The crystal ball has had its ups and downs as a means of divination. Although it was esteemed by the Druids and other ancient peoples, the crystal ball fell into disrepute during the Middle Ages, only to enjoy a Renaissance during the, well, Renaissance. In those daring times, the crystal ball acquired a quasi-scientific status among academics, who would use it while hoping to communicate with angels. Purportedly, angels would convey their superior wisdom through fleeting visions to be perceived by crystal ball readers.

Today, the crystal ball is just a reminder that we still want glimpses of the future, visions conveyed by angels. That’s certainly the case for those of us in fast-changing fields such as biotechnology and genomics. So, where is our crystal ball? It’s right here—the January issue of GEN! In this special issue, we’re presenting visionary insights courtesy of 20 life sciences experts, both veteran scientists and emerging talents. They reward crystal ball gazing from multiple angles of view: genomics, proteomics, synthetic biology, cancer research, gene therapy, drug discovery, bioinformatics, artificial intelligence, and more.

Gene Editing


Jennifer DoudnaJennifer Doudna, PhD

Li Ka Shing Chancellor’s Chair in Biomedical and Health Sciences, Professor of Chemistry, and Professor of Molecular and Cell Biology, University of California, Berkeley


What have been the biggest advances in your field over the past few years?

Doudna: The development of CRISPR-Cas proteins for genome editing applications has had a profound impact on biology and biotechnology over the past seven years. These tools have democratized the ability to rewrite the information contained in genomes and thereby to both understand and alter genetic traits. Additionally, there has been exciting work to determine how these tools might be delivered into cells and organisms, as well as used in a clinical context.

What’s your vision for the future of the field over the next 5–10 years?

Doudna: I believe CRISPR technology will positively change the lives of millions of people. Over the next decade, researchers will continue to advance the use of CRISPR-based tools to treat and in some cases cure diseases, develop more nutritious crops, and eradicate infectious disease. It is a profoundly powerful technology, but we must be mindful of potential unintended or undesirable consequences and apply it responsibly.

How did you get into your field?

Doudna: Working initially with UC Berkeley colleague, Jillian Banfield, my lab began investigating adaptive bacterial immunity encoded within Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR) DNA sequences. Banfield’s research hinted that RNA was somehow involved in deploying CRISPR sequences in bacteria to detect and destroy viruses. My research on CRISPR function eventually led to a collaboration with the lab of Emmanuelle Charpentier, resulting in our 2012 publication describing CRISPR-Cas9 as an RNA-guided DNA-cutting enzyme that can be used for genome editing. Since that time, my work has focused on CRISPR-Cas protein mechanisms, applications to genome engineering, disease detection, and societal implications of this transformative technology.

What was the biggest eureka moment or near-miss in your career?

Doudna: My biggest eureka moment came after first seeing our data showing that the CRISPR-Cas9 protein can cut DNA in a programmable way. Working with Martin Jinek, who conducted these initial experiments while he was a postdoctoral trainee in my lab, we knew this was going to be a technology that could change the way we live.

How is your field going to “translate” to help patients? What do you want to see happen?

Doudna: The key challenges are demonstrating the effectiveness of using CRISPR-Cas9 in humans, delivering these molecules for genome editing in specific tissues of the body, and more broadly, ensuring that breakthrough CRISPR-based therapies are affordable and equally accessible for all. I would like to see a comprehensive strategy to both develop genome editing therapies and control costs so that many people will benefit from the coming advances in the field.

What else would you like to talk about?

Doudna: For CRISPR-Cas9 genome editing technology to be embraced by the public, it must be applied responsibly. The global research effort must remain focused on treating disease rather than engineering new human traits or creating so-called designer babies.


Nicole Gaudelli

Nicole Gaudelli, PhD

Senior Scientist II, Head of DNA Editing Platform
Beam Therapeutics


What have been the biggest advances in your field over the past few years?

Gaudelli: In the field of genome editing, the biggest advancement is the discovery and application of the CRISPR-associated nuclease Cas9, which has advanced the gene editing field with both its target design simplicity and overall robust nuclease efficiency, allowing researchers to target and modify the human genome at precise locations containing homology to a researcher-defined, small stretch of RNA. The versatility of Cas9 has revolutionized the field and enabled the creation of a variety of opportunities and mechanistic pathways for the treatment of genetic diseases. Additionally, it is an essential component to next-generation gene editing technologies such as base and prime editing because it brings the molecular machinery to the loci of interest and participates in the overall mechanism of gene editing in these systems.

What’s your vision for the future of the field over the next 5–10 years?

Gaudelli: The responsible and ethical application of the latest genome editing tools is to work toward curing patients who suffer debilitating genetic diseases. This endeavor will most efficiently be achieved through the cooperation of researchers across government, academic, and industrial sectors, working together in a spirit of transparency and a common desire to propel cutting-edge science forward in order to both advance the field and make an impact on human health and genetic disease. As with any bold challenge, cross-sector collaboration, informational transparency, honest dialogue, and a commitment to scientific excellence and integrity are essential to treating genetic disease through the modification of a patient’s DNA.

How did you get into your field?

Gaudelli: I came into the gene editing field by chance. Prior to entering genome editing, I spent about a decade in the field of natural products and antibiotic biosynthesis. During my postdoctoral work in Prof. David R. Liu’s lab, I was interested in protein evolution and engineering. I began work in his lab engineering enzymes involved in antibiotic biosynthesis. I soon became increasingly distracted by gene editing projects and found myself spending more time thinking about chemically modifying the genome via base editing than about antibiotics. About a year and a half after I joined his lab, I found a project that allowed me to apply my interest and experience in mechanistic enzymology and evolution to base editing and created a new base-editing enzyme: ABE.

What is holding your field back?

Gaudelli: One of the biggest challenges in the gene editing field is having the ability to deliver these large, polypeptide molecular machines into the relevant tissues and cells in vivo, in humans. If we can successfully achieve the efficient delivery of gene editing enzymes, we will be one step closer to treating genetic disease. I would be pleased as punch if we, as a scientific community, could make some serious strides and breakthroughs on delivery modalities to enable more widespread application of gene editors beyond ex vivo indications.

What’s the biggest lesson you’ve learned in your career that you wished newer investigators knew?

Gaudelli: Science is hard. If it were easy, then we would have had all challenges resolved by now. Meaningful and impactful advancement doesn’t come without great risk. Take the risk. Be vulnerable. Know that most risks will end in failure, but it is those failures that will lead you in the right direction. Listen to where the data is taking you.

If you weren’t doing this, what would you be doing?

Gaudelli: As far as scientific careers are considered, I would likely be working in the field of antibiotics, most likely in a chemistry department at an academic institution. Multidrug antibiotic resistance is a serious threat to human health, and we need to continue to tirelessly innovate in this area of research. Nature provides many solutions to our problems; we just need to spend the time and exercise the care to discover her secrets.

Alternatively, I would love to teach flute lessons and perform in a professional ensemble. (I love the Boston Pops!) I also love animals and would find a lot of enjoyment in operating a doggie hotel and animal shelter.

Drug Discovery


John McCaffertyJohn McCafferty, PhD

Founder and CEO, Iontas



What have been the biggest advances in your field over the past few years?

McCafferty: We first described antibody phage display in 1990, and this heralded a revolution in the ability to create and engineer human antibodies. It became possible to select antibody genes to any target from these massive libraries based on the binding properties of the encoded antibody. In the years that followed, novel display platforms with additional advantages were generated, including yeast display and mammalian display. Liberated from the need for immunization, novel binding molecules based on alternative scaffolds were created. Display technologies created a world of opportunity! Medicines have been created which improve and extend the lives of patients.

