Extended survival versus accelerated rejection of nonhuman primate islet allografts: Effect of mesenchymal stem cell source and timing

Mesenchymal stem cells (MSC) have been shown to be immunomodulatory, tissue regenerative, and graft promoting; however, several questions remain with regard to ideal MSC source and timing of administration. In this study, we utilized a rigorous preclinical model of allogeneic islet cell transplantation, incorporating reduced immune suppression and near to complete mismatch of major histocompatibility antigens between the diabetic cynomolgus monkey recipient and the islet donor, to evaluate both the graft promoting impact of MSC source, that is, derived from the islet recipient, the islet donor or an unrelated third party as well as the impact of timing. Co-transplant of MSC and islets on post-operative day 0, followed by additional IV MSC infusions in the first posttransplant month, resulted in prolongation of rejection free and overall islet survival and superior metabolic control for animals treated with recipient as compared to donor or third-party MSC. Immunological analyses demonstrated that infusion of MSC from either source did not prevent alloantibody formation to the islet or MSC donor; however, treatment with recipient MSC resulted in significant downregulation of memory T cells, decreased anti-donor T cell proliferation, and a trend toward increased Tregulatory:Tconventional ratios.

Discovery and cross-validation of peripheral blood and renal biopsy gene expression signatures from ethnically diverse kidney transplant populations

We determined peripheral blood (PB) and biopsy (Bx) RNA expression signatures in a Brazilian and US cohort of kidney transplant patients. Phenotypes assigned by precise histology were: acute rejection (AR), interstitial fibrosis/tubular atrophy/chronic rejection (CR), excellent functioning transplants (TX), and glomerulonephritis recurrence (GN). Samples were analyzed on microarrays and profiles from each cohort were cross-validated on the other cohort with similar phenotypes. We discovered signatures for each tissue: (1) AR vs TX, (2) CR vs TX, and (3) GN vs TX using the Random Forests algorithm. We validated biopsies signatures of AR vs TX (area under the curve [AUC] 0.97) and CR vs TX (AUC 0.87). We also validated both PB and Bx signatures of AR vs TX and CR vs TX with varying degrees of accuracy. Several biological pathways were shared between AR and CR, suggesting similar rejection mechanisms in these 2 clinical phenotypes. Thus, we identified gene expression signatures for AR and CR in transplant patients and validated them in independent cohorts of significantly different racial/ethnic backgrounds. These results reveal that there are strong unifying immune mechanisms driving transplant diseases and identified in the signatures discovered in each cohort, suggesting that molecular diagnostics across populations are feasible despite ethnic and environmental differences.

Development and clinical validity of a novel blood-based molecular biomarker for subclinical acute rejection following kidney transplant

Noninvasive biomarkers are needed to monitor stable patients after kidney transplant (KT), because subclinical acute rejection (subAR), currently detectable only with surveillance biopsies, can lead to chronic rejection and graft loss. We conducted a multicenter study to develop a blood-based molecular biomarker for subAR using peripheral blood paired with surveillance biopsies and strict clinical phenotyping algorithms for discovery and validation. At a predefined threshold, 72% to 75% of KT recipients achieved a negative biomarker test correlating with the absence of subAR (negative predictive value: 78%-88%), while a positive test was obtained in 25% to 28% correlating with the presence of subAR (positive predictive value: 47%-61%). The clinical phenotype and biomarker independently and statistically correlated with a composite clinical endpoint (renal function, biopsy-proved acute rejection, ≥grade 2 interstitial fibrosis, and tubular atrophy), as well as with de novo donor-specific antibodies. We also found that <50% showed histologic improvement of subAR on follow-up biopsies despite treatment and that the biomarker could predict this outcome. Our data suggest that a blood-based biomarker that reduces the need for the indiscriminate use of invasive surveillance biopsies and that correlates with transplant outcomes could be used to monitor KT recipients with stable renal function, including after treatment for subAR, potentially improving KT outcomes.

Expression of the miR-150 tumor suppressor is restored by and synergizes with rapamycin in a human leukemia T-cell line

miR-150 functions as a tumor suppressor in malignancies of the lymphocyte lineage and its expression is significantly reduced in these cells. However, the mechanism of miR-150 repression is unknown and so are pharmacological interventions that can reverse it. Here, we report that reduced expression of miR-150 in human Jurkat T-cell acute lymphoblastic leukemia (T-ALL) cells is mediated by constitutive mTOR signaling, a common characteristic of T-ALL cell lines and clinical isolates. Activating mTOR signaling in non-malignant T cells also resulted in a significant miR-150 down-regulation. Conversely, treatment with a pharmacological mTOR inhibitor, rapamycin, increased miR-150 expression in a dose-dependent manner in Jurkat cells, as well as in other leukemia cells. Interestingly, ectopic over-expression of miR-150 acted in a feed-forward loop and further sensitized Jurkat cells to a rapamycin-induced cell cycle arrest by targeting a large network of cell cycle genes. These findings suggest that miR-150 is normally expressed in quiescent T lymphocytes to reinforce an anti-proliferative state, and that mTOR signaling promotes cell proliferation in part by inhibiting miR-150 expression. Restoration of the miR-150-dependent anti-proliferative loop constitutes a novel mechanism underlying the efficacy of rapamycin in a T-ALL cell line. Further investigation of this mechanism in clinical isolates of T-ALL and other hematopoietic malignancies could help better guide development of targeted therapies.

A genome-wide survey of mutations in the Jurkat cell line

Background

The Jurkat cell line has an extensive history as a model of T cell signaling. But at the turn of the 21st century, some expression irregularities were observed, raising doubts about how closely the cell line paralleled normal human T cells. While numerous expression deficiencies have been described in Jurkat, genetic explanations have only been provided for a handful of defects.

Results

Here, we report a comprehensive catolog of genomic variation in the Jurkat cell line based on whole-genome sequencing. With this list of all detectable, non-reference sequences, we prioritize potentially damaging mutations by mining public databases for functional effects. We confirm documented mutations in Jurkat and propose links from detrimental gene variants to observed expression abnormalities in the cell line.

Conclusions

The Jurkat cell line harbors many mutations that are associated with cancer and contribute to Jurkat’s unique characteristics. Genes with damaging mutations in the Jurkat cell line are involved in T-cell receptor signaling (PTEN, INPP5D, CTLA4, and SYK), maintenance of genome stability (TP53, BAX, and MSH2), and O-linked glycosylation (C1GALT1C1). This work ties together decades of molecular experiments and serves as a resource that will streamline both the interpretation of past research and the design of future Jurkat studies.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4718-6) contains supplementary material, which is available to authorized users.

Microdroplet PCR for Highly Multiplexed Targeted Bisulfite Sequencing

Many methods exist for examining CpG DNA methylation. However, many of these are qualitative, laborious to apply to a large number of genes simultaneously, or are not easy to target to specific regions of interest. Microdroplet PCR-based bisulfite sequencing allows for quantitative single base resolution analysis of investigator selected regions of interest. Following bisulfite conversion of genomic DNA, targeted microdroplet PCR is conducted with custom primer libraries. Samples are then fragmented, concatenated, and sequenced by high-throughput sequencing. The most recent technology allows for this method to be conducted with as little as 250 ng of bisulfite-converted DNA. The primary advantage of this method is the ability to hand-select the targeted regions covered by up to 10,000 amplicons of 500-600 bp. Moreover, the nature of microdroplet PCR virtually eliminates PCR bias and allows for the amplification of all targets simultaneously in a single tube.

Gene expression signature predicts human islet integrity and transplant functionality in diabetic mice

There is growing evidence that transplantation of cadaveric human islets is an effective therapy for type 1 diabetes. However, gauging the suitability of islet samples for clinical use remains a challenge. We hypothesized that islet quality is reflected in the expression of specific genes. Therefore, gene expression in 59 human islet preparations was analyzed and correlated with diabetes reversal after transplantation in diabetic mice. Analysis yielded 262 differentially expressed probesets, which together predict islet quality with 83% accuracy. Pathway analysis revealed that failing islet preparations activated inflammatory pathways, while functional islets showed increased regeneration pathway gene expression. Gene expression associated with apoptosis and oxygen consumption showed little overlap with each other or with the 262 probeset classifier, indicating that the three tests are measuring different aspects of islet cell biology. A subset of 36 probesets surpassed the predictive accuracy of the entire set for reversal of diabetes, and was further reduced by logistic regression to sets of 14 and 5 without losing accuracy. These genes were further validated with an independent cohort of 16 samples. We believe this limited number of gene classifiers in combination with other tests may provide complementary verification of islet quality prior to their clinical use.

