Attenuating ribosome load improves protein output from mRNA by limiting translation-dependent mRNA decay

Unlock the sustained therapeutic efficacy of mRNA

mRNA therapies have emerged as a transformative class of medicines, offering immense potential across a diverse array of applications. This progress has been particularly evident in the wake of the success of lipid nanoparticle (LNP)-based mRNA vaccines during the COVID-19 pandemic. As these applications expand, the demand for sustained protein production has become increasingly critical. However, conventional mRNA therapies face significant challenges, including inherent RNA instability and suboptimal expression efficiency, often requiring repeated dosing to maintain therapeutic efficacy over time. This review highlights recent advances in strategies to prolong the therapeutic efficacy of LNP-mRNA systems. We focus on preclinical and emerging approaches aimed at extending the period of protein translation by engineering both the mRNA molecule and the LNP delivery system. Sustained protein expression is a cornerstone of mRNA-based therapeutics, and addressing this challenge is vital for unlocking their therapeutic potential. We hope this review provides valuable insights to guide the development of optimized delivery platforms for LNP-mRNA therapeutics.

A generative language model decodes contextual constraints on codon choice for mRNA design

The genetic code allows multiple synonymous codons to encode the same amino acid, creating a vast sequence space for protein-coding regions. Codon choice can impact mRNA function and protein output, a consideration newly relevant with advances in mRNA technology. Genomes preferentially use some codons, but simple optimization methods that select preferred codons miss complex contextual patterns. We present Trias, an encoder-decoder language model trained on millions of eukaryotic coding sequences. Trias learns codon usage rules directly from sequence data, integrating local and global dependencies to generate species-specific codon sequences that align with biological constraints. Without explicit training on protein expression, Trias generates sequences and scores that correlate strongly with experimental measurements of mRNA stability, ribosome load, and protein output. The model outperforms commercial codon optimization tools in generating sequences resembling high-expression codon sequence variants. By modeling codon usage in context, Trias offers a data-driven framework for synthetic mRNA design and for understanding the molecular and evolutionary principles behind codon choice.

mRNAdesigner: an integrated web server for optimizing mRNA design and protein translation in eukaryotes

Messenger RNA (mRNA) therapy has revolutionized modern medicine through its rapid development capabilities and ability to induce effective immune responses, becoming a powerful weapon against infectious diseases. The expression level of target proteins from mRNA sequences is primarily influenced by translational efficiency and stability, which can be significantly enhanced by modifying the 5' and 3' untranslated regions (UTRs), codon adaptation index, GC content, and secondary structure. To address the challenges of optimizing mRNA design, we have developed mRNAdesigner (https://www.biosino.org/mRNAdesigner/), a web server specifically designed to improve mRNA stability and translational efficiency in eukaryotes. Users can input a coding sequence (CDS) along with optional 5' UTR and 3' UTR, and the tool optimizes the CDS by reducing unpaired regions, minimizing complex stem-loop structures, and mitigating the use of rare codons while adhering to user-defined GC content preferences. Additionally, mRNAdesigner identifies optimal UTR sequences to enhance translation efficiency and stability. As an open-access computational resource, mRNAdesigner supports full-length mRNA design, enabling researchers to generate high-expression mRNA sequences for efficient protein production in eukaryotic expression systems, providing extra support for vaccine development and protein therapeutics. This is the first such tool that was made open accessible to the public.

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.

Optimizing Protein Production in the One-Pot PURE System: Insights into Reaction Composition and Expression Efficiency

The One-Pot PURE (Protein synthesis Using Recombinant Elements) system simplifies the preparation of traditional PURE systems by coculturing and purifying 36 essential proteins for gene expression in a single step, enhancing accessibility and affordability for widespread laboratory adoption and customization. However, replicating this protocol to match the productivity of traditional PURE systems can take considerable time and effort due to uncharacterized variability. In this work, we observed unstable PURE protein expression in the original One-Pot PURE strains, E. coli M15/pREP4 and BL21(DE3), and addressed this issue using glucose-mediated catabolite repression to minimize burdensome background expression. We also identified several limitations making the M15/pREP4 strain unsuitable for PURE protein expression, including coculture incompatibility with BL21(DE3) and uncharacterized proteolytic activity. We showed that consolidating all expression vectors into a protease-deficient BL21(DE3) strain minimized proteolysis, led to more uniform coculture cell growth at the time of induction, and improved the stoichiometry of critical translation initiation factors in the final PURE mixture for efficient cell-free protein production. In addition to optimizing the One-Pot PURE protein composition, we found that variations in commercial energy solution formulations could compensate for suboptimal PURE protein stoichiometry. Notably, altering the source of E. coli tRNAs in the energy solution alone led to significant differences in the expression capacity of cell-free reactions, highlighting the importance of tRNA codon usage in influencing protein expression yield. Taken together, this work systematically investigates the proteome and biochemical factors influencing the One-Pot PURE system productivity, offering insights to enhance its robustness and adaptability across laboratories.

