Biology subjects

Riley, R.

Publications and source records attributed to Riley, R..

At least 19 recordsLinked to original sources

bioRxiv2026

Distinct Strategies for Engineering Bioenergy Traits in Sorghum Drive Divergent Functional Shifts in the Rhizosphere Microbiome

Engineering bioenergy crops for enhanced biomass digestibility and high-value co-products is a promising approach to sustainable biofuel production. However, the impact of these engineered crops on the belowground microbiome remains poorly understood. In this study, we characterized the composition and functional responses of the belowground microbiome associated with transgenic sorghum lines: one with reduced cell wall crosslinking (AT10) and another with elevated protocatechuic acid (PCA) production (Qsub). The lines were grown under field conditions with four irrigation levels, and samples were collected twice during the growing season. We found that the two transgenic types drove a subtle but significant divergence in bacterial communities, both compositionally and functionally. Community-wide functional profiling showed that AT10 rhizospheres were consistently depleted in genes associated with mobile genetic elements, while Qsub rhizospheres were enriched in TonB-dependent transport and vanillate monooxygenase, an enzyme that funnels lignin-derived monomers toward PCA degradation, alongside reduced pectin- and cellulose-degradation genes. Genome-resolved analysis linked these community-level shifts to specific taxa: in Qsub, the enriched MAGs were taxonomically diverse, ranging from genome-reduced Patescibacteria with an episymbiotic lifestyle to taxa enriched in lignin-associated auxiliary activity enzymes. In AT10, the depleted Azospirillaceae MAGs carried unusually high mobile genetic element content, consistent with the community-wide pattern. Collectively, these findings offer new insights into how genetic modifications aimed at improving bioenergy traits shapes the composition and function of the rhizosphere microbiome, with potential downstream consequences for soil carbon cycling.

plant biology↗

bioRxiv2026

Comparative genomics reveals shared accessory regions between members of two Fusarium species complexes virulent on garden pea

The contribution of accessory or conditionally dispensable chromosomes to host-specific virulence was first demonstrated in members of the Fusarium solani species complex (FSSC) that are pathogens of garden pea, Pisum sativum L. The phenomenon has since been shown to exist in many fungal plant pathogens, including the closely related F. oxysporum species complex (FOSC). Genome analysis of members of the FSSC and FOSC pathogenic on pea revealed a diverse size range of the accessory genome of these fungi. Despite the [~]65 million years of diverging time, regions on a chromosome known to carry host-specific virulence factors for pea, including the cytochrome P450 pisatin demethylase (PDA) and other pea pathogenicity (PEP) genes, were present in all genomes of these pea pathogens. Genes directly involved in virulence on pea - PEP2, PDA, and PEP5- were the most frequently clustered together. Transcriptome analysis of fungal mycelia treated with the pea phytoalexin pisatin, identified 1,155 differentially expressed genes where many were involved in cellular stress responses. As wilt pathogens that invade host xylem, members of the FOSC encode more putative effectors, when compared to those in the FSSC, and several FOSC effectors were identified to confer race specificity. The conservation of part of the accessory genomes across two evolutionarily diverged species complexes suggests a common origin. Horizontal transfer of accessory chromosomes containing genetic loci involved in pathogenesis for garden pea offers a parsimonious explanation of the polyphyletic origin of host specificity.

genomics↗

bioRxiv2026

Confident Identification and Quantification of Mouse Brain Tissues Reveals Sirtuin 5-Dependent Regulation

