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At least 55 records · Page 3

Orthogonal chemical genomics approaches reveal genomic targets for increasing anaerobic chemical tolerance in Zymomonas mobilis

Genetically engineered microbes have the potential to increase efficiency in the bioeconomy by overcoming growth-limiting production stress. Screens of gene perturbation libraries against production stressors can identify high-value engineering targets, but follow-up experiments needed to guard against false positives are slow and resource-intensive. In principle, the use of orthogonal gene perturbation approaches could increase recovery of true positives over false positives because the strengths of one technique compensate for the weaknesses of the other, but, in practice, two parallel screens are rarely performed at the genome scale. Here, we screen genome-scale CRISPRi (CRISPR interference) knockdown and transposon insertion libraries of the bioenergy-relevant Alphaproteobacterium, Zymomonas mobilis, against growth inhibitors commonly found in deconstructed plant material. Integrating data from the two gene perturbation techniques, we established an approach for defining engineering targets with high specificity. This allowed us to identify all known genes in the cytochrome bc1 and cytochrome c synthesis pathway as potential targets for engineering resistance to phenolic acids under anaerobic conditions, a subset of which we validated using precise gene deletions. Strikingly, this finding is specific to the cytochrome bc1 and cytochrome c pathway and does not extend to other branches of the electron transport chain. We further show that exposure of Z. mobilis to ferulic acid causes substantial remodeling of the cell envelope proteome, as well as the downregulation of TonB-dependent transporters. Our work provides a generalizable strategy for identifying high-value engineering targets from gene perturbation screens that is broadly applicable.

CRISPRi↗

Zymomonas mobilis : bringing an ancient human tool into the genomic era

Zymomonas mobilis is an ethanologenic bacterium that has been used for over 1500 years to produce alcoholic beverages. Recently, this microbe has become a top candidate for biofuel production due to its efficient metabolism. Z. mobilis is being developed to utilize lignocellulosic biomass as a feedstock and synthesize a range of valuable chemicals and fuels. Genetic and metabolic engineering strategies are crucial to reach these goals. Recent advances include genome engineering, CRISPR editing, and CRISPRi knockdown of genes. Metabolic engineering has enabled redirection of carbon from the natural product ethanol to chemicals such as 2,3-butanediol and polyhydroxybutyrate. Finally, the approaches summarized here will streamline the development of Z. mobilis as an industrial chassis for sustainable liquid fuels and chemicals.

Boismier, Emma C. [Michigan State Univ., East Lans↗

Chromosomal integration of complex DNA constructs using CRAGE and CRAGE-Duet systems

Our recent development of the CRAGE (chassis-independent recombinase-assisted genome engineering) system enables single-step integration of large, complex DNA constructs directly into bacteria genomes across multiple phyla. This protocol describes the details of the experimental design and procedures of CRAGE and extended CRAGE-Duet systems. It also describes a strategy that combines CRISPR with CRAGE, which allows implementation of CRISPR-Cas9, CRISPRa, and CRISPRi in diverse bacteria, overcoming major limitations to broaden the application of CRISPR in non-model bacterial genome engineering. For complete details on the use and execution of this protocol, please refer to Wang et al. (2019), Wang et al. (2020), and Liu et al. (2020).

79 ASTRONOMY AND ASTROPHYSICS↗

Systems-Level Modeling for CRISPR-Based Metabolic Engineering

The CRISPR-Cas system has enabled the development of sophisticated, multigene metabolic engineering programs through the use of guide RNA-directed activation or repression of target genes. To optimize biosynthetic pathways in microbial systems, we need improved models to inform design and implementation of transcriptional programs. Recent progress has resulted in new modeling approaches for identifying gene targets and predicting the efficacy of guide RNA targeting. Genome-scale and flux balance models have successfully been applied to identify targets for improving biosynthetic production yields using combinatorial CRISPR-interference (CRISPRi) programs. Here, the advent of new approaches for tunable and dynamic CRISPR activation (CRISPRa) promises to further advance these engineering capabilities. Once appropriate targets are identified, guide RNA prediction models can lead to increased efficacy in gene targeting. Developing improved models and incorporating approaches from machine learning may be able to overcome current limitations and greatly expand the capabilities of CRISPR-Cas9 tools for metabolic engineering.

