Funding, Deals & Partnerships: BIOLOGICS & MEDICAL DEVICES; BioMed e-Series; Medicine and Life Sciences Scientific Journal – http://PharmaceuticalIntelligence.com
Analysis of Utilizing LPBI Group’s Scientific Curation Platform as an Educational Tool: New Paradigm for Student Engagement
Author: Stephen J. Williams, Ph.D.
Use of LBPI Platform for Educational Purposes
Goal: to offer supplemental information for student lessons in an upper level Biology course on Cell Signaling and Cell Motility with emphasis on disease etiology including cancer, neurological disease, and cardiovascular disease.
Course: Temple University Department of Biology course Cell Signaling and Motility Spring semester 2019. Forty five students enrolled.
Methodology: Each weekly lesson was presented to students as a PowerPoint presentation. After each lesson the powerpoint presentation was originally meant to be disseminated to each class-registered student on the students Canvas account. Canvas is a cloud based Learning Management Software developed by educational technology company Salt Lake City, Utah company Infrastructure, Inc. According to rough figures, Canvas® charges a setup fee and at least $30 per user (for a university the size of Temple University: 55,000 students at $30 each = 1.6 million a semester for user fees only).
As a result of a technical issue with uploading the first week lesson on this system, I had informed the class that, as an alternative means, class presentation notes and lectures will be posted on the site www.pharmaceuticalintelligence.com as a separate post and searchable on all search engines including Google, Twitter, Yahoo, Bing, Facebook etc. In addition, I had informed the students that supplemental information, from curated posts and articles from our site, would be added to the class lecture post as supplemental information they could use for further reading on the material as well as helpful information and reference for class projects.
The posted material was tagged with #TUBiol3373 (university abbreviation, department, course number) and disseminated to various social media platforms using our system. This allowed the students to enter #TUBiol3373 in any search engine to easily find their lecture notes and supplemental information.
This gave students access to lectures on a mobile platform which was easily discoverable due to our ability to do search engine optimization. (#TUBiol3373 was among the first search results on most popular search engines).
From a technical standpoint, the ease at which posts of this nature can be made as well as the ease of including links to full articles as references as well as media has been noted. Although students seem to navigate the Canvas software with ease, they had noticed many professors have issues or problems with using this software, especially with navigating the software for their needs. LBPI’s platform is an easily updated, accessible, and extensive knowledge system which can alleviate many of these technical issues and provide the added value of incorporating media based instructional material as well as downloadable file and allow the instructor ability to expound on the presented material with commentary. In addition due to the social nature of the platform, feedback can be attained by use of curated site statistics and commentary sections as well as online surveys.
Results
After the first week, all 45 students used LBPI platform to access these lecture notes with 17 out of 45 continuing to refer to the site during every week (week 1-4) to the class notes. This was evident from our site statistics as well as number of downloads of the material. The students had used the #TUBIol3373 and were directed to the site mainly from search engines Google and Yahoo. In addition, students had also clicked on the links corresponding to supplemental information which I had included, from articles on our site. In addition, because of the ability to incorporate media on our site, additional information including instructional videos and interviews were included in lecture posts, and this material was easily updated on the instructor’s side.
Adoption of the additional material from our site was outstanding, as many students had verbally said that the additional material was very useful in their studies. This was also evidenced by site statistics owing to the secondary clicks made from the class lecture post going to additional articles, some not even included as links on the original post.
In addition, and more important, students had incorporated many of the information from the additional site articles posted and referenced in their class group projects. At end of semester a survey was emailed to each student to assess the usefulness of such a teaching strategy. Results of the polling are shown below.
Results from polling of students of #TUBiol3373 “Cell Signaling & Motility” Class
Do you find using a web based platform such as a site like this an easier communication platform for posting lecture notes/added information than a platform like Canvas®? (5 votes)
Answer
Votes
Percent
Yes
2
40%
Somewhat but could use some improvement
2
40%
No
1
20%
Did not use web site
0
0%
Do you find using an open access, curated information platform like this site more useful than using multiple sources to find useful extra study/presentation materials? (6 votes)
Answer
Votes
Percent
Yes
5
83%
No
1
17%
Did you use the search engine on the site (located on the top right of the home page) to find extra information on topics for your presentations/study material? (5 votes)
Answer
Votes
Percent
Yes
4
67%
No
1
17%
Did not use web site
1
17%
Were you able to easily find the supplemental information for each lecture on search engines like Google/Yahoo/Bing/Twitter using the hashtag #TUBiol3373? (6 votes)
Answer
Votes
Percent
Yes I was able to find the site easily
4
67%
No
1
17%
Did not use a search engine to find site, went directly to site
1
17%
Encountered some difficulty
0
0%
Did not use the site for supplemental or class information
0
0%
How did you find the supplemental material included on this site above the Powerpoint presented material for each of the lectures? (7 votes)
Note: for calculation of %views on days 1 and 2 of posting lesson and supplemental material on the journal; %views day1 and 2 = (#views day 1 + #views day 2)*100/45 {45 students in class}
For calculation of %views past day 1 and 2 = (total # views – day1 views – day2 views) * 100/45
For calculation in total column last two columns were divided by # of students (45) and # of posts (8)
Overall class engagement was positive with 31% of students interacting with the site during the course on the first two days after posting lessons while 61% of students interacted with the site during the rest of the duration of the course. The higher number of students interacting with the site after the first two days after lecture and posting may be due to a higher number of students using the posted material for study for the test and using material for presentation purposes.
Engagement with the site for the first two days post lecture ranged from 93% engagement to 22% engagement. As the class neared the first exam engagement with the site was high however engagement was lower near the end of the class period potentially due to the last exam was a group project and not a written exam. Students appeared to engage highly with the site to get material for study for the written exam however there still was significant engagement by students for purposes of preparation for oral group projects. Possibly engagement with the site post 2 days for the later lectures could be higher if a written exam was also given towards the end of the class as well. This type of analysis allows the professor to understand the level of class engagement week by week.
The results of post-class polling confirm some of the conclusions on engagement. After the final grades were given out all 45 students received an email with a link to the poll. Of the 45 students emailed, there were 20 views of the poll with 5-7 answers per question. Interestingly, most answers were positive on the site and the use of curated material for learning and a source of research project material. It was very easy finding the posts using the #classname and most students used Google to find the material, which was at the top of Google search results. Not many students used Twitter or other search engines. Some went directly to the site. A majority (71%) found the material useful or somewhat useful for their class presentations and researching topics.
Babies born at or before 25 weeks have quite low survival outcomes, and in the US it is the leading cause of infant mortality and morbidity. Just a few weeks of extra ‘growing time’ can be the difference between severe health problems and a relatively healthy baby.
Researchers from The Children’s Hospital of Philadelphia (USA) Research Institute have shown it’s possible to nurture and protect a mammal in late stages of gestation inside an artificial womb; technology which could become a lifesaver for many premature human babies in just a few years.
The researchers took eight lambs between 105 to 120 days gestation (the physiological equivalent of 23 to 24 weeks in humans) and placed them inside the artificial womb. The artificial womb is a sealed and sterile bag filled with an electrolyte solution which acts like amniotic fluid in the uterus. The lamb’s own heart pumps the blood through the umbilical cord into a gas exchange machine outside the bag.
The artificial womb worked in this study and after just four weeks the lambs’ brains and lungs had matured like normal. They had also grown wool and could wiggle, open their eyes, and swallow. Although this study is looking incredibly promising but getting the research up to scratch for human babies still requires a big leap.
Nevertheless, if all goes well, the researchers hope to test the device on premature humans within three to five years. Potential therapeutic applications of this invention may include treatment of fetal growth retardation related to placental insufficiency or the salvage of preterm infants threatening to deliver after fetal intervention or fetal surgery.
The technology may also provide the opportunity to deliver infants affected by congenital malformations of the heart, lung and diaphragm for early correction or therapy before the institution of gas ventilation. Numerous applications related to fetal pharmacologic, stem cell or gene therapy could be facilitated by removing the possibility for maternal exposure and enabling direct delivery of therapeutic agents to the isolated fetus.
Chemotherapy Benefit in Early Breast Cancer Patients
Larry H Bernstein, MD, FCAP, Curator
LPBI
Agendia’s MammaPrint® First and Only Genomic Assay to Receive Level 1A Clinical Utility Evidence for Chemotherapy Benefit in Early Breast Cancer Patients
Clinical high-risk patients with a low-risk MammaPrint® result, including 48 percent node-positive, had five-year distant metastasis-free survival rate in excess of 94 percent, whether randomized to receive adjuvant chemotherapy or not
MammaPrint could change clinical practice by substantially de-escalating the use of adjuvant chemotherapy and sparing many patients an aggressive treatment they will not benefit from
Forty-six percent overall reduction in chemotherapy prescription among clinically high-risk patients
April 19, 2016 / B3C newswire / —Agendia, Inc., together with the European Organisation for Research and Treatment of Cancer (EORTC) and Breast International Group (BIG), announced results from the initial analysis of the primary objective of the Microarray In Node-negative (and 1 to 3 positive lymph node) Disease may Avoid ChemoTherapy (MINDACT) study at the American Association for Cancer Research Annual Meeting 2016 in New Orleans, LA.
Using the company’s MammaPrint® assay, patients with early-stage breast cancer who were considered at high risk for disease recurrence based on clinical and biological criteria had a distant metastasis-free survival at five years in excess of 94 percent.The MammaPrint test—the first and only genomic assay with FDA 510(k) clearance for use in risk assessment for women of all ages with early stage breast cancer—identified a large group of patients for whom five-year distant metastasis–free survival was equally good whether or not they received adjuvant chemotherapy (chemotherapy given post-surgery).
“The MINDACT trial design is the optimal way to prove clinical utility of a genomic assay,” said Prof. Laura van ’t Veer, CRO at Agendia, Leader, Breast Oncology Program, and Director, Applied Genomics at UCSF Helen Diller Family Comprehensive Cancer Center. “It gives the level 1A clinical evidence (prospective, randomized and controlled) that empowers physicians to clearly and confidently know when chemotherapy is part of optimal early-stage breast cancer therapy. In this trial, MammaPrint (70-gene assay) was compared to the standard of care physicians use today, to decide what is the best treatment option for an early-stage breast cancer patient.”
The MINDACT trial is the first prospective randomized controlled clinical trial of a breast cancer recurrence genomic assay with level 1A clinical evidence and the first prospective translational research study of this magnitude in breast cancer to report the results of its primary objective.
Among the 3,356 patients enrolled in the MINDACT trial, who were categorized as having a high risk of breast cancer recurrence based on common clinical and pathological criteria (C-high), the MammaPrint assay reduced the chemotherapy treatment prescription by 46 percent.Using the 70-gene assay, MammaPrint, 48 percent of lymph-node positive breast cancer patients considered clinically high-risk (Clinical-high) and genomic low-risk (MammaPrint-low) had an excellent distant metastasis-free survival at five years in excess of 94 percent.
“Traditionally, physicians have relied on clinical-pathological factors such as age, tumor size, tumor grade, lymph node involvement, and hormone receptor status to make breast cancer treatment decisions,” said Massimo Cristofanilli, MD, Associate Director of Translational Research and Precision Medicine at the Robert H. Lurie Comprehensive Cancer Center, Northwestern University in Chicago. “These findings provide level 1A clinical utility evidence by demonstrating that the detection of low-risk of distant recurrence reported by the MammaPrint test can be safely used in the management of thousands of women by identifying those who can be spared from a toxic and unnecessary treatment.”
MINDACT is a randomized phase III trial that investigates the clinical utility of MammaPrint, when compared (or – “used in conjunction with”) to the standard clinical pathological criteria, for the selection of patients unlikely to benefit from adjuvant chemotherapy. From 2007 to 2011, 6,693 women who had undergone surgery for early-stage breast cancer enrolled in the trial (111 centers in nine countries). Participants were categorized as low or high risk for tumor recurrence in two ways: first, through analysis of tumor tissue using MammaPrint at a central location in Amsterdam; and second, using Adjuvant! Online, a tool that calculates risk of breast cancer recurrence based on common clinical and biological criteria.
Patients characterized in both clinical and genomic assessments as “low- risk” are spared chemotherapy, while patients characterized as “high- risk” are advised chemotherapy. Those with conflicting results are randomized to use either clinical or genomic risk (MammaPrint) evaluation to decide on chemotherapy treatment.
The MINDACT trial is managed and sponsored by the EORTC as part of an extensive and complex partnership in collaboration with Agendia and BIG, and many other academic and commercial partners, as well as patient advocates.
“These MINDACT trial results are a testament that the science of the MammaPrint test is the most robust in the genomic breast recurrence assay market. Agendia will continue to collaborate with pharmaceutical companies, leading cancer centers and academic groups on additional clinical research and in the pursuit of bringing more effective, individualized treatments within reach of cancer patients,” said Mark Straley, Chief Executive Officer at Agendia. “We value the partnership with the EORTC and BIG and it’s a great honor to share this critical milestone.”
Breast cancer is the most frequently diagnosed cancer in women worldwide(1). In 2012, there were nearly 1.7 million new breast cancer cases among women worldwide, accounting for 25 percent of all new cancer cases in women(2).
Imaging of Cancer Cells, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)
Imaging of Cancer Cells
Larry H. Bernstein, MD, FCAP, Curator
LPBI
Microscope uses nanosecond-speed laser and deep learning to detect cancer cells more efficiently
April 13, 2016
Scientists at the California NanoSystems Institute at UCLA have developed a new technique for identifying cancer cells in blood samples faster and more accurately than the current standard methods.
In one common approach to testing for cancer, doctors add biochemicals to blood samples. Those biochemicals attach biological “labels” to the cancer cells, and those labels enable instruments to detect and identify them. However, the biochemicals can damage the cells and render the samples unusable for future analyses. There are other current techniques that don’t use labeling but can be inaccurate because they identify cancer cells based only on one physical characteristic.
Time-stretch quantitative phase imaging (TS-QPI) and analytics system
The new technique images cells without destroying them and can identify 16 physical characteristics — including size, granularity and biomass — instead of just one.
The new technique combines two components that were invented at UCLA:
A “photonic time stretch” microscope, which is capable of quickly imaging cells in blood samples. Invented by Barham Jalali, professor and Northrop-Grumman Optoelectronics Chair in electrical engineering, it works by taking pictures of flowing blood cells using laser bursts (similar to how a camera uses a flash). Each flash only lasts nanoseconds (billionths of a second) to avoid damage to cells, but that normally means the images are both too weak to be detected and too fast to be digitized by normal instrumentation. The new microscope overcomes those challenges by using specially designed optics that amplify and boost the clarity of the images, and simultaneously slow them down enough to be detected and digitized at a rate of 36 million images per second.
A deep learning computer program, which identifies cancer cells with more than 95 percent accuracy. Deep learning is a form of artificial intelligence that uses complex algorithms to extract patterns and knowledge from rich multidimenstional datasets, with the goal of achieving accurate decision making.
The study was published in the open-access journal Nature Scientific Reports. The researchers write in the paper that the system could lead to data-driven diagnoses by cells’ physical characteristics, which could allow quicker and earlier diagnoses of cancer, for example, and better understanding of the tumor-specific gene expression in cells, which could facilitate new treatments for disease.
The research was supported by NantWorks, LLC.
Abstract of Deep Learning in Label-free Cell Classification
Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. This system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.
references:
Claire Lifan Chen, Ata Mahjoubfar, Li-Chia Tai, Ian K. Blaby, Allen Huang, Kayvan Reza Niazi & Bahram Jalali. Deep Learning in Label-free Cell Classification. Scientific Reports 6, Article number: 21471 (2016); doi:10.1038/srep21471 (open access)
Supplementary Information
Deep Learning in Label-free Cell Classification
Claire Lifan Chen, Ata Mahjoubfar, Li-Chia Tai, Ian K. Blaby, Allen Huang,Kayvan Reza Niazi & Bahram Jalali
Deep learning extracts patterns and knowledge from rich multidimenstional datasets. While it is extensively used for image recognition and speech processing, its application to label-free classification of cells has not been exploited. Flow cytometry is a powerful tool for large-scale cell analysis due to its ability to measure anisotropic elastic light scattering of millions of individual cells as well as emission of fluorescent labels conjugated to cells1,2. However, each cell is represented with single values per detection channels (forward scatter, side scatter, and emission bands) and often requires labeling with specific biomarkers for acceptable classification accuracy1,3. Imaging flow cytometry4,5 on the other hand captures images of cells, revealing significantly more information about the cells. For example, it can distinguish clusters and debris that would otherwise result in false positive identification in a conventional flow cytometer based on light scattering6.
In addition to classification accuracy, the throughput is another critical specification of a flow cytometer. Indeed high throughput, typically 100,000 cells per second, is needed to screen a large enough cell population to find rare abnormal cells that are indicative of early stage diseases. However there is a fundamental trade-off between throughput and accuracy in any measurement system7,8. For example, imaging flow cytometers face a throughput limit imposed by the speed of the CCD or the CMOS cameras, a number that is approximately 2000 cells/s for present systems9. Higher flow rates lead to blurred cell images due to the finite camera shutter speed. Many applications of flow analyzers such as cancer diagnostics, drug discovery, biofuel development, and emulsion characterization require classification of large sample sizes with a high-degree of statistical accuracy10. This has fueled research into alternative optical diagnostic techniques for characterization of cells and particles in flow.
Recently, our group has developed a label-free imaging flow-cytometry technique based on coherent optical implementation of the photonic time stretch concept11. This instrument overcomes the trade-off between sensitivity and speed by using Amplified Time-stretch Dispersive Fourier Transform12,13,14,15. In time stretched imaging16, the object’s spatial information is encoded in the spectrum of laser pulses within a pulse duration of sub-nanoseconds (Fig. 1). Each pulse representing one frame of the camera is then stretched in time so that it can be digitized in real-time by an electronic analog-to-digital converter (ADC). The ultra-fast pulse illumination freezes the motion of high-speed cells or particles in flow to achieve blur-free imaging. Detection sensitivity is challenged by the low number of photons collected during the ultra-short shutter time (optical pulse width) and the drop in the peak optical power resulting from the time stretch. These issues are solved in time stretch imaging by implementing a low noise-figure Raman amplifier within the dispersive device that performs time stretching8,11,16. Moreover, warped stretch transform17,18can be used in time stretch imaging to achieve optical image compression and nonuniform spatial resolution over the field-of-view19. In the coherent version of the instrument, the time stretch imaging is combined with spectral interferometry to measure quantitative phase and intensity images in real-time and at high throughput20. Integrated with a microfluidic channel, coherent time stretch imaging system in this work measures both quantitative optical phase shift and loss of individual cells as a high-speed imaging flow cytometer, capturing 36 million images per second in flow rates as high as 10 meters per second, reaching up to 100,000 cells per second throughput.
Box 1: The pulse train is spatially dispersed into a train of rainbow flashes illuminating the target as line scans. The spatial features of the target are encoded into the spectrum of the broadband optical pulses, each representing a one-dimensional frame. The ultra-short optical pulse illumination freezes the motion of cells during high speed flow to achieve blur-free imaging with a throughput of 100,000 cells/s. The phase shift and intensity loss at each location within the field of view are embedded into the spectral interference patterns using a Michelson interferometer. Box 2: The interferogram pulses were then stretched in time so that spatial information could be mapped into time through time-stretch dispersive Fourier transform (TS-DFT), and then captured by a single pixel photodetector and an analog-to-digital converter (ADC). The loss of sensitivity at high shutter speed is compensated by stimulated Raman amplification during time stretch. Box 3: (a) Pulse synchronization; the time-domain signal carrying serially captured rainbow pulses is transformed into a series of one-dimensional spatial maps, which are used for forming line images. (b) The biomass density of a cell leads to a spatially varying optical phase shift. When a rainbow flash passes through the cells, the changes in refractive index at different locations will cause phase walk-off at interrogation wavelengths. Hilbert transformation and phase unwrapping are used to extract the spatial phase shift. (c) Decoding the phase shift in each pulse at each wavelength and remapping it into a pixel reveals the protein concentration distribution within cells. The optical loss induced by the cells, embedded in the pulse intensity variations, is obtained from the amplitude of the slowly varying envelope of the spectral interferograms. Thus, quantitative optical phase shift and intensity loss images are captured simultaneously. Both images are calibrated based on the regions where the cells are absent. Cell features describing morphology, granularity, biomass, etc are extracted from the images. (d) These biophysical features are used in a machine learning algorithm for high-accuracy label-free classification of the cells.
On another note, surface markers used to label cells, such as EpCAM21, are unavailable in some applications; for example, melanoma or pancreatic circulating tumor cells (CTCs) as well as some cancer stem cells are EpCAM-negative and will escape EpCAM-based detection platforms22. Furthermore, large-population cell sorting opens the doors to downstream operations, where the negative impacts of labels on cellular behavior and viability are often unacceptable23. Cell labels may cause activating/inhibitory signal transduction, altering the behavior of the desired cellular subtypes, potentially leading to errors in downstream analysis, such as DNA sequencing and subpopulation regrowth. In this way, quantitative phase imaging (QPI) methods24,25,26,27 that categorize unlabeled living cells with high accuracy are needed. Coherent time stretch imaging is a method that enables quantitative phase imaging at ultrahigh throughput for non-invasive label-free screening of large number of cells.
In this work, the information of quantitative optical loss and phase images are fused into expert designed features, leading to a record label-free classification accuracy when combined with deep learning. Image mining techniques are applied, for the first time, to time stretch quantitative phase imaging to measure biophysical attributes including protein concentration, optical loss, and morphological features of single cells at an ultrahigh flow rate and in a label-free fashion. These attributes differ widely28,29,30,31 among cells and their variations reflect important information of genotypes and physiological stimuli32. The multiplexed biophysical features thus lead to information-rich hyper-dimensional representation of the cells for label-free classification with high statistical precision.
We further improved the accuracy, repeatability, and the balance between sensitivity and specificity of our label-free cell classification by a novel machine learning pipeline, which harnesses the advantages of multivariate supervised learning, as well as unique training by evolutionary global optimization of receiver operating characteristics (ROC). To demonstrate sensitivity, specificity, and accuracy of multi-feature label-free flow cytometry using our technique, we classified (1) OT-IIhybridoma T-lymphocytes and SW-480 colon cancer epithelial cells, and (2) Chlamydomonas reinhardtii algal cells (herein referred to as Chlamydomonas) based on their lipid content, which is related to the yield in biofuel production. Our preliminary results show that compared to classification by individual biophysical parameters, our label-free hyperdimensional technique improves the detection accuracy from 77.8% to 95.5%, or in other words, reduces the classification inaccuracy by about five times. ……..
Feature Extraction
The decomposed components of sequential line scans form pairs of spatial maps, namely, optical phase and loss images as shown in Fig. 2 (see Section Methods: Image Reconstruction). These images are used to obtain biophysical fingerprints of the cells8,36. With domain expertise, raw images are fused and transformed into a suitable set of biophysical features, listed in Table 1, which the deep learning model further converts into learned features for improved classification.
The new technique combines two components that were invented at UCLA:
A “photonic time stretch” microscope, which is capable of quickly imaging cells in blood samples. Invented by Barham Jalali, professor and Northrop-Grumman Optoelectronics Chair in electrical engineering, it works by taking pictures of flowing blood cells using laser bursts (similar to how a camera uses a flash). Each flash only lasts nanoseconds (billionths of a second) to avoid damage to cells, but that normally means the images are both too weak to be detected and too fast to be digitized by normal instrumentation. The new microscope overcomes those challenges by using specially designed optics that amplify and boost the clarity of the images, and simultaneously slow them down enough to be detected and digitized at a rate of 36 million images per second.
