FTH1 overexpression using a dCasRx translation enhancement system protects the kidney from calcium oxalate crystal-induced injury.

The engineered clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein (Cas) system is currently widely applied in genetic editing and transcriptional regulation. The catalytically inactivated CasRx (dCasRx) has the ability to selectively focus on the mRNA coding region without disrupting transcription and translation, opening up new avenues for research on RNA modification and protein translation control. This research utilized dCasRx to create a translation-enhancement system for mammals called dCasRx-eIF4GI, which combined eukaryotic translation initiation factor 4G (eIF4GI) to boost translation levels of the target gene by recruiting ribosomes, without affecting mRNA levels, ultimately increasing translation levels of different endogenous proteins. Due to the small size of dCasRx, the dCasRx-eIF4GI translation enhancement system was integrated into a single viral vector, thus optimizing the delivery and transfection efficiency in subsequent applications. Previous studies reported that ferroptosis, mediated by calcium oxalate (CaOx) crystals, significantly promotes stone formation. In order to further validate its developmental potential, it was applied to a kidney stone model in vitro and in vivo. The manipulation of the ferroptosis regulatory gene FTH1 through single-guide RNA (sgRNA) resulted in a notable increase in FTH1 protein levels without affecting its mRNA levels. This ultimately prevented intracellular ferroptosis and protected against cell damage and renal impairment caused by CaOx crystals. Taken together, this study preliminarily validated the effectiveness and application prospects of the dCasRx-eIF4GI translation enhancement system in mammalian cell-based disease models, providing novel insights and a universal tool platform for protein translation research and future therapeutic approaches for nephrolithiasis.

TIR predictor and optimizer: Web-tools for accurate prediction of translation initiation rate and precision gene design in Saccharomyces cerevisiae.

Translation initiation is the primary determinant of the rate of protein production. The variation in the rate with which this step occurs can cause up to three orders of magnitude differences in cellular protein levels. Several mRNA features, including mRNA stability in proximity to the start codon, coding sequence length, and presence of specific motifs in the mRNA molecule, have been shown to influence the translation initiation rate. These molecular factors acting at different strengths allow precise control of in vivo translation initiation rate and thus the rate of protein synthesis. However, despite the paramount importance of translation initiation rate in protein synthesis, accurate prediction of the absolute values of initiation rate remains a challenge. In fact, as of now, there is no available model for predicting the initiation rate in Saccharomyces cerevisiae. To address this, we train a machine learning model for predicting the in vivo initiation rate in S. cerevisiae transcripts. The model is trained using a diverse set of mRNA transcripts, enabling the comparison of initiation rates across different transcripts. Our model exhibited excellent accuracy in predicting the translation initiation rate and demonstrated its effectiveness with both endogenous and exogenous transcripts. Then, by combining the machine learning model with the Monte-Carlo search algorithm, we have also devised a method to optimize the nucleotide sequence of any gene to achieve a specific target initiation rate. The machine learning model we've developed for predicting translation initiation rates, along with the gene optimization method, are deployed as a web server. Both web servers are accessible for free at the following link: ajeetsharmalab.com/TIRPredictor. Thus, this research advances our fundamental understanding of translation initiation processes, with direct applications in biotechnology.

IGHMBP2 deletion suppresses translation and activates the integrated stress response.

IGHMBP2 is a nonessential, superfamily 1 DNA/RNA helicase that is mutated in patients with rare neuromuscular diseases SMARD1 and CMT2S. IGHMBP2 is implicated in translational and transcriptional regulation via biochemical association with ribosomal proteins, pre-rRNA processing factors, and tRNA-related species. To uncover the cellular consequences of perturbing IGHMBP2, we generated full and partial IGHMBP2 deletion K562 cell lines. Using polysome profiling and a nascent protein synthesis assay, we found that IGHMBP2 deletion modestly reduces global translation. We performed Ribo-seq and RNA-seq and identified diverse gene expression changes due to IGHMBP2 deletion, including ATF4 up-regulation. With recent studies showing the integrated stress response (ISR) can contribute to tRNA metabolism-linked neuropathies, we asked whether perturbing IGHMBP2 promotes ISR activation. We generated ATF4 reporter cell lines and found IGHMBP2 knockout cells demonstrate basal, chronic ISR activation. Our work expands upon the impact of IGHMBP2 in translation and elucidates molecular mechanisms that may link mutant IGHMBP2 to severe clinical phenotypes.

