Precise tuning of gene expression levels in mammalian cells

Programming anti-ribozymes to sense trigger RNAs for modulating gene expression in mammalian cells

Synthetic RNA-based switches provide distinctive merits in modulating gene expression. Simple and flexible RNA-based switches are crucial for advancing the field of gene regulation, paving the way for innovative tools that can sense and manipulate cellular processes. In this research, we have developed programmable ribozymes that are capable of suppressing gene expression in response to specific, endogenously expressed trigger RNAs. We engineer ribozymes by introducing upstream antisense sequences (anti-ribozymes) to inhibit the self-cleaving activity of the hammerhead ribozyme and open the expression of the target gene. The trigger RNA is designed to recognize and bind to complementary sequences within the anti-ribozymes, thereby inhibiting their ability to direct protein synthesis. The anti-ribozyme performance is optimized by regulating the essential sequence modules that play a crucial role in determining the specificity and efficiency of the anti-ribozyme's interaction with its trigger RNA. By applying this switch mechanism to various ribozyme designs, we have shown that it is possible to achieve control over gene expression across a wide range of trigger RNAs. By exploiting these programmable anti-ribozymes, we aim to create a powerful tool for controlling gene expression in mammalian cells, which could have important implications for basic research, disease diagnosis, and therapeutic interventions.

MiRNA Chaining for Efficient Stable Overexpression to Improve Protein Quantity and Quality in CHO Cells

MicroRNAs (miRNAs), small noncoding RNAs with a length of about 22 nucleotides, harbor the potential to be powerful tools for the genetic engineering of production cell lines like Chinese hamster ovary (CHO) cells. Their ability to regulate multiple targets at once and their potential to fine-tune effect strengths contrast with classical engineering approaches. However, most studies of miRNAs rely on transiently flooding the cells with miRNA mimics. Since this approach is not suitable for long-term cultivation in a bioprocess, stable overexpression of miRNAs becomes more and more important for the biotech industry. Here, the user might be confronted with insufficient overexpression of the miRNA of interest. In this chapter, we present a method for the generation of stable CHO cell lines expressing a miRNA from a plasmid-based system containing multiple copies of the miRNA, allowing tuning of overexpression and regulation.

Harnessing Gene Editing Technology for Tumor Microenvironment Modulation: An Emerging Anticancer Strategy

Cancer is a multifaceted disease influenced by both intrinsic cellular traits and extrinsic factors, with the tumor microenvironment (TME) being crucial for cancer progression. To satisfy their high proliferation and aggressiveness, cancer cells always plunder large amounts of nutrients and release various signals to their surroundings, forming a dynamic TME with special metabolic, immune, microbial and physical characteristics. Due to the neglect of interactions between tumor cells and the TME, traditional cancer therapies often struggle with challenges such as drug resistance, low efficacy, and recurrence. Importantly, the development of gene editing technologies, particularly the CRISPR-Cas system, offers promising new strategies for cancer treatment. Combined with nanomaterial strategies, CRISPR-Cas technology exhibits precision, affordability, and user-friendliness with reduced side effects, which holds great promise for profoundly altering the TME at the genetic level, potentially leading to lasting anticancer outcomes. This review will delve into how CRISPR-Cas can be leveraged to manipulate the TME, examining its potential as a transformative anticancer therapy.

Coding, or non-coding, that is the question

The advent of high-throughput sequencing uncovered that our genome is pervasively transcribed into RNAs that are seemingly not translated into proteins. It was also found that non-coding RNA transcripts outnumber canonical protein-coding genes. This mindboggling discovery prompted a surge in non-coding RNA research that started unraveling the functional relevance of these new genetic units, shaking the classic definition of "gene". While the non-coding RNA revolution was still taking place, polysome/ribosome profiling and mass spectrometry analyses revealed that peptides can be translated from non-canonical open reading frames. Therefore, it is becoming evident that the coding vs non-coding dichotomy is way blurrier than anticipated. In this review, we focus on several examples in which the binary classification of coding vs non-coding genes is outdated, since the same bifunctional gene expresses both coding and non-coding products. We discuss the implications of this intricate usage of transcripts in terms of molecular mechanisms of gene expression and biological outputs, which are often concordant, but can also surprisingly be discordant. Finally, we discuss the methodological caveats that are associated with the study of bifunctional genes, and we highlight the opportunities and challenges of therapeutic exploitation of this intricacy towards the development of anticancer therapies.

Advances in delivery systems for CRISPR/Cas-mediated cancer treatment: a focus on viral vectors and extracellular vesicles

The delivery of CRISPR/Cas systems holds immense potential for revolutionizing cancer treatment, with recent advancements focusing on extracellular vesicles (EVs) and viral vectors. EVs, particularly exosomes, offer promising opportunities for targeted therapy due to their natural cargo transport capabilities. Engineered EVs have shown efficacy in delivering CRISPR/Cas components to tumor cells, resulting in inhibited cancer cell proliferation and enhanced chemotherapy sensitivity. However, challenges such as off-target effects and immune responses remain significant hurdles. Viral vectors, including adeno-associated viruses (AAVs) and adenoviral vectors (AdVs), represent robust delivery platforms for CRISPR/Cas systems. AAVs, known for their safety profile, have already been employed in clinical trials for gene therapy, demonstrating their potential in cancer treatment. AdVs, capable of infecting both dividing and non-dividing cells, offer versatility in CRISPR/Cas delivery for disease modeling and drug discovery. Despite their efficacy, viral vectors present several challenges, including immune responses and off-target effects. Future directions entail refining delivery systems to enhance specificity and minimize adverse effects, heralding personalized and effective CRISPR/Cas-mediated cancer therapies. This article underscores the importance of optimized delivery mechanisms in realizing the full therapeutic potential of CRISPR/Cas technology in oncology. As the field progresses, addressing these challenges will be pivotal for translating CRISPR/Cas-mediated cancer treatments from bench to bedside.

