October 20th, 2024

Recent Publications Harnessing the Power of Translatomics

Every week we provide a digest of a small number of recent interesting papers in the field of translatomics.

In this week’s Sunday papers, Tomuro et al. address contamination from rRNA and the inability to accurately measure the number of ribosomes on transcripts in Ribo-Seq libraries. Filomena et al. analyze two RNA-seq datasets, focusing on the hippocampal and fusiform gyrus transcriptomic profiles of Alzheimer’s patients. Lastly, Brunetti et al. perform ribosome profiling in NPM1-mutated cell lines to investigate its role in leukemogenesis.

Calibrated ribosome profiling assesses the dynamics of ribosomal flux on transcripts

Nature Communications, 2024

Tomuro, K., Mito, M., Toh, H., Kawamoto, N., Miyake, T., Chow, S.Y.A., Doi, M., Ikeuchi, Y., Shichino, Y. and Iwasaki, S.

Current methods of ribosome profiling have some limitations, including the high level of contamination from rRNA and the inability to accurately (i.e. non non-relative) measure the number of ribosomes on transcripts. To address these limitations, this study develops two new methods, “Ribo-FilterOut” and “Ribo-Calibration”. Ribo-FilterOut uses ultrafiltration to separate ribosome footprints from large and small ribosomal subunits following RNase treatment, effectively removing fragmented but still complex-assembled rRNAs. When used with rRNA depletion approaches, this increases the return of genuine ribosome footprints from 18% to 49%. Ribo-Calibration involves the use of spike-ins with known molar ratios of ribosomes and mRNA, prepared through an in vitro translation system. These spike-ins enable the assessment of ribosome numbers on transcripts by standardizing the data.

By combining this approach with a ribosome run-off assay to estimate initiation rate, the authors could estimate ribosome numbers on transcripts (~5.1). Next, the authors used 5’-bromo-uridine immunoprecipitation chase-deep sequencing to estimate mRNA stability rates, and to deduce the total number of translation events (~1800) before transcript decay. Additionally, this method provides insights into how ribosomes are distributed during stress conditions like heat shock, throughout aging, and across different cell types. Overall, the modified ribosome profiling approach allows for the measurement of both kinetic and stoichiometric aspects of cellular translation across the transcriptome, enhancing our understanding of protein synthesis regulation.

Identification of deregulated lncRNAs in Alzheimer's disease: an integrated gene co-expression network analysis of hippocampus and fusiform gyrus RNAseq datasets

Frontiers in Aging Neuroscience, 2024

Filomena, E., Picardi, E., Tullo, A., Pesole, G. and D’Erchia, A.M.

Long non-coding RNAs (lncRNAs) have gained growing attention as novel epigenetic regulators of gene expression, acting at both transcriptional and post-transcriptional levels. The deregulation of  lncRNAs has been linked to neuronal damage in Alzheimer’s disease (AD), though their role in AD onset remains unclear. To investigate this, the authors analyzed two RNA-seq datasets, focusing on the hippocampal and fusiform gyrus transcriptomic profiles of AD patients compared to non-demented controls. A substantial number of differential expressed (DE) genes, including lncRNAs, were identified in the brain regions of AD patients. By comparing the DE genes from both datasets, 225 lncRNAs and 857 protein-coding genes were found to be DE in both regions.

To infer the function of these DE lncRNAs, a co-expression network analysis using weighted correlation network analysis was conducted. This approach clusters genes based on the similarity of expression across multiple samples. The clusters produced will contain genes (some of unknown function) which are more likely to share the same biological pathways. They identified several modules linked to neurotransmission and memory-related pathways, including CREB signaling in neurons and synaptic long-term depression. These common deregulated lncRNAs may serve as shared signatures of AD pathogenesis, offering valuable insights into the molecular changes underlying the disease.

Mutant NPM1 marginally impacts ribosome footprint in acute myeloid leukemia cells

eJHaem, 2024

Brunetti, L., Pianigiani, G., Gundry, M.C., Goodell, M.A. and Falini, B.

NPM1-mutated acute myeloid leukemia (AML) accounts for about 30–35% of adult AML cases. NPM1, a nucleolar protein, plays key roles in ribosome biogenesis and genome stability. Mutations in the C-terminus of NPM1 disrupt its ability to localize in the nucleolus, creating a nuclear export signal motif. This leads to increased interaction with the nuclear exporter XPO1, causing the mutant NPM1 (NPM1c) to accumulate in the cytoplasm of AML cells. NPM1-mutated AML is the most common AML subtype and it has been suggested that altered translation may contribute to the development and maintenance of leukemia in NPM1-mutated AML. However, this idea had not been explored. Researchers hypothesized that if NPM1c directly affects translation in leukemic cells, removing NPM1c would cause immediate changes in ribosome activity.

To investigate, ribosome footprint profiling (Ribo-Seq) and bulk mRNA sequencing were performed in two NPM1-mutated cell lines engineered to degrade NPM1c using the FKBP (F36V) degron tag. Treatment with dTAG-13 led to specific degradation of NPM1c within four hours. As expected, RNA sequencing showed early loss of homeobox gene expression after NPM1c degradation, validating the model. However, Ribo-Seq data revealed minimal changes in translation across both cell lines, indicating that NPM1c does not impact translation initiation or ribosome positioning on mRNA. While NPM1c likely contributes to leukemogenesis in various ways, these results suggest that it does not influence translation at the ribosome footprint level.

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