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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Engineering Rhodosporidium toruloides for production of 3-hydroxypropionic acid from lignocellulosic hydrolysate

Microbial production of valuable bioproducts is a promising route towards green and sustainable manufacturing. The oleaginous yeast, Rhodosporidium toruloides, has emerged as an attractive host for the production of biofuels and bioproducts from lignocellulosic hydrolysates. 3-hydroxypropionic acid (3HP) is an attractive platform molecule that can be used to produce a wide range of commodity chemicals. This study focuses on establishing and optimizing the production of 3HP in R. toruloides. As R. toruloides naturally has a high metabolic flux towards malonyl-CoA, we exploited this pathway to produce 3HP. Upon finding the yeast capable of catabolizing 3HP, we then implemented functional genomics and metabolomic analysis to identify the catabolic pathways. Deletion of a putative malonate semialdehyde dehydrogenase gene encoding an oxidative 3HP pathway was found to significantly reduce 3HP degradation. We further explored monocarboxylate transporters to promote 3HP transport and identified a novel 3HP transporter in Aspergillus pseudoterreus by RNA-seq and proteomics. Combining these engineering efforts with media optimization in a fed-batch fermentation resulted in 45.4 g/L 3HP production. This represents one of the highest 3HP titers reported, and the highest titer produced from lignocellulosic hydrolysate to the best of our knowledge. This work demonstrates microbial production of 3HP in R. toruloides from lignocellulosic hydrolysate at high titers, and it represents a significant step toward enabling industrial production of 3HP in the future.

3-Hydroxypropionic acid↗
DOE OSTI2024

Spatial co-transcriptomics reveals discrete stages of the arbuscular mycorrhizal symbiosis

Abstract The symbiotic interaction of plants with arbuscular mycorrhizal (AM) fungi is ancient and widespread. Plants provide AM fungi with carbon in exchange for nutrients and water, making this interaction a prime target for crop improvement. However, plant–fungal interactions are restricted to a small subset of root cells, precluding the application of most conventional functional genomic techniques to study the molecular bases of these interactions. Here we used single-nucleus and spatial RNA sequencing to explore both Medicago truncatula and Rhizophagus irregularis transcriptomes in AM symbiosis at cellular and spatial resolution. Integrated, spatially registered single-cell maps revealed infected and uninfected plant root cell types. We observed that cortex cells exhibit distinct transcriptome profiles during different stages of colonization by AM fungi, indicating dynamic interplay between both organisms during establishment of the cellular interface enabling successful symbiosis. Our study provides insight into a symbiotic relationship of major agricultural and environmental importance and demonstrates a paradigm combining single-cell and spatial transcriptomics for the analysis of complex organismal interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Microbial production of advanced biofuels

Concerns over climate change have necessitated a rethinking of our transportation infrastructure. One possible alternative to carbon-polluting fossil fuels is biofuels produced by engineered microorganisms that use a renewable carbon source. Two biofuels, ethanol and biodiesel, have made inroads in displacing petroleum-based fuels, but their uptake has been limited by the amounts that can be used in conventional engines and by their cost. Further, advanced biofuels that mimic petroleum-based fuels are not limited by the amounts that can be used in existing transportation infrastructure but have had limited uptake due to costs. In this Review, we discuss engineering metabolic pathways to produce advanced biofuels, challenges with substrate and product toxicity with regard to host microorganisms and methods to engineer tolerance, and the use of functional genomics and machine learning approaches to produce advanced biofuels and prospects for reducing their costs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Knowledge graph-aided Bayesian active learning for top- K genetic interaction discovery

In silico methods for predicting the effects of multi-gene perturbations hold great promise for advancing functional genomics, computational drug discovery, and disease modeling. However, the development of these predictive algorithms for mammalian systems has been hampered by limited datasets and high experimental costs. In this study, we present a Bayesian active learning framework designed to discover pairwise host gene knockdowns that effectively inhibit viral proliferation in an in vitro HIV-1 infection model. Our method leverages a biological knowledge graph as side information and employs a computationally efficient batch diversification approach. We evaluated this framework using a dataset of viral load measurements obtained from multi-day dual-gene depletion experiments, encompassing all possible pairwise knockdowns of over 350 host genes associated with HIV infection. We demonstrate that our framework rapidly identifies the most effective gene knockdown pairs for reducing viral load. Furthermore, we show that incorporating side information enhances performance during the early stages of active learning (low data regime), while our batch diversification strategy significantly boosts performance in later stages (high data regime). This framework is general and can be adapted to explore gene interactions in other contexts, such as synthetic lethality prediction and mapping epistatic effects across quantitative trait loci.

