Synthetic Gene Research Articles

Lipopeptides from Bacillus velezensis ZLP-101 and their mode of action against bean aphids Acyrthosiphon pisum Harris

BackgroundNatural products are important sources for the discovery of new biopesticides to control the worldwide destructive pests Acyrthosiphon pisum Harris. Here, insecticidal substances were discovered and characterized from the secondary metabolites of the bio-control microorganism Bacillus velezensis strain ZLP-101, as informed by whole-genome sequencing and analysis.ResultsThe genome was annotated, revealing the presence of four potentially novel gene clusters and eight known secondary metabolite synthetic gene clusters. Crude extracts, prepared through ammonium sulfate precipitation, were used to evaluate the effects of strain ZLP-101 on Acyrthosiphon pisum Harris aphid pests via exposure experiments. The half lethal concentration (LC50) of the crude extract from strain ZLP-101 against aphids was 411.535 mg/L. Preliminary exploration of the insecticidal mechanism revealed that the crude extract affected aphids to a greater extent through gastric poisoning than through contact. Further, the extracts affected enzymatic activities, causing holes to form in internal organs along with deformation, such that normal physiological activities could not be maintained, eventually leading to death. Isolation and purification of extracellular secondary metabolites were conducted in combination with mass spectrometry analysis to further identify the insecticidal components of the crude extracts. A total of 15 insecticidal active compounds were identified including iturins, fengycins, surfactins, and spergualins. Further insecticidal experimentation revealed that surfactin, iturin, and fengycin all exhibited certain aphidicidal activities, and the three exerted synergistic lethal effects.ConclusionsThis study improved the available genomic resources for B. velezensis and serves as a foundation for comprehensive studies of the insecticidal mechanism by Bacillus velezensis ZLP-101 in addition to the active components within biological control strains.

Transcriptomic Analysis Reveals the Effect of Urea on Metabolism of Nannochloropsis oceanica.

The eukaryotic microalga Nannochloropsis oceanica represents a promising bioresource for the production of biofuels and pharmaceuticals. Urea, a crucial nutrient for the photosynthetic N. oceanica, stimulates the accumulation of substances such as lipids, which influence growth and physiology. However, the specific mechanisms by which N. oceanica responds and adapts to urea addition remain unknown. High-throughput mRNA sequencing and differential gene expression analysis under control and urea-added conditions revealed significant metabolic changes. This involved the differential expression of 2104 genes, with 1354 being upregulated and 750 downregulated, resulting in the reprogramming of crucial pathways such as carbon and nitrogen metabolism, photosynthesis, and lipid metabolism. The results specifically showed that genes associated with photosynthesis in N. oceanica were significantly downregulated, particularly those related to light-harvesting proteins. Interestingly, urea absorption and transport may depend not only on specialized transport channels such as urease but also on alternative transport channels such as the ABC transporter family and the CLC protein family. In addition, urea caused specific changes in carbon and lipid metabolism. Genes associated with the Calvin cycle and carbon concentration mechanisms were significantly upregulated. In lipid metabolism, the expression of genes associated with lipases and polyunsaturated fatty acid synthesis was highly activated. Furthermore, the expression of several genes involved in the tricarboxylic acid cycle and folate metabolism was enhanced, making important contributions to energy supply and the synthesis and modification of genes and macromolecules. Our observations indicate that N. oceanica actively and dynamically regulates the redistribution of carbon and nitrogen after urea addition, providing references for further research on the effects of urea on N. oceanica.

The efficient synthesis strategy of bacillomycin D in Bacillus amyloliquefaciens fmbJ