A Luciferase-Based Approach for Functional Screening of 5' and 3' Untranslated Regions of the mRNA Component for mRNA Vaccines

Background/Objectives: The recent COVID-19 pandemic caused by SARS-CoV-2 infection has highlighted the need for protocols for rapid development of efficient screening methods to search for the optimal mRNA vaccine structures against mutable viral agents. The unmatched success of mRNA vaccines by Pfizer and Moderna encoding the spike protein of SARS-CoV-2 confirms the potential of lipid nanoparticles for mRNA delivery for an accelerated development of new vaccines. The efficacy of vaccination and the production cost of mRNA-based vaccines largely depend on the composition of mRNA components, since the synthesis of an immunogenic protein requires precise and efficient translation in vivo. The composition of 5' and 3' UTR combinations of mRNA has a strong impact on the translation efficiency. The major objective of this study was to increase the probability of producing the immunogenic protein encoded by vaccine mRNA. For this purpose, we proposed to find a new combination of natural UTRs and, in parallel with that, to design and test the system for in vivo selection of translationally active UTRs. Methods: By using Ribo-Seq analysis, sets of candidate short UTRs were generated. These UTRs were tested both in cell cultures and in mice for effective production of secreted nanoluciferase (NLuc) and the S protein of SARS-CoV-2. A combination of the most effective UTRs was used to generate a prototype of an mRNA vaccine capable of inducing neutralizing antibodies against coronavirus. Results: The usefulness of the selected UTRs for vaccine development was tested by implicating the full-length coding sequence of SARS-CoV-2 S protein to produce the main immunogen. As a result, the system for functional screening of UTRs was created by using the NLuc gene. Conclusions: The proposed approach allows non-invasive quantitative assessment of the translational activity of UTRs in the blood serum of mice. By using the full-length sequence of SARS-CoV-2 S protein as a prototype, we demonstrated that the combination of UTRs selected using our luciferase-based reporter assay induces IgG titers and neutralization rates comparable to those obtained by using UTRs from commercial S-protein-based mRNA vaccines.

Sequencing technologies to measure translation in single cells

Translation is one of the most energy-intensive processes in a cell and, accordingly, is tightly regulated. Genome-wide methods to measure translation and the translatome and to study the complex regulation of protein synthesis have enabled unprecedented characterization of this crucial step of gene expression. However, technological limitations have hampered our understanding of translation control in multicellular tissues, rare cell types and dynamic cellular processes. Recent optimizations, adaptations and new techniques have enabled these measurements to be made at single-cell resolution. In this Progress, we discuss single-cell sequencing technologies to measure translation, including ribosome profiling, ribosome affinity purification and spatial translatome methods.

mRNA-based vaccines and therapies - a revolutionary approach for conquering fast-spreading infections and other clinical applications: a review

Since the beginning of the COVID-19 pandemic, the development of messenger RNA (mRNA) vaccines has made significant progress in the pharmaceutical industry. The two COVID-19 mRNA vaccines from Moderna and Pfizer/BioNTech have been approved for marketing and have made significant contributions to preventing the spread of SARS-CoV-2. In addition, mRNA therapy has brought hope to some diseases that do not have specific treatment methods or are difficult to treat, such as the Zika virus and influenza virus infections, as well as the prevention and treatment of tumors. With the rapid development of in vitro transcription (IVT) technology, delivery systems, and adjuvants, mRNA therapy has also been applied to hereditary diseases such as Fabry's disease. This article reviews the recent development of mRNA vaccines for structural modification, treatment and prevention of different diseases; delivery carriers and adjuvants; and routes of administration to promote the clinical application of mRNA therapies.

Multi-objective computational optimization of human 5' UTR sequences

The computational design of messenger RNA (mRNA) sequences is a critical technology for both scientific research and industrial applications. Recent advances in prediction and optimization models have enabled the automatic scoring and optimization of $5^\prime $ UTR sequences, key upstream elements of mRNA. However, fully automated design of $5^\prime $ UTR sequences with more than two objective scores has not yet been explored. In this study, we present a computational pipeline that optimizes human $5^\prime $ UTR sequences in a multi-objective framework, addressing up to four distinct and conflicting objectives. Our work represents an important advancement in the multi-objective computational design of mRNA sequences, paving the way for more sophisticated mRNA engineering.

