Single-cell Transcriptomics and Solid Organ Transplantation

Application of spatial-omics to the classification of kidney biopsy samples in transplantation

Improvement of long-term outcomes through targeted treatment is a primary concern in kidney transplant medicine. Currently, the validation of a rejection diagnosis and subsequent treatment depends on the histological assessment of allograft biopsy samples, according to the Banff classification system. However, the lack of (early) disease-specific tissue markers hinders accurate diagnosis and thus timely intervention. This challenge mainly results from an incomplete understanding of the pathophysiological processes underlying late allograft failure. Integration of large-scale multimodal approaches for investigating allograft biopsy samples might offer new insights into this pathophysiology, which are necessary for the identification of novel therapeutic targets and the development of tailored immunotherapeutic interventions. Several omics technologies - including transcriptomic, proteomic, lipidomic and metabolomic tools (and multimodal data analysis strategies) - can be applied to allograft biopsy investigation. However, despite their successful application in research settings and their potential clinical value, several barriers limit the broad implementation of many of these tools into clinical practice. Among spatial-omics technologies, mass spectrometry imaging, which is under-represented in the transplant field, has the potential to enable multi-omics investigations that might expand the insights gained with current clinical analysis technologies.

Transcriptional Profiling Underscores the Role of Preprocurement Allograft Metabolism and Innate Immune Status on Outcomes in Human Liver Transplantation

Objective

The adverse effects of ischemia-reperfusion injury (IRI) remain a principal barrier to a successful outcome after lifesaving orthotopic liver transplantation (OLT). Gene expression during different phases of IRI is dynamic and modified by individual exposures, making it attractive for identifying potential therapeutic targets for improving the number of suitable organs for transplantation and patient outcomes. However, data remain limited on the functional landscape of gene expression during liver graft IRI, spanning procurement to reperfusion and recovery. Therefore, we sought to characterize transcriptomic profiles of IRI during multiple phases in human OLT.

Methods

We conducted clinical data analyses, histologic evaluation, and RNA sequencing of 17 consecutive human primary OLT. We performed liver allograft biopsies at 4 time points: baseline (B, before donor cross-clamp), at the end of cold ischemia (CI), during early reperfusion (ER, after revascularization), and during late reperfusion (LR). Data were generated and then recipients grouped by post-OLT outcomes categories: immediate allograft function (IAF; n = 11) versus early allograft dysfunction (EAD; n = 6) groups.

Results

We observed that CI (vs B) modified a transcriptomic landscape enriched for a metabolic and immune process. Expression levels of hallmark inflammatory response genes were higher transitioning from CI to ER and decreased from ER to LR. IAF group predominantly showed higher bile and fatty acid metabolism activity during LR compared with EAD group, while EAD group maintained more immunomodulatory activities. Throughout all time points, EAD specimens exhibited decreased metabolic activity in both bile and fatty acid pathways.

Conclusions

We report transcriptomic profiles of human liver allograft IRI from prepreservation in the donor to posttransplantation in the recipient. Immunomodulatory and metabolic landscapes across ER and LR phases were different between IAF and EAD allografts. Our study also highlights marker genes for these biological processes that we plan to explore as novel therapeutic targets or surrogate markers for severe allograft injury in clinical OLT.

Creating superior lungs for transplantation with next-generation gene therapy during ex vivo lung perfusion

Engineering donor organs to better tolerate the harmful non-immunological and immunological responses inherently related to solid organ transplantation would improve transplant outcomes. Our enhanced knowledge of ischemia-reperfusion injury, alloimmune responses and pathological fibroproliferation after organ transplantation, and the advanced toolkit available for gene therapies, have brought this goal closer to clinical reality. Ex vivo organ perfusion has evolved rapidly especially in the field of lung transplantation, where clinicians routinely use ex vivo lung perfusion (EVLP) to confirm the quality of marginal donor lungs before transplantation, enabling safe transplantation of organs originally considered unusable. EVLP would also be an attractive platform to deliver gene therapies, as treatments could be administered to an isolated organ before transplantation, thereby providing a window for sophisticated organ engineering while minimizing off-target effects to the recipient. Here, we review the status of lung transplant first-generation gene therapies that focus on inducing transgene expression in the target cells. We also highlight recent advances in next-generation gene therapies, that enable gene editing and epigenetic engineering, that could be used to permanently change the donor organ genome and to induce widespread transcriptional gene expression modulation in the donor lung. In a future vision, dedicated organ repair and engineering centers will use gene editing and epigenetic engineering, to not only increase the donor organ pool, but to create superior organs that will function better and longer in the recipient.

