Search

The signaling molecule stimulator of IFN genes (STING) was identified as a crucial regulator of the DNA-sensing cyclic GMP-AMP synthase (cGAS)-STING pathway, and this signaling pathway regulates inflammation and energy homeostasis under conditions of obesity, kidney fibrosis, and AKI. However, the role of STING in causing CKD, including diabetic kidney disease (DKD) and Alport syndrome, is unknown.To investigate whether STING activation contributes to the development and progression of glomerular diseases such as DKD and Alport syndrome, immortalized human and murine podocytes were differentiated for 14 days and treated with a STING-specific agonist. We used diabeticThe activation of the STING pathway acts as a mediator of disease progression in DKD and Alport syndrome. Targeting STING may offer a therapeutic option to treat glomerular diseases of metabolic and nonmetabolic origin or prevent their development, progression, or both.

Introduction: Individuals with focal segmental glomerular sclerosis (FSGS) typically undergo kidney biopsy only once, which limits the ability to characterize kidney cell gene expression over time. Methods: We used single-cell RNA sequencing (scRNA-seq) to explore disease-related molecular signatures in urine cells from subjects with FSGS. We collected 17 urine samples from 12 FSGS subjects and captured these as 23 urine cell samples. The inflammatory signatures from renal epithelial and immune cells were evaluated in bulk gene expression data sets of FSGS and minimal change disease (MCD) (The Nephrotic Syndrome Study Network [NEPTUNE] study) and an immune single-cell data set from lupus nephritis (Accelerating Medicines Partnership). Results: We identified immune cells, predominantly monocytes, and renal epithelial cells in the urine. Further analysis revealed 2 monocyte subtypes consistent with M1 and M2 monocytes. Shed podocytes in the urine had high expression of marker genes for epithelial-to-mesenchymal transition (EMT). We selected the 16 most highly expressed genes from urine immune cells and 10 most highly expressed EMT genes from urine podocytes as immune signatures and EMT signatures, respectively. Using kidney biopsy transcriptomic data from NEPTUNE, we found that urine cell immune signature and EMT signature genes were more highly expressed in FSGS biopsies compared with MCD biopsies. Conclusion: The identification of monocyte subsets and podocyte expression signatures in the urine samples of subjects with FSGS suggests that urine cell profiling might serve as a diagnostic and prognostic tool in nephrotic syndrome. Furthermore, this approach may aid in the development of novel biomarkers and identifying personalized therapies targeting particular molecular pathways in immune cells and podocytes.

Kidney fibrosis constitutes the shared final pathway of nearly all chronic nephropathies, but biomarkers for the non-invasive assessment of kidney fibrosis are currently not available. To address this, we characterize five candidate biomarkers of kidney fibrosis: Cadherin-11 (CDH11), Sparc-related modular calcium binding protein-2 (SMOC2), Pigment epithelium-derived factor (PEDF), Matrix-Gla protein, and Thrombospondin-2. Gene expression profiles in single-cell and single-nucleus RNA-sequencing (sc/snRNA-seq) datasets from rodent models of fibrosis and human chronic kidney disease (CKD) were explored, and Luminex-based assays for each biomarker were developed. Plasma and urine biomarker levels were measured using independent prospective cohorts of CKD: the Boston Kidney Biopsy Cohort, a cohort of individuals with biopsy-confirmed semiquantitative assessment of kidney fibrosis, and the Seattle Kidney Study, a cohort of patients with common forms of CKD. Ordinal logistic regression and Cox proportional hazards regression models were used to test associations of biomarkers with interstitial fibrosis and tubular atrophy and progression to end-stage kidney disease and death, respectively. Sc/snRNA-seq data confirmed cell-specific expression of biomarker genes in fibroblasts. After multivariable adjustment, higher levels of plasma CDH11, SMOC2, and PEDF and urinary CDH11 and PEDF were significantly associated with increasing severity of interstitial fibrosis and tubular atrophy in the Boston Kidney Biopsy Cohort. In both cohorts, higher levels of plasma and urinary SMOC2 and urinary CDH11 were independently associated with progression to end-stage kidney disease. Higher levels of urinary PEDF associated with end-stage kidney disease in the Seattle Kidney Study, with a similar signal in the Boston Kidney Biopsy Cohort, although the latter narrowly missed statistical significance. Thus, we identified CDH11, SMOC2, and PEDF as promising non-invasive biomarkers of kidney fibrosis.

Kidney organoids are a promising model to study kidney disease, but use is constrained by limited knowledge of their functional protein expression profile. We aimed to define the organoid proteome and transcriptome trajectories over culture duration and upon exposure to TNFα, a cytokine stressor. Older organoids increased deposition of extracellular matrix but decreased expression of glomerular proteins. Single cell transcriptome integration revealed that most proteome changes localized to podocytes, tubular and stromal cells. TNFα-treatment of organoids effected 320 differentially expressed proteins, including cytokines and complement components. Transcript expression of these 320 proteins was significantly higher in individuals with poorer clinical outcomes in proteinuric kidney disease. Key TNFα-associated protein (C3 and VCAM1) expression was increased in both human tubular and organoid kidney cell populations, highlighting the potential for organoids to advance biomarker development. By integrating kidney organoid omic layers, incorporating a disease-relevant cytokine stressor and comparing to human data, we provide crucial evidence of functional relevance of the kidney organoid model to human kidney disease.

Summary Codetta is a Python program for predicting the genetic code table of an organism from nucleotide sequences. Codetta can analyze an arbitrary nucleotide sequence and needs no sequence annotation or taxonomic placement. The most likely amino acid decoding for each of the 64 codons is inferred from alignments of profile hidden Markov models of conserved proteins to the input sequence. Availability and implementation Codetta 2.0 is implemented as a Python 3 program for MacOS and Linux and is available from http://eddylab.org/software/codetta/codetta2.tar.gz and at http://github.com/kshulgina/codetta. Supplementary information Supplementary data are available at Bioinformatics online.

The molecular mechanisms of SGLT2 inhibitors (SGLT2i) remain incompletely understood. Single-cell RNA sequencing and morphometrics data were collected from research kidney biopsies donated by participants with youth onset type 2 diabetes (T2D), aged 12-21 years of age, and healthy controls (HC) to study the effects of SGLT2i on kidney transcriptomics. Participants with T2D were more obese, had higher glomerular filtration rate, mesangial and glomerular volumes than HC. There were no clinically significant differences between participants prescribed SGLT2i (T2Di(+), n=10) and other T2D (T2Di(-), n=6). Transcriptional profiles showed SGLT2 expression exclusively in the proximal tubular (PT) cluster. Transcriptional alterations in T2Di(+) compared to T2Di(-) were seen across most nephron segments, most prominently in the distal nephron. SGLT2i treatment was associated with suppression of genes in the glycolysis, gluconeogenesis, tricarboxylic acid cycle pathways in PT, but enhanced expression in thick ascending limb. The energy sensitive mTOR signaling pathway transcripts were suppressed towards HC level in all nephron segments in T2Di(+). These transcriptional changes were confirmed in a diabetes mouse model treated with SGLT2i. Therefore, the beneficial effects of SGLT2i treatment to the kidneys might be from mitigating diabetes-induced metabolic perturbations via suppression of mTORC1 signaling across nephron segments, including those not expressing SGLT2.

