updated research descriptions

Author: cancenik

_research/RiboITP.md

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 <p>
-We are thrilled to share a new ribosome profiling approach that leverages the principles of microfluidics and isotachophoresis: <a href="https://www.nature.com/articles/s41586-023-06228-9">Ribo-ITP</a> (Ozadam et al., Nature):
+We developed a new ribosome profiling approach that leverages the principles of microfluidics and isotachophoresis: <a href="https://www.nature.com/articles/s41586-023-06228-9">Ribo-ITP (Ozadam et al., Nature)</a>:
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 <p>
 <i> 
-Translation regulation is critical for early mammalian embryonic development. However, previous studies had been restricted to bulk measurements precluding precise determination of translation regulation including allele-specific analyses. To address this challenge, we developed a novel microfluidic isotachophoresis approach, named RIBOsome profiling via IsoTachoPhoresis (Ribo-ITP), and characterized translation in single oocytes and embryos during early mouse development. We identified differential translation efficiency as a key mechanism regulating genes involved in centrosome organization and N6-methyladenosine modification of RNAs. Our high coverage measurements enabled the first analysis of allele-specific ribosome engagement in early development and led to the discovery of stage-specific differential engagement of zygotic RNAs with ribosomes and reduced translation efficiency of transcripts exhibiting allelic-biased expression. By integrating our measurements with proteomics data, we discovered that ribosome occupancy in germinal vesicle stage oocytes is the predominant determinant of protein abundance in the zygote. The novel Ribo-ITP approach will enable numerous applications by providing high coverage and high resolution ribosome occupancy measurements from ultra-low input samples including single cells.
+Previous studies had been restricted to bulk measurements precluding precise determination of translation regulation including allele-specific analyses. To address this challenge, we developed a novel microfluidic isotachophoresis approach, named RIBOsome profiling via IsoTachoPhoresis (Ribo-ITP), and characterized translation in single oocytes and embryos during early mouse development. Our high coverage measurements enabled the first analysis of allele-specific ribosome engagement in early development and led to the discovery of stage-specific differential engagement of zygotic RNAs with ribosomes and reduced translation efficiency of transcripts exhibiting allelic-biased expression. The novel Ribo-ITP approach will enable numerous applications by providing high coverage and high resolution ribosome occupancy measurements from ultra-low input samples including single cells.
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 <p>
-Our lab uses ribosome profiling and Ribo-ITP to study diverse biological questions, often in close collaboration with experts in specific fields. In partnership with Dr. Sarinay-Cenik (UT Austin), we identified naturally occurring human mutations that affect ribosome expression. Collaborating with Dr. Palazzo (University of Toronto), we investigated how the metabolic enzyme PKM influences translation by interacting with ribosomes (<a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC10325899/">Kejiou et al., NAR</a>). In work with Dr. Buszczak (UT Southwestern), we used Ribo-ITP to characterize novel allelic variants in the ribosome biogenesis factor AIRIM in human cerebral organoids (<a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC10802443/">Ni et al., Nature Cell Biology, in press</a>).
+We use Ribo-ITP to investigate diverse biological questions, often in close collaboration with domain experts. Recent highlights include:
+</p>
 
-We have also extended Ribo-ITP to other model organisms. In <i>C. elegans</i>, we mapped dynamic changes in translation of maternal mRNAs during the first four cell cycles of embryogenesis (<a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC11741243/">Shukla et al., bioRxiv</a>). In yeast, using selective ribosome profiling, we found that Reh1-bound ribosomes accumulate near start codons. Our data suggest that Reh1 is displaced by the elongating nascent peptide and is the final assembly factor released from the 60S ribosomal subunit during its first round of translation (<a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC11791190/">Musalgaonkar et al., Nature Communications</a>).
-</p>
+<ol>
+  <li>
+    Characterization of allelic variants in the ribosome biogenesis factor AIRIM in human cerebral organoids 
+    (<a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC10802443/" target="_blank">Ni et al., <em>Nature Cell Biology</em>, in press</a>).
+  </li>
+  <li>
+    Application of Ribo-ITP in <em>C. elegans</em> to map dynamic changes in the translation of maternal mRNAs during the first four cell cycles of embryogenesis 
+    (<a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC11741243/" target="_blank">Shukla et al., <em>Cell Reports</em>, in press</a>).
+  </li>
+  <li>
+    Use of selective ribosome profiling in yeast to show that that Reh1-bound ribosomes accumulate near start codons. Our data suggest that Reh1 is displaced by the elongating nascent peptide and is the final assembly factor released from the 60S ribosomal subunit during its first round of translation 
+    (<a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC11791190/" target="_blank">Musalgaonkar et al., <em>Nature Communications</em></a>).
+  </li>
+</ol>

_research/ribo-ecosystem.md

@@ -10,21 +10,17 @@ summary: We develop machine learning models to integrate quantitative measuremen
 <!-- <h1> A computational ecosystem to understand translation</h1> -->
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-<p>
-Accurately predicting gene expression across biological contexts requires reliable and reusable data.  Ribosome profiling has become a key method for measuring translation, but much of the existing data is scattered across general-purpose databases with poor metadata, limiting reuse and integrative analyses.
 
-To address this, we manually curated and uniformly reprocessed over 3,500 ribosome profiling experiments. These have been enabled by a computational ecosystem around a dedicated binary hierarchical data format to efficiently store,
-organize and process ribosome profiling data that <a href="https://academic.oup.com/bioinformatics/article/36/9/2929/5701654">we have developed</a>. This effort provided us with a large-scale, high-quality compendium of translation efficiency (TE) data across diverse biological conditions.
+<p>
+Accurately predicting gene expression across biological contexts requires reliable and reusable data. We developed a software framework around a compact binary hierarchical data format to efficiently store, process (<a href="https://academic.oup.com/bioinformatics/article/36/9/2929/5701654"><em>Ozadam, Geng, and Cenik.</em> <em>Bioinformatics</em></a>), and visualize ribosome profiling data (<a href="https://academic.oup.com/bioinformatics/article/40/6/btae369/7696317"><em>Chacko, Ozadam, and Cenik.</em> <em>Bioinformatics</em></a>).
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 <p>
-Inspired by how co-expression of RNA reveals gene function and regulatory programs, we introduced the concept of translation efficiency covariation (TEC). TEC turns out to be a conserved and biologically meaningful signal, reflecting coordinated translational control. It also uncovers new regulatory mechanisms and can predict protein–protein interactions and gene functions. For instance, TEC revealed a novel regulator of glycolysis that was invisible to RNA expression and protein abundance analyses (<a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC11326257/">Liu et al. Nature Biotechnology, in press</a>).
+Using this infrastructure, we manually curated and uniformly reprocessed over 3,500 ribosome profiling experiments. This effort provided us with a large-scale, high-quality compendium of translation efficiency (TE) data across diverse biological conditions. Inspired by how co-expression of RNA reveals gene function and regulatory programs, we introduced the concept of translation efficiency covariation (TEC), a conserved property of mammalian transcriptomes, reflecting coordinated translational control. It also uncovers new regulatory mechanisms and can predict protein–protein interactions and gene functions. For instance, TEC revealed a regulator of glycolysis that was missed by RNA expression and protein abundance analyses (<a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC11326257/">Liu et al. Nature Biotechnology, in press</a>).
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@@ -34,5 +30,5 @@ These tools and insights open the door to new applications in synthetic biology
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 <p>
-We emphasize development of reusable, portable and <a href="https://github.com/CenikLab/">open source software</a>.
+We emphasize the development of reusable, portable, and <a href="https://github.com/CenikLab/">open-source software</a>.
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