Single-cell RNA sequencing reveals peripheral blood mononuclear immune cell landscape associated with operational tolerance in a kidney transplant recipient.

Operational tolerance (OT) after kidney transplantation is defined as stable graft acceptance without the need for immunosuppression therapy. However, it is not clear which cellular and molecular pathways are driving tolerance in these patients. In this first-of-its-kind pilot study, we assessed the immune landscape associated with OT using single-cell analyses. Peripheral mononuclear cells from a kidney transplant recipient with OT (Tol), 2 healthy individuals (HC), and a kidney transplant recipient with normal kidney function on standard-of-care immunosuppression (SOC) were evaluated. The immune landscape of the Tol was drastically different from that of SOC and emerged closer to the profile of HC. TCL1A+ naive B cells and LSGAL1+ regulatory T cells (Tregs) were in higher proportions in Tol. We were unable to identify the Treg subcluster in SOC. The ligand-receptor analysis in HC and Tol identified interactions between B cells, and Tregs that enhance the proliferation and suppressive function of Tregs. SOC reported the highest proportion of activated B cells with more cells in the G2M phase. Our single-cell RNA sequencing study identified the mediators of tolerance; however, it emphasizes the requirement of similar investigations on a larger cohort to reaffirm the role of immune cells in tolerance.

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.

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.

Pretransplant kidney transcriptome captures intrinsic donor organ quality and predicts 24-month outcomes.

With the development of novel prognostic tools derived from omics technologies, transplant medicine is entering the era of precision medicine. Currently, there are no established predictive biomarkers for posttransplant kidney function. A total of 270 deceased donor pretransplant kidney biopsies were collected and posttransplant function was prospectively monitored. This study first assessed the utility of pretransplant gene expression profiles in predicting 24-month outcomes in a training set (n = 174). Nearly 600 differentially expressed genes were associated with 24-month graft function. Grafts that progressed to low function at 24 months exhibited upregulated immune responses and downregulated metabolic processes at pretransplantation. Using penalized logistic regression modeling, a 55 gene model area under the receiver operating curve (AUROC) for 24-month graft function was 0.994. Gene expression for a subset of candidate genes was then measured in an independent set of pretransplant biopsies (n = 96) using quantitative polymerase chain reaction. The AUROC when using 13 genes with three donor characteristics (age, race, body mass index) was 0.821. Subsequently, a risk score was calculated using this combination for each patient in the validation cohort, demonstrating the translational feasibility of using gene markers as prognostic tools. These findings support the potential of pretransplant transcriptomic biomarkers as novel instruments for improving posttransplant outcome predictions and associated management.

Nucleic acid biomarkers to assess graft injury after liver transplantation.

Many risk factors and complications impact the success of liver transplantation, such as ischaemia-reperfusion injury, acute rejection, and primary graft dysfunction. Molecular biomarkers have the potential to accurately diagnose, predict, and monitor injury progression or organ failure. There is a critical opportunity for reliable and non-invasive biomarkers to reduce the organ shortage by enabling i) the assessment of donor organ quality, ii) the monitoring of short- and long-term graft function, and iii) the prediction of acute and chronic disease development. To date, no established molecular biomarkers have been used to guide clinical decision-making in transplantation. In this review, we outline the recent advances in cell-free nucleic acid biomarkers for monitoring graft injury in liver transplant recipients. Prior work in this area can be divided into two categories: biomarker discovery and validation studies. Circulating nucleic acids (CNAs) can be found in the extracellular environment pertaining to different biological fluids such as bile, blood, urine, and perfusate. CNAs that are packaged into extracellular vesicles may facilitate intercellular and interorgan communication. Thus, decoding their biological function, cellular origins and molecular composition is imperative for diagnosing causes of graft injury, guiding immunosuppression and improving overall patient survival. Herein, we discuss the most promising molecular biomarkers, their state of development, and the critical aspects of study design in biomarker research for early detection of post-transplant liver injury. Future advances in biomarker studies are expected to personalise post-transplant therapy, leading to improved patient care and outcomes.

Surveillance of Plasmodium falciparum pfcrt haplotypes in southwestern uganda by high-resolution melt analysis.

