Science Sketches at MMCRI

Very recently I found myself in a revelationary conversation with a non-scientific colleague as we were planning our annual exhibition for the Maine Science Festival. We needed a display that would highlight the molecular biology work we do at MMCRI that would be exciting and comprehensible to a broad audience plus a related hands-on activity that could be completed in just a few minutes. Pulling from the expertise of the folks attending the festival, I proposed that we have a display on our use of 3D silk scaffolds in modeling cancer. One of the hallmarks of the cancer cells compared to healthy cells is reduced lipid content, so the hands-on activity could be a demonstration of dye solubility with the explanation that this is how we measure lipid content in our cell populations.

Well, about halfway into the conversation I found that I had completely failed to convey A. the link between the silk scaffold models and the hands-on activity and B. the importance of dye solubility in highlighting specific structures and substances. Fortunately, my colleague asked me to take several steps back and was able to ask very specific questions such that I was able to reform my explanation for her. In the end, my idea was passed along, but the episode highlighted to me that despite all the opportunities I have to explain my science to both scientific and lay audiences I still need lots more practice.

This past summer at MMCRI we had an excellent opportunity to think in great depth about how to present our work in a concise and comprehensible manner: we produced Science Sketches! A Science Sketch is a two-minute or less video summary of a scientific topic. I have seen examples of more universal basic scientific principles as well as very specific projects.

All sketches start as an idea or concept that the writer wants to convey to their audience. The writer must decide who their audience will be, as this will dictate the vocabulary and the level of explanation that needs to be employed. Science Sketches has a great tutorial to help writers as they get started telling their stories. They recommend a 300-word script with no jargon that has been proofread by several colleagues and assessed using online tools that highlight terms above a given reading level. With a complete script, you can start putting together a storyboard that illustrates every sentence.

The sketches generally utilize pen and ink drawing on copy paper or white board, but they can also employ cut paper shapes, building blocks, or other props to illustrate an idea. They can be made very rapidly and at very little expense as they are often filmed using a cell-phone camera mounted on a ring stand.  The writer films him or herself drawing or moving paper cut outs, records his or her script, then uses video editing software to compress the video and match it to the audio. The writer can take as long as he or she likes drawing the images as they can be sped up to whatever speed is necessary using the editing software.

Video summaries of scientific concepts have been around for a long time, and I am particularly fond of this trippy vintage recording of translation, but organizing an approachable tutorial that anyone can carry out is a novel model. Science Sketches arose at the Max Plank Institute of Molecular Cell Biology and Genetics in Dresden Germany as a collaboration between the institute’s postdoc program manager, Lisa Dennison, PhD, and the Hyman lab. More recently, Science Sketches has focused on improving their public engagement, so Liam Holt, PhD of NYU, became involved and helped them develop their science fundamentals video series.

I found this summer’s workshop challenging but rewarding. I had to take a high altitude view of my project again after months of detailed experiments in order to highlight the key features of my work and keep my audience’s attention for the full two minutes. It also gave me an excuse to binge watch lots of science vignettes, making me feel really well rounded and intelligent for a day, as I decided how I wanted to construct my own video. Hope you enjoy!

NIH signs PACT with big pharma to boost immunotherapy

On October 2017, the NIH announced a formal collaboration between the public and private sector as a new leap in the War On Cancer. The collaboration, termed PACT for “Partnership for Accelerating Cancer Therapeutics”, is a five-year project that will focus first on cancer biomarker identification & validation and then on developing novel immunotherapies. As Dr. Francis Collins, Director of NIH, stated to the press, “we have seen dramatic responses from immunotherapy… We need to bring that kind of success – and hope – for more people and more types of cancers, and we need to do it quickly.” He believes that this collaborative effort between the NIH and 11 heavyweight pharmaceutical companies (see below for complete list) will “help achieve this success faster.”

This new collaboration will allocate $215 million over the five years, with NIH contributing $160 million over 5 years (depending on availability of funds) and each pharma company contributing $1 million/year (totaling 55$ million over 5 years). The Foundation for the National Institutes of Health (FNIH), a congressionally established nonprofit, and the U.S. FDA will be supervising this partnership. The Pharmaceutical Research and Manufacturers of America (PhRMA), a trade group found in 1958 to advocate for public policies that encourage drug discovery for patients, will also provide support for this initiative.

