Deciphering the rules by which 5'-UTR sequences affect protein expression in yeast

The regulatory landscape of 5' UTRs in translational control during zebrafish embryogenesis

The 5' UTRs of mRNAs are critical for translation regulation during development, but their in vivo regulatory features are poorly characterized. Here, we report the regulatory landscape of 5' UTRs during early zebrafish embryogenesis using a massively parallel reporter assay of 18,154 sequences coupled to polysome profiling. We found that the 5' UTR suffices to confer temporal dynamics to translation initiation and identified 86 motifs enriched in 5' UTRs with distinct ribosome recruitment capabilities. A quantitative deep learning model, Danio Optimus 5-Prime (DaniO5P), identified a combined role for 5' UTR length, translation initiation site context, upstream AUGs, and sequence motifs on ribosome recruitment. DaniO5P predicts the activities of maternal and zygotic 5' UTR isoforms and indicates that modulating 5' UTR length and motif grammar contributes to translation initiation dynamics. This study provides a first quantitative model of 5' UTR-based translation regulation in development and lays the foundation for identifying the underlying molecular effectors.

Deciphering disordered regions controlling mRNA decay in high-throughput

Intrinsically disordered regions within proteins drive specific molecular functions despite lacking a defined structure1,2. Although disordered regions are integral to controlling mRNA stability and translation, the mechanisms underlying these regulatory effects remain unclear3. Here we reveal the molecular determinants of this activity using high-throughput functional profiling. Systematic mutagenesis across hundreds of regulatory disordered elements, combined with machine learning, reveals a complex pattern of molecular features important for their activity. The presence and arrangement of aromatic residues strongly predicts the ability of seemingly diverse protein sequences to influence mRNA stability and translation. We further show how many of these regulatory elements exert their effects by engaging core mRNA decay machinery. Our results define molecular features and biochemical pathways that explain how disordered regions control mRNA expression and shed light on broader principles within functional, unstructured proteins.

Deciphering the landscape of cis-acting sequences in natural yeast transcript leaders

Protein synthesis is a vital process that is highly regulated at the initiation step of translation. Eukaryotic 5' transcript leaders (TLs) contain a variety of cis-acting features that influence translation and messenger RNA stability. However, the relative influences of these features in natural TLs are poorly characterized. To address this, we used massively parallel reporter assays (MPRAs) to quantify RNA levels, ribosome loading, and protein levels from 11,027 natural yeast TLs in vivo and systematically compared the relative impacts of their sequence features on gene expression. We found that yeast TLs influence gene expression over two orders of magnitude. While a leaky scanning model using Kozak contexts (-4 to +1 around the AUG start) and upstream AUGs (uAUGs) explained half of the variance in expression across TLs, the addition of other features explained ∼80% of gene expression variation. Our analyses detected key cis-acting sequence features, quantified their effects in vivo, and compared their roles to motifs reported from an in vitro study of ribosome recruitment. In addition, our work quantitated the effects of alternative transcription start site usage on gene expression in yeast. Thus, our study provides new quantitative insights into the roles of TL cis-acting sequences in regulating gene expression.

NaP-TRAP reveals the regulatory grammar in 5'UTR-mediated translation regulation during zebrafish development

The cis-regulatory elements encoded in an mRNA determine its stability and translational output. While there has been a considerable effort to understand the factors driving mRNA stability, the regulatory frameworks governing translational control remain more elusive. We have developed a novel massively parallel reporter assay (MPRA) to measure mRNA translation, named Nascent Peptide Translating Ribosome Affinity Purification (NaP-TRAP). NaP-TRAP measures translation in a frame-specific manner through the immunocapture of epitope tagged nascent peptides of reporter mRNAs. We benchmark NaP-TRAP to polysome profiling and use it to quantify Kozak strength and the regulatory landscapes of 5' UTRs in the developing zebrafish embryo and in human cells. Through this approach we identified general and developmentally dynamic cis-regulatory elements, as well as potential trans-acting proteins. We find that U-rich motifs are general enhancers, and upstream ORFs and GC-rich motifs are global repressors of translation. We also observe a translational switch during the maternal-to-zygotic transition, where C-rich motifs shift from repressors to prominent activators of translation. Conversely, we show that microRNA sites in the 5' UTR repress translation following the zygotic expression of miR-430. Together these results demonstrate that NaP-TRAP is a versatile, accessible, and powerful method to decode the regulatory functions of UTRs across different systems.

Designing strong inducible synthetic promoters in yeasts

Inducible promoters are essential for precise control of target gene expression in synthetic biological systems. However, engineering eukaryotic promoters is often more challenging than engineering prokaryotic promoters due to their greater mechanistic complexity. In this study, we describe a simple and reliable approach for constructing strongly inducible synthetic promoters with minimum leakiness in yeasts. The results indicate that the leakiness of yeast-inducible synthetic promoters is primarily the result of cryptic transcriptional activation of heterologous sequences that may be avoided by appropriate insulation and operator mutagenesis. Our promoter design approach has successfully generated robust, inducible promoters that achieve a > 103-fold induction in reporter gene expression. The utility of these promoters is demonstrated by using them to produce various biologics with titers up to 2 g/L, including antigens designed to raise specific antibodies against a SARS-CoV-2 omicron variant through chicken immunization.

A strategy for successful dual-species protein expression of genes with non-optimal codon usage destined for bacterial and yeast cell factories

Recombinant protein expression on an industrial scale traditionally utilizes one of two microbial workhorses: Escherichia coli or Saccharomyces cerevisiae. Additionally, random protein engineering of enzymes and proteins aimed for expression in S. cerevisiae are often mutagenized and pre-screened in E. coli before expression in yeast. This introduces artificial bottlenecks as the bacterial expression vector needs to be substituted for a yeast expression vector via sub-cloning, and the new library re-evaluated before a final screening in yeast. Here, we put forward a protein expression and engineering strategy that involves the use of a dual-host shuttle vector (pYB-Dual) designed with both a strong inducible yeast promoter (pGAL1), and a strong inducible bacterial promoter (pT7-RNAP), which allows for inducible protein expression in both species. Additionally, we demonstrate that by transforming the pYB-Dual vector into the E. coli strain Rosetta 2, which has elevated levels of 7 rare tRNAs, we can achieve high-level protein expression in both yeast and bacteria, even when using a mNeonGreen gene codon optimized for yeast. This dual expression vector is expected to remove bottlenecks during protein engineering of commercially important enzymes destined for high-titer expression in yeast.

Decoding biology with massively parallel reporter assays and machine learning

Massively parallel reporter assays (MPRAs) are powerful tools for quantifying the impacts of sequence variation on gene expression. Reading out molecular phenotypes with sequencing enables interrogating the impact of sequence variation beyond genome scale. Machine learning models integrate and codify information learned from MPRAs and enable generalization by predicting sequences outside the training data set. Models can provide a quantitative understanding of cis-regulatory codes controlling gene expression, enable variant stratification, and guide the design of synthetic regulatory elements for applications from synthetic biology to mRNA and gene therapy. This review focuses on cis-regulatory MPRAs, particularly those that interrogate cotranscriptional and post-transcriptional processes: alternative splicing, cleavage and polyadenylation, translation, and mRNA decay.