A deep learning computer program, which identifies cancer cells with more than 95 percent accuracy. Deep learning is a form of artificial intelligence that uses complex algorithms to extract patterns and knowledge from rich multidimenstional datasets, with the goal of achieving accurate decision making.
The study was published in the open-access journal Nature Scientific Reports. The researchers write in the paper that the system could lead to data-driven diagnoses by cells’ physical characteristics, which could allow quicker and earlier diagnoses of cancer, for example, and better understanding of the tumor-specific gene expression in cells, which could facilitate new treatments for disease.
The optical loss images of the cells are affected by the attenuation of multiplexed wavelength components passing through the cells. The attenuation itself is governed by the absorption of the light in cells as well as the scattering from the surface of the cells and from the internal cell organelles. The optical loss image is derived from the low frequency component of the pulse interferograms. The optical phase image is extracted from the analytic form of the high frequency component of the pulse interferograms using Hilbert Transformation, followed by a phase unwrapping algorithm. Details of these derivations can be found in Section Methods. Also, supplementary Videos 1 and 2 show measurements of cell-induced optical path length difference by TS-QPI at four different points along the rainbow for OT-II and SW-480, respectively.
Table 1: List of extracted features.
Feature Name Description Category
Figure 3: Biophysical features formed by image fusion.
(a) Pairwise correlation matrix visualized as a heat map. The map depicts the correlation between all major 16 features extracted from the quantitative images. Diagonal elements of the matrix represent correlation of each parameter with itself, i.e. the autocorrelation. The subsets in box 1, box 2, and box 3 show high correlation because they are mainly related to morphological, optical phase, and optical loss feature categories, respectively. (b) Ranking of biophysical features based on their AUCs in single-feature classification. Blue bars show performance of the morphological parameters, which includes diameter along the interrogation rainbow, diameter along the flow direction, tight cell area, loose cell area, perimeter, circularity, major axis length, orientation, and median radius. As expected, morphology contains most information, but other biophysical features can contribute to improved performance of label-free cell classification. Orange bars show optical phase shift features i.e. optical path length differences and refractive index difference. Green bars show optical loss features representing scattering and absorption by the cell. The best performed feature in these three categories are marked in red.
Figure 4: Machine learning pipeline. Information of quantitative optical phase and loss images are fused to extract multivariate biophysical features of each cell, which are fed into a fully-connected neural network.
The neural network maps input features by a chain of weighted sum and nonlinear activation functions into learned feature space, convenient for classification. This deep neural network is globally trained via area under the curve (AUC) of the receiver operating characteristics (ROC). Each ROC curve corresponds to a set of weights for connections to an output node, generated by scanning the weight of the bias node. The training process maximizes AUC, pushing the ROC curve toward the upper left corner, which means improved sensitivity and specificity in classification.
…. How to cite this article: Chen, C. L. et al. Deep Learning in Label-free Cell Classification.
To better characterize the functional context of genomic variations in cancer, researchers developed a new computer algorithm called REVEALER. [UC San Diego Health]
Scientists at the University of California San Diego School of Medicine and the Broad Institute say they have developed a new computer algorithm—REVEALER—to better characterize the functional context of genomic variations in cancer. The tool, described in a paper (“Characterizing Genomic Alterations in Cancer by Complementary Functional Associations”) published in Nature Biotechnology, is designed to help researchers identify groups of genetic variations that together associate with a particular way cancer cells get activated, or how they respond to certain treatments.
REVEALER is available for free to the global scientific community via the bioinformatics software portal GenePattern.org.
“This computational analysis method effectively uncovers the functional context of genomic alterations, such as gene mutations, amplifications, or deletions, that drive tumor formation,” said senior author Pablo Tamayo, Ph.D., professor and co-director of the UC San Diego Moores Cancer Center Genomics and Computational Biology Shared Resource.
Dr. Tamayo and team tested REVEALER using The Cancer Genome Atlas (TCGA), the NIH’s database of genomic information from more than 500 human tumors representing many cancer types. REVEALER revealed gene alterations associated with the activation of several cellular processes known to play a role in tumor development and response to certain drugs. Some of these gene mutations were already known, but others were new.
For example, the researchers discovered new activating genomic abnormalities for beta-catenin, a cancer-promoting protein, and for the oxidative stress response that some cancers hijack to increase their viability.
REVEALER requires as input high-quality genomic data and a significant number of cancer samples, which can be a challenge, according to Dr. Tamayo. But REVEALER is more sensitive at detecting similarities between different types of genomic features and less dependent on simplifying statistical assumptions, compared to other methods, he adds.
“This study demonstrates the potential of combining functional profiling of cells with the characterizations of cancer genomes via next-generation sequencing,” said co-senior author Jill P. Mesirov, Ph.D., professor and associate vice chancellor for computational health sciences at UC San Diego School of Medicine.
Characterizing genomic alterations in cancer by complementary functional associations
Jong Wook Kim, Olga B Botvinnik, Omar Abudayyeh, Chet Birger, et al.
Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment. We used REVEALER to uncover complementary genomic alterations associated with the transcriptional activation of β-catenin and NRF2, MEK-inhibitor sensitivity, and KRAS dependency. REVEALER successfully identified both known and new associations, demonstrating the power of combining functional profiles with extensive characterization of genomic alterations in cancer genomes
Figure 2: REVEALER results for transcriptional activation of β-catenin in cancer.close
(a) This heatmap illustrates the use of the REVEALER approach to find complementary genomic alterations that match the transcriptional activation of β-catenin in cancer. The target profile is a TCF4 reporter that provides an estimate of…
An imaging-based platform for high-content, quantitative evaluation of therapeutic response in 3D tumour models
Jonathan P. Celli, Imran Rizvi, Adam R. Blanden, Iqbal Massodi, Michael D. Glidden, Brian W. Pogue & Tayyaba Hasan
While it is increasingly recognized that three-dimensional (3D) cell culture models recapitulate drug responses of human cancers with more fidelity than monolayer cultures, a lack of quantitative analysis methods limit their implementation for reliable and routine assessment of emerging therapies. Here, we introduce an approach based on computational analysis of fluorescence image data to provide high-content readouts of dose-dependent cytotoxicity, growth inhibition, treatment-induced architectural changes and size-dependent response in 3D tumour models. We demonstrate this approach in adherent 3D ovarian and pancreatic multiwell extracellular matrix tumour overlays subjected to a panel of clinically relevant cytotoxic modalities and appropriately designed controls for reliable quantification of fluorescence signal. This streamlined methodology reads out the high density of information embedded in 3D culture systems, while maintaining a level of speed and efficiency traditionally achieved with global colorimetric reporters in order to facilitate broader implementation of 3D tumour models in therapeutic screening.
The attrition rates for preclinical development of oncology therapeutics are particularly dismal due to a complex set of factors which includes 1) the failure of pre-clinical models to recapitulate determinants of in vivo treatment response, and 2) the limited ability of available assays to extract treatment-specific data integral to the complexities of therapeutic responses1,2,3. Three-dimensional (3D) tumour models have been shown to restore crucial stromal interactions which are missing in the more commonly used 2D cell culture and that influence tumour organization and architecture4,5,6,7,8, as well as therapeutic response9,10, multicellular resistance (MCR)11,12, drug penetration13,14, hypoxia15,16, and anti-apoptotic signaling17. However, such sophisticated models can only have an impact on therapeutic guidance if they are accompanied by robust quantitative assays, not only for cell viability but also for providing mechanistic insights related to the outcomes. While numerous assays for drug discovery exist18, they are generally not developed for use in 3D systems and are often inherently unsuitable. For example, colorimetric conversion products have been noted to bind to extracellular matrix (ECM)19 and traditional colorimetric cytotoxicity assays reduce treatment response to a single number reflecting a biochemical event that has been equated to cell viability (e.g. tetrazolium salt conversion20). Such approaches fail to provide insight into the spatial patterns of response within colonies, morphological or structural effects of drug response, or how overall culture viability may be obscuring the status of sub-populations that are resistant or partially responsive. Hence, the full benefit of implementing 3D tumour models in therapeutic development has yet to be realized for lack of analytical methods that describe the very aspects of treatment outcome that these systems restore.
Motivated by these factors, we introduce a new platform for quantitative in situ treatment assessment (qVISTA) in 3D tumour models based on computational analysis of information-dense biological image datasets (bioimage-informatics)21,22. This methodology provides software end-users with multiple levels of complexity in output content, from rapidly-interpreted dose response relationships to higher content quantitative insights into treatment-dependent architectural changes, spatial patterns of cytotoxicity within fields of multicellular structures, and statistical analysis of nodule-by-nodule size-dependent viability. The approach introduced here is cognizant of tradeoffs between optical resolution, data sampling (statistics), depth of field, and widespread usability (instrumentation requirement). Specifically, it is optimized for interpretation of fluorescent signals for disease-specific 3D tumour micronodules that are sufficiently small that thousands can be imaged simultaneously with little or no optical bias from widefield integration of signal along the optical axis of each object. At the core of our methodology is the premise that the copious numerical readouts gleaned from segmentation and interpretation of fluorescence signals in these image datasets can be converted into usable information to classify treatment effects comprehensively, without sacrificing the throughput of traditional screening approaches. It is hoped that this comprehensive treatment-assessment methodology will have significant impact in facilitating more sophisticated implementation of 3D cell culture models in preclinical screening by providing a level of content and biological relevance impossible with existing assays in monolayer cell culture in order to focus therapeutic targets and strategies before costly and tedious testing in animal models.
Using two different cell lines and as depicted in Figure 1, we adopt an ECM overlay method pioneered originally for 3D breast cancer models23, and developed in previous studies by us to model micrometastatic ovarian cancer19,24. This system leads to the formation of adherent multicellular 3D acini in approximately the same focal plane atop a laminin-rich ECM bed, implemented here in glass-bottom multiwell imaging plates for automated microscopy. The 3D nodules resultant from restoration of ECM signaling5,8, are heterogeneous in size24, in contrast to other 3D spheroid methods, such as rotary or hanging drop cultures10, in which cells are driven to aggregate into uniformly sized spheroids due to lack of an appropriate substrate to adhere to. Although the latter processes are also biologically relevant, it is the adherent tumour populations characteristic of advanced metastatic disease that are more likely to be managed with medical oncology, which are the focus of therapeutic evaluation herein. The heterogeneity in 3D structures formed via ECM overlay is validated here by endoscopic imaging ofin vivo tumours in orthotopic xenografts derived from the same cells (OVCAR-5).
Figure 1: A simplified schematic flow chart of imaging-based quantitative in situ treatment assessment (qVISTA) in 3D cell culture.
(This figure was prepared in Adobe Illustrator® software by MD Glidden, JP Celli and I Rizvi). A detailed breakdown of the image processing (Step 4) is provided in Supplemental Figure 1.
A critical component of the imaging-based strategy introduced here is the rational tradeoff of image-acquisition parameters for field of view, depth of field and optical resolution, and the development of image processing routines for appropriate removal of background, scaling of fluorescence signals from more than one channel and reliable segmentation of nodules. In order to obtain depth-resolved 3D structures for each nodule at sub-micron lateral resolution using a laser-scanning confocal system, it would require ~ 40 hours (at approximately 100 fields for each well with a 20× objective, times 1 minute/field for a coarse z-stack, times 24 wells) to image a single plate with the same coverage achieved in this study. Even if the resources were available to devote to such time-intensive image acquisition, not to mention the processing, the optical properties of the fluorophores would change during the required time frame for image acquisition, even with environmental controls to maintain culture viability during such extended imaging. The approach developed here, with a mind toward adaptation into high throughput screening, provides a rational balance of speed, requiring less than 30 minutes/plate, and statistical rigour, providing images of thousands of nodules in this time, as required for the high-content analysis developed in this study. These parameters can be further optimized for specific scenarios. For example, we obtain the same number of images in a 96 well plate as for a 24 well plate by acquiring only a single field from each well, rather than 4 stitched fields. This quadruples the number conditions assayed in a single run, at the expense of the number of nodules per condition, and therefore the ability to obtain statistical data sets for size-dependent response, Dfrac and other segmentation-dependent numerical readouts.
We envision that the system for high-content interrogation of therapeutic response in 3D cell culture could have widespread impact in multiple arenas from basic research to large scale drug development campaigns. As such, the treatment assessment methodology presented here does not require extraordinary optical instrumentation or computational resources, making it widely accessible to any research laboratory with an inverted fluorescence microscope and modestly equipped personal computer. And although we have focused here on cancer models, the methodology is broadly applicable to quantitative evaluation of other tissue models in regenerative medicine and tissue engineering. While this analysis toolbox could have impact in facilitating the implementation of in vitro 3D models in preclinical treatment evaluation in smaller academic laboratories, it could also be adopted as part of the screening pipeline in large pharma settings. With the implementation of appropriate temperature controls to handle basement membranes in current robotic liquid handling systems, our analyses could be used in ultra high-throughput screening. In addition to removing non-efficacious potential candidate drugs earlier in the pipeline, this approach could also yield the additional economic advantage of minimizing the use of costly time-intensive animal models through better estimates of dose range, sequence and schedule for combination regimens.
Microscope Uses AI to Find Cancer Cells More Efficiently
Scientists at the California NanoSystems Institute at UCLA have developed a new technique for identifying cancer cells in blood samples faster and more accurately than the current standard methods.
In one common approach to testing for cancer, doctors add biochemicals to blood samples. Those biochemicals attach biological “labels” to the cancer cells, and those labels enable instruments to detect and identify them. However, the biochemicals can damage the cells and render the samples unusable for future analyses.
There are other current techniques that don’t use labeling but can be inaccurate because they identify cancer cells based only on one physical characteristic.
The new technique images cells without destroying them and can identify 16 physical characteristics — including size, granularity and biomass — instead of just one. It combines two components that were invented at UCLA: a photonic time stretch microscope, which is capable of quickly imaging cells in blood samples, and a deep learning computer program that identifies cancer cells with over 95 percent accuracy.
Deep learning is a form of artificial intelligence that uses complex algorithms to extract meaning from data with the goal of achieving accurate decision making.
The study, which was published in the journal Nature Scientific Reports, was led by Barham Jalali, professor and Northrop-Grumman Optoelectronics Chair in electrical engineering; Claire Lifan Chen, a UCLA doctoral student; and Ata Mahjoubfar, a UCLA postdoctoral fellow.
Photonic time stretch was invented by Jalali, and he holds a patent for the technology. The new microscope is just one of many possible applications; it works by taking pictures of flowing blood cells using laser bursts in the way that a camera uses a flash. This process happens so quickly — in nanoseconds, or billionths of a second — that the images would be too weak to be detected and too fast to be digitized by normal instrumentation.
The new microscope overcomes those challenges using specially designed optics that boost the clarity of the images and simultaneously slow them enough to be detected and digitized at a rate of 36 million images per second. It then uses deep learning to distinguish cancer cells from healthy white blood cells.
“Each frame is slowed down in time and optically amplified so it can be digitized,” Mahjoubfar said. “This lets us perform fast cell imaging that the artificial intelligence component can distinguish.”
Normally, taking pictures in such minuscule periods of time would require intense illumination, which could destroy live cells. The UCLA approach also eliminates that problem.
“The photonic time stretch technique allows us to identify rogue cells in a short time with low-level illumination,” Chen said.
The researchers write in the paper that the system could lead to data-driven diagnoses by cells’ physical characteristics, which could allow quicker and earlier diagnoses of cancer, for example, and better understanding of the tumor-specific gene expression in cells, which could facilitate new treatments for disease. ….. see also http://www.nature.com/article-assets/npg/srep/2016/160315/srep21471/images_hires/m685/srep21471-f1.jpg
CRISPR/Cas9, Familial Amyloid Polyneuropathy (FAP) and Neurodegenerative Disease, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 2: CRISPR for Gene Editing and DNA Repair
CRISPR/Cas9, Familial Amyloid Polyneuropathy ( FAP) and Neurodegenerative Disease
Curator: Larry H. Bernstein, MD, FCAP
CRISPR/Cas9 and Targeted Genome Editing: A New Era in Molecular Biology
The development of efficient and reliable ways to make precise, targeted changes to the genome of living cells is a long-standing goal for biomedical researchers. Recently, a new tool based on a bacterial CRISPR-associated protein-9 nuclease (Cas9) from Streptococcus pyogenes has generated considerable excitement (1). This follows several attempts over the years to manipulate gene function, including homologous recombination (2) and RNA interference (RNAi) (3). RNAi, in particular, became a laboratory staple enabling inexpensive and high-throughput interrogation of gene function (4, 5), but it is hampered by providing only temporary inhibition of gene function and unpredictable off-target effects (6). Other recent approaches to targeted genome modification – zinc-finger nucleases [ZFNs, (7)] and transcription-activator like effector nucleases [TALENs (8)]– enable researchers to generate permanent mutations by introducing doublestranded breaks to activate repair pathways. These approaches are costly and time-consuming to engineer, limiting their widespread use, particularly for large scale, high-throughput studies.
The Biology of Cas9
The functions of CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) and CRISPR-associated (Cas) genes are essential in adaptive immunity in select bacteria and archaea, enabling the organisms to respond to and eliminate invading genetic material. These repeats were initially discovered in the 1980s in E. coli (9), but their function wasn’t confirmed until 2007 by Barrangou and colleagues, who demonstrated that S. thermophilus can acquire resistance against a bacteriophage by integrating a genome fragment of an infectious virus into its CRISPR locus (10).
Three types of CRISPR mechanisms have been identified, of which type II is the most studied. In this case, invading DNA from viruses or plasmids is cut into small fragments and incorporated into a CRISPR locus amidst a series of short repeats (around 20 bps). The loci are transcribed, and transcripts are then processed to generate small RNAs (crRNA – CRISPR RNA), which are used to guide effector endonucleases that target invading DNA based on sequence complementarity (Figure 1) (11).
Figure 1. Cas9 in vivo: Bacterial Adaptive Immunity
In the acquisition phase, foreign DNA is incorporated into the bacterial genome at the CRISPR loci. CRISPR loci is then transcribed and processed into crRNA during crRNA biogenesis. During interference, Cas9 endonuclease complexed with a crRNA and separate tracrRNA cleaves foreign DNA containing a 20-nucleotide crRNA complementary sequence adjacent to the PAM sequence. (Figure not drawn to scale.)
One Cas protein, Cas9 (also known as Csn1), has been shown, through knockdown and rescue experiments to be a key player in certain CRISPR mechanisms (specifically type II CRISPR systems). The type II CRISPR mechanism is unique compared to other CRISPR systems, as only one Cas protein (Cas9) is required for gene silencing (12). In type II systems, Cas9 participates in the processing of crRNAs (12), and is responsible for the destruction of the target DNA (11). Cas9’s function in both of these steps relies on the presence of two nuclease domains, a RuvC-like nuclease domain located at the amino terminus and a HNH-like nuclease domain that resides in the mid-region of the protein (13).
To achieve site-specific DNA recognition and cleavage, Cas9 must be complexed with both a crRNA and a separate trans-activating crRNA (tracrRNA or trRNA), that is partially complementary to the crRNA (11). The tracrRNA is required for crRNA maturation from a primary transcript encoding multiple pre-crRNAs. This occurs in the presence of RNase III and Cas9 (12).
During the destruction of target DNA, the HNH and RuvC-like nuclease domains cut both DNA strands, generating double-stranded breaks (DSBs) at sites defined by a 20-nucleotide target sequence within an associated crRNA transcript (11, 14). The HNH domain cleaves the complementary strand, while the RuvC domain cleaves the noncomplementary strand.
The double-stranded endonuclease activity of Cas9 also requires that a short conserved sequence, (2–5 nts) known as protospacer-associated motif (PAM), follows immediately 3´- of the crRNA complementary sequence (15). In fact, even fully complementary sequences are ignored by Cas9-RNA in the absence of a PAM sequence (16).
Cas9 and CRISPR as a New Tool in Molecular Biology
The simplicity of the type II CRISPR nuclease, with only three required components (Cas9 along with the crRNA and trRNA) makes this system amenable to adaptation for genome editing. This potential was realized in 2012 by the Doudna and Charpentier labs (11). Based on the type II CRISPR system described previously, the authors developed a simplified two-component system by combining trRNA and crRNA into a single synthetic single guide RNA (sgRNA). sgRNAprogrammed Cas9 was shown to be as effective as Cas9 programmed with separate trRNA and crRNA in guiding targeted gene alterations (Figure 2A).
To date, three different variants of the Cas9 nuclease have been adopted in genome-editing protocols. The first is wild-type Cas9, which can site-specifically cleave double-stranded DNA, resulting in the activation of the doublestrand break (DSB) repair machinery. DSBs can be repaired by the cellular Non-Homologous End Joining (NHEJ) pathway (17), resulting in insertions and/or deletions (indels) which disrupt the targeted locus. Alternatively, if a donor template with homology to the targeted locus is supplied, the DSB may be repaired by the homology-directed repair (HDR) pathway allowing for precise replacement mutations to be made (Figure 2A) (17, 18).
Cong and colleagues (1) took the Cas9 system a step further towards increased precision by developing a mutant form, known as Cas9D10A, with only nickase activity. This means it cleaves only one DNA strand, and does not activate NHEJ. Instead, when provided with a homologous repair template, DNA repairs are conducted via the high-fidelity HDR pathway only, resulting in reduced indel mutations (1, 11, 19). Cas9D10A is even more appealing in terms of target specificity when loci are targeted by paired Cas9 complexes designed to generate adjacent DNA nicks (20) (see further details about “paired nickases” in Figure 2B).
The third variant is a nuclease-deficient Cas9 (dCas9, Figure 2C) (21). Mutations H840A in the HNH domain and D10A in the RuvC domain inactivate cleavage activity, but do not prevent DNA binding (11, 22). Therefore, this variant can be used to sequence-specifically target any region of the genome without cleavage. Instead, by fusing with various effector domains, dCas9 can be used either as a gene silencing or activation tool (21, 23–26). Furthermore, it can be used as a visualization tool. For instance, Chen and colleagues used dCas9 fused to Enhanced Green Fluorescent Protein (EGFP) to visualize repetitive DNA sequences with a single sgRNA or nonrepetitive loci using multiple sgRNAs (27).
Wild-type Cas9 nuclease site specifically cleaves double-stranded DNA activating double-strand break repair machinery. In the absence of a homologous repair template non-homologous end joining can result in indels disrupting the target sequence. Alternatively, precise mutations and knock-ins can be made by providing a homologous repair template and exploiting the homology directed repair pathway.
B. Mutated Cas9 makes a site specific single-strand nick. Two sgRNA can be used to introduce a staggered double-stranded break which can then undergo homology directed repair.
C. Nuclease-deficient Cas9 can be fused with various effector domains allowing specific localization. For example, transcriptional activators, repressors, and fluorescent proteins.
Targeting Efficiency and Off-target Mutations
Targeting efficiency, or the percentage of desired mutation achieved, is one of the most important parameters by which to assess a genome-editing tool. The targeting efficiency of Cas9 compares favorably with more established methods, such as TALENs or ZFNs (8). For example, in human cells, custom-designed ZFNs and TALENs could only achieve efficiencies ranging from 1% to 50% (29–31). In contrast, the Cas9 system has been reported to have efficiencies up to >70% in zebrafish (32) and plants (33), and ranging from 2–5% in induced pluripotent stem cells (34). In addition, Zhou and colleagues were able to improve genome targeting up to 78% in one-cell mouse embryos, and achieved effective germline transmission through the use of dual sgRNAs to simultaneously target an individual gene (35).
