Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “diversion”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,369 records · Page 76

Using high-throughput amplicon sequencing to determine diet of generalist lady beetles in agricultural landscapes

Determining feeding relationships is central to understanding biological control potential in the field. However, methods to differentiate actual (or realized) feeding relationships from potential feeding relationships is lacking especially for small, generalist predators such as lady beetles. In this study, we used DNA metabarcoding approaches to characterize actual feeding relationships of lady beetles (Coccinellidae) in the field and validated our methods with a lab study. We first asked whether high-throughput amplicon sequencing (HTS) can characterize diets of lady beetles ranging from monotypic diets to diverse diet mixtures in the lab. We then examined whether diet composition and breadth of lady beetles collected from different habitat types in southern WI varied between monocultures of soybean and corn, diverse tallgrass prairie, and urban habitats. Lastly, we asked whether different body or tissue types (partial-body versus whole-body specimens) would change the likelihood of prey detection for both studies. In our controlled lab study, we found that HTS can accurately assess diet composition and diet breadth for lady beetle populations, but at the individual level, HTS has limitation for individuals feeding on more than three species of prey at any given time. In our field study, we documented lower prey richness and diet breadth in corn compared to soybean and grassland, and greater prey DNA in regurgitants than in whole-body specimens. Finally, we found that reduced diet diversity was associated with an increased prevalence of intraguild predation, but that habitat and prey diversity are not necessarily correlated. The prey detection rates (proportion of specimens with prey DNA) in our study were comparable to other studies (55% in the lab study, 33% in field study) and varied with diet composition and habitat type. Furthermore, the relatively low detection rates suggest that many consumer individuals would need to be assayed to fully assess diet diversity, especially in diverse systems.

59 BASIC BIOLOGICAL SCIENCES↗

Determining the Reliability of Measuring Mercury Cycling Gene Abundance with Correlations with Mercury and Methylmercury Concentrations

Methylmercury (MeHg) is a bioaccumulative toxic contaminant in many ecosystems but factors governing its production are poorly understood. Recent work has shown that the anaerobic microbial conversion of mercury (Hg) to MeHg requires the Hg-methylation genes hgcAB and that these genes can be used as biomarkers in PCR-based estimators of Hg-methylator abundance. In an effort to determine reliable methods for assessing hgcA abundance and diversity and linking it to MeHg concentrations, multiple approaches were compared including metagenomic shotgun sequencing, 16S rRNA gene pyrosequencing and cloning/sequencing hgcAB gene products. Hg-methylator abundance was also determined by quantitative hgcA qPCR amplification and metaproteomics for comparison to the above measurements. Samples from eight Hg-contaminated sites were examined over a range of total Hg (HgT; 0.03–14 mg kg-1 wet wt. soil) and MeHg (0.05–27 µg kg-1 wet wt. soil) concentrations. In the metagenome and amplicon sequencing of hgcAB diversity, the Deltaproteobacteria were the dominant Hg-methylators, while Firmicutes and methanogenic Archaea were typically ~50% less abundant. This was consistent with metaproteomics estimates where the Deltaproteobacteria were consistently higher. The 16S rRNA gene pyrosequencing did not have sufficient resolution to identify hgcAB+ species. Metagenomic and hgcAB results were similar for Hg-methylator diversity and showed a tractable relationship between Hg-methylating bacteria and soil Hg concentrations among similar environmental samples. However, clade-specific qPCR-based approaches for hgcA are only appropriate when comparing the abundance of a particular clade across various samples.

59 BASIC BIOLOGICAL SCIENCES↗

CRAGE enables rapid activation of biosynthetic gene clusters in undomesticated bacteria

