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At least 73 records · Page 4

Systematic identification of cis -regulatory variants that cause gene expression differences in a yeast cross

Sequence variation in regulatory DNA alters gene expression and shapes genetically complex traits. However, the identification of individual, causal regulatory variants is challenging. Here, we used a massively parallel reporter assay to measure the cis-regulatory consequences of 5832 natural DNA variants in the promoters of 2503 genes in the yeast Saccharomyces cerevisiae. We identified 451 causal variants, which underlie genetic loci known to affect gene expression. Several promoters harbored multiple causal variants. In five promoters, pairs of variants showed non-additive, epistatic interactions. Causal variants were enriched at conserved nucleotides, tended to have low derived allele frequency, and were depleted from promoters of essential genes, which is consistent with the action of negative selection. Causal variants were also enriched for alterations in transcription factor binding sites. Models integrating these features provided modest, but statistically significant, ability to predict causal variants. This work revealed a complex molecular basis for cis-acting regulatory variation.

60 APPLIED LIFE SCIENCES↗

Accurate flux predictions using tissue-specific gene expression in plant metabolic modeling

The accurate prediction of complex phenotypes such as metabolic fluxes in living systems is a grand challenge for systems biology and central to efficiently identifying biotechnological interventions that can address pressing industrial needs. The application of gene expression data to improve the accuracy of metabolic flux predictions using mechanistic modeling methods such as flux balance analysis (FBA) has not been previously demonstrated in multi-tissue systems, despite their biotechnological importance. We hypothesized that a method for generating metabolic flux predictions informed by relative expression levels between tissues would improve prediction accuracy. Relative gene expression levels derived from multiple transcriptomic and proteomic datasets were integrated into FBA predictions of a multi-tissue, diel model of Arabidopsis thaliana’s central metabolism. This integration dramatically improved the agreement of flux predictions with experimentally based flux maps from 13 C metabolic flux analysis compared with a standard parsimonious FBA approach. Disagreement between FBA predictions and MFA flux maps was measured using weighted averaged percent error values, and for parsimonious FBA this was 169%–180% for high light conditions and 94%–103% for low light conditions, depending on the gene expression dataset used. This fell to 10%-13% and 9%-11% upon incorporating expression data into the modeling process, which also substantially altered the predicted carbon and energy economy of the plant.

59 BASIC BIOLOGICAL SCIENCES↗

Bidirectional titration of yeast gene expression using a pooled CRISPR guide RNA approach

Most classic genetic approaches utilize binary modifications that preclude the identification of key knockdowns for essential genes or other targets that only require moderate modulation. As a complementary approach to these classic genetic methods, we describe a plasmid-based library methodology that affords bidirectional, graded modulation of gene expression enabled by tiling the promoter regions of all 969 genes that comprise the ito977 model of Saccharomyces cerevisiae’s metabolic network. When coupled with a CRISPR-dCas9–based modulation and next-generation sequencing, this method affords a library-based, bidirection titration of gene expression across all major metabolic genes. We utilized this approach in two case studies: growth enrichment on alternative sugars, glycerol and galactose, and chemical overproduction of betaxanthins, leading to the identification of unique gene targets. In particular, we identify essential genes and other targets that were missed by classic genetic approaches.

59 BASIC BIOLOGICAL SCIENCES↗

Transcription initiation as a control point in plastid gene expression

The extensive processing and protein-assisted stabilization of transcripts have been taken as evidence for a viewpoint that the control of gene expression had shifted entirely in evolution from transcriptional in the bacterial endosymbiont to posttranscriptional in the plastid. This suggestion is however at odds with many observations on plastid gene transcription. Chloroplasts of flowering plants and mosses contain two or more RNA polymerases with distinct promoter preference and division of labor for the coordinated synthesis of plastid RNAs. Plant and algal plastids further possess multiple nonredundant sigma factors that function as transcription initiation factors. The controlled accumulation of plastid sigma factors and modification of their activity by sigma-binding proteins and phosphorylation constitute additional transcriptional regulatory strategies. Plant and algal plastids also contain dedicated one- or two-component transcriptional regulators. Finally, transcription initiation thus continues to form a critical control point at which varied developmental and environmental signals intersect with plastid gene expression.

