Vladimir M. Liarski

Cell Distance Mapping Identifies Functional T Follicular Helper Cells in Inflamed Human Renal Tissue

Visualizing and quantifying the spatial relationships between T and B cells identifies adaptive immune cell networks in human inflammation. Putting Human Inflammation on the Map B cells cannot fight infection by antigen stimulation alone—they need help from T cells. In mice, two-photon electron microscopy has demonstrated that T follicular helper (TFH) cells are critical for providing B cell help in germinal centers. However, it has remained unclear whether—and if so, how—TFH cells provide B cell help in humans. Now, Liarski et al. report that cell distance mapping (CDM) can be used to demonstrate cognate TFH-mediated B cell help in the context of human inflammation. CDM is a computational tool that quantifies spatial relationships between different cell types in tissue. The authors used CDM to measure the internuclear distances between TFH and B cells in inflamed human tissues. They were able to discriminate between noncognate and cognate interactions, which are required for providing help. They also characterized cognate-competent TFH cells and found that they expressed Bcl-6 and IL-21. This technique should be generalizable to diverse antigen presentation and immune cell interactions and, if so, should enhance our knowledge of the immune system in situ. 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.

Self-reactive IgE exacerbates interferon responses associated with autoimmunity

Canonically, immunoglobulin E (IgE) mediates allergic immune responses by triggering mast cells and basophils to release histamine and type 2 helper cytokines. Here we found that in human systemic lupus erythematosus (SLE), IgE antibodies specific for double-stranded DNA (dsDNA) activated plasmacytoid dendritic cells (pDCs), a type of cell of the immune system linked to viral defense, which led to the secretion of substantial amounts of interferon-α (IFN-α). The concentration of dsDNA-specific IgE found in patient serum correlated with disease severity and greatly potentiated pDC function by triggering phagocytosis via the high-affinity FcɛRI receptor for IgE, followed by Toll-like receptor 9 (TLR9)-mediated sensing of DNA in phagosomes. Our findings expand the known pathogenic mechanisms of IgE-mediated inflammation beyond those found in allergy and demonstrate that IgE can trigger interferon responses capable of exacerbating self-destructive autoimmune responses.

ERK-dependent T cell receptor threshold calibration in rheumatoid arthritis.

Immune responses to citrullinated neoantigens and clinical efficacy of costimulation blockade indicate a general defect in maintaining T cell tolerance in rheumatoid arthritis (RA). To examine whether TCR threshold calibration contributes to disease pathogenesis, signaling in RA T cells was quantified. RA patients had a selective increase in ERK phosphorylation compared with demographically matched controls due to a mechanism distal of Ras activation. Increased ERK responses included naive and memory CD4 and CD8 T cells and did not correlate with disease activity. The augmented ERK activity delayed SHP-1 recruitment to the TCR synapse and sustained TCR-induced Zap70 and NF-κB signaling, facilitating responses to suboptimal stimulation. Increased responsiveness of the ERK pathway was also a characteristic finding in the SKG mouse model of RA where it preceded clinical symptoms. Treatment with subtherapeutic doses of a MEK-1/2 inhibitor delayed arthritis onset and reduced severity, suggesting that increased ERK phosphorylation predisposes for autoimmunity and can be targeted to prevent disease.

Germinal Center B-cells

Within the B-cell follicle of secondary lymphoid organs, germinal center (GC) reactions produce high affinity antibody-secreting plasma cells (PCs) and memory B-cells necessary for the hosts defense against invading pathogens. This process of GC formation is reliant on the activation of antigen-specific B-cells by T-cells capable of recognizing epitopes of the same antigenic complex. The unique architecture of secondary lymphoid organs facilitates these initial GC events through the placement of large clonally-diverse B-cell follicles near equally diverse T-cell zones. Antigen-activated B-cells that receive proper differentiation signals at the T-cell border of the B-cell follicle initiate an early GC B-cell transcriptional profile and migrate to follicular dendritic cell (FDC) networks within the B-cell follicle to seed the GC reaction. Peripheral to FDCs, GC B-cells rapidly divide in dark zones of the GC, and undergo somatic hypermutation of their immunoglobulin (Ig) variable domain. Newly formed GC B-cell clones then migrate into the GC light zone where they compete for antigen and secondary signals presented by FDCs and a specialized subset of CD4+ T-cells known as T-follicular helper (TFH) cells. Survival, proliferative and differentiation signals delivered by mature FDCs and TFH cells initiate transcriptional programs that determine if GC B-cells become memory B-cells or terminally differentiated PCs. To prevent oncogenic transformation and/or the escape of autoreactive clones, there are several regulatory mechanisms that restrict GC B-cell proliferation and survival. Here we will detail the recent advances in GC B-cell biology that relate to their generation and fate-determination as well as their pathogenic potential.

