Application of an optimized marker amplification protocol in immunohistochemistry — a valuable tool for visualizing antigenic sites of low signal strength or sparse distribution

Amplification of immunohistochemical markers received considerable attention during the 1980s and 1990s. The amplification approach was largely abandoned following the development of antigen retrieval and reporter amplification techniques, because the latter were incorporated more easily into high throughput automated procedures in industrial and diagnostic laboratories. There remain, however, a number of instances where marker amplification still has much to offer. Consequently, we examined experimentally the utility of an optimized marker amplification technique in diagnostically relevant tissue where either the original signal strength was low or positive sites were visible, but sparsely distributed. Marker amplification in the former case not only improved the visibility of existing positive sites, but also revealed additional sites that previously were undetectable. In the latter case, positive sites were rendered more intense and therefore more easily seen during low magnification examination of large areas of tissue.     

EFFECT OF VITAMIN E SUPPLEMENTATION AND PARTIAL SUBSTITUTION OF POLY- WITH MONO-UNSATURATED FATTY ACIDS IN PIG DIETS ON MUSCLE,AND MICROSOME EXTRACT a-TOCOPHEROL CONCENTRATION AND LIPID OXIDATION

The experiment was organized in a 3×2 factorial arrangement with three dietary fat blends and a basal (20 mg kg^?1 diet) or supplemented (220 mg kg^?1) level of α-tocopheryl acetate. Dietary vitamin E and monounsaturated to polyunsaturated fatty acid ratio (dietary MUFA/PUFA) affected muscle α-tocopherol concentration (α-tocopherol [log μg g^?1]=0.18 (±0.105)+0.0034 (±0.0003)·dietary α-tocopherol [mg kg^?1 diet] (P<0.0001)+0.39 (±0.122)·dietary MUFA/PUFA (P<0.0036)). An interaction between dietary α-tocopherol and dietary MUFA/PUFA exists for microsome α-tocopherol concentration (α-tocopherol [log μg g^?1]=1.14 (±0.169) (P<0.0001)+0.0056 (±0.00099)·dietary α-tocopherol [mg kg^?1 diet] (P<0.0001)+0.54 (±0.206)·dietary MUFA/PUFA (P<0.0131)?0.0033 (±0.0011)·dietary α-tocopherol [mg kg^?1)]×dietary MUFA/PUFA (P<0.0067)), and hexanal concentration in meat (hexanal [ng·g^?1]=14807.9 (±1489.8)?28.8 (±10.6) dietary α-tocopherol [mg·kg^?1] (P<0.01)?8436.6 (±1701.6)·dietary MUFA/PUFA (P<0.001)+24.0 (±11.22)·dietary α-tocopherol·dietary MUFA/PUFA (P<0.0416)). It is concluded that partial substitution of dietary PUFA with MUFA lead to an increase in the concentration of α-tocopherol in muscle and microsome extracts. An interaction between dietary α-tocopherol and fatty acids exists, in which at low level of dietary vitamin E inclusion, a low MUFA/PUFA ratio leads to a reduction in the concentration of α-tocopherol in microsome extracts and a concentration of hexanal in meat above the expected values.     

Quirks of dye nomenclature. 5. Rhodamines

Rhodamines were first produced in the late 19^th century, when they constituted a new class of synthetic dyes. These compounds since have been used to color many things including cosmetics, inks, textiles, and in some countries, food products. Certain rhodamine dyes also have been used to stain biological specimens and currently are widely used as fluorescent probes for mitochondria in living cells. The early history and current biological applications are sketched briefly and an account of the ambiguities, complications and confusions concerning dye identification and nomenclature are discussed.     

Quirks of dye nomenclature. 6. Malachite green

Malachite green was discovered independently by two researchers in Germany in the 19^th century and found immediate employment as a dye and a pigment. Subsequently, other uses, such as staining biological specimens, emerged. A much later application was the control of fungal and protozoan infections in fish, for which the dye remains popular, although illegal in many countries owing to a variety of toxicity problems. In solution, malachite green can exist as five different species depending on the pH. The location of the positive charge of the colored cation on a carbon atom or a nitrogen atom is still debated. The original names of this dye, and their origins, are briefly surveyed.     