Methylmalonylation is a non-enzymatic lysine post-translational modification derived from methylmalonyl-CoA, a reactive intermediate that accumulates during mitochondrial dysfunction and branched-chain amino acid catabolism. Although reported in models of methylmalonic acidemia, its broader distribution and functional relevance remain largely unexplored. Progress has been hindered by a key analytical challenge: methylmalonyl-and succinyl-lysine are isobaric (+100.0160 Da) and generate overlapping mass spectrometric fragmentation spectra, preventing confident identification in conventional proteomic workflows. Here, we establish a straightforward proteomic workflow that overcomes this barrier and enables confident identification and quantification of lysine methylmalonylation by combining antibody-based enrichment with data-independent acquisition mass spectrometry (DIA-MS). Anti-malonyl antibodies were used to enrich methylmalonylated peptides through cross-reactivity. Using synthetic peptide standards containing malonyl-, succinyl-, or methylmalonyl-lysine, we defined distinguishing analytical features including chromatographic retention time, ion mobility, and fragmentation patterns. Applying this approach to mouse brain tissues from Sirtuin-5 (SIRT5) knockout and wild-type mice, we identified 44 methylmalonylated peptides across 41 proteins, enriched in neuronal and myelin-associated proteins (NEFM, NEFL, MBP) and mitochondrial enzymes such as ADT1. Several sites were increased in SIRT5-deficient brains, consistent with regulation by this mitochondrial deacylase. Functional assays demonstrated that methylmalonylation of myelin basic protein (MBP) impairs lipid binding, linking this modification to myelin stability. Together, this workflow enables confident methylmalonylation identification and defines it as a widespread and regulated modification in the brain, providing a framework to study metabolically driven protein acylation in neurobiology and disease. SignificanceLysine methylmalonylation has remained largely unexplored due to its isobaric overlap with succinylation, which prevents confident identification using conventional proteomic workflows. Here, we establish an integrated strategy combining antibody-based enrichment, data-independent acquisition mass spectrometry, and orthogonal analytical features to resolve these modifications with high confidence. Applying this approach to mouse brain tissue reveals a SIRT5-regulated methylmalonylome enriched in mitochondrial and myelin-associated proteins, including myelin basic protein (MBP). Functional assays demonstrate that methylmalonylation impairs MBP lipid binding, linking this modification to myelin stability. Beyond this specific application, our workflow provides a generalizable framework to resolve isobaric post-translational modifications and expands the study of metabolically driven protein acylation in neurobiology and disease.

cell biology↗

bioRxiv2025

A functional map of phosphoprotein phosphatase regulation identifies an evolutionary conserved reductase for the catalytic metal ions

Serine/Threonine phosphoprotein phosphatases (PPPs, PP1-PP7) are conserved metalloenzymes and central to intracellular signaling in eukaryotes, but the details of their regulation is poorly understood. To address this, we performed genome-wide CRISPR knockout and focused base editor screens in PPP perturbed conditions to establish a high-resolution functional map of PPP regulation that pinpoints novel regulatory mechanisms. Through this, we identify the orphan reductase CYB5R4 as an evolutionarily conserved activator of PP4 and PP6, but not the closely related PP2A. Heme binding is essential for CYB5R4 function and mechanistically involves the reduction of the metal ions in the active site. Importantly, CYB5R4-mediated activation of PP4 is critical for cell viability when cells are treated with DNA damage-inducing agents known to cause oxidative stress. The discovery of a dedicated PPP reductase points to shared regulatory principles with protein tyrosine phosphatases, where specific enzymes dictate activity by regulating the active site redox state. In sum, our work provides a resource for understanding PPP function and the regulation of intracellular signaling.

cell biology↗

bioRxiv2025

GenomeOcean: An Efficient Genome Foundation Model Trained on Large-Scale Metagenomic Assemblies

Functional genomic sequences occupy an infinitesimal fraction of the astronomically large DNA sequence space, implying that evolution explores a low-dimensional manifold shaped by universal biochemical and evolutionary constraints. To investigate this underexplored Genomic Manifold Hypothesis using scalable, data-driven evidence, we developed GenomeOcean, a 4-billion-parameter generative model trained on 219 TB of diverse, co-assembled global environmental metagenomic data using an optimized transformer. The model captures both universal phylogenetic syntax and protein-coding fidelity. Furthermore, we validate the embeddings intrinsic low dimensionality. Crucially, comparisons with the independently trained Evo 2 model demonstrate a strong linear correspondence between their embedding spaces and convergent generative behaviors. These results suggest that the genomic manifold represents a fundamental biological principle, offering a unified framework for understanding evolutionary constraints and guiding synthetic biology.

