SOC bioavailability significantly correlated with the microbial activity mediated by size fractionation and soil morphology in agricultural ecosystems.

Despite the fact that physical and chemical processes have been widely proposed to explicate the stabilization mechanisms of soil organic carbon (SOC), thebioavailability of SOC linked to soil physical structure, microbial community structure, and functional genes remains poorly understood. This study aims to investigate the SOC division based on bioavailability differences formed by physical isolation, and to clarify the relationships of SOC bioavailability with soil elements, pore characteristics, and microbial activity. Results revealed that soil element abundances such as SOC, TN, and DOC ranked in the same order as the soil porosity as clay > silt ≥ coarse sand > fine sand in both top and sub soil. In contrast to silt and clay, which had reduced SOC bioavailability, fine sand and coarse sand had dramatically enhanced SOC bioavailability compared to the bulk soil. The bacterial and fungal community structure was significantly influenced by particle size, porosity, and soil elements. Copiotrophic bacteria and functional genes were more prevalent in fine sand than clay, which also contained more oligotrophic bacteria. The SOC bioavailability was positively correlated with abundances of functional genes, C degradation genes, and copiotrophic bacteria, but negatively correlated with abundances of soil elements, porosity, oligotrophic bacteria, and microbial biomass (p < 0.05). This indicated that the soil physical structure divided SOC into pools with varying levels of bioavailability, with sand fractions having more bioavailable organic carbon than finer fractions. Copiotrophic Proteobacteria and oligotrophic Acidobacteria, Firmicutes, and Gemmatimonadetes made up the majority of the bacteria linked to SOC mineralization. Additionally, the fungi Mortierellomycota and Mucoromycota, which are mostly involved in SOC mineralization, may have the potential for oligotrophic metabolism. Our results indicated that particle-size fractionation could influence the SOC bioavailability by restricting SOC accessibility and microbial activity, thus having a significant impact on sustaining soil organic carbon reserves in temperate agricultural ecosystems, and provided a new research direction for organic carbon stability.

Genome-Wide Association Study Identifies Pharmacogenomic Variants Associated With Metformin Glycemic Response in African American Patients With Type 2 Diabetes.

OBJECTIVE: Metformin is the most common treatment for type 2 diabetes (T2D). However, there have been no pharmacogenomic studies for T2D in which a population of color was used in the discovery analysis. This study sought to identify genomic variants associated with metformin response in African American patients with diabetes. RESEARCH DESIGN AND METHODS: Patients in the discovery set were adult, African American participants from the Diabetes Multi-omic Investigation of Drug Response (DIAMOND), a cohort study of patients with T2D from a health system serving southeast Michigan. DIAMOND participants had genome-wide genotype data and longitudinal electronic records of laboratory results and medication fills. The genome-wide discovery analysis identified polymorphisms correlated to changes in glycated hemoglobin (HbA1c) levels among individuals on metformin monotherapy. Lead associations were assessed for replication in an independent cohort of African American participants from Kaiser Permanente Northern California (KPNC) and in European American participants from DIAMOND. RESULTS: The discovery set consisted of 447 African American participants, whereas the replication sets included 353 African American KPNC participants and 466 European American DIAMOND participants. The primary analysis identified a variant, rs143276236, in the gene ARFGEF3, which met the threshold for genome-wide significance, replicated in KPNC African Americans, and was still significant in the meta-analysis (P = 1.17 × 10-9). None of the significant discovery variants replicated in European Americans DIAMOND participants. CONCLUSIONS: We identified a novel and biologically plausible genetic variant associated with a change in HbA1c levels among African American patients on metformin monotherapy. These results highlight the importance of diversity in pharmacogenomic studies.

Gene expression in African Americans, Puerto Ricans and Mexican Americans reveals ancestry-specific patterns of genetic architecture.

We explored ancestry-related differences in the genetic architecture of whole-blood gene expression using whole-genome and RNA sequencing data from 2,733 African Americans, Puerto Ricans and Mexican Americans. We found that heritability of gene expression significantly increased with greater proportions of African genetic ancestry and decreased with higher proportions of Indigenous American ancestry, reflecting the relationship between heterozygosity and genetic variance. Among heritable protein-coding genes, the prevalence of ancestry-specific expression quantitative trait loci (anc-eQTLs) was 30% in African ancestry and 8% for Indigenous American ancestry segments. Most anc-eQTLs (89%) were driven by population differences in allele frequency. Transcriptome-wide association analyses of multi-ancestry summary statistics for 28 traits identified 79% more gene-trait associations using transcriptome prediction models trained in our admixed population than models trained using data from the Genotype-Tissue Expression project. Our study highlights the importance of measuring gene expression across large and ancestrally diverse populations for enabling new discoveries and reducing disparities.

Differences in Self-Reported Food Allergy and Food-Associated Anaphylaxis by Race and Ethnicity Among SAPPHIRE Cohort Participants.