Advances in the prediction of biosynthetic gene clusters (BGCs) from genomic and metagenomic data have made the large-scale identification of candidate secondary metabolite biosynthesis pathways routine. However, most predicted BGCs cannot be successfully expressed in the limited range of expression hosts currently available, which prevents the identification and characterization of their respective products. Here we show that parallelized use of a phylogenetically and physiologically diverse panel of purpose-engineered chassis strains offers a versatile strategy for the rapid activation of BGCs. We domesticated an ensemble of 25 diverse ?-proteobacteria from 11 different genera by integrating a unified landing pad that enables efficient introduction of large BGCs into their genome. We deployed this chassis-independent recombinase-assisted genome engineering (CRAGE) strategy to express several previously posited but experimentally elusive non-ribosomal peptide synthase (NRPS) and NRPSpolyketide synthase (PKS) hybrid BGCs from Photorhabdus luminescens. Successful activation of 6 BGCs identified 21 products, including several with likely roles in host-microbe interactions. Taken together, we illustrate how the regulatory and physiological diversity naturally present across bacteria can be harnessed for the exploration of novel bioproducts and provide a sizable panel of domesticated chassis strains to enable this strategy.

applied microbiology, genetic engineering, industr↗

Spatial and temporal coevolution of N2 neuraminidase and H1 and H3 hemagglutinin genes of influenza A virus in US swine

Abstract The neuraminidase (NA) and hemagglutinin (HA) are essential surface glycoproteins of influenza A virus (IAV). In this study, the evolution of subtype N2 NA paired with H1 and H3 subtype HA in swine was evaluated to understand if the genetic diversity of HA and NA were linked. Using time-scaled Bayesian phylodynamic analyses, the relationships of paired swine N2 with H1 or H3 from 2009 to 2018 were evaluated. These data demonstrated increased relative genetic diversity within the major N2 clades circulating in swine in the USA (N2.1998 between 2014 and 2017 and N2.2002 between 2010 and 2016). Preferential pairing was observed among specific NA and HA genetic clades. Gene reassortment between cocirculating influenza A strains resulted in novel pairings that persisted. The changes in genetic diversity in the NA gene were quantified using Bayesian phylodynamic analyses, and increases in diversity were observed subsequent to novel NA–HA reassortment events. The rate of evolution among NA–N2 clades and HA–H1 and HA–H3 clades were similar. Bayesian phylodynamic analyses demonstrated strong spatial patterns in N2 genetic diversity, but frequent interstate movement of rare N2 clades provided opportunity for reassortment and emergence of new N2–HA pairings. The frequent regional movement of pigs and their influenza viruses is an explanation for the documented patterns of reassortment and subsequent changes in gene diversity. The reassortment and evolution of NA and linked HA evolution may result in antigenic drift of both major surface glycoproteins, reducing vaccine efficacy, with subsequent impact on animal health.

59 BASIC BIOLOGICAL SCIENCES↗

A trait-based framework for linking microbial communities with carbon transformations under precipitation change

