Metabolic profiles of six African cultivars of cassava (Manihot esculenta Crantz) highlight bottlenecks of root yield

Open Access Article; Published online: 17 Jan 2020Cassava is an important staple crop in sub‐Saharan Africa, due to its high productivity even on nutrient poor soils. The metabolic characteristics underlying this high productivity are poorly understood including the mode of photosynthesis, reasons for the high rate of photosynthesis, the extent of source/sink limitation, the impact of environment, and the extent of variation between cultivars. Six commercial African cassava cultivars were grown in a greenhouse in Erlangen, Germany, and in the field in Ibadan, Nigeria. Source leaves, sink leaves, stems and storage roots were harvested during storage root bulking and analyzed for sugars, organic acids, amino acids, phosphorylated intermediates, minerals, starch, protein, activities of enzymes in central metabolism and yield traits. High ratios of RuBisCO:phosphoenolpyruvate carboxylase activity support a C3 mode of photosynthesis. The high rate of photosynthesis is likely to be attributed to high activities of enzymes in the Calvin–Benson cycle and pathways for sucrose and starch synthesis. Nevertheless, source limitation is indicated because root yield traits correlated with metabolic traits in leaves rather than in the stem or storage roots. This situation was especially so in greenhouse‐grown plants, where irradiance will have been low. In the field, plants produced more storage roots. This was associated with higher AGPase activity and lower sucrose in the roots, indicating that feedforward loops enhanced sink capacity in the high light and low nitrogen environment in the field. Overall, these results indicated that carbon assimilation rate, the K battery, root starch synthesis, trehalose, and chlorogenic acid accumulation are potential target traits for genetic improvement

Effect of serum 25-hydroxyvitamin D on risk for type 2 diabetes may be partially mediated by subclinical inflammation: results from the MONICA/KORA Augsburg study

OBJECTIVE: To assess the association between serum 25-hydroxyvitamin D (25-OHD) and incident type 2 diabetes and to determine whether the association is mediated by subclinical inflammation. RESEARCH DESIGN AND METHODS: Using a case-cohort design, baseline levels of 25-OHD were measured in 416 case subjects with incident type 2 diabetes and 1,267 noncase subjects selected from a source population of 7,936 middle-aged participants in the population-based Monitoring of Trends and Determinants in Cardiovascular Disease (MONICA)/Cooperative Health Research in the Region of Augsburg (KORA) study. RESULTS: A significant inverse association was observed between serum 25-OHD and incident type 2 diabetes after adjustment for diabetes risk factors and season. The hazard ratio (HR) and 95% CI comparing tertile extremes was 0.63 (0.44–0.90) (P(trend) = 0.010). Further adjustment for C-reactive protein, interleukin-6, soluble intercellular adhesion molecule-1, and interferon-γ–inducible protein-10 attenuated this association by 16% (HR 0.73 [0.50–1.05], P = 0.090). CONCLUSIONS: Vitamin D status is inversely related to type 2 diabetes risk and our data suggest that this association may be partially mediated by subclinical inflammation

Transforming Growth Factor-β1 and Incident Type 2 Diabetes: Results from the MONICA/KORA case-cohort study, 1984–2002

Subclinical inflammation leads to insulin resistance and beta-cell dysfunction. This study aimed to assess whether levels of circulating transforming growth factor-beta1 (TGF-beta1)-a central, mainly immunosuppressive, and anti-inflammatory cytokine-were associated with incident type 2 diabetes. RESEARCH DESIGN AND METHODS: We measured serum levels of TGF-beta1 from 460 individuals with and 1,474 individuals without incident type 2 diabetes in a prospective case-cohort study within the population-based MONICA (MONItoring of Trends and Determinants in CArdiovascular Disease)/KORA (Cooperative Health Research in the Region of Augsburg) cohort. RESULTS: Elevated TGF-beta1 concentrations were associated with higher, not lower, risk for type 2 diabetes (age-, sex-, and survey-adjusted hazard ratios [95% CI] for increasing TGF-beta1 tertiles: 1.0, 1.08 [0.83-1.42], and 1.41 [1.08-1.83]; P(for) (trend) = 0.012). Adjustment for BMI and metabolic and lifestyle factors had virtually no impact on the effect size. CONCLUSIONS: Elevated serum concentrations of the cytokine TGF-beta1 indicate an increased risk for type 2 diabetes. TGF-beta1 may be upregulated to counterbalance metabolic and immunological disturbances preceding type 2 diabetes

Auxin signaling and vascular cambium formation enables storage metabolism in cassava tuberous roots

