Modeling the sequence dependence of differential antibody binding in the immune response to infectious disease.

Past studies have shown that incubation of human serum samples on high density peptide arrays followed by measurement of total antibody bound to each peptide sequence allows detection and discrimination of humoral immune responses to a variety of infectious diseases. This is true even though these arrays consist of peptides with near-random amino acid sequences that were not designed to mimic biological antigens. This "immunosignature" approach, is based on a statistical evaluation of the binding pattern for each sample but it ignores the information contained in the amino acid sequences that the antibodies are binding to. Here, similar array-based antibody profiles are instead used to train a neural network to model the sequence dependence of molecular recognition involved in the immune response of each sample. The binding profiles used resulted from incubating serum from 5 infectious disease cohorts (Hepatitis B and C, Dengue Fever, West Nile Virus and Chagas disease) and an uninfected cohort with 122,926 peptide sequences on an array. These sequences were selected quasi-randomly to represent an even but sparse sample of the entire possible combinatorial sequence space (~1012). This very sparse sampling of combinatorial sequence space was sufficient to capture a statistically accurate representation of the humoral immune response across the entire space. Processing array data using the neural network not only captures the disease-specific sequence-binding information but aggregates binding information with respect to sequence, removing sequence-independent noise and improving the accuracy of array-based classification of disease compared with the raw binding data. Because the neural network model is trained on all samples simultaneously, a highly condensed representation of the differential information between samples resides in the output layer of the model, and the column vectors from this layer can be used to represent each sample for classification or unsupervised clustering applications.

Integrating fluorescence computed tomography with optical sheet illumination for imaging of live single cells.

We present a new approach for three-dimensional (3D) live single-cell imaging with isotropic sub-micron spatial resolution using fluorescence computed tomography (fCT). A thin, highly inclined and laminated optical (HILO) sheet of light is used for fluorescence excitation in live single cells that are rotated around an axis perpendicular to the optical axis. During a full rotation, 400-500 two-dimensional (2D) projection images of the cell are acquired from multiple viewing perspectives by rapidly scanning the HILO light sheet along the optical axis. We report technical characteristics of the HILO approach and the results of a quantitative comparison with conventional epi fCT, demonstrating that HILO fCT offers significantly (about 17 times) reduced photobleaching and a two-fold improvement in 3D imaging contrast. We discuss potential application areas of the method for cell structure studies in live single cells with isotropic 3D spatial resolution.

Modulating short wavelength fluorescence with long wavelength light.

Two molecules in which the intensity of shorter-wavelength fluorescence from a strong fluorophore is modulated by longer-wavelength irradiation of an attached merocyanine-spirooxazine reverse photochromic moiety have been synthesized and studied. This unusual fluorescence behavior is the result of quenching of fluorophore fluorescence by the thermally stable, open, zwitterionic form of the spirooxazine, whereas the photogenerated closed, spirocyclic form has no effect on the fluorophore excited state. The population ratio of the closed and open forms of the spirooxazine is controlled by the intensity of the longer-wavelength modulated light. Both square wave and sine wave modulation were investigated. Because the merocyanine-spirooxazine is an unusual reverse photochrome with a thermally stable long-wavelength absorbing form and a short-wavelength absorbing photogenerated isomer with a very short lifetime, this phenomenon does not require irradiation of the molecules with potentially damaging ultraviolet light, and rapid modulation of fluorescence is possible. Molecules demonstrating these properties may be useful in fluorescent probes, as their use can discriminate between probe fluorescence and various types of adventitious "autofluorescence" from other molecules in the system being studied.

Quantitative characterization of preneoplastic progression using single-cell computed tomography and three-dimensional karyometry.