Optimization of extended Kozak elements enhances recombinant proteins expression in CHO cells

In eukaryotes, the localization of small ribosomal subunits to mRNA transcripts requires the translation of Kozak elements at the starting site. The sequence of Kozak elements affects the translation efficiency of protein synthesis. However, whether the upstream nucleotide of Kozak sequence affects the expression of recombinant proteins in Chinese hamster ovary (CHO) cells remains unclear. In order to find the optimal sequence to enhance recombinant proteins expression in CHO cells, -10 to +4 sequences around ATG in 100 CHO genes were compared, and the extended Kozak elements with different translation intensities were constructed. Using the classic Kozak element as control, the effects of optimized extended Kozak elements on the secreted alkaline phosphatase (SEAP) and human serum albumin (HSA) gene were studied. The results showed that the optimized extended Kozak sequence can enhance the stable expression level of recombinant proteins in CHO cells. Furthermore, it was found that the increased expression level of the recombinant protein was not related with higher transcription level. In summary, optimizing extended Kozak elements can enhance the expression of recombinant proteins in CHO cells, which contributes to the construction of an efficient expression system for CHO cells.

High-throughput identification of functional regulatory SNPs in systemic lupus erythematosus

Genome-wide association studies implicate multiple loci in risk for systemic lupus erythematosus (SLE), but few contain exonic variants, rendering systematic identification of non-coding variants essential to decoding SLE genetics. We utilized SNP-seq and bioinformatic enrichment to interrogate 2180 single-nucleotide polymorphisms (SNPs) from 87 SLE risk loci for potential binding of transcription factors and related proteins from B cells. 52 SNPs that passed initial screening were tested by electrophoretic mobility shift and luciferase reporter assays. To validate the approach, we studied rs2297550 in detail, finding that the risk allele enhanced binding to the transcription factor Ikaros (encoded by IKZF1), thereby modulating expression of IKBKE. Correspondingly, primary cells from genotyped healthy donors bearing the risk allele expressed higher levels of the interferon / NF-κB regulator IKKε. Together, these findings define a set of likely functional non-coding lupus risk variants and identify a regulatory pathway involving rs2297550, Ikaros, and IKKε implicated by human genetics in risk for SLE.

Deciphering the cis-regulatory landscape of natural yeast Transcript Leaders

Protein synthesis is a vital process that is highly regulated at the initiation step of translation. Eukaryotic 5' transcript leaders (TLs) contain a variety of cis-regulatory features that influence translation and mRNA stability. However, the relative influences of these features in natural TLs are poorly characterized. To address this, we used massively parallel reporter assays (MPRAs) to quantify RNA levels, ribosome loading, and protein levels from 11,027 natural yeast TLs in vivo and systematically compared the relative impacts of their sequence features on gene expression. We found that yeast TLs influence gene expression over two orders of magnitude. While a leaky scanning model using Kozak contexts and uAUGs explained half of the variance in expression across transcript leaders, the addition of other features explained ~70% of gene expression variation. Our analyses detected key cis-acting sequence features, quantified their effects in vivo, and compared their roles to motifs reported from an in vitro study of ribosome recruitment. In addition, our work quantitated the effects of alternative transcription start site usage on gene expression in yeast. Thus, our study provides new quantitative insights into the roles of TL cis-acting sequences in regulating gene expression.

eIF4F complex dynamics are important for the activation of the integrated stress response

In response to stress, eukaryotes activate the integrated stress response (ISR) via phosphorylation of eIF2α to promote the translation of pro-survival effector genes, such as GCN4 in yeast. Complementing the ISR is the target of rapamycin (TOR) pathway, which regulates eIF4E function. Here, we probe translational control in the absence of eIF4E in Saccharomyces cerevisiae. Intriguingly, we find that loss of eIF4E leads to de-repression of GCN4 translation. In addition, we find that de-repression of GCN4 translation is accompanied by neither eIF2α phosphorylation nor reduction in initiator ternary complex (TC). Our data suggest that when eIF4E levels are depleted, GCN4 translation is de-repressed via a unique mechanism that may involve faster scanning by the small ribosome subunit due to increased local concentration of eIF4A. Overall, our findings suggest that relative levels of eIF4F components are key to ribosome dynamics and may play important roles in translational control of gene expression.

High-throughput identification of functional regulatory SNPs in systemic lupus erythematosus

Genome-wide association studies implicate multiple loci in risk for systemic lupus erythematosus (SLE), but few contain exonic variants, rendering systematic identification of non-coding variants essential to decoding SLE genetics. We utilized SNP-seq and bioinformatic enrichment to interrogate 2180 single-nucleotide polymorphisms (SNPs) from 87 SLE risk loci for potential binding of transcription factors and related proteins from B cells. 52 SNPs that passed initial screening were tested by electrophoretic mobility shift and luciferase reporter assays. To validate the approach, we studied rs2297550 in detail, finding that the risk allele enhanced binding to the transcription factor Ikaros (IKZF1), thereby modulating expression of IKBKE. Correspondingly, primary cells from genotyped healthy donors bearing the risk allele expressed higher levels of the interferon / NF-κB regulator IKKϵ. Together, these findings define a set of likely functional non-coding lupus risk variants and identify a new regulatory pathway involving rs2297550, Ikaros, and IKKϵ implicated by human genetics in risk for SLE.

Functional analysis of the AUG initiator codon context reveals novel conserved sequences that disfavor mRNA translation in eukaryotes

mRNA translation is a fundamental process for life. Selection of the translation initiation site (TIS) is crucial, as it establishes the correct open reading frame for mRNA decoding. Studies in vertebrate mRNAs discovered that a purine at -3 and a G at +4 (where A of the AUG initiator codon is numbered + 1), promote TIS recognition. However, the TIS context in other eukaryotes has been poorly experimentally analyzed. We analyzed in vitro the influence of the -3, -2, -1 and + 4 positions of the TIS context in rabbit, Drosophila, wheat, and yeast. We observed that -3A conferred the best translational efficiency across these species. However, we found variability at the + 4 position for optimal translation. In addition, the Kozak motif that was defined from mammalian cells was only weakly predictive for wheat and essentially non-predictive for yeast. We discovered eight conserved sequences that significantly disfavored translation. Due to the big differences in translational efficiency observed among weak TIS context sequences, we define a novel category that we termed 'barren AUG context sequences (BACS)', which represent sequences disfavoring translation. Analysis of mRNA-ribosomal complexes structures provided insights into the function of BACS. The gene ontology of the BACS-containing mRNAs is presented.

Vo N, Nguyen BT, Huynh ST, Nguyen HD. 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.