59 BASIC BIOLOGICAL SCIENCES↗

Genome-scale metabolic rewiring improves titers rates and yields of the non-native product indigoidine at scale

Abstract High titer, rate, yield (TRY), and scalability are challenging metrics to achieve due to trade-offs between carbon use for growth and production. To achieve these metrics, we take the minimal cut set (MCS) approach that predicts metabolic reactions for elimination to couple metabolite production strongly with growth. We compute MCS solution-sets for a non-native product indigoidine, a sustainable pigment, in Pseudomonas putida KT2440, an emerging industrial microbe. From the 63 solution-sets, our omics guided process identifies one experimentally feasible solution requiring 14 simultaneous reaction interventions. We implement a total of 14 genes knockdowns using multiplex-CRISPRi. MCS-based solution shifts production from stationary to exponential phase. We achieve 25.6 g/L, 0.22 g/l/h, and ~50% maximum theoretical yield (0.33 g indigoidine/g glucose). These phenotypes are maintained from batch to fed-batch mode, and across scales (100-ml shake flasks, 250-ml ambr®, and 2-L bioreactors).

59 BASIC BIOLOGICAL SCIENCES↗

Genome-scale analysis of interactions between genetic perturbations and natural variation

Interactions between genetic perturbations and segregating loci can cause perturbations to show different phenotypic effects across genetically distinct individuals. To study these interactions on a genome scale in many individuals, we used combinatorial DNA barcode sequencing to measure the fitness effects of 8046 CRISPRi perturbations targeting 1721 distinct genes in 169 yeast cross progeny (or segregants). We identified 460 genes whose perturbation has different effects across segregants. Several factors caused perturbations to show variable effects, including baseline segregant fitness, the mean effect of a perturbation across segregants, and interacting loci. We mapped 234 interacting loci and found four hub loci that interact with many different perturbations. Perturbations that interact with a given hub exhibit similar epistatic relationships with the hub and show enrichment for cellular processes that may mediate these interactions. These results suggest that an individual’s response to perturbations is shaped by a network of perturbation-locus interactions that cannot be measured by approaches that examine perturbations or natural variation alone.

59 BASIC BIOLOGICAL SCIENCES↗

A frugal CRISPR kit for equitable and accessible education in gene editing and synthetic biology

Equitable and accessible education in life sciences, bioengineering, and synthetic biology is crucial for training the next generation of scientists, fostering transparency in public decision-making, and ensuring biotechnology can benefit a wide-ranging population. As a groundbreaking technology for genome engineering, CRISPR has transformed research and therapeutics. However, hands-on exposure to this technology in educational settings remains limited due to the extensive resources required for CRISPR experiments. Here, we develop CRISPRkit, an affordable kit designed for gene editing and regulation in high school education. CRISPRkit eliminates the need for specialized equipment, prioritizes biosafety, and utilizes cost-effective reagents. By integrating CRISPRi gene regulation, colorful chromoproteins, cell-free transcription-translation systems, smartphone-based quantification, and an in-house automated algorithm (CRISPectra), our kit offers an inexpensive (~$2) and user-friendly approach to performing and analyzing CRISPR experiments, without the need for a traditional laboratory setup. Experiments conducted by high school students in classroom settings highlight the kit’s utility for reliable CRISPRkit experiments. Furthermore, CRISPRkit provides a modular and expandable platform for genome engineering, and we demonstrate its applications for controlling fluorescent proteins and metabolic pathways such as melanin production. We envision CRISPRkit will facilitate biotechnology education for communities of diverse socioeconomic and geographic backgrounds.

