The nuclease activity of DNA2 promotes exonuclease 1–independent mismatch repair

The DNA mismatch repair (MMR) system is a major DNA repair system that corrects DNA replication errors. In eukaryotes, the MMR system functions via mechanisms both dependent on and independent of exonuclease 1 (EXO1), an enzyme that has multiple roles in DNA metabolism. Although the mechanism of EXO1-dependent MMR is well understood, less is known about EXO1-independent MMR. Here, we provide genetic and biochemical evidence that the DNA2 nuclease/helicase has a role in EXO1-independent MMR. Biochemical reactions reconstituted with purified human proteins demonstrated that the nuclease activity of DNA2 promotes an EXO1-independent MMR reaction via a mismatch excision-independent mechanism that involves DNA polymerase δ. We show that DNA polymerase ε is not able to replace DNA polymerase δ in the DNA2-promoted MMR reaction. Unlike its nuclease activity, the helicase activity of DNA2 is dispensable for the ability of the protein to enhance the MMR reaction. Further examination established that DNA2 acts in the EXO1-independent MMR reaction by increasing the strand-displacement activity of DNA polymerase δ. These data reveal a mechanism for EXO1-independent mismatch repair.

The mismatch repair (MMR) system has been conserved from bacteria to humans (1, 2). It promotes genome stability by suppressing spontaneous and DNA damage-induced mutations (1, 3, 4, 5, 6, 7, 8, 9, 10, 11). The key function of the MMR system is the correction of DNA replication errors that escape the proofreading activities of replicative DNA polymerases (1, 4, 5, 6, 7, 8, 9, 10, 12). In addition, the MMR system removes mismatches formed during strand exchange in homologous recombination, suppresses homeologous recombination, initiates apoptosis in response to irreparable DNA damage caused by several anticancer drugs, and contributes to instability of triplet repeats and alternative DNA structures (1, 4, 5, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18). The principal components of the eukaryotic MMR system are MutSα (MSH2-MSH6 heterodimer), MutLα (MLH1-PMS2 heterodimer in humans and Mlh1-Pms1 heterodimer in yeast), MutSβ (MSH2-MSH3 heterodimer), proliferating cell nuclear antigen (PCNA), replication factor C (RFC), exonuclease 1 (EXO1), RPA, and DNA polymerase δ (Pol δ). Loss-of-function mutations in the MSH2, MLH1, MSH6, and PMS2 genes of the human MMR system cause Lynch and Turcot syndromes, and hypermethylation of the MLH1 promoter is responsible for ∼15% of sporadic cancers in several organs (19, 20). MMR deficiency leads to cancer initiation and progression via a multistage process that involves the inactivation of tumor suppressor genes and action of oncogenes (21).MMR occurs behind the replication fork (22, 23) and is a major determinant of the replication fidelity (24). The correction of DNA replication errors by the MMR system increases the replication fidelity by ∼100 fold (25). Strand breaks in leading and lagging strands as well as ribonucleotides in leading strands serve as signals that direct the eukaryotic MMR system to remove DNA replication errors (26, 27, 28, 29, 30). MMR is more efficient on the lagging than the leading strand (31). The substrates for MMR are all six base–base mismatches and 1 to 13-nt insertion/deletion loops (25, 32, 33, 34). Eukaryotic MMR commences with recognition of the mismatch by MutSα or MutSβ (32, 34, 35, 36). MutSα is the primary mismatch-recognition factor that recognizes both base–base mismatches and small insertion/deletion loops whereas MutSβ recognizes small insertion/deletion loops (32, 34, 35, 36, 37). After recognizing the mismatch, MutSα or MutSβ cooperates with RFC-loaded PCNA to activate MutLα endonuclease (38, 39, 40, 41, 42, 43). The activated MutLα endonuclease incises the discontinuous daughter strand 5′ and 3′ to the mismatch. A 5'' strand break formed by MutLα endonuclease is utilized by EXO1 to enter the DNA and excise a discontinuous strand portion encompassing the mismatch in a 5''→3′ excision reaction stimulated by MutSα/MutSβ (38, 44, 45). The generated gap is filled in by the Pol δ holoenzyme, and the nick is ligated by a DNA ligase (44, 46, 47). DNA polymerase ε (Pol ε) can substitute for Pol δ in the EXO1-dependent MMR reaction, but its activity in this reaction is much lower than that of Pol δ (48). Although MutLα endonuclease is essential for MMR in vivo, 5′ nick-dependent MMR reactions reconstituted in the presence of EXO1 are MutLα-independent (44, 47, 49).EXO1 deficiency in humans does not seem to cause significant cancer predisposition (19). Nevertheless, it is known that Exo1^-/- mice are susceptible to the development of lymphomas (50). Genetic studies in yeast and mice demonstrated that EXO1 inactivation causes only a modest defect in MMR (50, 51, 52, 53). In agreement with these genetic studies, a defined human EXO1-independent MMR reaction that depends on the strand-displacement DNA synthesis activity of Pol δ holoenzyme to remove the mismatch was reconstituted (54). Furthermore, an EXO1-independent MMR reaction that occurred in a mammalian cell extract system without the formation of a gapped excision intermediate was observed (54). Together, these findings implicated the strand-displacement activity of Pol δ holoenzyme in EXO1-independent MMR.In this study, we investigated DNA2 in the context of MMR. DNA2 is an essential multifunctional protein that has nuclease, ATPase, and 5''→3′ helicase activities (55, 56, 57). Previous research ascertained that DNA2 removes long flaps during Okazaki fragment maturation (58, 59, 60), participates in the resection step of double-strand break repair (61, 62, 63), initiates the replication checkpoint (64), and suppresses the expansions of GAA repeats (65). We have found in vivo and in vitro evidence that DNA2 promotes EXO1-independent MMR. Our data have indicated that the nuclease activity of DNA2 enhances the strand-displacement activity of Pol δ holoenzyme in an EXO1-independent MMR reaction.     

TRAF2 is a biologically important necroptosis suppressor

Tumor necrosis factor α (TNFα) triggers necroptotic cell death through an intracellular signaling complex containing receptor-interacting protein kinase (RIPK) 1 and RIPK3, called the necrosome. RIPK1 phosphorylates RIPK3, which phosphorylates the pseudokinase mixed lineage kinase-domain-like (MLKL)—driving its oligomerization and membrane-disrupting necroptotic activity. Here, we show that TNF receptor-associated factor 2 (TRAF2)—previously implicated in apoptosis suppression—also inhibits necroptotic signaling by TNFα. TRAF2 disruption in mouse fibroblasts augmented TNFα–driven necrosome formation and RIPK3-MLKL association, promoting necroptosis. TRAF2 constitutively associated with MLKL, whereas TNFα reversed this via cylindromatosis-dependent TRAF2 deubiquitination. Ectopic interaction of TRAF2 and MLKL required the C-terminal portion but not the N-terminal, RING, or CIM region of TRAF2. Induced TRAF2 knockout (KO) in adult mice caused rapid lethality, in conjunction with increased hepatic necrosome assembly. By contrast, TRAF2 KO on a RIPK3 KO background caused delayed mortality, in concert with elevated intestinal caspase-8 protein and activity. Combined injection of TNFR1-Fc, Fas-Fc and DR5-Fc decoys prevented death upon TRAF2 KO. However, Fas-Fc and DR5-Fc were ineffective, whereas TNFR1-Fc and interferon α receptor (IFNAR1)-Fc were partially protective against lethality upon combined TRAF2 and RIPK3 KO. These results identify TRAF2 as an important biological suppressor of necroptosis in vitro and in vivo.Apoptotic cell death is mediated by caspases and has distinct morphological features, including membrane blebbing, cell shrinkage and nuclear fragmentation.^{1, 2, 3, 4} In contrast, necroptotic cell death is caspase-independent and is characterized by loss of membrane integrity, cell swelling and implosion.^{1, 2, 5} Nevertheless, necroptosis is a highly regulated process, requiring activation of RIPK1 and RIPK3, which form the core necrosome complex.^{1, 2, 5} Necrosome assembly can be induced via specific death receptors or toll-like receptors, among other modules.^{6, 7, 8, 9} The activated necrosome engages MLKL by RIPK3-mediated phosphorylation.^{6, 10, 11} MLKL then oligomerizes and binds to membrane phospholipids, forming pores that cause necroptotic cell death.^{10, 12, 13, 14, 15} Unchecked necroptosis disrupts embryonic development in mice and contributes to several human diseases.^{7, 8, 16, 17, 18, 19, 20, 21, 22}The apoptotic mediators FADD, caspase-8 and cFLIP suppress necroptosis.^{19, 20, 21, 23, 24} Elimination of any of these genes in mice causes embryonic lethality, subverted by additional deletion of RIPK3 or MLKL.^{19, 20, 21, 25} Necroptosis is also regulated at the level of RIPK1. Whereas TNFα engagement of TNFR1 leads to K63-linked ubiquitination of RIPK1 by cellular inhibitor of apoptosis proteins (cIAPs) to promote nuclear factor (NF)-κB activation,²⁶ necroptosis requires suppression or reversal of this modification to allow RIPK1 autophosphorylation and consequent RIPK3 activation.^{2, 23, 27, 28} CYLD promotes necroptotic signaling by deubiquitinating RIPK1, augmenting its interaction with RIPK3.²⁹ Conversely, caspase-8-mediated CYLD cleavage inhibits necroptosis.²⁴TRAF2 recruits cIAPs to the TNFα-TNFR1 signaling complex, facilitating NF-κB activation.^{30, 31, 32, 33} TRAF2 also supports K48-linked ubiquitination and proteasomal degradation of death-receptor-activated caspase-8, curbing apoptosis.³⁴ TRAF2 KO mice display embryonic lethality; some survive through birth but have severe developmental and immune deficiencies and die prematurely.^{35, 36} Conditional TRAF2 KO leads to rapid intestinal inflammation and mortality.³⁷ Furthermore, hepatic TRAF2 depletion augments apoptosis activation via Fas/CD95.³⁴ TRAF2 attenuates necroptosis induction in vitro by the death ligands Apo2L/TRAIL and Fas/CD95L.³⁸ However, it remains unclear whether TRAF2 regulates TNFα-induced necroptosis—and if so—how. Our present findings reveal that TRAF2 inhibits TNFα necroptotic signaling. Furthermore, our results establish TRAF2 as a biologically important necroptosis suppressor in vitro and in vivo and provide initial insight into the mechanisms underlying this function.     

