An MSCV-Based shRNA Expression Vector for Mouse Hematopoietic Cells

February 11th, 2013 by cellectablog No comments »
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At Cellecta, we have relied primarily on lentiviral vectors to develop our RNAi genetic screening technology. The broad tropism of lentivirus-based plasmids packaged into VSV-g pseudotyped viral particles provides a very convenient vector system to introduce and stably express shRNA expression constructs or constructs expressing small proteins, peptides, or other biological molecules into virtually any mammalian cell line. Unlike with most retroviruses, cells do not need to be dividing take up a lentivirus, and unlike adenoviruses, the lentiviral expression construct integrates into the cell’s genomic DNA so it is stably passed onto progeny allowing long term studies over several cell passages. Also, in contrast with advenoviral vectors, lentiviral plasmids can be easily engineered allowing construction of complex pooled libraries such as those we use for RNAi screening.

However, there are some cells for which lentiviral vectors seem to work poorly. In particular, mouse hematopoietic cells appear to sometimes shut down expression of lentiviral constructs. We have found this anecdotally based on feedback from researchers using our system, and it has been noted in published literature. To address this, we looked into developing a more effective vector for stable shRNA expression in these types of cells.

We adapted a murine stem cell viral (MSCV) plasmid with our shRNA cloning cassette, which incorporates the U6 promoter to drive hairpin expression. As with our standard lentiviral constructs, the MSCV shRNA vector constitutively expresses a fluorescent protein marker (tagRFP) and puromycin antibiotic selection gene on a single transcript separated by a 2A self-cleaving peptide. These features enable easy assessment of infection rates and selection for transduced shRNA-expressing cells.

University of Pennsylvania uses Cellecta pMSCV-U6-sh-UbiC-TagRFP-2A-Puro vector system

To test knockdown, we cloned an shRNA known to effectively knock down mouse p53 into the MSCV plasmid. Vikram Paralkar in Mitch Weiss’s lab at the Children’s Hospital of Philadelphia tested the effectiveness of the construct in erythroid progenitor cells extracted from day 14.5 CD-1 mouse embryo fetal livers. The erythroid progenitors were infected with the MSCV-p53 construct, as well a control construct that did not contain the p53 sequence, packaged in viral particles. A multiplicity of infection (MOI) of virus to cells was used such that approximately 90% of the cells were transduced. Then, after 48 hours, the cells were harvested and RT-PCR was used to assess the expression level of the p53 target gene. The results below show that at least 75% knockdown of the p53 target transcript was obtained.

University of Pennsylvania shows shRNA knockdown of p53 in mouse hematopoietic cells using MSCV vector system

The results indicate that this MSCV vector provides an effective alternative for shRNA expression in mouse hematopoietic cells where lentivirus infection is problematic. The efficiency levels of cloning and transduction with the MSCV vector appear to be sufficient to enable construction and screening with complex pooled shRNA libraries as effectively as with our standard lentiviral system.

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The 2012 Cell Biology Meeting: A Good Finish to the Year

January 4th, 2013 by pauld-cellecta No comments »
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2013 seems to have started at a full sprint. It feels as though the annual meeting of the American Society of Cell Biology in San Francisco just finished. We exhibited and presented a tutorial there entitled, Find Functionally Important Driver Genes with RNAi Genetic Screening
Using Pooled shRNA Libraries
on December 17. Now in the first week of January, the holidays seemed to have come and gone with barely a skip in stride.

With almost 7,500 attendees, the Cell Biology meeting was a good finish to the year—a chance to catch up with old colleagues and meet some new ones.
Cellecta exhibit booth at ASCB 2012
With the focus on Cell Biology, of course there was a full complement of microscope and imaging companies. Our exhibit was situated near Zeiss which had a rotating sequence of exceptional images of drosophila larvae, tissues, and butterfly wings. Some we couldn’t figure out and neither, it seemed, could anyone at the Zeiss booth. You can see similar ones from Zeiss here with details on the image subject.

