Multi-cellular organisms face the challenge of coordinating all of their tissues' functions in response to changing nutrients, temperatures, and environments for the benefit of the whole organism. Disease and aging also have effects that are both tissue-specific and systemic. However, the question of how tissues are coordinated throughout a whole organism is currently an unsolved problem. The nematode C. elegans has a simple body plan, with only 959 cells and a small number of major tissues. While some tissues have been well studied, we know less about others, and it is becoming appreciated that some of these lesser-studied tissues have endocrine (hormonal signaling) functions. Specifically, recent evidence suggests that the worm's skin (hypodermis) and intestine are major endocrine tissues, coordinating signals from the neurons about nutrients and conditions, and translating that information into decisions about longevity and reproduction. In our previous work, we found that reproductive aging and somatic aging rates are determined non-cell autonomously. However, the relevant tissues are relatively uncharacterized, due to the difficulty in isolating adult C. elegans tissues. My lab recently solved this problem, developing a method to gently dissociate adult C. elegans tissues, allowing us to sort cells and perform RNA-seq to identify the transcriptome of each tissue type in the animal. In this project, we will use our technique to obtain tissue-specific transcriptome information for every tissue (the tissueome) and couple that information with computational approaches to identify networks of activity and communication. We will also use biochemical methods to determine tissue-specific transcription factor activity, which will allow us to understand how C. elegans integrates signals to convey metabolic and longevity decisions to the whole animal. C. elegans' small number of cells and simple tissues make it an ideal system in which to not only
The biggest challenge in the post-genomic era is to make sense of the wealth of information encoded by the genome. Unfortunately, just knowing an organism's entire genomic sequence is not sufficient to understand how it functions. Instead, one must understand the set of transcripts that are expressed in each cell type that allow that cell to carry out its specialized function, and the networks of genes that signal between the tissues. Understanding these differences in tissue-specific expression is particularly important in the case of multicellular organisms, because each cell or tissue expresses a particular set of transcripts that enable that tissue to carry out its particular function, and to communicate and coordinate with other tissues. Longevity and metabolism are both controlled through multi-tissue regulatory mechanisms, and most diseases have both tissue-specific and systemic effects. If we understood the defining characteristics of each cell and tissue in detail and the network of genes that interact in and between those tissues, we could understand the integration of these functions in the whole organism, and how those characteristics change at different stages of life and with disease. While transcriptional analysis has been performed on individual tissues dissected from many animals, including humans, a system-wide understanding of the whole transcriptional regulatory network of an adult multicellular organism has not yet been reached. Such an understanding could inform our treatment of diseases that are systemic rather than restricted to a single tissue. This problem is further amplified when one considers the brain, in which many different types of neurons have distinct jobs; these are partly determined by how they are connected to one another, but these connections will not make sense until we also understand how these neurons are able to function through the genes they express. Likewise, aging and many types of disease can only be understood in terms of their multi-organ and system-wide effects. Therefore, our challenge is to unravel the cell autonomous (within cell) and non- autonomous signaling mechanisms between tissues by identifying every tissue's transcriptome?an organism's ?tissueome?. While such a large-scale project would be unfeasible at this time in most multi-cellular organisms, our preliminary data suggest that it is achievable in C. elegans.
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