Immunomodulation by Mesenchymal Stem Cells in Veterinary Species

Mesenchymal stem cells (MSC) are adult-derived multipotent stem cells that have been derived from almost every tissue. They are classically defined as spindle-shaped, plastic-adherent cells capable of adipogenic, chondrogenic, and osteogenic differentiation. This capacity for trilineage differentiation has been the foundation for research into the use of MSC to regenerate damaged tissues. Recent studies have shown that MSC interact with cells of the immune system and modulate their function. Although many of the details underlying the mechanisms by which MSC modulate the immune system have been defined for human and rodent (mouse and rat) MSC, much less is known about MSC from other veterinary species. This knowledge gap is particularly important because the clinical use of MSC in veterinary medicine is increasing and far exceeds the use of MSC in human medicine. It is crucial to determine how MSC modulate the immune system for each animal species as well as for MSC derived from any given tissue source. A comparative approach provides a unique translational opportunity to bring novel cell-based therapies to the veterinary market as well as enhance the utility of animal models for human disorders. The current review covers what is currently known about MSC and their immunomodulatory functions in veterinary species, excluding laboratory rodents.Abbreviations: AT, adipose tissue; BM, Bone marrow; CB, umbilical cord blood; CT, umbilical cord tissue; DC, dendritic cell; IDO, indoleamine 2;3-dioxygenase; MSC, mesenchymal stem cells; PGE₂, prostaglandin E2; VEGF, vascular endothelial growth factorMesenchymal stem cells (MSC, alternatively known as mesenchymal stromal cells) were first reported in the literature in 1968.³⁹ MSC are thought to be of pericyte origin (cells that line the vasculature)^21,22 and typically are isolated from highly vascular tissues. In humans and mice, MSC have been isolated from fat, placental tissues (placenta, Wharton jelly, umbilical cord, umbilical cord blood), hair follicles, tendon, synovial membrane, periodontal ligament, and every major organ (brain, spleen, liver, kidney, lung, bone marrow, muscle, thymus, pancreas, skin).^23,121 For most current clinical applications, MSC are isolated from adipose tissue (AT), bone marrow (BM), umbilical cord blood (CB), and umbilical cord tissue (CT; 11,87,99 Clinical trials in human medicine focus on the use of MSC both for their antiinflammatory properties (graft-versus-host disease, irritable bowel syndrome) and their ability to aid in tissue and bone regeneration in combination with growth factors and bone scaffolds (clinicaltrials.gov).¹³¹ For tissue regeneration, the abilities of MSC to differentiate and to secrete mediators and interact with cells of the immune system likely contribute to tissue healing (Figure 1). The current review will not address the specific use of MSC for orthopedic applications and tissue regeneration, although the topic is covered widely in current literature for both human and veterinary medicine.^57,62,90

Table 1.

Tissues from which MSC have been isolated

Focus Issue on Roots: The Optimal Lateral Root Branching Density for Maize Depends on Nitrogen and Phosphorus Availability

