Category: Uncategorized

Molecular bumper cars (RNA polymerase-ribosomal interactions): their (unexpected) functional effects and how to control them

Cells are extremely complex.1 Much of their “core” complexity appears to have been present in their last (universal) common ancestor, known as LUCA. We find it in the “conserved” molecular mechanisms and machines active in modern cells. LUCA and its offspring are membrane-bounded, non-equilibrium systems that import free energy and export entropy to maintain and repair themselves, to grow, behave, and reproduce (and all the other things living things do). One problem, however, with LUCA is that it makes speculation on the steps that preceded it impossible to know with certainty. Not withstanding claims of breakthroughs (e.g. ‘Monumental’ experiment suggests how life on Earth may have started“), it is likely that we will never know the actual steps involved; after all, the origin of life occurred billions of years ago and under rather different conditions than exist today.

Living systems “work” based on inherited, pre-existing molecular machines and mechanisms (1). The actions of these machines are fueled through coupling to thermodynamically favorable reactions taking place under non-equilibrium conditions, i.e. the living state. Looking at the details of these interactions reveals interesting and unexpected behaviors. Unfortunately, the “simple” physical-chemical underpinnings of these processes, key to understanding them, are not always presented to students effectively (2).  At the same time, the complexity of cellular systems means that in practice, the link between “simple” molecular mechanisms and the behavior of a biological systems can be obscure (see 3).  That said, key insights are illuminated when molecular mechanisms are examined, as illustrated by Wee et al., (2023)(4).  

Emerging from LUCA, biological populations have diverged into distinct “prokaryotic” lineages: the bacteria and archaea.2 Both are defined by a protein-lipid boundary layer, the plasma membrane. Within this membrane is a single internal compartment, the cytoplasm. Information is stored in cells in two forms, first in the on-going LUCA-derived living system and the second, information in the sequence of double-stranded DNA molecules. These two types of information are interdependent: the information in DNA makes sense only within a cell and the on-going cellular processes depend upon and utilize the information in DNA. In bacteria and archaea, these are circular double-stranded DNA molecules. Here we restrict our discussion to the common unicellular bacterium Escherichia coli (E. coli), one of the workhorse systems that led to an understanding of core molecular mechanisms.  

E. coli hasa single circular genomic DNA molecule of ~5 million nucleotide base pairs in length; it contains about 5000 distinct genes that encode polypeptides and functional “non-coding” RNA molecules (if you are interested in numbers, check out bionumbers).  An E. coli cell is rod-shaped and ~1 micrometer (10-6 meters) long. Its genomic DNA molecule is ~1000 times longer than the cell that contains it, and a rapidly dividing cell can contain multiple copies of the genome. Genes typically contain two distinct functional regions. Regulatory regions interact with various proteins that determine whether a gene is “expressed” or not. Coding regions specify what is expressed. The first step is the synthesis of an RNA molecule; such a molecule can encode a polypeptide or a non-coding RNA.3 Non-coding RNAs can have structural, catalytic, or regulatory functions.  

The first step in gene expression in all cell types is the binding of proteins to a gene’s regulatory sequences. Typically a complex of proteins leads to the binding and activation of a DNA-dependent, RNA polymerase. The RNA polymerase complex unwinds a specific region of the DNA and uses the complementary nature of nucleotide base pairing: A binding to T in DNA and U in RNA, and C binding to G in both, to synthesize an RNA molecule based on DNA sequence. Synthesis of RNAs that encode polypeptides, known as messenger RNAs (mRNAs) starts with the 5′ end of the molecule and moves toward the 3′ end (replaced ↓ soon).

In prokaryotic cells, both DNA and mRNA synthesis reactions occur in the cytoplasm. A ribosome, a molecular machine composed of multiple proteins and RNAs, can engage the 5′ end region of an mRNA as soon as it appears – before the synthesis of the mRNA is complete. The cytoplasm of a cell contains lots of ribosomes; in E. coli there are ~70,000 ribosomes per cell (more or less). This leads to some interesting and functionally significant interactions.  One thing to consider, not always stressed, is that these synthetic processes are not error proof.  DNA replication (DNA-directed, DNA synthesis), transcription (DNA-directed, RNA synthesis), and polypeptide synthesis (RNA-directed, polypeptide synthesis) all have an error rate, typically 1 error per ~106 addition events for DNA replication and transcription. Errors can lead to mutations in the DNA, RNAs that encode abnormal proteins, or abnormal and potentially toxic polypeptides.