The development of morphological biosignatures to precisely characterize preneoplastic progression necessitates high-resolution three-dimensional (3D) cell imagery and robust image processing algorithms. We report on the quantitative characterization of nuclear structure alterations associated with preneoplastic progression in human esophageal epithelial cells using single-cell optical tomography and fully automated 3D karyometry. We stained cultured cells with hematoxylin and generated 3D images of individual cells by mathematically reconstructing 500 projection images acquired using optical absorption tomographic imaging. For 3D karyometry, we developed novel, fully automated algorithms to robustly segment the cellular, nuclear, and subnuclear components in the acquired cell images, and computed 41 quantitative morphological descriptors from these segmented volumes. In addition, we developed algorithms to quantify the spatial distribution and texture of the nuclear DNA. We applied our methods to normal, metaplastic, and dysplastic human esophageal epithelial cell lines, analyzing 100 cells per line. The 3D karyometric descriptors elucidated quantitative differences in morphology and enabled robust discrimination between cell lines on the basis of extracted morphological features. The morphometric hallmarks of cancer progression such as increased nuclear size, elevated nuclear content, and anomalous chromatin texture and distribution correlated with this preneoplastic progression model, pointing to the clinical use of our method for early cancer detection.

Quantitative single-cell gene expression measurements of multiple genes in response to hypoxia treatment.

Cell-to-cell heterogeneity in gene transcription plays a central role in a variety of vital cell processes. To quantify gene expression heterogeneity patterns among cells and to determine their biological significance, methods to measure gene expression levels at the single-cell level are highly needed. We report an experimental technique based on the DNA-intercalating fluorescent dye SYBR green for quantitative expression level analysis of up to ten selected genes in single mammalian cells. The method features a two-step procedure consisting of a step to isolate RNA from a single mammalian cell, synthesize cDNA from it, and a qPCR step. We applied the method to cell populations exposed to hypoxia, quantifying expression levels of seven different genes spanning a wide dynamic range of expression in randomly picked single cells. In the experiment, 72 single Barrett's esophageal epithelial (CP-A) cells, 36 grown under normal physiological conditions (controls) and 36 exposed to hypoxia for 30 min, were randomly collected and used for measuring the expression levels of 28S rRNA, PRKAA1, GAPDH, Angptl4, MT3, PTGES, and VEGFA genes. The results demonstrate that the method is sensitive enough to measure alterations in gene expression at the single-cell level, clearly showing heterogeneity within a cell population. We present technical details of the method development and implementation, and experimental results obtained by use of the procedure. We expect the advantages of this technique will facilitate further developments and advances in the field of single-cell gene expression profiling on a nanotechnological scale, and eventually as a tool for future point-of-care medical applications.

Intrinsic promoter nucleosome stability/dynamics variations support a novel targeting mechanism.

Genomic processes like transcription initiation typically involve the alteration of nucleosome structure, to expose DNA elements for regulatory factor binding. Nucleosome altering/modifying complexes have been identified, but precisely how these complexes find their specific targets remains unclear. We have shown that nucleosomes can exhibit significant DNA sequence-dependent stability and dynamics variations and have suggested that these inherent variations could facilitate nucleosome recognition and thus aid in specific targeting. Here, we confirm an important prediction of the model, namely, that stability and DNA dynamics features can correlate with the transcriptional involvement of specific promoter nucleosomes. A transcriptionally inert Mouse Mammary Tumor Virus promoter-region nucleosome (MMTV-D) has greater inherent stability than and reduced dynamics compared to a nearby nucleosome (MMTV-B) that is the initial target of transcription activation-associated processes on this promoter. MMTV-D stability could help direct activation-associated events to the less stable and more dynamic target, MMTV-B.

Nucleosomal stability and dynamics vary significantly when viewed by internal versus terminal labels.

Nucleosomes are a major impediment to regulatory factor activities and therefore to the operation of genomic processes in eukaryotes. One suggested mechanism for overcoming in vivo nucleosomal repression is factor-mediated removal of H2A/H2B from nucleosomes. Using nucleosomes labeled internally with FRET fluorophores, we previously observed significant, DNA sequence-dependent variation in stability and dynamics under conditions (subnanomolar concentrations) reported to produce H2A/H2B release from nucleosomes. Here, the same analytical approaches are repeated using 5S and MMTV-B nucleosomes containing FRET labels that monitor the terminal regions. The results show that stability and dynamics vary significantly within the nucleosome; terminally labeled constructs report significantly reduced stability and enhanced DNA dynamics compared to internally labeled constructs. The data also strongly support previous suggestions (1) that subnanomolar concentrations cause H2A/H2B release from nucleosomes, including the 5S, and (2) that stabilities in the internal regions of 5S and two promoter-derived nucleosomes (MMTV-B, GAL10) differ. Sequence-dependent nucleosome stability/dynamics differences could produce inherent variations in the accessibility of histone-associated DNA in vivo. Such intrinsic variation could also provide a mechanism for producing enhanced effects on specific nucleosomes by processes affecting large chromatin regions, thus facilitating the localized targeting of alterations to nucleosomes on crucial regulatory sequences. The results demonstrate clearly the importance of studying physiologically relevant nucleosomes.

