Beyond pathogenesis: Detecting the full spectrum of ecological interactions in the virosphere.

The public perception of viruses has historically been negative. We are now at a stage where the development of tools to study viruses is at an all-time high, but society's perception of viruses is at an all-time low. The literature regarding viral interactions has been skewed towards negative (i.e., pathogenic) symbioses, whereas viral mutualisms remain relatively underexplored. Viral interactions with their hosts are complex and some non-pathogenic viruses could have potential benefits to society. However, viral research is seldom designed to identify viral mutualists, a gap that merits considering new experimental designs. Determining whether antagonisms, mutualisms, and commensalisms are equally common ecological strategies requires more balanced research efforts that characterize the full spectrum of viral interactions.

Methodological Approaches Frame Insights into Endophyte Richness and Community Composition.

Isolating microbes is vital to study microbiomes, but insights into microbial diversity and ecology can be constrained by recalcitrant or unculturable strains. Culture-free methods (e.g., next-generation sequencing, NGS) have become popular in part because they detect greater richness than culturing alone. Both approaches are used widely to characterize microfungi within healthy leaves (foliar endophytes), but methodological differences among studies can constrain large-scale insights into endophyte ecology. We examined endophytes in a temperate plant community to quantify how certain methodological factors, such as the choice of cultivation media for culturing and storage period after leaf collection, affect inferences regarding endophyte communities; how such effects vary among plant taxa; and how complementary culturing and NGS can be when subsets of the same plant tissue are used for each. We found that endophyte richness and composition from culturing were consistent across five media types. Insights from culturing and NGS were largely robust to differences in storage period (1, 5, and 10 days). Although endophyte richness, composition, and taxonomic diversity identified via culturing vs. NGS differed markedly, both methods revealed host-structured communities. Studies differing only in cultivation media or storage period thus can be compared to estimate endophyte richness, composition, and turnover at scales larger than those of individual studies alone. Our data show that it is likely more important to sample more host species, rather than sampling fewer species more intensively, to quantify endophyte diversity in given locations, with the richest insights into endophyte ecology emerging when culturing and NGS are paired.

Symbiosis and the Anthropocene.

Recent human activity has profoundly transformed Earth biomes on a scale and at rates that are unprecedented. Given the central role of symbioses in ecosystem processes, functions, and services throughout the Earth biosphere, the impacts of human-driven change on symbioses are critical to understand. Symbioses are not merely collections of organisms, but co-evolved partners that arise from the synergistic combination and action of different genetic programs. They function with varying degrees of permanence and selection as emergent units with substantial potential for combinatorial and evolutionary innovation in both structure and function. Following an articulation of operational definitions of symbiosis and related concepts and characteristics of the Anthropocene, we outline a basic typology of anthropogenic change (AC) and a conceptual framework for how AC might mechanistically impact symbioses with select case examples to highlight our perspective. We discuss surprising connections between symbiosis and the Anthropocene, suggesting ways in which new symbioses could arise due to AC, how symbioses could be agents of ecosystem change, and how symbioses, broadly defined, of humans and "farmed" organisms may have launched the Anthropocene. We conclude with reflections on the robustness of symbioses to AC and our perspective on the importance of symbioses as ecosystem keystones and the need to tackle anthropogenic challenges as wise and humble stewards embedded within the system.

Whole-Genome Resequencing Reveals Extensive Natural Variation in the Model Green Alga Chlamydomonas reinhardtii.

We performed whole-genome resequencing of 12 field isolates and eight commonly studied laboratory strains of the model organism Chlamydomonas reinhardtii to characterize genomic diversity and provide a resource for studies of natural variation. Our data support previous observations that Chlamydomonas is among the most diverse eukaryotic species. Nucleotide diversity is ∼3% and is geographically structured in North America with some evidence of admixture among sampling locales. Examination of predicted loss-of-function mutations in field isolates indicates conservation of genes associated with core cellular functions, while genes in large gene families and poorly characterized genes show a greater incidence of major effect mutations. De novo assembly of unmapped reads recovered genes in the field isolates that are absent from the CC-503 assembly. The laboratory reference strains show a genomic pattern of polymorphism consistent with their origin as the recombinant progeny of a diploid zygospore. Large duplications or amplifications are a prominent feature of laboratory strains and appear to have originated under laboratory culture. Extensive natural variation offers a new source of genetic diversity for studies of Chlamydomonas, including naturally occurring alleles that may prove useful in studies of gene function and the dissection of quantitative genetic traits.

Genetic evidence for algal auxin production in Chlamydomonas and its role in algal-bacterial mutualism.

