Concomitant quantification of targeted drug delivery and biological response in individual cells

Long-term in vitro recording of cardiac action potentials on microelectrode arrays for chronic cardiotoxicity assessment

The reliable identification of chronic cardiotoxic effects in in vitro screenings is fundamental for filtering out toxic molecular entities before in vivo animal experimentation and clinical trials. Present techniques such as patch-clamp, voltage indicators, and standard microelectrode arrays do not offer at the same time high sensitivity for measuring transmembrane ion currents and low-invasiveness for monitoring cells over long time. Here, we show that optoporation applied to microelectrode arrays enables measuring action potentials from human-derived cardiac syncytia for more than 1 continuous month and provides reliable data on chronic cardiotoxic effects caused by known compounds such as pentamidine. The technique has high potential for detecting chronic cardiotoxicity in the early phases of drug development.

Microfluidic platforms for single neuron analysis

Single-neuron actions are the basis of brain function, as clinical sequelae, neuronal dysfunction or failure for most of the central nervous system (CNS) diseases and injuries can be identified via tracing single-neurons. The bulk analysis methods tend to miscue critical information by assessing the population-averaged outcomes. However, its primary requisite in neuroscience to analyze single-neurons and to understand dynamic interplay of neurons and their environment. Microfluidic systems enable precise control over nano-to femto-liter volumes via adjusting device geometry, surface characteristics, and flow-dynamics, thus facilitating a well-defined micro-environment with spatio-temporal control for single-neuron analysis. The microfluidic platform not only offers a comprehensive landscape to study brain cell diversity at the level of transcriptome, genome, and/or epigenome of individual cells but also has a substantial role in deciphering complex dynamics of brain development and brain-related disorders. In this review, we highlight recent advances of microfluidic devices for single-neuron analysis, i.e., single-neuron trapping, single-neuron dynamics, single-neuron proteomics, single-neuron transcriptomics, drug delivery at the single-neuron level, single axon guidance, and single-neuron differentiation. Moreover, we also emphasize limitations and future challenges of single-neuron analysis by focusing on key performances of throughput and multiparametric activity analysis on microfluidic platforms.

Microfluidic Multielectrode Arrays for Spatially Localized Drug Delivery and Electrical Recordings of Primary Neuronal Cultures

Neuropathological models and neurological disease progression and treatments have always been of great interest in biomedical research because of their impact on society. The application of in vitro microfluidic devices to neuroscience-related disciplines provided several advancements in therapeutics or neuronal modeling thanks to the ability to control the cellular microenvironment at spatiotemporal level. Recently, the introduction of three-dimensional nanostructures has allowed high performance in both in vitro recording of electrogenic cells and drug delivery using minimally invasive devices. Independently, both delivery and recording have let to pioneering solutions in neurobiology. However, their combination on a single chip would provide further fundamental improvements in drug screening systems and would offer comprehensive insights into pathologies and diseases progression. Therefore, it is crucial to develop platforms able to monitor progressive changes in electrophysiological behavior in the electrogenic cellular network, induced by spatially localized injection of biochemical agents. In this work, we show the application of a microfluidic multielectrode array (MEA) platform to record spontaneous and chemically stimulated activity in primary neuronal networks. By means of spatially localized caffeine injection via microfluidic nanochannels, the device demonstrated its capability of combined localized drug delivery and cell signaling recording. The platform could detect activity of the neural network at multiple sites while delivering molecules into just a few selected cells, thereby examining the effect of biochemical agents on the desired portion of cell culture.

Selective intracellular delivery and intracellular recordings combined in MEA biosensors

Biological studies on in vitro cell cultures are of fundamental importance to investigate cell response to external stimuli, such as new drugs for the treatment of specific pathologies, or to study communication between electrogenic cells. Although three-dimensional (3D) nanostructures brought tremendous improvements on biosensors used for various biological in vitro studies, including drug delivery and electrical recording, there is still a lack of multifunctional capabilities that could help gain deeper insights in several bio-related research fields. In this work, the electrical recording of large cell ensembles and the intracellular delivery of few selected cells are combined on the same device by integrating microfluidic channels on the bottom of a multi-electrode array decorated with 3D hollow nanostructures. The novel platform allows the recording of intracellular-like action potentials from large ensembles of cardiomyocytes derived from human induced pluripotent stem cells (hiPSC) and from the HL-1 line, while different molecules are selectively delivered into single/few targeted cells. The proposed approach shows high potential for enabling new comprehensive studies that can relate drug effects to network level cell communication processes.