Characterization of the Possible Roles for B Class MADS Box Genes in Regulation of Perianth Formation in Orchid

To investigate sepal/petal/lip formation in Oncidium Gower Ramsey, three paleoAPETALA3 genes, O. Gower Ramsey MADS box gene5 (OMADS5; clade 1), OMADS3 (clade 2), and OMADS9 (clade 3), and one PISTILLATA gene, OMADS8, were characterized. The OMADS8 and OMADS3 mRNAs were expressed in all four floral organs as well as in vegetative leaves. The OMADS9 mRNA was only strongly detected in petals and lips. The mRNA for OMADS5 was only strongly detected in sepals and petals and was significantly down-regulated in lip-like petals and lip-like sepals of peloric mutant flowers. This result revealed a possible negative role for OMADS5 in regulating lip formation. Yeast two-hybrid analysis indicated that OMADS5 formed homodimers and heterodimers with OMADS3 and OMADS9. OMADS8 only formed heterodimers with OMADS3, whereas OMADS3 and OMADS9 formed homodimers and heterodimers with each other. We proposed that sepal/petal/lip formation needs the presence of OMADS3/8 and/or OMADS9. The determination of the final organ identity for the sepal/petal/lip likely depended on the presence or absence of OMADS5. The presence of OMADS5 caused short sepal/petal formation. When OMADS5 was absent, cells could proliferate, resulting in the possible formation of large lips and the conversion of the sepal/petal into lips in peloric mutants. Further analysis indicated that only ectopic expression of OMADS8 but not OMADS5/9 caused the conversion of the sepal into an expanded petal-like structure in transgenic Arabidopsis (Arabidopsis thaliana) plants.The ABCDE model predicts the formation of any flower organ by the interaction of five classes of homeotic genes in plants (Yanofsky et al., 1990; Jack et al., 1992; Mandel et al., 1992; Goto and Meyerowitz, 1994; Jofuku et al., 1994; Pelaz et al., 2000, 2001; Theißen and Saedler, 2001; Pinyopich et al., 2003; Ditta et al., 2004; Jack, 2004). The A class genes control sepal formation. The A, B, and E class genes work together to regulate petal formation. The B, C, and E class genes control stamen formation. The C and E class genes work to regulate carpel formation, whereas the D class gene is involved in ovule development. MADS box genes seem to have a central role in flower development, because most ABCDE genes encode MADS box proteins (Coen and Meyerowitz, 1991; Weigel and Meyerowitz, 1994; Purugganan et al., 1995; Rounsley et al., 1995; Theißen and Saedler, 1995; Theißen et al., 2000; Theißen, 2001).The function of B group genes, such as APETALA3 (AP3) and PISTILLATA (PI), has been thought to have a major role in specifying petal and stamen development (Jack et al., 1992; Goto and Meyerowitz, 1994; Krizek and Meyerowitz, 1996; Kramer et al., 1998; Hernandez-Hernandez et al., 2007; Kanno et al., 2007; Whipple et al., 2007; Irish, 2009). In Arabidopsis (Arabidopsis thaliana), mutation in AP3 or PI caused identical phenotypes of second whorl petal conversion into a sepal structure and third flower whorl stamen into a carpel structure (Bowman et al., 1989; Jack et al., 1992; Goto and Meyerowitz, 1994). Similar homeotic conversions for petal and stamen were observed in the mutants of the AP3 and PI orthologs from a number of core eudicots such as Antirrhinum majus, Petunia hybrida, Gerbera hybrida, Solanum lycopersicum, and Nicotiana benthamiana (Sommer et al., 1990; Tröbner et al., 1992; Angenent et al., 1993; van der Krol et al., 1993; Yu et al., 1999; Liu et al., 2004; Vandenbussche et al., 2004; de Martino et al., 2006), from basal eudicot species such as Papaver somniferum and Aquilegia vulgaris (Drea et al., 2007; Kramer et al., 2007), as well as from monocot species such as Zea mays and Oryza sativa (Ambrose et al., 2000; Nagasawa et al., 2003; Prasad and Vijayraghavan, 2003; Yadav et al., 2007; Yao et al., 2008). This indicated that the function of the B class genes AP3 and PI is highly conserved during evolution.It has been thought that B group genes may have arisen from an ancestral gene through multiple gene duplication events (Doyle, 1994; Theißen et al., 1996, 2000; Purugganan, 1997; Kramer et al., 1998; Kramer and Irish, 1999; Lamb and Irish, 2003; Kim et al., 2004; Stellari et al., 2004; Zahn et al., 2005; Hernandez-Hernandez et al., 2007). In the gymnosperms, there was a single putative B class lineage that duplicated to generate the paleoAP3 and PI lineages in angiosperms (Kramer et al., 1998; Theißen et al., 2000; Irish, 2009). The paleoAP3 lineage is composed of AP3 orthologs identified in lower eudicots, magnolid dicots, and monocots (Kramer et al., 1998). Genes in this lineage contain the conserved paleoAP3- and PI-derived motifs in the C-terminal end of the proteins, which have been thought to be characteristics of the B class ancestral gene (Kramer et al., 1998; Tzeng and Yang, 2001; Hsu and Yang, 2002). The PI lineage is composed of PI orthologs that contain a highly conserved PI motif identified in most plant species (Kramer et al., 1998). Subsequently, there was a second duplication at the base of the core eudicots that produced the euAP3 and TM6 lineages, which have been subject to substantial sequence changes in eudicots during evolution (Kramer et al., 1998; Kramer and Irish, 1999). The paleoAP3 motif in the C-terminal end of the proteins was retained in the TM6 lineage and replaced by a conserved euAP3 motif in the euAP3 lineage of most eudicot species (Kramer et al., 1998). In addition, many lineage-specific duplications for paleoAP3 lineage have occurred in plants such as orchids (Hsu and Yang, 2002; Tsai et al., 2004; Kim et al., 2007; Mondragón-Palomino and Theißen, 2008, 2009; Mondragón-Palomino et al., 2009), Ranunculaceae, and Ranunculales (Kramer et al., 2003; Di Stilio et al., 2005; Shan et al., 2006; Kramer, 2009).Unlike the A or C class MADS box proteins, which form homodimers that regulate flower development, the ability of B class proteins to form homodimers has only been reported in gymnosperms and in the paleoAP3 and PI lineages of some monocots. For example, LMADS1 of the lily Lilium longiflorum (Tzeng and Yang, 2001), OMADS3 of the orchid Oncidium Gower Ramsey (Hsu and Yang, 2002), and PeMADS4 of the orchid Phalaenopsis equestris (Tsai et al., 2004) in the paleoAP3 lineage, LRGLOA and LRGLOB of the lily Lilium regale (Winter et al., 2002), TGGLO of the tulip Tulipa gesneriana (Kanno et al., 2003), and PeMADS6 of the orchid P. equestris (Tsai et al., 2005) in the PI lineage, and GGM2 of the gymnosperm Gnetum gnemon (Winter et al., 1999) were able to form homodimers that regulate flower development. Proteins in the euAP3 lineage and in most paleoAP3 lineages were not able to form homodimers and had to interact with PI to form heterodimers in order to regulate petal and stamen development in various plant species (Schwarz-Sommer et al., 1992; Tröbner et al., 1992; Riechmann et al., 1996; Moon et al., 1999; Winter et al., 2002; Kanno et al., 2003; Vandenbussche et al., 2004; Yao et al., 2008). In addition to forming dimers, AP3 and PI were able to interact with other MADS box proteins, such as SEPALLATA1 (SEP1), SEP2, and SEP3, to regulate petal and stamen development (Pelaz et al., 2000; Honma and Goto, 2001; Theißen and Saedler, 2001; Castillejo et al., 2005).Orchids are among the most important plants in the flower market around the world, and research on MADS box genes has been reported for several species of orchids during the past few years (Lu et al., 1993, 2007; Yu and Goh, 2000; Hsu and Yang, 2002; Yu et al., 2002; Hsu et al., 2003; Tsai et al., 2004, 2008; Xu et al., 2006; Guo et al., 2007; Kim et al., 2007; Chang et al., 2009). Unlike the flowers in eudicots, the nearly identical shape of the sepals and petals as well as the production of a unique lip in orchid flowers make them a very special plant species for the study of flower development. Four clades (1–4) of genes in the paleoAP3 lineage have been identified in several orchids (Hsu and Yang, 2002; Tsai et al., 2004; Kim et al., 2007; Mondragón-Palomino and Theißen, 2008, 2009; Mondragón-Palomino et al., 2009). Several works have described the possible interactions among these four clades of paleoAP3 genes and one PI gene that are involved in regulating the differentiation and formation of the sepal/petal/lip of orchids (Tsai et al., 2004; Kim et al., 2007; Mondragón-Palomino and Theißen, 2008, 2009). However, the exact mechanism that involves the orchid B class genes remains unclear and needs to be clarified by more experimental investigations.O. Gower Ramsey is a popular orchid with important economic value in cut flower markets. Only a few studies have been reported on the role of MADS box genes in regulating flower formation in this plant species (Hsu and Yang, 2002; Hsu et al., 2003; Chang et al., 2009). An AP3-like MADS gene that regulates both floral formation and initiation in transgenic Arabidopsis has been reported (Hsu and Yang, 2002). In addition, four AP1/AGAMOUS-LIKE9 (AGL9)-like MADS box genes have been characterized that show novel expression patterns and cause different effects on floral transition and formation in Arabidopsis (Hsu et al., 2003; Chang et al., 2009). Compared with other orchids, the production of a large and well-expanded lip and five small identical sepals/petals makes O. Gower Ramsey a special case for the study of the diverse functions of B class MADS box genes during evolution. Therefore, the isolation of more B class MADS box genes and further study of their roles in the regulation of perianth (sepal/petal/lip) formation during O. Gower Ramsey flower development are necessary. In addition to the clade 2 paleoAP3 gene OMADS3, which was previously characterized in our laboratory (Hsu and Yang, 2002), three more B class MADS box genes, OMADS5, OMADS8, and OMADS9, were characterized from O. Gower Ramsey in this study. Based on the different expression patterns and the protein interactions among these four orchid B class genes, we propose that the presence of OMADS3/8 and/or OMADS9 is required for sepal/petal/lip formation. Further sepal and petal formation at least requires the additional presence of OMADS5, whereas large lip formation was seen when OMADS5 expression was absent. Our results provide a new finding and information pertaining to the roles for orchid B class MADS box genes in the regulation of sepal/petal/lip formation.     

