Samer Mabrouk and Omer Inan have been working on a wearable, battery-powered device that monitors joint health and gives personalized strengthening exercises. Inan and Mabrouk’s new company, Arthroba, created a device of the same name that uses electrical sensors to track swelling and tissue damage in the knee, ankle, and other critical joints.

Effective January 1st, David Sherrill will serve as interim executive director of the Georgia Tech Institute for Data Engineering and Science (IDEaS). Sherrill is a Regents' Professor in the School of Chemistry and Biochemistry with a joint appointment in the College of Computing. Sherrill has served as associate director for IDEaS since its founding in 2016.

"David Sherrill's leadership role in IDEaS as associate director, together with his interdisciplinary background in chemistry and computer science, makes him the right person to support this transition as interim executive director," said Julia Kubanek, professor and vice president for interdisciplinary research at Georgia Tech. 

Sherrill succeeds Srinivas Aluru who will be taking a new position as Senior Associate Dean in the College of Computing. Aluru, a Regents' Professor in the School of Computational Science and Engineering, co-founded IDEaS and served as its co-executive director (2016-2019) and then as executive director (2019-date), spanning eight and a half years. Under his leadership IDEaS grew to more than 200 affiliate faculty spanning all colleges, encompassing multiple state, federal, and industry funded centers. Notable among these is the South Big Data Hub, catalyzing the Southern data science community to collectively accelerate scientific discovery and innovation, spur economic development in the region, broaden participation and diversity in data science, and the CloudHub, a Microsoft funded center that provides research funding and cloud resources for innovative applications in Generative Artificial Intelligence. More recently, Aluru established the Center for Artificial Intelligence in Science and Engineering (ARTISAN), and expanded the Institute’s research staff to provide needed cyberinfrastructure, software resources, and expertise to support faculty projects with large data sets and AI-driven discovery. "I've had the pleasure of serving as Associate Director of IDEaS since it was founded by Srinivas Aluru and Dana Randall, and I'm excited to step into this interim role.” said Sherrill. “IDEaS has an important mission to serve the many faculty doing interdisciplinary research involving data science and high performance computing."

Sherrill’s research group focuses on the development of ab initio electronic structure theory and its application to problems of broad chemical interest, including the influence of non-covalent interactions in drug binding, biomolecular structure, organic crystals, and organocatalytic transition states. The group seeks to apply the most accurate quantum models possible for a given problem and specializes in generating high-quality datasets for testing new methods or machine-learning purposes. 

Sherrill earned a B.S. in chemistry from MIT in 1992 and a Ph.D. in chemistry from the University of Georgia in 1996. From 1996-1999 Sherril was an NSF Postdoctoral Fellow, working under M. Head-Gordon, at the University of California, Berkeley.

Sherrill is a Fellow of the American Association for the Advancement of Science (AAAS), the American Chemical Society, and the American Physical Society, and he has been Associate Editor of the Journal of Chemical Physics since 2009. Sherrill has received a Camille and Henry Dreyfus New Faculty Award, the International Journal of Quantum Chemistry Young Investigator Award, an NSF CAREER Award, and Georgia Tech's W. Howard Ector Outstanding Teacher Award. In 2023, he received the Herty Medal from the Georgia Section of the American Chemical Society, and in 2024, he was elected to the International Academy of Quantum Molecular Science.

--Christa M. Ernst

From combating cancer and infections to storing energy, lipid-protein interactions are critical to biological processes in cells. But the mechanisms that drive these interactions have historically been difficult to map and understand.

A study led by Georgia Tech is showcasing a new resource to help researchers understand the structure and function of these interactions — called assemblies — at both molecular and functional levels. The work is published in the Nature-family journal Communications Chemistry.

Called BioDolphin — short for Biological Database of Lipid-Protein Highly Inclusive Interactions — the resource is the first comprehensive, annotated database of protein-lipid interactions. Integrated into a user-friendly web server, BioDolphin is freely accessible to all. Users can easily view and download interaction data and systematically analyze lipid-protein assemblies.

“Understanding lipid-protein interactions is crucial in advancing our understanding of human health and disease treatment,” says the study’s corresponding author, Andrew McShan. “BioDolphin is the first resource to collect this type of information for all kinds of proteins, not just those found in membranes. And because it is publicly available, this information is now at the tips of researchers’ fingertips.”

