bluuebunny/crossref_metadata_2025_split huggingface dataset:
Follicular B cell derived CD21lo B cells are immediate precursors to autoreactive extrafollicular antibody secreting cells
Authors: Zhu Danni , Castrillon Carlos , Carroll Michael C 
Published: August 2023

Abstract
Systemic lupus erythematosus (SLE) is an incurable autoimmune B cell disorder that is in part due to ineffective clearance of nuclear antigens and activation of the TLR pathway. The extrafollicular (EF) differentiation pathway of antibody secreting cells (ASCs) is recognized to play a prominent role in generating pathogenic antibodies in both mice and human. For example, a novel population of CD21lo CD11c+ B cells identified in both mice (age-associated B cells) and human (DN2 cells) are thought to be a major source of autoreactive EF ASCs. However, the developmental kinetics and cellular origin of EF ASCs remain elusive. To track early events of B cell break of tolerance and EF ASC generation, an adoptive transfer system was established, where WT B cells are transferred into the autoreactive BCR transgenic 564Igi host enriched in nuclear antigens. By introducing competing populations of WT and TLR7 deficient B cells, we demonstrated that the differentiation of EF ASCs requires TLR7. To examine the kinetics of autoreactive B cell proliferation and EF ASC differentiation, a Cell Trace labeling approach was used. We found that donor B cells require at least 7 divisions to differentiate to EF ASCs and that TLR7 deficient B cells are gradually outcompeted by WT at each division. Interestingly, CD21lo CD23neg B cells were highly proliferative, expressed CD11c, and were sensitive to TLR7 defect. Our interpretation is that they are likely the immediate developmental precursors of EF ASCs. These findings advance our current understanding of the fundamental biological circuitry behind EF-derived autoantibody producing cells and potentially point to future avenues for therapeutic development.
Supported by NIH (5R01AR074105-05), CIHR Doctoral Foreign Study Award (DFSA) (DFD-181607)
Impact of B cell specific neutral lipid accumulation on B cell activation and function
Authors: Song Wenxia , Halpern Clarissa , Hu Cecilia , Lazzaro Michelle , Shapiro Melanie , Sherman Emily , Fan Sherry , Tyrlik Adam , Seeley-Fallen Margaret Kathryn 
Published: August 2023

Abstract
Obesity and its resultant inflammation have been shown to lead to a multitude of disease states, including Type II diabetes and cancer. Immune cells play a role in perpetuating obesity related diseases. B cells have been shown to infiltrate the visceral adipose tissue of obese individuals, where they activate other immune cells and produce autoantibodies. This study examined the impact of B cell neutral lipid accumulation on B cell function and activation, using B cell specific comparative gene identification-58 (CGI-58) knockout mice (bCKO). CGI-58 is the co-activator of adipose triglyceride lipase, a key enzyme initiating lipid droplet lipolysis. CGI-58 knockout and flox control mice were fed a low-fat diet for 16 or 32 weeks. B cells from bCKO mice exhibited a higher level of neutral lipid accumulation than other cell types and flox control B cells. Unimmunized bCKO mice showed increased percentages of spontaneous germinal center B cells compared to flox controls. Isolated bCKO B cells survived in culture significantly better than flox control B cells, which was concurrent with decreased levels of cellular and mitochondrial ROS and mitochondrial membrane potential in bCKO B cells compared to flox B cells. Furthermore, bCKO mice had increased numbers of crown-like structures in their visceral adipose tissues and elevated protein levels in their urine, predictors of metabolic disorder. Together, our results suggest that neutral lipid accumulation in B cells alone leads to non-specific survival and activation of B cells by downregulating ROS production and modulating mitochondrial functions.
Supported by a grant from NIH (RO1 GM064625)
Multiomic Spatial Phenotyping of the Tumor Immune Microenvironment at Single Cell Resolution
Authors: Jhaveri Niyati , Ji HaYeun , Dikshit Anushka , Yuan Jessica , Doolittle Emerald , Zhou Steve , Srinivasan Maithreyan , Darling Julia Kennedy , Braubach Oliver 
Published: August 2023