The cyclic lipopeptide bacillomycin D exhibits potent antifungal activity against a wide range of fungi, particularly filamentous fungi, thereby exhibiting significant potential for application in food preservation. However, the limited yield obtained from wild strains hinders the practical application of bacillomycin D. In this study, we used different strategies to modify the original strain Bacillus amyloliquefaciens fmbJ, including promoter replacement, competitive synthetic gene knockout, and overexpression of the lipopeptide transporter gene. Subsequently, we analyzed changes in the production and expression of bacillomycin D genes in the engineered strain. The results demonstrated that PbacA exhibits the highest promoter activity, leading to a significant increase (2.05-fold) in bacillomycin D production compared with control group. Additionally, deletion of the epsA-O gene cluster also significantly enhances the synthesis of bacillomycin D. However, when amyloid gene cluster tasA-sipW-yqxM was deleted,bacillomycin D accumulation time was shortened, resulting in no significant increase in bacillomycin D production. In addition, lipopeptide transporters SwrC, KrsE and YcxA did not promote bacillomycin D production. Finally, by replacing the promoter PbacA, we successfully disrupted the epsA-O gene cluster, and bacillomycin D production increased by 2.55 times compared to the initial bacillomycin D strain. In conclusion, this study indicated that genetic engineering of regulatory genes was an effective strategy to improve the yields of bacillomycin D and provided promising strains for industrial production of bacillomycin D.

Microbial Synthetic Epigenetic Tools Design and Applications.

Microbial synthetic epigenetics offers significant opportunities for the design of synthetic biology tools by leveraging reversible gene control mechanisms without altering DNA sequences. However, limited understanding and a lack of technologies for thorough analysis of the mechanisms behind epigenetic modifications have hampered their utilization in biotechnological applications. In this review, we explore advancements in developing epigenetic-based synthetic gene regulatory tools at both transcriptional and post-transcriptional levels. Furthermore, we examine strategies developed to construct epigenetic-based circuits that provide controllable and stable gene regulation, aiming to boost the performance of microbial chassis cells. Finally, we discuss the current challenges and perspectives in the development of synthetic epigenetic tools.

Rationally seeded computational protein design of ɑ-helical barrels

Computational protein design is advancing rapidly. Here we describe efficient routes starting from validated parallel and antiparallel peptide assemblies to design two families of α-helical barrel proteins with central channels that bind small molecules. Computational designs are seeded by the sequences and structures of defined de novo oligomeric barrel-forming peptides, and adjacent helices are connected by loop building. For targets with antiparallel helices, short loops are sufficient. However, targets with parallel helices require longer connectors; namely, an outer layer of helix–turn–helix–turn–helix motifs that are packed onto the barrels. Throughout these computational pipelines, residues that define open states of the barrels are maintained. This minimizes sequence sampling, accelerating the design process. For each of six targets, just two to six synthetic genes are made for expression in Escherichia coli. On average, 70% of these genes express to give soluble monomeric proteins that are fully characterized, including high-resolution structures for most targets that match the design models with high accuracy.

Effect of antibiotics on the expression of pyocyanin synthetic genes in Pseudomonas aeruginosa isolated from different clinical sources of a few hospitals in Mosul, Iraq

Effect of antibiotics on the expression of pyocyanin synthetic genes in Pseudomonas aeruginosa isolated from different clinical sources of a few hospitals in Mosul, Iraq

Genome-Wide Identification and Characterization of Lignin Synthesis Genes in Maize.

Lignin is a crucial substance in the formation of the secondary cell wall in plants. It is widely distributed in various plant tissues and plays a significant role in various biological processes. However, the number of copies, characteristics, and expression patterns of genes involved in lignin biosynthesis in maize are not fully understood. In this study, bioinformatic analysis and gene expression analysis were used to discover the lignin synthetic genes, and two representative maize inbred lines were used for stem strength phenotypic analysis and gene identification. Finally, 10 gene families harboring 117 related genes involved in the lignin synthesis pathway were retrieved in the maize genome. These genes have a high number of copies and are typically clustered on chromosomes. By examining the lignin content of stems and the expression patterns of stem-specific genes in two representative maize inbred lines, we identified three potential stem lodging resistance genes and their interactions with transcription factors. This study provides a foundation for further research on the regulation of lignin biosynthesis and maize lodging resistance genes.

Use of CRISPRoff and synthetic Notch to modulate and relay endogenous gene expression programs in engineered cells.