Open Access Article; Published online: 13 Mar 2021Cassava storage roots are among the most important root crops worldwide and represent one of the most consumed staple foods in Sub-Saharan Africa. The vegetatively propagated tropical shrub can form many starchy tuberous roots from its stem. These storage roots are formed through the activation of secondary root growth processes. However, the underlying genetic regulation of storage root development is largely unknown. Here we report on distinct structural and transcriptional changes occurring during the early phases of storage root development. A pronounced increase in auxin-related transcripts and the transcriptional activation of secondary growth factors, as well as a decrease in gibberellin-related transcripts was observed during the early stages of secondary root growth. This was accompanied by increased cell wall biosynthesis, increased most notably during the initial xylem expansion within the root vasculature. Starch storage metabolism was activated only after the formation of the vascular cambium. The formation of nonlignified xylem parenchyma cells and the activation of starch storage metabolism coincided with increased expression of the KNOX/BEL genes KNAT1, PENNYWISE and POUND-FOOLISH, indicating their importance for proper xylem parenchyma function

Hsp90 middle domain phosphorylation initiates a complex conformational program to recruit the ATPase-stimulating cochaperone Aha1

Complex conformational dynamics are essential for function of the dimeric molecular cha- perone heat shock protein 90 (Hsp90), including transient, ATP-biased N-domain dimer- ization that is necessary to attain ATPase competence. The intrinsic, but weak, ATP hydrolyzing activity of human Hsp90 is markedly enhanced by the co-chaperone Aha1. However, the cellular concentration of Aha1 is substoichiometric relative to Hsp90. Here we report that initial recruitment of this cochaperone to Hsp90 is markedly enhanced by phosphorylation of a highly conserved tyrosine (Y313 in Hsp90α) in the Hsp90 middle domain. Importantly, phosphomimetic mutation of Y313 promotes formation of a transient complex in which both N- and C-domains of Aha1 bind to distinct surfaces of the middle domains of opposing Hsp90 protomers prior to ATP-directed N-domain dimerization. Thus, Y313 represents a phosphorylation-sensitive conformational switch, engaged early after client loading, that affects both local and long-range conformational dynamics to facilitate initial recruitment of Aha1 to Hsp90

Rare and common genetic determinants of metabolic individuality and their effects on human health

Garrod’s concept of ‘chemical individuality’ has contributed to comprehension of the molecular origins of human diseases. Untargeted high-throughput metabolomic technologies provide an in-depth snapshot of human metabolism at scale. We studied the genetic architecture of the human plasma metabolome using 913 metabolites assayed in 19,994 individuals and identified 2,599 variant–metabolite associations (P < 1.25 × 10−11) within 330 genomic regions, with rare variants (minor allele frequency ≤ 1%) explaining 9.4% of associations. Jointly modeling metabolites in each region, we identified 423 regional, co-regulated, variant–metabolite clusters called genetically influenced metabotypes. We assigned causal genes for 62.4% of these genetically influenced metabotypes, providing new insights into fundamental metabolite physiology and clinical relevance, including metabolite-guided discovery of potential adverse drug effects (DPYD and SRD5A2). We show strong enrichment of inborn errors of metabolism-causing genes, with examples of metabolite associations and clinical phenotypes of non-pathogenic variant carriers matching characteristics of the inborn errors of metabolism. Systematic, phenotypic follow-up of metabolite-specific genetic scores revealed multiple potential etiological relationships

Immunological and Cardiometabolic Risk Factors in the Prediction of Type 2 Diabetes and Coronary Events: MONICA/KORA Augsburg Case-Cohort Study

BACKGROUND: This study compares inflammation-related biomarkers with established cardiometabolic risk factors in the prediction of incident type 2 diabetes and incident coronary events in a prospective case-cohort study within the population-based MONICA/KORA Augsburg cohort. METHODS AND FINDINGS: Analyses for type 2 diabetes are based on 436 individuals with and 1410 individuals without incident diabetes. Analyses for coronary events are based on 314 individuals with and 1659 individuals without incident coronary events. Mean follow-up times were almost 11 years. Areas under the receiver-operating characteristic curve (AUC), changes in Akaike's information criterion (ΔAIC), integrated discrimination improvement (IDI) and net reclassification index (NRI) were calculated for different models. A basic model consisting of age, sex and survey predicted type 2 diabetes with an AUC of 0.690. Addition of 13 inflammation-related biomarkers (CRP, IL-6, IL-18, MIF, MCP-1/CCL2, IL-8/CXCL8, IP-10/CXCL10, adiponectin, leptin, RANTES/CCL5, TGF-β1, sE-selectin, sICAM-1; all measured in nonfasting serum) increased the AUC to 0.801, whereas addition of cardiometabolic risk factors (BMI, systolic blood pressure, ratio total/HDL-cholesterol, smoking, alcohol, physical activity, parental diabetes) increased the AUC to 0.803 (ΔAUC [95% CI] 0.111 [0.092-0.149] and 0.113 [0.093-0.149], respectively, compared to the basic model). The combination of all inflammation-related biomarkers and cardiometabolic risk factors yielded a further increase in AUC to 0.847 (ΔAUC [95% CI] 0.044 [0.028-0.066] compared to the cardiometabolic risk model). Corresponding AUCs for incident coronary events were 0.807, 0.825 (ΔAUC [95% CI] 0.018 [0.013-0.038] compared to the basic model), 0.845 (ΔAUC [95% CI] 0.038 [0.028-0.059] compared to the basic model) and 0.851 (ΔAUC [95% CI] 0.006 [0.003-0.021] compared to the cardiometabolic risk model), respectively. CONCLUSIONS: Inclusion of multiple inflammation-related biomarkers into a basic model and into a model including cardiometabolic risk factors significantly improved the prediction of type 2 diabetes and coronary events, although the improvement was less pronounced for the latter endpoint