Interactions between algae and bacteria are ubiquitous and play fundamental roles in nutrient cycling and biomass production. Recent studies have shown that the plant auxin indole acetic acid (IAA) can mediate chemical crosstalk between algae and bacteria, resembling its role in plant-bacterial associations. Here, we report a mechanism for algal extracellular IAA production from L-tryptophan mediated by the enzyme L-amino acid oxidase (LAO1) in the model Chlamydomonas reinhardtii. High levels of IAA inhibit algal cell multiplication and chlorophyll degradation, and these inhibitory effects can be relieved by the presence of the plant-growth-promoting bacterium (PGPB) Methylobacterium aquaticum, whose growth is mutualistically enhanced by the presence of the alga. These findings reveal a complex interplay of microbial auxin production and degradation by algal-bacterial consortia and draws attention to potential ecophysiological roles of terrestrial microalgae and PGPB in association with land plants.

Whole community shotgun metagenomes of two biological soil crust types from the Mojave Desert.

We present six whole community shotgun metagenomic sequencing data sets of two types of biological soil crusts sampled at the ecotone of the Mojave Desert and Colorado Desert in California. These data will help us understand the diversity and function of biocrust microbial communities, which are essential for desert ecosystems.

Metatranscriptomes of two biological soil crust types from the Mojave desert in response to wetting.

We present eight metatranscriptomic datasets of light algal and cyanolichen biological soil crusts from the Mojave Desert in response to wetting. These data will help us understand gene expression patterns in desert biocrust microbial communities after they have been reactivated by the addition of water.

Mutualism-enhancing mutations dominate early adaptation in a two-species microbial community.

Species interactions drive evolution while evolution shapes these interactions. The resulting eco-evolutionary dynamics and their repeatability depend on how adaptive mutations available to community members affect fitness and ecologically relevant traits. However, the diversity of adaptive mutations is not well characterized, and we do not know how this diversity is affected by the ecological milieu. Here we use barcode lineage tracking to address this question in a community of yeast Saccharomyces cerevisiae and alga Chlamydomonas reinhardtii that have a net commensal relationship that results from a balance between competitive and mutualistic interactions. We find that yeast has access to many adaptive mutations with diverse ecological consequences, in particular those that increase and reduce the yields of both species. The presence of the alga does not change which mutations are adaptive in yeast (that is, there is no fitness trade-off for yeast between growing alone or with alga), but rather shifts selection to favour yeast mutants that increase the yields of both species and make the mutualism stronger. Thus, in the presence of the alga, adaptative mutations contending for fixation in yeast are more likely to enhance the mutualism, even though cooperativity is not directly favoured by natural selection in our system. Our results demonstrate that ecological interactions not only alter the trajectory of evolution but also dictate its repeatability; in particular, weak mutualisms can repeatably evolve to become stronger.

Metabolic network analysis integrated with transcript verification for sequenced genomes.

With sequencing of thousands of organisms completed or in progress, there is a growing need to integrate gene prediction with metabolic network analysis. Using Chlamydomonas reinhardtii as a model, we describe a systems-level methodology bridging metabolic network reconstruction with experimental verification of enzyme encoding open reading frames. Our quantitative and predictive metabolic model and its associated cloned open reading frames provide useful resources for metabolic engineering.

Metabolic network reconstruction of Chlamydomonas offers insight into light-driven algal metabolism.

Metabolic network reconstruction encompasses existing knowledge about an organism's metabolism and genome annotation, providing a platform for omics data analysis and phenotype prediction. The model alga Chlamydomonas reinhardtii is employed to study diverse biological processes from photosynthesis to phototaxis. Recent heightened interest in this species results from an international movement to develop algal biofuels. Integrating biological and optical data, we reconstructed a genome-scale metabolic network for this alga and devised a novel light-modeling approach that enables quantitative growth prediction for a given light source, resolving wavelength and photon flux. We experimentally verified transcripts accounted for in the network and physiologically validated model function through simulation and generation of new experimental growth data, providing high confidence in network contents and predictive applications. The network offers insight into algal metabolism and potential for genetic engineering and efficient light source design, a pioneering resource for studying light-driven metabolism and quantitative systems biology.

The community ecology perspective of omics data.

The measurement of uncharacterized pools of biological molecules through techniques such as metabarcoding, metagenomics, metatranscriptomics, metabolomics, and metaproteomics produces large, multivariate datasets. Analyses of these datasets have successfully been borrowed from community ecology to characterize the molecular diversity of samples (ɑ-diversity) and to assess how these profiles change in response to experimental treatments or across gradients (ß-diversity). However, sample preparation and data collection methods generate biases and noise which confound molecular diversity estimates and require special attention. Here, we examine how technical biases and noise that are introduced into multivariate molecular data affect the estimation of the components of diversity (i.e., total number of different molecular species, or entities; total number of molecules; and the abundance distribution of molecular entities). We then explore under which conditions these biases affect the measurement of ɑ- and ß-diversity and highlight how novel methods commonly used in community ecology can be adopted to improve the interpretation and integration of multivariate molecular data. Video Abstract.

