Transcriptional response in the unaffected kidney after contralateral hydronephrosis or nephrectomy

Transcriptional response in the unaffected kidney after contralateral hydronephrosis or nephrectomy.BackgroundUnilateral loss of kidney function is followed by compensatory contralateral growth. The early, genome-wide transcriptional response of the untouched kidney to unilateral ureteral obstruction (UUO) or unilateral nephrectomy is unknown.MethodsTwelve adult male Sprague-Dawley rats were subjected to UUO and twelve rats to unilateral nephrectomy. At time points 12, 24, and 72 hours after insult four rats each were sacrificed and the contralateral kidney harvested for genome-wide gene expression analysis, transcription factor analysis, and histomorphology.ResultsMicroarray studies revealed that the majority of differentially expressed transcripts were suppressed in UUO and unilateral nephrectomy compared to control kidneys. The function of these suppressed genes is predominantly growth inhibition and apoptosis suggesting a net pro-hypertrophic response. Insulin-like growth factor-2 (IGF-2)-binding protein was one of the few activated genes. We observed a distinctly different molecular signature between UUO and unilateral nephrectomy at the three time points investigated. The early response in UUO rats suggests a counterbalance to the nonfiltering kidney by activation of transport pathways such as the aquaporins. Unilateral nephrectomy kidneys, on the other hand, respond immediately to contralateral nephrectomy by activation of cell cycle regulators such as the cyclin family. Several genes with weakly defined function were found to be associated with either UUO or unilateral nephrectomy. Transcription factor analysis of the identified transcripts suggests common regulation at least of some of these genes. All kidneys showed normal histology.ConclusionRelease of growth inhibition by nephrectomy leads to immediate cell cycle activation after unilateral nephrectomy, whereas UUO kidneys counterbalance filtration failure by activation of several transporters

Inhibition of SIRT1 Impairs the Accumulation and Transcriptional Activity of HIF-1α Protein under Hypoxic Conditions

Sirtuins and hypoxia-inducible transcription factors (HIF) have well-established roles in regulating cellular responses to metabolic and oxidative stress. Recent reports have linked these two protein families by demonstrating that sirtuins can regulate the activity of HIF-1 and HIF-2. Here we investigated the role of SIRT1, a NAD+-dependent deacetylase, in the regulation of HIF-1 activity in hypoxic conditions. Our results show that in hepatocellular carcinoma (HCC) cell lines, hypoxia did not alter SIRT1 mRNA or protein expression, whereas it predictably led to the accumulation of HIF-1α and the up-regulation of its target genes. In hypoxic models in vitro and in in vivo models of systemic hypoxia and xenograft tumor growth, knockdown of SIRT1 protein with shRNA or inhibition of its activity with small molecule inhibitors impaired the accumulation of HIF-1α protein and the transcriptional increase of its target genes. In addition, endogenous SIRT1 and HIF-1α proteins co-immunoprecipitated and loss of SIRT1 activity led to a hyperacetylation of HIF-1α. Taken together, our data suggest that HIF-1α and SIRT1 proteins interact in HCC cells and that HIF-1α is a target of SIRT1 deacetylase activity. Moreover, SIRT1 is necessary for HIF-1α protein accumulation and activation of HIF-1 target genes under hypoxic conditions

Soluble CD137: A Potential Prognostic Biomarker in Critically Ill Patients

T cell depletion and functional impairment are characteristics of sepsis. CD137 is a costimulatory receptor on activated T cells, while soluble CD137 (sCD137) inhibits CD137 signaling. This study found elevated sCD137 levels in the plasma of patients with systemic inflammatory response syndrome (SIRS), sepsis, or septic shock compared to healthy controls. The sCD137 levels negatively correlated with the C-reactive protein and positively with procalcitonin and interleukin-6. There was no difference in sCD137 levels based on ventilation, dialysis, or vasopressor treatment. Patients with SARS-CoV-2, Gram-positive, or Gram-negative bacterial infections had similar sCD137 levels as noninfected individuals. Notably, higher plasma sCD137 levels were observed in non-survivors compared to survivors in both the SIRS/sepsis group and the SARS-CoV-2 subgroup. In conclusion, plasma sCD137 levels are associated with severe illness and survival in critically ill patients

