The effect of dose and time on the induction of genetic alterations insaccharomyces cerevisiae by aminoacridines in the presence and absence of visible light irradiation in comparison with the dose-effect-curves of mutagens with other type of action

Summary Aminoacridines induce frameshift mutations and are photodynamically active, depending on whether visible light is absent or present. Therefore, a test system which allows to compare quantitatively the genetic effects of aminoacridines irradiated or unirradiated by visible light ought to be susceptible to the different DNA alterations which can be induced by these substances. For this reason in most experiments mitotic gene conversion and only in some selected experiments reverse mutation was chosen as the indicator of genetic activity. In contrast to mutation systems mitotic gene conversion has never shown a response specific to only some types of mutagens. The three aminoacridine derivatives used-acridine orange (AO), proflavine (PF), and acridine yellow (AY)—were successful in the induction of convertants at two different loci. No locus-specificity could be observed. The time-dependent induction of convertants proceeds quickly but soon reaches—especially after treatment without light—a saturation point. The dose/effect-curve after treatment in the dark has a slope increasing with increasing concentration. Irradiation with visible light results in a dose/effect-curve consisting of three parts. At first the increase of convertants is nearly linear extending one (AY) to three (AO) orders of magnitude. After that a saturation effect begins at the point at which an effectiveness of the acridines in the dark is apparent. At high concentrations an induction of convertants can again be observed which is nearly the same as that after treatment in the dark. To determine whether the dose/effect-curves obtained for gene conversion refer to similar curves for gene mutations after treatment with AO at the same locus not only gene conversions but also reverse mutations were scored for. AO-treatment in the dark is ineffective in inducing reverse mutations. Irradiation with visible light results in a dose/effect-curve beeing parallel only in its first part to the dose/effect-curve obtained for gene conversion, while in its second part a mutation frequency decline can be observed. Comparing the dose/effect-curves of AO resulting from the induction of gene conversion and gene mutation, and taking into account that no mutants can be induced by AO-treatment in the dark, the increase in convertants at high acridine-concentrations can be explained as an addition of light-dependent and light-independent effects. That means, in mutation systems at low concentrations of aminoacridines irradiation with visible light should cause transitions, transversions and microlesions, at intermediate concentrations frameshift lesions should begin to appear, and at very high concentrations nearly exclusively frameshift lesions should occur. The dose/effect-curves of aminoacridines compared with those of other mutagens are very complex. The dose/effect-curves of the mutagens of other type of action tested are linear in a double logarithmic scale, and parallel for induced gene conversion and induced gene mutation. These results indicate that the gene conversion ability of a given compound depends on its mutagenic property. That means, many mutagens may exert specific genetic effects not directly but mainly in indirect ways by leading to DNA damage, a situation for repair synthesis resulting as well in mutations as recombinations.     

PlantMetabolomics.org: A Web Portal for Plant Metabolomics Experiments

PlantMetabolomics.org (PM) is a web portal and database for exploring, visualizing, and downloading plant metabolomics data. Widespread public access to well-annotated metabolomics datasets is essential for establishing metabolomics as a functional genomics tool. PM integrates metabolomics data generated from different analytical platforms from multiple laboratories along with the key visualization tools such as ratio and error plots. Visualization tools can quickly show how one condition compares to another and which analytical platforms show the largest changes. The database tries to capture a complete annotation of the experiment metadata along with the metabolite abundance databased on the evolving Metabolomics Standards Initiative. PM can be used as a platform for deriving hypotheses by enabling metabolomic comparisons between genetically unique Arabidopsis (Arabidopsis thaliana) populations subjected to different environmental conditions. Each metabolite is linked to relevant experimental data and information from various annotation databases. The portal also provides detailed protocols and tutorials on conducting plant metabolomics experiments to promote metabolomics in the community. PM currently houses Arabidopsis metabolomics data generated by a consortium of laboratories utilizing metabolomics to help elucidate the functions of uncharacterized genes. PM is publicly available at http://www.plantmetabolomics.org.In the post genomics era, metabolomics is fast emerging as a vital source of information to aid in solving systems biology puzzles with an emphasis on metabolic solutions. Metabolomics is the science of measuring the pool sizes of metabolites (small molecules of M_r ≤ 1,000 D), which collectively define the metabolome of a biological sample (Fiehn et al., 2000; Hall et al., 2002). Coverage of the entire plant metabolome is a daunting task as it is estimated that there are over 200,000 different metabolites within the plant kingdom (Goodacre et al., 2004). Although technology is rapidly advancing, there are still large gaps in our knowledge of the plant metabolome.Despite this lack of complete knowledge and the immense metabolic diversity among plants, metabolomics has become a key analytical tool in the plant community (Hall et al., 2002). This has led to the emergence of multiple experimental and analytical platforms that collectively generate millions of metabolite data points. Because of this vast amount of data, the development of public databases to capture information from metabolomics experiments is vital to provide the scientific community with comprehensive knowledge about metabolite data generation, annotation, and integration with metabolic pathway data. Some examples of these public databases are given below. The Human Metabolome Project contains comprehensive data for more than 2,000 metabolites found within the human body (Wishart et al., 2007). The Golm Database is a repository that provides access to mass spectrometry (MS) libraries, metabolite profiling experiments, and related information from gas chromatography (GC)-MS experimental platforms, along with tools to integrate this information with other systems biology knowledge (Kopka et al., 2005). The Madison Metabolomics Consortium Database contains primarily NMR spectra for Arabidopsis (Arabidopsis thaliana) and features thorough NMR search tools (Cui et al., 2008). SetupX and Binbase provide a framework that combines MS data and biological metadata for steering laboratory work flows and employs automated metabolite annotation (Scholz and Fiehn, 2007).A single analytical technique cannot identify and quantify all the metabolites found in plants. Thus, PlantMetabolomics.org (PM) was developed to provide a portal for accessing publicly available MS-based plant metabolomics experimental results from multiple analytical and separation techniques. PM also follows the emerging metabolomics standards for experiment annotation. PM has extensive annotation links between the identified metabolites and metabolic pathways in AraCyc (Mueller et al., 2003) at The Arabidopsis Information Resource (Rhee et al., 2003) and the Plant Metabolic Network (www.plantcyc.org), the Kyoto Encyclopedia of Genes and Genomes (KEGG; Kanehisa et al., 2004), and MetNetDB (Wurtele et al., 2007).Standards for the annotation of metabolomics experiments are still under active development and the metadata types collected in PM are based on the recommendations of the Metabolomics Standards Initiative (MSI; Fiehn et al., 2007a) and the Minimal Information for a Metabolomic Experiment (Bino et al., 2004) standards. MSI attempts to capture the complete annotation of metabolomics experiments and includes metadata of the experiments along with the metabolite abundance data. The initial database schema design was guided by the schema proposed in the Architecture for Metabolomics project (Jenkins et al., 2004).     