H3K27 Methylation Dynamics during CD4 T Cell Activation: Regulation of JAK/STAT and IL12RB2 Expression by JMJD3

The changes to the epigenetic landscape in response to Ag during CD4 T cell activation have not been well characterized. Although CD4 T cell subsets have been mapped globally for numerous epigenetic marks, little has been done to study their dynamics early after activation. We have studied changes to promoter H3K27me3 during activation of human naive and memory CD4 T cells. Our results show that these changes occur relatively early (1 d) after activation of naive and memory cells and that demethylation is the predominant change to H3K27me3 at this time point, reinforcing high expression of target genes. Additionally, inhibition of the H3K27 demethylase JMJD3 in naive CD4 T cells demonstrates how critically important molecules required for T cell differentiation, such as JAK2 and IL12RB2, are regulated by H3K27me3. Our results show that H3K27me3 is a dynamic and important epigenetic modification during CD4 T cell activation and that JMJD3-driven H3K27 demethylation is critical for CD4 T cell function.

Precision medicine for suicidality: from universality to subtypes and personalization

Suicide remains a clear, present and increasing public health problem, despite being a potentially preventable tragedy. Its incidence is particularly high in people with overt or un(der)diagnosed psychiatric disorders. Objective and precise identification of individuals at risk, ways of monitoring response to treatments and novel preventive therapeutics need to be discovered, employed and widely deployed. We sought to investigate whether blood gene expression biomarkers for suicide (that is, a 'liquid biopsy' approach) can be identified that are more universal in nature, working across psychiatric diagnoses and genders, using larger cohorts than in previous studies. Such markers may reflect and/or be a proxy for the core biology of suicide. We were successful in this endeavor, using a comprehensive stepwise approach, leading to a wealth of findings. Steps 1, 2 and 3 were discovery, prioritization and validation for tracking suicidality, resulting in a Top Dozen list of candidate biomarkers comprising the top biomarkers from each step, as well as a larger list of 148 candidate biomarkers that survived Bonferroni correction in the validation step. Step 4 was testing the Top Dozen list and Bonferroni biomarker list for predictive ability for suicidal ideation (SI) and for future hospitalizations for suicidality in independent cohorts, leading to the identification of completely novel predictive biomarkers (such as CLN5 and AK2), as well as reinforcement of ours and others previous findings in the field (such as SLC4A4 and SKA2). Additionally, we examined whether subtypes of suicidality can be identified based on mental state at the time of high SI and identified four potential subtypes: high anxiety, low mood, combined and non-affective (psychotic). Such subtypes may delineate groups of individuals that are more homogenous in terms of suicidality biology and behavior. We also studied a more personalized approach, by psychiatric diagnosis and gender, with a focus on bipolar males, the highest risk group. Such a personalized approach may be more sensitive to gender differences and to the impact of psychiatric co-morbidities and medications. We compared testing the universal biomarkers in everybody versus testing by subtypes versus personalized by gender and diagnosis, and show that the subtype and personalized approaches permit enhanced precision of predictions for different universal biomarkers. In particular, LHFP appears to be a strong predictor for suicidality in males with depression. We also directly examined whether biomarkers discovered using male bipolars only are better predictors in a male bipolar independent cohort than universal biomarkers and show evidence for a possible advantage of personalization. We identified completely novel biomarkers (such as SPTBN1 and C7orf73), and reinforced previously known biomarkers (such as PTEN and SAT1). For diagnostic ability testing purposes, we also examined as predictors phenotypic measures as apps (for suicide risk (CFI-S, Convergent Functional Information for Suicidality) and for anxiety and mood (SASS, Simplified Affective State Scale)) by themselves, as well as in combination with the top biomarkers (the combination being our a priori primary endpoint), to provide context and enhance precision of predictions. We obtained area under the curves of 90% for SI and 77% for future hospitalizations in independent cohorts. Step 5 was to look for mechanistic understanding, starting with examining evidence for the Top Dozen and Bonferroni biomarkers for involvement in other psychiatric and non-psychiatric disorders, as a mechanism for biological predisposition and vulnerability. The biomarkers we identified also provide a window towards understanding the biology of suicide, implicating biological pathways related to neurogenesis, programmed cell death and insulin signaling from the universal biomarkers, as well as mTOR signaling from the male bipolar biomarkers. In particular, HTR2A increase coupled with ARRB1 and GSK3B decreases in expression in suicidality may provide a synergistic mechanistical corrective target, as do SLC4A4 increase coupled with AHCYL1 and AHCYL2 decrease. Step 6 was to move beyond diagnostics and mechanistical risk assessment, towards providing a foundation for personalized therapeutics. Items scored positive in the CFI-S and subtypes identified by SASS in different individuals provide targets for personalized (psycho)therapy. Some individual biomarkers are targets of existing drugs used to treat mood disorders and suicidality (lithium, clozapine and omega-3 fatty acids), providing a means toward pharmacogenomics stratification of patients and monitoring of response to treatment. Such biomarkers merit evaluation in clinical trials. Bioinformatics drug repurposing analyses with the gene expression biosignatures of the Top Dozen and Bonferroni-validated universal biomarkers identified novel potential therapeutics for suicidality, such as ebselen (a lithium mimetic), piracetam (a nootropic), chlorogenic acid (a polyphenol) and metformin (an antidiabetic and possible longevity promoting drug). Finally, based on the totality of our data and of the evidence in the field to date, a convergent functional evidence score prioritizing biomarkers that have all around evidence (track suicidality, predict it, are reflective of biological predisposition and are potential drug targets) brought to the fore APOE and IL6 from among the universal biomarkers, suggesting an inflammatory/accelerated aging component that may be a targetable common denominator.

Comparative top down proteomics of peripheral blood mononuclear cells from kidney transplant recipients with normal kidney biopsies or acute rejection

Recent studies utilizing transcriptomics, metabolomics, and bottom up proteomics have identified molecular signatures of kidney allograft pathology. Although these results make significant progress toward non-invasive differential diagnostics of dysfunction of a transplanted kidney, they provide little information on the intact, often modified, protein molecules present during progression of this pathology. Because intact proteins underpin diverse biological processes, measuring the relative abundance of their modified forms promises to advance mechanistic understanding, and might provide a new class of biomarker candidates. Here, we used top down proteomics to inventory the modified forms of whole proteins in peripheral blood mononuclear cells (PBMCs) taken at the time of kidney biopsy for 40 kidney allograft recipients either with healthy transplants or those suffering acute rejection. Supported by gas-phase fragmentation of whole protein ions during tandem mass spectrometry, we identified 344 proteins mapping to 2905 distinct molecular forms (proteoforms). Using an initial implementation of a label-free approach to quantitative top down proteomics, we obtained evidence suggesting relative abundance changes in 111 proteoforms between the two patient groups. Collectively, our work is the first to catalog intact protein molecules in PBMCs and suggests differentially abundant proteoforms for further analysis.

Changes in Urinary Microbiome Populations Correlate in Kidney Transplants With Interstitial Fibrosis and Tubular Atrophy Documented in Early Surveillance Biopsies

An unbalanced microbiome may lead to disease by creating aberrant immune responses. A recent association of cellular rejection with the development of interstitial fibrosis and tubular atrophy (IFTA) suggests the role of immune-mediated tissue injury. We hypothesized that developing IFTA correlates with altered urinary tract microbiomes (UMBs). UMBs at two serial time points, 1 and 6-8 months posttransplant, were assessed by 16S microbial ribosomal gene sequencing in 25 patients developing biopsy-proven IFTA compared to 23 transplant patients with normal biopsies and excellent function (TX) and 20 healthy nontransplant controls (HC). Streptococcus, the dominant genera in HC males, was lower in IFTA and TX males at 1 month compared to HCs. At 6-8 months, Streptococcus was further decreased in IFTA males, but normalized in TX. IFTA males and females had increases in number of genera per sample at 6-8 months. UMB composition varied substantially between individuals in all groups. Despite the wide variation in UMBs between individuals, IFTA was associated with a loss in dominant resident urinary microbes in males, and a parallel increase in nonresident, pathogenic bacteria in males and females. UMB changes may contribute to IFTA development by alteration of the host immune response.

