Monitoring microorganisms’ growth using multisensor electrochemical devices

Mestrado de dupla diplomação com a Université Libre de TunisSome microorganisms contribute beneficially in processing, safety and quality of certain food products. However, many microorganisms are involved in processes that cause undesirable effects on food, or on the health of consumers, leading to spoilage or to occurrence of foodborne diseases. For that, microbiological surveillance of food corresponds to an area of great interest to ensure the quality and the safety of food to prevent foodborne diseases. Indeed, for reasons related to sampling, methodology and distribution of the microorganisms in the matrix, microbiological analysis for itself does not guarantee the safety of a final product analyzed. For that, a possible promising alternative to the traditional diagnostic methods in the electronic sensors such as the E-tongues that has been used for different applications in food and pharmaceutical industries, they have been useful for the detection of bacterial contamination or diagnosis of infections. The aim of the present study was the detection and discrimination of microorganism that played an important role in food and environmental areas, namely E. coli, Enterococcus faecalis, Pseudomonas aeruginosa and S. aureus. In this context, electronic tongues (E-tongues) have been employed for the detection and screening of microorganisms. Thus; the use of a potentiometric E-tongue, comprising lipid polymeric sensor membranes, together with unsupervised and supervised chemometric tools (e.g., principal component analysis, PCA; linear discriminant analysis, LDA; and. multiple linear regression models, MLRM) was evaluated aiming to explore the advantages of these innovative (bio)sensing devices for microorganism’s recognition and discrimination, in aqueous solutions. Our results showed that the potentiometric signals profiles acquired by the 40 E-tongue sensors allowed a satisfactory unsupervised recognition of P. aeruginosa and E. faecalis, contrary to E. coli and S. aureus, showed a clear over-plotting. Still to further assess the E-tongue classification capability, a LDA was performed since it represents the most discriminant and non-redundant sensors selected by the SA algorithm. The supervised discriminant model allowed to classify 100% of the original grouped data. Overall, the unsupervised and supervised classification performances clearly showed the potential use of the E-tongue as an accurate and fast recognition device of the four microorganisms studied.Alguns microrganismos contribuem para a segurança e qualidade de certos produtos alimentares. No entanto, outros grupos de microrganismos causam efeitos indesejáveis nos alimentos provocando a sua deterioração ou inclusive dando origem a doenças de origem alimentar colocando em risco a saúde dos consumidores. Neste contexto, a vigilância microbiológica dos alimentos é uma área de grande relevância de forma a garantir a qualidade e a segurança dos alimentos. Contudo, as técnicas analíticas convencionais utilizadas na deteção de microrganismos em alimentos são caras e demoradas. Alternativamente, podem ser aplicadas outras técnicas, nomeadamente línguas eletrónicas (LE), para cumprir essa tarefa crítica. Com este estudo pretendeu-se estudar a capacidade de deteção e discriminação de microrganismos que desempenham um papel importante nas áreas alimentares e ambientais, nomeadamente Escherichia coli, Enterococcus faecalis, Pseudomonas aeruginosa e Staphylococcus aureus. Para tal, utilizou-se uma LE potenciométrica e o seu desempenho de deteção foi avaliado recorrendo a ferramentas quimiométricas não supervisionadas e supervisionadas (análise principal de componentes, ACP; análise discriminante linear ADL). Os resultados mostraram que os sinais potenciométricos adquiridos pelos sensores da LE permitem reconhecer satisfatoriamente e não supervisionado a P. aeruginosa e o E. faecalis, ao contrário da E. coli e S. aureus A capacidade de classificação da LE foi ainda avaliada pela ADL, com vista a identificar os sensores não redundantes e com maior potencial discriminante. O modelo discriminatório supervisionado permitiu classificar 100% dos dados originais. Globalmente, os desempenhos de classificação confirmaram a possível utilização da LE como um dispositivo de reconhecimento preciso e rápido dos quatro microrganismos estudados

Fundamentals of SARS-CoV-2 Biosensors

COVID-19 diagnostic strategies based on advanced techniques are currently essential topics of interest, with crucial roles in scientific research. This book integrates fundamental concepts and critical analyses that explore the progress of modern methods for the detection of SARS-CoV-2

A novel immunopeptidomic-based pipeline for the generation of personalized oncolytic cancer vaccines