Abstract
The Tumor microenvironment (TME) is critical in cancer development, progression, and control. Immunological components within tumors, known as the tumor immune microenvironment (TIME), have been implicated in cancer progression. Effective strategies for cancer immunotherapies will require a deep understanding of factors that shape the TME and TIME. Here, we describe a spatial multiomics assay utilizing RNAscope™ ISH technology paired with high-plex whole-slide spatial phenotyping with the PhenoCycler®-Fusion platform. This two-step approach is compatible with human FFPE tissues and enables characterization of the TIME more accurately by detecting RNA and protein markers on serial sections.
We performed ultrahigh-plex spatial phenotyping on FFPE tumor tissue sections, using an antibody panel designed for immune cell phenotyping, evaluation of immune contexture and proliferation across the TME. On a serial section, we ran the RNAscope HiPlex v2 assay using the PhenoCycler-Fusion system. This assay consisted of a 12-plex immuno-oncology panel of RNA target probes, which detect macrophages, chemokines, and cytokines.
In this proof-of-concept study, we demonstrate multiomic spatial phenotyping on the PhenoCycler-Fusion platform. Analysis of the resulting multiplex imaging data revealed structural organization of cells within the TME and activation states of immune cells. Together, this information provides a more complete functional map of immune cells within the TME and TIME and thereby enriches our understanding of tumor biology that may be deterministic of immunotherapy responsiveness.
Optimization of CRISPR-Cas9 Mediated Knockout Protocol in Primary Human Myeloid Cells
Authors: Ruvalcaba Angel , Reijneveld Josephine F , Suliman Sara 
Published: August 2023

Abstract
Myeloid cells are an important player in the immune system, and form the first line of defense against pathogens, such as Mycobacterium tuberculosis (Mtb), the causative pathogen for tuberculosis (TB) disease. They include macrophages, a target of Mtb infection, and dendritic cells (DCs), which present Mtb-derived antigens to prime and activate T cells. In order to investigate myeloid-specific host factors involved in the response to Mtb infection, we sought to optimize a protocol to genetically edit primary human monocyte-derived DCs and macrophages for subsequent infection experiments with Mtb. We built on prior published protocol by Hiatt, et al. to edit monocyte-derived DCs and macrophages using nucleofection with ribonucleoproteins (RNP), which are Cas9 recombinant protein complexed with multiplexed guide RNA (gRNA) molecules. We tested reaction volume, RNP concentration, rest time, and nucleofection programs. We found that a molar ratio of Cas9:gRNA was most efficient at 1:2 at 1.8μM final RNP concentration in combination with a 2hr rest time after nucleofection before adding differentiation supplement. Lonza nucleofection program EA100 proved to be the optimal program with the most recovered cells. In conclusion, we optimized a robust protocol for editing and culturing edited primary monocyte-derived DCs and macrophages. This opens opportunities for interrogation of candidate TB risk genes such as Fumarylacetoacetate hydrolase (FAH). These cells can now be used for mechanistic studies of Mtb infection to define mechanisms of pathogenesis.
FastqToGenCounts: Converting Fastq Files to Gene Counts Matrices
Authors: Loecker Josh , Bessell Brandt 
Published: August 2023

Abstract
FastqToGeneCounts is a computational pipeline built on Snakemake to process and analyze bulk RNA sequencing data to determine gene expression. It can handle raw data from the Gene Expression Omnibus or local FastQ files and runs on a supercomputing cluster. The primary function of FastqToGeneCounts is to align FastQ files to a reference genome. To ensure accurate outputs, it also offers trimming, quality control, and contaminant screening options.
One of the benefits of using FastqToGeneCounts is that it addresses the issues commonly encountered with traditional alignment workflows. These include the need for manual file naming and directory setup, which can lead to errors and problems resuming failed workflows. Additionally, these workflows often require many resources requested at once, leading to long “wait times” for cluster access. Modifying parameters can also be challenging, as most settings are not localized to a single file.
In contrast, FastqToGeneCounts integrates with Snakemake to improve resume-ability, minimize resource usage, and provide easy parameter modification. Jobs can be resumed from a failed state, only the minimum required resources are requested to reduce waiting time, and a single YAML file can be used to configure parameters within the pipeline.
FastqToGeneCounts has been used to analyze four immature natural killer datasets and has successfully determined gene expression in these samples. It is capable of analyzing a single raw RNA-seq input file in approximately 15 compute minutes, and additional files do not increase runtime due to Snakemake’s high interoperability with SLURM. FastqToGeneCounts removes poor-quality reads from downstream analysis and presents results in an easy-to-read report.
Artificial Intelligence (AI) based approach for identifying biomarkers associated with neutralizing antidrug antibodies to Factor VIII used in Hemophilia A treatment
Authors: Rawal Atul , Kidchob Christopher , Ou Jiayi , Yogurtcu Osman N , Yang Hong , Sauna Zuben E 
Published: August 2023