PACT seeks to identify why certain patients respond so dramatically to immunotherapy, as evidenced by the recent observations of near-complete eradication of pediatric lymphomas, and how such treatments can be expanded to a larger patient population and a wider range of tumors, especially solid tumors which have not had much success with immunotherapy despite a lot of initial promise. To that end, this program will first perform cancer biomarker discovery, validation and standardization and then integrate these biomarkers for patient recruitment into oncology trials for immunotherapy and combination trials. PACT also aims to embrace the data sharing aspect of collaboration to “better coordinate clinical efforts, align investigative approaches, reduce duplication and enable more high-quality trials to be conducted.”

As part of the Cancer Moonshot program and PACT collaboration, the National Cancer Institute (NCI) recently awarded cooperative agreements to Dana-Farber Cancer Institute, Stanford Cancer Institute, Precision Immunology Institute and the Tisch Cancer Institute to Icahn School of Medicine at Mt. Sinai, and MD Anderson Cancer Center. These cancer centers will serve as Cancer Immune Monitoring and Analysis Centers (CIMACs) where tumors will be deep sequenced and immune profiled. The data obtained will be archived in a immune response biomarker database created at Dana Farber, which is slated to act as a Cancer Immunologic Data Center (CIDC). These cancer centers will form a network of laboratories that can support both basic research efforts and adult and pediatric immunotherapy trials.

Dr. Thomas Hudson, vice president of oncology discovery and early development at AbbVie, who represented the industry at the PACT press conference, stressed on the need for collaborative efforts to drive innovations in immunotherapy, despite the competitive nature of the field. Based on his prior experience in large scale public-private sector collaboratives, such as the International Cancer Genome Consortium, he believes that this collaboration will ultimately prove to be more fruitful than expected for all parties involved. Besides Abbvie, the other pharma partners include Amgen, Boehringer Ingelheim, Bristol-Meyers Squibb, Celgene Corporation, Genentech, Gilead Sciences, GlaxoSmithKline, Janssen Pharmaceuticals (Johnson & Johnson), Novarits and Pfizer.

 

Sources –

https://www.nih.gov/news-events/news-releases/nih-partners-11-leading-biopharmaceutical-companies-accelerate-development-new-cancer-immunotherapy-strategies-more-patients

https://www.nih.gov/news-events/multimedia-partnership-accelerating-cancer-therapies

https://www.statnews.com/2017/10/12/nih-pharma-cancer-moonshot/

https://cen.acs.org/articles/95/web/2017/10/Big-pharma-joins-NIHs-Cancer.html

Top Techniques: Single-Cell RNA Sequencing

Image from Papalexi E & Satija R, Single-cell RNA sequencing to explore immune cell heterogeneity. Nat Rev Immun (2017).

As scientists ask increasingly focused and nuanced questions regarding cellular biology, the technology required to answer such questions must also become more focused and nuanced. In the last decade, we have already seen several significant paradigm shifts in how to process data in a high-throughput manner, especially for genomic and transcriptomic analyses. Microarrays gave way to next-generation sequencing, and now next-generation sequencing has moved past bulk sample analysis and onto a new frontier: single cell RNA sequencing (scRNA-Seq). First published in 2009, this technique has gained increasing traction in the last three years due to increased accessibility and decreased cost.

So, what is scRNA-Seq?

As the name suggests, this technique obtains gene expression profiles of individual cells for analysis, as opposed to comparing averaged gene expression signals between bulk samples of cells.  

When and/or why should I use scRNA-Seq compared to bulk RNA-Seq? What are its advantages and disadvantages?

The ability to examine transcriptional changes between individual cells uniquely allows researchers to define rare cell populations, to identify heterogeneity within cell populations, to investigate cell population dynamics in depth over time, or to interrogate nuances of cell signaling pathways—all at high resolution. The increased specificity and subtlety given by single-cell sequencing data benefits, for example, developmental biologists who seek to elucidate cell lineage dynamics of organ formation and function, or cancer biologists who may be searching for rare stem cell populations within tumor samples.

