Biology subjects

Garcia-Comas, C.

Publications and source records attributed to Garcia-Comas, C..

5 recordsLinked to original sources

bioRxiv2026

Temperature-driven dynamics of Chlorella sorokiniana and its microbiome

Temperature is a critical factor in microalgal production, yet its impact on microalgae and their microbiome remains poorly understood. Here, we investigated the responses of Chlorella sorokiniana and its microbial community to temperature increases in four wastewater-based cultures over two months. Two Test cultures were subjected to a thermal gradient from 20 {degrees}C to 34 {degrees}C, and two were Controls at 20 {degrees}C. Eukaryotic and bacterial communities were analyzed using 18S and 16S rRNA gene sequencing, and the microalga genome was reconstructed using PacBio HiFi sequencing and functionally annotated. Control cultures remained stable, whereas Test cultures showed a decline in C. sorokiniana relative abundance and biomass from approximately 24 {degrees}C. In contrast, photosynthetic efficiency remained stable until temperatures exceeded 33 {degrees}C. Above 22-24 {degrees}C, the bacterial community, dominated by Fontibacter, Flavobacterium, and Luteolibacter, was replaced by taxa whose relative abundance increased with rising temperature and microalgal decline, pointing to bacteria better adapted to the stress conditions. Candidate predator-prey dynamics with the protist Cercozoa also intensified as temperature increased. Microalgal genome annotation identified 28 candidate genes corresponding to seven of eight literature-informed high-temperature/heat-stress targets, primarily associated with protein homeostasis, Reactive oxygen species protection, membrane lipid remodeling, and protein degradation. Collectively, these genes likely support the microalga's response and adaptation to environmental stress. Overall, culture destabilization resulted from interacting thermal, microbial, and grazing-related processes rather than temperature alone. Early microbiome changes may therefore provide useful warning signals of culture instability and help improve the management of large-scale microalgal production systems.

microbiology↗

bioRxiv2026

The natural history of bacterial bloomers in a decade-long time series

Bacterial bloomers--populations that experience rapid and significant increases in abundance in response to environmental triggers--briefly dominate marine microbial communities, potentially impacting the ecosystem by channeling large amounts of nutrients and affecting carbon fluxes. Due to their ephemeral nature, bacterial bloomers are challenging to capture, and it remains unknown whether they are restricted to specific taxonomic groups or whether they exhibit recurrent patterns. We analyzed a decade-long time series from the Blanes Bay Microbial Observatory (BBMO, NW Mediterranean Sea) to investigate bacterial bloomers in two size fractions (free-living (0.2-3 {micro}m) and particle-attached (3-20 {micro}m) communities. We identified 57 Amplicon Sequence Variants (ASVs), less than 1% of the total bacterial richness, exhibiting recurrent or chaotic blooming-like behavior. Bloomers spanned diverse phyla, though some taxonomic coherence appeared within families containing multiple blooming taxa. Monthly sampling detected bloom events on average 4.6 {+/-} 1.9 times per year across both size fractions. Once seasonality was accounted for, blooms showed weak associations with biological and physicochemical variables, likely a consequence of monthly sampling resolution. Nonetheless, a marked shift in the blooming community within the particle-attached size fraction coincided with ecosystem disturbances from the nearby harbour restoration, suggesting that bloomers may act as disturbance sentinels. Metagenomic data showed that blooms led to marked shifts in the community functional potential. Overall, our findings underscore the importance of investigating bloom dynamics to understand microbial contributions to biogeochemical cycles and stress the need for higher-frequency sampling to accurately capture these transient but ecologically relevant events.

microbiology↗

bioRxiv2025

INDITEK-2.0: A Bayesian inverse eco-evolutionary modelling framework for reconstructing Phanerozoic biodiversity

