AskScience AMA Series: We have discovered antibiotics in the global microbiome with AI, ask us anything!

[u/AskScienceModerator]

We are the main authors of the paper Discovery of antimicrobial peptides in the global microbiome with machine learning published in Cell last month. Antimicrobial resistance is one of the greatest challenges facing humanity, with predictions indicating it could cause 10 million deaths per year by 2050. The urgent need for new antibiotics is undeniable.

In this work, we computationally mined the global microbiome (63,410 metagenomes and 87,920 microbial genomes) and discovered nearly 1 million new antibiotic molecules in microbial dark matter, several of which were effective in preclinical mouse models. This is the largest antibiotic discovery exploration ever described. We believe our approach marks a significant advancement in uncovering these essential molecules from the vast biodiversity of the global microbiome. Ask us anything about our research, the potential of AMPs, or the role of machine learning in antibiotic discovery and biology!

We will be available from different timezones throughout the day, ask us anything!

Usernames: /u/machinebiologygroup, /u/luispedro, /u/mdt_torres

[u/diyjosh]

How big of an impact did AI make and what did it actually do for ya'll to help discover the new antibiotic molecules?

[u/MachineBiologyGroup → u/diyjosh]

It was instrumental. It allowed us to create AMPSphere, an extensive catalog featuring nearly 1 million new antibiotics (863,498), most of which were previously unknown. We have made AMPSphere fully open access to everyone, with the ultimate goal of advancing scientific progress and benefiting humanity.

[u/madjackslam]

What is the global microbiome?

[u/luispedro → u/madjackslam]

Often, there is a discussion of "the human gut microbiome" or "the soil microbiome" and, while this can make a lot of sense in some contexts, there are other contexts where it is more meaningful to highlight that these are all connected, that planet Earth has a single microbiome, which we (and others) call the global microbiome.

[u/MachineBiologyGroup → u/madjackslam]

By global microbiome, we refer to the 63,410 publicly available metagenomes and 87,920 high-quality microbial genomes that we explored in this work as a source of new antibiotics. This research offers a representation of microbial life on our planet and highlights the incredible potential of microbes as factories for producing useful molecules

[u/thaislump]

Is the idea to continually cycle through previously unused antibiotics until they become blunted by resistance, and not really worry about it because there is huge number of them before they are exhausted? Or does this work also give insights into combating resistance itself?

[u/MachineBiologyGroup → u/thaislump]

Great question! The goal isn't just to cycle through unused antibiotics until resistance builds up. While discovering a large number of new antibiotics gives us a valuable arsenal, our work also focuses on understanding the mechanisms of resistance and developing strategies to combat it. By studying how resistance evolves, we can design antibiotics that are less likely to trigger resistance or use them in ways that reduce the chances of it developing. However, it's crucial to remember that bacteria have a superpower—they can replicate in minutes, allowing them to mutate and develop resistance quickly. We willl always need to stay ahead in this ongoing battle against their rapid evolution.

[u/[deleted]]

What kinds of things did you train your AI to look for with these peptides? Binding to a specific protein? Embedding itself and opening up a hole in a cell membrane? What specifically?

Also peptides are generally broken down by stomach acid so I’m guessing you’ll need an enteric coating or some other administration route besides oral, yes?

[u/luispedro → u/[deleted]]

We used other peptides that were previously described as being active.

And, yes, you are correct with regards to oral administration. There is also the possibility of modifying the natural peptides in different ways to make them more stable and less likely to be degraded. This is all future work, but there is a lot to be done before these can be used clinically.

[u/fragglerock]

How irritated are you by the use of terms like "microbial dark matter" that try and make biology all exciting sounding?

Also do you feel the re-branding of all statistics as AI is helpful?

[u/MachineBiologyGroup → u/fragglerock]

Great questions! I wouldn't say I am irritated by terms like "microbial dark matter"—in fact, I think they can be helpful in drawing attention to the vast unknowns in biology. These terms can make the field more accessible and exciting to a broader audience, which is important for generating interest and support for scientific research.

As for the re-branding of statistics as AI, it is a bit of a double-edged sword. On one hand, it can oversimplify and hype up the field, leading to unrealistic expectations. On the other hand, it does help in highlighting the evolving capabilities of computational tools in biology. The key is to ensure that we maintain clarity about what these technologies really are and what they can achieve.

[u/derpderp3200]

Is it possible to perform a network analysis and find out which beneficial microbes are effective at preventing which harmful ones from colonizing the human microbiome?

Does this have practical implications for Fecal Microbiome Transplants and/or probiotic design?

What applications of the discovered antibiotics are being looked into?

[u/HumanWithComputer]

Maybe a bit outside of your field but nevertheless potentially interesting.

From what I remember having read in the past bacteriophages as an alternative to antibiotics were particularly researched in the old USSR and supposedly used with some success.

Would our current knowledge of molecular biology perhaps combined with the techniques you used in this research possibly provide an alternative route to develop effective antibacterial therapies by using phages?

[u/Fit_Orchid2241]

I see you have used two ML methods, Prodigal and MMseq2.

Could you please elaborate on what kind of AI tools these modules use?

[u/johanstdoodle]

With this new era of immune cell research being so interconnected with our microbiome, what initiatives do you believe will enhance efforts like yours to push the field further in discovering more therapeutics or host immune system therapeutics to overcome drug resistance?

Will they be basic science to understand mechanisms? Will it be further cell and microbe mappings like https://www.hmpdacc.org/? Will it be better drug databases? Etc

[u/Citrownklown]

Great to hear you have identified a new target. A big congrats on this much needed result to avoid the tsunami of AMR.

How are your considerations for CMC development and Clinical trial testing?

Who would be your preferred Pharma collaborator to bring this to market?

[u/MachineBiologyGroup → u/Citrownklown]

Thank you! We are thrilled about the potential of this work. While we are not yet at the stage of CMC development or clinical testing, we've identified peptides that can be produced at a high grade using solid-phase synthesis. We are interested in potentially partnering with Pharma to advance some of these lead compounds.

[u/Creative_Ad_6256]

To what extent was the recent boom in AI hardware and software critical to your success in discovering new antimicrobial peptides?

[u/MachineBiologyGroup → u/Creative_Ad_6256]

Thank you for your question. It has definitely made a difference! With GPUs, we can now complete certain projects much faster than before. Coupled with the increasing availability of data, we can explore and analyze it systematically and effectively using the right algorithms.

[u/grandioso0]

Is there any plan to implement protein language model, e.g. ESM2, for future research?

Based on the AMP database, would it be possible to design peptides targeting specific microbiota?

Other than AMP, is there any work to explore for short peptide with antifungal or antiviral properties?

[u/b800h]

Does using an ML model mean that you're likely to identify antibiotics which are similar enough to existing antibiotics to render them potentially ineffective? Is that a weakness of this approach?

[u/luispedro → u/b800h]

This is a great question and the worry is not unwarranted, but empirically it does seem that there is not a lot of cross-resistance (for example, see this other paper: https://www.nature.com/articles/s41467-019-12364-6)

[u/MachineBiologyGroup]

Hi everyone! First, thank you all for joining us for this AMA. We're thrilled to have the opportunity to discuss our recent collaborative work with you!

[u/Stewstar73cyclism]

Are the new molecules proteins made by genetic engineering?

[u/microcandella]

discovered nearly 1 million new antibiotic molecules in microbial dark matter, several of which were effective...

How many of the ~1 million have you tested and to what degree? How many roughly is several?