Abstract
Lack of clinically validated markers associated with the development of neutralizing antibodies (inhibitors) to the replacement protein-drug, Factor VIII (FVIII) is a major challenge in managing Hemophilia A (HA). By utilizing Machine Learning (ML) and Explainable AI (XAI) we identified and ranked relevant variables (biomarkers) that could be predictive for developing inhibitors to FVIII drugs in hemophilia A patients. The dataset used for the study was derived from the My Life Our Future (MLOF) repository and included variables such as age, race, ethnicity, mutations in the F8 gene and the Human Leucocyte Antigen Class II (HLA-II) type. We computed the number of foreign FVIII derived peptides, based on the alignment of the endogenous FVIII and infused drug sequences, and the foreign-peptide HLA-II molecule binding affinity (using the NetMHCIIpan algorithm). The complete dataset with the added variables was trained and validated using multiple ML classification models to identify the top performing model, which was chosen for further processing with XAI via SHAP (SHapley Additive exPlanations) to identify the variables critical for the prediction of FVIII inhibitor development in a hemophilia A patients. The top five variables for predicting inhibitor development based on SHAP values are: (i) the baseline activity of the FVIII protein, (ii) mean affinity of all foreign peptides for HLA DRB 3, 4, & 5 alleles, (iii) mean affinity of all foreign peptides for HLA DRB1 alleles, (iv) the maximum affinity among all foreign peptides for HLA DRB1 alleles, and (v) F8 mutation type.
This research was supported by funds from the Hemostasis Branch/Division of Plasma Protein 344 Therapeutics/Office of Tissues and Advanced Therapies/Center for Biologics Evaluation and Research 345 of the U.S. Food and Drug Administration and in part by an appointment to the Research Participation 346 Program at the Center for Biologics Evaluation and Research administered by the Oak Ridge Institute 347 for Science and Education through an interagency agreement between the U.S. Department of Energy 348 and the U.S. Food and Drug Administration. The MLOF program was developed as a partnership 349 between NHF, ATHN, Bloodworks Northwest, and Bioverativ and supported financially by 350 Bioverativ, NHF, Bloodworks Northwest, and ATHN.
Expanding panel size in spectral flow cytometry with StarBright Dyes excitable by the ultraviolet (355 nm), violet (405 nm), blue (488 nm) and yellow (561 nm) lasers
Authors: Blundell Michael , Sanderson Sharon 
Published: August 2023

Abstract
The recently launched fluorescent dyes from Bio-Rad, StarBright Dyes, deliver tunable brightness and spectral properties, greater stability, improved lot-to-lot reproducibility, and spectral consistency. Specifically designed for multicolor flow cytometry with researchers needs in mind, StarBright Dyes address the common pain points in flow such as brightness, broad emission spectra, staining consistency, and ease-of-use, solving issues of signal resolution when constructing complex panels. These bright dyes have the additional benefit of a unique full spectral profile, making them ideal for inclusion in spectral flow cytometry, when creating multicolor panels.
Here we present data of our newest additions to the StarBright range, the StarBright Blue and StarBright Yellow Dyes on a five-laser spectral cell analyzer. Both dye series are bright and allow expansion across the 488 and 561 lasers giving more dye choice for all panel sizes but are particularly useful when large panel design is required.
In this study we show, when StarBright Blue and StarBright Yellow Dyes are combined with other members of the StarBright Dye range, polymer dyes and traditional fluorescent dyes, very large immunophenotyping panels can be constructed allowing identification of many peripheral blood subsets. In addition, novel dye combinations can be identified increasing the numbers of dyes and therefore markers identified from one sample.
When combined with their ability to be fixed in both PFA based and alcohol-based fixatives, with minimal spectral changes, and to be pre-mixed for up to 33 days, the flexibility of StarBright Dyes means they are ideal for new and expanding existing panels regardless of the type of flow cytometer being used.
Mapping the gene space at single-cell resolution with gene signal pattern analysis
Authors: Venkat Aarthi , Damo Martina , Joshi Nikhil S , Krishnaswamy Smita 
Published: August 2023