Salt Lake City based Vutara, who specialize in molecular resolution imaging, were located right next to us. A spin off of technology developed at the University of Utah, which seems to have an active incubator program. They told us that the University of Utah produces as many start ups as MIT, which surprised me. Evidently, it’s true though. The school seems to have a pretty effective Technology Commercialization Office.

Of course, the exhibitors represented a broad range of technology. For instance, across from our site, was Chromotek, a small German company who offer unique single-chain Alpaca antibody reagents. They came in just for the conference and were giving away cool flashing yo-yos. Also, similar sounding Cellectis, a French company specializing in targeted gene knockout technology, was just a few rows away. They are a much larger company than I realized with significant R&D efforts in drug development. And, B-Bridge International, who helped us get our start, were exhibiting the mechanical cell stretching instrument they distribute for Japanese manufacturer STREX.

Finally, there was also an interesting initiative from the US Dept. of Health and Human Services to consolidate all the regulatory information concerning Hopefully, this project will help eliminate the time and frustration in searching the websites of various government regulatory agencies to see which rule apply when shipping or working with certain biologics. Here’s more about the S3: Science, Safety, Security project.

All-in-all the conference was a good way to end the year. As we start the new one, we wish all our friends, customers, and colleagues a healthy, happy, and prosperous 2013.

Here’s a copy of the slides from the presentation.

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Second Phase SBIR Contract from the National Cancer Institute (NCI) to Identify Lethal Gene Combinations in Cancer Cell Models

October 23rd, 2012 by pauld-cellecta No comments »
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It’s been a while since the last post to this blog. It is not that nothing has been going on, in fact, quite the opposite. It has been quite busy the past several months and, unfortunately, blog postings have suffered. However, I thought I would get things started again with short post about our recent SBIR Contract.

Cellecta has been awarded an SBIR Phase II Contract from the NIH National Cancer Institute to continue its work using RNAi screens to identify paired combinations of DNA damage and repair (DDR) genes essential for cancer cells. Some results from the first phase of the grant were posted previously: http://cellecta.com/blog/2011/08/31/rnai-screen-cancer-synergistic-lethality. That work was essentially a proof of principle targeting combinations of 40 DDR genes. With this continuation of the contract, we can now move into a full scale screen of over 400 different DDR genes and run the screen in multiple cell models so we can identify which gene combinations are essential in each.

The purpose of the screen is to identify synthetic lethal genes–genes that, when inactivated together, have a significantly stronger lethal effect than when either is inactivated alone. The idea is that combination therapies could be developed using drugs that target both of the genes together. This combination approach makes is less likely for cancer cells to develop resistance to treatment.

With array based screening, however, it is extremely resource and labor intensive to identify these lethal combinations. However, a pooled RNAi screening approach using a library that co-expresses pairs of shRNAs targeting all combinations of the DDR genes enables efficient screens of tens of thousands of combinations.

We are making the dual shRNA expression libraries now and looking forward to getting these combinational screens started as soon as possible. As soon as we have something interesting, I’ll post it here—so keep an eye out for updates.
You can read the press release about Cellecta’s new SBIR Contract at http://www.prweb.com/releases/20121023/cellecta-rnai-screening/prweb10043967.htm

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Another Group Finds Similar Keys to Optimal Pooled shRNA Library Screens

March 20th, 2012 by pauld-cellecta 2 comments »
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Our group recently ran across an article describing an independent RNAi screen with a non-Cellecta pooled shRNA expression library that piqued our interest. In the October 2011 online Genome Biology Journal, Sims, et al. comprehensively described how to run a rigorous genome-wide pooled RNA interference screen using next generation sequencing. The article thoroughly describes the procedural steps involved in screening a heterogeneous pooled library of thousands of lentiviral shRNA expression constructs. Although they used a library somewhat different than our design (the lack of unique sequenceable barcodes being one notable difference), the study nicely demonstrates many of the requirements to ensure meaningful screening results and emphasizes the need to use high throughput next-generation sequencing (as opposed to microarray hybridization) for reproducible measurements of shRNA depletion or enrichment following selection.

