Biased Nucleotide Composition and Differential Codon Usage Pattern in HIV-1 and HIV-2

Schlafen14 Impairs HIV-1 Expression in a Codon Usage-Dependent Manner

Schlafen (SLFN) is a family of proteins upregulated by type I interferons with a regulatory role in translation. Intriguingly, SLFN14 associates with the ribosome and can degrade rRNA, tRNA, and mRNA in vitro, but a role in translation is still unknown. Ribosomes are important regulatory hubs during translation elongation of mRNAs rich in rare codons. Therefore, we evaluated the potential role of SLFN14 in the expression of mRNAs enriched in rare codons, using HIV-1 genes as a model. We found that, in a variety of cell types, including primary immune cells, SLFN14 regulates the expression of HIV-1 and non-viral genes based on their codon adaptation index, a measurement of the synonymous codon usage bias; consequently, SLFN14 inhibits the replication of HIV-1. The potent inhibitory effect of SLFN14 on the expression of the rare codon-rich transcript HIV-1 Gag was minimized by codon optimization. Mechanistically, we found that the endoribonuclease activity of SLFN14 is required, and that ribosomal RNA degradation is involved. Therefore, we propose that SLFN14 impairs the expression of HIV-1 transcripts rich in rare codons, in a catalytic-dependent manner.

Different Patterns of Codon Usage and Amino Acid Composition across Primate Lentiviruses

A common feature of the mammalian Lentiviruses (family Retroviridae) is an RNA genome that contains an extremely high frequency of adenine (31.7-38.2%) while being extremely poor in cytosine (13.9-21.2%). Such a biased nucleotide composition has implications for codon usage, causing a striking difference between the frequency of synonymous codons in Lentiviruses and that in their hosts. To test whether primate Lentiviruses present differences in codon and amino acid composition, we assembled a dataset of genome sequences that includes SIV species infecting Old-World monkeys and African apes, HIV-2, and the four groups of HIV-1. Using principal component analysis, we found that HIV-1 shows a significant enrichment in adenine plus thymine in the third synonymous codon position and in adenine and guanine in the first and second nonsynonymous codon positions. Similarly, we observed an enrichment in adenine and in guanine in nonsynonymous first and second codon positions, which affects the amino acid composition of the proteins Gag, Pol, Vif, Vpr, Tat, Rev, Env, and Nef. This result suggests an effect of natural selection in shaping codon usage. Under the hypothesis that the use of synonyms in HIV-1 could reflect adaptation to that of genes expressed in specific cell types, we found a highly significant correlation between codon usage in HIV-1 and monocytes, which was remarkably higher than that with B and T lymphocytes. This finding is in line with the notion that monocytes represent an HIV-1 reservoir in infected patients, and it could help understand how this reservoir is established and maintained.

Analysis of evolutionary and genetic patterns in structural genes of primate lentiviruses

Background

Primate lentiviruses (HIV1, HIV2, and Simian immunodeficiency virus [SIV]) cause immune deficiency, encephalitis, and infectious anemia in mammals such as cattle, cat, goat, sheep, horse, and puma.

Objective

This study was designed and conducted with the main purpose of confirming the overall codon usage pattern of primate lentiviruses and exploring the evolutionary and genetic characteristics commonly or specifically expressed in HIV1, HIV2, and SIV.

Methods

The gag, pol, and env gene sequences of HIV1, HIV2, and SIV were analyzed to determine their evolutionary relationships, nucleotide compositions, codon usage patterns, neutrality, selection pressure (influence of mutational pressure and natural selection), and viral adaptation to human codon usage.

Results

A strong ‘A’ bias was confirmed in all three structural genes, consistent with previous findings regarding HIV. Notably, the ENC-GC3s plot and neutral evolution analysis showed that all primate lentiviruses were more affected by selection pressure than by mutation caused by the GC composition of the gene, consistent with prior reports regarding HIV1. The overall codon usage bias of pol was highest among the structural genes, while the codon usage bias of env was lowest. The virus groups showing high codon bias in all three genes were HIV1 and SIVcolobus. The codon adaptation index (CAI) and similarity D(A, B) values indicated that although there was a high degree of similarity to human codon usage in all three structural genes of HIV, this similarity was not caused by translation pressure. In addition, compared with HIV1, the codon usage of HIV2 is more similar to the human codon usage, but the overall codon usage bias is lower.

Conclusion

The origin viruses of HIV (SIVcpz_gor and SIVsmm) exhibit greater similarity to human codon usage in the gag gene, confirming their robust adaptability to human codon usage. Therefore, HIV1 and HIV2 may have evolved to avoid human codon usage by selection pressure in the gag gene after interspecies transmission from SIV hosts to humans. By overcoming safety and stability issues, information from codon usage analysis will be useful for attenuated HIV1 vaccine development. A recoded HIV1 variant can be used as a vaccine vector or in immunotherapy to induce specific innate immune responses. Further research regarding HIV1 dinucleotide usage and codon pair usage will facilitate new approaches to the treatment of AIDS.

