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Infection-induced T cell responses must be properly tempered and terminated to prevent immuno-pathology. Using transgenic mice, we demonstrate that T cell intrinsic STAT1 signaling is required to curb inflammation during acute infection with Toxoplasma gondii . Specifically, we report that mice lacking STAT1 selectively in T cells expel parasites but ultimately succumb to lethal immuno-pathology characterized by aberrant Th1-type responses with reduced IL-10 and increased IL-13 production. We also find that, unlike STAT1, STAT3 is not required for induction of IL-10 or suppression of IL-13 during acute toxoplasmosis. Each of these findings was confirmed in vitro and ChIP-seq data mining showed that STAT1 and STAT3 co-localize at the Il10 locus, as well as loci encoding other transcription factors that regulate IL-10 production, most notably Maf and Irf4 . These data advance basic understanding of how infection-induced T cell responses are managed to prevent immuno-pathology and provide specific insights on the anti-inflammatory properties of STAT1, highlighting its role in shaping the character of Th1-type responses.

In this paper, we discuss observations of temperature variability in the tidal portion of the San Joaquín River in California. The San Joaquín River makes up the southern portion of the Sacramento San Joaquín Delta, the eastern end of San Francisco Bay. Observations made in August 2004 and August 2005 show significant diurnal variations in temperature in response to surface heat exchange. However, to account for observed changes in heat content a sizeable downstream heat flux (approximately 100 W m⁻²) must be added to the surface heat flux. To account for this flux via Fickian dispersion, a flow-dependent dispersion coefficient varying from 500 to 4,000 m² s⁻₁ is needed. These values are much larger than would be predicted for a river of this size, suggesting that the complex topology of the Delta greatly enhances longitudinal dispersion. Building on these observations, we present a simple theory that explores how the subtidal temperature field varies in response to changes in flow rate, dispersion, and heat exchange.

Cdc42 is a Rho-family GTPase that controls cell polarization from yeast to human cells. In fission yeast, under normal growth conditions, Cdc42-GTP oscillates between cell tips to promote polarized growth. However, when exposed to environmental stressors, Cdc42 adopts an \"exploratory\" pattern of Cdc42 activation along the cell membrane. This pattern also occurs when the NDR kinase Orb6 is downregulated. Here, we describe the molecular mechanism behind the emergence of exploratory Cdc42 dynamics and identify a new substrate of Orb6 kinase, the Cdc42 GAP Rga3. Additionally, we show that MAP kinase Sty1, known for linking stress signals to the Cdc42 polarity module, negatively regulates Orb6 kinase. During nutritional stress, activation of Sty1 and inactivation of Orb6 are associated with chronological lifespan extension. Our findings reveal a novel mechanism controlling cell morphology during stress, with important implications for cell survival.

Despite decades of work on implementing best management practices to reduce the movement of excess nitrogen (N) to aquatic ecosystems, the amount of N in streams and rivers remains high in many watersheds. Stream restoration has become increasingly popular, yet efforts to quantify N-removal benefits are only just beginning. Natural resource managers are asking scientists to provide advice for reducing the downstream flux of N. Here, we propose a framework for prioritizing restoration sites that involves identifying where potential N loads are large due to sizeable sources and efficient delivery to streams, and when the majority of N is exported. Small streams (1st-3rd order) with considerable loads delivered during low to moderate flows offer the greatest opportunities for N removal. We suggest approaches that increase in-stream carbon availability, contact between the water and benthos, and connections between streams and adjacent terrestrial environments. Because of uncertainties concerning the magnitude of N reduction possible, potential approaches should be tested in various landscape contexts; until more is known, stream restoration alone is not appropriate for compensatory mitigation and should be seen as complementary to land-based best management practices.

