The need to reassess single-cell RNA sequencing datasets: the importance of biological sample processing

Challenges and opportunities to computationally deconvolve heterogeneous tissue with varying cell sizes using single-cell RNA-sequencing datasets

Deconvolution of cell mixtures in "bulk" transcriptomic samples from homogenate human tissue is important for understanding disease pathologies. However, several experimental and computational challenges impede transcriptomics-based deconvolution approaches using single-cell/nucleus RNA-seq reference atlases. Cells from the brain and blood have substantially different sizes, total mRNA, and transcriptional activities, and existing approaches may quantify total mRNA instead of cell type proportions. Further, standards are lacking for the use of cell reference atlases and integrative analyses of single-cell and spatial transcriptomics data. We discuss how to approach these key challenges with orthogonal "gold standard" datasets for evaluating deconvolution methods.

Simultaneous selection of nanobodies for accessible epitopes on immune cells in the tumor microenvironment

In the rapidly advancing field of synthetic biology, there exists a critical need for technology to discover targeting moieties for therapeutic biologics. Here we present INSPIRE-seq, an approach that utilizes a nanobody library and next-generation sequencing to identify nanobodies selected for complex environments. INSPIRE-seq enables the parallel enrichment of immune cell-binding nanobodies that penetrate the tumor microenvironment. Clone enrichment and specificity vary across immune cell subtypes in the tumor, lymph node, and spleen. INSPIRE-seq identifies a dendritic cell binding clone that binds PHB2. Single-cell RNA sequencing reveals a connection with cDC1s, and immunofluorescence confirms nanobody-PHB2 colocalization along cell membranes. Structural modeling and docking studies assist binding predictions and will guide nanobody selection. In this work, we demonstrate that INSPIRE-seq offers an unbiased approach to examine complex microenvironments and assist in the development of nanobodies, which could serve as active drugs, modified to become drugs, or used as targeting moieties.

Understanding Fibroblast Heterogeneity in Form and Function

Historically believed to be a homogeneous cell type that is often overlooked, fibroblasts are more and more understood to be heterogeneous in nature. Though the mechanisms behind how fibroblasts participate in homeostasis and pathology are just beginning to be understood, these cells are believed to be highly dynamic and play key roles in fibrosis and remodeling. Focusing primarily on fibroblasts within the skin and during wound healing, we describe the field's current understanding of fibroblast heterogeneity in form and function. From differences due to embryonic origins to anatomical variations, we explore the diverse contributions that fibroblasts have in fibrosis and plasticity. Following this, we describe molecular techniques used in the field to provide deeper insights into subpopulations of fibroblasts and their varied roles in complex processes such as wound healing. Limitations to current work are also discussed, with a focus on future directions that investigators are recommended to take in order to gain a deeper understanding of fibroblast biology and to develop potential targets for translational applications in a clinical setting.

Challenges and Opportunities for the Translation of Single-Cell RNA Sequencing Technologies to Dermatology

Skin is a complex and heterogeneous organ at the cellular level. This complexity is beginning to be understood through the application of single-cell genomics and computational tools. A large number of datasets that shed light on how the different human skin cell types interact in homeostasis-and what ceases to work in diverse dermatological diseases-have been generated and are publicly available. However, translation of these novel aspects to the clinic is lacking. This review aims to summarize the state-of-the-art of skin biology using single-cell technologies, with a special focus on skin pathologies and the translation of mechanistic findings to the clinic. The main implications of this review are to summarize the benefits and limitations of single-cell analysis and thus help translate the emerging insights from these novel techniques to the bedside.