Collaborative Mining of Whole Genome Sequences for Intelligent HIV-1 Sub-Strain(s) Discovery

BACKGROUND

Effective global antiretroviral vaccines and therapeutic strategies depend on the diversity, evolution, and epidemiology of their various strains as well as their transmission and pathogenesis. Most viral disease-causing particles are clustered into a taxonomy of subtypes to suggest pointers toward nucleotide-specific vaccines or therapeutic applications of clinical significance sufficient for sequence-specific diagnosis and homologous viral studies. These are very useful to formulate predictors to induce cross-resistance to some retroviral control drugs being used across study areas.

OBJECTIVE

This research proposed a collaborative framework of hybridized (Machine Learning and Natural Language Processing) techniques to discover hidden genome patterns and feature predictors, for HIV-1 genome sequences mining.

METHOD

630 human HIV-1 genome sequences above 8500 bps were excavated from the National Center for Biotechnology Information (NCBI) database (https://www.ncbi.nlm.nih.gov) for 21 countries across different continents, Antarctica exempt. These sequences were transformed and learned using a self-organizing map (SOM). To discriminate emerging/new sub-strain(s), the HIV-1 reference genome was included as part of the input isolates/samples during the training. After training the SOM, component planes defining pattern clusters of the input datasets were generated, for cognitive knowledge mining and subsequent labelling of the datasets. Additional genome features including dinucleotide transmission recurrences, codon recurrences, and mutation recurrences, were finally extracted from the raw genomes to construct output classification targets for supervised learning.

RESULTS

SOM training explains the inherent pattern diversity of HIV-1 genomes as well as inter- and intra-country transmissions in which mobility might play an active role, as corroborated by literature. Nine sub-strains were discovered after disassembling the SOM correlation hunting matrix space attributed to disparate clusters. Cognitive knowledge mining separated similar pattern clusters bounded by a certain degree of correlation range, discovered by the SOM. A Kruskal-Wallis rank-sum test and Wilcoxon rank-sum test showed statistically significant variations in dinucleotide, codon, and mutation patterns.

CONCLUSION

Results of the discovered sub-strains and response clusters visualizations corroborate existing literature, with significant haplotype variations. The proposed framework would assist in the development of decision support systems for easy contact tracing, infectious disease surveillance, and studying the progressive evolution of the reference HIV-1 genome.

Analysis of codon usage patterns and influencing factors in rice tungro bacilliform virus

Rice tungro bacilliform virus (RTBV) belongs to genus Tungrovirus within the family Caulimoviridae harbors circular double-stranded DNA (dsDNA). Rice tungro disease (RTD) caused by RTBV, responsible for severe rice yield losses in South and Southeast Asia. Here, we performed a systematic evolutionary and codon usage bias (CUB) analysis of RTBV genome sequences. We analysed different bioinformatics techniques to calculate the nucleotide compositions, the relative synonymous codon usage (RSCU), and other indices. The results indicated slightly or low codon usage bias in RTBV isolates. Mutation and natural selection pressures have equally contributed to this low codon usage bias. Additionally, multiple factors such as host, geographical distribution also affect codon usage patterns in RTBV genomes. RSCU analysis revealed that RTBV shows mutation bias and prefers A and U ended codons to code amino acids. Codon usage patterns of RTBV were also found to be influenced by its host. This indicates that RTBV have evolved codon usage patterns that are specific to its host. The findings from this study are expected to increase our understanding of factors leading to viral evolution and fitness with respect to hosts and the environment.

Y44A Mutation in the Acidic Domain of HIV-2 Tat Impairs Viral Reverse Transcription and LTR-Transactivation

HIV transactivator protein (Tat) plays a pivotal role in viral replication through modulation of cellular transcription factors and transactivation of viral genomic transcription. The effect of HIV-1 Tat on reverse transcription has long been described in the literature, however, that of HIV-2 is understudied. Sequence homology between Tat proteins of HIV-1 and 2 is estimated to be less than 30%, and the main difference lies within their N-terminal region. Here, we describe Y44A-inactivating mutation of HIV-2 Tat, studying its effect on capsid production, reverse transcription, and the efficiency of proviral transcription. Investigation of the mutation was performed using sequence- and structure-based in silico analysis and in vitro experiments. Our results indicate that the Y44A mutant HIV-2 Tat inhibited the activity and expression of RT (reverse transcriptase), in addition to diminishing Tat-dependent LTR (long terminal repeat) transactivation. These findings highlight the functional importance of the acidic domain of HIV-2 Tat in the regulation of reverse transcription and transactivation of the integrated provirions.