Comparison of muscle activation imbalance following core stability or general exercises in nonspecific low back pain: a quasi-randomized controlled trial.

BACKGROUND: Low back pain causes changes in muscle activation patterns. Knowing how different exercises may improve altered muscle activation is useful in the treatment of patients. The aim of the study was to investigate whether there was a difference in the pattern of muscle activation in chronic nonspecific low back pain sufferers following core stability exercise (CSE) and general exercise (GE). METHODS: Fifty-six non-specific chronic LBP subjects were randomly assigned to either groups (28 participants in CSE and 28 in GE group). Both groups performed 16 sessions of an exercise program for about 5 weeks. Pain, disability and trunk muscle activation patterns (using surface electromyography) were measured at baseline and post-training. RESULTS: After the intervention period, antagonist coactivation ratio did not change in either groups. Though all compensated imbalance ratios (residual unequal muscular activity after cancellation of directionality) decreased towards negative (imbalance to left side) only this change for total muscles ratio in GE was significant (mean difference in GE group, 0.15; 95% CI: 0.02 to 0.28; p-value of paired t-test: 0.022); (mean difference in CSE, 0.02; 95% CI: - 0.07 to 0.11; p-value of paired t-test: 0.614).. No overall significantly decrease in uncompensated imbalance ratio (absolute imbalance values without cancellation directionality) was observed. Pain and disability decreased significantly in both groups. However, there was no difference between two groups in either of the variables after the intervention. CONCLUSIONS: Both exercise programs reduced pain and disability and made or kept trunk muscle activation imbalance to the left side. The effects of two exercises on pain, disability and antagonist coactivation or imbalance ratios were not different. TRIAL REGISTRATION: This study was registered in the Iranian Clinical Trial Center with the code IRCT201111098035N1, Registered Jan 21, 2013.

Multi-functional genome-wide CRISPR system for high throughput genotype-phenotype mapping.

Genome-scale engineering is an indispensable tool to understand genome functions due to our limited knowledge of cellular networks. Unfortunately, most existing methods for genome-wide genotype-phenotype mapping are limited to a single mode of genomic alteration, i.e. overexpression, repression, or deletion. Here we report a multi-functional genome-wide CRISPR (MAGIC) system to precisely control the expression level of defined genes to desired levels throughout the whole genome. By combining the tri-functional CRISPR system and array-synthesized oligo pools, MAGIC is used to create, to the best of our knowledge, one of the most comprehensive and diversified genomic libraries in yeast ever reported. The power of MAGIC is demonstrated by the identification of previously uncharacterized genetic determinants of complex phenotypes, particularly those having synergistic interactions when perturbed to different expression levels. MAGIC represents a powerful synthetic biology tool to investigate fundamental biological questions as well as engineer complex phenotypes for biotechnological applications.

Towards a fully automated algorithm driven platform for biosystems design.

Large-scale data acquisition and analysis are often required in the successful implementation of the design, build, test, and learn (DBTL) cycle in biosystems design. However, it has long been hindered by experimental cost, variability, biases, and missed insights from traditional analysis methods. Here, we report the application of an integrated robotic system coupled with machine learning algorithms to fully automate the DBTL process for biosystems design. As proof of concept, we have demonstrated its capacity by optimizing the lycopene biosynthetic pathway. This fully-automated robotic platform, BioAutomata, evaluates less than 1% of possible variants while outperforming random screening by 77%. A paired predictive model and Bayesian algorithm select experiments which are performed by Illinois Biological Foundry for Advanced Biomanufacturing (iBioFAB). BioAutomata excels with black-box optimization problems, where experiments are expensive and noisy and the success of the experiment is not dependent on extensive prior knowledge of biological mechanisms.

Highly Efficient Single-Pot Scarless Golden Gate Assembly.

Golden Gate assembly is one of the most widely used DNA assembly methods due to its robustness and modularity. However, despite its popularity, the need for BsaI-free parts, the introduction of scars between junctions, as well as the lack of a comprehensive study on the linkers hinders its more widespread use. Here, we first developed a novel sequencing scheme to test the efficiency and specificity of 96 linkers of 4-bp length and experimentally verified these linkers and their effects on Golden Gate assembly efficiency and specificity. We then used this sequencing data to generate 200 distinct linker sets that can be used by the community to perform efficient Golden Gate assemblies of different sizes and complexity. We also present a single-pot scarless Golden Gate assembly and BsaI removal scheme and its accompanying assembly design software to perform point mutations and Golden Gate assembly. This assembly scheme enables scarless assembly without compromising efficiency by choosing optimized linkers near assembly junctions.

