Reinforcement learning-guided control strategies for CAR T-cell activation and expansion.

Reinforcement learning (RL), a subset of machine learning (ML), could optimize and control biomanufacturing processes, such as improved production of therapeutic cells. Here, the process of CAR T-cell activation by antigen-presenting beads and their subsequent expansion is formulated in silico. The simulation is used as an environment to train RL-agents to dynamically control the number of beads in culture to maximize the population of robust effector cells at the end of the culture. We make periodic decisions of incremental bead addition or complete removal. The simulation is designed to operate in OpenAI Gym, enabling testing of different environments, cell types, RL-agent algorithms, and state inputs to the RL-agent. RL-agent training is demonstrated with three different algorithms (PPO, A2C, and DQN), each sampling three different state input types (tabular, image, mixed); PPO-tabular performs best for this simulation environment. Using this approach, training of the RL-agent on different cell types is demonstrated, resulting in unique control strategies for each type. Sensitivity to input-noise (sensor performance), number of control step interventions, and advantages of pre-trained RL-agents are also evaluated. Therefore, we present an RL framework to maximize the population of robust effector cells in CAR T-cell therapy production.

Single-Walled Carbon Nanotube Probes for the Characterization of Biofilm-Degrading Enzymes Demonstrated against Pseudomonas aeruginosa Extracellular Matrices.

Hydrolase co-therapies that degrade biofilm extracellular polymeric substances (EPS) allow for a better diffusion of antibiotics and more effective treatment; current methods for quantitatively measuring the enzymatic degradation of EPS are not amendable to high-throughput screening. Herein, we present biofilm EPS-functionalized single-walled carbon nanotube (SWCNT) probes for rapid screening of hydrolytic enzyme selectivity and activity on EPS. The extent of biofilm EPS degradation is quantified by monitoring the quenching of the SWCNT fluorescence. We used this platform to screen 16 hydrolases with varying bond breaking selectivity against a panel of wild-type Pseudomonas aeruginosa and mutants deficient or altered in one or more EPS. Next, we performed concentration-dependent studies of six enzymes on two common strains found in cystic fibrosis (CF) environments and, for each enzyme, extracted three first-order rate constants and their relative contributions by fitting a parallel, multi-site degradation model, with a good model fit (R2 from 0.65 to 0.97). Reaction rates (turnover rates) are dependent on the enzyme concentration and range from 6.67 × 10-11 to 2.80 × 10-3 *s-1 per mg/mL of enzymes. Lastly, we confirmed findings from this new assay using an established crystal-violet staining assay for a subset of hydrolase panels. In summary, our work shows that this modular sensor is amendable to the high-throughput screening of EPS degradation, thereby improving the rate of discovery and development of novel hydrolases.

Nesting box imager: Contact-free, real-time measurement of activity, surface body temperature, and respiratory rate applied to hibernating mouse models.

Noncontact methods to measure animal activity and physiology are necessary to monitor undisturbed states such as hibernation. Although some noncontact measurement systems are commercially available, they are often incompatible with realistic habitats, which feature freely moving animals in small, cluttered environments. A growing market of single-board computers, microcontrollers, and inexpensive sensors has made it possible to assemble bespoke integrated sensor systems at significantly lower price points. Herein, we describe a custom-built nesting box imager (NBI) that uses a single-board computer (Raspberry Pi) with a passive infrared (IR) motion sensor, silicon charge-coupled device (CCD), and IR camera CCD to monitor the activity, surface body temperature, and respiratory rate of the meadow jumping mouse during hibernation cycles. The data are logged up to 12 samples per minute and postprocessed using custom Matlab scripts. The entire unit can be built at a price point below US$400, which will be drastically reduced as IR (thermal) arrays are integrated into more consumer electronics and become less expensive.

Effects of Sequence Features on Machine-Learned Enzyme Classification Fidelity.

