Development of a whole cell biochip for toxicant detection.

In the development of biosensors for ecotoxicity testing it is desirable to produce a small, portable system that can be used in the field. Toxicity testing using bioluminescence is widely used in the laboratory utilising natural and genetically modified (lux/ luc-marked) bacteria and other microorganisms. It is currently not possible to use genetically manipulated microorganisms in field testing and a biosensor, therefore, that incorporates naturally luminescent organisms may be preferred. In the development of a biosensor it is aimed to use the naturally luminescent bacterium Vibrio fischeri as a toxicity detection system on a chip. The bacterium will be immobilised in a polymeric matrix. Current work deals with the optimisation of light output and light preservation within the bacterium prior to immobilisation in polyvinyl alcohol. An examination of a range of physicochemical conditions within the polymer will be made, including cell density, thickness of polymer film, growth and light induction environment, and, preservation conditions, in order to develop a testing system giving consistent results over the lifetime of the biosensor. Data will be presented on light production using different culture media for the growth of V. fischeri and retention of light under immobilised conditions. .

Neuronal Assembly Detection and Cell Membership Specification by Principal Component Analysis

LOPES-DOS-SANTOS, V. , CONDE-OCAZIONEZ, S. ; NICOLELIS, M. A. L. , RIBEIRO, S. T. , TORT, A. B. L. . Neuronal assembly detection and cell membership specification by principal component analysis. Plos One, v. 6, p. e20996, 2011.

Detecting cell assemblies in large neuronal populations

Recent progress in the technology for single unit recordings has given the neuroscientific community theopportunity to record the spiking activity of large neuronal populations. At the same pace, statistical andmathematical tools were developed to deal with high-dimensional datasets typical of such recordings.A major line of research investigates the functional role of subsets of neurons with significant co-firingbehavior: the Hebbian cell assemblies. Here we review three linear methods for the detection of cellassemblies in large neuronal populations that rely on principal and independent component analysis.Based on their performance in spike train simulations, we propose a modified framework that incorpo-rates multiple features of these previous methods. We apply the new framework to actual single unitrecordings and show the existence of cell assemblies in the rat hippocampus, which typically oscillate attheta frequencies and couple to different phases of the underlying field rhythm

Cell-cell communication in three dimensional microenvironments

Cellular behavior is dependent on a variety of extracellular cues required for normal tissue function, wound healing, and activation of the immune system. Removed from their in vivo microenvironment and cultured in vitro, cells lose many environmental cues and that may result in abberant behavior, making it difficult to study cellular processes. In order to mimic native tissue environments, optical tweezer and microfluidic technologies were used to place cells within defined areas of the culture environment. To provide three dimensional supports found in natural tissues, hydrogel scaffolds of poly (ethylene glycol) diacrylate and the basement membrane matrix Matrigel were used. Optical tweezer technology allowed precision placement and formation of homotypic and heterotypic arrays of human U937, HEK 293, and porcine mesenchymal stem cells. Alternatively, two microfluidic devices were designed to pattern Matrigel scaffolds. The first microfluidic device utilized laminar flow to spatially pattern multiple cell types within the device. Gradients of soluble molecules were then be formed and manipulated across the Matrigel scaffolds. Patterning Matrigel using laminar flow techniques require microfluidic expertise and do not produce consistent patterning conditions, limiting their use difficult in most cell culture laboratories. Thus, a buried Matrigel polydimethylsiloxane (PDMS) device was developed for spatial patterning of biological scaffolds. Matrigel is injected into micron sized channels of PDMS fabricated by soft lithography and allowed to thermally cure. Following curing, a second PDMS device was placed on top of the buried Matrigel channels to support media flow. In order to validate these systems, a cell-cell communication model system was developed utilizing LPS and TNFα signaling with fluorescent reporter systems to monitor communication in real time. We demonstrated the utility of microfluidic devices to support the cell-cell communication model system by co culturing three cell types within Matrigel scaffolds and monitoring signaling activity via fluorescent reporters.