Concerted action of the new Genomic Peptide Finder and AUGUSTUS allows for automated proteogenomic annotation of the Chlamydomonas reinhardtii genome.

The use and development of post-genomic tools naturally depends on large-scale genome sequencing projects. The usefulness of post-genomic applications is dependent on the accuracy of genome annotations, for which the correct identification of intron-exon borders in complex genomes of eukaryotic organisms is often an error-prone task. Although automated algorithms for predicting intron-exon structures are available, supporting exon evidence is necessary to achieve comprehensive genome annotation. Besides cDNA and EST support, peptides identified via MS/MS can be used as extrinsic evidence in a proteogenomic approach. We describe an improved version of the Genomic Peptide Finder (GPF), which aligns de novo predicted amino acid sequences to the genomic DNA sequence of an organism while correcting for peptide sequencing errors and accounting for the possibility of splicing. We have coupled GPF and the gene finding program AUGUSTUS in a way that provides automatic structural annotations of the Chlamydomonas reinhardtii genome, using highly unbiased GPF evidence. A comparison of the AUGUSTUS gene set incorporating GPF evidence to the standard JGI FM4 (Filtered Models 4) gene set reveals 932 GPF peptides that are not contained in the Filtered Models 4 gene set. Furthermore, the GPF evidence improved the AUGUSTUS gene models by altering 65 gene models and adding three previously unidentified genes.

On the move: sloths and their epibionts as model mobile ecosystems.

Sloths are unusual mobile ecosystems, containing a high diversity of epibionts living and growing in their fur as they climb slowly through the canopies of tropical forests. These epibionts include poorly studied algae, arthropods, fungi, and bacteria, making sloths likely reservoirs of unexplored biodiversity. This review aims to identify gaps and eliminate misconceptions in our knowledge of sloths and their epibionts, and to identify key questions to stimulate future research into the functions and roles of sloths within a broader ecological and evolutionary context. This review also seeks to position the sloth fur ecosystem as a model for addressing fundamental questions in metacommunity and movement ecology. The conceptual and evidence-based foundation of this review aims to serve as a guide for future hypothesis-driven research into sloths, their microbiota, sloth health and conservation, and the coevolution of symbioses in general.

Towards a Systems Biology Approach to Understanding the Lichen Symbiosis: Opportunities and Challenges of Implementing Network Modelling.

Lichen associations, a classic model for successful and sustainable interactions between micro-organisms, have been studied for many years. However, there are significant gaps in our understanding about how the lichen symbiosis operates at the molecular level. This review addresses opportunities for expanding current knowledge on signalling and metabolic interplays in the lichen symbiosis using the tools and approaches of systems biology, particularly network modelling. The largely unexplored nature of symbiont recognition and metabolic interdependency in lichens could benefit from applying a holistic approach to understand underlying molecular mechanisms and processes. Together with 'omics' approaches, the application of signalling and metabolic network modelling could provide predictive means to gain insights into lichen signalling and metabolic pathways. First, we review the major signalling and recognition modalities in the lichen symbioses studied to date, and then describe how modelling signalling networks could enhance our understanding of symbiont recognition, particularly leveraging omics techniques. Next, we highlight the current state of knowledge on lichen metabolism. We also discuss metabolic network modelling as a tool to simulate flux distribution in lichen metabolic pathways and to analyse the co-dependence between symbionts. This is especially important given the growing number of lichen genomes now available and improved computational tools for reconstructing such models. We highlight the benefits and possible bottlenecks for implementing different types of network models as applied to the study of lichens.

Climate and seasonality drive the richness and composition of tropical fungal endophytes at a landscape scale.

Understanding how species-rich communities persist is a foundational question in ecology. In tropical forests, tree diversity is structured by edaphic factors, climate, and biotic interactions, with seasonality playing an essential role at landscape scales: wetter and less seasonal forests typically harbor higher tree diversity than more seasonal forests. We posited that the abiotic factors shaping tree diversity extend to hyperdiverse symbionts in leaves-fungal endophytes-that influence plant health, function, and resilience to stress. Through surveys in forests across Panama that considered climate, seasonality, and covarying biotic factors, we demonstrate that endophyte richness varies negatively with temperature seasonality. Endophyte community structure and taxonomic composition reflect both temperature seasonality and climate (mean annual temperature and precipitation). Overall our findings highlight the vital role of climate-related factors in shaping the hyperdiversity of these important and little-known symbionts of the trees that, in turn, form the foundations of tropical forest biodiversity.

Fungi in the Marine Environment: Open Questions and Unsolved Problems.