Observed phenotypic variation in the lateral root branching density (LRBD) in maize (Zea mays) is large (1–41 cm⁻¹ major axis [i.e. brace, crown, seminal, and primary roots]), suggesting that LRBD has varying utility and tradeoffs in specific environments. Using the functional-structural plant model SimRoot, we simulated the three-dimensional development of maize root architectures with varying LRBD and quantified nitrate and phosphorus uptake, root competition, and whole-plant carbon balances in soils varying in the availability of these nutrients. Sparsely spaced (less than 7 branches cm⁻¹), long laterals were optimal for nitrate acquisition, while densely spaced (more than 9 branches cm⁻¹), short laterals were optimal for phosphorus acquisition. The nitrate results are mostly explained by the strong competition between lateral roots for nitrate, which causes increasing LRBD to decrease the uptake per unit root length, while the carbon budgets of the plant do not permit greater total root length (i.e. individual roots in the high-LRBD plants stay shorter). Competition and carbon limitations for growth play less of a role for phosphorus uptake, and consequently increasing LRBD results in greater root length and uptake. We conclude that the optimal LRBD depends on the relative availability of nitrate (a mobile soil resource) and phosphorus (an immobile soil resource) and is greater in environments with greater carbon fixation. The median LRBD reported in several field screens was 6 branches cm⁻¹, suggesting that most genotypes have an LRBD that balances the acquisition of both nutrients. LRBD merits additional investigation as a potential breeding target for greater nutrient acquisition.At least four major classes of plant roots can be distinguished based on the organ from which they originate: namely the seed, the shoot, the hypocotyl/mesocotyl, and other roots (Zobel and Waisel, 2010). The last class is lateral roots, which form in most plants the majority of the root length, but not necessarily of the root weight, as lateral roots have smaller diameter. Lateral roots start with the formation of lateral root primordia, closely behind the root tip of the parent root. These primordia undergo nine distinguishable steps, of which the last step is the emergence from the cortex of the parent root just behind the zone of elongation, usually only a few days after the first cell divisions that lead to their formation (Malamy and Benfey, 1997). However, not all primordia develop into lateral roots; some stay dormant (Dubrovsky et al., 2006), although dormancy of primordia may not occur in maize (Zea mays; Jordan et al., 1993; Ploshchinskaia et al., 2002). The final number of lateral roots is thereby dependent on the rate of primordia formation as well as the percentage of primordia that develop into lateral roots. This process of primordia formation and lateral root emergence is being studied intensively, including the genes that are activated during the different steps and the hormones regulating the process (López-Bucio et al., 2003; Dubrovsky et al., 2006; Osmont et al., 2007; Péret et al., 2009; Lavenus et al., 2013). Significant genotypic variation in the density of lateral roots has been observed, ranging from no lateral roots to 41 roots cm⁻¹ in maize (Trachsel et al., 2010; Lynch, 2013). This suggests that clear tradeoffs exist for the development of lateral roots and that these genotypes have preprogrammed growth patterns that are adaptive to specific environments. While some of the variation for lateral root branching density (LRBD) that has been observed across environments, for example by Trachsel et al. (2010), is constitutive, many genotypes have strong plasticity responses of LRBD to variations in soil fertility (Zhu et al., 2005a; Osmont et al., 2007). Both the nutrient and carbon status of the plant and the local nutrient environment of the (parent) root tip influence LRBD. Many studies have documented these plasticity responses, and others have tried to unravel parts of the sensing and signaling pathways that regulate LRBD. The utility of root proliferation into a nutrient patch has been studied and debated (Robinson et al., 1999; Hodge, 2004), but much less so the utility of having fewer or more branches across the whole root system. Our understanding of the adaptive significance of variation in LRBD among genotypes is thereby limited, with many studies not accounting for relevant tradeoffs. In this study, we integrate several functional aspects of LRBD with respect to nutrient acquisition, root competition, and internal resource costs and quantify these functional aspects using the functional structural plant model SimRoot. SimRoot simulates plant growth with explicit representation of root architecture in three dimensions (Fig. 1; Supplemental Movie S1). The model focuses on the resource acquisition by the root system and carbon fixation by the shoot while estimating the resource utilization and requirements by all the different organs.

Table I.

Minimum, maximum, and median LRBD in different populations phenotyped by various researchers at several locations in the worldLocations are as follows: D, Juelich, Germany; PA, State College, PA; and SA, Alma, South Africa. Some of the experiments included nutrient treatments: LN, low nitrogen availability; and LP, low phosphorus availability. Data were collected by counting the number of roots along a nodal root segment. Data were supplied by the person indicated under source: H.S., H. Schneider; L.Y., L. York; A.Z., A. Zhan; and J.P., J.A. Postma. WiDiv, Wisconsin Diversity panel; IBM, intermated B73 × Mo17; NAM, nested association mapping.

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

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

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) (

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.