Unlocking the potential of iPSC-derived immune cells: engineering iNK and iT cells for cutting-edge immunotherapy

Induced pluripotent stem cells (iPSCs) have emerged as a revolutionary tool in cell therapies due to their ability to differentiate into various cell types, unlimited supply, and potential as off-the-shelf cell products. New advances in iPSC-derived immune cells have generated potent iNK and iT cells which showed robust killing of cancer cells in animal models and clinical trials. With the advent of advanced genome editing technologies that enable the development of highly engineered cells, here we outline 12 strategies to engineer iPSCs to overcome limitations and challenges of current cell-based immunotherapies, including safety switches, stealth edits, avoiding graft-versus-host disease (GvHD), targeting, reduced lymphodepletion, efficient differentiation, increased in vivo persistence, stemness, metabolic fitness, homing/trafficking, and overcoming suppressive tumor microenvironment and stromal cell barrier. With the development of advanced genome editing techniques, it is now possible to insert large DNA sequences into precise genomic locations without the need for DNA double strand breaks, enabling the potential for multiplexed knock out and insertion. These technological breakthroughs have made it possible to engineer complex cell therapy products at unprecedented speed and efficiency. The combination of iPSC derived iNK, iT and advanced gene editing techniques provides new opportunities and could lead to a new era for next generation of cell immunotherapies.

Using Chemistry To Recreate the Complexity of the Extracellular Matrix: Guidelines for Supramolecular Hydrogel-Cell Interactions

Hydrogels have emerged as a promising class of extracellular matrix (ECM)-mimicking materials in regenerative medicine. Here, we briefly describe current state-of-the-art of ECM-mimicking hydrogels, ranging from natural to hybrid to completely synthetic versions, giving the prelude to the importance of supramolecular interactions to make true ECM mimics. The potential of supramolecular interactions to create ECM mimics for cell culture is illustrated through a focus on two different supramolecular hydrogel systems, both developed in our laboratories. We use some recent, significant findings to present important design principles underlying the cell-material interaction. To achieve cell spreading, we propose that slow molecular dynamics (monomer exchange within fibers) is crucial to ensure the robust incorporation of cell adhesion ligands within supramolecular fibers. Slow bulk dynamics (stress-relaxation─fiber rearrangements, τ1/2 ≈ 1000 s) is required to achieve cell spreading in soft gels (<1 kPa), while gel stiffness overrules dynamics in stiffer gels. Importantly, this resonates with the findings of others which specialize in different material types: cell spreading is impaired in case substrate relaxation occurs faster than clutch binding and focal adhesion lifetime. We conclude with discussing considerations and limitations of the supramolecular approach as well as provide a forward thinking perspective to further understand supramolecular hydrogel-cell interactions. Future work may utilize the presented guidelines underlying cell-material interactions to not only arrive at the next generation of ECM-mimicking hydrogels but also advance other fields, such as bioelectronics, opening up new opportunities for innovative applications.

Effect of genomic and cellular environments on gene expression noise

BACKGROUND

Individual cells from isogenic populations often display large cell-to-cell differences in gene expression. This "noise" in expression derives from several sources, including the genomic and cellular environment in which a gene resides. Large-scale maps of genomic environments have revealed the effects of epigenetic modifications and transcription factor occupancy on mean expression levels, but leveraging such maps to explain expression noise will require new methods to assay how expression noise changes at locations across the genome.

RESULTS

To address this gap, we present Single-cell Analysis of Reporter Gene Expression Noise and Transcriptome (SARGENT), a method that simultaneously measures the noisiness of reporter genes integrated throughout the genome and the global mRNA profiles of individual reporter-gene-containing cells. Using SARGENT, we perform the first comprehensive genome-wide survey of how genomic locations impact gene expression noise. We find that the mean and noise of expression correlate with different histone modifications. We quantify the intrinsic and extrinsic components of reporter gene noise and, using the associated mRNA profiles, assign the extrinsic component to differences between the CD24+ "stem-like" substate and the more "differentiated" substate. SARGENT also reveals the effects of transgene integrations on endogenous gene expression, which will help guide the search for "safe-harbor" loci.

CONCLUSIONS

Taken together, we show that SARGENT is a powerful tool to measure both the mean and noise of gene expression at locations across the genome and that the data generatd by SARGENT reveals important insights into the regulation of gene expression noise genome-wide.

