Article
Multidisciplinary Sciences
Yingxin Lin, Yue Cao, Elijah Willie, Ellis Patrick, Jean Y. H. Yang
Summary: The emergence of multi-sample multi-condition single-cell multi-cohort studies allows researchers to investigate different cell states. The algorithm scMerge2 enables integration and analysis of large-scale single-cell datasets, revealing accurate signatures of disease progression and removing dataset variability in various single-cell profiling technologies.
NATURE COMMUNICATIONS
(2023)
Article
Multidisciplinary Sciences
Wanying Wu, Jinyang Zhang, Xiaofei Cao, Zhengyi Cai, Fangqing Zhao
Summary: This study explores the cellular landscape of circular RNAs (circRNAs) in human and mouse tissues using single-cell RNA-seq datasets. Through large-scale analysis, a large number of circRNAs in humans and mice are identified. The circRNAs are validated through integration with other resources. The study reveals the expression pattern of circRNAs in different cell types and tumors, and their application in immune cell composition deconvolution is validated.
NATURE COMMUNICATIONS
(2022)
Article
Biochemical Research Methods
Leah L. Weber, Palash Sashittal, Mohammed El-Kebir
Summary: The study introduces a standalone method, doubletD, for detecting doublets in scDNA-seq data, achieving high performance through a simple maximum likelihood approach that outperforms current methods. Applying doubletD in scDNA-seq analysis pipelines can reduce complexity and improve result accuracy.
Article
Biochemistry & Molecular Biology
Qi Song, Matthew Ruffalo, Ziv Bar-Joseph
Summary: Inference of global gene regulatory networks from omics data is a long-term goal of systems biology. We developed a new computational method that combines neural networks and multi-task learning to predict RNA velocity rather than gene expression values. Application of our method to atlas scale single cell data from 6 HuBMAP tissues led to several validated and novel predictions and greatly improved on prior methods proposed for this task.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Biochemical Research Methods
Zhenhua Yu, Fang Du
Summary: Single-cell DNA sequencing allows for high-resolution analysis of intra-tumor heterogeneity. Existing methods for phylogenetic inference from scDNA-seq data perform well on small datasets, but are computationally inefficient and less accurate on large datasets. In this study, we introduce a new software called AMC that accurately clusters mutations, improving the efficiency of phylogenetic inference.
Article
Multidisciplinary Sciences
Alok K. Maity, Andrew E. Teschendorff
Summary: This study introduces a differential abundance testing paradigm called ELVAR, which uses cell attribute aware clustering to infer differentially enriched communities within the single-cell manifold. By benchmarking ELVAR against other algorithms using simulated and real datasets, the authors demonstrate that ELVAR improves the sensitivity to detect cell-type composition shifts in relation to aging, precancerous states, and Covid-19 phenotypes. Leveraging cell attribute information helps denoise single-cell data, avoid batch correction, and retrieve more robust cell states for subsequent differential abundance testing.
NATURE COMMUNICATIONS
(2023)
Article
Biochemical Research Methods
Wenpin Hou, Zhicheng Ji
Summary: Palo optimizes the color palette assignment for improved visualization in single-cell and spatial genomic data analysis.
Article
Biochemical Research Methods
Cassandra Burdziak, Chujun Julia Zhao, Doron Haviv, Direna Alonso-Curbelo, Scott W. Lowe, Dana Pe'er
Summary: scKINETICS is a dynamical model that fits gene expression change with the learning of per-cell transcriptional velocities and a governing gene regulatory network. It successfully recapitulates the process of acinar-to-ductal transdifferentiation and proposes novel regulators of this process in an acute pancreatitis dataset. In benchmarking experiments, scKINETICS extends and improves existing velocity approaches to generate interpretable, mechanistic models of gene regulatory dynamics.
Article
Biochemical Research Methods
Jiaqian Yan, Ming Ma, Zhenhua Yu
Summary: bmVAE is a bioinformatics tool that utilizes variational autoencoder to learn low-dimensional latent representation of single cells and clusters cells in the latent space. It has been demonstrated to be effective in uncovering genomic intra-tumor heterogeneity, performing competitively with existing methods, through evaluations on synthetic and real datasets.