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 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

Evolutionary Strata in a Small Mating-Type-Specific Region of the Smut Fungus Microbotryum violaceum

DNA sequence analysis and genetic mapping of loci from mating-type-specific chromosomes of the smut fungus Microbotryum violaceum demonstrated that the nonrecombining mating-type-specific region in this species comprises ∼25% (∼1 Mb) of the chromosome length. Divergence between homologous mating-type-linked genes in this region varies between 0 and 8.6%, resembling the evolutionary strata of vertebrate and plant sex chromosomes.EVOLUTION of mating types or sex-determining systems often involves the suppression of recombination around the primary sex-determining or mating-type-determining locus. In animals and plants, it is often an entire or almost entire chromosome (Y or W in male or female heterogametic species, respectively) that ceases to recombine with its homologous (X or Z) chromosome (Charlesworth and Charlesworth 2000; Charlesworth 2008). Self-incompatibility loci in plants are also thought to be located in regions of suppressed recombination (Charlesworth et al. 2005; Kamau and Charlesworth 2005; Kamau et al. 2007; Li et al. 2007; Yang et al. 2007). Regardless of the phylogenetic position of a species, such nonrecombining regions are known to follow similar evolutionary trajectories. The nonrecombining region on the sex-specific chromosome expands in several steps, forming evolutionary strata—regions of different X/Y (or Z/W) divergence (Lahn and Page 1999; Handley et al. 2004; Sandstedt and Tucker 2004; Nicolas et al. 2005)—and genes in the nonrecombining regions gradually accumulate deleterious mutations that eventually render them dysfunctional (Charlesworth and Charlesworth 2005; Charlesworth 2008).Fungal mating-type systems are very diverse, with the number of mating types varying from two to several hundred (Casselton 2002). Like sex chromosomes in several animals and plants, suppressed recombination has evolved in regions near fungal mating-type loci, including in Ustilago hordei (Lee et al. 1999), Cryptococcus neoformans (Lengeler et al. 2002), and Neurospora tetrasperma (Menkis et al. 2008). These species have two mating types, but no morphologically distinct sexes. The mating-type locus (the region of suppressed recombination) of C. neoformans is small (∼100 kb) compared with known sex chromosomes and contains only ∼20 genes that, unlike many sex chromosomes (Y or W chromosomes), show no obvious signs of genetic degeneration (Lengeler et al. 2002; Fraser et al. 2004). Judging from the divergence between the homologous genes on the two mating-type-specific chromosomes, C. neoformans started to evolve sex chromosomes a long time ago because silent divergence between the two mating types in the most ancient region exceeds 100% (Fraser et al. 2004). Genes in the younger mating-type-specific region are much less diverged between the two sex chromosomes, suggesting that the evolution of the sex locus in C. neoformans might have proceeded through several steps. The nonrecombining region around the mating-type locus of N. tetrasperma is much larger than in C. neoformans (at least 6.6 Mb), and silent divergence between homologous genes on the mating-type-specific chromosomes ranges from zero to 9%, demonstrating that these mating-type-specific chromosomes evolved recently (Menkis et al. 2008).M. violaceum, which causes anther smut disease in Silene latifolia and other species in the family Caryophyllaceae, has two mating types, A1 and A2 (reviewed by Giraud et al. 2008), which are determined by the presence of mating-type-specific chromosomes (hereafter A1 and A2 chromosomes, or sex chromosomes) in the haploid stage of the life cycle (Hood 2002; Hood et al. 2004). The A1 and A2 chromosomes are distinguishable by size in pulsed-field electrophoresis, and it is possible to isolate individual chromosomes electrophoretically (Hood et al. 2004). Random fragments of A1 and A2 chromosomes have previously been isolated from mating-type-specific bands of pulsed-field separated chromosomes of M. violaceum (Hood et al. 2004). These fragments were assumed to be linked to mating type. The same method was used to isolate fragments of non-mating-type-specific chromosomes. On the basis of the analysis of their sequences, (Hood et al. 2004) proposed that mating-type-specific chromosomes in M. violaceum might be degenerate because they contained a lower proportion of protein-coding genes than other chromosomes. However, it was not determined whether the sequences isolated from the mating-type chromosomes originated from the mating-type-specific or from the recombining regions (Hood et al. 2004), and the relative sizes of these regions are not known for these M. violaceum chromosomes. We tested the mating-type specificity of 86 of these fragments and demonstrate that fewer than a quarter of these loci are located in the mating-type-specific region, suggesting that the nonrecombining region on the A1 and A2 chromosomes is quite small, while