CRISPR-Cas tools for simultaneous transcription & translation control in bacteria.

Robust control over gene translation at arbitrary mRNA targets is an outstanding challenge in microbial synthetic biology. The development of tools that can regulate translation will greatly expand our ability to precisely control genes across the genome. In Escherichia coli, most genes are contained in multi-gene operons, which are subject to polar effects where targeting one gene for repression leads to silencing of other genes in the same operon. These effects pose a challenge for independently regulating individual genes in multi-gene operons. Here, we use CRISPR-dCas13 to address this challenge. We find dCas13-mediated repression exhibits up to 6-fold lower polar effects compared to dCas9. We then show that we can selectively activate single genes in a synthetic multi-gene operon by coupling dCas9 transcriptional activation of an operon with dCas13 translational repression of individual genes within the operon. We also show that dCas13 and dCas9 can be multiplexed for improved biosynthesis of a medically-relevant human milk oligosaccharide. Taken together, our findings suggest that combining transcriptional and translational control can access effects that are difficult to achieve with either mode independently. These combined tools for gene regulation will expand our abilities to precisely engineer bacteria for biotechnology and perform systematic genetic screens.

Overexpression of YTHDF3 increases the specific productivity of the recombinant protein in CHO cells by promoting the translation process.

Due to their high-quality characteristics, Chinese hamster ovary (CHO) cells have become the most widely used and reliable host cells for the production of recombinant therapeutic proteins in the biomedical field. Previous studies have shown that the m6A reader YTHDF3, which contains the YTH domain, can affect a variety of biological processes by regulating the translation and stability of target mRNAs. This study investigates the effect of YTHDF3 on transgenic CHO cells. The results indicate that stable overexpression of YTHDF3 significantly enhances recombinant protein expression without affecting host cell growth. Transcriptome sequencing indicated that several genes, including translation initiation factor, translation extension factor, and ribosome assembly factor, were upregulated in CHO cells overexpressing YTHDF3. In addition, cycloheximide experiments confirmed that YTHDF3 enhanced transgene expression by promoting translation in CHO cells. In conclusion, the findings in this study provide a novel approach for mammalian cell engineering to increase protein productivity by regulating m6A.

Prioritization of genes for translation: a computational approach.

INTRODUCTION: Gene identification for genetic diseases is critical for the development of new diagnostic approaches and personalized treatment options. Prioritization of gene translation is an important consideration in the molecular biology field, allowing researchers to focus on the most promising candidates for further investigation. AREAS COVERED: In this paper, we discussed different approaches to prioritize genes for translation, including the use of computational tools and machine learning algorithms, as well as experimental techniques such as knockdown and overexpression studies. We also explored the potential biases and limitations of these approaches and proposed strategies to improve the accuracy and reliability of gene prioritization methods. Although numerous computational methods have been developed for this purpose, there is a need for computational methods that incorporate tissue-specific information to enable more accurate prioritization of candidate genes. Such methods should provide tissue-specific predictions, insights into underlying disease mechanisms, and more accurate prioritization of genes. EXPERT OPINION: Using advanced computational tools and machine learning algorithms to prioritize genes, we can identify potential targets for therapeutic intervention of complex diseases. This represents an up-and-coming method for drug development and personalized medicine.

Translation velocity determines the efficacy of engineered suppressor tRNAs on pathogenic nonsense mutations.

Nonsense mutations - the underlying cause of approximately 11% of all genetic diseases - prematurely terminate protein synthesis by mutating a sense codon to a premature stop or termination codon (PTC). An emerging therapeutic strategy to suppress nonsense defects is to engineer sense-codon decoding tRNAs to readthrough and restore translation at PTCs. However, the readthrough efficiency of the engineered suppressor tRNAs (sup-tRNAs) largely varies in a tissue- and sequence context-dependent manner and has not yet yielded optimal clinical efficacy for many nonsense mutations. Here, we systematically analyze the suppression efficacy at various pathogenic nonsense mutations. We discover that the translation velocity of the sequence upstream of PTCs modulates the sup-tRNA readthrough efficacy. The PTCs most refractory to suppression are embedded in a sequence context translated with an abrupt reversal of the translation speed leading to ribosomal collisions. Moreover, modeling translation velocity using Ribo-seq data can accurately predict the suppression efficacy at PTCs. These results reveal previously unknown molecular signatures contributing to genotype-phenotype relationships and treatment-response heterogeneity, and provide the framework for the development of personalized tRNA-based gene therapies.

dCas13-mediated translational repression for accurate gene silencing in mammalian cells.

