Co-expression Of Multiple Genes Research Articles

Terminal-Enhanced Polymerization in the Biosynthesis of Polysialic Acid

Plasmids are commonly used tools in microbiology and molecular biology and have important and wide-ranging applications in the study of gene function, protein expression, and compound synthesis. The complex relationship between necessary antibiotic addition, compatibility between multiple plasmids, and the growth burden of host bacteria has plagued the wider use of compatibility plasmids. In this study, we constructed the terminal polymerization pathway of PSA by exogenously expressing the neuA, neuD, and neuS genes after the knockdown of Eschesrichia coli BL21 (DE3). Duet series vectors were utilized to regulate the expression level of neuA, neuD, and neuS genes to study the gene expression level, plasmid copy number growth burden, pressure of antibiotic addition, stability of compatible plasmids, and the level of expression stability of exogenous genes, as well as the effect on the biological reaction process. The results showed that the three genes, neuA, neuD, and neuS, were enhanced in the recombinant strain E. coli NA-05, with low copy, medium copy, and high copy, respectively. The effect of PSA synthesis under standard antibiotic pressure was remarkable. The results of this thesis suggest the use of a Duet series of compatible expression vectors to achieve the stable existence and co-expression of multiple genes in recombinant bacteria, which is a good reason for further research.

Gene Stacking and Stoichiometric Expression of ER-Targeted Constructs Using "2A" Self-Cleaving Peptides.

Simultaneous stoichiometric expression of multiple genes plays a major part in modern research and biotechnology. Traditional methods for incorporating multiple transgenes (or "gene stacking") have drawbacks such as long time frames, uneven gene expression, gene silencing, and segregation derived from the use of multiple promoters. 2A self-cleaving peptides have emerged over the last two decades as a functional gene stacking method and have been used in plants for the co-expression of multiple genes under a single promoter. Here we describe design features of multicistronic polyproteins using 2A peptides for co-expression in plant cells and targeting to the endoplasmic reticulum (ER). We designed up to quad-cistronic vectors that could target proteins in tandem to the ER. We also exemplify the incorporation of self-excising intein domains within 2A polypeptides, to remove residue additions. These features could aid in the design of stoichiometric protein co-expression strategies in plants in combination with targeting to different subcellular compartments.

Expanding the toolbox of probiotic Escherichia coli Nissle 1917 for synthetic biology.

Escherichia coli Nissle 1917 (EcN) is a probiotic microbe that has the potential to be developed as a promising chassis for synthetic biology applications. However, the molecular tools and techniques for utilizing EcN remain to be further explored. To address this opportunity, the EcN-based toolbox was systematically expanded, enabling EcN as a powerful platform for more applications. First, two EcN cryptic plasmids and other compatible plasmids were genetically engineered to enrich the manipulable plasmid toolbox for multiple gene coexpression. Next, two EcN-based technologies were developed, including the conjugation strategy for DNA transfer, and quantification of protein expression capability. Finally, the EcN-based applications were further expanded by developing EcN native integrase-mediated genetic engineering and establishing an in vitro cell-free protein synthesis (CFPS) system. Overall, this study expanded the toolbox for manipulating and making full use of EcN as a commonly used probiotic chassis, providing several simplified, dependable, and predictable strategies for researchers working in synthetic biology fields.

Comprehensive regulatory networks for tomato organ development based on the genome and RNAome of MicroTom tomato.

MicroTom has a short growth cycle and high transformation efficiency, and is a prospective model plant for studying organ development, metabolism, and plant-microbe interactions. Here, with a newly assembled reference genome for this tomato cultivar and abundant RNA-seq data derived from tissues of different organs/developmental stages/treatments, we constructed multiple gene co-expression networks, which will provide valuable clues for the identification of important genes involved in diverse regulatory pathways during plant growth, e.g. arbuscular mycorrhizal symbiosis and fruit development. Additionally, non-coding RNAs, including miRNAs, lncRNAs, and circRNAs were also identified, together with their potential targets. Interacting networks between different types of non-coding RNAs (miRNA-lncRNA), and non-coding RNAs and genes (miRNA-mRNA and lncRNA-mRNA) were constructed as well. Our results and data will provide valuable information for the study of organ differentiation and development of this important fruit. Lastly, we established a database (http://eplant.njau.edu.cn/microTomBase/) with genomic and transcriptomic data, as well as details of gene co-expression and interacting networks on MicroTom, and this database should be of great value to those who want to adopt MicroTom as a model plant for research.

