Maintaining beneficial alga-associated bacterial communities under heat stress: insights from controlled co-culture experiments using antibiotic-resistant bacterial strains.

Brown algae, like many eukaryotes, possess diverse microbial communities. Ectocarpus-a model brown alga-relies on these communities for essential processes, such as growth development. Controlled laboratory systems are needed for functional studies of these algal-bacterial interactions. We selected bacterial strains based on their metabolic networks to provide optimal completion of the algal metabolism, rendered them resistant to two antibiotics, and inoculate them to establish controlled co-cultures with Ectocarpus under continuous antibiotic treatment. We then monitored the stability of the resulting associations under control conditions and heat stress using 16S metabarcoding. Antibiotics strongly reduced bacterial diversity both in terms of taxonomy and predicted metabolic functions. In the inoculated sample, 63%-69% of reads corresponded to the inoculated strains, and the communities remained stable during temperature stress. They also partially restored the predicted metabolic functions of the natural community. Overall, the development of antibiotic-resistant helper cultures offers a promising route to fully controlled laboratory experiments with algae and microbiota and thus represents an important step towards generating experimental evidence for specific host-microbe interactions in the systems studied. Further work will be required to achieve full control and progressively expand our repertoire of helper strains including those currently 'unculturable'.

The Rhodoexplorer Platform for Red Algal Genomics and Whole-Genome Assemblies for Several Gracilaria Species.

Macroalgal (seaweed) genomic resources are generally lacking as compared with other eukaryotic taxa, and this is particularly true in the red algae (Rhodophyta). Understanding red algal genomes is critical to understanding eukaryotic evolution given that red algal genes are spread across eukaryotic lineages from secondary endosymbiosis and red algae diverged early in the Archaeplastids. The Gracilariales is a highly diverse and widely distributed order including species that can serve as ecosystem engineers in intertidal habitats and several notorious introduced species. The genus Gracilaria is cultivated worldwide, in part for its production of agar and other bioactive compounds with downstream pharmaceutical and industrial applications. This genus is also emerging as a model for algal evolutionary ecology. Here, we report new whole-genome assemblies for two species (Gracilaria chilensis and Gracilaria gracilis), a draft genome assembly of Gracilaria caudata, and genome annotation of the previously published Gracilaria vermiculophylla genome. To facilitate accessibility and comparative analysis, we integrated these data in a newly created web-based portal dedicated to red algal genomics (https://rhodoexplorer.sb-roscoff.fr). These genomes will provide a resource for understanding algal biology and, more broadly, eukaryotic evolution.

Inferring and comparing metabolism across heterogeneous sets of annotated genomes using AuCoMe.

Comparative analysis of genome-scale metabolic networks (GSMNs) may yield important information on the biology, evolution, and adaptation of species. However, it is impeded by the high heterogeneity of the quality and completeness of structural and functional genome annotations, which may bias the results of such comparisons. To address this issue, we developed AuCoMe, a pipeline to automatically reconstruct homogeneous GSMNs from a heterogeneous set of annotated genomes without discarding available manual annotations. We tested AuCoMe with three data sets, one bacterial, one fungal, and one algal, and showed that it successfully reduces technical biases while capturing the metabolic specificities of each organism. Our results also point out shared and divergent metabolic traits among evolutionarily distant algae, underlining the potential of AuCoMe to accelerate the broad exploration of metabolic evolution across the tree of life.

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. We investigated this phenomenon by modifying the microbiome of laboratory-grown E. subulatus using mild antibiotic treatments, which affected its ability to grow in low salinity. Low salinity acclimation of these algal-bacterial associations was then compared. Salinity significantly impacted bacterial and viral gene expression, albeit in different ways across algal-bacterial communities. In contrast, gene expression of the host and metabolite profiles were affected almost exclusively in the freshwater-intolerant algal-bacterial communities. We found no evidence of bacterial protein production that would directly improve algal stress tolerance. However, vitamin K synthesis is one possible bacterial service missing specifically in freshwater-intolerant cultures in low salinity. In this condition, we also observed a relative increase in bacterial transcriptomic activity and the induction of microbial genes involved in the biosynthesis of the autoinducer AI-1, a quorum-sensing regulator. This could have resulted in dysbiosis by causing a shift in bacterial behaviour in the intolerant algal-bacterial community. Together, these results provide two promising hypotheses to be examined by future targeted experiments. Although they apply only to the specific study system, they offer an example of how bacteria may impact their host's stress response.

