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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Metals and methylotrophy: Via global gene expression studies

A number of minerals, such as copper, cobalt, and rare earth elements (REE), are essential modulators of microbial one carbon metabolism. This chapter provides an overview of the gene expression study design and analysis protocols for uncovering REE-induced changes in methylotrophic bacteria. By interrogating relationships and differences in total gene expression induced by mineral micronutrients, a deeper understanding of gene regulation at a systems scale can be gained. With careful design and execution of RNA-sequencing experiments, thorough processing and assessment of read quality can be utilized to assess and adjust for possible biases. By ensuring only quality data are utilized in downstream processes, differential gene expression, overrepresented analyses, and gene-set enrichment analyses provide reliable and reproducible representation of pathways and functions which are being affected by changes in environmental conditions.

Johnson, Zachary J.↗
DOE OSTI2021

Metals and methylotrophy: Via global gene expression studies

A number of minerals, such as copper, cobalt, and rare earth elements (REE), are essential modulators of microbial one-carbon metabolism. This chapter provides an overview of the gene expression study design and analysis protocols for uncovering REE-induced changes in methylotrophic bacteria. By interrogating relationships and differences in total gene expression induced by mineral micronutrients, a deeper understanding of gene regulation at a systems scale can be gained. With careful design and execution of RNA-sequencing experiments, thorough processing and assessment of read quality can be utilized to assess and adjust for possible biases. Here, by ensuring only quality data are utilized in downstream processes, differential gene expression, overrepresented analyses, and gene-set enrichment analyses provide reliable and reproducible representation of pathways and functions which are being affected by changes in environmental conditions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Coding and noncoding variants in EBF3 are involved in HADDS and simplex autism

Abstract Background Previous research in autism and other neurodevelopmental disorders (NDDs) has indicated an important contribution of protein-coding (coding) de novo variants (DNVs) within specific genes. The role of de novo noncoding variation has been observable as a general increase in genetic burden but has yet to be resolved to individual functional elements. In this study, we assessed whole-genome sequencing data in 2671 families with autism (discovery cohort of 516 families, replication cohort of 2155 families). We focused on DNVs in enhancers with characterized in vivo activity in the brain and identified an excess of DNVs in an enhancer named hs737. Results We adapted the fitDNM statistical model to work in noncoding regions and tested enhancers for excess of DNVs in families with autism. We found only one enhancer (hs737) with nominal significance in the discovery (p = 0.0172), replication (p = 2.5 × 10 −3 ), and combined dataset (p = 1.1 × 10 −4 ). Each individual with a DNV in hs737 had shared phenotypes including being male, intact cognitive function, and hypotonia or motor delay. Our in vitro assessment of the DNVs showed they all reduce enhancer activity in a neuronal cell line. By epigenomic analyses, we found that hs737 is brain-specific and targets the transcription factor gene EBF3 in human fetal brain. EBF3 is genome-wide significant for coding DNVs in NDDs (missense p = 8.12 × 10 −35 , loss-of-function p = 2.26 × 10 −13 ) and is widely expressed in the body. Through characterization of promoters bound by EBF3 in neuronal cells, we saw enrichment for binding to NDD genes (p = 7.43 × 10 −6 , OR = 1.87) involved in gene regulation. Individuals with coding DNVs have greater phenotypic severity (hypotonia, ataxia, and delayed development syndrome [HADDS]) in comparison to individuals with noncoding DNVs that have autism and hypotonia. Conclusions In this study, we identify DNVs in the hs737 enhancer in individuals with autism. Through multiple approaches, we find hs737 targets the gene EBF3 that is genome-wide significant in NDDs. By assessment of noncoding variation and the genes they affect, we are beginning to understand their impact on gene regulatory networks in NDDs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Integrated transcriptomic and metabolomic investigation of the genes and metabolites involved in swine follicular cyst formation

