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At least 325 records · Page 18

Symbiont-Mediated Digestion of Plant Biomass in Fungus-Farming Insects

Feeding on living or dead plant material is widespread in insects. Seminal work on termites and aphids has provided profound insights into the critical nutritional role that microbes play in plant-feeding insects. Here, some ants, beetles, and termites, among others, have evolved the ability to use microbes to gain indirect access to plant substrate through the farming of a fungus on which they feed. Recent genomic studies, including studies of insect hosts and fungal and bacterial symbionts, as well as metagenomics and proteomics, have provided important insights into plant biomass digestion across insect–fungal mutualisms. Not only do advances in understanding of the divergent and complementary functions of complex symbionts reveal the mechanism of how these herbivorous insects catabolize plant biomass, but these symbionts also represent a promising reservoir for novel carbohydrate-active enzyme discovery, which is of considerable biotechnological interest.

59 BASIC BIOLOGICAL SCIENCES↗

Conservation of endo -glucanase 16 (EG16) activity across highly divergent plant lineages

Plant cell walls are highly dynamic structures that are composed predominately of polysaccharides. As such, endogenous carbohydrate active enzymes (CAZymes) are central to the synthesis and subsequent modification of plant cells during morphogenesis. The endo-glucanase 16 (EG16) members constitute a distinct group of plant CAZymes, angiosperm orthologs of which were recently shown to have dual β-glucan/xyloglucan hydrolase activity. Molecular phylogeny indicates that EG16 members comprise a sister clade with a deep evolutionary relationship to the widely studied apoplastic xyloglucan endo-transglycosylases/hydrolases (XTH). A cross-genome survey indicated that EG16 members occur as a single ortholog across species and are widespread in early diverging plants, including the non-vascular bryophytes, for which functional data were previously lacking. Remarkably, enzymological characterization of an EG16 ortholog from the model moss Physcomitrella patens (PpEG16) revealed that EG16 activity and sequence/structure are highly conserved across 500 million years of plant evolution, vis-à-vis orthologs from grapevine and poplar. Ex vivo biomechanical assays demonstrated that the application of EG16 gene products caused abrupt breakage of etiolated hypocotyls rather than slow extension, thereby indicating a mode-of-action distinct from endogenous expansins and microbial endo-glucanases. As a result, the biochemical data presented here will inform future genomic, genetic, and physiological studies of EG16 enzymes.

59 BASIC BIOLOGICAL SCIENCES↗

Systematic identification of transcriptional activation domains from non-transcription factor proteins in plants and yeast

Transcription factors can promote gene expression through activation domains. Whole-genome screens have systematically mapped activation domains in transcription factors but not in non-transcription factor proteins (e.g., chromatin regulators and coactivators). To fill this knowledge gap, we employed the activation domain predictor PADDLE to analyze the proteomes of Arabidopsis thaliana and Saccharomyces cerevisiae. We screened 18,000 predicted activation domains from >800 non-transcription factor genes in both species, confirming that 89% of candidate proteins contain active fragments. Our work enables the annotation of hundreds of nuclear proteins as putative coactivators, many of which have never been ascribed any function in plants. Analysis of peptide sequence compositions reveals how the distribution of key amino acids dictates activity. Finally, we validated short, "universal" activation domains with comparable performance to state-of-the-art activation domains used for genome engineering. Our approach enables the genome-wide discovery and annotation of activation domains that can function across diverse eukaryotes.

