Biology subjects

Rawi, R.

Publications and source records attributed to Rawi, R..

6 recordsLinked to original sources

bioRxiv2018

Accurate Prediction of Antibody Resistance in Clinical HIV-1 Isolates

Broadly neutralizing antibodies (bNAbs) targeting the HIV-1 envelope glycoprotein (Env) have promising utility in prevention and treatment of HIV-1 infection with several undergoing clinical trials. Due to high sequence diversity and mutation rate of HIV-1, viral isolates are often resistant to particular bNAbs. Resistant strains are commonly identified by time-consuming and expensive in vitro neutralization experiments. Here, we developed machine learning-based classifiers that accurately predict resistance of HIV-1 strains to 33 neutralizing antibodies. Notably, our classifiers achieved an overall prediction accuracy of 96% for 212 clinical isolates from patients enrolled in four different clinical trials. Moreover, use of the tree-based machine learning method gradient boosting machine enabled us to identify critical epitope features that distinguish between antibody resistance and sensitivity. The availability of an in silico antibody resistance predictor will facilitate informed decisions of antibody usage in clinical settings.

bioinformatics↗

bioRxiv2018

Structural survey of HIV-1-neutralizing antibodies targeting Env trimer delineates epitope categories and suggests vaccine templates

HIV-1 broadly neutralizing antibodies are desired for their therapeutic potential and as templates for vaccine design. Such antibodies target the HIV-1-envelope (Env) trimer, which is shielded from immune recognition by extraordinary glycosylation and sequence variability. Recognition by broadly neutralizing antibodies thus provides insight into how antibody can bypass these immune-evasion mechanisms. Remarkably, antibodies neutralizing >25% of HIV-1 strains have now been identified that recognize all major exposed surfaces of the prefusion-closed Env trimer. Here we analyzed all 206 broadly neutralizing antibody-HIV-1 Env complexes in the PDB with resolution suitable to define their interaction chemistries. These segregated into 20 antibody classes based on ontogeny and recognition, and into 6 epitope categories (V1V2, glycan-V3, CD4-binding site, silent face center, fusion peptide, and subunit interface) based on recognized Env residues. We measured antibody neutralization on a 208-isolate panel and analyzed features of paratope and B cell ontogeny. The number of protruding loops, CDR H3 length, and level of somatic hypermutation for broadly HIV-1 neutralizing antibodies were significantly higher than for a comparison set of non-HIV-1 antibodies. For epitope, the number of independent sequence segments was higher (P < 0.0001), as well as the glycan component surface area (P = 0.0005). Based on B cell ontogeny, paratope, and breadth, the CD4-binding site antibody IOMA appeared to be a promising candidate for lineage-based vaccine design. In terms of epitope-based vaccine design, antibody VRC34.01 had few epitope segments, low epitope-glycan content, and high epitope-conformational variability, which may explain why VRC34.01-based design is yielding promising vaccine results.

bioinformatics↗

bioRxiv2018

Complete functional mapping of infection- and vaccine-elicited antibodies against the fusion peptide of HIV

Eliciting broadly neutralizing antibodies (bnAbs) targeting envelope (Env) is a major goal of HIV vaccine development, but cross-clade breadth from immunization has only sporadically been observed. Recently, Xu et al (2018) elicited cross-reactive neutralizing antibody responses in a variety of animal models using immunogens based on the epitope of bnAb VRC34.01. The VRC34.01 antibody, which was elicited by natural human infection, targets the N terminus of the Env fusion peptide, a critical component of the virus entry machinery. Here we precisely characterize the functional epitopes of VRC34.01 and two vaccine-elicited murine antibodies by mapping all single amino-acid mutations to the BG505 Env that affect viral neutralization. While escape from VRC34.01 occurred via mutations in both fusion peptide and distal interacting sites of the Env trimer, escape from the vaccine-elicited antibodies was mediated predominantly by mutations in the fusion peptide. Cryo-electron microscopy of four vaccine-elicited antibodies in complex with Env trimer revealed focused recognition of the fusion peptide and provided a structural basis for development of neutralization breadth. Together, these functional and structural data suggest that the breadth of vaccine-elicited antibodies targeting the fusion peptide can be enhanced by specific interactions with additional portions of Env. Thus, our complete maps of viral escape provide a template to improve the breadth or potency of future vaccine-induced antibodies against Envs fusion peptide.\n\nAuthor summaryA major goal of HIV-1 vaccine design is to elicit antibodies that neutralize diverse strains of HIV-1. Recently, some of us elicited such antibodies in animal models using immunogens based on the epitope of a broad antibody (VRC34.01) isolated from an infected individual. Further improving these vaccine-elicited antibody responses will require a detailed understanding of how the resulting antibodies target HIVs envelope protein (Env). Here, we used mutational antigenic profiling to precisely map the epitope of two vaccine-elicited antibodies and the template VRC34.01 antibody. We did this by quantifying the effect of all possible amino acid mutations to Env on antibody neutralization. Although all antibodies target a similar region of Env, we found clear differences in the functional interaction of Env with the vaccine- and infection-elicited antibodies. We combined these functional data with structural analyses to identify antibody-Env interactions that could improve the breadth of vaccine-elicited antibodies, and thereby help to refine vaccination schemes to achieve broader responses.