The whole-cell immobilization of D-hydantoinase-engineered Escherichia coli for D-CpHPG biosynthesis

Background: D-Hydroxyphenylglycine is considered to be an important chiral molecular building-block of antibiotic reagents such as pesticides, and β-lactam antibiotics. The process of its production is catalyzed by D-hydantoinase and D-carbamoylase in a two-step enzyme reaction. How to enhance the catalytic potential of the two enzymes is valuable for industrial application. In this investigation, an Escherichia coli strain genetically engineered with D-hydantoinase was immobilized by calcium alginate with certain adjuncts to evaluate the optimal condition for the biosynthesis of D-carbamoyl-p-hydroxyphenylglycine (D-CpHPG), the compound further be converted to D-hydroxyphenylglycine (D-HPG) by carbamoylase. Result: The optimal medium to produce D-CpHPG by whole-cell immobilization was a modified Luria-Bertani (LB) added with 3.0% (W/V) alginate, 1.5% (W/V) diatomite, 0.05% (W/V) CaCl2 and 1.00 mM MnCl2. The optimized diameter of immobilized beads for the whole-cell biosynthesis here was 2.60 mm. The maximized production rates of D-CpHPG were up to 76%, and the immobilized beads could be reused for 12 batches. Conclusions: This investigation not only provides an effective procedure for biological production of D-CpHPG, but gives an insight into the whole-cell immobilization technology. © 2016 Pontificia Universidad Católica de Valparaíso. Production and hosting by Elsevier B.V. All rights reserved.

Fabrication and Pseudo-Analog Characteristics of Ta2O5 -Based ReRAM Cell

Memristori on yksi elektroniikan peruskomponenteista vastuksen, kondensaattorin ja kelan lisäksi. Se on passiivinen komponentti, jonka teorian kehitti Leon Chua vuonna 1971. Kesti kuitenkin yli kolmekymmentä vuotta ennen kuin teoria pystyttiin yhdistämään kokeellisiin tuloksiin. Vuonna 2008 Hewlett Packard julkaisi artikkelin, jossa he väittivät valmistaneensa ensimmäisen toimivan memristorin. Memristori eli muistivastus on resistiivinen komponentti, jonka vastusarvoa pystytään muuttamaan. Nimens mukaisesti memristori kykenee myös säilyttämään vastusarvonsa ilman jatkuvaa virtaa ja jännitettä. Tyypillisesti memristorilla on vähintään kaksi vastusarvoa, joista kumpikin pystytään valitsemaan syöttämällä komponentille jännitettä tai virtaa. Tämän vuoksi memristoreita kutsutaankin usein resistiivisiksi kytkimiksi. Resistiivisiä kytkimiä tutkitaan nykyään paljon erityisesti niiden mahdollistaman muistiteknologian takia. Resistiivisistä kytkimistä rakennettua muistia kutsutaan ReRAM-muistiksi (lyhenne sanoista resistive random access memory). ReRAM-muisti on Flash-muistin tapaan haihtumaton muisti, jota voidaan sähköisesti ohjelmoida tai tyhjentää. Flash-muistia käytetään tällä hetkellä esimerkiksi muistitikuissa. ReRAM-muisti mahdollistaa kuitenkin nopeamman ja vähävirtaiseman toiminnan Flashiin verrattuna, joten se on tulevaisuudessa varteenotettava kilpailija markkinoilla. ReRAM-muisti mahdollistaa myös useammin bitin tallentamisen yhteen muistisoluun binäärisen (”0” tai ”1”) toiminnan sijaan. Tyypillisesti ReRAM-muistisolulla on kaksi rajoittavaa vastusarvoa, mutta näiden kahden tilan välille pystytään mahdollisesti ohjelmoimaan useampia tiloja. Muistisoluja voidaan kutsua analogisiksi, jos tilojen määrää ei ole rajoitettu. Analogisilla muistisoluilla olisi mahdollista rakentaa tehokkaasti esimerkiksi neuroverkkoja. Neuroverkoilla pyritään mallintamaan aivojen toimintaa ja suorittamaan tehtäviä, jotka ovat tyypillisesti vaikeita perinteisille tietokoneohjelmille. Neuroverkkoja käytetään esimerkiksi puheentunnistuksessa tai tekoälytoteutuksissa. Tässä diplomityössä tarkastellaan Ta2O5 -perustuvan ReRAM-muistisolun analogista toimintaa pitäen mielessä soveltuvuus neuroverkkoihin. ReRAM-muistisolun valmistus ja mittaustulokset käydään läpi. Muistisolun toiminta on harvoin täysin analogista, koska kahden rajoittavan vastusarvon välillä on usein rajattu määrä tiloja. Tämän vuoksi toimintaa kutsutaan pseudoanalogiseksi. Mittaustulokset osoittavat, että yksittäinen ReRAM-muistisolu kykenee binääriseen toimintaan hyvin. Joiltain osin yksittäinen solu kykenee tallentamaan useampia tiloja, mutta vastusarvoissa on peräkkäisten ohjelmointisyklien välillä suurta vaihtelevuutta, joka hankaloittaa tulkintaa. Valmistettu ReRAM-muistisolu ei sellaisenaan kykene toimimaan pseudoanalogisena muistina, vaan se vaati rinnalleen virtaa rajoittavan komponentin. Myös valmistusprosessin kehittäminen vähentäisi yksittäisen solun toiminnassa esiintyvää varianssia, jolloin sen toiminta muistuttaisi enemmän pseudoanalogista muistia.

