A Public BCR Present in a Unique Dual-Receptor-Expressing Lymphocyte from Type 1 Diabetes Patients Encodes a Potent T Cell Autoantigen

Exploring an In-Plane Graphene and Hexagonal Boron Nitride Array for Separation of Single Nucleotides

Regular nanofluidic sieving structures are emerging as rapid and compatible on-chip techniques for biomolecular separation. Although the current nanofluidic sieving devices, mostly based on three-dimensional nanostructures, have achieved a separation resolution of ∼20 nm, it is still far away from single-nucleotide resolution. Using all-atom molecular dynamics simulations, here we demonstrate a two-dimensional (2D) nanofluidic sieve consisting of an in-plane graphene (GRA)/hexagonal boron nitride (h-BN) nanoarray, which enables ultrahigh resolution in the successful separation of four types of single nucleotides. The alternating GRA and h-BN stripes can create size-dependent energy barriers for adsorbed nucleotides, which provide a strong modulation for their mobility, thus causing distinct band separations on the 2D surface. We further show that this 2D sieve is particularly sensitive when the sample dimensions are within the range from a half period to one period of the nanoarray. This 2D sieving structure may shed light on the development of lab-on-a-chip sequencing in the future.

A subset of cytotoxic effector memory T cells enhances CAR T cell efficacy in a model of pancreatic ductal adenocarcinoma

In humans, the natural killer (NK) cell marker CD161 identifies several subsets of T cells, including a polyclonal CD8 αβ T cell receptor-expressing subset with characteristic specificity for tissue-localized viruses. This subset also displays enhanced cytotoxic and memory phenotypes. Here, we characterized this unique T cell subset and determined its potential suitability for use in chimeric antigen receptor (CAR) T cell therapy. In mice, gene expression profiling among the CD161-equivalent CD8⁺ T cell populations (CD8⁺NK1.1⁺) revealed substantial up-regulation of granzymes, perforin, killer lectin-like receptors, and innate signaling molecules in comparison to CD8⁺NK1.1^- T cells. Adoptive transfer of CD8⁺NK1.1⁺ cells from previously exposed animals offered substantially enhanced protection and improved survival against melanoma tumors and influenza infection compared to CD8⁺NK1.1^- cells. Freshly isolated human CD8⁺CD61⁺ T cells exhibited heightened allogeneic killing activity in comparison to CD8⁺CD61^- T cells or total peripheral blood mononuclear cells (PBMCs). To determine whether this subset might improve the antitumor efficacy of CAR T cell therapy against solid tumors, we compared bulk PBMCs, CD8⁺CD161^-, and CD8⁺CD161⁺ T cells transduced with a human epidermal growth factor receptor-2 (HER2)-specific CAR construct. In vitro, CD8⁺CD161⁺ CAR-transduced T cells killed HER2⁺ targets faster and with greater efficiency. Similarly, these cells mediated enhanced in vivo antitumor efficacy in xenograft models of HER2⁺ pancreatic ductal adenocarcinoma, exhibiting elevated expression of granzymes and reduced expression of exhaustion markers. These data suggest that this T cell subset presents an opportunity to improve CAR T cell therapy for the treatment of solid tumors.

DNA-Based Microparticle Tension Sensors (μTS) for Measuring Cell Mechanics in Non-planar Geometries and for High-Throughput Quantification

Mechanotransduction, the interplay between physical and chemical signaling, plays vital roles in many biological processes. The state-of-the-art techniques to quantify cell forces employ deformable polymer films or molecular probes tethered to glass substrates. However, the applications of these assays in fundamental and clinical research are restricted by the planar geometry and low throughput of microscopy readout. Herein, we develop a DNA-based microparticle tension sensor, which features a spherical surface and thus allows for investigation of mechanotransduction at curved interfaces. The micron-scale of μTS enables flow cytometry readout, which is rapid and high throughput. We applied the method to map and measure T-cell receptor forces and platelet integrin forces at 12 and 56 pN thresholds. Furthermore, we quantified the inhibition efficiency of two anti-platelet drugs providing a proof-of-concept demonstration of μTS to screen drugs that modulate cellular mechanics.

CD5-expressing CD8+ T-cell subsets differ between children with type 1 diabetes and controls

Different lymphocyte subsets are involved in autoimmune pathogenesis of type 1 diabetes (T1D). Previous studies suggested a role of CD5-expressing T and B cells including rare unconventional lymphocytes with combined T- and B-cell features [dual expressing (DE) cells]. We performed algorithm-supported multiparameter flow cytometry and quantitative PCR to investigate immune cell subsets and DE cells in children with T1D (n = 20) and matched controls (n = 20). Comparisons of conventional immune cells detected increased proportions of CD3⁺ T cells in T1D patients, whereas CD19⁺ B-cell proportions were comparable to controls. Self-organizing maps for flow cytometry analyses (FlowSOM) showed highly similar CD5-expressing B-cell subsets and no differences for DE cells were detected between the study groups by flow cytometry or specific quantitative PCR. Notably, differences in CD8⁺ T cells were indicated by FlowSOM and similarity-based t-distributed stochastic neighbor embedding (tSNE) analyses. Study group comparisons confirmed significantly reduced CD8⁺ T-cell proportions with moderate or low CD5 expression in T1D patients. Finally, in vitro experiments showed stable CD5 expression differences of CD8⁺ T cells after T-cell activation, cytokine stimulation and culture. We observed differences of T-cell coreceptor CD5 expression in T1D patients with potential relevance for immune regulation of CD8⁺ T-cell activation.