The pathogenic T42A mutation in SHP2 rewires the interaction specificity of its N-terminal regulatory domain

Mutations in the tyrosine phosphatase SHP2 are associated with a variety of human diseases. Most mutations in SHP2 increase its basal catalytic activity by disrupting auto-inhibitory interactions between its phosphatase domain and N-terminal SH2 (phosphotyrosine recognition) domain. By contrast, some disease-associated mutations located in the ligand-binding pockets of the N- or C-terminal SH2 domains do not increase basal activity and likely exert their pathogenicity through alternative mechanisms. We lack a molecular understanding of how these SH2 mutations impact SHP2 structure, activity, and signaling. Here, we characterize five SHP2 SH2 domain ligand-binding pocket mutants through a combination of high-throughput biochemical screens, biophysical and biochemical measurements, and molecular dynamics simulations. We show that, while some of these mutations alter binding affinity to phosphorylation sites, the T42A mutation in the N-SH2 domain is unique in that it also substantially alters ligand-binding specificity, despite being 8-10 Å from the specificity-determining region of the SH2 domain. This mutation exerts its effect on sequence specificity by remodeling the phosphotyrosine binding pocket, altering the mode of engagement of both the phosphotyrosine and surrounding residues on the ligand. The functional consequence of this altered specificity is that the T42A mutant has biased sensitivity toward a subset of activating ligands and enhances downstream signaling. Our study highlights an example of a nuanced mechanism of action for a disease-associated mutation, characterized by a change in protein-protein interaction specificity that alters enzyme activation.

Developing microRNAs as engineering tools to modulate monoclonal antibody galactosylation

N-linked glycosylation is one of the most important post-translational modifications of monoclonal antibodies (mAbs) and is considered to be a critical quality attribute (CQA), as the glycan composition often has immunomodulatory effects. Since terminal galactose residues of mAbs can affect antibody-dependent cellular cytotoxicity (ADCC), complement-dependent cytolysis (CDC) activation, serum half-life, and antiviral activity it has to be monitored, controlled and modulated to ensure therapeutic effects. The ability of small noncoding microRNAs (miRNAs) to modulate glycosylation in Chinese hamster ovary (CHO) production cells was recently reported establishing miRNAs as engineering tools for modulation of protein glycosylation. In this study, we report the characterization and validation of miRNAs as engineering tools for increased (mmu-miR-452-5p, mmu-miR-193b-3p) or decreased (mmu-miR-7646-5p, mmu-miR-7243-3p, mmu-miR-1668, mmu-let-7c-1-3p, mmu-miR-7665-3p, mmu-miR-6403) degree of galactosylation. Furthermore, the biological mode of action regulating gene expression of the galactosylation pathway was characterized as well as their influence on bioprocess-related parameters. Most important, stable plasmid-based overexpression of these miRNAs represents a versatile tool for engineering N-linked galactosylation to achieve favorable phenotypes in cell lines for biopharmaceutical production.

Prediction of on-target and off-target activity of CRISPR-Cas13d guide RNAs using deep learning

Transcriptome engineering applications in living cells with RNA-targeting CRISPR effectors depend on accurate prediction of on-target activity and off-target avoidance. Here we design and test ~200,000 RfxCas13d guide RNAs targeting essential genes in human cells with systematically designed mismatches and insertions and deletions (indels). We find that mismatches and indels have a position- and context-dependent impact on Cas13d activity, and mismatches that result in G-U wobble pairings are better tolerated than other single-base mismatches. Using this large-scale dataset, we train a convolutional neural network that we term targeted inhibition of gene expression via gRNA design (TIGER) to predict efficacy from guide sequence and context. TIGER outperforms the existing models at predicting on-target and off-target activity on our dataset and published datasets. We show that TIGER scoring combined with specific mismatches yields the first general framework to modulate transcript expression, enabling the use of RNA-targeting CRISPRs to precisely control gene dosage.

Mechanical forces amplify TCR mechanotransduction in T cell activation and function

Adoptive T cell immunotherapies, including engineered T cell receptor (eTCR) and chimeric antigen receptor (CAR) T cell immunotherapies, have shown efficacy in treating a subset of hematologic malignancies, exhibit promise in solid tumors, and have many other potential applications, such as in fibrosis, autoimmunity, and regenerative medicine. While immunoengineering has focused on designing biomaterials to present biochemical cues to manipulate T cells ex vivo and in vivo, mechanical cues that regulate their biology have been largely underappreciated. This review highlights the contributions of mechanical force to several receptor-ligand interactions critical to T cell function, with central focus on the TCR-peptide-loaded major histocompatibility complex (pMHC). We then emphasize the role of mechanical forces in (i) allosteric strengthening of the TCR-pMHC interaction in amplifying ligand discrimination during T cell antigen recognition prior to activation and (ii) T cell interactions with the extracellular matrix. We then describe approaches to design eTCRs, CARs, and biomaterials to exploit TCR mechanosensitivity in order to potentiate T cell manufacturing and function in adoptive T cell immunotherapy.

Comprehensive review of CRISPR-based gene editing: mechanisms, challenges, and applications in cancer therapy

The CRISPR system is a revolutionary genome editing tool that has the potential to revolutionize the field of cancer research and therapy. The ability to precisely target and edit specific genetic mutations that drive the growth and spread of tumors has opened up new possibilities for the development of more effective and personalized cancer treatments. In this review, we will discuss the different CRISPR-based strategies that have been proposed for cancer therapy, including inactivating genes that drive tumor growth, enhancing the immune response to cancer cells, repairing genetic mutations that cause cancer, and delivering cancer-killing molecules directly to tumor cells. We will also summarize the current state of preclinical studies and clinical trials of CRISPR-based cancer therapy, highlighting the most promising results and the challenges that still need to be overcome. Safety and delivery are also important challenges for CRISPR-based cancer therapy to become a viable clinical option. We will discuss the challenges and limitations that need to be overcome, such as off-target effects, safety, and delivery to the tumor site. Finally, we will provide an overview of the current challenges and opportunities in the field of CRISPR-based cancer therapy and discuss future directions for research and development. The CRISPR system has the potential to change the landscape of cancer research, and this review aims to provide an overview of the current state of the field and the challenges that need to be overcome to realize this potential.