bioinformatics↗

bioRxiv2024

Hydrophobins from Aspergillus mediate fungal interactions with microplastics

Microplastics present myriad ecological and human health risks including serving as a vector for pathogens in human and animal food chains. However, the specific mechanisms by which pathogenic fungi colonize these microplastics have yet to be explored. In this work, we examine the opportunistic fungal pathogen, Aspergillus fumigatus, and other common soil and marine Aspergilli, which we found bind microplastics tightly. Up to 3.85+/-1.48 g microplastic plastic/g fungi were bound and flocculated for polypropylene (PP), polyethylene (PE), and polyethylene terephthalate (PET) powders and particles ranging in size from 0.05 - 5 mm. Gene knockouts revealed hydrophobins as a key biomolecule driving microplastic-fungi binding. Moreover, purified hydrophobins were still able to flocculate microplastics independent of the fungus. Our work elucidates a role for hydrophobins in fungal colonization of microplastics and highlights a potential target for mitigating the harm of microplastics through engineered fungal-microplastic interactions. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/622132v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@13eb679org.highwire.dtl.DTLVardef@3dc9c0org.highwire.dtl.DTLVardef@888c96org.highwire.dtl.DTLVardef@c5e1aa_HPS_FORMAT_FIGEXP M_FIG C_FIG Significance StatementMicroplastics pose serious ecological and human health effects by introducing pathogens and toxins into animal and human food chains. Many pathogenic microorganisms preferentially form biofilms on microplastic particles that are then ingested. Here, we demonstrate that hydrophobins, highly hydrophobic, cell surface proteins, enable microplastic binding and colonization by the opportunistic pathogen Aspergillus fumigatus and other fungi within the Aspergillus genus. Our work recognizes a novel role for hydrophobin proteins, identifying potential strategies for pathogen control and protein-based microplastics recovery.

molecular biology↗

bioRxiv2024

Soil redox drives virus-host community dynamics and plant biomass degradation in tropical rainforest soils

BackgroundWet tropical forest soils store a vast amount of organic carbon and cycle over a third of terrestrial net primary production. The microbiomes of these soils have a global impact on greenhouse gases and tolerate a remarkably dynamic redox environment--driven by high availability of reductant, high soil moisture, and fine-textured soils that limit oxygen diffusion. Yet tropical soil microbiomes, particularly virus-host interactions, remain poorly characterized, and we have little understanding of how they will shape future soil carbon cycling as high-intensity drought and precipitation events make soil redox conditions less predictable. ResultsTo investigate the effects of shifting soil redox conditions on active viral communities and virus-microbe interactions, we conducted a 44-day redox manipulation experiment using soils from the Luquillo Experimental Forest, Puerto Rico, amended with 13C-enriched plant biomass. We sequenced 10 bulk metagenomes and 85 stable isotope probing targeted metagenomes generated by extracting whole community DNA, performing density fractionation, and conducting shotgun sequencing. Viral and microbial genomes were assembled resulting in 5,420 viral populations (vOTUs) and 927 medium-to-high-quality metagenome-assembled genomes across 25 bacterial phyla. Notably, over half (54%) of the vOTUs were 13C-enriched, highlighting their active role in microbial degradation of plant litter. These active vOTUs primarily infected bacterial phyla Pseudomonadota, Acidobacteriota, and Actinomycetota, and 57% were unique to a particular redox treatment. The anoxic samples exhibited the most distinct viral communities, with an increased potential for modulating host metabolism by carrying redox-specific glycoside hydrolases. However, over a third of the vOTUs were present in all redox conditions, suggesting selection for cosmopolitan viruses occurs in these soils that naturally experience dynamic redox conditions. ConclusionsOur study demonstrates how redox conditions shape viral communities and virus-host interactions in soils. By applying different DNA assembly methods on stable isotope probing targeted metagenomes and incubating soils under various redox regimes, we identified distinct viral populations and observed significant variations in viral community composition and function. These findings highlight the specialized roles of viruses in microbial carbon degradation under diverse environmental conditions, providing important insights into their contributions to carbon cycling and the broader implications for climate change.