Abstract
In single-cell RNA sequencing analysis, several computational methods have been developed to map the cellular state space, but little has been done to map the gene space. A mapping that preserves gene-gene relationships within the dataset is particularly useful for characterizing cellular heterogeneity within cell types, where boundaries between cell subpopulations are often unclear or even arbitrary.
Here, we present gene signal pattern analysis, a new paradigm for analyzing single cells. We build a cell-cell graph and design a dictionary of diffusion wavelets, capturing a multiscale view of the cell space. We then transform genes by the dictionary and learn a reduced gene representation. Given the gap in prior research for this problem, we design nine alternative strategies and three benchmarks for evaluating preservation of gene-gene relationships, all of which are outperformed by diffusion wavelet-transformed signals. We also define, calculate, and evaluate localization, a key property of a gene signal on the cellular graph.
We demonstrate the utility of gene signal pattern analysis on T cells from a mouse model of peripheral tolerance in skin. The gene space mapping reveals a continuum of gene signals characterized by T cell subtypes and transcriptional programs related to effector function and proliferation. Furthermore, we built a multiscale manifold of 48 melanoma patient samples, demonstrating the ability of our method to characterize differences between responders and non-responders to checkpoint immunotherapy. Together, we show gene signal pattern analysis, through methodology from graph signal processing, spectral graph theory, and machine learning, represents an avenue for future research in scRNA-seq analysis.
Gruber Foundation
Flexible and high-throughput approach for capturing large number of single cells simultaneously using microwell-based technology
Authors: Nguyen Rosary , Hlathu Zorine , Gordon Chelsea , Zhao Xueying , Moskwa Jamie , Jensen Devon , Acob Ricelle A , Wang Larry , Ayer Aruna 
Published: August 2023

Abstract
Single-cell RNA-seq is a powerful method for studying complex cell populations. As opportunities grow for single-cell multiomics methods in translational research, there is an increased need for high-throughput approaches capable of efficiently capturing and analyzing large numbers of cells simultaneously. Current assays on scRNA-seq platforms have limited throughput due to the low cell recovery and high multiplet rates with high cell inputs.
Here we demonstrate the feasibility of profiling the single-cell gene expression of hundreds of thousands of cells in a single experiment using an eight-lane microwell based cartridge. We also increased the cell label diversity of cell capture beads to enable high cell loading with a lower rate of barcode collisions. To show the range of cell capture capabilities of the eight-lane microwell cartridge, we loaded different numbers of cells per lane ranging from 100 to over 40,000 cells. To evaluate the multiplet rates and sensitivity, we labeled two different cell types with antibody-based sample multiplexing prior to cell capture. Cell multiplet rates were also assessed through Sample Tag analysis. Detection of Sample Tags used showed no contamination of Sample Tag between samples. In addition, less than 0.5% barcode collision rate was detected from 360,000 viable cells captured with a bead. Targeted mRNA profiling had high correlation (R2 &gt; 0.95) of gene expression across cell capture lanes. This study demonstrates that the eight-lane microwell-based cartridge technology provides flexibility and high-throughput cell capture of thousands of cells and could be readily extended to other existing single-cell technologies such as surface protein marker detection and immune profiling.
Universal, open MHC-I for rapid ligand loading and enhanced complex stability across classical and non-classical allotypes
Authors: Young Michael C , Sun Yi , Woodward Claire H , Danon Julia N , Truong Hau V , Sgourakis Nikolaos G 
Published: August 2023

