The microbiome: Effects of region, season, and physiology.

Introduction: is a canopy-forming species of brown algae and, as such, is considered an ecosystem engineer. Several populations of this alga are exploited worldwide, and a decrease in the abundance of at its southern distributional range limits has been observed. Despite its economic and ecological interest, only a few data are available on the composition of microbiota associated with and its role in algal physiologyn.

Insights into the potential for mutualistic and harmful host-microbe interactions affecting brown alga freshwater acclimation.

Microbes can modify their hosts' stress tolerance, thus potentially enhancing their ecological range. An example of such interactions is Ectocarpus subulatus, one of the few freshwater-tolerant brown algae. This tolerance is partially due to its (un)cultivated microbiome.

Effects of sampling and storage procedures on 16S rDNA amplicon sequencing results of kelp microbiomes.

Brown macroalgae, including the kelp Saccharina latissima, are of both ecological and increasing economic interest. Together with their microbiota, these organisms form a singular entity, the holobiont. Sampling campaigns are required to study the microbiome of algae in natural populations, but freezing samples in liquid nitrogen is complex in the field, particularly at remote locations.

Semi-Quantitative Targeted Gas Chromatography-Mass Spectrometry Profiling Supports a Late Side-Chain Reductase Cycloartenol-to-Cholesterol Biosynthesis Pathway in Brown Algae.

Sterols are biologically important molecules that serve as membrane fluidity regulators and precursors of signaling molecules, either endogenous or involved in biotic interactions. There is currently no model of their biosynthesis pathways in brown algae. Here, we benefit from the availability of genome data and gas chromatography-mass spectrometry (GC-MS) sterol profiling using a database of internal standards to build such a model.

Inferring Biochemical Reactions and Metabolite Structures to Understand Metabolic Pathway Drift.

Inferring genome-scale metabolic networks in emerging model organisms is challenged by incomplete biochemical knowledge and partial conservation of biochemical pathways during evolution. Therefore, specific bioinformatic tools are necessary to infer biochemical reactions and metabolic structures that can be checked experimentally. Using an integrative approach combining genomic and metabolomic data in the red algal model Chondrus crispus, we show that, even metabolic pathways considered as conserved, like sterols or mycosporine-like amino acid synthesis pathways, undergo substantial turnover.