Peripheral Blood Cell Gene Expression Diagnostic for Identifying Symptomatic Transthyretin Amyloidosis Patients: Male and Female Specific Signatures

Background: Early diagnosis of familial transthyretin (TTR) amyloid diseases remains challenging because of variable disease penetrance. Currently, patients must have an amyloid positive tissue biopsy to be eligible for disease-modifying therapies. Endomyocardial biopsies are typically amyloid positive when cardiomyopathy is suspected, but this disease manifestation is generally diagnosed late. Early diagnosis is often difficult because patients exhibit apparent symptoms of polyneuropathy, but have a negative amyloid biopsy. Thus, there is a pressing need for an additional early diagnostic strategy for TTR-aggregation-associated polyneuropathy and cardiomyopathy.

Methods and Findings: Global peripheral blood cell mRNA expression profiles from 263 tafamidis-treated and untreated V30M Familiar Amyloid Neuropathy patients, asymptomatic V30M carriers, and healthy, age- and sex-matched controls without TTR mutations were used to differentiate symptomatic from asymptomatic patients. We demonstrate that blood cell gene expression patterns reveal sex-independent, as well as male- and female-specific inflammatory signatures in symptomatic FAP patients, but not in asymptomatic carriers. These signatures differentiated symptomatic patients from asymptomatic V30M carriers with >80% accuracy. There was a global downregulation of the eIF2 pathway and its associated genes in all symptomatic FAP patients. We also demonstrated that the molecular scores based on these signatures significantly trended toward normalized values in an independent cohort of 46 FAP patients after only 3 months of tafamidis treatment.

Conclusions: This study identifies novel molecular signatures that differentiate symptomatic FAP patients from asymptomatic V30M carriers as well as affected males and females. We envision using this approach, initially in parallel with amyloid biopsies, to identify individuals who are asymptomatic gene carriers that may convert to FAP patients. Upon further validation, peripheral blood cell mRNA expression profiling could become an independent early diagnostic. This quantitative gene expression signature for symptomatic FAP could also become a biomarker to demonstrate significant disease-modifying effects of drugs and drug candidates. For example, when new disease modifiers are being evaluated in a FAP clinical trial, such surrogate biomarkers have the potential to provide an objective, quantitative and mechanistic molecular diagnostic of disease response to therapy.

Towards understanding and predicting suicidality in women: biomarkers and clinical risk assessment

Women are under-represented in research on suicidality to date. Although women have a lower rate of suicide completion than men, due in part to the less-violent methods used, they have a higher rate of suicide attempts. Our group has previously identified genomic (blood gene expression biomarkers) and clinical information (apps) predictors for suicidality in men. We now describe pilot studies in women. We used a powerful within-participant discovery approach to identify genes that change in expression between no suicidal ideation (no SI) and high suicidal ideation (high SI) states (n=12 participants out of a cohort of 51 women psychiatric participants followed longitudinally, with diagnoses of bipolar disorder, depression, schizoaffective disorder and schizophrenia). We then used a Convergent Functional Genomics (CFG) approach to prioritize the candidate biomarkers identified in the discovery step by using all the prior evidence in the field. Next, we validated for suicidal behavior the top-ranked biomarkers for SI, in a demographically matched cohort of women suicide completers from the coroner's office (n=6), by assessing which markers were stepwise changed from no SI to high SI to suicide completers. We then tested the 50 biomarkers that survived Bonferroni correction in the validation step, as well as top increased and decreased biomarkers from the discovery and prioritization steps, in a completely independent test cohort of women psychiatric disorder participants for prediction of SI (n=33) and in a future follow-up cohort of psychiatric disorder participants for prediction of psychiatric hospitalizations due to suicidality (n=24). Additionally, we examined how two clinical instruments in the form of apps, Convergent Functional Information for Suicidality (CFI-S) and Simplified Affective State Scale (SASS), previously tested in men, perform in women. The top CFI-S item distinguishing high SI from no SI states was the chronic stress of social isolation. We then showed how the clinical information apps combined with the 50 validated biomarkers into a broad predictor (UP-Suicide), our apriori primary end point, predicts suicidality in women. UP-Suicide had a receiver-operating characteristic (ROC) area under the curve (AUC) of 82% for predicting SI and an AUC of 78% for predicting future hospitalizations for suicidality. Some of the individual components of the UP-Suicide showed even better results. SASS had an AUC of 81% for predicting SI, CFI-S had an AUC of 84% and the combination of the two apps had an AUC of 87%. The top biomarker from our sequential discovery, prioritization and validation steps, BCL2, predicted future hospitalizations due to suicidality with an AUC of 89%, and the panel of 50 validated biomarkers (BioM-50) predicted future hospitalizations due to suicidality with an AUC of 94%. The best overall single blood biomarker for predictions was PIK3C3 with an AUC of 65% for SI and an AUC of 90% for future hospitalizations. Finally, we sought to understand the biology of the biomarkers. BCL2 and GSK3B, the top CFG scoring validated biomarkers, as well as PIK3C3, have anti-apoptotic and neurotrophic effects, are decreased in expression in suicidality and are known targets of the anti-suicidal mood stabilizer drug lithium, which increases their expression and/or activity. Circadian clock genes were overrepresented among the top markers. Notably, PER1, increased in expression in suicidality, had an AUC of 84% for predicting future hospitalizations, and CSNK1A1, decreased in expression, had an AUC of 96% for predicting future hospitalizations. Circadian clock abnormalities are related to mood disorder, and sleep abnormalities have been implicated in suicide. Docosahexaenoic acid signaling was one of the top biological pathways overrepresented in validated biomarkers, which is of interest given the potential therapeutic and prophylactic benefits of omega-3 fatty acids. Some of the top biomarkers from the current work in women showed co-directionality of change in expression with our previous work in men, whereas others had changes in opposite directions, underlying the issue of biological context and differences in suicidality between the two genders. With this study, we begin to shed much needed light in the area of female suicidality, identify useful objective predictors and help understand gender commonalities and differences. During the conduct of the study, one participant committed suicide. In retrospect, when the analyses were completed, her UP-Suicide risk prediction score was at the 100 percentile of all participants tested.

UHM-ULM interactions in the RBM39-U2AF65 splicing-factor complex

RNA-binding protein 39 (RBM39) is a splicing factor and a transcriptional co-activator of estrogen receptors and Jun/AP-1, and its function has been associated with malignant progression in a number of cancers. The C-terminal RRM domain of RBM39 belongs to the U2AF homology motif family (UHM), which mediate protein-protein interactions through a short tryptophan-containing peptide known as the UHM-ligand motif (ULM). Here, crystal and solution NMR structures of the RBM39-UHM domain, and the crystal structure of its complex with U2AF65-ULM, are reported. The RBM39-U2AF65 interaction was confirmed by co-immunoprecipitation from human cell extracts, by isothermal titration calorimetry and by NMR chemical shift perturbation experiments with the purified proteins. When compared with related complexes, such as U2AF35-U2AF65 and RBM39-SF3b155, the RBM39-UHM-U2AF65-ULM complex reveals both common and discriminating recognition elements in the UHM-ULM binding interface, providing a rationale for the known specificity of UHM-ULM interactions. This study therefore establishes a structural basis for specific UHM-ULM interactions by splicing factors such as U2AF35, U2AF65, RBM39 and SF3b155, and a platform for continued studies of intermolecular interactions governing disease-related alternative splicing in eukaryotic cells.

Genome-wide expression profiling in the peripheral blood of patients with fibromyalgia

OBJECTIVES

Fibromyalgia (FM) is a common pain disorder characterized by nociceptive dysregulation. The basic biology of FM is poorly understood. Herein we have used agnostic gene expression as a potential probe for informing its underlying biology and the development of a proof-of-concept diagnostic gene expression signature.

