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

Optimized genome-wide CRISPR screening enables rapid engineering of growth-based phenotypes in Yarrowia lipolytica

CRISPR-Cas9 functional genomic screens uncover gene targets linked to various phenotypes for metabolic engineering with remarkable efficiency. However, these genome-wide screens face a number of design challenges, including variable guide RNA activity, ensuring sufficient genome coverage, and maintaining high transformation efficiencies to ensure full library representation. These challenges are prevalent in non-conventional yeast, many of which exhibit traits that are well suited to metabolic engineering and bioprocessing. To address these hurdles in the oleaginous yeast Yarrowia lipolytica, we designed a compact, high-activity genome-wide sgRNA library. The library was designed using DeepGuide, an sgRNA activity prediction algorithm and a large dataset of ∼50,000 sgRNAs with known activity. Three guides per gene enables redundant targeting of 98.8% of genes in the genome in a library of 23,900 sgRNAs. We deployed the optimized library to uncover genes essential to the tolerance of acetate, a promising alternative carbon source, and various hydrocarbons present in many waste streams. Our screens yielded several gene knockouts that improve acetate tolerance on their own and as double knockouts in media containing acetate as the sole carbon source. Analysis of the hydrocarbon screens revealed genes related to fatty acid and alkane metabolism in Y. lipolytica. The optimized CRISPR gRNA library and its successful use in Y. lipolytica led to the discovery of alternative carbon source-related genes and provides a workflow for creating high-activity, compact genome-wide libraries for strain engineering.

Edible mycelium bioengineered for enhanced nutritional value and sensory appeal using a modular synthetic biology toolkit

Filamentous fungi are critical in the transition to a more sustainable food system. While genetic modification of these organisms has promise for enhancing the nutritional value, sensory appeal, and scalability of fungal foods, genetic tools and demonstrated use cases for bioengineered food production by edible strains are lacking. Here, we develop a modular synthetic biology toolkit for Aspergillus oryzae, an edible fungus used in fermented foods, protein production, and meat alternatives. Our toolkit includes a CRISPR-Cas9 method for gene integration, neutral loci, and tunable promoters. We use these tools to elevate intracellular levels of the nutraceutical ergothioneine and the flavor-and color molecule heme in the edible biomass. The strain overproducing heme is red in color and is readily formulated into imitation meat patties with minimal processing. These findings highlight the promise of synthetic biology to enhance fungal foods and provide useful genetic tools for applications in food production and beyond.

Application of genome editing techniques to regulate gene expression in crops

BACKGROUND

Enhanced agricultural production is urgently required to meet the food demands of the increasing global population. Abundant genetic diversity is expected to accelerate crop development. In particular, the development of the CRISPR/Cas genome editing technology has greatly enhanced our ability to improve crop's genetic diversity through direct artificial gene modification. However, recent studies have shown that most crop improvement efforts using CRISPR/Cas techniques have mainly focused on the coding regions, and there is a relatively lack of studies on the regulatory regions of gene expression.

RESULTS

This review briefly summarizes the development of CRISPR/Cas system in the beginning. Subsequently, the importance of gene regulatory regions in plants is discussed. The review focuses on recent developments and applications of mutations in regulatory regions via CRISPR/Cas techniques in crop breeding.

CONCLUSION

Finally, an outline of perspectives for future crop breeding using genome editing technologies is provided. This review provides new research insights for crop improvement using genome editing techniques.

Coupling High-Throughput and Targeted Screening for Identification of Nonobvious Metabolic Engineering Targets