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. Here we tested two simple alternative methods for sampling the microbial diversity associated with the kelp S. latissima: silica gel conservation of tissue and swab samples preserved in DNA/RNA shield solution. We used these techniques to compare apex and meristem samples from Roscoff (Brittany, France) and evaluated their impact on the results of 16S rDNA metabarcoding experiments. Both methods were able to separate apex and meristem microbiomes, and the results were concordant with results obtained for flash-frozen samples. However, differences were observed for several rare genera and ASVs, and the detection of contaminant sequences in the silica gel-preserved samples underline the importance of including blank samples for this method. Globally, our results confirm that the silica gel technique and swabbing combined with DNA/RNA shield preservation are valid alternatives to liquid nitrogen preservation when sampling brown macroalgae in the field. However, they also underline that, regardless of the method, caution should be taken when interpreting data on rare sequences.

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

Introduction: Saccharina latissima 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 S. latissima 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 S. latissima and its role in algal physiologyn. Methods: We studied the whole bacterial community composition associated with S. latissima samples from three locations (Brittany, Helgoland, and Skagerrak) by 16S metabarcoding analyses at different scales: algal blade part, regions, season (at one site), and algal physiologic state. Results and Discussion: We have shown that the difference in bacterial composition is driven by factors of decreasing importance: (i) the algal tissues (apex/meristem), (ii) the geographical area, (iii) the seasons (at the Roscoff site), and (iv) the algal host's condition (healthy vs. symptoms). Overall, Alphaproteobacteria, Gammaproteobacteria, and Bacteroidia dominated the general bacterial communities. Almost all individuals hosted bacteria of the genus Granulosicoccus, accounting for 12% of the total sequences, and eight additional core genera were identified. Our results also highlight a microbial signature characteristic for algae in poor health independent of the disease symptoms. Thus, our study provides a comprehensive overview of the S. latissima microbiome, forming a basis for understanding holobiont functioning.

Robustness analysis of metabolic predictions in algal microbial communities based on different annotation pipelines.

Animals, plants, and algae rely on symbiotic microorganisms for their development and functioning. Genome sequencing and genomic analyses of these microorganisms provide opportunities to construct metabolic networks and to analyze the metabolism of the symbiotic communities they constitute. Genome-scale metabolic network reconstructions rest on information gained from genome annotation. As there are multiple annotation pipelines available, the question arises to what extent differences in annotation pipelines impact outcomes of these analyses. Here, we compare five commonly used pipelines (Prokka, MaGe, IMG, DFAST, RAST) from predicted annotation features (coding sequences, Enzyme Commission numbers, hypothetical proteins) to the metabolic network-based analysis of symbiotic communities (biochemical reactions, producible compounds, and selection of minimal complementary bacterial communities). While Prokka and IMG produced the most extensive networks, RAST and DFAST networks produced the fewest false positives and the most connected networks with the fewest dead-end metabolites. Our results underline differences between the outputs of the tested pipelines at all examined levels, with small differences in the draft metabolic networks resulting in the selection of different microbial consortia to expand the metabolic capabilities of the algal host. However, the consortia generated yielded similar predicted producible compounds and could therefore be considered functionally interchangeable. This contrast between selected communities and community functions depending on the annotation pipeline needs to be taken into consideration when interpreting the results of metabolic complementarity analyses. In the future, experimental validation of bioinformatic predictions will likely be crucial to both evaluate and refine the pipelines and needs to be coupled with increased efforts to expand and improve annotations in reference databases.