Practically, scRNA-Seq often requires far less input material than traditional bulk RNA-Seq (~103-104 cells per biological sample, on average). The trade-off for this downsizing advantage, however, is because of the lower input, there is often more noise in the output data that requires additional filtering. Also, as with any rising star high-throughput technique, standardized pipelines for bioinformatics processing of the raw output data are still being finalized and formalized. As the same type of growing pains occurred when bulk RNA-Seq rose to prominence, no doubt a more final consensus will also eventually be reached for scRNA-Seq.

What platforms are used for scRNA-Seq?  

The three most current and common workflows to isolate single cells for sequencing are by microplates, microfluidics, or droplets.

Microplate-based single cell isolation is carried out by laser capture of cells, for example by FACS, into wells of microplates. This approach is useful if there are known surface markers that can be used to separate cell populations of interest. It also provides the opportunity to image the plate and ensure that enough cells were isolated and that it was truly a single cell isolation. Reagents for lysing, reverse transcribing, and preparing libraries are then added to individual wells to prepare samples for sequencing.   

Microfluidics-based single cell isolation consists of a chip with a maze of miniature lanes that contain traps, which each catch a single cell as the bulk cell mixture is flowed through. Once cells are caught within the traps, reagents for each step of the sample preparation process (lysis, reverse transcription, library preparation) are flowed through the chip lanes, pushing the cell contents and subsequent intermediate materials into various chambers for preparation, followed by harvesting the final material for sequencing.

Droplet-based single cell isolation also uses microfluidics but instead of traps it involves encapsulating, within a single droplet of lysis buffer, (1) a single cell and (2) a bead linked to microparticles, which are the reagents necessary for sample preparation. The advantage of this approach is that a barcode can be assigned to the microparticles on each bead, and thus all transcripts from a single cell will be marked with the same barcode. This aspect allows pooling of prepared samples for sequencing (decreasing cost) as the cell-specific barcodes then can be used to map transcripts back to their cell of origin.

The other significant consideration for designing scRNA-Seq experiments is what sequencing method to use. Full-length sequencing provides read coverage of entire transcripts, whereas tag-based sequencing involves capture of only one end of transcripts. While the former approach allows for improved mapping ability and isoform expression analyses, the latter allows for addition of short barcodes (Unique Molecular Identifiers, UMIs) onto transcripts that assist in reducing noise and bias during data processing.    

So, which platform should­ I use?

As with most advanced techniques, determining which platform to use depends on the biological question being asked. A microplate-based platform does not accommodate high throughput analyses but does allow for specificity in what types of cells are being analyzed. So, for example, it would be a good choice for investigating gene expression changes within a rare population of cells. It also does not require particularly specialized equipment (beyond a FACS machine) and thus is a relevant choice for researchers without access to more sophisticated options. Microfluidics-based platforms are capable of more throughput than microplate-based while retaining sensitivity, but they are more expensive. Finally, droplet-based platforms provide the greatest amount of throughput but are not as sensitive. Thus, they are most appropriate for elucidating cell population composition and/or dynamics within complex tissues.

How can my scRNA-Seq data be processed, and is it different than bulk mRNA-Seq data processing?

Performing computational analysis on scRNA-Seq data follows a similar pipeline as bulk RNA-Seq, though there are specific considerations required for scRNA-Seq data processing, especially during later stages of the pipeline. One of the major considerations is significant cell-to-cell discrepancies in expression values for individual genes. This effect occurs because each cell represents a unique sequencing library, which introduces additional technical error that could confound results when comparing cell-specific (and therefore library-specific) results. This effect can be mitigated during data processing by additional normalization and correction steps, which are included in most of the publicly available scRNA-Seq processing pipelines.

