Aspergillomarasmine A inhibits metallo-β-lactamases by selectively sequestering Zn2+

Class B metallo-β-lactamases (MBLs) are Zn²⁺-dependent enzymes that catalyze the hydrolysis of β-lactam antibiotics to confer resistance in bacteria. Several problematic groups of MBLs belong to subclass B1, including the binuclear New Delhi MBL (NDM), Verona integrin-encoded MBL, and imipenemase-type enzymes, which are responsible for widespread antibiotic resistance. Aspergillomarasmine A (AMA) is a natural aminopolycarboxylic acid that functions as an effective inhibitor of class B1 MBLs. The precise mechanism of action of AMA is not thoroughly understood, but it is known to inactivate MBLs by removing one catalytic Zn²⁺ cofactor. We investigated the kinetics of MBL inactivation in detail and report that AMA is a selective Zn²⁺ scavenger that indirectly inactivates NDM-1 by encouraging the dissociation of a metal cofactor. To further investigate the mechanism in living bacteria, we used an active site probe and showed that AMA causes the loss of a Zn²⁺ ion from a low-affinity binding site of NDM-1. Zn²⁺-depleted NDM-1 is rapidly degraded, contributing to the efficacy of AMA as a β-lactam potentiator. However, MBLs with higher metal affinity and stability such as NDM-6 and imipenemase-7 exhibit greater tolerance to AMA. These results indicate that the mechanism of AMA is broadly applicable to diverse Zn²⁺ chelators and highlight that leveraging Zn²⁺ availability can influence the survival of MBL-producing bacteria when they are exposed to β-lactam antibiotics.     

Total cost estimation for implementing genome-enabled selection in a multi-level swine production system

Background

Determining an animal’s genetic merit using genomic information can improve estimated breeding value (EBV) accuracy; however, the magnitude of the accuracy improvement must be large enough to recover the costs associated with implementing genome-enabled selection. One way to reduce costs is to genotype nucleus herd selection candidates using a low-density chip and to use high-density chip genotyping for animals that are used as parents in the nucleus breeding herd. The objective of this study was to develop a tool to estimate the cost structure associated with incorporating genome-enabled selection into multi-level commercial breeding programs.

Results

For the purpose of this deterministic study, it was assumed that a commercial pig is created from a terminal line sire and a dam that is a cross between two maternal lines. It was also assumed that all male and female selection candidates from the 1000 sow maternal line nucleus herds were genotyped at low density and all animals used for breeding at high density. With the assumptions used in this analysis, it was estimated that genome-enabled selection costs for a maternal line would be approximately US$0.082 per weaned pig in the commercial production system. A total of US$0.164 per weaned pig is needed to incorporate genome-enabled selection into the two maternal lines. Similarly, for a 600 sow terminal line nucleus herd and genotyping only male selection candidates with the low-density panel, the cost per weaned pig in the commercial herd was estimated to be US$0.044. This means that US$0.21 per weaned pig produced at the commercial level and sired by boars obtained from the nucleus herd breeding program needs to be added to the genetic merit value in order to break even on the additional cost required when genome-enabled selection is used in both maternal lines and the terminal line.

Conclusions

By modifying the input values, such as herd size and genotyping strategy, a flexible spreadsheet tool developed from this work can be used to estimate the additional costs associated with genome-enabled selection. This tool will aid breeders in estimating the economic viability of incorporating genome-enabled selection into their specific breeding program.     

Seasonality affects leaf nutrient and condensed tannin concentration in southern African savannah browse

Trees that maintain some leaves throughout dry seasons become important ruminant browse depending on nutritive and antinutritive values. Leaves from seven tree species that maintained some leaves during the dry season were collected during dry and wet seasons and analysed for nutritive and antinutritive values. Neutral detergent fibre of leaves was either not different or less (P ≤ 0.05) during the dry season as compared to the wet season depending on species. Acid detergent fibre was either not different or greater (P ≤ 0.05) during the dry season as compared to the wet season. Crude protein and condensed tannins (CT) were either not different or less (P ≤ 0.05) during the dry season than during the wet season for the seven species. The biological activity (protein‐binding ability; PB) of the CT was highly species specific and was either not different between seasons, more bioactive during the wet season, or more bioactive during the dry season depending on the species. Based on combinations of low fibre, high protein and potentially beneficial levels of bioactive CT, Senegalia caffra, Vachellia karoo and Searsia lancea may be the most promising dry‐season browse of the species studied.     

Innate food aversions and culturally transmitted food taboos in pregnant women in rural southwest India: Separate systems to protect the fetus?

Pregnancy increases women's nutritional requirements, yet causes aversions to nutritious foods. Most societies further restrict pregnant women's diet with food taboos. Pregnancy food aversions are theorized to protect mothers and fetuses from teratogens and pathogens or increase dietary diversity in response to resource scarcity. Tests of these hypotheses have had mixed results, perhaps because many studies are in Westernized populations with reliable access to food and low exposure to pathogens. If pregnancy food aversions are adaptations, however, then they likely evolved in environments with uncertain access to food and high exposure to pathogens. Pregnancy food taboos, on the other hand, have been theorized to limit resource consumption, mark social identity, or also protect mothers and fetuses from dangerous foods. There have been few tests of evolutionary theories of culturally transmitted food taboos.We investigated these and other theories of psychophysiological food aversions and culturally transmitted food taboos among two non-Western populations of pregnant women in Mysore, India, that vary in food insecurity and exposure to infectious disease. The first was a mixed caste rural farming population (N = 72), and the second was the Jenu Kurubas, a resettled population of former hunter-gatherers (N = 30). Women rated their aversions to photos of 31 foods and completed structured interviews that assessed aversions and socially learned avoidances of foods, pathogen exposure, food insecurity, sources of culturally acquired dietary advice, and basic sociodemographic information. Aversions to spicy foods were associated with early trimester and nausea and vomiting, supporting a protective role against plant teratogens. Variation in exposure to pathogens did not explain variation in meat aversions or avoidances, however, raising some doubts about the importance of pathogen avoidance. Aversions to staple foods were common, but were not associated with resource stress, providing mixed support for the role of dietary diversification. Avoided foods outnumbered aversive foods, were believed to be abortifacients or otherwise harmful to the fetus, influenced diet throughout pregnancy, and were largely distinct from aversive foods. These results suggest that aversions target foods with cues of toxicity early in pregnancy, and taboos target suspected abortifacients throughout pregnancy.     