Viability or “drop-out” screens that look for depletion of shRNA sequences in selected populations to identify essential genes are one of the most common applications of pooled shRNA screening. The Sims et al. study focuses primarily on the key factors to ensure reproducible results for these screens. Among the most important ones, they note the following:

  1. The shRNA expression library itself must be generated systematically to minimize variation in hairpin representation. This should be assessed by HT sequencing of the plasmid form of the library. Interestingly, Sims et al. also found that the plasmid library is a better reference for starting hairpin representation than the pseudoviral packaged library, which is consistent with our experience at Cellecta, too.
  2. It is essential to manage cell numbers to maintain hairpin representation through the whole screen. Specifically, Sims et al. recommends maintaining at least 1,000 cells per RNA–which is also the ratio we find optimal as described in an earlier blog post. They also caution against letting cells grow past 70% confluency before replating.
  3. Following selection, it is important to amplify sufficient genomic DNA to ensure a representative population from each cell sample. For their library of 10,000 shRNAs, they used at least 60ug of genomic DNA for pre-sequencing PCR amplification. We too find similar amounts necessary (i.e., for 27,000 shRNA, we us 200 ug/sample).
  4. Biological replicates are a requirement to overcome stochastic noise inherent in the screen. However, replicates should have a high level of reproducibility with R-squared values of 0.9 or better.
  5. The pooled shRNA library must be a reasonable size to enable practical handling of the cell populations, genomic DNA amplification, and biological replicates required for an effective screen. Sims et al used a library with 10,000 shRNA.

    As a result of the thorough technique, Sims et al. estimated they were able to identify more than 98% of the hairpins in all replicates. One distinct difference in the Sims et al. library compared with Cellecta’s is the presence of an barcode, that is, a unique readily identifiable sequence separate from the hairpin sequence that can be used to identify the particular shRNA in the expression cassette. Somewhat confusingly, though, Sims et al. used the term “barcode screen” although no barcode is present in their library. Detection of shRNA levels in selected populations was done by sequencing a portion of the shRNA encoding region. From our experience, use of a separate unique barcode optimized for sequence analysis increases sequencing calls and helps improve replicate correlations. Sims et al. did find that the pre-sequencing PCR step introduced a certain amount of noise in the data, which is consistent with amplification variability of shRNA sequences as opposed to short standardized barcodes.

    The consistency of the general findings of this independent study with our experience, however, is very encouraging. Using a similar but distinct library, Sims et al. have uncovered many of the same critical requirements for optimal screening with complex shRNA pools as we have. This alignment emphasizes the importance of these procedural details to obtaining meaningful screening results, and it provides additional support for RNAi screening standards of practice that was the topic of the previous post.

    Sims et al. also mentioned the development of two open source programs for computational analysis of pooled shRNA screening results–shALIGN and shRNAseq: http://rock.icr.ac.uk/software/shrnaseq.jsp.

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    The Need for RNAi Screening Standards

    February 3rd, 2012 by pauld-cellecta No comments »
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    A couple of months ago at the CHI Discovery on Target Conference, Hakim Djaballah, Director of the HTS Core Facility at the Memorial Sloan Kettering Cancer Center, gave a unique and insightful presentation highlighting the challenges RNAi screening to identify lethal loss of function interaction in oncogenic systems.

    For the exceptional benefits RNAi offers as a targeted tool to elucidate gene function, it is still a relatively new technology with limitations, potential, and idiosyncrasies that remain somewhat undefined.  These features are especially evident when RNAi is adapted for large-scale screening of gene function where small details in the set-up, screening process, quality of the reagents, and types of cells can significantly affect the variation and consistency in the large amount of data generated.  By highlighting some disappointing follow-up results from initially exciting high-profile publications, Dr. Djaballah identified a few critical benchmarks for evaluating RNAi screening.

