ABSTRACT 
 
 
 

 
Title of Dissertation: FEEDBACK-CONTROLLED 

BIOELECTRONIC HYBRID SYSTEM 
ENABLED BY ELECTROGENETIC CRISPR 

  
 Sally Patricia Wang, Doctor of Philosophy, 

2023 
  
Dissertation directed by: Professor William E. Bentley, Fischell 

Department of Bioengineering 
 
 

With the rise of concepts like the “internet of things” and the advances in electronic 

technologies, our lives have now been occupied with smart devices that easily communicate with 

one another. These devices, however, lack the ability to freely exchange information with the 

world of biology, since electronics and biology possess very different communication modalities. 

Recently, the field of “electrogenetics” was introduced by enlisting redox mediators like hydrogen 

peroxide as a novel signaling medium to facilitate the connection between electronics with biology. 

In this dissertation, we expanded the electrogenetic framework and established a complete network 

of Bio-Nano Things, which collectively allowed automated, algorithm-based feedback control of 

electrogenetic CRISPR activity. First, we engineered the abiotic/biotic interface in order to 

improve information transfer between electronics and biological systems. Inspired by nature, we 

created an “artificial biofilm” that immobilized living cells on the surface of the electrode by 

electrochemically assembling bacteria and thiolated polyethylene glycol (PEG-SH) to form a thin 

film. We then endowed the PEG-SH hydrogel with redox capabilities via conjugation to generate 



  

an interactive material that can autonomously synthesize hydrogen peroxide to initiate 

communication with a bacterial population. Additionally, a polycysteine-tagged Streptococcal 

protein G was introduced for PEG-SH hydrogel surface decoration to enable the recognition of 

cells and other biological molecules. Next, we developed oxyRS-based electrogenetic CRISPR to 

broaden the bandwidth of electrochemical signaling, allowing multiplexed transcriptional 

regulation on various genetic targets. These include two crucial quorum sensing genes that 

controlled the relay of electrochemical signals to a broader yet selective audience of microbial 

populations through quorum sensing communication. We then integrated the engineered interface 

with eCRISPR-mediated transcriptional regulation to present “Biospark”, a full electrogenetic 

system including custom-made hardware and software, for algorithm-governed automated control 

of gene expression. Finally, we demonstrated a network of Bio-Nano Things by connecting the 

Biospark system with another custom bio-electrochemical device and even users to achieve remote 

feedback control of eCRISPR activity and more importantly, multidirectional communication 

between living systems regardless of physical distance. Together, we believe this work represents 

a huge leap toward making “smarter” devices and networks that can seamlessly guide biological 

processes with electronic input and can spawn various applications in the fields of biotechnology. 

 

 

 

  



  

 

 
 
 
 
 
 
 
 
 
 

FEEDBACK-CONTROLLED BIOELECTRONIC HYBRID SYSTEM ENABLED BY 
ELECTROGENETIC CRISPR 

 
 
 

by 
 
 

Sally Patricia Wang 

 
 
 
 
 

Dissertation submitted to the Faculty of the Graduate School of the  
University of Maryland, College Park, in partial fulfillment 

of the requirements for the degree of 
Doctor of Philosophy 

2023 
 
 
 

 
 
 
 
Advisory Committee: 
Professor William E. Bentley, Chair 
Professor Gregg Duncan 
Professor Greg F. Payne 
Professor Nam Sun Wang 
Professor Srinivasa Raghavan, Dean’s Representative 



  

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

© Copyright by 
Sally Patricia Wang 

2023 
 
 
 
 
 
 
 
 
 



 

 

ii 
 

Dedication 

To mom and dad, 你們可以來接我放學回家了<3 



 

 

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Acknowledgments 

First and foremost, thank you Dr. Bentley for all your scientific guidance, warm 

encouragement, and witty comments. Thank you for all the freedom you have given 

me to fail, to learn, to grow as a scientist, and to discover how to be an engineer.  

I’d also like to thank all my committee members: Dr. Duncan, Dr. Payne, Dr. Wang, 

Dr. Karlsson, and Dr. Raghavan for your insights into my dissertation and proposal.  

Thank you to all the past and present Bentley lab members, all of whom I will try my 

best to give my gratitude below: 

To Chen-Yu Tsao- thank you for taking me under your wings and being my mentor in 

both science and life during my Ph.D. journey. Thank you for always responding to my 

SOS messages and never failing to come up with a solution. 

To Jinyang- thank you for introducing me to the world of electrochemistry and 

involving me in a lot of your projects that most of this work stems from. And thank you 

just for being a good friend. 

To my collaborators Chen-Yu Chen and John- thank you for allowing me to work with 

you, for your patience, and for your immense contributions to my dissertation work.  

To Kristina and Eric- thank you for being the best ‘senpai’s in Bentley lab. I am so 

grateful for all the help, guidance, and encouragement you have given me. I will also 

cherish our lively scientific (in most times, non-scientific) discussions and all the good 

times we spent together in lab, in TCM, or in that heated pool at Orlando Hilton 

(#ACSSpring2019). 

To David- You joined at a time when I was constantly doubting myself and felt 

extremely lost. Thank you for instilling a lot of confidence in me. 



 

 

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To Dana- thank you for being my ride-or-die and lab spouse for the past five years. 

Without you, I could probably be a hundred times more productive in lab but will also 

not gain all the crucial knowledge on trash TV shows and F1 racing. I will miss our 

Britney Fridays greatly.  

To Rahma, Kayla, Monica, Nick, Briahnna, and Ben- thank you for joining to do cool 

science with us! Shoutout to Rahma who helped me a lot with another project that did 

not make it into this dissertation.  

To Futoon- thank you for trusting me enough to become my mentee, a member of our 

F1/baking/HBO shows gang and most importantly, a great friend.  

To Kimberly- what are the odds to meet someone randomly in class (and lab) and turns 

out you both went to the same concert in Taiwan back in 2014? Thank you for all the 

times we got quality boba and tacos together. 

And thank you to all the other great people I met in this program. Special shout out to 

Divya who “made” me go to the gym and be healthy for a whole semester. 

To all friends I made in Maryland, especially my flatmates in Mazza, the “Maryland 

girl squad”, the “Cheapers”, my baseball fan buddies in Miner St., and Janus- we all 

came to this place knowing no one, but you guys have become my family here. Thank 

you for your support, encouragements, laughter and all the good times.  

To all my friends and family in Taiwan- knowing that y’all have my back gave me the 

courage to pursue this degree halfway across the world. Thank you. 

Finally, to the three people who also resides in Hotel 72-1 3F-1- I am extremely grateful 

to be raised by two amazing scientists and proud to be the 3rd doctor in this household 

(it’s your turn now bro?). Thank you for everything. I love you. 



 

 

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Table of Contents 

Dedication ..................................................................................................................... ii 
Acknowledgments ........................................................................................................ iii 
Table of Contents .......................................................................................................... v 
List of Tables ............................................................................................................. viii 
List of Figures .............................................................................................................. ix 
Chapter 1. Connecting the disparate worlds of biology and electronics ....................... 1 

1.1 Introduction ......................................................................................................... 1 
1.2 Biochemical Molecular Communication ............................................................ 2 

1.2.1 Direct Electron Transfer .............................................................................. 2 
1.2.2 Optogenetics ................................................................................................ 4 
1.2.3 Redox electrochemistry ............................................................................... 6 

1.3 Physical Electromagnetic Nanocommunication ............................................... 11 
1.4 Conclusion ........................................................................................................ 12 

Chapter 2. Quorum Sensing Communication: Molecularly Connecting Cells, Their 
Neighbors, and Even Devices ..................................................................................... 13 

2.1 Quorum Sensing: History and Background ...................................................... 13 
2.2 Quorum Sensing Systems and Networks .......................................................... 13 

2.2.1 AI-1, LuxI/R System .................................................................................. 14 
2.2.2 AI-2, LuxS System..................................................................................... 15 
2.2.3 Global Quorum Sensing Regulons ............................................................. 19 

2.3 Manipulation of Quorum Sensing Systems: Endowing Cells with New Function
................................................................................................................................. 20 

2.3.1 Biosensing and programming population-wide behavior .......................... 21 
2.3.2 Therapeutics: QS-regulated sense-and-kill probiotics ............................... 23 
2.3.3 Therapeutics: QS-regulated in situ production and delivery ..................... 24 
2.3.4 Biosynthesis ............................................................................................... 25 

2.4 Manipulation of QS Systems: Opening Lines of Communication ................... 29 
2.4.1 Microbial Consortium: A Prospective Platform ........................................ 29 
2.4.2 Engineering QS-based communication ...................................................... 30 
2.4.3 Engineering a microbial consortium: challenges. ...................................... 33 

2.5 Interkingdom Consortia: Engineering Communication Networks ................... 38 
2.5.1 Interkingdom and beyond. ......................................................................... 40 

2.6 Conclusion and Future Outlook ........................................................................ 44 
Chapter 3. Engineering communication between the biotic and abiotic realms ......... 45 

3.1 Chapter Overview ............................................................................................. 45 
3.2 Motivation and Background ............................................................................. 45 
3.3 Results ............................................................................................................... 47 

3.3.1 Electrodeposition of PEG-SH and living cells. .......................................... 47 



 

 

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3.3.2 Controllable fabrication of “artificial biofilm.” ......................................... 50 
3.3.3 Catechol conjugation to PEG-SH film. ...................................................... 52 
3.3.4 Catechol-PEG-SH film promotes communication through ROS signaling.
............................................................................................................................. 54 
3.3.5 Interactive communication between catechol-PEG-SH film and E. coli. .. 60 

3.4 Discussion and Conclusion ............................................................................... 62 
3.5 Methods............................................................................................................. 63 

3.5.1 Materials .................................................................................................... 63 
3.5.2 Electrode chip fabrication .......................................................................... 64 
3.5.3 Instrumentation .......................................................................................... 64 
3.5.4 Electrodeposition of PEG-SH .................................................................... 65 
3.5.5 Co-deposition of MDA-MB-231 Cells. ..................................................... 65 
3.5.6 Electrodeposition of E. coli and PEG-SH. ................................................. 66 
3.5.7 Mass Spectroscopy to characterize catechol-PEG-SH conjugation. .......... 66 
3.5.8 Redox-responsive E. coli reporter cells and FACS measurements ............ 67 

Chapter 4. Strategies to Facilitate Expression of 5xCys-Tagged Proteins for 
Electrobiofabrication ................................................................................................... 69 