Combinatorial optimization of gene expression through recombinase-mediated promoter and terminator shuffling in yeast

Microbes are increasingly employed as cell factories to produce biomolecules. This often involves the expression of complex heterologous biosynthesis pathways in host strains. Achieving maximal product yields and avoiding build-up of (toxic) intermediates requires balanced expression of every pathway gene. However, despite progress in metabolic modeling, the optimization of gene expression still heavily relies on trial-and-error. Here, we report an approach for in vivo, multiplexed Gene Expression Modification by LoxPsym-Cre Recombination (GEMbLeR). GEMbLeR exploits orthogonal LoxPsym sites to independently shuffle promoter and terminator modules at distinct genomic loci. This approach facilitates creation of large strain libraries, in which expression of every pathway gene ranges over 120-fold and each strain harbors a unique expression profile. When applied to the biosynthetic pathway of astaxanthin, an industrially relevant antioxidant, a single round of GEMbLeR improved pathway flux and doubled production titers. Together, this shows that GEMbLeR allows rapid and efficient gene expression optimization in heterologous biosynthetic pathways, offering possibilities for enhancing the performance of microbial cell factories.

Defining the mechanisms and properties of post-transcriptional regulatory disordered regions by high-throughput functional profiling

Disordered regions within RNA binding proteins are required to control mRNA decay and protein synthesis. To understand how these disordered regions modulate gene expression, we surveyed regulatory activity across the entire disordered proteome using a high-throughput functional assay. We identified hundreds of regulatory sequences within intrinsically disordered regions and demonstrate how these elements cooperate with core mRNA decay machinery to promote transcript turnover. Coupling high-throughput functional profiling with mutational scanning revealed diverse molecular features, ranging from defined motifs to overall sequence composition, underlying the regulatory effects of disordered peptides. Machine learning analysis implicated aromatic residues in particular contexts as critical determinants of repressor activity, consistent with their roles in forming protein-protein interactions with downstream effectors. Our results define the molecular principles and biochemical mechanisms that govern post-transcriptional gene regulation by disordered regions and exemplify the encoding of diverse yet specific functions in the absence of well-defined structure.

Characterization and optimization of 5´ untranslated region containing poly-adenine tracts in Kluyveromyces marxianus using machine-learning model

BACKGROUND

The 5´ untranslated region (5´ UTR) plays a key role in regulating translation efficiency and mRNA stability, making it a favored target in genetic engineering and synthetic biology. A common feature found in the 5´ UTR is the poly-adenine (poly(A)) tract. However, the effect of 5´ UTR poly(A) on protein production remains controversial. Machine-learning models are powerful tools for explaining the complex contributions of features, but models incorporating features of 5´ UTR poly(A) are currently lacking. Thus, our goal is to construct such a model, using natural 5´ UTRs from Kluyveromyces marxianus, a promising cell factory for producing heterologous proteins.

RESULTS

We constructed a mini-library consisting of 207 5´ UTRs harboring poly(A) and 34 5´ UTRs without poly(A) from K. marxianus. The effects of each 5´ UTR on the production of a GFP reporter were evaluated individually in vivo, and the resulting protein abundance spanned an approximately 450-fold range throughout. The data were used to train a multi-layer perceptron neural network (MLP-NN) model that incorporated the length and position of poly(A) as features. The model exhibited good performance in predicting protein abundance (average R2 = 0.7290). The model suggests that the length of poly(A) is negatively correlated with protein production, whereas poly(A) located between 10 and 30 nt upstream of the start codon (AUG) exhibits a weak positive effect on protein abundance. Using the model as guidance, the deletion or reduction of poly(A) upstream of 30 nt preceding AUG tended to improve the production of GFP and a feruloyl esterase. Deletions of poly(A) showed inconsistent effects on mRNA levels, suggesting that poly(A) represses protein production either with or without reducing mRNA levels.

CONCLUSION

The effects of poly(A) on protein production depend on its length and position. Integrating poly(A) features into machine-learning models improves simulation accuracy. Deleting or reducing poly(A) upstream of 30 nt preceding AUG tends to enhance protein production. This optimization strategy can be applied to enhance the yield of K. marxianus and other microbial cell factories.

Discovery of regulatory motifs in 5' untranslated regions using interpretable multi-task learning models

The sequence in the 5' untranslated regions (UTRs) is known to affect mRNA translation rates. However, the underlying regulatory grammar remains elusive. Here, we propose MTtrans, a multi-task translation rate predictor capable of learning common sequence patterns from datasets across various experimental techniques. The core premise is that common motifs are more likely to be genuinely involved in translation control. MTtrans outperforms existing methods in both accuracy and the ability to capture transferable motifs across species, highlighting its strength in identifying evolutionarily conserved sequence motifs. Our independent fluorescence-activated cell sorting coupled with deep sequencing (FACS-seq) experiment validates the impact of most motifs identified by MTtrans. Additionally, we introduce "GRU-rewiring," a technique to interpret the hidden states of the recurrent units. Gated recurrent unit (GRU)-rewiring allows us to identify regulatory element-enriched positions and examine the local effects of 5' UTR mutations. MTtrans is a powerful tool for deciphering the translation regulatory motifs.

Decoding stoichiometric protein synthesis in E. coli through translation rate parameters

E. coli is one of the most widely used organisms for understanding the principles of cellular and molecular genetics. However, we are yet to understand the origin of several experimental observations related to the regulation of gene expression in E. coli. One of the prominent examples in this context is the proportional synthesis in multiprotein complexes where all of their obligate subunits are produced in proportion to their stoichiometry. In this work, by combining the next-generation sequencing data with the stochastic simulations of protein synthesis, we explain the origin of proportional protein synthesis in multicomponent complexes. We find that the estimated initiation rates for the translation of all subunits in those complexes are proportional to their stoichiometry. This constraint on protein synthesis kinetics enforces proportional protein synthesis without requiring any feedback mechanism. We also find that the translation initiation rates in E. coli are influenced by the coding sequence length and the enrichment of A and C nucleotides near the start codon. Thus, this study rationalizes the role of conserved and nonrandom features of genes in regulating the translation kinetics and unravels a key principle of the regulation of protein synthesis.

The regulatory landscape of 5' UTRs in translational control during zebrafish embryogenesis

The 5' UTRs of mRNAs are critical for translation regulation, but their in vivo regulatory features are poorly characterized. Here, we report the regulatory landscape of 5' UTRs during early zebrafish embryogenesis using a massively parallel reporter assay of 18,154 sequences coupled to polysome profiling. We found that the 5' UTR is sufficient to confer temporal dynamics to translation initiation, and identified 86 motifs enriched in 5' UTRs with distinct ribosome recruitment capabilities. A quantitative deep learning model, DaniO5P, revealed a combined role for 5' UTR length, translation initiation site context, upstream AUGs and sequence motifs on in vivo ribosome recruitment. DaniO5P predicts the activities of 5' UTR isoforms and indicates that modulating 5' UTR length and motif grammar contributes to translation initiation dynamics. This study provides a first quantitative model of 5' UTR-based translation regulation in early vertebrate development and lays the foundation for identifying the underlying molecular effectors.