What’s your vision for the future of the field over the next 5–10 years?

McCafferty: There are approximately 300 human antibodies in Phase II/III clinical trials and a similar number in Phase I, so there will be no shortage of novel antibody products. Antibody developers have realized that in addition to affinity and specificity, antibodies need to have good biophysical properties. Prescreening for aspects of “developability” and using technologies such as mammalian display during the discovery process can help select “developable” antibodies. Also necessary are improvements in cell line development,
production, and downstream processing.

I have become interested in extending the benefits of recombinant antibody technology into the world of antivenoms. The first point of intervention remains the use of animal-derived antiserum with ensuing problems of anaphylaxis, poor reproducibility, and variable potency. We need to bring the benefits of recombinant antibody technology to this field.

How did you get into your field?

McCafferty: I jumped into commercial research in the “blue skies” corporate research group at Amersham International. As profits fell, however, blue skies turned to grey, and a decision was made to close the corporate research group.

This was the impetus to start Cambridge Antibody Technology. Six months later, I found myself working in Greg Winter’s group.

After another stint in academia, I formed Iontas, a biotechnology company that uses phage display technology. In this period, I also developed a technology that allows the construction of very large mammalian display libraries and permits the direct discovery of high-affinity antibodies with optimal biophysical properties.

I have also led the development of a novel molecular fusion format (KnotBody™), wherein naturally occurring, venom-derived cysteine-rich peptides (knottins) are inserted into peripheral complementarity-determining region loops of an antibody. The technology has already been used to generated Knotbody blockers to three different ion channel targets.

What was the biggest eureka moment or near-miss in your career?

McCafferty: I still clearly remember an ELISA experiment I did in early 1990 which confirmed that I had, for the first time, achieved the display of functional antibodies on phage. My co-founders (Sir Greg Winter and Dave Chiswell) and I had seen a 1988 paper from George Smith describing the display of linear peptides on phage, and we set about extending this to antibodies.

For the first half of 1990, I worked in Greg’s lab, where I built a vector which fused an anti-lysozyme antibody with the minor coat protein of filamentous phage. Some sheep anti-phage antiserum was found in the bowels of the freezer, and the components came together that day to give the substrate color change in the correct test wells! In the weeks that followed, I showed that we could achieve a millionfold enrichment of lysosome-binding phage over nonbinding phage, and we published this work in our Nature paper of December 1990.

What’s the biggest question the next generation of researchers should be asking?

McCafferty: It is humbling that even today when we create knockout mice or interfere in biological processes in vivo, we often do not know what the precise outcome will be. This highlights our lack of knowledge of biology as an integrated system. As more pharmaceutical companies circle around fewer viable targets, the identification of new validated targets will be no bad thing.


Robert PlengeRobert Plenge, MD, PhD

Senior Vice President, Research and Early Development
Bristol-Myers Squibb


What have been the biggest advances in your field over the past few years?

Plenge: There have been two: (1) a deeper understanding of the genetic basis of disease, and (2) the ability to pharmacologically modulate genetic nodes with unique therapeutic modalities. Just 15 years ago, there were few reproducible genetic variants associated with complex traits; now there are tens of thousands of variants associated with a wide variety of disease and quantitative traits. Back then, nearly all approved therapies were for small molecules or biologics; now there is a panoply of therapeutic modalities, including nucleic acid therapies, cell therapies, stem cells, and CRISPR approaches. We will soon have the ability to match genetic mechanism with therapeutic modality to recapitulate causal human biology, enabling us to invent medicines that will transform patients’ lives.

What’s your vision for the future of the field over the next 5–10 years?

Plenge: I hope we can “click” on any gene in the genome to generate, instantaneously, genetic dose–response curves. This will require more sequence data and more functional data, all linked to clinical data from the real world.

While we’ve made progress unraveling the genetic basis of complex traits, there are many variants yet to be discovered—especially in the rare/low-frequency allelic spectrum. Genome sequencing in extremely large patient populations will likely uncover a spectrum of alleles for each gene. As the functional consequences of these alleles are understood, it should be possible to use an allelic series to create genetic dose–response curves for the majority of human genes. These function-phenotype maps should provide information to guide critical aspects of drug discovery: mechanism, magnitude, and markers of therapeutic perturbation. Such functional genetic information, especially when combined with novel therapeutic modalities, should lead to more efficient and impactful drug R&D—and ultimately help patients.

How did you get into your field?

Plenge: As an MD-PhD student at Case Western Reserve, I was fortunate to be in a progressive lab surrounded by talented graduate students, postdocs, and faculty members just as the human genome project was being launched. There was a sense of excitement that human genetics could help patients, although the exact clinical applications were still unclear. As my clinical and scientific training advanced, I became more and more convinced that a major application of human genetics would be through the invention of new medicines. I made the move from academia to industry and entered the trenches of genetics and drug discovery.

What is holding your field back?

Plenge: Two areas are required to generate genetic dose–response curves: (1) access to extremely large cohorts where genetic data are linked to phenotypic data, and (2) a deeper understanding of the functional impact of variants, genes, and pathways on physiology. For the former, we need to release human genetics into the wild.

We need more genetic information on individuals linked to real-world clinical data. Genetic data linked to electronic health records is a good start, but this is only the beginning. For the latter, we need physiologically relevant, high-throughput assays that faithfully recapitulate human biology, and we need to study trait-associated alleles in these assays. What makes these assays particularly challenging is there is not a one-size-fits-all approach for all physiological traits.

What’s the biggest lesson you’ve learned in your career that you wished newer investigators knew?

Plenge: If you think you have a great idea, run with it. Trust your instincts, and don’t give up, despite the skeptics. . . . There are many good ideas out there. You need the passion, conviction, and persistence to develop an idea when nobody other than your dog believes in you.

What’s the biggest question the next generation of researchers should be asking?

Plenge: How are we going to cure chronic diseases in a way that is cost-effective for society?



Deanna M. Church, PhD

Deanna M. Church, PhD

Senior Director, Mammalian Applications


What have been the biggest advances in your field over the past few years?

Church: The ability to do genomic analysis at the level of the single cell. This has always been the holy grail, but it was not really achievable until relatively recently. Now it’s gone from being something that a few experts can do to a method that is being done routinely. These data are providing a new level of detail and understanding while providing the ability to generate new cellular models in ways that have not been available before.

What’s your vision for the future of the field over the next 5–10 years?

Church: To continue to improve on single-cell biology, moving from just being able to make the measurements to really being able to develop more robust cellular models. For example, there was a very interesting paper that came out recently from a large consortium demonstrating the value of carrying out a genome-wide assessment of quantitative trait loci (QTL) for many induced pluripotent stem cell lines. I think this paper is exciting as it shows the utility of cellular models to help identify molecular phenotypes and allows identification of variants relevant to development stages.

These new cellular models, coupled with genome editing and genome engineering, will be a powerful combination for us in the future. This will allow us to think about moving from observational biology, with sometimes pretty squishy phenotypes, to thinking more about interventional biology with fine-grained molecular phenotypes. That doesn’t mean that we won’t look at the whole organism. Eventually, even if you have a nice molecular phenotype, you want to go back into the organism and understand how that might impact the phenotype at the organismal level, and how that might influence disease. But I think that these tools will give us the power to break down phenotypes that were previously inaccessible.

How did you get into your field?

Church: So, it’s kind of funny. . . . I started in genomics because I did not get into graduate school the first time around. So, I went and worked as a technician for a couple of years with Alan Buckler when he was a postdoc with David Housman at the Massachusetts Institute of Technology.