Bcl-2 as a Therapeutic Target in Human Tubulointerstitial Inflammation.

In lupus nephritis, tubulointerstitial inflammation (TII) is associated with in situ adaptive immune cell networks that amplify local tissue damage. Since conventional therapy appears ineffective for severe TII, and these patients often progress to renal failure, understanding in situ mechanisms might reveal new therapeutic targets. This study was undertaken to assess whether dysregulated apoptotic regulators maintain local adaptive immunity and drive inflammation in TII.

Overview of pathophysiology and treatment of human lupus nephritis.

Purpose of reviewDespite recent developments and treatment successes, the outcome, and prognosis of patients with lupus nephritis (LuN) have not greatly changed since the 1980s. This review covers the application of new concepts to the understanding of renal inflammation and the study of new pharmacologic agents to improve patient outcomes. Recent findingsStudies have shown that the presence of anti-vimentin antibodies and T follicular helper cells in patient biopsies is associated with more severe interstitial inflammation, which has been tied to faster disease progression and onset of end-stage renal disease. Additionally, data regarding the role of serum IgE antidouble-stranded DNA antibodies in LuN by means of mediating IFN1 production by plasmacytoid dendritic cells are highlighted. Finally, a thorough review of completed and currently open clinical trials of therapeutic agents is provided. SummaryCurrent management of LuN is guided almost exclusively by glomerular involvement. Based on the data provided in this review, we argue that renal tubulointerstitial inflammation is no less important and represents an overlooked feature in the current clinical approach to patients. Tubulointerstitial inflammation is driven by both adaptive and innate immune mechanisms that are still poorly understood. Studying these pathogenic processes promises to reveal new therapeutic opportunities for those LuN patients with the worst prognosis. Video abstractAlternate video abstract introduction (see Video, Supplemental Digital Content 1, with introduction by two of the authors – VL and KT). Abstract Video: http://links.lww.com/COR/A35

Computerized image analysis of cell-cell interactions in human renal tissue by using multi-channel immunoflourescent confocal microscopy

Analysis of interactions between B and T cells in tubulointerstitial inflammation is important for understanding human lupus nephritis. We developed a computer technique to perform this analysis, and compared it with manual analysis. Multi-channel immunoflourescent-microscopy images were acquired from 207 regions of interest in 40 renal tissue sections of 19 patients diagnosed with lupus nephritis. Fresh-frozen renal tissue sections were stained with combinations of immunoflourescent antibodies to membrane proteins and counter-stained with a cell nuclear marker. Manual delineation of the antibodies was considered as the reference standard. We first segmented cell nuclei and cell membrane markers, and then determined corresponding cell types based on the distances between cell nuclei and specific cell-membrane marker combinations. Subsequently, the distribution of the shortest distance from T cell nuclei to B cell nuclei was obtained and used as a surrogate indicator of cell-cell interactions. The computer and manual analyses results were concordant. The average absolute difference was 1.1±1.2% between the computer and manual analysis results in the number of cell-cell distances of 3 μm or less as a percentage of the total number of cell-cell distances. Our computerized analysis of cell-cell distances could be used as a surrogate for quantifying cell-cell interactions as either an automated and quantitative analysis or for independent confirmation of manual analysis.

Simultaneous segmentation and classification of multichannel immuno-fluorescently labeled confocal microscopy images using deep convolutional neural networks.

The feasibility of localizing, segmenting, and classifying individual cells in multi-channel confocal microscopy images is highly dependent on image quality. In certain applications, with good image quality, the segmentation can be trivial and accomplished via thresholding, watershed, or a collection of other well-established and studied heuristics; however, at the limit of poor image quality and complex image features, these techniques fail. It is at this limit that deep convolutional neural network (DCNN) approaches excel. Our research studies the interaction of individual immune cells and their shape changes relative to inflammatory immune reactions1 using multi-channel immunofluorescence imaging of renal biopsies from patients with inflammatory kidney disease. We present here a deep learning methodology for application to nuclear and cell membrane immunofluorescent stains to automatically segment and classify multiple T-cell and dendritic cell types. With both T-cells and dendritic cells segmented, we are able to study how T-cells with different surface antigens change shape with proximity to dendritic cells. Shape changes are seen when T-cells move close to dendritic cells and interact. We use a sliding window, max-filtering DCNN to segment and classify 3 cell types from 6 image stains channels within a single DCNN. This DCNN maintains images at original resolution throughout the network using dilated convolutions and max-filtering in place of max pooling layers. In addition, we use 3D convolution kernels with two spatial dimensions and one channel dimension. This allows us to output a multi-class binary classification based on multichannel data at the original image resolution. We trained and validated the network across 24 patients with 8,572 segmented cells. Our results demonstrate a mean Dice-Sorensen score of 0.78 +/- 0.18, a mean classification sensitivity of 0.76, and a mean classification specificity of 0.75 across all 3 segmented cell types.