Computational biology and bioinformatics↗
DOE OSTI2022

Engineering Pseudomonas putida KT2440 for chain length tailored free fatty acid and oleochemical production

Abstract Despite advances in understanding the metabolism of Pseudomonas putida KT2440, a promising bacterial host for producing valuable chemicals from plant-derived feedstocks, a strain capable of producing free fatty acid-derived chemicals has not been developed. Guided by functional genomics, we engineered P. putida to produce medium- and long-chain free fatty acids (FFAs) to titers of up to 670 mg/L. Additionally, by taking advantage of the varying substrate preferences of paralogous native fatty acyl-CoA ligases, we employed a strategy to control FFA chain length that resulted in a P. putida strain specialized in producing medium-chain FFAs. Finally, we demonstrate the production of oleochemicals in these strains by synthesizing medium-chain fatty acid methyl esters, compounds useful as biodiesel blending agents, in various media including sorghum hydrolysate at titers greater than 300 mg/L. This work paves the road to produce high-value oleochemicals and biofuels from cheap feedstocks, such as plant biomass, using this host.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

acCRISPR: an activity-correction method for improving the accuracy of CRISPR screens

Abstract High throughput CRISPR screens are revolutionizing the way scientists unravel the genetic underpinnings of engineered and evolved phenotypes. One of the critical challenges in accurately assessing screening outcomes is accounting for the variability in sgRNA cutting efficiency. Poorly active guides targeting genes essential to screening conditions obscure the growth defects that are expected from disrupting them. Here, we develop acCRISPR, an end-to-end pipeline that identifies essential genes in pooled CRISPR screens using sgRNA read counts obtained from next-generation sequencing. acCRISPR uses experimentally determined cutting efficiencies for each guide in the library to provide an activity correction to the screening outcomes via calculation of an optimization metric, thus determining the fitness effect of disrupted genes. CRISPR-Cas9 and -Cas12a screens were carried out in the non-conventional oleaginous yeast Yarrowia lipolytica and acCRISPR was used to determine a high-confidence set of essential genes for growth under glucose, a common carbon source used for the industrial production of oleochemicals. acCRISPR was also used in screens quantifying relative cellular fitness under high salt conditions to identify genes that were related to salt tolerance. Collectively, this work presents an experimental-computational framework for CRISPR-based functional genomics studies that may be expanded to other non-conventional organisms of interest.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Phenylpropanoid methyl esterase unlocks catabolism of aromatic biological nitrification inhibitors

Microbial nitrification of fertilizers represents is a significant global source of greenhouse gas emissions. This process increases emissions, fosters toxic algal blooms, and raises crop production costs. Some plants naturally release biological nitrification inhibitors to suppress ammonium-oxidizing microbes and reduce nitrification. Engineering nitrification inhibitor production into food and bioenergy crops via synthetic biology offers a promising mitigation strategy, but its success depends on addressing gaps in our understanding of inhibitor degradation in soil. This study begins to fill this gap by identifying a previously unknown microbial pathway for degrading phenylpropanoid methyl esters, a key class of aromatic nitrification inhibitors. Using transcriptomics and high-throughput functional genomics, we discovered genes essential for phenylpropanoid methyl ester degradation. Genetic and biochemical analyses revealed two novel enzymes, including a newly identified phenylpropanoid methyl esterase, that direct phenylpropanoid methyl esters into known metabolic pathways. Importantly, transferring these genes into bacteria capable of metabolizing other phenylpropanoids enabled them to use the methyl esters as a carbon source. This work provides critical insights into microbial nitrification inhibitor degradation, a poorly understood element of the nitrification cycle.