METHODS

We analyzed RNA expression in 70 FM patients and 70 healthy controls. The isolated RNA was amplified and hybridized to Affymetrix® Human Gene 1.1 ST Peg arrays. The data was analyzed using Partek Genomics Suite version 6.6.

RESULTS

Fibromyalgia patients exhibited a differential expression of 421 genes (p<0.001), several relevant to pathways for pain processing, such as glutamine/glutamate signaling and axonal development. There was also an upregulation of several inflammatory pathways and downregulation of pathways related to hypersensitivity and allergy. Using rigorous diagnostic modeling strategies, we show "locked" gene signatures discovered on Training and Test cohorts, that have a mean Area Under the Curve (AUC) of 0.81 on randomized, independent external data cohorts. Lastly, we identified a subset of 10 probesets that provided a diagnostic sensitivity for FM of 95% and a specificity of 96%. We also show that the signatures for FM were very specific to FM rather than common FM comorbidities.

CONCLUSIONS

These findings provide new insights relevant to the pathogenesis of FM, and provide several testable hypotheses that warrant further exploration and also establish the foundation for a first blood-based molecular signature in FM that needs to be validated in larger cohorts of patients.

Transplant-induced reactivation of murine cytomegalovirus immediate early gene expression is associated with recruitment of NF-κB and AP-1 to the major immediate early promoter

Reactivation of latent human cytomegalovirus is a significant infectious complication of organ transplantation and current therapies target viral replication once reactivation of latent virus has already occurred. The specific molecular pathways that activate viral gene expression in response to transplantation are not well understood. Our studies aim to identify these factors, with the goal of developing novel therapies that prevent transcriptional reactivation in transplant recipients. Murine cytomegalovirus (MCMV) is a valuable model for studying latency and reactivation of CMV in vivo. We previously demonstrated that transplantation of MCMV-latently infected kidneys into allogeneic recipients induces reactivation of immediate early (IE) gene expression and epigenetic reprogramming of the major immediate early promoter (MIEP) within 48 h. We hypothesize that these events are mediated by activation of signalling pathways that lead to binding of transcription factors to the MIEP, including AP-1 and NF-κB. Here we show that transplantation induces rapid activation of several members of the AP-1 and NF-κB transcription factor family and we demonstrate that canonical NF-κB (p65/p50), the junD component of AP-1, and nucleosome remodelling complexes are recruited to the MIEP following transplantation. Proteomic analysis of recipient plasma and transcriptome analysis of kidney RNA identified five extracellular ligands, including TNF, IL-1β, IL-18, CD40L and IL-6, and three intracellular signalling pathways associated with reactivation of IE gene expression. Identification of the factors that mediate activation of these signalling pathways may eventually lead to new therapies to prevent reactivation of CMV and its sequelae.

The Activation-Induced Assembly of an RNA/Protein Interactome Centered on the Splicing Factor U2AF2 Regulates Gene Expression in Human CD4 T Cells

Activation of CD4 T cells is a reaction to challenges such as microbial pathogens, cancer and toxins that defines adaptive immune responses. The roles of T cell receptor crosslinking, intracellular signaling, and transcription factor activation are well described, but the importance of post-transcriptional regulation by RNA-binding proteins (RBPs) has not been considered in depth. We describe a new model expanding and activating primary human CD4 T cells and applied this to characterizing activation-induced assembly of splicing factors centered on U2AF2. We immunoprecipitated U2AF2 to identify what mRNA transcripts were bound as a function of activation by TCR crosslinking and costimulation. In parallel, mass spectrometry revealed the proteins incorporated into the U2AF2-centered RNA/protein interactome. Molecules that retained interaction with the U2AF2 complex after RNAse treatment were designated as "central" interactome members (CIMs). Mass spectrometry also identified a second class of activation-induced proteins, "peripheral" interactome members (PIMs), that bound to the same transcripts but were not in physical association with U2AF2 or its partners. siRNA knockdown of two CIMs and two PIMs caused changes in activation marker expression, cytokine secretion, and gene expression that were unique to each protein and mapped to pathways associated with key aspects of T cell activation. While knocking down the PIM, SYNCRIP, impacts a limited but immunologically important set of U2AF2-bound transcripts, knockdown of U2AF1 significantly impairs assembly of the majority of protein and mRNA components in the activation-induced interactome. These results demonstrated that CIMs and PIMs, either directly or indirectly through RNA, assembled into activation-induced U2AF2 complexes and play roles in post-transcriptional regulation of genes related to cytokine secretion. These data suggest an additional layer of regulation mediated by the activation-induced assembly of RNA splicing interactomes that is important for understanding T cell activation.

Suppression of transcriptional drift extends C. elegans lifespan by postponing the onset of mortality

Longevity mechanisms increase lifespan by counteracting the effects of aging. However, whether longevity mechanisms counteract the effects of aging continually throughout life, or whether they act during specific periods of life, preventing changes that precede mortality is unclear. Here, we uncover transcriptional drift, a phenomenon that describes how aging causes genes within functional groups to change expression in opposing directions. These changes cause a transcriptome-wide loss in mRNA stoichiometry and loss of co-expression patterns in aging animals, as compared to young adults. Using Caenorhabditis elegans as a model, we show that extending lifespan by inhibiting serotonergic signals by the antidepressant mianserin attenuates transcriptional drift, allowing the preservation of a younger transcriptome into an older age. Our data are consistent with a model in which inhibition of serotonergic signals slows age-dependent physiological decline and the associated rise in mortality levels exclusively in young adults, thereby postponing the onset of major mortality.

DOI:http://dx.doi.org/10.7554/eLife.08833.001

All organisms age, leading to gradual declines in the body’s systems and eventually death. How certain genetic mutations and drugs delay the effects of aging and promote survival to an older age is a question many researchers are exploring. One way this problem is investigated is by looking at how the activity – or expression – of different genes changes during aging.

Scientists interested in understanding aging and longevity often study a simple worm called Caenorhabditis elegans. This worm normally lives for about three weeks, and young C. elegans are able to produce offspring within days of hatching. This accelerated life cycle allows scientists to observe the entire lifespan of the worms. Over time, experiments have shown that DNA damage, changes in behavior and changes to gene expression are all markers of aging in the worms.

Now, Rangaraju et al. describe how changes in gene expression patterns that begin early in the lives of C. elegans shorten their lifespan. Specifically, in groups of genes that work together, some genes increase expression, while others decrease expression with age. This phenomenon is called “transcriptional drift” and leads to an age-associated loss of coordination among groups of genes that help orchestrate specific tasks.

Rangaraju et al. show that an antidepressant called mianserin prevents transcriptional drift in many of C. elegans’ genes: young worms treated with the drug resist the effects of aging on the transcriptome and maintain coordinated patterns of gene expression for longer. Maintaining coordinated patterns of gene expression postpones the onset of age-related bodily declines and extends the life of treated worms by extending the duration of young adulthood and postponing the onset of age-associated death. The drug also appears to protect against stress-induced changes in gene expression. This suggests that some of the age-related shifts in gene expression occur when cells fail to recover normal gene expression patterns after a stressful event.

Questions that remain to be investigated in future studies are whether other longevity mechanisms also extend lifespan by preserving coordinated gene expression patterns, and whether other longevity mechanisms act by extending specific periods of life.

