Percorrer por autor "Bashir, Sana"
A mostrar 1 - 8 de 8
Resultados por página
Opções de ordenação
- Bioinformatics pipeline to evaluate patterns of diversity in detoxification genes in the Western honey bee (Apis mellifera)Publication . Barbosa, Daniela; Li, Fernanda; Bashir, Sana; Lopes, Ana Rita; Yadró Garcia, Carlos A.; Quaresma, Andreia; Rufino, José; Rosa-Fontana, Annelise; Verbinnen, Gilles; de Graaf, Dirk C.; De Smet, Lina; Taliadoros, Demetris; Webster, Matthew; Pinto, M. Alice; Henriques, DoraThe Western honey bee, Apis mellifera, displays significant genetic diversity in detoxification genes, which is pivotal for environmental adaptation and resilience. Herein, we developed a bioinformatics pipeline to investigate patterns of diversity in these genes, focusing on single nucleotide polymorphisms (SNPs) across A. mellifera populations, with variant annotation performed using both snpEff and the Variant Effect Predictor (VEP). Our pipeline integrates GATK, VCFtools, PLINK, bcftools, snpEff, and VEP to process genomic data systematically. Regions of interest were defined in a BED file for variant filtering. Using GATK, SNPs were extracted from a VCF file and conversion to PLINK format for population genetics analyses. Variants were filtered by minor allele frequency (MAF) and population differentiation (FST index) to identify SNPs with considerable. Variants were annotated with snpEff and VEP to predict functional impacts, enabling a comparative analysis of their annotation consistency and depth. Custom scripts were developed to map SNPs to detoxification genes, quantify SNP density, and integrated gene descriptions and lineage data. The resulting data were visualized using a combination of and generate different graphs using ggplot2 and chromoMap for chromossomal maps. Quality control steps were applied through the pipeline ensuring data reliability. Our findings reveal distinct SNP patterns in detoxification genes, highlighting candidate SNPs associated with A. mellifera subspecies-specific adaptations. The comparison of snpEff and VEP annotations provides insights into their strengths and limitations, which can help optimize software selection for genomic studies. This pipeline offers a reproducible framework for studying genetic diversity in A. mellifera that is adaptable to other species, advancing conservation and evolutionary genomics.
- Computational analysis to predict the impact of non-synonymous mutations in a protein: an example with the Odorant Receptor 49bPublication . Bashir, Sana; Shiraishi, Carlos S.H.; Yadró Garcia, Carlos A.; Henriques, Dora; Pinto, M. Alice; Abreu, Rui M.V.Non-synonymous mutations lead to amino acid substitutions within proteins, potentially affecting protein structure and function. While some mutations have a minimal impact on protein structure and function, others can alter their stability, conformation, and biological activity. Therefore, predicting how mutations affect proteins is important when uncovering the genetic basis of honey bee response to selective pressures. In a recent whole-genome scan for signatures of selection in Apis mellifera syriaca, we found a non-synonymous mutation under selection in the Odorant Receptor 49b (Or49b) gene. According to the literature, this gene plays a role in honeybee foraging, communication, and environmental adaptation. In an attempt to understand the biological impact at the molecular level of the discovered mutation, we assembled a pipeline that integrates bioinformatics and protein modelling techniques to evaluate the structural and functional consequences of a mutation in a protein. Protein structures were generated from a FASTA file using AlphaFold3, converted from mmCIF to PDB format, and visualized in PyMOL, where mutations were introduced. Functional site predictions were performed using Proteins Plus, and molecular dynamics simulations were conducted in YASARA to assess stability and conformational changes. Our findings suggest that the mutation under selection in the OR49b gene, which replaces tyrosine with histidine, alters protein dynamics by modifying its energy landscape and stability. At the end of the molecular dynamics simulation, the total potential energy of the wild-type protein was calculated as -384,675 kcal/mol. In contrast, this value increased to -287,075 kcal/mol for the mutant protein. This difference suggests that the mutation may affect the OR49b conformation, flexibility, and eventually its biological function. Whether this change affects honey bee olfactory perception remains uncertain. However, given that the mutation is under selection, it is plausible that the alternative amino acid variants confer an adaptive advantage in different environments. From a practical perspective, understanding how mutations affect biological function can ultimately assist honey bee breeders in selecting colonies for breeding programs, enhancing resilience and adaptability.
