Biology subjects

Abraham, P. E.

Publications and source records attributed to Abraham, P. E..

14 recordsLinked to original sources

bioRxiv2026

The Everything Bagel Feature Finder: Ultra-fast automated feature finding for untargeted metabolomics

Metabolomics studies are increasingly being applied with hundreds to thousands, even tens of thousands of samples that demand rapid, automated data processing while maintaining analytical sensitivity or quantitative accuracy. A major computational bottleneck is feature finding, which is the transformation of LC-MS and LC-MS/MS data into a set of analyte signals aligned and quantified across samples. Feature finding can be computationally intensive and often requires manual iterative parameter optimization. To accelerate this process, we present the Everything Bagel (EB) feature finder, an ultra-fast automated feature finding tool that integrates feature detection, retention-time alignment, and gap filling designed for run-time and memory efficiency. We benchmarked EB against two automated feature finding methods on eight benchmarking datasets. Specifically, we evaluated these three feature finding methods by measuring spike-in standard detection coverage, dilution series quantification accuracy, and yeast 12C/13C credentialed features. In this evaluation, the EB feature finder achieved performance comparable to, and often exceeding, existing methods while requiring up to 150-fold lower CPU hours and up to 113-fold lower wall time. We further demonstrated the bioanalytical validity of EB by reanalyzing published datasets used for biomarker discovery and reproduced biologically significant features that matched the published findings using manually tuned feature finding settings. Taken along with the speed improvements, we anticipate EB will enhance the ability to automatically analyze datasets with thousands to tens of thousands of samples for the community.

bioinformatics↗

bioRxiv2025

Genome shuffling enables quantitative trait locus mapping in Bacillus subtilis

Genetic mapping is a powerful tool for eukaryotic genetics that has only been applied to bacteria in limited circumstances. Quantitative trait locus (QTL) mapping generally relies on sexual recombination to break linkages between genes, yet bacteria rarely undergo sufficient homologous recombination to generate suitable mapping populations. In this work, we used iterative biparental genome shuffling by protoplast fusion in Bacillus subtilis to generate a population of bacteria with substantial random recombination throughout their genomes. Individual shuffled progeny were arrayed in well plates, resequenced, and characterized for a range of complex phenotypes including spore germination and swarming motility. Genetic mapping of the resulting phenotypes identified high-confidence QTLs of moderate size ([~]10 kb), and these associations were validated through targeted genetic swaps. This B. subtilis QTL population can easily be used to map additional phenotypes, and the general approach for QTL mapping is applicable in a wide range of bacteria. One-Sentence SummaryBacterial genome shuffling mimics sexual recombination and enables genetic mapping of complex phenotypes to causal alleles.

microbiology↗

bioRxiv2025

Microbial Modulation of Host Plant Proteasome Activity Improves Heat Stress Tolerance

Global climate change marked by rising temperatures and increasingly frequent, severe heat waves, threatens plant health, productivity, and ecosystem function. Beneficial plant-microbe associations are increasingly recognized for their role in mitigating abiotic stress, yet the molecular mechanisms underlying microbially-conferred thermotolerance remain poorly understood. Here, we developed a population-based assay using Sphagnum peat mosses, a key species in peatland ecosystems that sequester 33-50% of the worlds soil carbon as recalcitrant peat, to perform microbiome transfers and assess microbial contributions to heat resilience. Strain-based assays in Sphagnum and Arabidopsis identified Variovorax as a key thermotolerance-enhancing microbe and identified ECM29, a proteasome-associated protein, as critical for this interaction. In Arabidopsis, Variovorax sp. CF313 association led to ECM29 preferentially binding the RPT1 subunit of the 19S regulatory particle, inhibiting 20S proteasome gate opening and slightly reducing proteasomal activity. This results in the accumulation of ubiquitinated proteins and induces HSP70 transcription, priming the host for heat shock stress even in the absence of prior heat exposure. These findings establish ECM29 as a key regulator of proteasome activity in response to microbial interactions, highlighting a previously unknown mechanism by which microbes enhance plant thermotolerance. More broadly, this work highlights the importance of leveraging natural systems and ecologically relevant models to identify strategies for enhancing plant and ecosystem resilience to a changing climate. Significance StatementGlobal climate change poses severe threats to plant health and productivity, with cascading impacts on ecosystems. Beneficial plant-microbe interactions offer promising strategies to mitigate abiotic stress, yet the molecular mechanisms often remain unclear. This study uncovers a novel thermotolerance mechanism mediated by Variovorax modulating the plant host proteasome. Using a QTL derived from Sphagnum peat mosses, and tested within a genetically tractable Arabidopsis model, we identified ECM29, a highly conserved protein across diverse plant species, as a key regulator of proteasome activity. ECM29 primes plants for heat stress by inducing HSP70 transcription through proteasome modulation. Additionally, we demonstrated that ECM29 is required for the host to receive microbially conferred thermotolerance, but is not necessary for innate priming to heat stress. These findings highlight the potential of leveraging natural systems and ecologically relevant species to develop innovative genetic models, advancing plant resilience and productivity in a warming world.

