Turning on Genes is No Lonely Job

At any given time, only some of the genes in our DNA are turned on, or “active,” while others are turned off. Making sure only the correct genes are turned on in the correct cells is critical for our health. Scientists aim to understand how proteins in cells coordinate to turn a gene on, which could help identify strategies for treating improper regulation of gene activity. Two 4D Nucleome program-funded studies recently published in the journal Science explore the protein interactions that help turn a gene on. Both studies found that proteins cluster together at regions in the DNA called enhancers and interact to trigger gene activation.

In one study, Dr. Ibrahim Cisse and a team of researchers used live-cell super-resolution microscopy to view single molecules of proteins in mouse cells. They were able to view the interactions of a protein complex called Mediator, which helps kick-start transcription, and RNA polymerase II, the protein that carries out transcription by copying DNA into RNA. They found that both Mediator and RNA polymerase II group into stable clusters forming liquid-like droplets, a process known as phase-separation. Protein interactions were found to be brief, with proteins able to move in and out of the droplets, and droplets able to fuse together. They propose that Mediator droplets cluster at enhancers and fuse with RNA polymerase II droplets, allowing interactions between Mediator and RNA polymerase II that spur transcription to turn on genes.

In another study, led by Dr. Robert Tijan and Dr. Xavier Darzacq, the research team used live-cell single-molecule imaging to explore how proteins called transcription factors bind to the DNA enhancer and interact to initiate gene activation. They found that transcription factors also form high-concentration clusters that localize at the enhancer to stabilize DNA binding, recruit RNA polymerase II, and activate transcription. The interactions between transcription factors and RNA Polymerase II were rapid, reversible, and selective, making them a potential class of drug targets for regulating the process of gene activation.


Mediator and RNA polymerase II clusters associate in transcription-dependent condensates. Cho, WK, Spille, JH, Hecht, M, Lee, C, Li, C, Grube, V, and Cisse, II. Science 361, 412-415. 2018 July 27.

Imaging dynamic and selective low-complexity domain interactions that control gene transcription. Chong, S, Dugast-Darzacq, C, Liu, Z, Dong, P, Dailey, GM, Cattoglio, C, Heckert, A, Banala, S, Lavis, L, Darzacq, X, and Tijan, R. Science 361 (6400). 2018 July 27.

In the News:

It may take a village (of proteins) to turn on genes, Science News

Classification of Career Pathways for Biomedical Trainees

A national movement is building to provide transparent information on career paths of biomedical graduates and postdoctoral alumni. One problem standing in the way is that institutions do not yet have an intuitive, complete, and replicable career classification (or “taxonomy”) that concisely and decidedly describes alumni career outcomes. To address this problem, several members of the NIH BEST consortium, Association of American Medical Colleges Graduate Research Education and Training (GREAT) group, and Rescuing Biomedical Research (RBR), collaborated to propose a three-tier career taxonomy. The first tier includes five career sectors (e.g. Government or For-Profit), the second tier includes five career types (e.g. primarily research or primarily teaching), and the third tier defines 24 job functions (e.g. administration or regulatory affairs). The developed classification is also suitable for use in other academic disciplines beyond the biomedical research fields.

Using a uniform classification across institutions in reporting outcomes of alumni has many advantages. It is valuable for comparing outcomes between institutions and providing data to potential applicants to help select institutions that may more closely match their career ambitions. Furthermore, being aware of the outcomes of trainees should help the training and mentoring community comprehensively aggregate, analyze, and disseminate information about career outcomes to guide professional development programs, teaching curricula, and possibly influence faculty opinions.

Importantly, many BEST institutions have already reported their data publicly for several years on websites and in publications using a similar taxonomy. Many schools outside the BEST consortium are doing this too (e.g. Stanford, University of Pennsylvania), and it is likely to become a standard in the field soon. Several NIH BEST consortium institutions are piloting the newly developed taxonomy for their institution’s doctoral alumni career outcomes and are contributing these data to populate a developing aggregated database. Combined data could be analyzed and reported to funding agencies, the public, science policymakers, and trainees to better understand and appreciate the full range of careers that Ph.D. trained scientists follow.

