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At least 739 records · Page 41

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DOE OSTI2025

Novosphingobium aromaticivorans LigR coordinates transcription of genes involved in metabolism of multiple types of aromatics

Aromatic compounds are a ubiquitous and diverse family of chemicals with functions as biomolecules, natural products, industrial chemicals, and pollutants. Novosphingobium aromaticivorans DSM 12444 uses multiple inducible pathways to catabolize H-, G-, and S-type aromatics that contain zero, one, or two methoxy groups, respectively. Here, we obtain a systems-level view of the transcriptional control of its aromatic metabolic pathways. Several in vitro analyses found that a N. aromaticivorans homolog of the Sphingobium lignivorans SYK-6 transcription factor LigR bound genomic DNA upstream of genes involved in metabolism of multiple aromatic types. We found that a ΔLigR mutant had growth defects on all three types of aromatics as sole carbon sources. Transcriptomic analysis revealed that LigR was required to increase expression of gene products that function in metabolism of all three aromatic types. We also found that, in media containing both glucose and an aromatic carbon source, the ΔLigR mutant directed intermediates through alternative aromatic metabolic pathways. Protein-DNA binding assays showed that N. aromaticivorans LigR binds immediately upstream of promoters of genes involved in aromatic metabolism. We found that N. aromaticivorans LigR coordinates the expression of enzymes that function in the catabolism of H-, G-, and S-type aromatics, and that there are differences in the role of LigR in N. aromaticivorans and S. lignivorans. A comparative genomic analysis predicted that LigR homologs and the aromatic-metabolizing genes that it directly regulates are often co-localized in the genomes of Sphingomonadales, but often not found in this arrangement in many other known aromatic metabolizing bacteria.

Aromatic Compound Degradation↗

DOE OSTI2026

Salt supplementation-induced metabolic reprogramming in Streptomyces coelicolor

Members of the genus Streptomyces are major producers of a wide variety of secondary metabolites that serve as bioactive compounds. Many secondary metabolites are produced in response to environmental signals such as biotic and abiotic stresses. In this study, we identified salt supplementation as one of the stimuli activating secondary metabolism in the model Streptomyces species, Streptomyces coelicolor. Comparative metabolomics revealed overproduction of several known secondary metabolites, most notably undecylprodigiosin and coelimycin P1, in addition to their biosynthetic intermediates and derivatives, as well as many unknown metabolites. Transcriptomic analysis revealed activation of diverse biological processes including cation uptake, compatible solute production, and the phosphate limitation stress response through conserved and species-specific mechanisms, presumably to overcome the increased salinity. This response leads to activation of a variety of regulatory and metabolic pathways required for production of secondary metabolites including activation of conserved metabolic pathways for energy and substrate supply and species-specific secondary metabolite biosynthetic gene clusters. Furthermore, several promoter sequences contributing to upregulation of secondary metabolism induced by salt supplementation were identified. Overall, our data show how S. coelicolor copes with the increased salinity and tailors the cellular metabolism toward secondary metabolism in a conserved and species-specific manner.

Otani, Hiroshi [USDOE Joint Genome Institute (JGI)↗

DOE OSTI2023

Deciphering the molecular components of the quorum sensing system in the fungus Ophiostoma piceae

Quorum sensing (QS) is a complex cell-cell communication mechanism that coordinates population-level behaviors in microbes. In eukaryotes, this phenomenon has been extensively described in the dimorphic yeast Candida albicans as its main QS molecule, the sesquiterpene alcohol farnesol, is responsible for various phenotypic (i.e., inhibition of yeast-to-hyphae transition, biofilm formation, and, hence, pathogenesis) and metabolic (i.e., induction of oxidative stress and apoptosis) changes. Ophiostoma piceae CECT 20416 is a dimorphic saprotrophic ascomycete with biotechnological interest that also produces farnesol as QS molecule, but in this case, the alcohol promotes the morphological transition to the mycelial form, biofilm formation, enzyme secretion, and melanin production. Here, we characterized the physiological response of Ophiostoma piceae to farnesol, the molecular components of the QS system of this fungus have been investigated using a “multiomics” approach that involved genomic, transcriptomic, and proteomic analyses. Some genes identified in this work are proposed as key factors in farnesol transport and signaling. We have also cataloged the genes undergoing major transcriptional changes triggered by the presence of the autoinducer, such as cell-wall remodeling, reactive oxygen species (ROS) protection, and melanin biosynthesis, using self-organizing maps. This analysis could be useful for applications in the forestry industry, for enzymes production, and for the valorization of residues. Furthermore, it might as well help to investigate the QS mechanisms of clinically relevant fungi phylogenetically related to Ophiostoma.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