COVID-19 morbidity and mortality are increased in patients with diabetes and kidney disease via unknown mechanisms. SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2) for entry into host cells. Since ACE2 is a susceptibility factor for infection, we investigated how diabetic kidney disease and medications alter ACE2 receptor expression in kidneys. Single cell RNA profiling of healthy living donor and kidney biopsies from patients with diabetic kidney disease revealed ACE2 expression primarily in proximal tubular epithelial cells. This cell specific localization was confirmed by in situ hybridization. ACE2 expression levels were unaltered by exposures to renin angiotensin aldosterone system inhibitors in diabetic kidney disease. Bayesian integrative analysis of a large compendium of public-omics datasets identified molecular network modules induced in ACE2-expressing proximal tubular epithelial cells in diabetic kidney disease (searchable at hb.flatironinstitute.org/covid-kidney) that were linked to viral entry, immune activation, endomembrane reorganization, and RNA processing. The diabetic kidney disease ACE2-positive proximal tubular epithelial cell module overlapped with expression patterns seen in SARS-CoV-2 infected cells. Similar cellular programs were seen in ACE2-positive proximal tubular epithelial cells obtained from urine samples of 13hospitalized patients with COVID-19, suggesting a consistent ACE2-coregulated proximal tubular epithelial cell expression program that may interact with the SARS-CoV-2 infection processes. Thus SARS-CoV-2 receptor networks can seed further research into risk stratification and therapeutic strategies for COVID-19 related kidney damage., Graphical abstract

Chronic kidney diseases (CKDs) are currently classified according to their clinical features, associated comorbidities and pattern of injury on biopsy. Even within a given classification, considerable variation exists in disease presentation, progression and response to therapy, highlighting heterogeneity in the underlying biological mechanisms. As a result, patients and clinicians experience uncertainty when considering optimal treatment approaches and risk projection. Technological advances now enable large-scale datasets, including DNA and RNA sequence data, proteomics and metabolomics data, to be captured from individuals and groups of patients along the genotype–phenotype continuum of CKD. The ability to combine these high-dimensional datasets, in which the number of variables exceeds the number of clinical outcome observations, using computational approaches such as machine learning, provides an opportunity to re-classify patients into molecularly defined subgroups that better reflect underlying disease mechanisms. Patients with CKD are uniquely poised to benefit from these integrative, multi-omics approaches since the kidney biopsy, blood and urine samples used to generate these different types of molecular data are frequently obtained during routine clinical care. The ultimate goal of developing an integrated molecular classification is to improve diagnostic classification, risk stratification and assignment of molecular, disease-specific therapies to improve the care of patients with CKD. Classification of kidney diseases according to their molecular mechanisms has potential to improve patient outcomes through the identification of targeted therapeutic approaches. This Review provides an overview of the ways in which omics and other data types can be integrated to enhance our understanding of the mechanisms underlying kidney function and failure.

The diagnosis of nephrotic syndrome relies on clinical presentation and descriptive patterns of injury on kidney biopsies, but not specific to underlying pathobiology. Consequently, there are variable rates of progression and response to therapy within diagnoses. Here, an unbiased transcriptomic-driven approach was used to identify molecular pathways which are shared by subgroups of patients with either minimal change disease (MCD) or focal segmental glomerulosclerosis (FSGS). Kidney tissue transcriptomic profile-based clustering identified three patient subgroups with shared molecular signatures across independent, North American, European, and African cohorts. One subgroup had significantly greater disease progression (Hazard Ratio 5.2) which persisted after adjusting for diagnosis and clinical measures (Hazard Ratio 3.8). Inclusion in this subgroup was retained even when clustering was limited to those with less than 25% interstitial fibrosis. The molecular profile of this subgroup was largely consistent with tumor necrosis factor (TNF) pathway activation. Two TNF pathway urine markers were identified, tissue inhibitor of metalloproteinases-1 (TIMP-1) and monocyte chemoattractant protein-1 (MCP-1), that could be used to predict an individual's TNF pathway activation score. Kidney organoids and single nucleus RNA-sequencing of participant kidney biopsies, validated TNF-dependent increases in pathway activation score, transcript and protein levels of TIMP-1 and MCP-1, in resident kidney cells. Thus, molecular profiling identified a subgroup of patients with either MCD or FSGS who shared kidney TNF pathway activation and poor outcomes. A clinical trial testing targeted therapies in patients selected using urinary markers of TNF pathway activation is ongoing.

Introduction Childhood-onset nephrotic syndrome has a variable clinical course. Improved predictive markers of long-term outcomes in children with nephrotic syndrome are needed. This study tests the association between baseline urinary epidermal growth factor (uEGF) excretion and longitudinal kidney function in children with nephrotic syndrome. Methods The study evaluated 191 participants younger than 18 years enrolled in the Nephrotic Syndrome Study Network, including 118 with their first clinically indicated kidney biopsy (68 minimal change disease; 50 focal segmental glomerulosclerosis) and 73 with incident nephrotic syndrome without a biopsy. uEGF was measured at baseline for all participants and normalized by the urine creatinine (Cr) concentration. Renal epidermal growth factor (EGF) mRNA was measured in the tubular compartment microdissected from kidney biopsy cores from a subset of patients. Linear mixed models were used to test if baseline uEGF/Cr and EGF mRNA expression were associated with change in estimated glomerular filtration rate (eGFR) over time. Results Higher uEGF/Cr at baseline was associated with slower eGFR decline during follow-up (median follow-up = 30 months). Halving of uEGF/Cr was associated with a decrease in eGFR slope of 2.0 ml/min per 1.73 m2 per year (P < 0.001) adjusted for age, race, diagnosis, baseline eGFR and proteinuria, and APOL1 genotype. In the biopsied subgroup, uEGF/Cr was correlated with EGF mRNA expression (r = 0.74; P < 0.001), but uEGF/Cr was retained over mRNA expression as the stronger predictor of eGFR slope after multivariable adjustment (decrease in eGFR slope of 1.7 ml/min per 1.73 m2 per year per log2 decrease in uEGF/Cr; P < 0.001). Conclusion uEGF/Cr may be a useful noninvasive biomarker that can assist in predicting the long-term course of kidney function in children with incident nephrotic syndrome., Graphical abstract

An understanding of the ethical underpinnings of human subjects research that involves some risk to participants without anticipated direct clinical benefit-such as the kidney biopsy procedure as part of the Kidney Precision Medicine Project (KPMP)-requires a critical examination of the risks as well as the diverse set of countervailing potential benefits to participants. This kind of deliberation has been foundational to the development and conduct of the KPMP. Herein, we use illustrative features of this research paradigm to develop a more comprehensive conceptualization of the types of benefits that may be important to research participants, including respecting pluralistic values, supporting the opportunity to act altruistically, and enhancing benefits to a participant's community. This approach may serve as a model to help researchers, ethicists, and regulators to identify opportunities to better respect and support participants in future research that entails some risk to these participants as well as to improve the quality of research for people with kidney disease.

Cutaneous lupus erythematosus (CLE) is a chronic inflammatory skin disease characterized by a diverse cadre of clinical presentations. CLE commonly occurs in patients with systemic lupus erythematosus (SLE), and CLE can also develop in the absence of systemic disease. Although CLE is a complex and heterogeneous disease, several studies have identified common signaling pathways, including those of type I interferons (IFNs), that play a key role in driving cutaneous inflammation across all CLE subsets. However, discriminating factors that drive different phenotypes of skin lesions remain to be determined. Thus, we sought to understand the skin-associated cellular and transcriptional differences in CLE subsets and how the different types of cutaneous inflammation relate to the presence of systemic lupus disease. In this study, we utilized two distinct cohorts comprising a total of 150 CLE lesional biopsies to compare discoid lupus erythematosus (DLE), subacute cutaneous lupus erythematosus (SCLE), and acute cutaneous lupus erythematosus (ACLE) in patients with and without associated SLE. Using an unbiased approach, we demonstrated a CLE subtype-dependent gradient of B cell enrichment in the skin, with DLE lesions harboring a more dominant skin B cell transcriptional signature and enrichment of B cells on immunostaining compared to ACLE and SCLE. Additionally, we observed a significant increase in B cell signatures in the lesional skin from patients with isolated CLE compared with similar lesions from patients with systemic lupus. This trend was driven primarily by differences in the DLE subgroup. Our work thus shows that skin-associated B cell responses distinguish CLE subtypes in patients with and without associated SLE, suggesting that B cell function in skin may be an important link between cutaneous lupus and systemic disease activity.