plant biology↗

bioRxiv2024

Ribozyme-based biosensor for imaging gene expression in plants

Detection of gene expression in plants is critical for understanding the molecular basis of complex plant biosystems and plant responses to environmental stresses. Here, we report the development of a split ribozyme-based biosensor that enables in vivo visualization of gene expression in plants. We demonstrated the utility of this biosensor in transient expression experiments (i.e., leaf infiltration in Nicotiana benthamiana) to detect RNAs derived from transgenes and tobacco rattle virus, respectively. Furthermore, we successfully engineered a split ribozyme-based biosensor in Arabidopsis thaliana for in vivo visualization of endogenous gene expression at the cellular level. In addition, we developed a platform for easy incorporation of different reporters into the RNA biosensor.

synthetic biology↗

bioRxiv2024

High-density CRISPRi screens reveal adaptive transcriptional gradients in cyanobacteria

Cyanobacteria are the oldest form of photosynthetic life on Earth and contribute to primary production in nearly every habitat, from permafrost to hot springs. Despite longstanding interest in the biochemical basis of environmental adaptation in these microbes, it remains poorly understood and challenging to re-wire. This study uses a high-density, genome-wide CRISPR interference (CRISPRi) screen to examine the influence of gene-specific transcriptional variation on the growth of Synechococcus sp. PCC 7002 under environmental extrema. Surprisingly, many partial knockdowns enhanced fitness under cold monochromatic conditions. Notably, transcriptional repression of a gene for a core subunit of the NDH-1 complex, which is important for photosynthesis and carbon uptake, improved growth rates under both red and blue light but at distinct, color-specific optima. In general, most genes with fitness-improving knockdowns were distinct to each light color, evidencing unique stress responses and alleviation mechanisms. Multi-target transcriptional repression produced nonadditive effects. Findings reveal diverse mechanisms of environmental adaptation in cyanobacteria and provide a new approach for using gradients in sgRNA activity to pinpoint biochemically influential transcriptional changes in cells. SIGNIFICANCE STATEMENTCyanobacteria are the most abundant photosynthetic organisms on Earth, where they endure a striking variety of environmental fluctuations. This study examines the biochemical basis of environmental adaptation in Synechococcus sp. PCC 7002, an important model strain, by modulating the expression of every gene in its genome. Results show that partial, but not complete, reduction in the expression of a subset of influential genes can improve growth under cold monochromatic conditions. Optimal expression levels differ between red and blue light and shift with multi-gene adjustments. Findings show how minor transcriptional adjustments can yield major improvements in growth under environmental extrema and provide a powerful systems-level approach for studying--and fine-tuning--the adaptive capacity of microbes.

microbiology↗

bioRxiv2024

Catabolic pathway acquisition by soil pseudomonads readily enables growth with salicyl alcohol but does not affect colonization of Populus roots

