Biofilms grow practically on every surface exposed to aqueous environments, including but not limited to metals, polymers, living tissues and medical implants. They are widely researched in agricultural, industrial, and life science domains. Biofilms can be incredibly beneficial or exceedingly harmful. For example, detached cells from pathogenic biofilms are known to transmit pathogens in food production facilities, water pipelines, and medical devices. The U.S alone spends ~$90 billion every year to deal with the associated infection challenges. Sulfate reducing bacteria (SRB), a special class of microorganisms are adept in colonizing and growing on metal surfaces. Furthermore, they play a pivotal role in accelerating corrosion of these surfaces and use the oxidizing power to meet their metabolic needs. This special class of corrosion, known as microbiologically influenced corrosion (MIC) is responsible for expenditure ~ $4 billion/year in the United States. Many other biofilms have been reported to thrive in the most known harsh conditions including the hot environments in deep biospheres (e.g., abandoned gold mines) as well as hot springs (Yellowstone national park). To solve these vexing problems, there is a need to develop focused transdisciplinary collaborations that cross typical disciplinary and organizational boundaries. This workshop will introduce a set of deep engineering science questions and pressing biofilm challenges, and subsequently the artificial intelligence (AI)-based data-driven approaches and bioinformatics tool for studying them. The participants will appreciate the need to embrace data science and AI resources for gaining a precise control over the early stages of biofilm growth. We will discuss recent advances in to address biofilm ecology challenges.

Microbial biofilms are assemblages of microscopic organisms (bacteria, algae and fungi) that accumulate at interfaces. Biofilms attached to solid surfaces are particularly troblesome in industry, public health, and medicine, where they can cause a wide range of problems from oil souring, corrosion, product spoilage, increased drag on ships and pipelines, to harboring and releasing pathogens in food and water systems to human infections of implants and host tissues in wounds, urogenital tract, the oral cavity and compromised lungs. When microorganisms form biofilms they become hundreds to thousands of times more tolerant to antimicrobial agents and antibiotics than would be predicted from routine testing of the isolated organisms. Biofilm microorganisms are also protected from immune defenses. In biofilms the microorganisms protect themselves in a layer of extracellular polymeric slime (EPS) layer. In many cases biofilms are polymicrobial which increases their complexity and the difficulty in their prevention and treatment. Currently, there are no definitive diagnostic markers for microorganisms in the biofilm phenotype making them difficult to detect. In industrial systems sensors can detect system abnormalities but may not differentiate from a primarily biological or chemical (i.e. biofilm, scale or corrosion) mechanism, so that amelioration techniques are often based on assumption or anecdotal experience. In medical infections conventional clinical microbiology diagnostics produce a high rate of false negatives, and the lack of a diagnostic marker or imaging modality retards detection as well as the ability to assess the efficacy of an implemented treatment more effectively. In the age of omics thr collection of big data such as genomics, proteomics, metabolomics provides complex patterns that might be associated with early detection or diagnosis of biological infection, or the host response to that infection. Similarly, sensing modalities such as hyperspectral imaging, Raman microscopy, medical imaging and multiple system performance parameters provide large data sets which have potential to be used for detection and diagnostics. What is missing is how to interpret these large data sets in order to make them useful in recognizing patterns that can be used to 1) more accurately provide early detection, 2) inform optimized treatment strategies and 3) rapidly assess the effectiveness of a treatment. In addition, the development of remote and indwelling sensors specifically designed to detect, characterize, and quantify biofilms will make a major contribution in our understanding and control of problems caused by biofilms which is a significant societal and personal burden. Conversely, such sensing technologies may facilitate the optimization of processes such as water treatment, bioremediation, carbon sequestration, biofuel production and fuel cell technology, all of which biofilms may be utilized.