Relationship between blood and tissue-based rejection-related transcripts in heart transplantation

BACKGROUND

The purpose of the study is to investigate the relationship between blood and tissue-derived rejection-related transcripts from blood gene expression profiling (GEP) and molecular microscope in the setting of allograft rejection in heart transplant.

METHODS

All heart transplant patients from August 2021 to May 2022 with both circulating blood GEP (AlloMap) and endomyocardial biopsy with molecular microscope diagnostic system (MMDx) within 4 weeks were included (N = 173 samples). We obtained individual blood GEP-based messenger RNA transcript expression levels of the 11 target genes from CareDx. Student's t-test was performed to compare blood GEP transcript expression levels between no rejection and rejection as assessed by MMDx. A Scatter plot with Spearman correlation analysis was performed to compare the relationship between transcript expression levels from AlloMap and MMDx, with and without allograft rejection.

RESULTS

There were 52 samples (30.1%) with antibody-mediated rejection (ABMR) and 15 samples (8.7%) with T-cell-mediated rejection (TCMR), as assessed by MMDx. Expression of one of the blood ITGA4 (Integrin alpha 4) expression level was elevated in ABMR, compared to no ABMR (4,607.5 vs 4,217.5; p = 0.019). Most tissue rejection-associated transcript expression levels were elevated in ABMR, and tissue ROBO4 expression correlated with the blood ITGA4 expression with moderate or greater effect size in all samples (Spearman's R = 0.31; p < 0.001). There was also a positive correlation between blood ITGA4 and tissue ROBO4 expression in samples without ABMR (Spearman's R = 0.33; p < 0.001), but no correlation between blood ITGA4 and tissue ROBO4 expression in samples with ABMR (Spearman's R = 0.009; p = 0.513).

CONCLUSIONS

Circulating blood ITGA4 expression is elevated in antibody-mediated rejection (AMR) and correlates with myocardial expression of ROBO4. The knowledge of individual transcript expression levels in blood and in tissue may provide insights into various disease processes in heart transplant patients. Taken together, the results of our study reveal an overlap between 2 objective post-heart transplant rejection surveillance methods, identify potential novel markers for ABMR, and reveal the need for a deeper understanding of molecular mechanisms underlying allograft rejection.

Dual-Targeting Nanovesicles Carrying CSF1/CD47 Identified from Single-Cell Transcriptomics of Innate Immune Cells in Heart Transplant for Alleviating Acute Rejection

Although immunosuppressive drugs for targeting T cells are the standard of care in acute transplantation rejection, the role of innate immune cells should not be ignored. Here, single-cell RNA sequencing (scRNA-seq) and flow cytometry are performed to reveal the dynamic changes of innate immune cells within the acute rejection time and find a significantly-increased presence of Ly6G- Ly6C+ inflammatory macrophages and decreased presence of neutrophils among all types of immune cells. Next, to further explore potential targets regulating Ly6G- Ly6C+ inflammatory macrophages, scRNA-seq is used to analyze the reciprocal signaling of both neutrophils and macrophages, along with the surface genes of macrophages. It is found that activating colony-stimulating factor 1/ colony-stimulating factor 1 receptor (CSF1/CSF1R) andcluster of differentiation 47/signal regulatory protein α (CD47/SIRPα) signaling may serve as a strategy to relieve Ly6G- Ly6C+ inflammatory macrophage-mediated early graft rejection. To investigate this hypothesis, CSF1/CD47 dual-targeting nanovesicles (NVs) derived from IFN-γ-stimulated induced pluripotent stem cell-derived mesenchymal stem cells ( iPSC-MSCs )are designed and constructed. It is confirmed that CSF1/CD47 NVs synergistically induce the differentiation of Ly6G- Ly6C- M2 inhibitory macrophages by the CSF1/CSF1R pathway, and inhibit the phagocytosis of inflammatory macrophages and inflammatory response by the CD47/SIRPα pathway, ultimately relieving immune rejection. This study highlights the power of dual-targeting CSF1/CD47 NVs as an immunosuppressant against early innate immune responses with the potential for broad clinical applications.