A polycistronic system for multiplexed and precalibrated expression of multigene pathways in fungi

Synthetic biology requires efficient systems that support the well-coordinated co-expression of multiple genes. Here, we discover a 9-bp nucleotide sequence that enables efficient polycistronic gene expression in yeasts and filamentous fungi. Coupling polycistronic expression to multiplexed, markerless, CRISPR/Cas9-based genome editing, we develop a strategy termed HACKing (Highly efficient and Accessible system by CracKing genes into the genome) for the assembly of multigene pathways. HACKing allows the expression level of each enzyme to be precalibrated by linking their translation to those of host proteins with predetermined abundances under the desired fermentation conditions. We validate HACKing by rapidly constructing highly efficient Saccharomyces cerevisiae cell factories that express 13 biosynthetic genes, and produce model endogenous (1,090.41 ± 80.92 mg L−1 squalene) or heterologous (1.04 ± 0.02 mg L−1 mogrol) terpenoid products. Thus, HACKing addresses the need of synthetic biology for predictability, simplicity, scalability, and speed upon fungal pathway engineering for valuable metabolites.

Integrative Functional Transcriptomic Analyses Implicate Shared Molecular Circuits in Sensorineural Hearing Loss.

Sensorineural hearing loss (SNHL) is referred to as the most common type of hearing loss and typically occurs when the inner ear or the auditory nerve is damaged. Aging, noise exposure, and ototoxic drugs represent three main causes of SNHL, leading to substantial similarities in pathophysiological characteristics of cochlear degeneration. Although the common molecular mechanisms are widely assumed to underlie these similarities, its validity lacks systematic examination. To address this question, we generated three SNHL mouse models from aging, noise exposure, and cisplatin ototoxicity, respectively. Through constructing gene co-expression networks for the cochlear transcriptome data across different hearing-damaged stages, the three models are found to significantly correlate with each other in multiple gene co-expression modules that implicate distinct biological functions, including apoptosis, immune, inflammation, and ion transport. Bioinformatics analyses reveal several potential hub regulators, such as IL1B and CCL2, both of which are verified to contribute to apoptosis accompanied by the increase of (ROS) in in vitro model system. Our findings disentangle the shared molecular circuits across different types of SNHL, providing potential targets for the broad effective therapeutic agents in SNHL.

An analysis of genetically regulated gene expression and the role of co-expression networks across 16 psychiatric and substance use phenotypes.

Genome-wide association studies (GWASs) have identified thousands of risk loci for psychiatric and substance use phenotypes, however the biological consequences of these loci remain largely unknown. We performed a transcriptome-wide association study of 10 psychiatric disorders and 6 substance use phenotypes (GWAS sample size range, N = 9725-807,553) using expression quantitative trait loci data from 532 prefrontal cortex samples. We estimated the correlation of genetically regulated expression between phenotype pairs, and compared the results with the genetic correlations. We identified 393 genes with at least one significant phenotype association, comprising 458 significant associations across 16 phenotypes. Overall, the transcriptomic correlations for phenotype pairs were significantly higher than the respective genetic correlations. For example, attention deficit hyperactivity disorder and autism spectrum disorder, both childhood developmental disorders, had significantly higher transcriptomic correlation (r = 0.84) than genetic correlation (r = 0.35). Finally, we tested the enrichment of phenotype-associated genes in gene co-expression networks built from human prefrontal cortex samples. Phenotype-associated genes were enriched in multiple gene co-expression modules and the implicated modules contained genes involved in mRNA splicing and glutamatergic receptors, among others. Together, our results highlight the utility of gene expression data in the understanding of functional gene mechanisms underlying psychiatric disorders and substance use phenotypes.

