Single-cell analysis of the physiology of mechanosensation in bacteria

Escherichia coli is one of the best studied living organisms and a model system for many biophysical investigations. Despite countless discoveries of the details of its physiology, we still lack a holistic understanding of how these bacteria react to changes in their environment. One of the most important examples is their response to osmotic shock. One of the mechanistic elements protecting cell integrity upon exposure to sudden changes of osmolarity is the presence of mechanosensitive channels in the cell membrane. These channels are believed to act as tension release valves protecting the inner membrane from rupturing. This thesis presents an experimental study of various aspects of mechanosensation in bacteria. We examine cell survival after osmotic shock and how the number of MscL (Mechanosensitive channel of Large conductance) channels expressed in a cell influences its physiology. We developed an assay that allows real-time monitoring of the rate of the osmotic challenge and direct observation of cell morphology during and after the exposure to osmolarity change. The work described in this thesis introduces tools that can be used to quantitatively determine at the single-cell level the number of expressed proteins (in this case MscL channels) as a function of, e.g., growth conditions. The improvement in our quantitative description of mechanosensation in bacteria allows us to address many, so far unsolved, problems, like the minimal number of channels needed for survival, and can begin to paint a clearer picture of why there are so many distinct types of mechanosensitive channels.

Sensitivity map of laser tweezers Raman spectroscopy for single-cell analysis of colorectal cancer

Raman spectroscopy on single, living epithelial cells captured in a laser trap is shown to have diagnostic power over colorectal cancer. This new single-cell technology comprises three major components: primary culture processing of human tissue samples to produce single-cell suspensions, Raman detection on singly trapped cells, and diagnoses of the cells by artificial neural network classifications. it is compared with DNA flow cytometry for similarities and differences. Its advantages over tissue Raman spectroscopy are also discussed. In the actual construction of a diagnostic model for colorectal cancer, real patient data were taken to generate a training set of 320 Raman spectra and, a test set of 80. By incorporating outlier corrections to a conventional binary neural classifier, our network accomplished significantly better predictions than logistic regressions, with sensitivity improved from 77.5% to 86.3% and specificity improved from 81.3% to 86.3% for the training set and moderate improvements for the test set. Most important, the network approach enables a sensitivity map analysis to quantitate the relevance of each Raman band to the normal-to-cancer transform at the cell level. Our technique has direct clinic applications for diagnosing cancers and basic science potential in the study of cell dynamics of carcinogenesis. (C) 2007 Society of Photo-Optical Instrumentation Engineers.

Sensitivity map of laser tweezers Raman spectroscopy for single-cell analysis of colorectal cancer

Raman spectroscopy on single, living epithelial cells captured in a laser trap is shown to have diagnostic power over colorectal cancer. This new single-cell technology comprises three major components: primary culture processing of human tissue samples to produce single-cell suspensions, Raman detection on singly trapped cells, and diagnoses of the cells by artificial neural network classifications. it is compared with DNA flow cytometry for similarities and differences. Its advantages over tissue Raman spectroscopy are also discussed. In the actual construction of a diagnostic model for colorectal cancer, real patient data were taken to generate a training set of 320 Raman spectra and, a test set of 80. By incorporating outlier corrections to a conventional binary neural classifier, our network accomplished significantly better predictions than logistic regressions, with sensitivity improved from 77.5% to 86.3% and specificity improved from 81.3% to 86.3% for the training set and moderate improvements for the test set. Most important, the network approach enables a sensitivity map analysis to quantitate the relevance of each Raman band to the normal-to-cancer transform at the cell level. Our technique has direct clinic applications for diagnosing cancers and basic science potential in the study of cell dynamics of carcinogenesis. (C) 2007 Society of Photo-Optical Instrumentation Engineers.