microbiology↗

bioRxiv2024

Multi-omics analysis of a traditional fermented food reveals a byproduct-associated subpopulation of Neurospora intermedia for waste-to-food upcycling

Fungal solid-state fermentation (SSF) of byproducts has promise for increasing food sustainability and security, but fungal waste-to-food upcycling remains poorly understood at the molecular level. Here we use a multi-omics approach to characterize oncom - a fermented food traditionally produced from byproducts in Java, Indonesia - as a model system for understanding fungal waste conversion. Metagenomic sequencing of two oncom types (red and black) indicated that Neurospora intermedia is the fungus dominating red oncom. Further transcriptomic, metabolomic, and phylogenomic analysis revealed that oncom-derived N. intermedia utilizes pectin and cellulose degradation for substrate conversion and belongs to a distinct byproduct-associated subpopulation that differs from wild strains at the genetic and biochemical level. Finally, we found that N. intermedia grew on a range of industrially relevant byproducts, did not encode for any known mycotoxins, and could be used to create foods that were positively perceived by consumers outside Indonesia. This study uncovers the microbial and genetic basis of a traditional upcycled food, sheds light on human domestication of microbes for sustainability challenges, and establishes the edible N. intermedia as a promising fungus for byproduct upcycling in SSF and beyond.

microbiology↗

bioRxiv2024

Unraveling Morphogenesis, Starvation, and Light Responses in a Mushroom-Forming Fungus, Coprinopsis cinerea, Using Long Read Sequencing and Extensive Expression Profiling

Mushroom-forming fungi (Agaricomycetes) are emerging as pivotal players in several fields, as drivers of nutrient cycling, sources of novel applications, and the group includes some of the most morphologically complex multicellular fungi. Genomic data for Agaricomycetes are accumulating at a steady pace, however, this is not paralleled by improvements in the quality of genome sequence and associated functional gene annotations, which leaves gene function notoriously poorly understood in comparison with other fungi and model eukaryotes. We set out to improve our functional understanding of the model mushroom Coprinopsis cinerea by integrating a new, chromosome-level assembly with high-quality gene predictions and functional information derived from gene-expression profiling data across 67 developmental, stress, and light conditions. The new annotation has considerably improved quality metrics and includes 5- and 3-untranslated regions (UTRs), polyadenylation sites (PAS), upstream ORFs (uORFs), splicing isoforms, conserved sequence motifs (e.g., TATA and Kozak boxes) and microexons. We found that alternative polyadenylation is widespread in C. cinerea, but that it is not specifically regulated across the various conditions used here. Transcriptome profiling allowed us to delineate core gene sets corresponding to carbon starvation, light-response, and hyphal differentiation, and uncover new aspects of the light-regulated phases of life cycle. As a result, the genome of C. cinerea has now become the most comprehensively annotated genome among mushroom-forming fungi, which will contribute to multiple rapidly expanding fields, including research on their life history, light and stress responses, as well as multicellular development.

genomics↗

bioRxiv2024

GenomeFace: a deep learning-based metagenome binner trained on 43,000 microbial genomes

Metagenomic binning, the process of grouping DNA sequences into taxonomic units, is critical for understanding the functions, interactions, and evolutionary dynamics of microbial communities. We propose a deep learning approach to binning using two neural networks, one based on composition and another on environmental abundance, dynamically weighting the contribution of each based on characteristics of the input data. Trained on over 43,000 prokaryotic genomes, our network for composition-based binning is inspired by metric learning techniques used for facial recognition. Using a task-specific, multi-GPU accelerated algorithm to cluster the embeddings produced by our network, our binner leverages marker genes observed to be universally present in nearly all taxa to grade and select optimal clusters of sequences from a hierarchy of candidates. We evaluate our approach on four simulated datasets with known ground truth. Our linear time integration of marker genes recovers more near complete genomes than state of the art but computationally infeasible solutions using them, while being over an order of magnitude faster. Finally, we demonstrate the scalability and acuity of our approach by testing it on three of the largest metagenome assemblies ever performed. Compared to other binners, we produced 47%-183% more near complete genomes. From these datasets, we find over the genomes of over 3000 new candidate species which have never been previously cataloged, representing a potential 4% expansion of the known bacterial tree of life.

