Multiplexed Immunoassay Using Quantum Dots to Monitor Proteins Secreted from Single Cells at Near-Single Molecule Resolution.

Single-cell secretion studies find important applications in molecular diagnostics, therapeutic target identification, and basic biology research. One increasingly important area of research is non-genetic cellular heterogeneity, a phenomenon that can be studied by assessing secretion of soluble effector proteins from single cells. This is particularly impactful for immune cells, as secreted proteins such as cytokines, chemokines, and growth factors are the gold standard for identifying phenotype. Current methods that rely upon immunofluorescence suffer from low detection sensitivity, requiring thousands of molecules to be secreted per cell. We have developed a quantum dot (QD)-based single-cell secretion analysis platform that can be used in different sandwich immunoassay formats to dramatically lower detection threshold, such that only one to a few molecules need be secreted per cell. We have also expanded this work to include multiplexing capabilities for different cytokines and employed this platform to study macrophage polarization under different stimuli at the single-cell level.

Fluidic Device System for Mechanical Processing and Filtering of Human Lipoaspirate Enhances Recovery of Mesenchymal Stem Cells.

BACKGROUND: Adipose tissue is an easily accessible source of stem and progenitor cells that offers exciting promise as an injectable autologous therapeutic for regenerative applications. Mechanical processing is preferred over enzymatic digestion, and the most common method involves shuffling lipoaspirate between syringes and filtering to produce nanofat. Although nanofat has shown exciting clinical results, the authors hypothesized that new device designs could enhance recovery of stem/progenitor cells through optimization of fluid dynamics principles, integration, and automation. METHODS: The authors designed and fabricated the emulsification and micronization device (EMD) and the filtration device (FD) to replace the manual nanofat procedures. Using human lipoaspirate samples, the EMD and the FD were optimized and compared to traditional nanofat using ex vivo measurements of cell number, viability, and percentage of mesenchymal stem cells and endothelial progenitor cells. RESULTS: The EMD produced results statistically similar to nanofat, and these findings were confirmed for a cohort of diabetic patients. Combining the FD with the EMD was superior to manually filtered nanofat in terms of both recovered cell percentages (>1.5-fold) and numbers (two- to three-fold). Differences were statistically significant for total mesenchymal stem cells and a DPP4 + /CD55 + subpopulation linked to improved wound healing in diabetes. CONCLUSIONS: The new EMD and the FD improved mechanical processing of human lipoaspirate in terms of mesenchymal stem cell enrichment and number compared to traditional nanofat. Future work will seek to investigate the wound healing response both in vitro and in vivo, and to refine the technology for automated operation within clinical settings. CLINICAL RELEVANCE STATEMENT: The new devices improved mechanical processing of human lipoaspirate in terms of stem cell enrichment and number compared to traditional methods. Future work will seek to validate wound healing response and refine the technology for automated operation within clinical settings.

Phasor Analysis of Fluorescence Lifetime Enables Quantitative Multiplexed Molecular Imaging of Three Probes.

The excited-state lifetime is an intrinsic property of fluorescent molecules that can be leveraged for multiplexed imaging. An advantage of fluorescence lifetime-based multiplexing is that signals from multiple probes can be gathered simultaneously, whereas traditional spectral fluorescence imaging typically requires multiple images at different excitation and emission wavelengths. Additionally, lifetime and spectra could both be utilized to expand the multiplexing capacity of fluorescence. However, resolving exogenous molecular probes based exclusively on the fluorescence lifetime has been limited by technical challenges in analyzing lifetime data. The phasor approach to lifetime analysis offers a simple, graphical solution that has increasingly been used to assess endogenous cellular autofluorescence to quantify metabolic factors. In this study, we employed the phasor analysis of FLIM to quantitatively resolve three exogenous, antibody-targeted fluorescent probes with similar spectral properties based on lifetime information alone. First, we demonstrated that three biomarkers that were spatially restricted to the cell membrane, cytosol, or nucleus could be accurately distinguished using FLIM and phasor analysis. Next, we successfully resolved and quantified three probes that were all targeted to cell surface biomarkers. Finally, we demonstrated that lifetime-based quantitation accuracy can be improved through intensity matching of various probe-biomarker combinations, which will expand the utility of this technique. Importantly, we reconstructed images for each individual probe, as well as an overlay of all three probes, from a single FLIM image. Our results demonstrate that FLIM and phasor analysis can be leveraged as a powerful tool for simultaneous detection of multiple biomarkers with high sensitivity and accuracy.