Rubisco small subunit, chlorophyll a/b-binding protein and sucrose : fructan-6-fructosyl transferase gene expression and sugar status in single barley leaf cells in situ. Cell type specificity and induction by light

Chungui Lu, Olga A. Koroleva, John F. Farrar, Joe Gallagher, Chris J. Pollock, and A. Deri Tomos (2002). Rubisco small subunit, chlorophyll a/b-binding protein and sucrose : fructan-6-fructosyl transferase gene expression and sugar status in single barley leaf cells in situ. Cell type specificity and induction by light. Plant Physiology, 130 (3) pp.1335-1348 Sponsorship: BBSRC RAE2008

RNA interference in adult Ascaris suum - an opportunity for the development of a functional genomics platform that supports organism-, tissue- and cell-based biology in a nematode parasite

The sustainable control of animal parasitic nematodes requires the development of efficient functional genomics platforms to facilitate target validation and enhance anthelmintic discovery. Unfortunately, the utility of RNA interference (RNAi) for the validation of novel drug targets in nematode parasites remains problematic. Ascaris suum is an important veterinary parasite and a zoonotic pathogen. Here we show that adult A. suum is RNAi competent, and highlight the induction, spread and consistency of RNAi across multiple tissue types. This platform provides a new opportunity to undertake whole organism-, tissue- and cell-level gene function studies to enhance target validation processes for nematode parasites of veterinary/medical significance.

Dynamic single cell measurements of kinase activity by synthetic kinase activity relocation sensors.

BACKGROUND: Mitogen activated protein kinases (MAPK) play an essential role in integrating extra-cellular signals and intra-cellular cues to allow cells to grow, adapt to stresses, or undergo apoptosis. Budding yeast serves as a powerful system to understand the fundamental regulatory mechanisms that allow these pathways to combine multiple signals and deliver an appropriate response. To fully comprehend the variability and dynamics of these signaling cascades, dynamic and quantitative single cell measurements are required. Microscopy is an ideal technique to obtain these data; however, novel assays have to be developed to measure the activity of these cascades. RESULTS: We have generated fluorescent biosensors that allow the real-time measurement of kinase activity at the single cell level. Here, synthetic MAPK substrates were engineered to undergo nuclear-to-cytoplasmic relocation upon phosphorylation of a nuclear localization sequence. Combination of fluorescence microscopy and automated image analysis allows the quantification of the dynamics of kinase activity in hundreds of single cells. A large heterogeneity in the dynamics of MAPK activity between individual cells was measured. The variability in the mating pathway can be accounted for by differences in cell cycle stage, while, in the cell wall integrity pathway, the response to cell wall stress is independent of cell cycle stage. CONCLUSIONS: These synthetic kinase activity relocation sensors allow the quantification of kinase activity in live single cells. The modularity of the architecture of these reporters will allow their application in many other signaling cascades. These measurements will allow to uncover new dynamic behaviour that previously could not be observed in population level measurements.

From a discrete to a continuum model of cell dynamics in one dimension

Multiscale modeling is emerging as one of the key challenges in mathematical biology. However, the recent rapid increase in the number of modeling methodologies being used to describe cell populations has raised a number of interesting questions. For example, at the cellular scale, how can the appropriate discrete cell-level model be identified in a given context? Additionally, how can the many phenomenological assumptions used in the derivation of models at the continuum scale be related to individual cell behavior? In order to begin to address such questions, we consider a discrete one-dimensional cell-based model in which cells are assumed to interact via linear springs. From the discrete equations of motion, the continuous Rouse [P. E. Rouse, J. Chem. Phys. 21, 1272 (1953)] model is obtained. This formalism readily allows the definition of a cell number density for which a nonlinear "fast" diffusion equation is derived. Excellent agreement is demonstrated between the continuum and discrete models. Subsequently, via the incorporation of cell division, we demonstrate that the derived nonlinear diffusion model is robust to the inclusion of more realistic biological detail. In the limit of stiff springs, where cells can be considered to be incompressible, we show that cell velocity can be directly related to cell production. This assumption is frequently made in the literature but our derivation places limits on its validity. Finally, the model is compared with a model of a similar form recently derived for a different discrete cell-based model and it is shown how the different diffusion coefficients can be understood in terms of the underlying assumptions about cell behavior in the respective discrete models.