A shift between mineral and nonmineral sources of iron and sulfur causes proteome-wide changes in Methanosarcina barkeri

ABSTRACT Iron (Fe) and sulfur (S) are required elements for life, and changes in their availability can limit the ecological distribution and function of microorganisms. In anoxic environments, soluble Fe typically exists as ferrous iron [Fe(II)] and S as sulfide (HS − ). These species exhibit a strong affinity that ultimately drives the formation of sedimentary pyrite (FeS 2 ). Recently, paradigm-shifting studies indicate that Fe and S in FeS 2 can be made bioavailable by methanogens through a reductive dissolution process. However, the impact of the utilization of FeS 2 , as opposed to canonical Fe and S sources, on the phenotype of cells is not fully understood. Here, shotgun proteomics was utilized to measure changes in the phenotype of Methanosarcina barkeri MS grown with FeS 2 , Fe(II)/HS − , or Fe(II)/cysteine. Shotgun proteomics tracked 1,019 proteins overall, with 307 observed to change between growth conditions. Functional characterization and pathway analyses revealed these changes to be systemic and largely tangential to Fe/S metabolism. As a final step, the proteomics data were viewed with respect to previously collected transcriptomics data to deepen the analysis. Presented here is evidence that M. barkeri adopts distinct phenotypes to exploit specific sources of Fe and S in its environment. This is supported by observed protein abundance changes across broad categories of cellular biology. DNA adjacent metabolism, central carbon metabolism methanogenesis, metal trafficking, quorum sensing, and porphyrin biosynthesis pathways are all features in the phenotypic differentiation. Differences in trace metal availability attributed to complexation with HS − , either as a component of the growth medium [Fe(II)/HS − ] or generated through reduction of FeS 2 , were likely a major factor underpinning these phenotypic differences. IMPORTANCE The methanogenic archaeon Methanosarcina barkeri holds great potential for industrial bio-mining and energy generation technologies. Much of the biochemistry of this microbe is poorly understood, and its characterization will provide a glimpse into biological processes that evolved close to life’s origin. The discovery of its ability to extract iron and sulfur from bulk, solid-phase minerals shifted a longstanding paradigm that these elements were inaccessible to biological systems. The full elucidation of this process has the potential to help scientists and engineers extract valuable metals from low-grade ore and mine waste generating energy in the form of methane while doing so.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Regulatory response to a hybrid ancestral nitrogenase in Azotobacter vinelandii

Biological nitrogen fixation, the microbial reduction of atmospheric nitrogen to bioavailable ammonia, represents both a major limitation on biological productivity and a highly desirable engineering target for synthetic biology. However, the engineering of nitrogen fixation requires an integrated understanding of how the gene regulatory dynamics of host diazotrophs respond across sequence-function space of its central catalytic metalloenzyme, nitrogenase. Here, we interrogate this relationship by analyzing the transcriptome of Azotobacter vinelandii engineered with a phylogenetically inferred ancestral nitrogenase protein variant. The engineered strain exhibits reduced cellular nitrogenase activity but recovers wild-type growth rates following an extended lag period. We find that expression of genes within the immediate nitrogen fixation network is resilient to the introduced nitrogenase sequence-level perturbations. Rather the sustained physiological compatibility with the ancestral nitrogenase variant is accompanied by reduced expression of genes that support trace metal and electron resource allocation to nitrogenase. Our results spotlight gene expression changes in cellular processes adjacent to nitrogen fixation as productive engineering considerations to improve compatibility between remodeled nitrogenase proteins and engineered host diazotrophs.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Mass Spectrometry–Based Proteogenomics: New Therapeutic Opportunities for Precision Medicine