DOI:http://dx.doi.org/10.7554/eLife.08833.002

Understanding and predicting suicidality using a combined genomic and clinical risk assessment approach

Worldwide, one person dies every 40 seconds by suicide, a potentially preventable tragedy. A limiting step in our ability to intervene is the lack of objective, reliable predictors. We have previously provided proof of principle for the use of blood gene expression biomarkers to predict future hospitalizations due to suicidality, in male bipolar disorder participants. We now generalize the discovery, prioritization, validation, and testing of such markers across major psychiatric disorders (bipolar disorder, major depressive disorder, schizoaffective disorder, and schizophrenia) in male participants, to understand commonalities and differences. We used a powerful within-participant discovery approach to identify genes that change in expression between no suicidal ideation and high suicidal ideation states (n=37 participants out of a cohort of 217 psychiatric participants followed longitudinally). We then used a convergent functional genomics (CFG) approach with existing prior evidence in the field to prioritize the candidate biomarkers identified in the discovery step. Next, we validated the top biomarkers from the prioritization step for relevance to suicidal behavior, in a demographically matched cohort of suicide completers from the coroner's office (n=26). The biomarkers for suicidal ideation only are enriched for genes involved in neuronal connectivity and schizophrenia, the biomarkers also validated for suicidal behavior are enriched for genes involved in neuronal activity and mood. The 76 biomarkers that survived Bonferroni correction after validation for suicidal behavior map to biological pathways involved in immune and inflammatory response, mTOR signaling and growth factor regulation. mTOR signaling is necessary for the effects of the rapid-acting antidepressant agent ketamine, providing a novel biological rationale for its possible use in treating acute suicidality. Similarly, MAOB, a target of antidepressant inhibitors, was one of the increased biomarkers for suicidality. We also identified other potential therapeutic targets or biomarkers for drugs known to mitigate suicidality, such as omega-3 fatty acids, lithium and clozapine. Overall, 14% of the top candidate biomarkers also had evidence for involvement in psychological stress response, and 19% for involvement in programmed cell death/cellular suicide (apoptosis). It may be that in the face of adversity (stress), death mechanisms are turned on at a cellular (apoptosis) and organismal level. Finally, we tested the top increased and decreased biomarkers from the discovery for suicidal ideation (CADM1, CLIP4, DTNA, KIF2C), prioritization with CFG for prior evidence (SAT1, SKA2, SLC4A4), and validation for behavior in suicide completers (IL6, MBP, JUN, KLHDC3) steps in a completely independent test cohort of psychiatric participants for prediction of suicidal ideation (n=108), and in a future follow-up cohort of psychiatric participants (n=157) for prediction of psychiatric hospitalizations due to suicidality. The best individual biomarker across psychiatric diagnoses for predicting suicidal ideation was SLC4A4, with a receiver operating characteristic (ROC) area under the curve (AUC) of 72%. For bipolar disorder in particular, SLC4A4 predicted suicidal ideation with an AUC of 93%, and future hospitalizations with an AUC of 70%. SLC4A4 is involved in brain extracellular space pH regulation. Brain pH has been implicated in the pathophysiology of acute panic attacks. We also describe two new clinical information apps, one for affective state (simplified affective state scale, SASS) and one for suicide risk factors (Convergent Functional Information for Suicide, CFI-S), and how well they predict suicidal ideation across psychiatric diagnoses (AUC of 85% for SASS, AUC of 89% for CFI-S). We hypothesized a priori, based on our previous work, that the integration of the top biomarkers and the clinical information into a universal predictive measure (UP-Suicide) would show broad-spectrum predictive ability across psychiatric diagnoses. Indeed, the UP-Suicide was able to predict suicidal ideation across psychiatric diagnoses with an AUC of 92%. For bipolar disorder, it predicted suicidal ideation with an AUC of 98%, and future hospitalizations with an AUC of 94%. Of note, both types of tests we developed (blood biomarkers and clinical information apps) do not require asking the individual assessed if they have thoughts of suicide, as individuals who are truly suicidal often do not share that information with clinicians. We propose that the widespread use of such risk prediction tests as part of routine or targeted healthcare assessments will lead to early disease interception followed by preventive lifestyle modifications and proactive treatment.

Transplanting Kidneys from Deceased Donors With Severe Acute Kidney Injury

Our aim was to determine outcomes with transplanting kidneys from deceased donors with acute kidney injury, defined as a donor with terminal serum creatinine ≥2.0 mg/dL, or a donor requiring acute renal replacement therapy. We included all patients who received deceased donor kidney transplant from June 2004 to October 2013. There were 162 AKI donor transplant recipients (21% of deceased donor transplants): 139 in the standard criteria donor (SCD) and 23 in the expanded criteria donor (ECD) cohort. 71% of the AKI donors had stage 3 (severe AKI), based on acute kidney injury network (AKIN) staging. Protocol biopsies were done at 1, 4, and 12 months posttransplant. One and four month formalin-fixed paraffin embedded (FFPE) biopsies from 48 patients (24 AKI donors, 24 non-AKI) underwent global gene expression profiling using DNA microarrays (96 arrays). DGF was more common in the AKI group but eGFR, graft survival at 1 year and proportion with IF/TA>2 at 1 year were similar for the two groups. At 1 month, there were 898 differentially expressed genes in the AKI group (p-value <0.005; FDR <10%), but by 4 months there were no differences. Transplanting selected kidneys from deceased donors with AKI is safe and has excellent outcomes.

Genomic profiles and predictors of early allograft dysfunction after human liver transplantation

Early hepatic allograft dysfunction (EAD) manifests posttransplantation with high serum transaminases, persistent cholestasis, and coagulopathy. The biological mechanisms are poorly understood. This study investigates the molecular mechanisms involved in EAD and defines a gene expression signature revealing different biological pathways in subjects with EAD from those without EAD, a potential first step in developing a molecular classifier as a potential clinical diagnostic. Global gene expression profiles of 30 liver transplant recipients of deceased donor grafts with EAD and 26 recipients without graft dysfunction were investigated using microarrays of liver biopsies performed at the end of cold storage and after graft reperfusion prior to closure. Results reveal a shift in inflammatory and metabolic responses between the two time points and differences between EAD and non-EAD. We identified relevant pathways (PPARα and NF-κB) and targets (such as CXCL1, IL1, TRAF6, TIPARP, and TNFRSF1B) associated with the phenotype of EAD. Preliminary proof of concept gene expression classifiers that distinguish EAD from non-EAD patients, with Area Under the Curve (AUC) >0.80 were also identified. This data may have mechanistic and diagnostic implications for EAD.

AST/ASTS workshop on increasing organ donation in the United States: creating an "arc of change" from removing disincentives to testing incentives

The American Society of Transplantation (AST) and American Society of Transplant Surgeons (ASTS) convened a workshop on June 2-3, 2014, to explore increasing both living and deceased organ donation in the United States. Recent articles in the lay press on illegal organ sales and transplant tourism highlight the impact of the current black market in kidneys that accompanies the growing global organ shortage. We believe it important not to conflate the illegal market for organs, which we reject in the strongest possible terms, with the potential in the United States for concerted action to remove all remaining financial disincentives for donors and critically consider testing the impact and acceptability of incentives to increase organ availability in the United States. However, we do not support any trials of direct payments or valuable considerations to donors or families based on a process of market-assigned values of organs. This White Paper represents a summary by the authors of the deliberations of the Incentives Workshop Group and has been approved by both AST and ASTS Boards.

Defining CD4 T cell memory by the epigenetic landscape of CpG DNA methylation

Memory T cells are primed for rapid responses to Ag; however, the molecular mechanisms responsible for priming remain incompletely defined. CpG methylation in promoters is an epigenetic modification, which regulates gene transcription. Using targeted bisulfite sequencing, we examined methylation of 2100 genes (56,000 CpGs) mapped by deep sequencing of T cell activation in human naive and memory CD4 T cells. Four hundred sixty-six CpGs (132 genes) displayed differential methylation between naive and memory cells. Twenty-one genes exhibited both differential methylation and gene expression before activation, linking promoter DNA methylation states to gene regulation; 6 of 21 genes encode proteins closely studied in T cells, whereas 15 genes represent novel targets for further study. Eighty-four genes demonstrated differential methylation between memory and naive cells that correlated to differential gene expression following activation, of which 39 exhibited reduced methylation in memory cells coupled with increased gene expression upon activation compared with naive cells. These reveal a class of primed genes more rapidly expressed in memory compared with naive cells and putatively regulated by DNA methylation. These findings define a DNA methylation signature unique to memory CD4 T cells that correlates with activation-induced gene expression.