immunology↗

bioRxiv2018

Epitope-based vaccine design yields fusion peptide-directed antibodies that neutralize diverse strains of HIV-1

A central goal of HIV-1-vaccine research is the elicitation of antibodies capable of neutralizing diverse primary isolates of HIV-1. Here we show that focusing the immune response to exposed N-terminal residues of the fusion peptide, a critical component of the viral entry machinery and the epitope of antibodies elicited by HIV-1 infection, through immunization with fusion peptide-coupled carriers and prefusion-stabilized envelope trimers, induces cross-clade neutralizing responses. In mice, these immunogens elicited monoclonal antibodies capable of neutralizing up to 31% of a cross-clade panel of 208 HIV-1 strains. Crystal and cryo-electron microscopy structures of these antibodies revealed fusion peptide-conformational diversity as a molecular explanation for the cross-clade neutralization. Immunization of guinea pigs and rhesus macaques induced similarly broad fusion peptide-directed neutralizing responses suggesting translatability. The N terminus of the HIV-1-fusion peptide is thus a promising target of vaccine efforts aimed at eliciting broadly neutralizing antibodies.

immunology↗

bioRxiv2017

Integrative Statistical Inferences for Drug Sensitivity Biomarkers in Cancer

Personal medicine has been associated with different patient responses to different anti-cancer therapies. Recently, scientists are looking not only for new biomarkers associated with a disease such as cancer but also identifying biomarkers that predict patients who are most likely to respond to a particular cancer treatment. Orderly endeavors to relate cancer mutational information with biological conditions may encourage the interpretation of somatic mutation indexes into significant biomarkers for patient stratification.\n\nWe have screened and incorporated a board of cancer cell lines from Genomics of Drug Sensitivity in Cancer (GDSC) database to recognize genomic highlights related with drug sensitivity. We used mutation, DNA copy number variation, and gene expression information from Catalogue of Somatic Mutations in Cancer (COSMIC) and The Cancer Genome ATLAS (TCGA) for cell lines with their reactions to associate focused and cytotoxic treatments with approved drugs and drugs under clinical and preclinical examination.\n\nWe discovered mutated cancer genes were related with cell reaction to, mostly accessible, cancer medications and some mutated genes were related with sensitivity to an expansive scope of therapeutic agents. By connecting drug activity to the useful many-sided quality of cancer genomes, efficient pharmacogenomic profiling in tumor cell lines gives an intense biomarker revelation stage to guide balanced malignancy remedial systems.\n\nOur study highlights that gene ANK2 amplification, and gene CELSER1 amplification and deletion are highly associated with anti-leukemic drug candidate LFM-A13. It also highlights that gene NUP214 and ROS1 copy number and gene NSD1 amplification are as a group highly associated with the parkinson drug Nilotinib. Finally, our study confirms that gene BRAF mutation is interacting with the BRAF-selective inhibitors drugs PLX4720 and SB590885. On the other hand, our study provides two open source analysis packages: bastah for the multitask-association analysis, and UNGeneAnno for automatic annotation of the variants.

genomics↗

bioRxiv2017

Application of High-Dimensional Statistics and Network based Visualization techniques on Arab Diabetes and Obesity data

BackgroundObesity and its co-morbidities are characterized by a chronic low-grade inflammatory state, uncontrolled expression of metabolic measurements and dis-regulation of various forms of stress response. However, the contribution and correlation of inflammation, metabolism and stress responses to the disease are not fully elucidated. In this paper a cross-sectional case study was conducted on clinical data comprising 117 human male and female subjects with and without type 2 diabetes (T2D). Characteristics such as anthropometric, clinical and bio-chemical measurements were collected.\n\nMethodsAssociation of these variables with T2D and BMI were assessed using penalized hierarchical linear and logistic regression. In particular, elastic net, hdi and glinternet were used as regularization models to distinguish between cases and controls. Differential network analysis using closed-form approach was performed to identify pairwise-interaction of variables that influence prediction of the phenotype.\n\nResultsFor the 117 participants, physical variables such as PBF, HDL and TBW had absolute coefficients 0.75, 0.65 and 0.34 using the glinternet approach, biochemical variables such as MIP, ROS and RANTES were identified as determinants of obesity with some interaction between inflammatory markers such as IL4, IL-6, MIP, CSF, Eotaxin and ROS. Diabetes was associated with a significant increase in thiobarbituric acid reactive substances (TBARS) which are considered as an index of endogenous lipid peroxidation and an increase in two inflammatory markers, MIP-1 and RANTES. Furthermore, we obtained 13 pairwise effects. The pairwise effects include pairs from and within physical, clinical and biochemical features, in particular metabolic, inflammatory, and oxidative stress markers.\n\nConclusionsWe showcase that markers of oxidative stress (derived from lipid peroxidation) such as MIP-1 and RANTES participate in the pathogenesis of diseases such as diabetes and obesity in the Arab population.

bioinformatics↗