Extensive post-transcriptional buffering of gene expression in the response to severe oxidative stress in baker's yeast

Comprehensive translational profiling and STE AI uncover rapid control of protein biosynthesis during cell stress

Translational control is important in all life, but it remains a challenge to accurately quantify. When ribosomes translate messenger (m)RNA into proteins, they attach to the mRNA in series, forming poly(ribo)somes, and can co-localize. Here, we computationally model new types of co-localized ribosomal complexes on mRNA and identify them using enhanced translation complex profile sequencing (eTCP-seq) based on rapid in vivo crosslinking. We detect long disome footprints outside regions of non-random elongation stalls and show these are linked to translation initiation and protein biosynthesis rates. We subject footprints of disomes and other translation complexes to artificial intelligence (AI) analysis and construct a new, accurate and self-normalized measure of translation, termed stochastic translation efficiency (STE). We then apply STE to investigate rapid changes to mRNA translation in yeast undergoing glucose depletion. Importantly, we show that, well beyond tagging elongation stalls, footprints of co-localized ribosomes provide rich insight into translational mechanisms, polysome dynamics and topology. STE AI ranks cellular mRNAs by absolute translation rates under given conditions, can assist in identifying its control elements and will facilitate the development of next-generation synthetic biology designs and mRNA-based therapeutics.

Gene and protein sequence features augment HLA class I ligand predictions

The sensitivity of malignant tissues to T cell-based immunotherapies depends on the presence of targetable human leukocyte antigen (HLA) class I ligands. Peptide-intrinsic factors, such as HLA class I affinity and proteasomal processing, have been established as determinants of HLA ligand presentation. However, the role of gene and protein sequence features as determinants of epitope presentation has not been systematically evaluated. We perform HLA ligandome mass spectrometry to evaluate the contribution of 7,135 gene and protein sequence features to HLA sampling. This analysis reveals that a number of predicted modifiers of mRNA and protein abundance and turnover, including predicted mRNA methylation and protein ubiquitination sites, inform on the presence of HLA ligands. Importantly, integration of such "hard-coded" sequence features into a machine learning approach augments HLA ligand predictions to a comparable degree as experimental measures of gene expression. Our study highlights the value of gene and protein features for HLA ligand predictions.

Noise robustness and metabolic load determine the principles of central dogma regulation

The processes of gene expression are inherently stochastic, even for essential genes required for growth. How does the cell maximize fitness in light of noise? To answer this question, we build a mathematical model to explore the trade-off between metabolic load and growth robustness. The model predicts novel principles of central dogma regulation: Optimal protein expression levels for many genes are in vast overabundance. Essential genes are transcribed above a lower limit of one message per cell cycle. Gene expression is achieved by load balancing between transcription and translation. We present evidence that each of these novel regulatory principles is observed. These results reveal that robustness and metabolic load determine the global regulatory principles that govern central dogma processes, and these principles have broad implications for cellular function.

Species-wide quantitative transcriptomes and proteomes reveal distinct genetic control of gene expression variation in yeast

Gene expression varies between individuals and corresponds to a key step linking genotypes to phenotypes. However, our knowledge regarding the species-wide genetic control of protein abundance, including its dependency on transcript levels, is very limited. Here, we have determined quantitative proteomes of a large population of 942 diverse natural Saccharomyces cerevisiae yeast isolates. We found that mRNA and protein abundances are weakly correlated at the population gene level. While the protein coexpression network recapitulates major biological functions, differential expression patterns reveal proteomic signatures related to specific populations. Comprehensive genetic association analyses highlight that genetic variants associated with variation in protein (pQTL) and transcript (eQTL) levels poorly overlap (3%). Our results demonstrate that transcriptome and proteome are governed by distinct genetic bases, likely explained by protein turnover. It also highlights the importance of integrating these different levels of gene expression to better understand the genotype-phenotype relationship.

Ribosome Profiling and Mass Spectrometry Reveal Widespread Mitochondrial Translation Defects in a Striatal Cell Model of Huntington Disease

Huntington disease (HD) is caused by an expanded polyglutamine mutation in huntingtin (mHTT) that promotes prominent atrophy in the striatum and subsequent psychiatric, cognitive deficits, and choreiform movements. Multiple lines of evidence point to an association between HD and aberrant striatal mitochondrial functions; however, the present knowledge about whether (or how) mitochondrial mRNA translation is differentially regulated in HD remains unclear. We found that protein synthesis is diminished in HD mitochondria compared to healthy control striatal cell models. We utilized ribosome profiling (Ribo-Seq) to analyze detailed snapshots of ribosome occupancy of the mitochondrial mRNA transcripts in control and HD striatal cell models. The Ribo-Seq data revealed almost unaltered ribosome occupancy on the nuclear-encoded mitochondrial transcripts involved in oxidative phosphorylation (SDHA, Ndufv1, Timm23, Tomm5, Mrps22) in HD cells. By contrast, ribosome occupancy was dramatically increased for mitochondrially encoded oxidative phosphorylation mRNAs (mt-Nd1, mt-Nd2, mt-Nd4, mt-Nd4l, mt-Nd5, mt-Nd6, mt-Co1, mt-Cytb, and mt-ATP8). We also applied tandem mass tag-based mass spectrometry identification of mitochondrial proteins to derive correlations between ribosome occupancy and actual mature mitochondrial protein products. We found many mitochondrial transcripts with comparable or higher ribosome occupancy, but diminished mitochondrial protein products, in HD. Thus, our study provides the first evidence of a widespread dichotomous effect on ribosome occupancy and protein abundance of mitochondria-related genes in HD.

