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Jochen K. Lennerz Jonathan B. Hurov Lynn S. White Katherine T. Lewandowski Julie L. Prior G. James Planer Robert W. Gereau IV David Piwnica-Worms Robert E. Schmidt Helen Piwnica-Worms 《Molecular and cellular biology》2010,30(21):5043-5056
Par-1 is an evolutionarily conserved protein kinase required for polarity in worms, flies, frogs, and mammals. The mammalian Par-1 family consists of four members. Knockout studies of mice implicate Par-1b/MARK2/EMK in regulating fertility, immune homeostasis, learning, and memory as well as adiposity, insulin hypersensitivity, and glucose metabolism. Here, we report phenotypes of mice null for a second family member (Par-1a/MARK3/C-TAK1) that exhibit increased energy expenditure, reduced adiposity with unaltered glucose handling, and normal insulin sensitivity. Knockout mice were protected against high-fat diet-induced obesity and displayed attenuated weight gain, complete resistance to hepatic steatosis, and improved glucose handling with decreased insulin secretion. Overnight starvation led to complete hepatic glycogen depletion, associated hypoketotic hypoglycemia, increased hepatocellular autophagy, and increased glycogen synthase levels in Par-1a−/− but not in control or Par-1b−/− mice. The intercrossing of Par-1a−/− with Par-1b−/− mice revealed that at least one of the four alleles is necessary for embryonic survival. The severity of phenotypes followed a rank order, whereby the loss of one Par-1b allele in Par-1a−/− mice conveyed milder phenotypes than the loss of one Par-1a allele in Par-1b−/− mice. Thus, although Par-1a and Par-1b can compensate for one another during embryogenesis, their individual disruption gives rise to distinct metabolic phenotypes in adult mice.Cellular polarity is a fundamental principle in biology (6, 36, 62). The prototypical protein kinase originally identified as a regulator of polarity was termed partitioning defective (Par-1) due to early embryonic defects in Caenorhabditis elegans (52). Subsequent studies revealed that Par-1 is required for cellular polarity in worms, flies, frogs, and mammals (4, 17, 58, 63, 65, 71, 89). An integral role for Par-1 kinases in multiple signaling pathways has also been established, and although not formally addressed, multifunctionality for individual Par-1 family members is implied in reviews of the list of recognized upstream regulators and downstream substrates (Table (Table1).1). Interestingly, for many Par-1 substrates the phosphorylated residues generate 14-3-3 binding sites (25, 28, 37, 50, 59, 61, 68, 69, 78, 95, 101, 103). 14-3-3 binding in turn modulates both nuclear/cytoplasmic as well as cytoplasmic/membrane shuttling of target proteins, thus allowing Par-1 activity to establish intracellular spatial organization (15, 101). The phosphorylation of Par-1 itself promotes 14-3-3 binding, thereby regulating its subcellular localization (37, 59, 101).
Open in a separate windowaLKB1 also is known as Par-4; MARKK also is known as Ste20-like; (−), inhibitory/negative regulation has been shown; GPCR, G protein-coupled receptors. MARKK is highly homologous to TAO-1 (thousand-and-one amino acid kinase) (46).The mammalian Par-1 family contains four members (Table (Table2).2). Physiological functions of the Par-1b kinase have been studied using targeted gene knockout approaches in mice (9, 44). Two independently derived mouse lines null for Par-1b have implicated this protein kinase in diverse physiological processes, including fertility (9), immune system homeostasis (44), learning and memory (86), the positioning of nuclei in pancreatic beta cells (35, 38), and growth and metabolism (43).
TABLE 1.
Multifunctionality of Par-1 polarity kinase pathwaysaRegulator or substrate | Function | Reference(s) |
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Regulators (upstream function) | ||
LKB1 | Wnt signaling, Peutz-Jeghers syndrome, insulin signal transduction, pattern formation | 2, 63, 93 |
TAO1 | MEK3/p38 stress-responsive mitogen-activated protein kinase (MAPK) pathway | 46 |
MARKK | Nerve growth factor signaling in neurite development and differentiation | 98 |
aPKC | Ca2+/DAG-independent signal transduction, cell polarity, glucose metabolism | 14, 37, 40, 45, 59, 75, 95 |
nPKC/PKD | DAG-dependent, Ca2+-independent signal transduction (GPCR) | 101 |
PAR-3/PAR-6/aPKC | (−); regulates Par-1, assembly of microtubules, axon-dendrite specification | 19 |
GSK3β | (−); tau phosphorylation, Alzheimer''s dementia, energy metabolism, body patterning | 54, 97 |
Pim-1 oncogene | (−); G2/M checkpoint, effector of cytokine signaling and Jak/STAT(3/5) | 5 |
CaMKI | (−); Ca2+-dependent signal transduction, neuronal differentiation | 99 |
Substrates (downstream function) | ||
Cdc25C | Regulation of mitotic entry by activation of the cdc2-cyclin B complex | 25, 72, 78, 103 |
Class II HDAC | Control of gene expression and master regulator of subcellular trafficking | 28, 50 |
CRTC2/TORC2 | Gluconeogenesis regulator via LKB1/AMPK/TORC2 signaling, PPARγ1a coactivator | 49 |
Dlg/PSD-95 | Synaptogenesis and neuromuscular junction, tumor suppressor (102) | 104 |
Disheveled | Wnt signaling, translocation of Dsh from cytoplasmic vesicles to cortex | 73, 94 |
KSR1 | Regulation of the Ras-MAPK pathway | 68, 69 |
MAP2/4/TAU | Dynamic instability (67, 83) of microtubules, Alzheimer''s dementia (30) | 11, 31-33, 47, 70, 96 |
Mib/Notch | Mind bomb (Mib degradation and repression of Notch signaling results in neurogenesis) | 57, 74, 81 |
Par3/OSKAR/Lgl | Cytoplasmic protein segregation, cell polarity, and asymmetric cell division | 7, 10 |
Pkp2 | Desmosome assembly and organization; nuclear shuttling | 68, 69 |
PTPH1 | Linkage between Ser/Thr and Tyr phosphorylation-dependent signaling | 103 |
Rab11-FIP | Regulation of endocytosis (23), trafficking of E-cadherin (64) | 34 |
TABLE 2.
Terminology and localization of mammalian Par-1 family membersOpen in a separate windowaPar should not to be confused with protease-activated receptor 1 (PAR1 [29]); C-TAK1, Cdc twenty-five C-associated kinase 1; MARK, microtubule affinity regulating kinase; MARKL, MAP/microtubule affinity-regulating kinase-like 1.bBasolateral to a lesser degree than Par-1b (37).cHuman KP78 is asymmetrically localized to the apical surface of epithelial cells (76).dVariant that does not show asymmetric localization in epithelial cells when overexpressed (95).Beyond Par-1b, most information regarding the cell biological functions of the Par-1 kinases comes from studies of Par-1a. Specifically, Par-1a has been implicated in pancreatic (76) and hepatocarcinogenesis (51), as well as colorectal tumors (77), hippocampal function (100), CagA (Helicobacter pylori)-associated epithelial cell polarity disruption (82), and Peutz-Jeghers syndrome (48), although the latter association has been excluded recently (27). As a first step toward determining unique and redundant functions of Par-1 family members, mice disrupted for a second member of the family (Par-1a/MARK3/C-TAK1) were generated. We report that Par-1a−/− mice are viable and develop normally, and adult mice are hypermetabolic, have decreased white and brown adipose tissue mass, and unaltered glucose/insulin handling. However, when challenged by a high-fat diet (HFD), Par-1a−/− mice exhibit resistance to hepatic steatosis, resistance to glucose intolerance, and the delayed onset of obesity relative to that of control littermates. Strikingly, overnight starvation results in a complete depletion of glycogen and lipid stores along with an increase in autophagic vacuoles in the liver of Par-1a−/− but not Par-1b−/− mice. Correspondingly, Par-1a−/− mice develop hypoketotic hypoglycemia. These findings reveal unique metabolic functions of two Par-1 family members. 相似文献3.
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Patti J. Miller Claudio L. Afonso Erica Spackman Melissa A. Scott Janice C. Pedersen Dennis A. Senne Justin D. Brown Chad M. Fuller Marcela M. Uhart William B. Karesh Ian H. Brown Dennis J. Alexander David E. Swayne 《Journal of virology》2010,84(21):11496-11504
The biological, serological, and genomic characterization of a paramyxovirus recently isolated from rockhopper penguins (Eudyptes chrysocome) suggested that this virus represented a new avian paramyxovirus (APMV) group, APMV10. This penguin virus resembled other APMVs by electron microscopy; however, its viral hemagglutination (HA) activity was not inhibited by antisera against any of the nine defined APMV serotypes. In addition, antiserum generated against this penguin virus did not inhibit the HA of representative viruses of the other APMV serotypes. Sequence data produced using random priming methods revealed a genomic structure typical of APMV. Phylogenetic evaluation of coding regions revealed that amino acid sequences of all six proteins were most closely related to APMV2 and APMV8. The calculation of evolutionary distances among proteins and distances at the nucleotide level confirmed that APMV2, APMV8, and the penguin virus all were sufficiently divergent from each other to be considered different serotypes. We propose that this isolate, named APMV10/penguin/Falkland Islands/324/2007, be the prototype virus for APMV10. Because of the known problems associated with serology, such as antiserum cross-reactivity and one-way immunogenicity, in addition to the reliance on the immune response to a single protein, the hemagglutinin-neuraminidase, as the sole base for viral classification, we suggest the need for new classification guidelines that incorporate genome sequence comparisons.Viruses from the Paramyxoviridae family have caused disease in humans and animals for centuries. Over the last 40 years, many paramyxoviruses isolated from animals and people have been newly described (16, 17, 22, 29, 31, 32, 36, 42, 44, 46, 49, 58, 59, 62-64). Viruses from this family are pleomorphic, enveloped, single-stranded, nonsegmented, negative-sense RNA viruses that demonstrate serological cross-reactivity with other paramyxoviruses related to them (30, 46). The subfamily Paramyxovirinae is divided into five genera: Respirovirus, Morbillivirus, Rubulavirus, Henipavirus, and Avulavirus (30). The Avulavirus genus contains nine distinct avian paramyxovirus (APMV) serotypes (Table (Table1),1), and information on the discovery of each has been reported elsewhere (4, 6, 7, 9, 12, 34, 41, 50, 51, 60, 68).
Open in a separate windowaRequires the addition of an exogenous protease.bProtease requirement depends on the isolate examined.cPutative.Six of these serotypes were classified in the latter half of the 1970s, when the most reliable assay available to classify paramyxoviruses was the hemagglutination inhibition (HI) assay (61). However, there are multiple problems associated with the use of serology, including the inability to classify some APMVs by comparing them to the sera of the nine defined APMVs alone (2, 8). In addition, one-way antigenicity and cross-reactivity between different serotypes have been documented for many years (4, 5, 14, 25, 29, 33, 34, 41, 51, 52, 60). The ability of APMVs, like other viruses, to show antigenic drift as it evolves over time (37, 43, 54) and the wide use and availability of precise molecular methods, such as PCR and genome sequencing, demonstrate the need for a more practical classification system.The genetic diversity of APMVs is still largely unexplored, as hundreds of avian species have never been surveyed for the presence of viruses that do not cause significant signs of disease or are not economically important. The emergence of H5N1 highly pathogenic avian influenza (HPAI) virus as the cause of the largest outbreak of a virulent virus in poultry in the past 100 years has spurred the development of surveillance programs to better understand the ecology of avian influenza (AI) viruses in aquatic birds around the globe, and in some instances it has provided opportunities for observing other viruses in wild bird populations (15, 53). In 2007, as part of a seabird health surveillance program in the Falkland Islands (Islas Malvinas), oral and cloacal swabs and serum were collected from rockhopper penguins (Eudyptes chrysocome) and environmental/fecal swab pools were collected from other seabirds.While AI virus has not yet been isolated from penguins in the sub-Antarctic and Antarctic areas, there have been two reports of serum antibodies positive to H7 and H10 from the Adélie species (11, 40). Rare isolations of APMV1, both virulent (45) and of low virulence (8), have been reported from Antarctic penguins. Sera positive for APMV1 and AMPV2 have also been reported (21, 24, 38, 40, 53). Since 1981, paramyxoviruses have been isolated from king penguins (Aptenodytes patagonicus), royal penguins (Eudyptes schlegeli), and Adélie penguins (Pygoscelis adeliae) from Antarctica and little blue penguins (Eudyptula minor) from Australia that cannot be identified as belonging to APMV1 to -9 and have not yet been classified (8, 11, 38-40). The morphology, biological and genomic characteristics, and antigenic relatedness of an APMV recently isolated from multiple penguin colonies on the Falkland Islands are reported here. Evidence that the virus belongs to a new serotype (APMV10) and a demonstration of the advantages of a whole genome system of analysis based on random sequencing followed by comparison of genetic distances are presented. Only after all APMVs are reported and classified will epidemiological information be known as to how the viruses are moving and spreading as the birds travel and interact with other avian species. 相似文献
TABLE 1.