59 BASIC BIOLOGICAL SCIENCES↗

EvoNet: A phylogenomic and systems biology approach to identify genes underlying plant survival in marginal, low‐N soils

The DOE‐BER “EvoNet” project investigates the genetic and molecular basis of plant resilience in extreme environments. We do this by identifying key genes that enable “extreme survivor” species to thrive in the nitrogen-poor soils of Chile’s hyper-arid Atacama Desert. Our collections focus on 32 Atacama extremophile species, including seven grass species with potential biofuel applications. To identify genes-of-importance to survival we compared genomic and transcriptomic profiles of extremophile species that thrive in the Atacama to those of closely related “sister” species from nitrogen-rich arid and mesic regions of California. Deep RNA sequencing and de novo transcriptome assembly across these triplet species sets supported a phylogenomic framework for identifying positively selected genes associated with adaptive divergence. Our integrative analysis combined ecological and environmental data, metagenomics, evolutionary and systems biology, and metabolomics. This enabled us to create an unprecedented framework for systematically understanding how non-model plants have adapted to survive in extreme conditions. Our resulting database of positively selected ortholog groups in the extremophile plants offers promising targets for engineering crop and biofuel species with enhanced resilience to drought and extreme weather. Additionally, our newest dataset explores and exploits a complementary metabolomic approach. This new aspect provides innovative strategies to manipulate plant cell metabolism, further supporting efforts to improve agricultural productivity in the face of extreme climates. Importantly, our combined evolutionary- and metabolomic-based strategies focused on convergent patterns of adaptation, providing a genetic and metabolomic toolkit for improving crop and biofuel resilience across diverse plant species. Finally, our novel exploration of ecological and evolutionary dynamics delivered to the community a phylogenomic computational pipeline called “PhyloGeneious.” Our continued adaptations of this pipeline are publicly available to expedite evolutionary genomic research for future scientific discoveries. In total, our DOE-BER has provided genomic, metabolomic, and computational strategies to understand how extremophile plants provide evolutionary and physiological targets for improving agricultural and biofuel production.

59 BASIC BIOLOGICAL SCIENCES↗

Holo-Omics disentangle drought response and biotic interactions among plant, endophyte and pathogen

Holo-omics provide a novel opportunity to study the interactions among fungi from different functional guilds in host plants in field conditions. We address the entangled responses of plant pathogenic and endophytic fungi associated with sorghum when droughted through the assembly of the most abundant fungal, endophyte genome from rhizospheric metagenomic sequences followed by a comparison of its metatranscriptome with the host plant metabolome and transcriptome. The rise in relative abundance of endophytic Acremonium persicinum (operational taxonomic unit 5 (OTU5)) in drought co-occurs with a rise in fungal membrane dynamics and plant metabolites, led by ethanolamine, a key phospholipid membrane component. The negative association between endophytic A. persicinum (OTU5) and plant pathogenic fungi co-occurs with a rise in expression of the endophyte's biosynthetic gene clusters coding for secondary compounds. Endophytic A. persicinum (OTU5) and plant pathogenic fungi are negatively associated under preflowering drought but not under postflowering drought, likely a consequence of variation in fungal fitness responses to changes in the availability of water and niche space caused by plant maturation over the growing season. Our findings suggest that the dynamic biotic interactions among host, beneficial and harmful microbiota in a changing environment can be disentangled by a blending of field observation, laboratory validation, holo-omics and ecological modelling.

Chen, Peilin↗

Detailed Method for the Purification of Rhamnogalacturonan-I (RG-I) in Arabidopsis thaliana

The plant cell wall is a dynamic and complex extracellular matrix that not only provides structural integrity and determines cell shape but also mediates intercellular communication. Among its major components, pectins play essential roles in cell adhesion, wall porosity, hydration, and flexibility. Rhamnogalacturonan-I (RG-I), a structurally diverse pectic polysaccharide, remains one of the least understood components of the plant cell wall. Its backbone is substituted with arabinan, galactan, and arabinogalactan side chains that vary in length, branching, and composition across tissues, species, and developmental stages. In addition, RG-I can undergo modifications such as backbone acetylation, further contributing to its structural complexity and functional diversity. To advance understanding of RG-I, we present a detailed method for isolating RG-I from the model plant Arabidopsis thaliana . Leveraging Arabidopsis as a model system provides major advantages owing to its well-characterized genome and powerful molecular toolkit, enabling deeper investigation into the roles of RG-I in plant development and responses to environmental stress. Our method consists of two major steps: an initial chemical extraction using oxalate, followed by endo-polygalacturonase (EPG) digestion to fragment the pectic domains. An advantage of this approach is that it produces a dry material that can be stored at room temperature without special handling and does not introduce chemicals that may interfere with downstream analyses. The purified RG-I can be used for detailed compositional and structural analyses, as well as for functional studies of enzymes involved in pectin biosynthesis, modification, and degradation. Although this protocol was developed for isolating RG-I from Arabidopsis rosette leaves, it is also applicable to other Arabidopsis organs and other plant species.

