Fungal secondary metabolites are compounds of considerable interest because of their medical, industrial and agricultural importance. A wide spread interest in studying the regulation of production of these secondary metabolites has developed among the scientific community because of their diverse functions. The regulation of secondary metabolite biosynthetic genes has been of particular interest, and has proven to be unique in a number of ways from previously understood models of gene regulation. The regulation of fungal secondarymetabolism appears to be dependent to some degree on the chromosomal organization of biosynthetic genes. The genes required for a fungus to produce a given secondary metabolites are frequently clustered, and present adjacent to one another on the chromosome. A widely studied cluster of genes to understand the regulation of secondary metabolite production is the 25 genes sterigmatocystine (ST) cluster. The transcriptional control and co-regulation of these clustered genes are coordinated by a narrow and a broad domain transcription factor. LaeA is a broad domain transcription factor for ST cluster and AflR is a narrow domain transcription factor, which is located in the cluster and is responsible for expression of the rest of the genes in the cluster. A strong evidence of chromatin level regulation of these genes was supported by recent studies in major histone deacetylases mutant hdaAΔ, which showed increased expression of both ST and PN gene clusters. The global regulator LaeA, which is responsible for activation of SM genes clusters, has an S- adenosyl-methionine (SAM) binding domain which is highly conserved in the members of the methylase superfamily. The SAM binding domain and chromatin binding SET domain is predicted to be a histone methyltansferase involved in chromatin modification. It is speculated that during the normal growth phase the gene clusters are repressed because of their location in silent loci, which are under the influence of heterochromatin. During secondarymetabolism, the global regulator LaeA with its chromatin modifying SAM domain remove the repressive histone marks and renders the genes for transcription by exposing them to pathway specific transcription factors. The hallmark of heterochromatin is hypoacetylation of lysine at histone H3 and H4 and trimethylation of lysine of histone H3, which is recognised by a highly conserved heterochromatin protein HP-1. This is responsible for transcriptional repression of genes, which are under the influence of heterochromatin. HepA is a homolog of HP-1 in
This review which is concerned with the application of recombinant DNA technology to studies on plant secondarymetabolism, presents the more common plant transformation strategies and shows how these genetic approaches are being used in attempts to manipulate and increase the yield of secondary metabolites, both in cultures and in transformed plants. The different plant transformation strategies reviewed here are: infection with intact Agrobacteria; particle bombardment, vacuum infiltration and floral dip; viral vectors and finally protoplast fusion. The review continues with examples of the application of several of these transformation strategies in the manipulation of secondarymetabolism. These are outlined under four subheadings which include developmentally regulated genes, addition of novel genes, down-regulation of specific genes and insertion of regulatory genes. Finally, under concluding remarks, reference is made to the advances achieved in the manipulation of plant secondarymetabolism and how these approaches may impact on this new
Although there have been many reports on the biological activity of PAHs and their transform a tion products formed by fungi (Cerniglia et al.,
1982; O kam oto and Yoshida, 1981), no attention has been paid to secondarymetabolism and m e tabolites produced during PAH m etabolization and the toxicity of these secondary metabolites. The present study shows that secondary m etabo lism of C. stipitaria can be induced by particular PAHs which results in the formation of a phyto toxic metabolite. Furtherm ore results of experi ments with radioactive labelled pyrene dem on strate, that not only transform ation and m inerali zation of PAHs contribute to the degradation of these compounds, secondarymetabolism as well has to be taken into consideration when fungal PAH metabolism is investigated.