Abstract
The instability of class I major histocompatibility complex (MHC-I) and MHC-like molecules loaded with suboptimal peptides, metabolites, or glycolipids presents an important biochemical challenge for identifying disease-relevant antigens and antigen-specific T cell receptors (TCRs) for autologous therapy development. Here, we leverage the coupled binding between ligand and the light chain (beta-2 microglobulin, β2 m) to the MHC-I heavy chain with the aim of developing conformationally stable molecules by engineering a disulfide bond to bridge the interface between the heavy and light chain. The resulting MHC-I molecules are stabilized in a ligand-receptive/open state, exhibit favorable ligand exchange properties, and are readily loaded with moderate affinity ligands to afford properly conformed protein complexes of enhanced stability compared to the wild type. We demonstrate the generality of the structural design using polymorphic HLA representatives covering multiple HLA-A and B supertypes, the nonclassical and oligomorphic HLA-Ib molecules, as well as MHC-like molecules, MR1 and CD1. Our platform allows spontaneous and rapid ligand exchange, which enables a range of approaches for ligand screening and the functional screening and characterization of polyclonal TCR repertoires.
Supported by grants from NIH (R01AI143997, R35GM125034, U01DK112217).
Comparison of CITE-Seq assay noise between leading microwell and droplet systems
Authors: Campbell Tracy L , Martin Jody , Song Hye-Won , Wang Larry , Ayer Aruna 
Published: August 2023

Abstract
CITE-Seq experiments in combination with whole transcriptome analysis (WTA) can provide researchers with invaluable multiomics data to answer critical cellular biology questions. In selecting the right platform to answer these questions, researchers are confronted with a myriad of options and the benefits of each may not always be clear when comparing summary metrics alone.
Proteomics assays using oligo-conjugated antibodies have metrics beyond sensitivity to consider when choosing the right platform, for example antibody specificity as well as antibody oligo-mediated noise. Noise from negative populations in a CITE-Seq experiment can add to overall experiment costs while complicating downstream analysis and obscuring conclusions.
In this study, we are comparing a CITE-Seq assay in combination with WTA between the leading microwell and droplet-based systems while controlling for final antibody staining concentrations.
We demonstrate that the CITE-Seq assay on the microwell-based system has higher resolution and less noise than the droplet system when comparing across two PBMC donors.
© 2023 BD. All rights reserved. NPM-0171 (v1.0) 0123
Fast Preparation of Peptide Tools to address new emerging Viruses: Case example SARS-CoV-2
Authors: Castro Aaron , Pfeil S , Holenya Pavlo , Reimer Ulf , Knaute Tobias , Zerweck Jonny , Eckey Maren , Kern Florian , Drosch Michael , Alem Aude Marie , Wenschuh Holger , Schnatbaum Karsten 
Published: August 2023

Abstract
The emergence of new virus species or variants poses a major challenge for healthcare systems. Countermeasures, including vaccine development, need to be developed without delay to ensure success. Vaccine and antibody development depend on highly efficient tools for antigen discovery, epitope mapping, diagnostics and (clinical) immune monitoring.
Here we present a workflow for peptide tool development that can be rapidly adapted to emerging viruses. It combines bioinformatics algorithms and an ultra-high throughput peptide synthesis method alongside high-content assay formats.
Data from different SARS-CoV-2 studies are presented addressing elucidation of both cellular and humoral immune responses. Robust spike-specific cellular immune responses were measured using SARS-CoV-2 Spike PepMix™ peptide pools during infection and/or vaccine response monitoring [1]. Using epitope mapping (matrix) pools an immunodominant T-cell epitope was identified that may contribute to the optimization of existing vaccines [2]. In addition, the immune response of Covid-19 convalescents against all major SARS-CoV-2 proteins was analyzed [2]. Humoral immune response analysis by high-density peptide microarrays identified immunodominant B cell epitopes as starting points for the development of alternative vaccines and diagnostic tests [3].
In conclusion, we show that readily available and tailored peptide formats, as exemplified for SARS-CoV-2, are important tools that contribute to the fast development and optimization of vaccines and diagnostic tests for emerging viruses of concern.