Demultiplexing of single-cell RNA-sequencing data using interindividual variation in gene expression.

Motivation: Pooled designs for single-cell RNA sequencing, where many cells from distinct samples are processed jointly, offer increased throughput and reduced batch variation. This study describes expression-aware demultiplexing (EAD), a computational method that employs differential co-expression patterns between individuals to demultiplex pooled samples without any extra experimental steps. Results: We use synthetic sample pools and show that the top interindividual differentially co-expressed genes provide a distinct cluster of cells per individual, significantly enriching the regulation of metabolism. Our application of EAD to samples of six isogenic inbred mice demonstrated that controlling genetic and environmental effects can solve interindividual variations related to metabolic pathways. We utilized 30 samples from both sepsis and healthy individuals in six batches to assess the performance of classification approaches. The results indicate that combining genetic and EAD results can enhance the accuracy of assignments (Min. 0.94, Mean 0.98, Max. 1). The results were enhanced by an average of 1.4% when EAD and barcoding techniques were combined (Min. 1.25%, Median 1.33%, Max. 1.74%). Furthermore, we demonstrate that interindividual differential co-expression analysis within the same cell type can be used to identify cells from the same donor in different activation states. By analysing single-nuclei transcriptome profiles from the brain, we demonstrate that our method can be applied to nonimmune cells. Availability and implementation: EAD workflow is available at https://isarnassiri.github.io/scDIV/ as an R package called scDIV (acronym for single-cell RNA-sequencing data demultiplexing using interindividual variations).

Multiscale topology classifies cells in subcellular spatial transcriptomics.

Spatial transcriptomics measures in situ gene expression at millions of locations within a tissue1, hitherto with some trade-off between transcriptome depth, spatial resolution and sample size2. Although integration of image-based segmentation has enabled impactful work in this context, it is limited by imaging quality and tissue heterogeneity. By contrast, recent array-based technologies offer the ability to measure the entire transcriptome at subcellular resolution across large samples3-6. Presently, there exist no approaches for cell type identification that directly leverage this information to annotate individual cells. Here we propose a multiscale approach to automatically classify cell types at this subcellular level, using both transcriptomic information and spatial context. We showcase this on both targeted and whole-transcriptome spatial platforms, improving cell classification and morphology for human kidney tissue and pinpointing individual sparsely distributed renal mouse immune cells without reliance on image data. By integrating these predictions into a topological pipeline based on multiparameter persistent homology7-9, we identify cell spatial relationships characteristic of a mouse model of lupus nephritis, which we validate experimentally by immunofluorescence. The proposed framework readily generalizes to new platforms, providing a comprehensive pipeline bridging different levels of biological organization from genes through to tissues.

Prolidase Deficiency Causes Spontaneous T Cell Activation and Lupus-like Autoimmunity.

Prolidase deficiency (PD) is a multisystem disorder caused by mutations in the PEPD gene, which encodes a ubiquitously expressed metallopeptidase essential for the hydrolysis of dipeptides containing C-terminal proline or hydroxyproline. PD typically presents in childhood with developmental delay, skin ulcers, recurrent infections, and, in some patients, autoimmune features that can mimic systemic lupus erythematosus. The basis for the autoimmune association is uncertain, but might be due to self-antigen exposure with tissue damage, or indirectly driven by chronic infection and microbial burden. In this study, we address the question of causation and show that Pepd-null mice have increased antinuclear autoantibodies and raised serum IgA, accompanied by kidney immune complex deposition, consistent with a systemic lupus erythematosus-like disease. These features are associated with an accumulation of CD4 and CD8 effector T cells in the spleen and liver. Pepd deficiency leads to spontaneous T cell activation and proliferation into the effector subset, which is cell intrinsic and independent of Ag receptor specificity or antigenic stimulation. However, an increase in KLRG1+ effector CD8 cells is not observed in mixed chimeras, in which the autoimmune phenotype is also absent. Our findings link autoimmune susceptibility in PD to spontaneous T cell dysfunction, likely to be acting in combination with immune activators that lie outside the hemopoietic system but result from the abnormal metabolism or loss of nonenzymatic prolidase function. This knowledge provides insight into the role of prolidase in the maintenance of self-tolerance and highlights the importance of treatment to control T cell activation.

NDRG1 is induced by antigen-receptor signaling but dispensable for B and T cell self-tolerance.

Peripheral tolerance prevents the initiation of damaging immune responses by autoreactive lymphocytes. While tolerogenic mechanisms are tightly regulated by antigen-dependent and independent signals, downstream pathways are incompletely understood. N-myc downstream-regulated gene 1 (NDRG1), an anti-cancer therapeutic target, has previously been implicated as a CD4+ T cell clonal anergy factor. By RNA-sequencing, we identified Ndrg1 as the third most upregulated gene in anergic, compared to naïve follicular, B cells. Ndrg1 is upregulated by B cell receptor activation (signal one) and suppressed by co-stimulation (signal two), suggesting that NDRG1 may be important in B cell tolerance. However, though Ndrg1-/- mice have a neurological defect mimicking NDRG1-associated Charcot-Marie-Tooth (CMT4d) disease, primary and secondary immune responses were normal. We find that B cell tolerance is maintained, and NDRG1 does not play a role in downstream responses during re-stimulation of in vivo antigen-experienced CD4+ T cells, demonstrating that NDGR1 is functionally redundant for lymphocyte anergy.