CD32+CD4+ T Cells Sharing B Cell Properties Increase With Simian Immunodeficiency Virus Replication in Lymphoid Tissues

CD4 T cell responses constitute an important component of adaptive immunity and are critical regulators of anti-microbial protection. CD4⁺ T cells expressing CD32a have been identified as a target for HIV. CD32a is an Fcγ receptor known to be expressed on myeloid cells, granulocytes, B cells and NK cells. Little is known about the biology of CD32⁺CD4⁺ T cells. Our goal was to understand the dynamics of CD32⁺CD4⁺ T cells in tissues. We analyzed these cells in the blood, lymph nodes, spleen, ileum, jejunum and liver of two nonhuman primate models frequently used in biomedical research: African green monkeys (AGM) and macaques. We studied them in healthy animals and during viral (SIV) infection. We performed phenotypic and transcriptomic analysis at different stages of infection. In addition, we compared CD32+CD4+ T cells in tissues with well-controlled (spleen) and not efficiently controlled (jejunum) SIV replication in AGM. The CD32⁺CD4⁺ T cells more frequently expressed markers associated with T cell activation and HIV infection (CCR5, PD-1, CXCR5, CXCR3) and had higher levels of actively transcribed SIV RNA than CD32^-CD4⁺T cells. Furthermore, CD32⁺CD4⁺ T cells from lymphoid tissues strongly expressed B-cell-related transcriptomic signatures, and displayed B cell markers at the cell surface, including immunoglobulins CD32+CD4+ T cells were rare in healthy animals and blood but increased strongly in tissues with ongoing viral replication. CD32⁺CD4⁺ T cell levels in tissues correlated with viremia. Our results suggest that the tissue environment induced by SIV replication drives the accumulation of these unusual cells with enhanced susceptibility to viral infection.

Double-jeopardy: scRNA-seq doublet/multiplet detection using multi-omic profiling

The computational detection and exclusion of cellular doublets and/or multiplets is a cornerstone for the identification the true biological signals from single-cell RNA sequencing (scRNA-seq) data. Current methods do not sensitively identify both heterotypic and homotypic doublets and/or multiplets. Here, we describe a machine learning approach for doublet/multiplet detection utilizing VDJ-seq and/or CITE-seq data to predict their presence based on transcriptional features associated with identified hybrid droplets. This approach highlights the utility of leveraging multi-omic single-cell information for the generation of high-quality datasets. Our method has high sensitivity and specificity in inflammatory-cell-dominant scRNA-seq samples, thus presenting a powerful approach to ensuring high-quality scRNA-seq data.

Ryanodine receptor and immune-related molecules in diabetic cardiomyopathy

Hyperglycaemia is a major aetiological factor in the development of diabetic cardiomyopathy. Excessive hyperglycaemia increases the levels of reactive carbonyl species (RCS), reactive oxygen species (ROS) and reactive nitrogen species (RNS) in the heart and causes derangements in calcium homeostasis, inflammation and immune‐system disorders. Ryanodine receptor 2 (RyR2) plays a key role in excitation–contraction coupling during heart contractions, including rhythmic contraction and relaxation of the heart. Cardiac inflammation has been indicated in part though interleukin 1 (IL‐1) signals, supporting a role for B and T lymphocytes in diabetic cardiomyopathy. Some of the post‐translational modifications of the ryanodine receptor (RyR) by RCS, ROS and RNS stress are known to affect its gating and Ca²⁺ sensitivity, which contributes to RyR dysregulation in diabetic cardiomyopathy. RyRs and immune‐related molecules are important signalling species in many physiological and pathophysiological processes in various heart and cardiovascular diseases. However, little is known regarding the mechanistic relationship between RyRs and immune‐related molecules in diabetes, as well as the mechanisms mediating complex communication among cardiomyocytes, fibroblasts and immune cells. This review highlights new findings on the complex cellular communications in the pathogenesis and progression of diabetic cardiomyopathy. We discuss potential therapeutic applications targeting RyRs and immune‐related molecules in diabetic complications.

Rituximab leads to early elimination of circulating CD20+ T and B lymphocytes in patients with iTTP despite ongoing TPEx

How TPEx impacts rituximab effectiveness in iTTP patients is not fully understood. In iTTP patients on therapeutic plasma exchange, rituximab eliminates circulating CD20+ B and T cells in 24 hours for at least 1 week.

Clinicomolecular Identification of Conserved and Individualized Features of Granulomatous Uveitis

Objective

To identify molecular features that distinguish individuals with shared clinical features of granulomatous uveitis.

Design

Cross-sectional, observational study.

Participants

Four eyes from patients with active granulomatous uveitis.

Methods

We performed single-cell RNA-sequencing with antigen-receptor sequence analysis to obtain an unbiased gene expression survey of ocular immune cells and identify clonally expanded lymphocytes.

Main Outcomes Measures

For each inflamed eye, we measured the proportion of distinct immune cell types, the amount of B or T cell clonal expansion, and the transcriptional profile of T and B cells.

Results

Each individual had robust clonal expansion arising from a single T or B cell lineage, suggesting distinct, antigen-driven pathogenic processes in each patient. This variability in clonal expansion was mirrored by individual variability in CD4 T cell populations, whereas ocular CD8 T cells and B cells were more transcriptionally similar between patients. Finally, ocular B cells displayed evidence of class-switching and plasmablast differentiation within the ocular microenvironment, providing additional support for antigen-driven immune responses in granulomatous uveitis.

Conclusions

Collectively, our study identified both conserved and individualized features of granulomatous uveitis, illuminating parallel pathophysiologic mechanisms, and suggesting that future personalized therapeutic approaches may be warranted.