Considerations for mRNA Product Development, Regulation and Deployment Across the Lifecycle

With the successful deployment of several mRNA vaccines against SARS-CoV-2, an mRNA vaccine against RSV (respiratory syncytial virus) and a large pipeline of mRNA products against other infectious diseases, cancers and rare diseases, it is important to examine the whole product lifecycle. mRNA technology enables product design, testing and manufacturing systems to be rapidly developed, but these advantages can be lost if other factors that determine public access are not closely considered. This review analyzes key aspects of the mRNA product lifecycle including candidate design, manufacturing, quality systems and product safety and storage. Regulatory thinking is well advanced in some countries but not others, but more thought on the regulation of mRNA vaccines outside of a pandemic situation as well as mRNA therapeutics including individual neoantigen therapies and rare disease treatments is needed. Consumer acceptance-the "social license to operate" around mRNA products-is critical for their uptake, particularly outside of a pandemic.

Current Analytical Strategies for mRNA-Based Therapeutics

Recent advancements in mRNA technology, utilized in vaccines, immunotherapies, protein replacement therapies, and genome editing, have emerged as promising and increasingly viable treatments. The rapid, potent, and transient properties of mRNA-encoded proteins make them attractive tools for the effective treatment of a variety of conditions, ranging from infectious diseases to cancer and single-gene disorders. The capability for rapid and large-scale production of mRNA therapeutics fueled the global response to the COVID-19 pandemic. For effective clinical implementation, it is crucial to deeply characterize and control important mRNA attributes such as purity/integrity, identity, structural quality features, and functionality. This implies the use of powerful and advanced analytical techniques for quality control and characterization of mRNA. Improvements in analytical techniques such as electrophoresis, chromatography, mass spectrometry, sequencing, and functionality assessments have significantly enhanced the quality and detail of information available for product and process characterization, as well as for routine stability and release testing. Here, we review the latest advancements in analytical techniques for the characterization of mRNA-based therapeutics, typically employed by the biopharmaceutical industry for eventual market release.

Macroevolutionary divergence of gene expression driven by selection on protein abundance

The regulation of messenger RNA (mRNA) and protein abundances is well-studied, but less is known about the evolutionary processes shaping their relationship. To address this, we derived a new phylogenetic model and applied it to multispecies mammalian data. Our analyses reveal (i) strong stabilizing selection on protein abundances over macroevolutionary time, (ii) mutations affecting mRNA abundances minimally impact protein abundances, (iii) mRNA abundances evolve under selection to align with protein abundances, and (iv) mRNA abundances adapt faster than protein abundances owing to greater mutational opportunity. These conclusions are supported by comparisons of model parameters with independent functional genomic data. By decomposing mutational and selective influences on mRNA-protein dynamics, our approach provides a framework for discovering the evolutionary rules that drive divergence in gene expression.

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.

mRNA Vaccines: Design Principles, Mechanisms, and Manufacturing-Insights From COVID-19 as a Model for Combating Infectious Diseases

The full approval of two SARS-CoV-2 mRNA vaccines, Comirnaty and Spikevax, has greatly accelerated the development of numerous mRNA vaccine candidates targeting infectious diseases and cancer. mRNA vaccines provide a rapid, safe, and versatile manufacturing process while eliciting strong humoral and cellular immune responses, making them particularly beneficial for addressing emerging pandemics. Recent advancements in modified nucleotides and lipid nanoparticle delivery systems have further emphasized the potential of this vaccine platform. Despite these transformative opportunities, significant improvements are needed to enhance vaccine efficacy, stability, and immunogenicity. This review outlines the fundamentals of mRNA vaccine design, the manufacturing process, and administration strategies, along with various optimization approaches. It also offers a comprehensive overview of the mRNA vaccine candidates developed since the onset of the COVID-19 pandemic, the challenges posed by emerging SARS-CoV-2 variants, and current strategies to address these variants. Finally, we discuss the potential of broad-spectrum and combined mRNA vaccines and examine the challenges and future prospects of the mRNA vaccine platform.

