Aluminum induced proteome changes in tomato cotyledons

Cotyledons of tomato seedlings that germinated in a 20 µM AlK(SO₄)₂ solution remained chlorotic while those germinated in an aluminum free medium were normal (green) in color. Previously, we have reported the effect of aluminum toxicity on root proteome in tomato seedlings (Zhou et al.¹). Two dimensional DIGE protein analysis demonstrated that Al stress affected three major processes in the chlorotic cotyledons: antioxidant and detoxification metabolism (induced), glyoxylate and glycolytic processes (enhanced), and the photosynthetic and carbon fixation machinery (suppressed).Key words: aluminum, cotyledons, proteome, tomatoDifferent biochemical processes occur depending on the developmental stages of cotyledons. During early seed germination, before the greening of the cotyledons, glyoxysomes enzymes are very active. Fatty acids are converted to glucose via the gluconeogenesis pathway.^2,3 In greening cotyledons, chloroplast proteins for photosynthesis and leaf peroxisomal enzymes in the glycolate pathway for photorespiration are metabolized.^2–4 Enzymes involved in regulatory mechanisms such as protein kinases, protein phosphatases, and mitochondrial enzymes are highly expressed.^3,5,6The chlorotic cotyledons are similar to other chlorotic counterparts in that both contains lower levels of chlorophyll, thus the photosynthetic activities are not as active. In order to understand the impact of Al on tomato cotyledon development, a comparative proteome analysis was performed using 2D-DIGE following the as previously described procedure.¹ Some proteins accumulated differentially in Al-treated (chlorotic) and untreated cotyledons (Fig. 1). Mass spectrometry of tryptic digestion fragments of the proteins followed by database search has identified some of the differentially expressed proteins (Open in a separate windowFigure 1Image of protein spots generated by Samspot analysis of Al treated and untreated tomato cotyledons proteomes separated on 2D-DIGE.

Table 1

Proteins identified from tomato cotyledons of seeds germinating in Al-solution

Allelic frequency and genotypes of prion protein at codon 136 and 171 in Iranian Ghezel sheep breeds

PrP genotypes at codons 136 and 171 in 120 Iranian Ghezel sheep breeds were studied using allele-specific PCR amplification and compared with the well-known sheep breeds in North America, the United States and Europe. The frequency of V allele and VV genotype at codon 136 of Ghezel sheep breed was significantly lower than AA and AV. At codon 171, the frequency of allele H was significantly lower than Q and R. Despite the similarities of PrP genotypes at codons 136 and 171 between Iranian Ghezel sheep breeds and some of the studied breeds, significant differences were found with others. Planning of effective breeding control and successful eradication of susceptible genotypes in Iranian Ghezel sheep breeds will not be possible unless the susceptibility of various genotypes in Ghezel sheep breeds to natural or experimental scrapie has been elucidated.Key words: scrapie, Ghezel sheep breed, PrP genotyping, allele specific amplification, codon 136, codon 171Scrapie was first described in England in 1732,¹ and it is an infectious neurodegenerative fatal disease of sheep and goats belonging to the group of transmissible subacute spongiform encephalopathies (TSEs), along with bovine spongiform encephalopathy (BSE), chronic wasting disease and Creutzfeldt-Jakob disease.^2,3 The term prion, proteinaceous infectious particles, coined by Stanley B. Prusiner, was introduced, and he presents the idea that the causal agent is a protein.⁴ Prion proteins are discovered in two forms, the wild-type form (PrP^c) and the mutant form (PrP^Sc).⁵ Although scrapie is an infectious disease, the susceptibility of sheep is influenced by genotypes of the prion protein (PrP) gene.^2,6 Researchers have found that the PrP allelic variant alanine/arginine/arginine (ARR) at codons 136, 154 and 171 is associated with resistance to scrapie in several breeds.^7–14 Most of the sheep populations in the Near East and North African Region (84% of the total population of 255 million) are raised in Iran, Turkey, Pakistan, Sudan, Algeria, Morocco, Afghanistan, Syria and Somalia.¹⁵ In 2003, the Iranian sheep population was estimated at 54,000,000 head. The Ghezel sheep breed, which also is known as Kizil-Karaman, Mor-Karaman, Dugli, Erzurum, Chacra, Chagra, Chakra, Gesel, Gezel, Kazil, Khezel, Khizel, Kizil, Qezel, Qizil and Turkish Brown, originated in northwestern Iran and northeastern Turkey. By considering sheep breeds as one of the main sources of meat, dairy products and related products, a global screening attempt is started in different areas. In compliance with European Union Decision 2003/100/EC, each member state has introduced a breeding program to select for resistance to TSEs in sheep populations to increase the frequency of the ARR allele. A similar breeding program is established in United States and Canada. The Near East and North African Region still needs additional programs to help the global plan of eradication of scrapie-susceptible genotypes. The current study was the first to assess the geographical and molecular variation of codons 136 and 171 polymorphism between Iranian Ghezel sheep breed and well-known sheep breeds.Polymorphism at codon 136 is associated with susceptibility to scrapie in both experimental and natural models.^10,11,13,16 17 and Austrian Carynthian sheep.¹⁸ Swiss White Alpine showed higher frequency of allele V at position 136 than Swiss Oxford Down, Swiss Black-Brown Mountain and Valais Blacknose.¹⁹ Comparison of polymorphism at codon 136 in the current study with some of other breeds (20 some flock of Hampshire sheep²¹ with current study, but the frequency of it is higher than that of some other breeds.

Table 1

Comparison of PrP allelic and genotype frequencies at codon 136 in different breeds

Genome-wide analysis of lipoxygenase gene family in Arabidopsis and rice

The enzymes called lipoxygenases (LOXs) can dioxygenate unsaturated fatty acids, which leads to lipoperoxidation of biological membranes. This process causes synthesis of signaling molecules and also leads to changes in cellular metabolism. LOXs are known to be involved in apoptotic (programmed cell death) pathway, and biotic and abiotic stress responses in plants. Here, the members of LOX gene family in Arabidopsis and rice are identified. The Arabidopsis and rice genomes encode 6 and 14 LOX proteins, respectively, and interestingly, with more LOX genes in rice. The rice LOXs are validated based on protein alignment studies. This is the first report wherein LOXs are identified in rice which may allow better understanding the initiation, progression and effects of apoptosis, and responses to bitoic and abiotic stresses and signaling cascades in plants.Key words: apoptosis, biotic and abiotic stresses, genomics, jasmonic acid, lipidsLipoxygenases (linoleate:oxygen oxidoreductase, EC 1.13.11.-; LOXs) catalyze the conversion of polyunsaturated fatty acids (lipids) into conjugated hydroperoxides. This process is called hydroperoxidation of lipids. LOXs are monomeric, non-heme and non-sulfur, but iron-containing dioxygenases widely expressed in fungi, animal and plant cells, and are known to be absent in prokaryotes. However, a recent finding suggests the existence of LOX-related genomic sequences in bacteria but not in archaea.¹ The inflammatory conditions in mammals like bronchial asthama, psoriasis and arthritis are a result of LOXs reactions.² Further, several clinical conditions like HIV-1 infection,³ disease of kidneys due to the activation of 5-lipoxygenase,^4,5 aging of the brain due to neuronal 5-lipoxygenase⁶ and atherosclerosis⁷ are mediated by LOXs. In plants, LOXs are involved in response to biotic and abiotic stresses.⁸ They are involved in germination⁹ and also in traumatin and jasmonic acid biochemical pathways.^10,11 Studies on LOX in rice are conducted to develop novel strategies against insect pests¹² in response to wounding and insect attack,¹³ and on rice bran extracts as functional foods and dietary supplements for control of inflammation and joint health.¹⁴ In Arabidopsis, LOXs are studied in response to natural and stress-induced senescence,¹⁵ transition to flowering,¹⁶ regulation of lateral root development and defense response.¹⁷The arachidonic, linoleic and linolenic acids can act as substrates for different LOX isozymes. A hydroperoxy group is added at carbons 5, 12 or 15, when arachidonic acid is the substrate, and so the LOXs are designated as 5-, 12- or 15-lipoxygenases. Sequences are available in the database for plant lipoxygenases (EC:1.13.11.12), mammalian arachidonate 5-lipoxygenase (EC:1.13.11.34), mammalian arachidonate 12-lipoxygenase (EC:1.13.11.31) and mammalian erythroid cell-specific 15-lipoxygenase (EC:1.13.11.33). The prototype member for LOX family, LOX-1 of Glycine max L. (soybean) is a 15-lipoxygenase. The LOX isoforms of soybean (LOX-1, LOX-2, LOX-3a and LOX-3b) are the most characterized of plant LOXs.¹⁸ In addition, five vegetative LOXs (VLX-A, -B, -C, -D, -E) are detected in soybean leaves.¹⁹ The 3-dimensional structure of soybean LOX-1 has been determined.^20,21 LOX-1 was shown to be made of two domains, the N-terminal domain-I which forms a β-barrel of 146 residues, and a C-terminal domain-II of bundle of helices of 693 residues²¹ (Fig. 1). The iron atom was shown to be at the centre of domain-II bound by four coordinating ligands, of which three are histidine residues.²²Open in a separate windowFigure 1Three-dimensional structure of soybean lipoxygenase L-1. The domain I (N-terminal) and domain II (C-terminal) are indicated. The catalytic iron atom is embedded in domain II (PDB ID-1YGE).²¹This article describes identification of LOX genes in Arabidopsis and rice. The Arabidopsis genome encodes for six LOX proteins²³ (www.arabidopsis.org) (LocusAnnotationNomenclatureA^*B^*C^*AT1G55020lipoxygenase 1 (LOX1)LOX185998044.45.2049AT1G17420lipoxygenase 3 (LOX3)LOX3919103725.18.0117AT1G67560lipoxygenase family proteinLOX4917104514.68.0035AT1G72520lipoxygenase, putativeLOX6926104813.17.5213AT3G22400lipoxygenase 5 (LOX5)LOX5886101058.86.6033AT3G45140lipoxygenase 2 (LOX2)LOX2896102044.75.3177Open in a separate window^*A, amino acids; B, molecular weight; C, isoelectric point.Interestingly, the rice genome (rice.plantbiology.msu.edu) encodes for 14 LOX proteins as compared to six in Arabidopsis (​and22). Of these, majority of them are composed of ∼790–950 aa with the exception for loci, LOC_Os06g04420 (126 aa), LOC_Os02g19790 (297 aa) and LOC_Os12g37320 (359 aa) (Fig. 2).Open in a separate windowFigure 2Protein alignment of rice LOXs and vegetative lipoxygenase, VLX-B,²⁸ a soybean LOX (AA B67732). The 14 rice LOCs are indicated on left and sequence position on right. Gaps are included to improve alignment accuracy. Figure was generated using ClustalX program.