Droughts are common throughout the world. As the climate changes, droughts may become more frequent and intense. Still, scientists are uncertain about how drought will affect the natural world, particularly the bacteria, fungi, and other microbes that live in soils. These tiny life forms are crucial because they control the Earth’s flows of carbon and essential nutrients. Researchers at the University of California, Irvine, and Lawrence Berkeley National Laboratory teamed up to study how the microbiome, or collection of bacteria and fungi in the soil, deals with drought. Since 2007, the researchers have used shelters with retractable roofs to prevent nearly half of normal rainfall from reaching grass and shrub ecosystems, and their soil microbiomes, in Southern California. The study team discovered that microbes have some clever tricks up their sleeve for surviving drought. When growing on dead grass as a food source, microbes ramp up production of specialized chemicals called osmolytes that keep their cells from drying out. But microbes growing on dead shrubs face another problem. Unlike grass, shrub leaves are a lousy food source. To digest and consume shrub leaves, microbes have to exude more enzymes, which act like biochemical chef knives that chop complex leaf molecules into bite-sized pieces. Carbon is the coin of the microbial realm, earned via enzyme action or slurping up dead plant juices. Microbes growing under normal conditions on tasty dead grass have it easy: they can spend most of their carbon currency on growth. With drought, life gets harder as microbes need to pay up for osmolytes and ramp down their growth. It gets worse with shrub leaves because microbes have to multi-task among growth, enzyme secretion, and osmolyte production. When drought hits, microbes on shrub leaves forgo the osmolytes, probably because losing the carbon revenue from enzyme investment would be a deal-breaker for survival. The next question tackled by the researchers asked how the genes controlling microbial lifestyles sort out across the tree of life. Most microbiologists thought these lifestyles would correspond to rather large branches on the tree. But the study team found that in fact, very closely related microbes differ in important and interesting ways. For example, bacteria that have nearly identical housekeeping genes respond distinctively to warming, rainfall, and plant chemistry. As a result, soil microbiomes are much richer in diversity than originally thought. And studying microbial diversity in much greater detail could open up many more possibilities for how microbial life deals with changing environmental conditions. Trying to understand microbial life without the fine details of genetic diversity is like trying to stream Netflix on a dial-up connection. By looking across the landscape, the researchers revealed that microbial diversity is absolutely critical for maintaining the planet’s flows of carbon and nutrients. The study team designed a new technology—microbial cages—for transplanting intact microbiomes. With the cages, the researchers could move microbiomes to novel environments and compare their ability to cycle carbon and nutrients. In some cases, performance tailed off when microbiomes found themselves in a new environment, but in other cases, performance rivaled or even exceeded that of the resident microbiome. And even the low performers eventually caught up to the native microbiomes if given sufficient time. These findings mean that microbiomes—at least in Southern California—may be resilient to climate shifts due to a high diversity of microbial lifestyles. Coping with heat and drought may literally be in their DNA. The last piece of the research puzzle, and a “Holy Grail” for microbial ecologists, is to forecast the behavior of diverse microbiomes. To meet this challenge, the study team developed new theory and computer models. For the first time, these models account for hundreds of different microbes and how their intricate lifestyles cope with drought. The models are starting to connect the tiniest microbes with the global cycles that sustain Earth’s farms, fields, and forests. With that connection, it will be easier for society to plan for a world with more droughts and other climate disruptions.

54 ENVIRONMENTAL SCIENCES↗

Multifunctional Collaborative Modeling and Analysis Methods in Engineering Science

Engineers are challenged to produce better designs in less time and for less cost. Hence, to investigate novel and revolutionary design concepts, accurate, high-fidelity results must be assimilated rapidly into the design, analysis, and simulation process. This assimilation should consider diverse mathematical modeling and multi-discipline interactions necessitated by concepts exploiting advanced materials and structures. Integrated high-fidelity methods with diverse engineering applications provide the enabling technologies to assimilate these high-fidelity, multi-disciplinary results rapidly at an early stage in the design. These integrated methods must be multifunctional, collaborative, and applicable to the general field of engineering science and mechanics. Multifunctional methodologies and analysis procedures are formulated for interfacing diverse subdomain idealizations including multi-fidelity modeling methods and multi-discipline analysis methods. These methods, based on the method of weighted residuals, ensure accurate compatibility of primary and secondary variables across the subdomain interfaces. Methods are developed using diverse mathematical modeling (i.e., finite difference and finite element methods) and multi-fidelity modeling among the subdomains. Several benchmark scalar-field and vector-field problems in engineering science are presented with extensions to multidisciplinary problems. Results for all problems presented are in overall good agreement with the exact analytical solution or the reference numerical solution. Based on the results, the integrated modeling approach using the finite element method for multi-fidelity discretization among the subdomains is identified as most robust. The multiple-method approach is advantageous when interfacing diverse disciplines in which each of the method's strengths are utilized. The multifunctional methodology presented provides an effective mechanism by which domains with diverse idealizations are interfaced. This capability rapidly provides the high-fidelity results needed in the early design phase. Moreover, the capability is applicable to the general field of engineering science and mechanics. Hence, it provides a collaborative capability that accounts for interactions among engineering analysis methods.