Ret is essential to mediate GDNF's neuroprotective and neuroregenerative effect in a Parkinson disease mouse model

Glial cell line-derived neurotrophic factor (GDNF) is a potent survival and regeneration-promoting factor for dopaminergic neurons in cell and animal models of Parkinson disease (PD). GDNF is currently tested in clinical trials on PD patients with so far inconclusive results. The receptor tyrosine kinase Ret is the canonical GDNF receptor, but several alternative GDNF receptors have been proposed, raising the question of which signaling receptor mediates here the beneficial GDNF effects. To address this question we overexpressed GDNF in the striatum of mice deficient for Ret in dopaminergic neurons and subsequently challenged these mice with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Strikingly, in this established PD mouse model, the absence of Ret completely abolished GDNF''s neuroprotective and regenerative effect on the midbrain dopaminergic system. This establishes Ret signaling as absolutely required for GDNF''s effects to prevent and compensate dopaminergic system degeneration and suggests Ret activation as the primary target of GDNF therapy in PD.Glial cell line-derived neurotrophic factor (GDNF) is the founding member of the four ligands in the GDNF family, which belong to the transforming growth factor-β superfamily.¹ GDNF was characterized as a potent survival factor for many neurons in culture such as dopaminergic, motor, sympathetic, parasympathetic, sensory and enteric neurons.^{1, 2} In addition, in dopaminergic neuron cultures GDNF stimulates neuronal differentiation, neurite outgrowth, synapse formation and dopamine release.^{1, 2}As degeneration of midbrain dopaminergic neurons in the substantia nigra pars compacta (SNpc) represents a major hallmark of Parkinson disease (PD), the most common neurodegenerative movement disorder, GDNF has raised considerable interest as a therapeutic molecule for the treatment of PD.^{3, 4, 5} PD affects >2% of individuals over the age of 60 years, but no curative treatment is available to date, mainly due to a lack of understanding disease etiology.^{6, 7, 8} Preclinical studies in the established 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and 6-hydroxydopamine (6-OHDA) rodent and primate models of PD demonstrated a substantial neuroprotection and regeneration effect by striatal provided GDNF or its close relative neurturin.^{3, 4, 9} However, clinical phase II trials on PD patients using GDNF or neurturin did so far not convincingly recapitulate their beneficial effects on the dopaminergic system in humans most likely due to technical problems and the selection of advanced PD patients.^{10, 11, 12, 13}GDNF signaling is highly complex as this neurotrophic factor can bind to a variety of receptors, thus being able to induce pleiotropic effects. GDNF efficiently binds to the GPI-linked GDNF family receptor α1 (GFRα1).^{1, 2} It has been shown that the GDNF/GFRα1 complex can activate not only the canonical GDNF receptor Ret, a receptor tyrosine kinase which signals through the sarcoma protein (Src)/rat sarcoma (Ras)/mitogen-activated protein kinase (MAPK), phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K)/Akt, NF-κB (nuclear factor ''kappa-light-chain-enhancer'' of activated B cells), JNK (c-Jun N-terminal kinases) and PLCγ (phospholipase γ) pathway, but also with other signaling inducing receptors.^{1, 2, 4, 5, 13} So far, at least four alternative GDNF receptors have been described which are all expressed in midbrain dopaminergic neurons, NCAM,^{14, 15} the integrins αV and βI,^{14, 16} syndecan 3¹⁷ and N-cadherin.¹⁸ Interestingly, Ret is not essential during pre- and postnatal development of the mouse dopaminergic system,^{19, 20, 21, 22, 23} but specifically required for the maintenance of SNpc dopaminergic neurons and their striatal innervation in aged mice.^{23, 24, 25} In contrast, GDNF seems most likely under physiological conditions to be dispensable during development and maintenance of midbrain dopaminergic neurons in mice, although conflicting results exist.^{26, 27, 28} Thus, Ret might be activated by a GDNF-independent mechanism to stimulate SNpc dopaminergic neuron survival. In addition, the in vivo function of the alternative GDNF receptors in the dopaminergic system under physiological and pathophysiological conditions, like PD, and their dependence on GDNF has not yet been addressed in detail. This raised the important question which GDNF receptor might be required to mediate GDNF''s reported neuroprotective and regenerative effect in the dopaminergic system in PD animal models and potentially in PD patients.^{5, 29}Previously, we showed in dopaminergic neuron-specific Ret knockout mice that Ret receptor loss does not result in a higher vulnerability of midbrain dopaminergic neurons against MPTP but to less resprouting of left over dopaminergic neuron axons in the striatum after MPTP intoxication.³⁰ In adult mice endogenous GDNF levels are rather low.^{26, 31} Therefore, we could not rule out in that study the possibility, that higher levels of GDNF—as also used in the clinical GDNF trials in PD patients—might have neuroprotective and regenerating effects even in the absence of the Ret receptor. Here we addressed now this question by viral overexpression of GDNF in MPTP-treated mice lacking expression of Ret again specifically in dopaminergic neurons.^{23, 30} We found that in the absence of Ret in dopaminergic neurons even a substantial overexpression of GDNF in the striatum does not have a neuroprotective and regenerative effect. Thus, despite the expression of alternative GDNF receptors on midbrain dopaminergic neurons, the presence of the canonical GDNF receptor Ret seems to be mandatory for mediating GDNF''s beneficial survival and axonal resprouting effect in these neurons.     