Phylogeny of lobose amoebae based on actin and small-subunit ribosomal RNA genes

Lobose amoebae are abundant free-living protists and important pathogenic agents, yet their evolutionary history and position in the universal tree of life are poorly known. Molecular data for lobose amoebae are limited to a few species, and all phylogenetic studies published so far lacked representatives of many of their taxonomic groups. Here we analyze actin and small-subunit ribosomal RNA (SSU rRNA) gene sequences of a broad taxon sampling of naked, lobose amoebae. Our results support the existence of a monophyletic Amoebozoa clade, which comprises all lobose amoebae examined so far, the amitochondriate pelobionts and entamoebids, and the slime molds. Both actin and SSU rRNA phylogenies distinguish two well-defined clades of amoebae, the "Gymnamoebia sensu stricto" and the Archamoebae (pelobionts + entamoebids), and one weakly supported and ill-resolved group comprising some naked, lobose amoebae and the Mycetozoa.     

Quantitative variability of 342 plasma proteins in a human twin population

The degree and the origins of quantitative variability of most human plasma proteins are largely unknown. Because the twin study design provides a natural opportunity to estimate the relative contribution of heritability and environment to different traits in human population, we applied here the highly accurate and reproducible SWATH mass spectrometry technique to quantify 1,904 peptides defining 342 unique plasma proteins in 232 plasma samples collected longitudinally from pairs of monozygotic and dizygotic twins at intervals of 2–7 years, and proportioned the observed total quantitative variability to its root causes, genes, and environmental and longitudinal factors. The data indicate that different proteins show vastly different patterns of abundance variability among humans and that genetic control and longitudinal variation affect protein levels and biological processes to different degrees. The data further strongly suggest that the plasma concentrations of clinical biomarkers need to be calibrated against genetic and temporal factors. Moreover, we identified 13 cis‐SNPs significantly influencing the level of specific plasma proteins. These results therefore have immediate implications for the effective design of blood‐based biomarker studies.     

Bipolar gene flow in deep-sea benthic foraminifera

Despite its often featureless appearance, the deep-ocean floor includes some of the most diverse habitats on Earth. However, the accurate assessment of global deep-sea diversity is impeded by a paucity of data on the geographical ranges of bottom-dwelling species, particularly at the genetic level. Here, we present molecular evidence for exceptionally wide distribution of benthic foraminifera, which constitute the major part of deep-sea meiofauna. Our analyses of nuclear ribosomal RNA genes revealed high genetic similarity between Arctic and Antarctic populations of three common deep-sea foraminiferal species (Epistominella exigua, Cibicides wuellerstorfi and Oridorsalis umbonatus), separated by distances of up to 17, 000 km. Our results contrast with the substantial level of cryptic diversity usually revealed by molecular studies, of shallow-water benthic and planktonic marine organisms. The very broad ranges of the deep-sea foraminifera that we examined support the hypothesis of global distribution of small eukaryotes and suggest that deep-sea biodiversity may be more modest at global scales than present estimates suggest.     

Impact of QTL properties on the accuracy of multi-breed genomic prediction

Background

Although simulation studies show that combining multiple breeds in one reference population increases accuracy of genomic prediction, this is not always confirmed in empirical studies. This discrepancy might be due to the assumptions on quantitative trait loci (QTL) properties applied in simulation studies, including number of QTL, spectrum of QTL allele frequencies across breeds, and distribution of allele substitution effects. We investigated the effects of QTL properties and of including a random across- and within-breed animal effect in a genomic best linear unbiased prediction (GBLUP) model on accuracy of multi-breed genomic prediction using genotypes of Holstein-Friesian and Jersey cows.

Methods

Genotypes of three classes of variants obtained from whole-genome sequence data, with moderately low, very low or extremely low average minor allele frequencies (MAF), were imputed in 3000 Holstein-Friesian and 3000 Jersey cows that had real high-density genotypes. Phenotypes of traits controlled by QTL with different properties were simulated by sampling 100 or 1000 QTL from one class of variants and their allele substitution effects either randomly from a gamma distribution, or computed such that each QTL explained the same variance, i.e. rare alleles had a large effect. Genomic breeding values for 1000 selection candidates per breed were estimated using GBLUP modelsincluding a random across- and a within-breed animal effect.

Results

For all three classes of QTL allele frequency spectra, accuracies of genomic prediction were not affected by the addition of 2000 individuals of the other breed to a reference population of the same breed as the selection candidates. Accuracies of both single- and multi-breed genomic prediction decreased as MAF of QTL decreased, especially when rare alleles had a large effect. Accuracies of genomic prediction were similar for the models with and without a random within-breed animal effect, probably because of insufficient power to separate across- and within-breed animal effects.

Conclusions

Accuracy of both single- and multi-breed genomic prediction depends on the properties of the QTL that underlie the trait. As QTL MAF decreased, accuracy decreased, especially when rare alleles had a large effect. This demonstrates that QTL properties are key parameters that determine the accuracy of genomic prediction.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0124-6) contains supplementary material, which is available to authorized users.