A reply to "TCR+/BCR+ dual-expressing cells and their associated public BCR clonotype are not enriched in type 1 diabetes"

We have recently identified a novel lymphocyte that is a dual expresser (DE) of TCRαβ and BCR. DEs in T1D patients are predominated by a public BCR clonotype (clone-x) that encodes a potent autoantigen that cross-activates insulin-reactive T cells. Betts and colleagues were able to detect DEs but alleged to not detect high DE frequency, clone-x, or similar clones in T1D patients. Unfortunately, the authors did not follow our methods and when they did, their flow cytometric data at two sites were conflicting. Moreover, contrary to their claim, we identified clones similar to clone-x in their data along with clones bearing the core motif (DTAMVYYFDYW). Additionally, their report of no increased usage of clone-x VH/DH genes by bulk B cells confirms rather than challenges our results. Finally, the authors failed to provide data verifying purity of their sorted DEs, making it difficult to draw reliable conclusion of their repertoire analysis. This Matters Arising Response paper addresses the Japp et al. (2021) Matters Arising paper, published concurrently in Cell.

A population of proinflammatory T cells coexpresses αβ and γδ T cell receptors in mice and humans

T cells are classically recognized as distinct subsets that express αβ or γδ TCRs. We identify a novel population of T cells that coexpress αβ and γδ TCRs in mice and humans. These hybrid αβ-γδ T cells arose in the murine fetal thymus by day 16 of ontogeny, underwent αβ TCR-mediated positive selection into CD4+ or CD8+ thymocytes, and constituted up to 10% of TCRδ+ cells in lymphoid organs. They expressed high levels of IL-1R1 and IL-23R and secreted IFN-γ, IL-17, and GM-CSF in response to canonically restricted peptide antigens or stimulation with IL-1β and IL-23. Hybrid αβ-γδ T cells were transcriptomically distinct from conventional γδ T cells and displayed a hyperinflammatory phenotype enriched for chemokine receptors and homing molecules that facilitate migration to sites of inflammation. These proinflammatory T cells promoted bacterial clearance after infection with Staphylococcus aureus and, by licensing encephalitogenic Th17 cells, played a key role in the development of autoimmune disease in the central nervous system.

Prevention strategies for type 1 diabetes: a story of promising efforts and unmet expectations

A number of studies have investigated primary and secondary prevention strategies for type 1 diabetes (T1D), since early interventions might improve long-term outcomes through the amelioration of immune processes and the preservation of beta-cell mass. Primary prevention trials focus on genetically at-risk individuals prior to the appearance of autoimmunity, whereas secondary prevention trials aim to halt the progression of complete beta-cell destruction in subjects with established islet autoimmunity (IA). Different approaches have been tested so far, focusing on both pharmaceutical (insulin and monoclonal antibodies) and non-pharmaceutical (vitamin D, omega-3 fatty acids, probiotics, and nicotinamide) interventions, as well as on environmental factors that are believed to trigger autoimmunity in T1D (cow's milk, gluten, and bovine insulin). Albeit certain strategies have displayed efficacy in reducing IA development rates, most efforts have been unsuccessful in preventing the onset of the disease in high-risk individuals. Moreover, significant heterogeneity in study designs, included populations, and explored outcomes renders the interpretation of study results challenging. The aim of this narrative review is to present and critically evaluate primary and secondary prevention strategies for T1D, seeking to fill existing knowledge gaps and providing insight into future directions.

Spontaneous Translocation of Single-Stranded DNA in Graphene-MoS2 Heterostructure Nanopores: Shape Effect

The appropriate translocation speed of a single-stranded DNA (ssDNA) through a solid-state nanopore is crucial for DNA sequencing technologies. By studying the geometry effect of graphene-MoS₂ hetero-nanopores with molecular dynamics simulations, we have found that the shape of these nanopores (circular, square, or triangular, with similar size) may have a significant effect on the spontaneous translocation of ssDNA, with the triangular nanopore showing the slowest translocation and the circular one the fastest. Further analyses reveal that such differences in the spontaneous ssDNA translocation arise from different electrostatic attractions between the positively charged Mo atoms exposed in the pore and the negatively charged phosphate groups (PO₄^-) in nucleotides; the "sharpness" and the total number of the exposed Mo atoms of the nanopores are responsible for different electrostatic attractions between ssDNA and the nanopore. Our findings suggest that graphene-MoS₂ heterostructure nanopores with lower symmetries (i.e., having sharper corners) are capable of slowing down the ssDNA translocation, which might help better facilitate the nucleotide sensing and DNA sequencing. The conclusion from these findings might also extend to other solid-state nanopores in designing appropriate shapes for better controlling of the translocation speed.

Retro-inverso D-peptides as a novel targeted immunotherapy for Type 1 diabetes

Over the past four decades, the number of people with Type 1 Diabetes (T1D) has increased by 4% per year, making it an important public health challenge. Currently, no curative therapy exists for T1D and the only available treatment is insulin replacement. HLA-DQ8 has been shown to present antigenic islet peptides driving the activation of CD4⁺ T-cells in T1D patients. Specifically, the insulin peptide InsB:9-23 activates self-reactive CD4⁺ T-cells, causing pancreatic beta cell destruction. The aim of the current study was to identify retro-inverso-d-amino acid based peptides (RI-D-peptides) that can suppress T-cell activation by blocking the presentation of InsB:9-23 peptide within HLA-DQ8 pocket. We identified a RI-D-peptide (RI-EXT) that inhibited InsB:9-23 binding to recombinant HLA-DQ8 molecule, as well as its binding to DQ8 expressed on human B-cells. RI-EXT prevented T-cell activation in a cellular antigen presentation assay containing human DQ8 cells loaded with InsB:9-23 peptide and murine T-cells expressing a human T-cell receptor specific for the InsB:9-23-DQ8 complex. Moreover, RI-EXT blocked T-cell activation by InsB:9-23 in a humanized DQ8 mice both ex vivo and in vivo, as shown by decreased production of IL-2 and IFN-γ and reduced lymphocyte proliferation. Interestingly, RI-EXT also blocked lymphocyte activation and proliferation by InsB:9-23 in PBMCs isolated from recent onset DQ8-T1D patients. In summary, we discovered a RI-D-peptide that blocks InsB:9-23 binding to HLA-DQ8 and its presentation to T-cells in T1D. These findings set the stage for using our approach as a novel therapy for patients with T1D and potentially other autoimmune diseases.