59 BASIC BIOLOGICAL SCIENCES↗

Modulation of Plant and Fungal Gene Expression Upon Cd Exposure and Symbiosis in Ericoid Mycorrhizal Vaccinium myrtillus

The success of Ericaceae in stressful habitats enriched in heavy metals has been ascribed to the distinctive abilities of their mycorrhizal fungal partners to withstand heavy metal stress and to enhance metal tolerance in the host plant. Whereas heavy metal tolerance has been extensively investigated in some ericoid mycorrhizal (ERM) fungi, the molecular and cellular mechanisms that extend tolerance to the host plant are currently unknown. Here, we show a reduced Cd content in Cd-exposed mycorrhizal roots of Vaccinium myrtillus colonized by a metal tolerant isolate of the fungus Oidiodendron maius as compared to non-mycorrhizal roots. To better understand this phenotype, we applied Next Generation Sequencing technologies to analyze gene expression in V. myrtillus and O. maius Zn grown under normal and Cd-stressed conditions, in the free living and in the mycorrhizal status. The results clearly showed that Cd had a stronger impact on plant gene expression than symbiosis, whereas fungal gene expression was mainly regulated by symbiosis. The higher abundance of transcripts coding for stress related proteins in non-mycorrhizal roots may be related to the higher Cd content. Regulated plant metal transporters have been identified that may play a role in reducing Cd content in mycorrhizal roots exposed to this metal.

Cd tolerance, transcriptomics↗

The effects of xylo-oligosaccharides on regulating growth performance, nutrient utilization, gene expression of tight junctions, nutrient transporters, and cecal short chain fatty acids profile in Eimeria-challenged broiler chickens

A 21-d experiment was conducted to investigate the effects of xylo-oligosaccharides (XOS) on growth performance, nutrient utilization, gene expression of tight junctions, nutrient transporters, and cecal short chain fatty acids (SCFA) profile of broiler chickens challenged with mixed Eimeria spp. Two hundred fifty-two zero-day-old chicks were allocated to 6 treatments in a 3 £ 2 factorial arrangement (corn-soybean meal diets supplemented with 0, 0.5, or 1.0 g/kg XOS; with or without Eimeria challenge). Challenged groups were inoculated with a solution containing E. maxima, E. acervulina, and E. tenella oocysts on d 15. During the infection period (d 15 to d 21), there was a significant (P < 0.05) Eimeria £ XOS interaction for weight gain (WG). XOS significantly (P < 0.05) increased WG in the unchallenged birds but not in the challenged treatments. There was no significant Eimeria £ XOS interaction for N and minerals utilization responses. XOS supplementation at 0.5 g/kg tended to alleviate Eimeria-induced depression in apparent ileal digestibility of DM (P = 0.052). Challenged birds had lower (P < 0.01) AME, AMEn, and total retention of N, Ca, and P. Eimeria upregulated (P < 0.01) gene expression of tight junction proteins claudin-1, junctional adhesion molecule-2, and glucose transporter GLUT1; but downregulated (P < 0.01) the peptide transporter PepT1, amino acid transporters rBAT, CAT2, y+LAT2, and zinc transporter ZnT1. XOS alleviated (P < 0.05) Eimeria-induced claudin-1 upregulation. Eimeria decreased (P < 0.05) cecal saccharolytic SCFA acetate, butyrate, and total SCFA, but increased (P < 0.05) branched chain fatty acids isobutyrate and isovalerate. The supplementation of XOS tended to decrease the concentration of isobutyrate (P = 0.08) and isovalerate (P = 0.062). In conclusion, 0.5 g/kg XOS supplementation alleviated depression in growth performance and nutrient utilization from the Eimeria challenge. In addition, supplemental XOS reversed the gene expression changes of claudin-1, also showed the potentials of alleviating the negative cecal fermentation pattern induced by Eimeria infection.

60 APPLIED LIFE SCIENCES↗

Model of metabolism and gene expression predicts proteome allocation in Pseudomonas putida

Abstract The genome-scale model of metabolism and gene expression (ME-model) forPseudomonas putidaKT2440,iPpu1676-ME, provides a comprehensive representation of biosynthetic costs and proteome allocation. Compared to a metabolic-only model,iPpu1676-ME significantly expands on gene expression, macromolecular assembly, and cofactor utilization, enabling accurate growth predictions without additional constraints. Multi-omics analysis using RNA sequencing and ribosomal profiling data revealed translational prioritization inP. putida, with core pathways, such as nicotinamide biosynthesis and queuosine metabolism, exhibiting higher translational efficiency, while secondary pathways displayed lower priority. Notably, the ME-model significantly outperformed the M-model in alignment with multi-omics data, thereby validating its predictive capacity. Thus,iPpu1676-ME offers valuable insights intoP. putida’s proteome allocation and presents a powerful tool for understanding resource allocation in this industrially relevant microorganism.