Impact of Molecular Modification on the Efficiency of Recombinant Baculovirus Vector Invasion to Mammalian Cells and Its Immunogenicity in Mice.

The baculovirus display system (BDS), an excellent eukaryotic surface display technology that offers the advantages of safety, efficiency, and economy, is widely used in biomedicine. A previous study using rBacmid-Δgp64-ires-gp64 expressed in low copy numbers of the gp64 gene achieved high-efficiency expression and co-display of three fluorescent proteins (GFP, YFP, and mCherry). However, low expression of GP64 in recombinant baculoviruses also reduces the efficiency of recombinant baculovirus transduction into mammalian cells. In addition, the baculovirus promoter has no expression activity in mammalian cells and thus cannot meet the application requirements of baculoviral vectors for the BDS. Based on previous research, this study first determined the expression activity of promoters in insect Spodoptera frugiperda 9 cells and mammalian cells and successfully screened the very early promoter pie1 to mediate the co-expression of multiple genes. Second, utilizing the envelope display effect of the INVASIN and VSVG proteins, the efficiency of transduction of recombinant baculovirus particles into non-host cells was significantly improved. Finally, based on the above improvement, a recombinant baculovirus vector displaying four antigen proteins with high efficiency was constructed. Compared with traditional BDSs, the rBacmid-Δgp64 system exhibited increased display efficiency of the target protein by approximately 3-fold and induced an approximately 4-fold increase in the titer of serum antibodies to target antigens in Bal B/c mice. This study systematically explored the application of a new multi-gene co-display technology applicable to multi-vaccine research, and the results provide a foundation for the development of novel BDS technologies.

Rapid Combinatorial Coexpression of Biosynthetic Genes by Transient Expression in the Plant Host Nicotiana benthamiana.

Metabolic engineering of heterologous hosts requires coexpression of multiple genes, often more than ten for a single pathway. Traditional approaches to create genetic constructs for this purpose are highly inflexible and suffer from very low throughput. In this book chapter, we describe a powerful method to overcome this bottleneck, namely, combinatorial co-expression in the Australian tobacco plant Nicotiana benthamiana. This system is based on Agrobacterium tumefaciens-mediated transient gene expression, often called agroinfiltration. Herein, instead of creating complex multigenic constructs, coexpression is achieved by simply mixing different plasmid-bearing Agrobacterium strains without the need for different selection markers. We present a practical guide for coexpressing multiple biosynthetic genes followed by GC-MS analysis, using production of the plant triterpene β-amyrin as an example. Our chapter provides a guideline to harness the potential of this versatile expression system in the natural product community for studying and engineering metabolic pathways.

Analysis of multiple gene co-expression networks to discover interactions favoring CFTR biogenesis and \u0394F508-CFTR rescue

BackgroundWe previously reported that expression of a miR-138 mimic or knockdown of SIN3A in primary cultures of cystic fibrosis (CF) airway epithelia increased ΔF508-CFTR mRNA and protein levels, and partially restored CFTR-dependent chloride transport. Global mRNA transcript profiling in ΔF508-CFBE cells treated with miR-138 mimic or SIN3A siRNA identified two genes, SYVN1 and NEDD8, whose inhibition significantly increased ΔF508-CFTR trafficking, maturation, and function. Little is known regarding the dynamic changes in the CFTR gene network during such rescue events. We hypothesized that analysis of condition-specific gene networks from transcriptomic data characterizing ΔF508-CFTR rescue could help identify dynamic gene modules associated with CFTR biogenesis.MethodsWe applied a computational method, termed M-module, to analyze multiple gene networks, each of which exhibited differential activity compared to a baseline condition. In doing so, we identified both unique and shared gene pathways across multiple differential networks. To construct differential networks, gene expression data from CFBE cells were divided into three groups: (1) siRNA inhibition of NEDD8 and SYVN1; (2) miR-138 mimic and SIN3A siRNA; and (3) temperature (27 °C for 24 h, 40 °C for 24 h, and 27 °C for 24 h followed by 40 °C for 24 h).ResultsInterrogation of individual networks (e.g., NEDD8/SYVN1 network), combinations of two networks (e.g., NEDD8/SYVN1 + temperature networks), and all three networks yielded sets of 1-modules, 2-modules, and 3-modules, respectively. Gene ontology analysis revealed significant enrichment of dynamic modules in pathways including translation, protein metabolic/catabolic processes, protein complex assembly, and endocytosis. Candidate CFTR effectors identified in the analysis included CHURC1, GZF1, and RPL15, and siRNA-mediated knockdown of these genes partially restored CFTR-dependent transepithelial chloride current to ΔF508-CFBE cells.ConclusionsThe ability of the M-module to identify dynamic modules involved in ΔF508 rescue provides a novel approach for studying CFTR biogenesis and identifying candidate suppressors of ΔF508.