Table 2

Genes encoding lipoxygenases in rice

Genome-wide analysis of thioredoxin fold superfamily peroxiredoxins in Arabidopsis and rice

A broad range of peroxides generated in subcellular compartments, including chloroplasts, are detoxified with peroxidases called peroxiredoxins (Prx). The Prx are ubiquitously distributed in all organisms including bacteria, fungi, animals and also in cyanobacteria and plants. Recently, the Prx have emerged as new molecules in antioxidant defense in plants. Here, the members which belong to Prx gene family in Arabidopsis and rice are been identified. Overall, the Prx members constitute a small family with 10 and 11 genes in Arabidopsis and rice respectively. The prx genes from rice are assigned to their functional groups based on homology search against Arabidopsis protein database. Deciphering the Prx functions in rice will add novel information to the mechanism of antioxidant defense in plants. Further, the Prx also forms the part of redox signaling cascade. Here, the Prx gene family has been described for rice.Key words: antioxidant defense, chloroplast, gene family, oxidative stress, reactive oxygen speciesThe formation of free radicals and reactive oxygen species (ROS) occur in several enzymatic and non-enzymatic reactions during cellular metabolism. The accumulation of these reactive and deleterious intermediates is suppressed by antioxidant defense mechanism comprised of low molecular weight antioxidants and enzymes. In photosynthetic organisms, the defense against the damage from free radicals and oxidative stress is crucial. For instance, the ROS production occurs in photosystem II with generation of singlet oxygen (¹O₂) and hydrogen peroxide (H₂O₂),^1,2 photosystem I from superoxide anion radicals (O₂⁻),³ and during photorespiration with generation of H₂O₂.⁴ ROS production may exceed under environmental stress conditions like excess light, low temperature and drought.⁵The antioxidant defense mechanism is activated by antioxidant metabolities and enzymes which detoxify ROS and lipid peroxides. The detoxification of ROS can occur in various cellular compartments such as chloroplasts, mitochondria, peroxisomes and cytosol.⁶ The enzymes like ascorbate peroxidase, catalase, glutathione peroxidase and superoxide dismutase are prominent antioxidant enzymes.⁶ The peroxiredoxins (Prx) emerged as new components in the antioxidant defense network of barley.^7,8 Later, Prx were studied in other plants.^9–14Prx can be classified into four different functional groups, PrxQ, 1-Cys Prx, 2-Cys Prx and Type-2 Prx.^15,16 They are members of the thioredoxin fold superfamily.^17,18 In this study, the prx genes found in Arabidopsis and rice genomes are been identified. The Arabidopsis genome encodes 10 prx genes classified into four functional categories, 1-Cys Prx, 2-Cys Prx, PrxQ and Type-2 Prx.¹³ Of these, one each of 1-Cys Prx and PrxQ, two of 2-Cys Prx (2-Cys PrxA and 2-Cys PrxB) and six Type-2 Prx (PrxA–F) are identified¹³ (LocusAnnotationSynonymA^*B^*C^*AT1G481301-Cysteine peroxiredoxin 1 (ATPER1)1-Cys Prx21624081.36.603AT1G60740Peroxiredoxin type 2Type-2 PrxD16217471.95.2297AT1G65970Thioredoxin-dependent peroxidase 2 (TPX2)Type-2 PrxC16217413.95.2297AT1G65980Thioredoxin-dependent peroxidase 1 (TPX1)Type-2 PrxB16217427.84.9977AT1G65990Type 2 peroxiredoxin-relatedType-2 PrxA55362653.66.4368AT3G06050Peroxiredoxin IIF (PRXIIF)Type-2 PrxF20121445.29.3905AT3G116302-Cys Peroxiredoxin A (2CPA, 2-Cys PrxA)2-Cys PrxA26629091.77.5686AT3G26060ATPRX Q, periredoxin QPrxQ21623677.810.0565AT3G52960Peroxiredoxin type 2Type-2 PrxE23424684.09.572AT5G062902-Cysteine Peroxiredoxin B (2CPB, 2-Cys PrxB)2-Cys PrxB27329779.55.414Open in a separate window^*A, amino acids; B, molecular weight; C, isoelectric point.In rice (rice.plantbiology.msu.edu/), there are 11 genomic loci which encode for Prx proteins (​and33). Interestingly, a new prx gene (LOC_Os07g15670) annotated as “peroxiredoxin, putative, expressed” is identified making the tally of prx genes to eleven in rice as compared to ten in Arabidopsis (​and22). The BLAST search has identified its counterpart in Arabidopsis which has been annotated as “antioxidant/oxidoreductase” (AT1G21350) in the TAIR database (www.arabidopsis.org). The rice LOC_Os07g15670 and Arabidopsis AT1G21350 share protein homology %68/78 for 236 amino acids (ChromosomeLocus IdPutative function/AnnotationA^*B^*C^*1LOC_Os01g16152peroxiredoxin, putative, expressed19920873.68.22091LOC_Os01g24740peroxiredoxin-2E-1, chloroplast precursor, putative10711591.56.79061LOC_Os01g48420peroxiredoxin, putative, expressed16317290.85.68282LOC_Os02g09940peroxiredoxin, putative, expressed22623179.56.5352LOC_Os02g33450peroxiredoxin, putative, expressed26228096.95.77094LOC_Os04g339702-Cys peroxiredoxin BAS1, chloroplast precursor, putative, expressed12213410.24.37056LOC_Os06g09610peroxiredoxin, putative, expressed2662892610.50976LOC_Os06g42000peroxiredoxin, putative, expressed23323688.39.20597LOC_Os07g15670peroxiredoxin, putative, expressed25327684.69.85457LOC_Os07g44440peroxiredoxin, putative, expressed22124232.65.36187LOC_Os07g44430peroxiredoxin, putative25627785.36.8544Open in a separate window^*A, amino acids; B, molecular weight; C, isoelectric point.