Article
Biochemical Research Methods
Johannes Smolander, Sini Junttila, Laura L. Elo
Summary: Totem is an open-source and user-friendly R package for inferring tree-shaped trajectories from single-cell data. It generates a large number of clustering results, estimates their topologies as minimum spanning trees, and uses them to measure cell connectivity. Totem allows for automatic selection of an appropriate trajectory and provides a visual representation of branching points and milestones relevant to the trajectory. Furthermore, testing different trajectories with Totem is easy, fast, and does not require expertise in methodology.
Article
Genetics & Heredity
David F. Stein, Huidong Chen, Michael E. Vinyard, Qian Qin, Rebecca D. Combs, Qian Zhang, Luca Pinello
Summary: Single-cell assays have revolutionized the modeling of heterogeneity within cell populations. Virtual Reality (VR) technology shows promise for visualizing complex single-cell data, but is hindered by expensive hardware and advanced data preprocessing requirements.
FRONTIERS IN GENETICS
(2021)
Article
Biochemical Research Methods
Yanglan Gan, Cheng Guo, Wenjing Guo, Guangwei Xu, Guobing Zou
Summary: The development of single-cell RNA-seq technology enables researchers to characterize cell types, states, and transitions in dynamic biological processes at single-cell resolution. This study proposes a new method called scTite, which is based on transition entropy, to identify transitional states and reconstruct cell trajectories accurately from scRNA-seq data.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Multidisciplinary Sciences
Rui Hong, Yusuke Koga, Shruthi Bandyadka, Anastasia Leshchyk, Yichen Wang, Vidya Akavoor, Xinyun Cao, Irzam Sarfraz, Zhe Wang, Salam Alabdullatif, Frederick Jansen, Masanao Yajima, W. Evan Johnson, Joshua D. Campbell
Summary: The authors present the SCTK-QC pipeline, which generates and visualizes a comprehensive set of QC metrics to streamline the process of detecting and removing poor quality cells and artifacts in scRNA-seq data. The pipeline can import data from different platforms, perform multiple QC tasks, and run on various programming environments.
NATURE COMMUNICATIONS
(2022)
Article
Biochemical Research Methods
Jing Xu, Aidi Zhang, Fang Liu, Xiujun Zhang
Summary: This paper introduces an interpretable transformer-based method called STGRNS for inferring gene regulatory networks (GRNs) from scRNA-seq data. By using a gene expression motif technique, gene pairs are converted into contiguous sub-vectors for transformer encoding. The experimental results show that STGRNS outperforms other methods on various scRNA-seq data types and is more interpretable than black box deep learning methods.
Article
Biochemistry & Molecular Biology
David DeTomaso, Nir Yosef
Summary: The study introduces a general approach named Hotspot for analyzing single-cell RNA-seq data to identify informative gene variations and determine gene organization into modules. By operating directly on a given metric of cell-cell similarity, Hotspot can identify genes that reflect alternative notions of similarity between cells.
Article
Multidisciplinary Sciences
Juraj Adamik, Paul Munson, Felix J. Hartmann, Alexis J. Combes, Philippe Pierre, Matthew F. Krummel, Sean C. Bendall, Rafael J. Arguello, Lisa H. Butterfield
Summary: Assessing metabolic activity at the single-cell level provides important insights into the immune profiles of human dendritic cells. This study reveals the metabolic differences between immune stimulatory and tolerogenic dendritic cells, and highlights the simultaneous engagement of multiple metabolic pathways in distinct stages of dendritic cell differentiation.
NATURE COMMUNICATIONS
(2022)
Article
Biochemistry & Molecular Biology
Rashmi Kumar, Candace C. C. Liu, Sean C. Bendall, Michael Angelo
Summary: This study introduces a synthesis method of a dendrimer-based polymer and its application in MIBI-TOF tissue imaging. By comparing the staining performance of antibodies conjugated with dendrimers or linear polymers in FFPE tissue, it was found that dendrimers and linear polymers have comparable avidities. Moreover, dendrimers have advantages such as less background staining and no off-target binding in neural tissue. Overall, this research provides a versatile framework for using third-generation dendrimer-conjugated antibodies with improved staining compared to conventional linear polymers.