632: Analysis of multiple gene co-expression networks identifies CHURC1, GZF1, and RPL15 as negative effectors of CFTR biogenesis and ΔF508-CFTR rescue

632: Analysis of multiple gene co-expression networks identifies CHURC1, GZF1, and RPL15 as negative effectors of CFTR biogenesis and ΔF508-CFTR rescue

New function of a well‐known promoter: Enhancer activity of minimal CMV promoter enables efficient dual‐cassette transgene expression

Co-expression of multiple genes in single vectors has achieved varying degrees of success by employing two promoters and/or application of viral 2A-peptide or the internal ribosome entry-site (IRES). However, promoter interference, potential functional-interruption of expressed-proteins by 2A-generated residual peptides or weaker translation of IRES-mediated downstream genes has curtailed their utilization. Thus, there is the need for single vectors that robustly express multiple proteins for enhanced gene therapy applications. We engineered lentiviral-vectors for dual-cassette expression of green fluorescent protein and mCherry in uni- or bidirectional architectures using the short-version (Es) of elongation factor 1α (EF) promoter and simian virus 40 promoter (Sv). The regulatory function of a core fragment (cC) from human cytomegalovirus promoter was investigated with cell-lineage specificity in NIH3T3 (fibroblast) and hematopoietic cell lines U937 (monocyte/macrophage), LCL (lymphoid), DAMI (megakaryocyte) and MEL (erythroid). The cC element in reverse-orientation not only boosted upstream Es promoter to levels comparable to full-length EF in DAMI, U937 and 3T3 cells, but also blocked the suppression of downstream Sv promoter by Es in U937 and 3T3 cells with further improved Sv activity in DAMI cells. Such lineage-restricted up-regulation is likely attributed to two protein-binding domains of cC and diverse expression of related factors in different cell types for enhancer and terminator activities, but not spacing function. Such a newly developed dual-cassette vector could be advantageous, particularly in hematopoietic cell-mediated gene/cancer therapy, by allowing for independent and robust co-expression of therapeutic gene(s) and/or a selectable gene or imaging marker in the same cells.

Computational analysis of fused co-expression networks for the identification of candidate cancer gene biomarkers

The complexity of cancer has always been a huge issue in understanding the source of this disease. However, by appreciating its complexity, we can shed some light on crucial gene associations across and in specific cancer types. In this study, we develop a general framework to infer relevant gene biomarkers and their gene-to-gene associations using multiple gene co-expression networks for each cancer type. Specifically, we infer computationally and biologically interesting communities of genes from kidney renal clear cell carcinoma, liver hepatocellular carcinoma, and prostate adenocarcinoma data sets of The Cancer Genome Atlas (TCGA) database. The gene communities are extracted through a data-driven pipeline and then evaluated through both functional analyses and literature findings. Furthermore, we provide a computational validation of their relevance for each cancer type by comparing the performance of normal/cancer classification for our identified gene sets and other gene signatures, including the typically-used differentially expressed genes. The hallmark of this study is its approach based on gene co-expression networks from different similarity measures: using a combination of multiple gene networks and then fusing normal and cancer networks for each cancer type, we can have better insights on the overall structure of the cancer-type-specific network.