This is before the human genome project got going in earnest. We didn’t have a reference assembly, and Alan’s focus was on developing tools to allow us to identify genes in a high-throughput fashion. This was my first foray into genomics, and it was a very exciting area to work in. We identified some of the first gene associations.

Working for Alan for the first couple of years of my career not only got me on the pathway of genomics, it also piqued my interest in developing tools for the community, which is something that I still do today. So, it actually worked out really well for me that I didn’t get into graduate school the first time. At the time, it seemed devastating. In retrospect, it was a great thing.

Are there any trends in your field that you find alarming?

Church: This is not really specific to my field, but the challenges that academic researchers face in trying to obtain funding is alarming. There is such a large emphasis being put on translational research today, but I think that that is a mistake, particularly at the academic level, which is not only where scientists are trained but also sits at the center of basic research discovery.

It’s very difficult to predict which discoveries are going to lead to the next breakthrough products. Some of the early understanding of mutations in genes involved in colon cancer came about from work done studying DNA repair mechanisms in yeast. And the training that happens at academic institutions is incredibly important. We need highly trained scientists out there. This lack of appreciation for basic research in the academic arena is what I find most concerning.

I don’t know what the solutions are. . . . Maybe we as scientists need to do a better job of explaining to everybody why research on a fruit fly or yeast is really important. Getting society to have a larger appreciation of that would help all of us.

What is your favorite science fiction movie and why?

Church: Blade Runner is one of my favorite science fiction movies. You can watch that movie today, and it stands up—well, as long as you can ignore the fact that the movie is set in November 2019, which we have already passed, obviously. But the rest of it stands up.


David HausslerDavid Haussler, PhD

Distinguished Professor of Biomolecular Engineering, University of California, Santa Cruz, and Scientific Director, UC Santa Cruz Genomics Institute; Scientific Co-director, California Institute for Quantitative Biosciences (QB3); Investigator, Howard Hughes Medical Institute

What have been the biggest advances in your field over the past few years?

Haussler: The ability to CRISPR-edit stem cells, including mouse, chimp, and human stem cells, and then grow them into organoids in the lab. My dream for decades has been to peer into human evolution at the level of individual genes and gene functions, directly experimenting with genetic modifications by verifying their effects on tissues in organs in the lab. It’s incredibly exciting that we’re able to do that now.

In 2013, when we presented our initial findings on the recently evolved human-specific Notch gene NOTCH2NL, the general reaction was, “amazing if true.” We spent the next five years working to convince everybody. The development of the CRISPR-Cas9 system provided a crucial tool for our work—as it has for so much other work—along with organoid technology.

What’s your vision for the future of the field over the next 5–10 years?

Haussler: I see a future where we routinely sequence complete, diploid human genomes with long-read technology, both in research and in clinical practice. That will allow us to understand the effects of rare mutations for the first time, including mutations in the currently impossible-to-sequence regions of the human genome, such as [the part of] chromosome 1q21.1 where NOTCH2NL resides. This region is associated with autism, schizophrenia, attention deficit hyperactivity disorder, and other conditions.

We’re betting on long-read sequencing technology to provide a complete, accurate understanding of human genome variation at all scales, from point mutations to large-scale rearrangements and duplications, and we’re launching a new “pangenome” initiative from the National Human Genome Research Institute to obtain at least 350 new reference genomes from people all over the world, each sequenced in diploid form with chromosomes more complete than those in the current reference genome. One human reference genome cannot represent all of humanity.

We must also move toward more data sharing, so that we can understand very rare or statistically subtle effects, which collectively dominate biomedical phenomena.

How did you get into your field?

Haussler: The summer after my freshman year in college, my brother invited me to learn to do science in his lab at the University of Arizona. We soon had a paper in Science, my first publication. I was hooked. My most unique contribution was the math, so that is what I pursued first. But I later came back around to biology and have always loved the combination of the two.

What was the biggest eureka moment or near-miss in your career?

Haussler: In 1985, Robert Sinsheimer convened the world’s experts at UC Santa Cruz to examine the possibility of sequencing the entire human genome. Most of his colleagues thought that attempting to read all that code was crazy. But other visionaries held similar meetings at Cold Spring Harbor and elsewhere, and the Human Genome Project (HGP) was born in 1990. My group developed methods to find the protein-coding regions of genes in a sequenced genome (“gene finding”), and in 1998, we applied these methods to the fly genome, which had been sequenced by Celera.

I joined the HGP to apply these methods to the human genome, but my group ended up focusing on the assembly of human DNA fragments into coherent chromosomes. That moment was my career highlight, the moment I’m most proud of. Humanity got its first glimpse of its genetic heritage, free and unrestricted.

What is holding your field back?

Haussler: Computational genomics and machine learning can succeed in revolutionizing biomedicine only if algorithms have access to a significant fraction of the biomedical data. Right now, virtually all data are locked up in tiny separate silos. I’m hoping that with organizations like the Global Alliance for Genomics and Health, we can break through this barrier.

Cancer Research


David Tuveson

David Tuveson, MD, PhD

Roy J. Zuckerberg Professor of Cancer Research and Director of the Cancer Center at Cold Spring Harbor Laboratory; Chief Scientist, Lustgarten Foundation


What have been the biggest advances in cancer research over the past few years?

Tuveson: The clinical approval of immunotherapy and multiple targeted therapies for cancer patients was an important outcome. Last year, the FDA had over 10 approvals for cancer patients, according to Norman Edward “Ned” Sharpless, director of the national cancer institute. Also, genetic tests have been developed that now help triage patients in clinical trials. Our new challenge is to develop predictive biomarkers for cancer patients, and organoids may be one approach for this.

What’s your vision for the future of cancer research over the next 5–10 years?

Tuveson: In the next 10 years, I would like to see changes in clinical trial design, so that patients can be exposed to many different therapies in efforts to find the ones that work. Combination therapies have been hard to develop, and we need to work harder to design safe combinations—for example, cytotoxic therapies with targeted, immune, and radiation therapies.

How did you get into this field?

Tuveson: Cancer aroused my curiosity when I was young as it seemed very mysterious. As I have aged, I have learned to hate cancer because, sadly, it has killed many people I have known, and many patients I have treated.

What is the most significant lesson you’ve learned over the course of your research career that you would like to impart to new investigators just entering the field of cancer research?

Tuveson: Pick a problem that seems very interesting to you, and don’t get discouraged if others tell you it’s too hard to work on. If you work on something you love, only good things will happen in the course of your research.

What’s the most important question the next generation of researchers should be asking?

Tuveson: The next generation should not follow the paths of those before them. They should learn from the past, but they should ask themselves how they might design therapies and diagnostics that will profoundly improve on what exists in the clinic today. Their job as cancer researchers is to put themselves out of work, so they should act like it. When they succeed, they can pursue second careers.

Gene Therapy


Terence R. FlotteTerence R. Flotte, MD

Executive Deputy Chancellor, Provost, and Dean of the University of Massachusetts School of Medicine; Editor in Chief, Human Gene Therapy, published by Mary Ann Liebert, Inc.


What have been the biggest advances in your field over the past few years?