Sequencing of Physically Interacting Cells in Human Kidney Allograft Rejection to Infer Contact-dependent Immune Cell Transcription

BACKGROUND

Rejection requires cell-cell contact involving immune cells. Inferring the transcriptional programs of cell-cell interactions from single-cell RNA-sequencing (scRNA-seq) data is challenging as spatial information is lost.

METHODS

We combined a CD45 pos enrichment strategy with Cellular Indexing of Transcriptomes and Epitopes by sequencing based quantification of leukocyte surface proteins to analyze cell-cell interactions in 11 human kidney transplant biopsies encompassing a spectrum of rejection diagnoses. scRNA-seq was performed using the 10X Genomics platform. We applied the sequencing physically interacting cells computational method to deconvolute the transcriptional profiles of heterotypic physically interacting cells.

RESULTS

The 11 human allograft biopsies generated 31 203 high-quality single-cell libraries. Clustering was further refined by combining Cellular Indexing of Transcriptomes and Epitopes by sequencing data from 6 different leukocyte-specific surface proteins. Three of 6 doublet clusters were identified as physically interacting cell complexes; macrophages or dendritic cells bound to B cells or plasma cells; natural killer (NK) or T cells bound to macrophages or dendritic cells and NK or T cells bound to endothelial cells. Myeloid-lymphocyte physically interacting cell complexes expressed activated and proinflammatory genes. Lymphocytes physically interacting with endothelial cells were enriched for NK and CD4 T cells. NK cell-endothelial cell contact caused increased expression of endothelial proinflammatory genes CXCL9 and CXCL10 and NK cell proinflammatory genes CCL3 , CCL4 , and GNLY .

CONCLUSIONS

The transcriptional profiles of physically interacting cells from human kidney transplant biopsies can be inferred from scRNA-seq data using the sequencing physically interacting cells method. This approach complements previous methods that estimate cell-cell physical contact from scRNA-seq data.

The Utility of Spatial Transcriptomics for Solid Organ Transplantation

Spatial transcriptomics (ST) measures and maps transcripts within intact tissue sections, allowing the visualization of gene activity within the spatial organization of complex biological systems. This review outlines advances in genomic sequencing technologies focusing on in situ sequencing-based ST, including applications in transplant and relevant nontransplant settings. We describe the experimental and analytical pipelines that underpin the current generation of spatial technologies. This context is important for understanding the potential role ST may play in expanding our knowledge, including in organ transplantation, and the important caveats/limitations when interpreting the vast data output generated by such methodological platforms.

Robust segregation of donor and recipient cells from single-cell RNA-sequencing of transplant samples

Background

Single-cell RNA-sequencing (scRNA-seq) technology has revealed novel cell populations in organs, uncovered regulatory relationships between genes, and allowed for tracking of cell lineage trajectory during development. It demonstrates promise as a method to better understand transplant biology; however, fundamental bioinformatic tools for its use in the context of transplantation have not been developed. One major need has been a robust method to identify cells as being either donor or recipient genotype origin, and ideally without the need to separately sequence the donor and recipient.

Methods

We implemented a novel two-stage genotype discovery method (scTx) optimized for transplant samples by being robust to disparities in cell number and cell type. Using both in silico and real-world scRNA-seq transplant data, we benchmarked our method against existing demultiplexing methods to profile their limitations in terms of sequencing depth, donor and recipient cell imbalance, and single nucleotide variant input selection.

Results

Using in silico data, scTx could more accurately separate donor from recipient cells and at much lower genotype ratios than existing methods. This was further validated using solid-organ scRNA-seq data where scTx could more reliably identify when a second genotype was present and at lower numbers of cells from a second genotype.

Conclusion

scTx introduces the capability to accurately segregate donor and recipient gene expression at the single-cell level from scRNA-seq data without the need to separately genotype the donor and recipient. This will facilitate the use of scRNA-seq in the context of transplantation.