Current gene silencing tools based on RNA interference (RNAi) or, more recently, clustered regularly interspaced short palindromic repeats (CRISPR)‒Cas13 systems have critical drawbacks, such as off-target effects (RNAi) or collateral mRNA cleavage (CRISPR‒Cas13). Thus, a more specific method of gene knockdown is needed. Here, we develop CRISPRδ, an approach for translational silencing, harnessing catalytically inactive Cas13 proteins (dCas13). Owing to its tight association with mRNA, dCas13 serves as a physical roadblock for scanning ribosomes during translation initiation and does not affect mRNA stability. Guide RNAs covering the start codon lead to the highest efficacy regardless of the translation initiation mechanism: cap-dependent, internal ribosome entry site (IRES)-dependent, or repeat-associated non-AUG (RAN) translation. Strikingly, genome-wide ribosome profiling reveals the ultrahigh gene silencing specificity of CRISPRδ. Moreover, the fusion of a translational repressor to dCas13 further improves the performance. Our method provides a framework for translational repression-based gene silencing in eukaryotes.

Cancer cells forgo translating mRNA transcribed from genes of nonspecialized tasks.

The coupling of transcription and translation enables prokaryotes to regulate mRNA stability and reduce nonfunctional transcripts. Eukaryotes evolved other means to perform these functions. Here, we quantify the disparity between gene expression and protein levels and attempt to explain its origins. We collected publicly available simultaneous measurements of gene expression, protein level, division rate, and growth inhibition of breast cancer cells under drug perturbation. We used the cell lines as entities with shared origin, different evolutionary trajectories, and cancer hallmarks to define tasks subject to specializing and trading-off. We observed varying average mRNA and protein correlation across cell lines, and it was consistently higher for the gene products in the cancer hallmarks. The enrichment of hallmark gene products signifies the resources invested in it as a task. Enrichment based on mRNA or protein abundance corresponds to the relative resources dedicated to transcription and translation. The differences in gene- and protein-based enrichment correlated with nominal division rates but not growth inhibition under drug perturbations. Comparing the range of enrichment scores of the hallmarks within each cell signifies the resources dedicated to each. Cells appear to have a wider range of enrichment in protein synthesis relative to gene transcription. The difference and range of enrichment of the hallmark genes and proteins correlated with cell division and inhibition in response to drug treatments. We posit that cancer cells may express the genes coding for seemingly nonspecialized tasks but do not translate them to the corresponding proteins. This trade-off may cost the cells under normal conditions but confer benefits during stress.

Extended stop codon context predicts nonsense codon readthrough efficiency in human cells.

Protein synthesis terminates when a stop codon enters the ribosome's A-site. Although termination is efficient, stop codon readthrough can occur when a near-cognate tRNA outcompetes release factors during decoding. Seeking to understand readthrough regulation we used a machine learning approach to analyze readthrough efficiency data from published HEK293T ribosome profiling experiments and compared it to comparable yeast experiments. We obtained evidence for the conservation of identities of the stop codon, its context, and 3'-UTR length (when termination is compromised), but not the P-site codon, suggesting a P-site tRNA role in readthrough regulation. Models trained on data from cells treated with the readthrough-promoting drug, G418, accurately predicted readthrough of premature termination codons arising from CFTR nonsense alleles that cause cystic fibrosis. This predictive ability has the potential to aid development of nonsense suppression therapies by predicting a patient's likelihood of improvement in response to drugs given their nonsense mutation sequence context.

Protein translation: biological processes and therapeutic strategies for human diseases.

