Functional analysis ofFRIGIDAusing naturally occurring variation inArabidopsis thaliana

International audienceTheFRIGIDAlocus (FRI, AT4G00650) has been extensively studied inArabidopsis thalianabecause of its role creating flowering time diversity. The FRI protein regulates flowering induction by binding partner proteins on its N-terminus and C-terminus domains and creating a supercomplex that promotes transcription of the floral repressor FLOWERING LOCUS C (FLC). Despite the knowledge accumulated on FRIGIDA (FRI), the function of the highly conserved central domain of the protein is still unknown. Functional characterization of naturally occurring DNA polymorphisms can provide useful information about the role of a protein and the localization of its operative domains. For FRI, loss-of-function mutations are positively selected and widespread in nature, making them a powerful tool to study the function of the different domains of the protein. Here we explore natural sequence variation in theFRIlocus in more than 1000 Arabidopsis accessions. We identify 127 mutations that alter the FRI protein, including 60 that had never been described before. We defined 103 different alleles of FRI and study their association with variation in flowering time. We confirmed these associations by cloning 22 different alleles and expressing them in a common null genetic background. Our analysis pinpoints two single amino acid changes in the central domain that render the protein non-functional. We show that these two mutations determine the stability and cellular localization of the FRI protein. In summary, our work makes use of natural variants at the FRI locus to help understanding the function of the central domain of the FRI protein

A sliding window-based algorithm for faster transformation of time series into complex networks

A new alternative method to approximate the Visibility Graph (VG) of a time series has been introduced here. It exploits the fact that most of the nodes in the resulting network are not connected to those that are far away from them. This means that the adjacency matrix is almost empty, and its nonzero values are close to the main diagonal. This new method is called Sliding Visibility Graph (SVG). Numerical tests have been performed for several time series, showing a time efficiency that scales linearly with the size of the series [O(N)], in contrast to the original VG that does so quadratically [O(N2)]. This fact is noticeably convenient when dealing with very large time series. The results obtained from the SVG of the studied time series have been compared to the exact values of the original VG. As expected, the SVG outcomes converge very rapidly to the desired ones, especially for random and stochastic series. Also, this method can be extended to the analysis of time series that evolve in real time, since it does not require the entire dataset to perform the analysis but a shorter segment of it. The length segment can remain constant, making possible a simple analysis as the series evolves in time.Comment: 33 pages, 8 figure

Checking complex networks indicators in search of singular episodes of the photochemical smog

A set of indicators derived from the analysis of complex networks have been introduced to identify singularities on a time series. To that end, the Visibility Graphs (VG) from three different signals related to photochemical smog (O3, NO2 concentration and temperature) have been computed. From the resulting complex network, the centrality parameters have been obtained and compared among them. Besides, they have been contrasted to two others that arise from a multifractal point of view, that have been widely used for singularity detection in many fields: the Holder and singularity exponents (specially the first one of them). The outcomes show that the complex network indicators give equivalent results to those already tested, even exhibiting some advantages such as the unambiguity and the more selective results. This suggest a favorable position as supplementary sources of information when detecting singularities in several environmental variables, such as pollutant concentration or temperature.Comment: 32 pages, 7 figure

Evaluation of agarose gel electrophoresis for characterization of silver nanoparticles in industrial products

Agarose gel electrophoresis (AGE) has been used extensively for characterization of pure nanomaterials or mixtures of pure nanomaterials. We have evaluated the use of AGE for characterization of Ag nanoparticles (NPs) in an industrial product (described as strong antiseptic). Influence of different stabilizing agents (PEG, SDS, and sodium dodecylbenzenesulfonate), buffers (TBE and Tris Glycine), and functionalizing agents (mercaptosuccinic acid (TMA) and proteins) has been investigated for the characterization of AgNPs in the industrial product using different sizes-AgNPs standards. The use of 1% SDS, 0.1% TMA, and Tris Glycine in gel, electrophoresis buffer and loading buffer led to the different sizes-AgNPs standards moved according to their size/charge ratio (obtaining a linear relationship between apparent mobility and mean diameter). After using SDS and TMA, the behavior of the AgNPs in the industrial product (containing a casein matrix) was completely different, being not possible their size characterization. However we demonstrated that AGE with LA-ICP-MS detection is an alternative method to confirm the protein corona formation between the industrial product and two proteins (BSA and transferrin) maintaining NPs-protein binding (what is not possible using SDS-PAGE)

A Wild Pseudomonas has appeared: An Exercise in Bacterial Isolation and Identification

The aim of our research was to isolate and identify wild type Pseudomonas putida from soil in various cities of San Gabriel Valley. P. putida iscapable of biomineralization. Biomineralization can potentially be used as a method of phosphorus recovery by using bacteria to produce phosphate rich struvite. In isolating bacteria for further observation, fluorescence was used as a primary determinant in identifying possible Pseudomonas strains as fluorescence is a common trait shared among varying Pseudomonas species; P. putida, P. aeruginosa, P. fluorescens, P. cichorii, P. chlororaphis, P. syringae,and P. aureofaciens. King’s B agar was used to promote the production of pyoverdine in these strains (allowing for direct identification based on a green fluorescence under UV light) as this medium has specific ingredients that enhance pigment production.These fluorescent bacteria were then further isolated from each other and identified using biochemical methods including catalase, oxidase, nitrate reduction, and gelatin hydrolysis tests to differentiate P. putida from the six other fluorescent Pseudomonas species. Of the 21 total samples isolated based on fluorescence, 5 of the samples were determined to be potential P. putida. While the biochemical assays were conducted, the isolated samples were placed in refrigeration for 3 weeks. After the biochemical tests were completed and 3 weeks had passed, visible crystals had formed in the potential P. putida. Albert’s metachromatic staining was performed to determine the presence of polyphosphate granules. Ultimately, each potential P. putida that produced crystals also showed polyphosphate granules when Albert’s stained, which further connects crystal formation with prior polyphosphate formation