BACKGROUND: Although food allergies are considered common, relatively little is known about disparities in food allergy by race in the United States. OBJECTIVE: To evaluate differences in reported food allergy and food-associated anaphylaxis among individuals enrolled in a longitudinal cohort study from metropolitan Detroit, Michigan. METHODS: Participants in the Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity (SAPPHIRE) were asked about food allergies, including the inciting food and associated symptoms. Individuals were considered to have food-associated anaphylaxis if symptoms coincided with established clinical criteria. Logistic regression was used to assess whether race difference persisted after adjusting for and stratifying by potential confounders. African genetic ancestry was individually estimated among African American SAPPHIRE participants to assess whether ancestry was associated with food allergy. RESULTS: Within the SAPPHIRE cohort, African American participants were significantly more likely to report food allergy (26.1% vs 17%; P = 3.47 × 10-18) and have food-associated anaphylactic symptoms (12.7% vs 7%; P = 4.65 × 10-14) when compared with European American participants. Allergy to seafood accounted for the largest difference (13.1% vs 4.6%; P = 1.38 × 10-31). Differences in food allergy by race persisted after adjusting for potential confounders including asthma status. Among African American participants, the proportion of African ancestry was not associated with any outcome evaluated. CONCLUSION: Compared with European Americans, African Americans appear to be at higher risk for developing food allergy and food-associated anaphylaxis, particularly with regard to seafood allergy. The lack of association with genetic ancestry suggests that socioenvironmental determinants may play a role in these disparities.

Identification of Genetic Variation Influencing Metformin Response in a Multiancestry Genome-Wide Association Study in the Diabetes Prevention Program (DPP).

Genome-wide significant loci for metformin response in type 2 diabetes reported elsewhere have not been replicated in the Diabetes Prevention Program (DPP). To assess pharmacogenetic interactions in prediabetes, we conducted a genome-wide association study (GWAS) in the DPP. Cox proportional hazards models tested associations with diabetes incidence in the metformin (MET; n = 876) and placebo (PBO; n = 887) arms. Multiple linear regression assessed association with 1-year change in metformin-related quantitative traits, adjusted for baseline trait, age, sex, and 10 ancestry principal components. We tested for gene-by-treatment interaction. No significant associations emerged for diabetes incidence. We identified four genome-wide significant variants after correcting for correlated traits (P < 9 × 10-9). In the MET arm, rs144322333 near ENOSF1 (minor allele frequency [MAF]AFR = 0.07; MAFEUR = 0.002) was associated with an increase in percentage of glycated hemoglobin (per minor allele, ß = 0.39 [95% CI 0.28, 0.50]; P = 2.8 × 10-12). rs145591055 near OMSR (MAF = 0.10 in American Indians) was associated with weight loss (kilograms) (per G allele, ß = -7.55 [95% CI -9.88, -5.22]; P = 3.2 × 10-10) in the MET arm. Neither variant was significant in PBO; gene-by-treatment interaction was significant for both variants [P(G×T) < 1.0 × 10-4]. Replication in individuals with diabetes did not yield significant findings. A GWAS for metformin response in prediabetes revealed novel ethnic-specific associations that require further investigation but may have implications for tailored therapy.

Overexpression of pdeR promotes biofilm formation of Paracoccus denitrificans by promoting ATP production and iron acquisition.

Bacterial biofilms are ubiquitous in natural environments and play an essential role in bacteria's environmental adaptability. Quorum sensing (QS), as the main signaling mechanism bacteria used for cell-to-cell communication, plays a key role in bacterial biofilm formation. However, little is known about the role of QS circuit in the N-transformation type strain, Paracoccus denitrificans, especially for the regulatory protein PdeR. In this study, we found the overexpression of pdeR promoted bacterial aggregation and biofilm formation. Through RNA-seq analysis, we demonstrated that PdeR is a global regulator which could regulate 656 genes expression, involved in multiple metabolic pathways. Combined with transcriptome as well as biochemical experiments, we found the overexpressed pdeR mainly promoted the intracellular degradation of amino acids and fatty acids, as well as siderophore biosynthesis and transportation, thus providing cells enough energy and iron for biofilm development. These results revealed the underlying mechanism for PdeR in biofilm formation of P. denitrificans, adding to our understanding of QS regulation in biofilm development.

Genome-wide association study in minority children with asthma implicates DNAH5 in bronchodilator responsiveness.

