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Abstract Coastal upwelling currents such as the California Current System (CCS) comprise some of the most productive biological systems on the planet. Diatoms dominate these upwelling events in part due to their rapid response to nutrient entrainment. In this region, they may also be limited by the micronutrient iron (Fe), an important trace element primarily involved in photosynthesis and nitrogen assimilation. The mechanisms behind how diatoms physiologically acclimate to the different stages of the upwelling conveyor belt cycle remain largely uncharacterized. Here, we explore their physiological and metatranscriptomic response to the upwelling cycle with respect to the Fe limitation mosaic that exists in the CCS. Subsurface, natural plankton assemblages that would potentially seed surface blooms were examined over wide and narrow shelf regions. The initial biomass and physiological state of the phytoplankton community had a large impact on the overall response to simulated upwelling. Following on‐deck incubations under varying Fe physiological states, our results suggest that diatoms quickly dominated the blooms by “frontloading” nitrogen assimilation genes prior to upwelling. However, diatoms subjected to induced Fe limitation exhibited reductions in carbon and nitrogen uptake and decreasing biomass accumulation. Simultaneously, they exhibited a distinct gene expression response which included increased expression of Fe‐starvation induced proteins and decreased expression of nitrogen assimilation and photosynthesis genes. These findings may have significant implications for upwelling events in future oceans, where changes in ocean conditions are projected to amplify the gradient of Fe limitation in coastal upwelling regions. 

ABSTRACT Eastern boundary upwelling currents are some of the most biologically productive and diverse regions in the world's oceans. Driven by equatorward winds and Ekman transport, surface waters are transported offshore and replaced by cold, nutrient‐rich deep waters that seed extensive phytoplankton blooms. Studying phytoplankton community succession and physiological acclimation during the initial stages of upwelling is critical to building a comprehensive understanding of phytoplankton responses to upwelling in these important regions. Additionally, factors like lateral transport, seed population dynamics and physiological and molecular shifts are conducive to shaping the community assemblage and primary productivity. This study examines how phytoplankton gene expression and resulting physiology change between early and later phases of upwelling. By incorporating metatranscriptomic analyses and stable isotope incubations to measure nutrient uptake kinetics into our assessment of early and later upwelling stages, we observed variability in phytoplankton assemblages and differential gene expression of phytoplankton that were de‐coupled from their physiology. We show that the gene expression response to a fresh upwelling event precedes their physiological response. Ultimately, understanding how phytoplankton change through the course of an upwelling event is critical to assessing their importance to regional biological rate processes, trophic systems and resulting biogeochemistry. 

Abstract The oceanic biogeochemical cycling of iron is globally important yet difficult to fully understand due to the many chemical processes involved. There is potential to use scandium, which has a similar ionic size and charge density to trivalent iron but lacks redox cycling, as a simpler analog for specific parts of the iron cycle, if we can sufficiently develop our understanding of scandium's reactivity. Here we move closer to this understanding. We look at particle reactivity and solubility through a 24‐hr incubation experiment: 5 nmol/kg of dissolved scandium and/or iron were added to filtered and unfiltered California Current System water. Particulate scandium formed only in the unfiltered treatments, at a quantity unlikely to have been taken up biologically. This is the first direct observation of scavenging of scandium, an attribute shared with iron. Our results also serve as the first test of scandium solubility in seawater: 1.9 nmol/kg of dissolved scandium was stable in the filtered treatment, 50 times more than the highest natural concentrations so far observed. This indicates that, in contrast to iron, scandium's oceanic cycling is unlikely to be influenced by solubility limits. We also compare particulate depth profiles: labile particulate iron was disproportionally higher than that of scandium in shelf‐influenced samples, likely due to iron reductively dissolving in the sediments, which scandium cannot do, and then precipitating in oxic seawater. Due to this combination of behaviors, our results suggest that paired observations of scandium and iron may help distinguish between iron sourced from sediment resuspension and reductive dissolution. 

Bacterial–fungal interactions (BFIs) can shape the structure of microbial communities, but the small molecules mediating these BFIs are often understudied. We explored various optimization steps for our microbial culture and chemical extraction protocols for bacterial–fungal co-cultures, and liquid chromatography-tandem mass spectrometry (LC-MS/MS) revealed that metabolomic profiles are mainly comprised of fungi derived features, indicating that fungi are the key contributors to small molecules in BFIs. LC-inductively coupled plasma MS (LC-ICP-MS) and MS/MS based dereplication using database searching revealed the presence of several known fungal specialized metabolites and structurally related analogues in these extracts, including siderophores such as desferrichrome, desferricoprogen, and palmitoylcoprogen. Among these analogues, a novel putative coprogen analogue possessing a terminal carboxylic acid motif was identified from Scopulariopsis sp. JB370, a common cheese rind fungus, and its structure was elucidated via MS/MS fragmentation. Based on these findings, filamentous fungal species appear to be capable of producing multiple siderophores with potentially different biological roles ( i.e. various affinities for different forms of iron). These findings highlight that fungal species are important contributors to microbiomes via their production of abundant specialized metabolites and that elucidating their role in complex communities should continue to be a priority. 

Abstract Diatom community composition has a critical influence on global ocean health and ecological processes. Developing accurate and efficient methods for diatom identification under dynamic environmental conditions is essential to understanding the implications of diatom community changes. Two developing methods for identifying and enumerating phytoplankton, cell imaging and molecular sequencing, are experiencing rapid advancements. This study aims to compare diatom taxonomic composition results within natural assemblages derived from rapidly advancing methods, FlowCam imaging and metabarcoding of the V4 region of the 18S rRNA gene, with traditional light microscopy cell counting techniques. All three methods were implemented in tandem to analyze changes in dynamic diatom assemblages within simulated upwelling experiments conducted in the California upwelling zone. The results of this study indicate that, summed across all samples, DNA sequencing detected four times as many genera as morphology‐based methods, thus supporting previous findings that DNA sequencing is the most powerful method for analyzing species richness. Results indicate that all three methods returned comparable relative abundance for the most abundant genera. However, the three methods did not return comparable absolute abundance, primarily due to barriers in deriving quantities in equal units. Overall, this study indicates that at the semi‐quantitative level of relative abundance measurements, FlowCam imaging and metabarcoding of the V4 region of the 18S rRNA gene yield comparable results with light microscopy but at the qualitative and quantitative levels, enumeration metrics diverge, and thus method selection and cross‐method comparison should be performed with caution. 

Multispecies microbiome systems are known to be closely linked to human, animal, and plant life processes. The growing field of metabolomics presents the opportunity to detect changes in overall metabolomic profiles of microbial species interactions. These metabolomic changes provide insight into function of metabolites as they correlate to different species presence and the observed phenotypic changes, but detection of subtle changes is often difficult in samples with complex backgrounds. Natural environments such as soil and food contain many molecules that convolute mass spectrometry-based analyses, and identification of microbial metabolites amongst environmental metabolites is an informatics problem we begin to address here. Our microbes are grown on solid or liquid cheese curd media. This medium, which is necessary for microbial growth, contains high amounts of salts, lipids, and casein breakdown products which make statistical analyses using LC-MS/MS data difficult due to the high background from the media. We have developed a simple algorithm to carry out background subtraction from microbes grown on solid or liquid cheese curd media to aid in our ability to conduct statistical analyses so that we may prioritize metabolites for further structure elucidation.