Ovine KRTAP36-2: A New Keratin-Associated Protein Gene Related to Variation in Wool Yield

Keratin-associated proteins (KAPs) are structural components of wool fibres. High-glycine/tyrosine (HGT)-KAPs are a subset of the KAP family, and their abundance in fibres varies. In this study, we report the discovery of an ovine HGT-KAP gene to which we assigned the name KRTAP36-2. Polymerase chain reaction and single-strand conformation polymorphism (PCR-SSCP) analyses revealed four variants of this gene in a screening population of 170 sheep from a variety of breeds. The DNA sequencing of the variants revealed four single-nucleotide polymorphisms (SNPs) and a dinucleotide deletion. Three of these SNPs were in the coding region, and one of these was non-synonymous and potentially led to the amino acid substitution p.Cys27Gly near the middle of the protein. The remaining SNP was located near the putative TATA box, and the di-nucleotide deletion was near the putative transcription initiation site. The effect of this variation in KRTAP36-2 was investigated in 274 Southdown × Merino lambs that were the progeny of five sires. Variation was only found to be associated with wool yield, that is, the proportion of the greasy fleece that remained as clean fleece upon scouring (expressed as a percentage). This may have some value in increasing wool production.

Dual Role of Dysfunctional Asc-1 Transporter in Distinct Human Pathologies, Human Startle Disease, and Developmental Delay

Human startle disease is associated with mutations in distinct genes encoding glycine receptors, transporters or interacting proteins at glycinergic synapses in spinal cord and brainstem. However, a significant number of diagnosed patients does not carry a mutation in the common genes GLRA1, GLRB, and SLC6A5 Recently, studies on solute carrier 7 subfamily 10 (SLC7A10; Asc-1, alanine-serine-cysteine transporter) knock-out (KO) mice displaying a startle disease-like phenotype hypothesized that this transporter might represent a novel candidate for human startle disease. Here, we screened 51 patients from our patient cohort negative for the common genes and found three exonic (one missense, two synonymous), seven intronic, and single nucleotide changes in the 5' and 3' untranslated regions (UTRs) in Asc-1. The identified missense mutation Asc-1G307R from a patient with startle disease and developmental delay was investigated in functional studies. At the molecular level, the mutation Asc-1G307R did not interfere with cell-surface expression, but disrupted glycine uptake. Substitution of glycine at position 307 to other amino acids, e.g., to alanine or tryptophan did not affect trafficking or glycine transport. By contrast, G307K disrupted glycine transport similar to the G307R mutation found in the patient. Structurally, the disrupted function in variants carrying positively charged residues can be explained by local structural rearrangements because of the large positively charged side chain. Thus, our data suggest that SLC7A10 may represent a rare but novel gene associated with human startle disease and developmental delay.

Exploring the adaptability of the secondary structure of mRNA to temperature in intertidal snails based on SHAPE experiments

RNA-based thermal regulation is an important strategy for organisms to cope with temperature changes. Inhabiting the intertidal rocky shore, a key interface of the ocean, atmosphere and terrestrial environments, intertidal species have developed variable thermal adaptation mechanisms; however, adaptions at the RNA level remain largely uninvestigated. To examine the relationship between mRNA structural stability and species distribution, in the present study, the secondary structure of cytosolic malate dehydrogenase (cMDH) mRNA of Echinolittorina malaccana, Echinolittorina radiata and Littorina brevicula was determined using selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE), and the change in folding free energy of formation (ΔGfold) was calculated. The results showed that ΔGfold increased as the temperature increased. The difference in ΔGfold (ΔΔGfold) between two specific temperatures (25 versus 0°C, 37 versus 0°C and 57 versus 0°C) differed among the three species, and the ΔΔGfold value of E. malaccana was significantly lower than those of E. radiata and L. brevicula. The number of stems of cMDH mRNA of the snails decreased with increasing temperature, and the breakpoint temperature of E. malaccana was the highest among these. The number of loops was also reduced with increasing temperature, while the length of the loop structure increased accordingly. Consequently, these structural changes can potentially affect the translational efficiency of mRNA. These results imply that there were interspecific differences in the thermal stability of RNA secondary structures in intertidal snails, and these differences may be related to snail distribution.

Translation factor and RNA binding protein mRNA interactomes support broader RNA regulons for posttranscriptional control

The regulation of translation provides a rapid and direct mechanism to modulate the cellular proteome. In eukaryotes, an established model for the recruitment of ribosomes to mRNA depends upon a set of conserved translation initiation factors. Nevertheless, how cells orchestrate and define the selection of individual mRNAs for translation, as opposed to other potential cytosolic fates, is poorly understood. We have previously found significant variation in the interaction between individual mRNAs and an array of translation initiation factors. Indeed, mRNAs can be separated into different classes based upon these interactions to provide a framework for understanding different modes of translation initiation. Here, we extend this approach to include new mRNA interaction profiles for additional proteins involved in shaping the cytoplasmic fate of mRNAs. This work defines a set of seven mRNA clusters, based on their interaction profiles with 12 factors involved in translation and/or RNA binding. The mRNA clusters share both physical and functional characteristics to provide a rationale for the interaction profiles. Moreover, a comparison with mRNA interaction profiles from a host of RNA binding proteins suggests that there are defined patterns in the interactions of functionally related mRNAs. Therefore, this work defines global cytoplasmic mRNA binding modules that likely coordinate the synthesis of functionally related proteins.

Using Synthetic DNA Libraries to Investigate Chromatin and Gene Regulation

Despite the recent explosion in genome-wide studies in chromatin and gene regulation, we are still far from extracting a set of genetic rules that can predict the function of the regulatory genome. One major reason for this deficiency is that gene regulation is a multi-layered process that involves an enormous variable space, which cannot be fully explored using native genomes. This problem can be partially solved by introducing synthetic DNA libraries into cells, a method that can test the regulatory roles of thousands to millions of sequences with limited variables. Here, we review recent applications of this method to study transcription factor (TF) binding, nucleosome positioning, and transcriptional activity. We discuss the design principles, experimental procedures, and major findings from these studies and compare the pros and cons of different approaches.

Evaluating single-cell variability in proteasomal decay

Gene expression is a stochastic process that leads to variability in mRNA and protein abundances even within an isogenic population of cells grown in the same environment. This variation, often called gene-expression noise, has typically been attributed to transcriptional and translational processes while ignoring the contributions of protein decay variability across cells. Here we estimate the single-cell protein decay rates of two degron GFPs in Saccharomyces cerevisiae using time-lapse microscopy. We find substantial cell-to-cell variability in the decay rates of the degron GFPs. We evaluate cellular features that explain the variability in the proteasomal decay and find that the amount of 20s catalytic beta subunit of the proteasome marginally explains the observed variability in the degron GFP half-lives. We propose alternate hypotheses that might explain the observed variability in the decay of the two degron GFPs. Overall, our study highlights the importance of studying the kinetics of the decay process at single-cell resolution and that decay rates vary at the single-cell level, and that the decay process is stochastic. A complex model of decay dynamics must be included when modeling stochastic gene expression to estimate gene expression noise.