The current classification system for focal segmental glomerulosclerosis (FSGS) and minimal change disease (MCD) does not fully capture the complex structural changes in kidney biopsies, nor the clinical and molecular heterogeneity of these diseases. The Nephrotic Syndrome Study Network (NEPTUNE) Digital Pathology Scoring System (NDPSS) was applied to 221 NEPTUNE FSGS/MCD digital kidney biopsies for glomerular scoring using 37 descriptors. The descriptor-based glomerular profiles were used to cluster patients with similar morphologic characteristics. Glomerular descriptors and patient clusters were assessed for association with time to proteinuria remission and disease progression by using adjusted Cox models, and eGFR measures over time by using linear mixed models. Messenger RNA from glomerular tissue was used to assess differentially expressed genes (DEG) between clusters and identify genes associated with individual descriptors driving cluster membership. Three clusters were identified: X (N=56), Y (N=68), and Z (N=97). Clusters Y and Z had higher probabilities of proteinuria remission (HR [95% CI]= 1.95 [0.99, 3.85] and 3.29 [1.52, 7.13], respectively), lower hazards of disease progression 0.22 [0.08, 0.57] and 0.11 [0.03, 0.45], respectively), and greater loss of eGFR over time compared with X. Cluster X had 1920 DEGs compared to Y+Z, which reflected activation of pathways of immune response and inflammation. Six individual descriptors driving the clusters individually correlated with clinical outcomes and gene expression. The NDPSS allows for characterization of FSGS/MCD patients into clinically and biologically relevant categories and uncovers histologic parameters associated with clinical outcomes and molecular signatures not included in current classification systems.TRANSLATIONAL STATEMENTFSGS and MCD are heterogeneous diseases that manifest with a variety of structural changes often not captured by conventional classification systems. This study shows that a detailed morphologic analysis and quantification of these changes allows for better representation of the structural abnormalities within each patient and for grouping patients with similar morphologic profiles into categories that are clinically and biologically relevant.

BackgroundClassification of nephrotic syndrome relies on clinical presentation and descriptive patterns of injury on kidney biopsies. This approach does not reflect underlying disease biology, limiting the ability to predict progression or treatment response.MethodsSystems biology approaches were used to categorize patients with minimal change disease (MCD) and focal segmental glomerulosclerosis (FSGS) based on kidney biopsy tissue transcriptomics across three cohorts and assessed association with clinical outcomes. Patient-level tissue pathway activation scores were generated using differential gene expression. Then, functional enrichment and non-invasive urine biomarker candidates were identified. Biomarkers were validated in kidney organoid models and single nucleus RNA-seq (snRNAseq) from kidney biopsies.ResultsTranscriptome-based categorization identified three subgroups of patients with shared molecular signatures across independent North American, European and African cohorts. One subgroup demonstrated worse longterm outcomes (HR 5.2, p = 0.001) which persisted after adjusting for diagnosis and clinical measures (HR 3.8, p = 0.035) at time of biopsy. This subgroup’s molecular profile was largely (48%) driven by tissue necrosis factor (TNF) activation and could be predicted based on levels of TNF pathway urinary biomarkers TIMP-1 and MCP-1 and clinical features (correlation 0.63, p ConclusionsMolecular profiling identified a patient subgroup within nephrotic syndrome with poor outcome and kidney TNF pathway activation. Clinical trials using non-invasive biomarkers of pathway activation to target therapies are currently being evaluated.Significance StatementMechanistic, targeted therapies are urgently needed for patients with nephrotic syndrome. The inability to target an individual’s specific disease mechanism using currently used diagnostic parameters leads to potential treatment failure and toxicity risk. Patients with focal segmental glomerulosclerosis (FSGS) and minimal change disease (MCD) were grouped by kidney tissue transcriptional profiles and a subgroup associated with poor outcomes defined. The segregation of the poor outcome group was driven by tumor necrosis factor (TNF) pathway activation and could be identified by urine biomarkers, MCP1 and TIMP1. Based on these findings, clinical trials utilizing non-invasive biomarkers of pathway activation to target therapies, improve response rates and facilitate personalized treatment in nephrotic syndrome have been initiated.

Understanding kidney disease relies upon defining the complexity of cell types and states, their associated molecular profiles, and interactions within tissue neighborhoods. We have applied multiple single-cell or -nucleus assays (>400,000 nuclei/cells) and spatial imaging technologies to a broad spectrum of healthy reference (n = 42) and disease (n = 42) kidneys. This has provided a high resolution cellular atlas of 100 cell types that include rare and novel cell populations. The multi-omic approach provides detailed transcriptomic profiles, epigenomic regulatory factors, and spatial localizations for major cell types spanning the entire kidney. We further identify and define cellular states altered in kidney injury, encompassing cycling, adaptive or maladaptive repair, transitioning and degenerative states affecting several segments. Molecular signatures of these states permitted their localization within injury neighborhoods using spatial transcriptomics, and large-scale 3D imaging analysis of ∼1.2 million neighborhoods provided linkages to active immune responses. These analyses further defined biological pathways relevant to injury niches, including signatures underlying the transition from reference to predicted maladaptive states that were associated with a decline in kidney function during chronic kidney disease. This human kidney cell atlas, including injury cell states and neighborhoods, will be a valuable resource for future studies.

Rationale & Objective The current classification system for focal segmental glomerulosclerosis (FSGS) and minimal change disease (MCD) does not fully capture the complex structural changes in kidney biopsies, nor the clinical and molecular heterogeneity of these diseases. Study Design Prospective observational cohort study. Setting & Participants N=221 MCD and FSGS patients enrolled in the Nephrotic Syndrome Study Network (NEPTUNE). Exposures The NEPTUNE Digital Pathology Scoring System (NDPSS) was applied to generate scores for 37 glomerular descriptors. Outcomes Time from biopsy to complete proteinuria remission, time from biopsy to kidney disease progression (40% eGFR decline or kidney failure), and eGFR over time. Analytical Approach Cluster analysis was used to group patients with similar morphologic characteristics. Glomerular descriptors and patient clusters were assessed for associations with outcomes using adjusted Cox models and linear mixed models. Messenger RNA from glomerular tissue was used to assess differentially expressed genes between clusters and identify genes associated with individual descriptors driving cluster membership. Results Three clusters were identified: X (N=56), Y (N=68), and Z (N=97). Clusters Y and Z had higher probabilities of proteinuria remission (HR [95% CI]= 1.95 [0.99, 3.85] and 3.29 [1.52, 7.13], respectively), lower hazards of disease progression 0.22 [0.08, 0.57] and 0.11 [0.03, 0.45], respectively), and lower loss of eGFR over time compared with X. Cluster X had 1920 differentially expressed genes compared to Y+Z, which reflected activation of pathways of immune response and inflammation. Six descriptors driving the clusters individually correlated with clinical outcomes and gene expression. Limitations Low prevalence of some descriptors and biopsy at a single time point. Conclusions The NDPSS allows for categorization of FSGS/MCD patients into clinically and biologically relevant subgroups, and uncovers histologic parameters associated with clinical outcomes and molecular signatures not included in current classification systems.