Prolonged irradiation of enhanced cyan fluorescent protein or Cerulean can invalidate Forster resonance energy transfer measurements.

Since its discovery, green fluorescent protein (GFP) and its variants have proven to be a good and convenient fluorescent label for proteins: GFP and other visible fluorescent proteins (VFPs) can be fused selectively to the protein of interest by simple cloning techniques and develop fluorescence without additional cofactors. Among the steadily growing collection of VFPs, several pairs can be chosen that can serve as donor and acceptor fluorophores in Forster resonance energy transfer (FRET) experiments. Among them, the cyan fluorescent proteins (ECFP/Cerulean) and the enhanced yellow fluorescent protein (EYFP) are most commonly used. We show that ECFP and Cerulean have some disadvantages despite their common use: Upon irradiation with light intensities that are commonly used for intensity- and lifetime-based FRET measurements, both the fluorescence intensity and the fluorescence lifetime of ECFP and Cerulean decrease. This can hamper both intensity- and lifetime-based FRET measurements and emphasizes the need for control measurements to exclude these artifacts.

Simultaneous Multiparameter Cellular Energy Metabolism Profiling of Small Populations of Cells.

Functional and genomic heterogeneity of individual cells are central players in a broad spectrum of normal and disease states. Our knowledge about the role of cellular heterogeneity in tissue and organism function remains limited due to analytical challenges one encounters when performing single cell studies in the context of cell-cell interactions. Information based on bulk samples represents ensemble averages over populations of cells, while data generated from isolated single cells do not account for intercellular interactions. We describe a new technology and demonstrate two important advantages over existing technologies: first, it enables multiparameter energy metabolism profiling of small cell populations (<100 cells)-a sample size that is at least an order of magnitude smaller than other, commercially available technologies; second, it can perform simultaneous real-time measurements of oxygen consumption rate (OCR), extracellular acidification rate (ECAR), and mitochondrial membrane potential (MMP)-a capability not offered by any other commercially available technology. Our results revealed substantial diversity in response kinetics of the three analytes in dysplastic human epithelial esophageal cells and suggest the existence of varying cellular energy metabolism profiles and their kinetics among small populations of cells. The technology represents a powerful analytical tool for multiparameter studies of cellular function.

Multi-dimensional fluorescence lifetime and FRET measurements.

When and where proteins associate with each other in living cells are key questions in many biological research projects. One way to address these questions is to measure the extent of Förster resonance energy transfer (FRET) between proteins that have been labeled with appropriate donor and acceptor fluorophores. When both proteins interact, donor and acceptor fluorophores are brought into close vicinity so that the donor can transmit a part of its excitation energy to the acceptor. As a result, both the intensity and the lifetime of the donor fluorescence decrease, whereas the intensity of the acceptor emission increases. This offers different approaches to determine FRET efficiency: One is to detect changes in the intensity of donor and acceptor emission, the other is to measure changes in the lifetime of the donor molecule. One important advantage of the fluorescence lifetime approach is that it allows to distinguish between free and associated donor molecules. However, like intensity measurements it lacks an intrinsic control ensuring that changes in the measured parameters are only due to FRET and not other quenching processes. Here, we show how this limitation can be overcome by spectrally resolved fluorescence lifetime measurements in the time domain. One technique is based on a streak camera system, the other technique is based on a time-correlated-single-photon-counting approach. Both approaches allow biologists to record both donor and acceptor fluorescence emitted by the sample in a single measurement.