- A Computational Approach to Study Non-Synonymous MutationsPublication . Bashir, Sana; Li, Fernanda; Shiraishi, Carlos S.H.; Yadró Garcia, Carlos A.; Barbosa, Daniela; Abreu, Rui M.V.; Rufino, José; Pinto, M. Alice; Henriques, DoraNon-synonymous SNPs (Single Nucleotide Polymorphisms) result in amino acid substitutions within proteins. While some may have minimal impact on protein structure and function, others can significantly alter stability, conformation, and biological activity. Therefore, it is crucial to predict how SNP-induced changes affect protein structure and function. Here, we developed a novel pipeline that integrates bioinformatics and molecular modeling techniques to evaluate the structural and functional consequences of a non-synonymous SNP in a protein. Initially, Protein Plus was used to predict the potential active sites, which will help to determine whether a mutation is located within the functional binding regions. Identification of active sites is necessary to prioritize mutations that may alter protein structure and function. PolyPhen-2 and I-Mutant were used to evaluate the functional impact of mutations and the thermodynamic stability of the proteins. Next, to visualize the structural changes, AlphaFold3 was used to generate highconfidence 3D models for wild and mutant proteins. Finally, molecular dynamics (MD) simulations were conducted using YASARA to explore the dynamic behavior and stability of both mutant and wild-type proteins. MD simulations provide valuable insight into structural flexibility, potential conformational shifts, and the overall impact of the mutation on protein function. This computational pipeline provides a detailed framework to evaluate the structural and energetic consequences of non-synonymous mutations.
- Computational Insights into the Impact of NonSynonymous Mutations in the ABC Transporter Gene of Apis melliferaPublication . Bashir, Sana; Li, Fernanda; Shiraishi, Carlos S.H.; Younes, Sarra Bin; Yadró Garcia, Carlos A.; Barbosa, Daniela; Abreu, Rui M.V.; Rufino, José; Pinto, M. Alice; Henriques, DoraNon-synonymous mutations lead to amino acid substitutions that can affect a protein’s structure and function, thereby influencing biological processes such as detoxification. ATP-binding cassette (ABC) transporters (an important superfamily of detoxification genes) play a critical role in the efflux of toxic compounds in honey bees (Apis mellifera), essential for their survival in environments exposed to natural and synthetic xenobiotics. In this study, non-synonymous mutations in 21 ABC transporter genes were identified. Then, computational tools were employed to investigate the structural and functional consequences of a non-synonymous mutation in the protein encoded by the ABC transporter gene LOC411997. Protein structures were generated from a FASTA file using AlphaFold3, converted from mmCIF to PDB format, and visualised in PyMOL, where mutations were introduced. Functional site predictions were performed using Proteins Plus, and molecular dynamics simulations were conducted in YASARA to assess stability and conformational changes. Our findings suggest that a mutation that replaces threonine with isoleucine alters the protein dynamics by modifying its energy landscape and stability. The total potential energy of the wild-type protein was calculated as -3,640,842 kcal/mol. In contrast, this value increased to -3,443,695 kcal/mol for the mutant protein. This difference suggests that the mutation may affect conformation, flexibility, and biological function of the protein encoded by the ABC transporter gene LOC411997. Understanding these conformational changes at the molecular level will contribute to strategies for improving honey bee’s resilience and conservation.