Assigning enzyme commission (EC) numbers using sequence information alone has been the subject of recent classification algorithms where statistics, homology and machine-learning based methods are used. This work benchmarks performance of a few of these algorithms as a function of sequence features such as chain length and amino acid composition (AAC). This enables determination of optimal classification windows for de novo sequence generation and enzyme design. In this work we developed a parallelization workflow which efficiently processes >500,000 annotated sequences through each candidate algorithm and a visualization workflow to observe the performance of the classifier over changing enzyme length, main EC class and AAC. We applied these workflows to the entire SwissProt database to date (n = 565245) using two, locally installable classifiers, ECpred and DeepEC, and collecting results from two other webserver-based tools, Deepre and BENZ-ws. It is observed that all the classifiers exhibit peak performance in the range of 300 to 500 amino acids in length. In terms of main EC class, classifiers were most accurate at predicting translocases (EC-6) and were least accurate in determining hydrolases (EC-3) and oxidoreductases (EC-1). We also identified AAC ranges that are most common in the annotated enzymes and found that all classifiers work best in this common range. Among the four classifiers, ECpred showed the best consistency in changing feature space. These workflows can be used to benchmark new algorithms as they are developed and find optimum design spaces for the generation of new, synthetic enzymes.

Inexpensive Near-Infrared Fluorimeters: Enabling Translation of nIR-Based Assays to the Field.

The practical impact of analytical probes that transduce in the near-infrared (nIR) has been dampened by the lack of cost-effective and portable nIR fluorimeters. Herein, we demonstrate straightforward designs for an inexpensive microplate reader and a portable fluorimeter. These instruments require minimally complex machining and fabrication and operate with an open-source programming language (Python). Complete wiring diagrams, assembly diagrams, and scripts are provided. To demonstrate the utility of these two instruments, we performed high-throughput and field-side measurements of soil samples to evaluate the effect of soil management strategies on extracellular proteolytic, cellulolytic, and lignin-modifying activities. This was accomplished with fluorescent enzyme probes that utilized uniquely sensitive transducers exclusive to the nIR spectrum, single-walled carbon nanotubes. We also used the portable fluorimeter to evaluate spatial variations of proteolytic activity within individual field plots, while minimizing the effects of soil storage and handling. These demonstrations indicate the utility of these fluorimeters for translating analytical probes that operate in the nIR beyond the laboratory and into actual use.

Substrate-Wrapped, Single-Walled Carbon Nanotube Probes for Hydrolytic Enzyme Characterization.

Hydrolytic enzymes are a topic of continual study and improvement due to their industrial impact and biological implications; however, the ability to measure the activity of these enzymes, especially in high-throughput assays, is limited to an established, few enzymes and often involves the measurement of secondary byproducts or the design of a complex degradation probe. Herein, a versatile single-walled carbon nanotube (SWNT)-based biosensor that is straightforward to produce and measure is described. The hydrolytic enzyme substrate is rendered as an amphiphilic polymer, which is then used to solubilize the hydrophobic nanotubes. When the target enzyme degrades the wrapping, the SWNT fluorescent signal is quenched due to increased solvent accessibility and aggregation, allowing quantitative measurement of hydrolytic enzyme activity. Using (6,5) chiral SWNT suspended with polypeptides and polysaccharides, turnover frequencies are estimated for cellulase, pectinase, and bacterial protease. Responses are recorded for concentrations as low as 5 fM using a well-characterized protease, Proteinase K. An established trypsin-based plate reader assay is used to compare this nanotube probe assay with standard techniques. Furthermore, the effect of freeze-thaw cycles and elevated temperature on enzyme activity is measured, suggesting freezing to have minimal impact even after 10 cycles and heating to be detrimental above 60 °C. Finally, rapid optimization of enzyme operating conditions is demonstrated by generating a response surface of cellulase activity with respect to temperature and pH to determine optimal conditions within 2 h of serial scans.

Mechanism of immobilized protein A binding to immunoglobulin G on nanosensor array surfaces.

Protein A is often used for the purification and detection of antibodies such as immunoglobulin G (IgG) because of its quadrivalent domains that bind to the Fc region of these macromolecules. However, the kinetics and thermodynamics of the binding to many sensor surfaces have eluded mechanistic description due to complexities associated with multivalent interactions. In this work, we use a near-infrared (nIR) fluorescent single-walled carbon nanotube sensor array to obtain the kinetics of IgG binding to protein A, immobilized using a chelated Cu(2+)/His-tag chemistry to hydrogel dispersed sensors. A bivalent binding mechanism is able to describe the concentration dependence of the effective dissociation constant, KD,eff, which varies from 100 pM to 1 µM for IgG concentrations from 1 ng mL(-1) to 100 µg mL(-1), respectively. The mechanism is shown to describe the unusual concentration-dependent scaling demonstrated by other sensor platforms in the literature as well, and a comparison is made between resulting parameters. For comparison, we contrast IgG binding with that of human growth hormone (hGH) to its receptor (hGH-R) which displays an invariant dissociation constant at KD = 9 µM. These results should aid in the use of protein A and other recognition elements in a variety of sensor types.