Unraveling the influences of sequence and position on yeast uORF activity using massively parallel reporter systems and machine learning

Upstream open-reading frames (uORFs) are potent cis-acting regulators of mRNA translation and nonsense-mediated decay (NMD). While both AUG- and non-AUG initiated uORFs are ubiquitous in ribosome profiling studies, few uORFs have been experimentally tested. Consequently, the relative influences of sequence, structural, and positional features on uORF activity have not been determined. We quantified thousands of yeast uORFs using massively parallel reporter assays in wildtype and ∆upf1 yeast. While nearly all AUG uORFs were robust repressors, most non-AUG uORFs had relatively weak impacts on expression. Machine learning regression modeling revealed that both uORF sequences and locations within transcript leaders predict their effect on gene expression. Indeed, alternative transcription start sites highly influenced uORF activity. These results define the scope of natural uORF activity, identify features associated with translational repression and NMD, and suggest that the locations of uORFs in transcript leaders are nearly as predictive as uORF sequences.

Distance-dependent inhibition of translation initiation by downstream out-of-frame AUGs is consistent with a Brownian ratchet process of ribosome scanning

BACKGROUND

Eukaryotic ribosomes are widely presumed to scan mRNA for the AUG codon to initiate translation in a strictly 5'-3' movement (i.e., strictly unidirectional scanning model), so that ribosomes initiate translation exclusively at the 5' proximal AUG codon (i.e., the first-AUG rule).

RESULTS

We generate 13,437 yeast variants, each with an ATG triplet placed downstream (dATGs) of the annotated ATG (aATG) codon of a green fluorescent protein. We find that out-of-frame dATGs can inhibit translation at the aATG, but with diminishing strength over increasing distance between aATG and dATG, undetectable beyond ~17 nt. This phenomenon is best explained by a Brownian ratchet mechanism of ribosome scanning, in which the ribosome uses small-amplitude 5'-3' and 3'-5' oscillations with a net 5'-3' movement to scan the AUG codon, thereby leading to competition for translation initiation between aAUG and a proximal dAUG. This scanning model further predicts that the inhibitory effect induced by an out-of-frame upstream AUG triplet (uAUG) will diminish as uAUG approaches aAUG, which is indeed observed among the 15,586 uATG variants generated in this study. Computational simulations suggest that each triplet is scanned back and forth approximately ten times until the ribosome eventually migrates to downstream regions. Moreover, this scanning process could constrain the evolution of sequences downstream of the aATG to minimize proximal out-of-frame dATG triplets in yeast and humans.

CONCLUSIONS

Collectively, our findings uncover the basic process by which eukaryotic ribosomes scan for initiation codons, and how this process could shape eukaryotic genome evolution.

YMLA: A comparative platform to carry out functional enrichment analysis for multiple gene lists in yeast

Comparative analysis among multiple gene lists on their functional features is now a routine task due to the advancement of high-throughput experiments. Several enrichment analysis tools were developed in the past. However, these tools mainly focus on one gene list and contain only gene ontology or interaction features. What makes it worse, comparative investigation and customized feature set reanalysis are still unavailable. Therefore, we constructed the YMLA (Yeast Multiple List Analyzer) platform in this research. YMLA includes 39 yeast features and facilitates comparative analysis among multiple gene lists via tabular views, heatmaps, and network plots. Moreover, the customized feature set reanalysis function was implemented in YMLA to help form mechanism hypotheses based on a selected enriched feature subset. We demonstrated the biological applicability of YMLA via example lists consisting of genes with top/bottom translation efficiency values. The analysis results provided by YMLA reveal novel facts consistent with previous experiments. YMLA is available at https://cosbi7.ee.ncku.edu.tw/YMLA/.

mRNA 5' terminal sequences drive 200-fold differences in expression through effects on synthesis, translation and decay

mRNA regulatory sequences control gene expression at multiple levels including translation initiation and mRNA decay. The 5' terminal sequences of mRNAs have unique regulatory potential because of their proximity to key post-transcriptional regulators. Here we have systematically probed the function of 5' terminal sequences in gene expression in human cells. Using a library of reporter mRNAs initiating with all possible 7-mer sequences at their 5' ends, we find an unexpected impact on transcription that underlies 200-fold differences in mRNA expression. Library sequences that promote high levels of transcription mirrored those found in native mRNAs and define two basic classes with similarities to classic Initiator (Inr) and TCT core promoter motifs. By comparing transcription, translation and decay rates, we identify sequences that are optimized for both efficient transcription and growth-regulated translation and stability, including variants of terminal oligopyrimidine (TOP) motifs. We further show that 5' sequences of endogenous mRNAs are enriched for multi-functional TCT/TOP hybrid sequences. Together, our results reveal how 5' sequences define two general classes of mRNAs with distinct growth-responsive profiles of expression across synthesis, translation and decay.

5′ Untranslated mRNA Regions Allow Bypass of Host Cell Translation Inhibition by Legionella pneumophila

Legionella pneumophila grows within membrane-bound vacuoles in alveolar macrophages during human disease. Pathogen manipulation of the host cell is driven by bacterial proteins translocated through a type IV secretion system (T4SS).

Genetic engineering and raising temperature enhance recombinant protein production with the cdna1 promoter in Trichoderma reesei

The fungus Trichoderma reesei is a powerful host for secreted production of proteins. The promoter of cdna1 gene, which encodes a small basic protein of unknown function and high expression, is commonly used for constitutive protein production in T. reesei. Nevertheless, the production level of proteins driven by this promoter still needs to be improved. Here, we identified that the region 600- to 700-bp upstream of the start codon is critical for the efficiency of the cdna1 promoter. Increasing the copy number of this region to three improved the production of a heterologous β-mannanase by 37.5%. Screening of several stressful conditions revealed that the cdna1 promoter is heat inducible. Cultivation at 37 °C significantly enhanced the production of β-mannanase as well as a polygalacturonase with the cdna1 promoter compared with those at 30 °C. Combing the strategies of promoter engineering, multi-copy gene insertion, and control of cultivation temperature, β-mannanase of 199.85 U/mL and relatively high purity was produced in shake flask, which was 6.6 times higher than that before optimization. Taken together, the results advance the understanding of the widely used cdna1 promoter and provide effective strategies for enhancing the production of recombinant proteins in T. reesei.