Plasma protein biomarkers enhance the clinical prediction of kidney injury recovery in patients undergoing liver transplantation

Biomarkers predictive of recovery from acute kidney injury (AKI) after liver transplantation (LT) could enhance decision algorithms regarding the need for liver-kidney transplantation or renal sparing regimens. Multianalyte plasma/urine kidney injury protein panels were performed immediately before and 1 month post-LT in an initial test group divided by reversible pre-LT AKI (rAKI = post-LT renal recovery) versus no AKI (nAKI). This was followed by a larger validation set that included an additional group: irreversible pre-LT AKI (iAKI = no post-LT renal recovery). In the test group (n = 16), six pre-LT plasma (not urine) kidney injury proteins (osteopontin [OPN], neutrophil gelatinase-associated lipocalin, cystatin C, trefoil factor 3, tissue inhibitor of metalloproteinase [TIMP]-1, and β-2-microglobulin) were higher in rAKI versus nAKI (P < 0.05) and returned to normal values with renal recovery post-LT. In the validation set (n = 46), a number of proteins were significantly higher in both rAKI and iAKI versus nAKI. However, only pre-LT plasma OPN (P = 0.009) and TIMP-1 (P = 0.019) levels were significantly higher in rAKI versus iAKI. Logistic regression modeling was used to correlate the probability of post-LT rAKI, factoring in both pre-LT protein markers and clinical variables. A combined model including elevated OPN and TIMP-1 levels, age <57, and absence of diabetes had the highest area under the curve of 0.82, compared to protein-only and clinical variable-only models.

CONCLUSION

These data suggest that plasma protein profiles might improve the prediction of pre-LT kidney injury recovery after LT. However, multicenter, prospective studies are needed to validate these findings and ultimately test the value of such protein panels in perioperative management and decision making.

A structurally distinct human mycoplasma protein that generically blocks antigen-antibody union

We report the discovery of a broadly reactive antibody-binding protein (Protein M) from human mycoplasma. The crystal structure of the ectodomain of transmembrane Protein M differs from other known protein structures, as does its mechanism of antibody binding. Protein M binds with high affinity to all types of human and nonhuman immunoglobulin G, predominantly through attachment to the conserved portions of the variable region of the κ and λ light chains. Protein M blocks antibody-antigen union, likely because of its large C-terminal domain extending over the antibody-combining site, blocking entry to large antigens. Similar to the other immunoglobulin-binding proteins such as Protein A, Protein M as well as its orthologs in other Mycoplasma species could become invaluable reagents in the antibody field.

RNA purification and expression analysis using microarrays and RNA deep sequencing

Transcriptome analysis or global gene expression profiling is a powerful tool for discovery as well as -understanding biological mechanisms in health and disease. We present in this chapter a description of methods used to isolate mRNA from cells and tissues that has been optimized for preservation of RNA quality using clinical materials and implemented successfully in several large, multicenter studies by the authors. In addition, two methods, gene expression microarrays and RNAseq, are described for mRNA profiling of cells and tissues from clinical or laboratory sources.

Library construction for next-generation sequencing: overviews and challenges

High-throughput sequencing, also known as next-generation sequencing (NGS), has revolutionized genomic research. In recent years, NGS technology has steadily improved, with costs dropping and the number and range of sequencing applications increasing exponentially. Here, we examine the critical role of sequencing library quality and consider important challenges when preparing NGS libraries from DNA and RNA sources. Factors such as the quantity and physical characteristics of the RNA or DNA source material as well as the desired application (i.e., genome sequencing, targeted sequencing, RNA-seq, ChIP-seq, RIP-seq, and methylation) are addressed in the context of preparing high quality sequencing libraries. In addition, the current methods for preparing NGS libraries from single cells are also discussed.

MicroRNA regulation of T-lymphocyte immunity: modulation of molecular networks responsible for T-cell activation, differentiation, and development

MicroRNAs (miRNA) are a class of small non-coding RNAs that constitute an essential and evolutionarily conserved mechanism for post-transcriptional gene regulation. Multiple miRNAs have been described to play key roles in T-lymphocyte development, differentiation, and function. In this review, we highlight the current literature regarding the differential expression of miRNAs in various models of murine and human T-cell biology. We emphasize mechanistic understandings of miRNA regulation of thymocyte development, T-cell activation, and differentiation into effector and memory subsets. We describe the participation of miRNAs in complex regulatory circuits shaping T-cell proteomes in a context-dependent manner. It is striking that some miRNAs regulate multiple processes, while others only appear in limited functional contexts. It is also evident that the expression and function of specific miRNAs can differ between murine and human systems. Ultimately, it is not always correct to simplify the complex events of T-cell biology into a model driven by only one or two master regulator miRNAs. In reality, T-cell activation and differentiation involve the expression of multiple miRNAs with many mRNA targets; thus, the true extent of miRNA regulation of T-cell biology is likely far more vast than currently appreciated.

Finding the active genes in deep RNA-seq gene expression studies

BACKGROUND

Early application of second-generation sequencing technologies to transcript quantitation (RNA-seq) has hinted at a vast mammalian transcriptome, including transcripts from nearly all known genes, which might be fully measured only by ultradeep sequencing. Subsequent studies suggested that low-abundance transcripts might be the result of technical or biological noise rather than active transcripts; moreover, most RNA-seq experiments did not provide enough read depth to generate high-confidence estimates of gene expression for low-abundance transcripts. As a result, the community adopted several heuristics for RNA-seq analysis, most notably an arbitrary expression threshold of 0.3 - 1 FPKM for downstream analysis. However, advances in RNA-seq library preparation, sequencing technology, and informatic analysis have addressed many of the systemic sources of uncertainty and undermined the assumptions that drove the adoption of these heuristics. We provide an updated view of the accuracy and efficiency of RNA-seq experiments, using genomic data from large-scale studies like the ENCODE project to provide orthogonal information against which to validate our conclusions.

RESULTS

We show that a human cell's transcriptome can be divided into active genes carrying out the work of the cell and other genes that are likely the by-products of biological or experimental noise. We use ENCODE data on chromatin state to show that ultralow-expression genes are predominantly associated with repressed chromatin; we provide a novel normalization metric, zFPKM, that identifies the threshold between active and background gene expression; and we show that this threshold is robust to experimental and analytical variations.

CONCLUSIONS

The zFPKM normalization method accurately separates the biologically relevant genes in a cell, which are associated with active promoters, from the ultralow-expression noisy genes that have repressed promoters. A read depth of twenty to thirty million mapped reads allows high-confidence quantitation of genes expressed at this threshold, providing important guidance for the design of RNA-seq studies of gene expression. Moreover, we offer an example for using extensive ENCODE chromatin state information to validate RNA-seq analysis pipelines.

Genomic biomarkers correlate with HLA-identical renal transplant tolerance

The ability to achieve immunologic tolerance after transplantation is a therapeutic goal. Here, we report interim results from an ongoing trial of tolerance in HLA-identical sibling renal transplantation. The immunosuppressive regimen included alemtuzumab induction, donor hematopoietic stem cells, tacrolimus/mycophenolate immunosuppression converted to sirolimus, and complete drug withdrawal by 24 months post-transplantation. Recipients were considered tolerant if they had normal biopsies and renal function after an additional 12 months without immunosuppression. Of the 20 recipients enrolled, 10 had at least 36 months of follow-up after transplantation. Five of these 10 recipients had immunosuppression successfully withdrawn for 16-36 months (tolerant), 2 had disease recurrence, and 3 had subclinical rejection in protocol biopsies (nontolerant). Microchimerism disappeared after 1 year, and CD4(+)CD25(high)CD127(-)FOXP3(+) regulatory T cells and CD19(+)IgD/M(+)CD27(-) B cells were increased through 5 years post-transplantation in both tolerant and nontolerant recipients. Immune/inflammatory gene expression pathways in the peripheral blood and urine, however, were differentially downregulated between tolerant and nontolerant recipients. In summary, interim results from this trial of tolerance in HLA-identical renal transplantation suggest that predictive genomic biomarkers, but not immunoregulatory phenotyping, may be able to discriminate tolerant from nontolerant patients.