A widely used method to identify mutations is the T7 Endonuclease I mutation detection assay (36, 37) (Figure 3). This assay detects heteroduplex DNA that results from the annealing of a DNA strand, including desired mutations, with a wildtype DNA strand (37).
Figure 3. T7 Endonuclease I Targeting Efficiency Assay
Genomic DNA is amplified with primers bracketing the modified locus. PCR products are then denatured and re-annealed yielding 3 possible structures. Duplexes containing a mismatch are digested by T7 Endonuclease I. The DNA is then electrophoretically separated and fragment analysis is used to calculate targeting efficiency.
Another important parameter is the incidence of off-target mutations. Such mutations are likely to appear in sites that have differences of only a few nucleotides compared to the original sequence, as long as they are adjacent to a PAM sequence. This occurs as Cas9 can tolerate up to 5 base mismatches within the protospacer region (36) or a single base difference in the PAM sequence (38). Off-target mutations are generally more difficult to detect, requiring whole-genome sequencing to rule them out completely.
Recent improvements to the CRISPR system for reducing off-target mutations have been made through the use of truncated gRNA (truncated within the crRNA-derived sequence) or by adding two extra guanine (G) nucleotides to the 5´ end (28, 37). Another way researchers have attempted to minimize off-target effects is with the use of “paired nickases” (20). This strategy uses D10A Cas9 and two sgRNAs complementary to the adjacent area on opposite strands of the target site (Figure 2B). While this induces DSBs in the target DNA, it is expected to create only single nicks in off-target locations and, therefore, result in minimal off-target mutations.
By leveraging computation to reduce off-target mutations, several groups have developed webbased tools to facilitate the identification of potential CRISPR target sites and assess their potential for off-target cleavage. Examples include the CRISPR Design Tool (38) and the ZiFiT Targeter, Version 4.2 (39, 40).
Applications as a Genome-editing and Genome Targeting Tool
Following its initial demonstration in 2012 (9), the CRISPR/Cas9 system has been widely adopted. This has already been successfully used to target important genes in many cell lines and organisms, including human (34), bacteria (41), zebrafish (32), C. elegans (42), plants (34), Xenopus tropicalis (43), yeast (44), Drosophila (45), monkeys (46), rabbits (47), pigs (42), rats (48) and mice (49). Several groups have now taken advantage of this method to introduce single point mutations (deletions or insertions) in a particular target gene, via a single gRNA (14, 21, 29). Using a pair of gRNA-directed Cas9 nucleases instead, it is also possible to induce large deletions or genomic rearrangements, such as inversions or translocations (50). A recent exciting development is the use of the dCas9 version of the CRISPR/Cas9 system to target protein domains for transcriptional regulation (26, 51, 52), epigenetic modification (25), and microscopic visualization of specific genome loci (27).
The CRISPR/Cas9 system requires only the redesign of the crRNA to change target specificity. This contrasts with other genome editing tools, including zinc finger and TALENs, where redesign of the protein-DNA interface is required. Furthermore, CRISPR/Cas9 enables rapid genome-wide interrogation of gene function by generating large gRNA libraries (51, 53) for genomic screening.
The Future of CRISPR/Cas9
The rapid progress in developing Cas9 into a set of tools for cell and molecular biology research has been remarkable, likely due to the simplicity, high efficiency and versatility of the system. Of the designer nuclease systems currently available for precision genome engineering, the CRISPR/Cas system is by far the most user friendly. It is now also clear that Cas9’s potential reaches beyond DNA cleavage, and its usefulness for genome locus-specific recruitment of proteins will likely only be limited by our imagination.
Scientists urge caution in using new CRISPR technology to treat human genetic disease
The bacterial enzyme Cas9 is the engine of RNA-programmed genome engineering in human cells. (Graphic by Jennifer Doudna/UC Berkeley)
A group of 18 scientists and ethicists today warned that a revolutionary new tool to cut and splice DNA should be used cautiously when attempting to fix human genetic disease, and strongly discouraged any attempts at making changes to the human genome that could be passed on to offspring.
Among the authors of this warning is Jennifer Doudna, the co-inventor of the technology, called CRISPR-Cas9, which is driving a new interest in gene therapy, or “genome engineering.” She and colleagues co-authored a perspective piece that appears in the March 20 issue of Science, based on discussions at a meeting that took place in Napa on Jan. 24. The same issue of Science features a collection of recent research papers, commentary and news articles on CRISPR and its implications. …..
A prudent path forward for genomic engineering and germline gene modification
Scientists today are changing DNA sequences to correct genetic defects in animals as well as cultured tissues generated from stem cells, strategies that could eventually be used to treat human disease. The technology can also be used to engineer animals with genetic diseases mimicking human disease, which could lead to new insights into previously enigmatic disorders.
The CRISPR-Cas9 tool is still being refined to ensure that genetic changes are precisely targeted, Doudna said. Nevertheless, the authors met “… to initiate an informed discussion of the uses of genome engineering technology, and to identify proactively those areas where current action is essential to prepare for future developments. We recommend taking immediate steps toward ensuring that the application of genome engineering technology is performed safely and ethically.”
Amyloid CRISPR Plasmids and si/shRNA Gene Silencers
Santa Cruz Biotechnology, Inc. offers a broad range of gene silencers in the form of siRNAs, shRNA Plasmids and shRNA Lentiviral Particles as well as CRISPR/Cas9 Knockout and CRISPR Double Nickase plasmids. Amyloid gene silencers are available as Amyloid siRNA, Amyloid shRNA Plasmid, Amyloid shRNA Lentiviral Particles and Amyloid CRISPR/Cas9 Knockout plasmids. Amyloid CRISPR/dCas9 Activation Plasmids and CRISPR Lenti Activation Systems for gene activation are also available. Gene silencers and activators are useful for gene studies in combination with antibodies used for protein detection. Amyloid CRISPR Knockout, HDR and Nickase Knockout Plasmids
CRISPR-Cas9-Based Knockout of the Prion Protein and Its Effect on the Proteome
The molecular function of the cellular prion protein (PrPC) and the mechanism by which it may contribute to neurotoxicity in prion diseases and Alzheimer’s disease are only partially understood. Mouse neuroblastoma Neuro2a cells and, more recently, C2C12 myocytes and myotubes have emerged as popular models for investigating the cellular biology of PrP. Mouse epithelial NMuMG cells might become attractive models for studying the possible involvement of PrP in a morphogenetic program underlying epithelial-to-mesenchymal transitions. Here we describe the generation of PrP knockout clones from these cell lines using CRISPR-Cas9 knockout technology. More specifically, knockout clones were generated with two separate guide RNAs targeting recognition sites on opposite strands within the first hundred nucleotides of the Prnp coding sequence. Several PrP knockout clones were isolated and genomic insertions and deletions near the CRISPR-target sites were characterized. Subsequently, deep quantitative global proteome analyses that recorded the relative abundance of>3000 proteins (data deposited to ProteomeXchange Consortium) were undertaken to begin to characterize the molecular consequences of PrP deficiency. The levels of ∼120 proteins were shown to reproducibly correlate with the presence or absence of PrP, with most of these proteins belonging to extracellular components, cell junctions or the cytoskeleton.
Recent advances in genome engineering technologies based on the CRISPR-associated RNA-guided endonuclease Cas9 are enabling the systematic interrogation of mammalian genome function. Analogous to the search function in modern word processors, Cas9 can be guided to specific locations within complex genomes by a short RNA search string. Using this system, DNA sequences within the endogenous genome and their functional outputs are now easily edited or modulated in virtually any organism of choice. Cas9-mediated genetic perturbation is simple and scalable, empowering researchers to elucidate the functional organization of the genome at the systems level and establish causal linkages between genetic variations and biological phenotypes. In this Review, we describe the development and applications of Cas9 for a variety of research or translational applications while highlighting challenges as well as future directions. Derived from a remarkable microbial defense system, Cas9 is driving innovative applications from basic biology to biotechnology and medicine.
The development of recombinant DNA technology in the 1970s marked the beginning of a new era for biology. For the first time, molecular biologists gained the ability to manipulate DNA molecules, making it possible to study genes and harness them to develop novel medicine and biotechnology. Recent advances in genome engineering technologies are sparking a new revolution in biological research. Rather than studying DNA taken out of the context of the genome, researchers can now directly edit or modulate the function of DNA sequences in their endogenous context in virtually any organism of choice, enabling them to elucidate the functional organization of the genome at the systems level, as well as identify causal genetic variations.
Broadly speaking, genome engineering refers to the process of making targeted modifications to the genome, its contexts (e.g., epigenetic marks), or its outputs (e.g., transcripts). The ability to do so easily and efficiently in eukaryotic and especially mammalian cells holds immense promise to transform basic science, biotechnology, and medicine (Figure 1).
For life sciences research, technologies that can delete, insert, and modify the DNA sequences of cells or organisms enable dissecting the function of specific genes and regulatory elements. Multiplexed editing could further allow the interrogation of gene or protein networks at a larger scale. Similarly, manipulating transcriptional regulation or chromatin states at particular loci can reveal how genetic material is organized and utilized within a cell, illuminating relationships between the architecture of the genome and its functions. In biotechnology, precise manipulation of genetic building blocks and regulatory machinery also facilitates the reverse engineering or reconstruction of useful biological systems, for example, by enhancing biofuel production pathways in industrially relevant organisms or by creating infection-resistant crops. Additionally, genome engineering is stimulating a new generation of drug development processes and medical therapeutics. Perturbation of multiple genes simultaneously could model the additive effects that underlie complex polygenic disorders, leading to new drug targets, while genome editing could directly correct harmful mutations in the context of human gene therapy (Tebas et al., 2014).
Eukaryotic genomes contain billions of DNA bases and are difficult to manipulate. One of the breakthroughs in genome manipulation has been the development of gene targeting by homologous recombination (HR), which integrates exogenous repair templates that contain sequence homology to the donor site (Figure 2A) (Capecchi, 1989). HR-mediated targeting has facilitated the generation of knockin and knockout animal models via manipulation of germline competent stem cells, dramatically advancing many areas of biological research. However, although HR-mediated gene targeting produces highly precise alterations, the desired recombination events occur extremely infrequently (1 in 106–109 cells) (Capecchi, 1989), presenting enormous challenges for large-scale applications of gene-targeting experiments.
Genome Editing Technologies Exploit Endogenous DNA Repair Machinery
To overcome these challenges, a series of programmable nuclease-based genome editing technologies have been developed in recent years, enabling targeted and efficient modification of a variety of eukaryotic and particularly mammalian species. Of the current generation of genome editing technologies, the most rapidly developing is the class of RNA-guided endonucleases known as Cas9 from the microbial adaptive immune system CRISPR (clustered regularly interspaced short palindromic repeats), which can be easily targeted to virtually any genomic location of choice by a short RNA guide. Here, we review the development and applications of the CRISPR-associated endonuclease Cas9 as a platform technology for achieving targeted perturbation of endogenous genomic elements and also discuss challenges and future avenues for innovation. ……
Figure 4Natural Mechanisms of Microbial CRISPR Systems in Adaptive Immunity
…… A key turning point came in 2005, when systematic analysis of the spacer sequences separating the individual direct repeats suggested their extrachromosomal and phage-associated origins (Mojica et al., 2005; Pourcel et al., 2005; Bolotin et al., 2005). This insight was tremendously exciting, especially given previous studies showing that CRISPR loci are transcribed (Tang et al., 2002) and that viruses are unable to infect archaeal cells carrying spacers corresponding to their own genomes (Mojica et al., 2005). Together, these findings led to the speculation that CRISPR arrays serve as an immune memory and defense mechanism, and individual spacers facilitate defense against bacteriophage infection by exploiting Watson-Crick base-pairing between nucleic acids (Mojica et al., 2005; Pourcel et al., 2005). Despite these compelling realizations that CRISPR loci might be involved in microbial immunity, the specific mechanism of how the spacers act to mediate viral defense remained a challenging puzzle. Several hypotheses were raised, including thoughts that CRISPR spacers act as small RNA guides to degrade viral transcripts in a RNAi-like mechanism (Makarova et al., 2006) or that CRISPR spacers direct Cas enzymes to cleave viral DNA at spacer-matching regions (Bolotin et al., 2005). …..
As the pace of CRISPR research accelerated, researchers quickly unraveled many details of each type of CRISPR system (Figure 4). Building on an earlier speculation that protospacer adjacent motifs (PAMs) may direct the type II Cas9 nuclease to cleave DNA (Bolotin et al., 2005), Moineau and colleagues highlighted the importance of PAM sequences by demonstrating that PAM mutations in phage genomes circumvented CRISPR interference (Deveau et al., 2008). Additionally, for types I and II, the lack of PAM within the direct repeat sequence within the CRISPR array prevents self-targeting by the CRISPR system. In type III systems, however, mismatches between the 5′ end of the crRNA and the DNA target are required for plasmid interference (Marraffini and Sontheimer, 2010). …..
In 2013, a pair of studies simultaneously showed how to successfully engineer type II CRISPR systems from Streptococcus thermophilus (Cong et al., 2013) andStreptococcus pyogenes (Cong et al., 2013; Mali et al., 2013a) to accomplish genome editing in mammalian cells. Heterologous expression of mature crRNA-tracrRNA hybrids (Cong et al., 2013) as well as sgRNAs (Cong et al., 2013; Mali et al., 2013a) directs Cas9 cleavage within the mammalian cellular genome to stimulate NHEJ or HDR-mediated genome editing. Multiple guide RNAs can also be used to target several genes at once. Since these initial studies, Cas9 has been used by thousands of laboratories for genome editing applications in a variety of experimental model systems (Sander and Joung, 2014). ……
The majority of CRISPR-based technology development has focused on the signature Cas9 nuclease from type II CRISPR systems. However, there remains a wide diversity of CRISPR types and functions. Cas RAMP module (Cmr) proteins identified in Pyrococcus furiosus and Sulfolobus solfataricus (Hale et al., 2012) constitute an RNA-targeting CRISPR immune system, forming a complex guided by small CRISPR RNAs that target and cleave complementary RNA instead of DNA. Cmr protein homologs can be found throughout bacteria and archaea, typically relying on a 5′ site tag sequence on the target-matching crRNA for Cmr-directed cleavage.
Unlike RNAi, which is targeted largely by a 6 nt seed region and to a lesser extent 13 other bases, Cmr crRNAs contain 30–40 nt of target complementarity. Cmr-CRISPR technologies for RNA targeting are thus a promising target for orthogonal engineering and minimal off-target modification. Although the modularity of Cmr systems for RNA-targeting in mammalian cells remains to be investigated, Cmr complexes native to P. furiosus have already been engineered to target novel RNA substrates (Hale et al., 2009, 2012). ……
Although Cas9 has already been widely used as a research tool, a particularly exciting future direction is the development of Cas9 as a therapeutic technology for treating genetic disorders. For a monogenic recessive disorder due to loss-of-function mutations (such as cystic fibrosis, sickle-cell anemia, or Duchenne muscular dystrophy), Cas9 may be used to correct the causative mutation. This has many advantages over traditional methods of gene augmentation that deliver functional genetic copies via viral vector-mediated overexpression—particularly that the newly functional gene is expressed in its natural context. For dominant-negative disorders in which the affected gene is haplosufficient (such as transthyretin-related hereditary amyloidosis or dominant forms of retinitis pigmentosum), it may also be possible to use NHEJ to inactivate the mutated allele to achieve therapeutic benefit. For allele-specific targeting, one could design guide RNAs capable of distinguishing between single-nucleotide polymorphism (SNP) variations in the target gene, such as when the SNP falls within the PAM sequence.
CRISPR/Cas9: a powerful genetic engineering tool for establishing large animal models of neurodegenerative diseases
Zhuchi Tu, Weili Yang, Sen Yan, Xiangyu Guo and Xiao-Jiang Li
Animal models are extremely valuable to help us understand the pathogenesis of neurodegenerative disorders and to find treatments for them. Since large animals are more like humans than rodents, they make good models to identify the important pathological events that may be seen in humans but not in small animals; large animals are also very important for validating effective treatments or confirming therapeutic targets. Due to the lack of embryonic stem cell lines from large animals, it has been difficult to use traditional gene targeting technology to establish large animal models of neurodegenerative diseases. Recently, CRISPR/Cas9 was used successfully to genetically modify genomes in various species. Here we discuss the use of CRISPR/Cas9 technology to establish large animal models that can more faithfully mimic human neurodegenerative diseases.
Neurodegenerative diseases — Alzheimer’s disease(AD),Parkinson’s disease(PD), amyotrophic lateral sclerosis (ALS), Huntington’s disease (HD), and frontotemporal dementia (FTD) — are characterized by age-dependent and selective neurodegeneration. As the life expectancy of humans lengthens, there is a greater prevalence of these neurodegenerative diseases; however, the pathogenesis of most of these neurodegenerative diseases remain unclear, and we lack effective treatments for these important brain disorders.
CRISPR/Cas9, Non-human primates, Neurodegenerative diseases, Animal model
There are a number of excellent reviews covering different types of neurodegenerative diseases and their genetic mouse models [8–12]. Investigations of different mouse models of neurodegenerative diseases have revealed a common pathology shared by these diseases. First, the development of neuropathology and neurological symptoms in genetic mouse models of neurodegenerative diseases is age dependent and progressive. Second, all the mouse models show an accumulation of misfolded or aggregated proteins resulting from the expression of mutant genes. Third, despite the widespread expression of mutant proteins throughout the body and brain, neuronal function appears to be selectively or preferentially affected. All these facts indicate that mouse models of neurodegenerative diseases recapitulate important pathologic features also seen in patients with neurodegenerative diseases.
However, it seems that mouse models can not recapitulate the full range of neuropathology seen in patients with neurodegenerative diseases. Overt neurodegeneration, which is the most important pathological feature in patient brains, is absent in genetic rodent models of AD, PD, and HD. Many rodent models that express transgenic mutant proteins under the control of different promoters do not replicate overt neurodegeneration, which is likely due to their short life spans and the different aging processes of small animals. Also important are the remarkable differences in brain development between rodents and primates. For example, the mouse brain takes 21 days to fully develop, whereas the formation of primate brains requires more than 150 days [13]. The rapid development of the brain in rodents may render neuronal cells resistant to misfolded protein-mediated neurodegeneration. Another difficulty in using rodent models is how to analyze cognitive and emotional abnormalities, which are the early symptoms of most neurodegenerative diseases in humans. Differences in neuronal circuitry, anatomy, and physiology between rodent and primate brains may also account for the behavioral differences between rodent and primate models.
Mitochondrial dynamics–fusion, fission, movement, and mitophagy–in neurodegenerative diseases
Neurons are metabolically active cells with high energy demands at locations distant from the cell body. As a result, these cells are particularly dependent on mitochondrial function, as reflected by the observation that diseases of mitochondrial dysfunction often have a neurodegenerative component. Recent discoveries have highlighted that neurons are reliant particularly on the dynamic properties of mitochondria. Mitochondria are dynamic organelles by several criteria. They engage in repeated cycles of fusion and fission, which serve to intermix the lipids and contents of a population of mitochondria. In addition, mitochondria are actively recruited to subcellular sites, such as the axonal and dendritic processes of neurons. Finally, the quality of a mitochondrial population is maintained through mitophagy, a form of autophagy in which defective mitochondria are selectively degraded. We review the general features of mitochondrial dynamics, incorporating recent findings on mitochondrial fusion, fission, transport and mitophagy. Defects in these key features are associated with neurodegenerative disease. Charcot-Marie-Tooth type 2A, a peripheral neuropathy, and dominant optic atrophy, an inherited optic neuropathy, result from a primary deficiency of mitochondrial fusion. Moreover, several major neurodegenerative diseases—including Parkinson’s, Alzheimer’s and Huntington’s disease—involve disruption of mitochondrial dynamics. Remarkably, in several disease models, the manipulation of mitochondrial fusion or fission can partially rescue disease phenotypes. We review how mitochondrial dynamics is altered in these neurodegenerative diseases and discuss the reciprocal interactions between mitochondrial fusion, fission, transport and mitophagy.
Applications of CRISPR–Cas systems in Neuroscience
Genome-editing tools, and in particular those based on CRISPR–Cas (clustered regularly interspaced short palindromic repeat (CRISPR)–CRISPR-associated protein) systems, are accelerating the pace of biological research and enabling targeted genetic interrogation in almost any organism and cell type. These tools have opened the door to the development of new model systems for studying the complexity of the nervous system, including animal models and stem cell-derived in vitro models. Precise and efficient gene editing using CRISPR–Cas systems has the potential to advance both basic and translational neuroscience research.
Cellular neuroscience, DNA recombination, Genetic engineering, Molecular neuroscience
Figure 3: In vitro applications of Cas9 in human iPSCs.close
a | Evaluation of disease candidate genes from large-population genome-wide association studies (GWASs). Human primary cells, such as neurons, are not easily available and are difficult to expand in culture. By contrast, induced pluripo…
The development of the CRISPR/Cas9 system has made gene editing a relatively simple task. While CRISPR and other gene editing technologies stand to revolutionize biomedical research and offers many promising therapeutic avenues (such as in the treatment of HIV), a great deal of debate exists over whether CRISPR should be used to modify human embryos. As I discussed in my previous Insight article, we lack enough fundamental biological knowledge to enhance many traits like height or intelligence, so we are not near a future with genetically-enhanced super babies. However, scientists have identified a few rare genetic variants that protect against disease. One such protective variant is a mutation in the APP gene that protects against Alzheimer’s disease and cognitive decline in old age. If we can perfect gene editing technologies, is this mutation one that we should be regularly introducing into embryos? In this article, I explore the potential for using gene editing as a way to prevent Alzheimer’s disease in future generations. Alzheimer’s Disease: Medicine’s Greatest Challenge in the 21st Century Can gene editing be the missing piece in the battle against Alzheimer’s? (Source: bostonbiotech.org) I chose to assess the benefit of germline gene editing in the context of Alzheimer’s disease because this disease is one of the biggest challenges medicine faces in the 21st century. Alzheimer’s disease is a chronic neurodegenerative disease responsible for the majority of the cases of dementia in the elderly. The disease symptoms begins with short term memory loss and causes more severe symptoms – problems with language, disorientation, mood swings, behavioral issues – as it progresses, eventually leading to the loss of bodily functions and death. Because of the dementia the disease causes, Alzheimer’s patients require a great deal of care, and the world spends ~1% of its total GDP on caring for those with Alzheimer’s and related disorders. Because the prevalence of the disease increases with age, the situation will worsen as life expectancies around the globe increase: worldwide cases of Alzheimer’s are expected to grow from 35 million today to over 115 million by 2050.
Despite much research, the exact causes of Alzheimer’s disease remains poorly understood. The disease seems to be related to the accumulation of plaques made of amyloid-β peptides that form on the outside of neurons, as well as the formation of tangles of the protein tau inside of neurons. Although many efforts have been made to target amyloid-β or the enzymes involved in its formation, we have so far been unsuccessful at finding any treatment that stops the disease or reverses its progress. Some researchers believe that most attempts at treating Alzheimer’s have failed because, by the time a patient shows symptoms, the disease has already progressed past the point of no return.
While research towards a cure continues, researchers have sought effective ways to prevent Alzheimer’s disease. Although some studies show that mental and physical exercise may lower ones risk of Alzheimer’s disease, approximately 60-80% of the risk for Alzheimer’s disease appears to be genetic. Thus, if we’re serious about prevention, we may have to act at the genetic level. And because the brain is difficult to access surgically for gene therapy in adults, this means using gene editing on embryos.