Cell type deconvolution of bulk blood RNA-Seq to reveal biological insights of neuropsychiatric disorders

Genome-wide association studies (GWAS) have uncovered susceptibility loci associated with psychiatric disorders like bipolar disorder (BP) and schizophrenia (SCZ). However, most of these loci are in non-coding regions of the genome with unknown causal mechanisms of the link between genetic variation and disease risk. Expression quantitative trait loci (eQTL) analysis of bulk tissue is a common approach to decipher underlying mechanisms, though this can obscure cell-type specific signals thus masking trait-relevant mechanisms. While single-cell sequencing can be prohibitively expensive in large cohorts, computationally inferred cell type proportions and cell type gene expression estimates have the potential to overcome these problems and advance mechanistic studies. Using bulk RNA-Seq from 1,730 samples derived from whole blood in a cohort ascertained for individuals with BP and SCZ this study estimated cell type proportions and their relation with disease status and medication. We found between 2,875 and 4,629 eGenes for each cell type, including 1,211 eGenes that are not found using bulk expression alone. We performed a colocalization test between cell type eQTLs and various traits and identified hundreds of associations between cell type eQTLs and GWAS loci that are not detected in bulk eQTLs. Finally, we investigated the effects of lithium use on cell type expression regulation and found examples of genes that are differentially regulated dependent on lithium use. Our study suggests that computational methods can be applied to large bulk RNA-Seq datasets of non-brain tissue to identify disease-relevant, cell type specific biology of psychiatric disorders and psychiatric medication

Cell-type deconvolution of bulk-blood RNA-seq reveals biological insights into neuropsychiatric disorders

Genome-wide association studies (GWASs) have uncovered susceptibility loci associated with psychiatric disorders such as bipolar disorder (BP) and schizophrenia (SCZ). However, most of these loci are in non-coding regions of the genome, and the causal mechanisms of the link between genetic variation and disease risk is unknown. Expression quantitative trait locus (eQTL) analysis of bulk tissue is a common approach used for deciphering underlying mechanisms, although this can obscure cell-type-specific signals and thus mask trait-relevant mechanisms. Although single-cell sequencing can be prohibitively expensive in large cohorts, computationally inferred cell-type proportions and cell-type gene expression estimates have the potential to overcome these problems and advance mechanistic studies. Using bulk RNA-seq from 1,730 samples derived from whole blood in a cohort ascertained from individuals with BP and SCZ, this study estimated cell-type proportions and their relation with disease status and medication. For each cell type, we found between 2,875 and 4,629 eGenes (genes with an associated eQTL), including 1,211 that are not found on the basis of bulk expression alone. We performed a colocalization test between cell-type eQTLs and various traits and identified hundreds of associations that occur between cell-type eQTLs and GWASs but that are not detected in bulk eQTLs. Finally, we investigated the effects of lithium use on the regulation of cell-type expression loci and found examples of genes that are differentially regulated according to lithium use. Our study suggests that applying computational methods to large bulk RNA-seq datasets of non-brain tissue can identify disease-relevant, cell-type-specific biology of psychiatric disorders and psychiatric medication