Optimization of Mechanical Tissue Dissociation Using an Integrated Microfluidic Device for Improved Generation of Single Cells Following Digestion.

The dissociation of tissue and cell aggregates into single cells is of high interest for single cell analysis studies, primary cultures, tissue engineering, and regenerative medicine. However, current methods are slow, poorly controlled, variable, and can introduce artifacts. We previously developed a microfluidic device that contains two separate dissociation modules, a branching channel array and nylon mesh filters, which was used as a polishing step after tissue processing with a microfluidic digestion device. Here, we employed the integrated disaggregation and filtration (IDF) device as a standalone method with both cell aggregates and traditionally digested tissue to perform a well-controlled and detailed study into the effect of mechanical forces on dissociation, including modulation of flow rate, device pass number, and even the mechanism. Using a strongly cohesive cell aggregate model, we found that single cell recovery was highest using flow rates exceeding 40 ml/min and multiple passes through the filter module, either with or without the channel module. For minced and digested kidney tissue, recovery of diverse cell types was maximal using multiple passes through the channel module and only a single pass through the filter module. Notably, we found that epithelial cell recovery from the optimized IDF device alone exceeded our previous efforts, and this result was maintained after reducing digestion time to 20 min. However, endothelial cells and leukocytes still required extended digestion time for maximal recover. These findings highlight the significance of parameter optimization to achieve the highest cell yield and viability based on tissue sample size, extracellular matrix content, and strength of cell-cell interactions.

Microfluidic Device Technologies for Digestion, Disaggregation, and Filtration of Tissue Samples for Single Cell Applications.

There is growing interest in breaking down tissues into the individual cellular constituents so that those cells can be identified, assayed for functional characteristics, or utilized for therapeutic purposes. A major driver is the development of single cell analysis methods, which are best poised to assess cellular heterogeneity and discover rare cells. Current tissue dissociation methods are inefficient, produce variable results, and require many labor-intensive, time-consuming steps. To address these shortcomings, we have developed three different microfluidic technologies to perform the critical steps of tissue digestion, disaggregation, and filtration with improved dissociation efficiency and speed. These devices will make it possible to process tissue into single cells for various downstream applications in a rapid and automated fashion.

Multiplexed Detection of Secreted Cytokines at near-Molecular Resolution Elucidates Macrophage Polarization Heterogeneity.

Monitoring the secretion of proteins from single cells can provide important insights into how cells respond to their microenvironment. This is particularly true for immune cells, which can exhibit a large degree of response heterogeneity. Microfabricated well arrays provide a powerful and versatile method to assess the secretion of cytokines, chemokines, and growth factors from single cells, but detection sensitivity has been limited to high levels on the order of 10,000 per cell. Recently, we reported a quantum dot-based immunoassay that lowered the detection limit for the cytokine TNF-α to concentrations to nearly the single-cell level. Here, we adapted this detection method to three additional targets while maintaining high detection sensitivity. Specifically, we detected MCP-1, TGF-ß, IL-10, and TNF-α using quantum dots with different emission spectra, each of which displayed a detection threshold in the range of 1-10 fM or ∼1-2 molecules per well. We then quantified secretion of all four proteins from single macrophage cells that were stimulated toward a pro-inflammatory state with lipopolysaccharide (LPS) or toward a pro-healing state with both LPS and interleukin 4 (IL-4). We found that MCP-1 and TGF-ß were predominantly secreted at high levels only (>10,000 molecules/cell), while a substantial number of cells secreted IL-10 and TNF-α at lower levels that could only be detected using our method. Subsequent principal component and cluster analysis revealed that secretion profiles could be classified as either exclusively pro-inflammatory, including MCP-1 and/or TNF-α, or more subtle responses displaying both pro-healing and pro-inflammatory characters. Our results highlight the heterogeneous and nondiscrete nature of macrophage phenotypes following in vitro stimulation of a cell line. Future work will focus on expanding the multiplexing capacity by extending emission spectra bandwidth and/or spatially barcoding capture antibodies, as well as evaluating the enhanced detection sensitivity capabilities with normal and diseased immune cell populations in vitro and in vivo.

