Integrated Single-Cell (Phospho-)Protein and RNA Detection Uncovers Phenotypic Characteristics and Active Signal Transduction of Human Antibody-Secreting Cells

Understanding developing kidneys and Wilms tumors one cell at a time

Single-cell sequencing-based techniques are revolutionizing all fields of biomedical sciences, including normal kidney development and how this is disturbed in the development of Wilms tumor. The many different techniques and the differences between them can obscure which technique is best used to answer which question. In this review we summarize the techniques currently available, discuss which have been used in kidney development or Wilms tumor context, and which techniques can or should be combined to maximize the increase in biological understanding we can get from them.

Integrative single-cell chromatin and transcriptome analysis of human plasma cell differentiation

ABSTRACT

Plasma cells (PCs) are highly specialized cells representing the end stage of B-cell differentiation. We have shown that PC differentiation can be reproduced in vitro using elaborate culture systems. The molecular changes occurring during PC differentiation are recapitulated in this in vitro differentiation model. However, a major challenge exists to decipher the spatiotemporal epigenetic and transcriptional programs that drive the early stages of PC differentiation. We combined single cell (sc) RNA sequencing (RNA-seq) and assay for transposase-accessible chromatin with high throughput sequencing (scATAC-seq) to decipher the trajectories involved in PC differentiation. ScRNA-seq experiments revealed a strong heterogeneity of the preplasmablastic and plasmablastic stages. Among genes that were commonly identified using scATAC-seq and scRNA-seq, we identified several transcription factors with significant stage specific potential importance in PC differentiation. Interestingly, differentially accessible peaks characterizing the preplasmablastic stage were enriched in motifs of BATF3, FOS and BATF, belonging to activating protein 1 (AP-1) transcription factor family that may represent key transcriptional nodes involved in PC differentiation. Integration of transcriptomic and epigenetic data at the single cell level revealed that a population of preplasmablasts had already undergone epigenetic remodeling related to PC profile together with unfolded protein response activation and are committed to differentiate in PC. These results and the supporting data generated with our in vitro PC differentiation model provide a unique resource for the identification of molecular circuits that are crucial for early and mature PC maturation and biological functions. These data thus provide critical insights into epigenetic- and transcription-mediated reprogramming events that sustain PC differentiation.

New insights into the mechanisms regulating plasma cell survival and longevity

Plasma cells correspond to the last stage of B cell differentiation and are professional antibody-secreting cells. While most persist for only few days, some may survive for weeks to years in dedicated survival niches. The determination of plasma cell survival rate seems to rely both on intrinsic and extrinsic factors. Although often opposed, the deterministic and environmental models for plasma cell longevity are certainly overlapping. Understanding the contribution and the regulation of these different factors is paramount to develop better vaccines but also to target malignant plasma cells. Here, we review recent literature highlighting new findings pertaining to plasma cell survival rate, intrinsic regulation of plasma cell persistence and function, as well as the plasma cell/niche dialogue. Moreover, the now well-recognised heterogeneity observed among plasma cells is also discussed.

A review of the current state of single-cell proteomics and future perspective

Single-cell methodologies and technologies have started a revolution in biology which until recently has primarily been limited to deep sequencing and imaging modalities. With the advent and subsequent torrid development of single-cell proteomics over the last 5 years, despite the fact that proteins cannot be amplified like transcripts, it has now become abundantly clear that it is a worthy complement to single-cell transcriptomics. In this review, we engage in an assessment of the current state of the art of single-cell proteomics including workflow, sample preparation techniques, instrumentation, and biological applications. We investigate the challenges associated with working with very small sample volumes and the acute need for robust statistical methods for data interpretation. We delve into what we believe is a promising future for biological research at single-cell resolution and highlight some of the exciting discoveries that already have been made using single-cell proteomics, including the identification of rare cell types, characterization of cellular heterogeneity, and investigation of signaling pathways and disease mechanisms. Finally, we acknowledge that there are a number of outstanding and pressing problems that the scientific community vested in advancing this technology needs to resolve. Of prime importance is the need to set standards so that this technology becomes widely accessible allowing novel discoveries to be easily verifiable. We conclude with a plea to solve these problems rapidly so that single-cell proteomics can be part of a robust, high-throughput, and scalable single-cell multi-omics platform that can be ubiquitously applied to elucidating deep biological insights into the diagnosis and treatment of all diseases that afflict us.

Single cell proteomics. Potential applications in Head and Neck oncology

In-depth transcriptomic and proteomic analyses are crucial for understanding normal and pathological biology. Next-generation sequencing technology (NGS) is used to assess gene expression, but protein abundance cannot be scaled up due to the lack of methods like PCR. This presents a major obstacle to proteomics at the single-cell level, as protein expression dictates cell state. Biochemists are interested in single-cell analysis of proteins, as analyzing tissues with diverse cell types hides cell-to-cell differences, making it difficult to interpret the resulting data. Single-cell proteomics is a promising field that provides direct yet comprehensive molecular insights into cellular functions without averaging effects. However, protein adsorption loss (PAL) has been a technical challenge, and mitigations have been generic, with efficacy evaluated by the size of the resolved proteome without specificity on individual proteins. Advances in sample processing, separations, and mass spectrometry have made it possible to quantify >1000 proteins from individual mammalian cells, a level of coverage that required thousands of cells just a few years ago.

Mapping the Protein Kinome: Current Strategy and Future Direction

The kinome includes over 500 different protein kinases, which form an integrated kinase network that regulates cellular phosphorylation signals. The kinome plays a central role in almost every cellular process and has strong linkages with many diseases. Thus, the evaluation of the cellular kinome in the physiological environment is essential to understand biological processes, disease development, and to target therapy. Currently, a number of strategies for kinome analysis have been developed, which are based on monitoring the phosphorylation of kinases or substrates. They have enabled researchers to tackle increasingly complex biological problems and pathological processes, and have promoted the development of kinase inhibitors. Additionally, with the increasing interest in how kinases participate in biological processes at spatial scales, it has become urgent to develop tools to estimate spatial kinome activity. With multidisciplinary efforts, a growing number of novel approaches have the potential to be applied to spatial kinome analysis. In this paper, we review the widely used methods used for kinome analysis and the challenges encountered in their applications. Meanwhile, potential approaches that may be of benefit to spatial kinome study are explored.