"The Evolution of Multicellularity and Cellular Differentiation" - A one-and-one-half-day symposium.

Visit Suddath Symposium website for full details and registration.

AGENDA
March 14:  1:00 - 4:45 p.m.
March 15:  8:00 a.m. - 4:10 p.m.

Few evolutionary innovations have been as impactful as the evolution of multicellularity, which opened the door to cellular differentiation and coordinated morphogenesis. Yet major gaps persist in our knowledge of how, when, and why this innovation evolved. This is due, in part, to extensive intellectual siloing that exists among developmental biologists, evolutionary biologists, paleontologists, physicists and mathematicians working on different aspects of this problem. This 32nd Annual Suddath Symposium will be focused on cutting through traditional disciplinary norms and expectations by presenting cutting-edge research that will open new routes for interdisciplinary research. 

The Suddath Symposium is held annually to celebrate the life and contribution of F.L. "Bud" Suddath by discussing the latest developments in bioengineering and bioscience. The speakers include leading researchers from around the world, and the research topic changes each year. This highly-interactive symposium has been taking place for over 30 years and is supported by the Institute for Bioengineering and Bioscience at Georgia Tech.

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Extreme environments offer a unique look into the process of adaptation since the selection pressures experienced there are often singular and strong. I will tell two stories of vertebrate adaptation to extreme environments: adaptation of a small mammal to high altitude and of a migratory fish to varying salinity environments. Using the North American deer mouse as a model, I show that adaptation to high altitude occurs through selection on existing phenotypic plasticity in aerobic metabolic performance as well as shifts in hypoxia signaling pathways that underly responses to low oxygen. Using repeatedly derived freshwater populations of a marine herring (the alewife), I show that natural selection acts on the physiological and underlying gene regulatory processes of osmoregulation to facilitate adaptation to cool, freshwater all year long. By connecting genotype-to-phenotype across biological levels of organization, my work offers a uniquely “whole-organism” perspective on the mechanisms of adaptation.

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Come join the Spatial Ecology and Paleontology Lab every Friday for Fossil Fridays! Become a fossil hunter and help discover how vertebrate communities have changed through time. Experience firsthand what it is like to be a paleontologist, finding and identifying new specimens! You will be picking and sorting 3,000 to 30,000-year-old fossil specimens from rock matrix that has been brought back from Natural Trap Cave, WY. These specimens are part of many research projects examining how the community of species living around Natural Trap Cave has changed since the extinction of the cheetahs, lions, dire wolves, mammoths, camels, horses, and other megafauna that used to live in North America. You are welcome to participate anytime that is convenient, with no commitment necessary. In fact, you can drop in or leave anytime within the two-hour timeframe. All are welcome, so bring your friends! For more information join our mailing list and/or contact Julia Schap (jschap3@gatech.edu) or Jenny McGuire (jmcguire@gatech.edu).

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Called “hilarious” by WIRED, Truth Values is also a serious exploration of the challenges women face in the STEM environment. The story follows NYC Writer/Performer and “Recovering Mathematician” Gioia De Cari’s adventures as a math Ph.D. student at M.I.T. Bewitched by the formal mathematical notion of Truth, she struggles with the clash of her personal reality in a world that is not binary.

This matinee is timed to coincide with the Gathering 4 Gardner (G4G), a biennial celebration of the legacy of beloved Scientific American writer Martin Gardner, with playful programming including math, science, puzzles, performance, magic, literature, and art.

It is not necessary to attend G4G to reserve a ticket. Seating is available on a first-come, first-served basis. To be assured a seat, please reserve asap. This event is free, reserve your ticket here.

About Truth Values

The mission of the Truth Values Community Project is to create a profoundly supportive community for women and underrepresented minorities in STEM through an innovative pairing of science, art, and conversation. 

The project was launched via sponsorship from the Alfred P. Sloan Foundation and the Massachusetts Institute of Technology.

Winner of a New York International Fringe Festival Overall Excellence Award, the play has been presented at more than 60 theaters and performing arts centers throughout the United States and Canada. Learn more at TruthValues.org/play

 Reviews for Truth Values

“Energetic, intimate, hilarious.”— Wired

"[Truth Values] is an extremely important work which deserves to be performed at every university." —Lied Center for the Arts

“Funny and insightful…replete with hilarious characters…The story is riveting...go see this show!” —CurtainUp

"Fantastic...pure humor, sadness, intelligence and struggle."
–Gigliola Staffilani, Mathematician, Member, National Academy of Sciences

“If you see only one play this year about reflexive nonbinary relations, make it this one.”— Los Angeles Times

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Microbial Experimental Evolution: social behavior, mutualism, and predator-prey interactions

Richard Lenski made microbial experimental evolution famous with his twelve flasks of Escherichia coli in minimal media, simply transferred daily without fail since 1988 for 75,000 generations in the Lenski lab.  The changes he documented along the way are monumental and occurred in the absence of any further manipulation.