Quantifying and controlling bond multivalency for advanced nanoparticle targeting to cells.

Nanoparticles have drawn intense interest as delivery agents for diagnosing and treating various cancers. Much of the early success was driven by passive targeting mechanisms such as the enhanced permeability and retention (EPR) effect, but this has failed to lead to the expected clinical successes. Active targeting involves binding interactions between the nanoparticle and cancer cells, which promotes tumor cell-specific accumulation and internalization. Furthermore, nanoparticles are large enough to facilitate multiple bond formation, which can improve adhesive properties substantially in comparison to the single bond case. While multivalent binding is universally believed to be an attribute of nanoparticles, it is a complex process that is still poorly understood and difficult to control. In this review, we will first discuss experimental studies that have elucidated roles for parameters such as nanoparticle size and shape, targeting ligand and target receptor densities, and monovalent binding kinetics on multivalent nanoparticle adhesion efficiency and cellular internalization. Although such experimental studies are very insightful, information is limited and confounded by numerous differences across experimental systems. Thus, we focus the second part of the review on theoretical aspects of binding, including kinetics, biomechanics, and transport physics. Finally, we discuss various computational and simulation studies of nanoparticle adhesion, including advanced treatments that compare directly to experimental results. Future work will ideally continue to combine experimental data and advanced computational studies to extend our knowledge of multivalent adhesion, as well as design the most powerful nanoparticle-based agents to treat cancer.

Microfluidic platform accelerates tissue processing into single cells for molecular analysis and primary culture models.

Tissues are complex mixtures of different cell subtypes, and this diversity is increasingly characterized using high-throughput single cell analysis methods. However, these efforts are hindered, as tissues must first be dissociated into single cell suspensions using methods that are often inefficient, labor-intensive, highly variable, and potentially biased towards certain cell subtypes. Here, we present a microfluidic platform consisting of three tissue processing technologies that combine tissue digestion, disaggregation, and filtration. The platform is evaluated using a diverse array of tissues. For kidney and mammary tumor, microfluidic processing produces 2.5-fold more single cells. Single cell RNA sequencing further reveals that endothelial cells, fibroblasts, and basal epithelium are enriched without affecting stress response. For liver and heart, processing time is dramatically reduced. We also demonstrate that recovery of cells from the system at periodic intervals during processing increases hepatocyte and cardiomyocyte numbers, as well as increases reproducibility from batch-to-batch for all tissues.

Pushing the limits of detection for proteins secreted from single cells using quantum dots.

Single cell analysis methods are increasingly being utilized to investigate how individual cells process information and respond to diverse stimuli. Soluble proteins play a critical role in controlling cell populations and tissues, but directly monitoring secretion is technically challenging. Microfabricated well arrays have been developed to assess secretion at the single cell level, but these systems are limited by low detection sensitivity. Semiconductor quantum dots (QD) exhibit remarkably bright and photostable luminescence signal, but to date they have not been evaluated in single cell secretion studies using microfabricated well arrays. Here, we used QDs in a sandwich immunoassay to detect secretion of the soluble cytokine tumor necrosis factor-α (TNF-α) from single cells. To enhance detection sensitivity, we employed two different strategies. First, we used a unique single QD imaging approach, which provided a detection threshold (180 attomolar) that was >100-fold lower than previously reported results using QDs. We also amplified QD binding to each captured TNF-α molecule using the bioorthogonal cycloaddition reaction between trans-cyclooctene and tetrazine, which further lowered detection threshold to 60 attomolar. This is 6 orders of magnitude more sensitive than organic fluorophores that have been used for single cell secretion studies, and far surpasses single molecule resolution within sub-picoliter microwells that are used to assess single cell secretion. Finally, single cell secretion studies were performed using phorbol 12-myristate 13-acetate (PMA) differentiated and lipopolysaccharide (LPS) activated U-937 cells. TNF-α secretion was detected from 3-fold more single cells using the QD-based method in comparison to rhodamine, which was accomplished by extending sensitivity into the range of ∼2 to 10 000 molecules captured per microwell. In future work, we will apply this technique to assess immune cell secretion dynamics under diverse stimuli and disease settings. We will also incorporate multiplexing capabilities to evaluate the secretome at the resolution of single molecules.