Besides the isolation and identification of major histocompatibility complex I-restricted peptides from the surface of cancer cells, one of the challenges is eliciting an effective antitumor CD8+ T-cell-mediated response as part of therapeutic cancer vaccine. Therefore, the establishment of a solid pipeline for the downstream selection of clinically relevant peptides and the subsequent creation of therapeutic cancer vaccines are of utmost importance. Indeed, the use of peptides for eliciting specific antitumor adaptive immunity is hindered by two main limitations: the efficient selection of the most optimal candidate peptides and the use of a highly immunogenic platform to combine with the peptides to induce effective tumor-specific adaptive immune responses. Here, we describe for the first time a streamlined pipeline for the generation of personalized cancer vaccines starting from the isolation and selection of the most immunogenic peptide candidates expressed on the tumor cells and ending in the generation of efficient therapeutic oncolytic cancer vaccines. This immunopeptidomics-based pipeline was carefully validated in a murine colon tumor model CT26. Specifically, we used state-of-the-art immunoprecipitation and mass spectrometric methodologies to isolate > 8000 peptide targets from the CT26 tumor cell line. The selection of the target candidates was then based on two separate approaches: RNAseq analysis and HEX software. The latter is a tool previously developed by Jacopo, 2020, able to identify tumor antigens similar to pathogen antigens in order to exploit molecular mimicry and tumor pathogen cross-reactive T cells in cancer vaccine development. The generated list of candidates (26 in total) was further tested in a functional characterization assay using interferon-gamma enzyme-linked immunospot (ELISpot), reducing the number of candidates to six. These peptides were then tested in our previously described oncolytic cancer vaccine platform PeptiCRAd, a vaccine platform that combines an immunogenic oncolytic adenovirus (OAd) coated with tumor antigen peptides. In our work, PeptiCRAd was successfully used for the treatment of mice bearing CT26, controlling the primary malignant lesion and most importantly a secondary, nontreated, cancer lesion. These results confirmed the feasibility of applying the described pipeline for the selection of peptide candidates and generation of therapeutic oncolytic cancer vaccine, filling a gap in the field of cancer immunotherapy, and paving the way to translate our pipeline into human therapeutic approach.Peer reviewe

Present and future of surface-enhanced Raman scattering

The discovery of the enhancement of Raman scattering by molecules adsorbed on nanostructured metal surfaces is a landmark in the history of spectroscopic and analytical techniques. Significant experimental and theoretical effort has been directed toward understanding the surface-enhanced Raman scattering (SERS) effect and demonstrating its potential in various types of ultrasensitive sensing applications in a wide variety of fields. In the 45 years since its discovery, SERS has blossomed into a rich area of research and technology, but additional efforts are still needed before it can be routinely used analytically and in commercial products. In this Review, prominent authors from around the world joined together to summarize the state of the art in understanding and using SERS and to predict what can be expected in the near future in terms of research, applications, and technological development. This Review is dedicated to SERS pioneer and our coauthor, the late Prof. Richard Van Duyne, whom we lost during the preparation of this article