Structural Basis of the Potential Binding Mechanism of Remdesivir to SARS-CoV-2 RNA-Dependent RNA Polymerase

Starting from late 2019, the coronavirus disease 2019 (COVID-19) has emerged as a once-in-a-century pandemic with deadly consequences, which urgently calls for new treatments, cures, and supporting apparatuses. Recently, because of its positive results in clinical trials, remdesivir was approved by the Food and Drug Administration to treat COVID-19 through Emergency Use Authorization. Here, we used molecular dynamics simulations and free energy perturbation methods to study the inhibition mechanism of remdesivir to its target SARS-CoV-2 virus RNA-dependent RNA polymerase (RdRp). We first constructed the homology model of this polymerase based on a previously available structure of SARS-CoV NSP12 RdRp (with a sequence identity of 95.8%). We then built a putative preinsertion binding structure by aligning the remdesivir + RdRp complex to the ATP bound poliovirus RdRp without the RNA template. The putative binding structure was further optimized with molecular dynamics simulations. The resulting stable preinsertion state of remdesivir appeared to form hydrogen bonds with the RNA template when aligned with the newly solved cryo-EM structure of SARS-CoV-2 RdRp. The relative binding free energy between remdesivir and ATP was calculated to be -2.80 ± 0.84 kcal/mol, where remdesivir bound much stronger to SARS-CoV-2 RdRp than the natural substrate ATP. The ∼100-fold improvement in the K_d from remdesivir over ATP indicates an effective replacement of ATP in blocking of the RdRp preinsertion site. Key residues D618, S549, and R555 are found to be the contributors to the binding affinity of remdesivir. These findings suggest that remdesivir can potentially act as a SARS-CoV-2 RNA-chain terminator, effectively stopping its RNA replication, with key residues also identified for future lead optimization and/or drug resistance studies.

Structural Basis of the Potential Binding Mechanism of Remdesivir to SARS-CoV-2 RNA-Dependent RNA Polymerase

Starting from late 2019, the coronavirus disease 2019 (COVID-19) has emerged as a once-in-a-century pandemic with deadly consequences, which urgently calls for new treatments, cures, and supporting apparatuses. Recently, because of its positive results in clinical trials, remdesivir was approved by the Food and Drug Administration to treat COVID-19 through Emergency Use Authorization. Here, we used molecular dynamics simulations and free energy perturbation methods to study the inhibition mechanism of remdesivir to its target SARS-CoV-2 virus RNA-dependent RNA polymerase (RdRp). We first constructed the homology model of this polymerase based on a previously available structure of SARS-CoV NSP12 RdRp (with a sequence identity of 95.8%). We then built a putative preinsertion binding structure by aligning the remdesivir + RdRp complex to the ATP bound poliovirus RdRp without the RNA template. The putative binding structure was further optimized with molecular dynamics simulations. The resulting stable preinsertion state of remdesivir appeared to form hydrogen bonds with the RNA template when aligned with the newly solved cryo-EM structure of SARS-CoV-2 RdRp. The relative binding free energy between remdesivir and ATP was calculated to be -2.80 ± 0.84 kcal/mol, where remdesivir bound much stronger to SARS-CoV-2 RdRp than the natural substrate ATP. The ∼100-fold improvement in the Kd from remdesivir over ATP indicates an effective replacement of ATP in blocking of the RdRp preinsertion site. Key residues D618, S549, and R555 are found to be the contributors to the binding affinity of remdesivir. These findings suggest that remdesivir can potentially act as a SARS-CoV-2 RNA-chain terminator, effectively stopping its RNA replication, with key residues also identified for future lead optimization and/or drug resistance studies.

Mass cytometry and type 1 diabetes research in the age of single-cell data science

PURPOSE OF REVIEW

New single-cell tec. hnologies developed over the past decade have considerably reshaped the biomedical research landscape, and more recently have found their way into studies probing the pathogenesis of type 1 diabetes (T1D). In this context, the emergence of mass cytometry in 2009 revolutionized immunological research in two fundamental ways that also affect the T1D world: first, its ready embrace by the community and rapid dissemination across academic and private science centers alike established a new standard of analytical complexity for the high-dimensional proteomic stratification of single-cell populations; and second, the somewhat unexpected arrival of mass cytometry awoke the flow cytometry field from its seeming sleeping beauty stupor and precipitated substantial technological advances that by now approach a degree of analytical dimensionality comparable to mass cytometry.

RECENT FINDINGS

Here, we summarize in detail how mass cytometry has thus far been harnessed for the pursuit of discovery studies in T1D science; we provide a succinct overview of other single-cell analysis platforms that already have been or soon will be integrated into various T1D investigations; and we briefly consider how effective adoption of these technologies requires an adjusted model for expense allocation, prioritization of experimental questions, division of labor, and recognition of scientific contributions.

SUMMARY

The introduction of contemporary single-cell technologies in general, and of mass cytometry, in particular, provides important new opportunities for current and future T1D research; the necessary reconfiguration of research strategies to accommodate implementation of these technologies, however, may both broaden research endeavors by fostering genuine team science, and constrain their actual practice because of the need for considerable investments into infrastructure and technical expertise.