With the latest CRISPR/Cas9 advance, the exhortation “turn on, tune in, drop out” comes to mind. The CRISPR/Cas9 gene-editing system was already a well-known means of “tuning in” (inserting new genes) and “dropping out” (knocking out genes). But when it came to “turning on” genes, CRISPR/Cas9 had little potency. That is, it had demonstrated only limited success as a way to activate specific genes.
A new CRISPR/Cas9 approach, however, appears capable of activating genes more effectively than older approaches. The new approach may allow scientists to more easily determine the function of individual genes, according to Feng Zhang, Ph.D., a researcher at MIT and the Broad Institute. Dr. Zhang and colleagues report that the new approach permits multiplexed gene activation and rapid, large-scale studies of gene function.
The new technique was introduced in the December 10 online edition of Nature, in an article entitled, “Genome-scale transcriptional activation by an engineered CRISPR-Cas9 complex.” The article describes how Dr. Zhang, along with the University of Tokyo’s Osamu Nureki, Ph.D., and Hiroshi Nishimasu, Ph.D., overhauled the CRISPR/Cas9 system. The research team based their work on their analysis (published earlier this year) of the structure formed when Cas9 binds to the guide RNA and its target DNA. Specifically, the team used the structure’s 3D shape to rationally improve the system.
In previous efforts to revamp CRISPR/Cas9 for gene activation purposes, scientists had tried to attach the activation domains to either end of the Cas9 protein, with limited success. From their structural studies, the MIT team realized that two small loops of the RNA guide poke out from the Cas9 complex and could be better points of attachment because they allow the activation domains to have more flexibility in recruiting transcription machinery.
Using their revamped system, the researchers activated about a dozen genes that had proven difficult or impossible to turn on using the previous generation of Cas9 activators. Each gene showed at least a twofold boost in transcription, and for many genes, the researchers found multiple orders of magnitude increase in activation.
After investigating single-guide RNA targeting rules for effective transcriptional activation, demonstrating multiplexed activation of 10 genes simultaneously, and upregulating long intergenic noncoding RNA transcripts, the research team decided to undertake a large-scale screen. This screen was designed to identify genes that confer resistance to a melanoma drug called PLX-4720.
“We … synthesized a library consisting of 70,290 guides targeting all human RefSeq coding isoforms to screen for genes that, upon activation, confer resistance to a BRAF inhibitor,” wrote the authors of the Nature paper. “The top hits included genes previously shown to be able to confer resistance, and novel candidates were validated using individual [single-guide RNA] and complementary DNA overexpression.”
A gene signature based on the top screening hits, the authors added, correlated with a gene expression signature of BRAF inhibitor resistance in cell lines and patient-derived samples. It was also suggested that large-scale screens such as the one demonstrated in the current study could help researchers discover new cancer drugs that prevent tumors from becoming resistant.
Familial amyloid polyneuropathy type I is an autosomal dominant disorder caused by mutations in the transthyretin (TTR ) gene; however, carriers of the same mutation exhibit variability in penetrance and clinical expression. We analyzed alleles of candidate genes encoding non-fibrillar components of TTR amyloid deposits and a molecule metabolically interacting with TTR [retinol-binding protein (RBP)], for possible associations with age of disease onset and/or susceptibility in a Portuguese population sample with the TTR V30M mutation and unrelated controls. We show that the V30M carriers represent a distinct subset of the Portuguese population. Estimates of genetic distance indicated that the controls and the classical onset group were furthest apart, whereas the late-onset group appeared to differ from both. Importantly, the data also indicate that genetic interactions among the multiple loci evaluated, rather than single-locus effects, are more likely to determine differences in the age of disease onset. Multifactor dimensionality reduction indicated that the best genetic model for classical onset group versus controls involved the APCS gene, whereas for late-onset cases, one APCS variant (APCSv1) and two RBP variants (RBPv1 and RBPv2) are involved. Thus, although the TTR V30M mutation is required for the disease in Portuguese patients, different genetic factors may govern the age of onset, as well as the occurrence of anticipation.
Autosomal dominant disorders may vary in expression even within a given kindred. The basis of this variability is uncertain and can be attributed to epigenetic factors, environment or epistasis. We have studied familial amyloid polyneuropathy (FAP), an autosomal dominant disorder characterized by peripheral sensorimotor and autonomic neuropathy. It exhibits variation in cardiac, renal, gastrointestinal and ocular involvement, as well as age of onset. Over 80 missense mutations in the transthyretin gene (TTR ) result in autosomal dominant disease http://www.ibmc.up.pt/~mjsaraiv/ttrmut.html). The presence of deposits consisting entirely of wild-type TTR molecules in the hearts of 10– 25% of individuals over age 80 reveals its inherent in vivo amyloidogenic potential (1).
FAP was initially described in Portuguese (2) where, until recently, the TTR V30M has been the only pathogenic mutation associated with the disease (3,4). Later reports identified the same mutation in Swedish and Japanese families (5,6). The disorder has since been recognized in other European countries and in North American kindreds in association with V30M, as well as other mutations (7).
TTR V30M produces disease in only 5–10% of Swedish carriers of the allele (8), a much lower degree of penetrance than that seen in Portuguese (80%) (9) or in Japanese with the same mutation. The actual penetrance in Japanese carriers has not been formally established, but appears to resemble that seen in Portuguese. Portuguese and Japanese carriers show considerable variation in the age of clinical onset (10,11). In both populations, the first symptoms had originally been described as typically occurring before age 40 (so-called ‘classical’ or early-onset); however, in recent years, more individuals developing symptoms late in life have been identified (11,12). Hence, present data indicate that the distribution of the age of onset in Portuguese is continuous, but asymmetric with a mean around age 35 and a long tail into the older age group (Fig. 1) (9,13). Further, DNA testing in Portugal has identified asymptomatic carriers over age 70 belonging to a subset of very late-onset kindreds in whose descendants genetic anticipation is frequent. The molecular basis of anticipation in FAP, which is not mediated by trinucleotide repeat expansions in the TTR or any other gene (14), remains elusive.
Variation in penetrance, age of onset and clinical features are hallmarks of many autosomal dominant disorders including the human TTR amyloidoses (7). Some of these clearly reflect specific biological effects of a particular mutation or a class of mutants. However, when such phenotypic variability is seen with a single mutation in the gene encoding the same protein, it suggests an effect of modifying genetic loci and/or environmental factors contributing differentially to the course of disease. We have chosen to examine age of onset as an example of a discrete phenotypic variation in the presence of the particular autosomal dominant disease-associated mutation TTR V30M. Although the role of environmental factors cannot be excluded, the existence of modifier genes involved in TTR amyloidogenesis is an attractive hypothesis to explain the phenotypic variability in FAP. ….
ATTR (TTR amyloid), like all amyloid deposits, contains several molecular components, in addition to the quantitatively dominant fibril-forming amyloid protein, including heparan sulfate proteoglycan 2 (HSPG2 or perlecan), SAP, a plasma glycoprotein of the pentraxin family (encoded by the APCS gene) that undergoes specific calcium-dependent binding to all types of amyloid fibrils, and apolipoprotein E (ApoE), also found in all amyloid deposits (15). The ApoE4 isoform is associated with an increased frequency and earlier onset of Alzheimer’s disease (Ab), the most common form of brain amyloid, whereas the ApoE2 isoform appears to be protective (16). ApoE variants could exert a similar modulatory effect in the onset of FAP, although early studies on a limited number of patients suggested this was not the case (17).
In at least one instance of senile systemic amyloidosis, small amounts of AA-related material were found in TTR deposits (18). These could reflect either a passive co-aggregation or a contributory involvement of protein AA, encoded by the serum amyloid A (SAA ) genes and the main component of secondary (reactive) amyloid fibrils, in the formation of ATTR.
Retinol-binding protein (RBP), the serum carrier of vitamin A, circulates in plasma bound to TTR. Vitamin A-loaded RBP and L-thyroxine, the two natural ligands of TTR, can act alone or synergistically to inhibit the rate and extent of TTR fibrillogenesis in vitro, suggesting that RBP may influence the course of FAP pathology in vivo (19). We have analyzed coding and non-coding sequence polymorphisms in the RBP4 (serum RBP, 10q24), HSPG2 (1p36.1), APCS (1q22), APOE (19q13.2), SAA1 and SAA2 (11p15.1) genes with the goal of identifying chromosomes carrying common and functionally significant variants. At the time these studies were performed, the full human genome sequence was not completed and systematic singlenucleotide polymorphism (SNP) analyses were not available for any of the suspected candidate genes. We identified new SNPs in APCS and RBP4 and utilized polymorphisms in SAA, HSPG2 and APOE that had already been characterized and shown to have potential pathophysiologic significance in other disorders (16,20–22). The genotyping data were analyzed for association with the presence of the V30M amyloidogenic allele (FAP patients versus controls) and with the age of onset (classical- versus late-onset patients). Multilocus analyses were also performed to examine the effects of simultaneous contributions of the six loci for determining the onset of the first symptoms. …..
The potential for different underlying models for classical and late onset is supported by the MDR analysis, which produces two distinct models when comparing each class with the controls. One could view the two onset classes as unique diseases. If this is the case, then the failure to detect a single predictive genetic model is consistent with two related, but different, diseases. This is exactly what would be expected in such a case of genetic heterogeneity (28). Using this approach, a major gene effect can be viewed as a necessary, but not sufficient, condition to explain the course of the disease. Analyzing the cases but omitting from the analysis of phenotype the necessary allele, in this case TTR V30M, can then reveal a variety of important modifiers that are distinct between the phenotypes.
The significant comparisons obtained in our study cohort indicate that the combined effects mainly result from two and three-locus interactions involving all loci except SAA1 and SAA2 for susceptibility to disease. A considerable number of four-site combinations modulate the age of onset with SAA1 appearing in a majority of significant combinations in late-onset disease, perhaps indicating a greater role of the SAA variants in the age of onset of FAP.
The correlation between genotype and phenotype in socalled simple Mendelian disorders is often incomplete, as only a subset of all mutations can reliably predict specific phenotypes (34). This is because non-allelic genetic variations and/or environmental influences underlie these disorders whose phenotypes behave as complex traits. A few examples include the identification of the role of homozygozity for the SAA1.1 allele in conferring the genetic susceptibility to renal amyloidosis in FMF (20) and the association of an insertion/deletion polymorphism in the ACE gene with disease severity in familial hypertrophic cardiomyopathy (35). In these disorders, the phenotypes arise from mutations in MEFV and b-MHC, but are modulated by independently inherited genetic variation. In this report, we show that interactions among multiple genes, whose products are confirmed or putative constituents of ATTR deposits, or metabolically interact with TTR, modulate the onset of the first symptoms and predispose individuals to disease in the presence of the V30M mutation in TTR. The exact nature of the effects identified here requires further study with potential application in the development of genetic screening with prognostic value pertaining to the onset of disease in the TTR V30M carriers.
If the effects of additional single or interacting genes dictate the heterogeneity of phenotype, as reflected in variability of onset and clinical expression (with the same TTR mutation), the products encoded by alleles at such loci could contribute to the process of wild-type TTR deposition in elderly individuals without a mutation (senile systemic amyloidosis), a phenomenon not readily recognized as having a genetic basis because of the insensitivity of family history in the elderly.
Safety and Efficacy of RNAi Therapy for Transthyretin Amyloidosis
Transthyretin amyloidosis is caused by the deposition of hepatocyte-derived transthyretin amyloid in peripheral nerves and the heart. A therapeutic approach mediated by RNA interference (RNAi) could reduce the production of transthyretin.
Methods We identified a potent antitransthyretin small interfering RNA, which was encapsulated in two distinct first- and second-generation formulations of lipid nanoparticles, generating ALN-TTR01 and ALN-TTR02, respectively. Each formulation was studied in a single-dose, placebo-controlled phase 1 trial to assess safety and effect on transthyretin levels. We first evaluated ALN-TTR01 (at doses of 0.01 to 1.0 mg per kilogram of body weight) in 32 patients with transthyretin amyloidosis and then evaluated ALN-TTR02 (at doses of 0.01 to 0.5 mg per kilogram) in 17 healthy volunteers.
Results Rapid, dose-dependent, and durable lowering of transthyretin levels was observed in the two trials. At a dose of 1.0 mg per kilogram, ALN-TTR01 suppressed transthyretin, with a mean reduction at day 7 of 38%, as compared with placebo (P=0.01); levels of mutant and nonmutant forms of transthyretin were lowered to a similar extent. For ALN-TTR02, the mean reductions in transthyretin levels at doses of 0.15 to 0.3 mg per kilogram ranged from 82.3 to 86.8%, with reductions of 56.6 to 67.1% at 28 days (P<0.001 for all comparisons). These reductions were shown to be RNAi mediated. Mild-to-moderate infusion-related reactions occurred in 20.8% and 7.7% of participants receiving ALN-TTR01 and ALN-TTR02, respectively.
ALN-TTR01 and ALN-TTR02 suppressed the production of both mutant and nonmutant forms of transthyretin, establishing proof of concept for RNAi therapy targeting messenger RNA transcribed from a disease-causing gene.
Alnylam May Seek Approval for TTR Amyloidosis Rx in 2017 as Other Programs Advance
Officials from Alnylam Pharmaceuticals last week provided updates on the two drug candidates from the company’s flagship transthyretin-mediated amyloidosis program, stating that the intravenously delivered agent patisiran is proceeding toward a possible market approval in three years, while a subcutaneously administered version called ALN-TTRsc is poised to enter Phase III testing before the end of the year.
Meanwhile, Alnylam is set to advance a handful of preclinical therapies into human studies in short order, including ones for complement-mediated diseases, hypercholesterolemia, and porphyria.
The officials made their comments during a conference call held to discuss Alnylam’s second-quarter financial results.
ATTR is caused by a mutation in the TTR gene, which normally produces a protein that acts as a carrier for retinol binding protein and is characterized by the accumulation of amyloid deposits in various tissues. Alnylam’s drugs are designed to silence both the mutant and wild-type forms of TTR.
Patisiran, which is delivered using lipid nanoparticles developed by Tekmira Pharmaceuticals, is currently in a Phase III study in patients with a form of ATTR called familial amyloid polyneuropathy (FAP) affecting the peripheral nervous system. Running at over 20 sites in nine countries, that study is set to enroll up to 200 patients and compare treatment to placebo based on improvements in neuropathy symptoms.
According to Alnylam Chief Medical Officer Akshay Vaishnaw, Alnylam expects to have final data from the study in two to three years, which would put patisiran on track for a new drug application filing in 2017.
Meanwhile, ALN-TTRsc, which is under development for a version of ATTR that affects cardiac tissue called familial amyloidotic cardiomyopathy (FAC) and uses Alnylam’s proprietary GalNAc conjugate delivery technology, is set to enter Phase III by year-end as Alnylam holds “active discussions” with US and European regulators on the design of that study, CEO John Maraganore noted during the call.
In the interim, Alnylam continues to enroll patients in a pilot Phase II study of ALN-TTRsc, which is designed to test the drug’s efficacy for FAC or senile systemic amyloidosis (SSA), a condition caused by the idiopathic accumulation of wild-type TTR protein in the heart.
Based on “encouraging” data thus far, Vaishnaw said that Alnylam has upped the expected enrollment in this study to 25 patients from 15. Available data from the trial is slated for release in November, he noted, stressing that “any clinical endpoint result needs to be considered exploratory given the small sample size and the very limited duration of treatment of only six weeks” in the trial.
Vaishnaw added that an open-label extension (OLE) study for patients in the ALN-TTRsc study will kick off in the coming weeks, allowing the company to gather long-term dosing tolerability and clinical activity data on the drug.
Enrollment in an OLE study of patisiran has been completed with 27 patients, he said, and, “as of today, with up to nine months of therapy … there have been no study drug discontinuations.” Clinical endpoint data from approximately 20 patients in this study will be presented at the American Neurological Association meeting in October.
As part of its ATTR efforts, Alnylam has also been conducting natural history of disease studies in both FAP and FAC patients. Data from the 283-patient FAP study was presented earlier this year and showed a rapid progression in neuropathy impairment scores and a high correlation of this measurement with disease severity.
During last week’s conference call, Vaishnaw said that clinical endpoint and biomarker data on about 400 patients with either FAC or SSA have already been collected in a nature history study on cardiac ATTR. Maraganore said that these findings would likely be released sometime next year.
The first medication for a rare and often fatal protein misfolding disorder has been approved in Europe. On November 16, the E gave a green light to Pfizer’s Vyndaqel (tafamidis) for treating transthyretin amyloidosis in adult patients with stage 1 polyneuropathy symptoms. [Jeffery Kelly, La Jolla]
The most clinically advanced RNA interference (RNAi) therapeutic achieved a milestone in April when Alnylam Pharmaceuticals in Cambridge, Massachusetts, reported positive results for patisiran, a small interfering RNA (siRNA) oligonucleotide targeting transthyretin for treating familial amyloidotic polyneuropathy (FAP). …
FAP is characterized by the systemic deposition of amyloidogenic variants of the transthyretin protein, especially in the peripheral nervous system, causing a progressive sensory and motor polyneuropathy.
FAP is caused by a mutation of the TTR gene, located on human chromosome 18q12.1-11.2.[5] A replacement of valine by methionine at position 30 (TTR V30M) is the mutation most commonly found in FAP.[1] The variant TTR is mostly produced by the liver.[citation needed] The transthyretin protein is a tetramer. ….
Proteome Sciences plc has strongly encouraged by two recent reports that emphasise the importance of protein profiling to improve outcomes in cancer treatment. These highlight the growing need for more detailed, personal assessment of protein profiles to improve the management of cancer treatment.
In the first study two groups from University College London and Cancer Research UK demonstrated that genetic mutations in cancer can lead to changes in the proteins on the cell surface1. These are new sequences which are seen as foreign by the body’s immune system and, with appropriate immunotherapy, the level of response in lung cancer was greatly enhanced.
However many of the patients with these types of mutations unfortunately still did not respond which highlighted the need for deeper analysis of the protein expression in tumours in order to better appreciate the mechanisms that contribute to treatment failure.
The second study, led by Professor Nigel Bundred of Manchester University, reported that use of two drugs that act on the same breast cancer target, an over-expressing protein called Her-2, were able to eradicate detectable tumours in around 10% of those treated in just 11 days, with 87% of those treated having a proteomic change indicating cells had stopped growing and/or cell death had increased2.
Whilst these results appear very promising it is worth noting that the over-expressing Her-2 target is only present in about 20% of breast tumours meaning this combination therapy was successful in clearing tumours in just 2% of the total breast cancer population.
Dr. Ian Pike, Chief Operating Officer of Proteome Sciences commented, “Both these recent studies should rightly be recognised as important steps forward towards better cancer treatment. However, in order to overcome the limitations of current drug therapy programs, a much deeper and more comprehensive analysis of the complex protein networks that regulate tumour growth and survival is required and will be essential to achieve a major advance in the battle to treat cancer.
“Our SysQuant® workflows provide that solution. As an example, in pancreatic cancer3 we have successfully mapped the complex network of regulatory processes and demonstrate the ability to devise personalised treatment combinations on an individual basis for each patient. A retrospective study with SysQuant® to predict response to the targeted drug Sorafenib in liver cancer is in process and we are planning further prospective trials to guide personalised treatment selection in liver cancer.
“We are already delivering systems-wide biology solutions through SysQuant® and TMTcalibrator™ programs to our clients that are generating novel biological data and results using more sensitive profiling that are helping them to better understand their drug development programs and to provide new biomarkers for tracking patient response in clinical trials.
“We are strongly positioned to deliver more comprehensive analysis of proteins and cellular pathways across other areas of disease and in particular to extend the use of SysQuant® with other leading cancer research groups in liver and other cancers.”
Proteome Sciences has also expanded its offering in personalised medicine through the use of its TMTcalibrator™ technology to uniquely identify protein biomarkers that reveal active cancer and other disease processes in body fluid samples. The importance of these ‘mechanistic’ biomarkers is that they are essential to monitor that drugs are being effective and that they can be used as early biomarkers of disease recurrence.
Using SysQuant® and TMTcalibrator™, Proteome Sciences can deliver more comprehensive analysis and provide unparalleled levels of sensitivity and breadth of coverage of the proteome, enabling faster, more efficient drug development and more accurate disease diagnosis.
Discovering ‘Outlier’ Enzymes
Researchers at TSRI and Salk Institute have discovered ‘Outlier’ enzymes that could offer new targets to treat type 2 diabetes and inflammatory disorders.
A team led by scientists at The Scripps Research Institute (TSRI) and the Salk Institute for Biological Studies have discovered two enzymes that appear to play a role in metabolism and inflammation—and might someday be targeted with drugs to treat type 2 diabetes and inflammatory disorders. The discovery is unusual because the enzymes do not bear a resemblance—in their structures or amino-acid sequences—to any known class of enzymes.
The team of scientists nevertheless identified them as “outlier” members of the serine/threonine hydrolase class, using newer techniques that detect biochemical activity. “A huge fraction of the human ‘proteome’ remains uncharacterized, and this paper shows how chemical approaches can be used to uncover proteins of a given functionality that have eluded classification based on sequence or predicted structure,” said co-senior author Benjamin F. Cravatt, chair of TSRI’s Department of Chemical Physiology.
“In this study, we found two genes that control levels of lipids with anti-diabetic and anti-inflammatory activity, suggesting exciting targets for diabetes and inflammatory diseases,” said co-senior author Alan Saghatelian, who holds the Dr. Frederik Paulsen Chair at the Salk Institute. The study, which appeared as a Nature Chemical Biology Advance Online Publication on March 28, 2016, began as an effort in the Cravatt laboratory to discover and characterize new serine/threonine hydrolases using fluorophosphonate (FP) probes—molecules that selectively bind and, in effect, label the active sites of these enzymes.
Pulling FP-binding proteins out of the entire proteome of test cells and identifying them using mass spectrometry techniques, the team matched nearly all to known hydrolases. The major outlier was a protein called androgen-induced gene 1 protein (AIG1). The only other one was a distant cousin in terms of sequence, a protein called ADTRP. “Neither of these proteins had been characterized as an enzyme; in fact, there had been little functional characterization of them at all,” said William H. Parsons, a research associate in the Cravatt laboratory who was co-first author of the study.
Experiments on AIG1 and ADTRP revealed that they do their enzymatic work in a unique way. “It looks like they have an active site that is novel—it had never been described in the literature,” said Parsons. Initial tests with panels of different enzyme inhibitors showed that AIG1 and ADTRP are moderately inhibited by inhibitors of lipases—enzymes that break down fats and other lipids. But on what specific lipids do these newly discovered outlier enzymes normally work?
At the Salk Institute, the Saghatelian laboratory was investigating a class of lipids it had discovered in 2014. Known as fatty acid esters of hydroxy fatty acids (FAHFAs), these molecules showed strong therapeutic potential. Saghatelian and his colleagues had found that boosting the levels of one key FAHFA lipid normalizes glucose levels in diabetic mice and also reduces inflammation.
“[Ben Cravatt’s] lab was screening panels of lipids to find the ones that their new enzymes work on,” said Saghatelian, who is a former research associate in the Cravatt laboratory. “We suggested they throw FAHFAs in there—and these turned out to be very good substrates.” The Cravatt laboratory soon developed powerful inhibitors of the newly discovered enzymes, and the two labs began working together, using the inhibitors and genetic techniques to explore the enzymes’ functions in vitro and in cultured cells.
Co-first author Matthew J. Kolar, an MD-PhD student, performed most of the experiments in the Saghatelian lab. The team concluded that AIG1 and ADTRP, at least in the cell types tested, appear to work mainly to break down FAHFAs and not any other major class of lipid. In principle, inhibitors of AIG1 and ADTRP could be developed into FAHFA-boosting therapies.