    Dr. Djaballah’s group looked at three potentially high value cancer targets identified in independent loss-of-function RNAi screens.  In addition to the publications, his group reviewed the primary screening data in more detail to evaluate the procedure and statistical significance of the data. The first screen, published in May 2009 in Cell (Scholl, et al.), identified STK33 as required for KRAS oncogenic activity.  Initially, a very exciting discovery, a number of groups pursued STK33 as a potential therapeutic target.  However, subsequent groups (Barbie, et al. and Luo, et al.) failed to find the STK33 among the strong hits in similar screens.  A recent publication in September 2011 by Babij, et al. in Cancer Research, which also does not see STK33 as a hit in a similar shRNA screen, presents compelling data indicating STK33 is not, in fact, generally essential for survival KRAS-dependant cells.  Although, based on recent letters to the editor in Cancer Research, this does not seem to be the end of the discussion between these two groups, the initial excitement of STK33 seems to have been premature at best.

    The KRAS synthetic lethal screens by Barbie et al. mentioned above that did not pick-up STK33 as a strong hit their screen did, however,  identify another potentially interesting gene—the IκB kinase TBK1—that appeared essential for, but previously unknown to be involved in,  KRAS lethality.  This target was not found by other groups and has yet to be confirmed, but Dr. Djaballah had some reservations as to whether statistical analysis of the data really supported this as a true “hit” or simply an outlier.  Dr. Djaballah also had similar concerns with a recent Nature Letter in Oct. 2011 by Zuber et al that identified Brd4 as an essential gene and possible therapeutic target in acute myeloid leukemia cells.  A more detailed review of the data from this screen revealed some issues with the confidence of this hit, as there was significant variability in the CV values and a couple of the shRNAs were enriched by as much as million fold.

    Dr. Djaballah’s discussion was clearly not intended to disparage any specific study, but rather to demonstrate the slippery potential of over-interpreting the extensive data produced by such a powerful approach.  Based on the amount of resources and effort put into a complex screen, it can be difficult to maintain the reserve required to coldly and rigorously analyze the experimental design and results in a detached manner and properly assess which candidates really meet the criteria for follow up.  As a relatively new screening technology without much in the way of standards and defined good practices, it is easy to prematurely “fall in love” with potentially interesting targets that may be just noise in the data.  From his analysis, Dr. Djaballah suggests paying particular attention to the following three aspects:

    1. Do the infections at the appropriate MOI and with sufficient cells to assess the effect. Although Dr. Djaballah was primarily talking about arrayed screens (with single shRNA plasmids in wells), the points is also very valid for pooled screening.  It is critical to ensure there are each cells containing each shRNA to be assayed to generate reliable reproducible results.
    2. Use correct passage times. Whether the screen requires looking at knockdowns or survival, it is important that the cells are maintained for a long enough passage number to produce a significant differential between affected and non-affected cells.  Conversely, too many passages will introduce too much noise.
    3. Pay attention to general data and overall results. It is important to see if the overall screening results make sense.  For example, are known lethal genes showing up in the hits?

    While pointing out the importance of these considerations in evaluating a screening, Dr. Djaballah contended overall that there are currently few standards of practice to provide guidelines around these and similar procedural details.  We at Cellecta would agree, having focused most of our effort in the last several years toward optimizing the many subtleties of pooled shRNA screening to enable consistent, robust, and interpretable results.

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    Tissue Targeting May Offer an Alternative Therapeutic Approach for Difficult-to-Treat Diseases

    October 13th, 2011 by pauld-cellecta No comments »
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    We recently received a phase II of our SBIR grant Exploiting Synthetic Lethality of Hematopoietic Lineage Cells to Develop Novel Targets from the NIH. Rather than trying to identify potential drug targets in oncogenic hematopoietic cells, much of the effort for this project focuses on trying to develop a pharmacologic approach to identify and kill off all hematopoietic cells (see recent press release). This sort of capability may offer an alternative therapeutic approach relying on tissue ablation and renewal to treat hematopoietic cancers such as leukemia and lymphoma.

    Clinical approaches exist to regrow and regenerate portions of many essential tissues. For serious diseases, this capability offers a somewhat aggressive treatment possibility where affected tissues are completely eliminated and replaced by new healthy tissue. Blood is one such tissue where that can be regenerated with current clinical procedures. Though risky, a patient’s blood can be regenerated from a bone marrow cell graft through autologous hematopoietic stem cell transplantation and this is a currently a treatment of last resort for individuals suffering with life-threatening blood or bone marrow cancers. However, there is also much focus on regenerative approaches with other tissues, such as bone and skin. In addition, loss of other tissues such as thymus, prostate, and ovary do not have a significant negative impact on the quality of life. As research advances, it is reasonable to assume regenerative approaches will be available for an increasing range of cell types and tissues.