Mathematical & Computational Biology↗

Cell-Free Gene Expression: Methods and Applications

Cell-free gene expression (CFE) systems empower synthetic biologists to build biological molecules and processes outside of living intact cells. The foundational principle is that precise, complex biomolecular transformations can be conducted in purified enzyme or crude cell lysate systems. This concept circumvents mechanisms that have evolved to facilitate species survival, bypasses limitations on molecular transport across the cell wall, and provides a significant departure from traditional, cell-based processes that rely on microscopic cellular “reactors.” In addition, cell-free systems are inherently distributable through freeze-drying, which allows simple distribution before rehydration at the point-of-use. Furthermore, as cell-free systems are nonliving, they provide built-in safeguards for biocontainment without the constraints attendant on genetically modified organisms. These features have led to a significant increase in the development and use of CFE systems over the past two decades. Here, we discuss recent advances in CFE systems and highlight how they are transforming efforts to build cells, control genetic networks, and manufacture biobased products.

59 BASIC BIOLOGICAL SCIENCES↗

Phenylpropanoid Biosynthesis Gene Expression Precedes Lignin Accumulation During Shoot Development in Lowland and Upland Switchgrass Genotypes

Efficient conversion of lignocellulosic biomass into biofuels is influenced by biomass composition and structure. Lignin and other cell wall phenylpropanoids, such as para -coumaric acid ( p CA) and ferulic acid (FA), reduce cell wall sugar accessibility and hamper biochemical fuel production. Toward identifying the timing and key parameters of cell wall recalcitrance across different switchgrass genotypes, this study measured cell wall composition and lignin biosynthesis gene expression in three switchgrass genotypes, A4 and AP13, representing the lowland ecotype, and VS16, representing the upland ecotype, at three developmental stages [Vegetative 3 (V3), Elongation 4 (E4), and Reproductive 3 (R3)] and three segments (S1–S3) of the E4 stage under greenhouse conditions. A decrease in cell wall digestibility and an increase in phenylpropanoids occur across development. Compared with AP13 and A4, VS16 has significantly less lignin and greater cell wall digestibility at the V3 and E4 stages; however, differences among genotypes diminish by the R3 stage. Gini correlation analysis across all genotypes revealed that lignin and p CA, but also pectin monosaccharide components, show the greatest negative correlations with digestibility. Lignin and p CA accumulation is delayed compared with expression of phenylpropanoid biosynthesis genes, while FA accumulation coincides with expression of these genes. The different cell wall component accumulation profiles and gene expression correlations may have implications for system biology approaches to identify additional gene products with cell wall component synthesis and regulation functions.

09 BIOMASS FUELS↗

Expanding the application of a UV-visible reporter for transient gene expression and stable transformation in plants

Abstract Green fluorescent protein (GFP) has been widely used for monitoring gene expression and protein localization in diverse organisms. However, highly sensitive imaging equipment, like fluorescence microscope, is usually required for the visualization of GFP, limitings its application to fixed locations in samples. A reporter that can be visualized in real-time regardless the shape, size and location of the target samples will increase the flexibility and efficiency of research work. Here, we report the application of a GFP-like protein, called eYGFPuv, in both transient expression and stable transformation, in two herbaceous plant species ( Arabidopsis and tobacco) and two woody plant species (poplar and citrus). We observed bright fluorescence under UV light in all of the four plant species without any effects on plant growth or development. eYGFPuv was shown to be effective for imaging transient expression in leaf and root tissues. With a focus on in vitro transformation, we demonstrated that the transgenic events expressing 1x eYGFPuv could be easily identified visually during the callus stage and the shoot stage, enabling early and efficient selection of transformants. Furthermore, whole-plant level visualization of eYGFPuv revealed its ubiquitous stability in transgenic plants. In addition, our transformation experiments showed that eYGFPuv can also be used to select transgenic plants without antibiotics. This work demonstrates the feasibility of utilizing 1x eYGFPuv in studies of gene expression and plant transformation in diverse plants.

59 BASIC BIOLOGICAL SCIENCES↗

Francisella novicida Two-Component System Response Regulator BfpR Modulates iglC Gene Expression, Antimicrobial Peptide Resistance, and Biofilm Production