Table 3

Identification of rice homologs of peroxiredoxins in A. thaliana

Stress-induced flowering

Many plant species can be induced to flower by responding to stress factors. The short-day plants Pharbitis nil and Perilla frutescens var. crispa flower under long days in response to the stress of poor nutrition or low-intensity light. Grafting experiments using two varieties of P. nil revealed that a transmissible flowering stimulus is involved in stress-induced flowering. The P. nil and P. frutescens plants that were induced to flower by stress reached anthesis, fruited and produced seeds. These seeds germinated, and the progeny of the stressed plants developed normally. Phenylalanine ammonialyase inhibitors inhibited this stress-induced flowering, and the inhibition was overcome by salicylic acid (SA), suggesting that there is an involvement of SA in stress-induced flowering. PnFT2, a P. nil ortholog of the flowering gene FLOWERING LOCUS T (FT) of Arabidopsis thaliana, was expressed when the P. nil plants were induced to flower under poor-nutrition stress conditions, but expression of PnFT1, another ortholog of FT, was not induced, suggesting that PnFT2 is involved in stress-induced flowering.Key words: flowering, stress, phenylalanine ammonia-lyase, salicylic acid, FLOWERING LOCUS T, Pharbitis nil, Perilla frutescensFlowering in many plant species is regulated by environmental factors, such as night-length in photoperiodic flowering and temperature in vernalization. On the other hand, a short-day (SD) plant such as Pharbitis nil (synonym Ipomoea nil) can be induced to flower under long days (LD) when grown under poor-nutrition, low-temperature or high-intensity light conditions.^1–9 The flowering induced by these conditions is accompanied by an increase in phenylalanine ammonia-lyase (PAL) activity.¹⁰ Taken together, these facts suggest that the flowering induced by these conditions might be regulated by a common mechanism. Poor nutrition, low temperature and high-intensity light can be regarded as stress factors, and PAL activity increases under these stress conditions.¹¹ Accordingly, we assumed that such LD flowering in P. nil might be induced by stress. Non-photoperiodic flowering has also been sporadically reported in several plant species other than P. nil, and a review of these studies suggested that most of the factors responsible for flowering could be regarded as stress. Some examples of these factors are summarized in 12^–14

Table 1

Some cases of stress-induced flowering

A Review of Principal Studies on the Development and Treatment of Epithelial Ovarian Cancer in the Laying Hen Gallus gallus

Often referred to as the silent killer, ovarian cancer is the most lethal gynecologic malignancy. This disease rarely shows any physical symptoms until late stages and no known biomarkers are available for early detection. Because ovarian cancer is rarely detected early, the physiology behind the initiation, progression, treatment, and prevention of this disease remains largely unclear. Over the past 2 decades, the laying hen has emerged as a model that naturally develops epithelial ovarian cancer that is both pathologically and histologically similar to that of the human form of the disease. Different molecular signatures found in human ovarian cancer have also been identified in chicken ovarian cancer including increased CA125 and elevated E-cadherin expression, among others. Chemoprevention studies conducted in this model have shown that decreased ovulation and inflammation are associated with decreased incidence of ovarian cancer development. The purpose of this article is to review the major studies performed in laying hen model of ovarian cancer and discuss how these studies shape our current understanding of the pathophysiology, prevention and treatment of epithelial ovarian cancer.

Ovarian cancer is the leading cause of death among female gynecologic malignancies, with a 47% 5 y relative survival rate.¹⁵⁴ Early detection of the disease is necessary for decreasing the high mortality rate. However, early detection is difficult due to the lack of known specific biomarkers and clinically detectable symptoms until the tumor reaches at an advanced stage. The disease has multiple subtypes. Epithelial ovarian cancer (EOC) is the most common type of ovarian cancer, accounting for about 90% of all reported cases.^127,164 EOC is commonly subdivided into 5 histotypes: high-grade serous (HGSOC), low-grade serous, mucinous, endometroid (EC), and clear cell. The histotypes differ in terms of tumor cell morphology, severity, systemic effect, and response to treatment. Among the different subtypes, HGSOC accounts for about 70% of cases of EOC observed in women. HGSOC has a higher mitotic index and is a more aggressive form of cancer with a worse prognosis. HGSOC and low-grade serous histotypes exhibit distinctly different presentations of the disease^82,166 and demand different treatment modalities. EC (10% to 20%), mucinous (5% to 20%), and clear cell (3% to 10%) histotypes are less common forms of the disease. The subtypes of EOC also differ in terms of 5 y survival rates of patients; that is, HGSOC (20% to 35%), EC (40% to 63%), mucinous (40% to 69%), and clear cell (35% to 50%).^20,76,148Developing a representative animal model for EOC has been challenging due to the histologic and pathologic differences among different subtypes of EOC. While developing a reliable animal model is challenging due to the vast complexity and limited understanding of the origin of the disease, laying hens naturally develop EOC that is histopathologically very similar to the human form of the disease (Figure 1).¹⁵ All the different human ovarian cancer histotypes have been observed in laying hen ovarian cancer (Figure 2). In addition, the presentation of the disease in chickens is remarkably similar to the human form of the disease, with early-stage ovarian cancer in laying hens having similar precursor lesions as occur in women.¹⁵ The laying hen develops ovarian cancer spontaneously, allowing analysis of early events and investigation into the natural course of the disease, as tumors can be examined as they progress from normal to late-stage ovarian carcinoma. The gross appearance of these stages is shown in Figure 3.Open in a separate windowFigure 1.Gross pathologic presentation of chicken compared with human ovarian cancer. The remarkably similar presentation in hens (A,B) and women (C,D) at the gross anatomic level with profuse abdominal ascites and peritoneal dissemination of metastasis. A) Ascites in abdominal cavity chicken with advanced ovarian cancer (photo credit: DB Hales); (B) Chicken ovarian cancer with extensive peritoneal dissemination of metastasis (photo credit: DB Hales); (C) Distended abdomen from ascites fluid accumulation in woman with ovarian cancer (http://www.pathguy.com/bryanlee/ovca.html) (D) Human ovarian cancer with extensive peritoneal dissemination of metastasis (http://www.pathguy.com/bryanlee/ovca.html).Open in a separate windowFigure 2.Gross anatomic appearance of different stages of ovarian cancer in the chicken The progression from the normal hen ovary to late-stage metastatic ovarian cancer. (A) Normal chicken ovary showing hierarchal clutch of developing follicles and postovulatory follicle; (B) Stage 1 ovarian cancer, confined to ovary with vascularized follicles; (C) Stage 2/3 ovarian cancer, metastasis locally to peritoneal cavity with ascites; (D) Stage 4 ovarian cancer, late stage with metastasis to lung and liver with extensive ascites (photo credits: DB Hales).Open in a separate windowFigure 3.Histologic subtypes in chicken compared with human ovarian cancers. H and E staining of formalin fixed paraffin embedded tissues from hens with ovarian cancer (A through D) and women (E through G). (A) Chicken clear cell carcinoma; (B) Chicken endometrioid carcinoma; (C) Chicken mucinous adenocarcinoma; (D) Chicken serous papillary adenocarcinoma (photo credits: DB Hales). (E) Human clear cell carcinoma; (F) Human endometrioid carcinoma; (G) Human mucinous cystadenocarcinoma; (H) Human serous adenocarcinoma (https://www.womenshealthsection.com).Over the past 2 decades, the laying hen has emerged as a valuable experimental model for EOC, in addition to other in vivo models such as Patient-Derived Xenografts (PDX) and Genetically Engineered Mouse Models (GEMMs). Comparison of the hen model with other animal models has been reviewed elsewhere.⁷² Modern-day laying hens, such as the white leghorn, have been selected from their ancestor red jungle fowl⁵⁷ for decreased broodiness and persistent ovulation, resulting in approximately one egg per day, if proper nutrition and light-dark cycles are maintained. Daily rupture and consequent repair of the ovarian surface epithelia (OSE) due to the persistent ovulation promotes potential error during rapid DNA replication. This increases the probability of oncogenic mutations, ultimately leading to neoplasia.¹³⁷ Inflammation resulting from continuous ovulation also promotes the natural development of EOC.⁸¹ By the age of 2.5 to 3 y, laying hens have undergone a similar number of ovulations as a perimenopausal woman. The risk of ovarian cancer in white leghorn hens in this time (4%) is similar to the lifetime risk of ovarian cancer in women (0.35% to 8.8%).¹²⁵ By the age of 4 to 6 y, the risk of ovarian cancer in hens rises to 30% to 60%.⁵⁴ The incidence of ovarian carcinoma in the hens, however, depends on the age, genetic strain,⁸⁰ and the egg-laying frequency of the specific breed.⁵⁴ The common white leghorn hen has routinely been employed in chicken ovarian cancer studies. On average, hens are exposed to 17 h of light per day, with lights turned on at 0500 h and turned off at 2200 h. The laying hen model of EOC does present some considerable challenges. Despite its great utility for research, the model is still used mainly by agricultural poultry scientists and a small number of ovarian cancer researchers.Comprehensive and proper vivarium support is required to conduct large-scale cancer prevention studies. Only a few facilities are available for biomedical chicken research, including University of Illinois Urbana-Champaign, Cornell University, Penn State University, NC State, Auburn University, and MS State University. Another difficulty is a lack of available antibodies specific for chicken antigens. Because of the structural dissimilarities between most human proteins and murine antigens to their chicken counterparts, cross-reactivity of available antibodies is also limited. The entire chicken genome was sequenced in 2004;⁷⁸ however, the chromosomal locus of many key genes, such as p53, are still unknown. Overall, humans and chickens share about 60% of genetic commonality, whereas humans and rats share about 88% of their genes. Specific pathway-mutated strains of chickens are not yet available, limiting the ability to study key pathways in carcinogenesis and prevention of cancer using this model. Although all 5 different subtypes of ovarian cancer are present in hens, their most predominant subtype is different from women. Close to 70% of women diagnosed with ovarian cancer have serous EOC, while the predominant subtype reported in hens is endometrioid.¹⁵ However, these comparisons are complicated because observations of cancer in hens consist of both early and late stages of the disease, wherein women, most of the data is from late stage and aggressive ovarian carcinoma.The spontaneous onset of ovarian cancer and the histologic and pathologic similarities to the human form of the disease make laying hens an excellent model for continued research on EOC. To date, a large number of studies have been performed on laying hens. Here we have divided the current studies into 2 groups— (A) studies that have described the molecular presentation of EOC to be similar to that in women; (AuthorYearSignificanceKey molecular targetsCitationHaritani and colleagues.1984Investigating ovarian tumors for key gene signaturesOvalbumin 71 Rodriguez-Burford and colleagues.2001Investigating expressions of clinically important prognostic markers in cancerous hensCA125, cytokeratin AE1/AE3, pan cytokeratin, Lewis Y, CEA, Tag 72, PCNA, EGFR, erbB-2, p27, TGF{α}, Ki-67, MUC1, and MUC2 135 Giles and colleagues.2004, 2006Investigating ovarian tumors for key gene signaturesOvalbumin, PR, PCNA, Vimentin62, 63Jackson and colleagues.2007CA125 expression in hen ovarian tumorsCA125 79 Stammer and colleagues.2008SELENBP1 downregulation in hen ovarian tumorsSELENBP1 149 Hales and colleagues.2008Cyclooxygenase expressions in hen ovarian tumorsCOX1, COX2, PGE2 67 Urick and colleagues.2008-2009VEGF expression in cultured ascites cells from hen ovarian tumorsVEGF160, 161Ansenberger and colleagues.2009Elevation of E-cadherin in hen ovarian tumorsE-cad 6 Hakim and colleagues.2009Investigating oncogenic mutations in hen ovarian tumorsp53, K-ras, H-ras 66 Zhuge and colleagues.2009CYP1B1 levels in chicken ovarian tumorsCYP1B1 175 Seo and colleagues.2010Upregulation of Claudin-10 in hen ovarian tumorsClaudin-10 145 Trevino and colleagues.2010Investigating ovarian tumors for key gene signaturesOvalbumin, Pax2, SerpinB3, OVM, LTF, RD 157 Choi and colleagues.2011Upregulation of MMP-3 in hen ovarian tumor stromaMMP-3 28 Barua and colleagues.2012Upregulation of DR6 in hen ovarian tumorsDR6 16 Lee and colleagues.2012-2014Upregulation of DNA methylation in hen ovarian tumorsDNMT1, DNMT3A, DNMT3B,
SPP1, SERPINB11, SERPINB1394, 101, 103, 104Lim and colleagues.2013-2014Key genes upregulated in endometrioid hen tumorsAvBD-11, CTNNB1, Wnt4102, 11, 100Bradaric and colleagues.2013Investigating immune cells in hen ovarian tumors 23 Ma and colleagues.2014Identifying unique proteins from proteomic profilingF2 thrombin, ITIH2 106 Hales and colleagues.2014Key genes upregulated in hen ovarian tumorsPAX2, MSX2, FOXA2, EN1 68 Parada and colleagues,2017Unique ganglioside expressed in hen ovarian tumorsNeuGcGM3 124 Open in a separate windowTable 2.Ovarian cancer prevention studies using laying hen model

