Denitrification and dissimilatory nitrate reduction to ammonium (DNRA) were thought to be carried-out by anaerobic bacteria constrained to anoxic conditions as they use nitrate (NO₃^-) as a terminal electron acceptor instead of molecular O₂. Three soil bacilli, Neobacillus spp. strains PS2-9 and PS3-12 and Bacillus salipaludis PS3-36, were isolated from rice paddy field soil in Korea. The bacterial strains were selected as possible candidates performing aerobic denitrification and DNRA as they were observed to reduce NO₃^- and produce extracellular NH₄⁺ regardless of oxygen presence at the initial screening. Whole genome sequencing revealed that these strains possessed all the denitrification and DNRA functional genes in their genomes, including the nirK, nosZ, nirB, and nrfA genes, which were simultaneously cotranscribed under aerobic condition. The ratio between the assimilatory and dissimilatory NO₃^- reduction pathways depended on the availability of a nitrogen source for cell growth, other than NO₃^-. Based on the phenotypic and transcriptional analyses of the NO₃^- reductions, all three of the facultative anaerobic strains reduced NO₃^- likely in both assimilatory and dissimilatory pathways under both aerobic and anoxic conditions. To our knowledge, this is the first report that describes coexistence of NO₃^- assimilation, denitrification, and DNRA in a Bacillus or Neobacillus strain under aerobic condition. These strains may play a pivotal role in the soil nitrogen cycle.

Chronic toxoplasmosis is caused by Toxoplasma gondii bradyzoites. This study assessed six candidate small molecule kinase inhibitors (SMKIs) against bradyzoites (ME49 strain), the reactivated form of the parasite resulting from the rupture of brain cysts. Bradyzoites were obtained from mouse brain cysts, cultured in ARPE-19 cells, and treated with afatinib and neratinib (HER2/HER4 inhibitors), ACTB-1003 and regorafenib (VEGFR-2 inhibitors), or altiratinib and foretinib (c-MET inhibitors). The effects on the growth of T. gondii were analyzed by western blot and immunofluorescence assay. Changes in the host cells were assessed using markers for cell viability, apoptosis, necrosis, and autophagy. All inhibitors blocked the growth of bradyzoites, although afatinib was less effective. Afatinib enhanced autophagy signals, while ACTB-1003 and neratinib affected mitochondrial biosynthesis and mitophagy. Altiratinib demonstrated an effect against bradyzoites at the lowest concentration with minimal impact on the host cells. It may be effective in blocking the reactivation of brain cysts in immunodeficiency patients caused by bradyzoites.

This review explores current advancements in microbiome functional analysis enabled by next-generation sequencing technologies, which have transformed our understanding of microbial communities from mere taxonomic composition to their functional potential. We examine approaches that move beyond species identification to characterize microbial activities, interactions, and their roles in host health and disease. Genome-scale metabolic models allow for in-depth simulations of metabolic networks, enabling researchers to predict microbial metabolism, growth, and interspecies interactions in diverse environments. Additionally, computational methods for predicting metabolite profiles offer indirect insights into microbial metabolic outputs, which is crucial for identifying biomarkers and potential therapeutic targets. Functional pathway analysis tools further reveal microbial contributions to metabolic pathways, highlighting alterations in response to environmental changes and disease states. Together, these methods offer a powerful framework for understanding the complex metabolic interactions within microbial communities and their impact on host physiology. While significant progress has been made, challenges remain in the accuracy of predictive models and the completeness of reference databases, which limit the applicability of these methods in under-characterized ecosystems. The integration of these computational tools with multi-omic data holds promise for personalized approaches in precision medicine, allowing for targeted interventions that modulate the microbiome to improve health outcomes. This review highlights recent advances in microbiome functional analysis, providing a roadmap for future research and translational applications in human health and environmental microbiology.