Protein translation is a tightly regulated cellular process that is essential for gene expression and protein synthesis. The deregulation of this process is increasingly recognized as a critical factor in the pathogenesis of various human diseases. In this review, we discuss how deregulated translation can lead to aberrant protein synthesis, altered cellular functions, and disease progression. We explore the key mechanisms contributing to the deregulation of protein translation, including functional alterations in translation factors, tRNA, mRNA, and ribosome function. Deregulated translation leads to abnormal protein expression, disrupted cellular signaling, and perturbed cellular functions- all of which contribute to disease pathogenesis. The development of ribosome profiling techniques along with mass spectrometry-based proteomics, mRNA sequencing and single-cell approaches have opened new avenues for detecting diseases related to translation errors. Importantly, we highlight recent advances in therapies targeting translation-related disorders and their potential applications in neurodegenerative diseases, cancer, infectious diseases, and cardiovascular diseases. Moreover, the growing interest lies in targeted therapies aimed at restoring precise control over translation in diseased cells is discussed. In conclusion, this comprehensive review underscores the critical role of protein translation in disease and its potential as a therapeutic target. Advancements in understanding the molecular mechanisms of protein translation deregulation, coupled with the development of targeted therapies, offer promising avenues for improving disease outcomes in various human diseases. Additionally, it will unlock doors to the possibility of precision medicine by offering personalized therapies and a deeper understanding of the molecular underpinnings of diseases in the future.

Development of Cell-Free Transcription-Translation Systems in Three Soil Pseudomonads.

In vitro transcription-translation (TX-TL) can enable faster engineering of biological systems. This speed-up can be significant, especially in difficult-to-transform chassis. This work shows the successful development of TX-TL systems using three soil-derived wild-type Pseudomonads known to promote plant growth: Pseudomonas synxantha, Pseudomonas chlororaphis, and Pseudomonas aureofaciens. All three species demonstrated multiple sonication, runoff, and salt conditions producing detectable protein synthesis. One of these new TX-TL systems, P. synxantha, demonstrated a maximum protein yield of 2.5 µM at 125 proteins per DNA template, a maximum protein synthesis rate of 20 nM/min, and a range of DNA concentrations with a linear correspondence with the resulting protein synthesis. A set of different constitutive promoters driving mNeonGreen expression were tested in TX-TL and integrated into the genome, showing similar normalized strengths for in vivo and in vitro fluorescence. This correspondence between the TX-TL-derived promoter strength and the in vivo promoter strength indicates that these lysate-based cell-free systems can be used to characterize and engineer biological parts without genomic integration, enabling a faster design-build-test cycle.

Stop-Codon Readthrough in Therapeutic Protein Candidates Expressed from Mammalian Cells.

Stop codon readthroughs were examined in 48 recombinant therapeutic protein candidates produced from multiple clones of Chinese hamster ovary cells, using peptide mapping with LC-MS/MS detection. We found that stop codon readthrough is a common phenomenon occurring in most of these candidates, with levels varying from below the detection limit of ∼0.001 % to ∼1 %. The readthrough propensity depends on the stop codon being used, as well as the nucleotides surrounding it. The amino acids misincorporated into the stop position can be well-predicted by a third-base wobble mismatch and a first-base U/G mismatch during codon recognition, i.e., tyrosine or glutamine insertion for the UAA and UAG stop codons, and tryptophan, cysteine or arginine insertion for the UGA stop codon. Data shown in this report demonstrate the importance of optimizing the DNA sequence near the stop codon, and the importance of detecting stop codon readthroughs during the development of a therapeutic product.

Development and Application of the CRISPR-dcas13d-eIF4G Translational Regulatory System to Inhibit Ferroptosis in Calcium Oxalate Crystal-Induced Kidney Injury.

The CRISPR-Cas system, initially for DNA-level gene editing and transcription regulation, has expanded to RNA targeting with the Cas13d family, notably the RfxCas13d. This advancement allows for mRNA targeting with high specificity, particularly after catalytic inactivation, broadening the exploration of translation regulation. This study introduces a CRISPR-dCas13d-eIF4G fusion module, combining dCas13d with the eIF4G translation regulatory element, enhancing target mRNA translation levels. This module, using specially designed sgRNAs, selectively boosts protein translation in targeted tissue cells without altering transcription, leading to notable protein expression upregulation. This system is applied to a kidney stone disease model, focusing on ferroptosis-linked GPX4 gene regulation. By targeting GPX4 with sgRNAs, its protein expression is upregulated in human renal cells and mouse kidney tissue, countering ferroptosis and resisting calcium oxalate-induced cell damage, hence mitigating stone formation. This study evidences the CRISPR-dCas13d-eIF4G system's efficacy in eukaryotic cells, presenting a novel protein translation research approach and potential kidney stone disease treatment advancements.

Evolving precision: rRNA expansion segment 7S modulates translation velocity and accuracy in eukaryal ribosomes.