GMM-Demux: sample demultiplexing, multiplet detection, experiment planning, and novel cell-type verification in single cell sequencing

Identifying and removing multiplets are essential to improving the scalability and the reliability of single cell RNA sequencing (scRNA-seq). Multiplets create artificial cell types in the dataset. We propose a Gaussian mixture model-based multiplet identification method, GMM-Demux. GMM-Demux accurately identifies and removes multiplets through sample barcoding, including cell hashing and MULTI-seq. GMM-Demux uses a droplet formation model to authenticate putative cell types discovered from a scRNA-seq dataset. We generate two in-house cell-hashing datasets and compared GMM-Demux against three state-of-the-art sample barcoding classifiers. We show that GMM-Demux is stable and highly accurate and recognizes 9 multiplet-induced fake cell types in a PBMC dataset.

Study of B Cell Repertoire in Patients With Anti-N-Methyl-D-Aspartate Receptor Encephalitis

Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is the most common antibody-mediated encephalitis. There are several studies on B cell repertoire of anti-NMDAR encephalitis in Caucasians. Here, the cerebrospinal fluid (CSF) samples of 12 Chinese patients with first-episode anti-NMDAR encephalitis were collected to investigate the B cell receptor (BCR) binding to NMDAR by single cell amplification of BCR and Sanger sequencing. BCR data of healthy persons, and of patients with anti-leucine-rich glioma inactivated 1 (anti-LGI1) encephalitis, multiple sclerosis (MS), and neuromyelitis optica spectrum disorder (NMOSD) from the public databases were used as control. A heavy chain common clone IGHV1-18^*04,IGHD1-26^*01/ IGHD2-2^*03/IGHD2-8^*01, IGHJ3^*02_(CDR3) ARVGSKYGFETFDI was found in 11 of 12 enrolled patients but not in the comparison data set. In addition, 4 shared clonotypes were found among these patients, and three of them contained the common clone. This study also revealed that the antibody gene family usage preference between patients and healthy controls were different, while they had similar antibody mutation rate. Our findings may have potential clinical implications for the diagnosis of anti-NMDAR encephalitis.

Planar graphene/h-BN/graphene heterostructures for protein stretching and confinement

Protein stretching and confinement in nanochannels is critical for advancing single-molecule detection techniques. For standard nanochannels integrated with nano-sensors, reducing their cross-section is beneficial for reading highly localized signals with minimal error, but results in increasing difficulty for the initial capture of any chain molecules due to the entropy barrier. Using molecular dynamics simulations, we show that spontaneous protein stretching can be realized by a two-dimensional (2D) heterostructure composed of a hexagonal boron nitride (h-BN) nanoribbon stitched with two graphene (GRA) sheets (i.e., a sandwiched GRA/BN/GRA structure). Due to fast protein diffusion on its flat surface and adsorption potential difference between two 2D materials, this planar nanochannel permits effective capture and elongation of three representative intrinsically disordered proteins including amyloid-β (1-42), polyglutamine (42) and α-synuclein (61-95). Moreover, we found that the extremely narrow h-BN stripe can provide stronger confinement for a longer polyglutamine chain after being stretched. Our approach has the potential to facilitate the bona fide readout of single-molecule protein sequencing techniques.

Artificial-cell-type aware cell-type classification in CITE-seq

MOTIVATION

Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE-seq), couples the measurement of surface marker proteins with simultaneous sequencing of mRNA at single cell level, which brings accurate cell surface phenotyping to single-cell transcriptomics. Unfortunately, multiplets in CITE-seq datasets create artificial cell types (ACT) and complicate the automation of cell surface phenotyping.

RESULTS

We propose CITE-sort, an artificial-cell-type aware surface marker clustering method for CITE-seq. CITE-sort is aware of and is robust to multiplet-induced ACT. We benchmarked CITE-sort with real and simulated CITE-seq datasets and compared CITE-sort against canonical clustering methods. We show that CITE-sort produces the best clustering performance across the board. CITE-sort not only accurately identifies real biological cell types (BCT) but also consistently and reliably separates multiplet-induced artificial-cell-type droplet clusters from real BCT droplet clusters. In addition, CITE-sort organizes its clustering process with a binary tree, which facilitates easy interpretation and verification of its clustering result and simplifies cell-type annotation with domain knowledge in CITE-seq.

AVAILABILITY AND IMPLEMENTATION

http://github.com/QiuyuLian/CITE-sort.

SUPPLEMENTARY INFORMATION

Supplementary data is available at Bioinformatics online.

An entropy-based metric for assessing the purity of single cell populations

Single-cell RNA sequencing (scRNA-seq) is a versatile tool for discovering and annotating cell types and states, but the determination and annotation of cell subtypes is often subjective and arbitrary. Often, it is not even clear whether a given cluster is uniform. Here we present an entropy-based statistic, ROGUE, to accurately quantify the purity of identified cell clusters. We demonstrate that our ROGUE metric is broadly applicable, and enables accurate, sensitive and robust assessment of cluster purity on a wide range of simulated and real datasets. Applying this metric to fibroblast, B cell and brain data, we identify additional subtypes and demonstrate the application of ROGUE-guided analyses to detect precise signals in specific subpopulations. ROGUE can be applied to all tested scRNA-seq datasets, and has important implications for evaluating the quality of putative clusters, discovering pure cell subtypes and constructing comprehensive, detailed and standardized single cell atlas.