Synthetic genetic circuits to uncover the OCT4 trajectories of successful reprogramming of human fibroblasts

Reprogramming human fibroblasts to induced pluripotent stem cells (iPSCs) is inefficient, with heterogeneity among transcription factor (TF) trajectories driving divergent cell states. Nevertheless, the impact of TF dynamics on reprogramming efficiency remains uncharted. We develop a system that accurately reports OCT4 protein levels in live cells and use it to reveal the trajectories of OCT4 in successful reprogramming. Our system comprises a synthetic genetic circuit that leverages noise to generate a wide range of OCT4 trajectories and a microRNA targeting endogenous OCT4 to set total cellular OCT4 protein levels. By fusing OCT4 to a fluorescent protein, we are able to track OCT4 trajectories with clonal resolution via live-cell imaging. We discover that a supraphysiological, stable OCT4 level is required, but not sufficient, for efficient iPSC colony formation. Our synthetic genetic circuit design and high-throughput live-imaging pipeline are generalizable for investigating TF dynamics for other cell fate programming applications.

Discerning the Prospects of miRNAs as a Multi-Target Therapeutic and Diagnostic for Alzheimer's Disease

Although over the last few decades, numerous attempts have been made to halt Alzheimer's disease (AD) progression and mitigate its symptoms, only a few have been proven beneficial. Most medications available, still only cater to the symptoms of the disease rather than fixing the cause at the root level. A novel approach involving the use of miRNAs, which work on the principle of gene silencing, is being explored by scientists. Naturally present miRNAs in the biological system help to regulate various genes than may be implicated in AD-like BACE-1 and APP. One miRNA thus, holds the power to keep a check on several genes, conferring it the ability to be used as a multi-target therapeutic. With aging and the onset of diseased pathology, dysregulation of these miRNAs is observed. This flawed miRNA expression is responsible for the unusual buildup of amyloid proteins, fibrillation of tau proteins in the brain, neuronal death and other hallmarks leading to AD. The use of miRNA mimics and miRNA inhibitors provides an attractive perspective for fixing the upregulation and downregulation of miRNAs that led to abnormal cellular activities. Furthermore, the detection of miRNAs in the CSF and serum of diseased patients might be considered an earlier biomarker for the disease. While most of the therapies designed around AD have not succeeded completely, the targeting of dysregulated miRNAs in AD patients might give a new direction to scholars to develop an effective treatment for Alzheimer's disease.

Mapping and exploring the organoid state space using synthetic biology

The functional relevance of an organoid is dependent on the differentiation, morphology, cell arrangement and biophysical properties, which collectively define the state of an organoid. For an organoid culture, an individual organoid or the cells that compose it, these state variables can be characterised, most easily by transcriptomics and by high-content image analysis. Their states can be compared to their in vivo counterparts. Current evidence suggests that organoids explore a wider state space than organs in vivo due to the lack of niche signalling and the variability of boundary conditions in vitro. Using data-driven state inference and in silico modelling, phase diagrams can be constructed to systematically sort organoids along biochemical or biophysical axes. These phase diagrams allow us to identify control strategies to modulate organoid state. To do so, the biochemical and biophysical environment, as well as the cells that seed organoids, can be manipulated.

RAD51 bypasses the CMG helicase to promote replication fork reversal

Replication fork reversal safeguards genome integrity as a replication stress response. DNA translocases and the RAD51 recombinase catalyze reversal. However, it remains unknown why RAD51 is required and what happens to the replication machinery during reversal. We find that RAD51 uses its strand exchange activity to circumvent the replicative helicase, which remains bound to the stalled fork. RAD51 is not required for fork reversal if the helicase is unloaded. Thus, we propose that RAD51 creates a parental DNA duplex behind the helicase that is used as a substrate by the DNA translocases for branch migration to create a reversed fork structure. Our data explain how fork reversal happens while maintaining the helicase in a position poised to restart DNA synthesis and complete genome duplication.

Engineering T Cell Development for the Next Generation of Stem Cell-Derived Immunotherapies

Engineered T cells are at the leading edge of clinical cell therapy. T cell therapies have had a remarkable impact on patient care for a subset of hematological malignancies. This foundation has motivated the development of off-the-shelf engineered cell therapies for a broad range of devastating indications. Achieving this vision will require cost-effective manufacturing of precision cell products capable of addressing multiple process and clinical-design challenges. Pluripotent stem cell (PSC)-derived engineered T cells are emerging as a solution of choice. To unleash the full potential of PSC-derived T cell therapies, the field will require technologies capable of robustly orchestrating the complex series of time- and dose-dependent signaling events needed to recreate functional T cell development in the laboratory. In this article, we review the current state of allogenic T cell therapies, focusing on strategies to generate engineered lymphoid cells from PSCs. We highlight exciting recent progress in this field and outline timely opportunities for advancement with an emphasis on niche engineering and synthetic biology.