Ransom, Jonathan B.↗

Algorithms for Learning Preferences for Sets of Objects

A method is being developed that provides for an artificial-intelligence system to learn a user's preferences for sets of objects and to thereafter automatically select subsets of objects according to those preferences. The method was originally intended to enable automated selection, from among large sets of images acquired by instruments aboard spacecraft, of image subsets considered to be scientifically valuable enough to justify use of limited communication resources for transmission to Earth. The method is also applicable to other sets of objects: examples of sets of objects considered in the development of the method include food menus, radio-station music playlists, and assortments of colored blocks for creating mosaics. The method does not require the user to perform the often-difficult task of quantitatively specifying preferences; instead, the user provides examples of preferred sets of objects. This method goes beyond related prior artificial-intelligence methods for learning which individual items are preferred by the user: this method supports a concept of setbased preferences, which include not only preferences for individual items but also preferences regarding types and degrees of diversity of items in a set. Consideration of diversity in this method involves recognition that members of a set may interact with each other in the sense that when considered together, they may be regarded as being complementary, redundant, or incompatible to various degrees. The effects of such interactions are loosely summarized in the term portfolio effect. The learning method relies on a preference representation language, denoted DD-PREF, to express set-based preferences. In DD-PREF, a preference is represented by a tuple that includes quality (depth) functions to estimate how desired a specific value is, weights for each feature preference, the desired diversity of feature values, and the relative importance of diversity versus depth. The system applies statistical concepts to estimate quantitative measures of the user s preferences from training examples (preferred subsets) specified by the user. Once preferences have been learned, the system uses those preferences to select preferred subsets from new sets. The method was found to be viable when tested in computational experiments on menus, music playlists, and rover images. Contemplated future development efforts include further tests on more diverse sets and development of a sub-method for (a) estimating the parameter that represents the relative importance of diversity versus depth, and (b) incorporating background knowledge about the nature of quality functions, which are special functions that specify depth preferences for features.

Wagstaff, Kiri L.↗

Range wide genetic differentiation in the bull kelp Nereocystis luetkeana with a seascape genetic focus on the Salish Sea

Introduction: In temperate regions, one of the most critical determinants of present range-wide genetic diversity was the Pleistocene climate oscillations, the most recent one created by the last glacial maximum (LGM). This study aimed to describe N. luetkeana genetic structure across its entire range (Alaska to California) and test different models of population connectivity within the Salish Sea. This region was colonized after the LGM and has been under increased disturbance in recent decades. Methods: We utilized microsatellite markers to study N. luetkeana genetic diversity at 53 sites across its range. Using higher sampling density in the Salish Sea, we employed a seascape genetics approach and tested isolation by hydrodynamic transport and environment models. Results: At the species distribution scale, we found four main groups of genetic co-ancestry, Alaska; Washington with Vancouver Island’s outer coast and Juan de Fuca Strait; Washington’s inner Salish Sea; and Oregon with California. The highest allelic richness (AR) levels were found in California, near the trailing range edge, although AR was also high in Alaska. The inner Salish Sea region had the poorest diversity across the species distribution. Nevertheless, a pattern of isolation by hydrodynamic transport and environment was supported in this region. Discussion: The levels of allelic, private allele richness and genetic differentiation suggest that during the LGM, bull kelp had both northern and southern glacial refugia in the Prince of Wales Island-Haida Gwaii region and Central California, respectively. Genetic diversity in Northern California sites seems resilient to recent disturbances, whereas the low levels of genetic diversity in the inner Salish Sea are concerning.

59 BASIC BIOLOGICAL SCIENCES↗

Ectomycorrhizal and Dark Septate Fungal Associations of Pinyon Pine Are Differentially Affected by Experimental Drought and Warming

Changing climates can cause shifts in temperature and precipitation, resulting in warming and drought in some regions. Although each of these factors has been shown to detrimentally affect forest ecosystems worldwide, information on the impacts of the combined effects of warming and drought is lacking. Forest trees rely on mutualistic root-associated fungi that contribute significantly to plant health and protection against climate stresses. We used a six-year, ecosystem-scale temperature and precipitation manipulation experiment targeted to simulate the climate in 2100 in the Southwestern United States to quantify the effects of drought, warming and combined drought and warming on the root colonization (abundance), species composition and diversity of ectomycorrhizal fungi (EMF), and dark septate fungal endophytes in a widespread woodland tree, pinyon pine (Pinus edulis E.). Our results show that pinyon shoot growth after 6 years of these treatments was reduced more by drought than warming. The combined drought and warming treatment reduced the abundance and diversity of EMF more than either treatment alone. Individual ectomycorrhizal fungal taxa, including the drought tolerant Cenococcum geophilum, were present in all treatments but the combined drought and warming treatment. The combined drought and warming treatment also reduced the abundance of dark septate endophytes (DSE), but did not affect their diversity or species composition. The current year shoot growth of the trees correlated positively with ectomycorrhizal fungal diversity, highlighting the importance of diversity in mutualistic relationships to plant growth. Our results suggest that EMF may be more important than DSE to aboveground growth in P. edulis, but also more susceptible to the negative effects of combined climate stressors.

