Collective behavior in gene regulation: Metabolic clocks and cross-talking

Biological functions governed by the circadian clock are the evident result of the entrainment operated by the earth's day and night cycle on living organisms. However, the circadian clock is not unique, and cells and organisms possess many other cyclic activities. These activities are difficult to observe if carried out by single cells and the cells are not coordinated but, if they can be detected, cell-to-cell cross-talk and synchronization among cells must exist. Some of these cycles are metabolic and cell synchronization is due to small molecules acting as metabolic messengers. We propose a short survey of cellular cycles, paying special attention to metabolic cycles and cellular cross-talking, particularly when the synchronization of metabolism or, more generally, cellular functions are concerned. Questions arising from the observation of phenomena based on cell communication and from basic cellular cycles are also proposed. © 2008 The Author

Active recombination of pKD1 derived vectors with resident pKD1 in Kluyveromyces lactis transformation

The host specificity of the 2 u-like circular plasmid pKD1 is such that this plasmid replicates stably in several species of Kluyveromyces yeasts, but not in Saccharomyces cerevisiae, pKD1-derived plasmids containing various parts of the pKD1 sequence were capable of transforming Kluyveromyces lactis with high efficiency. When such vectors were introduced into host strains that contained resident pKD1 plasmid, the input DNA frequently recombined with it to produce high proportions of additive recombinant molecules that replicate stably. Recombination events were shown to occur with vectors differing for the presence or absence of the putative origin of replication and of the inverted repeats. Structure, stability and copy number of the recombination products were analyzed for various types of vectors

Probabilistic load forecasting with Reservoir Computing

Some applications of deep learning require not only to provide accurate results but also to quantify the amount of confidence in their prediction. The management of an electric power grid is one of these cases: to avoid risky scenarios, decision-makers need both precise and reliable forecasts of, for example, power loads. For this reason, point forecasts are not enough hence it is necessary to adopt methods that provide an uncertainty quantification. This work focuses on reservoir computing as the core time series forecasting method, due to its computational efficiency and effectiveness in predicting time series. While the RC literature mostly focused on point forecasting, this work explores the compatibility of some popular uncertainty quantification methods with the reservoir setting. Both Bayesian and deterministic approaches to uncertainty assessment are evaluated and compared in terms of their prediction accuracy, computational resource efficiency and reliability of the estimated uncertainty, based on a set of carefully chosen performance metrics

Italian open-end funds: performance of asset management companies

We empirically analyse the returns of both Italian and round-trip open-end funds managed by Italian asset management companies (SGRs) in the period 2003-2008. Taking into account a modified version of the capital asset pricing model (CAPM), we estimated a performance measure for each asset management company and for each fund, as is usually done in the relevant literature. The analysis shows that the performance of any asset management company, with reference to its managed funds, is on average no greater than that of the benchmark chosen by the managers. In addition, as expected, the funds’ systematic risk is close to that of the benchmarks. Finally, robust estimation techniques let us control for the heteroskedasticity due to the presence of outliers and also to the different excess returns of individual funds.open-end funds, asset management companies, panel data, robust estimators, normal inverse Gaussian distribution

Epigenetic and posttranslational modifications in light signal transduction and the circadian clock in Neurospora crassa

Blue light, a key abiotic signal, regulates a wide variety of physiological processes in many organisms. One of these phenomena is the circadian rhythm presents in organisms sensitive to the phase-setting effects of blue light and under control of the daily alternation of light and dark. Circadian clocks consist of autoregulatory alternating negative and positive feedback loops intimately connected with the cellular metabolism and biochemical processes. Neurospora crassa provides an excellent model for studying the molecular mechanisms involved in these phenomena. The White Collar Complex (WCC), a blue-light receptor and transcription factor of the circadian oscillator, and Frequency (FRQ), the circadian clock pacemaker, are at the core of the Neurospora circadian system. The eukaryotic circadian clock relies on transcriptional/translational feedback loops: some proteins rhythmically repress their own synthesis by inhibiting the activity of their transcriptional factors, generating self-sustained oscillations over a period of about 24 h. One of the basic mechanisms that perpetuate self-sustained oscillations is post translation modification (PTM). The acronym PTM generically indicates the addition of acetyl, methyl, sumoyl, or phosphoric groups to various types of proteins. The protein can be regulatory or enzymatic or a component of the chromatin. PTMs influence protein stability, interaction, localization, activity, and chromatin packaging. Chromatin modification and PTMs have been implicated in regulating circadian clock function in Neurospora. Research into the epigenetic control of transcription factors such as WCC has yielded new insights into the temporal modulation of light-dependent gene transcription. Here we report on epigenetic and protein PTMs in the regulation of the Neurospora crassa circadian clock. We also present a model that illustrates the molecular mechanisms at the basis of the blue light control of the circadian clock