Electrochemical imaging of living cell metabolism: investigation on Warburg effect in cancer

Cancer is one of the principal causes of death in the world; almost 8.2 million of deaths were counted in 2012. Emerging evidences indicate that most of the tumors have an increased glycolytic rate and a detriment of oxidative phosphorylation to support abnormal cell proliferation; this phenomenon is known as aerobic glycolysis or Warburg effect. This switching toward glycolysis implies that cancer tissues metabolize approximately tenfold more glucose to lactate in a given time and the amount of lactate released from cancer tissues is much greater than from normal ones. In view of these fundamental discoveries alterations of the cellular metabolism should be considered a crucial hallmark of cancer. Therefore, the investigation of the metabolic differences between normal and transformed cells is important in cancer research and it might find clinical applications. The aim of the project was to investigate the cellular metabolic alterations at single cell level, by monitoring glucose and lactate, in order to provide a better insight in cancer research. For this purpose, electrochemical techniques have been applied. Enzyme-based electrode biosensors for lactate and glucose were –ad hoc- optimized within the project and used as probes for Scanning Electrochemical Microscopy (SECM). The UME biosensor manufacturing and optimization represented a consistent part of the work and a full description of the sensor preparation protocols and of the characterization methods employed is reported. This set-up (SECM used with microbiosensor probes) enabled the non-invasive study of cellular metabolism at single cell level. The knowledge of cancer cell metabolism is required to design more efficient treatment strategies.

Protein quantification from complex protein mixtures using a proteomics methodology with single-cell resolution

We have developed an extremely sensitive technique, termed immuno-detection amplified by T7 RNA polymerase (IDAT) that is capable of monitoring proteins, lipids, and metabolites and their modifications at the single-cell level. A double-stranded oligonucleotide containing the T7 promoter is conjugated to an antibody (Ab), and then T7 RNA polymerase is used to amplify RNA from the double-stranded oligonucleotides coupled to the Ab in the Ab-antigen complex. By using this technique, we are able to detect the p185her2/neu receptor from the crude lysate of T6–17 cells at 10−13 dilution, which is 109-fold more sensitive than the conventional ELISA method. Single-chain Fv fragments or complementarity determining region peptides of the Ab also can be substituted for the Ab in IDAT. In a modified protocol, the oligonucleotide has been coupled to an Ab against a common epitope to create a universal detector species. With the linear amplification ability of T7 RNA polymerase, IDAT represents a significant improvement over immuno-PCR in terms of sensitivity and has the potential to provide a robotic platform for proteomics.

Arrested development of embryonic red cell precursors in mouse embryos lacking transcription factor GATA-1.

The X chromosome-linked transcription factor GATA-1 is expressed specifically in erythroid, mast, megakaryocyte, and eosinophil lineages, as well as in hematopoietic progenitors. Prior studies revealed that gene-disrupted GATA-1- embryonic stem cells give rise to adult (or definitive) erythroid precursors arrested at the proerythroblast stage in vitro and fail to contribute to adult red blood cells in chimeric mice but did not clarify a role in embryonic (or yolk sac derived) erythroid cells. To examine the consequences of GATA-1 loss on embryonic erythropoiesis in vivo, we inactivated the GATA-1 locus in embryonic stem cells by gene targeting and transmitted the mutated allele through the mouse germ line. Male GATA-1- embryos die between embryonic day 10.5 and 11.5 (E10.5-E11.5) of gestation. At E9.5, GATA-1- embryos exhibit extreme pallor yet contain embryonic erythroid cells arrested at an early proerythroblast-like stage of their development. Embryos stain weakly with benzidine reagent, and yolk sac cells express globin RNAs, indicating globin gene activation in the absence of GATA-1. Female heterozygotes (GATA-1+/-) are born pale due to random inactivation of the X chromosome bearing the normal allele. However, these mice recover during the neonatal period, presumably as a result of in vivo selection for progenitors able to express GATA-1. Our findings conclusively establish the essential role for GATA-1 in erythropoiesis within the context of the intact developing mouse and further demonstrate that the block to cellular maturation is similar in GATA-1- embryonic and definitive erythroid precursors. Moreover, the recovery of GATA-1+/- mice from anemia seen at birth provides evidence indicating a role for GATA-1 at the hematopoietic progenitor cell level.