“Our prediction,” said Saghatelian, “is that if FAHFAs do what we think they’re doing, then using an enzyme inhibitor to block their degradation would make FAHFA levels go up and should thus reduce inflammation as well as improve glucose levels and insulin sensitivity.” The two labs are now collaborating on further studies of the new enzymes—and the potential benefits of inhibiting them—in mouse models of diabetes, inflammation and autoimmune disease.
“One of the neat things this study shows,” said Cravatt, “is that even for enzyme classes as well studied as the hydrolases, there may still be hidden members that, presumably by convergent evolution, arrived at that basic enzyme mechanism despite sharing no sequence or structural homology.”
Other co-authors of the study, “AIG1 and ADTRP are atypical integral membrane hydrolases that degrade bioactive FAHFAs,” were Siddhesh S. Kamat, Armand B. Cognetta III, Jonathan J. Hulce and Enrique Saez, of TSRI; and co-senior author Barbara B. Kahn of Beth Israel Deaconess Medical Center and Harvard Medical School
New Weapon Against Breast Cancer
Molecular marker in healthy tissue can predict a woman’s risk of getting the disease, research says.
Harvard Stem Cell Institute (HSCI) researchers at Dana-Farber Cancer Institute (DFCI) and collaborators at Brigham and Women’s Hospital (BWH) have identified a molecular marker in normal breast tissue that can predict a woman’s risk for developing breast cancer, the leading cause of death in women with cancer worldwide.
The work, led by HSCI principal faculty member Kornelia Polyak and Rulla Tamimi of BWH, was published in an early online release and in the April 1 issue of Cancer Research.
The study builds on Polyak’s earlier research finding that women already identified as having a high risk of developing cancer — namely those with a mutation called BRCA1 or BRCA2 — or women who did not give birth before their 30s had a higher number of mammary gland progenitor cells.
In the latest study, Polyak, Tamimi, and their colleagues examined biopsies, some taken as many as four decades ago, from 302 participants in the Nurses’ Health Study and the Nurses’ Health Study II who had been diagnosed with benign breast disease. The researchers compared tissue from the 69 women who later developed cancer to the tissue from the 233 women who did not. They found that women were five times as likely to develop cancer if they had a higher percentage of Ki67, a molecular marker that identifies proliferating cells, in the cells that line the mammary ducts and milk-producing lobules. These cells, called the mammary epithelium, undergo drastic changes throughout a woman’s life, and the majority of breast cancers originate in these tissues.
Doctors already test breast tumors for Ki67 levels, which can inform decisions about treatment, but this is the first time scientists have been able to link Ki67 to precancerous tissue and use it as a predictive tool.
“Instead of only telling women that they don’t have cancer, we could test the biopsies and tell women if they were at high risk or low risk for developing breast cancer in the future,” said Polyak, a breast cancer researcher at Dana-Farber and co-senior author of the paper.
“Currently, we are not able to do a very good job at distinguishing women at high and low risk of breast cancer,” added co-senior author Tamimi, an associate professor at the Harvard T.H. Chan School of Public Health and Harvard Medical School. “By identifying women at high risk of breast cancer, we can better develop individualized screening and also target risk reducing strategies.”
To date, mammograms are the best tool for the early detection, but there are risks associated with screening. False positive and negative results and over-diagnosis could cause psychological distress, delay treatment, or lead to overtreatment, according to the National Cancer Institute (NCI).
Mammography machines also use low doses of radiation. While a single mammogram is unlikely to cause harm, repeated screening can potentially cause cancer, though the NCI writes that the benefits “nearly always outweigh the risks.”
“If we can minimize unnecessary radiation for women at low risk, that would be good,” said Tamimi.
Screening for Ki67 levels would “be easy to apply in the current setting,” said Polyak, though the researchers first want to reproduce the results in an independent cohort of women.
AIG1 and ADTRP are atypical integral membrane hydrolases that degrade bioactive FAHFAs
Enzyme classes may contain outlier members that share mechanistic, but not sequence or structural, relatedness with more common representatives. The functional annotation of such exceptional proteins can be challenging. Here, we use activity-based profiling to discover that the poorly characterized multipass transmembrane proteins AIG1 and ADTRP are atypical hydrolytic enzymes that depend on conserved threonine and histidine residues for catalysis. Both AIG1 and ADTRP hydrolyze bioactive fatty acid esters of hydroxy fatty acids (FAHFAs) but not other major classes of lipids. We identify multiple cell-active, covalent inhibitors of AIG1 and show that these agents block FAHFA hydrolysis in mammalian cells. These results indicate that AIG1 and ADTRP are founding members of an evolutionarily conserved class of transmembrane threonine hydrolases involved in bioactive lipid metabolism. More generally, our findings demonstrate how chemical proteomics can excavate potential cases of convergent or parallel protein evolution that defy conventional sequence- and structure-based predictions.
Figure 1: Discovery and characterization of AIG1 and ADTRP as FP-reactive proteins in the human proteome.
(a) Competitive ABPP-SILAC analysis to identify FP-alkyne-inhibited proteins, in which protein enrichment and inhibition were measured in proteomic lysates from SKOV3 cells treated with FP-alkyne (20 μM, 1 h) or DMSO using the FP-biotin…
Willems, L.I., Overkleeft, H.S. & van Kasteren, S.I.Current developments in activity-based protein profiling. Bioconjug. Chem.25, 1181–1191 (2014).
Berger, A.B., Vitorino, P.M. & Bogyo, M.Activity-based protein profiling: applications to biomarker discovery, in vivo imaging and drug discovery. Am. J. Pharmacogenomics4,371–381 (2004).
Simon, G.M. & Cravatt, B.F.Activity-based proteomics of enzyme superfamilies: serine hydrolases as a case study. J. Biol. Chem.285, 11051–11055 (2010).
National Institutes of Health (NIH)-sponsored screening centers provide academic researchers with a special opportunity to pursue small-molecule probes for protein targets that are outside the current interest of, or beyond the standard technologies employed by, the pharmaceutical industry. Here, we describe the outcome of an inhibitor screen for one such target, the enzyme protein phosphatase methylesterase-1 (PME-1), which regulates the methylesterification state of protein phosphatase 2A (PP2A) and is implicated in cancer and neurodegeneration. Inhibitors of PME-1 have not yet been described, which we attribute, at least in part, to a dearth of substrate assays compatible with high-throughput screening. We show that PME-1 is assayable by fluorescence polarization-activity-based protein profiling (fluopol-ABPP) and use this platform to screen the 300,000+ member NIH small-molecule library. This screen identified an unusual class of compounds, the aza-β-lactams (ABLs), as potent (IC50 values of approximately 10 nM), covalent PME-1 inhibitors. Interestingly, ABLs did not derive from a commercial vendor but rather an academic contribution to the public library. We show using competitive-ABPP that ABLs are exquisitely selective for PME-1 in living cells and mice, where enzyme inactivation leads to substantial reductions in demethylated PP2A. In summary, we have combined advanced synthetic and chemoproteomic methods to discover a class of ABL inhibitors that can be used to selectively perturb PME-1 activity in diverse biological systems. More generally, these results illustrate how public screening centers can serve as hubs to create spontaneous collaborative opportunities between synthetic chemistry and chemical biology labs interested in creating first-in-class pharmacological probes for challenging protein targets.
Protein phosphorylation is a pervasive and dynamic posttranslational protein modification in eukaryotic cells. In mammals, more than 500 protein kinases catalyze the phosphorylation of serine, threonine, and tyrosine residues on proteins (1). A much more limited number of phosphatases are responsible for reversing these phosphorylation events (2). For instance, protein phosphatase 2A (PP2A) and PP1 are thought to be responsible together for > 90% of the total serine/threonine phosphatase activity in mammalian cells (3). Specificity is imparted on PP2A activity by multiple mechanisms, including dynamic interactions between the catalytic subunit (C) and different protein-binding partners (B subunits), as well as a variety of posttranslational chemical modifications (2, 4). Within the latter category is an unusual methylesterification event found at the C terminus of the catalytic subunit of PP2A that is introduced and removed by a specific methyltransferase (leucine carbxoylmethyltransferase-1 or LCMT1) (5, 6) and methylesterase (protein phosphatase methylesterase-1 or PME-1) (7), respectively (Fig. 1A). PP2A carboxymethylation (hereafter referred to as “methylation”) has been proposed to regulate PP2A activity, at least in part, by modulating the binding interaction of the C subunit with various regulatory B subunits (8–10). A predicted outcome of these shifts in subunit association is the targeting of PP2A to different protein substrates in cells. PME-1 has also been hypothesized to stabilize inactive forms of nuclear PP2A (11), and recent structural studies have shed light on the physical interactions between PME-1 and the PP2A holoenzyme (12).
There were several keys to the success of our probe development effort. First, screening for inhibitors of PME-1 benefited from the fluopol-ABPP technology, which circumvented the limited throughput of previously described substrate assays for this enzyme. Second, we were fortunate that the NIH compound library contained several members of the ABL class of small molecules. These chiral compounds, which represent an academic contribution to the NIH library, occupy an unusual portion of structural space that is poorly accessed by commercial compound collections. Although at the time of their original synthesis (23) it may not have been possible to predict whether these ABLs would show specific biological activity, their incorporation into the NIH library provided a forum for screening against many proteins and cellular targets, culminating in their identification as PME-1 inhibitors. We then used advanced chemoproteomic assays to confirm the remarkable selectivity displayed by ABLs for PME-1 across (and beyond) the serine hydrolase superfamily. That the mechanism for PME-1 inhibition involves acylation of the enzyme’s conserved serine nucleophile (Fig. 3) suggests that exploration of a more structurally diverse set of ABLs might uncover inhibitors for other serine hydrolases. In this way, the chemical information gained from a single high-throughput screen may be leveraged to initiate probe development programs for additional enzyme targets.
Projecting forward, this research provides an example of how public small-molecule screening centers can serve as a portal for spawning academic collaborations between chemical biology and synthetic chemistry labs. By continuing to develop versatile high-throughput screens and combining them with a small-molecule library of expanding structural diversity conferred by advanced synthetic methodologies, academic biologists and chemists are well-positioned to collaboratively deliver pharmacological probes for a wide range of proteins and pathways in cell biology.
The frequency and proliferative activity of tissue-specific stem and progenitor cells are suggested to correlate with cancer risk. In this study, we investigated the association between breast cancer risk and the frequency of mammary epithelial cells expressing p27, estrogen receptor (ER), and Ki67 in normal breast tissue. We performed a nested case-control study of 302 women (69 breast cancer cases, 233 controls) who had been initially diagnosed with benign breast disease according to the Nurses’ Health Studies. Immunofluorescence for p27, ER, and Ki67 was performed on tissue microarrays constructed from benign biopsies containing normal mammary epithelium and scored by computational image analysis. We found that the frequency of Ki67+ cells was positively associated with breast cancer risk among premenopausal women (odds ratio [OR]=10.1, 95% confidence interval [CI]=2.12-48.0). Conversely, the frequency of ER+ or p27+ cells was inversely, but not significantly, associated with subsequent breast cancer risk (ER+: OR=0.70, 95% CI=0.33-1.50; p27+: OR=0.89, 95% CI=0.45-1.75). Notably, high Ki67+/low p27+ and high Ki67+/low ER+ cell frequencies were significantly associated with a 5-fold higher risk of breast cancer compared to low Ki67+/low p27+ and low Ki67+/low ER+ cell frequencies, respectively, among premenopausal women (Ki67hi/p27lo: OR=5.08, 95% CI=1.43-18.1; Ki67hi/ERlo: OR=4.68, 95% CI=1.63-13.5). Taken together, our data suggest that the fraction of actively cycling cells in normal breast tissue may represent a marker for breast cancer risk assessment, which may therefore impact the frequency of screening procedures in at-risk women.
Scientists have discovered a group of six proteins that may help to divulge secrets of how we age, potentially unlocking new insights into diabetes, Alzheimer’s, cancer, and other aging-related diseases.
The proteins appear to play several roles in our bodies’ cells, from decreasing the amount of damaging free radicals and controlling the rate at which cells die to boosting metabolism and helping tissues throughout the body respond better to insulin. The naturally occurring amounts of each protein decrease with age, leading investigators to believe that they play an important role in the aging process and the onset of diseases linked to older age.
The research team led by Pinchas Cohen, M.D., dean and professor of the University of Southern California Leonard Davis School of Gerontology, identified the proteins and observed their origin from mitochondria and their game-changing roles in metabolism and cell survival. This latest finding builds upon prior research by Dr. Cohen and his team that uncovered two significant proteins, humanin and MOTS-c, hormones that appear to have significant roles in metabolism and diseases of aging.
Unlike most other proteins, humanin and MOTS-c are encoded in mitochondria. Dr. Cohen’s team used computer analysis to see if the part of the mitochondrial genome that provides the code for humanin was coding for other proteins as well. The analysis uncovered the genes for six new proteins, which were dubbed small humanin-like peptides, or SHLPs, 1 through 6 (pronounced “schlep”).
After identifying the six SHLPs and successfully developing antibodies to test for several of them, the team examined both mouse tissues and human cells to determine their abundance in different organs as well as their functions. The proteins were distributed quite differently among organs, which suggests that the proteins have varying functions based on where they are in the body. Of particular interest is SHLP 2, according to Dr. Cohen. The protein appears to have insulin-sensitizing, antidiabetic effects as well as neuroprotective activity that may emerge as a strategy to combat Alzheimer’s disease. He added that SHLP 6 is also intriguing, with a unique ability to promote cancer cell death and thus potentially target malignant diseases.
Proteins That May Protect Against Age Related Illnesses Discovered
Tested in both mice and human cells, the proteins may lead to greater understanding of aging-related diseases, from diabetes to Alzheimer’s to cancer, according to researchers at USC Davis School of Gerontology who led the study.
Researchers have identified a group of six proteins that they believe may divulge secrets of how we age and unlock new insights into diabetes, Alzheimer’s, cancer, and other aging-related diseases.
Nicknamed “Schlep” or “SHLP” for “small humanin-like peptides,” these proteins appear to play several big roles in our bodies’ cells, from decreasing the amount of damaging free radicals and controlling the rate at which cells die, to boosting metabolism and helping tissues throughout the body respond better to insulin. The naturally occurring amounts of each protein decrease with age, leading researchers to believe that they play an important role in the aging process and the onset of age-related diseases.
The research team led by Pinchas Cohen, dean and professor of the USC Leonard Davis School of Gerontology, identified the tiny proteins for the first time and observed their surprising origin: organelles in the cell called mitochondria and their game-changing roles in metabolism and cell survival.
This latest finding builds upon prior research by Cohen and his team that uncovered two significant proteins, humanin and MOTS-c, hormones that appear to have significant roles in metabolism and diseases of aging.
The cell proliferation antigen Ki-67 organises heterochromatin
MichalSobecki,
KarimMrouj
Montpellier Institute of Molecular Genetics (IGMM) CNRS UMR 5535, Centre National de la Recherche Scientifique (CNRS), Montpellier, France; Faculty of Sciences, University of Montpellier, Montpellier, France
Contribution: Acquisition of data, Analysis and interpretation of data, Drafting or revising the article
No competing interests declared
</div>”>KarimMrouj,
AlainCamasses
Montpellier Institute of Molecular Genetics (IGMM) CNRS UMR 5535, Centre National de la Recherche Scientifique (CNRS), Montpellier, France; Faculty of Sciences, University of Montpellier, Montpellier, France
Contribution: Conception and design, Acquisition of data, Analysis and interpretation of data
No competing interests declared
</div>”>AlainCamasses,
NikolaosParisis
Montpellier Institute of Molecular Genetics (IGMM) CNRS UMR 5535, Centre National de la Recherche Scientifique (CNRS), Montpellier, France; Faculty of Sciences, University of Montpellier, Montpellier, France
Contribution: Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article
RNA Molecular Biology, Center for Microscopy and Molecular Imaging, Fonds de la Recherche Nationale, Université Libre de Bruxelles, Charleroi-Gosselies, Belgium
Contribution: Conception and design, Acquisition of data, Analysis and interpretation of data
Antigen Ki-67 is a nuclear protein expressed in proliferating mammalian cells. It is widely used in cancer histopathology but its functions remain unclear. Here, we show that Ki-67 controls heterochromatin organisation. Altering Ki-67 expression levels did not significantly affect cell proliferation in vivo. Ki-67 mutant mice developed normally and cells lacking Ki-67 proliferated efficiently. Conversely, upregulation of Ki-67 expression in differentiated tissues did not prevent cell cycle arrest. Ki-67 interactors included proteins involved in nucleolar processes and chromatin regulators. Ki-67 depletion disrupted nucleologenesis but did not inhibit pre-rRNA processing. In contrast, it altered gene expression. Ki-67 silencing also had wide-ranging effects on chromatin organisation, disrupting heterochromatin compaction and long-range genomic interactions. Trimethylation of histone H3K9 and H4K20 was relocalised within the nucleus. Finally, overexpression of human or Xenopus Ki-67 induced ectopic heterochromatin formation. Altogether, our results suggest that Ki-67 expression in proliferating cells spatially organises heterochromatin, thereby controlling gene expression.
A protein called Ki-67 is only produced in actively dividing cells, where it is located in the nucleus – the structure that contains most of the cell’s DNA. Researchers often use Ki-67 as a marker to identify which cells are actively dividing in tissue samples from cancer patients, and previous studies indicated that Ki-67 is needed for cells to divide. However, the exact role of this protein was not clear. Before cells can divide they need to make large amounts of new proteins using molecular machines called ribosomes and it has been suggested that Ki-67 helps to produce ribosomes.
Now, Sobecki et al. used genetic techniques to study the role of Ki-67 in mice. The experiments show that Ki-67 is not required for cells to divide in the laboratory or to make ribosomes. Instead, Ki-67 alters the way that DNA is packaged in the nucleus. Loss of Ki-67 from mice cells resulted in DNA becoming less compact, which in turn altered the activity of genes in those cells.
There is growing interest in the field of glycobiology given the fact that epitopes with physiological and pathological relevance have glyco moieties. We believe that another “omics” revolution is on the horizon—the study of the glyco modifications on the surface of cells and their potential as biomarkers and therapeutic targets in many disease classes. Not much industry tracking of this field has taken place. Thus, we sought to map this landscape by examining the entire ensemble of academic publications in this space and teasing apart the trends operative in this field from a qualitative and quantitative perspective. We believe that this methodology of en masse capture and publication and annotation provides an effective approach to evaluate this early-stage field.
Identifiation and Growth of Glycobiology Publications
For this article, we identified 7000 publications in the broader glycobiology space and analyzed them in detail. It is important to frame glycobiology in the context of genomics and proteomics as a means to assess the scale of the field. Figure 1 presents the relative sizes of these fields as assessed by publications in from 1975 to 2015.
Note that the relative scale of genomics versus proteomics and glycobiology/glycomics in this graph strongly suggests that glycobiology is a nascent space, and thus a driver for us to map its landscape today and as it evolves over the coming years.
Figure 2. (A) Segmentation of the glycobiology landscape. (B) Glycobiology versus glycomics publication growth.
To examine closely the various components of the glycobiology space, we segmented the publications database, presented in Figure 2A. Note the relative sizes and growth rates (slopes) of the various segments.
Clearly, glycoconjugates currently are the majority of this space and account for the bulk of the publications. Glycobiology and glycomics are small but expanding and therefore can be characterized as “nascent market segments.” These two spaces are characterized in more detail in Figure 2B, which presents their publication growth rates.
Note the very recent increased attention directed at these spaces and hence our drive to initiate industry coverage of these spaces. Figure 2B presents the overall growth and timeline of expansion of these fields—especially glycobiology—but it provides no information about the qualitative nature of these fields.
Figure 2C. Word cloud based on titles of publications in the glycobiology and glycomics spaces.
To understand the focus of publications in this field, and indeed the nature of this field, we constructed a word cloud based on titles of the publications that comprise this space presented in Figure 2C.
There is a marked emphasis on terms such as oligosaccharides and an emphasis on cells (this is after all glycosylation on the surface of cells). Overall, a pictorial representation of the types and classes of modifications that comprise this field emerge in this word cloud, demonstrating the expansion of the glycobiology and to a lesser extent the glycomics spaces as well as the character of these nascent but expanding spaces.
Characterization of the Glycobiology Space in Journals
Figure 3A. Breakout of publications in the glycobiology/glycomics fields. http://www.genengnews.com/Media/images/AnalysisAndInsight/April12_2016_SelectBiosciences_Figure3a_5002432117316.jpg
Having framed the overall growth of the glycobiology field, we wanted to understand its structure and the classes of researchers as well as publications that comprise this field. To do this, we segmented the publications that constitute this field into the various journals in which glycobiology research is published. Figure 3A presents the breakout of publications by journal to illustrate the “scope” of this field.
The distribution of glycobiology publications across the various journals suggests a very concentrated marketplace that is very technically focused. The majority of the publications segregate into specialized journals on this topic, a pattern very indicative of a field in the very early stages of development—a truly nascent marketplace.
Figure 3B. Origin of publications in the glycobiology/glycomics fields.
We also sought to understand the “origin” of these publications—the breakout between academic- versus industry-derived journals. Figure 3B presents this breakout and shows that these publications are overwhelmingly (92.3%) derived from the academic sector. This is again a testimonial to the early nascent nature of this marketplace without significant engagement by the commercial sector and therefore is an important field to characterize and track from the ground up.
Select Biosciences, Inc. further analyzed the growth trajectory of the glycobiology papers in Figure 3C as a means to examine closely the publications trajectory. Although there appears to be some wobble along the way, overall the trajectory is upward, and of late it is expanding significantly.
In Summary
Figure 3C. Trajectory of the glycobiology space. http://www.genengnews.com/Media/images/AnalysisAndInsight/April12_2016_SelectBiosciences_Figure3c1236921793.jpg
Glycobiology is the study of what coats living cells—glycans, or carbohydrates, and glycoconjugates. This is an important field of study with medical applications because it is known that tumor cells alter their glycosylation pattern, which may contribute to their metastatic potential as well as potential immune evasion.
At this point, glycobiology is largely basic research and thus it pales in comparison with the field of genomics. But in 10 years, we predict the study of glycobiology and glycomics will be ubiquitous and in the mainstream.
We started our analysis of this space because we’ve been focusing on many other classes of analytes, such as microRNAs, long-coding RNAs, oncogenes, tumor suppressor genes, etc., whose potential as biomarkers is becoming established. Glycobiology, on the other hand, represents an entire new space—a whole new category of modifications that could be analyzed for diagnostic potential and perhaps also for therapeutic targeting.
Today, glycobiology and glycomics are where genomics was at the start of the Human Genome Project. They respresent a nascent space and with full headroom for growth. Select Biosciences will continue to track this exciting field for research developments as well as development of biomarkers based on glyco-epitopes.
Enal Razvi, Ph.D., conducted his doctoral work on viral immunology and subsequent to receiving his Ph.D. went on to the Rockefeller University in New York to serve as Aaron Diamond Post-doctoral fellow under Professor Ralph Steinman [Nobel Prize Winner in 2011 for his discovery of dendritic cells in the early-70s with Zanvil Cohn]. Subsequently, Dr. Razvi completed his research fellowship at Harvard Medical School. For the last two decades Dr. Razvi has worked with small and large companies and consulted for more than 100 clients worldwide. He currently serves as Biotechnology Analyst and Managing Director of SelectBio U.S. He can be reached at enal@selectbio.us. Gary M. Oosta holds a Ph.D. in Biophysics from Massachusetts Institute of Technology and a B.A. in Chemistry from E. Mich. Univ. He has 25 years of industrial research experience in various technology areas including medical diagnostics, thin-layer coating, bio-effects of electromagnetic radiation, and blood coagulation. Dr. Oosta has authored 20 technical publications and is an inventor on 77 patents worldwide. In addition, he has managed research groups that were responsible for many other patented innovations. Dr. Oosta has a long-standing interest in using patents and publications as strategic technology indicators for future technology selection and new product development. To enjoy more articles like this from GEN, click here to subscribe now!