Mouse Models of Osteoarthritis: A Summary of Models and Outcomes Assessment

Osteoarthritis (OA) is a multidimensional health problem and a common chronic disease. It has a substantial impact on patient quality of life and is a common cause of pain and mobility issues in older adults. The functional limitations, lack of curative treatments, and cost to society all demonstrate the need for translational and clinical research. The use of OA models in mice is important for achieving a better understanding of the disease. Models with clinical relevance are needed to achieve 2 main goals: to assess the impact of the OA disease (pain and function) and to study the efficacy of potential treatments. However, few OA models include practical strategies for functional assessment of the mice. OA signs in mice incorporate complex interrelations between pain and dysfunction. The current review provides a comprehensive compilation of mouse models of OA and animal evaluations that include static and dynamic clinical assessment of the mice, merging evaluation of pain and function by using automatic and noninvasive techniques. These new techniques allow simultaneous recording of spontaneous activity from thousands of home cages and also monitor environment conditions. Technologies such as videography and computational approaches can also be used to improve pain assessment in rodents but these new tools must first be validated experimentally. An example of a new tool is the digital ventilated cage, which is an automated home-cage monitor that records spontaneous activity in the cages.

Osteoarthritis (OA) is a multidimensional health problem and a common chronic disease.³⁶ Functional limitations, the absence of curative treatments, and the considerable cost to society result in a substantial impact on quality of life.⁷⁶ Historically, OA has been described as whole joint and whole peri-articular diseases and as a systemic comorbidity.^9,111 OA consists of a disruption of articular joint cartilage homeostasis leading to a catabolic pathway characterized by chondrocyte degeneration and destruction of the extracellular matrix (ECM). Low-grade chronic systemic inflammation is also actively involved in the process.^42,92 In clinical practice, mechanical pain, often accompanied by a functional decline, is the main reason for consultations. Recommendations to patients provide guidance for OA management.^{22, 33,49,86} Evidence-based consensus has led to a variety of pharmacologic and nonpharmacologic modalities that are intended to guide health care providers in managing symptomatic patients. Animal-based research is of tremendous importance for the study of early diagnosis and treatment, which are crucial to prevent the disease progression and provide better care to patients.The purpose of animal-based OA research is 2-fold: to assess the impact of the OA disease (pain and function) and to study the efficacy of a potential treatment.^18,67 OA model species include large animals such as the horse, goat, sheep, and dog, whose size and anatomy are expected to better reflect human joint conditions. However, small animals such as guinea pig, rabbit, mouse, and rat represent 77% of the species used.^1,87 In recent years, mice have become the most commonly used model for studying OA. Mice have several advantageous characteristics: a short development and life span, easy and low-cost breeding and maintenance, easy handling, small joints that allow histologic analysis of the whole joint,³² and the availability of genetically modified lines.¹⁰⁸ Standardized housing, genetically defined strains and SPF animals reduce the genetic and interindividual acquired variability. Mice are considered the best vertebrate model in terms of monitoring and controlling environmental conditions.^7,14,15,87 Mouse skeletal maturation is reached at 10 wk, which theoretically constitutes the minimal age at which mice should be entered into an OA study.^64,87,102 However, many studies violate this limit by testing mice at 8 wk of age.Available models for OA include the following (32,111 physical activity and exercise induced OA; noninvasive mechanical loading (repetitive mild loading and single-impact injury); and surgically induced (meniscectomy models or anterior cruciate ligament transection). The specific model used would be based on the goal of the study.⁷ For example, OA pathophysiology, OA progression, and OA therapies studies could use spontaneous, genetic, surgical, or noninvasive models. In addition, pain studies could use chemical models. Lastly, post-traumatic studies would use surgical or noninvasive models; the most frequently used method is currently destabilization of the medial meniscus,³² which involves transection of the medial meniscotibial ligament, thereby destabilizing the joint and causing instability-driven OA. An important caveat for mouse models is that the mouse and human knee differ in terms of joint size, joint biomechanics, and histologic characteristics (layers, cellularity),^32,64 and joint differences could confound clinical translation.¹⁰ Table 1. Mouse models of osteoarthritis.