The relationship of mRNA with protein expression in CD8+ T cells associates with gene class and gene characteristics

T cells are key players in our defence against infections and malignancies. When T cells differentiate or become activated, they undergo substantial alterations in gene expression. Even though RNA expression levels are now well documented throughout different stages of T cells, it is not well understood how mRNA expression translates into the protein landscape. By combining paired RNA sequencing and mass spectrometry data of primary human CD8+ T cells, we report that mRNA expression is a poor proxy for the overall protein output, irrespective of the differentiation or activation status. Yet, gene class stratification revealed a function-specific correlation of mRNA with protein expression. This gene class-specific expression pattern associated with differences in gene characteristics such as sequence conservation and untranslated region (UTR) lengths. In addition, the presence of AU-rich elements in the 3'UTR associated with alterations in mRNA and protein abundance T cell activation dependent, gene class-specific manner. In conclusion, our study highlights the role of gene characteristics as a determinant for gene expression in T cells.

Translational buffering by ribosome stalling in upstream open reading frames

Upstream open reading frames (uORFs) are present in over half of all human mRNAs. uORFs can potently regulate the translation of downstream open reading frames through several mechanisms: siphoning away scanning ribosomes, regulating re-initiation, and allowing interactions between scanning and elongating ribosomes. However, the consequences of these different mechanisms for the regulation of protein expression remain incompletely understood. Here, we performed systematic measurements on the uORF-containing 5' UTR of the cytomegaloviral UL4 mRNA to test alternative models of uORF-mediated regulation in human cells. We find that a terminal diproline-dependent elongating ribosome stall in the UL4 uORF prevents decreases in main ORF protein expression when ribosome loading onto the mRNA is reduced. This uORF-mediated buffering is insensitive to the location of the ribosome stall along the uORF. Computational kinetic modeling based on our measurements suggests that scanning ribosomes dissociate rather than queue when they collide with stalled elongating ribosomes within the UL4 uORF. We identify several human uORFs that repress main ORF protein expression via a similar terminal diproline motif. We propose that ribosome stalls in uORFs provide a general mechanism for buffering against reductions in main ORF translation during stress and developmental transitions.

Tuning heterologous glucan biosynthesis in yeast to understand and exploit plant starch diversity

Background

Starch, a vital plant-derived polysaccharide comprised of branched glucans, is essential in nutrition and many industrial applications. Starch is often modified post-extraction to alter its structure and enhance its functionality. Targeted metabolic engineering of crops to produce valuable and versatile starches requires knowledge of the relationships between starch biosynthesis, structure, and properties, but systematic studies to obtain this knowledge are difficult to conduct in plants. Here we used Saccharomyces cerevisiae as a testbed to dissect the functions of plant starch biosynthetic enzymes and create diverse starch-like polymers.

Results

We explored yeast promoters and terminators to tune the expression levels of the starch-biosynthesis machinery from Arabidopsis thaliana. We systematically modulated the expression of each starch synthase (SS) together with a branching enzyme (BE) in yeast. Protein quantification by parallel reaction monitoring (targeted proteomics) revealed unexpected effects of glucan biosynthesis on protein abundances but showed that the anticipated broad range of SS/BE enzyme ratios was maintained during the biosynthetic process. The different SS/BE ratios clearly influenced glucan structure and solubility: The higher the SS/BE ratio, the longer the glucan chains and the more glucans were partitioned into the insoluble fraction. This effect was irrespective of the SS isoform, demonstrating that the elongation/branching ratio controls glucan properties separate from enzyme specificity.

Conclusions

Our results provide a quantitative framework for the in silico design of improved starch biosynthetic processes in plants. Our study also exemplifies a workflow for the rational tuning of a complex pathway in yeast, starting from the selection and evaluation of expression modules to multi-gene assembly and targeted protein monitoring during the biosynthetic process.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01408-x.

Controlling gene expression with deep generative design of regulatory DNA

Design of de novo synthetic regulatory DNA is a promising avenue to control gene expression in biotechnology and medicine. Using mutagenesis typically requires screening sizable random DNA libraries, which limits the designs to span merely a short section of the promoter and restricts their control of gene expression. Here, we prototype a deep learning strategy based on generative adversarial networks (GAN) by learning directly from genomic and transcriptomic data. Our ExpressionGAN can traverse the entire regulatory sequence-expression landscape in a gene-specific manner, generating regulatory DNA with prespecified target mRNA levels spanning the whole gene regulatory structure including coding and adjacent non-coding regions. Despite high sequence divergence from natural DNA, in vivo measurements show that 57% of the highly-expressed synthetic sequences surpass the expression levels of highly-expressed natural controls. This demonstrates the applicability and relevance of deep generative design to expand our knowledge and control of gene expression regulation in any desired organism, condition or tissue.

Design of de novo synthetic regulatory DNA is a promising avenue to control gene expression in biotechnology and medicine. Here the authors present EspressionGAN, a generative adversarial network that uses genomic and transcriptomic data to generate regulatory sequences.

Precise tuning of bacterial translation initiation by non-equilibrium 5'-UTR unfolding observed in single mRNAs

Noncoding, structured 5′-untranslated regions (5′-UTRs) of bacterial messenger RNAs (mRNAs) can control translation efficiency by forming structures that either recruit or repel the ribosome. Here we exploit a 5′-UTR embedded preQ₁-sensing, pseudoknotted translational riboswitch to probe how binding of a small ligand controls recruitment of the bacterial ribosome to the partially overlapping Shine-Dalgarno (SD) sequence. Combining single-molecule fluorescence microscopy with mutational analyses, we find that the stability of 30S ribosomal subunit binding is inversely correlated with the free energy needed to unfold the 5′-UTR during mRNA accommodation into the mRNA binding cleft. Ligand binding to the riboswitch stabilizes the structure to both antagonize 30S recruitment and accelerate 30S dissociation. Proximity of the 5′-UTR and stability of the SD:anti-SD interaction both play important roles in modulating the initial 30S-mRNA interaction. Finally, depletion of small ribosomal subunit protein S1, known to help resolve structured 5′-UTRs, further increases the energetic penalty for mRNA accommodation. The resulting model of rapid standby site exploration followed by gated non-equilibrium unfolding of the 5′-UTR during accommodation provides a mechanistic understanding of how translation efficiency is governed by riboswitches and other dynamic structure motifs embedded upstream of the translation initiation site of bacterial mRNAs.

Efficient quantitative monitoring of translational initiation by RelE cleavage

The sequences of the 5′ untranslated regions (5′-UTRs) of mRNA alter gene expression across domains of life. Transcriptional modulators can be easily assayed through transcription termination, but translational regulators often require indirect, laborious methods. We have leveraged RelE’s ribosome-dependent endonuclease activity to develop a quantitative assay to monitor translation initiation of cis-regulatory mRNAs. RelE cleavage accurately reports ligand-dependent changes in ribosome association for two translational riboswitches and provides quantitative information about each switch's sensitivity and range of response. RelE accurately reads out sequence-driven changes in riboswitch specificity and function and is quantitatively dependent upon ligand concentration. RelE cleavage similarly captures differences in translation initiation between yeast 5′-UTR isoforms. RelE cleavage can thus reveal a plethora of information about translation initiation in different domains of life.