Translation efficiency covariation across cell types is a conserved organizing principle of mammalian transcriptomes

Characterization of shared patterns of RNA expression between genes across conditions has led to the discovery of regulatory networks and novel biological functions. However, it is unclear if such coordination extends to translation, a critical step in gene expression. Here, we uniformly analyzed 3,819 ribosome profiling datasets from 117 human and 94 mouse tissues and cell lines. We introduce the concept of Translation Efficiency Covariation (TEC), identifying coordinated translation patterns across cell types. We nominate potential mechanisms driving shared patterns of translation regulation. TEC is conserved across human and mouse cells and helps uncover gene functions. Moreover, our observations indicate that proteins that physically interact are highly enriched for positive covariation at both translational and transcriptional levels. Our findings establish translational covariation as a conserved organizing principle of mammalian transcriptomes.

Codon optimality modulates cellular stress and innate immune responses triggered by exogenous RNAs

The COVID-19 mRNA vaccines demonstrated the power of mRNA medicines. Despite advancements in sequence design, evidence regarding the preferential use of synonymous codons on cellular stress and innate immune responses is lacking. To this end, we developed a proprietary codon optimality matrix to re-engineer the coding sequences of three luciferase reporters. We demonstrate that optimal mRNAs elicited dramatic increases in luciferase activities compared to non-optimal sequences. Notably, transfecting an optimal RNA affects the translation of other RNAs in the cell including control transcripts in dual luciferase assays. This held true in multiple cell lines and for an unrelated reporter. Further, non-optimal mRNAs preferentially activated innate immune pathways and the phosphorylation of the translation initiation factor eIF2α, a central event of the integrated stress response. Using nucleoside-modified or circular RNAs partially or fully abrogated these responses. Finally, we show that circularizing RNAs enhances both RNA lifespan and durability of protein expression. Our results show that RNA sequence, composition, and structure all govern RNA translatability. However, we also show that RNA sequences with poor codon optimality are immunogenic and induce cellular stress. Hence, RNA sequence engineering, chemical, and topological modifications must all be combined to elicit favorable therapeutic outcomes.

IL7R, GZMA and CD8A serve as potential molecular biomarkers for sepsis based on bioinformatics analysis

Purpose

Sepsis is an unusual systemic reaction to what is sometimes an otherwise ordinary infection, and it probably represents a pattern of response by the immune system to injury. However, the relationship between biomarkers and sepsis remains unclear. This study aimed to find potential molecular biomarkers, which could do some help to patients with sepsis.

Methods

The sepsis dataset GSE28750, GSE57065 was downloaded from the GEO database, and ten patients with or without sepsis from our hospital were admitted for RNA-seq and the differentially expressed genes (DEGs) were screened. The Metascape database was used for functional enrichment analysis and was used to found the differential gene list. Protein-protein interaction network was used and further analyzed by using Cytoscape and STRING. Logistic regression and Correlation analysis were used to find the potential molecular biomarkers.

Results

Taking the intersection of the three datasets yielded 287 differential genes. The enrichment results included Neutrophil degranulation, leukocyte activation, immune effectors process, positive regulation of immune response, regulation of leukocyte activation. The top 10 key genes of PPI connectivity were screened using cytoHubba plugin, which were KLRK1, KLRB1, IL7R, GZMA, CD27, PRF1, CD8A, CD2, IL2RB, and GZMB. All of the hub genes are higher expressed in health group of different databases. Logistic regression showed that IL7R, GZMA and CD8A proteins were analyzed and all of them were statistically significant. Correlation analysis showed that there was a statistically significant correlation between IL7R, GZMA and CD8A.

Conclusion

KLRK1, KLRB1, IL7R, GZMA, CD27, PRF1, CD8A, CD2, IL2RB, GZMB are key genes in sepsis, which associated with the development of sepsis. However, IL7R, GZMA and CD8A may serve as the attractively potential molecular biomarkers for sepsis.

Enhancing RNA-lipid nanoparticle delivery: Organ- and cell-specificity and barcoding strategies

Recent advancements in RNA therapeutics highlight the critical need for precision gene delivery systems that target specific organs and cells. Lipid nanoparticles (LNPs) have emerged as key vectors in delivering mRNA and siRNA, offering protection against enzymatic degradation, enabling targeted delivery and cellular uptake, and facilitating RNA cargo release into the cytosol. This review discusses the development and optimization of organ- and cell-specific LNPs, focusing on their design, mechanisms of action, and therapeutic applications. We explore innovations such as DNA/RNA barcoding, which facilitates high-throughput screening and precise adjustments in formulations. We address major challenges, including improving endosomal escape, minimizing off-target effects, and enhancing delivery efficiencies. Notable clinical trials and recent FDA approvals illustrate the practical applications and future potential of LNP-based RNA therapies. Our findings suggest that while considerable progress has been made, continued research is essential to resolve existing limitations and bridge the gap between preclinical and clinical evaluation of the safety and efficacy of RNA therapeutics. This review highlights the dynamic progress in LNP research. It outlines a roadmap for future advancements in RNA-based precision medicine.