Uncovering the stimulus-response histories that give rise to cell fates and behaviors is an area of great interest in developmental biology, tissue engineering, and regenerative medicine. A comprehensive accounting of cell experiences that lead to the development of organs and tissues can help us to understand developmental anomalies that may underly disease. Perhaps more provocatively, such a record can also reveal clues as to how to drive cell collective decision-making processes, which may yield predictable cell-based therapies or facilitate production of tissue substitutes for transplantation or in vitro screening of prospective therapies to mitigate disease. Toward this end, various methods have been applied to molecularly trace developmental trajectories and record interaction histories of cells. Typical methods involve artificial gene circuits based on recombinases that activate a suite of fluorescent reporters or CRISPR-Cas9 genome writing technologies whose nucleic acid-based record keeping serves to chronicle cell-cell interactions or past exposure to stimuli of interests. Exciting expansions of the synthetic biology toolkit with artificial receptors that permit establishment of defined input-to-output linkages of cell decision-making processes opens the door to not only record cell-cell interactions, but to also potentiate directed manipulation of the outcomes of such interactions via regulation of carefully selected transgenes. Here, we combine CRISPR-based strategies to genetically and epigenetically manipulate cells to express components of the synthetic Notch receptor platform, a widely used artificial cell signaling module. Our approach gives rise to the ability to conditionally record interactions between human cells, where the record of engagement depends on expression of a state-specific marker of a subset of cells in a population. Further, such signal-competent interactions can be used to direct differentiation of human embryonic stem cells toward pre-selected fates based on assigned synNotch outputs. We also implemented CRISPR-based manipulation of native gene expression profiles to bias outcomes of cell engagement histories in a targeted manner. Thus, we present a useful strategy that gives rise to both state-specific recording of cell-cell interactions as well as methods to intentionally influence products of such cell-cell exchanges.

Overriding Mendelian inheritance in Arabidopsis with a CRISPR toxin-antidote gene drive that impairs pollen germination.

Synthetic gene drives, inspired by natural selfish genetic elements and transmitted to progeny at super-Mendelian (>50%) frequencies, present transformative potential for disseminating traits that benefit humans throughout wild populations, even facing potential fitness costs. Here we constructed a gene drive system in plants called CRISPR-Assisted Inheritance utilizing NPG1 (CAIN), which uses a toxin-antidote mechanism in the male germline to override Mendelian inheritance. Specifically, a guide RNA-Cas9 cassette targets the essential No Pollen Germination 1 (NPG1) gene, serving as the toxin to block pollen germination. A recoded, CRISPR-resistant copy of NPG1 serves as the antidote, providing rescue only in pollen cells that carry the drive. To limit potential consequences of inadvertent release, we used self-pollinating Arabidopsis thaliana as a model. The drive demonstrated a robust 88-99% transmission rate over two successive generations, producing minimal resistance alleles that are unlikely to inhibit drive spread. Our study provides a strong basis for rapid genetic modification or suppression of outcrossing plant populations.

Therapeutic expression of RAS Degrader RRSP in Pancreatic Cancer via Nanocarrier-mediated mRNA delivery.

About one-third of all human cancers encode abnormal RAS proteins locked in a constitutively activated state to drive malignant transformation and uncontrolled tumor growth. Despite progress in development of small molecules for treatment of mutant KRAS cancers, there is a need for a pan-RAS inhibitor that is effective against all RAS isoforms and variants and that avoids drug resistance. We have previously shown that the naturally occurring bacterial enzyme RAS/RAP1-specific endopeptidase (RRSP) is a potent RAS degrader that can be re-engineered as a biologic therapy to induce regression of colorectal, breast, and pancreatic tumors. Here, we have developed a strategy for in vivo expression of this RAS degrader via mRNA delivery using a synthetic nonviral gene delivery platform composed of the poly(ethylene glycol)-b-poly(propylene sulfide) (PEG-b-PPS) block copolymer conjugated to a dendritic cationic peptide (PPDP2). Using this strategy, PPDP2 is shown to deliver mRNA to both human and mouse pancreatic cells resulting in RRSP gene expression, activity, and loss of cell proliferation. Further, pancreatic tumors are reduced with residual tumors lacking detectable RAS and phosphorylated ERK. These data support that mRNA-loaded synthetic nanocarrier delivery of a RAS degrader can interrupt the RAS signaling system within pancreatic cancer cells while avoiding side effects during therapy.

