By Aaron Conley
Systems biology and the Lopez lab
The history of hermeneutics started with Aristotle—parts comprise the whole. To understand the whole, we need to understand the parts. And to understand the parts, we need to understand them in the context of the whole.
Carlos F. Lopez, associate professor of biochemistry, described this concept and its connection to systems biology. The biomedical research field has “spent a lot of time breaking down the whole to understand individual components, such as the organs in a human or single cells in a tissue,” Lopez said. “But now we are trying to take our knowledge of components and understand how each works as part of the whole system.”
Biology researchers are now at a point where instrumentation, large genotyped and phenotyped data sets, and computer analytics can be used to address complex systems biology questions in the search for new discoveries. Lopez’s lab employs these tools, including computational modeling, machine learning and dynamic network analysis methods, to explain and predict cell behaviors, with a focus on mechanism dysregulation—such as that found in cancer. The lab also creates tools that can aid in systems biology research. The Lopez lab has had a prolific year, publishing six papers in 2021 and developing multiple open-source tools.
Lopez’s draw to the field
Lopez was drawn to the huge scientific questions that need multiple perspectives for finding the answer. For example: When you have a headache, you take a pill, then it goes into your bloodstream and your organs, and it blocks one molecule to take away your headache. “But how,” Lopez asked, “do the molecular interactions that take place at the nanometer space scale and femtosecond time scale translate to a whole-body response? A femtosecond is to a second, as a second is to a century. It’s equivalent to trying to understand how this interview is going to change the whole earth in 100 years! Understanding how molecular changes change the whole body is a very hard problem because small things can have huge impacts, and we do not yet know how this works—mutations, viruses, drugs, et cetera—these happen at a small scale but have huge impacts.”
To unpack these systems biology questions, it takes massive amounts of (often) noisy or uninformative data. “Nature evolved despite the noise in this data,” Lopez explained. “That is a fundamental question we want to answer: how does nature work?”
To get to these answers, “we can generate lots of data,” Lopez said. “Our mass spectrometry cores can measure 100,000 proteins and metabolites in one shot, at one time point, and we need tens or even hundreds of time points to extract mechanistic knowledge from this data. So, we get into the millions of measurements very quickly. In addition, scRNA-seq data provides gene expression information for thousands of cells, each comprising approximately 20,000 genes, at each time point. You get into the millions and billions of data points rapidly. It’s terabytes of data. It is very complex to understand, to get knowledge out of so many measurements, and that is our challenge: How do we take this data and turn it into knowledge?”
Development of tools
Often the tools to address these challenges simply do not exist, so the Lopez lab will develop them. One such tool, recently developed by the Lopez lab and its collaborators, is Thunor, which organizes, analyzes and visualizes cell responses to drug treatment from high throughput screening. The ability to visualize and analyze cell proliferation has meaningful implications for drug discovery efforts. Lopez’s goal with Thunor is to have “open-source tools to make crowd-driven knowledge attainable and move the field forward.”
In collaboration, Lopez and Vito Quaranta, professor of biochemistry and director of the Vanderbilt Quantitative Systems Biology Center, have developed a novel theory and algorithm called MuSyC to deconvolve efficacy and potency of drug combination in cancer. David Wooten, PhD’18, and Christian Meyer, PhD’20, who both have backgrounds in physics, developed the theory for MuSyC, published in the journal Nature Communications, and showcased its application in a separate publication in Cell Systems. Lopez explained that MuSyC has the “potential to transform the enterprise of drug-combination screens.” MuSyC acts by precisely guiding researchers and physicians to combinations of drugs they can prescribe to patients at lower doses, with improved efficacy, or both. Read more about MuSyC here.
The software, tools and expertise of the Lopez lab helps researchers internationally sift through large data to obtain hypotheses through analytics that help reduce bias and open new discoveries. Lopez added, “Systems biology is at a threshold where something big is going to happen.”
Go deeper – Lopez lab publications
- Probability-based mechanisms in biological networks with parameter uncertainty
- Programmatic modeling for biological systems
- The misleading certainty of uncertain data in biological network processes
- Unsupervised logic-based mechanism inference for network-driven biological processes
- Thunor: visualization and analysis of high-throughput dose–response datasets
- Microbench: Automated metadata management for systems biology benchmarking and reproducibility in Python
Funding
The research above was supported by the Vanderbilt International Students Program, the National Science Foundation, the National Institutes of Health, the National Cancer Institute, the National Library of Medicine, the Vanderbilt Biomedical Informatics Training Program and the Defense Advanced Research Projects Agency.