SigniSite: Identification of residue-level genotype-phenotype correlations in protein multiple sequence alignments

Diversification of the VH3-53 immunoglobulin gene segment by somatic hypermutation results in neutralization of SARS-CoV-2 virus variants

COVID-19 induces re-circulating long-lived memory B cells (MBC) that, upon re-encounter with the pathogen, are induced to mount immunoglobulin responses. During convalescence, antibodies are subjected to affinity maturation, which enhances the antibody binding strength and generates new specificities that neutralize virus variants. Here, we performed a single-cell RNA sequencing analysis of spike-specific B cells from a SARS-CoV-2 convalescent subject. After COVID-19 vaccination, matured infection-induced MBC underwent recall and differentiated into plasmablasts. Furthermore, the transcriptomic profiles of newly activated B cells transiently shifted toward the ones of atypical and CXCR3+ B cells and several B-cell clonotypes massively expanded. We expressed monoclonal antibodies (mAbs) from all B-cell clones from the largest clonotype that used the VH3-53 gene segment. The in vitro analysis revealed that some somatic hypermutations enhanced the neutralization breadth of mAbs in a putatively stochastic manner. Thus, somatic hypermutation of B-cell clonotypes generates an anticipatory memory that can neutralize new virus variants.

Associating protein sequence positions with the modulation of quantitative phenotypes

Although protein sequences encode the information for folding and function, understanding their link is not an easy task. Unluckily, the prediction of how specific amino acids contribute to these features is still considerably impaired. Here, we developed a simple algorithm that finds positions in a protein sequence with potential to modulate the studied quantitative phenotypes. From a few hundred protein sequences, we perform multiple sequence alignments, obtain the per-position pairwise differences for both the sequence and the observed phenotypes, and calculate the correlation between these last two quantities. We tested our methodology with four cases: archaeal Adenylate Kinases and the organisms optimal growth temperatures, microbial rhodopsins and their maximal absorption wavelengths, mammalian myoglobins and their muscular concentration, and inhibition of HIV protease clinical isolates by two different molecules. We found from 3 to 10 positions tightly associated with those phenotypes, depending on the studied case. We showed that these correlations appear using individual positions but an improvement is achieved when the most correlated positions are jointly analyzed. Noteworthy, we performed phenotype predictions using a simple linear model that links per-position divergences and differences in the observed phenotypes. Predictions are comparable to the state-of-art methodologies which, in most of the cases, are far more complex. All of the calculations are obtained at a very low information cost since the only input needed is a multiple sequence alignment of protein sequences with their associated quantitative phenotypes. The diversity of the explored systems makes our work a valuable tool to find sequence determinants of biological activity modulation and to predict various functional features for uncharacterized members of a protein family.

Multiplex measurement of protein-peptide dissociation constants using dialysis and mass spectrometry

We propose a high-throughput method for quantitively measuring hundreds of protein-peptide binding affinities in parallel. In this assay a solution of protein is dialyzed into a buffer containing a pool of potential binding peptides, such that upon equilibration the relative abundance of a peptide species is mathematically related to that peptide's dissociation constant, K_d . We use isobaric multiplexed quantitative proteomics to simultaneously determine the relative abundance, and hence the K_d and its associated error, for an entire peptide library. We apply this technique, which we call PEDAL (Parallel Equilibrium Dialysis for Affinity Learning), to determine accurate K_d 's between a PDZ domain and hundreds of peptides, spanning an affinity range of multiple orders of magnitude in a single experiment. PEDAL is a convenient, fast, and low-cost method for measuring large numbers of protein-peptide affinities in parallel, providing a rare combination of true in-solution binding equilibria with the ability to multiplex. This article is protected by copyright. All rights reserved.

