Molecular and Biochemical Characterization of the Protein Template Controlling Biosynthesis of the Lipopeptide Lichenysin

Lichenysins are surface-active lipopeptides with antibiotic properties produced nonribosomally by several strains of Bacillus licheniformis. Here, we report the cloning and sequencing of an entire 26.6-kb lichenysin biosynthesis operon from B. licheniformis ATCC 10716. Three large open reading frames coding for peptide synthetases, designated licA, licB (three modules each), and licC (one module), could be detected, followed by a gene, licTE, coding for a thioesterase-like protein. The domain structure of the seven identified modules, which resembles that of the surfactin synthetases SrfA-A to -C, showed two epimerization domains attached to the third and sixth modules. The substrate specificity of the first, fifth, and seventh recombinant adenylation domains of LicA to -C (cloned and expressed in Escherichia coli) was determined to be Gln, Asp, and Ile (with minor Val and Leu substitutions), respectively. Therefore, we suppose that the identified biosynthesis operon is responsible for the production of a lichenysin variant with the primary amino acid sequence l-Gln–l-Leu–d-Leu–l-Val–l-Asp–d-Leu–l-Ile, with minor Leu and Val substitutions at the seventh position.Many strains of Bacillus are known to produce lipopeptides with remarkable surface-active properties (11). The most prominent of these powerful lipopeptides is surfactin from Bacillus subtilis (1). Surfactin is an acylated cyclic heptapeptide that reduces the surface tension of water from 72 to 27 mN m⁻¹ even in a concentration below 0.05% and shows some antibacterial and antifungal activities (1). Some B. subtilis strains are also known to produce other, structurally related lipoheptapeptides (Table ​(Table1),1), like iturin (32, 34) and bacillomycin (3, 27, 30), or the lipodecapeptides fengycin (50) and plipastatin (29).

TABLE 1

Lipoheptapeptide antibiotics of Bacillus spp.

Peptidoglycan Fine Structure of the Radiotolerant Bacterium Deinococcus radiodurans Sark

Peptidoglycan from Deinococcus radiodurans was analyzed by high-performance liquid chromatography and mass spectrometry. The monomeric subunit was: N-acetylglucosamine–N-acetylmuramic acid–l-Ala–d-Glu-(γ)–l-Orn-[(δ)Gly-Gly]–d-Ala–d-Ala. Cross-linkage was mediated by (Gly)₂ bridges, and glycan strands were terminated in (1→6)anhydro-muramic acid residues. Structural relations with the phylogenetically close Thermus thermophilus are discussed.The gram-positive bacterium Deinococcus radiodurans is remarkable because of its extreme resistance to ionizing radiation (14). Phylogenetically the closest relatives of Deinococcus are the extreme thermophiles of the genus Thermus (4, 11). In 16S rRNA phylogenetic trees, the genera Thermus and Deinococcus group together as one of the older branches in bacterial evolution (11). Both microorganisms have complex cell envelopes with outer membranes, S-layers, and ornithine-Gly-containing mureins (7, 12, 19, 20, 22, 23). However, Deinococcus and Thermus differ in their response to the Gram reaction, having positive and negative reactions, respectively (4, 14). The murein structure for Thermus thermophilus HB8 has been recently elucidated (19). Here we report the murein structure of Deinococcus radiodurans with similar detail.D. radiodurans Sark (23) was used in the present study. Cultures were grown in Luria-Bertani medium (13) at 30°C with aeration. Murein was purified and subjected to amino acid and high-performance liquid chromatography (HPLC) analyses as previously described (6, 9, 10, 19). For further analysis muropeptides were purified, lyophilized, and desalted as reported elsewhere (6, 19). Purified muropeptides were subjected to plasma desorption linear time-of-flight mass spectrometry (PDMS) as described previously (1, 5, 16, 19). Positive and negative ion mass spectra were obtained on a short linear ²⁵²californium time-of-flight instrument (BioIon AB, Uppsala, Sweden). The acceleration voltage was between 17 and 19 kV, and spectra were accumulated for 1 to 10 million fission events. Calibration of the mass spectra was done in the positive ion mode with H⁺ and Na⁺ ions and in the negative ion mode with H⁻ and CN⁻ ions. Calculated m/z values are based on average masses.Amino acid analysis of muramidase (Cellosyl; Hoechst, Frankfurt am Main, Germany)-digested sacculi (50 μg) revealed Glu, Orn, Ala, and Gly as the only amino acids in the muramidase-solubilized material. Less than 3% of the total Orn remained in the muramidase-insoluble fraction, indicating an essentially complete solubilization of murein.Muramidase-digested murein samples (200 μg) were analyzed by HPLC as described in reference 19. The muropeptide pattern (Fig. ​(Fig.1)1) was relatively simple, with five dominating components (DR5 and DR10 to DR13 [Fig. 1]). The muropeptides resolved by HPLC were collected, desalted, and subjected to PDMS. The results are presented in Table ​Table11 compared with the m/z values calculated for best-matching muropeptides made up of N-acetylglucosamine (GlucNAc), N-acetylmuramic acid (MurNAc), and the amino acids detected in the murein. The more likely structures are shown in Fig. ​Fig.1.1. According to the m/z values, muropeptides DR1 to DR7 and DR9 were monomers; DR8, DR10, and DR11 were dimers; and DR12 and DR13 were trimers. The best-fitting structures for DR3 to DR8, DR11, and DR13 coincided with muropeptides previously characterized in T. thermophilus HB8 (19) and had identical retention times in comparative HPLC runs. The minor muropeptide DR7 (Fig. ​(Fig.1)1) was the only one detected with a d-Ala–d-Ala dipeptide and most likely represents the basic monomeric subunit. The composition of the major cross-linked species DR11 and DR13 confirmed that cross-linking is mediated by (Gly)₂ bridges, as proposed previously (20). Open in a separate windowFIG. 1HPLC muropeptide elution patterns of murein purified from D. radiodurans. Muramidase-digested murein samples were subjected to HPLC analysis, and the A₂₀₄ of the eluate was recorded. The most likely structures for each muroeptide as deduced by PDMS are shown. The position of residues in brackets is the most likely one as deduced from the structures of other muropeptides but could not be formally demonstrated. R = GlucNac–MurNac–l-Ala–d-Glu-(γ)→.