DNA Area and NETosis Analysis (DANA): a High-Throughput Method to Quantify Neutrophil Extracellular Traps in Fluorescent Microscope Images

Background

Neutrophil extracellular traps (NETs), extracellular structures composed of decondensed chromatin and antimicrobial molecules, are released in a process called NETosis. NETs, which are part of normal host defense, have also been implicated in multiple human diseases. Unfortunately, methods for quantifying NETs have limitations which constrain the study of NETs in disease. Establishing optimal methods for NET quantification holds the potential to further elucidate the role of NETs in normal and pathologic processes.

Results

To better quantify NETs and NET-like structures, we created DNA Area and NETosis Analysis (DANA), a novel ImageJ/Java based program which provides a simple, semi-automated approach to quantify NET-like structures and DNA area. DANA can analyze many fluorescent microscope images at once and provides data on a per cell, per image, and per sample basis. Using fluorescent microscope images of Sytox-stained human neutrophils, DANA quantified a similar frequency of NET-like structures to the frequency determined by two different individuals counting by eye, and in a fraction of the time. As expected, DANA also detected increased DNA area and frequency of NET-like structures in neutrophils from subjects with rheumatoid arthritis as compared to control subjects. Using images of DAPI-stained murine neutrophils, DANA (installed by an individual with no programming background) gave similar frequencies of NET-like structures as the frequency of NETs determined by two individuals counting by eye. Further, DANA quantified more NETs in stimulated murine neutrophils compared to unstimulated, as expected.

Conclusions

DANA provides a means to quantify DNA decondensation and the frequency of NET-like structures using a variety of different fluorescent markers in a rapid, reliable, simple, high-throughput, and cost-effective manner making it optimal to assess NETosis in a variety of conditions.

     

Leaf functional trait responses to changes in water status differ among three oak (<Emphasis Type="Italic">Quercus</Emphasis>) species

We monitored differences in rates of foliar carbon-compound increases with progressive drought as an indicator of sink limitation status and subsequent drought tolerance. We postulate that species which increase foliar carbohydrates and protein-precipitable phenolics (PPP) more quickly than related species over the same time period and drought conditions have stronger sink limitations and are therefore less drought tolerant. Quercus macrocarpa, Q. shumardii, and Q. virginiana saplings were subjected to two treatments for approximately 3.5 months: (1) watered, which received the equivalent of average weekly precipitation for College Station, TX, USA, and (2) droughted, in which precipitation was reduced by 100%. Q. virginiana’s photosynthesis (A) and stomatal conductance (g_s) were 44 and 54% greater, respectively, than the other species in the drought treatment. Q. virginiana’s g_s also increased more dramatically with watering and subsequent increases in predawn leaf water potential. This plasticity suggests Q. virginiana is best equipped to deal with sporadic rainfall events and soil moisture changes, at least in the short term. Results indicate that the three species allocate carbon from photosynthate in different ways. Q. shumardii had the most soluble sugar in its foliage but had the least PPP, while Q. virginiana and macrocarpa had more PPP and less sugar than Q. shumardii. Diameter:height growth rate was greatest in Q. shumardii. Foliar protein-precipitable phenolic content appears to be more affected by factors other than drought. Differences in species’ physiological responses to drought may result in stand composition shifts with future climate alterations.     

Functional classification of protein structures by local structure matching in graph representation

As a result of high‐throughput protein structure initiatives, over 14,400 protein structures have been solved by Structural Genomics (SG) centers and participating research groups. While the totality of SG data represents a tremendous contribution to genomics and structural biology, reliable functional information for these proteins is generally lacking. Better functional predictions for SG proteins will add substantial value to the structural information already obtained. Our method described herein, Graph Representation of Active Sites for Prediction of Function (GRASP‐Func), predicts quickly and accurately the biochemical function of proteins by representing residues at the predicted local active site as graphs rather than in Cartesian coordinates. We compare the GRASP‐Func method to our previously reported method, Structurally Aligned Local Sites of Activity (SALSA), using the Ribulose Phosphate Binding Barrel (RPBB), 6‐Hairpin Glycosidase (6‐HG), and Concanavalin A‐like Lectins/Glucanase (CAL/G) superfamilies as test cases. In each of the superfamilies, SALSA and the much faster method GRASP‐Func yield similar correct classification of previously characterized proteins, providing a validated benchmark for the new method. In addition, we analyzed SG proteins using our SALSA and GRASP‐Func methods to predict function. Forty‐one SG proteins in the RPBB superfamily, nine SG proteins in the 6‐HG superfamily, and one SG protein in the CAL/G superfamily were successfully classified into one of the functional families in their respective superfamily by both methods. This improved, faster, validated computational method can yield more reliable predictions of function that can be used for a wide variety of applications by the community.