Survival of tumor and normal cells upon targeting with electron-emitting radionuclides

PURPOSE

Previous studies have shown that the mean absorbed dose to a tissue element may not be a suitable quantity for correlating with the biological response of cells in that tissue element. Cell survival can depend strongly on the distribution of radioactivity at the cellular and multicellular levels. Furthermore, when cellular absorbed doses are examined, the cross-dose from neighbor cells can be less radiotoxic than the self-dose component. To better understand how the nonuniformity of activity among cells can affect the dose response, a computer model of a 3D tissue culture was previously constructed and showed that activity distribution among cells is significantly more relevant than the mean absorbed dose for low-energy-electron emitters. The present work greatly expands upon those findings.

METHODS

In the present study, we used this same computer model but restricted the number of labeled cells to a fraction of the whole cell population (50%, 10%, and 1%, respectively). The labeled cells were randomly distributed among the whole cell population.

RESULTS

While the activity distribution is an important factor in determining the tissue response for low-energy-electron emitters, the fraction of labeled cells has an even more pronounced effect on survival response. For all electron energies studied, reducing the percentage of cells labeled significantly increases the surviving fraction of the whole population.

CONCLUSIONS

This study provides abundant information on killing tumor and normal cells under some conditions relevant to targeted radionuclide therapy of isolated tumor cells and micrometastases. The percentage of cells labeled, activity distribution among the labeled cells, and electron energy play key roles in determining their response. Most importantly, and not previously demonstrated, lognormal activity distributions can have a profound impact on the response of the tumor cells even when the radionuclide emits high-energy electrons.

Induction of lethal bystander effects in human breast cancer cell cultures by DNA-incorporated Iodine-125 depends on phenotype

PURPOSE

This study uses a three-dimensional cell culture model to investigate lethal bystander effects in human breast cancer cell cultures (MCF-7, MDA-MB-231) treated with (125)I-labeled 5-iodo-2 -deoxyuridine ((125)IdU). These breast cancer cell lines respectively form metastatic xenografts in nude mice in an estrogen-dependent and independent manner.

MATERIALS AND METHODS

In the present study, these cells were cultured in loosely-packed three-dimensional architecture in a Cytomatrix™ carbon scaffold. Cultures were pulse-labeled for 3 h with (125)IdU to selectively irradiate a minor fraction of cells, and simultaneously co-pulse-labeled with 0.04 mM 5-ethynyl-2'-deoxyuridine (EdU) to identify the radiolabeled cells using Click-iT(®) EdU and flow cytometry. The cultures were then washed and incubated for 48 h. The cells were then harvested, serially diluted, and seeded for colony formation. Aliquots of cells were subjected to flow cytometry to determine the percentage of cells labeled with (125)IdU/EdU. Additional aliquots were used to determine the mean (125)I activity per labeled cell. The percentage of labeled cells was about 15% and 10% for MCF-7 and MDA cells, respectively. This created irradiation conditions wherein the cross-dose to unlabeled cells was small relative to the self-dose to labeled cells. The surviving fraction relative to EdU-treated controls was measured.

RESULTS

Survival curves indicated significant lethal bystander effect in MCF-7 cells, however, no significant lethal bystander effect was observed in MDA-MB-231 cells.

CONCLUSIONS

These studies demonstrate the capacity of (125)IdU to induce lethal bystander effects in human breast cancer cells and suggest that the response depends on phenotype.

Monte Carlo simulation of irradiation and killing in three-dimensional cell populations with lognormal cellular uptake of radioactivity

PURPOSE

The biological response of tissue exposed to radiations emitted by internal radioactivity is often correlated with the mean absorbed dose to a tissue element. However, experimental studies show that even when the mean absorbed dose to the tissue element is constant, the response of the cell population within the tissue element can vary significantly depending on the distribution of radioactivity at the cellular and multicellular levels. The present work develops theoretical models to simulate these observations.