4.1 Chapter Overview ............................................................................................. 69 
4.2 Introduction ....................................................................................................... 70 
4.3 Results ............................................................................................................... 75 

4.3.1 Polycysteine (5xCys) Tag Allows Protein Biofabrication on Thiolated 
Surfaces to Create Biohybrid Devices. ............................................................... 75 
4.3.2 Cellular Induction Strategies to Improve 5xCys-Tag Recombinant 
Expression. .......................................................................................................... 80 
4.3.3 QS-Mediated Autoinduction Reduces Inclusion Body Formation ............ 82 
4.3.4 Deletion of oxyRS Enhances 5xCys-Tagged Protein Production .............. 85 

4.4 Discussion ......................................................................................................... 89 
4.5 Materials and Methods ...................................................................................... 93 

4.5.1 Bacterial Strains and Growth Media .......................................................... 93 
4.5.2 Plasmid Construction ................................................................................. 95 
4.5.3 Chromosomal Deletion of oxyRS, lsrFG ................................................... 95 
4.5.4 Recombinant 5xCys-Tagged Protein Expression and Purification ............ 96 
4.5.5 Western Blot .............................................................................................. 97 
4.5.6 Electroassembly of PEG-SH, Protein G-5xCys, and Antibody Interfaces 98 

Chapter 5. Genetically Focused, Feedback-Controlled Electrogenetic Guidance of 
Microbial Communities ............................................................................................ 100 

5.1 Introduction ..................................................................................................... 100 
5.2 Results ............................................................................................................. 104 

5.2.1 ITO-based electrochemical biohybrid device .......................................... 104 
5.2.2 oxyRS-based electrogenetics CRISPR activation ..................................... 106 



 

 

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5.2.3 eCRISPR inhibition and multiplexed control of QS to enable ‘multilingual’ 
communication. ................................................................................................. 113 
5.2.4 Automated dynamic control of eCRISPRa activity ................................. 124 
5.2.5 Network integration for remote, feedback control ................................... 136 

5.3 Discussion and Conclusion ............................................................................. 142 
5.4 Methods........................................................................................................... 143 

5.4.1 Chemicals ................................................................................................. 143 
5.4.3 Plasmid construction ................................................................................ 144 
5.4.4 Fabrication of the biohybrid electronic device ........................................ 151 
5.4.5 Peroxide Generation and Quantification .................................................. 151 
5.4.6 General and coculture electroinduction set-up ........................................ 152 
5.4.7 AI-1 quantification ................................................................................... 153 
5.4.8 RT-qPCR ................................................................................................. 153 
5.4.9 AI-2 activity assay ................................................................................... 154 
5.4.10 Custom-built bioelectronic system (Biospark) setup ............................. 155 
5.4.11 Algorithm for “smart” control of gene expression ................................ 157 
5.4.12 Electrodeposition of HRP/gelatin hydrogel and electrochemical detection 
of H2O2. ............................................................................................................. 157 
5.4.13 Custom algorithm for controlling the remote ‘actuation checkpoint’. .. 158 

Chapter 6. Conclusion and Future Outlooks ............................................................. 160 
Bibliography ............................................................................................................. 166 
 



 

 

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List of Tables 

Table 3.1 E. coli strain and plasmid used in this chapter. ........................................... 68 
Table 4.1 Bacteria strains and plasmids used in this chapter. ..................................... 93 
Table 4.2 Primers used in this chapter. ....................................................................... 94 
Table 5.1 Strains and plasmids used in this chapter. ................................................ 147 
Table 5.2 Sequences of relevant genetic parts. ......................................................... 148 
Table 5.3 Primers used in this chapter. ..................................................................... 150 
 



 

 

ix 
 

List of Figures 

Figure 1.1 Molecular mechanisms of the OxyR transcriptional activator. ................... 9 
Figure 2.1 Canonical quorum sensing (QS) systems. ................................................. 18 
Figure 2.2 Quorum sensing (QS)-enabled cell functions. ........................................... 27 
Figure 2.3 Applications and challenges of quorum sensing (QS)-based synthetic 
consortia. ..................................................................................................................... 36 
Figure 2.4 QS-mediated communication to interkingdom and beyond. ..................... 43 
Figure 3.1 PEG-SH hydrogel and “artificial biofilm” deposition. .............................. 49 
Figure 3.2 Co-deposited cells in PEG-SH films retain high viability. ........................ 49 
Figure 3.3 “Artificial biofilm” can be controllably electrodeposited. ........................ 51 
Figure 3.4 Catechol conjugation to PEG-SH hydrogel. .............................................. 53 
Figure 3.5 The CatRed film generates H2O2 in the presence of O2. ............................. 55 
Figure 3.6 Interactive communication between redox-active film and engineered E. 
coli reporter cells. ........................................................................................................ 58 
Figure 3.7 Dose-dependence and time-dependence of gene expression in response to 
H2O2. ........................................................................................................................... 59 
Figure 4.1 Schematic of the E. coli quorum sensing (Lsr) system. ............................ 74 
Figure 4.2 Schematic of the engineered 5xCys-tagged protein. ................................. 77 
Figure 4.3 Demonstration of biodevice assemblies. ................................................... 78 
Figure 4.4 5xCys tag promotes inclusion body formation. ......................................... 81 
Figure 4.5 Protein G-5xCys production with conventional IPTG induction and QS-
mediated autoinduction. .............................................................................................. 84 
Figure 4.6 Growth of different cell cultures. .............................................................. 87 
Figure 4.7 Effect of oxyRS deletion to protein G-5xCys expression. ......................... 88 
Figure 5.1 Information flow within the Bio-Nano Things Network. ........................ 102 
Figure 5.2 ITO-based electrochemical biohybrid device. ......................................... 105 
Figure 5.3 Demonstration of a tunable eCRISPRa on an “artificial biofilm.” ......... 109 
Figure 5.4 H2O2-inducible CRISPR activation of GFPmut2. ................................... 111 
Figure 5.5 H2O2-inducible CRISPR activation of lasI. ............................................. 112 
Figure 5.6 eCRISPR inhibition of a native QS signal and multiplexed control of QS 
communication. ......................................................................................................... 119 
Figure 5.7 H2O2-inducible luxS CRISPRi and multiplexed control of QS signaling.
................................................................................................................................... 121 
Figure 5.8 oxyS CRISPRi to selectively filter biological noise and enhance oxyS 
promoter activity. ...................................................................................................... 123 
Figure 5.9 H2O2-induced gene expression is temporal and can be dynamically 
controlled. ................................................................................................................. 127 
Figure 5.10 Autonomous dynamic control of gene expression via electrogenetic 
CRISPR. .................................................................................................................... 129 



 

 

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Figure 5.11 Performance in fluorescence measurements of the optical module from 
our custom Biospark System. ................................................................................... 131 
Figure 5.12 Development of a custom algorithm to achieve dynamic control of gene 
expression. ................................................................................................................ 132 
Figure 5.13 Automated control of electro-induced gene expression. ....................... 134 
Figure 5.14 Network integration for establishing a Bio-Nano Things framework to 
enable remote feedback control of eCRISPR activity. ............................................. 138 
Figure 5.15 Bio-electrochemical platform serving as an actuation checkpoint in the 
smart feedback-control system. ................................................................................ 140 
 
 



 

 

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Chapter 1. Connecting the disparate worlds of biology and 

electronics 
iThis chapter is partially adapted, with permission, from the book chapter: Wang, S.; Payne, 

G. F.; Bentley, W. E. Repurposing E. coli by Engineering Quorum Sensing and Redox Genetic 

Circuits. Gene Expression and Control, IntechOpen. 2019 

1.1 Introduction 

Recent feats in engineering communication between electronic devices and 

sensors provide us with a plethora of new “smart” technologies that greatly benefit our 

daily lives. For example, Internet of Things (IoT), an emerging paradigm that connects 

electronic devices and sensors through the internet, has revolutionized our current 

lifestyle. Dazzling technologies that used to only exist in science fiction films like smart 

cities, smart homes, pollution and energy consumption control, agriculture automation, 

and smart transportation are now a reality due to IoT (1). Although these achievements 

make our lives immensely easier, these networks still struggle to connect humans/living 

organisms or artificial nano-biological functional devices (e.g., engineered bacteria, 

human cells, nanobiosensors) to the vast IoT due to disparate modalities in 

communication between the electronics and biological systems. To establish such a 

heterogeneous and collaborative network, new communication conduits must be 

created since conventional electromagnetic techniques for the electronics are either not 

feasible for the size- and energy-constrained biological systems or not performing well 

in vivo due to physical constraints (2-4). Molecular communication, on the other hand, 

is one of the promising techniques to enable biology-electronics communication, as it 

is already utilized by natural biological systems in an incredibly energy-efficient and 



 

 

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robust manner (5). In this chapter, we summarize the recent approaches that aim to 

bridge the communication gap between electronics and biology, from rewiring native 

molecular/biochemical communication to several novel physical methods based on 

electromagnetic waves, in hopes to achieve electrically probing, interrogation, or 

control of biological systems. 

1.2 Biochemical Molecular Communication 

1.2.1 Direct Electron Transfer 

While most technological devices rely on electron flow, nature designed the cell 

membrane to be an insulator that restricts the flow of charged species. This has made 

it significantly challenging to introduce a biocompatible pathway for transferring 

electrons across the membrane without disrupting the cell. Remarkably, a limited set 

of bacterial species, named exoelectrogens (6), are discovered to possess the ability to 

directly transfer electrons to electrodes. These include Shewanella putrefaciens (7), 

Geobacter sulfurreducens (8), Rhodoferax ferrireducens (9), or even an evolved 

consortium of facultative anaerobes (10) (consisting of Alcaligenes faecalis, 

Enterococcus gallinarum, Pseudomonas and more). These dissimilatory metal-

reducing bacteria have evolved mechanisms to use electrodes as electron acceptors and 

for anaerobic respiration (11, 12). One of the best-understood electron transfer 

pathways belongs to that of Shewanella oneidensis MR-1 and is comprised of c-type 

cytochromes that are responsible for shuttling electrons from cytoplasmic and inner 

membrane oxidizing enzymes toward the cell surface during anaerobic respiration. 