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. We expand the set of identified sterols in 11 species of red, brown, and green macroalgae and integrate these new data with genomic data. Our analyses suggest that some metabolic reactions may be conserved despite the loss of canonical eukaryotic enzymes, like the sterol side-chain reductase (SSR). Our findings are consistent with the principle of metabolic pathway drift through enzymatic replacement and show that cholesterol synthesis from cycloartenol may be a widespread but variable pathway among chlorophyllian eukaryotes. Among the factors contributing to this variability, one could be the recruitment of cholesterol biosynthetic intermediates to make signaling molecules, such as the mozukulins. These compounds were found in some brown algae belonging to Ectocarpales, and we here provide a first mozukulin biosynthetic model. Our results demonstrate that integrative approaches can already be used to infer experimentally testable models, which will be useful to further investigate the biological roles of those newly identified algal pathways.

A community perspective on the concept of marine holobionts: current status, challenges, and future directions.

Host-microbe interactions play crucial roles in marine ecosystems. However, we still have very little understanding of the mechanisms that govern these relationships, the evolutionary processes that shape them, and their ecological consequences. The holobiont concept is a renewed paradigm in biology that can help to describe and understand these complex systems. It posits that a host and its associated microbiota with which it interacts, form a holobiont, and have to be studied together as a coherent biological and functional unit to understand its biology, ecology, and evolution. Here we discuss critical concepts and opportunities in marine holobiont research and identify key challenges in the field. We highlight the potential economic, sociological, and environmental impacts of the holobiont concept in marine biological, evolutionary, and environmental sciences. Given the connectivity and the unexplored biodiversity specific to marine ecosystems, a deeper understanding of such complex systems requires further technological and conceptual advances, e.g., the development of controlled experimental model systems for holobionts from all major lineages and the modeling of (info)chemical-mediated interactions between organisms. Here we propose that one significant challenge is to bridge cross-disciplinary research on tractable model systems in order to address key ecological and evolutionary questions. This first step is crucial to decipher the main drivers of the dynamics and evolution of holobionts and to account for the holobiont concept in applied areas, such as the conservation, management, and exploitation of marine ecosystems and resources, where practical solutions to predict and mitigate the impact of human activities are more important than ever.

Using automated reasoning to explore the metabolism of unconventional organisms: a first step to explore host-microbial interactions.

Systems modelled in the context of molecular and cellular biology are difficult to represent with a single calibrated numerical model. Flux optimisation hypotheses have shown tremendous promise to accurately predict bacterial metabolism but they require a precise understanding of metabolic reactions occurring in the considered species. Unfortunately, this information may not be available for more complex organisms or non-cultured microorganisms such as those evidenced in microbiomes with metagenomic techniques. In both cases, flux optimisation techniques may not be applicable to elucidate systems functioning. In this context, we describe how automatic reasoning allows relevant features of an unconventional biological system to be identified despite a lack of data. A particular focus is put on the use of Answer Set Programming, a logic programming paradigm with combinatorial optimisation functionalities. We describe its usage to over-approximate metabolic responses of biological systems and solve gap-filling problems. In this review, we compare steady-states and Boolean abstractions of metabolic models and illustrate their complementarity via applications to the metabolic analysis of macro-algae. Ongoing applications of this formalism explore the emerging field of systems ecology, notably elucidating interactions between a consortium of microbes and a host organism. As the first step in this field, we will illustrate how the reduction in microbiotas according to expected metabolic phenotypes can be addressed with gap-filling problems.

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. This phenomenon, here formally defined as "metabolic pathway drift," is consistent with findings from other areas of evolutionary biology, indicating that a given phenotype can be conserved even if the underlying molecular mechanisms are changing. We present a proof of concept with a methodological approach to formalize the logical reasoning necessary to infer reactions and molecular structures, abstracting molecular transformations based on previous biochemical knowledge.

Revisiting Australian Ectocarpus subulatus (Phaeophyceae) From the Hopkins River: Distribution, Abiotic Environment, and Associated Microbiota.