Proteogenomics refers to the integration of comprehensive genomic, transcriptomic, and proteomic measurements from the same samples with the goal of fully understanding the regulatory processes converting genotypes to phenotypes, often with an emphasis on gaining a deeper understanding of disease processes. Although specific genetic mutations have long been known to drive the development of multiple cancers, gene mutations alone do not always predict prognosis or response to targeted therapy. The benefit of proteogenomics research is that information obtained from proteins and their corresponding pathways provides insight into therapeutic targets that can complement genomic information by providing an additional dimension regarding the underlying mechanisms and pathophysiology of tumors. This review describes the novel insights into tumor biology and drug resistance derived from proteogenomic analysis while highlighting the clinical potential of proteogenomic observations and advances in technique and analysis tools.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Codon2Vec v1.0

Background: Codon2Vec is an embedding neural network that predicts 'high' or 'low' gene expression directly from the protein-coding sequences. Embedding neural networks are commonly used for natural language processing (NLP) applications. Analogous to how an English sentence is a string of words, a gene can be thought of as a string of codons. Similar to how NLP neural networks model English sentences as a non-random sequence of words, we considered a coding sequence as a non-random non-overlapping array of codons (k-mers of length = 3). Value Proposition: - Codon2Vec achieved a high median AUC-ROC score of 83.8% when trained and applied to transcriptomic data from 300 fungal species - Unlike Codo2Vec, conventional methods predicting for expression based on codon usage rely on a priori knowledge of optimal codons or a set of reference genes. - Unlike Codon2vec, these methods do not account for the effect of codon order on gene expression. - Codon2Vec neural network bypasses the need for artisanal feature selection step that is necessary for traditional machine learning models.

Wint, Rhondene↗

DOE OSTI2021

PayamDiba/CoNSEPT

Deciphering the sequence-function relationship encoded in enhancers holds the key to interpreting non-coding variants and understanding mechanisms of transcriptomic variation. Several quantitative models exist for predicting enhancer function and underlying mechanisms; however, there has been no systematic comparison of these models characterizing their relative strengths and shortcomings. Here, we interrogated a rich data set of neuroectodermal enhancers in Drosophila, representing cis- and trans- sources of expression variation, with a suite of biophysical and machine learning models. We performed rigorous comparisons of thermodynamics-based models implementing different mechanisms of activation, repression and cooperativity. Moreover, we developed a convolutional neural network (CNN) model, called CoNSEPT, that learns enhancer ‘grammar’ in an unbiased manner. CoNSEPT is the first general-purpose CNN tool for predicting enhancer function in varying conditions, such as different cell types and experimental conditions, and we show that such complex models can suggest interpretable mechanisms. We found model-based evidence for mechanisms previously established for the studied system, including cooperative activation and short-range repression. The data also favored one hypothesized activation mechanism over another and suggested an intriguing role for a direct, distance-independent repression mechanism. Our modeling shows that while fundamentally different models can yield similar fits to data, they vary in their utility for mechanistic inference.

Dibaeinia, Payam↗

DOE OSTI2021

raogroupuiuc/rt88_growth

Project: Integrating transcriptomic and metabolomic analysis of the oleaginous yeast Rhodosporidium toruloides IFO0880 during growth under different carbon sources Key points • Gene expression and metabolite concentrations were significantly changed. • Reduced expression of xylulokinase induces a bypass leading to arabitol production. • R. toruloides reprograms its metabolism to allow growth on different substrates.

Deewan, Anshu↗

DOE OSTI2022

raogroupuiuc/lipo11557_growth

Project: Systems analysis of Lipomyces starkeyi during growth on various plant-based sugars Authors: Anshu Deewan*, Jing-Jing Liu*, Sujit Sadashiv Jagtap, Eun Ju Yun, Hanna E Walukiewicz, Yong-Su Jin, Christopher V Rao (* - co-authors) Abstract : Oleaginous yeasts have received significant attention due to their substantial lipids storage capability. The accumulated lipids can be utilized directly or processed into various bioproducts and biofuels. Lipomyces starkeyi is an oleaginous yeast capable of using multiple plant-based sugars, such as glucose, xylose, and cellobiose. It is, however, a relatively unexplored yeast due to limited knowledge about its physiology. In this study, we have evaluated the growth of L. starkeyi on different sugars and performed transcriptomic and metabolomic analyses to understand the underlying mechanisms of sugar metabolism. Principal component analysis showed clear differences resulting from growth on different sugars. We have further reported various metabolic pathways activated during growth on these sugars. We also observed non-specific regulation in L. starkeyi and have updated the gene annotations for the NRRL Y-11557 strain. This analysis provides a foundation for understanding the metabolism of these plant-based sugars and potentially valuable information to guide the metabolic engineering of L. starkeyi to produce bioproducts and biofuels.