Single-cell spatial transcriptomic and translatomic profiling of dopaminergic neurons in health, aging, and disease

The brain is spatially organized and contains unique cell types, each performing diverse functions and exhibiting differential susceptibility to neurodegeneration. This is exemplified in Parkinson's disease with the preferential loss of dopaminergic neurons of the substantia nigra pars compacta. Using a Parkinson's transgenic model, we conducted a single-cell spatial transcriptomic and dopaminergic neuron translatomic analysis of young and old mouse brains. Through the high resolving capacity of single-cell spatial transcriptomics, we provide a deep characterization of the expression features of dopaminergic neurons and 27 other cell types within their spatial context, identifying markers of healthy and aging cells, spanning Parkinson's relevant pathways. We integrate gene enrichment and genome-wide association study data to prioritize putative causative genes for disease investigation, identifying CASR as a regulator of dopaminergic calcium handling. These datasets represent the largest public resource for the investigation of spatial gene expression in brain cells in health, aging, and disease.

Translation variation across genetic backgrounds reveals a post-transcriptional buffering signature in yeast

Gene expression is known to vary among individuals, and this variability can impact the phenotypic diversity observed in natural populations. While the transcriptome and proteome have been extensively studied, little is known about the translation process itself. Here, we therefore performed ribosome and transcriptomic profiling on a genetically and ecologically diverse set of natural isolates of the Saccharomyces cerevisiae yeast. Interestingly, we found that the Euclidean distances between each profile and the expression fold changes in each pairwise isolate comparison were higher at the transcriptomic level. This observation clearly indicates that the transcriptional variation observed in the different isolates is buffered through a phenomenon known as post-transcriptional buffering at the translation level. Furthermore, this phenomenon seemed to have a specific signature by preferentially affecting essential genes as well as genes involved in complex-forming proteins, and low transcribed genes. We also explored the translation of the S. cerevisiae pangenome and found that the accessory genes related to introgression events displayed similar transcription and translation levels as the core genome. By contrast, genes acquired through horizontal gene transfer events tended to be less efficiently translated. Together, our results highlight both the extent and signature of the post-transcriptional buffering.

Translation regulation in response to stress

Cell stresses occur in a wide variety of settings: in disease, during industrial processes, and as part of normal day-to-day rhythms. Adaptation to these stresses requires cells to alter their proteome. Cells modify the proteins they synthesize to aid proteome adaptation. Changes in both mRNA transcription and translation contribute to altered protein synthesis. Here, we discuss the changes in translational mechanisms that occur following the onset of stress, and the impact these have on stress adaptation.

Multi-omics reveals largely distinct transcript- and protein-level responses to the environment in an intertidal mussel

Organismal responses to stressful environments are influenced by numerous transcript- and protein-level mechanisms, and the relationships between expression changes at these levels are not always straightforward. Here, we used paired transcriptomic and proteomic datasets from two previous studies from gill of the California mussel, Mytilus californianus, to explore how simultaneous transcript and protein abundance patterns may diverge under different environmental scenarios. Field-acclimatized mussels were sampled from two disparate intertidal sites; individuals from one site were subjected to three further treatments (common garden, low-intertidal or high-intertidal outplant) that vary in temperature and feeding time. Assessing 1519 genes shared between the two datasets revealed that both transcript and protein expression patterns differentiated the treatments at a global level, despite numerous underlying discrepancies. There were far more instances of differential expression between treatments in transcript only (1451) or protein only (226) than of the two levels shifting expression concordantly (68 instances). Upregulated expression of cilium-associated transcripts (likely related to feeding) was associated with relatively benign field treatments. In the most stressful treatment, transcripts, but not proteins, for several molecular chaperones (including heat shock proteins and endoplasmic reticulum chaperones) were more abundant, consistent with a threshold model for induction of translation of constitutively available mRNAs. Overall, these results suggest that the relative importance of transcript- and protein-level regulation (translation and/or turnover) differs among cellular functions and across specific microhabitats or environmental contexts. Furthermore, the degree of concordance between transcript and protein expression can vary across benign versus acutely stressful environmental conditions.

Workability of mRNA Sequencing for Predicting Protein Abundance

Transcriptomics methods (RNA-Seq, PCR) today are more routine and reproducible than proteomics methods, i.e., both mass spectrometry and immunochemical analysis. For this reason, most scientific studies are limited to assessing the level of mRNA content. At the same time, protein content (and its post-translational status) largely determines the cell's state and behavior. Such a forced extrapolation of conclusions from the transcriptome to the proteome often seems unjustified. The ratios of "transcript-protein" pairs can vary by several orders of magnitude for different genes. As a rule, the correlation coefficient between transcriptome-proteome levels for different tissues does not exceed 0.3-0.5. Several characteristics determine the ratio between the content of mRNA and protein: among them, the rate of movement of the ribosome along the mRNA and the number of free ribosomes in the cell, the availability of tRNA, the secondary structure, and the localization of the transcript. The technical features of the experimental methods also significantly influence the levels of the transcript and protein of the corresponding gene on the outcome of the comparison. Given the above biological features and the performance of experimental and bioinformatic approaches, one may develop various models to predict proteomic profiles based on transcriptomic data. This review is devoted to the ability of RNA sequencing methods for protein abundance prediction.

Species-wide quantitative transcriptomes and proteomes reveal distinct genetic control of gene expression variation in yeast

Gene expression varies between individuals and corresponds to a key step linking genotypes to phenotypes. However, our knowledge regarding the species-wide genetic control of protein abundance, including its dependency on transcript levels, is very limited. Here, we have determined quantitative proteomes of a large population of 942 diverse natural Saccharomyces cerevisiae yeast isolates. We found that mRNA and protein abundances are weakly correlated at the population gene level. While the protein co-expression network recapitulates major biological functions, differential expression patterns reveal proteomic signatures related to specific populations. Comprehensive genetic association analyses highlight that genetic variants associated with variation in protein (pQTL) and transcript (eQTL) levels poorly overlap (3.6%). Our results demonstrate that transcriptome and proteome are governed by distinct genetic bases, likely explained by protein turnover. It also highlights the importance of integrating these different levels of gene expression to better understand the genotype-phenotype relationship.

Highlights

At the level of individual genes, the abundance of transcripts and proteins is weakly correlated within a species ( ρ = 0.165). While the proteome is not imprinted by population structure, co-expression patterns recapitulate the cellular functional landscapeWild populations exhibit a higher abundance of respiration-related proteins compared to domesticated populationsLoci that influence protein abundance differ from those that impact transcript levels, likely because of protein turnover.

