Phylogenetic analysis reveals that the H5N1 avian influenza A outbreak in poultry in Ecuador in November 2022 is associated with the highly pathogenic clade 2.3.4.4b.

The ongoing H5N1 outbreak in the Americas caused by clade 2.3.4.4 is causing unprecedented impact in poultry and wild birds. In November 2022, a highly pathogenic avian influenza A outbreak was declared in poultry in Ecuador, affecting more than 1.1 million heads of poultry in two farms by February 2023. Phylogenetic analysis shows that the virus clade is 2.3.4.4b, and to the best of our knowledge, this is the first scientific publication reporting this clade in South America.

Metallopeptidases as Key Virulence Attributes of Clinically Relevant Protozoa: New Discoveries, Perspectives, and Frontiers of Knowledge.

This article provides a comprehensive review of several subclasses of metallo-type peptidases expressed by the main clinically relevant protozoa, including Plasmodium spp., Toxoplasma gondii, Cryptosporidium spp., Leishmania spp., Trypanosoma spp., Entamoeba histolytica, Giardia duodenalis, and Trichomonas vaginalis. These species comprise a diverse group of unicellular eukaryotic microorganisms responsible for widespread and severe human infections. Metallopeptidases, defined as hydrolases with activity mediated by divalent metal cation, play important roles in the induction and maintenance of parasitic infections. In this context, metallopeptidases can be considered veritable virulence factors in protozoa with direct/indirect participation in several key pathophysiological processes, including adherence, invasion, evasion, excystation, central metabolism, nutrition, growth, proliferation, and differentiation. Indeed, metallopeptidases have become an important and valid target to search for new compounds with chemotherapeutic purposes. The present review aims to gather updates regarding metallopeptidase subclasses, exploring their participation in protozoa virulence as well as investigating the similarity of peptidase sequences through bioinformatic techniques in order to discover clusters of great relevance for the development of new broad antiparasitic molecules.