Enhancing cell-based therapies with synthetic gene circuits responsive to molecular stimuli.

Synthetic biology aims to contribute to the development of next-generation patient-specific cell-based therapies for chronic diseases especially through the construction of sophisticated synthetic gene switches to enhance the safety and spatiotemporal controllability of engineered cells. Indeed, switches that sense and process specific cues, which may be either externally administered triggers or endogenous disease-associated molecules, have emerged as powerful tools for programming and fine-tuning therapeutic outputs. Living engineered cells, often referred to as designer cells, incorporating such switches are delivered to patients either as encapsulated cell implants or by infusion, as in the case of the clinically approved CAR-T cell therapies. Here, we review recent developments in synthetic gene switches responsive to molecular stimuli, spanning regulatory mechanisms acting at the transcriptional, translational, and posttranslational levels. We also discuss current challenges facing clinical translation of cell-based therapies employing these devices.

Abstract B013: Deep learning-based prediction of synthetic essentialities in CTNNB1-mutated hepatocellular carcinoma

Abstract Background: Synthetic essentiality represents a promising therapeutic approach by identifying genes that are necessary for the proliferation and survival of tumors harboring hard-to-target gene alterations. Understanding and accurately predicting synthetic essential genes, through genetic dependencies, may reveal therapeutically effective drug targets in a specific molecular context. Deep learning, as exemplified by our published DeepDEP model, has the potential to capture intricate multi-omic profiles for such prediction tasks. However, the validity of such tools in specific biological contexts remains to be fully examined and presents a major obstacle to adoption by researchers. Materials and Methods: To address this gap, we conducted a case study in which we screened for synthetic essential genes for one of the most frequently mutated and yet undruggable genes, CTNNB1, in hepatocellular carcinoma (HCC). Specifically, we predicted the genetic dependencies of each HCC patient in The Cancer Genome Atlas (TCGA; n=346) by DeepDEP and identified potential dependencies that were intensified with the presence of CTNNB1 mutations. The top 10 genes, ranked by p-value of differential gene-effect scores for CTNNB1-mutated (n=92) versus CTNNB1-WT HCC (n=254), were reviewed in the literature to validate their essentiality in CTNNB1-mutated HCC as well as their potential for pharmacologic inhibition. Survival analysis was performed using published data from the IMBrave150 trial to validate one of the findings. Results: Experimental evidence in the literature supported the essentiality of many of the top 10 predicted genes for CTNNB1-mutated HCC, including one gene with mechanistic evidence of being a transcriptional co-activator of β-catenin target genes. Furthermore, several of these genes have known pharmacologic inhibitors which are either natural compounds or FDA-approved drugs. One example was PDGFB, which encodes a ligand activating the PDGF signaling pathway. PDGF signaling is targeted by sorafenib, an FDA-approved first line drug for HCC. Survival analysis of the sorafenib-treated arm of the IMBrave150 trial showed that patients with mutated CTNNB1 had improved progression-free survival compared to those with wild-type CTNNB1 (p = 0.044). Conclusions: Our study illustrates a potential application of deep learning to identify synthetic essential genes, including genes with readily available pharmacologic inhibitors, for targeting challenging gene alterations. Remarkably, our tool demonstrates the ability to predict cancer dependencies with molecular subtype specificity, suggesting a potential for in silico screening of gene dependencies to facilitate drug discovery and personalized medicine approaches. Our current efforts are focused on optimizing this computational pipeline and making it publicly available for cancer researchers. Citation Format: Tyler M. Yasaka, Michael Kasper, Li-Ju Wang, Michael Ning, Yufei Huang, Satdarshan P Monga, Yu-Chiao Chiu. Deep learning-based prediction of synthetic essentialities in CTNNB1-mutated hepatocellular carcinoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr B013.

