Translation and mRNA Stability Control.

Messenger RNA (mRNA) stability and translational efficiency are two crucial aspects of the post-transcriptional process that profoundly impact protein production in a cell. While it is widely known that ribosomes produce proteins, studies during the past decade have surprisingly revealed that ribosomes also control mRNA stability in a codon-dependent manner, a process referred to as codon optimality. Therefore, codons, the three-nucleotide words read by the ribosome, have a potent effect on mRNA stability and provide cis-regulatory information that extends beyond the amino acids they encode. While the codon optimality molecular mechanism is still unclear, the translation elongation rate appears to trigger mRNA decay. Thus, transfer RNAs emerge as potential master gene regulators affecting mRNA stability. Furthermore, while few factors related to codon optimality have been identified in yeast, the orthologous genes in vertebrates do not necessary share the same functions. Here, we discuss codon optimality findings and gene regulation layers related to codon composition in different eukaryotic species.

Synonymous but Not Silent: The Codon Usage Code for Gene Expression and Protein Folding.

Codon usage bias, the preference for certain synonymous codons, is found in all genomes. Although synonymous mutations were previously thought to be silent, a large body of evidence has demonstrated that codon usage can play major roles in determining gene expression levels and protein structures. Codon usage influences translation elongation speed and regulates translation efficiency and accuracy. Adaptation of codon usage to tRNA expression determines the proteome landscape. In addition, codon usage biases result in nonuniform ribosome decoding rates on mRNAs, which in turn influence the cotranslational protein folding process that is critical for protein function in diverse biological processes. Conserved genome-wide correlations have also been found between codon usage and protein structures. Furthermore, codon usage is a major determinant of mRNA levels through translation-dependent effects on mRNA decay and translation-independent effects on transcriptional and posttranscriptional processes. Here, we discuss the multifaceted roles and mechanisms of codon usage in different gene regulatory processes.

Repertoires of tRNAs: The Couplers of Genomics and Proteomics.

The pool of transfer RNA (tRNA) molecules in cells allows the ribosome to decode genetic information. This repertoire of molecular decoders is positioned in the crossroad of the genome, the transcriptome, and the proteome. Omics and systems biology now allow scientists to explore the entire repertoire of tRNAs of many organisms, revealing basic exciting biology. The tRNA gene set of hundreds of species is now characterized, in addition to the tRNA genes of organelles and viruses. Genes encoding tRNAs for certain anticodon types appear in dozens of copies in a genome, while others are universally absent from any genome. Transcriptome measurement of tRNAs is challenging, but in recent years new technologies have allowed researchers to determine the dynamic expression patterns of tRNAs. These advances reveal that availability of ready-to-translate tRNA molecules is highly controlled by several transcriptional and posttranscriptional regulatory processes. This regulation shapes the proteome according to the cellular state. The tRNA pool profoundly impacts many aspects of cellular and organismal life, including protein expression level, translation accuracy, adequacy of folding, and even mRNA stability. As a result, the shape of the tRNA pool affects organismal health and may participate in causing conditions such as cancer and neurological conditions.

ALKBH1-Mediated tRNA Demethylation Regulates Translation.

tRNA is a central component of protein synthesis and the cell signaling network. One salient feature of tRNA is its heavily modified status, which can critically impact its function. Here, we show that mammalian ALKBH1 is a tRNA demethylase. It mediates the demethylation of N1-methyladenosine (m1A) in tRNAs. The ALKBH1-catalyzed demethylation of the target tRNAs results in attenuated translation initiation and decreased usage of tRNAs in protein synthesis. This process is dynamic and responds to glucose availability to affect translation. Our results uncover reversible methylation of tRNA as a new mechanism of post-transcriptional gene expression regulation.

The Ongoing Quest to Crack the Genetic Code for Protein Production.

Understanding the genetic design principles that determine protein production remains a major challenge. Although the key principles of gene expression were discovered 50 years ago, additional factors are still being uncovered. Both protein-coding and non-coding sequences harbor elements that collectively influence the efficiency of protein production by modulating transcription, mRNA decay, and translation. The influences of many contributing elements are intertwined, which complicates a full understanding of the individual factors. In natural genes, a functional balance between these factors has been obtained in the course of evolution, whereas for genetic-engineering projects, our incomplete understanding still limits optimal design of synthetic genes. However, notable advances have recently been made, supported by high-throughput analysis of synthetic gene libraries as well as by state-of-the-art biomolecular techniques. We discuss here how these advances further strengthen understanding of the gene expression process and how they can be harnessed to optimize protein production.