Arabidopsis thaliana overexpressing glycolate oxidase in chloroplasts: H2O2-induced changes in primary metabolic pathways

Reactive oxygen species (ROS) represent both toxic by-products of aerobic metabolism as well as signaling molecules in processes like growth regulation and defense pathways. The study of signaling and oxidative-damage effects can be separated in plants expressing glycolate oxidase in the plastids (GO plants), where the production of H₂O₂ in the chloroplasts is inducible and sustained perturbations can reproducibly be provoked by exposing the plants to different ambient conditions. Thus, GO plants represent an ideal non-invasive model to study events related to the perception and responses to H₂O₂ accumulation. Metabolic profiling of GO plants indicated that under high light a sustained production of H₂O₂ imposes coordinate changes on central metabolic pathways. The overall metabolic scenario is consistent with decreased carbon assimilation, which results in lower abundance of glycolytic and tricarboxylic acid cycle intermediates, while simultaneously amino acid metabolism routes are specifically modulated. The GO plants, although retarded in growth and flowering, can complete their life cycle indicating that the reconfiguration of the central metabolic pathways is part of a response to survive and thus, to adapt to stress conditions imposed by the accumulation of H₂O₂ during the light period.Key words: Arabidopsis thaliana, H₂O₂, oxidative stress, reactive oxygen species, signalingReactive oxygen species (ROS) are key molecules in the regulation of plant development, stress responses and programmed cell death. Depending on the identity of ROS species or its subcellular production site, different cellular responses are provoked.¹ To assess the effects of metabolically generated H₂O₂ in chloroplasts, we have recently generated Arabidopsis plants in which the peroxisomal GO was targeted to chloroplasts.² The GO overexpressing plants (GO plants) show retardation in growth and flowering time, features also observed in catalase, ascorbate peroxidase and MnSOD deficient mutants.^3–5 The analysis of GO plants indicated that H₂O₂ is responsible for the observed phenotype. GO plants represent an ideal non-invasive model system to study the effects of H₂O₂ directly in the chloroplasts because H₂O₂ accumulation can be modulated by growing the plants under different ambient conditions. By this, growth under low light or high CO₂ concentrations minimizes the oxygenase activity of RubisCO and thus the flux through GO whereas the exposition to high light intensities enhances photorespiration and thus the flux through GO.Here, we explored the impact of H₂O₂ production on the primary metabolism of GO plants by assessing the relative levels of various metabolites by gas chromatography coupled to mass spectrometry (GC-MS)⁶ in rosettes of plants grown at low light (30 µmol quanta m⁻² s⁻¹) and after exposing the plants for 7 h to high light (600 µmol quanta m⁻² s⁻¹). The results obtained for the GO5 line are shown in After 1 h at 30 µEAfter 7 h at 600 µEAlanine0.88 ± 0.052.83 ± 0.68Asparagine1.39 ± 0.123.64 ± 0.21Aspartate0.88 ± 0.031.65 ± 0.10GABA1.14 ± 0.051.13 ± 0.05Glutamate0.97 ± 0.041.51 ± 0.07Glutamine1.06 ± 0.111.87 ± 0.06Glycine1.23 ± 0.070.30 ± 0.02Isoleucine3.52 ± 0.403.00 ± 0.15Leucine1.36 ± 0.220.57 ± 0.06Lysine1.49 ± 0.130.38 ± 0.02Methionine0.96 ± 0.054.54 ± 0.51Phenylalanine0.95 ± 0.030.94 ± 0.04Proline1.32 ± 0.221.60 ± 0.13Serine1.05 ± 0.041.49 ± 0.15Threonine4.74 ± 0.175.51 ± 0.34Valine0.91 ± 0.130.29 ± 0.02Citrate/Isocitrate0.65 ± 0.020.64 ± 0.022-oxoglutarate0.95 ± 0.110.76 ± 0.05Succinate0.78 ± 0.040.72 ± 0.02Fumarate0.64 ± 0.030.31 ± 0.01Malate0.74 ± 0.030.60 ± 0.02Pyruvate1.19 ± 0.280.79 ± 0.04Ascorbate1.13 ± 0.142.44 ± 0.45Galactonate-γ-lactone1.81 ± 0.401.62 ± 0.28Fructose1.20 ± 0.130.37 ± 0.01Glucose1.38 ± 0.170.30 ± 0.01Mannose0.90 ± 0.271.34 ± 0.28Sucrose1.04 ± 0.070.49 ± 0.02Fructose-6P0.82 ± 0.151.20 ± 0.15Glucose-6P0.87 ± 0.061.25 ± 0.183-PGA1.13 ± 0.110.35 ± 0.02DHAP1.38 ± 0.091.26 ± 0.08Glycerate0.99 ± 0.040.67 ± 0.01Glycerol1.07 ± 0.041.12 ± 0.05Shikimate1.18 ± 0.040.35 ± 0.01Salicylic acid1.04 ± 0.180.66 ± 0.18Open in a separate windowPlants were grown at 30 µmol m⁻² sec⁻¹ (30 µE). The samples were collected 1 h after the onset of the light period and after 7 h of exposure to 600 µmol m⁻² sec⁻¹ (600 µE), respectively. The values are relative to the respective wild-type (each metabolite = 1) and represent means ± SE of four determinations of eight plants. (*) indicates the value is significantly different from the respective wild-type as determined by the Student''s t test (p < 0.05).At the beginning of the light period in low light conditions, some significant deviations in the levels of metabolites tested were observed in GO plants when compared to the wild-type (2 the transgenic GO activity is sufficient to induce a characteristic metabolic phenotype (Fig. 1). The levels of the tricarboxylic acid (TCA) cycle intermediates, citrate/isocitrate, succinate, fumarate and malate were lower in the GO plants (7 In consequence, OAA might not freely enter the TCA cycle and is redirected to the synthesis of Lys, Thr and Ile, which accumulate in the GO plants (Open in a separate windowFigure 1Simplified scheme of the primary metabolism showing the qualitative variations in metabolite abundance in GO plants obtained by GC-MS analysis (2 Blue boxes indicate a significant increase in the content of the particular metabolite compared to the wild-type, while red boxes indicate a significant decrease. Metabolites without boxes have not been determined. The arrows do not always indicate single steps. Adapted from Baxter et al., 2007.High light treatment induced massive changes in the metabolic profile of GO plants (Fig. 1). The OAA-derived amino acids Asp, Asn, Thr, Ile and Met as well as the 2-oxoglutarate-derived amino acids Glu and Gln accumulated. On the contrary, the levels of the Pyr-derived amino acids Val and Leu and the OAA-derived amino acid Lys decreased. A rational explanation for these metabolic changes is difficult to assess, but these changes could be a consequence of a metabolic reconfiguration in response to high light leading to required physiological functions and thus ensuring continued cellular function and survival, e.g., production of secondary metabolites to mitigate photooxidative damage. The higher levels of Glu observed in the GO plants could be attributed to alternative pathways of glyoxylate metabolism that may occur during photorespiration.⁸ It has been shown earlier that isocitrate derived from glyoxylate and succinate is decarboxylated by cytosolic isocitrate dehydrogenase producing 2-oxoglutarate and further glutamate.⁸In GO plants grown under low light conditions (minimized photorespiratory conditions), the levels of Gly were similar to those of the wild-type whereas, after exposure to high light (photorespiratory conditions), the Gly levels were extremely low, indicating that the GO activity diverts a significant portion of flux from the photorespiratory pathway (7 and also the levels of the lipoic acid-containing subunits of the pyruvate- and 2-oxoglutarate dehydrogenases were shown to be significantly reduced under oxidative stress conditions.^9,10 Similarly, the contents of the soluble sugars sucrose, fructose and glucose and those of 3-PGA and glycerate were lower. In addition, the GO plants showed an impairment in the accumulation of starch under high light conditions, a feature that was not observed if the plants were grown under non-photorespiratory conditions.²Together, these results indicate that the low photosynthetic carbon assimilation in the GO plants exposed to high light is most probably due to enhanced photoinhibition,² the repression of genes encoding photosynthetic components by H₂O₂,^11–13 and the direct damage or inhibition of enzyme activities involved in CO₂ assimilation and energy metabolism by H₂O₂.^7,10,14,15 Moreover, Scarpeci and Valle¹³ showed that in plants treated with the superoxid anion radical producing methylviologen (MV) most of the genes involved in phosphorylytic starch degradation, e.g., the trioseP/Pi translocator and genes involved in starch and sucrose synthesis were repressed, while genes involved in hydrolytic starch breakdown and those involved in sucrose degradation were induced. In line with this, the contents of carbohydrates were also lower in MV-treated plants. Together, these observations can also explain the lower growth rates of the GO plants in conditions where the oxygenase activity of RubisCO becomes important and thus, the flux through GO increases.²The levels of shikimate were lower in GO plants (2^,16 and the low levels of substrates available, as anthocyanins are ultimately synthesized from photosynthates and the GO plants showed a diminished photosynthetic performance.²As expected, the levels of ascorbate and its precursor, galactonate-γ-lactone, were enhanced in the GO plants clearly showing the activation of the cellular antioxidant machinery (10 described the metabolic response to oxidative stress of heterotrophic Arabidopsis cells treated with menadione, which also generates superoxide anion radicals. This oxidative stress was shown to induce metabolic inhibition of flux through the TCA cycle and sectors of amino acid metabolism together with a diversion of carbon into the oxidative pentose phosphate pathway.Signaling and oxidative-damage effects are difficult to separate by manipulating the enzymes of antioxidant systems. In this regard, the GO plants represent a challenging inducible model that avoid acclimatory and adaptative effects. Moreover, it is possible to control the H₂O₂ production in the chloroplasts of GO plants without inducing oxidative damage by changing the conditions of growth.² Further exploration of metabolic changes imposed by different ROS at the cellular and whole organ levels will allow to address many intriguing questions on how plants can rearrange metabolism to cope with oxidative stresses.     

