Periodic Reporting for period 4 - TransTempoFold (A need for speed: mechanisms to coordinate protein synthesis and folding in metazoans)
Reporting period: 2023-07-01 to 2025-03-31
Proteins are central to most biological processes. These molecules can only perform their roles after being accurately produced by ribosomes and properly folded into their specific three-dimensional shapes. When this process is disrupted, it can have serious consequences for the health of cells and organisms. Accumulation of misfolded proteins is a common feature of aging and is linked to many human diseases.
The human genome encodes nearly 20,000 proteins, with some expressed in all cells and others specific to certain cell types or stages of development. The production and proper folding of these proteins are controlled by a complex network of hundreds of RNA and protein factors. How this network for protein biogenesis adapts to the diverse and changing needs of different tissues and during development remains largely unknown. Disruptions in protein biogenesis have been linked to various human diseases, many of which affect the nervous system, but the molecular causes are not well understood. Furthermore, the levels of key components of the biogenesis machinery vary among tissues and cell types, yet the significance of this heterogeneity for cell identity and overall cellular health is still unclear.
The main goal of this project was to uncover the molecular mechanisms by which different cell types establish and maintain their unique proteomes. Understanding these processes is crucial because some cell types are more vulnerable to problems in protein homeostasis, which can lead to disease. To study this in models that closely resemble human physiology, we applied methods that enable the differentiation of human induced pluripotent stem cells (hiPSCs) into specific cell lineages, including neural progenitors, neurons, and cardiomyocytes, with high efficiency. These cell models allowed us to investigate how different healthy human cells regulate protein production. The insights gained from this research can improve our understanding of cell development, differentiation, and disease mechanisms related to protein production defects.
The human genome encodes nearly 20,000 proteins, with some expressed in all cells and others specific to certain cell types or stages of development. The production and proper folding of these proteins are controlled by a complex network of hundreds of RNA and protein factors. How this network for protein biogenesis adapts to the diverse and changing needs of different tissues and during development remains largely unknown. Disruptions in protein biogenesis have been linked to various human diseases, many of which affect the nervous system, but the molecular causes are not well understood. Furthermore, the levels of key components of the biogenesis machinery vary among tissues and cell types, yet the significance of this heterogeneity for cell identity and overall cellular health is still unclear.
The main goal of this project was to uncover the molecular mechanisms by which different cell types establish and maintain their unique proteomes. Understanding these processes is crucial because some cell types are more vulnerable to problems in protein homeostasis, which can lead to disease. To study this in models that closely resemble human physiology, we applied methods that enable the differentiation of human induced pluripotent stem cells (hiPSCs) into specific cell lineages, including neural progenitors, neurons, and cardiomyocytes, with high efficiency. These cell models allowed us to investigate how different healthy human cells regulate protein production. The insights gained from this research can improve our understanding of cell development, differentiation, and disease mechanisms related to protein production defects.
A key goal of this project was to understand how the levels of transfer RNAs (tRNAs) are regulated to support accurate and efficient protein production in different human cell types. This fundamental question had remained unanswered due to the lack of methods capable of precise, high-throughput measurement of tRNA abundance. tRNAs contain chemical modifications that hinder traditional sequencing approaches by blocking reverse transcription or causing errors, and many tRNAs have over 98% sequence similarity, complicating read alignment and quantification. To overcome these barriers, we developed a novel method called modification-induced misincorporation tRNA sequencing (mim-tRNAseq). This technique allows full-length sequencing of tRNAs while preserving their modification signatures. We also created a user-friendly, open-source computational pipeline for automated tRNA read mapping, quantification, and visualization. We demonstrated in yeast, flies, and human cells that mim-tRNAseq accurately measures tRNA abundance, charging levels, and identifies modification patterns—all within a single sequencing experiment. This breakthrough has enabled many laboratories to begin investigate previously challenging aspects of tRNA biology.