The Changes in the p53 Protein across the Animal Kingdom Point to Its Involvement in Longevity

Recently, the quest for the mythical fountain of youth has produced extensive research programs that aim to extend the healthy lifespan of humans. Despite advances in our understanding of the aging process, the surprisingly extended lifespan and cancer resistance of some animal species remain unexplained. The p53 protein plays a crucial role in tumor suppression, tissue homeostasis, and aging. Long-lived, cancer-free African elephants have 20 copies of the TP53 gene, including 19 retrogenes (38 alleles), which are partially active, whereas humans possess only one copy of TP53 and have an estimated cancer mortality rate of 11–25%. The mechanism through which p53 contributes to the resolution of the Peto’s paradox in Animalia remains vague. Thus, in this work, we took advantage of the available datasets and inspected the p53 amino acid sequence of phylogenetically related organisms that show variations in their lifespans. We discovered new correlations between specific amino acid deviations in p53 and the lifespans across different animal species. We found that species with extended lifespans have certain characteristic amino acid substitutions in the p53 DNA-binding domain that alter its function, as depicted from the Phenotypic Annotation of p53 Mutations, using the PROVEAN tool or SWISS-MODEL workflow. In addition, the loop 2 region of the human p53 DNA-binding domain was identified as the longest region that was associated with longevity. The 3D model revealed variations in the loop 2 structure in long-lived species when compared with human p53. Our findings show a direct association between specific amino acid residues in p53 protein, changes in p53 functionality, and the extended animal lifespan, and further highlight the importance of p53 protein in aging.

Cross-recognition of a pit viper (Crotalinae) polyspecific antivenom explored through high-density peptide microarray epitope mapping

Snakebite antivenom is a 120 years old invention based on polyclonal mixtures of antibodies purified from the blood of hyper-immunized animals. Knowledge on antibody recognition sites (epitopes) on snake venom proteins is limited, but may be used to provide molecular level explanations for antivenom cross-reactivity. In turn, this may help guide antivenom development by elucidating immunological biases in existing antivenoms. In this study, we have identified and characterized linear elements of B-cell epitopes from 870 pit viper venom protein sequences by employing a high-throughput methodology based on custom designed high-density peptide microarrays. By combining data on antibody-peptide interactions with multiple sequence alignments of homologous toxin sequences and protein modelling, we have determined linear elements of antibody binding sites for snake venom metalloproteases (SVMPs), phospholipases A₂s (PLA₂s), and snake venom serine proteases (SVSPs). The studied antivenom antibodies were found to recognize linear elements in each of the three enzymatic toxin families. In contrast to a similar study of elapid (non-enzymatic) neurotoxins, these enzymatic toxins were generally not recognized at the catalytic active site responsible for toxicity, but instead at other sites, of which some are known for allosteric inhibition or for interaction with the tissue target. Antibody recognition was found to be preserved for several minor variations in the protein sequences, although the antibody-toxin interactions could often be eliminated completely by substitution of a single residue. This finding is likely to have large implications for the cross-reactivity of the antivenom and indicate that multiple different antibodies are likely to be needed for targeting an entire group of toxins in these recognized sites.

Although snakebite antivenom is a 120-year-old invention, saving lives and limbs of thousands of snakebite victims every year, little is known about the mechanisms and molecular interactions of how antivenoms neutralize snake toxins. Antivenoms are produced by immunizing large animals with cocktails of snake venoms resulting in antibodies recognizing toxic as well as non-toxic venom proteins to variable degrees. As a result, high doses of antivenom are needed for treating a snakebite victim, causing more severe adverse reactions due to a high burden of heterologous antivenom proteins. For the first time, we have characterized the antibody recognition sites on hundreds of pit viper toxins using high-throughput peptide microarray technology and an antivenom specific for three pit vipers inflicting a high number of bites in Central America. Most pit viper toxins are enzymes known to have a catalytic site important for toxicity. However, our results suggest that the employed antivenom generally does not target such sites, but instead inhibits toxicity by binding to alternative sites, possibly causing conformational shifts in the toxin structures or interference with toxin-target recognition. The identification of these toxin-specific recognition sites may explain why the antivenom is effective against certain snakebites from pit vipers whose venoms are not part of the immunization mixture.

Identifying selectively important amino acid positions associated with alternative habitat environments in fish mitochondrial genomes

Fish species inhabitating seawater (SW) or freshwater (FW) habitats have to develop genetic adaptations to alternative environment factors, especially salinity. Functional consequences of the protein variations associated with habitat environments in fish mitochondrial genomes have not yet received much attention. We analyzed 829 complete fish mitochondrial genomes and compared the amino acid differences of 13 mitochondrial protein families between FW and SW fish groups. We identified 47 specificity determining sites (SDS) that associated with FW or SW environments from 12 mitochondrial protein families. Thirty-two (68%) of the SDS sites are hydrophobic, 13 (28%) are neutral, and the remaining sites are acidic or basic. Seven of those SDS from ND1, ND2 and ND5 were scored as probably damaging to the protein structures. Furthermore, phylogenetic tree based Bayes Empirical Bayes analysis also detected 63 positive sites associated with alternative habitat environments across ten mtDNA proteins. These signatures could be important for studying mitochondrial genetic variation relevant to fish physiology and ecology.