Plant nanobionics approach to augment photosynthesis and biochemical sensing.

The interface between plant organelles and non-biological nanostructures has the potential to impart organelles with new and enhanced functions. Here, we show that single-walled carbon nanotubes (SWNTs) passively transport and irreversibly localize within the lipid envelope of extracted plant chloroplasts, promote over three times higher photosynthetic activity than that of controls, and enhance maximum electron transport rates. The SWNT-chloroplast assemblies also enable higher rates of leaf electron transport in vivo through a mechanism consistent with augmented photoabsorption. Concentrations of reactive oxygen species inside extracted chloroplasts are significantly suppressed by delivering poly(acrylic acid)-nanoceria or SWNT-nanoceria complexes. Moreover, we show that SWNTs enable near-infrared fluorescence monitoring of nitric oxide both ex vivo and in vivo, thus demonstrating that a plant can be augmented to function as a photonic chemical sensor. Nanobionics engineering of plant function may contribute to the development of biomimetic materials for light-harvesting and biochemical detection with regenerative properties and enhanced efficiency.

Recent advances in molecular recognition based on nanoengineered platforms.

Nanoparticles and nanoengineered platforms have great potential for technologies involving biomoleuclar detection or cell-related biosensing, and have provided effective chemical interfaces for molecular recognition. Typically, chemists work on the modification of synthetic polymers or macromolecules, which they link to the nanoparticles by covalent or noncovalent approaches. The motivation for chemical modification is to enhance the selectivity and sensitivity, and to improve the biocompatibility for the in vivo applications. In this Account, we present recent advances in the development and application of chemical interfaces for molecular recognition for nanoparticles and nanoengineered platforms, in particular single-walled carbon nanotubes (SWNTs). We discuss emerging approaches for recognizing small molecules, glycosylated proteins, and serum biomarkers. For example, we compare and discuss detection methods for ATP, NO, H2O2, and monosaccharides for recent nanomaterials. Fluorometric detection appears to have great potential for quantifying concentration gradients and determining their location in living cells. For macromolecular detection, new methods for glycoprofiling using such interfaces appear promising, and benefit specifically from the potential elimination of cumbersome labeling and liberation steps during conventional analysis of glycans, augmenting the currently used mass spectrometry (MS), capillary electrophoresis (CE), and liquid chromatography (LC) methods. In particular, we demonstrated the great potential of fluorescent SWNTs for glycan-lectin interactions sensing. In this case, SWNTs are noncovalently functionalized to introduce a chelated nickel group. This group provides a docking site for the His-tagged lectin and acts as the signal modulator. As the nickel proximity to the SWNT surface changes, the fluorescent signal is increased or attenuated. When a free glycan or glycosylated probe interacts with the lectin, the signal increases and they are able to obtain loading curves similar to surface plasmon resonance measurements. They demonstrate the sensitivity and specificity of this platform with two higher-affined glycan-lectin pairs: fucose (Fuc) to PA-IIL and N-acetylglucosamine (GlcNAc) to GafD. Lastly, we discuss how developments in protein biomarker detection in general are benefiting specifically from label-free molecular recognition. Electrical field effect transistors, chemi-resistive and fluorometric nanosensors based on various nanomaterials have demonstrated substantial progress in recent years in addressing this challenging problem. In this Account, we compare the balance between sensitivity, selectivity, and nonspecific adsorption for various applications. In particular, our group has utilized SWNTs as fluorescence sensors for label-free protein-protein interaction measurements. In this assay, we have encapsulated each nanotube in a biocompatible polymer, chitosan, which has been further modified to conjugate nitrilotriacetic acid (NTA) groups. After Ni(2+) chelation, NTA Ni(2+) complexes bind to his-tagged proteins, resulting in a local environment change of the SWNT array, leading to optical fluorescence modulation with detection limit down to 100 nM. We have further engineered the platform to monitor single protein binding events, with an even lower detection limit down to 10 pM.

Neurotransmitter detection using corona phase molecular recognition on fluorescent single-walled carbon nanotube sensors.