Terrestrial fungi play critical roles in nutrient cycling and food webs and can shape macroorganism communities as parasites and mutualists. Although estimates for the number of fungal species on the planet range from 1.5 to over 5 million, likely fewer than 10% of fungi have been identified so far. To date, a relatively small percentage of described species are associated with marine environments, with ∼1,100 species retrieved exclusively from the marine environment. Nevertheless, fungi have been found in nearly every marine habitat explored, from the surface of the ocean to kilometers below ocean sediments. Fungi are hypothesized to contribute to phytoplankton population cycles and the biological carbon pump and are active in the chemistry of marine sediments. Many fungi have been identified as commensals or pathogens of marine animals (e.g., corals and sponges), plants, and algae. Despite their varied roles, remarkably little is known about the diversity of this major branch of eukaryotic life in marine ecosystems or their ecological functions. This perspective emerges from a Marine Fungi Workshop held in May 2018 at the Marine Biological Laboratory in Woods Hole, MA. We present the state of knowledge as well as the multitude of open questions regarding the diversity and function of fungi in the marine biosphere and geochemical cycles.

OK, thanks! A new mutualism between Chlamydomonas and methylobacteria facilitates growth on amino acids and peptides.

Nitrogen is a key nutrient for land plants and phytoplankton in terrestrial and aquatic ecosystems. The model alga Chlamydomonas reinhardtii can grow efficiently on several inorganic nitrogen sources (e.g. ammonium, nitrate, nitrite) as well as many amino acids. In this study, we show that Chlamydomonas is unable to use proline, hydroxyproline and peptides that contain these amino acids. However, we discovered that algal growth on these substrates is supported in association with Methylobacterium spp., and that a mutualistic carbon-nitrogen metabolic exchange between Chlamydomonas and Methylobacterium spp. is established. Specifically, the mineralization of these amino acids and peptides by Methylobacterium spp. produces ammonium that can be assimilated by Chlamydomonas, and CO2 photosynthetically fixed by Chlamydomonas yields glycerol that can be assimilated by Methylobacterium. As Chlamydomonas is an algal ancestor to land plants and Methylobacterium is a plant growth-promoting bacterium, this new model of mutualism may facilitate insights into the ecology and evolution of plant-bacterial interactions and design principles of synthetic ecology.

Fluorescence correlation spectroscopy simulations of photophysical phenomena and molecular interactions: a molecular dynamics/monte carlo approach.

Fluorescence correlation spectroscopy (FCS) is being applied increasingly to study diffusion and interactions of fluorescently labeled macromolecules in complex biological systems. Fluctuations in detected fluorescence, deltaF(t), are expressed as time-correlation functions, G(tau), and photon-count histograms, P(k;DeltaT). Here, we developed a generalized simulation approach to compute G(tau) and P(k;DeltaT) for complex systems with arbitrary geometry, photophysics, diffusion, and macromolecular interactions. G(tau) and P(k;DeltaT) were computed from deltaF(t) generated by a Brownian dynamics simulation of single-molecule trajectories followed by a Monte Carlo simulation of fluorophore excitation and detection statistics. Simulations were validated by comparing analytical and simulated G(tau) and P(k;DeltaT) for diffusion of noninteracting fluorophores in a three-dimensional Gaussian excitation and detection volume. Inclusion of photobleaching and triplet-state relaxation produced significant changes in G(tau) and P(k;DeltaT). Simulations of macromolecular interactions and complex diffusion were done, including transient fluorophore binding to an immobile matrix, cross-correlation analysis of interacting fluorophores, and anomalous sub- and superdiffusion. The computational method developed here is generally applicable for simulating FCS measurements on systems complicated by fluorophore interactions or molecular crowding, and experimental protocols for which G(tau) and P(k;DeltaT) cannot be computed analytically.

A Chemical Perspective on Microalgal-Microbial Interactions.

The exchange of chemical compounds is central to the interactions of microalgae with other microorganisms. Although foundational for many food webs, these interactions have been poorly studied compared with higher plant-microbe interactions. Emerging insights have begun to reveal how these interactions and the participating chemical compounds shape microbial communities and broadly impact biogeochemical processes.

Plant-fungal ecology. Niche engineering demonstrates a latent capacity for fungal-algal mutualism.

Mutualistic symbioses shape the evolution of species and ecosystems and catalyze the emergence of biological complexity, yet how such symbioses first form is unclear. We show that an obligate mutualism between the yeast Saccharomyces cerevisiae and the alga Chlamydomonas reinhardtii--two model eukaryotes with very different life histories--can arise spontaneously in an environment requiring reciprocal carbon and nitrogen exchange. This capacity for mutualism is phylogenetically broad, extending to other Chlamydomonas and fungal species. Furthermore, we witnessed the spontaneous association of Chlamydomonas algal cells physically interacting with filamentous fungi. These observations demonstrate that under specific conditions, environmental change induces free-living species to become obligate mutualists and establishes a set of experimentally tractable, phylogenetically related, synthetic systems for studying the evolution of symbiosis.