Flotte: The application of in vivo recombinant adeno-associated virus (rAAV)-based gene therapy for single-gene disorders took a quantum leap forward with the availability of many more serotypes in the early 2000s. This allowed for the use of rAAV vectors with enhanced tropisms for organs and tissues such as retina, spinal cord, brain, liver, and muscle. Clinical efficacy in small trials in rare monogenic disorders resulted in the years that followed, mostly coming to light between 2008 and the present. More recently, rAAV vectors have been used to deliver the machinery for more sophisticated means of gene regulation, such as synthetic miRNAs and CRISPR. In parallel to this, the refinement of safe recombinant lentivirus vectors has provided the basis for ex vivo gene therapy, including chimeric antigen receptor (CAR) T-cell immunotherapy for cancer and hematopoietic stem cell gene therapy for immune deficiency and hematologic disorders.

What’s your vision for the future of the field over the next 5–10 years?

Flotte: A range of in vivo rAAV gene therapies and ex vivo lentiviral gene therapies will demonstrate clinical efficacy, and many more will reach the stage of being FDA- and EMA-approved products. In the meanwhile, the various versions of gene editing, base editing, and prime editing will be tested in various preclinical proof-of-concept and early-phase clinical trials, and the benefits and limitations of each system will be clarified.

How did you get into your field?

Flotte: I began my gene therapy research career in 1989 as a postdoctoral research fellow funded by the Cystic Fibrosis Foundation (CFF) with a mission to create rAAV vectors suitable for cystic fibrosis gene therapy. I was sent to work at Johns Hopkins Pediatric Pulmonary for three years in the laboratory of Barrie Carter at the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) intramural program in Bethesda, MD. In 1995, after starting my own lab at Johns Hopkins, I was able to initiate the first human trial of our rAAV2-CFTR vector in adult cystic fibrosis patients with mild lung disease, in a program that had, since 1993, both CFF and National Heart, Lung, and Blood Institute (NHLBI) funding. I have had continuous funding from the NHLBI (and additional funding from NIDDK, the National Eye Institute, and the National Center for Research Resources) for rAAV gene therapy for single-gene disorders ever since, 26 years and counting.

What was the biggest eureka moment or near-miss in your career?

Flotte: While doing late-stage preclinical and clinical trials of rAAV, we made several observations regarding the basic biology of these vectors. The most interesting of these was published in 1994 and 1996. Our initial observation was that rAAV persistence was primarily episomal in airway epithelial cells. This was one of the fundamental limitations of rAAV’s application to rapidly dividing cells like epithelial cells. While it proved to be a major limitation to cystic fibrosis gene therapy, it was ultimately an important aspect of the vector platform that logically led to the application of rAAV to disorders of the central nervous system and retina.

How is your field going to “translate” to help patients? What do you want to see happen?

Flotte: So far, the successes of gene therapy are primarily in single-gene disorders. The value of these therapies for these individual patients and families is immense. However, many more individuals and families would be helped if effective gene therapies could be developed for more common serious diseases, like Alzheimer’s disease or solid tumors. We may not be far away from some of these.

If you weren’t doing this, what would you be doing?

Flotte: If I weren’t in medicine, I would be a historian … and not particularly in the history of medicine or science, either. History is the story of the human experience and the record of the decisions that humans have made. I believe that we are shaped much more by what we choose to do than by either our genes or our environment.  


Nicole K. PaulkNicole K. Paulk, PhD

Assistant Adjunct Professor, Biochemistry and Biophysics
School of Medicine, University of California, San Francisco



What have been the biggest advances in your field over the past few years?

Paulk: Gene therapy is experiencing the most remarkable moment ever right now, and we’re all living through it. We have two FDA-approved viruses that are medicines! For Leber’s congenital amaurosis and spinal muscular atrophy, you can go to your normal family care physician with a diagnosis and get a prescription—for a virus! This never really gets old for me. It’s why I’ve dedicated my entire career to this. I get paid to do the coolest thing I can imagine.

What’s your vision for the future of the field over the next 5–10 years?

Paulk: The next decade in gene therapy is going to be positively wild! With the current rate of trials and treatments in the queue for approval at the FDA, we’ll have approved viral gene therapeutics to treat, and in some cases cure, about 5–20 new rare diseases/year in the next several years. In a decade, it’s not inconceivable that we’ll beat back 200 diseases. Think about that! This will be the biggest transformation in medicine since antibiotics and vaccines. I’m personally committed to curing two of those diseases myself. One of the cures, for a common disorder, would really move the needle on global health. The other cure is for an ultra-rare disorder. I got my start working in rare liver diseases with kids, and I owe it to those families to follow through, even if I have to self-fund it.

How did you get into your field?

Paulk: I joined a lab that worked on liver biology and got really interested in the idea of using viruses to treat several of the rare liver diseases they worked on. My professor liked my work ethic and asked me to join his lab as a graduate student. My first couple of projects worked out well, and before I knew it, we had six papers in four years. I was hooked. I was a viral gene therapy “lifer.”

What was the biggest eureka moment in your career?

Paulk: Discovering that adeno-associated virus (AAV) has post-translational modifications. At a major conference, I heard folks presenting on a failed trial. Nobody knew why there wasn’t any expression in these patients when all the preclinical data had looked great. I
agonized about it the whole flight home and wondered if the dogma (that said AAV had no post-translational modifications) was wrong. I became convinced that different species of cells (human and insect) we use to manufacture this virus were producing different viruses, with modifications, and that this was contributing to the functional differences we were seeing clinically. I walked over to the mass spectrometry core facility with a vial of AAV and asked, “Will you run this for me?” A week later, I got a spreadsheet back with the litany of viral capsid modifications … and fell out of my chair. I’ve been studying this ever since.

What’s the biggest lesson you’ve learned in your career that you wished newer investigators knew?

Paulk: It’s important to choose your mentors wisely. You need to ensure that this is someone who has your best interests at heart, and who has a history of championing their mentees. Ideally, you’ll have more than one, so you’ll have diverse viewpoints when you seek guidance. A good mentor can guide you through any difficulty, brainstorm with you on the most intractable problems, place those critical phone calls that will make hurdles disappear, and be your champion throughout your career.

Are there any trends in your field that you find alarming?

Paulk: I’m worried how comfortable gene therapists are with financial conflicts of interest. Our field has exploded with new therapies. However, those successes have come with a lot of money, and money can be a poison. I can’t name a single gene therapy professor who doesn’t have financial conflicts of interest—lucrative patents, spin-off companies, paid board positions, speaking and consulting gigs, grants from big pharma, and more. While none of these are necessarily bad, if they remain undeclared or, even worse, go unmanaged by the university, they can lead to all sorts of problems: pressure to falsify or hide damaging data, misleading the public, as well as harassment of and retaliation against trainees. Such misdeeds could even harm patients. We need to enforce declaration and management of these conflicts as our field swells with success.



Jack GilbertJack Gilbert, PhD

Professor, Department of Pediatrics and Scripps Institution of Oceanography, UC San Diego School of Medicine


What have been the biggest advances in your field over the past few years?

Gilbert: In my opinion, it has been the full integration of microbiome and metabolomics research, and the integration of these new tools into clinical trials. The use of combined data to provide fine-resolution stratification of populations by disease state or treatment outcome, combined with the identification of host receptor targets, including small molecules and immune activators for use as therapies, has been profound. A large proportion of this comes from the development of novel analytical tools, including the use of artificial intelligence and network-based platforms, such as MMvec, which is used to create microbe-metabolic vectors.

What’s your vision for the future of the field over the next 5–10 years?

Gilbert: We are focused on targeted preclinical and clinical trials that can be used to demonstrate the effectiveness of better biomarkers for predicting successful outcomes from clinical trials, as well as testing new therapies using known targets. The rapid development of sensor platforms and automated sampling of microbiome and metabolome profiles will make continuous microbiome analysis routine in large-scale clinical studies, providing unparalleled access to longitudinal observations of microbial dynamics. When combined with advanced tools for analyzing the volume of data generated by these approaches, we will see discovery of new therapeutics rapidly accelerate, as well as the vision for precision healthcare mediated by new biomarkers.