Article
Oncology
Paul Munson, Juraj Adamik, Felix J. Hartmann, Patricia M. B. Favaro, Daniel Ho, Sean C. Bendall, Alexis J. Combes, Matthew F. Krummel, Karen Zhang, Robin K. Kelley, Lisa H. Butterfield
Summary: Hepatocellular cancer tumors express a-Fetoprotein (AFP), which inhibits dendritic cell differentiation and maturation, and blocks oxidative phosphorylation. Tumor-derived AFP increases glycolytic capacity and glucose dependence of dendritic cells, leading to increased glucose uptake and lactate secretion. Furthermore, AFP bound with polyunsaturated fatty acids (PUFAs) skews dendritic cell metabolism and promotes immune suppression.
Review
Immunology
YeEun Kim, William J. Greenleaf, Sean C. Bendall
Summary: Single-cell technologies have revealed the heterogeneity and complexity of the immune system. Systems biology approaches in immunology have utilized high-parameter, high-throughput data to analyze immune cell types. This approach has led to the discovery of new cell types and functions, especially in the field of human immunology. This review focuses on recent findings in lymphocyte biology enabled by systems approaches and discusses the challenges of handling high-dimensional datasets.
CURRENT OPINION IN IMMUNOLOGY
(2023)
Editorial Material
Immunology
Hadeesha Piyadasa, Michael Angelo, Sean C. Bendall
Summary: Capturing cell organization in the tumor microenvironment using spatial proteomics can provide insight into the disease. A pair of studies applying this to advanced lung and brain tumors identifies organizational immune hallmarks that are associated with patient outcomes.
Article
Multidisciplinary Sciences
Jolanda Sarno, Pablo Domizi, Yuxuan Liu, Milton Merchant, Christina Bligaard Pedersen, Dorra Jedoui, Astraea Jager, Garry P. Nolan, Giuseppe Gaipa, Sean C. Bendall, Felice-Alessio Bava, Kara L. Davis
Summary: Resistance to glucocorticoids (GC) in B-cell progenitor acute lymphoblastic leukemia (BCP-ALL) is driven by coordination between the glucocorticoid receptor pathway and B-cell developmental pathways. The interplay between B-cell development and glucocorticoid pathways is crucial for GC resistance in leukemic cells. Targeting the active signaling through the addition of dasatinib may represent a therapeutic approach to overcome GC resistance in BCP-ALL.
NATURE COMMUNICATIONS
(2023)
Article
Multidisciplinary Sciences
Makeda L. Robinson, David R. Glass, Veronica Duran, Olga Lucia Agudelo Rojas, Ana Maria Sanz, Monika Consuegra, Malaya Kumar Sahoo, Felix J. Hartmann, Marc Bosse, Rosa Margarita Gelvez, Nathalia Bueno, Benjamin A. Pinsky, Jose G. Montoya, Holden Maecker, Maria Isabel Estupinan Cardenas, Luis Angel Villar Centeno, Elsa Marina Rojas Garrido, Fernando Rosso, Sean C. Bendall, Shirit Einav
Summary: Approximately 5 million dengue virus-infected patients progress to severe dengue (SD) infection annually. This study reveals uncoordinated immune responses in SD patients and provides insights into SD pathogenesis in humans with potential implications for prediction and treatment.
Article
Multidisciplinary Sciences
Eloise Berson, Chandresh R. Gajera, Thanaphong Phongpreecha, Amalia Perna, Syed A. Bukhari, Martin Becker, Alan L. Chang, Davide De Francesco, Camilo Espinosa, Neal G. Ravindra, Nadia Postupna, Caitlin S. Latimer, Carol A. Shively, Thomas C. Register, Suzanne Craft, Kathleen S. Montine, Edward J. Fox, C. Dirk Keene, Sean C. Bendall, Nima Aghaeepour, Thomas J. Montine
Summary: Comparing brain structure across species and regions allows for important functional insights. In this study, a novel mass cytometry-based method called synaptometry by time of flight (SynTOF) was used to compare presynapse molecular abundance across three species and three brain regions. The results showed significant differences in presynaptic composition between human, macaque, and mouse samples, with a notable overlap between human and macaque in certain brain regions.