T helper cells exhibit a dynamic and reversible 3'-UTR landscape.

3' untranslated regions (3' UTRs) are critical elements of messenger RNAs, as they contain binding sites for RNA-binding proteins (RBPs) and microRNAs that affect various aspects of the RNA life cycle including transcript stability and cellular localization. In response to T cell receptor activation, T cells undergo massive expansion during the effector phase of the immune response and dynamically modify their 3' UTRs. Whether this serves to directly regulate the abundance of specific mRNAs or is a secondary effect of proliferation remains unclear. To study 3'-UTR dynamics in T helper cells, we investigated division-dependent alternative polyadenylation (APA). In addition, we generated 3' end UTR sequencing data from naive, activated, memory, and regulatory CD4+ T cells. 3'-UTR length changes were estimated using a nonnegative matrix factorization approach and were compared with those inferred from long-read PacBio sequencing. We found that APA events were transient and reverted after effector phase expansion. Using an orthogonal bulk RNA-seq data set, we did not find evidence of APA association with differential gene expression or transcript usage, indicating that APA has only a marginal effect on transcript abundance. 3'-UTR sequence analysis revealed conserved binding sites for T cell-relevant microRNAs and RBPs in the alternative 3' UTRs. These results indicate that poly(A) site usage could play an important role in the control of cell fate decisions and homeostasis.

Translational Control through Differential Ribosome Pausing during Amino Acid Limitation in Mammalian Cells.

Limitation for amino acids is thought to regulate translation in mammalian cells primarily by signaling through the kinases mTORC1 and GCN2. We find that a selective loss of arginine tRNA charging during limitation for arginine regulates translation through ribosome pausing at two of six arginine codons. Surprisingly, limitation for leucine, an essential and abundant amino acid in protein, results in little or no ribosome pausing. Chemical and genetic perturbation of mTORC1 and GCN2 signaling revealed that their robust response to leucine limitation prevents ribosome pausing, while an insufficient response to arginine limitation leads to loss of tRNA charging and ribosome pausing. Ribosome pausing decreases protein production and triggers premature ribosome termination without reducing mRNA levels. Together, our results suggest that amino acids that are not optimally sensed by the mTORC1 and GCN2 pathways still regulate translation through an evolutionarily conserved mechanism based on codon-specific ribosome pausing.

msqrob2PTM: Differential Abundance and Differential Usage Analysis of MS-Based Proteomics Data at the Posttranslational Modification and Peptidoform Level.

In the era of open-modification search engines, more posttranslational modifications than ever can be detected by LC-MS/MS-based proteomics. This development can switch proteomics research into a higher gear, as PTMs are key in many cellular pathways important in cell proliferation, migration, metastasis, and aging. However, despite these advances in modification identification, statistical methods for PTM-level quantification and differential analysis have yet to catch up. This absence can partly be explained by statistical challenges inherent to the data, such as the confounding of PTM intensities with its parent protein abundance. Therefore, we have developed msqrob2PTM, a new workflow in the msqrob2 universe capable of differential abundance analysis at the PTM and at the peptidoform level. The latter is important for validating PTMs found as significantly differential. Indeed, as our method can deal with multiple PTMs per peptidoform, there is a possibility that significant PTMs stem from one significant peptidoform carrying another PTM, hinting that it might be the other PTM driving the perceived differential abundance. Our workflows can flag both differential peptidoform abundance (DPA) and differential peptidoform usage (DPU). This enables a distinction between direct assessment of differential abundance of peptidoforms (DPA) and differences in the relative usage of peptidoforms corrected for corresponding protein abundances (DPU). For DPA, we directly model the log2-transformed peptidoform intensities, while for DPU, we correct for parent protein abundance by an intermediate normalization step which calculates the log2-ratio of the peptidoform intensities to their summarized parent protein intensities. We demonstrated the utility and performance of msqrob2PTM by applying it to datasets with known ground truth, as well as to biological PTM-rich datasets. Our results show that msqrob2PTM is on par with, or surpassing the performance of, the current state-of-the-art methods. Moreover, msqrob2PTM is currently unique in providing output at the peptidoform level.

A snoRNA-tRNA modification network governs codon-biased cellular states.