Introductions: Kidney injury molecule-1 (KIM-1) and periostin (POSTN) are proximal and distal tubule injury biomarkers. We tested whether baseline urine KIM-1/Cr (uKIM-1/Cr) and/or uPOSTN/Cr correlated with disease severity or improved a remission prediction model. Methods: Baseline uKIM-1/Cr and uPOSTN/Cr were measured on spot urine samples from immunosuppression-free patients enrolled in Nephrotic Syndrome Study Network until December 15, 2014. Urine protein/Cr (UPCR) and albumin/Cr (UACR) were measured at baseline, 4 months, and until last follow-up. Glomerular and tubulointerstitial (TI) expression arrays were analyzed from a baseline research renal biopsy core collected during a clinically indicated biopsy. Renal diagnoses were centrally confirmed, sections scanned, and measured morphometrically. Correlations between baseline uKIM-1/Cr and uPOSTN/Cr and UPCR, UACR, histopathologic features, glomerular and TI KIM-1 and POSTN expression levels, and renal outcomes were assessed. Results: Baseline uKIM-1/cr correlated with UPCR and UACR and were associated with complete remission (CR) after adjustment for proteinuria, histopathologic diagnosis, and treatment. Baseline uKIM-1/Cr also correlated with degree of foot process effacement and acute tubular injury. Glomerular and TI KIM-1 expression levels correlated with UPCR and UACR. Higher TI KIM-1 expression levels correlated with interstitial fibrosis, tubular atrophy, and global glomerulosclerosis, while glomerular KIM-1 expression correlated with time to remission. Findings for POSTN were of lesser statistical strength. Discussion/Conclusion: Lower baseline uKIM-1/Cr values were associated with more rapid time to CR after adjusting for proteinuria, histopathologic diagnosis, and treatment. Increased TI KIM-1 expression levels in proteinuric states were associated with chronic morphological injury; lower glomerular expression levels were associated with a greater potential for proteinuria reversibility.

Chronic kidney disease (CKD) and acute kidney injury (AKI) are common, heterogeneous, and morbid diseases. Mechanistic characterization of CKD and AKI in patients may facilitate a precision medicine approach to prevention, diagnosis, and treatment. The Kidney Precision Medicine Project aims to ethically and safely obtain kidney biopsies from participants with CKD or AKI, create a reference kidney atlas, and characterize disease subgroups to stratify patients based on molecular features of disease, clinical characteristics, and associated outcomes. An additional aim is to identify critical cells, pathways, and targets for novel therapies and preventive strategies. This project is a multicenter prospective cohort study of adults with CKD or AKI who undergo a protocol kidney biopsy for research purposes. This investigation focuses on kidney diseases that are most prevalent and therefore substantially burden the public health, including CKD attributed to diabetes or hypertension and AKI attributed to ischemic and toxic injuries. Reference kidney tissues (for example, living kidney donor biopsies) will also be evaluated. Traditional and digital pathology will be combined with transcriptomic, proteomic, and metabolomics analysis of the kidney tissue as well as deep clinical phenotyping for supervised and unsupervised subgroup analysis and systems biology analysis. Participants will be followed prospectively for ten years to ascertain clinical outcomes. Cell types, locations, and functions will be characterized in health and disease in an open, searchable, online kidney tissue atlas. All data from the Kidney Precision Medicine Project will be made readily available for broad use by scientists, clinicians, and patients.

The diagnosis of focal segmental glomerulosclerosis (FSGS) requires a renal biopsy, which is invasive and can be problematic in children and in some adults. We used single cell RNA-sequencing to explore disease-related cellular signatures in 23 urine samples from 12 FSGS subjects. We identified immune cells, predominantly monocytes, and renal epithelial cells, including podocytes. Analysis revealed M1 and M2 monocyte subsets, and podocytes showing high expression of genes for epithelial-to-mesenchymal transition (EMT). We confirmed M1 and M2 gene signatures using published monocyte/macrophage data from lupus nephritis and cancer. Using renal transcriptomic data from the Nephrotic Syndrome Study Network (NEPTUNE), we found that urine cell immune and EMT signature genes showed higher expression in FSGS biopsies compared to minimal change disease biopsies. These results suggest that urine cell profiling may serve as a diagnostic and prognostic tool in nephrotic syndrome and aid in identifying novel biomarkers and developing personalized therapeutic strategies.

Since failed resolution of inflammation is a major contributor to the progression of diabetic nephropathy, identifying endogenously generated molecules that promote the physiological resolution of inflammation may be a promising therapeutic approach for this disease. Annexin A1 (ANXA1), as an endogenous mediator, plays an important role in resolving inflammation. Whether ANXA1 could affect established diabetic nephropathy through modulating inflammatory states remains largely unknown. In the current study, we found that in patients with diabetic nephropathy, the levels of ANXA1 were upregulated in kidneys, and correlated with kidney function as well as kidney outcomes. Therefore, the role of endogenous ANXA1 in mouse models of diabetic nephropathy was further evaluated. ANXA1 deficiency exacerbated kidney injuries, exhibiting more severe albuminuria, mesangial matrix expansion, tubulointerstitial lesions, kidney inflammation and fibrosis in high fat diet/streptozotocin-induced-diabetic mice. Consistently, ANXA1 overexpression ameliorated kidney injuries in mice with diabetic nephropathy. Additionally, we found Ac2-26 (an ANXA1 mimetic peptide) had therapeutic potential for alleviating kidney injuries in db/db mice and diabetic Anxa1 knockout mice. Mechanistic studies demonstrated that intracellular ANXA1 bound to the transcription factor NF-κB p65 subunit, inhibiting its activation thereby modulating the inflammatory state. Thus, our data indicate that ANXA1 may be a promising therapeutic approach to treating and reversing diabetic nephropathy.

BACKGROUND AND OBJECTIVES: IgA nephropathy is the most common primary glomerular disease in the world. Marked by mesangial inflammation and proliferation, it generally leads to progressive kidney fibrosis. As the Janus kinase signal transducer and activator of transcription pathway has been implicated as an important mediator of diabetic kidney disease and FSGS, detailed investigation of this pathway in IgA nephropathy was undertaken to establish the basis for targeting this pathway across glomerular diseases. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Well characterized patients with IgA nephropathy and controls were studied, allowing us to compare 77 patients with biopsy-proven IgA nephropathy with 45 healthy subjects. STAT phosphorylation was assessed in peripheral blood monocytes (PBMCs) by phosphoflow before and after cytokine stimulation. Kidney Janus kinase signal transducer and activator of transcription activity was studied by immunofluorescence and by transcriptomic studies. An STAT1 activity score was established using downstream transcriptional targets of pSTAT1 and associated with disease and clinical outcomes. RESULTS: We found PBMCs to have upregulated pSTAT production at baseline in patients with IgA nephropathy with a limited reserve to respond to cytokine stimulation compared with controls. Increased staining in glomerular mesangium and endothelium was seen for Jak-2 and pSTAT1 and in the tubulointerstitial for JAK2, pSTAT1, and pSTAT3. Activation of the Janus kinase signal transducer and activator of transcription pathway was further supported by increased pSTAT1 and pSTAT3 scores in glomerular and tubulointerstitial sections of the kidney (glomerular activation Z scores: 7.1 and 4.5, respectively; P values

To define cellular mechanisms underlying kidney function and failure, the KPMP analyzes biopsy tissue in a multicenter research network to build cell-level process maps of the kidney. This study aimed to establish a single cell RNA sequencing strategy to use cell-level transcriptional profiles from kidney biopsies in KPMP to define molecular subtypes in glomerular diseases. Using multiple sources of adult human kidney reference tissue samples, 22,268 single cell profiles passed KPMP quality control parameters. Unbiased clustering resulted in 31 distinct cell clusters that were linked to kidney and immune cell types using specific cell markers. Focusing on endothelial cell phenotypes, in silico and in situ hybridization methods assigned 3 discrete endothelial cell clusters to distinct renal vascular beds. Transcripts defining glomerular endothelial cells (GEC) were evaluated in biopsies from patients with 10 different glomerular diseases in the NEPTUNE and European Renal cDNA Bank (ERCB) cohort studies. Highest GEC scores were observed in patients with focal segmental glomerulosclerosis (FSGS). Molecular endothelial signatures suggested 2 distinct FSGS patient subgroups with α-2 macroglobulin (A2M) as a key downstream mediator of the endothelial cell phenotype. Finally, glomerular A2M transcript levels associated with lower proteinuria remission rates, linking endothelial function with long-term outcome in FSGS.

