Analyse von B-lymphozytären Subpopulationen des darmassoziierten lymphatischen Gewebes

ZUSAMMENFASSUNG Hintergrund: Das primäre und sekundäre Immunglobulinrepertoire bilden eine bedeutende Grundlage der Pathogenbekämpfung im Wirbeltier. Das Mukosa-assoziierte lymphatische Gewebe stellt hierbei die erste Front des humoralen Immunsystems gegen invasive Infektionen dar. An der Mukosa überwiegt das Immunglobulin A, welches sowohl in das Plasma als auch auf die Schleimhaut sezerniert werden kann. Eine Differenzierung der B-Lymphozyten zu Plasma- und Gedächtniszellen gewährleistet bei erneuter Infektion mit dem gleichen Pathogen eine viel schnellere und effektivere Immunantwort. Fragestellung: Unklar sind grundlegende Fragen zur Entwicklung der B-Zell- bzw. Antikörper-Repertoires im darmassoziierten lymphatischen Gewebe (gut-associated lymphoid tissue: (GALT): Welchem Selektionsdruck unterliegt das B-Zell-Repertoire während des Klassenwechsels zu IgA? Weiterhin ist nicht bekannt, nach welchen Kriterien Lymphozyten in den Pool der IgA-bildenden Gedächtnis- und Plasmazellen rekrutiert werden. In dieser Arbeit haben wir die Hypothese geprüft, dass IgA-bildende Subpopulationen der Gedächtnis- und Plasmazellen nicht zufällig, sondern aufgrund ihrer Antigen-Bindungseigenschaften rekrutiert werden. Methoden: Wir haben mittels Durchflusszytometrie Plasma- und Gedächtniszellen aus Peyerschen Plaques adulter BALB/C Wildtyp-Mäuse separiert und mittels Reverse Transkriptase-PCR selektiv IgM- und IgA-Transkripte der schweren Immunglobulin-Ketten amplifiziert und kloniert. Die so gewonnenen Transkripte wurden sequenziert und mittels Datenbankanalyse (Alignment mittels IMGT VQuest) ausgewertet. Ergebnisse: Es wurden insgesamt 413 Immunglobulinsequenzen in vier unabhängigen Experimenten erhoben, von denen sich 323 (78%) als nicht-redundante Transkripte erwiesen. Immunglobulin A-Sequenzen der Gedächtnis- und Plasmazellen wiesen mit 74% bzw. 72% eine signifikant niedrigere klonale Diversität auf als Immunglobuline der Klasse M (94%; jeweils p<0,01). Immunglobulin A-Sequenzen der Gedächtnis- und Plasmazellen enthielten mehr somatische Mutationen (37‰ bzw. 35‰) als IgM-Sequenzen (14‰, p<0,01). Bei IgA-Sequenzen aus Gedächtniszellen waren weniger zufällige, sogenannte N-Nukleotide innerhalb der Antigen-Bindungsstelle vorhanden als bei IgA-Sequenzen aus Plasmazellen (p<0,01). Zusätzlich wiesen IgA-Sequenzen aus Gedächtniszellen im Vergleich zu IgM-Sequenzen signifikant kürzere CDR3-Regionen auf (p<0,05) bei signifikant kürzeren NDN-Regionen (p<0,01). Ein ähnlicher Trend war bei IgA-Sequenzen aus Plasmazellen erkennbar. In unserer Studie korrelierte zudem die Nutzung von JH- und VH-Gen-Familien. Diskussion: IgA-Sequenzen weisen die typischen Anzeichen der klassischen Antigenselektion auf. Die eingeschränkte klonale Diversität und die erhöhte Mutationsrate der IgA-Transkripte aus Gedächtnis- und Plasmazellen gegenüber IgM-Transkripten der gleichen Gewebeproben belegt eine Antigen-abhängige fokussierte Selektion während des Klassenwechsels von IgM zu IgA. Interessanterweise wiesen Immunglobuline A der Gedächtniszellen eine andere Binnenstruktur innerhalb der Antigen-Bindungsstelle (CDR-H3) auf als Immunglobuline M. Daher haben IgA aus Gedächtniszellen gegenüber IgM eine geringere strukturelle Vielfalt und im Durchschnitt eine flachere Antigen-Bindungsstelle, wodurch eine engere Interaktion mit dem Antigen möglich ist. Im Gegensatz zu früheren Annahmen beeinflußt die VH-Segment-Nutzung die JH-Segment-Nutzung und damit die Zusammensetzung der CDR3-Region eines Immunglobulins. Schlussfolgerung: Immunglobulin A produzierende Gedächtnis- und Plasmazellen stellen separate Populationen mit unterschiedlichen Repertoires an Antigen-Bindungsstellen innerhalb ihrer Antikörper dar. Sie weisen alle Charakteristika einer individuellen Antigen-abhängigen Selektion auf. Dies weist darauf hin, dass die CDR3-Region ein entscheidender Selektionsfaktor während des Klassenwechsels zu IgA darstellt