Finally, the types of interpretations drawn from scRNA-Seq experiments are also technique-specific and question-dependent. Common analyses of scRNA-Seq data include clustering, psuedotime, and differential expression. While clustering is done with bulk RNA-Seq data, clustering scRNA-Seq data allows for assessing relationships between cell populations at higher resolution. This aspect is advantageous for investigating complex tissues—such as the brain—as well as for identifying rare cell populations. Given the large sizes of scRNA-Seq data sets, performing clustering of scRNA-Seq often requires dimensionality reduction (i.e. PCA or t-SNE) to make the data less noisy as well as easier to visualize. By coupling clustering results along with differential expression data, identifying gene markers for novel or rare populations is made easier. Psuedotime analysis is particularly useful for scRNA-Seq experiments investigating stages of differentiation within a tissue. Using statistical modeling paired with data reflecting a time course (for example, various developmental stages of a tissue), this analytical method tracks the transcriptional evolution of each cell and computationally orders them into a timeline of sorts, thus providing information relevant for determining lineages and differentiation states of cells in greater detail.  

Where can I do scRNA-Seq in Boston?  

Tufts Genomics Core here at Sackler has a Fluidigm C1 machine (microfluidics). Harvard Medical School (HMS) has several options for single-cell sequencing platforms. HMS Biopolymers Core also has a Fluidigm C1 system that is available for use on a for-fee, self-serve basis after training, with reagents purchased and samples prepared by the individual, as well as a 10X machine (droplet). HMS Single-Cell Core has a inDrop machine (droplet) that includes for-fee full service with faculty consultation.

What is the future for scRNA-Seq?

Bettering the way in which samples are processed and data is analyzed is a priority for scRNA-Seq experts. Specifically, ongoing work seeks to improve library preparation and sequencing efficiency. The programs used to process scRNA-Seq data are also still in flux so as to provide better normalization and correction tools for increasingly accurate data. On a larger scale, developing technology to analyze other biological aspects (genomics, epigenomics, transcriptomics) at the single cell level is of high interest, especially when considering how powerful combining these other forms of single-cell analysis with transcriptomics could be for understanding both normal and disease biology.

Resources:

  1. scRNA-Seq software packages: https://github.com/seandavi/awesome-single-cell
  2. Review of bioinformatics and computational aspects of scRNA_Seq: https://www.frontiersin.org/articles/10.3389/fgene.2016.00163/full
  3. Practical technique review: https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-017-0467-4
  4. Start-to-finish detailed instructions on scRNA-Seq: https://hemberg-lab.github.io/scRNA.seq.course/biological-analysis.html

The Perks of Resting Your White Matter

All images used here are released under Creative Commons CC0. The author would like to thank her good friend E.C. for help in editing this article.

While the stigma of mental health issues has begun to lessen somewhat in recent years, it’s still very present in our society. Let’s take a moment to talk honestly about mental health and work/life balance.

Graduate students have a high risk of having or developing mental health issues
In a paper published in the Journal of Medical Education in 1984, Heins et al. studied perceived stress in medical, law, and graduate students. While the authors acknowledged that stress is related to doing graduate work regardless of program, they caution that overabundance of stress is, paradoxically, likely to be detrimental to the learning process (Heins et al. 1984). Even in the 80s, scientists were studying and acknowledging mental health issues resulting from too much stress, and the importance of its management in post-secondary education. So why has it taken so long to address this, even in everyday society?

Aside from the inertia created by social norms, there doesn’t seem to be a reasonable answer to this. Graduate students face an extraordinarily high amount of pressure, including the their own expectations and those of their peers, funding concerns, publishing, and finding a job once their degree is finally obtained (Hyun et al. 2006). A small study of Ph.D. students in Flanders, Belgium indicated that the risk having or developing a common psychiatric disorder, such as anxiety or depression, was 2.43 times higher in Ph.D. students than in the highly educated general population (Levecque et al. 2017). A similar pattern was published in the Graduate Student Happiness & Well-Being Report from University of California, Berkeley, where 28-64% of graduate students scored as being depressed (depending on the field of study; biological sciences scored 43-46%) (University of California, Berkeley 2014). This study’s top ten predictors of overall graduate student well-being are:

1. Career Prospects
2. Overall Health
3. Living Conditions
4. Academic Engagement
5. Social Support
6. Financial Confidence
7. Academic Progress & Preparation
8. Sleep
9. Feeling Valued and Included
10. Advisor Relationship

So, what does this mean?