    Since all cells of one tissue or lineage type are removed and replaced using this approach, the specific pathology is not particularly significant for ablative and regenerative treatments. Rather than targeting specific cells based on certain disease biology, eradication of all cells in a particular class eliminates the disorder regardless of its nature. This opens up a real opportunity to develop effective therapies for a range of diseases for which there are currently limited treatment options. As clinical technology develops, stem cell therapies improves, more tissue regeneration protocols are established, and in vitro tissue and organ culture technology becomes routine, ablative/replacement treatments may become the preferred therapeutic approach to treat any number of a broad range of disease states.

    A major hurdle with this sort of therapy, however, is the in situ eradication step of the diseased cell or tissue. Currently, the principal ways to eliminate damaged cells types or tissues are through localized excision via surgery or radioactive ablation. For example, with autologous hematopoietic stem cell transplantation mentioned above, much of the toxicity of the treatment is associated with the general full-body radiation treatments to which patients are subjected to ablate an individual’s endogenous bone marrow before grafting in new healthy tissue. More precisely targeted approaches to eliminate affected cells are necessary if tissue replacement is to become a generally useful treatment option. Pharmacologicals that target and kill specific types of cells would provide a much needed solution for this problem, and may be easier to develop than drugs that specifically target only diseased, but not healthy, cells. The first step in developing these sorts of targeted molecules is identifying unique tissue-specific markers and potential drug targets as we are attempting for hematopoietic cells with this project.

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    Screening for Synergistically Lethal Knockdown Combinations in Cancer Cells

    August 31st, 2011 by pauld-cellecta No comments »
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    Therapeutic approaches using multiple drug combinations have become a standard treatment model for many types of cancer. Due to the tremendous genetic complexity and adaptive nature of most human malignancies, the use of multiple drugs acting on different targets increases the efficacy and helps thwart the development of drug resistance. However, the search for new treatment options and expanding number of drug candidates create a demand for better understanding and prediction of the most effective combinations to expedite evaluation and application in clinical settings.

    To help address this challenge, Cellecta responded to an NIH contract request to develop new tools that help assess the effect of combinatorially silencing pairs of genes. We developed a variation of our RNAi pooled screening that systematically identifies and prioritizes gene pairs that, when knocked down, significantly inhibit cancer cell growth. In other words, rather than simply identifying which individual genes are essential for growth of cancer cell lines, we identify which pairs that, when silenced, most significantly inhibit cancer cell proliferation.

    In some cases, the loss of two genes may be additive and strongly impair cell growth much more significantly than the loss of either gene independently. In fact, sometimes either gene independently may not have any negative effect on cells but, when both are knocked down, there is a synergistic effect that is very lethal to cells. Conversely, losing the function of two known essential genes may not, in fact, have any more of an adverse affect on cell proliferation than the loss either separately. As a result, then, it is very difficult to predict the effect of a loss of a pair of genes so each combination must be tested.

    For this project, we made a specialized lentiviral vector containing two shRNA expression cassettes so the construct expresses two different shRNAs from independent promoters. A library of shRNAs was cloned into each of these shRNA expression cassettes to make a pooled heterogeneous population that expressed all paired combinations of shRNAs. With some cloning tricks, we were able to incorporate a short uniquely identifiable sequence (i.e., a “bar-code”) that identified which two shRNAs were in each vector.

    The data below were generated with four shRNAs designed against each of 40 DNA damage and repair genes (160 shRNAs total) so, on completion, there were 25,600 different combinations—160 in the first shRNA position vs. 160 in the second. Using this library, we ran an RNAi lethality screen with an isogenic panel of immortalized human mammary epithelial (HMEC) cells using our standard procedures. We have validated several of the pairs and confirmed the combinatorial effect on cell growth. The approach can be reasonably extended to systematically test all combinations of approximately 200 targets in a single screen.