Multifractal detrended fluctuation analysis of rainfall time series in the Guadeloupe archipelago

Due to the vulnerability of the Caribbean islands to the climate change issue, it is important to investigate the behavior of rainfall. In addition, the soil of the French West Indies Islands has been contaminated by an insecticide (Chlordecone) whose decontamination is mainly done by drainage water. Thus, it is crucial to investigate the fluctuations of rainfall in these complex environments. In this study, 19 daily rainfall series recorded in different stations of Guadeloupe archipelago from 2005 to 2014 were analyzed with the multifractal detrended fluctuation analysis (MF-DFA) method. The aim of this work is to characterize the long-range correlations and multifractal properties of the time series and to find geographical patterns over the three most important islands. This is the first study that addresses the analysis of multifractal properties of rainfall series in the Caribbean islands. This region is typically characterized by the almost constant influence of the trade winds and a high exposure to changes in the general atmospheric circulation. 12 stations exhibit two different power-law scaling regions in rainfall series, with distinct long-range correlations and multifractal properties for large and small scales. On the contrary, the rest of stations only show a single region of scales for relatively small scales. Hurst exponents reveal persistent long-range correlations. In the most eastern analyzed areas, larger scales exhibit higher persistence than smaller scales, which suggests a relationship between persistence and the highest exposure to the trade winds. Stronger conclusions can be drawn from multifractal spectra, which indicate that most rainfall series have a multifractal nature with higher complexity and degree of multifractality at the smallest scales. Furthermore, a clear dependence of multifractal nature on the latitude is revealed.Comment: 43 pages. 11 figure

Improving graph-based detection of singular events for photochemical smog agents

Recently, a set of graph-based tools have been introduced for the identification of singular events of O3, NO2 and temperature time series, as well as description of their dynamics. These are based on the use of the Visibility Graphs (VG). In this work, an improvement of the original approach is proposed, being called Upside-Down Visibility Graph (UDVG). It adds the possibility of investigating the singular lowest episodes, instead of the highest. Results confirm the applicability of the new method for describing the multifractal nature of the underlying O3, NO2, and temperature. Asymmetries in the NO2 degree distribution are observed, possibly due to the interaction with different chemicals. Furthermore, a comparison of VG and UDVG has been performed and the outcomes show that they describe opposite subsets of the time series (low and high values) as expected. The combination of the results from the two networks is proposed and evaluated, with the aim of obtaining all the information at once. It turns out to be a more complete tool for singularity detection in photochemical time series, which could be a valuable asset for future research.Comment: 35 pages, 7 figure

Can complex networks describe the urban and rural tropospheric O3 dynamics?

Tropospheric ozone (O3) time series have been converted into complex networks through the recent so-called Visibility Graph (VG), using the data from air quality stations located in the western part of Andalusia (Spain). The aim is to apply this novel method to differentiate the behavior between rural and urban regions when it comes to the ozone dynamics. To do so, some centrality parameters of the resulting complex networks have been investigated: the degree, betweenness and shortest path. Some of them are expected to corroborate previous works in order to support the use of this technique; while others to supply new information. Results coincide when describing the difference that tropospheric ozone exhibits seasonally and geographically. It is seen that ozone behavior is fractal, in accordance to previous works. Also, it has been demonstrated that this methodology is able to characterize the divergence encountered between measurements in urban environments and countryside. In addition to that, the promising outcomes of this technique support the use of complex networks for the study of air pollutants dynamics. Particularly, new nuances are offered such as the identification and description of singularities in the signal.Comment: 27 pages, 7 figures, 1 graphical abstrac

Multiplex Visibility Graphs as a complementary tool for describing the relation between ground level O3 and NO2

The usage of multilayer complex networks for the analysis of correlations among environmental variables (such as O3 and NO2 concentrations from the photochemical smog) is investigated in this work. The mentioned technique is called Multiplex Visibility Graphs (MVG). By performing the joint analysis of those layers, the parameters named Average Edge Overlap and Interlayer Mutual Information are extracted, which accounts for the microscopical time coherence and the correlation between the time series behavior, respectively. These parameters point to the possibility of using them independently to describe the correlation between atmospheric pollutants (which could be extended to environmental time series). More precisely the first one of them is considered to be a potential new approach to determine the time required for the correlation of NO2 and O3 to be observed, since it is obtained from the correlation of the pollutants at the smallest time scale. As for the second one, it has been checked that the proposed technique can be used to describe the variation of the correlation between the two gases along the seasons. In short, MVGs parameters are introduced and results show that they could be potentially used in a future for correlation studies, supplementing already existing techniques.Comment: 29 pages, 7 figure