Multiple imputation for estimating the risk of developing dementia and its impact on survival

Dementia, Alzheimer's disease in particular, is one of the major causes of disability and decreased quality of life among the elderly and a leading obstacle to successful aging. Given the profound impact on public health, much research has focused on the age-specific risk of developing dementia and the impact on survival. Early work has discussed various methods of estimating age-specific incidence of dementia, among which the illness-death model is popular for modeling disease progression. In this article we use multiple imputation to fit multi-state models for survival data with interval censoring and left truncation. This approach allows semi-Markov models in which survival after dementia depends on onset age. Such models can be used to estimate the cumulative risk of developing dementia in the presence of the competing risk of dementia-free death. Simulations are carried out to examine the performance of the proposed method. Data from the Honolulu Asia Aging Study are analyzed to estimate the age-specific and cumulative risks of dementia and to examine the effect of major risk factors on dementia onset and death.     

Selection and mutation in the “new” genetics: an emerging hypothesis

It has been anticipated that new, much more sensitive, next generation sequencing (NGS) techniques, using massively parallel sequencing, will likely provide radical insights into the genetics of multifactorial diseases. While NGS has been used initially to analyze individual human genomes, and has revealed considerable differences between healthy individuals, we have used NGS to examine genetic variation within individuals, by sequencing tissues “in depth”, i.e., oversequencing many thousands of times. Initial studies have revealed intra-tissue genetic heterogeneity, in the form of multiple variants of a single gene that exist as distinct “majority and “minority” variants. This highly specialized form of somatic mosaicism has been found within both cancer and normal tissues. If such genetic variation within individual tissues is widespread, it will need to be considered as a significant factor in the ontogeny of many multifactorial diseases, including cancer. The discovery of majority and minority gene variants and the resulting somatic cell heterogeneity in both normal and diseased tissues suggests that selection, as opposed to mutation, might be the critical event in disease ontogeny. We, therefore, are proposing a hypothesis to explain multifactorial disease ontogeny in which pre-existing multiple somatic gene variants, which may arise at a very early stage of tissue development, are eventually selected due to changes in tissue microenvironments.     

A suppressor of fab1 challenges hypotheses on the role of thylakoid unsaturation in photosynthetic function