Leccinum vulpinum Watling induces DNA damage, decreases cell proliferation and induces apoptosis on the human MCF-7 breast cancer cell line

The current work aimed to study the antitumour activity of a phenolic extract of the edible mushroom Leccinum vulpinum Watling, rich essentially in hydroxybenzoic acids. In a first approach, the mushroom extract was tested against cancer cell growth by using four human tumour cell lines. Given the positive results obtained in these initial screening experiments and the evidence of some studies for an inverse relationship between mushroom consumption and breast cancer risk, a detailed study of the bioactivity of the extract was carried out on MCF-7 cells. Once the selected cell line to precede the work was the breast adenocarcinoma cell line, the human breast non-malignant cell line MCF-10A was used as control. Overall, the extract decreased cellular proliferation and induced apoptosis. Furthermore, the results also suggest that the extract causes cellular DNA damage. Data obtained highlight the potential of mushrooms as a source of biologically active compounds, particularly with antitumour activity.

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.

Metastability and dynamics of stem cells: from direct observations to inference at the single cell level

Organismal development, homeostasis, and pathology are rooted in inherently probabilistic events. From gene expression to cellular differentiation, rates and likelihoods shape the form and function of biology. Processes ranging from growth to cancer homeostasis to reprogramming of stem cells all require transitions between distinct phenotypic states, and these occur at defined rates. Therefore, measuring the fidelity and dynamics with which such transitions occur is central to understanding natural biological phenomena and is critical for therapeutic interventions.

While these processes may produce robust population-level behaviors, decisions are made by individual cells. In certain circumstances, these minuscule computing units effectively roll dice to determine their fate. And while the 'omics' era has provided vast amounts of data on what these populations are doing en masse, the behaviors of the underlying units of these processes get washed out in averages.

Therefore, in order to understand the behavior of a sample of cells, it is critical to reveal how its underlying components, or mixture of cells in distinct states, each contribute to the overall phenotype. As such, we must first define what states exist in the population, determine what controls the stability of these states, and measure in high dimensionality the dynamics with which these cells transition between states.