Calibrated ribosome profiling assesses the dynamics of ribosomal flux on transcripts

Ribosome profiling, which is based on deep sequencing of ribosome footprints, has served as a powerful tool for elucidating the regulatory mechanism of protein synthesis. However, the current method has substantial issues: contamination by rRNAs and the lack of appropriate methods to measure ribosome numbers in transcripts. Here, we overcome these hurdles through the development of "Ribo-FilterOut", which is based on the separation of footprints from ribosome subunits by ultrafiltration, and "Ribo-Calibration", which relies on external spike-ins of stoichiometrically defined mRNA-ribosome complexes. A combination of these approaches estimates the number of ribosomes on a transcript, the translation initiation rate, and the overall number of translation events before its decay, all in a genome-wide manner. Moreover, our method reveals the allocation of ribosomes under heat shock stress, during aging, and across cell types. Our strategy of modified ribosome profiling measures kinetic and stoichiometric parameters of cellular translation across the transcriptome.

Respiratory Syncytial Virus (RSV) optimizes the translational landscape during infection

Viral infection often triggers eukaryotic initiator factor 2α (eIF2α) phosphorylation, leading to global 5'-cap-dependent translation inhibition. RSV encodes messenger RNAs (mRNAs) mimicking 5'-cap structures of host mRNAs and thus inhibition of cap-dependent translation initiation would likely also reduce viral translation. We confirmed that RSV limits widespread translation initiation inhibition and unexpectedly found that the fraction of ribosomes within polysomes increases during infection, indicating higher ribosome loading on mRNAs during infection. We found that AU-rich host transcripts that are less efficiently translated under normal conditions become more efficient at recruiting ribosomes, similar to RSV transcripts. Viral transcripts are transcribed in cytoplasmic inclusion bodies, where the viral AU-rich binding protein M2-1 has been shown to bind viral transcripts and shuttle them into the cytoplasm. We further demonstrated that M2-1 is found on polysomes, and that M2-1 might deliver host AU-rich transcripts for translation.

Recent Advancements in mRNA Vaccines: From Target Selection to Delivery Systems

mRNA vaccines are leading a medical revolution. mRNA technologies utilize the host's own cells as bio-factories to produce proteins that serve as antigens. This revolutionary approach circumvents the complicated processes involved in traditional vaccine production and empowers vaccines with the ability to respond to emerging or mutated infectious diseases rapidly. Additionally, the robust cellular immune response elicited by mRNA vaccines has shown significant promise in cancer treatment. However, the inherent instability of mRNA and the complexity of tumor immunity have limited its broader application. Although the emergence of pseudouridine and ionizable cationic lipid nanoparticles (LNPs) made the clinical application of mRNA possible, there remains substantial potential for further improvement of the immunogenicity of delivered antigens and preventive or therapeutic effects of mRNA technology. Here, we review the latest advancements in mRNA vaccines, including but not limited to target selection and delivery systems. This review offers a multifaceted perspective on this rapidly evolving field.

Hypoxia and inflammation induce synergistic transcriptome turnover in macrophages

Macrophages are effector immune cells that experience substantial changes to oxygenation when transiting through tissues, especially when entering tumors or infected wounds. How hypoxia alters gene expression and macrophage effector function at the post-transcriptional level remains poorly understood. Here, we use TimeLapse-seq to measure how inflammatory activation modifies the hypoxic response in primary macrophages. Nucleoside recoding sequencing allows the derivation of steady-state transcript levels, degradation rates, and transcriptional synthesis rates from the same dataset. We find that hypoxia produces distinct responses from resting and inflammatory macrophages. Hypoxia induces destabilization of mRNA transcripts, though inflammatory macrophages substantially increase mRNA degradation compared to resting macrophages. Increased RNA turnover results in the upregulation of ribosomal protein genes and downregulation of extracellular matrix components in inflammatory macrophages. Pathways regulated by mRNA decay in vitro are differentially regulated in tumor-associated macrophages implying that mixed stimuli could induce post-transcriptional regulation of macrophage function in solid tumors.

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.