Enzymatic degradation of polyethylene terephthalate nanoplastics analyzed in real time by isothermal titration calorimetry

Plastics are globally used for a variety of benefits. As a consequence of poor recycling or reuse, improperly disposed plastic waste accumulates in terrestrial and aquatic ecosystems to a considerable extent. Large plastic waste items become fragmented to small particles through mechanical and (photo)chemical processes. Particles with sizes ranging from millimeter (microplastics, <5 mm) to nanometer (nanoplastics, NP, <100 nm) are apparently persistent and have adverse effects on ecosystems and human health. Current research therefore focuses on whether and to what extent microorganisms or enzymes can degrade these NP. In this study, we addressed the question of what information isothermal titration calorimetry, which tracks the heat of reaction of the chain scission of a polyester, can provide about the kinetics and completeness of the degradation process. The majority of the heat represents the cleavage energy of the ester bonds in polymer backbones providing real-time kinetic information. Calorimetry operates even in complex matrices. Using the example of the cutinase-catalyzed degradation of polyethylene terephthalate (PET) nanoparticles, we found that calorimetry (isothermal titration calorimetry-ITC) in combination with thermokinetic models is excellently suited for an in-depth analysis of the degradation processes of NP. For instance, we can separately quantify i) the enthalpy of surface adsorption ∆AdsH = 129 ± 2 kJ mol−1, ii) the enthalpy of the cleavage of the ester bonds ∆EBH = −58 ± 1.9 kJ mol−1 and the apparent equilibrium constant of the enzyme substrate complex K = 0.046 ± 0.015 g L−1. It could be determined that the heat production of PET NP degradation depends to 95% on the reaction heat and only to 5% on the adsorption heat. The fact that the percentage of cleaved ester bonds (η = 12.9 ± 2.4%) is quantifiable with the new method is of particular practical importance. The new method promises a quantification of enzymatic and microbial adsorption to NP and their degradation in mimicked real-world aquatic conditions

Разработка алгоритмического и программного обеспечения для укладки графов на плоскости

Объектом исследования является процесс укладки графов на плоскость. Цель работы - Разработка алгоритмического и программного обеспечения для укладки графов на плоскости. В процессе работы производилось изучение существующих способов отображения планарных и непланарных графов на плоскости и разработка программного обеспечения для отображения диаграмм баз данных на плоскости.The object of the study is the process of laying graphs on a plane. The aim of the work is to Develop algorithmic and software for laying graphs on the plane. In the course of work, the study of existing methods of displaying planar and non-planar graphs on the plane and the development of software for displaying database digrams on the plane were carried out

Design and Characterization of a High Resolution Microfluidic Heat Flux Sensor with Thermal Modulation