Evolution of a functional taxonomy of career pathways for biomedical trainees. Mathur, A., Brandt, P., Chalkley, R., Daniel, L., Labosky, P., Stayart, C., & Meyers, F. (2018) Journal of Clinical and Translational Science, 2(2), 63-65. doi:10.1017/cts.2018.22

Viewing the Moment a Gene Turns On

Genes are segments of our DNA that code for proteins that determine our traits. Over 90% of our DNA does not encode Close proximity of enhancer and target gene allows gene activationgenes and was long considered “junk” DNA that had no known purpose. We now know that much of this DNA does have a purpose, for example, some of this non-coding DNA contains enhancers- regions of DNA that help “turn on” genes to ultimately produce proteins. The timing of turning a gene on is very important for normal development and issues with timing can lead to development of disease. Enhancers are typically located far away from the gene they turn on, and how the enhancers find their target genes within the nucleus of the cell and how they interact with gene- coding regions to result in protein production is not well understood. In a recent study by 4D Nucleome program-funded investigator Dr. Thomas Gregor and his research team, a live imaging approach was used to track the position of an enhancer and its target gene in developing fly embryos, while also monitoring gene activity. Using this technique, they were able to observe the moment when a gene was turned on. The results showed that close proximity between the enhancer and target gene was required not only to turn the gene on, but also to keep the gene active. When the enhancer disconnected from the target gene, the gene turned off. They also found that when the gene was turned on, the structure formed by the enhancer and target gene became more compact, and the results suggest changes in the 3D DNA arrangement improve the stability of this structure, allowing the gene to remain active. The results of this study improve our understanding of how gene activity is regulated and may help provide insight into how improper regulation of gene activity leads to developmental defects and disease.

Reference: Dynamic interplay between enhancer-promoter topology and gene activity. Chen, H, Levo, M, Barinov, L, Fujioka, M, Jaynes, JB, and Gregor, T. Nature Genetics. 2018.

In the news:

Imaging in living cells reveals how ‘junk DNA’ switches on a gene, Princeton University

DNA Enhancer Video Rules Out Hit-and-Run Activity, Genetic Engineering & Biotechnology News

Accelerating a Paradigm Shift

For the Public

The behavior and function of individual cells in the body can vary greatly, even between cells that are very close together. These differences can play a role in determining health, disease, and therapy outcomes, making the ability to study single cells crucial. The NIH Common Fund Single Cell Analysis Program (SCAP) launched in 2012 to speed up the discovery, development, and translation of approaches to analyze single cells in humans.  A variety of new tools and technologies for single cell analysis were developed through the program. SCAP funding ended in 2017. During the period of SCAP funding, there was a significant increase in interest and funding for “single cell analysis” studies, indicating that the program accelerated research in the field. The technological advances made possible by SCAP will undoubtedly have a broad impact on health and disease research.

For Researchers

Variation in cells in human tissues can play a role in determining health, disease, and therapeutic outcomes, making the ability to analyze single cells critical. The NIH Common Fund Single Cell Analysis Program (SCAP) launched in 2012 to speed up the discovery, development, and translation of approaches to analyze single cells in humans. SCAP particularly focused on technology development and a variety of single cell technologies were developed to analyze DNA sequence, DNA methylation, chromosome conformation, and chromatin state. Technology development evolved around three broad themes: droplet-based sequencing approaches, enhanced spatial resolution via fluorescent-based techniques, and barcoding techniques to multiplex microscopic approaches. In 2014, SCAP instituted a grand challenge, called “Follow that Cell,” to stimulate development of new tools for analyzing changes in individual cells over time. The winning project demonstrated a new nanopipette technology that can be used to repeatedly and non-destructively monitor the molecular properties of single cells over time. In addition, the program established the SCAP Transcriptome Consortium project, which developed a public portal containing phenotypic information and whole transcriptome data from 56 human subjects. SCAP-developed resources have been used by the Genotype-Tissue Expression (GTEx) program and the Human BioMolecular Atlas Program (HuBMAP), among others. SCAP funding ended in 2017. The technological advances made possible by SCAP, particularly in single cell RNA-seq and multiplexed imaging combined with computational methods, will undoubtedly have a broad impact on health and disease research.

Reference: Accelerating a Paradigm Shift- the Common Fund Single Cell Analysis Program. Roy AL, Conroy R, Smith J, Yao Y, Beckel-Mitchener AC, Anderson JM, and Wilder EL. Science Advances. August 2018.

