Intragraft B cell differentiation during the development of tolerance to kidney allografts is associated with a regulatory B cell signature revealed by single cell transcriptomics

Mouse kidney allografts are spontaneously accepted in select, fully mismatched donor-recipient strain combinations, like DBA/2J to C57BL/6 (B6), by natural tolerance. We previously showed accepted renal grafts form aggregates containing various immune cells within 2 weeks posttransplant, referred to as regulatory T cell-rich organized lymphoid structures, which are a novel regulatory tertiary lymphoid organ. To characterize the cells within T cell-rich organized lymphoid structures, we performed single-cell RNA sequencing on CD45+ sorted cells from accepted and rejected renal grafts from 1-week to 6-months posttransplant. Analysis of single-cell RNA sequencing data revealed a shifting from a T cell-dominant to a B cell-rich population by 6 months with an increased regulatory B cell signature. Furthermore, B cells were a greater proportion of the early infiltrating cells in accepted vs rejecting grafts. Flow cytometry of B cells at 20 weeks posttransplant revealed T cell, immunoglobulin domain and mucin domain-1+ B cells, potentially implicating a regulatory role in the maintenance of allograft tolerance. Lastly, B cell trajectory analysis revealed intragraft differentiation from precursor B cells to memory B cells in accepted allografts. In summary, we show a shifting T cell- to B cell-rich environment and a differential cellular pattern among accepted vs rejecting kidney allografts, possibly implicating B cells in the maintenance of kidney allograft acceptance.

Reliably Engineering and Controlling Stable Optogenetic Gene Circuits in Mammalian Cells

Reliable gene expression control in mammalian cells requires tools with high fold change, low noise, and determined input-to-output transfer functions, regardless of the method used. Toward this goal, optogenetic gene expression systems have gained much attention over the past decade for spatiotemporal control of protein levels in mammalian cells. However, most existing circuits controlling light-induced gene expression vary in architecture, are expressed from plasmids, and utilize variable optogenetic equipment, creating a need to explore characterization and standardization of optogenetic components in stable cell lines. Here, the study provides an experimental pipeline of reliable gene circuit construction, integration, and characterization for controlling light-inducible gene expression in mammalian cells, using a negative feedback optogenetic circuit as a case example. The protocols also illustrate how standardizing optogenetic equipment and light regimes can reliably reveal gene circuit features such as gene expression noise and protein expression magnitude. Lastly, this paper may be of use for laboratories unfamiliar with optogenetics who wish to adopt such technology. The pipeline described here should apply for other optogenetic circuits in mammalian cells, allowing for more reliable, detailed characterization and control of gene expression at the transcriptional, proteomic, and ultimately phenotypic level in mammalian cells.

Noise-reducing optogenetic negative-feedback gene circuits in human cells

Gene autorepression is widely present in nature and is also employed in synthetic biology, partly to reduce gene expression noise in cells. Optogenetic systems have recently been developed for controlling gene expression levels in mammalian cells, but most have utilized activator-based proteins, neglecting negative feedback except for in silico control. Here, we engineer optogenetic gene circuits into mammalian cells to achieve noise-reduction for precise gene expression control by genetic, in vitro negative feedback. We build a toolset of these noise-reducing Light-Inducible Tuner (LITer) gene circuits using the TetR repressor fused with a Tet-inhibiting peptide (TIP) or a degradation tag through the light-sensitive LOV2 protein domain. These LITers provide a range of nearly 4-fold gene expression control and up to 5-fold noise reduction from existing optogenetic systems. Moreover, we use the LITer gene circuit architecture to control gene expression of the cancer oncogene KRAS(G12V) and study its downstream effects through phospho-ERK levels and cellular proliferation. Overall, these novel LITer optogenetic platforms should enable precise spatiotemporal perturbations for studying multicellular phenotypes in developmental biology, oncology and other biomedical fields of research.