the rest of the chromosome probably recombines (like pseudoautosomal regions of sex chromosomes) and is therefore not expected to undergo genetic degeneration. Genetic mapping confirms the presence of two pseudoautosomal regions in the M. violaceum mating-type-specific chromosomes.As these chromosomes are mating type specific in the haploid stage of M. violaceum, mating-type-specific loci (or DNA fragments) can be identified by testing whether they are present exclusively in A1 or A2 haploid strains. We therefore prepared haploid A1 and A2 M. violaceum cultures from S. latifolia plants from two geographically remote locations (accessions Sl405 from Sweden and Sl127 from the French Pyrenees). Haploid sporidial cultures were isolated by a standard dilution method (Kaltz and Shykoff 1997; Oudemans and Alexander 1998). Mating types were determined by PCR amplification of each culture with primers designed for A1 and A2 pheromone receptor genes linked to A1 and A2 mating types (Yockteng et al. 2007). The primers were as follows: 5′-TGGCATCCCTCAATGTTTCC-3′ and 5′-CACCTTTTGATGAGAGGCCG-3′ for the A1 pheromone receptor (GenBank accession no. {"type":"entrez-nucleotide","attrs":{"text":"EF584742","term_id":"156254864","term_text":"EF584742"}}EF584742) and 5′-TGACGAGAGCATTCCTACCG-3′ and 5′-GAAGCGGAACTTGCCTTTCT-3′ for the A2 pheromone receptor (GenBank accession no. {"type":"entrez-nucleotide","attrs":{"text":"EF584741","term_id":"156254862","term_text":"EF584741"}}EF584741). Cultures with PCR product amplified only from an A1 or A2 pheromone receptor gene were selected for further use. The mating types of the cultures were verified by conjugating them in all combinations.The GenBank nucleotide database was searched using BLAST for sequences similar to those isolated by Hood et al. (2004). Sequences with similarity to transposable elements (TE) and other repeats were excluded. The resulting set of nonredundant sequences was used to design PCR primers for 98 fragments. Half of these were originally isolated from the A1 and half from the A2 chromosomes and are hereafter called A1-NNN or A2-NNN (where NNN is the locus number; supporting information, Table S1), which does not imply that these loci are A1 or A2 specific, but merely indicates that they were originally isolated from the A1 or A2 chromosomes. Amplification of these regions from new A1 and A2 M. violaceum cultures, independently isolated by ourselves, revealed that only 5 of the 49 loci isolated from the A1 chromosome are indeed A1 specific and only 6 of 49 isolated from the A2 chromosome are A2 specific. All other loci amplified from both A1 and A2 cultures. Figure 1 illustrates some of these results from the Swedish sample (Sl405).Open in a separate windowFigure 1.—Testing of mating-type specificity for loci isolated from A1 and A2 chromosomes. (a) PCR amplifications from haploid cultures from Sl405 using primers designed from six A1-originated loci. Loci in which a PCR product could be amplified only from A1 cultures (boxed) were classified as specific to mating type A1. (b) PCR tests of six A2-originated loci on the same set of haploids as in a. Loci in which a PCR product amplified only from A2 cultures (boxed) were classified as specific to mating type A2. Loci amplified from both A1 and A2 cultures are not mating type specific.The fragments that amplified from both A1 and A2 mating types may be in recombining regions, or they could be present in mating-type-specific regions on both A1 and A2 chromosomes. If they are in recombining regions, the A1- and A2-linked homologs should not be diverged from each other, but if they are in nonrecombining, mating-type-specific regions, the divergence of the A1- and A2-linked homologs should be roughly proportional to the time since recombination stopped in the region. We therefore sequenced and compared PCR fragments amplified from the two mating types of Sl405 or Sl127 cultures (GenBank accession nos. {"type":"entrez-nucleotide","attrs":{"text":"FI855822","term_id":"258612459","term_text":"FI855822"}}FI855822–{"type":"entrez-nucleotide","attrs":{"text":"FI856001","term_id":"258612570","term_text":"FI856001"}}FI856001). Sequencing of PCR products showed that 12 (4 A1 and 8 A2) loci have more than one copy, and they were excluded from further analysis. Sequences of 61 loci were identical between the A1 and A2 strains, and four loci demonstrated low total divergence (0.24–0.61%) between the two mating types (otintseva and D. Filatov, unpublished results). Thus, these loci might be located in the recombining part of the mating-type-specific chromosomes. Ten of 75 loci that amplified in both mating types demonstrated multiple polymorphisms fixed between the mating types rather than between the locations. Given that the strains that we used in the analysis originated from two geographically distant locations, it is highly unlikely that multiple polymorphisms distinguishing the A1 and A2 sequences arose purely by chance; thus, these loci are probably located in the nonrecombining mating-type-specific region of the M. violaceum A1 and A2 chromosomes.