Characteristics of prototype viruses APMV1 to APMV9 and the penguin virusStrain | Host | Disease | Distribution | Fusion cleavagec | GI accession no. |
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APMV1/Newcastle disease virus | >250 species | High mortality | Worldwide | GRRQKRF | 45511218 |
Inapparent | Worldwide | GGRQGRLa | 11545722 | ||
APMV2/Chicken/CA/Yucaipa/1956 | Turkey, chickens, psittacines, rails, passerines | Decrease in egg production and respiratory disease | Worldwide | DKPASRF | 169144527 |
APMV3/Turkey/WI/1968 | Turkey | Mild respiratory disease and moderate egg decrease | Worldwide | PRPSGRLa | 209484147 |
APMV3/Parakeet/Netherlands/449/1975 | Psittacines, passerines, flamingos | Neurological, enteric, and respiratory disease | Worldwide | ARPRGRLa | 171472314 |
APMV4/Duck/Hong Kong/D3/1975 | Duck, geese, chickens | None known | Worldwide | VDIQPRF | 210076708 |
APMV5/Budgerigar/Japan/Kunitachi/1974 | Budgerigars, lorikeets | High mortality, enteric disease | Japan, United Kingdom, Australia | GKRKKRFa | 290563909 |
APMV6/Duck/Hong Kong/199/1977 | Ducks, geese, turkeys | Mild respiratory disease and increased mortality in turkeys | Worldwide | PAPEPRLb | 15081567 |
APMV7/Dove/TN/4/1975 | Pigeons, doves, turkeys | Mild respiratory disease in turkeys | United States, England, Japan | TLPSSRF | 224979458 |
APMV8/Goose/DE/1053/1976 | Ducks, geese | None known | United States, Japan | TYPQTRLa | 226343050 |
APMV9/Duck/NY/22/1978 | Ducks | None known | Worldwide | RIREGRIa | 217068693 |
APMV10/Penguin/Falkland Islands/324/2007 | Rockhopper penguins | None Known | Falkland Islands | DKPSQRIa | 300432141 |
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Andrew D. Morgan R. Craig MacLean Kristina L. Hillesland Gregory J. Velicer 《Applied and environmental microbiology》2010,76(20):6920-6927
Predator-prey relationships among prokaryotes have received little attention but are likely to be important determinants of the composition, structure, and dynamics of microbial communities. Many species of the soil-dwelling myxobacteria are predators of other microbes, but their predation range is poorly characterized. To better understand the predatory capabilities of myxobacteria in nature, we analyzed the predation performance of numerous Myxococcus isolates across 12 diverse species of bacteria. All predator isolates could utilize most potential prey species to effectively fuel colony expansion, although one species hindered predator swarming relative to a control treatment with no growth substrate. Predator strains varied significantly in their relative performance across prey types, but most variation in predatory performance was determined by prey type, with Gram-negative prey species supporting more Myxococcus growth than Gram-positive species. There was evidence for specialized predator performance in some predator-prey combinations. Such specialization may reduce resource competition among sympatric strains in natural habitats. The broad prey range of the Myxococcus genus coupled with its ubiquity in the soil suggests that myxobacteria are likely to have very important ecological and evolutionary effects on many species of soil prokaryotes.Predation plays a major role in shaping both the ecology and evolution of biological communities. The population and evolutionary dynamics of predators and their prey are often tightly coupled and can greatly influence the dynamics of other organisms as well (1). Predation has been invoked as a major cause of diversity in ecosystems (11, 12). For example, predators may mediate coexistence between superior and inferior competitors (2, 13), and differential trajectories of predator-prey coevolution can lead to divergence between separate populations (70).Predation has been investigated extensively in higher organisms but relatively little among prokaryotes. Predation between prokaryotes is one of the most ancient forms of predation (27), and it has been proposed that this process may have been the origin of eukaryotic cells (16). Prokaryotes are key players in primary biomass production (44) and global nutrient cycling (22), and predation of some prokaryotes by others is likely to significantly affect these processes. Most studies of predatory prokaryotes have focused on Bdellovibrionaceae species (e.g., see references 51, 55, and 67). These small deltaproteobacteria prey on other Gram-negative cells, using flagella to swim rapidly until they collide with a prey cell. After collision, the predator cells then enter the periplasmic space of the prey cell, consume the host cell from within, elongate, and divide into new cells that are released upon host cell lysis (41). Although often described as predatory, the Bdellovibrionaceae may also be considered to be parasitic, as they typically depend (apart from host-independent strains that have been observed [60]) on the infection and death of their host for their reproduction (47).In this study, we examined predation among the myxobacteria, which are also deltaproteobacteria but constitute a monophyletic clade divergent from the Bdellovibrionaceae (17). Myxobacteria are found in most terrestrial soils and in many aquatic environments as well (17, 53, 74). Many myxobacteria, including the model species Myxococcus xanthus, exhibit several complex social traits, including fruiting body formation and spore formation (14, 18, 34, 62, 71), cooperative swarming with two motility systems (64, 87), and group (or “wolf pack”) predation on both bacteria and fungi (4, 5, 8, 9, 15, 50). Using representatives of the genus Myxococcus, we tested for both intra- and interspecific variation in myxobacterial predatory performance across a broad range of prey types. Moreover, we examined whether prey vary substantially in the degree to which they support predatory growth by the myxobacteria and whether patterns of variation in predator performance are constant or variable across prey environments. The latter outcome may reflect adaptive specialization and help to maintain diversity in natural populations (57, 59).Although closely related to the Bdellovibrionaceae (both are deltaproteobacteria), myxobacteria employ a highly divergent mode of predation. Myxobacteria use gliding motility (64) to search the soil matrix for prey and produce a wide range of antibiotics and lytic compounds that kill and decompose prey cells and break down complex polymers, thereby releasing substrates for growth (66). Myxobacterial predation is cooperative both in its “searching” component (6, 31, 82; for details on cooperative swarming, see reference 64) and in its “handling” component (10, 29, 31, 32), in which secreted enzymes turn prey cells into consumable growth substrates (56, 83). There is evidence that M. xanthus employs chemotaxis-like genes in its attack on prey cells (5) and that predation is stimulated by close contact with prey cells (48).Recent studies have revealed great genetic and phenotypic diversity within natural populations of M. xanthus, on both global (79) and local (down to centimeter) scales (78). Phenotypic diversity includes variation in social compatibility (24, 81), the density and nutrient thresholds triggering development (33, 38), developmental timing (38), motility rates and patterns (80), and secondary metabolite production (40). Although natural populations are spatially structured and both genetic diversity and population differentiation decrease with spatial scale (79), substantial genetic diversity is present even among centimeter-scale isolates (78). No study has yet systematically investigated quantitative natural variation in myxobacterial predation phenotypes across a large number of predator genotypes.Given the previous discovery of large variation in all examined phenotypes, even among genetically extremely similar strains, we anticipated extensive predatory variation as well. Using a phylogenetically broad range of prey, we compared and contrasted the predatory performance of 16 natural M. xanthus isolates, sampled from global to local scales, as well as the commonly studied laboratory reference strain DK1622 and representatives of three additional Myxococcus species: M. flavescens (86), M. macrosporus (42), and M. virescens (63) (Table (Table1).1). In particular, we measured myxobacterial swarm expansion rates on prey lawns spread on buffered agar (31, 50) and on control plates with no nutrients or with prehydrolyzed growth substrate.
Open in a separate window 相似文献
TABLE 1.
List of myxobacteria used, with geographical originOrganism abbreviation used in text | Species | Strain | Geographic origin | Reference(s) |
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A9 | Myxococcus xanthus | A9 | Tübingen, Germany | 78 |
A23 | Myxococcus xanthus | A23 | Tübingen, Germany | 78 |
A30 | Myxococcus xanthus | A30 | Tübingen, Germany | 78 |
A41 | Myxococcus xanthus | A41 | Tübingen, Germany | 78 |
A46 | Myxococcus xanthus | A46 | Tübingen, Germany | 78 |
A47 | Myxococcus xanthus | A47 | Tübingen, Germany | 78 |
A75 | Myxococcus xanthus | A75 | Tübingen, Germany | 78 |
A85 | Myxococcus xanthus | A85 | Tübingen, Germany | 78 |
TV | Myxococcus xanthus | Tvärminne | Tvärminne, Finland | 79 |
PAK | Myxococcus xanthus | Paklenica | Paklenica, Croatia | 79 |
MAD | Myxococcus xanthus | Madeira 1 | Madeira, Portugal | 79 |
WAR | Myxococcus xanthus | Warwick 1 | Warwick, UK | 79 |
TOR | Myxococcus xanthus | Toronto 1 | Toronto, Ontario, Canada | 79 |
SUL2 | Myxococcus xanthus | Sulawesi 2 | Sulawesi, Indonesia | 79 |
KAL | Myxococcus xanthus | Kalalau | Kalalau, HI | 79 |
DAV | Myxococcus xanthus | Davis 1A | Davis, CA | 79 |
GJV1 | Myxococcus xanthus | GJV 1 | Unknown | 35, 72 |
MXFL1 | Myxococcus flavescens | Mx fl1 | Unknown | 65 |
MXV2 | Myxococcus virescens | Mx v2 | Unknown | 65 |
CCM8 | Myxococcus macrosporus | Cc m8 | Unknown | 65 |
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The rates of pilin antigenic variation (Av) of two strains of Neisseria meningitidis were determined using an unbiased DNA sequencing assay. Strain MC58 underwent pilin Av at a rate similar to that of N. gonorrhoeae strain MS11 but lower than that of N. gonorrhoeae strain FA1090. Pilin Av was undetectable in strain FAM18.Neisseria meningitidis is a Gram-negative diplococcus that colonizes the nasopharynx of approximately 5 to 10% of the population and is usually nonpathogenic but can occasionally enter the bloodstream to cause septicemia and can eventually spread to the meninges, causing meningitis (15). Approximately 500,000 cases of meningococcal meningitis occur every year, with nearly 10% resulting in fatality (2).Type IV pili (TFP) are long filamentous structures protruding from the bacterial surface and are required for adherence of N. meningitidis to host cells (7). As with the TFP of the closely related pathogen Neisseria gonorrhoeae, the pili are able to undergo antigenic variation (Av). In N. gonorrhoeae, pilin Av occurs as a result of recombination between one of the multiple silent pilS copies and the expressed pilin gene (pilE). The pilS copies share significant regions of homology with pilE yet lack a promoter or ribosome-binding site and the initial 5′ coding sequence. Pilin Av relies on RecA and the RecF-like recombination pathway to catalyze gene conversion, resulting in an altered pilE sequence, carrying part of the pilS donor, and the original unaltered pilS sequence (8, 9).While the frequency of pilin Av has been measured in N. gonorrhoeae (5, 10, 12), this process has never been quantified in N. meningitidis. Two sequenced strains were picked to measure pilin Av: serogroup B strain MC58 (sequence type [ST-32] complex), isolated from an invasive infection (14), and serogroup C strain FAM18 (ST-11 complex), which was isolated from a patient with septicemia (1). In both strains, the native recA gene was replaced with the very highly conserved N. gonorrhoeae recA6 construct, which allows regulation of expression with IPTG (isopropyl-β-d-thiogalactopyranoside) (17). recA6 strains are RecA+ when grown with IPTG but are RecA− when grown without IPTG (17). These phenotypes were confirmed by measuring the UV sensitivities and DNA transformation competence levels of both strains with or without IPTG, and both strains were shown to be piliated by transmission electron microscopy (data not shown). Bacteria were grown at 37°C with 5% CO2 on gonococcal medium base (GCB; Difco) plus Kellogg supplements I and II (11).The pilin Av sequencing assay was performed as described previously (5, 10, 12) with slight modifications. Briefly, FAM18 and MC58 were grown on solid GCB with 1 mM IPTG, allowing for the expression of RecA, for 22 h and 12.5 h, respectively, which was estimated to produce 20 generations. For FAM18, little or no pilin Av was expected since the G-quartet-forming sequence required for pilin Av is degenerate in this strain (3). Therefore, two random progenitor colonies were picked from IPTG-enriched medium and passaged on GCB without IPTG. Between 91 and 94 colonies were isolated from each FAM18 progenitor, and the sequence of the pilE gene was determined. For MC58, seven random progenitor colonies were picked and passaged on GCB without IPTG. Between 28 and 47 progeny colonies arising from each of the seven progenitors were isolated, and the pilE gene sequence was determined. In both MC58 and FAM18, the progeny colonies were passaged on GCB two times to ensure colony clonality. A single colony from each sample was isolated, and the pilE gene was PCR amplified as described previously (13).The primers used for amplification of MC58 pilE were McPilRBS (5′-GCATTTCCTTTCCAATTAGGAG) and MC58SP3A (5′-TTCCGTACGGATAGCTTCGTC). The primers used for amplification of FAM18 pilE were FAMFOR-2 (5′-ATTACGGGTTTACGTTTGCGG) and FAMREV-2 (5′-ACGCACCTACGCCTCACCCTAC). The DNA sequence was determined for each sample (SeqWright, Houston, TX, and the Genomics Core at Northwestern University) and analyzed (MacVector; Symantec Corp.). Colonies that showed pilE sequence changes were reanalyzed to confirm the Av event.The pilin Av frequency was determined for the progeny of each progenitor by dividing the total number of detected pilin Av events by the number of progeny of each set, resulting in two values for FAM18 and seven values for MC58 (Table (Table1).1). The pilin Av rate was determined by dividing the pilin Av frequency by the number of generations for each sample grown in the presence of IPTG, as determined by a colony assay at the time of harvest. After growth for the same time period, the total numbers of generations for MC58 and FAM18 grown under RecA induction were approximately 19 and 23, respectively.