Background Chronic kidney disease (CKD) is a complex disorder that has become a high prevalence global health problem, with diabetes being its predominant pathophysiologic driver. Autosomal genetic variation only explains some of the predisposition to kidney disease. Variations in the mitochondrial genome (mtDNA) and nuclear-encoded mitochondrial genes (NEMG) are implicated in susceptibility to kidney disease and CKD progression, but they have not been thoroughly explored. Our aim was to investigate the association of variation in both mtDNA and NEMG with CKD (and related traits), with a particular focus on diabetes. Methods We used the UK Biobank (UKB) and UK-ROI, an independent collection of individuals with type 1 diabetes mellitus (T1DM) patients. Results Fourteen mitochondrial variants were associated with estimated glomerular filtration rate (eGFR) in UKB. Mitochondrial variants and haplogroups U, H and J were associated with eGFR and serum variables. Mitochondrial haplogroup H was associated with all the serum variables regardless of the presence of diabetes. Mitochondrial haplogroup X was associated with end-stage kidney disease (ESKD) in UKB. We confirmed the influence of several known NEMG on kidney disease and function and found novel associations for SLC39A13 , CFL1 , ACP2 or ATP5G1 with serum variables and kidney damage, and for SLC4A1 , NUP210 and MYH14 with ESKD. The G allele of TBC1D32 -rs113987180 was associated with higher risk of ESKD in patients with diabetes (OR:9.879; CI 95% :4.440–21.980; P  = 2.0E-08). In UK-ROI, AGXT2 -rs71615838 and SURF1 -rs183853102 were associated with diabetic nephropathies, and TFB1M -rs869120 with eGFR. Conclusions We identified novel variants both in mtDNA and NEMG which may explain some of the missing heritability for CKD and kidney phenotypes. We confirmed the role of MT-ND5 and mitochondrial haplogroup H on renal disease (serum variables), and identified the MT-ND5 -rs41535848G variant, along with mitochondrial haplogroup X, associated with higher risk of ESKD. Despite most of the associations were independent of diabetes, we also showed potential roles for NEMG in T1DM.

Biomarkers of monocyte activation (soluble CD14 [sCD14]), inflammation (interleukin-6 [IL-6]), and altered coagulation (D-dimer) are associated with increased mortality risk in people with HIV. The objective of the Russia Alcohol Research Collaboration on HIV/AIDS (ARCH) study was to evaluate the association between heavy alcohol use and inflammatory biomarkers over time. The study sought antiretroviral therapy naive participants with HIV (n = 350) and assessed them at baseline, 12 and 24 months. Linear mixed effects models were used to determine whether heavy drinking (self-report augmented by phosphatidylethanol [PEth], an alcohol biomarker) was longitudinally associated with IL-6, sCD14 and D-dimer adjusting for potential confounders (e.g., demographics, HIV factors, comorbid conditions). Participants' baseline characteristics were as follows: 71% male; mean age of 34 years; 87% self-reported hepatitis C; and 86% current smokers. Mean log10 (HIV RNA) was 4.3 copies/mL. Heavy alcohol use, based on National Institute of Alcohol Abuse and Alcoholism risky drinking criteria and PEth (versus non-heavy alcohol use) was associated with higher sCD14 (adjusted mean difference 125 ng/mL [95% CI: 42, 209]), IL-6 (ratio of means 1.35 [95% CI: 1.17, 1.55] pg/mL), and D-dimer (ratio of means 1.20 [95% CI: 1.06, 1.37] ug/mL) across the two-year follow-up. Among HIV+ adults, current heavy alcohol use is associated with higher sCD14, IL-6 and D-dimer over time. Since these biomarkers are associated with mortality, interventions to mitigate effects of heavy drinking on these immune processes merit consideration.

Type 1 diabetes affects over nine million individuals globally, with approximately 40% developing diabetic kidney disease. Emerging evidence suggests that epigenetic alterations, such as DNA methylation, are involved in diabetic kidney disease. Here we assess differences in blood-derived genome-wide DNA methylation associated with diabetic kidney disease in 1304 carefully characterised individuals with type 1 diabetes and known renal status from two cohorts in the United Kingdom-Republic of Ireland and Finland. In the meta-analysis, we identify 32 differentially methylated CpGs in diabetic kidney disease in type 1 diabetes, 18 of which are located within genes differentially expressed in kidneys or correlated with pathological traits in diabetic kidney disease. We show that methylation at 21 of the 32 CpGs predict the development of kidney failure, extending the knowledge and potentially identifying individuals at greater risk for diabetic kidney disease in type 1 diabetes. Approximately 40 percent of people with type 1 diabetes develop kidney disease, but the risk factors are not well understood. Here, the authors identify DNA methylation signatures associated with diabetic kidney disease, of which 21 biomarkers predict the development of kidney failure.

Megabase-scale mosaic chromosomal alterations (mCAs) in blood are prognostic markers for a host of human diseases. Here, to gain a better understanding of mCA rates in genetically diverse populations, we analyzed whole-genome sequencing data from 67,390 individuals from the National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program. We observed higher sensitivity with whole-genome sequencing data, compared with array-based data, in uncovering mCAs at low mutant cell fractions and found that individuals of European ancestry have the highest rates of autosomal mCAs and the lowest rates of chromosome X mCAs, compared with individuals of African or Hispanic ancestry. Although further studies in diverse populations will be needed to replicate our findings, we report three loci associated with loss of chromosome X, associations between autosomal mCAs and rare variants in DCPS , ADM17 , PPP1R16B and TET2 and ancestry-specific variants in ATM and MPL with mCAs in cis . A method that allows for the detection of mosaic chromosomal alterations from blood whole-genome sequencing data highlights ancestry-specific differences in the distribution of common and rare germline susceptibility variants.

