Context-dependent effects of bluegill in experimental mesocosm communities

Most knowledge of direct and indirect effects of zooplanktivorous fish has come from studies in which a treatment with a zooplanktivore is compared to a fishless control. However, effects of a zooplanktivore may be different in the presence of other fish species because the other fish have direct and indirect effects that may alter the effects of the zooplanktivore in question. To test this hypothesis, we conducted a tank mesocosm experiment of 2×2 factorial design in which the presence and absence of bluegill (Lepomis macrochirus) were cross-classified with the presence and absence of a fish assemblage composed of western mosquitofish (Gambusia affinis) and common carp (Cyprinus carpio). The presence of bluegill decreased Daphnia, Ceriodaphnia, cyclopoid copepodids, calanoid copepodids, copepod nauplii, amphipods, gastropods, and notonectids. Daphnia, Ceriodaphnia, cyclopoid copepodids, copepod nauplii, gastropods, notonectids, Najas, and Chara were decreased and herbivorous rotifers, turbidity, chlorophyll a, total nitrogen and total phosphorus were increased in the presence of the fish assemblage. Significant bluegill×fish assemblage interaction effects were detected for Daphnia, Ceriodaphnia, cyclopoid copepodids, copepod nauplii, gastropods, and notonectids. Analysis of simple effects for these response variables revealed that all significant bluegill effects in the absence of the fish assemblage were not significant in the presence of the fish assemblage. Our results indicate that the effects of bluegill may be context dependent, or dependent upon the presence of other trophically similar fish species. Received: 3 November 1998 / Accepted: 24 September 1999     

Modelling and the monitoring of mesocosm experiments: two case studies

Mesocosm experiments have played an important role over thelast decade in increasing our understanding of marine ecosystems.Many studies use these controlled environments to examine ecosystemresponses to factors such as nutrient addition and light limitation.A few studies have been able to successfully model mesocosmexperiments using carefully designed and comprehensive modelsand experimental design. Nevertheless, it is rare for such modelsto be compared with oceanic studies, and to consider the sulphurcycle as well as the carbon and nitrogen budgets. Here we takean ecosystem model, including a dimethylsulphide loop, thathas been successfully used in modelling the evolution of theplanktonic system in a Lagrangian field experiment in the NorthAtlantic—the PRIME cruise of 1996—and apply it totwo mesocosm experiments. These were operated by two differentgroups of scientists, but in the same field station in a Norwegianfjord. The experiments were not explicitly designed with thedata requirements of any model in mind. We show that the modelis best able to simulate mesocosm data using model parameterstaken from the real ocean. However, most sensitivity tests aresignificantly less successful in the mesocosm environment thanthe real ocean, especially if the model parameters are allowedto vary in a best fit sense. The limitations of the model–mesocosmmatch highlight the importance of comprehensive monitoring ofmesocosms if they are to be useful for validating models suitablefor the open ocean.     

Threshold-free high-power methods for the ontological analysis of genome-wide gene-expression studies

Ontological analysis facilitates the interpretation of microarray data. Here we describe new ontological analysis methods which, unlike existing approaches, are threshold-free and statistically powerful. We perform extensive evaluations and introduce a new concept, detection spectra, to characterize methods. We show that different ontological analysis methods exhibit distinct detection spectra, and that it is critical to account for this diversity. Our results argue strongly against the continued use of existing methods, and provide directions towards an enhanced approach.     

Biophysical studies of phase separation integrating experimental and computational methods

Biomolecular phase separation that contributes to the formation of membraneless organelles and biomolecular condensates has recently gained tremendous attention because of the importance of these assemblies in physiology, disease, and engineering applications. Understanding and directing biomolecular phase separation requires a multiscale view of the biophysical properties of these phases. Yet, many classic tools to characterize biomolecular properties do not apply in these condensed phases. Here, we discuss insights obtained from spectroscopic methods, in particular nuclear magnetic resonance and optical spectroscopy, in understanding the molecular and atomic interactions that underlie the formation of protein-rich condensates. We also review approaches closely coupling nuclear magnetic resonance data with computational methods especially coarse-grained and all-atom molecular simulations, which provide insight into molecular features of phase separation. Finally, we point to future methodolical developments, particularly visualizing biophysical properties of condensates in cells.     