TABLE 1

Calculated and measured m/z values for the molecular ions of the major muropeptides from D. radiodurans

Disease Mutations in the Human Mitochondrial DNA Polymerase Thumb Subdomain Impart Severe Defects in Mitochondrial DNA Replication

Forty-five different point mutations in POLG, the gene encoding the catalytic subunit of the human mitochondrial DNA polymerase (pol γ), cause the early onset mitochondrial DNA depletion disorder, Alpers syndrome. Sequence analysis of the C-terminal polymerase region of pol γ revealed a cluster of four Alpers mutations at highly conserved residues in the thumb subdomain (G848S, c.2542g→a; T851A, c.2551a→g; R852C, c.2554c→t; R853Q, c.2558g→a) and two Alpers mutations at less conserved positions in the adjacent palm subdomain (Q879H, c.2637g→t and T885S, c.2653a→t). Biochemical characterization of purified, recombinant forms of pol γ revealed that Alpers mutations in the thumb subdomain reduced polymerase activity more than 99% relative to the wild-type enzyme, whereas the palm subdomain mutations retained 50–70% wild-type polymerase activity. All six mutant enzymes retained physical and functional interaction with the pol γ accessory subunit (p55), and none of the six mutants exhibited defects in misinsertion fidelity in vitro. However, differential DNA binding by these mutants suggests a possible orientation of the DNA with respect to the polymerase during catalysis. To our knowledge this study represents the first structure-function analysis of the thumb subdomain in pol γ and examines the consequences of mitochondrial disease mutations in this region.As the only DNA polymerase found in animal cell mitochondria, DNA polymerase γ (pol γ)³ bears sole responsibility for DNA synthesis in all replication and repair transactions involving mitochondrial DNA (1, 2). Mammalian cell pol γ is a heterotrimeric complex composed of one catalytic subunit of 140 kDa (p140) and two 55-kDa accessory subunits (p55) that form a dimer (3). The catalytic subunit contains an N-terminal exonuclease domain connected by a linker region to a C-terminal polymerase domain. Whereas the exonuclease domain contains essential motifs I, II, and III for its activity, the polymerase domain comprising the thumb, palm, and finger subdomains contains motifs A, B, and C that are crucial for polymerase activity. The catalytic subunit is a family A DNA polymerase that includes bacterial pol I and T7 DNA polymerase and possesses DNA polymerase, 3′ → 5′ exonuclease, and 5′-deoxyribose phosphate lyase activities (for review, see Refs. 1 and 2). The 55-kDa accessory subunit (p55) confers processive DNA synthesis and tight binding of the pol γ complex to DNA (4, 5).Depletion of mtDNA as well as the accumulation of deletions and point mutations in mtDNA have been observed in several mitochondrial disorders (for review, see Ref. 6). mtDNA depletion syndromes are caused by defects in nuclear genes responsible for replication and maintenance of the mitochondrial genome (7). Mutation of POLG, the gene encoding the catalytic subunit of pol γ, is frequently involved in disorders linked to mutagenesis of mtDNA (8, 9). Presently, more than 150 point mutations in POLG are linked with a wide variety of mitochondrial diseases, including the autosomal dominant (ad) and recessive forms of progressive external ophthalmoplegia (PEO), Alpers syndrome, parkinsonism, ataxia-neuropathy syndromes, and male infertility (tools.niehs.nih.gov/polg) (9).Alpers syndrome, a hepatocerebral mtDNA depletion disorder, and myocerebrohepatopathy are rare heritable autosomal recessive diseases primarily affecting young children (10–12). These diseases generally manifest during the first few weeks to years of life, and symptoms gradually develop in a stepwise manner eventually leading to death. Alpers syndrome is characterized by refractory seizures, psychomotor regression, and hepatic failure (11, 12). Mutation of POLG was first