The one-message-per-cell-cycle rule: A conserved minimum transcription level for essential genes

The inherent stochasticity of cellular processes leads to significant cell-to-cell variation in protein abundance. Although this noise has already been characterized and modeled, its broader implications and significance remain unclear. In this paper, we revisit the noise model and identify the number of messages transcribed per cell cycle as the critical determinant of noise. In yeast, we demonstrate that this quantity predicts the non-canonical scaling of noise with protein abundance, as well as quantitatively predicting its magnitude. We then hypothesize that growth robustness requires an upper ceiling on noise for the expression of essential genes, corresponding to a lower floor on the transcription level. We show that just such a floor exists: a minimum transcription level of one message per cell cycle is conserved between three model organisms: Escherichia coli, yeast, and human. Furthermore, all three organisms transcribe the same number of messages per gene, per cell cycle. This common transcriptional program reveals that robustness to noise plays a central role in determining the expression level of a large fraction of essential genes, and that this fundamental optimal strategy is conserved from E. coli to human cells.

The one-message-per-cell-cycle rule: A conserved minimum transcription level for essential genes

The inherent stochasticity of cellular processes leads to significant cell-to-cell variation in protein abundance. Although this noise has already been characterized and modeled, its broader implications and significance remain unclear. In this paper, we revisit the noise model and identify the number of messages transcribed per cell cycle as the critical determinant of noise. In yeast, we demonstrate that this quantity predicts the non-canonical scaling of noise with protein abundance, as well as quantitatively predicting its magnitude. We then hypothesize that growth robustness requires an upper ceiling on noise for the expression of essential genes, corresponding to a lower floor on the transcription level. We show that just such a floor exists: a minimum transcription level of one message per cell cycle is conserved between three model organisms: Escherichia coli, yeast, and human. Furthermore, all three organisms transcribe the same number of messages per gene, per cell cycle. This common transcriptional program reveals that robustness to noise plays a central role in determining the expression level of a large fraction of essential genes, and that this fundamental optimal strategy is conserved from E. coli to human cells.

Evolutionary trade-off and mutational bias could favor transcriptional over translational divergence within paralog pairs

How changes in the different steps of protein synthesis-transcription, translation and degradation-contribute to differences of protein abundance among genes is not fully understood. There is however accumulating evidence that transcriptional divergence might have a prominent role. Here, we show that yeast paralogous genes are more divergent in transcription than in translation. We explore two causal mechanisms for this predominance of transcriptional divergence: an evolutionary trade-off between the precision and economy of gene expression and a larger mutational target size for transcription. Performing simulations within a minimal model of post-duplication evolution, we find that both mechanisms are consistent with the observed divergence patterns. We also investigate how additional properties of the effects of mutations on gene expression, such as their asymmetry and correlation across levels of regulation, can shape the evolution of paralogs. Our results highlight the importance of fully characterizing the distributions of mutational effects on transcription and translation. They also show how general trade-offs in cellular processes and mutation bias can have far-reaching evolutionary impacts.

The NELF pausing checkpoint mediates the functional divergence of Cdk9

Promoter-proximal pausing by RNA Pol II is a rate-determining step in gene transcription that is hypothesized to be a prominent point at which regulatory factors act. The pausing factor NELF is known to induce and stabilize pausing, but not all kinds of pausing are NELF-mediated. Here, we find that NELF-depleted Drosophila melanogaster cells functionally recapitulate the NELF-independent pausing we previously observed in fission yeast (which lack NELF). Critically, only NELF-mediated pausing establishes a strict requirement for Cdk9 kinase activity for the release of paused Pol II into productive elongation. Upon inhibition of Cdk9, cells with NELF efficiently shutdown gene transcription, while in NELF-depleted cells, defective, non-productive transcription continues unabated. By introducing a strict checkpoint for Cdk9, the evolution of NELF was likely critical to enable increased regulation of Cdk9 in higher eukaryotes, as Cdk9 availability can be restricted to limit gene transcription without inducing wasteful, non-productive transcription.

"Transfer" of power: The intersection of DNA virus infection and tRNA biology

Transfer RNAs (tRNAs) are at the heart of the molecular biology central dogma, functioning to decode messenger RNAs into proteins. As obligate intracellular parasites, viruses depend on the host translation machinery, including host tRNAs. Thus, the ability of a virus to fine-tune tRNA expression elicits the power to impact the outcome of infection. DNA viruses commonly upregulate the output of RNA polymerase III (Pol III)-dependent transcripts, including tRNAs. Decades after these initial discoveries we know very little about how mature tRNA pools change during viral infection, as tRNA sequencing methodology has only recently reached proficiency. Here, we review perturbation of tRNA biogenesis by DNA virus infection, including an emerging player called tRNA-derived fragments (tRFs). We discuss how tRNA dysregulation shifts the power landscape between the host and virus, highlighting the potential for tRNA-based antivirals as a future therapeutic.

Development of a ribosome profiling protocol to study translation in Kluyveromyces marxianus

Kluyveromyces marxianus is an interesting and important yeast because of particular traits such as thermotolerance and rapid growth, and for applications in food and industrial biotechnology. For both understanding its biology and developing bioprocesses, it is important to understand how K. marxianus responds and adapts to changing environments. For this, a full suite of omics tools to measure and compare global patterns of gene expression and protein synthesis is needed. We report here the development of a ribosome profiling method for K. marxianus, which allows codon resolution of translation on a genome-wide scale by deep sequencing of ribosome locations on mRNAs. To aid in the analysis and sharing of ribosome profiling data, we added the K. marxianus genome as well as transcriptome and ribosome profiling data to the publicly accessible GWIPS-viz and Trips-Viz browsers. Users are able to upload custom ribosome profiling and RNA-Seq data to both browsers, therefore allowing easy analysis and sharing of data. We also provide a set of step-by-step protocols for the experimental and bioinformatic methods that we developed.