Reliance of Host-Encoded Regulators of Retromobility on Ty1 Promoter Activity or Architecture

The Ty1 retrotransposon family is maintained in a functional but dormant state by its host, Saccharomyces cerevisiae. Several hundred RHF and RTT genes encoding co-factors and restrictors of Ty1 retromobility, respectively, have been identified. Well-characterized examples include MED3 and MED15, encoding subunits of the Mediator transcriptional co-activator complex; control of retromobility by Med3 and Med15 requires the Ty1 promoter in the U3 region of the long terminal repeat. To characterize the U3-dependence of other Ty1 regulators, we screened a library of 188 known rhf and rtt mutants for altered retromobility of Ty1his3AI expressed from the strong, TATA-less TEF1 promoter or the weak, TATA-containing U3 promoter. Two classes of genes, each including both RHFs and RTTs, were identified. The first class comprising 82 genes that regulated Ty1his3AI retromobility independently of U3 is enriched for RHF genes that restrict the G1 phase of the cell cycle and those involved in transcriptional elongation and mRNA catabolism. The second class of 51 genes regulated retromobility of Ty1his3AI driven only from the U3 promoter. Nineteen U3-dependent regulators (U3DRs) also controlled retromobility of Ty1his3AI driven by the weak, TATA-less PSP2 promoter, suggesting reliance on the low activity of U3. Thirty-one U3DRs failed to modulate P_PSP2-Ty1his3AI retromobility, suggesting dependence on the architecture of U3. To further investigate the U3-dependency of Ty1 regulators, we developed a novel fluorescence-based assay to monitor expression of p22-Gag, a restriction factor expressed from the internal Ty1i promoter. Many U3DRs had minimal effects on levels of Ty1 RNA, Ty1i RNA or p22-Gag. These findings uncover a role for the Ty1 promoter in integrating signals from diverse host factors to modulate Ty1 RNA biogenesis or fate.

Secondary structures in RNA synthesis, splicing and translation

Even though the functional role of mRNA molecules is primarily decided by the nucleotide sequence, several properties are determined by secondary structure conformations. Examples of secondary structures include long range interactions, hairpins, R-loops and G-quadruplexes and they are formed through interactions of non-adjacent nucleotides. Here, we discuss advances in our understanding of how secondary structures can impact RNA synthesis, splicing, translation and mRNA half-life. During RNA synthesis, secondary structures determine RNA polymerase II (RNAPII) speed, thereby influencing splicing. Splicing is also determined by RNA binding proteins and their binding rates are modulated by secondary structures. For the initiation of translation, secondary structures can control the choice of translation start site. Here, we highlight the mechanisms by which secondary structures modulate these processes, discuss advances in technologies to detect and study them systematically, and consider the roles of RNA secondary structures in disease.

Toolbox for Genetic Transformation of Non-Conventional Saccharomycotina Yeasts: High Efficiency Transformation of Yeasts Belonging to the Schwanniomyces Genus

Non-conventional yeasts are increasingly being investigated and used as producers in biotechnological processes which often offer advantages in comparison to traditional and well-established systems. Most biotechnologically interesting non-conventional yeasts belong to the Saccharomycotina subphylum, including those already in use (Pichia pastoris, Yarrowia lypolitica, etc.), as well as those that are promising but as yet insufficiently characterized. Moreover, for many of these yeasts the basic tools of genetic engineering needed for strain construction, including a procedure for efficient genetic transformation, heterologous protein expression and precise genetic modification, are lacking. The first aim of this study was to construct a set of integrative and replicative plasmids which can be used in various yeasts across the Saccharomycotina subphylum. Additionally, we demonstrate here that the electroporation procedure we developed earlier for transformation of B. bruxellensis can be applied in various yeasts which, together with the constructed plasmids, makes a solid starting point when approaching a transformation of yeasts form the Saccharomycotina subphylum. To provide a proof of principle, we successfully transformed three species from the Schwanniomyces genus (S. polymorphus var. polymorphus, S. polymorphus var. africanus and S. pseudopolymorphus) with high efficiencies (up to 8 × 10³ in case of illegitimate integration of non-homologous linear DNA and up to 4.7 × 10⁵ in case of replicative plasmid). For the latter two species this is the first reported genetic transformation. Moreover, we found that a plasmid carrying replication origin from Scheffersomyces stipitis can be used as a replicative plasmid for these three Schwanniomyces species.

Direct analysis of ribosome targeting illuminates thousand-fold regulation of translation initiation

Translational control shapes the proteome in normal and pathophysiological conditions. Current high-throughput approaches reveal large differences in mRNA-specific translation activity but cannot identify the causative mRNA features. We developed direct analysis of ribosome targeting (DART) and used it to dissect regulatory elements within 5' untranslated regions that confer 1,000-fold differences in ribosome recruitment in biochemically accessible cell lysates. Using DART, we determined a functional role for most alternative 5' UTR isoforms expressed in yeast, revealed a general mode of increased translation via direct binding to a core translation factor, and identified numerous translational control elements including C-rich silencers that are sufficient to repress translation both in vitro and in vivo. DART enables systematic assessment of the translational regulatory potential of 5' UTR variants, whether native or disease-associated, and will facilitate engineering of mRNAs for optimized protein production in various systems.

Increased expression of the fluorescent reporter protein ymNeonGreen in Saccharomyces cerevisiae by reducing RNA secondary structure near the start codon

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Stable secondary RNA structure 3′ of the start codon inhibits ymNeonGreen expression.

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Removing secondary RNA structure increased expression in S. cerevisiae and E. coli.

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Expression was increased 2-fold in S. cerevisiae.

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Expression was increased 3.8-fold in E. coli.

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Increased expression in S. cerevisiae was promoter independent.

Expression of a new fluorescent reporter protein called mNeonGreen, that is not based on the jellyfish green fluorescent protein (GFP) sequence, shows increased brightness and folding speed compared to enhanced GFP. However, in vivo brightness of mNeonGreen and its yeast-optimized variant ymNeonGreen in S. cerevisiae is lower than expected, limiting the use of this high quantum yield, fast-folding reporter in budding yeast. This study shows that secondary RNA structure near the start codon in the ymNeonGreen ORF inhibits expression in S. cerevisiae. Removing secondary structure, without altering the ymNeonGreen protein sequence, led to a 2 and 4-fold increase in fluorescence when expressed in S. cerevisiae and E. coli, respectively. In S. cerevisiae, increased fluorescence was seen with strong and weak promoters and led to higher transcript levels suggesting greater transcript stability and improved expression in the absence of stable secondary RNA structure near the start codon.