Genetic Engineering↗
DOE OSTI2021

Predictive Models of Genetic Redundancy in Arabidopsis thaliana

Abstract Genetic redundancy refers to a situation where an individual with a loss-of-function mutation in one gene (single mutant) does not show an apparent phenotype until one or more paralogs are also knocked out (double/higher-order mutant). Previous studies have identified some characteristics common among redundant gene pairs, but a predictive model of genetic redundancy incorporating a wide variety of features derived from accumulating omics and mutant phenotype data is yet to be established. In addition, the relative importance of these features for genetic redundancy remains largely unclear. Here, we establish machine learning models for predicting whether a gene pair is likely redundant or not in the model plant Arabidopsis thaliana based on six feature categories: functional annotations, evolutionary conservation including duplication patterns and mechanisms, epigenetic marks, protein properties including posttranslational modifications, gene expression, and gene network properties. The definition of redundancy, data transformations, feature subsets, and machine learning algorithms used significantly affected model performance based on holdout, testing phenotype data. Among the most important features in predicting gene pairs as redundant were having a paralog(s) from recent duplication events, annotation as a transcription factor, downregulation during stress conditions, and having similar expression patterns under stress conditions. We also explored the potential reasons underlying mispredictions and limitations of our studies. This genetic redundancy model sheds light on characteristics that may contribute to long-term maintenance of paralogs, and will ultimately allow for more targeted generation of functionally informative double mutants, advancing functional genomic studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Three-dimensional structure of a flavivirus dumbbell RNA reveals molecular details of an RNA regulator of replication

Abstract Mosquito-borne flaviviruses (MBFVs) including dengue, West Nile, yellow fever, and Zika viruses have an RNA genome encoding one open reading frame flanked by 5′ and 3′ untranslated regions (UTRs). The 3′ UTRs of MBFVs contain regions of high sequence conservation in structured RNA elements known as dumbbells (DBs). DBs regulate translation and replication of the viral RNA genome, functions proposed to depend on the formation of an RNA pseudoknot. To understand how DB structure provides this function, we solved the x-ray crystal structure of the Donggang virus DB to 2.1Å resolution and used structural modeling to reveal the details of its three-dimensional fold. The structure confirmed the predicted pseudoknot and molecular modeling revealed how conserved sequences form a four-way junction that appears to stabilize the pseudoknot. Single-molecule FRET suggests that the DB pseudoknot is a stable element that can regulate the switch between translation and replication during the viral lifecycle by modulating long-range RNA conformational changes.

Akiyama, Benjamin M.↗
DOE OSTI2022

‘ Candidatus Liberibacter asiaticus’-Encoded BCP Peroxiredoxin Suppresses Lipopolysaccharide-Mediated Defense Signaling and Nitrosative Stress In Planta

The lipopolysaccharides (LPS) of gram-negative bacteria trigger a nitrosative and oxidative burst in both animals and plants during pathogen invasion. Liberibacter crescens strain BT-1 is a surrogate for functional genomic studies of the uncultured pathogenic ‘Candidatus Liberibacter’ spp. that are associated with severe diseases such as citrus greening and potato zebra chip. Structural determination of L. crescens LPS revealed the presence of a very long chain fatty acid modification. L. crescens LPS pretreatment suppressed growth of Xanthomonas perforans on nonhost tobacco (Nicotiana benthamiana) and X. citri subsp. citri on host orange (Citrus sinensis), confirming bioactivity of L. crescens LPS in activation of systemic acquired resistance (SAR). L. crescens LPS elicited a rapid burst of nitric oxide (NO) in suspension cultured tobacco cells. Pharmacological inhibitor assays confirmed that arginine-utilizing NO synthase (NOS) activity was the primary source of NO generation elicited by L. crescens LPS. LPS treatment also resulted in biological markers of NO-mediated SAR activation, including an increase in the glutathione pool, callose deposition, and activation of the salicylic acid and azelaic acid (AzA) signaling networks. Transient expression of ‘Ca. L. asiaticus’ bacterioferritin comigratory protein (BCP) peroxiredoxin in tobacco compromised AzA signaling, a prerequisite for LPS-triggered SAR. Western blot analyses revealed that ‘Ca. L. asiaticus’ BCP peroxiredoxin prevented peroxynitrite-mediated tyrosine nitration in tobacco. ‘Ca. L. asiaticus’ BCP peroxiredoxin (i) attenuates NO-mediated SAR signaling and (ii) scavenges peroxynitrite radicals, which would facilitate repetitive cycles of ‘Ca. L. asiaticus’ acquisition and transmission by fecund psyllids throughout the limited flush period in citrus.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Convergence in simulating global soil organic carbon by structurally different models after data assimilation

