Generalized Coefficients for Hopf Cyclic Cohomology

A category of coefficients for Hopf cyclic cohomology is defined. It is shown that this category has two proper subcategories of which the smallest one is the known category of stable anti Yetter-Drinfeld modules. The middle subcategory is comprised of those coefficients which satisfy a generalized SAYD condition depending on both the Hopf algebra and the (co)algebra in question. Some examples are introduced to show that these three categories are different. It is shown that all components of Hopf cyclic cohomology work well with the new coefficients we have defined

Integrating pH into the metabolic theory of ecology to predict bacterial diversity in soil

Microorganisms play essential roles in soil ecosystem functioning and maintenance, but methods are currently lacking for quantitative assessments of the mechanisms underly-ing microbial diversity patterns observed across disparate systems and scales. Here we established a quantitative model to incorporate pH into metabolic theory to capture and explain some of the unexplained variation in the relationship between temperature and soil bacterial diversity. We then tested and validated our newly developed models across multiple scales of ecological organization. At the species level, we modeled the diversification rate of the model bacterium Pseudomonas fluorescens evolving under laboratory media gradients varying in temperature and pH. At the community level, we modeled patterns of bacterial communities in paddy soils across a continental scale, which included natural gradients of pH and temperature. Last, we further extended our model at a global scale by integrating a meta-analysis comprising 870 soils collected worldwide from a wide range of ecosystems. Our results were robust in consistently predicting the distributional patterns of bacterial diversity across soil temperature and pH gradients-with model variation explaining from 7 to 66% of the variation in bacterial diversity, depending on the scale and system complexity. Together, our study represents a nexus point for the integration of soil bacterial diversity and quantitative models with the potential to be used at distinct spatiotemporal scales. By mechanisti-cally representing pH into metabolic theory, our study enhances our capacity to explain and predict the patterns of bacterial diversity and functioning under current or future climate change scenarios

Connecting the multiple dimensions of global soil fungal diversity

How the multiple facets of soil fungal diversity vary worldwide remains virtually unknown, hindering the management of this essential species-rich group. By sequencing high-resolution DNA markers in over 4000 topsoil samples from natural and human-altered ecosystems across all continents, we illustrate the distributions and drivers of different levels of taxonomic and phylogenetic diversity of fungi and their ecological groups. We show the impact of precipitation and temperature interactions on local fungal species richness (alpha diversity) across different climates. Our findings reveal how temperature drives fungal compositional turnover (beta diversity) and phylogenetic diversity, linking them with regional species richness (gamma diversity). We integrate fungi into the principles of global biodiversity distribution and present detailed maps for biodiversity conservation and modeling of global ecological processes

Impact of hurricane disturbance on mycorrhizal co-occurrence networks: Resilience and community dynamics in the Neotropics

Extreme climatic events and related disturbances such as hurricanes are increasingly altering forest ecosystems. How these events impact forest fungal communities is poorly characterized. We examined the effect of a hurricane on mycorrhizal community structure and potential interspecific fungal interactions, inferred from OTU co-occurrences. We characterized the root fungal communities of dual-mycorrhizal plants from nine plots during two consecutive years after a category four hurricane impacted the coastal Mexican Pacific tropical forest in Jalisco. Presence-abundance matrices were used to calculate properties of mycorrhizal networks including nestedness and modularity, and to infer patterns of co-occurrence. One year after the hurricane there was a loss of links between plants and fungi. Increased network modularity and connectivity were observed after two years. We also found that disturbance changed arbuscular mycorrhizal fungal network structure more strongly than ectomycorrhizal fungal networks. Fungal guilds changed their putative interspecific interactions, from mutual exclusion in the first year to a significant increase in co-occurrence of plant pathogens, saprotrophs, and endophytes in the second year. Our results suggest that in the short term, rhizospheric interactions can be resilient to hurricanes, but fungal guilds may have divergent responses

EUKARYOME: the rRNA gene reference database for identification of all eukaryotes

Molecular identification of micro- and macroorganisms based on nuclear markers has revolutionized our understanding of their taxonomy, phylogeny and ecology. Today, research on the diversity of eukaryotes in global ecosystems heavily relies on nuclear ribosomal RNA (rRNA) markers. Here, we present the research community-curated reference database EUKARYOME for nuclear ribosomal 18S rRNA, internal transcribed spacer (ITS) and 28S rRNA markers for all eukaryotes, including metazoans (animals), protists, fungi and plants. It is particularly useful for the identification of arbuscular mycorrhizal fungi as it bridges the four commonly used molecular markers-ITS1, ITS2, 18S V4-V5 and 28S D1-D2 subregions. The key benefits of this database over other annotated reference sequence databases are that it is not restricted to certain taxonomic groups and it includes all rRNA markers. EUKARYOME also offers a number of reference long-read sequences that are derived from (meta)genomic and (meta)barcoding-a unique feature that can be used for taxonomic identification and chimera control of third-generation, long-read, high-throughput sequencing data. Taxonomic assignments of rRNA genes in the database are verified based on phylogenetic approaches. The reference datasets are available in multiple formats from the project homepage, http://www.eukaryome.org