Response regulators are a critical part of the two-component system of gene expression regulation in bacteria, transferring a signal from a sensor kinase into DNA binding activity resulting in alteration of gene expression. In this study, we investigated a previously uncharacterized response regulator in Francisella novicida, FTN_1452 that we have named BfpR (Biofilm-regulating Francisella protein Regulator, FTN_1452). In contrast to another Francisella response regulator, QseB/PmrA, BfpR appears to be a negative regulator of biofilm production, and also a positive regulator of antimicrobial peptide resistance in this bacterium. The protein was crystallized and X-ray crystallography studies produced a 1.8 Å structure of the BfpR N-terminal receiver domain revealing interesting insight into its potential interaction with the sensor kinase. Structural analysis of BfpR places it in the OmpR/PhoP family of bacterial response regulators along with WalR and ResD. Proteomic and transcriptomic analyses suggest that BfpR overexpression affects expression of the critical Francisella virulence factor iglC, as well as other proteins in the bacterium. We demonstrate that mutation of bfpR is associated with an antimicrobial peptide resistance phenotype, a phenotype also associated with other response regulators, for the human cathelicidin peptide LL-37 and a sheep antimicrobial peptide SMAP-29. F. novicida with mutated bfpR replicated better than WT in intracellular infection assays in human-derived macrophages suggesting that the down-regulation of iglC expression in bfpR mutant may enable this intracellular replication to occur. Response regulators have been shown to play important roles in the regulation of bacterial biofilm production. We demonstrate that F. novicida biofilm formation was highly increased in the bfpR mutant, corresponding to altered glycogen synthesis. Waxworm infection experiments suggest a role of BfpR as a negative modulator of iglC expression with de-repression by Mg 2+ . In this study, we find that the response regulator BfpR may be a negative regulator of biofilm formation, and a positive regulator of antimicrobial peptide resistance in F. novicida.

59 BASIC BIOLOGICAL SCIENCES↗

Enhancers that direct gene expression to central nervous system vascular endothelial cells in vivo

CNS vascular endothelial cells (ECs) exhibit a distinctive gene expression program that is foundational for the blood-brain barrier (BBB). Previous research identified candidate cis-regulatory elements (CREs) that were hypothesized to control this program. In this work, transgenic mice and recombinant adeno-associated virus (rAAV) vectors have been used to interrogate these candidate CREs in vivo. These experiments show that an 850 bp genomic DNA segment ∼60 kb 5′ of Slc2a1 possesses enhancer activity that is (1) specific for BBB+ CNS ECs and (2) both necessary and sufficient for BBB+ EC gene expression. A screen of >8,000 genomic DNA segments from CNS EC-specific CRE candidates reveals several hundred with enhancer activity. Transcription factors ERG and LEF1 are shown to occupy sites in brain ECs that are highly enriched in candidate and experimentally validated CREs, lending strong support to a model in which canonical Wnt signaling activates the BBB program via LEF1.

CUT&RUN↗

Disease resistance in coral is mediated by distinct adaptive and plastic gene expression profiles

Infectious diseases are an increasing threat to coral reefs, resulting in altered community structure and hindering the functional contributions of disease-susceptible species. We exposed seven reef-building coral species from the Caribbean to white plague disease and determined processes involved in (i) lesion progression, (ii) within-species gene expression plasticity, and (iii) expression-level adaptation among species that lead to differences in disease risk. Gene expression networks enriched in immune genes and cytoskeletal arrangement processes were correlated to lesion progression rates. Whether or not a coral developed a lesion was mediated by plasticity in genes involved in extracellular matrix maintenance, autophagy, and apoptosis, while resistant coral species had constitutively higher expression of intracellular protein trafficking. This study offers insight into the process involved in lesion progression and within- and between-species dynamics that lead to differences in disease risk that is evident on current Caribbean reefs.

59 BASIC BIOLOGICAL SCIENCES↗

Changes in DNA Methylation in Response to 6-Benzylaminopurine Affect Allele-Specific Gene Expression in Populus Tomentosa

Cytokinins play important roles in the growth and development of plants. Physiological and photosynthetic characteristics are common indicators to measure the growth and development in plants. However, few reports have described the molecular mechanisms of physiological and photosynthetic changes in response to cytokinin, particularly in woody plants. DNA methylation is an essential epigenetic modification that dynamically regulates gene expression in response to the external environment. In this study, we examined genome-wide DNA methylation variation and transcriptional variation in poplar (Populus tomentosa) after short-term treatment with the synthetic cytokinin 6-benzylaminopurine (6-BA). We identified 460 significantly differentially methylated regions (DMRs) in response to 6-BA treatment. Transcriptome analysis showed that 339 protein-coding genes, 262 long non-coding RNAs (lncRNAs), and 15,793 24-nt small interfering RNAs (siRNAs) were differentially expressed under 6-BA treatment. Among these, 79% were differentially expressed between alleles in P. tomentosa, and 102,819 allele-specific expression (ASE) loci in 19,200 genes were detected showing differences in ASE levels after 6-BA treatment. Combined DNA methylation and gene expression analysis demonstrated that DNA methylation plays an important role in regulating allele-specific gene expression. To further investigate the relationship between these 6-BA-responsive genes and phenotypic variation, we performed SNP analysis of 460 6-BA-responsive DMRs via re-sequencing using a natural population of P. tomentosa, and we identified 206 SNPs that were significantly associated with growth and wood properties. Association analysis indicated that 53% of loci with allele-specific expression had primarily dominant effects on poplar traits. Our comprehensive analyses of P. tomentosa DNA methylation and the regulation of allele-specific gene expression suggest that DNA methylation is an important regulator of imbalanced expression between allelic loci.