Horizontal gene transfer (HGT) is a fundamental evolutionary process that plays a key role in bacterial evolution. The likelihood of a successful transfer event is expected to depend on the precise balance of costs and benefits resulting from pathway acquisition. Most experimental analyses of HGT have focused on phenotypes that have large fitness benefits under appropriate selective conditions, such as antibiotic resistance. However, many examples of HGT involve phenotypes that are predicted to provide smaller benefits, such as the ability to catabolize additional carbon sources. We have experimentally reproduced one such HGT event in the laboratory, studying the effects of transferring a pathway for catabolism of the plant-derived aromatic compound salicyl alcohol into soil isolates from the Pseudomonas genus. We find that pathway acquisition enables rapid catabolism of salicyl alcohol with only minor disruptions to existing metabolic and regulatory networks of the new host. However, this new catabolic potential does not confer a measurable fitness advantage during competitive growth in the rhizosphere. We conclude that the phenotype of salicyl alcohol catabolism is readily transferred by HGT but is selectively neutral under environmentally-relevant conditions. We propose that this condition is common and that HGT of many pathways will be self-limiting, because the selective benefits are small and negative frequency-dependent.

microbiology↗

bioRxiv2023

Decoding the chemical language of Suillus fungi: genome mining and untargeted metabolomics uncover terpene chemical diversity

Ectomycorrhizal fungi establish mutually beneficial relationships with trees, trading nutrients for carbon. Suillus are ectomycorrhizal fungi that are critical to the health of boreal and temperate forest ecosystems. Comparative genomics has identified a high number of non-ribosomal peptide synthetase and terpene biosynthetic gene clusters (BGC) potentially involved in fungal competition and communication. However, the functionality of these BGCs is not known. This study employed co-culture techniques to activate BGC expression and then used metabolomics to investigate the diversity of metabolic products produced by three Suillus species (S. hirtellus EM16, S. decipiens EM49, and S. cothurnatus VC1858), core members of the Pine microbiome. After 28 days of growth on solid media, liquid chromatography-tandem mass spectrometry identified a diverse range of extracellular metabolites (exometabolites) along the interaction zone between Suillus co-cultures. Prenol lipids were among the most abundant chemical classes. Out of the 62 unique terpene BGCs predicted by genome mining, 116 putative terpenes were identified across the three Suillus species using metabolomics. Notably, some terpenes were significantly more abundant in co-culture conditions. For example, we identified a metabolite matching to isomers isopimaric acid, sandaracopimaric acid, and abietic acid, which can be found in pine resin and play important roles in host defense mechanisms and Suillus spore germination. This research highlights the importance of combining genomics and metabolomics to advance our understanding of the chemical diversity underpinning fungal signaling and communication. ImportanceUsing a combination of genomics and metabolomics, this studys findings offer new insights into the signaling and communication of Suillus fungi, which serve a critical role in forest ecosystems.

microbiology↗

bioRxiv2023

A phosphorylation-deficient ribosomal protein eS6 is largely functional in Arabidopsis thaliana, rescuing mutant defects from global translation and gene expression to photosynthesis and growth

The eukaryote-specific ribosomal protein of the small subunit eS6 is phosphorylated through the Target of rapamycin (TOR) kinase pathway. Although this phosphorylation event responds dynamically to environmental conditions and has been studied for over 50 years, its biochemical and physiological significance remains controversial and poorly understood. Here we report data from Arabidopsis thaliana, which indicate that plants expressing only a largely phospho-deficient isoform of eS6 grow essentially normally under laboratory conditions. The eS6A (RPS6A) paralog of eS6 functionally rescued double mutations in both rps6a and rps6b genes when expressed at approximately twice the wild-type dosage. A mutant isoform of eS6A lacking the major six phosphorylatable serine and threonine residues in its carboxyl-terminal tail also rescued the lethality, rosette growth, and polyribosome loading of the double mutant. It also complemented many mutant phenotypes of rps6 that were newly characterized here, including photosynthetic efficiency, and the vast majority of gene expression defects that were measured by transcriptomics and proteomics. However, compared to plants rescued with a phospho-enabled version of eS6A, the phospho-deficient seedlings retained a mild pointed-leaf phenotype, root growth was reduced, and certain cell cycle related mRNAs and ribosome biogenesis proteins were misexpressed. The residual defects of the phospho-deficient seedlings could be understood as an incomplete rescue of the rps6 mutant defects, with little or no evidence for gain-of-function defects. As expected, the phospho-deficient eS6A also rescued the rps6a and rps6b single mutants; however, phosphorylation of the eS6B paralog remained lower than predicted, further underscoring that plants can tolerate phospho-deficiency of eS6 well. Our data also yield new insights into how plants cope with mutations in essential, duplicated ribosomal protein isoforms.