Open in a separate windowaValues in parentheses indicate the detection limit of pilin Av in this assay.MC58 possesses eight pilS copies in a single locus directly upstream of pilE, designated pilS1 to pilS8 (GenBank accession numbers NMB0019 to NMB0026, respectively) (16). FAM18 possesses two pilS sequences in a single locus, designated pilS1 and pilS2 (GenBank accession numbers NMC0002 and NMC0003, respectively) (1). All MC58 pilin Av events were confirmed by comparing the sequence of the altered pilE to the eight pilS sequences, and each was matched to a pilS sequence donor.As predicted, no pilin Av was detected in FAM18 within the 185 progeny colonies analyzed (Table (Table1).1). Therefore, the pilin Av frequency is less than the detection limit of 5.4 × 10−3 events/CFU and the rate is less than the detection limit of 2.3 × 10−4 events/CFU/generation. This result is consistent with observations from clinical ST-11 isolates which have a conserved pilE sequence (4).In contrast, pilin Av in MC58 was detected in five of the seven sets, with the highest frequency and rate belonging to set A, which had a frequency of 0.2 events/CFU and a rate of 1 × 10−2 events/CFU/generation (Table (Table1).1). The median frequency of pilin Av in MC58 was 0.03 events/CFU, and the median rate was 1.6 × 10−3 events/CFU/generation. Using the Wilcoxon rank sum test, the rates of pilin Av of MC58 were statistically reduced relative to the rates previously reported for N. gonorrhoeae strain FA1090 grown for 20 generations (10), with a P value of <0.05. In contrast, the rates of pilin Av of MC58 and gonococcal strain MS11, which was shown to have a reduced level of pilin Av relative to that of strain FA1090 from the same study (10), were not statistically different from each other.The pilS donor was determined for all 13 MC58 samples with a variant pilE gene. Five pilin Av events were the result of recombination with pilS3. One pilin Av event was the result of recombination with pilS1. One event was the result of recombination with pilS8. Five events could have been the result of recombination with pilS1, pilS2, or pilS3 in areas of these pilS copies that are identical. One event was the result of recombination with either pilS5 or pilS7. No recombination events with either pilS4 or pilS6 were detected. While these data suggest that there is a nonrandom distribution of donor pilS copies, which has been shown in N. gonorrhoeae (4, 9), further studies with more samples will have to be performed to verify this.These results definitively demonstrate that N. meningitidis strain MC58 undergoes pilin Av at a rate similar to that of N. gonorrhoeae strain MS11 yet reduced relative to that of N. gonorrhoeae strain FA1090. N. meningitidis strain FAM18, which lacks a well-defined G-4 quartet and encodes class II pilin (6, 18), undergoes pilin Av at a rate not detectable by the assay described here and is unlikely to undergo antigenic variation at all. These data clearly show that major differences in strain-to-strain pilin Av rates exist, an observation previously made for N. gonorrhoeae (10). The greatly reduced level of pilin Av in FAM18 suggests that this strain is not dependent upon pilin Av for its survival and spread from host to host and that other class II pilin gene-expressing strains (4) must have a relationship with the host immune system different from that of class I pilin-expressing strains. Whether there are differences in transmission, pilus function, or interactions with the host remains to be determined. 相似文献
TABLE 1.
Frequencies and rates of pilin Av in MC58 and FAM18aStrain and progenitor | No. of progeny analyzed | No. of pilin Av events detected | Pilin Av frequency (events/CFU) | Pilin Av rate (events/CFU/ generation) |
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MC58 | ||||
A | 30 | 6 | 0.2 | 1.0 × 10−2 |
B | 45 | 0 | 0 | 0 |
C | 31 | 2 | 0.06 | 3.1 × 10−3 |
D | 47 | 1 | 0.02 | 1.0 × 10−3 |
E | 45 | 0 | 0 | 0 |
F | 31 | 3 | 0.1 | 5.2 × 10−3 |
G | 31 | 1 | 0.03 | 1.6 × 10−3 |
FAM18 | ||||
A | 94 | 0 | 0 (<0.01) | 0 (<4.6 × 10−4) |
B | 91 | 0 | 0 (<0.01) | 0 (<4.7 × 10−4) |
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Pablo I. Nikel Andrea M. Giordano Alejandra de Almeida Manuel S. Godoy M. Julia Pettinari 《Applied and environmental microbiology》2010,76(22):7400-7406
The effect of eliminating d-lactate synthesis in poly(3-hydroxybutyrate) (PHB)-accumulating recombinant Escherichia coli (K24K) was analyzed using glycerol as a substrate. K24KL, an ldhA derivative, produced more biomass and had altered carbon partitioning among the metabolic products, probably due to the increased availability of carbon precursors and reducing power. This resulted in a significant increase of PHB and ethanol synthesis and a decrease in acetate production. Cofactor measurements revealed that cultures of K24K and K24KL had a high intracellular NADPH content and that the NADPH/NADP+ ratio was higher than the NADH/NAD+ ratio. The ldhA mutation affected cofactor distribution, resulting in a more reduced intracellular state, mainly due to a further increase in NADPH/NADP+. In 60-h fed-batch cultures, K24KL reached 41.9 g·liter−1 biomass and accumulated PHB up to 63% ± 1% (wt/wt), with a PHB yield on glycerol of 0.41 ± 0.03 g·g−1, the highest reported using this substrate.Poly(3-hydroxybutyrate) (PHB) is the best-known and most common polyhydroxyalkanoate (PHA). PHAs are polymers with thermoplastic properties that are totally biodegradable by microorganisms present in most environments and that can be produced from different renewable carbon sources (38). Accumulated as intracellular granules by many bacteria under unfavorable conditions (1, 21), PHAs are carbon and energy reserves and also act as electron sinks, enhancing the fitness and stress resistance of bacteria and contributing to redox balance (12, 30). Escherichia coli offers a well-defined physiological environment for the construction and manipulation of various metabolic pathways to produce different bioproducts, such as PHB, from cost-effective carbon sources.In recent years, a significant increase in the production of biodiesel has caused a sharp fall in the cost of glycerol, the main by-product of biodiesel synthesis. As a result, glycerol has become a very attractive substrate for bacterial fermentations (10), specially for reduced products, such as PHB (36). The E. coli strain used in this work, K24K, carries phaBAC, the structural genes responsible for PHB synthesis, from Azotobacter sp. strain FA8 (23) (Table (Table1).1). The pha genes in K24K are expressed from a chimeric promoter and consequently are not subject to the genetic regulatory systems present in natural PHA producers. Because of this, it can be assumed that regulation of PHA synthesis in the recombinants is restricted by enzyme activity levels, modulated principally by substrate availability. In most natural producers, and also in PHB-producing E. coli recombinants, PHB is synthesized through the condensation of two molecules of acetyl-coenzyme A (acetyl-CoA), catalyzed by an acetoacetyl-CoA transferase or 3-ketothiolase, resulting in acetoacetyl-CoA. This compound is subsequently reduced by an NAD(P)H-dependent acetoacetyl-CoA reductase to R-(−)-3-hydroxybutyryl-CoA, which is then polymerized by a specific PHA synthase (34).
Open in a separate windowaStrain obtained through the E. coli Genetic Stock Center, Yale University, New Haven, CT.bFor oligonucleotides, the ATG codon of ldhA is underlined and the sequences with homology to FRT-kan-FRT in the template plasmid pKD4 (11) are shown in boldface.Cells growing on glycerol are in a more reduced intracellular state than cells grown on glucose under similar conditions of oxygen availability. This has a significant effect on the intracellular redox state, which causes the cells to direct carbon flow toward the synthesis of more-reduced products when glycerol is used than when glucose is used in order to achieve redox balance (31). When metabolic product distribution was analyzed in bioreactor cultures of K24K using glucose or glycerol as the substrate, product distributions with the two substrates were found to be different, as glycerol-grown cultures produced smaller amounts of acetate, lactate, and formate and more ethanol than those grown on glucose. However, PHB production from glycerol was lower than that from glucose, except under conditions of low oxygen availability (13).Manipulations to enhance the synthesis of a metabolic product include several approaches to increase the availability of the substrates needed for its formation or to inhibit competing pathways. The effect of eliminating competing pathways on PHB production from glucose has been investigated through the inactivation of different genes, such as those encoding enzymes participating in the synthesis of acetate (ackA, pta, and poxB) or d-lactate (ldhA). A pta mutant, which produces very little acetate (6), and an frdA ldhA double mutant (40) had increased PHB accumulation from glucose. A recent report using an ackA pta poxB ldhA adhE mutant under microaerobic conditions attained similar results (17). The inactivation of ldhA has also been shown to have an important effect on the metabolic product distribution in recombinant E. coli with glycerol as the carbon source, promoting ethanol synthesis (28). In the present work we analyzed the effect of ldhA inactivation in strain K24K using glycerol as the carbon source, with special emphasis on changes in carbon distribution and in the intracellular redox state, determined through cofactor levels. 相似文献
TABLE 1.