MATERIALS AND METHODS

Two theoretical models were created to simulate experimental three-dimensional cell culture models with homogeneous and inhomogeneous tissue environments. The cells were assigned activities according to lognormal distributions of an alpha particle emitter or a monoenergetic electron emitter. Absorbed doses to the cell nuclei were assessed with point-kernel geometric-factor and Electron Gamma Shower version nrc (EGSnrc) Monte Carlo radiation transport simulations, respectively. The self- and cross-dose to individual cell nuclei were calculated and a Monte Carlo method was used to determine their fate. Survival curves were produced after tallying the live and dead cells.

RESULTS

Both percent cells labeled and breadth of lognormal distribution affected the dose distribution at the cellular level, which in turn, influenced the shape of the cell survival curves.

CONCLUSIONS

Multicellular Monte Carlo dosimetry-models offer improved capacity to predict response to radiopharmaceuticals compared to approaches based on mean absorbed dose to the tissue.

Flow cytometry-assisted Monte Carlo simulation predicts clonogenic survival of cell populations with lognormal distributions of radiopharmaceuticals and anticancer drugs

PURPOSE

Although the distribution of therapeutic agents within cell populations may appear uniform at the macroscopic level, the distribution at the multicellular level is nonuniform. As such, the mean agent concentration in tissue may not be a suitable quantity for use in predicting biological effects. Failure in chemotherapy and targeted radionuclide therapy has been attributed, in part, to the ubiquity of lognormal distributions of therapeutic agents. To improve capacity to predict biological response, this work develops approaches that determine the fate of a cell population on a cell-by-cell basis.

METHODS

Incorporation of the α-particle emitting radiochemical ((210)Po-citrate) and two anticancer drugs (daunomycin and doxorubicin) by Chinese hamster V79 cells was determined using flow cytometry. Monte Carlo simulation was used to estimate cell survival on the bases of mean and individual cell incorporation of each cytotoxic agent. The interrelationships between the Monte Carlo simulated cell survival and clonogenic cell survival were evaluated.

RESULTS

Cell survival obtained by Monte Carlo simulation based on individual cell incorporation was in good agreement with clonogenic cell survival for all agents. However, the agreement was poor when the simulation was carried out using the mean cell incorporation of the agents.

CONCLUSION

These data indicate that, with the aid of flow cytometry, Monte Carlo simulations can be used to predict the toxicity of therapeutic agents in a manner that takes into account the effects of lognormal and other nonuniform distributions of agents within cell populations.

Investigation of adaptive responses in bystander cells in 3D cultures containing tritium-labeled and unlabeled normal human fibroblasts

The study of radiation-induced bystander effects in normal human cells maintained in three-dimensional (3D) architecture provides more in vivo-like conditions and is relevant to human risk assessment. Linear energy transfer, dose and dose rate have been considered as critical factors in propagating radiation-induced effects. This investigation uses an in vitro 3D tissue culture model in which normal AG1522 human fibroblasts are grown in a carbon scaffold to investigate induction of a G(1) arrest in bystander cells that neighbor radiolabeled cells. Cell cultures were co-pulse-labeled with [(3)H]deoxycytidine ((3)HdC) to selectively irradiate a minor fraction of cells with 1-5 keV/microm beta particles and bromodeoxyuridine (BrdU) to identify the radiolabeled cells using immunofluorescence. The induction of a G(1) arrest was measured specifically in unlabeled cells (i.e. bystander cells) using a flow cytometry-based version of the cumulative labeling index assay. To investigate the relationship between bystander effects and adaptive responses, cells were challenged with an acute 4 Gy gamma-radiation dose after they had been kept under the bystander conditions described above for several hours, and the regulation of the radiation-induced G(1) arrest was measured selectively in bystander cells. When the average dose rate in (3)HdC-labeled cells (<16% of population) was 0.04-0.37 Gy/h (average accumulated dose 0.14-10 Gy), no statistically significant stressful bystander effects or adaptive bystander effects were observed as measured by magnitude of the G(1) arrest, micronucleus formation, or changes in mitochondrial membrane potential. Higher dose rates and/or higher LET may be required to observe stressful bystander effects in this experimental system, whereas lower dose rates and challenge doses may be required to detect adaptive bystander responses.