How did you get into your field?

Gilbert: I am interested in how things work and have always been able to see connections between disparate systems. I started life as an ecologist, and I am still one, in my opinion. I just apply systems thinking to the exploration of how microorganisms communicate with each other and with the world around them. I got into my field partly through necessity and partly through a drive to discover new ways of looking at our invisible worlds.

How is your field going to “translate” to help patients? What do you want to see happen?

Gilbert: The biggest thing in the next five years for patients will be an ability to harness artificial intelligence in your hand that can improve detection of minor issues and provide advice on mitigation, which will require appropriate technology, sensors, and screens. I believe the microbiome will be part of that screening technology, especially with toilet sensors and automatic collection and analysis platforms.

If you weren’t doing this, what would you be doing?

Gilbert: Surfing or playing in a band—mind you, I try and do those things anyway, but I would definitely do a lot more of them with my family.


Stephanie CullerStephanie Culler, PhD

Co-founder and CEO, Persephone Biome



What have been the biggest advances in your field over the past few years?

Culler: There have been many advances. One of the biggest has been the discovery that gut microbes can impact and modulate the efficacy of cancer drugs, most notably checkpoint inhibitors, a type of immunotherapy which activates the immune system. The same microbes can serve as diagnostic biomarkers for patient response to these drugs which in turn will help with selecting or stratifying patients that will most likely respond to these curative treatments. These findings have led the development of live biotherapeutic products (LBPs) that are aimed at enhancing the efficacy of current FDA-approved checkpoint inhibitors. Several LBPs have entered clinical trials with early readouts anticipated later this year.

What’s your vision for the future of the field over the next 5–10 years?

Culler: My vision for the future of the microbiome field over the next 5–10 years is one where functional omics analysis of patient biospecimens are routinely integrated into microbiome drug development pipelines, standardized animal models for translational research will be developed, the FDA will have a clearly defined regulatory roadmap for LBPs and robust chemistry, manufacturing, and control (CMC) processes for anaerobic bacteria will be established.

How did you get into your field?

Culler: I was previously a synthetic biologist at an industrial biotechnology company (Genomatica) engineering microbes for the sustainable production of chemicals. Over the last several years, I became fascinated by the role of the gut microbiome in human health and its impact on the activity of cancer drugs. Much of the data in the microbiome space has been correlative, and I felt compelled to leverage the skills I had developed as a chemical engineer in microbial systems and synthetic biology toward elucidating the mechanism of how the gut microbiome impacts the immune system. So, in the summer of 2017, I founded Persephone Biome, a technology platform company that uses machine learning to rapidly develop microbial immunotherapies for cancer patients of severe unmet needs.

If you weren’t a scientist, what nonscience career path would you have chosen and why?

Culler: I would have become a professional violinist. I started playing the violin when I was in elementary school and quickly fell in love with performing classical music. As a young teenager, I was fortunate to tour Europe with my youth symphony and spent a summer at the prestigious Interlochen Arts Academy.

Are there any trends in your field that you find alarming?

Culler: In the microbiome field, there has been a lot of hype encouraged by consumer companies in the probiotics and sequencing spaces. This may be an area where additional regulatory oversight is needed to provide consumers with safe over-the-counter products and physician-reviewed health analyses.

Has there been a person or an event that has had a large influence on your career path?

Culler: I was inspired to attend Caltech for my graduate studies in the Department of Chemical Engineering by the pioneering work in directed evolution conduced in the lab of Frances Arnold, the 2018 Nobel Prize awardee in chemistry. Since my time at Caltech, Arnold has served as a continued role model through her academic, entrepreneurial, and industrial accomplishments.


Richard PetersRichard Peters, MD, PhD

CEO, Yumanity Therapeutics



What have been the biggest advances in neuroscience over the past few years?

Peters: There are several advances to call out, including the better understanding of genetic drivers of disease, tools to probe brain activity at the bench in a meaningful way (with CRISPR-edited and iPSC-derived stem cells, for example), novel imaging technology that enables us to monitor the initiation and progression of disease, and the ability to select more homogeneous groups of participants for clinical trials—to name a few! In addition, we have seen a paradigm shift in research with a greater appreciation for the potential role of lipid metabolism and lipid signaling, the immune system, and the complex interplay between genetics and environmental risk factors.

What’s your vision for the future of neuroscience research for the next 5–10 years?

Peters: I believe we are at a key inflection point for neuroscience R&D and expect significant breakthroughs in the field, analogous to HIV in the 1990s or cancer therapies over the past two decades. The famed Nobel laureate and physicist, Richard Feynman, said that if one is to achieve a breakthrough, one must approach a problem from a totally different perspective. Too often in neuroscience, scientists and companies have repeated the same approach and used the same mental constructs while expecting different outcomes. . . . It is time to think differently. We need to adopt and utilize key breakthroughs from other fields. At Yumanity Therapeutics, for instance, we are applying an unbiased yeast-based phenotypic screen to discover numerous novel targets previously unknown in neurodegeneration. Other advances will come from immunotherapy, gene/mRNA therapies, and digital or neurotech therapeutics/devices.

How did you get into your field?

Peters: I have always looked to tackle challenges where I could have maximum impact by addressing significant medical needs. I have evolved from oncology to rare diseases, and now to neurodegenerative diseases, as I believe that developing therapeutic options for neurodegeneration is the greatest medical opportunity of our time.

What is the most significant lesson you’ve learned over the course of your research career that you would like to impart to new investigators just entering the field of neuroscience?

Peters: The paramount importance of testing drugs in well-defined patient populations so that the treatment effect can be clearly documented. Avoid cherry-picking results; look for maximum treatment effect size. Don’t worry about market size as the business will take care of itself if patients are helped.

What’s the most important question the next generation of neuroscientists should be asking?

Peters: Are we better understanding the biology of the brain, and are we able to translate that understanding of pathways and biology to identify new and relevant targets? The field is in desperate need of new targets. Unlike any other organ, the brain is uniquely complex, and we need to better understand where to intervene to stop degeneration.

Artificial Intelligence


Tom ChittendenTom Chittenden, PhD, DPhil

Chief Data Science Officer and Founding Director, Advanced Artificial Intelligence Research Laboratory, WuXi NextCODE


What have been the major advances in AI in the life sciences over the past few years?

Chittenden: Without a doubt, one of the most significant advances is the integration of robust causal inference and probabilistic programming into machine learning (ML) strategies. In our lab, we now rigorously apply causal inference to all our ensemble AI/ML strategies. This gives us the ability to build putative causal dependency structures within high-dimensional, genome-wide multiomics datasets to find the causal drivers of human disease. In the simplest terms, we are taking the first revolutionary steps from medicine based on correlation to medicine based on causal understanding.

We didn’t have any hand in the 3.5 billion years of natural engineering underlying human biology, but AI/ML strategies are giving us the ability to reveal the rules that govern this molecular and cellular complexity. We now have empirical evidence indicating that our toolkit works: that we are indeed uncovering these causal dependency structures, the signal transduction cascades that drive cellular behavior. Further research in this area will ultimately allow us to advance more effective therapeutics based on interrupting disease progression precisely where we want.

What’s your vision for the future of AI over the next 5–10 years?