E. coli strains, plasmids, and oligonucleotides used in this studyStrain, plasmid, or oligonucleotide | Relevant characteristicsb | Reference or source |
---|---|---|
E. coli strains | ||
K1060a | F−fadE62 lacI60 tyrT58(AS) fabB5 mel-1 | 29 |
K24 | Same as K1060, carrying pJP24; Apr | 23 |
K24K | Same as K1060, carrying pJP24K; Apr Kmr | 23 |
ALS786a | F− λ−rph-1 ΔldhA::kan; Kmr | 14 |
K24LT | Same as K1060 but ΔldhA::kan by K1060 × P1(ALS786), carrying pJP24; Apr Kmr | This work |
K24KL | Same as K1060 but ΔldhA by allelic replacement, carrying pJP24K; Kmr | This work |
TA3522a | F− λ− Δ(his-gnd)861 hisJo-701 | 2 |
TA3514a | Same as TA3522 but pta-200 | 19 |
TA3522L | Same as TA3522 but ΔldhA::kan by TA3522 × P1(ALS786); Kmr | This work |
TA3514L | Same as TA3514 but ΔldhA::kan by TA3514 × P1(ALS786); Kmr | This work |
Plasmids | ||
pQE32 | Expression vector, ColE1 ori; Apr | Qiagen GmbH, Hilden, Germany |
pJP24 | pQE32 derivative expressing a 4.3-kb BamHI-HindIII insert containing the phaBAC genes from Azotobacter sp. strain FA8 under the control of a T5 promoter/lac operator element; Apr | 23 |
pJP24K | pJP24 derivative; Apr Kmr | 23 |
pCP20 | Helper plasmid used for kan excision; Saccharomyces cerevisiae FLP λ cI857 λ PRrepA(Ts); Apr Cmr | 7 |
Oligonucleotides | ||
ΔldhA-F | 5′-TAT TTT TAG TAG CTT AAA TGT GAT TCA ACA TCA CTG GAG AAA GTC TTA TGG TGT AGG CTG GAG CTG CTT C-3′ | This work |
ΔldhA-R | 5′-CTC CCC TGG AAT GCA GGG GAG CGG CAA GAT TAA ACC AGT TCG TTC GGG CAC ATA TGA ATA TCC TCC TTA G-3′ | This work |
10.
11.
12.
13.
14.
Haruyuki Nakayama-Imaohji Hideki Hirakawa Minoru Ichimura Shin Wakimoto Satoru Kuhara Tetsuya Hayashi Tomomi Kuwahara 《Journal of bacteriology》2009,191(19):6003-6011
The human gut microbe Bacteroides fragilis can alter the expression of its surface molecules, such as capsular polysaccharides and SusC/SusD family outer membrane proteins, through reversible DNA inversions. We demonstrate here that DNA inversions at 12 invertible regions, including three gene clusters for SusC/SusD family proteins, were controlled by a single tyrosine site-specific recombinase (Tsr0667) encoded by BF0667 in B. fragilis strain YCH46. Genetic disruption of BF0667 diminished or attenuated shufflon-type DNA inversions at all three susC/susD genes clusters, as well as simple DNA inversions at nine other loci, most of which colocalized with susC/susD family genes. The inverted repeat sequences found within the Tsr0667-regulated invertible regions shared the consensus motif sequence AGTYYYN4GDACT. Tsr0667 specifically mediated the DNA inversions of 10 of the 12 regions, even under an Escherichia coli background when the invertible regions were exposed to BF0667 in E. coli cells. Thus, Tsr0667 is an additional globally acting DNA invertase in B. fragilis, which probably involves the selective expression of SusC/SusD family outer membrane proteins.The human gut harbors an abundant and diverse microbiota. Bacteroides is one of the most abundant genera of human gut microflora (10, 17, 20), and the biological activities of Bacteroides species are deeply integrated into human physiology through nutrient degradation, the production of short-chain fatty acids, or immunomodulatory molecules (11-14, 24). Recent genomic analyses of Bacteroides have revealed that the bacteria possess redundant abilities not only to bind and degrade otherwise indigestible dietary polysaccharides but also to produce vast arrays of capsular polysaccharide (5, 19, 38, 39). These functional redundancies have been established by the extensive duplication of various genes that encode molecules such as glycosylhydrolases, glycosyltransferases, and outer membrane proteins of the SusC/SusD family (starch utilization system) known to be involved in polysaccharide recognition and transport (7, 27, 28, 30). It has been assumed that these functional redundancies of Bacteroides contribute to the stability of the gut ecosystem (3, 21, 23, 32, 39).Another characteristic feature common in Bacteroides species is that the expression of some of the genes is altered in an on-off manner by reversible DNA inversions at gene promoters or within the protein-coding regions (5, 9, 19, 38, 39). These phase-variable phenotypes are associated with surface architectures such as capsular polysaccharides and SusC/SusD family proteins (5, 6, 16, 19). Our previous genomic analyses of Bacteroides fragilis strain YCH46 revealed that it contained as many as 31 invertible regions in its chromosome (19). These invertible regions can be grouped into six classes according to the internal motif sequences within inverted repeat sequences (IRs) (Table (Table1).1). The DNA inversions within these regions are thought to be controlled by site-specific DNA invertases specific to each class. B. fragilis strain YCH46 contains 33 tyrosine site-specific recombinases (Tsr) genes and four serine site-specific recombinases (Ssr) genes. Generally, DNA invertases mediate DNA inversions at adjacent regions, such as FimB and FimE, that flip their immediate downstream promoters to generate a phase-variable phenotype of type I pili in Escherichia coli (15). B. fragilis is unique in that this anaerobe possesses not only locally acting DNA invertases but also globally acting DNA invertases that mediate DNA inversions at distant loci (8, 29). It has been reported that B. fragilis possesses at least two types of master DNA invertase that regulate DNA inversions at multiple loci simultaneously (8, 29). One is Mpi, an Ssr that mediates the on-off switching of 13 promoter regions (corresponding to class I regions in B. fragilis strain YCH46), including seven promoter regions for capsular polysaccharide biosynthesis in B. fragilis strain NCTC9343 (8). The other master DNA invertase is Tsr19, a Tsr that regulates DNA inversions at two distantly located promoter regions (corresponding to class IV regions in B. fragilis strain YCH46) associated with the large encapsulation phenotype (6, 26, 29). The invertible regions contain specific consensus motifs within the IRs corresponding to each DNA invertase and constitute a regulatory unit. We designated this type of regulatory unit as an “inverlon,” which consists of at least two invertible regions controlled by a single master DNA invertase.
Open in a separate windowaOur previous classification of the invertible regions identified in B. fragilis strain YCH46 genome (19).bConsensus motif sequences found within IRs are shown. R = A or G, W = A or T, and N = A, G, C, or T.cThe gene identifications in B. fragilis strain YCH46 genome are shown.Our previous studies indicated that an additional inverlon other than the Mpi- and Tsr19-regulated inverlons is present in B. fragilis, based on the finding that at least 10 invertible regions (corresponding to class II regions in B. fragilis strain YCH46) contain a particular consensus motif sequence (AAGTTCN5GAACTT) within their IRs (19) but do not appear to colocalize with a DNA invertase gene. The majority of the class II regions were associated with the selective switching of a particular set of susC/susD family genes. Since the SusC/SusD family of outer membrane proteins play an important role in polysaccharide utilization by Bacteroides (3, 23, 32), the inverlon associated with the phase variation of SusC/SusD family proteins would likely be involved in the survival of this anaerobe in the distal gut.In the present study, we sought to identify the DNA invertase regulating the additional inverlon in B. fragilis. Our results indicated that the Tsr encoded by BF0667 is a master DNA invertase for this inverlon (designated the Tsr0667-inverlon) in B. fragilis. 相似文献
TABLE 1.
Classification of the invertible regions in B. fragilis strain YCH46 based on internal motif sequences within IRsClassa | No. | Consensus motif sequencesb | Master DNA invertase genec | Regulated genes | Source or reference(s) |
---|---|---|---|---|---|
I | 14 | ARACGTWCGT | BF2765 (mpi) | Capsular polysaccharide biosynthesis genes | 8 |
II | 10 | AGTTC{N5}GAACT | BF0667 | susC/susD paralogs | This study |
III | 3 | GTTAC{N7}GTAAC | BF3038, BF4033, BF4283 | Putative outer membrane protein genes | 36 |
IV | 2 | TACTTANTAGGTAANAGAA | BF2766 | Extracellular polysacharide biosynthesis genes | 6, 26, 29 |
V | 1 | TCTGCAAAGNCTTTGCAGA | BF0667 | susC/susD paralogs | This study |
VI | 1 | ACTAAGTTCTATCGG | BF0667 | susC/susD paralogs | This study |
15.
16.
Lisa M. Durso Gregory P. Harhay Timothy P. L. Smith James L. Bono Todd Z. DeSantis Dayna M. Harhay Gary L. Andersen James E. Keen William W. Laegreid Michael L. Clawson 《Applied and environmental microbiology》2010,76(14):4858-4862
The intestinal microbiota of beef cattle are important for animal health, food safety, and methane emissions. This full-length sequencing survey of 11,171 16S rRNA genes reveals animal-to-animal variation in communities that cannot be attributed to breed, gender, diet, age, or weather. Beef communities differ from those of dairy. Core bovine taxa are identified.The gastrointestinal tracts (GIT) of beef cattle are colonized by microorganisms that profoundly impact animal physiology, nutrition, health, and productivity (5). The GIT microbiota potentially impact food safety via pathogen shedding (13) by interacting with organisms such as Salmonella and competing for resources in the GIT. Cattle intestinal microbiota also play an important role in methane emissions, with U.S. beef cattle alone contributing an estimated 3.87 million metric tons of methane into the environment each year, both from rumen and large-intestine fermentations (7). Although the bovine fecal microbiota have been well characterized using culture-based methods, these techniques are necessarily limited to characterizing bacteria that can be grown in the laboratory. Culture-independent methods can reveal community members that are recalcitrant to culture. Only a handful of deep-sequencing studies have been done using culture-independent 16S rRNA-based methods (1, 11, 12, 14), all with dairy cattle, which have a fundamentally different diet and metabolism from beef cattle. Despite the potential contributions of the beef cattle GIT microbiota to animal health, food safety, and global warming, these communities remain poorly characterized. With the advent of pyrosequencing technology, researchers now have the tools to characterize these important communities. Pyrosequencing will allow rapid characterization of large-sample data sets (1). However, the taxonomic information generated by rapid sequencing is approximate by necessity (9), and full-length 16S-rRNA sequencing remains the “gold standard” method. Accordingly, we have characterized fecal bacteria from six feedlot cattle by full-length capillary sequence analysis of 11,171 16S rRNA gene clones (Fig. (Fig.11).Open in a separate windowFIG. 1.Bacterial diversity of six feedlot beef cattle. Gray bars represent the percentages of all 16S sequences that were assigned to each taxonomy. Colored dots represent the percentages of 16S sequences from each library that were assigned to each taxonomic group. Asterisks indicate unclassified members of the named taxon. Panel A shows the data for the first 99% of all the sequences. Panel B shows the data for the remaining 1% of sequences. Note differences in scales for panels A and B.Rectal grab fecal samples (n = 6) were collected according to institutional animal care guidelines. All animals were female cross-bred MARCIII beef heifers, 6 to 8 months of age, 214 to 241 kg, housed in the same feedlot pen for 2 months prior to fecal collection, and fed the same typical feedlot beef production growing rations consisting of 61.6% corn silage (41.3% dry matter), 15.2% alfalfa hay, 20.9% corn, and 2.3% liquid supplement.Total fecal DNA was isolated from homogenized samples using MoBio UltraClean fecal kit (Carlsbad, CA). PCR was performed using 27F and 1392R primers (11). Amplification consisted of 25 cycles, with an annealing temperature of 55°C. Amplicons from three reactions per sample were pooled (8), cloned using the Invitrogen TOPO TA cloning kit (Carlsbad, CA), and sequenced bidirectionally with M13 primers using an ABI 3700 sequencer (17). Low-quality and chimeric sequences (6) were excluded from further analysis. Distance matrices were compiled from ClustalW alignments (18) in PHYLIP (4). Pairwise estimates of shared richness were calculated using EstimateS, version 8.2 (R. K. Colwell; http://purl.oclc.org/estimates). DOTUR (16) was used to identify operational taxonomic units (OTUs) and to generate rarefaction curves (Fig. (Fig.2),2), richness and evenness estimates, and Shannon''s and Simpson''s diversity indices (Table (Table1).1). A 97% similarity cutoff and an 85% similarity cutoff for estimating OTUs were used to approximate species and class-level designations (15). Taxonomies were assigned to one member of each OTU using the RDP “classifier” tool (19), and the RDP taxonomic information was used for Fig. Fig.11 and and3.3. Common bovine taxa were identified based on inclusion in all three U.S. culture-independent studies (this study and references 1 and 11).Open in a separate windowFIG. 2.Rarefaction curves for six feedlot beef cattle. OTUs were assigned at the 85% DNA sequence similarity level. For comparison purposes, all six curves were truncated after 1,321 sequences.Open in a separate windowFIG. 3.Phylum-level distribution of bacterial sequences from six beef feedlot cattle. Asterisks indicate unclassified members of the named taxon.