Implications for environmental health of multiple stressors

Recent insights into the mechanisms underlying the biological effects of low dose effects of ionising radiation have revealed that similar mechanisms can be induced by chemical stressors in the environment. This means that interactions between radiation and chemicals are likely and that the outcomes following mixed exposures to radiation and chemicals may not be predictable for human health, by consideration of single agent effects. Our understanding of the biological effects of low dose exposure has undergone a major paradigm shift. We now possess technologies which can detect very subtle changes in cells due to small exposures to radiation or other pollutants. We also understand much more now about cell communication, systems biology and the need to consider effects of low dose exposure at different hierarchical levels of organisation from molecules up to and including ecosystems. Furthermore we understand, at least in part, some of the mechanisms which drive low dose effects and which perpetuate these not only in the exposed organism but also in its progeny and in certain cases, its kin. This means that previously held views about safe doses or lack of harmful effects cannot be sustained. The International Commission on Radiological Protection (ICRP) and all national radiation and environmental protection organisations have always accepted a theoretical risk and have applied the precautionary principle and the LNT (linear-non-threshold) model which basically says that there is no safe dose of radiation. Therefore even in the absence of visible effects, exposure of people to radiation is strictly limited. This review will consider the historical context and the new discoveries and will focus on evidence for emergent effects after mixed exposures to combined stressors which include ionising radiation. The implications for regulation of low dose exposures to protect human health and environmental security will be discussed.

Lognormal distribution of cellular uptake of radioactivity: statistical analysis of alpha-particle track autoradiography

Recently, the distribution of radioactivity among a population of cells labeled with 210Po was shown to be well described by a lognormal (LN) distribution function (J Nucl Med. 2006;47:1049-1058) with the aid of autoradiography. To ascertain the influence of Poisson statistics on the interpretation of the autoradiographic data, the present work reports on a detailed statistical analysis of these earlier data.

METHODS

The measured distributions of alpha-particle tracks per cell were subjected to statistical tests with Poisson, LN, and Poisson-lognormal (P-LN) models.

RESULTS

The LN distribution function best describes the distribution of radioactivity among cell populations exposed to 0.52 and 3.8 kBq/mL of 210Po-citrate. When cells were exposed to 67 kBq/mL, the P-LN distribution function gave a better fit; however, the underlying activity distribution remained lognormal.

CONCLUSION

The present analysis generally provides further support for the use of LN distributions to describe the cellular uptake of radioactivity. Care should be exercised when analyzing autoradiographic data on activity distributions to ensure that Poisson processes do not distort the underlying LN distribution.

Log normal distribution of cellular uptake of radioactivity: implications for biologic responses to radiopharmaceuticals

It is widely recognized that radiopharmaceuticals are generally distributed nonuniformly in tissues. Such nonuniformities are observed over the entire range of spatial levels, ranging from organ to subcellular levels. The implications of nonuniform distributions of radioactivity for dosimetry, and ultimately for the biologic response of tissues containing radioactivity, have been investigated extensively. However, there is a paucity of experimental data on the distribution of cellular activity within a population of cells. In the present study, the distribution of activity per cell is experimentally determined and its implications for predicting biologic response are examined.

METHODS

Chinese hamster V79 cells were exposed to different concentrations of (210)Po-citrate. The radiolabeled cells were washed, seeded into culture dishes or glass slides, covered with photographic emulsion, and stored in an opaque container. Subsequently, the emulsion was developed, thereby resulting in observable alpha-particle tracks that were scored.

RESULTS

The distribution of activity per cell was found to be well described by a log normal distribution function. Theoretic modeling of cell survival as a function of mean activity per cell showed that survival curves differed substantially when the activity per cell was log normally distributed versus when it was assumed conventionally that every cell in the population contained the mean activity.

CONCLUSION

The present study provides experimental evidence of log normal cellular uptake of radioactivity. Theoretic calculations show that a log normal distribution of cellular activity can have a substantial impact on modeling the biologic response of cell populations.