25 ENERGY STORAGE↗

Section-level genome sequencing and comparative genomics of Aspergillus sections Cavernicolus and Usti.

The genus Aspergillus is diverse, including species of industrial importance, human pathogens, plant pests, and model organisms. Aspergillus includes species from sections Usti and Cavernicolus, which until recently were joined in section Usti, but have now been proposed to be non-monophyletic and were split by section Nidulantes, Aenei and Raperi. To learn more about these sections, we have sequenced the genomes of 13 Aspergillus species from section Cavernicolus (A. cavernicola, A. californicus, and A. egyptiacus), section Usti (A. carlsbadensis, A. germanicus, A. granulosus, A. heterothallicus, A. insuetus, A. keveii, A. lucknowensis, A. pseudodeflectus and A. pseudoustus), and section Nidulantes (A. quadrilineatus, previously A. tetrazonus). We compared these genomes with 16 additional species from Aspergillus to explore their genetic diversity, based on their genome content, repeat-induced point mutations (RIPs), transposable elements, carbohydrate-active enzyme (CAZyme) profile, growth on plant polysaccharides, and secondary metabolite gene clusters (SMGCs). All analyses support the split of section Usti and provide additional insights: Analyses of genes found only in single species show that these constitute genes which appear to be involved in adaptation to new carbon sources, regulation to fit new niches, and bioactive compounds for competitive advantages, suggesting that these support species differentiation in Aspergillus species. Sections Usti and Cavernicolus have mainly unique SMGCs. Section Usti contains very large and information-rich genomes, an expansion partially driven by CAZymes, as section Usti contains the most CAZyme-rich species seen in genus Aspergillus. Section Usti is clearly an underutilized source of plant biomass degraders and shows great potential as industrial enzyme producers. Citation: Nybo JL, Vesth TC, Theobald S, Frisvad JC, Larsen TO, Kjaerboelling I, Rothschild-Mancinelli K, Lyhne EK, Barry K, Clum A, Yoshinaga Y, Ledsgaard L, Daum C, Lipzen A, Kuo A, Riley R, Mondo S, LaButti K, Haridas S, Pangalinan J, Salamov AA, Simmons BA, Magnuson JK, Chen J, Drula E, Henrissat B, Wiebenga A, Lubbers RJM, Müller A, dos Santos Gomes AC, Mäkelä MR, Stajich JE, Grigoriev IV, Mortensen UH, de Vries RP, Baker SE, Andersen MR (2025). Section-level genome sequencing and comparative genomics of Aspergillus sections Cavernicolus and Usti. Studies in Mycology 111: 101-114. doi: 10.3114/sim.2025.111.03.

59 BASIC BIOLOGICAL SCIENCES↗

Modeling Plant Metabolism: From Network Reconstruction to Mechanistic Models

Mathematical modeling of plant metabolism allows the plant science community to understand the organization of plant metabolism, obtain quantitative insights into metabolic functions, and derive engineering strategies for manipulation of metabolism. Among the various modeling approaches, metabolic pathway analysis can dissect the basic functional modes of subsections of core metabolism, such as photorespiration, and reveal how classical definitions of metabolic pathways have overlapping functionality. In current research using constraint-based modeling in plants, numerous computational tools are currently available to analyze large-scale and genome-scale metabolic networks. For 13 C-metabolic flux analysis, principles of isotopic steady state have been used to study heterotrophic plant tissues, while nonstationary isotope labeling approaches are amenable to the study of photoautotrophic and secondary metabolism. Enzyme kinetic models explore pathways in mechanistic detail, and we discuss different approaches to determine or estimate kinetic parameters. In this review, we describe recent advances and challenges in modeling plant metabolism.