A dual-activity topoisomerase complex regulates mRNA translation and turnover

Topoisomerase 3β (TOP3B) and TDRD3 form a dual-activity topoisomerase complex that interacts with FMRP and can change the topology of both DNA and RNA. Here, we investigated the post-transcriptional influence of TOP3B and associated proteins on mRNA translation and turnover. First, we discovered that in human HCT116 colon cancer cells, knock-out (KO) of TOP3B had similar effects on mRNA turnover and translation as did TDRD3-KO, while FMRP-KO resulted in rather distinct effects, indicating that TOP3B had stronger coordination with TDRD3 than FMRP in mRNA regulation. Second, we identified TOP3B-bound mRNAs in HCT116 cells; we found that while TOP3B did not directly influence the stability or translation of most TOP3B target mRNAs, it stabilized a subset of target mRNAs but had a more complex effect on translation-enhancing for some mRNAs whereas reducing for others. Interestingly, a point mutation that specifically disrupted TOP3B catalytic activity only partially recapitulated the effects of TOP3B-KO on mRNA stability and translation, suggesting that the impact of TOP3B on target mRNAs is partly linked to its ability to change topology of mRNAs. Collectively, our data suggest that TOP3B-TDRD3 can regulate mRNA translation and turnover by mechanisms that are dependent and independent of topoisomerase activity.

Genome-wide translation control analysis of developing human neurons

During neuronal differentiation, neuroprogenitor cells become polarized, change shape, extend axons, and form complex dendritic trees. While growing, axons are guided by molecular cues to their final destination, where they establish synaptic connections with other neuronal cells. Several layers of regulation are integrated to control neuronal development properly. Although control of mRNA translation plays an essential role in mammalian gene expression, how it contributes temporarily to the modulation of later stages of neuronal differentiation remains poorly understood. Here, we investigated how translation control affects pathways and processes essential for neuronal maturation, using H9-derived human neuro progenitor cells differentiated into neurons as a model. Through Ribosome Profiling (Riboseq) combined with RNA sequencing (RNAseq) analysis, we found that translation control regulates the expression of critical hub genes. Fundamental synaptic vesicle secretion genes belonging to SNARE complex, Rab family members, and vesicle acidification ATPases are strongly translationally regulated in developing neurons. Translational control also participates in neuronal metabolism modulation, particularly affecting genes involved in the TCA cycle and glutamate synthesis/catabolism. Importantly, we found translation regulation of several critical genes with fundamental roles regulating actin and microtubule cytoskeleton pathways, critical to neurite generation, spine formation, axon guidance, and circuit formation. Our results show that translational control dynamically integrates important signals in neurons, regulating several aspects of its development and biology.

Diverse impact of N-acetylcysteine or alpha-lipoic acid supplementation during high-fat diet regime on fatty acid transporters in visceral and subcutaneous adipose tissue

PURPOSE

Adipose tissue's (AT) structural changes accompanying obesity may alter lipid transport protein expression and, thus, the fatty acids (FAs) transport and lipid balance of the body. Metabolic abnormalities within AT contribute to the elevated production of reactive oxygen species and increased oxidative/nitrosative stress. Although compounds such as N-acetylcysteine (NAC) and α-lipoic acid (ALA), which restore redox homeostasis, may improve lipid metabolism in AT, the mechanism of action of these antioxidants on lipid metabolism in AT is still unknown. This study aimed to examine the impact of NAC and ALA on the level and FA composition of the lipid fractions, and the expression of FA transporters in the visceral and subcutaneous AT of high-fat diet-fed rats.

MATERIALS AND METHODS

Male Wistar rats were randomly divided into four groups. The mRNA levels and protein expression of FA transporters were assessed using real-time PCR and Western Blot analyses. The collected samples were subjected to histological evaluation. The level of lipids (FFA, DAG, and TAG) was measured using gas-liquid chromatography.

RESULTS

We found that antioxidants affect FA transporter expressions at both the transcript and protein levels, and, therefore, they promote changes in AT's lipid pools. One of the most remarkable findings of our research is that different antioxidant molecules may have a varying impact on AT phenotype.

CONCLUSION

NAC and ALA exert different influences on AT, which is reflected in histopathological images, FA transport proteins expression patterns, or even the lipid storage capacity of adipocytes.

Small open reading frames in plant research: from prediction to functional characterization

Gene prediction is a laborious and time-consuming task. The advancement of sequencing technologies and bioinformatics tools, coupled with accelerated rate of ribosome profiling and mass spectrometry development, have made identification of small open reading frames (sORFs) (< 100 codons) in various plant genomes possible. The past 50 years have seen sORFs being isolated from many organisms. However, to date, a comprehensive sORF annotation pipeline is as yet unavailable, hence, addressed in our review. Here, we also provide current information on classification and functions of plant sORFs and their potential applications in crop improvement programs.

Coordinated post-transcriptional control of oncogene-induced senescence by UNR/CSDE1

Oncogene-induced senescence (OIS) is a form of stable cell-cycle arrest arising in response to oncogenic stimulation. OIS must be bypassed for transformation, but the mechanisms of OIS establishment and bypass remain poorly understood, especially at the post-transcriptional level. Here, we show that the RNA-binding protein UNR/CSDE1 enables OIS in primary mouse keratinocytes. Depletion of CSDE1 leads to senescence bypass, cell immortalization, and tumor formation, indicating that CSDE1 behaves as a tumor suppressor. Unbiased high-throughput analyses uncovered that CSDE1 promotes OIS by two independent molecular mechanisms: enhancement of the stability of senescence-associated secretory phenotype (SASP) factor mRNAs and repression of Ybx1 mRNA translation. Importantly, depletion of YBX1 from immortal keratinocytes rescues senescence and uncouples proliferation arrest from the SASP, revealing multilayered mechanisms exerted by CSDE1 to coordinate senescence. Our data highlight the relevance of post-transcriptional control in the regulation of senescence.