59 BASIC BIOLOGICAL SCIENCES↗

The genetic basis for panicle trait variation in switchgrass ( Panicum virgatum )

Grass species exhibit large diversity in panicle architecture influenced by genes, the environment, and their interaction. The genetic study of panicle architecture in perennial grasses is limited. In this study, we evaluate the genetic basis of panicle architecture including panicle length, primary branching number, and secondary branching number in an outcrossed switchgrass QTL population grown across ten field sites in the central USA through multi-environment mixed QTL analysis. We also evaluate genetic effects in a diversity panel of switchgrass grown at three of the ten field sites using genome-wide association (GWAS) and multivariate adaptive shrinkage. Furthermore, we search for candidate genes underlying panicle traits in both of these independent mapping populations. Overall, 18 QTL were detected in the QTL mapping population for the three panicle traits, and 146 unlinked genomic regions in the diversity panel affected one or more panicle trait. Twelve of the QTL exhibited consistent effects (i.e., no QTL by environment interactions or no QTL × E), and most (four of six) of the effects with QTL × E exhibited site-specific effects. Most (59.3%) significant partially linked diversity panel SNPs had significant effects in all panicle traits and all field sites and showed pervasive pleiotropy and limited environment interactions. Panicle QTL co-localized with significant SNPs found using GWAS, providing additional power to distinguish between true and false associations in the diversity panel.

59 BASIC BIOLOGICAL SCIENCES↗

A novel approach to build algal consortia for sustainable biomass production

In the last decade, microalgae have reemerged as a feedstock for biofuels and a diverse suite of bioproducts. Yet, considerable challenges must be overcome before algal biofuels and bioproducts become technoeconomically viable. At present, single algal strain selected for particular phenotypic traits, such as maximum specific growth rate or lipid content, are commonly scaled for cultivation in open, outdoor raceway ponds due to the low capital costs of these systems. Although this monoculture approach may maximize the production of end products, monocultures are particularly susceptible to crashes associated with environmental and biological variability. An approach that has been proposed to generate more productive and stable microalgal crops is the use of eco-engineered communities, or consortia. Yet, attempts to construct productive consortia have not been consistently successful. We argue that failures stem from the lack of an eco-engineering approach to design species combinations. Here, we used an in silico method to build consortia before testing their performance against monocultures. Focusing on consortia of Nannochloropsis and Microchloropsis, we measured growth of strains along gradients of light, temperature, and salinity and used a functional dispersion approach to generate over 8000 functionally-diverse consortia combinations. We tested the 50 most functionally diverse consortia in a laboratory experiment and found that consortia overwhelmingly outperformed monocultures. Indeed, overyielding (OY) and a positive net biodiversity effect (NBE) was found respetively in 8%-86% and 88-92% of consortia combinations over the different experimental phases. To our knowledge, this is the first application of an in silico approach to design functionally diverse consortia before laboratory and field testing. Furthermore, our results highlight the importance of employing a functional diversity approach for consortia design.

09 BIOMASS FUELS↗

A genomic view of Earth’s biomes

Microorganisms are essential to all life on Earth through critical roles in key biological processes and diverse interactions with other organisms that shape ecosystems, drive biogeochemical cycles and influence both human health and environmental health. High-throughput sequencing from environmental samples has revolutionized the understanding of microbial diversity and functions. With vast amounts of genomes now available across Earth’s biomes, these data provide a blueprint of microbial life that can be harnessed for a more holistic understanding of microbiome structure and function across the various ecosystems on Earth. Here we review the application of genome-centric approaches, including recent advances in single-cell sequencing and functional profiling, to survey microbial and viral diversity. Furthermore, we highlight some of the most impactful evolutionary and functional discoveries, explore the spatial diversity and temporal dynamics of microorganisms across diverse environments, and discuss genome-enabled insights into host-associated microorganisms.

