Cesar de la Fuente-Nunez, Ph.D.

Scientists used an algorithm to mine ‘the entirety of the microbial diversity’ on Earth, speeding up antibiotic resistance research

A new study used machine learning to predict potential new antibiotics in the global microbiome, which study authors say marks a significant advance in the use of artificial intelligence in antibiotic resistance research.

The report, published Wednesday in the journal Cell, details the findings of scientists who used an algorithm to mine the “entirety of the microbial diversity that we have on earth – or a huge representation of that – and find almost 1m new molecules encoded or hidden within all that microbial dark matter”, said César de la Fuente, an author of the study and professor at the University of Pennsylvania. De la Fuente directs the Machine Biology Group, which aims to use computers to accelerate discoveries in biology and medicine… Continue reading.

Cesar de la Fuente believes the next breakthrough antibiotic might come from animals that have been dead for thousands of years.

Since 2021, his lab here at the University of Pennsylvania has built algorithms to trawl genetic databases for protein fragments, called peptides, with microbe-squashing properties. They started with human DNA. But more recently, he’s looked deep into the fossilized past, hunting for potential drugs lurking in the code of Neanderthals, giant sloths and woolly mammoths, among other ancient animals.

His team uses robots to resurrect the most promising snippets and then tests whether they can clear infections in mice at rates comparable to the standard antibiotic polymyxin B. Last year, he named the approach “molecular de-extinction” — a much safer, more feasible and perhaps less lucrative version of Jurassic Park… Continue reading.

The specter of antibiotic-resistant bacteria looms large in our society. In two presentations we delve into AI-assisted research into antibiotic drug development. We will explore the latest research using AI to search the human genome for microbe-fighting peptides, as well as using AI as a novel approach to testing the susceptibility of antibiotics.

Continue listening at Science History.

César de la Fuente and a team of Penn engineers work on creative ways to create faster and cheaper testing for COVID-19. Their latest innovation incorporates speed and cost-effectiveness with eco-friendly materials.

When it comes to COVID-19 testing, polymerase chain reaction (PCR) tests, are the “gold standard” for diagnostic testing. However, these tests are hampered by waste. They require significant time (results can take up to a day or more) as well as specialized equipment and labor, all of which increase costs. The sophistication of PCR tests makes them harder to tweak, and therefore slower to respond to new variants. They also carry environmental impacts.

In order to balance the need for fast, affordable and accurate testing while addressing these environmental concerns, César de la Fuente, Presidential Assistant Professor in bioengineering and chemical and biomolecular Engineering in the School of Engineering and Applied Science, with additional primary appointments in Psychiatry and Microbiology within the Perelman School of Medicine, has turned his attention to the urgent need for “green” testing materials… Continue reading.

Scientists at the University of Pennsylvania Machine Biology Group have developed what they call a groundbreaking approach to drug discovery, which uses artificial intelligence to discover antibiotics in extinct organisms. In a newly published study in Cell Host and Microbe, the team described the use of the “molecular de-extinction” technology to discover antimicrobial peptides (AMPs) in our closest hominid relatives, the Neanderthals and Denisovans. Initial tests showed that the newly discovered archaic peptides encrypted in these extinct human proteins displayed anti-infective activity against bacterial infections in different preclinical in vivo models. The achievement could mark the start of a new chapter in the search for antibiotics and other valuable biomolecules, allowing scientists to harness AI and systematically explore long extinct organisms to help us better understand life’s molecular diversity and sequence space.

Senior and corresponding author César de la Fuente-Nunez, PhD, and colleagues reported on their study in a paper titled, “Molecular de-extinction of antimicrobial peptides enabled by machine learning.” In their paper, the team concluded, “These results suggest that machine-learning-based encrypted peptide (EP) prospection can identify stable, nontoxic AMPs … we establish molecular de-extinction through paleoproteome mining as a framework for antibacterial drug discovery… Continue reading.

Synthetic peptides can keep their bug-fighting properties but lose the sting

In the hunt for new antibiotics, people have looked in myriad locations. At the University of Pennsylvania, Cesar de la Fuente’s team goes hunting in the protein world. The researchers aim to find small proteins around 8–50 amino acids long with antimicrobial properties because peptide-based antimicrobials are thought to be less likely to induce resistance than small molecules. In the team’s latest published research, the researchers reprogrammed proteins in wasp venom to create antimicrobial peptides (AMPs) that fight bacteria without also hurting host cells, at least in mice… Continue reading.

Artificial intelligence is a new addition to the infectious disease researcher’s toolbox. Yet in merely half a decade, AI has accelerated progress on some of the most urgent issues in medical science and public health. Researchers in this field blend knowledge of life sciences with skill in computation, chemistry and design, satisfying decades-long appeals for interdisciplinary tactics to treat these disorders and stop their spread.

Diseases are “infectious” when they are caused by organisms, including parasites, viruses, bacteria and fungi. People and animals can contract infectious diseases from their environments or food, or through interactions with one another. Some, but not all, are contagious… Continue reading.

The American Peptide Society has selected César de la Fuente, Presidential Assistant Professor in Psychiatry, Microbiology, Bioengineering and in Chemical and Biomolecular Engineering, as the recipient of the prestigious 2023 Rao Makineni Lectureship Award.

Presented at the biennial American Peptide Symposium, the Makineni Lectureship Award recognizes an individual who has made a recent contribution of unusual merit to research in the field of peptide science, and is intended to acknowledge original and singular discoveries… Continue reading.

WASHINGTON, D.C. — The American Institute for Medical and Biological Engineering (AIMBE) has announced the induction of Cesar de la Fuente-Nunez, Ph.D., Presidential Assistant Professor at University of Pennsylvania to its College of Fellows.

Election to the AIMBE College of Fellows is among the highest professional distinctions accorded to a medical and biological engineer. The College of Fellows is comprised of the top two percent of medical and biological engineers. College membership honors those who have made outstanding contributions to “engineering and medicine research, practice, or education” and to “the pioneering of new and developing fields of technology, making major advancements in traditional fields of medical and biological engineering or developing/implementing innovative approaches to bioengineering education… Continue reading.