A versatile method for dynamically controlled patterning of small populations of epithelial cells on substrates via non-contact piezoelectric inkjet printing.

Intercellular interactions play a central role at the tissue and whole organism level modulating key cellular functions in normal and disease states. Studies of cell-cell communications are challenging due to ensemble averaging effects brought about by intrinsic heterogeneity in cellular function which requires such studies to be conducted with small populations of cells. Most of the current methods for producing and studying such small cell populations are complex to implement and require skilled personnel limiting their widespread utility in biomedical research labs. We present a simple and rapid method to produce small populations with varying size of epithelial cells (10-50 cells/population) with high-throughput (~ 1 population/second) on flat surfaces via patterning of extracellular matrix (ECM) proteins and random seeding of cells. We demonstrate that despite inherent limitations of non-contact, drop-on-demand piezoelectric inkjet printing for protein patterning, varying mixtures of ECM proteins can be deposited with high reproducibility and level of control on glass substrates using a set of dynamically adjustable optimized deposition parameters. We demonstrate high consistency for the number of cells per population (~1 cell standard error of mean), the population's size (~0.2 coefficient of variation) and shape, as well as accurate spatial placement of and distance between colonies of a panel of metaplastic and dysplastic esophageal epithelial cells with differing adhesion and motility characteristics. The number of cells per colony, colony size and shape can be varied by dynamically varying the amount of ECM proteins deposited per spatial location and the number of spatial locations on the substrate. The method is applicable to a broad range of biological and biomedical studies including cell-cell communications, cellular microenvironment, migration, and stimulus response.

Optical computed tomography for spatially isotropic four-dimensional imaging of live single cells.

Quantitative three-dimensional (3D) computed tomography (CT) imaging of living single cells enables orientation-independent morphometric analysis of the intricacies of cellular physiology. Since its invention, x-ray CT has become indispensable in the clinic for diagnostic and prognostic purposes due to its quantitative absorption-based imaging in true 3D that allows objects of interest to be viewed and measured from any orientation. However, x-ray CT has not been useful at the level of single cells because there is insufficient contrast to form an image. Recently, optical CT has been developed successfully for fixed cells, but this technology called Cell-CT is incompatible with live-cell imaging due to the use of stains, such as hematoxylin, that are not compatible with cell viability. We present a novel development of optical CT for quantitative, multispectral functional 4D (three spatial + one spectral dimension) imaging of living single cells. The method applied to immune system cells offers truly isotropic 3D spatial resolution and enables time-resolved imaging studies of cells suspended in aqueous medium. Using live-cell optical CT, we found a heterogeneous response to mitochondrial fission inhibition in mouse macrophages and differential basal remodeling of small (0.1 to 1 fl) and large (1 to 20 fl) nuclear and mitochondrial structures on a 20- to 30-s time scale in human myelogenous leukemia cells. Because of its robust 3D measurement capabilities, live-cell optical CT represents a powerful new tool in the biomedical research field.

A platform for high-throughput bioenergy production phenotype characterization in single cells.

Driven by an increasing number of studies demonstrating its relevance to a broad variety of disease states, the bioenergy production phenotype has been widely characterized at the bulk sample level. Its cell-to-cell variability, a key player associated with cancer cell survival and recurrence, however, remains poorly understood due to ensemble averaging of the current approaches. We present a technology platform for performing oxygen consumption and extracellular acidification measurements of several hundreds to 1,000 individual cells per assay, while offering simultaneous analysis of cellular communication effects on the energy production phenotype. The platform comprises two major components: a tandem optical sensor for combined oxygen and pH detection, and a microwell device for isolation and analysis of single and few cells in hermetically sealed sub-nanoliter chambers. Our approach revealed subpopulations of cells with aberrant energy production profiles and enables determination of cellular response variability to electron transfer chain inhibitors and ion uncouplers.

Transcriptional regulation by normal epithelium of premalignant to malignant progression in Barrett's esophagus.