Cap analysis of gene expression reveals alternative promoter usage in a rat model of hypertension

The role of alternative promoter usage in tissue-specific gene expression has been well established; however, its role in complex diseases is poorly understood. We performed cap analysis of gene expression (CAGE) sequencing from the left ventricle of a rat model of hypertension, the spontaneously hypertensive rat (SHR), and a normotensive strain, Brown Norway to understand the role of alternative promoter usage in complex disease. We identified 26,560 CAGE-defined transcription start sites in the rat left ventricle, including 1,970 novel cardiac transcription start sites. We identified 28 genes with alternative promoter usage between SHR and Brown Norway, which could lead to protein isoforms differing at the amino terminus between two strains and 475 promoter switching events altering the length of the 5' UTR. We found that the shift in Insr promoter usage was significantly associated with insulin levels and blood pressure within a panel of HXB/BXH recombinant inbred rat strains, suggesting that hyperinsulinemia due to insulin resistance might lead to hypertension in SHR. Our study provides a preliminary evidence of alternative promoter usage in complex diseases.

High-Throughput Quantitation of Yeast uORF Regulatory Impacts Using FACS-uORF

Eukaryotic upstream Open Reading Frames (uORFs) are short translated regions found in many transcript leaders (Barbosa et al. PLoS Genet 9:e1003529, 2013; Zhang et al. Trends Biochem Sci 44:782-794, 2019). Modern transcript annotations and ribosome profiling studies have found thousands of AUG-initiated uORFs, and many more uORFs initiated by near-cognate codons (CUG, GUG, UUG, etc.). Their translation generally decreases the expression of the main encoded protein by preventing ribosomes from reaching the main ORF of each gene, and by inducing nonsense mediated decay (NMD) through premature termination. Under many cellular stresses, uORF containing transcripts are de-repressed due to decreased translation initiation (Young et al. J Biol Chem 291:16927-16935, 2016). Traditional experimental evaluation of uORFs involves comparing expression from matched uORF-containing and start-codon mutated transcript leader reporter plasmids. This tedious process has precluded analysis of large numbers of uORFs. We recently used FACS-uORF to simultaneously assay thousands of yeast uORFs in order to evaluate the impact of codon usage on their functions (Lin et al. Nucleic Acids Res 2:1-10, 2019). Here, we provide a step-by-step protocol for this assay.

Overproduction of Membrane-Associated, and Integrated, Proteins Using Saccharomyces cerevisiae

Structural and functional eukaryotic membrane protein research continues to grow at an increasing rate, placing greater significance on leveraging productive protein expression pipelines to feed downstream studies. Bacterial expression systems (e.g., E. coli) are often the preferred system due to their simple growth conditions, relative simplicity in experimental workflow, low overall cost per liter of cell growth, and ease of genetic manipulation. However, overproduction success of eukaryotic membrane proteins in bacterial systems is hindered by the limited native processing ability of bacterial systems for important protein folding interactions (e.g., disulfide bonds), post-translational modifications (e.g., glycosylation), and inherent disadvantages in protein trafficking and folding machinery compared to other expression systems.In contrast, Saccharomyces cerevisiae expression systems combine positive benefits of simpler bacterial systems with those of more complex eukaryotic systems (e.g., mammalian cells). Benefits include inexpensive growth, robust DNA repair and recombination machinery, amenability to high density growths in bioreactors, efficient transformation, and robust post-translational modification machinery. These characteristics make S. cerevisiae a viable first-alternative when bacterial overproduction is insufficient. Thus, this chapter provides a framework, using methods that have proven successful in prior efforts, for overproducing membrane anchored or membrane integrated proteins in S. cerevisiae. The framework is designed to improve yields for all levels of overexpression expertise, providing optimization insights for the variety of processes involved in heterologous protein expression.

Multiplexed Analysis of Human uORF Regulatory Functions During the ISR Using PoLib-Seq

Protein synthesis is a highly regulated essential process. As such, it is subjected to substantial regulation in response to stress. One hallmark of the Integrated Stress Response (ISR) is the immediate shutdown of most translation through phosphorylation of the alpha subunit of translation initiation factor eIF2 and activation of eIF4E binding proteins. While these posttranslational modifications largely inhibit cap-dependent translation, many mRNA resist this inhibition by alternative translation mechanisms involving cis-regulatory sequences and structures in 5' transcript leaders, including upstream Open Reading Frames (uORFs), Internal Ribosome Entry Sites (IRESes), and Cap-Independent Translation Elements (CITEs). Studies of uORF and IRES activity are often performed on a gene-by-gene basis; however, high-throughput methods have recently emerged. Here, we describe a protocol for Polysome Library Sequencing (PoLib-Seq; Fig. 1), a multiplexed assay of reporter gene translation that can be used during the ISR. A designer library of reporter RNAs are transfected into tissue-culture cells, and their translation is assayed via sucrose gradient fractionation followed by high-throughput sequencing. As an example, we include PoLib-seq results simultaneously assaying translation of wildtype and uORF mutant human ATF4 reporter RNAs, recapitulating the known function of uORF1 in resisting translational inhibition during the ISR.

Quantitative model suggests both intrinsic and contextual features contribute to the transcript coding ability determination in cells

Gene transcription and protein translation are two key steps of the 'central dogma.' It is still a major challenge to quantitatively deconvolute factors contributing to the coding ability of transcripts in mammals. Here, we propose ribosome calculator (RiboCalc) for quantitatively modeling the coding ability of RNAs in human genome. In addition to effectively predicting the experimentally confirmed coding abundance via sequence and transcription features with high accuracy, RiboCalc provides interpretable parameters with biological information. Large-scale analysis further revealed a number of transcripts with a variety of coding ability for distinct types of cells (i.e. context-dependent coding transcripts), suggesting that, contrary to conventional wisdom, a transcript's coding ability should be modeled as a continuous spectrum with a context-dependent nature.

Characterization and optimization of the LAC4 upstream region for low-leakage expression in Kluyveromyces marxianus

Kluyveromyces marxianus is a promising host for the production of heterologous proteins, chemicals, and bioethanol. One superior feature of this species is its capacity to assimilate lactose, which is rendered by the LAC12-LAC4 gene pair encoding a lactose permease and a β-galactosidase enzyme. Little is known about the regulation of LAC4 in K. marxianus. In this study, we showed the presence of weak glucose repression in the regulation of LAC4 and that might contribute to the leaky expression of LAC4 in the glucose medium. In a mutagenesis screen of 1000-bp LAC4 upstream region, one mutant region, named H1, drove low-leakage expression of a URA3 reporter gene in glucose medium. Two mutations inside a polyadenosine stretch (poly(A)) of 5' UTR were major contributors to the low-leakage phenotype of H1. H1 directed low-leakage expression of GFP on a plasmid and that of LAC4 in situ in the glucose medium, which was not due to the reduction of mRNA levels. Meanwhile, H1 did not affect the induction of GFP or LAC4 by lactose. Cre recombinase expressed by H1 caused lower toxicity in the repressive condition and achieved higher yield after induction, compared with that expressed by a wild-type LAC4 upstream region or a strong INU1 promoter. Our study suggested that poly(A) inside 5' UTR played a role in regulating the expression of LAC4 in the repressive condition. Meanwhile, H1 provided a base for the development of a strict inducible system for expressing industrial proteins, especially toxic proteins.