Single nuclei transcriptomics delineates complex immune and kidney cell interactions contributing to kidney allograft fibrosis

Chronic allograft dysfunction (CAD), characterized histologically by interstitial fibrosis and tubular atrophy, is the major cause of kidney allograft loss. Here, using single nuclei RNA sequencing and transcriptome analysis, we identified the origin, functional heterogeneity, and regulation of fibrosis-forming cells in kidney allografts with CAD. A robust technique was used to isolate individual nuclei from kidney allograft biopsies and successfully profiled 23,980 nuclei from five kidney transplant recipients with CAD and 17,913 nuclei from three patients with normal allograft function. Our analysis revealed two distinct states of fibrosis in CAD; low and high extracellular matrix (ECM) with distinct kidney cell subclusters, immune cell types, and transcriptional profiles. Imaging mass cytometry analysis confirmed increased ECM deposition at the protein level. Proximal tubular cells transitioned to an injured mixed tubular (MT1) phenotype comprised of activated fibroblasts and myofibroblast markers, generated provisional ECM which recruited inflammatory cells, and served as the main driver of fibrosis. MT1 cells in the high ECM state achieved replicative repair evidenced by dedifferentiation and nephrogenic transcriptional signatures. MT1 in the low ECM state showed decreased apoptosis, decreased cycling tubular cells, and severe metabolic dysfunction, limiting the potential for repair. Activated B, T and plasma cells were increased in the high ECM state, while macrophage subtypes were increased in the low ECM state. Intercellular communication between kidney parenchymal cells and donor-derived macrophages, detected several years post-transplantation, played a key role in injury propagation. Thus, our study identified novel molecular targets for interventions aimed to ameliorate or prevent allograft fibrogenesis in kidney transplant recipients.

Allograft tissue under the microscope: only the beginning

PURPOSE OF REVIEW

To review novel modalities for interrogating a kidney allograft biopsy to complement the current Banff schema.

RECENT FINDINGS

Newer approaches of Artificial Intelligence (AI), Machine Learning (ML), digital pathology including Ex Vivo Microscopy, evaluation of the biopsy gene expression using bulk, single cell, and spatial transcriptomics and spatial proteomics are now available for tissue interrogation.

SUMMARY

Banff Schema of classification of allograft histology has standardized reporting of tissue pathology internationally greatly impacting clinical care and research. Inherent sampling error of biopsies, and lack of automated morphometric analysis with ordinal outputs limit its performance in prognostication of allograft health. Over the last decade, there has been an explosion of newer methods of evaluation of allograft tissue under the microscope. Digital pathology along with the application of AI and ML algorithms could revolutionize histopathological analyses. Novel molecular diagnostics such as spatially resolved single cell transcriptomics are identifying newer mechanisms underlying the pathologic diagnosis to delineate pathways of immunological activation, tissue injury, repair, and regeneration in allograft tissues. While these techniques are the future of tissue analysis, costs and complex logistics currently limit their clinical use.

The Value of Single-cell Technologies in Solid Organ Transplantation Studies

Single-cell technologies open up new opportunities to explore the behavior of cells at the individual level. For solid organ transplantation, single-cell technologies can provide in-depth insights into the underlying mechanisms of the immunological processes involved in alloimmune responses after transplantation by investigating the role of individual cells in tolerance and rejection. Here, we review the value of single-cell technologies, including cytometry by time-of-flight and single-cell RNA sequencing, in the context of solid organ transplantation research. Various applications of single-cell technologies are addressed, such as the characterization and identification of immune cell subsets involved in rejection or tolerance. In addition, we explore the opportunities for analyzing specific alloreactive T- or B-cell clones by linking phenotype data to T- or B-cell receptor data, and for distinguishing donor- from recipient-derived immune cells. Moreover, we discuss the use of single-cell technologies in biomarker identification and risk stratification, as well as the remaining challenges. Together, this review highlights that single-cell approaches contribute to a better understanding of underlying immunological mechanisms of rejection and tolerance, thereby potentially accelerating the development of new or improved therapies to avoid allograft rejection.

Single-Cell RNA sequencing reveals immune cell dynamics and local intercellular communication in acute murine cardiac allograft rejection

Rationale: Transplant rejection is a major impediment to long-term allograft survival, in which the actions of immune cells are of fundamental importance. However, the immune cell dynamics and local intercellular communication of acute cardiac allograft rejection are not completely clear.