Open in a separate windowaCI, confidence interval.The GIT community of beef feedlot cattle characterized in this study was found to share many taxa with the bovine GIT community described for dairy cattle (1, 11, 14), although the relative abundances of the major bacterial groups differed considerably. The fecal microbiota of beef cattle were dominated by members of the Firmicutes, with 62.8% of the OTUs belonging to this taxonomic group (Fig. (Fig.3).3). Bacteroidetes (29.5% of the OTUs) and Proteobacteria (4.4% of the OTUs) were also represented in feces (Fig. (Fig.3).3). A total of seven phyla were found in our six animals.Total estimated species richness values (Chao) for each of the six animals were 372, 600, 1,393, 526, 612, and 320 (Table (Table1).1). These cattle richness numbers are higher than those observed for three human subjects (164, 332, and 297) (2). The mean of Chao pairwise estimates of shared richness between any two of the six cattle fecal libraries was 230.Our findings, in addition to those from pyrosequencing studies (1), identify a core set of bovine GIT bacterial taxa, including the Bacteroidetes Prevotella and Bacteroides; the Firmicutes Faecalibacterium, Ruminococcus, Roseburia, and Clostridium; and the proteobacterium Succinovibrio (Fig. (Fig.1).1). These genera are consistently identified in bovine feces and likely compose part of the bovine resident microbiota. Although the potential exists for culture-independent methods to reveal minority microbial community members, 16S rRNA gene sequencing in dairy (1, 11) and beef cattle supports the list of core taxa identified using culture-based methods.Comparisons between our data set and recent studies done with dairy cattle (1, 11, 12) suggest that although beef and dairy cattle share many of the same major bacterial groups, the relative abundances of these groups in beef and dairy cattle may differ, and there may be differences between the two groups in the compositions of minority community members. The most common genus in beef cattle from our study was Prevotella, representing 24% of the total number of sequences evaluated. In comparison, Dowd et al. (1) found that Prevotella spp. represented only 5.5% of the total 16S genes sequenced from 20 dairy cattle, and Prevotella was not listed in the top 10 most frequently occurring OTUs in either of the studies from McGarvey et al. (11, 12). Likewise, Clostridium represented only 1.5% of the total beef sequences but 19% of the dairy pyrosequences (1). There were a number of bacterial sequences present in the beef cattle sequences but not reported in the dairy sequences, including Arthrobacter, Asteroleplasma, Bifidobacterium, Collinsella, Delftia, Eggerthella, Lactobacillus, Mitsuokella, Olsenella, and Propionibacterium (1, 11), although a number of these genera have been cultured from dairy animals in the past. It must be noted that all of these sequencing studies examined only a small number of animals, and each method has limitations which affect interpretation of the results. The full-length sequencing performed as part of this beef cattle study and two dairy studies (11, 12) relies on a PCR step which can potentially affect the relative numbers of each taxon observed due to PCR bias, while the pyrosequeincg method used in the 20-animal dairy study suffers from artifacts that potentially affect taxonomic assignment and richness estimates due to short read lengths and potential biases in evenness (how many of each group) due to primer and template mismatches (3). Nonetheless, these studies indicate that there may be fundamental differences between the gastrointestinal communities of beef and dairy cattle, they provide a comprehensive examination of the communities present in the specific animals tested, and they serve to provide important baseline information for further studies examining various factors which can impact cattle gastrointestinal communities.The taxonomic information generated by deep sequencing of beef cattle feces revealed considerable animal-to-animal variation in the operational taxonomic unit (OTU) composition of the individual libraries (Fig. (Fig.1).1). The OTU designation facilitates an analysis of the community data without forcing the assignment of sequences into an incomplete and imperfect bacterial taxonomic system. It relies on DNA sequence similarity to assign sequences to a particular OTU defined by the level of DNA sequence similarity. In total, 1,906 OTUs (97% OTU designation) were identified in the six libraries. Of these, only 24 OTUs (1.2%) (comprising 1,253 [11.2%] of sequences) were present in all six libraries, while 1,348 OTUs (69%) were found only in individual libraries. Of these, 1,064 OTUs (77%) were unique, represented by a solitary clone (range of 3% to 29% of the total clones from each individual animal). These data hint at considerable animal-to-animal variation in bacterial community structure at the species level that cannot be readily attributed to breed, gender, age, macroecologic factors such as weather conditions, or diet, given that the animals in this study were controlled for these variables, and support the conclusions of Manter et al. (10) that pooling samples can obscure rare phylotypes.Our results from beef cattle suggest that there may be differences in the bacterial community members present in the GIT of each individual animal that cannot be attributed to diet, breed, gender, age, or macroecologic factors such as weather and suggest the need for the high-resolution community sequencing of much larger numbers of animals before “core” minority community members can be identified. Considering the limited nature of the community surveys to date and all of the genetic, management, geographic, and temporal factors that can contribute to the composition of GIT microbiota, much work remains before we are able to understand and predict the community composition of any individual animal. 相似文献
TABLE 1.
Richness and diversity indices for 6 beef feedlot cattleLibrary and animal (n) | No. of OTUs observed | Species richness (CI)a by: | Diversity (CI) by: | ||
---|---|---|---|---|---|
Chao | ACE | Shannon''s index | Simpson''s index | ||
97% DNA sequence similarity | |||||
Animal 1 (2,485) | 198 | 372 (294-515) | 329 (280-408) | 3.89 (3.83-3.95) | 0.0422 |
Animal 2 (2,084) | 416 | 600 (538-694) | 604 (552-675) | 5.40 (5.35-5.45) | 0.0066 |
Animal 3 (1,710) | 696 | 1,393 (1,224-1,615) | 1,418 (1,327-1,523) | 6.13 (6.08-6.18) | 0.0027 |
Animal 4 (1,512) | 294 | 526 (439-665) | 483 (425-566) | 4.71 (4.63-4.78) | 0.0237 |
Animal 5 (2,059) | 314 | 612 (495-805) | 488 (434-566) | 4.93 (4.88-4.99) | 0.0126 |
Animal 6 (1,321) | 174 | 320 (252-447) | 289 (244-361) | 4.18 (4.11-4.25) | 0.0286 |
85% DNA sequence similarity | |||||
Animal 1 (2,485) | 48 | 61 (51-99) | 62 (52-90) | 2.64 (2.59-2.68) | 0.1056 |
Animal 2 (2,084) | 77 | 107 (87-165) | 102 (87-139) | 3.38 (3.34-3.43) | 0.0505 |
Animal 3 (1,710) | 130 | 153 (139-186) | 151 (140-174) | 4.07 (4.02-4.12) | 0.0254 |
Animal 4 (1,512) | 66 | 75 (68-98) | 77 (70-96) | 2.71 (2.64-2.78) | 0.0931 |
Animal 5 (2,059) | 69 | 80 (72-109) | 84 (75-110) | 3.31 (3.26-3.36) | 0.0545 |
Animal 6 (1,321) | 54 | 65 (57-102) | 61 (56-76) | 2.90 (2.83-2.97) | 0.0939 |
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18.
Todd J. Ward Thomas Usgaard Peter Evans 《Applied and environmental microbiology》2010,76(19):6680-6684
A 30-probe assay was developed for simultaneous classification of Listeria monocytogenes isolates by lineage (I to IV), major serogroup (4b, 1/2b, 1/2a, and 1/2c), and epidemic clone (EC) type (ECI, ECIa, ECII, and ECIII). The assay was designed to facilitate rapid strain characterization and the integration of subtype data into risk-based inspection programs.Listeria monocytogenes is a facultative intracellular pathogen that can cause serious invasive illness (listeriosis) in humans and other animals. L. monocytogenes is responsible for over 25% of food-borne-disease-related deaths attributable to known pathogens and is a leading cause of food recalls due to microbial adulteration (12, 21). However, not all L. monocytogenes subtypes contribute equally to human illness, and substantial differences in the ecologies and virulence attributes of different L. monocytogenes subtypes have been identified (9, 13, 14, 23, 24, 33, 35, 36). Among the four major evolutionary lineages of L. monocytogenes, only lineages I and II are commonly isolated from contaminated food and human listeriosis patients (19, 27, 29, 33). Lineage I strains are overrepresented among human listeriosis isolates, particularly those associated with epidemic outbreaks, whereas lineage II strains are overrepresented in foods and the environment (13, 14, 24). Lineage III strains account for approximately 1% of human listeriosis cases but are common among animal listeriosis isolates and appear to be a host-adapted group that is poorly adapted to food-processing environments (6, 34-36). The ecological and virulence attributes of lineage IV are poorly understood, as this lineage is rare and was only recently described based on a small number of strains (19, 26, 29, 33).L. monocytogenes is differentiated into 13 serotypes; however, four major serogroups (4b, 1/2b, 1/2a, and 1/2c) from within lineages I and II account for more than 98% of human and food isolates (16, 31). Serogroups refer to evolutionary complexes typified by a predominant serotype but which include very rare serotypes that represent minor evolutionary variants (7, 9, 33). Phylogenetic analyses have indicated that rare serotypes may have evolved recently, or even multiple times, from one of the major serotypes (9), and numerous molecular methods fail to discriminate minor serotypes as independent groups (1, 4, 7, 9, 18, 22, 33, 38, 39). Serotyping is one of the most common methods for L. monocytogenes subtyping, and serogroup classifications are a useful component of strain characterization because ecotype divisions appear largely congruent with serogroup distinctions (16, 34). Serogroup 4b strains are of particular public health concern because contamination with these strains appears to increase the probability that a ready-to-eat (RTE) food will be implicated in listeriosis (16, 28). Serogroup 4b strains account for approximately 40% of sporadic listeriosis and also are responsible for the majority of listeriosis outbreaks despite being relatively rare contaminants of food products (9, 13, 17, 30, 34). In addition, serogroup 4b strains are associated with more severe clinical presentations and higher mortality rates than other serogroups (11, 16, 20, 31, 34). Serogroups 1/2a and 1/2b are overrepresented among food isolates but also contribute significantly to human listeriosis, whereas serogroup 1/2c rarely causes human illness and may pose a lower risk of listeriosis for humans (16). Serogroup-specific differences in association with human listeriosis are consistent with the prevalence of virulence-attenuating mutations in inlA within these serogroups (32, 34); however, a number of additional factors likely contribute to these differences.Four previously described epidemic clones (ECs; ECI, ECIa, ECII, and ECIII) of L. monocytogenes have been implicated in numerous listeriosis outbreaks and have contributed significantly to sporadic illness (15, 34). ECI, ECIa, and ECII are distinct groups within serogroup 4b that were each responsible for repeated outbreaks of listeriosis in the United States and Europe. ECIII is a lineage II clone of serotype 1/2a that persisted in the same processing facility for more than a decade prior to causing a multistate outbreak linked to contaminated turkey (15, 25). While there has been speculation that epidemic clones possess unique adaptations that explain their frequent involvement in listeriosis outbreaks (9, 34, 37), it is not clear that epidemic clones are more virulent than other strains with the same serotype. However, contamination of RTE food with EC strains would be cause for increased concern due to the previous involvement of these clones in major outbreaks of listeriosis (16).As a result of the L. monocytogenes subtype-specific differences in ecology, virulence, and association with human illness, molecular subtyping technologies have the potential to inform assessments of relative risk and to improve risk-based inspection programs. The objective of the present study was to develop a single assay for rapid and accurate classification of L. monocytogenes isolates by lineage, major serogroup, and epidemic clone in order to facilitate strain characterization and the integration of subtype data into inspection programs that are based on assessment of relative risk.A database of more than 5.3 Mb of comparative DNA sequences from 238 L. monocytogenes isolates (9, 33-35) was scanned for single nucleotide polymorphisms that could be used to differentiate lineages, major serogroups, and epidemic clones via a targeted multilocus genotyping (TMLGT) approach. The acronym TMLGT is used to distinguish this approach from previously published multilocus genotyping (MLGT) assays that were lineage specific and designed for haplotype discrimination (9, 33). To provide for simultaneous interrogation of the selected polymorphisms via TMLGT, six genomic regions (Table (Table1)1) were coamplified in a multiplex PCR. While the previous MLGT assays were based on three lineage-specific multiplexes and required prior identification of lineage identity, TMLGT was designed to target variation across all of the lineages simultaneously and is based on a unique set of amplicons. PCR was performed in 50-μl volumes with 1× High Fidelity PCR buffer (Invitrogen Life Technologies), 2 mM MgSO4, 100 μM deoxynucleoside triphosphate (dNTP), 300 nM primer, 1.5 U Platinum Taq high-fidelity DNA polymerase (Invitrogen Life Technologies), and 100 ng of genomic DNA. PCR consisted of an initial denaturation of 90 s at 96°C, followed by 40 cycles of 30 s at 94°C, 30 s at 50°C, and 90 s at 68°C. Amplification products were purified using Montage PCR cleanup filter plates (Millipore) and served as a template for allele-specific primer extension (ASPE) reactions utilizing subtype-specific probes.