Ribosome-enhanced translational miscoding of the genetic code causes protein dysfunction and loss of cellular fitness. During evolution, open reading frame length increased, necessitating mechanisms for enhanced translation fidelity. Indeed, eukaryal ribosomes are more accurate than bacterial counterparts, despite their virtually identical, conserved active centers. During the evolution of eukaryotic organisms ribosome expansions at the rRNA and protein level occurred, which potentially increases the options for translation regulation and cotranslational events. Here we tested the hypothesis that ribosomal RNA expansions can modulate the core function of the ribosome, faithful protein synthesis. We demonstrate that a short expansion segment present in all eukaryotes' small subunit, ES7S, is crucial for accurate protein synthesis as its presence adjusts codon-specific velocities and guarantees high levels of cognate tRNA selection. Deletion of ES7S in yeast enhances mistranslation and causes protein destabilization and aggregation, dramatically reducing cellular fitness. Removal of ES7S did not alter ribosome architecture but altered the structural dynamics of inter-subunit bridges thus affecting A-tRNA selection. Exchanging the yeast ES7S sequence with the human ES7S increases accuracy whereas shortening causes the opposite effect. Our study demonstrates that ES7S provided eukaryal ribosomes with higher accuracy without perturbing the structurally conserved decoding center.

Analyzing the correlation between protein expression and sequence-related features of mRNA and protein in Escherichia coli K-12 MG1655 model.

It was necessary to have a tool that could predict the amount of protein and optimize the gene sequences to produce recombinant proteins efficiently. The Transim model published by Tuller et al. in 2018 can calculate the translation rate in E. coli using features on the mRNA sequence, achieving a Spearman correlation with the amount of protein per mRNA of 0.36 when tested on the dataset of operons' first genes in E. coli K-12 MG1655 genome. However, this Spearman correlation was not high, and the model did not fully consider the features of mRNA and protein sequences. Therefore, to enhance the prediction capability, our study firstly tried expanding the testing dataset, adding genes inside the operon, and using the microarray of the mRNA expression data set, thereby helping to improve the correlation of translation rate with the amount of protein with more than 0.42. Next, the applicability of 6 traditional machine learning models to calculate a "new translation rate" was examined using initiation rate and elongation rate as inputs. The result showed that the SVR algorithm had the most correlated new translation rates, with Spearman correlation improving to R = 0.6699 with protein level output and to R = 0.6536 with protein level per mRNA. Finally, the study investigated the degree of improvement when combining more features with the new translation rates. The results showed that the model's predictive ability to produce a protein per mRNA reached R = 0.6660 when using six features, while the correlation of this model's final translation rate to protein level was up to R = 0.6729. This demonstrated the model's capability to predict protein expression of a gene, rather than being limited to predicting expression by an mRNA and showed the model's potential for development into gene expression predicting tools.

Molecular Mechanisms and the Significance of Synonymous Mutations.

Synonymous mutations result from the degeneracy of the genetic code. Most amino acids are encoded by two or more codons, and mutations that change a codon to another synonymous codon do not change the amino acid in the gene product. Historically, such mutations have been considered silent because they were assumed to have no to very little impact. However, research in the last few decades has produced several examples where synonymous mutations play important roles. These include optimizing expression by enhancing translation initiation and accelerating or decelerating translation elongation via codon usage and mRNA secondary structures, stabilizing mRNA molecules and preventing their breakdown before translation, and faulty protein folding or increased degradation due to enhanced ubiquitination and suboptimal secretion of proteins into the appropriate cell compartments. Some consequences of synonymous mutations, such as mRNA stability, can lead to different outcomes in prokaryotes and eukaryotes. Despite these examples, the significance of synonymous mutations in evolution and in causing disease in comparison to nonsynonymous mutations that do change amino acid residues in proteins remains controversial. Whether the molecular mechanisms described by which synonymous mutations affect organisms can be generalized remains poorly understood and warrants future research in this area.

Low baseline ribosome-related gene expression and resistance training-induced declines in ribosome-related gene expression are associated with skeletal muscle hypertrophy in young men and women.

