Interactions among microbes determine the prevalence of harmful algal blooms that threaten water quality. These interactions can be indirectly mediated by shared resources or consumers, or through interference by the production of allelochemicals. Allelopathic interactions and resource competition have been shown to occur among algae and associated microbes. However, little work has considered seasonal influences on ecosystem structure and function. Here, we report results of our investigations on seasonal changes in the interactions between benthic microbial assemblies and the bloom forming cyanobacterium Microcystis aeruginosa. We show that phosphorus (P) competition and allelopathy by the microbial assembly vary seasonally and inhibit growth of M. aeruginosa. The interactions per unit biomass of the microbial assembly are stronger under winter than summer conditions and inhibit the recruitment of the cyanobacteria, thereby preventing the reoccurrence of cyanobacterial blooms in the following summer. The seasonality of these interactions correlates with changes in composition, metabolic activity and functional diversity of the microbial assembly. Our findings highlight the importance of competitive and allelopathic interactions in regulating the occurrence of harmful algal blooms. Our results also imply that seasonal variation of competition and allelopathy of the microbial assembly might be beneficial to adjust aquatic ecosystem structure and function.
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http://dx.doi.org/10.1111/1462-2920.13781 | DOI Listing |
Mathematical modeling of somatic evolution, a process impacting both host cells and microbial communities in the human body, can capture important dynamics driving carcinogenesis. Here we considered models for esophageal adenocarcinoma (EAC), a cancer that has dramatically increased in incidence over the past few decades in Western populations, with high case fatality rates due to late-stage diagnoses. Despite advancements in genomic analyses of the precursor Barrett's esophagus (BE), prevention of late-stage EAC remains a significant clinical challenge.
View Article and Find Full Text PDFUnlabelled: Antibiotic resistance is frequently observed shortly after the clinical introduction of an antibiotic. Whether and how frequently that resistance occurred before the introduction is harder to determine, as isolates could not have been tested for resistance before an antibiotic was discovered. Historical collections, like the British National Collection of Type Cultures (NCTC), stretching back to 1885, provide a window into this history.
View Article and Find Full Text PDFBackground: Neonatal mice are frequently used to model diseases that affect human infants. Microbial community composition has been shown to impact disease progression in these models. Despite this, the maturation of the early-life murine microbiome has not been well-characterized.
View Article and Find Full Text PDFISME Commun
January 2025
State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China.
Antarctic snow harbors diverse microorganisms, including pigmented algae and bacteria, which create colored snow patches and influence global climate and biogeochemical cycles. However, the genomic diversity and metabolic potential of colored snow remain poorly understood. We conducted a genome-resolved study of microbiomes in colored snow from 13 patches (7 green and 6 red) on the Fildes Peninsula, Antarctica.
View Article and Find Full Text PDFVirus Res
January 2025
Molecular Biology and Functional Genomics Platform, National Centre for Scientific and Technical Research (CNRST), Rabat, Morocco; Genomic Centre for Human Pathologies (GENOPATH), Neuroscience and Neurogenetics Research Team, Faculty of Medicine and Pharmacy, University Mohammed V, Rabat, Morocco. Electronic address:
This study investigates the evolution and genetic diversity of SARS-CoV-2 strains circulating in Morocco to track the spread, clade distributions and mutations of the virus across various regions from February 2020 to June 2024. The genome sequences were retrieved from the GISAID database. A total of 2630 SARS-CoV-2 genome sequences were analyzed using bioinformatic tools such as Nextclade, followed by phylogenetic and statistical analyses.
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