Monitoring and modeling infiltration–recharge dynamics of managed aquifer recharge with desalinated seawater

We study the relation between surface infiltration and groundwater recharge during managed aquifer recharge (MAR) with desalinated seawater in an infiltration pond, at the Menashe site that overlies the northern part of the Israeli Coastal Aquifer. We monitor infiltration dynamics at multiple scales (up to the scale of the entire pond) by measuring the ponding depth, sediment water content and groundwater levels, using pressure sensors, single-ring infiltrometers, soil sensors, and observation wells. During a month (January 2015) of continuous intensive MAR (2.45  ×  10⁶ m³ discharged to a 10.7 ha area), groundwater level has risen by 17 m attaining full connection with the pond, while average infiltration rates declined by almost 2 orders of magnitude (from  ∼  11 to  ∼  0.4 m d⁻¹). This reduction can be explained solely by the lithology of the unsaturated zone that includes relatively low-permeability sediments. Clogging processes at the pond-surface – abundant in many MAR operations – are negated by the high-quality desalinated seawater (turbidity  ∼  0.2 NTU, total dissolved solids  ∼  120 mg L⁻¹) or negligible compared to the low-permeability layers. Recharge during infiltration was estimated reasonably well by simple analytical models, whereas a numerical model was used for estimating groundwater recharge after the end of infiltration. It was found that a calibrated numerical model with a one-dimensional representative sediment profile is able to capture MAR dynamics, including temporal reduction of infiltration rates, drainage and groundwater recharge. Measured infiltration rates of an independent MAR event (January 2016) fitted well to those calculated by the calibrated numerical model, showing the model validity. The successful quantification methodologies of the temporal groundwater recharge are useful for MAR practitioners and can serve as an input for groundwater flow models

Managed aquifer recharge with reverse-osmosis desalinated seawater: modeling the spreading in groundwater using stable water isotopes

The spreading of reverse-osmosis desalinated seawater (DSW) in the Israeli coastal aquifer was studied using groundwater modeling and stable water isotopes as tracers. The DSW produced at the Hadera seawater reverse-osmosis (SWRO) desalination plant is recharged into the aquifer through an infiltration pond at the managed aquifer recharge (MAR) site of Menashe, Israel. The distinct difference in isotope composition between DSW (δ18O&thinsp; = &thinsp;1.41&thinsp;‰; δ2H&thinsp; = &thinsp;11.34&thinsp;‰) and the natural groundwater (δ18O&thinsp; = &thinsp;−4.48&thinsp;‰ to −5.43&thinsp;‰; δ2H&thinsp; = &thinsp;−18.41&thinsp;‰ to −22.68&thinsp;‰) makes the water isotopes preferable for use as a tracer compared to widely used chemical tracers, such as chloride. Moreover, this distinct difference can be used to simplify the system to a binary mixture of two end-members: desalinated seawater and groundwater. This approach is validated through a sensitivity analysis, and it is especially robust when spatial data of stable water isotopes in the aquifer are scarce. A calibrated groundwater flow and transport model was used to predict the DSW plume distribution in the aquifer after 50 years of MAR with DSW. The results suggest that after 50 years, 94&thinsp;% of the recharged DSW was recovered by the production wells at the Menashe MAR site. The presented methodology is useful for predicting the distribution of reverse-osmosis desalinated seawater in various downstream groundwater systems.</p

Identification of novel proteins associated with yeast snR30 small nucleolar RNA

H/ACA small nucleolar RNPs (snoRNPs) that guide pseudouridylation reactions are comprised of one small nucleolar RNA (snoRNA) and four common proteins (Cbf5, Gar1, Nhp2 and Nop10). Unlike other H/ACA snoRNPs, snR30 is essential for the early processing reactions that lead to the production of 18S ribosomal RNA in the yeast Saccharomyces cerevisiae. To determine whether snR30 RNP contains specific proteins that contribute to its unique functional properties, we devised an affinity purification strategy using TAP-tagged Gar1 and an RNA aptamer inserted in snR30 snoRNA to selectively purify the RNP. Northern blotting and pCp labeling experiments showed that S1-tagged snR30 snoRNA can be selectively purified with streptavidin beads. Protein analysis revealed that aptamer-tagged snR30 RNA was associated with the four H/ACA proteins and a number of additional proteins: Nop6, ribosomal proteins S9 and S18 and histones H2B and H4. Using antibodies raised against Nop6 we show that endogenous Nop6 localizes to the nucleolus and that it cosediments with snR30 snoRNA in sucrose density gradients. We demonstrate through primer extension experiments that snR30 snoRNA is required for cleavages at site A0, A1 and A2, and that the absence of Nop6 decreases the efficiency of cleavage at site A2. Finally, electron microscopy analyses of chromatin spreads from cells depleted of snR30 snoRNA show that it is required for SSU processome assembly