“BioDolphin as a comprehensive database of lipid–protein binding interactions” is led by McShan, an assistant professor in the School of Chemistry and Biochemistry at Georgia Tech, alongside first author Li-Yen (Zoey) Yang, Bioinformatics Ph.D. student; School of Computational Science and Engineering Assistant Professor Yunan Luo; and Kaike Ping, a Ph.D. student at Virginia Tech.

Diving into accessible data

A curated database with richly annotated information, BioDolphin contains over 127,000 lipid-protein binding interactions. And while most databases of lipid-protein assemblies have focused solely on a specific type of protein — membrane proteins — BioDolphin expands beyond that.

“BioDolphin enables us to globally define the structural features of lipid-protein assemblies across the eight different classes of lipid compounds to understand their cellular function and roles in disease,” says McShan, adding that the database also provides information on paired lipid-protein annotation, experimental binding affinities, intermolecular interactions, and atomic structures across a wide range of lipid-protein interactions — all available to anyone with an internet connection.

A molecular blueprint for research — and teaching

“In the past, this research has been limited because lipids are notoriously difficult to study in the lab,” McShan says. "BioDolphin changes the paradigm. It is the first time that anyone has collected, annotated, and analyzed the known structural universe of lipid-protein interactions across all organisms.”

It’s a rapidly developing field. McShan was recently awarded a prestigious Curci grant for cutting-edge cancer research into lipid-based universal immunotherapies and vaccines.

Beyond research applications, the team hopes that BioDolphin will be a resource for biochemistry students. 

“The database can serve as a tool for teachers and students studying these protein-lipid interactions, which is often an underdeveloped topic in biology and biochemistry courses,” McShan says. “I hope that BioDolphin is a valuable resource for the researchers of today — and that it can also be a building block for the researchers of tomorrow.”

Funding: Shurl and Kay Curci Foundation, NSF Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program, NIH National Institute of General Medical Sciences (NIGMS), Partnership for an Advanced Computing Environment (PACE) at the Georgia Institute of Technology, and Taiwan Ministry of Education Government Scholarship to Study Abroad program.

DOI: https://doi.org/10.1038/s42004-024-01384-z 

In South Florida, two Caribbean lizard species met for the first time. What followed provided some of the clearest evidence to date of evolution in action. 

Lead author James Stroud, an assistant professor in the School of Biological Sciences, was studying Cuban brown anoles (Anolis sagrei) in South Florida when the Puerto Rican crested anole (Anolis cristatellus), suddenly appeared in the region.

Published in Nature Communications, the study documents what happens as the two Anolis lizards adapted in response to the new competitor, while helping to resolve a longstanding challenge in evolutionary biology — directly observing the role of natural selection in character displacement: how similar animals adapt in response to competition.

"Most of what we know about how animals change in response to this process comes from studying patterns that evolved long ago,” Stroud says. “This was a rare opportunity where we could watch evolution as it happened."

Competition from coexistence 

While these two small, brown lizards diverged evolutionarily between 40-60 million years ago and evolved on completely separate Caribbean islands, the two species are nearly identical, and fill similar ecological niches.

So, when the Puerto Rican crested anole suddenly appeared in Cuban brown anole habitat at Fairchild Tropical Botanic Garden in 2018, the two were competing for similar habitats and food sources.

“When two similar species compete for the same resources, like food and territory, they often evolve differences that allow them to coexist,” Stroud says. But, while scientists have found many examples of similar species developing different traits to ease this overlap, “scientists have rarely been able to observe this process as it unfolds in nature.”

Stroud’s team had already been studying Cuban brown anoles at the Fairchild Tropical Botanic Gardens in Miami, Florida, two years prior to when the crested anoles invaded. The team was able to quickly pivot to observe how the invasion changed both species, analyzing the lizards’ changing diets, measuring if the lizards were moving through foliage or on the forest floor, and recording the different species’ locations relative to each other. For over a thousand lizards, they also measured perch height — the distance from the ground that the lizard is perching — a primary marker of how Anolis lizards divvy up habitat.

“We not only observed how these lizards changed their habitat use and behavior when they encountered each other,” says Stroud, “but we also documented the natural selection pressures driving their physical evolution in real-time."

Human-made habitats and natural experiments

The research team found that when these lizard species occur together, they divide up their habitat in predictable ways — the Cuban brown anole shifted to spend more time on the ground, and evolved longer legs to run faster in this habitat, while the slightly larger Cuban crested anole lived in vegetation above the ground. 

"We found that brown anoles with longer legs had higher survival after crested anoles showed up," says Stroud. "This matches perfectly with the physical differences we see in populations where these species have been living together for many generations."