BACKGROUND: Chloroquine (CQ) resistance is conferred by mutations in the Plasmodium falciparum CQ resistance transporter (pfcrt). Following CQ withdrawal for anti-malarial treatment, studies across malaria-endemic countries have shown a range of responses. In some areas, CQ sensitive parasites re-emerge, and in others, mutant haplotypes persist. Active surveillance of resistance mutations in clinical parasites is essential to inform treatment regimens; this effort requires fast, reliable, and cost-effective methods that work on a variety of sample types with reagents accessible in malaria-endemic countries. METHODS: Quantitative PCR followed by High-Resolution Melt (HRM) analysis was performed in a field setting to assess pfcrt mutations in two groups of clinical samples from Southwestern Uganda. Group 1 samples (119 in total) were collected in 2010 as predominantly Giemsa-stained slides; Group 2 samples (125 in total) were collected in 2015 as blood spots on filter paper. The Rotor-Gene Q instrument was utilized to assess the impact of different PCR-HRM reagent mixes and the detection of mixed haplotypes present in the clinical samples. Finally, the prevalence of the wild type (CVMNK) and resistant pfcrt haplotypes (CVIET and SVMNT) was evaluated in this understudied Southwestern region of Uganda. RESULTS: The sample source (i.e. Giemsa-stained slides or blood spots) and type of LCGreen-based reagent mixes did not impact the success of PCR-HRM. The detection limit of 10- 5 ng and the ability to identify mixed haplotypes as low as 10 % was similar to other HRM platforms. The CVIET haplotype predominated in the clinical samples (66 %, 162/244); however, there was a large regional variation between the sample groups (94 % CVIET in Group 1 and 44 % CVIET in Group 2). CONCLUSIONS: The HRM-based method exhibits the flexibility required to conduct reliable assessment of resistance alleles from various sample types generated during the clinical management of malaria. Large regional variations in CQ resistance haplotypes across Southwestern Uganda emphasizes the need for continued local parasite genotype assessment to inform anti-malarial treatment policies.

Extrachromosomal DNA amplicons in antimalarial-resistant Plasmodium falciparum.

Extrachromosomal (ec) DNAs are genetic elements that exist separately from the genome. Since ecDNA can carry beneficial genes, they are a powerful adaptive mechanism in cancers and many pathogens. For the first time, we report ecDNA contributing to antimalarial resistance in Plasmodium falciparum, the most virulent human malaria parasite. Using pulse field gel electrophoresis combined with PCR-based copy number analysis, we detected two ecDNA elements that differ in migration and structure. Entrapment in the electrophoresis well and low susceptibility to exonucleases revealed that the biologically relevant ecDNA element is large and complex in structure. Using deep sequencing, we show that ecDNA originates from the chromosome and expansion of an ecDNA-specific sequence may improve its segregation or expression. We speculate that ecDNA is maintained using established mechanisms due to shared characteristics with the mitochondrial genome. Implications of ecDNA discovery in this organism are wide-reaching due to the potential for new strategies to target resistance development.

Visual attraction in Drosophila larvae develops during a critical period and is modulated by crowding conditions.

The development of social behavior is poorly understood. Many animals adjust their behavior to environmental conditions based on a social context. Despite having relatively simple visual systems, Drosophila larvae are capable of identifying and are attracted to the movements of other larvae. Here, we show that Drosophila larval visual recognition is encoded by the movements of nearby larvae, experienced during a specific developmental critical period. Exposure to moving larvae, only during a specific period, is sufficient for later visual recognition of movement. Larvae exposed to wild-type body movements, during the critical period, are not attracted to the movements of tubby mutants, which have altered morphology. However, exposure to tubby, during the critical period, results in tubby recognition at the expense of wild-type recognition indicating that this is true learning. Visual recognition is not learned in excessively crowded conditions, and this is emulated by exposure, during the critical period, to food previously used by crowded larvae. We propose that Drosophila larvae have a distinct critical period, during which they assess both social and resource conditions, and that this irreversibly determines later visually guided social behavior. This model provides a platform towards understanding the regulation and development of social behavior.