Observational and Physical Classification of Supernovae

This chapter describes the current classification scheme of supernovae (SNe). This scheme has evolved over many decades and now includes numerous SN Types and sub-types. Many of these are universally recognized, while there are controversies regarding the definitions, membership and even the names of some sub-classes; we will try to review here the commonly-used nomenclature, noting the main variants when possible. SN Types are defined according to observational properties; mostly visible-light spectra near maximum light, as well as according to their photometric properties. However, a long-term goal of SN classification is to associate observationally-defined classes with specific physical explosive phenomena. We show here that this aspiration is now finally coming to fruition, and we establish the SN classification scheme upon direct observational evidence connecting SN groups with specific progenitor stars. Observationally, the broad class of Type II SNe contains objects showing strong spectroscopic signatures of hydrogen, while objects lacking such signatures are of Type I, which is further divided to numerous subclasses. Recently a class of super-luminous SNe (SLSNe, typically 10 times more luminous than standard events) has been identified, and it is discussed. We end this chapter by briefly describing a proposed alternative classification scheme that is inspired by the stellar classification system. This system presents our emerging physical understanding of SN explosions, while clearly separating robust observational properties from physical inferences that can be debated. This new system is quantitative, and naturally deals with events distributed along a continuum, rather than being strictly divided into discrete classes. Thus, it may be more suitable to the coming era where SN numbers will quickly expand from a few thousands to millions of events.Comment: Extended final draft of a chapter in the "SN Handbook". Comments most welcom

SN 2018fif: The explosion of a large red supergiant discovered in its infancy by the Zwicky transient facility

High-cadence transient surveys are able to capture supernovae closer to their first light than ever before. Applying analytical models to such early emission, we can constrain the progenitor stars’ properties. In this paper, we present observations of SN 2018fif (ZTF 18abokyfk). The supernova was discovered close to first light and monitored by the Zwicky Transient Facility (ZTF) and the Neil Gehrels Swift Observatory. Early spectroscopic observations suggest that the progenitor of SN 2018fif was surrounded by relatively small amounts of circumstellar material compared to all previous cases. This particularity, coupled with the high-cadence multiple-band coverage, makes it a good candidate to investigate using shock-cooling models. We employ the SOPRANOS code, an implementation of the model by Sapir &amp; Waxman and its extension to early times by Morag et al. Compared with previous implementations, SOPRANOS has the advantage of including a careful account of the limited temporal validity domain of the shock-cooling model as well as allowing usage of the entirety of the early UV data. We find that the progenitor of SN 2018fif was a large red supergiant with a radius of R = 744.0-+128.0183.0 R☉ and an ejected mass of Mej = 9.3-+5.80.4 M☉. Our model also gives information on the explosion epoch, the progenitor’s inner structure, the shock velocity, and the extinction. The distribution of radii is double-peaked, with smaller radii corresponding to lower values of the extinction, earlier recombination times, and a better match to the early UV data. If these correlations persist in future objects, denser spectroscopic monitoring constraining the time of recombination, as well as accurate UV observations (e.g., with ULTRASAT), will help break the extinction/radius degeneracy and independently determine both

Adaptations to Endosymbiosis in a Cnidarian-Dinoflagellate Association: Differential Gene Expression and Specific Gene Duplications

Trophic endosymbiosis between anthozoans and photosynthetic dinoflagellates forms the key foundation of reef ecosystems. Dysfunction and collapse of symbiosis lead to bleaching (symbiont expulsion), which is responsible for the severe worldwide decline of coral reefs. Molecular signals are central to the stability of this partnership and are therefore closely related to coral health. To decipher inter-partner signaling, we developed genomic resources (cDNA library and microarrays) from the symbiotic sea anemone Anemonia viridis. Here we describe differential expression between symbiotic (also called zooxanthellate anemones) or aposymbiotic (also called bleached) A. viridis specimens, using microarray hybridizations and qPCR experiments. We mapped, for the first time, transcript abundance separately in the epidermal cell layer and the gastrodermal cells that host photosynthetic symbionts. Transcriptomic profiles showed large inter-individual variability, indicating that aposymbiosis could be induced by different pathways. We defined a restricted subset of 39 common genes that are characteristic of the symbiotic or aposymbiotic states. We demonstrated that transcription of many genes belonging to this set is specifically enhanced in the symbiotic cells (gastroderm). A model is proposed where the aposymbiotic and therefore heterotrophic state triggers vesicular trafficking, whereas the symbiotic and therefore autotrophic state favors metabolic exchanges between host and symbiont. Several genetic pathways were investigated in more detail: i) a key vitamin K–dependant process involved in the dinoflagellate-cnidarian recognition; ii) two cnidarian tissue-specific carbonic anhydrases involved in the carbon transfer from the environment to the intracellular symbionts; iii) host collagen synthesis, mostly supported by the symbiotic tissue. Further, we identified specific gene duplications and showed that the cnidarian-specific isoform was also up-regulated both in the symbiotic state and in the gastroderm. Our results thus offer new insight into the inter-partner signaling required for the physiological mechanisms of the symbiosis that is crucial for coral health