Previous studies suggest that this pathway consists of an inner membrane tetraheme 



 

 

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cytochrome CymA, a periplasmic decaheme cytochrome MtrA, outer membrane 

decaheme cytochromes OmcA and MtrC, and an outer membrane β-barrel protein 

MtrB (13-17). Through a series of intermolecular electron transfer events from quinol 

to either MtrC and/or OmcA, this pathway is proposed to move electrons from the 

intracellular quinol pool to extracellular metal oxides, such as Fe2O3 (s). One major and 

direct application of these electron-generating species is, conceivably, generating 

electricity. They serve as the workhorses in many microbial fuel cells (MFC), as 

reviewed in (18, 19), providing alternate solutions to energy production and waste 

treatment to address the current global energy crisis. As the field of synthetic biology 

matures, it continues to provide more sophisticated tools to engineer living cells as a 

material for advanced biological systems and applications. Researchers are now able 

to rewire native extracellular electron transfer (EET) pathways to generate current as 

an output to be directly integrated with electronic systems, creating bioelectronic living 

sensors (20-22) or controlling microbial electrosynthesis and electrofermentation (23). 

Conversely, these pathways can be modified and ported to other chassis endowing non-

exoelectrogens with new functions related to electron transfer. For example, a portion 

of the extracellular electron transfer chain of S. oneidensis MR-1 was reconstituted into 

the model microbe Escherichia coli to create a conduit for electronic communication 

from living cells to inorganic materials (24). Living conductive materials can also be 

engineered by employing native and or rewired EET pathways, as reviewed by Bird et 

al. (25). 

Intracellular electron transfer pathways, contrary to the extracellular pathways, 

are common and have vital importance in biological systems. Essential biological 



 

 

4 
 

functions such as cellular respiration (26), DNA repair (27), and activation of sensory 

proteins (28). Through synthetic biology, direct and dynamic control over these 

electron transfer pathways has led to progress in metabolic engineering for chemical 

synthesis (29, 30). Recently, dynamic control over energy flow in metabolism was 

enabled by the creation of electron ferredoxin logic gates that utilize various inputs to 

control energy flow through a synthetic electron transfer pathway required for bacterial 

growth (31). Coupling this feature with the reconstituted S. oneidensis electron transfer 

pathway and endogenous sulfur assimilation proteins, Atkinson et al. (32) achieved 

real-time environmental biosensing of chemicals with an E. coli biosensor that 

generates electron flow to an electrode upon detecting thiosulfate. These living 

electronic sensors provide a platform that can be expanded for continuous 

environmental sensing and potential integration with IoT to allow alerts and smart 

pollution control. 

1.2.2 Optogenetics 

Light represents an alternative modality to interface biological systems with 

electronic networks since light-sensitive proteins and bioluminescent/fluorescent 

proteins are now routinely used in many biotechnological systems. Optogenetics 

combines optical and genetic techniques to design and apply light-sensitive proteins in 

order to control cellular processes within living organisms. Often plant-derived, light 

sensitive proteins such as channelrhodopsins, halorhodopsins, and other LOV domain 

proteins can also be found in unicellular organisms (e.g., bacteria and archaea) or 

higher animals (33). Upon illumination with a specific wavelength, the light-sensing 

domains undergo a conformational change that leads to association/dissociation with 



 

 

5 
 

an interaction partner or partial folding/unfolding of the protein structure, which in turn 

controls downstream biological processes. Optogenetic control systems resemble 

electronics in several ways, for example, it is highly spatiotemporal and allows for often 

reversible on/off manipulation of biological processes (34, 35). Light is also easily 

controllable and programmable through microchip controllers and optical filters, 

allowing direct integration with existing paradigms for electronic devices (36, 37). 

Recent endeavors demonstrated the translation of electronic commands into biological 

optogenetic responses through engineering far red/green light-triggered engineered cell 

systems (38, 39). The engineered optogenetically-controlled cells can produce a variant 

of human glucagon-like peptide 1 (shGLP-1) or mouse insulin for diabetes treatment 

when given a wireless electromagnetic signal that encoded the details (e.g., duration, 

brightness) of illumination.  

While the majority of applications were originally developed in eukaryotes, 

optogenetics increasingly finds its way into prokaryotic (or yeast) systems to facilitate 

drug production/delivery, biosensing, and biomanufacturing (40). When combined 

with electronics, real-time and remote feedback control of cell cultures can be achieved 

through optogenetics regulation, as reviewed by Liu et al. (41). These hardware-

integrated platforms enable feedback control over bacterial growth rate (42, 43), 

consortia composition (44), unfolded protein response in yeast (45), and gene 

expression in mammalian cells (46).  

In addition to optogenetics, which uses light as an input, light can also be an 

output signal produced by biological systems to be easily fed into electronic devices 

via existing hardware like phototransistors or photomultiplier tubes. Following the 



 

 

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initial discovery of green fluorescent protein (GFP) in jellyfish Aequorea victoria, GFP 

has been widely used as a reporter for monitoring dynamic processes in biological 

systems (47); and likewise for bioluminescent proteins LuxCDABE (48). As a proof of 

concept, Mimee et al. (49) presented a luminescence biosensor for heme that is housed 

in an ingestible micro-bio-electronic device (IMBED) and demonstrated accurate 

diagnosis of gastrointestinal bleeding in swine. In Chapter 5, we also presented a 

bioelectronic system that employs green fluorescence as the representation of gene 

expression for automated feedback control of CRISPR activity.  

1.2.3 Redox electrochemistry  

As discussed in Section 1.2.1, while there are no freely moving electrons exist 

within biological systems, native electron transport chains transfer electrons with the 

help of redox molecular mediators (e.g., NADPH) and metalloproteins (e.g., iron-sulfur 

cluster containing proteins) (50). The dual nature of redox reactions combines the 

unique characteristics of both biological and electronic networks (51),  therefore 

enabling electron-based communication that is transduced between both domains 

through ‘‘redox channels’’. As electrons pass through the redox molecules, their 

oxidative states and unique structures change accordingly, thus determining their 

interactions with receptors and sensor proteins. That is, we can electronically interpret 

or actuate the structural changes of these molecules through standard electrochemical 

techniques and subsequently initiate or diminish molecular communication. We argue 

that by harnessing native redox mechanisms, many approaches can be spawned to allow 

the control of biorecognition and associated genetic machinery (52) via electronic 

signals.  



 

 

7 
 

Owing to the dual nature of redox communication, researchers have engineered 

ways to exploit redox reactions for bridging electronic input to biological systems and 

translating biological output to electronics. Practicable methodologies that enable bio-

to-electronics connectivity, as extensively reviewed by VanArsdale et al. (53), include 

clever ways to electrochemically detect many native redox molecules produced and 

generated by cells (including exoelectrogens), probe the state of complex materials and 

biological systems, and decode biological reporter gene activity. In this section, we 

focus on methods based on native redox signaling that are developed to transform 

electronic input into a signal recognizable by biological systems, and in turn, achieve 

electrogenetic control (54). First, two vital oxidative stress protein sensors, SoxR and 

OxyR, and their corresponding signaling pathway will be introduced. 

 1.2.3.1 SoxR: [Fe-S]-cluster based, superoxide/nitric oxide stress sensor. 

The E. coli soxRS system enhances the production of ~45 proteins in response 

to superoxide exposure, including those in detoxification (sodA, manganese superoxide 

dismutase), DNA repair (nfo, endonuclease IV), maintaining cellular reducing power 

(zwf, glucose-6-phosphate dehydrogenase) and central metabolism (fumC, superoxide-

stable fumarase C and acnA, aconitase A). The E. coli SoxR protein exists as a 

homodimer that contains one [2Fe–2S] cluster per subunit. During aerobic growth, up 

to 95% of SoxR is held in the reduced ([2Fe–2S]1+) state. Upon sensing conditions that 

promote the production of superoxide, SoxR is oxidized to ([2Fe–2S]2+) clusters and it 

leaves the soxR/S promoter region (PsoxRS) to activate the expression of transcription 

factor SoxS. SoxS, unlike SoxR, when bound to PsoxRS initiates the expression of the 

proteins listed above located downstream of the promoter (55).   



 

 

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1.2.3.2 OxyR: thiol-based, peroxide stress sensor. 

OxyR, the hydrogen peroxide sensor, and transcription regulator, belongs to the 

cohort for combating oxidative stress and is perhaps the model for bacterial redox 

sensors considering its widespread occurrence in Gram-positive and Gram-negative 

bacteria (52). Although OxyR acts as a repressor in some bacteria, in E. coli and most 

species it is an activator that recruits RNA polymerase (56). Consisting of an N-

terminal DNA-binding domain and a C-terminal regulatory domain, OxyR forms an 

intramolecular disulfide bond between residues C199 and C208 in the regulatory 

domain that introduces large structural changes upon binding hydrogen peroxide 

(henceforth, peroxide or H2O2) (57, 58) (Figure 1). The structural changes within the 

regulatory domain of each monomer in turn induces the overall structural change of the 

tetramer, resulting in the occupation of four consecutive major grooves of DNA (59, 

60). Once the oxidized OxyR binds to the promoter region of oxyRS, it then recruits 

RNA polymerase and activates the transcription of the downstream gene oxyS. 

Remarkably, OxyS is a small regulatory RNA that mediates the activation or repression 

of several crucial transcription factors including fhlA (61), rpoS (62), and nusG (63). In 

addition to oxyS, OxyR globally regulates the activation or repression of over 40 genes, 

including several detoxifying enzymes such as hydroperoxidase I (katG) and 

alkylhydroperoxide reductase (ahpCF) (56). 



 

 

9 
 

 

 

Figure 1.1 Molecular mechanisms of the OxyR transcriptional activator. 

Transcriptional activator OxyR in E. coli contains two conserved cysteine residues, 

Cys199 and Cys208, in the C-terminus regulatory domain. Once exposed to hydrogen 

peroxide, Cys199 is oxidized to sulfenic acid, which can then react with Cys208 to 

form an intramolecular disulfide bond. This disulfide bond formation within the 

monomer results in a structural change in the whole OxyR tetramer, which allows more 

occupation and higher affinity to the oxyRS promoter region. Once the oxidized OxyR 

is bound, it will recruit RNA polymerase to initiate the transcription of the downstream 

small regulatory RNA oxyS. 

  



 

 

10 
 

1.2.3.3 Development of Electrogenetics 

 We believed that the first intended attempt at controlling gene expression 

through electronic means, while being indirect, belongs to this synthetic, mammalian 

electro-genetic transcription circuit (64). By linking the electrochemical oxidation of 

ethanol to acetaldehyde, an applied voltage was shown to trigger the acetaldehyde-

inducible gene expression circuit. A more direct methodology recently appeared in 

which the engineered genetic circuit responds directly to the electrode-oxidized signal 

molecule, opening an entirely new modality for bioelectronic control (65). Using 

pyocyanin as the redox mediator, it is responsible for translating electrical signals into 

a biochemical redox signal that, in turn, can be sensed by SoxR and initiate the 

expression from the soxS promoter. Strikingly, gene expression controlled by this 

device is functionally reversible on relatively short time scales (30–45 min). It was also 

found to be quite robust, as oscillatory behaviors were shown over many cycles. 

