Arginine limitation drives a directed codon-dependent DNA sequence evolution response in colorectal cancer cells

Dengue virus preferentially uses human and mosquito non-optimal codons

Codon optimality refers to the effect that codon composition has on messenger RNA (mRNA) stability and translation level and implies that synonymous codons are not silent from a regulatory point of view. Here, we investigated the adaptation of virus genomes to the host optimality code using mosquito-borne dengue virus (DENV) as a model. We demonstrated that codon optimality exists in mosquito cells and showed that DENV preferentially uses nonoptimal (destabilizing) codons and avoids codons that are defined as optimal (stabilizing) in either human or mosquito cells. Human genes enriched in the codons preferentially and frequently used by DENV are upregulated during infection, and so is the tRNA decoding the nonoptimal and DENV preferentially used codon for arginine. We found that adaptation during single-host passaging in human or mosquito cells results in the selection of synonymous mutations towards DENV's preferred nonoptimal codons that increase virus fitness. Finally, our analyses revealed that hundreds of viruses preferentially use nonoptimal codons, with those infecting a single host displaying an even stronger bias, suggesting that host-pathogen interaction shapes virus-synonymous codon choice.

DNA-binding proteins from MBD through ZF to BEN: recognition of cytosine methylation status by one arginine with two conformations

Maintenance methylation, of palindromic CpG dinucleotides at DNA replication forks, is crucial for the faithful mitotic inheritance of genomic 5-methylcytosine (5mC) methylation patterns. MBD proteins use two arginine residues to recognize symmetrically-positioned methyl groups in fully-methylated 5mCpG/5mCpG and 5mCpA/TpG dinucleotides. In contrast, C2H2 zinc finger (ZF) proteins recognize CpG and CpA, whether methylated or not, within longer specific sequences in a site- and strand-specific manner. Unmethylated CpG sites, often within CpG island (CGI) promoters, need protection by protein factors to maintain their hypomethylated status. Members of the BEN domain proteins bind CGCG or CACG elements within CGIs to regulate gene expression. Despite their overall structural diversity, MBD, ZF and BEN proteins all use arginine residues to recognize guanine, adopting either a 'straight-on' or 'oblique' conformation. The straight-on conformation accommodates a methyl group in the (5mC/T)pG dinucleotide, while the oblique conformation can clash with the methyl group of 5mC, leading to preferential binding of unmethylated sequences.

Threonine fuels glioblastoma through YRDC-mediated codon-biased translational reprogramming

Cancers commonly reprogram translation and metabolism, but little is known about how these two features coordinate in cancer stem cells. Here we show that glioblastoma stem cells (GSCs) display elevated protein translation. To dissect underlying mechanisms, we performed a CRISPR screen and identified YRDC as the top essential transfer RNA (tRNA) modification enzyme in GSCs. YRDC catalyzes the formation of N6-threonylcarbamoyladenosine (t6A) on ANN-decoding tRNA species (A denotes adenosine, and N denotes any nucleotide). Targeting YRDC reduced t6A formation, suppressed global translation and inhibited tumor growth both in vitro and in vivo. Threonine is an essential substrate of YRDC. Threonine accumulated in GSCs, which facilitated t6A formation through YRDC and shifted the proteome to support mitosis-related genes with ANN codon bias. Dietary threonine restriction (TR) reduced tumor t6A formation, slowed xenograft growth and augmented anti-tumor efficacy of chemotherapy and anti-mitotic therapy, providing a molecular basis for a dietary intervention in cancer treatment.

Cysteine substitutants emerge in lung cancer proteomes during arginine restriction

In this issue of Molecular Cell, Yang et al.1 find that arginine-to-cysteine substitutants are enriched in a subset of lung cancer proteomes, potentiated by arginine deprivation, and promote resistance to chemotherapy.

Arginine deprivation enriches lung cancer proteomes with cysteine by inducing arginine-to-cysteine substitutants

Many types of human cancers suppress the expression of argininosuccinate synthase 1 (ASS1), a rate-limiting enzyme for arginine production. Although dependency on exogenous arginine can be harnessed by arginine-deprivation therapies, the impact of ASS1 suppression on the quality of the tumor proteome is unknown. We therefore interrogated proteomes of cancer patients for arginine codon reassignments (substitutants) and surprisingly identified a strong enrichment for cysteine (R>C) in lung tumors specifically. Most R>C events did not coincide with genetically encoded R>C mutations but were likely products of tRNA misalignments. The expression of R>C substitutants was highly associated with oncogenic kelch-like epichlorohydrin (ECH)-associated protein 1 (KEAP1)-pathway mutations and suppressed by intact-KEAP1 in KEAP1-mutated cancer cells. Finally, functional interrogation indicated a key role for R>C substitutants in cell survival to cisplatin, suggesting that regulatory codon reassignments endow cancer cells with more resilience to stress. Thus, we present a mechanism for enriching lung cancer proteomes with cysteines that may affect therapeutic decisions.