Nanotechnology's application in Type 1 diabetes

Type 1 diabetes mellitus (T1D) is an autoimmune disease caused by the immune system attacking islet cells. T1D, with a long prediabetes period, and the incidence of T1D increases with age during childhood and peaks at 10-14 years. And once it gets overt, it requires lifelong insulin replace treatment. Therefore, the diagnosis of early-stage T1D and effective treatments are important for the management of T1D patients. The imaging methods, such as magnetic resonance imaging (MRI) and so on, were applied in diagnosis of the early stage T1D and its development tracking. The addition of nanomaterials, especially in MRI, can improve the quality of T1D imaging for the diagnosis of T1D at early stage and cause less harm to human body. Meantime, among various treatment options, islet transplantation and immunotherapy are promising, effective, and less independent on insulin. The addition of nanotechnology can effectively reduce the attack of the immune system on drugs and cells, making the therapeutic drug more targeted in the body and prolonging the action time between drugs and cells, thus its addition makes these therapy safer and more efficient. In this review, we attempt to summarize the recent advances in the development of nanotechnology advances of T1D including using nanomaterials for the diagnosis and immunological imaging of T1D, protecting the transplanted islet cells from immune system attack, and delivering relevant molecules to targeted immunocytes. This article is categorized under: Diagnostic Tools > in vivo Nanodiagnostics and Imaging Therapeutic Approaches and Drug Discovery > Emerging Technologies Implantable Materials and Surgical Technologies > Nanotechnology in Tissue Repair and Replacement.

The Challenge of Distinguishing Cell-Cell Complexes from Singlet Cells in Non-Imaging Flow Cytometry and Single-Cell Sorting

Our recent work has highlighted that care needs to be taken when interpreting single cell data originating from flow cytometry acquisition or cell sorting: We found that doublets of T cells bound to other immune cells are often present in the live singlet gate of human peripheral blood samples acquired by flow cytometry. This hidden "contamination" generates atypical gene signatures of mixed cell lineage in what is assumed to be single cells, which can lead to data misinterpretation, such as the description of novel immune cell types. Here, based on the example of T cell-monocyte complexes, we identify experimental and data analysis strategies to help distinguishing between singlets and cell-cell complexes in non-imaging flow cytometry and single-cell sorting. We found robust molecular signatures in both T cell-monocyte and T cell-B cell complexes that can distinguish them from singlets at both protein and mRNA levels. Imaging flow cytometry with appropriate gating strategy (matching the one used in cell sorting) and direct microscopy imaging after cell sorting were the two methods of choice to detect the presence of cell-cell complexes in suspicious dual-expressing cells. We finally applied this knowledge to highlight the likely presence of T cell-B cell complexes in a recently published dataset describing a novel cell population with mixed T cell and B cell lineage properties. © 2020 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

Autoantigen Treatment in Type 1 Diabetes: Unsolved Questions on How to Select Autoantigen and Administration Route

Autoantigen treatment has been tried for the prevention of type 1 diabetes (T1D) and to preserve residual beta-cell function in patients with a recent onset of the disease. In experimental animal models, efficacy was good, but was insufficient in human subjects. Besides the possible minor efficacy of peroral insulin in high-risk individuals to prevent T1D, autoantigen prevention trials have failed. Other studies on autoantigen prevention and intervention at diagnosis are ongoing. One problem is to select autoantigen/s; others are dose and route. Oral administration may be improved by using different vehicles. Proinsulin peptide therapy in patients with T1D has shown possible minor efficacy. In patients with newly diagnosed T1D, subcutaneous injection of glutamic acid decarboxylase (GAD) bound to alum hydroxide (GAD-alum) can likely preserve beta-cell function, but the therapeutic effect needs to be improved. Intra-lymphatic administration may be a better alternative than subcutaneous administration, and combination therapy might improve efficacy. This review elucidates some actual problems of autoantigen therapy in the prevention and/or early intervention of type 1 diabetes.

Immunology in the Era of Single-Cell Technologies

Immune cells are characterized by diversity, specificity, plasticity, and adaptability-properties that enable them to contribute to homeostasis and respond specifically and dynamically to the many threats encountered by the body. Single-cell technologies, including the assessment of transcriptomics, genomics, and proteomics at the level of individual cells, are ideally suited to studying these properties of immune cells. In this review we discuss the benefits of adopting single-cell approaches in studying underappreciated qualities of immune cells and highlight examples where these technologies have been critical to advancing our understanding of the immune system in health and disease.

Discovery and characteristics of B cell-like T cells: A potential novel tumor immune marker?

BACKGROUND

CD3 and CD19 are the characteristic surface markers of mature T lymphocytes and B lymphocytes of human respectively. A special subset of immune cells that characteristically expressed the surface markers CD19+ of B lymphocytes and CD3+ of T lymphocytes simultaneously (CD19+CD3+ cells, hereinafter referred to as B-T cells) was found in the peripheral blood of human, yet it has not been reported in cancer research before. Our aims were to characterize the expression and possible value of B-T cells in cancer patients.

METHODS

Flow cytometry was applied to analyse the CD19+CD3+ cells, and laser scanning confocal microscope was utilized to prove co-expressing CD19+ of B lymphocytes and CD3+ of T lymphocytes simultaneously on the surface of the cells. Then a total of 523 patients with malignant tumor were enrolled in this study, and 177 healthy donors were recruited as the control group. The levels of CD19+CD3+ cells in peripheral blood were measured by flow cytometry, and the differences between the two groups were compared.

RESULTS

The healthy donors and cancer patients all had B-T cells in their peripheral blood, but the percentage of B-T cells was 0.16 % ± 0.11 % and 0.58 % ± 0.38 % respectively, showing statistically significant (P < 0.0001). There was no significant correlation between the percentage of B-T cells and lymphocyte subsets (P > 0.05). The percentages of B-T cells in different tumor species were different. The proportion of B-T cells was high in esophageal cancer, non-Hodgkin's lymphoma and lung cancer, but it was low in pancreatic cancer, ovarian cancer and kidney cancer. Meanwhile, there was significant difference between esophageal cancer and kidney cancer (P < 0.001). The distribution of B-T cells in pancreatic cancer and kidney cancer was more concentrated, yet more dispersed in other cancers. Although there was a trend of increase in clinical stage Ⅲ+Ⅳ and a trend of decrease in age above 60 years for breast cancer, gastric cancer and liver cancer, there was no significant difference in the percentage of B-T cells in age, gender, different clinical stages, tumor metastasis, lymph node metastasis, and splenomegaly (P > 0.05).