Accordingly, electrogenetic systems will require that an entirely new ‘suite’ of genetic 

elements be developed that respond to and coordinate these environmental cues. In (65), 

the expression of AHL-synthesizing enzyme LasI was electronically actuated, resulting 

in electronic control of QS behavior of nearby cells. Analogously, motility regulator 

CheZ was also electronically stimulated demonstrating the electronic initiation of cell 

motility. In (66), Bhokisham et al. coupled soxRS-based electrogenetics with CRISPR 

transcriptional regulation and enabled signal amplification, noise attenuation, and 

spatiotemporal information processing. Furthermore, Lawrence et al. (67) redesigned 

the PsoxS promoter and demonstrated electrochemical activation of gene expression 



 

 

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under aerobic conditions using a modular bio-electrochemical device. These studies in 

cooperation continue to improve the ever-developing electrogenetic systems. 

 Recently, Terrell et al. employed H2O2 signaling and oxyRS regulon to create 

an electronically controlled biological local area network (BioLAN) (68). Peroxide, as 

the redox signal, can be generated directly from an electrode and without mediators to 

carry information to bacteria that are attached to the electrode by surface engineering. 

The initiated genetic response, when coupled with a second, recognition-based redox 

event, propagates and validates information flow between the electronic system and a 

consortium of engineered microbes. Jointly, BioLAN can reliably facilitate on-demand 

bioelectronic communication and concurrently perform programmed tasks. In 

Chapters 3 and 5, we also demonstrated novel approaches to allow or expand 

electronic-to-bio communication based on H2O2 signaling and oxyRS regulon. 

1.3 Physical Electromagnetic Nanocommunication 

 Other non-MC (molecular communication) nanocommunication modalities 

were also being proposed by researchers to compensate for several drawbacks of 

molecular communication such as low communication rate, non-linearity, and 

molecular interference (69). Many of the novel approaches, including 

nanocommunication enabled by THz-band electromagnetic waves, acoustic waves, and 

Forster Resonance Energy Transfer (FRET) were reviewed by (5). Improvements that 

are intentionally made for bridging biological systems in traditional electromagnetic 

communication are also paving ways for highly energy-efficient and secured 

transmission of information. For example, human body communication (HBC) takes 

advantage of the high-water content of human bodies and uses it as a medium for low-



 

 

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loss transmission, enabling energy-efficient communication means for wearable 

technologies (70). To enhance transmission security, Das et al. (2) presented “Electro-

Quasistatic Human Body Communication” (EQS-HBC), a method for localizing 

signals within the body using low-frequency carrier-less (broadband) transmission. 

Other various forms of HBC were introduced in (71). As wearable devices slowly 

become a necessity in our daily lives, we imagine more advancements in this field will 

continue to emerge. 

1.4 Conclusion 

In this chapter, we introduced and discussed a variety of approaches for 

connecting the seemingly disparate worlds of electronics and biology. This conduit is 

vital to building a complete Bio-Nano Things framework that, we believe, can spawn 

many revolutionary applications in the medical, environmental, and biomanufacturing 

fields. As a rising and interdisciplinary research area, we envision many novel and 

creative ways will soon join the growing repertoire described here to facilitate the 

development of new technologies that can greatly benefit our lives. 



 

 

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Chapter 2.  Quorum Sensing Communication: Molecularly 

Connecting Cells, Their Neighbors, and Even Devices 
iThis chapter is adapted, with permission, from the publication: Wang, S.; Payne, G. F.; 

Bentley, W. E. Quorum Sensing Communication: Molecularly Connecting Cell, Their 

Neighbors, and Even Devices. Annu. Rev. Chem. Biomol. Eng. 2020. 11:11.1–11.22 

2.1 Quorum Sensing: History and Background 

Although they are considered primitive, microbes have been found to be social 

creatures, just like humans. Whereas we use words and body gestures, gregarious 

bacteria converse through secretion and perception of small signal molecules. 

Greenberg and colleagues termed this phenomenon quorum sensing (QS). Hints of 

microbial social interaction through extracellular molecules had been found in early 

studies in which scientists discovered that both (a) luminescence in two species of 

marine bacteria (72, 73) and (b) genetic competence in Streptococcus pneumoniae (74) 

required production of hormone-like small molecules. The big breakthrough in QS 

studies came with two landmark discoveries: One identified the genes that control (luxI, 

luxR) and produce (lux) luminescence in Vibrio fischeri (75, 76), and the other unveiled 

the QS-signal molecule to be N-(3-oxohexanoyl)-l-homoserine lactone (3OC6-HSL) 

(77). Soon after, the dawn of genomic profiling allowed the discovery of an explosion 

of systems that are homologous to the lux QS system in different species (78, 79). Since 

then, many and widely disparate scientific efforts have been dedicated to understanding 

how bacteria communicate. 

2.2 Quorum Sensing Systems and Networks 



 

 

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In general, QS bacteria produce and release chemical signal molecules termed 

autoinducers (AIs), the external concentrations of which increase as a function of 

increasing cell-population density within a particular niche. Once the bacteria detect 

that AIs have reached a threshold concentration, they will respond by altering their 

gene expression and behavior. AIs, playing a vital role in QS, are the cues by which 

QS bacteria communicate and synchronize particular behaviors on a population-wide 

scale, thus gaining the ability to function as multicellular ororganisms. In this section, 

two well-characterized QS systems and their signals, receptors, mechanisms of signal 

transduction, and target outputs are reviewed. 

2.2.1 AI-1, LuxI/R System 

For most QS systems in Gram-negative bacteria, the LuxI/R system of V. 

fischeri (Figure 2.1a) serves as an underlying paradigm (80). In this system, proteins 

LuxI and LuxR control expression of the luciferase operon (luxICDABE) required for 

luminescence. luxI encodes for an AI synthase that produces the acyl-homoserine 

lactone (AHL) autoinducer N-3-oxododecanoyl HSL (3OC6-HSL). Following its 

production, the AHL will accumulate - its concentration increasing as the cell density 

increases. Upon reaching a critical level, LuxR, the cytoplasmic AI receptor/DNA-

binding transcriptional activator, will bind to AHL, and this complex will initiate the 

expression of the luciferase operon. This actuates a positive feedback loop, as luxI is 

encoded in the operon, and soon the environment is flooded with AHL, which, in turn, 

switches all bacteria nearby to the QS-active, light-shedding mode (81). All other 

LuxI/R systems share a general mechanism: LuxI homologs synthesize AHL as AIs, 

and LuxR homologs recognize, specifically, their cognate AHL. This specificity makes 



 

 

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LuxI/R QS systems ideal for enabling intraspecies communication. In Gram-positive 

bacteria, such as the aforementioned S. pneumoniae, the modified oligopeptides are 

used as AIs, and the two-component-type membrane-bound sensor histidine kinases 

are used as receptors. Like the Gram-negative LuxI/R system, each Gram-positive 

bacterium uses a signal different from that used by other bacteria, and the cognate 

receptors are exquisitely sensitive to the signals’ structures. Because AHLs from 

different species have been characterized extensively, they can be used for synthetic 

cell–cell communication. In addition, components of the LuxI/R system can be used 

as modules within heterologous gene circuits, as they are often ported to non-native 

strains. Particularly important, the broad class of signals comprising the AHLs freely 

diffuse through Gram-negative membranes so that active signal transduction motifs are 

not needed for synthetic communications systems. Also, bacteria rarely rely on one 

exclusive LuxI/R QS system but often employ multiple signaling systems in parallel. 

This biochemical diversity of AHL signaling pathways can be leveraged for circuits 

controlled by combinations of unique signals (82). Together, these characteristics make 

the LuxI/R system particularly attractive to fields like synthetic biology, as they can be 

translated to function in engineered systems and environments. 

2.2.2 AI-2, LuxS System 

The LuxS/AI-2 system (Figure 2.1b) was first observed in yet another 

bioluminescent marine bacterium, Vibrio harveyi, which can communicate via multiple 

QS signals, including those secreted by other species (83). The QS signal AI-2, which 

is actually a family of cyclic furanones (84), serves as the “bacterial Esperanto” (85), 

as it can be generated by more than 80 species of both Gram-negative and Gram-



 

 

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positive bacteria (81, 86). During central metabolism, the reactive methyl moieties of 

S-adenosylmethionine are transferred to various substrates, yielding by-product S-

adenosylhomocysteine (SAH). LuxS-containing bacteria have two enzymes (Pfs and 

LuxS) acting sequentially to convert SAH to adenine, homocysteine, and the signal 

molecule, 4,5-dihydroxy-2,3-pentanedione (DPD). This, in turn, is exported and 

cyclized to AI-2, enabling both the synthesis of AI-2 and the detoxification of the toxic 

by-product SAH (87).  

Remarkably, AI-2 is found to be actively transported into the cell by the luxS-

regulated (Lsr) transporter in Enterobacteriaceae and several other taxa (88, 89). In 

Escherichia coli, the AI is imported by the Lsr transporter (LsrACDB) and in turn, is 

phosphorylated by LsrK to AI-2P. As AI-2P binds LsrR, it relieves the repression of 

LsrR on the lsr genes and accelerates AI-2 intake. Interestingly, through modeling and 

experimental studies, alternative, less prominent routes of AI-2 synthesis (90) and 

uptake (91, 92) have been postulated. Also interestingly, LsrACDB is also regulated 

via glucose and cyclic AMP/cyclic AMP receptor protein, as well as other common 

carbon sources (91, 93). Based on these discoveries, the LuxS/AI-2 system has two 

noteworthy features: (a) the desynchronization of the LuxS/AI-2 QS system caused by 

AI-2 intake via the lsr operon, which allows the display of bimodal Lsr signaling and 

fractional induction (94), and (b) the ability to endow cell population–dependent 

behavior while interacting with central metabolism and regulating cell fitness through 

the intracellular activated methyl cycle and intervention of the aforementioned S-

adenosylmethionine metabolism pathway. Moreover, in Figure 2.1b, we also show that 

the AI-2 uptake mechanism (Lsr) is phylogenetically dispersed among Gram negatives 



 

 

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and Gram positives (89). That is, although bacteria possessing the AI-2 signal 

transduction mechanisms are believed to have the ability to sense the general bacterial 

population density in a multispecies consortium, this diversity suggests the ability to 

self-report. The prevalence of LuxS among bacteria (and AI-2 in proximal 

microenvironments) has fueled speculation about the role of AI-2 as a QS-signal 

molecule, yet its diverse uptake and signal translocation mechanisms enable species-

specific ability to respond to AI-2. Interestingly, some question whether AI-2 and the 

LuxS/AI-2 QS system can be defined as a true interspecies QS-signaling pathway, or 

in some cases a non-QS-related cue (95), but this system possesses many attributes and 

components that can be rewired and incorporated into engineered systems. 