linked to Alpers syndrome in 2004 (13), and to date 45 different point mutations in POLG (18 localized to the polymerase domain) are associated with Alpers syndrome (9, 14, 15). However, only two Alpers mutations (A467T and W748S, both in the linker region) have been biochemically characterized (16, 17).During the initial cloning and sequencing of the human, Drosophila, and chicken pol γ genes, we noted a highly conserved region N-terminal to motif A in the polymerase domain that was specific to pol γ (18). This region corresponds to part of the thumb subdomain that tracks DNA into the active site of both Escherichia coli pol I and T7 DNA polymerase (19–21). A high concentration of disease mutations, many associated with Alpers syndrome, is found in the thumb subdomain.Here we investigated six mitochondrial disease mutations clustered in the N-terminal portion of the polymerase domain of the enzyme (Fig. 1A). Four mutations (G848S, c.2542g→a; T851A, c.2551a→g; R852C, c.2554c→t; R853Q, c.2558g→a) reside in the thumb subdomain and two (Q879H, c.2637g→t and T885S, c.2653a→t) are located in the palm subdomain. These mutations are associated with Alpers, PEO, mitochondrial myopathy, encephalopathy, lactic acidosis, and stroke-like episodes (MELAS), ataxia-neuropathy syndrome, Leigh syndrome, and myocerebrohepatopathy (

Immunological Mechanisms Mediating Hantavirus Persistence in Rodent Reservoirs

Hantaviruses, similar to several emerging zoonotic viruses, persistently infect their natural reservoir hosts, without causing overt signs of disease. Spillover to incidental human hosts results in morbidity and mortality mediated by excessive proinflammatory and cellular immune responses. The mechanisms mediating the persistence of hantaviruses and the absence of clinical symptoms in rodent reservoirs are only starting to be uncovered. Recent studies indicate that during hantavirus infection, proinflammatory and antiviral responses are reduced and regulatory responses are elevated at sites of increased virus replication in rodents. The recent discovery of structural and non-structural proteins that suppress type I interferon responses in humans suggests that immune responses in rodent hosts could be mediated directly by the virus. Alternatively, several host factors, including sex steroids, glucocorticoids, and genetic factors, are reported to alter host susceptibility and may contribute to persistence of hantaviruses in rodents. Humans and reservoir hosts differ in infection outcomes and in immune responses to hantavirus infection; thus, understanding the mechanisms mediating viral persistence and the absence of disease in rodents may provide insight into the prevention and treatment of disease in humans. Consideration of the coevolutionary mechanisms mediating hantaviral persistence and rodent host survival is providing insight into the mechanisms by which zoonotic viruses have remained in the environment for millions of years and continue to be transmitted to humans.Hantaviruses are negative sense, enveloped RNA viruses (family: Bunyaviridae) that are comprised of three RNA segments, designated small (S), medium (M), and large (L), which encode the viral nucleocapsid (N), envelope glycoproteins (G_N and G_C), and an RNA polymerase (Pol), respectively. More than 50 hantaviruses have been found worldwide [1]. Each hantavirus appears to have coevolved with a specific rodent or insectivore host as similar phylogenetic trees are produced from virus and host mitochondrial gene sequences [2]. Spillover to humans causes hemorrhagic fever with renal syndrome (HFRS) or hantavirus cardiopulmonary syndrome (HCPS), depending on the virus [3]–[5]. Although symptoms vary, a common feature of both HFRS and HCPS is increased permeability of the vasculature and mononuclear infiltration [4]. Pathogenesis of HRFS and HCPS in humans is hypothesized to be mediated by excessive proinflammatory and CD8+ T cell responses (​).