To deal with physical realities, these synthetic processes employ various “error correction” strategies.  In the case of DNA and RNA synthesis, the polymerases involved have what is known as “proof-reading” activities. If the incorrect nucleotide is inserted into a growing DNA or RNA chain, it can be recognized; the polymerase can then “reverse” (move backward along the DNA), remove the mistakenly inserted nucleotide, and then move forward again, adding the correct nucleotide. Key here is that the polymerase is moving back and forth along the DNA strand. The result of proof-reading is to reduce the error rate of DNA-dependent DNA and RNA synthesis substantially, down to 10-8 to 10-10 per base pair in the case of DNA synthesis.  

In the case of the RNA polymerase, the newly synthesized RNA can fold back on itself, forming what is known as a “hairpin”. This hairpin “can stabilize an elemental pause (in RNA synthesis) an allosteric interaction with the β-flap tip helix of RNAP”. What Wee et al (4) report is as the mRNA-associated ribosome moves along the RNA it unfold the hairpin and “bumps” into the polymerase, inhibiting this “pause” which increases the rate of mRNA synthesis and inhibits the polymerase’s error correction function. The resulting mRNA population has more frequent base pair changes, errors that can influence the polypeptides synthesized. While cells of all types have various  “chaperone” systems that can deal with misfolded proteins that arise in response to various stresses or errors, these can be overwhelmed. The resulting misfolded (damaged) proteins can lead to cellular defects and long term effects on viability (discussed in 5).  

About 1.5 billion years later (give or take), a new type of cell appeared, the result (apparently) of a symbiotic interaction between an archaeal-like “host” and a O2-utilizing bacterium.  This synthetic organism, the progenitor of the eukaryotes, differed from either type of prokaryote in that it sequestered its genome, now composed of linear DNA molecules, within a double membrane bounded “nuclear” compartment. In this hybrid cell type, DNA and RNA synthesis was confined to the nucleus, while ribosomes and polypeptide synthesis were confined to the cytoplasm. Eukaryotic cells are typically much larger that prokaryotic cells, reproduce more slowly, and are more complex in terms of the numbers of genes, and the amount of genomic DNA they contain. It is tempting to speculated that while rapidly dividing, relatively simple prokaryotic cells may be able to tolerate more mistakes in terms of the synthesis of their polypeptides, larger, more complex eukaryotic cells would be vulnerable. A plausible result would be a selection pressure to separating RNA from polypeptide synthesis.

literature cited

  1. Alberts, B. (1998). The cell as a collection of protein machines: preparing the next generation of molecular biologists. Cell, 92, 291-294.
  2. de Lorenzo, V., 2024. The principle of uncertainty in biology: Will machine learning/artificial intelligence lead to the end of mechanistic studies?. Plos Biology, 22, p.e3002495.
  3. Klymkowsky, M.W., 2021. Making mechanistic sense: are we teaching students what they need to know? Developmental Biology, 476, pp.308-313.
  4. Wee et al., 2023. A trailing ribosome speeds up RNA polymerase at the expense of transcript fidelity via force and allostery. Cell, 186, pp.1244-1262.
  5. Klymkowsky, M.W., 2019. Filaments and phenotypes: cellular roles and orphan effects associated with mutations in cytoplasmic intermediate filament proteins. F1000Research, 8.