coexpression and several other techniques, various reports have well documented that plant secondarymetabolism is under TF control (Butelli et al., 2008; Luo et al., 2008; Adato et al., 2009). TFs, such as CNR, RIN, FUL1, FUL2, ZFP2, AP2a, ERF6, CMB1, ETR3, HB1, BZR1, ARF4, GLK2, JAI1, TAGL1, SlMADS1 and SGR have been shown to be involved in regulating tomato fruit ripening (Figure 3.1) (Dong et al., 2013; Fortes et al., 2017; Liu et al., 2014; Fujisawa et al., 2013; Lin et al., 2008; Vrebalov et al., 2009). Additionally, TFs that regulate tomato secondarymetabolism have also been found. For example, CSN5B, AtERF98, ABI4, and AMR1 have been found to regulate ascorbic acid levels (Wang et al., 2013; Zhang et al., 2012; Kerchev et al., 2011; Zhang et al., 2009). Furthermore, in an attempt to combine metabolomics and transcriptomics data, Mounet et al., (2009) detected up to 37 direct gene-metabolite correlations involving regulatory genes (e.g. the correlations between glutamine, bZIP, and MYB TFs). Combined systems-based analysis of transcriptome, genetic diversity of ILs and metabolite profiling in tomato fruit elucidated important role of SlERF6 in ripening and carotenoid accumulation (Lee et al., 2011). Metabolite profiling on surface of leaves of S. pennellii ILs led to identification of genomic regions affecting acyl chain substitutions (IL1-3/1-4 and IL8- 1/8-1-1) and quantity (IL5-3 and IL11-3) of acyl-sugar metabolites (Schilmiller et al., 2010). Many attempts are also being made to annotate genes and identify key regulators of secondarymetabolism, by integrating mQTL analysis with expression QTL (eQTL) studies. For example, by integrating mQTL analysis with eQTL study in an arabidopsis Bay-06 × Sha RIL population, Sonderby et al. (2008) identified MYB28 as a candidate regulator of aliphatic glucosinolates. Little studies of such integration approaches are being conducted in tomato. Recently, Alseekh et al., (2015) have carried out metabolic correlation network analysis in tomato fruit by using primary and secondary metabolite data. Doing this, they have narrowed down two candidate genes for glycoalkaloid mQTLs. Furthermore, they have also exemplary evaluated these candidates via the use of virus-induced gene silencing (VIGS) technique.
Several members of the genus Legionella cause Legionnaires’ disease, a potentially debilitating form of pneumonia. Studies frequently focus on the abundant number of virulence factors present in this genus. However, what is often overlooked is the role of secondary metabolites from Legionella. Following whole genome sequencing, we assembled and annotated the Legionella parisiensis DSM 19216 genome. Together with 14 other members of the Legionella, we performed comparative genomics and analysed the secondary metabolite potential of each strain. We found that Legionella contains a huge variety of biosynthetic gene clusters (BGCs) that are potentially making a significant number of novel natural products with undefined function. Surprisingly, only a single Sfp-like phosphopantetheinyl transferase is found in all Legionella strains analyzed that might be responsible for the activation of all carrier proteins in primary (fatty acid biosynthesis) and secondarymetabolism (polyketide and non-ribosomal peptide synthesis). Using conserved active site motifs, we predict some novel compounds that are probably involved in cell-cell communication, differing to known communication systems. We identify several gene clusters, which may represent novel signaling mechanisms and demonstrate the natural product potential of Legionella.
In addition to temperature, light is a major influencing factor on plant quality, especially in winter when, in the northern hemisphere, artificial light is required to enable year-round production of herbal plants. In basil, the content of phenolic compounds and fresh weight production were positively correlated with increasing daily light integral from 9.3 to 17.8 mol/m²d of plants grown in a controlled environment (Dou et al., 2018). Higher light intensities in the greenhouse led to higher quantities of essential oil production including linalool and eugenol in a greenhouse experiment using different shading materials (Chang et al., 2008). Additionally, higher light intensities provided by supplemental light from HPS lamps were found to increase essential oil production in basil (Nitz and Schnitzler, 2004). As recent reviewed plant quality can also change according to spectral light quality, which has a high impact on plant morphology and secondarymetabolism (Bantis et al., 2018). With the development of LEDs, experiments with monochromatic light appeared numerous. At the beginning of LED development, the technology was focused on the emission of blue and red light to induce photosynthesis in plants. Nevertheless, for full plant development, other wavelengths are often required: far-red light is known to affect flowering, stem elongation or germination in several species (Demotes-Mainard et al., 2016). Additionally, UV-B light is supposed to induce secondarymetabolism, not only increasing the nutritional impact for the human diet (Schreiner et al., 2012) but also increasing stress tolerance in plants. Furthermore, green light can be beneficial for growth, as observed in lettuce when supplemental green light was added to red and blue LEDs (Kim et al., 2004).