Exploring Unexplained Bowel Pain

Understanding the causes of inflammatory bowel disease is difficult because the associated abdominal pain can occur without any obvious changes to the structure of the colon or signs of inflammation. Because pain sensations can be carried by sensory neurons, one factor in the generation of abdominal pain could be abnormal sensory neuron activity, which can be influenced by secretions from cells called  “epithelial cells” that line the interior of the colon. Understanding interactions between colon epithelial cells and sensory neurons could help us understand and treat abdominal pain. To study the interactions between the types of cells, a SPARC-funded team led by investigators Dr. Brian Davis and Dr. Kathryn Albers used genetically modified mice that contain blue light-activated colon epithelial cells to examine signaling between colon epithelial cells and neurons. These mouse colon epithelial cells could be specifically stimulated by blue light without any physical or chemical stimulation, allowing the study of their effects apart from other factors. Stimulating the epithelial cells caused activity in the pain-sensing neurons and behavioral responses similar to those that result from pain-inducing physical stimulation of the colon. Further study found that firing of neurons was likely triggered by release of a molecule called ATP from the colon epithelial cells. The results indicate that the activity of the colon epithelial cells alone, without any physical or chemical stimulation, could lead to abdominal pain through activation of the pain-sensing neurons. This study advances the understanding of how colon sensory neuron activity is regulated and could aid in development of new treatment strategies for inflammatory bowel disease.

Reference: Optogenetic Activation of Colon Epithelium of the Mouse Produces High-Frequency Bursting in Extrinsic Colon Afferents and Engages Visceromotor Responses. Makadia, PA, Naijar, SA, Saloman, JL, Adelman, P, Feng, B, Margiotta, J, Albers, KM, Davis, BM. June 2018. J Neurosci. 38(25): 5788-5798.

New Technique for 3D Genome Mapping

The 3D organization of DNA in the nucleus of a cell plays an important role in determining which genes are DNA on two different chromosomes coming together around the nucleolusturned on in that cell. This has important implications for human health, as problems with DNA organization are linked to human diseases such as cancer and early aging. Understanding how the DNA is organized in healthy cells is a critical step in identifying targets and developing treatments for abnormal nuclear organization. A current method for mapping 3D genome organization uses a technique called “proximity ligation” in which regions of DNA that are very close together, or “touching,” are linked together and then sequenced to determine where these DNA “touches” occur. This technique mostly identifies interactions of DNA regions within the same chromosome. However, imaging of the genome using microscopy techniques has shown that there are interactions between chromosomes and that these interactions tend to occur at discrete regions of the nucleus known as nuclear bodies. This indicates limitations of proximity ligation techniques in identifying interactions between chromosomes that occur over longer-range distances. In addition, both proximity ligation and microscopy techniques are limited to measuring simultaneous contacts between a small number of DNA regions, making it difficult to develop a comprehensive model of global genome organization.

A recent study led by NIH Common Fund 4D Nucleome Program-funded investigator Dr. Mitchell Guttman, developed a new technique for detecting simultaneous genome-wide interactions within the nucleus, called Split-Pool Recognition of Interactions by Tag Extension (SPRITE). SPRITE works by linking interacting DNA, RNA, and proteins in cells, isolating the nuclei, fragmenting the chromatin, “barcoding” interacting molecules within a complex, and sequencing and matching the areas with identical “barcodes” to identify interacting regions. Unlike proximity ligation and microscopy techniques, SPRITE is not limited in the number of simultaneous DNA interactions that it can identify. Using SPRITE, they were able to detect interactions that occur across larger distances than those found by proximity ligation techniques. They found two “hubs” of interactions between chromosomes, both associated with nuclear bodies: an inactive gene-poor hub that organizes around the nucleolus and an active gene-rich hub that organizes around regions called “nuclear speckles.” Using the SPRITE results, they created a global model of 3D genome organization, in which nuclear bodies act as inter-chromosomal hubs that shape the 3D packaging of DNA in the nucleus.

Reference: Higher-order inter-chromosomal hubs shape three-dimensional genome organization in the nucleus. Quinodoz, SA, Ollikainen, N, Tabak, B, Palla, A, Schmidt, JM, Detmar, E, Lai, MM, Shishkin, AA, Bhat, P, Takei, Y, Trinh, V, Aznauryan, E, Russell, P, Cheng, C, Jovanovic, M, Chow, A, Cai, L, McDonel, P, Garber, M, and Guttman, M. Cell. 2018.