59 BASIC BIOLOGICAL SCIENCES↗

Imitating the “breeder's eye”: Predicting grain yield from measurements of non‐yield traits

Abstract Plant breeding relies on information gathered from field trials to select promising new crop varieties for release to farmers and to develop genomic prediction models that can enhance the efficiency of genetic improvement in future breeding cycles. However, generating the genetic marker data required to apply genomic prediction at the early stages of a breeding program remains costly for many public‐sector breeding programs as well as for many plant breeders operating in developing countries. As the pace of climate change intensifies, the time lag of developing and deploying new crop varieties requires plant breeders to make selection decisions without knowing the future environments those crop varieties will encounter in farmers’ fields. Therefore, both lower cost and higher accuracy methods for prediction of crop performance are essential for creating and maintaining resilient agricultural systems in the latter half of the 21 st century. To address this challenge, we conducted linked yield trials of 752 public maize ( Zea mays ) genotypes in two distinct environments. We developed and trained a phenotypic prediction model to predict yield from manually scored plant traits. The phenotypic prediction approach we employed outperformed genomic prediction in predicting yields in a second environment, with 8.7%–63% higher R 2 and 4%–13% less root mean square error than the genomic prediction. The phenotypic prediction has the potential to be applied to a wider range of breeding programs, including those that lack the resources to genotype large populations, such as programs in the developing world, breeding programs for specialty crops, and public sector programs.

60 APPLIED LIFE SCIENCES↗

Genome-wide identification and functional prediction of silicon (Si) transporters in poplar (Populus trichocarpa)

Abstract Silicon (Si) enhances plant tolerance to various biotic and abiotic stressors such as salinity, drought, and heat. In addition, Si can be biomineralized within plants to form organic carbon-containing phytoliths that can have ecosystem-level consequences by contributing to long-term carbon sequestration. Si is taken up and transported in plants via different transporter proteins such as influx transporters (e.g., Lsi1, Lsi6) and efflux transporters (e.g., Lsi2). Additionally, the imported Si can be deposited in plant leaves via silicification process using the Siliplant 1 (e.g., Slp1) protein. Functional homologs of these proteins have been reported in different food crops. Here, we performed a genome-wide analysis to identify different Si transporters and Slp1 homologs in the bioenergy crop poplar ( Populus trichocarpa Torr. and A. Gray ex W. Hook). We identified one channel-type Si influx transporter (PtLsi1; Potri.017G083300), one Si efflux transporter (PtLsi2; Potri.012G144000) and two proteins like Slp1 (PtSlp1a; Potri.004G168600 and PtSlp1b; Potri.009G129900 ) in the P. trichocarpa genome. We found a unique sequence (KPKPPVFKPPPVPI) in PtSlp1a which is repeated six times. Repeated presence of this sequence in PtSlp1a indicates that this protein might be important for silicification processes in P. trichocarpa. The mutation profiles of different Si transporters in a P. trichocarpa genome-wide association study population identified significant and impactful mutations in Potri.004G168600 and Potri.009G129900 . Using a publically accessible database ( http://bar.utoronto.ca/eplant_poplar/ ), digital expression analysis of the putative Si transporters in P. trichocarpa found low to moderate expression in the anticipated tissues, such as roots and leaves. Subcellular localization analysis found that PtLsi1/PtLsi2 are localized in the plasma membrane, whereas PtSlp1a/PtSlp1b are found in the extracellular spaces. Protein–Protein interaction analysis of PtLsi1/PtLsi2 identified Delta-1-pyrroline-5-carboxylate synthase (P5CS) as one of the main interacting partners of PtLsi2, which plays a key role in proline biosynthesis. Proline is a well-known participant in biotic and abiotic stress tolerance in plants. These findings will reinforce future efforts to modify Si accumulation for enhancing plant stress tolerance and carbon sequestration in poplar.