Methods: Here we performed single-cell RNA sequencing on CD45⁺ immune cells isolated from cardiac grafts and spleens in a model of murine heterotopic heart transplantation. Moreover, we applied unsupervised clustering, functional enrichment analysis, cell trajectory construction and intercellular communication analysis to explore the immune cell dynamics and local intercellular communication of acute cardiac allograft rejection at single-cell level. The effect of CXCR3 antagonist and neutralizing antibody against its ligand on allograft rejection and T cell function was evaluated in murine heart transplantation model.

Results: We presented the immune cell landscape of acute murine cardiac allograft rejection at single-cell resolution, and uncovered the functional characteristics and differentiation trajectory of several alloreactive cell subpopulations, including Mki67^hi CTLs, Ccl5^hi CTLs, activated Tregs and alloreactive B cells. We demonstrated local intercellular communication and revealed the upregulation of CXCR3 and its ligands in cardiac allografts. Finally, CXCR3 blockade significantly suppressed acute cardiac allograft rejection and inhibited the alloreactive T cell function.

Conclusions: These results provide a new insight into the immune cell dynamics and local intercellular communication of acute cardiac allograft rejection, and suggest CXCR3 pathway may serve as a potential therapeutic target for transplant rejection.

T Cells With Activated STAT4 Drive the High-Risk Rejection State to Renal Allograft Failure After Kidney Transplantation

In kidney transplantation, deteriorated progression of rejection is considered to be a leading course of postoperative mortality. However, the conventional histologic diagnosis is limited in reading the rejection status at the molecular level, thereby triggering mismatched pathogenesis with clinical phenotypes. Here, by applying uniform manifold approximation and projection and Leiden algorithms to 2,611 publicly available microarray datasets of renal transplantation, we uncovered six rejection states with corresponding signature genes and revealed a high-risk (HR) state that was essential in promoting allograft loss. By identifying cell populations from single-cell RNA sequencing data that were associated with the six rejection states, we identified a T-cell population to be the pathogenesis-triggering cells associated with the HR rejection state. Additionally, by constructing gene regulatory networks, we identified that activated STAT4, as a core transcription factor that was regulated by PTPN6 in T cells, was closely linked to poor allograft function and prognosis. Taken together, our study provides a novel strategy to help with the precise diagnosis of kidney allograft rejection progression, which is powerful in investigating the underlying molecular pathogenesis, and therefore, for further clinical intervention.

Cancer Risk and Mutational Patterns Following Organ Transplantation

The rapid development of medical technology and widespread application of immunosuppressive drugs have improved the success rate of organ transplantation significantly. However, the use of immunosuppressive agents increases the frequency of malignancy greatly. With the prospect of “precision medicine” for tumors and development of next-generation sequencing technology, more attention has been paid to the application of high-throughput sequencing technology in clinical oncology research, which is mainly applied to the early diagnosis of tumors and analysis of tumor-related genes. All generations of cancers carry somatic mutations, meanwhile, significant differences were observed in mutational signatures across tumors. Systematic sequencing of cancer genomes from patients after organ transplantation can reveal DNA damage and repair processes in exposed cancer cells and their precursors. In this review, we summarize the application of high-throughput sequencing and organoids in the field of organ transplantation, the mutational patterns of cancer genomes, and propose a new research strategy for understanding the mechanism of cancer following organ transplantation.

An optimized protocol for single nuclei isolation from clinical biopsies for RNA-seq

Single nuclei RNA sequencing (snRNA-seq) has evolved as a powerful tool to study complex human diseases. Single cell resolution enables the study of novel cell types, biological processes, cell trajectories, and cell-cell signaling pathways. snRNA-seq largely relies on the dissociation of intact nuclei from human tissues. However, the study of complex tissues using small core biopsies presents many technical challenges. Here, an optimized protocol for single nuclei isolation is presented for frozen and RNAlater preserved human kidney biopsies. The described protocol is fast, low cost, and time effective due to the elimination of cell sorting and ultra-centrifugation. Samples can be processed in 90 min or less. This method is effective for obtaining normal nuclei morphology without signs of structural damage. Using snRNA-seq, 16 distinct kidney cell clusters were recovered from normal and peri-transplant acute kidney injury allograft samples, including immune cell clusters. Quality control measurements demonstrated that these optimizations eliminated cellular debris and allowed for a high yield of high-quality nuclei and RNA for library preparation and sequencing. Cellular disassociation did not induce cellular stress responses, which recapitulated transcriptional patterns associated with standardized methods of nuclei isolation. Future applications of this protocol will allow for thorough investigations of small biobank biopsies, identifying cell-specific injury pathways and driving the discovery of novel diagnostics and therapeutic targets.