Ergosterol reduction impairs mitochondrial DNA maintenance in S. cerevisiae

Sterols are essential lipids, involved in many biological processes. In Saccharomyces cerevisiae, the enzymes of the ergosterol biosynthetic pathway (Erg proteins) are localized in different cellular compartments. With the aim of studying organelle interactions, we discovered that Erg27p resides mainly in Lipid Droplets (LDs) in respiratory competent cells, while in absence of respiration, is found mostly in the ER. The results presented in this paper demonstrate an interplay between the mitochondrial respiration and ergosterol production: on the one hand, rho° cells show lower ergosterol content when compared with wild type respiratory competent cells, on the other hand, the ergosterol biosynthetic pathway influences the mitochondrial status, since treatment with ketoconazole, which blocks the ergosterol pathway, or the absence of the ERG27 gene, induced rho° production in S. cerevisiae. The loss of mitochondrial DNA in the ∆erg27 strain is fully suppressed by exogenous addition of ergosterol. These data suggest the notion that ergosterol is essential for maintaining the mitochondrial DNA attached to the inner mitochondrial membrane

Explainability in subgraphs-enhanced Graph Neural Networks

Recently, subgraphs-enhanced Graph Neural Networks (SGNNs) have been introduced to enhance the expressive power of Graph Neural Networks (GNNs), which was proved to be not higher than the 1-dimensional Weisfeiler-Leman isomorphism test. The new paradigm suggests using subgraphs extracted from the input graph to improve the model's expressiveness, but the additional complexity exacerbates an already challenging problem in GNNs: explaining their predictions. In this work, we adapt PGExplainer, one of the most recent explainers for GNNs, to SGNNs. The proposed explainer accounts for the contribution of all the different subgraphs and can produce a meaningful explanation that humans can interpret. The experiments that we performed both on real and synthetic datasets show that our framework is successful in explaining the decision process of an SGNN on graph classification tasks

Initiation of tran-scription of Mitochondrial tRNA gene cluster in S.cerevisiae

In Saccharomyces cerevisiae most mitochondrial tRNA genes are clustered in a 9 kbp region between the cap and oxil genes. Polygenic transcripts of this region have been previously identified. A transcriptional initiation site at a TTATAAGTA box, located upstream from the tRNAcys gene, has now been detected by SI mapping experiments and by the capping of primary transcripts. Results are consistent with the hypothesis that this box represents the initiation site for transcription of a cluster of tRNA genes, while the adjacent tRNAthr is cotranscribed with the 21S rRNA. Results obtained with various strains are compared, and the efficiency of this sequence as a tran scriptional initiation site in different mitochondrial contexts is discussed

Explainability in subgraphs-enhanced Graph Neural Networks

Paper submitted to https://septentrio.uit.no/index.php/nldl/indexRecently, subgraphs-enhanced Graph Neural Networks (SGNNs) have been introduced to enhance the expressive power of Graph Neural Networks (GNNs), which was proved to be not higher than the 1-dimensional Weisfeiler-Leman isomorphism test. The new paradigm suggests using subgraphs extracted from the input graph to improve the model’s expressiveness, but the additional complexity exacerbates an already challenging problem in GNNs: explaining their predictions. In this work, we adapt PGExplainer, one of the most recent explainers for GNNs, to SGNNs. The proposed explainer accounts for the contribution of all the different subgraphs and can produce a meaningful explanation that humans can interpret. The experiments that we performed both on real and synthetic datasets show that our framework is successful in explaining the decision process of an SGNN on graph classification tasks

Host range of the pKD1-derived plasmids in yeast

pKD1 is a 2u-like circular plasmid found in the yeast Kluyveromyces drosophilarum that can also stably replicate in Kluyveromyces lactis. We have found a short intergenic region in this genome that appears to be functionally neutral; that is, the introduction of foreign sequences into the single EcoRI restriction site located near one of the inverted repeats did not affect the high stability of the natural plasmid. By introducing a G418 resistance gene at this site, we constructed an autonomous recombinant plasmid. Since this vector did not require cir+ hosts for its stable maintenance, it could be used to examine the transformation host range of pKD1 among all the species belonging to the genus Kluyveromyces. Both species closely related to K. drosophilarum as well as a few other species that are very different in chromosomal GC % could be transformed to yield highly stable transformant clones