Luminescent method for experimental studies of the heart

Experiments on 20 rabbits were made to explore the fluorescent properties of a water-soluble drug pyrroloindolysin administered to the blood vessels. The fluorescent spectra were excited in the UV spectrum. The drug was rapidly accumulated by the heart, with the fluorescence being mainly seen in the structures of the interatrial septum. The data obtained point to the possibility of the use of the described method for fluorescent studies of the different parts and structures of the heart.     

Principal component analysis based methods in bioinformatics studies

In analysis of bioinformatics data, a unique challenge arises from the high dimensionality of measurements. Without loss of generality, we use genomic study with gene expression measurements as a representative example but note that analysis techniques discussed in this article are also applicable to other types of bioinformatics studies. Principal component analysis (PCA) is a classic dimension reduction approach. It constructs linear combinations of gene expressions, called principal components (PCs). The PCs are orthogonal to each other, can effectively explain variation of gene expressions, and may have a much lower dimensionality. PCA is computationally simple and can be realized using many existing software packages. This article consists of the following parts. First, we review the standard PCA technique and their applications in bioinformatics data analysis. Second, we describe recent 'non-standard' applications of PCA, including accommodating interactions among genes, pathways and network modules and conducting PCA with estimating equations as opposed to gene expressions. Third, we introduce several recently proposed PCA-based techniques, including the supervised PCA, sparse PCA and functional PCA. The supervised PCA and sparse PCA have been shown to have better empirical performance than the standard PCA. The functional PCA can analyze time-course gene expression data. Last, we raise the awareness of several critical but unsolved problems related to PCA. The goal of this article is to make bioinformatics researchers aware of the PCA technique and more importantly its most recent development, so that this simple yet effective dimension reduction technique can be better employed in bioinformatics data analysis.     

Nutrient manipulation methods for coral reef studies: A critical review and experimental field data

The results reported in this paper demonstrate suboptimal experimental designs in some of the previously published manipulative methods and provide insights for the improvement of in-situ nutrient studies on coral reefs. Overgrown 0.5-liter porous clay-pot diffusers (“mini-reefs”—following a decade of recruitment, colonization and competition) were utilized to evaluate protocols for studies of controlled nutrient enrichment on coral reefs. A commonly used fertilizer, Tree Food Stakes resulted in detrimental 11-fold and 20-fold decreases of fleshy algae and calcareous coralline algae, respectively, relative to the Control treatments; while blue-green algae (Cyanobacteria) became significantly (6 times) more abundant. Osmocote-filled mini-reefs showed no such negative differences in mortality from the Controls for any functional group. By avoiding the pitfalls of inappropriate sources of enrichment, insufficient durations of colonization/competition studies, suboptimal study areas and inadequate nutrient detection limits in future research, the potential to provide new insights into the nutrient status of coral reefs is greatly increased.     

Molecular dynamics of Emiliania huxleyi and cooccurring viruses during two separate mesocosm studies

In this study we used denaturing gradient gel electrophoresis, sequencing analysis, and analytical flow cytometry to monitor the dynamics and genetic richness of Emiliania huxleyi isolates and cooccurring viruses during two mesocosm experiments in a Norwegian fjord in 2000 and 2003. We exploited variations in a gene encoding a protein with calcium-binding motifs (GPA) and in the major capsid protein (MCP) gene to assess allelic and genotypic richness within E. huxleyi and E. huxleyi-specific viruses (EhVs), respectively. To our knowledge, this is the first report that shows the effectiveness of the GPA gene for analysis of natural communities of E. huxleyi. Our results revealed the existence of a genetically rich, yet stable E. huxleyi and EhV community in the fjordic environment. Incredibly, the same virus and host genotypes dominated in separate studies conducted 3 years apart. Both E. huxleyi-dominated blooms contained the same six E. huxleyi alleles. In addition, despite the presence of at least six and four EhV genotypes at the start of the blooms in 2000 and 2003, respectively, the same two virus genotypes dominated the naturally occurring infections during the exponential and termination phases of the blooms in both years.     