Extracting multivalent detachment rates from heterogeneous nanoparticle populations.

Nanoparticles can form multiple bonds with target surfaces, thereby increasing adhesion strength and internalization rate into cells. This property has helped to drive interest in nanoparticles as delivery vehicles for drugs and imaging agents, but significant gaps in our understanding of multivalent adhesion make it difficult to control and optimize binding dynamics. In previous work, we experimentally observed that multivalent nanoparticle adhesion can exhibit a time-dependent detachment rate. However, simulations later indicated that the underlying cause was variability in the number of bonds that formed between individual nanoparticles within the population. Here, we use this insight to develop a simple model to isolate a series of constant detachment rates from such heterogeneous populations. Using simulations of experimental data to train the model, we first classified nanoparticles within a given population based on the most likely equilibrium bond number, which we termed the bond potential. We then assumed that each bond potential category would follow standard first-order kinetics with constant detachment rates. Model results matched the population binding data, but only if we further divided each bond potential category into two sub-components, the second of which did not detach. We then utilized bonding rates from the simulation to estimate detachment rates for the second, slower detaching sub-component. These results confirm our hypothesis that nanoparticle populations can be sub-divided based on bond potential, each of which could be characterized by a constant detachment rate. Finally, we established relationships between the new heterogeneous population detachment model and a time-dependent, empirical detachment model that we developed in previous work. This could make it possible to determine bond potential distributions directly from experimental data without computationally costly simulations, which will be explored in future work.

Microfluidic filter device with nylon mesh membranes efficiently dissociates cell aggregates and digested tissue into single cells.

Tissues are increasingly being analyzed at the single cell level in order to characterize cellular diversity and identify rare cell types. Single cell analysis efforts are greatly limited, however, by the need to first break down tissues into single cell suspensions. Current dissociation methods are inefficient, leaving a significant portion of the tissue as aggregates that are filtered away or left to confound results. Here, we present a simple and inexpensive microfluidic device that simultaneously filters large tissue fragments and dissociates smaller aggregates into single cells, thereby improving single cell yield and purity. The device incorporates two nylon mesh membranes with well-defined, micron-sized pores that operate on aggregates of different size scales. We also designed the device so that the first filtration could be performed under tangential flow to minimize clogging. Using cancer cell lines, we demonstrated that aggregates were effectively dissociated using high flow rates and pore sizes that were smaller than a single cell. However, pore sizes that were less than half the cell size caused significant damage. We then improved results by passing the sample through two filter devices in series, with single cell yield and purity predominantly determined by the pore size of the second membrane. Next, we optimized performance using minced and digested murine kidney tissue samples, and determined that the combination of 50 and 15 µm membranes was optimal. Finally, we integrated these two membranes into a single filter device and performed validation experiments using minced and digested murine kidney, liver, and mammary tumor tissue samples. The dual membrane microfluidic filter device increased single cell numbers by at least 3-fold for each tissue type, and in some cases by more than 10-fold. These results were obtained in minutes without affecting cell viability, and additional filtering would not be required prior to downstream applications. In future work, we will create complete tissue analysis platforms by integrating the dual membrane microfluidic filter device with additional upstream tissue processing technologies, as well as downstream operations such as cell sorting and detection.

Microfluidic channel optimization to improve hydrodynamic dissociation of cell aggregates and tissue.