In situ isolation of mRNA from individual plant cells: creation of cell-specific cDNA libraries.

A method for isolating and cloning mRNA populations from individual cells in living, intact plant tissues is described. The contents of individual cells were aspirated into micropipette tips filled with RNA extraction buffer. The mRNA from these cells was purified by binding to oligo(dT)-linked magnetic beads and amplified on the beads using reverse transcription and PCR. The cell-specific nature of the isolated mRNA was verified by creating cDNA libraries from individual tomato leaf epidermal and guard cell mRNA preparations. In testing the reproducibility of the method, we discovered an inherent limitation of PCR amplification from small amounts of any complex template. This phenomenon, which we have termed the "Monte Carlo" effect, is created by small and random differences in amplification efficiency between individual templates in an amplifying cDNA population. The Monte Carlo effect is dependent upon template concentration: the lower the abundance of any template, the less likely its true abundance will be reflected in the amplified library. Quantitative assessment of the Monte Carlo effect revealed that only rare mRNAs (< or = 0.04% of polyadenylylated mRNA) exhibited significant variation in amplification at the single-cell level. The cDNA cloning approach we describe should be useful for a broad range of cell-specific biological applications.

Light sheet fluorescence microscopy for in situ cell interaction analysis in mouse lymph nodes.

Reactive lymph nodes (LNs) are sites where pMHC-loaded dendritic cells (DCs) interact with rare cognate T cells, leading to their clonal expansion. While DC interactions with T cell subsets critically shape the ensuing immune response, surprisingly little is known on their spatial orchestration at physiologically T cell low precursor frequencies. Light sheet fluorescence microscopy and one of its implementations, selective plane illumination microscopy (SPIM), is a powerful method to obtain precise spatial information of entire organs of 0.5-10mm diameter, the size range of murine LNs. Yet, its usefulness for immunological research has thus far not been comprehensively explored. Here, we have tested and defined protocols that preserve fluorescent protein function during lymphoid tissue clearing required for SPIM. Reconstructions of SPIM-generated 3D data sets revealed that calibrated numbers of adoptively transferred T cells and DCs are successfully detected at a single cell level within optically cleared murine LNs. Finally, we define parameters to quantify specific interactions between antigen-specific T cells and pMHC-bearing DCs in murine LNs. In sum, our studies describe the successful application of light sheet fluorescence microscopy to immunologically relevant tissues.

Statistical Hurdle Models for Single Cell Gene Expression: Differential Expression and Graphical Modeling

Thesis (Ph.D.)--University of Washington, 2016-06

Microfluidics-based single-cell functional proteomics microchip for portraying protein signal transduction networks within the framework of physicochemical principles, with applications in fundamental and translational cancer research

Single-cell functional proteomics assays can connect genomic information to biological function through quantitative and multiplex protein measurements. Tools for single-cell proteomics have developed rapidly over the past 5 years and are providing unique opportunities. This thesis describes an emerging microfluidics-based toolkit for single cell functional proteomics, focusing on the development of the single cell barcode chips (SCBCs) with applications in fundamental and translational cancer research.

The microchip designed to simultaneously quantify a panel of secreted, cytoplasmic and membrane proteins from single cells will be discussed at the beginning, which is the prototype for subsequent proteomic microchips with more sophisticated design in preclinical cancer research or clinical applications. The SCBCs are a highly versatile and information rich tool for single-cell functional proteomics. They are based upon isolating individual cells, or defined number of cells, within microchambers, each of which is equipped with a large antibody microarray (the barcode), with between a few hundred to ten thousand microchambers included within a single microchip. Functional proteomics assays at single-cell resolution yield unique pieces of information that significantly shape the way of thinking on cancer research. An in-depth discussion about analysis and interpretation of the unique information such as functional protein fluctuations and protein-protein correlative interactions will follow.