Chittenden: Human biology is the most complex system that exists. AI—particularly as applied to life sciences—will prove to be the most transformative technology in human history. To advance it, our lab develops “narrow AI” methods, including deep learning, statistical machine learning, and probabilistic programming to analyze large, high-dimensional, genome-wide biological datasets. In the last two years, we have gained significant new insight into the mechanisms of cancer and cardiovascular disease at the single-cell level, and we are striving to apply our understanding of the complex molecular interactions that drive cellular behavior to develop more effective therapeutics.

To take the next steps, my team is investigating the use of unconventional high-performance computing architectures, such as quantum and neuromorphic computing, to address current limitations related to large-scale statistical optimization in AI/ML. Advances in these unconventional computing technologies will provide the means to fully address human disease. Specifically, the design and application of robust quantum ML and deep spiking neural networks (SNNs) will allow us to understand virtually any disease in much greater depth using cost-effective experimental designs. This is an absolutely fundamental capability for creating precision medicine, and the result will be a range of validated potential endpoints for developing more effective therapeutic interventions, validated markers for designing smaller clinical trials with a greater chance of success, and a wealth of information for identifying patients likely to respond to approved compounds.

How did you get into your field?

Chittenden: I have always had a keen interest in knowing how things work, and thus, I was naturally attracted to the biomedical sciences. In graduate school, I came to the realization that if I wanted to truly understand human physiology, I needed to expand my knowledge of biochemistry and molecular and cellular biology. As my sense of the scale and complexity of the data and processes in biology and disease grew, I was drawn to AI/ML for its unique potential to unravel this complexity. If designed and applied responsibly, AI/ML has the potential to help scientists understand, at a much greater depth, the molecular underpinnings that drive cellular behavior and dictate phenotype. Armed with this information, we will be able to ultimately design more effective therapies.

What is the most significant lesson you’ve learned over the course of your research career that you would like to impart to new investigators just entering the field of AI in the life sciences?

Chittenden: Biology is extremely complex, and biological data and processes are intrinsically different from and more complex than those in computer science. Our work has given me a much greater appreciation for these differences and the need for understanding
the complexities of cellular behavior and human biology. While statistical machine learning methods are teaching us the rules that govern molecular and cellular biology, it is vital that the next generation of AI/ML investigators possess formal academic training in the biomedical sciences.



Chris DwanChris Dwan, PhD

Independent Technology Consultant



What have been the biggest advances in your field over the past few years?

Dwan: The “cloud” is finally mainstream and boring. Silly, absolutist cloud vs. on premises arguments have given way to nuanced and thoughtful analysis. This is a big deal. Cloud native data architectures have great potential to enable data reuse and collaboration. This shift will enable machine learning technologies, which have also hit their stride.

What’s your vision for the future of the field over the next 5–10 years?

Dwan: As William Gibson said: “The future is already here. It’s just not very well distributed.” We use amazing, secure, trustworthy digital technologies to consume media and entertainment, to manage our money, and to buy and sell goods. It is jarring to shift back and forth from that modern framework to the arcane legacy silos of technology I find in laboratories, clinical research, and electronic medical record systems. While modernizing these systems will come with significant challenges to privacy and regulatory compliance, I’m optimistic that we are up to the task.

How did you get into your field?

Dwan: In 2000, I joined a bioinformatics group at a midwestern university where I investigated scaling our computing and storage systems to keep pace with the volume of data generated by next-generation sequencing.

A few years later, I joined a small biological information technology consulting company. I got to work all over the country solving problems of scale, interoperability, and processing for groups in industry, government, and academia. I helped start the New York Genome Center and lead the information technology organization for another [Ed.—the Broad Institute]. There was no forward-looking career plan. Rather, it felt like a series of “right place, right time” accidents where people offered interesting problems that were barely within reach of my skills.

What’s the biggest lesson you’ve learned in your career that you wished newer investigators knew?

Dwan: Domain expertise matters. There is a huge difference between summarized knowledge of the sort that comes from popular science books, as opposed to the deep expertise and intuition that comes from actually doing the work. Computational biology is littered with stories about well-intentioned, brilliant mathematicians, physicists, and computer scientists who initially failed to appreciate the depth and complexity of biology and wound up wasting a lot of people’s time. I expect us to recapitulate this as we bring machine learning and even artificial intelligence to bear.

Are there any trends in your field that you find alarming?

Dwan: Health systems are under incredible pressure to monetize their data holdings by sharing them, deidentified of course, with pharma and technology companies. While this has the potential to accelerate discovery, progress will come at the expense of patient privacy.

The Health Insurance Portability and Accountability Act standards for data handling and deidentification are inadequate to preserve our anonymity, particularly when we’re talking about the analytical firepower of organizations like Amazon and Google. These “anonymous” medical records and other information will quickly be reidentified and linked with the other digital traces. I’m not seeing nearly enough thoughtful conversation about insisting that we all benefit directly from the inevitable sharing and exploitation of our personal data.

What else would you like to talk about?

Dwan: 2020 should be the year that we commit to addressing the enduring legacy of bias, cronyism, nepotism, sexism, abuse, neglect, and outright bigotry that biomedicine inherited from our broader culture. While we have made substantial progress on this front, biotech still lags other fields in terms of inclusion, equity, and diversity. We have a terrible case of the Grand Old Man syndrome, in which we gloss over toxic and abusive behaviors of senior contributors as though they were mere personality quirks.

I know of several instances where junior staff members were pushed out of their jobs to prevent “embarrassment” to the professor or executive who abused his power over them. We’re punishing the wrong people, and it’s time to make a change.



John R.Yates IIIJohn R. Yates III, PhD

Professor of Chemical Physiology, Scripps Research



What have been the biggest advances in proteomics over the past few years?

Yates: Proteomics has been very incremental over the past five years. There have been advances in mass spectrometers that have enabled things like top-down mass spectrometry and native mass spectrometry. Single-cell proteomics has really started to come on strong.

A second area is structural proteomics—trying to look at the 3D proteome, to get information about what protein conformations
exist inside cells and tissues, and then trying to relate that to how protein conformations might change as a function of some kind of disease. That comes into play when you are looking at misfolding diseases—Alzheimer’s, Parkinson’s, etc.

The third area is precision medicine. How can measurements from targeted proteomics enable more personal applications?

Another area I’m really excited about is metaproteomics—the ability to look at proteins inside a microbiome. Metagenomics allows you to see the population of microorganisms that are present. But metaproteomics really allows you to start asking questions such as, what metabolic activity is going on inside the microbiome?

What is your vision for proteomics over the next 5–10 years?

Yates: Single-cell proteomics is going to be huge. One of the questions I often get from NIH program officers is, what is the status of single-cell proteomics? I think the NIH is going to start investing in it more and more. And the 3D structural proteome is also going to be a pretty exciting area.

How did you get into your field?

Yates: I’ve always been in this field! My PhD dissertation was entitled, “Protein Sequencing by Tandem Mass Spectrometry.” Back then, it was called protein biochemistry, and when I started my independent career, one of the things I was very interested in was trying to come up with algorithms as a way to interpret the tandem mass spectra of peptides. As the genome project progressed, that got me into developing algorithms for using databases as a way to interpret tandem mass spectra of peptides. And that evolved into trying to scale it up to look at whole proteomes.

When proteomics started back in the early 1990s, the bulk of the field was really interested in using mass spectrometry technology as a way to identify bands or spots on gels. My interests deviated from that because I had this new algorithm that would allow us to interpret tandem mass spectra of peptides. My interest became, how can one eliminate the use of gels and digest protein mixtures directly, and then analyze them on the mass spectrometer and interpret the data. Then we started working on shotgun proteomics as a way of eliminating gel electrophoresis as a way to identify proteins that are in mixtures. [Yates developed the SEQUEST algorithm for automated peptide sequencing and multidimensional protein identification technology (MudPIT)—Ed.]

