A professor in the UH Cullen College of Engineering and his collaborator in the College of Pharmacy remain players in the relentless cat-and-mouse game played between bacteria and antibiotics with a $519,000 grant from the National Institutes of Health.
Chemical and biomolecular engineering professor Mike Nikolaou and pharmacy professor Vincent Tam earned their initial $400,000 grant from the National Science Foundation (NSF) a few years ago. Their work to combat drug-resistant bacteria has produced a patented equation that universally assesses the effects of combinations of antibiotics on bacteria found in preliminary lab data. By the end of 2015, the researchers anticipate the development of the first working prototype of a methodology and associated software to improve the process of determining effective antibiotic cocktails for patients in clinical settings and to expedite the development and approval of new antibiotics.
“So this is a race of humans developing antibiotics against nature’s evolving bacteria, and it’s very difficult to win that race because bacteria evolve fairly rapidly,” Nikolaou said.
The process of antibiotic development and approval is painstaking. From the moment a company discovers a molecule that kills bacteria to the time it determines a safe and effective dosing regimen for patients, the process can easily last a decade, Nikolaou said. Nikolaou and Tam’s work can more efficiently analyze data to find dosing regimens at particular concentrations that are both effective against bacteria and safe for patients.
Different antibiotics kill the multitudes of bacterial varieties in many ways, but the common thread is that all antibiotics remove elements vital to the survival and proliferation of bacterial cells. Through trial and error, physicians determine the least toxic antibiotic concentrations that are still potent enough to cure serious clinical infections, such as cancer in patients with weakened immune systems. At microbiology labs in hospitals, they add progressively more potent antibiotic concentrations to bacteria-infected blood in test tubes. After a certain period of time, usually 24 hours, they examine the results. Blood that remains cloudy is still infected with bacteria, while blood that appears clear is free of the microorganisms. The lowest antibiotic concentration that clears the blood is given to patients.
The problem is that bacteria are increasingly resistant, so physicians test concentrations of antibiotics that are so high that they become toxic for patients, and they still do not kill the bacteria. Bacteria develop mechanisms of resistance that counter the actions of the antibiotics. For example, the bacteria might develop efflux pumps that push antibiotics out of cells, or they might secrete substances that neutralize the antibiotics. In such cases, other substances are used to augment the same antibiotics to battle the countermeasures of bacteria.
“Single antibiotics are becoming less and less effective against bacteria, so very frequently you have to use combinations of antibiotics,” Nikolaou said. “In recent years, we’ve been using more combinations of antibiotics so that we can have a combined effect that can make the antibiotics more potent and perhaps kill bacteria that would otherwise be resistant.”
Numerous possibilities for interactions between antibiotics exist. An example of an interaction might involve one antibiotic opening pores in bacterial cell walls so another antibiotic might easily enter to do the killing, Nikolaou said. Physicians are presented with the challenge of considering overwhelming varieties of antibiotic combinations, or cocktails, and their dosing regimens for patients. Time restrictions necessitate that they eyeball results and make best guesses about treatments based on their expertise and intuition.
“Unfortunately, no one has the time,” Nikolaou said. “Doctors’ and patients’ time is extremely precious.”
Nikolaou and Tam are working to optimize the process by reducing the amount of time and guesswork needed to assess the most effective drug combinations for killing bacteria.
“Our approach is empirical, so it relies on experimental data rather than detailed prior knowledge,” Nikolaou said. “So you don’t need to know the type of bacteria, the type of killing mechanism or the mechanism of resistance.”
Nikolaou and his team of students composed their basic mathematical model based on Tam’s observations of the effects of antibiotics and combinations of antibiotics on bacteria populations in blood over time. Through better use of collected data, their equations predict the course of bacteria populations in realistic situations reasonably well.
“The equations do not define logic, they augment logic and intuition more accurately,” Nikolaou said.
The researchers plan to use existing image analysis technology to automatically record the effects of various antibiotic cocktails on bacteria in blood samples. A photometer modified for their purposes can feed the data to computer software, which the team is in the process of developing, that runs the patented mathematical model.
“The user will simply have to push the button, and the software will do the calculations that tell the doctor what antibiotic or combination of antibiotics to use at what concentration,” Nikolaou said.
Automation provides opportunities to collect additional data that is more accurate at more frequent intervals. The photometer can record data every hour, for example, rather than once at the end of a 24-hour time period. Instead of plotting two points on a graph, the software can plot 24 or more points and create an entire curve that helps to more accurately extrapolate outcomes beyond 24 hours. Furthermore, photo analysis can provide more precise information such as the extent of the blood’s cloudiness or clearness and the rate of decline of bacteria populations.
The software can also account for differences between patients and test tubes. Concentrations of antibiotics degrade over time in patients while they remain fixed in test tubes. In the field of antibiotics development, test tube research is often followed by tests conducted with elaborate systems that attempt to mimic the ways antibiotics work in the human body.
“So you’re gaining efficiency … plus you don’t have to do a bunch of tests afterwards,” Nikolaou said.