In carcinogenesis, intercellular interactions within and between cell types are critical but remain poorly understood. We present a study on intercellular interactions between normal and premalignant epithelial cells and their functional relevance in the context of premalignant to malignant progression in Barrett's esophagus. Using whole transcriptome profiling we found that in the presence of normal epithelial cells, dysplastic cells but not normal cells, exhibit marked down-regulation of a number of key signaling pathways, including the transforming growth factor beta (TGFß) and epithelial growth factor (EGF). Functional assays revealed both cell types showed repressed proliferation and significant changes in motility (speed, displacement and directionality) as a result of interactions between the two cell types. Cellular interactions appear to be mediated through both direct cell-cell contact and secreted ligands. The findings of this study are important in that they reveal, for the first time, the effects of cellular communication on gene expression and cellular function between premalignant (dysplastic) epithelial cells and their normal counterparts.

Interaction of PSD-95 with potassium channels visualized by fluorescence lifetime-based resonance energy transfer imaging.

Resonance energy transfer (RET) has been extensively used to estimate the distance between two different fluorophores. This study demonstrates how protein-protein interactions can be visualized and quantified in living cells by time-correlated single-photon counting (TCSPC) imaging techniques that exploit the RET between appropriate fluorescent labels. We used this method to investigate the association of the potassium inward rectifier channel Kir2.1 and the neuronal PDZ protein PSD-95, which has been implicated in subcellular targeting and clustering of ion channels. Our data show that the two proteins not only colocalize within clusters but also interact with each other. Moreover, the data allow a spatially resolved quantification of this protein-protein interaction with respect to the relative number and the proximity between interacting molecules. Depending on the subcellular localization, a fraction of 20 to 60% of PSD-95 molecules interacted with Kir2.1 channels, approximating their fluorescent labels by less than 5 nm.

A minimally invasive method for retrieving single adherent cells of different types from cultures.

The field of single-cell analysis has gained a significant momentum over the last decade. Separation and isolation of individual cells is an indispensable step in almost all currently available single-cell analysis technologies. However, stress levels introduced by such manipulations remain largely unstudied. We present a method for minimally invasive retrieval of selected individual adherent cells of different types from cell cultures. The method is based on a combination of mechanical (shear flow) force and biochemical (trypsin digestion) treatment. We quantified alterations in the transcription levels of stress response genes in individual cells exposed to varying levels of shear flow and trypsinization. We report optimal temperature, RNA preservation reagents, shear force and trypsinization conditions necessary to minimize changes in the stress-related gene expression levels. The method and experimental findings are broadly applicable and can be used by a broad research community working in the field of single cell analysis.

Single-cell analysis reveals early manifestation of cancerous phenotype in pre-malignant esophageal cells.

Cellular heterogeneity plays a pivotal role in a variety of functional processes in vivo including carcinogenesis. However, our knowledge about cell-to-cell diversity and how differences in individual cells manifest in alterations at the population level remains very limited mainly due to the lack of appropriate tools enabling studies at the single-cell level. We present a study on changes in cellular heterogeneity in the context of pre-malignant progression in response to hypoxic stress. Utilizing pre-malignant progression of Barrett's esophagus (BE) as a disease model system we studied molecular mechanisms underlying the progression from metaplastic to dysplastic (pre-cancerous) stage. We used newly developed methods enabling measurements of cell-to-cell differences in copy numbers of mitochondrial DNA, expression levels of a set of mitochondrial and nuclear genes involved in hypoxia response pathways, and mitochondrial membrane potential. In contrast to bulk cell studies reported earlier, our study shows significant differences between metaplastic and dysplastic BE cells in both average values and single-cell parameter distributions of mtDNA copy numbers, mitochondrial function, and mRNA expression levels of studied genes. Based on single-cell data analysis, we propose that mitochondria may be one of the key factors in pre-malignant progression in BE.

A physical sciences network characterization of non-tumorigenic and metastatic cells.