In 1995 a strain of Ectocarpus was isolated from Hopkins River Falls, Victoria, Australia, constituting one of few available freshwater or nearly freshwater brown algae, and the only one belonging to the genus Ectocarpus. It has since been used as a model to study acclimation and adaptation to low salinities and the role of its microbiota in these processes. To provide more background information on this model, we assessed if Ectocarpus was still present in the Hopkins river 22 years after the original finding, estimated its present distribution, described its abiotic environment, and determined its in situ microbial composition. We sampled for Ectocarpus at 15 sites along the Hopkins River as well as 10 neighboring sites and found individuals with ITS and cox1 sequences identical to the original isolate at three sites upstream of Hopkins River Falls. The salinity of the water at these sites ranged from 3.1 to 6.9, and it was rich in sulfate (1-5 mM). The diversity of bacteria associated with the algae in situ (1312 operational taxonomic units) was one order of magnitude higher than in previous studies of the original laboratory culture, and 95 alga-associated bacterial strains were isolated from algal filaments on site. In particular, species of Planctomycetes were abundant in situ but rare in laboratory cultures. Our results confirmed that Ectocarpus was still present in the Hopkins River, and the newly isolated algal and bacterial strains offer new possibilities to study the adaptation of Ectocarpus to low salinity and its interactions with its microbiome.

The genome of Ectocarpus subulatus - A highly stress-tolerant brown alga.

Brown algae are multicellular photosynthetic stramenopiles that colonize marine rocky shores worldwide. Ectocarpus sp. Ec32 has been established as a genomic model for brown algae. Here we present the genome and metabolic network of the closely related species, Ectocarpus subulatus Kützing, which is characterized by high abiotic stress tolerance. Since their separation, both strains show new traces of viral sequences and the activity of large retrotransposons, which may also be related to the expansion of a family of chlorophyll-binding proteins. Further features suspected to contribute to stress tolerance include an expanded family of heat shock proteins, the reduction of genes involved in the production of halogenated defence compounds, and the presence of fewer cell wall polysaccharide-modifying enzymes. Overall, E. subulatus has mainly lost members of gene families down-regulated in low salinities, and conserved those that were up-regulated in the same condition. However, 96% of genes that differed between the two examined Ectocarpus species, as well as all genes under positive selection, were found to encode proteins of unknown function. This underlines the uniqueness of brown algal stress tolerance mechanisms as well as the significance of establishing E. subulatus as a comparative model for future functional studies.

Genome Sequences of 72 Bacterial Strains Isolated from Ectocarpus subulatus: A Resource for Algal Microbiology.

Brown algae are important primary producers and ecosystem engineers in the ocean, and Ectocarpus has been established as a laboratory model for this lineage. Like most multicellular organisms, Ectocarpus is associated with a community of microorganisms, a partnership frequently referred to as holobiont due to the tight interconnections between the components. Although genomic resources for the algal host are well established, its associated microbiome is poorly characterized from a genomic point of view, limiting the possibilities of using these types of data to study host-microbe interactions. To address this gap in knowledge, we present the annotated draft genome sequences of seventy-two cultivable Ectocarpus-associated bacteria. A screening of gene clusters related to the production of secondary metabolites revealed terpene, bacteriocin, NRPS, PKS-t3, siderophore, PKS-t1, and homoserine lactone clusters to be abundant among the sequenced genomes. These compounds may be used by the bacteria to communicate with the host and other microbes. Moreover, detoxification and provision of vitamin B pathways have been observed in most sequenced genomes, highlighting potential contributions of the bacterial metabolism toward host fitness and survival. The genomes sequenced in this study form a valuable resource for comparative genomic analyses and evolutionary surveys of alga-associated bacteria. They help establish Ectocarpus as a model for brown algal holobionts and will enable the research community to produce testable hypotheses about the molecular interactions within this complex system.

Evaluation of a new primer combination to minimize plastid contamination in 16S rDNA metabarcoding analyses of alga-associated bacterial communities.