Table 1

Summary of Immune Responses in Humans during Hantavirus Infection.

Protein Identification Using Top-Down Spectra

In the last two years, because of advances in protein separation and mass spectrometry, top-down mass spectrometry moved from analyzing single proteins to analyzing complex samples and identifying hundreds and even thousands of proteins. However, computational tools for database search of top-down spectra against protein databases are still in their infancy. We describe MS-Align+, a fast algorithm for top-down protein identification based on spectral alignment that enables searches for unexpected post-translational modifications. We also propose a method for evaluating statistical significance of top-down protein identifications and further benchmark various software tools on two top-down data sets from Saccharomyces cerevisiae and Salmonella typhimurium. We demonstrate that MS-Align+ significantly increases the number of identified spectra as compared with MASCOT and OMSSA on both data sets. Although MS-Align+ and ProSightPC have similar performance on the Salmonella typhimurium data set, MS-Align+ outperforms ProSightPC on the (more complex) Saccharomyces cerevisiae data set.In the past two decades, proteomics was dominated by bottom-up mass spectrometry that analyzes digested peptides rather than intact proteins. Bottom-up approaches, although powerful, do have limitations in analyzing protein species, e.g. various proteolytic forms of the same protein or various protein isoforms resulting from alternative splicing. Top-down mass spectrometry focuses on analyzing intact proteins and large peptides (1–10) and has advantages in localizing multiple post-translational modifications (PTMs)¹ in a coordinated fashion (e.g. combinatorial PTM code) and identifying multiple protein species (e.g. proteolytically processed protein species) (11). Until recently, most top-down studies were limited to single purified proteins (12–15). Top-down studies of protein mixtures were restricted by difficulties in separating and fragmenting intact proteins and a shortage of robust computational tools.In the last two years, because of advances in protein separation and top-down instrumentation, top-down mass spectrometry moved from analyzing single proteins to analyzing complex samples containing hundreds and even thousands of proteins (16–21). Because algorithms for interpreting top-down spectra are still in their infancy, many recent developments include computational innovations in protein identification.Because top-down spectra are complex, the first step in top-down spectral interpretation is usually spectral deconvolution, which converts a complex top-down spectrum to a list of monoisotopic masses (a deconvolved spectrum). Every protein (possibly with modifications) can be scored against a top-down deconvoluted spectrum, resulting in a Protein-Spectrum-Match (PrSM). The top-down protein identification problem is finding a protein in a database with the highest scoring PrSM for a top-down spectrum and further output the PrSM if it is statistically significant. There are several software tools for top-down protein identification (SoftwareIdentification of unexpected modificationsProteogenomics search against 6-frame translationSpeedEstimation of statistical significanceProSightPC+/−^a+Fast/Slow^b+PIITA+/−−Fast−UStag++Fast−MS-TopDown+−Slow−MS-Align+++Fast+Open in a separate window^a ProSightPC has various search modes that contribute to bridging the gap between blind and restrictive modes of MS/MS database search. It can identify truncated proteins by using biomarker search and identify unexpected modifications by using Δm mode and setting the error tolerance of precursor mass to a large value (e.g., 1999 Da). However, it is not designed for identifying truncated proteins with unexpected PTMs which are not represented in the “shotgun annotated” database.^b In its most advances mode, ProSightPC can search the annotated top-down database that contains various protein species. However, ProSightPC searches in this mode become an order of magnitude slower.

