Low-Impedance 3D PEDOT:PSS Ultramicroelectrodes

The technology for producing microelectrode arrays (MEAs) has been developing since the 1970s and extracellular electrophysiological recordings have become well established in neuroscience, drug screening and cardiology. MEAs allow monitoring of long-term spiking activity of large ensembles of excitable cells noninvasively with high temporal resolution and mapping its spatial features. However, their inability to register subthreshold potentials, such as intrinsic membrane oscillations and synaptic potentials, has inspired a number of laboratories to search for alternatives to bypass the restrictions and/or increase the sensitivity of microelectrodes. In this study, we present the fabrication and in vitro experimental validation of arrays of PEDOT:PSS-coated 3D ultramicroelectrodes, with the best-reported combination of small size and low electrochemical impedance. We observed that this type of microelectrode does not alter neuronal network biological properties, improves the signal quality of extracellular recordings and exhibits higher selectivity toward single unit recordings. With fabrication processes simpler than those reported in the literature for similar electrodes, our technology is a promising tool for study of neuronal networks. \ua9 Copyright \ua9 2020 Jones, Moskalyuk, Barthold, Gut\uf6hrlein, Heusel, Schr\uf6ppel, Samba and Giugliano

A Study of T Cell Tolerance to the Tumor-Associated Antigen MDM2: Cytokines Can Restore Antigen Responsiveness, but Not High Avidity T Cell Function

BACKGROUND: Most tumor-associated antigens (TAA) currently used for immunotherapy of cancer are also expressed in normal tissues, which may induce tolerance and impair T cell-mediated immunity. However, there is limited information about how physiological expression in normal tissues alters the function of TAA-specific T cells. METHODOLOGY/PRINCIPAL FINDINGS: We used a T cell receptor transgenic model to study how MDM2 expression in normal tissues affects the function of T cells specific for this TAA that is found at high levels in many different types of tumors. We found that some MDM2-specific T cells escaped thymic deletion and persisted in the peripheral T cell pool. When stimulated with antigen, these T cells readily initiated cell division but failed to proliferate and expand, which was associated with a high rate of apoptosis. Both IL-2 and IL-15 efficiently rescued T cell survival and antigen-specific T cell proliferation, while IL-7 and IL-21 were ineffective. Antigen-stimulated T cells showed impaired expression of the effector molecules CD43, granzyme-B and IFN-γ, a defect that was completely restored when T cells were stimulated in the presence of IL-2. In contrast, IL-15 and IL-21 only restored the expression of CD43 and granzyme-B, but not IFN-γ production. Finally, peptide titration experiments with IL-2 rescued T cells indicated that they were of lower avidity than non-tolerant control T cells expressing the same TCR. CONCLUSIONS/SIGNIFICANCE: These data indicate that cytokines can rescue the antigen-specific proliferation and effector function of MDM2-specific T cells, although this does not lead to the recovery of high avidity T cell function. This study sheds light on possible limitations of immunotherapy approaches that target widely expressed TAA, such as MDM2

An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge

BACKGROUND: There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data was donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. RESULTS: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. CONCLUSIONS: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups

An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge

There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. RESULTS: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. CONCLUSIONS: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups

Precise Temporal Profiling of Signaling Complexes in Primary Cells Using SWATH Mass Spectrometry

Spatiotemporal organization of protein interactions in cell signaling is a fundamental process that drives cellular functions. Given differential protein expression across tissues and developmental stages, the architecture and dynamics of signaling interaction proteomes is, likely, highly context dependent. However, current interaction information has been almost exclusively obtained from transformed cells. In this study, we applied an advanced and robust workflow combining mouse genetics and affinity purification (AP)-SWATH mass spectrometry to profile the dynamics of 53 high-confidence protein interactions in primary T cells, using the scaffold protein GRB2 as a model. The workflow also provided a sufficient level of robustness to pinpoint differential interaction dynamics between two similar, but functionally distinct, primary T cell populations. Altogether, we demonstrated that precise and reproducible quantitative measurements of protein interaction dynamics can be achieved in primary cells isolated from mammalian tissues, allowing resolution of the tissue-specific context of cell-signaling events

SECAT: Quantifying Protein Complex Dynamics across Cell States by Network-Centric Analysis of SEC-SWATH-MS Profiles

Protein-protein interactions (PPIs) play critical functional and regulatory roles in cellular processes. They are essential for macromolecular complex formation, which in turn constitutes the basis for protein interaction networks that determine the functional state of a cell. We and others have previously shown that chromatographic fractionation of native protein complexes in combination with bottom-up mass spectrometric analysis of consecutive fractions supports the multiplexed characterization and detection of state-specific changes of protein complexes. In this study, we extend co-fractionation and mass spectrometric data analysis to perform quantitative, network-based studies of proteome organization, via the size-exclusion chromatography algorithmic toolkit (SECAT). This framework explicitly accounts for the dynamic nature and rewiring of protein complexes across multiple cell states and samples, thus, elucidating molecular mechanisms that are differentially implemented across different experimental settings. Systematic analysis of multiple datasets shows that SECAT represents a highly scalable and effective methodology to assess condition/state-specific protein-network state. A record of this paper’s transparent peer review process is included in the Supplemental Information.ISSN:2405-472