Plant- and alga-associated bacterial communities are generally described via 16S rDNA metabarcoding using universal primers. As plastid genomes encode 16S rDNA related to cyanobacteria, these data sets frequently contain >90% plastidial sequences, and the bacterial diversity may be under-sampled. To overcome this limitation we evaluated in silico the taxonomic coverage for four primer combinations targeting the 16S rDNA V3-V4 region. They included a forward primer universal to Bacteria (S-D-Bact-0341-b-S-17) and four reverse primers designed to avoid plastid DNA amplification. The best primer combination (NOCHL) was compared to the universal primer set in the wet lab using a synthetic community and samples from three macroalgal species. The proportion of plastid sequences was reduced by 99%-100% with the NOCHL primers compared to the universal primers, irrespective of algal hosts, sample collection and extraction protocols. Additionally, the NOCHL primers yielded a higher richness while maintaining the community structure. As Planctomycetes, Verrucomicrobia and Cyanobacteria were underrepresented (70%-90%) compared to universal primers, combining the NOCHL set with taxon-specific primers may be useful for a complete description of the alga-associated bacterial diversity. The NOCHL primers represent an innovation to study algal holobionts without amplifying host plastid sequences and may further be applied to other photosynthetic hosts.

Genome-Scale Metabolic Networks Shed Light on the Carotenoid Biosynthesis Pathway in the Brown Algae Saccharina japonica and Cladosiphon okamuranus.

Understanding growth mechanisms in brown algae is a current scientific and economic challenge that can benefit from the modeling of their metabolic networks. The sequencing of the genomes of Saccharina japonica and Cladosiphon okamuranus has provided the necessary data for the reconstruction of Genome-Scale Metabolic Networks (GSMNs). The same in silico method deployed for the GSMN reconstruction of Ectocarpus siliculosus to investigate the metabolic capabilities of these two algae, was used. Integrating metabolic profiling data from the literature, we provided functional GSMNs composed of an average of 2230 metabolites and 3370 reactions. Based on these GSMNs and previously published work, we propose a model for the biosynthetic pathways of the main carotenoids in these two algae. We highlight, on the one hand, the reactions and enzymes that have been preserved through evolution and, on the other hand, the specificities related to brown algae. Our data further indicate that, if abscisic acid is produced by Saccharina japonica, its biosynthesis pathway seems to be different in its final steps from that described in land plants. Thus, our work illustrates the potential of GSMNs reconstructions for formalizing hypotheses that can be further tested using targeted biochemical approaches.

Seasonal and algal diet-driven patterns of the digestive microbiota of the European abalone Haliotis tuberculata, a generalist marine herbivore.

BACKGROUND: Holobionts have a digestive microbiota with catabolic abilities allowing the degradation of complex dietary compounds for the host. In terrestrial herbivores, the digestive microbiota is known to degrade complex polysaccharides from land plants while in marine herbivores, the digestive microbiota is poorly characterized. Most of the latter are generalists and consume red, green, and brown macroalgae, three distinct lineages characterized by a specific composition in complex polysaccharides, which represent half of their biomass. Subsequently, each macroalga features a specific epiphytic microbiota, and the digestive microbiota of marine herbivores is expected to vary with a monospecific algal diet. We investigated the effect of four monospecific diets (Palmaria palmata, Ulva lactuca, Saccharina latissima, Laminaria digitata) on the composition and specificity of the digestive microbiota of a generalist marine herbivore, the abalone, farmed in a temperate coastal area over a year. The microbiota from the abalone digestive gland was sampled every 2 months and explored using metabarcoding. RESULTS: Diversity and multivariate analyses showed that patterns of the microbiota were significantly linked to seasonal variations of contextual parameters but not directly to a specific algal diet. Three core genera: Psychrilyobacter, Mycoplasma, and Vibrio constantly dominated the microbiota in the abalone digestive gland. Additionally, a less abundant and diet-specific core microbiota featured genera representing aerobic primary degraders of algal polysaccharides. CONCLUSIONS: This study highlights the establishment of a persistent core microbiota in the digestive gland of the abalone since its juvenile state and the presence of a less abundant and diet-specific core community. While composed of different microbial taxa compared to terrestrial herbivores, the digestive gland constitutes a particular niche in the abalone holobiont, where bacteria (i) may cooperate to degrade algal polysaccharides to products assimilable by the host or (ii) may have acquired these functions through gene transfer from the aerobic algal microbiota.

Evolution and Expansion of the Prokaryote-Like Lipoxygenase Family in the Brown Alga Saccharina japonica.