bioinformatics↗

bioRxiv2023

Viral gene drive spread during herpes simplex virus 1 infection in mice

Gene drives are genetic modifications designed to propagate efficiently through a population. Most applications rely on homologous recombination during sexual reproduction in diploid organisms such as insects, but we recently developed a gene drive in herpesviruses that relies on co-infection of cells by wild-type and engineered viruses. Here, we developed a viral gene drive against human herpes simplex virus 1 (HSV-1) and showed that it propagated efficiently in vitro and during HSV-1 infection in mice. We observed high levels of co-infection and gene drive-mediated recombination in neuronal tissues during herpes encephalitis as the infection progressed from the site of inoculation to the peripheral and central nervous systems. In addition, we found evidence that a superinfecting gene drive virus could recombine with wild-type viruses during latent infection. These findings indicated that HSV-1 achieves high rates of co-infection and recombination during viral infection, a phenomenon that is currently underappreciated. Overall, this study showed that a viral gene drive could spread in vivo during HSV-1 infection, paving the way toward therapeutic applications.

microbiology↗

bioRxiv2023

Chronically disrupted sleep induces senescence in the visceral adipose tissue of C57BL/6J mice

The role of sleep in systemic aging remains poorly understood, despite sleeps essential function in preserving overall health and the prevalence of reduced sleep quality in modern society. Although reduced sleep correlates with an elevated risk of age-related diseases in humans, the mechanisms underlying this are unclear. In this study, we established a link between sleep and aging by demonstrating that disrupting sleep in C57BL/6 mice drives cellular senescence in the visceral adipose tissue. Sleep disruption also led to increased oxidative stress and DNA damage, both recognized triggers for senescence induction. Cellular senescence is implicated in numerous age-related conditions which are associated with insufficient sleep, such as cardiovascular disease, type 2 diabetes, and chronic inflammation. Our findings identify an accumulation of senescent cells in the adipose tissue, which serves as a potential target through which disturbed sleep accelerates the aging process and elevates the risk of age-related diseases.

molecular biology↗

bioRxiv2023

CD38 regulates ovarian function and fecundity via NAD+ metabolism

Mammalian female reproductive lifespan is typically significantly shorter than life expectancy and is associated with a decrease in ovarian NAD+ levels. However, the mechanisms underlying this loss of ovarian NAD+ are unclear. Here, we show that CD38, a NAD+ consuming enzyme, is expressed in the ovarian extrafollicular space, primarily in immune cells, and its levels increase with reproductive age. Reproductively young mice lacking CD38 exhibit larger primordial follicle pools, elevated ovarian NAD+ levels, and increased fecundity relative to wild type controls. This larger ovarian reserve results from a prolonged window of follicle formation during early development. However, the beneficial effect of CD38 loss on reproductive function is not maintained at advanced age. Our results demonstrate a novel role of CD38 in regulating ovarian NAD+ metabolism and establishing the ovarian reserve, a critical process that dictates a females reproductive lifespan.

developmental biology↗

bioRxiv2023

Interpreting Generative Adversarial Networks to Infer Natural Selection from Genetic Data