Temporal and spatial changes in neurotransmitter concentrations are central to information processing in neural networks. Therefore, biosensors for neurotransmitters are essential tools for neuroscience. In this work, we applied a new technique, corona phase molecular recognition (CoPhMoRe), to identify adsorbed polymer phases on fluorescent single-walled carbon nanotubes (SWCNTs) that allow for the selective detection of specific neurotransmitters, including dopamine. We functionalized and suspended SWCNTs with a library of different polymers (n = 30) containing phospholipids, nucleic acids, and amphiphilic polymers to study how neurotransmitters modulate the resulting band gap, near-infrared (nIR) fluorescence of the SWCNT. We identified several corona phases that enable the selective detection of neurotransmitters. Catecholamines such as dopamine increased the fluorescence of specific single-stranded DNA- and RNA-wrapped SWCNTs by 58-80% upon addition of 100 µM dopamine depending on the SWCNT chirality (n,m). In solution, the limit of detection was 11 nM [K(d) = 433 nM for (GT)15 DNA-wrapped SWCNTs]. Mechanistic studies revealed that this turn-on response is due to an increase in fluorescence quantum yield and not covalent modification of the SWCNT or scavenging of reactive oxygen species. When immobilized on a surface, the fluorescence intensity of a single DNA- or RNA-wrapped SWCNT is enhanced by a factor of up to 5.39 ± 1.44, whereby fluorescence signals are reversible. Our findings indicate that certain DNA/RNA coronae act as conformational switches on SWCNTs, which reversibly modulate the SWCNT fluorescence. These findings suggest that our polymer-SWCNT constructs can act as fluorescent neurotransmitter sensors in the tissue-compatible nIR optical window, which may find applications in neuroscience.

Peptide secondary structure modulates single-walled carbon nanotube fluorescence as a chaperone sensor for nitroaromatics.

A class of peptides from the bombolitin family, not previously identified for nitroaromatic recognition, allows near-infrared fluorescent single-walled carbon nanotubes to transduce specific changes in their conformation. In response to the binding of specific nitroaromatic species, such peptide-nanotube complexes form a virtual "chaperone sensor," which reports modulation of the peptide secondary structure via changes in single-walled carbon nanotubes, near-infrared photoluminescence. A split-channel microscope constructed to image quantized spectral wavelength shifts in real time, in response to nitroaromatic adsorption, results in the first single-nanotube imaging of solvatochromic events. The described indirect detection mechanism, as well as an additional exciton quenching-based optical nitroaromatic detection method, illustrate that functionalization of the carbon nanotube surface can result in completely unique sites for recognition, resolvable at the single-molecule level.

Experimental tools to study molecular recognition within the nanoparticle corona.

Advancements in optical nanosensor development have enabled the design of sensors using synthetic molecular recognition elements through a recently developed method called Corona Phase Molecular Recognition (CoPhMoRe). The synthetic sensors resulting from these design principles are highly selective for specific analytes, and demonstrate remarkable stability for use under a variety of conditions. An essential element of nanosensor development hinges on the ability to understand the interface between nanoparticles and the associated corona phase surrounding the nanosensor, an environment outside of the range of traditional characterization tools, such as NMR. This review discusses the need for new strategies and instrumentation to study the nanoparticle corona, operating in both in vitro and in vivo environments. Approaches to instrumentation must have the capacity to concurrently monitor nanosensor operation and the molecular changes in the corona phase. A detailed overview of new tools for the understanding of CoPhMoRe mechanisms is provided for future applications.

Amplified DNA Heterogeneity Assessment with Oxford Nanopore Sequencing Applied to Cell Free Expression Templates.

In this work, Oxford Nanopore sequencing is tested as an accessible method for quantifying heterogeneity of amplified DNA. This method enables rapid quantification of deletions, insertions, and substitutions, the probability of each mutation error, and their locations in the replicated sequences. Amplification techniques tested were conventional polymerase chain reaction (PCR) with varying levels of polymerase fidelity (OneTaq, Phusion, and Q5) as well as rolling circle amplification (RCA) with Phi29 polymerase. Plasmid amplification using bacteria was also assessed. By analyzing the distribution of errors in a large set of sequences for each sample, we examined the heterogeneity and mode of errors in each sample. This analysis revealed that Q5 and Phusion polymerases exhibited the lowest error rates observed in the amplified DNA. As a secondary validation, we analyzed the emission spectra of sfGFP fluorescent proteins synthesized with amplified DNA using cell free expression. Error-prone polymerase chain reactions confirmed the dependency of reporter protein emission spectra peak broadness to DNA error rates. The presented nanopore sequencing methods serve as a roadmap to quantify the accuracy of other gene amplification techniques, as they are discovered, enabling more homogenous cell-free expression of desired proteins.