Follicular cysts are a common reproductive disorder in mammals that is usually caused by stress. However, the pathogenesis of follicular cysts in sows remains unclear. To provide new insights into the mechanisms of follicular cyst formation in pigs, we conducted a combined transcriptomic and metabolomic analysis on theca interna and mural granulosa cells of follicular cysts and mature follicles. We identified 2,533 up-regulated and 1,355 down-regulated genes in follicular cysts, compared with mature follicles. These differentially expressed genes were mainly found in signaling pathways related to tumor formation and cortisol synthesis and secretion as shown by Ingenuity Pathway Analysis, which predicted 4,362 upstream regulatory factors. The combined gene expression and pathway analysis identified the following genes as potential biomarkers for porcine follicular cysts: cytochrome P450 family 2 subfamily C polypeptide 18, L-lactate dehydrogenase, carbamoyl-phosphate synthase, fibroblast growth factor 7, integrin binding sialoprotein, interleukin 23 receptor, prolactin receptor, epiregulin, interleukin 1 receptor type II, arginine vasopressin receptor 1A, fibroblast growth factor 10, claudin 7, G Protein Subunit Gamma 3, cholecystokinin B receptor and cytosolic phospholipase A2 . Metabolomics analysis found significant differences in 87 metabolites, which were enriched in unsaturated fatty acid biosynthesis, and sphingolipid signaling pathways. These results provide valuable information on the molecular mechanisms of follicular cyst formation, which may facilitate the development of new therapeutics to prevent and treat follicular cysts.

Dai, Jiage↗
DOE OSTI2023

Discovery of a novel transcriptional regulator of sugar catabolism in archaea

Abstract The haloarchaeon Haloferax volcanii degrades D‐glucose via the semiphosphorylative Entner‐Doudoroff pathway and D‐fructose via a modified Embden‐Meyerhof pathway. Here, we report the identification of GfcR, a novel type of transcriptional regulator that functions as an activator of both D‐glucose and D‐fructose catabolism. We find that in the presence of D‐glucose, GfcR activates gluconate dehydratase, glyceraldehyde‐3‐phosphate dehydrogenase and pyruvate kinase and also acts as activator of the phosphotransferase system and of fructose‐1,6‐bisphosphate aldolase, which are involved in uptake and degradation of D‐fructose. In addition, glyceraldehyde‐3‐phosphate dehydrogenase and pyruvate kinase are activated by GfcR in the presence of D‐fructose and also during growth on D‐galactose and glycerol. Electrophoretic mobility shift assays indicate that GfcR binds directly to promoters of regulated genes. Specific intermediates of the degradation pathways of the three hexoses and of glycerol were identified as inducer molecules of GfcR. GfcR is composed of a phosphoribosyltransferase (PRT) domain with an N‐terminal helix‐turn‐helix motif and thus shows homology to PurR of Gram‐positive bacteria that is involved in the transcriptional regulation of nucleotide biosynthesis. We propose that GfcR of H. volcanii evolved from a PRT‐like enzyme to attain a function as a transcriptional regulator of central sugar catabolic pathways in archaea.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Homologs of Phycobilisome Abundance Regulator PsoR Are Widespread across Cyanobacteria

During chromatic acclimation (CA), cyanobacteria undergo shifts in their physiology and metabolism in response to changes in their light environment. Various forms of CA, which involves the tuning of light-harvesting accessory complexes known as phycobilisomes (PBS) in response to distinct wavelengths of light, have been recognized. Recently, a negative regulator of PBS abundance, PsoR, about which little was known, was identified. We used sequence analyses and bioinformatics to predict the role of PsoR in cyanobacteria and PBS regulation and to examine its presence in a diverse range of cyanobacteria. PsoR has sequence similarities to the β-CASP family of proteins involved in DNA and RNA processing. PsoR is a putative nuclease widespread across Cyanobacteria, of which over 700 homologs have been observed. Promoter analysis suggested that psoR is co-transcribed with upstream gene tcpA. Multiple transcription factors involved in global gene regulation and stress responses were predicted to bind to the psoR-tcpA promoter. The predicted protein–protein interactions with PsoR homologs included proteins involved in DNA and RNA metabolism, as well as a phycocyanin-associated protein predicted to interact with PsoR from Fremyella diplosiphon (FdPsoR). The widespread presence of PsoR homologs in Cyanobacteria and their ties to DNA- and RNA-metabolizing proteins indicated a potentially unique role for PsoR in CA and PBS abundance regulation.