Terpenes represent the largest class of secondary metabolites that are produced as volatile organic compounds in fungi by terpene cyclases (TCs) (Christianson, 2008). While polyketides and nonribosomal peptides are the major class of secondary metabolites discovered in filamentous fungi, terpenes appear to be a predominant class of secondary metabolites in Basidiomycota. Terpenes are derived from the basic five-carbon units isopentenyl diphosphate and its isomer dimethylallyl diphosphate, which are sequentially coupled via prenyltransferase enzymes to produce longer prenyl diphosphates, the direct precursors for terpene biosynthesis (Wawrzyn et al., 2012). Terpenes are classified in monoterpenes, which are derived from geranyl pyrophosphate (GPP); sesquiterpenes, generated from farnesyl pyrophosphate (FPP); diterpenes and carotenoids, produced by geranylgeranyl pyrophosphate (GGPP) (Figure 11). In fungi, most of the different classes of terpenes has been observed, except for the monoterpenes (Shaw et al., 2015). Botrydial is a sesquiterpenoid considered as the primary phytotoxic metabolite of Botrytis cinerea. It is mainly responsible for the development of necrotic lesions on tobacco and beans when applied to leaves (González-Collado et al., 2007). Trichothecenes, also belonging to the class of sesquiterpenes, contain a common 12,13-epoxytrichothene skeleton and an olefinic bond with various side chain substitutions. Fusarium is the major genus producing such compounds like diacetoxscirpenol, deoxynivalenol and T2, which are considered as potent inhibitors of eukaryotic protein synthesis (Bennett and Klich, 2003). On the other hand, aristolochenes, from A. terreus and P. roqueforti, constitute and important group of sesquiterpenes (Cane et al., 1993; Proctor and Hohn, 1993), which also likely serve as precursors for several sesquiterpenoid toxins produced by filamentous fungi (Hohn et al., 1991), including PR-toxin produced by P. roqueforti. Related to diterpenes, many Fusarium species also synthesize the plant hormones gibberellins (GAs), which act as virulence factors
compounds as well as turning sulfur-containing organic substances into easier accessible and digestible sulfate (Satola et al. 2012). Making sulfur easily accessible for their hosts could be a possible reason for the symbiosis of V. eiseniae and V. tuberculata and their respective earthworm species. The entry about the sulfur metabolism of V. eiseniae in the KEGG database shows that this scenario is unlikely, though. V. eiseniae does not seem to be capable of converting a lot of different sulfur- containing organic substances into sulfate or other easier accessible forms of sulfur (KEGG PATHWAY n.d.). Some of the previously mentioned toxic compounds were halogenated hydrocarbons which are present in the soil due to their application as herbicides or industrial solvents. Since earthworms constantly ingest soil they are likely exposed to toxic compounds. Hence, a potential benefit of the symbiosis for the earthworm hosts could be the ability of the Verminephrobacter species to degrade and detoxify those substances. Since no compounds like that were present in the medium used for the cultivation, the collected data does not contain any information about the capability of V. eiseniae and V. tuberculata to degrade them. However, according to the KEGG database V. eiseniae is capable of degrading certain chloro- and fluoro- hydrocarbons. Thus, it is possible that the competence to degrade certain possibly toxic compounds is one of the reasons for and benefits of the symbiosis.
The EMP database (Selkov et al., 1996) started as an eﬀort to curate literature in- formation on enzymology and metabolism into graphical representations of metabolic pathways. It was initiated in 1984 at the Russian Academy of Sciences to support in- ternal projects in the mathematical simulation of cell metabolism by encoding as much of the known data relating to enzymology as possible. In 1995 the pathway diagrams covering primary and secondarymetabolism, membrane transport, signal transduction pathways, intracellular traﬃc, translation and transcription were made freely available to other researchers. Later the pathways from EMP were integrated into the PUMA system (see Section 2.2.8) and further developed into MPW, the Metabolic Pathways Database. The original pathway diagrams of the EMP database were converted into a standardized data format. The stoichiometry of reactions as well as substrate and coenzyme speciﬁcity of enzymes, their sub-cellular locations, required prosthetic groups and cofactors, and taxonomic occurrence (not organism speciﬁc) of the reactions are presented on the respective diagrams (Selkov et al., 1998). The EMP pathways can be downloaded from ftp://ftp.mcs.anl.gov/pub/compbio/PUMA2/EMP_DATA/. However, this version has not been updated since 2002.