Rapid single cell evaluation of human disease and disorder targets using REVEAL: SingleCell\u2122

BackgroundSingle-cell (sc) sequencing performs unbiased profiling of individual cells and enables evaluation of less prevalent cellular populations, often missed using bulk sequencing. However, the scale and the complexity of the sc datasets poses a great challenge in its utility and this problem is further exacerbated when working with larger datasets typically generated by consortium efforts. As the scale of single cell datasets continues to increase exponentially, there is an unmet technological need to develop database platforms that can evaluate key biological hypotheses by querying extensive single-cell datasets.Large single-cell datasets like Human Cell Atlas and COVID-19 cell atlas (collection of annotated sc datasets from various human organs) are excellent resources for profiling target genes involved in human diseases and disorders ranging from oncology, auto-immunity, as well as infectious diseases like COVID-19 caused by SARS-CoV-2 virus. SARS-CoV-2 infections have led to a worldwide pandemic with massive loss of lives, infections exceeding 7 million cases. The virus uses ACE2 and TMPRSS2 as key viral entry associated proteins expressed in human cells for infections. Evaluating the expression profile of key genes in large single-cell datasets can facilitate testing for diagnostics, therapeutics, and vaccine targets, as the world struggles to cope with the on-going spread of COVID-19 infections.Main bodyIn this manuscript we describe REVEAL: SingleCell, which enables storage, retrieval, and rapid query of single-cell datasets inclusive of millions of cells. The array native database described here enables selecting and analyzing cells across multiple studies. Cells can be selected using individual metadata tags, more complex hierarchical ontology filtering, and gene expression threshold ranges, including co-expression of multiple genes. The tags on selected cells can be further evaluated for testing biological hypotheses. One such example includes identifying the most prevalent cell type annotation tag on returned cells.We used REVEAL: SingleCell to evaluate the expression of key SARS-CoV-2 entry associated genes, and queried the current database (2.2 Million cells, 32 projects) to obtain the results in < 60 s. We highlighted cells expressing COVID-19 associated genes are expressed on multiple tissue types, thus in part explains the multi-organ involvement in infected patients observed worldwide during the on-going COVID-19 pandemic.ConclusionIn this paper, we introduce the REVEAL: SingleCell database that addresses immediate needs for SARS-CoV-2 research and has the potential to be used more broadly for many precision medicine applications. We used the REVEAL: SingleCell database as a reference to ask questions relevant to drug development and precision medicine regarding cell type and co-expression for genes that encode proteins necessary for SARS-CoV-2 to enter and reproduce in cells.

Serial gene co-expression network approach to mine biological meanings from integrated transcriptomes of the porcine endometrium during estrous cycle.

The estrous cycle is a complex process regulated by several hormones. To understand the dynamic changes in gene expression that takes place in the swine endometrium during the estrous cycle relative to the day of estrus onset, we performed RNA-sequencing analysis on days 0, 3, 6, 9, 12, 15, and 18, resulting in the identification of 4495 differentially expressed genes (DEGs; Q ≤ 0.05 and |log2FC| ≥ 1) at various phases in the estrous cycle. These DEGs were integrated into multiple gene co-expression networks based on different fold changes and correlation coefficient (R2) thresholds and a suitable network, which included 899 genes (|log2FC| ≥ 2 and R2 ≥ 0.99), was identified for downstream analyses based on the biological relevance of the Gene Ontology (GO) terms enriched. The genes in this network were partitioned into 6 clusters based on the expression pattern. Several GO terms including cell cycle, apoptosis, hormone signaling, and lipid biosynthetic process were found to be enriched. Furthermore, we found 15 significant KEGG pathways, including cell adhesion molecules, cytokine-cytokine receptor signaling, steroid biosynthesis, and estrogen signaling pathways. We identified several genes and GO terms to be stage-specific. Moreover, the identified genes and pathways extend our understanding of porcine endometrial regulation during estrous cycle and will serve as a good resource for future studies.