Comprehensive analysis of protein-protein interactions between Arabidopsis MAPKs and MAPK kinases helps define potential MAPK signalling modules

The Arabidopsis genome encodes a 20-member gene family of mitogen-activated protein kinases (MPKs) but biological roles have only been identified for a small subset of these crucial signalling components. In particular, it is unclear how the MPKs may be organized into functional modules within the cell. To gain insight into their potential relationships, we used the yeast two-hybrid system to conduct a directed protein-protein interaction screen between all the Arabidopsis MPKs and their upstream activators (MAPK kinases; MKK). Novel interactions were also tested in vitro for enzyme-substrate functionality, using recombinant proteins. The resulting data confirm a number of earlier reported MKK-MPK relationships, but also reveal a more extensive pattern of interactions that should help to guide future analyses of MAPK signalling in plants.Key words: mitogen-activated protein kinase, mitogen-activated protein kinase kinase, yeast two-hybrid, phosphorylation, protein-protein interaction, ArabidopsisPlant genomes are notably rich in the number of protein kinase signalling components they encode^1–3 and it can therefore be anticipated that the associated signal transduction networks will be highly specialized and complex. Within the plant protein kinase super-family, the highly conserved Arabidopsis mitogen-activated protein kinases (MAPKs; MPKs) are represented by a 20-member family that is most closely related to the ERK class of metazoan MAPKs.⁴ This family includes three sub-families of MPKs whose activation domain carries a -TEY- motif, as well as a fourth, evolutionarily distinct -TDY- sub-family.^4,5 Dual-specificity MAPK kinases (MKK) serve as the canonical activators of MPKs through phosphorylation of both the threonine and tyrosine residues within the MPK activation loop -TXY- motif. The Arabidopsis genome encodes ten members of the MKK gene family, among which one (MKK10) lacks the fully conserved -S/T-X_3-5-S/T- motif that typifies eukaryotic MAPK kinases.⁵Numerous reports have provided evidence for the involvement of plant MPKs in a wide range of biotic and abiotic stress responses, as well as phytohormone signalling and developmental patterning, as recently reviewed in.⁶ However, defining functional MKK-MPK module combinations by connecting a particular activated MPK to a specific upstream MKK remains a challenge. Since there are precedents for activation of multiple MPKs by one MKK, as well as evidence for more than one MKK having the capability of activating a given MPK, there are many possible ways in which MKK-MPK signalling modules might potentially be configured. Phenotype-based forward genetic screens in Arabidopsis have provided relatively little insight into these relationships, with only one MPK (MPK4) being recovered as a loss-of-function mutant.⁷ The failure to recover mutations in the other MPK loci, or in any of the MKKs, in such screens could indicate that there is considerable functional redundancy within the MAPK signalling network, that the phenotypic consequences of a loss-of-function mutation are subtle or conditional, or that loss-of-function genotypes are non-viable.Since the nature of protein kinase/phosphatase activities depends on direct physical encounters between the enzyme and its target protein, we hypothesized that the ability of particular proteins to interact effectively with each other would define one level of specificity within the global Arabidopsis MKK/MPK network. To test this idea, we conducted a comprehensive directed yeast two-hybrid screen using the ten Arabidopsis MKKs as individual bait proteins, and each of the twenty MPKs as prey proteins. Several of the protein-protein interactions detected in this Y2H screen were also tested in direct phosphorylation assays in vitro, using recombinant proteins.Nine of the ten Arabidopsis MKK proteins were found to interact with at least one MPK protein in our Y2H assays (https://www.genevestigator.ethz.ch/gv/index.jsp). Its putative orthologue in Populus trichocarpa is similarly silent,^5,8 consistent with a gene that may be losing its biological functionality. Most other MKKs were found to interact with two or more MPK targets, and in several cases these results confirmed earlier reports of MKK-MPK interactions. For example, we found that MKK1 and MKK2, two closely related MAPKKs, both interacted with MPK 4 and with MPK11, a pair of paralogous MPKs. Interaction between MKK1 (MEK1) and MPK4 had already been observed in one of the first studies of plant MKK-MPK relationships,⁹ while a later study also found that MKK2 could interact with MPK4, among twelve MPKs surveyed.¹⁰ However, neither of these reports had examined MPK11. We could confirm by in vitro phosphorylation assays using “constitutively active” (CA) forms of recombinant MKK1 and MKK2 that both of these MKKs can phosphorylate recombinant MPK4, but, in contrast to the Y2H interaction pattern, both CAMKKs showed only very weak activity with MPK11 as a substrate (Fig. 2A and B).Open in a separate windowFigure 2Effects of incubation with recombinant GST-CAMKK proteins on protein phosphorylation of recombinant GST-MPKs. The constitutively active mutant forms of the MKKs were generated by QuickChange site-directed mutagenesis (Stratagene) and confirmed by sequencing. The conserved Ser or Thr residues in the activation loop in MKKs were replaced with acidic residues to create a “constitutively active” kinase (T218E and S224D for CAMKK1, T220D and T226E for CAMKK2, S221D and T227E for CAMKK6, S193E and S199D for CAMKK7, and S195E and S201E for CAMKK9). PCR amplicons of the full-length cDNAs corresponding to MPK2 (At1g59580), MPK4 (At4g01370), MPK6 (At2g43790), MPK10 (At3g59790), MPK11 (At1g01560), MPK13 (At1g07880), MPK17 (At2g01450), MPK20 (At2g42880), MKK1 (At4g26070), MKK2 (At4g29810), MKK6 (At5g56580), MKK7 (At1g18350) and MKK9 (At1g73500) were purified, digested with the appropriate restriction enzymes and subcloned in either the pGEX 4T-2 or pDEST15 vector, which expresses the recombinant protein with a N-terminal GST tag. Each of wild-type MAPK and mutant recombinant CAMKK1, CAMKK2, CAMKK6, CAMKK7 and CAMKK9 were expressed as glutathione S-transferase (GST) fusion proteins as previously described.¹⁹ For the in vitro phosphorylation assays, each GST-MPK (1 µg) was incubated in 25 µL of kinase reaction buffer (50 mM Tris-HCl, pH 7.5, 5 mM β-glycerolphosphate, 2 mM DTT, 10 mM MgCl₂, 0.1 mM Na₃VO₄, 0.1 mM ATP and 3 µCi of [γ-³²P] ATP) either with or without constitutively active GST-MKKs (0.3 µg) at 30°C for 30 min. The reaction was terminated by addition of concentrated SDS-PAGE sample buffer followed by boiling for 5 min. Reaction products were analyzed using SDS-PAGE, autoradiography, and CBB staining. (A) Phosphorylation of MPKs by incubation with CAMKK1. (B) Phosphorylation of MPKs by incubation with CAMKK2. (C) Phosphorylation of MPKs by incubation with CAMKK6. (D) Phosphorylation of MPK2 by incubation with CAMKK7. (E) Phosphorylation of MPKs by incubation with CAMKK9.