The dynamic balance between tRNA supply and codon usage demand is a fundamental principle in the cellular translation economy. However, the regulation and functional consequences of this balance remain unclear. Here, we use PARIS2 interactome capture, structure modeling, conservation analysis, RNA-protein interaction analysis, and modification mapping to reveal the targets of hundreds of snoRNAs, many of which were previously considered orphans. We identify a snoRNA-tRNA interaction network that is required for global tRNA modifications, including 2'-O-methylation and others. Loss of Fibrillarin, the snoRNA-guided 2'-O-methyltransferase, induces global upregulation of tRNA fragments, a large group of regulatory RNAs. In particular, the snoRNAs D97/D133 guide the 2'-O-methylation of multiple tRNAs, especially for the amino acid methionine (Met), a protein-intrinsic antioxidant. Loss of D97/D133 snoRNAs in human HEK293 cells reduced target tRNA levels and induced codon adaptation of the transcriptome and translatome. Both single and double knockouts of D97 and D133 in HEK293 cells suppress Met-enriched proliferation-related gene expression programs, including, translation, splicing, and mitochondrial energy metabolism, and promote Met-depleted programs related to development, differentiation, and morphogenesis. In a mouse embryonic stem cell model of development, knockdown and knockout of D97/D133 promote differentiation to mesoderm and endoderm fates, such as cardiomyocytes, without compromising pluripotency, consistent with the enhanced development-related gene expression programs in human cells. This work solves a decades-old mystery about orphan snoRNAs and reveals a function of snoRNAs in controlling the codon-biased dichotomous cellular states of proliferation and development.

Combination of hydrophobicity and codon usage bias determines sorting of model K+ channel protein to either mitochondria or endoplasmic reticulum.

When the K+ channel-like protein Kesv from Ectocarpus siliculosus virus 1 is heterologously expressed in mammalian cells, it is sorted to the mitochondria. This targeting can be redirected to the endoplasmic reticulum (ER) by altering the codon usage in distinct regions of the gene or by inserting a triplet of hydrophobic amino acids (AAs) into the protein's C-terminal transmembrane domain (ct-TMD). Systematic variations in the flavor of the inserted AAs and/or its codon usage show that a positive charge in the inserted AA triplet alone serves as strong signal for mitochondria sorting. In cases of neutral AA triplets, mitochondria sorting are favored by a combination of hydrophilic AAs and rarely used codons; sorting to the ER exhibits the inverse dependency. This propensity for ER sorting is particularly high when a common codon follows a rarer one in the AA triplet; mitochondria sorting in contrast is supported by codon uniformity. Since parameters like positive charge, hydrophobic AAs, and common codons are known to facilitate elongation of nascent proteins in the ribosome the data suggest a mechanism in which local changes in elongation velocity and co-translational folding in the ct-TMD influence intracellular protein sorting.

The Patterns of Codon Usage between Chordates and Arthropods are Different but Co-evolving with Mutational Biases.

Different frequencies amongst codons that encode the same amino acid (i.e. synonymous codons) have been observed in multiple species. Studies focused on uncovering the forces that drive such codon usage showed that a combined effect of mutational biases and translational selection works to produce different frequencies of synonymous codons. However, only few have been able to measure and distinguish between these forces that may leave similar traces on the coding regions. Here, we have developed a codon model that allows the disentangling of mutation, selection on amino acids and synonymous codons, and GC-biased gene conversion (gBGC) which we employed on an extensive dataset of 415 chordates and 191 arthropods. We found that chordates need 15 more synonymous codon categories than arthropods to explain the empirical codon frequencies, which suggests that the extent of codon usage can vary greatly between animal phyla. Moreover, methylation at CpG sites seems to partially explain these patterns of codon usage in chordates but not in arthropods. Despite the differences between the two phyla, our findings demonstrate that in both, GC-rich codons are disfavored when mutations are GC-biased, and the opposite is true when mutations are AT-biased. This indicates that selection on the genomic coding regions might act primarily to stabilize its GC/AT content on a genome-wide level. Our study shows that the degree of synonymous codon usage varies considerably among animals, but is likely governed by a common underlying dynamic.

Differential transcript usage analysis incorporating quantification uncertainty via compositional measurement error regression modeling.

