All the Small Things

Growing up, I was always fascinated with the show StarTrek and the show’s portrayal of vast advancements in STEM fields and the crew’s mandate to “boldly go where no man had gone before” into the vast recesses of unknown space. While I do believe we are still a ways off from interstellar travel at warp speed and transporting people to and from various locations with light beams, the rapid progress of technology seen in our everyday lives makes some of these advancements an eventually inevitability rather than something out of science fiction.

Love it or hate it, we live in the technological age of artificial intelligence. AI summaries can be found at the top of a website page; denoting answers to questions with summarized bullet points within seconds of pressing ‘enter’. ChatGPT has revolutionized, to great benefit or detriment depending on one’s point of view, how academic literature can be composed, ‘smart’ computer software is now used to generate the coding required for new computer programming, and even programs as mundane as Microsoft Power Point have facilities to artificially improve presentation design. Everywhere we look today, it seems, there is some form of technology ready to assist us upon command. Nowhere is this truer than the use of technologically generated intelligence within the ever-growing field of science and scientific research.

The question now becomes this: how do we use such powerful tools that are currently at our disposal to expedite the current rate of scientific discovery?

This increased pace of scientific innovation may seem, at first, to be rather unnecessary. Surely, if we as a society have reached a zenith of technological capability, certainly this would also be reflected in fields like science and technology that the very creation of artificial intelligence is dependent upon? Our ability to accrue novel information about the world around us is at an all-time high. Included in this plethora of knowledge is a massive amount of information garnered from traditional culturing methods from millions of species within the microbiome. While this may seem like a great achievement, it is estimated that only around two percent of microbials can be effectively studied in laboratory settings; meaning there is still an untold amount of microbial information left unaccounted for. Discovery of what remains unknown is not only paramount for the betterment scientific practice as a whole, the answers that may potentially remain hidden within these as-of-yet undiscovered and unstudied species could be pivotal for the mounting pressures in today’s society. Global populations are expected to increase to 9.8 billion by 2050, placing even greater burdens on current food and pharmaceutical supplies. Occurrences of bacterial resistance to currently prescribed antibiotics continue to be an increasing concern in healthcare and over the past several decades there has been a notable increase in the number of emerging infectious diseases that have been detected worldwide due to a variety of factors.

So how are we supposed to figure out how to deal with all of these issues at the same time we continue research upon currently known microbial species and attempt to unlock the rest of the microbiome that has yet to be studied?

Enter the modern marvel of artificial intelligence in all its diversified glory.

Thanks to modern technology and artificial intelligence, advances in traditional, culture-dependent microbial research as well as novel methods such as single-cell genomics and metagenomics – the process of deducing the genetic structure and potential function of all organisms within a select area- from various biomes. We now have access to many microbial species from a wide variety of niches that were previously difficult or impossible to maintain in laboratory settings through genome sequencing and analysis. A number of programs have been developed for multiple, such as species discovery, genomic profiling and sequencing, studies on novel functional proteins, and pattern recognition and prediction. The functional protein profiling and pattern recognition, in particular, could play a key role in the near future. Rapid discovery of new proteins could lead to breakthroughs in refining medicine and agriculture.  Pattern recognition and predictive algorithms could be invaluable to the medical field for predicting antimicrobial resistance likelihoods, emergent infectious diseases and potential outbreaks of epidemics before they occur. The applications of AI need not be limited to handling raw data from novel microbial niches, however. With time, algorithms reliant upon real-time calculations could be implemented to accommodate the ever-changing microbial content of location-specific areas to monitor changes to the biome resulting from either environmental shifts seen as a result of climate change or in more subtle microbial alterations such as gut microbiota influenced by location and diet to better predict the likelihood of developing diseases. The continued creation of analytical tools and the amount of microbiota we have yet to unearth from the unknown truly make the possibilities seem endless.

Of course, no feat of technological engineering no matter how masterfully crafted will generate the perfect variant of all-encompassing artificial intelligence. Many programs currently established are designed with a singular objective in mind, and each – much like their human research counterparts – come with their notable shortcomings. Current flaws and glitches aside, the amount of information garnered from these numerous sources in even the short amount of time that AI has been implemented into scientific and microbial study all but indicates that in the future, AI complimented research will not merely be one possible pathway forward, it will be the only way forward for any researcher who wishes to produce relevant results in conjunction with their peers. And while numerous data storage and analytical systems and computational models will need to be developed and adjusted accordingly as both our knowledge of microbials shifts and as the microbes themselves adapt to survive within their niches, the future for exponential discovery of new species paired with their genetic code and functional proteins that may serve to benefit the global community in a multitude of ways is very promising.

Witnessing the future will certainly prove to be interesting, especially with how microbial research and scientific research as a whole will unfold in the coming years and decades as artificial intelligence becomes more thoroughly integrated into every facet of the experimental process. AI has opened the door, both figuratively and literally, to a whole new world of possibilities, and will no doubt continue to generate countless more opportunities as we boldly venture into the world of undiscovered microbiology to find the answers and the solutions for today and for tomorrow.