Abstract Current biogeochemical models produce carbon–climate feedback projections with large uncertainties, often attributed to their structural differences when simulating soil organic carbon (SOC) dynamics worldwide. However, choices of model parameter values that quantify the strength and represent properties of different soil carbon cycle processes could also contribute to model simulation uncertainties. Here, we demonstrate the critical role of using common observational data in reducing model uncertainty in estimates of global SOC storage. Two structurally different models featuring distinctive carbon pools, decomposition kinetics, and carbon transfer pathways simulate opposite global SOC distributions with their customary parameter values yet converge to similar results after being informed by the same global SOC database using a data assimilation approach. The converged spatial SOC simulations result from similar simulations in key model components such as carbon transfer efficiency, baseline decomposition rate, and environmental effects on carbon fluxes by these two models after data assimilation. Moreover, data assimilation results suggest equally effective simulations of SOC using models following either first‐order or Michaelis–Menten kinetics at the global scale. Nevertheless, a wider range of data with high‐quality control and assurance are needed to further constrain SOC dynamics simulations and reduce unconstrained parameters. New sets of data, such as microbial genomics‐function relationships, may also suggest novel structures to account for in future model development. Overall, our results highlight the importance of observational data in informing model development and constraining model predictions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

An efficient virus–induced gene silencing (VIGS) system for gene functional studies in Miscanthus

Virus-induced gene silencing (VIGS) is a powerful tool for transient gene functional analysis in plants, especially for monocot species (e.g., grasses) that are recalcitrant to transformation. Despite various VIGS systems that have been developed in different plant species, none was previously available for the bioenergy crop Miscanthus. Here, we report the establishment of an efficient and robust VIGS system mediated by Tobacco Rattle Virus (TRV) in Miscanthus. We first investigated the impact of various factors that may affect gene silencing efficiency using the Miscanthus sinensis Phytoene Desaturase (MsPDS) gene as a visual indicator of photobleaching. Then, we optimized the TRV-elicited VIGS procedure using an orthogonal experimental design with four factors (sprout size, Agrobacterium concentration, vacuum infiltration time, and co-incubation time) each at three levels. The following led to the highest silencing efficiency (~76%): inoculation of germinating seedlings (1.0–2.0 mm), Agrobacterium tumefaciens culture grown to optical density at 600 nm (OD 600 ) of 0.4, vacuum infiltration for 90 min, and co-incubation for 5 h. The VIGS system established was applicable for both M. sinensis and M. lutarioriparius, with comparable gene silencing efficiency. We verified the efficacy of the VIGS system via the functional characterization of the role of a MYB transcription factor, MsMYB112, in salt stress tolerance. Expression of MsMYB112 was successfully knocked down using the VIGS system, and this led to compromised salt tolerance in the silenced Miscanthus plants. The TRV-based VIGS system established may, therefore, substantially facilitate functional genomic studies in Miscanthus.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

TbsP and TrmB jointly regulate gapII to influence cell development phenotypes in the archaeon Haloferax volcanii