Detection of infiltrating fibroblasts by single-cell transcriptomics in human kidney allografts

We tested the hypothesis that single-cell RNA-sequencing (scRNA-seq) analysis of human kidney allograft biopsies will reveal distinct cell types and states and yield insights to decipher the complex heterogeneity of alloimmune injury. We selected 3 biopsies of kidney cortex from 3 individuals for scRNA-seq and processed them fresh using an identical protocol on the 10x Chromium platform; (i) HK: native kidney biopsy from a living donor, (ii) AK1: allograft kidney with transplant glomerulopathy, tubulointerstitial fibrosis, and worsening graft function, and (iii) AK2: allograft kidney after successful treatment of active antibody-mediated rejection. We did not study T-cell-mediated rejections. We generated 7217 high-quality single cell transcriptomes. Taking advantage of the recipient-donor sex mismatches revealed by X and Y chromosome autosomal gene expression, we determined that in AK1 with fibrosis, 42 months after transplantation, more than half of the kidney allograft fibroblasts were recipient-derived and therefore likely migratory and graft infiltrative, whereas in AK2 without fibrosis, 84 months after transplantation, most fibroblasts were donor-organ-derived. Furthermore, AK1 was enriched for tubular progenitor cells overexpressing profibrotic extracellular matrix genes. AK2, eight months after successful treatment of rejection, contained plasmablast cells with high expression of immunoglobulins, endothelial cell elaboration of T cell chemoattractant cytokines, and persistent presence of cytotoxic T cells. In addition to these key findings, our analysis revealed unique cell types and states in the kidney. Altogether, single-cell transcriptomics yielded novel mechanistic insights, which could pave the way for individualizing the care of transplant recipients.

Kidney cell type-specific changes in the chromatin and transcriptome landscapes following epithelial Hdac1 and Hdac2 knockdown

Recent studies have identified at least 20 different kidney cell types based upon chromatin structure and gene expression. Histone deacetylases (HDACs) are epigenetic transcriptional repressors via deacetylation of histone lysines resulting in inaccessible chromatin. We reported that kidney epithelial HDAC1 and HDAC2 activity is critical for maintaining a healthy kidney and preventing fluid-electrolyte abnormalities. However, to what extent does Hdac1/Hdac2 knockdown affect chromatin structure and subsequent transcript expression in the kidney? To answer this question, we used single nucleus assay for transposase-accessible chromatin-sequencing (snATAC-seq) and snRNA-seq to profile kidney nuclei from male and female, control, and littermate kidney epithelial Hdac1/Hdac2 knockdown mice. Hdac1/Hdac2 knockdown resulted in significant changes in the chromatin structure predominantly within the promoter region of gene loci involved in fluid-electrolyte balance such as the aquaporins, with both increased and decreased accessibility captured. Moreover, Hdac1/Hdac2 knockdown resulted different gene loci being accessible with a corresponding increased transcript number in the kidney, but among all mice only 24%-30% of chromatin accessibility agreed with transcript expression (e.g., open chromatin and increased transcript). To conclude, although chromatin structure does affect transcription, ∼70% of the differentially expressed genes cannot be explained by changes in chromatin accessibility and HDAC1/HDAC2 had a minimal effect on these global patterns. Yet, the genes that are targets of HDAC1 and HDAC2 are critically important for maintaining kidney function.

Single-cell transcriptomic identified HIF1A as a target for attenuating acute rejection after heart transplantation