Identification of metabolic engineering targets is a fundamental challenge in strain development programs. While high-throughput (HTP) genetic engineering methodologies capable of generating vast diversity are being developed at a rapid rate, a majority of industrially interesting molecules cannot be screened at sufficient throughput to leverage these techniques. We propose a workflow that couples HTP screening of common precursors (e.g., amino acids) that can be screened either directly or by artificial biosensors, with low-throughput targeted validation of the molecule of interest to uncover nonintuitive beneficial metabolic engineering targets and combinations hereof. Using this workflow, we identified several nonobvious novel targets for improving p-coumaric acid (p-CA) and l-DOPA production from two large 4k gRNA libraries each deregulating 1000 metabolic genes in the yeast Saccharomyces cerevisiae. We initially screened yeast cells transformed with gRNA library plasmids for individual regulatory targets improving the production of l-tyrosine-derived betaxanthins, identifying 30 targets that increased intracellular betaxanthin content 3.5-5.7 fold. Hereafter, we screened the targets individually in a high-producing p-CA strain, narrowing down the targets to six that increased the secreted titer by up to 15%. To investigate whether any of the six targets could be additively combined to improve p-CA production further, we created a gRNA multiplexing library and subjected it to our proposed coupled workflow. The combination of regulating PYC1 and NTH2 simultaneously resulted in the highest (threefold) improvement of the betaxanthin content, and an additive trend was also observed in the p-CA strain. Lastly, we tested the initial 30 targets in a l-DOPA producing strain, identifying 10 targets that increased the secreted titer by up to 89%, further validating our screening by proxy workflow. This coupled approach is useful for strain development in the absence of direct HTP screening assays for products of interest.

Tuning plant phenotypes by precise, graded downregulation of gene expression

The ability to control gene expression and generate quantitative phenotypic changes is essential for breeding new and desired traits into crops. Here we report an efficient, facile method for downregulating gene expression to predictable, desired levels by engineering upstream open reading frames (uORFs). We used base editing or prime editing to generate de novo uORFs or to extend existing uORFs by mutating their stop codons. By combining these approaches, we generated a suite of uORFs that incrementally downregulate the translation of primary open reading frames (pORFs) to 2.5-84.9% of the wild-type level. By editing the 5' untranslated region of OsDLT, which encodes a member of the GRAS family and is involved in the brassinosteroid transduction pathway, we obtained, as predicted, a series of rice plants with varied plant heights and tiller numbers. These methods offer an efficient way to obtain genome-edited plants with graded expression of traits.

Titrating Avidity of Yeast-Displayed Proteins Using a Transcriptional Regulator

Yeast surface display is a valuable tool for protein engineering and directed evolution; however, significant variability in the copy number (i.e., avidity) of displayed variants on the yeast cell wall complicates screening and selection campaigns. Here, we report an engineered titratable display platform that modulates the avidity of Aga2-fusion proteins on the yeast cell wall dependent on the concentration of the anhydrotetracycline (aTc) inducer. Our design is based on a genomic Aga1 gene copy and an episomal Aga2-fusion construct both under the control of an aTc-dependent transcriptional regulator that enables stoichiometric and titratable expression, secretion, and display of Aga2-fusion proteins. We demonstrate tunable display levels over 2-3 orders of magnitude for various model proteins, including glucose oxidase enzyme variants, mechanostable dockerin-binding domains, and anti-PDL1 affibody domains. By regulating the copy number of displayed proteins, we demonstrate the effects of titratable avidity levels on several specific phenotypic activities, including enzyme activity and cell adhesion to surfaces under shear flow. Finally, we show that titrating down the display level allows yeast-based binding affinity measurements to be performed in a regime that avoids ligand depletion effects while maintaining small sample volumes, avoiding a well-known artifact in yeast-based binding assays. The ability to titrate the multivalency of proteins on the yeast cell wall through simple inducer control will benefit protein engineering and directed evolution methodology relying on yeast display for broad classes of therapeutic and diagnostic proteins of interest.