RELATED CONTENT
Ezose, Hirosaki University Sign Glycomics Partnership to Identify Urologic Cancer Biomarkers
Getting Testy Over Liquid Biopsies
Enabling High-Throughput Glycomics
Market & Tech Analysis
The Evolution of the Glycobiology Space
Cancer Immunotherapy 2016
The Cancer Biomarkers Marketplace
Microfluidics in the Life Sciences
Liquid Biopsies Landscape
Alternative CRISPR discovered @MIT, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 2: CRISPR for Gene Editing and DNA Repair
Alternative CRISPR Discovered @MIT
Reporter & Curator: Larry H. Bernstein, MD, FCAP
New breakthrough! – A better alternative CRISPR system just identified
CRISPR-Cas9 system has revolutionized the field of genome editing since its first application in human cells was reported in 2012. A recent publication in Cell reported the identification of a different CRISPR system with the potential for even simpler and more precise genome editing. The newly identified CRISPR-Cpf1 system mediates robust DNA interference with features different from Cas9. Cpf1 possesses several advantages over the currently used Cas9 system.
The Cpf1 system is simpler than Cas9 system as it requires only a single RNA for its DNA-cutting enzymatic activity.
Cpf1 cut has shot overhangs on the exposed ends, allowing more efficient and precise genome engineering; while Cas9 cut produces blunt ends that often undergo mutations when rejoined.
Cpf1 is smaller than Cas9, thus easier to deliver into the cells or tissues.
Cpf1 cut is far away from the recognition site, leaving space for further editing if mutation occurred at the cutting site.
The Cpf1 complex recognize very different PAM sequences than those of Cas9, adding more flexibility in choosing target sites.
These properties of Cpf1 and its potential with more precise gene editing expanded the application scope of CRISPR, from gene knock-out and knock-ins, genomic deletions, to even gene therapy.
•Cpf1 is a CRISPR-associated two-component RNA-programmable DNA nuclease
•Targeted DNA is cleaved as a 5-nt staggered cut distal to a 5′ T-rich PAM
•Two Cpf1 orthologs exhibit robust nuclease activity in human cells
Summary
The microbial adaptive immune system CRISPR mediates defense against foreign genetic elements through two classes of RNA-guided nuclease effectors. Class 1 effectors utilize multi-protein complexes, whereas class 2 effectors rely on single-component effector proteins such as the well-characterized Cas9. Here, we report characterization of Cpf1, a putative class 2 CRISPR effector. We demonstrate that Cpf1 mediates robust DNA interference with features distinct from Cas9. Cpf1 is a single RNA-guided endonuclease lacking tracrRNA, and it utilizes a T-rich protospacer-adjacent motif. Moreover, Cpf1 cleaves DNA via a staggered DNA double-stranded break. Out of 16 Cpf1-family proteins, we identified two candidate enzymes from Acidaminococcus and Lachnospiraceae, with efficient genome-editing activity in human cells. Identifying this mechanism of interference broadens our understanding of CRISPR-Cas systems and advances their genome editing applications.
Almost all archaea and many bacteria achieve adaptive immunity through a diverse set of CRISPR-Cas (clustered regularly interspaced short palindromicrepeats and CRISPR-associated proteins) systems, each of which consists of a combination of Cas effector proteins and CRISPR RNAs (crRNAs) (Makarova et al., 2011, Makarova et al., 2015). The defense activity of the CRISPR-Cas systems includes three stages: (1) adaptation, when a complex of Cas proteins excises a segment of the target DNA (known as a protospacer) and inserts it into the CRISPR array (where this sequence becomes a spacer); (2) expression and processing of the precursor CRISPR (pre-cr) RNA resulting in the formation of mature crRNAs; and (3) interference, when the effector module—either another Cas protein complex or a single large protein—is guided by a crRNA to recognize and cleave target DNA (or in some cases, RNA) (Horvath and Barrangou, 2010,Sorek et al., 2013, Barrangou and Marraffini, 2014). The adaptation stage is mediated by the complex of the Cas1 and Cas2 proteins, which are shared by all known CRISPR-Cas systems, and sometimes involves additional Cas proteins. Diversity is observed at the level of processing of the pre-crRNA to mature crRNA guides, proceeding via either a Cas6-related ribonuclease or a housekeeping RNaseIII that specifically cleaves double-stranded RNA hybrids of pre-crRNA and tracrRNA. Moreover, the effector modules differ substantially among the CRISPR-Cas systems (Makarova et al., 2011, Makarova et al., 2015,Charpentier et al., 2015). In the latest classification, the diverse CRISPR-Cas systems are divided into two classes according to the configuration of their effector modules: class 1 CRISPR systems utilize several Cas proteins and the crRNA to form an effector complex, whereas class 2 CRISPR systems employ a large single-component Cas protein in conjunction with crRNAs to mediate interference (Makarova et al., 2015).
Multiple class 1 CRISPR-Cas systems, which include the type I and type III systems, have been identified and functionally characterized in detail, revealing the complex architecture and dynamics of the effector complexes (Brouns et al., 2008, Marraffini and Sontheimer, 2008, Hale et al., 2009, Sinkunas et al., 2013,Jackson et al., 2014, Mulepati et al., 2014). Several class 2 CRISPR-Cas systems have also been identified and experimentally characterized, but they are all type II and employ homologous RNA-guided endonucleases of the Cas9 family as effectors (Barrangou et al., 2007, Garneau et al., 2010, Deltcheva et al., 2011, Sapranauskas et al., 2011, Jinek et al., 2012, Gasiunas et al., 2012). A second, putative class 2 CRISPR system, tentatively assigned to type V, has been recently identified in several bacterial genomes (http://www.jcvi.org/cgi-bin/tigrfams/HmmReportPage.cgi?acc=TIGR04330) (Schunder et al., 2013, Vestergaard et al., 2014, Makarova et al., 2015). The putative type V CRISPR-Cas systems contain a large, ∼1,300 amino acid protein called Cpf1 (CRISPR from Prevotella and Francisella 1). It remains unknown, however, whether Cpf1-containing CRISPR loci indeed represent functional CRISPR systems. Given the broad applications of Cas9 as a genome-engineering tool (Hsu et al., 2014, Jiang and Marraffini, 2015), we sought to explore the function of Cpf1-based putative CRISPR systems.
Here, we show that Cpf1-containing CRISPR-Cas loci of Francisella novicida U112 encode functional defense systems capable of mediating plasmid interference in bacterial cells guided by the CRISPR spacers. Unlike Cas9 systems, Cpf1-containing CRISPR systems have three features. First, Cpf1-associated CRISPR arrays are processed into mature crRNAs without the requirement of an additional trans-activating crRNA (tracrRNA) (Deltcheva et al., 2011, Chylinski et al., 2013). Second, Cpf1-crRNA complexes efficiently cleave target DNA proceeded by a short T-rich protospacer-adjacent motif (PAM), in contrast to the G-rich PAM following the target DNA for Cas9 systems. Third, Cpf1 introduces a staggered DNA double-stranded break with a 4 or 5-nt 5′ overhang.
To explore the suitability of Cpf1 for genome-editing applications, we characterized the RNA-guided DNA-targeting requirements for 16 Cpf1-family proteins from diverse bacteria, and we identified two Cpf1 enzymes fromAcidaminococcus sp. BV3L6 and Lachnospiraceae bacterium ND2006 that are capable of mediating robust genome editing in human cells. Collectively, these results establish Cpf1 as a class 2 CRISPR-Cas system that includes an effective single RNA-guided endonuclease with distinct properties that has the potential to substantially advance our ability to manipulate eukaryotic genomes.
Results
Figure 1
The Francisella novicida U112 Cpf1 CRISPR Locus Provides Immunity against Transformation of Plasmids Containing Protospacers Flanked by a 5′-TTN PAM
(A) Organization of two CRISPR loci found in Francisella novicida U112 (NC_008601). The domain architectures of FnCas9 and FnCpf1 are compared.
(B) Schematic illustrating the plasmid depletion assay for discovering the PAM position and identity. Competent E. coliharboring either the heterologous FnCpf1 locus plasmid (pFnCpf1) or the empty vector control were transformed with a library of plasmids containing the matching protospacer flanked by randomized 5′ or 3′ PAM sequences and selected with antibiotic to deplete plasmids carrying successfully targeted PAM. Plasmids from surviving colonies were extracted and sequenced to determine depleted PAM sequences.
(C and D) Sequence logo for the FnCpf1 PAM as determined by the plasmid depletion assay. Letter height at each position is measured by information content (C) or frequency (D); error bars show 95% Bayesian confidence interval.
(E) E. coli harboring pFnCpf1 provides robust interference against plasmids carrying 5′-TTN PAMs (n = 3; error bars represent mean ± SEM).
Cpf1-Containing CRISPR Loci Are Active Bacterial Immune Systems
The Cpf1-Associated CRISPR Array Is Processed Independent of TracrRNA
Cpf1 Is a Single crRNA-Guided Endonuclease
The RuvC-like Domain of Cpf1 Mediates RNA-Guided DNA Cleavage
Sequence and Structural Requirements for the Cpf1 crRNA
Cpf1-Family Proteins from Diverse Bacteria Share Common crRNA Structures and PAMs
Cpf1 Can Be Harnessed to Facilitate Genome Editing in Human Cells
In this work, we characterize Cpf1-containing class 2 CRISPR systems, classified as type V, and show that its effector protein, Cpf1, is a single RNA-guided endonuclease. Cpf1 substantially differs from Cas9—to date, the only other experimentally characterized class 2 effector—in terms of structure and function and might provide important advantages for genome-editing applications. Specifically, Cpf1 contains a single identified nuclease domain, in contrast to the two nuclease domains present in Cas9. The results presented here show that, in FnCpf1, inactivation of RuvC-like domain abolishes cleavage of both DNA strands. Conceivably, FnCpf1 forms a homodimer (Figure S2B), with the RuvC-like domains of each of the two subunits cleaving one DNA strand. However, we cannot rule out that FnCpf1 contains a second yet-to-be-identified nuclease domain. Structural characterization of Cpf1-RNA-DNA complexes will allow testing of these hypotheses and elucidation of the cleavage mechanism.
February 8, 2016 | When a geneticist stares down the 3 billion DNA base pairs of the human genome, searching for a clue to what’s gone awry in a single patient, it helps to narrow the field. One of the most popular places to look is the exome, the tiny fraction of our DNA―less than 2%―that actually codes for proteins. For patients with rare genetic diseases, which might be fully explained by one key mutation, many studies sequence the whole exome and leave all the noncoding DNA out. Similarly, personalized cancer tests, which can help bring to light unexpected treatment options, often sequence the tumor exome, or a smaller panel of protein-coding genes.
Unfortunately, we know that’s not the whole picture. “There are a substantial number of noncoding regions that are just as effective at turning off a gene as a mutation in the gene itself,” says Richard Sherwood, a geneticist at Brigham and Women’s Hospital in Boston. “Exome sequencing is not going to be a good proxy for what genes are working.”
Sherwood studies regulatory DNA, the vast segment of the genome that governs which genes are turned on or off in any cell at a given time. It’s a confounding area of genetics; we don’t even know how much of the genome is made up of these regulatory elements. While genes can be recognized by the presence of “start” and “stop” codons―sequences of three DNA letters that tell the cell’s molecular machinery which stretches of DNA to transcribe into RNA, and eventually into protein―there are no definite signs like this for regulatory DNA.
Instead, studies to discover new regulatory elements have been somewhat trial-and-error. If you suspect a gene’s activity might be regulated by a nearby DNA element, you can inhibit that element in a living cell, and see if your gene shuts down with it.
With these painstaking experiments, scientists can slowly work their way through potential regulatory regions―but they can’t sweep across the genome with the kind of high-throughput testing that other areas of genetics thrive on. “Previously, you couldn’t do these sorts of tests in a large form, like 4,000 of them at once,” says David Gifford, a computational biologist at MIT. “You would really need to have a more hypothesis-directed methodology.”
Recently, Gifford and Sherwood collaborated on a paper, published in Nature Biotechnology, which presents a new method for testing thousands of DNA loci for regulatory activity at once. Their assay, called MERA (multiplexed editing regulatory assay), is built on the recent technology boom in CRISPR-Cas9 gene editing, which lets scientists quickly and easily cut specific sequences of DNA out of the genome.
So far, their team, including lead author Nisha Rajagopal from Gifford’s lab, has used MERA to study the regulation of four genes involved in the development of embryonic stem cells. Already, the results have defied the accepted wisdom about regulatory DNA. Many areas of the genome flagged by MERA as important factors in gene expression do not fall into any known categories of regulatory elements, and would likely never have been tested with previous-generation methods.
“Our approach allows you to look away from the lampposts,” says Sherwood. “The more unbiased you can be, the more we’ll actually know.”
A New Kind of CRISPR Screen
In the past three years, CRISPR-Cas9 experiments have taken all areas of molecular biology by storm, and Sherwood and Gifford are far from the first to use the technology to run large numbers of tests in parallel. CRISPR screens are an excellent way to learn which genes are involved in a cellular process, like tumor growth or drug resistance. In these assays, scientists knock out entire genes, one by one, and see what happens to cells without them.
This kind of CRISPR screen, however, operates on too small a scale to study the regulatory genome. For each gene knocked out in a CRISPR screen, you have to engineer a strain of virus to deliver a “guide RNA” into the cellular genome, showing the vicelike Cas9 molecule which DNA region to cut. That works well if you know exactly where a gene lies and only need to cut it once—but in a high-throughput regulatory test, you would want to blanket vast stretches of DNA with cuts, not knowing which areas will turn out to contain regulatory elements. Creating a new virus for each of these cuts is hugely impractical.
The insight behind MERA is that, with the right preparation, most of the genetic engineering can be done in advance. Gifford and Sherwood’s team used a standard viral vector to put a “dummy” guide RNA sequence, one that wouldn’t tell Cas9 to cut anything, into an embryonic stem cell’s genome. Then they grew plenty of cells with this prebuilt CRISPR system inside, and attacked each one with a Cas9 molecule targeted to the dummy sequence, chopping out the fake guide.
Normally, the result would just be a gap in the CRISPR system where the guide once was. But along with Cas9, the researchers also exposed the cells to new, “real” guide RNA sequences. Through a DNA repair mechanism called homologous recombination, the cells dutifully patched over the gaps with new guides, whose sequences were very similar to the missing dummy code. At the end of the process, each cell had a unique guide sequence ready to make cuts at a specific DNA locus—just like in a standard CRISPR screen, but with much less hands-on engineering.
By using a large enough library of guide RNA molecules, a MERA screen can include thousands of cuts that completely tile a broad region of the genome, providing an agnostic look at anywhere regulatory elements might be hiding. “It’s a lot easier [than a typical CRISPR screen],” says Sherwood. “The day the library comes in, you just perform one PCR reaction, and the cells do the rest of the work.”
In the team’s first batch of MERA screens, they created almost 4,000 guide RNAs for each gene they studied, covering roughly 40,000 DNA bases of the “cis-regulatory region,” or the area surrounding the gene where most regulatory elements are thought to lie. It’s unclear just how large any gene’s cis-regulatory region is, but 40,000 bases is a big leap from the highly targeted assays that have come before.
“We’re now starting to do follow-up studies where we increase the number of guide RNAs,” Sherwood adds. “Eventually, what you’d like is to be able to tile an entire chromosome.”
Far From the Lampposts
Sherwood and Gifford tried to focus their assays on regions that would be rich in regulatory elements. To that end, they made sure their guide RNAs covered parts of the genome with well-known signs of regulatory activity, like histone markers and transcription factor binding sites. For many of these areas, Cas9 cuts did, in fact, shut down gene expression in the MERA screens.
But the study also targeted regions around each gene that were empty of any known regulatory features. “We tiled some other regions that we thought might serve as negative controls,” explains Gifford. “But they turned out not to be negative at all.”
The study’s most surprising finding was that several cuts to seemingly random areas of the genome caused genes to become nonfunctional. The authors named these DNA regions “unmarked regulatory elements,” or UREs. They were especially prevalent around the genes Tdgf1 and Zfp42, and in many cases, seemed to be every bit as necessary to gene activity as more predictable hits on the MERA screen.
These results caught the researchers so off guard that it was natural to wonder if MERA screens are prone to false positives. Yet follow-up experiments strongly supported the existence of UREs. Switching the guide RNAs from aTdgf1 MERA screen and aZfp42 screen, for example, produced almost no positive results: the UREs’ regulatory effects were indeed specific to the genes near them.
In a more specific test, the researchers chose a particular URE connected to Tdgf1, and cut it out of a brand new population of cells for a closer look. “We showed that, if we deleted that region from the genome, the cells lost expression of the gene,” says Sherwood. “And then when we put it back in, the gene became expressed again. Which was good proof to us that the URE itself was responsible.”
From these results, it seems likely that follow-up MERA screens will find even more unknown stretches of regulatory DNA. Gifford and Sherwood’s experiments didn’t try to cover as much ground around their target genes as they might have, because the researchers assumed that MERA would mostly confirm what was already known. At best, they hoped MERA would rule out some suspected regulatory regions, and help show which regulatory elements have the biggest effect on gene expression.
“We tended to prioritize regions that had been known before,” Sherwood says. “Unfortunately, in the end, our datasets weren’t ideally suited to discovering these UREs.”
Getting to Basic Principles
MERA could open up huge swaths of the regulatory genome to investigation. Compared to an ordinary CRISPR screen, says Sherwood, “there’s only upside,” as MERA is cheaper, easier, and faster to run.
Still, interpreting the results is not trivial. Like other CRISPR screens, MERA makes cuts at precise points in the genome, but does not tell cells to repair those cuts in any particular way. As a result, a population of cells all carrying the same guide RNA can have a huge variety of different gaps and scars in their genomes, typically deletions in the range of 10 to 100 bases long. Gifford and Sherwood created up to 100 cells for each of their guides, and sometimes found that gene expression was affected in some but not all of them; only sequencing the genomes of their mutated cells could reveal exactly what changes had been made.
By repeating these experiments many times, and learning which mutations affect gene expression, it will eventually be possible to pin down the exact DNA bases that make up each regulatory element. Future studies might even be able to distinguish between regulatory elements with small and large effects on gene expression. In Gifford and Sherwood’s MERA screens, the target genes were altered to produce a green fluorescent protein, so the results were read in terms of whether cells gave off fluorescent light. But a more precise, though expensive, approach would be to perform RNA sequencing, to learn which cuts reduced the cell’s ability to transcribe a gene into RNA, and by how much.
A MERA screen offers a rich volume of data on the behavior of the regulatory genome. Yet, as with so much else in genetics, there are few robust principles to let scientists know where they should be focusing their efforts. Histone markers provide only a very rough sketch of regulatory elements, often proving to be red herrings on closer examination. And the existence of UREs, if confirmed by future experiments, shows that we don’t yet even know which areas of the genome to rule out in the hunt for regulatory regions.
“Every dataset we get comes closer and closer to computational principles that let us predict these regions,” says Sherwood. As more studies are conducted, patterns may emerge in the DNA sequences of regulatory elements that link UREs together, or reveal which histone markers truly point toward regulatory effects. There might also be functional clues hidden in these sequences, hinting at what is happening on a molecular level as regulatory elements turn genes on and off in the course of a cell’s development.
For now, however, the data is still rough and disorganized. For better and for worse, high-throughput tools like MERA are becoming the foundation for most discoveries in genetics—and that means there is a lot more work to do before the regulatory genome begins to come into focus.
CORRECTED 2/9/16: Originally, this story incorrectly stated that only certain cell types could be assayed with MERA for reasons related to homologous recombination. In fact, the authors see no reason MERA could not be applied to any in vitro cell line, and hope to perform screens in a wide range of cell types. The text has been edited to correct the error.
Gene Editing for Exon 51: Why CRISPR Snipping might be better than Exon Skipping for DMD
Why CRISPR might be better than exon skipping for DMD: Snipping vs. skipping for DMD
By Lauren Martz, Senior Writer
Published on Thursday, January 21, 2016
As if to preempt the regulatory setbacks in Duchenne muscular dystrophy (DMD) that last week disappointed the field, a trio of preclinical studies emerged two weeks earlier showing that cutting out DMD mutations with gene editing might offer a viable alternative to the exon-skipping strategies that have dominated the pipeline. Now, the question is whether there’s reason to believe the mouse studies will translate any better to the clinic.
The studies, published Dec. 31 in Science, provide in vivo proof of concept for the first time that CRISPR-Cas9 used postnatally can have a disease-modifying effect. Despite the hype around its therapeutic promise, the technology has so far proved itself primarily in research applications, for example, in modifying cells for in vitro screening or creating animal models of disease.
RNA interference (RNAi) silences, or knocks down, the translation of a gene by inducing degradation of a gene target’s transcript. To advance RNAi applications, Thermo Fisher Scientific has developed two types of small RNA molecules: short interfering RNAs and microRNAs. The company also offers products for RNAi analysis in vitro and in vivo, including libraries for high-throughput applications.
Genes can be knocked down with RNA interference (RNAi) or knocked out with CRISPR-Cas9. RNAi, the screening workhorse, knocks down the translation of genes by inducing rapid degradation of a gene target’s transcript.
CRISPR-Cas9, the new but already celebrated genome-editing technology, cleaves specific DNA sequences to render genes inoperative. Although mechanistically different, the two techniques complement one another, and when used together facilitate discovery and validation of scientific findings.
RNAi technologies along with other developments in functional genomics screening were discussed by industry leaders at the recent Discovery on Target conference. The conference, which emphasized the identification and validation of novel drug targets and the exploration of unknown cellular pathways, included a symposium on the development of CRISPR-based therapies.
RNAi screening can be performed in either pooled or arrayed formats. Pooled screening provides an affordable benchtop option, but requires back-end deconvolution and deep sequencing to identify the shRNA causing the specific phenotype. Targets are much easier to identify using the arrayed format since each shRNA clone is in an individual well.
“CRISPR complements RNAi screens,” commented Ryan Raver, Ph.D., global product manager of functional genomics at Sigma-Aldrich. “You can do a whole genome screen with either small interfering RNA (siRNA) or small hairpin RNA (shRNA), then validate with individual CRISPRs to ensure it is a true result.”
A powerful and useful validation method for knockdown or knockout studies is to use lentiviral open reading frames (ORFs) for gene re-expression, for rescue experiments, or to detect whether the wild-type phenotype is restored. However, the ORF randomly integrates into the genome. Also, with this validation technique, gene expression is not acting under the endogenous promoter. Accordingly, physiologically relevant levels of the gene may not be expressed unless controlled for via an inducible system.
In the future, CRISPR activators may provide more efficient ways to express not only wild-type but also mutant forms of genes under the endogenous promoter.
Choice of screening technique depends on the researcher and the research question. Whole gene knockout may be necessary to observe a phenotype, while partial knockdown might be required to investigate functions of essential or lethal genes. Use of both techniques is recommended to identify all potential targets.
