High-Throughput Biofilm Assay to Investigate Bacterial Interactions with Surface Topographies


A thorough knowledge of how surface texture influences bacterial-material interactions is necessary to rationalize safe medical devices. While some medical devices, such as surgical instruments, are purposefully textured on the surface to promote tissue interactions, other medical devices, such as breast implants, are developed with smooth surfaces to assure cleanability. The texture of medical device surfaces can impact bacterial adherence and colonization. Textured breast implants are an example of a recent, well-known case of unfavourable occurrences connected to surface texture. Roughness of the device’s surface has been the focus of numerous attempts to link safety risk to texture of medical devices. The precise topography of biomaterials significantly impacts how they interact biologically with cells and, consequently, how safe medical implants are. Topographic features can be included into antifouling materials to prevent colonization of bacterial pathogens. On the other hand, undesirable implant topographies can result in problems including breast implant-associated anaplastic large cell lymphoma. A better understanding of pattern-specific bacteria-material interactions is required to determine how quantitative measurements will function across a range of different qualitative textures and size scales and whether they may be applied to novel, untested features. Due to manual sample processing, particularly manual sample wash processes, current methods of measuring bacterial adhesion are low throughput and have significant data variations between researchers and different laboratories.

In a new study published in the journal ACS Applied Bio Materials, Professor Dacheng Ren from Syracuse University together with Dr. Sang Lee, Dr. Erick Johnson, Dr. Alex Chediak, Dr. Hainsworth Shin, Dr. Yi Wang, and Dr. Scott Phillips from the United States Food and Drug Administration, devised a reliable and controllable high-throughput approach and improved the parameters for screening material libraries. They used a library of polydimethylsiloxane (PDMS) surfaces with different sizes of recessive topographic features and spacing between features to validate this method.

The authors used a high-throughput approach to better understand how common textural features may affect adhesion and biofilm formation, which could help understand device-associated infetions. They were able to evaluate a sizable library created with the aim of separating the influence of specific topographic patterns from general surface roughness thanks to the high throughput capability of the new technology. In their study, the side length and distance were deliberately changed to produce various designs with the same level of surface roughness. Some specific patterns were found to promote E. coli adhesion. The overhangs or pores that can be seen in optical microscopic photographs and scanning electron microscopic images of some commercial implants are not present in the square-like recessive features investigated in this work.

The authors’ findings suggest that size and qualitative feature type are important in the early adhesion behaviour, which may be connected to the size of the E. coli flagella and their functions in the early biofilm formation. They were able to better comprehend bacterial adhesion to various topographies by screening a reasonably large pattern library than through low-throughput approaches using only a few sample designs. They also demonstrated that estimating the tendency for bacterial adhesion and biofilm formation in vitro only based on surface area or roughness is insufficient. The new assay created here can be utilized to investigate further how these other factors affect bacterial adhesion at an early stage. By changing the rinse conditions, this approach can also be used with different strains and materials.

In conclusion, a high-throughput methodology was developed to compare biofilm growth on biomaterial surfaces quantitatively. The new assay will stimulate further research into the interactions between bacteria and specific qualitative types of surface characteristics and patterns at various size scales, which may be present on medical devices.

About the author

Dr. Dacheng Ren received his Ph.D. in Chemical Engineering from University of Connecticut in 2003. After finishing postdoctoral training at Cornell University, he joined Syracuse University in 2006. Currently, he is Stevenson Endowed Professor in the Department of Biomedical and Chemical Engineering, and Associate Dean for Research and Graduate Programs in the College of Engineering and Computer Science.

Dr. Ren received an Early Career Translational Research Award in Biomedical Engineering from the Wallace H. Coulter Foundation in 2009 and a NSF CAREER award in 2011. He was named the College Technology Educator of the Year by the Technology Alliance of Central New York in 2010. Dr. Ren is also a recipient of the Faculty Excellence Award from the School of Engineering and Computer Science at Syracuse University in 2014, and Chancellor’s Citation for Faculty Excellence and Scholarly Distinction in 2018. Dr. Ren currently has more than 70 journal publications, 13 issued/pending patents, and more than 50 invited talks.  Dr. Ren has broad research interests in microbial control and the safety of medical devices. His research has been supported by NSF, NIH, EPA, Wallace H. Coulter Foundation, Alfred P. Sloan Foundation, and industrial sponsors. He is a fellow of American Institute for Medical and Biological Engineering (AIMBE).


Lee SW, Johnson EL, Chediak JA, Shin H, Wang Y, Phillips KS, Ren D. High-Throughput Biofilm Assay to Investigate Bacterial Interactions with Surface Topographies. ACS applied bio materials. 2022 Jul 11;5(8):3816-25..

Go To ACS applied bio materials.