TABLE 1

Loci from mating-type-specific chromosomes of M. violaceum used for PCR analysis and genetic map construction

		With nonzero A1/A2 divergenceb
Loci	Mating type specific	<1%	>1%	With zero A1/A2 divergenceb	Total
A1a	5	2 (1)	3 (3)	35 (3)	45 (7)
A2a	6	2 (0)	7 (7)	26 (3)	41 (10)
Subtotal		4 (1)	10 (10)
Total	11	14 (11)		61 (6)	86 (17)

Open in a separate window^aA1, loci originated from the A1 sex chromosome; A2, loci originated from the A2 sex chromosome.^bThe number of loci used for genetic map construction is in parentheses.To confirm the mating-type-specific or pseudoautosomal locations of the loci with and without A1/A2 divergence, we conducted genetic mapping in a family of 99 individuals, 50 of which were of mating type A1 and 49 of mating type A2. The family was generated by a cross between A1 and A2 M. violaceum strains from S. latifolia accessions Sl405 (Sweden) and Sl127 (France), respectively. The choice of strains from geographically distant locations was motivated by the hope of maximizing the number of DNA sequence differences between them that can be used as molecular genetic markers in segregation analysis. We inoculated S. latifolia seedlings with sporidial cultures of both mating types. For inoculation, petri dishes with 12-day-old seedlings of S. latifolia were flooded with 2.5 ml of inoculum suspension. Inoculum suspension consisted of equal volumes of the A1 and A2 sporidial cultures that were mixed and conjugated overnight at 14° under rotation (Biere and Honders 1996; Van Putten et al. 2003). Seedlings were potted 3 days after inoculation. Two months later, teliospores were collected from the flowers of the infected plant and grown in petri dishes on 3.6% potato dextrose agar medium. Haploid sporidia formed after meiosis were isolated and grown as separate cultures for DNA extraction. The mating types of single sporidia cultures were identified as described above. The loci analyzed in the segregation analysis were sequenced in the two parental haploid strains and in 99 (50 A1 and 49 A2) haploid strains that were generated in the cross. Single nucleotide differences between the parental strains were used as molecular genetic markers for segregation analysis in the progeny. The genetic map was constructed using MAPMAKER/EXP v3.0 (Lincoln et al. 1992) and MapDisto v1.7 (http://mapdisto.free.fr/).The resulting genetic map is shown in Figure 2. As expected, no recombination was observed between the 10 loci with diverged A1- and A2-linked copies. In addition, one marker with no A1/A2 divergence, A2-397, was also completely linked to the loci with significant A1/A2 divergence. This locus either may be very tightly linked to the nonrecombining mating-type-specific region or may have been added to that region more recently than the loci that had already accumulated some divergence between the alleles in the two mating types. The mating-type-specific pheromone receptor locus (Devier et al. 2009) and 11 mating-type-specific loci are also located in this nonrecombining region (Figure 2). Interestingly, the cluster of nonrecombining markers is flanked on both sides with markers that recombine in meiosis, demonstrating that there are pseudoautosomal regions on both ends of the mating-type-specific chromosomes.Open in a separate windowFigure 2.—Genetic map of the mating-type-determining chromosome in M. violaceum. Genetic distance (in centimorgans) and the relative positions of the markers are shown to the left and the right of the chromosome, respectively. The position of the nonrecombining region corresponds to the cluster of linked markers shown on the right of the figure. Total A1/A2 divergence is shown in parentheses. Eleven mating-type-specific markers (for which sequences are available from only one mating type), located in the nonrecombining mating-type-specific region, are not shown.Our results demonstrate that although the loci reported by Hood et al. (2004) were isolated from the A1 and A2 chromosomes, most of these loci are not located in the nonrecombining mating-type-specific regions. In fact, the nonrecombining region might be relatively small: of 86 tested fragments, only 21 appeared to be either mating type specific or linked to the mating-type locus. Assuming that these loci represent a random set of DNA fragments isolated from the A1 and A2 chromosomes, it is possible to estimate the size of the nonrecombining region using the binomial distribution: the nonrecombining region is expected to be 24.4% (95% CI: 16.7–33.6%) of the chromosome length. As the sizes of the A1 and A2 chromosomes are ∼3.4 and 4.2 Mb long (Hood 2002; Hood et al. 2004), the nonrecombining region might be ∼1 Mb long.Interestingly, total A1/A2 divergence for the 11 loci with A1- and A2-linked copies mapped to the nonrecombining region varied from 0% to 8.6% (Figure 2). In addition, 11 loci amplified from only one mating type. These genes could represent degenerated genes, some of which degenerated in A1 strains, and some in A2 strains. Alternatively, they might be highly diverged genes, such that the PCR primers amplify only one allele, and not the other. Variation in divergence may be the result of the stepwise cessation of recombination between the A1 and A2 chromosomes in M. violaceum, resembling the evolutionary strata reported for human, chicken, and white campion sex chromosomes (Lahn and Page 1999; Handley et al. 2004; Bergero et al. 2007). However, only the differences between the most and the least diverged loci are statistically significant (Devier et al. 2009), the M. violaceum mating-type region has at least three strata: one oldest stratum, including the pheromone receptor locus; a younger stratum with ∼5–9% A1/A2 divergence; and the youngest stratum with 1–4% divergence between the two mating types. There may also be an additional very recently evolved stratum containing the locus named A2-397, which is also present in all A1 strains tested, with no fixed differences between the A1 and A2 strains (No. of sites analyzedWithin A1