Plasma membrane poration by opioid neuropeptides: a possible mechanism of pathological signal transduction

Neuropeptides induce signal transduction across the plasma membrane by acting through cell-surface receptors. The dynorphins, endogenous ligands for opioid receptors, are an exception; they also produce non-receptor-mediated effects causing pain and neurodegeneration. To understand non-receptor mechanism(s), we examined interactions of dynorphins with plasma membrane. Using fluorescence correlation spectroscopy and patch-clamp electrophysiology, we demonstrate that dynorphins accumulate in the membrane and induce a continuum of transient increases in ionic conductance. This phenomenon is consistent with stochastic formation of giant (~2.7 nm estimated diameter) unstructured non-ion-selective membrane pores. The potency of dynorphins to porate the plasma membrane correlates with their pathogenic effects in cellular and animal models. Membrane poration by dynorphins may represent a mechanism of pathological signal transduction. Persistent neuronal excitation by this mechanism may lead to profound neuropathological alterations, including neurodegeneration and cell death.Neuropeptides are the largest and most diverse family of neurotransmitters. They are released from axon terminals and dendrites, diffuse to pre- or postsynaptic neuronal structures and activate membrane G-protein-coupled receptors. Prodynorphin (PDYN)-derived opioid peptides including dynorphin A (Dyn A), dynorphin B (Dyn B) and big dynorphin (Big Dyn) consisting of Dyn A and Dyn B are endogenous ligands for the κ-opioid receptor. Acting through this receptor, dynorphins regulate processing of pain and emotions, memory acquisition and modulate reward induced by addictive substances.^{1, 2, 3, 4} Furthermore, dynorphins may produce robust cellular and behavioral effects that are not mediated through opioid receptors.^{5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29} As evident from pharmacological, morphological, genetic and human neuropathological studies, these effects are generally pathological, including cell death, neurodegeneration, neurological dysfunctions and chronic pain. Big Dyn is the most active pathogenic peptide, which is about 10- to 100-fold more potent than Dyn A, whereas Dyn B does not produce non-opioid effects.^{16, 17, 22, 25} Big Dyn enhances activity of acid-sensing ion channel-1a (ASIC1a) and potentiates ASIC1a-mediated cell death in nanomolar concentrations^{30, 31} and, when administered intrathecally, induces characteristic nociceptive behavior at femtomolar doses.^{17, 22} Inhibition of endogenous Big Dyn degradation results in pathological pain, whereas prodynorphin (Pdyn) knockout mice do not maintain neuropathic pain.^{22, 32} Big Dyn differs from its constituents Dyn A and Dyn B in its unique pattern of non-opioid memory-enhancing, locomotor- and anxiolytic-like effects.²⁵Pathological role of dynorphins is emphasized by the identification of PDYN missense mutations that cause profound neurodegeneration in the human brain underlying the SCA23 (spinocerebellar ataxia type 23), a very rare dominantly inherited neurodegenerative disorder.^{27, 33} Most PDYN mutations are located in the Big Dyn domain, demonstrating its critical role in neurodegeneration. PDYN mutations result in marked elevation in dynorphin levels and increase in its pathogenic non-opioid activity.^{27, 34} Dominant-negative pathogenic effects of dynorphins are not produced through opioid receptors.ASIC1a, glutamate NMDA (N-methyl-d-aspartate) and AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid)/kainate ion channels, and melanocortin and bradykinin B2 receptors have all been implicated as non-opioid dynorphin targets.^{5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 30, 31, 35, 36} Multiplicity of these targets and their association with the cellular membrane suggest that their activation is a secondary event triggered by a primary interaction of dynorphins with the membrane. Dynorphins are among the most basic neuropeptides.^{37, 38} The basic nature is also a general property of anti-microbial peptides (AMPs) and amyloid peptides that act by inducing membrane perturbations, altering membrane curvature and causing pore formation that disrupts membrane-associated processes including ion fluxes across the membrane.³⁹ The similarity between dynorphins and these two peptide groups in overall charge and size suggests a similar mode of their interactions with membranes.In this study, we dissect the interactions of dynorphins with the cell membrane, the primary event in their non-receptor actions. Using fluorescence imaging, correlation spectroscopy and patch-clamp techniques, we demonstrate that dynorphin peptides accumulate in the plasma membrane in live cells and cause a profound transient increase in cell membrane conductance. Membrane poration by endogenous neuropeptides may represent a novel mechanism of signal transduction in the brain. This mechanism may underlie effects of dynorphins under pathological conditions including chronic pain and tissue injury.     

Functional Genomics Reveals That a Compact Terpene Synthase Gene Family Can Account for Terpene Volatile Production in Apple

Terpenes are specialized plant metabolites that act as attractants to pollinators and as defensive compounds against pathogens and herbivores, but they also play an important role in determining the quality of horticultural food products. We show that the genome of cultivated apple (Malus domestica) contains 55 putative terpene synthase (TPS) genes, of which only 10 are predicted to be functional. This low number of predicted functional TPS genes compared with other plant species was supported by the identification of only eight potentially functional TPS enzymes in apple ‘Royal Gala’ expressed sequence tag databases, including the previously characterized apple (E,E)-α-farnesene synthase. In planta functional characterization of these TPS enzymes showed that they could account for the majority of terpene volatiles produced in cv Royal Gala, including the sesquiterpenes germacrene-D and (E)-β-caryophyllene, the monoterpenes linalool and α-pinene, and the homoterpene (E)-4,8-dimethyl-1,3,7-nonatriene. Relative expression analysis of the TPS genes indicated that floral and vegetative tissues were the primary sites of terpene production in cv Royal Gala. However, production of cv Royal Gala floral-specific terpenes and TPS genes was observed in the fruit of some heritage apple cultivars. Our results suggest that the apple TPS gene family has been shaped by a combination of ancestral and more recent genome-wide duplication events. The relatively small number of functional enzymes suggests that the remaining terpenes produced in floral and vegetative and fruit tissues are maintained under a positive selective pressure, while the small number of terpenes found in the fruit of modern cultivars may be related to commercial breeding strategies.Terpenes (also referred to as terpenoids or isoprenoids) constitute a large class of plant natural products with highly diversified functionality. Terpenes serve as precursors for the biosynthesis of essential plant metabolites (Croteau et al., 2000), including those involved in growth regulation (GAs, abscisic acid, and strigolactones), membrane stabilization (sterols), photosynthesis (carotenoids and the phytol side chain of chlorophyll), and electron transport coenzymes (ubiquinone and plastoquinone). Primarily, however, terpenes function as specialized plant metabolites that operate as attractants to pollinators or as defensive compounds against pathogens and herbivores (Kessler and Baldwin, 2001; Pichersky and Gershenzon, 2002). Terpenes are also important in determining the quality of horticultural food products, including the taste and aroma of wine (Styger et al., 2011) and fruit crops such as Citrus spp. (Vora et al., 1983; Maccarone et al., 1998; Aharoni et al., 2004) and strawberry (Fragaria spp.; Aharoni et al., 2004).Terpenes are derived from linear assemblages of prenyldiphosphates, including the C10 monoterpene precursor geranyl diphosphate (GDP), the C15 sesquiterpene precursor farnesyl diphosphate (FDP), and the C20 diterpene precursor geranylgeranyl diphosphate (GGDP). The catalytic conversion of these relatively simple precursors to the diverse array of terpenes seen in nature is carried out by terpene synthase (TPS) enzymes, which have the capacity to direct myriad precursor-binding conformations through subtle variations in their conserved catalytic fold (Yoshikuni et al., 2006; O’Maille et al., 2008; Miller and Allemann, 2012).TPS gene families have been explored in Arabidopsis (Arabidopsis thaliana; Aubourg et al., 2002; Lange and Ghassemian, 2003), grape (Vitis vinifera; Martin et al., 2010), poplar (Populus trichocarpa; Tuskan et al., 2006), rice (Oryza sativa; Goff et al., 2002), and sorghum (Sorghum bicolor; Paterson et al., 2009) as well as most recently in cultivated tomato (Solanum lycopersicum; Bleeker et al., 2011; Falara et al., 2011). The identification of 44 tomato TPS genes concurs with the comparative genome analysis work of Chen et al. (2011), indicating that the plant TPS gene family is midsized, with gene numbers ranging from approximately 20 to 150. The only exception so far appears to be the moss Physcomitrella patens, which has a single functional TPS gene (Chen et al., 2011). This analysis has also extended the phylogenetics used to define the initial TPS subfamilies (TPS-a to TPS-g; Bohlmann et al., 1998; Dudareva et al., 2003; Martin et al., 2004), culminating in the merging of the TPS-e and TPS-f subgroups (comprising gymnosperm and angiosperm ent-kaurene genes associated with primary metabolism) and the TPS-h subgroup so far specific to the lycopod Selaginalla moellendorffii.The domestic apple (Malus domestica), which has long been recognized by consumers for its flavor, health, and nutritional properties (Harker et al., 2003), is one of the most widely cultivated fruit species in the world’s temperate regions. Apple belongs to the Rosaceae family, and while most Rosaceae have a haploid chromosome number of seven, eight, or nine, Malus spp., as the result of a relatively recent genome-wide duplication (GWD) event in the Pyreae, have transitioned from nine ancestral chromosomes to 17 chromosomes (Velasco et al., 2010).Apple fruit produce more than 300 volatile organic compounds (VOCs), including alcohols, aldehyde esters, and ketones (Dimick and Hoskin, 1983; Paillard, 1990; Dixon and Hewett, 2000). Various terpenes have also been identified, although they only contribute a relatively minor component of total VOCs produced (Rapparini et al., 2001; Fuhrmann and Grosch, 2002; Hern and Dorn, 2003; Rowan et al., 2009a). The specific VOC composition in apple depends on several factors, including cultivar, climacteric ethylene production levels, maturity, and environmental conditions (Loughrin et al., 1990; Dixon and Hewett, 2000; Rapparini et al., 2001; Vallat et al., 2005). While the acyclic branched sesquiterpene (E,E)-α-farnesene appears to be the predominant terpene volatile associated with ripe fruit (Sutherland et al., 1977; Bengtsson et al., 2001; Hern and Dorn, 2003; Ferreira et al., 2009; Rowan et al., 2009b), various monoterpenes, cyclic sesquiterpenes, and terpene derivatives have also been identified, particularly in floral and vegetative tissues (Takabayashi et al., 1991; Bengtsson et al., 2001; Rapparini et al., 2001; Vallat and Dorn, 2005). Although many of these compounds are constitutively produced in relatively low amounts, a subset of common apple terpenes either are induced in response to insect infestation or have been observed to affect apple pest behavior directly. For example, (E)-β-ocimene is induced in immature apple fruit following infestation by codling moth (Cydia pomonella) larvae (Hern and Dorn, 2002), while (E,E)-α-farnesene exerts a concentration-dependent sexually dimorphic response in adult codling moth, attracting mated females at low dosages and repelling them at high dosages, while only attracting mated males at high dosages (Hern and Dorn, 1999). The relative abundance and diversity of terpenes in floral and vegetative tissues compared with ripe fruit suggests that these compounds are more likely to participate in defense and pollinator attraction roles rather than to attract seed dispersers or contribute to fruit flavor and aroma.Despite numerous studies on apple terpene volatile production, to our knowledge the only reported apple TPS enzyme to be functionally characterized is that of the α-farnesene synthase (AFS1/MdAFS1; Rupasinghe et al., 2000; Pechous and Whitaker, 2004; Green et al., 2007). The recent availability of the draft sequence assembly of the apple genome (Velasco et al., 2010), combined with a large number of accessible apple ESTs, provided an opportunity to extend the current knowledge on the organization and functional annotation of the apple TPS gene family. In this study, we initially survey the volatile terpenes produced in cv Royal Gala and then use available apple genomic and EST information to identify candidate TPS genes for functional characterization and quantitative expression analysis. We show that only a small number of the TPS genes in the apple genome encode functional TPS enzymes, but these enzymes can account for the diversity of terpenes present in apple. Our results also provide insight into how this small but evolutionarily conserved family was shaped by GWD events and how the range of terpenes has been influenced by selective pressures and commercial breeding strategies.     