Mesangial matrix expansion is an important process in the initiation of chronic kidney disease, yet the genetic factors driving its development are unknown. Our previous studies have implicated Far2 as a candidate gene associated with differences in mesangial matrix expansion between mouse inbred strains. Consistent with the hypothesis that increased expression of Far2 leads to mesangial matrix expansion through increased production of platelet-activating factor precursors, we show that FAR2 is capable of mediating de novo platelet-activating factor synthesis in vitro and driven by the transcription factor NKX3.2. We demonstrate that knockdown of Far2 in mice delays the progression of mesangial matrix expansion with at least six months (equivalent to ~15 yr in human). Furthermore, we show that increased FAR2 expression in human patients is associated with diabetic nephropathy, lupus nephritis, and IgA nephropathy. Taken together, these results highlight FAR2’s role in the development of mesangial matrix expansion and chronic kidney disease.

Expression quantitative trait loci (eQTL) studies illuminate the genetics of gene expression and, in disease research, can be particularly illuminating when using the tissues directly impacted by the condition. In nephrology, there is a paucity of eQTL studies of human kidney. Here, we used whole-genome sequencing (WGS) and microdissected glomerular (GLOM) and tubulointerstitial (TI) transcriptomes from 187 individuals with nephrotic syndrome (NS) to describe the eQTL landscape in these functionally distinct kidney structures. Using MatrixEQTL, we performed cis-eQTL analysis on GLOM (n = 136) and TI (n = 166). We used the Bayesian “Deterministic Approximation of Posteriors” (DAP) to fine-map these signals, eQTLBMA to discover GLOM- or TI-specific eQTLs, and single-cell RNA-seq data of control kidney tissue to identify the cell type specificity of significant eQTLs. We integrated eQTL data with an IgA Nephropathy (IgAN) GWAS to perform a transcriptome-wide association study (TWAS). We discovered 894 GLOM eQTLs and 1,767 TI eQTLs at FDR < 0.05. 14% and 19% of GLOM and TI eQTLs, respectively, had >1 independent signal associated with its expression. 12% and 26% of eQTLs were GLOM specific and TI specific, respectively. GLOM eQTLs were most significantly enriched in podocyte transcripts and TI eQTLs in proximal tubules. The IgAN TWAS identified significant GLOM and TI genes, primarily at the HLA region. In this study, we discovered GLOM and TI eQTLs, identified those that were tissue specific, deconvoluted them into cell-specific signals, and used them to characterize known GWAS alleles. These data are available for browsing and download via our eQTL browser, “nephQTL.”

IntroductionThe current study aimed to investigate the association between urinary epidermal growth factor (uEGF) and renal disease severity and outcomes in patients with antineutrophil cytoplasmic antibody-associated vasculitis (AAV).MethodsIntrarenalEGFmRNA expression was extracted from transcriptomic data of microdissected tubulointerstitial compartments of kidney biopsies of patients with AAV. uEGF was measured in 173 patients with AAV in active stage and 143 in remission, and normalised to urine creatinine excretion (uEGF/Cr). The association between uEGF/Cr (orEGFmRNA) and clinical–pathological parameters was tested using linear regression analysis. The ability of uEGF/Cr to predict renal outcomes was analysed using Cox’s regression analysis.ResultsIn patients with AAV, intrarenalEGFmRNA expression was significantly associated with estimated glomerular filtration rate (eGFR)(log2) at time of biopsy (β=0.63, p2) at time of sampling in both active and remission stage (β=0.60, pConclusionLower uEGF/Cr levels are associated with more severe renal disease, renal resistance to treatment and higher risk of progression to composite outcome in patients with AAV.

Focal segmental glomerulosclerosis (FSGS) accounts for about 40% of all nephrotic syndrome cases in adults. The presence of several potential circulating factors has been suggested in patients with primary FSGS and particularly in patients with recurrent disease after transplant. Irrespectively of the nature of the circulating factors, this study was aimed at identifying early glomerular/podocyte-specific pathways that are activated by the sera of patients affected by FSGS. Kidney biopsies were obtained from patients undergoing kidney transplantation due to primary FSGS. Donor kidneys were biopsied pre-reperfusion (PreR) and a subset 1-2 hours after reperfusion of the kidney (PostR). Thirty-one post reperfusion (PostR) and 36 PreR biopsy samples were analyzed by microarray and gene enrichment KEGG pathway analysis. Data were compared to those obtained from patients with incident primary FSGS enrolled in other cohorts as well as with another cohort to correct for pathways activated by ischemia reperfusion. Using an ex-vivo cell-based assay in which human podocytes were cultured in the presence of sera from patients with recurrent and non recurrent FSGS, the molecular signature of podocytes exposed to sera from patients with REC was compared to the one established from patients with NON REC. We demonstrate that inflammatory pathways, including the TNF pathway, are primarily activated immediately after exposure to the sera of patients with primary FSGS, while phagocytotic pathways are activated when proteinuria becomes clinically evident. The TNF pathway activation by one or more circulating factors present in the sera of patients with FSGS supports prior experimental findings from our group demonstrating a causative role of local TNF in podocyte injury in FSGS. Correlation analysis with clinical and histological parameters of disease was performed and further supported a possible role for TNF pathway activation in FSGS. Additionally, we identified a unique set of genes that is specifically activated in podocytes when cultured in the presence of serum of patients with REC FSGS. This clinical translational study supports our prior experimental findings describing a potential role of the TNF pathway in the pathogenesis of FSGS. Validation of these findings in larger cohorts may lay the ground for the implementation of integrated system biology approaches to risk stratify patients affected by FSGS and to identify novel pathways relevant to podocyte injury.

Pharmacological Na+-glucose linked cotransporter (SGLT)2 inhibition is being examined as a renal protection strategy in nondiabetic chronic kidney disease. We quantified renal SGLT mRNA expression in healthy controls (HC), glomerulonephritis (GN), and diabetic kidney disease (DKD) to identify differences in expression across a spectrum of renal diseases. mRNA expression of SGLT1 and SGLT2 in renal tubules and glomeruli, obtained using microdissection and microarray techniques, was evaluated in two large cohorts. The European Renal cDNA bank included HC, GN, and DKD (98 glomeruli and 93 tubulointerstitium). The Nephrotic Syndrome Study Network cohort included 124 adults with membranous nephropathy, minimal change disease, focal segmental glomerulosclerosis, and IgA nephropathy. Within the European Renal cDNA bank, SGLT2 tubular and glomerular log2 mRNA expression significantly differed across HC, GN, and DKD ( P = 0.0009 and P = 0.0004), with the highest expression in HC. Within the Nephrotic Syndrome Study Network, there were no differences in SGLT log2 mRNA expression across GN subtypes. Tubular SGLT2 log2 mRNA expression positively correlated with estimated glomerular filtration rate (by the Modification of Diet in Renal Disease Study equation) and glycated hemoglobin ( r = 0.33 and 0.34, P < 0.05) and inversely correlated with interstitial fibrosis ( r = −0.21, P < 0.05). In conclusion, SGLT2 mRNA expression was lower in DKD compared with HC or GN and inversely related to interstitial fibrosis. The relationships between SGLT mRNA, protein expression, and transporter activity require further elucidation.