Label-Free Monitoring of Tumor Models by Surface-Enhanced Raman Scattering

184 p.El objetivo general de la presente tesis se ha centrado en la monitorización de modelos celulares mediante la técnica de espectroscopia de Raman aumentada en superficies (SERS). Las tecnologías desarrolladas en la tesis han perseguido, por un lado, mejorar la recreación del ambiente tumoral a escala de laboratorio, y por otra parte, su integración junto con estructuras plasmónicas para el análisis por SERS de los modelos tumorales creados artificialmente. Más en concreto, se han analizado las alteraciones en la concentración relativa de los metabolitos presentes en el medio extracelular como resultado de la reprogramación metabólica característica de los tumores, la cual permite a su vez un crecimiento descontrolado de dichas células.La disposición conjunta de ambas tecnologías (cultivos celulares en 3D y nanoplasmónica) ofrece un marco único para la identificación de aquellos procesos celulares que se encuentran alterados durante el crecimiento de tumores. Hasta la fecha, la mayoría de las técnicas de laboratorio que se habían empleado para caracterizar ambientes celulares en el laboratorio implicaban procesos invasivos, es decir, quemodifican o incluso desintegraban la muestra para poder analizarla. En contraposición, la espectroscopia Raman había permitido adquirir información sobre la composición del medio celular de una manera mínimamente invasiva. Basada en los fenómenos de dispersión inelástica, la técnica de Raman emplea luz monocromática (generalmente de un láser) para irradiar la muestra bajo análisis, de forma que la interacción entre la muestra y el láser provoca un cambio en la energía de los fotones dispersados, específico de los modos vibraciones de las moléculas irradiadas. Por lo tanto, la luz dispersada y recogida por un detector, permite caracterizar el sistema biológico que ha sido previamente iluminado, sin marcaje previo. Sin embargo, las señales detectadas por dispersión Raman son de manera general muy débiles, por lo que se requiere una intensificación de dichas señales para poder detectar la presencia de metabolitos extracelulares (a bajas concentraciones). En esta tesis se decidió implantar la modalidad conocida como SERS, que hace uso de las propiedades plasmónicas de nanopartículas metálicas (principalmente de oro), las cuales dan lugar a campos eléctricos elevados cuando se iluminan en resonancia con los plasmones superficiales. Como resultado, la señal de Raman de las moléculas adsorbidas sobre dichas superficies metálicas se ve amplificada en varios órdenes de magnitud. Sobre esta base, se han desarrollado en la tesis diferentes plataformas destinadas a combinar sustratos plasmónicos, formados por fijación de nanopartículas de oro sobre estructuras rígidas en 2D, o bien embebidas en redes poliméricas, junto con modelos de células tumorales en crecimiento. La finalidad de la tesis ha sido pues, la monitorización de diferentes procesos celulares en dichos dispositivos mediante SERS, y su posterior interpretación biológica en el ámbito del metabolismo tumoral y la mejora del tratamiento.CICbioGUNE; CICbiomaGUN

A bispecific monomeric nanobody induces spike trimer dimers and neutralizes SARS-CoV-2 in vivo

Experiments with replication-competent SARS-CoV-2 were performed in the Biomedicum BSL3 core facility, Karolinska Institutet. We thank Jonas Klingström for providing Calu-3 cells and sharing the Swedish SARS-CoV-2 isolate, and Alex Sigal from the Africa Health Research Institute for providing the beta variant (B.1.351/501Y.V2) isolate. We thank Penny Moore and the NICD (South Africa) for providing the B.1.351/beta variant spike plasmid, which was generated using funding from the South African Medical Research Council. We gratefully acknowledge the G2P-UK National Virology consortium funded by MRC/UKRI (grant ref: MR/W005611/1.) and the Barclay Lab at Imperial College for providing the B.1.617.2 spike plasmid. All cryo-EM data were collected in the Karolinska Institutet’s 3D-EM facility. We thank Agustin Ure for assistance with figure generation and Tomas Nyman (Protein Science Facility at KI) for providing access to SPR instruments. L.H. was supported by the David och Astrid Hageléns stiftelse, the Clas Groschinskys Minnesfond and a Jonas Söderquist’s scholarship. This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 101003653 (CoroNAb), to B.M. and G.M.M. B.M.H. is supported by the Knut and Alice Wallenberg Foundation (KAW 2017.0080 and KAW 2018.0080). The work was supported by project grants from the Swedish Research Council to E.S. (2020-02682), B.M.H. (2017-6702 and 2018-3808), B.M. (2018-02381) and to G.M.M. (2018-03914 and 2018-03843). E.S. is supported by Karolinska Institutet Foundation Grants, National Molecular Medicine Program Grants, and the grants from the SciLifeLab National COVID-19 Research Program, financed by the Knut and Alice Wallenberg Foundation. We thank National Microscopy Infrastructure, NMI (VR-RFI 2016-00968).N

Ultrafast Microfluidic Immunoassays Towards Real-time Intervention of Cytokine Storms