Genome-wide characterization of circulating metabolic biomarkers

Genome-wide association analyses using high-throughput metabolomics platforms have led to novel insights into the biology of human metabolism1,2,3,4,5,6,7. This detailed knowledge of the genetic determinants of systemic metabolism has been pivotal for uncovering how genetic pathways influence biological mechanisms and complex diseases8,9,10,11. Here we present a genome-wide association study for 233 circulating metabolic traits quantified by nuclear magnetic resonance spectroscopy in up to 136,016 participants from 33 cohorts. We identify more than 400 independent loci and assign probable causal genes at two-thirds of these using manual curation of plausible biological candidates. We highlight the importance of sample and participant characteristics that can have significant effects on genetic associations. We use detailed metabolic profiling of lipoprotein- and lipid-associated variants to better characterize how known lipid loci and novel loci affect lipoprotein metabolism at a granular level. We demonstrate the translational utility of comprehensively phenotyped molecular data, characterizing the metabolic associations of intrahepatic cholestasis of pregnancy. Finally, we observe substantial genetic pleiotropy for multiple metabolic pathways and illustrate the importance of careful instrument selection in Mendelian randomization analysis, revealing a putative causal relationship between acetone and hypertension. Our publicly available results provide a foundational resource for the community to examine the role of metabolism across diverse diseases

Rare and common genetic determinants of metabolic individuality and their effects on human health

Garrod’s concept of ‘chemical individuality’ has contributed to comprehension of the molecular origins of human diseases. Untargeted high-throughput metabolomic technologies provide an in-depth snapshot of human metabolism at scale. We studied the genetic architecture of the human plasma metabolome using 913 metabolites assayed in 19,994 individuals and identified 2,599 variant–metabolite associations (P < 1.25 × 10−11) within 330 genomic regions, with rare variants (minor allele frequency ≤ 1%) explaining 9.4% of associations. Jointly modeling metabolites in each region, we identified 423 regional, co-regulated, variant–metabolite clusters called genetically influenced metabotypes. We assigned causal genes for 62.4% of these genetically influenced metabotypes, providing new insights into fundamental metabolite physiology and clinical relevance, including metabolite-guided discovery of potential adverse drug effects (DPYD and SRD5A2). We show strong enrichment of inborn errors of metabolism-causing genes, with examples of metabolite associations and clinical phenotypes of non-pathogenic variant carriers matching characteristics of the inborn errors of metabolism. Systematic, phenotypic follow-up of metabolite-specific genetic scores revealed multiple potential etiological relationships

A Genome-Wide Association Study of Diabetic Kidney Disease in Subjects With Type 2 Diabetes

dentification of sequence variants robustly associated with predisposition to diabetic kidney disease (DKD) has the potential to provide insights into the pathophysiological mechanisms responsible. We conducted a genome-wide association study (GWAS) of DKD in type 2 diabetes (T2D) using eight complementary dichotomous and quantitative DKD phenotypes: the principal dichotomous analysis involved 5,717 T2D subjects, 3,345 with DKD. Promising association signals were evaluated in up to 26,827 subjects with T2D (12,710 with DKD). A combined T1D+T2D GWAS was performed using complementary data available for subjects with T1D, which, with replication samples, involved up to 40,340 subjects with diabetes (18,582 with DKD). Analysis of specific DKD phenotypes identified a novel signal near GABRR1 (rs9942471, P = 4.5 x 10(-8)) associated with microalbuminuria in European T2D case subjects. However, no replication of this signal was observed in Asian subjects with T2D or in the equivalent T1D analysis. There was only limited support, in this substantially enlarged analysis, for association at previously reported DKD signals, except for those at UMOD and PRKAG2, both associated with estimated glomerular filtration rate. We conclude that, despite challenges in addressing phenotypic heterogeneity, access to increased sample sizes will continue to provide more robust inference regarding risk variant discovery for DKD.Peer reviewe