Advancements in Airborne Viral Nucleic Acid Detection with Wearable Devices.

Wearable health sensors for an expanding range of physiological parameters have experienced rapid development in recent years and are poised to disrupt the way healthcare is tracked and administered. The monitoring of environmental contaminants with wearable technologies is an additional layer of personal and public healthcare and is also receiving increased focus. Wearable sensors that detect exposure to airborne viruses could alert wearers of viral exposure and prompt proactive testing and minimization of viral spread, benefitting their own health and decreasing community risk. With the high levels of asymptomatic spread of COVID-19 observed during the pandemic, such devices could dramatically enhance our pandemic response capabilities in the future. To facilitate advancements in this area, this review summarizes recent research on airborne viral detection using wearable sensing devices as well as technologies suitable for wearables. Since the low concentration of viral particles in the air poses significant challenges to detection, methods for airborne viral particle collection and viral sensing are discussed in detail. A special focus is placed on nucleic acid-based viral sensing mechanisms due to their enhanced ability to discriminate between viral subtypes. Important considerations for integrating airborne viral collection and sensing on a single wearable device are also discussed.

Screening putative polyester polyurethane degrading enzymes with semi-automated cell-free expression and nitrophenyl probes.

Cell-free expression (CFE) has shown recent utility in prototyping enzymes for discovery efforts. In this work, CFE is demonstrated as an effective tool to screen putative polyester polyurethane degrading enzyme sequences sourced from metagenomic analysis of biofilms prospected on aircraft and vehicles. An automated fluid handler with a controlled temperature block is used to assemble the numerous 30 µL CFE reactions to provide more consistent results over human assembly. In sum, 13 putative hydrolase enzymes from the biofilm organisms as well as a previously verified, polyester-degrading cutinase were expressed using in-house E. coli extract and minimal linear templates. The enzymes were then tested for esterase activity directly in extract using nitrophenyl conjugated substrates, showing highest sensitivity to shorter substrates (4-nitrophenyl hexanoate and 4-nNitrophenyl valerate). This screen identified 10 enzymes with statistically significant activities against these substrates; however, all were lower in measured relative activity, on a CFE volume basis, to the established cutinase control. This approach portends the use of CFE and reporter probes to rapidly prototype, screen and design for synthetic polymer degrading enzymes from environmental consortia. Graphical Abstract.

Single-Use, Metabolite Absorbing, Resonant Transducer (SMART) Culture Vessels for Label-Free, Continuous Cell Culture Progression Monitoring.

Secreted metabolites are an important class of bio-process analytical technology (PAT) targets that can correlate to cell conditions. However, current strategies for measuring metabolites are limited to discrete measurements, resulting in limited understanding and ability for feedback control strategies. Herein, a continuous metabolite monitoring strategy is demonstrated using a single-use metabolite absorbing resonant transducer (SMART) to correlate with cell growth. Polyacrylate is shown to absorb secreted metabolites from living cells containing hydroxyl and alkenyl groups such as terpenoids, that act as a plasticizer. Upon softening, the polyacrylate irreversibly conformed into engineered voids above a resonant sensor, changing the local permittivity which is interrogated, contact-free, with a vector network analyzer. Compared to sensing using the intrinsic permittivity of cells, the SMART approach yields a 20-fold improvement in sensitivity. Tracking growth of many cell types such as Chinese hamster ovary, HEK293, K562, HeLa, and E. coli cells as well as perturbations in cell proliferation during drug screening assays are demonstrated. The sensor is benchmarked to show continuous measurement over six days, ability to track different growth conditions, selectivity to transducing active cell growth metabolites against other components found in the media, and feasibility to scale out for high throughput campaigns.

NoRSE: noise reduction and state evaluator for high-frequency single event traces.