Another approach to experimental evolution is to change something thought to be important and see if the predicted response occurs. This can be done in a relatively short time involving tens or hundreds of generations rather than thousands. Here I discuss several such experiments with the social amoeba Dictyostelium discoideum. This organism has a social stage in which tens of thousands of formerly independent amoebas aggregate into a fruiting body in which about 20% die to form a stalk which facilitates dispersal of the remaining 80% of hardy spores. Another attribute of D. discoideum is that it carries symbiotic bacteria which change its ability to consume bacteria.

We manipulate relatedness in the social stage to see if cooperation diminishes and then find the gene behind it. We remove the social stage to see if clones become less good at becoming reproductive spores instead of somatic stalks. We see if social stage somatic function is compromised. We make pseudo-organisms and manipulate the location of the germ line to see if cells compete to join it. We remove a symbiont to see if symbiont or host become more or less cooperative. Finally, we look at D. discoideum as a generalist predator that has costs when food bacteria change.

Taken together, these experiments show the promise of experimental evolution and the ease with which fundamental concepts in biology can be tested in microbial systems.

 

Hosted by Dr. Steve Diggle

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Scale as a unifying tool for synthesis in biodiversity studies

Some of the most important questions in biodiversity studies also remain the most controversial. Are species distributions structured by deterministic processes such as environmental filtering and species interactions, or do random processes reign supreme? Amidst a global extinction crisis, how is local biodiversity changing? How are productivity and diversity related? These and dozens of other questions have caused a considerable amount of strife in ecology over the decades. In my work, I have endeavored to find approaches, tools, data and perspectives that can synthesize these disparate views into a broader and more cohesive perspective. In this talk, I will use the concept of scale (mostly spatial, but also temporal, taxonomic ) as a fundamental mediator of biodiversity patterns and processes, and as such, as a way in which to synthesize seemingly disparate results. I will present some of the tools and approaches that we have developed that move beyond treating scale as a mere nuisance to treating it as a fundamental property of data that can help us to develop a more cohesive perspective on process and pattern in biodiversity studies. Finally, I conclude with a broader perspective on how the lessons learned in scale-dependence in biodiversity studies can help provide context for synthesis throughout ecology.

 

Hosted By Dr. Mark Hay

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Georgia Tech will be holding a high school regional competition to find the best three high school teams to be advanced to the National Science Bowl, a nationwide academic competition that tests high school and middle school students’ knowledge in all areas of sciences and math. 

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For over three decades, a highly accurate early diagnostic test for ovarian cancer has eluded physicians. Now, scientists in the Georgia Tech Integrated Cancer Research Center (ICRC) have combined machine learning with information on blood metabolites to develop a new test able to detect ovarian cancer with 93 percent accuracy among samples from the team’s study group.

John McDonald, professor emeritus in the School of Biological Sciences, founding director of the ICRC, and the study’s corresponding author, explains that the new test’s accuracy is better in detecting ovarian cancer than existing tests for women clinically classified as normal, with a particular improvement in detecting early-stage ovarian disease in that cohort.

The team’s results and methodologies are detailed in a new paper, “A Personalized Probabilistic Approach to Ovarian Cancer Diagnostics,” published in the March 2024 online issue of the medical journal Gynecologic Oncology. Based on their computer models, the researchers have developed what they believe will be a more clinically useful approach to ovarian cancer diagnosis — whereby a patient’s individual metabolic profile can be used to assign a more accurate probability of the presence or absence of the disease.

“This personalized, probabilistic approach to cancer diagnostics is more clinically informative and accurate than traditional binary (yes/no) tests,” McDonald says. “It represents a promising new direction in the early detection of ovarian cancer, and perhaps other cancers as well.”

The study co-authors also include Dongjo Ban, a Bioinformatics Ph.D. student in McDonald’s lab; Research Scientists Stephen N. Housley, Lilya V. Matyunina, and L.DeEtte (Walker) McDonald; Regents’ Professor Jeffrey Skolnick, who also serves as Mary and Maisie Gibson Chair in the School of Biological Sciences and Georgia Research Alliance Eminent Scholar in Computational Systems Biology; and two collaborating physicians: University of North Carolina Professor Victoria L. Bae-Jump and Ovarian Cancer Institute of Atlanta Founder and Chief Executive Officer Benedict B. Benigno. Members of the research team are forming a startup to transfer and commercialize the technology, and plan to seek requisite trials and FDA approval for the test.

Silent killer

Ovarian cancer is often referred to as the silent killer because the disease is typically asymptomatic when it first arises — and is usually not detected until later stages of development, when it is difficult to treat.

McDonald explains that while the average five-year survival rate for late-stage ovarian cancer patients, even after treatment, is around 31 percent — but that if ovarian cancer is detected and treated early, the average five-year survival rate is more than 90 percent.