Genome-Wide Screen for Enhanced Noncanonical Amino Acid Incorporation in Yeast

Numerous applications of noncanonical amino acids (ncAAs) in basic biology and therapeutic development require efficient protein biosynthesis using an expanded genetic code. However, achieving such incorporation at repurposed stop codons in cells is generally inefficient and limited by complex cellular processes that preserve the fidelity of protein synthesis. A more comprehensive understanding of the processes that contribute to ncAA incorporation would aid in the development of genomic engineering strategies for augmenting genetic code manipulation. In this work, we used a series of fluorescent reporters to screen a pooled Saccharomyces cerevisiae molecular barcoded yeast knockout (YKO) collection. Fluorescence-activated cell sorting enabled isolation of strains encoding single-gene deletions exhibiting improved ncAA incorporation efficiency in response to the amber (TAG) stop codon; 55 unique candidate deletions were identified. The deleted genes encoded for proteins that participate in diverse cellular processes, including many genes that have no known connection with protein translation. We then verified that two knockouts, yil014c-aΔ and alo1Δ, exhibited improved ncAA incorporation efficiency starting from independently acquired strains possessing the knockouts. Using additional orthogonal translation systems and ncAAs, we determined that yil014c-aΔ and alo1Δ enhance ncAA incorporation efficiency without loss of fidelity over a wide range of conditions. Our findings highlight opportunities for further modulating gene expression with genetic, genomic, and synthetic biology approaches to improve ncAA incorporation efficiency. In addition, these discoveries have the potential to enhance our fundamental understanding of protein translation. Ultimately, cells that efficiently biosynthesize ncAA-containing proteins will streamline the realization of applications utilizing expanded genetic codes ranging from basic biology to drug discovery.

Dynamic Progress in Technological Advances to Study Lipids in Aging: Challenges and Future Directions

Lipids participate in all cellular processes. Diverse methods have been developed to investigate lipid composition and distribution in biological samples to understand the effect of lipids across an organism’s lifespan. Here, we summarize the advanced techniques for studying lipids, including mass spectrometry-based lipidomics, lipid imaging, chemical-based lipid analysis and lipid engineering and their advantages. We further discuss the limitation of the current methods to gain an in-depth knowledge of the role of lipids in aging, and the possibility of lipid-based therapy in aging-related diseases.

Biosensor-Coupled In Vivo Mutagenesis and Omics Analysis Reveals Reduced Lysine and Arginine Synthesis To Improve Malonyl-Coenzyme A Flux in Saccharomyces cerevisiae

Malonyl-coenzyme A (malonyl-CoA) is an important precursor for producing various chemicals, but its low availability limits the synthesis of downstream products in Saccharomyces cerevisiae. Owing to the complexity of metabolism, evolutionary engineering is required for developing strains with improved malonyl-CoA synthesis. Here, using the biosensor we constructed previously, a growth-based screening system that links the availability of malonyl-CoA with cell growth is developed. Coupling this system with in vivo continuous mutagenesis enabled rapid generation of genome-scale mutation library and screening strains with improved malonyl-CoA availability. The mutant strains are analyzed by whole-genome sequencing and transcriptome analysis. The omics analysis revealed that the carbon flux rearrangement to storage carbohydrate and amino acids synthesis affected malonyl-CoA metabolism. Through reverse engineering, new processes especially reduced lysine and arginine synthesis were found to improve malonyl-CoA synthesis. Our study provides a valuable complementary tool to other high-throughput screening method for mutant strains with improved metabolite synthesis and improves our understanding of the metabolic regulation of malonyl-CoA synthesis.

IMPORTANCE Malonyl-CoA is a key precursor for the production a variety of value-added chemicals. Although rational engineering has been performed to improve the synthesis of malonyl-CoA in S. cerevisiae, due to the complexity of the metabolism there is a need for evolving strains and analyzing new mechanism to improve malonyl-CoA flux. Here, we developed a growth-based screening system that linked the availability of malonyl-CoA with cell growth and manipulated DNA replication for rapid in vivo mutagenesis. The combination of growth-based screening with in vivo mutagenesis enabled quick evolution of strains with improved malonyl-CoA availability. The whole-genome sequencing, transcriptome analysis of the mutated strains, together with reverse engineering, demonstrated weakening carbon flux to lysine and arginine synthesis and storage carbohydrate can contribute to malonyl-CoA synthesis. Our work provides a guideline in simultaneous strain screening and continuous evolution for improved metabolic intermediates and identified new targets for improving malonyl-CoA downstream product synthesis.