Synthetic gene circuits for cell state detection and protein tuning in human pluripotent stem cells

During development, cell state transitions are coordinated through changes in the identity of molecular regulators in a cell type‐ and dose‐specific manner. The ability to rationally engineer such transitions in human pluripotent stem cells (hPSC) will enable numerous applications in regenerative medicine. Herein, we report the generation of synthetic gene circuits that can detect a desired cell state using AND‐like logic integration of endogenous miRNAs (classifiers) and, upon detection, produce fine‐tuned levels of output proteins using an miRNA‐mediated output fine‐tuning technology (miSFITs). Specifically, we created an “hPSC ON” circuit using a model‐guided miRNA selection and circuit optimization approach. The circuit demonstrates robust PSC‐specific detection and graded output protein production. Next, we used an empirical approach to create an “hPSC‐Off” circuit. This circuit was applied to regulate the secretion of endogenous BMP4 in a state‐specific and fine‐tuned manner to control the composition of differentiating hPSCs. Our work provides a platform for customized cell state‐specific control of desired physiological factors in hPSC, laying the foundation for programming cell compositions in hPSC‐derived tissues and beyond.

Identification of a Maturation Plasma Cell Index through a Highly Sensitive Droplet Digital PCR Assay Gene Expression Signature Validation in Newly Diagnosed Multiple Myeloma Patients

DNA microarrays and RNA-based sequencing approaches are considered important discovery tools in clinical medicine. However, cross-platform reproducibility studies undertaken so far have highlighted that microarrays are not able to accurately measure gene expression, particularly when they are expressed at low levels. Here, we consider the employment of a digital PCR assay (ddPCR) to validate a gene signature previously identified by gene expression profile. This signature included ten Hedgehog (HH) pathways' genes able to stratify multiple myeloma (MM) patients according to their self-renewal status. Results show that the designed assay is able to validate gene expression data, both in a retrospective as well as in a prospective cohort. In addition, the plasma cells' differentiation status determined by ddPCR was further confirmed by other techniques, such as flow cytometry, allowing the identification of patients with immature plasma cells' phenotype (i.e., expressing CD19+/CD81+ markers) upregulating HH genes, as compared to others, whose plasma cells lose the expression of these markers and were more differentiated. To our knowledge, this is the first technical report of gene expression data validation by ddPCR instead of classical qPCR. This approach permitted the identification of a Maturation Index through the integration of molecular and phenotypic data, able to possibly define upfront the differentiation status of MM patients that would be clinically relevant in the future.

Design and characterization of a salicylic acid-inducible gene expression system for Jurkat cells

With continued progress in cell and gene therapies, there is an immediate need for exogenously tunable gene expression systems with safe and predictable behavior in specific human cell types. Here, we demonstrate the ability of the salicylic acid (SA)-inducible MarR repressor protein from Escherichia coli to regulate target gene expression in a human T lymphocyte cell line. Two lentiviral vectors, one encoding an enhanced green fluorescent protein (EGFP) reporter cassette and the other a repressor cassette, were sequentially transduced into Jurkat cells, using fluorescence-activated cell sorting (FACS) to isolate stable Jurkat progeny. As a result, EGFP expression was repressed by MarR and was inducible upon the addition of SA (~1.3 fold). This represents the first example of functional expression of bacterial MarR in mammalian cells, and opens the possibility for further development of regulated, SA-tunable gene expression system for T-cells.

CRISPR Editing Enables Consequential Tag-Activated MicroRNA-Mediated Endogene Deactivation

Molecular therapies and functional studies greatly benefit from spatial and temporal precision of genetic intervention. We therefore conceived and explored tag-activated microRNA (miRNA)-mediated endogene deactivation (TAMED) as a research tool and potential lineage-specific therapy. For proof of principle, we aimed to deactivate γ-globin repressor BCL11A in erythroid cells by tagging the 3' untranslated region (UTR) of BCL11A with miRNA recognition sites (MRSs) for the abundant erythromiR miR-451a. To this end, we employed nucleofection of CRISPR/Cas9 ribonucleoprotein (RNP) particles alongside double- or single-stranded oligodeoxynucleotides for, respectively, non-homologous-end-joining (NHEJ)- or homology-directed-repair (HDR)-mediated MRS insertion. NHEJ-based tagging was imprecise and inefficient (≤6%) and uniformly produced knock-in- and indel-containing MRS tags, whereas HDR-based tagging was more efficient (≤18%), but toxic for longer donors encoding concatenated and thus potentially more efficient MRS tags. Isolation of clones for robust HEK293T cells tagged with a homozygous quadruple MRS resulted in 25% spontaneous reduction in BCL11A and up to 36% reduction after transfection with an miR-451a mimic. Isolation of clones for human umbilical cord blood-derived erythroid progenitor-2 (HUDEP-2) cells tagged with single or double MRS allowed detection of albeit weak γ-globin induction. Our study demonstrates suitability of TAMED for physiologically relevant modulation of gene expression and its unsuitability for therapeutic application in its current form.

Construction of a tunable promoter library to optimize gene expression in Methylomonas sp. DH-1, a methanotroph, and its application to cadaverine production

BACKGROUND

As methane is 84 times more potent than carbon dioxide in exacerbating the greenhouse effect, there is an increasing interest in the utilization of methanotrophic bacteria that can convert harmful methane into various value-added compounds. A recently isolated methanotroph, Methylomonas sp. DH-1, is a promising biofactory platform because of its relatively fast growth. However, the lack of genetic engineering tools hampers its wide use in the bioindustry.