Abstract IA001: Exploiting pathway activation as a new form of synthetic lethality

Abstract Targeting activated oncogenes is an effective treatment strategy across many cancers now including therapeutics targeting KRAS. Genetic events including DNA damage deficiencies and tumor suppressor mutations require alternative strategies and the concept of synthetic lethality has been applied to these alterations. PARPi inhibitors were a founding member of this class of therapeutics demonstrating enhanced activity in the setting of BRCA-deficiency. By applying large-scale loss-of-function approaches1 we and other discovered the vulnerability to PRMT5 and WRN inhibition imposed by co-deletions of MTAP and CDKN2A, and the MSI+ genotype respectively2,3. Such inhibitors are now in clinical trials. To explore the potential for paralogous genes to act as synthetic lethal gene pairs we enacted dual knockout screens. These early efforts led to the discovery of DUSP4/6 paralog dependence in the setting of BRAF and NRAS mutations in melanoma4. Intriguingly the loss of DUSP4/6 impaired cancer cell viability through the increased activation of ERK highlighting the susceptibility of cancers to pathway activation in addition to the more common sensitivity to pathway inhibition. This inappropriate activation of the ERK signaling pathway, the conflict between EGFR and KRAS activation, the synthetic lethality enacted by TRIM8 knockouts, and the effects of AR agonists on prostate cancer viability, points to a wider than expected vulnerability of cancer to inappropriate gene activation. To systematically identify context-specific gene activation induced lethalities in cancer, we developed methods for enacting gain-of-function perturbations across ∼500 barcoded cancer cell lines. With this approach, we queried the pan-cancer vulnerability landscape upon activating 10 key cancer pathway revealing activation dependencies in MAPK and PI3K pathways. Notably, we discovered novel pathway hyperactivation dependencies in subsets of APC-mutant colorectal cancers where further activation of the WNT pathway by APC knockdown or direct β-catenin overexpression led to robust antitumor effects in xenograft and patient-derived organoid models. These latter discoveries paradoxically point to the residual activity of the APC ubiquitin-ligase complex as a target in APC-mutant CRC5. 1. McDonald, E. R., 3rd et al. Project DRIVE: A Compendium of Cancer Dependencies and Synthetic Lethal Relationships Uncovered by Large-Scale, Deep RNAi Screening. Cell 170, 577-592.e10 (2017). 2. Mavrakis, K. J. et al. Disordered methionine metabolism in MTAP/CDKN2A-deleted cancers leads to dependence on PRMT5. Science 351, 1208–1213 (2016). 3. Chan, E. M. et al. WRN helicase is a synthetic lethal target in microsatellite unstable cancers. Nature 568, 551–556 (2019). 4. Ito, T. et al. Paralog knockout profiling identifies DUSP4 and DUSP6 as a digenic dependence in MAPK pathway-driven cancers. Nat. Genet. 53, 1664–1672 (2021). 5. Chang, L. et al. Systematic profiling of conditional pathway activation identifies contextdependent synthetic lethalities. Nat. Genet. 55, 1709–1720 (2023). Citation Format: William R. Sellers. Exploiting pathway activation as a new form of synthetic lethality [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr IA001.

Regulatory properties of transcription factors with diverse mechanistic function.

Transcription factors (TFs) regulate the process of transcription through the modulation of different kinetic steps. Although models can often describe the observed transcriptional output of a measured gene, predicting a TFs role on a given promoter requires an understanding of how the TF alters each step of the transcription process. In this work, we use a simple model of transcription to assess the role of promoter identity, and the degree to which TFs alter binding of RNAP (stabilization) and initiation of transcription (acceleration) on three primary characteristics: the range of steady-state regulation, cell-to-cell variability in expression, and the dynamic response time of a regulated gene. We find that steady state regulation and the response time of a gene behave uniquely for TFs that regulate incoherently, i.e that speed up one step but slow the other. We also find that incoherent TFs have dynamic implications, with one type of incoherent mode configuring the promoter to respond more slowly at intermediate TF concentrations. We also demonstrate that the noise of gene expression for these TFs is sensitive to promoter strength, with a distinct non-monotonic profile that is apparent under stronger promoters. Taken together, our work uncovers the coupling between promoters and TF regulatory modes with implications for understanding natural promoters and engineering synthetic gene circuits with desired expression properties.

Deciphering regulatory architectures from synthetic single-cell expression patterns.