What is the most significant lesson you have learned over the course of your career?

Yates: Persistence and tenacity. A system is designed to say no, and you have to be persistent and tenacious and develop a thick skin.

What should the next generation of proteomics researchers be asking?

Yates: What information in biological systems are we not capable of getting to right now? How can we go about getting that? Do you want to be addressing biological questions, or do you want to be developing technology?

Some of the technology frontiers are how to make things more sensitive, how to increase the scale, how to get at different kinds of information simultaneously. If you want to ask biological questions, consider how you can use this technology to ask questions that people are not asking. If we are asking the right questions but not getting answers, we should consider whether our technology is suitable?

If you weren’t doing what you’re doing now, what career path would you have chosen?

Yates: The answer probably would have been different at different times in my life. But one of the things I’m interested in recently is the process of innovation. Where does it come from? That, of course, leads into economics. I’ve been intrigued by issues of economic development.


Lisa JonesLisa Jones, PhD

Associate Professor, Pharmaceutical Sciences, University of Maryland



What have been the biggest advances in your field over the past few years?

Jones: The rise of proteome-wide structural biology methods has been a great advance in recent years. Mass spectrometry-based methods such as thermal proteome profiling, SPROX, chemical crosslinking, and in-cell fast photochemical oxidation of proteins (FPOP) can provide structural information on hundreds to thousands of proteins in a single experiment. These methods have been used for protein interaction network analysis and drug target engagement. They have been applied to a large number of cell systems, and in some initial studies, they have demonstrated efficacy in tissue samples. These methods contribute to a powerful strategy for studying proteins in their native environment.

What’s your vision for the future of the field over the next 5–10 years?

Jones: I would like these proteome-wide methods to be more accessible to other users. Currently, these methods are fairly specialized and utilized only by a handful of labs. This expansion of use would first and foremost require better data analysis software. Currently, for some methods, there is not a universal analysis platform. Rather, several research labs have developed in-house software for analysis, limiting the use of these methods by the broader community. Also, for the laser-based FPOP method, further developments that eliminate the use of a high energy laser will make it more tractable to a wider variety of labs.

How did you get into your field?

Jones: As a graduate student, I used NMR and fluorescence methods for structural studies on small model proteins. As I neared graduation, I realized that I wanted to work with large protein complexes. I accepted a postdoc position in the lab of Peter E. Prevelige, PhD, at the University of Alabama-Birmingham. He was using both native and hydrogen/deuterium exchange mass spectrometry to study virus capsids. This was my first introduction to mass spectrometry and its use for structural biology. Two years later, I moved to the lab of Michael L. Gross, PhD, at Washington University in St. Louis for a second postdoc. His lab had recently developed the FPOP method that I use in my current research. While there, I applied FPOP for epitope mapping, which has become a major application of the method. The irreversibility of the label makes the method highly suitable for the in-cell studies my lab currently uses it for.

If you weren’t a scientist, what nonscience career path would you have chosen and why?

Jones: I have always been interested in architecture and at one time seriously considered becoming an architect. The thought of designing a new building and watching it be erected was exciting.

Has there been a person or an event that has had a large influence on your career path?

Jones: Definitely Michael Gross. He was the one to encourage me to stay in academia and become a professor. My intention when I joined his lab was to go to industry. Somehow, he changed my mind and pushed me toward the path I am on currently.

What is your favorite science fiction movie and why?

Jones: I am a huge fan of science fiction movies, so this is a tough question. But for originality and a major shock moment, I would have to say the first Alien movie. Although it is almost older than I am and does not have the flashy special effects of the current movies, that moment when the alien bursts through the chest cavity is in my opinion without equal.

Ancient DNA


Dennis H. O’RourkeDennis H. O’Rourke, PhD

Foundation Distinguished Professor of Anthropology,
University of Kansas


What have been the major advances in ancient DNA and genetic anthropology over the past 5–10 years?

O’Rourke: It has mostly been methodological. Lab methods, particularly sequencing techniques, allow us to access more and higher quality data than we could have accessed 5 or 10 years ago, particularly in the ancient DNA field. Extraction techniques allow us to minimize contamination in ways we could not before, and next-generation sequencing techniques and approaches have certainly been a big boon to the work.

What is your vision for the future of human evolutionary genetics and ancient DNA?

O’Rourke: I expect to see more development and advancement in quantitative analytical methods and modeling. Given the plethora of data we are now able to generate, I think we will see new analytical methods developed. We will also see more modeling in human evolutionary genetics for testing of hypotheses in new and innovative ways.

From my own perspective, because I mostly work in ancient DNA, one of the things I hope for is a much more interdisciplinary and integrative approach to researching and studying the past through molecular and genetic methods. By this I mean a geneticist working closely with geologists, historians, archaeologists, and local and indigenous communities who also have a say, and to have the analyses done with full consultation in a
multivocal approach.

What was the most important lesson you have learned in your career that you wished newer investigations had known when they got into the field?

O’Rourke: One of the things that I keep coming back to is, I wish all of us paid a little more attention to history and especially the history of the discipline and what came before. As new research methods are developed, we forget that the methods that were used a decade ago or longer were techniques that addressed many of the same kinds of questions we ask today. Sometimes the inferences are similar to the ones we make with modern methods. If we are not aware of this, we lose something in our understanding. I am always harassing my graduate students and colleagues by telling them that they need to read the historical literature more to know why it is we think we know what we know.

What is the most important question the next generation of researchers should be asking about this field?

O’Rourke: Why are we doing what we are doing? Are the hypotheses we are attempting to test substantive ones? Are we really moving beyond some sort of database creation or description?

Some of the questions that we are beginning to address now—and we will be much better able to do this in the future—will have to do with functional genomics and, in evolutionary terms, selection versus other mechanisms of evolution because we will have the resolution with data and analytical approaches that we did not have in the recent past.

How did you get into this field?

O’Rourke: I started as a student with an interest in prehistory and history and soon learned as an undergraduate that history, in many ways, is archived in genomes. I became interested in utilizing that.

I was offered the opportunity to go to the field with a research team my first year in graduate school and became hooked on anthropological genetic approaches to understanding history and population structure and how they related to work that my archaeological colleagues were carrying out.

If you weren’t a scientist, what nonscience career path would you have chosen and why?

O’Rourke: I thought a good deal about a career in conservation or forestry. I am not sure that is nonscience, but it is a very different kind of science than what I ended up with as a career.


Maria Nieves-ColonMaria A. Nieves-Colón, PhD

Affiliated Researcher, School of Human Evolution and Social Change, Arizona State University


What have been the major advances in ancient DNA research over the past few years?

Nieves-Colón: In the past few years, ancient DNA research has matured into the field of paleogenomics. The advent of high-throughput sequencing methods and the adoption of more sensitive approaches for sampling, isolating, and capturing DNA from ancient tissues now allow for recovery of complete genomes from ancient organisms. Improvements in methods are also pushing the temporal boundaries of the field. It is now possible to obtain ancient DNA from Pleistocene remains such as those of Neanderthals and other hominids. This has shifted our understanding of the evolution of the human lineage.

Some notable findings in the last few years include the discovery of a new hominid species known as the Denisovans, the sequencing of the earliest Neanderthal genome, and the identification of a first-generation Denisovan-Neanderthal hybrid. Recent advances have also expanded the geographic scope of the field, as we are now able to obtain DNA from warm or tropical world regions such as the Pacific and Caribbean islands. In the last decade alone, thousands of ancient human genomes have been sequenced, something that seemed impossible when the field began in the 1980s.