59 BASIC BIOLOGICAL SCIENCES↗

Genome-sequenced bacterial collection from sorghum aerial root mucilage

ABSTRACT A collection of 47 bacteria isolated from the mucilage of aerial roots of energy sorghum is available at the Great Lakes Bioenergy Research Center, Michigan State University, Michigan, USA. We enriched bacteria with putative plant-beneficial phenotypes and included information on phenotypic diversity, taxonomy, and whole genome sequences.

Mechan-Llontop, Marco E.↗

Genomic fingerprints of the world’s soil ecosystems

Despite the explosion of soil metagenomic data, we lack a synthesized understanding of patterns in the distribution and functions of soil microorganisms. These patterns are critical to predictions of soil microbiome responses to climate change and resulting feedbacks that regulate greenhouse gas release from soils. To address this gap, we assay 1,512 manually curated soil metagenomes using complementary annotation databases, read-based taxonomy, and machine learning to extract multidimensional genomic fingerprints of global soil microbiomes. Our objective is to uncover novel biogeographical patterns of soil microbiomes across environmental factors and ecological biomes with high molecular resolution. We reveal shifts in the potential for (i) microbial nutrient acquisition across pH gradients; (ii) stress-, transport-, and redox-based processes across changes in soil bulk density; and (iii) greenhouse gas emissions across biomes. We also use an unsupervised approach to reveal a collection of soils with distinct genomic signatures, characterized by coordinated changes in soil organic carbon, nitrogen, and cation exchange capacity and in bulk density and clay content that may ultimately reflect soil environments with high microbial activity. Genomic fingerprints for these soils highlight the importance of resource scavenging, plant-microbe interactions, fungi, and heterotrophic metabolisms. Across all analyses, we observed phylogenetic coherence in soil microbiomes—more closely related microorganisms tended to move congruently in response to soil factors. Collectively, the genomic fingerprints uncovered here present a basis for global patterns in the microbial mechanisms underlying soil biogeochemistry and help beget tractable microbial reaction networks for incorporation into process-based models of soil carbon and nutrient cycling.

59 BASIC BIOLOGICAL SCIENCES↗

Gene family expansions and transcriptome signatures uncover fungal adaptations to wood decay

Because they comprise some of the most efficient wood-decayers, Polyporales fungi impact carbon cycling in forest environment. Despite continuous discoveries on the enzymatic machinery involved in wood decomposition, the vision on their evolutionary adaptation to wood decay and genome diversity remains incomplete. We combined the genome sequence information from 50 Polyporales species, including 26 newly sequenced genomes and sought for genomic and functional adaptations to wood decay through the analysis of genome composition and transcriptome responses to different carbon sources. The genomes of Polyporales from different phylogenetic clades showed poor conservation in macrosynteny, indicative of genome rearrangements. We observed different gene family expansion/contraction histories for plant cell wall degrading enzymes in core polyporoids and phlebioids and captured expansions for genes involved in signalling and regulation in the lineages of white rotters. Furthermore, we identified conserved cupredoxins, thaumatin-like proteins and lytic polysaccharide monooxygenases with a yet uncharacterized appended module as new candidate players in wood decomposition. Given the current need for enzymatic toolkits dedicated to the transformation of renewable carbon sources, the observed genomic diversity among Polyporales strengthens the relevance of mining Polyporales biodiversity to understand the molecular mechanisms of wood decay.

59 BASIC BIOLOGICAL SCIENCES↗

Calcium/calmodulin-mediated signal network in plants

Various extracellular stimuli elicit specific calcium signatures that can be recognized by different calcium sensors. Calmodulin, the predominant calcium receptor, is one of the best-characterized calcium sensors in eukaryotes. In recent years, completion of the Arabidopsis genome project and advances in functional genomics have helped to identify and characterize numerous calmodulin-binding proteins in plants. There are some similarities in Ca(2+)/calmodulin-mediated signaling in plants and animals. However, plants possess multiple calmodulin genes and many calmodulin target proteins, including unique protein kinases and transcription factors. Some of these proteins are likely to act as "hubs" during calcium signal transduction. Hence, a better understanding of the function of these calmodulin target proteins should help in deciphering the Ca(2+)/calmodulin-mediated signal network and its role in plant growth, development and response to environmental stimuli.

