Effect of increasing the time between slurry application and first rainfall event on phosphorus concentrations in runoff

Publication history: Accepted - 26 May 2021; Published online - 12 August 2021.Minimizing slurry phosphorus (P) losses in runoff requires careful management in the context of both soil P surpluses and changing patterns in rainfall. Increasing the time interval between slurry application and the first rainstorm event is known to reduce P loss in runoff although the risk period for elevated P concentrations in runoff can extend for weeks. This study investigated the impact of increasing the time interval between slurry application and first rainstorm event on P concentrations in runoff. Simulated rainfall (40 mm h−1) was applied at 2, 4, 10, 18, 30 and 49 days after dairy slurry was surface-applied to a grassland sward in Ireland. Increasing time to runoff resulted in a decrease in dissolved reactive P concentrations from 5.0 to 1.0 mg P L−1 and a P signal in runoff for 18 days. Beyond 18 days, elevated P concentrations were observed in runoff collected from natural rainfall that preceded the day 49 rainstorm event. A published surface phosphorus and runoff model (SurPhos) was used to understand the slurry P dynamics controlling P interactions with runoff. Dissolved reactive P in runoff was predicted with accuracy by SurPhos, R2 = .89. The SurPhos model implied thatslurry P mineralization occurred during the experimental period that resulted in a small spike in P concentrations beyond the defined risk period. This study shows that the experimental data have the potential to be extrapolated to different weather scenarios using SurPhos and could test when and where slurry P could be most safely spread.Open access funding provided by IReL. WOA Institution: University College Dublin Blended DEAL: IReL

Pseudomonas aeruginosa 4-Amino-4-Deoxychorismate Lyase: Spatial Conservation of an Active Site Tyrosine and Classification of Two Types of Enzyme

4-Amino-4-deoxychorismate lyase (PabC) catalyzes the formation of 4-aminobenzoate, and release of pyruvate, during folate biosynthesis. This is an essential activity for the growth of Gram-negative bacteria, including important pathogens such as Pseudomonas aeruginosa. A high-resolution (1.75 Å) crystal structure of PabC from P. aeruginosa has been determined, and sequence-structure comparisons with orthologous structures are reported. Residues around the pyridoxal 5′-phosphate cofactor are highly conserved adding support to aspects of a mechanism generic for enzymes carrying that cofactor. However, we suggest that PabC can be classified into two groups depending upon whether an active site and structurally conserved tyrosine is provided from the polypeptide that mainly forms an active site or from the partner subunit in the dimeric assembly. We considered that the conserved tyrosine might indicate a direct role in catalysis: that of providing a proton to reduce the olefin moiety of substrate as pyruvate is released. A threonine had previously been suggested to fulfill such a role prior to our observation of the structurally conserved tyrosine. We have been unable to elucidate an experimentally determined structure of PabC in complex with ligands to inform on mechanism and substrate specificity. Therefore we constructed a computational model of the catalytic intermediate docked into the enzyme active site. The model suggests that the conserved tyrosine helps to create a hydrophobic wall on one side of the active site that provides important interactions to bind the catalytic intermediate. However, this residue does not appear to participate in interactions with the C atom that undergoes an sp2 to sp3 conversion as pyruvate is produced. The model and our comparisons rather support the hypothesis that an active site threonine hydroxyl contributes a proton used in the reduction of the substrate methylene to pyruvate methyl in the final stage of the mechanism

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

The omit map for PLP and Lys140 from subunit A.

<p>|(<i>F_o</i>)-(<i>F_c</i>)| difference density contoured at 3σ (green chicken wire). Selected hydrogen bonding associations between the protein, two water molecules (red spheres) and PLP are depicted as dashed lines. A * marks Tyr92 as contributed from subunit B. The side chain of Glu173 displays two rotamers with only one shown.</p

Structure-based alignment of <i>Pa</i>PabC and <i>Lp</i>PabC.

<p>Residues encased in black are strictly conserved. Red stars indicate the tyrosine residues at Position I (<i>Pa</i>PabC Y92) and Position II (<i>Lp</i>PabC Y144). Triangles mark residues that are discussed in the text. Red triangles identify Lys140 and residues that interact directly with the Lys140-PLP adduct; yellow triangles mark residues that contribute to the organization of the active site or that participate in solvent mediated interactions between the protein and the cofactor.</p

Structural conservation of tyrosine in the PabC active site.

<p>PLP is shown in the same manner as <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0024158#pone-0024158-g002" target="_blank">Figure 2</a>. Left panel. A structural overlay of <i>Pa</i>PabC (green C atoms) and <i>Ec</i>PabC (blue C atoms). Here, Tyr92 and Tyr109, which represent position I, are contributed from the partner subunit. Centre panel. <i>Lp</i>PabC. Right panel. <i>Tt</i>PabC. Residue Thr27 displays two rotamers. In the <i>Lp</i>PabC and <i>Tt</i>PabC structures, Tyr144 and Tyr130 respectively represent position II and belong to the same subunit that forms the PLP-binding site.</p

Ribbon diagram of the <i>Pa</i>PabC monomer (β-sheet is shown in purple, α-helix in yellow).

<p>Domain I is formed by α-helices 1–3 and the anti-parallel β-strands 1–4. Domain II is formed by α-helices 4–8 and β-strands 5–8.</p

Crystallographic statistics.

a<p>Values in parentheses refer to the highest resolution shell (1.84−1.75 Å).</p>b<p><i>R_merge</i> = ∑<i>_hkl∑_i|</i>I<i>_i</i>(<i>hkl</i>)−hkl)><i>|/</i>∑<i>_hkl∑_i</i> I<i>_i</i>(<i>hkl</i>); where I<i>_i</i>(<i>hkl</i>) is the intensity of the <i>i</i>th measurement of reflection <i>hkl</i> and hkl)> is the mean value of I<i>_i</i>(<i>hkl</i>) for all <i>i</i> measurements.</p>c<p><i>R_cryst</i> = ∑<i>_hkl</i>||<i>F_o</i>|−|<i>F_c</i>||/∑|<i>F_o</i>|, where <i>F_o</i> is the observed structure factor and <i>F_c</i> is the calculated structure factor.</p>d<p><i>R_free</i> is the same as <i>R_cryst</i> except calculated with a subset, 5%, of data that are excluded from refinement calculations.</p

The <i>Pa</i>PabC dimer.

<p>Each subunit is depicted as a Cα trace (yellow and purple) with the PLP shown as stick model in a similar fashion to Figure 3. The N and C – terminal residue positions are labelled.</p