Machine Learning to Quantify In Situ Humoral Selection in Human Lupus Tubulointerstitial Inflammation

In human lupus nephritis, tubulointerstitial inflammation (TII) is associated with in situ expansion of B cells expressing anti-vimentin antibodies (AVAs). The mechanism by which AVAs are selected is unclear. Herein, we demonstrate that AVA somatic hypermutation (SHM) and selection increase affinity for vimentin. Indeed, germline reversion of several antibodies demonstrated that higher affinity AVAs can be selected from both low affinity B cell germline clones and even those that are strongly reactive with other autoantigens. While we demonstrated affinity maturation, enzyme-linked immunosorbent assays (ELISAs) suggested that affinity maturation might be a consequence of increasing polyreactivity or even non-specific binding. Therefore, it was unclear if there was also selection for increased specificity. Subsequent multi-color confocal microscopy studies indicated that while TII AVAs often appeared polyreactive by ELISA, they bound selectively to vimentin fibrils in whole cells or inflamed renal tissue. Using a novel machine learning pipeline (CytoSkaler) to quantify the cellular distribution of antibody staining, we demonstrated that TII AVAs were selected for both enhanced binding and specificity in situ. Furthermore, reversion of single predicted amino acids in antibody variable regions indicated that we could use CytoSkaler to capture both negative and positive selection events. More broadly, our data suggest a new approach to assess and define antibody polyreactivity based on quantifying the distribution of binding to native and contextually relevant antigens.

Regulated Capture of Vκ Gene Topologically Associating Domains by Transcription Factories

Expression of vast repertoires of antigen receptors by lymphocytes, with each cell expressing a single receptor, requires stochastic activation of individual variable (V) genes for transcription and recombination. How this occurs remains unknown. Using single-cell RNA sequencing (scRNA-seq) and allelic variation, we show that individual pre-B cells monoallelically transcribe divergent arrays of V_κ genes, thereby opening stochastic repertoires for subsequent V_κ-J_κ recombination. Transcription occurs upon translocation of V_κ genes to RNA polymerase II arrayed on the nuclear matrix in transcription factories. Transcription is anchored by CTCF-bound sites or E2A-loaded V_κ promotors and continues over large genomic distances delimited only by topological associating domains (TADs). Prior to their monoallelic activation, V_κ loci are transcriptionally repressed by cyclin D3, which prevents capture of V_κ gene containing TADs by transcription factories. Cyclin D3 also represses protocadherin, olfactory, and other monoallelically expressed genes, suggesting a widely deployed mechanism for coupling monoallelic gene activation with cell cycle exit.

The mechanisms controlling V_κ transcription and their relationships to Ig_κ recombination are obscure. Karki et al. demonstrate that, upon translocation to transcription factories, V_κ-gene-containing chromatin loops are transcribed over long distances, which opens large, monoallelic, and diverse V_κ repertoires for subsequent V_κ-J_κ recombination.

Cell distance mapping identifies functional T follicular helper cells in inflamed human renal tissue

T follicular helper (TFH) cells are critical for B cell activation in germinal centers and are often observed in human inflamed tissue. However, it is difficult to know if they contribute in situ to inflammation. Expressed markers define TFH subsets associated with distinct functions in vitro. However, such markers may not reflect in situ function. The delivery of T cell help to B cells requires direct cognate recognition. We hypothesized that by visualizing and quantifying such interactions, we could directly assess TFH cell competency in situ. Therefore, we developed computational tools to quantify spatial relationships between different cell subtypes in tissue [cell distance mapping (CDM)]. Analysis of inflamed human tissues indicated that measurement of internuclear distances between TFH and B cells could be used to discriminate between apparent cognate and noncognate interactions. Furthermore, only cognate-competent TFH cell populations expressed high levels of Bcl-6 and interleukin-21. These data suggest that CDM can be used to identify adaptive immune cell networks driving in situ inflammation. Such knowledge should help identify diseases, and disease subsets, that may benefit from therapeutic targeting of specific T cell-antigen-presenting cell interactions.

In vitro processing and secretion of mutant insulin proteins that cause permanent neonatal diabetes

Permanent neonatal diabetes mellitus is a rare form of insulin-requiring diabetes presenting within the first few weeks or months of life. Mutations in the insulin gene are the second most common cause of this form of diabetes. These mutations are located in critical regions of preproinsulin and are likely to prevent normal processing or folding of the preproinsulin/proinsulin molecule. To characterize these mutations, we transiently expressed proinsulin-GFP fusion proteins in MIN6 mouse insulinoma cells. Our study revealed three groups of mutant proteins: 1) mutations that result in retention of proinsulin in the endoplasmic reticulum (ER) and attenuation of secretion of cotransfected wild-type insulin: C43G, F48C, and C96Y; 2) mutations with partial ER retention, partial recruitment to granules, and attenuation of secretion of wild-type insulin: G32R, G32S, G47V, G90C, and Y108C; and 3) similar to (2) but with no significant attenuation of wild-type insulin secretion: A24D and R89C. The mutant insulin proteins do not prevent targeting of wild-type insulin to secretory granules, but most appear to lead to decreased secretion of wild-type insulin. Each of the mutants triggers the expression of the proapoptotic gene Chop, indicating the presence of ER stress.