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A taxogenomic study of three strains (3986 T , 51.81, and JF 2415) isolated from rabbits between 1972 and 2000 led to the description of a new Neisseria species. The highest sequence similarity of the 16S rRNA gene was found to Neisseria animalis NCTC 10212 T (96.7 %). The 16S rRNA gene similarity above 99 % and average nucleotide identity (ANI) values above 96 % among the strains, indicated that they belong to the same species. At the same time, the strains shared ANI values below 81 % and dDDH values below 24 % with all described Neisseria species. In the bac120 gene phylogenetic tree, the three strains clustered near Neisseria elongata and Neisseria bacilliformis in the Neisseria clade. However, the Neisseria clade is not monophyletic, and includes the type strains of Morococcus cerebrosus , Bergeriella denitrificans , Kingella potus , Uruburuella suis , and Uruburuella testudinis. Neisseria shayeganii clustered outside the clade with members of the genus Eikenella . Amino acid identity (AAI) values were calculated, and a threshold of 71 % was used to circumscribe the genus Neisseria . According to this proposed AAI threshold, strains 3986 T , 51.81, and JF 2415 were placed within the genus Neisseria . The cells of the three strains were Gram-stain-negative diplococcobacilli and non-motile. Optimal growth on trypticase soy agar occurred at 37 °C and pH 8.5 in aerobic conditions. Notably, all strains exhibited indole production in the API-NH test, which is atypical for Neisseria and the family Neisseriaceae . The strains exhibited a common set of 68 peaks in their MALDI-TOF MS profiles, facilitating the swift and accurate identification of this species. Based on genotypic and phenotypic data, it is proposed that strains 3986 T , 51.81, and JF 2415 represent a novel species within the genus Neisseria , for which the name Neisseria leonii sp. nov. is proposed (type strain 3986 T =R726 T =CIP 109994 T =LMG 32907 T ).

Microbial biobanks preserve and provide microbial bioresources for research, training, and quality control purposes. They ensure the conservation of biodiversity, contribute to taxonomical research, and support scientific advancements. Microbial biobanks can cover a wide range of phylogenetic and metabolic diversity ("category killers") or focus on specific taxonomic, thematic, or disease areas. The strategic decisions about strain selection for certain applications or for the biobank culling necessitate a method to support prioritization and selection. Here, we propose an unbiased scoring approach based on objective parameters to assess, categorize, and assign priorities among samples in stock in a microbial biobank. We describe the concept of this ranking tool and its application to identify high-priority strains for whole genome sequencing with two main goals: (i) genomic characterization of quality control, reference, and type strains; (ii) genome mining for the discovery of natural products, bioactive and antimicrobial molecules, with focus on human diseases. The general concept of the tool can be useful to any biobank and for any ranking or culling needs.