Low complexity regions (LCRs) contribute to the hypervariability of the HIV-1 gp120 protein

Anti-Plasmodium vivax merozoite surface protein 3 ϒ (PvMSP3 ϒ) antibodies upon natural infection

Merozoite surface protein 3 of Plasmodium vivax (PvMSP3) contains a repertoire of protein members with unique sequence organization. While the biological functions of these proteins await elucidation, PvMSP3 has been suggested to be potential vaccine targets. To date, studies on natural immune responses to this protein family have been confined to two members, PvMSP3α and PvMSP3β. This study analyzed natural IgG antibody responses to PvMSP3γ recombinant proteins derived from two variants: one containing insert blocks (CT1230nF) and the other without insert domain (NR25nF). The former variant was also expressed as two subfragment proteins: one encompassing variable domain I and insert block A (CT1230N) and the other spanning from insert block B to conserved block III (CT1230C). Serum samples were obtained from 246 symptomatic vivax malaria patients in Tak (n = 50) and Ubon Ratchathani (n = 196) Provinces. In total, 176 (71.5%) patients could mount antibodies to at least one recombinant PvMSP3γ antigen. IgG antibodies directed against antigens CT1230nF, CT1230N, CT1230C and NR25nF occurred in 96.6%, 61.4%, 71.6% and 68.2% of samples, respectively, suggesting the widespread occurrence of B-cell epitopes across PvMSP3γ. The rates of seropositivity seemed to correlate with the number of previous malaria episodes. Isotype analysis of anti-PvMSP3γ antibodies has shown predominant cytophilic subclass responses, accounting for 75.4-81.7% for IgG1 and 63.6-77.5% for IgG3. Comparing with previous studies in the same cohort, the numbers of serum samples reactive to antigens derived from P. vivax merozoite surface protein 9 (PvMSP9) and thrombospondin-related anonymous protein (PvTRAP) were higher than those to PvMSP3γ, being 92.7% and 87.0% versus 71.5%, respectively. Three (1.22%) serum samples were nonresponsive to all these malarial proteins. Nevertheless, the relevance of naturally acquired antibodies to PvMSP3γ in host protection requires further studies.

Two short low complexity regions (LCRs) are hallmark sequences of the Delta SARS-CoV-2 variant spike protein

Low complexity regions (LCRs) are protein sequences formed by a set of compositionally biased residues. LCRs are extremely abundant in cellular proteins and have also been reported in viruses, where they may partake in evasion of the host immune system. Analyses of 28,231 SARS-CoV-2 whole proteomes and of 261,051 spike protein sequences revealed the presence of four extremely conserved LCRs in the spike protein of several SARS-CoV-2 variants. With the exception of Iota, where it is absent, the Spike LCR-1 is present in the signal peptide of 80.57% of the Delta variant sequences, and in other variants of concern and interest. The Spike LCR-2 is highly prevalent (79.87%) in Iota. Two distinctive LCRs are present in the Delta spike protein. The Delta Spike LCR-3 is present in 99.19% of the analyzed sequences, and the Delta Spike LCR-4 in 98.3% of the same set of proteins. These two LCRs are located in the furin cleavage site and HR1 domain, respectively, and may be considered hallmark traits of the Delta variant. The presence of the medically-important point mutations P681R and D950N in these LCRs, combined with the ubiquity of these regions in the highly contagious Delta variant opens the possibility that they may play a role in its rapid spread.

Disentangling the complexity of low complexity proteins

There are multiple definitions for low complexity regions (LCRs) in protein sequences, with all of them broadly considering LCRs as regions with fewer amino acid types compared to an average composition. Following this view, LCRs can also be defined as regions showing composition bias. In this critical review, we focus on the definition of sequence complexity of LCRs and their connection with structure. We present statistics and methodological approaches that measure low complexity (LC) and related sequence properties. Composition bias is often associated with LC and disorder, but repeats, while compositionally biased, might also induce ordered structures. We illustrate this dichotomy, and more generally the overlaps between different properties related to LCRs, using examples. We argue that statistical measures alone cannot capture all structural aspects of LCRs and recommend the combined usage of a variety of predictive tools and measurements. While the methodologies available to study LCRs are already very advanced, we foresee that a more comprehensive annotation of sequences in the databases will enable the improvement of predictions and a better understanding of the evolution and the connection between structure and function of LCRs. This will require the use of standards for the generation and exchange of data describing all aspects of LCRs.