Deewan, Anshu↗

DOE OSTI2024

mrizwanriaz/lcm-dataset

Laser capture microdissection (LCM) derived stem cell-type transcriptome (Jie et al.) How to run on your system Install R on your system. Install the required packages shiny, shinyjs, ggplot2, dplyr, formattable, rcartocolor Download the RShiny app code (ui.R and server.R) and RDS files from the GitHub repository to the same directory. Usage: Run the R code file (ui.R) in the RStudio. The app will open in the default web browser.

Riaz, Muhammad Rizwan↗

DOE OSTI2026

TransTissueFormer

This software builds models for translating transcriptomic profiles between tissues.

Cong, Guojing↗

DOE OSTI2023

Loss of $ZNF148$ enhances insulin secretion in human pancreatic β cells

Insulin secretion from pancreatic β cells is essential to the maintenance of glucose homeostasis. Defects in this process result in diabetes. Identifying genetic regulators that impair insulin secretion is crucial for the identification of novel therapeutic targets. Here, we show that reduction of ZNF148 in human islets, and its deletion in stem cell–derived β cells (SC–β cells), enhances insulin secretion. Transcriptomics of ZNF148-deficient SC–β cells identifies increased expression of annexin and S100 genes whose proteins form tetrameric complexes involved in regulation of insulin vesicle trafficking and exocytosis. ZNF148 in SC–β cells prevents translocation of annexin A2 from the nucleus to its functional place at the cell membrane via direct repression of S100A16 expression. These findings point to ZNF148 as a regulator of annexin-S100 complexes in human β cells and suggest that suppression of ZNF148 may provide a novel therapeutic strategy to enhance insulin secretion.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Endogenous adenine mediates kidney injury in diabetic models and predicts diabetic kidney disease in patients

Diabetic kidney disease (DKD) can lead to end-stage kidney disease (ESKD) and mortality, however, few mechanistic biomarkers are available for high-risk patients, especially those without macroalbuminuria. Urine from participants with diabetes from Chronic Renal Insufficiency Cohort (CRIC), Singapore Study of Macro-Angiopathy and Reactivity in Type 2 Diabetes (SMART2D), and the Pima Indian Study determined if urine adenine/creatinine ratio (UAdCR) could be a mechanistic biomarker for ESKD. ESKD and mortality were associated with the highest UAdCR tertile in CRIC (HR 1.57, 1.18, 2.10) and SMART2D (HR 1.77, 1.00, 3.12). ESKD was associated with the highest UAdCR tertile in patients without macroalbuminuria in CRIC (HR 2.36, 1.26, 4.39), SMART2D (HR 2.39, 1.08, 5.29), and Pima Indian study (HR 4.57, CI 1.37-13.34). Empagliflozin lowered UAdCR in non-macroalbuminuric participants. Spatial metabolomics localized adenine to kidney pathology and transcriptomics identified ribonucleoprotein biogenesis as a top pathway in proximal tubules of patients without macroalbuminuria, implicating mammalian target of rapamycin (mTOR). Adenine stimulated matrix in tubular cells via mTOR and stimulated mTOR in mouse kidneys. A specific inhibitor of adenine production was found to reduce kidney hypertrophy and kidney injury in diabetic mice. We propose that endogenous adenine may be a causative factor in DKD.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Molecular profiles of blood from numerous species that differ in sensitivity to acute inflammation

Abstract Vertebrates differ over 100,000-fold in responses to pro-inflammatory agonists such as bacterial lipopolysaccharide (LPS), complicating use of animal models to study human sepsis or inflammatory disorders. We compared transcriptomes of resting and LPS-exposed blood from six LPS-sensitive species (rabbit, pig, sheep, cow, chimpanzee, human) and four LPS-resilient species (mice, rats, baboon, rhesus), as well as plasma proteomes and lipidomes. Unexpectedly, at baseline, sensitive species already had enhanced expression of LPS-responsive genes relative to resilient species. After LPS stimulation, maximally different genes in resilient species included genes that detoxify LPS, diminish bacterial growth, discriminate sepsis from SIRS, and play roles in autophagy and apoptosis. The findings reveal the molecular landscape of species differences in inflammation. This may inform better selection of species for pre-clinical models and could lead to new therapeutic strategies that mimic mechanisms in inflammation-resilient species to limit inflammation without causing immunosuppression.