AUTHOr’S MAIn MeSSAGe
Married women moving to major immigrant-receiving countries tend to assimilate into the labor market following patterns similar to those for immigrant men: employment and wages grow along with years in the country. Studies of skill progression also find mobility toward higher status jobs. While these findings seem to dispel the notion that immigrant women behave like secondary workers, studies find that highly educated immigrants remain disproportionally in low-skill occupations. Policies to integrate immigrant women in the labor market, by providing support in finding initial jobs, could improve the economic assimilation of immigrant families.
This paper offers a theory of the macroeconomic effects of secondary market trading. Secondary market trading impacts the flow of credit through the distribution of aggregate risk exposure in the cross-section of financial intermediaries. Some risk transfer away from constrained lenders relaxes a borrowing constraint and allows for the expansion of credit volumes. Excessive risk transfer destroys monitoring incentives and leads to lax credit standards and excessive aggregate risk exposure. The level of risk transfer is determined by the distribution of wealth in the financial system. I distinguish between “banks” – intermediaries that lend to firms and household directly, such as commercial banks or mortgage originators – and “financiers” – those who do trade in assets originated by other intermediaries, such as hedge funds or dealer banks. There is exces- sive risk transfer when financiers are too well-capitalized relative to banks. Dynamically, the risk transfer that allows credit volumes to expand when financiers are not too large causes financier wealth to grow disproportionately after a sequence of good shocks. As a result, there are credit cycles with gradually declining investment efficiency and increasing financial fragility.
a pecuniary externality, but it affects real investment quality rather than liquidity.
Mendoza (2010) quantitatively studies collateral constraints and leverage over the business cycle, and shows that these constraints amplify the response to negative macroeconomic shocks. Lorenzoni (2008), Bianchi (2011), and Bianchi and Mendoza (2012) show that pecuniary external- ities can trigger fire sales that amplify credit crunches, while Bigio (2014) and Kurlat (2013) study market shutdowns during downturns. I study how the reallocation of risk during upturns harms credit quality and generates excessive risk-taking. Di Tella (2014) shows that financial interme- diaries want to insure themselves against aggregate shocks that tighten equity-based borrowing constraints. I study the allocation of risk across heteregeneous intermediaries when a V aR = 0 rule prevents such risk-sharing amongst all agents. Gorton and Ordo ˜nez (2014) propose a dynamic model of credit booms and busts based on the desire of agents to trade informationally-insensitive assets. Booms and busts occur due to the evolution of beliefs. I emphasize the evolution of the wealth distribution and the deterioration of investment efficiency over the credit cycle. Gennaioli, Shleifer, and Vishny (2013) argue that securitization allows for improved sharing of idiosyncratic risk, and is efficient unless agents neglect aggregate risk. I study the re-allocation of aggregate risk, and show that excessive secondary market trading can have deleterious effects even in a fully rational framework. Moreover, I explicitly model the dynamics of secondary markets and argue why booms can endogenously lead to financial fragility. Parlour and Plantin (2008) and Vanasco (2014) have studied the effects of secondary market liquidity on moral hazard and infor- mation acquisition in primary markets in static partial equilibrium settings. I differ in that I study the macroeconomic dynamics of secondary markets and emphasize the endogenous evolution of intermediary wealth. Chari, Shourideh, and Zetlin-Jones (2014) show how secondary markets may collapse suddenly in the presence of adverse selection. I study how growing secondary mar- kets can lead to falling asset quality. This concern is shared by Bolton, Santos, and Scheinkman (2016), who study how origination incentives vary with the demand for assets by informed and uninformed buyers.
and signal signal power. An extended discussion on the calculation method is provided in .
Figure 6.2 shows the link spectral efficiency in relation to the spectral power density of the received signal from the eNodeB. We have normalized the power to the CC bandwidth in order to more easily compare it to a pure thermal noise environment. The black dashed line shows the baseline case, when the LTE equipment operates in exclusive spectrum. We observe that at a power density level of -167.6 dBm/Hz, which is only 6.3 dB above the thermal noise floor (-174 dBm/Hz), a link can be established. At -142.4 dBm/Hz, i.e. 31.8 dB above the noise floor, LTE reaches its maximum spectral exploitation capabil- ity. For a secondary deployments, this metric is significantly worsened. In order to support a minimum MCS connection, the power density of a cell lo- cated at the closest permissible distance to the coverage contour needs to be 9 dB higher than for the exclusive spectrum case. An equivalent increase in power density is required for the highest MCS in relation to the non-interfered case. This is a relevant finding, as it shows that the relative distance between an UE and the primary interference source in relation to the distance to the eNodeB plays a subordinate role, i.e. the primary interference may be readily approximated by a constant decrease in SINR over the whole cell area. We also plot results for LTE cells at increased distances to the coverage contour. For a cell located 54 km from the coverage contour, the increase in noise plus inter- ference reduces to 3.8 dB, i.e. primary-induced interference level increases the noise floor by 140%. At approximately 59 km, the noise floor increase equals the erosion margin ε. These figures depict the obvious asymmetry between the radio systems operating in the same spectrum band, where the effect of primary interference on the secondary exceeds the permissible SINR reduc- tion of the primary due to secondary activities.