---

Within A2

---

Fixed differences between A1 and A2A1/A2 divergence (%)Loci^aS^b totalSπ (%)^cSπ (%)^cA1/A2 divergence <1%A1-23645630020.4410.44A1-0456544000040.61A2-568413220.4820.4800.24A2-411480210.210010.31A1/A2 divergence >1%A1-2176679000091.35A1-12856990010.1881.49A1-199618130010.16122.02A2-4223449000092.62A2-516470140000142.98A2-404508200030.59173.64A2-4355062220.3920.39183.95A2-4734572310.2210.22214.81A2-4573031710.3300165.54A2-5755034750.9930.59398.55Open in a separate window^aA1, loci originated from the A1 sex chromosome; A2, loci originated from the A2 sex chromosome.^bS, number of polymorphic sites.^cπ (%), average number of differences per 100 nucleotides.

TABLE 3

P-values for the 2 × 2 G-tests for significance of differences in A1/A2 divergence between the loci in the nonrecombining region

Spontaneous Quinolone Resistance in the Zoonotic Serovar of Vibrio vulnificus

This work demonstrates that Vibrio vulnificus biotype 2, serovar E, an eel pathogen able to infect humans, can become resistant to quinolone by specific mutations in gyrA (substitution of isoleucine for serine at position 83) and to some fluoroquinolones by additional mutations in parC (substitution of lysine for serine at position 85). Thus, to avoid the selection of resistant strains that are potentially pathogenic for humans, antibiotics other than quinolones must be used to treat vibriosis on farms.Vibrio vulnificus is an aquatic bacterium from warm and tropical ecosystems that causes vibriosis in humans and fish (http://www.cdc.gov/nczved/dfbmd/disease_listing/vibriov_gi.html) (33). The species is heterogeneous and has been subdivided into three biotypes and more than eight serovars (6, 15, 33; our unpublished results). While biotypes 1 and 3 are innocuous for fish, biotype 2 can infect nonimmune fish, mainly eels, by colonizing the gills, invading the bloodstream, and causing death by septicemia (23). The disease is rapidly transmitted through water and can result in significant economic losses to fish farmers. Surviving eels are immune to the disease and can act as carriers, transmitting vibriosis between farms. Interestingly, biotype 2 isolates belonging to serovar E have been isolated from human infections, suggesting that serovar E is zoonotic (2). This serovar is also the most virulent for fish and has been responsible for the closure of several farms due to massive losses of fish. A vaccine, named Vulnivaccine, has been developed from serovar E isolates and has been successfully tested in the field (14). Although the vaccine provides fish with long-term protection from vibriosis, at present its use is restricted to Spain. For this reason, in many fish farms around the world, vibriosis is treated with antibiotics, which are usually added to the food or water.Quinolones are considered the most effective antibiotics against human and fish vibriosis (19, 21, 31). These antibiotics can persist for a long time in the environment (20), which could favor the emergence of resistant strains under selective pressure. In fact, spontaneous resistances to quinolones by chromosomal mutations have been described for some gram-negative bacteria (10, 11, 17, 24, 