RESULTS

Through three different approaches, we constructed a tunable promoter library comprising 33 promoters that can be used for the metabolic engineering of Methylomonas sp. DH-1. The library had an expression level of 0.24-410% when compared with the strength of the lac promoter. For practical application of the promoter library, we fine-tuned the expressions of cadA and cadB genes, required for cadaverine synthesis and export, respectively. The strain with P_rpmB-cadA and P_DnaA-cadB produced the highest cadaverine titre (18.12 ± 1.06 mg/L) in Methylomonas sp. DH-1, which was up to 2.8-fold higher than that obtained from a non-optimized strain. In addition, cell growth and lysine (a precursor of cadaverine) production assays suggested that gene expression optimization through transcription tuning can afford a balance between the growth and precursor supply.

CONCLUSIONS

The tunable promoter library provides standard and tunable components for gene expression, thereby facilitating the use of methanotrophs, specifically Methylomonas sp. DH-1, as a sustainable cell factory.

Role of microRNAs in Disorders of Gut-Brain Interactions: Clinical Insights and Therapeutic Alternatives

Disorders of gut-brain interactions (DGBIs) are heterogeneous in nature and intertwine with diverse pathophysiological mechanisms. Regular functioning of the gut requires complex coordinated interplay between a variety of gastrointestinal (GI) cell types and their functions are regulated by multiple mechanisms at the transcriptional, post-transcriptional, translational, and post-translational levels. MicroRNAs (miRNAs) are small non-coding RNA molecules that post-transcriptionally regulate gene expression by binding to specific mRNA targets to repress their translation and/or promote the target mRNA degradation. Dysregulation of miRNAs might impair gut physiological functions leading to DGBIs and gut motility disorders. Studies have shown miRNAs regulate gut functions such as visceral sensation, gut immune response, GI barrier function, enteric neuronal development, and GI motility. These biological processes are highly relevant to the gut where neuroimmune interactions are key contributors in controlling gut homeostasis and functional defects lead to DGBIs. Although extensive research has explored the pathophysiology of DGBIs, further research is warranted to bolster the molecular mechanisms behind these disorders. The therapeutic targeting of miRNAs represents an attractive approach for the treatment of DGBIs because they offer new insights into disease mechanisms and have great potential to be used in the clinic as diagnostic markers and therapeutic targets. Here, we review recent advances regarding the regulation of miRNAs in GI pacemaking cells, immune cells, and enteric neurons modulating pathophysiological mechanisms of DGBIs. This review aims to assess the impacts of miRNAs on the pathophysiological mechanisms of DGBIs, including GI dysmotility, impaired intestinal barrier function, gut immune dysfunction, and visceral hypersensitivity. We also summarize the therapeutic alternatives for gut microbial dysbiosis in DGBIs, highlighting the clinical insights and areas for further exploration. We further discuss the challenges in miRNA therapeutics and promising emerging approaches.

Context-aware synthetic biology by controller design: Engineering the mammalian cell

The rise of systems biology has ushered a new paradigm: the view of the cell as a system that processes environmental inputs to drive phenotypic outputs. Synthetic biology provides a complementary approach, allowing us to program cell behavior through the addition of synthetic genetic devices into the cellular processor. These devices, and the complex genetic circuits they compose, are engineered using a design-prototype-test cycle, allowing for predictable device performance to be achieved in a context-dependent manner. Within mammalian cells, context effects impact device performance at multiple scales, including the genetic, cellular, and extracellular levels. In order for synthetic genetic devices to achieve predictable behaviors, approaches to overcome context dependence are necessary. Here, we describe control systems approaches for achieving context-aware devices that are robust to context effects. We then consider cell fate programing as a case study to explore the potential impact of context-aware devices for regenerative medicine applications.

The functional activity of the miR-1914-5p in lipid metabolism of the hepatocarcinoma cell line HepG2: a potential molecular tool for controlling hepatic cellular migration

Hepatocellular carcinoma is one of the most common types of cancer in the world with high mortality rate and new therapies that control of fatty acid metabolism may limit the proliferation of cancer cells. In the last two decades, the non-coding RNAs have been considered as promising molecular tools to treat diseases, because they are able to modulate gene expression and the metabolic routes; however, deep investigation of their mechanistic behavior in pathologies must be performed. Thus, our aim was to evaluate the modulatory effect of the miR-1914-5p in controlling lipid metabolism in HepG2, a widely used human hepatocarcinoma cell line. The molecular and cellular analyses demonstrated that the functional inhibition of the investigated microRNA completely changed the cellular metabolism and behavior, compared to control groups. The in vitro inhibition of the miR-1914-5p increased the energy expenditure pointed in different analyses, decreasing cell doubling time and migration rate verified in wound healing and in the classical transwell chambers invasion assays, which makes the miR-1914-5p a candidate for further translational and preclinical studies to validate its function in controlling metastasis in liver cancer or even treat those diseases.

Genetic engineering of T cells for immunotherapy

Genetically engineered T cell immunotherapies have provided remarkable clinical success to treat B cell acute lymphoblastic leukaemia by harnessing a patient's own T cells to kill cancer, and these approaches have the potential to provide therapeutic benefit for numerous other cancers, infectious diseases and autoimmunity. By introduction of either a transgenic T cell receptor or a chimeric antigen receptor, T cells can be programmed to target cancer cells. However, initial studies have made it clear that the field will need to implement more complex levels of genetic regulation of engineered T cells to ensure both safety and efficacy. Here, we review the principles by which our knowledge of genetics and genome engineering will drive the next generation of adoptive T cell therapies.