Open in a separate windowaCorresponding nucleotide positions in the complete genome sequence of L. monocytogenes strain EGD-e (GenBank accession number ).bSee IUPAC codes for definition of degenerate bases.ASPE was performed in multiplex reactions including 30 probes, with each lineage (I to IV), major serogroup (4b, 1/2b, 1/2a, and 1/2c), and epidemic clone (ECI, ECIa, ECII, and ECIII) targeted by two different probes (Table NC_003210(Table2).2). In addition, positive-control probes were included to confirm the presence of each amplicon in the multiplex PCR. As serogroups and epidemic clones are nested within a particular lineage, probes for these groups were designed to be specific within the appropriate lineage and values for these probes were evaluated only for isolates of the appropriate lineage. For example, serogroup 1/2a probes were evaluated only for isolates that were positive for lineage II probes. ASPE probes were designed with a unique 5′ sequence tag specific to individual sets of xMAP fluorescent polystyrene microspheres (Luminex Corporation) used to sort extension products. Extension and hybridization reactions were performed as described previously (9) except microspheres were twice pelleted by centrifugation (4 min at 2,250 × g) and resuspended in 75 μl 1× TM buffer prior to being pelleted and resuspended in 100 μl 1× TM buffer containing 2 μg/ml streptavidin-R-phycoerythrin (Invitrogen Life Technologies). Samples were incubated for 15 min at 37°C prior to detecting the microsphere complexes with a Luminex 100 flow cytometer (Luminex Corporation). The median fluorescence intensity (MFI) from biotinylated extension products attached to 100 microspheres was measured for each probe. The average MFI from three template-free control samples was also determined and subtracted from the raw MFI of each sample to account for background fluorescence. Probe performance was initially evaluated via the index of discrimination (ID) as described by Ducey et al. (9), and probes with ID values less than 2.0 were redesigned.
Open in a separate windowaNA, not applicable for positive amplicon control probes.bLuminex microsphere sets (Luminex Corporation) used for hybridization reactions are indicated following the hyphen.cn, number of isolates representing the target subtype among the 906 tested isolates.dThe 5′ sequence tag portions of extension probes are capitalized. See IUPAC codes for definitions of degenerate bases.eID, index of discrimination.Validation of the TMLGT assay was performed using 906 L. monocytogenes isolates for which the lineage, major serogroup, and epidemic clone type had been determined independently (see Table S1 in the supplemental material). A subset of 92 isolates, including at least five isolates from each lineage, serogroup, and epidemic clone type, was used to evaluate the discriminatory power of subtype-specific probes and the repeatability of the assay (see Table S1). Two independent runs of the 30-probe TMLGT assay produced identical results for these 92 isolates. In addition, genotypes matched expectations for all isolate/probe combinations, and the fluorescence intensities for positive genotypes (those targeted by a particular probe) were 3.8 to 58.3 (mean, 18.5) times as high as background values for isolates with negative genotypes (those not targeted by a particular probe) (Table (Table2).2). The performances of individual probes also were assessed in terms of sensitivity and specificity, where sensitivity is defined as the percentage of positive samples that produced positive results and specificity indicates the percentage of negative samples that produce negative results (5). Based on results from all 906 isolates analyzed by TMLGT, probe sensitivity was at least 98.6% and 23 of the 24 subtype-specific probes exhibited 100% sensitivity (Table (Table2).2). The specificities for all probes were also greater than 98.6%, and 21 of the 24 subtype-specific probes exhibited 100% specificity (Table (Table22).All but three of the 906 isolates in the validation panel were fully and accurately typed relative to lineage, serogroup, and epidemic clone by using the TMLGT assay (typeability, 99.9%; accuracy of isolate assignment, 99.8%). One of the lineage II isolates, NRRL B-33880, could not be assigned to a serogroup based on the TMLGT results because this isolate was positive for one of the serogroup 1/2a probes (VGCb-40) and one of the serogroup 1/2c probes (LMO-9). This isolate was previously identified as a member of serogroup 1/2c based on mapping lineage-specific MLGT data onto a multilocus phylogeny (34) but produced a serogroup 1/2a-specific banding pattern (data not shown) with the multiplex PCR assay described by Doumith et al. (7). Similar strains, including the common laboratory strain EGD-e, were found to have genomes that are more similar to serogroup 1/2c strains than to strains from the 1/2a serogroup (8, 33) and likely represent intermediates in the evolution of the 1/2c clade from 1/2a ancestors. There is a poor correlation between genomic and antigenic variation for such isolates (34), consistent with the ambiguous results produced by application of the TMLGT assay to NRRL B-33880. The two other problematic isolates, NRRL B-33555 and NRRL B-33559, were accurately identified based on TMLGT data as lineage II isolates from the 1/2a serogroup. However, these two isolates were positive for both ECIII-specific probes in the TMLGT assay but have lineage-specific MLGT haplotypes (Lm2.46), indicating that they are representatives of a sister group closely related to ECIII (33).In 2005, the Food Safety and Inspection Service (FSIS) implemented an approach to inspection that includes consideration of relative risk in order to determine L. monocytogenes sampling frequency among establishments that produce certain RTE products. This approach incorporates information on production volume, outgrowth potential in the product, steps taken to prevent postlethality contamination, and FSIS sampling history. However, L. monocytogenes subtype-specific variation in ecology and virulence indicates that information on the lineage, major serogroup, and epidemic clone identities of isolates could be used to inform assessments of relative risk and to improve inspection programs that are based on consideration of risk. Several PCR-based methods have been described for differentiation of various combinations of these subgroups (1-3, 5, 7, 10, 35, 37); however, these approaches have focused on a single subgroup or a smaller set of subgroups than is differentiated by TMLGT analysis. Although we previously developed a set of three MLGT assays that can be used to differentiate all of the major serogroups and epidemic clones of L. monocytogenes (9, 33, 34), those assays did not include probes for lineage discrimination and require identification of the lineage prior to application of one of three unique sets of probes. In addition, the MLGT assays were designed to maximize strain discrimination, as opposed to subgroup identification, and require the use of at least twice as many probes as is needed for TMLGT analysis. MLGT data analysis is also more complicated than analysis of TMLGT data, and serogroup or epidemic clone type identification via MLGT requires phylogenetic analyses to place novel haplotypes within an established phylogenetic framework.In the present study, we developed the first assay for simultaneous discrimination of the four lineages, the four major serogroups, and the four previously described epidemic clones of L. monocytogenes. The assay includes multiple markers for each of these subtype probes as well as control probes to ensure that negative probe data were not the result of amplification failure, providing a high degree of internal validation required for use in inspection programs that consider risk in making sampling decisions. In addition, the utility of the assay has been validated with a large and diverse panel of 906 isolates, including 567 isolates from FSIS surveillance of RTE products and processing facilities (see Table S1 in the supplemental material). Data produced by the TMLGT assay are amenable to high-throughput analysis, and a simple spreadsheet utility has been developed to semiautomate subtype identifications and to alert investigators to potentially conflicting probe data (available upon request). In addition to having a potential application in inspection programs, the TMLGT assay provides a rapid and accurate means of characterizing L. monocytogenes isolates from different environments, which would facilitate pathogen tracking and improve understanding of L. monocytogenes ecology. 相似文献
TABLE 1.
Primers used in multiplex amplification for the TMLGT assayAmplicon | Positiona | Gene(s) | Primer | Sequence (5′-3′)b |
---|---|---|---|---|
INLa | 455381-456505 | inlA | inl2-a1 | GTCCTTGATAGTCTACTG |
inl2-a2 | ACCAAATTAGTAATCTAGCAC | |||
INLb | 457726-458752 | inlB | inl-f1d | GAATTRTTTAGYCAAGAATGT |
inlb-r | CTACCGGRACTTTATAGTAYG | |||
LMO | 325116-326096 | lmo0298-lmo0300 | lmo-a1 | AAGGCTTACAAGATGGCT |
lmo1a-1r | AAATAATAYGTGATACCGAC | |||
VGCa | 205366-206622 | plcA, hly | plca-f | CTCATCGTATCRTGTGTACC |
hly-r | TCTGGAAGGTCKTGTAGGTTC | |||
VGCb | 208447-209465 | mpl | ra_mpl-f | GTGGAYAGAACTCATAAAGG |
ra_mpl-r | ACTCCCTCCTYGTGATASGCT | |||
VGCc | 209728-211239 | actA | vgc1a-2f | TTCMATRCCAGCAGAACG |
vgc1a-2r | GCAGACCTAATAGCAATGTTG |
TABLE 2.