“Clearly, there is a tremendous need for an accurate early diagnostic test for this insidious disease,” McDonald says.

And although development of an early detection test for ovarian cancer has been vigorously pursued for more than three decades, the development of early, accurate diagnostic tests has proven elusive. Because cancer begins on the molecular level, McDonald explains, there are multiple possible pathways capable of leading to even the same cancer type.

“Because of this high-level molecular heterogeneity among patients, the identification of a single universal diagnostic biomarker of ovarian cancer has not been possible,” McDonald says. “For this reason, we opted to use a branch of artificial intelligence — machine learning — to develop an alternative probabilistic approach to the challenge of ovarian cancer diagnostics.”

Metabolic profiles

Georgia Tech co-author Dongjo Ban, whose thesis research contributed to the study, explains that “because end-point changes on the metabolic level are known to be reflective of underlying changes operating collectively on multiple molecular levels, we chose metabolic profiles as the backbone of our analysis.”

“The set of human metabolites is a collective measure of the health of cells,” adds coauthor Jeffrey Skolnick, “and by not arbitrarily choosing any subset in advance, one lets the artificial intelligence figure out which are the key players for a given individual.”

Mass spectrometry can identify the presence of metabolites in the blood by detecting their mass and charge signatures. However, Ban says, the precise chemical makeup of a metabolite requires much more extensive characterization.

Ban explains that because the precise chemical composition of less than seven percent of the metabolites circulating in human blood have, thus far, been chemically characterized, it is currently impossible to accurately pinpoint the specific molecular processes contributing to an individual's metabolic profile.

However, the research team recognized that, even without knowing the precise chemical make-up of each individual metabolite, the mere presence of different metabolites in the blood of different individuals, as detected by mass spectrometry, can be incorporated as features in the building of accurate machine learning-based predictive models (similar to the use of individual facial features in the building of facial pattern recognition algorithms).

“Thousands of metabolites are known to be circulating in the human bloodstream, and they can be readily and accurately detected by mass spectrometry and combined with machine learning to establish an accurate ovarian cancer diagnostic,” Ban says.

A new probabilistic approach

The researchers developed their integrative approach by combining metabolomic profiles and machine learning-based classifiers to establish a diagnostic test with 93 percent accuracy when tested on 564 women from Georgia, North Carolina, Philadelphia and Western Canada. 431 of the study participants were active ovarian cancer patients, and while the remaining 133 women in the study did not have ovarian cancer.

Further studies have been initiated to study the possibility that the test is able to detect very early-stage disease in women displaying no clinical symptoms, McDonald says.

McDonald anticipates a clinical future where a person with a metabolic profile that falls within a score range that makes cancer highly unlikely would only require yearly monitoring. But someone with a metabolic score that lies in a range where a majority (say, 90%) have previously been diagnosed with ovarian cancer would likely be monitored more frequently — or perhaps immediately referred for advanced screening.

Citation: https://doi.org/10.1016/j.ygyno.2023.12.030

Funding

This research was funded by the Ovarian Cancer Institute (Atlanta), the Laura Crandall Brown Foundation, the Deborah Nash Endowment Fund, Northside Hospital (Atlanta), and the Mark Light Integrated Cancer Research Student Fellowship.

Disclosure

Study co-authors John McDonald, Stephen N. Housley, Jeffrey Skolnick, and Benedict B. Benigno are the co-founders of MyOncoDx, Inc., formed to support further research, technology transfer, and commercialization for the team’s new clinical tool for the diagnosis of ovarian cancer.

Members of the Georgia Tech community are opening their doors once again as part of the 11th annual Atlanta Science Festival. This year, Science and Engineering Day at Georgia Tech will serve as the kickoff event for the entire festival!

Whether you’re interested in robotics, brains, biology, space, art, nanotechnology, paper, computer science, wearables, bioengineering, chemical engineering, or systems engineering, there will be activities for you. Visit campus for hands-on STEAM activities, exhibits, demonstrations, opportunities to meet student researchers, and learn about the exciting things happening at Georgia Tech.

Visit the 2024 Georgia Tech Science and Engineering Day webpage for more information!

Activity Guide - Coming Soon!

Interested in Volunteering for the Event? Sign up here.

For general questions about Science and Engineering Day at Georgia Tech, contact Georgia Tech Research Events


The Atlanta Science Festival, returning March 9-23, 2024, is an annual public celebration of local science and technology. Curious people of all ages will explore the science and technology in our region and see how science is connected to all parts of our lives. Learn more.

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Join us for a career panel featuring NASA civil servants who will share their journey, specific roles, and information about NASA careers. Attendees will have the opportunity to ask questions, network, and learn more about employment opportunities at NASA. 

NASA Panelists: 

  • Derrick Bailey, Launch Vehicle Certification Manager
  • Marisa Wyssling-Horn, Senior Integration Engineer
  • Jarrod Bales, Education and Outreach Specialist

 

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