Biomarker-guided precision medicine holds great promise to provide personalized therapy with a good understanding of the molecular or cellular data of an individual patient. However, implementing this approach in critical care uniquely faces enormous challenges as it requires obtaining “real-time” data with high sensitivity, reliability, and multiplex capacity near the patient’s bedside in the quickly evolving illness. Current immunodiagnostic platforms generally compromise assay sensitivity and specificity for speed or face significantly increased complexity and cost for highly multiplexed detection with low sample volume. This thesis introduces two novel ultrafast immunoassay platforms: one is a machine learning-based digital molecular counting assay, and the other is a label-free nano-plasmonic sensor integrated with an electrokinetic mixer. Both of them incorporate microfluidic approaches to pave the way for near-real-time interventions of cytokine storms. In the first part of the thesis, we present an innovative concept and the theoretical study that enables ultrafast measurement of multiple protein biomarkers (<1 min assay incubation) with comparable sensitivity to the gold standard ELISA method. The approach, which we term “pre-equilibrium digital enzyme-linked immunosorbent assay” (PEdELISA) incorporates the single-molecular counting of proteins at the early, pre-equilibrium state to achieve the combination of high speed and sensitivity. We experimentally demonstrated the assay’s application in near-real-time monitoring of patients receiving chimeric antigen receptor (CAR) T-cell therapy and for longitudinal serum cytokine measurements in a mouse sepsis model. In the second part, we report the further development of a machine learning-based PEdELISA microarray data analysis approach with a significantly extended multiplex capacity using the spatial-spectral microfluidic encoding technique. This unique approach, together with a convolutional neural network-based image analysis algorithm, remarkably reduced errors faced by the highly multiplexed digital immunoassay at low analyte concentrations. As a result, we demonstrated the longitudinal data collection of 14 serum cytokines in human patients receiving CAR-T cell therapy at concentrations < 10pg/mL with a sample volume < 10 µL and 5-min assay incubation. In the third part, we demonstrate the clinical application of a machine learning-based digital protein microarray platform for rapid multiplex quantification of cytokines from critically ill COVID-19 patients admitted to the intensive care unit. The platform comprises two low-cost modules: (i) a semi-automated fluidic dispensing module that can be operated inside a biosafety cabinet to minimize the exposure of technician to the virus infection and (ii) a compact fluorescence optical scanner for the potential near-bedside readout. The automated system has achieved high interassay precision (~10% CV) with high sensitivity (<0.4pg/mL). Our data revealed large subject-to-subject variability in patient responses to anti-inflammatory treatment for COVID-19, reaffirming the need for a personalized strategy guided by rapid cytokine assays. Lastly, an AC electroosmosis-enhanced localized surface plasmon resonance (ACE-LSPR) biosensing device was presented for rapid analysis of cytokine IL-1β among sepsis patients. The ACE-LSPR device is constructed using both bottom-up and top-down sensor fabrication methods, allowing the seamless integration of antibody-conjugated gold nanorod (AuNR) biosensor arrays with microelectrodes on the same microfluidic platform. Applying an AC voltage to microelectrodes while scanning the scattering light intensity variation of the AuNR biosensors results in significantly enhanced biosensing performance. The technologies developed have enabled new capabilities with broad application to advance precision medicine of life-threatening acute illnesses in critical care, which potentially will allow the clinical team to make individualized treatment decisions based on a set of time-resolved biomarker signatures.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163129/1/yujing_1.pd

Raman scattering in pathology

Smith ZJ, Huser T, Wachsman-Hogiu S. Raman scattering in pathology. Analytical Cellular Pathology. 2012;35(3):145-163

Review of photoacoustic imaging plus X

Photoacoustic imaging (PAI) is a novel modality in biomedical imaging technology that combines the rich optical contrast with the deep penetration of ultrasound. To date, PAI technology has found applications in various biomedical fields. In this review, we present an overview of the emerging research frontiers on PAI plus other advanced technologies, named as PAI plus X, which includes but not limited to PAI plus treatment, PAI plus new circuits design, PAI plus accurate positioning system, PAI plus fast scanning systems, PAI plus novel ultrasound sensors, PAI plus advanced laser sources, PAI plus deep learning, and PAI plus other imaging modalities. We will discuss each technology's current state, technical advantages, and prospects for application, reported mostly in recent three years. Lastly, we discuss and summarize the challenges and potential future work in PAI plus X area

Present and Future of Surface-Enhanced Raman Scattering.

The discovery of the enhancement of Raman scattering by molecules adsorbed on nanostructured metal surfaces is a landmark in the history of spectroscopic and analytical techniques. Significant experimental and theoretical effort has been directed toward understanding the surface-enhanced Raman scattering (SERS) effect and demonstrating its potential in various types of ultrasensitive sensing applications in a wide variety of fields. In the 45 years since its discovery, SERS has blossomed into a rich area of research and technology, but additional efforts are still needed before it can be routinely used analytically and in commercial products. In this Review, prominent authors from around the world joined together to summarize the state of the art in understanding and using SERS and to predict what can be expected in the near future in terms of research, applications, and technological development. This Review is dedicated to SERS pioneer and our coauthor, the late Prof. Richard Van Duyne, whom we lost during the preparation of this article