Characterization and functional analysis of hypoxia-inducible factor HIF1α and its inhibitor HIF1αn in tilapia

Hypoxia is a major cause of fish morbidity and mortality in the aquatic environment. Hypoxia-inducible factors are very important modulators in the transcriptional response to hypoxic stress. In this study, we characterized and conducted functional analysis of hypoxia-inducible factor HIF1α and its inhibitor HIF1αn in Nile tilapia (Oreochromis niloticus). By cloning and Sanger sequencing, we obtained the full length cDNA sequences for HIF1α (2686bp) and HIF1αn (1308bp), respectively. The CDS of HIF1α includes 15 exons encoding 768 amino acid residues and the CDS of HIF1αn contains 8 exons encoding 354 amino acid residues. The complete CDS sequences of HIF1α and HIF1αn cloned from tilapia shared very high homology with known genes from other fishes. HIF1α show differentiated expression in different tissues (brain, heart, gill, spleen, liver) and at different hypoxia exposure times (6h, 12h, 24h). HIF1αn expression level under hypoxia is generally increased (6h, 12h, 24h) and shows extremely highly upregulation in brain tissue under hypoxia. A functional determination site analysis in the protein sequences between fish and land animals identified 21 amino acid sites in HIF1α and 2 sites in HIF1αn as significantly associated sites (α = 0.05). Phylogenetic tree-based positive selection analysis suggested 22 sites in HIF1α as positively selected sites with a p-value of at least 95% for fish lineages compared to the land animals. Our study could be important for clarifying the mechanism of fish adaptation to aquatic hypoxia environment.

LEON-BIS: multiple alignment evaluation of sequence neighbours using a Bayesian inference system

Background

A standard procedure in many areas of bioinformatics is to use a multiple sequence alignment (MSA) as the basis for various types of homology-based inference. Applications include 3D structure modelling, protein functional annotation, prediction of molecular interactions, etc. These applications, however sophisticated, are generally highly sensitive to the alignment used, and neglecting non-homologous or uncertain regions in the alignment can lead to significant bias in the subsequent inferences.

Results

Here, we present a new method, LEON-BIS, which uses a robust Bayesian framework to estimate the homologous relations between sequences in a protein multiple alignment. Sequences are clustered into sub-families and relations are predicted at different levels, including ‘core blocks’, ‘regions’ and full-length proteins. The accuracy and reliability of the predictions are demonstrated in large-scale comparisons using well annotated alignment databases, where the homologous sequence segments are detected with very high sensitivity and specificity.

Conclusions

LEON-BIS uses robust Bayesian statistics to distinguish the portions of multiple sequence alignments that are conserved either across the whole family or within subfamilies. LEON-BIS should thus be useful for automatic, high-throughput genome annotations, 2D/3D structure predictions, protein-protein interaction predictions etc.

Identification of a Major Dimorphic Region in the Functionally Critical N-Terminal ID1 Domain of VAR2CSA

The VAR2CSA protein of Plasmodium falciparum is transported to and expressed on the infected erythrocyte surface where it plays a key role in placental malaria (PM). It is the current leading candidate for a vaccine to prevent PM. However, the antigenic polymorphism integral to VAR2CSA poses a challenge for vaccine development. Based on detailed analysis of polymorphisms in the sequence of its ligand-binding N-terminal region, currently the main focus for vaccine development, we assessed var2csa from parasite isolates infecting pregnant women. The results reveal for the first time the presence of a major dimorphic region in the functionally critical N-terminal ID1 domain. Parasite isolates expressing VAR2CSA with particular motifs present within this domain are associated with gravidity- and parasite density-related effects. These observations are of particular interest in guiding efforts with respect to optimization of the VAR2CSA-based vaccines currently under development.