AO_SCPLOWBSTRACTC_SCPLOWUnderstanding natural selection in humans and other species is a major focus for the use of machine learning in population genetics. Existing methods rely on computationally intensive simulated training data. Unlike efficient neutral coalescent simulations for demographic inference, realistic simulations of selection typically requires slow forward simulations. Because there are many possible modes of selection, a high dimensional parameter space must be explored, with no guarantee that the simulated models are close to the real processes. Mismatches between simulated training data and real test data can lead to incorrect inference. Finally, it is difficult to interpret trained neural networks, leading to a lack of understanding about what features contribute to classification. Here we develop a new approach to detect selection that requires relatively few selection simulations during training. We use a Generative Adversarial Network (GAN) trained to simulate realistic neutral data. The resulting GAN consists of a generator (fitted demographic model) and a discriminator (convolutional neural network). For a genomic region, the discriminator predicts whether it is "real" or "fake" in the sense that it could have been simulated by the generator. As the "real" training data includes regions that experienced selection and the generator cannot produce such regions, regions with a high probability of being real are likely to have experienced selection. To further incentivize this behavior, we "fine-tune" the discriminator with a small number of selection simulations. We show that this approach has high power to detect selection in simulations, and that it finds regions under selection identified by state-of-the art population genetic methods in three human populations. Finally, we show how to interpret the trained networks by clustering hidden units of the discriminator based on their correlation patterns with known summary statistics. In summary, our approach is a novel, efficient, and powerful way to use machine learning to detect natural selection.

genomics↗

bioRxiv2023

Development of a novel epigenetic clock resistant to changes in immune cell composition

Epigenetic clocks are age predictors that use machine-learning models trained on DNA CpG methylation values to predict chronological or biological age. Increases in predicted epigenetic age relative to chronological age (epigenetic age acceleration) are connected to aging-associated pathologies, and changes in epigenetic age are linked to canonical aging hallmarks. However, epigenetic clocks rely on training data from bulk tissues whose cellular composition changes with age. We found that human naive CD8+ T cells, which decrease during aging, exhibit an epigenetic age 15-20 years younger than effector memory CD8+ T cells from the same individual. Importantly, homogenous naive T cells isolated from individuals of different ages show a progressive increase in epigenetic age, indicating that current epigenetic clocks measure two independent variables, aging and immune cell composition. To isolate the age-associated cell intrinsic changes, we created a new clock, the IntrinClock, that did not change among 10 immune cell types tested. IntrinClock showed a robust predicted epigenetic age increase in a model of replicative senescence in vitro and age reversal during OSKM-mediated reprogramming.

genomics↗

bioRxiv2023

T-toxin virulence genes: unconnected dots in a sea of repeats

In 1970, the Southern Corn Leaf Blight epidemic ravaged US fields to great economic loss. The outbreak was caused by never-before-seen, super-virulent, Race T of the fungus Cochliobolus heterostrophus. The functional difference between Race T and O, the previously known, far less aggressive strain, is production of T-toxin, a host-selective polyketide. Super-virulence is associated with [~]1 Mb of Race T- specific DNA; only a fraction encodes T-toxin biosynthetic genes (Tox1). Tox1 is genetically and physically complex, with unlinked loci (Tox1A, Tox1B) genetically inseparable from breakpoints of a Race O reciprocal translocation that generated hybrid Race T chromosomes. Previously, we identified ten genes for T-toxin biosynthesis. Unfortunately, high depth, short-read sequencing placed these genes on four small, unconnected scaffolds surrounded by repeated A+T rich sequence, concealing context. To sort out Tox1 topology and pinpoint the hypothetical Race O translocation breakpoints corresponding to Race T-specific insertions, we undertook PacBio long-read sequencing which revealed Tox1 gene arrangement and the breakpoints. Six Tox1A genes are arranged as three small islands in a Race T-specific sea ([~]634 kb) of repeats. Four Tox1B genes are linked, on a large loop of Race T-specific DNA ([~]210 kb). The race O breakpoints are short sequences of race O-specific DNA; corresponding positions in race T are large insertions of race T-specific, A+T rich DNA, often with similarity to transposable (predominantly Gypsy) elements. Nearby, are Voyager Starship elements and DUF proteins. These elements may have facilitated Tox1 integration into progenitor Race O and promoted large scale recombination resulting in race T. ImportanceIn 1970 a corn disease epidemic ravaged fields in the US to great economic loss. The outbreak was caused by a never-before seen, super-virulent strain of the fungal pathogen Cochliobolus heterostrophus. This was a plant disease epidemic, however, the current COVID-19 pandemic of humans is a stark reminder that novel, highly virulent, pathogens evolve with devastating consequences, no matter what the host-animal, plant, or other organism. Long read DNA sequencing technology allowed in depth structural comparisons between the sole, previously known, much less aggressive, version of the pathogen and the super-virulent version and revealed, in meticulous detail, the structure of the unique virulence-causing DNA. These data are foundational for future analysis of mechanisms of DNA acquisition from a foreign source.