Maximizing the speed and efficiency at which single cells can be liberated from tissues would dramatically advance cell-based diagnostics and therapies. Conventional methods involve numerous manual processing steps and long enzymatic digestion times, yet are still inefficient. In previous work, we developed a microfluidic device with a network of branching channels to improve the dissociation of cell aggregates into single cells. However, this device was not tested on tissue specimens, and further development was limited by high cost and low feature resolution. In this work, we utilized a single layer, laser micro-machined polyimide film as a rapid prototyping tool to optimize the design of our microfluidic channels to maximize dissociation efficiency. This resulted in a new design with smaller dimensions and a shark fin geometry, which increased recovery of single cells from cancer cell aggregates. We then tested device performance on mouse kidney tissue, and found that optimal results were obtained using two microfluidic devices in series, the larger original design followed by the new shark fin design as a final polishing step. We envision our microfluidic dissociation devices being used in research and clinical settings to generate single cells from various tissue specimens for diagnostic and therapeutic applications.

Microfluidic device for rapid digestion of tissues into cellular suspensions.

The ability to harvest single cells from tissues is currently a bottleneck for cell-based diagnostic technologies, and remains crucial in the fields of tissue engineering and regenerative medicine. Tissues are typically broken down using proteolytic digestion and various mechanical treatments, but success has been limited due to long processing times, low yield, and high manual labor burden. Here, we present a novel microfluidic device that utilizes precision fluid flows to improve the speed and efficiency of tissue digestion. The microfluidic channels were designed to apply hydrodynamic shear forces at discrete locations on tissue specimens up to 1 cm in length and 1 mm in diameter, thereby accelerating digestion through hydrodynamic shear forces and improved enzyme-tissue contact. We show using animal organs that our digestion device with hydro-mincing capabilities was superior to conventional scalpel mincing and digestion based on recovery of DNA and viable single cells. Thus, our microfluidic digestion device can eliminate or reduce the need to mince tissue samples with a scalpel, while reducing sample processing time and preserving cell viability. Another advantage is that downstream microfluidic operations could be integrated to enable advanced cell processing and analysis capabilities. We envision our novel device being used in research and clinical settings to promote single cell-based analysis technologies, as well as to isolate primary, progenitor, and stem cells for use in the fields of tissue engineering and regenerative medicine.

Evolution of Multivalent Nanoparticle Adhesion via Specific Molecular Interactions.

The targeted delivery of nanoparticle carriers holds tremendous potential to transform the detection and treatment of diseases. A major attribute of nanoparticles is the ability to form multiple bonds with target cells, which greatly improves the adhesion strength. However, the multivalent binding of nanoparticles is still poorly understood, particularly from a dynamic perspective. In previous experimental work, we studied the kinetics of nanoparticle adhesion and found that the rate of detachment decreased over time. Here, we have applied the adhesive dynamics simulation framework to investigate binding dynamics between an antibody-conjugated, 200-nm-diameter sphere and an ICAM-1-coated surface on the scale of individual bonds. We found that nano adhesive dynamics (NAD) simulations could replicate the time-varying nanoparticle detachment behavior that we observed in experiments. As expected, this behavior correlated with a steady increase in mean bond number with time, but this was attributed to bond accumulation only during the first second that nanoparticles were bound. Longer-term increases in bond number instead were manifested from nanoparticle detachment serving as a selection mechanism to eliminate nanoparticles that had randomly been confined to lower bond valencies. Thus, time-dependent nanoparticle detachment reflects an evolution of the remaining nanoparticle population toward higher overall bond valency. We also found that NAD simulations precisely matched experiments whenever mechanical force loads on bonds were high enough to directly induce rupture. These mechanical forces were in excess of 300 pN and primarily arose from the Brownian motion of the nanoparticle, but we also identified a valency-dependent contribution from bonds pulling on each other. In summary, we have achieved excellent kinetic consistency between NAD simulations and experiments, which has revealed new insights into the dynamics and biophysics of multivalent nanoparticle adhesion. In future work, we will leverage the simulation as a design tool for optimizing targeted nanoparticle agents.

Phenotypic Analysis of Stromal Vascular Fraction after Mechanical Shear Reveals Stress-Induced Progenitor Populations.