Ecology↗

Environmental RNA as a Tool for Marine Community Biodiversity Assessments

Abstract Microscopic organisms are often overlooked in traditional diversity assessments due to the difficulty of identifying them based on morphology. Metabarcoding is a method for rapidly identifying organisms where Environmental DNA (eDNA) is used as a template. However, legacy DNA is problematically detected from organisms no longer in the environment during sampling. Environmental RNA (eRNA), which is only produced by living organisms, can also be collected from environmental samples and used for metabarcoding. The aim of this study was to determine differences in community composition and diversity between eRNA and eDNA templates for metabarcoding. Using mesocosms containing field-collected communities from an estuary, RNA and DNA were co-extracted from sediment, libraries were prepared for two loci (18S and COI), and sequenced using an Illumina MiSeq. Results show a higher number of unique sequences detected from eRNA in both markers and higher α-diversity compared to eDNA. Significant differences between eRNA and eDNA for all β-diversity metrics were also detected. This study is the first to demonstrate community differences detected with eRNA compared to eDNA from an estuarine system and illustrates the broad applications of eRNA as a tool for assessing benthic community diversity, particularly for environmental conservation and management applications.

Giroux, Marissa S.↗

Genomic description of human clinical Aspergillus fumigatus isolates, California, 2020

Abstract Aspergillus fumigatus, an environmental mold, causes life-threatening infections. Studies on the phylogenetic structure of human clinical A. fumigatus isolates are limited. Here, we performed whole genome sequencing of 24 A. fumigatus isolates collected from 18 patients in U.S. healthcare facilities in California. Single-nucleotide polymorphism (SNP) differences between patient isolates ranged from 187 to 70 829 SNPs. For five patients with multiple isolates, we calculated the within-host diversities. Three patients had a within-host diversity that ranged from 4 to 10 SNPs and two patients ranged from 2 to 16 977 SNPs. Findings revealed highly diverse A. fumigatus strains among patients and two patterns of diversity for isolates that come from the same patient, low and extremely high diversity.

Misas, Elizabeth (ORCID:0000000162437716)↗

A defined medium based on R2A for cultivation and exometabolite profiling of soil bacteria

SummaryExometabolomics is an approach to assess how microorganisms alter their environments through the depletion and secretion of chemical compounds. Comparisons of inoculated with uninoculated media can be used to provide direct biochemical observations on depleted and secreted metabolites which can be used to predict resource competition, cross-feeding and secondary metabolite production in microbial isolates and communities. This approach is most powerful when used with defined media that enable tracking of all depleted metabolites. However, microbial growth media have traditionally been developed for the isolation and growth of microorganisms but not metabolite utilization profiling through LC-MS/MS. Here, we describe the construction of a defined medium, the Northen Lab Defined Medium (NLDM), that not only supports the growth of diverse bacteria but is defined and therefore suited for exometabolomic experiments. Metabolites included in NLDM were selected based on their presence in R2A medium and soil, elemental stoichiometry requirements, as well as knowledge of metabolite usage by different bacteria. We found that NLDM supported the growth of 53 phylogenetically diverse soil bacterial isolates and all of its metabolites were trackable through LC–MS/MS analysis. These results demonstrate the viability and utility of the constructed NLDM medium for cultivating and characterizing diverse microbial isolates and communities.Originality-Significance StatementWe build a defined medium based on the metabolite composition of R2A medium and soil, elemental stoichiometry requirements, and knowledge of metabolite usage by different bacteria. The newly formulated defined medium was evaluated on its ability to support the growth of soil isolates and its application for metabolite utilization profiling. We found that of 53 phylogenetically diverse soil bacterial isolates grew on the defined medium and all of its metabolites were trackable through LC–MS/MS analysis. This demonstrates the viability and utility of the constructed defined medium for cultivating and characterizing diverse microbial isolates and communities.