The Transcriptional Response to Oxidative Stress is Independent of Stress-Granule Formation

Cells respond to stress with translational arrest, robust transcriptional changes, and transcription-independent formation of mRNP assemblies termed stress granules (SGs). Despite considerable interest in the role of SGs in oxidative, unfolded-protein and viral stress responses, whether and how SGs contribute to stress-induced transcription has not been rigorously examined. To address this, we characterized transcriptional changes in Drosophila S2 cells induced by acute oxidative-stress and assessed how these were altered under conditions that disrupted SG assembly. Oxidative stress for 3-hours predominantly resulted in induction or upregulation of stress-responsive mRNAs whose levels peaked during recovery after stress cessation. The stress-transcriptome is enriched in mRNAs coding for chaperones, including HSP70s, small heat shock proteins, glutathione transferases, and several non-coding RNAs. Oxidative stress also induced cytoplasmic SGs that disassembled 3-hours after stress cessation. As expected, RNAi-mediated knockdown of the conserved G3BP1/Rasputin protein inhibited SG assembly. However, this disruption had no significant effect on the stress-induced transcriptional response or stress-induced translational arrest. Thus, SG assembly and stress-induced gene expression alterations appear to be driven by distinctive signaling processes. We suggest that while SG assembly represents a fast, transient mechanism, the transcriptional response enables a slower, longer-lasting mechanism for adaptation to and recovery from cell stress.

Uncovering the impacts of alternative splicing on the proteome with current omics techniques

The high‐throughput sequencing of cellular RNAs has underscored a broad effect of isoform diversification through alternative splicing on the transcriptome. Moreover, the differential production of transcript isoforms from gene loci has been recognized as a critical mechanism in cell differentiation, organismal development, and disease. Yet, the extent of the impact of alternative splicing on protein production and cellular function remains a matter of debate. Multiple experimental and computational approaches have been developed in recent years to address this question. These studies have unveiled how molecular changes at different steps in the RNA processing pathway can lead to differences in protein production and have functional effects. New and emerging experimental technologies open exciting new opportunities to develop new methods to fully establish the connection between messenger RNA expression and protein production and to further investigate how RNA variation impacts the proteome and cell function.

This article is categorized under:

RNA Processing > Splicing Regulation/Alternative Splicing

Translation > Regulation

RNA Evolution and Genomics > Computational Analyses of RNA

Interchangeable utilization of metals: New perspectives on the impacts of metal ions employed in ancient and extant biomolecules

Metal ions provide considerable functionality across biological systems, and their utilization within biomolecules has adapted through changes in the chemical environment to maintain the activity they facilitate. While ancient earth's atmosphere was rich in iron and manganese and low in oxygen, periods of atmospheric oxygenation significantly altered the availability of certain metal ions, resulting in ion replacement within biomolecules. This adaptation mechanism has given rise to the phenomenon of metal cofactor interchangeability, whereby contemporary proteins and nucleic acids interact with multiple metal ions interchangeably, with different coordinated metals influencing biological activity, stability, and toxic potential. The ability of extant organisms to adapt to fluctuating metal availability remains relevant in a number of crucial biomolecules, including the superoxide dismutases of the antioxidant defense systems and ribonucleotide reductases. These well-studied and ancient enzymes illustrate the potential for metal interchangeability and adaptive utilization. More recently, the ribosome has also been demonstrated to exhibit interchangeable interactions with metal ions with impacts on function, stability, and stress adaptation. Using these and other examples, here we review the biological significance of interchangeable metal ions from a new angle that combines both biochemical and evolutionary viewpoints. The geochemical pressures and chemical properties that underlie biological metal utilization are discussed in the context of their impact on modern disease states and treatments.

Transcriptomic entropy benchmarks stem cell-derived cardiomyocyte maturation against endogenous tissue at single cell level

The immaturity of pluripotent stem cell (PSC)-derived tissues has emerged as a universal problem for their biomedical applications. While efforts have been made to generate adult-like cells from PSCs, direct benchmarking of PSC-derived tissues against in vivo development has not been established. Thus, maturation status is often assessed on an ad-hoc basis. Single cell RNA-sequencing (scRNA-seq) offers a promising solution, though cross-study comparison is limited by dataset-specific batch effects. Here, we developed a novel approach to quantify PSC-derived cardiomyocyte (CM) maturation through transcriptomic entropy. Transcriptomic entropy is robust across datasets regardless of differences in isolation protocols, library preparation, and other potential batch effects. With this new model, we analyzed over 45 scRNA-seq datasets and over 52,000 CMs, and established a cross-study, cross-species CM maturation reference. This reference enabled us to directly compare PSC-CMs with the in vivo developmental trajectory and thereby to quantify PSC-CM maturation status. We further found that our entropy-based approach can be used for other cell types, including pancreatic beta cells and hepatocytes. Our study presents a biologically relevant and interpretable metric for quantifying PSC-derived tissue maturation, and is extensible to numerous tissue engineering contexts.

Proteomics in the pharmaceutical and biotechnology industry: a look to the next decade

INTRODUCTION

Pioneering technologies such as proteomics have helped fuel the biotechnology and pharmaceutical industry with the discovery of novel targets and an intricate understanding of the activity of therapeutics and their various activities in vitro and in vivo. The field of proteomics is undergoing an inflection point, where new sensitive technologies are allowing intricate biological pathways to be better understood, and novel biochemical tools are pivoting us into a new era of chemical proteomics and biomarker discovery. In this review, we describe these areas of innovation, and discuss where the fields are headed in terms of fueling biotechnological and pharmacological research and discuss current gaps in the proteomic technology landscape.

AREAS COVERED

Single cell sequencing and single molecule sequencing. Chemoproteomics. Biological matrices and clinical samples including biomarkers. Computational tools including instrument control software, data analysis.

EXPERT OPINION

Proteomics will likely remain a key technology in the coming decade, but will have to evolve with respect to type and granularity of data, cost and throughput of data generation as well as integration with other technologies to fulfill its promise in drug discovery.