BACKGROUND: Optimization of fat grafting continues to gain increasing attention in the field of regenerative medicine. "Nanofat grafting" implements mechanical emulsification and injection of standard lipoaspirate for the correction of superficial rhytides and skin discoloration; however, little is known about the cellular constituents of the graft. Based on recent evidence that various stressors can induce progenitor activity, the authors hypothesized that the shear forces used in common fat grafting techniques may impact their regenerative capacities. METHODS: Lipoaspirates were obtained from 10 patients undergoing elective procedures. Half of each sample was subjected to nanofat processing; the other half was left unchallenged. The viscosity of each sample was measured for computational analysis. The stromal vascular fraction of each sample was isolated, quantified, and analyzed by means of flow cytometry with two multicolor fluorescence antibody panels. RESULTS: Standard lipoaspirate is ideally suited for mechanical stress induction. The mechanical emulsification involved in nanofat processing did not affect cell number; however, viability was greatly reduced when compared with the stromal vascular fraction of standard lipoaspirate. Interestingly, nanofat processing resulted in stress-induced stromal vascular fraction with a higher proportion of endothelial progenitor cells, mesenchymal stem cells, and multilineage differentiating stress-enduring cells. Single-parameter analysis also revealed significant increases in CD34, CD13, CD73, and CD146 of the stress-induced stromal vascular fraction, markers associated with mesenchymal stem cell activity. CONCLUSIONS: Mechanical processing used in techniques such as nanofat grafting induces the up-regulation of progenitor phenotypes consistent with multipotency and pluripotency. These data provide a first step in characterizing the potential regenerative benefits realized through stress induction in fat grafting. CLINCAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, V.

Macrophage secretion heterogeneity in engineered microenvironments revealed using a microwell platform.

Secreted proteins play a major role in orchestrating the response of cell populations. However, a quantitative understanding of the dynamic changes in protein secretion in response to microenvironmental cues at the single cell level remains elusive. Measurements taken using traditional molecular techniques typically require bulk cultures, and therefore cannot capture the diversity within cell populations. Recent advances in chip-based technologies have shown that single cell measurements can provide important insights into the temporal dynamics of cellular activation and function, but these tools have had limited control of the adhesive cellular microenvironment. Here, we created a single cell cytokine detection platform that allows for controlled physical and adhesive microenvironment. We validated the platform by examining cytokine secretion of macrophages exposed to varying dosages of soluble stimulation and on different adhesive substrates. We also used the platform to demonstrate that cell shape affects single macrophage cytokine secretion. Together, these results show the ability of the microwell system to detect secreted cytokines from individual macrophages in controlled adhesive environments. This technique may be broadly applied to detect secreted products from any adherent cell type.

Enhancing reactivity for bioorthogonal pretargeting by unmasking antibody-conjugated trans-cyclooctenes.

The bioorthogonal cycloaddition reaction between tetrazine and trans-cyclooctene (TCO) is rapidly growing in use for molecular imaging and cell-based diagnostics. We have surprisingly uncovered that the majority of TCOs conjugated to monoclonal antibodies using standard amine-coupling procedures are nonreactive. We show that antibody-bound TCOs are not inactivated by trans-cis isomerization and that the bulky cycloaddition reaction is not sterically hindered. Instead, TCOs are likely masked by hydrophobic interactions with the antibody. We show that introducing TCO via hydrophilic poly(ethylene glycol) (PEG) linkers can fully preserve reactivity, resulting in >5-fold enhancement in functional density without affecting antibody binding. This is accomplished using a novel dual bioorthogonal approach in which heterobifunctional dibenzylcyclooctyne (DBCO)-PEG-TCO molecules are reacted with azido-antibodies. Improved imaging capabilities are demonstrated for different cancer biomarkers using tetrazine-modified fluorophore and quantum dot probes. We believe that the PEG linkers prevent TCOs from burying within the antibody during conjugation, which could be relevant to other bioorthogonal tags and biomolecules. We expect the improved TCO reactivity obtained using the reported methods will significantly advance bioorthogonal pretargeting applications.

Microfluidic device for mechanical dissociation of cancer cell aggregates into single cells.