     
    Cytotoxicity level of shRNA combinations identified in synergistic lethality screen with 27K DDR library in HMEC-TERT cells.
     

    Cytotoxicity (bar-code depletion) level of bispecific shRNA constructs identified in SL screen with 27K DDR library in HMEC-TERT cells. Control – shRNA targeting luciferase gene.
     

    Obviously, this approach provides an alternative to what would otherwise be extremely time consuming and expensive pair-wise individual assays to assess lethal gene knockdown combinations in large numbers of target genes. Moreover, it demonstrates the power and flexibility of pooled library screens to address the challenges of elucidating the multiple functional roles and importance of various genes in the variety of biological model systems used in life science and drug discovery research.

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    shRNA Design Results – How good is your algorithm?

    August 3rd, 2011 by pauld-cellecta No comments »
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    The last blog entry discussed how hairpin structural features affect representation and effectiveness of shRNA sequences in pooled libraries. However, it is clear that the nucleotide sequence is possibly the major factor that determines the efficiency at which a particular siRNA or shRNA knocks down a target.
    Despite a large amount of research over the last several years on various features that affect knockdown potential, a priori prediction of most effective siRNA/shRNA sequences continues to be very much “hit and miss.” As anyone familiar with RNAi is aware, there are numerous design algorithms available online from a variety of commercial and academic sources. For example, several publicly available prediction algorithms are listed and described at Protocol Online and on the Charité-Universitätsmedizin Berlin website.

    Cellecta, of course, has also focused a large amount of effort divining the critical parameters to effectively predict shRNA. With a pooled screening, even small improvements in our proportion of effective sequences produces significant differences in screening results. We have been using an approach that assesses a number of parameters related to GC composition and distribution. This approach has been quite effective as the data from a recent set of designed shRNA shows (see below). In this case, we designed 5 shRNA to each of 29 gene targets. For all but one of the targets, at least one shRNA construct generated greater than 70% knockdown of the targeted transcript (measured by qRT-PCR) and, for 23 of the targets there were multiple constructs generating >70% knockdown for each target.

    result of new shRNA design on knockdown efficiency

    The results of the project shown here were produced using a relatively straightforward approach. Recently, as part of an NIH grant, we have coupled knockdown data and results from phenotypic screens with a self-learning algorithm to produce a more sophisticated analysis that assesses over a hundred characteristics in a tree like process to identify “good” shRNA. This sort of analysis has increased the fraction of effective shRNA (shRNA that knockdown that target by >70%) by about 10%–from about 65%-70% to close to 80%. Access to this design algorithm will soon be available on the Decipher Project website. In the end, the improvement seems to be a result of eliminating the worst performers, rather than improving the prediction of the best shRNA. This indicates that improvements in effective prediction may not lie with identifying which parameters enhance or promote effective RNA inhibition, but rather, in identifying which parameters can potentially disrupt inhibition.

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    The Importance of shRNA Structural Design for Pooled Libraries

    June 23rd, 2011 by pauld-cellecta No comments »
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    We have done a significant amount of evaluation to identify features of the optimal shRNA structure necessary to ensure our complex libraries maintain and express representative and effective shRNA. Independent from particular targeting sequences, structural variations such as defined mismatches, loop sizes, and stem lengths have significant affect on both the cloning and maintenance of the hairpin-coding insert in the heterogeneous library, as well as subsequent stability of the insert to integrate and stably express in the host cell. To provide comprehensive screening, it is critical to optimize the structure so that the library can maintain a representative copy number of all shRNA sequences with minimal bias through cloning, amplification, packaging, transduction, and selection.