CONCLUSION

The percentage of B-T cells in cancer patients was significantly higher than that of healthy donors. B-T cells maybe play a very complicated role in tumor, whether it could be a potential tumor immune marker or not and what are the specific phenotypes and functions of it to need be further verified.

Current understandings of the pathogenesis of type 1 diabetes: Genetics to environment

Type 1 diabetes (T1D) is an autoimmune disease that usually strikes early in life, but can affect individuals at almost any age. It is caused by autoreactive T cells that destroy insulin-producing beta cells in the pancreas. Epidemiological studies estimate a prevalence of 1 in 300 children in the United States with an increasing incidence of 2%-5% annually worldwide. The daily responsibility, clinical management, and vigilance required to maintain blood sugar levels within normal range and avoid acute complications (hypoglycemic episodes and diabetic ketoacidosis) and long term micro- and macro-vascular complications significantly affects quality of life and public health care costs. Given the expansive impact of T1D, research work has accelerated and T1D has been intensively investigated with the focus to better understand, manage and cure this condition. Many advances have been made in the past decades in this regard, but key questions remain as to why certain people develop T1D, but not others, with the glaring example of discordant disease incidence among monozygotic twins. In this review, we discuss the field’s current understanding of its pathophysiology and the role of genetics and environment on the development of T1D. We examine the potential implications of these findings with an emphasis on T1D inheritance patterns, twin studies, and disease prevention. Through a better understanding of this process, interventions can be developed to prevent or halt it at early stages.

Unlocking the Power of Artificial Intelligence and Big Data in Medicine

Data-driven science and its corollaries in machine learning and the wider field of artificial intelligence have the potential to drive important changes in medicine. However, medicine is not a science like any other: It is deeply and tightly bound with a large and wide network of legal, ethical, regulatory, economical, and societal dependencies. As a consequence, the scientific and technological progresses in handling information and its further processing and cross-linking for decision support and predictive systems must be accompanied by parallel changes in the global environment, with numerous stakeholders, including citizen and society. What can be seen at the first glance as a barrier and a mechanism slowing down the progression of data science must, however, be considered an important asset. Only global adoption can transform the potential of big data and artificial intelligence into an effective breakthroughs in handling health and medicine. This requires science and society, scientists and citizens, to progress together.

The Genetic Contribution to Type 1 Diabetes

PURPOSE OF REVIEW

To provide an updated summary of discoveries made to date resulting from genome-wide association study (GWAS) and sequencing studies, and to discuss the latest loci added to the growing repertoire of genetic signals predisposing to type 1 diabetes (T1D).

RECENT FINDINGS

Genetic studies have identified over 60 loci associated with T1D susceptibility. GWAS alone does not specifically inform on underlying mechanisms, but in combination with other sequencing and omics-data, advances are being made in our understanding of T1D genetic etiology and pathogenesis. Current knowledge indicates that genetic variation operating in both pancreatic β cells and in immune cells is central in mediating T1D risk. One of the main challenges is to determine how these recently discovered GWAS-implicated variants affect the expression and function of gene products. Once we understand the mechanism of action for disease-causing variants, we will be well placed to apply targeted genomic approaches to impede the premature activation of the immune system in an effort to ultimately prevent the onset of T1D.

Surface Inhomogeneity of Graphene Oxide Influences Dissociation of Aβ16-21 Peptide Assembly

Abnormal peptide assembly and aggregation is associated with an array of neurodegenerative diseases including Alzheimer's disease (AD). A detailed understanding of how nanostructured materials such as oxidized graphene perturb the peptide assembly and subsequently induce fibril dissociation may open new directions for the development of potential AD treatments. Here, we investigate the impact of surface inhomogeneity of graphene oxide (GO) on the assembly of amyloid-beta Aβ_16-21 peptides on GO surfaces with different degrees of oxidation using molecular dynamics simulations. Interestingly, nonuniform GO nanosheets (in terms of oxidation sites) have a much stronger perturbation effect on the structure of Aβ_16-21 assembly. The Aβ peptides exhibit a remarkable tendency in binding to the scattered interfaces between unoxidized and oxidized regions, which induces the dissociation of Aβ amyloid fibril. These findings should deepen our understanding of surface-induced peptide dissociation and stimulate discovery of alternative AD treatments.

Lanosterol Disrupts the Aggregation of Amyloid-β Peptides

Lanosterol, an amphipathic molecule, was discovered only very recently to effectively hinder the aggregation of lens proteins and dissolve the extremely stable fibrillar aggregates in cataracts. Here, we combined computational and experimental approaches to study how lanosterol disrupts the aggregation of another important peptide, amyloid-β (Aβ) peptide, associated with the Alzheimer's Disease (AD). Molecular dynamics simulations using the core amyloidogenic segment (KLVFFA) of Aβ peptide revealed that lanosterol exhibits at least two types of inhibition mechanism on the self-assembly of Aβ peptides. First, lanosterol entangles with peptides and forms a hydrophobic core with residues Phe-19 and Phe-20 in particular. Second, it interferes with the steric zipper interaction at the β-sheet-β-sheet interface. These simulation data suggest that lanosterol induces the unfolding of the Aβ peptide and the separation of the β-sheet layers. This predicted inhibition effect of lanosterol was then confirmed by an in vitro ThT fluorescence assay and AFM imaging. The cell toxicity assay also showed that the treatment of lanosterol indeed mitigates the cytotoxicity of the Aβ peptide in PC-12 cells. Moreover, lanosterol shows a stronger suppression effect on Aβ peptides' aggregation than cholesterol because of its higher hydrophobicity. This result establishes a foundation for the development of lanosterol-based potential therapies for AD and other protein conformational diseases.