59 BASIC BIOLOGICAL SCIENCES↗

Automation and machine learning drive rapid optimization of isoprenol production in Pseudomonas putida

Advances in genome engineering have improved our ability to perturb microbial metabolic networks, yet bioproduction campaigns often struggle with parsing complex metabolic datasets to efficiently enhance product titers. We address this challenge by coupling laboratory automation with machine learning to systematically optimize the production of isoprenol, a sustainable aviation fuel precursor, in Pseudomonas putida. The simultaneous downregulation through CRISPR interference of combinations of up to four gene targets, guided by machine learning, permitted us to increase isoprenol titer 5-fold in six consecutive design-build-test-learn cycles. Moreover, machine learning enabled us to swiftly explore a vast experimental design space of 800,000 possible combinations by strategically recommending approximately 400 priority constructs. High-throughput proteomics allowed us to validate CRISPRi downregulation and identify biological mechanisms driving production increases. Our work demonstrates that ML-driven automated design-build-test-learn cycles, when combined with rigorous data validation, can rapidly enhance titers without specific biological knowledge, suggesting that it can be applied to any host, product, or pathway.

Carruthers, David N↗

The minimal SUF system is not required for Fe–S cluster biogenesis in the methanogenic archaeon Methanosarcina acetivorans

Abstract Iron–sulfur (Fe–S) proteins are essential for the ability of methanogens to carry out methanogenesis and biological nitrogen fixation (diazotrophy). Nonetheless, the factors involved in Fe–S cluster biogenesis in methanogens remain largely unknown. The minimal SUF Fe–S cluster biogenesis system (i.e., SufBC) is postulated to serve as the primary system in methanogens. Here, the role of SufBC in Methanosarcina acetivorans , which contains two sufCB gene clusters, was investigated. The CRISPRi-dCas9 and CRISPR-Cas9 systems were utilized to repress or delete sufC1B1 and sufC2B2 , respectively. Neither the dual repression of sufC1B1 and sufC2B2 nor the deletion of both sufC1B1 and sufC2B2 affected the growth of M. acetivorans under any conditions tested, including diazotrophy. Interestingly, deletion of only sufC1B1 led to a delayed-growth phenotype under all growth conditions, suggesting that the deletion of sufC2B2 acts as a suppressor mutation in the absence of sufC1B1 . In addition, the deletion of sufC1B1 and/or sufC2B2 did not affect the total Fe–S cluster content in M. acetivorans cells. Overall, these results reveal that the minimal SUF system is not required for Fe–S cluster biogenesis in M. acetivorans and challenge the universal role of SufBC in Fe–S cluster biogenesis in methanogens.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An essential and highly selective protein import pathway encoded by nucleus-forming phage

Targeting proteins to specific subcellular destinations is essential in prokaryotes, eukaryotes, and the viruses that infect them. Chimalliviridae phages encapsulate their genomes in a nucleus-like replication compartment composed of the protein chimallin (ChmA) that excludes ribosomes and decouples transcription from translation. These phages selectively partition proteins between the phage nucleus and the bacterial cytoplasm. Currently, the genes and signals that govern selective protein import into the phage nucleus are unknown. Here, we identify two components of this protein import pathway: a species-specific surface-exposed region of a phage intranuclear protein required for nuclear entry and a conserved protein, PicA (Protein importer of chimalliviruses A), that facilitates cargo protein trafficking across the phage nuclear shell. We also identify a defective cargo protein that is targeted to PicA on the nuclear periphery but fails to enter the nucleus, providing insight into the mechanism of nuclear protein trafficking. Using CRISPRi-ART protein expression knockdown of PicA, we show that PicA is essential early in the chimallivirus replication cycle. Together, our results allow us to propose a multistep model for the Protein Import Chimallivirus pathway, where proteins are targeted to PicA by amino acids on their surface and then licensed by PicA for nuclear entry. The divergence in the selectivity of this pathway between closely related chimalliviruses implicates its role as a key player in the evolutionary arms race between competing phages and their hosts.