25, 26). Therefore, improper antibiotic treatment of eel vibriosis or inadequate residue elimination at farms could favor the emergence of human-pathogenic serovar E strains resistant to quinolones by spontaneous mutations. Thus, the main objective of the present work was to find out if the zoonotic serovar of biotype 2 can become quinolone resistant under selective pressure and determine the molecular basis of this resistance.Very few reports on resistance to antibiotics in V. vulnificus have been published; most of them have been performed with biotype 1 isolates. For this reason, the first task of this study was to determine the antibiotic resistance patterns in a wide collection of V. vulnificus strains belonging to the three biotypes that had been isolated worldwide from different sources (see Table S1 in the supplemental material). Isolates were screened for antimicrobial susceptibility to the antibiotics listed in Table S1 in the supplemental material by the agar diffusion disk procedure of Bauer et al. (5), according to the standard guideline (9). The resistance pattern found for each isolate is shown in Table S1 in the supplemental material. Less than 14% of isolates were sensitive to all the antibiotics tested, and more than 65% were resistant to more than one antibiotic, irrespective of their biotypes or serovars. The most frequent resistances were to ampicillin-sulbactam (SAM; 65.6% of the strains) and nitrofurantoin (F; 60.8% of the strains), and the least frequent were to tetracycline (12%) and oxytetracycline (8%). In addition, 15% of the strains were resistant to nalidixic acid (NAL) and oxolinic acid (OA), and 75% of these strains came from fish farms (see Table S1 in the supplemental material). Thus, high percentages of strains of the three biotypes were shown to be resistant to one or more antibiotics, with percentages similar to those found in nonbiotyped environmental V. vulnificus isolates from Asia and North America (4, 27, 34). In those studies, resistance to antibiotics could not be related to human contamination. However, the percentage of quinolone-resistant strains found in our study is higher than that reported in other ones, probably due to the inclusion of fish farm isolates, where the majority of quinolone-resistant strains were concentrated. This fact suggests that quinolone resistance could be related to human contamination due to the improper use of these drugs in therapy against fish diseases, as has been previously suggested (18, 20). Although no specific resistance pattern was associated with particular biotypes or serovars, we found certain differences in resistance distribution, as shown in Table ​Table1.1. In this respect, biotype 3 displayed the narrowest spectrum of resistances and biotype 1 the widest. The latter biotype encompassed the highest number of strains with multiresistance (see Table S1 in the supplemental material). Within biotype 2, there were differences among serovars, with quinolone resistance being restricted to the zoonotic serovar (Table ​(Table11).

TABLE 1.

Percentage of resistant strains distributed by biotypes and serovars

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