Global translational landscape of the Candida albicans morphological transition

Candida albicans, a major human fungal pathogen associated with high mortality and/or morbidity rates in a wide variety of immunocompromised individuals, undergoes a reversible morphological transition from yeast to filamentous cells that is required for virulence. While previous studies have identified and characterized global transcriptional mechanisms important for driving this transition, as well as other virulence properties, in C. albicans and other pathogens, considerably little is known about the role of genome-wide translational mechanisms. Using ribosome profiling, we report the first global translational profile associated with C. albicans morphogenesis. Strikingly, many genes involved in pathogenesis, filamentation, and the response to stress show reduced translational efficiency (TE). Several of these genes are known to be strongly induced at the transcriptional level, suggesting that a translational fine-tuning mechanism is in place. We also identify potential upstream open reading frames (uORFs), associated with genes involved in pathogenesis, and novel ORFs, several of which show altered TE during filamentation. Using a novel bioinformatics method for global analysis of ribosome pausing that will be applicable to a wide variety of genetic systems, we demonstrate an enrichment of ribosome pausing sites in C. albicans genes associated with protein synthesis and cell wall functions. Altogether, our results suggest that the C. albicans morphological transition, and most likely additional virulence processes in fungal pathogens, is associated with widespread global alterations in TE that do not simply reflect changes in transcript levels. These alterations affect the expression of many genes associated with processes essential for virulence and pathogenesis.

Oxidative stress induces coordinated remodeling of RNA-enzyme interactions

RNA-binding proteins (RBPs) are key post-transcriptional regulators that play a substantial role during stress adaptation. Recent proteome-wide surveys have uncovered a large number of new and “unconventional” RBPs such as metabolic enzymes, yet little is known about the reconfiguration of the RNA-binding proteome (RBPome) and RNA-enzyme interactions in response to cellular stress. Here, we applied RNA-interactome capture to monitor the dynamics of the mRBPome upon mild oxidative stress in the yeast Saccharomyces cerevisiae. Among the 257 proteins that significantly changed RNA associations, we observed the coordinated remodeling of RNA-binding enzymes — particularly of the central carbon metabolism — that complemented known metabolic responses. Furthermore, we recognized the propensity for paralogous specific alterations of enzyme-RNA interactions. Our results suggest coordinated cross talk between RNA-enzyme interactions and intermediary metabolism to maintain the physiological and molecular balance upon oxidative stress, perhaps through specialization of paralogous during evolution.

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Oxidative stress induces the rearrangement of 257 proteins on polyadenylated RNAs

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Coordinated response of RNA-enzyme interactions and metabolism

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Yeast RNA-binding enzymes are paralog specific

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Integration of three different mass spectrometry analysis tools

Impact of uORFs in mediating regulation of translation in stress conditions

Background

A large fraction of genes contains upstream ORFs (uORFs) in the 5′ untranslated region (5’UTR). The translation of uORFs can inhibit the translation of the main coding sequence, for example by causing premature dissociation of the two ribosomal units or ribosome stalling. However, it is currently unknown if most uORFs are inhibitory or if this activity is restricted to specific cases. Here we interrogate ribosome profiling data from three different stress experiments in yeast to gain novel insights into this question.

Results

By comparing ribosome occupancies in different conditions and experiments we obtain strong evidence that, in comparison to primary coding sequences (CDS), which undergo translational arrest during stress, the translation of uORFs is mostly unaffected by changes in the environment. As a result, the relative abundance of uORF-encoded peptides increases during stress. In general, the changes in the translational efficiency of regions containing uORFs do not seem to affect downstream translation. The exception are uORFs found in a subset of genes that are significantly up-regulated at the level of translation during stress; these uORFs tend to be translated at lower levels in stress conditions than in optimal growth conditions, facilitating the translation of the CDS during stress. We find new examples of uORF-mediated regulation of translation, including the Gcn4 functional homologue fil1 and ubi4 genes in S. pombe.

Conclusion

We find evidence that the relative amount of uORF-encoded peptides increases during stress. The increased translation of uORFs is however uncoupled from the general CDS translational repression observed during stress. In a subset of genes that encode proteins that need to be rapidly synthesized upon stress uORFs act as translational switches.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12860-021-00363-9.

RiboDoc: A Docker-based package for ribosome profiling analysis

Ribosome profiling (RiboSeq) has emerged as a powerful technique for studying the genome-wide regulation of translation in various cells. Several steps in the biological protocol have been improved, but the bioinformatics part of RiboSeq suffers from a lack of standardization, preventing the straightforward and complete reproduction of published results. Too many published studies provide insufficient detail about the bioinformatics pipeline used. The broad range of questions that can be asked with RiboSeq makes it difficult to use a single bioinformatics tool. Indeed, many scripts have been published for addressing diverse questions. Here (https://github.com/equipeGST/RiboDoc), we propose a unique tool (for use with multiple operating systems, OS) to standardize the general steps that must be performed systematically in RiboSeq analysis, together with the statistical analysis and quality control of the sample. The data generated can then be exploited with more specific tools. We hope that this tool will help to standardize bioinformatics analyses pipelines in the field of translation.

Reasons for 2-furaldehyde and 5-hydroxymethyl-2-furaldehyde resistance in Saccharomyces cerevisiae: current state of knowledge and perspectives for further improvements

Common toxic compounds 2-furaldehyde (furfural) and 5-hydroxymethyl-2-furaldehyde (HMF) are formed from dehydration of pentose and hexose, respectively, during decomposition of lignocellulosic biomass polymers. Furfural and HMF represent a major class of aldehyde toxic chemicals that inhibit microbial growth and interfere with subsequent fermentation for production of renewable fuels and chemicals. Understanding mechanisms of yeast tolerance aids development of tolerant strains as the most economic means to overcome the toxicity. This review updates current knowledge on yeast resistance to these toxic chemicals obtained from rapid advances in the past few years. Findings are largely exemplified by an adapted strain NRRL Y-50049 compared with its progenitor, the industrial yeast Saccharomyces cerevisiae type strain NRRL Y-12632. Newly characterized molecular phenotypes distinguished acquired resistant components of Y-50049 from innate stress response of its progenitor Y-12632. These findings also raised important questions on how to address more deeply ingrained changes in addition to local renovations for yeast adaptation. An early review on understandings of yeast tolerance to these inhibitory compounds is available and its contents omitted here to avoid redundancy. Controversial and confusing issues on identification of yeast resistance to furfural and HMF are further clarified aiming improved future research. Propositions and perspectives on research understanding molecular mechanisms of yeast resistance and future improvements are also presented. KEY POINTS: • Distinguished adapted resistance from innate stress response in yeast. • Defined pathway-based molecular phenotypes of yeast resistance. • Proposed genomic insight and perspectives on yeast resistance and adaptation.

