Researchers led by SFI External Professor Andreas Wagner have developed a new quantitative approach to identifying the chemical reactions most essential to life-sustaining metabolism.
By identifying those select few biochemical reactions that are required in the metabolic networks they sustain, the research may help address the problem of antibiotic-resistant pathogens. Such pathogens rapidly evolve biochemical workarounds to the chemical processes that traditional antibiotics are designed to disrupt. Drug-resistant pathogens are among the most dangerous threats to public health.
Previous research has focused on identifying chemical reactions essential for specific pathogens to live. The approach has been to develop drugs to inhibit those reactions essential to the individual pathogen but not needed by people, such as reactions for constructing cell walls not present in human cells.
“But a reaction essential in one pathogen may not even exist in another,” says Andreas, “because there may be an alternative pathway of chemical reactions that can produce the products that the pathogen needs [say, to construct cell walls].”
When such an alternative pathway exists, pathogens under selection pressure from antibiotic use may quickly develop drug resistance by gaining the genetic machinery from another organism (through a process called horizontal gene transfer) for that alternative pathway.
The new research identifies a short list of reactions essential to all metabolic processes and that cannot be bypassed. Those reactions Andreas calls “superessential,” and the research identifies 125 of them.
To identify these reactions, Andreas and his team constructed a “universal metabolic network” from 5,906 metabolic reactions known to take place in some organisms. Because this universal network would contain all possible alternative pathways that could bypass a reaction, the team was able to identify an irreducible set of reactions essential for metabolism, then generate a ranking based on how essential each reaction is. The team cross-checked the results by identifying essential reactions in randomly generated combinations of reactions that form, fictional, but viable, metabolic networks for given environmental conditions.
By targeting those reactions that rank highest in this essentiality index, the researchers say, drug developers might be able to identify the most promising reactions to inhibit a pathogen while heading off evolutionary processes that lead drug resistance. Analyzing this many networks in this much detail required enormous computational processing power, Andreas says.
The results the team reported in the May 1 issue of PNAS are limited to reactions that are superessential for the biological use of carbon sources, such as the sugar glucose. Now the team is turning its sights on reactions involving nitrogen and sulfur sources -- two more of the six total elements required for life.
The additional results are forthcoming, says Andreas, “but the day only has 24 hours.”
Read the paper in PNAS (April 16, 2012, subscription required)