Hybrid lipids, peptides, and lymphocytes: new era in type 1 diabetes research

Type 1 diabetes (T1D) results from autoimmune destruction of insulin-producing β cells in islets of Langerhans. Many genetic and immunological insights into autoimmune disease pathogenesis were initially uncovered in the context of T1D and facilitated by preclinical studies using the nonobese diabetic (NOD) mouse model. Recently, the study of T1D has led to the discovery of fatty acid esters of hydroxyl fatty acids (FAHFAs), which are naturally occurring hybrid peptides that modulate inflammation and diabetes pathogenesis, and a hybrid lymphocyte that expresses both B and T cell receptors. Palmitic acid esters of hydroxy stearic acids (PAHSAs) are the most extensively studied FAHFA. In this issue of the JCI, Syed et al. have shown that PAHSAs both attenuate autoimmune responses and promote β cell survival in NOD mice. Given the lack of effective T1D therapies and the paucity of known side effects of PAHSAs, this lipid may have therapeutic potential for individuals at risk for or newly diagnosed with T1D.

Adaptive innate immunity or innate adaptive immunity?

The innate immunity is frequently accepted as a first line of relatively primitive defense interfering with the pathogen invasion until the mechanisms of ‘privileged’ adaptive immunity with the production of antibodies and activation of cytotoxic lymphocytes ‘steal the show’. Recent advancements on the molecular and cellular levels have shaken the traditional view of adaptive and innate immunity. The innate immune memory or ‘trained immunity’ based on metabolic changes and epigenetic reprogramming is a complementary process insuring adaptation of host defense to previous infections.

Innate immune cells are able to recognize large number of pathogen- or danger- associated molecular patterns (PAMPs and DAMPs) to behave in a highly specific manner and regulate adaptive immune responses. Innate lymphoid cells (ILC1, ILC2, ILC3) and NK cells express transcription factors and cytokines related to subsets of T helper cells (Th1, Th2, Th17). On the other hand, T and B lymphocytes exhibit functional properties traditionally attributed to innate immunity such as phagocytosis or production of tissue remodeling growth factors. They are also able to benefit from the information provided by pattern recognition receptors (PRRs), e.g. γδT lymphocytes use T-cell receptor (TCR) in a manner close to PRR recognition. Innate B cells represent another example of limited combinational diversity usage participating in various innate responses. In the view of current knowledge, the traditional black and white classification of immune mechanisms as either innate or an adaptive needs to be adjusted and many shades of gray need to be included.

The role of proteomics in assessing beta-cell dysfunction and death in type 1 diabetes

Introduction: Type 1 diabetes (T1D) is characterized by autoimmune-induced dysfunction and destruction of the pancreatic beta cells. Unfortunately, this process is poorly understood, and the current best treatment for type 1 diabetes is the administration of exogenous insulin. To better understand these mechanisms and to develop new therapies, there is an urgent need for biomarkers that can reliably predict disease stage. Areas covered: Mass spectrometry (MS)-based proteomics and complementary techniques play an important role in understanding the autoimmune response, inflammation and beta-cell death. MS is also a leading technology for the identification of biomarkers. This, and the technical difficulties and new technologies that provide opportunities to characterize small amounts of sample in great depth and to analyze large sample cohorts will be discussed in this review. Expert opinion: Understanding disease mechanisms and the discovery of disease-associated biomarkers are highly interconnected goals. Ideal biomarkers would be molecules specific to the different stages of the disease process that are released from beta cells to the bloodstream. However, such molecules are likely to be present in trace amounts in the blood due to the small number of pancreatic beta cells in the human body and the heterogeneity of the target organ and disease process.

A Novel Liposome Formulation Carrying Both an Insulin Peptide and a Ligand for Invariant Natural Killer T Cells Induces Accumulation of Regulatory T Cells to Islets in Nonobese Diabetic Mice

Type 1 diabetes (T1D) is an autoimmune disease caused by the destruction of pancreatic β cells by autoantigen-reactive diabetogenic cells. Antigen-specific therapies using islet autoantigens for restoring immune tolerance have emerged as promising approaches for the treatment of T1D but have been unsuccessful in humans. Herein, we report that RGI-3100-iB, a novel liposomal formulation carrying both α-galactosylceramide (α-GalCer), which is a representative ligand for invariant natural killer T (iNKT) cells, and insulin B chain 9-23 peptide, which is an epitope for CD4⁺ T cells, could induce the accumulation of regulatory T cells (Tregs) in islets in a peptide-dependent manner, followed by the remarkable prevention of diabetes onset in nonobese diabetic (NOD) mice. While multiple administrations of a monotherapy using either α-GalCer or insulin B peptide in a liposomal formulation was confirmed to delay/prevent T1D in NOD mice, RGI-3100-iB synergistically enhanced the prevention effect of each monotherapy and alleviated insulitis in NOD mice. Immunopathological analysis showed that Foxp3⁺ Tregs accumulated in the islets in RGI-3100-iB-treated mice. Cotransfer of diabetogenic T cells and splenocytes of NOD mice treated with RGI-3100-iB, but not liposomal α-GalCer encapsulating an unrelated peptide, to NOD-SCID mice resulted in the prevention of diabetes and elevation of Foxp3 mRNA expression in the islets. These data indicate that the migration of insulin B-peptide-specific Tregs to islet of NOD mice that are involved in the suppression of pathogenic T cells related to diabetes onset and progression could be enhanced by the administration of liposomes containing α-GalCer and insulin B peptide.