59 BASIC BIOLOGICAL SCIENCES↗

CRISPR-RNAa: targeted activation of translation using dCas13 fusions to translation initiation factors

Abstract Tools for synthetically controlling gene expression are a cornerstone of genetic engineering. CRISPRi and CRISPRa technologies have been applied extensively for programmable modulation of gene transcription, but there are few such tools for targeted modulation of protein translation rates. Here, we employ CRISPR-Cas13 as a programmable activator of translation. We develop a novel variant of the catalytically-deactivated Cas13d enzyme dCasRx by fusing it to translation initiation factor IF3. We demonstrate dCasRx-IF3’s ability to enhance expression 21.3-fold above dCasRx when both are targeted to the start of the 5′ untranslated region of mRNA encoding red fluorescent protein in Escherichia coli. Activation of translation is location-dependent, and we show dCasRx-IF3 represses translation when targeted to the ribosomal binding site, rather than enhancing it. We provide evidence that dCasRx-IF3 targeting enhances mRNA stability relative to dCasRx, providing mechanistic insights into how this new tool functions to enhance gene expression. We also demonstrate targeted upregulation of native LacZ 2.6-fold, showing dCasRx-IF3’s ability to enhance expression of endogenous genes. dCasRx-IF3 requires no additional host modification to influence gene expression. This work outlines a novel approach, CRISPR-RNAa, for post-transcriptional control of translation to activate gene expression.

59 BASIC BIOLOGICAL SCIENCES↗

Revealing oxidative pentose metabolism in new Pseudomonas putida isolates

Abstract The Pseudomonas putida group in the Gammaproteobacteria has been intensively studied for bioremediation and plant growth promotion. Members of this group have recently emerged as promising hosts to convert intermediates derived from plant biomass to biofuels and biochemicals. However, most strains of P. putida cannot metabolize pentose sugars derived from hemicellulose. Here, we describe three isolates that provide a broader view of the pentose sugar catabolism in the P. putida group. One of these isolates clusters with the well‐characterized P. alloputida KT2440 (Strain BP6); the second isolate clustered with plant growth‐promoting strain P. putida W619 (Strain M2), while the third isolate represents a new species in the group (Strain BP8). Each of these isolates possessed homologous genes for oxidative xylose catabolism ( xylDXA ) and a potential xylonate transporter. Strain M2 grew on arabinose and had genes for oxidative arabinose catabolism ( araDXA ). A CRISPR interference (CRISPRi) system was developed for strain M2 and identified conditionally essential genes for xylose growth. A glucose dehydrogenase was found to be responsible for initial oxidation of xylose and arabinose in strain M2. These isolates have illuminated inherent diversity in pentose catabolism in the P. putida group and may provide alternative hosts for biomass conversion.

59 BASIC BIOLOGICAL SCIENCES↗

Development of dual‐inducible duet‐expression vectors for tunable gene expression control and CRISPR interference‐based gene repression in Pseudomonas putida KT2440

Summary The development of P. putida as an industrial host requires a sophisticated molecular toolbox for strain improvement, including vectors for gene expression and repression. To augment existing expression plasmids for metabolic engineering, we developed a series of dual‐inducible duet‐expression vectors for P. putida KT2440. A number of inducible promoters (P lac , P tac , P tetR/tetA and P bad ) were used in different combinations to differentially regulate the expression of individual genes. Protein expression was evaluated by measuring the fluorescence of reporter proteins (GFP and RFP). Our experiments demonstrated the use of compatible plasmids, a useful approach to coexpress multiple genes in P. putida KT2440. These duet vectors were modified to generate a fully inducible CRISPR interference system using two catalytically inactive Cas9 variants from S. pasteurianus (dCas9) and S. pyogenes (spdCas9). The utility of developed CRISPRi system(s) was demonstrated by repressing the expression of nine conditionally essential genes, resulting in growth impairment and prolonged lag phase for P. putida KT2440 growth on glucose. Furthermore, the system was shown to be tightly regulated, tunable and to provide a simple way to identify essential genes with an observable phenotype.

