About

Bahareh Behkam is a professor in the Department of Mechanical Engineering at Virginia Tech, where she has been serving since 2024. She is also an affiliate faculty member in the Department of Biological Systems Engineering and a member of the Center for Soft Matter and Biological Physics. Her research expertise lies in micro- and nanoscale systems engineering, with a focus on biomedical and environmental applications. Her lab's current research interests include bio-hybrid microrobotic systems for cancer therapy, engineered living materials for biosensing, mechanobiology of microbial infection, microbial adhesion, mammalian cell migration in multi-cue environments, and Micro/NanoScale Biotic/Abiotic Systems Engineering (MicroN BASE). She has contributed to developing engineered living systems for indoor air monitoring and creating bacterial robot platforms capable of targeting cancer cells. Dr. Behkam has been recognized as an emerging leader in biological engineering and has received numerous awards for her research and leadership. Her background includes a Ph.D. and M.S. in Mechanical Engineering from Carnegie Mellon University and a B.S. from Sharif University of Technology.

Research topics

• Computer Science
• Biology
• Artificial Intelligence
• Materials science
• Nanotechnology
• Human–computer interaction
• Medicine
• Ecology
• Computational biology
• Engineering
• Biochemistry
• Mathematics
• Cancer research
• Biophysics
• Pharmacology
• Internal medicine
• Chemistry

Selected publications

• Engineered live bacteria as disease detection and diagnosis tools

  Journal of Biological Engineering · 2023 · 43 citations

  Senior authorCorresponding
  • Computer Science
  • Computer Science
  • Computational biology

  Sensitive and minimally invasive medical diagnostics are essential to the early detection of diseases, monitoring their progression and response to treatment. Engineered bacteria as live sensors are being developed as a new class of biosensors for sensitive, robust, noninvasive, and in situ detection of disease onset at low cost. Akin to microrobotic systems, a combination of simple genetic rules, basic logic gates, and complex synthetic bioengineering principles are used to program bacterial vectors as living machines for detecting biomarkers of diseases, some of which cannot be detected with other sensing technologies. Bacterial whole-cell biosensors (BWCBs) can have wide-ranging functions from detection only, to detection and recording, to closed-loop detection-regulated treatment. In this review article, we first summarize the unique benefits of bacteria as living sensors. We then describe the different bacteria-based diagnosis approaches and provide examples of diagnosing various diseases and disorders. We also discuss the use of bacteria as imaging vectors for disease detection and image-guided surgery. We conclude by highlighting current challenges and opportunities for further exploration toward clinical translation of these bacteria-based systems.

  DOI

• Biohybrid robots: recent progress, challenges, and perspectives

  Bioinspiration & Biomimetics · 2022 · 118 citations

  • Artificial Intelligence
  • Computer Science
  • Artificial Intelligence

  The past ten years have seen the rapid expansion of the field of biohybrid robotics. By combining engineered, synthetic components with living biological materials, new robotics solutions have been developed that harness the adaptability of living muscles, the sensitivity of living sensory cells, and even the computational abilities of living neurons. Biohybrid robotics has taken the popular and scientific media by storm with advances in the field, moving biohybrid robotics out of science fiction and into real science and engineering. So how did we get here, and where should the field of biohybrid robotics go next? In this perspective, we first provide the historical context of crucial subareas of biohybrid robotics by reviewing the past 10+ years of advances in microorganism-bots and sperm-bots, cyborgs, and tissue-based robots. We then present critical challenges facing the field and provide our perspectives on the vital future steps toward creating autonomous living machines.

  DOI

• Active Targeting Significantly Outperforms Nanoparticle Size in Facilitating Tumor-Specific Uptake in Orthotopic Pancreatic Cancer

  ACS Applied Materials & Interfaces · 2021 · 35 citations

  • Materials science
  • Nanotechnology
  • Cancer research

  imaging. Size has a secondary effect on uptake for actively targeted nanoparticles in which 26 nm nanoparticles outperform larger 45 and 73 nm nanoparticles. Nanoparticle size had no significant effect on uptake for passively targeted nanoparticles. Results highlight the superiority of active targeting over nanoparticle size for tumor uptake. These findings suggest a framework for optimizing similar nonaggregate nanoparticles for theranostic treatment of recalcitrant cancers.

  DOI

• Robust and Repeatable Biofabrication of Bacteria‐Mediated Drug Delivery Systems: Effect of Conjugation Chemistry, Assembly Process Parameters, and Nanoparticle Size

  Advanced Intelligent Systems · 2021 · 10 citations

  Senior authorCorresponding
  • Nanotechnology
  • Chemistry
  • Biophysics

  Bacteria‐mediated drug delivery systems comprising nanotherapeutics conjugated onto bacteria synergistically augment the efficacy of both therapeutic modalities in cancer therapy. Nanocarriers preserve therapeutics’ bioavailability and reduce systemic toxicity, while bacteria selectively colonize the cancerous tissue, impart intrinsic and immune‐mediated antitumor effects, and propel nanotherapeutics interstitially. The optimal bacteria–nanoparticle (NP) conjugates will carry the maximal NP load with minimal motility speed hindrance for effective interstitial distribution. Furthermore, a well‐defined and repeatable NP attachment density distribution is crucial to determining these biohybrid systems’ efficacious dosage and robust performance. Herein, our nanoscale bacteria‐enabled autonomous delivery system (NanoBEADS) platform is utilized to investigate the effects of assembly process parameters of mixing method, volume, and duration on NP attachment density and repeatability. The effect of linkage chemistry and NP size on NP attachment density, viability, growth rate, and motility of NanoBEADS is also evaluated. It is shown that the linkage chemistry impacts NP attachment density while the self‐assembly process parameters affect the repeatability and, to a lesser extent, attachment density. Lastly, the attachment density affects NanoBEADS’ growth rate and motility in an NP size‐dependent manner. These findings will contribute to the development of scalable and repeatable bacteria–NP biohybrids for applications in drug delivery and beyond. An interactive preprint version of the article can be found here: https://www.authorea.com/doi/full/10.22541/au.163100509.93917936.

  PublisherOA PDFDOI

Recent grants

• RI: Small: Distributed Network of BacteriaBots

  NSF · $425k · 2011–2016

• CAREER: A Biomanufactured Platform for Modulating Immune Cell-Bacteria Interactions in the Tumor Microenvironment

  NSF · $515k · 2015–2023

Frequent coauthors

• Lacey R. McNally

  Oklahoma City University

  26 shared

• Amrinder S. Nain

  Virginia Tech

  25 shared

• Ying Zhan

  Guiyang Medical University

  21 shared

• Metin Sitti

  16 shared

• Ali Sahari

  University Ferhat Abbas of Setif

  15 shared

• Eric J. Leaman

  Virginia Tech

  14 shared

• Mahama A. Traoré

  Washington University in St. Louis

  13 shared

• Abhilash Samykutty

  University of Alabama at Birmingham

  12 shared

Awards & honors

• Virginia Tech Office of the Vice President of Research Schol…
• National Science Foundation CAREER Award (2015)
• Best Poster Award, ASME Global Congress on NanoEngineering f…
• Aline Inc. Best Paper Award, ASME Global Congress on NanoEng…
• Outstanding New Assistant Professor Award, College of Engine…

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