UNLABELLED: NoRSE was developed to analyze high-frequency datasets collected from multistate, dynamic experiments, such as molecular adsorption and desorption onto carbon nanotubes. As technology improves sampling frequency, these stochastic datasets become increasingly large with faster dynamic events. More efficient algorithms are needed to accurately locate the unique states in each time trace. NoRSE adapts and optimizes a previously published noise reduction algorithm and uses a custom peak flagging routine to rapidly identify unique event states. The algorithm is explained using experimental data from our lab and its fitting accuracy and efficiency are then shown with a generalized model of stochastic datasets. The algorithm is compared to another recently published state finding algorithm and is found to be 27 times faster and more accurate over 55% of the generalized experimental space. NoRSE is written as an M-file for Matlab. AVAILABILITY: http://web.mit.edu/stranogroup/NoRSE.txt.

Nanoengineered glycan sensors enabling native glycoprofiling for medicinal applications: towards profiling glycoproteins without labeling or liberation steps.

Nanoengineered glycan sensors may help realize the long-held goal of accurate and rapid glycoprotein profiling without labeling or glycan liberation steps. Current methods of profiling oligosaccharides displayed on protein surfaces, such as liquid chromatography, mass spectrometry, capillary electrophoresis, and microarray methods, are limited by sample pretreatment and quantitative accuracy. Microarrayed platforms can be improved with methods that better estimate kinetic parameters rather than simply reporting relative binding information. These quantitative glycan sensors are enabled by an emerging class of nanoengineered materials that differ in their mode of signal transduction from traditional methods. Platforms that respond to mass changes include a quartz crystal microbalance and cantilever sensors. Electronic response can be detected from electrochemical, field effect transistor, and pore impedance sensors. Optical methods include fluorescent frontal affinity chromatography, surface plasmon resonance methods, and fluorescent carbon nanotubes. After a very brief primer on glycobiology and its connection to medicine, these emerging systems are critically reviewed for their potential use as core sensors in future glycoprofiling tools.

Contact-Free, Passive, Electromagnetic Resonant Sensors for Enclosed Biomedical Applications: A Perspective on Opportunities and Challenges.

Inexpensive and accurate tools for monitoring conditions in enclosed environments (through garments, bandages, tissue, etc.) have been a long-standing goal of medicine. Passive resonant sensors are a promising solution for such wearable health sensors as well as off-body diagnostics. They are simple circuits with inherent inductance and capacitance (LC tank) that have a measurable resonant frequency. Changes in local parameters, e.g., permittivity or geometry, effect inductance and capacitance which cause a resonant frequency shift response. This signal transduction has been applied to several biomedical applications such as intracranial pressure, hemodynamics, epidermal hydration, etc. Despite these many promising applications presented in the literature, resonant sensors still do not see widespread adoption in biomedical applications, especially as wearable or embedded sensing devices. This perspective highlights some of the current challenges facing LC resonant sensors in biomedical applications, such as positional sensitivity, and potential strategies that have been developed to overcome them. An outlook on adoption in medicine and health monitoring is presented, and a perspective is given on next steps for research in this field.

Characterizing the Interactions of Cell-Membrane-Disrupting Peptides with Lipid-Functionalized Single-Walled Carbon Nanotubes.

Lipid-functionalized single-walled carbon nanotubes (SWNTs) have garnered significant interest for their potential use in a wide range of biomedical applications. In this work, we used molecular dynamics simulations to study the equilibrium properties of SWNTs surrounded by the phosphatidylcholine (POPC) corona phase and their interactions with three cell membrane disruptor peptides: colistin, TAT peptide, and crotamine-derived peptide. Our results show that SWNTs favor asymmetrical positioning within the POPC corona, so that one side of the SWNT, covered by the thinnest part of the corona, comes in contact with charged and polar functional groups of POPC and water. We also observed that colistin and TAT insert deeply into the POPC corona, while crotamine-derived peptide only adsorbs to the corona surface. In separate simulations, we show that three examined peptides exhibit similar insertion and adsorption behaviors when interacting with POPC bilayers, confirming that peptide-induced perturbations to POPC in conjugates and bilayers are similar in nature and magnitude. Furthermore, we observed correlations between the peptide-induced structural perturbations and the near-infrared emission of the lipid-functionalized SWNTs, which suggest that the optical signal of the conjugates transduces the morphological changes in the lipid corona. Overall, our findings indicate that lipid-functionalized SWNTs could serve as simplified cell membrane model systems for prescreening of new antimicrobial compounds that disrupt cell membranes.