NASA Discipline Plant Biology↗

Tousled-like kinase 2 targets ASF1 histone chaperones through client mimicry

Tousled-like kinases (TLKs) are nuclear serine-threonine kinases essential for genome maintenance and proper cell division in animals and plants. A major function of TLKs is to phosphorylate the histone chaperone proteins ASF1a and ASF1b to facilitate DNA replication-coupled nucleosome assembly, but how TLKs selectively target these critical substrates is unknown. Here, we show that TLK2 selectivity towards ASF1 substrates is achieved in two ways. First, the TLK2 catalytic domain recognizes consensus phosphorylation site motifs in the ASF1 C-terminal tail. Second, a short sequence at the TLK2 N-terminus docks onto the ASF1a globular N-terminal domain in a manner that mimics its histone H3 client. Disrupting either catalytic or non-catalytic interactions through mutagenesis hampers ASF1 phosphorylation by TLK2 and cell growth. Our results suggest that the stringent selectivity of TLKs for ASF1 is enforced by an unusual interaction mode involving mutual recognition of a short sequence motifs by both kinase and substrate.

59 BASIC BIOLOGICAL SCIENCES↗

Discovery of an ultraspecific triuret hydrolase (TrtA) establishes the triuret biodegradation pathway

Triuret (carbonyldiurea) is an impurity found in industrial urea fertilizer (<0.1% w/w) that is applied, worldwide, around 300 million pounds each year on agricultural lands. In addition to anthropogenic sources, endogenous triuret has been identified in amoeba and human urine, the latter being diagnostic for hypokalemia. The present study is the first to describe the metabolic breakdown of triuret, which funnels into biuret metabolism. We identified the gene responsible for triuret decomposition ( trtA ) in bacterial genomes, clustered with biuH , which encodes biuret hydrolase and has close protein sequence homology. TrtA is a member of the isochorismatase-like hydrolase (IHL) protein family, similarly to BiuH, and has a catalytic efficiency (k cat/ K M ) of 6 x 10 5 M –1 s –1 , a K M for triuret of 20 μM, and exquisite substrate specificity. Indeed, TrtA has four orders of magnitude less activity with biuret. Crystal structures of TrtA in apo and holo form were solved and compared with the BiuH structure. The high substrate selectivity was found to be conveyed by second shell residues around each active site. Mutagenesis of residues conserved in TrtA to the alternate consensus found in BiuHs revealed residues critical to triuret hydrolase activity but no single mutant evolved more biuret activity, and likely a combination of mutations is required to interconvert between TrtA, BiuH functions. TrtA-mediated triuret metabolism is relatively rare in recorded genomes (1–2%), but is largely found in plant-associated, nodulating, and endophytic bacteria. This study suggests functions for triuret hydrolase in certain eukaryotic intermediary processes and prokaryotic intermediary or biodegradative metabolism.

36 MATERIALS SCIENCE↗

Galba: genome annotation with miniprot and AUGUSTUS

The Earth Biogenome Project has rapidly increased the number of available eukaryotic genomes, but most released genomes continue to lack annotation of protein-coding genes. In addition, no transcriptome data is available for some genomes. Various gene annotation tools have been developed but each has its limitations. Here, we introduce GALBA, a fully automated pipeline that utilizes miniprot, a rapid protein-to-genome aligner, in combination with AUGUSTUS to predict genes with high accuracy. Accuracy results indicate that GALBA is particularly strong in the annotation of large vertebrate genomes. We also present use cases in insects, vertebrates, and a land plant. GALBA is fully open source and available as a docker image for easy execution with Singularity in high-performance computing environments. Our pipeline addresses the critical need for accurate gene annotation in newly sequenced genomes, and we believe that GALBA will greatly facilitate genome annotation for diverse organisms.

59 BASIC BIOLOGICAL SCIENCES↗