Lipoxygenase (LOX) plays important roles in fatty acid oxidation and lipid mediator biosynthesis. In this study, we give first insights into brown algal LOX evolution. Whole genome searches revealed four, three, and eleven LOXs in Ectocarpus siliculosus, Cladosiphon okamuranus, and Saccharina japonica, respectively. In phylogenetic analyses, LOXs from brown algae form a robust clade with those from prokaryotes, suggesting an ancestral origin and slow evolution. Brown algal LOXs were divided into two clades, C1 and C2 in a phylogenetic tree. Compared to the two species of Ectocarpales, LOX gene expansion occurred in the kelp S. japonica through tandem duplication and segmental duplication. Selection pressure analysis showed that LOX genes in brown algae have undergone strong purifying selection, while the selective constraint in the C2 clade was more relaxed than that in the C1 clade. Furthermore, within each clade, LOXs of S. japonica evolved under more relaxed selection constraints than E. siliculosus and C. okamuranus. Structural modeling showed that unlike LOXs of plants and animals, which contain a ß barrel in the N-terminal part of the protein, LOXs in brown algae fold into a single domain. Analysis of previously published transcriptomic data showed that LOXs in E. siliculosus are responsive to hyposaline, hypersaline, oxidative, and copper stresses. Moreover, clear divergence of expression patterns was observed among different life stages, as well as between duplicate gene pairs. In E. siliculosus, all four LOXs are male-biased in immature gametophytes, and mature gametophytes showed significantly higher LOX mRNA levels than immature gametophytes and sporophytes. In S. japonica, however, our RNA-Seq data showed that most LOXs are highly expressed in sporophytes. Even the most recently duplicated gene pairs showed divergent expression patterns, suggesting that functional divergence has likely occurred since LOX genes duplicated, which potentially contributes to the production of various oxylipins in brown algae.

Detection of bacterial contaminants and hybrid sequences in the genome of the kelp Saccharina japonica using Taxoblast.

Modern genome sequencing strategies are highly sensitive to contamination making the detection of foreign DNA sequences an important part of analysis pipelines. Here we use Taxoblast, a simple pipeline with a graphical user interface, for the post-assembly detection of contaminating sequences in the published genome of the kelp Saccharina japonica. Analyses were based on multiple blastn searches with short sequence fragments. They revealed a number of probable bacterial contaminations as well as hybrid scaffolds that contain both bacterial and algal sequences. This or similar types of analysis, in combination with manual curation, may thus constitute a useful complement to standard bioinformatics analyses prior to submission of genomic data to public repositories. Our analysis pipeline is open-source and freely available at http://sdittami.altervista.org/taxoblast and via SourceForge (https://sourceforge.net/projects/taxoblast).

Insights into the red algae and eukaryotic evolution from the genome of Porphyra umbilicalis (Bangiophyceae, Rhodophyta).

Porphyra umbilicalis (laver) belongs to an ancient group of red algae (Bangiophyceae), is harvested for human food, and thrives in the harsh conditions of the upper intertidal zone. Here we present the 87.7-Mbp haploid Porphyra genome (65.8% G + C content, 13,125 gene loci) and elucidate traits that inform our understanding of the biology of red algae as one of the few multicellular eukaryotic lineages. Novel features of the Porphyra genome shared by other red algae relate to the cytoskeleton, calcium signaling, the cell cycle, and stress-tolerance mechanisms including photoprotection. Cytoskeletal motor proteins in Porphyra are restricted to a small set of kinesins that appear to be the only universal cytoskeletal motors within the red algae. Dynein motors are absent, and most red algae, including Porphyra, lack myosin. This surprisingly minimal cytoskeleton offers a potential explanation for why red algal cells and multicellular structures are more limited in size than in most multicellular lineages. Additional discoveries further relating to the stress tolerance of bangiophytes include ancestral enzymes for sulfation of the hydrophilic galactan-rich cell wall, evidence for mannan synthesis that originated before the divergence of green and red algae, and a high capacity for nutrient uptake. Our analyses provide a comprehensive understanding of the red algae, which are both commercially important and have played a major role in the evolution of other algal groups through secondary endosymbioses.