Footnotes

  1. if you want brush up on you molecular biology, check out chapter 7 of biofundamentals  ↩︎
  2. Image from Govindjee – doi:10.3389/fpls.2011.00028, CC BY 3.0.  Given the diversity of biological systems, these are general descriptions – often there a exceptions, but recognizing them all makes generating a coherent narrative difficult (and beyond me).  Mea culpa.    ↩︎
  3. bioliteracy link: When is a gene product a protein when is it a polypeptide? ↩︎

Avoiding unrecognized racist implications arising from teaching genetics

Update to relevant article in the New York Times. December 2019

It is common to think of teaching as socially and politically beneficial, or at least benign, but Donovan et al. (2019. ” Toward a more humane genetics education” Science Education 103: 529-560)(1) raises the interesting possibility, supported by various forms of analysis and a thorough review of the literature, that conventional approaches to teaching genetics can exacerbate students’ racialist ideas. A focus on genetic diseases associated with various population groups, say for example Tay-Sachs disease within Eastern European Jewish populations of sickle cell anemia within African populations, can result in more racialist and racist perspectives among students.

What is meant by racialist? Basically it is an essentialist perspective that a person is an exemplar of the essence of a group, and that all members of a particular group “carry” that essence, an essence that defines them as different and distinct from members of other groups. Such an essence may reflect a culture, or in our more genetical age, their genome, that is the versions of the genes that they possess. In a sense, their essence is more real than their individuality, an idea that contradicts the core reality of biological systems, as outlined in works by Mayr (2,3) – a mistake he termed typological thinking.

Donovan et al. go on to present evidence that exposure of students to lessons that stress the genomic similarities between humans can help. That “any two humans share 99.9% of their DNA, which means that 0.1% of human DNA varies between individuals. Studies find that, on average, 4.3% of genetic variability in humans (4.3% of the 0.1% of the variable portion of human DNA) occurs between the continental populations commonly associated with US census racial groups (i.e., Africa, Asia, Pacific Islands, and The Americas, Europe). In contrast, 95.7% of human genetic variation (95.7% of the 0.1% of variable portion of human DNA) occurs between individuals within those same groups” (italics added). And that “there is more variability in skull shape, facial structure, and blood types within racially defined populations … than there is between them.” Lessons that emphasized the genomic similarities between people and the dissimilarities within groups, appeared effective in reducing racialist ideation – they can help dispel racist beliefs while presenting the most scientifically accurate information available.

This is of particular importance given the dangers of genetic essentialism, that is the idea that we are our genomes and that our genomes determine who (and what) we are. A pernicious ideology that even the co-discover of DNA’s structure, James Watson, has fallen prey to. One pernicious aspect of such conclusions is illustrated in the critique of a recent genomic analysis of educational attainment and cognitive performance by John Warner (4).

An interesting aspect of this work is to raise the question of where, within a curriculum, should genetics go? What are the most important aspects of the complex molecular-level interaction networks that connect genotype with phenotype that need to be included in order to flesh out the overly simplified Mendelian view (pure dominant and recessive alleles, monogenic traits, and unlinked genes) often presented? A point of particular relevance given the growing complexity of what genes are and how they act (5,6). Perhaps the serious consideration of genetic systems would be better left for later in a curriculum. At the very least, it points out the molecular and genomic contexts that should be included so as to minimize the inadvertent support for racialist predilections and predispositions. 

modified from F1000 post

References

  1. Donovan, B. M., R. Semmens, P. Keck, E. Brimhall, K. Busch, M. Weindling, A. Duncan, M. Stuhlsatz, Z. B. Bracey and M. Bloom (2019). “Toward a more humane genetics education: Learning about the social and quantitative complexities of human genetic variation research could reduce racial bias in adolescent and adult populations.” Science Education 103(3): 529-560.
  2. Mayr (1985) The Growth of Biological Thought: Diversity, Evolution, and Inheritance. Belknap Press of Harvard University Press ISBN: 9780674364462
  3. Mayr (1994) Typological versus population thinking. In: Conceptual issues in evolutionary biology. MIT Press, Bradford Books, 157-160. Sober E (ed)
  4. Why we shouldn’t embrace the genetics of education. Warner J. Inside Higher Ed blog, July 26 2018 Available online (accessed Aug 22 2019)
  5. Genes – way weirder than you thought. Bioliteracy blog, Jul 09 2018
  6. The evolving definition of the term “gene”. Portin & Wilkins. 2017 Genetics. 205:1353-1364

Remembering the past and recognizing the limits of science …

A recent article in the Guardian reports on a debate at University College London (1) on whether to rename buildings because the people honored harbored odious ideological and political positions. Similar debates and decisions, in some cases involving unacceptable and abusive behaviors rather than ideological positions, have occurred at a number of institutions (see Calhoun at Yale, Sackler in NYC, James Watson at Cold Spring Harbor, Tim Hunt at the MRC, and sexual predators within the National Academy of Sciences). These debates raise important and sometimes troubling issues.