Orthogonal control of mean and variability of endogenous genes in a human cell line

Stochastic fluctuations at the transcriptional level contribute to isogenic cell-to-cell heterogeneity in mammalian cell populations. However, we still have no clear understanding of the repercussions of this heterogeneity, given the lack of tools to independently control mean expression and variability of a gene. Here, we engineer a synthetic circuit to modulate mean expression and heterogeneity of transgenes and endogenous human genes. The circuit, a Tunable Noise Rheostat (TuNR), consists of a transcriptional cascade of two inducible transcriptional activators, where the output mean and variance can be modulated by two orthogonal small molecule inputs. In this fashion, different combinations of the inputs can achieve the same mean but with different population variability. With TuNR, we achieve low basal expression, over 1000-fold expression of a transgene product, and up to 7-fold induction of the endogenous gene NGFR. Importantly, for the same mean expression level, we are able to establish varying degrees of heterogeneity in expression within an isogenic population, thereby decoupling gene expression noise from its mean. TuNR is therefore a modular tool that can be used in mammalian cells to enable direct interrogation of the implications of cell-to-cell variability.

Systematic use of synthetic 5'-UTR RNA structures to tune protein translation improves yield and quality of complex proteins in mammalian cell factories

Predictably regulating protein expression levels to improve recombinant protein production has become an important tool, but is still rarely applied to engineer mammalian cells. We therefore sought to set-up an easy-to-implement toolbox to facilitate fast and reliable regulation of protein expression in mammalian cells by introducing defined RNA hairpins, termed 'regulation elements (RgE)', in the 5'-untranslated region (UTR) to impact translation efficiency. RgEs varying in thermodynamic stability, GC-content and position were added to the 5'-UTR of a fluorescent reporter gene. Predictable translation dosage over two orders of magnitude in mammalian cell lines of hamster and human origin was confirmed by flow cytometry. Tuning heavy chain expression of an IgG with the RgEs to various levels eventually resulted in up to 3.5-fold increased titers and fewer IgG aggregates and fragments in CHO cells. Co-expression of a therapeutic Arylsulfatase-A with RgE-tuned levels of the required helper factor SUMF1 demonstrated that the maximum specific sulfatase activity was already attained at lower SUMF1 expression levels, while specific production rates steadily decreased with increasing helper expression. In summary, we show that defined 5'-UTR RNA-structures represent a valid tool to systematically tune protein expression levels in mammalian cells and eventually help to optimize recombinant protein expression.

MicroRNAs as Biomarkers and Therapeutic Targets in Inflammation- and Ischemia-Reperfusion-Related Acute Renal Injury

Acute kidney injury (AKI), caused mainly by ischemia-reperfusion, sepsis, or nephrotoxins (such as contrast medium), is identified by an abrupt decline in kidney function and is associated with high morbidity and mortality. Despite decades of efforts, the pathogenesis of AKI remains poorly understood, and effective therapies are lacking. MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression at the posttranscriptional level to control cell differentiation, development, and homeostasis. Additionally, extracellular miRNAs might mediate cell-cell communication during various physiological and pathological processes. Recently, mounting evidence indicates that miRNAs play a role in the pathogenesis of AKI. Moreover, emerging research suggests that because of their remarkable stability in body fluids, microRNAs can potentially serve as novel diagnostic biomarkers of AKI. Of note, our previous finding that miR-494 is rapidly elevated in urine but not in serum provides insight into the ultimate role of urine miRNAs in AKI. Additionally, exosomal miRNAs derived from stem cells, known as the stem cell secretome, might be a potential innovative therapeutic strategy for AKI. This review aims to provide new data obtained in this field of research. It is hoped that new studies on this topic will not only generate new insights into the pathophysiology of urine miRNAs in AKI but also might lead to the precise management of this fatal disease.

TargetDB: A target information aggregation tool and tractability predictor

When trying to identify new potential therapeutic protein targets, access to data and knowledge is increasingly important. In a field where new resources and data sources become available every day, it is crucial to be able to take a step back and look at the wider picture in order to identify potential drug targets. While this task is routinely performed by bespoke literature searches, it is often time-consuming and lacks uniformity when comparing multiple targets at one time. To address this challenge, we developed TargetDB, a tool that aggregates public information available on given target(s) (links to disease, safety, 3D structures, ligandability, novelty, etc.) and assembles it in an easy to read output ready for the researcher to analyze. In addition, we developed a target scoring system based on the desirable attributes of good therapeutic targets and machine learning classification system to categorize novel targets as having promising or challenging tractrability. In this manuscript, we present the methodology used to develop TargetDB as well as test cases.

Titrating gene expression using libraries of systematically attenuated CRISPR guide RNAs

A lack of tools to precisely control gene expression has limited our ability to evaluate relationships between expression levels and phenotypes. Here, we describe an approach to titrate expression of human genes using CRISPR interference and series of single-guide RNAs (sgRNAs) with systematically modulated activities. We used large-scale measurements across multiple cell models to characterize activities of sgRNAs containing mismatches to their target sites and derived rules governing mismatched sgRNA activity using deep learning. These rules enabled us to synthesize a compact sgRNA library to titrate expression of ~2,400 genes essential for robust cell growth and to construct an in silico sgRNA library spanning the human genome. Staging cells along a continuum of gene expression levels combined with single-cell RNA-seq readout revealed sharp transitions in cellular behaviors at gene-specific expression thresholds. Our work provides a general tool to control gene expression, with applications ranging from tuning biochemical pathways to identifying suppressors for diseases of dysregulated gene expression.

