The Identification of Human Translational Biomarkers of Neuropathic Pain and Cross-Species Validation Using an Animal Model.

Neuropathic pain is a common chronic condition, which remains poorly understood. Many patients receiving treatment continue to experience severe pain, due to limited diagnostic/treatment management programmes. The development of objective clinical diagnostic/treatment strategies requires identification of robust biomarkers of neuropathic pain. To this end, we looked to identify biomarkers of chronic neuropathic pain by assessing gene expression profiles in an animal model of neuropathic pain, and differential gene expression in patients to determine the potential translatability. We demonstrated cross-species validation of several genes including those identified through bioinformatic analysis by assessing their expression in blood samples from neuropathic pain patients, according to conservative assessments of significance measured using Bonferroni-corrected p-values. These include CASP5 (p = 0.00226), CASP8 (p = 0.00587), CASP9 (p = 2.09 × 10-9), FPR2 (p = 0.00278), SH3BGRL3 (p = 0.00633), and TMEM88 (p = 0.00038). A ROC analysis revealed several combinations of genes to show high levels of discriminatory power in the comparison of neuropathic pain patients and control participants, of which the combination SH3BGRL3, TMEM88, and CASP9 achieved the highest level (AUROC = 0.923). The CASP9 gene was found to be common in five combinations of three genes revealing the highest levels of discriminatory power. In contrast, the gene combination PLAC8, ROMO1, and A3GALT2 showed the highest levels of discriminatory power in the comparison of neuropathic pain and nociceptive pain (AUROC = 0.919), when patients were grouped by S-LANSS scores. Molecules that demonstrate an active role in neuropathic pain have the potential to be developed into a biological measure for objective diagnostic tests, or as novel drug targets for improved pain management.

The Identification of Blood Biomarkers of Chronic Neuropathic Pain by Comparative Transcriptomics.

In this study, we recruited 50 chronic pain (neuropathic and nociceptive) and 43 pain-free controls to identify specific blood biomarkers of chronic neuropathic pain (CNP). Affymetrix microarray was carried out on a subset of samples selected 10 CNP and 10 pain-free control participants. The most significant genes were cross-validated using the entire dataset by quantitative real-time PCR (qRT-PCR). In comparative analysis of controls and CNP patients, WLS (P = 4.80 × 10-7), CHPT1 (P = 7.74 × 10-7) and CASP5 (P = 2.30 × 10-5) were highly significant, whilst FGFBP2 (P = 0.00162), STAT1 (P = 0.00223), FCRL6 (P = 0.00335), MYC (P = 0.00335), XCL2 (P = 0.0144) and GZMA (P = 0.0168) were significant in all CNP patients. A three-arm comparative analysis was also carried out with control as the reference group and CNP samples differentiated into two groups of high and low S-LANSS score using a cut-off of 12. STAT1, XCL2 and GZMA were not significant but KIR3DL2 (P = 0.00838), SH2D1B (P = 0.00295) and CXCR31 (P = 0.0136) were significant in CNP high S-LANSS group (S-LANSS score > 12), along with WLS (P = 8.40 × 10-5), CHPT1 (P = 7.89 × 10-4), CASP5 (P = 0.00393), FGFBP2 (P = 8.70 × 10-4) and FCRL6 (P = 0.00199), suggesting involvement of immune pathways in CNP mechanisms. None of the genes was significant in CNP samples with low (< 12) S-LANSS score. The area under the receiver operating characteristic (AUROC) analysis showed that combination of MYC, STAT1, TLR4, CASP5 and WLS gene expression could be potentially used as a biomarker signature of CNP (AUROC - 0.852, (0.773, 0.931 95% CI)).

Evidence in disease and non-disease contexts that nonsense mutations cause altered splicing via motif disruption.

Transcripts containing premature termination codons (PTCs) can be subject to nonsense-associated alternative splicing (NAS). Two models have been evoked to explain this, scanning and splice motif disruption. The latter postulates that exonic cis motifs, such as exonic splice enhancers (ESEs), are disrupted by nonsense mutations. We employ genome-wide transcriptomic and k-mer enrichment methods to scrutinize this model. First, we show that ESEs are prone to disruptive nonsense mutations owing to their purine richness and paucity of TGA, TAA and TAG. The motif model correctly predicts that NAS rates should be low (we estimate 5-30%) and approximately in line with estimates for the rate at which random point mutations disrupt splicing (8-20%). Further, we find that, as expected, NAS-associated PTCs are predictable from nucleotide-based machine learning approaches to predict splice disruption and, at least for pathogenic variants, are enriched in ESEs. Finally, we find that both in and out of frame mutations to TAA, TGA or TAG are associated with exon skipping. While a higher relative frequency of such skip-inducing mutations in-frame than out of frame lends some credence to the scanning model, these results reinforce the importance of considering splice motif modulation to understand the etiology of PTC-associated disease.