SCIENTIFIC REPORTS
(2023)
Article
Cell Biology
Mahil Rao, Meelad Amouzgar, James T. Harden, M. Gay Lapasaran, Amber Trickey, Brian Armstrong, Jonah Odim, Tracia Debnam, Carlos O. Esquivel, Sean C. Bendall, Olivia M. Martinez, Sheri M. Krams
Summary: Solid organ transplant is a life-saving therapy for children with end-stage organ diseases, but a significant proportion of recipients experience acute rejection. This study analyzed the immune composition of pediatric solid organ transplant recipients using high-dimensional mass cytometry, and found that the type of organ transplant strongly influences the post-transplant immune profile. Changes in the proportion of different T cell subpopulations are associated with graft health. These findings provide a basis for further understanding and developing new immunosuppressive agents.
CELL REPORTS MEDICINE
(2023)
Article
Multidisciplinary Sciences
Yunhao Bai, Bokai Zhu, John-Paul Oliveria, Bryan J. Cannon, Dorien Feyaerts, Marc Bosse, Kausalia Vijayaragavan, Noah F. Greenwald, Darci Phillips, Christian M. Schuerch, Samuel M. Naik, Edward A. Ganio, Brice Gaudilliere, Scott J. Rodig, Michael B. Miller, Michael Angelo, Sean C. Bendall, Xavier Rovira-Clave, Garry P. Nolan, Sizun Jiang
Summary: Emerging high-plex imaging technologies are limited in resolving subcellular biomolecular features. Here, the authors propose a spatial histopathology tool that allows for high-plex protein staining and physical expansion, while retaining the lateral tissue expansion.
NATURE COMMUNICATIONS
(2023)
Meeting Abstract
Pediatrics
Mahil Rao, Meelad Amouzgar, James T. Harden, Mary G. Lapasaran, Amber Trickey, Brian Armstrong, Jonah Odim, Tracia Debnam, Carlos O. Esquivel, Sean C. Bendall, Olivia M. Martinez, Sheri M. Krams
PEDIATRIC TRANSPLANTATION
(2023)
Meeting Abstract
Rheumatology
Sven Wischnewski, Chiseko Ikenaga, Anna Kocharyan, Thomas Thaewel, Amel Zulji, Hans-Werner Rausch, Celia Lerma Martin, Dunja Mrdjen, David Brenner, Lukas Bunse, Chin Leng Tan, Leonie Thomas, Michael Kutza, Tim Trobisch, Corinna Preusse, Nicole Reed, Harald D. Von Pein, Angela Rosenbohm, Albert Ludolph, Ahmet Hoke, Michael Platten, Sean C. Bendall, Jochen H. Weishaupt, Clemens J. Sommer, Werner Stenzel, Thomas E. Lloyd, Lucas Schirmer
CLINICAL AND EXPERIMENTAL RHEUMATOLOGY
(2023)
Article
Multidisciplinary Sciences
Juraj Adamik, Paul V. Munson, Deena M. Maurer, Felix J. Hartmann, Sean C. Bendall, Rafael J. Arguello, Lisa H. Butterfield
Summary: This study analyzed the transcriptomic and immune-metabolic profiles of dendritic cells (DCs) from patients with late-stage melanoma. The results suggest that the metabolic profile of DCs is associated with the immunostimulatory potential of cancer vaccines.
NATURE COMMUNICATIONS
(2023)
Meeting Abstract
Hematology
Patricia Favaro, David Glass, Luciene Borges, Reema Baskar, Warren Reynolds, Daniel Ho, Trevor Bruce, Dmitry Tebaykin, Albert Tsai, Ilya Shestopalov, Sean Bendall
EXPERIMENTAL HEMATOLOGY
(2023)
Meeting Abstract
Oncology
Pablo Domizi, Jolanda Sarno, Astraea Jager, Maria Caterina Rotiroti, Reema Baskar, Warren Reynolds, Bita Sahaf, Sean Bendall, Charles Mullighan, Allison Leahy, Regina Myers, Stephan Grupp, Robbie Majzner, Elena Sotillo, David Barrett, Kara Davis
PEDIATRIC BLOOD & CANCER
(2022)