Table 1

Full-length cDNA clones corresponding to the open reading frame of each of the ten Arabidopsis MKK and twenty distinct MAPKs were isolated from Arabidopsis cDNA and cloned into a Gateway™ entry vector, either pENTR (Invitrogen) or pCR8 (Invitrogen)

Variation in Adult Plant Phenotypes and Partitioning among Seed and Stem-Borne Roots across Brachypodium distachyon Accessions to Exploit in Breeding Cereals for Well-Watered and Drought Environments

Seedling roots enable plant establishment. Their small phenotypes are measured routinely. Adult root systems are relevant to yield and efficiency, but phenotyping is challenging. Root length exceeds the volume of most pots. Field studies measure partial adult root systems through coring or use seedling roots as adult surrogates. Here, we phenotyped 79 diverse lines of the small grass model Brachypodium distachyon to adults in 50-cm-long tubes of soil with irrigation; a subset of 16 lines was droughted. Variation was large (total biomass, ×8; total root length [TRL], ×10; and root mass ratio, ×6), repeatable, and attributable to genetic factors (heritabilities ranged from approximately 50% for root growth to 82% for partitioning phenotypes). Lines were dissected into seed-borne tissues (stem and primary seminal axile roots) and stem-borne tissues (tillers and coleoptile and leaf node axile roots) plus branch roots. All lines developed one seminal root that varied, with branch roots, from 31% to 90% of TRL in the well-watered condition. With drought, 100% of TRL was seminal, regardless of line because nodal roots were almost always inhibited in drying topsoil. Irrigation stimulated nodal roots depending on genotype. Shoot size and tillers correlated positively with roots with irrigation, but partitioning depended on genotype and was plastic with drought. Adult root systems of B. distachyon have genetic variation to exploit to increase cereal yields through genes associated with partitioning among roots and their responsiveness to irrigation. Whole-plant phenotypes could enhance gain for droughted environments because root and shoot traits are coselected.Adult plant root systems are relevant to the size and efficiency of seed yield. They supply water and nutrients for the plant to acquire biomass, which is positively correlated to the harvest index (allocation to seed grain), and the stages of flowering and grain development. Modeling in wheat (Triticum aestivum) suggested that an extra 10 mm of water absorbed by such adult root systems during grain filling resulted in an increase of approximately 500 kg grain ha⁻¹ (Manschadi et al., 2006). This was 25% above the average annual yield of wheat in rain-fed environments of Australia. This number was remarkably close to experimental data obtained in the field in Australia (Kirkegaard et al., 2007). Together, these modeling and field experiments have shown that adult root systems are critical for water absorption and grain yield in cereals, such as wheat, emphasizing the importance of characterizing adult root systems to identify phenotypes for productivity improvements.Most root phenotypes, however, have been described for seedling roots. Seedling roots are essential for plant establishment, and hence, the plant’s potential to set seed. For technical reasons, seedlings are more often screened than adult plants because of the ease of handling smaller plants and the high throughput. Seedling-stage phenotyping may also improve overall reproducibility of results because often, growth media are soil free. Seedling soil-free root phenotyping conditions are well suited to dissecting fine and sensitive mechanisms, such as lateral root initiation (Casimiro et al., 2003; Péret et al., 2009a, 2009b). A number of genes underlying root processes have been identified or characterized using seedlings, notably with the dicotyledonous models Arabidopsis (Arabidopsis thaliana; Mouchel et al., 2004; Fitz Gerald et al., 2006; Yokawa et al., 2013) and Medicago truncatula (Laffont et al., 2010) and the cereals maize (Zea mays; Hochholdinger et al., 2001) and rice (Oryza sativa; Inukai et al., 2005; Kitomi et al., 2008).Extrapolation from seedling to adult root systems presents major questions (Hochholdinger and Zimmermann, 2008; Chochois et al., 2012; Rich and Watt, 2013). Are phenotypes in seedling roots present in adult roots given developmental events associated with aging? Is expression of phenotypes correlated in seedling and adult roots if time compounds effects of growth rates and growth conditions on roots? Watt et al. (2013) showed in wheat seedlings that root traits in the laboratory and field correlated positively but that neither correlated with adult root traits in the field. Factors between seedling and adult roots seemed to be differences in developmental stage and the time that growing roots experience the environment.Seedling and adult root differences may be larger in grasses than dicotyledons. Grass root systems have two developmental components: seed-borne (seminal) roots, of which a number emerge at germination and continue to grow and branch throughout the plant life, and stem-borne (nodal or adventitious) roots, which emerge from around the three-leaf stage and continue to emerge, grow, and branch throughout the plant life. Phenotypes and traits of adult root systems of grasses, which include the major cereal crops wheat, rice, and maize, are difficult to predict in seedling screens and ideally identified from adult root systems first (Gamuyao et al., 2012).Phenotyping of adult roots is possible in the field using trenches (Maeght et al., 2013) or coring (Wasson et al., 2014). A portion of the root system is captured with these methods. Alternatively, entire adult root systems can be contained within pots dug into the ground before sowing. These need to be large; field wheat roots, for example, can reach depths greater than 1.5 m depending on genotype and environment. This method prevents root-root interactions that occur under normal field sowing of a plant canopy and is also a compromise.A solution to the problem of phenotyping adult cereal root systems is a model for monocotyledon grasses: Brachypodium distachyon. B. distachyon is a small-stature grass with a small genome that is fully sequenced (Vogel et al., 2010). It has molecular tools equivalent to those available in Arabidopsis (Draper et al., 2001; Brkljacic et al., 2011; Mur et al., 2011). The root system of B. distachyon reference line Bd21 is more similar to wheat than other model and crop grasses (Watt et al., 2009). It has a seed-borne primary seminal root (PSR) that emerges from the embryo at seed germination and multiple stem-borne coleoptile node axile roots (CNRs) and leaf node axile roots (LNRs), also known as crown roots or adventitious roots, that emerge at about three leaves through to grain development. Branch roots emerge from all root types. There are no known anatomical differences between root types of wheat and B. distachyon (Watt et al., 2009). In a recent study, we report postflowering root growth in B. distachyon line Bd21-3, showing that this model can be used to answer questions relevant to the adult root systems of grasses (Chochois et al., 2012).In this study, we used B. distachyon to identify adult plant phenotypes related to the partitioning among seed-borne and stem-borne shoots and roots for the genetic improvement of well-watered and droughted cereals (Fig. 1; Krassovsky, 1926; Navara et al., 1994), nitrogen, phosphorus (Tennant, 1976; Brady et al., 1995), oxygen (Wiengweera and Greenway, 2004), soil hardness (Acuna et al., 2007), and microorganisms (Sivasithamparam et al., 1978). Of note is the study by Krassovsky (1926), which was the first, to our knowledge, to show differences in function related to water. Krassovsky (1926) showed that seminal roots of wheat absorbed almost 2 times the water as nodal roots per unit dry weight but that nodal roots absorbed a more diluted nutrient solution than seminal roots. Krassovsky (1926) also showed by removing seminal or nodal roots as they emerged that “seminal roots serve the main stem, while nodal roots serve the tillers” (Krassovsky, 1926). Volkmar (1997) showed, more recently, in wheat that nodal and seminal roots may sense and respond to drought differently. In millet (Pennisetum glaucum) and sorghum (Sorghum bicolor), Rostamza et al. (2013) found that millet was able to grow nodal roots in a dryer soil than sorghum, possibly because of shoot and root vigor.Open in a separate windowFigure 1.B. distachyon plant scanned at the fourth leaf stage, with the root and shoot phenotypes studied indicated. Supplemental Table S1.

Antimicrobial Activity of Simulated Solar Disinfection against Bacterial,Fungal, and Protozoan Pathogens and Its Enhancement by Riboflavin