- Evaluating the consequences of plant protection products in the Western honey bee (Apis mellifera) genomePublication . Barbosa, Daniela; Li, Fernanda; Bashir, Sana; Yadró Garcia, Carlos A.; Taliadoros, Demetris; Webster, Matthew; Rufino, José; Roessink, Ivo; Buddendorf, Bas; van der Steen, Jozef; Murcia, Maria; Fernández-Alba, Amadeo Rodríguez; Pinto, M. Alice; Henriques, DoraThe Western honey bee (Apis mellifera)is a key model organism for evaluating risks from Plant Protection Products (PPPs). Despite well-documented impacts of PPPs on honey bees survival and behaviour, their molecular consequences remain underexplored. Herein, over 472 whole genomes from samples collected across Europe in the framework of the project Better-B were used to investigate the genetic basis of PPP exposure through Genomic-Environment Association (GEA) analysis. By integrating genomic data from honey bee colonies with processed PPP exposure data collected in the framework of the project INSIGNIAEU and from the PEST-CHEMGRIDS database as well as from environmental datasets from CORINE land cover, this study used SAMBADA (a spatial analysis tool) and Redundancy Analysis (RDA) scripts to identify candidate genes potentially linked to pesticide stress. This research addresses a knowledge gap, offering a pathway to mitigate PPPrelated molecular effects and support sustainable beekeeping, and can inform breeding programs to bolster honey bee resilience. Ultimately, this work advances our understanding of PPP impacts at the molecular level, fostering resilience in a key pollinator essential for global food security.
- Genetic Diversity of Detoxification Genes in 18 Honey Bee SubspeciesPublication . Li, Fernanda; Barbosa, Daniela; Bashir, Sana; Moreira de Sá, Leandro; Yadró Garcia, Carlos A.; Rufino, José; Rosa-Fontana, Annelise; Verbinnen, Gilles; de Graaf, Dirk; de Smet, Lina; Taliadoros, Demetris; Webster, Matthew; Pinto, M. Alice; Henriques, DoraThe honey bees (Apis mellifera) is a key pollinator that is exposed to a wide array of xenobiotics, both natural (plant allelochemicals) and synthetic (pesticides), while foraging or through contaminated food within the hive. These compounds have both lethal and sub-lethal effects, impairing foraging activity and negatively affecting bee development and colony health. Similar to other insects, honey bees rely on detoxification pathways to metabolise xenobiotics into less toxic or more readily excretable forms. This process is a key mechanism underlying insecticide resistance and is influenced by genetic variation. Therefore, investigating polymorphisms in detoxification-related genes is a promising approach to predict species-specific responses to pesticide exposure. Five major gene families are involved in xenobiotic detoxification: cytochrome P450 monooxygenases (CYPs), carboxyl/cholinesterases (CCEs), glutathione Stransferases (GSTs), ATP-binding cassette transporters (ABCs), and uridine 5′-diphospho-glucuronosyltransferases (UGTs). In this study, we examined the genomic detoxification inventory of over 1,600 individuals representing 18 A. mellifera subspecies representing the four main evolutionary lineages. For each lineage and subspecies, single-nucleotide polymorphism (SNP) loci were identified within these genes, allele frequency and FST (fixation index) were calculated. Additionally, all variants were annotated to assess their potential impact on protein function. Findings from this study have the potential to inform breeding and conservation strategies by identifying populations more vulnerable to chemical stressors, ultimately supporting honey bee health in changing environments.