Abstract Microbial cells must continually adapt their physiology in the face of changing environmental conditions. Archaea living in extreme conditions, such as saturated salinity, represent important examples of such resilience. The model salt‐loving organism Haloferax volcanii exhibits remarkable plasticity in its morphology, biofilm formation, and motility in response to variations in nutrients and cell density. However, the mechanisms regulating these lifestyle transitions remain unclear. In prior research, we showed that the transcriptional regulator, TrmB, maintains the rod shape in the related species Halobacterium salinarum by activating the expression of enzyme‐coding genes in the gluconeogenesis metabolic pathway. In Hbt. salinarum , TrmB‐dependent production of glucose moieties is required for cell surface glycoprotein biogenesis. Here, we use a combination of genetics and quantitative phenotyping assays to demonstrate that TrmB is essential for growth under gluconeogenic conditions in Hfx. volcanii . The ∆ trmB strain rapidly accumulated suppressor mutations in a gene encoding a novel transcriptional regulator, which we name t rm B s u p pressor, or TbsP (a.k.a. “tablespoon”). TbsP is required for adhesion to abiotic surfaces (i.e., biofilm formation) and maintains wild‐type cell morphology and motility. We use functional genomics and promoter fusion assays to characterize the regulons controlled by each of TrmB and TbsP, including joint regulation of the glucose‐dependent transcription of gapII , which encodes an important gluconeogenic enzyme. We conclude that TrmB and TbsP coregulate gluconeogenesis, with downstream impacts on lifestyle transitions in response to nutrients in Hfx. volcanii .

Biochemistry & Molecular Biology↗
DOE OSTI2022

Capturing an Early Gene Induction Event during Wood Decay by the Brown Rot Fungus Rhodonia placenta

Brown rot fungi dominate wood decomposition in coniferous forests, and their carbohydrate-selective mechanisms are of commercial interest. Brown rot was recently described as a two-step, sequential mechanism orchestrated by fungi using differentially expressed genes (DEGs) and consisting of oxidation via reactive oxygen species (ROS) followed by enzymatic saccharification. There have been indications, however, that the initial oxidation step itself might require induction. To capture this early gene regulation event, here, we integrated fine-scale cryosectioning with whole-transcriptome sequencing to dissect gene expression at the single-hyphal-cell scale (tens of micrometers). This improved the spatial resolution 50-fold, relative to previous work, and we were able to capture the activity of the first 100 μm of hyphal front growth by Rhodonia placenta in aspen wood. This early decay period was dominated by delayed gene expression patterns as the fungus ramped up its mechanism. These delayed DEGs included many genes implicated in ROS pathways (lignocellulose oxidation [LOX]) that were previously and incorrectly assumed to be constitutively expressed. These delayed DEGs, which include those with and without predicted functions, also create a focused subset of target genes for functional genomics. However, this delayed pattern was not universal, with a few genes being upregulated immediately at the hyphal front. Most notably, this included a gene commonly implicated in hydroquinone and iron redox cycling: benzoquinone reductase.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Development of a Markerless Deletion Mutagenesis System in Nitrate-Reducing Bacterium Rhodanobacter denitrificans

Rhodanobacter has been found as the dominant genus in aquifers contaminated with high concentrations of nitrate and uranium in Oak Ridge, TN, USA. The in situ stimulation of denitrification has been proposed as a potential method to remediate nitrate and uranium contamination. Among the Rhodanobacter species, Rhodanobacter denitrificans strains have been reported to be capable of denitrification and contain abundant metal resistance genes. However, due to the lack of a mutagenesis system in these strains, our understanding of the mechanisms underlying low-pH resistance and the ability to dominate in the contaminated environment remains limited. Here, we developed an in-frame markerless deletion system in two R. denitrificans strains. First, we optimized the growth conditions, tested antibiotic resistance, and determined appropriate transformation parameters in 10 Rhodanobacter strains. We then deleted the upp gene, which encodes uracil phosphoribosyltransferase, in R. denitrificans strains FW104-R3 and FW104-R5. The resulting strains were designated R3_Δupp and R5_Δupp and used as host strains for mutagenesis with 5-fluorouracil (5-FU) resistance as the counterselection marker to generate markerless deletion mutants. Further, to test the developed protocol, the narG gene encoding nitrate reductase was knocked out in the R3_Δupp and R5_Δupp host strains. As expected, the narG mutants could not grow in anoxic medium with nitrate as the electron acceptor. Overall, these results show that the in-frame markerless deletion system is effective in two R. denitrificans strains, which will allow for future functional genomic studies in these strains furthering our understanding of the metabolic and resistance mechanisms present in Rhodanobacter species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A transcriptomic atlas of acute stress response to low pH in multiple Issatchenkia orientalis strains

