Identification and analysis of the transferrin protein family in the honey bee, Apis mellifera

MUCCI, CLAUDIO ANDONI; VILLAREAL, FERNANDO; FORESI, NOELIA; MAGGI, MATÍAS; RAMÍREZ, LEONOR

Conferencia; Virtual Conference Biology & Genomics of Social Insects; 2021

The increasing availability of insect genomes information has formed the basis of new approaches to the study of the bee?s health. The search for similarity in protein sequences has provided important insights into the molecular mechanisms that regulate diverse biological traits of organisms. Transferrins (Tfs) are proteins that play a central role in iron transport, growth, differentiation and immunity in vertebrates. Tfs consist of a 13-member evolutionarily related protein family among the putative Tfs of vertebrates, invertebrates, and plants. In the Insecta class, at least four Tf family members (Tsf 1-4) have been identified. Recently, Tsf1 was shown to play an important role in the nutritional immunity of Drospohila melanogaster by sequestering iron from invading pathogens. Tsf2 from D. melanogaster also binds iron and it works in the formation of epithelial cell junctions. At the moment, there is no empirical evidence on the state of binding to iron and the function of Tsf3 and Tsf4. In the honey bee Apis mellifera an exhaustive search for Tfs has not yet been carried out. The goals of this project are: i) to identify all the Tfs members in a diverse set of insect proteomes, ii) to perform a comprehensive phylogenetic analysis, iii) to analyze the characteristic motif and iron-binding residues of A. mellifera Tfs, iv) to predict their functional annotation. We initially used hmmbuild to create an insect Tf hidden Markov model (HMM) profile using a set of insect Tf sequences from Pfam and Swiss-Prot databases. Subsequently, the new HMM profile was used to search (hmmsearch) against 50 proteomes of organisms belonging to the different orders of insects, including several representatives of the order Hymenoptera. Next, we removed pseudogenes and entries from incorrect gene models with a dedicated automated pipeline. Finally, the resulting hits were recognized as putative Tfs and such sequences were subjected to alignment and, finally we identify whether they have the Tf domains. The phylogenetic reconstruction of insect Tfs was performed with a maximum likelihood approach (PhyML). In this work, we were able to identify in A. mellifera members of the Tfs family, their characteristic residues, and evolutionary relationships. Due to the accumulation of studies supporting the immunological role of insect Tfs against infections, our results allow to identify new candidates to study the specific roles of Tfs in honey bee health.