  



 

 

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Figure 2.1 Canonical quorum sensing (QS) systems. 

(a) QS in Vibrio fischeri. Pink pentagons denote the acyl-homoserine lactone (AHL) 

autoinducers (AIs) that LuxI produces (3OC6-homoserine lactone). Transcriptional 

regulator LuxR modulates the expression of AHL synthase, LuxI, and the lux operon, 

leading to luciferase-mediated light emission. Homologous lux-like systems are 

described in Reference 7. (b) Regulatory mechanisms of the LuxS/AI-2 circuit in 

Escherichia coli. AI-2 (green pentagons) is imported into the cell by the Lsr transporter 

(LsrACDB) and is then phosphorylated by LsrK. When AI-2P binds LsrR and releases 

LsrR from the promoter region (thus modulating Lsr gene expression), AI-2 uptake is 

increased. LuxS produces DPD, the precursor to AI-2. The AI is exported by YdgG 

(TqsA). Lsr homologs and their organizational structures are found in both Gram-

positive and Gram-negative bacteria (89).  



 

 

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2.2.3 Global Quorum Sensing Regulons 

The prevalence of genomic fingerprinting has revealed that QS can control gene 

expression in a global manner. QS mutants of S. pneumoniae and related Streptococci 

show defects in multiple pathways, including biofilm formation, acid tolerance, 

bacteriocin production, and virulence (78). E. coli, too, have been reported to elicit 

broad QS activities. For example, the quantity and architecture of biofilms are regulated 

by lsrR/K, as well as the generation of several small RNAs (96, 97). Transcriptome 

analyses of an E. coli luxS mutant, which showed that 242 genes (5.6% of the whole 

genome) exhibited significant transcriptional changes upon a 300-fold AI-2 signaling 

differential (79, 92, 98), suggest that QS coordinates the control of a large subset of 

genes. Although we are not entirely certain whether these luxS mutant phenotypes are 

a result of the lack of QS signaling or may simply be due to metabolic perturbations, 

these findings surely demonstrate that QS allows bacteria to alternate between distinct 

genome-wide programs by activating numerous genes both directly and indirectly. For 

example, AI-2 also serves as a chemoattractant for E. coli (99, 100). Chemotaxis studies 

have revealed that both LsrB and Tsr, a serine chemoreceptor, are involved in AI-2 

sensing (101). As a signal molecule, AI-2 is not a nutrient, unlike other known 

chemoattractants of E. coli; therefore, chemotaxis toward AI-2 may not involve the 

narrow dose ranges that are characteristic of most indirectly binding chemoattractants 

(102). This provides opportunities to enable programmed motility toward user-selected 

features on nearby surfaces. Antigen 43–dependent autoaggregation of E. coli is also 

mediated by AI-2. Hence, the AI-2 chemotactic response will lead to active aggregation, 



 

 

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and in turn, autoaggregation enhances AI-2-mediated signaling, and subsequently, 

biofilm formation and stress resistance (103).  

Since long before the formal recognition of metabolic engineering in 1991 (104), 

scientists and engineers had been developing microbial strains for the production of 

valuable chemicals. The emergence of metabolic engineering and synthetic biology 

was predicated on the multidimensional value associated with biological synthesis 

processes for chemical products—a natural progression was the desire to program cells 

to carry out these functions. QS regulons, having the potential to connect inter- and 

intraspecies communication systems with genome-spanning regulatory processes, 

dramatically simplify what otherwise might be the de novo engineering of gene circuits 

(105, 106). QS serves as an excellent platform for many technologies, particularly if 

one understands the regulatory reach of the genetic circuits. In the past two decades, 

the rewiring of native QS networks has enabled novel ways to engineer cell behavior, 

exemplified by such advances as programmed population controllers (107), 

synchronized genetic clocks (108), and population-based autonomous gene actuators 

(109, 110). These studies have set the stage for the future development of a variety of 

innovative biotechnological applications, which are discussed in the following sections. 

2.3 Manipulation of Quorum Sensing Systems: Endowing Cells with New 

Function 

Owing to their diversity and versatility, QS systems are perfect candidates as 

platforms for facilitating the endowment of bacterial strains with unique and 

increasingly complex functions. In this section, we explore recent endeavors to excerpt 



 

 

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QS mechanisms and pathways to enable cells with advanced functions for various 

applications. 

2.3.1 Biosensing and programming population-wide behavior 

Whole-cell biosensors, as the name suggests, are native or engineered cells that 

detect and report on a target or condition of interest (111, 112). Biocompatible and 

renewable, they make good substitutes for current chemical or electrical sensors. 

Originally, cells that elicit QS behavior were simply rewired to detect their own 

autoinducers (113) (Figure 2.2a). This was typically accomplished by the deletion of 

the terminal autoinducer-synthase gene and replacing the native QS-induced gene 

system with a reporter gene. Perhaps the most well-characterized and used sensor is the 

V. harveyi strain BB170, of Bassler and co-workers (114). While developed over two-

decades ago, these biosensor cells continue to benefit science; for example, they are 

frequently utilized in studies to probe for new QS inhibitors (115-118). Analogously, 

by fusing QS promoters with fluorescence genes, P. aeruginosa were given the ability 

to report on the genetic expression of four QS networks (119). Owing to the wide 

diversity of natural QS systems, various pathogens and infection markers can also be 

detected by engineered QS-based biosensors (120-122). These bacterial ‘sentinels’ 

were further enhanced to perform with higher sensitivity (123) or to encode and 

distribute therapeutic payload upon detection, which will be discussed in the following 

section. 

QS-based biosensors are also employed to probe pollutants (i.e., heavy metal 

ions) in the environment, in which the positive feedback loop of LuxI/R system is used 

for signal amplification (124, 125). On top of enhancing signal amplitude, QS circuits 



 

 

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have been shown to resolve some common problems met by biosensors. Genetic noise, 

or specifically variation in phenotype between cells, can be assisted by QS systems 

(126, 127). Early work showed that by coupling LuxI/R circuitry to the expression of 

a toxic protein (CcdB), it was possible to program population dynamics irrespective of 

the variability in individual cells (107). With the same notion in mind, a synchronized 

genetic clock was engineered based on both the LuxI/R system and the QS system of 

Bacillus thuringiensis (108). Here, colony-level synchronized oscillation could 

diminish single-cell variability and increase the sensitivity and robustness of the 

response to external signals. These frontier endeavors have paved the way for building 

better, more effective macroscopic biosensors. Interestingly, one further study chose to 

dwell on the heterogeneity observed within bacterial populations that, despite the group 

showing collective behavior, could still be observed. In this work, a stable quorum 

wherein a specific fraction of the whole exhibits the desired collective behavior is 

generated – say a group of cells was programmed to have 65% of the total population 

to express DsRed, a red fluorescent protein (128). This was done by manipulating the 

native E. coli AI-2 transduction cascade along with an autoinducer signal amplification 

vector that makes the strain hypersensitive to AI-2, therefore it overexpresses the 

marker protein and with this QS mechanism leads a subgroup of cells to exhibit the 

same behavior. More than an AI-2 biosensor, we believe studies like this also 

anticipated many future works to focus on intentional control of group behavior, which 

will be discussed later in this article. Owing to the development of the many tools of 

synthetic biology, QS components and signaling mechanisms have helped to streamline 

biosensor development. The adaptable and well-defined nature of QS systems will 



 

 

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surely continue to benefit the improvement of biosensors, even broadening their 

capabilities. 

2.3.2 Therapeutics: QS-regulated sense-and-kill probiotics 

In an extension of previous work (129), Hwang et al. (130) have endowed 

probiotic E. coli strain Nissle 1917 to seek the pathogen through AI (3OC12HSL)-

regulated motility; induce self-lysis (driven by lysin E7); and release pyocin c5, an 

anti–P. aeruginosa toxin (Figure 2.2b). The engineered strain exhibits in vivo 

prophylactic and therapeutic activity against P. aeruginosa during gut infection. 

Recently, BeQuIK (Biosensor Engineered Quorum Induced Killing), a newly proposed 

design that aims to combat recalcitrant biofilms, adopted the same sense-and-kill 

premise but with a twist for aiding in the targeting and penetration of biofilms (131). 

Biofilms are 3D structures in which a cluster of bacteria resides within a self-produced 

matrix primarily composed of proteins, polysaccharides, and extracellular DNA (132). 

Mature biofilms are notoriously difficult to penetrate or degrade. Because the formation 

of biofilms is governed by QS activity, the “sense-and-kill” system can be adopted to 

clear these three-dimensional structures, yet success depends on localization of the 

engineered E. coli, since this system relies heavily on the diffusion of autoinducers. 

Better eradication of biofilms could perchance be achieved through surface display of 

one or more biofilm-targeting “nanobodies” (Nb), which are single-domain antibodies 

derived from the heavy chain antibodies of camelids (133), to recognize and bind to 

components of the extracellular polymeric substance (EPS) or biofilm-mediated 

proteins. Additionally, fusing one or more biofilm-degrading enzyme domains to the 



 

 

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Nbs would possibly allow for more effective diffusion of autoinducers for activating 

the killing mechanism as well as better permeation of the therapeutic agents. 