Aortic Valve Replacement for Moderate Aortic Stenosis with Severe Calcification and Left Ventricualr Dysfunction—A Case Report and Review of the Literature

A 55-year-old man with a history of erosive, seropositive rheumatoid arthritis (RA), and interstitial lung disease presented with shortness of breath. Echocardiography showed new-onset severe left ventricular (LV) dysfunction with an ejection fraction (EF) of 15% and moderately increased mean aortic valve gradient of 20 mmHg in a trileaflet aortic valve with severe sclero-calcific degeneration. Coronary angiography revealed no significant obstructive coronary disease. Invasive hemodynamic studies and dobutamine stress echocardiography were consistent with moderate aortic stenosis. Guideline directed medical therapy for heart failure with reduced EF was initiated; however, diuretics and neurohormonal blockade (beta-blocker and angiotensin receptor blocker) provided minimal improvement, and the patient remained functionally limited. Of interest, echocardiography performed 1 year prior to his presentation showed normal LV EF and mild aortic leaflet calcification with moderate stenosis, suggesting a rapid progressing of calcific aortic valve disease. Subsequently, the patient underwent surgical aortic valve replacement and demonstrated excellent postsurgical recovery of LV EF (55%). Calcific aortic valve disease is commonly associated with aging, bicuspid aortic valve, and chronic kidney disease. Pathophysiological mechanism for valvular calcification is incompletely understood but include osteogenic transformation of valvular interstitial cells mediated by local and systemic inflammatory processes. Several rheumatologic diseases including RA are associated with premature atherosclerosis and arterial calcification, and we speculated a similar role of RA accelerating calcific aortic valve disease. We present a case of accelerated aortic valve calcification with (only) moderate stenosis, complicated by a rapid decline in LV systolic performance. Guidelines for AVR in moderate stenosis without concomitant cardiac surgery are not well established, although it should be considered in selected patients.

II-07 Generation of cell distance mapping plus (CDM+): mapping cognate T cell: dendritic cell interactions and their relationship to cell shape

Background We developed Cell Distance Mapping (CDM) to study tubulointerstitial inflammation in human lupus nephritis biopsies. Using CDM, we were able to translate proximal distance measurements of T:B cell pairs to their functional state in human tissue. One criticism of our work was that it could be considered descriptive. To address this, we utilise an animal model, wherein the antigen specificity of cells can be controlled. Using this, we wanted to expand CDM to the study of innate and adaptive immune responses, chief among which are T cell:Dendritic cell (DC) interactions. We also wanted to incorporate measures of cell shape parameters to improve our ability to distinguish cognate from non-cognate interactions. Materials and methods An adoptive triple transfer mouse model was utilised, with each population labelled with fluorescent cell trackers: pigeon cytochrome C-pulsed and LPS-activated dendritic cells (DCs), antigen-specific T cells, and wild type T cells. After transfer, cervical lymph nodes were subjected to two-photon excitation microscopy (TPEM) analysis, frozen at −80 °C, and further subjected to CDM analysis. A total of 79 images from the lymph nodes of 5 animals was used. The results were analysed with respect to global cell shape, as visualised by freely diffusible cell trackers for T cells. This was superimposed on CDM data for interactions between respective T cell subsets and dendritic cells. Results Analysis of 512×512 pixel images, representing 640 ×magnification views, revealed significant differences at <0.27 μm (8.70 vs 3.22%, p = 0.028), <1 μm (11.7 vs 3.70%, p = 0.01), and <2 μm (13.1 vs 5.26%, p = 0.031) distance cutoffs comparing antigen specific T cell:DC interactions versus WT T cell:DC interactions. Our results compared favourably with arrest coefficient calculation performed on TPEM data (mean of 0.06 vs 0.26, respectively; p < 0.01). Global cell shape analysis did not reveal any additional statistically significant differences. Increasing acquisition resolution to 1024×1024 pixels revealed the following measurements that distinguished between the two T cell subsets: area (p < 0.0001), circularity (p < 0.0001), perimeter to area ratio (p < 0.0001), aspect ratio to area ratio (p < 0.0001). Each variables\ was controlled for area to ensure that observed findings were not due to global differences between the two respective T cell subsets or influenced by variances in wavelengths, utilised to visualise individual cell trackers. Conclusions Our data shows that CDM is able to reliably identify cognate interactions on par with TPEM, using distance as the main measurement. The addition of global cell shape parameter measurements helped to further distinguish cognate from non-cognate interactions at the same distance measurements. Acknowledgements Vladimir Liarski is supported by NIH NIAMS K08 AR068421. Marcus Clark is supported by NIH grants U19 AI082724 and AR55646.