Riboflavin significantly enhanced the efficacy of simulated solar disinfection (SODIS) at 150 watts per square meter (W m⁻²) against a variety of microorganisms, including Escherichia coli, Fusarium solani, Candida albicans, and Acanthamoeba polyphaga trophozoites (>3 to 4 log₁₀ after 2 to 6 h; P < 0.001). With A. polyphaga cysts, the kill (3.5 log₁₀ after 6 h) was obtained only in the presence of riboflavin and 250 W m⁻² irradiance.Solar disinfection (SODIS) is an established and proven technique for the generation of safer drinking water (11). Water is collected into transparent plastic polyethylene terephthalate (PET) bottles and placed in direct sunlight for 6 to 8 h prior to consumption (14). The application of SODIS has been shown to be a simple and cost-effective method for reducing the incidence of gastrointestinal infection in communities where potable water is not available (2-4). Under laboratory conditions using simulated sunlight, SODIS has been shown to inactivate pathogenic bacteria, fungi, viruses, and protozoa (6, 12, 15). Although SODIS is not fully understood, it is believed to achieve microbial killing through a combination of DNA-damaging effects of ultraviolet (UV) radiation and thermal inactivation from solar heating (21).The combination of UVA radiation and riboflavin (vitamin B₂) has recently been reported to have therapeutic application in the treatment of bacterial and fungal ocular pathogens (13, 17) and has also been proposed as a method for decontaminating donor blood products prior to transfusion (1). In the present study, we report that the addition of riboflavin significantly enhances the disinfectant efficacy of simulated SODIS against bacterial, fungal, and protozoan pathogens.Chemicals and media were obtained from Sigma (Dorset, United Kingdom), Oxoid (Basingstoke, United Kingdom), and BD (Oxford, United Kingdom). Pseudomonas aeruginosa (ATCC 9027), Staphylococcus aureus (ATCC 6538), Bacillus subtilis (ATCC 6633), Candida albicans (ATCC 10231), and Fusarium solani (ATCC 36031) were obtained from ATCC (through LGC Standards, United Kingdom). Escherichia coli (JM101) was obtained in house, and the Legionella pneumophila strain used was a recent environmental isolate.B. subtilis spores were produced from culture on a previously published defined sporulation medium (19). L. pneumophila was grown on buffered charcoal-yeast extract agar (5). All other bacteria were cultured on tryptone soy agar, and C. albicans was cultured on Sabouraud dextrose agar as described previously (9). Fusarium solani was cultured on potato dextrose agar, and conidia were prepared as reported previously (7). Acanthamoeba polyphaga (Ros) was isolated from an unpublished keratitis case at Moorfields Eye Hospital, London, United Kingdom, in 1991. Trophozoites were maintained and cysts prepared as described previously (8, 18).Assays were conducted in transparent 12-well tissue culture microtiter plates with UV-transparent lids (Helena Biosciences, United Kingdom). Test organisms (1 × 10⁶/ml) were suspended in 3 ml of one-quarter-strength Ringer''s solution or natural freshwater (as pretreated water from a reservoir in United Kingdom) with or without riboflavin (250 μM). The plates were exposed to simulated sunlight at an optical output irradiance of 150 watts per square meter (W m⁻²) delivered from an HPR125 W quartz mercury arc lamp (Philips, Guildford, United Kingdom). Optical irradiances were measured using a calibrated broadband optical power meter (Melles Griot, Netherlands). Test plates were maintained at 30°C by partial submersion in a water bath.At timed intervals for bacteria and fungi, the aliquots were plated out by using a WASP spiral plater and colonies subsequently counted by using a ProtoCOL automated colony counter (Don Whitley, West Yorkshire, United Kingdom). Acanthamoeba trophozoite and cyst viabilities were determined as described previously (6). Statistical analysis was performed using a one-way analysis of variance (ANOVA) of data from triplicate experiments via the InStat statistical software package (GraphPad, La Jolla, CA).The efficacies of simulated sunlight at an optical output irradiance of 150 W m⁻² alone (SODIS) and in the presence of 250 μM riboflavin (SODIS-R) against the test organisms are shown in Table ​Table1.1. With the exception of B. subtilis spores and A. polyphaga cysts, SODIS-R resulted in a significant increase in microbial killing compared to SODIS alone (P < 0.001). In most instances, SODIS-R achieved total inactivation by 2 h, compared to 6 h for SODIS alone (Table ​(Table1).1). For F. solani, C. albicans, ands A. polyphaga trophozoites, only SODIS-R achieved a complete organism kill after 4 to 6 h (P < 0.001). All control experiments in which the experiments were protected from the light source showed no reduction in organism viability over the time course (results not shown).

TABLE 1.

Efficacies of simulated SODIS for 6 h alone and with 250 μM riboflavin (SODIS-R)

Prion interference with multiple prion isolates

Co-inoculation of prion strains into the same host can result in interference, where replication of one strain hinders the ability of another strain to cause disease. The drowsy (DY) strain of hamster-adapted transmissible mink encephalopathy (TME) extends the incubation period or completely blocks the hyper (HY) strain of TME following intracerebral, intraperitoneal or sciatic nerve routes of inoculation. However, it is not known if the interfering effect of the DY TME agent is exclusive to the HY TME agent by these experimental routes of infection. To address this issue, we show that the DY TME agent can block hamster-adapted chronic wasting disease (HaCWD) and the 263K scrapie agent from causing disease following sciatic nerve inoculation. Additionally, per os inoculation of DY TME agent slightly extends the incubation period of per os superinfected HY TME agent. These studies suggest that prion strain interference can occur by a natural route of infection and may be a more generalized phenomenon of prion strains.Key words: prion diseases, prion interference, prion strainsPrion diseases are fatal neurodegenerative diseases that are caused by an abnormal isoform of the prion protein, PrP^Sc.¹ Prion strains are hypothesized to be encoded by strain-specific conformations of PrP^Sc resulting in strain-specific differences in clinical signs, incubation periods and neuropathology.^2–7 However, a universally agreed upon definition of prion strains does not exist. Interspecies transmission and adaptation of prions to a new host species leads to the emergence of a dominant prion strain, which can be due to selection of strains from a mixture present in the inoculum, or produced upon interspecies transmission.^8,9 Prion strains, when present in the same host, can interfere with each other.Prion interference was first described in mice where a long incubation period strain 22C extended the incubation period of a short incubation period strain 22A following intracerebral inoculation.¹⁰ Interference between other prion strains has been described in mice and hamsters using rodent-adapted strains of scrapie, TME, Creutzfeldt-Jacob disease and Gerstmannn-Sträussler-Scheinker syndrome following intracerebral, intraperitoneal, intravenous and sciatic nerve routes of inoculation.^10–15 We previously demonstrated the detection of PrP^Sc from the long incubation period DY TME agent correlated with its ability to extend the incubation period or completely block the superinfecting short incubation period HY TME agent from causing disease and results in a reduction of HY PrP^Sc levels following sciatic nerve inoculation.¹² However, it is not known if a single long incubation period agent (e.g., DY TME) can interfere with more than one short incubation period agent or if interference can occur by a natural route of infection.To examine the question if one long incubation period agent can extend the incubation period of additional short incubation period agents, hamsters were first inoculated in the sciatic nerve with the DY TME agent 120 days prior to superinfection with the short-incubation period agents HY TME, 263K scrapie and HaCWD.^16–18 The HY TME and 263K scrapie agents have been biologically cloned and have distinct PrP^Sc properties.^19,20 The HaCWD agent used in this study is seventh hamster passage that has not been biologically cloned and therefore will be referred to as a prion isolate. Sciatic nerve inoculations were performed as previously described.^11,12 Briefly, hamsters were inoculated with 103.0 i.c. LD₅₀ of the DY TME agent or equal volume (2 µl of a 1% w/v brain homogenate) of uninfected brain homogenate 120 days prior to superinfection of the same sciatic nerve with either 10^4.6 i.c. LD₅₀ of the HY TME agent, 10^5.2 i.c. LD₅₀ of the HaCWD agent or 10^4.6 i.c. LD₅₀/g 263K scrapie agent (Bartz J, unpublished data).^16,18,21 Animals were observed three times per week for the onset of clinical signs of HY TME, 263K and HaCWD based on the presence of ataxia and hyperexcitability, while the clinical diagnosis of DY TME was based on the appearance of progressive lethargy.^16–18 The incubation period was calculated as the number of days between the onset of clinical signs of the agent strain that caused disease and the inoculation of that strain. The Student''s t-test was used to compare incubation periods.¹² We found that sciatic nerve inoculation of both the HaCWD agent and 263K scrapie agent caused disease with a similar incubation period to animals infected with the HY TME agent (12 In hamsters inoculated with the DY TME agent 120 days prior to superinfection with the HaCWD or 263K agents, the animals developed clinical signs of DY TME with an incubation period that was not different from the DY TME agent control group (12 The PrP^Sc migration properties were consistent with the clinical diagnosis and all co-infected animals had PrP^Sc that migrated similar to PrP^Sc from the DY TME agent infected control animal (Fig. 1, lanes 1–10). This data indicates that the DY TME agent can interfere with more than one isolate and that interference in the CNS may be a more generalized phenomenon of prion strains.Open in a separate windowFigure 1The strain-specific properties of PrP^Sc correspond to the clinical diagnosis of disease. Western blot analysis of 250 µg brain equivalents of proteinase K digested brain homogenate from prion-infected hamsters following intracerebral (i.c.), sciatic nerve (i.sc.) or per os inoculation with either the HY TME (HY), DY TME (DY), 263K scrapie (263K), hamster-adapted CWD (CWD) agents or mock-infected (UN). The unglycoyslated PrP^Sc glycoform of HY TME, 263K scrapie and hamster-adapted CWD migrates at 21 kDa. The unglycosylated PrP^Sc glycoform of DY PrP^Sc migrates at 19 kDa. Migration of 19 and 21 kDa PrP^Sc are indicated by the arrows on the left of the figure. n.a., not applicable.

Table 1

Clinical signs and incubation periods of hamsters inoculated in the sciatic nerve with either the HY TME, HaCWD or 263K scrapie agents, or co-infected with the DY TME agent 120 days prior to superinfection of hamsters with the HY TME, HaCWD or 263K agents