plant biology↗

bioRxiv2023

Functional analysis of Salix purpurea genes support roles for ARR17 and GATA15 as master regulators of sex determination

The Salicaceae family is of growing interest in the study of dioecy in plants because the sex determination region (SDR) has been shown to be highly dynamic, with differing locations and heterogametic systems between species. Without the ability to transform and regenerate Salix in tissue culture, previous studies investigating the mechanisms regulating sex in the genus Salix have been limited to genome resequencing and differential gene expression, which are mostly descriptive in nature, and functional validation of candidate sex determination genes has not yet been conducted. Here we used Arabidopsis to functionally characterize a suite of previously identified candidate genes involved in sex determination and sex dimorphism in the bioenergy shrub willow Salix purpurea. Six candidate master regulator genes for sex determination were heterologously expressed in Arabidopsis, followed by floral proteome analysis. In addition, 11 transcription factors with predicted roles in mediating sex dimorphism downstream of the SDR were tested using DAP-Seq in both male and female S. purpurea DNA. The results of this study provide further evidence to support models for the roles of ARR17 and GATA15 as master regulator genes of sex determination in S. purpurea, contributing to a regulatory system that is notably different from that of its sister genus Populus. Evidence was also obtained for the roles of two transcription factors, an AP2/ERF family gene and a homeodomain-like transcription factor, in downstream regulation of sex dimorphism.

plant biology↗

bioRxiv2022

Fungal antibiotics control bacterial community diversity in the cheese rind microbiome

Potent antimicrobial metabolites are produced by filamentous fungi in pure lab cultures, but their ecological functions in nature are often unknown. Using an antibiotic-producing Penicillium isolate and the cheese rind microbial community, we demonstrate that a fungal specialized metabolite can regulate the diversity of bacterial communities. Inactivation of the global regulator, LaeA, resulted in the loss of antibacterial activity in the Penicillium isolate. Cheese rind bacterial communities assembled with the laeA deletion strain had significantly higher bacterial abundances than the wild-type strain. RNA-sequencing and metabolite profiling demonstrated a striking reduction in the expression and production of the natural product pseurotin in the laeA deletion strain. Inactivation of a core gene in the pseurotin biosynthetic cluster restored bacterial community composition, demonstrating the role of pseurotins in mediating bacterial community assembly. Our discovery demonstrates how antibiotic production can drive the assembly of microbiomes and provides an ecological context for widespread fungal specialized metabolites.

microbiology↗

bioRxiv2022

A guidance into the fungal metabolomic abyss: Network analysis for revealing relationships between exogenous compounds and their outputs

AO_SCPLOWBSTRACTC_SCPLOWFungal specialized metabolites include many bioactive compounds with potential applications as pharmaceuticals, agrochemical agents, and industrial chemicals. Exploring and discovering novel fungal metabolites is critical to combat antimicrobial resistance in various fields, including medicine and agriculture. Yet, identifying the conditions or treatments that will trigger the production of specialized metabolites in fungi can be cumbersome since most of these metabolites are not produced under standard culture conditions. Here, we introduce a data-driven algorithm comprising various network analysis routes to characterize the production of known and putative specialized metabolites and unknown analytes triggered by different exogenous compounds. We use bipartite networks to quantify the relationship between the metabolites and the treatments stimulating their production through two routes. The first, called the direct route, determines the production of known and putative specialized metabolites induced by a treatment. The second, called the auxiliary route, is specific for unknown analytes. We demonstrated the two routes by applying chitooligosaccharides and lipids at two different temperatures to the opportunistic human fungal pathogen Aspergillus fumigatus. We used various network centrality measures to rank the treatments based on their ability to trigger a broad range of specialized metabolites. The specialized metabolites were ranked based on their receptivity to various treatments. Altogether, our data-driven techniques can track the influence of any exogenous treatment or abiotic factor on the metabolomic output for targeted metabolite research. This approach can be applied to complement existing LC/MS analyses to overcome bottlenecks in drug discovery and development from fungi. NoticeThis manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). Author summaryTriggering silent biosynthetic gene clusters in fungi to produce specialized metabolites is a tedious process that requires assessing various environmental conditions, applications of epigenetic modulating agents, or co-cultures with other microbes. We provide a data-driven solution using network analysis, called "direct route", to characterize the production of known and putative specialized metabolites triggered by various exogenous compounds. We also provide a "auxiliary route" to distinguish unique unknown analytes amongst the abundantly produced analytes in response to these treatments. The developed techniques can assist researchers to identify treatments or applications that could positively influence the production of a targeted metabolite or recognize unique unknown analytes that can be further fractionated, characterized, and screened for their biological activities and hence, discover new metabolites.