Background Understanding podocyte-specific responses to injury at a systems level is difficult because injury leads to podocyte loss or an increase of extracellular matrix, altering glomerular cellular composition. Finding a window into early podocyte injury might help identify molecular pathways involved in the podocyte stress response. Methods We developed an approach to apply proteome analysis to very small samples of purified podocyte fractions. To examine podocytes in early disease states in FSGS mouse models, we used podocyte fractions isolated from individual mice after chemical induction of glomerular disease (with Doxorubicin or LPS). We also applied single-glomerular proteome analysis to tissue from patients with FSGS. Results Transcriptome and proteome analysis of glomeruli from patients with FSGS revealed an underrepresentation of podocyte-specific genes and proteins in late-stage disease. Proteome analysis of purified podocyte fractions from FSGS mouse models showed an early stress response that includes perturbations of metabolic, mechanical, and proteostasis proteins. Additional analysis revealed a high correlation between the amount of proteinuria and expression levels of the mechanosensor protein Filamin-B. Increased expression of Filamin-B in podocytes in biopsy samples from patients with FSGS, in single glomeruli from proteinuric rats, and in podocytes undergoing mechanical stress suggests that this protein has a role in detrimental stress responses. In Drosophila, nephrocytes with reduced filamin homolog Cher displayed altered filtration capacity, but exhibited no change in slit diaphragm structure. Conclusions We identified conserved mechanisms of the podocyte stress response through ultrasensitive proteome analysis of human glomerular FSGS tissue and purified native mouse podocytes during early disease stages. This approach enables systematic comparisons of large-scale proteomics data and phenotype-to-protein correlation.

Studies suggest that altered renal lipid metabolism plays a role in the pathogenesis of diabetic kidney disease and that genetic or pharmacological induction of cholesterol efflux protects from the development of diabetic kidney disease and focal segmental glomerulosclerosis (FSGS). Here we tested whether altered lipid metabolism contributes to renal failure in the Col4a3 knockout mouse model for Alport Syndrome. There was an eight-fold increase in the cholesterol content in renal cortexes of mice with Alport Syndrome. This was associated with increased glomerular lipid droplets and cholesterol crystals. Treatment of mice with Alport Syndrome with hydroxypropyl-β-cyclodextrin (HPβCD) reduced cholesterol content in the kidneys of mice with Alport Syndrome and protected from the development of albuminuria, renal failure, inflammation and tubulointerstitial fibrosis. Cholesterol efflux and trafficking-related genes were primarily affected in mice with Alport Syndrome and were differentially regulated in the kidney cortex and isolated glomeruli. HPβCD also protected from proteinuria and mesangial expansion in a second model of non-metabolic kidney disease, adriamycin-induced nephropathy. Consistent with our experimental findings, microarray analysis confirmed dysregulation of several lipid-related genes in glomeruli isolated from kidney biopsies of patients with primary FSGS enrolled in the NEPTUNE study. Thus, lipid dysmetabolism occurs in non-metabolic glomerular disorders such as Alport Syndrome and FSGS, and HPβCD improves renal function in experimental Alport Syndrome and FSGS.

SummaryA tissue transcriptome driven classification of nephrotic syndrome patients identified a high risk group of patients with TNF activation and established a non-invasive marker panel for pathway activity assessment paving the way towards precision medicine trials in NS.AbstractNephrotic syndrome from primary glomerular diseases can lead to chronic kidney disease (CKD) and/or end-stage renal disease (ESRD). Conventional diagnoses using a combination of clinical presentation and descriptive biopsy information do not accurately predict risk for progression in patients with nephrotic syndrome, which complicates disease management. To address this challenge, a transcriptome-driven approach was used to classify patients with minimal change disease and focal segmental glomerulosclerosis in the Nephrotic Syndrome Study Network (NEPTUNE). Transcriptome-based classification revealed a group of patients at risk for disease progression. High risk patients had a transcriptome profile consistent with TNF activation. Non-invasive urine biomarkers TIMP1 and CCL2 (MCP1), which are causally downstream of TNF, accurately predicted TNF activation in the NEPTUNE cohort setting the stage for patient stratification approaches and precision medicine in kidney disease.

BackgroundGlomerular diseases of the kidney are presently differentiated, diagnosed and treated according to conventional clinical or structural features. While etiologically diverse, these diseases share common clinical features including but not limited to reduced glomerular filtration rate, increased serum creatinine and proteinuria suggesting shared pathogenic mechanisms across diseases. Renal biopsies from patients with nephrotic syndrome (NS) or ANCA-associated vasculitis (AAV) were evaluated for molecular signals cutting across conventional disease categories as candidates for therapeutic targets.MethodsRenal biopsies were obtained from patients with NS (minimal change disease, focal segmental glomerulosclerosis, or membranous nephropathy) (n=187) or AAV (granulomatosis with polyangiitis or microscopic polyangiitis) (n=80) from the Nephrotic Syndrome Study Network (NEPTUNE) and the European Renal cDNA Bank. Transcriptional profiles were assessed for shared disease mechanisms.ResultsIn the discovery cohort, 10–25% transcripts were differentially regulated versus healthy controls in both NS and AAV, >500 transcripts were shared across diseases. The majority of shared transcripts (60–77%) were validated in independent samples. Therapeutically targetable networks were identified, including inflammatory JAK-STAT signaling. STAT1 eQTLs were identified and STAT1 expression associated with GFR-based outcome. A transcriptional STAT1 activity score was generated from STAT1-regulated target genes which correlated with CXCL10 (pConclusionAAV and NS caused from histopathologically distinct disease categories share common intra-renal molecular pathways cutting across conventional disease classifications. This approach provides a starting point for de novo drug development, and repurposing efforts in rare kidney diseases.

Podocyte injury is central to many forms of kidney disease, but transcriptional signatures reflecting podocyte injury and compensation mechanisms are challenging to analyze in vivo. Human kidney organoids derived from pluripotent stem cells (PSCs), a potentially new model for disease and regeneration, present an opportunity to explore the transcriptional plasticity of podocytes. Here, transcriptional profiling of more than 12,000 single cells from human PSC-derived kidney organoid cultures was used to identify robust and reproducible cell lineage gene expression signatures shared with developing human kidneys based on trajectory analysis. Surprisingly, the gene expression signature characteristic of developing glomerular epithelial cells was also observed in glomerular tissue from a kidney disease cohort. This signature correlated with proteinuria and inverse eGFR, and it was confirmed in an independent podocytopathy cohort. Three genes in particular were further characterized as potentially novel components of the glomerular disease signature. We conclude that cells in human PSC-derived kidney organoids reliably recapitulate the developmental transcriptional program of podocytes and other cell lineages in the human kidney and that transcriptional profiles seen in developing podocytes are reactivated in glomerular disease. Our findings demonstrate an approach to identifying potentially novel molecular programs involved in the pathogenesis of glomerulopathies.

SUMMARYUnsupervised machine learning methods provide a promising means to analyze and interpret large datasets. However, most gene expression datasets generated by individual researchers remain too small to fully benefit from these methods. In the case of rare diseases, there may be too few cases available, even when multiple studies are combined. We trained a Pathway Level Information ExtractoR (PLIER) model using on a large public data compendium comprised of multiple experiments, tissues, and biological conditions. We then transferred the model to small rare disease datasets in an approach we term MultiPLIER. Models constructed from large, diverse public data i) included features that aligned well to important biological factors; ii) were more comprehensive than those constructed from individual datasets or conditions; iii) transferred to rare disease datasets where the models describe biological processes related to disease severity more effectively than models trained on specifically those datasets.

