNA increases as rapidly as levels and less dependent on prior sequence knowledge of the the other SSH genes but it remains high even after a prolonged transcriptome. Such methods include differential display (Stein
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