Manganese status,gut endogenous losses of manganese,and antioxidant enzyme activity in rats fed varying levels of manganese and fat

We hypothesized that manganese deficient animals fed high vs moderate levels of polyunsaturated fat would either manifest evidence of increased oxidative stress or would experience compensatory changes in antioxidant enzymes and/or shifts in manganese utilization that result in decreased endogenous gut manganese losses. Rats (females in Study 1, males in Study 2,n = 8/treatment) were fed diets that contained 5 or 20% corn oil by weight and either 0.01 or 1.5 μmol manganese/g diet. In study 2,⁵⁴Mn complexed to albumin was injected into the portal vein to assess gut endogenous losses of manganese. The manganese deficient rats:

Particle size influences decay rates of environmental DNA in aquatic systems

Environmental DNA (eDNA) analysis is a powerful tool for remote detection of target organisms. However, obtaining quantitative and longitudinal information from eDNA data is challenging, requiring a deep understanding of eDNA ecology. Notably, if the various size components of eDNA decay at different rates, and we can separate them within a sample, their changing proportions could be used to obtain longitudinal dynamics information on targets. To test this possibility, we conducted an aquatic mesocosm experiment in which we separated fish-derived eDNA components using sequential filtration to evaluate the decay rate and changing proportion of various eDNA particle sizes over time. We then fit four alternative mathematical decay models to the data, building towards a predictive framework to interpret eDNA data from various particle sizes. We found that medium-sized particles (1–10 μm) decayed more slowly than other size classes (i.e., <1 and > 10 μm), and thus made up an increasing proportion of eDNA particles over time. We also observed distinct eDNA particle size distribution (PSD) between our Common carp and Rainbow trout samples, suggesting that target-specific assays are required to determine starting eDNA PSDs. Additionally, we found evidence that different sizes of eDNA particles do not decay independently, with particle size conversion replenishing smaller particles over time. Nonetheless, a parsimonious mathematical model where particle sizes decay independently best explained the data. Given these results, we suggest a framework to discern target distance and abundance with eDNA data by applying sequential filtration, which theoretically has both metabarcoding and single-target applications.     

Expression of wild-type GBSS transgenes in the off-spring of partially and fully complementedamylose-free transformants of potato

Theamylose-free (amf) potato mutant can easily be complemented through introduction of the wild-type gene coding for granule-bound starch synthase (GBSS). After iodine staining the starch of theamf mutant is red whereas that of the wild type and the complementedamf mutant is blue. The level of complementation of selected transformants and their sexual off-spring after backcrossing withamf was investigated using sporophytic tuber cells and gametophytic microspore cells. Two diploid and two tetraploid transformants with full complementation demonstrated the expected segregation patterns of 1:1 (one active insert) or 3:1 (two independently segregating active inserts) in the microspores and in the F1 offspring based on staining of tubers. All expected genotypes in the F1 generation were found, based on microspore segregation patterns of the individual F1 plants. Two transformants with partial complementation (mixed phenotypes) were investigated. One of them, B1, was tetraploid and duplex for the GBSS insert, which had originated through mitotic doubling of the transformed diploid cells. In the F1 generation three phenotypic classes were found:amf, fully complemented and partially complemented. The latter two classes exist independently of a simplex or duplex gene status. The second transformant with partial complementation, B10, appeared to have a complex molecular composition. One cluster of five transgenes caused the partial complementation. Fully and partially complemented phenotypic classes were found after crossing B10 with theamf mutant. Indications were found that the ploidy level of the tissue in which the genes were introduced and expressed played an important role. Firstly, partial complementation was found after transformation of the diploid and not of the tetraploidamf genotypes. Secondly, the level of complementation was higher in tissue with lower ploidy levels, as illustrated by the colour of the starch inin vitro tubers (2x–4x cells) versus field-grown tubers (16x–64x).     

Increased signal complexity is associated with increased mating success

The evolution of complex signals has often been explored by testing multiple functional hypotheses regarding how independent signal components provide selective benefits to offset the costs of their production. In the present study, we take a different approach by exploring the function of complexity per se. We test the hypothesis that increased vibratory signal complexity—based on both proportional and temporal patterning—provides selective benefits to courting male Schizocosa stridulans wolf spiders. In support of this hypothesis, all of our quantified metrics of vibratory signal complexity predicted the mating success of male S. stridulans. The rate of visual signalling, which is mechanistically tied to vibratory signal production, was also associated with mating success. We additionally found evidence that males can dynamically adjust the complexity of their vibratory signalling. Together, our results suggest that complexity per se may be a target of female choice.     

Experimental evolution of a pheromone signal

Sexual signals are important in speciation, but understanding their evolution is complex as these signals are often composed of multiple, genetically interdependent components. To understand how signals evolve, we thus need to consider selection responses in multiple components and account for the genetic correlations among components. One intriguing possibility is that selection changes the genetic covariance structure of a multicomponent signal in a way that facilitates a response to selection. However, this hypothesis remains largely untested empirically. In this study, we investigate the evolutionary response of the multicomponent female sex pheromone blend of the moth Heliothis subflexa to 10 generations of artificial selection. We observed a selection response of about three‐quarters of a phenotypic standard deviation in the components under selection. Interestingly, other pheromone components that are biochemically and genetically linked to the components under selection did not change. We also found that after the onset of selection, the genetic covariance structure diverged, resulting in the disassociation of components under selection and components not under selection across the first two genetic principle components. Our findings provide rare empirical support for an intriguing mechanism by which a sexual signal can respond to selection without possible constraints from indirect selection responses.     