Layer, Alicia↗
DOE OSTI2023

Inference of cell type-specific gene regulatory networks on cell lineages from single cell omic datasets

Abstract Cell type-specific gene expression patterns are outputs of transcriptional gene regulatory networks (GRNs) that connect transcription factors and signaling proteins to target genes. Single-cell technologies such as single cell RNA-sequencing (scRNA-seq) and single cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq), can examine cell-type specific gene regulation at unprecedented detail. However, current approaches to infer cell type-specific GRNs are limited in their ability to integrate scRNA-seq and scATAC-seq measurements and to model network dynamics on a cell lineage. To address this challenge, we have developed single-cell Multi-Task Network Inference (scMTNI), a multi-task learning framework to infer the GRN for each cell type on a lineage from scRNA-seq and scATAC-seq data. Using simulated and real datasets, we show that scMTNI is a broadly applicable framework for linear and branching lineages that accurately infers GRN dynamics and identifies key regulators of fate transitions for diverse processes such as cellular reprogramming and differentiation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

CRAGE-RB-PI-seq reveals transcriptional dynamics of plant-associated bacteria during root colonization

Plant roots release a wide array of metabolites into the rhizosphere, shaping microbial communities and their functions. While metagenomics has expanded our understanding of these communities, little is known about the physiology of their members in host environments. Transcriptome analysis via RNA sequencing is a common approach to learning more, but its use has been challenging because of low bacterial biomass and interference from plant RNA. To overcome this, we developed a randomly-barcoded promoter-library insertion sequencing (RB-PI-seq) combined with chassis-independent recombinase-assisted genome engineering (CRAGE). Using Pseudomonas simiae WCS417 as a model rhizobacterium, this method enabled targeted amplification of barcoded transcripts, bypassing plant RNA interference and allowing measurement of thousands of promoter activities during Arabidopsis root colonization. Our analysis revealed temporally resolved transcriptional regulation, including those associated with cell growth, chemotaxis, plant immune suppression, biofilm formation, and stress responses, reflecting the coordinated physiological adaptation to the root environment. Additionally, we discovered that transcriptional activation of xanthine dehydrogenase and a lysozyme inhibitor is crucial for evading plant immune systems. This framework is scalable to other bacterial species and provides new opportunities for understanding rhizobacterial gene regulation in native environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Crystal Structure of an i‐Motif from the HRAS Oncogene Promoter

Abstract An i‐motif is a non‐canonical DNA structure implicated in gene regulation and linked to cancers. The C‐rich strand of the HRAS oncogene, 5′‐CG CCC GTG CCC TGCG CCC GCAA CCC GA‐3′ (herein referred to as iHRAS), forms an i‐motif in vitro but its exact structure was unknown. HRAS is a member of the RAS proto‐oncogene family. About 19 % of US cancer patients carry mutations in RAS genes. We solved the structure of iHRAS at 1.77 Å resolution. The structure reveals that iHRAS folds into a double hairpin. The two double hairpins associate in an antiparallel fashion, forming an i‐motif dimer capped by two loops on each end and linked by a connecting region. Six C−C + base pairs form each i‐motif core, and the core regions are extended by a G−G base pair and a cytosine stacking. Extensive canonical and non‐canonical base pairing and stacking stabilizes the connecting region and loops. The iHRAS structure is the first atomic resolution structure of an i‐motif from a human oncogene. This structure sheds light on i‐motifs folding and function in the cell.

Li, Kevin S.↗
DOE OSTI2023

Crystal Structure of an i‐Motif from the HRAS Oncogene Promoter

Abstract An i‐motif is a non‐canonical DNA structure implicated in gene regulation and linked to cancers. The C‐rich strand of the HRAS oncogene, 5′‐CG CCC GTG CCC TGCG CCC GCAA CCC GA‐3′ (herein referred to as iHRAS), forms an i‐motif in vitro but its exact structure was unknown. HRAS is a member of the RAS proto‐oncogene family. About 19 % of US cancer patients carry mutations in RAS genes. We solved the structure of iHRAS at 1.77 Å resolution. The structure reveals that iHRAS folds into a double hairpin. The two double hairpins associate in an antiparallel fashion, forming an i‐motif dimer capped by two loops on each end and linked by a connecting region. Six C−C + base pairs form each i‐motif core, and the core regions are extended by a G−G base pair and a cytosine stacking. Extensive canonical and non‐canonical base pairing and stacking stabilizes the connecting region and loops. The iHRAS structure is the first atomic resolution structure of an i‐motif from a human oncogene. This structure sheds light on i‐motifs folding and function in the cell.