Work-life balance is important
You may be protesting, “I am in graduate school. I am extremely busy and I simply don’t have time to do things outside of work.” Good news: studies show that taking breaks can boost your focus (Ariga and Lleras 2011; Finkbeiner et al. 2014; Zacher et al. 2016). There are lots of opportunities hidden within your day-to-day life that you can seize, if you know where to look. Not convinced? Try taking just one extra hour of time for yourself per week for a few months and see if your stress levels decrease. Here are some beneficial things to try during that hour:

Get some exercise
The gym in Sackler is free and readily accessible for students, but there are lots of other things you could do. Running is a great, rhythmic option that can double as a jam session to your favorite tunes. High-impact exercise not your style? Try taking a stroll with a friend to get some bubble tea and fresh air! Or take advantage of the weekly “Walk with the Dean” that Dean Jay recently implemented. The Student Advisory and Health Administration Office has also sponsored beginner’s level yoga and meditation, which will hopefully continue in future semesters.

Catch more zzz’s
Most of the time, caffeine does a passable job at convincing us that sleep isn’t all that important after all, right? As miraculous (and delicious!) as coffee is, the caffeine-induced buzz just isn’t a substitute for getting enough sleep. It’s very difficult to commit to a full 8 hours every night (and some of us may not even need quite that much), but if you are consistently running low on sleep, try committing to just an extra half hour each night. At the very least, you’ll get another 3.5 hours per week, which is a step in the right direction!

Start talking
Open a dialogue with your colleagues about mental health and well-being. You might be surprised by how many people have something to say on the topic, and by starting a conversation, you will play an active role in decreasing the stigma surrounding mental health. This can be a particularly helpful and important step if you are feeling alone, frustrated, helpless, or overwhelmed. If opening up to a friend is too daunting, you can also take advantage of peer-to-peer mentoring. Groups like Tufts Mentoring Circles aim to support students (and Postdocs!) through topics such as applying for jobs, time management, conflict resolution, and, of course, work/life balance.

Know where to go for help
Did you know that Tufts has a Student Wellness Advisor? This resource is available to all students on the Boston Health Science Campus. Our Wellness Advisor, Sharon “Snaggs” Gendron is here to help us manage the everyday stress of being graduate students. She can also refer students struggling with depression, anxiety, or other mental health challenges to clinicians who can help. You can read more about how to get in touch with the Wellness Advisor here.

If any of this sounds familiar and you want to try changing your habits, you’re in luck! There are two Wellness Gatherings coming up, one on November 15th from 3 PM – 4:30 PM and one on December 14th from 2:30 PM – 4 PM, in the Sackler 4th floor Reading Room. Take a few minutes to stop by and meet the Wellness Advisor (and a Canine Companion)!

A final note…
TL;DR? You are important and your health is paramount. Keep in mind that the definition of ‘health’ is not limited to the physical realm; you need to take care of your mind and feelings just as much as the rest of you.

Finally, and this cannot be emphasized enough, if you are struggling with mental health challenges like anxiety, depression, or suicidal thoughts, please seek help. You are not alone. In the event of a crisis, you can contact the National Suicide Prevention Lifeline 24/7 at 1 (800) 273-8255.

Literature Cited
Ariga A and Lleras A. (2011) Brief and rare mental ‘‘breaks’’ keep you focused: Deactivation and reactivation of task goals preempt vigilance decrements. Cognition 118:439-443.

Finkbeiner KM, Russell PN, and Helton WS. (2016) Rest improves performance, nature improves happiness: Assessment of break periods on the abbreviated vigilance task. Conscious Cogn 42:277-285.

Heins M, Fahey SN, and Leiden LI. (1984) Perceived stress in medical, law, and graduate students. J Med Educ 59:169-179.

Hyun JK, Quinn BC, Madon T, and Lustig S. (2006) Graduate student mental health: needs assessment and utilization of counseling services. J Coll Stud Dev 47(3):247-266.

Levecque K, Answeel F, De Beuckelaer A et al. (2017) Work organization and mental health problems in PhD students. Res Policy 46:868-879.

University of California, Berkeley. (2014) The Graduate Assembly: Graduate student happiness & well-being report. http://ga.berkeley.edu/wellbeingreport/. Accessed 31 October 2017.

Zacher H, Brailsford HA, and Parker SL. (2014) Micro-breaks matter: A diary study on the effects of energy management strategies on occupational well-being. J Vocat Behav 85:287-297.