CRISPR/Cas9-mediated knock-in of an optimized TetO repeat for live cell imaging of endogenous loci.

Nuclear organization has an important role in determining genome function; however, it is not clear how spatiotemporal organization of the genome relates to functionality. To elucidate this relationship, a method for tracking any locus of interest is desirable. Recently clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) or transcription activator-like effectors were adapted for imaging endogenous loci; however, they are mostly limited to visualization of repetitive regions. Here, we report an efficient and scalable method named SHACKTeR (Short Homology and CRISPR/Cas9-mediated Knock-in of a TetO Repeat) for live cell imaging of specific chromosomal regions without the need for a pre-existing repetitive sequence. SHACKTeR requires only two modifications to the genome: CRISPR/Cas9-mediated knock-in of an optimized TetO repeat and its visualization by TetR-EGFP expression. Our simplified knock-in protocol, utilizing short homology arms integrated by polymerase chain reaction, was successful at labeling 10 different loci in HCT116 cells. We also showed the feasibility of knock-in into lamina-associated, heterochromatin regions, demonstrating that these regions prefer non-homologous end joining for knock-in. Using SHACKTeR, we were able to observe DNA replication at a specific locus by long-term live cell imaging. We anticipate the general applicability and scalability of our method will enhance causative analyses between gene function and compartmentalization in a high-throughput manner.

Genome-scale engineering of Saccharomyces cerevisiae with single-nucleotide precision.

We developed a CRISPR-Cas9- and homology-directed-repair-assisted genome-scale engineering method named CHAnGE that can rapidly output tens of thousands of specific genetic variants in yeast. More than 98% of target sequences were efficiently edited with an average frequency of 82%. We validate the single-nucleotide resolution genome-editing capability of this technology by creating a genome-wide gene disruption collection and apply our method to improve tolerance to growth inhibitors.

Advancing Metabolic Engineering of Saccharomyces cerevisiae Using the CRISPR/Cas System.

Thanks to its ease of use, modularity, and scalability, the clustered regularly interspaced short palindromic repeats (CRISPR) system has been increasingly used in the design and engineering of Saccharomyces cerevisiae, one of the most popular hosts for industrial biotechnology. This review summarizes the recent development of this disruptive technology for metabolic engineering applications, including CRISPR-mediated gene knock-out and knock-in as well as transcriptional activation and interference. More importantly, multi-functional CRISPR systems that combine both gain- and loss-of-function modulations for combinatorial metabolic engineering are highlighted.

RNAi assisted genome evolution unveils yeast mutants with improved xylose utilization.

Xylose is a major component of lignocellulosic biomass, one of the most abundant feedstocks for biofuel production. Therefore, efficient and rapid conversion of xylose to ethanol is crucial in the viability of lignocellulosic biofuel plants. In this study, RNAi Assisted Genome Evolution (RAGE) was used to improve the xylose utilization rate in SR8, one of the most efficient publicly available xylose utilizing Saccharomyces cerevisiae strains. To identify gene targets for further improvement, we created a genome-scale library consisting of both genetic over-expression and down-regulation mutations in SR8. Followed by screening in media containing xylose as the sole carbon source, yeast mutants with 29% faster xylose utilization, and 45% higher ethanol productivity were obtained relative to the parent strain. Two known and two new effector genes were identified in these mutant strains. Notably, down-regulation of CDC11, an essential gene, resulted in faster xylose utilization, and this gene target cannot be identified in genetic knock-out screens.

Pathway Design, Engineering, and Optimization.

The microbial metabolic versatility found in nature has inspired scientists to create microorganisms capable of producing value-added compounds. Many endeavors have been made to transfer and/or combine pathways, existing or even engineered enzymes with new function to tractable microorganisms to generate new metabolic routes for drug, biofuel, and specialty chemical production. However, the success of these pathways can be impeded by different complications from an inherent failure of the pathway to cell perturbations. Pursuing ways to overcome these shortcomings, a wide variety of strategies have been developed. This chapter will review the computational algorithms and experimental tools used to design efficient metabolic routes, and construct and optimize biochemical pathways to produce chemicals of high interest.

Combinatorial metabolic engineering using an orthogonal tri-functional CRISPR system.