2.3.3 Therapeutics: QS-regulated in situ production and delivery 

It is perhaps inevitable that some bacteria would evolve to preferentially grow 

in environments that harbor disease, and hence these cells may serve as a natural 

platform for the development of engineered therapies (134-136). Salmonella, for 

instance, are one of the ideal candidates because they preferentially accumulate in 

tumors, actively penetrate tumor tissue, and can be engineered to produce anticancer 

drugs in situ (137-140). Notably, however, nonspecific expression can damage healthy 

tissue. Engineering QS signaling offers the opportunity to restrict expression of the 

therapeutic compounds to relevant body sites. For example, the LuxI/R QS system was 

excerpted to build a density-dependent switch in Salmonella so that the engineered 

bacteria express the to-be-delivered proteins only in tightly packed colonies within 

tumors (141). This proof-of-concept study using an in vitro 3D tumor-on-a-chip device 

and in vivo mouse models showed that QS Salmonella specifically initiates green 

fluorescent protein expression within cancerous tissue while remaining uninduced in 

liver; hence, this study provided a road map for limiting systemic toxicity caused by 

unwanted expression in healthy tissues. In addition, such therapies could also benefit 

from bacteria that are programmed to maintain relatively low overall colonization 

levels in the body while continually producing and releasing cytotoxic agents (142, 

143). Using coupled positive and negative feedback loops that had previously been 

used to generate robust oscillatory dynamics (108, 144), Din et al. (145) constructed a 

synchronized lysis circuit to allow engineered Salmonella to deliver therapeutic cargo 



 

 

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and lyse synchronously at a threshold population. In this system, both luxI and hlyE 

(which encodes haemolysin E, an antitumor toxin) were constitutively expressed. As 

the AIs slowly built up to reach a threshold level, the bacteriophage lysis gene (φX174E) 

was induced, thus triggering cell lysis and simultaneously releasing the therapeutic 

toxin.  

Alternatively, targeted therapeutic cargo delivery has also been made possible 

in E. coli via incorporation of the native AI-2/Lsr signaling pathway (146) (Figure 

2.2b). Here, bacteria were modified to enable programmed motility, sensing, and 

actuation based on the density of user-selected features on nearby surfaces. Specifically, 

bacterial enzymes LuxS and Pfs were introduced onto cancerous eukaryotic cells as a 

nanofactory, where they were used to synthesize chemoattractant AI-2. That is, the 

LuxS-Pfs fusion protein also contained a bacterial protein G domain that enabled the 

assembly of targeting antibodies. After expression and purification from E. coli and 

incubation with an antibody targeting epidermal growth factor receptor (which is 

upregulated on cancer cells), these nanofactories were used to synthesize AI-2 on the 

cell surfaces at EGFR sites, thus directing engineered E. coli to swim toward the cancer 

cell line (SCCHN). Once in place, the same AI-2, which is differentially accumulated 

above cancer cells, enabled QS computation to induce red fluorescent protein (RFP), a 

marker for therapeutic or other compounds. 

2.3.4 Biosynthesis  

Metabolic engineering often takes inspiration from natural regulatory 

mechanisms in microbes and repurposes them to maximize productivity; QS systems 

offer many suitable components that can be exploited for this purpose. One of the more 



 

 

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severe problems met by the most productive metabolic engineering methods is the 

heavy metabolic burden that accompanies the genetic modification. Because QS 

networks can report the metabolic state of a bacterial population and the metabolic 

burden is self-indicated by this network (98), Tsao et al. (109) created a system in 

which the system itself can autonomously induce protein expression and achieve 

metabolically balanced coordination through rewiring native AI-2/LuxS QS circuitry 

in E. coli. Further, a LuxI/R-based, semiautonomous induction circuit was assembled 

in E. coli and employed for isopropanol production (147); it was later modified to create 

a fully self-induced system for synthesis of a biofuels compound, bisabolene (148). 

These approaches allow cells to grow with less metabolic burden in early stages and 

transition to a production mode after the population growth phase has completed. 

Notably, these systems can ensue without exogenous addition of inducers or perhaps 

even user input. Compared with other strategies exploiting dynamic pathway 

engineering, QS-based regulatory mechanisms provide process- and pathway-

independent control of the metabolic state, which makes them highly applicable to 

different bioprocesses. That said, there remains a general lack of quantitative 

understanding of exactly how much burden the additional QS logic gates bring to these 

engineered systems; perhaps computational modeling or fundamental understanding of 

resource competition within cells could bring about a more robust, productive cell 

factory in the future. 

  



 

 

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Figure 2.2 Quorum sensing (QS)-enabled cell functions.  

(a, left) Paradigm of QS biosensors. A wide range of signals can be detected and 

amplified through QS circuitry and reported via optical or biological means. (right) A 

quantified quorum of biosensors is engineered to respond to different levels of signal 

and produce a collective response. (b) Examples of QS therapeutics. (left) Sense-and-

kill probiotics (green) can sense pathogenic signals, specifically acyl-homoserine 

lactone (AHL) produced by pathogens, and express toxin (pyocin S5) and cell-lysis 

proteins (lysin E7) to eliminate Pseudomonas aeruginosa. Anti-biofilm enzyme (DspB) 

and biofilm-targeted nanobodies can be incorporated to facilitate biofilm penetration. 



 

 

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These smart probiotics can either autoaggregate toward tumor cells (e.g., Salmonella) 

or be programmed to actively seek target cells. (right) Nanofactories consisting of Pfs, 

LuxS, protein G, and anti-EGFR antibody will specifically bind to selected biomarkers 

(EGFR) and produce AI-2. Probiotics (Escherichia coli Nissle 1917) recognize and 

then chemotax toward AI-2 (produced by targeted cells). Upon arriving at their 

destination, smart probiotics use the same AI-2 level to report (via red/green 

fluorescence) (green/red, E. coli) or lyse when the population threshold is reached and 

release genetic-encoded cargo (tan, Salmonella).   



 

 

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2.4 Manipulation of QS Systems: Opening Lines of Communication 

In the previous section, we witnessed how QS regulons could be taken apart 

and reassembled into novel genetic circuits and how these endow cells with various 

advanced functions. These strategies mostly made use of the QS information/control 

paradigm in which cells autonomously regulate gene expression after detecting self-

generated or synthetically produced molecular cues in their immediate 

microenvironments. Most often these systems have employed diffusible AIs, such as 

the large family of AHLs. That said, QS derives from its well-established function as a 

means for conveying and coordinating social behavior (149, 150); hence, it is also 

expedient to apply and further engineer QS systems to do what they do best: launch 

and promote communication between groups of bacteria. 

2.4.1 Microbial Consortium: A Prospective Platform 

As the saying goes, “Two heads are better than one.” Microbial consortia have 

long proven their abilities to outperform single microorganisms at multiple tasks, as 

evidenced by the evolutional development of natural communities. The gut microbiota, 

for example, plays multiple vital roles in human health, from regulating metabolism to 

influencing the immune system and even guiding maturation of the enteric nervous 

system, all while varying in composition across time, location, and individuals (151, 

152). Besides their versatility, native consortia (such as the gastrointestinal microbiome) 

are also robust; they respond to environmental challenges, display cooperation and 

exchange of public goods, and communicate (chemically or physically) between 

species. In light of these beneficial traits, microbial communities present themselves as 

an attractive platform for synthetic biologists who aim to modify microorganisms for 



 

 

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biotechnological applications. From an engineering perspective, the division of labor, 

in which different populations are charged to perform different tasks, represents a key 

to overall effectiveness. Some potential advantages born by such a division of labor 

include improving functionality via specialization, reducing metabolic burden via 

function distribution, and reducing engineering complexity (153). Within consortia, 

complex tasks can be segmented, and each part can be delegated to a subpopulation. 

This allows subgroups to specialize and together display sophisticated 

multifunctionality that cannot be achieved in a single clonal population. Because cells 

are now completing only part of the overall function, they can be relieved from the 

responsibility of carrying all the modified genetic machineries and hence ameliorate 

their heavy metabolic burden. Lastly, compartmentalizing cellular processes into 

different populations increases modularity. Therefore, engineering design becomes 

more facile, as each module (or subpopulation) can be tuned, modified, or even 

replaced in a plug-and-play manner (154). That said, synthetic microbial communities 

are significantly more complex to engineer than monocultures. With each additional 

member, the size of the interaction matrix increases geometrically, so that the transition 

from static monoculture to dynamic consortia presents a new challenge for us to 

conquer. In the following sections, we discuss how QS networks may contribute to the 

synthetic biology toolbox that assists in the construction and deployment of synthetic 

microbial communities. 

2.4.2 Engineering QS-based communication 

Brenner et al. (155) first demonstrated a synthetic coculture composed of two 

engineered E. coli strains that were able to communicate bidirectionally and reach a 



 

 

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consensus (see the middle panel of Figure 2.3). Two populations conversed through 

secretion and detection of 3-oxododecanoyl-HSL (3OC12HSL) and butanoyl-HSL 

(C4HSL), which are AIs made by enzymes LasI and RhlI, respectively, from the QS 

networks of P. aeruginosa. In this consortium, one population relied on the signal from 

the other population to activate gene expression, and a consensus could be attained 

when both populations reached their cell-density thresholds. Remarkably, the 

responses were sustained for up to several days when the consortium was cultured as a 

biofilm. This success took scientists one step closer to engineering a living film—the 

consensus response could potentially be replaced into an enzyme and prodrug pair or 

two inactive fragments of a toxin. Complex metabolic tasks could be divided into two 

or more, and the intermediate pieces could be assembled to reach a consensus. Soon 

after, the concept of synthetic consortia with bidirectional communication became a 

paradigm for many similarly programmed consortia. Balagaddé et al. (156) reported an 

artificial ecosystem that aims to mimic the canonical predator–prey systems in terms 

of logic and dynamics. Here, communication was fostered by lux and las QS networks, 

and similarly the two populations regulated each other’s gene expression via QS-

rewired circuits. The predator population could kill the prey population by secreting 

AIs, which, in turn, induced a killer protein (CcdB) expression within the prey; 

meanwhile, the prey revived the predator, in which the killer protein was constitutively 

expressed, but with an induced antidote protein (CcdA). Recently, it was proposed and 

modeled in silico that this predator-and-prey architecture, or a slightly altered version 

in which two groups rescue each other, could turn into a population-controlled 

consortium (157, 158). A similar lux-based population control strategy was later 



 

 

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applied to a synthetic three-species consortium for vitamin C fermentation (159). A 

subsequent study built a symbiotic microbial ecosystem with the aid of lux and rhl QS 

networks to examine the interplay between the environment and the ecosystem (160). 

