Percorrer por autor "Lima, Daniela"
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- Landscape-scale genomic responses of the western honey bee (Apis mellifera) to pesticide pressurePublication . Lima, Daniela; Li, Fernanda; Yadró Garcia, Carlos A.; Taliadoros, Demetris; Webster, Matthew; Rufino, José; Roessink, I.; Buddendorf, Bas; Van der Steen, Jozef; Murcia-Morales, María; Fernández-Alba, Amadeo R.; Graaf, Dirk C. de; Lopes, Ana Rita; Pinto, M. Alice; Henriques, DoraWidespread pesticide use associated with intensive agriculture has been proven to impact the Western honey bee (Apis mellifera). However, despite evidence of declines in survival, development, foraging efficiency, and overall colony health, the genomic underpinning of this abiotic stressor is largely unknown. This study involved 102 whole-genome sequences from honey bee colonies from across Europe, sampled under the Better-B project, to search for genetic correlations to pesticide exposure using Genomic-Environment Association (GEA) analyses. The environmental exposure data were collected within the framework of the INSIGNIA-EU project, which used APIStrips (in-hive pesticide-adsorbing strips) to quantify pesticide residues brought into the hive by foraging in many of the sampled colonies. The APISTRIP data were complemented by modelled exposure grids from PEST-CHEMGRIDS and agriculture zones from the CORINE Land Cover. Employing three complementary GEA approaches-SAMBADA (spatial analysis tool), LFMM (latent factor mixed models), and RDA (Redundancy Analysis)—we identified SNPs in the bee’s genome significantly correlated with agricultural pressure and pesticide use. Notably, several genes with known roles in detoxification and stress response, including venom carboxylesterase6 and CYP336A1, were highlighted. These variants point to molecular pathways targeted by agrochemical toxicity, offering insights into the consequences of pesticide use. Such findings may, in the future and upon further validation, help refine risk assessment frameworks, support the development of resilience-oriented breeding programs, and promote sustainable apicultural practices.
- 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.