Acute rejection (AR) is an important contributor to graft failure, which remains a leading cause of death after heart transplantation (HTX). The regulation of immune metabolism has become a new hotspot in the development of immunosuppressive drugs. In this study, Increased glucose metabolism of cardiac macrophages was found in patients with AR. To find new therapeutic targets of immune metabolism regulation for AR, CD45⁺ immune cells extracted from murine isografts, allografts, and untransplanted donor hearts were explored by single-cell RNA sequencing. Total 20 immune cell subtypes were identified among 46,040 cells. The function of immune cells in AR were illustrated simultaneously. Cardiac resident macrophages were substantially replaced by monocytes and proinflammatory macrophages during AR. Monocytes/macrophages in AR allograft were more active in antigen presentation and inflammatory recruitment ability, and glycolysis. Based on transcription factor regulation analysis, we found that the increase of glycolysis in monocytes/macrophages was mainly regulated by HIF1A. Inhibition of HIF1A could alleviate inflammatory cells infiltration in AR. To find out the effect of HIF1A on AR, CD45⁺ immune cells extracted from allografts after HIF1A inhibitor treatment were explored by single-cell RNA sequencing. HIF1A inhibitor could reduce the antigen presenting ability and pro-inflammatory ability of macrophages, and reduce the infiltration of Cd4+ and Cd8a+ T cells in AR. The expression of Hif1α in AR monocytes/macrophages was regulated by pyruvate kinase 2. Higher expression of HIF1A in macrophages was also detected in human hearts with AR. These indicated HIF1A may serve as a potential target for attenuating AR.

Advances in single-cell sequencing: insights from organ transplantation

Single-cell RNA sequencing (scRNA-seq) is a comprehensive technical tool to analyze intracellular and intercellular interaction data by whole transcriptional profile analysis. Here, we describe the application in biomedical research, focusing on the immune system during organ transplantation and rejection. Unlike conventional transcriptome analysis, this method provides a full map of multiple cell populations in one specific tissue and presents a dynamic and transient unbiased method to explore the progression of allograft dysfunction, starting from the stress response to final graft failure. This promising sequencing technology remarkably improves individualized organ rejection treatment by identifying decisive cellular subgroups and cell-specific interactions.

Antibody-Mediated Rejection and Lung Transplantation

Antibody-mediated rejection (AMR) is now a widely recognized form of lung allograft rejection, with mounting evidence for AMR as an important risk factor for the development of chronic lung allograft dysfunction and markedly decreased long-term survival. Despite the recent development of the consensus diagnostic criteria, it remains a challenging diagnosis of exclusion. Furthermore, even after diagnosis, treatment directed at pulmonary AMR has been nearly exclusively derived from practices with other solid-organ transplants and other areas of medicine, such that there is a significant lack of data regarding the efficacy for these in pulmonary AMR. Lastly, outcomes after AMR remain quite poor despite aggressive treatment. In this review, we revisit the history of AMR in lung transplantation, describe our current understanding of its pathophysiology, discuss the use and limitations of the consensus diagnostic criteria, review current treatment strategies, and summarize long-term outcomes. We conclude with a synopsis of our most pressing gaps in knowledge, introduce recommendations for future directions, and highlight promising areas of active research.

Synchronous control of magnetic particles and magnetized cells in a tri-axial magnetic field

Precise manipulation of single particles is one of the main goals in the lab-on-a-chip field. Here, we present a microfluidic platform with "T" and "I" shaped magnetic tracks on the substrate to transport magnetic particles and magnetized cells in a tri-axial time-varying magnetic field. The driving magnetic field is composed of a vertical field bias and an in-plane rotating field component, with the advantage of lowering the attraction tendency and cluster formation between the particles compared to the traditional magnetophoretic circuits. We demonstrate three fundamental achievements. First, all the particle movements are synced with the external rotating field to achieve precise control over individual particles. Second, single-particle and single living cell transport in a controlled fashion is achieved for a large number of them in parallel, without the need for a complicated control system to send signals to individual particles. We carefully study the proposed design and introduce proper operating parameters. Finally, in addition to moving the particles along straight tracks, transporting them using a ∼60° bend is demonstrated. The proposed chip has direct applications in the fields of lab-on-a-chip, single-cell biology, and drug screening, where precise control over single particles is needed.

Molecular Analysis of Renal Allograft Biopsies: Where Do We Stand and Where Are We Going?

A renal core biopsy for histological evaluation is the gold standard for diagnosing renal transplant pathology. However, renal biopsy interpretation is subjective and can render insufficient precision, making it difficult to apply a targeted therapeutic regimen for the individual patient. This warrants a need for additional methods assessing disease state in the renal transplant. Significant research activity has been focused on the role of molecular analysis in the diagnosis of renal allograft rejection. The identification of specific molecular expression patterns in allograft biopsies related to different types of allograft injury could provide valuable information about the processes underlying renal transplant dysfunction and can be used for the development of molecular classifier scores, which could improve our diagnostic and prognostic ability and could guide treatment. Molecular profiling has the potential to be more precise and objective than histological evaluation and may identify injury even before it becomes visible on histology, making it possible to start treatment at the earliest time possible. Combining conventional diagnostics (histology, serology, and clinical data) and molecular evaluation will most likely offer the best diagnostic approach. We believe that the use of state-of-the-art molecular analysis will have a significant impact in diagnostics after renal transplantation. In this review, we elaborate on the molecular phenotype of both acute and chronic T cell-mediated rejection and antibody-mediated rejection and discuss the additive value of molecular profiling in the setting of diagnosing renal allograft rejection and how this will improve transplant patient care.