To investigate the transition from non-cancerous to metastatic from a physical sciences perspective, the Physical Sciences-Oncology Centers (PS-OC) Network performed molecular and biophysical comparative studies of the non-tumorigenic MCF-10A and metastatic MDA-MB-231 breast epithelial cell lines, commonly used as models of cancer metastasis. Experiments were performed in 20 laboratories from 12 PS-OCs. Each laboratory was supplied with identical aliquots and common reagents and culture protocols. Analyses of these measurements revealed dramatic differences in their mechanics, migration, adhesion, oxygen response, and proteomic profiles. Model-based multi-omics approaches identified key differences between these cells' regulatory networks involved in morphology and survival. These results provide a multifaceted description of cellular parameters of two widely used cell lines and demonstrate the value of the PS-OC Network approach for integration of diverse experimental observations to elucidate the phenotypes associated with cancer metastasis.

A statistical framework for multiparameter analysis at the single-cell level.

Phenotypic characterization of individual cells provides crucial insights into intercellular heterogeneity and enables access to information that is unavailable from ensemble averaged, bulk cell analyses. Single-cell studies have attracted significant interest in recent years and spurred the development of a variety of commercially available and research-grade technologies. To quantify cell-to-cell variability of cell populations, we have developed an experimental platform for real-time measurements of oxygen consumption (OC) kinetics at the single-cell level. Unique challenges inherent to these single-cell measurements arise, and no existing data analysis methodology is available to address them. Here we present a data processing and analysis method that addresses challenges encountered with this unique type of data in order to extract biologically relevant information. We applied the method to analyze OC profiles obtained with single cells of two different cell lines derived from metaplastic and dysplastic human Barrett's esophageal epithelium. In terms of method development, three main challenges were considered for this heterogeneous dynamic system: (i) high levels of noise, (ii) the lack of a priori knowledge of single-cell dynamics, and (iii) the role of intercellular variability within and across cell types. Several strategies and solutions to address each of these three challenges are presented. The features such as slopes, intercepts, breakpoint or change-point were extracted for every OC profile and compared across individual cells and cell types. The results demonstrated that the extracted features facilitated exposition of subtle differences between individual cells and their responses to cell-cell interactions. With minor modifications, this method can be used to process and analyze data from other acquisition and experimental modalities at the single-cell level, providing a valuable statistical framework for single-cell analysis.

Isotropic 3D nuclear morphometry of normal, fibrocystic and malignant breast epithelial cells reveals new structural alterations.

BACKGROUND: Grading schemes for breast cancer diagnosis are predominantly based on pathologists' qualitative assessment of altered nuclear structure from 2D brightfield microscopy images. However, cells are three-dimensional (3D) objects with features that are inherently 3D and thus poorly characterized in 2D. Our goal is to quantitatively characterize nuclear structure in 3D, assess its variation with malignancy, and investigate whether such variation correlates with standard nuclear grading criteria. METHODOLOGY: We applied micro-optical computed tomographic imaging and automated 3D nuclear morphometry to quantify and compare morphological variations between human cell lines derived from normal, benign fibrocystic or malignant breast epithelium. To reproduce the appearance and contrast in clinical cytopathology images, we stained cells with hematoxylin and eosin and obtained 3D images of 150 individual stained cells of each cell type at sub-micron, isotropic resolution. Applying volumetric image analyses, we computed 42 3D morphological and textural descriptors of cellular and nuclear structure. PRINCIPAL FINDINGS: We observed four distinct nuclear shape categories, the predominant being a mushroom cap shape. Cell and nuclear volumes increased from normal to fibrocystic to metastatic type, but there was little difference in the volume ratio of nucleus to cytoplasm (N/C ratio) between the lines. Abnormal cell nuclei had more nucleoli, markedly higher density and clumpier chromatin organization compared to normal. Nuclei of non-tumorigenic, fibrocystic cells exhibited larger textural variations than metastatic cell nuclei. At p<0.0025 by ANOVA and Kruskal-Wallis tests, 90% of our computed descriptors statistically differentiated control from abnormal cell populations, but only 69% of these features statistically differentiated the fibrocystic from the metastatic cell populations. CONCLUSIONS: Our results provide a new perspective on nuclear structure variations associated with malignancy and point to the value of automated quantitative 3D nuclear morphometry as an objective tool to enable development of sensitive and specific nuclear grade classification in breast cancer diagnosis.