Ribosomes are essential cellular machinery for protein synthesis. It is hypothesised that ribosome content supports muscle growth and that individuals with more ribosomes have greater increases in muscle size following resistance training (RT). Aerobic conditioning (AC) also elicits distinct physiological adaptations; however, no measures of ribosome content following AC have been conducted. We used ribosome-related gene expression as a proxy measure for ribosome content and hypothesised that AC and RT would increase ribosome-related gene expression. Fourteen young men and women performed 6 weeks of single-legged AC followed by 10 weeks of double-legged RT. Muscle biopsies were taken following AC and following RT in the aerobically conditioned (AC+RT) and unconditioned (RT) legs. No differences in regulatory genes (Ubf, Cyclin D1, Tif-1a and Polr-1b) involved in ribosomal biogenesis or ribosomal RNA (45S, 5.8S, 18S and 28S rRNAs) expression were observed following AC and RT, except for c-Myc (RT > AC+RT) and 5S rRNA (RT < AC+RT at pre-RT) with 18S external transcribed spacer and 5.8S internal transcribed spacer expression decreasing from pre-RT to post-RT in the RT leg only. When divided for change in leg-lean soft tissue mass (ΔLLSTM) following RT, legs with the greatest ΔLLSTM had lower expression in 11/13 measured ribosome-related genes before RT and decreased expression in 9/13 genes following RT. These results indicate that AC and RT did not increase ribosome-related gene expression. Contrary to previous research, the greatest increase in muscle mass was associated with lower changes in ribosome-related gene expression over the course of the 10-week training programme. This may point to the importance of translational efficiency rather than translational capacity (i.e. ribosome content) in mediating long-term exercise-induced adaptations in skeletal muscle.

Improved super-resolution ribosome profiling reveals prevalent translation of upstream ORFs and small ORFs in Arabidopsis.

A crucial step in functional genomics is identifying actively translated ORFs and linking them to biological functions. The challenge lies in identifying short ORFs, as their identification is greatly influenced by data quality and depth. Here, we improved the coverage of super-resolution Ribo-seq in Arabidopsis (Arabidopsis thaliana), revealing uncharacterized translation events for nuclear, chloroplastic, and mitochondrial genes. Assisted by a transcriptome assembly, we identified 7,751 unconventional translation events, comprising 6,996 upstream ORFs (uORFs) and 209 downstream ORFs on annotated protein-coding genes, as well as 546 ORFs in presumed noncoding RNAs. Proteomic data confirmed the production of stable proteins from some of these unannotated translation events. We present evidence of active translation from primary transcripts of trans-acting small interfering RNAs (TAS1-4) and microRNAs (pri-MIR163 and pri-MIR169) and periodic ribosome stalling supporting cotranslational decay. Additionally, we developed a method for identifying extremely short uORFs, including 370 minimum uORFs (AUG-stop), and 2,921 tiny uORFs (2 to 10 amino acids) and 681 uORFs that overlap with each other. Remarkably, these short uORFs exhibit strong translational repression as do longer uORFs. We also systematically discovered 594 uORFs regulated by alternative splicing, suggesting widespread isoform-specific translational control. Finally, these prevalent uORFs are associated with numerous important pathways. In summary, our improved Arabidopsis translational landscape provides valuable resources to study gene expression regulation.

Co-translational Assembly Pathways of Nuclear Multiprotein Complexes Involved in the Regulation of Gene Transcription.

Most factors that regulate gene transcription in eukaryotic cells are multimeric, often large, protein complexes. The understanding of the biogenesis pathways of such large and heterogeneous protein assemblies, as well as the dimerization partner choice among transcription factors, is crucial to interpret and control gene expression programs and consequent cell fate decisions. Co-translational assembly (Co-TA) is thought to play key roles in the biogenesis of protein complexes by directing complex formation during protein synthesis. In this review we discuss the principles of Co-TA with a special focus for the assembly of transcription regulatory complexes. We outline the expected molecular advantages of establishing co-translational interactions, pointing at the available, or missing, evidence for each of them. We hypothesize different molecular mechanisms based on Co-TA to explain the allocation "dilemma" of paralog proteins and subunits shared by different transcription complexes. By taking as a paradigm the different assembly pathways employed by three related transcription regulatory complexes (TFIID, SAGA and ATAC), we discuss alternative Co-TA strategies for nuclear multiprotein complexes and the widespread - yet specific - use of Co-TA for the formation of nuclear complexes involved in gene transcription. Ultimately, we outlined a series of open questions which demand well-defined lines of research to investigate the principles of gene regulation that rely on the coordinated assembly of protein complexes.