Doctor of Philosophy, Stanford University, BIOC-PHD (2013)
Bachelor of Science, University of Wisconsin Madison, Biochemistry (2005)
A growing body of evidence supports the existence of an extensive network of RNA-binding proteins (RBPs) whose combinatorial binding affects the post-transcriptional fate of every mRNA in the cell-yet we still do not have a complete understanding of which proteins bind to mRNA, which of these bind concurrently, and when and where in the cell they bind. We describe here a method to identify the proteins that bind to RNA concurrently with an RBP of interest, using quantitative mass spectrometry combined with RNase treatment of affinity-purified RNA-protein complexes. We applied this method to the known RBPs Pab1, Nab2, and Puf3. Our method significantly enriched for known RBPs and is a clear improvement upon previous approaches in yeast. Our data reveal that some reported protein-protein interactions may instead reflect simultaneous binding to shared RNA targets. We also discovered more than 100 candidate RBPs, and we independently confirmed that 77% (23/30) bind directly to RNA. The previously recognized functions of the confirmed novel RBPs were remarkably diverse, and we mapped the RNA-binding region of one of these proteins, the transcriptional coactivator Mbf1, to a region distinct from its DNA-binding domain. Our results also provided new insights into the roles of Nab2 and Puf3 in post-transcriptional regulation by identifying other RBPs that bind simultaneously to the same mRNAs. While existing methods can identify sets of RBPs that interact with common RNA targets, our approach can determine which of those interactions are concurrent-a crucial distinction for understanding post-transcriptional regulation.
View details for DOI 10.1101/gr.153031.112
View details for Web of Science ID 000319803700012
View details for PubMedID 23636942
RNA binding proteins (RBPs) are vital to the regulation of mRNA transcripts, and can alter mRNA localization, degradation, translation, and storage. Whi3 was originally identified in a screen for small cell size mutants, and has since been characterized as an RBP. The identification of Whi3-interacting mRNAs involved in mediating cellular responses to stress suggested that Whi3 might be involved in stress-responsive RNA processing. We show that Whi3 localizes to stress granules in response to glucose deprivation or heat shock. The kinetics and pattern of Whi3 localization in response to a range of temperatures were subtly but distinctly different from those of known components of RNA processing granules. Deletion of Whi3 resulted in an increase in the relative abundance of Whi3 target RNAs, either in the presence or absence of heat shock. Increased levels of the CLN3 mRNA in whi3? cells may explain their decreased cell size. Another mRNA target of Whi3 encodes the zinc-responsive transcription factor Zap1, suggesting a role for Whi3 in response to zinc stress. Indeed, we found that whi3? cells have enhanced sensitivity to zinc toxicity. Together our results suggest an expanded model for Whi3 function: in addition to its role as a regulator of the cell cycle, Whi3 may have a role in stress-dependent RNA processing and responses to a variety of stress conditions.
View details for DOI 10.1371/journal.pone.0084060
View details for Web of Science ID 000329117900073
View details for PubMedID 24386330
High throughput molecular-interaction studies using immunoprecipitations (IP) or affinity purifications are powerful and widely used in biology research. One of many important applications of this method is to identify the set of RNAs that interact with a particular RNA-binding protein (RBP). Here, the unique statistical challenge presented is to delineate a specific set of RNAs that are enriched in one sample relative to another, typically a specific IP compared to a non-specific control to model background. The choice of normalization procedure critically impacts the number of RNAs that will be identified as interacting with an RBP at a given significance threshold - yet existing normalization methods make assumptions that are often fundamentally inaccurate when applied to IP enrichment data.In this paper, we present a new normalization methodology that is specifically designed for identifying enriched RNA or DNA sequences in an IP. The normalization (called adaptive or AD normalization) uses a basic model of the IP experiment and is not a variant of mean, quantile, or other methodology previously proposed. The approach is evaluated statistically and tested with simulated and empirical data.The adaptive (AD) normalization method results in a greatly increased range in the number of enriched RNAs identified, fewer false positives, and overall better concordance with independent biological evidence, for the RBPs we analyzed, compared to median normalization. The approach is also applicable to the study of pairwise RNA, DNA and protein interactions such as the analysis of transcription factors via chromatin immunoprecipitation (ChIP) or any other experiments where samples from two conditions, one of which contains an enriched subset of the other, are studied.
View details for DOI 10.1371/journal.pone.0053930
View details for Web of Science ID 000314019100038
View details for PubMedID 23349766
The vast landscape of RNA-protein interactions at the heart of post-transcriptional regulation remains largely unexplored. Indeed it is likely that, even in yeast, a substantial fraction of the regulatory RNA-binding proteins (RBPs) remain to be discovered. Systematic experimental methods can play a key role in discovering these RBPs--most of the known yeast RBPs lack RNA-binding domains that might enable this activity to be predicted. We describe here a proteome-wide approach to identify RNA-protein interactions based on in vitro binding of RNA samples to yeast protein microarrays that represent over 80% of the yeast proteome. We used this procedure to screen for novel RBPs and RNA-protein interactions. A complementary mass spectrometry technique also identified proteins that associate with yeast mRNAs. Both the protein microarray and mass spectrometry methods successfully identify previously annotated RBPs, suggesting that other proteins identified in these assays might be novel RBPs. Of 35 putative novel RBPs identified by either or both of these methods, 12, including 75% of the eight most highly-ranked candidates, reproducibly associated with specific cellular RNAs. Surprisingly, most of the 12 newly discovered RBPs were enzymes. Functional characteristics of the RNA targets of some of the novel RBPs suggest coordinated post-transcriptional regulation of subunits of protein complexes and a possible link between mRNA trafficking and vesicle transport. Our results suggest that many more RBPs still remain to be identified and provide a set of candidates for further investigation.
View details for DOI 10.1371/journal.pone.0012671
View details for Web of Science ID 000281687300015
View details for PubMedID 20844764