genomics↗

bioRxiv2022

A standardized quantitative analysis strategy for stable isotope probing metagenomics

Stable isotope probing (SIP) facilitates culture-independent identification of active microbial populations within complex ecosystems through isotopic enrichment of nucleic acids. Many SIP studies rely on 16S rRNA sequences to identify active taxa but connecting these sequences to specific bacterial genomes is often challenging. Here, we describe a standardized laboratory and analysis framework to quantify isotopic enrichment on a per-genome basis using shotgun metagenomics instead of 16S rRNA sequencing. To develop this framework, we explored various sample processing and analysis approaches using a designed microbiome where the identity of labeled genomes, and their level of isotopic enrichment, were experimentally controlled. With this ground truth dataset, we empirically assessed the accuracy of different analytic models for identifying active taxa, and examined how sequencing depth impacts the detection of isotopically labeled genomes. We also demonstrate that using synthetic DNA internal standards to measure absolute genome abundances in SIP density fractions improves estimates of isotopic enrichment. In addition, our study illustrates the utility of internal standards to reveal anomalies in sample handling that could negatively impact SIP metagenomic analyses if left undetected. Finally, we present SIPmg, an R package to facilitate the estimation of absolute abundances and perform statistical analyses for identifying labeled genomes within SIP metagenomic data. This experimentally validated analysis framework strengthens the foundation of DNA-SIP metagenomics as a tool for accurately measuring the in situ activity of environmental microbial populations and assessing their genomic potential. ImportanceAnswering the question of who is eating what? within complex microbial communities is paramount for our ability to model, predict, and modulate microbiomes for improved human and planetary health. This question is often pursued using stable isotope probing to track the incorporation of labeled compounds into cellular DNA during microbial growth. However, with traditional stable isotope methods, it is challenging to establish links between an active microorganisms taxonomic identity and genome composition, while providing quantitative estimates of the microorganisms isotope incorporation rate. Here, we report an experimental and analytical workflow that lays the foundation for improved detection of metabolically active microorganisms and better quantitative estimates of genome-resolved isotope incorporation, which can be used to further refine ecosystem-scale models for carbon and nutrient fluxes within microbiomes.

microbiology↗

bioRxiv2022

Genomic innovation and horizontal gene transfer shaped plant colonization and biomass degradation strategies of a globally prevalent fungal pathogen

Members of the fungal genus Armillaria are necrotrophic pathogens with efficient plant biomass-degrading strategies. The genus includes some of the largest terrestrial organisms on Earth, spreading underground and causing tremendous losses in diverse ecosystems. Despite their global importance, the mechanism by which Armillaria evolved pathogenicity in a clade of dominantly non-pathogenic wood-degraders (Agaricales) remains elusive. Here, using new genomic data, we show that Armillaria species, in addition to widespread gene duplications and de novo gene origins, appear to have at least 775 genes that were acquired via 101 horizontal gene transfer (HGT) events, primarily from Ascomycota. Functional and expression data suggest that HGT might have affected plant biomass-degrading and virulence abilities of Armillaria, two pivotal traits in their lifestyle. We further assayed gene expression during root and cambium colonization, and report putative virulence factors, extensive regulation of horizontally acquired and wood-decay related genes as well as novel pathogenicity-induced small secreted proteins (PiSSPs). Two PiSSPs induced necrosis in live plants, suggesting they are potential virulence effectors conserved across Armillaria. Overall, this study details how evolution knitted together horizontally and vertically inherited genes in complex adaptive traits, such as plant biomass degradation and pathogenicity, paving the way for development of infection models for one of the most influential pathogens of temperate forest ecosystems.

genomics↗