Ribosome-Profiling Reveals Restricted Post Transcriptional Expression of Antiviral Cytokines and Transcription Factors during SARS-CoV-2 Infection

The global COVID-19 pandemic caused by SARS-CoV-2 has resulted in over 2.2 million deaths. Disease outcomes range from asymptomatic to severe with, so far, minimal genotypic change to the virus so understanding the host response is paramount. Transcriptomics has become incredibly important in understanding host-pathogen interactions; however, post-transcriptional regulation plays an important role in infection and immunity through translation and mRNA stability, allowing tight control over potent host responses by both the host and the invading virus. Here, we apply ribosome profiling to assess post-transcriptional regulation of host genes during SARS-CoV-2 infection of a human lung epithelial cell line (Calu-3). We have identified numerous transcription factors (JUN, ZBTB20, ATF3, HIVEP2 and EGR1) as well as select antiviral cytokine genes, namely IFNB1, IFNL1,2 and 3, IL-6 and CCL5, that are restricted at the post-transcriptional level by SARS-CoV-2 infection and discuss the impact this would have on the host response to infection. This early phase restriction of antiviral transcripts in the lungs may allow high viral load and consequent immune dysregulation typically seen in SARS-CoV-2 infection.

Ribo-ODDR: Oligo design pipeline for experiment-specific rRNA depletion in ribo-seq

Motivation

Ribosome Profiling (Ribo-seq) has revolutionized the study of RNA translation by providing information on ribosome positions across all translated RNAs with nucleotide-resolution. Yet several technical limitations restrict the sequencing depth of such experiments, the most common of which is the overabundance of rRNA fragments. Various strategies can be employed to tackle this issue, including the use of commercial rRNA depletion kits. However, as they are designed for more standardized RNAseq experiments, they may perform suboptimally in Ribo-seq. In order to overcome this, it is possible to use custom biotinylated oligos complementary to the most abundant rRNA fragments, however currently no computational framework exists to aid the design of optimal oligos.

Results

Here, we first show that a major confounding issue is that the rRNA fragments generated via Ribo-seq vary significantly with differing experimental conditions, suggesting that a ‘one-size-fits-all’ approach may be inefficient. Therefore we developed Ribo-ODDR, an oligo design pipeline integrated with a user-friendly interface that assists in oligo selection for efficient experiment-specific rRNA depletion. Ribo-ODDR uses preliminary data to identify the most abundant rRNA fragments, and calculates the rRNA depletion efficiency of potential oligos. We experimentally show that Ribo-ODDR designed oligos outperform commercially available kits and lead to a significant increase in rRNA depletion in Ribo-seq.

Availability and implementation

Ribo-ODDR is freely accessible at https://github.com/fallerlab/Ribo-ODDR.

Supplementary information

Supplementary data are available at Bioinformatics online.

Uncovering de novo gene birth in yeast using deep transcriptomics

De novo gene origination has been recently established as an important mechanism for the formation of new genes. In organisms with a large genome, intergenic and intronic regions provide plenty of raw material for new transcriptional events to occur, but little is know about how de novo transcripts originate in more densely-packed genomes. Here, we identify 213 de novo originated transcripts in Saccharomyces cerevisiae using deep transcriptomics and genomic synteny information from multiple yeast species grown in two different conditions. We find that about half of the de novo transcripts are expressed from regions which already harbor other genes in the opposite orientation; these transcripts show similar expression changes in response to stress as their overlapping counterparts, and some appear to translate small proteins. Thus, a large fraction of de novo genes in yeast are likely to co-evolve with already existing genes.

Translational landscape and protein biogenesis demands of the early secretory pathway in Komagataella phaffii

Background

Eukaryotes use distinct networks of biogenesis factors to synthesize, fold, monitor, traffic, and secrete proteins. During heterologous expression, saturation of any of these networks may bottleneck titer and yield. To understand the flux through various routes into the early secretory pathway, we quantified the global and membrane-associated translatomes of Komagataella phaffii.

Results

By coupling Ribo-seq with long-read mRNA sequencing, we generated a new annotation of protein-encoding genes. By using Ribo-seq with subcellular fractionation, we quantified demands on co- and posttranslational translocation pathways. During exponential growth in rich media, protein components of the cell-wall represent the greatest number of nascent chains entering the ER. Transcripts encoding the transmembrane protein PMA1 sequester more ribosomes at the ER membrane than any others. Comparison to Saccharomyces cerevisiae reveals conservation in the resources allocated by gene ontology, but variation in the diversity of gene products entering the secretory pathway.

Conclusion

A subset of host proteins, particularly cell-wall components, impose the greatest biosynthetic demands in the early secretory pathway. These proteins are potential targets in strain engineering aimed at alleviating bottlenecks during heterologous protein production.

Acute stress drives global repression through two independent RNA polymerase II stalling events in Saccharomyces

In multicellular eukaryotes, RNA polymerase (Pol) II pauses transcription ~30-50 bp after initiation. While the budding yeast Saccharomyces has its transcription mechanisms mostly conserved with other eukaryotes, it appears to lack this fundamental promoter-proximal pausing. However, we now report that nearly all yeast genes, including constitutive and inducible genes, manifest two distinct transcriptional stall sites that are brought on by acute environmental signaling (e.g., peroxide stress). Pol II first stalls at the pre-initiation stage before promoter clearance, but after DNA melting and factor acquisition, and may involve inhibited dephosphorylation. The second stall occurs at the +2 nucleosome. It acquires most, but not all, elongation factor interactions. Its regulation may include Bur1/Spt4/5. Our results suggest that a double Pol II stall is a mechanism to downregulate essentially all genes in concert.