Insights from 20 years of bacterial genome sequencing

Since the first two complete bacterial genome sequences were published in 1995, the science of bacteria has dramatically changed. Using third-generation DNA sequencing, it is possible to completely sequence a bacterial genome in a few hours and identify some types of methylation sites along the genome as well. Sequencing of bacterial genome sequences is now a standard procedure, and the information from tens of thousands of bacterial genomes has had a major impact on our views of the bacterial world. In this review, we explore a series of questions to highlight some insights that comparative genomics has produced. To date, there are genome sequences available from 50 different bacterial phyla and 11 different archaeal phyla. However, the distribution is quite skewed towards a few phyla that contain model organisms. But the breadth is continuing to improve, with projects dedicated to filling in less characterized taxonomic groups. The clustered regularly interspaced short palindromic repeats (CRISPR)-Cas system provides bacteria with immunity against viruses, which outnumber bacteria by tenfold. How fast can we go? Second-generation sequencing has produced a large number of draft genomes (close to 90 % of bacterial genomes in GenBank are currently not complete); third-generation sequencing can potentially produce a finished genome in a few hours, and at the same time provide methlylation sites along the entire chromosome. The diversity of bacterial communities is extensive as is evident from the genome sequences available from 50 different bacterial phyla and 11 different archaeal phyla. Genome sequencing can help in classifying an organism, and in the case where multiple genomes of the same species are available, it is possible to calculate the pan- and core genomes; comparison of more than 2000 Escherichia coli genomes finds an E. coli core genome of about 3100 gene families and a total of about 89,000 different gene families. Why do we care about bacterial genome sequencing? There are many practical applications, such as genome-scale metabolic modeling, biosurveillance, bioforensics, and infectious disease epidemiology. In the near future, high-throughput sequencing of patient metagenomic samples could revolutionize medicine in terms of speed and accuracy of finding pathogens and knowing how to treat them.

IDEPI: rapid prediction of HIV-1 antibody epitopes and other phenotypic features from sequence data using a flexible machine learning platform

Since its identification in 1983, HIV-1 has been the focus of a research effort unprecedented in scope and difficulty, whose ultimate goals--a cure and a vaccine--remain elusive. One of the fundamental challenges in accomplishing these goals is the tremendous genetic variability of the virus, with some genes differing at as many as 40% of nucleotide positions among circulating strains. Because of this, the genetic bases of many viral phenotypes, most notably the susceptibility to neutralization by a particular antibody, are difficult to identify computationally. Drawing upon open-source general-purpose machine learning algorithms and libraries, we have developed a software package IDEPI (IDentify EPItopes) for learning genotype-to-phenotype predictive models from sequences with known phenotypes. IDEPI can apply learned models to classify sequences of unknown phenotypes, and also identify specific sequence features which contribute to a particular phenotype. We demonstrate that IDEPI achieves performance similar to or better than that of previously published approaches on four well-studied problems: finding the epitopes of broadly neutralizing antibodies (bNab), determining coreceptor tropism of the virus, identifying compartment-specific genetic signatures of the virus, and deducing drug-resistance associated mutations. The cross-platform Python source code (released under the GPL 3.0 license), documentation, issue tracking, and a pre-configured virtual machine for IDEPI can be found at https://github.com/veg/idepi.

NEP: web server for epitope prediction based on antibody neutralization of viral strains with diverse sequences

Delineation of the antigenic site, or epitope, recognized by an antibody can provide clues about functional vulnerabilities and resistance mechanisms, and can therefore guide antibody optimization and epitope-based vaccine design. Previously, we developed an algorithm for antibody-epitope prediction based on antibody neutralization of viral strains with diverse sequences and validated the algorithm on a set of broadly neutralizing HIV-1 antibodies. Here we describe the implementation of this algorithm, NEP (Neutralization-based Epitope Prediction), as a web-based server. The users must supply as input: (i) an alignment of antigen sequences of diverse viral strains; (ii) neutralization data for the antibody of interest against the same set of antigen sequences; and (iii) (optional) a structure of the unbound antigen, for enhanced prediction accuracy. The prediction results can be downloaded or viewed interactively on the antigen structure (if supplied) from the web browser using a JSmol applet. Since neutralization experiments are typically performed as one of the first steps in the characterization of an antibody to determine its breadth and potency, the NEP server can be used to predict antibody-epitope information at no additional experimental costs. NEP can be accessed on the internet at http://exon.niaid.nih.gov/nep.