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

Genome-wide association reveals host-specific genomic traits in Escherichia coli

Background: Escherichia coli is an opportunistic pathogen which colonizes various host species. However, to what extent genetic lineages of E. coli are adapted or restricted to specific hosts and the genomic determinants of such adaptation or restriction is poorly understood. Results: We randomly sampled E. coli isolates from four countries (Germany, UK, Spain, and Vietnam), obtained from five host species (human, pig, cattle, chicken, and wild boar) over 16 years, from both healthy and diseased hosts, to construct a collection of 1198 whole-genome sequenced E. coli isolates. We identified associations between specific E. coli lineages and the host from which they were isolated. A genome-wide association study (GWAS) identified several E. coli genes that were associated with human, cattle, or chicken hosts, whereas no genes associated with the pig host could be found. In silico characterization of nine contiguous genes (collectively designated as nan-9) associated with the human host indicated that these genes are involved in the metabolism of sialic acids (Sia). In contrast, the previously described sialic acid regulon known as sialoregulon (i.e. nanRATEK-yhcH, nanXY, and nanCMS) was not associated with any host species. In vitro growth experiments with a Δnan-9 E. coli mutant strain, using the sialic acids 5-N-acetylneuraminic acid (Neu5Ac) and N-glycolylneuraminic acid (Neu5Gc) as sole carbon source, showed impaired growth behaviour compared to the wild-type. Conclusions: This study provides an extensive analysis of genetic determinants which may contribute to host specificity in E. coli. Our findings should inform risk analysis and epidemiological monitoring of (antimicrobial resistant) E. coli

Genome-wide association reveals host-specific genomic traits in Escherichia coli

BACKGROUND: Escherichia coli is an opportunistic pathogen which colonizes various host species. However, to what extent genetic lineages of E. coli are adapted or restricted to specific hosts and the genomic determinants of such adaptation or restriction is poorly understood. RESULTS: We randomly sampled E. coli isolates from four countries (Germany, UK, Spain, and Vietnam), obtained from five host species (human, pig, cattle, chicken, and wild boar) over 16 years, from both healthy and diseased hosts, to construct a collection of 1198 whole-genome sequenced E. coli isolates. We identified associations between specific E. coli lineages and the host from which they were isolated. A genome-wide association study (GWAS) identified several E. coli genes that were associated with human, cattle, or chicken hosts, whereas no genes associated with the pig host could be found. In silico characterization of nine contiguous genes (collectively designated as nan-9) associated with the human host indicated that these genes are involved in the metabolism of sialic acids (Sia). In contrast, the previously described sialic acid regulon known as sialoregulon (i.e. nanRATEK-yhcH, nanXY, and nanCMS) was not associated with any host species. In vitro growth experiments with a Δnan-9 E. coli mutant strain, using the sialic acids 5-N-acetylneuraminic acid (Neu5Ac) and N-glycolylneuraminic acid (Neu5Gc) as sole carbon source, showed impaired growth behaviour compared to the wild-type. CONCLUSIONS: This study provides an extensive analysis of genetic determinants which may contribute to host specificity in E. coli. Our findings should inform risk analysis and epidemiological monitoring of (antimicrobial resistant) E. coli

Identification of regulatory variants associated with genetic susceptibility to meningococcal disease.

Non-coding genetic variants play an important role in driving susceptibility to complex diseases but their characterization remains challenging. Here, we employed a novel approach to interrogate the genetic risk of such polymorphisms in a more systematic way by targeting specific regulatory regions relevant for the phenotype studied. We applied this method to meningococcal disease susceptibility, using the DNA binding pattern of RELA - a NF-kB subunit, master regulator of the response to infection - under bacterial stimuli in nasopharyngeal epithelial cells. We designed a custom panel to cover these RELA binding sites and used it for targeted sequencing in cases and controls. Variant calling and association analysis were performed followed by validation of candidate polymorphisms by genotyping in three independent cohorts. We identified two new polymorphisms, rs4823231 and rs11913168, showing signs of association with meningococcal disease susceptibility. In addition, using our genomic data as well as publicly available resources, we found evidences for these SNPs to have potential regulatory effects on ATXN10 and LIF genes respectively. The variants and related candidate genes are relevant for infectious diseases and may have important contribution for meningococcal disease pathology. Finally, we described a novel genetic association approach that could be applied to other phenotypes