Biochemistry & Molecular Biology↗

DOE OSTI2021

Asc-Seurat: analytical single-cell Seurat-based web application

Abstract Background Single-cell RNA sequencing (scRNA-seq) has revolutionized the study of transcriptomes, arising as a powerful tool for discovering and characterizing cell types and their developmental trajectories. However, scRNA-seq analysis is complex, requiring a continuous, iterative process to refine the data and uncover relevant biological information. A diversity of tools has been developed to address the multiple aspects of scRNA-seq data analysis. However, an easy-to-use web application capable of conducting all critical steps of scRNA-seq data analysis is still lacking. Summary We present Asc-Seurat, a feature-rich workbench, providing an user-friendly and easy-to-install web application encapsulating tools for an all-encompassing and fluid scRNA-seq data analysis. Asc-Seurat implements functions from the Seurat package for quality control, clustering, and genes differential expression. In addition, Asc-Seurat provides a pseudotime module containing dozens of models for the trajectory inference and a functional annotation module that allows recovering gene annotation and detecting gene ontology enriched terms. We showcase Asc-Seurat’s capabilities by analyzing a peripheral blood mononuclear cell dataset. Conclusions Asc-Seurat is a comprehensive workbench providing an accessible graphical interface for scRNA-seq analysis by biologists. Asc-Seurat significantly reduces the time and effort required to analyze and interpret the information in scRNA-seq datasets.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

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↗

DOE OSTI2026

From 2D to 4D: a containerized workflow and browser to explore dynamic chromatin architecture

Background Characterizing the physical organization of the genome is essential for understanding long-range gene regulation, chromatin compartmentalization, and epigenetic accessibility. Hi-C experiments generate two-dimensional (2D) genome-wide contact maps of chromatin interactions by capturing the spatial proximity between genomic loci, which reveal interaction frequencies but lack the spatial resolution needed to interpret the three-dimensional (3D) genome structure(s). Emerging evidence suggests that epigenetic regulation is closely linked to 3D genome architecture, and that structural changes over time (4D) drive key biological processes in development, disease, and environmental response. Thus, integrating 3D structure with functional data is critical for a more complete understanding of genome regulation. Previous work, most notably the 4DHiC chromosome modeling framework, has shown that physical multi-dimensional modeling approaches rooted in polymer physics and molecular dynamics can resolve these structures at biologically meaningful resolutions by integrating temporal Hi-C data with physical constraints to uncover dynamic chromosome reorganization. Thus, molecular dynamics simulations, constrained by Hi-C contact matrices, can resolve fine-scale structural changes and reveal functionally significant transitions in chromatin conformation. Results Herein, we present the 4D Genome Browser Workflow (4DGBWorkflow) and the 4D Genome Browser (4DGB). The algorithm is based on the 4DHiC method, and the containerized tool is an end-to-end workflow that can transform, filter, and view 4D epigenomics and chromatin datasets, allowing non-specialists to apply three-dimensional modeling principles to diverse datasets and experimental conditions. The software executes on a laptop running macOS, Linux or Windows. From input Hi-C files (.hic), the 4DGBWorkflow produces 3D reconstructions of chromosomes, integrates the reconstruction with track data (e.g., epigenetic marks, transcriptome profiles), and provides comparative visualization of the results in a single workflow. Conclusions The 4DGBWorkflow and 4D Genome Browser are open-source tools for comparative analysis and visualization of 4D chromosome datasets, including chromatin architecture and epigenomic signals. Automatic integration of Hi-C data with molecular dynamics democratizes the construction of time resolved 3D genome structures, simplifying complex simulations and data integration schemes.

3D Genome Browser↗