For the vast majority of genes in sequenced genomes, there is limited understanding of how they are regulated. Without such knowledge, it is not possible to perform a quantitative theory-experiment dialogue on how such genes give rise to physiological and evolutionary adaptation. One category of high-throughput experiments used to understand the sequence-phenotype relationship of the transcriptome is massively parallel reporter assays (MPRAs). However, to improve the versatility and scalability of MPRA pipelines, we need a "theory of the experiment" to help us better understand the impact of various biological and experimental parameters on the interpretation of experimental data. These parameters include binding site copy number, where a large number of specific binding sites may titrate away transcription factors, as well as the presence of overlapping binding sites, which may affect analysis of the degree of mutual dependence between mutations in the regulatory region and expression levels. To that end, in this paper we create tens of thousands of synthetic single-cell gene expression outputs using both equilibrium and out-of-equilibrium models. These models make it possible to imitate the summary statistics (information footprints and expression shift matrices) used to characterize the output of MPRAs and from this summary statistic to infer the underlying regulatory architecture. Specifically, we use a more refined implementation of the so-called thermodynamic models in which the binding energies of each sequence variant are derived from energy matrices. Our simulations reveal important effects of the parameters on MPRA data and we demonstrate our ability to optimize MPRA experimental designs with the goal of generating thermodynamic models of the transcriptome with base-pair specificity. Further, this approach makes it possible to carefully examine the mapping between mutations in binding sites and their corresponding expression profiles, a tool useful not only for better designing MPRAs, but also for exploring regulatory evolution.

Anethum graveolens L. restores expression of free fatty acid synthesis-related genes in high fat induced-HepG2 cells

IntroductionThe ethanolic extract of Anethum graveolens (dill) and its major constituents, chlorogenic acid (CGA) and ellagic acid (EA), were investigated for hepatoprotective effects in a HepG2 cell fatty liver model. MethodsHepG2 cells were induced with a combination of oleic (1mM OA) and palmitic (1mM PA) acids and treated with either 10 µM fenofibrate, 1-10 µg/mL CGA or EA, 60-360 µg/mL A. graveolens extract, or left untreated (n=4-5 per group). After 48 hours, cell medium and cells were collected for alanine transaminase (ALT), aspartate transaminase (AST), reactive oxygen species (ROS), and fatty acid accumulation assays. The mRNA and protein expression levels of free fatty acid (FFA) synthetic pathway-related genes were determined using reverse transcription/real-time polymerase chain reaction and Western blotting analysis, respectively. ResultsHepG2 cells treated with OA and PA showed increased ALT, AST, and ROS levels, fatty acid accumulation, and modified mRNA and protein expression of PPAR, SREBP1, ACC, ACOX, FAS, SCD1, and HMGCR fatty acid synthesis-related genes. The CGA, EA, and A. graveolens extract showed hepatoprotective activities in OA and PA-induced HepG2 cells by preventing fatty acid accumulation and restoring mRNA and protein expression levels of the fatty acid synthesis-related genes to control levels, with comparable efficacy to the standard anti-lipidemic drug, fenofibrate. Furthermore, CGA, EA, and A. graveolens extract did not increase ALT and ROS levels in HepG2 cells, in contrast to fenofibrate. ConclusionA. graveolens extract, CGA, and EA are good candidates for development as preventive health supplements for fatty liver disease therapy.

Kazuo Ishiguro’s Klara and the Sun: A Posthumanist Anatomization

Kazuo Ishiguro’s eighth novel Klara and the Sun is a quintessence to manifest Ishiguro’s power when he tactfully explored the new arena of technology that encompasses Artificial Intelligence and Gene Editing. The novel stands as a test of time to prove Ishiguro’s humanitarianism in the post era of pandemic. While transhumanism is on the rise, the society is in a great flux across the globe with speedy technology that marches to post humanist epoch. It is a watershed moment to wake up to the fact that breakthrough in technology has mixed blessings and albeit the high fidelity world provides sophisticated artificial intelligence to aid human existence, still there are certain things a machine has less competence doing. The article aims to give a panoramic view of how the novel foreshadows post anthropocentric world where it questions the identity of human dignity and how with the leading edge of technology viz. gene editing to push the frontier of the human excellence for the maximum reap will come home to roost.

Transgenic expression of artificial microRNA targeting soybean mosaic virus P1 gene confers virus resistance in plant.