TMLGT probes and probe performance dataProbeb | Target (n)c | Probe sequenced | IDe | Sensitivity (%) | Specificity (%) |
---|---|---|---|---|---|
VGCb-21 | Lineage I (506) | AATCCTTTCTTTAATCTCAAATCAgcggaagcttgggaagcggtc | 7.3 | 100 | 100 |
VGCa-94 | Lineage I | CTTTCTATCTTTCTACTCAATAATcaacccgatgttcttcctgtc | 51.7 | 100 | 100 |
VGCc-8 | Lineage II (340) | AATCCTTTTACATTCATTACTTACattagctgattcgctttcct | 14.1 | 100 | 100 |
INLb-51 | Lineage II | TCATTTCAATCAATCATCAACAATagcgccaataaagctggc | 21.9 | 100 | 100 |
VGCb-19 | Lineage III (50) | TCAATCAATTACTTACTCAAATACccgctattaaaatgtactcca | 31.0 | 100 | 100 |
VGCb-29 | Lineage III | AATCTTACTACAAATCCTTTCTTTggtataccgctattaaaatgt | 45.1 | 100 | 100 |
LMO-17 | Lineage IV (10) | CTTTAATCCTTTATCACTTTATCAgaaccaaacaatgttattggt | 11.8 | 100 | 100 |
VGCa-27 | Lineage IV | CTTTTCAAATCAATACTCAACTTTttaacgacggtaacgtgccac | 58.3 | 100 | 100 |
INLb-84 | Serogroup 4b (213) | TCAACTAACTAATCATCTATCAATggtaaaaatatgcgaatattg | 9.7 | 100 | 100 |
INLb-85 | Serogroup 4b | ATACTACATCATAATCAAACATCActcgtgaacaagctttcc | 5.5 | 100 | 100 |
INLb-16 | Serogroup 1/2b (293) | AATCAATCTTCATTCAAATCATCAggtaaaaatatgcgtatctta | 11.7 | 100 | 100 |
INLb-100 | Serogroup 1/2b | CTATCTTTAAACTACAAATCTAACgtgaataagctatcggtctat | 13.0 | 100 | 100 |
LMO-42 | Serogroup 1/2a (268) | CTATCTTCATATTTCACTATAAACtggcgttgctgrctaagtttg | 6.6 | 100 | 100 |
VGCb-40 | Serogroup 1/2a | CTTTCTACATTATTCACAACATTAaatcaagcsgctcatatgaag | 10.4 | 100 | 98.6 |
LMO-9 | Serogroup 1/2c (72) | TAATCTTCTATATCAACATCTTACtttactggtgaaatggcg | 13.5 | 100 | 100 |
VGCb-5 | Serogroup 1/2c | CAATTCAAATCACAATAATCAATCaagattacgaatcgcttccac | 20.8 | 98.6 | 100 |
LMO-10 | ECI (111) | ATCATACATACATACAAATCTACAatgattaaaagtcagggaaag | 19.0 | 100 | 100 |
LMO-28 | ECI | CTACAAACAAACAAACATTATCAAaatcgaggcttacgaacgt | 23.7 | 100 | 100 |
VGCc-80 | ECIa (44) | CTAACTAACAATAATCTAACTAACactacaacgaaaacagcgc | 10.7 | 100 | 100 |
VGCa-35 | ECIa | CAATTTCATCATTCATTCATTTCAgttacttttatgtcgagt | 9.2 | 100 | 100 |
LMO-12 | ECII (35) | TACACTTTCTTTCTTTCTTTCTTTataccgattatttggacggtt | 3.8 | 100 | 100 |
LMO-30 | ECII | TTACCTTTATACCTTTCTTTTTACgacttgtagcagttgatttcaa | 7.5 | 100 | 100 |
VGCc-45 | ECIII (10) | TCATTTCACAATTCAATTACTCAActcttatttgcttttgttggtc | 21.1 | 100 | 99.4 |
INLa-3 | ECIII | TACACTTTATCAAATCTTACAATCgagcttaatgaaaatcagcta | 17.0 | 100 | 99.4 |
INLa-1 | INLa control | CTTTAATCTCAATCAATACAAATCagaagtggaagctgggaa | NAa | NA | NA |
INLb-13 | INLb control | CAATAAACTATACTTCTTCACTAAtgcacctaaacctccgac | NA | NA | NA |
LMO-88 | LMO control | TTACTTCACTTTCTATTTACAATCccgtttccttatgccaca | NA | NA | NA |
VGCa-23 | VGCa control | TTCAATCATTCAAATCTCAACTTTcaagycctaagacgccaatcg | NA | NA | NA |
VGCb-25 | VGCb control | CTTTTCAATTACTTCAAATCTTCAgcatgcgttagttcatgrcca | NA | NA | NA |
VGCc-82 | VGCc control | TACATACACTAATAACATACTCATgactgcatgctagaatctaag | NA | NA | NA |
19.
Brittney L. Gurda Kristin N. Parent Heather Bladek Robert S. Sinkovits Michael A. DiMattia Chelsea Rence Alejandro Castro Robert McKenna Norm Olson Kevin Brown Timothy S. Baker Mavis Agbandje-McKenna 《Journal of virology》2010,84(12):5880-5889
Human bocavirus (HBoV) was recently discovered and classified in the Bocavirus genus (family Parvoviridae, subfamily Parvovirinae) on the basis of genomic similarity to bovine parvovirus and canine minute virus. HBoV has been implicated in respiratory tract infections and gastroenteric disease in children worldwide, yet despite numerous epidemiological reports, there has been limited biochemical and molecular characterization of the virus. Reported here is the three-dimensional structure of recombinant HBoV capsids, assembled from viral protein 2 (VP2), at 7.9-Å resolution as determined by cryo-electron microscopy and image reconstruction. A pseudo-atomic model of HBoV VP2 was derived from sequence alignment analysis and knowledge of the crystal structure of human parvovirus B19 (genus Erythrovirus). Comparison of the HBoV capsid structure to that of parvoviruses from five separate genera demonstrates strong conservation of a β-barrel core domain and an α-helix, from which emanate several loops of various lengths and conformations, yielding a unique surface topology that differs from the three already described for this family. The highly conserved core is consistent with observations for other single-stranded DNA viruses, and variable surface loops have been shown to confer the host-specific tropism and the diverse antigenic properties of this family.Human bocavirus (HBoV), a newly discovered member of the family Parvoviridae, was originally isolated in randomly selected nasopharyngeal aspirates (5). Since this initial discovery, HBoV has also been detected worldwide, predominantly in children under the age of 2 years with respiratory infections, in serum, urine, and fecal samples (40). Symptomatic children commonly exhibit acute diseases of the upper and lower respiratory tracts (7, 36, 44, 56) and, possibly, gastroenteritis (31, 56) though the link to gastroenteritis outbreaks has been questioned (12). It is still unclear if HBoV is the sole etiologic agent of respiratory disease as higher rates of coinfections with other respiratory pathogens such as human rhinovirus and Streptococcus spp. are often observed (4). However, Allander et al. recently reported (4) that HBoV was found in 19% of children with acute wheezing, thereby making it the fourth most common virus, after rhinoviruses, enteroviruses, and respiratory syncytial virus, detected in children exhibiting this symptom. These findings suggest that, at high viral load, HBoV could be an etiologic agent of respiratory tract disease (4). HBoV infection is common in the first few years of life, and clinical research suggests it may follow the primary period for acquisition of human parvovirus B19 (B19) though there is no antigenic cross-reactivity between B19 and HBoV (28, 30). By age 5, most people have circulating antibodies against HBoV, as is also true for other respiratory viruses such as respiratory syncytial virus, rhinoviruses, and human metapneumovirus (17). HBoV has also been identified in adults, with ∼63% of samples tested being seropositive, showing a positive correlation with age and a slight positive bias toward women (14).The Parvoviridae is a family of small, nonenveloped viruses that package a single-stranded DNA (ssDNA) genome of ∼5,000 bases. These viruses are subdivided into two subfamilies: Parvovirinae and Densovirinae (Table (Table1).1). The Parvovirinae are further subdivided into five genera, all of whose members infect vertebrates. The Densovirinae (four genera) infect only invertebrates. Phylogenetic analysis places HBoV in the recently classified Bocavirus genus (Table (Table1).1). In addition to HBoV, numerous parvoviruses circulate among the human population. Among these are the following: several dependoviruses; adeno-associated virus (AAV) serotypes AAV1 to AAV3, AAV5, and AAV9; the Erythrovirus B19; and the newly discovered human parvovirus genotypes 4 (Parv4) and 5 (Parv5) (23, 27, 50). Of these, only B19 had been implicated in disease until the discovery of HBoV and Parv4, which has been isolated from patients who present symptoms of acute HIV infection (50).
Open in a separate windowaAalDNV, Aedes albopictus densovirus; AaeDNV, Aedes aegypti densovirus; BmDNV, Bombyx mori densovirus; BPV, bovine parvovirus; CnMV, canine minute virus; CPV, canine parvovirus; FPV, feline panleukopenia virus; GPV, goose parvovirus; JcDNV, Junonia coenia densovirus; PfDNV, Periplaneta fuliginosa densovirus; SPV, simian parvovirus. *, structure determined by X-ray crystallography; †, structure determined by cryo-EM.bThe number of VPs in the virion capsid.cGroup refers to the surface topologies described in Results and Discussion (HBoV is currently the only bocavirus with a known structure; there is no structure available for Periplaneta fuliginosa densovirus or the brevidensoviruses). NA, structural group not assigned.dThe VP(s) that comprises most of the wild-type virion.The HBoV genome, like that of all members of the Bocavirus genus, contains three open reading frames (ORFs). The first ORF, at the 5′ end, encodes NS1, a nonstructural protein. The next ORF, unique to the bocaviruses, encodes NP1, a second nonstructural protein. The third ORF, at the 3′ end, encodes the two structural capsid viral proteins (VPs), VP1 and VP2. The HBoV VPs share 42% and 43% amino acid sequence identity with the corresponding VPs of bovine parvovirus and canine minute virus, respectively (5). More recently, two additional HBoV-like viruses, HBoV-2 and HBoV-3, were identified in stool samples from children (8, 31). The genome organization of these viruses is identical to that of HBoV, with the NS1, NP1, and VP proteins of HBoV-2 and HBoV-3 being, respectively, ∼80 and 90%, ∼70 and 80%, and ∼80 and 80% identical to the respective proteins in HBoV (8, 31).Parvovirus genomes are packaged into a T=1 icosahedral capsid that is assembled from 60 copies of a combination of up to six types of capsid VPs (VP1 to VP6), all of which share a C terminus. VP1 is always a minor component, typically comprising about five copies per capsid, whereas the smallest VP is always the major component. The unique N-terminal region of VP1 (VP1u) contains a conserved phospholipase A2 (PLA2) motif within the first 131 amino acids that is essential for infection (49, 61). Interestingly, Aleutian mink disease virus (AMDV), the only member of the Amdovirus genus, is the only exception in that this motif is absent, which suggests that this virus employs a different mechanism to escape the endosome during infection (54).The X-ray crystal structures of several parvoviruses show that all VPs contain a conserved, eight-stranded β-barrel motif (βB to βI) that forms the core of the capsid (15). There is also a conserved α-helix (αA) observed in all parvovirus structures determined to date. The bulk of the VP consists of elaborate loops between the strands that form the surface of the capsid. For example, the GH loop between the βG and βH strands is ∼230 residues. The composition and topology of these loops encode several important functions, including tissue tropism, pathogenicity, and the antigenic response directed against each parvovirus during infection (2).A number of parvoviruses have been studied by cryo-electron microscopy (cryo-EM) and three-dimensional (3D) image reconstruction in concert with and complementary to X-ray crystallographic studies (reviewed in reference 15). Reported here is the 3D structure of a recombinant HBoV capsid solved to 7.9-Å resolution using cryo-EM. The capsid of HBoV was compared to that of representative members of the Parvoviridae (Table (Table1)1) with known atomic structures (AAV2, minute virus of mice [MVM], B19, and Galleria mellonella densovirus [GmDNV]) or pseudo-atomic models built into cryo-EM reconstructed density (AMDV) to identify similarities and differences. The capsid topology of the newly emerging HBoV incorporates a combination of surface structural features seen in other members of the Parvovirinae and is closest to that of B19, the only other structurally characterized parvovirus that is pathogenic to humans. A pseudo-atomic model of the HBoV VP2, built into the reconstructed density, identified conserved core secondary structure elements, which are known to be important for parvovirus capsid assembly, and variable surface loops, which likely govern host specific interactions. 相似文献
TABLE 1.
Selected properties of representative members of the ParvoviridaeSubfamily (host) and genus | Member(s)a | No. of VPsb | Groupc | Major VP(s)d |
---|---|---|---|---|
Parvovirinae (vertebrate) | ||||
Parvovirus | MVM*, CPV*, FPV* | 3 | I | VP2 |
Erythrovirus | B19*†, SPV | 2 | III | VP2 |
Dependovirus | AAV2*†, AAV4*†, GPV | 3 | III | VP3 |
Amdovirus | AMDV† | 2 | III | VP2 |
Bocavirus | HBoV†, BPV, CnMV | 2 | NA | VP2 |
Densovirinae (invertebrate) | ||||
Densovirus | GmDNV*, JcDNV† | 4 | II | VP4 |
Iteravirus | BmDNV† | 4-6 | II | VP1-VP4 |
Brevidensovirus | AaeDNV, AalDNV | 2-3 | NA | VP1 or VP2/3 |
Pefudensovirus | PfDNV | 5 | NA | VP1 |
20.