High-content CRISPR screening

CRISPR screens are a powerful source of biological discovery, enabling the unbiased interrogation of gene function in a wide range of applications and species. In pooled CRISPR screens, various genetically encoded perturbations are introduced into pools of cells. The targeted cells proliferate under a biological challenge such as cell competition, drug treatment or viral infection. Subsequently, the perturbation-induced effects are evaluated by sequencing-based counting of the guide RNAs that specify each perturbation. The typical results of such screens are ranked lists of genes that confer sensitivity or resistance to the biological challenge of interest. Contributing to the broad utility of CRISPR screens, adaptations of the core CRISPR technology make it possible to activate, silence or otherwise manipulate the target genes. Moreover, high-content read-outs such as single-cell RNA sequencing and spatial imaging help characterize screened cells with unprecedented detail. Dedicated software tools facilitate bioinformatic analysis and enhance reproducibility. CRISPR screening has unravelled various molecular mechanisms in basic biology, medical genetics, cancer research, immunology, infectious diseases, microbiology and other fields. This Primer describes the basic and advanced concepts of CRISPR screening and its application as a flexible and reliable method for biological discovery, biomedical research and drug development - with a special emphasis on high-content methods that make it possible to obtain detailed biological insights directly as part of the screen.

Intelligent host engineering for metabolic flux optimisation in biotechnology

Optimising the function of a protein of length N amino acids by directed evolution involves navigating a 'search space' of possible sequences of some 20N. Optimising the expression levels of P proteins that materially affect host performance, each of which might also take 20 (logarithmically spaced) values, implies a similar search space of 20P. In this combinatorial sense, then, the problems of directed protein evolution and of host engineering are broadly equivalent. In practice, however, they have different means for avoiding the inevitable difficulties of implementation. The spare capacity exhibited in metabolic networks implies that host engineering may admit substantial increases in flux to targets of interest. Thus, we rehearse the relevant issues for those wishing to understand and exploit those modern genome-wide host engineering tools and thinking that have been designed and developed to optimise fluxes towards desirable products in biotechnological processes, with a focus on microbial systems. The aim throughput is 'making such biology predictable'. Strategies have been aimed at both transcription and translation, especially for regulatory processes that can affect multiple targets. However, because there is a limit on how much protein a cell can produce, increasing kcat in selected targets may be a better strategy than increasing protein expression levels for optimal host engineering.

Sorting for secreted molecule production using a biosensor-in-microdroplet approach

Sorting large libraries of cells for improved small molecule secretion is throughput limited. Here, we combine producer/secretor cell libraries with whole-cell biosensors using a microfluidic-based screening workflow. This approach enables a mix-and-match capability using off-the-shelf biosensors through either coencapsulation or pico-injection. We demonstrate the cell type and library agnostic nature of this workflow by utilizing single-guide RNA, transposon, and ethyl-methyl sulfonate mutagenesis libraries across three distinct microbes (Escherichia coli, Saccharomyces cerevisiae, and Yarrowia lipolytica), biosensors from two organisms (E. coli and S. cerevisiae), and three products (triacetic acid lactone, naringenin, and L-DOPA) to identify targets improving production/secretion.

Synthetic Lethality in Cancer Therapeutics: The Next Generation

Synthetic lethality (SL) provides a conceptual framework for tackling targets that are not classically "druggable," including loss-of-function mutations in tumor suppressor genes required for carcinogenesis. Recent technological advances have led to an inflection point in our understanding of genetic interaction networks and ability to identify a wide array of novel SL drug targets. Here, we review concepts and lessons emerging from first-generation trials aimed at testing SL drugs, discuss how the nature of the targeted lesion can influence therapeutic outcomes, and highlight the need to develop clinical biomarkers distinct from those based on the paradigms developed to target activated oncogenes. SIGNIFICANCE: SL offers an approach for the targeting of loss of function of tumor suppressor and DNA repair genes, as well as of amplification and/or overexpression of genes that cannot be targeted directly. A next generation of tumor-specific alterations targetable through SL has emerged from high-throughput CRISPR technology, heralding not only new opportunities for drug development, but also important challenges in the development of optimal predictive biomarkers.

