Search Results (3)

Synthetic biology has advanced in creating artificial microbial and algal communities, but technical and evolutionary complexities still pose significant challenges. Traditional methods, like microscopy and pigment analysis, are limited in throughput and resolution. In contrast, advancements in full-spectrum cytometry enabled high-throughput, multidimensional analysis of single cells based on size, complexity, and spectral fingerprints, offering more precision and flexibility than conventional flow cytometry. This study uses full-spectrum cytometry to analyze synthetic algal–microbial communities, enabling rapid species identification and enumeration. The workflow involves recording individual spectral signatures from monocultures, using autofluorescence to capture populations of interest, and creating a spectral library for further analysis. This spectral library was used for the analysis of the synthetic phytoplankton communities, revealing differences in spectral signatures. Moreover, the synthetic consortium experiment monitored algal growth, comparing results from different instruments, highlighting the advantages of the spectral virtual filter system for precise population separation and abundance tracking. By capturing the entire emission spectrum of each cell, this method enhances understanding of algal–microbial community dynamics and responses to environmental stressors. The development of standardized spectral libraries would improve the characterization of algal communities, further advancing synthetic biology and phytoplankton ecology research. Full article

Over the years, foodborne pathogens have caused countess health problems and massive financial losses. Therefore, an essential goal for the food industry is to prevent food contamination and the related foodborne illnesses as microbial contamination of food items during their acquiring and distribution processes is still a hygienic issue. Moreover, there is an important movement leading to the pursuit of more natural and safe food supplies and ingredients with a special emphasis on the vegan and vegetarian community; as a result, there has been a resurgence in demand for natural and eco-friendly products as a replacement for synthetic ingredients. In this context, and due to their active substances, macroalgae stand out as they are known for possessing antibacterial qualities among other abilities. Because of this, the current study updates our understanding of microbial pollutants in the food industry and compiles the latest updates on the scientific reports on antimicrobial activity of the edible brown algae species with special attention to the algae Bifurcaria bifurcata, Fucus spiralis, and Ascophyllum nodosum. These species which belong to the Phaeophyceae class and order Fucales are reportedly rich in active compounds and are still an undervalued resource. So, the ability of algal extracts to stop the growth of various significant food pathogens is reviewed herein, while considering their advantageous effects on food safety and quality issues. Full article

The pennate diatom Phaeodactylum tricornutum is a model organism able to synthesize industrially-relevant molecules. Commercial-scale cultivation currently requires large monocultures, prone to bio-contamination. However, little is known about the identity of the invading organisms. To reduce the complexity of natural systems, we systematically investigated the microbiome of non-axenic P. tricornutum cultures from a culture collection in reproducible experiments. The results revealed a dynamic bacterial community that developed differently in “complete” and “minimal” media conditions. In complete media, we observed an accelerated “culture crash”, indicating a more stable culture in minimal media. The identification of only four bacterial families as major players within the microbiome suggests specific roles depending on environmental conditions. From our results we propose a network of putative interactions between P. tricornutum and these main bacterial factions. We demonstrate that, even with rather sparse data, a mathematical model can be reconstructed that qualitatively reproduces the observed population dynamics, thus indicating that our hypotheses regarding the molecular interactions are in agreement with experimental data. Whereas the model in its current state is only qualitative, we argue that it serves as a starting point to develop quantitative and predictive mathematical models, which may guide experimental efforts to synthetically construct and monitor stable communities required for robust upscaling strategies. Full article