McKay intended going.
For a single jury to convict D as a secondary party of any kind to a murder by P that the jury is not sure P committed because they are not sure P intended at least GBH or that P was not acting in lawful self defence is quite another matter. All three commentators noted above are to varying degrees equivocal about this possibil- ity. The CFA accepts this maybe the law for joint enterprise D but “not on the basis of accessorial liability only”. But why? D’s and P’s initial intention that the killing would occur would be the same in either case.
In the absence of cognitive constraints, the DM would optimize R 1 at the first stage and then R 2 at the second stage, amounting to a procedure of lexicographic preference maximization. Indeed, this is precisely how our DM will behave when faced with “binary” choice problems containing just two alternatives. For instance, when facing the menu xy, a DM with the two relations specified above will apply the strict primary preference xP 1 y and eliminate alternative y from consideration, at which point the secondary relation R 2 is irrelevant. The rationale here is that binary menus are particularly simple in terms of cognition, and so it is in these contexts that the DM’s true primary rankings are most likely to be reflected accurately.
The expression of genes coordinating iron uptake, storage and export is regulated in re- sponse to iron supply . This regulation is executed by the IRE-IRP system and made possible by the ability of cytosolic iron regulatory proteins (IRP1 and IRP2), which represent homolog proteins that sense cellular iron status to affect the stability of mRNA or translation from mRNA into protein. In cells that are iron depleted, IRP1 and IRP2 bind to conserved stem-loop structures found in the mRNAs of iron-regulatory proteins, which are known as iron responsive elements (IREs) . In ferritin mRNA and isoforms of FPN1 mRNA, the IREs are located in the 5’-untranslated region (UTR) near the cap-binding site, where transla- tion factors usually bind. Binding of IRPs to this site down-regulate the translation of these proteins, because translation factors or ribosomes cannot bind. In contrast, in TFR1 mRNA and isoforms of DMT1 mRNA, the IREs are found in the 3’-UTR, a region of the mRNA that is important for regulating the half-life of transcripts. IRP binding to these IREs stabilizes the mRNA resulting in increased protein levels . The translation of other proteins involved in iron metabolism such as HIF2 α is controlled by the IRE-IRP regulatory system as well . However, the IRE-IRP system is susceptible to many disturbances, especially the activation of the interaction between IRE and IRP by iron chelator, nitric oxide (NO), hypoxia and H 2 O 2 ,
Interferons (IFNs) are potent pleiotropic cytokines that broadly alter cellular functions in response to viral and other infections. These alterations include changes in protein synthesis, proliferation, membrane composition, and the nutritional microenvironment. Recent evidence suggests that antiviral responses are supported by an IFN-induced rewiring of the cellular metabolism. In this review, we discuss the roles of type I and type II IFNs in regulating the cellular metabolism and biosynthetic reactions. Furthermore, we give an overview of how viruses themselves affect these metabolic activities to promote their replication. In addition, we focus on the lipid as well as amino acid metabolisms, through which IFNs exert potent antiviral and immunomodulatory activities. Conversely, the expression of IFNs is controlled by the nutrient sensor mammalian target of rapa- mycin or by direct reprograming of lipid metabolic pathways. These findings establish a mutual relationship between IFN production and metabolic core processes.
V. Peroxidizing Herbicides
VI. Amino Acid and N-Metabolism; Miscella neous Topics.
Papers on photosystem II inhibition dominated due both to the following 9th Intern. Congress on Photosynthesis in Nagoya as well as to the ad vanced studies and understanding of this part of photosynthesis. One afternoon was assigned to