Many population dynamics, such as extinction, mutualism, and commensalism, can be 

observed by tuning different levels of environmental factors (represented in this work 

by antibiotics) and initial cell densities. Genetic oscillations, previously made possible 

in monocultures, were now shown to be generated by an activator and repressor 

coculture (161). Two strains conversed through QS networks: rhl (from P. aeruginosa), 

providing the additional positive feedback loop, and cin (from Rhizobidium), providing 

the additional negative feedback loop, with both containing an inherent AiiA-mediated 

negative feedback loop. Experimental and modeling data together had shown that this 

network topology displays more robust oscillations than those generated by just one 

negative feedback loop. AHL-mediated communication can also be coupled with AI-2 

signaling to create an autonomously regulated consortium (162). In particular, this 

system consists of two populations of E. coli, one of which generates AHL based on 

nearby AI-2 levels, and the AHL concentration, in turn, affects the growth rate of the 

other population, resulting in a change in coculture composition. Subsequent 

programming enables composition trajectories and control. Together, these studies 

portend the engineering of complex synthetic populations, perhaps bacteria in 

combination with tissues and even organs composed of multiple cell types.  

Co-cultured cellular networks can also serve as effective biosensors. Terrell et 

al. (163) described assembly of a nano-guided QS information processor, which 

included two cell populations that independently interrogate natural microbial 



 

 

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communities and autonomously generate information about QS activity by accessing 

AI-2. They were used to eavesdrop on the dialogue initiated by Gram-positive Listeria 

innocua in complex media. Populations displayed either red or green fluorescent 

proteins on their outer surfaces and were designed to detect lower and higher levels of 

AI-2, respectively. With the help of streptavidin-binding protein that was expressed on 

their outer surfaces and exogenously added magnetic nanoparticles, both populations 

reported on AI-2 secreted by L. innocua and were binned by their fluorescence 

responses. The magnetic nanoparticles enabled an unbiased collection of the sensing 

cells and at the same time focused the signal responses. This multidimensional setup 

combined biotic and abiotic features for the active probing of molecular space and 

translated the molecular dialogue into light signals that were easy to bin and interpret. 

The success of these studies has proven QS-based communication to be an effective, 

modular, and robust icebreaker for initiating communication in a microbial society. 

2.4.3 Engineering a microbial consortium: challenges. 

Despite their utility for engineering microbial consortia, QS systems have 

several drawbacks that limit their use as field-deployable communication networks. 

First and foremost is the crosstalk (see challenges in Figure 2.3) between different QS 

networks at both the promoter and signal levels (164). Signal crosstalk occurs when a 

receptor can bind its noncanonical AI. For example, LuxR is known to bind 3OC12HSL, 

the AI native to another QS system, the las system. Promoter crosstalk occurs when 

activated receptors can bind a noncanonical promoter. For instance, Brenner et al. (155) 

encountered this issue when pairing QS networks rhl and las. Specifically, high levels 

of activated LasR were found to initiate the rhl promoter. A combination of signal and 



 

 

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promoter crosstalk is also possible, whereby a receptor that is activated by a 

noncanonical AI binds to a noncanonical promoter.  

That said, if parts are well-characterized, such crosstalk can be harnessed to 

create unique dynamic circuits. Initially, most endeavors were made to avoid crosstalk; 

for example, a positive feedback loop on the I proteins was incorporated into the design 

of the bidirectional communication circuit to mitigate promoter crosstalk between lasR 

and rhl (155). However, it is critical that additional QS systems with complete 

orthogonality be developed. Via rational promoter and protein engineering, Scott & 

Hasty (164) adapted two new QS systems, the rpa system from Rhodopseudomonas 

palustris and the tra system from Agrobacterium tumefaciens, into E. coli to expand 

upon the extensively used lux and las systems. Notably, engineered rpa and tra systems 

displayed complete orthogonality, while signal and promoter orthogonality was 

observed between rpa/lux and tra/las QS systems, respectively. Another recent study 

systematically characterized six commonly used QS systems, the lux, las, tra, rpa, rhl, 

and cin networks, and developed a software tool that automatically identifies 

combinations of receptors and AIs that behave orthogonally within a given AI 

concentration regime (165). The software predictions were carefully validated through 

experimental characterization of synthetic E. coli consortia that, in turn, implemented 

three orthogonal communication channels: rhl, lux, and las. The use of different classes 

of QS systems, such as the AI-2/LuxS system or Gram-positive signaling oligopeptide 

systems, in parallel with the lux-like systems has also demonstrated orthogonality (94, 

166). 



 

 

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Another challenge in consortia engineering would be the presence of cheaters 

in a microbial community (see challenges in Figure 2.3). Microbial social cheaters rely 

on public goods or other beneficial collective actions to survive, but they do not 

contribute. These noncooperating populations pose a potential threat to the robustness 

of consortia. Studies have shown, however, that native consortia can stably maintain 

coexistence with and prevent proliferation of these external populations compared with 

high-fitness monocultures that are more prone to be exploited by cheaters (167). While 

it was postulated that employing QS could also be a way to reward cooperators and 

thus aid in eliminating cheaters (168), QS was also shown to be exploitable in many 

laboratory cultures (169). One illustrative case concerned the opportunistic pathogen 

P. aeruginosa, which relies on QS to induce the production of extracellular proteases 

that are required for growth on proteins. It was observed that QS mutants were able to 

survive when in coculture with QS-competent cells (170). This phenomenon 

subsequently led to an ongoing debate as to why there remain numerous functional QS 

systems that are maintained in nature, especially if QS systems are so easily exploited 

or circumvented. Policing, the ability of cooperators or hosts to hinder the fitness of 

cheaters, could be one of the possible reasons; this idea was used to introduce the 

concept of punishing freeloaders (171). Majerczyk et al. (172) described how QS 

regulation of pairs of genes coding for toxins and toxin immunity serves as a policing 

mechanism. In Burkholderia thailandensis, those that are QS competent deliver toxins 

to other individuals. Although the QS-competent cells are immune, QS mutants are not. 

Perhaps this scheme can be incorporated into future circuit and consortium designs to 

help create more robust communities that repress or eliminate social cheaters.  



 

 

36 
 

 

 

Figure 2.3 Applications and challenges of quorum sensing (QS)-based synthetic 

consortia.  

The middle images provide an example in which QS-communicative consortia are used 

to provide a collective response. Population 1 (green) expresses regulator (QS1)R and 

secretes AHL2 and target 1 under the control of promoter PQS1, which activates upon 

AHL1-bound QS1R. Population 2 (tan) does the reverse. Because one population 

makes the required signal for the other's gene expression, both cells and genetic circuits 

are needed to generate a response. Hence, this is an AND logic switch. Such synthetic 

consortia can be applied to metabolic engineering for distributing tasks among multiple 



 

 

37 
 

strains (top left). Such a system can be fine-tuned by controlling the growth rate of one 

of the populations relative to the other (top right). Challenges must be overcome, 

however, for these systems to work effectively. One involves signal crosstalk (bottom 

left), and another, social cheaters (bottom right). 

  



 

 

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2.5 Interkingdom Consortia: Engineering Communication Networks 

As described earlier, the AI-2/LuxS system was shown to be distinct relative to 

the lux systems in many Gram-negative bacteria, and it has been dubbed the bacterial 

Esperanto since a plethora of both Gram-negative and Gram-positive bacteria have 

been reported to synthesize AI-2 and putatively use AI-2 as a signal molecule. Because 

this LuxS-mediated AI-2 synthesis system is so widespread, it is only natural to think 

of its perception as a way of delineating its role as a signal molecule. That is, there is 

significant diversity in the uptake/signal transduction systems across many genera, 

including Gram positives and Gram-negatives. The canonical lsr operon, found in E. 

coli, consists of the genes noted in Figure 2.1b. Quan & Bentley (89) showed how 

some of these genes (e.g., lsrRK, tam) are absent in some strains, whereas their order 

and regulatory regions are different in others, providing great diversity in the way AI-

2 is perceived. The net result of this is that evolutionary pressures may have led to 

distinct patterns by which AI-2 could be taken up or processed and thereby used as a 

signal molecule. This is completely orthogonal to its synthesis as a metabolic by-

product. As such, it may be possible that next-generation antimicrobials could be 

created by intercepting intra- and interspecies bacterial communication for the creation 

of smart, disease-fighting bacteria. Instead of targeting the viability of pathogenic 

strains, interruption of their communication is proposed, as there may be less selective 

pressure to develop resistance if instead one targets the mechanisms that key 

pathogenicity (173). This idea is not new for small-molecule drugs, but to our 

knowledge not as mediated by bacteria. Because it is an AI, inhibition of the signal AI-

2 could possibly lead to decreased virulence in a variety of bacterial species. Many 



 

 

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parts of the AI-2/LuxS system, from signal generators (Pfs and LuxS) to signal 

receptors (LsrK, LsrR), are likely targets for inhibition, especially because many 

synthesized AI-2 analogs are available for quorum quenching (116-118, 174). For 

example, commensal E. coli were engineered to increase AI-2 levels in the mouse gut. 

During streptomycin-induced dysbiosis, these AI-2-producing E. coli promoted gut 

colonization by Firmicutes over Bacteroidetes (175), whereas added streptomycin 

massively favored the Bacteroidetes and inhibited Firmicutes. This offered an exciting 

possibility that by altering AI-2, one could ameliorate the effect of an applied antibiotic 

on microbiota-derived functions. This success suggests that continued efforts to 

engineer strains with the intent to bias microbiome signaling (123) will surely emerge. 

Additionally, AI-2-producing Ruminococcus obeum were also shown to be vital for 

defeating Vibrio cholerae infection and facilitating recovery (176). R. obeum restricted 

colonization of V. cholerae through upregulation of the luxS gene to produce more AI-

2, and in turn, AI-2 displayed QS-mediated repression of several V. cholerae 

colonization factors. Whereas AI-2 signaling was found to be critical in native gut 

environments, LuxI/R-type systems have not been detected in the normal, healthy gut. 

This provides another possible opportunity to interrogate and manipulate 

communication for positive gain. A recent study constructed an information-transfer 

system to probe whether the lux QS system can be repurposed into a functional, 

artificially established language in the mammalian gut (177). Both interspecies and 

intraspecies communication were made possible despite some complexities in in vivo 

studies. Together, these studies promise to underpin many valuable uses of QS 



 

 

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networks in the future to either promote or interrupt communication, not just at the 

species level but to affect a whole microbiome. 