Optimization of a 2A self-cleaving peptide-based multigene expression system for efficient expression of upstream and downstream genes in silkworm.

The multigene expression system is highly attractive to co-express multiple genes or multi-subunit complex-based genes for their functional studies, and in gene therapy and visual tracking of expressed proteins. However, the current multiple gene co-expression strategies usually suffer from severe inefficiency and unbalanced expression of multiple genes. Here, we report on an improved 2A self-cleaving peptide (2A)-based multigene expression system (2A-MGES), by introducing an optimized Kozak region (Ck) and altering the gene arrangement, both of which contributed to the efficient expression of two fluorescent protein genes in silkworm. By co-expressing DsRed and EGFP genes in insect cells and silkworms, the potent Ck was first found to improve the translation efficiency of downstream genes, and the expression of the flanking genes of 2A were improved by altering the gene arrangement in 2A-MGES. Moreover, we showed that combining Ck and an optimized gene arrangement in 2A-MGES could synergistically improve the expression of genes in the cell. Further, these two flanking genes, regulated by modified 2A-MGES, were further co-expressed in the middle silk gland and secreted into the cocoon, and both achieved efficient expression in the transgenic silkworms and their cocoons. These results suggested that the modified Ck-2A-MGES will be a potent tool for multiple gene expression, for studies of their functions, and their applications in insect species.

Coexpression network analysis identifies transcriptional modules associated with genomic alterations in neuroblastoma

Neuroblastoma is a highly complex and heterogeneous cancer in children. Acquired genomic alterations including MYCN amplification, 1p deletion and 11q deletion are important risk factors and biomarkers in neuroblastoma. Here, we performed a co-expression-based gene network analysis to study the intrinsic association between specific genomic changes and transcriptome organization. We identified multiple gene coexpression modules which are recurrent in two independent datasets and associated with functional pathways including nervous system development, cell cycle, immune system process and extracellular matrix/space. Our results also indicated that modules involved in nervous system development and cell cycle are highly associated with MYCN amplification and 1p deletion, while modules responding to immune system process are associated with MYCN amplification only. In summary, this integrated analysis provides novel insights into molecular heterogeneity and pathogenesis of neuroblastoma. This article is part of a Special Issue entitled: Accelerating Precision Medicine through Genetic and Genomic Big Data Analysis edited by Yudong Cai & Tao Huang.

Construction of the IRES-based Vector for Multiple Gene Co-expression

Construction of the IRES-based Vector for Multiple Gene Co-expression

A vector for multiple gene co-expression in Chlamydomonas reinhardtii

The expression or regulation of multiple genes in a metabolic pathway is an important approach for enhancing and adding value to production in Chlamydomonas reinhardtii. However, few methods for such an approach have been reported. Here, we describe a novel method for multi-gene co-expression in C. reinhardtii, using the vector pJDHSP. With this vector, multi-gene expression cassettes can be easily constructed in vitro by simple digestion and ligation. Using this vector, we successfully co-expressed codon-optimized luciferase and GFP genes.

Development of all-in-one multicistronic Tet-On lentiviral vectors for inducible co-expression of two transgenes.

Inducible co-expression of multiple genes is often needed in research. Here we describe a single-vector-based Tet-On inducible system for co-expression of two transgenes. The two transgenes (DsRed1 and eGFP as model genes) and reverse tetracycline-controlled transactivator were separated by internal ribosomal entry sites and 2A sequences, and their transcription was controlled by the same tetracycline responsive element. Two novel vectors with different internal ribosomal entry sites and 2A positions on the vectors were constructed. The DsRed1 and eGFP in cells transduced with both vectors are undetectable in the absence of doxycycline and can be efficiently induced in the presence of doxycycline in vitro and in vivo. These two vectors can be useful tools when regulated co-expression of two ecotopic genes is needed.