Genomic meta-analysis of growth factor and integrin pathways in chronic kidney transplant injury

BACKGROUND

Chronic Allograft Nephropathy (CAN) is a clinical entity of progressive kidney transplant injury. The defining histology is tubular atrophy with interstitial fibrosis (IFTA). Using a meta-analysis of microarrays from 84 kidney transplant biopsies, we revealed growth factor and integrin adhesion molecule pathways differentially expressed and correlated with histological progression. A bioinformatics approach mining independent datasets leverages new and existing data to identify correlative changes in integrin and growth factor signaling pathways.

RESULTS

Analysis of CAN/IFTA Banff grades showed that hepatocyte growth factor (HGF), and epidermal growth factor (EGF) pathways are significantly differentially expressed in all classes of CAN/IFTA. MAPK-dependent pathways were also significant. However, the TGFβ pathways, albeit present, failed to differentiate CAN/IFTA progression. The integrin subunits β8, αv, αμ and β5 are differentially expressed, but β1, β6 and α6 specifically correlate with progression of chronic injury. Results were validated using our published proteomic profiling of CAN/IFTA.

CONCLUSIONS

CAN/IFTA with chronic kidney injury is characterized by expression of distinct growth factors and specific integrin adhesion molecules as well as their canonical signaling pathways. Drug target mapping suggests several novel candidates for the next generation of therapeutics to prevent or treat progressive transplant dysfunction with interstitial fibrosis.

Systemic immunoregulatory and proteogenomic effects of tacrolimus to sirolimus conversion in liver transplant recipients

Immunosuppression (IS) withdrawal from calcineurin inhibitors is only possible in ≈ 20% of liver transplant recipients. However, mammalian target of rapamycin inhibitors (e.g., sirolimus; SRL) appear to be more immunoregulatory and might promote a tolerant state for withdrawal. Our aim was to determine whether systemic (i.e., blood, marrow, and allograft) signatures of immunoregulation are promoted by conversion from tacrolimus (TAC) to SRL. We therefore performed the following serial assays before and after SRL conversion in liver transplant recipients to test for enhanced markers of immunoregulation: (1) flow-cytometry immunophenotyping of peripheral blood mononuclear cells (PBMCs) and bone marrow aspirates for regulatory T cells (Tregs) (e.g., CD4(+) CD25(+++) FOXP3(+) ) and regulatory dendritic cells (DCregs) (immunoglobulin-like transcript 3(+) /4(+) ); (2) liver biopsy immunohistochemical staining (e.g., FOXP3:CD3 and CD4:CD8 ratios) and immunophenotyping of biopsy-derived Tregs after growth in culture; (3) effects of pre- versus postconversion sera on Treg generation in mixed lymphocyte reactions; (4) peripheral blood nonspecific CD4 responses; and (5) peripheral blood gene transcripts and proteomic profiles. We successfully converted 20 nonimmune, nonviremic recipients (age, 57.2 ± 8.0; 3.5 ± 2.1 years post-liver transplantation) from TAC to SRL for renal dysfunction. Our results demonstrated significant increases in Tregs in PBMCs and marrow and DCregs in PBMCs (P < 0.01) after conversion. In biopsy staining, FOXP3:CD3 and CD4:CD8 ratios were significantly higher after conversion and a number of biopsy cultures developed new or higher FOXP3(+) cell growth. Nonspecific CD4 responses did not change. Both pre- and postconversion sera inhibited mixed lymphocyte reactions, although only TAC sera suppressed Treg generation. Finally, 289 novel genes and 22 proteins, several important in immunoregulatory pathways, were expressed after conversion.

CONCLUSIONS

TAC to SRL conversion increases systemic Tregs, DCregs, and immunoregulatory proteogenomic signatures in liver transplant recipients and may therefore facilitate IS minimization or withdrawal.

HLA identical non-chimeric and HLA disparate chimeric renal transplant tolerance

In this chapter, we describe studies on non-chimeric human leukocyte antigen (HLA) identical tolerance and chimeric HLA disparate tolerance brought about by infusions of hematopoietic stem cells from the renal donor (DHSC). In our HLA identical series, 4 DHSC infusions were administered during the first 9 months posttransplant in a highly immunoregulatory environment using alemtuzumab induction and rapid conversion from early tacrolimus to mycophenolate and sirolimus. This resulted in the generation of recipient T regulatory cells accompanied by genomic indicators, but only transient chimerism. Seven of the first 12 recipients have been immunosuppression-free between 1 1/2 - 4 years with transplant biopsies free of rejection one year after immunosuppression withdrawal. The HLAdisparate group was treated by non-myeloablative conditioning consisting of: 200cGy whole body irradiation; fludarabine; cyclophosphamide; and, perioperative infusion of a product termed FCRx that contained DHSC, T cells, and a unique fraction of bone marrow derived CD8+TCR-alphabeta-negative cells. Five of the first 8 subjects became 100% chimeric in the peripheral blood and have been immunosuppression-free for 2 to 4 years without graft-versus-host-disease and with normal function and transplant biopsies. An additional 12 recipients with shorter follow-up have had similar courses. Those with non-durable chimerism have not been able to have immunosuppression withdrawn but maintain normal renal transplant function. We conclude that non-HLA disparities in renal transplants between HLA identical pairs may not need durable chimerism to induce tolerance provided by DHSC and temporary immunosuppression supporting the development of regulatory T cells. However, more intense conditioning and infusion of FCRx leading to durable chimerism in the absence of graft versus host disease is necessary to induce tolerance in HLA disparate pairs.

Outcomes and native renal recovery following simultaneous liver-kidney transplantation

With the increase in patients having impaired renal function at liver transplant due to MELD, accurate predictors of posttransplant native renal recovery are needed to select candidates for simultaneous liver-kidney transplantation (SLK). Current UNOS guidelines rely on specific clinical criteria for SLK allocation. To examine these guidelines and other variables predicting nonrecovery, we analyzed 155 SLK recipients, focusing on a subset (n = 78) that had post-SLK native GFR (nGFR) determined by radionuclide renal scans. The 77 patients not having renal scans received a higher number of extended criteria donor organs and had worse posttransplant survival. Of the 78 renal scan patients, 31 met and 47 did not meet pre-SLK UNOS criteria. The UNOS criteria were more predictive than our institutional criteria for all nGFR recovery thresholds (20-40 mL/min), although at the most conservative cut-off (nGFR ≤ 20) it had low sensitivity (55.3%), specificity (75%), PPV (67.6%) and NPV (63.8%) for predicting post-SLK nonrecovery. On multivariate analysis, the only predictor of native renal nonrecovery (nGFR ≤ 20) was abnormal pre-SLK renal imaging (OR 3.85, CI 1.22-12.5). Our data support the need to refine SLK selection utilizing more definitive biomarkers and predictors of native renal recovery than current clinical criteria.

Hematopoietic stem cell gene therapy for the multisystemic lysosomal storage disorder cystinosis

Cystinosis is an autosomal recessive metabolic disease that belongs to the family of lysosomal storage disorders (LSDs). The defective gene is CTNS encoding the lysosomal cystine transporter, cystinosin. Cystine accumulates in all tissues and leads to organ damage including end-stage renal disease. Using the Ctns(-/-) murine model for cystinosis, we tested the use of hematopoietic stem and progenitor cells (HSPC) genetically modified to express a functional CTNS transgene using a self-inactivating-lentiviral vector (SIN-LV). We showed that transduced cells were capable of decreasing cystine content in all tissues and improved kidney function. Transduced HSPC retained their differentiative capabilities, populating all tissue compartments examined and allowing long-term expression of the transgene. Direct correlation between the levels of lentiviral DNA present in the peripheral blood and the levels present in tissues were demonstrated, which could be useful to follow future patients. Using a new model of cystinosis, the DsRed Ctns(-/-) mice, and a LV driving the expression of the fusion protein cystinosin-enhanced green fluorescent protein (eGFP), we showed that cystinosin was transferred from CTNS-expressing cells to Ctns-deficient adjacent cells in vitro and in vivo. This transfer led to cystine decreases in Ctns-deficient cells in vitro. These data suggest that the mechanism of cross-correction is possible in cystinosis.