Designing an optimal microbial cell factory often requires overexpression, knock-down, and knock-out of multiple gene targets. Unfortunately, such rewiring of cellular metabolism is often carried out sequentially and with low throughput. Here, we report a combinatorial metabolic engineering strategy based on an orthogonal tri-functional CRISPR system that combines transcriptional activation, transcriptional interference, and gene deletion (CRISPR-AID) in the yeast Saccharomyces cerevisiae. This strategy enables perturbation of the metabolic and regulatory networks in a modular, parallel, and high-throughput manner. We demonstrate the application of CRISPR-AID not only to increase the production of ß-carotene by 3-fold in a single step, but also to achieve 2.5-fold improvement in the display of an endoglucanase on the yeast surface by optimizing multiple metabolic engineering targets in a combinatorial manner.

Regulatory RNA-assisted genome engineering in microorganisms.

Regulatory RNAs are increasingly recognized and utilized as key modulators of gene expression in diverse organisms. Thanks to their modular and programmable nature, trans-acting regulatory RNAs are especially attractive in genome-scale applications. Here we discuss the recent examples in microbial genome engineering implementing various trans-acting RNA platforms, including sRNA, RNAi, asRNA and CRISRP-Cas. In particular, we focus on how the scalable and multiplex nature of trans-acting RNAs has been used to tackle the challenges in creating genome-wide and combinatorial diversity for functional genomics and metabolic engineering applications. Advances in computational design and context-dependent regulation are also discussed for their contribution in improving fine-tuning capabilities of trans-acting RNAs.

Orthogonal Fatty Acid Biosynthetic Pathway Improves Fatty Acid Ethyl Ester Production in Saccharomyces cerevisiae.

Fatty acid ethyl esters (FAEEs) are a form of biodiesel that can be microbially produced via a transesterification reaction of fatty acids with ethanol. The titer of microbially produced FAEEs can be greatly reduced by unbalanced metabolism and an insufficient supply of fatty acids, resulting in a commercially inviable process. Here, we report on a pathway engineering strategy in Saccharomyces cerevisiae for enhancing the titer of microbially produced FAEEs by providing the cells with an orthogonal route for fatty acid synthesis. The fatty acids generated from this heterologous pathway would supply the FAEE production, safeguarding endogenous fatty acids for cellular metabolism and growth. We investigated the heterologous expression of a Type-I fatty acid synthase (FAS) from Brevibacterium ammoniagenes coupled with WS/DGAT, the wax ester synthase/acyl-coenzyme that catalyzes the transesterification reaction with ethanol. Strains harboring the orthologous fatty acid synthesis yielded a 6.3-fold increase in FAEE titer compared to strains without the heterologous FAS. Variations in fatty acid chain length and degree of saturation can affect the quality of the biodiesel; therefore, we also investigated the diversity of the fatty acid production profile of FAS enzymes from other Actinomyces organisms.

Directed evolution of a cellodextrin transporter for improved biofuel production under anaerobic conditions in Saccharomyces cerevisiae.

Introduction of a cellobiose utilization pathway consisting of a cellodextrin transporter and a ß-glucosidase into Saccharomyces cerevisiae enables co-fermentation of cellobiose and xylose. Cellodextrin transporter 1 (CDT1) from Neurospora crassa has been established as an effective transporter for the engineered cellobiose utilization pathways. However, cellodextrin transporter 2 (CDT2) from the same species is a facilitator and has the potential to be more efficient than CDT1 under anaerobic conditions due to its energetic benefits. Currently, CDT2 has a very low activity and is considered rate-limiting in cellobiose fermentation. Here, we report the directed evolution of CDT2 with an increased cellobiose uptake activity, which results in improved cellobiose fermentation under anaerobic conditions. After three rounds of directed evolution, the cellobiose uptake activity of CDT2 was increased by 2.2-fold, which resulted from both increased specific activity and transporter expression level. Using high cell density fermentation under anaerobic conditions, the evolved mutant conferred 4.0- and 4.4-fold increase in the cellobiose consumption rate and ethanol productivity, respectively. In addition, although the cellobiose uptake activity was still lower than that of CDT1, the engineered CDT2 showed significantly improved cellobiose consumption and ethanol production under anaerobic conditions, representing the energetic benefits of a sugar facilitator for anaerobic cellobiose fermentation. This study demonstrated that anaerobic biofuel production could be significantly improved via directed evolution of a sugar transporter protein in yeast.