• ProSightPC—ProSightPC is the most commonly used tool for top-down protein identification (22, 23). ProSightPC searches spectra against a “shotgun annotated” protein database, which is generated by considering all expected PTMs. The “shotgun annotated” protein database is much larger than the original protein database. ProSightPC can identify some (but not all) proteins with unexpected PTMs using advanced search options, such as biomarker search and Δm mode, but it is not designed for identifying truncated proteins with unexpected PTMs that are not represented in the “shotgun annotated” database. ProSightPC is a fast tool that reports the statistical significance of PrSMs.
• PIITA—Unlike ProSightPC, PIITA (19) is a precursor independent method that uses only fragment ions for protein identification. It is capable of identifying protein species with unexpected PTMs on N- or C-termini, but it cannot directly identify protein species with PTMs on both N- and C-termini. PIITA is a fast tool that provides FIT scores and Δ scores rather than statistical significance estimates.
• USTag—Unique Sequence Tag (USTag) (17) generates long (6 amino acids or longer) peptide sequence tags to identify PrSMs. This approach, although fast, relies on long peptide sequence tags that may be difficult to obtain for some spectra. It also does not provide an estimate of the statistical significance of PrSMs.
• MS-TopDown—MS-TopDown (24) is based on spectral alignment (25). MS-TopDown allows one to match top-down spectra to proteins with unexpected PTMs, i.e. without knowing which PTMs are present in the sample. However, MS-TopDown is rather slow when searching against large proteomes and does not provide the statistical significance of PrSMs, making it difficult to select good PrSMs.
• In addition, MASCOT, SEQUEST, and OMSSA (16, 26, 27) have been used for top-down protein identification.

We describe MS-Align+, a fast software tool for top-down protein identification. MS-Align+ shares the spectral alignment approach with MS-TopDown, but greatly improves on speed, statistical analysis (providing E-values of PrSMs), and the number of identified PrSMs (e.g. by finding spectral alignments between spectra and truncated proteins). We benchmarked various tools for top-down protein identification on two data sets from Saccharomyces cerevisiae (SC) and Salmonella typhimurium (ST). We demonstrate that MS-Align+ significantly increase the number of identified spectra as compared with MASCOT and OMSSA on both data sets. Although MS-Align+ and ProSightPC have similar performance on the ST data set, MS-Align+ outperforms ProSightPC on the more complex SC data set.     

Loss of Par-1a/MARK3/C-TAK1 Kinase Leads to Reduced Adiposity,Resistance to Hepatic Steatosis,and Defective Gluconeogenesis

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).

TABLE 1.

Multifunctionality of Par-1 polarity kinase pathways^a

Zinc-Independent Folate Biosynthesis: Genetic,Biochemical, and Structural Investigations Reveal New Metal Dependence for GTP Cyclohydrolase IB