de Raad, Markus↗

Hidden Allies: Decoding the Core Endohyphal Bacteriome of Aspergillus fumigatus

ABSTRACT Bacterial–fungal interactions that influence the behaviour of one or both organisms are common in nature. Well‐studied systems include endosymbiotic relationships that range from transient to long‐term associations. Diverse endohyphal bacteria associate with fungal hosts, emphasising the need to better comprehend the fungal bacteriome. We evaluated the hypothesis thatAspergillus fumigatusharbours an endohyphal community of bacteria that influence the host phenotype. We analysed whether 38A. fumigatusstrains show stable association with diverse endohyphal bacteria; all derived from single‐conidium cultures that were subjected to antibiotic and heat treatments. The fungal bacteriome, inferred through analysis of bacterial diversity within the fungal strains (short‐ and long‐ read sequencing methods), revealed the presence of core endohyphal bacterial genera. Microscopic analysis further confirmed the presence of endohyphal bacteria. The fungal strains exhibited high genetic diversity and phenotypic heterogeneity in drug susceptibility and in vivo virulence. No correlations were observed between genomic or functional traits and bacteriome diversity, but the abundance of some bacterial genera correlated with fungal virulence or posaconazole susceptibility. The observed endobacteriome may play functional roles, for example, nitrogen fixation. Our study emphasises the existence of complex interactions between fungi and endohyphal bacteria, possibly impacting the phenotype of the fungal host, including virulence.

Environmental Sciences & Ecology↗

Ecological generalism drives hyperdiversity of secondary metabolite gene clusters in xylarialean endophytes

Although secondary metabolites are typically associated with competitive or pathogenic interactions, the high bioactivity of endophytic fungi in the Xylariales, coupled with their abundance and broad host ranges spanning all lineages of land plants and lichens, suggests that enhanced secondary metabolism might facilitate symbioses with phylogenetically diverse hosts. Here, we examined secondary metabolite gene clusters (SMGCs) across 96 Xylariales genomes in two clades (Xylariaceae s.l. and Hypoxylaceae), including 88 newly sequenced genomes of endophytes and closely related saprotrophs and pathogens. We paired genomic data with extensive metadata on endophyte hosts and substrates, enabling us to examine genomic factors related to the breadth of symbiotic interactions and ecological roles. All genomes contain hyperabundant SMGCs; however, Xylariaceae have increased numbers of gene duplications, horizontal gene transfers (HGTs) and SMGCs. Enhanced metabolic diversity of endophytes is associated with a greater diversity of hosts and increased capacity for lignocellulose decomposition. Our results suggest that, as host and substrate generalists, Xylariaceae endophytes experience greater selection to diversify SMGCs compared with more ecologically specialised Hypoxylaceae species. Altogether, our results provide new evidence that SMGCs may facilitate symbiosis with phylogenetically diverse hosts, highlighting the importance of microbial symbioses to drive fungal metabolic diversity.

59 BASIC BIOLOGICAL SCIENCES↗

A metagenomic perspective on the microbial prokaryotic genome census

Following 30 years of sequencing, we assessed the phylogenetic diversity (PD) of >1.5 million microbial genomes in public databases, including metagenome-assembled genomes (MAGs) of uncultivated microbes. As compared to the vast diversity uncovered by metagenomic sequences, cultivated taxa account for a modest portion of the overall diversity, 9.73% in bacteria and 6.55% in archaea, while MAGs contribute 48.54% and 57.05%, respectively. Therefore, a substantial fraction of bacterial (41.73%) and archaeal PD (36.39%) still lacks any genomic representation. This unrepresented diversity manifests primarily at lower taxonomic ranks, exemplified by 134,966 species identified in 18,087 metagenomic samples. Our study exposes diversity hotspots in freshwater, marine subsurface, sediment, soil, and other environments, whereas human samples yielded minimal novelty within the context of existing datasets. These results offer a roadmap for future genome recovery efforts, delineating uncaptured taxa in underexplored environments and underscoring the necessity for renewed isolation and sequencing.

59 BASIC BIOLOGICAL SCIENCES↗