For example, recently, a whole genome siRNA screen on a human glioblastoma cell line identified a gene, known as FAT1, as a negative regulator of apoptosis. A CRISPR-mediated knockout of the gene also conferred sensitivity to death receptor–induced apoptosis with an even stronger phenotype, thereby validating FAT1’s new role and link to extrinsic apoptosis, a new model system.
Dr. Raver indicated that next-generation RNAi libraries that are microRNA-adapted might have a more robust knockdown of gene expression, up to 90–95% in some cases. Ultracomplex shRNA libraries help to minimize both false-negative and false-positive rates by targeting each gene with ~25 independent shRNAs and by including thousands of negative-control shRNAs.
Recently, a relevant paper emerged from the laboratory of Jonathan Weissman, Ph.D., a professor of cellular and molecular pharmacology at the University of California, San Francisco. The paper described how a new ultracomplex pooled shRNA library was optimized by means of a microRNA-adapted system. This system, which was able to achieve high specificity in the detection of hit genes, produced robust results. In fact, they were comparable to results obtained with a CRISPR pooled screen. Members of the Weissman group systematically optimized the promoter and microRNA contexts for shRNA expression along with a selection of guide strands.
Using a sublibrary of proteostasis genes (targeting 2,933 genes), the investigators compared CRISPR and RNAi pooled screens. Data showed 48 hits unique to RNAi, 40 unique to CRISPR, and an overlap of 21 hits (with a 5% false discovery rate cut-off). Together, the technologies provided a more complete research story.
Arrayed CRISPR Screens
Click Image To Enlarge +
Synthetic crRNA:tracrRNA reagents can be used in a similar manner to siRNA reagents for assessment of phenotypes in a cell population. Top row: A reporter cell line stably expressing Cas9 nuclease was transfected with GE Dharmacon’s Edit-R synthetic crRNA:tracrRNA system, which was used to target three positive control genes (PSMD7, PSMD14, and VCP) and a negative control gene (PPIB). Green cells indicate EGFP signaling occuring as a result of proteasome pathway disruption. Bottom row: A siGENOME siRNA pool targeting the same genes was used in the same reporter cell line.
“RNA screens are well accepted and will continue to be used, but it is important biologically that researchers step away from the RNA mechanism to further study and validate their hits to eliminate potential bias,” explained Louise Baskin, senior product manager, Dharmacon, part of GE Healthcare. “The natural progression is to adopt CRISPR in the later stages.”
RNAi uses the cell’s endogenous mechanism. All of the components required for gene knockdown are already within the cell, and the delivery of the siRNA starts the process. With the CRISPR gene-editing system, which is derived from a bacterial immune defense system, delivery of both the guide RNA and the Cas9 nuclease, often the rate limiter in terms of knockout efficiency, are required.
In pooled approaches, the cell has to either drop out or overexpress so that it is sortable, limiting the types of addressable biological questions. A CRISPR-arrayed approach opens up the door for use of other analytical tools, such as high-content imaging, to identify hits of interest.
To facilitate use of CRISPR, GE recently introduced Dharmacon Edit-R synthetic CRISPR RNA (crRNA) libraries that can be used to carry out high-throughput arrayed analysis of multiple genes. Rather than a vector- or plasmid-based gRNA to guide the targeting of the Cas9 cleavage, a synthetic crRNA and tracrRNA are used. These algorithm-designed crRNA reagents can be delivered into the cells very much like siRNA, opening up the capability to screen multiple target regions for many different genes simultaneously.
GE showed a very strong overlap between CRISPR and RNAi using this arrayed approach to validate RNAi screen hits with synthetic crRNA. The data concluded that CRISPR can be used for medium- or high-throughput validation of knockdown studies.
“We will continue to see a lot of cooperation between RNAi and gene editing,” declared Baskin. “Using the CRISPR mechanism to knockin could introduce mutations to help understand gene function at a much deeper level, including a more thorough functional analysis of noncoding genes.
“These regulatory RNAs often act in the nucleus to control translation and transcription, so to knockdown these genes with RNAi would require export to the cytoplasm. Precision gene editing, which takes place in the nucleus, will help us understand the noncoding transcriptome and dive deeper into how those genes regulate disease progression, cellular development and other aspects of human health and biology.”
Tool Selection
Click Image To Enlarge +
Schematic of a pooled shRNA screening workflow developed by Transomic Technologies. Cells are transduced, and positive or negative selection screens are performed. PCR amplification and sequencing of the shRNA integrated into the target cell genome allows the determination of shRNA representation in the population.
The functional genomics tool should fit the specific biology; the biology should not be forced to fit the tool. Points to consider include the regulation of expression, the cell line or model system, as well as assay scale and design. For example, there may be a need for regulatable expression. There may be limitations around the cell line or model system. And assay scale and design may include delivery conditions and timing to optimally complete perturbation and reporting.
“Both RNAi- and CRISPR-based gene modulation strategies have pros and cons that should be considered based on the biology of the genes being studied,” commented Gwen Fewell, Ph.D., chief commercial officer, Transomic Technologies.
RNAi reagents, which can produce hypomorphic or transient gene-suppression states, are well known for their use in probing drug targets. In addition, these reagents are enriching studies of gene function. CRISPR-Cas9 reagents, which produce clean heterozygous and null mutations, are important for studying tumor suppressors and other genes where complete loss of function is desired.
Timing to readout the effects of gene perturbation must be considered to ensure that the biological assay is feasible. RNAi gene knockdown effects can be seen in as little as 24–72 hours, and inducible and reversible gene knockdown can be realized. CRISPR-based gene knockout effects may become complete and permanent only after 10 days.
Both RNAi and CRISPR reagents work well for pooled positive selection screens; however, for negative selection screens, RNAi is the more mature tool. Current versions of CRISPR pooled reagents can produce mixed populations containing a fraction of non-null mutations, which can reduce the overall accuracy of the readout.
To meet the needs of varied and complex biological questions, Transomic Technologies has developed both RNAi and CRISPR tools with options for optimal expression, selection, and assay scale. For example, the company’s shERWOOD-UltramiR shRNA reagents incorporate advances in design and small RNA processing to produce increased potency and specificity of knockdown, particularly important for pooled screens.
Sequence-verified pooled shRNA screening libraries provide flexibility in promoter choice, in vitro formats, in vivo formats, and a choice of viral vectors for optimal delivery and expression in biologically relevant cell lines, primary cells or in vivo.
The company’s line of lentiviral-based CRISPR-Cas9 reagents has variable selectable markers such that guide RNA- and Cas9-expressing vectors, including inducible Cas9, can be co-delivered and selected for in the same cell to increase editing efficiency. Promoter options are available to ensure expression across a range of cell types.
“Researchers are using RNAi and CRISPR reagents individually and in combination as cross-validation tools, or to engineer CRISPR-based models to perform RNAi-based assays,” informs Dr. Fewell. “Most exciting are parallel CRISPR and RNAi screens that have tremendous potential to uncover novel biology.”
Converging Technologies
The convergence of RNAi technology with genome-editing tools, such as CRISPR-Cas9 and transcription activator-like effector nucleases, combined with next-generation sequencing will allow researchers to dissect biological systems in a way not previously possible.
“From a purely technical standpoint, the challenges for traditional RNAi screens come down to efficient delivery of the RNAi reagents and having those reagents provide significant, consistent, and lasting knockdown of the target mRNAs,” states Ross Whittaker, Ph.D., a product manager for genome editing products at Thermo Fisher Scientific. “We have approached these challenges with a series of reagents and siRNA libraries designed to increase the success of RNAi screens.”
Thermo Fisher’ provides lipid-transfection RNAiMax reagents, which effectively deliver siRNA. In addition, the company’s Silencer and Silencer Select siRNA libraries provide consistent and significant knockdown of the target mRNAs. These siRNA libraries utilize highly stringent bioinformatic designs that ensure accurate and potent targeting for gene-silencing studies. The Silencer Select technology adds a higher level of efficacy and specificity due to chemical modifications with locked nucleic acid (LNA) chemistry.
The libraries alleviate concerns for false-positive or false-negative data. The high potency allows less reagent use; thus, more screens or validations can be conducted per library.
Dr. Whittaker believes that researchers will migrate regularly between RNAi and CRISPR-Cas9 technology in the future. CRISPR-Cas9 will be used to create engineered cell lines not only to validate RNAi hits but also to follow up on the underlying mechanisms. Cell lines engineered with CRISPR-Cas9 will be utilized in RNAi screens. In the long term, CRISPR-Cas9 screening will likely replace RNAi screening in many cases, especially with the introduction of arrayed CRISPR libraries.
Validating Antibodies with RNAi
Unreliable antibody specificity is a widespread problem for researchers, but RNAi is assuaging scientists’ concerns as a validation method.
The procedure introduces short hairpin RNAs (shRNAs) to reduce expression levels of a targeted protein. The associated antibody follows. With its protein knocked down, a truly specific antibody shows dramatically reduced or no signal on a Western blot. Short of knockout animal models, RNAi is arguably the most effective method of validating research antibodies.
The method is not common among antibody suppliers—time and cost being the chief barriers to its adoption, although some companies are beginning to embrace RNAi validation.
“In the interest of fostering better science, Proteintech felt it was necessary to implement this practice,” said Jason Li, Ph.D., founder and CEO of Proteintech Group, which made RNAi standard protocol in February 2015. “When researchers can depend on reproducibility, they execute more thorough experiments and advance the treatment of human diseases and conditions.”
Junk DNA Kept in Good Repair by Nuclear Membrane
Heterochromatin has the dubious distinction of being called the “dark matter” of DNA, and it has even suffered the indignity of being dismissed as “junk DNA.” But it seems to get more respectful treatment inside the nucleus, where it has the benefit of a special repair mechanism. This mechanism, discovered by scientists based at the University of Southern California (USC), transports broken heterochromatin sequences from the hurly-burly of the heterochromatin domain so that they can be repaired in the relative peace and quiet of the nuclear periphery.
This finding suggests that the nuclear membrane is more versatile than is generally appreciated. Yes, it serves as a protective container for nuclear material, and it uses its pores to manage the transport of molecules in and out of the nucleus. But it may also play a special role in maintaining the integrity of heterochromatin, which tends to be overlooked because it consists largely of noncoding DNA, including repetitive stretches of no apparent function.
“Scientists are now starting to pay a lot of attention to this mysterious component of the genome,” said Irene E. Chiolo, Ph.D., an assistant professor at USC. “Heterochromatin is not only essential for chromosome maintenance during cell division; it also poses specific threats to genome stability. Heterochromatin is potentially one of the most powerful driving forces for cancer formation, but it is the ‘dark matter’ of the genome. We are just beginning to unravel how repair works here.”
Dr. Chilo led an effort to understand how heterochromatin stays in good repair, even though it is particularly vulnerable to a kind of repair error called ectopic recombination. This kind of error is apt to occur when flaws in repeated sequences undergo homologous recombination (HR) by means of double-strand break (DSB) repair. Specifically, repeated sequences tend to recombine with each other during DNA repair.
Working with the fruit fly Drosophila melanogaster, Dr. Chilo’s team observed that breaks in heterochromatin are repaired after damaged sequences move away from the rest of the chromosome to the inner wall of the nuclear membrane. There, a trio of proteins mends the break in a safe environment, where it cannot accidentally get tangled up with incorrect chromosomes.
The details appeared October 26 in Nature Cell Biology, in an article entitled, “Heterochromatic breaks move to the nuclear periphery to continue recombinational repair.”
“[Heterochromatic] DSBs move to the nuclear periphery to continue HR repair,” the authors wrote. “Relocalization depends on nuclear pores and inner nuclear membrane proteins (INMPs) that anchor repair sites to the nuclear periphery through the Smc5/6-interacting proteins STUbL/RENi. Both the initial block to HR progression inside the heterochromatin domain, and the targeting of repair sites to the nuclear periphery, rely on SUMO and SUMO E3 ligases.”
“We knew that nuclear membrane dysfunctions are common in cancer cells,” Dr. Chiolo said. “Our studies now suggest how these dysfunctions can affect heterochromatin repair and have a causative role in cancer progression.”
This study may help reveal how and why organisms become more predisposed to cancer as they age—the nuclear membrane progressively deteriorates as an organism ages, removing this bulwark against genome instability.
Next, Dr. Chiolo and her team will explore how the movement of broken sequences is accomplished and regulated, and what happens in cells and organisms when this membrane-based repair mechanism fails. Their ultimate goal is to understand how this mechanism functions in human cells and identify new strategies to prevent their catastrophic failure and cancer formation.
Gene Found that Regulates Stem Cell Number Production
The gene Prkci promotes the generation of differentiated cells (red). However if Prkci activity is reduced or absent, neural stem cells (green) are promoted. [In Kyoung Mah]
A scientific team from the University of Southern California (USC) and the University of California, San Diego have described an important gene that maintains a critical balance between producing too many and too few stem cells. Called Prkci, the gene influences whether stem cells self-renew to produce more stem cells, or differentiate into more specialized cell types, such as blood or nerves.
When it comes to stem cells, too much of a good thing isn’t necessarily a benefit: producing too many new stem cells may lead to cancer; making too few inhibits the repair and maintenance of the body.
In their experiments, the researchers grew mouse embryonic stem cells, which lacked Prkci, into embryo-like structures in the laboratory. Without Prkci, the stem cells favored self-renewal, generating large numbers of stem cells and, subsequently, an abundance of secondary structures.
Upon closer inspection, the stem cells lacking Prkci had many activated genes typical of stem cells, and some activated genes typical of neural, cardiac, and blood-forming cells. Therefore, the loss of Prkci can also encourage stem cells to differentiate into the progenitor cells that form neurons, heart muscle, and blood.
Prkci achieves these effects by activating or deactivating a well-known group of interacting genes that are part of the Notch signaling pathway. In the absence of Prkci, the Notch pathway produces a protein that signals to stem cells to make more stem cells. In the presence of Prkci, the Notch pathway remains silent, and stem cells differentiate into specific cell types.
These findings have implications for developing patient therapies. Even though Prkci can be active in certain skin cancers, inhibiting it might lead to unintended consequences, such as tumor overgrowth. However, for patients with certain injuries or diseases, it could be therapeutic to use small molecule inhibitors to block the activity of Prkci, thus boosting stem cell production.
“We expect that our findings will be applicable in diverse contexts and make it possible to easily generate stem cells that have typically been difficult to generate,” said Francesca Mariani, Ph.D., principal investigator at the Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research at USC.
Their study (“Atypical PKC-iota Controls Stem Cell Expansion via Regulation of the Notch Pathway”) was published in a Stem Cell Reports.
Atypical PKC-iota Controls Stem Cell Expansion via Regulation of the Notch Pathway
In Kyoung Mah,1 Rachel Soloff,2,3 Stephen M. Hedrick,2 and Francesca V. Mariani1, *
The number of stem/progenitor cells available can profoundly impact tissue homeostasis and the response to injury or disease. Here, we propose that an atypical PKC, Prkci, is a key player in regulating the switch from an expansion to a differentiation/maintenance phase via regulation of Notch, thus linking the polarity pathway with the control of stem cell self-renewal. Prkci is known to influence symmetric cell division in invertebrates; however a definitive role in mammals has not yet emerged. Using a genetic approach, we find that loss of Prkci results in a marked increase in the number of various stem/progenitor cells. The mechanism used likely involves inactivation and symmetric localization of NUMB, leading to the activation of NOTCH1 and its downstream effectors. Inhibition of atypical PKCs may be useful for boosting the production of pluripotent stem cells, multipotent stem cells, or possibly even primordial germ cells by promoting the stem cell/progenitor fate.
The control of asymmetric versus symmetric cell division in stem and progenitor cells balances self-renewal and differentiation to mediate tissue homeostasis and repair and involves key proteins that control cell polarity. In the case of excess symmetric division, too many stem-cell-like daughter cells are generated that can lead to tumor initiation and growth. Conversely, excess asymmetric cell division can severely limit the number of cells available for homeostasis and repair (Go´mez-Lo´pez et al., 2014; Inaba and Yamashita, 2012). The Notch pathway has been implicated in controlling stem cell self-renewal in a number of different contexts (Hori et al., 2013). However, how cell polarity, asymmetric cell division, and the activation of determinants ultimately impinges upon the control of stem cell expansion and maintenance is not fully understood. In this study, we examine the role of an atypical protein kinase C (aPKC), PRKCi, in stem cell self-renewal and, in particular, determine whether PRKCi acts via the Notch pathway. PKCs are serine-threonine kinases that control many basic cellular processes and are typically classified into three subgroups—conventional, novel, and the aPKCs iota and zeta, which, in contrast to the others, are not activated by diacylglyceride or calcium. The aPKC proteins are best known for being central components of an evolutionarily conserved Par3-Par6-aPKC trimeric complex that controls cell polarity in C. elegans, Drosophila, Xenopus, zebrafish, and mammalian cells (Suzuki and Ohno, 2006).
Before Notch influences stem cell self-renewal, the regulation of cell polarity, asymmetric versus symmetric cell division, and the segregation of cell fate determinants such as NUMB may first be required (Knoblich, 2008). For example, mutational analysis in Drosophila has demonstrated that the aPKC-containing trimeric complex is required for maintaining polarity and for mediating asymmetric cell division during neurogenesis via activation and segregation of NUMB (Wirtz-Peitz et al., 2008). NUMB then functions as a cell fate determinant by inhibiting Notch signaling and preventing self-renewal (Wang et al., 2006). In mammals, the PAR3-PAR6-aPKC complex also can bind and phosphorylate NUMB in epithelial cells and can regulate the unequal distribution of Numb during asymmetric cell division (Smith et al., 2007). During mammalian neurogenesis, asymmetric division is also thought to involve the PAR3-PAR6-aPKC complex, NUMB segregation, and NOTCH activation (Bultje et al., 2009).
Mice deficient in Prkcz are grossly normal, with mild defects in secondary lymphoid organs (Leitges et al., 2001). In contrast, deficiency of the Prkci isozyme results in early embryonic lethality at embryonic day (E)9.5 (Seidl et al., 2013; Soloff et al., 2004). A few studies have investigated the conditional inactivation of Prkci; however, no dramatic changes in progenitor generation were detected in hematopoietic stem cells (HSCs) or the brain (Imai et al., 2006; Sengupta et al., 2011), although one study found evidence of a role for Prkci in controlling asymmetric cell division in the skin (Niessen et al., 2013). Analysis may be complicated by functional redundancy between the iota and zeta isoforms and/or because further studies perturbing aPKCs in specific cell lineages and/or at specific developmental stages are needed.
Here, we investigate the requirement of Prkci in mouse cells using an in vitro system that bypasses early embryonic lethality. Embryonic stem (ES) cells are used to make embryoid bodies (EBs) that develop like the early post-implantation embryo in terms of lineage specification and morphology and can also be maintained in culture long enough to observe advanced stages of cellular differentiation (Desbaillets et al., 2000). Using this approach, we provide genetic evidence that inactivation of Prkci signaling leads to enhanced generation of pluripotent cells and some types of multipotent stem cells, including cells with primordial germ cell (PGC) characteristics. In addition, we provide evidence that aPKCs ultimately regulate stem cell fate via the Notch pathway.
Figure 1. Prkci/ EBs Contain Cells with Pluripotency Characteristics (A and A0 ) Day (d) 12 heterozygous EBs have few OCT4/E-CAD+ cells, while null EBs contain many in clusters at the EB periphery. Inset: OCT4 (nucleus)/E-CAD (cytoplasm) double-positive cells. (B and B0 ) Adjacent sections in a null EB show that OCT4+ cells are likely also SSEA1+. (C) Dissociated day-12 Prkci/ EBs contain five to six times more OCT4+ and approximately three times more SSEA1+ cells than heterozygous EBs (three independent experiments). (D and D0 ) After 2 days in ES cell culture, no colonies are visible in null SSEA1 cultures while present in null SSEA1+ cultures (red arrows). (E–E00) SSEA1+ sorted cells can be maintained for many passages, 27+. (E) Prkci+/ sorted cells make colonies with differentiated cells at the outer edges (n = 27/35). (E0 ) Null cells form colonies with distinct edges (n = 39/45). (E00) The percentage of undifferentiated colonies is shown. ***p < 0.001. (F) Sorted null cells express stem cell and differentiation markers at similar levels to normal ES cells (versus heterozygous EBs) (three independent experiments). (G) EBs made from null SSEA1+ sorted cells express germ layer marker genes at the indicated days. Error bars indicate mean ± SEM, three independent experiments. Scale bars, 100 mm in (A, D, and E); 25 mm in (B). See also Figure S1.
RESULTS
Prkci/ Cultures Have More Pluripotent Cells Even under Differentiation Conditions First, we compared Prkci null EB development to that of Prkci/ embryos. Consistent with another null allele (Seidl et al., 2013), both null embryos and EBs fail to properly cavitate (Figures S1A and S1B). The failure to cavitate is unlikely to be due to the inability to form one of the three germ layers, as null EBs express germ-layer-specific genes (Figure S1E). A failure of cavitation could alternatively be caused by an accumulation of pluripotent cells. For example, EBs generated from Timeless knockdown cells do not cavitate and contain large numbers of OCT4-expressing cells (O’Reilly et al., 2011). In addition, EBs generated with Prkcz isoform knockdown cells contain OCT4+ cells under differentiation conditions (Dutta et al., 2011; Rajendran et al., 2013). Thus, we first evaluated ES colony differentiation by alkaline phosphatase (AP) staining. After 4 days without leukemia inhibitory factor (LIF), Prkci/ ES cell colonies retained crisp boundaries and strong AP staining. In contrast, Prkci+/ colonies had uneven colony boundaries with diffuse AP staining (Figures S1F–S1F00). To definitively detect pluripotent cells, day-12 EBs were assayed for OCT4 and E-CADHERIN (E-CAD) protein expression. Prkci+/ EBs had very few OCT4/E-CAD double-positive cells (Figure 1A); however, null EBs contained large clusters of OCT4/E-CAD double-positive cells, concentrated in a peripheral zone (Figure 1A0 ). By examining adjacent sections, we found that OCT4+ cells could also be positive for stage-specific embryonic antigen 1 (SSEA1) (Figures 1B and 1B0 ). Quantification by fluorescence-activated cell sorting (FACS) analysis showed that day-12 Prkci/ EBs had more OCT4+ and SSEA1+ cells than Prkci+/ EBs (Figure 1C). We did not find any difference between heterozygous and wild-type cells with respect to the number of OCT4+ or SSEA1+ cells or in their levels of expression for Oct4, Nanog, and Sox2 (Figures S1I, S1I0 and S1J). However, we did find that Oct4, Nanog, and Sox2 were highly upregulated in OCT4+ null cells (Figure S1G). Thus, together, these data indicate that Prkci/ EBs contain large numbers of pluripotent stem cells, despite being cultured under differentiation conditions.