Emerging Approaches for Regulation and Control of CAR T Cells: A Mini Review

Chimeric antigen receptor (CAR) T cells have emerged as a promising treatment for patients with advanced B-cell cancers. However, widespread application of the therapy is currently limited by potentially life-threatening toxicities due to a lack of control of the highly potent transfused cells. Researchers have therefore developed several regulatory mechanisms in order to control CAR T cells in vivo. Clinical adoption of these control systems will depend on several factors, including the need for temporal and spatial control, the immunogenicity of the requisite components as well as whether the system allows reversible control or induces permanent elimination. Here we describe currently available and emerging control methods and review their function, advantages, and limitations.

MaveDB: an open-source platform to distribute and interpret data from multiplexed assays of variant effect

Multiplex assays of variant effect (MAVEs), such as deep mutational scans and massively parallel reporter assays, test thousands of sequence variants in a single experiment. Despite the importance of MAVE data for basic and clinical research, there is no standard resource for their discovery and distribution. Here, we present MaveDB ( https://www.mavedb.org ), a public repository for large-scale measurements of sequence variant impact, designed for interoperability with applications to interpret these datasets. We also describe the first such application, MaveVis, which retrieves, visualizes, and contextualizes variant effect maps. Together, the database and applications will empower the community to mine these powerful datasets.

Allelic Imbalance of Recurrently Mutated Genes in Acute Myeloid Leukaemia

The patho-mechanism of somatic driver mutations in cancer usually involves transcription, but the proportion of mutations and wild-type alleles transcribed from DNA to RNA is largely unknown. We systematically compared the variant allele frequencies of recurrently mutated genes in DNA and RNA sequencing data of 246 acute myeloid leukaemia (AML) patients. We observed that 95% of all detected variants were transcribed while the rest were not detectable in RNA sequencing with a minimum read-depth cut-off (10x). Our analysis focusing on 11 genes harbouring recurring mutations demonstrated allelic imbalance (AI) in most patients. GATA2, RUNX1, TET2, SRSF2, IDH2, PTPN11, WT1, NPM1 and CEBPA showed significant AIs. While the effect size was small in general, GATA2 exhibited the largest allelic imbalance. By pooling heterogeneous data from three independent AML cohorts with paired DNA and RNA sequencing (N = 253), we could validate the preferential transcription of GATA2-mutated alleles. Differential expression analysis of the genes with significant AI showed no significant differential gene and isoform expression for the mutated genes, between mutated and wild-type patients. In conclusion, our analyses identified AI in nine out of eleven recurrently mutated genes. AI might be a common phenomenon in AML which potentially contributes to leukaemogenesis.

Next-generation AAV vectors—do not judge a virus (only) by its cover

Recombinant adeno-associated viruses (AAV) are under intensive investigation in numerous clinical trials after they have emerged as a highly promising vector for human gene therapy. Best exemplifying their power and potential is the authorization of three gene therapy products based on wild-type AAV serotypes, comprising Glybera (AAV1), Luxturna (AAV2) and, most recently, Zolgensma (AAV9). Nonetheless, it has also become evident that the current AAV vector generation will require improvements in transduction potency, antibody evasion and cell/tissue specificity to allow the use of lower and safer vector doses. To this end, others and we devoted substantial previous research to the implementation and application of key technologies for engineering of next-generation viral capsids in a high-throughput ‘top-down’ or (semi-)rational ‘bottom-up’ approach. Here, we describe a set of recent complementary strategies to enhance features of AAV vectors that act on the level of the recombinant cargo. As examples that illustrate the innovative and synergistic concepts that have been reported lately, we highlight (i) novel synthetic enhancers/promoters that provide an unprecedented degree of AAV tissue specificity, (ii) pioneering genetic circuit designs that harness biological (microRNAs) or physical (light) triggers as regulators of AAV gene expression and (iii) new insights into the role of AAV DNA structures on vector genome stability, integrity and functionality. Combined with ongoing capsid engineering and selection efforts, these and other state-of-the-art innovations and investigations promise to accelerate the arrival of the next generation of AAV vectors and to solidify the unique role of this exciting virus in human gene therapy.

Decoupling tRNA promoter and processing activities enables specific Pol-II Cas9 guide RNA expression

Spatial/temporal control of Cas9 guide RNA expression could considerably expand the utility of CRISPR-based technologies. Current approaches based on tRNA processing offer a promising strategy but suffer from high background. Here, to address this limitation, we present a screening platform which allows simultaneous measurements of the promoter strength, 5', and 3' processing efficiencies across a library of tRNA variants. This analysis reveals that the sequence determinants underlying these activities, while overlapping, are dissociable. Rational design based on the ensuing principles allowed us to engineer an improved tRNA scaffold that enables highly specific guide RNA production from a Pol-II promoter. When benchmarked against other reported systems this tRNA scaffold is superior to most alternatives, and is equivalent in function to an optimized version of the Csy4-based guide RNA release system. The results and methods described in this manuscript enable avenues of research both in genome engineering and basic tRNA biology.