The SCBC is a powerful tool to resolve the functional heterogeneity of cancer cells. It has the capacity to extract a comprehensive picture of the signal transduction network from single tumor cells and thus provides insight into the effect of targeted therapies on protein signaling networks. We will demonstrate this point through applying the SCBCs to investigate three isogenic cell lines of glioblastoma multiforme (GBM).

The cancer cell population is highly heterogeneous with high-amplitude fluctuation at the single cell level, which in turn grants the robustness of the entire population. The concept that a stable population existing in the presence of random fluctuations is reminiscent of many physical systems that are successfully understood using statistical physics. Thus, tools derived from that field can probably be applied to using fluctuations to determine the nature of signaling networks. In the second part of the thesis, we will focus on such a case to use thermodynamics-motivated principles to understand cancer cell hypoxia, where single cell proteomics assays coupled with a quantitative version of Le Chatelier's principle derived from statistical mechanics yield detailed and surprising predictions, which were found to be correct in both cell line and primary tumor model.

The third part of the thesis demonstrates the application of this technology in the preclinical cancer research to study the GBM cancer cell resistance to molecular targeted therapy. Physical approaches to anticipate therapy resistance and to identify effective therapy combinations will be discussed in detail. Our approach is based upon elucidating the signaling coordination within the phosphoprotein signaling pathways that are hyperactivated in human GBMs, and interrogating how that coordination responds to the perturbation of targeted inhibitor. Strongly coupled protein-protein interactions constitute most signaling cascades. A physical analogy of such a system is the strongly coupled atom-atom interactions in a crystal lattice. Similar to decomposing the atomic interactions into a series of independent normal vibrational modes, a simplified picture of signaling network coordination can also be achieved by diagonalizing protein-protein correlation or covariance matrices to decompose the pairwise correlative interactions into a set of distinct linear combinations of signaling proteins (i.e. independent signaling modes). By doing so, two independent signaling modes – one associated with mTOR signaling and a second associated with ERK/Src signaling have been resolved, which in turn allow us to anticipate resistance, and to design combination therapies that are effective, as well as identify those therapies and therapy combinations that will be ineffective. We validated our predictions in mouse tumor models and all predictions were borne out.

In the last part, some preliminary results about the clinical translation of single-cell proteomics chips will be presented. The successful demonstration of our work on human-derived xenografts provides the rationale to extend our current work into the clinic. It will enable us to interrogate GBM tumor samples in a way that could potentially yield a straightforward, rapid interpretation so that we can give therapeutic guidance to the attending physicians within a clinical relevant time scale. The technical challenges of the clinical translation will be presented and our solutions to address the challenges will be discussed as well. A clinical case study will then follow, where some preliminary data collected from a pediatric GBM patient bearing an EGFR amplified tumor will be presented to demonstrate the general protocol and the workflow of the proposed clinical studies.

Plasticity in leaf-level water relations of tropical rainforest trees in response to experimental drought.

The tropics are predicted to become warmer and drier, and understanding the sensitivity of tree species to drought is important for characterizing the risk to forests of climate change. This study makes use of a long-term drought experiment in the Amazon rainforest to evaluate the role of leaf-level water relations, leaf anatomy and their plasticity in response to drought in six tree genera. The variables (osmotic potential at full turgor, turgor loss point, capacitance, elastic modulus, relative water content and saturated water content) were compared between seasons and between plots (control and through-fall exclusion) enabling a comparison between short- and long-term plasticity in traits. Leaf anatomical traits were correlated with water relation parameters to determine whether water relations differed among tissues. The key findings were: osmotic adjustment occurred in response to the long-term drought treatment; species resistant to drought stress showed less osmotic adjustment than drought-sensitive species; and water relation traits were correlated with tissue properties, especially the thickness of the abaxial epidermis and the spongy mesophyll. These findings demonstrate that cell-level water relation traits can acclimate to long-term water stress, and highlight the limitations of extrapolating the results of short-term studies to temporal scales associated with climate change.