Leaf membrane lipids of the Arabidopsis (Arabidopsis thaliana) fatty acid biosynthesis 1 (fab1) mutant contain a 35% to 40% increase in the predominant saturated fatty acid 16:0, relative to wild type. This increase in membrane saturation is associated with loss of photosynthetic function and death of mutant plants at low temperatures. We have initiated a suppressor screen for mutations that allow survival of fab1 plants at 2 degrees C. Five suppressor mutants identified in this screen all rescued the collapse of photosynthetic function observed in fab1 plants. While fab1 plants died after 5 to 7 weeks at 2 degrees C, the suppressors remained viable after 16 weeks in the cold, as judged by their ability to resume growth following a return to 22 degrees C and to subsequently produce viable seed. Three of the suppressors had changes in leaf fatty acid composition when compared to fab1, indicating that one mechanism of suppression may involve compensating changes in thylakoid lipid composition. Surprisingly, the suppressor phenotype in one line, S31, was associated with a further substantial increase in lipid saturation. The overall leaf fatty acid composition of S31 plants contained 31% 16:0 compared with 23% in fab1 and 17% in wild type. Biochemical and genetic analysis showed that S31 plants contain a new allele of fatty acid desaturation 5 (fad5), fad5-2, and are therefore partially deficient in activity of the chloroplast 16:0 Delta7 desaturase. A double mutant produced by crossing fab1 to the original fad5-1 allele also remained alive at 2 degrees C, indicating that the fad5-2 mutation is the suppressor in the S31 (fab1 fad5-2) line. Based on the biophysical characteristics of saturated and unsaturated fatty acids, the increased 16:0 in fab1 fad5-2 plants would be expected to exacerbate, rather than ameliorate, low-temperature damage. We propose instead that a change in shape of the major thylakoid lipid, monogalactosyldiacylglycerol, mediated by the fad5-2 mutation, may compensate for changes in lipid structure resulting from the original fab1 mutation. Our identification of mutants that suppress the low-temperature phenotype of fab1 provides new tools to understand the relationship between thylakoid lipid structure and photosynthetic function.     

A species‐centered approach for uncovering generalities in organism responses to habitat loss and fragmentation

Theoretical models predict strong influences of habitat loss and fragmentation on species distributions and demography, but empirical studies have shown relatively inconsistent support across species and systems. We argue that species’ responses to landscape‐scale habitat loss and fragmentation are likely to appear less idiosyncratic if it is recognized that species perceive the same landscapes in different ways. We present a new quantitative approach that uses species distribution models (SDMs) to measure landscapes (e.g. patch size, isolation, matrix amount) from the perspective of individual species. First, we briefly summarize the few efforts to date demonstrating that once differences in habitat distributions are controlled, consistencies in species’ responses to landscape structure emerge. Second, we present a detailed example providing step‐by‐step methods for application of a species‐centered approach using freely available land‐cover data and recent statistical modeling approaches. Third, we discuss pitfalls in current applications of the approach and recommend avenues for future developments. We conclude that the species‐centered approach offers considerable promise as a means to test whether sensitivity to habitat loss and fragmentation is mediated by phylogenetic, ecological, and life‐history traits. Cross‐species generalities in responses to habitat loss and fragmentation will be challenging to uncover unless landscape mosaics are defined using models that reflect differing species‐specific distributions, functional connectivity, and domains of scale. The emergence of such generalities would not only enhance scientific understanding of biotic processes driving fragmentation effects, but would allow managers to estimate species sensitivities in new regions.     

Multiplexed screening of natural humoral immunity identifies antibodies at fine specificity for complex and dynamic viral targets

Viral entry targets with therapeutic neutralizing potential are subject to multiple escape mechanisms, including antigenic drift, immune dominance of functionally irrelevant epitopes, and subtle variations in host cell mechanisms. A surprising finding of recent years is that potent neutralizing antibodies to viral epitopes independent of strain exist, but are poorly represented across the diverse human population. Identifying these antibodies and understanding the biology mediating the specific immune response is thus difficult. An effective strategy for meeting this challenge is to incorporate multiplexed antigen screening into a high throughput survey of the memory B cell repertoire from immune individuals. We used this approach to discover suites of cross-clade antibodies directed to conformational epitopes in the stalk region of the influenza A hemagglutinin (HA) protein and to select high-affinity anti-peptide antibodies to the glycoprotein B (gB) of human cytomegalovirus. In each case, our screens revealed a restricted V_H and V_L germline usage, including published and previously unidentified gene families. The in vivo evolution of paratope specificity with optimal neutralizing activity was understandable after correlating biological activities with kinetic binding and epitope recognition. Iterative feedback between antigen probe design based on structure and function information with high throughput multiplexed screening demonstrated a generally applicable strategy for efficient identification of safe, native, finely tuned antibodies with the potential for high genetic barriers to viral escape.     

Just a hypothesis: a reply to Hanski

Hanski's critique of the habitat amount hypothesis (Hanski, 2015, Journal of Biogeography, 42 , 989–993) does not actually constitute a test of the hypothesis, but rather a series of arguments for why he suspects that it is not correct. But the habitat amount hypothesis is exactly that – a hypothesis. It will remain ‘just’ a hypothesis until it has been rigorously tested against empirical data. To facilitate such testing, in Fahrig (2013, Journal of Biogeography, 40 , 1649–1663) I presented specific, testable predictions of the hypothesis. Here, I reiterate the main tests needed, in the hope that some readers will be encouraged to carry them out. I appreciate this opportunity to emphasize that the habitat amount hypothesis needs to be tested against empirical data, and I look forward to seeing the results of such tests.