Causes and Consequences of Purifying Selection on SARS-CoV-2.

Owing to a lag between a deleterious mutation's appearance and its selective removal, gold-standard methods for mutation rate estimation assume no meaningful loss of mutations between parents and offspring. Indeed, from analysis of closely related lineages, in SARS-CoV-2, the Ka/Ks ratio was previously estimated as 1.008, suggesting no within-host selection. By contrast, we find a higher number of observed SNPs at 4-fold degenerate sites than elsewhere and, allowing for the virus's complex mutational and compositional biases, estimate that the mutation rate is at least 49-67% higher than would be estimated based on the rate of appearance of variants in sampled genomes. Given the high Ka/Ks one might assume that the majority of such intrahost selection is the purging of nonsense mutations. However, we estimate that selection against nonsense mutations accounts for only ∼10% of all the "missing" mutations. Instead, classical protein-level selective filters (against chemically disparate amino acids and those predicted to disrupt protein functionality) account for many missing mutations. It is less obvious why for an intracellular parasite, amino acid cost parameters, notably amino acid decay rate, is also significant. Perhaps most surprisingly, we also find evidence for real-time selection against synonymous mutations that move codon usage away from that of humans. We conclude that there is common intrahost selection on SARS-CoV-2 that acts on nonsense, missense, and possibly synonymous mutations. This has implications for methods of mutation rate estimation, for determining times to common ancestry and the potential for intrahost evolution including vaccine escape.

Transcription, mRNA Export, and Immune Evasion Shape the Codon Usage of Viruses.

The nucleotide composition, dinucleotide composition, and codon usage of many viruses differ from their hosts. These differences arise because viruses are subject to unique mutation and selection pressures that do not apply to host genomes; however, the molecular mechanisms that underlie these evolutionary forces are unclear. Here, we analyzed the patterns of codon usage in 1,520 vertebrate-infecting viruses, focusing on parameters known to be under selection and associated with gene regulation. We find that GC content, dinucleotide content, and splicing and m6A modification-related sequence motifs are associated with the type of genetic material (DNA or RNA), strandedness, and replication compartment of viruses. In an experimental follow-up, we find that the effects of GC content on gene expression depend on whether the genetic material is delivered to the cell as DNA or mRNA, whether it is transcribed by endogenous or exogenous RNA polymerase, and whether transcription takes place in the nucleus or cytoplasm. Our results suggest that viral codon usage cannot be explained by a simple adaptation to the codon usage of the host-instead, it reflects the combination of multiple selective and mutational pressures, including the need for efficient transcription, export, and immune evasion.

Evidence for Strong Mutation Bias toward, and Selection against, U Content in SARS-CoV-2: Implications for Vaccine Design.

Large-scale re-engineering of synonymous sites is a promising strategy to generate vaccines either through synthesis of attenuated viruses or via codon-optimized genes in DNA vaccines. Attenuation typically relies on deoptimization of codon pairs and maximization of CpG dinucleotide frequencies. So as to formulate evolutionarily informed attenuation strategies that aim to force nucleotide usage against the direction favored by selection, here, we examine available whole-genome sequences of SARS-CoV-2 to infer patterns of mutation and selection on synonymous sites. Analysis of mutational profiles indicates a strong mutation bias toward U. In turn, analysis of observed synonymous site composition implicates selection against U. Accounting for dinucleotide effects reinforces this conclusion, observed UU content being a quarter of that expected under neutrality. Possible mechanisms of selection against U mutations include selection for higher expression, for high mRNA stability or lower immunogenicity of viral genes. Consistent with gene-specific selection against CpG dinucleotides, we observe systematic differences of CpG content between SARS-CoV-2 genes. We propose an evolutionarily informed approach to attenuation that, unusually, seeks to increase usage of the already most common synonymous codons. Comparable analysis of H1N1 and Ebola finds that GC3 deviated from neutral equilibrium is not a universal feature, cautioning against generalization of results.