Differential transcript usage (DTU) occurs when the relative expression of multiple transcripts arising from the same gene changes between different conditions. Existing approaches to detect DTU often rely on computational procedures that can have speed and scalability issues as the number of samples increases. Here we propose a new method, CompDTU, that uses compositional regression to model the relative abundance proportions of each transcript that are of interest in DTU analyses. This procedure leverages fast matrix-based computations that make it ideally suited for DTU analysis with larger sample sizes. This method also allows for the testing of and adjustment for multiple categorical or continuous covariates. Additionally, many existing approaches for DTU ignore quantification uncertainty in the expression estimates for each transcript in RNA-seq data. We extend our CompDTU method to incorporate quantification uncertainty leveraging common output from RNA-seq expression quantification tool in a novel method CompDTUme. Through several power analyses, we show that CompDTU has excellent sensitivity and reduces false positive results relative to existing methods. Additionally, CompDTUme results in further improvements in performance over CompDTU with sufficient sample size for genes with high levels of quantification uncertainty, while also maintaining favorable speed and scalability. We motivate our methods using data from the Cancer Genome Atlas Breast Invasive Carcinoma data set, specifically using RNA-seq data from primary tumors for 740 patients with breast cancer. We show greatly reduced computation time from our new methods as well as the ability to detect several novel genes with significant DTU across different breast cancer subtypes.

SpliceWiz: interactive analysis and visualization of alternative splicing in R.

Alternative splicing (AS) is a crucial mechanism for regulating gene expression and isoform diversity in eukaryotes. However, the analysis and visualization of AS events from RNA sequencing data remains challenging. Most tools require a certain level of computer literacy and the available means of visualizing AS events, such as coverage and sashimi plots, have limitations and can be misleading. To address these issues, we present SpliceWiz, an R package with an interactive Shiny interface that allows easy and efficient AS analysis and visualization at scale. A novel normalization algorithm is implemented to aggregate splicing levels within sample groups, thereby allowing group differences in splicing levels to be accurately visualized. The tool also offers downstream gene ontology enrichment analysis, highlighting ASEs belonging to functional pathways of interest. SpliceWiz is optimized for speed and efficiency and introduces a new file format for coverage data storage that is more efficient than BigWig. Alignment files are processed orders of magnitude faster than other R-based AS analysis tools and on par with command-line tools. Overall, SpliceWiz streamlines AS analysis, enabling reliable identification of functionally relevant AS events for further characterization. SpliceWiz is a Bioconductor package and is also available on GitHub (https://github.com/alexchwong/SpliceWiz).

Cellular energy regulates mRNA degradation in a codon-specific manner.

Codon optimality is a major determinant of mRNA translation and degradation rates. However, whether and through which mechanisms its effects are regulated remains poorly understood. Here we show that codon optimality associates with up to 2-fold change in mRNA stability variations between human tissues, and that its effect is attenuated in tissues with high energy metabolism and amplifies with age. Mathematical modeling and perturbation data through oxygen deprivation and ATP synthesis inhibition reveal that cellular energy variations non-uniformly alter the effect of codon usage. This new mode of codon effect regulation, independent of tRNA regulation, provides a fundamental mechanistic link between cellular energy metabolism and eukaryotic gene expression.

Real-time pandemic surveillance using hospital admissions and mobility data.

Forecasting the burden of COVID-19 has been impeded by limitations in data, with case reporting biased by testing practices, death counts lagging far behind infections, and hospital census reflecting time-varying patient access, admission criteria, and demographics. Here, we show that hospital admissions coupled with mobility data can reliably predict severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission rates and healthcare demand. Using a forecasting model that has guided mitigation policies in Austin, TX, we estimate that the local reproduction number had an initial 7-d average of 5.8 (95% credible interval [CrI]: 3.6 to 7.9) and reached a low of 0.65 (95% CrI: 0.52 to 0.77) after the summer 2020 surge. Estimated case detection rates ranged from 17.2% (95% CrI: 11.8 to 22.1%) at the outset to a high of 70% (95% CrI: 64 to 80%) in January 2021, and infection prevalence remained above 0.1% between April 2020 and March 1, 2021, peaking at 0.8% (0.7-0.9%) in early January 2021. As precautionary behaviors increased safety in public spaces, the relationship between mobility and transmission weakened. We estimate that mobility-associated transmission was 62% (95% CrI: 52 to 68%) lower in February 2021 compared to March 2020. In a retrospective comparison, the 95% CrIs of our 1, 2, and 3 wk ahead forecasts contained 93.6%, 89.9%, and 87.7% of reported data, respectively. Developed by a task force including scientists, public health officials, policy makers, and hospital executives, this model can reliably project COVID-19 healthcare needs in US cities.

Molecular basis of differential receptor usage for naturally occurring CD55-binding and -nonbinding coxsackievirus B3 strains.