Short abstract

There are multiple definitions for low complexity regions (LCRs) in protein sequences. In this critical review, we focus on the definition of sequence complexity of LCRs and their connection with structure. We present statistics and methodological approaches that measure low complexity (LC) and related sequence properties. Composition bias is often associated with LC and disorder, but repeats, while compositionally biased, might also induce ordered structures. We illustrate this dichotomy, plus overlaps between different properties related to LCRs, using examples.

Common low complexity regions for SARS-CoV-2 and human proteomes as potential multidirectional risk factor in vaccine development

BACKGROUND

The rapid spread of the COVID-19 demands immediate response from the scientific communities. Appropriate countermeasures mean thoughtful and educated choice of viral targets (epitopes). There are several articles that discuss such choices in the SARS-CoV-2 proteome, other focus on phylogenetic traits and history of the Coronaviridae genome/proteome. However none consider viral protein low complexity regions (LCRs). Recently we created the first methods that are able to compare such fragments.

RESULTS

We show that five low complexity regions (LCRs) in three proteins (nsp3, S and N) encoded by the SARS-CoV-2 genome are highly similar to regions from human proteome. As many as 21 predicted T-cell epitopes and 27 predicted B-cell epitopes overlap with the five SARS-CoV-2 LCRs similar to human proteins. Interestingly, replication proteins encoded in the central part of viral RNA are devoid of LCRs.

CONCLUSIONS

Similarity of SARS-CoV-2 LCRs to human proteins may have implications on the ability of the virus to counteract immune defenses. The vaccine targeted LCRs may potentially be ineffective or alternatively lead to autoimmune diseases development. These findings are crucial to the process of selection of new epitopes for drugs or vaccines which should omit such regions.

Effect of low complexity regions within the PvMSP3α block II on the tertiary structure of the protein and implications to immune escape mechanisms

Background

Plasmodium vivax merozoite surface protein 3α (PvMSP3α) is a promising vaccine candidate which has shown strong association with immunogenicity and protectiveness. Its use is however complicated by evolutionary plasticity features which enhance immune evasion. Low complexity regions (LCRs) provide plasticity in surface proteins of Plasmodium species, but its implication in vaccine design remain unexplored. Here population genetic, comparative phylogenetic and structural biology analysis was performed on the gene encoding PvMSP3α.

Results

Three LCRs were found in PvMSP3α block II. Both the predicted tertiary structure of the protein and the phylogenetic trees based on this region were influenced by the presence of the LCRs. The LCRs were mainly B cell epitopes within or adjacent. In addition a repeat motif mimicking one of the B cell epitopes was found within the PvMSP3a block II low complexity region. This particular B cell epitope also featured rampant alanine substitutions which might impair antibody binding.

Conclusion

The findings indicate that PvMSP3α block II possesses LCRs which might confer a strong phenotypic plasticity. The phenomenon of phenotypic plasticity and implication of LCRs in malaria immunology in general and vaccine candidate genes in particular merits further exploration.

Electronic supplementary material

The online version of this article (10.1186/s12900-019-0104-0) contains supplementary material, which is available to authorized users.