O_LIMechanistic eco-evolutionary models are powerful tools for understanding how life diversified over geological timescales, yet estimating their parameters remains a key challenge. The high computational requirements of these models make probabilistic inversion methods unfeasible. C_LIO_LIWe address this challenge with INDITEK-2.0, a new, cost-efficient eco-evolutionary model that integrates a Bayesian inverse modelling framework for probabilistic estimation of parameters. C_LIO_LITo validate this framework, we conducted a proof-of-concept study. We first generated synthetic biodiversity data for marine invertebrates using INDITEK-2.0 with known parameter values. To mimic field data, some realistic random Gaussian errors were added to the data. We then used our Bayesian inverse modelling framework to recover these original (true) parameter values from the dataset of current biodiversity distributions after 500 million years of diversification. Our solution is a probability distribution on the parameter space, and we show that the method successfully recovered the target parameter values with a relatively low degree of uncertainity. C_LIO_LIINDITEK-2.0s ability to probabilistically infer underlying eco-evolutionary processes provides a new modelling tool for reconstructing the evolutionary history of biodiversity across Earths ecosystems and taxonomic groups. C_LI

ecology↗

bioRxiv2025

The complex interplay between microalgae and the microbiome in production raceways

Algae-associated microbiomes are underexplored, limiting our understanding of their influence on the productivity of large-scale microalgae reactors. To address this, we monitored microbial dynamics in two microalgae biomass production raceways over two 8-month intervals inoculated with Desmodesmus armatus. One reactor was fed with wastewater, while the other received clean water and fertilizers. Metabarcoding of the 18S and 16S rRNA genes revealed a high microbial diversity across two time series, showing thousands of eukaryotic and prokaryotic species growing alongside the microalgae. Chlorophyta and Fungi were the dominant eukaryotic groups, while Alphaproteobacteria, Gammaproteobacteria, Actinobacteria, and Bacteroidia dominated the prokaryotic communities. We found contrasting ASVs (Amplicon Sequence Variant) patterns between healthy (D. armatus abundance >70%) and unhealthy (D. armatus abundance <20%) microbiomes, across reactors and time series. Network analysis identified up to 10 potential ecological interactions among D. armatus and its microbiome, predominantly positive. Our results suggest a link between microbiome composition and D. armatus abundance. Specifically, ASVs associated with a healthy microbiome were positively correlated with D. armatus, while ASVs characteristic of an unhealthy microbiome were negatively correlated. Potentially pathogenic bacteria included Mycobacterium and Flavobacterium, whereas potentially beneficial taxa included Geminocystis, Thiocapsa, Ahniella and Bosea. Several fungal ASVs showed context-specific associations, whereas specific P. tribonemae, A. parallelum, A. desmodesmi, Aphelidiomycota sp., Rozellomycota sp. and, Rhizophidium sp. ASVs were identified as potentially harmful. This study reveals the striking diversity and complexity of microalgae-associated microbiomes within raceways, providing valuable insights for optimizing industrial production processes, particularly for wastewater treatment and sustainable green biomass generation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC="FIGDIR/small/633910v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@dfa478org.highwire.dtl.DTLVardef@a6ce03org.highwire.dtl.DTLVardef@11f41f6org.highwire.dtl.DTLVardef@12397b2_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical Abstract.C_FLOATNO General overview of the metabarcoding methodology. Step 1: Sample collection, 2: DNA extraction of the samples, 3: PCR and DNA sequencing of the 18S and 16S rRNA genes, 4: Processing and quality filtering of the DNA sequencing data, 5: Taxonomic, community, and network analyses and, 6: Interpretation and discussion of the results. C_FIG

microbiology↗

bioRxiv2020

Contrasting species functional trait structuring of subarctic versus subtropical copepod communities

Classic niche theory assumes that species-level functional traits affect species relative fitness and thus community structuring, but empirical tests of this assumption are scarce. Moreover, recent evidence shows increasing functional over-redundancy towards the tropics, suggesting that the extent to which functional traits confer species fitness and thus impact community structuring differs across latitudes. Here, we develop a new method: comparing the frequencies of trait categories in the species-rank abundance distributions of local communities versus their frequencies in the regional average species pool. We contrasted subarctic versus subtropical copepod communities for six important traits. In subarctic communities, medium-sized and cold-water species are selected to dominate, thus traits affect relative fitness as predicted by classic niche theory. In subtropical communities, most species are small and warm-water, but these categories are not selected to dominate, suggesting that greater diversity towards the tropics results from lesser trait-based fitness differences allowing more species to coexist.

ecology↗