A recombinant monoclonal-based Taenia antigen assay that reflects disease activity in extra-parenchymal neurocysticercosis

BackgroundAntigen tests for diagnosis and disease monitoring in some types of neurocysticercosis (NCC) are useful but access to testing has been limited by availability of proprietary reagents and/or kits.Methods/Principal findingsThree previously identified IgM-secreting hybridomas whose IgM products demonstrated specificity to Taenia solium underwent variable heavy and light chain sequencing and isotype conversion to mouse IgG. Screening of these recombinantly expressed IgG anti-Ts hybridomas, identified one (TsG10) with the highest affinity to crude Taenia antigen. TsG10 was then used as a capture antibody in a sandwich antigen detection immunoassay in combination with either a high titer polyclonal anti-Ts antibody or with biotinylated TsG10 (termed TsG10*bt). Using serum, plasma, and CSF samples from patients with active NCC and those from NCC-uninfected patients, ROC curve analyses demonstrated that the TsG10-TsG10-*bt assay achieved a 98% sensitivity and 100% specificity in detecting samples known to be antigen positive and outperformed the polyclonal based assay (sensitivity of 93% with 100% specificity). By comparing levels of Ts antigen (Ag) in paired CSF (n = 10) or plasma/serum (n = 19) samples from well-characterized patients with extra-parenchymal NCC early in infection and at the time of definitive cure, all but 2 (1 from CSF and 1 from plasma) became undetectable. There was a high degree of correlation (r = 0.98) between the Ag levels detected by this new assay and levels found by a commercial assay. Pilot studies indicate that this antigen can be detected in the urine of patients with active NCC.Conclusions/SignificanceA newly developed recombinant monoclonal antibody-based Ts Ag detection immunoassay is extremely sensitive in the detection of extra-parenchymal NCC and can be used to monitor the success of treatment in the CSF, serum/plasma and urine. The ability to produce recombinant TsG10 at scale should enable use of this antigen detection immunoassay wherever NCC is endemic.Clinical Trial RegistrationClinicalTrials.gov Identifiers: {"type":"clinical-trial","attrs":{"text":"NCT00001205","term_id":"NCT00001205"}}NCT00001205 - & {"type":"clinical-trial","attrs":{"text":"NCT00001645","term_id":"NCT00001645"}}NCT00001645.     

Proteomics and ovarian cancer: Integrating proteomics information into clinical care

The power of proteomics allows unparalleled opportunity to query the molecular mechanisms of a malignant cell and the tumor microenvironment in patients with ovarian cancer and other solid tumors. This information has given us insight into the perturbations of signaling pathways within tumor cells and has aided the discovery of new drug targets for the tumor and possible prognostic indicators of outcome and disease response to therapy. Proteomics analysis of serum and ascites has also given us sources with which to discover possible early markers for the presence of new disease and for the progression of established cancer throughout the course of treatment. Unfortunately, this wealth of information has yielded little to date in changing the clinical care of these patients from a diagnostic, prognostic, or treatment perspective. The rational examination and translation of proteomics data in the context of past clinical trials and the design of future clinical trials must occur before we can march forward into the future of personalized medicine.     

Plant rhizosphere influence on microbial C metabolism: the role of elevated CO2, N availability and root stoichiometry

Microbial decomposer C metabolism is considered a factor controlling soil C stability, a key regulator of global climate. The plant rhizosphere is now recognized as a crucial driver of soil C dynamics but specific mechanisms by which it can affect C processing are unclear. Climate change could affect microbial C metabolism via impacts on the plant rhizosphere. Using continuous ¹³C labelling under controlled conditions that allowed us to quantify SOM derived-C in all pools and fluxes, we evaluated the microbial metabolism of soil C in the rhizosphere of a C4 native grass exposed to elevated CO₂ and under variation in N concentrations in soil and in plant root C:N stoichiometry. Our results demonstrated that this plant can influence soil C metabolism and further, that elevated CO₂ conditions can alter this role by increasing microbial C efficiency as indicated by a reduction in soil-derived C respiration per unit of soil C-derived microbial biomass. Moreover, under elevated CO₂ increases in soil N, and notably, root tissue N concentration increased C efficiency, suggesting elevated CO₂ shifted the stoichiometric balance so N availability was a more critical factor regulating efficiency than under ambient conditions. The root C:N stoichiometry effect indicates that plant chemical traits such as root N concentration are able to influence the metabolism of soil C and that elevated CO₂ conditions can modulate this role. Increased efficiency in soil C use was associated with negative rhizosphere priming and we hypothesize that the widely observed phenomenon of rhizosphere priming may result, at least in part, from changes in the metabolic efficiency of microbial populations. Observed changes in the microbial community support that shifting microbial populations were a contributing factor to the observed metabolic responses. Our case study points at greater efficiency of the SOM-degrading populations in a high CO₂, high N world, potentially leading to greater C storage of microbially assimilated C in soil.