RNA silencing is an innate immune mechanism of plants against invasion by viral pathogens. Artificial microRNA (amiRNA) can be engineered to specifically induce RNA silencing against viruses in transgenic plants and has great potential for disease control. Here, we describe the development and application of amiRNA-based technology to induce resistance to soybean mosaic virus (SMV), a plant virus with a positive-sense single-stranded RNA genome. We have shown that the amiRNA targeting the SMV P1 coding region has the highest antiviral activity than those targeting other SMV genes in a transient amiRNA expression assay. We transformed the gene encoding the P1-targeting amiRNA and obtained stable transgenic Nicotiana benthamiana lines (amiR-P1-3-1-2-1 and amiR-P1-4-1-2-1). Our results have demonstrated the efficient suppression of SMV infection in the P1-targeting amiRNA transgenic plants in an expression level-dependent manner. In particular, the amiR-P1-3-1-2-1 transgenic plant showed high expression of amiR-P1 and low SMV accumulation after being challenged with SMV. Thus, a transgenic approach utilizing the amiRNA technology appears to be effective in generating resistance to SMV.

Liver-specific glucocorticoid action in alcoholic liver disease: Study of glucocorticoid receptor knockout and knockin mice

Background and aimGlucocorticoids are the only first-line drugs for severe alcoholic hepatitis (AH), with limited efficacy and various side effects on extrahepatic tissues. Liver-targeting glucocorticoid therapy may have multiple advantages over systemic glucocorticoid for AH. The aim of this study was to determine the role of hepatocellular glucocorticoid receptor (GR) in alcohol-associated steatosis (AS) and AH. Materials and methodsAS was induced by a high-fat diet plus binge alcohol in adult male and female mice with liver-specific knockout (LKO) and heterozygote of GR. AH was induced by chronic-plus-binge in middle-aged male mice with liver-specific knockin of GR. Changes in hepatic mRNA and protein expression were determined by quantitative real-time polymerase chain reaction and Western blot. ResultsGR-LKO aggravated steatosis and decreased hepatic expression and circulating levels of albumin in both genders of AS mice but only increased markers of liver injury in male AS mice. Marked steatosis in GR-LKO mice was associated with induction of lipogenic genes and down-regulation of bile acid synthetic genes. Hepatic protein levels of GR, hepatocyte nuclear factor 4 alpha, and phosphorylated signal transducer and activator of transcription 3 were gene-dosage-dependently decreased, whereas that of lipogenic ATP citrate lyase was increased in male GR heterozygote and LKO mice. Interestingly, hepatic expression of estrogen receptor alpha (ERα) was induced, and the essential estrogen-inactivating enzyme sulfotransferase 1e1 was gene-dosage-dependently down-regulated in GR heterozygote and knockout AS mice, which was associated with induction of ERα-target genes. Liver-specific knockin of GR protected against liver injury and steatohepatitis in middle-aged AH mice. ConclusionsHepatic GR deficiency plays a crucial role in the pathogenesis of AS induced by high-fat diet plus binge, and liver-specific overexpression/activation of GR protects against chronic-plus-binge-induced AH in middle-aged mice. Hepatocellular GR is important for protection against AS and AH.

A high-throughput synthetic biology approach for studying combinatorial chromatin-based transcriptional regulation

The construction of synthetic gene circuits requires the rational combination of multiple regulatory components, but predicting their behavior can be challenging due to poorly understood component interactions and unexpected emergent behaviors. In eukaryotes, chromatin regulators (CRs) are essential regulatory components that orchestrate gene expression. Here, we develop a screening platform to investigate the impact of CR pairs on transcriptional activity in yeast. We construct a combinatorial library consisting of over 1,900 CR pairs and use a high-throughput workflow to characterize the impact of CR co-recruitment on gene expression. We recapitulate known interactions and discover several instances of CR pairs with emergent behaviors. We also demonstrate that supervised machine learning models trained with low-dimensional amino acid embeddings accurately predict the impact of CR co-recruitment on transcriptional activity. This work introduces a scalable platform and machine learning approach that can be used to study how networks of regulatory components impact gene expression.