GTP cyclohydrolase I (GCYH-I) is an essential Zn²⁺-dependent enzyme that catalyzes the first step of the de novo folate biosynthetic pathway in bacteria and plants, the 7-deazapurine biosynthetic pathway in Bacteria and Archaea, and the biopterin pathway in mammals. We recently reported the discovery of a new prokaryotic-specific GCYH-I (GCYH-IB) that displays no sequence identity to the canonical enzyme and is present in ∼25% of bacteria, the majority of which lack the canonical GCYH-I (renamed GCYH-IA). Genomic and genetic analyses indicate that in those organisms possessing both enzymes, e.g., Bacillus subtilis, GCYH-IA and -IB are functionally redundant, but differentially expressed. Whereas GCYH-IA is constitutively expressed, GCYH-IB is expressed only under Zn²⁺-limiting conditions. These observations are consistent with the hypothesis that GCYH-IB functions to allow folate biosynthesis during Zn²⁺ starvation. Here, we present biochemical and structural data showing that bacterial GCYH-IB, like GCYH-IA, belongs to the tunneling-fold (T-fold) superfamily. However, the GCYH-IA and -IB enzymes exhibit significant differences in global structure and active-site architecture. While GCYH-IA is a unimodular, homodecameric, Zn²⁺-dependent enzyme, GCYH-IB is a bimodular, homotetrameric enzyme activated by a variety of divalent cations. The structure of GCYH-IB and the broad metal dependence exhibited by this enzyme further underscore the mechanistic plasticity that is emerging for the T-fold superfamily. Notably, while humans possess the canonical GCYH-IA enzyme, many clinically important human pathogens possess only the GCYH-IB enzyme, suggesting that this enzyme is a potential new molecular target for antibacterial development.The Zn²⁺-dependent enzyme GTP cyclohydrolase I (GCYH-I; EC 3.5.4.16) is the first enzyme of the de novo tetrahydrofolate (THF) biosynthesis pathway (Fig. ​(Fig.1)1) (38). THF is an essential cofactor in one-carbon transfer reactions in the synthesis of purines, thymidylate, pantothenate, glycine, serine, and methionine in all kingdoms of life (38), and formylmethionyl-tRNA in bacteria (7). Recently, it has also been shown that GCYH-I is required for the biosynthesis of the 7-deazaguanosine-modified tRNA nucleosides queuosine and archaeosine produced in Bacteria and Archaea (44), respectively, as well as the 7-deazaadenosine metabolites produced in some Streptomyces species (33). GCYH-I is encoded in Escherichia coli by the folE gene (28) and catalyzes the conversion of GTP to 7,8-dihydroneopterin triphosphate (55), a complex reaction that begins with hydrolytic opening of the purine ring at C-8 of GTP to generate an N-formyl intermediate, followed by deformylation and subsequent rearrangement and cyclization of the ribosyl moiety to generate the pterin ring in THF (Fig. ​(Fig.1).1). Notably, the enzyme is dependent on an essential active-site Zn²⁺ that serves to activate a water molecule for nucleophilic attack at C-8 in the first step of the reaction (2).Open in a separate windowFIG. 1.Reaction catalyzed by GCYH-I, and metabolic fate of 7,8-dihydroneopterin triphosphate.A homologous GCYH-I is found in mammals and other higher eukaryotes, where it catalyzes the first step of the biopterin (BH₄) pathway (Fig. ​(Fig.1),1), an essential cofactor in the biosynthesis of tyrosine and neurotransmitters, such as serotonin and l-3,4-dihydroxyphenylalanine (3, 52). Recently, a distinct class of GCYH-I enzymes, GCYH-IB (encoded by the folE2 gene), was discovered in microbes (26% of sequenced Bacteria and most Archaea) (12), including several clinically important human pathogens, e.g., Neisseria and Staphylococcus species. Notably, GCYH-IB is absent in eukaryotes.The distribution of folE (gene product renamed GCYH-IA) and folE2 (GCYH-IB) in bacteria is diverse (12). The majority of organisms possess either a folE (65%; e.g., Escherichia coli) or a folE2 (14%; e.g., Neisseria gonorrhoeae) gene. A significant number (12%; e.g., B. subtilis) possess both genes (a subset of 50 bacterial species is shown in Table ​Table1),1), and 9% lack both genes, although members of the latter group are mainly intracellular or symbiotic bacteria that rely on external sources of folate. The majority of Archaea possess only a folE2 gene, and the encoded GCYH-IB appears to be necessary only for the biosynthesis of the modified tRNA nucleoside archaeosine (44) except in the few halophilic Archaea that are known to synthesize folates, such as Haloferax volcanii, where GCYH-IB is involved in both archaeosine and folate formation (13, 44).

TABLE 1.

Distribution and candidate Zur-dependent regulation of alternative GCYH-I genes in bacteria^a

Bar-Coded Pyrosequencing of 16S rRNA Gene Amplicons Reveals Changes in Ileal Porcine Bacterial Communities Due to High Dietary Zinc Intake