Using Sugars to Find Cancer Cells

Our cells are covered with a unique coating of various types of sugar molecules collectively called glycans. Glycans on the surface ofcancer cell among healthy cells diseased cells, such as cancer cells, are distinct from those of healthy cells. A glycan called sialyl-T is present in low levels in some normal cells but is present in higher levels on the surface of many types of cancer cells where it is attached to proteins on the cell surface, forming glycoproteins. The presence of sialyl-T on cell surfaces is believed to be correlated with tumor development and progression. This makes sialyl-T an important molecule for the recognition of cancer cells (a biomarker) and a potential target for treatment. However, sialyl-T has a complex structure and occurs at relatively low levels, even on cancer cells. The current two-step biochemical labeling methods for detecting sialyl-T are not sensitive or specific enough for detecting the presence of sialyl-T and analyzing the role of this glycan in disease.

In a recent study led by NIH Common Fund Glycoscience program awardee Dr. Peng George Wang, a new method was developed for labeling sialyl-T for visualization, quantification, and analysis. This simple method requires only one step and is more sensitive, specific, and rapid than existing methods of sialyl-T labeling. The new method uses an enzyme called ST6GalNAc-IV, which specifically recognizes sialyl-T and can attach another molecule to sialyl-T and its bound protein. ST6GalNAc-IV transfers a compound containing the molecule biotin onto the sialyl-T bound protein. Biotin can be used as a tag allowing sialyl-T glycoproteins to be visualized or captured and analyzed to identify unknown sialyl-T-glycoproteins. The authors were able to successfully identify 78 sialyl-T-linked proteins on the surface of human breast cancer cells and 43 sialyl-T-linked proteins on the surface of human colon cancer cells using cells grown under laboratory conditions. This method could speed up the study of sialyl-T in a variety of biological processes such as cancer progression. The next step of this research will be to test the labeling method in living animals.

Reference: A One-Step Chemoenzymatic Labeling Strategy for Probing Sialylated Thomsen-Friedenreich Antigen. Wen, L, Liu, D, Zheng, Y, Huang, K, Cao, X, Song, J, and Wang, PG. ACS Central Science. Feb 23, 2018. DOI: 10.1021/acscentsci.7b00573.

In the News: Detecting the Sweet Biomarker on Cancer Cells, American Chemical Society First Reactions


No Llama? No Problem!

LlamaThe importance of llamas, alpacas, camels, and other camelids in protein research is little-known, but their antibodies play a key role in solving protein structures. They also serve as a major obstacle and bottleneck to researchers where access to camelids is limited, and generating the desired antibody is time-consuming (often taking six months), expensive, and frequently doesn’t work. Now, a team of researchers including Andrew Kruse (2015), Aashish Manglik (2016), and Aaron Ring (2016), have created a synthetic library that uses yeast cells instead of camelids to create the essential antibodies. Camelids produce a unique class of antibodies called nanobodies that can bind to key proteins because of their much smaller size than regular antibodies. Nanobodies can lock a protein into a particular conformation, which is necessary in determining a protein’s structure. Instead of laboriously generating several milligrams of a target protein to use to inoculate a llama and hoping the llama’s immune system creates the desired antibodies, Kruse and Manglik’s team created a library of 500 million camelid antibodies using yeast cells. Each tube is like a miniature llama immune system. Researchers can label their protein of interest with a fluorescent tag and add it to the yeast library. Yeast with nanobodies that recognize and bind to the protein will glow and can be separated out using fluorescence-activated cell sorting. The yeast cells can then be sequenced to learn what the nanobodies are and E. coli bacteria used to grow more nanobodies. The entire process takes three to six weeks. The system was tested on the beta-2 adrenergic receptor and adenosine receptor and successfully and robustly bound nanobodies to their target receptors. Kruse and Manglik are offering the yeast nanobody library free of charge to any interested nonprofit labs and hope their platform will accelerate discoveries and eliminate the need of llamas for protein research.

Reference: Yeast Surface Display Platform For Rapid Discovery of Conformationally Selective Nanobodies. McMahon C, Baier AS, Pascolutti R, Wegrecki M, Zheng S, Ong JX, Erlandson SC, Hilger D, Rasmussen SGF, Ring AM, Manglik A, Kruse AC. Nature Structural & Molecular Biology. 2018 Feb 12. doi: 10.1038/s41594-018-0028-6.