Mechanisms of sensing and response to proteotoxic stress

Cells are continuously subject to various stresses, battling both exogenous insults as well as toxic by-products of normal cellular metabolism and nutrient deprivation. Throughout the millennia, cells developed a core set of general stress responses that promote survival and reproduction under adverse circumstances. Past and current research efforts have been devoted to understanding how cells sense stressors and how that input is deciphered and transduced, resulting in stimulation of stress management pathways. A prime element of cellular stress responses is the increased transcription and translation of proteins specialized in managing and mitigating distinct types of stress. In this review, we focus on recent developments in our understanding of cellular sensing of proteotoxic stressors that impact protein synthesis, folding, and maturation provided by the model eukaryote the budding yeast, Saccharomyces cerevisiae, with reference to similarities and differences with other model organisms and humans.

Building blocks are synthesized on demand during the yeast cell cycle

For cells to replicate, a sufficient supply of biosynthetic precursors is needed, necessitating the concerted action of metabolism and protein synthesis during progressive phases of cell division. A global understanding of which biosynthetic processes are involved and how they are temporally regulated during replication is, however, currently lacking. Here, quantitative multiomics analysis is used to generate a holistic view of the eukaryal cell cycle, using the budding yeast Saccharomyces cerevisiae Protein synthesis and central carbon pathways such as glycolysis and amino acid metabolism are shown to synchronize their respective abundance profiles with division, with pathway-specific changes in metabolite abundance also being reflected by a relative increase in mitochondrial volume, as shown by quantitative fluorescence microscopy. These results show biosynthetic precursor production to be temporally regulated to meet phase-specific demands of eukaryal cell division.

Pathway-based signature transcriptional profiles as tolerance phenotypes for the adapted industrial yeast Saccharomyces cerevisiae resistant to furfural and HMF

The industrial yeast Saccharomyces cerevisiae has a plastic genome with a great flexibility in adaptation to varied conditions of nutrition, temperature, chemistry, osmolarity, and pH in diversified applications. A tolerant strain against 2-furaldehyde (furfural) and 5-hydroxymethyl-2-furaldehyde (HMF) was successfully obtained previously by adaptation through environmental engineering toward development of the next-generation biocatalyst. Using a time-course comparative transcriptome analysis in response to a synergistic challenge of furfural-HMF, here we report tolerance phenotypes of pathway-based transcriptional profiles as components of the adapted defensive system for the tolerant strain NRRL Y-50049. The newly identified tolerance phenotypes were involved in biosynthesis superpathway of sulfur amino acids, defensive reduction-oxidation reaction process, cell wall response, and endogenous and exogenous cellular detoxification. Key transcription factors closely related to these pathway-based components, such as Yap1, Met4, Met31/32, Msn2/4, and Pdr1/3, were also presented. Many important genes in Y-50049 acquired an enhanced transcription background and showed continued increased expressions during the entire lag phase against furfural-HMF. Such signature expressions distinguished tolerance phenotypes of Y-50049 from the innate stress response of its progenitor NRRL Y-12632, an industrial type strain. The acquired yeast tolerance is believed to be evolved in various mechanisms at the genomic level. Identification of legitimate tolerance phenotypes provides a basis for continued investigations on pathway interactions and dissection of mechanisms of yeast tolerance and adaptation at the genomic level.

Expanding Role of Ubiquitin in Translational Control

The eukaryotic proteome has to be precisely regulated at multiple levels of gene expression, from transcription, translation, and degradation of RNA and protein to adjust to several cellular conditions. Particularly at the translational level, regulation is controlled by a variety of RNA binding proteins, translation and associated factors, numerous enzymes, and by post-translational modifications (PTM). Ubiquitination, a prominent PTM discovered as the signal for protein degradation, has newly emerged as a modulator of protein synthesis by controlling several processes in translation. Advances in proteomics and cryo-electron microscopy have identified ubiquitin modifications of several ribosomal proteins and provided numerous insights on how this modification affects ribosome structure and function. The variety of pathways and functions of translation controlled by ubiquitin are determined by the various enzymes involved in ubiquitin conjugation and removal, by the ubiquitin chain type used, by the target sites of ubiquitination, and by the physiologic signals triggering its accumulation. Current research is now elucidating multiple ubiquitin-mediated mechanisms of translational control, including ribosome biogenesis, ribosome degradation, ribosome-associated protein quality control (RQC), and redox control of translation by ubiquitin (RTU). This review discusses the central role of ubiquitin in modulating the dynamism of the cellular proteome and explores the molecular aspects responsible for the expanding puzzle of ubiquitin signals and functions in translation.

Intestinal response to dietary manganese depletion inDrosophila

Metabolic adaptations to manganese deficiency.

The Impact of Oxidative Stress on Ribosomes: From Injury to Regulation

The ribosome is a complex ribonucleoprotein-based molecular machine that orchestrates protein synthesis in the cell. Both ribosomal RNA and ribosomal proteins can be chemically modified by reactive oxygen species, which may alter the ribosome′s functions or cause a complete loss of functionality. The oxidative damage that ribosomes accumulate during their lifespan in a cell may lead to reduced or faulty translation and contribute to various pathologies. However, remarkably little is known about the biological consequences of oxidative damage to the ribosome. Here, we provide a concise summary of the known types of changes induced by reactive oxygen species in rRNA and ribosomal proteins and discuss the existing experimental evidence of how these modifications may affect ribosome dynamics and function. We emphasize the special role that redox-active transition metals, such as iron, play in ribosome homeostasis and stability. We also discuss the hypothesis that redox-mediated ribosome modifications may contribute to adaptive cellular responses to stress.