When a building is named after a scientist, it is generally in order to honor that person’s scientific contributions. The scientist’s ideological opinions are rarely considered explicitly, although they may influence the decision at the time.  In general, scientific contributions are timeless in that they represent important steps in the evolution of a discipline, often by establishing a key observation, idea, or conceptual framework upon which subsequent progress is based – they are historically important.  In this sense, whether a scientific contribution was correct (as we currently understand the natural world) is less critical than what that contribution led to. The contribution marks a milestone or a turning point in a discipline, understanding that the efforts of many underlie disciplinary progress and that those contributors made it possible for others to “see further.” (2)

Since science is not about recognizing or establishing a single unchanging capital-T-Truth, but rather about developing an increasingly accurate model for how the world works, it is constantly evolving and open to revision.  Working scientists are not particularly upset when new observations lead to revisions to or the abandonment of ideas or the addition of new terms to equations.(3)

Compare that to the situation in the ideological, political, or religious realms.  A new translation or interpretation of a sacred text can provoke schism and remarkably violent responses between respective groups of believers. The closer the groups are to one another, the more horrific the levels of violence that emerge often are.  In contrast, over the long term, scientific schools of thought resolve, often merging with one another to form unified disciplines. From my own perspective, and not withstanding the temptation to generate new sub-disciplines (in part in response to funding factors), all of the life sciences have collapsed into a unified evolutionary/molecular framework.  All scientific disciplines tend to become, over time, consistent with, although not necessarily deducible from, one another, particularly when the discipline respects and retains connections to the real (observable) world.(4)  How different from the political and ideological.

The historical progression of scientific ideas is dramatically different from that of political, religious, or social mores.  No matter what some might claim, the modern quantum mechanical view of the atom bears little meaningful similarity to the ideas of the cohort that included Leucippus and Democritus.  There is progress in science.  In contrast, various belief systems rarely abandon their basic premises.  A politically right- or left-wing ideologue might well find kindred spirits in the ancient world.  There were genocidal racists, theists, and nationalists in the past and there are genocidal racists, theists, and nationalists now.  There were (limited) democracies then, as there are (limited) democracies now; monarchical, oligarchical, and dictatorial political systems then and now; theistic religions then and now. Absolutist ideals of innate human rights, then as now, are routinely sacrificed for a range of mostly self-serving or politically expedient reasons.  Advocates of rule by the people repeatedly install repressive dictatorships. The authors of the United States Constitution declare the sacredness of human rights and then legitimized slavery. “The Bible … posits universal brotherhood, then tells Israel to kill all the Amorites.” (Phil Christman). The eugenic movement is a good example; for the promise of a genetically perfect future, existing people are treated inhumanely – just another version of apocalyptic (ends justify the means) thinking. 

Ignoring the simpler case of not honoring criminals (sexual and otherwise), most calls for removing names from buildings are based on the odious ideological positions espoused by the honored – typically some version of racist, nationalistic, or sexist ideologies.  The complication comes from the fact that people are complex, shaped by the context within which they grow up, their personal histories and the dominant ideological milieu they experienced, as well as their reactions to it.  But these ideological positions are not scientific, although a person’s scientific worldview and their ideological positions may be intertwined. The honoree may claim that science “says” something unambiguous and unarguable, often in an attempt to force others to acquiesce to their perspective.  A modern example would be arguments about whether climate is changing due to anthropogenic factors, a scientific topic, and what to do about it, an economic, political, and perhaps ideological question.(5)

So what to do?  To me, the answer seems reasonably obvious – assuming that the person’s contribution was significant enough, we should leave the name in place and use the controversy to consider why they held their objectionable beliefs and more explicitly why they were wrong to claim scientific justification for their ideological (racist / nationalist / sexist / socially prejudiced) positions.(6)  Consider explicitly why an archeologist (Flinders Petrie), a naturalist (Francis Galton), a statistician (Karl Pearson), and an advocate for women’s reproductive rights (Marie Stopes) might all support the non-scientific ideology of eugenics and forced sterilization.  We can use such situations as a framework within which to delineate the boundaries between the scientific and the ideological. 