Functional Pluripotency Tests If primary EBs have a pluripotent population with the capacity to undergo self-renewal, they can easily form secondary EBs (O’Reilly et al., 2011). Using this assay, we found that more secondary EBs could be generated from Prkci/ versus Prkci+/ EBs, especially at days 6, 10, and 16; even when plated at a low density to control for aggregation (Figure S1H). To test whether SSEA1+ cells could maintain pluripotency long term, FACS-sorted Prkci/ SSEA1+ and SSEA1 cells were plated at a low density and maintained under ES cell culture conditions. SSEA1 cells were never able to form identifiable colonies and could not be maintained in culture (Figure 1D). SSEA1+ cells, however, formed many distinct colonies after 2 days of culture, and these cells could be maintained for over 27 passages (Figures 1D0 , 1E0 , and 1E00). Prkci+/ SSEA1+ cells formed colonies that easily differentiated at the outer edge, even in the presence of LIF (Figure 1E). In contrast Prkci/ SSEA1+ cells maintained distinct round colonies (Figure 1E0 ). Next, we determined whether null SSEA1+ cells expressed pluripotency and differentiation markers similarly to normal ES cells. Indeed, we found that Oct4, Nanog, and Sox2 were upregulated in both null SSEA1+ EB cells and heterozygous ES cells. In addition, differentiated markers (Fgf5, T, Wnt3, and Afp) and tissue stem/progenitor cell markers (neural: Nestin, Sox1, and NeuroD; cardiac: Nkx2-5 and Isl1; and hematopoietic: Gata1 and Hba-x) were downregulated in both SSEA1+ cells and heterozygous ES cells (Figure 1F). SSEA1+ cells likely have a wide range of potential, since EBs generated from these cells expressed markers for all three germ layers (Figure 1G).
Figure 2. Prkci and Pluripotency Pathways (A) ERK1/2 phosphorylation (Y202/Y204) is reduced in null ES cells and early day (d)-6 null EBs compared to heterozygous EBs and strongly increased at later stages. The first lane shows ES cells activated (A) by serum treatment 1 day after serum depletion. (B) Quantification of pERK1/2 normalized to non-phosphorylated ERK1/2 (three independent experiments; mean ± SEM; **p < 0.01). (C) pERK1/2 Y202/Y204 is strongly expressed in the columnar epithelium of heterozygous EBs that have just cavitated. Null EBs have lower expression. OCT4 and pERK1/2 expression do not co-localize. Scale bar, 100 mm. (D) pERK1/2Y202/Y204 levels are lower in null SSEA1+ sorted cells than in heterozygous or in null day-12 EBs that have undergone further differentiation. pSTAT3 and STAT levels are unchanged. See also Figure S2.
ERK1/2 Signaling during EB Development Stem cell self-renewal has been shown to require the activation of the JAK/STAT3 and PI3K/AKT pathways and the inhibition of ERK1/2 and GSK3 pathways (Kunath et al., 2007; Niwa et al., 1998; Sato et al., 2004; Watanabe et al., 2006). We found that both STAT3 and phosphorylated STAT3 levels were not grossly altered and that the p-STAT3/STAT3 ratio was similar between heterozygous and null ES cells and EBs (Figures S2A and S2B). In addition we did not see any difference in AKT, pAKT, or b-CATENIN levels when comparing heterozygous to null ES cells or EBs (Figures S2A and S2C). Thus, the effects observed by the loss of Prkci are unlikely to be due to a significant alteration in the JAK/STAT3, PI3K/AKT, or GSK3 pathways.
Next, we investigated ERK1/2 expression and activation. Consistent with other studies showing ERK1/2 activation to be downstream of Prkci in some mammalian cell types (Boeckeler et al., 2010; Litherland et al., 2010), pERK1/2 was markedly inactivated in Prkci null versus heterozygous ES cells. In addition, during differentiation, null EBs displayed strong pERK1/2 inhibition early (until day 6). Later, pERK1/2 was activated strongly, as the EB began differentiating (Figures 2A and 2B). By immunofluorescence, pERK1/2 was strongly enriched in the columnar epithelium of control EBs, while overall levels were much lower in Prkci/ EBs (Figure 2C). In addition, high OCT4 expression correlated with a marked inactivation of pERK1/2 (Figure 2C). Next, we examined Prkci/ SSEA1+ cells by western blot. We found that SSEA1+ cells isolated from day-12 null EBs had pSTAT3 expression levels similar to whole EBs, while pERK1/2 levels were low (Figure 2D). Thus, these experiments indicate that the higher numbers of pluripotent cells in null EBs correlate with a strong inactivation of ERK1/2.
Neural Stem Cell Fate Is Favored in Prkci/ EBs It is well known that ERK/MEK inhibition is not sufficient for pluripotent stem cell maintenance (Ying et al., 2008); thus, other pathways are likely involved. Therefore, we used a TaqMan Mouse Stem Cell Pluripotency Panel (#4385363) on an OpenArray platform to investigate the mechanism of Prkci action. Day 13 and day 20 Prkci/ EBs expressed high levels of pluripotency and stemness markers versus heterozygous EBs, including Oct4, Utf1, Nodal, Xist, Fgf4, Gal, Lefty1, and Lefty2. However, interestingly, EBs also expressed markers for differentiated cell types and tissue stem cells, including Sst, Syp, and Sycp3 (neural-related genes), Isl1 (cardiac progenitor marker), Hba-x, and Cd34 (hematopoietic markers). Based on this first-pass test, we sought to determine whether loss of Prkci might favor the generation of neural, cardiac, and hematopoietic cell types and/or their progenitors.
Figure 3. Neural Stem Cell Populations Are Increased in Null EBs (A–C0 ) Prkci/ EBs (B) have more NESTINpositive cells than Prkci+/ EBs (A). (C and C0 ) MAP2 and TUJ1 are expressed in null EBs, similarly to heterozygous EBs (data not shown). (D) EBs were assessed for PAX6 expression, and the images were used for quantification (Figures S3A and S3B). The pixel count ratio of PAX6+ cells in null EBs (green) is substantially higher than that found in heterozygous EBs (black) (three independent experiments; mean ± SEM; *p < 0.05). (E–F000) Day 4 after RA treatment, Prkci/ EBs have more NESTIN- than TUJ1-positive neurons (E and F). However, null cells can still terminally differentiate into NEUROD-, NEUN-, and MAP2-positive cells (F0 –F000). Scale bars, 25 mm in (A and C) and 50 mm in (E). See also Figure S3. Ste
The Generation of Cardiomyocyte and Erythrocyte Progenitors Is Also Favored Next, we examined ISL1 expression (a cardiac stem cell marker) by immunofluorescence and found that Prkci/ EBs contained larger ISL1 clusters compared with Prkci+/ EBs; this was confirmed using an image quantification assay (Figures 4A, 4A0 , and 4C). Differentiated cardiac cells and ventral spinal neurons can also express ISL1 (Ericson et al., 1992); therefore, we also examined Nkx2-5 expression, a better stem cell marker and regulator of cardiac progenitor determination (Brown et al., 2004), by RT-PCR and immunofluorescence. In null EBs, Nkx2-5 was upregulated (Figure 4D). In addition, in response to RA, which can promote cardiac fates in vitro (Niebruegge et al., 2008), cells expressing NKX2-5 were more prevalent in null versus heterozygous EBs (Figures 4B and 4B0 ).The abundant cardiac progenitors found in null EBs were still capable of undergoing differentiation (Figures 4E–4F0 ).
Figure 4. Cardiomyocyte and Erythrocyte Progenitors Are Increased in Prkci/ EBs (A–F0 ) In (A, A0 , E, and E0 ), Prkci/ EBs cultured without LIF have more ISL1 (cardiac progenitor marker) and a-ACTININ-positive cells compared to heterozygous EBs. (C) At day (d) 9, the pixel count ratio for ISL1 expression indicates that null EBs (green) have larger ISL1 populations than heterozygous EBs (black) (three independent experiments, n = 20 heterozygous EBs, 21 null EBs total; mean ± SEM; *p < 0.05). In (B, B0 , D, F, and F0 ), RA treatment induces more NKX2-5 (both nuclear and cytoplasmic) and a-ACTININ expression in null EBs. Arrows point to fibers in (F0 ). (G) Null EBs (green) generate more beating EBs with RA treatment compared to heterozygous EBs (black) (four independent experiments; mean ± SEM; *p < 0.05, ***p < 0.001). (H) Dissociated null EBs of different stages (green) generate more erythrocytes in a colony-forming assay (CFU-E) (four independent experiments; mean ± SEM; **p < 0.01). (I) Examples of red colonies. (J) Gene expression for primitive HSC markers is upregulated in null EBs (relative to heterozygous EBs) (three independent experiments; mean ± SEM). Scale bars, 50 mm in (A, B, and E); 100 mm in (F), and 25 mm in (I). See also Figure S4. 6
Hba-x expression is restricted to yolk sac blood islands and primitive erythrocyte populations (Lux et al., 2008; Trimborn et al., 1999). Cd34 is also a primitive HSC marker (Sutherland et al., 1992). Next, we determined whether the elevated expression of these markers observed with OpenArray might represent higher numbers of primitive hematopoietic progenitors. Using a colony-forming assay (Baum et al., 1992), we found that red colonies (indicative of erythrocyte differentiation; examples in Figure 4I) were produced significantly earlier and more readily from cells isolated from null versus heterozygous EBs (Figure 4H). By quantitative real-time PCR, upregulation of Hba-x and Cd34 genes confirmed the OpenArray results (Figure 4J). In addition, we found Gata1, an erythropoiesis-specific factor, and Epor, an erythropoietin receptor that mediates erythroid cell proliferation and differentiation (Chiba et al., 1991), to be highly upregulated in null versus heterozygous EBs (Figure 4J). These data suggest that the loss of Prkci promotes the generation of primitive erythroid progenitors that can differentiate into erythrocytes.
To determine whether the aforementioned tissue stem cells identified were represented in the OCT4+ population that we described earlier, we examined the expression of PAX6, ISL1, and OCT4 in adjacent EB sections. We found that cells expressing OCT4 appeared to represent a distinct population from those expressing PAX6 and ISL1 (although some cells were PAX6 and ISL1 double-positive) (Figures S4A–S4C).
Prkci/ Cells Are More Likely to Inherit NUMB/aNOTCH1 Symmetrically The enhanced production of both pluripotent and tissue stem cells suggests that the mechanism underlying the action of Prkci in these different contexts is fundamentally similar. Because the Notch pathway controls stem cell self-renewal in many contexts (Hori et al., 2013), and because previous studies implicated a connection between PRKCi function and the Notch pathway (Bultje et al., 2009; Smith et al., 2007), we examined the localization and activation of a key player in the Notch pathway, NUMB, (Inaba and Yamashita, 2012). Differences in NUMB expression were first evident in whole EBs, where polarized expression was evident in the ectodermal and endodermal epithelia of heterozygous EBs, while Prkci/ EBs exhibited a more even distribution (Figures 5A–5B0 ). To more definitively determine the inheritance of NUMB during cell division, doublets undergoing telophase or cytokinesis were scored for symmetric (evenly distributed in both cells) or asymmetric (unequally distributed) NUMB localization (examples: Figures 5C and 5C0 ).
Because NUMB can be directly phosphorylated by aPKCs (both PRKCi and PRKCz) (Smith et al., 2007; Zhou et al., 2011), loss of Prkci might be expected to lead to decreased NUMB phosphorylation. Three NUMB phosphorylation sites—Ser7, Ser276, and Ser295—could be aPKC mediated (Smith et al., 2007). By immunofluorescence, we found that one of the most well-characterized sites (Ser276), was strongly inactivated in null versus heterozygous EBs, especially in the core (Figures 5F and 5G). Western analysis also confirmed that the levels of pNUMB (Ser276) were decreased in null versus heterozygous EBs (Figure S5F). Thus, genetic inactivation of Prkci leads to a marked decrease in the phosphorylation status of NUMB.
Notch pathway inhibition by NUMB has been observed in flies and mammals (Berdnik et al., 2002; French et al., 2002). Therefore, we investigated whether reduced Numb activity in Prkci/ EBs might lead to enhanced NOTCH1 activity and the upregulation of the downstream transcriptional readouts (Meier-Stiegen et al., 2010). An overall increase in NOTCH1 activation was supported by western blot analysis showing that the level of activated NOTCH1 (aNOTCH1) was strongly increased in day 6 and day 10 null versus heterozygous EBs (Figure S5G). This was supported by immunofluorescence in EBs, where widespread strong expression of aNOTCH1 was seen in most null cells (Figures 5I and 5I0 ), while in heterozygous EBs, this pattern was observed only in the OCT4+ cells (Figures 5H and 5H0 ).
Figure 5. Prkci/ Cells Preferentially Inherit Symmetric Localization of NUMB and aNOTCH1 and Notch Signaling Is Required for Stem Cell Self-Renewal in Null Cells (A–B0 ) In (A and B), day (d)-7 heterozygous EBs have polarized NUMB localization within epithelia and strong expression in the endoderm, while null EBs have a more even distribution. (A0 and B0 ) Enlarged views. (C and C0 ) Asymmetric and symmetric NUMB expression examples. (D) Doublets from day-10 null EBs have more symmetric inheritance when compared to day-10 heterozygous doublets (three independent experiments; mean ± SEM; **p < 0.01). A red line indicates a ratio of 1 (equal percent symmetric and asymmetric). (E) CD24high null doublets exhibited more symmetric NUMB inheritance than CD24high heterozygous doublets (three independent experiments; mean ± SEM; *p < 0.05). A red line indicates where the ratio is 1. (F and G) Decreased pNUMB (Ser276) is evident in the core of null versus heterozygous EBs (n = 10 of each genotype). (H–I0 ) In (H and I), aNOTCH1 is strongly expressed in heterozygous EBs, including both OCT4+ and OCT4 cells, while strong aNOTCH1 expression is predominant in OCT4+ cells of null EBs (n = 10 of each genotype)). (H0 and I0 ) Enlarged views of boxed regions. OCT4+ cells are demarcated with dotted lines. (J and J0 ) OCT4+ cells express HES5 strongly in the nucleus (three independent experiments). (K) Null doublets from dissociated EBs have more symmetric aNOTCH1 inheritance compared to heterozygous doublets (three independent experiments; mean ± SEM; **p < 0.01). A red line indicates where the ratio is 1. (L) CD24high Prkci/ doublets exhibit more symmetric aNOTCH1 than CD24high heterozygous doublets (three independent experiments; mean ± SEM; *p < 0.05). A red line indicates where the ratio is 1. (M and M0 ) Examples of asymmetric and symmetric aNOTCH1 localization. (N and O) Day-3 DMSO-treated null ES colonies show strong AP staining all the way to the colony edge in (N). Treatment with 3 mM DAPT led to more differentiation in (O). (P–R) OCT4 is strongly expressed in day-4 DMSO-treated null ES cultures (P). With DAPT (Q,R), OCT4 expression is decreased. (S) Working model: In daughter cells that undergo differentiation, PRKCi can associate with PAR3 and PAR6. NUMB is recruited and directly phosphorylated. The activation of NUMB then leads to an inhibition in NOTCH1 activation and stimulation of a differentiation/maintenance program. In the absence of Prkci, the PAR3/PAR6 complex cannot assemble (although it may do so minimally with Prkcz). NUMB asymmetric localization and phosphorylation is reduced. Low levels of pNUMB are not sufficient to block NOTCH1 activation, and activated NOTCH1 preserves the stem cell self-renewal program. We suggest that PRKCi functions to drive differentiation by pushing the switch from an expansion phase that is symmetric to a differentiation and/or maintenance phase that is predominantly asymmetric. In situations of low or absent PRKCi, we propose that the expansion phase is prolonged. Scale bars, 50 mm in (A, B, F, G, H, I, J, J0 , P–R); 200 mm in (A0 and B0 ); 25 mm in (C, C0 , M, and M0 ); and 100 mm in (H0 , I0 , N, and O). See also Figure S5.
Figure 6. Additional Inhibition of PRKCz Results in an Even Higher Percentage of OCT4-, SSEA1-, and STELLA-Positive Cells (A and A0 ) After day 4 without LIF, heterozygous ES cells undergo differentiation in the presence of Go¨6983, while null ES cells stay as distinct colonies in (A0 ). (B and B0 ) Go¨6983 stimulates an increase in OCT4+ populations in heterozygous EBs and an even larger OCT4+ population in null EBs in (B0 , insets: green and red channels separately). (C–D0 ) An even higher percentage of cells are OCT4+ (C and C0 ) and SSEA1+ (D and D0 ) with Go¨6983 treatment (day 12, three independent experiments). (E and F) More STELLA+ clusters containing a larger number of cells are present in drugtreated heterozygous EBs. (G and H) Null EBs also have more STELLA+ clusters and cells. Drug-treated null EBs exhibit a dramatic increase in the number of STELLA+ cells. (I–K) Some cells are double positive for STELLA and VASA in drug-treated null EBs (yellow arrows). There are also VASAonly (green arrows) and STELLA-only cells (red arrows) (three independent experiments). (L–P) Treatment with ZIP results in an increase in OCT4+ and STELLA+ cells. ZIP treatment also results in more cells that are VASA+ (three independent experiments); n = 11 for Prkci+/, and n = 13 for Prkci+/ + ZIP; n = 14 for Prkci/, and n = 20 for Prkci/ + ZIP; eight EBs assayed for both STELLA and VASA expression). Scale bars, 100 mm in (A and A0 ); 50 mm in (B and B0 ); and 25 mm in (E, I, and L).
DISCUSSION In this report, we suggest that Prkci controls the balance between stem cell expansion and differentiation/maintenance by regulating the activation of NUMB, NOTCH1, and Hes /Hey downstream effector genes. In the absence of Prkci, the pluripotent cell fate is favored, even without LIF, yet cells still retain a broad capacity to differentiate. In addition, loss of Prkci results in enhanced generation of tissue progenitors such as neural stem cells and cardiomyocyte and erythrocyte progenitors. In contrast to recent findings on Prkcz (Dutta et al., 2011), loss of Prkci does not appear to influence STAT3, AKT, or GSK3 signaling but results in decreased ERK1/2 activation. We hypothesize that, in the absence of Prkci, although ERK1/2 inhibition may be involved, it is the decreased NUMB phosphorylation and increased NOTCH1 activation that promotes stem and progenitor cell fate. Thus, we conclude that PRKCi, a protein known to be required for cell polarity, also plays an essential role in controlling stem cell fate and generation via regulating NOTCH1 activation.
Notch Activation Drives the Decision to Self-Renew versus Differentiate Notch plays an important role in balancing stem cell selfrenewal and differentiation in a variety of stem cell types and may be one of the key downstream effectors of Prkci signaling. Sustained Notch1 activity in embryonic neural progenitors has been shown to maintain their undifferentiated state (Jadhav et al., 2006). Similarly, sustained constitutive activation of NOTCH1 stimulates the proliferation of immature cardiomyocytes in the rat myocardium (Collesi et al., 2008). In HSCs, overexpression of constitutively active NOTCH1 in hematopoietic progenitors and stem cells supports both primitive and definitive HSC selfrenewal (Stier et al., 2002). Together, these studies suggest that activation and/or sustained Notch signaling can lead to an increase in certain tissue stem cell populations. Thus, a working model for how tissue stem cell populations are favored in the absence of Prkci involves a sequence of events that ultimately leads to Notch activation. Recent studies have shown that aPKCs can be found in a complex with NUMB in both Drosophila and mammalian cells (Smith et al., 2007; Zhou et al., 2011); hence, in our working model (Figure 5S), we propose that the localization and phosphorylation of NUMB is highly dependent on the activity of PRKCi. When Prkci is downregulated or absent (as shown here), cell polarity is not promoted, leading to diffuse distribution and decreased phosphorylation of NUMB. Without active NUMB, NOTCH1 activation is enhanced, Hes/Hey genes are upregulated, and stem/progenitor fate generation is favored. To initiate differentiation, polarization could be stochastically determined but could also be dependent on external cues such as the presentation of certain ligands or extracellular matrix (ECM) proteins (Habib et al., 2013). When PRKCi is active and the cell becomes polarized, a trimeric complex is formed with PRKCi, PAR3, and PAR6. Numb is then recruited and phosphorylated, leading to Notch inactivation, the repression of downstream Hes/Hey genes, and differentiation is favored (see Figure 5S). Support for this working model comes from studies in Drosophila showing that the aPKC complex is essential for Numb activation and asymmetric localization (Knoblich, 2008; Smith et al., 2007; Wang et al., 2006). Additional studies on mouse neural progenitors show that regulating Numb localization and Notch activation is critical for maintaining the proper number of stem/progenitor cells in balance with differentiation (Bultje et al., 2009). Thus, an important function for PRKCi may be to regulate the switch between symmetric expansion of stem/progenitor cells to an asymmetric differentiation/maintenance phase. In situations of low or absent PRKCi, we propose that the expansion phase is favored. Thus, temporarily blocking either, or both, of the aPKC isozymes may be a powerful approach for expanding specific stem/progenitor populations for use in basic research or for therapeutic applications.
Although we do not see changes in the activation status of the STAT3, AKT, or GSK3 pathway, loss of Prkci results in an inhibition of ERK1/2 (Figures 2A and 2B). This result is consistent with the findings that ERK1/2 inhibition is both correlated with and directly increases ES cell selfrenewal (Burdon et al., 1999). Modulation of ERK1/2 activity by Prkci has been observed in cancer cells and chondrocytes (Litherland et al., 2010; Murray et al., 2011). Although it is not clear whether a direct interaction exists between Prkci and ERK1/2, Prkcz directly interacts with ERK1/2 in the mouse liver and in hypoxia-exposed cells (Das et al., 2008; Peng et al., 2008). The Prkcz isozyme is still expressed in Prkci null cells but evidently cannot suf- ficiently compensate and activate the pathway normally. Furthermore, knocking down Prkcz function in ES cells does not result in ERK1/2 inhibition, suggesting that this isozyme does not impact ERK1/2 signaling in ES cells (Dutta et al., 2011). Therefore, although PRKCi may interact with ERK1/2 and be directly required for its activation, ERK1/2 inhibition could also be a readout for cells that are more stem-like. Further studies will be needed to address this question.
Utility of Inhibiting aPKC Function Loss of Prkci resulted in EBs that contained slightly more STELLA+ cells than EBs made from +/ cells. Furthermore, inhibition of both aPKC isozymes by treating Prkci null cells with the PKC inhibitor Go¨6983 or the more specific inhibitor, ZIP, strongly promoted the generation of large clusters of STELLA+ and VASA+ cells, suggesting that inhibition of both isozymes is important for PGC progenitor expansion (Figure 6). It is unclear what the mechanism for this might be; however, one possibility is that blocking both aPKCs is necessary to promote NOTCH1 activation in PGCs or in PGC progenitor cells that may ordinarily have strong inhibitions to expansion (Feng et al., 2014). Regardless of mechanism, the ability to generate PGC-like cells in culture is notoriously challenging, and our results provide a method for future studies on PGC specification and differentiation. Expansion of stem/progenitor pools may not be desirable in the context of cancer. Prkci has been characterized as a human oncogene, a useful prognostic cancer marker, and a therapeutic target for cancer treatment. Overexpression of Prkci is found in epithelial cancers (Fields and Regala, 2007), and Prkci inhibitors are being evaluated as candidate cancer therapies (Atwood et al., 2013; Mansfield et al., 2013). However, because our results show that Prkci inhibition leads to enhanced stem cell production in vitro, Prkci inhibitor treatment as a cancer therapy might lead to unintended consequences (tumor overgrowth), depending on the context and treatment regimen. Thus, extending our findings to human stem and cancer stem cells is needed.
In summary, here, we demonstrate that loss of Prkci leads to the generation of abundant pluripotent cells, even under differentiation conditions. In addition, we show that tissue stem cells such as neural stem cells, primitive erythrocytes, and cardiomyocyte progenitors can also be abundantly produced in the absence of Prkci. These increases in stem cell production correlate with decreased NUMB activation and symmetric NUMB localization and require Notch signaling. Further inhibition of Prkcz may have an additive effect and can enhance the production of PGC-like cells. Thus, Prkci (along with Prkcz) may play key roles in stem cell self-renewal and differentiation by regulating the Notch pathway. Furthermore, inhibition of Prkci and or Prkcz activity with specific small-molecule inhibitors might be a powerful method to boost stem cell production in the context of injury or disease.