Airborne Induction and Priming of Plant Defenses against a Bacterial Pathogen

Herbivore-induced plant volatiles affect the systemic response of plants to local damage and hence represent potential plant hormones. These signals can also lead to “plant-plant communication,” a defense induction in yet undamaged plants growing close to damaged neighbors. We observed this phenomenon in the context of disease resistance. Lima bean (Phaseolus lunatus) plants in a natural population became more resistant against a bacterial pathogen, Pseudomonas syringae pv syringae, when located close to conspecific neighbors in which systemic acquired resistance to pathogens had been chemically induced with benzothiadiazole (BTH). Airborne disease resistance induction could also be triggered biologically by infection with avirulent P. syringae. Challenge inoculation after exposure to induced and noninduced plants revealed that the air coming from induced plants mainly primed resistance, since expression of PATHOGENESIS-RELATED PROTEIN2 (PR-2) was significantly stronger in exposed than in nonexposed individuals when the plants were subsequently challenged by P. syringae. Among others, the plant-derived volatile nonanal was present in the headspace of BTH-treated plants and significantly enhanced PR-2 expression in the exposed plants, resulting in reduced symptom appearance. Negative effects on growth of BTH-treated plants, which usually occur as a consequence of the high costs of direct resistance induction, were not observed in volatile organic compound-exposed plants. Volatile-mediated priming appears to be a highly attractive means for the tailoring of systemic acquired resistance against plant pathogens.Plants respond to attack by pathogens or herbivores with extensive changes in gene expression that lead to induced resistance phenomena (Karban and Baldwin, 1997); various traits are then expressed de novo or at much higher intensities, which reduce or prevent further tissue damage. As both pathogens and herbivores can spread from the initial site of attack to other organs, such plant responses are often not restricted to the damaged tissue but are expressed systemically, in yet undamaged organs. Three plant hormones playing central roles in the long-distance signaling that underlies this systemic response to local attack are jasmonic acid (JA), ethylene, and salicylic acid (SA). SA and JA, in particular, are transported themselves or in the form of derivatives within the plant in order to elicit systemic responses (Truman et al., 2007; Wasternack, 2007; Heil and Ton, 2008).Recent studies have revealed that long-distance signaling is not only caused by molecules that are transported in the vascular system; signals can also be volatile compounds that move in the headspace outside the plant (Heil and Ton, 2008). In particular, green-leaf volatiles and other herbivore-induced volatile organic compounds (VOCs) can mediate the systemic response of plants to local herbivore damage (Karban et al., 2006; Frost et al., 2007; Heil and Silva Bueno, 2007). Since such VOCs move freely in the air, they may also affect neighboring plants and then mediate the phenomenon of “plant-plant communication,” which has been found in taxonomically unrelated plants such as Arabidopsis (Arabidopsis thaliana), alder (Alnus glutinosa), corn (Zea mays), lima bean (Phaseolus lunatus), maple (Acer saccharum), sagebrush (Artemisia tridentata), and wild tobacco (Nicotiana attenuata; Baldwin and Schultz, 1983; Rhoades, 1983; Tscharntke et al., 2001; Engelberth et al., 2004; Heil and Kost, 2006; Karban et al., 2006; Paschold et al., 2006; Heil and Silva Bueno, 2007; Ton et al., 2007; Godard et al., 2008).Plant-plant communication via VOCs thus appears to be a common phenomenon in herbivore resistance, and similar volatile compounds can also mediate the beneficial effects that are caused by plant growth-promoting rhizobacteria (Ryu et al., 2003, 2004b). Furthermore, exposure to VOCs such as trans-2-hexenal, cis-3-hexenal, or cis-3-hexenol enhanced resistance of Arabidopsis against the fungal pathogen Botrytis cinerea (Kishimoto et al., 2005), which indicates that VOCs may also induce disease resistance. However, the wound response, the induction of VOCs, the effects of plant growth-promoting rhizobacteria, and even the resistance to necrotrophic pathogens such as B. cinerea and Alternaria brassiccicola are mediated via JA signaling (Wasternack and Parthier, 1997; Pieterse et al., 1998; Schilmiller and Howe, 2005; Francia et al., 2007; Heil, 2008; Heil and Ton, 2008). In contrast, systemic acquired resistance (SAR) to biotrophic pathogens in many plant species is mediated by SA signaling, which increases the expression of phytoalexins and of several PATHOGENESIS-RELATED (PR) proteins (van Loon, 1997; Hammerschmidt and Smith-Becker, 1999; Durrant and Dong, 2004) and which usually is thought to act as an antagonist to JA signaling (Maleck et al., 2000; Pieterse and Dicke, 2007; Korneef and Pieterse, 2008). The volatile derivative of SA, methyl salicylate (MeSA), has been proposed as the most likely systemic signal (Park et al., 2007). In tobacco (Nicotiana tabacum), MeSA is converted back to SA, which then forms the active resistance-inducing compound (Kumar and Klessig, 2003; Forouhar et al., 2005). This mechanism might underlie the resistance induction in tobacco plants that were exposed to high MeSA concentrations (Shulaev et al., 1997). In a study on the role of MeSA as a mobile signal, Park and coworkers (2007), however, only found evidence for the vascular transport of this compound.We used lima bean to investigate whether plant-plant signaling can also affect SAR to biotrophic bacterial pathogens. Plants were exposed to the VOCs emitted from neighbors that had been treated with the chemical SAR elicitor benzothiadiazole [BTH; benzo(1,2,3)thiadiazole-7-carbothioic acid S-methyl ester] or that had been induced biologically, and resulting changes in resistance were monitored at the phenotypic and gene expression levels. A common phenomenon involved in disease resistance is priming, which prepares the plant to respond more rapidly and/or effectively to subsequent attack (van Hulten et al., 2006; Bruce et al., 2007; Goellner and Conrath, 2008) but which comes at much lower costs than direct resistance induction (Heil and Baldwin, 2002; Walters and Boyle, 2005; Walters and Heil, 2007). Therefore, we investigated whether VOCs also can prime resistance to pathogens by first exposing plants to VOCs coming from directly induced plants and then challenging them with Pseudomonas syringae pv syringae. Finally, VOCs released from induced plants were analyzed, and the most likely candidates were evaluated for their effect on expression of the resistance marker gene PR-2 in order to understand the chemical nature of the signal.     