To address a specific example of this general problem, we investigate the heterogeneity and dynamics of mouse embryonic stem cells (mESCs). While a number of reports have identified particular genes in ES cells that switch between 'high' and 'low' metastable expression states in culture, it remains unclear how levels of many of these regulators combine to form states in transcriptional space. Using a method called single molecule mRNA fluorescent in situ hybridization (smFISH), we quantitatively measure and fit distributions of core pluripotency regulators in single cells, identifying a wide range of variabilities between genes, but each explained by a simple model of bursty transcription. From this data, we also observed that strongly bimodal genes appear to be co-expressed, effectively limiting the occupancy of transcriptional space to two primary states across genes studied here. However, these states also appear punctuated by the conditional expression of the most highly variable genes, potentially defining smaller substates of pluripotency.

Having defined the transcriptional states, we next asked what might control their stability or persistence. Surprisingly, we found that DNA methylation, a mark normally associated with irreversible developmental progression, was itself differentially regulated between these two primary states. Furthermore, both acute or chronic inhibition of DNA methyltransferase activity led to reduced heterogeneity among the population, suggesting that metastability can be modulated by this strong epigenetic mark.

Finally, because understanding the dynamics of state transitions is fundamental to a variety of biological problems, we sought to develop a high-throughput method for the identification of cellular trajectories without the need for cell-line engineering. We achieved this by combining cell-lineage information gathered from time-lapse microscopy with endpoint smFISH for measurements of final expression states. Applying a simple mathematical framework to these lineage-tree associated expression states enables the inference of dynamic transitions. We apply our novel approach in order to infer temporal sequences of events, quantitative switching rates, and network topology among a set of ESC states.

Taken together, we identify distinct expression states in ES cells, gain fundamental insight into how a strong epigenetic modifier enforces the stability of these states, and develop and apply a new method for the identification of cellular trajectories using scalable in situ readouts of cellular state.

Fabrication and characterization of a nanostructured TiO2/In2S3-Sb2S3/CuSCN extremely thin absorber (eta) solar cell

CuSCN extremely thin absorber solar cell. Nanostructured TiO2 deposited by screen printing on an ITO substrate was used as an n-type electrode. An ∼80 nm extremely thin layer of the system In2S3-Sb2S3 deposited by successive ionic layer adsorption and a reaction (silar) method was used as an absorber. The voids were filled with p-type CuSCN and the entire assembly was completed with a gold contact. The solar cell fabricated with this heterostructure showed an energy conversion efficiency of 4.9%, which is a promising result in the development of low cost and simple fabrication of solar cells.

Establishment of a protocol for the cryopreservation of cell sheets of adipose tissue stem cells

Dissertação de Mestrado, Ciências Biomédicas, Departamento de Ciências Biomédicas e Medicina, Universidade do Algarve, 2016

Evolution of emerging iPS cell-based therapies for age-related macular degeneration (AMD)

Stem cell-based regenerative medicine is poised to revolutionize the way diseases are treated. In recent years, induced pluripotent stem (iPS) cells, a newly stem cell species, has attracted significant attention. This paper seeks to understand the pathways along which emerging clinical research efforts in the field of iPS cells is evolved. In particular, the empirical case of age-related macular degeneration (AMD) is used, which is the world-pioneering clinical application of iPS cells. In line with the literature, this study explores the interrelations between three different pathways, such as biomedical scientific understanding, development of medical technologies, and learning in clinical practice. For this, a techmining approach is used including co-term, co-citation, and direct citation methods. Scientific publications indexed in the Thomson Reuters' Web of Science and Elsevier's Scopus databases form the basis of the study. This research first explores the iPS cell research landscape through the construction of a co-term map, particularly stressing the location and intensity of disease-tackling efforts; then focus on the evolution of scientific knowledge on AMD through co-citation networks and the main path algorithm on direct citations. At the researcher level, the development of four different research groups working on cell therapies for AMD is evaluated through the software CitNetExplorer. By integrating these approaches, the result shows a wider picture of the complexities inherent in the translation of knowledge into revolutionary clinical methods.