54 ENVIRONMENTAL SCIENCES↗

Structural basis of differential gene expression at eQTLs loci from high-resolution ensemble models of 3D single-cell chromatin conformations

Abstract Motivation Techniques such as high-throughput chromosome conformation capture (Hi-C) have provided a wealth of information on nucleus organization and genome important for understanding gene expression regulation. Genome-Wide Association Studies have identified numerous loci associated with complex traits. Expression quantitative trait loci (eQTL) studies have further linked the genetic variants to alteration in expression levels of associated target genes across individuals. However, the functional roles of many eQTLs in noncoding regions remain unclear. Current joint analyses of Hi-C and eQTLs data lack advanced computational tools, limiting what can be learned from these data. Results We developed a computational method for simultaneous analysis of Hi-C and eQTL data, capable of identifying a small set of nonrandom interactions from all Hi-C interactions. Using these nonrandom interactions, we reconstructed large ensembles (×105) of high-resolution single-cell 3D chromatin conformations with thorough sampling, accurately replicating Hi-C measurements. Our results revealed many-body interactions in chromatin conformation at the single-cell level within eQTL loci, providing a detailed view of how 3D chromatin structures form the physical foundation for gene regulation, including how genetic variants of eQTLs affect the expression of associated eGenes. Furthermore, our method can deconvolve chromatin heterogeneity and investigate the spatial associations of eQTLs and eGenes at subpopulation level, revealing their regulatory impacts on gene expression. Together, ensemble modeling of thoroughly sampled single-cell chromatin conformations combined with eQTL data, helps decipher how 3D chromatin structures provide the physical basis for gene regulation, expression control, and aid in understanding the overall structure-function relationships of genome organization. Availability and implementation It is available at https://github.com/uic-liang-lab/3DChromFolding-eQTL-Loci.

Du, Lin (ORCID:0009000289869812)↗

Mechanistic Insights into Cell-Free Gene Expression through an Integrated -Omics Analysis of Extract Processing Methods

Cell-free systems derived from crude cell extracts have developed into tools for gene expression, with applications in prototyping, biosensing, and protein production. Key to the development of these systems is optimization of cell extract preparation methods. However, the applied nature of these optimizations often limits investigation into the complex nature of the extracts themselves, which contain thousands of proteins and reaction networks with hundreds of metabolites. In this report we sought to uncover the black box of proteins and metabolites in Escherichia coli cell-free reactions based on different extract preparation methods. We assess changes in transcription and translation activity from σ70 promoters in extracts prepared with acetate or glutamate buffer and the common post-lysis processing steps of a runoff incubation and dialysis. We then utilize proteomic and metabolomic analyses to uncover potential mechanisms behind these changes in gene expression, highlighting the impact of cold shock-like proteins and the role of buffer composition.

59 BASIC BIOLOGICAL SCIENCES↗

FUN-PROSE: A deep learning approach to predict condition-specific gene expression in fungi

mRNA levels of all genes in a genome is a critical piece of information defining the overall state of the cell in a given environmental condition. Being able to reconstruct such condition-specific expression in fungal genomes is particularly important to metabolically engineer these organisms to produce desired chemicals in industrially scalable conditions. Most previous deep learning approaches focused on predicting the average expression levels of a gene based on its promoter sequence, ignoring its variation across different conditions. Here we present FUN-PROSE—a deep learning model trained to predict differential expression of individual genes across various conditions using their promoter sequences and expression levels of all transcription factors. We train and test our model on three fungal species and get the correlation between predicted and observed condition-specific gene expression as high as 0.85. We then interpret our model to extract promoter sequence motifs responsible for variable expression of individual genes. We also carried out input feature importance analysis to connect individual transcription factors to their gene targets. A sizeable fraction of both sequence motifs and TF-gene interactions learned by our model agree with previously known biological information, while the rest corresponds to either novel biological facts or indirect correlations.

59 BASIC BIOLOGICAL SCIENCES↗