Patterns of Metabolite Changes Identified from Large-Scale Gene Perturbations in Arabidopsis Using a Genome-Scale Metabolic Network

Metabolomics enables quantitative evaluation of metabolic changes caused by genetic or environmental perturbations. However, little is known about how perturbing a single gene changes the metabolic system as a whole and which network and functional properties are involved in this response. To answer this question, we investigated the metabolite profiles from 136 mutants with single gene perturbations of functionally diverse Arabidopsis (Arabidopsis thaliana) genes. Fewer than 10 metabolites were changed significantly relative to the wild type in most of the mutants, indicating that the metabolic network was robust to perturbations of single metabolic genes. These changed metabolites were closer to each other in a genome-scale metabolic network than expected by chance, supporting the notion that the genetic perturbations changed the network more locally than globally. Surprisingly, the changed metabolites were close to the perturbed reactions in only 30% of the mutants of the well-characterized genes. To determine the factors that contributed to the distance between the observed metabolic changes and the perturbation site in the network, we examined nine network and functional properties of the perturbed genes. Only the isozyme number affected the distance between the perturbed reactions and changed metabolites. This study revealed patterns of metabolic changes from large-scale gene perturbations and relationships between characteristics of the perturbed genes and metabolic changes.Rational and quantitative assessment of metabolic changes in response to genetic modification (GM) is an open question and in need of innovative solutions. Nontargeted metabolite profiling can detect thousands of compounds, but it is not easy to understand the significance of the changed metabolites in the biochemical and biological context of the organism. To better assess the changes in metabolites from nontargeted metabolomics studies, it is important to examine the changed metabolites in the context of the genome-scale metabolic network of the organism.Metabolomics is a technique that aims to quantify all the metabolites in a biological system (Nikolau and Wurtele, 2007; Nicholson and Lindon, 2008; Roessner and Bowne, 2009). It has been used widely in studies ranging from disease diagnosis (Holmes et al., 2008; DeBerardinis and Thompson, 2012) and drug discovery (Cascante et al., 2002; Kell, 2006) to metabolic reconstruction (Feist et al., 2009; Kim et al., 2012) and metabolic engineering (Keasling, 2010; Lee et al., 2011). Metabolomic studies have demonstrated the possibility of identifying gene functions from changes in the relative concentrations of metabolites (metabotypes or metabolic signatures; Ebbels et al., 2004) in various species including yeast (Saccharomyces cerevisiae; Raamsdonk et al., 2001; Allen et al., 2003), Arabidopsis (Arabidopsis thaliana; Brotman et al., 2011), tomato (Solanum lycopersicum; Schauer et al., 2006), and maize (Zea mays; Riedelsheimer et al., 2012). Metabolomics has also been used to better understand how plants interact with their environments (Field and Lake, 2011), including their responses to biotic and abiotic stresses (Dixon et al., 2006; Arbona et al., 2013), and to predict important agronomic traits (Riedelsheimer et al., 2012). Metabolite profiling has been performed on many plant species, including angiosperms such as Arabidopsis, poplar (Populus trichocarpa), and Catharanthus roseus (Sumner et al., 2003; Rischer et al., 2006), basal land plants such as Selaginella moellendorffii and Physcomitrella patens (Erxleben et al., 2012; Yobi et al., 2012), and Chlamydomonas reinhardtii (Fernie et al., 2012; Davis et al., 2013). With the availability of whole genome sequences of various species, metabolomics has the potential to become a useful tool for elucidating the functions of genes using large-scale systematic analyses (Fiehn et al., 2000; Saito and Matsuda, 2010; Hur et al., 2013).Although metabolomics data have the potential for identifying the roles of genes that are associated with metabolic phenotypes, the biochemical mechanisms that link functions of genes with metabolic phenotypes are still poorly characterized. For example, we do not yet know the principles behind how perturbing the expression of a single gene changes the metabolic system as a whole. Large-scale metabolomics data have provided useful resources for linking phenotypes to genotypes (Fiehn et al., 2000; Roessner et al., 2001; Tikunov et al., 2005; Schauer et al., 2006; Lu et al., 2011; Fukushima et al., 2014). For example, Lu et al. (2011) compared morphological and metabolic phenotypes from more than 5,000 Arabidopsis chloroplast mutants using gas chromatography (GC)- and liquid chromatography (LC)-mass spectrometry (MS). Fukushima et al. (2014) generated metabolite profiles from various characterized and uncharacterized mutant plants and clustered the mutants with similar metabolic phenotypes by conducting multidimensional scaling with quantified metabolic phenotypes. Nonetheless, representation and analysis of such a large amount of data remains a challenge for scientific discovery (Lu et al., 2011). In addition, these studies do not examine the topological and functional characteristics of metabolic changes in the context of a genome-scale metabolic network. To understand the relationship between genotype and metabolic phenotype, we need to investigate the metabolic changes caused by perturbing the expression of a gene in a genome-scale metabolic network perspective, because metabolic pathways are not independent biochemical factories but are components of a complex network (Berg et al., 2002; Merico et al., 2009).Much progress has been made in the last 2 decades to represent metabolism at a genome scale (Terzer et al., 2009). The advances in genome sequencing and emerging fields such as biocuration and bioinformatics enabled the representation of genome-scale metabolic network reconstructions for model organisms (Bassel et al., 2012). Genome-scale metabolic models have been built and applied broadly from microbes to plants. The first step toward modeling a genome-scale metabolism in a plant species started with developing a genome-scale metabolic pathway database for Arabidopsis (AraCyc; Mueller et al., 2003) from reference pathway databases (Kanehisa and Goto, 2000; Karp et al., 2002; Zhang et al., 2010). Genome-scale metabolic pathway databases have been built for several plant species (Mueller et al., 2005; Zhang et al., 2005, 2010; Urbanczyk-Wochniak and Sumner, 2007; May et al., 2009; Dharmawardhana et al., 2013; Monaco et al., 2013, 2014; Van Moerkercke et al., 2013; Chae et al., 2014; Jung et al., 2014). Efforts have been made to develop predictive genome-scale metabolic models using enzyme kinetics and stoichiometric flux-balance approaches (Sweetlove et al., 2008). de Oliveira Dal’Molin et al. (2010) developed a genome-scale metabolic model for Arabidopsis and successfully validated the model by predicting the classical photorespiratory cycle as well as known key differences between redox metabolism in photosynthetic and nonphotosynthetic plant cells. Other genome-scale models have been developed for Arabidopsis (Poolman et al., 2009; Radrich et al., 2010; Mintz-Oron et al., 2012), C. reinhardtii (Chang et al., 2011; Dal’Molin et al., 2011), maize (Dal’Molin et al., 2010; Saha et al., 2011), sorghum (Sorghum bicolor; Dal’Molin et al., 2010), and sugarcane (Saccharum officinarum; Dal’Molin et al., 2010). These predictive models have the potential to be applied broadly in fields such as metabolic engineering, drug target discovery, identification of gene function, study of evolutionary processes, risk assessment of genetically modified crops, and interpretations of mutant phenotypes (Feist and Palsson, 2008; Ricroch et al., 2011).Here, we interrogate the metabotypes caused by 136 single gene perturbations of Arabidopsis by analyzing the relative concentration changes of 1,348 chemically identified metabolites using a reconstructed genome-scale metabolic network. We examine the characteristics of the changed metabolites (the metabolites whose relative concentrations were significantly different in mutants relative to the wild type) in the metabolic network to uncover biological and topological consequences of the perturbed genes.     

Concerted actions of DnaA complexes with DNA-unwinding sequences within and flanking replication origin oriC promote DnaB helicase loading

Unwinding of the replication origin and loading of DNA helicases underlie the initiation of chromosomal replication. In Escherichia coli, the minimal origin oriC contains a duplex unwinding element (DUE) region and three (Left, Middle, and Right) regions that bind the initiator protein DnaA. The Left/Right regions bear a set of DnaA-binding sequences, constituting the Left/Right-DnaA subcomplexes, while the Middle region has a single DnaA-binding site, which stimulates formation of the Left/Right-DnaA subcomplexes. In addition, a DUE-flanking AT-cluster element (TATTAAAAAGAA) is located just outside of the minimal oriC region. The Left-DnaA subcomplex promotes unwinding of the flanking DUE exposing TT[A/G]T(T) sequences that then bind to the Left-DnaA subcomplex, stabilizing the unwound state required for DnaB helicase loading. However, the role of the Right-DnaA subcomplex is largely unclear. Here, we show that DUE unwinding by both the Left/Right-DnaA subcomplexes, but not the Left-DnaA subcomplex only, was stimulated by a DUE-terminal subregion flanking the AT-cluster. Consistently, we found the Right-DnaA subcomplex–bound single-stranded DUE and AT-cluster regions. In addition, the Left/Right-DnaA subcomplexes bound DnaB helicase independently. For only the Left-DnaA subcomplex, we show the AT-cluster was crucial for DnaB loading. The role of unwound DNA binding of the Right-DnaA subcomplex was further supported by in vivo data. Taken together, we propose a model in which the Right-DnaA subcomplex dynamically interacts with the unwound DUE, assisting in DUE unwinding and efficient loading of DnaB helicases, while in the absence of the Right-DnaA subcomplex, the AT-cluster assists in those processes, supporting robustness of replication initiation.