Powertrain Architectures and Technologies for New Emission and Fuel Consumption Standards

New powertrain design is highly influenced by CO2 and pollutant limits defined by legislations, the demand of fuel economy in for real conditions, high performances and acceptable cost. To reach the requirements coming from both end-users and legislations, several powertrain architectures and engine technologies are possible (e.g. SI or CI engines), with many new technologies, new fuels, and different degree of electrification. The benefits and costs given by the possible architectures and technology mix must be accurately evaluated by means of objective procedures and tools in order to choose among the best alternatives. This work presents a basic design methodology and a comparison at concept level of the main powertrain architectures and technologies that are currently being developed, considering technical benefits and their cost effectiveness. The analysis is carried out on the basis of studies from the technical literature, integrating missing data with evaluations performed by means of powertrain-vehicle simplified models, considering the most important powertrain architectures. Technology pathways for passenger cars up to 2025 and beyond have been defined. After that, with support of more detailed models and experimentations, the investigation has been focused on the more promising technologies to improve internal combustion engine, such as: water injection, low temperature combustions and heat recovery systems.

Development of 3D Cancer Cell Models to Test Metabolic Interventions as an Anticancer Strategy

In recent years, it has become evident that the role of mitochondria in the metabolic rewiring is essential for cancer development and progression. The metabolic profile during tumorigenesis has been performed mainly in traditional 2D cell models, including cell lines of various lineages and phenotypes. Although useful in many ways, their relevance can be often debatable, as they lack the interactions between different cells of the tumour microenvironment and/or interaction with the extracellular matrix 1,2. Improved models are now being developed using 3D cell culture technology, contributing with increased physiological relevance 3,4. In this work, we improved a method for the generation of 3D models from healthy and tumour colon tissue, based on organoid technology, and performed their molecular and biochemical characterization and validation. Further, in-plate cryopreservation was applied to these models, and optimal results were obtained in terms of cell viability and functionality of the cryopreserved models. We also cryopreserved colon fibroblasts with the aim to introduce them in a co-culture cryopreserved model with organoids. This technology allows the conversion of cell models into “plug and play” formats. Therefore, cryopreservation in-plate facilitates the accessibility of specialized cell models to cell-based research and application, in cases where otherwise such specialized models would be out of reach. Finally, we briefly explored the field of bioprinting, by testing a new matrix to support the growth of colon tumour organoids, which revealed promising preliminary results. To facilitate the reader, we organized this thesis into chapters, divided by the main points of work which include development, characterization and validation of the model, commercial output, and associated applications. Each chapter has a brief introduction, followed by results and discussion and a final conclusion. The thesis has also a general discussion and conclusion section in the end, which covers the main results obtained during this work.

Convergent bioenergetic defects in Coenzyme Q10 depleted cells by pharmacological inhibition of coq2 enzyme (p-hydroxybenzoate polyprenyl transferase) and by genome editing technology targeting the encoding gene (COQ2)

Primary CoQ10 deficiency diseases encompass a heterogeneous spectrum of clinical phenotypes. Among these, defect or mutation on COQ2 gene, encoding a para-hydroxybenzoate polyprenyl transferase, have been associated with different diseases. Understanding the functional and metabolic impact of COQ2 mutation and the consequent CoQ10 deficiency is still a matter of debate. To date the aetiology of the neurological phenotypes correlated to CoQ10 deficiency does not present a clear genotype-phenotype association. In addition to the metabolic alterations due to Coenzyme Q depletion, the impairment of mitochondrial function, associated with the reduced CoQ level, could play a significant role in the metabolic flexibility of cancer. This study aimed to characterize the effect of varying degrees of CoQ10 deficiency and investigate the multifaceted aspect of CoQ10 depletion and its impact on cell metabolism. To induced CoQ10 depletion, different cell models were used, employing a chemical and genome editing approach. In T67 and MCF-7 CoQ10 depletion was achieved by a competitive inhibitor of the enzyme, 4-nitrobenzoate (4-NB), whereas in SH-SY5Y the COQ2 gene was edited via CRISPR-Cas9 cutting edge technology.