59 BASIC BIOLOGICAL SCIENCES↗

ModE Regulates Alternative Nitrogenase Expression in the Methanogen Methanosarcina acetivorans

ABSTRACT All methanogens that can fix nitrogen use molybdenum (Mo) nitrogenase. Some methanogens, including Methanosarcina acetivorans , also contain alternative vanadium‐ and iron‐nitrogenases, encoded by the vnf and anf operons, respectively. These nitrogenases are produced when there is insufficient Mo to support Mo‐nitrogenase activity. The factors that control the expression of the alternative nitrogenases in response to Mo availability are unknown in methanogens. Here we show that ModE is the regulator that represses transcription of the vnf and anf operons in M. acetivorans when cells are grown with Mo. CRISPRi repression of modE results in a significant increase in the transcription of the vnf and anf operons as well as the detection of Fe‐nitrogenase during nitrogen fixation in the presence of Mo. Gel shift assays with recombinant ModE demonstrated that ModE binds a specific sequence motif upstream of the vnf and anf operons, as well as other genes and operons related to nitrogen fixation and Mo transport. However, purified ModE does not contain Mo, and the addition of Mo does not alter the affinity of ModE for DNA, indicating M. acetivorans ModE may not directly bind Mo. This study shows that ModE is the primary Mo‐responsive regulator of alternative nitrogenase expression in M. acetivorans , but other factor(s) are likely involved in directly sensing Mo.

Chanderban, Melissa [Department of Biological Scie↗

Physiological roles of an Acinetobacter -specific σ factor

ABSTRACT The Gram-negative pathogen Acinetobacter baumannii is considered an “urgent threat” to human health due to its propensity to become antibiotic resistant. Understanding the distinct regulatory paradigms used by A. baumannii to mitigate cellular stresses may uncover new therapeutic targets. Many γ-proteobacteria use the extracytoplasmic function (ECF) σ factor, RpoE, to invoke envelope homeostasis networks in response to stress. Acinetobacter species contain the poorly characterized ECF “SigAb”; however, it is unclear if SigAb has the same physiological role as RpoE. Here, we show that SigAb is a metal stress-responsive ECF that appears unique to Acinetobacter species and distinct from RpoE-like ECFs. We combine promoter mutagenesis, motif scanning, and chromatin immunoprecipitation-sequencing (ChIP-seq) to define the direct SigAb regulon, which consists of genes encoding SigAb itself, the stringent response mediator, RelA, and the uncharacterized small RNA, “SabS.” However, RNA-seq of strains overexpressing SigAb revealed a large, indirect regulon containing hundreds of genes. Metal resistance genes are key elements of the indirect regulon, as CRISPRi knockdown of sigAb or sabS resulted in increased copper sensitivity and excess copper-induced SigAb-dependent transcription. Furthermore, we found that two uncharacterized genes in the sigAb operon, “ aabA ” and “ aabB ,” have anti-SigAb activity. Finally, employing a targeted Tn-seq approach that uses CRISPR-associated transposons, we show that sigAb , aabA , and aabB are important for fitness even during optimal growth conditions. Our work reveals new physiological roles for SigAb and SabS, provides a novel approach for assessing gene fitness, and highlights the distinct regulatory architecture of A. baumannii . IMPORTANCE Acinetobacter baumannii is a hospital-acquired pathogen, and many strains are resistant to multiple antibiotics. Understanding how A. baumannii senses and responds to stress may uncover novel routes to treat infections. Here, we examine how the Acinetobacter -specific transcription factor, SigAb, mitigates stress. We find that SigAb directly regulates only a small number of genes, but indirectly controls hundreds of genes that have substantial impacts on cell physiology. We show that SigAb is required for maximal growth, even during optimal conditions, and is acutely required during growth in the presence of elevated copper. Given that copper toxicity plays roles in pathogenesis and on copper-containing surfaces in hospitals, we speculate that SigAb function may be important in clinically relevant contexts.