Tumors tissues house a diverse array of cell types, requiring powerful cell-based analysis methods to characterize cellular heterogeneity and identify rare cells. Tumor tissue is dissociated into single cells by treatment with proteolytic enzymes, followed by mechanical disruption using vortexing or pipetting. These procedures can be incomplete and require significant time, and the latter mechanical treatments are poorly defined and controlled. Here, we present a novel microfluidic device to improve mechanical dissociation of digested tissue and cell aggregates into single cells. The device design includes a network of branching channels that range in size from millimeters down to hundreds of microns. The channels also contain flow constrictions that generate well-defined regions of high shear force, which we refer to as "hydrodynamic micro-scalpels", to progressively disaggregate tissue fragments and clusters into single cells. We show using in vitro cancer cell models that the microfluidic device significantly enhances cell recovery in comparison to mechanical disruption by pipetting and vortexing after digestion with trypsin or incubation with EDTA. Notably, the device enabled superior results to be obtained after shorter proteolytic digestion times, resulting in fully viable cells in less than ten minutes. The device could also be operated under enzyme-free conditions that could better maintain expression of certain surface markers. The microfluidic format is advantageous because it enables application of well-defined mechanical forces and rapid processing times. Furthermore, it may be possible to directly integrate downstream processing and detection operations to create integrated cell-based analysis platforms. The enhanced capabilities enabled by our novel device may help promote applications of single cell detection and purification techniques to tumor tissue specimens, advancing the current understanding of cancer biology and enabling molecular diagnostics in clinical settings.

Using engineered single-chain antibodies to correlate molecular binding properties and nanoparticle adhesion dynamics.

Elucidation of the relationship between targeting molecule binding properties and the adhesive behavior of therapeutic or diagnostic nanocarriers would aid in the design of optimized vectors and lead to improved efficacy. We measured the adhesion of 200-nm-diameter particles under fluid flow that was mediated by a diverse array of molecular interactions, including recombinant single-chain antibodies (scFvs), full antibodies, and the avidin/biotin interaction. Within the panel of scFvs, we used a family of mutants that display a spectrum of binding kinetics, allowing us to compare nanoparticle adhesion to bond chemistry. In addition, we explored the effect of molecular size by inserting a protein linker into the scFv fusion construct and by employing scFvs that are specific for targets with vastly different sizes. Using computational models, we extracted multivalent kinetic rate constants for particle attachment and detachment from the adhesion data and correlated the results to molecular binding properties. Our results indicate that the factors that increase encounter probability, such as adhesion molecule valency and size, directly enhance the rate of nanoparticle attachment. Bond kinetics had no influence on scFv-mediated nanoparticle attachment within the kinetic range tested, however, but did appear to affect antibody/antigen and avidin/biotin mediated adhesion. We attribute this finding to a combination of multivalent binding and differences in bond mechanical strength between recombinant scFvs and the other adhesion molecules. Nanoparticle detachment probability correlated directly with adhesion molecule valency and size, as well as the logarithm of the affinity for all molecules tested. On the basis of this work, scFvs can serve as viable targeting receptors for nanoparticles, but improvements to their bond mechanical strength would likely be required to fully exploit their tunable kinetic properties and maximize the adhesion efficiency of nanoparticles that bear them.

Probing intracellular biomarkers and mediators of cell activation using nanosensors and bioorthogonal chemistry.

Nanomaterials offer unique physical properties that make them ideal biosensors for scant cell populations. However, specific targeting of nanoparticles to intracellular proteins has been challenging. Here, we describe a technique to improve intracellular biomarker sensing using nanoparticles that is based on bioorthogonal chemistry. Using trans-cyclooctene-modified affinity ligands that are administered to semipermeabilized cells and revealed by cycloaddition reaction with tetrazine-conjugated nanoparticles, we demonstrate site-specific amplification of nanomaterial binding. We also show that this technique is capable of sensing protein biomarkers and phosho-protein signal mediators, both within the cytosol and nucleus, via magnetic or fluorescent modalities. We expect the described method will have broad applications in nanomaterial-based diagnostics and therapeutics.