Analyses of these data have revealed complex population histories for human groups on every continent. For example, we have new insights on the timing, scale, and complexity of transformative events such as the out-of-Africa migration; the spread of agriculture into Europe; the peopling of the Americas; and the domestication of dogs, pigs, and other species. There have also been significant advances in the study of ancient microbes, assessing them both as pathogens and as part of our microbiomes.

What’s your vision for the future of ancient DNA over the next 5–10 years?

Nieves-Colón: The next 5–10 years will see a shift in the types of questions being asked by ancient DNA researchers. Studies are starting to move away from the continental-scale human migration questions and are delving instead into smaller-scale processes and local population histories. For instance, we are now seeing more studies that use ancient DNA to understand kinship, residential patterns, and intersite mobility. Using ancient genomes to understand human behavior and sociocultural transformations at the regional or community level will require that paleogenomics become more integrative, drawing insights from other fields such as archaeology, history, and anthropology to examine the human experience through a multidisciplinary lens.

I am hopeful we will also see increased consideration of the ethics of ancient DNA research, especially as it pertains to the management of biological remains and cultural heritage objects which are often destroyed in the process of obtaining DNA. As a field, we have to balance the tradeoff of destroying irreplaceable remains to generate more data now versus safeguarding them for the future when newer methods may allow for different kinds of insights that we cannot yet foresee.

Lastly, I expect we will see more engagement of ancient DNA researchers with indigenous and descendant communities in the design, execution, and interpretation of paleogenomics studies. We are already seeing some movement in this direction as many researchers consult with diverse stakeholders before beginning destructive analysis. Working with communities who are the cultural or biological descendants of the ancient peoples that we study can also bring new perspectives to our work, guiding us toward questions that we did not think of previously or helping us interpret findings within the context of oral histories or other traditional knowledge systems.

How did you get into your field?

Nieves-Colón: As an undergraduate student in archaeology, I was interested in research questions about the past that were just not answerable through the study of material remains alone. I wanted to know how ancient populations were biologically linked to present-day peoples. Because of this interest, I decided to study anthropological genetics in graduate school with a focus on ancient DNA.

Synthetic Biology


James J. CollinsJames J. Collins, PhD

Termeer Professor of Medical Engineering and Science, Institute for Medical Engineering and Science, Massachusetts Institute of Technology; Institute Member, Broad Institute of MIT and Harvard; Founding Core Faculty and Lead, Living Cellular Devices, Wyss Institute at Harvard University

What have been the biggest advances in synthetic biology over the past few years?

Collins: I think the biggest advances in the field have been in the area of cell-free synthetic biology. These developments have led to new tools for basic research, as well as novel diagnostics, educational kits, and portable platforms for producing biomolecules in the field.

What’s your vision for the future of the field over the next 5–10 years?

Collins: Synthetic biology is well positioned to help advance medicine via the development of next-generation diagnostics and gene and cell therapies. I also think the field has tremendous potential to help advance basic research in molecular biology, by enabling the creation of novel tools to probe and analyze the complex functions of biomolecular components and systems in living cells.

How did you get into your field?

Collins: In the 1990s, I was applying techniques from nonlinear dynamics to physiological systems, ranging from sensory neurons to the human balance control system. My department chair, Charles Cantor, and college dean, Charles DeLisi, encouraged me to consider applying such techniques to biomolecular systems. This led to our work on the genetic toggle switch, which helped to launch the field of synthetic biology.

What is holding your field back?

Collins: We are being held back by two factors: (1) too much hype being generated by high priests in the field, and (2) insufficient biological insight on how molecular components interact to create biological circuits and how such circuits interact with the host cell.

If you weren’t a scientist, what nonscience career path would you have chosen and why?

Collins: Professional basketball player. Unfortunately, there was not a market to sustain such a path—even my mom was reluctant to pay to watch me play basketball.

What is your favorite science fiction movie and why?

Collins: I have two favorites: Jurassic Park and Real Genius. As for Jurassic Park, who doesn’t love dinosaurs? As for Real Genius, it was one of the first movies to present smart, quirky scientists as oddly cool characters—in many ways, it was a precursor to Big Bang Theory.


John CumbersJohn Cumbers, PhD

Founder and CEO, SynBioBeta



What have been the biggest advances in synthetic biology over the past few years?

Cumbers: The biggest advance has been the continuing fall in the cost of synthesizing large genes, which has been following the trend of the falling cost of sequencing DNA. Over the last decade, the cost of reading DNA has been falling faster than Moore’s law would have predicted, and the cost of writing DNA is following close behind.

The next biggest advance has been the discovery of CRISPR. The definition that I use for synthetic biology is “a movement to make biology easier to engineer,” and that movement is propelled by tools, platforms, and technologies that allow us to easily design, build, and test biological systems, such as biological cells, and to read, write, and edit DNA. A tool capable of editing DNA in living cells had long been needed. Transcription activator-like effector nucleases and zinc finger nucleases had been around, but they were expensive and time-consuming. Then CRISPR came along, opening up access to gene editing.

What’s your vision for the future of the field over the next 5–10 years?

Cumbers: We need to quantify our progress toward making biology easier to engineer. That is we need benchmarks for the design, build, and test cycle for strain engineering. We need to show how easy it is to engineer biological systems. We know that we’re making progress. I don’t think we know that we’re making progress along a particular quantifiable path.

How did you get into your field?

Cumbers: I was a software engineer, but I was interested in the biology of aging because I’m interested in space settlement and how we can travel long distances in space and explore the universe. So, I want to understand homeostasis and how we could keep the body alive for long periods of time. I transitioned from engineering into science when I earned a master’s degree in bioinformatics and a doctorate in molecular biology, cell biology, and biochemistry. I discovered that science is about asking questions and hypothesizing, and that engineering is about building and improving things. I stumbled across the fields of systems biology and synthetic biology and chose the path of synthetic biology.

What three people would you most like to have dinner with?

Cumbers: The first person is Elon Musk. I met him 10 years ago for the first time and asked, “If I came to you after my PhD and said I wanted to set up a bio-based life support systems group at SpaceX, what would you want to see on my resume?” At the time I was at NASA running experiments for bioengineering programs for food production and water purification. He looked at me and said, “I think you’re doing just fine.” I haven’t asked him for a job.

The second person is Tim Cook. I’d like to ask him how Apple plans to get into biomanufacturing and to create more sustainable pathways and supply chains.

The third person I’d like to have dinner with is Priscilla Chan, MD, from the Chan Zuckerberg Initiative. I’d like to discuss with her some of the efforts at the Chan Zuckerberg Biohub around measuring biological systems and vaccines and around the impact of biological technologies on global health and well-being.

Has there been a person or an event that has had a large influence on your career path?

Cumbers: Drew Endy, an associate professor of bioengineering at Stanford, is one of the founders of the field of synthetic biology and the president of the BioBricks Foundation. He has been a friend and mentor for many years. Drew has demonstrated amazing intellectual leadership around the future of humanity’s relationship with biology. His role in growing and driving this global community of passionate synthetic biologists is unprecedented.

What is your favorite science fiction movie and why?

Cumbers: My favorite science fiction movie is Avatar. It’s a great vision of a wonderful, alternate, evolved world with beautiful plants, animals, and creatures. It also demonstrates the perfect example of how a civilization can grow and thrive in collaboration with the planet and the environment around us. I think the Na’vi is a wonderful model for how humanity could thrive here on planet Earth in collaboration with working with biology to make a more environmentally sustainable world.


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