Bacon, Emily E. (ORCID:0000000180907689)↗

A Functional Survey of the Regulatory Landscape of Estrogen Receptor–Positive Breast Cancer Evolution

Abstract Only a handful of somatic alterations have been linked to endocrine therapy resistance in hormone-dependent breast cancer, potentially explaining ∼40% of relapses. If other mechanisms underlie the evolution of hormone-dependent breast cancer under adjuvant therapy is currently unknown. In this work, we employ functional genomics to dissect the contribution of cis-regulatory elements (CRE) to cancer evolution by focusing on 12 megabases of noncoding DNA, including clonal enhancers, gene promoters, and boundaries of topologically associating domains. Parallel epigenetic perturbation (CRISPRi) in vitro reveals context-dependent roles for many of these CREs, with a specific impact on dormancy entrance and endocrine therapy resistance. Profiling of CRE somatic alterations in a unique, longitudinal cohort of patients treated with endocrine therapies identifies a limited set of noncoding changes potentially involved in therapy resistance. Overall, our data uncover how endocrine therapies trigger the emergence of transient features which could ultimately be exploited to hinder the adaptive process. Significance: This study shows that cells adapting to endocrine therapies undergo changes in the usage or regulatory regions. Dormant cells are less vulnerable to regulatory perturbation but gain transient dependencies which can be exploited to decrease the formation of dormant persisters.

Oncology↗

Developing Multi-Gene CRISPRa/I Programs to Accelerate DBTL Cycles in ABF Hosts Engineered for Chemical Production (CRADA 468)

Bacterial metabolism is comprised of large and complex gene networks that can produce valuable chemical products. Sophisticated organism engineering efforts are required to optimize production of high-value compounds from these networks. In principle, synthetic multi-gene transcriptional programs could be constructed to reengineer these networks for efficient industrial chemical production. In practice, however, our incomplete ability to understand and model the underlying networks, combined with our limited ability to predictably control the expression of multiple genes makes achieving this goal difficult. To overcome these challenges, we will combine new CRISPR-Cas multi-gene expression programs with computational modeling, machine learning, and multi-omics data to enhance the efficacy of design-build-test-learn (DBTL) cycles. For industrially promising microorganisms in early stages of development, creating technologies for rapidly engineering complex multi-gene programs could be transformative for accelerating data- and model-driven strain design. New CRISPR-Cas tools allow programmable gene activation (CRISPRa) or repression (CRISPRi) at multiple genes simultaneously, using the catalytically inactive Cas9 protein (dCas9) with guide RNAs that recognize DNA targets through predictable Watson-Crick base pairing. To enable accelerated DBTL cycles, we will combine these technologies with advanced Agile BioFoundry (ABF) capabilities for multi-omics data collection and machine learning. We will demonstrate the immediate applicability of these tools by rapidly improving the production of an industrial aromatic in multiple ABF organisms. We recently identified and optimized new transcriptional activators that can be linked to programmable CRISPR-Cas DNA binding domains to activate gene expression in E. coli. We can now use these CRISPRa tools as generalizable trans-acting regulators for combinatorial multi-gene expression tuning that can be easily transferred to new pathways and networks without additional genome engineering. We anticipate these tools will also transfer to new hosts. We have recently found that CRISPRa systems developed in E. coli can be readily ported to Pseudomonas putida, suggesting that multi-gene CRISPRa/i programs for diverse ABF organisms may be within reach.

59 BASIC BIOLOGICAL SCIENCES↗

Chapter 7 - CRISPR-Based Tools for Microbial Cell Factories

The development of microbial chassis for the production of a variety of biochemicals and biofuels is a growing area of research. How to efficiently manipulate genetic information to achieve optimal production of these compounds is a key area of focus in the field. In recent years, clustered regularly interspaced palindromic repeats (CRISPR) and its associated proteins (Cas) have become a popular strategy for gene editing and regulation in many organisms due to its versatility and efficacy. Here, we describe methods developed utilizing CRISPR-Cas systems for engineering microbial cell factories (e.g., bacteria and yeast) at the single gene to genome scale for mutagenesis and transcriptional regulation of target genes. Finally, we provide a perspective on the challenges and opportunities for the applications of advanced CRISPR-Cas-based tools for engineering microbial cell factories.

BIOMASS FUELS↗