High levels of circulating TNF and its receptors, TNFR1 and TNFR2, predict the progression of diabetic kidney disease (DKD), but their contribution to organ damage in DKD remains largely unknown. Here, we investigated the function of local and systemic TNF in podocyte injury. We cultured human podocytes with sera collected from DKD patients, who displayed elevated TNF levels, and focal segmental glomerulosclerosis (FSGS) patients, whose TNF levels resembled those of healthy patients. Exogenous TNF administration or local TNF expression was equally sufficient to cause free cholesterol-dependent apoptosis in podocytes by acting through a dual mechanism that required a reduction in ATP-binding cassette transporter A1-mediated (ABCA1-mediated) cholesterol efflux and reduced cholesterol esterification by sterol-O-acyltransferase 1 (SOAT1). TNF-induced albuminuria was aggravated in mice with podocyte-specific ABCA1 deficiency and was partially prevented by cholesterol depletion with cyclodextrin. TNF-stimulated free cholesterol-dependent apoptosis in podocytes was mediated by nuclear factor of activated T cells 1 (NFATc1). ABCA1 overexpression or cholesterol depletion was sufficient to reduce albuminuria in mice with podocyte-specific NFATc1 activation. Our data implicate an NFATc1/ABCA1-dependent mechanism in which local TNF is sufficient to cause free cholesterol-dependent podocyte injury irrespective of TNF, TNFR1, or TNFR2 serum levels.

To characterise renal tissue metabolic pathway gene expression in different forms of glomerulonephritis.Patients with nephrotic syndrome (NS), antineutrophil cytoplasmic antibody-associated vasculitis (AAV), systemic lupus erythematosus (SLE) and healthy living donors (LD) were studied. Clinically indicated renal biopsies were obtained at time of diagnosis and microdissected into glomerular and tubulointerstitial compartments. Microarray-derived differential gene expression of 88 genes representing critical enzymes of metabolic pathways and 25 genes related to immune cell markers was compared between disease groups. Correlation analyses measured relationships between metabolic pathways, kidney function and cytokine production.Reduced steady state levels of mRNA species were enriched in pathways of oxidative phosphorylation and increased in the pentose phosphate pathway (PPP) with maximal perturbation in AAV and SLE followed by NS, and least in LD. Transcript regulation was isozymes specific with robust regulation in hexokinases, enolases and glucose transporters. Intercorrelation networks were observed between enzymes of the PPP (eg, transketolase) and macrophage markers (eg, CD68) (r=0.49, p0.01). Increased PPP transcript levels were associated with reduced glomerular filtration rate in the glomerular (r=-0.49, p0.01) and tubulointerstitial (r=-0.41, p0.01) compartments. PPP expression and tumour necrosis factor activation were tightly co-expressed (r=0.70, p0.01).This study demonstrated concordant alterations of the renal transcriptome consistent with metabolic reprogramming across different forms of glomerulonephritis. Activation of the PPP was tightly linked with intrarenal macrophage marker expression, reduced kidney function and increased production of cytokines. Modulation of glucose metabolism may offer novel immune-modulatory therapeutic approaches in rare kidney diseases.

Aberrant constitutive expression of NF-kappaB subunits, reported in more than 90% of breast cancers and multiple other malignancies, plays pivotal roles in tumorigenesis. Higher RelB subunit expression was demonstrated in estrogen receptor alpha (ERalpha)-negative breast cancers versus ERalpha-positive ones, due in part to repression of RelB synthesis by ERalpha signaling. Notably, RelB promoted a more invasive phenotype in ERalpha-negative cancers via induction of the BCL2 gene. We report here that RelB reciprocally inhibits ERalpha synthesis in breast cancer cells, which contributes to a more migratory phenotype. Specifically, RelB is shown for the first time to induce expression of the zinc finger repressor protein Blimp1 (B-lymphocyte-induced maturation protein), the critical mediator of B- and T-cell development, which is transcribed from the PRDM1 gene. Blimp1 protein repressed ERalpha (ESR1) gene transcription. Commensurately higher Blimp1/PRDM1 expression was detected in ERalpha-negative breast cancer cells and primary breast tumors. Induction of PRDM1 gene expression was mediated by interaction of Bcl-2, localized in the mitochondria, with Ras. Thus, the induction of Blimp1 represents a novel mechanism whereby the RelB NF-kappaB subunit mediates repression, specifically of ERalpha, thereby promoting a more migratory phenotype.

Mammalian hibernation combines a profound net metabolic rate suppression with the selective up-regulation of key genes whose protein products address specific metabolic needs of the hibernator. The signal transduction pathways and transcription factors involved in regulating hibernation-responsive gene expression are of great interest. The present study suggests an important role for the p38 mitogen-activated protein kinase (p38MAPK) and selected downstream transcription factors under its control (CREB, ATF-2, Elk-1) in the metabolic response by skeletal muscle during hibernation of little brown bats, Myotis lucifugus. Western blotting was used to quantify both total protein and levels of the phosphorylated, active forms of p38MAPK, CREB, ATF-2 and Elk-1 in both skeletal muscle and heart of euthermic and hibernating bats. The p38MAPK pathway was not apparently activated in heart during torpor but skeletal muscle showed strong increases (2.2–11-fold) in the amounts of phosphorylated p38T180/Y182, CREBS133, ATF-2T69/71 and Elk-1S383 in the torpid versus aroused state. By contrast both total and phosphorylated levels of Elk-1 in heart were reduced during hibernation to just 30% of the euthermic values. These data implicate p38MAPK and its transcription factor targets, CREB, ATF-2 and Elk-1 in skeletal muscle maintenance during hibernation. Copyright © 2007 John Wiley & Sons, Ltd.

Aberrant activation of nuclear factor-kappaB (NF-kappaB) transcription factors has been implicated in the pathogenesis of breast cancer. We previously showed elevated activity of IkappaB kinase alpha (IKKalpha), IKKbeta, and protein kinase CK2 in primary human breast cancer specimens and cultured cells. A novel inducible IKK protein termed IKK-i/IKKepsilon has been characterized as a potential NF-kappaB activator. Here, we provide evidence that implicates IKK-i/IKKepsilon in the pathogenesis of breast cancer. We show IKK-i/IKKepsilon expression in primary human breast cancer specimens and carcinogen-induced mouse mammary tumors. Multiple breast cancer cell lines showed higher levels of IKK-i/IKKepsilon and kinase activity compared with untransformed MCF-10F breast epithelial cells. Interestingly, IKK-i/IKKepsilon expression correlated with CK2alpha expression in mammary glands and breast tumors derived from MMTV-CK2alpha transgenic mice. Ectopic CK2 expression in untransformed cells led to increased IKK-i/IKKepsilon mRNA and protein levels. Inhibition of CK2alpha via the pharmacologic inhibitor apigenin or upon transfection of a CK2 kinase-inactive subunit reduced IKK-i/IKKepsilon levels. Expression of a kinase-inactive IKK-i/IKKepsilon mutant in breast cancer cells reduced NF-kappaB activity as judged by transfection assays of reporters driven either by NF-kappaB elements or the promoters of two NF-kappaB target genes, cyclin D1 and relB. Importantly, the kinase-inactive IKK-i/IKKepsilon mutant reduced the endogenous levels of these genes as well as the ability of breast cancer cells to grow in soft agar or form invasive colonies in Matrigel. Thus, CK2 induces functional IKK-i/IKKepsilon, which is an important mediator of the activation of NF-kappaB that plays a critical role in the pathogenesis of breast cancer.