Comparison of the convergent receptor utilization of a retargeted feline leukemia virus envelope with a naturally-occurring porcine endogenous retrovirus A

In vitro screening of randomized FeLV Envelope libraries identified the CP isolate, which enters cells through HuPAR-1, one of two human receptors utilized by porcine endogenous retrovirus-A (PERV-A), a distantly related gammaretrovirus. The CP and PERV-A Envs however, share little amino acid homology. Their receptor utilization was examined to define the common receptor usage of these disparate viral Envs. We demonstrate that the receptor usage of CP extends to HuPAR-2 but not to the porcine receptor PoPAR, the cognate receptor for PERV-A. Reciprocal interference between virus expressing CP and PERV-A Envs was observed on human cells. Amino acid residues localized to within the putative second extracellular loop (ECL-2) of PAR-1 and PAR-2 are found to be critical for CP envelope function. Through a panel of receptor chimeras and point mutations, this area was also found to be responsible for the differential usage of the PoPAR receptor between CP and PERV-A.

Why are some amyloidoses systemic? Does hepatic "chaperoning at a distance" prevent cardiac deposition in a transgenic model of human senile systemic (transthyretin) amyloidosis?

In the human systemic amyloidoses caused by mutant or wild-type transthyretin (TTR), deposition occurs at a distance from the site of synthesis. The TTR synthesized and secreted by the hepatocyte circulates in plasma, then deposits in target tissues far from the producing cell, a pattern reproduced in mice transgenic for multiple copies of the human wild-type TTR gene. By 2 yr of age, half of the transgenic males show cardiac deposition resembling human senile systemic amyloidosis. However, as early as 3 mo of age, when there are no deposits, cardiac gene transcription differs from that of nontransgenic littermates, primarily in the expression of a large number of genes associated with inflammation and the immune response. At 24 mo, the hearts with histologically proven TTR deposits show expression of stress response genes, exuberant mitochondrial gene transcription, and increased expression of genes associated with apoptosis, relative to the hearts without TTR deposition. These 24-mo-old hearts with TTR deposits also show a decrease in transcription of inflammatory genes relative to that in the younger transgenic mice. After 2 yr of expressing large amounts of human TTR, the livers of the transgenic mice without cardiac deposition display chaperone gene expression and evidence of an activated unfolded protein response, while the livers of animals with cardiac TTR deposition display neither, showing increased transcription of interferon-responsive inflammatory genes and those encoding an antioxidant response. With time, in animals with cardiac deposition, it appears that hepatic proteostatic capacity is diminished, exposing the heart to a greater load of misfolded TTR with subsequent extracellular deposition. Hence systemic (cardiac) TTR deposition may be the direct result of the diminution in the distant chaperoning capacity of the liver related to age or long-standing exposure to misfolded TTR, or both.

Quantitative bias in Illumina TruSeq and a novel post amplification barcoding strategy for multiplexed DNA and small RNA deep sequencing

Here we demonstrate a method for unbiased multiplexed deep sequencing of RNA and DNA libraries using a novel, efficient and adaptable barcoding strategy called Post Amplification Ligation-Mediated (PALM). PALM barcoding is performed as the very last step of library preparation, eliminating a potential barcode-induced bias and allowing the flexibility to synthesize as many barcodes as needed. We sequenced PALM barcoded micro RNA (miRNA) and DNA reference samples and evaluated the quantitative barcode-induced bias in comparison to the same reference samples prepared using the Illumina TruSeq barcoding strategy. The Illumina TruSeq small RNA strategy introduces the barcode during the PCR step using differentially barcoded primers, while the TruSeq DNA strategy introduces the barcode before the PCR step by ligation of differentially barcoded adaptors. Results show virtually no bias between the differentially barcoded miRNA and DNA samples, both for the PALM and the TruSeq sample preparation methods. We also multiplexed miRNA reference samples using a pre-PCR barcode ligation. This barcoding strategy results in significant bias.

Clinical and plasma proteomic markers correlating with chronic kidney disease after liver transplantation

Chronic kidney disease (CKD) occurs frequently after liver transplantation (LT) and is associated with significant morbidity and mortality. Thus, there is a pressing need to identify characteristics and biomarkers diagnostic of CKD to enable early diagnosis allowing preemptive interventions, as well as mechanistic insights into the progression from kidney injury to irreversible kidney failure. We analyzed 342 patients who had baseline glomerular filteration rate (GFR) >60 at the time of LT and are now >3 years post-LT. Risk factors for post-LT CKD were compared between three different groups defined by current GFR: >90 (n = 40), 60-90 (n = 146) and <60 (n = 156) mL/min. Age, cyclosporine use and pre-LT GFR were independently associated with new onset CKD. A subset (n = 64) without viral/immune disease or graft dysfunction underwent multianalyte plasma proteomic evaluations for correlation with CKD. Plasma proteomic analysis of two independent cohorts, test (n = 22) and validation (n = 42), identified 10 proteins highly associated with new onset CKD. In conclusion, we have identified clinical characteristics and a unique plasma proteomic signature correlating with new onset CKD after LT. These preliminary results are currently being validated in a prospective, multicenter study to determine if this signature precedes the onset of CKD and resolves with early interventions aimed at preserving kidney function.

Strategies for aggregating gene expression data: the collapseRows R function

Background

Genomic and other high dimensional analyses often require one to summarize multiple related variables by a single representative. This task is also variously referred to as collapsing, combining, reducing, or aggregating variables. Examples include summarizing several probe measurements corresponding to a single gene, representing the expression profiles of a co-expression module by a single expression profile, and aggregating cell-type marker information to de-convolute expression data. Several standard statistical summary techniques can be used, but network methods also provide useful alternative methods to find representatives. Currently few collapsing functions are developed and widely applied.

Results

We introduce the R function collapseRows that implements several collapsing methods and evaluate its performance in three applications. First, we study a crucial step of the meta-analysis of microarray data: the merging of independent gene expression data sets, which may have been measured on different platforms. Toward this end, we collapse multiple microarray probes for a single gene and then merge the data by gene identifier. We find that choosing the probe with the highest average expression leads to best between-study consistency. Second, we study methods for summarizing the gene expression profiles of a co-expression module. Several gene co-expression network analysis applications show that the optimal collapsing strategy depends on the analysis goal. Third, we study aggregating the information of cell type marker genes when the aim is to predict the abundance of cell types in a tissue sample based on gene expression data ("expression deconvolution"). We apply different collapsing methods to predict cell type abundances in peripheral human blood and in mixtures of blood cell lines. Interestingly, the most accurate prediction method involves choosing the most highly connected "hub" marker gene. Finally, to facilitate biological interpretation of collapsed gene lists, we introduce the function userListEnrichment, which assesses the enrichment of gene lists for known brain and blood cell type markers, and for other published biological pathways.

Conclusions

The R function collapseRows implements several standard and network-based collapsing methods. In various genomic applications we provide evidence that both types of methods are robust and biologically relevant tools.

MicroRNA regulation of molecular networks mapped by global microRNA, mRNA, and protein expression in activated T lymphocytes

MicroRNAs (miRNAs) regulate specific immune mechanisms, but their genome-wide regulation of T lymphocyte activation is largely unknown. We performed a multidimensional functional genomics analysis to integrate genome-wide differential mRNA, miRNA, and protein expression as a function of human T lymphocyte activation and time. We surveyed expression of 420 human miRNAs in parallel with genome-wide mRNA expression. We identified a unique signature of 71 differentially expressed miRNAs, 57 of which were previously not known as regulators of immune activation. The majority of miRNAs are upregulated, mRNA expression of these target genes is downregulated, and this is a function of binding multiple miRNAs (combinatorial targeting). Our data reveal that consideration of this complex signature, rather than single miRNAs, is necessary to construct a full picture of miRNA-mediated regulation. Molecular network mapping of miRNA targets revealed the regulation of activation-induced immune signaling. In contrast, pathways populated by genes that are not miRNA targets are enriched for metabolism and biosynthesis. Finally, we specifically validated miR-155 (known) and miR-221 (novel in T lymphocytes) using locked nucleic acid inhibitors. Inhibition of these two highly upregulated miRNAs in CD4(+) T cells was shown to increase proliferation by removing suppression of four target genes linked to proliferation and survival. Thus, multiple lines of evidence link top functional networks directly to T lymphocyte immunity, underlining the value of mapping global gene, protein, and miRNA expression.