Comparative analysis of low complexity regions in Plasmodia

Low complexity regions (LCRs) are a common feature shared by many genomes, but their evolutionary and functional significance remains mostly unknown. At the core of the uncertainty is a poor understanding of the mechanisms that regulate their retention in genomes, whether driven by natural selection or neutral evolution. Applying a comparative approach of LCRs to multiple strains and species is a powerful approach to identify patterns of conservation in these regions. Using this method, we investigate the evolutionary history of LCRs in the genus Plasmodium based on orthologous protein coding genes shared by 11 species and strains from primate and rodent-infecting pathogens. We find multiple lines of evidence in support of natural selection as a major evolutionary force shaping the composition and conservation of LCRs through time and signatures that their evolutionary paths are species specific. Our findings add a comparative analysis perspective to the debate on the evolution of LCRs and harness the power of sequence comparisons to identify potential functionally important LCR candidates.

Screening for clusters of charge in human virus proteomes

Background

The identification of charge clusters (runs of charged residues) in proteins and their mapping within the protein structure sequence is an important step toward a comprehensive analysis of how these particular motifs mediate, via electrostatic interactions, various molecular processes such as protein sorting, translocation, docking, orientation and binding to DNA and to other proteins. Few algorithms that specifically identify these charge clusters have been designed and described in the literature. In this study, 197 distinctive human viral proteomes were screened for the occurrence of charge clusters (CC) using a new computational approach.

Results

Three hundred and seventy three CC have been identified within the 2549 viral protein sequences screened. The number of protein sequences that are CC-free is 2176 (85.3 %) while 150 and 180 proteins contained positive charge (PCC) and negative charge clusters (NCC), respectively. The NCCs (211 detected) were more prevalent than PCC (162). PCC-containing proteins are significantly longer than those having NCCs (p = 2.10^-16). The most prevalent virus families having PCC and NCC were Herpesviridae followed by Papillomaviridae. However, the single-strand RNA group has in average three times more NCC than PCC. According to the functional domain classification, a significant difference in distribution was observed between PCC and NCC (p = 2. 10⁻⁸) with the occurrence of NCCs being more frequent in C-terminal region while PCC more often fall within functional domains. Only 29 proteins sequences contained both NCC and PCC. Moreover, 101 NCC were conserved in 84 proteins while only 62 PCC were conserved in 60 protein sequences. To understand the mechanism by which the membrane translocation functionalities are embedded in viral proteins, we screened our PCC for sequences corresponding to cell-penetrating peptides (CPPs) using two online databases: CellPPd and CPPpred. We found that all our PCCs, having length varying from 7 to 30 amino-acids were predicted as CPPs. Experimental validation is required to improve our understanding of the role of these PCCs in viral infection process.

Conclusions

Screening distinctive cluster charges in viral proteomes suggested a functional role of these protein regions and might provide potential clues to improve the current understanding of viral diseases in order to tailor better preventive and therapeutic approaches.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3086-3) contains supplementary material, which is available to authorized users.

Genome-Wide Identification and Characterization of bZIP Transcription Factors in Brassica oleracea under Cold Stress

Cabbages (Brassica oleracea L.) are an important vegetable crop around world, and cold temperature is among the most significant abiotic stresses causing agricultural losses, especially in cabbage crops. Plant bZIP transcription factors play diverse roles in biotic/abiotic stress responses. In this study, 119 putative BolbZIP transcription factors were identified using amino acid sequences from several bZIP domain consensus sequences. The BolbZIP members were classified into 63 categories based on amino acid sequence similarity and were also compared with BrbZIP and AtbZIP transcription factors. Based on this BolbZIP identification and classification, cold stress-responsive BolbZIP genes were screened in inbred lines, BN106 and BN107, using RNA sequencing data and qRT-PCR. The expression level of the 3 genes, Bol008071, Bol033132, and Bol042729, was significantly increased in BN107 under cold conditions and was unchanged in BN106. The upregulation of these genes in BN107, a cold-susceptible inbred line, suggests that they might be significant components in the cold response. Among three identified genes, Bol033132 has 97% sequence similarity to Bra020735, which was identified in a screen for cold-related genes in B. rapa and a protein containing N-rich regions in LCRs. The results obtained in this study provide valuable information for understanding the potential function of BolbZIP transcription factors in cold stress responses.