Two-dimensional gel electrophoresis was used to assess differential protein expression between euthermic and hibernating states in heart of Myotis lucifugus . A hibernation-induced protein was identified by mass spectrometry as a thioredoxin peroxidase-like protein known as PAG. Western blotting confirmed up-regulation (>2-fold) and RT-PCR also revealed up-regulation (>5-fold) of pag mRNA. Cloning revealed a highly conserved sequence suggesting a conserved function for PAG. Oxidative stress markers, p-IκB-α (Ser 32) and p-HSP27 (Ser 78/82), were also up-regulated in heart and skeletal muscle during hibernation. Although there are selected increases in gene/protein expression during hibernation, general translation inhibition occurs as part of metabolic rate depression. This was confirmed by elevated levels of the inactive forms of the eIF2α (Ser 51) in both heart and skeletal muscle (2- to 5-fold higher than in euthermia) and the eEF2 (Thr 51) in skeletal muscle (a 15-fold increase). This study suggests that hibernators may use up-regulation of specific proteins to counteract oxidative stress.

The peroxisome proliferator-activated receptor (PPAR) family of transcription factors play a key role in lipid metabolism and have been implicated in a number of disease states, most notably of which is obesity. Controlled regulation of lipid metabolism is a key ingredient for successful hibernation. Partial cDNA sequences for one of the PPAR proteins, PPARgamma and the PPARgamma co-activator (PGC-1alpha) have been cloned from the hibernating ground squirrel, Spermophilus tridecemlineatus and show differential regulation during hibernation at the mRNA level using relative RT-PCR and at the protein level via immunoblotting in brown adipose tissue (BAT), heart, skeletal muscle and white adipose tissue (WAT). The cDNA sequence for PGC-1alpha revealed a number of amino acid substitutions and two were worthy of note, one resulting in the loss of a potential protein kinase C (PKC) site, while another resulted in the creation of a PKC site, suggesting that PKC may be important in regulating PGC-1alpha. RT-PCR revealed a near 2-fold up-regulation of PPARgamma in BAT and to a lesser extent (

Hibernating animals rely primarily on lipids throughout winter as their primary fuel source, thus it is hypothesized that an increase in genes and proteins relating to lipid transport will increase accordingly. The cloning and expression of heart type fatty acid-binding protein (h-fabp) from a mammalian hibernator, the little brown bat Myotis lucifugus, is presented. Northern blot analysis revealed that transcript levels of h-fabp were significantly higher during hibernation in brown adipose tissue and skeletal muscle compared with levels in euthermic bats. Similarly, heterologous probing with rat adipose type a-fabp found 3.9-fold higher levels of a-fabp transcripts in brown adipose from hibernating animals. Levels of A- and H-FABP protein were quantified in tissues of euthermic versus hibernating animals by Western blotting. A-FABP was 4-fold higher in brown adipose of hibernating, compared with euthermic bats, whereas H-FABP was significantly higher in hibernator brown adipose, heart and skeletal muscle. The present work implicates FABPs as important elements related to the hibernating state in mammals; alterations in gene and protein expression along with amino acid substitutions are shown. These likely contribute to optimizing the function of FABPs at the low body temperatures (near 0 °C) experienced in the hibernating state.

Background Critical to advancing the systems-level evaluation of complex biological processes is the development of comprehensive networks and computational methods to apply to the analysis of systems biology data (transcriptomics, proteomics/phosphoproteomics, metabolomics, etc.). Ideally, these networks will be specifically designed to capture the normal, non-diseased biology of the tissue or cell types under investigation, and can be used with experimentally generated systems biology data to assess the biological impact of perturbations like xenobiotics and other cellular stresses. Lung cell proliferation is a key biological process to capture in such a network model, given the pivotal role that proliferation plays in lung diseases including cancer, chronic obstructive pulmonary disease (COPD), and fibrosis. Unfortunately, no such network has been available prior to this work. Results To further a systems-level assessment of the biological impact of perturbations on non-diseased mammalian lung cells, we constructed a lung-focused network for cell proliferation. The network encompasses diverse biological areas that lead to the regulation of normal lung cell proliferation (Cell Cycle, Growth Factors, Cell Interaction, Intra- and Extracellular Signaling, and Epigenetics), and contains a total of 848 nodes (biological entities) and 1597 edges (relationships between biological entities). The network was verified using four published gene expression profiling data sets associated with measured cell proliferation endpoints in lung and lung-related cell types. Predicted changes in the activity of core machinery involved in cell cycle regulation (RB1, CDKN1A, and MYC/MYCN) are statistically supported across multiple data sets, underscoring the general applicability of this approach for a network-wide biological impact assessment using systems biology data. Conclusions To the best of our knowledge, this lung-focused Cell Proliferation Network provides the most comprehensive connectivity map in existence of the molecular mechanisms regulating cell proliferation in the lung. The network is based on fully referenced causal relationships obtained from extensive evaluation of the literature. The computable structure of the network enables its application to the qualitative and quantitative evaluation of cell proliferation using systems biology data sets. The network is available for public use.

Profile hidden Markov models (profile HMMs) and probabilistic inference methods have made important contributions to the theory of sequence database homology search. However, practical use of profile HMM methods has been hindered by the computational expense of existing software implementations. Here I describe an acceleration heuristic for profile HMMs, the “multiple segment Viterbi” (MSV) algorithm. The MSV algorithm computes an optimal sum of multiple ungapped local alignment segments using a striped vector-parallel approach previously described for fast Smith/Waterman alignment. MSV scores follow the same statistical distribution as gapped optimal local alignment scores, allowing rapid evaluation of significance of an MSV score and thus facilitating its use as a heuristic filter. I also describe a 20-fold acceleration of the standard profile HMM Forward/Backward algorithms using a method I call “sparse rescaling”. These methods are assembled in a pipeline in which high-scoring MSV hits are passed on for reanalysis with the full HMM Forward/Backward algorithm. This accelerated pipeline is implemented in the freely available HMMER3 software package. Performance benchmarks show that the use of the heuristic MSV filter sacrifices negligible sensitivity compared to unaccelerated profile HMM searches. HMMER3 is substantially more sensitive and 100- to 1000-fold faster than HMMER2. HMMER3 is now about as fast as BLAST for protein searches., Author Summary Searching sequence databases is one of the most important applications in computational molecular biology. The main workhorse in the field is the BLAST suite of programs. Since the introduction of BLAST in the 1990's, important theoretical advances in homology search methodology have been made using probabilistic inference methods and hidden Markov models (HMMs). However, previous software implementations of these newer probabilistic methods were slower than BLAST by about 100-fold. This hindered their utility, because computation speed is so critical with the rapidly increasing size of modern sequence databases. Here I describe the acceleration methods I implemented in a new, freely available profile HMM software package, HMMER3. HMMER3 makes profile HMM searches about as fast as BLAST, while retaining the power of using probabilistic inference technology.

To understand the molecular mechanisms underlying compound-induced hemangiosarcomas in mice, and therefore, their human relevance, a systems biology approach was undertaken using transcriptomics and Causal Network Modeling from mice treated with 2-butoxyethanol (2-BE). 2-BE is a hemolytic agent that induces hemangiosarcomas in mice. We hypothesized that the hemolysis induced by 2-BE would result in local tissue hypoxia, a well-documented trigger for endothelial cell proliferation leading to hemangiosarcoma. Gene expression data from bone marrow (BM), liver, and spleen of mice exposed to a single dose (4 h) or seven daily doses of 2-BE were used to develop a mechanistic model of hemangiosarcoma. The resulting mechanistic model confirms previous work proposing that 2-BE induces macrophage activation and inflammation in the liver. In addition, the model supports local tissue hypoxia in the liver and spleen, coupled with increased erythropoeitin signaling and erythropoiesis in the spleen and BM, and suppression of mechanisms that contribute to genomic stability, events that could be contributing factors to hemangiosarcoma formation. Finally, an immunohistochemistry method (Hypoxyprobe) demonstrated that tissue hypoxia was present in the spleen and BM. Together, the results of this study identify molecular mechanisms that initiate hemangiosarcoma, a key step in understanding safety concerns that can impact drug decision processes, and identified hypoxia as a possible contributing factor for 2-BE–induced hemangiosarcoma in mice.