systems biology↗

bioRxiv2021

An intein-mediated split-nCas9 system for base editing in plants

Virus-assisted delivery of the clustered regularly interspaced short palindromic (CRISPR)/CRISPR-associated (Cas) system represents a promising approach for editing plant genomes. However, the relatively large size of the CRISPR/Cas9 system is challenging to package into viral vectors with confined packaging capacity. To address this technical challenge, we developed a strategy that splits the required CRISPR-Cas9 components across a dual-vector system in which CRISPR-Cas reassembles into an active form following co-infection to achieve targeted genome editing in plant cells. An intein-mediated split system was adapted and optimized in plant cells by successfully demonstrating split-eYGFPuv expression. Using a plant-based biosensor, we demonstrated for the first time that the split-SpnCas9 is capable of inducing efficient base editing in plant cells and identified several valid split sites for future biodesign strategies. Overall, this strategy provides new opportunities to bridge different CRISPR/Cas9 tools including base editor, prime editor, and CRISPR activation with virus-mediated gene editing.

plant biology↗

bioRxiv2021

Plant-based biosensors for detecting CRISPR-mediated genome engineering

CRISPR/Cas has recently emerged as the most reliable system for genome engineering in various species. However, concerns about risks associated with CRISPR/Cas9 technology are increasing on potential unintended DNA changes that might accidentally arise from CRISPR gene editing. Developing a system that can detect and report the presence of active CRIPSR/Cas tools in biological systems is therefore very necessary. Here, we developed the real-time detection systems that can spontaneously indicate CRISPR-Cas tools for genome editing and gene regulation including CRISPR/Cas9 nuclease, base editing, prime editing and CRISPRa in plants. Using the fluorescence-based molecular biosensors, we demonstrated that the activities of CRISPR/Cas9 nuclease, base editing, prime editing and CRIPSRa can be effectively detected in transient expression via protoplast transformation and leaf infiltration (in Arabidopsis, poplar, and tobacco) and stable transformation in Arabidopsis.

plant biology↗

bioRxiv2021

Critical Assessment of Metaproteome Investigation (CAMPI): a Multi-Lab Comparison of Established Workflows

Metaproteomics has matured into a powerful tool to assess functional interactions in microbial communities. While many metaproteomic workflows are available, the impact of method choice on results remains unclear. Here, we carried out the first community-driven, multi-laboratory comparison in metaproteomics: the critical assessment of metaproteome investigation study (CAMPI). Based on well-established workflows, we evaluated the effect of sample preparation, mass spectrometry, and bioinformatic analysis using two samples: a simplified, laboratory-assembled human intestinal model and a human fecal sample. We observed that variability at the peptide level was predominantly due to sample processing workflows, with a smaller contribution of bioinformatic pipelines. These peptide-level differences largely disappeared at the protein group level. While differences were observed for predicted community composition, similar functional profiles were obtained across workflows. CAMPI demonstrates the robustness of present-day metaproteomics research, serves as a template for multi-laboratory studies in metaproteomics, and provides publicly available data sets for benchmarking future developments.

microbiology↗