Understanding this distinction is critical and is one of the primary justifications for why people not necessarily interested in science or science-based careers are often required to take science courses.  Yet all too often these courses fail to address the constraints of science, the difference between political and ideological opinions, and the implications of scientific models.  I would argue that unless students (and citizens) come to understand what constitutes a scientific idea or conclusion and what reflects a political or ideological position couched in scientific or pseudo-scientific terms, they are not learning what they need to know about science or its place in society.  That science is used as a proxy for Truth writ large is deeply misguided. It is much more important to understand how science works than it is to remember the number of phyla or the names of amino acids, the ability to calculate the pH of a solution, or to understand processes going on at the center of a galaxy or the details of a black hole’s behavior.  While sometimes harmless, misunderstanding science and how it is used socially can result in traumatic social implications, such as drawing harmful conclusions about individuals from statistical generalizations of populations, avoidable deaths from measles, and the forced “eugenic” sterilization of people deemed defective.  We should seek out and embrace opportunities to teach about these issues, even if it means we name buildings after imperfect people.  

footnotes:

  1. The location of some of my post-doc work.
  2. In the words of Isaac Newton, “If I have seen further than others, it is by standing upon the shoulders of giants.”
  3.  Unless, of course, the ideas and equations being revised or abandoned are one’s own. 
  4.  Perhaps the most striking exception occurs in physics on the subjects of quantum mechanics and relativity, but as I am not a physicist, I am not sure about that. 
  5.  Perhaps people are “meant” to go extinct. 
  6.  The situation is rather different outside of science, because the reality of progress is more problematic and past battles continue to be refought.  Given the history of Reconstruction and the Confederate “Lost Cause” movement [see PBS’s Reconstruction] following the American Civil War, monuments to defenders of slavery, no matter how admirable they may have been in terms of personal bravery and such, reek of implied violence, subjugation, and repression, particularly when the person honored went on to found an institution dedicated to racial hatred and violent intimidation [link]. There would seem little doubt that a monument in honor of a Nazi needs to be eliminated and replaced by one to their victims or to those who defeated them.

Science “awareness” versus “literacy” and why it matters, politically.

Montaigne concludes, like Socrates, that ignorance aware of itself is the only true knowledge”  – from “forbidden knowledge” by Roger Shattuck

A month or so ago we were treated to a flurry of media excitement surrounding the release of the latest Pew Research survey on Americans’ scientific knowledge.  The results of such surveys have been interpreted to mean many things. As an example, the title of Maggie Koerth-Baker’s short essay for the 538 web site was a surprising “Americans are Smart about Science”, a conclusion not universally accepted (see also).  Koerth-Baker was taken by the observation that the survey’s results support a conclusion that Americans’ display “pretty decent scientific literacy”.  Other studies (see Drummond & Fischhoff 2017) report that one’s ability to recognize scientifically established statements does not necessarily correlate with the acceptance of science policies – on average climate change “deniers” scored as well on the survey as “acceptors”.  In this light, it is worth noting that science-based policy pronouncements generally involve projections of what the future will bring, rather than what exactly is happening now.  Perhaps more surprisingly, greater “science literacy” correlates with more polarized beliefs that, given the tentative nature of scientific understanding –which is not about truth per se but practical knowledge–suggests that the surveys’ measure something other than scientific literacy.  While I have written on the subject before  it seems worth revisiting – particularly since since then I have read Rosling’s FactFullness and thought more about the apocalyptic bases of many secular and religious movements, described in detail by the historian Norman Cohn and the philosopher John Gray and gained a few, I hope, potentially useful insights on the matter.  