Variability in response to short-acting ß2-agonists (e.g., albuterol) among patients with asthma from diverse racial/ethnic groups may contribute to asthma disparities. We sought to identify genetic variants associated with bronchodilator response (BDR) to identify potential mechanisms of drug response and risk factors for worse asthma outcomes. Genome-wide association studies of bronchodilator response (BDR) were performed using TOPMed Whole Genome Sequencing data of the Asthma Translational Genomic Collaboration (ATGC), which corresponded to 1136 Puerto Rican, 656 Mexican and 4337 African American patients with asthma. With the population-specific GWAS results, a trans-ethnic meta-analysis was performed to identify BDR-associated variants shared across the three populations. Replication analysis was carried out in three pediatric asthma cohorts, including CAMP (Childhood Asthma Management Program; n = 560), GACRS (Genetics of Asthma in Costa Rica Study; n = 967) and HPR (Hartford-Puerto Rico; n = 417). A genome-wide significant locus (rs35661809; P = 3.61 × 10-8) in LINC02220, a non-coding RNA gene, was identified in Puerto Ricans. While this region was devoid of protein-coding genes, capture Hi-C data showed a distal interaction with the promoter of the DNAH5 gene in lung tissue. In replication analysis, the GACRS cohort yielded a nominal association (1-tailed P < 0.05). No genetic variant was associated with BDR at the genome-wide significant threshold in Mexicans and African Americans. Our findings help inform genetic underpinnings of BDR for understudied minority patients with asthma, but the limited availability of genetic data for racial/ethnic minority children with asthma remains a paramount challenge.

Antimicrobial peptide antibiotics inhibit aerobic denitrification via affecting electron transportation and remolding carbon metabolism.

The harmful effects of antibiotics on biological denitrification have attracted widespread attention due to their excessive usage. Polymyxin B (PMB) as the typical antimicrobial peptides having been regarded as the "last hope" for treatment of multidrug-resistance bacteria, has also been detected in wastewater. However, little is known about the influence of PMB on aerobic denitrification. In this study, the impact of PMB on aerobic denitrification performance was investigated. Results showed 0.50 mg/L PMB decreased nitrate removal efficiency from 97.4% to 85.3%, and drove denitrifiers to transform more nitrate to biomass instead of producing gas-N. The live/dead staining method showed PMB damaged bacterial membrane. Transcriptome analysis further indicated the key enzymes participating in denitrification and aerobic respiratory chains were suppressed by PMB. To resist the PMB stress, denitrifiers formed thicker biofilm to protect cells from PMB damaging and thus remodeling the central carbon metabolism. Further investigation revealed denitrifiers have different preference on various carbon sources when PMB is present. Subsequently, the underlying mechanism of the distinctive carbon sources preference was explored by the combination of transcriptome and metabolism analysis. Overall, our data suggested denitrifiers have distinctive carbon sources preference under PMB treatment conditions, reminding us that carbon source selection should be cautious in practical applications.

A Highly Efficient Ion and Electron Conductive Interlayer To Achieve Low Self-Discharge of Lithium-Sulfur Batteries.

The practical use of lithium-sulfur (Li-S) batteries is limited by serious self-discharge, fast capacity loss, and severe lithium anode erosion due to the shuttling of lithium polysulfides (LiPSs). Herein, we developed a highly efficient ion and electron conductive interlayer composed of Ti2(SO4)3/carbon composite layer-coated Li1.3Al0.3Ti1.7(PO4)3 (CLATP) and graphene to effectively block the diffusion of polysulfide anions but allow rapid Li ion transfer, therefore significantly inhibiting the self-discharge and boosting the cyclic stability of Li-S batteries. The Ti2(SO4)3/carbon thin protective layer endows an optimized adsorption ability toward LiPSs and avoids the side reactions between LATP and LiPSs. The high electronic conductivity of graphene and high ionic conductivity of CLATP ensures the hybrid interlayer rapid electron and fast Li ion transport. As a result, the Li-S battery with the hybrid interlayer shows a high discharge capacity of 671 mAh g-1 after 500 cycles with an extremely low capacity fading of 0.022% per cycle at 1 C. Moreover, the battery shows no self-discharge even after rest for 12 days. This work opens up a new way for the design of functional separators to significantly improve the electrochemical performance of Li-S batteries.

Predicting death from COVID-19 using pre-existing conditions: implications for vaccination triage.

INTRODUCTION: Global shortages in the supply of SARS-CoV-2 vaccines have resulted in campaigns to first inoculate individuals at highest risk for death from COVID-19. Here, we develop a predictive model of COVID-19-related death using longitudinal clinical data from patients in metropolitan Detroit. METHODS: All individuals included in the analysis had a laboratory-confirmed SARS-CoV-2 infection. Thirty-six pre-existing conditions with a false discovery rate p<0.05 were combined with other demographic variables to develop a parsimonious prediction model using least absolute shrinkage and selection operator regression. The model was then prospectively validated in a separate set of individuals with confirmed COVID-19. RESULTS: The study population consisted of 15 502 individuals with laboratory-confirmed SARS-CoV-2. The main prediction model was developed using data from 11 635 individuals with 709 reported deaths (case fatality ratio 6.1%). The final prediction model consisted of 14 variables with 11 comorbidities. This model was then prospectively assessed among the remaining 3867 individuals (185 deaths; case fatality ratio 4.8%). When compared with using an age threshold of 65 years, the 14-variable model detected 6% more of the individuals who would die from COVID-19. However, below age 45 years and its risk equivalent, there was no benefit to using the prediction model over age alone. DISCUSSION: Using a prediction model, such as the one described here, may help identify individuals who would most benefit from COVID-19 inoculation, and thereby may produce more dramatic initial drops in deaths through targeted vaccination.