Feeding high levels of zinc oxide to piglets significantly increased the relative abundance of ileal Weissella spp., Leuconostoc spp., and Streptococcus spp., reduced the occurrence of Sarcina spp. and Neisseria spp., and led to numerical increases of all Gram-negative facultative anaerobic genera. High dietary zinc oxide intake has a major impact on the porcine ileal bacterial composition.Zinc oxide (ZnO) is used as a feed additive for diarrhea prophylaxis in piglets (23). However, the mode of action of ZnO is not fully understood. Besides its effects on the host (10, 30, 31), high dietary zinc levels may affect the diversity of intestinal microbial communities (2, 11, 20). The prevention of postweaning diarrhea in piglets due to high dietary ZnO intake may not be directly related to a reduction of pathogenic E. coli (8) but, rather, to the diversity of the coliform community (15). Studies on the impact of high ZnO levels on the porcine ileal bacterial community are scarce but nevertheless important, as bacterial diarrhea is initiated in the small intestine (9, 17). The small intestine is a very complex habitat with many different factors shaping the bacterial community. Studies on the ecophysiology (22) and maturation of the porcine ileal microbiota (13, 27) indicate a drastic impact directly after weaning and a gradual decline of modifications during the following 2 weeks. Thus, the time point for analysis chosen in this study (14 days postweaning) does reflect a more stable period of the ileal porcine microbiota. In this study, we used bar-coded pyrosequencing of 16S rRNA genes to gain further insight into the mode of action of pharmacological levels of ZnO in the gastrointestinal tract of young pigs.Total DNA was extracted from the ileal digesta of 40- to 42-day-old piglets using a commercial kit (Qiagen stool kit; Qiagen, Hilden, Germany) and PCR amplified with unique bar-coded primer sets targeting the V1-to-V3 and the V6-to-V8 hypervariable regions (see the supplemental material for detailed methods). The rationale behind this approach was derived from the fact that no single “universal” primer pair can completely cover a complex bacterial habitat (4, 24, 32, 33). Furthermore, these studies also show that in silico information on the coverage of selected primer sets diverges from empirical results, and hence, two hypervariable regions were chosen in this study to maximize the detection of phylogenetically diverse bacterial groups.Equimolar dilutions of all samples were combined into one master sample. Pyrosequencing was performed by Agowa (Berlin, Germany) on a Roche genome sequencer FLX system using a Titanium series PicoTiterPlate. The resulting data files were uploaded to the MG-RAST server (http://metagenomics.nmpdr.org/) (19) and processed with its SEED software tool using the RDP database (5) as the reference database. After automated sequence analysis, all sequences with less than five identical reads per sample were deleted in order to increase the confidence of sequence reads and reduce bias from possible sequencing errors (12, 16). Thus, 0.43% of all sequences were not considered (1,882 of 433,302 sequences). These sequences were assigned to a total of 238 genera, of which most only occurred in a few samples (see the supplemental material). Furthermore, all unclassified sequences were removed (8.7%; 41,467 of 474,769 sequences). Due to the use of the RDP reference database, the SEED software incorrectly assigned the majority of unclassified sequences as unclassified Deferribacterales (83%; 34,393 sequences), which were actually identified as 16S soybean or wheat chloroplasts by BLAST or as cyanobacterial chloroplasts by the RDP II seqmatch tool.The pyrosequencing results for the two primer combinations were merged by taking only sequences from the primer combination that yielded the higher number of reads for a specific sequence assignment in a sample. The remaining reads were used to calculate the relative contribution of assigned sequences to total sequence reads in a sample.The Firmicutes phylum dominated the small intestinal bacterial communities in both the control group and the group with high dietary ZnO intake, with 98.3% and 97.0% of total sequence reads, respectively. No significant influence of high dietary ZnO intake was found for the main phyla Proteobacteria (0.92% versus 1.84%), Actinobacteria (0.61% versus 0.75%), Bacteroidetes (0.15% versus 0.17%), and Fusobacteria (0.09% versus 0.12%).On the order level, a total of 20 bacterial orders were detected (data not shown). Lactobacillales dominated bacterial communities in the control and high-dietary-ZnO-intake groups, with 83.37% and 93.24% of total reads. Lactic acid bacteria are well known to dominate the bacterial community in the ileum of piglets (11, 22). No significant difference between the control group and the group with high dietary ZnO intake was observed on the order level, although high dietary ZnO intake led to a strong numerical decrease for Clostridiales (14.4 ± 24.0% [mean ± standard deviation] versus 2.8 ± 1.7%), as well as to numerical increases for Pseudomonadales (0.3 ± 0.3% versus 0.6 ± 0.6%) and Enterobacteriales (0.2 ± 0.2% versus 0.5 ± 0.6%).On the genus level, a total of 103 genera were detected. Table ​Table11 summarizes the main 31 genera which exceeded 0.05% of total reads (see the supplemental material for a complete list). Lactobacilli clearly dominated the bacterial communities in both trial groups, but they also were numerically lower due to high dietary ZnO intake.

TABLE 1.

Bacterial genera in the ileum of piglets fed diets supplemented with 200 or 3,000 ppm ZnO