- Genetic variation of detoxification genes: from genes to proteinsPublication . Henriques, Dora; Li, Fernanda; Bashir, Sana; Quaresma, Andreia; Lopes, Ana Rita; Taliadoros, Demetris; Webster, Matthew; Shiraishi, Carlos S.H.; Yadró Garcia, Carlos A.; Abreu, Rui M.V.; Rufino, José; Rosa-Fontana, Annelise; Verbinnen, Gilles; Graaf, Dirk C. de; De Smet, Lina; Pinto, M. AliceHoney bees (Apis mellifera) are exposed to natural and synthetic xenobiotics, requiring genetic adaptations for survival. Several gene families have been implicated in insect pesticide resistance, including cytochrome P450s, glutathione-S-transferases (GSTs), esterases, and uridine diphosphate (UDP)-glycosyltransferases. This study investigates genetic variation in these detoxification gene families and predicts the structural and functional effects of non-synonymous SNPs (single nucleotide polymorphisms) on protein structure and function. We analyzed SNPs mapped to these detoxification genes extracted from over 1,500 whole genomes representing 15 subspecies and the four main honey bee lineages: M, C, A, and O. Functional annotation and variant effects were predicted using SnpEff. Allele frequencies and each SNP’s fixation index (FST) were calculated per population and evolutionary lineage. Bioinformatics and molecular modeling techniques were employed to evaluate non-synonymous SNPs’ structural and functional consequences. Protein structures were generated from FASTA files using AlphaFold3, converted from mmCIF to PDB format, and visualized in PyMOL. Functional site predictions were performed using Proteins Plus, and molecular dynamics simulations were conducted in YASARA to assess stability and conformational changes in proteins. Our results indicate many non-synonymous SNPs in some subspecies, such as A. m. jemenitica and A. m. intermissa. The genes with the highest number of non-synonymous mutations belong to the CYP family, particularly Probable cytochrome P450 6a14 and CYP9Q1. Conversely, genes such as Cytochrome P450 6k1 and Methyl farnesoate epoxidase exhibit no non-synonymous SNPs. By understanding intraspecific genetic variation, we move closer to reliably predicting how honey bee populations will respond to pesticide exposure.
- Why single snp analyses fail: epistatic structural effects in honey bee CYP336A1Publication . Li, Fernanda; Lima, Daniela; Bashir, Sana; Yadró Garcia, Carlos A.; Graaf, Dirk C. de; De Smet, Lina; Verbinnen, Gilles; Rosa-Fontana, Annelise; Rufino, José; Martín-Hernández, Raquel; Pinto, M. Alice; Henriques, DoraCytochrome P450 enzymes are central to pesticide metabolism and resistance, yet how these proteins diversify substrate specificity while maintaining catalytic function remains poorly understood. A genome-wide analysis of CYP336A1 (a nicotine-metabolizing P450) across 1467 Apis mellifera males from 25 countries spanning the Mediterranean, Middle East, Europe, and Cuba revealed an intricate haplotype architecture. Despite the detection of only 28 single-nucleotide variants (SNPs), 45 distinct haplotypes were detected for CYP336A1. Among these, 23 haplotypes carried at least four SNPs, and four harboured more than 10. A five-SNP haplotype (D202G; M207I; I222V; V226I; Q238K) dominated at 36% frequency, far exceeding the next most common single-SNP haplotype (D262N, 9%). Interestingly, this dominant haplotype was completely absent from the Iberian Peninsula, North Africa, and Oman and, consequently, from five A. mellifera subspecies: iberiensis, intermissa, jemenitica, mellifera and sahariensis. To investigate the functional impact of the identified variants, individually and in combination, we used in sillico protein structural approaches. Protein models were generated with trRosetta, validated with MolProbity, and evaluated using TM-score and RMSD via TM-Align. Structural modelling revealed remarkable fold congruency: the enzyme encoded by the five-SNP haplotype retained a near-identical fold as compared to the wild-type enzyme (TM-score = 0.998, RMSD = 0.34 Å), as did a rarer 13-SNP haplotype (2%) (TM-score = 0.998, RMSD = 0.38 Å). Individual SNPs also produced minimal backbone displacement (0.32–0.54 Å), suggesting that P450 diversification proceeds through subtle structural adjustments rather than major disruption. Moreover, most SNPs clustered within substrate-recognition regions, whereas catalytic residues remained invariant across haplotypes, demonstrating a partitioning between substrate-recognition/binding evolution and preservation of catalytic machinery. Importantly, single-variant effects cannot predict multi-variant haplotype outcomes. As such, heavy reliance on individual SNPs for pesticide risk assessment may misestimate real metabolic capacity.