Akkermansia muciniphila is a well-known bacterium with the ability to degrade mucin. This metabolic capability is believed to play an important role in the colonization of this bacterium in the gut. In this study, we report the identification and characterization of a novel Akkermansia sp. DSM 33459 isolated from human feces of a healthy donor. Phylogenetic analysis based on the genome-wide average nucleotide identity indicated that the Akkermansia sp. DSM 33459 has only 87.5% similarity with the type strain A. muciniphila ATCC BAA-835. Akkermansia sp. DSM 33459 showed significant differences in its fatty acid profile and carbon utilization as compared to the type strain. The Akkermansia sp. DSM 33459 strain was tested in a preclinical obesity model to determine its effect on metabolic markers. Akkermansia sp. DSM 33459 showed significant improvement in body weight, total fat weight, and resistin and insulin levels. Interestingly, these effects were more pronounced with the live form as compared to a pasteurized form of the strain. The strain showed production of agmatine, suggesting a potential novel mechanism for supporting metabolic and cognitive health. Based on its phenotypic features and phylogenetic position, it is proposed that this isolate represents a novel species in the genus Akkermansia and a promising therapeutic candidate for the management of metabolic diseases.

Everyday actions such as eating, tooth brushing or applying cosmetics inherently modulate our microbiome. Advances in sequencing technologies now facilitate detailed microbial profiling, driving intentional microbiome-targeted product development. Inspired by an academic-industry workshop held in January 2024, this review explores the oral, skin and gut microbiomes, focussing on the potential long-term implications of perturbations. Key challenges in microbiome safety assessment include confounding factors (ecological variability, host influences and external conditions like geography and diet) and biases from experimental measurements and bioinformatics analyses. The taxonomic composition of the microbiome has been associated with both health and disease, and perturbations like regular disruption of the dental biofilm are essential for preventing caries and inflammatory gum disease. However, further research is required to understand the potential long-term impacts of microbiome disturbances, particularly in vulnerable populations including infants. We propose that emerging technologies, such as omics technologies to characterize microbiome functions rather than taxa, leveraging artificial intelligence to interpret clinical study data and in vitro models to characterize and measure host–microbiome interaction endpoints, could all enhance the risk assessments. The workshop emphasized the importance of detailed documentation, transparency and openness in computational models to reduce uncertainties. Harmonisation of methods could help bridge regulatory gaps and streamline safety assessments but should remain flexible enough to allow innovation and technological advancements. Continued scientific collaboration and public engagement are critical for long-term microbiome monitoring, which is essential to advancing safety assessments of microbiome perturbations.