A complementary metal-oxide semiconductor-compatible process was used in the design and fabrication of a suspended membrane microfluidic heat flux sensor with a thermopile for the purpose of measuring the heat flow rate. The combination of a thirty-junction gold and nickel thermoelectric sensor with an ultralow noise preamplifier, a low pass filter, and a lock-in amplifier can yield a resolution 20 nW with a sensitivity of 461 V/W. The thermal modulation method is used to eliminate low-frequency noise from the sensor output, and various amounts of fluidic heat were applied to the sensor to investigate its suitability for microfluidic applications. For sensor design and analysis of signal output, a method of modeling and simulating electro-thermal behavior in a microfluidic heat flux sensor with an integrated electronic circuit is presented and validated. The electro-thermal domain model was constructed by using system dynamics, particularly the bond graph. The electro-thermal domain system model in which the thermal and the electrical domains are coupled expresses the heat generation of samples and converts thermal input to electrical output. The proposed electro-thermal domain system model is in good agreement with the measured output voltage response in both the transient and the steady state

Real-time label-free monitoring of adipose-derived stem cell differentiation with electric cell-substrate impedance sensing

Real-time monitoring of stem cells (SCs) differentiation will be critical to scale-up SC technologies, while label-free techniques will be desirable to quality-control SCs without precluding their therapeutic potential. We cultured adipose-derived stem cells (ADSCs) on top of multielectrode arrays and measured variations in the complex impedance Z* throughout induction of ADSCs toward osteoblasts and adipocytes. Z* was measured up to 17 d, every 180 s, over a 62.5–64kHz frequency range with an ECIS Zθ instrument. We found that osteogenesis and adipogenesis were characterized by distinct Z* time-courses. Significant differences were found (P = 0.007) as soon as 12 h post induction. An increase in the barrier resistance (Rb) up to 1.7 ohm·cm(2) was associated with early osteo-induction, whereas Rb peaked at 0.63 ohm·cm(2) for adipo-induced cells before falling to zero at t = 129 h. Dissimilarities in Z* throughout early induction (<24 h) were essentially attributed to variations in the cell-substrate parameter α. Four days after induction, cell membrane capacitance (Cm) of osteo-induced cells (Cm = 1.72 ± 0.10 μF/cm(2)) was significantly different from that of adipo-induced cells (Cm = 2.25 ± 0.27 μF/cm(2)), indicating that Cm could be used as an early marker of differentiation. Finally, we demonstrated long-term monitoring and measured a shift in the complex plane in the middle frequency range (1 kHz to 8 kHz) between early (t = 100 h) and late induction (t = 380 h). This study demonstrated that the osteoblast and adipocyte lineages have distinct dielectric properties and that such differences can be used to perform real-time label-free quantitative monitoring of adult stem cell differentiation with impedance sensing

A scalable algorithm to explore the Gibbs energy landscape of genome-scale metabolic networks

The integration of various types of genomic data into predictive models of biological networks is one of the main challenges currently faced by computational biology. Constraint-based models in particular play a key role in the attempt to obtain a quantitative understanding of cellular metabolism at genome scale. In essence, their goal is to frame the metabolic capabilities of an organism based on minimal assumptions that describe the steady states of the underlying reaction network via suitable stoichiometric constraints, specifically mass balance and energy balance (i.e. thermodynamic feasibility). The implementation of these requirements to generate viable configurations of reaction fluxes and/or to test given flux profiles for thermodynamic feasibility can however prove to be computationally intensive. We propose here a fast and scalable stoichiometry-based method to explore the Gibbs energy landscape of a biochemical network at steady state. The method is applied to the problem of reconstructing the Gibbs energy landscape underlying metabolic activity in the human red blood cell, and to that of identifying and removing thermodynamically infeasible reaction cycles in the Escherichia coli metabolic network (iAF1260). In the former case, we produce consistent predictions for chemical potentials (or log-concentrations) of intracellular metabolites; in the latter, we identify a restricted set of loops (23 in total) in the periplasmic and cytoplasmic core as the origin of thermodynamic infeasibility in a large sample ($10^6$) of flux configurations generated randomly and compatibly with the prior information available on reaction reversibility.Comment: 11 pages, 6 figures, 1 table; for associated supporting material see http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.100256