Engineering the bilayer: Emerging genetic tool kits for mechanistic lipid biology

The structural diversity of lipids underpins the biophysical properties of cellular membranes, which vary across all scales of biological organization. Because lipid composition results from complex metabolic and transport pathways, its experimental control has been a major goal of mechanistic membrane biology. Here, we argue that in the wake of synthetic biology, similar metabolic engineering strategies can be applied to control the composition, physicochemical properties, and function of cell membranes. In one emerging area, titratable expression platforms allow for specific and genome-wide alterations in lipid biosynthetic genes, providing analog control over lipidome stoichiometry in membranes. Simultaneously, heterologous expression of biosynthetic genes and pathways has allowed for gain-of-function experiments with diverse lipids in non-native systems. Finally, we highlight future directions for tool development, including recently discovered lipid transport pathways to intracellular lipid pools. Further tool development providing synthetic control of membrane properties can allow biologists to untangle membrane lipid structure-associated functions.

A genome-scale CRISPR interference guide library enables comprehensive phenotypic profiling in yeast

BACKGROUND

CRISPR/Cas9-mediated transcriptional interference (CRISPRi) enables programmable gene knock-down, yielding loss-of-function phenotypes for nearly any gene. Effective, inducible CRISPRi has been demonstrated in budding yeast, and genome-scale guide libraries enable systematic, genome-wide genetic analysis.

RESULTS

We present a comprehensive yeast CRISPRi library, based on empirical design rules, containing 10 distinct guides for most genes. Competitive growth after pooled transformation revealed strong fitness defects for most essential genes, verifying that the library provides comprehensive genome coverage. We used the relative growth defects caused by different guides targeting essential genes to further refine yeast CRISPRi design rules. In order to obtain more accurate and robust guide abundance measurements in pooled screens, we link guides with random nucleotide barcodes and carry out linear amplification by in vitro transcription.

CONCLUSIONS

Taken together, we demonstrate a broadly useful platform for comprehensive, high-precision CRISPRi screening in yeast.

A simplified strategy for titrating gene expression reveals new relationships between genotype, environment, and bacterial growth

A lack of high-throughput techniques for making titrated, gene-specific changes in expression limits our understanding of the relationship between gene expression and cell phenotype. Here, we present a generalizable approach for quantifying growth rate as a function of titrated changes in gene expression level. The approach works by performing CRISPRi with a series of mutated single guide RNAs (sgRNAs) that modulate gene expression. To evaluate sgRNA mutation strategies, we constructed a library of 5927 sgRNAs targeting 88 genes in Escherichia coli MG1655 and measured the effects on growth rate. We found that a compounding mutational strategy, through which mutations are incrementally added to the sgRNA, presented a straightforward way to generate a monotonic and gradated relationship between mutation number and growth rate effect. We also implemented molecular barcoding to detect and correct for mutations that 'escape' the CRISPRi targeting machinery; this strategy unmasked deleterious growth rate effects obscured by the standard approach of ignoring escapers. Finally, we performed controlled environmental variations and observed that many gene-by-environment interactions go completely undetected at the limit of maximum knockdown, but instead manifest at intermediate expression perturbation strengths. Overall, our work provides an experimental platform for quantifying the phenotypic response to gene expression variation.

Applications of CRISPR in a Microbial Cell Factory: From Genome Reconstruction to Metabolic Network Reprogramming

The well-designed microbial cell factory finds wide applications in chemical, pharmaceutical, and food industries due to its sustainable and environmentally friendly features. Recently, the clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated proteins (CRISPR-Cas) systems have been developed into powerful tools to perform genome editing and transcriptional regulation in prokaryotic and eukaryotic cells. Accordingly, these tools are useful to build microbial cell factories not only by reconstructing the genome but also by reprogramming the metabolic network. In this review, we summarize the recent significant headway and potential uses of the CRISPR technology in the construction of efficient microbial cell factories. Moreover, the future perspectives on the improvement and upgradation of CRISPR-based tools are also discussed.