Single cell transcriptomics of mouse kidney transplants reveals a myeloid cell pathway for transplant rejection

Myeloid cells are increasingly recognized as major players in transplant rejection. Here, we used a murine kidney transplantation model and single cell transcriptomics to dissect the contribution of myeloid cell subsets and their potential signaling pathways to kidney transplant rejection. Using a variety of bioinformatic techniques, including machine learning, we demonstrate that kidney allograft–infiltrating myeloid cells followed a trajectory of differentiation from monocytes to proinflammatory macrophages, and they exhibited distinct interactions with kidney allograft parenchymal cells. While this process correlated with a unique pattern of myeloid cell transcripts, a top gene identified was Axl, a member of the receptor tyrosine kinase family Tyro3/Axl/Mertk (TAM). Using kidney transplant recipients with Axl gene deficiency, we further demonstrate that Axl augmented intragraft differentiation of proinflammatory macrophages, likely via its effect on the transcription factor Cebpb. This, in turn, promoted intragraft recruitment, differentiation, and proliferation of donor-specific T cells, and it enhanced early allograft inflammation evidenced by histology. We conclude that myeloid cell Axl expression identified by single cell transcriptomics of kidney allografts in our study plays a major role in promoting intragraft myeloid cell and T cell differentiation, and it presents a potentially novel therapeutic target for controlling kidney allograft rejection and improving kidney allograft survival.

In a murine model of allogeneic kidney transplantation, single-cell transcriptomics identifies that myeloid cell Axl expression promotes allograft rejection by inducing inflammatory macrophage differentiation.

Banff Digital Pathology Working Group: Going digital in transplant pathology

The Banff Digital Pathology Working Group (DPWG) was formed in the time leading up to and during the joint American Society for Histocompatibility and Immunogenetics/Banff Meeting, September 23-27, 2019, held in Pittsburgh, Pennsylvania. At the meeting, the 14th Banff Conference, presentations directly and peripherally related to the topic of "digital pathology" were presented; and discussions before, during, and after the meeting have resulted in a list of issues to address for the DPWG. Included are practice standardization, integrative approaches for study classification, scoring of histologic parameters (eg, interstitial fibrosis and tubular atrophy and inflammation), algorithm classification, and precision diagnosis (eg, molecular pathways and therapeutics). Since the meeting, a survey with international participation of mostly pathologists (81%) was conducted, showing that whole slide imaging is available at the majority of centers (71%) but that artificial intelligence (AI)/machine learning was only used in ≈12% of centers, with a wide variety of programs/algorithms employed. Digitalization is not just an end in itself. It also is a necessary precondition for AI and other approaches. Discussions at the meeting and the survey highlight the unmet need for a Banff DPWG and point the way toward future contributions that can be made.

Maintenance Immunosuppression in Solid Organ Transplantation: Integrating Novel Pharmacodynamic Biomarkers to Inform Calcineurin Inhibitor Dose Selection

Calcineurin inhibitors, the primary immunosuppressive therapy used to prevent alloreactivity of transplanted organs, have a narrow therapeutic index. Currently, treatment is individualized based on clinical assessment of the risk of rejection or toxicity guided by trough concentration monitoring. Advances in immune monitoring have identified potential markers that may have value in understanding calcineurin inhibitor pharmacodynamics. Integration of these markers has the potential to complement therapeutic drug monitoring. Existing pharmacokinetic-pharmacodynamic (PK-PD) data is largely limited to correlation between the biomarker and trough concentrations at single time points. Immune related gene expression currently has the most evidence supporting PK-PD integration. Novel biomarker-based approaches to pharmacodynamic monitoring including development of enhanced PK-PD models are proposed to realize the full clinical benefit.