Studies by researchers at Rockefeller University have helped to explain why target-based antibiotics against Mycobacterium tuberculosis (Mtb), the bacterium that causes tuberculosis (TB), are not always effective. Their research suggests that while the discovery of genes essential to the bacterium’s life cycle may send scientists rushing off to develop drugs that inhibit that target, such essential gene targets differ in their degree of vulnerability to antibiotics.
The new results indicate that an ideal target is one that is so vulnerable to attack that the cell cannot survive when it is even slightly inhibited. Invulnerable genes, on the other hand, can weather nearly total inhibition, eking out just enough target activity to keep the cell alive while being bombarded with antibiotics. Rockefeller University researchers, headed by Jeremy Rock, PhD, head of the Laboratory of Host-Pathogen Biology, have now also quantified vulnerability in a pathogen for the first time, producing an index that ranks almost every essential gene in Mtb by the amount of inhibition necessary to disable the gene and cripple the cell.
“The failures of target-based drug discovery are often ascribed to problems with the compound, like its inability to cross the bacterial envelope,” Rock said. “This is the other side of that coin. If you pick a gene target that is highly invulnerable, you’re just not setting yourself up for success.” The authors reported on their work in Cell, in a paper titled, “Genome-wide gene expression tuning reveals diverse vulnerabilities of M. tuberculosis.”
New antimicrobial drugs typically come from broad screening tests. Researchers assess libraries of compounds in bacteria in the lab, and see which ones prevent further growth. It’s quick and can be incredibly effective—every drug approved to treat TB was discovered in this manner.
Another discovery approach, known as target-based drug discovery, involves identifying essential genes that the bacteria cannot live without, and then developing compounds that inhibit those targets. This method has given us a number of potent anticancer and antiviral drugs.
But, to date, the target-based approach hasn’t worked well for antibiotics, and developing drugs to combat tuberculosis has proven a frustrating business. Scientists may identify a gene essential to the bacterium’s lifecycle, and rush to develop drugs that inhibit the target, but are then faced with disappointment. Volleys of compounds thrown at the essential gene target have little impact on microbial growth, the bacteria live on, and the scientists return to the drawing board.
Rock and his team wondered why this target-based drug discovery approach wasn’t working for antibiotics. Conventional wisdom had it that the compounds were getting lost en route. Perhaps they were blocked by the cell wall, pumped out upon entry, or metabolized within. Those were hurdles that potential antibiotics may face. But Rock suspected that drug developers were also sometimes choosing the wrong targets. It’s not enough to identify an essential gene that a bacterium cannot live without. A good target should also be vulnerable. “Vulnerability relates the magnitude of gene expression inhibition with the resulting decrease in organismal fitness, thus describing gene essentiality as a continuous trait,” the authors wrote.
So, a vulnerable gene effectively buckles under pressure—even slightly hindering its expression will take the gene offline and cripple the bacteria. Invulnerable genes, however, can take quite a beating and still get their essential jobs done. Given that most drugs inhibit only a portion of their targets, failed antibiotics could be finding their mark only to bounce off an invulnerable gene.
“If a target is highly invulnerable and requires 99% inhibition in order to kill the bacteria, then you’re going to need to target it with a small molecule that can do something special, like inhibit 99% of that gene product,” Rock said. “That’s not impossible but, if you have 600 essential genes to choose from, you don’t want to pick that one as your target.”
Rock and his team decided to quantify gene vulnerability in Mtb, a pathogen that claims 1.4 million lives each year. They developed a technique to look at the whole genome of the pathogen at once, and rank each essential gene based on how much of it would need to be inhibited in order to kill the bacteria. “We developed a CRISPR interference-based functional genomics method to systematically titrate gene expression in Mtb and monitor fitness outcomes,” the authors noted. “We developed a mathematical framework to describe bacterial fitness as a function of predicted inhibition of target gene expression.”
“We developed a system that can be tuned, from no inhibition to nearly 100% inhibition,” explained Barbara Bosch, MD, a physician-scientist in the Rock lab. “This allowed us to determine whether the bacteria were having serious fitness costs, or whether they were still alive and kicking.”
The resulting index, which relates inhibition percentages to bacterial fitness, suggests that vulnerability is a key factor in determining whether antibiotics succeed. Two of the most vulnerable genes, for example, happen to also be the targets of the two most potent TB drugs on the market. “The fact that the targets of the two most potent first-line TB drugs rank in the upper vulnerability quartile lends credence to the validity of vulnerability estimates to nominate valuable therapeutic targets,” the team commented. Conversely, two of the least vulnerable genes, coaA and def, were once promising drug targets before antibiotics tailored to inhibit those genes failed to kill the bacteria. The invulnerability of those targets may be one reason that these therapies flopped.
The index also identified several new targets that are essential, highly vulnerable, and as-yet unexplored by drug developers. Some of those targets are even more vulnerable than those of the current first-line TB therapies, and influence surprisingly diverse activities in the cell. “This work provides a technical and conceptual framework for genome-scale assessment of gene vulnerability in diverse bacterial pathogens and a roadmap for prioritization of targets for drug discovery,” the investigators noted. “Numerous targets that are highly vulnerable in Mtb have yet to be pursued, including targets significantly more vulnerable than the current first-line TB therapies and in underexplored processes ….”
“We expected that genes involved in the central dogma would be vulnerable—to replicate, you need to be able to turn DNA into RNA into protein,” Rock said. “But some of the most vulnerable genes were involved in protein folding and secretion. We wouldn’t necessarily have predicted that …. These are under-explored targets that would be worth exploring in the future.”
The current index is based solely on how TB reacts to inhibition in a dish in the lab. So, In future studies, Rock and his team hope to test their index on TB that has infected a living organism. “The next big step is investigating how vulnerability changes in the context of the host-pathogen relationship,” Rock commented. “In vivo studies will give us a more complete picture of vulnerability.”
Encouragingly, the results from the lab do match clinical observations. Effective TB drugs work by disabling genes that also rank high on the vulnerability index, while stubborn targets that baffle scientists rank lowest. The upshot is that drug developers would likely benefit from consulting the vulnerability index even now, prioritizing vulnerable genes when investing in target-based drug discovery. “We don’t want to equate invulnerability with undruggability—that would be unfair,” Rock pointed out. “But the path forward is to start prioritizing vulnerable targets over invulnerable ones … If you want to work with an invulnerable target, it’s going to be an uphill battle.”
The authors concluded, “Our results provide a roadmap to reinvigorate target-based drug discovery in TB; all else being equal (e.g., druggability), prioritize vulnerable targets and de-prioritize invulnerable targets for drug screening. Increasing the success rate of target-based drug discovery would be particularly impactful, given the failures of this platform to robustly identify new clinical antibacterial leads.”