The initiation of bacterial DNA replication requires local duplex unwinding of the chromosomal replication origin oriC, which is regulated by highly ordered initiation complexes. In Escherichia coli, the initiation complex contains oriC, the ATP-bound form of the DnaA initiator protein (ATP–DnaA), and the DNA-bending protein IHF (Fig. 1, A and B), which promotes local unwinding of oriC (1, 2, 3, 4). Upon this oriC unwinding, two hexamers of DnaB helicases are bidirectionally loaded onto the resultant single-stranded (ss) region with the help of the DnaC helicase loader (Fig. 1B), leading to bidirectional chromosomal replication (5, 6, 7, 8). However, the fundamental mechanism underlying oriC-dependent bidirectional DnaB loading remains elusive.Open in a separate windowFigure 1Schematic structures of oriC, DnaA, and the initiation complexes. A, the overall structure of oriC. The minimal oriC region and the AT-cluster region are indicated. The sequence of the AT-cluster−DUE (duplex-unwinding element) region is also shown below. The DUE region (DUE; pale orange bars) contains three 13-mer repeats: L-DUE, M-DUE, and R-DUE. DnaA-binding motifs in M/R-DUE, TT(A/G)T(T), are indicated by red characters. The AT-cluster region (AT cluster; brown bars) is flanked by DUE outside of the minimal oriC. The DnaA-oligomerization region (DOR) consists of three subregions called Left-, Middle-, and Right-DOR. B, model for replication initiation. DnaA is shown as light brown (for domain I–III) and darkbrown (for domain IV) polygons (right panel). ATP–DnaA forms head-to-tail oligomers on the Left- and Right-DORs (left panel). The Middle-DOR (R2 box)-bound DnaA interacts with DnaA bound to the Left/Right-DORs using domain I, but not domain III, stimulating DnaA assembly. IHF, shown as purple hexagons, bends DNA >160° and supports DUE unwinding by the DnaA complexes. M/R-DUE regions are efficiently unwound. Unwound DUE is recruited to the Left-DnaA subcomplex and mainly binds to R1/R5M-bound DnaA molecules. The sites of ssDUE-binding B/H-motifs V211 and R245 of R1/R5M-bound DnaA molecules are indicated (pink). Two DnaB homohexamer helicases (light green) are recruited and loaded onto the ssDUE regions with the help of the DnaC helicase loader (cyan). ss, single stranded.The minimal oriC region consists of the duplex unwinding element (DUE) and the DnaA oligomerization region (DOR), which contains specific arrays of 9-mer DnaA-binding sites (DnaA boxes) with the consensus sequence TTA[T/A]NCACA (Fig. 1A) (3, 4). The DUE underlies the local unwinding and contains 13-mer AT-rich sequence repeats named L-, M-, and R-DUE (9). The M/R-DUE region includes TT[A/G]T(A) sequences with specific affinity for DnaA (10). In addition, a DUE-flanking AT-cluster (TATTAAAAAGAA) region resides just outside of the minimal oriC (Fig. 1A) (11). The DOR is divided into three subregions, the Left-, Middle-, and Right-DORs, where DnaA forms structurally distinct subcomplexes (Fig. 1A) (8, 12, 13, 14, 15, 16, 17). The Left-DOR contains high-affinity DnaA box R1, low-affinity boxes R5M, τ1−2, and I1-2, and an IHF-binding region (17, 18, 19, 20). The τ1 and IHF-binding regions partly overlap (17).In the presence of IHF, ATP–DnaA molecules cooperatively bind to R1, R5M, τ2, and I1-2 boxes in the Left-DOR, generating the Left-DnaA subcomplex (Fig. 1B) (8, 17). Along with IHF causing sharp DNA bending, the Left-DnaA subcomplex plays a leading role in DUE unwinding and subsequent DnaB loading. The Middle-DOR contains moderate-affinity DnaA box R2. Binding of DnaA to this box stimulates DnaA assembly in the Left- and Right-DORs using interaction by DnaA N-terminal domain (Fig. 1B; also see below) (8, 12, 14, 16, 21). The Right-DOR contains five boxes (C3-R4 boxes) and cooperative binding of ATP–DnaA molecules to these generates the Right-DnaA subcomplex (Fig. 1B) (12, 18). This subcomplex is not essential for DUE unwinding and plays a supportive role in DnaB loading (8, 15, 17). The Left-DnaA subcomplex interacts with DnaB helicase, and the Right-DnaA subcomplex has been suggested to play a similar role (Fig. 1B) (8, 13, 16).In the presence of ATP–DnaA, M- and R-DUE adjacent to the Left-DOR are predominant sites for in vitro DUE unwinding: unwinding of L-DUE is less efficient than unwinding of the other two (Fig. 1B) (9, 22, 23). Deletion of L-DUE or the whole DUE inhibits replication of oriC in vitro moderately or completely, respectively (23). A chromosomal oriC Δ(AT-cluster−L-DUE) mutant with an intact DOR, as well as deletion of Right-DOR, exhibits limited inhibition of replication initiation, whereas the synthetic mutant combining the two deletions exhibits severe inhibition of cell growth (24). These studies suggest that AT-cluster−L-DUE regions stimulate replication initiation in a manner concerted with Right-DOR, although the underlying mechanisms remain elusive.DnaA consists of four functional domains (Fig. 1B) (4, 25). Domain I supports weak domain I–domain I interaction and serves as a hub for interaction with various proteins such as DnaB helicase and DiaA, which stimulates ATP–DnaA assembly at oriC (26, 27, 28, 29, 30). Two or three domain I molecules of the oriC–DnaA subcomplex bind a single DnaB hexamer, forming a stable higher-order complex (7). Domain II is a flexible linker (28, 31). Domain III contains AAA+ (ATPase associated with various cellular activities) motifs essential for ATP/ADP binding, ATP hydrolysis, and DnaA–DnaA interactions in addition to specific sites for ssDUE binding and a second, weak interaction with DnaB helicase (1, 4, 8, 10, 19, 25, 32, 33, 34, 35). Domain IV bears a helix-turn-helix motif with specific affinity for the DnaA box (36).As in typical AAA+ proteins, a head-to-tail interaction underlies formation of ATP–DnaA pentamers on the DOR, where the AAA+ arginine-finger motif Arg285 recognizes ATP bound to the adjacent DnaA protomer, promoting cooperative ATP–DnaA binding (Fig. 1B) (19, 32). DnaA ssDUE-binding H/B-motifs (Val211 and Arg245) in domain III sustain stable unwinding by directly binding to the T-rich (upper) strand sequences TT[A/G]T(A) within the unwound M/R-DUE (Fig. 1B) (8, 10). Val211 residue is included in the initiator-specific motif of the AAA+ protein family (10). For DUE unwinding, ssDUE is recruited to the Left-DnaA subcomplex via DNA bending by IHF and directly interacts with H/B-motifs of DnaA assembled on Left-DOR, resulting in stable DUE unwinding competent for DnaB helicase loading; in particular, DnaA protomers bound to R1 and R5M boxes play a crucial role in the interaction with M/R-ssDUE (Fig. 1B) (8, 10, 17). Collectively, these mechanisms are termed ssDUE recruitment (4, 17, 37).Two DnaB helicases are thought to be loaded onto the upper and lower strands of the region including the AT-cluster and DUE, with the aid of interactions with DnaC and DnaA (Fig. 1B) (25, 38, 39). DnaC binding modulates the closed ring structure of DnaB hexamer into an open spiral form for entry of ssDNA (40, 41, 42, 43). Upon ssDUE loading of DnaB, DnaC is released from DnaB in a manner stimulated by interactions with ssDNA and DnaG primase (44, 45). Also, the Left- and Right-DnaA subcomplexes, which are oriented opposite to each other, could regulate bidirectional loading of DnaB helicases onto the ssDUE (Fig. 1B) (7, 8, 35). Similarly, recent works suggest that the origin complex structure is bidirectionally organized in both archaea and eukaryotes (1, 46). In Saccharomyces cerevisiae, two origin recognition complexes containing AAA+ proteins bind to the replication origin region in opposite orientations; this, in turn, results in efficient loading of two replicative helicases, leading to head-to-head interactions in vitro (46). Consistent with this, origin recognition complex dimerization occurs in the origin region during the late M-G1 phase (47). The fundamental mechanism of bidirectional origin complexes might be widely conserved among species.In this study, we analyzed various mutants of oriC and DnaA in reconstituted systems to reveal the regulatory mechanisms underlying DUE unwinding and DnaB loading. The Right-DnaA subcomplex assisted in the unwinding of oriC, dependent upon an interaction with L-DUE, which is important for efficient loading of DnaB helicases. The AT-cluster region adjacent to the DUE promoted loading of DnaB helicase in the absence of the Right-DnaA subcomplex. Consistently, the ssDNA-binding activity of the Right-DnaA subcomplex sustained timely initiation of growing cells. These results indicate that DUE unwinding and efficient loading of DnaB helicases are sustained by concerted actions of the Left- and Right-DnaA subcomplexes. In addition, loading of DnaB helicases are sustained by multiple mechanisms that ensure robust replication initiation, although the complete mechanisms are required for precise timing of initiation during the cell cycle.     

