Many effective medications have their roots in naturally occurring organisms including plants, fungus, and bacteria, yet it is still challenging to screen natural items for therapeutic potential.
According to a study published November 30 in Proceedings of the National Academy of Sciences, a novel strategy using molecular biology, analytical chemistry, and bioinformatics to integrate data from various screening platforms addresses some of the most difficult problems in natural products drug discovery.
Determining a novel bioactive compound’s mode of action and the biological target has proven to be a significant problem. Finding the molecule or molecules that are responsible for biological action in a complicated mixture of natural ingredients is another major difficulty.
“These two big concepts have been at the heart of our collaborative program, and this paper brings those two questions together in a fully integrated approach,” said corresponding author John MacMillan, professor of chemistry and biochemistry at UC Santa Cruz.
Along with MacMillan, the collaboration includes Roger Linington from Simon Fraser University in British Columbia, Michael White from the University of Texas Southwestern Medical Center, and Scott Lokey, professor of chemistry and biochemistry and director of the Chemical Screening Center at UC Santa Cruz.
The researchers developed a special and effective framework for natural product biological characterization by merging the outcomes of two very diverse screening platforms with next-generation metabolomics analysis of their natural product libraries.
They were able to identify a known compound (trichostatin A) and confirm its mode of action using this method to screen a small collection of randomly chosen microbial natural product fractions. They were also able to link a known compound (surugamide) with novel biological activity (cyclin-dependent kinase inhibition) and discover new compounds (parkamycins A and B) with complex biological activity.
If we see similar effects to one of those known compounds, that suggests a similar mechanism of action. We have used this technology effectively to understand the biological activity of a number of unique small molecules.
Professor John MacMillan
“Finding a known compound that groups, as expected, tells us it’s working, and then we were able to correlate a known compound with a new mechanism of action,” MacMillan said. “Finally, we discovered a new chemical compound with a unique biological signature, unlike any known compounds. That’s an exciting finding we want to investigate further.”
The researchers combined data from two natural product screening systems their labs had created using a bioinformatic technique called Similarity Network Fusion (SNF), which was created for merging complex information.
By combining pattern-matching algorithms with gene expression patterns elicited in cells by known and unknown substances, one platform (Functional Signature Ontology, or FUSION) created by MacMillan’s team employs “guilt by association” to suggest mechanisms of action.
“If we see similar effects to one of those known compounds, that suggests a similar mechanism of action. We have used this technology effectively to understand the biological activity of a number of unique small molecules,” MacMillan said.
The second platform, a cytological profiling (CP) tool created by Lokey’s team, analyzes high-content images of cells exposed to the samples being screened and then uses a panel of fluorescent probes to highlight important cytological traits. Each sample produces a total of 251 distinctive cytological characteristics from automated fluorescence microscopy photographs.
The scientists screened sophisticated natural product libraries created by MacMillan and Linington’s labs using the CP and FUSION technologies. These libraries were from marine bacteria that the two labs isolated.
The researchers cultivate the bacterial strains in the lab, prepare a crude extract of every component each strain produces, and then use chromatography to divide each extract into a series of fractions, each of which contains two to twenty compounds, in order to look for bioactive natural products.
When studying tiny molecules on a large scale (“metabolomics”), mass spectrometry techniques are frequently used and can be used to determine the chemical components of each fraction.
Compound Activity Mapping, a method created by Linington and colleagues, combines biological screening data with mass spectrometry-based metabolomics to determine which chemicals in a mixture are responsible for a specific biological signature.
With the help of mass spectrometry and a modified version of their Compound Activity Mapping platform, the researchers created a sample processing workflow for the current study that incorporates the combined outcomes of their screening technologies gained through Similarity Network Fusion.
“The question is, can we use all that to pull out the chemicals that are driving a particular signature and make more robust predictions of the mechanism of action? Our approach allowed us to accomplish that in a pretty substantial way,” MacMillan said.
In addition to MacMillan, Lokey, and Linington, the coauthors of the paper include Michael White, Suzie Hight, Elizabeth McMillan, Anam Shaikh, Rachel Vaden, Jeon Lee, and Shuguang Wei at University of Texas Southwestern Medical Center; Trevor Clark, Kenji Kurita, Jake Haecki, and Fausto Carnevale-Neto at Simon Fraser University; and Walter Bray, Aswad Khadilkar, Scott La, and Akshar Lohith at UC Santa Cruz. This work was supported by the National Institutes of Health.