2.5.1 Interkingdom and beyond. 

QS bacteria are also observed reaching out to eukaryotes. Indeed, QS-

communicating bacteria and their components are emerging at many interfaces, 

including in interactions with viruses, eukaryotic cells and organisms (e.g., plants), 

artificial cells, biomaterials, and even electronic devices (Figure 2.4). Orphan, or solo, 

LuxR homologs were first discovered in Salmonella typhimurium, a bacterium that was 

reported as lacking a LuxI homolog and the ability to produce AHL-type AIs. It was 

further discovered that an E. coli luxR homolog, sdiA, was shown to respond to 

mammalian host-produced small molecules (178). This discovery hinted at the 

possibility that LuxR homologs, instead of acting as QS receptors, were sensors of the 

host environment. Many orphan LuxR homologs were then found in plant-associated 

bacteria, regulating plant–bacterial interactions through detection of small molecules 

secreted by the host (179). Contrarily, host cells could respond to AIs secreted by their 

commensal bacteria. RNA-sequencing technology revealed that human colonic cell 

line HCT-8 expresses inflammatory cytokine interleukin 8 in response to AI-2 secreted 

by nonpathogenic E. coli (180). Surprisingly, Silpe & Bassler (181) recently revealed 

that vibriophage VP882 can respond to a V. cholerae–produced QS AI (DPO). Once 

bound to DPO, the phage QS receptor VqmAPhage in turn activates the phage lytic 

program. Activated VqmAPhage can even recognize the host vqmR promoter and 

influence its QS behavior. This is the first case reported to show that viruses can 

eavesdrop on their hosts and decide their actions based on what they have heard. 



 

 

41 
 

 Finally, when considering more biotechnological objectives, we note that QS 

systems have also enabled cell signaling to pass from biological niches to abiotic and 

even microelectromechanical systems. Although this could be the topic of a far more 

extensive review, we note a few examples that are logical extensions of the above work 

in that the molecular components of AI-2 QS are abstracted and put in play to mediate 

bio-/device signaling. For example, to understand the interplay between QS signal 

molecules and human epithelial cells, a nanofactory consisting of the two terminal AI-

2 synthases, Pfs and LuxS, and a targeting antibody was created and electro-assembled 

into microfluidic devices, where it was used to capture cells and stimulate their QS 

responses (182, 183). Analogously, the construct was loaded onto receptor molecules 

of human intestine epithelial cells, where they stimulated QS activity among nearby 

commensal E. coli (183, 184). The same enzyme construct was later shown to be 

grafted onto spider silk and subsequently wound into place in a microfluidic device, 

where its molecular signaling activity could be localized with minimal machine 

guidance or intervention (185). In another example, Lentini et al. (186) engineered 

minimal artificial cells capable of expressing AI-2 synthesizing fusion protein HLPT 

(His6-LuxSPfs-Tyr5) (182), wherein newly synthesized AI-2 was proven to induce 

luminescence in nearby cells. The same HLPT fusion was shown to be electrically 

assembled onto gold electrodes, where its activity was controlled electrochemically 

(187) by simply applied voltage and redox actuation. In all these systems, AI-2 is 

synthesized in carefully controlled environments and in ways that are programmed by 

external inputs—some even electronic. That is, biomolecular synthesis reactions, even 

pathways, are carried out in well-controlled microsystems so that the kinetics and mass 



 

 

42 
 

transfer processes can be controlled, designed, and even optimized. Such complex 

microfluidic environments are recreated on chips for preclinical drug development and 

toxicity screening. These studies ultimately suggest that, by bridging with 

nonbiological materials, there are many opportunities to build novel microelectronic, 

biohybrid devices that can alter the complex networks of natural cells without 

tampering with the original genetic makeup. In turn, these can be used in drug 

development studies as well as detailed biological studies in which distances and 

dynamics are of the same scale as the cells and molecules themselves.  



 

 

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Figure 2.4 QS-mediated communication to interkingdom and beyond. 

Native and engineered quorum sensing (QS)-mediated communication can be used to 

target a variety of areas. QS bacteria not only are observed to display both intra- and 

interspecies communication (right) but also are capable of interpreting signals from 

eukaryotes, such as plants (top left) and mammalian cells (bottom). Recently, viruses 

(top right) have been found to respond to and make decisions based upon host-produced 

acyl-homoserine lactones (AHLs). Communications between abiotic materials and QS-

communicating bacteria (left) by QS-component assembly on gold electrodes or 

on/within artificial cells. 

  



 

 

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2.6 Conclusion and Future Outlook 

QS has provided researchers with a variety of novel platforms or techniques from which 

to address biotechnological problems. In this article, we addressed the versatility of 

native QS and the numerous strategies aiming to repurpose QS systems to program the 

behavior of a single cell, a cell consortium, or even a microbiome. QS advances 

synthetic biology by offering various genetic building blocks that can be reassembled 

into functional circuits to regulate gene expression and biological phenotype. Owing to 

the engineered QS circuitry, cells are endowed with smart functions, such as user-

specified sensing and reporting, in situ drug delivery, and sophisticated biosynthesis 

processes. Further, as researchers have attempted to build more complex functions into 

a single cell, they have realized that these may be too much responsibility for one 

microbe to carry. Hence, looking again to nature for guidance, many groups have 

turned to engineering multispecies consortia that are considered to be more robust than 

monocultures. In this way, rewired QS networks can help create a synthetic microbial 

community in which members actively interact with each other with end user–designed 

guidance. These activities feed well into the emergence of systems biology tools that 

enable detailed interrogation of various microbiomes. Finally, QS systems and their 

components can allow direct interaction with abiotic materials, creating biohybrid, 

microelectronic devices that may integrate with our daily lives. We believe these 

innovative QS-based methods will no doubt continue to generate impactful applications 

in the future.    



 

 

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Chapter 3. Engineering communication between the biotic 

and abiotic realms 
iThis chapter is partially adapted with permission, from the following publications:  

(1) Li, J., Wang, S. P., Zong, G., Kim, E., Tsao, C.-Y., VanArsdale, E., Wang, L.-X., Bentley, 

W. E., Payne, G. F., Interactive Materials for Bidirectional Redox-Based Communication. Adv. 

Mater. 2021, 33, 2007758.  

(2) Li, J., Kim, E., Gray, K. M., Conrad, C., Tsao, C.-Y., Wang, S. P., Zong, G., Scarcelli, G., 

Stroka, K. M., Wang, L.-X., Bentley, W. E., Payne, G. F., Mediated Electrochemistry to Mimic 

Biology's Oxidative Assembly of Functional Matrices. Adv. Funct. Mater. 2020, 30, 2001776. 

3.1 Chapter Overview 

In this chapter, we focused on engineering the interface between biotic factors 

and abiotic materials to facilitate information transfer between these domains. First, we 

developed a simple, yet controllable method for assembling live cells with thiolated 

polyethylene glycol (PEG-SH) to form a hydrogel that resembled the microbial 

biofilms found in nature. We then modified the PEG-SH hydrogel, endowing it with 

redox capabilities by covalently crosslinking a redox-active molecule catechol to PEG-

SH. This resulted in an interactive material that can autonomously synthesize H2O2 as 

the electrochemical signaling molecule for communication with a bacterial population. 

3.2 Motivation and Background  

Cell immobilization provides a clever strategy to spatially fix cells on an abiotic 

surface to create a biohybrid “living electrode,” in order to better integrate biological 

systems that were mostly cultured in a suspension aqueous state with electronic devices. 

While ideal for bacterial growth, liquid cultures are only viable for a few days and tend 

to be difficult to maintain and transport (188). Moreover, due to the diffusion-limiting 



 

 

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nature of most electronic signals (e.g., electrons or redox mediators), this also greatly 

benefits the signal transfer by localizing the cells at the bioelectronic interface. Many 

immobilization techniques have been explored, and can be roughly categorized into 

entrapment, adsorption, encapsulation, and containment within synthetic polymers 

(189, 190). To enable cell attachment on electrode surfaces, certain adsorption-based 

techniques initially emerge as good candidates since they are developed based on the 

interactions between biochemical moieties and metal surfaces. For example, both 

histidine and cysteine residues are known to interact strongly with gold, via its 

carboxylate or sulfhydryl (thiol) groups, respectively (191, 192). These findings 

previously birthed multiple biotechnological applications, mostly biosensors (193), 

enabling multimodal detection of many critical biochemical small molecules. Recently, 

cell-surface engineering allowed the display of specific peptides to be presented on the 

cell membrane. Dong et al. designed several gold-binding sequences to be surface 

displayed on E. coli outer membrane and demonstrated successful self-assembly of 

gold nanoparticles driven by metal-peptide interaction (194). Instead of utilizing 

sulfhydryl moieties, Terrell et al. surface displayed a known gold-binding peptide 

without cysteine and achieved direct assembly of engineered E. coli onto the electrode 

(68). However, these methods require extra genetic engineering to express non-native 

peptides/proteins which may add metabolic stress to the cells. On the other hand, 

electrofabrication is an emerging biofabrication approach that provides complementary 

additive manufacturing capabilities for life science applications (195-198), including 

bioelectronics (199-201), and regenerative medicine (202). This approach utilizes the 

fabricated hydrogel to entrap cells within, mimicking key features of the oxidative 



 

 

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assembly of tissue extracellular matrices. Here, we chose a synthetic yet biocompatible 

polymer PEG-SH that is commonly used in biological applications as a mimic for 

extracellular matrix (203) and mucin (204) for the entrapment of engineered E. coli. In 

addition to cell immobilization, soft materials were now designed to be capable of 

enabling “communication” between the material and biology via tailored moduli (205) 

or specific ligands (206) that interact with cells through mechanical modalities or 

distinct cell-surface receptors. Because diffusible reactive oxygen species (ROS) are 

major signaling molecules for redox-based communication in biological systems (e.g., 

gut microbiome or the rhizosphere) (207-211), we aimed to endow abiotic materials 

with the ability to participate in redox-based communication and induce biological 

responses. As nucleophiles, thiol (-SH) groups can undergo conjugation reactions with 

moieties like quinones that are commonly found in biological systems (212, 213).  In 

this work, we chose to investigate the interaction between PEG-SH and the quinone-

forming species catechol (214), with the focus on how catechol-conjugated PEG 

hydrogel promoted molecular communication with bacterial cells through ROS 

signaling. 

3.3 Results 

3.3.1 Electrodeposition of PEG-SH and living cells. 

We took inspiration from bacterial biofilms found in nature and created an 

“artificial biofilm” to immobilize cells onto the electrode surface, generating a “living 

electrode”. The “artificial biofilm” was generated through electrodepositing the 

bacteria with PEG-SH to form a cell-containing hydrogel. Specifically, cells were 



 

 

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mixed with PEG-SH monomer in a solution containing a redox mediator ferrocene (Fc) 

to fac