Because of its natural stress tolerance to low pH, Issatchenkia orientalis (a.k.a. Pichia kudriavzevii) is a promising non-model yeast for bio-based production of organic acids. Yet, this organism is relatively unstudied, and specific mechanisms of its tolerance to low pH are poorly understood, limiting commercial use. In this study, we selected 12 I. orientalis strains with varying acid stress tolerance (six tolerant and six susceptible) and profiled their transcriptomes in different pH conditions to study potential mechanisms of pH tolerance in this species. We identified hundreds of genes whose expression response is shared by tolerant strains but not by susceptible strains, or vice versa, as well as genes whose responses are reversed between tolerant and susceptible strains. We mapped regulatory mechanisms of transcriptomic responses via motif analysis as well as differential network reconstruction, identifying several transcription factors, including Stb5, Mac1, and Rtg1/Rtg3, some of which are known for their roles in acid response in Saccharomyces cerevisiae. Functional genomics analysis of short-listed genes and transcription factors suggested significant roles for energy metabolism and translation-related processes, as well as the cell wall integrity pathway and RTG-dependent retrograde signaling pathway. Finally, we conducted additional experiments for two organic acids, 3-hydroxypropionate and citramalate, to eliminate acid-specific effects and found potential roles for glycolysis and trehalose biosynthesis specifically for response to low pH. In summary, our approach of comparative transcriptomics and phenotypic contrasting, along with a multi-pronged bioinformatics analysis, suggests specific mechanisms of tolerance to low pH in I. orientalis that merit further validation through experimental perturbation and engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

RolyPoly (rp) v0.1.0

The Rolypoly pipeline is designed to process raw RNA-seq data and identify potential RNA viral sequences. It is split into several self contained steps: 1. input data filtering and QC, 2. Genome assembly and refinement, 3. Assembly filtering, 4. Mapping to known RNA viral genomes, 5. Searching for RNA viral marker genes. 6. Genome functional and structural annotation. 6. Report preparation and potential downstream analysis The last module, may include taxonomic assignment, host range estimation, and phenotypic prediction. There are many similar software, but they focus on human related viruses, and lack the downstream applications or differ in their sensitivity. The initial user base are non-computational microbial ecologists who wish to better understand the potential RNA viruses in their own generated samples.

Neri, Uri↗
DOE OSTI2024

A Functional Survey of the Regulatory Landscape of Estrogen Receptor–Positive Breast Cancer Evolution

Abstract Only a handful of somatic alterations have been linked to endocrine therapy resistance in hormone-dependent breast cancer, potentially explaining ∼40% of relapses. If other mechanisms underlie the evolution of hormone-dependent breast cancer under adjuvant therapy is currently unknown. In this work, we employ functional genomics to dissect the contribution of cis-regulatory elements (CRE) to cancer evolution by focusing on 12 megabases of noncoding DNA, including clonal enhancers, gene promoters, and boundaries of topologically associating domains. Parallel epigenetic perturbation (CRISPRi) in vitro reveals context-dependent roles for many of these CREs, with a specific impact on dormancy entrance and endocrine therapy resistance. Profiling of CRE somatic alterations in a unique, longitudinal cohort of patients treated with endocrine therapies identifies a limited set of noncoding changes potentially involved in therapy resistance. Overall, our data uncover how endocrine therapies trigger the emergence of transient features which could ultimately be exploited to hinder the adaptive process. Significance: This study shows that cells adapting to endocrine therapies undergo changes in the usage or regulatory regions. Dormant cells are less vulnerable to regulatory perturbation but gain transient dependencies which can be exploited to decrease the formation of dormant persisters.

Oncology↗