Genome engineering in Saccharomyces cerevisiae using CRISPR-Cas systems

DiCarlo, James E.; Norville, Julie E.; Mali, Prashant; Rios, Xavier; Aach, John; Church, George M.

doi:10.1093/nar/gkt135

Cited by 1,423 publications

(1,411 citation statements)

References 23 publications

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“…The replacements were verified by PCR and sequenced to make sure that no mutations were introduced. The strains carrying the hybrid GAL80 promoters were constructed as described above, except that two strains (WP0089 and WP0090) were constructed by using the CRISPR/Cas9 gene editing approach 29 . For this, we integrated the Cas9 gene into our strain by using TRP1 as the marker.…”

Section: Discussionmentioning

confidence: 99%

Evolution of gene network activity by tuning the strength of negative-feedback regulation

et al. 2015

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Despite the examples of protein evolution via mutations in coding sequences, we have very limited understanding on gene network evolution via changes in cis-regulatory elements. Using the galactose network as a model, here we show how the regulatory promoters of the network contribute to the evolved network activity between two yeast species. In Saccharomyces cerevisiae, we combinatorially replace all regulatory network promoters by their counterparts from Saccharomyces paradoxus, measure the resulting network inducibility profiles, and model the results. Lowering relative strength of GAL80-mediated negative feedback by replacing GAL80 promoter is necessary and sufficient to have high network inducibility levels as in S. paradoxus. This is achieved by increasing OFF-to-ON phenotypic switching rates. Competitions performed among strains with or without the GAL80 promoter replacement show strong relationships between network inducibility and fitness. Our results support the hypothesis that gene network activity can evolve by optimizing the strength of negative-feedback regulation.

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Section: Discussionmentioning

confidence: 99%

Evolution of gene network activity by tuning the strength of negative-feedback regulation

et al. 2015

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“…Interestingly we detected the hypothetical protein Rv2817c (Cas1, a CRISPR-associated endonuclease) in the early stage of reactivation (R6). CRISPR-Cas system has gained much attention in recent times because of its involvement in genome editing (70). Therefore detection of Cas1, along with proteins involved in DNA recombination and repair in the early phase of reactivation could indicate that genome editing might play a role during reactivation of dormant MTB.…”

Section: Validation Of Quantitative Proteomic Data By Qpcr-tomentioning

confidence: 99%

Profiling the Proteome of Mycobacterium tuberculosis during Dormancy and Reactivation

Gopinath

Raghunandanan

Gomez

et al. 2015

Molecular & Cellular Proteomics

114

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Tuberculosis, caused by Mycobacterium tuberculosis, still remains a major global health problem. The main obstacle in eradicating this disease is the ability of this pathogen to remain dormant in macrophages, and then reactivate later under immuno-compromised conditions. The physiology of hypoxic nonreplicating M. tuberculosis is well-studied using many in vitro dormancy models. However, the physiological changes that take place during the shift from dormancy to aerobic growth (reactivation) have rarely been subjected to a detailed investigation. In this study, we developed an in vitro reactivation system by re-aerating the virulent laboratory strain of M. tuberculosis that was made dormant employing Wayne's dormancy model, and compared the proteome profiles of dormant and reactivated bacteria using label-free onedimensional LC/MS/MS analysis. The proteome of dormant bacteria was analyzed at nonreplicating persistent stage 1 (NRP1) and stage 2 (NRP2), whereas that of reactivated bacteria was analyzed at 6 and 24 h post reaeration. Proteome of normoxially grown bacteria served as the reference. In total, 1871 proteins comprising 47% of the M. tuberculosis proteome were identified, and many of them were observed to be expressed differentially or uniquely during dormancy and reactivation. The number of proteins detected at different stages of dormancy (764 at NRP1, 691 at NRP2) and reactivation (768 at R6 and 983 at R24) was very low compared with that of the control (1663). The number of unique proteins identified during normoxia, NRP1, NRP2, R6, and R24 were 597, 66, 56, 73, and 94, respectively. We analyzed various biological functions during these conditions. Fluctuation in the relative quantities of proteins involved in energy metabolism during dormancy and reactivation was the most significant observation we made in this study. Proteins that are up-regulated or uniquely expressed during reactivation from dormancy offer to be attractive targets for therapeutic intervention to

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“…These vectors use the recombination machinery from the prophage lambda, promoting recombination of 30-50 bp regions, and stability of linear DNA fragments (PCR products) or plasmids (Yu et al, 2000). Recently the use of a cas gene and a guiding RNA from CRISPR were shown to promote targeted chromosome dsDNA breakage leading to 130 fold increase in double homologous recombination rates in yeast (DiCarlo et al, 2013). The use of these systems would require that the cyanobacteria are transformable, even at low rates.…”

Section: Functional Barriers To Gene Acquisitionmentioning

confidence: 99%

Cyanobacterial defense mechanisms against foreign DNA transfer and their impact on genetic engineering

2013

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SUMMARYCyanobacteria display a large diversity of cellular forms ranging from unicellular to complex multicellular fi laments or aggregates. Species in the group present a wide range of metabolic characteristics including the fi xation of atmospheric nitrogen, resistance to extreme environments, production of hydrogen, secondary metabolites and exopolysaccharides. These characteristics led to the growing interest in cyanobacteria across the fi elds of ecology, evolution, cell biology and biotechnology. The number of available cyanobacterial genome sequences has increased considerably in recent years, with more than 140 fully sequenced genomes to date. Genetic engineering of cyanobacteria is widely applied to the model unicellular strains Synechocystis sp. PCC 6803 and Synechococcus elongatus PCC 7942. However the establishment of transformation protocols in many other cyanobacterial strains is challenging. One obstacle to the development of these novel model organisms is that many species have doubling times of 48 h or more, much longer than the bacterial models E. coli or B. subtilis. Furthermore, cyanobacterial defense mechanisms against foreign DNA pose a physical and biochemical barrier to DNA insertion in most strains. Here we review the various barriers to DNA uptake in the context of lateral gene transfer among microbes and the various mechanisms for DNA acquisition within the prokaryotic domain. Understanding the cyanobacterial defense mechanisms is expected to assist in the development and establishment of novel transformation protocols that are specifi cally suitable for this group.

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Genome engineering in Saccharomyces cerevisiae using CRISPR-Cas systems

Cited by 1,423 publications

References 23 publications

Evolution of gene network activity by tuning the strength of negative-feedback regulation

Evolution of gene network activity by tuning the strength of negative-feedback regulation

Profiling the Proteome of Mycobacterium tuberculosis during Dormancy and Reactivation

Cyanobacterial defense mechanisms against foreign DNA transfer and their impact on genetic engineering

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