In the News:

Speedy Sugar Binding Analysis

Glycans are types of sugars that play important roles in the function of our bodies. They modify proteins and lipids to form sugar cubes aligned in rowsmore complex molecules, and they can be recognized and bound specifically by glycan-binding proteins and antibodies. These protein-glycan interactions play critical roles in many cellular functions such as cell signaling, initiation of viral infection, the development of cancer, and initiation of the immune response. It has been difficult for scientists to study glycans because of the limited tools available to detect and quantify them. Methods that do exist can be technically challenging, are limited in the number of glycans that can be analyzed, have long turn-around times, and can be expensive. This lack of appropriate analysis tools has hindered progress on the study of glycans and glycan-binding proteins for biomedical research, clinical diagnoses, and therapies. There is therefore an urgent need for improved tools and methods for rapidly analyzing large numbers of glycans and glycan-binding proteins.

In a study led by Common Fund Glycoscience program investigator Dr. Jin-Xiong She, a new tool was developed for the speedy analysis of interactions between glycans and proteins that bind to them. This new, highly sensitive and specific high-throughput platform is called “multiplex glycan bead array” (MGBA) and uses microbeads, with a specific glycan attached to each individual uniquely tagged bead. Scientists can read the array to determine which beads and their attached glycans bind to which proteins. Because there are so many beads on an array, this allows analysis of a protein’s ability to bind to hundreds of individual glycans and can be used to greatly speed up studies of glycan-binding proteins. This tool may be adapted for use in clinical tests, with the potential to identify diagnostic biomarkers for diseases such as cancer. The utility of this platform was illustrated by identifying a glycan-binding antibody protein that predicts the survival of patients with ovarian cancer. This method is inexpensive, simple enough to be carried out by non-specialists, and relatively quick (~4 hours), making it suitable for clinical use by those not extensively trained as glycan scientists.

Reference: Multiplex glycan bead array for high throughput and high content analyses of glycan binding proteins. Purohit, S, Tiehai, L, Guan, W, Song, X, Song, J, Tian, Y, Li, L, Sharma, A, Dun, B, Mysona, D, Ghamande, S, Rungruang, B, Cummings, RD, Wang, PG, and She, JX. Nature Communications. 2018 Jan 17. 9(1):258.

Packaging Chromosomes for Cell Division

As a cell moves through the cell cycle, the shape of the DNA in the nucleus changes dramatically, from a ball of DNA during Process of Cell Divisionnormal cell activities to distinct X-shaped chromosomes as the cell prepares to divide. This change in shape is important for the orderly passage of one copy of the DNA to each new cell. Before the cells begin to divide, the DNA compacts into the dense X-shaped chromosomes that are made up of consecutive DNA loops. How the compaction of loops occurs is not well understood. One of the goals of the 4D Nucleome program is to determine how the structure of DNA in the nucleus of a cell changes over time.

In a recent study in Science, a team led by 4DN-funded researchers Dr. Leonid Mirny and Dr. Job Dekker combined techniques that are used to determine where regions of the genome “touch” with imaging and modeling techniques at one-minute time intervals to investigate how DNA rearrangement occurs before cell division. Based on their results, they propose a model in which cells use a protein called “condensin” to drive the compaction of DNA. Condensin proteins create DNA loops by pushing DNA through their ring-like structures. In this model, condensin I creates wide loops in the DNA that are then split into smaller loops by condensin II. The loops twist around a condesin scaffold in a structure resembling a spiral staircase, creating a condensed helix of consecutive DNA loops that makes up the X-structure of the chromosomes and results in formation of compact units of DNA that can be easily divided between new cells. Understanding how the organization of DNA changes throughout the cell cycle is critical for determining how problems with cell cycle-associated DNA rearrangement (such as chromosome breakage) lead to human diseases such as cancer.

Reference: A pathway for mitotic chromosome formation. Gibcus, JH, Samejima, K, Goloborodko, A, Samejima, I, Naumova, N, Nuebler, J, Kanemaki, MT, Xie, L, Paulson, JR, Earnshaw, WC, Mirny, LA, Dekker, J. Science. 2018 Jan 18. doi: 10.1126/science.aao6135.

In the news: Packing a Genome, Step-by-Step, Howard Hughes Medical Institute

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This page last reviewed on August 27, 2018