Applying this technology to human stem cell differentiation, we combined mim-tRNAseq with measurements of RNA Polymerase III (Pol III) binding at tRNA genes with ChIP-Seq and translation rates with ribosome profiling. We found that during hiPSC differentiation into neural or cardiac cells, tRNA pools are extensively remodeled at the individual transcript level. Intriguingly, however, the overall tRNA populations at the anticodon level remained largely stable across different cell types. This stability was maintained by high expression of the most abundant tRNA transcripts within each anticodon family, ensuring consistent decoding speeds regardless of cell identity. Furthermore, we classified the 619 predicted human tRNA genes into three groups based on their expression patterns: only a third were “housekeeping” tRNAs expressed across all cell types, while the rest showed more variable expression. We discovered that Pol III occupancy at human tRNA genes is governed by specific sequence features, which we identified through computational analysis and verified experimentally. During differentiation, reduced activity of the mTORC1 signaling pathway activates the Pol III repressor MAF1, which restricts tRNA expression primarily to housekeeping tRNAs. These findings provide new insights into how tRNA levels are tightly controlled in human cells and set the stage for investigating how tRNA dysregulation may contribute to diseases.
Another key question we addressed was aimed at understanding how the protein production system adapts to the diverse and rapidly changing demands during cell differentiation. To explore this, we established workflows that allow us to control and study gene function over time using inducible CRISPR interference (CRISPRi) screens in hiPSCs and their differentiated progeny. Using this approach, we discovered that certain quality control pathways linked to mRNA translation are only crucial in specific cellular contexts. In particular, human stem cells heavily rely on pathways that manage and resolve ribosomes that have stalled or collided during protein synthesis. We identified a previously unrecognized type of ribosome collisions, which occur on mRNAs with high ribosome density and are caused by the slow transition of ribosomes from initiation to elongation. Our work has highlighted the importance of translation initiation as a physiological source of ribosome collisions and has provided valuable insights into the specialized pathways that maintain the fidelity of protein production in different cell types.
Applying this technology to human stem cell differentiation, we combined mim-tRNAseq with measurements of RNA Polymerase III (Pol III) binding at tRNA genes with ChIP-Seq and translation rates with ribosome profiling. We found that during hiPSC differentiation into neural or cardiac cells, tRNA pools are extensively remodeled at the individual transcript level. Intriguingly, however, the overall tRNA populations at the anticodon level remained largely stable across different cell types. This stability was maintained by high expression of the most abundant tRNA transcripts within each anticodon family, ensuring consistent decoding speeds regardless of cell identity. Furthermore, we classified the 619 predicted human tRNA genes into three groups based on their expression patterns: only a third were “housekeeping” tRNAs expressed across all cell types, while the rest showed more variable expression. We discovered that Pol III occupancy at human tRNA genes is governed by specific sequence features, which we identified through computational analysis and verified experimentally. During differentiation, reduced activity of the mTORC1 signaling pathway activates the Pol III repressor MAF1, which restricts tRNA expression primarily to housekeeping tRNAs. These findings provide new insights into how tRNA levels are tightly controlled in human cells and set the stage for investigating how tRNA dysregulation may contribute to diseases.
Another key question we addressed was aimed at understanding how the protein production system adapts to the diverse and rapidly changing demands during cell differentiation. To explore this, we established workflows that allow us to control and study gene function over time using inducible CRISPR interference (CRISPRi) screens in hiPSCs and their differentiated progeny. Using this approach, we discovered that certain quality control pathways linked to mRNA translation are only crucial in specific cellular contexts. In particular, human stem cells heavily rely on pathways that manage and resolve ribosomes that have stalled or collided during protein synthesis. We identified a previously unrecognized type of ribosome collisions, which occur on mRNAs with high ribosome density and are caused by the slow transition of ribosomes from initiation to elongation. Our work has highlighted the importance of translation initiation as a physiological source of ribosome collisions and has provided valuable insights into the specialized pathways that maintain the fidelity of protein production in different cell types.
Using our innovative methods to analyze tRNAs in healthy human cells, we identified key principles that determine how tRNA levels are regulated and how they influence the decoding of mRNAs during protein synthesis. These insights will improve our ability to predict tRNA expression across various cell types and conditions, investigate how disruptions in tRNA production or processing may lead to disease, and develop tRNA-based therapies with improved effectiveness. Additionally, our platform for comparative studies of gene function in human stem cell-derived models enables detailed exploration of the molecular pathways controlling protein production in cells that closely resemble human biology. This approach will help us understand how errors in mRNA translation contribute to disease and guide the development of therapeutic mRNAs that minimize ribosome collisions and cellular stress, paving the way for more effective treatments.