Jana Rühl Andreas Schmid Lars Mathias Blank 《Applied and environmental microbiology》2009,75(13):4653-4656
Adapted Pseudomonas putida strains grew in the presence of up to 6% (vol/vol) butanol, the highest reported butanol concentration tolerated by a microbe. P. putida might be an alternative host for biobutanol production, overcoming the primary limitation of currently used strains—insufficient product titers due to low butanol tolerance.The focus of biofuel production research has recently shifted from ethanol to bioenergy carriers that are more compatible with existing infrastructure (e.g., refineries, transport, and car engines). At the forefront is n-butanol (hereafter referred to as butanol) for which large-scale production processes have been implemented (16, 35). Existing fermentations, however, are limited in energetically attractive butanol titers, because butanol inhibits microbial growth at concentrations above 16 g/liter (2, 10). As reported for other organic solvents with low logarithm of the partition coefficient in a two-phase octanol/water system (log Pow), this toxicity is due primarily to accumulation of butanol (log Pow, 0.8) in the cell membrane and subsequent impairment (4, 17, 30, 33). With the maximum aqueous solubility of 0.97 M (8.8% [vol/vol]), the maximum membrane concentration of butanol was calculated to be 1.59 M (17), spotlighting its potential toxicity. The low achievable butanol titers have necessitated large reactor volumes, resulting in high purification costs (8, 15). Recent metabolic engineering strategies for improving biobutanol fermentation have focused on maximization of butanol production rates (10, 19), reducing the levels of by-products (20), finding alternative substrates (20), or finding alternative hosts (2, 12, 21, 31). However, recently engineered microbial strains (1, 14) have not overcome butanol toxicity.High organic solvent concentrations are tolerated by strains of the bacterial species Pseudomonas putida reported to grow in a second phase of octanol (25), toluene (13), or styrene (32). This suggests that solvent-tolerant P. putida strains withstand high butanol titers and therefore warrant exploitation as host for butanol production. Indeed, viable solvent-tolerant P. putida S12 cells were observed at butanol concentrations of up to 10% (vol/vol) by live-dead staining and fluorescence microscopy (5) (see supplemental material). We used growth as the parameter of interest, because growth in the presence of butanol directly indicates the potential of selected P. putida strains as hosts for recombinant butanol production.Three solvent-tolerant P. putida strains, DOT-T1E (23), S12 (32), and Pseudomonas sp. strain VLB120 (18), and the solvent-sensitive P. putida reference strain KT2440 (24) were examined for their ability to grow in the presence of butanol. Toxicity assays were performed in 96-well microtiter plates (System Duetz [7]) at 30°C and 300 rpm using glucose-supplemented LB and M9 media (with 10 and 5 g/liter glucose, respectively) (26). Higher glucose concentrations in LB medium did not increase butanol tolerance (data not shown). Butanol was added in all experiments to cells in the mid-exponential phase. Cell growth was monitored by changes in optical density, and substrate and butanol concentrations were analyzed by high-pressure liquid chromatography (Trentec 308R-Gel.H; VWR Hitachi). Comparable low butanol concentrations were withstood by all P. putida strains, with butanol tolerance highly dependent on the medium composition (Table (Table1).1). Growth was observed at butanol concentrations up to 3% (vol/vol), occurring in a culture of Pseudomonas sp. strain VLB120 using glucose-supplemented LB medium.
Open in a separate windowaValues represent the maximum butanol concentration allowing growth (growth rate of ≥0.05 h−1). Data in parentheses were measured in experiments with cells that were stored at −80°C.Because reported adaptation approaches (3, 17, 18, 32) were not successful (see supplemental material), a modified adaptation protocol was developed. Cells were incubated at 30°C on LB agar plates in an airtight desiccator with a butanol saturated gas phase. Colonies were repeatedly transferred every 2 days to new plates for at least 15 times. Cells that underwent this procedure, referred to as treated cells, were harvested and either stored at −80°C prior to testing or assessed immediately for tolerance to butanol (Fig. (Fig.11).Open in a separate windowFIG. 1.Butanol tolerance of P. putida. Growth rates of untreated (A) and adapted (B) cells in LB medium with 10 g/liter glucose as an additional energy and carbon source. The concentration of butanol (cBuOH) is shown on the x axis. The growth rates are normalized to the growth rate in the respective control experiments without butanol. Lines are drawn for better visualization. Error bars present standard deviations of independent experiments (n = 3 to 6). Symbols: ▪, P. putida DOT-T1E; •, P. putida KT2440; ▴, P. putida S12; ▾, Pseudomonas sp. strain VLB120.The treated solvent-tolerant cells grew at rates above 0.05 h−1 (approximately 5% of the maximum growth rate without butanol) in the presence of up to 6% (vol/vol) butanol. Butanol concentrations in the medium decreased during the experiments due to evaporation (i.e., at a rate of 0.76 ± 0.03 mmol l−1 h−1) from an initial concentration of 5% (vol/vol) and, more significantly, due to consumption. Similar butanol uptake rates were observed for all four strains at 5% (vol/vol) initial butanol, ranging from 5.2 to 6.6 mmol l−1 h−1. Therefore, the butanol concentration decreased to only 3.5% (vol/vol) and 4% (vol/vol) after 9 h of cultivation in experiments at initial butanol concentrations of 5% (vol/vol) and 6% (vol/vol), respectively. This decrease resulted in an average butanol concentration of 4.5% (vol/vol) tolerated by the DOT-T1E, S12, and VLB120 cells. Notably, the time course of butanol concentration did not differ significantly with solvent-sensitive P. putida KT2440 that did not grow above 1.5% (vol/vol) butanol.To rationalize the metabolic responses of untreated and treated strains to butanol, we performed 13C-labeled tracer-based flux analysis (3, 18, 27, 34), using minimal medium with 20% U-13C-labeled and 80% naturally labeled glucose, as reported recently (3, 6, 9). During growth without butanol, the four Pseudomonas strains had similar intracellular carbon flux distributions, independent of any prior adaptation to butanol (data not shown). In the presence of butanol, all untreated cells revealed significantly higher specific glucose uptake rates while growth rates decreased (Fig. (Fig.2).2). The reduced biomass yield was not caused by by-product formation (data not shown) but by changes in intracellular flux distribution: the carbon flux was rerouted from biomass synthesis to the tricarboxylic acid (TCA) cycle, which was fueled by pyruvate via pyruvate dehydrogenase and citrate synthase activity. The anaplerotic and gluconeogenic reactions were unaffected. The overall redox cofactor regeneration rates (approximately fourfold higher) resulting from this rerouting suggest that larger amounts of energy are demanded for cell maintenance during butanol stress, similar to the response of P. putida during growth in the presence of other organic solvents with low log Pow (22, 23, 28).Open in a separate windowFIG. 2.Flux distributions in P. putida under butanol stress conditions. The flux distributions in the P. putida strains DOT-T1E, KT2440, and S12 and Pseudomonas sp. strain VLB120 (from top to bottom) were determined during growth in glucose-containing M9 medium supplemented with 1% (vol/vol) butanol using untreated and adapted cells. Butanol catabolism was traced by the fractional labeling of central carbon metabolites (see text for details). The errors for all fluxes were below 10% with the exception of highly active or negligibly fluxes including PEP carboxykinase, pentose-phosphate-pathway (PPP), and phosphoglycoisomerase. The upper bound of the NAD(P)H regeneration rate is presented. Glucose-6-P, glucose-6-phosphate; PGA, 3-phosphoglycerate; PEP, phosphoenolpyruvate.In contrast, physiology and flux distributions differed for adapted DOT-T1E, S12, and VLB120 cells, but not treated KT2440 cells. These strains, coping with high butanol concentrations, had low net glucose consumptions, resulting in comparably lower TCA cycle fluxes and consequently lower redox cofactor regeneration rates (Fig. (Fig.2).2). As indicated above (Fig. (Fig.1),1), P. putida KT2440 did not adapt to butanol, and no metabolic changes were observed compared with the untreated strain.Coconsumption of butanol was considered in calculating the absolute intracellular fluxes by correcting the fractional labeling [FL = n13C/(n12C + n13C)] of the affected amino acids—aspartate, glutamine, isoleucine, leucine, and threonine. The dilution of the fractional isotope label due to butanol coconsumption decreased from acetyl coenzyme A (acetyl-CoA) (FL = 8%) to 2-ketoglutarate (FL = 13%) and oxaloacetate (FL = 15%), suggesting that butanol is cometabolized via β-oxidation to acetyl-CoA, followed by oxidation in the TCA cycle.As calculated from the fractional label of the m-15 isotopomer of leucine (FL = 14%), approximately 60% of the acetyl-CoA originated from butanol. For example, in P. putida KT2440, butanol contributed to the synthesis of acetyl-CoA about 7.22 ± 0.23 mmol g−1 h−1, corresponding to the measured glucose uptake rate of 11.22 ± 0.74 mmol g−1 h−1 [(7.22/11.22) × 100 = 64%]. The untreated solvent-tolerant strains had slightly lower consumption rates of approximately 6.5 mmol g−1 h−1 for butanol and 10.2 mmol g−1 h−1 for glucose. Compared with the untreated strains, adapted DOT-T1E, S12, and VLB120 cells had lower uptake rates of 3.8 to 5.2 mmol g−1 h−1 for butanol and 4.9 to 6.6 mmol g−1 h−1 for glucose. Butanol did not contribute significantly to the synthesis of pyruvate (FL = 19%) and PEP (FL = 20%, or the contribution was below the FL detection limit of 0.5%), suggesting that malic enzyme and phosphoenolpyruvate (PEP) carboxykinase are marginally active under these conditions. This suggests that a synthetic pathway for butanol synthesis from glucose can be implemented in P. putida using native genes for butanol dehydrogenase and aldehyde dehydrogenase with a concomitant decrease of ß-oxidation activity.Butanol degradation of P. putida KT2440 was comparable with the rates of solvent-tolerant cells, but butanol tolerance was not induced, suggesting activity of additional mechanisms of adaptation or tolerance, such as solvent removal by efflux pumps and physiochemical changes of membrane lipids (11, 22). These mechanisms reduce cellular growth rates and biomass yields by imposing higher energy demands. Additionally, energy loss can be caused by swelling and alteration of the lipid layer due to increased proton permeability of the membrane (4) and by reduced efficiency of the electron transport chain (30). In butanol-tolerant cells, the observed reduction in TCA cycle use and energy production in the presence of butanol suggests cell membrane adaptation by lowering its energy demands for maintenance.The observed higher tolerance to butanol in LB medium compared with minimal medium can also be explained by decreased metabolic costs for sustaining biomass synthesis due to direct supply of biomass precursors like amino acids (29). Additional supplementation of LB medium with glucose enhanced butanol tolerance, most likely due to increased energy supplies. For P. putida S12, we calculated glucose uptake rates of 8.01 ± 0.21 mmol g−1 h−1 and 13.53 ± 0.34 mmol g−1 h−1 at initial butanol concentrations of 1% (vol/vol) and 3% (vol/vol), respectively, translating into an increased ATP regeneration rate at 3% (vol/vol) butanol of minimally 13.5 mmol g−1 h−1 (substrate phosphorylation via the Entner-Doudoroff pathway) and up to approximately 350 mmol g−1 h−1 (oxidative phosphorylation). The additional energy demand in the presence of butanol necessitates particular attention during strain and medium engineering.We report solvent-tolerant P. putida strains growing at butanol concentrations as high as 6% (vol/vol). Metabolic flux analysis suggests that this is not based on glucose-butanol coconsumption but rather effected by lowered cell maintenance costs.In conclusion, butanol-tolerant P. putida strains are promising candidates as production hosts, overcoming the principal limitation of biobutanol production—product inhibition at low concentrations. 相似文献
TABLE 1.
Tolerated butanol concentrations in different growth mediaPseudomonas strain and treatment or cell type | Maximum butanol concn [% (vol/vol)]a
| ||
---|---|---|---|
M9 minimal medium with glucose (5 g/liter) | LB medium | LB medium with glucose (10 g/liter) | |
P. putida DOT-T1E | |||
Untreated | 1.5 | 1.5-2.0 | 2.5 |
Adapted | 1.0 (1.0) | 1.5 (2.0) | 6.0 (5.0) |
P. putida KT2440 | |||
Untreated | 1.0 | 1.5 | 2.0 |
Treated | 1.0 (1.0) | 1.5 (1.0) | 1.5 (1.5) |
P. putida S12 | |||
Untreated | 1.5 | 2.0 | 2.5 |
Adapted | 1.0 (1.0) | 1.5-2.0 (1.5) | 6.0 (5.0) |
Pseudomonas sp. strain VLB120 | |||
Untreated | 1.5 | 2.0 | 2.5-3.0 |
Adapted | 1.0 (1.5) | 1.5-2.0 (1.5) | 6.0 (6.0) |