The importance of protein domain mutations in cancer therapy

Cancer is a complex disease that is caused by multiple genetic factors. Researchers have been studying protein domain mutations to understand how they affect the progression and treatment of cancer. These mutations can significantly impact the development and spread of cancer by changing the protein structure, function, and signalling pathways. As a result, there is a growing interest in how these mutations can be used as prognostic indicators for cancer prognosis. Recent studies have shown that protein domain mutations can provide valuable information about the severity of the disease and the patient's response to treatment. They may also be used to predict the response and resistance to targeted therapy in cancer treatment. The clinical implications of protein domain mutations in cancer are significant, and they are regarded as essential biomarkers in oncology. However, additional techniques and approaches are required to characterize changes in protein domains and predict their functional effects. Machine learning and other computational tools offer promising solutions to this challenge, enabling the prediction of the impact of mutations on protein structure and function. Such predictions can aid in the clinical interpretation of genetic information. Furthermore, the development of genome editing tools like CRISPR/Cas9 has made it possible to validate the functional significance of mutants more efficiently and accurately. In conclusion, protein domain mutations hold great promise as prognostic and predictive biomarkers in cancer. Overall, considerable research is still needed to better define genetic and molecular heterogeneity and to resolve the challenges that remain, so that their full potential can be realized.

Transfer RNAs as dynamic and critical regulators of cancer progression

Transfer RNAs (tRNAs) have been historically viewed as non-dynamic adaptors that decode the genetic code into proteins. Recent work has uncovered dynamic regulatory roles for these fascinating molecules. Advances in tRNA detection methods have revealed that specific tRNAs can become modulated upon DNA copy number and chromatin alterations and can also be perturbed by oncogenic signalling and transcriptional regulators in cancer cells or the tumour microenvironment. Such alterations in the levels of specific tRNAs have been shown to causally impact cancer progression, including metastasis. Moreover, sequencing methods have identified tRNA-derived small RNAs that influence various aspects of cancer progression, such as cell proliferation and invasion, and could serve as diagnostic and prognostic biomarkers or putative therapeutic targets in various cancers. Finally, there is accumulating evidence, including from genetic models, that specific tRNA synthetases - the enzymes responsible for charging tRNAs with amino acids - can either promote or suppress tumour formation. In this Review, we provide an overview of how deregulation of tRNAs influences cancer formation and progression.

Development of a synthetic biosensor for chemical exchange MRI utilizing in silico optimized peptides

Chemical exchange saturation transfer (CEST) MRI has been identified as a novel alternative to classical diagnostic imaging. Over the last several decades, many studies have been conducted to determine possible CEST agents, such as endogenously expressed compounds or proteins, that can be utilized to produce contrast with minimally invasive procedures and reduced or non-existent levels of toxicity. In recent years there has been an increased interest in the generation of genetically engineered CEST contrast agents, typically based on existing proteins with CEST contrast or modified to produce CEST contrast. We have developed an in silico method for the evolution of peptide sequences to optimize CEST contrast and showed that these peptides could be combined to create de novo biosensors for CEST MRI. A single protein, superCESTide, was designed to be 198 amino acids. SuperCESTide was expressed in E. coli and purified with size exclusion chromatography. The magnetic transfer ratio asymmetry generated by superCESTide was comparable to levels seen in previous CEST reporters, such as protamine sulfate (salmon protamine) and human protamine. These data show that novel peptides with sequences optimized in silico for CEST contrast that utilize a more comprehensive range of amino acids can still produce contrast when assembled into protein units expressed in complex living environments.

Development of a Synthetic Biosensor for Chemical Exchange MRI Utilizing In Silico Optimized Peptides

Chemical Exchange Saturation Transfer (CEST) magnetic resonance imaging (MRI) has been identified as a novel alternative to classical diagnostic imaging. Over the last several decades, many studies have been conducted to determine possible CEST agents, such as endogenously expressed compounds or proteins, that can be utilized to produce contrast with minimally invasive procedures and reduced or non-existent levels of toxicity. In recent years there has been an increased interest in the generation of genetically engineered CEST contrast agents, typically based on existing proteins with CEST contrast or modified to produce CEST contrast. We have developed an in-silico method for the evolution of peptide sequences to optimize CEST contrast and showed that these peptides could be combined to create de novo biosensors for CEST MRI. A single protein, superCESTide 2.0, was designed to be 198 amino acids. SuperCESTide 2.0 was expressed in E. coli and purified with size-exclusion chromatography. The magnetic transfer ratio asymmetry (MTR asym ) generated by superCESTide 2.0 was comparable to levels seen in previous CEST reporters, such as protamine sulfate (salmon protamine, SP), Poly-L-Lysine (PLL), and human protamine (hPRM1). This data shows that novel peptides with sequences optimized in silico for CEST contrast that utilizes a more comprehensive range of amino acids can still produce contrast when assembled into protein units expressed in complex living environments.

How the Competition for Cysteine May Promote Infection of SARS-CoV-2 by Triggering Oxidative Stress

SARS-CoV-2 induces a broad range of clinical manifestations. Besides the main receptor, ACE2, other putative receptors and co-receptors have been described and could become genuinely relevant to explain the different tropism manifested by new variants. In this study, we propose a biochemical model envisaging the competition for cysteine as a key mechanism promoting the infection and the selection of host receptors. The SARS-CoV-2 infection produces ROS and triggers a massive biosynthesis of proteins rich in cysteine; if this amino acid becomes limiting, glutathione levels are depleted and cannot control oxidative stress. Hence, infection succeeds. A receptor should be recognized as a marker of suitable intracellular conditions, namely the full availability of amino acids except for low cysteine. First, we carried out a comparative investigation of SARS-CoV-2 proteins and human ACE2. Then, using hierarchical cluster protein analysis, we searched for similarities between all human proteins and spike produced by the latest variant, Omicron BA.1. We found 32 human proteins very close to spike in terms of amino acid content. Most of these potential SARS-CoV-2 receptors have less cysteine than spike. We suggest that these proteins could signal an intracellular shortage of cysteine, predicting a burst of oxidative stress when used as viral entry mediators.