Li, Kevin S.↗
DOE OSTI2026

An expanded registry of candidate cis -regulatory elements

Mammalian genomes contain millions of regulatory elements that control the complex patterns of gene expression. Previously, the ENCODE consortium mapped biochemical signals across hundreds of cell types and tissues and integrated these data to develop a registry containing 0.9 million human and 300,000 mouse candidate cis-regulatory elements (cCREs) annotated with potential functions. Here we have expanded the registry to include 2.37 million human and 967,000 mouse cCREs, leveraging new ENCODE datasets and enhanced computational methods. This expanded registry covers hundreds of unique cell and tissue types, providing a comprehensive understanding of gene regulation. Functional characterization data from assays such as STARR-seq, massively parallel reporter assay, CRISPR perturbation and transgenic mouse assays have profiled more than 90% of human cCREs, revealing complex regulatory functions. We identified thousands of novel silencer cCREs and demonstrated their dual enhancer and silencer roles in different cellular contexts. Integrating the registry with other ENCODE annotations facilitates genetic variation interpretation and trait-associated gene identification, exemplified by the identification of KLF1 as a novel causal gene for red blood cell traits. This expanded registry is a valuable resource for studying the regulatory genome and its impact on health and disease.

Moore, Jill E. [Univ. of Massachusetts, Worchester↗
DOE OSTI2024

Highly multiplexed design of an allosteric transcription factor to sense new ligands

Allosteric transcription factors (aTF) regulate gene expression through conformational changes induced by small molecule binding. Although widely used as biosensors, aTFs have proven challenging to design for detecting new molecules because mutation of ligand-binding residues often disrupts allostery. Here, we develop Sensor-seq, a high-throughput platform to design and identify aTF biosensors that bind to non-native ligands. We screen a library of 17,737 variants of the aTF TtgR, a regulator of a multidrug exporter, against six non-native ligands of diverse chemical structures – four derivatives of the cancer therapeutic tamoxifen, the antimalarial drug quinine, and the opiate analog naltrexone – as well as two native flavonoid ligands, naringenin and phloretin. Sensor-seq identifies biosensors for each of these ligands with high dynamic range and diverse specificity profiles. The structure of a naltrexone-bound design shows shape-complementary methionine-aromatic interactions driving ligand specificity. To demonstrate practical utility, we develop cell-free detection systems for naltrexone and quinine. Sensor-seq enables rapid and scalable design of new biosensors, overcoming constraints of natural biosensors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Nonclassical autophagy activation pathways are essential for production of infectious Influenza A virus in vitro

Autophagy is a critical mechanism deployed by eukaryotic cells in response to stress, including viral infection, to boost the innate antimicrobial responses. However, an increasing number of pathogens hijack the autophagic machinery to facilitate their own replication. Influenza A virus (IAV), responsible for several global pandemics, has an intricate dependence on autophagy for successful replication in mammalian cells. To elucidate key chokepoints in the host stress responses facilitating IAV replication, we constructed a meta-transcriptome of IAV and host gene expression dynamics during early (1–3 hpi), mid (4–6 hpi), and late (8–12 hpi) stages of the viral replication cycle at two multiplicities of infection (MOI): 1 and 5. We supplemented the global transcriptome study with phosphoproteomic analysis of stress-activated protein kinase (SAPK/JNK) signaling in lung carcinoma (predominantly used as an in vitro model of IAV replication) and normal human bronchial epithelial cells. We report significant differences in the activation profiles of autophagy regulating genes upon IAV infection at the two MOI as well as divergent dependence on ULK1 signaling within the normal and cancer cells. Regardless of the cell model, JNK-Thr187 signaling was crucial for the production of infectious viral particles.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

PERCEPTIVE: an R shiny $\underline{p}$ipelin$\underline{e}$ for the p$\underline{r}$edi$\underline{c}$tion of $\underline{ep}$igenetic modula$\underline{t}$ors $\underline{i}$n no$\underline{v}$el sp$\underline{e}$cies

Epigenetic processes are central to regulating gene expression, genome stability, and metabolic function across the tree of life; yet, their roles remain underexplored in microalgae, especially as new species continue to be identified and characterized. This is likely due to the cumbersome nature and species-dependent attributes of epigenetic wet-lab methodologies, which preclude the rapid identification of epigenetic modifications and modulators. However, there is high conservation of epigenetic processes from budding yeast to humans; in many cases, one may infer how behavior and function are epigenetically regulated in novel species by identifying epigenetic modulators, or the proteins responsible for conferring epigenetic modifications. Here, to this end, we have developed a graphical software package, titled PERCEPTIVE (pipeline for the prediction of epigenetic modulators in novel species). This platform solely uses the genomic sequence of an algal species, and preexisting information from other model organisms, to predict the epigenetic modulators and associated modifications in algae. Predictions are presented to the user in a graphical interface, which provides literature-based interpretation of results, enabling users to quickly understand potential epigenetic processes in their algal species of interest and plan follow-up experiments. To test PERCEPTIVE, we predicted epigenetic modulators in several feedstock candidate algae species. To validate these predictions, wet-lab studies were performed, including mass spectrometry; these results underscore the high accuracy of PERCEPTIVE predictions. Overall, PERCEPTIVE represents a powerful in silico tool for the research and manipulation of algal species, which does not require a priori knowledge of epigenetics and is accessible to a broad set of investigators.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Gene regulatory networks controlling carbohydrate selective deconstruction pathways in fungi