    For the initial structural analysis, we made use of an shRNA-testing reporter construct using a destabilized green fluorescent protein (GFP). A description of this reporter system can be found in the Technology section of our website and more details will be available for publication shortly. I would just point out that, by combining this reporter construct with our library screening technology, we were able to analyze the effects of 40 different design variations of 150 different shRNA targeting sequences. Subsequent analysis by qRT-PCR of the best 10 designs showed significant variation as you can see from the data below that shows three examples of 10 variations of shRNA targeting the same region of the p53 gene. In the end, the best structure was a 25-base stem containing a few precise mismatches and a 7-nt loop.
     

    p53 knockdown percentage for various shRNA structures

     
    One question we often get asked when presenting this optimization strategy is how the miRNA structure compares. In fact, we did not include miRNA variations in this study because we previously found that they anecdotally did not perform as well as shRNA. Cellular processing of miRNA to form the RNA-induced silencing complex requires digestion with both the Drosha and Dicer enzymes. Intuitively, the addition of the extra Drosha processing might be expected to make the effective concentration of the active siRNA form somewhat lower in the cells and also make it less universally effective across different cell lines since it depends on the effective activity of two enzymes instead of just the one. Anecdotally, we did find a lot of variation with miRNA forms that we tested. Published results from a CGAP-sponsored inhibition study of the shRNAmir miRNA variation also found similar results in terms of effectiveness and variation. The study contained a lot of interesting data presented many ways but the finding that particularly stood out what that, across more than 100 genes, only about 37% of expressed shRNAmir produced >75% knockdown in OVCAR-8 cells and just 12% provided 75% knockdown in MCF7 cells (See CGAP Study Figure 1). Hairpin shRNA structures routinely generated much better knockdown rates.
     

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    RNAi Screening with An Inducible Promoter: Is There an Advantage?

    May 12th, 2011 by pauld-cellecta 2 comments »
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    Inducible expression is often desirable for functional genetic testing to establish clear cause and effect for a specific phenotype. A particular phenotype can be demonstrably linked to expression of a specific cDNA by showing it disappears when transcription is suppressed. Although less direct, similar logic applies to shRNA expression, where a phenotype appears when an shRNA is expressed and disappears when the same shRNA is repressed. To facilitate these types of analyses, we developed inducible versions of both the H1 and U6 RNA polymerase III promoters using the tetracycline repressor element. These promoter constructs were optimized so that the addition of tetracycline (actually, a tetracycline-analog doxycycline) induces expression of the shRNA by inhibiting the tetracycline-element-specific repressor (TetR) from binding and blocking transcription. An example of induced repression of GFP can be seen in the figure below.

    Fluorescent cell images indicating inducible shRNA inhibiting GFP expression

    We routinely use tetracycline-inducible shRNA promoters to validate the effectiveness of individual shRNA sequences identified in our screenings. In particular, with potentially lethal shRNA that target essential genes for cell viability, it is almost a requirement to prevent expression of the shRNA until the cells are established so that the phenotype of cell arrest, necrosis, or apoptosis can be clearly observed and specifically linked to expression of the shRNA. Since the purpose of a majority of our screens is to identify essential genes required for cell proliferation, these inducible shRNA constructs are essential for validating the identified “hits.”

    For general functional shRNA screening, however, inducibility is not always desirable. Although it is often assumed by research groups with whom we interact that a library with an inducible shRNA promoter would produce more reproducible and quantitative hits from a genetic screen, our experience indicates this is not necessarily the case. For example, with viability screens, where we are simply looking for which shRNA sequences inhibit cell proliferation (i.e., shRNAs that are depleted in the overall cell population after several divisions), the need to induce the expression of the library by adding doxycycline to the cells complicates the screening procedure and can introduce some unnecessary variation in the system. Of course, with some screens, it may be preferable or even necessary to use an inducible library. For example, screens to identify genes which repress a particular reporter may be easier to carry out when shRNA expression in the library is repressed until sometime after infection and selection of a baseline population. Also, for in vivo screening, using an inducible library may be almost essential so that significant library shRNA expression and selection does not occur until the cells are established in the mouse model. However, there is no clear benefit to including a defined induction step in any particular screen.

    As with most experimental options, choosing between inducible vs. constitutive shRNA expression for a library requires careful consideration of the experimental setup. While the disadvantages are not always so obvious, there are often unforeseen drawbacks in adding seemingly small variables into what is already a technically challenging assay.

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