New-Onset Diabetes Mellitus After Transplantation in a Cynomolgus Macaque (Macaca fasicularis)

A 5.5-y-old intact male cynomolgus macaque (Macaca fasicularis) presented with inappetence and weight loss 57 d after heterotopic heart and thymus transplantation while receiving an immunosuppressant regimen consisting of tacrolimus, mycophenolate mofetil, and methylprednisolone to prevent graft rejection. A serum chemistry panel, a glycated hemoglobin test, and urinalysis performed at presentation revealed elevated blood glucose and glycated hemoglobin (HbA1c) levels (727 mg/dL and 10.1%, respectively), glucosuria, and ketonuria. Diabetes mellitus was diagnosed, and insulin therapy was initiated immediately. The macaque was weaned off the immunosuppressive therapy as his clinical condition improved and stabilized. Approximately 74 d after discontinuation of the immunosuppressants, the blood glucose normalized, and the insulin therapy was stopped. The animal''s blood glucose and HbA1c values have remained within normal limits since this time. We suspect that our macaque experienced new-onset diabetes mellitus after transplantation, a condition that is commonly observed in human transplant patients but not well described in NHP. To our knowledge, this report represents the first documented case of new-onset diabetes mellitus after transplantation in a cynomolgus macaque.Abbreviations: NODAT, new-onset diabetes mellitus after transplantationNew-onset diabetes mellitus after transplantation (NODAT, formerly known as posttransplantation diabetes mellitus) is an important consequence of solid-organ transplantation in humans.^{7-10,15,17,19,21,25-28,31,33,34,37,38,42} A variety of risk factors have been identified including increased age, sex (male prevalence), elevated pretransplant fasting plasma glucose levels, and immunosuppressive therapy.^{7-10,15,17,19,21,25-28,31,33,34,37,38,42} The relationship between calcineurin inhibitors, such as tacrolimus and cyclosporin, and the development of NODAT is widely recognized in human medicine.^{7-10,15,17,19,21,25-28,31,33,34,37,38,42} Cynomolgus macaques (Macaca fasicularis) are a commonly used NHP model in organ transplantation research. Cases of natural and induced diabetes of cynomolgus monkeys have been described in the literature;^14,43,45 however, NODAT in a macaque model of solid-organ transplantation has not been reported previously to our knowledge.     

The K-Segment of Maize DHN1 Mediates Binding to Anionic Phospholipid Vesicles and Concomitant Structural Changes

Dehydrins (DHNs; late embryogenesis abundant D11 family) are a family of intrinsically unstructured plant proteins that accumulate in the late stages of seed development and in vegetative tissues subjected to water deficit, salinity, low temperature, or abscisic acid treatment. We demonstrated previously that maize (Zea mays) DHNs bind preferentially to anionic phospholipid vesicles; this binding is accompanied by an increase in α-helicity of the protein, and adoption of α-helicity can be induced by sodium dodecyl sulfate. All DHNs contain at least one “K-segment,” a lysine-rich 15-amino acid consensus sequence. The K-segment is predicted to form a class A2 amphipathic α-helix, a structural element known to interact with membranes and proteins. Here, three K-segment deletion proteins of maize DHN1 were produced. Lipid vesicle-binding assays revealed that the K-segment is required for binding to anionic phospholipid vesicles, and adoption of α-helicity of the K-segment accounts for most of the conformational change of DHNs upon binding to anionic phospholipid vesicles or sodium dodecyl sulfate. The adoption of structure may help stabilize cellular components, including membranes, under stress conditions.When plants encounter environmental stresses such as drought or low temperature, various responses take place to adapt to these conditions. Typical responses include increased expression of chaperones, signal transduction pathway and late embryogenesis abundant (LEA) proteins, osmotic adjustment, and induction of degradation and repair systems (Ingram and Bartels, 1996).Dehydrins (DHNs; LEA D11 family) are a subfamily of group 2 LEA proteins that accumulate to high levels during late stages of seed development and in vegetative tissues subjected to water deficit, salinity, low temperature, or abscisic acid (ABA) treatment (Svensson et al., 2002). Some DHNs are expressed constitutively during normal growth (Nylander et al., 2001; Rorat et al., 2004, 2006; Rodriguez et al., 2005). DHNs exist in a wide range of photosynthetic organisms, including angiosperms, gymnosperms, algae, and mosses (Svensson et al., 2002). DHNs are encoded by a dispersed multigene family and are differentially regulated, at least in higher plants. For example, 13 Dhn genes have been identified in barley (Hordeum vulgare), dispersed over seven genetic map locations (Choi et al., 1999; Svensson et al., 2002) and regulated variably by drought, low temperature, and embryo development (Tommasini et al., 2008). DHNs are localized in various subcellular compartments, including cytosol (Roberts et al., 1993), nucleus (Houde et al., 1995), chloroplast (Artus et al., 1996), vacuole (Heyen et al., 2002), and proximal to the plasma membrane and protein bodies (Asghar et al., 1994; Egerton-Warburton et al., 1997; Puhakainen et al., 2004). Elevated expression of Dhn genes generally has been correlated with the acquisition of tolerance to abiotic stresses such as drought (Whitsitt et al., 1997), salt (Godoy et al., 1994; Jayaprakash et al., 1998), chilling (Ismail et al., 1999a), or freezing (Houde et al., 1995; Danyluk et al., 1998; Fowler et al., 2001). The differences in expression and tissue location suggest that individual members of the Dhn multigene family have somewhat distinct biological functions (Close, 1997; Zhu et al., 2000; Nylander et al., 2001). Many studies have observed a positive correlation between the accumulation of DHNs and tolerance to abiotic stresses (Svensson et al., 2002). However, overexpression of a single DHN protein has not, in general, been sufficient to confer stress tolerance (Puhakainen et al., 2004).DHNs are subclassified by sequence motifs referred to as the K-segment (Lys-rich consensus sequence), the Y-segment (N-terminal conserved sequence), the S-segment (a tract of Ser residues), and the φ-segment (Close, 1996). Because of high hydrophilicity, high content of Gly (>20%), and the lack of a defined three-dimensional structure in the pure form (Lisse et al., 1996), DHNs have been categorized as “intrinsically disordered/unstructured proteins” or “hydrophilins” (Wright and Dyson, 1999; Garay-Arroyo et al., 2000; Tompa, 2005; Kovacs et al., 2008). On the basis of compositional and biophysical properties and their link to abiotic stresses, several functions of DHNs have been proposed, including ion sequestration (Roberts et al., 1993), water retention (McCubbin et al., 1985), and stabilization of membranes or proteins (Close, 1996, 1997). Observations from in vitro experiments include DHN binding to lipid vesicles (Koag et al., 2003; Kovacs et al., 2008) or metals (Svensson et al., 2000; Heyen et al., 2002; Kruger et al., 2002; Alsheikh et al., 2003; Hara et al., 2005), protection of membrane lipid against peroxidation (Hara et al., 2003), retention of hydration or ion sequestration (Bokor et al., 2005; Tompa et al., 2006), and chaperone activity against the heat-induced inactivation and aggregation of various proteins (Kovacs et al., 2008).Intrinsically disordered/unstructured proteins that lack a well-defined three-dimensional structure have recently been recognized to be prevalent in prokaryotes and eukaryotes (Oldfield et al., 2005). They fulfill important functions in signal transduction, gene expression, and binding to targets such as protein, RNA, ions, and membranes (Wright and Dyson, 1999; Tompa, 2002; Dyson and Wright, 2005). The disorder confers structural flexibility and malleability to adapt to changes in the protein environment, including water potential, pH, ionic strength, and temperature, and to undergo structural transition when complexed with ligands such as other proteins, DNA, RNA, or membranes (Prestrelski et al., 1993; Uversky, 2002). Structural changes from disorder to ordered functional structure also can be induced by the folding of a partner protein (Wright and Dyson, 1999; Tompa, 2002; Mouillon et al., 2008).The idea that DHNs interact with membranes is consistent with many immunolocalization studies, which have shown that DHNs accumulate near the plasma membrane or membrane-rich areas surrounding lipid and protein bodies (Asghar et al., 1994; Egerton-Warburton et al., 1997; Danyluk et al., 1998; Puhakainen et al., 2004). The K-segment is predicted to form a class A2 amphipathic α-helix, in which hydrophilic and hydrophobic residues are arranged on opposite faces (Close, 1996). The amphipathic α-helix is a structural element known to interact with membranes and proteins (Epand et al., 1995). Also, in the presence of helical inducers such as SDS and trifluoroethanol (Dalal and Pio, 2006), DHNs take on α-helicity (Lisse et al., 1996; Ismail et al., 1999b). We previously examined the binding of DHN1 to liposomes and found that DHNs bind preferentially to anionic phospholipids and that this binding is accompanied by an increase in α-helicity of the protein (Koag et al., 2003). Similarly, a mitochondrial LEA protein, one of the group III LEA proteins, recently has been shown to interact with and protect membranes subjected to desiccation, coupled with the adoption of amphipathic α-helices (Tolleter et al., 2007).Here, we explore the basis of DHN-vesicle interaction using K-segment deletion proteins. This study reveals that the K-segment is necessary and sufficient for binding to anionic phospholipid vesicles and that the adoption of α-helicity of DHN proteins can be attributed mainly to the K-segment.