Receptor usage defines cell tropism and contributes to cell entry and infection. Coxsackievirus B (CVB) engages coxsackievirus and adenovirus receptor (CAR), and selectively utilizes the decay-accelerating factor (DAF; CD55) to infect cells. However, the differential receptor usage mechanism for CVB remains elusive. This study identified VP3-234 residues (234Q/N/V/D/E) as critical population selection determinants during CVB3 virus evolution, contributing to diverse binding affinities to CD55. Cryoelectron microscopy (cryo-EM) structures of CD55-binding/nonbinding isolates and their complexes with CD55 or CAR were obtained under both neutral and acidic conditions, and the molecular mechanism of VP3-234 residues determining CD55 affinity/specificity for naturally occurring CVB3 strains was elucidated. Structural and biochemical studies in vitro revealed the dynamic entry process of CVB3 and the function of the uncoating receptor CAR with different pH preferences. This work provides detailed insight into the molecular mechanism of CVB infection and contributes to an in-depth understanding of enterovirus attachment receptor usage.

Assembly and comparative analysis of the complete mitochondrial genome of white towel gourd (Luffa cylindrica).

Mitochondria play an important role in the energy production of plant cells through independent genetic systems. This study has aimed to assemble and annotate the functions of the mitochondrial (mt) genome of Luffa cylindrica. The mt genome of L. cylindrica contained two chromosomes with lengths of 380,879 bp and 67,982 bp, respectively. Seventy-seven genes including 39 protein-coding genes, 34 tRNA genes, 3 rRNA genes, and 1 pseudogene, were identified. About 90.63% of the codons ended with A or U bases, and 98.63% of monomers contained A/T, which contributed to the high A/T content (55.91%) of the complete mt genome. Six genes (ATP8, CCMFC, NAD4, RPL10, RPL5 and RPS4) showed positive selection. Phylogenetic analysis indicates that L. cylindrica is closely related to L. acutangula. The present results provide the mt genome of L. cylindrica, which may facilitate possible genetic variation, evolutionary, and molecular breeding studies of L. cylindrica.

Sequence determinants as key regulators in gene expression of T cells.

T cell homeostasis, T cell differentiation, and T cell effector function rely on the constant fine-tuning of gene expression. To alter the T cell state, substantial remodeling of the proteome is required. This remodeling depends on the intricate interplay of regulatory mechanisms, including post-transcriptional gene regulation. In this review, we discuss how the sequence of a transcript influences these post-transcriptional events. In particular, we review how sequence determinants such as sequence conservation, GC content, and chemical modifications define the levels of the mRNA and the protein in a T cell. We describe the effect of different forms of alternative splicing on mRNA expression and protein production, and their effect on subcellular localization. In addition, we discuss the role of sequences and structures as binding hubs for miRNAs and RNA-binding proteins in T cells. The review thus highlights how the intimate interplay of post-transcriptional mechanisms dictate cellular fate decisions in T cells.

Emerging Roles of tRNAs in RNA Virus Infections.

Viruses rely on the host cell translation machinery for efficient synthesis of their own proteins. Emerging evidence highlights different roles for host transfer RNAs (tRNAs) in the process of virus replication. For instance, different RNA viruses manipulate host tRNA pools to favor viral protein translation. Interestingly, specific host tRNAs are used as reverse transcription primers and are packaged into retroviral virions. Recent data also demonstrate the formation of tRNA-derived fragments (tRFs) upon infection to facilitate viral replication. Here, we comprehensively discuss how RNA viruses exploit distinct aspects of the host tRNA biology for their benefit. In light of the recent advances in the field, we propose that host tRNA-related pathways and mechanisms represent promising cellular targets for the development of novel antiviral strategies.

Tissue Usage Preference and Intrinsically Disordered Region Remodeling of Alternative Splicing Derived Proteoforms in the Heart.

A computational analysis of mass spectrometry data was performed to uncover alternative splicing derived protein variants across chambers of the human heart. Evidence for 216 non-canonical isoforms was apparent in the atrium and the ventricle, including 52 isoforms not documented on SwissProt and recovered using an RNA sequencing derived database. Among non-canonical isoforms, 29 show signs of regulation based on statistically significant preferences in tissue usage, including a ventricular enriched protein isoform of tensin-1 (TNS1) and an atrium-enriched PDZ and LIM Domain 3 (PDLIM3) isoform 2 (PDLIM3-2/ALP-H). Examined variant regions that differ between alternative and canonical isoforms are highly enriched with intrinsically disordered regions. Moreover, over two-thirds of such regions are predicted to function in protein binding and RNA binding. The analysis here lends further credence to the notion that alternative splicing diversifies the proteome by rewiring intrinsically disordered regions, which are increasingly recognized to play important roles in the generation of biological function from protein sequences.