Expression and Processing of a Small Nucleolar RNA from the Epstein-Barr Virus Genome

Small nucleolar RNAs (snoRNAs) are localized within the nucleolus, a sub-nuclear compartment, in which they guide ribosomal or spliceosomal RNA modifications, respectively. Up until now, snoRNAs have only been identified in eukaryal and archaeal genomes, but are notably absent in bacteria. By screening B lymphocytes for expression of non-coding RNAs (ncRNAs) induced by the Epstein-Barr virus (EBV), we here report, for the first time, the identification of a snoRNA gene within a viral genome, designated as v-snoRNA1. This genetic element displays all hallmark sequence motifs of a canonical C/D box snoRNA, namely C/C′- as well as D/D′-boxes. The nucleolar localization of v-snoRNA1 was verified by in situ hybridisation of EBV-infected cells. We also confirmed binding of the three canonical snoRNA proteins, fibrillarin, Nop56 and Nop58, to v-snoRNA1. The C-box motif of v-snoRNA1 was shown to be crucial for the stability of the viral snoRNA; its selective deletion in the viral genome led to a complete down-regulation of v-snoRNA1 expression levels within EBV-infected B cells. We further provide evidence that v-snoRNA1 might serve as a miRNA-like precursor, which is processed into 24 nt sized RNA species, designated as v-snoRNA124pp. A potential target site of v-snoRNA124pp was identified within the 3′-UTR of BALF5 mRNA which encodes the viral DNA polymerase. V-snoRNA1 was found to be expressed in all investigated EBV-positive cell lines, including lymphoblastoid cell lines (LCL). Interestingly, induction of the lytic cycle markedly up-regulated expression levels of v-snoRNA1 up to 30-fold. By a computational approach, we identified a v-snoRNA1 homolog in the rhesus lymphocryptovirus genome. This evolutionary conservation suggests an important role of v-snoRNA1 during γ-herpesvirus infection

SN 2018fif: The Explosion of a Large Red Supergiant Discovered in Its Infancy by the Zwicky Transient Facility

High-cadence transient surveys are able to capture supernovae closer to their first light than ever before. Applying analytical models to such early emission, we can constrain the progenitor stars' properties. In this paper, we present observations of SN 2018fif (ZTF 18abokyfk). The supernova was discovered close to first light and monitored by the Zwicky Transient Facility (ZTF) and the Neil Gehrels Swift Observatory. Early spectroscopic observations suggest that the progenitor of SN 2018fif was surrounded by relatively small amounts of circumstellar material compared to all previous cases. This particularity, coupled with the high-cadence multiple-band coverage, makes it a good candidate to investigate using shock-cooling models. We employ the SOPRANOS code, an implementation of the model by Sapir & Waxman and its extension to early times by Morag et al. Compared with previous implementations, SOPRANOS has the advantage of including a careful account of the limited temporal validity domain of the shock-cooling model as well as allowing usage of the entirety of the early UV data. We find that the progenitor of SN 2018fif was a large red supergiant with a radius of $R={744.0}_{-128.0}^{+183.0}\,{R}_{\odot }$ and an ejected mass of ${M}_{\mathrm{ej}}={9.3}_{-5.8}^{+0.4}\,{M}_{\odot }$. Our model also gives information on the explosion epoch, the progenitor's inner structure, the shock velocity, and the extinction. The distribution of radii is double-peaked, with smaller radii corresponding to lower values of the extinction, earlier recombination times, and a better match to the early UV data. If these correlations persist in future objects, denser spectroscopic monitoring constraining the time of recombination, as well as accurate UV observations (e.g., with ULTRASAT), will help break the extinction/radius degeneracy and independently determine both

Operons

Operons (clusters of co-regulated genes with related functions) are common features of bacterial genomes. More recently, functional gene clustering has been reported in eukaryotes, from yeasts to filamentous fungi, plants, and animals. Gene clusters can consist of paralogous genes that have most likely arisen by gene duplication. However, there are now many examples of eukaryotic gene clusters that contain functionally related but non-homologous genes and that represent functional gene organizations with operon-like features (physical clustering and co-regulation). These include gene clusters for use of different carbon and nitrogen sources in yeasts, for production of antibiotics, toxins, and virulence determinants in filamentous fungi, for production of defense compounds in plants, and for innate and adaptive immunity in animals (the major histocompatibility locus). The aim of this article is to review features of functional gene clusters in prokaryotes and eukaryotes and the significance of clustering for effective function