The work performed at Clark University (PI, David Hibbett) was a subcomponent of the research lead by Jonathan Schilling at University of Minnesota (award number DE-SC0019427). The overall goal of this project was to address how fungi metabolize lignocellulose. Specifically, we targeted a carbohydrate-selective group of fungi known as 'brown rot' fungi that are well-aligned to be harness for bioconversion to biofuels and other products. These organisms orchestrate a two-step mechanism that initiates decomposition using oxidative radical-based chemistry and follows with enzymatic attack. We have helped characterize that this mechanism occurs in this sequence, but currently lack the fundamental regulatory information needed to harness these fungi for application. Thus, the major goal of this project was to use systems biology to create an integrated model of brown rot wood decay that couples fungal gene regulation with the metabolite feedbacks used to coordinate a two-step oxidative-hydrolytic mechanism. The research at Clark University focused on phylogenomic analyses of data produced by other project partners. Hence, the Clark component of the research was staged to initiate somewhat after that in other partner laboratories. The major Clark-based accomplishment was to advise on selection of fungal species for analyses of brown rot decay chemistry, and to interpret results in a phylogenetic context. The Clark University group also performed complementary analyses of gene families encoding plant cell wall-degrading enzymes in the the basidiomycete genus Lentinula, as well as analyses of substrate-specific gene expression and RNA editing in brown rot fungi.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Learning genetic perturbation effects with variational causal inference

Advances in sequencing technologies have enhanced the understanding of gene regulation in cells. In particular, Perturb-seq has enabled high-resolution profiling of the transcriptomic response to genetic perturbations at the single-cell level. This understanding has implications in functional genomics and potentially for identifying therapeutic targets. Various computational models have been developed to predict perturbational effects. While deep learning models excel at interpolating observed perturbational data, they tend to overfit in the lack of enough data and may not generalize well to unseen perturbations. In contrast, mechanistic models, such as linear causal models based on gene regulatory networks, hold greater potential for extrapolation, as they encapsulate regulatory information that can predict responses to unseen perturbations. However, their application has been limited to small studies due to overly simplistic assumptions, making them less effective in handling noisy, large-scale single-cell data. We propose a hybrid approach that combines a mechanistic causal model with variational deep learning, termed Single Cell Causal Variational Autoencoder (SCCVAE). The mechanistic model employs a learned regulatory network to represent perturbational changes as shift interventions that propagate through the learned network. SCCVAE integrates this mechanistic causal model into a variational autoencoder, generating rich, comprehensive transcriptomic responses. Our results indicate that SCCVAE exhibits superior performance over current state-of-the-art baselines for extrapolating to predict unseen perturbational responses. Additionally, for the observed perturbations, the latent space learned by SCCVAE allows for the identification of functional perturbation modules and simulation of single-gene knockdown experiments of varying penetrance, presenting a robust tool for interpreting and interpolating perturbational responses at the single-cell level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Automated model-predictive design of synthetic promoters to control transcriptional profiles in bacteria

Abstract Transcription rates are regulated by the interactions between RNA polymerase, sigma factor, and promoter DNA sequences in bacteria. However, it remains unclear how non-canonical sequence motifs collectively control transcription rates. Here, we combine massively parallel assays, biophysics, and machine learning to develop a 346-parameter model that predicts site-specific transcription initiation rates for any σ 70 promoter sequence, validated across 22132 bacterial promoters with diverse sequences. We apply the model to predict genetic context effects, design σ 70 promoters with desired transcription rates, and identify undesired promoters inside engineered genetic systems. The model provides a biophysical basis for understanding gene regulation in natural genetic systems and precise transcriptional control for engineering synthetic genetic systems.

42 ENGINEERING↗