First, to understand what the survey reports we should take a look at the questions asked and decide what the ability to chose correctly implies about scientific literacy, as generally claimed, or something simpler – perhaps familiarity.  It is worth recognizing that all such instruments, particularly  those that are multiple choice in format, are proxies for a more detailed, time consuming, and costly Socratic interrogation designed to probe the depth of a persons’ knowledge and understanding.  In the Pew (and most other such surveys) choosing the correct response implies familiarity with various topics impacted by scientific observations. They do not necessarily reveal whether or not the respondent understands where the ideas come from, why they are the preferred response, or exactly where and when they are relevant (2). So is “getting the questions correct” demonstrates a familiarity with the language of science and some basic observations and principles but not the limits of respondents’ understanding.  

Take for example the question on antibiotic resistance (→).  The correct answer “it can lead to antibiotic-resistant bacteria” does not reveal whether the respondent understands the evolutionary (selective) basis for this effect, that is random mutagenesis (or horizontal gene transfer) and antibiotic-resistance based survival.  It is imaginable that a fundamentalist religious creationist could select the correct answer based on  plausible, non-evolutionary mechanisms (3).  In a different light, the question on oil, natural gas and coal (↓) could be seen as ambiguous – aren’t these all derived from long dead organisms, so couldn’t they reasonably be termed biofuels?  

While there are issues with almost any such multiple choice survey instrument, surely we would agree that choosing the “correct” answers to these 11 questions reflects some awareness of current scientific ideas and terminologies.  Certainly knowing (I think) that a base can neutralize and acid leaves unresolved how exactly the two interact, that is what chemical reaction is going on, not to mention what is going on in the stomach and upper gastrointestinal tract of a human being.  In this case, selecting the correct answer is not likely to conflict with one’s view of anthropogenic effects on climate, sex versus gender, or whether one has an up to date understanding of the mechanisms of immunity and brain development, or the social dynamics behind vaccination – specifically the responsibilities that members of a social group have to one another.   

But perhaps a more relevant point is our understanding of how science deals with the subject of predictions, because at the end of the day it is these predictions that may directly impact people in personal, political, and economically impactful ways. 

We can, I think, usefully divide scientific predictions into two general classes.  There are predictions about a system that can be immediately confirmed or dismissed through direct experiment and observation and those that cannot. The immediate (accessible) type of prediction is the standard model of scientific hypothesis testing, an approach that reveals errors or omissions in one’s understanding of a system or process.  Generally these are the empirical drivers of theoretical understanding (although perhaps not in some areas of physics).  The second type of prediction is inherently more problematic, as it deals with the currently unobservable future (or the distant past).  We use our current understanding of the system, and various assumptions, to build a predictive model of the system’s future behavior (or past events), and then wait to see if they are confirmed. In the case of models about the past, we often have to wait for a fortuitous discovery, for example the discovery of a fossil that might support or disprove our model.   

It’s tough to make predictions, especially about the future
– Yogi Berra (apparently)

Anthropogenic effects on climate are an example of the second type of prediction. No matter our level of confidence, we cannot be completely sure our model is accurate until the future arrives. Nevertheless, there is a marked human tendency to take predictions, typically about the end of the world or the future of the stock market, very seriously and to make urgent decisions based upon them. In many cases, these predictions impact only ourselves, they are personal.  In the case of climate change, however, they are likely to have disruptive effects that impact many. Part of the concern about study predictions is that responses to these predictions will have immediate impacts, they produce social and economic winners and losers whether or not the predictions are confirmed by events. As Hans Rosling points out in his book Factfullness, there is an urge to take urgent, drastic, and pro-active actions in the face of perceived (predicted) threats.  These recurrent and urgent calls to action (not unlike repeated, and unfulfilled predictions of the apocalypse) can lead to fatigue with the eventual dismissal of important warnings; warnings that should influence albeit perhaps not dictate ecological-economic and political policy decisions.  

Footnotes and literature cited:
1. As a Pew Biomedical Scholar, I feel some peripheral responsibility for the impact of these reports

2. As pointed out in a forthcoming review, the quality of the distractors, that is the incorrect choices, can dramatically impact the conclusions derived from such instruments. 

3.  I won’t say intelligent design creationist, as that makes no sense. Organisms are clearly not intelligently designed, as anyone familiar with their workings can attest

Drummond, C. & B. Fischhoff (2017). “Individuals with greater science literacy and education have more polarized beliefs on controversial science topics.” Proceedings of the National Academy of Sciences 114: 9587-9592.