Zoonotic spillover of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to humans in December 2019 caused the coronavirus disease 2019 (COVID-19) pandemic. Serological monitoring is critical for detailed understanding of individual immune responses to infection and protection to guide clinical therapeutic and vaccine strategies. We developed a high throughput multiplexed SARS-CoV-2 antigen microarray incorporating spike (S) and nucleocapsid protein (NP) and fragments expressed in various hosts which allowed simultaneous assessment of serum IgG, IgA, and IgM responses. Antigen glycosylation influenced antibody binding, with S glycosylation generally increasing and NP glycosylation decreasing binding. Purified antibody isotypes demonstrated a binding pattern and intensity different from the same isotype in whole serum, probably due to competition from the other isotypes present. Using purified antibody isotypes from naïve Irish COVID-19 patients, we correlated antibody isotype binding to different panels of antigens with disease severity, with binding to the S region S1 expressed in insect cells (S1 Sf21) significant for IgG, IgA, and IgM. Assessing longitudinal response for constant concentrations of purified antibody isotypes for a patient subset demonstrated that the relative proportion of antigen-specific IgGs decreased over time for severe disease, but the relative proportion of antigen-specific IgA binding remained at the same magnitude at 5 and 9 months post-first symptom onset. Further, the relative proportion of IgM binding decreased for S antigens but remained the same for NP antigens. This may support antigen-specific serum IgA and IgM playing a role in maintaining longer-term protection, important for developing and assessing vaccine strategies. Overall, these data demonstrate the multiplexed platform as a sensitive and useful platform for expanded humoral immunity studies, allowing detailed elucidation of antibody isotypes response against multiple antigens. This approach will be useful for monoclonal antibody therapeutic studies and screening of donor polyclonal antibodies for patient infusions.

Aims/hypothesisDiabetic kidney disease (DKD) is the leading cause of kidney failure and has a substantial genetic component. Our aim was to identify novel genetic factors and genes contributing to DKD by performing meta-analysis of previous genome-wide association studies (GWAS) on DKD and by integrating the results with renal transcriptomics datasets.MethodsWe performed GWAS meta-analyses using ten phenotypic definitions of DKD, including nearly 27,000 individuals with diabetes. Meta-analysis results were integrated with estimated quantitative trait locus data from human glomerular (N=119) and tubular (N=121) samples to perform transcriptome-wide association study. We also performed gene aggregate tests to jointly test all available common genetic markers within a gene, and combined the results with various kidney omics datasets.ResultsThe meta-analysis identified a novel intronic variant (rs72831309) in the TENM2 gene associated with a lower risk of the combined chronic kidney disease (eGFR<60 ml/min per 1.73 m2) and DKD (microalbuminuria or worse) phenotype (p=9.8×10−9; although not withstanding correction for multiple testing, p>9.3×10−9). Gene-level analysis identified ten genes associated with DKD (COL20A1, DCLK1, EIF4E, PTPRN–RESP18, GPR158, INIP–SNX30, LSM14A and MFF; p<2.7×10−6). Integration of GWAS with human glomerular and tubular expression data demonstrated higher tubular AKIRIN2 gene expression in individuals with vs without DKD (p=1.1×10−6). The lead SNPs within six loci significantly altered DNA methylation of a nearby CpG site in kidneys (p<1.5×10−11). Expression of lead genes in kidney tubules or glomeruli correlated with relevant pathological phenotypes (e.g. TENM2 expression correlated positively with eGFR [p=1.6×10−8] and negatively with tubulointerstitial fibrosis [p=2.0×10−9], tubular DCLK1 expression correlated positively with fibrosis [p=7.4×10−16], and SNX30 expression correlated positively with eGFR [p=5.8×10−14] and negatively with fibrosis [p<2.0×10−16]).Conclusions/interpretationAltogether, the results point to novel genes contributing to the pathogenesis of DKD.Data availabilityThe GWAS meta-analysis results can be accessed via the type 1 and type 2 diabetes (T1D and T2D, respectively) and Common Metabolic Diseases (CMD) Knowledge Portals, and downloaded on their respective download pages (https://t1d.hugeamp.org/downloads.html; https://t2d.hugeamp.org/downloads.html; https://hugeamp.org/downloads.html).