Use of "complementary methods" for experimental animal studies of digestion in the 18th and 19th centuries

The use of complementary methods to animal experiments is very old. Spallanzani (1785) apparently was the first who used such methods in his studies on digestion. In the 19th century Eberle, Pappenheim, Purkyné and others used on their studies on the process of digestion artificial chyme. On this view, Beaumont published in 1834 an interesting paper on the digestion of men after observations in vivo and parallel in vitro. All papers show, that the using of complementary methods to animal experiments was not unusual in the 19th century.     

Machine learning methods for microbiome studies

Researches on the microbiome have been actively conducted worldwide and the results have shown human gut bacterial environment significantly impacts on immune system, psychological conditions, cancers, obesity, and metabolic diseases. Thanks to the development of sequencing technology, microbiome studies with large number of samples are eligible on an acceptable cost nowadays. Large samples allow analysis of more sophisticated modeling using machine learning approaches to study relationships between microbiome and various traits. This article provides an overview of machine learning methods for non-data scientists interested in the association analysis of microbiomes and host phenotypes. Once genomic feature of microbiome is determined, various analysis methods can be used to explore the relationship between microbiome and host phenotypes that include penalized regression, support vector machine (SVM), random forest, and artificial neural network (ANN). Deep neural network methods are also touched. Analysis procedure from environment setup to extract analysis results are presented with Python programming language.     

Genotype relative risks: methods for design and analysis of candidate-gene association studies.

Design and analysis methods are presented for studying the association of a candidate gene with a disease by using parental data in place of nonrelated controls. This alternative design eliminates spurious differences in allele frequencies between cases and nonrelated controls resulting from different ethnic origins and population stratification for these two groups. We present analysis methods which are based on two genetic relative risks: (1) the relative risk of disease for homozygotes with two copies of the candidate gene versus homozygotes without the candidate gene and (2) the relative risk for heterozygotes with one copy of the candidate gene versus homozygotes without the candidate gene. In addition to estimating the magnitude of these relative risks, likelihood methods allow specific hypotheses to be tested, namely, a test for overall association of the candidate gene with disease, as well as specific genetic hypotheses, such as dominant or recessive inheritance. Two likelihood methods are presented: (1) a likelihood method appropriate when Hardy-Weinberg equilibrium holds and (2) a likelihood method in which we condition on parental genotype data when Hardy-Weinberg equilibrium does not hold. The results for the relative efficiency of these two methods suggest that the conditional approach may at times be preferable, even when equilibrium holds. Sample-size and power calculations are presented for a multitiered design. The purpose of tier 1 is to detect the presence of an abnormal sequence for a postulated candidate gene among a small group of cases. The purpose of tier 2 is to test for association of the abnormal variant with disease, such as by the likelihood methods presented. The purpose of tier 3 is to confirm positive results from tier 2. Results indicate that required sample sizes are smaller when expression of disease is recessive, rather than dominant, and that, for recessive disease and large relative risks, necessary sample sizes may be feasible, even if only a small percentage of the disease can be attributed to the candidate gene.     

Share the details of your experimental methods

Incomplete methods sections have made it difficult for researchers to replicate and build on the work of others, contributing to problems in reproducibility. It is important to increase the level of detail in our methods sections and to share step-by-step protocols in protocol repositories or journals. Request a Protocol is a new feature in Molecular Biology of the Cell that allows readers to request detailed protocols directly from the methods section of the research article, with links between the protocols and the research articles, and has the potential to improve research reproducibility and help everyone design and execute robust life science experiments.     

一种适合粉虱实验观察的新型微虫笼

介绍了一种适合粉虱实验观察的新型微虫笼。该微虫笼利用具盖塑料杯、条形发夹等材料制作而成,底部直径3 0mm ,高约3 5mm ,单个重量约5g。虫笼可开启的底板上特制一小圆孔,便于接入粉虱成虫。可将单头或小群体粉虱罩在植物叶片上饲养观察,使用方便。可用于粉虱的基本生物学特性、寄主植物适应性、交配行为以及饲毒和传毒等试验研究。