After the March for Science, What Now?

Recently, I contributed to a project that turned healthy human tissues into an earlier stage of pancreatic cancer—a disease that carries a dismal 5-year survival rate of 5 percent.

 

When I described our project to a friend, she asked, “why in the world would you want to grow cancer in a lab?” I explained that by the time a patient learns that he has pancreatic cancer, the tumor has spread throughout the body. At that point, the patient typically has less than a year to live and his tumor cells have racked up a number of mutations, making clinical trials and molecular studies of pancreatic cancer evolution downright difficult. For this reason, our laboratory model of pancreatic cancer was available to scientists who wanted to use it to find the biological buttons that turn healthy cells into deadly cancer. By sharing our discovery, we wanted to enable others in developing drugs to treat cancer and screening tests to diagnose patients early. The complexity of this process demonstrates that science is a team effort that involves lots of time, money, and the brainpower of highly-trained individuals working together toward a single goal.

 

Many of the challenges we face today—from lifestyle diseases, to the growing strains of antibiotic-resistant superbugs in hospitals, to the looming energy crisis—require scientific facts and solutions. And although there’s never a guarantee of success, scientists persist in hopes that our collective discoveries will reverberate into the future. However, as a corollary, hindering scientific progress means a loss of possibilities.

 

Unfortunately, the deceleration of scientific progress seems likely possibility. In March, the White House released a document called “America First: A Budget Blueprint to Make America Great Again,” which describes deep cuts to some of the country’s most important funding agencies for science.

 

As it stands, the National Institutes of Health is set to lose nearly a fifth of its budget; the Department of Energy’s Office of Science, $900 million; and the Environmental Protection Agency, a 31.5 percent budget cut worth $2.6 billion. Imagine the discoveries that could have saved our lives or created jobs, which will instead languish solely as unsupported hypotheses in the minds of underfunded scientists.

 

Scientists cannot remain idle on the sidelines; we must be active in making the importance of scientific research known. Last weekend’s March on Science drew tens of thousands of people around more than 600 rallies across the world, but the challenge now lies in harnessing the present momentum and energy to make sustained efforts to maintain government funding for a wide range of scientific projects.

 

The next step is to get involved in shaping public opinion and policy. As it stands, Americans on both sides of the political spectrum have expressed ambivalence about the validity of science on matters ranging from climate change to childhood vaccinations. Academics can start tempering the public’s unease toward scientific authority and increase public support for the sciences by stepping off the ivory tower. Many researchers are already engaging with the masses by posting on social media, penning opinion articles, and appearing on platforms aimed at public consumption (Youtube channels, TED, etc). A researcher is her own best spokesperson in explaining the importance of her work and the scientific process; unfortunately, a scientist’s role as an educator in the classroom and community is often shoved out by the all-encompassing imperative to publish or perish. As a profession, we must become more willing to step out of our laboratories to engage with the public and educate the next generation of science-savvy citizens.

 

In addition, many scientists have expressed interest in running for office, including UC Berkeley’s Michael Eisen (who also a co-founder of PLOS). When asked by Science why he was considering a run for senate, Eisen responded:

 

“My motivation was simple. I’m worried that the basic and critical role of science in policymaking is under a bigger threat than at any point in my lifetime. We have a new administration and portions of Congress that don’t just reject science in a narrow sense, but they reject the fundamental idea that undergirds science: That we need to make observations about the world and make our decisions based on reality, not on what we want it to be. For years science has been under political threat, but this is the first time that the whole notion that science is important for our politics and our country has been under such an obvious threat.”

 

If scientists can enter into the house and senate in greater numbers, they will be able to inject scientific sense into the discussions held by members of legislature whose primary backgrounds are in business and law.

 

Science is a bipartisan issue that should not be bogged down by the whims of political machinations. We depend on research to address some of the most pressing problems of our time, and America’s greatness lies in part on its leadership utilizing science as an exploration of physical truths and a means of overcoming our present limitations and challenges.

 

 

Check out Yoo Jung’s book aimed at helping college students excel in science, What Every Science Student Should Know (University of Chicago Press)