Stroud adds that while the research provides some of the strongest observations of evolution in action to date, it also demonstrates how human activities can create natural experiments that help us understand fundamental evolutionary processes — both species of Anolis lizard in the study were originally non-native to South Florida.

“As species increasingly come into contact due to human-mediated introductions and climate change, these studies may be important for predicting how communities will respond,” he says. "By studying these non-native lizards who are meeting each other for the first time in their existence, we had a unique opportunity to see the actual process unfold and connect it to the patterns we observe in nature."

Saurabh Sinha and a multi-institutional team of researchers have created a computational toolkit with the detection power and precision of a spy satellite. But instead of keeping tabs of human traffic on the ground, or infrastructure development in a city, they’re focusing on RNA with unprecedented clarity at the subcellular level. 

Their intracellular spatial transcriptomic analysis toolkit, or InSTAnT, can analyze cellular data and chart RNA interactions, providing new insights into the molecular processes of life and advancing an evolving field of research.

“Conventional spatial transcriptomics maps RNA at the tissue level,” said Sinha, professor in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University. “But InSTAnT represents a step forward. It provides, for the first time, an analytic technique to fully exploit single-molecule resolution. This means we can explore the intricate architecture, machinery, and activity of cells in ways that were not possible before.”

In addition to Georgia Tech and Emory, the team included researchers from from the University of Illinois Urbana-Champaign. With Anurendra Kumar, a grad student in the Sinha lab, as lead author, they explained their innovative work recently in Nature Communications.

Subcellular GPS

Spatial transcriptomics has enhanced the study of gene expression (how genes regulate cellular functions and behaviors), revealing molecular activity in its natural environment. The aim is to gain a deeper understanding of biology, health, and disease, with the hope of developing targeted treatments.

“One of the biggest challenges in the field was the lack of systematic tools to analyze spatial relationships at the subcellular level,” Sinha said. “We saw this gap as an opportunity to innovate and solve a problem that was truly spatial in nature.”

InSTAnT was designed to work in tandem with imaging-based spatial transcriptomics technologies like MERFISH (Multiplexed Error-Robust Fluorescence In Situ Hybridization, developed by Harvard in 2015), which can observe thousands of RNA molecules inside single cells, gathering detailed information about gene activity. 

“It’s like a GPS for tissue, looking all the way down to city street level,” said Sinha. “The little dots on this GPS aren’t people. They’re RNA molecules called gene transcripts. But we didn’t really know how to make sense of this distribution of molecules in the cytoplasm or the nucleus, or generally within the cell.”

InSTAnT translates what MERFISH gathers, using advanced statistical tests and algorithms, analyzing the distribution of RNA molecules that carry genetic information needed for various cell functions.

The Cities in Our Cells

If a cell was a busy little city, think of the gene transcripts — RNA molecules, the dots in Sinha’s GPS scenario — as workers moving around town, performing their important tasks.

 InSTAnT keeps tabs on this activity, investigating where and how these workers interact, and what they might be up to. So, InSTAnT identifies RNA pairs in specific areas, observing molecular interactions that are critical for cellular functions like protein production.

“Our toolkit provides a level of detail crucial for understanding complex biological processes and how they contribute to diseases,” said Sinha, whose team tested the toolkit on a variety of datasets, including human and mouse cells, and across multiple cell types and brain regions. 

He expects InSTAnT to transform how researchers study RNA interactions and explore unknown aspects of cellular organization and function.

“I think we’ve opened new possibilities for studying how cells coordinate their activities and adapt to challenges,” said Sinha, adding, “and it was a true team effort, with two other PIs from another institution, and a talented Ph.D. student as the lead author. This is a great example of how collaboration and data-driven science can uncover new biological frontiers.”

CITATION: Aunrendra Kumar, Alex Schrader, Bhavay Aggarwal, Ali Ebrahimpour Boroojeny, Marisa Asadian, JuYeon Lee, You Jin Song, Sihai Dave Zhao, Hee-Sun Han, Saurabh Sinha. “Intracellular spatial transcriptomic analysis toolkit (InSTAnT),” Nature Communications. https://doi.org/10.1038/s41467-024-49457-w

FUNDING: This research was supported by the National Institutes of Health, grant Nos. R35GM131819, R35GM147420, R21HG013180, and T32- 842 GM136629; Johnson & Johnson (WiSTEM2D Award for Science). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of any funding agency.